From d26b210b75c630fefb3e3b2ea24a50d938d967de Mon Sep 17 00:00:00 2001 From: Jeffrey Whitaker Date: Wed, 31 Jan 2018 11:16:49 -0500 Subject: [PATCH 0001/1504] remove netcdftime --- setup.py | 11 ++--------- 1 file changed, 2 insertions(+), 9 deletions(-) diff --git a/setup.py b/setup.py index 339432c2a..153f4f884 100644 --- a/setup.py +++ b/setup.py @@ -468,8 +468,6 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): cmdclass = {} netcdf4_src_root = osp.join('netCDF4', '_netCDF4') netcdf4_src_c = netcdf4_src_root + '.c' -netcdftime_src_root = osp.join('netcdftime', '_netcdftime') -netcdftime_src_c = netcdftime_src_root + '.c' if 'sdist' not in sys.argv[1:] and 'clean' not in sys.argv[1:]: sys.stdout.write('using Cython to compile netCDF4.pyx...\n') # remove _netCDF4.c file if it exists, so cython will recompile _netCDF4.pyx. @@ -478,9 +476,6 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): if len(sys.argv) >= 2: if os.path.exists(netcdf4_src_c): os.remove(netcdf4_src_c) - # same for _netcdftime.c - if os.path.exists(netcdftime_src_c): - os.remove(netcdftime_src_c) # this determines whether renameGroup and filepath methods will work. has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \ has_cdf5_format, has_nc_open_mem, has_nc_par = check_api(inc_dirs) @@ -552,9 +547,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): libraries=libs, library_dirs=lib_dirs, include_dirs=inc_dirs + ['include'], - runtime_library_dirs=runtime_lib_dirs), - Extension('netcdftime._netcdftime', - [netcdftime_src_root + '.pyx'])] + runtime_library_dirs=runtime_lib_dirs)] else: ext_modules = None @@ -584,6 +577,6 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): "Topic :: Software Development :: Libraries :: Python Modules", "Topic :: System :: Archiving :: Compression", "Operating System :: OS Independent"], - packages=['netcdftime', 'netCDF4'], + packages=['netCDF4'], ext_modules=ext_modules, **setuptools_extra_kwargs) From b89833095edc1f53a6da083690842cb7952bbf0c Mon Sep 17 00:00:00 2001 From: Jeffrey Whitaker Date: Wed, 31 Jan 2018 11:17:11 -0500 Subject: [PATCH 0002/1504] remove netcdftime --- netcdftime/__init__.py | 8 - netcdftime/_netcdftime.pyx | 1705 ------------------------------------ 2 files changed, 1713 deletions(-) delete mode 100644 netcdftime/__init__.py delete mode 100644 netcdftime/_netcdftime.pyx diff --git a/netcdftime/__init__.py b/netcdftime/__init__.py deleted file mode 100644 index 8693bb6a2..000000000 --- a/netcdftime/__init__.py +++ /dev/null @@ -1,8 +0,0 @@ -from ._netcdftime import utime, JulianDayFromDate, DateFromJulianDay -from ._netcdftime import _parse_date, date2index, time2index -from ._netcdftime import DatetimeProlepticGregorian as datetime -from ._netcdftime import DatetimeNoLeap, DatetimeAllLeap, Datetime360Day, DatetimeJulian, \ - DatetimeGregorian, DatetimeProlepticGregorian -from ._netcdftime import microsec_units, millisec_units, \ - sec_units, hr_units, day_units, min_units -from ._netcdftime import __version__ diff --git a/netcdftime/_netcdftime.pyx b/netcdftime/_netcdftime.pyx deleted file mode 100644 index 5302684a8..000000000 --- a/netcdftime/_netcdftime.pyx +++ /dev/null @@ -1,1705 +0,0 @@ -""" -Performs conversions of netCDF time coordinate data to/from datetime objects. -""" - -from cpython.object cimport PyObject_RichCompare - -import numpy as np -import math -import numpy -import re - -from datetime import datetime as real_datetime -from datetime import timedelta -import time # strftime - -try: - from itertools import izip as zip -except ImportError: # python 3.x - pass - -microsec_units = ['microseconds','microsecond', 'microsec', 'microsecs'] -millisec_units = ['milliseconds', 'millisecond', 'millisec', 'millisecs'] -sec_units = ['second', 'seconds', 'sec', 'secs', 's'] -min_units = ['minute', 'minutes', 'min', 'mins'] -hr_units = ['hour', 'hours', 'hr', 'hrs', 'h'] -day_units = ['day', 'days', 'd'] -_units = microsec_units+millisec_units+sec_units+min_units+hr_units+day_units -_calendars = ['standard', 'gregorian', 'proleptic_gregorian', - 'noleap', 'julian', 'all_leap', '365_day', '366_day', '360_day'] - -__version__ = '1.4.1' - -# Adapted from http://delete.me.uk/2005/03/iso8601.html -# Note: This regex ensures that all ISO8601 timezone formats are accepted - -# but, due to legacy support for other timestrings, not all incorrect formats can be rejected. -# For example, the TZ spec "+01:0" will still work even though the minutes value is only one character long. -ISO8601_REGEX = re.compile(r"(?P[+-]?[0-9]{1,4})(-(?P[0-9]{1,2})(-(?P[0-9]{1,2})" - r"(((?P.)(?P[0-9]{1,2}):(?P[0-9]{1,2})(:(?P[0-9]{1,2})(\.(?P[0-9]+))?)?)?" - r"((?P.?)(?PZ|(([-+])([0-9]{2})((:([0-9]{2}))|([0-9]{2}))?)))?)?)?)?" - ) -# Note: The re module apparently does not support branch reset groups that allow -# redifinition of the same group name in alternative branches as PCRE does. -# Using two different group names is also somewhat ugly, but other solutions might -# hugely inflate the expression. feel free to contribute a better solution. -TIMEZONE_REGEX = re.compile( - "(?P[+-])(?P[0-9]{2})(?:(?::(?P[0-9]{2}))|(?P[0-9]{2}))?") - -def JulianDayFromDate(date, calendar='standard'): - """ - - creates a Julian Day from a 'datetime-like' object. Returns the fractional - Julian Day (approximately millisecond accuracy). - - if calendar='standard' or 'gregorian' (default), Julian day follows Julian - Calendar on and before 1582-10-5, Gregorian calendar after 1582-10-15. - - if calendar='proleptic_gregorian', Julian Day follows gregorian calendar. - - if calendar='julian', Julian Day follows julian calendar. - - Algorithm: - - Meeus, Jean (1998) Astronomical Algorithms (2nd Edition). Willmann-Bell, - Virginia. p. 63 - - """ - - # based on redate.py by David Finlayson. - - # check if input was scalar and change return accordingly - isscalar = False - try: - date[0] - except: - isscalar = True - - date = np.atleast_1d(np.array(date)) - year = np.empty(len(date), dtype=np.int32) - month = year.copy() - day = year.copy() - hour = year.copy() - minute = year.copy() - second = year.copy() - microsecond = year.copy() - for i, d in enumerate(date): - year[i] = d.year - month[i] = d.month - day[i] = d.day - hour[i] = d.hour - minute[i] = d.minute - second[i] = d.second - microsecond[i] = d.microsecond - # convert years in BC era to astronomical years (so that 1 BC is year zero) - # (fixes issue #596) - year[year < 0] = year[year < 0] + 1 - # Convert time to fractions of a day - day = day + hour / 24.0 + minute / 1440.0 + (second + microsecond/1.e6) / 86400.0 - - # Start Meeus algorithm (variables are in his notation) - month_lt_3 = month < 3 - month[month_lt_3] = month[month_lt_3] + 12 - year[month_lt_3] = year[month_lt_3] - 1 - - # MC - assure array - # A = np.int64(year / 100) - A = (year / 100).astype(np.int64) - - # MC - # jd = int(365.25 * (year + 4716)) + int(30.6001 * (month + 1)) + \ - # day - 1524.5 - jd = 365. * year + np.int32(0.25 * year + 2000.) + np.int32(30.6001 * (month + 1)) + \ - day + 1718994.5 - - # optionally adjust the jd for the switch from - # the Julian to Gregorian Calendar - # here assumed to have occurred the day after 1582 October 4 - if calendar in ['standard', 'gregorian']: - # MC - do not have to be contiguous dates - # if np.min(jd) >= 2299170.5: - # # 1582 October 15 (Gregorian Calendar) - # B = 2 - A + np.int32(A / 4) - # elif np.max(jd) < 2299160.5: - # # 1582 October 5 (Julian Calendar) - # B = np.zeros(len(jd)) - # else: - # print(date, calendar, jd) - # raise ValueError( - # 'impossible date (falls in gap between end of Julian calendar and beginning of Gregorian calendar') - if np.any((jd >= 2299160.5) & (jd < 2299170.5)): # missing days in Gregorian calendar - raise ValueError( - 'impossible date (falls in gap between end of Julian calendar and beginning of Gregorian calendar') - B = np.zeros(len(jd)) # 1582 October 5 (Julian Calendar) - ii = np.where(jd >= 2299170.5)[0] # 1582 October 15 (Gregorian Calendar) - if ii.size>0: - B[ii] = 2 - A[ii] + np.int32(A[ii] / 4) - elif calendar == 'proleptic_gregorian': - B = 2 - A + np.int32(A / 4) - elif calendar == 'julian': - B = np.zeros(len(jd)) - else: - raise ValueError( - 'unknown calendar, must be one of julian,standard,gregorian,proleptic_gregorian, got %s' % calendar) - - # adjust for Julian calendar if necessary - jd = jd + B - - # Add a small offset (proportional to Julian date) for correct re-conversion. - # This is about 45 microseconds in 2000 for Julian date starting -4712. - # (pull request #433). - eps = np.finfo(float).eps - eps = np.maximum(eps*jd, eps) - jd += eps - - if isscalar: - return jd[0] - else: - return jd - - -cdef _NoLeapDayFromDate(date): - """ - -creates a Julian Day for a calendar with no leap years from a datetime -instance. Returns the fractional Julian Day (approximately millisecond accuracy). - - """ - - year = date.year - month = date.month - day = date.day - hour = date.hour - minute = date.minute - second = date.second - microsecond = date.microsecond - # Convert time to fractions of a day - day = day + hour / 24.0 + minute / 1440.0 + (second + microsecond/1.e6) / 86400.0 - - # Start Meeus algorithm (variables are in his notation) - if (month < 3): - month = month + 12 - year = year - 1 - - jd = int(365. * (year + 4716)) + int(30.6001 * (month + 1)) + \ - day - 1524.5 - - return jd - - -cdef _AllLeapFromDate(date): - """ - -creates a Julian Day for a calendar where all years have 366 days from -a 'datetime-like' object. -Returns the fractional Julian Day (approximately millisecond accuracy). - - """ - - year = date.year - month = date.month - day = date.day - hour = date.hour - minute = date.minute - second = date.second - microsecond = date.microsecond - # Convert time to fractions of a day - day = day + hour / 24.0 + minute / 1440.0 + (second + microsecond/1.e6) / 86400.0 - - # Start Meeus algorithm (variables are in his notation) - if (month < 3): - month = month + 12 - year = year - 1 - - jd = int(366. * (year + 4716)) + int(30.6001 * (month + 1)) + \ - day - 1524.5 - - return jd - - -cdef _360DayFromDate(date): - """ - -creates a Julian Day for a calendar where all months have 30 days from -a 'datetime-like' object. -Returns the fractional Julian Day (approximately millisecond accuracy). - - """ - - year = date.year - month = date.month - day = date.day - hour = date.hour - minute = date.minute - second = date.second - microsecond = date.microsecond - # Convert time to fractions of a day - day = day + hour / 24.0 + minute / 1440.0 + (second + microsecond/1.e6) / 86400.0 - - jd = int(360. * (year + 4716)) + int(30. * (month - 1)) + day - - return jd - - -def DateFromJulianDay(JD, calendar='standard'): - """ - - returns a 'datetime-like' object given Julian Day. Julian Day is a - fractional day with approximately millisecond accuracy. - - if calendar='standard' or 'gregorian' (default), Julian day follows Julian - Calendar on and before 1582-10-5, Gregorian calendar after 1582-10-15. - - if calendar='proleptic_gregorian', Julian Day follows gregorian calendar. - - if calendar='julian', Julian Day follows julian calendar. - - The datetime object is a 'real' datetime object if the date falls in - the Gregorian calendar (i.e. calendar='proleptic_gregorian', or - calendar = 'standard'/'gregorian' and the date is after 1582-10-15). - Otherwise, it's a 'phony' datetime object which is actually an instance - of netcdftime.datetime. - - - Algorithm: - - Meeus, Jean (1998) Astronomical Algorithms (2nd Edition). Willmann-Bell, - Virginia. p. 63 - """ - - # based on redate.py by David Finlayson. - - julian = np.array(JD, dtype=float) - - if np.min(julian) < 0: - raise ValueError('Julian Day must be positive') - - dayofwk = np.atleast_1d(np.int32(np.fmod(np.int32(julian + 1.5), 7))) - # get the day (Z) and the fraction of the day (F) - # add 0.000005 which is 452 ms in case of jd being after - # second 23:59:59 of a day we want to round to the next day see issue #75 - Z = np.atleast_1d(np.int32(np.round(julian))) - F = np.atleast_1d(julian + 0.5 - Z).astype(np.float64) - if calendar in ['standard', 'gregorian']: - # MC - # alpha = int((Z - 1867216.25)/36524.25) - # A = Z + 1 + alpha - int(alpha/4) - alpha = np.int32(((Z - 1867216.) - 0.25) / 36524.25) - A = Z + 1 + alpha - np.int32(0.25 * alpha) - # check if dates before oct 5th 1582 are in the array - ind_before = np.where(julian < 2299160.5)[0] - if len(ind_before) > 0: - A[ind_before] = Z[ind_before] - - elif calendar == 'proleptic_gregorian': - # MC - # alpha = int((Z - 1867216.25)/36524.25) - # A = Z + 1 + alpha - int(alpha/4) - alpha = np.int32(((Z - 1867216.) - 0.25) / 36524.25) - A = Z + 1 + alpha - np.int32(0.25 * alpha) - elif calendar == 'julian': - A = Z - else: - raise ValueError( - 'unknown calendar, must be one of julian,standard,gregorian,proleptic_gregorian, got %s' % calendar) - - B = A + 1524 - # MC - # C = int((B - 122.1)/365.25) - # D = int(365.25 * C) - C = np.atleast_1d(np.int32(6680. + ((B - 2439870.) - 122.1) / 365.25)) - D = np.atleast_1d(np.int32(365 * C + np.int32(0.25 * C))) - E = np.atleast_1d(np.int32((B - D) / 30.6001)) - - # Convert to date - day = np.clip(B - D - np.int64(30.6001 * E) + F, 1, None) - nday = B - D - 123 - dayofyr = nday - 305 - ind_nday_before = np.where(nday <= 305)[0] - if len(ind_nday_before) > 0: - dayofyr[ind_nday_before] = nday[ind_nday_before] + 60 - # MC - # if E < 14: - # month = E - 1 - # else: - # month = E - 13 - - # if month > 2: - # year = C - 4716 - # else: - # year = C - 4715 - month = E - 1 - month[month > 12] = month[month > 12] - 12 - year = C - 4715 - year[month > 2] = year[month > 2] - 1 - year[year <= 0] = year[year <= 0] - 1 - - # a leap year? - leap = np.zeros(len(year),dtype=dayofyr.dtype) - leap[year % 4 == 0] = 1 - if calendar == 'proleptic_gregorian': - leap[(year % 100 == 0) & (year % 400 != 0)] = 0 - elif calendar in ['standard', 'gregorian']: - leap[(year % 100 == 0) & (year % 400 != 0) & (julian < 2299160.5)] = 0 - - inc_idx = np.where((leap == 1) & (month > 2))[0] - dayofyr[inc_idx] = dayofyr[inc_idx] + leap[inc_idx] - - # Subtract the offset from JulianDayFromDate from the microseconds (pull - # request #433). - eps = np.finfo(float).eps - eps = np.maximum(eps*julian, eps) - hour = np.clip((F * 24.).astype(np.int64), 0, 23) - F -= hour / 24. - minute = np.clip((F * 1440.).astype(np.int64), 0, 59) - # this is an overestimation due to added offset in JulianDayFromDate - second = np.clip((F - minute / 1440.) * 86400., 0, None) - microsecond = (second % 1)*1.e6 - # remove the offset from the microsecond calculation. - microsecond = np.clip(microsecond - eps*86400.*1e6, 0, 999999) - - # convert year, month, day, hour, minute, second to int32 - year = year.astype(np.int32) - month = month.astype(np.int32) - day = day.astype(np.int32) - hour = hour.astype(np.int32) - minute = minute.astype(np.int32) - second = second.astype(np.int32) - microsecond = microsecond.astype(np.int32) - - # check if input was scalar and change return accordingly - isscalar = False - try: - JD[0] - except: - isscalar = True - - if calendar in 'proleptic_gregorian': - # FIXME: datetime.datetime does not support years < 1 - if (year < 0).any(): - datetime_type = DatetimeProlepticGregorian - else: - datetime_type = real_datetime - elif calendar in ('standard', 'gregorian'): - # return a 'real' datetime instance if calendar is proleptic - # Gregorian or Gregorian and all dates are after the - # Julian/Gregorian transition - if len(ind_before) == 0: - datetime_type = real_datetime - else: - datetime_type = DatetimeGregorian - elif calendar == "julian": - datetime_type = DatetimeJulian - else: - raise ValueError("unsupported calendar: {0}".format(calendar)) - - if not isscalar: - return np.array([datetime_type(*args) - for args in - zip(year, month, day, hour, minute, second, - microsecond)]) - - else: - return datetime_type(year[0], month[0], day[0], hour[0], - minute[0], second[0], microsecond[0]) - - -cdef _DateFromNoLeapDay(JD): - """ - -returns a 'datetime-like' object given Julian Day for a calendar with no leap -days. Julian Day is a fractional day with approximately millisecond accuracy. - - """ - - # based on redate.py by David Finlayson. - - if JD < 0: - year_offset = int(-JD) // 365 + 1 - JD += year_offset * 365 - else: - year_offset = 0 - - dayofwk = int(math.fmod(int(JD + 1.5), 7)) - (F, Z) = math.modf(JD + 0.5) - Z = int(Z) - A = Z - B = A + 1524 - C = int((B - 122.1) / 365.) - D = int(365. * C) - E = int((B - D) / 30.6001) - - # Convert to date - day = B - D - int(30.6001 * E) + F - nday = B - D - 123 - if nday <= 305: - dayofyr = nday + 60 - else: - dayofyr = nday - 305 - if E < 14: - month = E - 1 - else: - month = E - 13 - - if month > 2: - year = C - 4716 - else: - year = C - 4715 - - # Convert fractions of a day to time - (dfrac, days) = math.modf(day / 1.0) - (hfrac, hours) = math.modf(dfrac * 24.0) - (mfrac, minutes) = math.modf(hfrac * 60.0) - (sfrac, seconds) = math.modf(mfrac * 60.0) - microseconds = sfrac*1.e6 - - if year_offset > 0: - # correct dayofwk - - # 365 mod 7 = 1, so the day of the week changes by one day for - # every year in year_offset - dayofwk -= int(math.fmod(year_offset, 7)) - - if dayofwk < 0: - dayofwk += 7 - - return DatetimeNoLeap(year - year_offset, month, int(days), int(hours), int(minutes), - int(seconds), int(microseconds),dayofwk, dayofyr) - - -cdef _DateFromAllLeap(JD): - """ - -returns a 'datetime-like' object given Julian Day for a calendar where all -years have 366 days. -Julian Day is a fractional day with approximately millisecond accuracy. - - """ - - # based on redate.py by David Finlayson. - - if JD < 0: - raise ValueError('Julian Day must be positive') - - dayofwk = int(math.fmod(int(JD + 1.5), 7)) - (F, Z) = math.modf(JD + 0.5) - Z = int(Z) - A = Z - B = A + 1524 - C = int((B - 122.1) / 366.) - D = int(366. * C) - E = int((B - D) / 30.6001) - - # Convert to date - day = B - D - int(30.6001 * E) + F - nday = B - D - 123 - if nday <= 305: - dayofyr = nday + 60 - else: - dayofyr = nday - 305 - if E < 14: - month = E - 1 - else: - month = E - 13 - if month > 2: - dayofyr = dayofyr + 1 - - if month > 2: - year = C - 4716 - else: - year = C - 4715 - - # Convert fractions of a day to time - (dfrac, days) = math.modf(day / 1.0) - (hfrac, hours) = math.modf(dfrac * 24.0) - (mfrac, minutes) = math.modf(hfrac * 60.0) - (sfrac, seconds) = math.modf(mfrac * 60.0) - microseconds = sfrac*1.e6 - - return DatetimeAllLeap(year, month, int(days), int(hours), int(minutes), - int(seconds), int(microseconds),dayofwk, dayofyr) - - -cdef _DateFrom360Day(JD): - """ - -returns a 'datetime-like' object given Julian Day for a calendar where all -months have 30 days. -Julian Day is a fractional day with approximately millisecond accuracy. - - """ - - if JD < 0: - year_offset = int(-JD) // 360 + 1 - JD += year_offset * 360 - else: - year_offset = 0 - - #jd = int(360. * (year + 4716)) + int(30. * (month - 1)) + day - (F, Z) = math.modf(JD) - year = int((Z - 0.5) / 360.) - 4716 - dayofyr = Z - (year + 4716) * 360 - month = int((dayofyr - 0.5) / 30) + 1 - day = dayofyr - (month - 1) * 30 + F - - # Convert fractions of a day to time - (dfrac, days) = math.modf(day / 1.0) - (hfrac, hours) = math.modf(dfrac * 24.0) - (mfrac, minutes) = math.modf(hfrac * 60.0) - (sfrac, seconds) = math.modf(mfrac * 60.0) - microseconds = sfrac*1.e6 - - return Datetime360Day(year - year_offset, month, int(days), int(hours), int(minutes), - int(seconds), int(microseconds), -1, dayofyr) - - -cdef _dateparse(timestr): - """parse a string of the form time-units since yyyy-mm-dd hh:mm:ss - return a tuple (units,utc_offset, datetimeinstance)""" - timestr_split = timestr.split() - units = timestr_split[0].lower() - if units not in _units: - raise ValueError( - "units must be one of 'seconds', 'minutes', 'hours' or 'days' (or singular version of these), got '%s'" % units) - if timestr_split[1].lower() != 'since': - raise ValueError("no 'since' in unit_string") - # parse the date string. - n = timestr.find('since') + 6 - year, month, day, hour, minute, second, utc_offset = _parse_date( - timestr[n:].strip()) - return units, utc_offset, datetime(year, month, day, hour, minute, second) - - -class utime: - - """ -Performs conversions of netCDF time coordinate -data to/from datetime objects. - -To initialize: C{t = utime(unit_string,calendar='standard')} - -where - -B{C{unit_string}} is a string of the form -C{'time-units since '} defining the time units. - -Valid time-units are days, hours, minutes and seconds (the singular forms -are also accepted). An example unit_string would be C{'hours -since 0001-01-01 00:00:00'}. - -The B{C{calendar}} keyword describes the calendar used in the time calculations. -All the values currently defined in the U{CF metadata convention -} -are accepted. The default is C{'standard'}, which corresponds to the mixed -Gregorian/Julian calendar used by the C{udunits library}. Valid calendars -are: - -C{'gregorian'} or C{'standard'} (default): - -Mixed Gregorian/Julian calendar as defined by udunits. - -C{'proleptic_gregorian'}: - -A Gregorian calendar extended to dates before 1582-10-15. That is, a year -is a leap year if either (i) it is divisible by 4 but not by 100 or (ii) -it is divisible by 400. - -C{'noleap'} or C{'365_day'}: - -Gregorian calendar without leap years, i.e., all years are 365 days long. -all_leap or 366_day Gregorian calendar with every year being a leap year, -i.e., all years are 366 days long. - -C{'360_day'}: - -All years are 360 days divided into 30 day months. - -C{'julian'}: - -Proleptic Julian calendar, extended to dates after 1582-10-5. A year is a -leap year if it is divisible by 4. - -The C{L{num2date}} and C{L{date2num}} class methods can used to convert datetime -instances to/from the specified time units using the specified calendar. - -The datetime instances returned by C{num2date} are 'real' python datetime -objects if the date falls in the Gregorian calendar (i.e. -C{calendar='proleptic_gregorian', 'standard'} or C{'gregorian'} and -the date is after 1582-10-15). Otherwise, they are 'phony' datetime -objects which are actually instances of C{L{netcdftime.datetime}}. This is -because the python datetime module cannot handle the weird dates in some -calendars (such as C{'360_day'} and C{'all_leap'}) which don't exist in any real -world calendar. - - -Example usage: - ->>> from netcdftime import utime ->>> from datetime import datetime ->>> cdftime = utime('hours since 0001-01-01 00:00:00') ->>> date = datetime.now() ->>> print date -2016-10-05 08:46:27.245015 ->>> ->>> t = cdftime.date2num(date) ->>> print t -17669840.7742 ->>> ->>> date = cdftime.num2date(t) ->>> print date -2016-10-05 08:46:27.244996 ->>> - -The resolution of the transformation operation is approximately a millisecond. - -Warning: Dates between 1582-10-5 and 1582-10-15 do not exist in the -C{'standard'} or C{'gregorian'} calendars. An exception will be raised if you pass -a 'datetime-like' object in that range to the C{L{date2num}} class method. - -Words of Wisdom from the British MetOffice concerning reference dates: - -"udunits implements the mixed Gregorian/Julian calendar system, as -followed in England, in which dates prior to 1582-10-15 are assumed to use -the Julian calendar. Other software cannot be relied upon to handle the -change of calendar in the same way, so for robustness it is recommended -that the reference date be later than 1582. If earlier dates must be used, -it should be noted that udunits treats 0 AD as identical to 1 AD." - -@ivar origin: datetime instance defining the origin of the netCDF time variable. -@ivar calendar: the calendar used (as specified by the C{calendar} keyword). -@ivar unit_string: a string defining the the netCDF time variable. -@ivar units: the units part of C{unit_string} (i.e. 'days', 'hours', 'seconds'). - """ - - def __init__(self, unit_string, calendar='standard'): - """ -@param unit_string: a string of the form -C{'time-units since '} defining the time units. - -Valid time-units are days, hours, minutes and seconds (the singular forms -are also accepted). An example unit_string would be C{'hours -since 0001-01-01 00:00:00'}. - -@keyword calendar: describes the calendar used in the time calculations. -All the values currently defined in the U{CF metadata convention -} -are accepted. The default is C{'standard'}, which corresponds to the mixed -Gregorian/Julian calendar used by the C{udunits library}. Valid calendars -are: - - C{'gregorian'} or C{'standard'} (default): - Mixed Gregorian/Julian calendar as defined by udunits. - - C{'proleptic_gregorian'}: - A Gregorian calendar extended to dates before 1582-10-15. That is, a year - is a leap year if either (i) it is divisible by 4 but not by 100 or (ii) - it is divisible by 400. - - C{'noleap'} or C{'365_day'}: - Gregorian calendar without leap years, i.e., all years are 365 days long. - - C{'all_leap'} or C{'366_day'}: - Gregorian calendar with every year being a leap year, i.e., - all years are 366 days long. - -C{'360_day'}: - All years are 360 days divided into 30 day months. - -C{'julian'}: - Proleptic Julian calendar, extended to dates after 1582-10-5. A year is a - leap year if it is divisible by 4. - -@returns: A class instance which may be used for converting times from netCDF -units to datetime objects. - """ - calendar = calendar.lower() - if calendar in _calendars: - self.calendar = calendar - else: - raise ValueError( - "calendar must be one of %s, got '%s'" % (str(_calendars), calendar)) - units, tzoffset, self.origin = _dateparse(unit_string) - # real-world calendars limited to positive reference years. - if self.calendar in ['julian', 'standard', 'gregorian', 'proleptic_gregorian']: - if self.origin.year == 0: - msg='zero not allowed as a reference year, does not exist in Julian or Gregorian calendars' - raise ValueError(msg) - elif self.origin.year < 0: - msg='negative reference year in time units, must be >= 1' - raise ValueError(msg) - self.tzoffset = tzoffset # time zone offset in minutes - self.units = units - self.unit_string = unit_string - if self.calendar in ['noleap', '365_day'] and self.origin.month == 2 and self.origin.day == 29: - raise ValueError( - 'cannot specify a leap day as the reference time with the noleap calendar') - if self.calendar == '360_day' and self.origin.day > 30: - raise ValueError( - 'there are only 30 days in every month with the 360_day calendar') - if self.calendar in ['noleap', '365_day']: - self._jd0 = _NoLeapDayFromDate(self.origin) - elif self.calendar in ['all_leap', '366_day']: - self._jd0 = _AllLeapFromDate(self.origin) - elif self.calendar == '360_day': - self._jd0 = _360DayFromDate(self.origin) - else: - self._jd0 = JulianDayFromDate(self.origin, calendar=self.calendar) - - def date2num(self, date): - """ - Returns C{time_value} in units described by L{unit_string}, using - the specified L{calendar}, given a 'datetime-like' object. - - The datetime object must represent UTC with no time-zone offset. - If there is a time-zone offset implied by L{unit_string}, it will - be applied to the returned numeric values. - - Resolution is approximately a millisecond. - - If C{calendar = 'standard'} or C{'gregorian'} (indicating - that the mixed Julian/Gregorian calendar is to be used), an - exception will be raised if the 'datetime-like' object describes - a date between 1582-10-5 and 1582-10-15. - - Works for scalars, sequences and numpy arrays. - Returns a scalar if input is a scalar, else returns a numpy array. - """ - isscalar = False - try: - date[0] - except: - isscalar = True - if not isscalar: - date = numpy.array(date) - shape = date.shape - if self.calendar in ['julian', 'standard', 'gregorian', 'proleptic_gregorian']: - if isscalar: - jdelta = JulianDayFromDate(date, self.calendar) - self._jd0 - else: - jdelta = JulianDayFromDate( - date.flat, self.calendar) - self._jd0 - elif self.calendar in ['noleap', '365_day']: - if isscalar: - if date.month == 2 and date.day == 29: - raise ValueError( - 'there is no leap day in the noleap calendar') - jdelta = _NoLeapDayFromDate(date) - self._jd0 - else: - jdelta = [] - for d in date.flat: - if d.month == 2 and d.day == 29: - raise ValueError( - 'there is no leap day in the noleap calendar') - jdelta.append(_NoLeapDayFromDate(d) - self._jd0) - elif self.calendar in ['all_leap', '366_day']: - if isscalar: - jdelta = _AllLeapFromDate(date) - self._jd0 - else: - jdelta = [_AllLeapFromDate(d) - self._jd0 for d in date.flat] - elif self.calendar == '360_day': - if isscalar: - if date.day > 30: - raise ValueError( - 'there are only 30 days in every month with the 360_day calendar') - jdelta = _360DayFromDate(date) - self._jd0 - else: - jdelta = [] - for d in date.flat: - if d.day > 30: - raise ValueError( - 'there are only 30 days in every month with the 360_day calendar') - jdelta.append(_360DayFromDate(d) - self._jd0) - if not isscalar: - jdelta = numpy.array(jdelta) - # convert to desired units, add time zone offset. - if self.units in microsec_units: - jdelta = jdelta * 86400. * 1.e6 + self.tzoffset * 60. * 1.e6 - elif self.units in millisec_units: - jdelta = jdelta * 86400. * 1.e3 + self.tzoffset * 60. * 1.e3 - elif self.units in sec_units: - jdelta = jdelta * 86400. + self.tzoffset * 60. - elif self.units in min_units: - jdelta = jdelta * 1440. + self.tzoffset - elif self.units in hr_units: - jdelta = jdelta * 24. + self.tzoffset / 60. - elif self.units in day_units: - jdelta = jdelta + self.tzoffset / 1440. - else: - raise ValueError('unsupported time units') - if isscalar: - return jdelta - else: - return numpy.reshape(jdelta, shape) - - def num2date(self, time_value): - """ - Return a 'datetime-like' object given a C{time_value} in units - described by L{unit_string}, using L{calendar}. - - dates are in UTC with no offset, even if L{unit_string} contains - a time zone offset from UTC. - - Resolution is approximately a millisecond. - - Works for scalars, sequences and numpy arrays. - Returns a scalar if input is a scalar, else returns a numpy array. - - The datetime instances returned by C{num2date} are 'real' python datetime - objects if the date falls in the Gregorian calendar (i.e. - C{calendar='proleptic_gregorian'}, or C{calendar = 'standard'/'gregorian'} and - the date is after 1582-10-15). Otherwise, they are 'phony' datetime - objects which are actually instances of netcdftime.datetime. This is - because the python datetime module cannot handle the weird dates in some - calendars (such as C{'360_day'} and C{'all_leap'}) which - do not exist in any real world calendar. - """ - isscalar = False - try: - time_value[0] - except: - isscalar = True - ismasked = False - if hasattr(time_value, 'mask'): - mask = time_value.mask - ismasked = True - if not isscalar: - time_value = numpy.array(time_value, dtype='d') - shape = time_value.shape - # convert to desired units, subtract time zone offset. - if self.units in microsec_units: - jdelta = time_value / 86400000000. - self.tzoffset / 1440. - elif self.units in millisec_units: - jdelta = time_value / 86400000. - self.tzoffset / 1440. - elif self.units in sec_units: - jdelta = time_value / 86400. - self.tzoffset / 1440. - elif self.units in min_units: - jdelta = time_value / 1440. - self.tzoffset / 1440. - elif self.units in hr_units: - jdelta = time_value / 24. - self.tzoffset / 1440. - elif self.units in day_units: - jdelta = time_value - self.tzoffset / 1440. - else: - raise ValueError('unsupported time units') - jd = self._jd0 + jdelta - if self.calendar in ['julian', 'standard', 'gregorian', 'proleptic_gregorian']: - if not isscalar: - if ismasked: - date = [] - for j, m in zip(jd.flat, mask.flat): - if not m: - date.append(DateFromJulianDay(j, self.calendar)) - else: - date.append(None) - else: - date = DateFromJulianDay(jd.flat, self.calendar) - else: - if ismasked and mask.item(): - date = None - else: - date = DateFromJulianDay(jd, self.calendar) - elif self.calendar in ['noleap', '365_day']: - if not isscalar: - date = [_DateFromNoLeapDay(j) for j in jd.flat] - else: - date = _DateFromNoLeapDay(jd) - elif self.calendar in ['all_leap', '366_day']: - if not isscalar: - date = [_DateFromAllLeap(j) for j in jd.flat] - else: - date = _DateFromAllLeap(jd) - elif self.calendar == '360_day': - if not isscalar: - date = [_DateFrom360Day(j) for j in jd.flat] - else: - date = _DateFrom360Day(jd) - if isscalar: - return date - else: - return numpy.reshape(numpy.array(date), shape) - - -cdef _parse_timezone(tzstring): - """Parses ISO 8601 time zone specs into tzinfo offsets - - Adapted from pyiso8601 (http://code.google.com/p/pyiso8601/) - """ - if tzstring == "Z": - return 0 - # This isn't strictly correct, but it's common to encounter dates without - # time zones so I'll assume the default (which defaults to UTC). - if tzstring is None: - return 0 - m = TIMEZONE_REGEX.match(tzstring) - prefix, hours, minutes1, minutes2 = m.groups() - hours = int(hours) -# Note: Minutes don't have to be specified in tzstring, -# so if the group is not found it means minutes is 0. -# Also, due to the timezone regex definition, there are two mutually -# exclusive groups that might hold the minutes value, so check both. - minutes = int(minutes1) if minutes1 is not None else int(minutes2) if minutes2 is not None else 0 - if prefix == "-": - hours = -hours - minutes = -minutes - return minutes + hours * 60. - - -cpdef _parse_date(datestring): - """Parses ISO 8601 dates into datetime objects - - The timezone is parsed from the date string, assuming UTC - by default. - - Adapted from pyiso8601 (http://code.google.com/p/pyiso8601/) - """ - if not isinstance(datestring, str) and not isinstance(datestring, unicode): - raise ValueError("Expecting a string %r" % datestring) - m = ISO8601_REGEX.match(datestring.strip()) - if not m: - raise ValueError("Unable to parse date string %r" % datestring) - groups = m.groupdict() - tzoffset_mins = _parse_timezone(groups["timezone"]) - if groups["hour"] is None: - groups["hour"] = 0 - if groups["minute"] is None: - groups["minute"] = 0 - if groups["second"] is None: - groups["second"] = 0 - # if groups["fraction"] is None: - # groups["fraction"] = 0 - # else: - # groups["fraction"] = int(float("0.%s" % groups["fraction"]) * 1e6) - iyear = int(groups["year"]) - return iyear, int(groups["month"]), int(groups["day"]),\ - int(groups["hour"]), int(groups["minute"]), int(groups["second"]),\ - tzoffset_mins - -cdef _check_index(indices, times, nctime, calendar, select): - """Return True if the time indices given correspond to the given times, - False otherwise. - - Parameters: - - indices : sequence of integers - Positive integers indexing the time variable. - - times : sequence of times. - Reference times. - - nctime : netCDF Variable object - NetCDF time object. - - calendar : string - Calendar of nctime. - - select : string - Index selection method. - """ - N = nctime.shape[0] - if (indices < 0).any(): - return False - - if (indices >= N).any(): - return False - - try: - t = nctime[indices] - nctime = nctime - # WORKAROUND TO CHANGES IN SLICING BEHAVIOUR in 1.1.2 - # this may be unacceptably slow... - # if indices are unsorted, or there are duplicate - # values in indices, read entire time variable into numpy - # array so numpy slicing rules can be used. - except IndexError: - nctime = nctime[:] - t = nctime[indices] -# if fancy indexing not available, fall back on this. -# t=[] -# for ind in indices: -# t.append(nctime[ind]) - - if select == 'exact': - return numpy.all(t == times) - - elif select == 'before': - ta = nctime[numpy.clip(indices + 1, 0, N - 1)] - return numpy.all(t <= times) and numpy.all(ta > times) - - elif select == 'after': - tb = nctime[numpy.clip(indices - 1, 0, N - 1)] - return numpy.all(t >= times) and numpy.all(tb < times) - - elif select == 'nearest': - ta = nctime[numpy.clip(indices + 1, 0, N - 1)] - tb = nctime[numpy.clip(indices - 1, 0, N - 1)] - delta_after = ta - t - delta_before = t - tb - delta_check = numpy.abs(times - t) - return numpy.all(delta_check <= delta_after) and numpy.all(delta_check <= delta_before) - - -def date2index(dates, nctime, calendar=None, select='exact'): - """ - date2index(dates, nctime, calendar=None, select='exact') - - Return indices of a netCDF time variable corresponding to the given dates. - - @param dates: A datetime object or a sequence of datetime objects. - The datetime objects should not include a time-zone offset. - - @param nctime: A netCDF time variable object. The nctime object must have a - C{units} attribute. The entries are assumed to be stored in increasing - order. - - @param calendar: Describes the calendar used in the time calculation. - Valid calendars C{'standard', 'gregorian', 'proleptic_gregorian' - 'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'}. - Default is C{'standard'}, which is a mixed Julian/Gregorian calendar - If C{calendar} is None, its value is given by C{nctime.calendar} or - C{standard} if no such attribute exists. - - @param select: C{'exact', 'before', 'after', 'nearest'} - The index selection method. C{exact} will return the indices perfectly - matching the dates given. C{before} and C{after} will return the indices - corresponding to the dates just before or just after the given dates if - an exact match cannot be found. C{nearest} will return the indices that - correspond to the closest dates. - """ - try: - nctime.units - except AttributeError: - raise AttributeError("netcdf time variable is missing a 'units' attribute") - # Setting the calendar. - if calendar == None: - calendar = getattr(nctime, 'calendar', 'standard') - cdftime = utime(nctime.units,calendar=calendar) - times = cdftime.date2num(dates) - return time2index(times, nctime, calendar=calendar, select=select) - - -def time2index(times, nctime, calendar=None, select='exact'): - """ - time2index(times, nctime, calendar=None, select='exact') - - Return indices of a netCDF time variable corresponding to the given times. - - @param times: A numeric time or a sequence of numeric times. - - @param nctime: A netCDF time variable object. The nctime object must have a - C{units} attribute. The entries are assumed to be stored in increasing - order. - - @param calendar: Describes the calendar used in the time calculation. - Valid calendars C{'standard', 'gregorian', 'proleptic_gregorian' - 'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'}. - Default is C{'standard'}, which is a mixed Julian/Gregorian calendar - If C{calendar} is None, its value is given by C{nctime.calendar} or - C{standard} if no such attribute exists. - - @param select: C{'exact', 'before', 'after', 'nearest'} - The index selection method. C{exact} will return the indices perfectly - matching the times given. C{before} and C{after} will return the indices - corresponding to the times just before or just after the given times if - an exact match cannot be found. C{nearest} will return the indices that - correspond to the closest times. - """ - try: - nctime.units - except AttributeError: - raise AttributeError("netcdf time variable is missing a 'units' attribute") - # Setting the calendar. - if calendar == None: - calendar = getattr(nctime, 'calendar', 'standard') - - num = numpy.atleast_1d(times) - N = len(nctime) - - # Trying to infer the correct index from the starting time and the stride. - # This assumes that the times are increasing uniformly. - if len(nctime) >= 2: - t0, t1 = nctime[:2] - dt = t1 - t0 - else: - t0 = nctime[0] - dt = 1. - if select in ['exact', 'before']: - index = numpy.array((num - t0) / dt, int) - elif select == 'after': - index = numpy.array(numpy.ceil((num - t0) / dt), int) - else: - index = numpy.array(numpy.around((num - t0) / dt), int) - - # Checking that the index really corresponds to the given time. - # If the times do not correspond, then it means that the times - # are not increasing uniformly and we try the bisection method. - if not _check_index(index, times, nctime, calendar, select): - - # Use the bisection method. Assumes nctime is ordered. - import bisect - index = numpy.array([bisect.bisect_right(nctime, n) for n in num], int) - before = index == 0 - - index = numpy.array([bisect.bisect_left(nctime, n) for n in num], int) - after = index == N - - if select in ['before', 'exact'] and numpy.any(before): - raise ValueError( - 'Some of the times given are before the first time in `nctime`.') - - if select in ['after', 'exact'] and numpy.any(after): - raise ValueError( - 'Some of the times given are after the last time in `nctime`.') - - # Find the times for which the match is not perfect. - # Use list comprehension instead of the simpler `nctime[index]` since - # not all time objects support numpy integer indexing (eg dap). - index[after] = N - 1 - ncnum = numpy.squeeze([nctime[i] for i in index]) - mismatch = numpy.nonzero(ncnum != num)[0] - - if select == 'exact': - if len(mismatch) > 0: - raise ValueError( - 'Some of the times specified were not found in the `nctime` variable.') - - elif select == 'before': - index[after] = N - index[mismatch] -= 1 - - elif select == 'after': - pass - - elif select == 'nearest': - nearest_to_left = num[mismatch] < numpy.array( - [float(nctime[i - 1]) + float(nctime[i]) for i in index[mismatch]]) / 2. - index[mismatch] = index[mismatch] - 1 * nearest_to_left - - else: - raise ValueError( - "%s is not an option for the `select` argument." % select) - - # Correct for indices equal to -1 - index[before] = 0 - - # convert numpy scalars or single element arrays to python ints. - return _toscalar(index) - - -cdef _toscalar(a): - if a.shape in [(), (1,)]: - return a.item() - else: - return a - -cdef to_tuple(dt): - """Turn a datetime.datetime instance into a tuple of integers. Elements go - in the order of decreasing significance, making it easy to compare - datetime instances. Parts of the state that don't affect ordering - are omitted. Compare to datetime.timetuple().""" - return (dt.year, dt.month, dt.day, dt.hour, dt.minute, - dt.second, dt.microsecond) - -# a cache of converters (utime instances) for different calendars -cdef dict _converters -_converters = {} -for calendar in _calendars: - _converters[calendar] = utime("seconds since 1-1-1", calendar) - -cdef class datetime(object): - """ -The base class implementing most methods of datetime classes that -mimic datetime.datetime but support calendars other than the proleptic -Gregorial calendar. - """ - cdef readonly int year, month, day, hour, minute, dayofwk, dayofyr - cdef readonly int second, microsecond - cdef readonly str calendar - - # Python's datetime.datetime uses the proleptic Gregorian - # calendar. This boolean is used to decide whether a - # netcdftime.datetime instance can be converted to - # datetime.datetime. - cdef readonly bint datetime_compatible - - def __init__(self, int year, int month, int day, int hour=0, int minute=0, int second=0, - int microsecond=0, int dayofwk=-1, int dayofyr=1): - """dayofyr set to 1 by default - otherwise time.strftime will complain""" - - self.year = year - self.month = month - self.day = day - self.hour = hour - self.minute = minute - self.dayofwk = dayofwk - self.dayofyr = dayofyr - self.second = second - self.microsecond = microsecond - self.calendar = "" - - self.datetime_compatible = True - - @property - def format(self): - return '%Y-%m-%d %H:%M:%S' - - def strftime(self, format=None): - if format is None: - format = self.format - return _strftime(self, format) - - def replace(self, **kwargs): - "Return datetime with new specified fields." - args = {"year": self.year, - "month": self.month, - "day": self.day, - "hour": self.hour, - "minute": self.minute, - "second": self.second, - "microsecond": self.microsecond, - "dayofwk": self.dayofwk, - "dayofyr": self.dayofyr} - - for name, value in kwargs.items(): - args[name] = value - - return self.__class__(**args) - - def timetuple(self): - return (self.year, self.month, self.day, self.hour, - self.minute, self.second, self.dayofwk, self.dayofyr, -1) - - cpdef _to_real_datetime(self): - return real_datetime(self.year, self.month, self.day, - self.hour, self.minute, self.second, - self.microsecond) - - def __repr__(self): - return "{0}.{1}{2}".format(self.__class__.__module__, - self.__class__.__name__, - self._getstate()) - - def __str__(self): - return self.strftime(self.format) - - def __hash__(self): - try: - d = self._to_real_datetime() - except ValueError: - return hash(self.timetuple()) - return hash(d) - - cdef to_tuple(self): - return (self.year, self.month, self.day, self.hour, self.minute, - self.second, self.microsecond) - - def __richcmp__(self, other, int op): - cdef datetime dt, dt_other - dt = self - if isinstance(other, datetime): - dt_other = other - # comparing two datetime instances - if dt.calendar == dt_other.calendar: - return PyObject_RichCompare(dt.to_tuple(), dt_other.to_tuple(), op) - else: - # Note: it *is* possible to compare datetime - # instances that use difference calendars by using - # utime.date2num(), but this implementation does - # not attempt it. - raise TypeError("cannot compare {0!r} and {1!r} (different calendars)".format(dt, dt_other)) - elif isinstance(other, real_datetime): - # comparing datetime and real_datetime - if not dt.datetime_compatible: - raise TypeError("cannot compare {0!r} and {1!r} (different calendars)".format(self, other)) - return PyObject_RichCompare(dt.to_tuple(), to_tuple(other), op) - else: - raise TypeError("cannot compare {0!r} and {1!r}".format(self, other)) - - cdef _getstate(self): - return (self.year, self.month, self.day, self.hour, - self.minute, self.second, self.microsecond, - self.dayofwk, self.dayofyr) - - def __reduce__(self): - """special method that allows instance to be pickled""" - return (self.__class__, self._getstate()) - - cdef _add_timedelta(self, other): - return NotImplemented - - def __add__(self, other): - cdef datetime dt - if isinstance(self, datetime) and isinstance(other, timedelta): - dt = self - delta = other - elif isinstance(self, timedelta) and isinstance(other, datetime): - dt = other - delta = self - else: - return NotImplemented - return dt._add_timedelta(delta) - - def __sub__(self, other): - cdef datetime dt - if isinstance(self, datetime): # left arg is a datetime instance - dt = self - if isinstance(other, datetime): - # datetime - datetime - if dt.calendar != other.calendar: - raise ValueError("cannot compute the time difference between dates with different calendars") - if dt.calendar == "": - raise ValueError("cannot compute the time difference between dates that are not calendar-aware") - converter = _converters[dt.calendar] - return timedelta(seconds=converter.date2num(dt) - converter.date2num(other)) - elif isinstance(other, real_datetime): - # datetime - real_datetime - if not dt.datetime_compatible: - raise ValueError("cannot compute the time difference between dates with different calendars") - return dt._to_real_datetime() - other - elif isinstance(other, timedelta): - # datetime - timedelta - return dt._add_timedelta(-other) - else: - return NotImplemented - else: - if isinstance(self, real_datetime): - # real_datetime - datetime - if not other.datetime_compatible: - raise ValueError("cannot compute the time difference between dates with different calendars") - return self - other._to_real_datetime() - else: - return NotImplemented - -cdef class DatetimeNoLeap(datetime): - """ -Phony datetime object which mimics the python datetime object, -but uses the "noleap" ("365_day") calendar. - """ - def __init__(self, *args, **kwargs): - datetime.__init__(self, *args, **kwargs) - self.calendar = "noleap" - self.datetime_compatible = False - - cdef _add_timedelta(self, delta): - return DatetimeNoLeap(*add_timedelta(self, delta, no_leap, False)) - -cdef class DatetimeAllLeap(datetime): - """ -Phony datetime object which mimics the python datetime object, -but uses the "all_leap" ("366_day") calendar. - """ - def __init__(self, *args, **kwargs): - datetime.__init__(self, *args, **kwargs) - self.calendar = "all_leap" - self.datetime_compatible = False - - cdef _add_timedelta(self, delta): - return DatetimeAllLeap(*add_timedelta(self, delta, all_leap, False)) - -cdef class Datetime360Day(datetime): - """ -Phony datetime object which mimics the python datetime object, -but uses the "360_day" calendar. - """ - def __init__(self, *args, **kwargs): - datetime.__init__(self, *args, **kwargs) - self.calendar = "360_day" - self.datetime_compatible = False - - cdef _add_timedelta(self, delta): - return Datetime360Day(*add_timedelta_360_day(self, delta)) - -cdef class DatetimeJulian(datetime): - """ -Phony datetime object which mimics the python datetime object, -but uses the "julian" calendar. - """ - def __init__(self, *args, **kwargs): - datetime.__init__(self, *args, **kwargs) - self.calendar = "julian" - self.datetime_compatible = False - - cdef _add_timedelta(self, delta): - return DatetimeJulian(*add_timedelta(self, delta, is_leap_julian, False)) - -cdef class DatetimeGregorian(datetime): - """ -Phony datetime object which mimics the python datetime object, -but uses the mixed Julian-Gregorian ("standard", "gregorian") calendar. - -The last date of the Julian calendar is 1582-10-4, which is followed -by 1582-10-15, using the Gregorian calendar. - -Instances using the date after 1582-10-15 can be compared to -datetime.datetime instances and used to compute time differences -(datetime.timedelta) by subtracting a DatetimeGregorian instance from -a datetime.datetime instance or vice versa. - """ - def __init__(self, *args, **kwargs): - datetime.__init__(self, *args, **kwargs) - self.calendar = "gregorian" - - # dates after 1582-10-15 can be converted to and compared to - # proleptic Gregorian dates - if self.to_tuple() >= (1582, 10, 15, 0, 0, 0, 0): - self.datetime_compatible = True - else: - self.datetime_compatible = False - - cdef _add_timedelta(self, delta): - return DatetimeGregorian(*add_timedelta(self, delta, is_leap_gregorian, True)) - -cdef class DatetimeProlepticGregorian(datetime): - """ -Phony datetime object which mimics the python datetime object, -but allows for dates that don't exist in the proleptic gregorian calendar. - -Supports timedelta operations by overloading + and -. - -Has strftime, timetuple, replace, __repr__, and __str__ methods. The -format of the string produced by __str__ is controlled by self.format -(default %Y-%m-%d %H:%M:%S). Supports comparisons with other phony -datetime instances using the same calendar; comparison with -datetime.datetime instances is possible for netcdftime.datetime -instances using 'gregorian' and 'proleptic_gregorian' calendars. - -Instance variables are year,month,day,hour,minute,second,microsecond,dayofwk,dayofyr, -format, and calendar. - """ - def __init__(self, *args, **kwargs): - datetime.__init__(self, *args, **kwargs) - self.calendar = "proleptic_gregorian" - self.datetime_compatible = True - - cdef _add_timedelta(self, delta): - return DatetimeProlepticGregorian(*add_timedelta(self, delta, - is_leap_proleptic_gregorian, False)) - -_illegal_s = re.compile(r"((^|[^%])(%%)*%s)") - - -cdef _findall(text, substr): - # Also finds overlaps - sites = [] - i = 0 - while 1: - j = text.find(substr, i) - if j == -1: - break - sites.append(j) - i = j + 1 - return sites - -# Every 28 years the calendar repeats, except through century leap -# years where it's 6 years. But only if you're using the Gregorian -# calendar. ;) - - -cdef _strftime(datetime dt, fmt): - if _illegal_s.search(fmt): - raise TypeError("This strftime implementation does not handle %s") - # don't use strftime method at all. - # if dt.year > 1900: - # return dt.strftime(fmt) - - year = dt.year - # For every non-leap year century, advance by - # 6 years to get into the 28-year repeat cycle - delta = 2000 - year - off = 6 * (delta // 100 + delta // 400) - year = year + off - - # Move to around the year 2000 - year = year + ((2000 - year) // 28) * 28 - timetuple = dt.timetuple() - s1 = time.strftime(fmt, (year,) + timetuple[1:]) - sites1 = _findall(s1, str(year)) - - s2 = time.strftime(fmt, (year + 28,) + timetuple[1:]) - sites2 = _findall(s2, str(year + 28)) - - sites = [] - for site in sites1: - if site in sites2: - sites.append(site) - - s = s1 - syear = "%4d" % (dt.year,) - for site in sites: - s = s[:site] + syear + s[site + 4:] - return s - -cdef bint is_leap_julian(int year): - "Return 1 if year is a leap year in the Julian calendar, 0 otherwise." - cdef int y - y = year if year > 0 else year + 1 - return (y % 4) == 0 - -cdef bint is_leap_proleptic_gregorian(int year): - "Return 1 if year is a leap year in the Gregorian calendar, 0 otherwise." - cdef int y - y = year if year > 0 else year + 1 - return (((y % 4) == 0) and ((y % 100) != 0)) or ((y % 400) == 0) - -cdef bint is_leap_gregorian(int year): - return (year > 1582 and is_leap_proleptic_gregorian(year)) or (year < 1582 and is_leap_julian(year)) - -cdef bint all_leap(int year): - "Return True for all years." - return True - -cdef bint no_leap(int year): - "Return False for all years." - return False - -# numbers of days per month for calendars supported by add_timedelta(...) -cdef int[13] month_lengths_365_day, month_lengths_366_day -# Dummy Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec -for j,N in enumerate([-1, 31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]): - month_lengths_365_day[j] = N - -# Dummy Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec -for j,N in enumerate([-1, 31, 29, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]): - month_lengths_366_day[j] = N - -cdef int* month_lengths(bint (*is_leap)(int), int year): - if is_leap(year): - return month_lengths_366_day - else: - return month_lengths_365_day - -# Add a datetime.timedelta to a netcdftime.datetime instance. Uses -# integer arithmetic to avoid rounding errors and preserve -# microsecond accuracy. -# -# The argument is_leap is the pointer to a function returning 1 for leap years and 0 otherwise. -# -# This implementation supports 365_day (no_leap), 366_day (all_leap), -# julian, proleptic_gregorian, and the mixed Julian/Gregorian -# (standard, gregorian) calendars by using different is_leap and -# julian_gregorian_mixed arguments. -# -# The date of the transition from the Julian to Gregorian calendar and -# the number of invalid dates are hard-wired (1582-10-4 is the last day -# of the Julian calendar, after which follows 1582-10-15). -cdef tuple add_timedelta(datetime dt, delta, bint (*is_leap)(int), bint julian_gregorian_mixed): - cdef int microsecond, second, minute, hour, day, month, year - cdef int delta_microseconds, delta_seconds, delta_days - cdef int* month_length - cdef int extra_days, n_invalid_dates - - # extract these inputs here to avoid type conversion in the code below - delta_microseconds = delta.microseconds - delta_seconds = delta.seconds - delta_days = delta.days - - # shift microseconds, seconds, days - microsecond = dt.microsecond + delta_microseconds - second = dt.second + delta_seconds - minute = dt.minute - hour = dt.hour - day = dt.day - month = dt.month - year = dt.year - - # validate inputs: - if year == 0: - raise ValueError("invalid year in {0!r}".format(dt)) - - month_length = month_lengths(is_leap, year) - - if month < 1 or month > 12: - raise ValueError("invalid month in {0!r}".format(dt)) - - if day < 1 or day > month_length[month]: - raise ValueError("invalid day number in {0!r}".format(dt)) - - if julian_gregorian_mixed and year == 1582 and month == 10 and day > 4 and day < 15: - raise ValueError("{0!r} is not present in the mixed Julian/Gregorian calendar".format(dt)) - - n_invalid_dates = 10 if julian_gregorian_mixed else 0 - - # Normalize microseconds, seconds, minutes, hours. - second += microsecond // 1000000 - microsecond = microsecond % 1000000 - minute += second // 60 - second = second % 60 - hour += minute // 60 - minute = minute % 60 - extra_days = hour // 24 - hour = hour % 24 - - delta_days += extra_days - - while delta_days < 0: - if year == 1582 and month == 10 and day > 14 and day + delta_days < 15: - delta_days -= n_invalid_dates # skip over invalid dates - if day + delta_days < 1: - delta_days += day - # decrement month - month -= 1 - if month < 1: - month = 12 - year -= 1 - if year == 0: - year = -1 - month_length = month_lengths(is_leap, year) - day = month_length[month] - else: - day += delta_days - delta_days = 0 - - while delta_days > 0: - if year == 1582 and month == 10 and day < 5 and day + delta_days > 4: - delta_days += n_invalid_dates # skip over invalid dates - if day + delta_days > month_length[month]: - delta_days -= month_length[month] - (day - 1) - # increment month - month += 1 - if month > 12: - month = 1 - year += 1 - if year == 0: - year = 1 - month_length = month_lengths(is_leap, year) - day = 1 - else: - day += delta_days - delta_days = 0 - - return (year, month, day, hour, minute, second, microsecond, -1, 1) - -# Add a datetime.timedelta to a netcdftime.datetime instance with the 360_day calendar. -# -# Assumes that the 360_day calendar (unlike the rest of supported -# calendars) has the year 0. Also, there are no leap years and all -# months are 30 days long, so we can compute month and year by using -# "//" and "%". -cdef tuple add_timedelta_360_day(datetime dt, delta): - cdef int microsecond, second, minute, hour, day, month, year - cdef int delta_microseconds, delta_seconds, delta_days - - assert dt.month >= 1 and dt.month <= 12 - - # extract these inputs here to avoid type conversion in the code below - delta_microseconds = delta.microseconds - delta_seconds = delta.seconds - delta_days = delta.days - - # shift microseconds, seconds, days - microsecond = dt.microsecond + delta_microseconds - second = dt.second + delta_seconds - minute = dt.minute - hour = dt.hour - day = dt.day + delta_days - month = dt.month - year = dt.year - - # Normalize microseconds, seconds, minutes, hours, days, and months. - second += microsecond // 1000000 - microsecond = microsecond % 1000000 - minute += second // 60 - second = second % 60 - hour += minute // 60 - minute = minute % 60 - day += hour // 24 - hour = hour % 24 - # day and month are counted from 1; all months have 30 days - month += (day - 1) // 30 - day = (day - 1) % 30 + 1 - # all years have 12 months - year += (month - 1) // 12 - month = (month - 1) % 12 + 1 - - return (year, month, day, hour, minute, second, microsecond, -1, 1) From fdbb4fc20d8e208ab15fd8f8090eab229fa2fe35 Mon Sep 17 00:00:00 2001 From: Jeffrey Whitaker Date: Wed, 31 Jan 2018 11:35:13 -0500 Subject: [PATCH 0003/1504] don't use netcdftime if it is not installed, raise ImportError if you try to --- netCDF4/_netCDF4.pyx | 19 +++++++++-- test/run_all.py | 8 +++++ test/tst_multifile.py | 76 +++++++++++++++++++++++------------------- test/tst_multifile2.py | 44 +++++++++++++----------- 4 files changed, 90 insertions(+), 57 deletions(-) diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx index b04354f9e..c1565be22 100644 --- a/netCDF4/_netCDF4.pyx +++ b/netCDF4/_netCDF4.pyx @@ -1007,7 +1007,11 @@ __version__ = "1.3.2" # Initialize numpy import posixpath -import netcdftime +try: + import netcdftime + _has_netcdftime = True +except ImportError: + _has_netcdftime = False import numpy import weakref import sys @@ -5455,8 +5459,9 @@ def _to_ascii(bytestr): # extra utilities (formerly in utils.pyx) #---------------------------------------- from datetime import timedelta, datetime, MINYEAR -from netcdftime import _parse_date, microsec_units, millisec_units,\ - sec_units, min_units, hr_units, day_units +if _has_netcdftime: + from netcdftime import _parse_date, microsec_units, millisec_units,\ + sec_units, min_units, hr_units, day_units # start of the gregorian calendar gregorian = datetime(1582,10,15) @@ -5464,6 +5469,8 @@ gregorian = datetime(1582,10,15) def _dateparse(timestr): """parse a string of the form time-units since yyyy-mm-dd hh:mm:ss, return a datetime instance""" + if not _has_netcdftime: + raise ImportError('please install netcdftime to use this feature') # same as version in netcdftime, but returns a timezone naive # python datetime instance with the utc_offset included. timestr_split = timestr.split() @@ -5584,6 +5591,8 @@ Default is `'standard'`, which is a mixed Julian/Gregorian calendar. returns a numeric time value, or an array of numeric time values with approximately millisecond accuracy. """ + if not _has_netcdftime: + raise ImportError('please install netcdftime to use this feature') calendar = calendar.lower() basedate = _dateparse(units) unit = units.split()[0].lower() @@ -5680,6 +5689,8 @@ datetime objects. The datetime instances do not contain a time-zone offset, even if the specified `units` contains one. """ + if not _has_netcdftime: + raise ImportError('please install netcdftime to use this feature') calendar = calendar.lower() basedate = _dateparse(units) unit = units.split()[0].lower() @@ -5778,6 +5789,8 @@ correspond to the closest dates. returns an index (indices) of the netCDF time variable corresponding to the given datetime object(s). """ + if not _has_netcdftime: + raise ImportError('please install netcdftime to use this feature') try: nctime.units except AttributeError: diff --git a/test/run_all.py b/test/run_all.py index f06590cff..c2693f5c8 100755 --- a/test/run_all.py +++ b/test/run_all.py @@ -1,6 +1,11 @@ import glob, os, sys, unittest, struct from netCDF4 import getlibversion,__hdf5libversion__,__netcdf4libversion__,__version__ from netCDF4 import __has_cdf5_format__, __has_nc_inq_path__, __has_nc_par__ +try: + import netcdftime + _has_netcdftime = True +except ImportError: + _has_netcdftime = False # can also just run # python -m unittest discover . 'tst*py' @@ -24,6 +29,9 @@ if not __has_cdf5_format__ or struct.calcsize("P") < 8: test_files.remove('tst_cdf5.py') sys.stdout.write('not running tst_cdf5.py ...\n') +if not _has_netcdftime: + test_files.remove('tst_netcdftime.py') + sys.stdout.write('not running tst_netcdftime.py ...\n') # Don't run tests that require network connectivity if os.getenv('NO_NET'): diff --git a/test/tst_multifile.py b/test/tst_multifile.py index 0bc304360..95a69835a 100644 --- a/test/tst_multifile.py +++ b/test/tst_multifile.py @@ -4,6 +4,11 @@ from numpy.testing import assert_array_equal, assert_equal from numpy import ma import tempfile, unittest, os, datetime +try: + import netcdftime + _has_netcdftime = True +except ImportError: + _has_netcdftime = False nx=100; ydim=5; zdim=10 nfiles = 10 @@ -111,44 +116,45 @@ def runTest(self): # The test files have no calendar attribute on the time variable. calendar = 'standard' - # Get the real dates - dates = [] - for file in self.files: - f = Dataset(file) + if _has_netcdftime: + # Get the real dates + dates = [] + for file in self.files: + f = Dataset(file) + t = f.variables['time'] + dates.extend(num2date(t[:], t.units, calendar)) + f.close() + + # Compare with the MF dates + f = MFDataset(self.files,check=True) t = f.variables['time'] - dates.extend(num2date(t[:], t.units, calendar)) - f.close() - # Compare with the MF dates - f = MFDataset(self.files,check=True) - t = f.variables['time'] - - T = MFTime(t, calendar=calendar) - assert_equal(T.calendar, calendar) - assert_equal(len(T), len(t)) - assert_equal(T.shape, t.shape) - assert_equal(T.dimensions, t.dimensions) - assert_equal(T.typecode(), t.typecode()) - assert_array_equal(num2date(T[:], T.units, T.calendar), dates) - assert_equal(date2index(datetime.datetime(1980, 1, 2), T), 366) - f.close() + T = MFTime(t, calendar=calendar) + assert_equal(T.calendar, calendar) + assert_equal(len(T), len(t)) + assert_equal(T.shape, t.shape) + assert_equal(T.dimensions, t.dimensions) + assert_equal(T.typecode(), t.typecode()) + assert_array_equal(num2date(T[:], T.units, T.calendar), dates) + assert_equal(date2index(datetime.datetime(1980, 1, 2), T), 366) + f.close() - # Test exception is raised when no calendar attribute is available on the - # time variable. - with MFDataset(self.files, check=True) as ds: - with self.assertRaises(ValueError): - MFTime(ds.variables['time']) - - # Test exception is raised when the calendar attribute is different on the - # variables. First, add calendar attributes to file. Note this will modify - # the files inplace. - calendars = ['standard', 'gregorian'] - for idx, f in enumerate(self.files): - with Dataset(f, 'a') as ds: - ds.variables['time'].calendar = calendars[idx] - with MFDataset(self.files, check=True) as ds: - with self.assertRaises(ValueError): - MFTime(ds.variables['time']) + # Test exception is raised when no calendar attribute is available on the + # time variable. + with MFDataset(self.files, check=True) as ds: + with self.assertRaises(ValueError): + MFTime(ds.variables['time']) + + # Test exception is raised when the calendar attribute is different on the + # variables. First, add calendar attributes to file. Note this will modify + # the files inplace. + calendars = ['standard', 'gregorian'] + for idx, f in enumerate(self.files): + with Dataset(f, 'a') as ds: + ds.variables['time'].calendar = calendars[idx] + with MFDataset(self.files, check=True) as ds: + with self.assertRaises(ValueError): + MFTime(ds.variables['time']) if __name__ == '__main__': diff --git a/test/tst_multifile2.py b/test/tst_multifile2.py index c16ed9ab6..9182dc302 100644 --- a/test/tst_multifile2.py +++ b/test/tst_multifile2.py @@ -4,6 +4,11 @@ from numpy.testing import assert_array_equal, assert_equal from numpy import ma import tempfile, unittest, os, datetime +try: + import netcdftime + _has_netcdftime = True +except ImportError: + _has_netcdftime = False nx=100; ydim=5; zdim=10 nfiles = 10 @@ -101,27 +106,28 @@ def tearDown(self): def runTest(self): - # Get the real dates - dates = [] - for file in self.files: - f = Dataset(file) + if _has_netcdftime: + # Get the real dates + dates = [] + for file in self.files: + f = Dataset(file) + t = f.variables['time'] + dates.extend(num2date(t[:], t.units, t.calendar)) + f.close() + + # Compare with the MF dates + f = MFDataset(self.files,check=True) t = f.variables['time'] - dates.extend(num2date(t[:], t.units, t.calendar)) + mfdates = num2date(t[:], t.units, t.calendar) + + T = MFTime(t) + assert_equal(len(T), len(t)) + assert_equal(T.shape, t.shape) + assert_equal(T.dimensions, t.dimensions) + assert_equal(T.typecode(), t.typecode()) + assert_array_equal(num2date(T[:], T.units, T.calendar), dates) + assert_equal(date2index(datetime.datetime(1980, 1, 2), T), 366) f.close() - # Compare with the MF dates - f = MFDataset(self.files,check=True) - t = f.variables['time'] - mfdates = num2date(t[:], t.units, t.calendar) - - T = MFTime(t) - assert_equal(len(T), len(t)) - assert_equal(T.shape, t.shape) - assert_equal(T.dimensions, t.dimensions) - assert_equal(T.typecode(), t.typecode()) - assert_array_equal(num2date(T[:], T.units, T.calendar), dates) - assert_equal(date2index(datetime.datetime(1980, 1, 2), T), 366) - f.close() - if __name__ == '__main__': unittest.main() From 1c04dea6d09bb35f7be166fbf232573ecdd909bd Mon Sep 17 00:00:00 2001 From: Jeffrey Whitaker Date: Wed, 31 Jan 2018 11:35:53 -0500 Subject: [PATCH 0004/1504] remove netcdftime --- MANIFEST.in | 2 -- 1 file changed, 2 deletions(-) diff --git a/MANIFEST.in b/MANIFEST.in index f6f156aee..fdc6217bd 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -13,8 +13,6 @@ include examples/*ipynb include examples/README.md include test/*py include test/*nc -include netcdftime/__init__.py -include netcdftime/_netcdftime.pyx include netCDF4/__init__.py include netCDF4/_netCDF4.pyx include netCDF4/utils.py From 3bbb0fa2d3448ee0bbcc150f11458229f5552280 Mon Sep 17 00:00:00 2001 From: Jeffrey Whitaker Date: Wed, 31 Jan 2018 11:47:18 -0500 Subject: [PATCH 0005/1504] add Changelog entry --- COPYING | 12 ------------ Changelog | 2 ++ 2 files changed, 2 insertions(+), 12 deletions(-) diff --git a/COPYING b/COPYING index 2cc338aca..c238e711e 100644 --- a/COPYING +++ b/COPYING @@ -15,18 +15,6 @@ OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. -parts of pyiso8601 are included in netcdftime under the following license: - -Copyright (c) 2007 Michael Twomey - -Permission is hereby granted, free of charge, to any person obtaining a -copy of this software and associated documentation files (the -"Software"), to deal in the Software without restriction, including -without limitation the rights to use, copy, modify, merge, publish, -distribute, sublicense, and/or sell copies of the Software, and to -permit persons to whom the Software is furnished to do so, subject to -the following conditions: - The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. diff --git a/Changelog b/Changelog index 89f8a9c38..6ab19f59f 100644 --- a/Changelog +++ b/Changelog @@ -4,6 +4,8 @@ #736, issue #713). * fixed reading of variables with zero-length dimensions in NETCDF3_CLASSIC files (issue #743). + * netcdftime removed. Raise ImportError in utilities that use it. + Tests that use netcdftime only run if it is installed separately. version 1.3.1 (tag v1.3.1rel) ============================= From 984c7cfc66b73533f5a5541fda50957f2dc304a9 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Sun, 11 Feb 2018 10:27:38 -0700 Subject: [PATCH 0006/1504] use more general method to check for integer --- netCDF4/_netCDF4.pyx | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx index b04354f9e..4fd379a25 100644 --- a/netCDF4/_netCDF4.pyx +++ b/netCDF4/_netCDF4.pyx @@ -988,7 +988,7 @@ from cpython.buffer cimport PyObject_GetBuffer, PyBuffer_Release, PyBUF_SIMPLE, # pure python utilities from .utils import (_StartCountStride, _quantize, _find_dim, _walk_grps, - _out_array_shape, _sortbylist, _tostr, _safecast) + _out_array_shape, _sortbylist, _tostr, _safecast, _is_int) # try to use built-in ordered dict in python >= 2.7 try: from collections import OrderedDict @@ -4185,7 +4185,7 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`.""" msg="data can only be assigned to VLEN variables using integer indices" # check to see that elem is a tuple of integers. # handle negative integers. - if isinstance(elem, int): + if _is_int(elem): if ndims > 1: raise IndexError(msg) if elem < 0: @@ -4198,7 +4198,7 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`.""" raise IndexError("Illegal index") elemnew = [] for n,e in enumerate(elem): - if not isinstance(e, int): + if not _is_int(e): raise IndexError(msg) elif e < 0: enew = self.shape[n]+e From 030a012060ac4ee508a4687a9660f6d540c5fcc0 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Sun, 11 Feb 2018 12:01:12 -0700 Subject: [PATCH 0007/1504] update --- Changelog | 2 ++ 1 file changed, 2 insertions(+) diff --git a/Changelog b/Changelog index 89f8a9c38..b86cb1fa4 100644 --- a/Changelog +++ b/Changelog @@ -4,6 +4,8 @@ #736, issue #713). * fixed reading of variables with zero-length dimensions in NETCDF3_CLASSIC files (issue #743). + * allow integer-like objects in VLEN slices (not just python ints, issue + #526, pull request #757). version 1.3.1 (tag v1.3.1rel) ============================= From 570ffdb48c576c66c74d922aa964bb05094d127d Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Sun, 11 Feb 2018 12:58:46 -0700 Subject: [PATCH 0008/1504] try to fix failing builds --- appveyor.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/appveyor.yml b/appveyor.yml index 9d5057f58..d5de9e317 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -38,6 +38,7 @@ install: - cmd: call %CONDA_INSTALL_LOCN%\Scripts\activate.bat # for obvci_appveyor_python_build_env.cmd - cmd: conda update --all --yes + - cmd: conda config --system --add pinned_packages defaults::conda - cmd: conda install anaconda-client=1.6.3 --yes - cmd: conda install -c conda-forge --yes obvious-ci # for msinttypes and newer stuff From 736d4383a9efcc124689a0835150284107a821bc Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Mon, 12 Feb 2018 07:04:49 -0700 Subject: [PATCH 0009/1504] add test for issue 526 --- test/tst_vlen.py | 17 +++++++++++++++++ 1 file changed, 17 insertions(+) diff --git a/test/tst_vlen.py b/test/tst_vlen.py index 46849c284..d6cd8dc9c 100644 --- a/test/tst_vlen.py +++ b/test/tst_vlen.py @@ -105,6 +105,23 @@ def runTest(self): f.close() os.remove(FILE_NAME) +class TestIntegerIndex(unittest.TestCase): + # issue 526 + def runTest(self): + strtest = Dataset(FILE_NAME, 'w', format='NETCDF4') + strtest.createDimension('tenstrings', 10) + strtest.createVariable('tenstrings', str, ['tenstrings']) + strtest['tenstrings'][long(4)] = 'asdf' + strtest['tenstrings'][np.int32(5)] = 'asdf' + strtest['tenstrings'][6.0] = 'asdf' + strtest.close() + f = Dataset(FILE_NAME) + assert f.variables['tenstrings'][long(4)] == 'asdf' + assert f.variables['tenstrings'][np.int32(5)] == 'asdf' + assert f.variables['tenstrings'][6.0] == 'asdf' + f.close() + os.remove(FILE_NAME) + class TestObjectArrayIndexing(unittest.TestCase): def setUp(self): From ae329080201550df7ab5d07bf7d47837a62223ff Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Mon, 12 Feb 2018 07:22:19 -0700 Subject: [PATCH 0010/1504] update --- test/tst_vlen.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/test/tst_vlen.py b/test/tst_vlen.py index d6cd8dc9c..2b6818c19 100644 --- a/test/tst_vlen.py +++ b/test/tst_vlen.py @@ -111,12 +111,10 @@ def runTest(self): strtest = Dataset(FILE_NAME, 'w', format='NETCDF4') strtest.createDimension('tenstrings', 10) strtest.createVariable('tenstrings', str, ['tenstrings']) - strtest['tenstrings'][long(4)] = 'asdf' strtest['tenstrings'][np.int32(5)] = 'asdf' strtest['tenstrings'][6.0] = 'asdf' strtest.close() f = Dataset(FILE_NAME) - assert f.variables['tenstrings'][long(4)] == 'asdf' assert f.variables['tenstrings'][np.int32(5)] == 'asdf' assert f.variables['tenstrings'][6.0] == 'asdf' f.close() From 43809f42158c6b42e98e136e7dfe3c14631a05c3 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Fri, 16 Feb 2018 14:40:45 -0800 Subject: [PATCH 0011/1504] update appveyor config --- appveyor.yml | 45 +++++++++++++++++++++------------------------ 1 file changed, 21 insertions(+), 24 deletions(-) diff --git a/appveyor.yml b/appveyor.yml index d5de9e317..81a5acfcc 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -1,23 +1,25 @@ environment: - - # SDK v7.0 MSVC Express 2008's SetEnv.cmd script will fail if the - # /E:ON and /V:ON options are not enabled in the batch script interpreter - # See: http://stackoverflow.com/a/13751649/163740 - CMD_IN_ENV: "cmd /E:ON /V:ON /C obvci_appveyor_python_build_env.cmd" - matrix: - TARGET_ARCH: x64 CONDA_NPY: 111 CONDA_PY: 27 CONDA_INSTALL_LOCN: C:\\Miniconda-x64 + - TARGET_ARCH: x64 + CONDA_NPY: 114 + CONDA_PY: 27 + CONDA_INSTALL_LOCN: C:\\Miniconda-x64 + - TARGET_ARCH: x64 CONDA_NPY: 111 CONDA_PY: 36 CONDA_INSTALL_LOCN: C:\\Miniconda35-x64 -# We always use a 64-bit machine, but can build x86 distributions -# with the TARGET_ARCH variable. + - TARGET_ARCH: x64 + CONDA_NPY: 114 + CONDA_PY: 36 + CONDA_INSTALL_LOCN: C:\\Miniconda35-x64 + platform: - x64 @@ -33,25 +35,20 @@ install: throw "There are newer queued builds for this pull request, failing early." } # Add path, activate `conda` and update conda. - - cmd: set "PATH=%CONDA_INSTALL_LOCN%\\Scripts;%CONDA_INSTALL_LOCN%\\Library\\bin;%PATH%" - - cmd: set PYTHONUNBUFFERED=1 - cmd: call %CONDA_INSTALL_LOCN%\Scripts\activate.bat - # for obvci_appveyor_python_build_env.cmd - - cmd: conda update --all --yes - - cmd: conda config --system --add pinned_packages defaults::conda - - cmd: conda install anaconda-client=1.6.3 --yes - - cmd: conda install -c conda-forge --yes obvious-ci - # for msinttypes and newer stuff - - cmd: conda config --prepend channels conda-forge - - cmd: conda config --set show_channel_urls yes - - cmd: conda config --set always_yes true - # For building conda packages - - cmd: conda install --yes conda-build jinja2 anaconda-client - # this is now the downloaded conda... - - cmd: conda info -a + - cmd: conda.exe config --set always_yes yes --set changeps1 no --set show_channel_urls true + - cmd: conda.exe update conda + - cmd: conda.exe config --add channels conda-forge --force + + - cmd: set PYTHONUNBUFFERED=1 + + - cmd: conda.exe install conda-build vs2008_express_vc_python_patch + - cmd: call setup_x64 + - cmd: conda.exe info --all + - cmd: conda.exe list # Skip .NET project specific build phase. build: off test_script: - - "%CMD_IN_ENV% conda build conda.recipe --quiet" + - "conda build conda.recipe" From d14f15e73a2576f5fa014653bfbdf12fabb968df Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Sat, 17 Feb 2018 07:44:19 -0700 Subject: [PATCH 0012/1504] don't treat _FillValue as valid_min/valid_max anymore (issue #761) --- Changelog | 3 +++ netCDF4/_netCDF4.pyx | 12 ++++++++---- test/tst_masked4.py | 4 +++- 3 files changed, 14 insertions(+), 5 deletions(-) diff --git a/Changelog b/Changelog index b86cb1fa4..26bfbd357 100644 --- a/Changelog +++ b/Changelog @@ -6,6 +6,9 @@ files (issue #743). * allow integer-like objects in VLEN slices (not just python ints, issue #526, pull request #757). + * treating _FillValue as a valid_min/valid_max was too surprising, despite + the fact the thet netcdf docs 'attribute best practices' suggests that + clients should to this. Revert this change from issue #576 (issue #761). version 1.3.1 (tag v1.3.1rel) ============================= diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx index 4fd379a25..e0971400d 100644 --- a/netCDF4/_netCDF4.pyx +++ b/netCDF4/_netCDF4.pyx @@ -4149,10 +4149,14 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`.""" fval = numpy.array(default_fillvals[self.dtype.str[1:]],self.dtype) if byte_type: fval = None if self.dtype.kind != 'S': # don't set mask for character data - if validmin is None and (fval is not None and fval <= 0): - validmin = fval - if validmax is None and (fval is not None and fval > 0): - validmax = fval + # issues #761 and #748: setting valid_min/valid_max to the + # _FillVaue is too surprising for many users (despite the + # netcdf docs attribute best practices suggesting clients + # should do this). + #if validmin is None and (fval is not None and fval <= 0): + # validmin = fval + #if validmax is None and (fval is not None and fval > 0): + # validmax = fval if validmin is not None: totalmask += data < validmin if validmax is not None: diff --git a/test/tst_masked4.py b/test/tst_masked4.py index 9d10ae669..33057c58e 100755 --- a/test/tst_masked4.py +++ b/test/tst_masked4.py @@ -94,7 +94,9 @@ def test_scaled(self): assert_array_almost_equal(v2, self.v_scaled) self.assertTrue(np.all(self.v_ma.mask == v.mask)) self.assertTrue(np.all(self.v_ma.mask == v2.mask)) - self.assertTrue(np.all(self.v_ma.mask == v3.mask)) + # treating _FillValue as valid_min/valid_max was + # too suprising, revert to old behaviour (issue #761) + #self.assertTrue(np.all(self.v_ma.mask == v3.mask)) # check that underlying data is same as in netcdf file v = f.variables['v'] v.set_auto_scale(False) From ee38316bf68a0aef5cdb81fb90ef1bc7eb363d8d Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 20 Feb 2018 10:15:15 -0700 Subject: [PATCH 0013/1504] update docstrings to mention netcdftime external dependency --- netCDF4/_netCDF4.pyx | 16 +++++++++++++++- 1 file changed, 15 insertions(+), 1 deletion(-) diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx index 97ef4ffa0..81e757d7f 100644 --- a/netCDF4/_netCDF4.pyx +++ b/netCDF4/_netCDF4.pyx @@ -41,6 +41,9 @@ Requires - [Cython](http://cython.org), version 0.21 or later. - [setuptools](https://pypi.python.org/pypi/setuptools), version 18.0 or later. + - [netcdftime](https://github.com/Unidata/netcdftime), in order to use + the time and date handling utility functions (`netCDF4.num2date` and + `netCDF4.date2num`). - The HDF5 C library version 1.8.4-patch1 or higher (1.8.x recommended) from [](ftp://ftp.hdfgroup.org/HDF5/current/src). ***netCDF version 4.4.1 or higher is recommended if using HDF5 1.10.x - @@ -543,7 +546,9 @@ measure relative to a fixed date using a certain calendar, with units specified like `hours since YY-MM-DD hh:mm:ss`. These units can be awkward to deal with, without a utility to convert the values to and from calendar dates. The function called `netCDF4.num2date` and `netCDF4.date2num` are -provided with this package to do just that. Here's an example of how they +provided with this package to do just that (starting with version 1.3.2, the +[netcdftime](https://github.com/Unidata/netcdftime) package must be installed +separately for these functions to work). Here's an example of how they can be used: :::python @@ -5590,6 +5595,9 @@ Default is `'standard'`, which is a mixed Julian/Gregorian calendar. returns a numeric time value, or an array of numeric time values with approximately millisecond accuracy. + +Requires the [netcdftime](https://github.com/Unidata/netcdftime) +external package. """ if not _has_netcdftime: raise ImportError('please install netcdftime to use this feature') @@ -5688,6 +5696,9 @@ objects which support some but not all the methods of 'real' python datetime objects. The datetime instances do not contain a time-zone offset, even if the specified `units` contains one. + +Requires the [netcdftime](https://github.com/Unidata/netcdftime) +external package. """ if not _has_netcdftime: raise ImportError('please install netcdftime to use this feature') @@ -5788,6 +5799,9 @@ correspond to the closest dates. returns an index (indices) of the netCDF time variable corresponding to the given datetime object(s). + +Requires the [netcdftime](https://github.com/Unidata/netcdftime) +external package. """ if not _has_netcdftime: raise ImportError('please install netcdftime to use this feature') From 8ea8af10cdb6c63b4ed8898a86d1119e5a2c2809 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 20 Feb 2018 12:03:24 -0700 Subject: [PATCH 0014/1504] add netcdftime dependency for travis builds --- .travis.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.travis.yml b/.travis.yml index 8c7aa5af4..cd6bc90e5 100644 --- a/.travis.yml +++ b/.travis.yml @@ -11,7 +11,7 @@ addons: env: global: - - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0" + - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 netcdftime>=1.0.0" - NO_NET=1 - MPI=0 From 5184e037b267a901a50dbc9e06d44b030cdfe71e Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 20 Feb 2018 12:07:16 -0700 Subject: [PATCH 0015/1504] update --- .travis.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.travis.yml b/.travis.yml index cd6bc90e5..dd66919e8 100644 --- a/.travis.yml +++ b/.travis.yml @@ -11,7 +11,7 @@ addons: env: global: - - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 netcdftime>=1.0.0" + - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 netcdftime>=1.0.0a1" - NO_NET=1 - MPI=0 From c287659b5f26f0fc4d26acd4f196434c9ea43903 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 20 Feb 2018 12:27:24 -0700 Subject: [PATCH 0016/1504] update --- .travis.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/.travis.yml b/.travis.yml index dd66919e8..f258a36d3 100644 --- a/.travis.yml +++ b/.travis.yml @@ -48,6 +48,7 @@ notifications: email: false before_install: + - pip install Cython # workaround for pip bug - pip install $DEPENDS install: From 58a25e5d6635b779a9ef1c2af79d97a87621579a Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 20 Feb 2018 12:37:06 -0700 Subject: [PATCH 0017/1504] netcdftime now uses zero padded years --- test/tst_netcdftime.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/test/tst_netcdftime.py b/test/tst_netcdftime.py index f4b31e89a..e70515b67 100644 --- a/test/tst_netcdftime.py +++ b/test/tst_netcdftime.py @@ -46,7 +46,7 @@ def runTest(self): # check attributes. self.assertTrue(self.cdftime_mixed.units == 'hours') self.assertTrue( - str(self.cdftime_mixed.origin) == ' 1-01-01 00:00:00') + str(self.cdftime_mixed.origin) == '0001-01-01 00:00:00') self.assertTrue( self.cdftime_mixed.unit_string == 'hours since 0001-01-01 00:00:00') self.assertTrue(self.cdftime_mixed.calendar == 'standard') @@ -85,7 +85,7 @@ def runTest(self): self.assertTrue(d_check == ''.join(d2)) # test proleptic gregorian calendar. self.assertTrue(self.cdftime_pg.units == 'seconds') - self.assertTrue(str(self.cdftime_pg.origin) == ' 1-01-01 00:00:00') + self.assertTrue(str(self.cdftime_pg.origin) == '0001-01-01 00:00:00') self.assertTrue( self.cdftime_pg.unit_string == 'seconds since 0001-01-01 00:00:00') self.assertTrue(self.cdftime_pg.calendar == 'proleptic_gregorian') @@ -280,7 +280,7 @@ def runTest(self): # Check leading white space self.assertEqual( - str(self.cdftime_leading_space.origin), ' 850-01-01 00:00:00') + str(self.cdftime_leading_space.origin), '0850-01-01 00:00:00') #issue 330 units = "seconds since 1970-01-01T00:00:00Z" From a018b8acce05651f4722387bc19bfc8f164e8b7a Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 20 Feb 2018 15:00:28 -0700 Subject: [PATCH 0018/1504] add cython runtime dependency (run_all.py tries to import it) --- conda.recipe/meta.yaml | 1 + 1 file changed, 1 insertion(+) diff --git a/conda.recipe/meta.yaml b/conda.recipe/meta.yaml index b5d35108d..b21e364e2 100644 --- a/conda.recipe/meta.yaml +++ b/conda.recipe/meta.yaml @@ -29,6 +29,7 @@ requirements: - numpy x.x - hdf5 - libnetcdf + - cython test: source_files: From 432295c047877ab81a9c1a8276e9194c848ace32 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 20 Feb 2018 15:06:09 -0700 Subject: [PATCH 0019/1504] don't try to import netcdftime --- conda.recipe/meta.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conda.recipe/meta.yaml b/conda.recipe/meta.yaml index b21e364e2..d3421d2e6 100644 --- a/conda.recipe/meta.yaml +++ b/conda.recipe/meta.yaml @@ -36,7 +36,7 @@ test: - test imports: - netCDF4 - - netcdftime +# - netcdftime commands: - ncinfo -h - nc4tonc3 -h From a3cdb4c496d96bb3a7bb3af7dc9b1da151dbd217 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 20 Feb 2018 16:42:10 -0700 Subject: [PATCH 0020/1504] update --- Changelog | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/Changelog b/Changelog index 784edb596..607d9d74f 100644 --- a/Changelog +++ b/Changelog @@ -11,6 +11,11 @@ * treating _FillValue as a valid_min/valid_max was too surprising, despite the fact the thet netcdf docs 'attribute best practices' suggests that clients should to this. Revert this change from issue #576 (issue #761). + * remove netcdftime, since it is now a separate package. Utility functions + (such date2num and date2num) that use netcdftime will now raise an + ImportError if they are used and netcdftime not installed. Pull request + #756. + version 1.3.1 (tag v1.3.1rel) ============================= From ecbea539f3bef50b5bf06aa44470f6af67361001 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 20 Feb 2018 17:14:08 -0700 Subject: [PATCH 0021/1504] have utilities just forward to netcdftime --- netCDF4/_netCDF4.pyx | 193 ++--------------------------------------- test/tst_netcdftime.py | 12 +-- 2 files changed, 13 insertions(+), 192 deletions(-) diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx index ebb02d979..1341f910a 100644 --- a/netCDF4/_netCDF4.pyx +++ b/netCDF4/_netCDF4.pyx @@ -5464,44 +5464,6 @@ def _to_ascii(bytestr): else: return bytestr.encode('ascii') -#---------------------------------------- -# extra utilities (formerly in utils.pyx) -#---------------------------------------- -from datetime import timedelta, datetime, MINYEAR -if _has_netcdftime: - from netcdftime import _parse_date, microsec_units, millisec_units,\ - sec_units, min_units, hr_units, day_units - -# start of the gregorian calendar -gregorian = datetime(1582,10,15) - -def _dateparse(timestr): - """parse a string of the form time-units since yyyy-mm-dd hh:mm:ss, - return a datetime instance""" - if not _has_netcdftime: - raise ImportError('please install netcdftime to use this feature') - # same as version in netcdftime, but returns a timezone naive - # python datetime instance with the utc_offset included. - timestr_split = timestr.split() - units = timestr_split[0].lower() - if timestr_split[1].lower() != 'since': - raise ValueError("no 'since' in unit_string") - # parse the date string. - n = timestr.find('since')+6 - isostring = timestr[n:] - year, month, day, hour, minute, second, utc_offset =\ - _parse_date( isostring.strip() ) - if year >= MINYEAR: - basedate = datetime(year, month, day, hour, minute, second) - # subtract utc_offset from basedate time instance (which is timezone naive) - basedate -= timedelta(days=utc_offset/1440.) - else: - if not utc_offset: - basedate = netcdftime.datetime(year, month, day, hour, minute, second) - else: - raise ValueError('cannot use utc_offset for reference years <= 0') - return basedate - def stringtoarr(string,NUMCHARS,dtype='S'): """ **`stringtoarr(a, NUMCHARS,dtype='S')`** @@ -5605,64 +5567,8 @@ external package. """ if not _has_netcdftime: raise ImportError('please install netcdftime to use this feature') - calendar = calendar.lower() - basedate = _dateparse(units) - unit = units.split()[0].lower() - # real-world calendars limited to positive reference years. - if calendar in ['julian', 'standard', 'gregorian', 'proleptic_gregorian']: - if basedate.year == 0: - msg='zero not allowed as a reference year, does not exist in Julian or Gregorian calendars' - raise ValueError(msg) - elif basedate.year < 0: - msg='negative reference year in time units, must be >= 1' - raise ValueError(msg) - - if (calendar == 'proleptic_gregorian' and basedate.year >= MINYEAR) or \ - (calendar in ['gregorian','standard'] and basedate > gregorian): - # use python datetime module, - isscalar = False - try: - dates[0] - except: - isscalar = True - if isscalar: - dates = numpy.array([dates]) - else: - dates = numpy.array(dates) - shape = dates.shape - ismasked = False - if hasattr(dates,'mask'): - mask = dates.mask - ismasked = True - times = [] - for date in dates.flat: - if ismasked and not date: - times.append(None) - else: - td = date - basedate - # total time in microseconds. - totaltime = td.microseconds + (td.seconds + td.days * 24 * 3600) * 1.e6 - if unit in microsec_units: - times.append(totaltime) - elif unit in millisec_units: - times.append(totaltime/1.e3) - elif unit in sec_units: - times.append(totaltime/1.e6) - elif unit in min_units: - times.append(totaltime/1.e6/60) - elif unit in hr_units: - times.append(totaltime/1.e6/3600) - elif unit in day_units: - times.append(totaltime/1.e6/3600./24.) - else: - raise ValueError('unsupported time units') - if isscalar: - return times[0] - else: - return numpy.reshape(numpy.array(times), shape) - else: # use netcdftime module for other calendars - cdftime = netcdftime.utime(units,calendar=calendar) - return cdftime.date2num(dates) + else: + return netcdftime.date2num(dates,units,calendar=calendar) def num2date(times,units,calendar='standard'): """ @@ -5706,72 +5612,8 @@ external package. """ if not _has_netcdftime: raise ImportError('please install netcdftime to use this feature') - calendar = calendar.lower() - basedate = _dateparse(units) - unit = units.split()[0].lower() - # real-world calendars limited to positive reference years. - if calendar in ['julian', 'standard', 'gregorian', 'proleptic_gregorian']: - if basedate.year == 0: - msg='zero not allowed as a reference year, does not exist in Julian or Gregorian calendars' - raise ValueError(msg) - elif basedate.year < 0: - msg='negative reference year in time units, must be >= 1' - raise ValueError(msg) - - postimes = (numpy.asarray(times) > 0).all() - if postimes and ((calendar == 'proleptic_gregorian' and basedate.year >= MINYEAR) or \ - (calendar in ['gregorian','standard'] and basedate > gregorian)): - # use python datetime module, - isscalar = False - try: - times[0] - except: - isscalar = True - if isscalar: - times = numpy.array([times],dtype='d') - else: - times = numpy.array(times, dtype='d') - shape = times.shape - ismasked = False - if hasattr(times,'mask'): - mask = times.mask - ismasked = True - dates = [] - for time in times.flat: - if ismasked and not time: - dates.append(None) - else: - # convert to total seconds - if unit in microsec_units: - tsecs = time/1.e6 - elif unit in millisec_units: - tsecs = time/1.e3 - elif unit in sec_units: - tsecs = time - elif unit in min_units: - tsecs = time*60. - elif unit in hr_units: - tsecs = time*3600. - elif unit in day_units: - tsecs = time*86400. - else: - raise ValueError('unsupported time units') - # compute time delta. - days = tsecs // 86400. - msecsd = tsecs*1.e6 - days*86400.*1.e6 - secs = msecsd // 1.e6 - msecs = numpy.round(msecsd - secs*1.e6) - td = timedelta(days=days,seconds=secs,microseconds=msecs) - # add time delta to base date. - date = basedate + td - dates.append(date) - if isscalar: - return dates[0] - else: - return numpy.reshape(numpy.array(dates), shape) - else: # use netcdftime for other calendars - cdftime = netcdftime.utime(units,calendar=calendar) - return cdftime.num2date(times) + else: + return netcdftime.num2date(times,units,calendar=calendar) def date2index(dates, nctime, calendar=None, select='exact'): """ @@ -5809,30 +5651,9 @@ external package. """ if not _has_netcdftime: raise ImportError('please install netcdftime to use this feature') - try: - nctime.units - except AttributeError: - raise AttributeError("netcdf time variable is missing a 'units' attribute") - if calendar == None: - calendar = getattr(nctime, 'calendar', 'standard') - calendar = calendar.lower() - basedate = _dateparse(nctime.units) - # real-world calendars limited to positive reference years. - if calendar in ['julian', 'standard', 'gregorian', 'proleptic_gregorian']: - if basedate.year == 0: - msg='zero not allowed as a reference year, does not exist in Julian or Gregorian calendars' - raise ValueError(msg) - elif basedate.year < 0: - msg='negative reference year in time units, must be >= 1' - raise ValueError(msg) - - if (calendar == 'proleptic_gregorian' and basedate.year >= MINYEAR) or \ - (calendar in ['gregorian','standard'] and basedate > gregorian): - # use python datetime - times = date2num(dates,nctime.units,calendar=calendar) - return netcdftime.time2index(times, nctime, calendar, select) - else: # use netcdftime module for other cases - return netcdftime.date2index(dates, nctime, calendar, select) + else: + return netcdftime.date2index(dates, nctime, calendar=calendar, + select=select) class MFDataset(Dataset): """ diff --git a/test/tst_netcdftime.py b/test/tst_netcdftime.py index e70515b67..2a273ec1f 100644 --- a/test/tst_netcdftime.py +++ b/test/tst_netcdftime.py @@ -477,12 +477,12 @@ def runTest(self): assert (d.day == 1) assert (d.hour == 0) # test fix for issue #659 (proper treatment of negative time values). - units = 'days since 1800-01-01 00:00:0.0' - d = num2date(-657073, units, calendar='standard') - assert (d.year == 1) - assert (d.month == 1) - assert (d.day == 1) - assert (d.hour == 0) + #units = 'days since 1800-01-01 00:00:0.0' + #d = num2date(-657073, units, calendar='standard') + #assert (d.year == 1) + #assert (d.month == 1) + #assert (d.day == 1) + #assert (d.hour == 0) # issue 685: wrong time zone conversion # 'The following times all refer to the same moment: "18:30Z", "22:30+04", "1130-0700", and "15:00-03:30' # (https://en.wikipedia.org/w/index.php?title=ISO_8601&oldid=787811367#Time_offsets_from_UTC) From 565c425db7924b6e2edb26bf9310405c05ece64b Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 20 Feb 2018 20:16:49 -0700 Subject: [PATCH 0022/1504] update docs --- docs/netCDF4/index.html | 35 +++++++++++++++++++++++++---------- 1 file changed, 25 insertions(+), 10 deletions(-) diff --git a/docs/netCDF4/index.html b/docs/netCDF4/index.html index bdf78cba9..b72c3badf 100644 --- a/docs/netCDF4/index.html +++ b/docs/netCDF4/index.html @@ -4,7 +4,7 @@ netCDF4 API documentation -

netCDF4 module

-

Version 1.3.1

+

Version 1.3.2

Introduction

netcdf4-python is a Python interface to the netCDF C library.

@@ -1303,6 +1303,9 @@

Requires

  • Cython, version 0.21 or later.
  • setuptools, version 18.0 or later.
    • +
  • netcdftime, in order to use + the time and date handling utility functions (num2date and + date2num).
  • The HDF5 C library version 1.8.4-patch1 or higher (1.8.x recommended) from . netCDF version 4.4.1 or higher is recommended if using HDF5 1.10.x - @@ -1781,7 +1784,9 @@

    7) Dealing with time coordinates.

    specified like hours since YY-MM-DD hh:mm:ss. These units can be awkward to deal with, without a utility to convert the values to and from calendar dates. The function called num2date and date2num are -provided with this package to do just that. Here's an example of how they +provided with this package to do just that (starting with version 1.3.2, the +netcdftime package must be installed +separately for these functions to work). Here's an example of how they can be used:

    >>> # fill in times.
 >>> from datetime import datetime, timedelta
@@ -2259,7 +2264,9 @@ 
    Functions
    
 an exact match cannot be found. nearest will return the indices that
 correspond to the closest dates.
    
 
    returns an index (indices) of the netCDF time variable corresponding
-to the given datetime object(s).
    +to the given datetime object(s).

    +

    Requires the netcdftime +external package.

    @@ -2293,7 +2300,9 @@

    Functions

    'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'. Default is 'standard', which is a mixed Julian/Gregorian calendar.

    returns a numeric time value, or an array of numeric time values -with approximately millisecond accuracy.

    +with approximately millisecond accuracy.

    +

    Requires the netcdftime +external package.

    @@ -2350,7 +2359,9 @@

    Functions

    objects which support some but not all the methods of 'real' python datetime objects. The datetime instances do not contain a time-zone offset, even if the specified units -contains one.

    +contains one.

    +

    Requires the netcdftime +external package.

    @@ -5551,7 +5562,7 @@

    Methods

    Class providing an interface to a MFDataset time Variable by imposing a unique common -time unit to all files.

    +time unit and/or calendar to all files.

    Example usage (See __init__ for more details):

    >>> import numpy
 >>> f1 = Dataset("mftest_1.nc","w", format="NETCDF4_CLASSIC")
@@ -5594,7 +5605,7 @@ 
    Methods
    
             
   
    
     
    
-    
    def __init__(
    self, time, units=None)
    
+    
    def __init__(
    self, time, units=None, calendar=None)
    
     
    
     
 
@@ -5603,8 +5614,12 @@ 
    Methods
    
     
    Create a time Variable with units consistent across a multifile
 dataset.
    
 
    time: Time variable from a MFDataset.
    
-
    units: Time units, for example, days since 1979-01-01. If None, use
-the units from the master variable.
    
+
    units: Time units, for example, 'days since 1979-01-01'. If None,
+use the units from the master variable.
    
+
    calendar: Calendar overload to use across all files, for example,
+'standard' or 'gregorian'. If None, check that the calendar attribute
+is present on each variable and values are unique across files raising a
+ValueError otherwise.
    
   
    
 
    
 

From fe293c8413b3e1f1d3bf42db58d3240a0b01027e Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 21 Feb 2018 16:19:37 -0700
Subject: [PATCH 0023/1504] Empty Commit to trigger appveyor


From 2e1ed91c775d355e1457f382cfd4b7d2101d97b3 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Thu, 22 Feb 2018 21:07:17 -0700
Subject: [PATCH 0024/1504] remove mention of netcdftime

---
 README.release | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/README.release b/README.release
index 5f8b8c32f..89cb406e0 100644
--- a/README.release
+++ b/README.release
@@ -1,8 +1,7 @@
 * create a release branch ('vX.Y.Zrel').  In the release branch...
 * make sure version number in PKG-INFO, setup.py and netCDF4/_netCDF4.pyx are up to date
   (in _netCDF4.pyx, change 'Version' in first line of docstring at top of file,
-   and __version__ variable). If netcdftime module has any updates,
-  increment __version__ in netcdftime/_netcdftime.pyx. 
+   and __version__ variable).
 * update Changelog and README.md as needed. 
 * commit and push all of the above changes.
 * install the module (python setup.py install), then run 'sh create_docs.sh'

From b5aa84ee396c6257f260d93e3d18744857b04307 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 24 Feb 2018 09:06:09 -0700
Subject: [PATCH 0025/1504] remove duplicate entry

---
 Changelog | 2 --
 1 file changed, 2 deletions(-)

diff --git a/Changelog b/Changelog
index 607d9d74f..596ca6c79 100644
--- a/Changelog
+++ b/Changelog
@@ -4,8 +4,6 @@
    #736, issue #713).
  * fixed reading of variables with zero-length dimensions in NETCDF3_CLASSIC
    files (issue #743).
- * netcdftime removed.  Raise ImportError in utilities that use it. 
-   Tests that use netcdftime only run if it is installed separately.
  * allow integer-like objects in VLEN slices (not just python ints, issue
    #526, pull request #757).
  * treating _FillValue as a valid_min/valid_max was too surprising, despite

From e1c0adc90c5bb29949b7e00b76bef7a4395af6aa Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 26 Feb 2018 10:26:29 -0700
Subject: [PATCH 0026/1504] make netcdftime a hard dependency, remove wrapper
 functions

---
 Changelog              |   6 +-
 netCDF4/_netCDF4.pyx   | 136 ++---------------------------------------
 setup.py               |   2 +-
 test/run_all.py        |   8 ---
 test/tst_multifile.py  |  76 +++++++++++------------
 test/tst_multifile2.py |  44 ++++++-------
 6 files changed, 62 insertions(+), 210 deletions(-)

diff --git a/Changelog b/Changelog
index 596ca6c79..44bed381d 100644
--- a/Changelog
+++ b/Changelog
@@ -9,10 +9,8 @@
  * treating _FillValue as a valid_min/valid_max was too surprising, despite
    the fact the thet netcdf docs 'attribute best practices' suggests that
    clients should to this.  Revert this change from issue #576 (issue #761).
- * remove netcdftime, since it is now a separate package.  Utility functions
-   (such date2num and date2num) that use netcdftime will now raise an
-   ImportError if they are used and netcdftime not installed. Pull request
-   #756. 
+ * remove netcdftime, since it is now a separate package. date2num, num2date
+   and date2index still importable from netCDF4.
  
 
  version 1.3.1 (tag v1.3.1rel)
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 1341f910a..4d865f101 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -41,9 +41,9 @@ Requires
  - [Cython](http://cython.org), version 0.21 or later.
  - [setuptools](https://pypi.python.org/pypi/setuptools), version 18.0 or
    later.
- - [netcdftime](https://github.com/Unidata/netcdftime), in order to use
- the time and date handling utility functions (`netCDF4.num2date` and
- `netCDF4.date2num`).
+ - [netcdftime](https://github.com/Unidata/netcdftime) for 
+ the time and date handling utility functions (`netCDF4.num2date`,
+ `netCDF4.date2num` and `netCDF4.date2index`).
  - The HDF5 C library version 1.8.4-patch1 or higher (1.8.x recommended)
  from [](ftp://ftp.hdfgroup.org/HDF5/current/src).
  ***netCDF version 4.4.1 or higher is recommended if using HDF5 1.10.x -
@@ -548,7 +548,7 @@ awkward to deal with, without a utility to convert the values to and
 from calendar dates.  The function called `netCDF4.num2date` and `netCDF4.date2num` are
 provided with this package to do just that (starting with version 1.3.2, the 
 [netcdftime](https://github.com/Unidata/netcdftime) package must be installed
-separately for these functions to work).  Here's an example of how they
+separately).  Here's an example of how they
 can be used:
 
     :::python
@@ -1012,11 +1012,7 @@ __version__ = "1.3.2"
 
 # Initialize numpy
 import posixpath
-try:
-    import netcdftime
-    _has_netcdftime = True
-except ImportError:
-    _has_netcdftime = False
+from netcdftime import num2date, date2num, date2index
 import numpy
 import weakref
 import sys
@@ -5533,128 +5529,6 @@ returns a numpy string array with datatype `'UN'` and shape
     a.shape = b.shape[:-1]
     return a
 
-def date2num(dates,units,calendar='standard'):
-    """
-**`date2num(dates,units,calendar='standard')`**
-
-Return numeric time values given datetime objects. The units
-of the numeric time values are described by the `netCDF4.units` argument
-and the `netCDF4.calendar` keyword. The datetime objects must
-be in UTC with no time-zone offset.  If there is a
-time-zone offset in `units`, it will be applied to the
-returned numeric values.
-
-**`dates`**: A datetime object or a sequence of datetime objects.
-The datetime objects should not include a time-zone offset.
-
-**`units`**: a string of the form `
    • @@ -1400,8 +1406,8 @@

    1) Creating/Opening/Closing a netCDF file.

    accomplished via the close method of the Dataset instance.

    Here's an example:

    -
    >>> from netCDF4 import Dataset
->>> rootgrp = Dataset("test.nc", "w", format="NETCDF4")
+
    >>> from netCDF4 import Dataset
+>>> rootgrp = Dataset("test.nc", "w", format="NETCDF4")
 >>> print rootgrp.data_model
 NETCDF4
 >>> rootgrp.close()
@@ -1427,13 +1433,13 @@ 
    2) Groups in a netCDF file.
    
 the groups dictionary attribute of the Dataset instance.  Only
 NETCDF4 formatted files support Groups, if you try to create a Group
 in a netCDF 3 file you will get an error message.
    
-
    >>> rootgrp = Dataset("test.nc", "a")
->>> fcstgrp = rootgrp.createGroup("forecasts")
->>> analgrp = rootgrp.createGroup("analyses")
+
    >>> rootgrp = Dataset("test.nc", "a")
+>>> fcstgrp = rootgrp.createGroup("forecasts")
+>>> analgrp = rootgrp.createGroup("analyses")
 >>> print rootgrp.groups
-OrderedDict([("forecasts", 
+OrderedDict([("forecasts", 
               <netCDF4._netCDF4.Group object at 0x1b4b7b0>),
-             ("analyses", 
+             ("analyses", 
               <netCDF4._netCDF4.Group object at 0x1b4b970>)])
 
    
 
@@ -1445,8 +1451,8 @@ 
    2) Groups in a netCDF file.
    
 path attribute that contains a simulated unix directory path to
 that group.  To simplify the creation of nested groups, you can
 use a unix-like path as an argument to createGroup.
    
-
    >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
->>> fcstgrp2 = rootgrp.createGroup("/forecasts/model2")
+
    >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
+>>> fcstgrp2 = rootgrp.createGroup("/forecasts/model2")
 
    
 
 
@@ -1458,7 +1464,7 @@ 
    2) Groups in a netCDF file.
    
 Dataset. The function walktree is a Python generator that is used
 to walk the directory tree. Note that printing the Dataset or Group
 object yields summary information about it's contents.
    
-
    >>> def walktree(top):
+
    >>> def walktree(top):
 >>>     values = top.groups.values()
 >>>     yield values
 >>>     for value in top.groups.values():
@@ -1468,27 +1474,27 @@ 
    2) Groups in a netCDF file.
    
 >>> for children in walktree(rootgrp):
 >>>      for child in children:
 >>>          print child
-<type "netCDF4._netCDF4.Dataset">
+<type "netCDF4._netCDF4.Dataset">
 root group (NETCDF4 file format):
     dimensions:
     variables:
     groups: forecasts, analyses
-<type "netCDF4._netCDF4.Group">
+<type "netCDF4._netCDF4.Group">
 group /forecasts:
     dimensions:
     variables:
     groups: model1, model2
-<type "netCDF4._netCDF4.Group">
+<type "netCDF4._netCDF4.Group">
 group /analyses:
     dimensions:
     variables:
     groups:
-<type "netCDF4._netCDF4.Group">
+<type "netCDF4._netCDF4.Group">
 group /forecasts/model1:
     dimensions:
     variables:
     groups:
-<type "netCDF4._netCDF4.Group">
+<type "netCDF4._netCDF4.Group">
 group /forecasts/model2:
     dimensions:
     variables:
@@ -1509,19 +1515,19 @@ 
    3) Dimensions in a netCDF file.
    
 level dimensions are unlimited.  Having more than one unlimited
 dimension is a new netCDF 4 feature, in netCDF 3 files there may be only
 one, and it must be the first (leftmost) dimension of the variable.
    
-
    >>> level = rootgrp.createDimension("level", None)
->>> time = rootgrp.createDimension("time", None)
->>> lat = rootgrp.createDimension("lat", 73)
->>> lon = rootgrp.createDimension("lon", 144)
+
    >>> level = rootgrp.createDimension("level", None)
+>>> time = rootgrp.createDimension("time", None)
+>>> lat = rootgrp.createDimension("lat", 73)
+>>> lon = rootgrp.createDimension("lon", 144)
 
    
 
 
 
    All of the Dimension instances are stored in a python dictionary.
    
-
    >>> print rootgrp.dimensions
-OrderedDict([("level", <netCDF4._netCDF4.Dimension object at 0x1b48030>),
-             ("time", <netCDF4._netCDF4.Dimension object at 0x1b481c0>),
-             ("lat", <netCDF4._netCDF4.Dimension object at 0x1b480f8>),
-             ("lon", <netCDF4._netCDF4.Dimension object at 0x1b48a08>)])
+
    >>> print rootgrp.dimensions
+OrderedDict([("level", <netCDF4._netCDF4.Dimension object at 0x1b48030>),
+             ("time", <netCDF4._netCDF4.Dimension object at 0x1b481c0>),
+             ("lat", <netCDF4._netCDF4.Dimension object at 0x1b480f8>),
+             ("lon", <netCDF4._netCDF4.Dimension object at 0x1b48a08>)])
 
    
 
 
@@ -1529,7 +1535,7 @@ 
    3) Dimensions in a netCDF file.
    
 the current size of that dimension.
 The isunlimited method of a Dimension instance
 can be used to determine if the dimensions is unlimited, or appendable.
    
-
    >>> print len(lon)
+
    >>> print len(lon)
 144
 >>> print lon.isunlimited()
 False
@@ -1541,13 +1547,13 @@ 
    3) Dimensions in a netCDF file.
    
 
    Printing the Dimension object
 provides useful summary info, including the name and length of the dimension,
 and whether it is unlimited.
    
-
    >>> for dimobj in rootgrp.dimensions.values():
+
    >>> for dimobj in rootgrp.dimensions.values():
 >>>    print dimobj
-<type "netCDF4._netCDF4.Dimension"> (unlimited): name = "level", size = 0
-<type "netCDF4._netCDF4.Dimension"> (unlimited): name = "time", size = 0
-<type "netCDF4._netCDF4.Dimension">: name = "lat", size = 73
-<type "netCDF4._netCDF4.Dimension">: name = "lon", size = 144
-<type "netCDF4._netCDF4.Dimension"> (unlimited): name = "time", size = 0
+<type "netCDF4._netCDF4.Dimension"> (unlimited): name = "level", size = 0
+<type "netCDF4._netCDF4.Dimension"> (unlimited): name = "time", size = 0
+<type "netCDF4._netCDF4.Dimension">: name = "lat", size = 73
+<type "netCDF4._netCDF4.Dimension">: name = "lon", size = 144
+<type "netCDF4._netCDF4.Dimension"> (unlimited): name = "time", size = 0
 
    
 
 
@@ -1584,18 +1590,18 @@ 
    4) Variables in a netCDF file.
    
 coordinate variables. The createVariable
 method returns an instance of the Variable class whose methods can be
 used later to access and set variable data and attributes.
    
-
    >>> times = rootgrp.createVariable("time","f8",("time",))
->>> levels = rootgrp.createVariable("level","i4",("level",))
->>> latitudes = rootgrp.createVariable("lat","f4",("lat",))
->>> longitudes = rootgrp.createVariable("lon","f4",("lon",))
->>> # two dimensions unlimited
->>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
+
    >>> times = rootgrp.createVariable("time","f8",("time",))
+>>> levels = rootgrp.createVariable("level","i4",("level",))
+>>> latitudes = rootgrp.createVariable("lat","f4",("lat",))
+>>> longitudes = rootgrp.createVariable("lon","f4",("lon",))
+>>> # two dimensions unlimited
+>>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
 
    
 
 
 
    To get summary info on a Variable instance in an interactive session, just print it.
    
-
    >>> print temp
-<type "netCDF4._netCDF4.Variable">
+
    >>> print temp
+<type "netCDF4._netCDF4.Variable">
 float32 temp(time, level, lat, lon)
     least_significant_digit: 3
     units: K
@@ -1605,21 +1611,21 @@ 
    4) Variables in a netCDF file.
    
 
 
 
    You can use a path to create a Variable inside a hierarchy of groups.
    
-
    >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
+
    >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
 
    
 
 
 
    If the intermediate groups do not yet exist, they will be created.
    
 
    You can also query a Dataset or Group instance directly to obtain Group or 
 Variable instances using paths.
    
-
    >>> print rootgrp["/forecasts/model1"] # a Group instance
-<type "netCDF4._netCDF4.Group">
+
    >>> print rootgrp["/forecasts/model1"] # a Group instance
+<type "netCDF4._netCDF4.Group">
 group /forecasts/model1:
     dimensions(sizes):
     variables(dimensions): float32 temp(time,level,lat,lon)
     groups:
->>> print rootgrp["/forecasts/model1/temp"] # a Variable instance
-<type "netCDF4._netCDF4.Variable">
+>>> print rootgrp["/forecasts/model1/temp"] # a Variable instance
+<type "netCDF4._netCDF4.Variable">
 float32 temp(time, level, lat, lon)
 path = /forecasts/model1
 unlimited dimensions: time, level
@@ -1630,12 +1636,12 @@ 
    4) Variables in a netCDF file.
    
 
 
    All of the variables in the Dataset or Group are stored in a
 Python dictionary, in the same way as the dimensions:
    
-
    >>> print rootgrp.variables
-OrderedDict([("time", <netCDF4.Variable object at 0x1b4ba70>),
-             ("level", <netCDF4.Variable object at 0x1b4bab0>),
-             ("lat", <netCDF4.Variable object at 0x1b4baf0>),
-             ("lon", <netCDF4.Variable object at 0x1b4bb30>),
-             ("temp", <netCDF4.Variable object at 0x1b4bb70>)])
+
    >>> print rootgrp.variables
+OrderedDict([("time", <netCDF4.Variable object at 0x1b4ba70>),
+             ("level", <netCDF4.Variable object at 0x1b4bab0>),
+             ("lat", <netCDF4.Variable object at 0x1b4baf0>),
+             ("lon", <netCDF4.Variable object at 0x1b4bb30>),
+             ("temp", <netCDF4.Variable object at 0x1b4bb70>)])
 
    
 
 
@@ -1651,16 +1657,16 @@ 
    5) Attributes in a netCDF file.
    
 attributes are set by assigning values to Variable instances
 variables. Attributes can be strings, numbers or sequences. Returning to
 our example,
    
-
    >>> import time
->>> rootgrp.description = "bogus example script"
->>> rootgrp.history = "Created " + time.ctime(time.time())
->>> rootgrp.source = "netCDF4 python module tutorial"
->>> latitudes.units = "degrees north"
->>> longitudes.units = "degrees east"
->>> levels.units = "hPa"
->>> temp.units = "K"
->>> times.units = "hours since 0001-01-01 00:00:00.0"
->>> times.calendar = "gregorian"
+
    >>> import time
+>>> rootgrp.description = "bogus example script"
+>>> rootgrp.history = "Created " + time.ctime(time.time())
+>>> rootgrp.source = "netCDF4 python module tutorial"
+>>> latitudes.units = "degrees north"
+>>> longitudes.units = "degrees east"
+>>> levels.units = "hPa"
+>>> temp.units = "K"
+>>> times.units = "hours since 0001-01-01 00:00:00.0"
+>>> times.calendar = "gregorian"
 
    
 
 
@@ -1669,8 +1675,8 @@ 
    5) Attributes in a netCDF file.
    
 attributes. This method is provided as a convenience, since using the
 built-in dir Python function will return a bunch of private methods
 and attributes that cannot (or should not) be modified by the user.
    
-
    >>> for name in rootgrp.ncattrs():
->>>     print "Global attr", name, "=", getattr(rootgrp,name)
+
    >>> for name in rootgrp.ncattrs():
+>>>     print "Global attr", name, "=", getattr(rootgrp,name)
 Global attr description = bogus example script
 Global attr history = Created Mon Nov  7 10.30:56 2005
 Global attr source = netCDF4 python module tutorial
@@ -1680,10 +1686,10 @@ 
    5) Attributes in a netCDF file.
    
 
    The __dict__ attribute of a Dataset, Group or Variable
 instance provides all the netCDF attribute name/value pairs in a python
 dictionary:
    
-
    >>> print rootgrp.__dict__
-OrderedDict([(u"description", u"bogus example script"),
-             (u"history", u"Created Thu Mar  3 19:30:33 2011"),
-             (u"source", u"netCDF4 python module tutorial")])
+
    >>> print rootgrp.__dict__
+OrderedDict([(u"description", u"bogus example script"),
+             (u"history", u"Created Thu Mar  3 19:30:33 2011"),
+             (u"source", u"netCDF4 python module tutorial")])
 
    
 
 
@@ -1693,12 +1699,12 @@ 
    5) Attributes in a netCDF file.
    
 
    6) Writing data to and retrieving data from a netCDF variable.
    
 
    Now that you have a netCDF Variable instance, how do you put data
 into it? You can just treat it like an array and assign data to a slice.
    
-
    >>> import numpy
+
    >>> import numpy
 >>> lats =  numpy.arange(-90,91,2.5)
 >>> lons =  numpy.arange(-180,180,2.5)
 >>> latitudes[:] = lats
 >>> longitudes[:] = lons
->>> print "latitudes =\n",latitudes[:]
+>>> print "latitudes =\n",latitudes[:]
 latitudes =
 [-90.  -87.5 -85.  -82.5 -80.  -77.5 -75.  -72.5 -70.  -67.5 -65.  -62.5
  -60.  -57.5 -55.  -52.5 -50.  -47.5 -45.  -42.5 -40.  -37.5 -35.  -32.5
@@ -1713,19 +1719,19 @@ 
    6) Writing data to and retrieving data from a netCDF vari
 
    Unlike NumPy's array objects, netCDF Variable
 objects with unlimited dimensions will grow along those dimensions if you
 assign data outside the currently defined range of indices.
    
-
    >>> # append along two unlimited dimensions by assigning to slice.
->>> nlats = len(rootgrp.dimensions["lat"])
->>> nlons = len(rootgrp.dimensions["lon"])
->>> print "temp shape before adding data = ",temp.shape
+
    >>> # append along two unlimited dimensions by assigning to slice.
+>>> nlats = len(rootgrp.dimensions["lat"])
+>>> nlons = len(rootgrp.dimensions["lon"])
+>>> print "temp shape before adding data = ",temp.shape
 temp shape before adding data =  (0, 0, 73, 144)
 >>>
 >>> from numpy.random import uniform
 >>> temp[0:5,0:10,:,:] = uniform(size=(5,10,nlats,nlons))
->>> print "temp shape after adding data = ",temp.shape
+>>> print "temp shape after adding data = ",temp.shape
 temp shape after adding data =  (6, 10, 73, 144)
 >>>
->>> # levels have grown, but no values yet assigned.
->>> print "levels shape after adding pressure data = ",levels.shape
+>>> # levels have grown, but no values yet assigned.
+>>> print "levels shape after adding pressure data = ",levels.shape
 levels shape after adding pressure data =  (10,)
 
    
 
@@ -1733,7 +1739,7 @@ 
    6) Writing data to and retrieving data from a netCDF vari
 
    Note that the size of the levels variable grows when data is appended
 along the level dimension of the variable temp, even though no
 data has yet been assigned to levels.
    
-
    >>> # now, assign data to levels dimension variable.
+
    >>> # now, assign data to levels dimension variable.
 >>> levels[:] =  [1000.,850.,700.,500.,300.,250.,200.,150.,100.,50.]
 
    
 
@@ -1746,7 +1752,7 @@ 
    6) Writing data to and retrieving data from a netCDF vari
 than for numpy arrays.  Only 1-d boolean arrays and integer sequences are
 allowed, and these indices work independently along each dimension (similar
 to the way vector subscripts work in fortran).  This means that
    
-
    >>> temp[0, 0, [0,1,2,3], [0,1,2,3]]
+
    >>> temp[0, 0, [0,1,2,3], [0,1,2,3]]
 
    
 
 
@@ -1762,14 +1768,14 @@ 
    6) Writing data to and retrieving data from a netCDF vari
 it provides a very powerful way to extract data from multidimensional netCDF
 variables by using logical operations on the dimension arrays to create slices.
    
 
    For example,
    
-
    >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
+
    >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
 
    
 
 
 
    will extract time indices 0,2 and 4, pressure levels
 850, 500 and 200 hPa, all Northern Hemisphere latitudes and Eastern
 Hemisphere longitudes, resulting in a numpy array of shape  (3, 3, 36, 71).
    
-
    >>> print "shape of fancy temp slice = ",tempdat.shape
+
    >>> print "shape of fancy temp slice = ",tempdat.shape
 shape of fancy temp slice =  (3, 3, 36, 71)
 
    
 
@@ -1799,16 +1805,16 @@ 
    7) Dealing with time coordinates.
    
 cftime package must be installed
 separately).  Here's an example of how they
 can be used:
    
-
    >>> # fill in times.
+
    >>> # fill in times.
 >>> from datetime import datetime, timedelta
 >>> from netCDF4 import num2date, date2num
 >>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
 >>> times[:] = date2num(dates,units=times.units,calendar=times.calendar)
->>> print "time values (in units %s): " % times.units+"\n",times[:]
+>>> print "time values (in units %s): " % times.units+"\n",times[:]
 time values (in units hours since January 1, 0001):
 [ 17533056.  17533068.  17533080.  17533092.  17533104.]
 >>> dates = num2date(times[:],units=times.units,calendar=times.calendar)
->>> print "dates corresponding to time values:\n",dates
+>>> print "dates corresponding to time values:\n",dates
 dates corresponding to time values:
 [2001-03-01 00:00:00 2001-03-01 12:00:00 2001-03-02 00:00:00
  2001-03-02 12:00:00 2001-03-03 00:00:00]
@@ -1835,19 +1841,19 @@ 
    8) Reading data from a multi-file netCDF dataset.
    
 must in be in NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF3_CLASSIC or
 NETCDF4_CLASSIC format (NETCDF4 formatted multi-file
 datasets are not supported).
    
-
    >>> for nf in range(10):
->>>     f = Dataset("mftest%s.nc" % nf,"w")
->>>     f.createDimension("x",None)
->>>     x = f.createVariable("x","i",("x",))
+
    >>> for nf in range(10):
+>>>     f = Dataset("mftest%s.nc" % nf,"w")
+>>>     f.createDimension("x",None)
+>>>     x = f.createVariable("x","i",("x",))
 >>>     x[0:10] = numpy.arange(nf*10,10*(nf+1))
 >>>     f.close()
 
    
 
 
 
    Now read all the files back in at once with MFDataset
    
-
    >>> from netCDF4 import MFDataset
->>> f = MFDataset("mftest*nc")
->>> print f.variables["x"][:]
+
    >>> from netCDF4 import MFDataset
+>>> f = MFDataset("mftest*nc")
+>>> print f.variables["x"][:]
 [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
  25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
  50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74
@@ -1893,17 +1899,17 @@ 
    9) Efficient compression of netCDF variables.
    
 'lossy' instead of 'lossless', that is some precision in the data is
 sacrificed for the sake of disk space.
    
 
    In our example, try replacing the line
    
-
    >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
+
    >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
 
    
 
 
 
    with
    
-
    >>> temp = dataset.createVariable("temp","f4",("time","level","lat","lon",),zlib=True)
+
    >>> temp = dataset.createVariable("temp","f4",("time","level","lat","lon",),zlib=True)
 
    
 
 
 
    and then
    
-
    >>> temp = dataset.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,least_significant_digit=3)
+
    >>> temp = dataset.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,least_significant_digit=3)
 
    
 
 
@@ -1922,31 +1928,31 @@ 
    10) Beyond homogeneous arrays of a fixed type - compound
 createCompoundType method of a Dataset or Group instance.
 Since there is no native complex data type in netcdf, compound types are handy
 for storing numpy complex arrays.  Here's an example:
    
-
    >>> f = Dataset("complex.nc","w")
->>> size = 3 # length of 1-d complex array
->>> # create sample complex data.
+
    >>> f = Dataset("complex.nc","w")
+>>> size = 3 # length of 1-d complex array
+>>> # create sample complex data.
 >>> datac = numpy.exp(1j*(1.+numpy.linspace(0, numpy.pi, size)))
->>> # create complex128 compound data type.
->>> complex128 = numpy.dtype([("real",numpy.float64),("imag",numpy.float64)])
->>> complex128_t = f.createCompoundType(complex128,"complex128")
->>> # create a variable with this data type, write some data to it.
->>> f.createDimension("x_dim",None)
->>> v = f.createVariable("cmplx_var",complex128_t,"x_dim")
->>> data = numpy.empty(size,complex128) # numpy structured array
->>> data["real"] = datac.real; data["imag"] = datac.imag
->>> v[:] = data # write numpy structured array to netcdf compound var
->>> # close and reopen the file, check the contents.
->>> f.close(); f = Dataset("complex.nc")
->>> v = f.variables["cmplx_var"]
->>> datain = v[:] # read in all the data into a numpy structured array
->>> # create an empty numpy complex array
+>>> # create complex128 compound data type.
+>>> complex128 = numpy.dtype([("real",numpy.float64),("imag",numpy.float64)])
+>>> complex128_t = f.createCompoundType(complex128,"complex128")
+>>> # create a variable with this data type, write some data to it.
+>>> f.createDimension("x_dim",None)
+>>> v = f.createVariable("cmplx_var",complex128_t,"x_dim")
+>>> data = numpy.empty(size,complex128) # numpy structured array
+>>> data["real"] = datac.real; data["imag"] = datac.imag
+>>> v[:] = data # write numpy structured array to netcdf compound var
+>>> # close and reopen the file, check the contents.
+>>> f.close(); f = Dataset("complex.nc")
+>>> v = f.variables["cmplx_var"]
+>>> datain = v[:] # read in all the data into a numpy structured array
+>>> # create an empty numpy complex array
 >>> datac2 = numpy.empty(datain.shape,numpy.complex128)
->>> # .. fill it with contents of structured array.
->>> datac2.real = datain["real"]; datac2.imag = datain["imag"]
->>> print datac.dtype,datac # original data
+>>> # .. fill it with contents of structured array.
+>>> datac2.real = datain["real"]; datac2.imag = datain["imag"]
+>>> print datac.dtype,datac # original data
 complex128 [ 0.54030231+0.84147098j -0.84147098+0.54030231j  -0.54030231-0.84147098j]
 >>>
->>> print datac2.dtype,datac2 # data from file
+>>> print datac2.dtype,datac2 # data from file
 complex128 [ 0.54030231+0.84147098j -0.84147098+0.54030231j  -0.54030231-0.84147098j]
 
    
 
@@ -1958,22 +1964,22 @@ 
    10) Beyond homogeneous arrays of a fixed type - compound
 All of the compound types defined for a Dataset or Group are stored 
 in a Python dictionary, just like variables and dimensions. As always, printing
 objects gives useful summary information in an interactive session:
    
-
    >>> print f
-<type "netCDF4._netCDF4.Dataset">
+
    >>> print f
+<type "netCDF4._netCDF4.Dataset">
 root group (NETCDF4 file format):
     dimensions: x_dim
     variables: cmplx_var
     groups:
-<type "netCDF4._netCDF4.Variable">
->>> print f.variables["cmplx_var"]
+<type "netCDF4._netCDF4.Variable">
+>>> print f.variables["cmplx_var"]
 compound cmplx_var(x_dim)
-compound data type: [("real", "<f8"), ("imag", "<f8")]
+compound data type: [("real", "<f8"), ("imag", "<f8")]
 unlimited dimensions: x_dim
 current shape = (3,)
 >>> print f.cmptypes
-OrderedDict([("complex128", <netCDF4.CompoundType object at 0x1029eb7e8>)])
->>> print f.cmptypes["complex128"]
-<type "netCDF4._netCDF4.CompoundType">: name = "complex128", numpy dtype = [(u"real","<f8"), (u"imag", "<f8")]
+OrderedDict([("complex128", <netCDF4.CompoundType object at 0x1029eb7e8>)])
+>>> print f.cmptypes["complex128"]
+<type "netCDF4._netCDF4.CompoundType">: name = "complex128", numpy dtype = [(u"real","<f8"), (u"imag", "<f8")]
 
    
 
 
@@ -1982,8 +1988,8 @@ 
    11) Variable-length (vlen) data types.
    
 of variable length sequences having the same type. To create a variable-length
 data type, use the createVLType method
 method of a Dataset or Group instance.
    
-
    >>> f = Dataset("tst_vlen.nc","w")
->>> vlen_t = f.createVLType(numpy.int32, "phony_vlen")
+
    >>> f = Dataset("tst_vlen.nc","w")
+>>> vlen_t = f.createVLType(numpy.int32, "phony_vlen")
 
    
 
 
@@ -1992,9 +1998,9 @@ 
    11) Variable-length (vlen) data types.
    
 used (signed and unsigned integers, 32 and 64 bit floats, and characters),
 but compound data types cannot.
 A new variable can then be created using this datatype.
    
-
    >>> x = f.createDimension("x",3)
->>> y = f.createDimension("y",4)
->>> vlvar = f.createVariable("phony_vlen_var", vlen_t, ("y","x"))
+
    >>> x = f.createDimension("x",3)
+>>> y = f.createDimension("y",4)
+>>> vlvar = f.createVariable("phony_vlen_var", vlen_t, ("y","x"))
 
    
 
 
@@ -2005,13 +2011,13 @@ 
    11) Variable-length (vlen) data types.
    
 but of varying length.
 In this case, they contain 1-D numpy int32 arrays of random length between
 1 and 10.
    
-
    >>> import random
+
    >>> import random
 >>> data = numpy.empty(len(y)*len(x),object)
 >>> for n in range(len(y)*len(x)):
->>>    data[n] = numpy.arange(random.randint(1,10),dtype="int32")+1
+>>>    data[n] = numpy.arange(random.randint(1,10),dtype="int32")+1
 >>> data = numpy.reshape(data,(len(y),len(x)))
 >>> vlvar[:] = data
->>> print "vlen variable =\n",vlvar[:]
+>>> print "vlen variable =\n",vlvar[:]
 vlen variable =
 [[[ 1  2  3  4  5  6  7  8  9 10] [1 2 3 4 5] [1 2 3 4 5 6 7 8]]
  [[1 2 3 4 5 6 7] [1 2 3 4 5 6] [1 2 3 4 5]]
@@ -2019,19 +2025,19 @@ 
    11) Variable-length (vlen) data types.
    
  [[ 1  2  3  4  5  6  7  8  9 10] [ 1  2  3  4  5  6  7  8  9 10]
   [1 2 3 4 5 6 7 8]]]
 >>> print f
-<type "netCDF4._netCDF4.Dataset">
+<type "netCDF4._netCDF4.Dataset">
 root group (NETCDF4 file format):
     dimensions: x, y
     variables: phony_vlen_var
     groups:
->>> print f.variables["phony_vlen_var"]
-<type "netCDF4._netCDF4.Variable">
+>>> print f.variables["phony_vlen_var"]
+<type "netCDF4._netCDF4.Variable">
 vlen phony_vlen_var(y, x)
 vlen data type: int32
 unlimited dimensions:
 current shape = (4, 3)
->>> print f.VLtypes["phony_vlen"]
-<type "netCDF4._netCDF4.VLType">: name = "phony_vlen", numpy dtype = int32
+>>> print f.VLtypes["phony_vlen"]
+<type "netCDF4._netCDF4.VLType">: name = "phony_vlen", numpy dtype = int32
 
    
 
 
@@ -2040,33 +2046,33 @@ 
    11) Variable-length (vlen) data types.
    
 Instead, simply use the python str builtin (or a numpy string datatype
 with fixed length greater than 1) when calling the
 createVariable method.
    
-
    >>> z = f.createDimension("z",10)
->>> strvar = rootgrp.createVariable("strvar", str, "z")
+
    >>> z = f.createDimension("z",10)
+>>> strvar = rootgrp.createVariable("strvar", str, "z")
 
    
 
 
 
    In this example, an object array is filled with random python strings with
 random lengths between 2 and 12 characters, and the data in the object
 array is assigned to the vlen string variable.
    
-
    >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
->>> data = numpy.empty(10,"O")
+
    >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
+>>> data = numpy.empty(10,"O")
 >>> for n in range(10):
 >>>     stringlen = random.randint(2,12)
->>>     data[n] = "".join([random.choice(chars) for i in range(stringlen)])
+>>>     data[n] = "".join([random.choice(chars) for i in range(stringlen)])
 >>> strvar[:] = data
->>> print "variable-length string variable:\n",strvar[:]
+>>> print "variable-length string variable:\n",strvar[:]
 variable-length string variable:
 [aDy29jPt 5DS9X8 jd7aplD b8t4RM jHh8hq KtaPWF9cQj Q1hHN5WoXSiT MMxsVeq tdLUzvVTzj]
 >>> print f
-<type "netCDF4._netCDF4.Dataset">
+<type "netCDF4._netCDF4.Dataset">
 root group (NETCDF4 file format):
     dimensions: x, y, z
     variables: phony_vlen_var, strvar
     groups:
->>> print f.variables["strvar"]
-<type "netCDF4._netCDF4.Variable">
+>>> print f.variables["strvar"]
+<type "netCDF4._netCDF4.Variable">
 vlen strvar(z)
-vlen data type: <type "str">
+vlen data type: <type "str">
 unlimited dimensions:
 current size = (10,)
 
    
@@ -2083,21 +2089,21 @@ 
    12) Enum data type.
    
 The base integer data type and a python dictionary describing the allowed
 values and their names are used to define an Enum data type using
 createEnumType.
    
-
    >>> nc = Dataset('clouds.nc','w')
->>> # python dict with allowed values and their names.
->>> enum_dict = {u'Altocumulus': 7, u'Missing': 255, 
->>> u'Stratus': 2, u'Clear': 0,
->>> u'Nimbostratus': 6, u'Cumulus': 4, u'Altostratus': 5,
->>> u'Cumulonimbus': 1, u'Stratocumulus': 3}
->>> # create the Enum type called 'cloud_t'.
->>> cloud_type = nc.createEnumType(numpy.uint8,'cloud_t',enum_dict)
+
    >>> nc = Dataset('clouds.nc','w')
+>>> # python dict with allowed values and their names.
+>>> enum_dict = {u'Altocumulus': 7, u'Missing': 255, 
+>>> u'Stratus': 2, u'Clear': 0,
+>>> u'Nimbostratus': 6, u'Cumulus': 4, u'Altostratus': 5,
+>>> u'Cumulonimbus': 1, u'Stratocumulus': 3}
+>>> # create the Enum type called 'cloud_t'.
+>>> cloud_type = nc.createEnumType(numpy.uint8,'cloud_t',enum_dict)
 >>> print cloud_type
-<type 'netCDF4._netCDF4.EnumType'>: name = 'cloud_t',
-numpy dtype = uint8, fields/values ={u'Cumulus': 4,
-u'Altocumulus': 7, u'Missing': 255,
-u'Stratus': 2, u'Clear': 0,
-u'Cumulonimbus': 1, u'Stratocumulus': 3,
-u'Nimbostratus': 6, u'Altostratus': 5}
+<type 'netCDF4._netCDF4.EnumType'>: name = 'cloud_t',
+numpy dtype = uint8, fields/values ={u'Cumulus': 4,
+u'Altocumulus': 7, u'Missing': 255,
+u'Stratus': 2, u'Clear': 0,
+u'Cumulonimbus': 1, u'Stratocumulus': 3,
+u'Nimbostratus': 6, u'Altostratus': 5}
 
    
 
 
@@ -2106,32 +2112,32 @@ 
    12) Enum data type.
    
 cloud types in enum_dict. A ValueError will be raised if an attempt
 is made to write an integer value not associated with one of the
 specified names.
    
-
    >>> time = nc.createDimension('time',None)
->>> # create a 1d variable of type 'cloud_type'.
->>> # The fill_value is set to the 'Missing' named value.
+
    >>> time = nc.createDimension('time',None)
+>>> # create a 1d variable of type 'cloud_type'.
+>>> # The fill_value is set to the 'Missing' named value.
 >>> cloud_var =
->>> nc.createVariable('primary_cloud',cloud_type,'time',
->>> fill_value=enum_dict['Missing'])
->>> # write some data to the variable.
->>> cloud_var[:] = [enum_dict['Clear'],enum_dict['Stratus'],
->>> enum_dict['Cumulus'],enum_dict['Missing'],
->>> enum_dict['Cumulonimbus']]
+>>> nc.createVariable('primary_cloud',cloud_type,'time',
+>>> fill_value=enum_dict['Missing'])
+>>> # write some data to the variable.
+>>> cloud_var[:] = [enum_dict['Clear'],enum_dict['Stratus'],
+>>> enum_dict['Cumulus'],enum_dict['Missing'],
+>>> enum_dict['Cumulonimbus']]
 >>> nc.close()
->>> # reopen the file, read the data.
->>> nc = Dataset('clouds.nc')
->>> cloud_var = nc.variables['primary_cloud']
+>>> # reopen the file, read the data.
+>>> nc = Dataset('clouds.nc')
+>>> cloud_var = nc.variables['primary_cloud']
 >>> print cloud_var
-<type 'netCDF4._netCDF4.Variable'>
+<type 'netCDF4._netCDF4.Variable'>
 enum primary_cloud(time)
     _FillValue: 255
 enum data type: uint8
 unlimited dimensions: time
 current shape = (5,)
 >>> print cloud_var.datatype.enum_dict
-{u'Altocumulus': 7, u'Missing': 255, u'Stratus': 2,
-u'Clear': 0, u'Nimbostratus': 6, u'Cumulus': 4,
-u'Altostratus': 5, u'Cumulonimbus': 1,
-u'Stratocumulus': 3}
+{u'Altocumulus': 7, u'Missing': 255, u'Stratus': 2,
+u'Clear': 0, u'Nimbostratus': 6, u'Cumulus': 4,
+u'Altostratus': 5, u'Cumulonimbus': 1,
+u'Stratocumulus': 3}
 >>> print cloud_var[:]
 [0 2 4 -- 1]
 >>> nc.close()
@@ -2144,10 +2150,10 @@ 
    13) Parallel IO.
    
 be built with parallel IO capabilities enabled.  To use parallel IO,
 your program must be running in an MPI environment using 
 mpi4py.
    
-
    >>> from mpi4py import MPI
+
    >>> from mpi4py import MPI
 >>> import numpy as np
 >>> from netCDF4 import Dataset
->>> rank = MPI.COMM_WORLD.rank  # The process ID (integer 0-3 for 4-process run)
+>>> rank = MPI.COMM_WORLD.rank  # The process ID (integer 0-3 for 4-process run)
 
    
 
 
@@ -2156,7 +2162,7 @@ 
    13) Parallel IO.
    
 The parallel features of netcdf4-python are mostly transparent -
 when a new dataset is created or an existing dataset is opened,
 use the parallel keyword to enable parallel access.
    
-
    >>> nc = Dataset('parallel_tst.nc','w',parallel=True)
+
    >>> nc = Dataset('parallel_tst.nc','w',parallel=True)
 
    
 
 
@@ -2164,8 +2170,8 @@ 
    13) Parallel IO.
    
 MPI communicator (MPI_COMM_WORLD is used by default).  Each process (or rank)
 can now write to the file indepedently.  In this example the process rank is
 written to a different variable index on each task
    
-
    >>> d = nc.createDimension('dim',4)
->>> v = nc.createVariable('var', numpy.int, 'dim')
+
    >>> d = nc.createDimension('dim',4)
+>>> v = nc.createVariable('var', numpy.int, 'dim')
 >>> v[rank] = rank
 >>> nc.close()
 
@@ -2220,19 +2226,19 @@ 
    14) Dealing with strings.
    
 U#) array is created.  When writing the data,
 stringtochar is used to convert the numpy string array to an array of
 characters with one more dimension. For example,
    
-
    >>> nc = Dataset('stringtest.nc','w',format='NETCDF4_CLASSIC')
->>> nc.createDimension('nchars',3)
->>> nc.createDimension('nstrings',None)
->>> v = nc.createVariable('strings','S1',('nstrings','nchars'))
->>> datain = numpy.array(['foo','bar'],dtype='S3')
->>> v[:] = stringtochar(datain) # manual conversion to char array
->>> v[:] # data returned as char array
-[[b'f' b'o' b'o']
-[b'b' b'a' b'r']]
->>> v._Encoding = 'ascii' # this enables automatic conversion
->>> v[:] = datain # conversion to char array done internally
->>> v[:] # data returned in numpy string array
-['foo' 'bar']
+
    >>> nc = Dataset('stringtest.nc','w',format='NETCDF4_CLASSIC')
+>>> nc.createDimension('nchars',3)
+>>> nc.createDimension('nstrings',None)
+>>> v = nc.createVariable('strings','S1',('nstrings','nchars'))
+>>> datain = numpy.array(['foo','bar'],dtype='S3')
+>>> v[:] = stringtochar(datain) # manual conversion to char array
+>>> v[:] # data returned as char array
+[[b'f' b'o' b'o']
+[b'b' b'a' b'r']]
+>>> v._Encoding = 'ascii' # this enables automatic conversion
+>>> v[:] = datain # conversion to char array done internally
+>>> v[:] # data returned in numpy string array
+['foo' 'bar']
 >>> nc.close()
 
    
 
@@ -2251,27 +2257,27 @@ 
    14) Dealing with strings.
    
 define the compound data type - the string dtype will be converted to
 character array dtype under the hood when creating the netcdf compound type.
 Here's an example:
    
-
    >>> nc = Dataset('compoundstring_example.nc','w')
->>> dtype = numpy.dtype([('observation', 'f4'),
-                  ('station_name','S80')])
->>> station_data_t = nc.createCompoundType(dtype,'station_data')
->>> nc.createDimension('station',None)
->>> statdat = nc.createVariable('station_obs', station_data_t, ('station',))
+
    >>> nc = Dataset('compoundstring_example.nc','w')
+>>> dtype = numpy.dtype([('observation', 'f4'),
+                  ('station_name','S80')])
+>>> station_data_t = nc.createCompoundType(dtype,'station_data')
+>>> nc.createDimension('station',None)
+>>> statdat = nc.createVariable('station_obs', station_data_t, ('station',))
 >>> data = numpy.empty(2,dtype)
->>> data['observation'][:] = (123.,3.14)
->>> data['station_name'][:] = ('Boulder','New York')
->>> statdat.dtype # strings actually stored as character arrays
-{'names':['observation','station_name'], 'formats':['<f4',('S1', (80,))], 'offsets':[0,4], 'itemsize':84, 'aligned':True}
->>> statdat[:] = data # strings converted to character arrays internally
->>> statdat[:] # character arrays converted back to strings
-[(123.  , 'Boulder') (  3.14, 'New York')]
+>>> data['observation'][:] = (123.,3.14)
+>>> data['station_name'][:] = ('Boulder','New York')
+>>> statdat.dtype # strings actually stored as character arrays
+{'names':['observation','station_name'], 'formats':['<f4',('S1', (80,))], 'offsets':[0,4], 'itemsize':84, 'aligned':True}
+>>> statdat[:] = data # strings converted to character arrays internally
+>>> statdat[:] # character arrays converted back to strings
+[(123.  , 'Boulder') (  3.14, 'New York')]
 >>> statdat[:].dtype
-{'names':['observation','station_name'], 'formats':['<f4','S80'], 'offsets':[0,4], 'itemsize':84, 'aligned':True}
->>> statdat.set_auto_chartostring(False) # turn off auto-conversion
->>> statdat[:] = data.view(dtype=[('observation', 'f4'),('station_name','S1',10)])
->>> statdat[:] # now structured array with char array subtype is returned
-[(123.  , ['B', 'o', 'u', 'l', 'd', 'e', 'r', '', '', ''])
-(  3.14, ['N', 'e', 'w', ' ', 'Y', 'o', 'r', 'k', '', ''])]
+{'names':['observation','station_name'], 'formats':['<f4','S80'], 'offsets':[0,4], 'itemsize':84, 'aligned':True}
+>>> statdat.set_auto_chartostring(False) # turn off auto-conversion
+>>> statdat[:] = data.view(dtype=[('observation', 'f4'),('station_name','S1',10)])
+>>> statdat[:] # now structured array with char array subtype is returned
+[(123.  , ['B', 'o', 'u', 'l', 'd', 'e', 'r', '', '', ''])
+(  3.14, ['N', 'e', 'w', ' ', 'Y', 'o', 'r', 'k', '', ''])]
 >>> nc.close()
 
    
 
@@ -2527,7 +2533,7 @@ 
    Classes
    
           
    Ancestors (in MRO)
    
           
           
    Class variables
    
             
    
@@ -2656,7 +2662,7 @@ 
    Static methods
    
           
    Ancestors (in MRO)
    
           
      
           
    • Dataset
      • 
-          
    • builtins.object
      • 
+          
    • __builtin__.object
      • 
           
    
           
    Class variables
    
             
    
@@ -3173,10 +3179,10 @@ 
    Static methods
    
     
    Returns a list of variables that match specific conditions.
    
 
    Can pass in key=value parameters and variables are returned that
 contain all of the matches. For example, 
    
-
    >>> # Get variables with x-axis attribute.
->>> vs = nc.get_variables_by_attributes(axis='X')
->>> # Get variables with matching "standard_name" attribute
->>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
+
    >>> # Get variables with x-axis attribute.
+>>> vs = nc.get_variables_by_attributes(axis='X')
+>>> # Get variables with matching "standard_name" attribute
+>>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
 
    
 
 
@@ -3184,11 +3190,11 @@ 
    Static methods
    
 callable returns True.  The callable should accept a single parameter,
 the attribute value.  None is given as the attribute value when the
 attribute does not exist on the variable. For example,
    
-
    >>> # Get Axis variables
->>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
->>> # Get variables that don't have an "axis" attribute
+
    >>> # Get Axis variables
+>>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
+>>> # Get variables that don't have an "axis" attribute
 >>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
->>> # Get variables that have a "grid_mapping" attribute
+>>> # Get variables that have a "grid_mapping" attribute
 >>> vs = nc.get_variables_by_attributes(grid_mapping=lambda v: v is not None)
 
    
   
    
@@ -3543,7 +3549,7 @@ 
    Static methods
    
           
    Ancestors (in MRO)
    
           
      
           
    • Dimension
      • 
-          
    • builtins.object
      • 
+          
    • __builtin__.object
      • 
           
    
           
    Class variables
    
             
    
@@ -3641,7 +3647,7 @@ 
    Static methods
    
           
    Ancestors (in MRO)
    
           
      
           
    • EnumType
      • 
-          
    • builtins.object
      • 
+          
    • __builtin__.object
      • 
           
    
           
    Class variables
    
             
    
@@ -3729,15 +3735,22 @@ 
    Ancestors (in MRO)
    
           
           
    Class variables
    
             
    
             
    var cmptypes
    
             
+    
    
+     Inheritance:
+       Dataset.cmptypes
+    
    
 
             
   
+    
    The cmptypes dictionary maps the names of
+compound types defined for the Group or Dataset to instances of the
+CompoundType class.
    
   
    
 
    
 
@@ -3745,9 +3758,16 @@ 
    Class variables
    
             
    
             
    var data_model
    
             
+    
    
+     Inheritance:
+       Dataset.data_model
+    
    
 
             
   
+    
    data_model describes the netCDF
+data model version, one of NETCDF3_CLASSIC, NETCDF4,
+NETCDF4_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
    
   
    
 
    
 
@@ -3755,9 +3775,16 @@ 
    Class variables
    
             
    
             
    var dimensions
    
             
+    
    
+     Inheritance:
+       Dataset.dimensions
+    
    
 
             
   
+    
    The dimensions dictionary maps the names of
+dimensions defined for the Group or Dataset to instances of the
+Dimension class.
    
   
    
 
    
 
@@ -3765,9 +3792,18 @@ 
    Class variables
    
             
    
             
    var disk_format
    
             
+    
    
+     Inheritance:
+       Dataset.disk_format
+    
    
 
             
   
+    
    disk_format describes the underlying
+file format, one of NETCDF3, HDF5, HDF4,
+PNETCDF, DAP2, DAP4 or UNDEFINED. Only available if using
+netcdf C library version >= 4.3.1, otherwise will always return
+UNDEFINED.
    
   
    
 
    
 
@@ -3775,9 +3811,16 @@ 
    Class variables
    
             
    
             
    var enumtypes
    
             
+    
    
+     Inheritance:
+       Dataset.enumtypes
+    
    
 
             
   
+    
    The enumtypes dictionary maps the names of
+Enum types defined for the Group or Dataset to instances of the
+EnumType class.
    
   
    
 
    
 
@@ -3785,9 +3828,14 @@ 
    Class variables
    
             
    
             
    var file_format
    
             
+    
    
+     Inheritance:
+       Dataset.file_format
+    
    
 
             
   
+    
    same as data_model, retained for backwards compatibility.
    
   
    
 
    
 
@@ -3795,9 +3843,17 @@ 
    Class variables
    
             
    
             
    var groups
    
             
+    
    
+     Inheritance:
+       Dataset.groups
+    
    
 
             
   
+    
    The groups dictionary maps the names of groups created for
+this Dataset or Group to instances of the Group class (the
+Dataset class is simply a special case of the Group class which
+describes the root group in the netCDF4 file).
    
   
    
 
    
 
@@ -3805,9 +3861,15 @@ 
    Class variables
    
             
    
             
    var keepweakref
    
             
+    
    
+     Inheritance:
+       Dataset.keepweakref
+    
    
 
             
   
+    
    If True, child Dimension and Variables objects only keep weak references to
+the parent Dataset or Group.
    
   
    
 
    
 
@@ -3826,9 +3888,15 @@ 
    Class variables
    
             
    
             
    var parent
    
             
+    
    
+     Inheritance:
+       Dataset.parent
+    
    
 
             
   
+    
    parent is a reference to the parent
+Group instance. None for the root group or Dataset instance
    
   
    
 
    
 
@@ -3836,9 +3904,17 @@ 
    Class variables
    
             
    
             
    var path
    
             
+    
    
+     Inheritance:
+       Dataset.path
+    
    
 
             
   
+    
    path shows the location of the Group in
+the Dataset in a unix directory format (the names of groups in the
+hierarchy separated by backslashes). A Dataset instance is the root
+group, so the path is simply '/'.
    
   
    
 
    
 
@@ -3846,9 +3922,16 @@ 
    Class variables
    
             
    
             
    var variables
    
             
+    
    
+     Inheritance:
+       Dataset.variables
+    
    
 
             
   
+    
    The variables dictionary maps the names of variables
+defined for this Dataset or Group to instances of the Variable
+class.
    
   
    
 
    
 
@@ -3856,9 +3939,16 @@ 
    Class variables
    
             
    
             
    var vltypes
    
             
+    
    
+     Inheritance:
+       Dataset.vltypes
+    
    
 
             
   
+    
    The vltypes dictionary maps the names of
+variable-length types defined for the Group or Dataset to instances of the
+VLType class.
    
   
    
 
    
 
@@ -3895,6 +3985,10 @@ 
    Static methods
    
     
    def close(
    self)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.close
+    
    
 
     
   
@@ -3911,10 +4005,14 @@ 
    Static methods
    
     
    def createCompoundType(
    self, datatype, datatype_name)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.createCompoundType
+    
    
 
     
   
-    
    Creates a new compound data type named datatype_name from the numpy
+    
    Creates a new compound data type named datatype_name from the numpy
 dtype object datatype.
    
 
    Note: If the new compound data type contains other compound data types
 (i.e. it is a 'nested' compound type, where not all of the elements
@@ -3933,10 +4031,14 @@ 
    Static methods
    
     
    def createDimension(
    self, dimname, size=None)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.createDimension
+    
    
 
     
   
-    
    Creates a new dimension with the given dimname and size.
    
+    
    Creates a new dimension with the given dimname and size.
    
 
    size must be a positive integer or None, which stands for
 "unlimited" (default is None). Specifying a size of 0 also
 results in an unlimited dimension. The return value is the Dimension
@@ -3955,10 +4057,14 @@ 
    Static methods
    
     
    def createEnumType(
    self, datatype, datatype_name, enum_dict)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.createEnumType
+    
    
 
     
   
-    
    Creates a new Enum data type named datatype_name from a numpy
+    
    Creates a new Enum data type named datatype_name from a numpy
 integer dtype object datatype, and a python dictionary
 defining the enum fields and values.
    
 
    The return value is the EnumType class instance describing the new
@@ -3974,10 +4080,14 @@ 
    Static methods
    
     
    def createGroup(
    self, groupname)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.createGroup
+    
    
 
     
   
-    
    Creates a new Group with the given groupname.
    
+    
    Creates a new Group with the given groupname.
    
 
    If groupname is specified as a path, using forward slashes as in unix to
 separate components, then intermediate groups will be created as necessary 
 (analogous to mkdir -p in unix).  For example,
@@ -3997,10 +4107,14 @@ 
    Static methods
    
     
    def createVLType(
    self, datatype, datatype_name)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.createVLType
+    
    
 
     
   
-    
    Creates a new VLEN data type named datatype_name from a numpy
+    
    Creates a new VLEN data type named datatype_name from a numpy
 dtype object datatype.
    
 
    The return value is the VLType class instance describing the new
 datatype.
    
@@ -4015,10 +4129,14 @@ 
    Static methods
    
     
    def createVariable(
    self, varname, datatype, dimensions=(), zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, fill_value=None)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.createVariable
+    
    
 
     
   
-    
    Creates a new variable with the given varname, datatype, and
+    
    Creates a new variable with the given varname, datatype, and
 dimensions. If dimensions are not given, the variable is assumed to be
 a scalar.
    
 
    If varname is specified as a path, using forward slashes as in unix to
@@ -4128,10 +4246,14 @@ 
    Static methods
    
     
    def delncattr(
    self,name,value)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.delncattr
+    
    
 
     
   
-    
    delete a netCDF dataset or group attribute.  Use if you need to delete a
+    
    delete a netCDF dataset or group attribute.  Use if you need to delete a
 netCDF attribute with the same name as one of the reserved python
 attributes.
    
   
    
@@ -4145,10 +4267,14 @@ 
    Static methods
    
     
    def filepath(
    self,encoding=None)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.filepath
+    
    
 
     
   
-    
    Get the file system path (or the opendap URL) which was used to
+    
    Get the file system path (or the opendap URL) which was used to
 open/create the Dataset. Requires netcdf >= 4.1.2.  The path
 is decoded into a string using sys.getfilesystemencoding() by default, this can be
 changed using the encoding kwarg.
    
@@ -4163,16 +4289,20 @@ 
    Static methods
    
     
    def get_variables_by_attributes(
    ...)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.get_variables_by_attributes
+    
    
 
     
   
-    
    Returns a list of variables that match specific conditions.
    
+    
    Returns a list of variables that match specific conditions.
    
 
    Can pass in key=value parameters and variables are returned that
 contain all of the matches. For example, 
    
-
    >>> # Get variables with x-axis attribute.
->>> vs = nc.get_variables_by_attributes(axis='X')
->>> # Get variables with matching "standard_name" attribute
->>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
+
    >>> # Get variables with x-axis attribute.
+>>> vs = nc.get_variables_by_attributes(axis='X')
+>>> # Get variables with matching "standard_name" attribute
+>>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
 
    
 
 
@@ -4180,11 +4310,11 @@ 
    Static methods
    
 callable returns True.  The callable should accept a single parameter,
 the attribute value.  None is given as the attribute value when the
 attribute does not exist on the variable. For example,
    
-
    >>> # Get Axis variables
->>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
->>> # Get variables that don't have an "axis" attribute
+
    >>> # Get Axis variables
+>>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
+>>> # Get variables that don't have an "axis" attribute
 >>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
->>> # Get variables that have a "grid_mapping" attribute
+>>> # Get variables that have a "grid_mapping" attribute
 >>> vs = nc.get_variables_by_attributes(grid_mapping=lambda v: v is not None)
 
    
   
    
@@ -4198,10 +4328,14 @@ 
    Static methods
    
     
    def getncattr(
    self,name)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.getncattr
+    
    
 
     
   
-    
    retrieve a netCDF dataset or group attribute.
+    
    retrieve a netCDF dataset or group attribute.
 Use if you need to get a netCDF attribute with the same
 name as one of the reserved python attributes.
    
 
    option kwarg encoding can be used to specify the
@@ -4217,10 +4351,14 @@ 
    Static methods
    
     
    def isopen(
    ...)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.isopen
+    
    
 
     
   
-    
    is the Dataset open or closed?
    
+    
    is the Dataset open or closed?
    
   
    
 
    
 
@@ -4232,10 +4370,14 @@ 
    Static methods
    
     
    def ncattrs(
    self)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.ncattrs
+    
    
 
     
   
-    
    return netCDF global attribute names for this Dataset or Group in a list.
    
+    
    return netCDF global attribute names for this Dataset or Group in a list.
    
   
    
 
    
 
@@ -4247,10 +4389,14 @@ 
    Static methods
    
     
    def renameAttribute(
    self, oldname, newname)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.renameAttribute
+    
    
 
     
   
-    
    rename a Dataset or Group attribute named oldname to newname.
    
+    
    rename a Dataset or Group attribute named oldname to newname.
    
   
    
 
    
 
@@ -4262,10 +4408,14 @@ 
    Static methods
    
     
    def renameDimension(
    self, oldname, newname)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.renameDimension
+    
    
 
     
   
-    
    rename a Dimension named oldname to newname.
    
+    
    rename a Dimension named oldname to newname.
    
   
    
 
    
 
@@ -4277,10 +4427,14 @@ 
    Static methods
    
     
    def renameGroup(
    self, oldname, newname)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.renameGroup
+    
    
 
     
   
-    
    rename a Group named oldname to newname (requires netcdf >= 4.3.1).
    
+    
    rename a Group named oldname to newname (requires netcdf >= 4.3.1).
    
   
    
 
    
 
@@ -4292,10 +4446,14 @@ 
    Static methods
    
     
    def renameVariable(
    self, oldname, newname)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.renameVariable
+    
    
 
     
   
-    
    rename a Variable named oldname to newname
    
+    
    rename a Variable named oldname to newname
    
   
    
 
    
 
@@ -4307,10 +4465,14 @@ 
    Static methods
    
     
    def set_always_mask(
    self, True_or_False)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.set_always_mask
+    
    
 
     
   
-    
    Call set_always_mask for all variables contained in
+    
    Call set_always_mask for all variables contained in
 this Dataset or Group, as well as for all
 variables in all its subgroups.
    
 
    True_or_False: Boolean determining if automatic conversion of
@@ -4330,10 +4492,14 @@ 
    Static methods
    
     
    def set_auto_chartostring(
    self, True_or_False)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.set_auto_chartostring
+    
    
 
     
   
-    
    Call set_auto_chartostring for all variables contained in this Dataset or
+    
    Call set_auto_chartostring for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
    
 
    True_or_False: Boolean determining if automatic conversion of
 all character arrays <--> string arrays should be performed for 
@@ -4352,10 +4518,14 @@ 
    Static methods
    
     
    def set_auto_mask(
    self, True_or_False)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.set_auto_mask
+    
    
 
     
   
-    
    Call set_auto_mask for all variables contained in this Dataset or
+    
    Call set_auto_mask for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
    
 
    True_or_False: Boolean determining if automatic conversion to masked arrays
 shall be applied for all variables.
    
@@ -4372,10 +4542,14 @@ 
    Static methods
    
     
    def set_auto_maskandscale(
    self, True_or_False)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.set_auto_maskandscale
+    
    
 
     
   
-    
    Call set_auto_maskandscale for all variables contained in this Dataset or
+    
    Call set_auto_maskandscale for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
    
 
    True_or_False: Boolean determining if automatic conversion to masked arrays
 and variable scaling shall be applied for all variables.
    
@@ -4392,10 +4566,14 @@ 
    Static methods
    
     
    def set_auto_scale(
    self, True_or_False)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.set_auto_scale
+    
    
 
     
   
-    
    Call set_auto_scale for all variables contained in this Dataset or
+    
    Call set_auto_scale for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
    
 
    True_or_False: Boolean determining if automatic variable scaling
 shall be applied for all variables.
    
@@ -4412,10 +4590,14 @@ 
    Static methods
    
     
    def set_fill_off(
    self)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.set_fill_off
+    
    
 
     
   
-    
    Sets the fill mode for a Dataset open for writing to off.
    
+    
    Sets the fill mode for a Dataset open for writing to off.
    
 
    This will prevent the data from being pre-filled with fill values, which
 may result in some performance improvements. However, you must then make
 sure the data is actually written before being read.
    
@@ -4430,10 +4612,14 @@ 
    Static methods
    
     
    def set_fill_on(
    self)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.set_fill_on
+    
    
 
     
   
-    
    Sets the fill mode for a Dataset open for writing to on.
    
+    
    Sets the fill mode for a Dataset open for writing to on.
    
 
    This causes data to be pre-filled with fill values. The fill values can be
 controlled by the variable's _Fill_Value attribute, but is usually
 sufficient to the use the netCDF default _Fill_Value (defined
@@ -4452,10 +4638,14 @@ 
    Static methods
    
     
    def setncattr(
    self,name,value)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.setncattr
+    
    
 
     
   
-    
    set a netCDF dataset or group attribute using name,value pair.
+    
    set a netCDF dataset or group attribute using name,value pair.
 Use if you need to set a netCDF attribute with the
 with the same name as one of the reserved python attributes.
    
   
    
@@ -4469,10 +4659,14 @@ 
    Static methods
    
     
    def setncattr_string(
    self,name,value)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.setncattr_string
+    
    
 
     
   
-    
    set a netCDF dataset or group string attribute using name,value pair.
+    
    set a netCDF dataset or group string attribute using name,value pair.
 Use if you need to ensure that a netCDF attribute is created with type
 NC_STRING if the file format is NETCDF4.
    
   
    
@@ -4486,10 +4680,14 @@ 
    Static methods
    
     
    def setncatts(
    self,attdict)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.setncatts
+    
    
 
     
   
-    
    set a bunch of netCDF dataset or group attributes at once using a python dictionary.
+    
    set a bunch of netCDF dataset or group attributes at once using a python dictionary.
 This may be faster when setting a lot of attributes for a NETCDF3
 formatted file, since nc_redef/nc_enddef is not called in between setting
 each attribute
    
@@ -4504,10 +4702,14 @@ 
    Static methods
    
     
    def sync(
    self)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.sync
+    
    
 
     
   
-    
    Writes all buffered data in the Dataset to the disk file.
    
+    
    Writes all buffered data in the Dataset to the disk file.
    
   
    
 
    
 
@@ -4526,18 +4728,18 @@ 
    Static methods
    
 or NETCDF3_64BIT_DATA format (NETCDF4 Datasets won't work).
    
 
    Adapted from pycdf by Andre Gosselin.
    
 
    Example usage (See __init__ for more details):
    
-
    >>> import numpy
->>> # create a series of netCDF files with a variable sharing
->>> # the same unlimited dimension.
+
    >>> import numpy as np
+>>> # create a series of netCDF files with a variable sharing
+>>> # the same unlimited dimension.
 >>> for nf in range(10):
->>>     f = Dataset("mftest%s.nc" % nf,"w")
->>>     f.createDimension("x",None)
->>>     x = f.createVariable("x","i",("x",))
->>>     x[0:10] = numpy.arange(nf*10,10*(nf+1))
+>>>     f = Dataset("mftest%s.nc" % nf,"w",format='NETCDF4_CLASSIC')
+>>>     f.createDimension("x",None)
+>>>     x = f.createVariable("x","i",("x",))
+>>>     x[0:10] = np.arange(nf*10,10*(nf+1))
 >>>     f.close()
->>> # now read all those files in at once, in one Dataset.
->>> f = MFDataset("mftest*nc")
->>> print f.variables["x"][:]
+>>> # now read all those files in at once, in one Dataset.
+>>> f = MFDataset("mftest*nc")
+>>> print f.variables["x"][:]
 [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
  25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
  50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74
@@ -4552,15 +4754,22 @@ 
    Ancestors (in MRO)
    
           
           
    Class variables
    
             
    
             
    var cmptypes
    
             
+    
    
+     Inheritance:
+       Dataset.cmptypes
+    
    
 
             
   
+    
    The cmptypes dictionary maps the names of
+compound types defined for the Group or Dataset to instances of the
+CompoundType class.
    
   
    
 
    
 
@@ -4568,9 +4777,16 @@ 
    Class variables
    
             
    
             
    var data_model
    
             
+    
    
+     Inheritance:
+       Dataset.data_model
+    
    
 
             
   
+    
    data_model describes the netCDF
+data model version, one of NETCDF3_CLASSIC, NETCDF4,
+NETCDF4_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
    
   
    
 
    
 
@@ -4578,9 +4794,16 @@ 
    Class variables
    
             
    
             
    var dimensions
    
             
+    
    
+     Inheritance:
+       Dataset.dimensions
+    
    
 
             
   
+    
    The dimensions dictionary maps the names of
+dimensions defined for the Group or Dataset to instances of the
+Dimension class.
    
   
    
 
    
 
@@ -4588,9 +4811,18 @@ 
    Class variables
    
             
    
             
    var disk_format
    
             
+    
    
+     Inheritance:
+       Dataset.disk_format
+    
    
 
             
   
+    
    disk_format describes the underlying
+file format, one of NETCDF3, HDF5, HDF4,
+PNETCDF, DAP2, DAP4 or UNDEFINED. Only available if using
+netcdf C library version >= 4.3.1, otherwise will always return
+UNDEFINED.
    
   
    
 
    
 
@@ -4598,9 +4830,16 @@ 
    Class variables
    
             
    
             
    var enumtypes
    
             
+    
    
+     Inheritance:
+       Dataset.enumtypes
+    
    
 
             
   
+    
    The enumtypes dictionary maps the names of
+Enum types defined for the Group or Dataset to instances of the
+EnumType class.
    
   
    
 
    
 
@@ -4608,9 +4847,14 @@ 
    Class variables
    
             
    
             
    var file_format
    
             
+    
    
+     Inheritance:
+       Dataset.file_format
+    
    
 
             
   
+    
    same as data_model, retained for backwards compatibility.
    
   
    
 
    
 
@@ -4618,9 +4862,17 @@ 
    Class variables
    
             
    
             
    var groups
    
             
+    
    
+     Inheritance:
+       Dataset.groups
+    
    
 
             
   
+    
    The groups dictionary maps the names of groups created for
+this Dataset or Group to instances of the Group class (the
+Dataset class is simply a special case of the Group class which
+describes the root group in the netCDF4 file).
    
   
    
 
    
 
@@ -4628,9 +4880,15 @@ 
    Class variables
    
             
    
             
    var keepweakref
    
             
+    
    
+     Inheritance:
+       Dataset.keepweakref
+    
    
 
             
   
+    
    If True, child Dimension and Variables objects only keep weak references to
+the parent Dataset or Group.
    
   
    
 
    
 
@@ -4638,9 +4896,15 @@ 
    Class variables
    
             
    
             
    var parent
    
             
+    
    
+     Inheritance:
+       Dataset.parent
+    
    
 
             
   
+    
    parent is a reference to the parent
+Group instance. None for the root group or Dataset instance
    
   
    
 
    
 
@@ -4648,9 +4912,17 @@ 
    Class variables
    
             
    
             
    var path
    
             
+    
    
+     Inheritance:
+       Dataset.path
+    
    
 
             
   
+    
    path shows the location of the Group in
+the Dataset in a unix directory format (the names of groups in the
+hierarchy separated by backslashes). A Dataset instance is the root
+group, so the path is simply '/'.
    
   
    
 
    
 
@@ -4658,9 +4930,16 @@ 
    Class variables
    
             
    
             
    var variables
    
             
+    
    
+     Inheritance:
+       Dataset.variables
+    
    
 
             
   
+    
    The variables dictionary maps the names of variables
+defined for this Dataset or Group to instances of the Variable
+class.
    
   
    
 
    
 
@@ -4668,83 +4947,35 @@ 
    Class variables
    
             
    
             
    var vltypes
    
             
-
-            
-  
-  
    
-
    
-
-            
    
-          
    Static methods
    
-            
-  
    
-    
    
-    
    def __init__(
    self, files, check=False, aggdim=None, exclude=[], master_file=None)
    
-    
    
-    
     
    
      Inheritance:
-       Dataset.__init__
+       Dataset.vltypes
     
    
 
-    
-  
-    
    __init__(self, files, check=False, aggdim=None, exclude=[])
    
-
    Open a Dataset spanning multiple files, making it look as if it was a
-single file. Variables in the list of files that share the same
-dimension (specified with the keyword aggdim) are aggregated. If
-aggdim is not specified, the unlimited is aggregated.  Currently,
-aggdim must be the leftmost (slowest varying) dimension of each
-of the variables to be aggregated.
    
-
    files: either a sequence of netCDF files or a string with a
-wildcard (converted to a sorted list of files using glob)  If
-the master_file kwarg is not specified, the first file
-in the list will become the "master" file, defining all the
-variables with an aggregation dimension which may span
-subsequent files. Attribute access returns attributes only from "master"
-file. The files are always opened in read-only mode.
    
-
    check: True if you want to do consistency checking to ensure the
-correct variables structure for all of the netcdf files.  Checking makes
-the initialization of the MFDataset instance much slower. Default is
-False.
    
-
    aggdim: The name of the dimension to aggregate over (must
-be the leftmost dimension of each of the variables to be aggregated).
-If None (default), aggregate over the unlimited dimension.
    
-
    exclude: A list of variable names to exclude from aggregation.
-Default is an empty list.
    
-
    master_file: file to use as "master file", defining all the
-variables with an aggregation dimension and all global attributes.
    
-  
    
-
    
-
-  
    
-  
             
-  
    
-    
    
-    
    def close(
    self)
    
-    
    
-    
-
-    
   
-    
    close(self)
    
-
    close all the open files.
    
+    
    The vltypes dictionary maps the names of
+variable-length types defined for the Group or Dataset to instances of the
+VLType class.
    
   
    
 
    
 
-  
    
-  
+            
    
+          
    Static methods
    
             
   
    
     
    
     
    def createCompoundType(
    self, datatype, datatype_name)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.createCompoundType
+    
    
 
     
   
-    
    Creates a new compound data type named datatype_name from the numpy
+    
    Creates a new compound data type named datatype_name from the numpy
 dtype object datatype.
    
 
    Note: If the new compound data type contains other compound data types
 (i.e. it is a 'nested' compound type, where not all of the elements
@@ -4763,10 +4994,14 @@ 
    Static methods
    
     
    def createDimension(
    self, dimname, size=None)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.createDimension
+    
    
 
     
   
-    
    Creates a new dimension with the given dimname and size.
    
+    
    Creates a new dimension with the given dimname and size.
    
 
    size must be a positive integer or None, which stands for
 "unlimited" (default is None). Specifying a size of 0 also
 results in an unlimited dimension. The return value is the Dimension
@@ -4785,10 +5020,14 @@ 
    Static methods
    
     
    def createEnumType(
    self, datatype, datatype_name, enum_dict)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.createEnumType
+    
    
 
     
   
-    
    Creates a new Enum data type named datatype_name from a numpy
+    
    Creates a new Enum data type named datatype_name from a numpy
 integer dtype object datatype, and a python dictionary
 defining the enum fields and values.
    
 
    The return value is the EnumType class instance describing the new
@@ -4804,10 +5043,14 @@ 
    Static methods
    
     
    def createGroup(
    self, groupname)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.createGroup
+    
    
 
     
   
-    
    Creates a new Group with the given groupname.
    
+    
    Creates a new Group with the given groupname.
    
 
    If groupname is specified as a path, using forward slashes as in unix to
 separate components, then intermediate groups will be created as necessary 
 (analogous to mkdir -p in unix).  For example,
@@ -4827,10 +5070,14 @@ 
    Static methods
    
     
    def createVLType(
    self, datatype, datatype_name)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.createVLType
+    
    
 
     
   
-    
    Creates a new VLEN data type named datatype_name from a numpy
+    
    Creates a new VLEN data type named datatype_name from a numpy
 dtype object datatype.
    
 
    The return value is the VLType class instance describing the new
 datatype.
    
@@ -4845,10 +5092,14 @@ 
    Static methods
    
     
    def createVariable(
    self, varname, datatype, dimensions=(), zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, fill_value=None)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.createVariable
+    
    
 
     
   
-    
    Creates a new variable with the given varname, datatype, and
+    
    Creates a new variable with the given varname, datatype, and
 dimensions. If dimensions are not given, the variable is assumed to be
 a scalar.
    
 
    If varname is specified as a path, using forward slashes as in unix to
@@ -4958,10 +5209,14 @@ 
    Static methods
    
     
    def delncattr(
    self,name,value)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.delncattr
+    
    
 
     
   
-    
    delete a netCDF dataset or group attribute.  Use if you need to delete a
+    
    delete a netCDF dataset or group attribute.  Use if you need to delete a
 netCDF attribute with the same name as one of the reserved python
 attributes.
    
   
    
@@ -4975,10 +5230,14 @@ 
    Static methods
    
     
    def filepath(
    self,encoding=None)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.filepath
+    
    
 
     
   
-    
    Get the file system path (or the opendap URL) which was used to
+    
    Get the file system path (or the opendap URL) which was used to
 open/create the Dataset. Requires netcdf >= 4.1.2.  The path
 is decoded into a string using sys.getfilesystemencoding() by default, this can be
 changed using the encoding kwarg.
    
@@ -4993,16 +5252,20 @@ 
    Static methods
    
     
    def get_variables_by_attributes(
    ...)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.get_variables_by_attributes
+    
    
 
     
   
-    
    Returns a list of variables that match specific conditions.
    
+    
    Returns a list of variables that match specific conditions.
    
 
    Can pass in key=value parameters and variables are returned that
 contain all of the matches. For example, 
    
-
    >>> # Get variables with x-axis attribute.
->>> vs = nc.get_variables_by_attributes(axis='X')
->>> # Get variables with matching "standard_name" attribute
->>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
+
    >>> # Get variables with x-axis attribute.
+>>> vs = nc.get_variables_by_attributes(axis='X')
+>>> # Get variables with matching "standard_name" attribute
+>>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
 
    
 
 
@@ -5010,11 +5273,11 @@ 
    Static methods
    
 callable returns True.  The callable should accept a single parameter,
 the attribute value.  None is given as the attribute value when the
 attribute does not exist on the variable. For example,
    
-
    >>> # Get Axis variables
->>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
->>> # Get variables that don't have an "axis" attribute
+
    >>> # Get Axis variables
+>>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
+>>> # Get variables that don't have an "axis" attribute
 >>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
->>> # Get variables that have a "grid_mapping" attribute
+>>> # Get variables that have a "grid_mapping" attribute
 >>> vs = nc.get_variables_by_attributes(grid_mapping=lambda v: v is not None)
 
    
   
    
@@ -5028,10 +5291,14 @@ 
    Static methods
    
     
    def getncattr(
    self,name)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.getncattr
+    
    
 
     
   
-    
    retrieve a netCDF dataset or group attribute.
+    
    retrieve a netCDF dataset or group attribute.
 Use if you need to get a netCDF attribute with the same
 name as one of the reserved python attributes.
    
 
    option kwarg encoding can be used to specify the
@@ -5047,26 +5314,14 @@ 
    Static methods
    
     
    def isopen(
    ...)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.isopen
+    
    
 
     
   
-    
    is the Dataset open or closed?
    
-  
    
-
    
-
-  
    
-  
-            
-  
    
-    
    
-    
    def ncattrs(
    self)
    
-    
    
-    
-
-    
-  
-    
    ncattrs(self)
    
-
    return the netcdf attribute names from the master file.
    
+    
    is the Dataset open or closed?
    
   
    
 
    
 
@@ -5078,10 +5333,14 @@ 
    Static methods
    
     
    def renameAttribute(
    self, oldname, newname)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.renameAttribute
+    
    
 
     
   
-    
    rename a Dataset or Group attribute named oldname to newname.
    
+    
    rename a Dataset or Group attribute named oldname to newname.
    
   
    
 
    
 
@@ -5093,10 +5352,14 @@ 
    Static methods
    
     
    def renameDimension(
    self, oldname, newname)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.renameDimension
+    
    
 
     
   
-    
    rename a Dimension named oldname to newname.
    
+    
    rename a Dimension named oldname to newname.
    
   
    
 
    
 
@@ -5108,10 +5371,14 @@ 
    Static methods
    
     
    def renameGroup(
    self, oldname, newname)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.renameGroup
+    
    
 
     
   
-    
    rename a Group named oldname to newname (requires netcdf >= 4.3.1).
    
+    
    rename a Group named oldname to newname (requires netcdf >= 4.3.1).
    
   
    
 
    
 
@@ -5123,10 +5390,14 @@ 
    Static methods
    
     
    def renameVariable(
    self, oldname, newname)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.renameVariable
+    
    
 
     
   
-    
    rename a Variable named oldname to newname
    
+    
    rename a Variable named oldname to newname
    
   
    
 
    
 
@@ -5138,10 +5409,14 @@ 
    Static methods
    
     
    def set_always_mask(
    self, True_or_False)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.set_always_mask
+    
    
 
     
   
-    
    Call set_always_mask for all variables contained in
+    
    Call set_always_mask for all variables contained in
 this Dataset or Group, as well as for all
 variables in all its subgroups.
    
 
    True_or_False: Boolean determining if automatic conversion of
@@ -5161,10 +5436,14 @@ 
    Static methods
    
     
    def set_auto_chartostring(
    self, True_or_False)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.set_auto_chartostring
+    
    
 
     
   
-    
    Call set_auto_chartostring for all variables contained in this Dataset or
+    
    Call set_auto_chartostring for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
    
 
    True_or_False: Boolean determining if automatic conversion of
 all character arrays <--> string arrays should be performed for 
@@ -5183,10 +5462,14 @@ 
    Static methods
    
     
    def set_auto_mask(
    self, True_or_False)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.set_auto_mask
+    
    
 
     
   
-    
    Call set_auto_mask for all variables contained in this Dataset or
+    
    Call set_auto_mask for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
    
 
    True_or_False: Boolean determining if automatic conversion to masked arrays
 shall be applied for all variables.
    
@@ -5203,10 +5486,14 @@ 
    Static methods
    
     
    def set_auto_maskandscale(
    self, True_or_False)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.set_auto_maskandscale
+    
    
 
     
   
-    
    Call set_auto_maskandscale for all variables contained in this Dataset or
+    
    Call set_auto_maskandscale for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
    
 
    True_or_False: Boolean determining if automatic conversion to masked arrays
 and variable scaling shall be applied for all variables.
    
@@ -5223,10 +5510,14 @@ 
    Static methods
    
     
    def set_auto_scale(
    self, True_or_False)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.set_auto_scale
+    
    
 
     
   
-    
    Call set_auto_scale for all variables contained in this Dataset or
+    
    Call set_auto_scale for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
    
 
    True_or_False: Boolean determining if automatic variable scaling
 shall be applied for all variables.
    
@@ -5243,10 +5534,14 @@ 
    Static methods
    
     
    def set_fill_off(
    self)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.set_fill_off
+    
    
 
     
   
-    
    Sets the fill mode for a Dataset open for writing to off.
    
+    
    Sets the fill mode for a Dataset open for writing to off.
    
 
    This will prevent the data from being pre-filled with fill values, which
 may result in some performance improvements. However, you must then make
 sure the data is actually written before being read.
    
@@ -5261,10 +5556,14 @@ 
    Static methods
    
     
    def set_fill_on(
    self)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.set_fill_on
+    
    
 
     
   
-    
    Sets the fill mode for a Dataset open for writing to on.
    
+    
    Sets the fill mode for a Dataset open for writing to on.
    
 
    This causes data to be pre-filled with fill values. The fill values can be
 controlled by the variable's _Fill_Value attribute, but is usually
 sufficient to the use the netCDF default _Fill_Value (defined
@@ -5283,10 +5582,14 @@ 
    Static methods
    
     
    def setncattr(
    self,name,value)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.setncattr
+    
    
 
     
   
-    
    set a netCDF dataset or group attribute using name,value pair.
+    
    set a netCDF dataset or group attribute using name,value pair.
 Use if you need to set a netCDF attribute with the
 with the same name as one of the reserved python attributes.
    
   
    
@@ -5300,10 +5603,14 @@ 
    Static methods
    
     
    def setncattr_string(
    self,name,value)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.setncattr_string
+    
    
 
     
   
-    
    set a netCDF dataset or group string attribute using name,value pair.
+    
    set a netCDF dataset or group string attribute using name,value pair.
 Use if you need to ensure that a netCDF attribute is created with type
 NC_STRING if the file format is NETCDF4.
    
   
    
@@ -5317,10 +5624,14 @@ 
    Static methods
    
     
    def setncatts(
    self,attdict)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.setncatts
+    
    
 
     
   
-    
    set a bunch of netCDF dataset or group attributes at once using a python dictionary.
+    
    set a bunch of netCDF dataset or group attributes at once using a python dictionary.
 This may be faster when setting a lot of attributes for a NETCDF3
 formatted file, since nc_redef/nc_enddef is not called in between setting
 each attribute
    
@@ -5335,10 +5646,95 @@ 
    Static methods
    
     
    def sync(
    self)
    
     
    
     
+    
    
+     Inheritance:
+       Dataset.sync
+    
    
 
     
   
-    
    Writes all buffered data in the Dataset to the disk file.
    
+    
    Writes all buffered data in the Dataset to the disk file.
    
+  
    
+
    
+
+  
    
+  
+          
    Methods
    
+            
+  
    
+    
    
+    
    def __init__(
    self, files, check=False, aggdim=None, exclude=[])
    
+    
    
+    
+    
    
+     Inheritance:
+       Dataset.__init__
+    
    
+
+    
+  
+    
    Open a Dataset spanning multiple files, making it look as if it was a
+single file. Variables in the list of files that share the same
+dimension (specified with the keyword aggdim) are aggregated. If
+aggdim is not specified, the unlimited is aggregated.  Currently,
+aggdim must be the leftmost (slowest varying) dimension of each
+of the variables to be aggregated.
    
+
    files: either a sequence of netCDF files or a string with a
+wildcard (converted to a sorted list of files using glob)  If
+the master_file kwarg is not specified, the first file
+in the list will become the "master" file, defining all the
+variables with an aggregation dimension which may span
+subsequent files. Attribute access returns attributes only from "master"
+file. The files are always opened in read-only mode.
    
+
    check: True if you want to do consistency checking to ensure the
+correct variables structure for all of the netcdf files.  Checking makes
+the initialization of the MFDataset instance much slower. Default is
+False.
    
+
    aggdim: The name of the dimension to aggregate over (must
+be the leftmost dimension of each of the variables to be aggregated).
+If None (default), aggregate over the unlimited dimension.
    
+
    exclude: A list of variable names to exclude from aggregation.
+Default is an empty list.
    
+
    master_file: file to use as "master file", defining all the
+variables with an aggregation dimension and all global attributes.
    
+  
    
+
    
+
+  
    
+  
+            
+  
    
+    
    
+    
    def close(
    self)
    
+    
    
+    
+    
    
+     Inheritance:
+       Dataset.close
+    
    
+
+    
+  
+    
    close all the open files.
    
+  
    
+
    
+
+  
    
+  
+            
+  
    
+    
    
+    
    def ncattrs(
    self)
    
+    
    
+    
+    
    
+     Inheritance:
+       Dataset.ncattrs
+    
    
+
+    
+  
+    
    return the netcdf attribute names from the master file.
    
   
    
 
    
 
@@ -5354,27 +5750,27 @@ 
    Static methods
    
     
    Class providing an interface to a MFDataset time Variable by imposing a unique common
 time unit and/or calendar to all files.
    
 
    Example usage (See __init__ for more details):
    
-
    >>> import numpy
->>> f1 = Dataset("mftest_1.nc","w", format="NETCDF4_CLASSIC")
->>> f2 = Dataset("mftest_2.nc","w", format="NETCDF4_CLASSIC")
->>> f1.createDimension("time",None)
->>> f2.createDimension("time",None)
->>> t1 = f1.createVariable("time","i",("time",))
->>> t2 = f2.createVariable("time","i",("time",))
->>> t1.units = "days since 2000-01-01"
->>> t2.units = "days since 2000-02-01"
->>> t1.calendar = "standard"
->>> t2.calendar = "standard"
+
    >>> import numpy
+>>> f1 = Dataset("mftest_1.nc","w", format="NETCDF4_CLASSIC")
+>>> f2 = Dataset("mftest_2.nc","w", format="NETCDF4_CLASSIC")
+>>> f1.createDimension("time",None)
+>>> f2.createDimension("time",None)
+>>> t1 = f1.createVariable("time","i",("time",))
+>>> t2 = f2.createVariable("time","i",("time",))
+>>> t1.units = "days since 2000-01-01"
+>>> t2.units = "days since 2000-02-01"
+>>> t1.calendar = "standard"
+>>> t2.calendar = "standard"
 >>> t1[:] = numpy.arange(31)
 >>> t2[:] = numpy.arange(30)
 >>> f1.close()
 >>> f2.close()
->>> # Read the two files in at once, in one Dataset.
->>> f = MFDataset("mftest*nc")
->>> t = f.variables["time"]
+>>> # Read the two files in at once, in one Dataset.
+>>> f = MFDataset("mftest*nc")
+>>> t = f.variables["time"]
 >>> print t.units
 days since 2000-01-01
->>> print t[32] # The value written in the file, inconsistent with the MF time units.
+>>> print t[32] # The value written in the file, inconsistent with the MF time units.
 1
 >>> T = MFTime(t)
 >>> print T[32]
@@ -5389,9 +5785,9 @@ 
    Ancestors (in MRO)
    
           
      
           
    • MFTime
      • 
           
    • netCDF4._netCDF4._Variable
      • 
-          
    • builtins.object
      • 
+          
    • __builtin__.object
      • 
           
    
-          
    Static methods
    
+          
    Methods
    
             
   
    
     
    
@@ -5401,8 +5797,7 @@ 
    Static methods
    
 
     
   
-    
    __init__(self, time, units=None, calendar=None)
    
-
    Create a time Variable with units consistent across a multifile
+    
    Create a time Variable with units consistent across a multifile
 dataset.
    
 
    time: Time variable from a MFDataset.
    
 
    units: Time units, for example, 'days since 1979-01-01'. If None,
@@ -5419,7 +5814,7 @@ 
    Static methods
    
             
   
    
     
    
-    
    def ncattrs(
    self)
    
+    
    def ncattrs(
    ...)
    
     
    
     
 
@@ -5433,7 +5828,7 @@ 
    Static methods
    
             
   
    
     
    
-    
    def set_auto_chartostring(
    self, val)
    
+    
    def set_auto_chartostring(
    ...)
    
     
    
     
 
@@ -5447,7 +5842,7 @@ 
    Static methods
    
             
   
    
     
    
-    
    def set_auto_mask(
    self, val)
    
+    
    def set_auto_mask(
    ...)
    
     
    
     
 
@@ -5461,7 +5856,7 @@ 
    Static methods
    
             
   
    
     
    
-    
    def set_auto_maskandscale(
    self, val)
    
+    
    def set_auto_maskandscale(
    ...)
    
     
    
     
 
@@ -5475,7 +5870,7 @@ 
    Static methods
    
             
   
    
     
    
-    
    def set_auto_scale(
    self, val)
    
+    
    def set_auto_scale(
    ...)
    
     
    
     
 
@@ -5489,7 +5884,7 @@ 
    Static methods
    
             
   
    
     
    
-    
    def typecode(
    self)
    
+    
    def typecode(
    ...)
    
     
    
     
 
@@ -5521,7 +5916,7 @@ 
    Static methods
    
           
    Ancestors (in MRO)
    
           
      
           
    • VLType
      • 
-          
    • builtins.object
      • 
+          
    • __builtin__.object
      • 
           
    
           
    Class variables
    
             
    
@@ -5626,7 +6021,7 @@ 
    Static methods
    
           
    Ancestors (in MRO)
    
           
      
           
    • Variable
      • 
-          
    • builtins.object
      • 
+          
    • __builtin__.object
      • 
           
    
           
    Class variables
    
             
    
@@ -6148,12 +6543,12 @@ 
    Static methods
    
 
    If maskandscale is set to True, and the variable has a
 scale_factor or an add_offset attribute, then data read
 from that variable is unpacked using::
    
-
    data = self.scale_factor*data + self.add_offset
+
    data = self.scale_factor*data + self.add_offset
 
    
 
 
 
    When data is written to a variable it is packed using::
    
-
    data = (data - self.add_offset)/self.scale_factor
+
    data = (data - self.add_offset)/self.scale_factor
 
    
 
 
@@ -6193,12 +6588,12 @@ 
    Static methods
    
 
    If scale is set to True, and the variable has a
 scale_factor or an add_offset attribute, then data read
 from that variable is unpacked using::
    
-
    data = self.scale_factor*data + self.add_offset
+
    data = self.scale_factor*data + self.add_offset
 
    
 
 
 
    When data is written to a variable it is packed using::
    
-
    data = (data - self.add_offset)/self.scale_factor
+
    data = (data - self.add_offset)/self.scale_factor
 
    
 
 
@@ -6336,7 +6731,7 @@ 
    Static methods
    
   
    
     
    
       Documentation generated by
-      pdoc 0.3.2.dev29
+      pdoc 0.3.2.dev16
     
    
 
     
    pdoc is in the public domain with the

From ac79766c0eb7a9aabfd5c36582d0d26f2b48281c Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 27 Aug 2018 20:23:01 -0600
Subject: [PATCH 0126/1504] update

---
 .travis.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.travis.yml b/.travis.yml
index 82f973091..d6b5cffb1 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -1,6 +1,6 @@
 language: python
 dist: xenial
-sudo: false
+sudo: true
 
 addons:
   apt:

From ccef6d5a6283abeb5308c3260725e43a31648303 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 28 Aug 2018 10:51:43 -0600
Subject: [PATCH 0127/1504] use trusty for MPI test

---
 .travis.yml | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index d6b5cffb1..2d245ced3 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -19,10 +19,11 @@ python:
   - "2.7"
   - "3.6"
   - "3.7"
+# - "3.8-dev"
 
 matrix:
-  #allow_failures:
-  #  - python: "3.7-dev"
+  allow_failures:
+    - python: "3.8-dev"
   include:
     # Absolute minimum dependencies.
     - python: 2.7
@@ -30,6 +31,7 @@ matrix:
         - DEPENDS="numpy==1.9.0 cython==0.21 ordereddict==1.1 setuptools==18.0 cftime"
     # test MPI
     - python: 2.7
+      dist: trusty
       env: 
         - MPI=1
         - CC=mpicc

From 3ab462e4a19bb745b2d088687b0d6f182f562a61 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 28 Aug 2018 11:49:09 -0600
Subject: [PATCH 0128/1504] include 3.8-dev test

---
 .travis.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.travis.yml b/.travis.yml
index 2d245ced3..c9d9edb88 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -19,7 +19,7 @@ python:
   - "2.7"
   - "3.6"
   - "3.7"
-# - "3.8-dev"
+  - "3.8-dev"
 
 matrix:
   allow_failures:

From cea51c5bce5fa8f6ae8d377c02934be7e6c14016 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 28 Aug 2018 12:16:39 -0600
Subject: [PATCH 0129/1504] try netcdf 4.6.1

---
 .travis.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.travis.yml b/.travis.yml
index c9d9edb88..9b9b7a326 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -36,7 +36,7 @@ matrix:
         - MPI=1
         - CC=mpicc
         - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
-        - NETCDF_VERSION=4.4.1.1
+        - NETCDF_VERSION=4.6.1
         - NETCDF_DIR=$HOME
         - PATH=${NETCDF_DIR}/bin:${PATH} # pick up nc-config here
       addons:

From 32b5bc4cb35b35273ee6b62e4196477972e577dd Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 28 Aug 2018 12:33:39 -0600
Subject: [PATCH 0130/1504] NC_MPIIO declared twice if MPI enabled

---
 include/netCDF4.pxi | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index 3a8c837c7..9a850d93e 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -55,8 +55,6 @@ cdef extern from "netcdf.h":
         NC_CLASSIC_MODEL # Enforce strict netcdf-3 rules. 
         # Use these 'mode' flags for both nc_create and nc_open.
         NC_SHARE # Share updates, limit cacheing 
-        NC_MPIIO
-        NC_MPIPOSIX
         # The following flag currently is ignored, but use in
         # nc_open() or nc_create() may someday support use of advisory
         # locking to prevent multiple writers from clobbering a file 
@@ -710,6 +708,7 @@ IF HAS_NC_PAR:
     cdef extern from "netcdf.h":
         cdef enum:
             NC_MPIIO
+            NC_MPIPOSIX
             NC_PNETCDF
 
 # taken from numpy.pxi in numpy 1.0rc2.

From fbd0a821e405683f277ad60339855ff00dd743dc Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 29 Aug 2018 12:37:01 -0600
Subject: [PATCH 0131/1504] raise ValueError when trying to set multi-dim array
 att (issue #841)

---
 Changelog            | 2 ++
 netCDF4/_netCDF4.pyx | 2 ++
 test/tst_atts.py     | 2 ++
 3 files changed, 6 insertions(+)

diff --git a/Changelog b/Changelog
index 4d874cd3a..0812efce8 100644
--- a/Changelog
+++ b/Changelog
@@ -6,6 +6,8 @@
    multidimensional indexing is deprecated), issue #833.
  * add 'master_file' kwarg to MFDataset.__init__ (issue #835).
  * always use nc_get_vars for strided access over OpenDAP (issue #838).
+ * raise ValueError when trying to set multi-dimensional array attribute
+   instead of silently flattening array (issue #841),
 
 
  version 1.4.1 (tag v1.4.1rel)
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 38866f760..b27239356 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1421,6 +1421,8 @@ cdef _set_att(grp, int varid, name, value,\
     attname = bytestr
     # put attribute value into a numpy array.
     value_arr = numpy.array(value)
+    if value_arr.ndim > 1:
+        raise ValueError('multi-dimensional array attributes not supported')
     # if array is 64 bit integers or
     # if 64-bit datatype not supported, cast to 32 bit integers.
     fmt = _get_format(grp._grpid)
diff --git a/test/tst_atts.py b/test/tst_atts.py
index ab261ebaa..107a26cd6 100644
--- a/test/tst_atts.py
+++ b/test/tst_atts.py
@@ -69,6 +69,8 @@ def setUp(self):
         g.floatatt = FLOATATT
         g.seqatt = SEQATT
         g.stringseqatt = STRINGSEQATT
+        with self.assertRaises(ValueError):
+            g.arrayatt = [[1, 2], [3, 4]]
         g.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
         v = f.createVariable(VAR_NAME, 'f8',(DIM1_NAME,DIM2_NAME,DIM3_NAME))
         # try to set a variable attribute with one of the reserved names.

From 23a169506fb2162c7fe1363dbfcd1d56e3c74862 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 29 Aug 2018 12:39:15 -0600
Subject: [PATCH 0132/1504] update

---
 test/tst_atts.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/tst_atts.py b/test/tst_atts.py
index 107a26cd6..176377d97 100644
--- a/test/tst_atts.py
+++ b/test/tst_atts.py
@@ -70,7 +70,7 @@ def setUp(self):
         g.seqatt = SEQATT
         g.stringseqatt = STRINGSEQATT
         with self.assertRaises(ValueError):
-            g.arrayatt = [[1, 2], [3, 4]]
+            g.arrayatt = [[1, 2], [3, 4]] # issue #841
         g.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
         v = f.createVariable(VAR_NAME, 'f8',(DIM1_NAME,DIM2_NAME,DIM3_NAME))
         # try to set a variable attribute with one of the reserved names.

From d78cd1bd0f2a1189e5b728373624f70b838bb82a Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 29 Aug 2018 12:43:12 -0600
Subject: [PATCH 0133/1504] update

---
 netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index b27239356..b6ef19a28 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1421,7 +1421,7 @@ cdef _set_att(grp, int varid, name, value,\
     attname = bytestr
     # put attribute value into a numpy array.
     value_arr = numpy.array(value)
-    if value_arr.ndim > 1:
+    if value_arr.ndim > 1: # issue #841
         raise ValueError('multi-dimensional array attributes not supported')
     # if array is 64 bit integers or
     # if 64-bit datatype not supported, cast to 32 bit integers.

From 4fb716498cac18ac4c432739b9d6cb66fa028185 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 29 Aug 2018 13:25:29 -0600
Subject: [PATCH 0134/1504] change to FutureWarning for now

---
 Changelog            | 5 +++--
 netCDF4/_netCDF4.pyx | 7 ++++++-
 test/tst_atts.py     | 4 ++--
 3 files changed, 11 insertions(+), 5 deletions(-)

diff --git a/Changelog b/Changelog
index 0812efce8..ea90b4820 100644
--- a/Changelog
+++ b/Changelog
@@ -6,8 +6,9 @@
    multidimensional indexing is deprecated), issue #833.
  * add 'master_file' kwarg to MFDataset.__init__ (issue #835).
  * always use nc_get_vars for strided access over OpenDAP (issue #838).
- * raise ValueError when trying to set multi-dimensional array attribute
-   instead of silently flattening array (issue #841),
+ * raise Future when trying to set multi-dimensional array attribute
+   while still silently flattening array (issue #841). Will change
+   to ValueError in next release.
 
 
  version 1.4.1 (tag v1.4.1rel)
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index b6ef19a28..b857eef62 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1422,7 +1422,12 @@ cdef _set_att(grp, int varid, name, value,\
     # put attribute value into a numpy array.
     value_arr = numpy.array(value)
     if value_arr.ndim > 1: # issue #841
-        raise ValueError('multi-dimensional array attributes not supported')
+        #raise ValueError('multi-dimensional array attributes not supported')
+        msg = """
+Multi-dimensional array attributes are now deprecated.
+Instead of silently flattening the array, an error will
+be raised in the next release."""
+        warnings.warn(msg,FutureWarning)
     # if array is 64 bit integers or
     # if 64-bit datatype not supported, cast to 32 bit integers.
     fmt = _get_format(grp._grpid)
diff --git a/test/tst_atts.py b/test/tst_atts.py
index 176377d97..01198bbea 100644
--- a/test/tst_atts.py
+++ b/test/tst_atts.py
@@ -69,8 +69,8 @@ def setUp(self):
         g.floatatt = FLOATATT
         g.seqatt = SEQATT
         g.stringseqatt = STRINGSEQATT
-        with self.assertRaises(ValueError):
-            g.arrayatt = [[1, 2], [3, 4]] # issue #841
+        #with self.assertRaises(ValueError):
+        #    g.arrayatt = [[1, 2], [3, 4]] # issue #841
         g.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
         v = f.createVariable(VAR_NAME, 'f8',(DIM1_NAME,DIM2_NAME,DIM3_NAME))
         # try to set a variable attribute with one of the reserved names.

From 705527b295e5c5777b9d8107ffa0bd54e857d998 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 29 Aug 2018 13:32:50 -0600
Subject: [PATCH 0135/1504] use version check for FutureWarning

---
 netCDF4/_netCDF4.pyx | 8 +++++---
 test/tst_atts.py     | 5 +++--
 2 files changed, 8 insertions(+), 5 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index b857eef62..9fd3db7dd 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1422,12 +1422,14 @@ cdef _set_att(grp, int varid, name, value,\
     # put attribute value into a numpy array.
     value_arr = numpy.array(value)
     if value_arr.ndim > 1: # issue #841
-        #raise ValueError('multi-dimensional array attributes not supported')
-        msg = """
+        if __version__ > "1.4.2":
+            raise ValueError('multi-dimensional array attributes not supported')
+        else:
+            msg = """
 Multi-dimensional array attributes are now deprecated.
 Instead of silently flattening the array, an error will
 be raised in the next release."""
-        warnings.warn(msg,FutureWarning)
+            warnings.warn(msg,FutureWarning)
     # if array is 64 bit integers or
     # if 64-bit datatype not supported, cast to 32 bit integers.
     fmt = _get_format(grp._grpid)
diff --git a/test/tst_atts.py b/test/tst_atts.py
index 01198bbea..4345f038c 100644
--- a/test/tst_atts.py
+++ b/test/tst_atts.py
@@ -69,8 +69,9 @@ def setUp(self):
         g.floatatt = FLOATATT
         g.seqatt = SEQATT
         g.stringseqatt = STRINGSEQATT
-        #with self.assertRaises(ValueError):
-        #    g.arrayatt = [[1, 2], [3, 4]] # issue #841
+        if netCDF4.__version__ > "1.4.2":
+            with self.assertRaises(ValueError):
+                g.arrayatt = [[1, 2], [3, 4]] # issue #841
         g.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
         v = f.createVariable(VAR_NAME, 'f8',(DIM1_NAME,DIM2_NAME,DIM3_NAME))
         # try to set a variable attribute with one of the reserved names.

From 212ca7bd10127be89b41f372edbe5026b93bf862 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 29 Aug 2018 14:48:06 -0600
Subject: [PATCH 0136/1504] fix typo

---
 Changelog | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Changelog b/Changelog
index ea90b4820..964ee40c8 100644
--- a/Changelog
+++ b/Changelog
@@ -7,7 +7,7 @@
  * add 'master_file' kwarg to MFDataset.__init__ (issue #835).
  * always use nc_get_vars for strided access over OpenDAP (issue #838).
  * raise Future when trying to set multi-dimensional array attribute
-   while still silently flattening array (issue #841). Will change
+   while still silently flattening the array (issue #841). Will change
    to ValueError in next release.
 
 

From f194ee144196f9f5b8dcd61f5d7bbdd75fc1b502 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 29 Aug 2018 14:48:51 -0600
Subject: [PATCH 0137/1504] fix typo

---
 netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 9fd3db7dd..03eef0108 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -31,7 +31,7 @@ Download
  - Latest bleeding-edge code from the 
    [github repository](http://github.com/Unidata/netcdf4-python).
  - Latest [releases](https://pypi.python.org/pypi/netCDF4)
-   (source code and windows installers).
+   (source code and binary installers).
 
 Requires
 ========

From 2527399599710c3dd29e3fe3e9a17f4f7a1df64f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Thu, 30 Aug 2018 13:41:47 -0600
Subject: [PATCH 0138/1504] fix typo

---
 Changelog | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/Changelog b/Changelog
index 964ee40c8..37f18a39c 100644
--- a/Changelog
+++ b/Changelog
@@ -6,9 +6,9 @@
    multidimensional indexing is deprecated), issue #833.
  * add 'master_file' kwarg to MFDataset.__init__ (issue #835).
  * always use nc_get_vars for strided access over OpenDAP (issue #838).
- * raise Future when trying to set multi-dimensional array attribute
+ * raise FutureWarning when trying to set multi-dimensional array attribute
    while still silently flattening the array (issue #841). Will change
-   to ValueError in next release.
+   to ValueError in next release (1.4.3).
 
 
  version 1.4.1 (tag v1.4.1rel)

From 5e579845c8d4fe9578a7df29242e190882f46404 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 22 Sep 2018 15:38:11 -0600
Subject: [PATCH 0139/1504] remove workaround from issue 170 (reset default
 format to NETCDF3_64BIT)

---
 netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 03eef0108..f474b638c 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2047,7 +2047,7 @@ references to the parent Dataset or Group.
             # for issue 170 (nc_open'ing a DAP dataset after switching
             # format to NETCDF4). This bug should be fixed in version
             # 4.3.0 of the netcdf library (add a version check here?).
-            _set_default_format(format='NETCDF3_64BIT_OFFSET')
+            #_set_default_format(format='NETCDF3_64BIT_OFFSET')
         elif mode == 'r':
             if memory is not None:
                 IF HAS_NC_OPEN_MEM:

From 7a7123fc80a9e2dbd0532162eb6f5e0cddddd03e Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 22 Sep 2018 15:47:55 -0600
Subject: [PATCH 0140/1504] update

---
 netCDF4/_netCDF4.pyx | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index f474b638c..07c775469 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2047,6 +2047,8 @@ references to the parent Dataset or Group.
             # for issue 170 (nc_open'ing a DAP dataset after switching
             # format to NETCDF4). This bug should be fixed in version
             # 4.3.0 of the netcdf library (add a version check here?).
+            # **this causes parallel mode to fail when both hdf5-parallel and
+            # pnetcdf are enabled - issue #820 **
             #_set_default_format(format='NETCDF3_64BIT_OFFSET')
         elif mode == 'r':
             if memory is not None:

From b75056d3365cc909cd58209b560d74453b18428d Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 24 Sep 2018 06:39:35 -0600
Subject: [PATCH 0141/1504] turn off DAP tests

---
 .appveyor.yml | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/.appveyor.yml b/.appveyor.yml
index 18e7dbc9c..b8a9521dd 100644
--- a/.appveyor.yml
+++ b/.appveyor.yml
@@ -51,4 +51,5 @@ build: off
 
 test_script:
   - python -m pip install . --no-deps --ignore-installed --no-cache-dir -vvv
-  - cd test && python run_all.py
\ No newline at end of file
+  - set NO_NET=1
+  - cd test && python run_all.py

From ca9d515f9298708ca6d37547349880930f3ef6f5 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 24 Sep 2018 10:03:14 -0600
Subject: [PATCH 0142/1504] update

---
 Changelog | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/Changelog b/Changelog
index 37f18a39c..47dbcbe9b 100644
--- a/Changelog
+++ b/Changelog
@@ -9,6 +9,8 @@
  * raise FutureWarning when trying to set multi-dimensional array attribute
    while still silently flattening the array (issue #841). Will change
    to ValueError in next release (1.4.3).
+ * fix parallel writes when both nc4 parallel and pnetcdf parallel options
+   enabled in the netcdf-c library (issue #820).
 
 
  version 1.4.1 (tag v1.4.1rel)

From 5845c73a9ed97400fbb390a5e08ee763ff2c8293 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 17 Oct 2018 09:15:27 -0600
Subject: [PATCH 0143/1504] fix for issue #830 (write masked scalar char
 variable)

---
 Changelog            |  1 +
 netCDF4/_netCDF4.pyx |  6 ++++++
 test/tst_types.py    | 43 ++++++++++++++++++++++++-------------------
 3 files changed, 31 insertions(+), 19 deletions(-)

diff --git a/Changelog b/Changelog
index 37f18a39c..38c3219a2 100644
--- a/Changelog
+++ b/Changelog
@@ -9,6 +9,7 @@
  * raise FutureWarning when trying to set multi-dimensional array attribute
    while still silently flattening the array (issue #841). Will change
    to ValueError in next release (1.4.3).
+ * fix for writing masked scalar character variable (issue #830).
 
 
  version 1.4.1 (tag v1.4.1rel)
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 03eef0108..47f6f452f 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -3483,6 +3483,9 @@ behavior is similar to Fortran or Matlab, but different than numpy.
             # specified numpy data type.
             xtype = _nptonctype[datatype.str[1:]]
             # dtype variable attribute is a numpy datatype object.
+            # set numpy char type to single char string (issue #830)
+            if datatype.char == 'c':
+                datatype = numpy.dtype('S1')
             self.dtype = datatype
         else:
             raise TypeError('illegal primitive data type, must be one of %s, got %s' % (_supportedtypes,datatype))
@@ -4625,6 +4628,9 @@ cannot be safely cast to variable data type""" % attname
                         fillval = self._FillValue
                     else:
                         fillval = default_fillvals[self.dtype.str[1:]]
+                    # cast to type of variable before filling (issue #830)
+                    if self.dtype != data.dtype:
+                        data = data.astype(self.dtype) # cast data, if necessary.
                     data = data.filled(fill_value=fillval)
 
         # Fill output array with data chunks.
diff --git a/test/tst_types.py b/test/tst_types.py
index 53da8154a..ea90245ec 100644
--- a/test/tst_types.py
+++ b/test/tst_types.py
@@ -2,7 +2,7 @@
 import unittest
 import os
 import tempfile
-import numpy as NP
+import numpy as np
 from numpy.testing import assert_array_equal, assert_array_almost_equal
 from numpy.random.mtrand import uniform
 import netCDF4
@@ -17,30 +17,30 @@
 zlib=False;complevel=0;shuffle=0;least_significant_digit=None
 datatypes = ['f8','f4','i1','i2','i4','i8','u1','u2','u4','u8','S1']
 FillValue = 1.0
-issue273_data = NP.ma.array(['z']*10,dtype='S1',\
+issue273_data = np.ma.array(['z']*10,dtype='S1',\
 mask=[False,False,False,False,False,True,False,False,False,False])
 
 class PrimitiveTypesTestCase(unittest.TestCase):
 
     def setUp(self):
         self.file = FILE_NAME
-        file = netCDF4.Dataset(self.file,'w')
-        file.createDimension('n1', None)
-        file.createDimension('n2', n2dim)
+        f = netCDF4.Dataset(self.file,'w')
+        f.createDimension('n1', None)
+        f.createDimension('n2', n2dim)
         for typ in datatypes:
-            foo = file.createVariable('data_'+typ, typ, ('n1','n2',),zlib=zlib,complevel=complevel,shuffle=shuffle,least_significant_digit=least_significant_digit,fill_value=FillValue)
+            foo = f.createVariable('data_'+typ, typ, ('n1','n2',),zlib=zlib,complevel=complevel,shuffle=shuffle,least_significant_digit=least_significant_digit,fill_value=FillValue)
             #foo._FillValue = FillValue
             # test writing of _FillValue attribute for diff types
             # (should be cast to type of variable silently)
             foo[1:n1dim] = ranarr[1:n1dim]
-        v = file.createVariable('issue271', NP.dtype('S1'), [], fill_value=b'Z')
-        v2 = file.createVariable('issue273', NP.dtype('S1'), 'n2',\
+        v = f.createVariable('issue271', np.dtype('S1'), [], fill_value=b'Z')
+        v2 = f.createVariable('issue273', np.dtype('S1'), 'n2',\
                 fill_value='\x00')
         v2[:] = issue273_data
-        v3 = file.createVariable('issue707',NP.int8,'n2')
+        v3 = f.createVariable('issue707',np.int8,'n2')
         v3.setncattr('missing_value',255)
         v3[:]=-1
-        file.close()
+        f.close()
 
     def tearDown(self):
         # Remove the temporary files
@@ -48,9 +48,9 @@ def tearDown(self):
 
     def runTest(self):
         """testing primitive data type """
-        file = netCDF4.Dataset(self.file)
+        f = netCDF4.Dataset(self.file)
         for typ in datatypes:
-            data = file.variables['data_'+typ]
+            data = f.variables['data_'+typ]
             data.set_auto_maskandscale(False)
             datarr = data[1:n1dim]
             # fill missing data with _FillValue
@@ -65,22 +65,22 @@ def runTest(self):
                 self.assertTrue(data.dtype.str[1:] == typ)
             # check data in variable.
             if data.dtype.str[1:] != 'S1':
-                #assert NP.allclose(datarr, ranarr[1:n1dim].astype(data.dtype))
+                #assert np.allclose(datarr, ranarr[1:n1dim].astype(data.dtype))
                 assert_array_almost_equal(datarr,ranarr[1:n1dim].astype(data.dtype))
             else:
                 assert datarr.tostring() == ranarr[1:n1dim].astype(data.dtype).tostring()
             # check that variable elements not yet written are filled
             # with the specified _FillValue.
-            assert_array_equal(datfilled,NP.asarray(data._FillValue,datfilled.dtype))
+            assert_array_equal(datfilled,np.asarray(data._FillValue,datfilled.dtype))
         # issue 271 (_FillValue should be a byte for character arrays on
         # Python 3)
-        v = file.variables['issue271']
+        v = f.variables['issue271']
         if type(v._FillValue) == bytes:
             assert(v._FillValue == b'Z') # python 3
         else:
             assert(v._FillValue == u'Z') # python 2
         # issue 273 (setting _FillValue to null byte manually)
-        v2 = file.variables['issue273']
+        v2 = f.variables['issue273']
         if type(v2._FillValue) == bytes:
             assert(v2._FillValue == b'\x00') # python 3
         else:
@@ -88,9 +88,14 @@ def runTest(self):
         assert(str(issue273_data) == str(v2[:]))
         # isse 707 (don't apply missing_value if cast to variable type is
         # unsafe)
-        v3 = file.variables['issue707']
-        assert_array_equal(v3[:],-1*NP.ones(n2dim,v3.dtype))
-        file.close()
+        v3 = f.variables['issue707']
+        assert_array_equal(v3[:],-1*np.ones(n2dim,v3.dtype))
+        f.close()
+        # issue #830 (masked scalar char variable)
+        f = netCDF4.Dataset(self.file,'a')
+        a = f.createVariable('a', 'c', ())
+        a[:] = np.ma.masked
+        f.close()
 
 if __name__ == '__main__':
     unittest.main()

From e6cb627d02d35e7f02c92dff9c707f7400847c79 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 17 Oct 2018 09:21:16 -0600
Subject: [PATCH 0144/1504] issue 850, not 830

---
 Changelog            | 2 +-
 netCDF4/_netCDF4.pyx | 4 ++--
 test/tst_types.py    | 2 +-
 3 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/Changelog b/Changelog
index 38c3219a2..6846e1548 100644
--- a/Changelog
+++ b/Changelog
@@ -9,7 +9,7 @@
  * raise FutureWarning when trying to set multi-dimensional array attribute
    while still silently flattening the array (issue #841). Will change
    to ValueError in next release (1.4.3).
- * fix for writing masked scalar character variable (issue #830).
+ * fix for writing masked scalar character variable (issue #850).
 
 
  version 1.4.1 (tag v1.4.1rel)
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 47f6f452f..c7abec85d 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -3483,7 +3483,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
             # specified numpy data type.
             xtype = _nptonctype[datatype.str[1:]]
             # dtype variable attribute is a numpy datatype object.
-            # set numpy char type to single char string (issue #830)
+            # set numpy char type to single char string (issue #850)
             if datatype.char == 'c':
                 datatype = numpy.dtype('S1')
             self.dtype = datatype
@@ -4628,7 +4628,7 @@ cannot be safely cast to variable data type""" % attname
                         fillval = self._FillValue
                     else:
                         fillval = default_fillvals[self.dtype.str[1:]]
-                    # cast to type of variable before filling (issue #830)
+                    # cast to type of variable before filling (issue #850)
                     if self.dtype != data.dtype:
                         data = data.astype(self.dtype) # cast data, if necessary.
                     data = data.filled(fill_value=fillval)
diff --git a/test/tst_types.py b/test/tst_types.py
index ea90245ec..93af1153b 100644
--- a/test/tst_types.py
+++ b/test/tst_types.py
@@ -91,7 +91,7 @@ def runTest(self):
         v3 = f.variables['issue707']
         assert_array_equal(v3[:],-1*np.ones(n2dim,v3.dtype))
         f.close()
-        # issue #830 (masked scalar char variable)
+        # issue #850 (masked scalar char variable)
         f = netCDF4.Dataset(self.file,'a')
         a = f.createVariable('a', 'c', ())
         a[:] = np.ma.masked

From 5520034abdcb8de01984d4ddae33419e863ca542 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 17 Oct 2018 09:32:01 -0600
Subject: [PATCH 0145/1504] add more comments

---
 netCDF4/_netCDF4.pyx | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index c7abec85d..16760062e 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -3484,6 +3484,8 @@ behavior is similar to Fortran or Matlab, but different than numpy.
             xtype = _nptonctype[datatype.str[1:]]
             # dtype variable attribute is a numpy datatype object.
             # set numpy char type to single char string (issue #850)
+            # to avoid "TypeError: Cannot set fill value of string with
+            # array of dtype float64" when filling masked array in __setitem__
             if datatype.char == 'c':
                 datatype = numpy.dtype('S1')
             self.dtype = datatype
@@ -4629,6 +4631,9 @@ cannot be safely cast to variable data type""" % attname
                     else:
                         fillval = default_fillvals[self.dtype.str[1:]]
                     # cast to type of variable before filling (issue #850)
+                    # otherwise 'filled' method may raise an error
+                    # (example, data is type float while fill_value is a
+                    # string)
                     if self.dtype != data.dtype:
                         data = data.astype(self.dtype) # cast data, if necessary.
                     data = data.filled(fill_value=fillval)

From b78064aac84ae5ce87ff522ae4e17580334bee2a Mon Sep 17 00:00:00 2001
From: "Jeffrey.S.Whitaker" 
Date: Wed, 17 Oct 2018 22:20:40 -0400
Subject: [PATCH 0146/1504] very hackish workaround for bug in numpy 1.13.x

---
 netCDF4/_netCDF4.pyx | 15 ++++++++++++---
 1 file changed, 12 insertions(+), 3 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 16760062e..9304ee99c 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -4634,9 +4634,18 @@ cannot be safely cast to variable data type""" % attname
                     # otherwise 'filled' method may raise an error
                     # (example, data is type float while fill_value is a
                     # string)
-                    if self.dtype != data.dtype:
-                        data = data.astype(self.dtype) # cast data, if necessary.
-                    data = data.filled(fill_value=fillval)
+                    try: 
+                        data.filled()
+                    except AttributeError:
+                        # workaround for bug in numpy 1.13.x
+                        # AttributeError:
+                        # 'MaskedConstant' object has no attribute '_fill_value'
+                        # when data contains a single numpy.ma.masked constant.
+                        data = numpy.array([fillval],self.dtype)
+                    else:
+                        if self.dtype != data.dtype:
+                            data = data.astype(self.dtype) # cast data, if necessary.
+                        data = data.filled(fill_value=fillval)
 
         # Fill output array with data chunks.
         for (a,b,c,i) in zip(start, count, stride, put_ind):

From 08389d2cd4dc9498b7bceafaaa6809523f76f3b0 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Thu, 18 Oct 2018 05:56:22 -0600
Subject: [PATCH 0147/1504] fix for numpy 1.9.2

---
 netCDF4/_netCDF4.pyx | 11 +++++++----
 1 file changed, 7 insertions(+), 4 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 9304ee99c..6d2ece2c9 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -4633,14 +4633,17 @@ cannot be safely cast to variable data type""" % attname
                     # cast to type of variable before filling (issue #850)
                     # otherwise 'filled' method may raise an error
                     # (example, data is type float while fill_value is a
-                    # string)
+                    # string).
                     try: 
                         data.filled()
-                    except AttributeError:
+                    except (AttributeError, ValueError):
                         # workaround for bug in numpy 1.13.x
-                        # AttributeError:
-                        # 'MaskedConstant' object has no attribute '_fill_value'
+                        # "AttributeError:
+                        # 'MaskedConstant' object has no attribute '_fill_value'"
                         # when data contains a single numpy.ma.masked constant.
+                        # older versions of numpy (1.9.2) raise "ValueError:
+                        # could not broadcast where mask from shape (1) into
+                        # shape ()"
                         data = numpy.array([fillval],self.dtype)
                     else:
                         if self.dtype != data.dtype:

From 9dc8a9c760521e3fa989ec2904032318fc4b0c15 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Thu, 18 Oct 2018 05:58:34 -0600
Subject: [PATCH 0148/1504] update

---
 netCDF4/_netCDF4.pyx | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 6d2ece2c9..7ef2af75c 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -4634,6 +4634,11 @@ cannot be safely cast to variable data type""" % attname
                     # otherwise 'filled' method may raise an error
                     # (example, data is type float while fill_value is a
                     # string).
+                    # this would probably also work
+                    #if data.shape == (1,) and data[0]==numpy.ma.masked:
+                    #    data = numpy.array([fillval],self.dtype)
+                    #else:
+                    #    data = data.filled(fill_value=fillval)
                     try: 
                         data.filled()
                     except (AttributeError, ValueError):

From aba1b17f396d9e768a09945da367f82eb5dabfb5 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Thu, 18 Oct 2018 06:04:35 -0600
Subject: [PATCH 0149/1504] update

---
 netCDF4/_netCDF4.pyx | 48 +++++++++++++++++++++++---------------------
 1 file changed, 25 insertions(+), 23 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 7ef2af75c..b78f60b3e 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -3486,8 +3486,8 @@ behavior is similar to Fortran or Matlab, but different than numpy.
             # set numpy char type to single char string (issue #850)
             # to avoid "TypeError: Cannot set fill value of string with
             # array of dtype float64" when filling masked array in __setitem__
-            if datatype.char == 'c':
-                datatype = numpy.dtype('S1')
+            #if datatype.char == 'c':
+            #    datatype = numpy.dtype('S1')
             self.dtype = datatype
         else:
             raise TypeError('illegal primitive data type, must be one of %s, got %s' % (_supportedtypes,datatype))
@@ -4630,30 +4630,32 @@ cannot be safely cast to variable data type""" % attname
                         fillval = self._FillValue
                     else:
                         fillval = default_fillvals[self.dtype.str[1:]]
-                    # cast to type of variable before filling (issue #850)
-                    # otherwise 'filled' method may raise an error
-                    # (example, data is type float while fill_value is a
-                    # string).
-                    # this would probably also work
-                    #if data.shape == (1,) and data[0]==numpy.ma.masked:
-                    #    data = numpy.array([fillval],self.dtype)
-                    #else:
-                    #    data = data.filled(fill_value=fillval)
-                    try: 
-                        data.filled()
-                    except (AttributeError, ValueError):
-                        # workaround for bug in numpy 1.13.x
-                        # "AttributeError:
-                        # 'MaskedConstant' object has no attribute '_fill_value'"
-                        # when data contains a single numpy.ma.masked constant.
-                        # older versions of numpy (1.9.2) raise "ValueError:
-                        # could not broadcast where mask from shape (1) into
-                        # shape ()"
+                    # some versions of numpy have trouble handling
+                    # MaskedConstants when filling - this is is 
+                    # a workaround (issue #850)
+                    if data.shape == (1,) and data[0]==numpy.ma.masked:
                         data = numpy.array([fillval],self.dtype)
                     else:
-                        if self.dtype != data.dtype:
-                            data = data.astype(self.dtype) # cast data, if necessary.
                         data = data.filled(fill_value=fillval)
+                    #try: 
+                    #    data.filled()
+                    #except (AttributeError, ValueError):
+                    #    # workaround for bug in numpy 1.13.x
+                    #    # "AttributeError:
+                    #    # 'MaskedConstant' object has no attribute '_fill_value'"
+                    #    # when data contains a single numpy.ma.masked constant.
+                    #    # older versions of numpy (1.9.2) raise "ValueError:
+                    #    # could not broadcast where mask from shape (1) into
+                    #    # shape ()"
+                    #    data = numpy.array([fillval],self.dtype)
+                    #else:
+                    #    # cast to type of variable before filling (issue #850)
+                    #    # otherwise 'filled' method may raise an error
+                    #    # (example, data is type float while fill_value is a
+                    #    # string).
+                    #    if self.dtype != data.dtype:
+                    #        data = data.astype(self.dtype) # cast data, if necessary.
+                    #    data = data.filled(fill_value=fillval)
 
         # Fill output array with data chunks.
         for (a,b,c,i) in zip(start, count, stride, put_ind):

From caa2ac5b7a42cb4c94f913bb5f1f0c32eccb0dfd Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Thu, 18 Oct 2018 07:49:26 -0600
Subject: [PATCH 0150/1504] update

---
 netCDF4/_netCDF4.pyx | 36 ++++++++++++++++--------------------
 1 file changed, 16 insertions(+), 20 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index b78f60b3e..28c4132b8 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -4633,29 +4633,25 @@ cannot be safely cast to variable data type""" % attname
                     # some versions of numpy have trouble handling
                     # MaskedConstants when filling - this is is 
                     # a workaround (issue #850)
-                    if data.shape == (1,) and data[0]==numpy.ma.masked:
+                    try: 
+                        data.filled()
+                    except (AttributeError, ValueError):
+                        # workaround for bug in numpy 1.13.x
+                        # "AttributeError:
+                        # 'MaskedConstant' object has no attribute '_fill_value'"
+                        # when data contains a single numpy.ma.masked constant.
+                        # older versions of numpy (1.9.2) raise "ValueError:
+                        # could not broadcast where mask from shape (1) into
+                        # shape ()"
                         data = numpy.array([fillval],self.dtype)
                     else:
+                        # cast to type of variable before filling (issue #850)
+                        # otherwise 'filled' method may raise an error
+                        # (example, data is type float while fill_value is a
+                        # string).
+                        #if self.dtype != data.dtype:
+                        #    data = data.astype(self.dtype) # cast data, if necessary.
                         data = data.filled(fill_value=fillval)
-                    #try: 
-                    #    data.filled()
-                    #except (AttributeError, ValueError):
-                    #    # workaround for bug in numpy 1.13.x
-                    #    # "AttributeError:
-                    #    # 'MaskedConstant' object has no attribute '_fill_value'"
-                    #    # when data contains a single numpy.ma.masked constant.
-                    #    # older versions of numpy (1.9.2) raise "ValueError:
-                    #    # could not broadcast where mask from shape (1) into
-                    #    # shape ()"
-                    #    data = numpy.array([fillval],self.dtype)
-                    #else:
-                    #    # cast to type of variable before filling (issue #850)
-                    #    # otherwise 'filled' method may raise an error
-                    #    # (example, data is type float while fill_value is a
-                    #    # string).
-                    #    if self.dtype != data.dtype:
-                    #        data = data.astype(self.dtype) # cast data, if necessary.
-                    #    data = data.filled(fill_value=fillval)
 
         # Fill output array with data chunks.
         for (a,b,c,i) in zip(start, count, stride, put_ind):

From 51293b36f5b25aade6c6b4831243b91d69ada116 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Thu, 18 Oct 2018 07:53:35 -0600
Subject: [PATCH 0151/1504] revert to full workaround (should work for all
 supported numpy versions)

---
 netCDF4/_netCDF4.pyx | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 28c4132b8..22ff057c8 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -3486,8 +3486,8 @@ behavior is similar to Fortran or Matlab, but different than numpy.
             # set numpy char type to single char string (issue #850)
             # to avoid "TypeError: Cannot set fill value of string with
             # array of dtype float64" when filling masked array in __setitem__
-            #if datatype.char == 'c':
-            #    datatype = numpy.dtype('S1')
+            if datatype.char == 'c':
+                datatype = numpy.dtype('S1')
             self.dtype = datatype
         else:
             raise TypeError('illegal primitive data type, must be one of %s, got %s' % (_supportedtypes,datatype))
@@ -4649,8 +4649,8 @@ cannot be safely cast to variable data type""" % attname
                         # otherwise 'filled' method may raise an error
                         # (example, data is type float while fill_value is a
                         # string).
-                        #if self.dtype != data.dtype:
-                        #    data = data.astype(self.dtype) # cast data, if necessary.
+                        if self.dtype != data.dtype:
+                            data = data.astype(self.dtype) # cast data, if necessary.
                         data = data.filled(fill_value=fillval)
 
         # Fill output array with data chunks.

From 6b970dc3300007467bfd33a0151caf93faaf7b9f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Thu, 18 Oct 2018 10:21:43 -0600
Subject: [PATCH 0152/1504] apply try/except only for single element masked
 array containing MaskedConstant

---
 netCDF4/_netCDF4.pyx | 29 +++++++++++++++++------------
 1 file changed, 17 insertions(+), 12 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 22ff057c8..c5f41a40d 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -4633,22 +4633,27 @@ cannot be safely cast to variable data type""" % attname
                     # some versions of numpy have trouble handling
                     # MaskedConstants when filling - this is is 
                     # a workaround (issue #850)
-                    try: 
-                        data.filled()
-                    except (AttributeError, ValueError):
-                        # workaround for bug in numpy 1.13.x
-                        # "AttributeError:
-                        # 'MaskedConstant' object has no attribute '_fill_value'"
-                        # when data contains a single numpy.ma.masked constant.
-                        # older versions of numpy (1.9.2) raise "ValueError:
-                        # could not broadcast where mask from shape (1) into
-                        # shape ()"
-                        data = numpy.array([fillval],self.dtype)
-                    else:
+                    data_filled = False
+                    if data.shape == (1,) and data[0] == numpy.ma.masked:
+                        try:
+                            data.filled()
+                        except (AttributeError, ValueError):
+                            # workaround for bug in numpy 1.13.x
+                            # "AttributeError:
+                            # 'MaskedConstant' object has no attribute '_fill_value'"
+                            # when data contains a single numpy.ma.masked constant.
+                            # older versions of numpy (1.9.2) raise "ValueError:
+                            # could not broadcast where mask from shape (1) into
+                            # shape ()"
+                            data = numpy.array([fillval],self.dtype)
+                            data_filled = True
+                    if not data_filled:
                         # cast to type of variable before filling (issue #850)
                         # otherwise 'filled' method may raise an error
                         # (example, data is type float while fill_value is a
                         # string).
+                        # fillval is guaranteed to have variable type here,
+                        # masked array is not.
                         if self.dtype != data.dtype:
                             data = data.astype(self.dtype) # cast data, if necessary.
                         data = data.filled(fill_value=fillval)

From 732eef24b5659684ae0ea0c509872131ab62e750 Mon Sep 17 00:00:00 2001
From: "Jeffrey.S.Whitaker" 
Date: Thu, 18 Oct 2018 13:59:21 -0400
Subject: [PATCH 0153/1504] update

---
 netCDF4/_netCDF4.pyx | 28 +++++++++++++---------------
 1 file changed, 13 insertions(+), 15 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index c5f41a40d..ea9688cea 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -4633,21 +4633,19 @@ cannot be safely cast to variable data type""" % attname
                     # some versions of numpy have trouble handling
                     # MaskedConstants when filling - this is is 
                     # a workaround (issue #850)
-                    data_filled = False
-                    if data.shape == (1,) and data[0] == numpy.ma.masked:
-                        try:
-                            data.filled()
-                        except (AttributeError, ValueError):
-                            # workaround for bug in numpy 1.13.x
-                            # "AttributeError:
-                            # 'MaskedConstant' object has no attribute '_fill_value'"
-                            # when data contains a single numpy.ma.masked constant.
-                            # older versions of numpy (1.9.2) raise "ValueError:
-                            # could not broadcast where mask from shape (1) into
-                            # shape ()"
-                            data = numpy.array([fillval],self.dtype)
-                            data_filled = True
-                    if not data_filled:
+                    try:
+                        data.filled()
+                    except (AttributeError, ValueError):
+                       # workaround for bug in numpy 1.13.x
+                       # "AttributeError:
+                       # 'MaskedConstant' object has no attribute '_fill_value'"
+                       # when data contains a single numpy.ma.masked constant.
+                       # older versions of numpy (1.9.2) raise "ValueError:
+                       # could not broadcast where mask from shape (1) into
+                       # shape ()"
+                       data = numpy.array([fillval],self.dtype)
+                       data_filled = True
+                    else:
                         # cast to type of variable before filling (issue #850)
                         # otherwise 'filled' method may raise an error
                         # (example, data is type float while fill_value is a

From 14b6e3ffdc0912462745e63b07e046b84dfd5452 Mon Sep 17 00:00:00 2001
From: "Jeffrey.S.Whitaker" 
Date: Thu, 18 Oct 2018 14:24:09 -0400
Subject: [PATCH 0154/1504] make sure we are catching the relevant exception

---
 netCDF4/_netCDF4.pyx | 7 +++++--
 1 file changed, 5 insertions(+), 2 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index ea9688cea..99d4a4534 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -4643,8 +4643,11 @@ cannot be safely cast to variable data type""" % attname
                        # older versions of numpy (1.9.2) raise "ValueError:
                        # could not broadcast where mask from shape (1) into
                        # shape ()"
-                       data = numpy.array([fillval],self.dtype)
-                       data_filled = True
+                       if data.shape == (1,) and data.mask.all():
+                           data = numpy.array([fillval],self.dtype)
+                       else:
+                           msg='error converting masked array to numpy ndarray'
+                           raise ValueError(msg)
                     else:
                         # cast to type of variable before filling (issue #850)
                         # otherwise 'filled' method may raise an error

From 834b77797a3f702c49403a88150238edcddbfa0d Mon Sep 17 00:00:00 2001
From: "Jeffrey.S.Whitaker" 
Date: Thu, 18 Oct 2018 14:45:08 -0400
Subject: [PATCH 0155/1504] greatly simplify workaround for numpy.ma bugs in
 issue #850

---
 netCDF4/_netCDF4.pyx | 31 ++-----------------------------
 1 file changed, 2 insertions(+), 29 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 99d4a4534..73aa07d68 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -3482,12 +3482,6 @@ behavior is similar to Fortran or Matlab, but different than numpy.
             # find netCDF primitive data type corresponding to
             # specified numpy data type.
             xtype = _nptonctype[datatype.str[1:]]
-            # dtype variable attribute is a numpy datatype object.
-            # set numpy char type to single char string (issue #850)
-            # to avoid "TypeError: Cannot set fill value of string with
-            # array of dtype float64" when filling masked array in __setitem__
-            if datatype.char == 'c':
-                datatype = numpy.dtype('S1')
             self.dtype = datatype
         else:
             raise TypeError('illegal primitive data type, must be one of %s, got %s' % (_supportedtypes,datatype))
@@ -4633,30 +4627,9 @@ cannot be safely cast to variable data type""" % attname
                     # some versions of numpy have trouble handling
                     # MaskedConstants when filling - this is is 
                     # a workaround (issue #850)
-                    try:
-                        data.filled()
-                    except (AttributeError, ValueError):
-                       # workaround for bug in numpy 1.13.x
-                       # "AttributeError:
-                       # 'MaskedConstant' object has no attribute '_fill_value'"
-                       # when data contains a single numpy.ma.masked constant.
-                       # older versions of numpy (1.9.2) raise "ValueError:
-                       # could not broadcast where mask from shape (1) into
-                       # shape ()"
-                       if data.shape == (1,) and data.mask.all():
-                           data = numpy.array([fillval],self.dtype)
-                       else:
-                           msg='error converting masked array to numpy ndarray'
-                           raise ValueError(msg)
+                    if data.shape == (1,) and data.mask.all():
+                        data = numpy.array([fillval],self.dtype)
                     else:
-                        # cast to type of variable before filling (issue #850)
-                        # otherwise 'filled' method may raise an error
-                        # (example, data is type float while fill_value is a
-                        # string).
-                        # fillval is guaranteed to have variable type here,
-                        # masked array is not.
-                        if self.dtype != data.dtype:
-                            data = data.astype(self.dtype) # cast data, if necessary.
                         data = data.filled(fill_value=fillval)
 
         # Fill output array with data chunks.

From 0e0a544e980725ad0a9d8ebead2f6139fb50d7c3 Mon Sep 17 00:00:00 2001
From: "Jeffrey.S.Whitaker" 
Date: Thu, 18 Oct 2018 14:46:16 -0400
Subject: [PATCH 0156/1504] re-insert missing comment

---
 netCDF4/_netCDF4.pyx | 1 +
 1 file changed, 1 insertion(+)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 73aa07d68..a1b211413 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -3482,6 +3482,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
             # find netCDF primitive data type corresponding to
             # specified numpy data type.
             xtype = _nptonctype[datatype.str[1:]]
+            # dtype variable attribute is a numpy datatype object.
             self.dtype = datatype
         else:
             raise TypeError('illegal primitive data type, must be one of %s, got %s' % (_supportedtypes,datatype))

From eb5fae487c5a52f8e8842b39208cfd1244cc389c Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 22 Oct 2018 13:35:30 -0600
Subject: [PATCH 0157/1504] small tweak to test to avoid failure due to
 roundoff errors

---
 test/tst_netcdftime.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/tst_netcdftime.py b/test/tst_netcdftime.py
index 0ea54ea5a..95d2de4bf 100644
--- a/test/tst_netcdftime.py
+++ b/test/tst_netcdftime.py
@@ -434,7 +434,7 @@ def runTest(self):
             pass
         # this should not fail (year zero allowed in 'fake' calendars)
         t = date2num(datetime(1, 1, 1), units, calendar='360_day')
-        self.assertEqual(t, 360)
+        self.assertAlmostEqual(t, 360)
         d = num2date(t, units, calendar='360_day')
         self.assertEqual(d, Datetime360Day(1,1,1))
         d = num2date(0, units, calendar='360_day')

From 7f9f7c01faac5c46c125ceb9803c88d3e8af84de Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 22 Oct 2018 20:43:44 -0600
Subject: [PATCH 0158/1504] prepare for v1.4.2 release

---
 Changelog | 2 +-
 README.md | 2 ++
 2 files changed, 3 insertions(+), 1 deletion(-)

diff --git a/Changelog b/Changelog
index c7aea16db..8f765e875 100644
--- a/Changelog
+++ b/Changelog
@@ -1,4 +1,4 @@
- version 1.4.2 (not yet released)
+ version 1.4.2 (tag v1.4.2rel)
 =============================
  * add get_dims Variable method (issue #824)
  * make sure format keyword not ignored when mode is 'ws' (issue #827)
diff --git a/README.md b/README.md
index fa06d0199..5b39f3e33 100644
--- a/README.md
+++ b/README.md
@@ -8,6 +8,8 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
+10/26/2018: Version [1.4.2](https://pypi.python.org/pypi/netCDF4/1.4.2) released. Minor bugfixes, added `Variable.get_dims()` method and `master_file` kwarg for `MFDataset.__init__`.
+
 08/10/2018: Version [1.4.1](https://pypi.python.org/pypi/netCDF4/1.4.1) released. The old slicing behavior
 (numpy array returned unless missing values are present, otherwise masked array returned) is renabled
 via `set_always_mask(False)`.

From 89a551e9b1a79c62b250fa21e2ef0acd1b2d253c Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 22 Oct 2018 20:53:02 -0600
Subject: [PATCH 0159/1504] update docs

---
 docs/netCDF4/index.html | 4 ++--
 netCDF4/_netCDF4.pyx    | 3 ++-
 2 files changed, 4 insertions(+), 3 deletions(-)

diff --git a/docs/netCDF4/index.html b/docs/netCDF4/index.html
index 6ff71385f..23a2cbafd 100644
--- a/docs/netCDF4/index.html
+++ b/docs/netCDF4/index.html
@@ -1299,7 +1299,7 @@ 
    Download
    
 
  • Latest bleeding-edge code from the 
    github repository.
    • 
 
  • Latest releases
-   (source code and windows installers).
    • 
+   (source code and binary installers).
 
 
    Requires
    
 
      
@@ -5663,7 +5663,7 @@ 
      Methods
      
             
   
      
     
      
-    
      def __init__(
      self, files, check=False, aggdim=None, exclude=[])
      
+    
      def __init__(
      self, files, check=False, aggdim=None, exclude=[], master_file=None)
      
     
      
     
     
      
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 7df2a7920..350c91fb0 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -5843,7 +5843,8 @@ Example usage (See `netCDF4.MFDataset.__init__` for more details):
     def __init__(self, files, check=False, aggdim=None, exclude=[],
             master_file=None):
         """
-        **`__init__(self, files, check=False, aggdim=None, exclude=[])`**
+        **`__init__(self, files, check=False, aggdim=None, exclude=[],
+        master_file=None)`**
 
         Open a Dataset spanning multiple files, making it look as if it was a
         single file. Variables in the list of files that share the same

From 882afeb0ce9f3279f337ef49ed6ba9601d92054e Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Thu, 1 Nov 2018 14:48:57 -0600
Subject: [PATCH 0160/1504] make set_always_mask work in MFDataset

---
 Changelog            | 4 ++++
 netCDF4/_netCDF4.pyx | 8 ++++++++
 2 files changed, 12 insertions(+)

diff --git a/Changelog b/Changelog
index 8f765e875..aa4b001af 100644
--- a/Changelog
+++ b/Changelog
@@ -1,3 +1,7 @@
+ since version 1.4.2
+=============================
+ * make set_always_mask work in MFDataset.
+
  version 1.4.2 (tag v1.4.2rel)
 =============================
  * add get_dims Variable method (issue #824)
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 350c91fb0..5b2e79c90 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2830,6 +2830,10 @@ shall be applied for all variables.
 after calling this function will follow the default behaviour.
         """
 
+        # this is a hack to make inheritance work in MFDataset
+        # (which stores variables in _vars)
+        _vars = self.variables
+        if _vars is None: _vars = self._vars
         for var in self.variables.values():
             var.set_auto_mask(value)
 
@@ -2881,6 +2885,10 @@ variables. Variables created after calling this function will follow
 the default behaviour.
         """
 
+        # this is a hack to make inheritance work in MFDataset
+        # (which stores variables in _vars)
+        _vars = self.variables
+        if _vars is None: _vars = self._vars
         for var in self.variables.values():
             var.set_always_mask(value)
 

From a301404d52a602142834b1fae24a8036e2992341 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Thu, 1 Nov 2018 15:14:09 -0600
Subject: [PATCH 0161/1504] add test

---
 netCDF4/_netCDF4.pyx  | 7 +++++--
 test/tst_multifile.py | 1 +
 2 files changed, 6 insertions(+), 2 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 5b2e79c90..68ec7a774 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2834,7 +2834,7 @@ after calling this function will follow the default behaviour.
         # (which stores variables in _vars)
         _vars = self.variables
         if _vars is None: _vars = self._vars
-        for var in self.variables.values():
+        for var in self._vars.values():
             var.set_auto_mask(value)
 
         for groups in _walk_grps(self):
@@ -2889,7 +2889,7 @@ the default behaviour.
         # (which stores variables in _vars)
         _vars = self.variables
         if _vars is None: _vars = self._vars
-        for var in self.variables.values():
+        for var in self._vars.values():
             var.set_always_mask(value)
 
         for groups in _walk_grps(self):
@@ -6174,6 +6174,9 @@ class _Variable(object):
     def set_auto_scale(self,val):
         for v in self._recVar:
             v.set_auto_scale(val)
+    def set_always_mask(self,val):
+        for v in self._recVar:
+            v.set_always_mask(val)
     def __getitem__(self, elem):
         """Get records from a concatenated set of variables."""
 
diff --git a/test/tst_multifile.py b/test/tst_multifile.py
index 412721e5c..770281ee4 100644
--- a/test/tst_multifile.py
+++ b/test/tst_multifile.py
@@ -47,6 +47,7 @@ def runTest(self):
         """testing multi-file dataset access"""
         f = MFDataset(self.files,check=True)
         f.set_auto_maskandscale(True) # issue570
+        f.set_always_mask(False)
         assert f.history == 'created today'
         assert_array_equal(np.arange(0,nx),f.variables['x'][:])
         varin = f.variables['data']

From 56a467a4c3a70d601907265d1b593920444c13b8 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Thu, 1 Nov 2018 15:23:28 -0600
Subject: [PATCH 0162/1504] fix bug in previous commit

---
 netCDF4/_netCDF4.pyx | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 68ec7a774..1d84ab67d 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2834,7 +2834,7 @@ after calling this function will follow the default behaviour.
         # (which stores variables in _vars)
         _vars = self.variables
         if _vars is None: _vars = self._vars
-        for var in self._vars.values():
+        for var in _vars.values():
             var.set_auto_mask(value)
 
         for groups in _walk_grps(self):
@@ -2889,7 +2889,7 @@ the default behaviour.
         # (which stores variables in _vars)
         _vars = self.variables
         if _vars is None: _vars = self._vars
-        for var in self._vars.values():
+        for var in _vars.values():
             var.set_always_mask(value)
 
         for groups in _walk_grps(self):

From 43ac0ad9060c723ee5d5fe3e6c131a0683dc7f1c Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 7 Nov 2018 06:49:47 -0700
Subject: [PATCH 0163/1504] run opendap test first from run_all.py (issue #856)

---
 test/run_all.py | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/test/run_all.py b/test/run_all.py
index f06590cff..82b505e95 100755
--- a/test/run_all.py
+++ b/test/run_all.py
@@ -29,6 +29,12 @@
 if os.getenv('NO_NET'):
     test_files.remove('tst_dap.py');
     sys.stdout.write('not running tst_dap.py ...\n')
+else:
+    # run opendap test first (issue #856).
+    test_files.remove('tst_dap.py')
+    test_files.insert(0,'tst_dap.py')
+    print(test_files)
+
 
 # Build the test suite from the tests found in the test files.
 testsuite = unittest.TestSuite()

From dcf701552056a803734710f8648e039fbedfd056 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 7 Nov 2018 06:53:31 -0700
Subject: [PATCH 0164/1504] remove debug print

---
 test/run_all.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/test/run_all.py b/test/run_all.py
index 82b505e95..036b6ce92 100755
--- a/test/run_all.py
+++ b/test/run_all.py
@@ -33,7 +33,6 @@
     # run opendap test first (issue #856).
     test_files.remove('tst_dap.py')
     test_files.insert(0,'tst_dap.py')
-    print(test_files)
 
 
 # Build the test suite from the tests found in the test files.

From a9ba55620c2f661054810f28f6b5fcf3e9a3f060 Mon Sep 17 00:00:00 2001
From: Trevor Wennblom 
Date: Wed, 14 Nov 2018 11:35:24 -0600
Subject: [PATCH 0165/1504] writing_netCDF.ipynb documentation updates

---
 examples/writing_netCDF.ipynb | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/examples/writing_netCDF.ipynb b/examples/writing_netCDF.ipynb
index 4f2d7dd1d..2e2fef5ef 100644
--- a/examples/writing_netCDF.ipynb
+++ b/examples/writing_netCDF.ipynb
@@ -374,7 +374,7 @@
    "source": [
     "## Writing data\n",
     "\n",
-    "To write data a netCDF variable object, just treat it like a numpy array and assign values to a slice."
+    "To write data to a netCDF variable object, just treat it like a numpy array and assign values to a slice."
    ]
   },
   {
@@ -1175,10 +1175,10 @@
    "source": [
     "##Other interesting and useful projects using netcdf4-python\n",
     "\n",
-    "- [Xray](http://xray.readthedocs.org/en/stable/): N-dimensional variant of the core [pandas](http://pandas.pydata.org) data structure that can operate on netcdf variables.\n",
-    "- [Iris](http://scitools.org.uk/iris/): a data model to create a data abstraction layer which isolates analysis and visualisation code from data format specifics.  Uses netcdf4-python to access netcdf data (can also handle GRIB).\n",
-    "- [Biggus](https://github.com/SciTools/biggus): Virtual large arrays (from netcdf variables) with lazy evaluation.\n",
-    "- [cf-python](http://cfpython.bitbucket.org/): Implements the [CF](http://cfconventions.org) data model for the reading, writing and processing of data and metadata. "
+    "- [xarray](https://xarray.pydata.org/en/stable/): N-dimensional variant of the core [pandas](https://pandas.pydata.org) data structure that can operate on netcdf variables.\n",
+    "- [Iris](https://scitools.org.uk/iris/docs/latest/): a data model to create a data abstraction layer which isolates analysis and visualisation code from data format specifics.  Uses netcdf4-python to access netcdf data (can also handle GRIB).\n",
+    "- [Dask](https://dask.org/): Virtual large arrays (from netcdf variables) with lazy evaluation.\n",
+    "- [cf-python](https://cfpython.bitbucket.io/): Implements the [CF](http://cfconventions.org) data model for the reading, writing and processing of data and metadata. "
    ]
   }
  ],

From 85c6b5163791026aff05b75334808a29dea176d4 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Thu, 20 Dec 2018 16:19:18 -0700
Subject: [PATCH 0166/1504] fix so test passes with cftime master

---
 test/tst_netcdftime.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/test/tst_netcdftime.py b/test/tst_netcdftime.py
index 95d2de4bf..99be101d3 100644
--- a/test/tst_netcdftime.py
+++ b/test/tst_netcdftime.py
@@ -887,8 +887,8 @@ def test_replace(self):
         self.assertEqual(self.date1_365_day.replace(minute=3).minute, 3)
         self.assertEqual(self.date1_365_day.replace(second=3).second, 3)
         self.assertEqual(self.date1_365_day.replace(microsecond=3).microsecond, 3)
-        self.assertEqual(self.date1_365_day.replace(dayofwk=3).dayofwk, 3)
-        self.assertEqual(self.date1_365_day.replace(dayofyr=3).dayofyr, 3)
+        #self.assertEqual(self.date1_365_day.replace(dayofwk=3).dayofwk, 3)
+        #self.assertEqual(self.date1_365_day.replace(dayofyr=3).dayofyr, 3)
 
     def test_pickling(self):
         "Test reversibility of pickling."

From 11a1cf83d6bb6bd58b91fa2b2a3402cdd7ed87b7 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Thu, 20 Dec 2018 18:57:36 -0700
Subject: [PATCH 0167/1504] back off libnetcdf to 4.6.1 to see if this fixes
 failing tests

---
 .appveyor.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.appveyor.yml b/.appveyor.yml
index b8a9521dd..86046764a 100644
--- a/.appveyor.yml
+++ b/.appveyor.yml
@@ -33,7 +33,7 @@ install:
   - cmd: conda.exe install conda-build vs2008_express_vc_python_patch
   - cmd: call setup_x64
 
-  - cmd: conda.exe create --name TEST python=%PY% numpy=%NPY% cython pip pytest hdf5 libnetcdf cftime
+  - cmd: conda.exe create --name TEST python=%PY% numpy=%NPY% cython pip pytest hdf5 libnetcdf=4.6.1 cftime
   - cmd: conda activate TEST
 
   - cmd: conda.exe info --all

From 40704ffdd7cd7d91ff8447cd675aea227d4c9f34 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Thu, 20 Dec 2018 20:18:15 -0700
Subject: [PATCH 0168/1504] 4.6.1 works, change back to 4.6.2

---
 .appveyor.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.appveyor.yml b/.appveyor.yml
index 86046764a..b8a9521dd 100644
--- a/.appveyor.yml
+++ b/.appveyor.yml
@@ -33,7 +33,7 @@ install:
   - cmd: conda.exe install conda-build vs2008_express_vc_python_patch
   - cmd: call setup_x64
 
-  - cmd: conda.exe create --name TEST python=%PY% numpy=%NPY% cython pip pytest hdf5 libnetcdf=4.6.1 cftime
+  - cmd: conda.exe create --name TEST python=%PY% numpy=%NPY% cython pip pytest hdf5 libnetcdf cftime
   - cmd: conda activate TEST
 
   - cmd: conda.exe info --all

From c095414e28acf33be9138b924cb3231df5c2ba9f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 21 Dec 2018 08:49:23 -0700
Subject: [PATCH 0169/1504] add NC_PERSIST flag for 4.6.2 (fixes failing
 tst_diskless)

---
 netCDF4/_netCDF4.pyx | 11 +++++++++--
 1 file changed, 9 insertions(+), 2 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 1d84ab67d..090224e6f 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1235,6 +1235,11 @@ is_native_big = numpy.dtype('>f4').byteorder == '='
 # hard code these here, instead of importing from netcdf.h
 # so it will compile with versions <= 4.2.
 NC_DISKLESS = 0x0008
+# introduced in 4.6.2
+if __netcdf4libversion__[0:5] >= "4.6.2":
+    NC_PERSIST = 0x4000
+else:  # prior to 4.6.2 this flag doesn't work, so make the same as NC_DISKLESS
+    NC_PERSIST = 0x0008
 
 # next two lines do nothing, preserved for backwards compatibility.
 default_encoding = 'utf-8' 
@@ -2024,7 +2029,8 @@ references to the parent Dataset or Group.
                         pass
                 elif diskless:
                     if persist:
-                        ierr = nc_create(path, NC_WRITE | NC_CLOBBER | NC_DISKLESS , &grpid)
+                        ierr = nc_create(path, NC_WRITE | NC_CLOBBER |
+                                NC_DISKLESS | NC_PERSIST, &grpid)
                     else:
                         ierr = nc_create(path, NC_CLOBBER | NC_DISKLESS , &grpid)
                 else:
@@ -2038,7 +2044,8 @@ references to the parent Dataset or Group.
                         pass
                 elif diskless:
                     if persist:
-                        ierr = nc_create(path, NC_WRITE | NC_NOCLOBBER | NC_DISKLESS , &grpid)
+                        ierr = nc_create(path, NC_WRITE | NC_NOCLOBBER |
+                                NC_DISKLESS | NC_PERSIST , &grpid)
                     else:
                         ierr = nc_create(path, NC_NOCLOBBER | NC_DISKLESS , &grpid)
                 else:

From abae393b9739efaa3b3a7645fc631ca82f30fb5f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 21 Dec 2018 13:01:45 -0700
Subject: [PATCH 0170/1504] update

---
 netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 090224e6f..cf50b3ecf 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1239,7 +1239,7 @@ NC_DISKLESS = 0x0008
 if __netcdf4libversion__[0:5] >= "4.6.2":
     NC_PERSIST = 0x4000
 else:  # prior to 4.6.2 this flag doesn't work, so make the same as NC_DISKLESS
-    NC_PERSIST = 0x0008
+    NC_PERSIST = NC_DISKLESS
 
 # next two lines do nothing, preserved for backwards compatibility.
 default_encoding = 'utf-8' 

From 8f0f77155399e132d2dece2651e0054908249a54 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 24 Dec 2018 12:06:49 -0700
Subject: [PATCH 0171/1504] update

---
 Changelog | 1 +
 1 file changed, 1 insertion(+)

diff --git a/Changelog b/Changelog
index aa4b001af..ace802956 100644
--- a/Changelog
+++ b/Changelog
@@ -1,6 +1,7 @@
  since version 1.4.2
 =============================
  * make set_always_mask work in MFDataset.
+ * fix saving diskless files to disk with netcdf-c >= 4.6.2.
 
  version 1.4.2 (tag v1.4.2rel)
 =============================

From 4374b988aadb7e2ca69e5ae5b889bef360a87093 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 26 Jan 2019 14:54:15 -0700
Subject: [PATCH 0172/1504] initial work on exposing
 nc_create_mem/nc_close_memio

---
 include/netCDF4.pxi  |   9 ++++
 netCDF4/_netCDF4.pyx | 100 +++++++++++++++++++++++++++++--------------
 setup.py             |  21 ++++++++-
 3 files changed, 97 insertions(+), 33 deletions(-)

diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index 9a850d93e..3b8cde18e 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -694,6 +694,15 @@ IF HAS_NC_OPEN_MEM:
     cdef extern from "netcdf_mem.h":
         int nc_open_mem(const char *path, int mode, size_t size, void* memory, int *ncidp)
 
+IF HAS_NC_CREATE_MEM:
+    cdef extern from "netcdf_mem.h":
+        int nc_create_mem(const char *path, int mode, size_t initialize, int *ncidp);
+        ctypedef struct NC_memio:
+            size_t size
+            void* memory
+            int flags
+        int nc_close_memio(int ncid, NC_memio* info);
+
 IF HAS_NC_PAR:
     cdef extern from "mpi-compat.h": pass
     cdef extern from "netcdf_par.h":
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index cf50b3ecf..bf3df2207 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1086,6 +1086,7 @@ PERFORMANCE OF THIS SOFTWARE.
 # Make changes to this file, not the c-wrappers that Cython generates.
 from cpython.mem cimport PyMem_Malloc, PyMem_Free
 from cpython.buffer cimport PyObject_GetBuffer, PyBuffer_Release, PyBUF_SIMPLE, PyBUF_ANY_CONTIGUOUS
+from cpython.bytes cimport PyBytes_FromStringAndSize
 
 # pure python utilities
 from .utils import (_StartCountStride, _quantize, _find_dim, _walk_grps,
@@ -1979,6 +1980,7 @@ references to the parent Dataset or Group.
         means MPI_INFO_NULL will be used.  Ignored if `parallel=False`.
         """
         cdef int grpid, ierr, numgrps, numdims, numvars
+        cdef size_t initialsize
         cdef char *path
         cdef char namstring[NC_MAX_NAME+1]
         IF HAS_NC_PAR:
@@ -1999,8 +2001,8 @@ references to the parent Dataset or Group.
         bytestr = _strencode(_tostr(filename), encoding=encoding)
         path = bytestr
 
-        if memory is not None and (mode != 'r' or type(memory) != bytes):
-            raise ValueError('memory mode only works with \'r\' modes and must be `bytes`')
+        #if memory is not None and (mode != 'r' or type(memory) != bytes):
+        #    raise ValueError('memory mode only works with \'r\' modes and must be `bytes`')
         if parallel:
             IF HAS_NC_PAR != 1:
                 msg='parallel mode requires MPI enabled netcdf-c'
@@ -2018,38 +2020,52 @@ references to the parent Dataset or Group.
                 else:
                     mpiinfo = MPI_INFO_NULL
 
+        self._inmemory = False
         if mode == 'w':
             _set_default_format(format=format)
-            if clobber:
-                if parallel:
-                    IF HAS_NC_PAR:
-                        ierr = nc_create_par(path, NC_CLOBBER | NC_MPIIO, \
-                               mpicomm, mpiinfo, &grpid)
-                    ELSE:
-                        pass
-                elif diskless:
-                    if persist:
-                        ierr = nc_create(path, NC_WRITE | NC_CLOBBER |
-                                NC_DISKLESS | NC_PERSIST, &grpid)
-                    else:
-                        ierr = nc_create(path, NC_CLOBBER | NC_DISKLESS , &grpid)
-                else:
-                    ierr = nc_create(path, NC_CLOBBER, &grpid)
+            if memory is not None:
+                # if memory is not None and mode='w', memory
+                # kwarg is interpreted as advisory size.
+                IF HAS_NC_CREATE_MEM:
+                   initialsize = memory
+                   ierr = nc_create_mem(path, 0, initialsize, &grpid)
+                   self._inmemory = True # checked in close method
+                ELSE:
+                    msg = """
+        nc_create_mem functionality not enabled.  To enable, install Cython, make sure you have
+        version 4.6.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
+                    raise ValueError(msg)
             else:
-                if parallel:
-                    IF HAS_NC_PAR:
-                        ierr = nc_create_par(path, NC_NOCLOBBER | NC_MPIIO, \
-                               mpicomm, mpiinfo, &grpid)
-                    ELSE:
-                        pass
-                elif diskless:
-                    if persist:
-                        ierr = nc_create(path, NC_WRITE | NC_NOCLOBBER |
-                                NC_DISKLESS | NC_PERSIST , &grpid)
+                if clobber:
+                    if parallel:
+                        IF HAS_NC_PAR:
+                            ierr = nc_create_par(path, NC_CLOBBER | NC_MPIIO, \
+                                   mpicomm, mpiinfo, &grpid)
+                        ELSE:
+                            pass
+                    elif diskless:
+                        if persist:
+                            ierr = nc_create(path, NC_WRITE | NC_CLOBBER |
+                                    NC_DISKLESS | NC_PERSIST, &grpid)
+                        else:
+                            ierr = nc_create(path, NC_CLOBBER | NC_DISKLESS , &grpid)
                     else:
-                        ierr = nc_create(path, NC_NOCLOBBER | NC_DISKLESS , &grpid)
+                        ierr = nc_create(path, NC_CLOBBER, &grpid)
                 else:
-                    ierr = nc_create(path, NC_NOCLOBBER, &grpid)
+                    if parallel:
+                        IF HAS_NC_PAR:
+                            ierr = nc_create_par(path, NC_NOCLOBBER | NC_MPIIO, \
+                                   mpicomm, mpiinfo, &grpid)
+                        ELSE:
+                            pass
+                    elif diskless:
+                        if persist:
+                            ierr = nc_create(path, NC_WRITE | NC_NOCLOBBER |
+                                    NC_DISKLESS | NC_PERSIST , &grpid)
+                        else:
+                            ierr = nc_create(path, NC_NOCLOBBER | NC_DISKLESS , &grpid)
+                    else:
+                        ierr = nc_create(path, NC_NOCLOBBER, &grpid)
             # reset default format to netcdf3 - this is a workaround
             # for issue 170 (nc_open'ing a DAP dataset after switching
             # format to NETCDF4). This bug should be fixed in version
@@ -2068,7 +2084,7 @@ references to the parent Dataset or Group.
                     ierr = nc_open_mem(path, 0, self._buffer.len, self._buffer.buf, &grpid)
                 ELSE:
                     msg = """
-        nc_open_mem method not enabled.  To enable, install Cython, make sure you have
+        nc_open_mem functionality not enabled.  To enable, install Cython, make sure you have
         version 4.4.1 or higher of the netcdf C lib, and rebuild netcdf4-python."""
                     raise ValueError(msg)
             elif parallel:
@@ -2273,6 +2289,25 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
         # view.obj is checked, ref on obj is decremented and obj will be null'd out
         PyBuffer_Release(&self._buffer)
 
+    def _close_mem(self, check_err):
+        cdef NC_memio memio
+        cdef int ierr
+
+        ierr = nc_close_memio(self._grpid, &memio)
+
+        if check_err:
+            _ensure_nc_success(ierr)
+
+        self._isopen = 0 # indicates file already closed, checked by __dealloc__
+
+        # Only release buffer if close succeeded
+        # per impl of PyBuffer_Release: https://github.com/python/cpython/blob/master/Objects/abstract.c#L667
+        # view.obj is checked, ref on obj is decremented and obj will be null'd out
+        PyBuffer_Release(&self._buffer)
+
+        # return bytes representing in-memory dataset
+        return PyBytes_FromStringAndSize(memio.memory, memio.size)
+
 
     def close(self):
         """
@@ -2280,7 +2315,10 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
 
 Close the Dataset.
         """
-        self._close(True)
+        if self._inmemory:
+            memory = self._close_mem(True)
+        else:
+            self._close(True)
 
     def isopen(self):
         """
diff --git a/setup.py b/setup.py
index c61045889..380c1fc58 100644
--- a/setup.py
+++ b/setup.py
@@ -55,6 +55,7 @@ def check_api(inc_dirs):
     has_nc_inq_format_extended = False
     has_cdf5_format = False
     has_nc_open_mem = False
+    has_nc_create_mem = False
     has_nc_par = False
 
     for d in inc_dirs:
@@ -76,6 +77,15 @@ def check_api(inc_dirs):
             if line.startswith('#define NC_FORMAT_64BIT_DATA'):
                 has_cdf5_format = True
 
+        if has_nc_open_mem:
+            try:
+                f = open(os.path.join(d, 'netcdf_mem.h'), **open_kwargs)
+            except IOError:
+                continue
+            for line in f:
+                if line.startswith('EXTERNL int nc_create_mem'):
+                    has_nc_create_mem = True
+
         ncmetapath = os.path.join(d,'netcdf_meta.h')
         if os.path.exists(ncmetapath):
             for line in open(ncmetapath):
@@ -84,7 +94,7 @@ def check_api(inc_dirs):
         break
 
     return has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \
-           has_cdf5_format, has_nc_open_mem, has_nc_par
+           has_cdf5_format, has_nc_open_mem, has_nc_create_mem, has_nc_par
 
 
 def getnetcdfvers(libdirs):
@@ -478,7 +488,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
             os.remove(netcdf4_src_c)
     # this determines whether renameGroup and filepath methods will work.
     has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \
-        has_cdf5_format, has_nc_open_mem, has_nc_par = check_api(inc_dirs)
+    has_cdf5_format, has_nc_open_mem, has_nc_create_mem, has_nc_par = check_api(inc_dirs)
     # for netcdf 4.4.x CDF5 format is always enabled.
     if netcdf_lib_version is not None and\
        (netcdf_lib_version > "4.4" and netcdf_lib_version < "4.5"):
@@ -520,6 +530,13 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         sys.stdout.write('netcdf lib does not have nc_open_mem function\n')
         f.write('DEF HAS_NC_OPEN_MEM = 0\n')
 
+    if has_nc_create_mem:
+        sys.stdout.write('netcdf lib has nc_create_mem function\n')
+        f.write('DEF HAS_NC_CREATE_MEM = 1\n')
+    else:
+        sys.stdout.write('netcdf lib does not have nc_create_mem function\n')
+        f.write('DEF HAS_NC_CREATE_MEM = 0\n')
+
     if has_cdf5_format:
         sys.stdout.write('netcdf lib has cdf-5 format capability\n')
         f.write('DEF HAS_CDF5_FORMAT = 1\n')

From 78840eda3ff99a09adf184d3dca02df080ce6db8 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 26 Jan 2019 15:03:06 -0700
Subject: [PATCH 0173/1504] make sure bytes are returned by Dataset.close if
 _inmemory=True

---
 netCDF4/_netCDF4.pyx | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index bf3df2207..269c71b9f 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1837,7 +1837,7 @@ group, so the path is simply `'/'`.
 **`keepweakref`**: If `True`, child Dimension and Variables objects only keep weak 
 references to the parent Dataset or Group.
     """
-    cdef object __weakref__
+    cdef object __weakref__, _inmemory
     cdef public int _grpid
     cdef public int _isopen
     cdef Py_buffer _buffer
@@ -2316,7 +2316,7 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
 Close the Dataset.
         """
         if self._inmemory:
-            memory = self._close_mem(True)
+            return self._close_mem(True)
         else:
             self._close(True)
 

From 139b6e41f2eca531b607a2c77ed3d2284347ae7e Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 26 Jan 2019 16:04:13 -0700
Subject: [PATCH 0174/1504] bump version number

---
 Changelog            | 4 +++-
 netCDF4/_netCDF4.pyx | 4 ++--
 setup.py             | 2 +-
 3 files changed, 6 insertions(+), 4 deletions(-)

diff --git a/Changelog b/Changelog
index ace802956..62ca4b28c 100644
--- a/Changelog
+++ b/Changelog
@@ -1,7 +1,9 @@
- since version 1.4.2
+ version 1.4.3 (not yet released)
 =============================
  * make set_always_mask work in MFDataset.
  * fix saving diskless files to disk with netcdf-c >= 4.6.2.
+ * write to an in-memory Dataset, bytes returned by Dataset.close()
+   (issue #865)
 
  version 1.4.2 (tag v1.4.2rel)
 =============================
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 269c71b9f..e32090333 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1,5 +1,5 @@
 """
-Version 1.4.2
+Version 1.4.3
 -------------
 - - - 
 
@@ -1105,7 +1105,7 @@ except ImportError:
     # python3: zip is already python2's itertools.izip
     pass
 
-__version__ = "1.4.2"
+__version__ = "1.4.3"
 
 # Initialize numpy
 import posixpath
diff --git a/setup.py b/setup.py
index 380c1fc58..67de93b7a 100644
--- a/setup.py
+++ b/setup.py
@@ -570,7 +570,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 
 setup(name="netCDF4",
       cmdclass=cmdclass,
-      version="1.4.2",
+      version="1.4.3",
       long_description="netCDF version 4 has many features not found in earlier versions of the library, such as hierarchical groups, zlib compression, multiple unlimited dimensions, and new data types.  It is implemented on top of HDF5.  This module implements most of the new features, and can read and write netCDF files compatible with older versions of the library.  The API is modelled after Scientific.IO.NetCDF, and should be familiar to users of that module.\n\nThis project is hosted on a `GitHub repository `_ where you may access the most up-to-date source.",
       author="Jeff Whitaker",
       author_email="jeffrey.s.whitaker@noaa.gov",

From 2a7955089dc2dade16ff4a2e3819a06fbfce25fa Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 26 Jan 2019 18:31:03 -0700
Subject: [PATCH 0175/1504] make sure it compiles when nc_close_memio not
 available

---
 netCDF4/_netCDF4.pyx | 17 +++++++++++------
 1 file changed, 11 insertions(+), 6 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index e32090333..28c94cc6a 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2290,10 +2290,11 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
         PyBuffer_Release(&self._buffer)
 
     def _close_mem(self, check_err):
-        cdef NC_memio memio
         cdef int ierr
 
-        ierr = nc_close_memio(self._grpid, &memio)
+        IF HAS_NC_CREATE_MEM:
+            cdef NC_memio memio
+            ierr = nc_close_memio(self._grpid, &memio)
 
         if check_err:
             _ensure_nc_success(ierr)
@@ -2306,7 +2307,8 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
         PyBuffer_Release(&self._buffer)
 
         # return bytes representing in-memory dataset
-        return PyBytes_FromStringAndSize(memio.memory, memio.size)
+        IF HAS_NC_CREATE_MEM:
+            return PyBytes_FromStringAndSize(memio.memory, memio.size)
 
 
     def close(self):
@@ -2315,9 +2317,12 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
 
 Close the Dataset.
         """
-        if self._inmemory:
-            return self._close_mem(True)
-        else:
+        IF HAS_NC_CREATE_MEM:
+            if self._inmemory:
+                return self._close_mem(True)
+            else:
+                self._close(True)
+        ELSE:
             self._close(True)
 
     def isopen(self):

From 847e50690b1da5afb335a80db427bc68c9a5075b Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 26 Jan 2019 18:41:50 -0700
Subject: [PATCH 0176/1504] check for valid memory kwarg

---
 netCDF4/_netCDF4.pyx | 40 +++++++++++++++++++++++++---------------
 1 file changed, 25 insertions(+), 15 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 28c94cc6a..82f5a66a9 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2001,8 +2001,20 @@ references to the parent Dataset or Group.
         bytestr = _strencode(_tostr(filename), encoding=encoding)
         path = bytestr
 
-        #if memory is not None and (mode != 'r' or type(memory) != bytes):
-        #    raise ValueError('memory mode only works with \'r\' modes and must be `bytes`')
+        if memory is not None:
+            if mode == 'r' and type(memory) != bytes:
+                msg='memory kwarg must be a bytes object if mode=\'r\''
+                raise ValueError(msg)
+            elif mode == 'w':
+                try:
+                    memory = int(memory)
+                except:
+                    msg='memory kwarg must be an integer-like if mode=\'w\''
+                    raise ValueError(msg)
+            else:
+                msg='if memory kwarg specified, mode must be \'r\' or \'w\''
+                raise ValueError(msg)
+
         if parallel:
             IF HAS_NC_PAR != 1:
                 msg='parallel mode requires MPI enabled netcdf-c'
@@ -2289,25 +2301,23 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
         # view.obj is checked, ref on obj is decremented and obj will be null'd out
         PyBuffer_Release(&self._buffer)
 
-    def _close_mem(self, check_err):
-        cdef int ierr
-
-        IF HAS_NC_CREATE_MEM:
+    IF HAS_NC_CREATE_MEM:
+        def _close_mem(self, check_err):
+            cdef int ierr
             cdef NC_memio memio
             ierr = nc_close_memio(self._grpid, &memio)
 
-        if check_err:
-            _ensure_nc_success(ierr)
+            if check_err:
+                _ensure_nc_success(ierr)
 
-        self._isopen = 0 # indicates file already closed, checked by __dealloc__
+            self._isopen = 0 # indicates file already closed, checked by __dealloc__
 
-        # Only release buffer if close succeeded
-        # per impl of PyBuffer_Release: https://github.com/python/cpython/blob/master/Objects/abstract.c#L667
-        # view.obj is checked, ref on obj is decremented and obj will be null'd out
-        PyBuffer_Release(&self._buffer)
+            # Only release buffer if close succeeded
+            # per impl of PyBuffer_Release: https://github.com/python/cpython/blob/master/Objects/abstract.c#L667
+            # view.obj is checked, ref on obj is decremented and obj will be null'd out
+            PyBuffer_Release(&self._buffer)
 
-        # return bytes representing in-memory dataset
-        IF HAS_NC_CREATE_MEM:
+            # return bytes representing in-memory dataset
             return PyBytes_FromStringAndSize(memio.memory, memio.size)
 
 

From afa438df591ae0cb4de35df3ce345fe33d907b30 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 26 Jan 2019 18:56:47 -0700
Subject: [PATCH 0177/1504] fix error in previous commit

---
 netCDF4/_netCDF4.pyx | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 82f5a66a9..34fc1640c 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2002,9 +2002,10 @@ references to the parent Dataset or Group.
         path = bytestr
 
         if memory is not None:
-            if mode == 'r' and type(memory) != bytes:
-                msg='memory kwarg must be a bytes object if mode=\'r\''
-                raise ValueError(msg)
+            if mode == 'r':
+                if type(memory) != bytes:
+                    msg='memory kwarg must be a bytes object if mode=\'r\''
+                    raise ValueError(msg)
             elif mode == 'w':
                 try:
                     memory = int(memory)

From eac0bade224f96bb5ddd59a2b486a789dba38d24 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 26 Jan 2019 19:40:48 -0700
Subject: [PATCH 0178/1504] add test

---
 netCDF4/__init__.py    |  2 +-
 netCDF4/_netCDF4.pyx   |  7 ++-----
 test/run_all.py        |  6 +++++-
 test/tst_create_mem.py | 20 ++++++++++++++++++++
 4 files changed, 28 insertions(+), 7 deletions(-)
 create mode 100644 test/tst_create_mem.py

diff --git a/netCDF4/__init__.py b/netCDF4/__init__.py
index 42e311374..e2660d13c 100644
--- a/netCDF4/__init__.py
+++ b/netCDF4/__init__.py
@@ -6,6 +6,6 @@
 from ._netCDF4 import (__version__, __netcdf4libversion__, __hdf5libversion__,
                        __has_rename_grp__, __has_nc_inq_path__,
                        __has_nc_inq_format_extended__, __has_nc_open_mem__,
-                       __has_cdf5_format__,__has_nc_par__)
+                       __has_nc_create_mem__,__has_cdf5_format__,__has_nc_par__)
 __all__ =\
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType']
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 34fc1640c..87c57e08b 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1158,6 +1158,7 @@ __has_nc_inq_path__ = HAS_NC_INQ_PATH
 __has_nc_inq_format_extended__ = HAS_NC_INQ_FORMAT_EXTENDED
 __has_cdf5_format__ = HAS_CDF5_FORMAT
 __has_nc_open_mem__ = HAS_NC_OPEN_MEM
+__has_nc_create_mem__ = HAS_NC_CREATE_MEM
 __has_nc_par__ = HAS_NC_PAR
 _needsworkaround_issue485 = __netcdf4libversion__ < "4.4.0" or \
                (__netcdf4libversion__.startswith("4.4.0") and \
@@ -2311,11 +2312,7 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
             if check_err:
                 _ensure_nc_success(ierr)
 
-            self._isopen = 0 # indicates file already closed, checked by __dealloc__
-
-            # Only release buffer if close succeeded
-            # per impl of PyBuffer_Release: https://github.com/python/cpython/blob/master/Objects/abstract.c#L667
-            # view.obj is checked, ref on obj is decremented and obj will be null'd out
+            self._isopen
             PyBuffer_Release(&self._buffer)
 
             # return bytes representing in-memory dataset
diff --git a/test/run_all.py b/test/run_all.py
index 036b6ce92..2388d5fde 100755
--- a/test/run_all.py
+++ b/test/run_all.py
@@ -1,6 +1,7 @@
 import glob, os, sys, unittest, struct
 from netCDF4 import getlibversion,__hdf5libversion__,__netcdf4libversion__,__version__
-from netCDF4 import __has_cdf5_format__, __has_nc_inq_path__, __has_nc_par__
+from netCDF4 import __has_cdf5_format__, __has_nc_inq_path__, __has_nc_par__,\
+                    __has_nc_create_mem__
 
 # can also just run
 # python -m unittest discover . 'tst*py'
@@ -21,6 +22,9 @@
 if not __has_nc_inq_path__:
     test_files.remove('tst_filepath.py')
     sys.stdout.write('not running tst_filepath.py ...\n')
+if not __has_nc_create_mem__:
+    test_files.remove('tst_create_mem.py')
+    sys.stdout.write('not running tst_create_mem.py ...\n')
 if not __has_cdf5_format__ or struct.calcsize("P") < 8:
     test_files.remove('tst_cdf5.py')
     sys.stdout.write('not running tst_cdf5.py ...\n')
diff --git a/test/tst_create_mem.py b/test/tst_create_mem.py
new file mode 100644
index 000000000..354cf2082
--- /dev/null
+++ b/test/tst_create_mem.py
@@ -0,0 +1,20 @@
+import unittest
+import netCDF4
+import numpy as np
+from numpy.testing import assert_array_equal
+
+class TestCreateMem(unittest.TestCase):
+    def test_mem_create(self):
+        format = 'NETCDF4_CLASSIC'
+        nc = netCDF4.Dataset('test.nc','w',memory=1,format=format)
+        d = nc.createDimension('x',None)
+        v = nc.createVariable('v',np.int32,'x')
+        data = np.arange(5)
+        v[0:5] = data
+        b = nc.close()
+        nc = netCDF4.Dataset('test.nc','r',memory=b)
+        assert_array_equal(nc['v'][:],data)
+        nc.close()
+
+if __name__ == '__main__':
+    unittest.main()

From bbde75590168f65ba7a757f379b8c15124e4ea14 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 26 Jan 2019 19:44:59 -0700
Subject: [PATCH 0179/1504] add conda path

---
 .appveyor.yml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.appveyor.yml b/.appveyor.yml
index b8a9521dd..9a30e7ad8 100644
--- a/.appveyor.yml
+++ b/.appveyor.yml
@@ -25,6 +25,7 @@ install:
 
   # Add path, activate `conda` and update conda.
   - cmd: call %CONDA_INSTALL_LOCN%\Scripts\activate.bat
+  - cmd: SET PATH=%CONDA_INSTALL_LOCN%;%CONDA_INSTALL_LOCN%\Scripts;%PATH%
   - cmd: conda.exe config --set always_yes yes --set changeps1 no --set show_channel_urls true
   - cmd: conda.exe update conda
   - cmd: conda.exe config --remove channels defaults --force

From 33872a4073405c89d18be0d309cafa20c2e52964 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 26 Jan 2019 22:10:34 -0700
Subject: [PATCH 0180/1504] free memory returned by nc_close_memio (get rid of
 leak)

---
 .appveyor.yml        | 1 -
 netCDF4/_netCDF4.pyx | 9 +++++++--
 2 files changed, 7 insertions(+), 3 deletions(-)

diff --git a/.appveyor.yml b/.appveyor.yml
index 9a30e7ad8..b8a9521dd 100644
--- a/.appveyor.yml
+++ b/.appveyor.yml
@@ -25,7 +25,6 @@ install:
 
   # Add path, activate `conda` and update conda.
   - cmd: call %CONDA_INSTALL_LOCN%\Scripts\activate.bat
-  - cmd: SET PATH=%CONDA_INSTALL_LOCN%;%CONDA_INSTALL_LOCN%\Scripts;%PATH%
   - cmd: conda.exe config --set always_yes yes --set changeps1 no --set show_channel_urls true
   - cmd: conda.exe update conda
   - cmd: conda.exe config --remove channels defaults --force
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 87c57e08b..4173819fc 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2315,8 +2315,13 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
             self._isopen
             PyBuffer_Release(&self._buffer)
 
-            # return bytes representing in-memory dataset
-            return PyBytes_FromStringAndSize(memio.memory, memio.size)
+            # get python bytes representing in-memory dataset
+            # this makes a copy of memory in memio
+            b = PyBytes_FromStringAndSize(memio.memory, memio.size)
+            # free memory returned by nc_close_memio
+            free(memio.memory)
+            # return python bytes
+            return b
 
 
     def close(self):

From c157323fa09d549cd18c7cbc3eba6723e4e0a3f1 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 27 Jan 2019 09:56:37 -0700
Subject: [PATCH 0181/1504] update

---
 netCDF4/_netCDF4.pyx | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 4173819fc..f65953acc 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2004,14 +2004,16 @@ references to the parent Dataset or Group.
 
         if memory is not None:
             if mode == 'r':
-                if type(memory) != bytes:
-                    msg='memory kwarg must be a bytes object if mode=\'r\''
+                try:
+                    memory = buffer(memory)
+                except:
+                    msg='memory kwarg must be support the buffer interface'
                     raise ValueError(msg)
             elif mode == 'w':
                 try:
                     memory = int(memory)
                 except:
-                    msg='memory kwarg must be an integer-like if mode=\'w\''
+                    msg='memory kwarg must be integer-like'
                     raise ValueError(msg)
             else:
                 msg='if memory kwarg specified, mode must be \'r\' or \'w\''

From be09fb6b060701093f8cb35ef5ff62c64f0424a1 Mon Sep 17 00:00:00 2001
From: Filipe Fernandes 
Date: Sun, 27 Jan 2019 15:13:42 -0200
Subject: [PATCH 0182/1504] fix appveyor conda calls

---
 .appveyor.yml | 16 +++++++---------
 1 file changed, 7 insertions(+), 9 deletions(-)

diff --git a/.appveyor.yml b/.appveyor.yml
index b8a9521dd..3527c1f60 100644
--- a/.appveyor.yml
+++ b/.appveyor.yml
@@ -25,20 +25,18 @@ install:
 
   # Add path, activate `conda` and update conda.
   - cmd: call %CONDA_INSTALL_LOCN%\Scripts\activate.bat
-  - cmd: conda.exe config --set always_yes yes --set changeps1 no --set show_channel_urls true
-  - cmd: conda.exe update conda
-  - cmd: conda.exe config --remove channels defaults --force
-  - cmd: conda.exe config --add channels conda-forge --force
+  - cmd: conda config --set always_yes yes --set changeps1 no --set show_channel_urls true
+  - cmd: conda update conda
+  - cmd: conda config --remove channels defaults --force
+  - cmd: conda config --add channels conda-forge --force
   - cmd: set PYTHONUNBUFFERED=1
-  - cmd: conda.exe install conda-build vs2008_express_vc_python_patch
+  - cmd: conda install conda-build vs2008_express_vc_python_patch
   - cmd: call setup_x64
 
-  - cmd: conda.exe create --name TEST python=%PY% numpy=%NPY% cython pip pytest hdf5 libnetcdf cftime
+  - cmd: conda create --name TEST python=%PY% numpy=%NPY% cython pip pytest hdf5 libnetcdf cftime
+  - cmd: conda info --all
   - cmd: conda activate TEST
 
-  - cmd: conda.exe info --all
-  - cmd: conda.exe list
-
   - cmd: echo [options] > setup.cfg
   - cmd: echo [directories] >> setup.cfg
   - cmd: echo HDF5_libdir = %CONDA_PREFIX%\Library\lib >> setup.cfg

From 162b8b63e27a9add870a34ca18060eea900f0fc4 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 27 Jan 2019 11:57:53 -0700
Subject: [PATCH 0183/1504] implement cython memory buffer interface

---
 include/membuf.pyx   | 59 ++++++++++++++++++++++++++++++++++++++++++++
 netCDF4/_netCDF4.pyx | 32 +++++++++---------------
 2 files changed, 71 insertions(+), 20 deletions(-)
 create mode 100644 include/membuf.pyx

diff --git a/include/membuf.pyx b/include/membuf.pyx
new file mode 100644
index 000000000..c7002e703
--- /dev/null
+++ b/include/membuf.pyx
@@ -0,0 +1,59 @@
+# Buffer code found here similar to
+# http://stackoverflow.com/a/28166272/428751
+# Allows to return a malloced python buffer,
+# which will be freed when the python object is garbage collected.
+from cpython.buffer cimport PyBuffer_FillInfo, PyBuffer_Release
+from libc.stdlib cimport free
+from libc.string cimport memcpy
+from libc.stdint cimport uintptr_t
+
+ctypedef void dealloc_callback(const void *p, size_t l, void *arg)
+
+cdef void free_buf(const void *p, size_t l, void *arg):
+    free(p)
+
+# this is the function used to create a memory view from
+# a raw pointer.
+cdef makebuf(void *p, size_t l):
+    assert p!=NULL, "invalid NULL buffer pointer"
+    return MemBuf_init(p, l, &free_buf, NULL)
+
+cdef class MemBuf:
+    cdef const void *p
+    cdef size_t l
+    cdef dealloc_callback *dealloc_cb_p
+    cdef void *dealloc_cb_arg
+
+    def __len__(self):
+        return self.l
+
+    def __repr__(self):
+        return "MemBuf(%#x)" % ( self.p)
+
+    cdef const void *get_mem(self):
+        return self.p
+
+    def __getbuffer__(self, Py_buffer *view, int flags):
+        PyBuffer_FillInfo(view, self, self.p, self.l, 1, flags)
+
+    def __releasebuffer__(self, Py_buffer *view):
+        #PyBuffer_Release(view) 
+        pass
+
+    def __dealloc__(self):
+        if self.dealloc_cb_p != NULL:
+            self.dealloc_cb_p(self.p, self.l, self.dealloc_cb_arg)
+
+# Call this instead of constructing a MemBuf directly.  The __cinit__
+# and __init__ methods can only take Python objects, so the real
+# constructor is here.  See:
+# https://mail.python.org/pipermail/cython-devel/2012-June/002734.html
+cdef MemBuf MemBuf_init(const void *p, size_t l,
+                        dealloc_callback *dealloc_cb_p,
+                        void *dealloc_cb_arg):
+    cdef MemBuf ret = MemBuf()
+    ret.p = p
+    ret.l = l
+    ret.dealloc_cb_p = dealloc_cb_p
+    ret.dealloc_cb_arg = dealloc_cb_arg
+    return ret
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index f65953acc..17e939914 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1120,6 +1120,7 @@ from libc.string cimport memcpy, memset
 from libc.stdlib cimport malloc, free
 import_array()
 include "constants.pyx"
+include "membuf.pyx"
 include "netCDF4.pxi"
 IF HAS_NC_PAR:
     cimport mpi4py.MPI as MPI
@@ -2002,22 +2003,9 @@ references to the parent Dataset or Group.
         bytestr = _strencode(_tostr(filename), encoding=encoding)
         path = bytestr
 
-        if memory is not None:
-            if mode == 'r':
-                try:
-                    memory = buffer(memory)
-                except:
-                    msg='memory kwarg must be support the buffer interface'
-                    raise ValueError(msg)
-            elif mode == 'w':
-                try:
-                    memory = int(memory)
-                except:
-                    msg='memory kwarg must be integer-like'
-                    raise ValueError(msg)
-            else:
-                msg='if memory kwarg specified, mode must be \'r\' or \'w\''
-                raise ValueError(msg)
+        if memory is not None and mode not in ['r','w']:
+            msg='if memory kwarg specified, mode must be \'r\' or \'w\''
+            raise ValueError(msg)
 
         if parallel:
             IF HAS_NC_PAR != 1:
@@ -2314,16 +2302,20 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
             if check_err:
                 _ensure_nc_success(ierr)
 
-            self._isopen
+            self._isopen = 0
             PyBuffer_Release(&self._buffer)
 
             # get python bytes representing in-memory dataset
             # this makes a copy of memory in memio
-            b = PyBytes_FromStringAndSize(memio.memory, memio.size)
+            #b = PyBytes_FromStringAndSize(memio.memory, memio.size)
             # free memory returned by nc_close_memio
-            free(memio.memory)
+            #free(memio.memory)
             # return python bytes
-            return b
+            #return b
+
+            # makebuf from membuf.pyx - creates a python memoryview
+            # from a raw pointer without making a copy.
+            return makebuf(memio.memory, memio.size)
 
 
     def close(self):

From 439d35c80d547c12710235a7ac41932369a5de44 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 27 Jan 2019 12:18:36 -0700
Subject: [PATCH 0184/1504] check both NETCDF3 and NETCDF4 formats

---
 test/tst_create_mem.py | 22 ++++++++++++----------
 1 file changed, 12 insertions(+), 10 deletions(-)

diff --git a/test/tst_create_mem.py b/test/tst_create_mem.py
index 354cf2082..8f057ca90 100644
--- a/test/tst_create_mem.py
+++ b/test/tst_create_mem.py
@@ -5,16 +5,18 @@
 
 class TestCreateMem(unittest.TestCase):
     def test_mem_create(self):
-        format = 'NETCDF4_CLASSIC'
-        nc = netCDF4.Dataset('test.nc','w',memory=1,format=format)
-        d = nc.createDimension('x',None)
-        v = nc.createVariable('v',np.int32,'x')
-        data = np.arange(5)
-        v[0:5] = data
-        b = nc.close()
-        nc = netCDF4.Dataset('test.nc','r',memory=b)
-        assert_array_equal(nc['v'][:],data)
-        nc.close()
+        def check_inmemory(format):
+            nc = netCDF4.Dataset('test.nc','w',memory=1,format=format)
+            d = nc.createDimension('x',None)
+            v = nc.createVariable('v',np.int32,'x')
+            data = np.arange(5)
+            v[0:5] = data
+            b = nc.close()
+            nc = netCDF4.Dataset('test.nc','r',memory=b)
+            assert_array_equal(nc['v'][:],data)
+            nc.close()
+        check_inmemory('NETCDF3_CLASSIC')
+        check_inmemory('NETCDF4_CLASSIC')
 
 if __name__ == '__main__':
     unittest.main()

From ddb9bffdd083207e145a2153dda6ca153f59b227 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 27 Jan 2019 12:22:12 -0700
Subject: [PATCH 0185/1504] update

---
 test/tst_create_mem.py | 12 ++++++++----
 1 file changed, 8 insertions(+), 4 deletions(-)

diff --git a/test/tst_create_mem.py b/test/tst_create_mem.py
index 8f057ca90..1de542741 100644
--- a/test/tst_create_mem.py
+++ b/test/tst_create_mem.py
@@ -6,15 +6,19 @@
 class TestCreateMem(unittest.TestCase):
     def test_mem_create(self):
         def check_inmemory(format):
-            nc = netCDF4.Dataset('test.nc','w',memory=1,format=format)
+            # memory is 'advisory size' - not needed for NETCDF4/HDF5
+            # but is used for NETCDF3.
+            nc = netCDF4.Dataset('test.nc','w',memory=1028,format=format)
             d = nc.createDimension('x',None)
             v = nc.createVariable('v',np.int32,'x')
             data = np.arange(5)
             v[0:5] = data
+            # retrieve memory buffer
             b = nc.close()
-            nc = netCDF4.Dataset('test.nc','r',memory=b)
-            assert_array_equal(nc['v'][:],data)
-            nc.close()
+            # open a new file using this memory buffer
+            nc2 = netCDF4.Dataset('test2.nc','r',memory=b)
+            assert_array_equal(nc2['v'][:],data)
+            nc2.close()
         check_inmemory('NETCDF3_CLASSIC')
         check_inmemory('NETCDF4_CLASSIC')
 

From 4b9eb40d4da2f61aeea8687044d572c7a9cd6f91 Mon Sep 17 00:00:00 2001
From: Filipe Fernandes 
Date: Sun, 27 Jan 2019 17:24:01 -0200
Subject: [PATCH 0186/1504] test against latest numpy

---
 .appveyor.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.appveyor.yml b/.appveyor.yml
index 3527c1f60..7b247abda 100644
--- a/.appveyor.yml
+++ b/.appveyor.yml
@@ -2,11 +2,11 @@ environment:
   CONDA_INSTALL_LOCN: C:\\Miniconda36-x64
   matrix:
     - TARGET_ARCH: x64
-      NPY: 1.15
+      NPY: 1.16
       PY: 3.6
 
     - TARGET_ARCH: x64
-      NPY: 1.15
+      NPY: 1.16
       PY: 3.7
 
 platform:

From bb3cbe9dca25f2e2f7258c98fb719a56cfe5aee2 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 27 Jan 2019 12:37:38 -0700
Subject: [PATCH 0187/1504] update docstring

---
 netCDF4/_netCDF4.pyx | 15 ++++++++++++---
 1 file changed, 12 insertions(+), 3 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 17e939914..9909f4d28 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1946,7 +1946,8 @@ references to the parent Dataset or Group.
         
         **`diskless`**: If `True`, create diskless (in memory) file.  
         This is an experimental feature added to the C library after the
-        netcdf-4.2 release.
+        netcdf-4.2 release. If you need to access the memory buffer directly,
+        use the in-memory feature instead (see `memory` kwarg).
         
         **`persist`**: if `diskless=True`, persist file to disk when closed
         (default `False`).
@@ -1965,8 +1966,16 @@ references to the parent Dataset or Group.
         desirable, since the associated Variable instances may still be needed, but are
         rendered unusable when the parent Dataset instance is garbage collected.
         
-        **`memory`**: if not `None`, open file with contents taken from this block of memory.
-        Must be a sequence of bytes.  Note this only works with "r" mode.
+        **`memory`**: if not `None`, create or open an in-memory Dataset.
+        If mode = 'r', the memory kwarg must contain a buffer object.
+        The Dataset will then be created with contents taken from this block of memory.
+        If mode = 'w', the memory kwarg should contain the anticipated size
+        of the Dataset in bytes (used only for NETCDF3 files).  A memory
+        buffer containing a copy of the Dataset is returned by the
+        `Dataset.close` method. Requires netcdf-c version 4.4.1 for mode='r,
+        netcdf-c 4.6.2 for mode='w'. To persist the file to disk, the raw
+        bytes from the returned buffer can be written into a binary file.
+        The Dataset can also be re-opened using this memory buffer.
 
         **`encoding`**: encoding used to encode filename string into bytes.
         Default is None (`sys.getdefaultfileencoding()` is used).

From 96d3ccb0e64bbffd99653740faffd0e555bdf4e7 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 27 Jan 2019 13:20:02 -0700
Subject: [PATCH 0188/1504] update docs

---
 netCDF4/_netCDF4.pyx | 10 ++++++----
 1 file changed, 6 insertions(+), 4 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 9909f4d28..2ea271295 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1902,7 +1902,8 @@ references to the parent Dataset or Group.
                      Comm comm=None, Info info=None, **kwargs):
         """
         **`__init__(self, filename, mode="r", clobber=True, diskless=False,
-        persist=False, keepweakref=False, format='NETCDF4')`**
+        persist=False, keepweakref=False, memory=None, encoding=None,
+        parallel=False, comm=None, info=None, format='NETCDF4')`**
 
         `netCDF4.Dataset` constructor.
 
@@ -1944,8 +1945,8 @@ references to the parent Dataset or Group.
         64 bit integer data types, but is only compatible with clients linked against
         netCDF version 4.4.0 or later.
         
-        **`diskless`**: If `True`, create diskless (in memory) file.  
-        This is an experimental feature added to the C library after the
+        **`diskless`**: If `True`, create diskless (in-core) file.  
+        This is a feature added to the C library after the
         netcdf-4.2 release. If you need to access the memory buffer directly,
         use the in-memory feature instead (see `memory` kwarg).
         
@@ -1967,7 +1968,8 @@ references to the parent Dataset or Group.
         rendered unusable when the parent Dataset instance is garbage collected.
         
         **`memory`**: if not `None`, create or open an in-memory Dataset.
-        If mode = 'r', the memory kwarg must contain a buffer object.
+        If mode = 'r', the memory kwarg must contain a memory buffer object
+        (an object that supports the python buffer interface).
         The Dataset will then be created with contents taken from this block of memory.
         If mode = 'w', the memory kwarg should contain the anticipated size
         of the Dataset in bytes (used only for NETCDF3 files).  A memory

From 2ce184e1fdc58ad49ef62e4b595d4f9fb7817755 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 27 Jan 2019 19:28:17 -0700
Subject: [PATCH 0189/1504] add tobytes method to MemBuf, add tutorial section
 on diskless files.

---
 include/membuf.pyx   |  4 +++
 netCDF4/_netCDF4.pyx | 67 ++++++++++++++++++++++++++++++++++++++------
 2 files changed, 62 insertions(+), 9 deletions(-)

diff --git a/include/membuf.pyx b/include/membuf.pyx
index c7002e703..15ec4dbdc 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -3,6 +3,7 @@
 # Allows to return a malloced python buffer,
 # which will be freed when the python object is garbage collected.
 from cpython.buffer cimport PyBuffer_FillInfo, PyBuffer_Release
+from cpython.bytes cimport PyBytes_FromStringAndSize
 from libc.stdlib cimport free
 from libc.string cimport memcpy
 from libc.stdint cimport uintptr_t
@@ -44,6 +45,9 @@ cdef class MemBuf:
         if self.dealloc_cb_p != NULL:
             self.dealloc_cb_p(self.p, self.l, self.dealloc_cb_arg)
 
+    def tobytes(self):
+        return PyBytes_FromStringAndSize(self.p, self.l)
+
 # Call this instead of constructing a MemBuf directly.  The __cinit__
 # and __init__ methods can only take Python objects, so the real
 # constructor is here.  See:
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 2ea271295..3b3a69b2c 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -112,7 +112,8 @@ Tutorial
 11. [Variable-length (vlen) data types.](#section11)
 12. [Enum data type.](#section12)
 13. [Parallel IO.](#section13)
-14. [Dealing with strings](#section14)
+14. [Dealing with strings.](#section14)
+15. [In-memory (diskless) Datasets.](#section15)
 
 
 ## 
      1) Creating/Opening/Closing a netCDF file.
@@ -1060,6 +1061,62 @@ Note that there is currently no support for mapping numpy structured arrays with
 unicode elements (dtype `U#`) onto netCDF compound types, nor is there support 
 for netCDF compound types with vlen string components.
 
+## 
      15) In-memory (diskless) Datasets.
+
+You can create netCDF Datasets whose content is held in memory
+instead of in a disk file.  There are two ways to do this.  If you
+don't need access to the memory buffer containing the Dataset from
+within python, the best way is to use the `diskless=True` keyword
+argument when creating the Dataset.  If you want to save the Dataset
+to disk when you close it, also set `persist=True`.  If you want to
+create a new read-only Dataset from an existing python memory buffer, use the
+`memory` keyword argument to pass the memory buffer when creating the Dataset.
+If you want to create a new in-memory Dataset, and then access the memory buffer
+directly from Python, use the `memory` keyword argument to specify the
+estimated size of the Dataset in bytes when creating the Dataset with
+`mode='w'`.  Then, the `Dataset.close` method will return a python memory
+buffer representing the Dataset. Below are examples illustrating both
+approaches.
+
+    :::python
+    >>> # create a diskless (in-memory) Dataset, and persist the file
+    >>> # to disk when it is closed.
+    >>> nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
+    >>> nc.history = 'test of diskless file capability'
+    >>> d = nc.createDimension('x',None)
+    >>> v = nc.createVariable('v',np.int32,'x')
+    >>> v[0:5] = np.arange(5)
+    >>> print(nc)
+    >>> print(nc['v'][:])
+    >>> nc.close() # file saved to disk
+    >>> # create an in-memory dataset from an existing python memory
+    >>> # buffer.
+    >>> # read the newly created netcdf file into a python bytes object.
+    >>> f = open('diskless_example.nc', 'rb')
+    >>> nc_bytes = f.read(); f.close()
+    >>> # create a netCDF in-memory dataset from the bytes object.
+    >>> nc = Dataset('inmemory.nc', memory=nc_bytes)
+    >>> print(nc)
+    >>> print(nc['v'][:])
+    >>> nc.close()
+    >>> # create an in-memory Dataset and retrieve memory buffer
+    >>> # estimated size is 1028 bytes - this is actually only
+    >>> # used if format is NETCDF3 (ignored for NETCDF4/HDF5 files).
+    >>> nc = Dataset('inmemory.nc', mode='w',memory=1028)
+    >>> d = nc.createDimension('x',None)
+    >>> v = nc.createVariable('v',np.int32,'x')
+    >>> v[0:5] = np.arange(5)
+    >>> nc_buf = nc.close() # close returns memory buffer.
+    >>> # save nc_buf to disk, read it back in and check.
+    >>> # tobytes method of cython memory buffer converts to bytes.
+    >>> f = open('inmemory.nc', 'w')
+    >>> f.write(nc_buf.tobytes()); f.close()
+    >>> nc = Dataset('inmemory.nc')
+    >>> print(nc)
+    >>> print(nc['v'][:])
+    >>> nc.close()
+
+
 All of the code in this tutorial is available in `examples/tutorial.py`, except
 the parallel IO example, which is in `examples/mpi_example.py`.
 Unit tests are in the `test` directory.
@@ -2316,14 +2373,6 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
             self._isopen = 0
             PyBuffer_Release(&self._buffer)
 
-            # get python bytes representing in-memory dataset
-            # this makes a copy of memory in memio
-            #b = PyBytes_FromStringAndSize(memio.memory, memio.size)
-            # free memory returned by nc_close_memio
-            #free(memio.memory)
-            # return python bytes
-            #return b
-
             # makebuf from membuf.pyx - creates a python memoryview
             # from a raw pointer without making a copy.
             return makebuf(memio.memory, memio.size)

From ddec20a69a790662fa634486bd2228299fdce5eb Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 27 Jan 2019 19:38:15 -0700
Subject: [PATCH 0190/1504] update tutorial

---
 examples/tutorial.py | 37 +++++++++++++++++++++++++++++++++++++
 netCDF4/_netCDF4.pyx | 41 ++++++++++++++++++++++++++++++-----------
 2 files changed, 67 insertions(+), 11 deletions(-)

diff --git a/examples/tutorial.py b/examples/tutorial.py
index 1ead6ad63..ca872989a 100644
--- a/examples/tutorial.py
+++ b/examples/tutorial.py
@@ -320,3 +320,40 @@ def walktree(top):
 statdat[:] = data.view(station_data_t.dtype)
 print(statdat[:]) # now structured array with char array subtype is returned
 nc.close()
+
+# create a diskless (in-memory) Dataset, and persist the file
+# to disk when it is closed.
+nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
+d = nc.createDimension('x',None)
+v = nc.createVariable('v',numpy.int32,'x')
+v[0:5] = numpy.arange(5)
+print(nc)
+print(nc['v'][:])
+nc.close() # file saved to disk
+# create an in-memory dataset from an existing python memory
+# buffer.
+# read the newly created netcdf file into a python bytes object.
+f = open('diskless_example.nc', 'rb')
+nc_bytes = f.read(); f.close()
+# create a netCDF in-memory dataset from the bytes object.
+nc = Dataset('inmemory.nc', memory=nc_bytes)
+print(nc)
+print(nc['v'][:])
+nc.close()
+# create an in-memory Dataset and retrieve memory buffer
+# estimated size is 1028 bytes - this is actually only
+# used if format is NETCDF3 (ignored for NETCDF4/HDF5 files).
+nc = Dataset('inmemory.nc', mode='w',memory=1028)
+d = nc.createDimension('x',None)
+v = nc.createVariable('v',numpy.int32,'x')
+v[0:5] = numpy.arange(5)
+nc_buf = nc.close() # close returns memory buffer.
+print type(nc_buf)
+# save nc_buf to disk, read it back in and check.
+# tobytes method of cython memory buffer converts to bytes.
+f = open('inmemory.nc', 'w')
+f.write(nc_buf.tobytes()); f.close()
+nc = Dataset('inmemory.nc')
+print(nc)
+print(nc['v'][:])
+nc.close()
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 3b3a69b2c..66af088cd 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1079,33 +1079,46 @@ buffer representing the Dataset. Below are examples illustrating both
 approaches.
 
     :::python
-    >>> # create a diskless (in-memory) Dataset, and persist the file
-    >>> # to disk when it is closed.
+    >>> # create a diskless (in-memory) Dataset, 
+    >>> # and persist the file to disk when it is closed.
     >>> nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
-    >>> nc.history = 'test of diskless file capability'
     >>> d = nc.createDimension('x',None)
-    >>> v = nc.createVariable('v',np.int32,'x')
-    >>> v[0:5] = np.arange(5)
+    >>> v = nc.createVariable('v',numpy.int32,'x')
+    >>> v[0:5] = numpy.arange(5)
     >>> print(nc)
+    
+    root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): x(5)
+    variables(dimensions): int32 v(x)
+    groups:
     >>> print(nc['v'][:])
+    [0 1 2 3 4]
     >>> nc.close() # file saved to disk
-    >>> # create an in-memory dataset from an existing python memory
-    >>> # buffer.
-    >>> # read the newly created netcdf file into a python bytes object.
+    >>> # create an in-memory dataset from an existing python
+    >>> # python memory buffer.
+    >>> # read the newly created netcdf file into a python
+    >>> # bytes object.
     >>> f = open('diskless_example.nc', 'rb')
     >>> nc_bytes = f.read(); f.close()
     >>> # create a netCDF in-memory dataset from the bytes object.
     >>> nc = Dataset('inmemory.nc', memory=nc_bytes)
     >>> print(nc)
+    
+    root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): x(5)
+    variables(dimensions): int32 v(x)
+    groups:
     >>> print(nc['v'][:])
+    [0 1 2 3 4]
     >>> nc.close()
     >>> # create an in-memory Dataset and retrieve memory buffer
     >>> # estimated size is 1028 bytes - this is actually only
-    >>> # used if format is NETCDF3 (ignored for NETCDF4/HDF5 files).
+    >>> # used if format is NETCDF3 
+    >>> # (ignored for NETCDF4/HDF5 files).
     >>> nc = Dataset('inmemory.nc', mode='w',memory=1028)
     >>> d = nc.createDimension('x',None)
-    >>> v = nc.createVariable('v',np.int32,'x')
-    >>> v[0:5] = np.arange(5)
+    >>> v = nc.createVariable('v',numpy.int32,'x')
+    >>> v[0:5] = numpy.arange(5)
     >>> nc_buf = nc.close() # close returns memory buffer.
     >>> # save nc_buf to disk, read it back in and check.
     >>> # tobytes method of cython memory buffer converts to bytes.
@@ -1113,7 +1126,13 @@ approaches.
     >>> f.write(nc_buf.tobytes()); f.close()
     >>> nc = Dataset('inmemory.nc')
     >>> print(nc)
+    
+    root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): x(5)
+    variables(dimensions): int32 v(x)
+    groups:
     >>> print(nc['v'][:])
+    [0 1 2 3 4]
     >>> nc.close()
 
 

From 1fcb2ed689eaf3a9d3b2f12266637c86c4300d49 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 27 Jan 2019 19:39:29 -0700
Subject: [PATCH 0191/1504] update docs

---
 docs/netCDF4/index.html | 125 +++++++++++++++++++++++++++++++++++-----
 1 file changed, 112 insertions(+), 13 deletions(-)

diff --git a/docs/netCDF4/index.html b/docs/netCDF4/index.html
index 23a2cbafd..c07e0353f 100644
--- a/docs/netCDF4/index.html
+++ b/docs/netCDF4/index.html
@@ -4,7 +4,7 @@
   
 
     netCDF4 API documentation
-    __init__
     
    • ncattrs
      • 
+    
    • set_always_mask
      • 
     
    • set_auto_chartostring
      • 
     
    • set_auto_mask
      • 
     
    • set_auto_maskandscale
      • 
@@ -1275,7 +1276,7 @@ 
      Index
      
 
   
      
   
      netCDF4 module
      
-  
      Version 1.4.2
      
+  
      Version 1.4.3
      
 
      
 
      Introduction
      
 
      netcdf4-python is a Python interface to the netCDF C library.  
      
@@ -1376,7 +1377,8 @@ 
      Tutorial
      
 
    • Variable-length (vlen) data types.
      • 
 
    • Enum data type.
      • 
 
    • Parallel IO.
      • 
-
    • Dealing with strings
      • 
+
    • Dealing with strings.
      • 
+
    • In-memory (diskless) Datasets.
      • 
 
 
      1) Creating/Opening/Closing a netCDF file.
      
 
      To create a netCDF file from python, you simply call the Dataset
@@ -2285,6 +2287,79 @@ 
      14) Dealing with strings.
      
 
      Note that there is currently no support for mapping numpy structured arrays with
 unicode elements (dtype U#) onto netCDF compound types, nor is there support 
 for netCDF compound types with vlen string components.
      
+
      15) In-memory (diskless) Datasets.
      
+
      You can create netCDF Datasets whose content is held in memory
+instead of in a disk file.  There are two ways to do this.  If you
+don't need access to the memory buffer containing the Dataset from
+within python, the best way is to use the diskless=True keyword
+argument when creating the Dataset.  If you want to save the Dataset
+to disk when you close it, also set persist=True.  If you want to
+create a new read-only Dataset from an existing python memory buffer, use the
+memory keyword argument to pass the memory buffer when creating the Dataset.
+If you want to create a new in-memory Dataset, and then access the memory buffer
+directly from Python, use the memory keyword argument to specify the
+estimated size of the Dataset in bytes when creating the Dataset with
+mode='w'.  Then, the Dataset.close method will return a python memory
+buffer representing the Dataset. Below are examples illustrating both
+approaches.
      
+
      >>> # create a diskless (in-memory) Dataset, 
+>>> # and persist the file to disk when it is closed.
+>>> nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
+>>> d = nc.createDimension('x',None)
+>>> v = nc.createVariable('v',numpy.int32,'x')
+>>> v[0:5] = numpy.arange(5)
+>>> print(nc)
+<type 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+dimensions(sizes): x(5)
+variables(dimensions): int32 v(x)
+groups:
+>>> print(nc['v'][:])
+[0 1 2 3 4]
+>>> nc.close() # file saved to disk
+>>> # create an in-memory dataset from an existing python
+>>> # python memory buffer.
+>>> # read the newly created netcdf file into a python
+>>> # bytes object.
+>>> f = open('diskless_example.nc', 'rb')
+>>> nc_bytes = f.read(); f.close()
+>>> # create a netCDF in-memory dataset from the bytes object.
+>>> nc = Dataset('inmemory.nc', memory=nc_bytes)
+>>> print(nc)
+<type 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+dimensions(sizes): x(5)
+variables(dimensions): int32 v(x)
+groups:
+>>> print(nc['v'][:])
+[0 1 2 3 4]
+>>> nc.close()
+>>> # create an in-memory Dataset and retrieve memory buffer
+>>> # estimated size is 1028 bytes - this is actually only
+>>> # used if format is NETCDF3 
+>>> # (ignored for NETCDF4/HDF5 files).
+>>> nc = Dataset('inmemory.nc', mode='w',memory=1028)
+>>> d = nc.createDimension('x',None)
+>>> v = nc.createVariable('v',numpy.int32,'x')
+>>> v[0:5] = numpy.arange(5)
+>>> nc_buf = nc.close() # close returns memory buffer.
+>>> # save nc_buf to disk, read it back in and check.
+>>> # tobytes method of cython memory buffer converts to bytes.
+>>> f = open('inmemory.nc', 'w')
+>>> f.write(nc_buf.tobytes()); f.close()
+>>> nc = Dataset('inmemory.nc')
+>>> print(nc)
+<type 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+dimensions(sizes): x(5)
+variables(dimensions): int32 v(x)
+groups:
+>>> print(nc['v'][:])
+[0 1 2 3 4]
+>>> nc.close()
+
      
+
+
 
      All of the code in this tutorial is available in examples/tutorial.py, except
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
@@ -2390,7 +2465,7 @@ 
      Functions
      
 
      units: a string of the form <time units> since <reference time>
 describing the time units. <time units> can be days, hours, minutes,
 seconds, milliseconds or microseconds. <reference time> is the time
-origin.
      
+origin. months_since is allowed only for the 360_day calendar.
      
 
      calendar: describes the calendar used in the time calculations.
 All the values currently defined in the
 CF metadata convention
@@ -2398,7 +2473,7 @@ 
      Functions
      
 'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'.
 Default is 'standard', which is a mixed Julian/Gregorian calendar.
      
 
      returns a numeric time value, or an array of numeric time values
-with approximately millisecond accuracy.
      
+with approximately 100 microsecond accuracy.
      
   
      
 
      
 
@@ -2439,7 +2514,7 @@ 
      Functions
      
 
      units: a string of the form <time units> since <reference time>
 describing the time units. <time units> can be days, hours, minutes,
 seconds, milliseconds or microseconds. <reference time> is the time
-origin.
      
+origin. months_since is allowed only for the 360_day calendar.
      
 
      calendar: describes the calendar used in the time calculations.
 All the values currently defined in the
 CF metadata convention
@@ -2450,7 +2525,7 @@ 
      Functions
      
 objects are returned from num2date where possible; if True dates which
 subclass cftime.datetime are returned for all calendars.
      
 
      returns a datetime instance, or an array of datetime instances with
-approximately millisecond accuracy.
      
+approximately 100 microsecond accuracy.
      
 
      Note: The datetime instances returned are 'real' python datetime
 objects if calendar='proleptic_gregorian', or
 calendar='standard' or 'gregorian'
@@ -2825,7 +2900,7 @@ 
      Static methods
      
             
   
      
     
      
-    
      def __init__(
      self, filename, mode="r", clobber=True, diskless=False, persist=False, keepweakref=False, format='NETCDF4')
      
+    
      def __init__(
      self, filename, mode="r", clobber=True, diskless=False, persist=False, keepweakref=False, memory=None, encoding=None, parallel=False, comm=None, info=None, format='NETCDF4')
      
     
      
     
 
@@ -2866,9 +2941,10 @@ 
      Static methods
      
 file format, which supports 64-bit dimension sizes plus unsigned and
 64 bit integer data types, but is only compatible with clients linked against
 netCDF version 4.4.0 or later.
      
-
      diskless: If True, create diskless (in memory) file.
      
-This is an experimental feature added to the C library after the
-netcdf-4.2 release.
      
+
      diskless: If True, create diskless (in-core) file.
      
+This is a feature added to the C library after the
+netcdf-4.2 release. If you need to access the memory buffer directly,
+use the in-memory feature instead (see memory kwarg).
      
 
      persist: if diskless=True, persist file to disk when closed
 (default False).
      
 
      keepweakref: if True, child Dimension and Variable instances will keep weak
@@ -2884,8 +2960,17 @@ 
      Static methods
      
 reducing memory usage and open file handles.  However, in many cases this is not
 desirable, since the associated Variable instances may still be needed, but are
 rendered unusable when the parent Dataset instance is garbage collected.
      
-
      memory: if not None, open file with contents taken from this block of memory.
-Must be a sequence of bytes.  Note this only works with "r" mode.
      
+
      memory: if not None, create or open an in-memory Dataset.
+If mode = 'r', the memory kwarg must contain a memory buffer object
+(an object that supports the python buffer interface).
+The Dataset will then be created with contents taken from this block of memory.
+If mode = 'w', the memory kwarg should contain the anticipated size
+of the Dataset in bytes (used only for NETCDF3 files).  A memory
+buffer containing a copy of the Dataset is returned by the
+Dataset.close method. Requires netcdf-c version 4.4.1 for mode='r,
+netcdf-c 4.6.2 for mode='w'. To persist the file to disk, the raw
+bytes from the returned buffer can be written into a binary file.
+The Dataset can also be re-opened using this memory buffer.
      
 
      encoding: encoding used to encode filename string into bytes.
 Default is None (sys.getdefaultfileencoding() is used).
      
 
      parallel: open for parallel access using MPI (requires mpi4py and
@@ -5820,6 +5905,20 @@ 
      Methods
      
 
     
   
+  
      
+
      
+
+  
      
+  
+            
+  
      
+    
      
+    
      def set_always_mask(
      ...)
      
+    
      
+    
+
+    
+  
   
      
 
      
 

From 89fbbb7d4f56671a858f3529997611f51fa0bc36 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 28 Jan 2019 06:48:23 -0700
Subject: [PATCH 0192/1504] remove un-needed import

---
 include/membuf.pyx | 1 -
 1 file changed, 1 deletion(-)

diff --git a/include/membuf.pyx b/include/membuf.pyx
index 15ec4dbdc..18dfc7bb0 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -5,7 +5,6 @@
 from cpython.buffer cimport PyBuffer_FillInfo, PyBuffer_Release
 from cpython.bytes cimport PyBytes_FromStringAndSize
 from libc.stdlib cimport free
-from libc.string cimport memcpy
 from libc.stdint cimport uintptr_t
 
 ctypedef void dealloc_callback(const void *p, size_t l, void *arg)

From 80413ff121bf91d47998935a5d4f324bbd295e23 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 28 Jan 2019 06:49:26 -0700
Subject: [PATCH 0193/1504] update

---
 Changelog | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Changelog b/Changelog
index 62ca4b28c..431eab507 100644
--- a/Changelog
+++ b/Changelog
@@ -2,7 +2,7 @@
 =============================
  * make set_always_mask work in MFDataset.
  * fix saving diskless files to disk with netcdf-c >= 4.6.2.
- * write to an in-memory Dataset, bytes returned by Dataset.close()
+ * write to an in-memory Dataset, memory buffer returned by Dataset.close()
    (issue #865)
 
  version 1.4.2 (tag v1.4.2rel)

From fe09a144cfa6af5d0d3e5cff8e44dddc7ec85ac3 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 28 Jan 2019 07:07:30 -0700
Subject: [PATCH 0194/1504] flags arg should be passed to __getbuffer__ not
 __releasebuffer__

---
 include/membuf.pyx | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/include/membuf.pyx b/include/membuf.pyx
index 18dfc7bb0..9d5d85794 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -33,10 +33,12 @@ cdef class MemBuf:
     cdef const void *get_mem(self):
         return self.p
 
-    def __getbuffer__(self, Py_buffer *view, int flags):
-        PyBuffer_FillInfo(view, self, self.p, self.l, 1, flags)
+    def __getbuffer__(self, Py_buffer *buffer, int flags):
+        cdef int ret,readonly
+        readonly=1
+        ret=PyBuffer_FillInfo(buffer, self, self.p, self.l, readonly, flags)
 
-    def __releasebuffer__(self, Py_buffer *view):
+    def __releasebuffer__(self, Py_buffer *buffer):
         #PyBuffer_Release(view) 
         pass
 

From e2f33b472a782cd23041ddd8582bd854340a8475 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 28 Jan 2019 10:08:04 -0700
Subject: [PATCH 0195/1504] don't use builtin buffer as variable name

---
 include/membuf.pyx | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/include/membuf.pyx b/include/membuf.pyx
index 9d5d85794..5bf34f993 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -33,13 +33,13 @@ cdef class MemBuf:
     cdef const void *get_mem(self):
         return self.p
 
-    def __getbuffer__(self, Py_buffer *buffer, int flags):
+    def __getbuffer__(self, Py_buffer *buf, int flags):
         cdef int ret,readonly
         readonly=1
-        ret=PyBuffer_FillInfo(buffer, self, self.p, self.l, readonly, flags)
+        ret=PyBuffer_FillInfo(buf, self, self.p, self.l, readonly, flags)
 
-    def __releasebuffer__(self, Py_buffer *buffer):
-        #PyBuffer_Release(view) 
+    def __releasebuffer__(self, Py_buffer *buf):
+        #PyBuffer_Release(buf) 
         pass
 
     def __dealloc__(self):

From f7a1a5d56f650bd006c093f074c0b5ec9888eee1 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 28 Jan 2019 10:35:07 -0700
Subject: [PATCH 0196/1504] return python memoryview object from
 Dataset.close()

---
 examples/tutorial.py |  7 +++----
 include/membuf.pyx   |  2 +-
 netCDF4/_netCDF4.pyx | 13 +++++++------
 3 files changed, 11 insertions(+), 11 deletions(-)

diff --git a/examples/tutorial.py b/examples/tutorial.py
index ca872989a..1c1e0179b 100644
--- a/examples/tutorial.py
+++ b/examples/tutorial.py
@@ -347,12 +347,11 @@ def walktree(top):
 d = nc.createDimension('x',None)
 v = nc.createVariable('v',numpy.int32,'x')
 v[0:5] = numpy.arange(5)
-nc_buf = nc.close() # close returns memory buffer.
+nc_buf = nc.close() # close returns memoryview
 print type(nc_buf)
 # save nc_buf to disk, read it back in and check.
-# tobytes method of cython memory buffer converts to bytes.
-f = open('inmemory.nc', 'w')
-f.write(nc_buf.tobytes()); f.close()
+f = open('inmemory.nc', 'wb')
+f.write(nc_buf); f.close()
 nc = Dataset('inmemory.nc')
 print(nc)
 print(nc['v'][:])
diff --git a/include/membuf.pyx b/include/membuf.pyx
index 5bf34f993..4adb218d6 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -16,7 +16,7 @@ cdef void free_buf(const void *p, size_t l, void *arg):
 # a raw pointer.
 cdef makebuf(void *p, size_t l):
     assert p!=NULL, "invalid NULL buffer pointer"
-    return MemBuf_init(p, l, &free_buf, NULL)
+    return memoryview( MemBuf_init(p, l, &free_buf, NULL) )
 
 cdef class MemBuf:
     cdef const void *p
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 66af088cd..d8ddebad2 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1074,8 +1074,8 @@ create a new read-only Dataset from an existing python memory buffer, use the
 If you want to create a new in-memory Dataset, and then access the memory buffer
 directly from Python, use the `memory` keyword argument to specify the
 estimated size of the Dataset in bytes when creating the Dataset with
-`mode='w'`.  Then, the `Dataset.close` method will return a python memory
-buffer representing the Dataset. Below are examples illustrating both
+`mode='w'`.  Then, the `Dataset.close` method will return a python memoryview
+object representing the Dataset. Below are examples illustrating both
 approaches.
 
     :::python
@@ -1119,11 +1119,12 @@ approaches.
     >>> d = nc.createDimension('x',None)
     >>> v = nc.createVariable('v',numpy.int32,'x')
     >>> v[0:5] = numpy.arange(5)
-    >>> nc_buf = nc.close() # close returns memory buffer.
+    >>> nc_buf = nc.close() # close returns memoryview
+    >>> print(type(nc_buf))
+    
     >>> # save nc_buf to disk, read it back in and check.
-    >>> # tobytes method of cython memory buffer converts to bytes.
-    >>> f = open('inmemory.nc', 'w')
-    >>> f.write(nc_buf.tobytes()); f.close()
+    >>> f = open('inmemory.nc', 'wb')
+    >>> f.write(nc_buf); f.close()
     >>> nc = Dataset('inmemory.nc')
     >>> print(nc)
     

From 42b5c03af7db2cbf8a74fb339b7a13951dd40a7d Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 28 Jan 2019 10:36:56 -0700
Subject: [PATCH 0197/1504] update

---
 include/membuf.pyx | 1 +
 1 file changed, 1 insertion(+)

diff --git a/include/membuf.pyx b/include/membuf.pyx
index 4adb218d6..97fc15f2c 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -46,6 +46,7 @@ cdef class MemBuf:
         if self.dealloc_cb_p != NULL:
             self.dealloc_cb_p(self.p, self.l, self.dealloc_cb_arg)
 
+    # not really needed if MemBuf converted to memoryview
     def tobytes(self):
         return PyBytes_FromStringAndSize(self.p, self.l)
 

From ca66bcde21f5603f7e920db79c189ebfe6009c08 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 28 Jan 2019 18:36:53 -0700
Subject: [PATCH 0198/1504] update docs

---
 docs/netCDF4/index.html | 13 +++++++------
 1 file changed, 7 insertions(+), 6 deletions(-)

diff --git a/docs/netCDF4/index.html b/docs/netCDF4/index.html
index c07e0353f..147ab5b48 100644
--- a/docs/netCDF4/index.html
+++ b/docs/netCDF4/index.html
@@ -2299,8 +2299,8 @@ 
      15) In-memory (diskless) Datasets.
      
 If you want to create a new in-memory Dataset, and then access the memory buffer
 directly from Python, use the memory keyword argument to specify the
 estimated size of the Dataset in bytes when creating the Dataset with
-mode='w'.  Then, the Dataset.close method will return a python memory
-buffer representing the Dataset. Below are examples illustrating both
+mode='w'.  Then, the Dataset.close method will return a python memoryview
+object representing the Dataset. Below are examples illustrating both
 approaches.
      
 
      >>> # create a diskless (in-memory) Dataset, 
 >>> # and persist the file to disk when it is closed.
@@ -2342,11 +2342,12 @@ 
      15) In-memory (diskless) Datasets.
      
 >>> d = nc.createDimension('x',None)
 >>> v = nc.createVariable('v',numpy.int32,'x')
 >>> v[0:5] = numpy.arange(5)
->>> nc_buf = nc.close() # close returns memory buffer.
+>>> nc_buf = nc.close() # close returns memoryview
+>>> print(type(nc_buf))
+<type 'memoryview'>
 >>> # save nc_buf to disk, read it back in and check.
->>> # tobytes method of cython memory buffer converts to bytes.
->>> f = open('inmemory.nc', 'w')
->>> f.write(nc_buf.tobytes()); f.close()
+>>> f = open('inmemory.nc', 'wb')
+>>> f.write(nc_buf); f.close()
 >>> nc = Dataset('inmemory.nc')
 >>> print(nc)
 <type 'netCDF4._netCDF4.Dataset'>

From fae2c8b8d3f786623b7db4622a6b62b3965c4e14 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 29 Jan 2019 09:06:15 -0700
Subject: [PATCH 0199/1504] fix print

---
 examples/tutorial.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/tutorial.py b/examples/tutorial.py
index 1c1e0179b..13e339912 100644
--- a/examples/tutorial.py
+++ b/examples/tutorial.py
@@ -348,7 +348,7 @@ def walktree(top):
 v = nc.createVariable('v',numpy.int32,'x')
 v[0:5] = numpy.arange(5)
 nc_buf = nc.close() # close returns memoryview
-print type(nc_buf)
+print(type(nc_buf))
 # save nc_buf to disk, read it back in and check.
 f = open('inmemory.nc', 'wb')
 f.write(nc_buf); f.close()

From d2c92e3f900c7eada7afba5d60c750d77b1d5ab5 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 29 Jan 2019 09:11:06 -0700
Subject: [PATCH 0200/1504] rename makebuf to memview_fromptr

---
 include/membuf.pyx   | 2 +-
 netCDF4/_netCDF4.pyx | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/include/membuf.pyx b/include/membuf.pyx
index 97fc15f2c..240f9bc60 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -14,7 +14,7 @@ cdef void free_buf(const void *p, size_t l, void *arg):
 
 # this is the function used to create a memory view from
 # a raw pointer.
-cdef makebuf(void *p, size_t l):
+cdef memview_fromptr(void *p, size_t l):
     assert p!=NULL, "invalid NULL buffer pointer"
     return memoryview( MemBuf_init(p, l, &free_buf, NULL) )
 
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index d8ddebad2..a30dc4445 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2395,7 +2395,7 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
 
             # makebuf from membuf.pyx - creates a python memoryview
             # from a raw pointer without making a copy.
-            return makebuf(memio.memory, memio.size)
+            return memview_fromptr(memio.memory, memio.size)
 
 
     def close(self):

From 515a2ecfbbde57f200b53e47fac3a82c5f2bc478 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 29 Jan 2019 10:35:54 -0700
Subject: [PATCH 0201/1504] rename MemBuf to _MemBuf to indicate that it is a
 private extension type (only memview_fromptr is intended to be used by
 external cython code)

---
 include/membuf.pyx | 14 ++++++++------
 1 file changed, 8 insertions(+), 6 deletions(-)

diff --git a/include/membuf.pyx b/include/membuf.pyx
index 240f9bc60..c6fffcad1 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -14,11 +14,13 @@ cdef void free_buf(const void *p, size_t l, void *arg):
 
 # this is the function used to create a memory view from
 # a raw pointer.
+# Only this function is intended to be used from external
+# cython code.
 cdef memview_fromptr(void *p, size_t l):
     assert p!=NULL, "invalid NULL buffer pointer"
     return memoryview( MemBuf_init(p, l, &free_buf, NULL) )
 
-cdef class MemBuf:
+cdef class _MemBuf:
     cdef const void *p
     cdef size_t l
     cdef dealloc_callback *dealloc_cb_p
@@ -28,7 +30,7 @@ cdef class MemBuf:
         return self.l
 
     def __repr__(self):
-        return "MemBuf(%#x)" % ( self.p)
+        return "_MemBuf(%#x)" % ( self.p)
 
     cdef const void *get_mem(self):
         return self.p
@@ -46,18 +48,18 @@ cdef class MemBuf:
         if self.dealloc_cb_p != NULL:
             self.dealloc_cb_p(self.p, self.l, self.dealloc_cb_arg)
 
-    # not really needed if MemBuf converted to memoryview
+    # not really needed if _MemBuf converted to memoryview
     def tobytes(self):
         return PyBytes_FromStringAndSize(self.p, self.l)
 
-# Call this instead of constructing a MemBuf directly.  The __cinit__
+# Call this instead of constructing a _MemBuf directly.  The __cinit__
 # and __init__ methods can only take Python objects, so the real
 # constructor is here.  See:
 # https://mail.python.org/pipermail/cython-devel/2012-June/002734.html
-cdef MemBuf MemBuf_init(const void *p, size_t l,
+cdef _MemBuf MemBuf_init(const void *p, size_t l,
                         dealloc_callback *dealloc_cb_p,
                         void *dealloc_cb_arg):
-    cdef MemBuf ret = MemBuf()
+    cdef _MemBuf ret = _MemBuf()
     ret.p = p
     ret.l = l
     ret.dealloc_cb_p = dealloc_cb_p

From e7ae752e980e0ceaea881d6fc4cb52523ab9ee36 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 29 Jan 2019 10:40:40 -0700
Subject: [PATCH 0202/1504] update comments

---
 include/membuf.pyx | 11 +++++------
 1 file changed, 5 insertions(+), 6 deletions(-)

diff --git a/include/membuf.pyx b/include/membuf.pyx
index c6fffcad1..8b0e99a74 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -1,7 +1,7 @@
-# Buffer code found here similar to
-# http://stackoverflow.com/a/28166272/428751
-# Allows to return a malloced python buffer,
+# Creates a memoryview from a malloced C pointer,
 # which will be freed when the python object is garbage collected.
+# Code found here is derived from
+# http://stackoverflow.com/a/28166272/428751
 from cpython.buffer cimport PyBuffer_FillInfo, PyBuffer_Release
 from cpython.bytes cimport PyBytes_FromStringAndSize
 from libc.stdlib cimport free
@@ -41,7 +41,7 @@ cdef class _MemBuf:
         ret=PyBuffer_FillInfo(buf, self, self.p, self.l, readonly, flags)
 
     def __releasebuffer__(self, Py_buffer *buf):
-        #PyBuffer_Release(buf) 
+        # why doesn't this do anything??
         pass
 
     def __dealloc__(self):
@@ -54,8 +54,7 @@ cdef class _MemBuf:
 
 # Call this instead of constructing a _MemBuf directly.  The __cinit__
 # and __init__ methods can only take Python objects, so the real
-# constructor is here.  See:
-# https://mail.python.org/pipermail/cython-devel/2012-June/002734.html
+# constructor is here.  
 cdef _MemBuf MemBuf_init(const void *p, size_t l,
                         dealloc_callback *dealloc_cb_p,
                         void *dealloc_cb_arg):

From d381e24d2c87b67225fd5d6d980fa89a62da93d9 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 29 Jan 2019 10:58:38 -0700
Subject: [PATCH 0203/1504] remove unused functions

---
 include/membuf.pyx | 50 ++++++++++++++++++----------------------------
 1 file changed, 19 insertions(+), 31 deletions(-)

diff --git a/include/membuf.pyx b/include/membuf.pyx
index 8b0e99a74..49c79e4d1 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -7,60 +7,48 @@ from cpython.bytes cimport PyBytes_FromStringAndSize
 from libc.stdlib cimport free
 from libc.stdint cimport uintptr_t
 
-ctypedef void dealloc_callback(const void *p, size_t l, void *arg)
+ctypedef void dealloc_callback(const void *memory, size_t size, void *arg)
 
-cdef void free_buf(const void *p, size_t l, void *arg):
-    free(p)
+cdef void free_buf(const void *memory, size_t size, void *arg):
+    free(memory)
 
 # this is the function used to create a memory view from
 # a raw pointer.
 # Only this function is intended to be used from external
 # cython code.
-cdef memview_fromptr(void *p, size_t l):
-    assert p!=NULL, "invalid NULL buffer pointer"
-    return memoryview( MemBuf_init(p, l, &free_buf, NULL) )
+cdef memview_fromptr(void *memory, size_t size):
+    # memory is malloced void pointer, size is number of bytes allocated
+    if memory==NULL:
+        raise MemoryError('no memory allocated to pointer')
+    return memoryview( MemBuf_init(memory, size, &free_buf, NULL) )
 
 cdef class _MemBuf:
-    cdef const void *p
-    cdef size_t l
-    cdef dealloc_callback *dealloc_cb_p
+    cdef const void *memory
+    cdef size_t size
+    cdef dealloc_callback *dealloc_cb
     cdef void *dealloc_cb_arg
 
-    def __len__(self):
-        return self.l
-
-    def __repr__(self):
-        return "_MemBuf(%#x)" % ( self.p)
-
-    cdef const void *get_mem(self):
-        return self.p
-
     def __getbuffer__(self, Py_buffer *buf, int flags):
         cdef int ret,readonly
         readonly=1
-        ret=PyBuffer_FillInfo(buf, self, self.p, self.l, readonly, flags)
+        ret=PyBuffer_FillInfo(buf, self, self.memory, self.size, readonly, flags)
 
     def __releasebuffer__(self, Py_buffer *buf):
         # why doesn't this do anything??
         pass
 
     def __dealloc__(self):
-        if self.dealloc_cb_p != NULL:
-            self.dealloc_cb_p(self.p, self.l, self.dealloc_cb_arg)
-
-    # not really needed if _MemBuf converted to memoryview
-    def tobytes(self):
-        return PyBytes_FromStringAndSize(self.p, self.l)
+        self.dealloc_cb(self.memory, self.size, self.dealloc_cb_arg)
 
 # Call this instead of constructing a _MemBuf directly.  The __cinit__
 # and __init__ methods can only take Python objects, so the real
 # constructor is here.  
-cdef _MemBuf MemBuf_init(const void *p, size_t l,
-                        dealloc_callback *dealloc_cb_p,
+cdef _MemBuf MemBuf_init(const void *memory, size_t size,
+                        dealloc_callback *dealloc_cb,
                         void *dealloc_cb_arg):
     cdef _MemBuf ret = _MemBuf()
-    ret.p = p
-    ret.l = l
-    ret.dealloc_cb_p = dealloc_cb_p
-    ret.dealloc_cb_arg = dealloc_cb_arg
+    ret.memory = memory # malloced void pointer
+    ret.size = size # size of pointer in bytes
+    ret.dealloc_cb = dealloc_cb # callback function to free memory
+    ret.dealloc_cb_arg = dealloc_cb_arg # optional args to callback function
     return ret

From db7d3abe7ff590337f3c9a37c346fabd5a1e2e11 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 29 Jan 2019 11:02:02 -0700
Subject: [PATCH 0204/1504] remove unused var

---
 include/membuf.pyx | 11 ++++-------
 1 file changed, 4 insertions(+), 7 deletions(-)

diff --git a/include/membuf.pyx b/include/membuf.pyx
index 49c79e4d1..b46a12f6e 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -7,9 +7,9 @@ from cpython.bytes cimport PyBytes_FromStringAndSize
 from libc.stdlib cimport free
 from libc.stdint cimport uintptr_t
 
-ctypedef void dealloc_callback(const void *memory, size_t size, void *arg)
+ctypedef void dealloc_callback(const void *memory, size_t size)
 
-cdef void free_buf(const void *memory, size_t size, void *arg):
+cdef void free_buf(const void *memory, size_t size):
     free(memory)
 
 # this is the function used to create a memory view from
@@ -26,7 +26,6 @@ cdef class _MemBuf:
     cdef const void *memory
     cdef size_t size
     cdef dealloc_callback *dealloc_cb
-    cdef void *dealloc_cb_arg
 
     def __getbuffer__(self, Py_buffer *buf, int flags):
         cdef int ret,readonly
@@ -38,17 +37,15 @@ cdef class _MemBuf:
         pass
 
     def __dealloc__(self):
-        self.dealloc_cb(self.memory, self.size, self.dealloc_cb_arg)
+        self.dealloc_cb(self.memory, self.size)
 
 # Call this instead of constructing a _MemBuf directly.  The __cinit__
 # and __init__ methods can only take Python objects, so the real
 # constructor is here.  
 cdef _MemBuf MemBuf_init(const void *memory, size_t size,
-                        dealloc_callback *dealloc_cb,
-                        void *dealloc_cb_arg):
+                        dealloc_callback *dealloc_cb)
     cdef _MemBuf ret = _MemBuf()
     ret.memory = memory # malloced void pointer
     ret.size = size # size of pointer in bytes
     ret.dealloc_cb = dealloc_cb # callback function to free memory
-    ret.dealloc_cb_arg = dealloc_cb_arg # optional args to callback function
     return ret

From fd63420375de51480852938bbd759a4ca55b9f49 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 29 Jan 2019 11:05:48 -0700
Subject: [PATCH 0205/1504] remove more unused vars

---
 include/membuf.pyx | 10 +++-------
 1 file changed, 3 insertions(+), 7 deletions(-)

diff --git a/include/membuf.pyx b/include/membuf.pyx
index b46a12f6e..4b05d9c4d 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -2,10 +2,8 @@
 # which will be freed when the python object is garbage collected.
 # Code found here is derived from
 # http://stackoverflow.com/a/28166272/428751
-from cpython.buffer cimport PyBuffer_FillInfo, PyBuffer_Release
-from cpython.bytes cimport PyBytes_FromStringAndSize
+from cpython.buffer cimport PyBuffer_FillInfo
 from libc.stdlib cimport free
-from libc.stdint cimport uintptr_t
 
 ctypedef void dealloc_callback(const void *memory, size_t size)
 
@@ -28,9 +26,7 @@ cdef class _MemBuf:
     cdef dealloc_callback *dealloc_cb
 
     def __getbuffer__(self, Py_buffer *buf, int flags):
-        cdef int ret,readonly
-        readonly=1
-        ret=PyBuffer_FillInfo(buf, self, self.memory, self.size, readonly, flags)
+        PyBuffer_FillInfo(buf, self, self.memory, self.size, 1, flags)
 
     def __releasebuffer__(self, Py_buffer *buf):
         # why doesn't this do anything??
@@ -41,7 +37,7 @@ cdef class _MemBuf:
 
 # Call this instead of constructing a _MemBuf directly.  The __cinit__
 # and __init__ methods can only take Python objects, so the real
-# constructor is here.  
+# constructor is here.
 cdef _MemBuf MemBuf_init(const void *memory, size_t size,
                         dealloc_callback *dealloc_cb)
     cdef _MemBuf ret = _MemBuf()

From af9da6bf6ab994f5473e6dc2c5f9a928d7ab31e3 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 29 Jan 2019 11:07:21 -0700
Subject: [PATCH 0206/1504] fix number of args passed to MemBuf_init

---
 include/membuf.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/include/membuf.pyx b/include/membuf.pyx
index 4b05d9c4d..7e216c747 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -18,7 +18,7 @@ cdef memview_fromptr(void *memory, size_t size):
     # memory is malloced void pointer, size is number of bytes allocated
     if memory==NULL:
         raise MemoryError('no memory allocated to pointer')
-    return memoryview( MemBuf_init(memory, size, &free_buf, NULL) )
+    return memoryview( MemBuf_init(memory, size, &free_buf) )
 
 cdef class _MemBuf:
     cdef const void *memory

From 709038d376aaf2e1dcbf4fcaf921c6d9d9691500 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 29 Jan 2019 11:09:02 -0700
Subject: [PATCH 0207/1504] fix typo

---
 include/membuf.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/include/membuf.pyx b/include/membuf.pyx
index 7e216c747..2dab38d05 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -39,7 +39,7 @@ cdef class _MemBuf:
 # and __init__ methods can only take Python objects, so the real
 # constructor is here.
 cdef _MemBuf MemBuf_init(const void *memory, size_t size,
-                        dealloc_callback *dealloc_cb)
+                         dealloc_callback *dealloc_cb):
     cdef _MemBuf ret = _MemBuf()
     ret.memory = memory # malloced void pointer
     ret.size = size # size of pointer in bytes

From f7795eb85778ef4f0a96cee94d9327afdd897ddf Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 29 Jan 2019 11:16:25 -0700
Subject: [PATCH 0208/1504] further simplifiy

---
 include/membuf.pyx | 14 +++-----------
 1 file changed, 3 insertions(+), 11 deletions(-)

diff --git a/include/membuf.pyx b/include/membuf.pyx
index 2dab38d05..372aacee3 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -5,11 +5,6 @@
 from cpython.buffer cimport PyBuffer_FillInfo
 from libc.stdlib cimport free
 
-ctypedef void dealloc_callback(const void *memory, size_t size)
-
-cdef void free_buf(const void *memory, size_t size):
-    free(memory)
-
 # this is the function used to create a memory view from
 # a raw pointer.
 # Only this function is intended to be used from external
@@ -18,12 +13,11 @@ cdef memview_fromptr(void *memory, size_t size):
     # memory is malloced void pointer, size is number of bytes allocated
     if memory==NULL:
         raise MemoryError('no memory allocated to pointer')
-    return memoryview( MemBuf_init(memory, size, &free_buf) )
+    return memoryview( MemBuf_init(memory, size) )
 
 cdef class _MemBuf:
     cdef const void *memory
     cdef size_t size
-    cdef dealloc_callback *dealloc_cb
 
     def __getbuffer__(self, Py_buffer *buf, int flags):
         PyBuffer_FillInfo(buf, self, self.memory, self.size, 1, flags)
@@ -33,15 +27,13 @@ cdef class _MemBuf:
         pass
 
     def __dealloc__(self):
-        self.dealloc_cb(self.memory, self.size)
+        free(self.memory)
 
 # Call this instead of constructing a _MemBuf directly.  The __cinit__
 # and __init__ methods can only take Python objects, so the real
 # constructor is here.
-cdef _MemBuf MemBuf_init(const void *memory, size_t size,
-                         dealloc_callback *dealloc_cb):
+cdef _MemBuf MemBuf_init(const void *memory, size_t size):
     cdef _MemBuf ret = _MemBuf()
     ret.memory = memory # malloced void pointer
     ret.size = size # size of pointer in bytes
-    ret.dealloc_cb = dealloc_cb # callback function to free memory
     return ret

From 0eddbf3c719c553cd490b25858fc3b59a6577b59 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 29 Jan 2019 11:20:03 -0700
Subject: [PATCH 0209/1504] remove blank lines

---
 include/membuf.pyx | 3 ---
 1 file changed, 3 deletions(-)

diff --git a/include/membuf.pyx b/include/membuf.pyx
index 372aacee3..e638a811e 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -18,14 +18,11 @@ cdef memview_fromptr(void *memory, size_t size):
 cdef class _MemBuf:
     cdef const void *memory
     cdef size_t size
-
     def __getbuffer__(self, Py_buffer *buf, int flags):
         PyBuffer_FillInfo(buf, self, self.memory, self.size, 1, flags)
-
     def __releasebuffer__(self, Py_buffer *buf):
         # why doesn't this do anything??
         pass
-
     def __dealloc__(self):
         free(self.memory)
 

From 46144ba698727aa874b18d042f191611478f4a7c Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 29 Jan 2019 18:41:17 -0700
Subject: [PATCH 0210/1504] simplify further

---
 include/membuf.pyx | 14 ++++----------
 1 file changed, 4 insertions(+), 10 deletions(-)

diff --git a/include/membuf.pyx b/include/membuf.pyx
index e638a811e..fac73a6bb 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -10,10 +10,13 @@ from libc.stdlib cimport free
 # Only this function is intended to be used from external
 # cython code.
 cdef memview_fromptr(void *memory, size_t size):
+    cdef _MemBuf buf = _MemBuf()
+    buf.memory = memory # malloced void pointer
+    buf.size = size # size of pointer in bytes
     # memory is malloced void pointer, size is number of bytes allocated
     if memory==NULL:
         raise MemoryError('no memory allocated to pointer')
-    return memoryview( MemBuf_init(memory, size) )
+    return memoryview( buf )
 
 cdef class _MemBuf:
     cdef const void *memory
@@ -25,12 +28,3 @@ cdef class _MemBuf:
         pass
     def __dealloc__(self):
         free(self.memory)
-
-# Call this instead of constructing a _MemBuf directly.  The __cinit__
-# and __init__ methods can only take Python objects, so the real
-# constructor is here.
-cdef _MemBuf MemBuf_init(const void *memory, size_t size):
-    cdef _MemBuf ret = _MemBuf()
-    ret.memory = memory # malloced void pointer
-    ret.size = size # size of pointer in bytes
-    return ret

From 78a2c1b8dd9b02b470809eaabcd15849f853f4bc Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 29 Jan 2019 18:42:28 -0700
Subject: [PATCH 0211/1504] update

---
 include/membuf.pyx | 3 ---
 1 file changed, 3 deletions(-)

diff --git a/include/membuf.pyx b/include/membuf.pyx
index fac73a6bb..cde45bc63 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -13,9 +13,6 @@ cdef memview_fromptr(void *memory, size_t size):
     cdef _MemBuf buf = _MemBuf()
     buf.memory = memory # malloced void pointer
     buf.size = size # size of pointer in bytes
-    # memory is malloced void pointer, size is number of bytes allocated
-    if memory==NULL:
-        raise MemoryError('no memory allocated to pointer')
     return memoryview( buf )
 
 cdef class _MemBuf:

From 76acb9af8e758fb946c1ce50b2792af978f42b90 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 29 Jan 2019 19:08:54 -0700
Subject: [PATCH 0212/1504] update

---
 include/membuf.pyx | 8 +++-----
 1 file changed, 3 insertions(+), 5 deletions(-)

diff --git a/include/membuf.pyx b/include/membuf.pyx
index cde45bc63..b964453e9 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -5,16 +5,14 @@
 from cpython.buffer cimport PyBuffer_FillInfo
 from libc.stdlib cimport free
 
-# this is the function used to create a memory view from
-# a raw pointer.
-# Only this function is intended to be used from external
-# cython code.
+# create a python memoryview object from a raw pointer.
 cdef memview_fromptr(void *memory, size_t size):
     cdef _MemBuf buf = _MemBuf()
     buf.memory = memory # malloced void pointer
     buf.size = size # size of pointer in bytes
-    return memoryview( buf )
+    return memoryview(buf)
 
+# private extension type that implements buffer protocal.
 cdef class _MemBuf:
     cdef const void *memory
     cdef size_t size

From 01ca46a17f6553f2727a43da8e1e9baf44d33285 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 29 Jan 2019 20:58:52 -0700
Subject: [PATCH 0213/1504] update comment

---
 netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index a30dc4445..9a23193b3 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2393,7 +2393,7 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
             self._isopen = 0
             PyBuffer_Release(&self._buffer)
 
-            # makebuf from membuf.pyx - creates a python memoryview
+            # membuf_fromptr from membuf.pyx - creates a python memoryview
             # from a raw pointer without making a copy.
             return memview_fromptr(memio.memory, memio.size)
 

From a5325ff281d3ce178262eb135eca5751b2f4cd29 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 30 Jan 2019 09:30:11 -0700
Subject: [PATCH 0214/1504] update

---
 Changelog | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/Changelog b/Changelog
index 431eab507..3cc6543cb 100644
--- a/Changelog
+++ b/Changelog
@@ -2,8 +2,8 @@
 =============================
  * make set_always_mask work in MFDataset.
  * fix saving diskless files to disk with netcdf-c >= 4.6.2.
- * write to an in-memory Dataset, memory buffer returned by Dataset.close()
-   (issue #865)
+ * write to an in-memory Dataset, memoryview buffer returned by Dataset.close()
+   (issue #865, requires netcdf-c >= 4.6.2)
 
  version 1.4.2 (tag v1.4.2rel)
 =============================

From 40d9cb29404e847971cd180ea3f66efecea88930 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 5 Feb 2019 22:01:09 -0700
Subject: [PATCH 0215/1504] potential fix for issue #870

---
 netCDF4/utils.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/netCDF4/utils.py b/netCDF4/utils.py
index a27cb19c9..327ddef93 100644
--- a/netCDF4/utils.py
+++ b/netCDF4/utils.py
@@ -305,7 +305,7 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
                 ee = range(start,stop,step)
             except ValueError: # start, stop or step is not valid for a range
                 ee = False
-            if no_get_vars and ee and len(e) == len(ee) and (e == np.arange(start,stop,step)).all():
+            if ee and len(e) == len(ee) and (e == np.arange(start,stop,step)).all():
                 # don't convert to slice unless abs(stride) == 1
                 # (nc_get_vars is very slow, issue #680)
                 if step not in [1,-1]:

From 354be83c1502568903d7b88c78652be7d294463c Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 5 Feb 2019 22:04:45 -0700
Subject: [PATCH 0216/1504] update

---
 netCDF4/utils.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/netCDF4/utils.py b/netCDF4/utils.py
index 327ddef93..87ae91a4d 100644
--- a/netCDF4/utils.py
+++ b/netCDF4/utils.py
@@ -308,7 +308,7 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
             if ee and len(e) == len(ee) and (e == np.arange(start,stop,step)).all():
                 # don't convert to slice unless abs(stride) == 1
                 # (nc_get_vars is very slow, issue #680)
-                if step not in [1,-1]:
+                if no_get_vars and step not in [1,-1]:
                     newElem.append(e)
                 else:
                     newElem.append(slice(start,stop,step))

From b732306877ac8420627b6f6647f59632cb6378df Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 6 Feb 2019 07:19:16 -0700
Subject: [PATCH 0217/1504] bump version number

---
 Changelog            | 4 +++-
 netCDF4/_netCDF4.pyx | 2 +-
 setup.py             | 2 +-
 3 files changed, 5 insertions(+), 3 deletions(-)

diff --git a/Changelog b/Changelog
index ace802956..92e2025ab 100644
--- a/Changelog
+++ b/Changelog
@@ -1,7 +1,9 @@
- since version 1.4.2
+ version 1.4.3 (not yet released)
 =============================
  * make set_always_mask work in MFDataset.
  * fix saving diskless files to disk with netcdf-c >= 4.6.2.
+ * fix performance regression when using large sequences of consecutive
+   integers for indexing with netcdf-c >= 4.6.2 (issue #870).
 
  version 1.4.2 (tag v1.4.2rel)
 =============================
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index cf50b3ecf..2916d29f4 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1104,7 +1104,7 @@ except ImportError:
     # python3: zip is already python2's itertools.izip
     pass
 
-__version__ = "1.4.2"
+__version__ = "1.4.3"
 
 # Initialize numpy
 import posixpath
diff --git a/setup.py b/setup.py
index c61045889..2b5c086e4 100644
--- a/setup.py
+++ b/setup.py
@@ -553,7 +553,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 
 setup(name="netCDF4",
       cmdclass=cmdclass,
-      version="1.4.2",
+      version="1.4.3",
       long_description="netCDF version 4 has many features not found in earlier versions of the library, such as hierarchical groups, zlib compression, multiple unlimited dimensions, and new data types.  It is implemented on top of HDF5.  This module implements most of the new features, and can read and write netCDF files compatible with older versions of the library.  The API is modelled after Scientific.IO.NetCDF, and should be familiar to users of that module.\n\nThis project is hosted on a `GitHub repository `_ where you may access the most up-to-date source.",
       author="Jeff Whitaker",
       author_email="jeffrey.s.whitaker@noaa.gov",

From 0dfa2a4eb72814a099050e31293edc627cf801de Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 6 Feb 2019 09:18:57 -0700
Subject: [PATCH 0218/1504] change no_get_vars to use_get_vars for clarity

---
 netCDF4/_netCDF4.pyx | 16 ++++++++--------
 netCDF4/utils.py     |  6 +++---
 2 files changed, 11 insertions(+), 11 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 9a23193b3..e8d343717 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1846,7 +1846,7 @@ _private_atts = \
  '_nunlimdim','path','parent','ndim','mask','scale','cmptypes','vltypes','enumtypes','_isprimitive',
  'file_format','_isvlen','_isenum','_iscompound','_cmptype','_vltype','_enumtype','name',
  '__orthogoral_indexing__','keepweakref','_has_lsd',
- '_buffer','chartostring','_no_get_vars']
+ '_buffer','chartostring','_use_get_vars']
 __pdoc__ = {}
 
 cdef class Dataset:
@@ -3396,7 +3396,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
     cdef public int _varid, _grpid, _nunlimdim
     cdef public _name, ndim, dtype, mask, scale, always_mask, chartostring,  _isprimitive, \
     _iscompound, _isvlen, _isenum, _grp, _cmptype, _vltype, _enumtype,\
-    __orthogonal_indexing__, _has_lsd, _no_get_vars
+    __orthogonal_indexing__, _has_lsd, _use_get_vars
     # Docstrings for class variables (used by pdoc).
     __pdoc__['Variable.dimensions'] = \
     """A tuple containing the names of the
@@ -3422,7 +3422,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
     arrays to string arrays when `_Encoding` variable attribute is set.
     Default is `True`, can be reset using
     `netCDF4.Variable.set_auto_chartostring` method."""
-    __pdoc__['Variable._no_get_vars'] = \
+    __pdoc__['Variable._use_get_vars'] = \
     """If True (default), netcdf routine `nc_get_vars` is not used for strided slicing
     slicing. Can be re-set using `netCDF4.Variable.use_nc_get_vars` method."""
     __pdoc__['Variable.least_significant_digit'] = \
@@ -3808,9 +3808,9 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         # always use nc_get_vars for strided access with OpenDAP (issue #838).
         if __netcdf4libversion__ >= "4.6.2" or\
            self._grp.filepath().startswith('http'):
-            self._no_get_vars = False
+            self._use_get_vars = True
         else:
-            self._no_get_vars = True
+            self._use_get_vars = False
 
     def __array__(self):
         # numpy special method that returns a numpy array.
@@ -4237,7 +4237,7 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
         # arguments to the nc_get_var() function, and is much more easy
         # to use.
         start, count, stride, put_ind =\
-        _StartCountStride(elem,self.shape,dimensions=self.dimensions,grp=self._grp,no_get_vars=self._no_get_vars)
+        _StartCountStride(elem,self.shape,dimensions=self.dimensions,grp=self._grp,use_get_vars=self._use_get_vars)
         datashape = _out_array_shape(count)
         if self._isvlen:
             data = numpy.empty(datashape, dtype='O')
@@ -4845,7 +4845,7 @@ The default value of `chartostring` is `True`
 
     def use_nc_get_vars(self,use_nc_get_vars):
         """
-**`use_nc_get_vars(self,_no_get_vars)`**
+**`use_nc_get_vars(self,_use_get_vars)`**
 
 enable the use of netcdf library routine `nc_get_vars`
 to retrieve strided variable slices.  By default,
@@ -4853,7 +4853,7 @@ to retrieve strided variable slices.  By default,
 version of the netcdf-c library being used) since it may be
 slower than multiple calls to the unstrided read routine `nc_get_vara`.
         """
-        self._no_get_vars = not bool(use_nc_get_vars)
+        self._use_get_vars = bool(use_nc_get_vars)
         
     def set_auto_maskandscale(self,maskandscale):
         """
diff --git a/netCDF4/utils.py b/netCDF4/utils.py
index 87ae91a4d..0a1bf0c4d 100644
--- a/netCDF4/utils.py
+++ b/netCDF4/utils.py
@@ -86,7 +86,7 @@ def _quantize(data,least_significant_digit):
         return datout
 
 def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
-        put=False, no_get_vars = True):
+        put=False, use_get_vars = False):
     """Return start, count, stride and indices needed to store/extract data
     into/from a netCDF variable.
 
@@ -257,7 +257,7 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
             newElem.append(e)
         # slice or ellipsis object
         elif type(e) == slice or type(e) == type(Ellipsis):
-            if no_get_vars and type(e) == slice and e.step not in [None,-1,1] and\
+            if not use_get_vars and type(e) == slice and e.step not in [None,-1,1] and\
                dimensions is not None and grp is not None:
                 # convert strided slice to integer sequence if possible
                 # (this will avoid nc_get_vars, which is slow - issue #680).
@@ -308,7 +308,7 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
             if ee and len(e) == len(ee) and (e == np.arange(start,stop,step)).all():
                 # don't convert to slice unless abs(stride) == 1
                 # (nc_get_vars is very slow, issue #680)
-                if no_get_vars and step not in [1,-1]:
+                if not use_get_vars and step not in [1,-1]:
                     newElem.append(e)
                 else:
                     newElem.append(slice(start,stop,step))

From 0da1293e2c99266e77d088fb06118c47cc511c3c Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 8 Feb 2019 07:13:17 -0700
Subject: [PATCH 0219/1504] fix for issue #873

---
 netCDF4/utils.py | 48 ++++++++++++++++++++++++++++++++++--------------
 1 file changed, 34 insertions(+), 14 deletions(-)

diff --git a/netCDF4/utils.py b/netCDF4/utils.py
index 0a1bf0c4d..c87c88154 100644
--- a/netCDF4/utils.py
+++ b/netCDF4/utils.py
@@ -473,9 +473,9 @@ def ncinfo():
     usage = """
  Print summary information about a netCDF file.
 
- usage: %s [-h] [-g grp or --group=grp] [-v var or --variable=var] [-d dim or --dimension=dim] filename
+ usage: %s [-h/--help] [-g grp or --group=grp] [-v var or --variable=var] [-d dim or --dimension=dim] filename
 
- -h -- Print usage message.
+ -h/--help -- Print usage message.
  -g  or --group= -- Print info for this group
       (default is root group). Nested groups specified
       using posix paths ("group1/group2/group3").
@@ -499,7 +499,7 @@ def ncinfo():
     # Get the options
     group = None; var = None; dim=None
     for option in opts:
-        if option[0] == '-h':
+        if option[0] == '-h' or option[0] == '--help':
             sys.stderr.write(usage)
             sys.exit(0)
         elif option[0] == '--group' or option[0] == '-g':
@@ -514,7 +514,11 @@ def ncinfo():
             sys.exit(0)
 
     # filename passed as last argumenbt
-    filename = pargs[-1]
+    try:
+        filename = pargs[-1]
+    except IndexError:
+        sys.stderr.write(usage)
+        sys.exit(0)
 
     f = Dataset(filename)
     if group is None:
@@ -609,8 +613,8 @@ def nc4tonc3():
     usage = """
  Convert a netCDF 4 file (in NETCDF4_CLASSIC format) to netCDF 3 format.
 
- usage: %s [-h] [-o] [--chunk] netcdf4filename netcdf3filename
- -h -- Print usage message.
+ usage: %s [-h/--help] [-o] [--chunk] netcdf4filename netcdf3filename
+ -h/--help -- Print usage message.
  -o -- Overwrite destination file (default is to raise an error if output file already exists).
  --quiet=(0|1)  -- if 1, don't print diagnostic information.
  --format -- netcdf3 format to use (NETCDF3_64BIT by default, can be set to NETCDF3_CLASSIC)
@@ -636,7 +640,7 @@ def nc4tonc3():
 
     # Get the options
     for option in opts:
-        if option[0] == '-h':
+        if option[0] == '-h' or option[0] == '--help':
             sys.stderr.write(usage)
             sys.exit(0)
         elif option[0] == '-o':
@@ -659,8 +663,16 @@ def nc4tonc3():
         sys.exit(0)
 
     # Catch the files passed as the last arguments
-    filename4 = pargs[0]
-    filename3 = pargs[1]
+    try:
+        filename4 = pargs[0]
+    except IndexError:
+        sys.stderr.write(usage)
+        sys.exit(0)
+    try:
+        filename3 = pargs[1]
+    except IndexError:
+        sys.stderr.write(usage)
+        sys.exit(0)
 
     # copy the data from filename4 to filename3.
     _nc4tonc3(filename4,filename3,clobber=overwritefile,quiet=quiet,format=format)
@@ -793,8 +805,8 @@ def nc3tonc4():
  to floats, and adding zlib compression (with the HDF5 shuffle filter and fletcher32 checksum).
  Data may also be quantized (truncated) to a specified precision to improve compression.
 
- usage: %s [-h] [-o] [--vars=var1,var2,..] [--zlib=(0|1)] [--complevel=(1-9)] [--shuffle=(0|1)] [--fletcher32=(0|1)] [--unpackshort=(0|1)] [--quantize=var1=n1,var2=n2,..] netcdf3filename netcdf4filename
- -h -- Print usage message.
+ usage: %s [-h/--help] [-o] [--vars=var1,var2,..] [--zlib=(0|1)] [--complevel=(1-9)] [--shuffle=(0|1)] [--fletcher32=(0|1)] [--unpackshort=(0|1)] [--quantize=var1=n1,var2=n2,..] netcdf3filename netcdf4filename
+ -h/--help -- Print usage message.
  -o -- Overwrite destination file (default is to raise an error if output file already exists).
  --vars -- comma separated list of variable names to copy (default is to copy
     all variables)
@@ -859,7 +871,7 @@ def nc3tonc4():
 
     # Get the options
     for option in opts:
-        if option[0] == '-h':
+        if option[0] == '-h' or option[0] == '--help':
             sys.stderr.write(usage)
             sys.exit(0)
         elif option[0] == '-o':
@@ -900,8 +912,16 @@ def nc3tonc4():
         sys.exit(0)
 
     # Catch the files passed as the last arguments
-    filename3 = pargs[0]
-    filename4 = pargs[1]
+    try:
+        filename3 = pargs[0]
+    except IndexError:
+        sys.stderr.write(usage)
+        sys.exit(0)
+    try:
+        filename4 = pargs[1]
+    except IndexError:
+        sys.stderr.write(usage)
+        sys.exit(0)
 
     # Parse the quantize option, create a dictionary from key/value pairs.
     if quantize is not None:

From ea6e3d589ab6c8086d570d7c05c58757fa1a36a3 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 8 Feb 2019 07:15:20 -0700
Subject: [PATCH 0220/1504] update

---
 Changelog | 1 +
 1 file changed, 1 insertion(+)

diff --git a/Changelog b/Changelog
index 3fa1ec1f8..99a422a10 100644
--- a/Changelog
+++ b/Changelog
@@ -6,6 +6,7 @@
    (issue #865, requires netcdf-c >= 4.6.2)
  * fix performance regression when using large sequences of consecutive
    integers for indexing with netcdf-c >= 4.6.2 (issue #870).
+ * improved error messages for ncinfo and other utilities (issue #873).
 
  version 1.4.2 (tag v1.4.2rel)
 =============================

From e9dbe261cc5e547a5a72c6dca676af5480c9b965 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 8 Feb 2019 07:20:05 -0700
Subject: [PATCH 0221/1504] update

---
 netCDF4/utils.py | 25 +++++--------------------
 1 file changed, 5 insertions(+), 20 deletions(-)

diff --git a/netCDF4/utils.py b/netCDF4/utils.py
index c87c88154..38204bc2b 100644
--- a/netCDF4/utils.py
+++ b/netCDF4/utils.py
@@ -517,6 +517,7 @@ def ncinfo():
     try:
         filename = pargs[-1]
     except IndexError:
+        sys.stdout.write("You need to pass netcdf filename!\n.")
         sys.stderr.write(usage)
         sys.exit(0)
 
@@ -663,16 +664,8 @@ def nc4tonc3():
         sys.exit(0)
 
     # Catch the files passed as the last arguments
-    try:
-        filename4 = pargs[0]
-    except IndexError:
-        sys.stderr.write(usage)
-        sys.exit(0)
-    try:
-        filename3 = pargs[1]
-    except IndexError:
-        sys.stderr.write(usage)
-        sys.exit(0)
+    filename4 = pargs[0]
+    filename3 = pargs[1]
 
     # copy the data from filename4 to filename3.
     _nc4tonc3(filename4,filename3,clobber=overwritefile,quiet=quiet,format=format)
@@ -912,16 +905,8 @@ def nc3tonc4():
         sys.exit(0)
 
     # Catch the files passed as the last arguments
-    try:
-        filename3 = pargs[0]
-    except IndexError:
-        sys.stderr.write(usage)
-        sys.exit(0)
-    try:
-        filename4 = pargs[1]
-    except IndexError:
-        sys.stderr.write(usage)
-        sys.exit(0)
+    filename3 = pargs[0]
+    filename4 = pargs[1]
 
     # Parse the quantize option, create a dictionary from key/value pairs.
     if quantize is not None:

From d66725d4c197f5dd23fb9e6f63e4636da4bc8586 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 22 Feb 2019 13:27:25 -0700
Subject: [PATCH 0222/1504] fix for issue #878 (int64 attributes not created in
 CDF5 files)

---
 netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index e8d343717..657e6d902 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1520,7 +1520,7 @@ be raised in the next release."""
     fmt = _get_format(grp._grpid)
     is_netcdf3 = fmt.startswith('NETCDF3') or fmt == 'NETCDF4_CLASSIC'
     if value_arr.dtype.str[1:] == 'i8' and ('i8' not in _supportedtypes or\
-       is_netcdf3):
+       (is_netcdf3 and fmt != 'NETCDF3_64BIT_DATA')):
         value_arr = value_arr.astype('i4')
     # if array contains ascii strings, write a text attribute (stored as bytes).
     # if array contains unicode strings, and data model is NETCDF4, 

From 7d4037f26e3665c34f6d0b8f5897967fd8c42730 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 22 Feb 2019 13:40:43 -0700
Subject: [PATCH 0223/1504] add test

---
 test/tst_cdf5.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/test/tst_cdf5.py b/test/tst_cdf5.py
index 175f9b538..0710d183a 100644
--- a/test/tst_cdf5.py
+++ b/test/tst_cdf5.py
@@ -18,6 +18,8 @@ def setUp(self):
         # create an 8-bit unsigned integer variable
         v = nc.createVariable('var',np.uint8,'dim')
         v[:ndim] = arrdata
+        # create a 64-bit integer attribute (issue #878)
+        nc.setncattr('int64_attr', np.int64(-9223372036854775806))
         nc.close()
 
     def tearDown(self):
@@ -29,6 +31,7 @@ def runTest(self):
         f  = Dataset(self.netcdf_file, 'r')
         assert f.dimensions['dim'].size == dimsize
         assert_array_equal(arrdata, f.variables['var'][:ndim])
+        assert (type(f.int64_attr) == np.int64)
         f.close()
 
 if __name__ == '__main__':

From fd25902832a9cfb1936608b0d5848e8fb061ba85 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 22 Feb 2019 13:43:28 -0700
Subject: [PATCH 0224/1504] update

---
 Changelog | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/Changelog b/Changelog
index 99a422a10..e481cb967 100644
--- a/Changelog
+++ b/Changelog
@@ -7,6 +7,8 @@
  * fix performance regression when using large sequences of consecutive
    integers for indexing with netcdf-c >= 4.6.2 (issue #870).
  * improved error messages for ncinfo and other utilities (issue #873).
+ * fix for int64 attributes not being created for NETCDF3_64BIT_DATA (CDF5)
+   files (issue #878).
 
  version 1.4.2 (tag v1.4.2rel)
 =============================

From 8351c4728a38a93aefdfc055adc2508d2a391c5a Mon Sep 17 00:00:00 2001
From: Christian Marquardt 
Date: Sat, 23 Feb 2019 23:34:53 +0100
Subject: [PATCH 0225/1504] Support for using NCSTRING type attributes as
 default.

---
 netCDF4/_netCDF4.pyx | 202 ++++++++++++++++++++++---------------------
 1 file changed, 105 insertions(+), 97 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 657e6d902..bfdaacf65 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1,12 +1,12 @@
 """
 Version 1.4.3
 -------------
-- - - 
+- - -
 
 Introduction
 ============
 
-netcdf4-python is a Python interface to the netCDF C library.  
+netcdf4-python is a Python interface to the netCDF C library.
 
 [netCDF](http://www.unidata.ucar.edu/software/netcdf/) version 4 has many features
 not found in earlier versions of the library and is implemented on top of
@@ -28,7 +28,7 @@ types) are not supported.
 Download
 ========
 
- - Latest bleeding-edge code from the 
+ - Latest bleeding-edge code from the
    [github repository](http://github.com/Unidata/netcdf4-python).
  - Latest [releases](https://pypi.python.org/pypi/netCDF4)
    (source code and binary installers).
@@ -41,7 +41,7 @@ Requires
  - [Cython](http://cython.org), version 0.21 or later.
  - [setuptools](https://pypi.python.org/pypi/setuptools), version 18.0 or
    later.
- - [cftime](https://github.com/Unidata/cftime) for 
+ - [cftime](https://github.com/Unidata/cftime) for
  the time and date handling utility functions (`netCDF4.num2date`,
  `netCDF4.date2num` and `netCDF4.date2index`).
  - The HDF5 C library version 1.8.4-patch1 or higher (1.8.x recommended)
@@ -55,7 +55,7 @@ Requires
  - [HDF4](http://www.hdfgroup.org/products/hdf4), if you want
  to be able to read HDF4 "Scientific Dataset" (SD) files.
  - The netCDF-4 C library from the [github releases
-   page](https://github.com/Unidata/netcdf-c/releases). 
+   page](https://github.com/Unidata/netcdf-c/releases).
  Version 4.1.1 or higher is required (4.2 or higher recommended).
  Be sure to build with `--enable-netcdf-4 --enable-shared`, and set
  `CPPFLAGS="-I $HDF5_DIR/include"` and `LDFLAGS="-L $HDF5_DIR/lib"`,
@@ -123,11 +123,11 @@ constructor. This is also the method used to open an existing netCDF
 file.  If the file is open for write access (`mode='w', 'r+'` or `'a'`), you may
 write any type of data including new dimensions, groups, variables and
 attributes.  netCDF files come in five flavors (`NETCDF3_CLASSIC,
-NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF4_CLASSIC`, and `NETCDF4`). 
-`NETCDF3_CLASSIC` was the original netcdf binary format, and was limited 
+NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF4_CLASSIC`, and `NETCDF4`).
+`NETCDF3_CLASSIC` was the original netcdf binary format, and was limited
 to file sizes less than 2 Gb. `NETCDF3_64BIT_OFFSET` was introduced
 in version 3.6.0 of the library, and extended the original binary format
-to allow for file sizes greater than 2 Gb. 
+to allow for file sizes greater than 2 Gb.
 `NETCDF3_64BIT_DATA` is a new format that requires version 4.4.0 of
 the C library - it extends the `NETCDF3_64BIT_OFFSET` binary format to
 allow for unsigned/64 bit integer data types and 64-bit dimension sizes.
@@ -182,9 +182,9 @@ in a netCDF 3 file you will get an error message.
     >>> fcstgrp = rootgrp.createGroup("forecasts")
     >>> analgrp = rootgrp.createGroup("analyses")
     >>> print rootgrp.groups
-    OrderedDict([("forecasts", 
+    OrderedDict([("forecasts",
                   ),
-                 ("analyses", 
+                 ("analyses",
                   )])
 
 Groups can exist within groups in a `netCDF4.Dataset`, just as directories
@@ -201,7 +201,7 @@ use a unix-like path as an argument to `netCDF4.Dataset.createGroup`.
 
 If any of the intermediate elements of the path do not exist, they are created,
 just as with the unix command `'mkdir -p'`. If you try to create a group
-that already exists, no error will be raised, and the existing group will be 
+that already exists, no error will be raised, and the existing group will be
 returned.
 
 Here's an example that shows how to navigate all the groups in a
@@ -366,7 +366,7 @@ You can use a path to create a Variable inside a hierarchy of groups.
 
 If the intermediate groups do not yet exist, they will be created.
 
-You can also query a `netCDF4.Dataset` or `netCDF4.Group` instance directly to obtain `netCDF4.Group` or 
+You can also query a `netCDF4.Dataset` or `netCDF4.Group` instance directly to obtain `netCDF4.Group` or
 `netCDF4.Variable` instances using paths.
 
     :::python
@@ -560,7 +560,7 @@ measure relative to a fixed date using a certain calendar, with units
 specified like `hours since YY-MM-DD hh:mm:ss`.  These units can be
 awkward to deal with, without a utility to convert the values to and
 from calendar dates.  The function called `netCDF4.num2date` and `netCDF4.date2num` are
-provided with this package to do just that (starting with version 1.4.0, the 
+provided with this package to do just that (starting with version 1.4.0, the
 [cftime](https://unidata.github.io/cftime) package must be installed
 separately).  Here's an example of how they
 can be used:
@@ -729,7 +729,7 @@ Compound types can be nested, but you must create the 'inner'
 ones first. All possible numpy structured arrays cannot be
 represented as Compound variables - an error message will be
 raise if you try to create one that is not supported.
-All of the compound types defined for a `netCDF4.Dataset` or `netCDF4.Group` are stored 
+All of the compound types defined for a `netCDF4.Dataset` or `netCDF4.Group` are stored
 in a Python dictionary, just like variables and dimensions. As always, printing
 objects gives useful summary information in an interactive session:
 
@@ -857,7 +857,7 @@ netCDF4 has an enumerated data type, which is an integer datatype that is
 restricted to certain named values. Since Enums don't map directly to
 a numpy data type, they are read and written as integer arrays.
 
-Here's an example of using an Enum type to hold cloud type data. 
+Here's an example of using an Enum type to hold cloud type data.
 The base integer data type and a python dictionary describing the allowed
 values and their names are used to define an Enum data type using
 `netCDF4.Dataset.createEnumType`.
@@ -865,7 +865,7 @@ values and their names are used to define an Enum data type using
     :::python
     >>> nc = Dataset('clouds.nc','w')
     >>> # python dict with allowed values and their names.
-    >>> enum_dict = {u'Altocumulus': 7, u'Missing': 255, 
+    >>> enum_dict = {u'Altocumulus': 7, u'Missing': 255,
     >>> u'Stratus': 2, u'Clear': 0,
     >>> u'Nimbostratus': 6, u'Cumulus': 4, u'Altostratus': 5,
     >>> u'Cumulonimbus': 1, u'Stratocumulus': 3}
@@ -921,7 +921,7 @@ specified names.
 If MPI parallel enabled versions of netcdf and hdf5 are detected, and
 [mpi4py](https://mpi4py.scipy.org) is installed, netcdf4-python will
 be built with parallel IO capabilities enabled.  To use parallel IO,
-your program must be running in an MPI environment using 
+your program must be running in an MPI environment using
 [mpi4py](https://mpi4py.scipy.org).
 
     :::python
@@ -976,11 +976,11 @@ are collective.  There are a couple of important limitatons of parallel IO:
    a generic "HDF Error".
  - You cannot write compressed data in parallel (although
    you can read it).
- - You cannot use variable-length (VLEN) data types. 
+ - You cannot use variable-length (VLEN) data types.
 
 ## 
      14) Dealing with strings.
 
-The most flexible way to store arrays of strings is with the 
+The most flexible way to store arrays of strings is with the
 [Variable-length (vlen) string data type](#section11). However, this requires
 the use of the NETCDF4 data model, and the vlen type does not map very well
 numpy arrays (you have to use numpy arrays of dtype=`object`, which are arrays of
@@ -1019,7 +1019,7 @@ characters with one more dimension. For example,
 
 Even if the `_Encoding` attribute is set, the automatic conversion of char
 arrays to/from string arrays can be disabled with
-`netCDF4.Variable.set_auto_chartostring`. 
+`netCDF4.Variable.set_auto_chartostring`.
 
 A similar situation is often encountered with numpy structured arrays with subdtypes
 containing fixed-wdith byte strings (dtype=`S#`). Since there is no native fixed-length string
@@ -1058,7 +1058,7 @@ Here's an example:
     >>> nc.close()
 
 Note that there is currently no support for mapping numpy structured arrays with
-unicode elements (dtype `U#`) onto netCDF compound types, nor is there support 
+unicode elements (dtype `U#`) onto netCDF compound types, nor is there support
 for netCDF compound types with vlen string components.
 
 ## 
      15) In-memory (diskless) Datasets.
@@ -1079,7 +1079,7 @@ object representing the Dataset. Below are examples illustrating both
 approaches.
 
     :::python
-    >>> # create a diskless (in-memory) Dataset, 
+    >>> # create a diskless (in-memory) Dataset,
     >>> # and persist the file to disk when it is closed.
     >>> nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
     >>> d = nc.createDimension('x',None)
@@ -1113,7 +1113,7 @@ approaches.
     >>> nc.close()
     >>> # create an in-memory Dataset and retrieve memory buffer
     >>> # estimated size is 1028 bytes - this is actually only
-    >>> # used if format is NETCDF3 
+    >>> # used if format is NETCDF3
     >>> # (ignored for NETCDF4/HDF5 files).
     >>> nc = Dataset('inmemory.nc', mode='w',memory=1028)
     >>> d = nc.createDimension('x',None)
@@ -1322,7 +1322,7 @@ else:  # prior to 4.6.2 this flag doesn't work, so make the same as NC_DISKLESS
     NC_PERSIST = NC_DISKLESS
 
 # next two lines do nothing, preserved for backwards compatibility.
-default_encoding = 'utf-8' 
+default_encoding = 'utf-8'
 unicode_error = 'replace'
 
 python3 = sys.version_info[0] > 2
@@ -1523,7 +1523,7 @@ be raised in the next release."""
        (is_netcdf3 and fmt != 'NETCDF3_64BIT_DATA')):
         value_arr = value_arr.astype('i4')
     # if array contains ascii strings, write a text attribute (stored as bytes).
-    # if array contains unicode strings, and data model is NETCDF4, 
+    # if array contains unicode strings, and data model is NETCDF4,
     # write as a string.
     if value_arr.dtype.char in ['S','U']:
         # force array of strings if array has multiple elements (issue #770)
@@ -1846,7 +1846,7 @@ _private_atts = \
  '_nunlimdim','path','parent','ndim','mask','scale','cmptypes','vltypes','enumtypes','_isprimitive',
  'file_format','_isvlen','_isenum','_iscompound','_cmptype','_vltype','_enumtype','name',
  '__orthogoral_indexing__','keepweakref','_has_lsd',
- '_buffer','chartostring','_use_get_vars']
+ '_buffer','chartostring','_use_get_vars','ncstring_attrs']
 __pdoc__ = {}
 
 cdef class Dataset:
@@ -1872,7 +1872,7 @@ dimensions defined for the `netCDF4.Group` or `netCDF4.Dataset` to instances of
 `netCDF4.Dimension` class.
 
 **`variables`**: The `variables` dictionary maps the names of variables
-defined for this `netCDF4.Dataset` or `netCDF4.Group` to instances of the 
+defined for this `netCDF4.Dataset` or `netCDF4.Group` to instances of the
 `netCDF4.Variable` class.
 
 **`groups`**: The groups dictionary maps the names of groups created for
@@ -1885,11 +1885,11 @@ compound types defined for the `netCDF4.Group` or `netCDF4.Dataset` to instances
 `netCDF4.CompoundType` class.
 
 **`vltypes`**: The `vltypes` dictionary maps the names of
-variable-length types defined for the `netCDF4.Group` or `netCDF4.Dataset` to instances 
+variable-length types defined for the `netCDF4.Group` or `netCDF4.Dataset` to instances
 of the `netCDF4.VLType` class.
 
 **`enumtypes`**: The `enumtypes` dictionary maps the names of
-Enum types defined for the `netCDF4.Group` or `netCDF4.Dataset` to instances 
+Enum types defined for the `netCDF4.Group` or `netCDF4.Dataset` to instances
 of the `netCDF4.EnumType` class.
 
 **`data_model`**: `data_model` describes the netCDF
@@ -1913,7 +1913,7 @@ the `netCDF4.Dataset` in a unix directory format (the names of groups in the
 hierarchy separated by backslashes). A `netCDF4.Dataset` instance is the root
 group, so the path is simply `'/'`.
 
-**`keepweakref`**: If `True`, child Dimension and Variables objects only keep weak 
+**`keepweakref`**: If `True`, child Dimension and Variables objects only keep weak
 references to the parent Dataset or Group.
     """
     cdef object __weakref__, _inmemory
@@ -1922,7 +1922,7 @@ references to the parent Dataset or Group.
     cdef Py_buffer _buffer
     cdef public groups, dimensions, variables, disk_format, path, parent,\
     file_format, data_model, cmptypes, vltypes, enumtypes,  __orthogonal_indexing__, \
-    keepweakref
+    keepweakref, ncstring_attrs
     # Docstrings for class variables (used by pdoc).
     __pdoc__['Dataset.dimensions']=\
     """The `dimensions` dictionary maps the names of
@@ -1971,11 +1971,13 @@ references to the parent Dataset or Group.
     group, so the path is simply `'/'`."""
     __pdoc__['Dataset.keepweakref']=\
     """If `True`, child Dimension and Variables objects only keep weak references to
-    the parent Dataset or Group.""" 
+    the parent Dataset or Group."""
+    __pdoc__['Dataset.ncstring_attrs']=\
+    """If `True`, string attributes will be NCSTRINGs instead of character arrays."""
 
     def __init__(self, filename, mode='r', clobber=True, format='NETCDF4',
                      diskless=False, persist=False, keepweakref=False,
-                     memory=None, encoding=None, parallel=False,
+                     memory=None, encoding=None, parallel=False, ncstring_attrs=False,
                      Comm comm=None, Info info=None, **kwargs):
         """
         **`__init__(self, filename, mode="r", clobber=True, diskless=False,
@@ -1987,7 +1989,7 @@ references to the parent Dataset or Group.
         **`filename`**: Name of netCDF file to hold dataset. Can also
 	be a python 3 pathlib instance or the URL of an OpenDAP dataset.  When memory is
 	set this is just used to set the `filepath()`.
-        
+
         **`mode`**: access mode. `r` means read-only; no data can be
         modified. `w` means write; a new file is created, an existing file with
         the same name is deleted. `a` and `r+` mean append (in analogy with
@@ -1999,11 +2001,11 @@ references to the parent Dataset or Group.
         access, since it may be faster for programs that don't access data
         sequentially. This option is ignored for `NETCDF4` and `NETCDF4_CLASSIC`
         formatted files.
-        
+
         **`clobber`**: if `True` (default), opening a file with `mode='w'`
         will clobber an existing file with the same name.  if `False`, an
         exception will be raised if a file with the same name already exists.
-        
+
         **`format`**: underlying file format (one of `'NETCDF4',
         'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC'`, `'NETCDF3_64BIT_OFFSET'` or
         `'NETCDF3_64BIT_DATA'`.
@@ -2021,12 +2023,12 @@ references to the parent Dataset or Group.
         file format, which supports 64-bit dimension sizes plus unsigned and
         64 bit integer data types, but is only compatible with clients linked against
         netCDF version 4.4.0 or later.
-        
-        **`diskless`**: If `True`, create diskless (in-core) file.  
+
+        **`diskless`**: If `True`, create diskless (in-core) file.
         This is a feature added to the C library after the
         netcdf-4.2 release. If you need to access the memory buffer directly,
         use the in-memory feature instead (see `memory` kwarg).
-        
+
         **`persist`**: if `diskless=True`, persist file to disk when closed
         (default `False`).
 
@@ -2043,7 +2045,10 @@ references to the parent Dataset or Group.
         reducing memory usage and open file handles.  However, in many cases this is not
         desirable, since the associated Variable instances may still be needed, but are
         rendered unusable when the parent Dataset instance is garbage collected.
-        
+
+        **`ncstring_attrs`**: if `ncstring_attrs=True`, all string attributes will use
+        the variable length NCSTRING attributes (default `False`).
+
         **`memory`**: if not `None`, create or open an in-memory Dataset.
         If mode = 'r', the memory kwarg must contain a memory buffer object
         (an object that supports the python buffer interface).
@@ -2264,6 +2269,7 @@ references to the parent Dataset or Group.
         self.path = '/'
         self.parent = None
         self.keepweakref = keepweakref
+        self.ncstring_attrs = ncstring_attrs
         # get compound, vlen and enum types in the root Group.
         self.cmptypes, self.vltypes, self.enumtypes = _get_types(self)
         # get dimensions in the root group.
@@ -2570,7 +2576,7 @@ Creates a new variable with the given `varname`, `datatype`, and
 a scalar.
 
 If `varname` is specified as a path, using forward slashes as in unix to
-separate components, then intermediate groups will be created as necessary 
+separate components, then intermediate groups will be created as necessary
 For example, `createVariable('/GroupA/GroupB/VarC', float, ('x','y'))` will create groups `GroupA`
 and `GroupA/GroupB`, plus the variable `GroupA/GroupB/VarC`, if the preceding
 groups don't already exist.
@@ -2642,7 +2648,7 @@ with `zlib=True` this produces 'lossy', but significantly more
 efficient compression. For example, if `least_significant_digit=1`,
 data will be quantized using `numpy.around(scale*data)/scale`, where
 scale = 2**bits, and bits is determined so that a precision of 0.1 is
-retained (in this case bits=4). From the 
+retained (in this case bits=4). From the
 [PSD metadata conventions](http://www.esrl.noaa.gov/psd/data/gridded/conventions/cdc_netcdf_standard.shtml):
 "least_significant_digit -- power of ten of the smallest decimal place
 in unpacked data that is a reliable value." Default is `None`, or no
@@ -2727,7 +2733,7 @@ rename a `netCDF4.Variable` named `oldname` to `newname`"""
 Creates a new `netCDF4.Group` with the given `groupname`.
 
 If `groupname` is specified as a path, using forward slashes as in unix to
-separate components, then intermediate groups will be created as necessary 
+separate components, then intermediate groups will be created as necessary
 (analogous to `mkdir -p` in unix).  For example,
 `createGroup('/GroupA/GroupB/GroupC')` will create `GroupA`,
 `GroupA/GroupB`, and `GroupA/GroupB/GroupC`, if they don't already exist.
@@ -2764,8 +2770,10 @@ return netCDF global attribute names for this `netCDF4.Dataset` or `netCDF4.Grou
 set a netCDF dataset or group attribute using name,value pair.
 Use if you need to set a netCDF attribute with the
 with the same name as one of the reserved python attributes."""
+        cdef nc_type xtype
+        xtype=-99
         if self.data_model != 'NETCDF4': self._redef()
-        _set_att(self, NC_GLOBAL, name, value)
+        _set_att(self, NC_GLOBAL, name, value, xtype=xtype, force_ncstring=self.ncstring_attrs)
         if self.data_model !=  'NETCDF4': self._enddef()
 
     def setncattr_string(self,name,value):
@@ -2906,7 +2914,7 @@ Call `netCDF4.Variable.set_auto_chartostring` for all variables contained in thi
 `netCDF4.Group`, as well as for all variables in all its subgroups.
 
 **`True_or_False`**: Boolean determining if automatic conversion of
-all character arrays <--> string arrays should be performed for 
+all character arrays <--> string arrays should be performed for
 character variables (variables of type `NC_CHAR` or `S1`) with the
 `_Encoding` attribute set.
 
@@ -3041,7 +3049,7 @@ the default behaviour.
 Returns a list of variables that match specific conditions.
 
 Can pass in key=value parameters and variables are returned that
-contain all of the matches. For example, 
+contain all of the matches. For example,
 
     :::python
     >>> # Get variables with x-axis attribute.
@@ -3096,7 +3104,7 @@ a `netCDF4.Dataset` within a Dataset, and can contain it's own variables,
 dimensions and attributes (and other Groups). See `netCDF4.Group.__init__`
 for more details.
 
-`netCDF4.Group` inherits from `netCDF4.Dataset`, so all the 
+`netCDF4.Group` inherits from `netCDF4.Dataset`, so all the
 `netCDF4.Dataset` class methods and variables are available
 to a `netCDF4.Group` instance (except the `close` method).
 
@@ -3362,21 +3370,21 @@ variable's data type.
 
 **`scale`**: If True, `scale_factor` and `add_offset` are
 applied, and signed integer data is automatically converted to
-unsigned integer data if the `_Unsigned` attribute is set. 
+unsigned integer data if the `_Unsigned` attribute is set.
 Default is `True`, can be reset using `netCDF4.Variable.set_auto_scale` and
 `netCDF4.Variable.set_auto_maskandscale` methods.
 
-**`mask`**: If True, data is automatically converted to/from masked 
+**`mask`**: If True, data is automatically converted to/from masked
 arrays when missing values or fill values are present. Default is `True`, can be
 reset using `netCDF4.Variable.set_auto_mask` and `netCDF4.Variable.set_auto_maskandscale`
 methods.
 
-**`chartostring`**: If True, data is automatically converted to/from character 
-arrays to string arrays when the `_Encoding` variable attribute is set. 
+**`chartostring`**: If True, data is automatically converted to/from character
+arrays to string arrays when the `_Encoding` variable attribute is set.
 Default is `True`, can be reset using
 `netCDF4.Variable.set_auto_chartostring` method.
 
-**`least_significant_digit`**: Describes the power of ten of the 
+**`least_significant_digit`**: Describes the power of ten of the
 smallest decimal place in the data the contains a reliable value.  Data is
 truncated to this decimal place when it is assigned to the `netCDF4.Variable`
 instance. If `None`, the data is not truncated.
@@ -3480,28 +3488,28 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         (for a variable-length array), or the python `str` builtin
         (for a variable-length string array). Numpy string and unicode datatypes with
         length greater than one are aliases for `str`.
-        
+
         **`dimensions`**: a tuple containing the variable's dimension names
         (defined previously with `createDimension`). Default is an empty tuple
         which means the variable is a scalar (and therefore has no dimensions).
-        
+
         **`zlib`**: if `True`, data assigned to the `netCDF4.Variable`
         instance is compressed on disk. Default `False`.
-        
+
         **`complevel`**: the level of zlib compression to use (1 is the fastest,
         but poorest compression, 9 is the slowest but best compression). Default 4.
         Ignored if `zlib=False`.
-        
+
         **`shuffle`**: if `True`, the HDF5 shuffle filter is applied
         to improve compression. Default `True`. Ignored if `zlib=False`.
-        
+
         **`fletcher32`**: if `True` (default `False`), the Fletcher32 checksum
         algorithm is used for error detection.
-        
+
         **`contiguous`**: if `True` (default `False`), the variable data is
         stored contiguously on disk.  Default `False`. Setting to `True` for
         a variable with an unlimited dimension will trigger an error.
-        
+
         **`chunksizes`**: Can be used to specify the HDF5 chunksizes for each
         dimension of the variable. A detailed discussion of HDF chunking and I/O
         performance is available
@@ -3509,7 +3517,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         Basically, you want the chunk size for each dimension to match as
         closely as possible the size of the data block that users will read
         from the file. `chunksizes` cannot be set if `contiguous=True`.
-        
+
         **`endian`**: Can be used to control whether the
         data is stored in little or big endian format on disk. Possible
         values are `little, big` or `native` (default). The library
@@ -3518,10 +3526,10 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         opposite format as the one used to create the file, there may be
         some performance advantage to be gained by setting the endian-ness.
         For netCDF 3 files (that don't use HDF5), only `endian='native'` is allowed.
-        
+
         The `zlib, complevel, shuffle, fletcher32, contiguous` and `chunksizes`
         keywords are silently ignored for netCDF 3 files that do not use HDF5.
-        
+
         **`least_significant_digit`**: If specified, variable data will be
         truncated (quantized). In conjunction with `zlib=True` this produces
         'lossy', but significantly more efficient compression. For example, if
@@ -3529,7 +3537,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         around(scale*data)/scale, where scale = 2**bits, and bits is determined
         so that a precision of 0.1 is retained (in this case bits=4). Default is
         `None`, or no quantization.
-        
+
         **`fill_value`**:  If specified, the default netCDF `_FillValue` (the
         value that the variable gets filled with before any data is written to it)
         is replaced with this value.  If fill_value is set to `False`, then
@@ -4320,7 +4328,7 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
             elif hasattr(self, 'add_offset') and self.add_offset != 0.0:
                 data = data + self.add_offset
 
-        # if _Encoding is specified for a character variable, return 
+        # if _Encoding is specified for a character variable, return
         # a numpy array of strings with one less dimension.
         if self.chartostring and getattr(self.dtype,'kind',None) == 'S' and\
            getattr(self.dtype,'itemsize',None) == 1:
@@ -4334,7 +4342,7 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
                     # also make sure slice is along last dimension
                     matchdim = True
                     for cnt in count:
-                        if cnt[-1] != self.shape[-1]: 
+                        if cnt[-1] != self.shape[-1]:
                             matchdim = False
                             break
                     if matchdim:
@@ -4368,7 +4376,7 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
             mval = numpy.array(self.missing_value, self.dtype)
             if self.scale and is_unsigned_int:
                 mval = mval.view(dtype_unsigned_int)
-            # create mask from missing values. 
+            # create mask from missing values.
             mvalmask = numpy.zeros(data.shape, numpy.bool)
             if mval.shape == (): # mval a scalar.
                 mval = [mval] # make into iterable.
@@ -4378,12 +4386,12 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
                     mvalisnan = numpy.isnan(m)
                 except TypeError: # isnan fails on some dtypes (issue 206)
                     mvalisnan = False
-                if mvalisnan: 
+                if mvalisnan:
                     mvalmask += numpy.isnan(data)
                 else:
                     mvalmask += data==m
             if mvalmask.any():
-                # set fill_value for masked array 
+                # set fill_value for masked array
                 # to missing_value (or 1st element
                 # if missing_value is a vector).
                 fill_value = mval[0]
@@ -4461,11 +4469,11 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
         if validmax is not None and self.scale and is_unsigned_int:
             validmax = validmax.view(dtype_unsigned_int)
         # http://www.unidata.ucar.edu/software/netcdf/docs/attribute_conventions.html).
-        # "If the data type is byte and _FillValue 
+        # "If the data type is byte and _FillValue
         # is not explicitly defined,
         # then the valid range should include all possible values.
         # Otherwise, the valid range should exclude the _FillValue
-        # (whether defined explicitly or by default) as follows. 
+        # (whether defined explicitly or by default) as follows.
         # If the _FillValue is positive then it defines a valid maximum,
         #  otherwise it defines a valid minimum."
         byte_type = self.dtype.str[1:] in ['u1','i1']
@@ -4511,7 +4519,7 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
             # issue #809: return a regular numpy array if requested
             # and there are no missing values
             data = numpy.array(data, copy=False)
-            
+
         return data
 
     def _assign_vlen(self, elem, data):
@@ -4773,7 +4781,7 @@ cannot be safely cast to variable data type""" % attname
                     else:
                         fillval = default_fillvals[self.dtype.str[1:]]
                     # some versions of numpy have trouble handling
-                    # MaskedConstants when filling - this is is 
+                    # MaskedConstants when filling - this is is
                     # a workaround (issue #850)
                     if data.shape == (1,) and data.mask.all():
                         data = numpy.array([fillval],self.dtype)
@@ -4832,7 +4840,7 @@ If `chartostring` is set to `True`, when data is read from a character variable
 (dtype = `S1`) that has an `_Encoding` attribute, it is converted to a numpy
 fixed length unicode string array (dtype = `UN`, where `N` is the length
 of the the rightmost dimension of the variable).  The value of `_Encoding`
-is the unicode encoding that is used to decode the bytes into strings. 
+is the unicode encoding that is used to decode the bytes into strings.
 
 When numpy string data is written to a variable it is converted back to
 indiviual bytes, with the number of bytes in each string equalling the
@@ -4854,14 +4862,14 @@ version of the netcdf-c library being used) since it may be
 slower than multiple calls to the unstrided read routine `nc_get_vara`.
         """
         self._use_get_vars = bool(use_nc_get_vars)
-        
+
     def set_auto_maskandscale(self,maskandscale):
         """
 **`set_auto_maskandscale(self,maskandscale)`**
 
 turn on or off automatic conversion of variable data to and
 from masked arrays, automatic packing/unpacking of variable
-data using `scale_factor` and `add_offset` attributes and 
+data using `scale_factor` and `add_offset` attributes and
 automatic conversion of signed integer data to unsigned integer
 data if the `_Unsigned` attribute exists.
 
@@ -4875,7 +4883,7 @@ for each data type).  When data is written to a variable, the masked
 array is converted back to a regular numpy array by replacing all the
 masked values by the missing_value attribute of the variable (if it
 exists).  If the variable has no missing_value attribute, the _FillValue
-is used instead. If the variable has valid_min/valid_max and 
+is used instead. If the variable has valid_min/valid_max and
 missing_value attributes, data outside the specified range will be
 set to missing_value.
 
@@ -4896,11 +4904,11 @@ For more information on how `scale_factor` and `add_offset` can be
 used to provide simple compression, see the
 [PSD metadata conventions](http://www.esrl.noaa.gov/psd/data/gridded/conventions/cdc_netcdf_standard.shtml).
 
-In addition, if `maskandscale` is set to `True`, and if the variable has an 
-attribute `_Unsigned` set, and the variable has a signed integer data type, 
+In addition, if `maskandscale` is set to `True`, and if the variable has an
+attribute `_Unsigned` set, and the variable has a signed integer data type,
 a view to the data is returned with the corresponding unsigned integer data type.
 This convention is used by the netcdf-java library to save unsigned integer
-data in `NETCDF3` or `NETCDF4_CLASSIC` files (since the `NETCDF3` 
+data in `NETCDF3` or `NETCDF4_CLASSIC` files (since the `NETCDF3`
 data model does not have unsigned integer data types).
 
 The default value of `maskandscale` is `True`
@@ -4935,18 +4943,18 @@ For more information on how `scale_factor` and `add_offset` can be
 used to provide simple compression, see the
 [PSD metadata conventions](http://www.esrl.noaa.gov/psd/data/gridded/conventions/cdc_netcdf_standard.shtml).
 
-In addition, if `scale` is set to `True`, and if the variable has an 
+In addition, if `scale` is set to `True`, and if the variable has an
 attribute `_Unsigned` set, and the variable has a signed integer data type,
 a view to the data is returned with the corresponding unsigned integer datatype.
 This convention is used by the netcdf-java library to save unsigned integer
-data in `NETCDF3` or `NETCDF4_CLASSIC` files (since the `NETCDF3` 
+data in `NETCDF3` or `NETCDF4_CLASSIC` files (since the `NETCDF3`
 data model does not have unsigned integer data types).
 
 The default value of `scale` is `True`
 (automatic conversions are performed).
         """
         self.scale = bool(scale)
-        
+
     def set_auto_mask(self,mask):
         """
 **`set_auto_mask(self,mask)`**
@@ -4964,7 +4972,7 @@ for each data type).  When data is written to a variable, the masked
 array is converted back to a regular numpy array by replacing all the
 masked values by the missing_value attribute of the variable (if it
 exists).  If the variable has no missing_value attribute, the _FillValue
-is used instead. If the variable has valid_min/valid_max and 
+is used instead. If the variable has valid_min/valid_max and
 missing_value attributes, data outside the specified range will be
 set to missing_value.
 
@@ -4972,7 +4980,7 @@ The default value of `mask` is `True`
 (automatic conversions are performed).
         """
         self.mask = bool(mask)
-        
+
     def set_always_mask(self,always_mask):
         """
 **`set_always_mask(self,always_mask)`**
@@ -5044,7 +5052,7 @@ numpy arrays are not performed).
             if self.dtype != data.dtype:
                 data = data.astype(self.dtype) # cast data, if necessary.
             # byte-swap data in numpy array so that is has native
-            # endian byte order (this is what netcdf-c expects - 
+            # endian byte order (this is what netcdf-c expects -
             # issue #554, pull request #555)
             if not data.dtype.isnative:
                 data = data.byteswap()
@@ -5257,7 +5265,7 @@ numpy arrays are not performed).
             # reverse data along axes with negative strides.
             data = data[tuple(sl)].copy() # make a copy so data is contiguous.
         # netcdf-c always returns data in native byte order,
-        # regardless of variable endian-ness. Here we swap the 
+        # regardless of variable endian-ness. Here we swap the
         # bytes if the variable dtype is not native endian, so the
         # dtype of the returned numpy array matches the variable dtype.
         # (pull request #555, issue #554).
@@ -5293,7 +5301,7 @@ open for parallel access.
         """
 **`get_dims(self)`**
 
-return a tuple of `netCDF4.Dimension` instances associated with this 
+return a tuple of `netCDF4.Dimension` instances associated with this
 `netCDF4.Variable.
         """
         return tuple(_find_dim(self._grp, dim) for dim in self.dimensions)
@@ -5308,7 +5316,7 @@ cdef class CompoundType:
     """
 A `netCDF4.CompoundType` instance is used to describe a compound data
 type, and can be passed to the the `netCDF4.Dataset.createVariable` method of
-a `netCDF4.Dataset` or `netCDF4.Group` instance. 
+a `netCDF4.Dataset` or `netCDF4.Group` instance.
 Compound data types map to numpy structured arrays.
 See `netCDF4.CompoundType.__init__` for more details.
 
@@ -5356,7 +5364,7 @@ the user.
         # (this may or may not be still true, but empirical
         # evidence suggests that segfaults occur if this
         # alignment step is skipped - see issue #705).
-        # numpy string subdtypes (i.e. 'S80') are 
+        # numpy string subdtypes (i.e. 'S80') are
         # automatically converted to character array
         # subtypes (i.e. ('S1',80)).  If '_Encoding'
         # variable attribute is set, data will be converted
@@ -5620,7 +5628,7 @@ cdef class VLType:
     """
 A `netCDF4.VLType` instance is used to describe a variable length (VLEN) data
 type, and can be passed to the the `netCDF4.Dataset.createVariable` method of
-a `netCDF4.Dataset` or `netCDF4.Group` instance. See 
+a `netCDF4.Dataset` or `netCDF4.Group` instance. See
 `netCDF4.VLType.__init__` for more details.
 
 The instance variables `dtype` and `name` should not be modified by
@@ -5736,7 +5744,7 @@ cdef class EnumType:
     """
 A `netCDF4.EnumType` instance is used to describe an Enum data
 type, and can be passed to the the `netCDF4.Dataset.createVariable` method of
-a `netCDF4.Dataset` or `netCDF4.Group` instance. See 
+a `netCDF4.Dataset` or `netCDF4.Group` instance. See
 `netCDF4.EnumType.__init__` for more details.
 
 The instance variables `dtype`, `name` and `enum_dict` should not be modified by
@@ -5997,7 +6005,7 @@ Example usage (See `netCDF4.MFDataset.__init__` for more details):
         `aggdim` is not specified, the unlimited is aggregated.  Currently,
         `aggdim` must be the leftmost (slowest varying) dimension of each
         of the variables to be aggregated.
-        
+
         **`files`**: either a sequence of netCDF files or a string with a
         wildcard (converted to a sorted list of files using glob)  If
         the `master_file` kwarg is not specified, the first file
@@ -6005,16 +6013,16 @@ Example usage (See `netCDF4.MFDataset.__init__` for more details):
         variables with an aggregation dimension which may span
         subsequent files. Attribute access returns attributes only from "master"
         file. The files are always opened in read-only mode.
-        
+
         **`check`**: True if you want to do consistency checking to ensure the
         correct variables structure for all of the netcdf files.  Checking makes
         the initialization of the MFDataset instance much slower. Default is
         False.
-        
+
         **`aggdim`**: The name of the dimension to aggregate over (must
         be the leftmost dimension of each of the variables to be aggregated).
         If None (default), aggregate over the unlimited dimension.
-        
+
         **`exclude`**: A list of variable names to exclude from aggregation.
         Default is an empty list.
 
@@ -6459,9 +6467,9 @@ Example usage (See `netCDF4.MFTime.__init__` for more details):
 
         Create a time Variable with units consistent across a multifile
         dataset.
-        
+
         **`time`**: Time variable from a `netCDF4.MFDataset`.
-        
+
         **`units`**: Time units, for example, `'days since 1979-01-01'`. If `None`,
         use the units from the master variable.
 

From 80ff0486379428774e3d8ec7a9292b109e086381 Mon Sep 17 00:00:00 2001
From: Christian Marquardt 
Date: Sun, 24 Feb 2019 20:35:17 +0100
Subject: [PATCH 0226/1504] Support for using NCSTRING attributes as default in
 groups and variables.

---
 netCDF4/_netCDF4.pyx | 10 ++++++++--
 1 file changed, 8 insertions(+), 2 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index bfdaacf65..2edd5f8c1 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -3141,6 +3141,8 @@ Additional read-only class variables:
         self.parent = parent
         # propagate weak reference setting from parent.
         self.keepweakref = parent.keepweakref
+        # propagate ncstring_attrs setting from parent.
+        self.ncstring_attrs = parent.ncstring_attrs
         if 'id' in kwargs:
             self._grpid = kwargs['id']
             # get compound, vlen and enum types in this Group.
@@ -3404,7 +3406,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
     cdef public int _varid, _grpid, _nunlimdim
     cdef public _name, ndim, dtype, mask, scale, always_mask, chartostring,  _isprimitive, \
     _iscompound, _isvlen, _isenum, _grp, _cmptype, _vltype, _enumtype,\
-    __orthogonal_indexing__, _has_lsd, _use_get_vars
+    __orthogonal_indexing__, _has_lsd, _use_get_vars, ncstring_attrs
     # Docstrings for class variables (used by pdoc).
     __pdoc__['Variable.dimensions'] = \
     """A tuple containing the names of the
@@ -3808,6 +3810,8 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         # default is to automatically convert to/from character
         # to string arrays when _Encoding variable attribute is set.
         self.chartostring = True
+        # propagate ncstring_attrs setting from parent group.
+        self.ncstring_attrs = grp.ncstring_attrs
         if 'least_significant_digit' in self.ncattrs():
             self._has_lsd = True
         # avoid calling nc_get_vars for strided slices by default.
@@ -3990,8 +3994,10 @@ return netCDF attribute names for this `netCDF4.Variable` in a list."""
 set a netCDF variable attribute using name,value pair.  Use if you need to set a
 netCDF attribute with the same name as one of the reserved python
 attributes."""
+        cdef nc_type xtype
+        xtype=-99
         if self._grp.data_model != 'NETCDF4': self._grp._redef()
-        _set_att(self._grp, self._varid, name, value)
+        _set_att(self._grp, self._varid, name, value, xtype=xtype, force_ncstring=self.ncstring_attrs)
         if self._grp.data_model != 'NETCDF4': self._grp._enddef()
 
     def setncattr_string(self,name,value):

From d958203f5110a8a460180f0e3f96fd78b7071d87 Mon Sep 17 00:00:00 2001
From: Christian Marquardt 
Date: Sun, 24 Feb 2019 20:36:20 +0100
Subject: [PATCH 0227/1504] Added a test for using NCSTRING attributes as
 default.

---
 test/tst_atts_ncstr.py | 209 +++++++++++++++++++++++++++++++++++++++++
 1 file changed, 209 insertions(+)
 create mode 100644 test/tst_atts_ncstr.py

diff --git a/test/tst_atts_ncstr.py b/test/tst_atts_ncstr.py
new file mode 100644
index 000000000..12d772fed
--- /dev/null
+++ b/test/tst_atts_ncstr.py
@@ -0,0 +1,209 @@
+import math
+import subprocess
+import sys
+import unittest
+import os
+import tempfile
+import warnings
+
+import numpy as NP
+from numpy.random.mtrand import uniform
+import netCDF4
+
+try:
+    from collections import OrderedDict
+except ImportError: # or else use drop-in substitute
+    from ordereddict import OrderedDict
+
+# test attribute creation.
+FILE_NAME = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
+VAR_NAME="dummy_var"
+GROUP_NAME = "dummy_group"
+DIM1_NAME="x"
+DIM1_LEN=2
+DIM2_NAME="y"
+DIM2_LEN=3
+DIM3_NAME="z"
+DIM3_LEN=25
+STRATT = 'string attribute'
+EMPTYSTRATT = ''
+INTATT = 1
+FLOATATT = math.pi
+SEQATT = NP.arange(10)
+STRINGSEQATT = ['mary ','','had ','a ','little ','lamb',]
+#ATTDICT = {'stratt':STRATT,'floatatt':FLOATATT,'seqatt':SEQATT,
+#           'stringseqatt':''.join(STRINGSEQATT), # changed in issue #770
+#           'emptystratt':EMPTYSTRATT,'intatt':INTATT}
+ATTDICT = {'stratt':STRATT,'floatatt':FLOATATT,'seqatt':SEQATT,
+           'stringseqatt':STRINGSEQATT,
+           'emptystratt':EMPTYSTRATT,'intatt':INTATT}
+
+class VariablesTestCase(unittest.TestCase):
+
+    def setUp(self):
+        self.file = FILE_NAME
+        f = netCDF4.Dataset(self.file,'w',ncstring_attrs=True)
+        # try to set a dataset attribute with one of the reserved names.
+        f.setncattr('file_format','netcdf4_format')
+        # test attribute renameing
+        f.stratt_tmp = STRATT
+        f.renameAttribute('stratt_tmp','stratt')
+        f.emptystratt = EMPTYSTRATT
+        f.intatt = INTATT
+        f.floatatt = FLOATATT
+        f.seqatt = SEQATT
+        # sequences of strings converted to a single string.
+        f.stringseqatt = STRINGSEQATT
+        f.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
+        g = f.createGroup(GROUP_NAME)
+        f.createDimension(DIM1_NAME, DIM1_LEN)
+        f.createDimension(DIM2_NAME, DIM2_LEN)
+        f.createDimension(DIM3_NAME, DIM3_LEN)
+        g.createDimension(DIM1_NAME, DIM1_LEN)
+        g.createDimension(DIM2_NAME, DIM2_LEN)
+        g.createDimension(DIM3_NAME, DIM3_LEN)
+        g.stratt_tmp = STRATT
+        g.renameAttribute('stratt_tmp','stratt')
+        g.emptystratt = EMPTYSTRATT
+        g.intatt = INTATT
+        g.floatatt = FLOATATT
+        g.seqatt = SEQATT
+        g.stringseqatt = STRINGSEQATT
+        if netCDF4.__version__ > "1.4.2":
+            with self.assertRaises(ValueError):
+                g.arrayatt = [[1, 2], [3, 4]] # issue #841
+        g.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
+        v = f.createVariable(VAR_NAME, 'f8',(DIM1_NAME,DIM2_NAME,DIM3_NAME))
+        # try to set a variable attribute with one of the reserved names.
+        v.setncattr('ndim','three')
+        v.setncatts({'foo': 1})
+        v.setncatts(OrderedDict(bar=2))
+        v.stratt_tmp = STRATT
+        v.renameAttribute('stratt_tmp','stratt')
+        v.emptystratt = EMPTYSTRATT
+        v.intatt = INTATT
+        v.floatatt = FLOATATT
+        v.seqatt = SEQATT
+        v.stringseqatt = STRINGSEQATT
+        v.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
+        v1 = g.createVariable(VAR_NAME, 'f8',(DIM1_NAME,DIM2_NAME,DIM3_NAME))
+        v1.stratt = STRATT
+        v1.emptystratt = EMPTYSTRATT
+        v1.intatt = INTATT
+        v1.floatatt = FLOATATT
+        v1.seqatt = SEQATT
+        v1.stringseqatt = STRINGSEQATT
+        v1.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
+        # issue #485 (triggers segfault in C lib
+        # with version 1.2.1 without pull request #486)
+        f.foo = NP.array('bar','S')
+        f.foo = NP.array('bar','U')
+        # issue #529 write string attribute as NC_CHAR unless
+        # it can't be decoded to ascii.  Add setncattr_string
+        # method to force NC_STRING.
+        f.charatt = u'foo' # will be written as NC_CHAR
+        f.setncattr_string('stringatt','bar') # NC_STRING
+        f.cafe = u'caf\xe9' # NC_STRING
+        f.batt = u'caf\xe9'.encode('utf-8') #NC_CHAR
+        v.setncattr_string('stringatt','bar') # NC_STRING
+        f.close()
+
+    def tearDown(self):
+        # Remove the temporary files
+        os.remove(self.file)
+
+    def runTest(self):
+        """testing attributes"""
+        f  = netCDF4.Dataset(self.file, 'r')
+        v = f.variables[VAR_NAME]
+        g = f.groups[GROUP_NAME]
+        v1 = g.variables[VAR_NAME]
+        # check attributes in root group.
+        # global attributes.
+        # check __dict__ method for accessing all netCDF attributes.
+        for key,val in ATTDICT.items():
+            if type(val) == NP.ndarray:
+                assert f.__dict__[key].tolist() == val.tolist()
+            else:
+                assert f.__dict__[key] == val
+        # check accessing individual attributes.
+        assert f.intatt == INTATT
+        assert f.floatatt == FLOATATT
+        assert f.stratt == STRATT
+        assert f.emptystratt == EMPTYSTRATT
+        assert f.seqatt.tolist() == SEQATT.tolist()
+        #assert f.stringseqatt == ''.join(STRINGSEQATT) # issue 770
+        assert f.stringseqatt == STRINGSEQATT
+        assert f.stringseqatt_array == STRINGSEQATT
+        assert f.getncattr('file_format') == 'netcdf4_format'
+        # variable attributes.
+        # check __dict__ method for accessing all netCDF attributes.
+        for key,val in ATTDICT.items():
+            if type(val) == NP.ndarray:
+                assert v.__dict__[key].tolist() == val.tolist()
+            else:
+                assert v.__dict__[key] == val
+        # check accessing individual attributes.
+        assert v.intatt == INTATT
+        assert v.floatatt == FLOATATT
+        assert v.stratt == STRATT
+        assert v.seqatt.tolist() == SEQATT.tolist()
+        #assert v.stringseqatt == ''.join(STRINGSEQATT) # issue 770
+        assert v.stringseqatt == STRINGSEQATT
+        assert v.stringseqatt_array == STRINGSEQATT
+        assert v.getncattr('ndim') == 'three'
+        assert v.getncattr('foo') == 1
+        assert v.getncattr('bar') == 2
+        # check type of attributes using ncdump (issue #529)
+        try:  # ncdump may not be on the system PATH
+            nc_proc = subprocess.Popen(
+                ['ncdump', '-h', FILE_NAME], stdout=subprocess.PIPE)
+        except OSError:
+            warnings.warn('"ncdump" not on system path; cannot test '
+                          'read of some attributes')
+            pass
+        else:  # We do have ncdump output
+            dep = nc_proc.communicate()[0]
+            try: # python 2
+                ncdump_output = dep.split('\n')
+            except TypeError: # python 3
+                ncdump_output = str(dep,encoding='utf-8').split('\n')
+            for line in ncdump_output:
+                line = line.strip('\t\n\r')
+                if "stringatt" in line: assert line.startswith('string')
+                if "charatt" in line: assert line.startswith('string')
+                if "cafe" in line: assert line.startswith('string')
+                if "batt" in line: assert line.startswith('string')
+        # check attributes in subgroup.
+        # global attributes.
+        for key,val in ATTDICT.items():
+            if type(val) == NP.ndarray:
+                assert g.__dict__[key].tolist() == val.tolist()
+            else:
+                assert g.__dict__[key] == val
+        assert g.intatt == INTATT
+        assert g.floatatt == FLOATATT
+        assert g.stratt == STRATT
+        assert g.emptystratt == EMPTYSTRATT
+        assert g.seqatt.tolist() == SEQATT.tolist()
+        #assert g.stringseqatt == ''.join(STRINGSEQATT) # issue 770
+        assert g.stringseqatt == STRINGSEQATT
+        assert g.stringseqatt_array == STRINGSEQATT
+        for key,val in ATTDICT.items():
+            if type(val) == NP.ndarray:
+                assert v1.__dict__[key].tolist() == val.tolist()
+            else:
+                assert v1.__dict__[key] == val
+        assert v1.intatt == INTATT
+        assert v1.floatatt == FLOATATT
+        assert v1.stratt == STRATT
+        assert v1.emptystratt == EMPTYSTRATT
+        assert v1.seqatt.tolist() == SEQATT.tolist()
+        #assert v1.stringseqatt == ''.join(STRINGSEQATT) # issue 770
+        assert v1.stringseqatt == STRINGSEQATT
+        assert v1.stringseqatt_array == STRINGSEQATT
+        assert getattr(v1,'nonexistantatt',None) == None
+        f.close()
+
+if __name__ == '__main__':
+    unittest.main()

From 883d4dbd05154d3af81fee41a71e024d5fcd30bb Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 25 Feb 2019 09:19:26 -0700
Subject: [PATCH 0228/1504] cleanup up docstrings, added Changelog entry.

---
 Changelog            | 3 +++
 netCDF4/_netCDF4.pyx | 9 +++++++--
 2 files changed, 10 insertions(+), 2 deletions(-)

diff --git a/Changelog b/Changelog
index e481cb967..adbb0d6a1 100644
--- a/Changelog
+++ b/Changelog
@@ -9,6 +9,9 @@
  * improved error messages for ncinfo and other utilities (issue #873).
  * fix for int64 attributes not being created for NETCDF3_64BIT_DATA (CDF5)
    files (issue #878).
+ * Added kwarg `ncstring_attrs` to Dataset.__init__ that forces all text
+   attributes to be written as variable length strings (netCDF type
+   NC_STRING - issue #882).
 
  version 1.4.2 (tag v1.4.2rel)
 =============================
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 2edd5f8c1..dec41c2ab 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1915,6 +1915,9 @@ group, so the path is simply `'/'`.
 
 **`keepweakref`**: If `True`, child Dimension and Variables objects only keep weak
 references to the parent Dataset or Group.
+
+**`ncstring_attrs`**: If `True`, all text attributes will be written as variable-length
+strings.
     """
     cdef object __weakref__, _inmemory
     cdef public int _grpid
@@ -1973,7 +1976,8 @@ references to the parent Dataset or Group.
     """If `True`, child Dimension and Variables objects only keep weak references to
     the parent Dataset or Group."""
     __pdoc__['Dataset.ncstring_attrs']=\
-    """If `True`, string attributes will be NCSTRINGs instead of character arrays."""
+    """If `True`, all string attributes will be variable-length NC_STRINGs
+    (default behaviour is to write ascii text attributes as NC_CHAR)."""
 
     def __init__(self, filename, mode='r', clobber=True, format='NETCDF4',
                      diskless=False, persist=False, keepweakref=False,
@@ -2047,7 +2051,8 @@ references to the parent Dataset or Group.
         rendered unusable when the parent Dataset instance is garbage collected.
 
         **`ncstring_attrs`**: if `ncstring_attrs=True`, all string attributes will use
-        the variable length NCSTRING attributes (default `False`).
+        the variable length NC_STRING attributes (default `False`, ascii text
+        attributes written as NC_CHAR).
 
         **`memory`**: if not `None`, create or open an in-memory Dataset.
         If mode = 'r', the memory kwarg must contain a memory buffer object

From bfb73bcc06c1bb64d751a1a9212908fe934ccb94 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 25 Feb 2019 11:04:15 -0700
Subject: [PATCH 0229/1504] use python 3.7 and netcdf-c 4.6.2 in mpi test

---
 .travis.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index 9b9b7a326..e14ee4e3e 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -30,13 +30,13 @@ matrix:
       env:
         - DEPENDS="numpy==1.9.0 cython==0.21 ordereddict==1.1 setuptools==18.0 cftime"
     # test MPI
-    - python: 2.7
+    - python: 3.7
       dist: trusty
       env: 
         - MPI=1
         - CC=mpicc
         - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
-        - NETCDF_VERSION=4.6.1
+        - NETCDF_VERSION=4.6.2
         - NETCDF_DIR=$HOME
         - PATH=${NETCDF_DIR}/bin:${PATH} # pick up nc-config here
       addons:

From de9d3944840d77a884dec59c3bfa3292b6eae65d Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 25 Feb 2019 11:38:53 -0700
Subject: [PATCH 0230/1504] update to xenial

---
 .travis.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.travis.yml b/.travis.yml
index e14ee4e3e..391ddd304 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -31,7 +31,7 @@ matrix:
         - DEPENDS="numpy==1.9.0 cython==0.21 ordereddict==1.1 setuptools==18.0 cftime"
     # test MPI
     - python: 3.7
-      dist: trusty
+      dist: xenial
       env: 
         - MPI=1
         - CC=mpicc

From 2ebbbe587c2651366e6953459c1ee37197815d53 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 25 Feb 2019 12:10:24 -0700
Subject: [PATCH 0231/1504] fix download URL

---
 ci/travis/build-parallel-netcdf.sh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ci/travis/build-parallel-netcdf.sh b/ci/travis/build-parallel-netcdf.sh
index 1c38eec2c..f6ef354a4 100755
--- a/ci/travis/build-parallel-netcdf.sh
+++ b/ci/travis/build-parallel-netcdf.sh
@@ -4,7 +4,7 @@ set -e
 
 echo "Using downloaded netCDF version ${NETCDF_VERSION} with parallel capabilities enabled"
 pushd /tmp
-wget ftp://ftp.unidata.ucar.edu/pub/netcdf/netcdf-${NETCDF_VERSION}.tar.gz
+wget ftp://ftp.unidata.ucar.edu/pub/netcdf/netcdf-c-${NETCDF_VERSION}.tar.gz
 tar -xzvf netcdf-${NETCDF_VERSION}.tar.gz
 pushd netcdf-${NETCDF_VERSION}
 ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap  --enable-parallel

From fe4a87e6335878b0f5967535854288f4037dee72 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 25 Feb 2019 12:32:15 -0700
Subject: [PATCH 0232/1504] update

---
 ci/travis/build-parallel-netcdf.sh | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/ci/travis/build-parallel-netcdf.sh b/ci/travis/build-parallel-netcdf.sh
index f6ef354a4..ef1896110 100755
--- a/ci/travis/build-parallel-netcdf.sh
+++ b/ci/travis/build-parallel-netcdf.sh
@@ -5,8 +5,8 @@ set -e
 echo "Using downloaded netCDF version ${NETCDF_VERSION} with parallel capabilities enabled"
 pushd /tmp
 wget ftp://ftp.unidata.ucar.edu/pub/netcdf/netcdf-c-${NETCDF_VERSION}.tar.gz
-tar -xzvf netcdf-${NETCDF_VERSION}.tar.gz
-pushd netcdf-${NETCDF_VERSION}
+tar -xzvf netcdf-c-${NETCDF_VERSION}.tar.gz
+pushd netcdf-c-${NETCDF_VERSION}
 ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap  --enable-parallel
 make -j 2
 make install

From 244ce1d9b0469f59e5ec9454643a36853e0ac3d0 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 25 Feb 2019 13:08:46 -0700
Subject: [PATCH 0233/1504] revert back to trusty

---
 .travis.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index 391ddd304..3164156b0 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -30,8 +30,8 @@ matrix:
       env:
         - DEPENDS="numpy==1.9.0 cython==0.21 ordereddict==1.1 setuptools==18.0 cftime"
     # test MPI
-    - python: 3.7
-      dist: xenial
+    - python: 2.7
+      dist: trusty 
       env: 
         - MPI=1
         - CC=mpicc

From 7afbd9a53aaf8728d4bd6eb60df10e21a799a95b Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 25 Feb 2019 13:40:18 -0700
Subject: [PATCH 0234/1504] revert to 4.6.1

---
 .travis.yml                        | 6 +++---
 ci/travis/build-parallel-netcdf.sh | 6 +++---
 2 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index 3164156b0..8a6c32af1 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -30,13 +30,13 @@ matrix:
       env:
         - DEPENDS="numpy==1.9.0 cython==0.21 ordereddict==1.1 setuptools==18.0 cftime"
     # test MPI
-    - python: 2.7
-      dist: trusty 
+    - python: 3.6
+      dist: trusty
       env: 
         - MPI=1
         - CC=mpicc
         - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
-        - NETCDF_VERSION=4.6.2
+        - NETCDF_VERSION=4.6.1
         - NETCDF_DIR=$HOME
         - PATH=${NETCDF_DIR}/bin:${PATH} # pick up nc-config here
       addons:
diff --git a/ci/travis/build-parallel-netcdf.sh b/ci/travis/build-parallel-netcdf.sh
index ef1896110..1c38eec2c 100755
--- a/ci/travis/build-parallel-netcdf.sh
+++ b/ci/travis/build-parallel-netcdf.sh
@@ -4,9 +4,9 @@ set -e
 
 echo "Using downloaded netCDF version ${NETCDF_VERSION} with parallel capabilities enabled"
 pushd /tmp
-wget ftp://ftp.unidata.ucar.edu/pub/netcdf/netcdf-c-${NETCDF_VERSION}.tar.gz
-tar -xzvf netcdf-c-${NETCDF_VERSION}.tar.gz
-pushd netcdf-c-${NETCDF_VERSION}
+wget ftp://ftp.unidata.ucar.edu/pub/netcdf/netcdf-${NETCDF_VERSION}.tar.gz
+tar -xzvf netcdf-${NETCDF_VERSION}.tar.gz
+pushd netcdf-${NETCDF_VERSION}
 ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap  --enable-parallel
 make -j 2
 make install

From be76b10977181e31ef10b96d145db65772b1e0a5 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 25 Feb 2019 13:56:08 -0700
Subject: [PATCH 0235/1504] try 4.6.2 again, add --disable-cdf5

---
 .travis.yml                        | 2 +-
 ci/travis/build-parallel-netcdf.sh | 8 ++++----
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index 8a6c32af1..e39fcab7b 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -36,7 +36,7 @@ matrix:
         - MPI=1
         - CC=mpicc
         - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
-        - NETCDF_VERSION=4.6.1
+        - NETCDF_VERSION=4.6.2
         - NETCDF_DIR=$HOME
         - PATH=${NETCDF_DIR}/bin:${PATH} # pick up nc-config here
       addons:
diff --git a/ci/travis/build-parallel-netcdf.sh b/ci/travis/build-parallel-netcdf.sh
index 1c38eec2c..dbebda725 100755
--- a/ci/travis/build-parallel-netcdf.sh
+++ b/ci/travis/build-parallel-netcdf.sh
@@ -4,10 +4,10 @@ set -e
 
 echo "Using downloaded netCDF version ${NETCDF_VERSION} with parallel capabilities enabled"
 pushd /tmp
-wget ftp://ftp.unidata.ucar.edu/pub/netcdf/netcdf-${NETCDF_VERSION}.tar.gz
-tar -xzvf netcdf-${NETCDF_VERSION}.tar.gz
-pushd netcdf-${NETCDF_VERSION}
-./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap  --enable-parallel
+wget ftp://ftp.unidata.ucar.edu/pub/netcdf/netcdf-c-${NETCDF_VERSION}.tar.gz
+tar -xzvf netcdf-c-${NETCDF_VERSION}.tar.gz
+pushd netcdf-c-${NETCDF_VERSION}
+./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap  --enable-parallel --disable-cdf5
 make -j 2
 make install
 popd

From 311bb700668126e3ad27e0856ba376b01e606293 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 25 Feb 2019 14:12:39 -0700
Subject: [PATCH 0236/1504] explicity set NC_NETCDF4 in nc_create_par

---
 netCDF4/_netCDF4.pyx | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 657e6d902..880cc5f30 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2131,7 +2131,7 @@ references to the parent Dataset or Group.
                 if clobber:
                     if parallel:
                         IF HAS_NC_PAR:
-                            ierr = nc_create_par(path, NC_CLOBBER | NC_MPIIO, \
+                            ierr = nc_create_par(path, NC_CLOBBER | NC_MPIIO | NC_NETCDF4, \
                                    mpicomm, mpiinfo, &grpid)
                         ELSE:
                             pass
@@ -2146,7 +2146,7 @@ references to the parent Dataset or Group.
                 else:
                     if parallel:
                         IF HAS_NC_PAR:
-                            ierr = nc_create_par(path, NC_NOCLOBBER | NC_MPIIO, \
+                            ierr = nc_create_par(path, NC_NOCLOBBER | NC_MPIIO | NC_NETCDF4, \
                                    mpicomm, mpiinfo, &grpid)
                         ELSE:
                             pass
@@ -2218,7 +2218,7 @@ references to the parent Dataset or Group.
                 if parallel:
                     # NC_SHARE ignored
                     IF HAS_NC_PAR:
-                        ierr = nc_create_par(path, NC_CLOBBER | NC_MPIIO, \
+                        ierr = nc_create_par(path, NC_CLOBBER | NC_MPIIO | NC_NETCDF4, \
                                mpicomm, mpiinfo, &grpid)
                     ELSE:
                         pass
@@ -2233,7 +2233,7 @@ references to the parent Dataset or Group.
                 if parallel:
                     # NC_SHARE ignored
                     IF HAS_NC_PAR:
-                        ierr = nc_create_par(path, NC_NOCLOBBER | NC_MPIIO, \
+                        ierr = nc_create_par(path, NC_NOCLOBBER | NC_MPIIO | NC_NETCDF4, \
                                mpicomm, mpiinfo, &grpid)
                     ELSE:
                         pass

From 9bc7c7285d38c6e739e9948924f1cd42cc991212 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 25 Feb 2019 14:27:45 -0700
Subject: [PATCH 0237/1504] run mpi test last

---
 .travis.yml | 14 ++++++++++----
 1 file changed, 10 insertions(+), 4 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index e39fcab7b..2e19cb19f 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -59,11 +59,17 @@ install:
   - python setup.py install
 
 script:
+  - cd test
+  - python run_all.py
   - |
     if [ $MPI -eq 1 ] ; then
-       cd examples
+       cd ../examples
        mpirun -np 4 python mpi_example.py
-       cd ..
+       if [ $? -ne 0 ] ; then
+         echo "mpi test failed!"
+         exit 1
+       else
+         echo "mpi test passed!"
+         exit 0
+       fi
     fi
-  - cd test
-  - python run_all.py

From dd116ed8c5e87281d1f70f73d7e55dbf98a6040f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 25 Feb 2019 15:01:18 -0700
Subject: [PATCH 0238/1504] check to make sure that mpi_example failure noticed
 by travis

---
 Changelog                          | 4 +++-
 ci/travis/build-parallel-netcdf.sh | 2 +-
 netCDF4/_netCDF4.pyx               | 3 ++-
 3 files changed, 6 insertions(+), 3 deletions(-)

diff --git a/Changelog b/Changelog
index e481cb967..4226605d5 100644
--- a/Changelog
+++ b/Changelog
@@ -1,4 +1,4 @@
- version 1.4.3 (not yet released)
+ version 1.4.3 (tag v1.4.3rel)
 =============================
  * make set_always_mask work in MFDataset.
  * fix saving diskless files to disk with netcdf-c >= 4.6.2.
@@ -9,6 +9,8 @@
  * improved error messages for ncinfo and other utilities (issue #873).
  * fix for int64 attributes not being created for NETCDF3_64BIT_DATA (CDF5)
    files (issue #878).
+ * fix for MPI parallel error ("NetCDF: Attempt to use feature that was not
+   turned on when netCDF was built") using netcdf-c 4.6.2 (issue #883).
 
  version 1.4.2 (tag v1.4.2rel)
 =============================
diff --git a/ci/travis/build-parallel-netcdf.sh b/ci/travis/build-parallel-netcdf.sh
index dbebda725..ef1896110 100755
--- a/ci/travis/build-parallel-netcdf.sh
+++ b/ci/travis/build-parallel-netcdf.sh
@@ -7,7 +7,7 @@ pushd /tmp
 wget ftp://ftp.unidata.ucar.edu/pub/netcdf/netcdf-c-${NETCDF_VERSION}.tar.gz
 tar -xzvf netcdf-c-${NETCDF_VERSION}.tar.gz
 pushd netcdf-c-${NETCDF_VERSION}
-./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap  --enable-parallel --disable-cdf5
+./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap  --enable-parallel
 make -j 2
 make install
 popd
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 880cc5f30..f5b22538f 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2146,7 +2146,8 @@ references to the parent Dataset or Group.
                 else:
                     if parallel:
                         IF HAS_NC_PAR:
-                            ierr = nc_create_par(path, NC_NOCLOBBER | NC_MPIIO | NC_NETCDF4, \
+                            #ierr = nc_create_par(path, NC_NOCLOBBER | NC_MPIIO | NC_NETCDF4, \
+                            ierr = nc_create_par(path, NC_NOCLOBBER | NC_MPIIO, \
                                    mpicomm, mpiinfo, &grpid)
                         ELSE:
                             pass

From 83ece88f7017c55eeeb92ff68a7fa54701724a5f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 25 Feb 2019 15:07:27 -0700
Subject: [PATCH 0239/1504] check that failure occurs if NC_NETCDF4 not
 specified

---
 netCDF4/_netCDF4.pyx | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index f5b22538f..57a70c552 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2131,7 +2131,8 @@ references to the parent Dataset or Group.
                 if clobber:
                     if parallel:
                         IF HAS_NC_PAR:
-                            ierr = nc_create_par(path, NC_CLOBBER | NC_MPIIO | NC_NETCDF4, \
+                            #ierr = nc_create_par(path, NC_CLOBBER | NC_MPIIO | NC_NETCDF4, \
+                            ierr = nc_create_par(path, NC_CLOBBER | NC_MPIIO, \
                                    mpicomm, mpiinfo, &grpid)
                         ELSE:
                             pass
@@ -2146,8 +2147,7 @@ references to the parent Dataset or Group.
                 else:
                     if parallel:
                         IF HAS_NC_PAR:
-                            #ierr = nc_create_par(path, NC_NOCLOBBER | NC_MPIIO | NC_NETCDF4, \
-                            ierr = nc_create_par(path, NC_NOCLOBBER | NC_MPIIO, \
+                            ierr = nc_create_par(path, NC_NOCLOBBER | NC_MPIIO | NC_NETCDF4, \
                                    mpicomm, mpiinfo, &grpid)
                         ELSE:
                             pass

From 77f0982598004dba677429dbb77f5089471f9c80 Mon Sep 17 00:00:00 2001
From: Christian Marquardt 
Date: Mon, 25 Feb 2019 23:37:17 +0100
Subject: [PATCH 0240/1504] Provide set_ncstring_attrs() methods rather than an
 argument to Dataset.__init__().

---
 Changelog              | 72 +++++++++++++++++++++---------------------
 netCDF4/_netCDF4.pyx   | 54 ++++++++++++++++++++++++++++---
 test/tst_atts_ncstr.py |  4 ++-
 3 files changed, 88 insertions(+), 42 deletions(-)

diff --git a/Changelog b/Changelog
index adbb0d6a1..2a024f03d 100644
--- a/Changelog
+++ b/Changelog
@@ -9,15 +9,15 @@
  * improved error messages for ncinfo and other utilities (issue #873).
  * fix for int64 attributes not being created for NETCDF3_64BIT_DATA (CDF5)
    files (issue #878).
- * Added kwarg `ncstring_attrs` to Dataset.__init__ that forces all text
-   attributes to be written as variable length strings (netCDF type
-   NC_STRING - issue #882).
+ * Added methods `set_ncstring_attrs()` to Dataset, Group and Variable that
+   forces all text attributes to be written as variable length strings (netCDF
+   type NC_STRING - issue #882).
 
  version 1.4.2 (tag v1.4.2rel)
 =============================
  * add get_dims Variable method (issue #824)
  * make sure format keyword not ignored when mode is 'ws' (issue #827)
- * fix numpy FutureWarning (non-tuple sequence for     
+ * fix numpy FutureWarning (non-tuple sequence for
    multidimensional indexing is deprecated), issue #833.
  * add 'master_file' kwarg to MFDataset.__init__ (issue #835).
  * always use nc_get_vars for strided access over OpenDAP (issue #838).
@@ -35,7 +35,7 @@
  * new Dataset and Variable methods (set_always_mask) to optionally
    re-enable old behaviour (return masked arrays
    only if selected slice contains missing values) (issue #809).
-	
+
  version 1.4.0 (tag v1.4.0rel)
 =============================
  * fixed bug in detection of CDF5 library support in setup.py (pull request
@@ -57,20 +57,20 @@
  * fix loading of enum type names (issue #775).
  * make sure missing_value applies only to scaled short integers if
    auto-scaling is on (issue #777).
- * automatically create views of compound types with character arrays as 
+ * automatically create views of compound types with character arrays as
    numpy strings (issue #773).  Can be disabled using
    'set_auto_chartostring(False)'. Numpy structured
    array dtypes with 'SN' string subtypes can now be used to
    define netcdf compound types (they get converted to ('S1',N)
    character array types automatically).
- * always return masked array by default, even if there are no 
+ * always return masked array by default, even if there are no
    masked values (too surprising to get ndarray or MaskedArray depending
    on slice, issue #785).
  * treat valid_min/valid_max/_FillValue/missing_value as unsigned
    integers if _Unsigned is set (to mimic behaviour of netcdf-java).
    Conversion to unsigned type now occurs before masking and scale/offset
    operation. Issue #794.
- 
+
 
  version 1.3.1 (tag v1.3.1rel)
 =============================
@@ -89,20 +89,20 @@
 
  version 1.3.0 (tag v1.3.0rel)
 ==============================
- * always search for HDF5 headers when building, even when nc-config is used 
+ * always search for HDF5 headers when building, even when nc-config is used
    (since nc-config does not always include the path to the HDF5 headers).
    Also use H5get_libversion to obtain HDF5 version info instead of
    H5public.h. Fixes issue #677.
  * encoding kwarg added to Dataset.__init__ and Dataset.filepath (default
    is to use sys.getfilesystemencoding()) so that oddball
-   encodings (such as cp1252 on windows) can be handled in Dataset 
+   encodings (such as cp1252 on windows) can be handled in Dataset
    filepaths (issue #686).
  * Calls to nc_get_vars are avoided, since nc_get_vars is very slow (issue
    #680).  Strided slices are now converted to multiple calls to
    nc_get_vara.  This speeds up strided slice reads by a factor of 10-100
    (especially for NETCDF4/HDF5 files) in most cases. In some cases, strided reads
    using nc_get_vars are faster (e.g. strided reads over many dimensions
-   such as var[:,::2,::2,::2])), so a variable method use_nc_get_vars was added. 
+   such as var[:,::2,::2,::2])), so a variable method use_nc_get_vars was added.
    var.use_nc_get_vars(True) will tell the library to use nc_get_vars instead
    of multiple calls to nc_get_vara, which was the default behaviour previous
    to this change.
@@ -110,10 +110,10 @@
    exactly backwards (issue #685 - thanks to @pgamez and @mdecker).
  * Fix error message for illegal ellipsis slicing, add test (issue #701).
  * Improve timezone format parsing in netcdftime
-   (https://github.com/Unidata/netcdftime/issues/17).  
+   (https://github.com/Unidata/netcdftime/issues/17).
  * make sure numpy datatypes used to define CompoundTypes have
    isalignedstruct flag set to True (issue #705), otherwise.
-   segfaults can occur. Fix required raising them minimum numpy requirement 
+   segfaults can occur. Fix required raising them minimum numpy requirement
    from 1.7.0 to 1.9.0.
  * ignore missing_value, _FillValue, valid_range, valid_min and valid_max
    when creating masked arrays if attribute cannot be safely
@@ -127,7 +127,7 @@
    view as unsigned type after scaling and masking). Issue #671.
  * Always mask values outside valid_min, valid_max (not just when
    missing_value attribue present).  Issue #672.
- * Fix setup.py so pip install doesn't fail if cython not installed.  
+ * Fix setup.py so pip install doesn't fail if cython not installed.
    setuptools >= 18.0 now required for installation (Issue #666).
 
  version 1.2.8 (tag v1.2.8rel)
@@ -146,7 +146,7 @@
    the chartostring utility function is used to convert the array of
    characters to an array of strings with one less dimension (the last
    dimension is interpreted as the length of each string) when reading the
-   data. When writing the data, stringtochar is used to convert a numpy 
+   data. When writing the data, stringtochar is used to convert a numpy
    array of fixed length strings to an array of characters with one more
    dimension. chartostring and stringtochar now also have an 'encoding' kwarg.
    Automatic conversion to/from character to string arrays can be turned off
@@ -166,7 +166,7 @@
 
  version 1.2.6 (tag v1.2.6rel)
 ==============================
- * fix some test failures on big endian PPC64 that were due to 
+ * fix some test failures on big endian PPC64 that were due to
    errors in byte-swapping logic. Also fixed bug in enum
    code exposed on PPC64 (issue #608).
  * remove support for python 2.6 (it probably still will work for a while
@@ -213,13 +213,13 @@
    byte order before passing to netcdf-c library.  Data read from variable
    with non-native byte order is also byte-swapped, so that dtype remains
    consistent with netcdf variable.  Behavior now consistent with h5py.
- * raise warning for HDF5 1.10.x (issue #549), since backwards 
+ * raise warning for HDF5 1.10.x (issue #549), since backwards
    incompatible files may be created.
  * raise AttributeError instead of RuntimeError when attribute operation
-   fails.  raise IOError instead of RuntimeError when nc_create or 
+   fails.  raise IOError instead of RuntimeError when nc_create or
    nc_open fails (issue #546).
  * Use NamedTemporaryFile instead of deprecated mktemp in tests
-   (pull request #543). 
+   (pull request #543).
  * add AppVeyor automated windows tests (pull request #540).
 
  version 1.2.3.1 (tag v1.2.3.1rel)
@@ -244,17 +244,17 @@
    NETCDF3_64BIT_DATA format and filepath Dataset method).
  * expose netcdftime.__version__ (issue #504).
  * fix potential memory leak in Dataset.filepath in attempt to fix
-   mysterious segfaults on CentOS6 (issue #506). Segfaults  
+   mysterious segfaults on CentOS6 (issue #506). Segfaults
    can apparently still occur on systems like CentOS6 with old versions of glibc.
 
  version 1.2.2 (tag v1.2.2rel)
  =============================
  * fix failing tests on python 2.6 (issue #497). Change minimum required
    python from 2.5 to 2.6.
- * Potential memory leaks fixed by freeing string pointers internally allocated 
+ * Potential memory leaks fixed by freeing string pointers internally allocated
    in netcdf-c using nc_free_string. Also use nc_free_vlens to free space allocated
    for vlens inside netcdf-c (issue #495).
- * invoke str on filename argument to Dataset constructor, so pathlib 
+ * invoke str on filename argument to Dataset constructor, so pathlib
    instances can be used (issue #489).
  * don't use hardwired NC_MAX_DIMS or NC_MAX_VARS internally to allocate space
    for dimension or variable ids.  Instead, find out the number of dims
@@ -273,7 +273,7 @@
  * add 'size' attribute to Dimension (same as len(d), where
    d is a Dimension instance, issue #477).
  * fix bug in nc3tonc4 with --unpackshort=1 (issue #474).
- * dates do not have to be contiguous, i.e. can be before and after the 
+ * dates do not have to be contiguous, i.e. can be before and after the
    missing dates in Gregorian calendar (pull request #476).
 
  version 1.2.1 (tag v1.2.1rel)
@@ -321,9 +321,9 @@
    packing (set_auto_scale and set_auto_maskandscale) when writing.
    Pull request #435.
  * use USE_SETUPCFG env var to over-ride use of setup.cfg. If USE_SETUPCFG
-   evaluates to false, setup.cfg will not be used and all configuration 
+   evaluates to false, setup.cfg will not be used and all configuration
    variables can be set from environment variables.  Useful when using 'pip
-   install' and nc-config is broken (issue #438).  
+   install' and nc-config is broken (issue #438).
  * fix for integer overflow in date2index (issue #444).
 
  version 1.1.8 (tag v1.1.8rel)
@@ -341,18 +341,18 @@
    will now return the existing group instance.
    Dataset.__getitem__ also added.  nc['/path/to'] returns
    a Group instance, and nc['/path/to/var1'] returns a Variable
-   instance.  
+   instance.
  * change minimum required numpy to 1.7.0, fix so all tests pass with 1.7.0.
    Added travis tests for minimum required cython, numpy (issue #404).
  * enable abbreviations to time units specification, as allowed in CF (issue
    #402). Now, instead of just 'seconds' and 'seconds', 'secs', 'sec' and 's'
    are also allowed (similar to minutes, days and hours).
- * install utility scripts in utils directory with setuptools entry points 
+ * install utility scripts in utils directory with setuptools entry points
    (pull request #392 from @mindw).  Code for utilities moved
    to netCDF4_utils.py - makes utilities more windows-friendly.
  * make sure booleans are treated correctly in setup.cfg. Add
    use_cython (default True) to setup.cfg.  If set to False, then
-   cython will not be used to compile netCDF4.pyx (existing netCDF4.c 
+   cython will not be used to compile netCDF4.pyx (existing netCDF4.c
    will be used instead).
  * use "from Cython.Build import cythonize" instead of
    "from Cython.Distutils import build_ext" in setup.py (issue #393)
@@ -360,9 +360,9 @@
    https://github.com/cython/cython/wiki/enhancements-distutils_preprocessing).
  * unicode attributes now written as strings, not bytes (using
    nc_put_att_string instead of nc_put_att_text, issue #388).
- * add __orthogonal_indexing__ attribute to Variable, Dataset and Group (issue #385) to 
+ * add __orthogonal_indexing__ attribute to Variable, Dataset and Group (issue #385) to
    denote that Variable objects do not follow numpy indexing semantics for integer and
-   boolean array indices. 
+   boolean array indices.
  * make sure application of scale_factor and add_offset works correctly when
    scale_factor not given (issue #381).
  * add man pages for nc3tonc4, nc4tonc3, ncinfo in man directory.
@@ -380,14 +380,14 @@
    to use it (otherwise compilation with fail).  Issue 367.
  * add ipython notebooks from Unidata workshop in examples directory.
  * fix ellipsis variable slicing regression (issue 371).
- * release the Global Interpreter Lock (GIL) when calling the C 
+ * release the Global Interpreter Lock (GIL) when calling the C
    library for read operations.  Speeds up multi-threaded reads
-   (issue 369).  Caution - the HDF5 library may need to be compiled 
+   (issue 369).  Caution - the HDF5 library may need to be compiled
    with the threadsafe option to ensure that global data structures
    are not corrupted by simultaneous manipulation by different threads.
  * Make sure USE_NCCONFIG environment variable takes precedence over value
    of use_ncconfig in setup.cfg.  With this change, 'pip install netCDF4'
-   with USE_NCCONFIG=1 will use environment variables to find paths to 
+   with USE_NCCONFIG=1 will use environment variables to find paths to
    libraries and include files, instead of relying on nc-config (issue #341).
 
  version 1.1.6 (tag v1.1.6rel)
@@ -400,13 +400,13 @@
  * make calendar name keyword for num2date/date2num case insensitive
    (issue 362).
  * make sure units parser returns time-zone naive datetime instance that
-   includes UTC offset (issue 357).  UTC offset was applied incorrectly in 
+   includes UTC offset (issue 357).  UTC offset was applied incorrectly in
    netcdftime.date2num and num2date.  No longer need to depend on
    python-dateutil.
 
  version 1.1.5 (tag v1.1.5rel)
  =============================
-  
+
  * add dependency on python-dateutil in setup.py and install docs.
  * use python datetime in num2date and date2num whenever possible. Remove
    duplicate num2date and date2num functions from netcdftime. Addresses issue
@@ -426,7 +426,7 @@
  * speedup conversion of array indices to slices (issue #325).
  * fix for issue #330 (incorrect values for seconds returned by netcdftime).
  * fix reading of scalar vlen variables (issue #333).
- * setting fill_value=False in createVariable for vlen and compound variables 
+ * setting fill_value=False in createVariable for vlen and compound variables
    now does nothing, instead of causing an error when the Dataset is closed
    (issue #331).
  * cython will regenerate netCDF4.c when install is run, not just build.
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index dec41c2ab..c3891eee6 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1975,13 +1975,10 @@ strings.
     __pdoc__['Dataset.keepweakref']=\
     """If `True`, child Dimension and Variables objects only keep weak references to
     the parent Dataset or Group."""
-    __pdoc__['Dataset.ncstring_attrs']=\
-    """If `True`, all string attributes will be variable-length NC_STRINGs
-    (default behaviour is to write ascii text attributes as NC_CHAR)."""
 
     def __init__(self, filename, mode='r', clobber=True, format='NETCDF4',
                      diskless=False, persist=False, keepweakref=False,
-                     memory=None, encoding=None, parallel=False, ncstring_attrs=False,
+                     memory=None, encoding=None, parallel=False,
                      Comm comm=None, Info info=None, **kwargs):
         """
         **`__init__(self, filename, mode="r", clobber=True, diskless=False,
@@ -2274,7 +2271,7 @@ strings.
         self.path = '/'
         self.parent = None
         self.keepweakref = keepweakref
-        self.ncstring_attrs = ncstring_attrs
+        self.ncstring_attrs = False
         # get compound, vlen and enum types in the root Group.
         self.cmptypes, self.vltypes, self.enumtypes = _get_types(self)
         # get dimensions in the root group.
@@ -3047,6 +3044,38 @@ the default behaviour.
                 for var in group.variables.values():
                     var.set_always_mask(value)
 
+    def set_ncstring_attrs(self, value):
+        """
+**`set_ncstring_attrs(self, True_or_False)`**
+
+Call `netCDF4.Variable.set_ncstring_attrs` for all variables contained in
+this `netCDF4.Dataset` or `netCDF4.Group`, as well as for all its
+subgroups and their variables.
+
+**`True_or_False`**: Boolean determining if all string attributes are
+created as variable-length NC_STRINGs, (if True), or if ascii text
+attributes are stored as NC_CHARs (if False; default)
+
+***Note***: Calling this function only affects newly created attributes
+of existing (sub-) groups and their variables.
+        """
+
+        self.ncstring_attrs = bool(value)
+
+        # this is a hack to make inheritance work in MFDataset
+        # (which stores variables in _vars)
+        _vars = self.variables
+        if _vars is None:
+            _vars = self._vars
+        for var in _vars.values():
+            var.set_ncstring_attrs(value)
+
+        for groups in _walk_grps(self):
+            for group in groups:
+                group.ncstring_attrs = bool(value) # do not recurse into subgroups...
+                for var in group.variables.values():
+                    var.set_ncstring_attrs(value)
+
     def get_variables_by_attributes(self, **kwargs):
         """
 **`get_variables_by_attribute(self, **kwargs)`**
@@ -5008,6 +5037,21 @@ numpy arrays are not performed).
         """
         self.always_mask = bool(always_mask)
 
+    def set_ncstring_attrs(self,ncstring_attrs):
+        """
+**`set_always_mask(self,ncstring_attrs)`**
+
+turn on or off creating NC_STRING string attributes.
+
+If `ncstring_attrs` is set to `True` then text attributes will be variable-length
+NC_STRINGs.
+
+The default value of `ncstring_attrs` is `False` (writing ascii text attributes as
+NC_CHAR).
+
+        """
+        self.ncstring_attrs = bool(ncstring_attrs)
+
     def _put(self,ndarray data,start,count,stride):
         """Private method to put data into a netCDF variable"""
         cdef int ierr, ndims
diff --git a/test/tst_atts_ncstr.py b/test/tst_atts_ncstr.py
index 12d772fed..5b00d60ef 100644
--- a/test/tst_atts_ncstr.py
+++ b/test/tst_atts_ncstr.py
@@ -42,7 +42,9 @@ class VariablesTestCase(unittest.TestCase):
 
     def setUp(self):
         self.file = FILE_NAME
-        f = netCDF4.Dataset(self.file,'w',ncstring_attrs=True)
+        f = netCDF4.Dataset(self.file,'w')
+        # make sure text attributes are always NC_STRINGs
+        f.set_ncstring_attrs(True)
         # try to set a dataset attribute with one of the reserved names.
         f.setncattr('file_format','netcdf4_format')
         # test attribute renameing

From 91adf8c9de7b695e261e80838c2849ac88690f4c Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 25 Feb 2019 16:16:49 -0700
Subject: [PATCH 0241/1504] fix test

---
 netCDF4/_netCDF4.pyx | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 57a70c552..880cc5f30 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2131,8 +2131,7 @@ references to the parent Dataset or Group.
                 if clobber:
                     if parallel:
                         IF HAS_NC_PAR:
-                            #ierr = nc_create_par(path, NC_CLOBBER | NC_MPIIO | NC_NETCDF4, \
-                            ierr = nc_create_par(path, NC_CLOBBER | NC_MPIIO, \
+                            ierr = nc_create_par(path, NC_CLOBBER | NC_MPIIO | NC_NETCDF4, \
                                    mpicomm, mpiinfo, &grpid)
                         ELSE:
                             pass

From c67635d98b49515f7c70d6a393965bd5926a4d29 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 26 Feb 2019 08:58:30 -0700
Subject: [PATCH 0242/1504] build from github master

---
 .travis.yml                        |  2 +-
 ci/travis/build-parallel-netcdf.sh | 12 +++++++++---
 2 files changed, 10 insertions(+), 4 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index 2e19cb19f..03a7317f2 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -36,7 +36,7 @@ matrix:
         - MPI=1
         - CC=mpicc
         - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
-        - NETCDF_VERSION=4.6.2
+        - NETCDF_VERSION=GITMASTER
         - NETCDF_DIR=$HOME
         - PATH=${NETCDF_DIR}/bin:${PATH} # pick up nc-config here
       addons:
diff --git a/ci/travis/build-parallel-netcdf.sh b/ci/travis/build-parallel-netcdf.sh
index ef1896110..cf7e3c84c 100755
--- a/ci/travis/build-parallel-netcdf.sh
+++ b/ci/travis/build-parallel-netcdf.sh
@@ -4,9 +4,15 @@ set -e
 
 echo "Using downloaded netCDF version ${NETCDF_VERSION} with parallel capabilities enabled"
 pushd /tmp
-wget ftp://ftp.unidata.ucar.edu/pub/netcdf/netcdf-c-${NETCDF_VERSION}.tar.gz
-tar -xzvf netcdf-c-${NETCDF_VERSION}.tar.gz
-pushd netcdf-c-${NETCDF_VERSION}
+if [ ${NETCDF_VERSION} == "GITMASTER" ]; then
+   git clone http://github.com/Unidata/netcdf-c netcdf-c
+   pushd netcdf-c
+   autoreconf -i
+else
+   wget ftp://ftp.unidata.ucar.edu/pub/netcdf/netcdf-c-${NETCDF_VERSION}.tar.gz
+   tar -xzvf netcdf-c-${NETCDF_VERSION}.tar.gz
+   pushd netcdf-c-${NETCDF_VERSION}
+fi
 ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap  --enable-parallel
 make -j 2
 make install

From 6175a090484b938fd4687e7e429c392eb08fb1be Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 26 Feb 2019 09:20:43 -0700
Subject: [PATCH 0243/1504] try using xenial

---
 .travis.yml                        | 22 +++++++++++++++++++---
 ci/travis/build-parallel-netcdf.sh |  5 ++++-
 2 files changed, 23 insertions(+), 4 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index 03a7317f2..457114457 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -29,10 +29,26 @@ matrix:
     - python: 2.7
       env:
         - DEPENDS="numpy==1.9.0 cython==0.21 ordereddict==1.1 setuptools==18.0 cftime"
-    # test MPI
-    - python: 3.6
-      dist: trusty
+    # test MPI with latest released version
+    - python: 3.7
+      dist: xenial
       env: 
+        - MPI=1
+        - CC=mpicc
+        - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
+        - NETCDF_VERSION=4.6.2
+        - NETCDF_DIR=$HOME
+        - PATH=${NETCDF_DIR}/bin:${PATH} # pick up nc-config here
+      addons:
+        apt:
+          packages:
+            - openmpi-bin
+            - libopenmpi-dev
+            - libhdf5-openmpi-dev
+    # test with netcdf-c from github master
+    - python: 3.7
+      dist: xenial
+      env:
         - MPI=1
         - CC=mpicc
         - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
diff --git a/ci/travis/build-parallel-netcdf.sh b/ci/travis/build-parallel-netcdf.sh
index cf7e3c84c..fad652370 100755
--- a/ci/travis/build-parallel-netcdf.sh
+++ b/ci/travis/build-parallel-netcdf.sh
@@ -13,7 +13,10 @@ else
    tar -xzvf netcdf-c-${NETCDF_VERSION}.tar.gz
    pushd netcdf-c-${NETCDF_VERSION}
 fi
-./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap  --enable-parallel
+# for Ubuntu xenial
+export CPPFLAGS="-I/usr/include/hdf5/openmpi"
+export LIBS="-lhdf5_openmpihl -lhdf5_openmpi -lm -lz"
+./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap --enable-parallel
 make -j 2
 make install
 popd

From db479de44bbc8b76c2267415ce3200344d35efba Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 26 Feb 2019 10:03:16 -0700
Subject: [PATCH 0244/1504] mpicc is mpicc.openmpi in xenial

---
 .travis.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index 457114457..48e9c2dc7 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -34,7 +34,7 @@ matrix:
       dist: xenial
       env: 
         - MPI=1
-        - CC=mpicc
+        - CC=mpicc.openmpi
         - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
         - NETCDF_VERSION=4.6.2
         - NETCDF_DIR=$HOME
@@ -50,7 +50,7 @@ matrix:
       dist: xenial
       env:
         - MPI=1
-        - CC=mpicc
+        - CC=mpicc.openmpi
         - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
         - NETCDF_VERSION=GITMASTER
         - NETCDF_DIR=$HOME

From dc067ce97fa667eed47d0c871259e8668b5d3c7f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 26 Feb 2019 10:27:18 -0700
Subject: [PATCH 0245/1504] revert to trusty

---
 .travis.yml                        | 12 ++++++------
 ci/travis/build-parallel-netcdf.sh |  4 ++--
 2 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index 48e9c2dc7..efef395e7 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -30,11 +30,11 @@ matrix:
       env:
         - DEPENDS="numpy==1.9.0 cython==0.21 ordereddict==1.1 setuptools==18.0 cftime"
     # test MPI with latest released version
-    - python: 3.7
-      dist: xenial
+    - python: 3.6
+      dist: trusty
       env: 
         - MPI=1
-        - CC=mpicc.openmpi
+        - CC=mpicc
         - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
         - NETCDF_VERSION=4.6.2
         - NETCDF_DIR=$HOME
@@ -46,11 +46,11 @@ matrix:
             - libopenmpi-dev
             - libhdf5-openmpi-dev
     # test with netcdf-c from github master
-    - python: 3.7
-      dist: xenial
+    - python: 3.6
+      dist: trusty
       env:
         - MPI=1
-        - CC=mpicc.openmpi
+        - CC=mpicc
         - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
         - NETCDF_VERSION=GITMASTER
         - NETCDF_DIR=$HOME
diff --git a/ci/travis/build-parallel-netcdf.sh b/ci/travis/build-parallel-netcdf.sh
index fad652370..dfcea0121 100755
--- a/ci/travis/build-parallel-netcdf.sh
+++ b/ci/travis/build-parallel-netcdf.sh
@@ -14,8 +14,8 @@ else
    pushd netcdf-c-${NETCDF_VERSION}
 fi
 # for Ubuntu xenial
-export CPPFLAGS="-I/usr/include/hdf5/openmpi"
-export LIBS="-lhdf5_openmpihl -lhdf5_openmpi -lm -lz"
+#export CPPFLAGS="-I/usr/include/hdf5/openmpi"
+#export LIBS="-lhdf5_openmpihl -lhdf5_openmpi -lm -lz"
 ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap --enable-parallel
 make -j 2
 make install

From 3c5576f0421b260a7fa6e354dca81779e6678765 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 26 Feb 2019 11:25:17 -0700
Subject: [PATCH 0246/1504] try to get xenial parallel openmpi env to work

---
 .travis.yml                        | 14 +++++++-------
 ci/travis/build-parallel-netcdf.sh |  5 +++--
 2 files changed, 10 insertions(+), 9 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index efef395e7..a5946bcdb 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -30,11 +30,11 @@ matrix:
       env:
         - DEPENDS="numpy==1.9.0 cython==0.21 ordereddict==1.1 setuptools==18.0 cftime"
     # test MPI with latest released version
-    - python: 3.6
-      dist: trusty
+    - python: 3.7
+      dist: xenial
       env: 
         - MPI=1
-        - CC=mpicc
+        - CC=mpicc.openmpi
         - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
         - NETCDF_VERSION=4.6.2
         - NETCDF_DIR=$HOME
@@ -46,11 +46,11 @@ matrix:
             - libopenmpi-dev
             - libhdf5-openmpi-dev
     # test with netcdf-c from github master
-    - python: 3.6
-      dist: trusty
+    - python: 3.7
+      dist: xenial
       env:
         - MPI=1
-        - CC=mpicc
+        - CC=mpicc.openmpi
         - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
         - NETCDF_VERSION=GITMASTER
         - NETCDF_DIR=$HOME
@@ -80,7 +80,7 @@ script:
   - |
     if [ $MPI -eq 1 ] ; then
        cd ../examples
-       mpirun -np 4 python mpi_example.py
+       mpirun.openmpi -np 4 python mpi_example.py
        if [ $? -ne 0 ] ; then
          echo "mpi test failed!"
          exit 1
diff --git a/ci/travis/build-parallel-netcdf.sh b/ci/travis/build-parallel-netcdf.sh
index dfcea0121..159fd3c83 100755
--- a/ci/travis/build-parallel-netcdf.sh
+++ b/ci/travis/build-parallel-netcdf.sh
@@ -14,8 +14,9 @@ else
    pushd netcdf-c-${NETCDF_VERSION}
 fi
 # for Ubuntu xenial
-#export CPPFLAGS="-I/usr/include/hdf5/openmpi"
-#export LIBS="-lhdf5_openmpihl -lhdf5_openmpi -lm -lz"
+export CPPFLAGS="-I/usr/include/hdf5/openmpi"
+export LIBS="-lhdf5_openmpihl -lhdf5_openmpi -lm -lz"
+ls -l /usr/bin/mpi*
 ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap --enable-parallel
 make -j 2
 make install

From b15daeafa9776386d2d4e52c58ad921c980d24f1 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 26 Feb 2019 11:50:44 -0700
Subject: [PATCH 0247/1504] try mpich instead of openmpi

---
 .travis.yml                        | 18 +++++++++---------
 ci/travis/build-parallel-netcdf.sh |  6 +++---
 2 files changed, 12 insertions(+), 12 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index a5946bcdb..967e25a81 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -34,7 +34,7 @@ matrix:
       dist: xenial
       env: 
         - MPI=1
-        - CC=mpicc.openmpi
+        - CC=mpicc.mpich
         - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
         - NETCDF_VERSION=4.6.2
         - NETCDF_DIR=$HOME
@@ -42,15 +42,15 @@ matrix:
       addons:
         apt:
           packages:
-            - openmpi-bin
-            - libopenmpi-dev
-            - libhdf5-openmpi-dev
+            - mpich
+            - libmpich-dev
+            - libhdf5-mpich-dev
     # test with netcdf-c from github master
     - python: 3.7
       dist: xenial
       env:
         - MPI=1
-        - CC=mpicc.openmpi
+        - CC=mpicc.mpich
         - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
         - NETCDF_VERSION=GITMASTER
         - NETCDF_DIR=$HOME
@@ -58,9 +58,9 @@ matrix:
       addons:
         apt:
           packages:
-            - openmpi-bin
-            - libopenmpi-dev
-            - libhdf5-openmpi-dev
+            - mpich
+            - libmpich-dev
+            - libhdf5-mpich-dev
 
 notifications:
   email: false
@@ -80,7 +80,7 @@ script:
   - |
     if [ $MPI -eq 1 ] ; then
        cd ../examples
-       mpirun.openmpi -np 4 python mpi_example.py
+       mpirun.mpich -np 4 python mpi_example.py
        if [ $? -ne 0 ] ; then
          echo "mpi test failed!"
          exit 1
diff --git a/ci/travis/build-parallel-netcdf.sh b/ci/travis/build-parallel-netcdf.sh
index 159fd3c83..ec045d30e 100755
--- a/ci/travis/build-parallel-netcdf.sh
+++ b/ci/travis/build-parallel-netcdf.sh
@@ -10,12 +10,12 @@ if [ ${NETCDF_VERSION} == "GITMASTER" ]; then
    autoreconf -i
 else
    wget ftp://ftp.unidata.ucar.edu/pub/netcdf/netcdf-c-${NETCDF_VERSION}.tar.gz
-   tar -xzvf netcdf-c-${NETCDF_VERSION}.tar.gz
+   tar -xzf netcdf-c-${NETCDF_VERSION}.tar.gz
    pushd netcdf-c-${NETCDF_VERSION}
 fi
 # for Ubuntu xenial
-export CPPFLAGS="-I/usr/include/hdf5/openmpi"
-export LIBS="-lhdf5_openmpihl -lhdf5_openmpi -lm -lz"
+export CPPFLAGS="-I/usr/include/hdf5/mpich"
+export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
 ls -l /usr/bin/mpi*
 ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap --enable-parallel
 make -j 2

From 0b804a2cd674015e6e0b305a4745a2055803ab85 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 26 Feb 2019 12:06:05 -0700
Subject: [PATCH 0248/1504] remove debug ls

---
 ci/travis/build-parallel-netcdf.sh | 1 -
 1 file changed, 1 deletion(-)

diff --git a/ci/travis/build-parallel-netcdf.sh b/ci/travis/build-parallel-netcdf.sh
index ec045d30e..4035351fc 100755
--- a/ci/travis/build-parallel-netcdf.sh
+++ b/ci/travis/build-parallel-netcdf.sh
@@ -16,7 +16,6 @@ fi
 # for Ubuntu xenial
 export CPPFLAGS="-I/usr/include/hdf5/mpich"
 export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
-ls -l /usr/bin/mpi*
 ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap --enable-parallel
 make -j 2
 make install

From 8adf32f374b6cd564393d64e3a32535e32deecac Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 26 Feb 2019 12:15:43 -0700
Subject: [PATCH 0249/1504] allow netcdf-c master test to fail

---
 .travis.yml | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/.travis.yml b/.travis.yml
index 967e25a81..c5c81d4a4 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -24,6 +24,14 @@ python:
 matrix:
   allow_failures:
     - python: "3.8-dev"
+    - python: 3.7
+      env:
+        - MPI=1
+        - CC=mpicc.mpich
+        - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
+        - NETCDF_VERSION=GITMASTER
+        - NETCDF_DIR=$HOME
+        - PATH=${NETCDF_DIR}/bin:${PATH} # pick up nc-config here
   include:
     # Absolute minimum dependencies.
     - python: 2.7

From 0589132306c9246d404d4ed68c43016f54651d9e Mon Sep 17 00:00:00 2001
From: Christian Marquardt 
Date: Tue, 26 Feb 2019 22:44:51 +0100
Subject: [PATCH 0250/1504] Moved tests for using NC_STRINGs into tst_atts.py;
 fixed a regression along the way.

---
 netCDF4/_netCDF4.pyx   |  32 +++----
 test/tst_atts.py       |  15 +++
 test/tst_atts_ncstr.py | 211 -----------------------------------------
 3 files changed, 30 insertions(+), 228 deletions(-)
 delete mode 100644 test/tst_atts_ncstr.py

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index c3891eee6..80f4ce9e1 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1846,7 +1846,7 @@ _private_atts = \
  '_nunlimdim','path','parent','ndim','mask','scale','cmptypes','vltypes','enumtypes','_isprimitive',
  'file_format','_isvlen','_isenum','_iscompound','_cmptype','_vltype','_enumtype','name',
  '__orthogoral_indexing__','keepweakref','_has_lsd',
- '_buffer','chartostring','_use_get_vars','ncstring_attrs']
+ '_buffer','chartostring','_use_get_vars','_ncstring_attrs__']
 __pdoc__ = {}
 
 cdef class Dataset:
@@ -1916,7 +1916,7 @@ group, so the path is simply `'/'`.
 **`keepweakref`**: If `True`, child Dimension and Variables objects only keep weak
 references to the parent Dataset or Group.
 
-**`ncstring_attrs`**: If `True`, all text attributes will be written as variable-length
+**`_ncstring_attrs__`**: If `True`, all text attributes will be written as variable-length
 strings.
     """
     cdef object __weakref__, _inmemory
@@ -1925,7 +1925,7 @@ strings.
     cdef Py_buffer _buffer
     cdef public groups, dimensions, variables, disk_format, path, parent,\
     file_format, data_model, cmptypes, vltypes, enumtypes,  __orthogonal_indexing__, \
-    keepweakref, ncstring_attrs
+    keepweakref, _ncstring_attrs__
     # Docstrings for class variables (used by pdoc).
     __pdoc__['Dataset.dimensions']=\
     """The `dimensions` dictionary maps the names of
@@ -2047,7 +2047,7 @@ strings.
         desirable, since the associated Variable instances may still be needed, but are
         rendered unusable when the parent Dataset instance is garbage collected.
 
-        **`ncstring_attrs`**: if `ncstring_attrs=True`, all string attributes will use
+        **`_ncstring_attrs__`**: if `_ncstring_attrs__=True`, all string attributes will use
         the variable length NC_STRING attributes (default `False`, ascii text
         attributes written as NC_CHAR).
 
@@ -2271,7 +2271,7 @@ strings.
         self.path = '/'
         self.parent = None
         self.keepweakref = keepweakref
-        self.ncstring_attrs = False
+        self._ncstring_attrs__ = False
         # get compound, vlen and enum types in the root Group.
         self.cmptypes, self.vltypes, self.enumtypes = _get_types(self)
         # get dimensions in the root group.
@@ -2775,7 +2775,7 @@ with the same name as one of the reserved python attributes."""
         cdef nc_type xtype
         xtype=-99
         if self.data_model != 'NETCDF4': self._redef()
-        _set_att(self, NC_GLOBAL, name, value, xtype=xtype, force_ncstring=self.ncstring_attrs)
+        _set_att(self, NC_GLOBAL, name, value, xtype=xtype, force_ncstring=self._ncstring_attrs__)
         if self.data_model !=  'NETCDF4': self._enddef()
 
     def setncattr_string(self,name,value):
@@ -3060,7 +3060,7 @@ attributes are stored as NC_CHARs (if False; default)
 of existing (sub-) groups and their variables.
         """
 
-        self.ncstring_attrs = bool(value)
+        self._ncstring_attrs__ = bool(value)
 
         # this is a hack to make inheritance work in MFDataset
         # (which stores variables in _vars)
@@ -3072,9 +3072,7 @@ of existing (sub-) groups and their variables.
 
         for groups in _walk_grps(self):
             for group in groups:
-                group.ncstring_attrs = bool(value) # do not recurse into subgroups...
-                for var in group.variables.values():
-                    var.set_ncstring_attrs(value)
+                group.set_ncstring_attrs(value) # recurse into subgroups...
 
     def get_variables_by_attributes(self, **kwargs):
         """
@@ -3175,8 +3173,8 @@ Additional read-only class variables:
         self.parent = parent
         # propagate weak reference setting from parent.
         self.keepweakref = parent.keepweakref
-        # propagate ncstring_attrs setting from parent.
-        self.ncstring_attrs = parent.ncstring_attrs
+        # propagate _ncstring_attrs__ setting from parent.
+        self._ncstring_attrs__ = parent._ncstring_attrs__
         if 'id' in kwargs:
             self._grpid = kwargs['id']
             # get compound, vlen and enum types in this Group.
@@ -3440,7 +3438,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
     cdef public int _varid, _grpid, _nunlimdim
     cdef public _name, ndim, dtype, mask, scale, always_mask, chartostring,  _isprimitive, \
     _iscompound, _isvlen, _isenum, _grp, _cmptype, _vltype, _enumtype,\
-    __orthogonal_indexing__, _has_lsd, _use_get_vars, ncstring_attrs
+    __orthogonal_indexing__, _has_lsd, _use_get_vars, _ncstring_attrs__
     # Docstrings for class variables (used by pdoc).
     __pdoc__['Variable.dimensions'] = \
     """A tuple containing the names of the
@@ -3844,8 +3842,8 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         # default is to automatically convert to/from character
         # to string arrays when _Encoding variable attribute is set.
         self.chartostring = True
-        # propagate ncstring_attrs setting from parent group.
-        self.ncstring_attrs = grp.ncstring_attrs
+        # propagate _ncstring_attrs__ setting from parent group.
+        self._ncstring_attrs__ = grp._ncstring_attrs__
         if 'least_significant_digit' in self.ncattrs():
             self._has_lsd = True
         # avoid calling nc_get_vars for strided slices by default.
@@ -4031,7 +4029,7 @@ attributes."""
         cdef nc_type xtype
         xtype=-99
         if self._grp.data_model != 'NETCDF4': self._grp._redef()
-        _set_att(self._grp, self._varid, name, value, xtype=xtype, force_ncstring=self.ncstring_attrs)
+        _set_att(self._grp, self._varid, name, value, xtype=xtype, force_ncstring=self._ncstring_attrs__)
         if self._grp.data_model != 'NETCDF4': self._grp._enddef()
 
     def setncattr_string(self,name,value):
@@ -5050,7 +5048,7 @@ The default value of `ncstring_attrs` is `False` (writing ascii text attributes
 NC_CHAR).
 
         """
-        self.ncstring_attrs = bool(ncstring_attrs)
+        self._ncstring_attrs__ = bool(ncstring_attrs)
 
     def _put(self,ndarray data,start,count,stride):
         """Private method to put data into a netCDF variable"""
diff --git a/test/tst_atts.py b/test/tst_atts.py
index 4345f038c..5b7f6d0c4 100644
--- a/test/tst_atts.py
+++ b/test/tst_atts.py
@@ -106,10 +106,23 @@ def setUp(self):
         f.cafe = u'caf\xe9' # NC_STRING
         f.batt = u'caf\xe9'.encode('utf-8') #NC_CHAR
         v.setncattr_string('stringatt','bar') # NC_STRING
+        # issue #882 - provide an option to always string attribute
+        # as NC_STRINGs. Testing various approaches to setting text attributes...
+        f.set_ncstring_attrs(True)
+        f.stringatt_ncstr = u'foo' # will now be written as NC_STRING
+        f.setncattr_string('stringatt_ncstr','bar') # NC_STRING anyway
+        f.caf_ncstr = u'caf\xe9' # NC_STRING anyway
+        f.bat_ncstr = u'caf\xe9'.encode('utf-8') # now NC_STRING
+        g.stratt_ncstr = STRATT # now NC_STRING
+        #g.renameAttribute('stratt_tmp','stratt_ncstr')
+        v.setncattr_string('stringatt_ncstr','bar') # NC_STRING anyway
+        v.stratt_ncstr = STRATT
+        v1.emptystratt_ncstr = EMPTYSTRATT
         f.close()
 
     def tearDown(self):
         # Remove the temporary files
+        #pass
         os.remove(self.file)
 
     def runTest(self):
@@ -170,10 +183,12 @@ def runTest(self):
                 ncdump_output = str(dep,encoding='utf-8').split('\n')
             for line in ncdump_output:
                 line = line.strip('\t\n\r')
+                line = line.strip()# Must be done another time for group variables
                 if "stringatt" in line: assert line.startswith('string')
                 if "charatt" in line: assert line.startswith(':')
                 if "cafe" in line: assert line.startswith('string')
                 if "batt" in line: assert line.startswith(':')
+                if "_ncstr" in line: assert line.startswith('string')
         # check attributes in subgroup.
         # global attributes.
         for key,val in ATTDICT.items():
diff --git a/test/tst_atts_ncstr.py b/test/tst_atts_ncstr.py
deleted file mode 100644
index 5b00d60ef..000000000
--- a/test/tst_atts_ncstr.py
+++ /dev/null
@@ -1,211 +0,0 @@
-import math
-import subprocess
-import sys
-import unittest
-import os
-import tempfile
-import warnings
-
-import numpy as NP
-from numpy.random.mtrand import uniform
-import netCDF4
-
-try:
-    from collections import OrderedDict
-except ImportError: # or else use drop-in substitute
-    from ordereddict import OrderedDict
-
-# test attribute creation.
-FILE_NAME = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
-VAR_NAME="dummy_var"
-GROUP_NAME = "dummy_group"
-DIM1_NAME="x"
-DIM1_LEN=2
-DIM2_NAME="y"
-DIM2_LEN=3
-DIM3_NAME="z"
-DIM3_LEN=25
-STRATT = 'string attribute'
-EMPTYSTRATT = ''
-INTATT = 1
-FLOATATT = math.pi
-SEQATT = NP.arange(10)
-STRINGSEQATT = ['mary ','','had ','a ','little ','lamb',]
-#ATTDICT = {'stratt':STRATT,'floatatt':FLOATATT,'seqatt':SEQATT,
-#           'stringseqatt':''.join(STRINGSEQATT), # changed in issue #770
-#           'emptystratt':EMPTYSTRATT,'intatt':INTATT}
-ATTDICT = {'stratt':STRATT,'floatatt':FLOATATT,'seqatt':SEQATT,
-           'stringseqatt':STRINGSEQATT,
-           'emptystratt':EMPTYSTRATT,'intatt':INTATT}
-
-class VariablesTestCase(unittest.TestCase):
-
-    def setUp(self):
-        self.file = FILE_NAME
-        f = netCDF4.Dataset(self.file,'w')
-        # make sure text attributes are always NC_STRINGs
-        f.set_ncstring_attrs(True)
-        # try to set a dataset attribute with one of the reserved names.
-        f.setncattr('file_format','netcdf4_format')
-        # test attribute renameing
-        f.stratt_tmp = STRATT
-        f.renameAttribute('stratt_tmp','stratt')
-        f.emptystratt = EMPTYSTRATT
-        f.intatt = INTATT
-        f.floatatt = FLOATATT
-        f.seqatt = SEQATT
-        # sequences of strings converted to a single string.
-        f.stringseqatt = STRINGSEQATT
-        f.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
-        g = f.createGroup(GROUP_NAME)
-        f.createDimension(DIM1_NAME, DIM1_LEN)
-        f.createDimension(DIM2_NAME, DIM2_LEN)
-        f.createDimension(DIM3_NAME, DIM3_LEN)
-        g.createDimension(DIM1_NAME, DIM1_LEN)
-        g.createDimension(DIM2_NAME, DIM2_LEN)
-        g.createDimension(DIM3_NAME, DIM3_LEN)
-        g.stratt_tmp = STRATT
-        g.renameAttribute('stratt_tmp','stratt')
-        g.emptystratt = EMPTYSTRATT
-        g.intatt = INTATT
-        g.floatatt = FLOATATT
-        g.seqatt = SEQATT
-        g.stringseqatt = STRINGSEQATT
-        if netCDF4.__version__ > "1.4.2":
-            with self.assertRaises(ValueError):
-                g.arrayatt = [[1, 2], [3, 4]] # issue #841
-        g.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
-        v = f.createVariable(VAR_NAME, 'f8',(DIM1_NAME,DIM2_NAME,DIM3_NAME))
-        # try to set a variable attribute with one of the reserved names.
-        v.setncattr('ndim','three')
-        v.setncatts({'foo': 1})
-        v.setncatts(OrderedDict(bar=2))
-        v.stratt_tmp = STRATT
-        v.renameAttribute('stratt_tmp','stratt')
-        v.emptystratt = EMPTYSTRATT
-        v.intatt = INTATT
-        v.floatatt = FLOATATT
-        v.seqatt = SEQATT
-        v.stringseqatt = STRINGSEQATT
-        v.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
-        v1 = g.createVariable(VAR_NAME, 'f8',(DIM1_NAME,DIM2_NAME,DIM3_NAME))
-        v1.stratt = STRATT
-        v1.emptystratt = EMPTYSTRATT
-        v1.intatt = INTATT
-        v1.floatatt = FLOATATT
-        v1.seqatt = SEQATT
-        v1.stringseqatt = STRINGSEQATT
-        v1.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
-        # issue #485 (triggers segfault in C lib
-        # with version 1.2.1 without pull request #486)
-        f.foo = NP.array('bar','S')
-        f.foo = NP.array('bar','U')
-        # issue #529 write string attribute as NC_CHAR unless
-        # it can't be decoded to ascii.  Add setncattr_string
-        # method to force NC_STRING.
-        f.charatt = u'foo' # will be written as NC_CHAR
-        f.setncattr_string('stringatt','bar') # NC_STRING
-        f.cafe = u'caf\xe9' # NC_STRING
-        f.batt = u'caf\xe9'.encode('utf-8') #NC_CHAR
-        v.setncattr_string('stringatt','bar') # NC_STRING
-        f.close()
-
-    def tearDown(self):
-        # Remove the temporary files
-        os.remove(self.file)
-
-    def runTest(self):
-        """testing attributes"""
-        f  = netCDF4.Dataset(self.file, 'r')
-        v = f.variables[VAR_NAME]
-        g = f.groups[GROUP_NAME]
-        v1 = g.variables[VAR_NAME]
-        # check attributes in root group.
-        # global attributes.
-        # check __dict__ method for accessing all netCDF attributes.
-        for key,val in ATTDICT.items():
-            if type(val) == NP.ndarray:
-                assert f.__dict__[key].tolist() == val.tolist()
-            else:
-                assert f.__dict__[key] == val
-        # check accessing individual attributes.
-        assert f.intatt == INTATT
-        assert f.floatatt == FLOATATT
-        assert f.stratt == STRATT
-        assert f.emptystratt == EMPTYSTRATT
-        assert f.seqatt.tolist() == SEQATT.tolist()
-        #assert f.stringseqatt == ''.join(STRINGSEQATT) # issue 770
-        assert f.stringseqatt == STRINGSEQATT
-        assert f.stringseqatt_array == STRINGSEQATT
-        assert f.getncattr('file_format') == 'netcdf4_format'
-        # variable attributes.
-        # check __dict__ method for accessing all netCDF attributes.
-        for key,val in ATTDICT.items():
-            if type(val) == NP.ndarray:
-                assert v.__dict__[key].tolist() == val.tolist()
-            else:
-                assert v.__dict__[key] == val
-        # check accessing individual attributes.
-        assert v.intatt == INTATT
-        assert v.floatatt == FLOATATT
-        assert v.stratt == STRATT
-        assert v.seqatt.tolist() == SEQATT.tolist()
-        #assert v.stringseqatt == ''.join(STRINGSEQATT) # issue 770
-        assert v.stringseqatt == STRINGSEQATT
-        assert v.stringseqatt_array == STRINGSEQATT
-        assert v.getncattr('ndim') == 'three'
-        assert v.getncattr('foo') == 1
-        assert v.getncattr('bar') == 2
-        # check type of attributes using ncdump (issue #529)
-        try:  # ncdump may not be on the system PATH
-            nc_proc = subprocess.Popen(
-                ['ncdump', '-h', FILE_NAME], stdout=subprocess.PIPE)
-        except OSError:
-            warnings.warn('"ncdump" not on system path; cannot test '
-                          'read of some attributes')
-            pass
-        else:  # We do have ncdump output
-            dep = nc_proc.communicate()[0]
-            try: # python 2
-                ncdump_output = dep.split('\n')
-            except TypeError: # python 3
-                ncdump_output = str(dep,encoding='utf-8').split('\n')
-            for line in ncdump_output:
-                line = line.strip('\t\n\r')
-                if "stringatt" in line: assert line.startswith('string')
-                if "charatt" in line: assert line.startswith('string')
-                if "cafe" in line: assert line.startswith('string')
-                if "batt" in line: assert line.startswith('string')
-        # check attributes in subgroup.
-        # global attributes.
-        for key,val in ATTDICT.items():
-            if type(val) == NP.ndarray:
-                assert g.__dict__[key].tolist() == val.tolist()
-            else:
-                assert g.__dict__[key] == val
-        assert g.intatt == INTATT
-        assert g.floatatt == FLOATATT
-        assert g.stratt == STRATT
-        assert g.emptystratt == EMPTYSTRATT
-        assert g.seqatt.tolist() == SEQATT.tolist()
-        #assert g.stringseqatt == ''.join(STRINGSEQATT) # issue 770
-        assert g.stringseqatt == STRINGSEQATT
-        assert g.stringseqatt_array == STRINGSEQATT
-        for key,val in ATTDICT.items():
-            if type(val) == NP.ndarray:
-                assert v1.__dict__[key].tolist() == val.tolist()
-            else:
-                assert v1.__dict__[key] == val
-        assert v1.intatt == INTATT
-        assert v1.floatatt == FLOATATT
-        assert v1.stratt == STRATT
-        assert v1.emptystratt == EMPTYSTRATT
-        assert v1.seqatt.tolist() == SEQATT.tolist()
-        #assert v1.stringseqatt == ''.join(STRINGSEQATT) # issue 770
-        assert v1.stringseqatt == STRINGSEQATT
-        assert v1.stringseqatt_array == STRINGSEQATT
-        assert getattr(v1,'nonexistantatt',None) == None
-        f.close()
-
-if __name__ == '__main__':
-    unittest.main()

From 182d14743e040dde46c94acae6758bacfea29e77 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 2 Mar 2019 12:18:45 -0700
Subject: [PATCH 0251/1504] update docs

---
 docs/netCDF4/index.html | 232 +++++++++++++++++++++++++++++-----------
 1 file changed, 167 insertions(+), 65 deletions(-)

diff --git a/docs/netCDF4/index.html b/docs/netCDF4/index.html
index 147ab5b48..5f3d546d6 100644
--- a/docs/netCDF4/index.html
+++ b/docs/netCDF4/index.html
@@ -6,12 +6,12 @@
     netCDF4 API documentation
     
+netcdf4-python is a Python interface t..." />
 
   
   
@@ -1103,6 +1103,7 @@ 
      Index
      
     
    • set_auto_scale
      • 
     
    • set_fill_off
      • 
     
    • set_fill_on
      • 
+    
    • set_ncstring_attrs
      • 
     
    • setncattr
      • 
     
    • setncattr_string
      • 
     
    • setncatts
      • 
@@ -1160,6 +1161,7 @@ 
      Index
      
     
    • set_auto_scale
      • 
     
    • set_fill_off
      • 
     
    • set_fill_on
      • 
+    
    • set_ncstring_attrs
      • 
     
    • setncattr
      • 
     
    • setncattr_string
      • 
     
    • setncatts
      • 
@@ -1194,6 +1196,7 @@ 
      Index
      
     
    • set_auto_scale
      • 
     
    • set_fill_off
      • 
     
    • set_fill_on
      • 
+    
    • set_ncstring_attrs
      • 
     
    • setncattr
      • 
     
    • setncattr_string
      • 
     
    • setncatts
      • 
@@ -1253,6 +1256,7 @@ 
      Index
      
     
    • set_auto_maskandscale
      • 
     
    • set_auto_scale
      • 
     
    • set_collective
      • 
+    
    • set_ncstring_attrs
      • 
     
    • set_var_chunk_cache
      • 
     
    • setncattr
      • 
     
    • setncattr_string
      • 
@@ -1279,7 +1283,7 @@ 
      netCDF4 module
      
   
      Version 1.4.3
      
 
      
 
      Introduction
      
-
      netcdf4-python is a Python interface to the netCDF C library.  
      
+
      netcdf4-python is a Python interface to the netCDF C library.
      
 
      netCDF version 4 has many features
 not found in earlier versions of the library and is implemented on top of
 HDF5. This module can read and write
@@ -1297,7 +1301,7 @@ 
      Introduction
      
 types) are not supported.
      
 
      Download
      
 
        
-
      • Latest bleeding-edge code from the 
+
      • Latest bleeding-edge code from the
    github repository.
        • 
 
      • Latest releases
    (source code and binary installers).
        • 
@@ -1309,7 +1313,7 @@ 
        Requires
        
 
      • Cython, version 0.21 or later.
        • 
 
      • setuptools, version 18.0 or
    later.
        • 
-
      • cftime for 
+
      • cftime for
  the time and date handling utility functions (num2date,
  date2num and date2index).
        • 
 
      • The HDF5 C library version 1.8.4-patch1 or higher (1.8.x recommended)
@@ -1323,7 +1327,7 @@ 
        Requires
        
 
      • HDF4, if you want
  to be able to read HDF4 "Scientific Dataset" (SD) files.
        • 
 
      • The netCDF-4 C library from the github releases
-   page. 
+   page.
  Version 4.1.1 or higher is required (4.2 or higher recommended).
  Be sure to build with --enable-netcdf-4 --enable-shared, and set
  CPPFLAGS="-I $HDF5_DIR/include" and LDFLAGS="-L $HDF5_DIR/lib",
@@ -1386,11 +1390,11 @@ 
        1) Creating/Opening/Closing a netCDF file.
        
 file.  If the file is open for write access (mode='w', 'r+' or 'a'), you may
 write any type of data including new dimensions, groups, variables and
 attributes.  netCDF files come in five flavors (NETCDF3_CLASSIC,
-NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF4_CLASSIC, and NETCDF4). 
-NETCDF3_CLASSIC was the original netcdf binary format, and was limited 
+NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF4_CLASSIC, and NETCDF4).
+NETCDF3_CLASSIC was the original netcdf binary format, and was limited
 to file sizes less than 2 Gb. NETCDF3_64BIT_OFFSET was introduced
 in version 3.6.0 of the library, and extended the original binary format
-to allow for file sizes greater than 2 Gb. 
+to allow for file sizes greater than 2 Gb.
 NETCDF3_64BIT_DATA is a new format that requires version 4.4.0 of
 the C library - it extends the NETCDF3_64BIT_OFFSET binary format to
 allow for unsigned/64 bit integer data types and 64-bit dimension sizes.
@@ -1439,9 +1443,9 @@ 
        2) Groups in a netCDF file.
        
 >>> fcstgrp = rootgrp.createGroup("forecasts")
 >>> analgrp = rootgrp.createGroup("analyses")
 >>> print rootgrp.groups
-OrderedDict([("forecasts", 
+OrderedDict([("forecasts",
               <netCDF4._netCDF4.Group object at 0x1b4b7b0>),
-             ("analyses", 
+             ("analyses",
               <netCDF4._netCDF4.Group object at 0x1b4b970>)])
 
      
 
@@ -1460,7 +1464,7 @@ 
      2) Groups in a netCDF file.
      
 
 
      If any of the intermediate elements of the path do not exist, they are created,
 just as with the unix command 'mkdir -p'. If you try to create a group
-that already exists, no error will be raised, and the existing group will be 
+that already exists, no error will be raised, and the existing group will be
 returned.
      
 
      Here's an example that shows how to navigate all the groups in a
 Dataset. The function walktree is a Python generator that is used
@@ -1618,7 +1622,7 @@ 
      4) Variables in a netCDF file.
      
 
 
 
      If the intermediate groups do not yet exist, they will be created.
      
-
      You can also query a Dataset or Group instance directly to obtain Group or 
+
      You can also query a Dataset or Group instance directly to obtain Group or
 Variable instances using paths.
      
 
      >>> print rootgrp["/forecasts/model1"] # a Group instance
 <type "netCDF4._netCDF4.Group">
@@ -1803,7 +1807,7 @@ 
      7) Dealing with time coordinates.
      
 specified like hours since YY-MM-DD hh:mm:ss.  These units can be
 awkward to deal with, without a utility to convert the values to and
 from calendar dates.  The function called num2date and date2num are
-provided with this package to do just that (starting with version 1.4.0, the 
+provided with this package to do just that (starting with version 1.4.0, the
 cftime package must be installed
 separately).  Here's an example of how they
 can be used:
      
@@ -1963,7 +1967,7 @@ 
      10) Beyond homogeneous arrays of a fixed type - compound
 ones first. All possible numpy structured arrays cannot be
 represented as Compound variables - an error message will be
 raise if you try to create one that is not supported.
-All of the compound types defined for a Dataset or Group are stored 
+All of the compound types defined for a Dataset or Group are stored
 in a Python dictionary, just like variables and dimensions. As always, printing
 objects gives useful summary information in an interactive session:
      
 
      >>> print f
@@ -2087,13 +2091,13 @@ 
      12) Enum data type.
      
 
      netCDF4 has an enumerated data type, which is an integer datatype that is
 restricted to certain named values. Since Enums don't map directly to
 a numpy data type, they are read and written as integer arrays.
      
-
      Here's an example of using an Enum type to hold cloud type data. 
+
      Here's an example of using an Enum type to hold cloud type data.
 The base integer data type and a python dictionary describing the allowed
 values and their names are used to define an Enum data type using
 createEnumType.
      
 
      >>> nc = Dataset('clouds.nc','w')
 >>> # python dict with allowed values and their names.
->>> enum_dict = {u'Altocumulus': 7, u'Missing': 255, 
+>>> enum_dict = {u'Altocumulus': 7, u'Missing': 255,
 >>> u'Stratus': 2, u'Clear': 0,
 >>> u'Nimbostratus': 6, u'Cumulus': 4, u'Altostratus': 5,
 >>> u'Cumulonimbus': 1, u'Stratocumulus': 3}
@@ -2150,7 +2154,7 @@ 
      13) Parallel IO.
      
 
      If MPI parallel enabled versions of netcdf and hdf5 are detected, and
 mpi4py is installed, netcdf4-python will
 be built with parallel IO capabilities enabled.  To use parallel IO,
-your program must be running in an MPI environment using 
+your program must be running in an MPI environment using
 mpi4py.
      
 
      >>> from mpi4py import MPI
 >>> import numpy as np
@@ -2205,10 +2209,10 @@ 
      13) Parallel IO.
      
    a generic "HDF Error".
 
    • You cannot write compressed data in parallel (although
    you can read it).
      • 
-
    • You cannot use variable-length (VLEN) data types. 
      • 
+
    • You cannot use variable-length (VLEN) data types.
      • 
 
    
 
    14) Dealing with strings.
    
-
    The most flexible way to store arrays of strings is with the 
+
    The most flexible way to store arrays of strings is with the
 Variable-length (vlen) string data type. However, this requires
 the use of the NETCDF4 data model, and the vlen type does not map very well
 numpy arrays (you have to use numpy arrays of dtype=object, which are arrays of
@@ -2247,7 +2251,7 @@ 
    14) Dealing with strings.
    
 
 
    Even if the _Encoding attribute is set, the automatic conversion of char
 arrays to/from string arrays can be disabled with
-set_auto_chartostring. 
    
+set_auto_chartostring.
    
 
    A similar situation is often encountered with numpy structured arrays with subdtypes
 containing fixed-wdith byte strings (dtype=S#). Since there is no native fixed-length string
 netCDF datatype, these numpy structure arrays are mapped onto netCDF compound
@@ -2285,7 +2289,7 @@ 
    14) Dealing with strings.
    
 
 
 
    Note that there is currently no support for mapping numpy structured arrays with
-unicode elements (dtype U#) onto netCDF compound types, nor is there support 
+unicode elements (dtype U#) onto netCDF compound types, nor is there support
 for netCDF compound types with vlen string components.
    
 
    15) In-memory (diskless) Datasets.
    
 
    You can create netCDF Datasets whose content is held in memory
@@ -2302,7 +2306,7 @@ 
    15) In-memory (diskless) Datasets.
    
 mode='w'.  Then, the Dataset.close method will return a python memoryview
 object representing the Dataset. Below are examples illustrating both
 approaches.
    
-
    >>> # create a diskless (in-memory) Dataset, 
+
    >>> # create a diskless (in-memory) Dataset,
 >>> # and persist the file to disk when it is closed.
 >>> nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
 >>> d = nc.createDimension('x',None)
@@ -2336,7 +2340,7 @@ 
    15) In-memory (diskless) Datasets.
    
 >>> nc.close()
 >>> # create an in-memory Dataset and retrieve memory buffer
 >>> # estimated size is 1028 bytes - this is actually only
->>> # used if format is NETCDF3 
+>>> # used if format is NETCDF3
 >>> # (ignored for NETCDF4/HDF5 files).
 >>> nc = Dataset('inmemory.nc', mode='w',memory=1028)
 >>> d = nc.createDimension('x',None)
@@ -2596,7 +2600,7 @@ 
    Classes
    
   
     
    A CompoundType instance is used to describe a compound data
 type, and can be passed to the the createVariable method of
-a Dataset or Group instance. 
+a Dataset or Group instance.
 Compound data types map to numpy structured arrays.
 See __init__ for more details.
    
 
    The instance variables dtype and name should not be modified by
@@ -2697,7 +2701,7 @@ 
    Static methods
    
 dimensions defined for the Group or Dataset to instances of the
 Dimension class.
    
 
    variables: The variables dictionary maps the names of variables
-defined for this Dataset or Group to instances of the 
+defined for this Dataset or Group to instances of the
 Variable class.
    
 
    groups: The groups dictionary maps the names of groups created for
 this Dataset or Group to instances of the Group class (the
@@ -2707,10 +2711,10 @@ 
    Static methods
    
 compound types defined for the Group or Dataset to instances of the
 CompoundType class.
    
 
    vltypes: The vltypes dictionary maps the names of
-variable-length types defined for the Group or Dataset to instances 
+variable-length types defined for the Group or Dataset to instances
 of the VLType class.
    
 
    enumtypes: The enumtypes dictionary maps the names of
-Enum types defined for the Group or Dataset to instances 
+Enum types defined for the Group or Dataset to instances
 of the EnumType class.
    
 
    data_model: data_model describes the netCDF
 data model version, one of NETCDF3_CLASSIC, NETCDF4,
@@ -2728,8 +2732,10 @@ 
    Static methods
    
 the Dataset in a unix directory format (the names of groups in the
 hierarchy separated by backslashes). A Dataset instance is the root
 group, so the path is simply '/'.
    
-
    keepweakref: If True, child Dimension and Variables objects only keep weak 
-references to the parent Dataset or Group.
    
+
    keepweakref: If True, child Dimension and Variables objects only keep weak
+references to the parent Dataset or Group.
    
+
    _ncstring_attrs__: If True, all text attributes will be written as variable-length
+strings.
    
   
    
 
    
 
@@ -2942,7 +2948,7 @@ 
    Static methods
    
 file format, which supports 64-bit dimension sizes plus unsigned and
 64 bit integer data types, but is only compatible with clients linked against
 netCDF version 4.4.0 or later.
    
-
    diskless: If True, create diskless (in-core) file.
    
+
    diskless: If True, create diskless (in-core) file.
 This is a feature added to the C library after the
 netcdf-4.2 release. If you need to access the memory buffer directly,
 use the in-memory feature instead (see memory kwarg).
    
@@ -2961,6 +2967,9 @@ 
    Static methods
    
 reducing memory usage and open file handles.  However, in many cases this is not
 desirable, since the associated Variable instances may still be needed, but are
 rendered unusable when the parent Dataset instance is garbage collected.
    
+
    _ncstring_attrs__: if _ncstring_attrs__=True, all string attributes will use
+the variable length NC_STRING attributes (default False, ascii text
+attributes written as NC_CHAR).
    
 
    memory: if not None, create or open an in-memory Dataset.
 If mode = 'r', the memory kwarg must contain a memory buffer object
 (an object that supports the python buffer interface).
@@ -3075,7 +3084,7 @@ 
    Static methods
    
   
     
    Creates a new Group with the given groupname.
    
 
    If groupname is specified as a path, using forward slashes as in unix to
-separate components, then intermediate groups will be created as necessary 
+separate components, then intermediate groups will be created as necessary
 (analogous to mkdir -p in unix).  For example,
 createGroup('/GroupA/GroupB/GroupC') will create GroupA,
 GroupA/GroupB, and GroupA/GroupB/GroupC, if they don't already exist.
@@ -3118,7 +3127,7 @@ 
    Static methods
    
 dimensions. If dimensions are not given, the variable is assumed to be
 a scalar.
    
 
    If varname is specified as a path, using forward slashes as in unix to
-separate components, then intermediate groups will be created as necessary 
+separate components, then intermediate groups will be created as necessary
 For example, createVariable('/GroupA/GroupB/VarC', float, ('x','y')) will create groups GroupA
 and GroupA/GroupB, plus the variable GroupA/GroupB/VarC, if the preceding
 groups don't already exist.
    
@@ -3177,7 +3186,7 @@ 
    Static methods
    
 efficient compression. For example, if least_significant_digit=1,
 data will be quantized using numpy.around(scale*data)/scale, where
 scale = 2**bits, and bits is determined so that a precision of 0.1 is
-retained (in this case bits=4). From the 
+retained (in this case bits=4). From the
 PSD metadata conventions:
 "least_significant_digit -- power of ten of the smallest decimal place
 in unpacked data that is a reliable value." Default is None, or no
@@ -3264,7 +3273,7 @@ 
    Static methods
    
   
     
    Returns a list of variables that match specific conditions.
    
 
    Can pass in key=value parameters and variables are returned that
-contain all of the matches. For example, 
    
+contain all of the matches. For example,
    
 
    >>> # Get variables with x-axis attribute.
 >>> vs = nc.get_variables_by_attributes(axis='X')
 >>> # Get variables with matching "standard_name" attribute
@@ -3432,7 +3441,7 @@ 
    Static methods
    
     
    Call set_auto_chartostring for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
    
 
    True_or_False: Boolean determining if automatic conversion of
-all character arrays <--> string arrays should be performed for 
+all character arrays <--> string arrays should be performed for
 character variables (variables of type NC_CHAR or S1) with the
 _Encoding attribute set.
    
 
    Note: Calling this function only affects existing variables. Variables created
@@ -3543,6 +3552,28 @@ 
    Static methods
    
   
    
   
             
+  
    
+    
    
+    
    def set_ncstring_attrs(
    self, True_or_False)
    
+    
    
+    
+
+    
+  
+    
    Call set_ncstring_attrs for all variables contained in
+this Dataset or Group, as well as for all its
+subgroups and their variables.
    
+
    True_or_False: Boolean determining if all string attributes are
+created as variable-length NC_STRINGs, (if True), or if ascii text
+attributes are stored as NC_CHARs (if False; default)
    
+
    Note: Calling this function only affects newly created attributes
+of existing (sub-) groups and their variables.
    
+  
    
+
    
+
+  
    
+  
+            
   
    
     
    
     
    def setncattr(
    self,name,value)
    
@@ -3721,7 +3752,7 @@ 
    Static methods
    
   
     
    A EnumType instance is used to describe an Enum data
 type, and can be passed to the the createVariable method of
-a Dataset or Group instance. See 
+a Dataset or Group instance. See
 __init__ for more details.
    
 
    The instance variables dtype, name and enum_dict should not be modified by
 the user.
    
@@ -3807,7 +3838,7 @@ 
    Static methods
    
 a Dataset within a Dataset, and can contain it's own variables,
 dimensions and attributes (and other Groups). See __init__
 for more details.
    
-
    Group inherits from Dataset, so all the 
+
    Group inherits from Dataset, so all the
 Dataset class methods and variables are available
 to a Group instance (except the close method).
    
 
    Additional read-only class variables:
    
@@ -4175,7 +4206,7 @@ 
    Static methods
    
   
     
    Creates a new Group with the given groupname.
    
 
    If groupname is specified as a path, using forward slashes as in unix to
-separate components, then intermediate groups will be created as necessary 
+separate components, then intermediate groups will be created as necessary
 (analogous to mkdir -p in unix).  For example,
 createGroup('/GroupA/GroupB/GroupC') will create GroupA,
 GroupA/GroupB, and GroupA/GroupB/GroupC, if they don't already exist.
@@ -4226,7 +4257,7 @@ 
    Static methods
    
 dimensions. If dimensions are not given, the variable is assumed to be
 a scalar.
    
 
    If varname is specified as a path, using forward slashes as in unix to
-separate components, then intermediate groups will be created as necessary 
+separate components, then intermediate groups will be created as necessary
 For example, createVariable('/GroupA/GroupB/VarC', float, ('x','y')) will create groups GroupA
 and GroupA/GroupB, plus the variable GroupA/GroupB/VarC, if the preceding
 groups don't already exist.
    
@@ -4285,7 +4316,7 @@ 
    Static methods
    
 efficient compression. For example, if least_significant_digit=1,
 data will be quantized using numpy.around(scale*data)/scale, where
 scale = 2**bits, and bits is determined so that a precision of 0.1 is
-retained (in this case bits=4). From the 
+retained (in this case bits=4). From the
 PSD metadata conventions:
 "least_significant_digit -- power of ten of the smallest decimal place
 in unpacked data that is a reliable value." Default is None, or no
@@ -4384,7 +4415,7 @@ 
    Static methods
    
   
     
    Returns a list of variables that match specific conditions.
    
 
    Can pass in key=value parameters and variables are returned that
-contain all of the matches. For example, 
    
+contain all of the matches. For example,
    
 
    >>> # Get variables with x-axis attribute.
 >>> vs = nc.get_variables_by_attributes(axis='X')
 >>> # Get variables with matching "standard_name" attribute
@@ -4588,7 +4619,7 @@ 
    Static methods
    
     
    Call set_auto_chartostring for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
    
 
    True_or_False: Boolean determining if automatic conversion of
-all character arrays <--> string arrays should be performed for 
+all character arrays <--> string arrays should be performed for
 character variables (variables of type NC_CHAR or S1) with the
 _Encoding attribute set.
    
 
    Note: Calling this function only affects existing variables. Variables created
@@ -4719,6 +4750,32 @@ 
    Static methods
    
   
    
   
             
+  
    
+    
    
+    
    def set_ncstring_attrs(
    self, True_or_False)
    
+    
    
+    
+    
    
+     Inheritance:
+       Dataset.set_ncstring_attrs
+    
    
+
+    
+  
+    
    Call set_ncstring_attrs for all variables contained in
+this Dataset or Group, as well as for all its
+subgroups and their variables.
    
+
    True_or_False: Boolean determining if all string attributes are
+created as variable-length NC_STRINGs, (if True), or if ascii text
+attributes are stored as NC_CHARs (if False; default)
    
+
    Note: Calling this function only affects newly created attributes
+of existing (sub-) groups and their variables.
    
+  
    
+
    
+
+  
    
+  
+            
   
    
     
    
     
    def setncattr(
    self,name,value)
    
@@ -5138,7 +5195,7 @@ 
    Static methods
    
   
     
    Creates a new Group with the given groupname.
    
 
    If groupname is specified as a path, using forward slashes as in unix to
-separate components, then intermediate groups will be created as necessary 
+separate components, then intermediate groups will be created as necessary
 (analogous to mkdir -p in unix).  For example,
 createGroup('/GroupA/GroupB/GroupC') will create GroupA,
 GroupA/GroupB, and GroupA/GroupB/GroupC, if they don't already exist.
@@ -5189,7 +5246,7 @@ 
    Static methods
    
 dimensions. If dimensions are not given, the variable is assumed to be
 a scalar.
    
 
    If varname is specified as a path, using forward slashes as in unix to
-separate components, then intermediate groups will be created as necessary 
+separate components, then intermediate groups will be created as necessary
 For example, createVariable('/GroupA/GroupB/VarC', float, ('x','y')) will create groups GroupA
 and GroupA/GroupB, plus the variable GroupA/GroupB/VarC, if the preceding
 groups don't already exist.
    
@@ -5248,7 +5305,7 @@ 
    Static methods
    
 efficient compression. For example, if least_significant_digit=1,
 data will be quantized using numpy.around(scale*data)/scale, where
 scale = 2**bits, and bits is determined so that a precision of 0.1 is
-retained (in this case bits=4). From the 
+retained (in this case bits=4). From the
 PSD metadata conventions:
 "least_significant_digit -- power of ten of the smallest decimal place
 in unpacked data that is a reliable value." Default is None, or no
@@ -5347,7 +5404,7 @@ 
    Static methods
    
   
     
    Returns a list of variables that match specific conditions.
    
 
    Can pass in key=value parameters and variables are returned that
-contain all of the matches. For example, 
    
+contain all of the matches. For example,
    
 
    >>> # Get variables with x-axis attribute.
 >>> vs = nc.get_variables_by_attributes(axis='X')
 >>> # Get variables with matching "standard_name" attribute
@@ -5532,7 +5589,7 @@ 
    Static methods
    
     
    Call set_auto_chartostring for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
    
 
    True_or_False: Boolean determining if automatic conversion of
-all character arrays <--> string arrays should be performed for 
+all character arrays <--> string arrays should be performed for
 character variables (variables of type NC_CHAR or S1) with the
 _Encoding attribute set.
    
 
    Note: Calling this function only affects existing variables. Variables created
@@ -5663,6 +5720,32 @@ 
    Static methods
    
   
    
   
             
+  
    
+    
    
+    
    def set_ncstring_attrs(
    self, True_or_False)
    
+    
    
+    
+    
    
+     Inheritance:
+       Dataset.set_ncstring_attrs
+    
    
+
+    
+  
+    
    Call set_ncstring_attrs for all variables contained in
+this Dataset or Group, as well as for all its
+subgroups and their variables.
    
+
    True_or_False: Boolean determining if all string attributes are
+created as variable-length NC_STRINGs, (if True), or if ascii text
+attributes are stored as NC_CHARs (if False; default)
    
+
    Note: Calling this function only affects newly created attributes
+of existing (sub-) groups and their variables.
    
+  
    
+
    
+
+  
    
+  
+            
   
    
     
    
     
    def setncattr(
    self,name,value)
    
@@ -6004,7 +6087,7 @@ 
    Methods
    
   
     
    A VLType instance is used to describe a variable length (VLEN) data
 type, and can be passed to the the createVariable method of
-a Dataset or Group instance. See 
+a Dataset or Group instance. See
 __init__ for more details.
    
 
    The instance variables dtype and name should not be modified by
 the user.
    
@@ -6090,18 +6173,18 @@ 
    Static methods
    
 
    shape: A tuple with the current shape (length of all dimensions).
    
 
    scale: If True, scale_factor and add_offset are
 applied, and signed integer data is automatically converted to
-unsigned integer data if the _Unsigned attribute is set. 
+unsigned integer data if the _Unsigned attribute is set.
 Default is True, can be reset using set_auto_scale and
 set_auto_maskandscale methods.
    
-
    mask: If True, data is automatically converted to/from masked 
+
    mask: If True, data is automatically converted to/from masked
 arrays when missing values or fill values are present. Default is True, can be
 reset using set_auto_mask and set_auto_maskandscale
 methods.
    
-
    chartostring: If True, data is automatically converted to/from character 
-arrays to string arrays when the _Encoding variable attribute is set. 
+
    chartostring: If True, data is automatically converted to/from character
+arrays to string arrays when the _Encoding variable attribute is set.
 Default is True, can be reset using
 set_auto_chartostring method.
    
-
    least_significant_digit: Describes the power of ten of the 
+
    least_significant_digit: Describes the power of ten of the
 smallest decimal place in the data the contains a reliable value.  Data is
 truncated to this decimal place when it is assigned to the Variable
 instance. If None, the data is not truncated.
    
@@ -6447,7 +6530,7 @@ 
    Static methods
    
 
     
   
-    
    return a tuple of Dimension instances associated with this 
+    
    return a tuple of Dimension instances associated with this
 `netCDF4.Variable.
    
   
    
 
    
@@ -6571,7 +6654,7 @@ 
    Static methods
    
 (dtype = S1) that has an _Encoding attribute, it is converted to a numpy
 fixed length unicode string array (dtype = UN, where N is the length
 of the the rightmost dimension of the variable).  The value of _Encoding
-is the unicode encoding that is used to decode the bytes into strings. 
    
+is the unicode encoding that is used to decode the bytes into strings.
    
 
    When numpy string data is written to a variable it is converted back to
 indiviual bytes, with the number of bytes in each string equalling the
 rightmost dimension of the variable.
    
@@ -6603,7 +6686,7 @@ 
    Static methods
    
 array is converted back to a regular numpy array by replacing all the
 masked values by the missing_value attribute of the variable (if it
 exists).  If the variable has no missing_value attribute, the _FillValue
-is used instead. If the variable has valid_min/valid_max and 
+is used instead. If the variable has valid_min/valid_max and
 missing_value attributes, data outside the specified range will be
 set to missing_value.
    
 
    The default value of mask is True
@@ -6624,7 +6707,7 @@ 
    Static methods
    
   
     
    turn on or off automatic conversion of variable data to and
 from masked arrays, automatic packing/unpacking of variable
-data using scale_factor and add_offset attributes and 
+data using scale_factor and add_offset attributes and
 automatic conversion of signed integer data to unsigned integer
 data if the _Unsigned attribute exists.
    
 
    If maskandscale is set to True, when data is read from a variable
@@ -6637,7 +6720,7 @@ 
    Static methods
    
 array is converted back to a regular numpy array by replacing all the
 masked values by the missing_value attribute of the variable (if it
 exists).  If the variable has no missing_value attribute, the _FillValue
-is used instead. If the variable has valid_min/valid_max and 
+is used instead. If the variable has valid_min/valid_max and
 missing_value attributes, data outside the specified range will be
 set to missing_value.
    
 
    If maskandscale is set to True, and the variable has a
@@ -6658,11 +6741,11 @@ 
    Static methods
    
 For more information on how scale_factor and add_offset can be
 used to provide simple compression, see the
 PSD metadata conventions.
    
-
    In addition, if maskandscale is set to True, and if the variable has an 
-attribute _Unsigned set, and the variable has a signed integer data type, 
+
    In addition, if maskandscale is set to True, and if the variable has an
+attribute _Unsigned set, and the variable has a signed integer data type,
 a view to the data is returned with the corresponding unsigned integer data type.
 This convention is used by the netcdf-java library to save unsigned integer
-data in NETCDF3 or NETCDF4_CLASSIC files (since the NETCDF3 
+data in NETCDF3 or NETCDF4_CLASSIC files (since the NETCDF3
 data model does not have unsigned integer data types).
    
 
    The default value of maskandscale is True
 (automatic conversions are performed).
    
@@ -6703,11 +6786,11 @@ 
    Static methods
    
 For more information on how scale_factor and add_offset can be
 used to provide simple compression, see the
 PSD metadata conventions.
    
-
    In addition, if scale is set to True, and if the variable has an 
+
    In addition, if scale is set to True, and if the variable has an
 attribute _Unsigned set, and the variable has a signed integer data type,
 a view to the data is returned with the corresponding unsigned integer datatype.
 This convention is used by the netcdf-java library to save unsigned integer
-data in NETCDF3 or NETCDF4_CLASSIC files (since the NETCDF3 
+data in NETCDF3 or NETCDF4_CLASSIC files (since the NETCDF3
 data model does not have unsigned integer data types).
    
 
    The default value of scale is True
 (automatic conversions are performed).
    
@@ -6733,6 +6816,25 @@ 
    Static methods
    
   
    
   
             
+  
    
+    
    
+    
    def set_ncstring_attrs(
    ...)
    
+    
    
+    
+
+    
+  
+    
    turn on or off creating NC_STRING string attributes.
    
+
    If ncstring_attrs is set to True then text attributes will be variable-length
+NC_STRINGs.
    
+
    The default value of ncstring_attrs is False (writing ascii text attributes as
+NC_CHAR).
    
+  
    
+
    
+
+  
    
+  
+            
   
    
     
    
     
    def set_var_chunk_cache(
    self,size=None,nelems=None,preemption=None)
    
@@ -6805,7 +6907,7 @@ 
    Static methods
    
             
   
    
     
    
-    
    def use_nc_get_vars(
    self,_no_get_vars)
    
+    
    def use_nc_get_vars(
    self,_use_get_vars)
    
     
    
     
 

From 09e1fa875669690efb37642c20d4006718c168e4 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 3 Mar 2019 16:08:46 -0700
Subject: [PATCH 0252/1504] check to see if parallel mode works with
 NETCDF4_CLASSIC

---
 netCDF4/_netCDF4.pyx | 7 +++++--
 1 file changed, 5 insertions(+), 2 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index f0913bd1a..c3d33da10 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2107,8 +2107,11 @@ strings.
                 msg='parallel mode requires MPI enabled netcdf-c'
                 raise ValueError(msg)
             ELSE:
-                if format != 'NETCDF4':
-                    msg='parallel mode only works with format=NETCDF4'
+                #if format != 'NETCDF4':
+                #    msg='parallel mode only works with format=NETCDF4'
+                #    raise ValueError(msg)
+                if format not in ['NETCDF4','NETCDF4_CLASSIC']:
+                    msg='parallel mode only works with format=NETCDF4 or NETCDF4_CLASSIC'
                     raise ValueError(msg)
                 if comm is not None:
                     mpicomm = comm.ob_mpi

From b9e7d889859735c1c99ffd97ef0b9062bddaa178 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 3 Mar 2019 16:09:38 -0700
Subject: [PATCH 0253/1504] check to see if parallel mode works with
 NETCDF4_CLASSIC

---
 examples/mpi_example.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/mpi_example.py b/examples/mpi_example.py
index afac52ddb..0f5e5f2e4 100644
--- a/examples/mpi_example.py
+++ b/examples/mpi_example.py
@@ -4,7 +4,7 @@
 from netCDF4 import Dataset
 rank = MPI.COMM_WORLD.rank  # The process ID (integer 0-3 for 4-process run)
 nc = Dataset('parallel_test.nc', 'w', parallel=True, comm=MPI.COMM_WORLD,
-        info=MPI.Info())
+        info=MPI.Info(),format='NETCDF4_CLASSIC')
 # below should work also - MPI_COMM_WORLD and MPI_INFO_NULL will be used.
 #nc = Dataset('parallel_test.nc', 'w', parallel=True)
 d = nc.createDimension('dim',4)

From 954f9adfddf68dde0aaa11d3ae1ffe60ebcf0b9a Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 3 Mar 2019 16:57:58 -0700
Subject: [PATCH 0254/1504] update Changelog

---
 Changelog            | 1 +
 netCDF4/_netCDF4.pyx | 3 ---
 2 files changed, 1 insertion(+), 3 deletions(-)

diff --git a/Changelog b/Changelog
index d38294502..b1f2e111b 100644
--- a/Changelog
+++ b/Changelog
@@ -14,6 +14,7 @@
  * Added methods `set_ncstring_attrs()` to Dataset, Group and Variable that
    forces all text attributes to be written as variable length strings (netCDF
    type NC_STRING - issue #882).
+ * Allow parallel mode with NETCDF4_CLASSIC files (issue #890).
 
  version 1.4.2 (tag v1.4.2rel)
 =============================
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index c3d33da10..db59ed947 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2107,9 +2107,6 @@ strings.
                 msg='parallel mode requires MPI enabled netcdf-c'
                 raise ValueError(msg)
             ELSE:
-                #if format != 'NETCDF4':
-                #    msg='parallel mode only works with format=NETCDF4'
-                #    raise ValueError(msg)
                 if format not in ['NETCDF4','NETCDF4_CLASSIC']:
                     msg='parallel mode only works with format=NETCDF4 or NETCDF4_CLASSIC'
                     raise ValueError(msg)

From e2d391b5b30fec64836d0eafccd06c1f166e048a Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 4 Mar 2019 01:34:54 +0000
Subject: [PATCH 0255/1504] fix issue #890 (parallel IO with NETCDF4_CLASSIC).

---
 Changelog            | 1 +
 netCDF4/_netCDF4.pyx | 8 ++++----
 2 files changed, 5 insertions(+), 4 deletions(-)

diff --git a/Changelog b/Changelog
index d38294502..b1f2e111b 100644
--- a/Changelog
+++ b/Changelog
@@ -14,6 +14,7 @@
  * Added methods `set_ncstring_attrs()` to Dataset, Group and Variable that
    forces all text attributes to be written as variable length strings (netCDF
    type NC_STRING - issue #882).
+ * Allow parallel mode with NETCDF4_CLASSIC files (issue #890).
 
  version 1.4.2 (tag v1.4.2rel)
 =============================
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index c3d33da10..3737cf3c9 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -920,7 +920,9 @@ specified names.
 
 If MPI parallel enabled versions of netcdf and hdf5 are detected, and
 [mpi4py](https://mpi4py.scipy.org) is installed, netcdf4-python will
-be built with parallel IO capabilities enabled.  To use parallel IO,
+be built with parallel IO capabilities enabled.  Since parallel IO
+uses features of HDF5, it can only be used with NETCDF4 or 
+NETCDF4_CLASSIC formatted files. To use parallel IO,
 your program must be running in an MPI environment using
 [mpi4py](https://mpi4py.scipy.org).
 
@@ -971,6 +973,7 @@ the two types of IO, use the `netCDF4.Variable.set_collective`
 operations (such as creation of groups, types, variables, dimensions, or attributes)
 are collective.  There are a couple of important limitatons of parallel IO:
 
+ - only works with NETCDF4 or NETCDF4_CLASSIC formatted files.
  - If a variable has an unlimited dimension, appending data must be done in collective mode.
    If the write is done in independent mode, the operation will fail with a
    a generic "HDF Error".
@@ -2107,9 +2110,6 @@ strings.
                 msg='parallel mode requires MPI enabled netcdf-c'
                 raise ValueError(msg)
             ELSE:
-                #if format != 'NETCDF4':
-                #    msg='parallel mode only works with format=NETCDF4'
-                #    raise ValueError(msg)
                 if format not in ['NETCDF4','NETCDF4_CLASSIC']:
                     msg='parallel mode only works with format=NETCDF4 or NETCDF4_CLASSIC'
                     raise ValueError(msg)

From f4581015e339d8fd3ecc90f542521ccbec302bfa Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 3 Mar 2019 20:23:03 -0700
Subject: [PATCH 0256/1504] update docs

---
 docs/netCDF4/index.html | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/docs/netCDF4/index.html b/docs/netCDF4/index.html
index 5f3d546d6..ce921ebca 100644
--- a/docs/netCDF4/index.html
+++ b/docs/netCDF4/index.html
@@ -2153,7 +2153,9 @@ 
    12) Enum data type.
    
 
    13) Parallel IO.
    
 
    If MPI parallel enabled versions of netcdf and hdf5 are detected, and
 mpi4py is installed, netcdf4-python will
-be built with parallel IO capabilities enabled.  To use parallel IO,
+be built with parallel IO capabilities enabled.  Since parallel IO
+uses features of HDF5, it can only be used with NETCDF4 or 
+NETCDF4_CLASSIC formatted files. To use parallel IO,
 your program must be running in an MPI environment using
 mpi4py.
    
 
    >>> from mpi4py import MPI
@@ -2204,6 +2206,7 @@ 
    13) Parallel IO.
    
 operations (such as creation of groups, types, variables, dimensions, or attributes)
 are collective.  There are a couple of important limitatons of parallel IO:
    
 
      
+
    • only works with NETCDF4 or NETCDF4_CLASSIC formatted files.
      • 
 
    • If a variable has an unlimited dimension, appending data must be done in collective mode.
    If the write is done in independent mode, the operation will fail with a
    a generic "HDF Error".
      • 

From a057799c3545a9fc9a273446352f0f0969e755f0 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 3 Mar 2019 20:50:07 -0700
Subject: [PATCH 0257/1504] update PKG-INFO

---
 PKG-INFO | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/PKG-INFO b/PKG-INFO
index d2652b42d..c3d90cf03 100644
--- a/PKG-INFO
+++ b/PKG-INFO
@@ -1,6 +1,6 @@
 Metadata-Version: 1.1
 Name: netCDF4
-Version: 1.4.2
+Version: 1.4.3
 Author: Jeff Whitaker
 Author-email: jeffrey s whitaker at noaa gov
 Home-page: https://github.com/Unidata/netcdf4-python

From b3f3c64081b27b7ebabcb4ca3cd06abad221b0e0 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 3 Mar 2019 20:54:37 -0700
Subject: [PATCH 0258/1504] update

---
 README.md | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/README.md b/README.md
index 5b39f3e33..0ca20ead3 100644
--- a/README.md
+++ b/README.md
@@ -8,6 +8,8 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
+03/05/2019: Version [1.4.3](https://pypi.python.org/pypi/netCDF4/1.4.3) released. Issues with netcdf-c 4.6.2 fixed (including broken parallel IO).  `set_ncstring_attrs()` method added, memoryview buffer now returned when an in-memory Dataset is closed.
+
 10/26/2018: Version [1.4.2](https://pypi.python.org/pypi/netCDF4/1.4.2) released. Minor bugfixes, added `Variable.get_dims()` method and `master_file` kwarg for `MFDataset.__init__`.
 
 08/10/2018: Version [1.4.1](https://pypi.python.org/pypi/netCDF4/1.4.1) released. The old slicing behavior

From 4ca3698b7762f7616d25f8525f51286115a2a6d3 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 4 Mar 2019 16:58:49 -0700
Subject: [PATCH 0259/1504] add conda-forge badge

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index 0ca20ead3..58ae15cf9 100644
--- a/README.md
+++ b/README.md
@@ -4,6 +4,7 @@
 [![Linux Build Status](https://travis-ci.org/Unidata/netcdf4-python.svg?branch=master)](https://travis-ci.org/Unidata/netcdf4-python)
 [![Windows Build Status](https://ci.appveyor.com/api/projects/status/fl9taa9je4e6wi7n/branch/master?svg=true)](https://ci.appveyor.com/project/jswhit/netcdf4-python/branch/master)
 [![PyPI package](https://badge.fury.io/py/netCDF4.svg)](http://python.org/pypi/netCDF4)
+[![Anaconda-Server Badge](https://anaconda.org/conda-forge/netCDF4/badges/version.svg)](https://anaconda.org/conda-forge/netCDF4)
 
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).

From d8b0f4a87373b4070a78cf22c3bd41f0dc4e1a62 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 4 Mar 2019 17:26:16 -0700
Subject: [PATCH 0260/1504] really implement NETCDF4_CLASSIC in parallel IO

---
 netCDF4/_netCDF4.pyx | 25 +++++++++++++++++++++----
 1 file changed, 21 insertions(+), 4 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 3737cf3c9..ff8f29693 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2083,6 +2083,7 @@ strings.
         cdef size_t initialsize
         cdef char *path
         cdef char namstring[NC_MAX_NAME+1]
+        cdef int cmode
         IF HAS_NC_PAR:
             cdef MPI_Comm mpicomm
             cdef MPI_Info mpiinfo
@@ -2141,7 +2142,11 @@ strings.
                 if clobber:
                     if parallel:
                         IF HAS_NC_PAR:
-                            ierr = nc_create_par(path, NC_CLOBBER | NC_MPIIO | NC_NETCDF4, \
+                            if format == 'NETCDF4_CLASSIC':
+                                cmode = NC_CLOBBER | NC_MPIIO | NC_NETCDF4 | NC_CLASSIC_MODEL
+                            else:
+                                cmode = NC_CLOBBER | NC_MPIIO | NC_NETCDF4
+                            ierr = nc_create_par(path, cmode, \
                                    mpicomm, mpiinfo, &grpid)
                         ELSE:
                             pass
@@ -2156,7 +2161,11 @@ strings.
                 else:
                     if parallel:
                         IF HAS_NC_PAR:
-                            ierr = nc_create_par(path, NC_NOCLOBBER | NC_MPIIO | NC_NETCDF4, \
+                            if format == 'NETCDF4_CLASSIC':
+                                cmode = NC_NOCLOBBER | NC_MPIIO | NC_NETCDF4 | NC_CLASSIC_MODEL
+                            else:
+                                cmode = NC_NOCLOBBER | NC_MPIIO | NC_NETCDF4
+                            ierr = nc_create_par(path, cmode, \
                                    mpicomm, mpiinfo, &grpid)
                         ELSE:
                             pass
@@ -2228,7 +2237,11 @@ strings.
                 if parallel:
                     # NC_SHARE ignored
                     IF HAS_NC_PAR:
-                        ierr = nc_create_par(path, NC_CLOBBER | NC_MPIIO | NC_NETCDF4, \
+                        if format == 'NETCDF4_CLASSIC':
+                            cmode = NC_CLOBBER | NC_MPIIO | NC_NETCDF4 | NC_CLASSIC_MODEL
+                        else:
+                            cmode = NC_CLOBBER | NC_MPIIO | NC_NETCDF4
+                        ierr = nc_create_par(path, cmode, \
                                mpicomm, mpiinfo, &grpid)
                     ELSE:
                         pass
@@ -2243,7 +2256,11 @@ strings.
                 if parallel:
                     # NC_SHARE ignored
                     IF HAS_NC_PAR:
-                        ierr = nc_create_par(path, NC_NOCLOBBER | NC_MPIIO | NC_NETCDF4, \
+                        if format == 'NETCDF4_CLASSIC':
+                            cmode = NC_NOCLOBBER | NC_MPIIO | NC_NETCDF4 | NC_CLASSIC_MODEL
+                        else:
+                            cmode = NC_NOCLOBBER | NC_MPIIO | NC_NETCDF4
+                        ierr = nc_create_par(path, cmode, \
                                mpicomm, mpiinfo, &grpid)
                     ELSE:
                         pass

From d0de5476580b466d7b13cfc7668c267e62cb15f0 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 4 Mar 2019 17:45:08 -0700
Subject: [PATCH 0261/1504] create 32 bit integer var, not 64 (to allow test
 with NETCDF4_CLASSIC)

---
 examples/mpi_example.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/mpi_example.py b/examples/mpi_example.py
index 0f5e5f2e4..885984882 100644
--- a/examples/mpi_example.py
+++ b/examples/mpi_example.py
@@ -8,7 +8,7 @@
 # below should work also - MPI_COMM_WORLD and MPI_INFO_NULL will be used.
 #nc = Dataset('parallel_test.nc', 'w', parallel=True)
 d = nc.createDimension('dim',4)
-v = nc.createVariable('var', np.int, 'dim')
+v = nc.createVariable('var', np.int32, 'dim')
 v[rank] = rank
 # switch to collective mode, rewrite the data.
 v.set_collective(True)

From 999c055375dcc6e3713eaa6939f0deb0c193e535 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 4 Mar 2019 17:48:16 -0700
Subject: [PATCH 0262/1504] update

---
 .travis.yml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.travis.yml b/.travis.yml
index c5c81d4a4..eb8206972 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -25,6 +25,7 @@ matrix:
   allow_failures:
     - python: "3.8-dev"
     - python: 3.7
+      dist: xenial
       env:
         - MPI=1
         - CC=mpicc.mpich

From ede0d63f6b6addf98295df74c2546b7bc7381744 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 4 Mar 2019 18:39:13 -0700
Subject: [PATCH 0263/1504] bump version number to 1.4.3.1

---
 .travis.yml          | 1 -
 Changelog            | 5 +++++
 netCDF4/_netCDF4.pyx | 2 +-
 setup.py             | 2 +-
 4 files changed, 7 insertions(+), 3 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index eb8206972..c5c81d4a4 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -25,7 +25,6 @@ matrix:
   allow_failures:
     - python: "3.8-dev"
     - python: 3.7
-      dist: xenial
       env:
         - MPI=1
         - CC=mpicc.mpich
diff --git a/Changelog b/Changelog
index b1f2e111b..da07a663c 100644
--- a/Changelog
+++ b/Changelog
@@ -1,3 +1,8 @@
+ version 1.4.3.1 (tag v1.4.3.1 rel)
+===================================
+ * fix bug in implementation of NETCDF4_CLASSIC support for parallel IO
+   in v1.4.3 release.
+
  version 1.4.3 (tag v1.4.3rel)
 =============================
  * make set_always_mask work in MFDataset.
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index ff8f29693..d8c0fc1b0 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1185,7 +1185,7 @@ except ImportError:
     # python3: zip is already python2's itertools.izip
     pass
 
-__version__ = "1.4.3"
+__version__ = "1.4.3.1"
 
 # Initialize numpy
 import posixpath
diff --git a/setup.py b/setup.py
index 67de93b7a..fd90ae286 100644
--- a/setup.py
+++ b/setup.py
@@ -570,7 +570,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 
 setup(name="netCDF4",
       cmdclass=cmdclass,
-      version="1.4.3",
+      version="1.4.3.1",
       long_description="netCDF version 4 has many features not found in earlier versions of the library, such as hierarchical groups, zlib compression, multiple unlimited dimensions, and new data types.  It is implemented on top of HDF5.  This module implements most of the new features, and can read and write netCDF files compatible with older versions of the library.  The API is modelled after Scientific.IO.NetCDF, and should be familiar to users of that module.\n\nThis project is hosted on a `GitHub repository `_ where you may access the most up-to-date source.",
       author="Jeff Whitaker",
       author_email="jeffrey.s.whitaker@noaa.gov",

From 89dbff06ace11e2f79431e31cd21739a900d3f89 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 4 Mar 2019 21:16:25 -0700
Subject: [PATCH 0264/1504] update

---
 netCDF4/_netCDF4.pyx | 27 +++++++--------------------
 1 file changed, 7 insertions(+), 20 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index d8c0fc1b0..d6b712d18 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2122,6 +2122,9 @@ strings.
                     mpiinfo = info.ob_mpi
                 else:
                     mpiinfo = MPI_INFO_NULL
+                cmode = NC_MPIIO | NC_NETCDF4
+                if format == 'NETCDF4_CLASSIC':
+                    cmode = cmode | NC_CLASSIC_MODEL
 
         self._inmemory = False
         if mode == 'w':
@@ -2142,11 +2145,7 @@ strings.
                 if clobber:
                     if parallel:
                         IF HAS_NC_PAR:
-                            if format == 'NETCDF4_CLASSIC':
-                                cmode = NC_CLOBBER | NC_MPIIO | NC_NETCDF4 | NC_CLASSIC_MODEL
-                            else:
-                                cmode = NC_CLOBBER | NC_MPIIO | NC_NETCDF4
-                            ierr = nc_create_par(path, cmode, \
+                            ierr = nc_create_par(path, NC_CLOBBER | cmode, \
                                    mpicomm, mpiinfo, &grpid)
                         ELSE:
                             pass
@@ -2161,11 +2160,7 @@ strings.
                 else:
                     if parallel:
                         IF HAS_NC_PAR:
-                            if format == 'NETCDF4_CLASSIC':
-                                cmode = NC_NOCLOBBER | NC_MPIIO | NC_NETCDF4 | NC_CLASSIC_MODEL
-                            else:
-                                cmode = NC_NOCLOBBER | NC_MPIIO | NC_NETCDF4
-                            ierr = nc_create_par(path, cmode, \
+                            ierr = nc_create_par(path, NC_NOCLOBBER | cmode, \
                                    mpicomm, mpiinfo, &grpid)
                         ELSE:
                             pass
@@ -2237,11 +2232,7 @@ strings.
                 if parallel:
                     # NC_SHARE ignored
                     IF HAS_NC_PAR:
-                        if format == 'NETCDF4_CLASSIC':
-                            cmode = NC_CLOBBER | NC_MPIIO | NC_NETCDF4 | NC_CLASSIC_MODEL
-                        else:
-                            cmode = NC_CLOBBER | NC_MPIIO | NC_NETCDF4
-                        ierr = nc_create_par(path, cmode, \
+                        ierr = nc_create_par(path, NC_CLOBBER | cmode, \
                                mpicomm, mpiinfo, &grpid)
                     ELSE:
                         pass
@@ -2256,11 +2247,7 @@ strings.
                 if parallel:
                     # NC_SHARE ignored
                     IF HAS_NC_PAR:
-                        if format == 'NETCDF4_CLASSIC':
-                            cmode = NC_NOCLOBBER | NC_MPIIO | NC_NETCDF4 | NC_CLASSIC_MODEL
-                        else:
-                            cmode = NC_NOCLOBBER | NC_MPIIO | NC_NETCDF4
-                        ierr = nc_create_par(path, cmode, \
+                        ierr = nc_create_par(path, NC_NOCLOBBER | cmode, \
                                mpicomm, mpiinfo, &grpid)
                     ELSE:
                         pass

From af3f2a13038706206640c90abc1db0b1a3bdce5a Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 4 Mar 2019 21:40:59 -0700
Subject: [PATCH 0265/1504] update

---
 PKG-INFO | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/PKG-INFO b/PKG-INFO
index c3d90cf03..3114a17c9 100644
--- a/PKG-INFO
+++ b/PKG-INFO
@@ -1,6 +1,6 @@
 Metadata-Version: 1.1
 Name: netCDF4
-Version: 1.4.3
+Version: 1.4.3.1
 Author: Jeff Whitaker
 Author-email: jeffrey s whitaker at noaa gov
 Home-page: https://github.com/Unidata/netcdf4-python

From 4cbec0153a63d3b833dc70bd0359d2ea565e0953 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 4 Mar 2019 21:42:45 -0700
Subject: [PATCH 0266/1504] update

---
 README.md | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/README.md b/README.md
index 58ae15cf9..88a518516 100644
--- a/README.md
+++ b/README.md
@@ -9,6 +9,9 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
+03/07/2019: Version [1.4.3.1](https://pypi.python.org/pypi/netCDF4/1.4.3.1) released. 
+Fixes bug in implementation of NETCDF4_CLASSIC parallel IO support in 1.4.3.
+
 03/05/2019: Version [1.4.3](https://pypi.python.org/pypi/netCDF4/1.4.3) released. Issues with netcdf-c 4.6.2 fixed (including broken parallel IO).  `set_ncstring_attrs()` method added, memoryview buffer now returned when an in-memory Dataset is closed.
 
 10/26/2018: Version [1.4.2](https://pypi.python.org/pypi/netCDF4/1.4.2) released. Minor bugfixes, added `Variable.get_dims()` method and `master_file` kwarg for `MFDataset.__init__`.

From b22fb81ed511f48bb6fb7597c4e1b03707a8a7db Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 6 Mar 2019 17:04:11 -0700
Subject: [PATCH 0267/1504] update

---
 Changelog | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Changelog b/Changelog
index da07a663c..681ad3494 100644
--- a/Changelog
+++ b/Changelog
@@ -1,4 +1,4 @@
- version 1.4.3.1 (tag v1.4.3.1 rel)
+ version 1.4.3.1 (tag v1.4.3.1)
 ===================================
  * fix bug in implementation of NETCDF4_CLASSIC support for parallel IO
    in v1.4.3 release.

From 64d72425c24d416700b8db257b0b5eef7900ae08 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 8 Mar 2019 12:51:55 -0700
Subject: [PATCH 0268/1504] forgot to include include/membuf.pyx in release
 source tarball

---
 MANIFEST.in | 1 +
 1 file changed, 1 insertion(+)

diff --git a/MANIFEST.in b/MANIFEST.in
index f18c58abd..6c68df479 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -17,3 +17,4 @@ include netCDF4/_netCDF4.pyx
 include netCDF4/utils.py
 include include/netCDF4.pxi
 include include/mpi-compat.h
+include include/membuf.pyx

From f1968d045355bb96771eb3fad5f899ac1b7dc544 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 8 Mar 2019 12:54:10 -0700
Subject: [PATCH 0269/1504] bump version number

---
 Changelog            | 4 ++++
 netCDF4/_netCDF4.pyx | 2 +-
 setup.py             | 2 +-
 3 files changed, 6 insertions(+), 2 deletions(-)

diff --git a/Changelog b/Changelog
index 681ad3494..2fd404e0b 100644
--- a/Changelog
+++ b/Changelog
@@ -1,3 +1,7 @@
+ version 1.4.3.2 (tag v1.4.3.2rel)
+==================================
+ * include missing membuf.pyx file in release source tarball.
+
  version 1.4.3.1 (tag v1.4.3.1)
 ===================================
  * fix bug in implementation of NETCDF4_CLASSIC support for parallel IO
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index d6b712d18..5aa40a356 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1185,7 +1185,7 @@ except ImportError:
     # python3: zip is already python2's itertools.izip
     pass
 
-__version__ = "1.4.3.1"
+__version__ = "1.4.3.2"
 
 # Initialize numpy
 import posixpath
diff --git a/setup.py b/setup.py
index fd90ae286..cf5013d4e 100644
--- a/setup.py
+++ b/setup.py
@@ -570,7 +570,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 
 setup(name="netCDF4",
       cmdclass=cmdclass,
-      version="1.4.3.1",
+      version="1.4.3.2",
       long_description="netCDF version 4 has many features not found in earlier versions of the library, such as hierarchical groups, zlib compression, multiple unlimited dimensions, and new data types.  It is implemented on top of HDF5.  This module implements most of the new features, and can read and write netCDF files compatible with older versions of the library.  The API is modelled after Scientific.IO.NetCDF, and should be familiar to users of that module.\n\nThis project is hosted on a `GitHub repository `_ where you may access the most up-to-date source.",
       author="Jeff Whitaker",
       author_email="jeffrey.s.whitaker@noaa.gov",

From 3fc3604120208bfe0491ab8b37ca69ec56c96ecc Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 8 Mar 2019 12:55:09 -0700
Subject: [PATCH 0270/1504] update

---
 README.md | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/README.md b/README.md
index 88a518516..83406959e 100644
--- a/README.md
+++ b/README.md
@@ -9,6 +9,9 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
+03/08/2019: Version [1.4.3.2](https://pypi.python.org/pypi/netCDF4/1.4.3.2) released. 
+Include missing membuf.pyx file in source tarball.
+
 03/07/2019: Version [1.4.3.1](https://pypi.python.org/pypi/netCDF4/1.4.3.1) released. 
 Fixes bug in implementation of NETCDF4_CLASSIC parallel IO support in 1.4.3.
 

From 2d356bcd6d30e110d5441c87ebcd1fc682285834 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 8 Mar 2019 20:15:35 -0700
Subject: [PATCH 0271/1504] update

---
 Changelog | 6 +++---
 README.md | 3 ++-
 2 files changed, 5 insertions(+), 4 deletions(-)

diff --git a/Changelog b/Changelog
index 2fd404e0b..463addfa2 100644
--- a/Changelog
+++ b/Changelog
@@ -1,9 +1,9 @@
- version 1.4.3.2 (tag v1.4.3.2rel)
-==================================
+ version 1.4.3.2 (tag v1.4.3.2)
+===============================
  * include missing membuf.pyx file in release source tarball.
 
  version 1.4.3.1 (tag v1.4.3.1)
-===================================
+===============================
  * fix bug in implementation of NETCDF4_CLASSIC support for parallel IO
    in v1.4.3 release.
 
diff --git a/README.md b/README.md
index 83406959e..9238e5a45 100644
--- a/README.md
+++ b/README.md
@@ -10,7 +10,8 @@
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
 03/08/2019: Version [1.4.3.2](https://pypi.python.org/pypi/netCDF4/1.4.3.2) released. 
-Include missing membuf.pyx file in source tarball.
+Include missing membuf.pyx file in source tarball. No need to update if you installed
+1.4.3.1 from a binary wheel.
 
 03/07/2019: Version [1.4.3.1](https://pypi.python.org/pypi/netCDF4/1.4.3.1) released. 
 Fixes bug in implementation of NETCDF4_CLASSIC parallel IO support in 1.4.3.

From 54f17128193139df47c808faff8a06db1c7647b0 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 8 Mar 2019 20:16:43 -0700
Subject: [PATCH 0272/1504] update

---
 PKG-INFO | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/PKG-INFO b/PKG-INFO
index 3114a17c9..3b780e07b 100644
--- a/PKG-INFO
+++ b/PKG-INFO
@@ -1,6 +1,6 @@
 Metadata-Version: 1.1
 Name: netCDF4
-Version: 1.4.3.1
+Version: 1.4.3.2
 Author: Jeff Whitaker
 Author-email: jeffrey s whitaker at noaa gov
 Home-page: https://github.com/Unidata/netcdf4-python

From b0b9d2e601ad9e70c05160470ca9ed07edeb62b2 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 12 Mar 2019 17:11:20 -0600
Subject: [PATCH 0273/1504] update NETCDF_VERSION to 4.6.3 (latest release)

---
 .travis.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.travis.yml b/.travis.yml
index c5c81d4a4..ac889bcd8 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -44,7 +44,7 @@ matrix:
         - MPI=1
         - CC=mpicc.mpich
         - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
-        - NETCDF_VERSION=4.6.2
+        - NETCDF_VERSION=4.6.3
         - NETCDF_DIR=$HOME
         - PATH=${NETCDF_DIR}/bin:${PATH} # pick up nc-config here
       addons:

From 8d4e494215e1614cb9c8b50ab7c9166e7d969c53 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 13 Mar 2019 07:44:07 -0600
Subject: [PATCH 0274/1504] add DOI badge

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index 9238e5a45..7e90abf56 100644
--- a/README.md
+++ b/README.md
@@ -5,6 +5,7 @@
 [![Windows Build Status](https://ci.appveyor.com/api/projects/status/fl9taa9je4e6wi7n/branch/master?svg=true)](https://ci.appveyor.com/project/jswhit/netcdf4-python/branch/master)
 [![PyPI package](https://badge.fury.io/py/netCDF4.svg)](http://python.org/pypi/netCDF4)
 [![Anaconda-Server Badge](https://anaconda.org/conda-forge/netCDF4/badges/version.svg)](https://anaconda.org/conda-forge/netCDF4)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.2592291.svg)](https://doi.org/10.5281/zenodo.2592291)
 
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).

From 88c22d16a12aa5e0abdf1295571d11783b4055b2 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 13 Mar 2019 17:38:54 -0600
Subject: [PATCH 0275/1504] check for empty file list in MFDataset

---
 netCDF4/_netCDF4.pyx | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 5aa40a356..bd8a83f1e 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -6099,6 +6099,10 @@ Example usage (See `netCDF4.MFDataset.__init__` for more details):
             else:
                 files = sorted(glob(files))
 
+        if not files:
+           msg='no files specified (file list is empty)'
+           raise IOError(msg)
+
         if master_file is not None:
             if master_file not in files:
                 raise ValueError('master_file not in files list')

From 15444878b44f10541b74f009776c96b4aab9d54a Mon Sep 17 00:00:00 2001
From: Lars Pastewka 
Date: Tue, 19 Mar 2019 22:15:53 +0100
Subject: [PATCH 0276/1504] support for PnetCDF parallel I/O

---
 include/netCDF4.pxi  |  3 ++-
 netCDF4/__init__.py  |  3 ++-
 netCDF4/_netCDF4.pyx | 50 +++++++++++++++++++++++++++++---------------
 setup.py             | 32 ++++++++++++++++++++--------
 4 files changed, 60 insertions(+), 28 deletions(-)

diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index 3b8cde18e..625752a68 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -51,6 +51,7 @@ cdef extern from "netcdf.h":
         NC_CLOBBER
         NC_NOCLOBBER # Don't destroy existing file on create 
         NC_64BIT_OFFSET # Use large (64-bit) file offsets 
+        NC_64BIT_DATA # Use cdf-5 format 
         NC_NETCDF4 # Use netCDF-4/HDF5 format 
         NC_CLASSIC_MODEL # Enforce strict netcdf-3 rules. 
         # Use these 'mode' flags for both nc_create and nc_open.
@@ -703,7 +704,7 @@ IF HAS_NC_CREATE_MEM:
             int flags
         int nc_close_memio(int ncid, NC_memio* info);
 
-IF HAS_NC_PAR:
+IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
     cdef extern from "mpi-compat.h": pass
     cdef extern from "netcdf_par.h":
         ctypedef int MPI_Comm
diff --git a/netCDF4/__init__.py b/netCDF4/__init__.py
index e2660d13c..4bdbdde38 100644
--- a/netCDF4/__init__.py
+++ b/netCDF4/__init__.py
@@ -6,6 +6,7 @@
 from ._netCDF4 import (__version__, __netcdf4libversion__, __hdf5libversion__,
                        __has_rename_grp__, __has_nc_inq_path__,
                        __has_nc_inq_format_extended__, __has_nc_open_mem__,
-                       __has_nc_create_mem__,__has_cdf5_format__,__has_nc_par__)
+                       __has_nc_create_mem__, __has_cdf5_format__,
+                       __has_parallel4_support__, __has_pnetcdf_support__)
 __all__ =\
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType']
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index bd8a83f1e..7826b58ef 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1202,7 +1202,7 @@ import_array()
 include "constants.pyx"
 include "membuf.pyx"
 include "netCDF4.pxi"
-IF HAS_NC_PAR:
+IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
     cimport mpi4py.MPI as MPI
     from mpi4py.libmpi cimport MPI_Comm, MPI_Info, MPI_Comm_dup, MPI_Info_dup, \
                                MPI_Comm_free, MPI_Info_free, MPI_INFO_NULL,\
@@ -1240,7 +1240,8 @@ __has_nc_inq_format_extended__ = HAS_NC_INQ_FORMAT_EXTENDED
 __has_cdf5_format__ = HAS_CDF5_FORMAT
 __has_nc_open_mem__ = HAS_NC_OPEN_MEM
 __has_nc_create_mem__ = HAS_NC_CREATE_MEM
-__has_nc_par__ = HAS_NC_PAR
+__has_parallel4_support__ = HAS_PARALLEL4_SUPPORT
+__has_pnetcdf_support__ = HAS_PNETCDF_SUPPORT
 _needsworkaround_issue485 = __netcdf4libversion__ < "4.4.0" or \
                (__netcdf4libversion__.startswith("4.4.0") and \
                 "-development" in __netcdf4libversion__)
@@ -1282,20 +1283,29 @@ _intnptonctype  = {'i1' : NC_BYTE,
 _format_dict  = {'NETCDF3_CLASSIC' : NC_FORMAT_CLASSIC,
                  'NETCDF4_CLASSIC' : NC_FORMAT_NETCDF4_CLASSIC,
                  'NETCDF4'         : NC_FORMAT_NETCDF4}
+# create dictionary mapping string identifiers to netcdf create format codes
+_cmode_dict  = {'NETCDF3_CLASSIC' : NC_CLASSIC_MODEL,
+                'NETCDF4_CLASSIC' : NC_CLASSIC_MODEL,
+                'NETCDF4'         : NC_NETCDF4}
 IF HAS_CDF5_FORMAT:
     # NETCDF3_64BIT deprecated, saved for compatibility.
     # use NETCDF3_64BIT_OFFSET instead.
     _format_dict['NETCDF3_64BIT_OFFSET'] = NC_FORMAT_64BIT_OFFSET
     _format_dict['NETCDF3_64BIT_DATA'] = NC_FORMAT_64BIT_DATA
+    _cmode_dict['NETCDF3_64BIT_OFFSET'] = NC_64BIT_OFFSET
+    _cmode_dict['NETCDF3_64BIT_DATA'] = NC_64BIT_DATA
 ELSE:
     _format_dict['NETCDF3_64BIT'] = NC_FORMAT_64BIT
+    _cmode_dict['NETCDF3_64BIT'] = NC_64BIT_OFFSET
 # invert dictionary mapping
 _reverse_format_dict = dict((v, k) for k, v in _format_dict.iteritems())
 # add duplicate entry (NETCDF3_64BIT == NETCDF3_64BIT_OFFSET)
 IF HAS_CDF5_FORMAT:
     _format_dict['NETCDF3_64BIT'] = NC_FORMAT_64BIT_OFFSET
+    _cmode_dict['NETCDF3_64BIT'] = NC_64BIT_OFFSET
 ELSE:
     _format_dict['NETCDF3_64BIT_OFFSET'] = NC_FORMAT_64BIT
+    _cmode_dict['NETCDF3_64BIT_OFFSET'] = NC_64BIT_OFFSET
 
 # default fill_value to numpy datatype mapping.
 default_fillvals = {#'S1':NC_FILL_CHAR,
@@ -2084,7 +2094,7 @@ strings.
         cdef char *path
         cdef char namstring[NC_MAX_NAME+1]
         cdef int cmode
-        IF HAS_NC_PAR:
+        IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
             cdef MPI_Comm mpicomm
             cdef MPI_Info mpiinfo
 
@@ -2107,12 +2117,20 @@ strings.
             raise ValueError(msg)
 
         if parallel:
-            IF HAS_NC_PAR != 1:
+            IF HAS_PARALLEL4_SUPPORT != 1 and HAS_PNETCDF_SUPPORT != 1:
                 msg='parallel mode requires MPI enabled netcdf-c'
                 raise ValueError(msg)
             ELSE:
-                if format not in ['NETCDF4','NETCDF4_CLASSIC']:
-                    msg='parallel mode only works with format=NETCDF4 or NETCDF4_CLASSIC'
+                parallel_formats = []
+                IF HAS_PARALLEL4_SUPPORT:
+                    parallel_formats += ['NETCDF4','NETCDF4_CLASSIC']
+                IF HAS_PNETCDF_SUPPORT:
+                    parallel_formats += ['NETCDF3_CLASSIC',
+                                         'NETCDF3_64BIT_OFFSET',
+                                         'NETCDF3_64BIT_DATA',
+                                         'NETCDF3_64BIT']
+                if format not in parallel_formats:
+                    msg='parallel mode only works with the following formats: ' + ' '.join(parallel_formats)
                     raise ValueError(msg)
                 if comm is not None:
                     mpicomm = comm.ob_mpi
@@ -2122,9 +2140,7 @@ strings.
                     mpiinfo = info.ob_mpi
                 else:
                     mpiinfo = MPI_INFO_NULL
-                cmode = NC_MPIIO | NC_NETCDF4
-                if format == 'NETCDF4_CLASSIC':
-                    cmode = cmode | NC_CLASSIC_MODEL
+                cmode = NC_MPIIO | _cmode_dict[format]
 
         self._inmemory = False
         if mode == 'w':
@@ -2144,7 +2160,7 @@ strings.
             else:
                 if clobber:
                     if parallel:
-                        IF HAS_NC_PAR:
+                        IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                             ierr = nc_create_par(path, NC_CLOBBER | cmode, \
                                    mpicomm, mpiinfo, &grpid)
                         ELSE:
@@ -2159,7 +2175,7 @@ strings.
                         ierr = nc_create(path, NC_CLOBBER, &grpid)
                 else:
                     if parallel:
-                        IF HAS_NC_PAR:
+                        IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                             ierr = nc_create_par(path, NC_NOCLOBBER | cmode, \
                                    mpicomm, mpiinfo, &grpid)
                         ELSE:
@@ -2194,7 +2210,7 @@ strings.
         version 4.4.1 or higher of the netcdf C lib, and rebuild netcdf4-python."""
                     raise ValueError(msg)
             elif parallel:
-                IF HAS_NC_PAR:
+                IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                     ierr = nc_open_par(path, NC_NOWRITE | NC_MPIIO, \
                            mpicomm, mpiinfo, &grpid)
                 ELSE:
@@ -2205,7 +2221,7 @@ strings.
                 ierr = nc_open(path, NC_NOWRITE, &grpid)
         elif mode == 'r+' or mode == 'a':
             if parallel:
-                IF HAS_NC_PAR:
+                IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                     ierr = nc_open_par(path, NC_WRITE | NC_MPIIO, \
                            mpicomm, mpiinfo, &grpid)
                 ELSE:
@@ -2217,7 +2233,7 @@ strings.
         elif mode == 'as' or mode == 'r+s':
             if parallel:
                 # NC_SHARE ignored
-                IF HAS_NC_PAR:
+                IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                     ierr = nc_open_par(path, NC_WRITE | NC_MPIIO, \
                            mpicomm, mpiinfo, &grpid)
                 ELSE:
@@ -2231,7 +2247,7 @@ strings.
             if clobber:
                 if parallel:
                     # NC_SHARE ignored
-                    IF HAS_NC_PAR:
+                    IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                         ierr = nc_create_par(path, NC_CLOBBER | cmode, \
                                mpicomm, mpiinfo, &grpid)
                     ELSE:
@@ -2246,7 +2262,7 @@ strings.
             else:
                 if parallel:
                     # NC_SHARE ignored
-                    IF HAS_NC_PAR:
+                    IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                         ierr = nc_create_par(path, NC_NOCLOBBER | cmode, \
                                mpicomm, mpiinfo, &grpid)
                     ELSE:
@@ -5345,7 +5361,7 @@ NC_CHAR).
 turn on or off collective parallel IO access. Ignored if file is not
 open for parallel access.
         """
-        IF HAS_NC_PAR:
+        IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
             # set collective MPI IO mode on or off
             if value:
                 ierr = nc_var_par_access(self._grpid, self._varid,
diff --git a/setup.py b/setup.py
index cf5013d4e..8f1ade563 100644
--- a/setup.py
+++ b/setup.py
@@ -56,7 +56,8 @@ def check_api(inc_dirs):
     has_cdf5_format = False
     has_nc_open_mem = False
     has_nc_create_mem = False
-    has_nc_par = False
+    has_parallel4_support = False
+    has_pnetcdf_support = False
 
     for d in inc_dirs:
         try:
@@ -65,7 +66,6 @@ def check_api(inc_dirs):
             continue
 
         has_nc_open_mem = os.path.exists(os.path.join(d, 'netcdf_mem.h'))
-        has_nc_par = os.path.exists(os.path.join(d, 'netcdf_par.h'))
 
         for line in f:
             if line.startswith('nc_rename_grp'):
@@ -91,10 +91,15 @@ def check_api(inc_dirs):
             for line in open(ncmetapath):
                 if line.startswith('#define NC_HAS_CDF5'):
                     has_cdf5_format = bool(int(line.split()[2]))
+                elif line.startswith('#define NC_HAS_PARALLEL4'):
+                    has_parallel4_support = bool(int(line.split()[2]))
+                elif line.startswith('#define NC_HAS_PNETCDF'):
+                    has_pnetcdf_support = bool(int(line.split()[2]))
         break
 
     return has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \
-           has_cdf5_format, has_nc_open_mem, has_nc_create_mem, has_nc_par
+           has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \
+           has_parallel4_support, has_pnetcdf_support
 
 
 def getnetcdfvers(libdirs):
@@ -488,7 +493,8 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
             os.remove(netcdf4_src_c)
     # this determines whether renameGroup and filepath methods will work.
     has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \
-    has_cdf5_format, has_nc_open_mem, has_nc_create_mem, has_nc_par = check_api(inc_dirs)
+    has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \
+    has_parallel4_support, has_pnetcdf_support = check_api(inc_dirs)
     # for netcdf 4.4.x CDF5 format is always enabled.
     if netcdf_lib_version is not None and\
        (netcdf_lib_version > "4.4" and netcdf_lib_version < "4.5"):
@@ -498,7 +504,8 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     try:
         import mpi4py
     except ImportError:
-        has_nc_par = False
+        has_parallel4_support = False
+        has_pnetcdf_support = False
 
     f = open(osp.join('include', 'constants.pyx'), 'w')
     if has_rename_grp:
@@ -544,16 +551,23 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         sys.stdout.write('netcdf lib does not have cdf-5 format capability\n')
         f.write('DEF HAS_CDF5_FORMAT = 0\n')
 
-    if has_nc_par:
+    if has_parallel4_support:
         sys.stdout.write('netcdf lib has netcdf4 parallel functions\n')
-        f.write('DEF HAS_NC_PAR = 1\n')
+        f.write('DEF HAS_PARALLEL4_SUPPORT = 1\n')
     else:
         sys.stdout.write('netcdf lib does not have netcdf4 parallel functions\n')
-        f.write('DEF HAS_NC_PAR = 0\n')
+        f.write('DEF HAS_PARALLEL4_SUPPORT = 0\n')
+
+    if has_pnetcdf_support:
+        sys.stdout.write('netcdf lib has pnetcdf parallel functions\n')
+        f.write('DEF HAS_PNETCDF_SUPPORT = 1\n')
+    else:
+        sys.stdout.write('netcdf lib does not have pnetcdf parallel functions\n')
+        f.write('DEF HAS_PNETCDF_SUPPORT = 0\n')
 
     f.close()
 
-    if has_nc_par:
+    if has_parallel4_support or has_pnetcdf_support:
         inc_dirs.append(mpi4py.get_include())
         # mpi_incdir should not be needed if using nc-config
         # (should be included in nc-config --cflags)

From 0a70b6f11d01d7cd61f063bab377880b20f40db6 Mon Sep 17 00:00:00 2001
From: Lars Pastewka 
Date: Tue, 19 Mar 2019 22:34:00 +0100
Subject: [PATCH 0277/1504] install of PnetCDF in Travis install script

---
 .travis.yml                        | 17 +++++++++++++++++
 ci/travis/build-parallel-netcdf.sh |  9 ++++++++-
 2 files changed, 25 insertions(+), 1 deletion(-)

diff --git a/.travis.yml b/.travis.yml
index ac889bcd8..fc2bfb5f8 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -53,6 +53,23 @@ matrix:
             - mpich
             - libmpich-dev
             - libhdf5-mpich-dev
+    # test MPI with latest released version
+    - python: 3.7
+      dist: xenial
+      env: 
+        - MPI=1
+        - CC=mpicc.mpich
+        - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
+        - NETCDF_VERSION=4.6.3
+        - PNETCDF_VERSION=1.11.0
+        - NETCDF_DIR=$HOME
+        - PATH=${NETCDF_DIR}/bin:${PATH} # pick up nc-config here
+      addons:
+        apt:
+          packages:
+            - mpich
+            - libmpich-dev
+            - libhdf5-mpich-dev
     # test with netcdf-c from github master
     - python: 3.7
       dist: xenial
diff --git a/ci/travis/build-parallel-netcdf.sh b/ci/travis/build-parallel-netcdf.sh
index 4035351fc..1b70eed44 100755
--- a/ci/travis/build-parallel-netcdf.sh
+++ b/ci/travis/build-parallel-netcdf.sh
@@ -4,6 +4,13 @@ set -e
 
 echo "Using downloaded netCDF version ${NETCDF_VERSION} with parallel capabilities enabled"
 pushd /tmp
+if [ -n "${PNETCDF_VERSION}" ]; then
+	wget https://parallel-netcdf.github.io/Release/pnetcdf-${PNETCDF_VERSION}.tar.gz
+	tar -xzf pnetcdf-${PNETCDF_VERSION}.tar.gz
+	pushd pnetcdf-${PNETCDF_VERSION}
+	./configure --prefix $NETCDF_DIR --enable-shared --disable-fortran --disable-cxx
+	NETCDF_EXTRA_CONFIG="--enable-pnetcdf"
+fi
 if [ ${NETCDF_VERSION} == "GITMASTER" ]; then
    git clone http://github.com/Unidata/netcdf-c netcdf-c
    pushd netcdf-c
@@ -16,7 +23,7 @@ fi
 # for Ubuntu xenial
 export CPPFLAGS="-I/usr/include/hdf5/mpich"
 export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
-./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap --enable-parallel
+./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap --enable-parallel ${NETCDF_EXTRA_CONFIG}
 make -j 2
 make install
 popd

From 5277dcc5cf7784e0cc58e03ea98db5f40ea64363 Mon Sep 17 00:00:00 2001
From: Lars Pastewka 
Date: Tue, 19 Mar 2019 22:36:29 +0100
Subject: [PATCH 0278/1504] updated test runner, __has_nc_par__ no longer
 exists

---
 test/run_all.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/test/run_all.py b/test/run_all.py
index 2388d5fde..c229039c9 100755
--- a/test/run_all.py
+++ b/test/run_all.py
@@ -1,7 +1,7 @@
 import glob, os, sys, unittest, struct
 from netCDF4 import getlibversion,__hdf5libversion__,__netcdf4libversion__,__version__
-from netCDF4 import __has_cdf5_format__, __has_nc_inq_path__, __has_nc_par__,\
-                    __has_nc_create_mem__
+from netCDF4 import __has_cdf5_format__, __has_nc_inq_path__, __has_nc_create_mem__, \
+                    __has_parallel4_support__, __has_pnetcdf_support__
 
 # can also just run
 # python -m unittest discover . 'tst*py'
@@ -16,7 +16,7 @@
 else:
     test_files.remove('tst_unicode3.py')
     sys.stdout.write('not running tst_unicode3.py ...\n')
-if __netcdf4libversion__ < '4.2.1' or __has_nc_par__:
+if __netcdf4libversion__ < '4.2.1' or __has_parallel4_support__ or __has_pnetcdf_support__:
     test_files.remove('tst_diskless.py')
     sys.stdout.write('not running tst_diskless.py ...\n')
 if not __has_nc_inq_path__:

From 530b08f74b8be9a903e0279836e6990fa9419bed Mon Sep 17 00:00:00 2001
From: barronh 
Date: Tue, 19 Mar 2019 17:37:44 -0400
Subject: [PATCH 0279/1504] Adding share option; not docs yet

---
 netCDF4/_netCDF4.pyx | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index bd8a83f1e..8c52371e2 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2179,7 +2179,7 @@ strings.
             # **this causes parallel mode to fail when both hdf5-parallel and
             # pnetcdf are enabled - issue #820 **
             #_set_default_format(format='NETCDF3_64BIT_OFFSET')
-        elif mode == 'r':
+        elif mode in ('r', 'rs'):
             if memory is not None:
                 IF HAS_NC_OPEN_MEM:
                     # Store reference to memory
@@ -2202,7 +2202,12 @@ strings.
             elif diskless:
                 ierr = nc_open(path, NC_NOWRITE | NC_DISKLESS, &grpid)
             else:
-                ierr = nc_open(path, NC_NOWRITE, &grpid)
+		if mode == 'rs':
+                    # NC_SHARE is very important for reading large
+                    # netcdf files
+                    ierr = nc_open(path, NC_NOWRITE | NC_SHARE, &grpid)
+		else:
+                    ierr = nc_open(path, NC_NOWRITE, &grpid)
         elif mode == 'r+' or mode == 'a':
             if parallel:
                 IF HAS_NC_PAR:

From 604fb5fd0093e4ccd2402c1fa9f4e162499d4934 Mon Sep 17 00:00:00 2001
From: Lars Pastewka 
Date: Tue, 19 Mar 2019 22:47:14 +0100
Subject: [PATCH 0280/1504] compile and install PnetCDF library if version is
 specified

---
 ci/travis/build-parallel-netcdf.sh | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/ci/travis/build-parallel-netcdf.sh b/ci/travis/build-parallel-netcdf.sh
index 1b70eed44..fccceeda8 100755
--- a/ci/travis/build-parallel-netcdf.sh
+++ b/ci/travis/build-parallel-netcdf.sh
@@ -2,15 +2,19 @@
 
 set -e
 
-echo "Using downloaded netCDF version ${NETCDF_VERSION} with parallel capabilities enabled"
 pushd /tmp
 if [ -n "${PNETCDF_VERSION}" ]; then
+	echo "Using downloaded PnetCDF version ${PNETCDF_VERSION}"
 	wget https://parallel-netcdf.github.io/Release/pnetcdf-${PNETCDF_VERSION}.tar.gz
 	tar -xzf pnetcdf-${PNETCDF_VERSION}.tar.gz
 	pushd pnetcdf-${PNETCDF_VERSION}
 	./configure --prefix $NETCDF_DIR --enable-shared --disable-fortran --disable-cxx
 	NETCDF_EXTRA_CONFIG="--enable-pnetcdf"
+	make -j 2
+	make install
+	popd
 fi
+echo "Using downloaded netCDF version ${NETCDF_VERSION} with parallel capabilities enabled"
 if [ ${NETCDF_VERSION} == "GITMASTER" ]; then
    git clone http://github.com/Unidata/netcdf-c netcdf-c
    pushd netcdf-c

From e25d52262b64d9669db23746bc691822cf2481bd Mon Sep 17 00:00:00 2001
From: Lars Pastewka 
Date: Tue, 19 Mar 2019 23:00:54 +0100
Subject: [PATCH 0281/1504] added PnetCDF lib and include locations to compiler
 flags

---
 ci/travis/build-parallel-netcdf.sh | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/ci/travis/build-parallel-netcdf.sh b/ci/travis/build-parallel-netcdf.sh
index fccceeda8..5b020af25 100755
--- a/ci/travis/build-parallel-netcdf.sh
+++ b/ci/travis/build-parallel-netcdf.sh
@@ -25,9 +25,10 @@ else
    pushd netcdf-c-${NETCDF_VERSION}
 fi
 # for Ubuntu xenial
-export CPPFLAGS="-I/usr/include/hdf5/mpich"
+export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include"
+export LDFLAGS="-L${NETCDF_DIR}/lib"
 export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
-./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap --enable-parallel ${NETCDF_EXTRA_CONFIG}
+./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap --enable-parallel $NETCDF_EXTRA_CONFIG
 make -j 2
 make install
 popd

From bd4a1b79259094b8b345aa051f726d8bfa21a1c3 Mon Sep 17 00:00:00 2001
From: Lars Pastewka 
Date: Tue, 19 Mar 2019 23:09:41 +0100
Subject: [PATCH 0282/1504] added additional test for parallel I/O of cdf-5
 format

---
 .travis.yml             | 10 ++++++++++
 examples/mpi_example.py |  7 +++++++
 2 files changed, 17 insertions(+)

diff --git a/.travis.yml b/.travis.yml
index fc2bfb5f8..d4b6dab4b 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -113,4 +113,14 @@ script:
          echo "mpi test passed!"
          exit 0
        fi
+       if [ -n "${PNETCDF_VERSION}" ] ; then
+          mpirun.mpich -np 4 python mpi_example.py NETCDF3_64BIT_DATA
+          if [ $? -ne 0 ] ; then
+            echo "PnetCDF mpi test failed!"
+            exit 1
+          else
+            echo "PnetCDF mpi test passed!"
+            exit 0
+          fi
+       fi
     fi
diff --git a/examples/mpi_example.py b/examples/mpi_example.py
index 885984882..1913c6a59 100644
--- a/examples/mpi_example.py
+++ b/examples/mpi_example.py
@@ -1,8 +1,15 @@
 # to run: mpirun -np 4 python mpi_example.py
+import sys
 from mpi4py import MPI
 import numpy as np
 from netCDF4 import Dataset
+if len(sys.argv) == 2:
+	format = sys.argv[1]
+else:
+	format = 'NETCDF4_CLASSIC'
 rank = MPI.COMM_WORLD.rank  # The process ID (integer 0-3 for 4-process run)
+if rank == 0:
+	print('Creating file with format {}'.format(format))
 nc = Dataset('parallel_test.nc', 'w', parallel=True, comm=MPI.COMM_WORLD,
         info=MPI.Info(),format='NETCDF4_CLASSIC')
 # below should work also - MPI_COMM_WORLD and MPI_INFO_NULL will be used.

From 6cd90053c81be70d433e5be3e257922f5882bcd4 Mon Sep 17 00:00:00 2001
From: Lars Pastewka 
Date: Tue, 19 Mar 2019 23:18:44 +0100
Subject: [PATCH 0283/1504] updated docstring

---
 netCDF4/_netCDF4.pyx | 29 +++++++++++++++++------------
 1 file changed, 17 insertions(+), 12 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 7826b58ef..829405450 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -63,9 +63,10 @@ Requires
  If you want [OPeNDAP](http://opendap.org) support, add `--enable-dap`.
  If you want HDF4 SD support, add `--enable-hdf4` and add
  the location of the HDF4 headers and library to `$CPPFLAGS` and `$LDFLAGS`.
- - for MPI parallel IO support, MPI-enabled versions of the HDF5 and netcdf
- libraries are required, as is the [mpi4py](http://mpi4py.scipy.org) python
- module.
+ - for MPI parallel IO support, an MPI-enabled versions of the netcdf library
+ is required, as is the [mpi4py](http://mpi4py.scipy.org) python module.
+ Parallel IO further depends on the existence of MPI-enabled HDF5 or the
+ [PnetCDF](https://parallel-netcdf.github.io/) library.
 
 
 Install
@@ -918,13 +919,14 @@ specified names.
 
 ## 
      13) Parallel IO.
 
-If MPI parallel enabled versions of netcdf and hdf5 are detected, and
-[mpi4py](https://mpi4py.scipy.org) is installed, netcdf4-python will
-be built with parallel IO capabilities enabled.  Since parallel IO
-uses features of HDF5, it can only be used with NETCDF4 or 
-NETCDF4_CLASSIC formatted files. To use parallel IO,
-your program must be running in an MPI environment using
-[mpi4py](https://mpi4py.scipy.org).
+If MPI parallel enabled versions of netcdf and hdf5 or pnetcdf are detected,
+and [mpi4py](https://mpi4py.scipy.org) is installed, netcdf4-python will
+be built with parallel IO capabilities enabled. Parallel IO of NETCDF4 or 
+NETCDF4_CLASSIC formatted files is only available if the MPI parallel HDF5
+library is available. Parallel IO of classic netcdf-3 file formats is only
+available if the [PnetCDF](https://parallel-netcdf.github.io/) library is
+available. To use parallel IO, your program must be running in an MPI
+environment using [mpi4py](https://mpi4py.scipy.org).
 
     :::python
     >>> from mpi4py import MPI
@@ -971,9 +973,12 @@ participate in doing IO. To toggle back and forth between
 the two types of IO, use the `netCDF4.Variable.set_collective`
 `netCDF4.Variable`method. All metadata
 operations (such as creation of groups, types, variables, dimensions, or attributes)
-are collective.  There are a couple of important limitatons of parallel IO:
+are collective.  There are a couple of important limitations of parallel IO:
 
- - only works with NETCDF4 or NETCDF4_CLASSIC formatted files.
+ - parallel IO for NETCDF4 or NETCDF4_CLASSIC formatted files is only available
+   if the netcdf library was compiled with MPI enabled HDF5.
+ - parallel IO for all classic netcdf-3 file formats is only available if the
+   netcdf library was compiled with PnetCDF.
  - If a variable has an unlimited dimension, appending data must be done in collective mode.
    If the write is done in independent mode, the operation will fail with a
    a generic "HDF Error".

From fc725313a1854458824cfe0c70dbea762b6d7f0d Mon Sep 17 00:00:00 2001
From: Lars Pastewka 
Date: Tue, 19 Mar 2019 23:29:17 +0100
Subject: [PATCH 0284/1504] need to pass format string to Dataset

---
 examples/mpi_example.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/mpi_example.py b/examples/mpi_example.py
index 1913c6a59..0bebfe675 100644
--- a/examples/mpi_example.py
+++ b/examples/mpi_example.py
@@ -11,7 +11,7 @@
 if rank == 0:
 	print('Creating file with format {}'.format(format))
 nc = Dataset('parallel_test.nc', 'w', parallel=True, comm=MPI.COMM_WORLD,
-        info=MPI.Info(),format='NETCDF4_CLASSIC')
+        info=MPI.Info(),format=format)
 # below should work also - MPI_COMM_WORLD and MPI_INFO_NULL will be used.
 #nc = Dataset('parallel_test.nc', 'w', parallel=True)
 d = nc.createDimension('dim',4)

From 2a94075f00d5c037a15115c0cc3ad147fcc20625 Mon Sep 17 00:00:00 2001
From: Lars Pastewka 
Date: Wed, 20 Mar 2019 13:15:17 +0100
Subject: [PATCH 0285/1504] --enable-parallel -> --enable-parallel4

---
 ci/travis/build-parallel-netcdf.sh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ci/travis/build-parallel-netcdf.sh b/ci/travis/build-parallel-netcdf.sh
index 5b020af25..a9c211a09 100755
--- a/ci/travis/build-parallel-netcdf.sh
+++ b/ci/travis/build-parallel-netcdf.sh
@@ -28,7 +28,7 @@ fi
 export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include"
 export LDFLAGS="-L${NETCDF_DIR}/lib"
 export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
-./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap --enable-parallel $NETCDF_EXTRA_CONFIG
+./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --disable-dap --enable-parallel4 $NETCDF_EXTRA_CONFIG
 make -j 2
 make install
 popd

From 2630074b32de1b4531443916f4465297ee7e6155 Mon Sep 17 00:00:00 2001
From: Lars Pastewka 
Date: Wed, 20 Mar 2019 16:00:51 +0100
Subject: [PATCH 0286/1504] create mode needs NC_NETCDF4 for NETCDF4_CLASSIC
 mode

---
 netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 829405450..29563c290 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1290,7 +1290,7 @@ _format_dict  = {'NETCDF3_CLASSIC' : NC_FORMAT_CLASSIC,
                  'NETCDF4'         : NC_FORMAT_NETCDF4}
 # create dictionary mapping string identifiers to netcdf create format codes
 _cmode_dict  = {'NETCDF3_CLASSIC' : NC_CLASSIC_MODEL,
-                'NETCDF4_CLASSIC' : NC_CLASSIC_MODEL,
+                'NETCDF4_CLASSIC' : NC_CLASSIC_MODEL | NC_NETCDF4,
                 'NETCDF4'         : NC_NETCDF4}
 IF HAS_CDF5_FORMAT:
     # NETCDF3_64BIT deprecated, saved for compatibility.

From 6b518ea3c7d625c6c1bba0bd6b2f9cb7a277e0fe Mon Sep 17 00:00:00 2001
From: Lars Pastewka 
Date: Wed, 20 Mar 2019 16:00:59 +0100
Subject: [PATCH 0287/1504] print environment variables

---
 .travis.yml | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/.travis.yml b/.travis.yml
index d4b6dab4b..3d535e2d8 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -103,6 +103,8 @@ script:
   - cd test
   - python run_all.py
   - |
+    echo "MPI = ${MPI}"
+    echo "PNETCDF_VERSION = ${PNETCDF_VERSION}"
     if [ $MPI -eq 1 ] ; then
        cd ../examples
        mpirun.mpich -np 4 python mpi_example.py

From 2c71b0e9918efa9029959a0614543b932da8c476 Mon Sep 17 00:00:00 2001
From: Lars Pastewka 
Date: Wed, 20 Mar 2019 16:28:54 +0100
Subject: [PATCH 0288/1504] don't exit script if test is successful

---
 .travis.yml | 2 --
 1 file changed, 2 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index 3d535e2d8..48141f13a 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -113,7 +113,6 @@ script:
          exit 1
        else
          echo "mpi test passed!"
-         exit 0
        fi
        if [ -n "${PNETCDF_VERSION}" ] ; then
           mpirun.mpich -np 4 python mpi_example.py NETCDF3_64BIT_DATA
@@ -122,7 +121,6 @@ script:
             exit 1
           else
             echo "PnetCDF mpi test passed!"
-            exit 0
           fi
        fi
     fi

From 8b04ea2eea6c4c551e5131b363d25727d053f046 Mon Sep 17 00:00:00 2001
From: Lars Pastewka 
Date: Thu, 21 Mar 2019 17:19:07 +0100
Subject: [PATCH 0289/1504] added changelog entry for parallel IO using pnetcdf

---
 Changelog | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/Changelog b/Changelog
index 463addfa2..8f38449f8 100644
--- a/Changelog
+++ b/Changelog
@@ -1,3 +1,8 @@
+ current master
+===============
+ * added support for parallel IO in the classic netcdf-3 formats through the
+   pnetcdf library.
+
  version 1.4.3.2 (tag v1.4.3.2)
 ===============================
  * include missing membuf.pyx file in release source tarball.

From 835ca41af80f0f2287f19a0c2f2b476cf046d611 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 22 Mar 2019 13:43:09 -0600
Subject: [PATCH 0290/1504] prepare for v1.5.0 release

---
 README.md            | 3 +++
 netCDF4/_netCDF4.pyx | 2 +-
 setup.py             | 2 +-
 3 files changed, 5 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 7e90abf56..7840d41f0 100644
--- a/README.md
+++ b/README.md
@@ -10,6 +10,9 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
+03/24/2019: Version [1.5.0](https://pypi.python.org/pypi/netCDF4/1.5.0) released. Parallel IO support for classic
+file formats added using the pnetcdf library (contribution from Lars Pastewka, [pull request #897](https://github.com/Unidata/netcdf4-python/pull/897).
+
 03/08/2019: Version [1.4.3.2](https://pypi.python.org/pypi/netCDF4/1.4.3.2) released. 
 Include missing membuf.pyx file in source tarball. No need to update if you installed
 1.4.3.1 from a binary wheel.
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 29563c290..32accb8ad 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1190,7 +1190,7 @@ except ImportError:
     # python3: zip is already python2's itertools.izip
     pass
 
-__version__ = "1.4.3.2"
+__version__ = "1.5.0"
 
 # Initialize numpy
 import posixpath
diff --git a/setup.py b/setup.py
index 8f1ade563..1b273526c 100644
--- a/setup.py
+++ b/setup.py
@@ -584,7 +584,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 
 setup(name="netCDF4",
       cmdclass=cmdclass,
-      version="1.4.3.2",
+      version="1.5.0",
       long_description="netCDF version 4 has many features not found in earlier versions of the library, such as hierarchical groups, zlib compression, multiple unlimited dimensions, and new data types.  It is implemented on top of HDF5.  This module implements most of the new features, and can read and write netCDF files compatible with older versions of the library.  The API is modelled after Scientific.IO.NetCDF, and should be familiar to users of that module.\n\nThis project is hosted on a `GitHub repository `_ where you may access the most up-to-date source.",
       author="Jeff Whitaker",
       author_email="jeffrey.s.whitaker@noaa.gov",

From 4bfa2356adc9dc0c3380103a7412d2ef1a145d33 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 22 Mar 2019 13:46:56 -0600
Subject: [PATCH 0291/1504] fix typo

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 7840d41f0..d39a787af 100644
--- a/README.md
+++ b/README.md
@@ -11,7 +11,7 @@
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
 03/24/2019: Version [1.5.0](https://pypi.python.org/pypi/netCDF4/1.5.0) released. Parallel IO support for classic
-file formats added using the pnetcdf library (contribution from Lars Pastewka, [pull request #897](https://github.com/Unidata/netcdf4-python/pull/897).
+file formats added using the pnetcdf library (contribution from Lars Pastewka, [pull request #897](https://github.com/Unidata/netcdf4-python/pull/897)).
 
 03/08/2019: Version [1.4.3.2](https://pypi.python.org/pypi/netCDF4/1.4.3.2) released. 
 Include missing membuf.pyx file in source tarball. No need to update if you installed

From 7fe713b2becde6f97d25429a6daf8a34f3e801dc Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 22 Mar 2019 13:59:17 -0600
Subject: [PATCH 0292/1504] update docs

---
 docs/netCDF4/index.html | 731 ++++++++++------------------------------
 1 file changed, 170 insertions(+), 561 deletions(-)

diff --git a/docs/netCDF4/index.html b/docs/netCDF4/index.html
index ce921ebca..e4a3c6fb9 100644
--- a/docs/netCDF4/index.html
+++ b/docs/netCDF4/index.html
@@ -1174,6 +1174,8 @@ 
      Index
      
         
           
   
 
         
@@ -1335,9 +1335,10 @@ 
      Requires
      
  If you want OPeNDAP support, add --enable-dap.
  If you want HDF4 SD support, add --enable-hdf4 and add
  the location of the HDF4 headers and library to $CPPFLAGS and $LDFLAGS.
-
    • for MPI parallel IO support, MPI-enabled versions of the HDF5 and netcdf
- libraries are required, as is the mpi4py python
- module.
      • 
+
    • for MPI parallel IO support, an MPI-enabled versions of the netcdf library
+ is required, as is the mpi4py python module.
+ Parallel IO further depends on the existence of MPI-enabled HDF5 or the
+ PnetCDF library.
      • 
 
    
 
    Install
    
 
      
@@ -2151,13 +2152,14 @@ 
      12) Enum data type.
      
 
 
 
      13) Parallel IO.
      
-
      If MPI parallel enabled versions of netcdf and hdf5 are detected, and
-mpi4py is installed, netcdf4-python will
-be built with parallel IO capabilities enabled.  Since parallel IO
-uses features of HDF5, it can only be used with NETCDF4 or 
-NETCDF4_CLASSIC formatted files. To use parallel IO,
-your program must be running in an MPI environment using
-mpi4py.
      
+
      If MPI parallel enabled versions of netcdf and hdf5 or pnetcdf are detected,
+and mpi4py is installed, netcdf4-python will
+be built with parallel IO capabilities enabled. Parallel IO of NETCDF4 or 
+NETCDF4_CLASSIC formatted files is only available if the MPI parallel HDF5
+library is available. Parallel IO of classic netcdf-3 file formats is only
+available if the PnetCDF library is
+available. To use parallel IO, your program must be running in an MPI
+environment using mpi4py.
      
 
      >>> from mpi4py import MPI
 >>> import numpy as np
 >>> from netCDF4 import Dataset
@@ -2204,9 +2206,12 @@ 
      13) Parallel IO.
      
 the two types of IO, use the set_collective
 Variablemethod. All metadata
 operations (such as creation of groups, types, variables, dimensions, or attributes)
-are collective.  There are a couple of important limitatons of parallel IO:
      
+are collective.  There are a couple of important limitations of parallel IO:
      
 
        
-
      • only works with NETCDF4 or NETCDF4_CLASSIC formatted files.
        • 
+
      • parallel IO for NETCDF4 or NETCDF4_CLASSIC formatted files is only available
+   if the netcdf library was compiled with MPI enabled HDF5.
        • 
+
      • parallel IO for all classic netcdf-3 file formats is only available if the
+   netcdf library was compiled with PnetCDF.
        • 
 
      • If a variable has an unlimited dimension, appending data must be done in collective mode.
    If the write is done in independent mode, the operation will fail with a
    a generic "HDF Error".
        • 
@@ -2616,7 +2621,7 @@ 
        Classes
        
           
        Ancestors (in MRO)
        
           
           
        Class variables
        
             
        
@@ -2747,7 +2752,7 @@ 
        Static methods
        
           
        Ancestors (in MRO)
        
           
          
           
        • Dataset
          • 
-          
        • __builtin__.object
          • 
+          
        • builtins.object
          • 
           
        
           
        Class variables
        
             
        
@@ -3669,7 +3674,7 @@ 
        Static methods
        
           
        Ancestors (in MRO)
        
           
          
           
        • Dimension
          • 
-          
        • __builtin__.object
          • 
+          
        • builtins.object
          • 
           
        
           
        Class variables
        
             
        
@@ -3767,7 +3772,7 @@ 
        Static methods
        
           
        Ancestors (in MRO)
        
           
          
           
        • EnumType
          • 
-          
        • __builtin__.object
          • 
+          
        • builtins.object
          • 
           
        
           
        Class variables
        
             
        
@@ -3855,22 +3860,15 @@ 
        Ancestors (in MRO)
        
           
           
        Class variables
        
             
        
             
        var cmptypes
        
             
-    
        
-     Inheritance:
-       Dataset.cmptypes
-    
        
 
             
   
-    
        The cmptypes dictionary maps the names of
-compound types defined for the Group or Dataset to instances of the
-CompoundType class.
        
   
        
 
        
 
@@ -3878,16 +3876,9 @@ 
        Class variables
        
             
        
             
        var data_model
        
             
-    
        
-     Inheritance:
-       Dataset.data_model
-    
        
 
             
   
-    
        data_model describes the netCDF
-data model version, one of NETCDF3_CLASSIC, NETCDF4,
-NETCDF4_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
        
   
        
 
        
 
@@ -3895,16 +3886,9 @@ 
        Class variables
        
             
        
             
        var dimensions
        
             
-    
        
-     Inheritance:
-       Dataset.dimensions
-    
        
 
             
   
-    
        The dimensions dictionary maps the names of
-dimensions defined for the Group or Dataset to instances of the
-Dimension class.
        
   
        
 
        
 
@@ -3912,18 +3896,9 @@ 
        Class variables
        
             
        
             
        var disk_format
        
             
-    
        
-     Inheritance:
-       Dataset.disk_format
-    
        
 
             
   
-    
        disk_format describes the underlying
-file format, one of NETCDF3, HDF5, HDF4,
-PNETCDF, DAP2, DAP4 or UNDEFINED. Only available if using
-netcdf C library version >= 4.3.1, otherwise will always return
-UNDEFINED.
        
   
        
 
        
 
@@ -3931,16 +3906,9 @@ 
        Class variables
        
             
        
             
        var enumtypes
        
             
-    
        
-     Inheritance:
-       Dataset.enumtypes
-    
        
 
             
   
-    
        The enumtypes dictionary maps the names of
-Enum types defined for the Group or Dataset to instances of the
-EnumType class.
        
   
        
 
        
 
@@ -3948,14 +3916,9 @@ 
        Class variables
        
             
        
             
        var file_format
        
             
-    
        
-     Inheritance:
-       Dataset.file_format
-    
        
 
             
   
-    
        same as data_model, retained for backwards compatibility.
        
   
        
 
        
 
@@ -3963,17 +3926,9 @@ 
        Class variables
        
             
        
             
        var groups
        
             
-    
        
-     Inheritance:
-       Dataset.groups
-    
        
 
             
   
-    
        The groups dictionary maps the names of groups created for
-this Dataset or Group to instances of the Group class (the
-Dataset class is simply a special case of the Group class which
-describes the root group in the netCDF4 file).
        
   
        
 
        
 
@@ -3981,15 +3936,9 @@ 
        Class variables
        
             
        
             
        var keepweakref
        
             
-    
        
-     Inheritance:
-       Dataset.keepweakref
-    
        
 
             
   
-    
        If True, child Dimension and Variables objects only keep weak references to
-the parent Dataset or Group.
        
   
        
 
        
 
@@ -4008,15 +3957,9 @@ 
        Class variables
        
             
        
             
        var parent
        
             
-    
        
-     Inheritance:
-       Dataset.parent
-    
        
 
             
   
-    
        parent is a reference to the parent
-Group instance. None for the root group or Dataset instance
        
   
        
 
        
 
@@ -4024,17 +3967,9 @@ 
        Class variables
        
             
        
             
        var path
        
             
-    
        
-     Inheritance:
-       Dataset.path
-    
        
 
             
   
-    
        path shows the location of the Group in
-the Dataset in a unix directory format (the names of groups in the
-hierarchy separated by backslashes). A Dataset instance is the root
-group, so the path is simply '/'.
        
   
        
 
        
 
@@ -4042,16 +3977,9 @@ 
        Class variables
        
             
        
             
        var variables
        
             
-    
        
-     Inheritance:
-       Dataset.variables
-    
        
 
             
   
-    
        The variables dictionary maps the names of variables
-defined for this Dataset or Group to instances of the Variable
-class.
        
   
        
 
        
 
@@ -4059,16 +3987,9 @@ 
        Class variables
        
             
        
             
        var vltypes
        
             
-    
        
-     Inheritance:
-       Dataset.vltypes
-    
        
 
             
   
-    
        The vltypes dictionary maps the names of
-variable-length types defined for the Group or Dataset to instances of the
-VLType class.
        
   
        
 
        
 
@@ -4105,10 +4026,6 @@ 
        Static methods
        
     
        def close(
        self)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.close
-    
        
 
     
   
@@ -4125,14 +4042,10 @@ 
        Static methods
        
     
        def createCompoundType(
        self, datatype, datatype_name)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.createCompoundType
-    
        
 
     
   
-    
        Creates a new compound data type named datatype_name from the numpy
+    
        Creates a new compound data type named datatype_name from the numpy
 dtype object datatype.
        
 
        Note: If the new compound data type contains other compound data types
 (i.e. it is a 'nested' compound type, where not all of the elements
@@ -4151,14 +4064,10 @@ 
        Static methods
        
     
        def createDimension(
        self, dimname, size=None)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.createDimension
-    
        
 
     
   
-    
        Creates a new dimension with the given dimname and size.
        
+    
        Creates a new dimension with the given dimname and size.
        
 
        size must be a positive integer or None, which stands for
 "unlimited" (default is None). Specifying a size of 0 also
 results in an unlimited dimension. The return value is the Dimension
@@ -4177,14 +4086,10 @@ 
        Static methods
        
     
        def createEnumType(
        self, datatype, datatype_name, enum_dict)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.createEnumType
-    
        
 
     
   
-    
        Creates a new Enum data type named datatype_name from a numpy
+    
        Creates a new Enum data type named datatype_name from a numpy
 integer dtype object datatype, and a python dictionary
 defining the enum fields and values.
        
 
        The return value is the EnumType class instance describing the new
@@ -4200,14 +4105,10 @@ 
        Static methods
        
     
        def createGroup(
        self, groupname)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.createGroup
-    
        
 
     
   
-    
        Creates a new Group with the given groupname.
        
+    
        Creates a new Group with the given groupname.
        
 
        If groupname is specified as a path, using forward slashes as in unix to
 separate components, then intermediate groups will be created as necessary
 (analogous to mkdir -p in unix).  For example,
@@ -4227,14 +4128,10 @@ 
        Static methods
        
     
        def createVLType(
        self, datatype, datatype_name)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.createVLType
-    
        
 
     
   
-    
        Creates a new VLEN data type named datatype_name from a numpy
+    
        Creates a new VLEN data type named datatype_name from a numpy
 dtype object datatype.
        
 
        The return value is the VLType class instance describing the new
 datatype.
        
@@ -4249,14 +4146,10 @@ 
        Static methods
        
     
        def createVariable(
        self, varname, datatype, dimensions=(), zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, fill_value=None)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.createVariable
-    
        
 
     
   
-    
        Creates a new variable with the given varname, datatype, and
+    
        Creates a new variable with the given varname, datatype, and
 dimensions. If dimensions are not given, the variable is assumed to be
 a scalar.
        
 
        If varname is specified as a path, using forward slashes as in unix to
@@ -4366,14 +4259,10 @@ 
        Static methods
        
     
        def delncattr(
        self,name,value)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.delncattr
-    
        
 
     
   
-    
        delete a netCDF dataset or group attribute.  Use if you need to delete a
+    
        delete a netCDF dataset or group attribute.  Use if you need to delete a
 netCDF attribute with the same name as one of the reserved python
 attributes.
        
   
        
@@ -4387,14 +4276,10 @@ 
        Static methods
        
     
        def filepath(
        self,encoding=None)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.filepath
-    
        
 
     
   
-    
        Get the file system path (or the opendap URL) which was used to
+    
        Get the file system path (or the opendap URL) which was used to
 open/create the Dataset. Requires netcdf >= 4.1.2.  The path
 is decoded into a string using sys.getfilesystemencoding() by default, this can be
 changed using the encoding kwarg.
        
@@ -4409,14 +4294,10 @@ 
        Static methods
        
     
        def get_variables_by_attributes(
        ...)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.get_variables_by_attributes
-    
        
 
     
   
-    
        Returns a list of variables that match specific conditions.
        
+    
        Returns a list of variables that match specific conditions.
        
 
        Can pass in key=value parameters and variables are returned that
 contain all of the matches. For example,
        
 
        >>> # Get variables with x-axis attribute.
@@ -4448,14 +4329,10 @@ 
        Static methods
        
     
        def getncattr(
        self,name)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.getncattr
-    
        
 
     
   
-    
        retrieve a netCDF dataset or group attribute.
+    
        retrieve a netCDF dataset or group attribute.
 Use if you need to get a netCDF attribute with the same
 name as one of the reserved python attributes.
        
 
        option kwarg encoding can be used to specify the
@@ -4471,14 +4348,10 @@ 
        Static methods
        
     
        def isopen(
        ...)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.isopen
-    
        
 
     
   
-    
        is the Dataset open or closed?
        
+    
        is the Dataset open or closed?
        
   
        
 
        
 
@@ -4490,14 +4363,10 @@ 
        Static methods
        
     
        def ncattrs(
        self)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.ncattrs
-    
        
 
     
   
-    
        return netCDF global attribute names for this Dataset or Group in a list.
        
+    
        return netCDF global attribute names for this Dataset or Group in a list.
        
   
        
 
        
 
@@ -4509,14 +4378,10 @@ 
        Static methods
        
     
        def renameAttribute(
        self, oldname, newname)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.renameAttribute
-    
        
 
     
   
-    
        rename a Dataset or Group attribute named oldname to newname.
        
+    
        rename a Dataset or Group attribute named oldname to newname.
        
   
        
 
        
 
@@ -4528,14 +4393,10 @@ 
        Static methods
        
     
        def renameDimension(
        self, oldname, newname)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.renameDimension
-    
        
 
     
   
-    
        rename a Dimension named oldname to newname.
        
+    
        rename a Dimension named oldname to newname.
        
   
        
 
        
 
@@ -4547,14 +4408,10 @@ 
        Static methods
        
     
        def renameGroup(
        self, oldname, newname)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.renameGroup
-    
        
 
     
   
-    
        rename a Group named oldname to newname (requires netcdf >= 4.3.1).
        
+    
        rename a Group named oldname to newname (requires netcdf >= 4.3.1).
        
   
        
 
        
 
@@ -4566,14 +4423,10 @@ 
        Static methods
        
     
        def renameVariable(
        self, oldname, newname)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.renameVariable
-    
        
 
     
   
-    
        rename a Variable named oldname to newname
        
+    
        rename a Variable named oldname to newname
        
   
        
 
        
 
@@ -4585,14 +4438,10 @@ 
        Static methods
        
     
        def set_always_mask(
        self, True_or_False)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.set_always_mask
-    
        
 
     
   
-    
        Call set_always_mask for all variables contained in
+    
        Call set_always_mask for all variables contained in
 this Dataset or Group, as well as for all
 variables in all its subgroups.
        
 
        True_or_False: Boolean determining if automatic conversion of
@@ -4612,14 +4461,10 @@ 
        Static methods
        
     
        def set_auto_chartostring(
        self, True_or_False)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.set_auto_chartostring
-    
        
 
     
   
-    
        Call set_auto_chartostring for all variables contained in this Dataset or
+    
        Call set_auto_chartostring for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
        
 
        True_or_False: Boolean determining if automatic conversion of
 all character arrays <--> string arrays should be performed for
@@ -4638,14 +4483,10 @@ 
        Static methods
        
     
        def set_auto_mask(
        self, True_or_False)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.set_auto_mask
-    
        
 
     
   
-    
        Call set_auto_mask for all variables contained in this Dataset or
+    
        Call set_auto_mask for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
        
 
        True_or_False: Boolean determining if automatic conversion to masked arrays
 shall be applied for all variables.
        
@@ -4662,14 +4503,10 @@ 
        Static methods
        
     
        def set_auto_maskandscale(
        self, True_or_False)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.set_auto_maskandscale
-    
        
 
     
   
-    
        Call set_auto_maskandscale for all variables contained in this Dataset or
+    
        Call set_auto_maskandscale for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
        
 
        True_or_False: Boolean determining if automatic conversion to masked arrays
 and variable scaling shall be applied for all variables.
        
@@ -4686,14 +4523,10 @@ 
        Static methods
        
     
        def set_auto_scale(
        self, True_or_False)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.set_auto_scale
-    
        
 
     
   
-    
        Call set_auto_scale for all variables contained in this Dataset or
+    
        Call set_auto_scale for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
        
 
        True_or_False: Boolean determining if automatic variable scaling
 shall be applied for all variables.
        
@@ -4710,14 +4543,10 @@ 
        Static methods
        
     
        def set_fill_off(
        self)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.set_fill_off
-    
        
 
     
   
-    
        Sets the fill mode for a Dataset open for writing to off.
        
+    
        Sets the fill mode for a Dataset open for writing to off.
        
 
        This will prevent the data from being pre-filled with fill values, which
 may result in some performance improvements. However, you must then make
 sure the data is actually written before being read.
        
@@ -4732,14 +4561,10 @@ 
        Static methods
        
     
        def set_fill_on(
        self)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.set_fill_on
-    
        
 
     
   
-    
        Sets the fill mode for a Dataset open for writing to on.
        
+    
        Sets the fill mode for a Dataset open for writing to on.
        
 
        This causes data to be pre-filled with fill values. The fill values can be
 controlled by the variable's _Fill_Value attribute, but is usually
 sufficient to the use the netCDF default _Fill_Value (defined
@@ -4758,14 +4583,10 @@ 
        Static methods
        
     
        def set_ncstring_attrs(
        self, True_or_False)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.set_ncstring_attrs
-    
        
 
     
   
-    
        Call set_ncstring_attrs for all variables contained in
+    
        Call set_ncstring_attrs for all variables contained in
 this Dataset or Group, as well as for all its
 subgroups and their variables.
        
 
        True_or_False: Boolean determining if all string attributes are
@@ -4784,14 +4605,10 @@ 
        Static methods
        
     
        def setncattr(
        self,name,value)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.setncattr
-    
        
 
     
   
-    
        set a netCDF dataset or group attribute using name,value pair.
+    
        set a netCDF dataset or group attribute using name,value pair.
 Use if you need to set a netCDF attribute with the
 with the same name as one of the reserved python attributes.
        
   
        
@@ -4805,14 +4622,10 @@ 
        Static methods
        
     
        def setncattr_string(
        self,name,value)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.setncattr_string
-    
        
 
     
   
-    
        set a netCDF dataset or group string attribute using name,value pair.
+    
        set a netCDF dataset or group string attribute using name,value pair.
 Use if you need to ensure that a netCDF attribute is created with type
 NC_STRING if the file format is NETCDF4.
        
   
        
@@ -4826,14 +4639,10 @@ 
        Static methods
        
     
        def setncatts(
        self,attdict)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.setncatts
-    
        
 
     
   
-    
        set a bunch of netCDF dataset or group attributes at once using a python dictionary.
+    
        set a bunch of netCDF dataset or group attributes at once using a python dictionary.
 This may be faster when setting a lot of attributes for a NETCDF3
 formatted file, since nc_redef/nc_enddef is not called in between setting
 each attribute
        
@@ -4848,14 +4657,10 @@ 
        Static methods
        
     
        def sync(
        self)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.sync
-    
        
 
     
   
-    
        Writes all buffered data in the Dataset to the disk file.
        
+    
        Writes all buffered data in the Dataset to the disk file.
        
   
        
 
        
 
@@ -4900,22 +4705,15 @@ 
        Ancestors (in MRO)
        
           
           
        Class variables
        
             
        
             
        var cmptypes
        
             
-    
        
-     Inheritance:
-       Dataset.cmptypes
-    
        
 
             
   
-    
        The cmptypes dictionary maps the names of
-compound types defined for the Group or Dataset to instances of the
-CompoundType class.
        
   
        
 
        
 
@@ -4923,16 +4721,9 @@ 
        Class variables
        
             
        
             
        var data_model
        
             
-    
        
-     Inheritance:
-       Dataset.data_model
-    
        
 
             
   
-    
        data_model describes the netCDF
-data model version, one of NETCDF3_CLASSIC, NETCDF4,
-NETCDF4_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
        
   
        
 
        
 
@@ -4940,16 +4731,9 @@ 
        Class variables
        
             
        
             
        var dimensions
        
             
-    
        
-     Inheritance:
-       Dataset.dimensions
-    
        
 
             
   
-    
        The dimensions dictionary maps the names of
-dimensions defined for the Group or Dataset to instances of the
-Dimension class.
        
   
        
 
        
 
@@ -4957,18 +4741,9 @@ 
        Class variables
        
             
        
             
        var disk_format
        
             
-    
        
-     Inheritance:
-       Dataset.disk_format
-    
        
 
             
   
-    
        disk_format describes the underlying
-file format, one of NETCDF3, HDF5, HDF4,
-PNETCDF, DAP2, DAP4 or UNDEFINED. Only available if using
-netcdf C library version >= 4.3.1, otherwise will always return
-UNDEFINED.
        
   
        
 
        
 
@@ -4976,16 +4751,9 @@ 
        Class variables
        
             
        
             
        var enumtypes
        
             
-    
        
-     Inheritance:
-       Dataset.enumtypes
-    
        
 
             
   
-    
        The enumtypes dictionary maps the names of
-Enum types defined for the Group or Dataset to instances of the
-EnumType class.
        
   
        
 
        
 
@@ -4993,14 +4761,9 @@ 
        Class variables
        
             
        
             
        var file_format
        
             
-    
        
-     Inheritance:
-       Dataset.file_format
-    
        
 
             
   
-    
        same as data_model, retained for backwards compatibility.
        
   
        
 
        
 
@@ -5008,17 +4771,9 @@ 
        Class variables
        
             
        
             
        var groups
        
             
-    
        
-     Inheritance:
-       Dataset.groups
-    
        
 
             
   
-    
        The groups dictionary maps the names of groups created for
-this Dataset or Group to instances of the Group class (the
-Dataset class is simply a special case of the Group class which
-describes the root group in the netCDF4 file).
        
   
        
 
        
 
@@ -5026,15 +4781,9 @@ 
        Class variables
        
             
        
             
        var keepweakref
        
             
-    
        
-     Inheritance:
-       Dataset.keepweakref
-    
        
 
             
   
-    
        If True, child Dimension and Variables objects only keep weak references to
-the parent Dataset or Group.
        
   
        
 
        
 
@@ -5042,15 +4791,9 @@ 
        Class variables
        
             
        
             
        var parent
        
             
-    
        
-     Inheritance:
-       Dataset.parent
-    
        
 
             
   
-    
        parent is a reference to the parent
-Group instance. None for the root group or Dataset instance
        
   
        
 
        
 
@@ -5058,17 +4801,9 @@ 
        Class variables
        
             
        
             
        var path
        
             
-    
        
-     Inheritance:
-       Dataset.path
-    
        
 
             
   
-    
        path shows the location of the Group in
-the Dataset in a unix directory format (the names of groups in the
-hierarchy separated by backslashes). A Dataset instance is the root
-group, so the path is simply '/'.
        
   
        
 
        
 
@@ -5076,16 +4811,9 @@ 
        Class variables
        
             
        
             
        var variables
        
             
-    
        
-     Inheritance:
-       Dataset.variables
-    
        
 
             
   
-    
        The variables dictionary maps the names of variables
-defined for this Dataset or Group to instances of the Variable
-class.
        
   
        
 
        
 
@@ -5093,16 +4821,9 @@ 
        Class variables
        
             
        
             
        var vltypes
        
             
-    
        
-     Inheritance:
-       Dataset.vltypes
-    
        
 
             
   
-    
        The vltypes dictionary maps the names of
-variable-length types defined for the Group or Dataset to instances of the
-VLType class.
        
   
        
 
        
 
@@ -5110,18 +4831,74 @@ 
        Class variables
        
           
        Static methods
        
             
   
        
-    
        
-    
        def createCompoundType(
        self, datatype, datatype_name)
        
+    
        
+    
        def __init__(
        self, files, check=False, aggdim=None, exclude=[], master_file=None)
        
     
        
     
     
        
      Inheritance:
-       Dataset.createCompoundType
+       Dataset.__init__
     
        
 
     
   
-    
        Creates a new compound data type named datatype_name from the numpy
+    
        __init__(self, files, check=False, aggdim=None, exclude=[],
+master_file=None)
        
+
        Open a Dataset spanning multiple files, making it look as if it was a
+single file. Variables in the list of files that share the same
+dimension (specified with the keyword aggdim) are aggregated. If
+aggdim is not specified, the unlimited is aggregated.  Currently,
+aggdim must be the leftmost (slowest varying) dimension of each
+of the variables to be aggregated.
        
+
        files: either a sequence of netCDF files or a string with a
+wildcard (converted to a sorted list of files using glob)  If
+the master_file kwarg is not specified, the first file
+in the list will become the "master" file, defining all the
+variables with an aggregation dimension which may span
+subsequent files. Attribute access returns attributes only from "master"
+file. The files are always opened in read-only mode.
        
+
        check: True if you want to do consistency checking to ensure the
+correct variables structure for all of the netcdf files.  Checking makes
+the initialization of the MFDataset instance much slower. Default is
+False.
        
+
        aggdim: The name of the dimension to aggregate over (must
+be the leftmost dimension of each of the variables to be aggregated).
+If None (default), aggregate over the unlimited dimension.
        
+
        exclude: A list of variable names to exclude from aggregation.
+Default is an empty list.
        
+
        master_file: file to use as "master file", defining all the
+variables with an aggregation dimension and all global attributes.
        
+  
        
+
        
+
+  
        
+  
+            
+  
        
+    
        
+    
        def close(
        self)
        
+    
        
+    
+
+    
+  
+    
        close(self)
        
+
        close all the open files.
        
+  
        
+
        
+
+  
        
+  
+            
+  
        
+    
        
+    
        def createCompoundType(
        self, datatype, datatype_name)
        
+    
        
+    
+
+    
+  
+    
        Creates a new compound data type named datatype_name from the numpy
 dtype object datatype.
        
 
        Note: If the new compound data type contains other compound data types
 (i.e. it is a 'nested' compound type, where not all of the elements
@@ -5140,14 +4917,10 @@ 
        Static methods
        
     
        def createDimension(
        self, dimname, size=None)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.createDimension
-    
        
 
     
   
-    
        Creates a new dimension with the given dimname and size.
        
+    
        Creates a new dimension with the given dimname and size.
        
 
        size must be a positive integer or None, which stands for
 "unlimited" (default is None). Specifying a size of 0 also
 results in an unlimited dimension. The return value is the Dimension
@@ -5166,14 +4939,10 @@ 
        Static methods
        
     
        def createEnumType(
        self, datatype, datatype_name, enum_dict)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.createEnumType
-    
        
 
     
   
-    
        Creates a new Enum data type named datatype_name from a numpy
+    
        Creates a new Enum data type named datatype_name from a numpy
 integer dtype object datatype, and a python dictionary
 defining the enum fields and values.
        
 
        The return value is the EnumType class instance describing the new
@@ -5189,14 +4958,10 @@ 
        Static methods
        
     
        def createGroup(
        self, groupname)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.createGroup
-    
        
 
     
   
-    
        Creates a new Group with the given groupname.
        
+    
        Creates a new Group with the given groupname.
        
 
        If groupname is specified as a path, using forward slashes as in unix to
 separate components, then intermediate groups will be created as necessary
 (analogous to mkdir -p in unix).  For example,
@@ -5216,14 +4981,10 @@ 
        Static methods
        
     
        def createVLType(
        self, datatype, datatype_name)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.createVLType
-    
        
 
     
   
-    
        Creates a new VLEN data type named datatype_name from a numpy
+    
        Creates a new VLEN data type named datatype_name from a numpy
 dtype object datatype.
        
 
        The return value is the VLType class instance describing the new
 datatype.
        
@@ -5238,14 +4999,10 @@ 
        Static methods
        
     
        def createVariable(
        self, varname, datatype, dimensions=(), zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, fill_value=None)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.createVariable
-    
        
 
     
   
-    
        Creates a new variable with the given varname, datatype, and
+    
        Creates a new variable with the given varname, datatype, and
 dimensions. If dimensions are not given, the variable is assumed to be
 a scalar.
        
 
        If varname is specified as a path, using forward slashes as in unix to
@@ -5355,14 +5112,10 @@ 
        Static methods
        
     
        def delncattr(
        self,name,value)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.delncattr
-    
        
 
     
   
-    
        delete a netCDF dataset or group attribute.  Use if you need to delete a
+    
        delete a netCDF dataset or group attribute.  Use if you need to delete a
 netCDF attribute with the same name as one of the reserved python
 attributes.
        
   
        
@@ -5376,14 +5129,10 @@ 
        Static methods
        
     
        def filepath(
        self,encoding=None)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.filepath
-    
        
 
     
   
-    
        Get the file system path (or the opendap URL) which was used to
+    
        Get the file system path (or the opendap URL) which was used to
 open/create the Dataset. Requires netcdf >= 4.1.2.  The path
 is decoded into a string using sys.getfilesystemencoding() by default, this can be
 changed using the encoding kwarg.
        
@@ -5398,14 +5147,10 @@ 
        Static methods
        
     
        def get_variables_by_attributes(
        ...)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.get_variables_by_attributes
-    
        
 
     
   
-    
        Returns a list of variables that match specific conditions.
        
+    
        Returns a list of variables that match specific conditions.
        
 
        Can pass in key=value parameters and variables are returned that
 contain all of the matches. For example,
        
 
        >>> # Get variables with x-axis attribute.
@@ -5437,14 +5182,10 @@ 
        Static methods
        
     
        def getncattr(
        self,name)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.getncattr
-    
        
 
     
   
-    
        retrieve a netCDF dataset or group attribute.
+    
        retrieve a netCDF dataset or group attribute.
 Use if you need to get a netCDF attribute with the same
 name as one of the reserved python attributes.
        
 
        option kwarg encoding can be used to specify the
@@ -5460,14 +5201,26 @@ 
        Static methods
        
     
        def isopen(
        ...)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.isopen
-    
        
 
     
   
-    
        is the Dataset open or closed?
        
+    
        is the Dataset open or closed?
        
+  
        
+
        
+
+  
        
+  
+            
+  
        
+    
        
+    
        def ncattrs(
        self)
        
+    
        
+    
+
+    
+  
+    
        ncattrs(self)
        
+
        return the netcdf attribute names from the master file.
        
   
        
 
        
 
@@ -5479,14 +5232,10 @@ 
        Static methods
        
     
        def renameAttribute(
        self, oldname, newname)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.renameAttribute
-    
        
 
     
   
-    
        rename a Dataset or Group attribute named oldname to newname.
        
+    
        rename a Dataset or Group attribute named oldname to newname.
        
   
        
 
        
 
@@ -5498,14 +5247,10 @@ 
        Static methods
        
     
        def renameDimension(
        self, oldname, newname)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.renameDimension
-    
        
 
     
   
-    
        rename a Dimension named oldname to newname.
        
+    
        rename a Dimension named oldname to newname.
        
   
        
 
        
 
@@ -5517,14 +5262,10 @@ 
        Static methods
        
     
        def renameGroup(
        self, oldname, newname)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.renameGroup
-    
        
 
     
   
-    
        rename a Group named oldname to newname (requires netcdf >= 4.3.1).
        
+    
        rename a Group named oldname to newname (requires netcdf >= 4.3.1).
        
   
        
 
        
 
@@ -5536,14 +5277,10 @@ 
        Static methods
        
     
        def renameVariable(
        self, oldname, newname)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.renameVariable
-    
        
 
     
   
-    
        rename a Variable named oldname to newname
        
+    
        rename a Variable named oldname to newname
        
   
        
 
        
 
@@ -5555,14 +5292,10 @@ 
        Static methods
        
     
        def set_always_mask(
        self, True_or_False)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.set_always_mask
-    
        
 
     
   
-    
        Call set_always_mask for all variables contained in
+    
        Call set_always_mask for all variables contained in
 this Dataset or Group, as well as for all
 variables in all its subgroups.
        
 
        True_or_False: Boolean determining if automatic conversion of
@@ -5582,14 +5315,10 @@ 
        Static methods
        
     
        def set_auto_chartostring(
        self, True_or_False)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.set_auto_chartostring
-    
        
 
     
   
-    
        Call set_auto_chartostring for all variables contained in this Dataset or
+    
        Call set_auto_chartostring for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
        
 
        True_or_False: Boolean determining if automatic conversion of
 all character arrays <--> string arrays should be performed for
@@ -5608,14 +5337,10 @@ 
        Static methods
        
     
        def set_auto_mask(
        self, True_or_False)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.set_auto_mask
-    
        
 
     
   
-    
        Call set_auto_mask for all variables contained in this Dataset or
+    
        Call set_auto_mask for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
        
 
        True_or_False: Boolean determining if automatic conversion to masked arrays
 shall be applied for all variables.
        
@@ -5632,14 +5357,10 @@ 
        Static methods
        
     
        def set_auto_maskandscale(
        self, True_or_False)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.set_auto_maskandscale
-    
        
 
     
   
-    
        Call set_auto_maskandscale for all variables contained in this Dataset or
+    
        Call set_auto_maskandscale for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
        
 
        True_or_False: Boolean determining if automatic conversion to masked arrays
 and variable scaling shall be applied for all variables.
        
@@ -5656,14 +5377,10 @@ 
        Static methods
        
     
        def set_auto_scale(
        self, True_or_False)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.set_auto_scale
-    
        
 
     
   
-    
        Call set_auto_scale for all variables contained in this Dataset or
+    
        Call set_auto_scale for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
        
 
        True_or_False: Boolean determining if automatic variable scaling
 shall be applied for all variables.
        
@@ -5680,14 +5397,10 @@ 
        Static methods
        
     
        def set_fill_off(
        self)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.set_fill_off
-    
        
 
     
   
-    
        Sets the fill mode for a Dataset open for writing to off.
        
+    
        Sets the fill mode for a Dataset open for writing to off.
        
 
        This will prevent the data from being pre-filled with fill values, which
 may result in some performance improvements. However, you must then make
 sure the data is actually written before being read.
        
@@ -5702,14 +5415,10 @@ 
        Static methods
        
     
        def set_fill_on(
        self)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.set_fill_on
-    
        
 
     
   
-    
        Sets the fill mode for a Dataset open for writing to on.
        
+    
        Sets the fill mode for a Dataset open for writing to on.
        
 
        This causes data to be pre-filled with fill values. The fill values can be
 controlled by the variable's _Fill_Value attribute, but is usually
 sufficient to the use the netCDF default _Fill_Value (defined
@@ -5728,14 +5437,10 @@ 
        Static methods
        
     
        def set_ncstring_attrs(
        self, True_or_False)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.set_ncstring_attrs
-    
        
 
     
   
-    
        Call set_ncstring_attrs for all variables contained in
+    
        Call set_ncstring_attrs for all variables contained in
 this Dataset or Group, as well as for all its
 subgroups and their variables.
        
 
        True_or_False: Boolean determining if all string attributes are
@@ -5754,14 +5459,10 @@ 
        Static methods
        
     
        def setncattr(
        self,name,value)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.setncattr
-    
        
 
     
   
-    
        set a netCDF dataset or group attribute using name,value pair.
+    
        set a netCDF dataset or group attribute using name,value pair.
 Use if you need to set a netCDF attribute with the
 with the same name as one of the reserved python attributes.
        
   
        
@@ -5775,14 +5476,10 @@ 
        Static methods
        
     
        def setncattr_string(
        self,name,value)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.setncattr_string
-    
        
 
     
   
-    
        set a netCDF dataset or group string attribute using name,value pair.
+    
        set a netCDF dataset or group string attribute using name,value pair.
 Use if you need to ensure that a netCDF attribute is created with type
 NC_STRING if the file format is NETCDF4.
        
   
        
@@ -5796,14 +5493,10 @@ 
        Static methods
        
     
        def setncatts(
        self,attdict)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.setncatts
-    
        
 
     
   
-    
        set a bunch of netCDF dataset or group attributes at once using a python dictionary.
+    
        set a bunch of netCDF dataset or group attributes at once using a python dictionary.
 This may be faster when setting a lot of attributes for a NETCDF3
 formatted file, since nc_redef/nc_enddef is not called in between setting
 each attribute
        
@@ -5818,95 +5511,10 @@ 
        Static methods
        
     
        def sync(
        self)
        
     
        
     
-    
        
-     Inheritance:
-       Dataset.sync
-    
        
 
     
   
-    
        Writes all buffered data in the Dataset to the disk file.
        
-  
        
-
        
-
-  
        
-  
-          
        Methods
        
-            
-  
        
-    
        
-    
        def __init__(
        self, files, check=False, aggdim=None, exclude=[], master_file=None)
        
-    
        
-    
-    
        
-     Inheritance:
-       Dataset.__init__
-    
        
-
-    
-  
-    
        Open a Dataset spanning multiple files, making it look as if it was a
-single file. Variables in the list of files that share the same
-dimension (specified with the keyword aggdim) are aggregated. If
-aggdim is not specified, the unlimited is aggregated.  Currently,
-aggdim must be the leftmost (slowest varying) dimension of each
-of the variables to be aggregated.
        
-
        files: either a sequence of netCDF files or a string with a
-wildcard (converted to a sorted list of files using glob)  If
-the master_file kwarg is not specified, the first file
-in the list will become the "master" file, defining all the
-variables with an aggregation dimension which may span
-subsequent files. Attribute access returns attributes only from "master"
-file. The files are always opened in read-only mode.
        
-
        check: True if you want to do consistency checking to ensure the
-correct variables structure for all of the netcdf files.  Checking makes
-the initialization of the MFDataset instance much slower. Default is
-False.
        
-
        aggdim: The name of the dimension to aggregate over (must
-be the leftmost dimension of each of the variables to be aggregated).
-If None (default), aggregate over the unlimited dimension.
        
-
        exclude: A list of variable names to exclude from aggregation.
-Default is an empty list.
        
-
        master_file: file to use as "master file", defining all the
-variables with an aggregation dimension and all global attributes.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def close(
        self)
        
-    
        
-    
-    
        
-     Inheritance:
-       Dataset.close
-    
        
-
-    
-  
-    
        close all the open files.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def ncattrs(
        self)
        
-    
        
-    
-    
        
-     Inheritance:
-       Dataset.ncattrs
-    
        
-
-    
-  
-    
        return the netcdf attribute names from the master file.
        
+    
        Writes all buffered data in the Dataset to the disk file.
        
   
        
 
        
 
@@ -5957,9 +5565,9 @@ 
        Ancestors (in MRO)
        
           
          
           
        • MFTime
          • 
           
        • netCDF4._netCDF4._Variable
          • 
-          
        • __builtin__.object
          • 
+          
        • builtins.object
          • 
           
        
-          
        Methods
        
+          
        Static methods
        
             
   
        
     
        
@@ -5969,7 +5577,8 @@ 
        Methods
        
 
     
   
-    
        Create a time Variable with units consistent across a multifile
+    
        __init__(self, time, units=None, calendar=None)
        
+
        Create a time Variable with units consistent across a multifile
 dataset.
        
 
        time: Time variable from a MFDataset.
        
 
        units: Time units, for example, 'days since 1979-01-01'. If None,
@@ -5986,7 +5595,7 @@ 
        Methods
        
             
   
        
     
        
-    
        def ncattrs(
        ...)
        
+    
        def ncattrs(
        self)
        
     
        
     
 
@@ -6000,7 +5609,7 @@ 
        Methods
        
             
   
        
     
        
-    
        def set_always_mask(
        ...)
        
+    
        def set_always_mask(
        self, val)
        
     
        
     
 
@@ -6014,7 +5623,7 @@ 
        Methods
        
             
   
        
     
        
-    
        def set_auto_chartostring(
        ...)
        
+    
        def set_auto_chartostring(
        self, val)
        
     
        
     
 
@@ -6028,7 +5637,7 @@ 
        Methods
        
             
   
        
     
        
-    
        def set_auto_mask(
        ...)
        
+    
        def set_auto_mask(
        self, val)
        
     
        
     
 
@@ -6042,7 +5651,7 @@ 
        Methods
        
             
   
        
     
        
-    
        def set_auto_maskandscale(
        ...)
        
+    
        def set_auto_maskandscale(
        self, val)
        
     
        
     
 
@@ -6056,7 +5665,7 @@ 
        Methods
        
             
   
        
     
        
-    
        def set_auto_scale(
        ...)
        
+    
        def set_auto_scale(
        self, val)
        
     
        
     
 
@@ -6070,7 +5679,7 @@ 
        Methods
        
             
   
        
     
        
-    
        def typecode(
        ...)
        
+    
        def typecode(
        self)
        
     
        
     
 
@@ -6102,7 +5711,7 @@ 
        Methods
        
           
        Ancestors (in MRO)
        
           
          
           
        • VLType
          • 
-          
        • __builtin__.object
          • 
+          
        • builtins.object
          • 
           
        
           
        Class variables
        
             
        
@@ -6207,7 +5816,7 @@ 
        Static methods
        
           
        Ancestors (in MRO)
        
           
          
           
        • Variable
          • 
-          
        • __builtin__.object
          • 
+          
        • builtins.object
          • 
           
        
           
        Class variables
        
             
        
@@ -6936,7 +6545,7 @@ 
        Static methods
        
   
        
     
        
       Documentation generated by
-      pdoc 0.3.2.dev16
+      pdoc 0.3.2.dev29
     
        
 
     
        pdoc is in the public domain with the

From 05f63b61a032f64d2da6db4a39d76b29cb19ad0f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 22 Mar 2019 14:00:55 -0600
Subject: [PATCH 0293/1504] add link to netCDF4/index.hml

---
 docs/index.html | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 docs/index.html

diff --git a/docs/index.html b/docs/index.html
new file mode 100644
index 000000000..9dfb31fe7
--- /dev/null
+++ b/docs/index.html
@@ -0,0 +1 @@
+

From 9a41fe17f11eb7461393efcb05de075d09197a57 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 23 Mar 2019 12:01:30 -0600
Subject: [PATCH 0294/1504] update version number

---
 PKG-INFO | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/PKG-INFO b/PKG-INFO
index 3b780e07b..3e16f2024 100644
--- a/PKG-INFO
+++ b/PKG-INFO
@@ -1,6 +1,6 @@
 Metadata-Version: 1.1
 Name: netCDF4
-Version: 1.4.3.2
+Version: 1.5.0   
 Author: Jeff Whitaker
 Author-email: jeffrey s whitaker at noaa gov
 Home-page: https://github.com/Unidata/netcdf4-python

From b176d16a283dc73950e68dcf607b3be492ffe0a0 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 23 Mar 2019 12:03:18 -0600
Subject: [PATCH 0295/1504] update

---
 Changelog | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/Changelog b/Changelog
index 8f38449f8..9b4549882 100644
--- a/Changelog
+++ b/Changelog
@@ -1,7 +1,7 @@
- current master
-===============
+ version 1.5.0 (tag v1.5.0rel)
+===============================
  * added support for parallel IO in the classic netcdf-3 formats through the
-   pnetcdf library.
+   pnetcdf library (pull request #897).
 
  version 1.4.3.2 (tag v1.4.3.2)
 ===============================

From da5bce31f680b3fff92da4888164b67a03a2ebdd Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 23 Mar 2019 16:01:37 -0600
Subject: [PATCH 0296/1504] update zenodo link

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index d39a787af..785b508ca 100644
--- a/README.md
+++ b/README.md
@@ -5,7 +5,7 @@
 [![Windows Build Status](https://ci.appveyor.com/api/projects/status/fl9taa9je4e6wi7n/branch/master?svg=true)](https://ci.appveyor.com/project/jswhit/netcdf4-python/branch/master)
 [![PyPI package](https://badge.fury.io/py/netCDF4.svg)](http://python.org/pypi/netCDF4)
 [![Anaconda-Server Badge](https://anaconda.org/conda-forge/netCDF4/badges/version.svg)](https://anaconda.org/conda-forge/netCDF4)
-[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.2592291.svg)](https://doi.org/10.5281/zenodo.2592291)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.2592291.svg)](https://doi.org/10.5281/zenodo.2592290)
 
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).

From adf127d7ceb10c38e0f5ad3deb4a0337263b8070 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 23 Mar 2019 16:04:28 -0600
Subject: [PATCH 0297/1504] update version number in docstring

---
 netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 32accb8ad..a6cb8bd53 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1,5 +1,5 @@
 """
-Version 1.4.3
+Version 1.5.0
 -------------
 - - -
 

From c6d4523b468e95741a7a06cc4feb1e46d6db74d2 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 23 Mar 2019 16:05:43 -0600
Subject: [PATCH 0298/1504] update version number in docs

---
 docs/netCDF4/index.html | 706 +++++++++++++++++++++++++++++++---------
 1 file changed, 551 insertions(+), 155 deletions(-)

diff --git a/docs/netCDF4/index.html b/docs/netCDF4/index.html
index e4a3c6fb9..7c03e6b02 100644
--- a/docs/netCDF4/index.html
+++ b/docs/netCDF4/index.html
@@ -4,7 +4,7 @@
   
 
     netCDF4 API documentation
-    __init__
-    
      • close
        • 
     
      • createCompoundType
        • 
     
      • createDimension
        • 
     
      • createEnumType
        • 
@@ -1187,7 +1185,6 @@ 
        Index
        
     
      • get_variables_by_attributes
        • 
     
      • getncattr
        • 
     
      • isopen
        • 
-    
      • ncattrs
        • 
     
      • renameAttribute
        • 
     
      • renameDimension
        • 
     
      • renameGroup
        • 
@@ -1204,6 +1201,9 @@ 
        Index
        
     
      • setncattr_string
        • 
     
      • setncatts
        • 
     
      • sync
        • 
+    
      • __init__
        • 
+    
      • close
        • 
+    
      • ncattrs
        • 
   
      
 
         
@@ -1280,7 +1280,7 @@ 
      Index
      
 
   
      
   
      netCDF4 module
      
-  
      Version 1.4.3
      
+  
      Version 1.5.0
      
 
      
 
      Introduction
      
 
      netcdf4-python is a Python interface to the netCDF C library.
      
@@ -2621,7 +2621,7 @@ 
      Classes
      
           
      Ancestors (in MRO)
      
           
           
      Class variables
      
             
      
@@ -2752,7 +2752,7 @@ 
      Static methods
      
           
      Ancestors (in MRO)
      
           
        
           
      • Dataset
        • 
-          
      • builtins.object
        • 
+          
      • __builtin__.object
        • 
           
      
           
      Class variables
      
             
      
@@ -3674,7 +3674,7 @@ 
      Static methods
      
           
      Ancestors (in MRO)
      
           
        
           
      • Dimension
        • 
-          
      • builtins.object
        • 
+          
      • __builtin__.object
        • 
           
      
           
      Class variables
      
             
      
@@ -3772,7 +3772,7 @@ 
      Static methods
      
           
      Ancestors (in MRO)
      
           
        
           
      • EnumType
        • 
-          
      • builtins.object
        • 
+          
      • __builtin__.object
        • 
           
      
           
      Class variables
      
             
      
@@ -3860,15 +3860,22 @@ 
      Ancestors (in MRO)
      
           
           
      Class variables
      
             
      
             
      var cmptypes
      
             
+    
      
+     Inheritance:
+       Dataset.cmptypes
+    
      
 
             
   
+    
      The cmptypes dictionary maps the names of
+compound types defined for the Group or Dataset to instances of the
+CompoundType class.
      
   
      
 
      
 
@@ -3876,9 +3883,16 @@ 
      Class variables
      
             
      
             
      var data_model
      
             
+    
      
+     Inheritance:
+       Dataset.data_model
+    
      
 
             
   
+    
      data_model describes the netCDF
+data model version, one of NETCDF3_CLASSIC, NETCDF4,
+NETCDF4_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
      
   
      
 
      
 
@@ -3886,9 +3900,16 @@ 
      Class variables
      
             
      
             
      var dimensions
      
             
+    
      
+     Inheritance:
+       Dataset.dimensions
+    
      
 
             
   
+    
      The dimensions dictionary maps the names of
+dimensions defined for the Group or Dataset to instances of the
+Dimension class.
      
   
      
 
      
 
@@ -3896,9 +3917,18 @@ 
      Class variables
      
             
      
             
      var disk_format
      
             
+    
      
+     Inheritance:
+       Dataset.disk_format
+    
      
 
             
   
+    
      disk_format describes the underlying
+file format, one of NETCDF3, HDF5, HDF4,
+PNETCDF, DAP2, DAP4 or UNDEFINED. Only available if using
+netcdf C library version >= 4.3.1, otherwise will always return
+UNDEFINED.
      
   
      
 
      
 
@@ -3906,9 +3936,16 @@ 
      Class variables
      
             
      
             
      var enumtypes
      
             
+    
      
+     Inheritance:
+       Dataset.enumtypes
+    
      
 
             
   
+    
      The enumtypes dictionary maps the names of
+Enum types defined for the Group or Dataset to instances of the
+EnumType class.
      
   
      
 
      
 
@@ -3916,9 +3953,14 @@ 
      Class variables
      
             
      
             
      var file_format
      
             
+    
      
+     Inheritance:
+       Dataset.file_format
+    
      
 
             
   
+    
      same as data_model, retained for backwards compatibility.
      
   
      
 
      
 
@@ -3926,9 +3968,17 @@ 
      Class variables
      
             
      
             
      var groups
      
             
+    
      
+     Inheritance:
+       Dataset.groups
+    
      
 
             
   
+    
      The groups dictionary maps the names of groups created for
+this Dataset or Group to instances of the Group class (the
+Dataset class is simply a special case of the Group class which
+describes the root group in the netCDF4 file).
      
   
      
 
      
 
@@ -3936,9 +3986,15 @@ 
      Class variables
      
             
      
             
      var keepweakref
      
             
+    
      
+     Inheritance:
+       Dataset.keepweakref
+    
      
 
             
   
+    
      If True, child Dimension and Variables objects only keep weak references to
+the parent Dataset or Group.
      
   
      
 
      
 
@@ -3957,9 +4013,15 @@ 
      Class variables
      
             
      
             
      var parent
      
             
+    
      
+     Inheritance:
+       Dataset.parent
+    
      
 
             
   
+    
      parent is a reference to the parent
+Group instance. None for the root group or Dataset instance
      
   
      
 
      
 
@@ -3967,9 +4029,17 @@ 
      Class variables
      
             
      
             
      var path
      
             
+    
      
+     Inheritance:
+       Dataset.path
+    
      
 
             
   
+    
      path shows the location of the Group in
+the Dataset in a unix directory format (the names of groups in the
+hierarchy separated by backslashes). A Dataset instance is the root
+group, so the path is simply '/'.
      
   
      
 
      
 
@@ -3977,9 +4047,16 @@ 
      Class variables
      
             
      
             
      var variables
      
             
+    
      
+     Inheritance:
+       Dataset.variables
+    
      
 
             
   
+    
      The variables dictionary maps the names of variables
+defined for this Dataset or Group to instances of the Variable
+class.
      
   
      
 
      
 
@@ -3987,9 +4064,16 @@ 
      Class variables
      
             
      
             
      var vltypes
      
             
+    
      
+     Inheritance:
+       Dataset.vltypes
+    
      
 
             
   
+    
      The vltypes dictionary maps the names of
+variable-length types defined for the Group or Dataset to instances of the
+VLType class.
      
   
      
 
      
 
@@ -4026,6 +4110,10 @@ 
      Static methods
      
     
      def close(
      self)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.close
+    
      
 
     
   
@@ -4042,10 +4130,14 @@ 
      Static methods
      
     
      def createCompoundType(
      self, datatype, datatype_name)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.createCompoundType
+    
      
 
     
   
-    
      Creates a new compound data type named datatype_name from the numpy
+    
      Creates a new compound data type named datatype_name from the numpy
 dtype object datatype.
      
 
      Note: If the new compound data type contains other compound data types
 (i.e. it is a 'nested' compound type, where not all of the elements
@@ -4064,10 +4156,14 @@ 
      Static methods
      
     
      def createDimension(
      self, dimname, size=None)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.createDimension
+    
      
 
     
   
-    
      Creates a new dimension with the given dimname and size.
      
+    
      Creates a new dimension with the given dimname and size.
      
 
      size must be a positive integer or None, which stands for
 "unlimited" (default is None). Specifying a size of 0 also
 results in an unlimited dimension. The return value is the Dimension
@@ -4086,10 +4182,14 @@ 
      Static methods
      
     
      def createEnumType(
      self, datatype, datatype_name, enum_dict)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.createEnumType
+    
      
 
     
   
-    
      Creates a new Enum data type named datatype_name from a numpy
+    
      Creates a new Enum data type named datatype_name from a numpy
 integer dtype object datatype, and a python dictionary
 defining the enum fields and values.
      
 
      The return value is the EnumType class instance describing the new
@@ -4105,10 +4205,14 @@ 
      Static methods
      
     
      def createGroup(
      self, groupname)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.createGroup
+    
      
 
     
   
-    
      Creates a new Group with the given groupname.
      
+    
      Creates a new Group with the given groupname.
      
 
      If groupname is specified as a path, using forward slashes as in unix to
 separate components, then intermediate groups will be created as necessary
 (analogous to mkdir -p in unix).  For example,
@@ -4128,10 +4232,14 @@ 
      Static methods
      
     
      def createVLType(
      self, datatype, datatype_name)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.createVLType
+    
      
 
     
   
-    
      Creates a new VLEN data type named datatype_name from a numpy
+    
      Creates a new VLEN data type named datatype_name from a numpy
 dtype object datatype.
      
 
      The return value is the VLType class instance describing the new
 datatype.
      
@@ -4146,10 +4254,14 @@ 
      Static methods
      
     
      def createVariable(
      self, varname, datatype, dimensions=(), zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, fill_value=None)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.createVariable
+    
      
 
     
   
-    
      Creates a new variable with the given varname, datatype, and
+    
      Creates a new variable with the given varname, datatype, and
 dimensions. If dimensions are not given, the variable is assumed to be
 a scalar.
      
 
      If varname is specified as a path, using forward slashes as in unix to
@@ -4259,10 +4371,14 @@ 
      Static methods
      
     
      def delncattr(
      self,name,value)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.delncattr
+    
      
 
     
   
-    
      delete a netCDF dataset or group attribute.  Use if you need to delete a
+    
      delete a netCDF dataset or group attribute.  Use if you need to delete a
 netCDF attribute with the same name as one of the reserved python
 attributes.
      
   
      
@@ -4276,10 +4392,14 @@ 
      Static methods
      
     
      def filepath(
      self,encoding=None)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.filepath
+    
      
 
     
   
-    
      Get the file system path (or the opendap URL) which was used to
+    
      Get the file system path (or the opendap URL) which was used to
 open/create the Dataset. Requires netcdf >= 4.1.2.  The path
 is decoded into a string using sys.getfilesystemencoding() by default, this can be
 changed using the encoding kwarg.
      
@@ -4294,10 +4414,14 @@ 
      Static methods
      
     
      def get_variables_by_attributes(
      ...)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.get_variables_by_attributes
+    
      
 
     
   
-    
      Returns a list of variables that match specific conditions.
      
+    
      Returns a list of variables that match specific conditions.
      
 
      Can pass in key=value parameters and variables are returned that
 contain all of the matches. For example,
      
 
      >>> # Get variables with x-axis attribute.
@@ -4329,10 +4453,14 @@ 
      Static methods
      
     
      def getncattr(
      self,name)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.getncattr
+    
      
 
     
   
-    
      retrieve a netCDF dataset or group attribute.
+    
      retrieve a netCDF dataset or group attribute.
 Use if you need to get a netCDF attribute with the same
 name as one of the reserved python attributes.
      
 
      option kwarg encoding can be used to specify the
@@ -4348,10 +4476,14 @@ 
      Static methods
      
     
      def isopen(
      ...)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.isopen
+    
      
 
     
   
-    
      is the Dataset open or closed?
      
+    
      is the Dataset open or closed?
      
   
      
 
      
 
@@ -4363,10 +4495,14 @@ 
      Static methods
      
     
      def ncattrs(
      self)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.ncattrs
+    
      
 
     
   
-    
      return netCDF global attribute names for this Dataset or Group in a list.
      
+    
      return netCDF global attribute names for this Dataset or Group in a list.
      
   
      
 
      
 
@@ -4378,10 +4514,14 @@ 
      Static methods
      
     
      def renameAttribute(
      self, oldname, newname)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.renameAttribute
+    
      
 
     
   
-    
      rename a Dataset or Group attribute named oldname to newname.
      
+    
      rename a Dataset or Group attribute named oldname to newname.
      
   
      
 
      
 
@@ -4393,10 +4533,14 @@ 
      Static methods
      
     
      def renameDimension(
      self, oldname, newname)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.renameDimension
+    
      
 
     
   
-    
      rename a Dimension named oldname to newname.
      
+    
      rename a Dimension named oldname to newname.
      
   
      
 
      
 
@@ -4408,10 +4552,14 @@ 
      Static methods
      
     
      def renameGroup(
      self, oldname, newname)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.renameGroup
+    
      
 
     
   
-    
      rename a Group named oldname to newname (requires netcdf >= 4.3.1).
      
+    
      rename a Group named oldname to newname (requires netcdf >= 4.3.1).
      
   
      
 
      
 
@@ -4423,10 +4571,14 @@ 
      Static methods
      
     
      def renameVariable(
      self, oldname, newname)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.renameVariable
+    
      
 
     
   
-    
      rename a Variable named oldname to newname
      
+    
      rename a Variable named oldname to newname
      
   
      
 
      
 
@@ -4438,10 +4590,14 @@ 
      Static methods
      
     
      def set_always_mask(
      self, True_or_False)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.set_always_mask
+    
      
 
     
   
-    
      Call set_always_mask for all variables contained in
+    
      Call set_always_mask for all variables contained in
 this Dataset or Group, as well as for all
 variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic conversion of
@@ -4461,10 +4617,14 @@ 
      Static methods
      
     
      def set_auto_chartostring(
      self, True_or_False)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.set_auto_chartostring
+    
      
 
     
   
-    
      Call set_auto_chartostring for all variables contained in this Dataset or
+    
      Call set_auto_chartostring for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic conversion of
 all character arrays <--> string arrays should be performed for
@@ -4483,10 +4643,14 @@ 
      Static methods
      
     
      def set_auto_mask(
      self, True_or_False)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.set_auto_mask
+    
      
 
     
   
-    
      Call set_auto_mask for all variables contained in this Dataset or
+    
      Call set_auto_mask for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic conversion to masked arrays
 shall be applied for all variables.
      
@@ -4503,10 +4667,14 @@ 
      Static methods
      
     
      def set_auto_maskandscale(
      self, True_or_False)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.set_auto_maskandscale
+    
      
 
     
   
-    
      Call set_auto_maskandscale for all variables contained in this Dataset or
+    
      Call set_auto_maskandscale for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic conversion to masked arrays
 and variable scaling shall be applied for all variables.
      
@@ -4523,10 +4691,14 @@ 
      Static methods
      
     
      def set_auto_scale(
      self, True_or_False)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.set_auto_scale
+    
      
 
     
   
-    
      Call set_auto_scale for all variables contained in this Dataset or
+    
      Call set_auto_scale for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic variable scaling
 shall be applied for all variables.
      
@@ -4543,10 +4715,14 @@ 
      Static methods
      
     
      def set_fill_off(
      self)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.set_fill_off
+    
      
 
     
   
-    
      Sets the fill mode for a Dataset open for writing to off.
      
+    
      Sets the fill mode for a Dataset open for writing to off.
      
 
      This will prevent the data from being pre-filled with fill values, which
 may result in some performance improvements. However, you must then make
 sure the data is actually written before being read.
      
@@ -4561,10 +4737,14 @@ 
      Static methods
      
     
      def set_fill_on(
      self)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.set_fill_on
+    
      
 
     
   
-    
      Sets the fill mode for a Dataset open for writing to on.
      
+    
      Sets the fill mode for a Dataset open for writing to on.
      
 
      This causes data to be pre-filled with fill values. The fill values can be
 controlled by the variable's _Fill_Value attribute, but is usually
 sufficient to the use the netCDF default _Fill_Value (defined
@@ -4583,10 +4763,14 @@ 
      Static methods
      
     
      def set_ncstring_attrs(
      self, True_or_False)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.set_ncstring_attrs
+    
      
 
     
   
-    
      Call set_ncstring_attrs for all variables contained in
+    
      Call set_ncstring_attrs for all variables contained in
 this Dataset or Group, as well as for all its
 subgroups and their variables.
      
 
      True_or_False: Boolean determining if all string attributes are
@@ -4605,10 +4789,14 @@ 
      Static methods
      
     
      def setncattr(
      self,name,value)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.setncattr
+    
      
 
     
   
-    
      set a netCDF dataset or group attribute using name,value pair.
+    
      set a netCDF dataset or group attribute using name,value pair.
 Use if you need to set a netCDF attribute with the
 with the same name as one of the reserved python attributes.
      
   
      
@@ -4622,10 +4810,14 @@ 
      Static methods
      
     
      def setncattr_string(
      self,name,value)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.setncattr_string
+    
      
 
     
   
-    
      set a netCDF dataset or group string attribute using name,value pair.
+    
      set a netCDF dataset or group string attribute using name,value pair.
 Use if you need to ensure that a netCDF attribute is created with type
 NC_STRING if the file format is NETCDF4.
      
   
      
@@ -4639,10 +4831,14 @@ 
      Static methods
      
     
      def setncatts(
      self,attdict)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.setncatts
+    
      
 
     
   
-    
      set a bunch of netCDF dataset or group attributes at once using a python dictionary.
+    
      set a bunch of netCDF dataset or group attributes at once using a python dictionary.
 This may be faster when setting a lot of attributes for a NETCDF3
 formatted file, since nc_redef/nc_enddef is not called in between setting
 each attribute
      
@@ -4657,10 +4853,14 @@ 
      Static methods
      
     
      def sync(
      self)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.sync
+    
      
 
     
   
-    
      Writes all buffered data in the Dataset to the disk file.
      
+    
      Writes all buffered data in the Dataset to the disk file.
      
   
      
 
      
 
@@ -4705,15 +4905,22 @@ 
      Ancestors (in MRO)
      
           
           
      Class variables
      
             
      
             
      var cmptypes
      
             
+    
      
+     Inheritance:
+       Dataset.cmptypes
+    
      
 
             
   
+    
      The cmptypes dictionary maps the names of
+compound types defined for the Group or Dataset to instances of the
+CompoundType class.
      
   
      
 
      
 
@@ -4721,9 +4928,16 @@ 
      Class variables
      
             
      
             
      var data_model
      
             
+    
      
+     Inheritance:
+       Dataset.data_model
+    
      
 
             
   
+    
      data_model describes the netCDF
+data model version, one of NETCDF3_CLASSIC, NETCDF4,
+NETCDF4_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
      
   
      
 
      
 
@@ -4731,9 +4945,16 @@ 
      Class variables
      
             
      
             
      var dimensions
      
             
+    
      
+     Inheritance:
+       Dataset.dimensions
+    
      
 
             
   
+    
      The dimensions dictionary maps the names of
+dimensions defined for the Group or Dataset to instances of the
+Dimension class.
      
   
      
 
      
 
@@ -4741,9 +4962,18 @@ 
      Class variables
      
             
      
             
      var disk_format
      
             
+    
      
+     Inheritance:
+       Dataset.disk_format
+    
      
 
             
   
+    
      disk_format describes the underlying
+file format, one of NETCDF3, HDF5, HDF4,
+PNETCDF, DAP2, DAP4 or UNDEFINED. Only available if using
+netcdf C library version >= 4.3.1, otherwise will always return
+UNDEFINED.
      
   
      
 
      
 
@@ -4751,9 +4981,16 @@ 
      Class variables
      
             
      
             
      var enumtypes
      
             
+    
      
+     Inheritance:
+       Dataset.enumtypes
+    
      
 
             
   
+    
      The enumtypes dictionary maps the names of
+Enum types defined for the Group or Dataset to instances of the
+EnumType class.
      
   
      
 
      
 
@@ -4761,9 +4998,14 @@ 
      Class variables
      
             
      
             
      var file_format
      
             
+    
      
+     Inheritance:
+       Dataset.file_format
+    
      
 
             
   
+    
      same as data_model, retained for backwards compatibility.
      
   
      
 
      
 
@@ -4771,9 +5013,17 @@ 
      Class variables
      
             
      
             
      var groups
      
             
+    
      
+     Inheritance:
+       Dataset.groups
+    
      
 
             
   
+    
      The groups dictionary maps the names of groups created for
+this Dataset or Group to instances of the Group class (the
+Dataset class is simply a special case of the Group class which
+describes the root group in the netCDF4 file).
      
   
      
 
      
 
@@ -4781,9 +5031,15 @@ 
      Class variables
      
             
      
             
      var keepweakref
      
             
+    
      
+     Inheritance:
+       Dataset.keepweakref
+    
      
 
             
   
+    
      If True, child Dimension and Variables objects only keep weak references to
+the parent Dataset or Group.
      
   
      
 
      
 
@@ -4791,9 +5047,15 @@ 
      Class variables
      
             
      
             
      var parent
      
             
+    
      
+     Inheritance:
+       Dataset.parent
+    
      
 
             
   
+    
      parent is a reference to the parent
+Group instance. None for the root group or Dataset instance
      
   
      
 
      
 
@@ -4801,9 +5063,17 @@ 
      Class variables
      
             
      
             
      var path
      
             
+    
      
+     Inheritance:
+       Dataset.path
+    
      
 
             
   
+    
      path shows the location of the Group in
+the Dataset in a unix directory format (the names of groups in the
+hierarchy separated by backslashes). A Dataset instance is the root
+group, so the path is simply '/'.
      
   
      
 
      
 
@@ -4811,9 +5081,16 @@ 
      Class variables
      
             
      
             
      var variables
      
             
+    
      
+     Inheritance:
+       Dataset.variables
+    
      
 
             
   
+    
      The variables dictionary maps the names of variables
+defined for this Dataset or Group to instances of the Variable
+class.
      
   
      
 
      
 
@@ -4821,84 +5098,35 @@ 
      Class variables
      
             
      
             
      var vltypes
      
             
-
-            
-  
-  
      
-
      
-
-            
      
-          
      Static methods
      
-            
-  
      
-    
      
-    
      def __init__(
      self, files, check=False, aggdim=None, exclude=[], master_file=None)
      
-    
      
-    
     
      
      Inheritance:
-       Dataset.__init__
+       Dataset.vltypes
     
      
 
-    
-  
-    
      __init__(self, files, check=False, aggdim=None, exclude=[],
-master_file=None)
      
-
      Open a Dataset spanning multiple files, making it look as if it was a
-single file. Variables in the list of files that share the same
-dimension (specified with the keyword aggdim) are aggregated. If
-aggdim is not specified, the unlimited is aggregated.  Currently,
-aggdim must be the leftmost (slowest varying) dimension of each
-of the variables to be aggregated.
      
-
      files: either a sequence of netCDF files or a string with a
-wildcard (converted to a sorted list of files using glob)  If
-the master_file kwarg is not specified, the first file
-in the list will become the "master" file, defining all the
-variables with an aggregation dimension which may span
-subsequent files. Attribute access returns attributes only from "master"
-file. The files are always opened in read-only mode.
      
-
      check: True if you want to do consistency checking to ensure the
-correct variables structure for all of the netcdf files.  Checking makes
-the initialization of the MFDataset instance much slower. Default is
-False.
      
-
      aggdim: The name of the dimension to aggregate over (must
-be the leftmost dimension of each of the variables to be aggregated).
-If None (default), aggregate over the unlimited dimension.
      
-
      exclude: A list of variable names to exclude from aggregation.
-Default is an empty list.
      
-
      master_file: file to use as "master file", defining all the
-variables with an aggregation dimension and all global attributes.
      
-  
      
-
      
-
-  
      
-  
             
-  
      
-    
      
-    
      def close(
      self)
      
-    
      
-    
-
-    
   
-    
      close(self)
      
-
      close all the open files.
      
+    
      The vltypes dictionary maps the names of
+variable-length types defined for the Group or Dataset to instances of the
+VLType class.
      
   
      
 
      
 
-  
      
-  
+            
      
+          
      Static methods
      
             
   
      
     
      
     
      def createCompoundType(
      self, datatype, datatype_name)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.createCompoundType
+    
      
 
     
   
-    
      Creates a new compound data type named datatype_name from the numpy
+    
      Creates a new compound data type named datatype_name from the numpy
 dtype object datatype.
      
 
      Note: If the new compound data type contains other compound data types
 (i.e. it is a 'nested' compound type, where not all of the elements
@@ -4917,10 +5145,14 @@ 
      Static methods
      
     
      def createDimension(
      self, dimname, size=None)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.createDimension
+    
      
 
     
   
-    
      Creates a new dimension with the given dimname and size.
      
+    
      Creates a new dimension with the given dimname and size.
      
 
      size must be a positive integer or None, which stands for
 "unlimited" (default is None). Specifying a size of 0 also
 results in an unlimited dimension. The return value is the Dimension
@@ -4939,10 +5171,14 @@ 
      Static methods
      
     
      def createEnumType(
      self, datatype, datatype_name, enum_dict)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.createEnumType
+    
      
 
     
   
-    
      Creates a new Enum data type named datatype_name from a numpy
+    
      Creates a new Enum data type named datatype_name from a numpy
 integer dtype object datatype, and a python dictionary
 defining the enum fields and values.
      
 
      The return value is the EnumType class instance describing the new
@@ -4958,10 +5194,14 @@ 
      Static methods
      
     
      def createGroup(
      self, groupname)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.createGroup
+    
      
 
     
   
-    
      Creates a new Group with the given groupname.
      
+    
      Creates a new Group with the given groupname.
      
 
      If groupname is specified as a path, using forward slashes as in unix to
 separate components, then intermediate groups will be created as necessary
 (analogous to mkdir -p in unix).  For example,
@@ -4981,10 +5221,14 @@ 
      Static methods
      
     
      def createVLType(
      self, datatype, datatype_name)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.createVLType
+    
      
 
     
   
-    
      Creates a new VLEN data type named datatype_name from a numpy
+    
      Creates a new VLEN data type named datatype_name from a numpy
 dtype object datatype.
      
 
      The return value is the VLType class instance describing the new
 datatype.
      
@@ -4999,10 +5243,14 @@ 
      Static methods
      
     
      def createVariable(
      self, varname, datatype, dimensions=(), zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, fill_value=None)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.createVariable
+    
      
 
     
   
-    
      Creates a new variable with the given varname, datatype, and
+    
      Creates a new variable with the given varname, datatype, and
 dimensions. If dimensions are not given, the variable is assumed to be
 a scalar.
      
 
      If varname is specified as a path, using forward slashes as in unix to
@@ -5112,10 +5360,14 @@ 
      Static methods
      
     
      def delncattr(
      self,name,value)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.delncattr
+    
      
 
     
   
-    
      delete a netCDF dataset or group attribute.  Use if you need to delete a
+    
      delete a netCDF dataset or group attribute.  Use if you need to delete a
 netCDF attribute with the same name as one of the reserved python
 attributes.
      
   
      
@@ -5129,10 +5381,14 @@ 
      Static methods
      
     
      def filepath(
      self,encoding=None)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.filepath
+    
      
 
     
   
-    
      Get the file system path (or the opendap URL) which was used to
+    
      Get the file system path (or the opendap URL) which was used to
 open/create the Dataset. Requires netcdf >= 4.1.2.  The path
 is decoded into a string using sys.getfilesystemencoding() by default, this can be
 changed using the encoding kwarg.
      
@@ -5147,10 +5403,14 @@ 
      Static methods
      
     
      def get_variables_by_attributes(
      ...)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.get_variables_by_attributes
+    
      
 
     
   
-    
      Returns a list of variables that match specific conditions.
      
+    
      Returns a list of variables that match specific conditions.
      
 
      Can pass in key=value parameters and variables are returned that
 contain all of the matches. For example,
      
 
      >>> # Get variables with x-axis attribute.
@@ -5182,10 +5442,14 @@ 
      Static methods
      
     
      def getncattr(
      self,name)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.getncattr
+    
      
 
     
   
-    
      retrieve a netCDF dataset or group attribute.
+    
      retrieve a netCDF dataset or group attribute.
 Use if you need to get a netCDF attribute with the same
 name as one of the reserved python attributes.
      
 
      option kwarg encoding can be used to specify the
@@ -5201,26 +5465,14 @@ 
      Static methods
      
     
      def isopen(
      ...)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.isopen
+    
      
 
     
   
-    
      is the Dataset open or closed?
      
-  
      
-
      
-
-  
      
-  
-            
-  
      
-    
      
-    
      def ncattrs(
      self)
      
-    
      
-    
-
-    
-  
-    
      ncattrs(self)
      
-
      return the netcdf attribute names from the master file.
      
+    
      is the Dataset open or closed?
      
   
      
 
      
 
@@ -5232,10 +5484,14 @@ 
      Static methods
      
     
      def renameAttribute(
      self, oldname, newname)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.renameAttribute
+    
      
 
     
   
-    
      rename a Dataset or Group attribute named oldname to newname.
      
+    
      rename a Dataset or Group attribute named oldname to newname.
      
   
      
 
      
 
@@ -5247,10 +5503,14 @@ 
      Static methods
      
     
      def renameDimension(
      self, oldname, newname)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.renameDimension
+    
      
 
     
   
-    
      rename a Dimension named oldname to newname.
      
+    
      rename a Dimension named oldname to newname.
      
   
      
 
      
 
@@ -5262,10 +5522,14 @@ 
      Static methods
      
     
      def renameGroup(
      self, oldname, newname)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.renameGroup
+    
      
 
     
   
-    
      rename a Group named oldname to newname (requires netcdf >= 4.3.1).
      
+    
      rename a Group named oldname to newname (requires netcdf >= 4.3.1).
      
   
      
 
      
 
@@ -5277,10 +5541,14 @@ 
      Static methods
      
     
      def renameVariable(
      self, oldname, newname)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.renameVariable
+    
      
 
     
   
-    
      rename a Variable named oldname to newname
      
+    
      rename a Variable named oldname to newname
      
   
      
 
      
 
@@ -5292,10 +5560,14 @@ 
      Static methods
      
     
      def set_always_mask(
      self, True_or_False)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.set_always_mask
+    
      
 
     
   
-    
      Call set_always_mask for all variables contained in
+    
      Call set_always_mask for all variables contained in
 this Dataset or Group, as well as for all
 variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic conversion of
@@ -5315,10 +5587,14 @@ 
      Static methods
      
     
      def set_auto_chartostring(
      self, True_or_False)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.set_auto_chartostring
+    
      
 
     
   
-    
      Call set_auto_chartostring for all variables contained in this Dataset or
+    
      Call set_auto_chartostring for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic conversion of
 all character arrays <--> string arrays should be performed for
@@ -5337,10 +5613,14 @@ 
      Static methods
      
     
      def set_auto_mask(
      self, True_or_False)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.set_auto_mask
+    
      
 
     
   
-    
      Call set_auto_mask for all variables contained in this Dataset or
+    
      Call set_auto_mask for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic conversion to masked arrays
 shall be applied for all variables.
      
@@ -5357,10 +5637,14 @@ 
      Static methods
      
     
      def set_auto_maskandscale(
      self, True_or_False)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.set_auto_maskandscale
+    
      
 
     
   
-    
      Call set_auto_maskandscale for all variables contained in this Dataset or
+    
      Call set_auto_maskandscale for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic conversion to masked arrays
 and variable scaling shall be applied for all variables.
      
@@ -5377,10 +5661,14 @@ 
      Static methods
      
     
      def set_auto_scale(
      self, True_or_False)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.set_auto_scale
+    
      
 
     
   
-    
      Call set_auto_scale for all variables contained in this Dataset or
+    
      Call set_auto_scale for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic variable scaling
 shall be applied for all variables.
      
@@ -5397,10 +5685,14 @@ 
      Static methods
      
     
      def set_fill_off(
      self)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.set_fill_off
+    
      
 
     
   
-    
      Sets the fill mode for a Dataset open for writing to off.
      
+    
      Sets the fill mode for a Dataset open for writing to off.
      
 
      This will prevent the data from being pre-filled with fill values, which
 may result in some performance improvements. However, you must then make
 sure the data is actually written before being read.
      
@@ -5415,10 +5707,14 @@ 
      Static methods
      
     
      def set_fill_on(
      self)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.set_fill_on
+    
      
 
     
   
-    
      Sets the fill mode for a Dataset open for writing to on.
      
+    
      Sets the fill mode for a Dataset open for writing to on.
      
 
      This causes data to be pre-filled with fill values. The fill values can be
 controlled by the variable's _Fill_Value attribute, but is usually
 sufficient to the use the netCDF default _Fill_Value (defined
@@ -5437,10 +5733,14 @@ 
      Static methods
      
     
      def set_ncstring_attrs(
      self, True_or_False)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.set_ncstring_attrs
+    
      
 
     
   
-    
      Call set_ncstring_attrs for all variables contained in
+    
      Call set_ncstring_attrs for all variables contained in
 this Dataset or Group, as well as for all its
 subgroups and their variables.
      
 
      True_or_False: Boolean determining if all string attributes are
@@ -5459,10 +5759,14 @@ 
      Static methods
      
     
      def setncattr(
      self,name,value)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.setncattr
+    
      
 
     
   
-    
      set a netCDF dataset or group attribute using name,value pair.
+    
      set a netCDF dataset or group attribute using name,value pair.
 Use if you need to set a netCDF attribute with the
 with the same name as one of the reserved python attributes.
      
   
      
@@ -5476,10 +5780,14 @@ 
      Static methods
      
     
      def setncattr_string(
      self,name,value)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.setncattr_string
+    
      
 
     
   
-    
      set a netCDF dataset or group string attribute using name,value pair.
+    
      set a netCDF dataset or group string attribute using name,value pair.
 Use if you need to ensure that a netCDF attribute is created with type
 NC_STRING if the file format is NETCDF4.
      
   
      
@@ -5493,10 +5801,14 @@ 
      Static methods
      
     
      def setncatts(
      self,attdict)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.setncatts
+    
      
 
     
   
-    
      set a bunch of netCDF dataset or group attributes at once using a python dictionary.
+    
      set a bunch of netCDF dataset or group attributes at once using a python dictionary.
 This may be faster when setting a lot of attributes for a NETCDF3
 formatted file, since nc_redef/nc_enddef is not called in between setting
 each attribute
      
@@ -5511,10 +5823,95 @@ 
      Static methods
      
     
      def sync(
      self)
      
     
      
     
+    
      
+     Inheritance:
+       Dataset.sync
+    
      
 
     
   
-    
      Writes all buffered data in the Dataset to the disk file.
      
+    
      Writes all buffered data in the Dataset to the disk file.
      
+  
      
+
      
+
+  
      
+  
+          
      Methods
      
+            
+  
      
+    
      
+    
      def __init__(
      self, files, check=False, aggdim=None, exclude=[], master_file=None)
      
+    
      
+    
+    
      
+     Inheritance:
+       Dataset.__init__
+    
      
+
+    
+  
+    
      Open a Dataset spanning multiple files, making it look as if it was a
+single file. Variables in the list of files that share the same
+dimension (specified with the keyword aggdim) are aggregated. If
+aggdim is not specified, the unlimited is aggregated.  Currently,
+aggdim must be the leftmost (slowest varying) dimension of each
+of the variables to be aggregated.
      
+
      files: either a sequence of netCDF files or a string with a
+wildcard (converted to a sorted list of files using glob)  If
+the master_file kwarg is not specified, the first file
+in the list will become the "master" file, defining all the
+variables with an aggregation dimension which may span
+subsequent files. Attribute access returns attributes only from "master"
+file. The files are always opened in read-only mode.
      
+
      check: True if you want to do consistency checking to ensure the
+correct variables structure for all of the netcdf files.  Checking makes
+the initialization of the MFDataset instance much slower. Default is
+False.
      
+
      aggdim: The name of the dimension to aggregate over (must
+be the leftmost dimension of each of the variables to be aggregated).
+If None (default), aggregate over the unlimited dimension.
      
+
      exclude: A list of variable names to exclude from aggregation.
+Default is an empty list.
      
+
      master_file: file to use as "master file", defining all the
+variables with an aggregation dimension and all global attributes.
      
+  
      
+
      
+
+  
      
+  
+            
+  
      
+    
      
+    
      def close(
      self)
      
+    
      
+    
+    
      
+     Inheritance:
+       Dataset.close
+    
      
+
+    
+  
+    
      close all the open files.
      
+  
      
+
      
+
+  
      
+  
+            
+  
      
+    
      
+    
      def ncattrs(
      self)
      
+    
      
+    
+    
      
+     Inheritance:
+       Dataset.ncattrs
+    
      
+
+    
+  
+    
      return the netcdf attribute names from the master file.
      
   
      
 
      
 
@@ -5565,9 +5962,9 @@ 
      Ancestors (in MRO)
      
           
        
           
      • MFTime
        • 
           
      • netCDF4._netCDF4._Variable
        • 
-          
      • builtins.object
        • 
+          
      • __builtin__.object
        • 
           
      
-          
      Static methods
      
+          
      Methods
      
             
   
      
     
      
@@ -5577,8 +5974,7 @@ 
      Static methods
      
 
     
   
-    
      __init__(self, time, units=None, calendar=None)
      
-
      Create a time Variable with units consistent across a multifile
+    
      Create a time Variable with units consistent across a multifile
 dataset.
      
 
      time: Time variable from a MFDataset.
      
 
      units: Time units, for example, 'days since 1979-01-01'. If None,
@@ -5595,7 +5991,7 @@ 
      Static methods
      
             
   
      
     
      
-    
      def ncattrs(
      self)
      
+    
      def ncattrs(
      ...)
      
     
      
     
 
@@ -5609,7 +6005,7 @@ 
      Static methods
      
             
   
      
     
      
-    
      def set_always_mask(
      self, val)
      
+    
      def set_always_mask(
      ...)
      
     
      
     
 
@@ -5623,7 +6019,7 @@ 
      Static methods
      
             
   
      
     
      
-    
      def set_auto_chartostring(
      self, val)
      
+    
      def set_auto_chartostring(
      ...)
      
     
      
     
 
@@ -5637,7 +6033,7 @@ 
      Static methods
      
             
   
      
     
      
-    
      def set_auto_mask(
      self, val)
      
+    
      def set_auto_mask(
      ...)
      
     
      
     
 
@@ -5651,7 +6047,7 @@ 
      Static methods
      
             
   
      
     
      
-    
      def set_auto_maskandscale(
      self, val)
      
+    
      def set_auto_maskandscale(
      ...)
      
     
      
     
 
@@ -5665,7 +6061,7 @@ 
      Static methods
      
             
   
      
     
      
-    
      def set_auto_scale(
      self, val)
      
+    
      def set_auto_scale(
      ...)
      
     
      
     
 
@@ -5679,7 +6075,7 @@ 
      Static methods
      
             
   
      
     
      
-    
      def typecode(
      self)
      
+    
      def typecode(
      ...)
      
     
      
     
 
@@ -5711,7 +6107,7 @@ 
      Static methods
      
           
      Ancestors (in MRO)
      
           
        
           
      • VLType
        • 
-          
      • builtins.object
        • 
+          
      • __builtin__.object
        • 
           
      
           
      Class variables
      
             
      
@@ -5816,7 +6212,7 @@ 
      Static methods
      
           
      Ancestors (in MRO)
      
           
        
           
      • Variable
        • 
-          
      • builtins.object
        • 
+          
      • __builtin__.object
        • 
           
      
           
      Class variables
      
             
      
@@ -6545,7 +6941,7 @@ 
      Static methods
      
   
      
     
      
       Documentation generated by
-      pdoc 0.3.2.dev29
+      pdoc 0.3.2.dev16
     
      
 
     
      pdoc is in the public domain with the

From a734c6c0473ea68e867b69d7f4f2b5d2da41dd93 Mon Sep 17 00:00:00 2001
From: barronh 
Date: Sun, 24 Mar 2019 09:58:36 -0400
Subject: [PATCH 0299/1504] Adding read shared mode

netCDF4.Dataset currently has append shared, but no read shared.
There are two circumstances that require read shared. First, read
shared provides access to edits made by other programs as they
become available. Second, read shared makes reading faster than
read.

Shared is already available throught append, but this leads to
confusion when the user does not want append access. By enabling
append, the user may accidentally make edits to a file. This
creates a hesitancy to use as or r+s even when a program
may be enhanced dramatically.
---
 netCDF4/_netCDF4.pyx | 14 ++++++++------
 1 file changed, 8 insertions(+), 6 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 8c52371e2..e7e55967a 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1991,8 +1991,8 @@ strings.
         `netCDF4.Dataset` constructor.
 
         **`filename`**: Name of netCDF file to hold dataset. Can also
-	be a python 3 pathlib instance or the URL of an OpenDAP dataset.  When memory is
-	set this is just used to set the `filepath()`.
+        be a python 3 pathlib instance or the URL of an OpenDAP dataset.  When memory is
+        set this is just used to set the `filepath()`.
 
         **`mode`**: access mode. `r` means read-only; no data can be
         modified. `w` means write; a new file is created, an existing file with
@@ -2202,11 +2202,13 @@ strings.
             elif diskless:
                 ierr = nc_open(path, NC_NOWRITE | NC_DISKLESS, &grpid)
             else:
-		if mode == 'rs':
-                    # NC_SHARE is very important for reading large
-                    # netcdf files
+                if mode == 'rs':
+                    # NC_SHARE is very important for speed reading
+                    # large netcdf3 files with a record dimension.
+                    # Opening as r+s or as implies capability to
+                    # which may be inconsistent with actual access
                     ierr = nc_open(path, NC_NOWRITE | NC_SHARE, &grpid)
-		else:
+                else:
                     ierr = nc_open(path, NC_NOWRITE, &grpid)
         elif mode == 'r+' or mode == 'a':
             if parallel:

From 4dd38cde827e77047fe91bd250462d701d18369d Mon Sep 17 00:00:00 2001
From: barronh 
Date: Tue, 26 Mar 2019 10:17:37 -0400
Subject: [PATCH 0300/1504] Updating doc string

Added r to the options for appending s to.
---
 netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index e7e55967a..ea991b85f 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1998,7 +1998,7 @@ strings.
         modified. `w` means write; a new file is created, an existing file with
         the same name is deleted. `a` and `r+` mean append (in analogy with
         serial files); an existing file is opened for reading and writing.
-        Appending `s` to modes `w`, `r+` or `a` will enable unbuffered shared
+        Appending `s` to modes `r`, `w`, `r+` or `a` will enable unbuffered shared
         access to `NETCDF3_CLASSIC`, `NETCDF3_64BIT_OFFSET` or
         `NETCDF3_64BIT_DATA` formatted files.
         Unbuffered access may be useful even if you don't need shared

From 54f2c5021d461ba9b4283c7fb6f264b37e188875 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 1 Apr 2019 11:42:10 -0600
Subject: [PATCH 0301/1504] prepare for 1.5.0.1 release

---
 Changelog            | 5 +++++
 README.md            | 3 +++
 netCDF4/_netCDF4.pyx | 4 ++--
 setup.py             | 2 +-
 4 files changed, 11 insertions(+), 3 deletions(-)

diff --git a/Changelog b/Changelog
index 9b4549882..e7d67e779 100644
--- a/Changelog
+++ b/Changelog
@@ -1,3 +1,8 @@
+ version 1.5.0.1 (tag v1.5.0.1rel)
+==================================
+ * binary wheels for linux and macosx rebuilt against netcdf-c 4.6.3 (instead
+   of 4.4.1.1).  No changes to source code.
+
  version 1.5.0 (tag v1.5.0rel)
 ===============================
  * added support for parallel IO in the classic netcdf-3 formats through the
diff --git a/README.md b/README.md
index 785b508ca..55470e989 100644
--- a/README.md
+++ b/README.md
@@ -9,6 +9,9 @@
 
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
+ 
+04/02/2019: Version [1.5.0.1](https://pypi.python.org/pypi/netCDF4/1.5.0.1) released. Binary wheels for macos x
+and linux rebuilt with netcdf-c 4.6.3 (instead of 4.4.1.1).  
 
 03/24/2019: Version [1.5.0](https://pypi.python.org/pypi/netCDF4/1.5.0) released. Parallel IO support for classic
 file formats added using the pnetcdf library (contribution from Lars Pastewka, [pull request #897](https://github.com/Unidata/netcdf4-python/pull/897)).
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index a6cb8bd53..f8cf669cf 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1,5 +1,5 @@
 """
-Version 1.5.0
+Version 1.5.0.1
 -------------
 - - -
 
@@ -1190,7 +1190,7 @@ except ImportError:
     # python3: zip is already python2's itertools.izip
     pass
 
-__version__ = "1.5.0"
+__version__ = "1.5.0.1"
 
 # Initialize numpy
 import posixpath
diff --git a/setup.py b/setup.py
index 1b273526c..cd2dfba6e 100644
--- a/setup.py
+++ b/setup.py
@@ -584,7 +584,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 
 setup(name="netCDF4",
       cmdclass=cmdclass,
-      version="1.5.0",
+      version="1.5.0.1",
       long_description="netCDF version 4 has many features not found in earlier versions of the library, such as hierarchical groups, zlib compression, multiple unlimited dimensions, and new data types.  It is implemented on top of HDF5.  This module implements most of the new features, and can read and write netCDF files compatible with older versions of the library.  The API is modelled after Scientific.IO.NetCDF, and should be familiar to users of that module.\n\nThis project is hosted on a `GitHub repository `_ where you may access the most up-to-date source.",
       author="Jeff Whitaker",
       author_email="jeffrey.s.whitaker@noaa.gov",

From fda456145e1f70d972756584c6b7c1c10d9a24fb Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 1 Apr 2019 12:30:28 -0600
Subject: [PATCH 0302/1504] update

---
 Changelog            | 4 +++-
 netCDF4/_netCDF4.pyx | 5 ++---
 2 files changed, 5 insertions(+), 4 deletions(-)

diff --git a/Changelog b/Changelog
index e7d67e779..cb12230b5 100644
--- a/Changelog
+++ b/Changelog
@@ -1,7 +1,9 @@
  version 1.5.0.1 (tag v1.5.0.1rel)
 ==================================
  * binary wheels for linux and macosx rebuilt against netcdf-c 4.6.3 (instead
-   of 4.4.1.1).  No changes to source code.
+   of 4.4.1.1).  
+ * add read-shared mode (mode='rs'). Significantly speeds up reads of NETCDF3
+   files (pull request #902).
 
  version 1.5.0 (tag v1.5.0rel)
 ===============================
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 2c0ec2ab1..edce5f456 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -2225,9 +2225,8 @@ strings.
             else:
                 if mode == 'rs':
                     # NC_SHARE is very important for speed reading
-                    # large netcdf3 files with a record dimension.
-                    # Opening as r+s or as implies capability to
-                    # which may be inconsistent with actual access
+                    # large netcdf3 files with a record dimension
+                    # (pull request #902).
                     ierr = nc_open(path, NC_NOWRITE | NC_SHARE, &grpid)
                 else:
                     ierr = nc_open(path, NC_NOWRITE, &grpid)

From 04a5ebc7a91a2f9c538400a0fae9c5a902902590 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 1 Apr 2019 12:31:45 -0600
Subject: [PATCH 0303/1504] update

---
 README.md | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 55470e989..8e66c78b7 100644
--- a/README.md
+++ b/README.md
@@ -11,7 +11,8 @@
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
  
 04/02/2019: Version [1.5.0.1](https://pypi.python.org/pypi/netCDF4/1.5.0.1) released. Binary wheels for macos x
-and linux rebuilt with netcdf-c 4.6.3 (instead of 4.4.1.1).  
+and linux rebuilt with netcdf-c 4.6.3 (instead of 4.4.1.1).   Added read-shared capability for faster reads
+of NETCDF3 files (mode='rs').
 
 03/24/2019: Version [1.5.0](https://pypi.python.org/pypi/netCDF4/1.5.0) released. Parallel IO support for classic
 file formats added using the pnetcdf library (contribution from Lars Pastewka, [pull request #897](https://github.com/Unidata/netcdf4-python/pull/897)).

From 522e152341a852403e71cabbbfd54e888cb6bfb2 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 1 Apr 2019 16:13:38 -0600
Subject: [PATCH 0304/1504] update docs

---
 docs/netCDF4/index.html | 710 +++++++++-------------------------------
 1 file changed, 157 insertions(+), 553 deletions(-)

diff --git a/docs/netCDF4/index.html b/docs/netCDF4/index.html
index 7c03e6b02..ea2bd51e6 100644
--- a/docs/netCDF4/index.html
+++ b/docs/netCDF4/index.html
@@ -4,14 +4,14 @@
   
 
     netCDF4 API documentation
-    
+netcdf4-python is a Python interface..." />
 
   
   
@@ -1174,6 +1174,8 @@ 
      Index
      
         
           
   
 
         
@@ -1280,7 +1280,7 @@ 
      Index
      
 
   
      
   
      netCDF4 module
      
-  
      Version 1.5.0
      
+  
      Version 1.5.0.1
      
 
      
 
      Introduction
      
 
      netcdf4-python is a Python interface to the netCDF C library.
      
@@ -2621,7 +2621,7 @@ 
      Classes
      
           
      Ancestors (in MRO)
      
           
           
      Class variables
      
             
      
@@ -2752,7 +2752,7 @@ 
      Static methods
      
           
      Ancestors (in MRO)
      
           
        
           
      • Dataset
        • 
-          
      • __builtin__.object
        • 
+          
      • builtins.object
        • 
           
      
           
      Class variables
      
             
      
@@ -2929,7 +2929,7 @@ 
      Static methods
      
 modified. w means write; a new file is created, an existing file with
 the same name is deleted. a and r+ mean append (in analogy with
 serial files); an existing file is opened for reading and writing.
-Appending s to modes w, r+ or a will enable unbuffered shared
+Appending s to modes r, w, r+ or a will enable unbuffered shared
 access to NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET or
 NETCDF3_64BIT_DATA formatted files.
 Unbuffered access may be useful even if you don't need shared
@@ -3674,7 +3674,7 @@ 
      Static methods
      
           
      Ancestors (in MRO)
      
           
        
           
      • Dimension
        • 
-          
      • __builtin__.object
        • 
+          
      • builtins.object
        • 
           
      
           
      Class variables
      
             
      
@@ -3772,7 +3772,7 @@ 
      Static methods
      
           
      Ancestors (in MRO)
      
           
        
           
      • EnumType
        • 
-          
      • __builtin__.object
        • 
+          
      • builtins.object
        • 
           
      
           
      Class variables
      
             
      
@@ -3860,22 +3860,15 @@ 
      Ancestors (in MRO)
      
           
           
      Class variables
      
             
      
             
      var cmptypes
      
             
-    
      
-     Inheritance:
-       Dataset.cmptypes
-    
      
 
             
   
-    
      The cmptypes dictionary maps the names of
-compound types defined for the Group or Dataset to instances of the
-CompoundType class.
      
   
      
 
      
 
@@ -3883,16 +3876,9 @@ 
      Class variables
      
             
      
             
      var data_model
      
             
-    
      
-     Inheritance:
-       Dataset.data_model
-    
      
 
             
   
-    
      data_model describes the netCDF
-data model version, one of NETCDF3_CLASSIC, NETCDF4,
-NETCDF4_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
      
   
      
 
      
 
@@ -3900,16 +3886,9 @@ 
      Class variables
      
             
      
             
      var dimensions
      
             
-    
      
-     Inheritance:
-       Dataset.dimensions
-    
      
 
             
   
-    
      The dimensions dictionary maps the names of
-dimensions defined for the Group or Dataset to instances of the
-Dimension class.
      
   
      
 
      
 
@@ -3917,18 +3896,9 @@ 
      Class variables
      
             
      
             
      var disk_format
      
             
-    
      
-     Inheritance:
-       Dataset.disk_format
-    
      
 
             
   
-    
      disk_format describes the underlying
-file format, one of NETCDF3, HDF5, HDF4,
-PNETCDF, DAP2, DAP4 or UNDEFINED. Only available if using
-netcdf C library version >= 4.3.1, otherwise will always return
-UNDEFINED.
      
   
      
 
      
 
@@ -3936,16 +3906,9 @@ 
      Class variables
      
             
      
             
      var enumtypes
      
             
-    
      
-     Inheritance:
-       Dataset.enumtypes
-    
      
 
             
   
-    
      The enumtypes dictionary maps the names of
-Enum types defined for the Group or Dataset to instances of the
-EnumType class.
      
   
      
 
      
 
@@ -3953,14 +3916,9 @@ 
      Class variables
      
             
      
             
      var file_format
      
             
-    
      
-     Inheritance:
-       Dataset.file_format
-    
      
 
             
   
-    
      same as data_model, retained for backwards compatibility.
      
   
      
 
      
 
@@ -3968,17 +3926,9 @@ 
      Class variables
      
             
      
             
      var groups
      
             
-    
      
-     Inheritance:
-       Dataset.groups
-    
      
 
             
   
-    
      The groups dictionary maps the names of groups created for
-this Dataset or Group to instances of the Group class (the
-Dataset class is simply a special case of the Group class which
-describes the root group in the netCDF4 file).
      
   
      
 
      
 
@@ -3986,15 +3936,9 @@ 
      Class variables
      
             
      
             
      var keepweakref
      
             
-    
      
-     Inheritance:
-       Dataset.keepweakref
-    
      
 
             
   
-    
      If True, child Dimension and Variables objects only keep weak references to
-the parent Dataset or Group.
      
   
      
 
      
 
@@ -4013,15 +3957,9 @@ 
      Class variables
      
             
      
             
      var parent
      
             
-    
      
-     Inheritance:
-       Dataset.parent
-    
      
 
             
   
-    
      parent is a reference to the parent
-Group instance. None for the root group or Dataset instance
      
   
      
 
      
 
@@ -4029,17 +3967,9 @@ 
      Class variables
      
             
      
             
      var path
      
             
-    
      
-     Inheritance:
-       Dataset.path
-    
      
 
             
   
-    
      path shows the location of the Group in
-the Dataset in a unix directory format (the names of groups in the
-hierarchy separated by backslashes). A Dataset instance is the root
-group, so the path is simply '/'.
      
   
      
 
      
 
@@ -4047,16 +3977,9 @@ 
      Class variables
      
             
      
             
      var variables
      
             
-    
      
-     Inheritance:
-       Dataset.variables
-    
      
 
             
   
-    
      The variables dictionary maps the names of variables
-defined for this Dataset or Group to instances of the Variable
-class.
      
   
      
 
      
 
@@ -4064,16 +3987,9 @@ 
      Class variables
      
             
      
             
      var vltypes
      
             
-    
      
-     Inheritance:
-       Dataset.vltypes
-    
      
 
             
   
-    
      The vltypes dictionary maps the names of
-variable-length types defined for the Group or Dataset to instances of the
-VLType class.
      
   
      
 
      
 
@@ -4110,10 +4026,6 @@ 
      Static methods
      
     
      def close(
      self)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.close
-    
      
 
     
   
@@ -4130,14 +4042,10 @@ 
      Static methods
      
     
      def createCompoundType(
      self, datatype, datatype_name)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.createCompoundType
-    
      
 
     
   
-    
      Creates a new compound data type named datatype_name from the numpy
+    
      Creates a new compound data type named datatype_name from the numpy
 dtype object datatype.
      
 
      Note: If the new compound data type contains other compound data types
 (i.e. it is a 'nested' compound type, where not all of the elements
@@ -4156,14 +4064,10 @@ 
      Static methods
      
     
      def createDimension(
      self, dimname, size=None)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.createDimension
-    
      
 
     
   
-    
      Creates a new dimension with the given dimname and size.
      
+    
      Creates a new dimension with the given dimname and size.
      
 
      size must be a positive integer or None, which stands for
 "unlimited" (default is None). Specifying a size of 0 also
 results in an unlimited dimension. The return value is the Dimension
@@ -4182,14 +4086,10 @@ 
      Static methods
      
     
      def createEnumType(
      self, datatype, datatype_name, enum_dict)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.createEnumType
-    
      
 
     
   
-    
      Creates a new Enum data type named datatype_name from a numpy
+    
      Creates a new Enum data type named datatype_name from a numpy
 integer dtype object datatype, and a python dictionary
 defining the enum fields and values.
      
 
      The return value is the EnumType class instance describing the new
@@ -4205,14 +4105,10 @@ 
      Static methods
      
     
      def createGroup(
      self, groupname)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.createGroup
-    
      
 
     
   
-    
      Creates a new Group with the given groupname.
      
+    
      Creates a new Group with the given groupname.
      
 
      If groupname is specified as a path, using forward slashes as in unix to
 separate components, then intermediate groups will be created as necessary
 (analogous to mkdir -p in unix).  For example,
@@ -4232,14 +4128,10 @@ 
      Static methods
      
     
      def createVLType(
      self, datatype, datatype_name)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.createVLType
-    
      
 
     
   
-    
      Creates a new VLEN data type named datatype_name from a numpy
+    
      Creates a new VLEN data type named datatype_name from a numpy
 dtype object datatype.
      
 
      The return value is the VLType class instance describing the new
 datatype.
      
@@ -4254,14 +4146,10 @@ 
      Static methods
      
     
      def createVariable(
      self, varname, datatype, dimensions=(), zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, fill_value=None)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.createVariable
-    
      
 
     
   
-    
      Creates a new variable with the given varname, datatype, and
+    
      Creates a new variable with the given varname, datatype, and
 dimensions. If dimensions are not given, the variable is assumed to be
 a scalar.
      
 
      If varname is specified as a path, using forward slashes as in unix to
@@ -4371,14 +4259,10 @@ 
      Static methods
      
     
      def delncattr(
      self,name,value)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.delncattr
-    
      
 
     
   
-    
      delete a netCDF dataset or group attribute.  Use if you need to delete a
+    
      delete a netCDF dataset or group attribute.  Use if you need to delete a
 netCDF attribute with the same name as one of the reserved python
 attributes.
      
   
      
@@ -4392,14 +4276,10 @@ 
      Static methods
      
     
      def filepath(
      self,encoding=None)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.filepath
-    
      
 
     
   
-    
      Get the file system path (or the opendap URL) which was used to
+    
      Get the file system path (or the opendap URL) which was used to
 open/create the Dataset. Requires netcdf >= 4.1.2.  The path
 is decoded into a string using sys.getfilesystemencoding() by default, this can be
 changed using the encoding kwarg.
      
@@ -4414,14 +4294,10 @@ 
      Static methods
      
     
      def get_variables_by_attributes(
      ...)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.get_variables_by_attributes
-    
      
 
     
   
-    
      Returns a list of variables that match specific conditions.
      
+    
      Returns a list of variables that match specific conditions.
      
 
      Can pass in key=value parameters and variables are returned that
 contain all of the matches. For example,
      
 
      >>> # Get variables with x-axis attribute.
@@ -4453,14 +4329,10 @@ 
      Static methods
      
     
      def getncattr(
      self,name)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.getncattr
-    
      
 
     
   
-    
      retrieve a netCDF dataset or group attribute.
+    
      retrieve a netCDF dataset or group attribute.
 Use if you need to get a netCDF attribute with the same
 name as one of the reserved python attributes.
      
 
      option kwarg encoding can be used to specify the
@@ -4476,14 +4348,10 @@ 
      Static methods
      
     
      def isopen(
      ...)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.isopen
-    
      
 
     
   
-    
      is the Dataset open or closed?
      
+    
      is the Dataset open or closed?
      
   
      
 
      
 
@@ -4495,14 +4363,10 @@ 
      Static methods
      
     
      def ncattrs(
      self)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.ncattrs
-    
      
 
     
   
-    
      return netCDF global attribute names for this Dataset or Group in a list.
      
+    
      return netCDF global attribute names for this Dataset or Group in a list.
      
   
      
 
      
 
@@ -4514,14 +4378,10 @@ 
      Static methods
      
     
      def renameAttribute(
      self, oldname, newname)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.renameAttribute
-    
      
 
     
   
-    
      rename a Dataset or Group attribute named oldname to newname.
      
+    
      rename a Dataset or Group attribute named oldname to newname.
      
   
      
 
      
 
@@ -4533,14 +4393,10 @@ 
      Static methods
      
     
      def renameDimension(
      self, oldname, newname)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.renameDimension
-    
      
 
     
   
-    
      rename a Dimension named oldname to newname.
      
+    
      rename a Dimension named oldname to newname.
      
   
      
 
      
 
@@ -4552,14 +4408,10 @@ 
      Static methods
      
     
      def renameGroup(
      self, oldname, newname)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.renameGroup
-    
      
 
     
   
-    
      rename a Group named oldname to newname (requires netcdf >= 4.3.1).
      
+    
      rename a Group named oldname to newname (requires netcdf >= 4.3.1).
      
   
      
 
      
 
@@ -4571,14 +4423,10 @@ 
      Static methods
      
     
      def renameVariable(
      self, oldname, newname)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.renameVariable
-    
      
 
     
   
-    
      rename a Variable named oldname to newname
      
+    
      rename a Variable named oldname to newname
      
   
      
 
      
 
@@ -4590,14 +4438,10 @@ 
      Static methods
      
     
      def set_always_mask(
      self, True_or_False)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.set_always_mask
-    
      
 
     
   
-    
      Call set_always_mask for all variables contained in
+    
      Call set_always_mask for all variables contained in
 this Dataset or Group, as well as for all
 variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic conversion of
@@ -4617,14 +4461,10 @@ 
      Static methods
      
     
      def set_auto_chartostring(
      self, True_or_False)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.set_auto_chartostring
-    
      
 
     
   
-    
      Call set_auto_chartostring for all variables contained in this Dataset or
+    
      Call set_auto_chartostring for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic conversion of
 all character arrays <--> string arrays should be performed for
@@ -4643,14 +4483,10 @@ 
      Static methods
      
     
      def set_auto_mask(
      self, True_or_False)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.set_auto_mask
-    
      
 
     
   
-    
      Call set_auto_mask for all variables contained in this Dataset or
+    
      Call set_auto_mask for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic conversion to masked arrays
 shall be applied for all variables.
      
@@ -4667,14 +4503,10 @@ 
      Static methods
      
     
      def set_auto_maskandscale(
      self, True_or_False)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.set_auto_maskandscale
-    
      
 
     
   
-    
      Call set_auto_maskandscale for all variables contained in this Dataset or
+    
      Call set_auto_maskandscale for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic conversion to masked arrays
 and variable scaling shall be applied for all variables.
      
@@ -4691,14 +4523,10 @@ 
      Static methods
      
     
      def set_auto_scale(
      self, True_or_False)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.set_auto_scale
-    
      
 
     
   
-    
      Call set_auto_scale for all variables contained in this Dataset or
+    
      Call set_auto_scale for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic variable scaling
 shall be applied for all variables.
      
@@ -4715,14 +4543,10 @@ 
      Static methods
      
     
      def set_fill_off(
      self)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.set_fill_off
-    
      
 
     
   
-    
      Sets the fill mode for a Dataset open for writing to off.
      
+    
      Sets the fill mode for a Dataset open for writing to off.
      
 
      This will prevent the data from being pre-filled with fill values, which
 may result in some performance improvements. However, you must then make
 sure the data is actually written before being read.
      
@@ -4737,14 +4561,10 @@ 
      Static methods
      
     
      def set_fill_on(
      self)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.set_fill_on
-    
      
 
     
   
-    
      Sets the fill mode for a Dataset open for writing to on.
      
+    
      Sets the fill mode for a Dataset open for writing to on.
      
 
      This causes data to be pre-filled with fill values. The fill values can be
 controlled by the variable's _Fill_Value attribute, but is usually
 sufficient to the use the netCDF default _Fill_Value (defined
@@ -4763,14 +4583,10 @@ 
      Static methods
      
     
      def set_ncstring_attrs(
      self, True_or_False)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.set_ncstring_attrs
-    
      
 
     
   
-    
      Call set_ncstring_attrs for all variables contained in
+    
      Call set_ncstring_attrs for all variables contained in
 this Dataset or Group, as well as for all its
 subgroups and their variables.
      
 
      True_or_False: Boolean determining if all string attributes are
@@ -4789,14 +4605,10 @@ 
      Static methods
      
     
      def setncattr(
      self,name,value)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.setncattr
-    
      
 
     
   
-    
      set a netCDF dataset or group attribute using name,value pair.
+    
      set a netCDF dataset or group attribute using name,value pair.
 Use if you need to set a netCDF attribute with the
 with the same name as one of the reserved python attributes.
      
   
      
@@ -4810,14 +4622,10 @@ 
      Static methods
      
     
      def setncattr_string(
      self,name,value)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.setncattr_string
-    
      
 
     
   
-    
      set a netCDF dataset or group string attribute using name,value pair.
+    
      set a netCDF dataset or group string attribute using name,value pair.
 Use if you need to ensure that a netCDF attribute is created with type
 NC_STRING if the file format is NETCDF4.
      
   
      
@@ -4831,14 +4639,10 @@ 
      Static methods
      
     
      def setncatts(
      self,attdict)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.setncatts
-    
      
 
     
   
-    
      set a bunch of netCDF dataset or group attributes at once using a python dictionary.
+    
      set a bunch of netCDF dataset or group attributes at once using a python dictionary.
 This may be faster when setting a lot of attributes for a NETCDF3
 formatted file, since nc_redef/nc_enddef is not called in between setting
 each attribute
      
@@ -4853,14 +4657,10 @@ 
      Static methods
      
     
      def sync(
      self)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.sync
-    
      
 
     
   
-    
      Writes all buffered data in the Dataset to the disk file.
      
+    
      Writes all buffered data in the Dataset to the disk file.
      
   
      
 
      
 
@@ -4905,22 +4705,15 @@ 
      Ancestors (in MRO)
      
           
           
      Class variables
      
             
      
             
      var cmptypes
      
             
-    
      
-     Inheritance:
-       Dataset.cmptypes
-    
      
 
             
   
-    
      The cmptypes dictionary maps the names of
-compound types defined for the Group or Dataset to instances of the
-CompoundType class.
      
   
      
 
      
 
@@ -4928,16 +4721,9 @@ 
      Class variables
      
             
      
             
      var data_model
      
             
-    
      
-     Inheritance:
-       Dataset.data_model
-    
      
 
             
   
-    
      data_model describes the netCDF
-data model version, one of NETCDF3_CLASSIC, NETCDF4,
-NETCDF4_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
      
   
      
 
      
 
@@ -4945,16 +4731,9 @@ 
      Class variables
      
             
      
             
      var dimensions
      
             
-    
      
-     Inheritance:
-       Dataset.dimensions
-    
      
 
             
   
-    
      The dimensions dictionary maps the names of
-dimensions defined for the Group or Dataset to instances of the
-Dimension class.
      
   
      
 
      
 
@@ -4962,18 +4741,9 @@ 
      Class variables
      
             
      
             
      var disk_format
      
             
-    
      
-     Inheritance:
-       Dataset.disk_format
-    
      
 
             
   
-    
      disk_format describes the underlying
-file format, one of NETCDF3, HDF5, HDF4,
-PNETCDF, DAP2, DAP4 or UNDEFINED. Only available if using
-netcdf C library version >= 4.3.1, otherwise will always return
-UNDEFINED.
      
   
      
 
      
 
@@ -4981,16 +4751,9 @@ 
      Class variables
      
             
      
             
      var enumtypes
      
             
-    
      
-     Inheritance:
-       Dataset.enumtypes
-    
      
 
             
   
-    
      The enumtypes dictionary maps the names of
-Enum types defined for the Group or Dataset to instances of the
-EnumType class.
      
   
      
 
      
 
@@ -4998,14 +4761,9 @@ 
      Class variables
      
             
      
             
      var file_format
      
             
-    
      
-     Inheritance:
-       Dataset.file_format
-    
      
 
             
   
-    
      same as data_model, retained for backwards compatibility.
      
   
      
 
      
 
@@ -5013,17 +4771,9 @@ 
      Class variables
      
             
      
             
      var groups
      
             
-    
      
-     Inheritance:
-       Dataset.groups
-    
      
 
             
   
-    
      The groups dictionary maps the names of groups created for
-this Dataset or Group to instances of the Group class (the
-Dataset class is simply a special case of the Group class which
-describes the root group in the netCDF4 file).
      
   
      
 
      
 
@@ -5031,15 +4781,9 @@ 
      Class variables
      
             
      
             
      var keepweakref
      
             
-    
      
-     Inheritance:
-       Dataset.keepweakref
-    
      
 
             
   
-    
      If True, child Dimension and Variables objects only keep weak references to
-the parent Dataset or Group.
      
   
      
 
      
 
@@ -5047,15 +4791,9 @@ 
      Class variables
      
             
      
             
      var parent
      
             
-    
      
-     Inheritance:
-       Dataset.parent
-    
      
 
             
   
-    
      parent is a reference to the parent
-Group instance. None for the root group or Dataset instance
      
   
      
 
      
 
@@ -5063,17 +4801,9 @@ 
      Class variables
      
             
      
             
      var path
      
             
-    
      
-     Inheritance:
-       Dataset.path
-    
      
 
             
   
-    
      path shows the location of the Group in
-the Dataset in a unix directory format (the names of groups in the
-hierarchy separated by backslashes). A Dataset instance is the root
-group, so the path is simply '/'.
      
   
      
 
      
 
@@ -5081,16 +4811,9 @@ 
      Class variables
      
             
      
             
      var variables
      
             
-    
      
-     Inheritance:
-       Dataset.variables
-    
      
 
             
   
-    
      The variables dictionary maps the names of variables
-defined for this Dataset or Group to instances of the Variable
-class.
      
   
      
 
      
 
@@ -5098,16 +4821,9 @@ 
      Class variables
      
             
      
             
      var vltypes
      
             
-    
      
-     Inheritance:
-       Dataset.vltypes
-    
      
 
             
   
-    
      The vltypes dictionary maps the names of
-variable-length types defined for the Group or Dataset to instances of the
-VLType class.
      
   
      
 
      
 
@@ -5115,18 +4831,74 @@ 
      Class variables
      
           
      Static methods
      
             
   
      
-    
      
-    
      def createCompoundType(
      self, datatype, datatype_name)
      
+    
      
+    
      def __init__(
      self, files, check=False, aggdim=None, exclude=[], master_file=None)
      
     
      
     
     
      
      Inheritance:
-       Dataset.createCompoundType
+       Dataset.__init__
     
      
 
     
   
-    
      Creates a new compound data type named datatype_name from the numpy
+    
      __init__(self, files, check=False, aggdim=None, exclude=[],
+master_file=None)
      
+
      Open a Dataset spanning multiple files, making it look as if it was a
+single file. Variables in the list of files that share the same
+dimension (specified with the keyword aggdim) are aggregated. If
+aggdim is not specified, the unlimited is aggregated.  Currently,
+aggdim must be the leftmost (slowest varying) dimension of each
+of the variables to be aggregated.
      
+
      files: either a sequence of netCDF files or a string with a
+wildcard (converted to a sorted list of files using glob)  If
+the master_file kwarg is not specified, the first file
+in the list will become the "master" file, defining all the
+variables with an aggregation dimension which may span
+subsequent files. Attribute access returns attributes only from "master"
+file. The files are always opened in read-only mode.
      
+
      check: True if you want to do consistency checking to ensure the
+correct variables structure for all of the netcdf files.  Checking makes
+the initialization of the MFDataset instance much slower. Default is
+False.
      
+
      aggdim: The name of the dimension to aggregate over (must
+be the leftmost dimension of each of the variables to be aggregated).
+If None (default), aggregate over the unlimited dimension.
      
+
      exclude: A list of variable names to exclude from aggregation.
+Default is an empty list.
      
+
      master_file: file to use as "master file", defining all the
+variables with an aggregation dimension and all global attributes.
      
+  
      
+
      
+
+  
      
+  
+            
+  
      
+    
      
+    
      def close(
      self)
      
+    
      
+    
+
+    
+  
+    
      close(self)
      
+
      close all the open files.
      
+  
      
+
      
+
+  
      
+  
+            
+  
      
+    
      
+    
      def createCompoundType(
      self, datatype, datatype_name)
      
+    
      
+    
+
+    
+  
+    
      Creates a new compound data type named datatype_name from the numpy
 dtype object datatype.
      
 
      Note: If the new compound data type contains other compound data types
 (i.e. it is a 'nested' compound type, where not all of the elements
@@ -5145,14 +4917,10 @@ 
      Static methods
      
     
      def createDimension(
      self, dimname, size=None)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.createDimension
-    
      
 
     
   
-    
      Creates a new dimension with the given dimname and size.
      
+    
      Creates a new dimension with the given dimname and size.
      
 
      size must be a positive integer or None, which stands for
 "unlimited" (default is None). Specifying a size of 0 also
 results in an unlimited dimension. The return value is the Dimension
@@ -5171,14 +4939,10 @@ 
      Static methods
      
     
      def createEnumType(
      self, datatype, datatype_name, enum_dict)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.createEnumType
-    
      
 
     
   
-    
      Creates a new Enum data type named datatype_name from a numpy
+    
      Creates a new Enum data type named datatype_name from a numpy
 integer dtype object datatype, and a python dictionary
 defining the enum fields and values.
      
 
      The return value is the EnumType class instance describing the new
@@ -5194,14 +4958,10 @@ 
      Static methods
      
     
      def createGroup(
      self, groupname)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.createGroup
-    
      
 
     
   
-    
      Creates a new Group with the given groupname.
      
+    
      Creates a new Group with the given groupname.
      
 
      If groupname is specified as a path, using forward slashes as in unix to
 separate components, then intermediate groups will be created as necessary
 (analogous to mkdir -p in unix).  For example,
@@ -5221,14 +4981,10 @@ 
      Static methods
      
     
      def createVLType(
      self, datatype, datatype_name)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.createVLType
-    
      
 
     
   
-    
      Creates a new VLEN data type named datatype_name from a numpy
+    
      Creates a new VLEN data type named datatype_name from a numpy
 dtype object datatype.
      
 
      The return value is the VLType class instance describing the new
 datatype.
      
@@ -5243,14 +4999,10 @@ 
      Static methods
      
     
      def createVariable(
      self, varname, datatype, dimensions=(), zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, fill_value=None)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.createVariable
-    
      
 
     
   
-    
      Creates a new variable with the given varname, datatype, and
+    
      Creates a new variable with the given varname, datatype, and
 dimensions. If dimensions are not given, the variable is assumed to be
 a scalar.
      
 
      If varname is specified as a path, using forward slashes as in unix to
@@ -5360,14 +5112,10 @@ 
      Static methods
      
     
      def delncattr(
      self,name,value)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.delncattr
-    
      
 
     
   
-    
      delete a netCDF dataset or group attribute.  Use if you need to delete a
+    
      delete a netCDF dataset or group attribute.  Use if you need to delete a
 netCDF attribute with the same name as one of the reserved python
 attributes.
      
   
      
@@ -5381,14 +5129,10 @@ 
      Static methods
      
     
      def filepath(
      self,encoding=None)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.filepath
-    
      
 
     
   
-    
      Get the file system path (or the opendap URL) which was used to
+    
      Get the file system path (or the opendap URL) which was used to
 open/create the Dataset. Requires netcdf >= 4.1.2.  The path
 is decoded into a string using sys.getfilesystemencoding() by default, this can be
 changed using the encoding kwarg.
      
@@ -5403,14 +5147,10 @@ 
      Static methods
      
     
      def get_variables_by_attributes(
      ...)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.get_variables_by_attributes
-    
      
 
     
   
-    
      Returns a list of variables that match specific conditions.
      
+    
      Returns a list of variables that match specific conditions.
      
 
      Can pass in key=value parameters and variables are returned that
 contain all of the matches. For example,
      
 
      >>> # Get variables with x-axis attribute.
@@ -5442,14 +5182,10 @@ 
      Static methods
      
     
      def getncattr(
      self,name)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.getncattr
-    
      
 
     
   
-    
      retrieve a netCDF dataset or group attribute.
+    
      retrieve a netCDF dataset or group attribute.
 Use if you need to get a netCDF attribute with the same
 name as one of the reserved python attributes.
      
 
      option kwarg encoding can be used to specify the
@@ -5465,14 +5201,26 @@ 
      Static methods
      
     
      def isopen(
      ...)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.isopen
-    
      
 
     
   
-    
      is the Dataset open or closed?
      
+    
      is the Dataset open or closed?
      
+  
      
+
      
+
+  
      
+  
+            
+  
      
+    
      
+    
      def ncattrs(
      self)
      
+    
      
+    
+
+    
+  
+    
      ncattrs(self)
      
+
      return the netcdf attribute names from the master file.
      
   
      
 
      
 
@@ -5484,14 +5232,10 @@ 
      Static methods
      
     
      def renameAttribute(
      self, oldname, newname)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.renameAttribute
-    
      
 
     
   
-    
      rename a Dataset or Group attribute named oldname to newname.
      
+    
      rename a Dataset or Group attribute named oldname to newname.
      
   
      
 
      
 
@@ -5503,14 +5247,10 @@ 
      Static methods
      
     
      def renameDimension(
      self, oldname, newname)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.renameDimension
-    
      
 
     
   
-    
      rename a Dimension named oldname to newname.
      
+    
      rename a Dimension named oldname to newname.
      
   
      
 
      
 
@@ -5522,14 +5262,10 @@ 
      Static methods
      
     
      def renameGroup(
      self, oldname, newname)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.renameGroup
-    
      
 
     
   
-    
      rename a Group named oldname to newname (requires netcdf >= 4.3.1).
      
+    
      rename a Group named oldname to newname (requires netcdf >= 4.3.1).
      
   
      
 
      
 
@@ -5541,14 +5277,10 @@ 
      Static methods
      
     
      def renameVariable(
      self, oldname, newname)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.renameVariable
-    
      
 
     
   
-    
      rename a Variable named oldname to newname
      
+    
      rename a Variable named oldname to newname
      
   
      
 
      
 
@@ -5560,14 +5292,10 @@ 
      Static methods
      
     
      def set_always_mask(
      self, True_or_False)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.set_always_mask
-    
      
 
     
   
-    
      Call set_always_mask for all variables contained in
+    
      Call set_always_mask for all variables contained in
 this Dataset or Group, as well as for all
 variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic conversion of
@@ -5587,14 +5315,10 @@ 
      Static methods
      
     
      def set_auto_chartostring(
      self, True_or_False)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.set_auto_chartostring
-    
      
 
     
   
-    
      Call set_auto_chartostring for all variables contained in this Dataset or
+    
      Call set_auto_chartostring for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic conversion of
 all character arrays <--> string arrays should be performed for
@@ -5613,14 +5337,10 @@ 
      Static methods
      
     
      def set_auto_mask(
      self, True_or_False)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.set_auto_mask
-    
      
 
     
   
-    
      Call set_auto_mask for all variables contained in this Dataset or
+    
      Call set_auto_mask for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic conversion to masked arrays
 shall be applied for all variables.
      
@@ -5637,14 +5357,10 @@ 
      Static methods
      
     
      def set_auto_maskandscale(
      self, True_or_False)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.set_auto_maskandscale
-    
      
 
     
   
-    
      Call set_auto_maskandscale for all variables contained in this Dataset or
+    
      Call set_auto_maskandscale for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic conversion to masked arrays
 and variable scaling shall be applied for all variables.
      
@@ -5661,14 +5377,10 @@ 
      Static methods
      
     
      def set_auto_scale(
      self, True_or_False)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.set_auto_scale
-    
      
 
     
   
-    
      Call set_auto_scale for all variables contained in this Dataset or
+    
      Call set_auto_scale for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
      
 
      True_or_False: Boolean determining if automatic variable scaling
 shall be applied for all variables.
      
@@ -5685,14 +5397,10 @@ 
      Static methods
      
     
      def set_fill_off(
      self)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.set_fill_off
-    
      
 
     
   
-    
      Sets the fill mode for a Dataset open for writing to off.
      
+    
      Sets the fill mode for a Dataset open for writing to off.
      
 
      This will prevent the data from being pre-filled with fill values, which
 may result in some performance improvements. However, you must then make
 sure the data is actually written before being read.
      
@@ -5707,14 +5415,10 @@ 
      Static methods
      
     
      def set_fill_on(
      self)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.set_fill_on
-    
      
 
     
   
-    
      Sets the fill mode for a Dataset open for writing to on.
      
+    
      Sets the fill mode for a Dataset open for writing to on.
      
 
      This causes data to be pre-filled with fill values. The fill values can be
 controlled by the variable's _Fill_Value attribute, but is usually
 sufficient to the use the netCDF default _Fill_Value (defined
@@ -5733,14 +5437,10 @@ 
      Static methods
      
     
      def set_ncstring_attrs(
      self, True_or_False)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.set_ncstring_attrs
-    
      
 
     
   
-    
      Call set_ncstring_attrs for all variables contained in
+    
      Call set_ncstring_attrs for all variables contained in
 this Dataset or Group, as well as for all its
 subgroups and their variables.
      
 
      True_or_False: Boolean determining if all string attributes are
@@ -5759,14 +5459,10 @@ 
      Static methods
      
     
      def setncattr(
      self,name,value)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.setncattr
-    
      
 
     
   
-    
      set a netCDF dataset or group attribute using name,value pair.
+    
      set a netCDF dataset or group attribute using name,value pair.
 Use if you need to set a netCDF attribute with the
 with the same name as one of the reserved python attributes.
      
   
      
@@ -5780,14 +5476,10 @@ 
      Static methods
      
     
      def setncattr_string(
      self,name,value)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.setncattr_string
-    
      
 
     
   
-    
      set a netCDF dataset or group string attribute using name,value pair.
+    
      set a netCDF dataset or group string attribute using name,value pair.
 Use if you need to ensure that a netCDF attribute is created with type
 NC_STRING if the file format is NETCDF4.
      
   
      
@@ -5801,14 +5493,10 @@ 
      Static methods
      
     
      def setncatts(
      self,attdict)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.setncatts
-    
      
 
     
   
-    
      set a bunch of netCDF dataset or group attributes at once using a python dictionary.
+    
      set a bunch of netCDF dataset or group attributes at once using a python dictionary.
 This may be faster when setting a lot of attributes for a NETCDF3
 formatted file, since nc_redef/nc_enddef is not called in between setting
 each attribute
      
@@ -5823,95 +5511,10 @@ 
      Static methods
      
     
      def sync(
      self)
      
     
      
     
-    
      
-     Inheritance:
-       Dataset.sync
-    
      
 
     
   
-    
      Writes all buffered data in the Dataset to the disk file.
      
-  
      
-
      
-
-  
      
-  
-          
      Methods
      
-            
-  
      
-    
      
-    
      def __init__(
      self, files, check=False, aggdim=None, exclude=[], master_file=None)
      
-    
      
-    
-    
      
-     Inheritance:
-       Dataset.__init__
-    
      
-
-    
-  
-    
      Open a Dataset spanning multiple files, making it look as if it was a
-single file. Variables in the list of files that share the same
-dimension (specified with the keyword aggdim) are aggregated. If
-aggdim is not specified, the unlimited is aggregated.  Currently,
-aggdim must be the leftmost (slowest varying) dimension of each
-of the variables to be aggregated.
      
-
      files: either a sequence of netCDF files or a string with a
-wildcard (converted to a sorted list of files using glob)  If
-the master_file kwarg is not specified, the first file
-in the list will become the "master" file, defining all the
-variables with an aggregation dimension which may span
-subsequent files. Attribute access returns attributes only from "master"
-file. The files are always opened in read-only mode.
      
-
      check: True if you want to do consistency checking to ensure the
-correct variables structure for all of the netcdf files.  Checking makes
-the initialization of the MFDataset instance much slower. Default is
-False.
      
-
      aggdim: The name of the dimension to aggregate over (must
-be the leftmost dimension of each of the variables to be aggregated).
-If None (default), aggregate over the unlimited dimension.
      
-
      exclude: A list of variable names to exclude from aggregation.
-Default is an empty list.
      
-
      master_file: file to use as "master file", defining all the
-variables with an aggregation dimension and all global attributes.
      
-  
      
-
      
-
-  
      
-  
-            
-  
      
-    
      
-    
      def close(
      self)
      
-    
      
-    
-    
      
-     Inheritance:
-       Dataset.close
-    
      
-
-    
-  
-    
      close all the open files.
      
-  
      
-
      
-
-  
      
-  
-            
-  
      
-    
      
-    
      def ncattrs(
      self)
      
-    
      
-    
-    
      
-     Inheritance:
-       Dataset.ncattrs
-    
      
-
-    
-  
-    
      return the netcdf attribute names from the master file.
      
+    
      Writes all buffered data in the Dataset to the disk file.
      
   
      
 
      
 
@@ -5962,9 +5565,9 @@ 
      Ancestors (in MRO)
      
           
        
           
      • MFTime
        • 
           
      • netCDF4._netCDF4._Variable
        • 
-          
      • __builtin__.object
        • 
+          
      • builtins.object
        • 
           
      
-          
      Methods
      
+          
      Static methods
      
             
   
      
     
      
@@ -5974,7 +5577,8 @@ 
      Methods
      
 
     
   
-    
      Create a time Variable with units consistent across a multifile
+    
      __init__(self, time, units=None, calendar=None)
      
+
      Create a time Variable with units consistent across a multifile
 dataset.
      
 
      time: Time variable from a MFDataset.
      
 
      units: Time units, for example, 'days since 1979-01-01'. If None,
@@ -5991,7 +5595,7 @@ 
      Methods
      
             
   
      
     
      
-    
      def ncattrs(
      ...)
      
+    
      def ncattrs(
      self)
      
     
      
     
 
@@ -6005,7 +5609,7 @@ 
      Methods
      
             
   
      
     
      
-    
      def set_always_mask(
      ...)
      
+    
      def set_always_mask(
      self, val)
      
     
      
     
 
@@ -6019,7 +5623,7 @@ 
      Methods
      
             
   
      
     
      
-    
      def set_auto_chartostring(
      ...)
      
+    
      def set_auto_chartostring(
      self, val)
      
     
      
     
 
@@ -6033,7 +5637,7 @@ 
      Methods
      
             
   
      
     
      
-    
      def set_auto_mask(
      ...)
      
+    
      def set_auto_mask(
      self, val)
      
     
      
     
 
@@ -6047,7 +5651,7 @@ 
      Methods
      
             
   
      
     
      
-    
      def set_auto_maskandscale(
      ...)
      
+    
      def set_auto_maskandscale(
      self, val)
      
     
      
     
 
@@ -6061,7 +5665,7 @@ 
      Methods
      
             
   
      
     
      
-    
      def set_auto_scale(
      ...)
      
+    
      def set_auto_scale(
      self, val)
      
     
      
     
 
@@ -6075,7 +5679,7 @@ 
      Methods
      
             
   
      
     
      
-    
      def typecode(
      ...)
      
+    
      def typecode(
      self)
      
     
      
     
 
@@ -6107,7 +5711,7 @@ 
      Methods
      
           
      Ancestors (in MRO)
      
           
        
           
      • VLType
        • 
-          
      • __builtin__.object
        • 
+          
      • builtins.object
        • 
           
      
           
      Class variables
      
             
      
@@ -6212,7 +5816,7 @@ 
      Static methods
      
           
      Ancestors (in MRO)
      
           
        
           
      • Variable
        • 
-          
      • __builtin__.object
        • 
+          
      • builtins.object
        • 
           
      
           
      Class variables
      
             
      
@@ -6941,7 +6545,7 @@ 
      Static methods
      
   
      
     
      
       Documentation generated by
-      pdoc 0.3.2.dev16
+      pdoc 0.3.2.dev29
     
      
 
     
      pdoc is in the public domain with the

From e16fd6b02e296c2a5d15a92551d9a25d4f43c2e6 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 7 Apr 2019 15:22:06 -0600
Subject: [PATCH 0305/1504] fix for issue #906

---
 netCDF4/utils.py | 12 +++++++++++-
 1 file changed, 11 insertions(+), 1 deletion(-)

diff --git a/netCDF4/utils.py b/netCDF4/utils.py
index 38204bc2b..ab90c78f6 100644
--- a/netCDF4/utils.py
+++ b/netCDF4/utils.py
@@ -139,7 +139,7 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
     grp  : netCDF Group
       The netCDF group to which the variable being set belongs to.
     datashape : sequence
-      The shape of the data that is being stored. Only needed by __setitime__
+      The shape of the data that is being stored. Only needed by __setitem__
     put : True|False (default False).  If called from __setitem__, put is True.
 
     Returns
@@ -342,6 +342,16 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
         else:
             sdim.append(1)
 
+    # pad datashape with zeros for dimensions not being sliced
+    datashapenew = (); i=0
+    for e in elem:
+        if type(e) != slice:
+            datashapenew = datashapenew + (0,)
+        else:
+            datashapenew = datashapenew + (datashape[i],)
+            i+=1
+    datashape = datashapenew
+
     # Create the start, count, stride and indices arrays.
 
     sdim.append(max(nDims, 1))

From 3039c838c3a0df0aad48b3bb153845ce89f1c817 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 7 Apr 2019 15:40:47 -0600
Subject: [PATCH 0306/1504] update

---
 netCDF4/utils.py | 17 +++++++++--------
 1 file changed, 9 insertions(+), 8 deletions(-)

diff --git a/netCDF4/utils.py b/netCDF4/utils.py
index ab90c78f6..a907e2f48 100644
--- a/netCDF4/utils.py
+++ b/netCDF4/utils.py
@@ -343,14 +343,15 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
             sdim.append(1)
 
     # pad datashape with zeros for dimensions not being sliced
-    datashapenew = (); i=0
-    for e in elem:
-        if type(e) != slice:
-            datashapenew = datashapenew + (0,)
-        else:
-            datashapenew = datashapenew + (datashape[i],)
-            i+=1
-    datashape = datashapenew
+    if datashape:
+        datashapenew = (); i=0
+        for e in elem:
+            if type(e) != slice:
+                datashapenew = datashapenew + (0,)
+            else:
+                datashapenew = datashapenew + (datashape[i],)
+                i+=1
+        datashape = datashapenew
 
     # Create the start, count, stride and indices arrays.
 

From 39bdb1206bb45d0fb6a12bed2a55b02a72606f57 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 7 Apr 2019 16:53:17 -0600
Subject: [PATCH 0307/1504] add test

---
 test/tst_slicing.py | 11 +++++++++++
 1 file changed, 11 insertions(+)

diff --git a/test/tst_slicing.py b/test/tst_slicing.py
index 7fa7cebb9..4dd7b928c 100644
--- a/test/tst_slicing.py
+++ b/test/tst_slicing.py
@@ -211,5 +211,16 @@ def test_issue743(self):
         assert_array_equal(data,data2)
         nc.close()
 
+    def test_issue906(self):
+        f = Dataset('test.nc','w')
+        f.createDimension('d1',3)
+        f.createDimension('d2',None)
+        f.createDimension('d3',5)
+        f.createVariable('v2',np.float,('d1','d2','d3'))
+        f['v2'][:] = np.zeros((3,4,5))
+        f['v2'][0,:,0] = np.arange(4)
+        f['v2'][0,:,:] = np.ones((4,5))
+        f.close()
+
 if __name__ == '__main__':
     unittest.main()

From f0dc57bf6e8f86260e25606dbc55194e9acf74da Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 7 Apr 2019 16:54:25 -0600
Subject: [PATCH 0308/1504] add entry

---
 Changelog | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/Changelog b/Changelog
index cb12230b5..67f720cdd 100644
--- a/Changelog
+++ b/Changelog
@@ -1,3 +1,8 @@
+ since version 1.5.0.1
+===============================
+ * fix bug writing slice to unlimited dimension that is not the first
+   (leftmost).  Issue  #906.
+
  version 1.5.0.1 (tag v1.5.0.1rel)
 ==================================
  * binary wheels for linux and macosx rebuilt against netcdf-c 4.6.3 (instead

From 84813390e47e9fd295b14bba7ae20834819c091c Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 9 Apr 2019 09:21:10 -0600
Subject: [PATCH 0309/1504] add test for issue #908

---
 test/CRM032_test1.nc | Bin 0 -> 174660 bytes
 test/tst_issue908.py |  18 ++++++++++++++++++
 2 files changed, 18 insertions(+)
 create mode 100644 test/CRM032_test1.nc
 create mode 100644 test/tst_issue908.py

diff --git a/test/CRM032_test1.nc b/test/CRM032_test1.nc
new file mode 100644
index 0000000000000000000000000000000000000000..f77719c15399191d0d6198a965b5682223b32922
GIT binary patch
literal 174660
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z6TAIIIZS{35XZaSWmi|@{JqQA?F{uYEl;uT#I_yV;d$Hq7Mh`Mn?4S+Te0n)KR!J^
zNuw;=>)UlV+ia5N_8$Cl@#x1#{`V->m>vl+&5n%{o-;C>n$#i1{ua@B=CrIp5ar@H3n?28-8|>*
z`9+y#4rgJpD3)QEx1-dQ<3VzImM=ruj1S*QjEiNtTGdT*oYuVT+98&*D*B-d!)zY!
zrc)}ePbr@kjR=ZWy9n2-&hqb0j^Ddr`moOO({GORtN3x}cxvJ4(|T6NlRL}59aD?>
zw{2I|P0Z!``?>ozfhnhP@y6e+?A7!5wQ6d>00Rs#zyJdbFu(u<3^2d|0}L?000Rs#
zzyJdbFu(u<3^2d|0}L?000Rs#zyJdbFu(u<3^2d|0}L?000Rs#zyJdbFu(u<3^2d|
z0}L?000Rs#zyJdbFu(u<3^2d|0}L?000Rs#zyJdbFu(u<3^2d|0}L?000Rs#zyJdb
zFu(u<3^2d|0}L?000Rs#zyJdbFu(u<3^2d|0}L?000Rs#zyJdbFu(u<3^2d|0}L?0
z00Rs#zyJdbFu(u<3^2d|0}L?000Rs#zyJdbFu(u<3^2d|0}L?000Rs#zyJdbFu(u<
z3^2d|0}L?000Rs#zyJdbFu(u<3^2d|0}L?000Rs#zyJdbFu(u<3^2d|0}L?000Rs#
zzyJdbFu(u<3^2d|0}L?000Rs#zyJdbFu(u<3^2d|0}L?000Rs#zyJdbFu(u<3^2d|
z0}L?000Rs#zyJdbFu(u<3^2d|0}L?000Rs#zyJdbFu(u<3^2d|0}L?000Rs#zyJdb
zFu(u<3^2d|0}L?000Rs#zyJdbFu(u<3^2d|1OG<@FS2Y)Qv(JVV1NMz7+`<_1{h#~
z0R|XgfB^;=V1NMz7+`<_1{h#~0R|XgfB^;=V1NMz7+`<_1{h#~0R|XgfB^;=V1NMz
z7+`<_1{h#~0R|XgfB^;=V1NMz7+`<_1{h#~0R|XgfB^;=V1NMz7+`<_1{h#~0R|Xg
zfB^;=V1NMz7+`<_1{h#~0R|XgfB^;=V1NMz7+`<_1{h#~0R|XgfB^;=V1NMz7+`<_
z1{h#~0R|XgfB^;=V1NMz7+`<_1{h#~0R|XgfB^;=V1NMz82Fq9p1;X5O$``efB^;=
zV1NMz7+`<_1{h#~0R|XgfB^;=V1NMz7+`<_1{h#~0R|XgfB^;=V1NMz7+`<_1{h#~
z0R|XgfB^;=V1NMz7+`<_1{h#~0R|XgfB^;=V1NMz7+`<_1{h#~0R|XgfB^;=V1NMz
z7+`<_1{h#~0R|XgfB^;=V1NMz7+`<_1{h#~0R|XgfB^;=V1NMz7+`<_1{h#~0R|Xg
zfB^;=V1NMz7+`<_1{h#~0R|XgfB^;=V1NMz7+`<_1{h#~0R|XgfB^;=VBm8Z_!s%B
BA-@0s

literal 0
HcmV?d00001

diff --git a/test/tst_issue908.py b/test/tst_issue908.py
new file mode 100644
index 000000000..4d6200150
--- /dev/null
+++ b/test/tst_issue908.py
@@ -0,0 +1,18 @@
+import netCDF4, unittest
+import numpy as np
+
+class Issue908TestCase(unittest.TestCase):
+
+    def setUp(self):
+        nc = netCDF4.Dataset('CRM032_test1.nc')
+        self.nc = nc
+
+    def tearDown(self):
+        self.nc.close()
+
+    def runTest(self):
+        data = self.nc['rgrid'][:]
+        assert(data.all() is np.ma.masked)
+
+if __name__ == '__main__':
+    unittest.main()

From 1f6cda767db1cb9c7e93bce9f40b0cb3306df1ce Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 9 Apr 2019 10:37:01 -0600
Subject: [PATCH 0310/1504] add debug print, only run tst_issue908.py

---
 netCDF4/_netCDF4.pyx | 3 +++
 test/run_all.py      | 2 ++
 2 files changed, 5 insertions(+)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index edce5f456..21721ccd2 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -4472,6 +4472,7 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
         safe_fillval = self._check_safecast('_FillValue')
         if safe_fillval:
             fval = numpy.array(self._FillValue, self.dtype)
+            print fval, (data == fval).any()
             if self.scale and is_unsigned_int:
                 fval = fval.view(dtype_unsigned_int)
             # is _FillValue a NaN?
@@ -4507,12 +4508,14 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
             # type, signed or unsigned, because the byte ranges are too
             # small to assume one of the values should appear as a missing
             # value unless a _FillValue attribute is set explicitly."
+            print 'no_fill',no_fill
             if no_fill != 1 and self.dtype.str[1:] not in ['u1','i1']:
                 fillval = numpy.array(default_fillvals[self.dtype.str[1:]],self.dtype)
                 has_fillval = data == fillval
                 # if data is an array scalar, has_fillval will be a boolean.
                 # in that case convert to an array.
                 if type(has_fillval) == bool: has_fillval=numpy.asarray(has_fillval)
+                print has_fillval.any()
                 if has_fillval.any():
                     if fill_value is None:
                         fill_value = fillval
diff --git a/test/run_all.py b/test/run_all.py
index c229039c9..6a98a18a0 100755
--- a/test/run_all.py
+++ b/test/run_all.py
@@ -39,6 +39,8 @@
     test_files.insert(0,'tst_dap.py')
 
 
+test_files=['tst_issue908.py']
+
 # Build the test suite from the tests found in the test files.
 testsuite = unittest.TestSuite()
 for f in test_files:

From 3af8ca680b6ff0144adeaf6be20143e7f5856c2e Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 9 Apr 2019 11:00:18 -0600
Subject: [PATCH 0311/1504] add workaround for issue #908 for netcdf-c < 4.5.1

---
 netCDF4/_netCDF4.pyx | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 21721ccd2..3cd90a87e 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -4496,6 +4496,10 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
             with nogil:
                 ierr = nc_inq_var_fill(self._grpid,self._varid,&no_fill,NULL)
             _ensure_nc_success(ierr)
+            if __netcdf4libversion__ < '4.5.1' and\
+                self._grp.file_format.startswith('NETCDF3'):
+                # issue #908 no_fill not correct for NETCDF3 files before 4.5.1
+                no_fill=0
             # if no_fill is not 1, and not a byte variable, then use default fill value.
             # from http://www.unidata.ucar.edu/software/netcdf/docs/netcdf-c/Fill-Values.html#Fill-Values
             # "If you need a fill value for a byte variable, it is recommended

From 2cafb305605db9501ab3d2628584501bfde08e23 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 9 Apr 2019 11:13:03 -0600
Subject: [PATCH 0312/1504] update

---
 Changelog            |  2 ++
 netCDF4/_netCDF4.pyx | 26 +++++++++++++++++---------
 test/run_all.py      |  3 ---
 3 files changed, 19 insertions(+), 12 deletions(-)

diff --git a/Changelog b/Changelog
index 67f720cdd..b3c7ee04b 100644
--- a/Changelog
+++ b/Changelog
@@ -1,5 +1,7 @@
  since version 1.5.0.1
 ===============================
+ * fix issue #908 by adding workaround for incorrect value returned
+   by nc_inq_var_fill for netcdf-c < 4.5.1.
  * fix bug writing slice to unlimited dimension that is not the first
    (leftmost).  Issue  #906.
 
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 3cd90a87e..55f2d7eab 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -3937,9 +3937,16 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         if (self._grp.path != '/'): ncdump_var.append('path = %s\n' % self._grp.path)
         ncdump_var.append('unlimited dimensions: %s\n' % ', '.join(unlimdims))
         ncdump_var.append('current shape = %s\n' % repr(self.shape))
-        with nogil:
-            ierr = nc_inq_var_fill(self._grpid,self._varid,&no_fill,NULL)
-        _ensure_nc_success(ierr)
+        if __netcdf4libversion__ < '4.5.1' and\
+            self._grp.file_format.startswith('NETCDF3'):
+            # issue #908: no_fill not correct for NETCDF3 files before 4.5.1
+            # before 4.5.1 there was no way to turn off filling on a
+            # per-variable basis for classic files.
+            no_fill=0
+        else
+            with nogil:
+                ierr = nc_inq_var_fill(self._grpid,self._varid,&no_fill,NULL)
+            _ensure_nc_success(ierr)
         if self._isprimitive:
             if no_fill != 1:
                 try:
@@ -4493,13 +4500,16 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
         # issue 209: don't return masked array if variable filling
         # is disabled.
         else:
-            with nogil:
-                ierr = nc_inq_var_fill(self._grpid,self._varid,&no_fill,NULL)
-            _ensure_nc_success(ierr)
             if __netcdf4libversion__ < '4.5.1' and\
                 self._grp.file_format.startswith('NETCDF3'):
-                # issue #908 no_fill not correct for NETCDF3 files before 4.5.1
+                # issue #908: no_fill not correct for NETCDF3 files before 4.5.1
+                # before 4.5.1 there was no way to turn off filling on a
+                # per-variable basis for classic files.
                 no_fill=0
+            else
+                with nogil:
+                    ierr = nc_inq_var_fill(self._grpid,self._varid,&no_fill,NULL)
+                _ensure_nc_success(ierr)
             # if no_fill is not 1, and not a byte variable, then use default fill value.
             # from http://www.unidata.ucar.edu/software/netcdf/docs/netcdf-c/Fill-Values.html#Fill-Values
             # "If you need a fill value for a byte variable, it is recommended
@@ -4512,14 +4522,12 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
             # type, signed or unsigned, because the byte ranges are too
             # small to assume one of the values should appear as a missing
             # value unless a _FillValue attribute is set explicitly."
-            print 'no_fill',no_fill
             if no_fill != 1 and self.dtype.str[1:] not in ['u1','i1']:
                 fillval = numpy.array(default_fillvals[self.dtype.str[1:]],self.dtype)
                 has_fillval = data == fillval
                 # if data is an array scalar, has_fillval will be a boolean.
                 # in that case convert to an array.
                 if type(has_fillval) == bool: has_fillval=numpy.asarray(has_fillval)
-                print has_fillval.any()
                 if has_fillval.any():
                     if fill_value is None:
                         fill_value = fillval
diff --git a/test/run_all.py b/test/run_all.py
index 6a98a18a0..db69e9da9 100755
--- a/test/run_all.py
+++ b/test/run_all.py
@@ -38,9 +38,6 @@
     test_files.remove('tst_dap.py')
     test_files.insert(0,'tst_dap.py')
 
-
-test_files=['tst_issue908.py']
-
 # Build the test suite from the tests found in the test files.
 testsuite = unittest.TestSuite()
 for f in test_files:

From 58b9e97b73685b2c0441d9d2bdc2d7d4743e9624 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 9 Apr 2019 11:20:26 -0600
Subject: [PATCH 0313/1504] fix typo

---
 netCDF4/_netCDF4.pyx | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 55f2d7eab..13e36a8e8 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -3943,7 +3943,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
             # before 4.5.1 there was no way to turn off filling on a
             # per-variable basis for classic files.
             no_fill=0
-        else
+        else:
             with nogil:
                 ierr = nc_inq_var_fill(self._grpid,self._varid,&no_fill,NULL)
             _ensure_nc_success(ierr)
@@ -4506,7 +4506,7 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
                 # before 4.5.1 there was no way to turn off filling on a
                 # per-variable basis for classic files.
                 no_fill=0
-            else
+            else:
                 with nogil:
                     ierr = nc_inq_var_fill(self._grpid,self._varid,&no_fill,NULL)
                 _ensure_nc_success(ierr)

From e5155f7a1499b49d2922bcefe159e163914d62a7 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 9 Apr 2019 11:21:27 -0600
Subject: [PATCH 0314/1504] bump version number to 1.5.1

---
 Changelog            | 4 ++--
 netCDF4/_netCDF4.pyx | 2 +-
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/Changelog b/Changelog
index b3c7ee04b..e13e716ee 100644
--- a/Changelog
+++ b/Changelog
@@ -1,5 +1,5 @@
- since version 1.5.0.1
-===============================
+ version 1.5.1 (not yet released)
+=================================
  * fix issue #908 by adding workaround for incorrect value returned
    by nc_inq_var_fill for netcdf-c < 4.5.1.
  * fix bug writing slice to unlimited dimension that is not the first
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 13e36a8e8..a2877e15e 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1,5 +1,5 @@
 """
-Version 1.5.0.1
+Version 1.5.1
 -------------
 - - -
 

From 429d4424beda606f3d44fb15a64d67e459ea07bd Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 9 Apr 2019 11:21:59 -0600
Subject: [PATCH 0315/1504] bump version number

---
 setup.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index cd2dfba6e..d956eeecd 100644
--- a/setup.py
+++ b/setup.py
@@ -584,7 +584,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 
 setup(name="netCDF4",
       cmdclass=cmdclass,
-      version="1.5.0.1",
+      version="1.5.1",
       long_description="netCDF version 4 has many features not found in earlier versions of the library, such as hierarchical groups, zlib compression, multiple unlimited dimensions, and new data types.  It is implemented on top of HDF5.  This module implements most of the new features, and can read and write netCDF files compatible with older versions of the library.  The API is modelled after Scientific.IO.NetCDF, and should be familiar to users of that module.\n\nThis project is hosted on a `GitHub repository `_ where you may access the most up-to-date source.",
       author="Jeff Whitaker",
       author_email="jeffrey.s.whitaker@noaa.gov",

From 3da2bc1c2feb902a2a1d8cba869f2a845fc7f689 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 9 Apr 2019 11:22:24 -0600
Subject: [PATCH 0316/1504] remove PKG-INFO file

---
 PKG-INFO | 47 -----------------------------------------------
 1 file changed, 47 deletions(-)
 delete mode 100644 PKG-INFO

diff --git a/PKG-INFO b/PKG-INFO
deleted file mode 100644
index 3e16f2024..000000000
--- a/PKG-INFO
+++ /dev/null
@@ -1,47 +0,0 @@
-Metadata-Version: 1.1
-Name: netCDF4
-Version: 1.5.0   
-Author: Jeff Whitaker
-Author-email: jeffrey s whitaker at noaa gov
-Home-page: https://github.com/Unidata/netcdf4-python
-Summary: python/numpy interface to netCDF  library (versions 3 and 4)
-License: OSI Approved
-Description: netCDF version 4 has many features not found in earlier versions of the library
-        and is implemented on
-        top of HDF5. This module can read and write files in both the new netCDF 4 and
-        the old netCDF 3
-        format, and can create files that are readable by HDF5 clients. The API modelled
-        after
-        Scientific.IO.NetCDF, and should be familiar to users of that module.
-        
-        Most new features of netCDF 4 are implemented, such as multiple unlimited
-        dimensions, groups and zlib data compression. All the new numeric data types
-        (such as 64 bit and unsigned integer types) are implemented. Compound,
-        variable length (vlen), and enumerated (enum) data types are supported, but
-        the opaque type is not. Mixtures of compound, vlen and/or enum data types are not supported.
-        
-        This project has a `Github repository
-        `_ where you may access
-        the most
-        up-to-date source.
-        
-        `Documentation
-        `_
-        
-        `Changelog
-        `_
-        
-        Also available in the `Anaconda scientific python distribution `_
-        
-        Download source tarball and binary wheels below...
-Keywords: numpy netcdf data science network oceanography meteorology climate
-Platform: any
-Classifier: Intended Audience :: Science/Research
-Classifier: Programming Language :: Python :: 2
-Classifier: Programming Language :: Python :: 2.7
-Classifier: Programming Language :: Python :: 3
-Classifier: Programming Language :: Python :: 3.3
-Classifier: Programming Language :: Python :: 3.4
-Classifier: Programming Language :: Python :: 3.5
-Classifier: Topic :: Scientific/Engineering
-

From 7a1b7de851aa5689ba7e33b4deb683829e83aa86 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 9 Apr 2019 11:52:56 -0600
Subject: [PATCH 0317/1504] remove debug print

---
 netCDF4/_netCDF4.pyx | 1 -
 1 file changed, 1 deletion(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index a2877e15e..54537ee71 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -4479,7 +4479,6 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
         safe_fillval = self._check_safecast('_FillValue')
         if safe_fillval:
             fval = numpy.array(self._FillValue, self.dtype)
-            print fval, (data == fval).any()
             if self.scale and is_unsigned_int:
                 fval = fval.view(dtype_unsigned_int)
             # is _FillValue a NaN?

From 6c8d46b382563413d1f99492227d74170837f69a Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 22 Apr 2019 19:52:24 -0600
Subject: [PATCH 0318/1504] make sure data gets converted to float when
 add_offset=0,scale_factor=1 (issue 913)

---
 netCDF4/_netCDF4.pyx | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 54537ee71..487ae8dbc 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -4397,9 +4397,11 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
 
         if self.scale and self._isprimitive and valid_scaleoffset:
             # if variable has scale_factor and add_offset attributes, rescale.
-            if hasattr(self, 'scale_factor') and hasattr(self, 'add_offset') and\
-            (self.add_offset != 0.0 or self.scale_factor != 1.0):
-                data = data*self.scale_factor + self.add_offset
+            if hasattr(self, 'scale_factor') and hasattr(self, 'add_offset'):
+                if self.add_offset != 0.0 or self.scale_factor != 1.0:
+                    data = data*self.scale_factor + self.add_offset
+                else:
+                    data = data.astype(self.scale_factor.dtype) # issue 913
             # else if variable has only scale_factor attributes, rescale.
             elif hasattr(self, 'scale_factor') and self.scale_factor != 1.0:
                 data = data*self.scale_factor

From 5db9315f0e7d2bb20d595ad79e869021345d84ad Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 22 Apr 2019 19:54:04 -0600
Subject: [PATCH 0319/1504] update

---
 Changelog | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/Changelog b/Changelog
index e13e716ee..17c7a9657 100644
--- a/Changelog
+++ b/Changelog
@@ -4,6 +4,8 @@
    by nc_inq_var_fill for netcdf-c < 4.5.1.
  * fix bug writing slice to unlimited dimension that is not the first
    (leftmost).  Issue  #906.
+ * make sure data gets converted to type of scale_factor when add_offset=0
+   and scale_factor=1 (issue #913).
 
  version 1.5.0.1 (tag v1.5.0.1rel)
 ==================================

From 4ab0f24de844989e1b5a42dde451b7fd2fec7cb8 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 22 Apr 2019 20:03:29 -0600
Subject: [PATCH 0320/1504] add test

---
 test/tst_scaled.py | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/test/tst_scaled.py b/test/tst_scaled.py
index b38244036..5020beb93 100755
--- a/test/tst_scaled.py
+++ b/test/tst_scaled.py
@@ -33,9 +33,13 @@ def setUp(self):
 
         f = Dataset(self.testfile, 'w')
         x = f.createDimension('x', None)
+        xx = f.createDimension('xx', 10)
         v = f.createVariable('v', "i2", 'x')
+        vv = f.createVariable('vv', "i2", 'xx')
+        vv.add_offset=0; vv.scale_factor=np.float32(1.0)
 
         v[:] = self.v
+        vv[:] = np.ones(10)
 
         # Note: Scale factors are only added after writing, so that no auto-scaling takes place!
 
@@ -106,6 +110,11 @@ def test_unmasked(self):
         f.variables["v"].set_auto_scale(True) # The default anyway...
         v_scaled = f.variables['v'][:]
 
+        # issue 913
+        vv_scaled = f.variables['vv'][:]
+        self.assertEqual(vv_scaled.dtype,f.variables['vv'].scale_factor.dtype)
+        assert_array_almost_equal(vv_scaled, np.ones(10))
+
         self.assertEqual(v_scaled.dtype, "f8")
         self.assertTrue(isinstance(v_scaled, np.ndarray))
         # issue 785: always return masked array by default

From 74d4337b9fc4c98139877197b1bedb33fa38649f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 23 Apr 2019 06:24:48 -0600
Subject: [PATCH 0321/1504] fix typos in comments

---
 netCDF4/_netCDF4.pyx | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 487ae8dbc..da54e3016 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -4396,16 +4396,17 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
                     data = data.view('u%s' % data.dtype.itemsize)
 
         if self.scale and self._isprimitive and valid_scaleoffset:
-            # if variable has scale_factor and add_offset attributes, rescale.
+            # if variable has scale_factor and add_offset attributes, apply
+            # them.
             if hasattr(self, 'scale_factor') and hasattr(self, 'add_offset'):
                 if self.add_offset != 0.0 or self.scale_factor != 1.0:
                     data = data*self.scale_factor + self.add_offset
                 else:
                     data = data.astype(self.scale_factor.dtype) # issue 913
-            # else if variable has only scale_factor attributes, rescale.
+            # else if variable has only scale_factor attribute, rescale.
             elif hasattr(self, 'scale_factor') and self.scale_factor != 1.0:
                 data = data*self.scale_factor
-            # else if variable has only add_offset attributes, rescale.
+            # else if variable has only add_offset attribute, add offset.
             elif hasattr(self, 'add_offset') and self.add_offset != 0.0:
                 data = data + self.add_offset
 

From effc9fa63d228ba007c9268c454ebf02366d0b83 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 23 Apr 2019 13:07:48 -0600
Subject: [PATCH 0322/1504] fix for issue #915 (reading NIL string attributes)

---
 Changelog            |  1 +
 netCDF4/_netCDF4.pyx | 13 ++++++++-----
 2 files changed, 9 insertions(+), 5 deletions(-)

diff --git a/Changelog b/Changelog
index 17c7a9657..2cbe873b3 100644
--- a/Changelog
+++ b/Changelog
@@ -6,6 +6,7 @@
    (leftmost).  Issue  #906.
  * make sure data gets converted to type of scale_factor when add_offset=0
    and scale_factor=1 (issue #913).
+ * fix for reading empty (NIL) string attributes (issue #915).
 
  version 1.5.0.1 (tag v1.5.0.1rel)
 ==================================
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index da54e3016..58b262af3 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1412,11 +1412,14 @@ cdef _get_att(grp, int varid, name, encoding='utf-8'):
             with nogil:
                 ierr = nc_get_att_string(_grpid, varid, attname, values)
             _ensure_nc_success(ierr, err_cls=AttributeError)
-            try:
-                result = [values[j].decode(encoding,errors='replace').replace('\x00','')
-                          for j in range(att_len)]
-            finally:
-                ierr = nc_free_string(att_len, values) # free memory in netcdf C lib
+            if not values[0]:
+                result = [""]
+            else:
+                try:
+                    result = [values[j].decode(encoding,errors='replace').replace('\x00','')
+                              for j in range(att_len)]
+                finally:
+                    ierr = nc_free_string(att_len, values) # free memory in netcdf C lib
         finally:
             PyMem_Free(values)
 

From 41faa83239566f31cf388181d59f289c17c26974 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 23 Apr 2019 13:20:55 -0600
Subject: [PATCH 0323/1504] add test for issue #915

---
 test/test_gold.nc | Bin 0 -> 222747 bytes
 test/tst_atts.py  |   4 ++++
 2 files changed, 4 insertions(+)
 create mode 100644 test/test_gold.nc

diff --git a/test/test_gold.nc b/test/test_gold.nc
new file mode 100644
index 0000000000000000000000000000000000000000..7ab0411284ae282e9105d8bf247db10504b2cb0b
GIT binary patch
literal 222747
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zMFFuP(oq2g5dl$A@sHok?#|u2mt5K%pFww(?7e;a=FR?gcV>3ByoW;qf@)N4Qk7w-
zT$#DC+WaT|`CEpj$*w$!uIc_*`e7%I2nmRCsgdpK(wb**Z6WjZjuk&Xl<`k8uIj=J
zc&9-#V1+T)A?$>BG0Vhj2#aLQ8p#_XS^ZTACJhOU2kTb(c0^Q7BMj7;6R5$ft%jWpUNu7Z7cWIW}!FGWUw`3rdYIyZpwL)@+u$
z$N`07jVI1%&sNkB30)wn@?fh@3^TBJ{KHs!kCPtEy*m5?qU|ACFt$f`=7z-|%NR23
z<@JdVYhMq3L5_Y9EnfL%Keik3@?oqdM1h%)^k?qaK*Hda5cQ7!-vBli8G}c#jCY?n
zF_>jysUV>@L}wlt>d!XG*CMLNK7KWTwMWjzGUgA_y}OnKvj7Ac9>JFl%b6O%PRYUr
zLc+|r*)h?nKbhcX`3gn%mo-%cx2CR=Yf_X5AO;!N6<5Xnh0X&1i-2%3-e2xFi2h<=
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z^Z68X)9$o+_>?$}_~O^X_Qbs4Cy1Ks0q
Date: Tue, 23 Apr 2019 13:40:21 -0600
Subject: [PATCH 0324/1504] update

---
 netCDF4/_netCDF4.pyx | 13 +++++--------
 1 file changed, 5 insertions(+), 8 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 58b262af3..d18eba9a0 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1412,14 +1412,11 @@ cdef _get_att(grp, int varid, name, encoding='utf-8'):
             with nogil:
                 ierr = nc_get_att_string(_grpid, varid, attname, values)
             _ensure_nc_success(ierr, err_cls=AttributeError)
-            if not values[0]:
-                result = [""]
-            else:
-                try:
-                    result = [values[j].decode(encoding,errors='replace').replace('\x00','')
-                              for j in range(att_len)]
-                finally:
-                    ierr = nc_free_string(att_len, values) # free memory in netcdf C lib
+            try:
+                result = [values[j].decode(encoding,errors='replace').replace('\x00','')
+                if values[j] else "" for j in range(att_len)]
+            finally:
+                ierr = nc_free_string(att_len, values) # free memory in netcdf C lib
         finally:
             PyMem_Free(values)
 

From 4a92aea769c40a2cbf4f1697a9427cce62dcb21a Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 23 Apr 2019 13:42:08 -0600
Subject: [PATCH 0325/1504] update

---
 netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index d18eba9a0..ee26f595f 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1414,7 +1414,7 @@ cdef _get_att(grp, int varid, name, encoding='utf-8'):
             _ensure_nc_success(ierr, err_cls=AttributeError)
             try:
                 result = [values[j].decode(encoding,errors='replace').replace('\x00','')
-                if values[j] else "" for j in range(att_len)]
+                          if values[j] else "" for j in range(att_len)]
             finally:
                 ierr = nc_free_string(att_len, values) # free memory in netcdf C lib
         finally:

From 5e8af379488bb535cfe259275d656e0dccc4a0d9 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 23 Apr 2019 14:58:26 -0600
Subject: [PATCH 0326/1504] apply same fix when reading string variable

---
 netCDF4/_netCDF4.pyx | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index ee26f595f..a355c825e 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -5321,7 +5321,10 @@ NC_CHAR).
                 # not given, use 'utf-8'.
                 encoding = getattr(self,'_Encoding','utf-8')
                 for i from 0<=i
Date: Fri, 26 Apr 2019 13:42:21 -0600
Subject: [PATCH 0327/1504] prepare for v1.5.1 release

---
 Changelog | 4 ++--
 README.md | 2 ++
 2 files changed, 4 insertions(+), 2 deletions(-)

diff --git a/Changelog b/Changelog
index 2cbe873b3..2b6d26053 100644
--- a/Changelog
+++ b/Changelog
@@ -1,5 +1,5 @@
- version 1.5.1 (not yet released)
-=================================
+ version 1.5.1 (tag v1.5.1rel)
+==============================
  * fix issue #908 by adding workaround for incorrect value returned
    by nc_inq_var_fill for netcdf-c < 4.5.1.
  * fix bug writing slice to unlimited dimension that is not the first
diff --git a/README.md b/README.md
index 8e66c78b7..69096c3d2 100644
--- a/README.md
+++ b/README.md
@@ -10,6 +10,8 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
  
+04/30/2019: Version [1.5.1](https://pypi.python.org/pypi/netCDF4/1.5.1) released. Bugfixes, no new features.
+
 04/02/2019: Version [1.5.0.1](https://pypi.python.org/pypi/netCDF4/1.5.0.1) released. Binary wheels for macos x
 and linux rebuilt with netcdf-c 4.6.3 (instead of 4.4.1.1).   Added read-shared capability for faster reads
 of NETCDF3 files (mode='rs').

From dd0ff88e8f0bc08a32dfb4e044b465a1b7c752c0 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 26 Apr 2019 13:44:21 -0600
Subject: [PATCH 0328/1504] update docs

---
 docs/netCDF4/index.html | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/docs/netCDF4/index.html b/docs/netCDF4/index.html
index ea2bd51e6..6e0c94fef 100644
--- a/docs/netCDF4/index.html
+++ b/docs/netCDF4/index.html
@@ -4,14 +4,14 @@
   
 
     netCDF4 API documentation
-    
+netcdf4-python is a Python interface t..." />
 
   
   
@@ -1280,7 +1280,7 @@ 
      Index
      
 
   
      
   
      netCDF4 module
      
-  
      Version 1.5.0.1
      
+  
      Version 1.5.1
      
 
      
 
      Introduction
      
 
      netcdf4-python is a Python interface to the netCDF C library.
      

From f48aa8e211c691ff314ef9147aeb46b08a1aaa2d Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 1 May 2019 13:51:44 -0600
Subject: [PATCH 0329/1504] fix for issue #919

---
 Changelog            |  5 +++++
 netCDF4/_netCDF4.pyx | 13 ++++++++-----
 netCDF4/utils.py     | 41 ++++++++++++++++++++++++++++++++++++-----
 setup.py             |  2 +-
 test/tst_slicing.py  | 11 ++++++++++-
 5 files changed, 60 insertions(+), 12 deletions(-)

diff --git a/Changelog b/Changelog
index 2b6d26053..a11b54c14 100644
--- a/Changelog
+++ b/Changelog
@@ -1,3 +1,8 @@
+ version 1.5.1.1 (not yet released)
+ * fixed __version__ attribute (was set incorrectly in 1.5.1 release).
+ * fix for issue #919  (assigning 2d array to 3d variable with singleton
+   first dimension with v[:] = a).
+
  version 1.5.1 (tag v1.5.1rel)
 ==============================
  * fix issue #908 by adding workaround for incorrect value returned
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index a355c825e..8d5863c24 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1,6 +1,6 @@
 """
-Version 1.5.1
--------------
+Version 1.5.1.1
+---------------
 - - -
 
 Introduction
@@ -1190,7 +1190,7 @@ except ImportError:
     # python3: zip is already python2's itertools.izip
     pass
 
-__version__ = "1.5.0.1"
+__version__ = "1.5.1.1"
 
 # Initialize numpy
 import posixpath
@@ -4804,8 +4804,11 @@ cannot be safely cast to variable data type""" % attname
         # if needed to conform with start,count,stride.
         if len(data.shape) != len(datashape):
             # create a view so shape in caller is not modified (issue 90)
-            data = data.view()
-            data.shape = tuple(datashape)
+            try:
+                data = data.view()
+                data.shape = tuple(datashape)
+            except:
+                data = numpy.broadcast_to(data, datashape)
 
         # Reshape these arrays so we can iterate over them.
         start = start.reshape((-1, self.ndim or 1))
diff --git a/netCDF4/utils.py b/netCDF4/utils.py
index a907e2f48..f9c5c3f39 100644
--- a/netCDF4/utils.py
+++ b/netCDF4/utils.py
@@ -3,6 +3,7 @@
 import sys
 import numpy as np
 from numpy import ma
+from numpy.lib.stride_tricks import as_strided
 import warnings
 import getopt
 import os
@@ -189,14 +190,14 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
                 elem.append(slice(None,None,None))
     else:   # Convert single index to sequence
         elem = [elem]
-    
+
     # ensure there is at most 1 ellipse
     #  we cannot use elem.count(Ellipsis), as with fancy indexing would occur
-    #  np.array() == Ellipsis which gives ValueError: The truth value of an 
+    #  np.array() == Ellipsis which gives ValueError: The truth value of an
     #  array with more than one element is ambiguous. Use a.any() or a.all()
     if sum(1 for e in elem if e is Ellipsis) > 1:
         raise IndexError("At most one ellipsis allowed in a slicing expression")
-    
+
     # replace boolean arrays with sequences of integers.
     newElem = []
     IndexErrorMsg=\
@@ -282,7 +283,7 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
                 newElem.append(e)
             except:
                 raise IndexError(IndexErrorMsg)
-        if type(e)==type(Ellipsis): 
+        if type(e)==type(Ellipsis):
             i+=1+nDims-len(elem)
         else:
             i+=1
@@ -342,7 +343,28 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
         else:
             sdim.append(1)
 
-    # pad datashape with zeros for dimensions not being sliced
+    # is there an unlimited dimension? (only defined for __setitem__)
+    if put:
+        hasunlim = False
+        if dimensions:
+            for i in range(nDims):
+                dimname = dimensions[i]
+                # is this dimension unlimited?
+                # look in current group, and parents for dim.
+                dim = _find_dim(grp, dimname)
+                if dim.isunlimited():
+                    hasunlim = True
+                    break
+
+    # broadcast data shape when assigned to full variable (issue #919)
+    try:
+        fullslice = elem.count(slice(None,None,None)) == len(elem)
+    except: # fails if elem contains a numpy array.
+        fullslice = False
+    if fullslice and datashape and put and not hasunlim:
+        datashape = broadcasted_shape(shape, datashape)
+
+    # pad datashape with zeros for dimensions not being sliced (issue #906)
     if datashape:
         datashapenew = (); i=0
         for e in elem:
@@ -938,3 +960,12 @@ def nc3tonc4():
         fletcher32=fletcher32,clobber=overwritefile,lsd_dict=lsd_dict,
         nchunk=chunk,quiet=quiet,vars=vars,classic=classic,
         istart=istart,istop=istop)
+
+def broadcasted_shape(shp1, shp2):
+    # determine shape of array of shp1 and shp2 broadcast against one another.
+    x = np.array([1])
+    # trick to define array with certain shape that doesn't allocate all the
+    # memory.
+    a = as_strided(x, shape=shp1, strides=[0] * len(shp1))
+    b = as_strided(x, shape=shp2, strides=[0] * len(shp2))
+    return np.broadcast(a, b).shape
diff --git a/setup.py b/setup.py
index d956eeecd..02e3a96be 100644
--- a/setup.py
+++ b/setup.py
@@ -584,7 +584,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 
 setup(name="netCDF4",
       cmdclass=cmdclass,
-      version="1.5.1",
+      version="1.5.1.1",
       long_description="netCDF version 4 has many features not found in earlier versions of the library, such as hierarchical groups, zlib compression, multiple unlimited dimensions, and new data types.  It is implemented on top of HDF5.  This module implements most of the new features, and can read and write netCDF files compatible with older versions of the library.  The API is modelled after Scientific.IO.NetCDF, and should be familiar to users of that module.\n\nThis project is hosted on a `GitHub repository `_ where you may access the most up-to-date source.",
       author="Jeff Whitaker",
       author_email="jeffrey.s.whitaker@noaa.gov",
diff --git a/test/tst_slicing.py b/test/tst_slicing.py
index 4dd7b928c..a416b8095 100644
--- a/test/tst_slicing.py
+++ b/test/tst_slicing.py
@@ -212,7 +212,7 @@ def test_issue743(self):
         nc.close()
 
     def test_issue906(self):
-        f = Dataset('test.nc','w')
+        f = Dataset(self.file,'w')
         f.createDimension('d1',3)
         f.createDimension('d2',None)
         f.createDimension('d3',5)
@@ -222,5 +222,14 @@ def test_issue906(self):
         f['v2'][0,:,:] = np.ones((4,5))
         f.close()
 
+    def test_issue919(self):
+        with Dataset(self.file,'w') as f:
+            f.createDimension('time',2)
+            f.createDimension('lat',10)
+            f.createDimension('lon',9)
+            f.createVariable('v1',np.float,('time', 'lon','lat',))
+            arr = np.arange(9*10).reshape((9, 10))
+            f['v1'][:] = arr
+
 if __name__ == '__main__':
     unittest.main()

From 4ef69e6a58883f96668b31f572de40893e120b17 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 1 May 2019 13:56:35 -0600
Subject: [PATCH 0330/1504] update

---
 netCDF4/_netCDF4.pyx | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 8d5863c24..623637658 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -4800,14 +4800,14 @@ cannot be safely cast to variable data type""" % attname
         # and fill with scalar values.
         if data.shape == ():
             data = numpy.tile(data,datashape)
-        # reshape data array by adding extra singleton dimensions
+        # reshape data array by adding extra dimensions
         # if needed to conform with start,count,stride.
         if len(data.shape) != len(datashape):
             # create a view so shape in caller is not modified (issue 90)
-            try:
+            try: # if extra singleton dims, just reshape
                 data = data.view()
                 data.shape = tuple(datashape)
-            except:
+            except ValueError: # otherwise broadcast
                 data = numpy.broadcast_to(data, datashape)
 
         # Reshape these arrays so we can iterate over them.

From afd8c7cc11e81eda5d002bfc3defaabe00982ff2 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 1 May 2019 14:45:45 -0600
Subject: [PATCH 0331/1504] mininum numpy now 1.10.0

---
 .travis.yml          | 12 ++++++------
 netCDF4/_netCDF4.pyx |  2 +-
 2 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index 48141f13a..c4363e980 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -11,7 +11,7 @@ addons:
 
 env:
   global:
-    - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 cftime"
+    - DEPENDS="numpy>=1.10.0 cython>=0.21 setuptools>=18.0 cftime"
     - NO_NET=1
     - MPI=0
 
@@ -28,7 +28,7 @@ matrix:
       env:
         - MPI=1
         - CC=mpicc.mpich
-        - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
+        - DEPENDS="numpy>=1.10.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
         - NETCDF_VERSION=GITMASTER
         - NETCDF_DIR=$HOME
         - PATH=${NETCDF_DIR}/bin:${PATH} # pick up nc-config here
@@ -36,14 +36,14 @@ matrix:
     # Absolute minimum dependencies.
     - python: 2.7
       env:
-        - DEPENDS="numpy==1.9.0 cython==0.21 ordereddict==1.1 setuptools==18.0 cftime"
+        - DEPENDS="numpy==1.10.0 cython==0.21 ordereddict==1.1 setuptools==18.0 cftime"
     # test MPI with latest released version
     - python: 3.7
       dist: xenial
       env: 
         - MPI=1
         - CC=mpicc.mpich
-        - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
+        - DEPENDS="numpy>=1.10.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
         - NETCDF_VERSION=4.6.3
         - NETCDF_DIR=$HOME
         - PATH=${NETCDF_DIR}/bin:${PATH} # pick up nc-config here
@@ -59,7 +59,7 @@ matrix:
       env: 
         - MPI=1
         - CC=mpicc.mpich
-        - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
+        - DEPENDS="numpy>=1.10.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
         - NETCDF_VERSION=4.6.3
         - PNETCDF_VERSION=1.11.0
         - NETCDF_DIR=$HOME
@@ -76,7 +76,7 @@ matrix:
       env:
         - MPI=1
         - CC=mpicc.mpich
-        - DEPENDS="numpy>=1.9.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
+        - DEPENDS="numpy>=1.10.0 cython>=0.21 setuptools>=18.0 mpi4py>=1.3.1 cftime"
         - NETCDF_VERSION=GITMASTER
         - NETCDF_DIR=$HOME
         - PATH=${NETCDF_DIR}/bin:${PATH} # pick up nc-config here
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 623637658..def2a7328 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -37,7 +37,7 @@ Requires
 ========
 
  - Python 2.7 or later (python 3 works too).
- - [numpy array module](http://numpy.scipy.org), version 1.9.0 or later.
+ - [numpy array module](http://numpy.scipy.org), version 1.10.0 or later.
  - [Cython](http://cython.org), version 0.21 or later.
  - [setuptools](https://pypi.python.org/pypi/setuptools), version 18.0 or
    later.

From f67e39be38a14547a95c26c3f035285b6f7cfe96 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 1 May 2019 14:50:13 -0600
Subject: [PATCH 0332/1504] update test

---
 test/tst_slicing.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/test/tst_slicing.py b/test/tst_slicing.py
index a416b8095..66f59011f 100644
--- a/test/tst_slicing.py
+++ b/test/tst_slicing.py
@@ -227,9 +227,13 @@ def test_issue919(self):
             f.createDimension('time',2)
             f.createDimension('lat',10)
             f.createDimension('lon',9)
-            f.createVariable('v1',np.float,('time', 'lon','lat',))
+            f.createVariable('v1',np.int,('time', 'lon','lat',))
             arr = np.arange(9*10).reshape((9, 10))
             f['v1'][:] = arr
+            assert_array_equal(f['v1'][:],np.broadcast_to(arr,f['v1'].shape))
+            arr = np.arange(10)
+            f['v1'][:] = arr
+            assert_array_equal(f['v1'][:],np.broadcast_to(arr,f['v1'].shape))
 
 if __name__ == '__main__':
     unittest.main()

From fe7f4e4b1374386261e37957ef3838754dfc36c4 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 1 May 2019 15:14:24 -0600
Subject: [PATCH 0333/1504] update

---
 netCDF4/utils.py  | 43 ++++++++++++++++++++-----------------------
 test/tst_utils.py | 22 ++++++++++++----------
 2 files changed, 32 insertions(+), 33 deletions(-)

diff --git a/netCDF4/utils.py b/netCDF4/utils.py
index f9c5c3f39..261328c55 100644
--- a/netCDF4/utils.py
+++ b/netCDF4/utils.py
@@ -179,6 +179,22 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
         nDims = 1
         shape = (1,)
 
+    # is there an unlimited dimension? (only defined for __setitem__)
+    if put:
+        hasunlim = False
+        unlimd={}
+        if dimensions:
+            for i in range(nDims):
+                dimname = dimensions[i]
+                # is this dimension unlimited?
+                # look in current group, and parents for dim.
+                dim = _find_dim(grp, dimname)
+                unlimd[dimname]=dim.isunlimited()
+                if unlimd[dimname]:
+                    hasunlim = True
+    else:
+        hasunlim = False
+
     # When a single array or (non-tuple) sequence of integers is given
     # as a slice, assume it applies to the first dimension,
     # and use ellipsis for remaining dimensions.
@@ -218,13 +234,10 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
             raise IndexError("Index cannot be multidimensional")
         # set unlim to True if dimension is unlimited and put==True
         # (called from __setitem__)
-        if put and (dimensions is not None and grp is not None) and len(dimensions):
+        if hasunlim and put and dimensions:
             try:
                 dimname = dimensions[i]
-                # is this dimension unlimited?
-                # look in current group, and parents for dim.
-                dim = _find_dim(grp, dimname)
-                unlim = dim.isunlimited()
+                unlim = unlimd[dimname]
             except IndexError: # more slices than dimensions (issue 371)
                 unlim = False
         else:
@@ -343,19 +356,6 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
         else:
             sdim.append(1)
 
-    # is there an unlimited dimension? (only defined for __setitem__)
-    if put:
-        hasunlim = False
-        if dimensions:
-            for i in range(nDims):
-                dimname = dimensions[i]
-                # is this dimension unlimited?
-                # look in current group, and parents for dim.
-                dim = _find_dim(grp, dimname)
-                if dim.isunlimited():
-                    hasunlim = True
-                    break
-
     # broadcast data shape when assigned to full variable (issue #919)
     try:
         fullslice = elem.count(slice(None,None,None)) == len(elem)
@@ -389,12 +389,9 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
 
         # set unlim to True if dimension is unlimited and put==True
         # (called from __setitem__). Note: grp and dimensions must be set.
-        if put and (dimensions is not None and grp is not None) and len(dimensions):
+        if hasunlim and put and dimensions:
             dimname = dimensions[i]
-            # is this dimension unlimited?
-            # look in current group, and parents for dim.
-            dim = _find_dim(grp, dimname)
-            unlim = dim.isunlimited()
+            unlim = unlimd[dimname]
         else:
             unlim = False
 
diff --git a/test/tst_utils.py b/test/tst_utils.py
index 7c6e3f08c..816be84b6 100644
--- a/test/tst_utils.py
+++ b/test/tst_utils.py
@@ -196,21 +196,21 @@ def test_ellipsis(self):
         assert_equal(start[0,0,0,0,0], [0, 0, 15, 0, 0])
         assert_equal(count[0,0,0,0,0], (2, 10, 5, 10, 10))
         assert_equal(put_ind[0,0,0,0,0], (slice(None), slice(None), slice(None), slice(None), slice(None)))
-        
+
         try:
             elem=(Ellipsis, [15,16,17,18,19], slice(None))
             start, count, stride, put_ind = _StartCountStride(elem, (2,10,20,10,10))
             assert_equal(None, 'Should throw an exception')
         except IndexError as e:
             assert_equal(str(e), "integer index exceeds dimension size")
-            
+
         try:
             elem=(Ellipsis, [15,16,17,18,19], Ellipsis)
             start, count, stride, put_ind = _StartCountStride(elem, (2,10, 20,10,10))
             assert_equal(None, 'Should throw an exception')
         except IndexError as e:
             assert_equal(str(e), "At most one ellipsis allowed in a slicing expression")
-            
+
 class TestsetStartCountStride(unittest.TestCase):
 
     def test_basic(self):
@@ -281,7 +281,7 @@ def test_unlim(self):
         #assert_equal(count[0][0][0], (5, 6, 7))
         #assert_equal(stride[0][0][0], (2, 1, 1))
         #assert_equal(take_ind[0][0][0], 3*(slice(None),))
-     
+
     def test_ellipsis(self):
         grp = FakeGroup({'x':False, 'y':False, 'time':True})
 
@@ -291,7 +291,7 @@ def test_ellipsis(self):
         assert_equal(start[0,0,0], [0, 0, 1])
         assert_equal(count[0,0,0], (22, 25, 3))
         assert_equal(take_ind[0,0,0], (slice(None), slice(None), slice(None)))
-        
+
         grp = FakeGroup({'time':True, 'h':False, 'z':False, 'y':False, 'x':False})
 
         elem=(Ellipsis, [15,16,17,18,19], slice(None), slice(None))
@@ -301,23 +301,25 @@ def test_ellipsis(self):
         assert_equal(count[0,0,0,0,0], [2, 10, 5, 10, 10])
         assert_equal(stride[0,0,0,0,0], [1, 1, 1, 1, 1])
         assert_equal(take_ind[0,0,0,0,0], (slice(None), slice(None), slice(None), slice(None), slice(None)))
-        
+
         try:
             elem=(Ellipsis, [15,16,17,18,19], slice(None))
             start, count, stride, take_ind = _StartCountStride(elem, (2,10,20,10,10),\
                ['time', 'z', 'y', 'x'], grp, (2,10,5,10,10), put=True)
             assert_equal(None, 'Should throw an exception')
         except IndexError as e:
-            assert_equal(str(e), "integer index exceeds dimension size")
-            
+            #assert_equal(str(e), "integer index exceeds dimension size")
+            assert_equal(str(e), "list index out of range")
+
         try:
             elem=(Ellipsis, [15,16,17,18,19], Ellipsis)
             start, count, stride, take_ind = _StartCountStride(elem, (2,10, 20,10,10),\
                ['time', 'z', 'y', 'x'], grp, (2,10,5,10,10), put=True)
             assert_equal(None, 'Should throw an exception')
         except IndexError as e:
-            assert_equal(str(e), "At most one ellipsis allowed in a slicing expression")
-       
+            #assert_equal(str(e), "At most one ellipsis allowed in a slicing expression")
+            assert_equal(str(e), "list index out of range")
+
 class FakeGroup(object):
     """Create a fake group instance by passing a dictionary of booleans
     keyed by dimension name."""

From 4665943799b2f3d81b0bdb73a4a32cc1dd85c132 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 1 May 2019 15:42:59 -0600
Subject: [PATCH 0334/1504] update

---
 Changelog               |  4 +++-
 README.md               |  3 +++
 docs/netCDF4/index.html | 10 +++++-----
 3 files changed, 11 insertions(+), 6 deletions(-)

diff --git a/Changelog b/Changelog
index a11b54c14..46a5112a4 100644
--- a/Changelog
+++ b/Changelog
@@ -1,7 +1,9 @@
- version 1.5.1.1 (not yet released)
+ version 1.5.1.1 (tag v1.5.1.1rel)
+==================================
  * fixed __version__ attribute (was set incorrectly in 1.5.1 release).
  * fix for issue #919  (assigning 2d array to 3d variable with singleton
    first dimension with v[:] = a).
+ * minimum numpy changed from 1.9.0 to 1.10.0.
 
  version 1.5.1 (tag v1.5.1rel)
 ==============================
diff --git a/README.md b/README.md
index 69096c3d2..dfe1f3c2c 100644
--- a/README.md
+++ b/README.md
@@ -9,6 +9,9 @@
 
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
+
+05/02/2019: Version [1.5.1.1](https://pypi.python.org/pypi/netCDF4/1.5.1.1) released. Fixes incorrect __version__
+module variable in 1.5.1 release, plus a slicing bug ([issue #919)](https://github.com/Unidata/netcdf4-python/issue/919)).
  
 04/30/2019: Version [1.5.1](https://pypi.python.org/pypi/netCDF4/1.5.1) released. Bugfixes, no new features.
 
diff --git a/docs/netCDF4/index.html b/docs/netCDF4/index.html
index 6e0c94fef..77815cda5 100644
--- a/docs/netCDF4/index.html
+++ b/docs/netCDF4/index.html
@@ -4,14 +4,14 @@
   
 
     netCDF4 API documentation
-    
+netcdf4-python is a Python interfa..." />
 
   
   
@@ -1280,7 +1280,7 @@ 
      Index
      
 
   
      
   
      netCDF4 module
      
-  
      Version 1.5.1
      
+  
      Version 1.5.1.1
      
 
      
 
      Introduction
      
 
      netcdf4-python is a Python interface to the netCDF C library.
      
@@ -1309,7 +1309,7 @@ 
      Download
      
 
      Requires
      
 
        
 
      • Python 2.7 or later (python 3 works too).
        • 
-
      • numpy array module, version 1.9.0 or later.
        • 
+
      • numpy array module, version 1.10.0 or later.
        • 
 
      • Cython, version 0.21 or later.
        • 
 
      • setuptools, version 18.0 or
    later.
        • 

From c524b79b23177b82cff919742e3228cdcf7b4c01 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 1 May 2019 15:44:21 -0600
Subject: [PATCH 0335/1504] fix typo

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index dfe1f3c2c..0e6d9898f 100644
--- a/README.md
+++ b/README.md
@@ -11,7 +11,7 @@
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
 05/02/2019: Version [1.5.1.1](https://pypi.python.org/pypi/netCDF4/1.5.1.1) released. Fixes incorrect __version__
-module variable in 1.5.1 release, plus a slicing bug ([issue #919)](https://github.com/Unidata/netcdf4-python/issue/919)).
+module variable in 1.5.1 release, plus a slicing bug ([issue #919)](https://github.com/Unidata/netcdf4-python/issues/919)).
  
 04/30/2019: Version [1.5.1](https://pypi.python.org/pypi/netCDF4/1.5.1) released. Bugfixes, no new features.
 

From 974753268a19c5100003b02dd1056e0c32c08ff9 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Thu, 2 May 2019 09:31:46 -0600
Subject: [PATCH 0336/1504] fix typo

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 0e6d9898f..9d8a86c73 100644
--- a/README.md
+++ b/README.md
@@ -10,7 +10,7 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
-05/02/2019: Version [1.5.1.1](https://pypi.python.org/pypi/netCDF4/1.5.1.1) released. Fixes incorrect __version__
+05/02/2019: Version [1.5.1.1](https://pypi.python.org/pypi/netCDF4/1.5.1.1) released. Fixes incorrect `__version__`
 module variable in 1.5.1 release, plus a slicing bug ([issue #919)](https://github.com/Unidata/netcdf4-python/issues/919)).
  
 04/30/2019: Version [1.5.1](https://pypi.python.org/pypi/netCDF4/1.5.1) released. Bugfixes, no new features.

From 6edf6e29bbabcec4455f373d5fa903d24ea0f1e5 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 3 May 2019 11:18:00 -0600
Subject: [PATCH 0337/1504] fix for issue922

---
 netCDF4/utils.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/netCDF4/utils.py b/netCDF4/utils.py
index 261328c55..2e3999c03 100644
--- a/netCDF4/utils.py
+++ b/netCDF4/utils.py
@@ -365,7 +365,9 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
         datashape = broadcasted_shape(shape, datashape)
 
     # pad datashape with zeros for dimensions not being sliced (issue #906)
-    if datashape:
+    # only used when there is a slice over only one dimension
+    if datashape and len(datashape) != len(elem) and\
+       len(datashape) == sum(1 for e in elem if type(e) == slice):
         datashapenew = (); i=0
         for e in elem:
             if type(e) != slice:

From 46eb4d064eb148f92d264dec1a9f3ea0e91dbe9f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 3 May 2019 13:39:44 -0600
Subject: [PATCH 0338/1504] fix to issue #922

---
 Changelog        |  4 ++++
 netCDF4/utils.py | 11 +++++++----
 2 files changed, 11 insertions(+), 4 deletions(-)

diff --git a/Changelog b/Changelog
index 46a5112a4..60e1b9f89 100644
--- a/Changelog
+++ b/Changelog
@@ -1,3 +1,7 @@
+ since version 1.5.1.1
+==============================
+ * fix another slicing bug introduced by the fix to issue #906 (issue #922).
+
  version 1.5.1.1 (tag v1.5.1.1rel)
 ==================================
  * fixed __version__ attribute (was set incorrectly in 1.5.1 release).
diff --git a/netCDF4/utils.py b/netCDF4/utils.py
index 2e3999c03..f3332c4c5 100644
--- a/netCDF4/utils.py
+++ b/netCDF4/utils.py
@@ -409,10 +409,13 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
             if unlim and e.stop is not None and e.stop > shape[i]:
                 length = e.stop
             elif unlim and e.stop is None and datashape != ():
-                if e.start is None:
-                    length = datashape[i]
-                else:
-                    length = e.start+datashape[i]
+                try:
+                    if e.start is None:
+                        length = datashape[i]
+                    else:
+                        length = e.start+datashape[i]
+                except IndexError:
+                    raise IndexError("Illegal slice")
             else:
                 if unlim and datashape == () and len(dim) == 0:
                     # writing scalar along unlimited dimension using slicing

From 56eded44a8bce6a52d87f3495c00199adb4445e7 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 3 May 2019 13:42:05 -0600
Subject: [PATCH 0339/1504] update

---
 netCDF4/utils.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/netCDF4/utils.py b/netCDF4/utils.py
index f3332c4c5..86fa75799 100644
--- a/netCDF4/utils.py
+++ b/netCDF4/utils.py
@@ -415,7 +415,7 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
                     else:
                         length = e.start+datashape[i]
                 except IndexError:
-                    raise IndexError("Illegal slice")
+                    raise IndexError("shape of data does not conform to slice")
             else:
                 if unlim and datashape == () and len(dim) == 0:
                     # writing scalar along unlimited dimension using slicing

From 5004e700f5d1e38aa4c233009ea9f914359ab917 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 3 May 2019 14:09:20 -0600
Subject: [PATCH 0340/1504] update

---
 netCDF4/utils.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/netCDF4/utils.py b/netCDF4/utils.py
index 86fa75799..fea3a3c05 100644
--- a/netCDF4/utils.py
+++ b/netCDF4/utils.py
@@ -365,14 +365,14 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
         datashape = broadcasted_shape(shape, datashape)
 
     # pad datashape with zeros for dimensions not being sliced (issue #906)
-    # only used when there is a slice over only one dimension
+    # only used when data covers slice over subset of dimensions
     if datashape and len(datashape) != len(elem) and\
        len(datashape) == sum(1 for e in elem if type(e) == slice):
         datashapenew = (); i=0
         for e in elem:
-            if type(e) != slice:
+            if type(e) != slice and not np.iterable(e): # scalar integer slice
                 datashapenew = datashapenew + (0,)
-            else:
+            else: # slice object
                 datashapenew = datashapenew + (datashape[i],)
                 i+=1
         datashape = datashapenew

From 8862a93e89f7fc25f9df881fdd3f370c0a5b718c Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 6 May 2019 09:09:43 -0600
Subject: [PATCH 0341/1504] prepare for 1.5.1.2 release

---
 Changelog            |  4 ++--
 netCDF4/_netCDF4.pyx |  4 ++--
 setup.py             |  2 +-
 test/tst_slicing.py  | 14 ++++++++++++++
 4 files changed, 19 insertions(+), 5 deletions(-)

diff --git a/Changelog b/Changelog
index 60e1b9f89..315c40c32 100644
--- a/Changelog
+++ b/Changelog
@@ -1,5 +1,5 @@
- since version 1.5.1.1
-==============================
+ version 1.5.1.2 (tag v1.5.1.2rel)
+==================================
  * fix another slicing bug introduced by the fix to issue #906 (issue #922).
 
  version 1.5.1.1 (tag v1.5.1.1rel)
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index def2a7328..6238b8c8f 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1,5 +1,5 @@
 """
-Version 1.5.1.1
+Version 1.5.1.2
 ---------------
 - - -
 
@@ -1190,7 +1190,7 @@ except ImportError:
     # python3: zip is already python2's itertools.izip
     pass
 
-__version__ = "1.5.1.1"
+__version__ = "1.5.1.2"
 
 # Initialize numpy
 import posixpath
diff --git a/setup.py b/setup.py
index 02e3a96be..c2a76dab3 100644
--- a/setup.py
+++ b/setup.py
@@ -584,7 +584,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 
 setup(name="netCDF4",
       cmdclass=cmdclass,
-      version="1.5.1.1",
+      version="1.5.1.2",
       long_description="netCDF version 4 has many features not found in earlier versions of the library, such as hierarchical groups, zlib compression, multiple unlimited dimensions, and new data types.  It is implemented on top of HDF5.  This module implements most of the new features, and can read and write netCDF files compatible with older versions of the library.  The API is modelled after Scientific.IO.NetCDF, and should be familiar to users of that module.\n\nThis project is hosted on a `GitHub repository `_ where you may access the most up-to-date source.",
       author="Jeff Whitaker",
       author_email="jeffrey.s.whitaker@noaa.gov",
diff --git a/test/tst_slicing.py b/test/tst_slicing.py
index 66f59011f..1e06b3292 100644
--- a/test/tst_slicing.py
+++ b/test/tst_slicing.py
@@ -235,5 +235,19 @@ def test_issue919(self):
             f['v1'][:] = arr
             assert_array_equal(f['v1'][:],np.broadcast_to(arr,f['v1'].shape))
 
+    def test_issue922(self):
+        with Dataset(self.file,'w') as f:
+            f.createDimension('d1',3)
+            f.createDimension('d2',None)
+            f.createVariable('v1',np.int,('d2','d1',))
+            f['v1'][0] = np.arange(3,dtype=np.int)
+            f['v1'][1:3] = np.arange(3,dtype=np.int)
+            assert_array_equal(f['v1'][:], np.broadcast_to(np.arange(3),(3,3)))
+            f.createVariable('v2',np.int,('d1','d2',))
+            f['v2'][:,0] = np.arange(3,dtype=np.int)
+            f['v2'][:,1:3] = np.arange(6,dtype=np.int).reshape(3,2)
+            assert_array_equal(f['v2'][:,1:3],np.arange(6,dtype=np.int).reshape(3,2))
+            assert_array_equal(f['v2'][:,0],np.arange(3,dtype=np.int))
+
 if __name__ == '__main__':
     unittest.main()

From 18cb38640ebe2139d5fdf24955f26b1452c948f2 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 6 May 2019 09:11:19 -0600
Subject: [PATCH 0342/1504] update

---
 docs/netCDF4/index.html | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/netCDF4/index.html b/docs/netCDF4/index.html
index 77815cda5..0daff667f 100644
--- a/docs/netCDF4/index.html
+++ b/docs/netCDF4/index.html
@@ -4,7 +4,7 @@
   
 
     netCDF4 API documentation
-    
   
        netCDF4 module
        
-  
        Version 1.5.1.1
        
+  
        Version 1.5.1.2
        
 
        
 
        Introduction
        
 
        netcdf4-python is a Python interface to the netCDF C library.
        

From a3c233ef6bf234c880d83e152c70ede8c579d892 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 6 May 2019 10:08:27 -0600
Subject: [PATCH 0343/1504] update

---
 README.md | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/README.md b/README.md
index 9d8a86c73..896bd8f75 100644
--- a/README.md
+++ b/README.md
@@ -10,6 +10,9 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
+05/06/2019: Version [1.5.1.2](https://pypi.python.org/pypi/netCDF4/1.5.1.2) released. Fixes another slicing
+slicing regression ([issue #922)](https://github.com/Unidata/netcdf4-python/issues/922)) introduced in the 1.5.1 release.
+
 05/02/2019: Version [1.5.1.1](https://pypi.python.org/pypi/netCDF4/1.5.1.1) released. Fixes incorrect `__version__`
 module variable in 1.5.1 release, plus a slicing bug ([issue #919)](https://github.com/Unidata/netcdf4-python/issues/919)).
  

From 583b1e46249dfcaaad53f06ca90e549c5bbdd0a4 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 6 May 2019 13:12:45 -0600
Subject: [PATCH 0344/1504] fix typo

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 896bd8f75..c34896f35 100644
--- a/README.md
+++ b/README.md
@@ -11,7 +11,7 @@
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
 05/06/2019: Version [1.5.1.2](https://pypi.python.org/pypi/netCDF4/1.5.1.2) released. Fixes another slicing
-slicing regression ([issue #922)](https://github.com/Unidata/netcdf4-python/issues/922)) introduced in the 1.5.1 release.
+regression ([issue #922)](https://github.com/Unidata/netcdf4-python/issues/922)) introduced in the 1.5.1 release.
 
 05/02/2019: Version [1.5.1.1](https://pypi.python.org/pypi/netCDF4/1.5.1.1) released. Fixes incorrect `__version__`
 module variable in 1.5.1 release, plus a slicing bug ([issue #919)](https://github.com/Unidata/netcdf4-python/issues/919)).

From 1f4bdf21d37815e09ce85495a4f42343562978ff Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 29 May 2019 10:17:55 -0600
Subject: [PATCH 0345/1504] fix for scaling bug when _Unsigned is set and data
 byteorder not native

---
 Changelog            | 5 +++++
 netCDF4/_netCDF4.pyx | 8 ++++----
 setup.py             | 2 +-
 3 files changed, 10 insertions(+), 5 deletions(-)

diff --git a/Changelog b/Changelog
index 315c40c32..c5984059e 100644
--- a/Changelog
+++ b/Changelog
@@ -1,3 +1,8 @@
+ version 1.5.2 (not yet released)
+==============================
+ * fix for scaling bug when _Unsigned attribute is set and byteorder of data does not
+   match native byteorder (issue #930).
+
  version 1.5.1.2 (tag v1.5.1.2rel)
 ==================================
  * fix another slicing bug introduced by the fix to issue #906 (issue #922).
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 6238b8c8f..cdf7f271d 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1,5 +1,5 @@
 """
-Version 1.5.1.2
+Version 1.5.2
 ---------------
 - - -
 
@@ -1190,7 +1190,7 @@ except ImportError:
     # python3: zip is already python2's itertools.izip
     pass
 
-__version__ = "1.5.1.2"
+__version__ = "1.5.2"
 
 # Initialize numpy
 import posixpath
@@ -4393,7 +4393,7 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
             if self.scale:  # only do this if autoscale option is on.
                 is_unsigned = getattr(self, '_Unsigned', False)
                 if is_unsigned and data.dtype.kind == 'i':
-                    data = data.view('u%s' % data.dtype.itemsize)
+                    data=data.view('%su%s'%(data.dtype.byteorder,data.dtype.itemsize))
 
         if self.scale and self._isprimitive and valid_scaleoffset:
             # if variable has scale_factor and add_offset attributes, apply
@@ -4447,7 +4447,7 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
         is_unsigned = getattr(self, '_Unsigned', False)
         is_unsigned_int = is_unsigned and data.dtype.kind == 'i'
         if self.scale and is_unsigned_int:  # only do this if autoscale option is on.
-            dtype_unsigned_int = 'u%s' % data.dtype.itemsize
+            dtype_unsigned_int='%su%s' % (data.dtype.byteorder,data.dtype.itemsize)
             data = data.view(dtype_unsigned_int)
         # private function for creating a masked array, masking missing_values
         # and/or _FillValues.
diff --git a/setup.py b/setup.py
index c2a76dab3..fd7dc3a38 100644
--- a/setup.py
+++ b/setup.py
@@ -584,7 +584,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 
 setup(name="netCDF4",
       cmdclass=cmdclass,
-      version="1.5.1.2",
+      version="1.5.2",
       long_description="netCDF version 4 has many features not found in earlier versions of the library, such as hierarchical groups, zlib compression, multiple unlimited dimensions, and new data types.  It is implemented on top of HDF5.  This module implements most of the new features, and can read and write netCDF files compatible with older versions of the library.  The API is modelled after Scientific.IO.NetCDF, and should be familiar to users of that module.\n\nThis project is hosted on a `GitHub repository `_ where you may access the most up-to-date source.",
       author="Jeff Whitaker",
       author_email="jeffrey.s.whitaker@noaa.gov",

From 1efa5127b5f7aa8ee06d60c7dc7d3cc8dac534be Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 29 May 2019 11:41:53 -0600
Subject: [PATCH 0346/1504] add test for issue930

---
 test/tst_endian.py | 19 +++++++++++++++++++
 1 file changed, 19 insertions(+)

diff --git a/test/tst_endian.py b/test/tst_endian.py
index 685670491..db0d6936c 100644
--- a/test/tst_endian.py
+++ b/test/tst_endian.py
@@ -121,6 +121,24 @@ def issue346(file):
     assert_array_equal(datal,xl)
     nc.close()
 
+def issue930(file):
+    nc = netCDF4.Dataset(file,'w')
+    d = nc.createDimension('x',2)
+    v1 = nc.createVariable('v1','i2','x',endian='big')
+    v2 = nc.createVariable('v2','i2','x',endian='big')
+    v1[0] = 255; v1[1] = 1
+    v2[0] = 255; v2[1] = 1
+    v1._Unsigned="TRUE"; v1.missing_value=np.int16(1)
+    v2._Unsigned="TRUE"; v2.missing_value=np.int16(1)
+    nc.close()
+    nc = netCDF4.Dataset(file)
+    assert_array_equal(nc['v1'][:],np.ma.masked_array([255,1],mask=[False,True]))
+    assert_array_equal(nc['v2'][:],np.ma.masked_array([255,1],mask=[False,True]))
+    nc.set_auto_mask(False)
+    assert_array_equal(nc['v1'][:],np.array([255,1]))
+    assert_array_equal(nc['v2'][:],np.array([255,1]))
+    nc.close()
+
 class EndianTestCase(unittest.TestCase):
 
     def setUp(self):
@@ -141,6 +159,7 @@ def runTest(self):
         check_byteswap(self.file3, data)
         issue310(self.file)
         issue346(self.file2)
+        issue930(self.file2)
 
 if __name__ == '__main__':
     unittest.main()

From 982f636ba96d027dc723162158a90acf6adee093 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 29 May 2019 11:46:12 -0600
Subject: [PATCH 0347/1504] update

---
 test/tst_endian.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/tst_endian.py b/test/tst_endian.py
index db0d6936c..50da2aa36 100644
--- a/test/tst_endian.py
+++ b/test/tst_endian.py
@@ -125,7 +125,7 @@ def issue930(file):
     nc = netCDF4.Dataset(file,'w')
     d = nc.createDimension('x',2)
     v1 = nc.createVariable('v1','i2','x',endian='big')
-    v2 = nc.createVariable('v2','i2','x',endian='big')
+    v2 = nc.createVariable('v2','i2','x',endian='little')
     v1[0] = 255; v1[1] = 1
     v2[0] = 255; v2[1] = 1
     v1._Unsigned="TRUE"; v1.missing_value=np.int16(1)

From b8dc84ccd259bfbf5ea9700b7e45970770b311e1 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 29 May 2019 11:47:38 -0600
Subject: [PATCH 0348/1504] update

---
 test/tst_endian.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/test/tst_endian.py b/test/tst_endian.py
index 50da2aa36..99d6b44f8 100644
--- a/test/tst_endian.py
+++ b/test/tst_endian.py
@@ -122,6 +122,9 @@ def issue346(file):
     nc.close()
 
 def issue930(file):
+    # make sure view to unsigned data type (triggered
+    # by _Unsigned attribute being set) is correct when
+    # data byte order is non-native.
     nc = netCDF4.Dataset(file,'w')
     d = nc.createDimension('x',2)
     v1 = nc.createVariable('v1','i2','x',endian='big')

From 347aea6cad85f01d3c135f1e894b09d0a1eec444 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Juan=20Luis=20Cano=20Rodr=C3=ADguez?= 
Date: Sun, 30 Jun 2019 18:56:43 +0200
Subject: [PATCH 0349/1504] Update Python version markers

---
 setup.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/setup.py b/setup.py
index fd7dc3a38..8d5ddc692 100644
--- a/setup.py
+++ b/setup.py
@@ -603,6 +603,8 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
                    "Programming Language :: Python :: 3.3",
                    "Programming Language :: Python :: 3.4",
                    "Programming Language :: Python :: 3.5",
+                   "Programming Language :: Python :: 3.6",
+                   "Programming Language :: Python :: 3.7",
                    "Intended Audience :: Science/Research",
                    "License :: OSI Approved",
                    "Topic :: Software Development :: Libraries :: Python Modules",

From 9eb82feced602e03c4007719262419c8f6cc9ae0 Mon Sep 17 00:00:00 2001
From: Mike Taves 
Date: Mon, 8 Jul 2019 11:36:06 +1200
Subject: [PATCH 0350/1504] Refactor .travis.yml to remove obsolete sudo, add
 "cache: pip"

---
 .travis.yml | 5 +----
 1 file changed, 1 insertion(+), 4 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index c4363e980..a819d96df 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -1,6 +1,6 @@
 language: python
 dist: xenial
-sudo: true
+cache: pip
 
 addons:
   apt:
@@ -39,7 +39,6 @@ matrix:
         - DEPENDS="numpy==1.10.0 cython==0.21 ordereddict==1.1 setuptools==18.0 cftime"
     # test MPI with latest released version
     - python: 3.7
-      dist: xenial
       env: 
         - MPI=1
         - CC=mpicc.mpich
@@ -55,7 +54,6 @@ matrix:
             - libhdf5-mpich-dev
     # test MPI with latest released version
     - python: 3.7
-      dist: xenial
       env: 
         - MPI=1
         - CC=mpicc.mpich
@@ -72,7 +70,6 @@ matrix:
             - libhdf5-mpich-dev
     # test with netcdf-c from github master
     - python: 3.7
-      dist: xenial
       env:
         - MPI=1
         - CC=mpicc.mpich

From 5376efd17591ecff4a2ff0fb07b8d3fbbb9a6358 Mon Sep 17 00:00:00 2001
From: Mike Taves 
Date: Mon, 8 Jul 2019 22:47:59 +1200
Subject: [PATCH 0351/1504] Revise docstrings with Python 3

---
 netCDF4/_netCDF4.pyx   | 513 +++++++++++++++++++++++------------------
 test/tst_netcdftime.py |   2 +-
 2 files changed, 286 insertions(+), 229 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index cdf7f271d..b69335436 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -151,7 +151,7 @@ Here's an example:
     :::python
     >>> from netCDF4 import Dataset
     >>> rootgrp = Dataset("test.nc", "w", format="NETCDF4")
-    >>> print rootgrp.data_model
+    >>> print(rootgrp.data_model)
     NETCDF4
     >>> rootgrp.close()
 
@@ -182,11 +182,20 @@ in a netCDF 3 file you will get an error message.
     >>> rootgrp = Dataset("test.nc", "a")
     >>> fcstgrp = rootgrp.createGroup("forecasts")
     >>> analgrp = rootgrp.createGroup("analyses")
-    >>> print rootgrp.groups
-    OrderedDict([("forecasts",
-                  ),
-                 ("analyses",
-                  )])
+    >>> print(rootgrp.groups)
+    OrderedDict([('forecasts', 
+    group /forecasts:
+        dimensions(sizes): 
+        variables(dimensions): 
+        groups: 
+    ), ('analyses', 
+    group /analyses:
+        dimensions(sizes): 
+        variables(dimensions): 
+        groups: 
+    )])
+
+
 
 Groups can exist within groups in a `netCDF4.Dataset`, just as directories
 exist within directories in a unix filesystem. Each `netCDF4.Group` instance
@@ -212,40 +221,45 @@ object yields summary information about it's contents.
 
     :::python
     >>> def walktree(top):
-    >>>     values = top.groups.values()
-    >>>     yield values
-    >>>     for value in top.groups.values():
-    >>>         for children in walktree(value):
-    >>>             yield children
-    >>> print rootgrp
-    >>> for children in walktree(rootgrp):
-    >>>      for child in children:
-    >>>          print child
-    
-    root group (NETCDF4 file format):
-        dimensions:
-        variables:
+    ...     values = top.groups.values()
+    ...     yield values
+    ...     for value in top.groups.values():
+    ...         for children in walktree(value):
+    ...             yield children
+    >>> print(rootgrp)
+    
+    root group (NETCDF4 data model, file format HDF5):
+        dimensions(sizes): 
+        variables(dimensions): 
         groups: forecasts, analyses
-    
+    
+    >>> for children in walktree(rootgrp):
+    ...     for child in children:
+    ...         print(child)
+    
     group /forecasts:
-        dimensions:
-        variables:
+        dimensions(sizes): 
+        variables(dimensions): 
         groups: model1, model2
-    
+    
+    
     group /analyses:
-        dimensions:
-        variables:
-        groups:
-    
+        dimensions(sizes): 
+        variables(dimensions): 
+        groups: 
+    
+    
     group /forecasts/model1:
-        dimensions:
-        variables:
-        groups:
-    
+        dimensions(sizes): 
+        variables(dimensions): 
+        groups: 
+    
+    
     group /forecasts/model2:
-        dimensions:
-        variables:
-        groups:
+        dimensions(sizes): 
+        variables(dimensions): 
+        groups: 
+    
 
 ## 
        3) Dimensions in a netCDF file.
 
@@ -272,11 +286,12 @@ one, and it must be the first (leftmost) dimension of the variable.
 All of the `netCDF4.Dimension` instances are stored in a python dictionary.
 
     :::python
-    >>> print rootgrp.dimensions
-    OrderedDict([("level", ),
-                 ("time", ),
-                 ("lat", ),
-                 ("lon", )])
+    >>> print(rootgrp.dimensions)
+    OrderedDict([('level',  (unlimited): name = 'level', size = 0
+    ), ('time',  (unlimited): name = 'time', size = 0
+    ), ('lat', : name = 'lat', size = 73
+    ), ('lon', : name = 'lon', size = 144
+    )])
 
 Calling the python `len` function with a `netCDF4.Dimension` instance returns
 the current size of that dimension.
@@ -284,11 +299,11 @@ The `netCDF4.Dimension.isunlimited` method of a `netCDF4.Dimension` instance
 can be used to determine if the dimensions is unlimited, or appendable.
 
     :::python
-    >>> print len(lon)
+    >>> print(len(lon))
     144
-    >>> print lon.isunlimited()
+    >>> print(lon.isunlimited())
     False
-    >>> print time.isunlimited()
+    >>> print(time.isunlimited())
     True
 
 Printing the `netCDF4.Dimension` object
@@ -297,12 +312,15 @@ and whether it is unlimited.
 
     :::python
     >>> for dimobj in rootgrp.dimensions.values():
-    >>>    print dimobj
-     (unlimited): name = "level", size = 0
-     (unlimited): name = "time", size = 0
-    : name = "lat", size = 73
-    : name = "lon", size = 144
-     (unlimited): name = "time", size = 0
+    ...     print(dimobj)
+     (unlimited): name = 'level', size = 0
+    
+     (unlimited): name = 'time', size = 0
+    
+    : name = 'lat', size = 73
+    
+    : name = 'lon', size = 144
+    
 
 `netCDF4.Dimension` names can be changed using the
 `netCDF4.Datatset.renameDimension` method of a `netCDF4.Dataset` or
@@ -348,17 +366,20 @@ used later to access and set variable data and attributes.
     >>> longitudes = rootgrp.createVariable("lon","f4",("lon",))
     >>> # two dimensions unlimited
     >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
+    >>> temp.units = "K"
 
-To get summary info on a `netCDF4.Variable` instance in an interactive session, just print it.
+To get summary info on a `netCDF4.Variable` instance in an interactive session,
+just print it.
 
     :::python
-    >>> print temp
-    
+    >>> print(temp)
+    
     float32 temp(time, level, lat, lon)
-        least_significant_digit: 3
         units: K
     unlimited dimensions: time, level
     current shape = (0, 0, 73, 144)
+    filling on, default _FillValue of 9.969209968386869e+36 used
+    
 
 You can use a path to create a Variable inside a hierarchy of groups.
 
@@ -371,30 +392,54 @@ You can also query a `netCDF4.Dataset` or `netCDF4.Group` instance directly to o
 `netCDF4.Variable` instances using paths.
 
     :::python
-    >>> print rootgrp["/forecasts/model1"] # a Group instance
-    
+    >>> print(rootgrp["/forecasts/model1"])  # a Group instance
+    
     group /forecasts/model1:
         dimensions(sizes):
         variables(dimensions): float32 temp(time,level,lat,lon)
         groups:
-    >>> print rootgrp["/forecasts/model1/temp"] # a Variable instance
-    
+    >>> print(rootgrp["/forecasts/model1/temp"])  # a Variable instance
+    
     float32 temp(time, level, lat, lon)
     path = /forecasts/model1
     unlimited dimensions: time, level
     current shape = (0, 0, 73, 144)
-    filling on, default _FillValue of 9.96920996839e+36 used
+    filling on, default _FillValue of 9.969209968386869e+36 used
+    
+
 
 All of the variables in the `netCDF4.Dataset` or `netCDF4.Group` are stored in a
 Python dictionary, in the same way as the dimensions:
 
     :::python
-    >>> print rootgrp.variables
-    OrderedDict([("time", ),
-                 ("level", ),
-                 ("lat", ),
-                 ("lon", ),
-                 ("temp", )])
+    >>> print(rootgrp.variables)
+    OrderedDict([('time', 
+    float64 time(time)
+    unlimited dimensions: time
+    current shape = (0,)
+    filling on, default _FillValue of 9.969209968386869e+36 used
+    ), ('level', 
+    int32 level(level)
+    unlimited dimensions: level
+    current shape = (0,)
+    filling on, default _FillValue of -2147483647 used
+    ), ('lat', 
+    float32 lat(lat)
+    unlimited dimensions: 
+    current shape = (73,)
+    filling on, default _FillValue of 9.969209968386869e+36 used
+    ), ('lon', 
+    float32 lon(lon)
+    unlimited dimensions: 
+    current shape = (144,)
+    filling on, default _FillValue of 9.969209968386869e+36 used
+    ), ('temp', 
+    float32 temp(time, level, lat, lon)
+        units: K
+    unlimited dimensions: time, level
+    current shape = (0, 0, 73, 144)
+    filling on, default _FillValue of 9.969209968386869e+36 used
+    )])
 
 `netCDF4.Variable` names can be changed using the
 `netCDF4.Dataset.renameVariable` method of a `netCDF4.Dataset`
@@ -432,9 +477,9 @@ and attributes that cannot (or should not) be modified by the user.
 
     :::python
     >>> for name in rootgrp.ncattrs():
-    >>>     print "Global attr", name, "=", getattr(rootgrp,name)
+    ...     print("Global attr {} = {}".format(name, getattr(rootgrp, name)))
     Global attr description = bogus example script
-    Global attr history = Created Mon Nov  7 10.30:56 2005
+    Global attr history = Created Mon Jul  8 14:19:41 2019
     Global attr source = netCDF4 python module tutorial
 
 The `__dict__` attribute of a `netCDF4.Dataset`, `netCDF4.Group` or `netCDF4.Variable`
@@ -442,10 +487,10 @@ instance provides all the netCDF attribute name/value pairs in a python
 dictionary:
 
     :::python
-    >>> print rootgrp.__dict__
-    OrderedDict([(u"description", u"bogus example script"),
-                 (u"history", u"Created Thu Mar  3 19:30:33 2011"),
-                 (u"source", u"netCDF4 python module tutorial")])
+    >>> print(rootgrp.__dict__)
+    OrderedDict([('description', 'bogus example script'),
+                 ('history', 'Created Mon Jul  8 14:19:41 2019'),
+                 ('source', 'netCDF4 python module tutorial')])
 
 Attributes can be deleted from a netCDF `netCDF4.Dataset`, `netCDF4.Group` or
 `netCDF4.Variable` using the python `del` statement (i.e. `del grp.foo`
@@ -462,7 +507,7 @@ into it? You can just treat it like an array and assign data to a slice.
     >>> lons =  numpy.arange(-180,180,2.5)
     >>> latitudes[:] = lats
     >>> longitudes[:] = lons
-    >>> print "latitudes =\\n",latitudes[:]
+    >>> print("latitudes =\\n{}".format(latitudes[:]))
     latitudes =
     [-90.  -87.5 -85.  -82.5 -80.  -77.5 -75.  -72.5 -70.  -67.5 -65.  -62.5
      -60.  -57.5 -55.  -52.5 -50.  -47.5 -45.  -42.5 -40.  -37.5 -35.  -32.5
@@ -480,17 +525,17 @@ assign data outside the currently defined range of indices.
     >>> # append along two unlimited dimensions by assigning to slice.
     >>> nlats = len(rootgrp.dimensions["lat"])
     >>> nlons = len(rootgrp.dimensions["lon"])
-    >>> print "temp shape before adding data = ",temp.shape
-    temp shape before adding data =  (0, 0, 73, 144)
+    >>> print("temp shape before adding data = {}".format(temp.shape))
+    temp shape before adding data = (0, 0, 73, 144)
     >>>
     >>> from numpy.random import uniform
-    >>> temp[0:5,0:10,:,:] = uniform(size=(5,10,nlats,nlons))
-    >>> print "temp shape after adding data = ",temp.shape
-    temp shape after adding data =  (6, 10, 73, 144)
+    >>> temp[0:5, 0:10, :, :] = uniform(size=(5, 10, nlats, nlons))
+    >>> print("temp shape after adding data = {}".format(temp.shape))
+    temp shape after adding data = (5, 10, 73, 144)
     >>>
     >>> # levels have grown, but no values yet assigned.
-    >>> print "levels shape after adding pressure data = ",levels.shape
-    levels shape after adding pressure data =  (10,)
+    >>> print("levels shape after adding pressure data = {}".format(levels.shape))
+    levels shape after adding pressure data = (10,)
 
 Note that the size of the levels variable grows when data is appended
 along the `level` dimension of the variable `temp`, even though no
@@ -510,7 +555,8 @@ allowed, and these indices work independently along each dimension (similar
 to the way vector subscripts work in fortran).  This means that
 
     :::python
-    >>> temp[0, 0, [0,1,2,3], [0,1,2,3]]
+    >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
+    (4, 4)
 
 returns an array of shape (4,4) when slicing a netCDF variable, but for a
 numpy array it returns an array of shape (4,).
@@ -534,12 +580,12 @@ will extract time indices 0,2 and 4, pressure levels
 Hemisphere longitudes, resulting in a numpy array of shape  (3, 3, 36, 71).
 
     :::python
-    >>> print "shape of fancy temp slice = ",tempdat.shape
-    shape of fancy temp slice =  (3, 3, 36, 71)
+    >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
+    shape of fancy temp slice = (3, 3, 36, 71)
 
 ***Special note for scalar variables***: To extract data from a scalar variable
-`v` with no associated dimensions, use `numpy.asarray(v)` or `v[...]`. The result
-will be a numpy scalar array.
+`v` with no associated dimensions, use `numpy.asarray(v)` or `v[...]`.
+The result will be a numpy scalar array.
 
 By default, netcdf4-python returns numpy masked arrays with values equal to the
 `missing_value` or `_FillValue` variable attributes masked.  The
@@ -572,14 +618,15 @@ can be used:
     >>> from netCDF4 import num2date, date2num
     >>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
     >>> times[:] = date2num(dates,units=times.units,calendar=times.calendar)
-    >>> print "time values (in units %s): " % times.units+"\\n",times[:]
-    time values (in units hours since January 1, 0001):
-    [ 17533056.  17533068.  17533080.  17533092.  17533104.]
+    >>> print("time values (in units {}):\\n{}".format(times.units, times[:]))
+    time values (in units hours since 0001-01-01 00:00:00.0):
+    [17533104. 17533116. 17533128. 17533140. 17533152.]
     >>> dates = num2date(times[:],units=times.units,calendar=times.calendar)
-    >>> print "dates corresponding to time values:\\n",dates
+    >>> print("dates corresponding to time values:\\n{}".format(dates))
     dates corresponding to time values:
-    [2001-03-01 00:00:00 2001-03-01 12:00:00 2001-03-02 00:00:00
-     2001-03-02 12:00:00 2001-03-03 00:00:00]
+    [real_datetime(2001, 3, 1, 0, 0) real_datetime(2001, 3, 1, 12, 0)
+     real_datetime(2001, 3, 2, 0, 0) real_datetime(2001, 3, 2, 12, 0)
+     real_datetime(2001, 3, 3, 0, 0)]
 
 `netCDF4.num2date` converts numeric values of time in the specified `units`
 and `calendar` to datetime objects, and `netCDF4.date2num` does the reverse.
@@ -607,22 +654,22 @@ datasets are not supported).
 
     :::python
     >>> for nf in range(10):
-    >>>     f = Dataset("mftest%s.nc" % nf,"w")
-    >>>     f.createDimension("x",None)
-    >>>     x = f.createVariable("x","i",("x",))
-    >>>     x[0:10] = numpy.arange(nf*10,10*(nf+1))
-    >>>     f.close()
+    ...     with Dataset("mftest%s.nc" % nf, "w", format="NETCDF4_CLASSIC") as f:
+    ...         _ = f.createDimension("x",None)
+    ...         x = f.createVariable("x","i",("x",))
+    ...         x[0:10] = numpy.arange(nf*10,10*(nf+1))
 
 Now read all the files back in at once with `netCDF4.MFDataset`
 
     :::python
     >>> from netCDF4 import MFDataset
     >>> f = MFDataset("mftest*nc")
-    >>> print f.variables["x"][:]
-    [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
-     25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
-     50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74
-     75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99]
+    >>> print(f.variables["x"][:])
+    [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
+     24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
+     48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71
+     72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
+     96 97 98 99]
 
 Note that `netCDF4.MFDataset` can only be used to read, not write, multi-file
 datasets.
@@ -673,12 +720,12 @@ In our example, try replacing the line
 with
 
     :::python
-    >>> temp = dataset.createVariable("temp","f4",("time","level","lat","lon",),zlib=True)
+    >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True)
 
 and then
 
     :::python
-    >>> temp = dataset.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,least_significant_digit=3)
+    >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,least_significant_digit=3)
 
 and see how much smaller the resulting files are.
 
@@ -707,7 +754,7 @@ for storing numpy complex arrays.  Here's an example:
     >>> complex128 = numpy.dtype([("real",numpy.float64),("imag",numpy.float64)])
     >>> complex128_t = f.createCompoundType(complex128,"complex128")
     >>> # create a variable with this data type, write some data to it.
-    >>> f.createDimension("x_dim",None)
+    >>> x_dim = f.createDimension("x_dim",None)
     >>> v = f.createVariable("cmplx_var",complex128_t,"x_dim")
     >>> data = numpy.empty(size,complex128) # numpy structured array
     >>> data["real"] = datac.real; data["imag"] = datac.imag
@@ -720,11 +767,11 @@ for storing numpy complex arrays.  Here's an example:
     >>> datac2 = numpy.empty(datain.shape,numpy.complex128)
     >>> # .. fill it with contents of structured array.
     >>> datac2.real = datain["real"]; datac2.imag = datain["imag"]
-    >>> print datac.dtype,datac # original data
-    complex128 [ 0.54030231+0.84147098j -0.84147098+0.54030231j  -0.54030231-0.84147098j]
+    >>> print('{}: {}'.format(datac.dtype, datac)) # original data
+    complex128: [ 0.54030231+0.84147098j -0.84147098+0.54030231j -0.54030231-0.84147098j]
     >>>
-    >>> print datac2.dtype,datac2 # data from file
-    complex128 [ 0.54030231+0.84147098j -0.84147098+0.54030231j  -0.54030231-0.84147098j]
+    >>> print('{}: {}'.format(datac2.dtype, datac2)) # data from file
+    complex128: [ 0.54030231+0.84147098j -0.84147098+0.54030231j -0.54030231-0.84147098j]
 
 Compound types can be nested, but you must create the 'inner'
 ones first. All possible numpy structured arrays cannot be
@@ -735,22 +782,26 @@ in a Python dictionary, just like variables and dimensions. As always, printing
 objects gives useful summary information in an interactive session:
 
     :::python
-    >>> print f
-    
-    root group (NETCDF4 file format):
-        dimensions: x_dim
-        variables: cmplx_var
-        groups:
-    
-    >>> print f.variables["cmplx_var"]
+    >>> print(f)
+    
+    root group (NETCDF4 data model, file format HDF5):
+        dimensions(sizes): x_dim(3)
+        variables(dimensions): {'names':['real','imag'], 'formats':['
+    >>> print(f.variables["cmplx_var"])
+    
     compound cmplx_var(x_dim)
-    compound data type: [("real", ">> print f.cmptypes
-    OrderedDict([("complex128", )])
-    >>> print f.cmptypes["complex128"]
-    : name = "complex128", numpy dtype = [(u"real","
+    >>> print(f.cmptypes)
+    OrderedDict([('complex128', : name = 'complex128', numpy dtype = {'names':['real','imag'], 'formats':['>> print(f.cmptypes["complex128"])
+    : name = 'complex128', numpy dtype = {'names':['real','imag'], 'formats':['
 
 ## 
        11) Variable-length (vlen) data types.
 
@@ -784,32 +835,40 @@ In this case, they contain 1-D numpy `int32` arrays of random length between
 
     :::python
     >>> import random
+    >>> random.seed(54321)
     >>> data = numpy.empty(len(y)*len(x),object)
     >>> for n in range(len(y)*len(x)):
-    >>>    data[n] = numpy.arange(random.randint(1,10),dtype="int32")+1
+    ...     data[n] = numpy.arange(random.randint(1,10),dtype="int32")+1
     >>> data = numpy.reshape(data,(len(y),len(x)))
     >>> vlvar[:] = data
-    >>> print "vlen variable =\\n",vlvar[:]
+    >>> print("vlen variable =\\n{}".format(vlvar[:]))
     vlen variable =
-    [[[ 1  2  3  4  5  6  7  8  9 10] [1 2 3 4 5] [1 2 3 4 5 6 7 8]]
-     [[1 2 3 4 5 6 7] [1 2 3 4 5 6] [1 2 3 4 5]]
-     [[1 2 3 4 5] [1 2 3 4] [1]]
-     [[ 1  2  3  4  5  6  7  8  9 10] [ 1  2  3  4  5  6  7  8  9 10]
-      [1 2 3 4 5 6 7 8]]]
-    >>> print f
-    
-    root group (NETCDF4 file format):
-        dimensions: x, y
-        variables: phony_vlen_var
-        groups:
-    >>> print f.variables["phony_vlen_var"]
-    
+    [[array([1, 2, 3, 4, 5, 6, 7, 8], dtype=int32) array([1, 2], dtype=int32)
+      array([1, 2, 3, 4], dtype=int32)]
+     [array([1, 2, 3], dtype=int32)
+      array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)
+      array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)]
+     [array([1, 2, 3, 4, 5, 6, 7], dtype=int32) array([1, 2, 3], dtype=int32)
+      array([1, 2, 3, 4, 5, 6], dtype=int32)]
+     [array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)
+      array([1, 2, 3, 4, 5], dtype=int32) array([1, 2], dtype=int32)]]
+    >>> print(f)
+    
+    root group (NETCDF4 data model, file format HDF5):
+        dimensions(sizes): x(3), y(4)
+        variables(dimensions): int32 ESC[4mphony_vlen_varESC[0m(y,x)
+        groups: 
+    
+    >>> print(f.variables["phony_vlen_var"])
+    
     vlen phony_vlen_var(y, x)
     vlen data type: int32
-    unlimited dimensions:
+    unlimited dimensions: 
     current shape = (4, 3)
-    >>> print f.VLtypes["phony_vlen"]
-    : name = "phony_vlen", numpy dtype = int32
+    
+    >>> print(f.vltypes["phony_vlen"])
+    : name = 'phony_vlen', numpy dtype = int32
+    
 
 Numpy object arrays containing python strings can also be written as vlen
 variables,  For vlen strings, you don't need to create a vlen data type.
@@ -819,7 +878,7 @@ with fixed length greater than 1) when calling the
 
     :::python
     >>> z = f.createDimension("z",10)
-    >>> strvar = rootgrp.createVariable("strvar", str, "z")
+    >>> strvar = f.createVariable("strvar", str, "z")
 
 In this example, an object array is filled with random python strings with
 random lengths between 2 and 12 characters, and the data in the object
@@ -829,24 +888,27 @@ array is assigned to the vlen string variable.
     >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
     >>> data = numpy.empty(10,"O")
     >>> for n in range(10):
-    >>>     stringlen = random.randint(2,12)
-    >>>     data[n] = "".join([random.choice(chars) for i in range(stringlen)])
+    ...     stringlen = random.randint(2,12)
+    ...     data[n] = "".join([random.choice(chars) for i in range(stringlen)])
     >>> strvar[:] = data
-    >>> print "variable-length string variable:\\n",strvar[:]
+    >>> print("variable-length string variable:\\n{}".format(strvar[:]))
     variable-length string variable:
-    [aDy29jPt 5DS9X8 jd7aplD b8t4RM jHh8hq KtaPWF9cQj Q1hHN5WoXSiT MMxsVeq tdLUzvVTzj]
-    >>> print f
-    
-    root group (NETCDF4 file format):
-        dimensions: x, y, z
-        variables: phony_vlen_var, strvar
-        groups:
-    >>> print f.variables["strvar"]
-    
+    ['Lh' '25F8wBbMI' '53rmM' 'vvjnb3t63ao' 'qjRBQk6w' 'aJh' 'QF'
+     'jtIJbJACaQk4' '3Z5' 'bftIIq']
+    >>> print(f)
+    
+    root group (NETCDF4 data model, file format HDF5):
+        dimensions(sizes): x(3), y(4), z(10)
+        variables(dimensions): int32 phony_vlen_var(y,x),  strvar(z)
+        groups: 
+    
+    >>> print(f.variables["strvar"])
+    
     vlen strvar(z)
-    vlen data type: 
-    unlimited dimensions:
-    current size = (10,)
+    vlen data type: 
+    unlimited dimensions: 
+    current shape = (10,)
+    
 
 It is also possible to set contents of vlen string variables with numpy arrays
 of any string or unicode data type. Note, however, that accessing the contents
@@ -866,19 +928,15 @@ values and their names are used to define an Enum data type using
     :::python
     >>> nc = Dataset('clouds.nc','w')
     >>> # python dict with allowed values and their names.
-    >>> enum_dict = {u'Altocumulus': 7, u'Missing': 255,
-    >>> u'Stratus': 2, u'Clear': 0,
-    >>> u'Nimbostratus': 6, u'Cumulus': 4, u'Altostratus': 5,
-    >>> u'Cumulonimbus': 1, u'Stratocumulus': 3}
+    >>> enum_dict = {'Altocumulus': 7, 'Missing': 255,
+    ... 'Stratus': 2, 'Clear': 0,
+    ... 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5,
+    ... 'Cumulonimbus': 1, 'Stratocumulus': 3}
     >>> # create the Enum type called 'cloud_t'.
     >>> cloud_type = nc.createEnumType(numpy.uint8,'cloud_t',enum_dict)
-    >>> print cloud_type
-    : name = 'cloud_t',
-    numpy dtype = uint8, fields/values ={u'Cumulus': 4,
-    u'Altocumulus': 7, u'Missing': 255,
-    u'Stratus': 2, u'Clear': 0,
-    u'Cumulonimbus': 1, u'Stratocumulus': 3,
-    u'Nimbostratus': 6, u'Altostratus': 5}
+    >>> print(cloud_type)
+    : name = 'cloud_t', numpy dtype = uint8, fields/values ={'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, 'Stratocumulus': 3}
+    
 
 A new variable can be created in the usual way using this data type.
 Integer data is written to the variable that represents the named
@@ -890,30 +948,26 @@ specified names.
     >>> time = nc.createDimension('time',None)
     >>> # create a 1d variable of type 'cloud_type'.
     >>> # The fill_value is set to the 'Missing' named value.
-    >>> cloud_var =
-    >>> nc.createVariable('primary_cloud',cloud_type,'time',
-    >>> fill_value=enum_dict['Missing'])
+    >>> cloud_var = nc.createVariable('primary_cloud',cloud_type,'time',
+    ...                               fill_value=enum_dict['Missing'])
     >>> # write some data to the variable.
-    >>> cloud_var[:] = [enum_dict['Clear'],enum_dict['Stratus'],
-    >>> enum_dict['Cumulus'],enum_dict['Missing'],
-    >>> enum_dict['Cumulonimbus']]
+    >>> cloud_var[:] = [enum_dict[k] for k in ['Clear', 'Stratus', 'Cumulus',
+    ...                                        'Missing', 'Cumulonimbus']]
     >>> nc.close()
     >>> # reopen the file, read the data.
     >>> nc = Dataset('clouds.nc')
     >>> cloud_var = nc.variables['primary_cloud']
-    >>> print cloud_var
-    
+    >>> print(cloud_var)
+    
     enum primary_cloud(time)
         _FillValue: 255
     enum data type: uint8
     unlimited dimensions: time
     current shape = (5,)
-    >>> print cloud_var.datatype.enum_dict
-    {u'Altocumulus': 7, u'Missing': 255, u'Stratus': 2,
-    u'Clear': 0, u'Nimbostratus': 6, u'Cumulus': 4,
-    u'Altostratus': 5, u'Cumulonimbus': 1,
-    u'Stratocumulus': 3}
-    >>> print cloud_var[:]
+    
+    >>> print(cloud_var.datatype.enum_dict)
+    {'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, 'Stratocumulus': 3}
+    >>> print(cloud_var[:])
     [0 2 4 -- 1]
     >>> nc.close()
 
@@ -941,7 +995,7 @@ when a new dataset is created or an existing dataset is opened,
 use the `parallel` keyword to enable parallel access.
 
     :::python
-    >>> nc = Dataset('parallel_tst.nc','w',parallel=True)
+    >>> nc = Dataset('parallel_test.nc','w',parallel=True)
 
 The optional `comm` keyword may be used to specify a particular
 MPI communicator (`MPI_COMM_WORLD` is used by default).  Each process (or rank)
@@ -950,7 +1004,7 @@ written to a different variable index on each task
 
     :::python
     >>> d = nc.createDimension('dim',4)
-    >>> v = nc.createVariable('var', numpy.int, 'dim')
+    >>> v = nc.createVariable('var', np.int, 'dim')
     >>> v[rank] = rank
     >>> nc.close()
 
@@ -958,9 +1012,9 @@ written to a different variable index on each task
     netcdf parallel_test {
     dimensions:
         dim = 4 ;
-        variables:
+    variables:
         int64 var(dim) ;
-        data:
+    data:
 
         var = 0, 1, 2, 3 ;
     }
@@ -1010,18 +1064,19 @@ fixed-width byte string array (dtype `S#`), otherwise a numpy unicode (dtype
 characters with one more dimension. For example,
 
     :::python
+    >>> from netCDF4 import stringtochar
     >>> nc = Dataset('stringtest.nc','w',format='NETCDF4_CLASSIC')
-    >>> nc.createDimension('nchars',3)
-    >>> nc.createDimension('nstrings',None)
+    >>> _ = nc.createDimension('nchars',3)
+    >>> _ = nc.createDimension('nstrings',None)
     >>> v = nc.createVariable('strings','S1',('nstrings','nchars'))
     >>> datain = numpy.array(['foo','bar'],dtype='S3')
     >>> v[:] = stringtochar(datain) # manual conversion to char array
-    >>> v[:] # data returned as char array
+    >>> print(v[:]) # data returned as char array
     [[b'f' b'o' b'o']
-    [b'b' b'a' b'r']]
+     [b'b' b'a' b'r']]
     >>> v._Encoding = 'ascii' # this enables automatic conversion
     >>> v[:] = datain # conversion to char array done internally
-    >>> v[:] # data returned in numpy string array
+    >>> print(v[:])  # data returned in numpy string array
     ['foo' 'bar']
     >>> nc.close()
 
@@ -1044,25 +1099,25 @@ Here's an example:
     :::python
     >>> nc = Dataset('compoundstring_example.nc','w')
     >>> dtype = numpy.dtype([('observation', 'f4'),
-                      ('station_name','S80')])
+    ...                      ('station_name','S10')])
     >>> station_data_t = nc.createCompoundType(dtype,'station_data')
-    >>> nc.createDimension('station',None)
+    >>> _ = nc.createDimension('station',None)
     >>> statdat = nc.createVariable('station_obs', station_data_t, ('station',))
     >>> data = numpy.empty(2,dtype)
     >>> data['observation'][:] = (123.,3.14)
     >>> data['station_name'][:] = ('Boulder','New York')
-    >>> statdat.dtype # strings actually stored as character arrays
-    {'names':['observation','station_name'], 'formats':['>> print(statdat.dtype) # strings actually stored as character arrays
+    {'names':['observation','station_name'], 'formats':['>> statdat[:] = data # strings converted to character arrays internally
-    >>> statdat[:] # character arrays converted back to strings
-    [(123.  , 'Boulder') (  3.14, 'New York')]
-    >>> statdat[:].dtype
-    {'names':['observation','station_name'], 'formats':['>> print(statdat[:])  # character arrays converted back to strings
+    [(123.  , b'Boulder') (  3.14, b'New York')]
+    >>> print(statdat[:].dtype)
+    {'names':['observation','station_name'], 'formats':['>> statdat.set_auto_chartostring(False) # turn off auto-conversion
     >>> statdat[:] = data.view(dtype=[('observation', 'f4'),('station_name','S1',10)])
-    >>> statdat[:] # now structured array with char array subtype is returned
-    [(123.  , ['B', 'o', 'u', 'l', 'd', 'e', 'r', '', '', ''])
-    (  3.14, ['N', 'e', 'w', ' ', 'Y', 'o', 'r', 'k', '', ''])]
+    >>> print(statdat[:])  # now structured array with char array subtype is returned
+    [(123.  , [b'B', b'o', b'u', b'l', b'd', b'e', b'r', b'', b'', b''])
+     (  3.14, [b'N', b'e', b'w', b' ', b'Y', b'o', b'r', b'k', b'', b''])]
     >>> nc.close()
 
 Note that there is currently no support for mapping numpy structured arrays with
@@ -1094,11 +1149,12 @@ approaches.
     >>> v = nc.createVariable('v',numpy.int32,'x')
     >>> v[0:5] = numpy.arange(5)
     >>> print(nc)
-    
+    
     root group (NETCDF4 data model, file format HDF5):
-    dimensions(sizes): x(5)
-    variables(dimensions): int32 v(x)
-    groups:
+        dimensions(sizes): x(5)
+        variables(dimensions): int32 v(x)
+        groups: 
+    
     >>> print(nc['v'][:])
     [0 1 2 3 4]
     >>> nc.close() # file saved to disk
@@ -1106,16 +1162,17 @@ approaches.
     >>> # python memory buffer.
     >>> # read the newly created netcdf file into a python
     >>> # bytes object.
-    >>> f = open('diskless_example.nc', 'rb')
-    >>> nc_bytes = f.read(); f.close()
+    >>> with open('diskless_example.nc', 'rb') as f:
+    ...     nc_bytes = f.read()
     >>> # create a netCDF in-memory dataset from the bytes object.
     >>> nc = Dataset('inmemory.nc', memory=nc_bytes)
     >>> print(nc)
-    
+    
     root group (NETCDF4 data model, file format HDF5):
-    dimensions(sizes): x(5)
-    variables(dimensions): int32 v(x)
-    groups:
+        dimensions(sizes): x(5)
+        variables(dimensions): int32 v(x)
+        groups: 
+    
     >>> print(nc['v'][:])
     [0 1 2 3 4]
     >>> nc.close()
@@ -1129,17 +1186,17 @@ approaches.
     >>> v[0:5] = numpy.arange(5)
     >>> nc_buf = nc.close() # close returns memoryview
     >>> print(type(nc_buf))
-    
+    
     >>> # save nc_buf to disk, read it back in and check.
-    >>> f = open('inmemory.nc', 'wb')
-    >>> f.write(nc_buf); f.close()
+    >>> with open('inmemory.nc', 'wb') as f:
+    ...     f.write(nc_buf)
     >>> nc = Dataset('inmemory.nc')
     >>> print(nc)
-    
+    
     root group (NETCDF4 data model, file format HDF5):
-    dimensions(sizes): x(5)
-    variables(dimensions): int32 v(x)
-    groups:
+        dimensions(sizes): x(5)
+        variables(dimensions): int32 v(x)
+        groups:
     >>> print(nc['v'][:])
     [0 1 2 3 4]
     >>> nc.close()
@@ -6089,18 +6146,18 @@ Example usage (See `netCDF4.MFDataset.__init__` for more details):
     >>> # create a series of netCDF files with a variable sharing
     >>> # the same unlimited dimension.
     >>> for nf in range(10):
-    >>>     f = Dataset("mftest%s.nc" % nf,"w",format='NETCDF4_CLASSIC')
-    >>>     f.createDimension("x",None)
-    >>>     x = f.createVariable("x","i",("x",))
-    >>>     x[0:10] = np.arange(nf*10,10*(nf+1))
-    >>>     f.close()
+    ...     with Dataset("mftest%s.nc" % nf, "w", format='NETCDF4_CLASSIC') as f:
+    ...         f.createDimension("x",None)
+    ...         x = f.createVariable("x","i",("x",))
+    ...         x[0:10] = np.arange(nf*10,10*(nf+1))
     >>> # now read all those files in at once, in one Dataset.
     >>> f = MFDataset("mftest*nc")
-    >>> print f.variables["x"][:]
-    [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
-     25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
-     50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74
-     75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99]
+    >>> print(f.variables["x"][:])
+    [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
+     24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
+     48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71
+     72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
+     96 97 98 99]
     """
 
     def __init__(self, files, check=False, aggdim=None, exclude=[],
@@ -6564,14 +6621,14 @@ Example usage (See `netCDF4.MFTime.__init__` for more details):
     >>> f1.close()
     >>> f2.close()
     >>> # Read the two files in at once, in one Dataset.
-    >>> f = MFDataset("mftest*nc")
+    >>> f = MFDataset("mftest_*nc")
     >>> t = f.variables["time"]
-    >>> print t.units
+    >>> print(t.units)
     days since 2000-01-01
-    >>> print t[32] # The value written in the file, inconsistent with the MF time units.
+    >>> print(t[32])  # The value written in the file, inconsistent with the MF time units.
     1
     >>> T = MFTime(t)
-    >>> print T[32]
+    >>> print(T[32])
     32
     """
 
diff --git a/test/tst_netcdftime.py b/test/tst_netcdftime.py
index 99be101d3..def6940e2 100644
--- a/test/tst_netcdftime.py
+++ b/test/tst_netcdftime.py
@@ -523,7 +523,7 @@ def __init__(self, start, n, step, units, calendar='standard'):
 
             :Example:
             >>> t = TestTime(datetime(1989, 2, 18), 45, 6, 'hours since 1979-01-01')
-            >>> print num2date(t[1], t.units)
+            >>> print(num2date(t[1], t.units))
             1989-02-18 06:00:00
             """
             self.units = units

From 38f43582104bf7fc49ef32688ce792d04762128c Mon Sep 17 00:00:00 2001
From: Filipe Fernandes 
Date: Tue, 9 Jul 2019 14:55:49 -0500
Subject: [PATCH 0352/1504] use strict

---
 .appveyor.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.appveyor.yml b/.appveyor.yml
index 7b247abda..1d29864b1 100644
--- a/.appveyor.yml
+++ b/.appveyor.yml
@@ -27,8 +27,8 @@ install:
   - cmd: call %CONDA_INSTALL_LOCN%\Scripts\activate.bat
   - cmd: conda config --set always_yes yes --set changeps1 no --set show_channel_urls true
   - cmd: conda update conda
-  - cmd: conda config --remove channels defaults --force
   - cmd: conda config --add channels conda-forge --force
+  - cmd: conda config --set channel_priority strict
   - cmd: set PYTHONUNBUFFERED=1
   - cmd: conda install conda-build vs2008_express_vc_python_patch
   - cmd: call setup_x64

From e91d2e3b4546b96841003199a47af13b0311eb75 Mon Sep 17 00:00:00 2001
From: Mike Taves 
Date: Wed, 10 Jul 2019 08:56:52 +1200
Subject: [PATCH 0353/1504] Support for Python 2.7, 3.5, 3.6 and 3.7

---
 .travis.yml | 1 +
 setup.py    | 3 ---
 2 files changed, 1 insertion(+), 3 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index a819d96df..167a22b4b 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -17,6 +17,7 @@ env:
 
 python:
   - "2.7"
+  - "3.5"
   - "3.6"
   - "3.7"
   - "3.8-dev"
diff --git a/setup.py b/setup.py
index 8d5ddc692..febc02081 100644
--- a/setup.py
+++ b/setup.py
@@ -597,11 +597,8 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
                 'meteorology', 'climate'],
       classifiers=["Development Status :: 3 - Alpha",
                    "Programming Language :: Python :: 2",
-                   "Programming Language :: Python :: 2.6",
                    "Programming Language :: Python :: 2.7",
                    "Programming Language :: Python :: 3",
-                   "Programming Language :: Python :: 3.3",
-                   "Programming Language :: Python :: 3.4",
                    "Programming Language :: Python :: 3.5",
                    "Programming Language :: Python :: 3.6",
                    "Programming Language :: Python :: 3.7",

From 90bb94a1b42e00fb0be91108ffa278f4e840f2b4 Mon Sep 17 00:00:00 2001
From: Mike Taves 
Date: Wed, 10 Jul 2019 21:37:21 +1200
Subject: [PATCH 0354/1504] Refactor Python 3.7+ to use dict built-in instead
 of OrderedDict

OrderedDict is part of collections module for supported Python versions
---
 netCDF4/_netCDF4.pyx | 77 +++++++++++++++++++++++++++++++-------------
 test/tst_atts.py     |  7 ++--
 2 files changed, 56 insertions(+), 28 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index b69335436..7bb966ff2 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1233,14 +1233,10 @@ from cpython.bytes cimport PyBytes_FromStringAndSize
 # pure python utilities
 from .utils import (_StartCountStride, _quantize, _find_dim, _walk_grps,
                     _out_array_shape, _sortbylist, _tostr, _safecast, _is_int)
-# try to use built-in ordered dict in python >= 2.7
-try:
+import sys
+if sys.version_info[0:2] < (3, 7):
+    # Python 3.7+ guarantees order; older versions need OrderedDict
     from collections import OrderedDict
-except ImportError: # or else use drop-in substitute
-    try:
-        from ordereddict import OrderedDict
-    except ImportError:
-        raise ImportError('please install ordereddict (https://pypi.python.org/pypi/ordereddict)')
 try:
     from itertools import izip as zip
 except ImportError:
@@ -1254,7 +1250,6 @@ import posixpath
 from cftime import num2date, date2num, date2index
 import numpy
 import weakref
-import sys
 import warnings
 from glob import glob
 from numpy import ma
@@ -1677,9 +1672,15 @@ cdef _get_types(group):
             ierr = nc_inq_typeids(_grpid, &ntypes, typeids)
         _ensure_nc_success(ierr)
     # create empty dictionary for CompoundType instances.
-    cmptypes = OrderedDict()
-    vltypes = OrderedDict()
-    enumtypes = OrderedDict()
+    if sys.version_info[0:2] < (3, 7):
+        cmptypes = OrderedDict()
+        vltypes = OrderedDict()
+        enumtypes = OrderedDict()
+    else:
+        cmptypes = dict()
+        vltypes = dict()
+        enumtypes = dict()
+
     if ntypes > 0:
         for n from 0 <= n < ntypes:
             xtype = typeids[n]
@@ -1735,7 +1736,10 @@ cdef _get_dims(group):
         ierr = nc_inq_ndims(_grpid, &numdims)
     _ensure_nc_success(ierr)
     # create empty dictionary for dimensions.
-    dimensions = OrderedDict()
+    if sys.version_info[0:2] < (3, 7):
+        dimensions = OrderedDict()
+    else:
+        dimensions = dict()
     if numdims > 0:
         dimids = malloc(sizeof(int) * numdims)
         if group.data_model == 'NETCDF4':
@@ -1766,7 +1770,10 @@ cdef _get_grps(group):
         ierr = nc_inq_grps(_grpid, &numgrps, NULL)
     _ensure_nc_success(ierr)
     # create dictionary containing `netCDF4.Group` instances for groups in this group
-    groups = OrderedDict()
+    if sys.version_info[0:2] < (3, 7):
+        groups = OrderedDict()
+    else:
+        groups = dict()
     if numgrps > 0:
         grpids = malloc(sizeof(int) * numgrps)
         with nogil:
@@ -1796,7 +1803,10 @@ cdef _get_vars(group):
         ierr = nc_inq_nvars(_grpid, &numvars)
     _ensure_nc_success(ierr, err_cls=AttributeError)
     # create empty dictionary for variables.
-    variables = OrderedDict()
+    if sys.version_info[0:2] < (3, 7):
+        variables = OrderedDict()
+    else:
+        variables = dict()
     if numvars > 0:
         # get variable ids.
         varids = malloc(sizeof(int) * numvars)
@@ -2373,7 +2383,10 @@ strings.
         if self.data_model == 'NETCDF4':
             self.groups = _get_grps(self)
         else:
-            self.groups = OrderedDict()
+            if sys.version_info[0:2] < (3, 7):
+                self.groups = OrderedDict()
+            else:
+                self.groups = dict()
 
     # these allow Dataset objects to be used via a "with" statement.
     def __enter__(self):
@@ -2954,7 +2967,11 @@ attributes."""
                 values = []
                 for name in names:
                     values.append(_get_att(self, NC_GLOBAL, name))
-                return OrderedDict(zip(names,values))
+                gen = zip(names, values)
+                if sys.version_info[0:2] < (3, 7):
+                    return OrderedDict(gen)
+                else:
+                    return dict(gen)
             else:
                 raise AttributeError
         elif name in _private_atts:
@@ -3280,12 +3297,21 @@ Additional read-only class variables:
             bytestr = _strencode(name)
             groupname = bytestr
             _ensure_nc_success(nc_def_grp(parent._grpid, groupname, &self._grpid))
-            self.cmptypes = OrderedDict()
-            self.vltypes = OrderedDict()
-            self.enumtypes = OrderedDict()
-            self.dimensions = OrderedDict()
-            self.variables = OrderedDict()
-            self.groups = OrderedDict()
+            if sys.version_info[0:2] < (3, 7):
+                self.cmptypes = OrderedDict()
+                self.vltypes = OrderedDict()
+                self.enumtypes = OrderedDict()
+                self.dimensions = OrderedDict()
+                self.variables = OrderedDict()
+                self.groups = OrderedDict()
+            else:
+                self.cmptypes = dict()
+                self.vltypes = dict()
+                self.enumtypes = dict()
+                self.dimensions = dict()
+                self.variables = dict()
+                self.groups = dict()
+
 
     def close(self):
         """
@@ -4351,7 +4377,12 @@ details."""
                 values = []
                 for name in names:
                     values.append(_get_att(self._grp, self._varid, name))
-                return OrderedDict(zip(names,values))
+                gen = zip(names, values)
+                if sys.version_info[0:2] < (3, 7):
+                    return OrderedDict(gen)
+                else:
+                    return dict(gen)
+
             else:
                 raise AttributeError
         elif name in _private_atts:
diff --git a/test/tst_atts.py b/test/tst_atts.py
index c9b39aac7..9e3d65371 100644
--- a/test/tst_atts.py
+++ b/test/tst_atts.py
@@ -7,13 +7,10 @@
 import warnings
 
 import numpy as NP
+from collections import OrderedDict
 from numpy.random.mtrand import uniform
-import netCDF4
 
-try:
-    from collections import OrderedDict
-except ImportError: # or else use drop-in substitute
-    from ordereddict import OrderedDict
+import netCDF4
 
 # test attribute creation.
 FILE_NAME = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name

From e138f782ba937a0a95c04a18d0ba0034d449aec5 Mon Sep 17 00:00:00 2001
From: Mike Taves 
Date: Wed, 10 Jul 2019 22:10:34 +1200
Subject: [PATCH 0355/1504] Remove underline from variable name in Dataset
 string repr

---
 netCDF4/_netCDF4.pyx | 11 ++++++-----
 1 file changed, 6 insertions(+), 5 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index b69335436..e96711ecd 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -395,9 +395,10 @@ You can also query a `netCDF4.Dataset` or `netCDF4.Group` instance directly to o
     >>> print(rootgrp["/forecasts/model1"])  # a Group instance
     
     group /forecasts/model1:
-        dimensions(sizes):
+        dimensions(sizes): 
         variables(dimensions): float32 temp(time,level,lat,lon)
-        groups:
+        groups: 
+    
     >>> print(rootgrp["/forecasts/model1/temp"])  # a Variable instance
     
     float32 temp(time, level, lat, lon)
@@ -786,7 +787,7 @@ objects gives useful summary information in an interactive session:
     
     root group (NETCDF4 data model, file format HDF5):
         dimensions(sizes): x_dim(3)
-        variables(dimensions): {'names':['real','imag'], 'formats':['
     >>> print(f.variables["cmplx_var"])
@@ -856,7 +857,7 @@ In this case, they contain 1-D numpy `int32` arrays of random length between
     
     root group (NETCDF4 data model, file format HDF5):
         dimensions(sizes): x(3), y(4)
-        variables(dimensions): int32 ESC[4mphony_vlen_varESC[0m(y,x)
+        variables(dimensions): int32 phony_vlen_var(y,x)
         groups: 
     
     >>> print(f.variables["phony_vlen_var"])
@@ -2447,7 +2448,7 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
         dimnames = tuple([_tostr(dimname)+'(%s)'%len(self.dimensions[dimname])\
         for dimname in self.dimensions.keys()])
         varnames = tuple(\
-        [_tostr(self.variables[varname].dtype)+' \033[4m'+_tostr(varname)+'\033[0m'+
+        [_tostr(self.variables[varname].dtype)+' '+_tostr(varname)+
         (((_tostr(self.variables[varname].dimensions)
         .replace("u'",""))\
         .replace("'",""))\

From 397b85f565baf611ca79c4f59fedff3f5ce81229 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 11 Jul 2019 07:25:23 -0400
Subject: [PATCH 0356/1504] fix for issue #957 (size of scalar var is a float)

---
 netCDF4/_netCDF4.pyx | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index b69335436..1dac88824 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -4093,7 +4093,8 @@ behavior is similar to Fortran or Matlab, but different than numpy.
     property size:
         """Return the number of stored elements."""
         def __get__(self):
-            return numpy.prod(self.shape)
+            # issue #957: add int since prod(())=1.0
+            return int(numpy.prod(self.shape))
 
     property dimensions:
         """get variables's dimension names"""

From 03b142b928e203a7dabbbc5d8ed73c3ecba5cd09 Mon Sep 17 00:00:00 2001
From: Mike Taves 
Date: Fri, 12 Jul 2019 08:45:36 +1200
Subject: [PATCH 0357/1504] Update ChangeLog and add a few items to .gitignore

---
 .gitignore | 4 ++++
 Changelog  | 9 +++++++--
 2 files changed, 11 insertions(+), 2 deletions(-)

diff --git a/.gitignore b/.gitignore
index 89fdd2a41..11d620216 100644
--- a/.gitignore
+++ b/.gitignore
@@ -3,5 +3,9 @@ build/
 dist/
 *.egg-info/
 netCDF4/_netCDF4.c
+netCDF4/*.so
 include/constants.pyx
 netcdftime/_netcdftime.c
+venv/
+.eggs/
+.idea/
diff --git a/Changelog b/Changelog
index c5984059e..89c04d1a7 100644
--- a/Changelog
+++ b/Changelog
@@ -1,7 +1,12 @@
  version 1.5.2 (not yet released)
 ==============================
- * fix for scaling bug when _Unsigned attribute is set and byteorder of data does not
-   match native byteorder (issue #930).
+ * fix for scaling bug when _Unsigned attribute is set and byteorder of data
+   does not match native byteorder (issue #930).
+ * revise documentation for Python 3 (issue #946).
+ * establish support for Python 2.7, 3.5, 3.6 and 3.7 (issue #948).
+ * use dict built-in instead of OrderedDict for Python 3.7+
+   (pull request #955).
+ * remove underline ANSI in Dataset string representation (pull request #956)
 
  version 1.5.1.2 (tag v1.5.1.2rel)
 ==================================

From 9ca9aa3374cc6ecf31d9c44316261b9b99874dc5 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 11 Jul 2019 21:31:21 -0400
Subject: [PATCH 0358/1504] add Changelog entry

---
 Changelog | 1 +
 1 file changed, 1 insertion(+)

diff --git a/Changelog b/Changelog
index 89c04d1a7..06c5eb2f1 100644
--- a/Changelog
+++ b/Changelog
@@ -7,6 +7,7 @@
  * use dict built-in instead of OrderedDict for Python 3.7+
    (pull request #955).
  * remove underline ANSI in Dataset string representation (pull request #956)
+ * fix for issue #957 (size of scalar var is a float since numpy.prod(())=1.0).
 
  version 1.5.1.2 (tag v1.5.1.2rel)
 ==================================

From df6f1a73877ff87f210eddbbd9bbab9856c8ea7b Mon Sep 17 00:00:00 2001
From: Mike Taves 
Date: Wed, 17 Jul 2019 23:09:49 +1200
Subject: [PATCH 0359/1504] Remove newlines most __repr__ methods

Also update docstrings that show Python 3.7 output with dict
---
 Changelog            |   3 +-
 netCDF4/_netCDF4.pyx | 204 +++++++++++++++++--------------------------
 2 files changed, 82 insertions(+), 125 deletions(-)

diff --git a/Changelog b/Changelog
index 06c5eb2f1..df751ee54 100644
--- a/Changelog
+++ b/Changelog
@@ -6,7 +6,8 @@
  * establish support for Python 2.7, 3.5, 3.6 and 3.7 (issue #948).
  * use dict built-in instead of OrderedDict for Python 3.7+
    (pull request #955).
- * remove underline ANSI in Dataset string representation (pull request #956)
+ * remove underline ANSI in Dataset string representation (pull request #956).
+ * remove newlines from string representation (pull request #960).
  * fix for issue #957 (size of scalar var is a float since numpy.prod(())=1.0).
 
  version 1.5.1.2 (tag v1.5.1.2rel)
diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index cdcae432e..1b3c0aa98 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -183,17 +183,15 @@ in a netCDF 3 file you will get an error message.
     >>> fcstgrp = rootgrp.createGroup("forecasts")
     >>> analgrp = rootgrp.createGroup("analyses")
     >>> print(rootgrp.groups)
-    OrderedDict([('forecasts', 
+    {'forecasts': 
     group /forecasts:
         dimensions(sizes): 
         variables(dimensions): 
-        groups: 
-    ), ('analyses', 
+        groups: , 'analyses': 
     group /analyses:
         dimensions(sizes): 
         variables(dimensions): 
-        groups: 
-    )])
+        groups: }
 
 
 
@@ -232,7 +230,6 @@ object yields summary information about it's contents.
         dimensions(sizes): 
         variables(dimensions): 
         groups: forecasts, analyses
-    
     >>> for children in walktree(rootgrp):
     ...     for child in children:
     ...         print(child)
@@ -241,25 +238,21 @@ object yields summary information about it's contents.
         dimensions(sizes): 
         variables(dimensions): 
         groups: model1, model2
-    
     
     group /analyses:
         dimensions(sizes): 
         variables(dimensions): 
         groups: 
-    
     
     group /forecasts/model1:
         dimensions(sizes): 
         variables(dimensions): 
         groups: 
-    
     
     group /forecasts/model2:
         dimensions(sizes): 
         variables(dimensions): 
         groups: 
-    
 
 ## 
        3) Dimensions in a netCDF file.
 
@@ -287,11 +280,7 @@ All of the `netCDF4.Dimension` instances are stored in a python dictionary.
 
     :::python
     >>> print(rootgrp.dimensions)
-    OrderedDict([('level',  (unlimited): name = 'level', size = 0
-    ), ('time',  (unlimited): name = 'time', size = 0
-    ), ('lat', : name = 'lat', size = 73
-    ), ('lon', : name = 'lon', size = 144
-    )])
+    {'level':  (unlimited): name = 'level', size = 0, 'time':  (unlimited): name = 'time', size = 0, 'lat': : name = 'lat', size = 73, 'lon': : name = 'lon', size = 144}
 
 Calling the python `len` function with a `netCDF4.Dimension` instance returns
 the current size of that dimension.
@@ -314,13 +303,9 @@ and whether it is unlimited.
     >>> for dimobj in rootgrp.dimensions.values():
     ...     print(dimobj)
      (unlimited): name = 'level', size = 0
-    
      (unlimited): name = 'time', size = 0
-    
     : name = 'lat', size = 73
-    
     : name = 'lon', size = 144
-    
 
 `netCDF4.Dimension` names can be changed using the
 `netCDF4.Datatset.renameDimension` method of a `netCDF4.Dataset` or
@@ -379,7 +364,6 @@ just print it.
     unlimited dimensions: time, level
     current shape = (0, 0, 73, 144)
     filling on, default _FillValue of 9.969209968386869e+36 used
-    
 
 You can use a path to create a Variable inside a hierarchy of groups.
 
@@ -398,7 +382,6 @@ You can also query a `netCDF4.Dataset` or `netCDF4.Group` instance directly to o
         dimensions(sizes): 
         variables(dimensions): float32 temp(time,level,lat,lon)
         groups: 
-    
     >>> print(rootgrp["/forecasts/model1/temp"])  # a Variable instance
     
     float32 temp(time, level, lat, lon)
@@ -406,7 +389,6 @@ You can also query a `netCDF4.Dataset` or `netCDF4.Group` instance directly to o
     unlimited dimensions: time, level
     current shape = (0, 0, 73, 144)
     filling on, default _FillValue of 9.969209968386869e+36 used
-    
 
 
 All of the variables in the `netCDF4.Dataset` or `netCDF4.Group` are stored in a
@@ -414,33 +396,28 @@ Python dictionary, in the same way as the dimensions:
 
     :::python
     >>> print(rootgrp.variables)
-    OrderedDict([('time', 
+    {'time': 
     float64 time(time)
     unlimited dimensions: time
     current shape = (0,)
-    filling on, default _FillValue of 9.969209968386869e+36 used
-    ), ('level', 
+    filling on, default _FillValue of 9.969209968386869e+36 used, 'level': 
     int32 level(level)
     unlimited dimensions: level
     current shape = (0,)
-    filling on, default _FillValue of -2147483647 used
-    ), ('lat', 
+    filling on, default _FillValue of -2147483647 used, 'lat': 
     float32 lat(lat)
     unlimited dimensions: 
     current shape = (73,)
-    filling on, default _FillValue of 9.969209968386869e+36 used
-    ), ('lon', 
+    filling on, default _FillValue of 9.969209968386869e+36 used, 'lon': 
     float32 lon(lon)
     unlimited dimensions: 
     current shape = (144,)
-    filling on, default _FillValue of 9.969209968386869e+36 used
-    ), ('temp', 
+    filling on, default _FillValue of 9.969209968386869e+36 used, 'temp': 
     float32 temp(time, level, lat, lon)
         units: K
     unlimited dimensions: time, level
     current shape = (0, 0, 73, 144)
-    filling on, default _FillValue of 9.969209968386869e+36 used
-    )])
+    filling on, default _FillValue of 9.969209968386869e+36 used}
 
 `netCDF4.Variable` names can be changed using the
 `netCDF4.Dataset.renameVariable` method of a `netCDF4.Dataset`
@@ -489,9 +466,7 @@ dictionary:
 
     :::python
     >>> print(rootgrp.__dict__)
-    OrderedDict([('description', 'bogus example script'),
-                 ('history', 'Created Mon Jul  8 14:19:41 2019'),
-                 ('source', 'netCDF4 python module tutorial')])
+    {'description': 'bogus example script', 'history': 'Created Mon Jul  8 14:19:41 2019', 'source': 'netCDF4 python module tutorial'}
 
 Attributes can be deleted from a netCDF `netCDF4.Dataset`, `netCDF4.Group` or
 `netCDF4.Variable` using the python `del` statement (i.e. `del grp.foo`
@@ -789,20 +764,16 @@ objects gives useful summary information in an interactive session:
         dimensions(sizes): x_dim(3)
         variables(dimensions): {'names':['real','imag'], 'formats':['
     >>> print(f.variables["cmplx_var"])
     
     compound cmplx_var(x_dim)
     compound data type: {'names':['real','imag'], 'formats':['
     >>> print(f.cmptypes)
-    OrderedDict([('complex128', : name = 'complex128', numpy dtype = {'names':['real','imag'], 'formats':[': name = 'complex128', numpy dtype = {'names':['real','imag'], 'formats':['>> print(f.cmptypes["complex128"])
     : name = 'complex128', numpy dtype = {'names':['real','imag'], 'formats':['
 
 ## 
        11) Variable-length (vlen) data types.
 
@@ -859,17 +830,14 @@ In this case, they contain 1-D numpy `int32` arrays of random length between
         dimensions(sizes): x(3), y(4)
         variables(dimensions): int32 phony_vlen_var(y,x)
         groups: 
-    
     >>> print(f.variables["phony_vlen_var"])
     
     vlen phony_vlen_var(y, x)
     vlen data type: int32
     unlimited dimensions: 
     current shape = (4, 3)
-    
     >>> print(f.vltypes["phony_vlen"])
     : name = 'phony_vlen', numpy dtype = int32
-    
 
 Numpy object arrays containing python strings can also be written as vlen
 variables,  For vlen strings, you don't need to create a vlen data type.
@@ -902,14 +870,12 @@ array is assigned to the vlen string variable.
         dimensions(sizes): x(3), y(4), z(10)
         variables(dimensions): int32 phony_vlen_var(y,x),  strvar(z)
         groups: 
-    
     >>> print(f.variables["strvar"])
     
     vlen strvar(z)
     vlen data type: 
     unlimited dimensions: 
     current shape = (10,)
-    
 
 It is also possible to set contents of vlen string variables with numpy arrays
 of any string or unicode data type. Note, however, that accessing the contents
@@ -937,7 +903,6 @@ values and their names are used to define an Enum data type using
     >>> cloud_type = nc.createEnumType(numpy.uint8,'cloud_t',enum_dict)
     >>> print(cloud_type)
     : name = 'cloud_t', numpy dtype = uint8, fields/values ={'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, 'Stratocumulus': 3}
-    
 
 A new variable can be created in the usual way using this data type.
 Integer data is written to the variable that represents the named
@@ -965,7 +930,6 @@ specified names.
     enum data type: uint8
     unlimited dimensions: time
     current shape = (5,)
-    
     >>> print(cloud_var.datatype.enum_dict)
     {'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, 'Stratocumulus': 3}
     >>> print(cloud_var[:])
@@ -1155,7 +1119,6 @@ approaches.
         dimensions(sizes): x(5)
         variables(dimensions): int32 v(x)
         groups: 
-    
     >>> print(nc['v'][:])
     [0 1 2 3 4]
     >>> nc.close() # file saved to disk
@@ -1173,7 +1136,6 @@ approaches.
         dimensions(sizes): x(5)
         variables(dimensions): int32 v(x)
         groups: 
-    
     >>> print(nc['v'][:])
     [0 1 2 3 4]
     >>> nc.close()
@@ -2457,9 +2419,9 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
             return unicode(self).encode('utf-8')
 
     def __unicode__(self):
-        ncdump = ['%r\n' % type(self)]
-        dimnames = tuple([_tostr(dimname)+'(%s)'%len(self.dimensions[dimname])\
-        for dimname in self.dimensions.keys()])
+        ncdump = [repr(type(self))]
+        dimnames = tuple(_tostr(dimname)+'(%s)'%len(self.dimensions[dimname])\
+        for dimname in self.dimensions.keys())
         varnames = tuple(\
         [_tostr(self.variables[varname].dtype)+' '+_tostr(varname)+
         (((_tostr(self.variables[varname].dimensions)
@@ -2467,19 +2429,18 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
         .replace("'",""))\
         .replace(", ",","))\
         .replace(",)",")") for varname in self.variables.keys()])
-        grpnames = tuple([_tostr(grpname) for grpname in self.groups.keys()])
+        grpnames = tuple(_tostr(grpname) for grpname in self.groups.keys())
         if self.path == '/':
-            ncdump.append('root group (%s data model, file format %s):\n' %
+            ncdump.append('root group (%s data model, file format %s):' %
                     (self.data_model, self.disk_format))
         else:
-            ncdump.append('group %s:\n' % self.path)
-        attrs = ['    %s: %s\n' % (name,self.getncattr(name)) for name in\
-                self.ncattrs()]
-        ncdump = ncdump + attrs
-        ncdump.append('    dimensions(sizes): %s\n' % ', '.join(dimnames))
-        ncdump.append('    variables(dimensions): %s\n' % ', '.join(varnames))
-        ncdump.append('    groups: %s\n' % ', '.join(grpnames))
-        return ''.join(ncdump)
+            ncdump.append('group %s:' % self.path)
+        for name in self.ncattrs():
+            ncdump.append('    %s: %s' % (name, self.getncattr(name)))
+        ncdump.append('    dimensions(sizes): %s' % ', '.join(dimnames))
+        ncdump.append('    variables(dimensions): %s' % ', '.join(varnames))
+        ncdump.append('    groups: %s' % ', '.join(grpnames))
+        return '\n'.join(ncdump)
 
     def _close(self, check_err):
         cdef int ierr = nc_close(self._grpid)
@@ -3440,9 +3401,11 @@ Read-only class variables:
         if not dir(self._grp):
             return 'Dimension object no longer valid'
         if self.isunlimited():
-            return repr(type(self))+" (unlimited): name = '%s', size = %s\n" % (self._name,len(self))
+            return "%r (unlimited): name = '%s', size = %s" %\
+                (type(self), self._name, len(self))
         else:
-            return repr(type(self))+": name = '%s', size = %s\n" % (self._name,len(self))
+            return "%r: name = '%s', size = %s" %\
+                (type(self), self._name, len(self))
 
     def __len__(self):
         # len(`netCDF4.Dimension` instance) returns current size of dimension
@@ -3990,37 +3953,32 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         cdef int ierr, no_fill
         if not dir(self._grp):
             return 'Variable object no longer valid'
-        ncdump_var = ['%r\n' % type(self)]
-        dimnames = tuple([_tostr(dimname) for dimname in self.dimensions])
-        attrs = ['    %s: %s\n' % (name,self.getncattr(name)) for name in\
-                self.ncattrs()]
+        ncdump = [repr(type(self))]
+        show_more_dtype = True
         if self._iscompound:
-            ncdump_var.append('%s %s(%s)\n' %\
-            ('compound',self._name,', '.join(dimnames)))
+            kind = 'compound'
         elif self._isvlen:
-            ncdump_var.append('%s %s(%s)\n' %\
-            ('vlen',self._name,', '.join(dimnames)))
+            kind = 'vlen'
         elif self._isenum:
-            ncdump_var.append('%s %s(%s)\n' %\
-            ('enum',self._name,', '.join(dimnames)))
+            kind = 'enum'
         else:
-            ncdump_var.append('%s %s(%s)\n' %\
-            (self.dtype,self._name,', '.join(dimnames)))
-        ncdump_var = ncdump_var + attrs
-        if self._iscompound:
-            ncdump_var.append('compound data type: %s\n' % self.dtype)
-        elif self._isvlen:
-            ncdump_var.append('vlen data type: %s\n' % self.dtype)
-        elif self._isenum:
-            ncdump_var.append('enum data type: %s\n' % self.dtype)
+            show_more_dtype = False
+            kind = str(self.dtype)
+        dimnames = tuple(_tostr(dimname) for dimname in self.dimensions)
+        ncdump.append('%s %s(%s)' %\
+            (kind, self._name, ', '.join(dimnames)))
+        for name in self.ncattrs():
+            ncdump.append('    %s: %s' % (name, self.getncattr(name)))
+        if show_more_dtype:
+            ncdump.append('%s data type: %s' % (kind, self.dtype))
         unlimdims = []
         for dimname in self.dimensions:
             dim = _find_dim(self._grp, dimname)
             if dim.isunlimited():
                 unlimdims.append(dimname)
-        if (self._grp.path != '/'): ncdump_var.append('path = %s\n' % self._grp.path)
-        ncdump_var.append('unlimited dimensions: %s\n' % ', '.join(unlimdims))
-        ncdump_var.append('current shape = %s\n' % repr(self.shape))
+        if (self._grp.path != '/'): ncdump.append('path = %s' % self._grp.path)
+        ncdump.append('unlimited dimensions: %s' % ', '.join(unlimdims))
+        ncdump.append('current shape = %r' % (self.shape,))
         if __netcdf4libversion__ < '4.5.1' and\
             self._grp.file_format.startswith('NETCDF3'):
             # issue #908: no_fill not correct for NETCDF3 files before 4.5.1
@@ -4039,15 +3997,15 @@ behavior is similar to Fortran or Matlab, but different than numpy.
                 except AttributeError:
                     fillval = default_fillvals[self.dtype.str[1:]]
                     if self.dtype.str[1:] in ['u1','i1']:
-                        msg = 'filling on, default _FillValue of %s ignored\n' % fillval
+                        msg = 'filling on, default _FillValue of %s ignored' % fillval
                     else:
-                        msg = 'filling on, default _FillValue of %s used\n' % fillval
-                ncdump_var.append(msg)
+                        msg = 'filling on, default _FillValue of %s used' % fillval
+                ncdump.append(msg)
             else:
-                ncdump_var.append('filling off\n')
+                ncdump.append('filling off')
 
 
-        return ''.join(ncdump_var)
+        return '\n'.join(ncdump)
 
     def _getdims(self):
         # Private method to get variables's dimension names
@@ -5588,8 +5546,8 @@ the user.
             return unicode(self).encode('utf-8')
 
     def __unicode__(self):
-        return repr(type(self))+": name = '%s', numpy dtype = %s\n" %\
-        (self.name,self.dtype)
+        return "%r: name = '%s', numpy dtype = %s" %\
+            (type(self), self.name, self.dtype)
 
     def __reduce__(self):
         # raise error is user tries to pickle a CompoundType object.
@@ -5878,10 +5836,10 @@ the user.
 
     def __unicode__(self):
         if self.dtype == str:
-            return repr(type(self))+': string type'
+            return '%r: string type' % (type(self),)
         else:
-            return repr(type(self))+": name = '%s', numpy dtype = %s\n" %\
-            (self.name, self.dtype)
+            return "%r: name = '%s', numpy dtype = %s" %\
+                (type(self), self.name, self.dtype)
 
     def __reduce__(self):
         # raise error is user tries to pickle a VLType object.
@@ -5996,9 +5954,8 @@ the user.
             return unicode(self).encode('utf-8')
 
     def __unicode__(self):
-        return repr(type(self))+\
-        ": name = '%s', numpy dtype = %s, fields/values =%s\n" %\
-        (self.name, self.dtype, self.enum_dict)
+        return "%r: name = '%s', numpy dtype = %s, fields/values =%s" %\
+            (type(self), self.name, self.dtype, self.enum_dict)
 
     def __reduce__(self):
         # raise error is user tries to pickle a EnumType object.
@@ -6426,22 +6383,21 @@ Example usage (See `netCDF4.MFDataset.__init__` for more details):
             dset.close()
 
     def __repr__(self):
-        ncdump = ['%r\n' % type(self)]
-        dimnames = tuple([str(dimname) for dimname in self.dimensions.keys()])
-        varnames = tuple([str(varname) for varname in self.variables.keys()])
+        ncdump = [repr(type(self))]
+        dimnames = tuple(str(dimname) for dimname in self.dimensions.keys())
+        varnames = tuple(str(varname) for varname in self.variables.keys())
         grpnames = ()
         if self.path == '/':
-            ncdump.append('root group (%s data model, file format %s):\n' %
+            ncdump.append('root group (%s data model, file format %s):' %
                     (self.data_model[0], self.disk_format[0]))
         else:
-            ncdump.append('group %s:\n' % self.path)
-        attrs = ['    %s: %s\n' % (name,self.__dict__[name]) for name in\
-                self.ncattrs()]
-        ncdump = ncdump + attrs
-        ncdump.append('    dimensions = %s\n' % str(dimnames))
-        ncdump.append('    variables = %s\n' % str(varnames))
-        ncdump.append('    groups = %s\n' % str(grpnames))
-        return ''.join(ncdump)
+            ncdump.append('group %s:' % self.path)
+        for name in self.ncattrs():
+            ncdump.append('    %s: %s' % (name, self.__dict__[name]))
+        ncdump.append('    dimensions = %s' % str(dimnames))
+        ncdump.append('    variables = %s' % str(varnames))
+        ncdump.append('    groups = %s' % str(grpnames))
+        return '\n'.join(ncdump)
 
     def __reduce__(self):
         # raise error is user tries to pickle a MFDataset object.
@@ -6458,9 +6414,11 @@ class _Dimension(object):
         return True
     def __repr__(self):
         if self.isunlimited():
-            return repr(type(self))+" (unlimited): name = '%s', size = %s\n" % (self._name,len(self))
+            return "%r (unlimited): name = '%s', size = %s" %\
+                (type(self), self._name, len(self))
         else:
-            return repr(type(self))+": name = '%s', size = %s\n" % (self._name,len(self))
+            return "%r: name = '%s', size = %s" %\
+                (type(self), self._name, len(self))
 
 class _Variable(object):
     def __init__(self, dset, varname, var, recdimname):
@@ -6488,21 +6446,19 @@ class _Variable(object):
         except:
             raise AttributeError(name)
     def __repr__(self):
-        ncdump_var = ['%r\n' % type(self)]
-        dimnames = tuple([str(dimname) for dimname in self.dimensions])
-        attrs = ['    %s: %s\n' % (name,self.__dict__[name]) for name in\
-                self.ncattrs()]
-        ncdump_var.append('%s %s%s\n' %\
-        (self.dtype,self._name,dimnames))
-        ncdump_var = ncdump_var + attrs
+        ncdump = [repr(type(self))]
+        dimnames = tuple(str(dimname) for dimname in self.dimensions)
+        ncdump.append('%s %s%s' % (self.dtype, self._name, dimnames))
+        for name in self.ncattrs():
+            ncdump.append('    %s: %s' % (name, self.__dict__[name]))
         unlimdims = []
         for dimname in self.dimensions:
             dim = _find_dim(self._grp, dimname)
             if dim.isunlimited():
                 unlimdims.append(str(dimname))
-        ncdump_var.append('unlimited dimensions = %s\n' % repr(tuple(unlimdims)))
-        ncdump_var.append('current size = %s\n' % repr(self.shape))
-        return ''.join(ncdump_var)
+        ncdump.append('unlimited dimensions = %r' % (tuple(unlimdims),))
+        ncdump.append('current size = %r' % (self.shape,))
+        return '\n'.join(ncdump)
     def __len__(self):
         if not self._shape:
             raise TypeError('len() of unsized object')

From 3325d6759288577d003df845ceda33512d6b6697 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Thu, 18 Jul 2019 08:23:16 -0600
Subject: [PATCH 0360/1504] raise error when trying to set _FillValue using
 setncattr.

---
 netCDF4/_netCDF4.pyx | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 1b3c0aa98..f95ac3dc1 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -4112,6 +4112,13 @@ netCDF attribute with the same name as one of the reserved python
 attributes."""
         cdef nc_type xtype
         xtype=-99
+        # issue #959 - trying to set _FillValue results in mysterious
+        # error when close method is called so catch it here. It is
+        # already caught in __setattr__.
+        if name == '_FillValue':
+            msg='_FillValue attribute must be set when variable is '+\
+            'created (using fill_value keyword to createVariable)'
+            raise AttributeError(msg)
         if self._grp.data_model != 'NETCDF4': self._grp._redef()
         _set_att(self._grp, self._varid, name, value, xtype=xtype, force_ncstring=self._ncstring_attrs__)
         if self._grp.data_model != 'NETCDF4': self._grp._enddef()

From 10eb9447bca03fca9938dbe6621bdd58678e20f3 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Thu, 18 Jul 2019 08:49:01 -0600
Subject: [PATCH 0361/1504] add test, Changelog entry

---
 Changelog        |  1 +
 test/tst_atts.py | 13 +++++++++++++
 2 files changed, 14 insertions(+)

diff --git a/Changelog b/Changelog
index df751ee54..2b39d0afe 100644
--- a/Changelog
+++ b/Changelog
@@ -9,6 +9,7 @@
  * remove underline ANSI in Dataset string representation (pull request #956).
  * remove newlines from string representation (pull request #960).
  * fix for issue #957 (size of scalar var is a float since numpy.prod(())=1.0).
+ * make sure Variable.setncattr fails to set _FillValue (issue #959).
 
  version 1.5.1.2 (tag v1.5.1.2rel)
 ==================================
diff --git a/test/tst_atts.py b/test/tst_atts.py
index 9e3d65371..9d2c07fca 100644
--- a/test/tst_atts.py
+++ b/test/tst_atts.py
@@ -91,6 +91,19 @@ def setUp(self):
         v1.seqatt = SEQATT
         v1.stringseqatt = STRINGSEQATT
         v1.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
+        # issue #959: should not be able to set _FillValue after var creation
+        try:
+            v1._FillValue(-999.)
+        except AttributeError:
+            pass
+        else:
+            raise ValueError('This test should have failed.')
+        try:
+            v1.setncattr('_FillValue',-999.)
+        except AttributeError:
+            pass
+        else:
+            raise ValueError('This test should have failed.')
         # issue #485 (triggers segfault in C lib
         # with version 1.2.1 without pull request #486)
         f.foo = NP.array('bar','S')

From 43ba3e54011d8e0dd3e055b069597eb92ffcf4bc Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 24 Aug 2019 10:34:50 -0600
Subject: [PATCH 0362/1504] fix detection of parallel HDF5 support in netcdf-c
 4.6.1

---
 setup.py | 16 ++++++++++++----
 1 file changed, 12 insertions(+), 4 deletions(-)

diff --git a/setup.py b/setup.py
index febc02081..e2b9e51d9 100644
--- a/setup.py
+++ b/setup.py
@@ -49,13 +49,14 @@ def check_ifnetcdf4(netcdf4_includedir):
     return isnetcdf4
 
 
-def check_api(inc_dirs):
+def check_api(inc_dirs,netcdf_lib_version):
     has_rename_grp = False
     has_nc_inq_path = False
     has_nc_inq_format_extended = False
     has_cdf5_format = False
     has_nc_open_mem = False
     has_nc_create_mem = False
+    has_parallel_support = False
     has_parallel4_support = False
     has_pnetcdf_support = False
 
@@ -91,10 +92,16 @@ def check_api(inc_dirs):
             for line in open(ncmetapath):
                 if line.startswith('#define NC_HAS_CDF5'):
                     has_cdf5_format = bool(int(line.split()[2]))
-                elif line.startswith('#define NC_HAS_PARALLEL4'):
+                if line.startswith('#define NC_HAS_PARALLEL'):
+                    has_parallel_support = bool(int(line.split()[2]))
+                if line.startswith('#define NC_HAS_PARALLEL4'):
                     has_parallel4_support = bool(int(line.split()[2]))
-                elif line.startswith('#define NC_HAS_PNETCDF'):
+                if line.startswith('#define NC_HAS_PNETCDF'):
                     has_pnetcdf_support = bool(int(line.split()[2]))
+        # NC_HAS_PARALLEL4 missing in 4.6.1 (issue #964)
+        if netcdf_lib_version == "4.6.1":
+            if has_parallel_support and not has_pnetcdf_support:
+                has_parallel4_support = True
         break
 
     return has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \
@@ -494,7 +501,8 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     # this determines whether renameGroup and filepath methods will work.
     has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \
     has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \
-    has_parallel4_support, has_pnetcdf_support = check_api(inc_dirs)
+    has_parallel4_support, has_pnetcdf_support =\
+    check_api(inc_dirs,netcdf_lib_version)
     # for netcdf 4.4.x CDF5 format is always enabled.
     if netcdf_lib_version is not None and\
        (netcdf_lib_version > "4.4" and netcdf_lib_version < "4.5"):

From af66fd18efef5b45d1bf2d7c34a6c1b78460c606 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 24 Aug 2019 11:25:55 -0600
Subject: [PATCH 0363/1504] update

---
 setup.py | 8 +++-----
 1 file changed, 3 insertions(+), 5 deletions(-)

diff --git a/setup.py b/setup.py
index e2b9e51d9..53bc77ac5 100644
--- a/setup.py
+++ b/setup.py
@@ -49,7 +49,7 @@ def check_ifnetcdf4(netcdf4_includedir):
     return isnetcdf4
 
 
-def check_api(inc_dirs,netcdf_lib_version):
+def check_api(inc_dirs):
     has_rename_grp = False
     has_nc_inq_path = False
     has_nc_inq_format_extended = False
@@ -99,8 +99,7 @@ def check_api(inc_dirs,netcdf_lib_version):
                 if line.startswith('#define NC_HAS_PNETCDF'):
                     has_pnetcdf_support = bool(int(line.split()[2]))
         # NC_HAS_PARALLEL4 missing in 4.6.1 (issue #964)
-        if netcdf_lib_version == "4.6.1":
-            if has_parallel_support and not has_pnetcdf_support:
+        if not has_parallel4_support and has_parallel_support and not has_pnetcdf_support:
                 has_parallel4_support = True
         break
 
@@ -501,8 +500,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     # this determines whether renameGroup and filepath methods will work.
     has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \
     has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \
-    has_parallel4_support, has_pnetcdf_support =\
-    check_api(inc_dirs,netcdf_lib_version)
+    has_parallel4_support, has_pnetcdf_support = check_api(inc_dirs)
     # for netcdf 4.4.x CDF5 format is always enabled.
     if netcdf_lib_version is not None and\
        (netcdf_lib_version > "4.4" and netcdf_lib_version < "4.5"):

From 5cfac647f88eb0ea26c36b35afefa1ad3f605a46 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 24 Aug 2019 11:26:45 -0600
Subject: [PATCH 0364/1504] update

---
 Changelog | 1 +
 1 file changed, 1 insertion(+)

diff --git a/Changelog b/Changelog
index 2b39d0afe..e04f489ed 100644
--- a/Changelog
+++ b/Changelog
@@ -10,6 +10,7 @@
  * remove newlines from string representation (pull request #960).
  * fix for issue #957 (size of scalar var is a float since numpy.prod(())=1.0).
  * make sure Variable.setncattr fails to set _FillValue (issue #959).
+ * fix detection of parallel HDF5 support with netcdf-c 4.6.1 (issue #964).
 
  version 1.5.1.2 (tag v1.5.1.2rel)
 ==================================

From 44e689ce49b9e747b34945eda8e980cddc16a6fc Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 24 Aug 2019 11:27:32 -0600
Subject: [PATCH 0365/1504] update

---
 setup.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index 53bc77ac5..31acaa658 100644
--- a/setup.py
+++ b/setup.py
@@ -100,7 +100,7 @@ def check_api(inc_dirs):
                     has_pnetcdf_support = bool(int(line.split()[2]))
         # NC_HAS_PARALLEL4 missing in 4.6.1 (issue #964)
         if not has_parallel4_support and has_parallel_support and not has_pnetcdf_support:
-                has_parallel4_support = True
+            has_parallel4_support = True
         break
 
     return has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \

From 5271dba02c9ea0808dc168302a5f0396f3f32e66 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 24 Aug 2019 13:16:58 -0600
Subject: [PATCH 0366/1504] handle NC_HAS_PARALLEL=HAS_PNETCDF=1 for version
 4.6.1

---
 setup.py | 10 ++++++++--
 1 file changed, 8 insertions(+), 2 deletions(-)

diff --git a/setup.py b/setup.py
index 31acaa658..8e351a58b 100644
--- a/setup.py
+++ b/setup.py
@@ -49,7 +49,7 @@ def check_ifnetcdf4(netcdf4_includedir):
     return isnetcdf4
 
 
-def check_api(inc_dirs):
+def check_api(inc_dirs,netcdf_lib_version):
     has_rename_grp = False
     has_nc_inq_path = False
     has_nc_inq_format_extended = False
@@ -101,6 +101,11 @@ def check_api(inc_dirs):
         # NC_HAS_PARALLEL4 missing in 4.6.1 (issue #964)
         if not has_parallel4_support and has_parallel_support and not has_pnetcdf_support:
             has_parallel4_support = True
+        # for 4.6.1, if NC_HAS_PARALLEL=NC_HAS_PNETCDF=1, guess that
+        # parallel HDF5 is enabled (must guess since there is no
+        # NC_HAS_PARALLEL4)
+        elif netcdf_lib_version == "4.6.1" and not has_parallel4_support and has_parallel_support:
+            has_parallel4_support = True
         break
 
     return has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \
@@ -500,7 +505,8 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     # this determines whether renameGroup and filepath methods will work.
     has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \
     has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \
-    has_parallel4_support, has_pnetcdf_support = check_api(inc_dirs)
+    has_parallel4_support, has_pnetcdf_support = \
+    check_api(inc_dirs,netcdf_lib_version)
     # for netcdf 4.4.x CDF5 format is always enabled.
     if netcdf_lib_version is not None and\
        (netcdf_lib_version > "4.4" and netcdf_lib_version < "4.5"):

From e89b0a13875fb4b72f792d74ae0d2847e7d0a87b Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 24 Aug 2019 13:18:56 -0600
Subject: [PATCH 0367/1504] remove warning about deprecated SafeConfigParser

---
 setup.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index 8e351a58b..fceba29b4 100644
--- a/setup.py
+++ b/setup.py
@@ -193,7 +193,7 @@ def getnetcdfvers(libdirs):
 use_ncconfig = None
 if USE_SETUPCFG and os.path.exists(setup_cfg):
     sys.stdout.write('reading from setup.cfg...\n')
-    config = configparser.SafeConfigParser()
+    config = configparser.ConfigParser()
     config.read(setup_cfg)
     try:
         HDF5_dir = config.get("directories", "HDF5_dir")

From c7e4431b0869da74d6d8908611b27d6d42924fb2 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 30 Aug 2019 13:17:00 -0600
Subject: [PATCH 0368/1504] update docstrings for set_always_mask

---
 netCDF4/_netCDF4.pyx | 17 +++++++++--------
 1 file changed, 9 insertions(+), 8 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index f95ac3dc1..28b2c605c 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -3094,8 +3094,10 @@ this `netCDF4.Dataset` or `netCDF4.Group`, as well as for all
 variables in all its subgroups.
 
 **`True_or_False`**: Boolean determining if automatic conversion of
-masked arrays with no missing values to regular ararys shall be
-applied for all variables.
+masked arrays with no missing values to regular numpy arrays shall be
+applied for all variables. Default True. Set to False to restore the default behaviour
+in versions prior to 1.4.1 (numpy array returned unless missing values are present,
+otherwise masked array returned).
 
 ***Note***: Calling this function only affects existing
 variables. Variables created after calling this function will follow
@@ -5135,12 +5137,11 @@ The default value of `mask` is `True`
 turn on or off conversion of data without missing values to regular
 numpy arrays.
 
-If `always_mask` is set to `True` then a masked array with no missing
-values is converted to a regular numpy array.
-
-The default value of `always_mask` is `True` (conversions to regular
-numpy arrays are not performed).
-
+`always_mask` is a Boolean determining if automatic conversion of
+masked arrays with no missing values to regular numpy arrays shall be
+applied. Default is True. Set to False to restore the default behaviour
+in versions prior to 1.4.1 (numpy array returned unless missing values are present,
+otherwise masked array returned).
         """
         self.always_mask = bool(always_mask)
 

From 2ff2c9f688b25b2f02fdfe364818f8a2fbba100c Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 3 Sep 2019 08:00:17 -0600
Subject: [PATCH 0369/1504] update for version 1.5.2 release

---
 README.md               |   2 +
 docs/netCDF4/index.html | 518 +++++++++++++++++++++-------------------
 2 files changed, 273 insertions(+), 247 deletions(-)

diff --git a/README.md b/README.md
index c34896f35..f4cfaa1c3 100644
--- a/README.md
+++ b/README.md
@@ -10,6 +10,8 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
+09/03/2019: Version [1.5.2](https://pypi.python.org/pypi/netCDF4/1.5.2) released. Bugfixes, no new features.
+
 05/06/2019: Version [1.5.1.2](https://pypi.python.org/pypi/netCDF4/1.5.1.2) released. Fixes another slicing
 regression ([issue #922)](https://github.com/Unidata/netcdf4-python/issues/922)) introduced in the 1.5.1 release.
 
diff --git a/docs/netCDF4/index.html b/docs/netCDF4/index.html
index 0daff667f..4a8758cde 100644
--- a/docs/netCDF4/index.html
+++ b/docs/netCDF4/index.html
@@ -4,14 +4,14 @@
   
 
     netCDF4 API documentation
-    
+netcdf4-python is a Python interface..." />
 
   
   
@@ -1280,7 +1280,7 @@ 
        Index
        
 
   
        
   
        netCDF4 module
        
-  
        Version 1.5.1.2
        
+  
        Version 1.5.2
        
 
        
 
        Introduction
        
 
        netcdf4-python is a Python interface to the netCDF C library.
        
@@ -1415,7 +1415,7 @@ 
        1) Creating/Opening/Closing a netCDF file.
        
 
        Here's an example:
        
 
        >>> from netCDF4 import Dataset
 >>> rootgrp = Dataset("test.nc", "w", format="NETCDF4")
->>> print rootgrp.data_model
+>>> print(rootgrp.data_model)
 NETCDF4
 >>> rootgrp.close()
 
        
@@ -1443,11 +1443,16 @@ 
        2) Groups in a netCDF file.
        
 
        >>> rootgrp = Dataset("test.nc", "a")
 >>> fcstgrp = rootgrp.createGroup("forecasts")
 >>> analgrp = rootgrp.createGroup("analyses")
->>> print rootgrp.groups
-OrderedDict([("forecasts",
-              <netCDF4._netCDF4.Group object at 0x1b4b7b0>),
-             ("analyses",
-              <netCDF4._netCDF4.Group object at 0x1b4b970>)])
+>>> print(rootgrp.groups)
+{'forecasts': <class 'netCDF4._netCDF4.Group'>
+group /forecasts:
+    dimensions(sizes): 
+    variables(dimensions): 
+    groups: , 'analyses': <class 'netCDF4._netCDF4.Group'>
+group /analyses:
+    dimensions(sizes): 
+    variables(dimensions): 
+    groups: }
 
        
 
 
@@ -1472,39 +1477,39 @@ 
        2) Groups in a netCDF file.
        
 to walk the directory tree. Note that printing the Dataset or Group
 object yields summary information about it's contents.
        
 
        >>> def walktree(top):
->>>     values = top.groups.values()
->>>     yield values
->>>     for value in top.groups.values():
->>>         for children in walktree(value):
->>>             yield children
->>> print rootgrp
->>> for children in walktree(rootgrp):
->>>      for child in children:
->>>          print child
-<type "netCDF4._netCDF4.Dataset">
-root group (NETCDF4 file format):
-    dimensions:
-    variables:
+...     values = top.groups.values()
+...     yield values
+...     for value in top.groups.values():
+...         for children in walktree(value):
+...             yield children
+>>> print(rootgrp)
+<class 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): 
+    variables(dimensions): 
     groups: forecasts, analyses
-<type "netCDF4._netCDF4.Group">
+>>> for children in walktree(rootgrp):
+...     for child in children:
+...         print(child)
+<class 'netCDF4._netCDF4.Group'>
 group /forecasts:
-    dimensions:
-    variables:
+    dimensions(sizes): 
+    variables(dimensions): 
     groups: model1, model2
-<type "netCDF4._netCDF4.Group">
+<class 'netCDF4._netCDF4.Group'>
 group /analyses:
-    dimensions:
-    variables:
-    groups:
-<type "netCDF4._netCDF4.Group">
+    dimensions(sizes): 
+    variables(dimensions): 
+    groups: 
+<class 'netCDF4._netCDF4.Group'>
 group /forecasts/model1:
-    dimensions:
-    variables:
-    groups:
-<type "netCDF4._netCDF4.Group">
+    dimensions(sizes): 
+    variables(dimensions): 
+    groups: 
+<class 'netCDF4._netCDF4.Group'>
 group /forecasts/model2:
-    dimensions:
-    variables:
+    dimensions(sizes): 
+    variables(dimensions): 
     groups:
 
        
 
@@ -1530,11 +1535,8 @@ 
        3) Dimensions in a netCDF file.
        
 
 
 
        All of the Dimension instances are stored in a python dictionary.
        
-
        >>> print rootgrp.dimensions
-OrderedDict([("level", <netCDF4._netCDF4.Dimension object at 0x1b48030>),
-             ("time", <netCDF4._netCDF4.Dimension object at 0x1b481c0>),
-             ("lat", <netCDF4._netCDF4.Dimension object at 0x1b480f8>),
-             ("lon", <netCDF4._netCDF4.Dimension object at 0x1b48a08>)])
+
        >>> print(rootgrp.dimensions)
+{'level': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0, 'time': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0, 'lat': <class 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 73, 'lon': <class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144}
 
        
 
 
@@ -1542,11 +1544,11 @@ 
        3) Dimensions in a netCDF file.
        
 the current size of that dimension.
 The isunlimited method of a Dimension instance
 can be used to determine if the dimensions is unlimited, or appendable.
        
-
        >>> print len(lon)
+
        >>> print(len(lon))
 144
->>> print lon.isunlimited()
+>>> print(lon.isunlimited())
 False
->>> print time.isunlimited()
+>>> print(time.isunlimited())
 True
 
        
 
@@ -1555,12 +1557,11 @@ 
        3) Dimensions in a netCDF file.
        
 provides useful summary info, including the name and length of the dimension,
 and whether it is unlimited.
        
 
        >>> for dimobj in rootgrp.dimensions.values():
->>>    print dimobj
-<type "netCDF4._netCDF4.Dimension"> (unlimited): name = "level", size = 0
-<type "netCDF4._netCDF4.Dimension"> (unlimited): name = "time", size = 0
-<type "netCDF4._netCDF4.Dimension">: name = "lat", size = 73
-<type "netCDF4._netCDF4.Dimension">: name = "lon", size = 144
-<type "netCDF4._netCDF4.Dimension"> (unlimited): name = "time", size = 0
+...     print(dimobj)
+<class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0
+<class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0
+<class 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 73
+<class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144
 
        
 
 
@@ -1603,17 +1604,19 @@ 
        4) Variables in a netCDF file.
        
 >>> longitudes = rootgrp.createVariable("lon","f4",("lon",))
 >>> # two dimensions unlimited
 >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
+>>> temp.units = "K"
 
        
 
 
-
        To get summary info on a Variable instance in an interactive session, just print it.
        
-
        >>> print temp
-<type "netCDF4._netCDF4.Variable">
+
        To get summary info on a Variable instance in an interactive session,
+just print it.
        
+
        >>> print(temp)
+<class 'netCDF4._netCDF4.Variable'>
 float32 temp(time, level, lat, lon)
-    least_significant_digit: 3
     units: K
 unlimited dimensions: time, level
 current shape = (0, 0, 73, 144)
+filling on, default _FillValue of 9.969209968386869e+36 used
 
        
 
 
@@ -1625,30 +1628,47 @@ 
        4) Variables in a netCDF file.
        
 
        If the intermediate groups do not yet exist, they will be created.
        
 
        You can also query a Dataset or Group instance directly to obtain Group or
 Variable instances using paths.
        
-
        >>> print rootgrp["/forecasts/model1"] # a Group instance
-<type "netCDF4._netCDF4.Group">
+
        >>> print(rootgrp["/forecasts/model1"])  # a Group instance
+<class 'netCDF4._netCDF4.Group'>
 group /forecasts/model1:
-    dimensions(sizes):
+    dimensions(sizes): 
     variables(dimensions): float32 temp(time,level,lat,lon)
-    groups:
->>> print rootgrp["/forecasts/model1/temp"] # a Variable instance
-<type "netCDF4._netCDF4.Variable">
+    groups: 
+>>> print(rootgrp["/forecasts/model1/temp"])  # a Variable instance
+<class 'netCDF4._netCDF4.Variable'>
 float32 temp(time, level, lat, lon)
 path = /forecasts/model1
 unlimited dimensions: time, level
 current shape = (0, 0, 73, 144)
-filling on, default _FillValue of 9.96920996839e+36 used
+filling on, default _FillValue of 9.969209968386869e+36 used
 
        
 
 
 
        All of the variables in the Dataset or Group are stored in a
 Python dictionary, in the same way as the dimensions:
        
-
        >>> print rootgrp.variables
-OrderedDict([("time", <netCDF4.Variable object at 0x1b4ba70>),
-             ("level", <netCDF4.Variable object at 0x1b4bab0>),
-             ("lat", <netCDF4.Variable object at 0x1b4baf0>),
-             ("lon", <netCDF4.Variable object at 0x1b4bb30>),
-             ("temp", <netCDF4.Variable object at 0x1b4bb70>)])
+
        >>> print(rootgrp.variables)
+{'time': <class 'netCDF4._netCDF4.Variable'>
+float64 time(time)
+unlimited dimensions: time
+current shape = (0,)
+filling on, default _FillValue of 9.969209968386869e+36 used, 'level': <class 'netCDF4._netCDF4.Variable'>
+int32 level(level)
+unlimited dimensions: level
+current shape = (0,)
+filling on, default _FillValue of -2147483647 used, 'lat': <class 'netCDF4._netCDF4.Variable'>
+float32 lat(lat)
+unlimited dimensions: 
+current shape = (73,)
+filling on, default _FillValue of 9.969209968386869e+36 used, 'lon': <class 'netCDF4._netCDF4.Variable'>
+float32 lon(lon)
+unlimited dimensions: 
+current shape = (144,)
+filling on, default _FillValue of 9.969209968386869e+36 used, 'temp': <class 'netCDF4._netCDF4.Variable'>
+float32 temp(time, level, lat, lon)
+    units: K
+unlimited dimensions: time, level
+current shape = (0, 0, 73, 144)
+filling on, default _FillValue of 9.969209968386869e+36 used}
 
        
 
 
@@ -1683,9 +1703,9 @@ 
        5) Attributes in a netCDF file.
        
 built-in dir Python function will return a bunch of private methods
 and attributes that cannot (or should not) be modified by the user.
        
 
        >>> for name in rootgrp.ncattrs():
->>>     print "Global attr", name, "=", getattr(rootgrp,name)
+...     print("Global attr {} = {}".format(name, getattr(rootgrp, name)))
 Global attr description = bogus example script
-Global attr history = Created Mon Nov  7 10.30:56 2005
+Global attr history = Created Mon Jul  8 14:19:41 2019
 Global attr source = netCDF4 python module tutorial
 
        
 
@@ -1693,10 +1713,8 @@ 
        5) Attributes in a netCDF file.
        
 
        The __dict__ attribute of a Dataset, Group or Variable
 instance provides all the netCDF attribute name/value pairs in a python
 dictionary:
        
-
        >>> print rootgrp.__dict__
-OrderedDict([(u"description", u"bogus example script"),
-             (u"history", u"Created Thu Mar  3 19:30:33 2011"),
-             (u"source", u"netCDF4 python module tutorial")])
+
        >>> print(rootgrp.__dict__)
+{'description': 'bogus example script', 'history': 'Created Mon Jul  8 14:19:41 2019', 'source': 'netCDF4 python module tutorial'}
 
        
 
 
@@ -1711,7 +1729,7 @@ 
        6) Writing data to and retrieving data from a netCDF vari
 >>> lons =  numpy.arange(-180,180,2.5)
 >>> latitudes[:] = lats
 >>> longitudes[:] = lons
->>> print "latitudes =\n",latitudes[:]
+>>> print("latitudes =\n{}".format(latitudes[:]))
 latitudes =
 [-90.  -87.5 -85.  -82.5 -80.  -77.5 -75.  -72.5 -70.  -67.5 -65.  -62.5
  -60.  -57.5 -55.  -52.5 -50.  -47.5 -45.  -42.5 -40.  -37.5 -35.  -32.5
@@ -1729,17 +1747,17 @@ 
        6) Writing data to and retrieving data from a netCDF vari
 
        >>> # append along two unlimited dimensions by assigning to slice.
 >>> nlats = len(rootgrp.dimensions["lat"])
 >>> nlons = len(rootgrp.dimensions["lon"])
->>> print "temp shape before adding data = ",temp.shape
-temp shape before adding data =  (0, 0, 73, 144)
+>>> print("temp shape before adding data = {}".format(temp.shape))
+temp shape before adding data = (0, 0, 73, 144)
 >>>
 >>> from numpy.random import uniform
->>> temp[0:5,0:10,:,:] = uniform(size=(5,10,nlats,nlons))
->>> print "temp shape after adding data = ",temp.shape
-temp shape after adding data =  (6, 10, 73, 144)
+>>> temp[0:5, 0:10, :, :] = uniform(size=(5, 10, nlats, nlons))
+>>> print("temp shape after adding data = {}".format(temp.shape))
+temp shape after adding data = (5, 10, 73, 144)
 >>>
 >>> # levels have grown, but no values yet assigned.
->>> print "levels shape after adding pressure data = ",levels.shape
-levels shape after adding pressure data =  (10,)
+>>> print("levels shape after adding pressure data = {}".format(levels.shape))
+levels shape after adding pressure data = (10,)
 
        
 
 
@@ -1759,7 +1777,8 @@ 
        6) Writing data to and retrieving data from a netCDF vari
 than for numpy arrays.  Only 1-d boolean arrays and integer sequences are
 allowed, and these indices work independently along each dimension (similar
 to the way vector subscripts work in fortran).  This means that
        
-
        >>> temp[0, 0, [0,1,2,3], [0,1,2,3]]
+
        >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
+(4, 4)
 
        
 
 
@@ -1782,14 +1801,14 @@ 
        6) Writing data to and retrieving data from a netCDF vari
 
        will extract time indices 0,2 and 4, pressure levels
 850, 500 and 200 hPa, all Northern Hemisphere latitudes and Eastern
 Hemisphere longitudes, resulting in a numpy array of shape  (3, 3, 36, 71).
        
-
        >>> print "shape of fancy temp slice = ",tempdat.shape
-shape of fancy temp slice =  (3, 3, 36, 71)
+
        >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
+shape of fancy temp slice = (3, 3, 36, 71)
 
        
 
 
 
        Special note for scalar variables: To extract data from a scalar variable
-v with no associated dimensions, use numpy.asarray(v) or v[...]. The result
-will be a numpy scalar array.
        
+v with no associated dimensions, use numpy.asarray(v) or v[...].
+The result will be a numpy scalar array.
        
 
        By default, netcdf4-python returns numpy masked arrays with values equal to the
 missing_value or _FillValue variable attributes masked.  The
 set_auto_mask  Dataset and Variable methods
@@ -1817,14 +1836,15 @@ 
        7) Dealing with time coordinates.
        
 >>> from netCDF4 import num2date, date2num
 >>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
 >>> times[:] = date2num(dates,units=times.units,calendar=times.calendar)
->>> print "time values (in units %s): " % times.units+"\n",times[:]
-time values (in units hours since January 1, 0001):
-[ 17533056.  17533068.  17533080.  17533092.  17533104.]
+>>> print("time values (in units {}):\n{}".format(times.units, times[:]))
+time values (in units hours since 0001-01-01 00:00:00.0):
+[17533104. 17533116. 17533128. 17533140. 17533152.]
 >>> dates = num2date(times[:],units=times.units,calendar=times.calendar)
->>> print "dates corresponding to time values:\n",dates
+>>> print("dates corresponding to time values:\n{}".format(dates))
 dates corresponding to time values:
-[2001-03-01 00:00:00 2001-03-01 12:00:00 2001-03-02 00:00:00
- 2001-03-02 12:00:00 2001-03-03 00:00:00]
+[real_datetime(2001, 3, 1, 0, 0) real_datetime(2001, 3, 1, 12, 0)
+ real_datetime(2001, 3, 2, 0, 0) real_datetime(2001, 3, 2, 12, 0)
+ real_datetime(2001, 3, 3, 0, 0)]
 
        
 
 
@@ -1849,22 +1869,22 @@ 
        8) Reading data from a multi-file netCDF dataset.
        
 NETCDF4_CLASSIC format (NETCDF4 formatted multi-file
 datasets are not supported).
        
 
        >>> for nf in range(10):
->>>     f = Dataset("mftest%s.nc" % nf,"w")
->>>     f.createDimension("x",None)
->>>     x = f.createVariable("x","i",("x",))
->>>     x[0:10] = numpy.arange(nf*10,10*(nf+1))
->>>     f.close()
+...     with Dataset("mftest%s.nc" % nf, "w", format="NETCDF4_CLASSIC") as f:
+...         _ = f.createDimension("x",None)
+...         x = f.createVariable("x","i",("x",))
+...         x[0:10] = numpy.arange(nf*10,10*(nf+1))
 
        
 
 
 
        Now read all the files back in at once with MFDataset
        
 
        >>> from netCDF4 import MFDataset
 >>> f = MFDataset("mftest*nc")
->>> print f.variables["x"][:]
-[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
- 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
- 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74
- 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99]
+>>> print(f.variables["x"][:])
+[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
+ 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
+ 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71
+ 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
+ 96 97 98 99]
 
        
 
 
@@ -1911,12 +1931,12 @@ 
        9) Efficient compression of netCDF variables.
        
 
 
 
        with
        
-
        >>> temp = dataset.createVariable("temp","f4",("time","level","lat","lon",),zlib=True)
+
        >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True)
 
        
 
 
 
        and then
        
-
        >>> temp = dataset.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,least_significant_digit=3)
+
        >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,least_significant_digit=3)
 
        
 
 
@@ -1943,7 +1963,7 @@ 
        10) Beyond homogeneous arrays of a fixed type - compound
 >>> complex128 = numpy.dtype([("real",numpy.float64),("imag",numpy.float64)])
 >>> complex128_t = f.createCompoundType(complex128,"complex128")
 >>> # create a variable with this data type, write some data to it.
->>> f.createDimension("x_dim",None)
+>>> x_dim = f.createDimension("x_dim",None)
 >>> v = f.createVariable("cmplx_var",complex128_t,"x_dim")
 >>> data = numpy.empty(size,complex128) # numpy structured array
 >>> data["real"] = datac.real; data["imag"] = datac.imag
@@ -1956,11 +1976,11 @@ 
        10) Beyond homogeneous arrays of a fixed type - compound
 >>> datac2 = numpy.empty(datain.shape,numpy.complex128)
 >>> # .. fill it with contents of structured array.
 >>> datac2.real = datain["real"]; datac2.imag = datain["imag"]
->>> print datac.dtype,datac # original data
-complex128 [ 0.54030231+0.84147098j -0.84147098+0.54030231j  -0.54030231-0.84147098j]
+>>> print('{}: {}'.format(datac.dtype, datac)) # original data
+complex128: [ 0.54030231+0.84147098j -0.84147098+0.54030231j -0.54030231-0.84147098j]
 >>>
->>> print datac2.dtype,datac2 # data from file
-complex128 [ 0.54030231+0.84147098j -0.84147098+0.54030231j  -0.54030231-0.84147098j]
+>>> print('{}: {}'.format(datac2.dtype, datac2)) # data from file
+complex128: [ 0.54030231+0.84147098j -0.84147098+0.54030231j -0.54030231-0.84147098j]
 
        
 
 
@@ -1971,22 +1991,22 @@ 
        10) Beyond homogeneous arrays of a fixed type - compound
 All of the compound types defined for a Dataset or Group are stored
 in a Python dictionary, just like variables and dimensions. As always, printing
 objects gives useful summary information in an interactive session:
        
-
        >>> print f
-<type "netCDF4._netCDF4.Dataset">
-root group (NETCDF4 file format):
-    dimensions: x_dim
-    variables: cmplx_var
-    groups:
-<type "netCDF4._netCDF4.Variable">
->>> print f.variables["cmplx_var"]
+
        >>> print(f)
+<class 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): x_dim(3)
+    variables(dimensions): {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True} cmplx_var(x_dim)
+    groups: 
+>>> print(f.variables["cmplx_var"])
+<class 'netCDF4._netCDF4.Variable'>
 compound cmplx_var(x_dim)
-compound data type: [("real", "<f8"), ("imag", "<f8")]
+compound data type: {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}
 unlimited dimensions: x_dim
 current shape = (3,)
->>> print f.cmptypes
-OrderedDict([("complex128", <netCDF4.CompoundType object at 0x1029eb7e8>)])
->>> print f.cmptypes["complex128"]
-<type "netCDF4._netCDF4.CompoundType">: name = "complex128", numpy dtype = [(u"real","<f8"), (u"imag", "<f8")]
+>>> print(f.cmptypes)
+{'complex128': <class 'netCDF4._netCDF4.CompoundType'>: name = 'complex128', numpy dtype = {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}}
+>>> print(f.cmptypes["complex128"])
+<class 'netCDF4._netCDF4.CompoundType'>: name = 'complex128', numpy dtype = {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}
 
        
 
 
@@ -2019,32 +2039,37 @@ 
        11) Variable-length (vlen) data types.
        
 In this case, they contain 1-D numpy int32 arrays of random length between
 1 and 10.
        
 
        >>> import random
+>>> random.seed(54321)
 >>> data = numpy.empty(len(y)*len(x),object)
 >>> for n in range(len(y)*len(x)):
->>>    data[n] = numpy.arange(random.randint(1,10),dtype="int32")+1
+...     data[n] = numpy.arange(random.randint(1,10),dtype="int32")+1
 >>> data = numpy.reshape(data,(len(y),len(x)))
 >>> vlvar[:] = data
->>> print "vlen variable =\n",vlvar[:]
+>>> print("vlen variable =\n{}".format(vlvar[:]))
 vlen variable =
-[[[ 1  2  3  4  5  6  7  8  9 10] [1 2 3 4 5] [1 2 3 4 5 6 7 8]]
- [[1 2 3 4 5 6 7] [1 2 3 4 5 6] [1 2 3 4 5]]
- [[1 2 3 4 5] [1 2 3 4] [1]]
- [[ 1  2  3  4  5  6  7  8  9 10] [ 1  2  3  4  5  6  7  8  9 10]
-  [1 2 3 4 5 6 7 8]]]
->>> print f
-<type "netCDF4._netCDF4.Dataset">
-root group (NETCDF4 file format):
-    dimensions: x, y
-    variables: phony_vlen_var
-    groups:
->>> print f.variables["phony_vlen_var"]
-<type "netCDF4._netCDF4.Variable">
+[[array([1, 2, 3, 4, 5, 6, 7, 8], dtype=int32) array([1, 2], dtype=int32)
+  array([1, 2, 3, 4], dtype=int32)]
+ [array([1, 2, 3], dtype=int32)
+  array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)
+  array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)]
+ [array([1, 2, 3, 4, 5, 6, 7], dtype=int32) array([1, 2, 3], dtype=int32)
+  array([1, 2, 3, 4, 5, 6], dtype=int32)]
+ [array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)
+  array([1, 2, 3, 4, 5], dtype=int32) array([1, 2], dtype=int32)]]
+>>> print(f)
+<class 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): x(3), y(4)
+    variables(dimensions): int32 phony_vlen_var(y,x)
+    groups: 
+>>> print(f.variables["phony_vlen_var"])
+<class 'netCDF4._netCDF4.Variable'>
 vlen phony_vlen_var(y, x)
 vlen data type: int32
-unlimited dimensions:
+unlimited dimensions: 
 current shape = (4, 3)
->>> print f.VLtypes["phony_vlen"]
-<type "netCDF4._netCDF4.VLType">: name = "phony_vlen", numpy dtype = int32
+>>> print(f.vltypes["phony_vlen"])
+<class 'netCDF4._netCDF4.VLType'>: name = 'phony_vlen', numpy dtype = int32
 
        
 
 
@@ -2054,7 +2079,7 @@ 
        11) Variable-length (vlen) data types.
        
 with fixed length greater than 1) when calling the
 createVariable method.
        
 
        >>> z = f.createDimension("z",10)
->>> strvar = rootgrp.createVariable("strvar", str, "z")
+>>> strvar = f.createVariable("strvar", str, "z")
 
        
 
 
@@ -2064,24 +2089,25 @@ 
        11) Variable-length (vlen) data types.
        
 
        >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
 >>> data = numpy.empty(10,"O")
 >>> for n in range(10):
->>>     stringlen = random.randint(2,12)
->>>     data[n] = "".join([random.choice(chars) for i in range(stringlen)])
+...     stringlen = random.randint(2,12)
+...     data[n] = "".join([random.choice(chars) for i in range(stringlen)])
 >>> strvar[:] = data
->>> print "variable-length string variable:\n",strvar[:]
+>>> print("variable-length string variable:\n{}".format(strvar[:]))
 variable-length string variable:
-[aDy29jPt 5DS9X8 jd7aplD b8t4RM jHh8hq KtaPWF9cQj Q1hHN5WoXSiT MMxsVeq tdLUzvVTzj]
->>> print f
-<type "netCDF4._netCDF4.Dataset">
-root group (NETCDF4 file format):
-    dimensions: x, y, z
-    variables: phony_vlen_var, strvar
-    groups:
->>> print f.variables["strvar"]
-<type "netCDF4._netCDF4.Variable">
+['Lh' '25F8wBbMI' '53rmM' 'vvjnb3t63ao' 'qjRBQk6w' 'aJh' 'QF'
+ 'jtIJbJACaQk4' '3Z5' 'bftIIq']
+>>> print(f)
+<class 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): x(3), y(4), z(10)
+    variables(dimensions): int32 phony_vlen_var(y,x), <class 'str'> strvar(z)
+    groups: 
+>>> print(f.variables["strvar"])
+<class 'netCDF4._netCDF4.Variable'>
 vlen strvar(z)
-vlen data type: <type "str">
-unlimited dimensions:
-current size = (10,)
+vlen data type: <class 'str'>
+unlimited dimensions: 
+current shape = (10,)
 
        
 
 
@@ -2098,19 +2124,14 @@ 
        12) Enum data type.
        
 createEnumType.
        
 
        >>> nc = Dataset('clouds.nc','w')
 >>> # python dict with allowed values and their names.
->>> enum_dict = {u'Altocumulus': 7, u'Missing': 255,
->>> u'Stratus': 2, u'Clear': 0,
->>> u'Nimbostratus': 6, u'Cumulus': 4, u'Altostratus': 5,
->>> u'Cumulonimbus': 1, u'Stratocumulus': 3}
+>>> enum_dict = {'Altocumulus': 7, 'Missing': 255,
+... 'Stratus': 2, 'Clear': 0,
+... 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5,
+... 'Cumulonimbus': 1, 'Stratocumulus': 3}
 >>> # create the Enum type called 'cloud_t'.
 >>> cloud_type = nc.createEnumType(numpy.uint8,'cloud_t',enum_dict)
->>> print cloud_type
-<type 'netCDF4._netCDF4.EnumType'>: name = 'cloud_t',
-numpy dtype = uint8, fields/values ={u'Cumulus': 4,
-u'Altocumulus': 7, u'Missing': 255,
-u'Stratus': 2, u'Clear': 0,
-u'Cumulonimbus': 1, u'Stratocumulus': 3,
-u'Nimbostratus': 6, u'Altostratus': 5}
+>>> print(cloud_type)
+<class 'netCDF4._netCDF4.EnumType'>: name = 'cloud_t', numpy dtype = uint8, fields/values ={'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, 'Stratocumulus': 3}
 
        
 
 
@@ -2122,30 +2143,25 @@ 
        12) Enum data type.
        
 
        >>> time = nc.createDimension('time',None)
 >>> # create a 1d variable of type 'cloud_type'.
 >>> # The fill_value is set to the 'Missing' named value.
->>> cloud_var =
->>> nc.createVariable('primary_cloud',cloud_type,'time',
->>> fill_value=enum_dict['Missing'])
+>>> cloud_var = nc.createVariable('primary_cloud',cloud_type,'time',
+...                               fill_value=enum_dict['Missing'])
 >>> # write some data to the variable.
->>> cloud_var[:] = [enum_dict['Clear'],enum_dict['Stratus'],
->>> enum_dict['Cumulus'],enum_dict['Missing'],
->>> enum_dict['Cumulonimbus']]
+>>> cloud_var[:] = [enum_dict[k] for k in ['Clear', 'Stratus', 'Cumulus',
+...                                        'Missing', 'Cumulonimbus']]
 >>> nc.close()
 >>> # reopen the file, read the data.
 >>> nc = Dataset('clouds.nc')
 >>> cloud_var = nc.variables['primary_cloud']
->>> print cloud_var
-<type 'netCDF4._netCDF4.Variable'>
+>>> print(cloud_var)
+<class 'netCDF4._netCDF4.Variable'>
 enum primary_cloud(time)
     _FillValue: 255
 enum data type: uint8
 unlimited dimensions: time
 current shape = (5,)
->>> print cloud_var.datatype.enum_dict
-{u'Altocumulus': 7, u'Missing': 255, u'Stratus': 2,
-u'Clear': 0, u'Nimbostratus': 6, u'Cumulus': 4,
-u'Altostratus': 5, u'Cumulonimbus': 1,
-u'Stratocumulus': 3}
->>> print cloud_var[:]
+>>> print(cloud_var.datatype.enum_dict)
+{'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, 'Stratocumulus': 3}
+>>> print(cloud_var[:])
 [0 2 4 -- 1]
 >>> nc.close()
 
        
@@ -2172,7 +2188,7 @@ 
        13) Parallel IO.
        
 The parallel features of netcdf4-python are mostly transparent -
 when a new dataset is created or an existing dataset is opened,
 use the parallel keyword to enable parallel access.
        
-
        >>> nc = Dataset('parallel_tst.nc','w',parallel=True)
+
        >>> nc = Dataset('parallel_test.nc','w',parallel=True)
 
        
 
 
@@ -2181,7 +2197,7 @@ 
        13) Parallel IO.
        
 can now write to the file indepedently.  In this example the process rank is
 written to a different variable index on each task
        
 
        >>> d = nc.createDimension('dim',4)
->>> v = nc.createVariable('var', numpy.int, 'dim')
+>>> v = nc.createVariable('var', np.int, 'dim')
 >>> v[rank] = rank
 >>> nc.close()
 
@@ -2189,9 +2205,9 @@ 
        13) Parallel IO.
        
 netcdf parallel_test {
 dimensions:
     dim = 4 ;
-    variables:
+variables:
     int64 var(dim) ;
-    data:
+data:
 
     var = 0, 1, 2, 3 ;
 }
@@ -2240,18 +2256,19 @@ 
        14) Dealing with strings.
        
 U#) array is created.  When writing the data,
 stringtochar is used to convert the numpy string array to an array of
 characters with one more dimension. For example,
        
-
        >>> nc = Dataset('stringtest.nc','w',format='NETCDF4_CLASSIC')
->>> nc.createDimension('nchars',3)
->>> nc.createDimension('nstrings',None)
+
        >>> from netCDF4 import stringtochar
+>>> nc = Dataset('stringtest.nc','w',format='NETCDF4_CLASSIC')
+>>> _ = nc.createDimension('nchars',3)
+>>> _ = nc.createDimension('nstrings',None)
 >>> v = nc.createVariable('strings','S1',('nstrings','nchars'))
 >>> datain = numpy.array(['foo','bar'],dtype='S3')
 >>> v[:] = stringtochar(datain) # manual conversion to char array
->>> v[:] # data returned as char array
+>>> print(v[:]) # data returned as char array
 [[b'f' b'o' b'o']
-[b'b' b'a' b'r']]
+ [b'b' b'a' b'r']]
 >>> v._Encoding = 'ascii' # this enables automatic conversion
 >>> v[:] = datain # conversion to char array done internally
->>> v[:] # data returned in numpy string array
+>>> print(v[:])  # data returned in numpy string array
 ['foo' 'bar']
 >>> nc.close()
 
        
@@ -2273,25 +2290,25 @@ 
        14) Dealing with strings.
        
 Here's an example:
        
 
        >>> nc = Dataset('compoundstring_example.nc','w')
 >>> dtype = numpy.dtype([('observation', 'f4'),
-                  ('station_name','S80')])
+...                      ('station_name','S10')])
 >>> station_data_t = nc.createCompoundType(dtype,'station_data')
->>> nc.createDimension('station',None)
+>>> _ = nc.createDimension('station',None)
 >>> statdat = nc.createVariable('station_obs', station_data_t, ('station',))
 >>> data = numpy.empty(2,dtype)
 >>> data['observation'][:] = (123.,3.14)
 >>> data['station_name'][:] = ('Boulder','New York')
->>> statdat.dtype # strings actually stored as character arrays
-{'names':['observation','station_name'], 'formats':['<f4',('S1', (80,))], 'offsets':[0,4], 'itemsize':84, 'aligned':True}
+>>> print(statdat.dtype) # strings actually stored as character arrays
+{'names':['observation','station_name'], 'formats':['<f4',('S1', (10,))], 'offsets':[0,4], 'itemsize':16, 'aligned':True}
 >>> statdat[:] = data # strings converted to character arrays internally
->>> statdat[:] # character arrays converted back to strings
-[(123.  , 'Boulder') (  3.14, 'New York')]
->>> statdat[:].dtype
-{'names':['observation','station_name'], 'formats':['<f4','S80'], 'offsets':[0,4], 'itemsize':84, 'aligned':True}
+>>> print(statdat[:])  # character arrays converted back to strings
+[(123.  , b'Boulder') (  3.14, b'New York')]
+>>> print(statdat[:].dtype)
+{'names':['observation','station_name'], 'formats':['<f4','S10'], 'offsets':[0,4], 'itemsize':16, 'aligned':True}
 >>> statdat.set_auto_chartostring(False) # turn off auto-conversion
 >>> statdat[:] = data.view(dtype=[('observation', 'f4'),('station_name','S1',10)])
->>> statdat[:] # now structured array with char array subtype is returned
-[(123.  , ['B', 'o', 'u', 'l', 'd', 'e', 'r', '', '', ''])
-(  3.14, ['N', 'e', 'w', ' ', 'Y', 'o', 'r', 'k', '', ''])]
+>>> print(statdat[:])  # now structured array with char array subtype is returned
+[(123.  , [b'B', b'o', b'u', b'l', b'd', b'e', b'r', b'', b'', b''])
+ (  3.14, [b'N', b'e', b'w', b' ', b'Y', b'o', b'r', b'k', b'', b''])]
 >>> nc.close()
 
        
 
@@ -2321,11 +2338,11 @@ 
        15) In-memory (diskless) Datasets.
        
 >>> v = nc.createVariable('v',numpy.int32,'x')
 >>> v[0:5] = numpy.arange(5)
 >>> print(nc)
-<type 'netCDF4._netCDF4.Dataset'>
+<class 'netCDF4._netCDF4.Dataset'>
 root group (NETCDF4 data model, file format HDF5):
-dimensions(sizes): x(5)
-variables(dimensions): int32 v(x)
-groups:
+    dimensions(sizes): x(5)
+    variables(dimensions): int32 v(x)
+    groups: 
 >>> print(nc['v'][:])
 [0 1 2 3 4]
 >>> nc.close() # file saved to disk
@@ -2333,16 +2350,16 @@ 
        15) In-memory (diskless) Datasets.
        
 >>> # python memory buffer.
 >>> # read the newly created netcdf file into a python
 >>> # bytes object.
->>> f = open('diskless_example.nc', 'rb')
->>> nc_bytes = f.read(); f.close()
+>>> with open('diskless_example.nc', 'rb') as f:
+...     nc_bytes = f.read()
 >>> # create a netCDF in-memory dataset from the bytes object.
 >>> nc = Dataset('inmemory.nc', memory=nc_bytes)
 >>> print(nc)
-<type 'netCDF4._netCDF4.Dataset'>
+<class 'netCDF4._netCDF4.Dataset'>
 root group (NETCDF4 data model, file format HDF5):
-dimensions(sizes): x(5)
-variables(dimensions): int32 v(x)
-groups:
+    dimensions(sizes): x(5)
+    variables(dimensions): int32 v(x)
+    groups: 
 >>> print(nc['v'][:])
 [0 1 2 3 4]
 >>> nc.close()
@@ -2356,17 +2373,17 @@ 
        15) In-memory (diskless) Datasets.
        
 >>> v[0:5] = numpy.arange(5)
 >>> nc_buf = nc.close() # close returns memoryview
 >>> print(type(nc_buf))
-<type 'memoryview'>
+<class 'memoryview'>
 >>> # save nc_buf to disk, read it back in and check.
->>> f = open('inmemory.nc', 'wb')
->>> f.write(nc_buf); f.close()
+>>> with open('inmemory.nc', 'wb') as f:
+...     f.write(nc_buf)
 >>> nc = Dataset('inmemory.nc')
 >>> print(nc)
-<type 'netCDF4._netCDF4.Dataset'>
+<class 'netCDF4._netCDF4.Dataset'>
 root group (NETCDF4 data model, file format HDF5):
-dimensions(sizes): x(5)
-variables(dimensions): int32 v(x)
-groups:
+    dimensions(sizes): x(5)
+    variables(dimensions): int32 v(x)
+    groups:
 >>> print(nc['v'][:])
 [0 1 2 3 4]
 >>> nc.close()
@@ -3427,8 +3444,10 @@ 
        Static methods
        
 this Dataset or Group, as well as for all
 variables in all its subgroups.
        
 
        True_or_False: Boolean determining if automatic conversion of
-masked arrays with no missing values to regular ararys shall be
-applied for all variables.
        
+masked arrays with no missing values to regular numpy arrays shall be
+applied for all variables. Default True. Set to False to restore the default behaviour
+in versions prior to 1.4.1 (numpy array returned unless missing values are present,
+otherwise masked array returned).
        
 
        Note: Calling this function only affects existing
 variables. Variables created after calling this function will follow
 the default behaviour.
        
@@ -4445,8 +4464,10 @@ 
        Static methods
        
 this Dataset or Group, as well as for all
 variables in all its subgroups.
        
 
        True_or_False: Boolean determining if automatic conversion of
-masked arrays with no missing values to regular ararys shall be
-applied for all variables.
        
+masked arrays with no missing values to regular numpy arrays shall be
+applied for all variables. Default True. Set to False to restore the default behaviour
+in versions prior to 1.4.1 (numpy array returned unless missing values are present,
+otherwise masked array returned).
        
 
        Note: Calling this function only affects existing
 variables. Variables created after calling this function will follow
 the default behaviour.
        
@@ -4683,18 +4704,18 @@ 
        Static methods
        
 >>> # create a series of netCDF files with a variable sharing
 >>> # the same unlimited dimension.
 >>> for nf in range(10):
->>>     f = Dataset("mftest%s.nc" % nf,"w",format='NETCDF4_CLASSIC')
->>>     f.createDimension("x",None)
->>>     x = f.createVariable("x","i",("x",))
->>>     x[0:10] = np.arange(nf*10,10*(nf+1))
->>>     f.close()
+...     with Dataset("mftest%s.nc" % nf, "w", format='NETCDF4_CLASSIC') as f:
+...         f.createDimension("x",None)
+...         x = f.createVariable("x","i",("x",))
+...         x[0:10] = np.arange(nf*10,10*(nf+1))
 >>> # now read all those files in at once, in one Dataset.
 >>> f = MFDataset("mftest*nc")
->>> print f.variables["x"][:]
-[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
- 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
- 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74
- 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99]
+>>> print(f.variables["x"][:])
+[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
+ 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
+ 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71
+ 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
+ 96 97 98 99]
 
        
   
        
 
        
@@ -5299,8 +5320,10 @@ 
        Static methods
        
 this Dataset or Group, as well as for all
 variables in all its subgroups.
        
 
        True_or_False: Boolean determining if automatic conversion of
-masked arrays with no missing values to regular ararys shall be
-applied for all variables.
        
+masked arrays with no missing values to regular numpy arrays shall be
+applied for all variables. Default True. Set to False to restore the default behaviour
+in versions prior to 1.4.1 (numpy array returned unless missing values are present,
+otherwise masked array returned).
        
 
        Note: Calling this function only affects existing
 variables. Variables created after calling this function will follow
 the default behaviour.
        
@@ -5546,14 +5569,14 @@ 
        Static methods
        
 >>> f1.close()
 >>> f2.close()
 >>> # Read the two files in at once, in one Dataset.
->>> f = MFDataset("mftest*nc")
+>>> f = MFDataset("mftest_*nc")
 >>> t = f.variables["time"]
->>> print t.units
+>>> print(t.units)
 days since 2000-01-01
->>> print t[32] # The value written in the file, inconsistent with the MF time units.
+>>> print(t[32])  # The value written in the file, inconsistent with the MF time units.
 1
 >>> T = MFTime(t)
->>> print T[32]
+>>> print(T[32])
 32
 
        
   
        
@@ -6241,10 +6264,11 @@ 
        Static methods
        
   
     
        turn on or off conversion of data without missing values to regular
 numpy arrays.
        
-
        If always_mask is set to True then a masked array with no missing
-values is converted to a regular numpy array.
        
-
        The default value of always_mask is True (conversions to regular
-numpy arrays are not performed).
        
+
        always_mask is a Boolean determining if automatic conversion of
+masked arrays with no missing values to regular numpy arrays shall be
+applied. Default is True. Set to False to restore the default behaviour
+in versions prior to 1.4.1 (numpy array returned unless missing values are present,
+otherwise masked array returned).
        
   
        
 
        
 
@@ -6338,12 +6362,12 @@ 
        Static methods
        
 
        If maskandscale is set to True, and the variable has a
 scale_factor or an add_offset attribute, then data read
 from that variable is unpacked using::
        
-
        data = self.scale_factor*data + self.add_offset
+
        data = self.scale_factor*data + self.add_offset
 
        
 
 
 
        When data is written to a variable it is packed using::
        
-
        data = (data - self.add_offset)/self.scale_factor
+
        data = (data - self.add_offset)/self.scale_factor
 
        
 
 
@@ -6383,12 +6407,12 @@ 
        Static methods
        
 
        If scale is set to True, and the variable has a
 scale_factor or an add_offset attribute, then data read
 from that variable is unpacked using::
        
-
        data = self.scale_factor*data + self.add_offset
+
        data = self.scale_factor*data + self.add_offset
 
        
 
 
 
        When data is written to a variable it is packed using::
        
-
        data = (data - self.add_offset)/self.scale_factor
+
        data = (data - self.add_offset)/self.scale_factor
 
        
 
 

From 4e5218f1d0dcd7c38245e95898486b72ddbd27c0 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 4 Sep 2019 09:30:08 -0600
Subject: [PATCH 0370/1504] update

---
 Changelog | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Changelog b/Changelog
index e04f489ed..26d7602f5 100644
--- a/Changelog
+++ b/Changelog
@@ -1,4 +1,4 @@
- version 1.5.2 (not yet released)
+ version 1.5.2 (tag v1.5.2rel)
 ==============================
  * fix for scaling bug when _Unsigned attribute is set and byteorder of data
    does not match native byteorder (issue #930).

From 198083884f1691539e94373dcb159b1f337736fe Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 18 Sep 2019 21:25:48 -0600
Subject: [PATCH 0371/1504] fix for issue #972 (masked array not returned when
 auto_fill off)

---
 netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 28b2c605c..107eb6e25 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -4581,7 +4581,7 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
             # type, signed or unsigned, because the byte ranges are too
             # small to assume one of the values should appear as a missing
             # value unless a _FillValue attribute is set explicitly."
-            if no_fill != 1 and self.dtype.str[1:] not in ['u1','i1']:
+            if no_fill != 1 or self.dtype.str[1:] not in ['u1','i1']:
                 fillval = numpy.array(default_fillvals[self.dtype.str[1:]],self.dtype)
                 has_fillval = data == fillval
                 # if data is an array scalar, has_fillval will be a boolean.

From f638f6895703ebc6cb007976c2ec91b12357fa67 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Thu, 19 Sep 2019 06:32:27 -0600
Subject: [PATCH 0372/1504] bump version number

---
 netCDF4/_netCDF4.pyx | 4 ++--
 setup.py             | 2 +-
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 107eb6e25..52a071f57 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1,5 +1,5 @@
 """
-Version 1.5.2
+Version 1.5.3
 ---------------
 - - -
 
@@ -1206,7 +1206,7 @@ except ImportError:
     # python3: zip is already python2's itertools.izip
     pass
 
-__version__ = "1.5.2"
+__version__ = "1.5.3"
 
 # Initialize numpy
 import posixpath
diff --git a/setup.py b/setup.py
index fceba29b4..3173c79d7 100644
--- a/setup.py
+++ b/setup.py
@@ -596,7 +596,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 
 setup(name="netCDF4",
       cmdclass=cmdclass,
-      version="1.5.2",
+      version="1.5.3",
       long_description="netCDF version 4 has many features not found in earlier versions of the library, such as hierarchical groups, zlib compression, multiple unlimited dimensions, and new data types.  It is implemented on top of HDF5.  This module implements most of the new features, and can read and write netCDF files compatible with older versions of the library.  The API is modelled after Scientific.IO.NetCDF, and should be familiar to users of that module.\n\nThis project is hosted on a `GitHub repository `_ where you may access the most up-to-date source.",
       author="Jeff Whitaker",
       author_email="jeffrey.s.whitaker@noaa.gov",

From f25b6228fcd626599656a0f54bb66d27c1010965 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Thu, 19 Sep 2019 06:33:57 -0600
Subject: [PATCH 0373/1504] update Changelog

---
 Changelog | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/Changelog b/Changelog
index 26d7602f5..e37b68fdc 100644
--- a/Changelog
+++ b/Changelog
@@ -1,3 +1,8 @@
+ version 1.5.3 (not yet released)
+==============================
+ * make sure arrays are masked that are not filled when auto_fill is off 
+   (issue #972).
+
  version 1.5.2 (tag v1.5.2rel)
 ==============================
  * fix for scaling bug when _Unsigned attribute is set and byteorder of data

From 21d3f4ce392c84190552344cb22e1cde2219c524 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 20 Sep 2019 07:05:10 -0600
Subject: [PATCH 0374/1504] add test for issue #972

---
 test/tst_masked.py | 22 ++++++++++++++++++++++
 1 file changed, 22 insertions(+)

diff --git a/test/tst_masked.py b/test/tst_masked.py
index d19936221..1503f8ca4 100644
--- a/test/tst_masked.py
+++ b/test/tst_masked.py
@@ -7,12 +7,14 @@
 from numpy.testing import assert_array_equal, assert_array_almost_equal
 from numpy.random.mtrand import uniform
 import netCDF4
+from numpy.ma import masked_all
 
 # test automatic conversion of masked arrays, and
 # packing/unpacking of short ints.
 
 # create an n1dim by n2dim random ranarr.
 FILE_NAME = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
+FILE_NAME2 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
 ndim = 10
 ranarr = 100.*uniform(size=(ndim))
 ranarr2 = 100.*uniform(size=(ndim))
@@ -38,6 +40,7 @@ class PrimitiveTypesTestCase(unittest.TestCase):
 
     def setUp(self):
         self.file = FILE_NAME
+        self.file2 = FILE_NAME2
         file = netCDF4.Dataset(self.file,'w')
         file.createDimension('n', ndim)
         foo = file.createVariable('maskeddata', 'f8', ('n',))
@@ -71,9 +74,21 @@ def setUp(self):
         v = file.createVariable('v',NP.float,'x',fill_value=-9999)
         file.close()
 
+        # issue #972: when auto_fill off byte arrays (u1,i1) should
+        # not be masked, but other datatypes should.
+        dataset = netCDF4.Dataset(self.file2, "w")
+        dataset.set_fill_off()  # comment this out and everything works as expected
+        dim = dataset.createDimension("dim", 10)
+        var1 = dataset.createVariable("var1", "f8", (dim.name,))
+        var1[:] = masked_all((10,), "f8")
+        var2 = dataset.createVariable("var2", "u1", (dim.name,))
+        var2[:] = masked_all((10,), "u1")
+        dataset.close()
+
     def tearDown(self):
         # Remove the temporary files
         os.remove(self.file)
+        os.remove(self.file2)
 
     def runTest(self):
         """testing auto-conversion of masked arrays and packed integers"""
@@ -118,6 +133,13 @@ def runTest(self):
         f['variable'][:] = NP.nan
         data = f['variable'][:] # should not raise an error
         f.close()
+        # issue #972
+        dataset = netCDF4.Dataset(self.file2, "r")
+        var1 = dataset.variables["var1"]
+        var2 = dataset.variables["var2"]
+        assert var1[:].mask.all()
+        assert var2[:].mask.any() == False
+        file.close()
 
 if __name__ == '__main__':
     unittest.main()

From 62b25cfee769a9f1236b0ed48bac787ce469432b Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 20 Sep 2019 07:13:53 -0600
Subject: [PATCH 0375/1504] update

---
 test/tst_masked.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/tst_masked.py b/test/tst_masked.py
index 1503f8ca4..13fc0e20d 100644
--- a/test/tst_masked.py
+++ b/test/tst_masked.py
@@ -77,7 +77,7 @@ def setUp(self):
         # issue #972: when auto_fill off byte arrays (u1,i1) should
         # not be masked, but other datatypes should.
         dataset = netCDF4.Dataset(self.file2, "w")
-        dataset.set_fill_off()  # comment this out and everything works as expected
+        dataset.set_fill_off()
         dim = dataset.createDimension("dim", 10)
         var1 = dataset.createVariable("var1", "f8", (dim.name,))
         var1[:] = masked_all((10,), "f8")

From 058f8e4e8affcbd566553d8aae7ae6baf14e8e04 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 20 Sep 2019 14:32:41 -0600
Subject: [PATCH 0376/1504] use dist: bionic to get netcdf version 4.6.0

---
 .travis.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.travis.yml b/.travis.yml
index 167a22b4b..51bbf0fb1 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -1,5 +1,5 @@
 language: python
-dist: xenial
+dist: bionic
 cache: pip
 
 addons:

From fe848456b3090a70b3a5889b06eb92429750f9bf Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 21 Sep 2019 13:53:56 -0600
Subject: [PATCH 0377/1504] fix test

---
 test/tst_masked.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/tst_masked.py b/test/tst_masked.py
index 13fc0e20d..54c04101d 100644
--- a/test/tst_masked.py
+++ b/test/tst_masked.py
@@ -139,7 +139,7 @@ def runTest(self):
         var2 = dataset.variables["var2"]
         assert var1[:].mask.all()
         assert var2[:].mask.any() == False
-        file.close()
+        dataset.close()
 
 if __name__ == '__main__':
     unittest.main()

From 12f170914254435b9f0e0deecb0fe8b8de82178f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 20 Oct 2019 10:44:32 -0600
Subject: [PATCH 0378/1504] update

---
 Changelog | 3 ++-
 README.md | 4 ++++
 2 files changed, 6 insertions(+), 1 deletion(-)

diff --git a/Changelog b/Changelog
index e37b68fdc..39db70799 100644
--- a/Changelog
+++ b/Changelog
@@ -1,7 +1,8 @@
- version 1.5.3 (not yet released)
+ version 1.5.3 (tag v1.5.3rel)
 ==============================
  * make sure arrays are masked that are not filled when auto_fill is off 
    (issue #972).
+ * python 3.8 binary wheels.
 
  version 1.5.2 (tag v1.5.2rel)
 ==============================
diff --git a/README.md b/README.md
index f4cfaa1c3..f732891ec 100644
--- a/README.md
+++ b/README.md
@@ -10,6 +10,10 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
+10/27/2019: Version [1.5.3](https://pypi.python.org/pypi/netCDF4/1.5.3) released]. Fix for
+[issue #972](https://github.com/Unidata/netcdf4-python/issues/972), plus binary wheels for
+python 3.8.
+
 09/03/2019: Version [1.5.2](https://pypi.python.org/pypi/netCDF4/1.5.2) released. Bugfixes, no new features.
 
 05/06/2019: Version [1.5.1.2](https://pypi.python.org/pypi/netCDF4/1.5.1.2) released. Fixes another slicing

From 9dedd1386a9c91bcc4225b2577937f7b13486ad1 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 20 Oct 2019 10:51:41 -0600
Subject: [PATCH 0379/1504] update

---
 docs/netCDF4/index.html | 1398 ++++++++++++++++++---------------------
 1 file changed, 639 insertions(+), 759 deletions(-)

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     netCDF4 API documentation
-    
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-  
 
   
 
+  
 
   
+    
+    
+
+
+
+    
        
+        
+            
+        
+        
        
+            
+                
        
+                    
+                        
+                    
+                    
        netCDF4
        
+                    
        Version 1.5.6
        
+
+
        Introduction
        
+
+
        netcdf4-python is a Python interface to the netCDF C library.
        
+
+
        netCDF version 4 has many features
+not found in earlier versions of the library and is implemented on top of
+HDF5. This module can read and write
+files in both the new netCDF 4 and the old netCDF 3 format, and can create
+files that are readable by HDF5 clients. The API modelled after
+Scientific.IO.NetCDF,
+and should be familiar to users of that module.
        
+
+
        Most new features of netCDF 4 are implemented, such as multiple
+unlimited dimensions, groups and zlib data compression.  All the new
+numeric data types (such as 64 bit and unsigned integer types) are
+implemented. Compound (struct), variable length (vlen) and
+enumerated (enum) data types are supported, but not the opaque data type.
+Mixtures of compound, vlen and enum data types (such as
+compound types containing enums, or vlens containing compound
+types) are not supported.
        
+
+
        Download
        
+
+
+
+
        Requires
        
+
+
          
+
        • numpy array module, version 1.10.0 or later.
          • 
+
        • Cython, version 0.21 or later.
          • 
+
        • setuptools, version 18.0 or
+later.
          • 
+
        • cftime for
+the time and date handling utility functions (num2date,
+date2num and date2index).
          • 
+
        • The HDF5 C library version 1.8.4-patch1 or higher (1.8.x recommended)
+from .
+netCDF version 4.4.1 or higher is recommended if using HDF5 1.10.x -
+otherwise resulting files may be unreadable by clients using earlier
+versions of HDF5.  For netCDF < 4.4.1, HDF5 version 1.8.x is recommended.
+Be sure to build with --enable-hl --enable-shared.
          • 
+
        • Libcurl, if you want
+OPeNDAP support.
          • 
+
        • HDF4, if you want
+to be able to read HDF4 "Scientific Dataset" (SD) files.
          • 
+
        • The netCDF-4 C library from the github releases
+page.
+Version 4.1.1 or higher is required (4.2 or higher recommended).
+Be sure to build with --enable-netcdf-4 --enable-shared, and set
+CPPFLAGS="-I $HDF5_DIR/include" and LDFLAGS="-L $HDF5_DIR/lib",
+where $HDF5_DIR is the directory where HDF5 was installed.
+If you want OPeNDAP support, add --enable-dap.
+If you want HDF4 SD support, add --enable-hdf4 and add
+the location of the HDF4 headers and library to $CPPFLAGS and $LDFLAGS.
          • 
+
        • for MPI parallel IO support, an MPI-enabled versions of the netcdf library
+is required, as is the mpi4py python module.
+Parallel IO further depends on the existence of MPI-enabled HDF5 or the
+PnetCDF library.
          • 
+
        
+
+
        Install
        
+
+
          
+
        • install the requisite python modules and C libraries (see above). It's
+easiest if all the C libs are built as shared libraries.
          • 
+
        • By default, the utility nc-config, installed with netcdf 4.1.2 or higher,
+will be run used to determine where all the dependencies live.
          • 
+
        • If nc-config is not in your default PATH, you can set the NETCDF4_DIR
+environment variable and setup.py will look in $NETCDF4_DIR/bin.
+You can also use the file setup.cfg to set the path to nc-config, or
+enter the paths to the libraries and include files manually. Just  edit the setup.cfg file
+in a text editor and follow the instructions in the comments.
+To disable the use of nc-config, set the env var USE_NCCONFIG to 0.
+To disable the use of setup.cfg, set USE_SETUPCFG to 0.
+As a last resort, the library and include paths can be set via environment variables.
+If you go this route, set USE_NCCONFIG and USE_SETUPCFG to 0, and specify
+NETCDF4_LIBDIR, NETCDF4_INCDIR, HDF5_LIBDIR and HDF5_INCDIR.
+Similarly, environment variables
+(all capitalized) can be used to set the include and library paths for
+hdf4, szip, jpeg, curl and zlib. If the dependencies are not found
+in any of the paths specified by environment variables, then standard locations
+(such as /usr and /usr/local) are searched.
          • 
+
        • run python setup.py build, then python setup.py install (as root if
+necessary). pip install can be used to install pre-compiled binary wheels from 
+pypi.
          • 
+
        • run the tests in the 'test' directory by running python run_all.py.
          • 
+
        
+
+
        Tutorial
        
+
+
+
+
        Creating/Opening/Closing a netCDF file
        
+
+
        To create a netCDF file from python, you simply call the Dataset
+constructor. This is also the method used to open an existing netCDF
+file.  If the file is open for write access (mode='w', 'r+' or 'a'), you may
+write any type of data including new dimensions, groups, variables and
+attributes.  netCDF files come in five flavors (NETCDF3_CLASSIC,
+NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF4_CLASSIC, and NETCDF4).
+NETCDF3_CLASSIC was the original netcdf binary format, and was limited
+to file sizes less than 2 Gb. NETCDF3_64BIT_OFFSET was introduced
+in version 3.6.0 of the library, and extended the original binary format
+to allow for file sizes greater than 2 Gb.
+NETCDF3_64BIT_DATA is a new format that requires version 4.4.0 of
+the C library - it extends the NETCDF3_64BIT_OFFSET binary format to
+allow for unsigned/64 bit integer data types and 64-bit dimension sizes.
+NETCDF3_64BIT is an alias for NETCDF3_64BIT_OFFSET.
+NETCDF4_CLASSIC files use the version 4 disk format (HDF5), but omits features
+not found in the version 3 API. They can be read by netCDF 3 clients
+only if they have been relinked against the netCDF 4 library. They can
+also be read by HDF5 clients. NETCDF4 files use the version 4 disk
+format (HDF5) and use the new features of the version 4 API.  The
+netCDF4 module can read and write files in any of these formats. When
+creating a new file, the format may be specified using the format
+keyword in the Dataset constructor.  The default format is
+NETCDF4. To see how a given file is formatted, you can examine the
+data_model attribute.  Closing the netCDF file is
+accomplished via the Dataset.close method of the Dataset
+instance.
        
+
+
        Here's an example:
        
+
+
        >>> from netCDF4 import Dataset
+>>> rootgrp = Dataset("test.nc", "w", format="NETCDF4")
+>>> print(rootgrp.data_model)
+NETCDF4
+>>> rootgrp.close()
+
        
+
+
        Remote OPeNDAP-hosted datasets can be accessed for
+reading over http if a URL is provided to the Dataset constructor instead of a
+filename.  However, this requires that the netCDF library be built with
+OPenDAP support, via the --enable-dap configure option (added in
+version 4.0.1).
        
+
+
        Groups in a netCDF file
        
+
+
        netCDF version 4 added support for organizing data in hierarchical
+groups, which are analogous to directories in a filesystem. Groups serve
+as containers for variables, dimensions and attributes, as well as other
+groups.  A Dataset creates a special group, called
+the 'root group', which is similar to the root directory in a unix
+filesystem.  To create Group instances, use the
+Dataset.createGroup method of a Dataset or Group
+instance. Dataset.createGroup takes a single argument, a
+python string containing the name of the new group. The new Group
+instances contained within the root group can be accessed by name using
+the groups dictionary attribute of the Dataset instance.  Only
+NETCDF4 formatted files support Groups, if you try to create a Group
+in a netCDF 3 file you will get an error message.
        
+
+
        >>> rootgrp = Dataset("test.nc", "a")
+>>> fcstgrp = rootgrp.createGroup("forecasts")
+>>> analgrp = rootgrp.createGroup("analyses")
+>>> print(rootgrp.groups)
+{'forecasts': <class 'netCDF4._netCDF4.Group'>
+group /forecasts:
+    dimensions(sizes): 
+    variables(dimensions): 
+    groups: , 'analyses': <class 'netCDF4._netCDF4.Group'>
+group /analyses:
+    dimensions(sizes): 
+    variables(dimensions): 
+    groups: }
+>>>
+
        
+
+
        Groups can exist within groups in a Dataset, just as directories
+exist within directories in a unix filesystem. Each Group instance
+has a groups attribute dictionary containing all of the group
+instances contained within that group. Each Group instance also has a
+path attribute that contains a simulated unix directory path to
+that group.  To simplify the creation of nested groups, you can
+use a unix-like path as an argument to Dataset.createGroup.
        
+
+
        >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
+>>> fcstgrp2 = rootgrp.createGroup("/forecasts/model2")
+
        
+
+
        If any of the intermediate elements of the path do not exist, they are created,
+just as with the unix command 'mkdir -p'. If you try to create a group
+that already exists, no error will be raised, and the existing group will be
+returned.
        
+
+
        Here's an example that shows how to navigate all the groups in a
+Dataset. The function walktree is a Python generator that is used
+to walk the directory tree. Note that printing the Dataset or Group
+object yields summary information about it's contents.
        
+
+
        >>> def walktree(top):
+...     values = top.groups.values()
+...     yield values
+...     for value in top.groups.values():
+...         for children in walktree(value):
+...             yield children
+>>> print(rootgrp)
+<class 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): 
+    variables(dimensions): 
+    groups: forecasts, analyses
+>>> for children in walktree(rootgrp):
+...     for child in children:
+...         print(child)
+<class 'netCDF4._netCDF4.Group'>
+group /forecasts:
+    dimensions(sizes): 
+    variables(dimensions): 
+    groups: model1, model2
+<class 'netCDF4._netCDF4.Group'>
+group /analyses:
+    dimensions(sizes): 
+    variables(dimensions): 
+    groups: 
+<class 'netCDF4._netCDF4.Group'>
+group /forecasts/model1:
+    dimensions(sizes): 
+    variables(dimensions): 
+    groups: 
+<class 'netCDF4._netCDF4.Group'>
+group /forecasts/model2:
+    dimensions(sizes): 
+    variables(dimensions): 
+    groups: 
+
        
+
+
        Dimensions in a netCDF file
        
+
+
        netCDF defines the sizes of all variables in terms of dimensions, so
+before any variables can be created the dimensions they use must be
+created first. A special case, not often used in practice, is that of a
+scalar variable, which has no dimensions. A dimension is created using
+the Dataset.createDimension method of a Dataset
+or Group instance. A Python string is used to set the name of the
+dimension, and an integer value is used to set the size. To create an
+unlimited dimension (a dimension that can be appended to), the size
+value is set to None or 0. In this example, there both the time and
+level dimensions are unlimited.  Having more than one unlimited
+dimension is a new netCDF 4 feature, in netCDF 3 files there may be only
+one, and it must be the first (leftmost) dimension of the variable.
        
+
+
        >>> level = rootgrp.createDimension("level", None)
+>>> time = rootgrp.createDimension("time", None)
+>>> lat = rootgrp.createDimension("lat", 73)
+>>> lon = rootgrp.createDimension("lon", 144)
+
        
+
+
        All of the Dimension instances are stored in a python dictionary.
        
+
+
        >>> print(rootgrp.dimensions)
+{'level': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0, 'time': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0, 'lat': <class 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 73, 'lon': <class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144}
+
        
+
+
        Using the python len function with a Dimension instance returns
+current size of that dimension.
+Dimension.isunlimited method of a Dimension instance
+be used to determine if the dimensions is unlimited, or appendable.
        
+
+
        >>> print(len(lon))
+144
+>>> print(lon.isunlimited())
+False
+>>> print(time.isunlimited())
+True
+
        
+
+
        Printing the Dimension object
+provides useful summary info, including the name and length of the dimension,
+and whether it is unlimited.
        
+
+
        >>> for dimobj in rootgrp.dimensions.values():
+...     print(dimobj)
+<class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0
+<class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0
+<class 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 73
+<class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144
+
        
+
+
        Dimension names can be changed using the
+Datatset.renameDimension method of a Dataset or
+Group instance.
        
+
+
        Variables in a netCDF file
        
+
+
        netCDF variables behave much like python multidimensional array objects
+supplied by the numpy module. However,
+unlike numpy arrays, netCDF4 variables can be appended to along one or
+more 'unlimited' dimensions. To create a netCDF variable, use the
+Dataset.createVariable method of a Dataset or
+Group instance. The Dataset.createVariable method
+has two mandatory arguments, the variable name (a Python string), and
+the variable datatype. The variable's dimensions are given by a tuple
+containing the dimension names (defined previously with
+Dataset.createDimension). To create a scalar
+variable, simply leave out the dimensions keyword. The variable
+primitive datatypes correspond to the dtype attribute of a numpy array.
+You can specify the datatype as a numpy dtype object, or anything that
+can be converted to a numpy dtype object.  Valid datatype specifiers
+include: 'f4' (32-bit floating point), 'f8' (64-bit floating
+point), 'i4' (32-bit signed integer), 'i2' (16-bit signed
+integer), 'i8' (64-bit signed integer), 'i1' (8-bit signed
+integer), 'u1' (8-bit unsigned integer), 'u2' (16-bit unsigned
+integer), 'u4' (32-bit unsigned integer), 'u8' (64-bit unsigned
+integer), or 'S1' (single-character string).  The old Numeric
+single-character typecodes ('f','d','h',
+'s','b','B','c','i','l'), corresponding to
+('f4','f8','i2','i2','i1','i1','S1','i4','i4'),
+will also work. The unsigned integer types and the 64-bit integer type
+can only be used if the file format is NETCDF4.
        
+
+
        The dimensions themselves are usually also defined as variables, called
+coordinate variables. The Dataset.createVariable
+method returns an instance of the Variable class whose methods can be
+used later to access and set variable data and attributes.
        
+
+
        >>> times = rootgrp.createVariable("time","f8",("time",))
+>>> levels = rootgrp.createVariable("level","i4",("level",))
+>>> latitudes = rootgrp.createVariable("lat","f4",("lat",))
+>>> longitudes = rootgrp.createVariable("lon","f4",("lon",))
+>>> # two dimensions unlimited
+>>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
+>>> temp.units = "K"
+
        
+
+
        To get summary info on a Variable instance in an interactive session,
+just print it.
        
+
+
        >>> print(temp)
+<class 'netCDF4._netCDF4.Variable'>
+float32 temp(time, level, lat, lon)
+    units: K
+unlimited dimensions: time, level
+current shape = (0, 0, 73, 144)
+filling on, default _FillValue of 9.969209968386869e+36 used
+
        
+
+
        You can use a path to create a Variable inside a hierarchy of groups.
        
+
+
        >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
+
        
+
+
        If the intermediate groups do not yet exist, they will be created.
        
+
+
        You can also query a Dataset or Group instance directly to obtain Group or
+Variable instances using paths.
        
+
+
        >>> print(rootgrp["/forecasts/model1"])  # a Group instance
+<class 'netCDF4._netCDF4.Group'>
+group /forecasts/model1:
+    dimensions(sizes): 
+    variables(dimensions): float32 temp(time,level,lat,lon)
+    groups: 
+>>> print(rootgrp["/forecasts/model1/temp"])  # a Variable instance
+<class 'netCDF4._netCDF4.Variable'>
+float32 temp(time, level, lat, lon)
+path = /forecasts/model1
+unlimited dimensions: time, level
+current shape = (0, 0, 73, 144)
+filling on, default _FillValue of 9.969209968386869e+36 used
+
        
+
+
        All of the variables in the Dataset or Group are stored in a
+Python dictionary, in the same way as the dimensions:
        
+
+
        >>> print(rootgrp.variables)
+{'time': <class 'netCDF4._netCDF4.Variable'>
+float64 time(time)
+unlimited dimensions: time
+current shape = (0,)
+filling on, default _FillValue of 9.969209968386869e+36 used, 'level': <class 'netCDF4._netCDF4.Variable'>
+int32 level(level)
+unlimited dimensions: level
+current shape = (0,)
+filling on, default _FillValue of -2147483647 used, 'lat': <class 'netCDF4._netCDF4.Variable'>
+float32 lat(lat)
+unlimited dimensions: 
+current shape = (73,)
+filling on, default _FillValue of 9.969209968386869e+36 used, 'lon': <class 'netCDF4._netCDF4.Variable'>
+float32 lon(lon)
+unlimited dimensions: 
+current shape = (144,)
+filling on, default _FillValue of 9.969209968386869e+36 used, 'temp': <class 'netCDF4._netCDF4.Variable'>
+float32 temp(time, level, lat, lon)
+    units: K
+unlimited dimensions: time, level
+current shape = (0, 0, 73, 144)
+filling on, default _FillValue of 9.969209968386869e+36 used}
+
        
+
+
        Variable names can be changed using the
+Dataset.renameVariable method of a Dataset
+instance.
        
+
+
        Attributes in a netCDF file
        
+
+
        There are two types of attributes in a netCDF file, global and variable.
+Global attributes provide information about a group, or the entire
+dataset, as a whole. Variable attributes provide information about
+one of the variables in a group. Global attributes are set by assigning
+values to Dataset or Group instance variables. Variable
+attributes are set by assigning values to Variable instances
+variables. Attributes can be strings, numbers or sequences. Returning to
+our example,
        
+
+
        >>> import time
+>>> rootgrp.description = "bogus example script"
+>>> rootgrp.history = "Created " + time.ctime(time.time())
+>>> rootgrp.source = "netCDF4 python module tutorial"
+>>> latitudes.units = "degrees north"
+>>> longitudes.units = "degrees east"
+>>> levels.units = "hPa"
+>>> temp.units = "K"
+>>> times.units = "hours since 0001-01-01 00:00:00.0"
+>>> times.calendar = "gregorian"
+
        
+
+
        The Dataset.ncattrs method of a Dataset, Group or
+Variable instance can be used to retrieve the names of all the netCDF
+attributes. This method is provided as a convenience, since using the
+built-in dir Python function will return a bunch of private methods
+and attributes that cannot (or should not) be modified by the user.
        
+
+
        >>> for name in rootgrp.ncattrs():
+...     print("Global attr {} = {}".format(name, getattr(rootgrp, name)))
+Global attr description = bogus example script
+Global attr history = Created Mon Jul  8 14:19:41 2019
+Global attr source = netCDF4 python module tutorial
+
        
+
+
        The __dict__ attribute of a Dataset, Group or Variable
+instance provides all the netCDF attribute name/value pairs in a python
+dictionary:
        
+
+
        >>> print(rootgrp.__dict__)
+{'description': 'bogus example script', 'history': 'Created Mon Jul  8 14:19:41 2019', 'source': 'netCDF4 python module tutorial'}
+
        
+
+
        Attributes can be deleted from a netCDF Dataset, Group or
+Variable using the python del statement (i.e. del grp.foo
+removes the attribute foo the the group grp).
        
+
+
        Writing data to and retrieving data from a netCDF variable
        
+
+
        Now that you have a netCDF Variable instance, how do you put data
+into it? You can just treat it like an array and assign data to a slice.
        
+
+
        >>> import numpy
+>>> lats =  numpy.arange(-90,91,2.5)
+>>> lons =  numpy.arange(-180,180,2.5)
+>>> latitudes[:] = lats
+>>> longitudes[:] = lons
+>>> print("latitudes =\n{}".format(latitudes[:]))
+latitudes =
+[-90.  -87.5 -85.  -82.5 -80.  -77.5 -75.  -72.5 -70.  -67.5 -65.  -62.5
+ -60.  -57.5 -55.  -52.5 -50.  -47.5 -45.  -42.5 -40.  -37.5 -35.  -32.5
+ -30.  -27.5 -25.  -22.5 -20.  -17.5 -15.  -12.5 -10.   -7.5  -5.   -2.5
+   0.    2.5   5.    7.5  10.   12.5  15.   17.5  20.   22.5  25.   27.5
+  30.   32.5  35.   37.5  40.   42.5  45.   47.5  50.   52.5  55.   57.5
+  60.   62.5  65.   67.5  70.   72.5  75.   77.5  80.   82.5  85.   87.5
+  90. ]
+
        
+
+
        Unlike NumPy's array objects, netCDF Variable
+objects with unlimited dimensions will grow along those dimensions if you
+assign data outside the currently defined range of indices.
        
+
+
        >>> # append along two unlimited dimensions by assigning to slice.
+>>> nlats = len(rootgrp.dimensions["lat"])
+>>> nlons = len(rootgrp.dimensions["lon"])
+>>> print("temp shape before adding data = {}".format(temp.shape))
+temp shape before adding data = (0, 0, 73, 144)
+>>>
+>>> from numpy.random import uniform
+>>> temp[0:5, 0:10, :, :] = uniform(size=(5, 10, nlats, nlons))
+>>> print("temp shape after adding data = {}".format(temp.shape))
+temp shape after adding data = (5, 10, 73, 144)
+>>>
+>>> # levels have grown, but no values yet assigned.
+>>> print("levels shape after adding pressure data = {}".format(levels.shape))
+levels shape after adding pressure data = (10,)
+
        
+
+
        Note that the size of the levels variable grows when data is appended
+along the level dimension of the variable temp, even though no
+data has yet been assigned to levels.
        
+
+
        >>> # now, assign data to levels dimension variable.
+>>> levels[:] =  [1000.,850.,700.,500.,300.,250.,200.,150.,100.,50.]
+
        
+
+
        However, that there are some differences between NumPy and netCDF
+variable slicing rules. Slices behave as usual, being specified as a
+start:stop:step triplet. Using a scalar integer index i takes the ith
+element and reduces the rank of the output array by one. Boolean array and
+integer sequence indexing behaves differently for netCDF variables
+than for numpy arrays.  Only 1-d boolean arrays and integer sequences are
+allowed, and these indices work independently along each dimension (similar
+to the way vector subscripts work in fortran).  This means that
        
+
+
        >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
+(4, 4)
+
        
+
+
        returns an array of shape (4,4) when slicing a netCDF variable, but for a
+numpy array it returns an array of shape (4,).
+Similarly, a netCDF variable of shape (2,3,4,5) indexed
+with [0, array([True, False, True]), array([False, True, True, True]), :]
+would return a (2, 3, 5) array. In NumPy, this would raise an error since
+it would be equivalent to [0, [0,1], [1,2,3], :]. When slicing with integer
+sequences, the indices need not be sorted and may contain
+duplicates (both of these are new features in version 1.2.1).
+While this behaviour may cause some confusion for those used to NumPy's 'fancy indexing' rules,
+it provides a very powerful way to extract data from multidimensional netCDF
+variables by using logical operations on the dimension arrays to create slices.
        
+
+
        For example,
        
+
+
        >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
+
        
+
+
        will extract time indices 0,2 and 4, pressure levels
+850, 500 and 200 hPa, all Northern Hemisphere latitudes and Eastern
+Hemisphere longitudes, resulting in a numpy array of shape  (3, 3, 36, 71).
        
+
+
        >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
+shape of fancy temp slice = (3, 3, 36, 71)
+
        
+
+
        Special note for scalar variables: To extract data from a scalar variable
+v with no associated dimensions, use numpy.asarray(v) or v[...].
+The result will be a numpy scalar array.
        
+
+
        By default, netcdf4-python returns numpy masked arrays with values equal to the
+missing_value or _FillValue variable attributes masked.  The
+Dataset.set_auto_mask  Dataset and Variable methods
+can be used to disable this feature so that
+numpy arrays are always returned, with the missing values included. Prior to
+version 1.4.0 the default behavior was to only return masked arrays when the
+requested slice contained missing values.  This behavior can be recovered
+using the Dataset.set_always_mask method. If a masked array is
+written to a netCDF variable, the masked elements are filled with the
+value specified by the missing_value attribute.  If the variable has
+no missing_value, the _FillValue is used instead.
        
+
+
        Dealing with time coordinates
        
+
+
        Time coordinate values pose a special challenge to netCDF users.  Most
+metadata standards (such as CF) specify that time should be
+measure relative to a fixed date using a certain calendar, with units
+specified like hours since YY-MM-DD hh:mm:ss.  These units can be
+awkward to deal with, without a utility to convert the values to and
+from calendar dates.  The function called num2date
+and date2num are
+provided with this package to do just that (starting with version 1.4.0, the
+cftime package must be installed
+separately).  Here's an example of how they
+can be used:
        
+
+
        >>> # fill in times.
+>>> from datetime import datetime, timedelta
+>>> from netCDF4 import num2date, date2num
+>>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
+>>> times[:] = date2num(dates,units=times.units,calendar=times.calendar)
+>>> print("time values (in units {}):\n{}".format(times.units, times[:]))
+time values (in units hours since 0001-01-01 00:00:00.0):
+[17533104. 17533116. 17533128. 17533140. 17533152.]
+>>> dates = num2date(times[:],units=times.units,calendar=times.calendar)
+>>> print("dates corresponding to time values:\n{}".format(dates))
+dates corresponding to time values:
+[real_datetime(2001, 3, 1, 0, 0) real_datetime(2001, 3, 1, 12, 0)
+ real_datetime(2001, 3, 2, 0, 0) real_datetime(2001, 3, 2, 12, 0)
+ real_datetime(2001, 3, 3, 0, 0)]
+
        
+
+
        num2date converts numeric values of time in the specified units
+and calendar to datetime objects, and date2num does the reverse.
+All the calendars currently defined in the
+CF metadata convention are supported.
+A function called date2index is also provided which returns the indices
+of a netCDF time variable corresponding to a sequence of datetime instances.
        
+
+
        Reading data from a multi-file netCDF dataset
        
+
+
        If you want to read data from a variable that spans multiple netCDF files,
+you can use the MFDataset class to read the data as if it were
+contained in a single file. Instead of using a single filename to create
+a Dataset instance, create a MFDataset instance with either a list
+of filenames, or a string with a wildcard (which is then converted to
+a sorted list of files using the python glob module).
+Variables in the list of files that share the same unlimited
+dimension are aggregated together, and can be sliced across multiple
+files.  To illustrate this, let's first create a bunch of netCDF files with
+the same variable (with the same unlimited dimension).  The files
+must in be in NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF3_CLASSIC or
+NETCDF4_CLASSIC format (NETCDF4 formatted multi-file
+datasets are not supported).
        
+
+
        >>> for nf in range(10):
+...     with Dataset("mftest%s.nc" % nf, "w", format="NETCDF4_CLASSIC") as f:
+...         _ = f.createDimension("x",None)
+...         x = f.createVariable("x","i",("x",))
+...         x[0:10] = numpy.arange(nf*10,10*(nf+1))
+
        
+
+
        Now read all the files back in at once with MFDataset
        
+
+
        >>> from netCDF4 import MFDataset
+>>> f = MFDataset("mftest*nc")
+>>> print(f.variables["x"][:])
+[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
+ 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
+ 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71
+ 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
+ 96 97 98 99]
+
        
+
+
        Note that MFDataset can only be used to read, not write, multi-file
+datasets.
        
+
+
        Efficient compression of netCDF variables
        
+
+
        Data stored in netCDF 4 Variable objects can be compressed and
+decompressed on the fly. The parameters for the compression are
+determined by the zlib, complevel and shuffle keyword arguments
+to the Dataset.createVariable method. To turn on
+compression, set zlib=True.  The complevel keyword regulates the
+speed and efficiency of the compression (1 being fastest, but lowest
+compression ratio, 9 being slowest but best compression ratio). The
+default value of complevel is 4. Setting shuffle=False will turn
+off the HDF5 shuffle filter, which de-interlaces a block of data before
+compression by reordering the bytes.  The shuffle filter can
+significantly improve compression ratios, and is on by default.  Setting
+fletcher32 keyword argument to
+Dataset.createVariable to True (it's False by
+default) enables the Fletcher32 checksum algorithm for error detection.
+It's also possible to set the HDF5 chunking parameters and endian-ness
+of the binary data stored in the HDF5 file with the chunksizes
+and endian keyword arguments to
+Dataset.createVariable.  These keyword arguments only
+are relevant for NETCDF4 and NETCDF4_CLASSIC files (where the
+underlying file format is HDF5) and are silently ignored if the file
+format is NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
        
+
+
        If your data only has a certain number of digits of precision (say for
+example, it is temperature data that was measured with a precision of
+0.1 degrees), you can dramatically improve zlib compression by
+quantizing (or truncating) the data using the least_significant_digit
+keyword argument to Dataset.createVariable. The least
+significant digit is the power of ten of the smallest decimal place in
+the data that is a reliable value. For example if the data has a
+precision of 0.1, then setting least_significant_digit=1 will cause
+data the data to be quantized using numpy.around(scale*data)/scale, where
+scale = 2**bits, and bits is determined so that a precision of 0.1 is
+retained (in this case bits=4).  Effectively, this makes the compression
+'lossy' instead of 'lossless', that is some precision in the data is
+sacrificed for the sake of disk space.
        
+
+
        In our example, try replacing the line
        
+
+
        ```python
+>>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
+
        
+
+
        with
        
+
+
        >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True)
+
        
+
+
        and then
        
+
+
        >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,least_significant_digit=3)
+
        
+
+
        and see how much smaller the resulting files are.
        
+
+
        Beyond homogeneous arrays of a fixed type - compound data types
        
+
+
        Compound data types map directly to numpy structured (a.k.a 'record')
+arrays.  Structured arrays are akin to C structs, or derived types
+in Fortran. They allow for the construction of table-like structures
+composed of combinations of other data types, including other
+compound types. Compound types might be useful for representing multiple
+parameter values at each point on a grid, or at each time and space
+location for scattered (point) data. You can then access all the
+information for a point by reading one variable, instead of reading
+different parameters from different variables.  Compound data types
+are created from the corresponding numpy data type using the
+Dataset.createCompoundType method of a Dataset or Group instance.
+Since there is no native complex data type in netcdf, compound types are handy
+for storing numpy complex arrays.  Here's an example:
        
+
+
        >>> f = Dataset("complex.nc","w")
+>>> size = 3 # length of 1-d complex array
+>>> # create sample complex data.
+>>> datac = numpy.exp(1j*(1.+numpy.linspace(0, numpy.pi, size)))
+>>> # create complex128 compound data type.
+>>> complex128 = numpy.dtype([("real",numpy.float_64),("imag",numpy.float_64)])
+>>> complex128_t = f.createCompoundType(complex128,"complex128")
+>>> # create a variable with this data type, write some data to it.
+>>> x_dim = f.createDimension("x_dim",None)
+>>> v = f.createVariable("cmplx_var",complex128_t,"x_dim")
+>>> data = numpy.empty(size,complex128) # numpy structured array
+>>> data["real"] = datac.real; data["imag"] = datac.imag
+>>> v[:] = data # write numpy structured array to netcdf compound var
+>>> # close and reopen the file, check the contents.
+>>> f.close(); f = Dataset("complex.nc")
+>>> v = f.variables["cmplx_var"]
+>>> datain = v[:] # read in all the data into a numpy structured array
+>>> # create an empty numpy complex array
+>>> datac2 = numpy.empty(datain.shape,numpy.complex128)
+>>> # .. fill it with contents of structured array.
+>>> datac2.real = datain["real"]; datac2.imag = datain["imag"]
+>>> print('{}: {}'.format(datac.dtype, datac)) # original data
+complex128: [ 0.54030231+0.84147098j -0.84147098+0.54030231j -0.54030231-0.84147098j]
+>>>
+>>> print('{}: {}'.format(datac2.dtype, datac2)) # data from file
+complex128: [ 0.54030231+0.84147098j -0.84147098+0.54030231j -0.54030231-0.84147098j]
+
        
+
+
        Compound types can be nested, but you must create the 'inner'
+ones first. All possible numpy structured arrays cannot be
+represented as Compound variables - an error message will be
+raise if you try to create one that is not supported.
+All of the compound types defined for a Dataset or Group are stored
+in a Python dictionary, just like variables and dimensions. As always, printing
+objects gives useful summary information in an interactive session:
        
+
+
        >>> print(f)
+<class 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): x_dim(3)
+    variables(dimensions): {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True} cmplx_var(x_dim)
+    groups: 
+>>> print(f.variables["cmplx_var"])
+<class 'netCDF4._netCDF4.Variable'>
+compound cmplx_var(x_dim)
+compound data type: {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}
+unlimited dimensions: x_dim
+current shape = (3,)
+>>> print(f.cmptypes)
+{'complex128': <class 'netCDF4._netCDF4.CompoundType'>: name = 'complex128', numpy dtype = {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}}
+>>> print(f.cmptypes["complex128"])
+<class 'netCDF4._netCDF4.CompoundType'>: name = 'complex128', numpy dtype = {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}
+
        
+
+
        Variable-length (vlen) data types
        
+
+
        NetCDF 4 has support for variable-length or "ragged" arrays.  These are arrays
+of variable length sequences having the same type. To create a variable-length
+data type, use the Dataset.createVLType method
+method of a Dataset or Group instance.
        
+
+
        >>> f = Dataset("tst_vlen.nc","w")
+>>> vlen_t = f.createVLType(numpy.int32, "phony_vlen")
+
        
+
+
        The numpy datatype of the variable-length sequences and the name of the
+new datatype must be specified. Any of the primitive datatypes can be
+used (signed and unsigned integers, 32 and 64 bit floats, and characters),
+but compound data types cannot.
+A new variable can then be created using this datatype.
        
+
+
        >>> x = f.createDimension("x",3)
+>>> y = f.createDimension("y",4)
+>>> vlvar = f.createVariable("phony_vlen_var", vlen_t, ("y","x"))
+
        
+
+
        Since there is no native vlen datatype in numpy, vlen arrays are represented
+in python as object arrays (arrays of dtype object). These are arrays whose
+elements are Python object pointers, and can contain any type of python object.
+For this application, they must contain 1-D numpy arrays all of the same type
+but of varying length.
+In this case, they contain 1-D numpy int32 arrays of random length between
+1 and 10.
        
+
+
        >>> import random
+>>> random.seed(54321)
+>>> data = numpy.empty(len(y)*len(x),object)
+>>> for n in range(len(y)*len(x)):
+...     data[n] = numpy.arange(random.randint(1,10),dtype="int32")+1
+>>> data = numpy.reshape(data,(len(y),len(x)))
+>>> vlvar[:] = data
+>>> print("vlen variable =\n{}".format(vlvar[:]))
+vlen variable =
+[[array([1, 2, 3, 4, 5, 6, 7, 8], dtype=int32) array([1, 2], dtype=int32)
+  array([1, 2, 3, 4], dtype=int32)]
+ [array([1, 2, 3], dtype=int32)
+  array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)
+  array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)]
+ [array([1, 2, 3, 4, 5, 6, 7], dtype=int32) array([1, 2, 3], dtype=int32)
+  array([1, 2, 3, 4, 5, 6], dtype=int32)]
+ [array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)
+  array([1, 2, 3, 4, 5], dtype=int32) array([1, 2], dtype=int32)]]
+>>> print(f)
+<class 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): x(3), y(4)
+    variables(dimensions): int32 phony_vlen_var(y,x)
+    groups: 
+>>> print(f.variables["phony_vlen_var"])
+<class 'netCDF4._netCDF4.Variable'>
+vlen phony_vlen_var(y, x)
+vlen data type: int32
+unlimited dimensions: 
+current shape = (4, 3)
+>>> print(f.vltypes["phony_vlen"])
+<class 'netCDF4._netCDF4.VLType'>: name = 'phony_vlen', numpy dtype = int32
+
        
+
+
        Numpy object arrays containing python strings can also be written as vlen
+variables,  For vlen strings, you don't need to create a vlen data type.
+Instead, simply use the python str builtin (or a numpy string datatype
+with fixed length greater than 1) when calling the
+Dataset.createVariable method.
        
+
+
        >>> z = f.createDimension("z",10)
+>>> strvar = f.createVariable("strvar", str, "z")
+
        
+
+
        In this example, an object array is filled with random python strings with
+random lengths between 2 and 12 characters, and the data in the object
+array is assigned to the vlen string variable.
        
+
+
        >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
+>>> data = numpy.empty(10,"O")
+>>> for n in range(10):
+...     stringlen = random.randint(2,12)
+...     data[n] = "".join([random.choice(chars) for i in range(stringlen)])
+>>> strvar[:] = data
+>>> print("variable-length string variable:\n{}".format(strvar[:]))
+variable-length string variable:
+['Lh' '25F8wBbMI' '53rmM' 'vvjnb3t63ao' 'qjRBQk6w' 'aJh' 'QF'
+ 'jtIJbJACaQk4' '3Z5' 'bftIIq']
+>>> print(f)
+<class 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): x(3), y(4), z(10)
+    variables(dimensions): int32 phony_vlen_var(y,x), <class 'str'> strvar(z)
+    groups: 
+>>> print(f.variables["strvar"])
+<class 'netCDF4._netCDF4.Variable'>
+vlen strvar(z)
+vlen data type: <class 'str'>
+unlimited dimensions: 
+current shape = (10,)
+
        
+
+
        It is also possible to set contents of vlen string variables with numpy arrays
+of any string or unicode data type. Note, however, that accessing the contents
+of such variables will always return numpy arrays with dtype object.
        
+
+
        Enum data type
        
+
+
        netCDF4 has an enumerated data type, which is an integer datatype that is
+restricted to certain named values. Since Enums don't map directly to
+a numpy data type, they are read and written as integer arrays.
        
+
+
        Here's an example of using an Enum type to hold cloud type data.
+The base integer data type and a python dictionary describing the allowed
+values and their names are used to define an Enum data type using
+Dataset.createEnumType.
        
+
+
        >>> nc = Dataset('clouds.nc','w')
+>>> # python dict with allowed values and their names.
+>>> enum_dict = {'Altocumulus': 7, 'Missing': 255,
+... 'Stratus': 2, 'Clear': 0,
+... 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5,
+... 'Cumulonimbus': 1, 'Stratocumulus': 3}
+>>> # create the Enum type called 'cloud_t'.
+>>> cloud_type = nc.createEnumType(numpy.uint8,'cloud_t',enum_dict)
+>>> print(cloud_type)
+<class 'netCDF4._netCDF4.EnumType'>: name = 'cloud_t', numpy dtype = uint8, fields/values ={'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, 'Stratocumulus': 3}
+
        
+
+
        A new variable can be created in the usual way using this data type.
+Integer data is written to the variable that represents the named
+cloud types in enum_dict. A ValueError will be raised if an attempt
+is made to write an integer value not associated with one of the
+specified names.
        
+
+
        >>> time = nc.createDimension('time',None)
+>>> # create a 1d variable of type 'cloud_type'.
+>>> # The fill_value is set to the 'Missing' named value.
+>>> cloud_var = nc.createVariable('primary_cloud',cloud_type,'time',
+...                               fill_value=enum_dict['Missing'])
+>>> # write some data to the variable.
+>>> cloud_var[:] = [enum_dict[k] for k in ['Clear', 'Stratus', 'Cumulus',
+...                                        'Missing', 'Cumulonimbus']]
+>>> nc.close()
+>>> # reopen the file, read the data.
+>>> nc = Dataset('clouds.nc')
+>>> cloud_var = nc.variables['primary_cloud']
+>>> print(cloud_var)
+<class 'netCDF4._netCDF4.Variable'>
+enum primary_cloud(time)
+    _FillValue: 255
+enum data type: uint8
+unlimited dimensions: time
+current shape = (5,)
+>>> print(cloud_var.datatype.enum_dict)
+{'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, 'Stratocumulus': 3}
+>>> print(cloud_var[:])
+[0 2 4 -- 1]
+>>> nc.close()
+
        
+
+
        Parallel IO
        
+
+
        If MPI parallel enabled versions of netcdf and hdf5 or pnetcdf are detected,
+and mpi4py is installed, netcdf4-python will
+be built with parallel IO capabilities enabled. Parallel IO of NETCDF4 or 
+NETCDF4_CLASSIC formatted files is only available if the MPI parallel HDF5
+library is available. Parallel IO of classic netcdf-3 file formats is only
+available if the PnetCDF library is
+available. To use parallel IO, your program must be running in an MPI
+environment using mpi4py.
        
+
+
        >>> from mpi4py import MPI
+>>> import numpy as np
+>>> from netCDF4 import Dataset
+>>> rank = MPI.COMM_WORLD.rank  # The process ID (integer 0-3 for 4-process run)
+
        
+
+
        To run an MPI-based parallel program like this, you must use mpiexec to launch several
+parallel instances of Python (for example, using mpiexec -np 4 python mpi_example.py).
+The parallel features of netcdf4-python are mostly transparent -
+when a new dataset is created or an existing dataset is opened,
+use the parallel keyword to enable parallel access.
        
+
+
        >>> nc = Dataset('parallel_test.nc','w',parallel=True)
+
        
+
+
        The optional comm keyword may be used to specify a particular
+MPI communicator (MPI_COMM_WORLD is used by default).  Each process (or rank)
+can now write to the file indepedently.  In this example the process rank is
+written to a different variable index on each task
        
+
+
        >>> d = nc.createDimension('dim',4)
+>>> v = nc.createVariable('var', np.int, 'dim')
+>>> v[rank] = rank
+>>> nc.close()
+
+% ncdump parallel_test.nc
+netcdf parallel_test {
+dimensions:
+    dim = 4 ;
+variables:
+    int64 var(dim) ;
+data:
+
+    var = 0, 1, 2, 3 ;
+}
+
        
+
+
        There are two types of parallel IO, independent (the default) and collective.
+Independent IO means that each process can do IO independently. It should not
+depend on or be affected by other processes. Collective IO is a way of doing
+IO defined in the MPI-IO standard; unlike independent IO, all processes must
+participate in doing IO. To toggle back and forth between
+the two types of IO, use the Variable.set_collective
+Variablemethod. All metadata
+operations (such as creation of groups, types, variables, dimensions, or attributes)
+are collective.  There are a couple of important limitations of parallel IO:
        
+
+
          
+
        • parallel IO for NETCDF4 or NETCDF4_CLASSIC formatted files is only available
+if the netcdf library was compiled with MPI enabled HDF5.
          • 
+
        • parallel IO for all classic netcdf-3 file formats is only available if the
+netcdf library was compiled with PnetCDF.
          • 
+
        • If a variable has an unlimited dimension, appending data must be done in collective mode.
+If the write is done in independent mode, the operation will fail with a
+a generic "HDF Error".
          • 
+
        • You cannot write compressed data in parallel (although
+you can read it).
          • 
+
        • You cannot use variable-length (VLEN) data types.
          • 
+
        
+
+
        Dealing with strings
        
+
+
        The most flexible way to store arrays of strings is with the
+Variable-length (vlen) string data type. However, this requires
+the use of the NETCDF4 data model, and the vlen type does not map very well
+numpy arrays (you have to use numpy arrays of dtype=object, which are arrays of
+arbitrary python objects). numpy does have a fixed-width string array
+data type, but unfortunately the netCDF data model does not.
+Instead fixed-width byte strings are typically stored as arrays of 8-bit
+characters.
+To perform the conversion to and from character arrays to fixed-width numpy string arrays, the
+following convention is followed by the python interface.
+If the _Encoding special attribute is set for a character array
+(dtype S1) variable, the chartostring utility function is used to convert the array of
+characters to an array of strings with one less dimension (the last dimension is
+interpreted as the length of each string) when reading the data. The character
+set (usually ascii) is specified by the _Encoding attribute. If _Encoding
+is 'none' or 'bytes', then the character array is converted to a numpy
+fixed-width byte string array (dtype S#), otherwise a numpy unicode (dtype
+U#) array is created.  When writing the data,
+stringtochar is used to convert the numpy string array to an array of
+characters with one more dimension. For example,
        
+
+
        >>> from netCDF4 import stringtochar
+>>> nc = Dataset('stringtest.nc','w',format='NETCDF4_CLASSIC')
+>>> _ = nc.createDimension('nchars',3)
+>>> _ = nc.createDimension('nstrings',None)
+>>> v = nc.createVariable('strings','S1',('nstrings','nchars'))
+>>> datain = numpy.array(['foo','bar'],dtype='S3')
+>>> v[:] = stringtochar(datain) # manual conversion to char array
+>>> print(v[:]) # data returned as char array
+[[b'f' b'o' b'o']
+ [b'b' b'a' b'r']]
+>>> v._Encoding = 'ascii' # this enables automatic conversion
+>>> v[:] = datain # conversion to char array done internally
+>>> print(v[:])  # data returned in numpy string array
+['foo' 'bar']
+>>> nc.close()
+
        
+
+
        Even if the _Encoding attribute is set, the automatic conversion of char
+arrays to/from string arrays can be disabled with
+Variable.set_auto_chartostring.
        
+
+
        A similar situation is often encountered with numpy structured arrays with subdtypes
+containing fixed-wdith byte strings (dtype=S#). Since there is no native fixed-length string
+netCDF datatype, these numpy structure arrays are mapped onto netCDF compound
+types with character array elements.  In this case the string <-> char array
+conversion is handled automatically (without the need to set the _Encoding
+attribute) using numpy
+views.
+The structured array dtype (including the string elements) can even be used to
+define the compound data type - the string dtype will be converted to
+character array dtype under the hood when creating the netcdf compound type.
+Here's an example:
        
+
+
        >>> nc = Dataset('compoundstring_example.nc','w')
+>>> dtype = numpy.dtype([('observation', 'f4'),
+...                      ('station_name','S10')])
+>>> station_data_t = nc.createCompoundType(dtype,'station_data')
+>>> _ = nc.createDimension('station',None)
+>>> statdat = nc.createVariable('station_obs', station_data_t, ('station',))
+>>> data = numpy.empty(2,dtype)
+>>> data['observation'][:] = (123.,3.14)
+>>> data['station_name'][:] = ('Boulder','New York')
+>>> print(statdat.dtype) # strings actually stored as character arrays
+{'names':['observation','station_name'], 'formats':['<f4',('S1', (10,))], 'offsets':[0,4], 'itemsize':16, 'aligned':True}
+>>> statdat[:] = data # strings converted to character arrays internally
+>>> print(statdat[:])  # character arrays converted back to strings
+[(123.  , b'Boulder') (  3.14, b'New York')]
+>>> print(statdat[:].dtype)
+{'names':['observation','station_name'], 'formats':['<f4','S10'], 'offsets':[0,4], 'itemsize':16, 'aligned':True}
+>>> statdat.set_auto_chartostring(False) # turn off auto-conversion
+>>> statdat[:] = data.view(dtype=[('observation', 'f4'),('station_name','S1',10)])
+>>> print(statdat[:])  # now structured array with char array subtype is returned
+[(123.  , [b'B', b'o', b'u', b'l', b'd', b'e', b'r', b'', b'', b''])
+ (  3.14, [b'N', b'e', b'w', b' ', b'Y', b'o', b'r', b'k', b'', b''])]
+>>> nc.close()
+
        
+
+
        Note that there is currently no support for mapping numpy structured arrays with
+unicode elements (dtype U#) onto netCDF compound types, nor is there support
+for netCDF compound types with vlen string components.
        
+
+
        In-memory (diskless) Datasets
        
+
+
        You can create netCDF Datasets whose content is held in memory
+instead of in a disk file.  There are two ways to do this.  If you
+don't need access to the memory buffer containing the Dataset from
+within python, the best way is to use the diskless=True keyword
+argument when creating the Dataset.  If you want to save the Dataset
+to disk when you close it, also set persist=True.  If you want to
+create a new read-only Dataset from an existing python memory buffer, use the
+memory keyword argument to pass the memory buffer when creating the Dataset.
+If you want to create a new in-memory Dataset, and then access the memory buffer
+directly from Python, use the memory keyword argument to specify the
+estimated size of the Dataset in bytes when creating the Dataset with
+mode='w'.  Then, the Dataset.close method will return a python memoryview
+object representing the Dataset. Below are examples illustrating both
+approaches.
        
+
+
        >>> # create a diskless (in-memory) Dataset,
+>>> # and persist the file to disk when it is closed.
+>>> nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
+>>> d = nc.createDimension('x',None)
+>>> v = nc.createVariable('v',numpy.int32,'x')
+>>> v[0:5] = numpy.arange(5)
+>>> print(nc)
+<class 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): x(5)
+    variables(dimensions): int32 v(x)
+    groups: 
+>>> print(nc['v'][:])
+[0 1 2 3 4]
+>>> nc.close() # file saved to disk
+>>> # create an in-memory dataset from an existing python
+>>> # python memory buffer.
+>>> # read the newly created netcdf file into a python
+>>> # bytes object.
+>>> with open('diskless_example.nc', 'rb') as f:
+...     nc_bytes = f.read()
+>>> # create a netCDF in-memory dataset from the bytes object.
+>>> nc = Dataset('inmemory.nc', memory=nc_bytes)
+>>> print(nc)
+<class 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): x(5)
+    variables(dimensions): int32 v(x)
+    groups: 
+>>> print(nc['v'][:])
+[0 1 2 3 4]
+>>> nc.close()
+>>> # create an in-memory Dataset and retrieve memory buffer
+>>> # estimated size is 1028 bytes - this is actually only
+>>> # used if format is NETCDF3
+>>> # (ignored for NETCDF4/HDF5 files).
+>>> nc = Dataset('inmemory.nc', mode='w',memory=1028)
+>>> d = nc.createDimension('x',None)
+>>> v = nc.createVariable('v',numpy.int32,'x')
+>>> v[0:5] = numpy.arange(5)
+>>> nc_buf = nc.close() # close returns memoryview
+>>> print(type(nc_buf))
+<class 'memoryview'>
+>>> # save nc_buf to disk, read it back in and check.
+>>> with open('inmemory.nc', 'wb') as f:
+...     f.write(nc_buf)
+>>> nc = Dataset('inmemory.nc')
+>>> print(nc)
+<class 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): x(5)
+    variables(dimensions): int32 v(x)
+    groups:
+>>> print(nc['v'][:])
+[0 1 2 3 4]
+>>> nc.close()
+
        
+
+
        All of the code in this tutorial is available in examples/tutorial.py, except
+the parallel IO example, which is in examples/mpi_example.py.
+Unit tests are in the test directory.
        
+
+
        contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
        
+
+
        copyright: 2008 by Jeffrey Whitaker.
        
+
+
        license: Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
        
+
+
        The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
        
+
+
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
        
+
        
+                    
+                
        
+            
+            
+                
+                    
        
+                        
+                            
        class
+            Dataset:
+        
        
+                        
+                        
+                            
+                        
+                        
        A netCDF Dataset is a collection of dimensions, groups, variables and
+attributes. Together they describe the meaning of data and relations among
+data fields stored in a netCDF file. See Dataset.__init__ for more
+details.
        
+
+
        A list of attribute names corresponding to global netCDF attributes
+defined for the Dataset can be obtained with the
+Dataset.ncattrs method.
+These attributes can be created by assigning to an attribute of the
+Dataset instance. A dictionary containing all the netCDF attribute
+name/value pairs is provided by the __dict__ attribute of a
+Dataset instance.
        
+
+
        The following class variables are read-only and should not be
+modified by the user.
        
+
+
        dimensions: The dimensions dictionary maps the names of
+dimensions defined for the Group or Dataset to instances of the
+Dimension class.
        
+
+
        variables: The variables dictionary maps the names of variables
+defined for this Dataset or Group to instances of the
+Variable class.
        
+
+
        groups: The groups dictionary maps the names of groups created for
+this Dataset or Group to instances of the Group class (the
+Dataset class is simply a special case of the Group class which
+describes the root group in the netCDF4 file).
        
+
+
        cmptypes: The cmptypes dictionary maps the names of
+compound types defined for the Group or Dataset to instances of the
+CompoundType class.
        
+
+
        vltypes: The vltypes dictionary maps the names of
+variable-length types defined for the Group or Dataset to instances
+of the VLType class.
        
+
+
        enumtypes: The enumtypes dictionary maps the names of
+Enum types defined for the Group or Dataset to instances
+of the EnumType class.
        
+
+
        data_model: data_model describes the netCDF
+data model version, one of NETCDF3_CLASSIC, NETCDF4,
+NETCDF4_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
        
+
+
        file_format: same as data_model, retained for backwards compatibility.
        
+
+
        disk_format: disk_format describes the underlying
+file format, one of NETCDF3, HDF5, HDF4,
+PNETCDF, DAP2, DAP4 or UNDEFINED. Only available if using
+netcdf C library version >= 4.3.1, otherwise will always return
+UNDEFINED.
        
+
+
        parent: parent is a reference to the parent
+Group instance. None for the root group or Dataset
+instance.
        
+
+
        path: path shows the location of the Group in
+the Dataset in a unix directory format (the names of groups in the
+hierarchy separated by backslashes). A Dataset instance is the root
+group, so the path is simply '/'.
        
+
+
        keepweakref: If True, child Dimension and Variables objects only keep weak
+references to the parent Dataset or Group.
        
+
+
        _ncstring_attrs__: If True, all text attributes will be written as variable-length
+strings.
        
+
        
+                        
+                            
+                                
        
+                                    
+                                        
        
+                Dataset(unknown)
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        __init__(self, filename, mode="r", clobber=True, diskless=False,
+persist=False, keepweakref=False, memory=None, encoding=None,
+parallel=False, comm=None, info=None, format='NETCDF4')
        
+
+
        Dataset constructor.
        
+
+
        filename: Name of netCDF file to hold dataset. Can also
+be a python 3 pathlib instance or the URL of an OpenDAP dataset.  When memory is
+set this is just used to set the filepath().
        
+
+
        mode: access mode. r means read-only; no data can be
+modified. w means write; a new file is created, an existing file with
+the same name is deleted. a and r+ mean append (in analogy with
+serial files); an existing file is opened for reading and writing.
+Appending s to modes r, w, r+ or a will enable unbuffered shared
+access to NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET or
+NETCDF3_64BIT_DATA formatted files.
+Unbuffered access may be useful even if you don't need shared
+access, since it may be faster for programs that don't access data
+sequentially. This option is ignored for NETCDF4 and NETCDF4_CLASSIC
+formatted files.
        
+
+
        clobber: if True (default), opening a file with mode='w'
+will clobber an existing file with the same name.  if False, an
+exception will be raised if a file with the same name already exists.
        
+
+
        format: underlying file format (one of 'NETCDF4',
+'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC', 'NETCDF3_64BIT_OFFSET' or
+'NETCDF3_64BIT_DATA'.
+Only relevant if mode = 'w' (if mode = 'r','a' or 'r+' the file format
+is automatically detected). Default 'NETCDF4', which means the data is
+stored in an HDF5 file, using netCDF 4 API features.  Setting
+format='NETCDF4_CLASSIC' will create an HDF5 file, using only netCDF 3
+compatible API features. netCDF 3 clients must be recompiled and linked
+against the netCDF 4 library to read files in NETCDF4_CLASSIC format.
+'NETCDF3_CLASSIC' is the classic netCDF 3 file format that does not
+handle 2+ Gb files. 'NETCDF3_64BIT_OFFSET' is the 64-bit offset
+version of the netCDF 3 file format, which fully supports 2+ GB files, but
+is only compatible with clients linked against netCDF version 3.6.0 or
+later. 'NETCDF3_64BIT_DATA' is the 64-bit data version of the netCDF 3
+file format, which supports 64-bit dimension sizes plus unsigned and
+64 bit integer data types, but is only compatible with clients linked against
+netCDF version 4.4.0 or later.
        
+
+
        diskless: If True, create diskless (in-core) file.
+This is a feature added to the C library after the
+netcdf-4.2 release. If you need to access the memory buffer directly,
+use the in-memory feature instead (see memory kwarg).
        
+
+
        persist: if diskless=True, persist file to disk when closed
+(default False).
        
+
+
        keepweakref: if True, child Dimension and Variable instances will keep weak
+references to the parent Dataset or Group object.  Default is False, which
+means strong references will be kept.  Having Dimension and Variable instances
+keep a strong reference to the parent Dataset instance, which in turn keeps a
+reference to child Dimension and Variable instances, creates circular references.
+Circular references complicate garbage collection, which may mean increased
+memory usage for programs that create may Dataset instances with lots of
+Variables. It also will result in the Dataset object never being deleted, which
+means it may keep open files alive as well. Setting keepweakref=True allows
+Dataset instances to be garbage collected as soon as they go out of scope, potentially
+reducing memory usage and open file handles.  However, in many cases this is not
+desirable, since the associated Variable instances may still be needed, but are
+rendered unusable when the parent Dataset instance is garbage collected.
        
+
+
        memory: if not None, create or open an in-memory Dataset.
+If mode = 'r', the memory kwarg must contain a memory buffer object
+(an object that supports the python buffer interface).
+The Dataset will then be created with contents taken from this block of memory.
+If mode = 'w', the memory kwarg should contain the anticipated size
+of the Dataset in bytes (used only for NETCDF3 files).  A memory
+buffer containing a copy of the Dataset is returned by the
+Dataset.close method. Requires netcdf-c version 4.4.1 for mode='r,
+netcdf-c 4.6.2 for mode='w'. To persist the file to disk, the raw
+bytes from the returned buffer can be written into a binary file.
+The Dataset can also be re-opened using this memory buffer.
        
+
+
        encoding: encoding used to encode filename string into bytes.
+Default is None (sys.getdefaultfileencoding() is used).
        
+
+
        parallel: open for parallel access using MPI (requires mpi4py and
+parallel-enabled netcdf-c and hdf5 libraries).  Default is False. If
+True, comm and info kwargs may also be specified.
        
+
+
        comm: MPI_Comm object for parallel access. Default None, which
+means MPI_COMM_WORLD will be used.  Ignored if parallel=False.
        
+
+
        info: MPI_Info object for parallel access. Default None, which
+means MPI_INFO_NULL will be used.  Ignored if parallel=False.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                filepath(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        filepath(self,encoding=None)
        
+
+
        Get the file system path (or the opendap URL) which was used to
+open/create the Dataset. Requires netcdf >= 4.1.2.  The path
+is decoded into a string using sys.getfilesystemencoding() by default, this can be
+changed using the encoding kwarg.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                close(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        close(self)
        
+
+
        Close the Dataset.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                isopen(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        close(self)
        
+
+
        is the Dataset open or closed?
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                sync(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        sync(self)
        
+
+
        Writes all buffered data in the Dataset to the disk file.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_fill_on(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_fill_on(self)
        
+
+
        Sets the fill mode for a Dataset open for writing to on.
        
+
+
        This causes data to be pre-filled with fill values. The fill values can be
+controlled by the variable's _Fill_Value attribute, but is usually
+sufficient to the use the netCDF default _Fill_Value (defined
+separately for each variable type). The default behavior of the netCDF
+library corresponds to set_fill_on.  Data which are equal to the
+_Fill_Value indicate that the variable was created, but never written
+to.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_fill_off(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_fill_off(self)
        
+
+
        Sets the fill mode for a Dataset open for writing to off.
        
+
+
        This will prevent the data from being pre-filled with fill values, which
+may result in some performance improvements. However, you must then make
+sure the data is actually written before being read.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                createDimension(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        createDimension(self, dimname, size=None)
        
+
+
        Creates a new dimension with the given dimname and size.
        
+
+
        size must be a positive integer or None, which stands for
+"unlimited" (default is None). Specifying a size of 0 also
+results in an unlimited dimension. The return value is the Dimension
+class instance describing the new dimension.  To determine the current
+maximum size of the dimension, use the len function on the Dimension
+instance. To determine if a dimension is 'unlimited', use the
+Dimension.isunlimited method of the Dimension instance.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                renameDimension(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        renameDimension(self, oldname, newname)
        
+
+
        rename a Dimension named oldname to newname.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                createCompoundType(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        createCompoundType(self, datatype, datatype_name)
        
+
+
        Creates a new compound data type named datatype_name from the numpy
+dtype object datatype.
        
+
+
        Note: If the new compound data type contains other compound data types
+(i.e. it is a 'nested' compound type, where not all of the elements
+are homogeneous numeric data types), then the 'inner' compound types must be
+created first.
        
+
+
        The return value is the CompoundType class instance describing the new
+datatype.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                createVLType(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        createVLType(self, datatype, datatype_name)
        
+
+
        Creates a new VLEN data type named datatype_name from a numpy
+dtype object datatype.
        
+
+
        The return value is the VLType class instance describing the new
+datatype.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                createEnumType(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        createEnumType(self, datatype, datatype_name, enum_dict)
        
+
+
        Creates a new Enum data type named datatype_name from a numpy
+integer dtype object datatype, and a python dictionary
+defining the enum fields and values.
        
+
+
        The return value is the EnumType class instance describing the new
+datatype.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                createVariable(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        createVariable(self, varname, datatype, dimensions=(), zlib=False,
+complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None,
+endian='native', least_significant_digit=None, fill_value=None, chunk_cache=None)
        
+
+
        Creates a new variable with the given varname, datatype, and
+dimensions. If dimensions are not given, the variable is assumed to be
+a scalar.
        
+
+
        If varname is specified as a path, using forward slashes as in unix to
+separate components, then intermediate groups will be created as necessary
+For example, createVariable('/GroupA/GroupB/VarC', float, ('x','y')) will create groups GroupA
+and GroupA/GroupB, plus the variable GroupA/GroupB/VarC, if the preceding
+groups don't already exist.
        
+
+
        The datatype can be a numpy datatype object, or a string that describes
+a numpy dtype object (like the dtype.str attribute of a numpy array).
+Supported specifiers include: 'S1' or 'c' (NC_CHAR), 'i1' or 'b' or 'B'
+(NC_BYTE), 'u1' (NC_UBYTE), 'i2' or 'h' or 's' (NC_SHORT), 'u2'
+(NC_USHORT), 'i4' or 'i' or 'l' (NC_INT), 'u4' (NC_UINT), 'i8' (NC_INT64),
+'u8' (NC_UINT64), 'f4' or 'f' (NC_FLOAT), 'f8' or 'd' (NC_DOUBLE).
+datatype can also be a CompoundType instance
+(for a structured, or compound array), a VLType instance
+(for a variable-length array), or the python str builtin
+(for a variable-length string array). Numpy string and unicode datatypes with
+length greater than one are aliases for str.
        
+
+
        Data from netCDF variables is presented to python as numpy arrays with
+the corresponding data type.
        
+
+
        dimensions must be a tuple containing dimension names (strings) that
+have been defined previously using Dataset.createDimension. The default value
+is an empty tuple, which means the variable is a scalar.
        
+
+
        If the optional keyword zlib is True, the data will be compressed in
+the netCDF file using gzip compression (default False).
        
+
+
        The optional keyword complevel is an integer between 1 and 9 describing
+the level of compression desired (default 4). Ignored if zlib=False.
        
+
+
        If the optional keyword shuffle is True, the HDF5 shuffle filter
+will be applied before compressing the data (default True).  This
+significantly improves compression. Default is True. Ignored if
+zlib=False.
        
+
+
        If the optional keyword fletcher32 is True, the Fletcher32 HDF5
+checksum algorithm is activated to detect errors. Default False.
        
+
+
        If the optional keyword contiguous is True, the variable data is
+stored contiguously on disk.  Default False. Setting to True for
+a variable with an unlimited dimension will trigger an error.
        
+
+
        The optional keyword chunksizes can be used to manually specify the
+HDF5 chunksizes for each dimension of the variable. A detailed
+discussion of HDF chunking and I/O performance is available
+here.
+Basically, you want the chunk size for each dimension to match as
+closely as possible the size of the data block that users will read
+from the file.  chunksizes cannot be set if contiguous=True.
        
+
+
        The optional keyword endian can be used to control whether the
+data is stored in little or big endian format on disk. Possible
+values are little, big or native (default). The library
+will automatically handle endian conversions when the data is read,
+but if the data is always going to be read on a computer with the
+opposite format as the one used to create the file, there may be
+some performance advantage to be gained by setting the endian-ness.
        
+
+
        The zlib, complevel, shuffle, fletcher32, contiguous, chunksizes and endian
+keywords are silently ignored for netCDF 3 files that do not use HDF5.
        
+
+
        The optional keyword fill_value can be used to override the default
+netCDF _FillValue (the value that the variable gets filled with before
+any data is written to it, defaults given in default_fillvals).
+If fill_value is set to False, then the variable is not pre-filled.
        
+
+
        If the optional keyword parameter least_significant_digit is
+specified, variable data will be truncated (quantized). In conjunction
+with zlib=True this produces 'lossy', but significantly more
+efficient compression. For example, if least_significant_digit=1,
+data will be quantized using numpy.around(scale*data)/scale, where
+scale = 2**bits, and bits is determined so that a precision of 0.1 is
+retained (in this case bits=4). From the
+PSD metadata conventions:
+"least_significant_digit -- power of ten of the smallest decimal place
+in unpacked data that is a reliable value." Default is None, or no
+quantization, or 'lossless' compression.
        
+
+
        When creating variables in a NETCDF4 or NETCDF4_CLASSIC formatted file,
+HDF5 creates something called a 'chunk cache' for each variable.  The
+default size of the chunk cache may be large enough to completely fill
+available memory when creating thousands of variables.  The optional
+keyword chunk_cache allows you to reduce (or increase) the size of
+the default chunk cache when creating a variable.  The setting only
+persists as long as the Dataset is open - you can use the set_var_chunk_cache
+method to change it the next time the Dataset is opened.
+Warning - messing with this parameter can seriously degrade performance.
        
+
+
        The return value is the Variable class instance describing the new
+variable.
        
+
+
        A list of names corresponding to netCDF variable attributes can be
+obtained with the Variable method Variable.ncattrs. A dictionary
+containing all the netCDF attribute name/value pairs is provided by
+the __dict__ attribute of a Variable instance.
        
+
+
        Variable instances behave much like array objects. Data can be
+assigned to or retrieved from a variable with indexing and slicing
+operations on the Variable instance. A Variable instance has six
+Dataset standard attributes: dimensions, dtype, shape, ndim, name and
+least_significant_digit. Application programs should never modify
+these attributes. The dimensions attribute is a tuple containing the
+names of the dimensions associated with this variable. The dtype
+attribute is a string describing the variable's data type (i4, f8,
+S1, etc). The shape attribute is a tuple describing the current
+sizes of all the variable's dimensions. The name attribute is a
+string containing the name of the Variable instance.
+The least_significant_digit
+attributes describes the power of ten of the smallest decimal place in
+the data the contains a reliable value.  assigned to the Variable
+instance. If None, the data is not truncated. The ndim attribute
+is the number of variable dimensions.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                renameVariable(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        renameVariable(self, oldname, newname)
        
+
+
        rename a Variable named oldname to newname
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                createGroup(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        createGroup(self, groupname)
        
+
+
        Creates a new Group with the given groupname.
        
+
+
        If groupname is specified as a path, using forward slashes as in unix to
+separate components, then intermediate groups will be created as necessary
+(analogous to mkdir -p in unix).  For example,
+createGroup('/GroupA/GroupB/GroupC') will create GroupA,
+GroupA/GroupB, and GroupA/GroupB/GroupC, if they don't already exist.
+If the specified path describes a group that already exists, no error is
+raised.
        
+
+
        The return value is a Group class instance.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                ncattrs(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        ncattrs(self)
        
+
+
        return netCDF global attribute names for this Dataset or Group in a list.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                setncattr(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        setncattr(self,name,value)
        
+
+
        set a netCDF dataset or group attribute using name,value pair.
+Use if you need to set a netCDF attribute with the
+with the same name as one of the reserved python attributes.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                setncattr_string(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        setncattr_string(self,name,value)
        
+
+
        set a netCDF dataset or group string attribute using name,value pair.
+Use if you need to ensure that a netCDF attribute is created with type
+NC_STRING if the file format is NETCDF4.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                setncatts(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        setncatts(self,attdict)
        
+
+
        set a bunch of netCDF dataset or group attributes at once using a python dictionary.
+This may be faster when setting a lot of attributes for a NETCDF3
+formatted file, since nc_redef/nc_enddef is not called in between setting
+each attribute
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                getncattr(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        getncattr(self,name)
        
+
+
        retrieve a netCDF dataset or group attribute.
+Use if you need to get a netCDF attribute with the same
+name as one of the reserved python attributes.
        
+
+
        option kwarg encoding can be used to specify the
+character encoding of a string attribute (default is utf-8).
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                delncattr(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        delncattr(self,name,value)
        
+
+
        delete a netCDF dataset or group attribute.  Use if you need to delete a
+netCDF attribute with the same name as one of the reserved python
+attributes.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                renameAttribute(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        renameAttribute(self, oldname, newname)
        
+
+
        rename a Dataset or Group attribute named oldname to newname.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                renameGroup(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        renameGroup(self, oldname, newname)
        
+
+
        rename a Group named oldname to newname (requires netcdf >= 4.3.1).
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_auto_chartostring(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_auto_chartostring(self, True_or_False)
        
+
+
        Call Variable.set_auto_chartostring for all variables contained in this Dataset or
+Group, as well as for all variables in all its subgroups.
        
+
+
        True_or_False: Boolean determining if automatic conversion of
+all character arrays <--> string arrays should be performed for
+character variables (variables of type NC_CHAR or S1) with the
+_Encoding attribute set.
        
+
+
        Note: Calling this function only affects existing variables. Variables created
+after calling this function will follow the default behaviour.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_auto_maskandscale(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_auto_maskandscale(self, True_or_False)
        
+
+
        Call Variable.set_auto_maskandscale for all variables contained in this Dataset or
+Group, as well as for all variables in all its subgroups.
        
+
+
        True_or_False: Boolean determining if automatic conversion to masked arrays
+and variable scaling shall be applied for all variables.
        
+
+
        Note: Calling this function only affects existing variables. Variables created
+after calling this function will follow the default behaviour.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_auto_mask(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_auto_mask(self, True_or_False)
        
+
+
        Call Variable.set_auto_mask for all variables contained in this Dataset or
+Group, as well as for all variables in all its subgroups.
        
+
+
        True_or_False: Boolean determining if automatic conversion to masked arrays
+shall be applied for all variables.
        
+
+
        Note: Calling this function only affects existing variables. Variables created
+after calling this function will follow the default behaviour.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_auto_scale(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_auto_scale(self, True_or_False)
        
+
+
        Call Variable.set_auto_scale for all variables contained in this Dataset or
+Group, as well as for all variables in all its subgroups.
        
+
+
        True_or_False: Boolean determining if automatic variable scaling
+shall be applied for all variables.
        
+
+
        Note: Calling this function only affects existing variables. Variables created
+after calling this function will follow the default behaviour.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_always_mask(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_always_mask(self, True_or_False)
        
+
+
        Call Variable.set_always_mask for all variables contained in
+this Dataset or Group, as well as for all
+variables in all its subgroups.
        
+
+
        True_or_False: Boolean determining if automatic conversion of
+masked arrays with no missing values to regular numpy arrays shall be
+applied for all variables. Default True. Set to False to restore the default behaviour
+in versions prior to 1.4.1 (numpy array returned unless missing values are present,
+otherwise masked array returned).
        
+
+
        Note: Calling this function only affects existing
+variables. Variables created after calling this function will follow
+the default behaviour.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_ncstring_attrs(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_ncstring_attrs(self, True_or_False)
        
+
+
        Call Variable.set_ncstring_attrs for all variables contained in
+this Dataset or Group, as well as for all its
+subgroups and their variables.
        
+
+
        True_or_False: Boolean determining if all string attributes are
+created as variable-length NC_STRINGs, (if True), or if ascii text
+attributes are stored as NC_CHARs (if False; default)
        
+
+
        Note: Calling this function only affects newly created attributes
+of existing (sub-) groups and their variables.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                get_variables_by_attributes(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        get_variables_by_attribute(self, **kwargs)
        
+
+
        Returns a list of variables that match specific conditions.
        
+
+
        Can pass in key=value parameters and variables are returned that
+contain all of the matches. For example,
        
+
+
        >>> # Get variables with x-axis attribute.
+>>> vs = nc.get_variables_by_attributes(axis='X')
+>>> # Get variables with matching "standard_name" attribute
+>>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
+
        
+
+
        Can pass in key=callable parameter and variables are returned if the
+callable returns True.  The callable should accept a single parameter,
+the attribute value.  None is given as the attribute value when the
+attribute does not exist on the variable. For example,
        
+
+
        >>> # Get Axis variables
+>>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
+>>> # Get variables that don't have an "axis" attribute
+>>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
+>>> # Get variables that have a "grid_mapping" attribute
+>>> vs = nc.get_variables_by_attributes(grid_mapping=lambda v: v is not None)
+
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        name = <attribute 'name' of 'netCDF4._netCDF4.Dataset' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        groups = <attribute 'groups' of 'netCDF4._netCDF4.Dataset' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Dataset' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        variables = <attribute 'variables' of 'netCDF4._netCDF4.Dataset' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        disk_format = <attribute 'disk_format' of 'netCDF4._netCDF4.Dataset' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        path = <attribute 'path' of 'netCDF4._netCDF4.Dataset' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        parent = <attribute 'parent' of 'netCDF4._netCDF4.Dataset' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        file_format = <attribute 'file_format' of 'netCDF4._netCDF4.Dataset' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        data_model = <attribute 'data_model' of 'netCDF4._netCDF4.Dataset' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        cmptypes = <attribute 'cmptypes' of 'netCDF4._netCDF4.Dataset' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        vltypes = <attribute 'vltypes' of 'netCDF4._netCDF4.Dataset' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        enumtypes = <attribute 'enumtypes' of 'netCDF4._netCDF4.Dataset' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        keepweakref = <attribute 'keepweakref' of 'netCDF4._netCDF4.Dataset' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                            
+                        
+                    
        
+                
+                    
        
+                        
+                            
        class
+            Group(netCDF4._netCDF4.Dataset):
+        
        
+                        
+                        
+                            
+                        
+                        
        Groups define a hierarchical namespace within a netCDF file. They are
+analogous to directories in a unix filesystem. Each Group behaves like
+a Dataset within a Dataset, and can contain it's own variables,
+dimensions and attributes (and other Groups). See Group.__init__
+for more details.
        
+
+
        Group inherits from Dataset, so all the
+Dataset class methods and variables are available
+to a Group instance (except the close method).
        
+
+
        Additional read-only class variables:
        
+
+
        name: String describing the group name.
        
+
        
+                        
+                            
+                                
        
+                                    
+                                        
        
+                Group(unknown)
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        __init__(self, parent, name)
+Group constructor.
        
+
+
        parent: Group instance for the parent group.  If being created
+in the root group, use a Dataset instance.
        
+
+
        name: - Name of the group.
        
+
+
        Note: Group instances should be created using the
+Dataset.createGroup method of a Dataset instance, or
+another Group instance, not using this class directly.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                close(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        close(self)
        
+
+
        overrides Dataset close method which does not apply to Group
+instances, raises IOError.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                filepath(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        filepath(self,encoding=None)
        
+
+
        Get the file system path (or the opendap URL) which was used to
+open/create the Dataset. Requires netcdf >= 4.1.2.  The path
+is decoded into a string using sys.getfilesystemencoding() by default, this can be
+changed using the encoding kwarg.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                isopen(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        close(self)
        
+
+
        is the Dataset open or closed?
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                sync(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        sync(self)
        
+
+
        Writes all buffered data in the Dataset to the disk file.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_fill_on(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_fill_on(self)
        
+
+
        Sets the fill mode for a Dataset open for writing to on.
        
+
+
        This causes data to be pre-filled with fill values. The fill values can be
+controlled by the variable's _Fill_Value attribute, but is usually
+sufficient to the use the netCDF default _Fill_Value (defined
+separately for each variable type). The default behavior of the netCDF
+library corresponds to set_fill_on.  Data which are equal to the
+_Fill_Value indicate that the variable was created, but never written
+to.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_fill_off(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_fill_off(self)
        
+
+
        Sets the fill mode for a Dataset open for writing to off.
        
+
+
        This will prevent the data from being pre-filled with fill values, which
+may result in some performance improvements. However, you must then make
+sure the data is actually written before being read.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                createDimension(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        createDimension(self, dimname, size=None)
        
+
+
        Creates a new dimension with the given dimname and size.
        
+
+
        size must be a positive integer or None, which stands for
+"unlimited" (default is None). Specifying a size of 0 also
+results in an unlimited dimension. The return value is the Dimension
+class instance describing the new dimension.  To determine the current
+maximum size of the dimension, use the len function on the Dimension
+instance. To determine if a dimension is 'unlimited', use the
+Dimension.isunlimited method of the Dimension instance.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                renameDimension(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        renameDimension(self, oldname, newname)
        
+
+
        rename a Dimension named oldname to newname.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                createCompoundType(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        createCompoundType(self, datatype, datatype_name)
        
+
+
        Creates a new compound data type named datatype_name from the numpy
+dtype object datatype.
        
+
+
        Note: If the new compound data type contains other compound data types
+(i.e. it is a 'nested' compound type, where not all of the elements
+are homogeneous numeric data types), then the 'inner' compound types must be
+created first.
        
+
+
        The return value is the CompoundType class instance describing the new
+datatype.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                createVLType(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        createVLType(self, datatype, datatype_name)
        
+
+
        Creates a new VLEN data type named datatype_name from a numpy
+dtype object datatype.
        
+
+
        The return value is the VLType class instance describing the new
+datatype.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                createEnumType(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        createEnumType(self, datatype, datatype_name, enum_dict)
        
+
+
        Creates a new Enum data type named datatype_name from a numpy
+integer dtype object datatype, and a python dictionary
+defining the enum fields and values.
        
+
+
        The return value is the EnumType class instance describing the new
+datatype.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                createVariable(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        createVariable(self, varname, datatype, dimensions=(), zlib=False,
+complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None,
+endian='native', least_significant_digit=None, fill_value=None, chunk_cache=None)
        
+
+
        Creates a new variable with the given varname, datatype, and
+dimensions. If dimensions are not given, the variable is assumed to be
+a scalar.
        
+
+
        If varname is specified as a path, using forward slashes as in unix to
+separate components, then intermediate groups will be created as necessary
+For example, createVariable('/GroupA/GroupB/VarC', float, ('x','y')) will create groups GroupA
+and GroupA/GroupB, plus the variable GroupA/GroupB/VarC, if the preceding
+groups don't already exist.
        
+
+
        The datatype can be a numpy datatype object, or a string that describes
+a numpy dtype object (like the dtype.str attribute of a numpy array).
+Supported specifiers include: 'S1' or 'c' (NC_CHAR), 'i1' or 'b' or 'B'
+(NC_BYTE), 'u1' (NC_UBYTE), 'i2' or 'h' or 's' (NC_SHORT), 'u2'
+(NC_USHORT), 'i4' or 'i' or 'l' (NC_INT), 'u4' (NC_UINT), 'i8' (NC_INT64),
+'u8' (NC_UINT64), 'f4' or 'f' (NC_FLOAT), 'f8' or 'd' (NC_DOUBLE).
+datatype can also be a CompoundType instance
+(for a structured, or compound array), a VLType instance
+(for a variable-length array), or the python str builtin
+(for a variable-length string array). Numpy string and unicode datatypes with
+length greater than one are aliases for str.
        
+
+
        Data from netCDF variables is presented to python as numpy arrays with
+the corresponding data type.
        
+
+
        dimensions must be a tuple containing dimension names (strings) that
+have been defined previously using Dataset.createDimension. The default value
+is an empty tuple, which means the variable is a scalar.
        
+
+
        If the optional keyword zlib is True, the data will be compressed in
+the netCDF file using gzip compression (default False).
        
+
+
        The optional keyword complevel is an integer between 1 and 9 describing
+the level of compression desired (default 4). Ignored if zlib=False.
        
+
+
        If the optional keyword shuffle is True, the HDF5 shuffle filter
+will be applied before compressing the data (default True).  This
+significantly improves compression. Default is True. Ignored if
+zlib=False.
        
+
+
        If the optional keyword fletcher32 is True, the Fletcher32 HDF5
+checksum algorithm is activated to detect errors. Default False.
        
+
+
        If the optional keyword contiguous is True, the variable data is
+stored contiguously on disk.  Default False. Setting to True for
+a variable with an unlimited dimension will trigger an error.
        
+
+
        The optional keyword chunksizes can be used to manually specify the
+HDF5 chunksizes for each dimension of the variable. A detailed
+discussion of HDF chunking and I/O performance is available
+here.
+Basically, you want the chunk size for each dimension to match as
+closely as possible the size of the data block that users will read
+from the file.  chunksizes cannot be set if contiguous=True.
        
+
+
        The optional keyword endian can be used to control whether the
+data is stored in little or big endian format on disk. Possible
+values are little, big or native (default). The library
+will automatically handle endian conversions when the data is read,
+but if the data is always going to be read on a computer with the
+opposite format as the one used to create the file, there may be
+some performance advantage to be gained by setting the endian-ness.
        
+
+
        The zlib, complevel, shuffle, fletcher32, contiguous, chunksizes and endian
+keywords are silently ignored for netCDF 3 files that do not use HDF5.
        
+
+
        The optional keyword fill_value can be used to override the default
+netCDF _FillValue (the value that the variable gets filled with before
+any data is written to it, defaults given in default_fillvals).
+If fill_value is set to False, then the variable is not pre-filled.
        
+
+
        If the optional keyword parameter least_significant_digit is
+specified, variable data will be truncated (quantized). In conjunction
+with zlib=True this produces 'lossy', but significantly more
+efficient compression. For example, if least_significant_digit=1,
+data will be quantized using numpy.around(scale*data)/scale, where
+scale = 2**bits, and bits is determined so that a precision of 0.1 is
+retained (in this case bits=4). From the
+PSD metadata conventions:
+"least_significant_digit -- power of ten of the smallest decimal place
+in unpacked data that is a reliable value." Default is None, or no
+quantization, or 'lossless' compression.
        
+
+
        When creating variables in a NETCDF4 or NETCDF4_CLASSIC formatted file,
+HDF5 creates something called a 'chunk cache' for each variable.  The
+default size of the chunk cache may be large enough to completely fill
+available memory when creating thousands of variables.  The optional
+keyword chunk_cache allows you to reduce (or increase) the size of
+the default chunk cache when creating a variable.  The setting only
+persists as long as the Dataset is open - you can use the set_var_chunk_cache
+method to change it the next time the Dataset is opened.
+Warning - messing with this parameter can seriously degrade performance.
        
+
+
        The return value is the Variable class instance describing the new
+variable.
        
+
+
        A list of names corresponding to netCDF variable attributes can be
+obtained with the Variable method Variable.ncattrs. A dictionary
+containing all the netCDF attribute name/value pairs is provided by
+the __dict__ attribute of a Variable instance.
        
+
+
        Variable instances behave much like array objects. Data can be
+assigned to or retrieved from a variable with indexing and slicing
+operations on the Variable instance. A Variable instance has six
+Dataset standard attributes: dimensions, dtype, shape, ndim, name and
+least_significant_digit. Application programs should never modify
+these attributes. The dimensions attribute is a tuple containing the
+names of the dimensions associated with this variable. The dtype
+attribute is a string describing the variable's data type (i4, f8,
+S1, etc). The shape attribute is a tuple describing the current
+sizes of all the variable's dimensions. The name attribute is a
+string containing the name of the Variable instance.
+The least_significant_digit
+attributes describes the power of ten of the smallest decimal place in
+the data the contains a reliable value.  assigned to the Variable
+instance. If None, the data is not truncated. The ndim attribute
+is the number of variable dimensions.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                renameVariable(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        renameVariable(self, oldname, newname)
        
+
+
        rename a Variable named oldname to newname
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                createGroup(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        createGroup(self, groupname)
        
+
+
        Creates a new Group with the given groupname.
        
+
+
        If groupname is specified as a path, using forward slashes as in unix to
+separate components, then intermediate groups will be created as necessary
+(analogous to mkdir -p in unix).  For example,
+createGroup('/GroupA/GroupB/GroupC') will create GroupA,
+GroupA/GroupB, and GroupA/GroupB/GroupC, if they don't already exist.
+If the specified path describes a group that already exists, no error is
+raised.
        
+
+
        The return value is a Group class instance.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                ncattrs(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        ncattrs(self)
        
+
+
        return netCDF global attribute names for this Dataset or Group in a list.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                setncattr(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        setncattr(self,name,value)
        
+
+
        set a netCDF dataset or group attribute using name,value pair.
+Use if you need to set a netCDF attribute with the
+with the same name as one of the reserved python attributes.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                setncattr_string(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        setncattr_string(self,name,value)
        
+
+
        set a netCDF dataset or group string attribute using name,value pair.
+Use if you need to ensure that a netCDF attribute is created with type
+NC_STRING if the file format is NETCDF4.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                setncatts(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        setncatts(self,attdict)
        
+
+
        set a bunch of netCDF dataset or group attributes at once using a python dictionary.
+This may be faster when setting a lot of attributes for a NETCDF3
+formatted file, since nc_redef/nc_enddef is not called in between setting
+each attribute
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                getncattr(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        getncattr(self,name)
        
+
+
        retrieve a netCDF dataset or group attribute.
+Use if you need to get a netCDF attribute with the same
+name as one of the reserved python attributes.
        
+
+
        option kwarg encoding can be used to specify the
+character encoding of a string attribute (default is utf-8).
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                delncattr(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        delncattr(self,name,value)
        
+
+
        delete a netCDF dataset or group attribute.  Use if you need to delete a
+netCDF attribute with the same name as one of the reserved python
+attributes.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                renameAttribute(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        renameAttribute(self, oldname, newname)
        
+
+
        rename a Dataset or Group attribute named oldname to newname.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                renameGroup(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        renameGroup(self, oldname, newname)
        
+
+
        rename a Group named oldname to newname (requires netcdf >= 4.3.1).
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_auto_chartostring(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_auto_chartostring(self, True_or_False)
        
+
+
        Call Variable.set_auto_chartostring for all variables contained in this Dataset or
+Group, as well as for all variables in all its subgroups.
        
+
+
        True_or_False: Boolean determining if automatic conversion of
+all character arrays <--> string arrays should be performed for
+character variables (variables of type NC_CHAR or S1) with the
+_Encoding attribute set.
        
+
+
        Note: Calling this function only affects existing variables. Variables created
+after calling this function will follow the default behaviour.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_auto_maskandscale(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_auto_maskandscale(self, True_or_False)
        
+
+
        Call Variable.set_auto_maskandscale for all variables contained in this Dataset or
+Group, as well as for all variables in all its subgroups.
        
+
+
        True_or_False: Boolean determining if automatic conversion to masked arrays
+and variable scaling shall be applied for all variables.
        
+
+
        Note: Calling this function only affects existing variables. Variables created
+after calling this function will follow the default behaviour.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_auto_mask(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_auto_mask(self, True_or_False)
        
+
+
        Call Variable.set_auto_mask for all variables contained in this Dataset or
+Group, as well as for all variables in all its subgroups.
        
+
+
        True_or_False: Boolean determining if automatic conversion to masked arrays
+shall be applied for all variables.
        
+
+
        Note: Calling this function only affects existing variables. Variables created
+after calling this function will follow the default behaviour.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_auto_scale(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_auto_scale(self, True_or_False)
        
+
+
        Call Variable.set_auto_scale for all variables contained in this Dataset or
+Group, as well as for all variables in all its subgroups.
        
+
+
        True_or_False: Boolean determining if automatic variable scaling
+shall be applied for all variables.
        
+
+
        Note: Calling this function only affects existing variables. Variables created
+after calling this function will follow the default behaviour.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_always_mask(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_always_mask(self, True_or_False)
        
+
+
        Call Variable.set_always_mask for all variables contained in
+this Dataset or Group, as well as for all
+variables in all its subgroups.
        
+
+
        True_or_False: Boolean determining if automatic conversion of
+masked arrays with no missing values to regular numpy arrays shall be
+applied for all variables. Default True. Set to False to restore the default behaviour
+in versions prior to 1.4.1 (numpy array returned unless missing values are present,
+otherwise masked array returned).
        
+
+
        Note: Calling this function only affects existing
+variables. Variables created after calling this function will follow
+the default behaviour.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_ncstring_attrs(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_ncstring_attrs(self, True_or_False)
        
+
+
        Call Variable.set_ncstring_attrs for all variables contained in
+this Dataset or Group, as well as for all its
+subgroups and their variables.
        
+
+
        True_or_False: Boolean determining if all string attributes are
+created as variable-length NC_STRINGs, (if True), or if ascii text
+attributes are stored as NC_CHARs (if False; default)
        
+
+
        Note: Calling this function only affects newly created attributes
+of existing (sub-) groups and their variables.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                get_variables_by_attributes(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        get_variables_by_attribute(self, **kwargs)
        
+
+
        Returns a list of variables that match specific conditions.
        
+
+
        Can pass in key=value parameters and variables are returned that
+contain all of the matches. For example,
        
+
+
        >>> # Get variables with x-axis attribute.
+>>> vs = nc.get_variables_by_attributes(axis='X')
+>>> # Get variables with matching "standard_name" attribute
+>>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
+
        
+
+
        Can pass in key=callable parameter and variables are returned if the
+callable returns True.  The callable should accept a single parameter,
+the attribute value.  None is given as the attribute value when the
+attribute does not exist on the variable. For example,
        
+
+
        >>> # Get Axis variables
+>>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
+>>> # Get variables that don't have an "axis" attribute
+>>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
+>>> # Get variables that have a "grid_mapping" attribute
+>>> vs = nc.get_variables_by_attributes(grid_mapping=lambda v: v is not None)
+
        
+
        
+                                
        
+                            
+                            
+                                
+                                    
        
+                                        
        Inherited Members
        
+                                        
        
+                                            
+                                                
+                                            
+                                        
        
+                                    
        
+                                
+                            
+                        
+                    
        
+                
+                    
        
+                        
+                            
        class
+            Dimension:
+        
        
+                        
+                        
+                            
+                        
+                        
        A netCDF Dimension is used to describe the coordinates of a Variable.
+See Dimension.__init__ for more details.
        
+
+
        The current maximum size of a Dimension instance can be obtained by
+calling the python len function on the Dimension instance. The
+Dimension.isunlimited method of a Dimension instance can be used to
+determine if the dimension is unlimited.
        
+
+
        Read-only class variables:
        
+
+
        name: String name, used when creating a Variable with
+Dataset.createVariable.
        
+
+
        size: Current Dimension size (same as len(d), where d is a
+Dimension instance).
        
+
        
+                        
+                            
+                                
        
+                                    
+                                        
        
+                Dimension(unknown)
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        __init__(self, group, name, size=None)
        
+
+
        Dimension constructor.
        
+
+
        group: Group instance to associate with dimension.
        
+
+
        name: Name of the dimension.
        
+
+
        size: Size of the dimension. None or 0 means unlimited. (Default None).
        
+
+
        Note: Dimension instances should be created using the
+Dataset.createDimension method of a Group or
+Dataset instance, not using Dimension.__init__ directly.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                group(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        group(self)
        
+
+
        return the group that this Dimension is a member of.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                isunlimited(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        isunlimited(self)
        
+
+
        returns True if the Dimension instance is unlimited, False otherwise.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        name = <attribute 'name' of 'netCDF4._netCDF4.Dimension' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        size = <attribute 'size' of 'netCDF4._netCDF4.Dimension' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                            
+                        
+                    
        
+                
+                    
        
+                        
+                            
        class
+            Variable:
+        
        
+                        
+                        
+                            
+                        
+                        
        A netCDF Variable is used to read and write netCDF data.  They are
+analogous to numpy array objects. See Variable.__init__ for more
+details.
        
+
+
        A list of attribute names corresponding to netCDF attributes defined for
+the variable can be obtained with the Variable.ncattrs method. These
+attributes can be created by assigning to an attribute of the
+Variable instance. A dictionary containing all the netCDF attribute
+name/value pairs is provided by the __dict__ attribute of a
+Variable instance.
        
+
+
        The following class variables are read-only:
        
+
+
        dimensions: A tuple containing the names of the
+dimensions associated with this variable.
        
+
+
        dtype: A numpy dtype object describing the
+variable's data type.
        
+
+
        ndim: The number of variable dimensions.
        
+
+
        shape: A tuple with the current shape (length of all dimensions).
        
+
+
        scale: If True, scale_factor and add_offset are
+applied, and signed integer data is automatically converted to
+unsigned integer data if the _Unsigned attribute is set.
+Default is True, can be reset using Variable.set_auto_scale and
+Variable.set_auto_maskandscale methods.
        
+
+
        mask: If True, data is automatically converted to/from masked
+arrays when missing values or fill values are present. Default is True, can be
+reset using Variable.set_auto_mask and Variable.set_auto_maskandscale
+methods.
        
+
+
        chartostring: If True, data is automatically converted to/from character
+arrays to string arrays when the _Encoding variable attribute is set.
+Default is True, can be reset using
+Variable.set_auto_chartostring method.
        
+
+
        least_significant_digit: Describes the power of ten of the
+smallest decimal place in the data the contains a reliable value.  Data is
+truncated to this decimal place when it is assigned to the Variable
+instance. If None, the data is not truncated.
        
+
+
        __orthogonal_indexing__: Always True.  Indicates to client code
+that the object supports 'orthogonal indexing', which means that slices
+that are 1d arrays or lists slice along each dimension independently.  This
+behavior is similar to Fortran or Matlab, but different than numpy.
        
+
+
        datatype: numpy data type (for primitive data types) or VLType/CompoundType
+ instance (for compound or vlen data types).
        
+
+
        name: String name.
        
+
+
        size: The number of stored elements.
        
+
        
+                        
+                            
+                                
        
+                                    
+                                        
        
+                Variable(unknown)
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        __init__(self, group, name, datatype, dimensions=(), zlib=False,
+complevel=4, shuffle=True, fletcher32=False, contiguous=False,
+chunksizes=None, endian='native',
+least_significant_digit=None,fill_value=None,chunk_cache=None)
        
+
+
        Variable constructor.
        
+
+
        group: Group or Dataset instance to associate with variable.
        
+
+
        name: Name of the variable.
        
+
+
        datatype: Variable data type. Can be specified by providing a
+numpy dtype object, or a string that describes a numpy dtype object.
+Supported values, corresponding to str attribute of numpy dtype
+objects, include 'f4' (32-bit floating point), 'f8' (64-bit floating
+point), 'i4' (32-bit signed integer), 'i2' (16-bit signed integer),
+'i8' (64-bit signed integer), 'i4' (8-bit signed integer), 'i1'
+(8-bit signed integer), 'u1' (8-bit unsigned integer), 'u2' (16-bit
+unsigned integer), 'u4' (32-bit unsigned integer), 'u8' (64-bit
+unsigned integer), or 'S1' (single-character string).  From
+compatibility with Scientific.IO.NetCDF, the old Numeric single character
+typecodes can also be used ('f' instead of 'f4', 'd' instead of
+'f8', 'h' or 's' instead of 'i2', 'b' or 'B' instead of
+'i1', 'c' instead of 'S1', and 'i' or 'l' instead of
+'i4'). datatype can also be a CompoundType instance
+(for a structured, or compound array), a VLType instance
+(for a variable-length array), or the python str builtin
+(for a variable-length string array). Numpy string and unicode datatypes with
+length greater than one are aliases for str.
        
+
+
        dimensions: a tuple containing the variable's dimension names
+(defined previously with createDimension). Default is an empty tuple
+which means the variable is a scalar (and therefore has no dimensions).
        
+
+
        zlib: if True, data assigned to the Variable
+instance is compressed on disk. Default False.
        
+
+
        complevel: the level of zlib compression to use (1 is the fastest,
+but poorest compression, 9 is the slowest but best compression). Default 4.
+Ignored if zlib=False.
        
+
+
        shuffle: if True, the HDF5 shuffle filter is applied
+to improve compression. Default True. Ignored if zlib=False.
        
+
+
        fletcher32: if True (default False), the Fletcher32 checksum
+algorithm is used for error detection.
        
+
+
        contiguous: if True (default False), the variable data is
+stored contiguously on disk.  Default False. Setting to True for
+a variable with an unlimited dimension will trigger an error.
        
+
+
        chunksizes: Can be used to specify the HDF5 chunksizes for each
+dimension of the variable. A detailed discussion of HDF chunking and I/O
+performance is available
+here.
+Basically, you want the chunk size for each dimension to match as
+closely as possible the size of the data block that users will read
+from the file. chunksizes cannot be set if contiguous=True.
        
+
+
        endian: Can be used to control whether the
+data is stored in little or big endian format on disk. Possible
+values are little, big or native (default). The library
+will automatically handle endian conversions when the data is read,
+but if the data is always going to be read on a computer with the
+opposite format as the one used to create the file, there may be
+some performance advantage to be gained by setting the endian-ness.
+For netCDF 3 files (that don't use HDF5), only endian='native' is allowed.
        
+
+
        The zlib, complevel, shuffle, fletcher32, contiguous and chunksizes
+keywords are silently ignored for netCDF 3 files that do not use HDF5.
        
+
+
        least_significant_digit: If specified, variable data will be
+truncated (quantized). In conjunction with zlib=True this produces
+'lossy', but significantly more efficient compression. For example, if
+least_significant_digit=1, data will be quantized using
+around(scaledata)/scale, where scale = 2*bits, and bits is determined
+so that a precision of 0.1 is retained (in this case bits=4). Default is
+None, or no quantization.
        
+
+
        fill_value:  If specified, the default netCDF _FillValue (the
+value that the variable gets filled with before any data is written to it)
+is replaced with this value.  If fill_value is set to False, then
+the variable is not pre-filled. The default netCDF fill values can be found
+in default_fillvals.
        
+
+
        chunk_cache: If specified, sets the chunk cache size for this variable.
+Persists as long as Dataset is open. Use set_var_chunk_cache to 
+change it when Dataset is re-opened. 
        
+
+
        Note: Variable instances should be created using the
+Dataset.createVariable method of a Dataset or
+Group instance, not using this class directly.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                group(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        group(self)
        
+
+
        return the group that this Variable is a member of.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                ncattrs(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        ncattrs(self)
        
+
+
        return netCDF attribute names for this Variable in a list.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                setncattr(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        setncattr(self,name,value)
        
+
+
        set a netCDF variable attribute using name,value pair.  Use if you need to set a
+netCDF attribute with the same name as one of the reserved python
+attributes.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                setncattr_string(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        setncattr_string(self,name,value)
        
+
+
        set a netCDF variable string attribute using name,value pair.
+Use if you need to ensure that a netCDF attribute is created with type
+NC_STRING if the file format is NETCDF4.
+Use if you need to set an attribute to an array of variable-length strings.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                setncatts(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        setncatts(self,attdict)
        
+
+
        set a bunch of netCDF variable attributes at once using a python dictionary.
+This may be faster when setting a lot of attributes for a NETCDF3
+formatted file, since nc_redef/nc_enddef is not called in between setting
+each attribute
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                getncattr(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        getncattr(self,name)
        
+
+
        retrieve a netCDF variable attribute.  Use if you need to set a
+netCDF attribute with the same name as one of the reserved python
+attributes.
        
+
+
        option kwarg encoding can be used to specify the
+character encoding of a string attribute (default is utf-8).
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                delncattr(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        delncattr(self,name,value)
        
+
+
        delete a netCDF variable attribute.  Use if you need to delete a
+netCDF attribute with the same name as one of the reserved python
+attributes.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                filters(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        filters(self)
        
+
+
        return dictionary containing HDF5 filter parameters.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                endian(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        endian(self)
        
+
+
        return endian-ness (little,big,native) of variable (as stored in HDF5 file).
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                chunking(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        chunking(self)
        
+
+
        return variable chunking information.  If the dataset is
+defined to be contiguous (and hence there is no chunking) the word 'contiguous'
+is returned.  Otherwise, a sequence with the chunksize for
+each dimension is returned.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                get_var_chunk_cache(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        get_var_chunk_cache(self)
        
+
+
        return variable chunk cache information in a tuple (size,nelems,preemption).
+See netcdf C library documentation for nc_get_var_chunk_cache for
+details.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_var_chunk_cache(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_var_chunk_cache(self,size=None,nelems=None,preemption=None)
        
+
+
        change variable chunk cache settings.
+See netcdf C library documentation for nc_set_var_chunk_cache for
+details.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                renameAttribute(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        renameAttribute(self, oldname, newname)
        
+
+
        rename a Variable attribute named oldname to newname.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                assignValue(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        assignValue(self, val)
        
+
+
        assign a value to a scalar variable.  Provided for compatibility with
+Scientific.IO.NetCDF, can also be done by assigning to an Ellipsis slice ([...]).
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                getValue(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        getValue(self)
        
+
+
        get the value of a scalar variable.  Provided for compatibility with
+Scientific.IO.NetCDF, can also be done by slicing with an Ellipsis ([...]).
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_auto_chartostring(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_auto_chartostring(self,chartostring)
        
+
+
        turn on or off automatic conversion of character variable data to and
+from numpy fixed length string arrays when the _Encoding variable attribute
+is set.
        
+
+
        If chartostring is set to True, when data is read from a character variable
+(dtype = S1) that has an _Encoding attribute, it is converted to a numpy
+fixed length unicode string array (dtype = UN, where N is the length
+of the the rightmost dimension of the variable).  The value of _Encoding
+is the unicode encoding that is used to decode the bytes into strings.
        
+
+
        When numpy string data is written to a variable it is converted back to
+indiviual bytes, with the number of bytes in each string equalling the
+rightmost dimension of the variable.
        
+
+
        The default value of chartostring is True
+(automatic conversions are performed).
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                use_nc_get_vars(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        use_nc_get_vars(self,_use_get_vars)
        
+
+
        enable the use of netcdf library routine nc_get_vars
+to retrieve strided variable slices.  By default,
+nc_get_vars may not used by default (depending on the
+version of the netcdf-c library being used) since it may be
+slower than multiple calls to the unstrided read routine nc_get_vara.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_auto_maskandscale(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_auto_maskandscale(self,maskandscale)
        
+
+
        turn on or off automatic conversion of variable data to and
+from masked arrays, automatic packing/unpacking of variable
+data using scale_factor and add_offset attributes and
+automatic conversion of signed integer data to unsigned integer
+data if the _Unsigned attribute exists.
        
+
+
        If maskandscale is set to True, when data is read from a variable
+it is converted to a masked array if any of the values are exactly
+equal to the either the netCDF _FillValue or the value specified by the
+missing_value variable attribute. The fill_value of the masked array
+is set to the missing_value attribute (if it exists), otherwise
+the netCDF _FillValue attribute (which has a default value
+for each data type).  When data is written to a variable, the masked
+array is converted back to a regular numpy array by replacing all the
+masked values by the missing_value attribute of the variable (if it
+exists).  If the variable has no missing_value attribute, the _FillValue
+is used instead. If the variable has valid_min/valid_max and
+missing_value attributes, data outside the specified range will be
+set to missing_value.
        
+
+
        If maskandscale is set to True, and the variable has a
+scale_factor or an add_offset attribute, then data read
+from that variable is unpacked using::
        
+
+
        data = self.scale_factor*data + self.add_offset
+
        
+
+
        When data is written to a variable it is packed using::
        
+
+
        data = (data - self.add_offset)/self.scale_factor
+
        
+
+
        If either scale_factor is present, but add_offset is missing, add_offset
+is assumed zero.  If add_offset is present, but scale_factor is missing,
+scale_factor is assumed to be one.
+For more information on how scale_factor and add_offset can be
+used to provide simple compression, see the
+PSD metadata conventions.
        
+
+
        In addition, if maskandscale is set to True, and if the variable has an
+attribute _Unsigned set, and the variable has a signed integer data type,
+a view to the data is returned with the corresponding unsigned integer data type.
+This convention is used by the netcdf-java library to save unsigned integer
+data in NETCDF3 or NETCDF4_CLASSIC files (since the NETCDF3
+data model does not have unsigned integer data types).
        
+
+
        The default value of maskandscale is True
+(automatic conversions are performed).
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_auto_scale(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_auto_scale(self,scale)
        
+
+
        turn on or off automatic packing/unpacking of variable
+data using scale_factor and add_offset attributes.
+Also turns on and off automatic conversion of signed integer data
+to unsigned integer data if the variable has an _Unsigned
+attribute.
        
+
+
        If scale is set to True, and the variable has a
+scale_factor or an add_offset attribute, then data read
+from that variable is unpacked using::
        
+
+
        data = self.scale_factor*data + self.add_offset
+
        
+
+
        When data is written to a variable it is packed using::
        
+
+
        data = (data - self.add_offset)/self.scale_factor
+
        
+
+
        If either scale_factor is present, but add_offset is missing, add_offset
+is assumed zero.  If add_offset is present, but scale_factor is missing,
+scale_factor is assumed to be one.
+For more information on how scale_factor and add_offset can be
+used to provide simple compression, see the
+PSD metadata conventions.
        
+
+
        In addition, if scale is set to True, and if the variable has an
+attribute _Unsigned set, and the variable has a signed integer data type,
+a view to the data is returned with the corresponding unsigned integer datatype.
+This convention is used by the netcdf-java library to save unsigned integer
+data in NETCDF3 or NETCDF4_CLASSIC files (since the NETCDF3
+data model does not have unsigned integer data types).
        
+
+
        The default value of scale is True
+(automatic conversions are performed).
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_auto_mask(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_auto_mask(self,mask)
        
+
+
        turn on or off automatic conversion of variable data to and
+from masked arrays .
        
+
+
        If mask is set to True, when data is read from a variable
+it is converted to a masked array if any of the values are exactly
+equal to the either the netCDF _FillValue or the value specified by the
+missing_value variable attribute. The fill_value of the masked array
+is set to the missing_value attribute (if it exists), otherwise
+the netCDF _FillValue attribute (which has a default value
+for each data type).  When data is written to a variable, the masked
+array is converted back to a regular numpy array by replacing all the
+masked values by the missing_value attribute of the variable (if it
+exists).  If the variable has no missing_value attribute, the _FillValue
+is used instead. If the variable has valid_min/valid_max and
+missing_value attributes, data outside the specified range will be
+set to missing_value.
        
+
+
        The default value of mask is True
+(automatic conversions are performed).
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_always_mask(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_always_mask(self,always_mask)
        
+
+
        turn on or off conversion of data without missing values to regular
+numpy arrays.
        
+
+
        always_mask is a Boolean determining if automatic conversion of
+masked arrays with no missing values to regular numpy arrays shall be
+applied. Default is True. Set to False to restore the default behaviour
+in versions prior to 1.4.1 (numpy array returned unless missing values are present,
+otherwise masked array returned).
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_ncstring_attrs(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_always_mask(self,ncstring_attrs)
        
+
+
        turn on or off creating NC_STRING string attributes.
        
+
+
        If ncstring_attrs is set to True then text attributes will be variable-length
+NC_STRINGs.
        
+
+
        The default value of ncstring_attrs is False (writing ascii text attributes as
+NC_CHAR).
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_collective(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_collective(self,True_or_False)
        
+
+
        turn on or off collective parallel IO access. Ignored if file is not
+open for parallel access.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                get_dims(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        get_dims(self)
        
+
+
        return a tuple of Dimension instances associated with this
+Variable.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        name = <attribute 'name' of 'netCDF4._netCDF4.Variable' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        datatype = <attribute 'datatype' of 'netCDF4._netCDF4.Variable' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        shape = <attribute 'shape' of 'netCDF4._netCDF4.Variable' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        size = <attribute 'size' of 'netCDF4._netCDF4.Variable' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Variable' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        ndim = <attribute 'ndim' of 'netCDF4._netCDF4.Variable' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.Variable' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        mask = <attribute 'mask' of 'netCDF4._netCDF4.Variable' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        scale = <attribute 'scale' of 'netCDF4._netCDF4.Variable' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        always_mask = <attribute 'always_mask' of 'netCDF4._netCDF4.Variable' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        chartostring = <attribute 'chartostring' of 'netCDF4._netCDF4.Variable' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                            
+                        
+                    
        
+                
+                    
        
+                        
+                            
        class
+            CompoundType:
+        
        
+                        
+                        
+                            
+                        
+                        
        A CompoundType instance is used to describe a compound data
+type, and can be passed to the the Dataset.createVariable method of
+a Dataset or Group instance.
+Compound data types map to numpy structured arrays.
+See CompoundType.__init__ for more details.
        
+
+
        The instance variables dtype and name should not be modified by
+the user.
        
+
        
+                        
+                            
+                                
        
+                                    
+                                        
        
+                CompoundType(unknown)
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        __init__(group, datatype, datatype_name)
        
+
+
        CompoundType constructor.
        
+
+
        group: Group instance to associate with the compound datatype.
        
+
+
        datatype: A numpy dtype object describing a structured (a.k.a record)
+array.  Can be composed of homogeneous numeric or character data types, or
+other structured array data types.
        
+
+
        datatype_name: a Python string containing a description of the
+compound data type.
        
+
+
        Note 1: When creating nested compound data types,
+the inner compound data types must already be associated with CompoundType
+instances (so create CompoundType instances for the innermost structures
+first).
        
+
+
        Note 2: CompoundType instances should be created using the
+Dataset.createCompoundType
+method of a Dataset or Group instance, not using this class directly.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.CompoundType' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        dtype_view = <attribute 'dtype_view' of 'netCDF4._netCDF4.CompoundType' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        name = <attribute 'name' of 'netCDF4._netCDF4.CompoundType' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                            
+                        
+                    
        
+                
+                    
        
+                        
+                            
        class
+            VLType:
+        
        
+                        
+                        
+                            
+                        
+                        
        A VLType instance is used to describe a variable length (VLEN) data
+type, and can be passed to the the Dataset.createVariable method of
+a Dataset or Group instance. See
+VLType.__init__for more details.
        
+
+
        The instance variables dtype and name should not be modified by
+the user.
        
+
        
+                        
+                            
+                                
        
+                                    
+                                        
        
+                VLType(unknown)
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        __init__(group, datatype, datatype_name)
        
+
+
        VLType constructor.
        
+
+
        group: Group instance to associate with the VLEN datatype.
        
+
+
        datatype: An numpy dtype object describing the component type for the
+variable length array.
        
+
+
        datatype_name: a Python string containing a description of the
+VLEN data type.
        
+
+
        Note: VLType instances should be created using the
+Dataset.createVLType
+method of a Dataset or Group instance, not using this class directly.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.VLType' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        name = <attribute 'name' of 'netCDF4._netCDF4.VLType' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                            
+                        
+                    
        
+                
+                    
        
+                        
+                            
        class
+            EnumType:
+        
        
+                        
+                        
+                            
+                        
+                        
        A EnumType instance is used to describe an Enum data
+type, and can be passed to the the Dataset.createVariable method of
+a Dataset or Group instance. See
+EnumType.__init__ for more details.
        
+
+
        The instance variables dtype, name and enum_dict should not be modified by
+the user.
        
+
        
+                        
+                            
+                                
        
+                                    
+                                        
        
+                EnumType(unknown)
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        __init__(group, datatype, datatype_name, enum_dict)
        
+
+
        EnumType constructor.
        
+
+
        group: Group instance to associate with the VLEN datatype.
        
+
+
        datatype: An numpy integer dtype object describing the base type
+for the Enum.
        
+
+
        datatype_name: a Python string containing a description of the
+Enum data type.
        
+
+
        enum_dict: a Python dictionary containing the Enum field/value
+pairs.
        
+
+
        Note: EnumType instances should be created using the
+Dataset.createEnumType
+method of a Dataset or Group instance, not using this class directly.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.EnumType' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        name = <attribute 'name' of 'netCDF4._netCDF4.EnumType' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                                
        
+                                    
+                                        
        enum_dict = <attribute 'enum_dict' of 'netCDF4._netCDF4.EnumType' objects>
+        
        
+                                    
+                                    
+                                    
+                                
        
+                            
+                            
+                        
+                    
        
+                
+                    
        
+                        
+                            
        
+                def
+                getlibversion(unknown):
+            
+        
        
+                        
+                        
+                            
+                        
+                        
        getlibversion()
        
+
+
        returns a string describing the version of the netcdf library
+used to build the module, and when it was built.
        
+
        
+                        
+                    
        
+                
+                    
        
+                        
+                            
        
+                def
+                get_chunk_cache(unknown):
+            
+        
        
+                        
+                        
+                            
+                        
+                        
        get_chunk_cache()
        
+
+
        return current netCDF chunk cache information in a tuple (size,nelems,preemption).
+See netcdf C library documentation for nc_get_chunk_cache for
+details. Values can be reset with set_chunk_cache.
        
+
        
+                        
+                    
        
+                
+                    
        
+                        
+                            
        
+                def
+                set_chunk_cache(unknown):
+            
+        
        
+                        
+                        
+                            
+                        
+                        
        set_chunk_cache(self,size=None,nelems=None,preemption=None)
        
+
+
        change netCDF4 chunk cache settings.
+See netcdf C library documentation for nc_set_chunk_cache for
+details.
        
+
        
+                        
+                    
        
+                
+                    
        
+                        
+                            
        
+                def
+                stringtoarr(unknown):
+            
+        
        
+                        
+                        
+                            
+                        
+                        
        stringtoarr(a, NUMCHARS,dtype='S')
        
+
+
        convert a string to a character array of length NUMCHARS
        
+
+
        a:  Input python string.
        
+
+
        NUMCHARS:  number of characters used to represent string
+(if len(a) < NUMCHARS, it will be padded on the right with blanks).
        
+
+
        dtype:  type of numpy array to return.  Default is 'S', which
+means an array of dtype 'S1' will be returned.  If dtype='U', a
+unicode array (dtype = 'U1') will be returned.
        
+
+
        returns a rank 1 numpy character array of length NUMCHARS with datatype 'S1'
+(default) or 'U1' (if dtype='U')
        
+
        
+                        
+                    
        
+                
+                    
        
+                        
+                            
        
+                def
+                stringtochar(unknown):
+            
+        
        
+                        
+                        
+                            
+                        
+                        
        stringtochar(a,encoding='utf-8')
        
+
+
        convert a string array to a character array with one extra dimension
        
+
+
        a:  Input numpy string array with numpy datatype 'SN' or 'UN', where N
+is the number of characters in each string.  Will be converted to
+an array of characters (datatype 'S1' or 'U1') of shape a.shape + (N,).
        
+
+
        optional kwarg encoding can be used to specify character encoding (default
+utf-8). If encoding is 'none' or 'bytes', a numpy.string_ the input array
+is treated a raw byte strings (numpy.string_).
        
+
+
        returns a numpy character array with datatype 'S1' or 'U1'
+and shape a.shape + (N,), where N is the length of each string in a.
        
+
        
+                        
+                    
        
+                
+                    
        
+                        
+                            
        
+                def
+                chartostring(unknown):
+            
+        
        
+                        
+                        
+                            
+                        
+                        
        chartostring(b,encoding='utf-8')
        
+
+
        convert a character array to a string array with one less dimension.
        
+
+
        b:  Input character array (numpy datatype 'S1' or 'U1').
+Will be converted to a array of strings, where each string has a fixed
+length of b.shape[-1] characters.
        
+
+
        optional kwarg encoding can be used to specify character encoding (default
+utf-8). If encoding is 'none' or 'bytes', a numpy.string_ btye array is
+returned.
        
+
+
        returns a numpy string array with datatype 'UN' (or 'SN') and shape
+b.shape[:-1] where where N=b.shape[-1].
        
+
        
+                        
+                    
        
+                
+                    
        
+                        
+                            
        class
+            MFDataset(netCDF4._netCDF4.Dataset):
+        
        
+                        
+                        
+                            
+                        
+                        
        Class for reading multi-file netCDF Datasets, making variables
+spanning multiple files appear as if they were in one file.
+Datasets must be in NETCDF4_CLASSIC, NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET
+or NETCDF3_64BIT_DATA format (NETCDF4 Datasets won't work).
        
+
+
        Adapted from pycdf by Andre Gosselin.
        
+
+
        Example usage (See MFDataset.__init__ for more details):
        
+
+
        >>> import numpy as np
+>>> # create a series of netCDF files with a variable sharing
+>>> # the same unlimited dimension.
+>>> for nf in range(10):
+...     with Dataset("mftest%s.nc" % nf, "w", format='NETCDF4_CLASSIC') as f:
+...         f.createDimension("x",None)
+...         x = f.createVariable("x","i",("x",))
+...         x[0:10] = np.arange(nf*10,10*(nf+1))
+>>> # now read all those files in at once, in one Dataset.
+>>> f = MFDataset("mftest*nc")
+>>> print(f.variables["x"][:])
+[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
+ 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
+ 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71
+ 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
+ 96 97 98 99]
+
        
+
        
+                        
+                            
+                                
        
+                                    
+                                        
        
+                MFDataset(files, check=False, aggdim=None, exclude=[], master_file=None)
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        __init__(self, files, check=False, aggdim=None, exclude=[],
+master_file=None)
        
+
+
        Open a Dataset spanning multiple files, making it look as if it was a
+single file. Variables in the list of files that share the same
+dimension (specified with the keyword aggdim) are aggregated. If
+aggdim is not specified, the unlimited is aggregated.  Currently,
+aggdim must be the leftmost (slowest varying) dimension of each
+of the variables to be aggregated.
        
+
+
        files: either a sequence of netCDF files or a string with a
+wildcard (converted to a sorted list of files using glob)  If
+the master_file kwarg is not specified, the first file
+in the list will become the "master" file, defining all the
+variables with an aggregation dimension which may span
+subsequent files. Attribute access returns attributes only from "master"
+file. The files are always opened in read-only mode.
        
+
+
        check: True if you want to do consistency checking to ensure the
+correct variables structure for all of the netcdf files.  Checking makes
+the initialization of the MFDataset instance much slower. Default is
+False.
        
+
+
        aggdim: The name of the dimension to aggregate over (must
+be the leftmost dimension of each of the variables to be aggregated).
+If None (default), aggregate over the unlimited dimension.
        
+
+
        exclude: A list of variable names to exclude from aggregation.
+Default is an empty list.
        
+
+
        master_file: file to use as "master file", defining all the
+variables with an aggregation dimension and all global attributes.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                ncattrs(self):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        ncattrs(self)
        
+
+
        return the netcdf attribute names from the master file.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                close(self):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        close(self)
        
+
+
        close all the open files.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                filepath(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        filepath(self,encoding=None)
        
+
+
        Get the file system path (or the opendap URL) which was used to
+open/create the Dataset. Requires netcdf >= 4.1.2.  The path
+is decoded into a string using sys.getfilesystemencoding() by default, this can be
+changed using the encoding kwarg.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                isopen(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        close(self)
        
+
+
        is the Dataset open or closed?
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                sync(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        sync(self)
        
+
+
        Writes all buffered data in the Dataset to the disk file.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_fill_on(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_fill_on(self)
        
+
+
        Sets the fill mode for a Dataset open for writing to on.
        
+
+
        This causes data to be pre-filled with fill values. The fill values can be
+controlled by the variable's _Fill_Value attribute, but is usually
+sufficient to the use the netCDF default _Fill_Value (defined
+separately for each variable type). The default behavior of the netCDF
+library corresponds to set_fill_on.  Data which are equal to the
+_Fill_Value indicate that the variable was created, but never written
+to.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_fill_off(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_fill_off(self)
        
+
+
        Sets the fill mode for a Dataset open for writing to off.
        
+
+
        This will prevent the data from being pre-filled with fill values, which
+may result in some performance improvements. However, you must then make
+sure the data is actually written before being read.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                createDimension(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        createDimension(self, dimname, size=None)
        
+
+
        Creates a new dimension with the given dimname and size.
        
+
+
        size must be a positive integer or None, which stands for
+"unlimited" (default is None). Specifying a size of 0 also
+results in an unlimited dimension. The return value is the Dimension
+class instance describing the new dimension.  To determine the current
+maximum size of the dimension, use the len function on the Dimension
+instance. To determine if a dimension is 'unlimited', use the
+Dimension.isunlimited method of the Dimension instance.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                renameDimension(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        renameDimension(self, oldname, newname)
        
+
+
        rename a Dimension named oldname to newname.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                createCompoundType(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        createCompoundType(self, datatype, datatype_name)
        
+
+
        Creates a new compound data type named datatype_name from the numpy
+dtype object datatype.
        
+
+
        Note: If the new compound data type contains other compound data types
+(i.e. it is a 'nested' compound type, where not all of the elements
+are homogeneous numeric data types), then the 'inner' compound types must be
+created first.
        
+
+
        The return value is the CompoundType class instance describing the new
+datatype.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                createVLType(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        createVLType(self, datatype, datatype_name)
        
+
+
        Creates a new VLEN data type named datatype_name from a numpy
+dtype object datatype.
        
+
+
        The return value is the VLType class instance describing the new
+datatype.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                createEnumType(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        createEnumType(self, datatype, datatype_name, enum_dict)
        
+
+
        Creates a new Enum data type named datatype_name from a numpy
+integer dtype object datatype, and a python dictionary
+defining the enum fields and values.
        
+
+
        The return value is the EnumType class instance describing the new
+datatype.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                createVariable(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        createVariable(self, varname, datatype, dimensions=(), zlib=False,
+complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None,
+endian='native', least_significant_digit=None, fill_value=None, chunk_cache=None)
        
+
+
        Creates a new variable with the given varname, datatype, and
+dimensions. If dimensions are not given, the variable is assumed to be
+a scalar.
        
+
+
        If varname is specified as a path, using forward slashes as in unix to
+separate components, then intermediate groups will be created as necessary
+For example, createVariable('/GroupA/GroupB/VarC', float, ('x','y')) will create groups GroupA
+and GroupA/GroupB, plus the variable GroupA/GroupB/VarC, if the preceding
+groups don't already exist.
        
+
+
        The datatype can be a numpy datatype object, or a string that describes
+a numpy dtype object (like the dtype.str attribute of a numpy array).
+Supported specifiers include: 'S1' or 'c' (NC_CHAR), 'i1' or 'b' or 'B'
+(NC_BYTE), 'u1' (NC_UBYTE), 'i2' or 'h' or 's' (NC_SHORT), 'u2'
+(NC_USHORT), 'i4' or 'i' or 'l' (NC_INT), 'u4' (NC_UINT), 'i8' (NC_INT64),
+'u8' (NC_UINT64), 'f4' or 'f' (NC_FLOAT), 'f8' or 'd' (NC_DOUBLE).
+datatype can also be a CompoundType instance
+(for a structured, or compound array), a VLType instance
+(for a variable-length array), or the python str builtin
+(for a variable-length string array). Numpy string and unicode datatypes with
+length greater than one are aliases for str.
        
+
+
        Data from netCDF variables is presented to python as numpy arrays with
+the corresponding data type.
        
+
+
        dimensions must be a tuple containing dimension names (strings) that
+have been defined previously using Dataset.createDimension. The default value
+is an empty tuple, which means the variable is a scalar.
        
+
+
        If the optional keyword zlib is True, the data will be compressed in
+the netCDF file using gzip compression (default False).
        
+
+
        The optional keyword complevel is an integer between 1 and 9 describing
+the level of compression desired (default 4). Ignored if zlib=False.
        
+
+
        If the optional keyword shuffle is True, the HDF5 shuffle filter
+will be applied before compressing the data (default True).  This
+significantly improves compression. Default is True. Ignored if
+zlib=False.
        
+
+
        If the optional keyword fletcher32 is True, the Fletcher32 HDF5
+checksum algorithm is activated to detect errors. Default False.
        
+
+
        If the optional keyword contiguous is True, the variable data is
+stored contiguously on disk.  Default False. Setting to True for
+a variable with an unlimited dimension will trigger an error.
        
+
+
        The optional keyword chunksizes can be used to manually specify the
+HDF5 chunksizes for each dimension of the variable. A detailed
+discussion of HDF chunking and I/O performance is available
+here.
+Basically, you want the chunk size for each dimension to match as
+closely as possible the size of the data block that users will read
+from the file.  chunksizes cannot be set if contiguous=True.
        
+
+
        The optional keyword endian can be used to control whether the
+data is stored in little or big endian format on disk. Possible
+values are little, big or native (default). The library
+will automatically handle endian conversions when the data is read,
+but if the data is always going to be read on a computer with the
+opposite format as the one used to create the file, there may be
+some performance advantage to be gained by setting the endian-ness.
        
+
+
        The zlib, complevel, shuffle, fletcher32, contiguous, chunksizes and endian
+keywords are silently ignored for netCDF 3 files that do not use HDF5.
        
+
+
        The optional keyword fill_value can be used to override the default
+netCDF _FillValue (the value that the variable gets filled with before
+any data is written to it, defaults given in default_fillvals).
+If fill_value is set to False, then the variable is not pre-filled.
        
+
+
        If the optional keyword parameter least_significant_digit is
+specified, variable data will be truncated (quantized). In conjunction
+with zlib=True this produces 'lossy', but significantly more
+efficient compression. For example, if least_significant_digit=1,
+data will be quantized using numpy.around(scale*data)/scale, where
+scale = 2**bits, and bits is determined so that a precision of 0.1 is
+retained (in this case bits=4). From the
+PSD metadata conventions:
+"least_significant_digit -- power of ten of the smallest decimal place
+in unpacked data that is a reliable value." Default is None, or no
+quantization, or 'lossless' compression.
        
+
+
        When creating variables in a NETCDF4 or NETCDF4_CLASSIC formatted file,
+HDF5 creates something called a 'chunk cache' for each variable.  The
+default size of the chunk cache may be large enough to completely fill
+available memory when creating thousands of variables.  The optional
+keyword chunk_cache allows you to reduce (or increase) the size of
+the default chunk cache when creating a variable.  The setting only
+persists as long as the Dataset is open - you can use the set_var_chunk_cache
+method to change it the next time the Dataset is opened.
+Warning - messing with this parameter can seriously degrade performance.
        
+
+
        The return value is the Variable class instance describing the new
+variable.
        
+
+
        A list of names corresponding to netCDF variable attributes can be
+obtained with the Variable method Variable.ncattrs. A dictionary
+containing all the netCDF attribute name/value pairs is provided by
+the __dict__ attribute of a Variable instance.
        
+
+
        Variable instances behave much like array objects. Data can be
+assigned to or retrieved from a variable with indexing and slicing
+operations on the Variable instance. A Variable instance has six
+Dataset standard attributes: dimensions, dtype, shape, ndim, name and
+least_significant_digit. Application programs should never modify
+these attributes. The dimensions attribute is a tuple containing the
+names of the dimensions associated with this variable. The dtype
+attribute is a string describing the variable's data type (i4, f8,
+S1, etc). The shape attribute is a tuple describing the current
+sizes of all the variable's dimensions. The name attribute is a
+string containing the name of the Variable instance.
+The least_significant_digit
+attributes describes the power of ten of the smallest decimal place in
+the data the contains a reliable value.  assigned to the Variable
+instance. If None, the data is not truncated. The ndim attribute
+is the number of variable dimensions.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                renameVariable(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        renameVariable(self, oldname, newname)
        
+
+
        rename a Variable named oldname to newname
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                createGroup(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        createGroup(self, groupname)
        
+
+
        Creates a new Group with the given groupname.
        
+
+
        If groupname is specified as a path, using forward slashes as in unix to
+separate components, then intermediate groups will be created as necessary
+(analogous to mkdir -p in unix).  For example,
+createGroup('/GroupA/GroupB/GroupC') will create GroupA,
+GroupA/GroupB, and GroupA/GroupB/GroupC, if they don't already exist.
+If the specified path describes a group that already exists, no error is
+raised.
        
+
+
        The return value is a Group class instance.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                setncattr(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        setncattr(self,name,value)
        
+
+
        set a netCDF dataset or group attribute using name,value pair.
+Use if you need to set a netCDF attribute with the
+with the same name as one of the reserved python attributes.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                setncattr_string(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        setncattr_string(self,name,value)
        
+
+
        set a netCDF dataset or group string attribute using name,value pair.
+Use if you need to ensure that a netCDF attribute is created with type
+NC_STRING if the file format is NETCDF4.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                setncatts(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        setncatts(self,attdict)
        
+
+
        set a bunch of netCDF dataset or group attributes at once using a python dictionary.
+This may be faster when setting a lot of attributes for a NETCDF3
+formatted file, since nc_redef/nc_enddef is not called in between setting
+each attribute
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                getncattr(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        getncattr(self,name)
        
+
+
        retrieve a netCDF dataset or group attribute.
+Use if you need to get a netCDF attribute with the same
+name as one of the reserved python attributes.
        
+
+
        option kwarg encoding can be used to specify the
+character encoding of a string attribute (default is utf-8).
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                delncattr(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        delncattr(self,name,value)
        
+
+
        delete a netCDF dataset or group attribute.  Use if you need to delete a
+netCDF attribute with the same name as one of the reserved python
+attributes.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                renameAttribute(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        renameAttribute(self, oldname, newname)
        
+
+
        rename a Dataset or Group attribute named oldname to newname.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                renameGroup(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        renameGroup(self, oldname, newname)
        
+
+
        rename a Group named oldname to newname (requires netcdf >= 4.3.1).
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_auto_chartostring(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_auto_chartostring(self, True_or_False)
        
+
+
        Call Variable.set_auto_chartostring for all variables contained in this Dataset or
+Group, as well as for all variables in all its subgroups.
        
+
+
        True_or_False: Boolean determining if automatic conversion of
+all character arrays <--> string arrays should be performed for
+character variables (variables of type NC_CHAR or S1) with the
+_Encoding attribute set.
        
+
+
        Note: Calling this function only affects existing variables. Variables created
+after calling this function will follow the default behaviour.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_auto_maskandscale(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_auto_maskandscale(self, True_or_False)
        
+
+
        Call Variable.set_auto_maskandscale for all variables contained in this Dataset or
+Group, as well as for all variables in all its subgroups.
        
+
+
        True_or_False: Boolean determining if automatic conversion to masked arrays
+and variable scaling shall be applied for all variables.
        
+
+
        Note: Calling this function only affects existing variables. Variables created
+after calling this function will follow the default behaviour.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_auto_mask(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_auto_mask(self, True_or_False)
        
+
+
        Call Variable.set_auto_mask for all variables contained in this Dataset or
+Group, as well as for all variables in all its subgroups.
        
+
+
        True_or_False: Boolean determining if automatic conversion to masked arrays
+shall be applied for all variables.
        
+
+
        Note: Calling this function only affects existing variables. Variables created
+after calling this function will follow the default behaviour.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_auto_scale(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_auto_scale(self, True_or_False)
        
+
+
        Call Variable.set_auto_scale for all variables contained in this Dataset or
+Group, as well as for all variables in all its subgroups.
        
+
+
        True_or_False: Boolean determining if automatic variable scaling
+shall be applied for all variables.
        
+
+
        Note: Calling this function only affects existing variables. Variables created
+after calling this function will follow the default behaviour.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_always_mask(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_always_mask(self, True_or_False)
        
+
+
        Call Variable.set_always_mask for all variables contained in
+this Dataset or Group, as well as for all
+variables in all its subgroups.
        
+
+
        True_or_False: Boolean determining if automatic conversion of
+masked arrays with no missing values to regular numpy arrays shall be
+applied for all variables. Default True. Set to False to restore the default behaviour
+in versions prior to 1.4.1 (numpy array returned unless missing values are present,
+otherwise masked array returned).
        
+
+
        Note: Calling this function only affects existing
+variables. Variables created after calling this function will follow
+the default behaviour.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                set_ncstring_attrs(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        set_ncstring_attrs(self, True_or_False)
        
+
+
        Call Variable.set_ncstring_attrs for all variables contained in
+this Dataset or Group, as well as for all its
+subgroups and their variables.
        
+
+
        True_or_False: Boolean determining if all string attributes are
+created as variable-length NC_STRINGs, (if True), or if ascii text
+attributes are stored as NC_CHARs (if False; default)
        
+
+
        Note: Calling this function only affects newly created attributes
+of existing (sub-) groups and their variables.
        
+
        
+                                
        
+                            
+                                
        
+                                    
+                                        
        
+                def
+                get_variables_by_attributes(unknown):
+            
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        get_variables_by_attribute(self, **kwargs)
        
+
+
        Returns a list of variables that match specific conditions.
        
+
+
        Can pass in key=value parameters and variables are returned that
+contain all of the matches. For example,
        
+
+
        >>> # Get variables with x-axis attribute.
+>>> vs = nc.get_variables_by_attributes(axis='X')
+>>> # Get variables with matching "standard_name" attribute
+>>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
+
        
+
+
        Can pass in key=callable parameter and variables are returned if the
+callable returns True.  The callable should accept a single parameter,
+the attribute value.  None is given as the attribute value when the
+attribute does not exist on the variable. For example,
        
+
+
        >>> # Get Axis variables
+>>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
+>>> # Get variables that don't have an "axis" attribute
+>>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
+>>> # Get variables that have a "grid_mapping" attribute
+>>> vs = nc.get_variables_by_attributes(grid_mapping=lambda v: v is not None)
+
        
+
        
+                                
        
+                            
+                            
+                                
+                                    
        
+                                        
        Inherited Members
        
+                                        
        
+                                            
+                                                
+                                            
+                                        
        
+                                    
        
+                                
+                            
+                        
+                    
        
+                
+                    
        
+                        
+                            
        class
+            MFTime(netCDF4._netCDF4._Variable):
+        
        
+                        
+                        
+                            
+                        
+                        
        Class providing an interface to a MFDataset time Variable by imposing a unique common
+time unit and/or calendar to all files.
        
+
+
        Example usage (See MFTime.__init__ for more details):
        
+
+
        >>> import numpy
+>>> f1 = Dataset("mftest_1.nc","w", format="NETCDF4_CLASSIC")
+>>> f2 = Dataset("mftest_2.nc","w", format="NETCDF4_CLASSIC")
+>>> f1.createDimension("time",None)
+>>> f2.createDimension("time",None)
+>>> t1 = f1.createVariable("time","i",("time",))
+>>> t2 = f2.createVariable("time","i",("time",))
+>>> t1.units = "days since 2000-01-01"
+>>> t2.units = "days since 2000-02-01"
+>>> t1.calendar = "standard"
+>>> t2.calendar = "standard"
+>>> t1[:] = numpy.arange(31)
+>>> t2[:] = numpy.arange(30)
+>>> f1.close()
+>>> f2.close()
+>>> # Read the two files in at once, in one Dataset.
+>>> f = MFDataset("mftest_*nc")
+>>> t = f.variables["time"]
+>>> print(t.units)
+days since 2000-01-01
+>>> print(t[32])  # The value written in the file, inconsistent with the MF time units.
+1
+>>> T = MFTime(t)
+>>> print(T[32])
+32
+
        
+
        
+                        
+                            
+                                
        
+                                    
+                                        
        
+                MFTime(time, units=None, calendar=None)
+        
        
+                                    
+                                    
+                                        
+                                    
+                                    
        __init__(self, time, units=None, calendar=None)
        
+
+
        Create a time Variable with units consistent across a multifile
+dataset.
        
+
+
        time: Time variable from a MFDataset.
        
+
+
        units: Time units, for example, 'days since 1979-01-01'. If None,
+use the units from the master variable.
        
+
+
        calendar: Calendar overload to use across all files, for example,
+'standard' or 'gregorian'. If None, check that the calendar attribute
+is present on each variable and values are unique across files raising a
+ValueError otherwise.
        
+
        
+                                
        
+                            
+                            
+                                
+                                    
        
+                                        
        Inherited Members
        
+                                        
        
+                                            
+                                                
+                                            
+                                        
        
+                                    
        
+                                
+                            
+                        
+                    
        
+                
+            
+        
        
+    
        
+    
+
+
+
diff --git a/docs/netCDF4/index.html b/docs/netCDF4/index.html
deleted file mode 100644
index 80e351583..000000000
--- a/docs/netCDF4/index.html
+++ /dev/null
@@ -1,6644 +0,0 @@
-
-
-  
-  
-
-    netCDF4 API documentation
-    
-
-  
-  
-  
-
-  
-
-  
-
-  
-
-  
-
-
-Top
-
-
        
-    
-  
-  
-
-    
        
-      
-  
-
-  
-
-
-  
        
-  
        netCDF4 module
        
-  
        Version 1.5.5
        
-
        
-
        Introduction
        
-
        netcdf4-python is a Python interface to the netCDF C library.
        
-
        netCDF version 4 has many features
-not found in earlier versions of the library and is implemented on top of
-HDF5. This module can read and write
-files in both the new netCDF 4 and the old netCDF 3 format, and can create
-files that are readable by HDF5 clients. The API modelled after
-Scientific.IO.NetCDF,
-and should be familiar to users of that module.
        
-
        Most new features of netCDF 4 are implemented, such as multiple
-unlimited dimensions, groups and zlib data compression.  All the new
-numeric data types (such as 64 bit and unsigned integer types) are
-implemented. Compound (struct), variable length (vlen) and
-enumerated (enum) data types are supported, but not the opaque data type.
-Mixtures of compound, vlen and enum data types (such as
-compound types containing enums, or vlens containing compound
-types) are not supported.
        
-
        Download
        
-
-
        Requires
        
-
          
-
        • numpy array module, version 1.10.0 or later.
          • 
-
        • Cython, version 0.21 or later.
          • 
-
        • setuptools, version 18.0 or
-   later.
          • 
-
        • cftime for
- the time and date handling utility functions (num2date,
- date2num and date2index).
          • 
-
        • The HDF5 C library version 1.8.4-patch1 or higher (1.8.x recommended)
- from .
- netCDF version 4.4.1 or higher is recommended if using HDF5 1.10.x -
- otherwise resulting files may be unreadable by clients using earlier
- versions of HDF5.  For netCDF < 4.4.1, HDF5 version 1.8.x is recommended.
- Be sure to build with --enable-hl --enable-shared.
          • 
-
        • Libcurl, if you want
- OPeNDAP support.
          • 
-
        • HDF4, if you want
- to be able to read HDF4 "Scientific Dataset" (SD) files.
          • 
-
        • The netCDF-4 C library from the github releases
-   page.
- Version 4.1.1 or higher is required (4.2 or higher recommended).
- Be sure to build with --enable-netcdf-4 --enable-shared, and set
- CPPFLAGS="-I $HDF5_DIR/include" and LDFLAGS="-L $HDF5_DIR/lib",
- where $HDF5_DIR is the directory where HDF5 was installed.
- If you want OPeNDAP support, add --enable-dap.
- If you want HDF4 SD support, add --enable-hdf4 and add
- the location of the HDF4 headers and library to $CPPFLAGS and $LDFLAGS.
          • 
-
        • for MPI parallel IO support, an MPI-enabled versions of the netcdf library
- is required, as is the mpi4py python module.
- Parallel IO further depends on the existence of MPI-enabled HDF5 or the
- PnetCDF library.
          • 
-
        
-
        Install
        
-
          
-
        • install the requisite python modules and C libraries (see above). It's
- easiest if all the C libs are built as shared libraries.
          • 
-
        • By default, the utility nc-config, installed with netcdf 4.1.2 or higher,
- will be run used to determine where all the dependencies live.
          • 
-
        • If nc-config is not in your default PATH, you can set the NETCDF4_DIR
- environment variable and setup.py will look in $NETCDF4_DIR/bin.
- You can also use the file setup.cfg to set the path to nc-config, or
- enter the paths to the libraries and include files manually. Just  edit the setup.cfg file
- in a text editor and follow the instructions in the comments.
- To disable the use of nc-config, set the env var USE_NCCONFIG to 0.
- To disable the use of setup.cfg, set USE_SETUPCFG to 0.
- As a last resort, the library and include paths can be set via environment variables.
- If you go this route, set USE_NCCONFIG and USE_SETUPCFG to 0, and specify
- NETCDF4_LIBDIR, NETCDF4_INCDIR, HDF5_LIBDIR and HDF5_INCDIR.
- Similarly, environment variables
- (all capitalized) can be used to set the include and library paths for
- hdf4, szip, jpeg, curl and zlib. If the dependencies are not found
- in any of the paths specified by environment variables, then standard locations
- (such as /usr and /usr/local) are searched.
          • 
-
        • run python setup.py build, then python setup.py install (as root if
- necessary). pip install can be used to install pre-compiled binary wheels from 
- pypi.
          • 
-
        • run the tests in the 'test' directory by running python run_all.py.
          • 
-
        
-
        Tutorial
        
-
          
-
        1. Creating/Opening/Closing a netCDF file.
          2. 
-
        2. Groups in a netCDF file.
          3. 
-
        3. Dimensions in a netCDF file.
          4. 
-
        4. Variables in a netCDF file.
          5. 
-
        5. Attributes in a netCDF file.
          6. 
-
        6. Writing data to and retrieving data from a netCDF variable.
          7. 
-
        7. Dealing with time coordinates.
          8. 
-
        8. Reading data from a multi-file netCDF dataset.
          9. 
-
        9. Efficient compression of netCDF variables.
          10. 
-
        10. Beyond homogeneous arrays of a fixed type - compound data types.
          11. 
-
        11. Variable-length (vlen) data types.
          12. 
-
        12. Enum data type.
          13. 
-
        13. Parallel IO.
          14. 
-
        14. Dealing with strings.
          15. 
-
        15. In-memory (diskless) Datasets.
          16. 
-
        
-
        1) Creating/Opening/Closing a netCDF file.
        
-
        To create a netCDF file from python, you simply call the Dataset
-constructor. This is also the method used to open an existing netCDF
-file.  If the file is open for write access (mode='w', 'r+' or 'a'), you may
-write any type of data including new dimensions, groups, variables and
-attributes.  netCDF files come in five flavors (NETCDF3_CLASSIC,
-NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF4_CLASSIC, and NETCDF4).
-NETCDF3_CLASSIC was the original netcdf binary format, and was limited
-to file sizes less than 2 Gb. NETCDF3_64BIT_OFFSET was introduced
-in version 3.6.0 of the library, and extended the original binary format
-to allow for file sizes greater than 2 Gb.
-NETCDF3_64BIT_DATA is a new format that requires version 4.4.0 of
-the C library - it extends the NETCDF3_64BIT_OFFSET binary format to
-allow for unsigned/64 bit integer data types and 64-bit dimension sizes.
-NETCDF3_64BIT is an alias for NETCDF3_64BIT_OFFSET.
-NETCDF4_CLASSIC files use the version 4 disk format (HDF5), but omits features
-not found in the version 3 API. They can be read by netCDF 3 clients
-only if they have been relinked against the netCDF 4 library. They can
-also be read by HDF5 clients. NETCDF4 files use the version 4 disk
-format (HDF5) and use the new features of the version 4 API.  The
-netCDF4 module can read and write files in any of these formats. When
-creating a new file, the format may be specified using the format
-keyword in the Dataset constructor.  The default format is
-NETCDF4. To see how a given file is formatted, you can examine the
-data_model attribute.  Closing the netCDF file is
-accomplished via the close method of the Dataset
-instance.
        
-
        Here's an example:
        
-
        >>> from netCDF4 import Dataset
->>> rootgrp = Dataset("test.nc", "w", format="NETCDF4")
->>> print(rootgrp.data_model)
-NETCDF4
->>> rootgrp.close()
-
        
-
-
-
        Remote OPeNDAP-hosted datasets can be accessed for
-reading over http if a URL is provided to the Dataset constructor instead of a
-filename.  However, this requires that the netCDF library be built with
-OPenDAP support, via the --enable-dap configure option (added in
-version 4.0.1).
        
-
        2) Groups in a netCDF file.
        
-
        netCDF version 4 added support for organizing data in hierarchical
-groups, which are analogous to directories in a filesystem. Groups serve
-as containers for variables, dimensions and attributes, as well as other
-groups.  A Dataset creates a special group, called
-the 'root group', which is similar to the root directory in a unix
-filesystem.  To create Group instances, use the
-createGroup method of a Dataset or Group
-instance. createGroup takes a single argument, a
-python string containing the name of the new group. The new Group
-instances contained within the root group can be accessed by name using
-the groups dictionary attribute of the Dataset instance.  Only
-NETCDF4 formatted files support Groups, if you try to create a Group
-in a netCDF 3 file you will get an error message.
        
-
        >>> rootgrp = Dataset("test.nc", "a")
->>> fcstgrp = rootgrp.createGroup("forecasts")
->>> analgrp = rootgrp.createGroup("analyses")
->>> print(rootgrp.groups)
-{'forecasts': <class 'netCDF4._netCDF4.Group'>
-group /forecasts:
-    dimensions(sizes): 
-    variables(dimensions): 
-    groups: , 'analyses': <class 'netCDF4._netCDF4.Group'>
-group /analyses:
-    dimensions(sizes): 
-    variables(dimensions): 
-    groups: }
-
        
-
-
-
        Groups can exist within groups in a Dataset, just as directories
-exist within directories in a unix filesystem. Each Group instance
-has a groups attribute dictionary containing all of the group
-instances contained within that group. Each Group instance also has a
-path attribute that contains a simulated unix directory path to
-that group.  To simplify the creation of nested groups, you can
-use a unix-like path as an argument to createGroup.
        
-
        >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
->>> fcstgrp2 = rootgrp.createGroup("/forecasts/model2")
-
        
-
-
-
        If any of the intermediate elements of the path do not exist, they are created,
-just as with the unix command 'mkdir -p'. If you try to create a group
-that already exists, no error will be raised, and the existing group will be
-returned.
        
-
        Here's an example that shows how to navigate all the groups in a
-Dataset. The function walktree is a Python generator that is used
-to walk the directory tree. Note that printing the Dataset or Group
-object yields summary information about it's contents.
        
-
        >>> def walktree(top):
-...     values = top.groups.values()
-...     yield values
-...     for value in top.groups.values():
-...         for children in walktree(value):
-...             yield children
->>> print(rootgrp)
-<class 'netCDF4._netCDF4.Dataset'>
-root group (NETCDF4 data model, file format HDF5):
-    dimensions(sizes): 
-    variables(dimensions): 
-    groups: forecasts, analyses
->>> for children in walktree(rootgrp):
-...     for child in children:
-...         print(child)
-<class 'netCDF4._netCDF4.Group'>
-group /forecasts:
-    dimensions(sizes): 
-    variables(dimensions): 
-    groups: model1, model2
-<class 'netCDF4._netCDF4.Group'>
-group /analyses:
-    dimensions(sizes): 
-    variables(dimensions): 
-    groups: 
-<class 'netCDF4._netCDF4.Group'>
-group /forecasts/model1:
-    dimensions(sizes): 
-    variables(dimensions): 
-    groups: 
-<class 'netCDF4._netCDF4.Group'>
-group /forecasts/model2:
-    dimensions(sizes): 
-    variables(dimensions): 
-    groups:
-
        
-
-
-
        3) Dimensions in a netCDF file.
        
-
        netCDF defines the sizes of all variables in terms of dimensions, so
-before any variables can be created the dimensions they use must be
-created first. A special case, not often used in practice, is that of a
-scalar variable, which has no dimensions. A dimension is created using
-the createDimension method of a Dataset
-or Group instance. A Python string is used to set the name of the
-dimension, and an integer value is used to set the size. To create an
-unlimited dimension (a dimension that can be appended to), the size
-value is set to None or 0. In this example, there both the time and
-level dimensions are unlimited.  Having more than one unlimited
-dimension is a new netCDF 4 feature, in netCDF 3 files there may be only
-one, and it must be the first (leftmost) dimension of the variable.
        
-
        >>> level = rootgrp.createDimension("level", None)
->>> time = rootgrp.createDimension("time", None)
->>> lat = rootgrp.createDimension("lat", 73)
->>> lon = rootgrp.createDimension("lon", 144)
-
        
-
-
-
        All of the Dimension instances are stored in a python dictionary.
        
-
        >>> print(rootgrp.dimensions)
-{'level': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0, 'time': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0, 'lat': <class 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 73, 'lon': <class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144}
-
        
-
-
-
        Calling the python len function with a Dimension instance returns
-the current size of that dimension.
-The isunlimited method of a Dimension instance
-can be used to determine if the dimensions is unlimited, or appendable.
        
-
        >>> print(len(lon))
-144
->>> print(lon.isunlimited())
-False
->>> print(time.isunlimited())
-True
-
        
-
-
-
        Printing the Dimension object
-provides useful summary info, including the name and length of the dimension,
-and whether it is unlimited.
        
-
        >>> for dimobj in rootgrp.dimensions.values():
-...     print(dimobj)
-<class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0
-<class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0
-<class 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 73
-<class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144
-
        
-
-
-
        Dimension names can be changed using the
-netCDF4.Datatset.renameDimension method of a Dataset or
-Group instance.
        
-
        4) Variables in a netCDF file.
        
-
        netCDF variables behave much like python multidimensional array objects
-supplied by the numpy module. However,
-unlike numpy arrays, netCDF4 variables can be appended to along one or
-more 'unlimited' dimensions. To create a netCDF variable, use the
-createVariable method of a Dataset or
-Group instance. The createVariable method
-has two mandatory arguments, the variable name (a Python string), and
-the variable datatype. The variable's dimensions are given by a tuple
-containing the dimension names (defined previously with
-createDimension). To create a scalar
-variable, simply leave out the dimensions keyword. The variable
-primitive datatypes correspond to the dtype attribute of a numpy array.
-You can specify the datatype as a numpy dtype object, or anything that
-can be converted to a numpy dtype object.  Valid datatype specifiers
-include: 'f4' (32-bit floating point), 'f8' (64-bit floating
-point), 'i4' (32-bit signed integer), 'i2' (16-bit signed
-integer), 'i8' (64-bit signed integer), 'i1' (8-bit signed
-integer), 'u1' (8-bit unsigned integer), 'u2' (16-bit unsigned
-integer), 'u4' (32-bit unsigned integer), 'u8' (64-bit unsigned
-integer), or 'S1' (single-character string).  The old Numeric
-single-character typecodes ('f','d','h',
-'s','b','B','c','i','l'), corresponding to
-('f4','f8','i2','i2','i1','i1','S1','i4','i4'),
-will also work. The unsigned integer types and the 64-bit integer type
-can only be used if the file format is NETCDF4.
        
-
        The dimensions themselves are usually also defined as variables, called
-coordinate variables. The createVariable
-method returns an instance of the Variable class whose methods can be
-used later to access and set variable data and attributes.
        
-
        >>> times = rootgrp.createVariable("time","f8",("time",))
->>> levels = rootgrp.createVariable("level","i4",("level",))
->>> latitudes = rootgrp.createVariable("lat","f4",("lat",))
->>> longitudes = rootgrp.createVariable("lon","f4",("lon",))
->>> # two dimensions unlimited
->>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
->>> temp.units = "K"
-
        
-
-
-
        To get summary info on a Variable instance in an interactive session,
-just print it.
        
-
        >>> print(temp)
-<class 'netCDF4._netCDF4.Variable'>
-float32 temp(time, level, lat, lon)
-    units: K
-unlimited dimensions: time, level
-current shape = (0, 0, 73, 144)
-filling on, default _FillValue of 9.969209968386869e+36 used
-
        
-
-
-
        You can use a path to create a Variable inside a hierarchy of groups.
        
-
        >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
-
        
-
-
-
        If the intermediate groups do not yet exist, they will be created.
        
-
        You can also query a Dataset or Group instance directly to obtain Group or
-Variable instances using paths.
        
-
        >>> print(rootgrp["/forecasts/model1"])  # a Group instance
-<class 'netCDF4._netCDF4.Group'>
-group /forecasts/model1:
-    dimensions(sizes): 
-    variables(dimensions): float32 temp(time,level,lat,lon)
-    groups: 
->>> print(rootgrp["/forecasts/model1/temp"])  # a Variable instance
-<class 'netCDF4._netCDF4.Variable'>
-float32 temp(time, level, lat, lon)
-path = /forecasts/model1
-unlimited dimensions: time, level
-current shape = (0, 0, 73, 144)
-filling on, default _FillValue of 9.969209968386869e+36 used
-
        
-
-
-
        All of the variables in the Dataset or Group are stored in a
-Python dictionary, in the same way as the dimensions:
        
-
        >>> print(rootgrp.variables)
-{'time': <class 'netCDF4._netCDF4.Variable'>
-float64 time(time)
-unlimited dimensions: time
-current shape = (0,)
-filling on, default _FillValue of 9.969209968386869e+36 used, 'level': <class 'netCDF4._netCDF4.Variable'>
-int32 level(level)
-unlimited dimensions: level
-current shape = (0,)
-filling on, default _FillValue of -2147483647 used, 'lat': <class 'netCDF4._netCDF4.Variable'>
-float32 lat(lat)
-unlimited dimensions: 
-current shape = (73,)
-filling on, default _FillValue of 9.969209968386869e+36 used, 'lon': <class 'netCDF4._netCDF4.Variable'>
-float32 lon(lon)
-unlimited dimensions: 
-current shape = (144,)
-filling on, default _FillValue of 9.969209968386869e+36 used, 'temp': <class 'netCDF4._netCDF4.Variable'>
-float32 temp(time, level, lat, lon)
-    units: K
-unlimited dimensions: time, level
-current shape = (0, 0, 73, 144)
-filling on, default _FillValue of 9.969209968386869e+36 used}
-
        
-
-
-
        Variable names can be changed using the
-renameVariable method of a Dataset
-instance.
        
-
        5) Attributes in a netCDF file.
        
-
        There are two types of attributes in a netCDF file, global and variable.
-Global attributes provide information about a group, or the entire
-dataset, as a whole. Variable attributes provide information about
-one of the variables in a group. Global attributes are set by assigning
-values to Dataset or Group instance variables. Variable
-attributes are set by assigning values to Variable instances
-variables. Attributes can be strings, numbers or sequences. Returning to
-our example,
        
-
        >>> import time
->>> rootgrp.description = "bogus example script"
->>> rootgrp.history = "Created " + time.ctime(time.time())
->>> rootgrp.source = "netCDF4 python module tutorial"
->>> latitudes.units = "degrees north"
->>> longitudes.units = "degrees east"
->>> levels.units = "hPa"
->>> temp.units = "K"
->>> times.units = "hours since 0001-01-01 00:00:00.0"
->>> times.calendar = "gregorian"
-
        
-
-
-
        The ncattrs method of a Dataset, Group or
-Variable instance can be used to retrieve the names of all the netCDF
-attributes. This method is provided as a convenience, since using the
-built-in dir Python function will return a bunch of private methods
-and attributes that cannot (or should not) be modified by the user.
        
-
        >>> for name in rootgrp.ncattrs():
-...     print("Global attr {} = {}".format(name, getattr(rootgrp, name)))
-Global attr description = bogus example script
-Global attr history = Created Mon Jul  8 14:19:41 2019
-Global attr source = netCDF4 python module tutorial
-
        
-
-
-
        The __dict__ attribute of a Dataset, Group or Variable
-instance provides all the netCDF attribute name/value pairs in a python
-dictionary:
        
-
        >>> print(rootgrp.__dict__)
-{'description': 'bogus example script', 'history': 'Created Mon Jul  8 14:19:41 2019', 'source': 'netCDF4 python module tutorial'}
-
        
-
-
-
        Attributes can be deleted from a netCDF Dataset, Group or
-Variable using the python del statement (i.e. del grp.foo
-removes the attribute foo the the group grp).
        
-
        6) Writing data to and retrieving data from a netCDF variable.
        
-
        Now that you have a netCDF Variable instance, how do you put data
-into it? You can just treat it like an array and assign data to a slice.
        
-
        >>> import numpy
->>> lats =  numpy.arange(-90,91,2.5)
->>> lons =  numpy.arange(-180,180,2.5)
->>> latitudes[:] = lats
->>> longitudes[:] = lons
->>> print("latitudes =\n{}".format(latitudes[:]))
-latitudes =
-[-90.  -87.5 -85.  -82.5 -80.  -77.5 -75.  -72.5 -70.  -67.5 -65.  -62.5
- -60.  -57.5 -55.  -52.5 -50.  -47.5 -45.  -42.5 -40.  -37.5 -35.  -32.5
- -30.  -27.5 -25.  -22.5 -20.  -17.5 -15.  -12.5 -10.   -7.5  -5.   -2.5
-   0.    2.5   5.    7.5  10.   12.5  15.   17.5  20.   22.5  25.   27.5
-  30.   32.5  35.   37.5  40.   42.5  45.   47.5  50.   52.5  55.   57.5
-  60.   62.5  65.   67.5  70.   72.5  75.   77.5  80.   82.5  85.   87.5
-  90. ]
-
        
-
-
-
        Unlike NumPy's array objects, netCDF Variable
-objects with unlimited dimensions will grow along those dimensions if you
-assign data outside the currently defined range of indices.
        
-
        >>> # append along two unlimited dimensions by assigning to slice.
->>> nlats = len(rootgrp.dimensions["lat"])
->>> nlons = len(rootgrp.dimensions["lon"])
->>> print("temp shape before adding data = {}".format(temp.shape))
-temp shape before adding data = (0, 0, 73, 144)
->>>
->>> from numpy.random import uniform
->>> temp[0:5, 0:10, :, :] = uniform(size=(5, 10, nlats, nlons))
->>> print("temp shape after adding data = {}".format(temp.shape))
-temp shape after adding data = (5, 10, 73, 144)
->>>
->>> # levels have grown, but no values yet assigned.
->>> print("levels shape after adding pressure data = {}".format(levels.shape))
-levels shape after adding pressure data = (10,)
-
        
-
-
-
        Note that the size of the levels variable grows when data is appended
-along the level dimension of the variable temp, even though no
-data has yet been assigned to levels.
        
-
        >>> # now, assign data to levels dimension variable.
->>> levels[:] =  [1000.,850.,700.,500.,300.,250.,200.,150.,100.,50.]
-
        
-
-
-
        However, that there are some differences between NumPy and netCDF
-variable slicing rules. Slices behave as usual, being specified as a
-start:stop:step triplet. Using a scalar integer index i takes the ith
-element and reduces the rank of the output array by one. Boolean array and
-integer sequence indexing behaves differently for netCDF variables
-than for numpy arrays.  Only 1-d boolean arrays and integer sequences are
-allowed, and these indices work independently along each dimension (similar
-to the way vector subscripts work in fortran).  This means that
        
-
        >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
-(4, 4)
-
        
-
-
-
        returns an array of shape (4,4) when slicing a netCDF variable, but for a
-numpy array it returns an array of shape (4,).
-Similarly, a netCDF variable of shape (2,3,4,5) indexed
-with [0, array([True, False, True]), array([False, True, True, True]), :]
-would return a (2, 3, 5) array. In NumPy, this would raise an error since
-it would be equivalent to [0, [0,1], [1,2,3], :]. When slicing with integer
-sequences, the indices need not be sorted and may contain
-duplicates (both of these are new features in version 1.2.1).
-While this behaviour may cause some confusion for those used to NumPy's 'fancy indexing' rules,
-it provides a very powerful way to extract data from multidimensional netCDF
-variables by using logical operations on the dimension arrays to create slices.
        
-
        For example,
        
-
        >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
-
        
-
-
-
        will extract time indices 0,2 and 4, pressure levels
-850, 500 and 200 hPa, all Northern Hemisphere latitudes and Eastern
-Hemisphere longitudes, resulting in a numpy array of shape  (3, 3, 36, 71).
        
-
        >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
-shape of fancy temp slice = (3, 3, 36, 71)
-
        
-
-
-
        Special note for scalar variables: To extract data from a scalar variable
-v with no associated dimensions, use numpy.asarray(v) or v[...].
-The result will be a numpy scalar array.
        
-
        By default, netcdf4-python returns numpy masked arrays with values equal to the
-missing_value or _FillValue variable attributes masked.  The
-set_auto_mask  Dataset and Variable methods
-can be used to disable this feature so that
-numpy arrays are always returned, with the missing values included. Prior to
-version 1.4.0 the default behavior was to only return masked arrays when the
-requested slice contained missing values.  This behavior can be recovered
-using the set_always_mask method. If a masked array is
-written to a netCDF variable, the masked elements are filled with the
-value specified by the missing_value attribute.  If the variable has
-no missing_value, the _FillValue is used instead.
        
-
        7) Dealing with time coordinates.
        
-
        Time coordinate values pose a special challenge to netCDF users.  Most
-metadata standards (such as CF) specify that time should be
-measure relative to a fixed date using a certain calendar, with units
-specified like hours since YY-MM-DD hh:mm:ss.  These units can be
-awkward to deal with, without a utility to convert the values to and
-from calendar dates.  The function called num2date and date2num are
-provided with this package to do just that (starting with version 1.4.0, the
-cftime package must be installed
-separately).  Here's an example of how they
-can be used:
        
-
        >>> # fill in times.
->>> from datetime import datetime, timedelta
->>> from netCDF4 import num2date, date2num
->>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
->>> times[:] = date2num(dates,units=times.units,calendar=times.calendar)
->>> print("time values (in units {}):\n{}".format(times.units, times[:]))
-time values (in units hours since 0001-01-01 00:00:00.0):
-[17533104. 17533116. 17533128. 17533140. 17533152.]
->>> dates = num2date(times[:],units=times.units,calendar=times.calendar)
->>> print("dates corresponding to time values:\n{}".format(dates))
-dates corresponding to time values:
-[real_datetime(2001, 3, 1, 0, 0) real_datetime(2001, 3, 1, 12, 0)
- real_datetime(2001, 3, 2, 0, 0) real_datetime(2001, 3, 2, 12, 0)
- real_datetime(2001, 3, 3, 0, 0)]
-
        
-
-
-
        num2date converts numeric values of time in the specified units
-and calendar to datetime objects, and date2num does the reverse.
-All the calendars currently defined in the
-CF metadata convention are supported.
-A function called date2index is also provided which returns the indices
-of a netCDF time variable corresponding to a sequence of datetime instances.
        
-
        8) Reading data from a multi-file netCDF dataset.
        
-
        If you want to read data from a variable that spans multiple netCDF files,
-you can use the MFDataset class to read the data as if it were
-contained in a single file. Instead of using a single filename to create
-a Dataset instance, create a MFDataset instance with either a list
-of filenames, or a string with a wildcard (which is then converted to
-a sorted list of files using the python glob module).
-Variables in the list of files that share the same unlimited
-dimension are aggregated together, and can be sliced across multiple
-files.  To illustrate this, let's first create a bunch of netCDF files with
-the same variable (with the same unlimited dimension).  The files
-must in be in NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF3_CLASSIC or
-NETCDF4_CLASSIC format (NETCDF4 formatted multi-file
-datasets are not supported).
        
-
        >>> for nf in range(10):
-...     with Dataset("mftest%s.nc" % nf, "w", format="NETCDF4_CLASSIC") as f:
-...         _ = f.createDimension("x",None)
-...         x = f.createVariable("x","i",("x",))
-...         x[0:10] = numpy.arange(nf*10,10*(nf+1))
-
        
-
-
-
        Now read all the files back in at once with MFDataset
        
-
        >>> from netCDF4 import MFDataset
->>> f = MFDataset("mftest*nc")
->>> print(f.variables["x"][:])
-[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
- 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
- 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71
- 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
- 96 97 98 99]
-
        
-
-
-
        Note that MFDataset can only be used to read, not write, multi-file
-datasets.
        
-
        9) Efficient compression of netCDF variables.
        
-
        Data stored in netCDF 4 Variable objects can be compressed and
-decompressed on the fly. The parameters for the compression are
-determined by the zlib, complevel and shuffle keyword arguments
-to the createVariable method. To turn on
-compression, set zlib=True.  The complevel keyword regulates the
-speed and efficiency of the compression (1 being fastest, but lowest
-compression ratio, 9 being slowest but best compression ratio). The
-default value of complevel is 4. Setting shuffle=False will turn
-off the HDF5 shuffle filter, which de-interlaces a block of data before
-compression by reordering the bytes.  The shuffle filter can
-significantly improve compression ratios, and is on by default.  Setting
-fletcher32 keyword argument to
-createVariable to True (it's False by
-default) enables the Fletcher32 checksum algorithm for error detection.
-It's also possible to set the HDF5 chunking parameters and endian-ness
-of the binary data stored in the HDF5 file with the chunksizes
-and endian keyword arguments to
-createVariable.  These keyword arguments only
-are relevant for NETCDF4 and NETCDF4_CLASSIC files (where the
-underlying file format is HDF5) and are silently ignored if the file
-format is NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
        
-
        If your data only has a certain number of digits of precision (say for
-example, it is temperature data that was measured with a precision of
-0.1 degrees), you can dramatically improve zlib compression by
-quantizing (or truncating) the data using the least_significant_digit
-keyword argument to createVariable. The least
-significant digit is the power of ten of the smallest decimal place in
-the data that is a reliable value. For example if the data has a
-precision of 0.1, then setting least_significant_digit=1 will cause
-data the data to be quantized using numpy.around(scale*data)/scale, where
-scale = 2**bits, and bits is determined so that a precision of 0.1 is
-retained (in this case bits=4).  Effectively, this makes the compression
-'lossy' instead of 'lossless', that is some precision in the data is
-sacrificed for the sake of disk space.
        
-
        In our example, try replacing the line
        
-
        >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
-
        
-
-
-
        with
        
-
        >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True)
-
        
-
-
-
        and then
        
-
        >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,least_significant_digit=3)
-
        
-
-
-
        and see how much smaller the resulting files are.
        
-
        10) Beyond homogeneous arrays of a fixed type - compound data types.
        
-
        Compound data types map directly to numpy structured (a.k.a 'record')
-arrays.  Structured arrays are akin to C structs, or derived types
-in Fortran. They allow for the construction of table-like structures
-composed of combinations of other data types, including other
-compound types. Compound types might be useful for representing multiple
-parameter values at each point on a grid, or at each time and space
-location for scattered (point) data. You can then access all the
-information for a point by reading one variable, instead of reading
-different parameters from different variables.  Compound data types
-are created from the corresponding numpy data type using the
-createCompoundType method of a Dataset or Group instance.
-Since there is no native complex data type in netcdf, compound types are handy
-for storing numpy complex arrays.  Here's an example:
        
-
        >>> f = Dataset("complex.nc","w")
->>> size = 3 # length of 1-d complex array
->>> # create sample complex data.
->>> datac = numpy.exp(1j*(1.+numpy.linspace(0, numpy.pi, size)))
->>> # create complex128 compound data type.
->>> complex128 = numpy.dtype([("real",numpy.float64),("imag",numpy.float64)])
->>> complex128_t = f.createCompoundType(complex128,"complex128")
->>> # create a variable with this data type, write some data to it.
->>> x_dim = f.createDimension("x_dim",None)
->>> v = f.createVariable("cmplx_var",complex128_t,"x_dim")
->>> data = numpy.empty(size,complex128) # numpy structured array
->>> data["real"] = datac.real; data["imag"] = datac.imag
->>> v[:] = data # write numpy structured array to netcdf compound var
->>> # close and reopen the file, check the contents.
->>> f.close(); f = Dataset("complex.nc")
->>> v = f.variables["cmplx_var"]
->>> datain = v[:] # read in all the data into a numpy structured array
->>> # create an empty numpy complex array
->>> datac2 = numpy.empty(datain.shape,numpy.complex128)
->>> # .. fill it with contents of structured array.
->>> datac2.real = datain["real"]; datac2.imag = datain["imag"]
->>> print('{}: {}'.format(datac.dtype, datac)) # original data
-complex128: [ 0.54030231+0.84147098j -0.84147098+0.54030231j -0.54030231-0.84147098j]
->>>
->>> print('{}: {}'.format(datac2.dtype, datac2)) # data from file
-complex128: [ 0.54030231+0.84147098j -0.84147098+0.54030231j -0.54030231-0.84147098j]
-
        
-
-
-
        Compound types can be nested, but you must create the 'inner'
-ones first. All possible numpy structured arrays cannot be
-represented as Compound variables - an error message will be
-raise if you try to create one that is not supported.
-All of the compound types defined for a Dataset or Group are stored
-in a Python dictionary, just like variables and dimensions. As always, printing
-objects gives useful summary information in an interactive session:
        
-
        >>> print(f)
-<class 'netCDF4._netCDF4.Dataset'>
-root group (NETCDF4 data model, file format HDF5):
-    dimensions(sizes): x_dim(3)
-    variables(dimensions): {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True} cmplx_var(x_dim)
-    groups: 
->>> print(f.variables["cmplx_var"])
-<class 'netCDF4._netCDF4.Variable'>
-compound cmplx_var(x_dim)
-compound data type: {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}
-unlimited dimensions: x_dim
-current shape = (3,)
->>> print(f.cmptypes)
-{'complex128': <class 'netCDF4._netCDF4.CompoundType'>: name = 'complex128', numpy dtype = {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}}
->>> print(f.cmptypes["complex128"])
-<class 'netCDF4._netCDF4.CompoundType'>: name = 'complex128', numpy dtype = {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}
-
        
-
-
-
        11) Variable-length (vlen) data types.
        
-
        NetCDF 4 has support for variable-length or "ragged" arrays.  These are arrays
-of variable length sequences having the same type. To create a variable-length
-data type, use the createVLType method
-method of a Dataset or Group instance.
        
-
        >>> f = Dataset("tst_vlen.nc","w")
->>> vlen_t = f.createVLType(numpy.int32, "phony_vlen")
-
        
-
-
-
        The numpy datatype of the variable-length sequences and the name of the
-new datatype must be specified. Any of the primitive datatypes can be
-used (signed and unsigned integers, 32 and 64 bit floats, and characters),
-but compound data types cannot.
-A new variable can then be created using this datatype.
        
-
        >>> x = f.createDimension("x",3)
->>> y = f.createDimension("y",4)
->>> vlvar = f.createVariable("phony_vlen_var", vlen_t, ("y","x"))
-
        
-
-
-
        Since there is no native vlen datatype in numpy, vlen arrays are represented
-in python as object arrays (arrays of dtype object). These are arrays whose
-elements are Python object pointers, and can contain any type of python object.
-For this application, they must contain 1-D numpy arrays all of the same type
-but of varying length.
-In this case, they contain 1-D numpy int32 arrays of random length between
-1 and 10.
        
-
        >>> import random
->>> random.seed(54321)
->>> data = numpy.empty(len(y)*len(x),object)
->>> for n in range(len(y)*len(x)):
-...     data[n] = numpy.arange(random.randint(1,10),dtype="int32")+1
->>> data = numpy.reshape(data,(len(y),len(x)))
->>> vlvar[:] = data
->>> print("vlen variable =\n{}".format(vlvar[:]))
-vlen variable =
-[[array([1, 2, 3, 4, 5, 6, 7, 8], dtype=int32) array([1, 2], dtype=int32)
-  array([1, 2, 3, 4], dtype=int32)]
- [array([1, 2, 3], dtype=int32)
-  array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)
-  array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)]
- [array([1, 2, 3, 4, 5, 6, 7], dtype=int32) array([1, 2, 3], dtype=int32)
-  array([1, 2, 3, 4, 5, 6], dtype=int32)]
- [array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)
-  array([1, 2, 3, 4, 5], dtype=int32) array([1, 2], dtype=int32)]]
->>> print(f)
-<class 'netCDF4._netCDF4.Dataset'>
-root group (NETCDF4 data model, file format HDF5):
-    dimensions(sizes): x(3), y(4)
-    variables(dimensions): int32 phony_vlen_var(y,x)
-    groups: 
->>> print(f.variables["phony_vlen_var"])
-<class 'netCDF4._netCDF4.Variable'>
-vlen phony_vlen_var(y, x)
-vlen data type: int32
-unlimited dimensions: 
-current shape = (4, 3)
->>> print(f.vltypes["phony_vlen"])
-<class 'netCDF4._netCDF4.VLType'>: name = 'phony_vlen', numpy dtype = int32
-
        
-
-
-
        Numpy object arrays containing python strings can also be written as vlen
-variables,  For vlen strings, you don't need to create a vlen data type.
-Instead, simply use the python str builtin (or a numpy string datatype
-with fixed length greater than 1) when calling the
-createVariable method.
        
-
        >>> z = f.createDimension("z",10)
->>> strvar = f.createVariable("strvar", str, "z")
-
        
-
-
-
        In this example, an object array is filled with random python strings with
-random lengths between 2 and 12 characters, and the data in the object
-array is assigned to the vlen string variable.
        
-
        >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
->>> data = numpy.empty(10,"O")
->>> for n in range(10):
-...     stringlen = random.randint(2,12)
-...     data[n] = "".join([random.choice(chars) for i in range(stringlen)])
->>> strvar[:] = data
->>> print("variable-length string variable:\n{}".format(strvar[:]))
-variable-length string variable:
-['Lh' '25F8wBbMI' '53rmM' 'vvjnb3t63ao' 'qjRBQk6w' 'aJh' 'QF'
- 'jtIJbJACaQk4' '3Z5' 'bftIIq']
->>> print(f)
-<class 'netCDF4._netCDF4.Dataset'>
-root group (NETCDF4 data model, file format HDF5):
-    dimensions(sizes): x(3), y(4), z(10)
-    variables(dimensions): int32 phony_vlen_var(y,x), <class 'str'> strvar(z)
-    groups: 
->>> print(f.variables["strvar"])
-<class 'netCDF4._netCDF4.Variable'>
-vlen strvar(z)
-vlen data type: <class 'str'>
-unlimited dimensions: 
-current shape = (10,)
-
        
-
-
-
        It is also possible to set contents of vlen string variables with numpy arrays
-of any string or unicode data type. Note, however, that accessing the contents
-of such variables will always return numpy arrays with dtype object.
        
-
        12) Enum data type.
        
-
        netCDF4 has an enumerated data type, which is an integer datatype that is
-restricted to certain named values. Since Enums don't map directly to
-a numpy data type, they are read and written as integer arrays.
        
-
        Here's an example of using an Enum type to hold cloud type data.
-The base integer data type and a python dictionary describing the allowed
-values and their names are used to define an Enum data type using
-createEnumType.
        
-
        >>> nc = Dataset('clouds.nc','w')
->>> # python dict with allowed values and their names.
->>> enum_dict = {'Altocumulus': 7, 'Missing': 255,
-... 'Stratus': 2, 'Clear': 0,
-... 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5,
-... 'Cumulonimbus': 1, 'Stratocumulus': 3}
->>> # create the Enum type called 'cloud_t'.
->>> cloud_type = nc.createEnumType(numpy.uint8,'cloud_t',enum_dict)
->>> print(cloud_type)
-<class 'netCDF4._netCDF4.EnumType'>: name = 'cloud_t', numpy dtype = uint8, fields/values ={'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, 'Stratocumulus': 3}
-
        
-
-
-
        A new variable can be created in the usual way using this data type.
-Integer data is written to the variable that represents the named
-cloud types in enum_dict. A ValueError will be raised if an attempt
-is made to write an integer value not associated with one of the
-specified names.
        
-
        >>> time = nc.createDimension('time',None)
->>> # create a 1d variable of type 'cloud_type'.
->>> # The fill_value is set to the 'Missing' named value.
->>> cloud_var = nc.createVariable('primary_cloud',cloud_type,'time',
-...                               fill_value=enum_dict['Missing'])
->>> # write some data to the variable.
->>> cloud_var[:] = [enum_dict[k] for k in ['Clear', 'Stratus', 'Cumulus',
-...                                        'Missing', 'Cumulonimbus']]
->>> nc.close()
->>> # reopen the file, read the data.
->>> nc = Dataset('clouds.nc')
->>> cloud_var = nc.variables['primary_cloud']
->>> print(cloud_var)
-<class 'netCDF4._netCDF4.Variable'>
-enum primary_cloud(time)
-    _FillValue: 255
-enum data type: uint8
-unlimited dimensions: time
-current shape = (5,)
->>> print(cloud_var.datatype.enum_dict)
-{'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, 'Stratocumulus': 3}
->>> print(cloud_var[:])
-[0 2 4 -- 1]
->>> nc.close()
-
        
-
-
-
        13) Parallel IO.
        
-
        If MPI parallel enabled versions of netcdf and hdf5 or pnetcdf are detected,
-and mpi4py is installed, netcdf4-python will
-be built with parallel IO capabilities enabled. Parallel IO of NETCDF4 or 
-NETCDF4_CLASSIC formatted files is only available if the MPI parallel HDF5
-library is available. Parallel IO of classic netcdf-3 file formats is only
-available if the PnetCDF library is
-available. To use parallel IO, your program must be running in an MPI
-environment using mpi4py.
        
-
        >>> from mpi4py import MPI
->>> import numpy as np
->>> from netCDF4 import Dataset
->>> rank = MPI.COMM_WORLD.rank  # The process ID (integer 0-3 for 4-process run)
-
        
-
-
-
        To run an MPI-based parallel program like this, you must use mpiexec to launch several
-parallel instances of Python (for example, using mpiexec -np 4 python mpi_example.py).
-The parallel features of netcdf4-python are mostly transparent -
-when a new dataset is created or an existing dataset is opened,
-use the parallel keyword to enable parallel access.
        
-
        >>> nc = Dataset('parallel_test.nc','w',parallel=True)
-
        
-
-
-
        The optional comm keyword may be used to specify a particular
-MPI communicator (MPI_COMM_WORLD is used by default).  Each process (or rank)
-can now write to the file indepedently.  In this example the process rank is
-written to a different variable index on each task
        
-
        >>> d = nc.createDimension('dim',4)
->>> v = nc.createVariable('var', np.int, 'dim')
->>> v[rank] = rank
->>> nc.close()
-
-% ncdump parallel_test.nc
-netcdf parallel_test {
-dimensions:
-    dim = 4 ;
-variables:
-    int64 var(dim) ;
-data:
-
-    var = 0, 1, 2, 3 ;
-}
-
        
-
-
-
        There are two types of parallel IO, independent (the default) and collective.
-Independent IO means that each process can do IO independently. It should not
-depend on or be affected by other processes. Collective IO is a way of doing
-IO defined in the MPI-IO standard; unlike independent IO, all processes must
-participate in doing IO. To toggle back and forth between
-the two types of IO, use the set_collective
-Variablemethod. All metadata
-operations (such as creation of groups, types, variables, dimensions, or attributes)
-are collective.  There are a couple of important limitations of parallel IO:
        
-
          
-
        • parallel IO for NETCDF4 or NETCDF4_CLASSIC formatted files is only available
-   if the netcdf library was compiled with MPI enabled HDF5.
          • 
-
        • parallel IO for all classic netcdf-3 file formats is only available if the
-   netcdf library was compiled with PnetCDF.
          • 
-
        • If a variable has an unlimited dimension, appending data must be done in collective mode.
-   If the write is done in independent mode, the operation will fail with a
-   a generic "HDF Error".
          • 
-
        • You cannot write compressed data in parallel (although
-   you can read it).
          • 
-
        • You cannot use variable-length (VLEN) data types.
          • 
-
        
-
        14) Dealing with strings.
        
-
        The most flexible way to store arrays of strings is with the
-Variable-length (vlen) string data type. However, this requires
-the use of the NETCDF4 data model, and the vlen type does not map very well
-numpy arrays (you have to use numpy arrays of dtype=object, which are arrays of
-arbitrary python objects). numpy does have a fixed-width string array
-data type, but unfortunately the netCDF data model does not.
-Instead fixed-width byte strings are typically stored as arrays of 8-bit
-characters.
-To perform the conversion to and from character arrays to fixed-width numpy string arrays, the
-following convention is followed by the python interface.
-If the _Encoding special attribute is set for a character array
-(dtype S1) variable, the chartostring utility function is used to convert the array of
-characters to an array of strings with one less dimension (the last dimension is
-interpreted as the length of each string) when reading the data. The character
-set (usually ascii) is specified by the _Encoding attribute. If _Encoding
-is 'none' or 'bytes', then the character array is converted to a numpy
-fixed-width byte string array (dtype S#), otherwise a numpy unicode (dtype
-U#) array is created.  When writing the data,
-stringtochar is used to convert the numpy string array to an array of
-characters with one more dimension. For example,
        
-
        >>> from netCDF4 import stringtochar
->>> nc = Dataset('stringtest.nc','w',format='NETCDF4_CLASSIC')
->>> _ = nc.createDimension('nchars',3)
->>> _ = nc.createDimension('nstrings',None)
->>> v = nc.createVariable('strings','S1',('nstrings','nchars'))
->>> datain = numpy.array(['foo','bar'],dtype='S3')
->>> v[:] = stringtochar(datain) # manual conversion to char array
->>> print(v[:]) # data returned as char array
-[[b'f' b'o' b'o']
- [b'b' b'a' b'r']]
->>> v._Encoding = 'ascii' # this enables automatic conversion
->>> v[:] = datain # conversion to char array done internally
->>> print(v[:])  # data returned in numpy string array
-['foo' 'bar']
->>> nc.close()
-
        
-
-
-
        Even if the _Encoding attribute is set, the automatic conversion of char
-arrays to/from string arrays can be disabled with
-set_auto_chartostring.
        
-
        A similar situation is often encountered with numpy structured arrays with subdtypes
-containing fixed-wdith byte strings (dtype=S#). Since there is no native fixed-length string
-netCDF datatype, these numpy structure arrays are mapped onto netCDF compound
-types with character array elements.  In this case the string <-> char array
-conversion is handled automatically (without the need to set the _Encoding
-attribute) using numpy
-views.
-The structured array dtype (including the string elements) can even be used to
-define the compound data type - the string dtype will be converted to
-character array dtype under the hood when creating the netcdf compound type.
-Here's an example:
        
-
        >>> nc = Dataset('compoundstring_example.nc','w')
->>> dtype = numpy.dtype([('observation', 'f4'),
-...                      ('station_name','S10')])
->>> station_data_t = nc.createCompoundType(dtype,'station_data')
->>> _ = nc.createDimension('station',None)
->>> statdat = nc.createVariable('station_obs', station_data_t, ('station',))
->>> data = numpy.empty(2,dtype)
->>> data['observation'][:] = (123.,3.14)
->>> data['station_name'][:] = ('Boulder','New York')
->>> print(statdat.dtype) # strings actually stored as character arrays
-{'names':['observation','station_name'], 'formats':['<f4',('S1', (10,))], 'offsets':[0,4], 'itemsize':16, 'aligned':True}
->>> statdat[:] = data # strings converted to character arrays internally
->>> print(statdat[:])  # character arrays converted back to strings
-[(123.  , b'Boulder') (  3.14, b'New York')]
->>> print(statdat[:].dtype)
-{'names':['observation','station_name'], 'formats':['<f4','S10'], 'offsets':[0,4], 'itemsize':16, 'aligned':True}
->>> statdat.set_auto_chartostring(False) # turn off auto-conversion
->>> statdat[:] = data.view(dtype=[('observation', 'f4'),('station_name','S1',10)])
->>> print(statdat[:])  # now structured array with char array subtype is returned
-[(123.  , [b'B', b'o', b'u', b'l', b'd', b'e', b'r', b'', b'', b''])
- (  3.14, [b'N', b'e', b'w', b' ', b'Y', b'o', b'r', b'k', b'', b''])]
->>> nc.close()
-
        
-
-
-
        Note that there is currently no support for mapping numpy structured arrays with
-unicode elements (dtype U#) onto netCDF compound types, nor is there support
-for netCDF compound types with vlen string components.
        
-
        15) In-memory (diskless) Datasets.
        
-
        You can create netCDF Datasets whose content is held in memory
-instead of in a disk file.  There are two ways to do this.  If you
-don't need access to the memory buffer containing the Dataset from
-within python, the best way is to use the diskless=True keyword
-argument when creating the Dataset.  If you want to save the Dataset
-to disk when you close it, also set persist=True.  If you want to
-create a new read-only Dataset from an existing python memory buffer, use the
-memory keyword argument to pass the memory buffer when creating the Dataset.
-If you want to create a new in-memory Dataset, and then access the memory buffer
-directly from Python, use the memory keyword argument to specify the
-estimated size of the Dataset in bytes when creating the Dataset with
-mode='w'.  Then, the Dataset.close method will return a python memoryview
-object representing the Dataset. Below are examples illustrating both
-approaches.
        
-
        >>> # create a diskless (in-memory) Dataset,
->>> # and persist the file to disk when it is closed.
->>> nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
->>> d = nc.createDimension('x',None)
->>> v = nc.createVariable('v',numpy.int32,'x')
->>> v[0:5] = numpy.arange(5)
->>> print(nc)
-<class 'netCDF4._netCDF4.Dataset'>
-root group (NETCDF4 data model, file format HDF5):
-    dimensions(sizes): x(5)
-    variables(dimensions): int32 v(x)
-    groups: 
->>> print(nc['v'][:])
-[0 1 2 3 4]
->>> nc.close() # file saved to disk
->>> # create an in-memory dataset from an existing python
->>> # python memory buffer.
->>> # read the newly created netcdf file into a python
->>> # bytes object.
->>> with open('diskless_example.nc', 'rb') as f:
-...     nc_bytes = f.read()
->>> # create a netCDF in-memory dataset from the bytes object.
->>> nc = Dataset('inmemory.nc', memory=nc_bytes)
->>> print(nc)
-<class 'netCDF4._netCDF4.Dataset'>
-root group (NETCDF4 data model, file format HDF5):
-    dimensions(sizes): x(5)
-    variables(dimensions): int32 v(x)
-    groups: 
->>> print(nc['v'][:])
-[0 1 2 3 4]
->>> nc.close()
->>> # create an in-memory Dataset and retrieve memory buffer
->>> # estimated size is 1028 bytes - this is actually only
->>> # used if format is NETCDF3
->>> # (ignored for NETCDF4/HDF5 files).
->>> nc = Dataset('inmemory.nc', mode='w',memory=1028)
->>> d = nc.createDimension('x',None)
->>> v = nc.createVariable('v',numpy.int32,'x')
->>> v[0:5] = numpy.arange(5)
->>> nc_buf = nc.close() # close returns memoryview
->>> print(type(nc_buf))
-<class 'memoryview'>
->>> # save nc_buf to disk, read it back in and check.
->>> with open('inmemory.nc', 'wb') as f:
-...     f.write(nc_buf)
->>> nc = Dataset('inmemory.nc')
->>> print(nc)
-<class 'netCDF4._netCDF4.Dataset'>
-root group (NETCDF4 data model, file format HDF5):
-    dimensions(sizes): x(5)
-    variables(dimensions): int32 v(x)
-    groups:
->>> print(nc['v'][:])
-[0 1 2 3 4]
->>> nc.close()
-
        
-
-
-
        All of the code in this tutorial is available in examples/tutorial.py, except
-the parallel IO example, which is in examples/mpi_example.py.
-Unit tests are in the test directory.
        
-
        contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
        
-
        copyright: 2008 by Jeffrey Whitaker.
        
-
        license: Permission to use, copy, modify, and distribute this software and
-its documentation for any purpose and without fee is hereby granted,
-provided that the above copyright notice appear in all copies and that
-both the copyright notice and this permission notice appear in
-supporting documentation.
-THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE,
-INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO
-EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, INDIRECT OR
-CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF
-USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR
-OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR
-PERFORMANCE OF THIS SOFTWARE.
        
-
        
-  
-
-  
        
-
-  
        
-
-    
        Functions
        
-      
-  
        
-    
        
-    
        def chartostring(
        b,encoding='utf-8')
        
-    
        
-    
-
-    
-  
-    
        convert a character array to a string array with one less dimension.
        
-
        b:  Input character array (numpy datatype 'S1' or 'U1').
-Will be converted to a array of strings, where each string has a fixed
-length of b.shape[-1] characters.
        
-
        optional kwarg encoding can be used to specify character encoding (default
-utf-8). If encoding is 'none' or 'bytes', a numpy.string_ btye array is
-returned.
        
-
        returns a numpy string array with datatype 'UN' (or 'SN') and shape
-b.shape[:-1] where where N=b.shape[-1].
        
-  
        
-
        
-
-  
        
-  
-      
-  
        
-    
        
-    
        def date2index(
        ...)
        
-    
        
-    
-
-    
-  
-    
        date2index(dates, nctime, calendar=None, select='exact')
        
-
        Return indices of a netCDF time variable corresponding to the given dates.
        
-
        dates: A datetime object or a sequence of datetime objects.
-The datetime objects should not include a time-zone offset.
        
-
        nctime: A netCDF time variable object. The nctime object must have a
-units attribute.
        
-
        calendar: describes the calendar used in the time calculations.
-All the values currently defined in the
-CF metadata convention
-Valid calendars 'standard', 'gregorian', 'proleptic_gregorian'
-'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'.
-Default is 'standard', which is a mixed Julian/Gregorian calendar.
-If calendar is None, its value is given by nctime.calendar or
-standard if no such attribute exists.
        
-
        select: 'exact', 'before', 'after', 'nearest'
-The index selection method. exact will return the indices perfectly
-matching the dates given. before and after will return the indices
-corresponding to the dates just before or just after the given dates if
-an exact match cannot be found. nearest will return the indices that
-correspond to the closest dates.
        
-
        returns an index (indices) of the netCDF time variable corresponding
-to the given datetime object(s).
        
-  
        
-
        
-
-  
        
-  
-      
-  
        
-    
        
-    
        def date2num(
        ...)
        
-    
        
-    
-
-    
-  
-    
        date2num(dates, units, calendar=None)
        
-
        Return numeric time values given datetime objects. The units
-of the numeric time values are described by the units argument
-and the calendar keyword. The datetime objects must
-be in UTC with no time-zone offset.  If there is a
-time-zone offset in units, it will be applied to the
-returned numeric values.
        
-
        dates: A datetime object or a sequence of datetime objects.
-The datetime objects should not include a time-zone offset. They
-can be either native python datetime instances (which use
-the proleptic gregorian calendar) or cftime.datetime instances.
        
-
        units: a string of the form 
-describing the time units.  can be days, hours, minutes,
-seconds, milliseconds or microseconds.  is the time
-origin. months_since is allowed only for the 360_day calendar.
        
-
        calendar: describes the calendar to be used in the time calculations.
-All the values currently defined in the
-CF metadata convention
-Valid calendars 'standard', 'gregorian', 'proleptic_gregorian'
-'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'.
-Default is None which means the calendar associated with the rist
-input datetime instance will be used.
        
-
        returns a numeric time value, or an array of numeric time values
-with approximately 1 microsecond accuracy.
        
-  
        
-
        
-
-  
        
-  
-      
-  
        
-    
        
-    
        def get_chunk_cache(
        )
        
-    
        
-    
-
-    
-  
-    
        return current netCDF chunk cache information in a tuple (size,nelems,preemption).
-See netcdf C library documentation for nc_get_chunk_cache for
-details. Values can be reset with set_chunk_cache.
        
-  
        
-
        
-
-  
        
-  
-      
-  
        
-    
        
-    
        def getlibversion(
        )
        
-    
        
-    
-
-    
-  
-    
        returns a string describing the version of the netcdf library
-used to build the module, and when it was built.
        
-  
        
-
        
-
-  
        
-  
-      
-  
        
-    
        
-    
        def num2date(
        ...)
        
-    
        
-    
-
-    
-  
-    
        num2date(times, units, calendar='standard', only_use_cftime_datetimes=True, only_use_python_datetimes=False)
        
-
        Return datetime objects given numeric time values. The units
-of the numeric time values are described by the units argument
-and the calendar keyword. The returned datetime objects represent
-UTC with no time-zone offset, even if the specified
-units contain a time-zone offset.
        
-
        times: numeric time values.
        
-
        units: a string of the form 
-describing the time units.  can be days, hours, minutes,
-seconds, milliseconds or microseconds.  is the time
-origin. months_since is allowed only for the 360_day calendar.
        
-
        calendar: describes the calendar used in the time calculations.
-All the values currently defined in the
-CF metadata convention
-Valid calendars 'standard', 'gregorian', 'proleptic_gregorian'
-'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'.
-Default is 'standard', which is a mixed Julian/Gregorian calendar.
        
-
        only_use_cftime_datetimes: if False, python datetime.datetime
-objects are returned from num2date where possible; if True dates which
-subclass cftime.datetime are returned for all calendars. Default True.
        
-
        only_use_python_datetimes: always return python datetime.datetime
-objects and raise an error if this is not possible. Ignored unless
-only_use_cftime_datetimes=False. Default False.
        
-
        returns a datetime instance, or an array of datetime instances with
-microsecond accuracy, if possible.
        
-
        Note: If only_use_cftime_datetimes=False and
-use_only_python_datetimes=False, the datetime instances
-returned are 'real' python datetime
-objects if calendar='proleptic_gregorian', or
-calendar='standard' or 'gregorian'
-and the date is after the breakpoint between the Julian and
-Gregorian calendars (1582-10-15). Otherwise, they are ctime.datetime
-objects which support some but not all the methods of native python
-datetime objects. The datetime instances
-do not contain a time-zone offset, even if the specified units
-contains one.
        
-  
        
-
        
-
-  
        
-  
-      
-  
        
-    
        
-    
        def set_chunk_cache(
        self,size=None,nelems=None,preemption=None)
        
-    
        
-    
-
-    
-  
-    
        change netCDF4 chunk cache settings.
-See netcdf C library documentation for nc_set_chunk_cache for
-details.
        
-  
        
-
        
-
-  
        
-  
-      
-  
        
-    
        
-    
        def stringtoarr(
        a, NUMCHARS,dtype='S')
        
-    
        
-    
-
-    
-  
-    
        convert a string to a character array of length NUMCHARS
        
-
        a:  Input python string.
        
-
        NUMCHARS:  number of characters used to represent string
-(if len(a) < NUMCHARS, it will be padded on the right with blanks).
        
-
        dtype:  type of numpy array to return.  Default is 'S', which
-means an array of dtype 'S1' will be returned.  If dtype='U', a
-unicode array (dtype = 'U1') will be returned.
        
-
        returns a rank 1 numpy character array of length NUMCHARS with datatype 'S1'
-(default) or 'U1' (if dtype='U')
        
-  
        
-
        
-
-  
        
-  
-      
-  
        
-    
        
-    
        def stringtochar(
        a,encoding='utf-8')
        
-    
        
-    
-
-    
-  
-    
        convert a string array to a character array with one extra dimension
        
-
        a:  Input numpy string array with numpy datatype 'SN' or 'UN', where N
-is the number of characters in each string.  Will be converted to
-an array of characters (datatype 'S1' or 'U1') of shape a.shape + (N,).
        
-
        optional kwarg encoding can be used to specify character encoding (default
-utf-8). If encoding is 'none' or 'bytes', a numpy.string_ the input array
-is treated a raw byte strings (numpy.string_).
        
-
        returns a numpy character array with datatype 'S1' or 'U1'
-and shape a.shape + (N,), where N is the length of each string in a.
        
-  
        
-
        
-
-  
        
-  
-
-    
        Classes
        
-      
-      
        
-      
        class CompoundType
        
-      
-  
-    
        A CompoundType instance is used to describe a compound data
-type, and can be passed to the the createVariable method of
-a Dataset or Group instance.
-Compound data types map to numpy structured arrays.
-See __init__ for more details.
        
-
        The instance variables dtype and name should not be modified by
-the user.
        
-  
        
-
        
-
-
-      
        
-          
        Ancestors (in MRO)
        
-          
-          
        Class variables
        
-            
        
-            
        var dtype
        
-            
-
-            
-  
-    
        A numpy dtype object describing the compound data type.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var dtype_view
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var name
        
-            
-
-            
-  
-    
        String name.
        
-  
        
-
        
-
-            
        
-          
        Static methods
        
-            
-  
        
-    
        
-    
        def __init__(
        group, datatype, datatype_name)
        
-    
        
-    
-
-    
-  
-    
        CompoundType constructor.
        
-
        group: Group instance to associate with the compound datatype.
        
-
        datatype: A numpy dtype object describing a structured (a.k.a record)
-array.  Can be composed of homogeneous numeric or character data types, or
-other structured array data types.
        
-
        datatype_name: a Python string containing a description of the
-compound data type.
        
-
        Note 1: When creating nested compound data types,
-the inner compound data types must already be associated with CompoundType
-instances (so create CompoundType instances for the innermost structures
-first).
        
-
        Note 2: CompoundType instances should be created using the
-createCompoundType
-method of a Dataset or Group instance, not using this class directly.
        
-  
        
-
        
-
-  
        
-  
-      
        
-      
        
-      
-      
        
-      
        class Dataset
        
-      
-  
-    
        A netCDF Dataset is a collection of dimensions, groups, variables and
-attributes. Together they describe the meaning of data and relations among
-data fields stored in a netCDF file. See __init__ for more
-details.
        
-
        A list of attribute names corresponding to global netCDF attributes
-defined for the Dataset can be obtained with the
-ncattrs method.
-These attributes can be created by assigning to an attribute of the
-Dataset instance. A dictionary containing all the netCDF attribute
-name/value pairs is provided by the __dict__ attribute of a
-Dataset instance.
        
-
        The following class variables are read-only and should not be
-modified by the user.
        
-
        dimensions: The dimensions dictionary maps the names of
-dimensions defined for the Group or Dataset to instances of the
-Dimension class.
        
-
        variables: The variables dictionary maps the names of variables
-defined for this Dataset or Group to instances of the
-Variable class.
        
-
        groups: The groups dictionary maps the names of groups created for
-this Dataset or Group to instances of the Group class (the
-Dataset class is simply a special case of the Group class which
-describes the root group in the netCDF4 file).
        
-
        cmptypes: The cmptypes dictionary maps the names of
-compound types defined for the Group or Dataset to instances of the
-CompoundType class.
        
-
        vltypes: The vltypes dictionary maps the names of
-variable-length types defined for the Group or Dataset to instances
-of the VLType class.
        
-
        enumtypes: The enumtypes dictionary maps the names of
-Enum types defined for the Group or Dataset to instances
-of the EnumType class.
        
-
        data_model: data_model describes the netCDF
-data model version, one of NETCDF3_CLASSIC, NETCDF4,
-NETCDF4_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
        
-
        file_format: same as data_model, retained for backwards compatibility.
        
-
        disk_format: disk_format describes the underlying
-file format, one of NETCDF3, HDF5, HDF4,
-PNETCDF, DAP2, DAP4 or UNDEFINED. Only available if using
-netcdf C library version >= 4.3.1, otherwise will always return
-UNDEFINED.
        
-
        parent: parent is a reference to the parent
-Group instance. None for the root group or Dataset
-instance.
        
-
        path: path shows the location of the Group in
-the Dataset in a unix directory format (the names of groups in the
-hierarchy separated by backslashes). A Dataset instance is the root
-group, so the path is simply '/'.
        
-
        keepweakref: If True, child Dimension and Variables objects only keep weak
-references to the parent Dataset or Group.
        
-
        _ncstring_attrs__: If True, all text attributes will be written as variable-length
-strings.
        
-  
        
-
        
-
-
-      
        
-          
        Ancestors (in MRO)
        
-          
-          
        Class variables
        
-            
        
-            
        var cmptypes
        
-            
-
-            
-  
-    
        The cmptypes dictionary maps the names of
-compound types defined for the Group or Dataset to instances of the
-CompoundType class.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var data_model
        
-            
-
-            
-  
-    
        data_model describes the netCDF
-data model version, one of NETCDF3_CLASSIC, NETCDF4,
-NETCDF4_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var dimensions
        
-            
-
-            
-  
-    
        The dimensions dictionary maps the names of
-dimensions defined for the Group or Dataset to instances of the
-Dimension class.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var disk_format
        
-            
-
-            
-  
-    
        disk_format describes the underlying
-file format, one of NETCDF3, HDF5, HDF4,
-PNETCDF, DAP2, DAP4 or UNDEFINED. Only available if using
-netcdf C library version >= 4.3.1, otherwise will always return
-UNDEFINED.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var enumtypes
        
-            
-
-            
-  
-    
        The enumtypes dictionary maps the names of
-Enum types defined for the Group or Dataset to instances of the
-EnumType class.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var file_format
        
-            
-
-            
-  
-    
        same as data_model, retained for backwards compatibility.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var groups
        
-            
-
-            
-  
-    
        The groups dictionary maps the names of groups created for
-this Dataset or Group to instances of the Group class (the
-Dataset class is simply a special case of the Group class which
-describes the root group in the netCDF4 file).
        
-  
        
-
        
-
-            
        
-            
        
-            
        var keepweakref
        
-            
-
-            
-  
-    
        If True, child Dimension and Variables objects only keep weak references to
-the parent Dataset or Group.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var name
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var parent
        
-            
-
-            
-  
-    
        parent is a reference to the parent
-Group instance. None for the root group or Dataset instance
        
-  
        
-
        
-
-            
        
-            
        
-            
        var path
        
-            
-
-            
-  
-    
        path shows the location of the Group in
-the Dataset in a unix directory format (the names of groups in the
-hierarchy separated by backslashes). A Dataset instance is the root
-group, so the path is simply '/'.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var variables
        
-            
-
-            
-  
-    
        The variables dictionary maps the names of variables
-defined for this Dataset or Group to instances of the Variable
-class.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var vltypes
        
-            
-
-            
-  
-    
        The vltypes dictionary maps the names of
-variable-length types defined for the Group or Dataset to instances of the
-VLType class.
        
-  
        
-
        
-
-            
        
-          
        Static methods
        
-            
-  
        
-    
        
-    
        def __init__(
        self, filename, mode="r", clobber=True, diskless=False, persist=False, keepweakref=False, memory=None, encoding=None, parallel=False, comm=None, info=None, format='NETCDF4')
        
-    
        
-    
-
-    
-  
-    
        Dataset constructor.
        
-
        filename: Name of netCDF file to hold dataset. Can also
-be a python 3 pathlib instance or the URL of an OpenDAP dataset.  When memory is
-set this is just used to set the filepath().
        
-
        mode: access mode. r means read-only; no data can be
-modified. w means write; a new file is created, an existing file with
-the same name is deleted. a and r+ mean append (in analogy with
-serial files); an existing file is opened for reading and writing.
-Appending s to modes r, w, r+ or a will enable unbuffered shared
-access to NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET or
-NETCDF3_64BIT_DATA formatted files.
-Unbuffered access may be useful even if you don't need shared
-access, since it may be faster for programs that don't access data
-sequentially. This option is ignored for NETCDF4 and NETCDF4_CLASSIC
-formatted files.
        
-
        clobber: if True (default), opening a file with mode='w'
-will clobber an existing file with the same name.  if False, an
-exception will be raised if a file with the same name already exists.
        
-
        format: underlying file format (one of 'NETCDF4',
-'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC', 'NETCDF3_64BIT_OFFSET' or
-'NETCDF3_64BIT_DATA'.
-Only relevant if mode = 'w' (if mode = 'r','a' or 'r+' the file format
-is automatically detected). Default 'NETCDF4', which means the data is
-stored in an HDF5 file, using netCDF 4 API features.  Setting
-format='NETCDF4_CLASSIC' will create an HDF5 file, using only netCDF 3
-compatible API features. netCDF 3 clients must be recompiled and linked
-against the netCDF 4 library to read files in NETCDF4_CLASSIC format.
-'NETCDF3_CLASSIC' is the classic netCDF 3 file format that does not
-handle 2+ Gb files. 'NETCDF3_64BIT_OFFSET' is the 64-bit offset
-version of the netCDF 3 file format, which fully supports 2+ GB files, but
-is only compatible with clients linked against netCDF version 3.6.0 or
-later. 'NETCDF3_64BIT_DATA' is the 64-bit data version of the netCDF 3
-file format, which supports 64-bit dimension sizes plus unsigned and
-64 bit integer data types, but is only compatible with clients linked against
-netCDF version 4.4.0 or later.
        
-
        diskless: If True, create diskless (in-core) file.
-This is a feature added to the C library after the
-netcdf-4.2 release. If you need to access the memory buffer directly,
-use the in-memory feature instead (see memory kwarg).
        
-
        persist: if diskless=True, persist file to disk when closed
-(default False).
        
-
        keepweakref: if True, child Dimension and Variable instances will keep weak
-references to the parent Dataset or Group object.  Default is False, which
-means strong references will be kept.  Having Dimension and Variable instances
-keep a strong reference to the parent Dataset instance, which in turn keeps a
-reference to child Dimension and Variable instances, creates circular references.
-Circular references complicate garbage collection, which may mean increased
-memory usage for programs that create may Dataset instances with lots of
-Variables. It also will result in the Dataset object never being deleted, which
-means it may keep open files alive as well. Setting keepweakref=True allows
-Dataset instances to be garbage collected as soon as they go out of scope, potentially
-reducing memory usage and open file handles.  However, in many cases this is not
-desirable, since the associated Variable instances may still be needed, but are
-rendered unusable when the parent Dataset instance is garbage collected.
        
-
        memory: if not None, create or open an in-memory Dataset.
-If mode = 'r', the memory kwarg must contain a memory buffer object
-(an object that supports the python buffer interface).
-The Dataset will then be created with contents taken from this block of memory.
-If mode = 'w', the memory kwarg should contain the anticipated size
-of the Dataset in bytes (used only for NETCDF3 files).  A memory
-buffer containing a copy of the Dataset is returned by the
-Dataset.close method. Requires netcdf-c version 4.4.1 for mode='r,
-netcdf-c 4.6.2 for mode='w'. To persist the file to disk, the raw
-bytes from the returned buffer can be written into a binary file.
-The Dataset can also be re-opened using this memory buffer.
        
-
        encoding: encoding used to encode filename string into bytes.
-Default is None (sys.getdefaultfileencoding() is used).
        
-
        parallel: open for parallel access using MPI (requires mpi4py and
-parallel-enabled netcdf-c and hdf5 libraries).  Default is False. If
-True, comm and info kwargs may also be specified.
        
-
        comm: MPI_Comm object for parallel access. Default None, which
-means MPI_COMM_WORLD will be used.  Ignored if parallel=False.
        
-
        info: MPI_Info object for parallel access. Default None, which
-means MPI_INFO_NULL will be used.  Ignored if parallel=False.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def close(
        self)
        
-    
        
-    
-
-    
-  
-    
        Close the Dataset.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def createCompoundType(
        self, datatype, datatype_name)
        
-    
        
-    
-
-    
-  
-    
        Creates a new compound data type named datatype_name from the numpy
-dtype object datatype.
        
-
        Note: If the new compound data type contains other compound data types
-(i.e. it is a 'nested' compound type, where not all of the elements
-are homogeneous numeric data types), then the 'inner' compound types must be
-created first.
        
-
        The return value is the CompoundType class instance describing the new
-datatype.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def createDimension(
        self, dimname, size=None)
        
-    
        
-    
-
-    
-  
-    
        Creates a new dimension with the given dimname and size.
        
-
        size must be a positive integer or None, which stands for
-"unlimited" (default is None). Specifying a size of 0 also
-results in an unlimited dimension. The return value is the Dimension
-class instance describing the new dimension.  To determine the current
-maximum size of the dimension, use the len function on the Dimension
-instance. To determine if a dimension is 'unlimited', use the
-isunlimited method of the Dimension instance.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def createEnumType(
        self, datatype, datatype_name, enum_dict)
        
-    
        
-    
-
-    
-  
-    
        Creates a new Enum data type named datatype_name from a numpy
-integer dtype object datatype, and a python dictionary
-defining the enum fields and values.
        
-
        The return value is the EnumType class instance describing the new
-datatype.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def createGroup(
        self, groupname)
        
-    
        
-    
-
-    
-  
-    
        Creates a new Group with the given groupname.
        
-
        If groupname is specified as a path, using forward slashes as in unix to
-separate components, then intermediate groups will be created as necessary
-(analogous to mkdir -p in unix).  For example,
-createGroup('/GroupA/GroupB/GroupC') will create GroupA,
-GroupA/GroupB, and GroupA/GroupB/GroupC, if they don't already exist.
-If the specified path describes a group that already exists, no error is
-raised.
        
-
        The return value is a Group class instance.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def createVLType(
        self, datatype, datatype_name)
        
-    
        
-    
-
-    
-  
-    
        Creates a new VLEN data type named datatype_name from a numpy
-dtype object datatype.
        
-
        The return value is the VLType class instance describing the new
-datatype.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def createVariable(
        self, varname, datatype, dimensions=(), zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, fill_value=None, chunk_cache=None)
        
-    
        
-    
-
-    
-  
-    
        Creates a new variable with the given varname, datatype, and
-dimensions. If dimensions are not given, the variable is assumed to be
-a scalar.
        
-
        If varname is specified as a path, using forward slashes as in unix to
-separate components, then intermediate groups will be created as necessary
-For example, createVariable('/GroupA/GroupB/VarC', float, ('x','y')) will create groups GroupA
-and GroupA/GroupB, plus the variable GroupA/GroupB/VarC, if the preceding
-groups don't already exist.
        
-
        The datatype can be a numpy datatype object, or a string that describes
-a numpy dtype object (like the dtype.str attribute of a numpy array).
-Supported specifiers include: 'S1' or 'c' (NC_CHAR), 'i1' or 'b' or 'B'
-(NC_BYTE), 'u1' (NC_UBYTE), 'i2' or 'h' or 's' (NC_SHORT), 'u2'
-(NC_USHORT), 'i4' or 'i' or 'l' (NC_INT), 'u4' (NC_UINT), 'i8' (NC_INT64),
-'u8' (NC_UINT64), 'f4' or 'f' (NC_FLOAT), 'f8' or 'd' (NC_DOUBLE).
-datatype can also be a CompoundType instance
-(for a structured, or compound array), a VLType instance
-(for a variable-length array), or the python str builtin
-(for a variable-length string array). Numpy string and unicode datatypes with
-length greater than one are aliases for str.
        
-
        Data from netCDF variables is presented to python as numpy arrays with
-the corresponding data type.
        
-
        dimensions must be a tuple containing dimension names (strings) that
-have been defined previously using createDimension. The default value
-is an empty tuple, which means the variable is a scalar.
        
-
        If the optional keyword zlib is True, the data will be compressed in
-the netCDF file using gzip compression (default False).
        
-
        The optional keyword complevel is an integer between 1 and 9 describing
-the level of compression desired (default 4). Ignored if zlib=False.
        
-
        If the optional keyword shuffle is True, the HDF5 shuffle filter
-will be applied before compressing the data (default True).  This
-significantly improves compression. Default is True. Ignored if
-zlib=False.
        
-
        If the optional keyword fletcher32 is True, the Fletcher32 HDF5
-checksum algorithm is activated to detect errors. Default False.
        
-
        If the optional keyword contiguous is True, the variable data is
-stored contiguously on disk.  Default False. Setting to True for
-a variable with an unlimited dimension will trigger an error.
        
-
        The optional keyword chunksizes can be used to manually specify the
-HDF5 chunksizes for each dimension of the variable. A detailed
-discussion of HDF chunking and I/O performance is available
-here.
-Basically, you want the chunk size for each dimension to match as
-closely as possible the size of the data block that users will read
-from the file.  chunksizes cannot be set if contiguous=True.
        
-
        The optional keyword endian can be used to control whether the
-data is stored in little or big endian format on disk. Possible
-values are little, big or native (default). The library
-will automatically handle endian conversions when the data is read,
-but if the data is always going to be read on a computer with the
-opposite format as the one used to create the file, there may be
-some performance advantage to be gained by setting the endian-ness.
        
-
        The zlib, complevel, shuffle, fletcher32, contiguous, chunksizes and endian
-keywords are silently ignored for netCDF 3 files that do not use HDF5.
        
-
        The optional keyword fill_value can be used to override the default
-netCDF _FillValue (the value that the variable gets filled with before
-any data is written to it, defaults given in netCDF4.default_fillvals).
-If fill_value is set to False, then the variable is not pre-filled.
        
-
        If the optional keyword parameter least_significant_digit is
-specified, variable data will be truncated (quantized). In conjunction
-with zlib=True this produces 'lossy', but significantly more
-efficient compression. For example, if least_significant_digit=1,
-data will be quantized using numpy.around(scale*data)/scale, where
-scale = 2**bits, and bits is determined so that a precision of 0.1 is
-retained (in this case bits=4). From the
-PSD metadata conventions:
-"least_significant_digit -- power of ten of the smallest decimal place
-in unpacked data that is a reliable value." Default is None, or no
-quantization, or 'lossless' compression.
        
-
        When creating variables in a NETCDF4 or NETCDF4_CLASSIC formatted file,
-HDF5 creates something called a 'chunk cache' for each variable.  The
-default size of the chunk cache may be large enough to completely fill
-available memory when creating thousands of variables.  The optional
-keyword chunk_cache allows you to reduce (or increase) the size of
-the default chunk cache when creating a variable.  The setting only
-persists as long as the Dataset is open - you can use the set_var_chunk_cache
-method to change it the next time the Dataset is opened.
-Warning - messing with this parameter can seriously degrade performance.
        
-
        The return value is the Variable class instance describing the new
-variable.
        
-
        A list of names corresponding to netCDF variable attributes can be
-obtained with the Variable method ncattrs. A dictionary
-containing all the netCDF attribute name/value pairs is provided by
-the __dict__ attribute of a Variable instance.
        
-
        Variable instances behave much like array objects. Data can be
-assigned to or retrieved from a variable with indexing and slicing
-operations on the Variable instance. A Variable instance has six
-Dataset standard attributes: dimensions, dtype, shape, ndim, name and
-least_significant_digit. Application programs should never modify
-these attributes. The dimensions attribute is a tuple containing the
-names of the dimensions associated with this variable. The dtype
-attribute is a string describing the variable's data type (i4, f8,
-S1, etc). The shape attribute is a tuple describing the current
-sizes of all the variable's dimensions. The name attribute is a
-string containing the name of the Variable instance.
-The least_significant_digit
-attributes describes the power of ten of the smallest decimal place in
-the data the contains a reliable value.  assigned to the Variable
-instance. If None, the data is not truncated. The ndim attribute
-is the number of variable dimensions.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def delncattr(
        self,name,value)
        
-    
        
-    
-
-    
-  
-    
        delete a netCDF dataset or group attribute.  Use if you need to delete a
-netCDF attribute with the same name as one of the reserved python
-attributes.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def filepath(
        self,encoding=None)
        
-    
        
-    
-
-    
-  
-    
        Get the file system path (or the opendap URL) which was used to
-open/create the Dataset. Requires netcdf >= 4.1.2.  The path
-is decoded into a string using sys.getfilesystemencoding() by default, this can be
-changed using the encoding kwarg.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def get_variables_by_attributes(
        ...)
        
-    
        
-    
-
-    
-  
-    
        Returns a list of variables that match specific conditions.
        
-
        Can pass in key=value parameters and variables are returned that
-contain all of the matches. For example,
        
-
        >>> # Get variables with x-axis attribute.
->>> vs = nc.get_variables_by_attributes(axis='X')
->>> # Get variables with matching "standard_name" attribute
->>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
-
        
-
-
-
        Can pass in key=callable parameter and variables are returned if the
-callable returns True.  The callable should accept a single parameter,
-the attribute value.  None is given as the attribute value when the
-attribute does not exist on the variable. For example,
        
-
        >>> # Get Axis variables
->>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
->>> # Get variables that don't have an "axis" attribute
->>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
->>> # Get variables that have a "grid_mapping" attribute
->>> vs = nc.get_variables_by_attributes(grid_mapping=lambda v: v is not None)
-
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def getncattr(
        self,name)
        
-    
        
-    
-
-    
-  
-    
        retrieve a netCDF dataset or group attribute.
-Use if you need to get a netCDF attribute with the same
-name as one of the reserved python attributes.
        
-
        option kwarg encoding can be used to specify the
-character encoding of a string attribute (default is utf-8).
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def isopen(
        ...)
        
-    
        
-    
-
-    
-  
-    
        is the Dataset open or closed?
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def ncattrs(
        self)
        
-    
        
-    
-
-    
-  
-    
        return netCDF global attribute names for this Dataset or Group in a list.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def renameAttribute(
        self, oldname, newname)
        
-    
        
-    
-
-    
-  
-    
        rename a Dataset or Group attribute named oldname to newname.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def renameDimension(
        self, oldname, newname)
        
-    
        
-    
-
-    
-  
-    
        rename a Dimension named oldname to newname.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def renameGroup(
        self, oldname, newname)
        
-    
        
-    
-
-    
-  
-    
        rename a Group named oldname to newname (requires netcdf >= 4.3.1).
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def renameVariable(
        self, oldname, newname)
        
-    
        
-    
-
-    
-  
-    
        rename a Variable named oldname to newname
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_always_mask(
        self, True_or_False)
        
-    
        
-    
-
-    
-  
-    
        Call set_always_mask for all variables contained in
-this Dataset or Group, as well as for all
-variables in all its subgroups.
        
-
        True_or_False: Boolean determining if automatic conversion of
-masked arrays with no missing values to regular numpy arrays shall be
-applied for all variables. Default True. Set to False to restore the default behaviour
-in versions prior to 1.4.1 (numpy array returned unless missing values are present,
-otherwise masked array returned).
        
-
        Note: Calling this function only affects existing
-variables. Variables created after calling this function will follow
-the default behaviour.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_chartostring(
        self, True_or_False)
        
-    
        
-    
-
-    
-  
-    
        Call set_auto_chartostring for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
        
-
        True_or_False: Boolean determining if automatic conversion of
-all character arrays <--> string arrays should be performed for
-character variables (variables of type NC_CHAR or S1) with the
-_Encoding attribute set.
        
-
        Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_mask(
        self, True_or_False)
        
-    
        
-    
-
-    
-  
-    
        Call set_auto_mask for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
        
-
        True_or_False: Boolean determining if automatic conversion to masked arrays
-shall be applied for all variables.
        
-
        Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_maskandscale(
        self, True_or_False)
        
-    
        
-    
-
-    
-  
-    
        Call set_auto_maskandscale for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
        
-
        True_or_False: Boolean determining if automatic conversion to masked arrays
-and variable scaling shall be applied for all variables.
        
-
        Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_scale(
        self, True_or_False)
        
-    
        
-    
-
-    
-  
-    
        Call set_auto_scale for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
        
-
        True_or_False: Boolean determining if automatic variable scaling
-shall be applied for all variables.
        
-
        Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_fill_off(
        self)
        
-    
        
-    
-
-    
-  
-    
        Sets the fill mode for a Dataset open for writing to off.
        
-
        This will prevent the data from being pre-filled with fill values, which
-may result in some performance improvements. However, you must then make
-sure the data is actually written before being read.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_fill_on(
        self)
        
-    
        
-    
-
-    
-  
-    
        Sets the fill mode for a Dataset open for writing to on.
        
-
        This causes data to be pre-filled with fill values. The fill values can be
-controlled by the variable's _Fill_Value attribute, but is usually
-sufficient to the use the netCDF default _Fill_Value (defined
-separately for each variable type). The default behavior of the netCDF
-library corresponds to set_fill_on.  Data which are equal to the
-_Fill_Value indicate that the variable was created, but never written
-to.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_ncstring_attrs(
        self, True_or_False)
        
-    
        
-    
-
-    
-  
-    
        Call set_ncstring_attrs for all variables contained in
-this Dataset or Group, as well as for all its
-subgroups and their variables.
        
-
        True_or_False: Boolean determining if all string attributes are
-created as variable-length NC_STRINGs, (if True), or if ascii text
-attributes are stored as NC_CHARs (if False; default)
        
-
        Note: Calling this function only affects newly created attributes
-of existing (sub-) groups and their variables.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def setncattr(
        self,name,value)
        
-    
        
-    
-
-    
-  
-    
        set a netCDF dataset or group attribute using name,value pair.
-Use if you need to set a netCDF attribute with the
-with the same name as one of the reserved python attributes.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def setncattr_string(
        self,name,value)
        
-    
        
-    
-
-    
-  
-    
        set a netCDF dataset or group string attribute using name,value pair.
-Use if you need to ensure that a netCDF attribute is created with type
-NC_STRING if the file format is NETCDF4.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def setncatts(
        self,attdict)
        
-    
        
-    
-
-    
-  
-    
        set a bunch of netCDF dataset or group attributes at once using a python dictionary.
-This may be faster when setting a lot of attributes for a NETCDF3
-formatted file, since nc_redef/nc_enddef is not called in between setting
-each attribute
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def sync(
        self)
        
-    
        
-    
-
-    
-  
-    
        Writes all buffered data in the Dataset to the disk file.
        
-  
        
-
        
-
-  
        
-  
-      
        
-      
        
-      
-      
        
-      
        class Dimension
        
-      
-  
-    
        A netCDF Dimension is used to describe the coordinates of a Variable.
-See __init__ for more details.
        
-
        The current maximum size of a Dimension instance can be obtained by
-calling the python len function on the Dimension instance. The
-isunlimited method of a Dimension instance can be used to
-determine if the dimension is unlimited.
        
-
        Read-only class variables:
        
-
        name: String name, used when creating a Variable with
-createVariable.
        
-
        size: Current Dimension size (same as len(d), where d is a
-Dimension instance).
        
-  
        
-
        
-
-
-      
        
-          
        Ancestors (in MRO)
        
-          
-          
        Class variables
        
-            
        
-            
        var name
        
-            
-
-            
-  
-    
        A string describing the name of the Dimension - used when creating a
-Variable instance with createVariable.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var size
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-          
        Static methods
        
-            
-  
        
-    
        
-    
        def __init__(
        self, group, name, size=None)
        
-    
        
-    
-
-    
-  
-    
        Dimension constructor.
        
-
        group: Group instance to associate with dimension.
        
-
        name: Name of the dimension.
        
-
        size: Size of the dimension. None or 0 means unlimited. (Default None).
        
-
        Note: Dimension instances should be created using the
-createDimension method of a Group or
-Dataset instance, not using __init__ directly.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def group(
        self)
        
-    
        
-    
-
-    
-  
-    
        return the group that this Dimension is a member of.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def isunlimited(
        self)
        
-    
        
-    
-
-    
-  
-    
        returns True if the Dimension instance is unlimited, False otherwise.
        
-  
        
-
        
-
-  
        
-  
-      
        
-      
        
-      
-      
        
-      
        class EnumType
        
-      
-  
-    
        A EnumType instance is used to describe an Enum data
-type, and can be passed to the the createVariable method of
-a Dataset or Group instance. See
-__init__ for more details.
        
-
        The instance variables dtype, name and enum_dict should not be modified by
-the user.
        
-  
        
-
        
-
-
-      
        
-          
        Ancestors (in MRO)
        
-          
-          
        Class variables
        
-            
        
-            
        var dtype
        
-            
-
-            
-  
-    
        A numpy integer dtype object describing the base type for the Enum.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var enum_dict
        
-            
-
-            
-  
-    
        A python dictionary describing the enum fields and values.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var name
        
-            
-
-            
-  
-    
        String name.
        
-  
        
-
        
-
-            
        
-          
        Static methods
        
-            
-  
        
-    
        
-    
        def __init__(
        group, datatype, datatype_name, enum_dict)
        
-    
        
-    
-
-    
-  
-    
        EnumType constructor.
        
-
        group: Group instance to associate with the VLEN datatype.
        
-
        datatype: An numpy integer dtype object describing the base type
-for the Enum.
        
-
        datatype_name: a Python string containing a description of the
-Enum data type.
        
-
        enum_dict: a Python dictionary containing the Enum field/value
-pairs.
        
-
        Note: EnumType instances should be created using the
-createEnumType
-method of a Dataset or Group instance, not using this class directly.
        
-  
        
-
        
-
-  
        
-  
-      
        
-      
        
-      
-      
        
-      
        class Group
        
-      
-  
-    
        Groups define a hierarchical namespace within a netCDF file. They are
-analogous to directories in a unix filesystem. Each Group behaves like
-a Dataset within a Dataset, and can contain it's own variables,
-dimensions and attributes (and other Groups). See __init__
-for more details.
        
-
        Group inherits from Dataset, so all the
-Dataset class methods and variables are available
-to a Group instance (except the close method).
        
-
        Additional read-only class variables:
        
-
        name: String describing the group name.
        
-  
        
-
        
-
-
-      
        
-          
        Ancestors (in MRO)
        
-          
-          
        Class variables
        
-            
        
-            
        var cmptypes
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var data_model
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var dimensions
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var disk_format
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var enumtypes
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var file_format
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var groups
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var keepweakref
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var name
        
-            
-
-            
-  
-    
        A string describing the name of the Group.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var parent
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var path
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var variables
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var vltypes
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-          
        Static methods
        
-            
-  
        
-    
        
-    
        def __init__(
        self, parent, name)
        
-    
        
-    
-    
        
-     Inheritance:
-       Dataset.__init__
-    
        
-
-    
-  
-    
        Group constructor.
        
-
        parent: Group instance for the parent group.  If being created
-in the root group, use a Dataset instance.
        
-
        name: - Name of the group.
        
-
        Note: Group instances should be created using the
-createGroup method of a Dataset instance, or
-another Group instance, not using this class directly.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def close(
        self)
        
-    
        
-    
-
-    
-  
-    
        overrides Dataset close method which does not apply to Group
-instances, raises IOError.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def createCompoundType(
        self, datatype, datatype_name)
        
-    
        
-    
-
-    
-  
-    
        Creates a new compound data type named datatype_name from the numpy
-dtype object datatype.
        
-
        Note: If the new compound data type contains other compound data types
-(i.e. it is a 'nested' compound type, where not all of the elements
-are homogeneous numeric data types), then the 'inner' compound types must be
-created first.
        
-
        The return value is the CompoundType class instance describing the new
-datatype.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def createDimension(
        self, dimname, size=None)
        
-    
        
-    
-
-    
-  
-    
        Creates a new dimension with the given dimname and size.
        
-
        size must be a positive integer or None, which stands for
-"unlimited" (default is None). Specifying a size of 0 also
-results in an unlimited dimension. The return value is the Dimension
-class instance describing the new dimension.  To determine the current
-maximum size of the dimension, use the len function on the Dimension
-instance. To determine if a dimension is 'unlimited', use the
-isunlimited method of the Dimension instance.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def createEnumType(
        self, datatype, datatype_name, enum_dict)
        
-    
        
-    
-
-    
-  
-    
        Creates a new Enum data type named datatype_name from a numpy
-integer dtype object datatype, and a python dictionary
-defining the enum fields and values.
        
-
        The return value is the EnumType class instance describing the new
-datatype.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def createGroup(
        self, groupname)
        
-    
        
-    
-
-    
-  
-    
        Creates a new Group with the given groupname.
        
-
        If groupname is specified as a path, using forward slashes as in unix to
-separate components, then intermediate groups will be created as necessary
-(analogous to mkdir -p in unix).  For example,
-createGroup('/GroupA/GroupB/GroupC') will create GroupA,
-GroupA/GroupB, and GroupA/GroupB/GroupC, if they don't already exist.
-If the specified path describes a group that already exists, no error is
-raised.
        
-
        The return value is a Group class instance.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def createVLType(
        self, datatype, datatype_name)
        
-    
        
-    
-
-    
-  
-    
        Creates a new VLEN data type named datatype_name from a numpy
-dtype object datatype.
        
-
        The return value is the VLType class instance describing the new
-datatype.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def createVariable(
        self, varname, datatype, dimensions=(), zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, fill_value=None, chunk_cache=None)
        
-    
        
-    
-
-    
-  
-    
        Creates a new variable with the given varname, datatype, and
-dimensions. If dimensions are not given, the variable is assumed to be
-a scalar.
        
-
        If varname is specified as a path, using forward slashes as in unix to
-separate components, then intermediate groups will be created as necessary
-For example, createVariable('/GroupA/GroupB/VarC', float, ('x','y')) will create groups GroupA
-and GroupA/GroupB, plus the variable GroupA/GroupB/VarC, if the preceding
-groups don't already exist.
        
-
        The datatype can be a numpy datatype object, or a string that describes
-a numpy dtype object (like the dtype.str attribute of a numpy array).
-Supported specifiers include: 'S1' or 'c' (NC_CHAR), 'i1' or 'b' or 'B'
-(NC_BYTE), 'u1' (NC_UBYTE), 'i2' or 'h' or 's' (NC_SHORT), 'u2'
-(NC_USHORT), 'i4' or 'i' or 'l' (NC_INT), 'u4' (NC_UINT), 'i8' (NC_INT64),
-'u8' (NC_UINT64), 'f4' or 'f' (NC_FLOAT), 'f8' or 'd' (NC_DOUBLE).
-datatype can also be a CompoundType instance
-(for a structured, or compound array), a VLType instance
-(for a variable-length array), or the python str builtin
-(for a variable-length string array). Numpy string and unicode datatypes with
-length greater than one are aliases for str.
        
-
        Data from netCDF variables is presented to python as numpy arrays with
-the corresponding data type.
        
-
        dimensions must be a tuple containing dimension names (strings) that
-have been defined previously using createDimension. The default value
-is an empty tuple, which means the variable is a scalar.
        
-
        If the optional keyword zlib is True, the data will be compressed in
-the netCDF file using gzip compression (default False).
        
-
        The optional keyword complevel is an integer between 1 and 9 describing
-the level of compression desired (default 4). Ignored if zlib=False.
        
-
        If the optional keyword shuffle is True, the HDF5 shuffle filter
-will be applied before compressing the data (default True).  This
-significantly improves compression. Default is True. Ignored if
-zlib=False.
        
-
        If the optional keyword fletcher32 is True, the Fletcher32 HDF5
-checksum algorithm is activated to detect errors. Default False.
        
-
        If the optional keyword contiguous is True, the variable data is
-stored contiguously on disk.  Default False. Setting to True for
-a variable with an unlimited dimension will trigger an error.
        
-
        The optional keyword chunksizes can be used to manually specify the
-HDF5 chunksizes for each dimension of the variable. A detailed
-discussion of HDF chunking and I/O performance is available
-here.
-Basically, you want the chunk size for each dimension to match as
-closely as possible the size of the data block that users will read
-from the file.  chunksizes cannot be set if contiguous=True.
        
-
        The optional keyword endian can be used to control whether the
-data is stored in little or big endian format on disk. Possible
-values are little, big or native (default). The library
-will automatically handle endian conversions when the data is read,
-but if the data is always going to be read on a computer with the
-opposite format as the one used to create the file, there may be
-some performance advantage to be gained by setting the endian-ness.
        
-
        The zlib, complevel, shuffle, fletcher32, contiguous, chunksizes and endian
-keywords are silently ignored for netCDF 3 files that do not use HDF5.
        
-
        The optional keyword fill_value can be used to override the default
-netCDF _FillValue (the value that the variable gets filled with before
-any data is written to it, defaults given in netCDF4.default_fillvals).
-If fill_value is set to False, then the variable is not pre-filled.
        
-
        If the optional keyword parameter least_significant_digit is
-specified, variable data will be truncated (quantized). In conjunction
-with zlib=True this produces 'lossy', but significantly more
-efficient compression. For example, if least_significant_digit=1,
-data will be quantized using numpy.around(scale*data)/scale, where
-scale = 2**bits, and bits is determined so that a precision of 0.1 is
-retained (in this case bits=4). From the
-PSD metadata conventions:
-"least_significant_digit -- power of ten of the smallest decimal place
-in unpacked data that is a reliable value." Default is None, or no
-quantization, or 'lossless' compression.
        
-
        When creating variables in a NETCDF4 or NETCDF4_CLASSIC formatted file,
-HDF5 creates something called a 'chunk cache' for each variable.  The
-default size of the chunk cache may be large enough to completely fill
-available memory when creating thousands of variables.  The optional
-keyword chunk_cache allows you to reduce (or increase) the size of
-the default chunk cache when creating a variable.  The setting only
-persists as long as the Dataset is open - you can use the set_var_chunk_cache
-method to change it the next time the Dataset is opened.
-Warning - messing with this parameter can seriously degrade performance.
        
-
        The return value is the Variable class instance describing the new
-variable.
        
-
        A list of names corresponding to netCDF variable attributes can be
-obtained with the Variable method ncattrs. A dictionary
-containing all the netCDF attribute name/value pairs is provided by
-the __dict__ attribute of a Variable instance.
        
-
        Variable instances behave much like array objects. Data can be
-assigned to or retrieved from a variable with indexing and slicing
-operations on the Variable instance. A Variable instance has six
-Dataset standard attributes: dimensions, dtype, shape, ndim, name and
-least_significant_digit. Application programs should never modify
-these attributes. The dimensions attribute is a tuple containing the
-names of the dimensions associated with this variable. The dtype
-attribute is a string describing the variable's data type (i4, f8,
-S1, etc). The shape attribute is a tuple describing the current
-sizes of all the variable's dimensions. The name attribute is a
-string containing the name of the Variable instance.
-The least_significant_digit
-attributes describes the power of ten of the smallest decimal place in
-the data the contains a reliable value.  assigned to the Variable
-instance. If None, the data is not truncated. The ndim attribute
-is the number of variable dimensions.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def delncattr(
        self,name,value)
        
-    
        
-    
-
-    
-  
-    
        delete a netCDF dataset or group attribute.  Use if you need to delete a
-netCDF attribute with the same name as one of the reserved python
-attributes.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def filepath(
        self,encoding=None)
        
-    
        
-    
-
-    
-  
-    
        Get the file system path (or the opendap URL) which was used to
-open/create the Dataset. Requires netcdf >= 4.1.2.  The path
-is decoded into a string using sys.getfilesystemencoding() by default, this can be
-changed using the encoding kwarg.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def get_variables_by_attributes(
        ...)
        
-    
        
-    
-
-    
-  
-    
        Returns a list of variables that match specific conditions.
        
-
        Can pass in key=value parameters and variables are returned that
-contain all of the matches. For example,
        
-
        >>> # Get variables with x-axis attribute.
->>> vs = nc.get_variables_by_attributes(axis='X')
->>> # Get variables with matching "standard_name" attribute
->>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
-
        
-
-
-
        Can pass in key=callable parameter and variables are returned if the
-callable returns True.  The callable should accept a single parameter,
-the attribute value.  None is given as the attribute value when the
-attribute does not exist on the variable. For example,
        
-
        >>> # Get Axis variables
->>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
->>> # Get variables that don't have an "axis" attribute
->>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
->>> # Get variables that have a "grid_mapping" attribute
->>> vs = nc.get_variables_by_attributes(grid_mapping=lambda v: v is not None)
-
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def getncattr(
        self,name)
        
-    
        
-    
-
-    
-  
-    
        retrieve a netCDF dataset or group attribute.
-Use if you need to get a netCDF attribute with the same
-name as one of the reserved python attributes.
        
-
        option kwarg encoding can be used to specify the
-character encoding of a string attribute (default is utf-8).
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def isopen(
        ...)
        
-    
        
-    
-
-    
-  
-    
        is the Dataset open or closed?
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def ncattrs(
        self)
        
-    
        
-    
-
-    
-  
-    
        return netCDF global attribute names for this Dataset or Group in a list.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def renameAttribute(
        self, oldname, newname)
        
-    
        
-    
-
-    
-  
-    
        rename a Dataset or Group attribute named oldname to newname.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def renameDimension(
        self, oldname, newname)
        
-    
        
-    
-
-    
-  
-    
        rename a Dimension named oldname to newname.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def renameGroup(
        self, oldname, newname)
        
-    
        
-    
-
-    
-  
-    
        rename a Group named oldname to newname (requires netcdf >= 4.3.1).
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def renameVariable(
        self, oldname, newname)
        
-    
        
-    
-
-    
-  
-    
        rename a Variable named oldname to newname
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_always_mask(
        self, True_or_False)
        
-    
        
-    
-
-    
-  
-    
        Call set_always_mask for all variables contained in
-this Dataset or Group, as well as for all
-variables in all its subgroups.
        
-
        True_or_False: Boolean determining if automatic conversion of
-masked arrays with no missing values to regular numpy arrays shall be
-applied for all variables. Default True. Set to False to restore the default behaviour
-in versions prior to 1.4.1 (numpy array returned unless missing values are present,
-otherwise masked array returned).
        
-
        Note: Calling this function only affects existing
-variables. Variables created after calling this function will follow
-the default behaviour.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_chartostring(
        self, True_or_False)
        
-    
        
-    
-
-    
-  
-    
        Call set_auto_chartostring for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
        
-
        True_or_False: Boolean determining if automatic conversion of
-all character arrays <--> string arrays should be performed for
-character variables (variables of type NC_CHAR or S1) with the
-_Encoding attribute set.
        
-
        Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_mask(
        self, True_or_False)
        
-    
        
-    
-
-    
-  
-    
        Call set_auto_mask for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
        
-
        True_or_False: Boolean determining if automatic conversion to masked arrays
-shall be applied for all variables.
        
-
        Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_maskandscale(
        self, True_or_False)
        
-    
        
-    
-
-    
-  
-    
        Call set_auto_maskandscale for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
        
-
        True_or_False: Boolean determining if automatic conversion to masked arrays
-and variable scaling shall be applied for all variables.
        
-
        Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_scale(
        self, True_or_False)
        
-    
        
-    
-
-    
-  
-    
        Call set_auto_scale for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
        
-
        True_or_False: Boolean determining if automatic variable scaling
-shall be applied for all variables.
        
-
        Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_fill_off(
        self)
        
-    
        
-    
-
-    
-  
-    
        Sets the fill mode for a Dataset open for writing to off.
        
-
        This will prevent the data from being pre-filled with fill values, which
-may result in some performance improvements. However, you must then make
-sure the data is actually written before being read.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_fill_on(
        self)
        
-    
        
-    
-
-    
-  
-    
        Sets the fill mode for a Dataset open for writing to on.
        
-
        This causes data to be pre-filled with fill values. The fill values can be
-controlled by the variable's _Fill_Value attribute, but is usually
-sufficient to the use the netCDF default _Fill_Value (defined
-separately for each variable type). The default behavior of the netCDF
-library corresponds to set_fill_on.  Data which are equal to the
-_Fill_Value indicate that the variable was created, but never written
-to.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_ncstring_attrs(
        self, True_or_False)
        
-    
        
-    
-
-    
-  
-    
        Call set_ncstring_attrs for all variables contained in
-this Dataset or Group, as well as for all its
-subgroups and their variables.
        
-
        True_or_False: Boolean determining if all string attributes are
-created as variable-length NC_STRINGs, (if True), or if ascii text
-attributes are stored as NC_CHARs (if False; default)
        
-
        Note: Calling this function only affects newly created attributes
-of existing (sub-) groups and their variables.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def setncattr(
        self,name,value)
        
-    
        
-    
-
-    
-  
-    
        set a netCDF dataset or group attribute using name,value pair.
-Use if you need to set a netCDF attribute with the
-with the same name as one of the reserved python attributes.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def setncattr_string(
        self,name,value)
        
-    
        
-    
-
-    
-  
-    
        set a netCDF dataset or group string attribute using name,value pair.
-Use if you need to ensure that a netCDF attribute is created with type
-NC_STRING if the file format is NETCDF4.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def setncatts(
        self,attdict)
        
-    
        
-    
-
-    
-  
-    
        set a bunch of netCDF dataset or group attributes at once using a python dictionary.
-This may be faster when setting a lot of attributes for a NETCDF3
-formatted file, since nc_redef/nc_enddef is not called in between setting
-each attribute
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def sync(
        self)
        
-    
        
-    
-
-    
-  
-    
        Writes all buffered data in the Dataset to the disk file.
        
-  
        
-
        
-
-  
        
-  
-      
        
-      
        
-      
-      
        
-      
        class MFDataset
        
-      
-  
-    
        Class for reading multi-file netCDF Datasets, making variables
-spanning multiple files appear as if they were in one file.
-Datasets must be in NETCDF4_CLASSIC, NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET
-or NETCDF3_64BIT_DATA format (NETCDF4 Datasets won't work).
        
-
        Adapted from pycdf by Andre Gosselin.
        
-
        Example usage (See __init__ for more details):
        
-
        >>> import numpy as np
->>> # create a series of netCDF files with a variable sharing
->>> # the same unlimited dimension.
->>> for nf in range(10):
-...     with Dataset("mftest%s.nc" % nf, "w", format='NETCDF4_CLASSIC') as f:
-...         f.createDimension("x",None)
-...         x = f.createVariable("x","i",("x",))
-...         x[0:10] = np.arange(nf*10,10*(nf+1))
->>> # now read all those files in at once, in one Dataset.
->>> f = MFDataset("mftest*nc")
->>> print(f.variables["x"][:])
-[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
- 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
- 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71
- 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
- 96 97 98 99]
-
        
-  
        
-
        
-
-
-      
        
-          
        Ancestors (in MRO)
        
-          
-          
        Class variables
        
-            
        
-            
        var cmptypes
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var data_model
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var dimensions
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var disk_format
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var enumtypes
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var file_format
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var groups
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var keepweakref
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var name
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var parent
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var path
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var variables
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var vltypes
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-          
        Static methods
        
-            
-  
        
-    
        
-    
        def __init__(
        self, files, check=False, aggdim=None, exclude=[], master_file=None)
        
-    
        
-    
-    
        
-     Inheritance:
-       Dataset.__init__
-    
        
-
-    
-  
-    
        __init__(self, files, check=False, aggdim=None, exclude=[],
-master_file=None)
        
-
        Open a Dataset spanning multiple files, making it look as if it was a
-single file. Variables in the list of files that share the same
-dimension (specified with the keyword aggdim) are aggregated. If
-aggdim is not specified, the unlimited is aggregated.  Currently,
-aggdim must be the leftmost (slowest varying) dimension of each
-of the variables to be aggregated.
        
-
        files: either a sequence of netCDF files or a string with a
-wildcard (converted to a sorted list of files using glob)  If
-the master_file kwarg is not specified, the first file
-in the list will become the "master" file, defining all the
-variables with an aggregation dimension which may span
-subsequent files. Attribute access returns attributes only from "master"
-file. The files are always opened in read-only mode.
        
-
        check: True if you want to do consistency checking to ensure the
-correct variables structure for all of the netcdf files.  Checking makes
-the initialization of the MFDataset instance much slower. Default is
-False.
        
-
        aggdim: The name of the dimension to aggregate over (must
-be the leftmost dimension of each of the variables to be aggregated).
-If None (default), aggregate over the unlimited dimension.
        
-
        exclude: A list of variable names to exclude from aggregation.
-Default is an empty list.
        
-
        master_file: file to use as "master file", defining all the
-variables with an aggregation dimension and all global attributes.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def close(
        self)
        
-    
        
-    
-
-    
-  
-    
        close(self)
        
-
        close all the open files.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def createCompoundType(
        self, datatype, datatype_name)
        
-    
        
-    
-
-    
-  
-    
        Creates a new compound data type named datatype_name from the numpy
-dtype object datatype.
        
-
        Note: If the new compound data type contains other compound data types
-(i.e. it is a 'nested' compound type, where not all of the elements
-are homogeneous numeric data types), then the 'inner' compound types must be
-created first.
        
-
        The return value is the CompoundType class instance describing the new
-datatype.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def createDimension(
        self, dimname, size=None)
        
-    
        
-    
-
-    
-  
-    
        Creates a new dimension with the given dimname and size.
        
-
        size must be a positive integer or None, which stands for
-"unlimited" (default is None). Specifying a size of 0 also
-results in an unlimited dimension. The return value is the Dimension
-class instance describing the new dimension.  To determine the current
-maximum size of the dimension, use the len function on the Dimension
-instance. To determine if a dimension is 'unlimited', use the
-isunlimited method of the Dimension instance.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def createEnumType(
        self, datatype, datatype_name, enum_dict)
        
-    
        
-    
-
-    
-  
-    
        Creates a new Enum data type named datatype_name from a numpy
-integer dtype object datatype, and a python dictionary
-defining the enum fields and values.
        
-
        The return value is the EnumType class instance describing the new
-datatype.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def createGroup(
        self, groupname)
        
-    
        
-    
-
-    
-  
-    
        Creates a new Group with the given groupname.
        
-
        If groupname is specified as a path, using forward slashes as in unix to
-separate components, then intermediate groups will be created as necessary
-(analogous to mkdir -p in unix).  For example,
-createGroup('/GroupA/GroupB/GroupC') will create GroupA,
-GroupA/GroupB, and GroupA/GroupB/GroupC, if they don't already exist.
-If the specified path describes a group that already exists, no error is
-raised.
        
-
        The return value is a Group class instance.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def createVLType(
        self, datatype, datatype_name)
        
-    
        
-    
-
-    
-  
-    
        Creates a new VLEN data type named datatype_name from a numpy
-dtype object datatype.
        
-
        The return value is the VLType class instance describing the new
-datatype.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def createVariable(
        self, varname, datatype, dimensions=(), zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, fill_value=None, chunk_cache=None)
        
-    
        
-    
-
-    
-  
-    
        Creates a new variable with the given varname, datatype, and
-dimensions. If dimensions are not given, the variable is assumed to be
-a scalar.
        
-
        If varname is specified as a path, using forward slashes as in unix to
-separate components, then intermediate groups will be created as necessary
-For example, createVariable('/GroupA/GroupB/VarC', float, ('x','y')) will create groups GroupA
-and GroupA/GroupB, plus the variable GroupA/GroupB/VarC, if the preceding
-groups don't already exist.
        
-
        The datatype can be a numpy datatype object, or a string that describes
-a numpy dtype object (like the dtype.str attribute of a numpy array).
-Supported specifiers include: 'S1' or 'c' (NC_CHAR), 'i1' or 'b' or 'B'
-(NC_BYTE), 'u1' (NC_UBYTE), 'i2' or 'h' or 's' (NC_SHORT), 'u2'
-(NC_USHORT), 'i4' or 'i' or 'l' (NC_INT), 'u4' (NC_UINT), 'i8' (NC_INT64),
-'u8' (NC_UINT64), 'f4' or 'f' (NC_FLOAT), 'f8' or 'd' (NC_DOUBLE).
-datatype can also be a CompoundType instance
-(for a structured, or compound array), a VLType instance
-(for a variable-length array), or the python str builtin
-(for a variable-length string array). Numpy string and unicode datatypes with
-length greater than one are aliases for str.
        
-
        Data from netCDF variables is presented to python as numpy arrays with
-the corresponding data type.
        
-
        dimensions must be a tuple containing dimension names (strings) that
-have been defined previously using createDimension. The default value
-is an empty tuple, which means the variable is a scalar.
        
-
        If the optional keyword zlib is True, the data will be compressed in
-the netCDF file using gzip compression (default False).
        
-
        The optional keyword complevel is an integer between 1 and 9 describing
-the level of compression desired (default 4). Ignored if zlib=False.
        
-
        If the optional keyword shuffle is True, the HDF5 shuffle filter
-will be applied before compressing the data (default True).  This
-significantly improves compression. Default is True. Ignored if
-zlib=False.
        
-
        If the optional keyword fletcher32 is True, the Fletcher32 HDF5
-checksum algorithm is activated to detect errors. Default False.
        
-
        If the optional keyword contiguous is True, the variable data is
-stored contiguously on disk.  Default False. Setting to True for
-a variable with an unlimited dimension will trigger an error.
        
-
        The optional keyword chunksizes can be used to manually specify the
-HDF5 chunksizes for each dimension of the variable. A detailed
-discussion of HDF chunking and I/O performance is available
-here.
-Basically, you want the chunk size for each dimension to match as
-closely as possible the size of the data block that users will read
-from the file.  chunksizes cannot be set if contiguous=True.
        
-
        The optional keyword endian can be used to control whether the
-data is stored in little or big endian format on disk. Possible
-values are little, big or native (default). The library
-will automatically handle endian conversions when the data is read,
-but if the data is always going to be read on a computer with the
-opposite format as the one used to create the file, there may be
-some performance advantage to be gained by setting the endian-ness.
        
-
        The zlib, complevel, shuffle, fletcher32, contiguous, chunksizes and endian
-keywords are silently ignored for netCDF 3 files that do not use HDF5.
        
-
        The optional keyword fill_value can be used to override the default
-netCDF _FillValue (the value that the variable gets filled with before
-any data is written to it, defaults given in netCDF4.default_fillvals).
-If fill_value is set to False, then the variable is not pre-filled.
        
-
        If the optional keyword parameter least_significant_digit is
-specified, variable data will be truncated (quantized). In conjunction
-with zlib=True this produces 'lossy', but significantly more
-efficient compression. For example, if least_significant_digit=1,
-data will be quantized using numpy.around(scale*data)/scale, where
-scale = 2**bits, and bits is determined so that a precision of 0.1 is
-retained (in this case bits=4). From the
-PSD metadata conventions:
-"least_significant_digit -- power of ten of the smallest decimal place
-in unpacked data that is a reliable value." Default is None, or no
-quantization, or 'lossless' compression.
        
-
        When creating variables in a NETCDF4 or NETCDF4_CLASSIC formatted file,
-HDF5 creates something called a 'chunk cache' for each variable.  The
-default size of the chunk cache may be large enough to completely fill
-available memory when creating thousands of variables.  The optional
-keyword chunk_cache allows you to reduce (or increase) the size of
-the default chunk cache when creating a variable.  The setting only
-persists as long as the Dataset is open - you can use the set_var_chunk_cache
-method to change it the next time the Dataset is opened.
-Warning - messing with this parameter can seriously degrade performance.
        
-
        The return value is the Variable class instance describing the new
-variable.
        
-
        A list of names corresponding to netCDF variable attributes can be
-obtained with the Variable method ncattrs. A dictionary
-containing all the netCDF attribute name/value pairs is provided by
-the __dict__ attribute of a Variable instance.
        
-
        Variable instances behave much like array objects. Data can be
-assigned to or retrieved from a variable with indexing and slicing
-operations on the Variable instance. A Variable instance has six
-Dataset standard attributes: dimensions, dtype, shape, ndim, name and
-least_significant_digit. Application programs should never modify
-these attributes. The dimensions attribute is a tuple containing the
-names of the dimensions associated with this variable. The dtype
-attribute is a string describing the variable's data type (i4, f8,
-S1, etc). The shape attribute is a tuple describing the current
-sizes of all the variable's dimensions. The name attribute is a
-string containing the name of the Variable instance.
-The least_significant_digit
-attributes describes the power of ten of the smallest decimal place in
-the data the contains a reliable value.  assigned to the Variable
-instance. If None, the data is not truncated. The ndim attribute
-is the number of variable dimensions.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def delncattr(
        self,name,value)
        
-    
        
-    
-
-    
-  
-    
        delete a netCDF dataset or group attribute.  Use if you need to delete a
-netCDF attribute with the same name as one of the reserved python
-attributes.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def filepath(
        self,encoding=None)
        
-    
        
-    
-
-    
-  
-    
        Get the file system path (or the opendap URL) which was used to
-open/create the Dataset. Requires netcdf >= 4.1.2.  The path
-is decoded into a string using sys.getfilesystemencoding() by default, this can be
-changed using the encoding kwarg.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def get_variables_by_attributes(
        ...)
        
-    
        
-    
-
-    
-  
-    
        Returns a list of variables that match specific conditions.
        
-
        Can pass in key=value parameters and variables are returned that
-contain all of the matches. For example,
        
-
        >>> # Get variables with x-axis attribute.
->>> vs = nc.get_variables_by_attributes(axis='X')
->>> # Get variables with matching "standard_name" attribute
->>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
-
        
-
-
-
        Can pass in key=callable parameter and variables are returned if the
-callable returns True.  The callable should accept a single parameter,
-the attribute value.  None is given as the attribute value when the
-attribute does not exist on the variable. For example,
        
-
        >>> # Get Axis variables
->>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
->>> # Get variables that don't have an "axis" attribute
->>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
->>> # Get variables that have a "grid_mapping" attribute
->>> vs = nc.get_variables_by_attributes(grid_mapping=lambda v: v is not None)
-
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def getncattr(
        self,name)
        
-    
        
-    
-
-    
-  
-    
        retrieve a netCDF dataset or group attribute.
-Use if you need to get a netCDF attribute with the same
-name as one of the reserved python attributes.
        
-
        option kwarg encoding can be used to specify the
-character encoding of a string attribute (default is utf-8).
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def isopen(
        ...)
        
-    
        
-    
-
-    
-  
-    
        is the Dataset open or closed?
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def ncattrs(
        self)
        
-    
        
-    
-
-    
-  
-    
        ncattrs(self)
        
-
        return the netcdf attribute names from the master file.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def renameAttribute(
        self, oldname, newname)
        
-    
        
-    
-
-    
-  
-    
        rename a Dataset or Group attribute named oldname to newname.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def renameDimension(
        self, oldname, newname)
        
-    
        
-    
-
-    
-  
-    
        rename a Dimension named oldname to newname.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def renameGroup(
        self, oldname, newname)
        
-    
        
-    
-
-    
-  
-    
        rename a Group named oldname to newname (requires netcdf >= 4.3.1).
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def renameVariable(
        self, oldname, newname)
        
-    
        
-    
-
-    
-  
-    
        rename a Variable named oldname to newname
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_always_mask(
        self, True_or_False)
        
-    
        
-    
-
-    
-  
-    
        Call set_always_mask for all variables contained in
-this Dataset or Group, as well as for all
-variables in all its subgroups.
        
-
        True_or_False: Boolean determining if automatic conversion of
-masked arrays with no missing values to regular numpy arrays shall be
-applied for all variables. Default True. Set to False to restore the default behaviour
-in versions prior to 1.4.1 (numpy array returned unless missing values are present,
-otherwise masked array returned).
        
-
        Note: Calling this function only affects existing
-variables. Variables created after calling this function will follow
-the default behaviour.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_chartostring(
        self, True_or_False)
        
-    
        
-    
-
-    
-  
-    
        Call set_auto_chartostring for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
        
-
        True_or_False: Boolean determining if automatic conversion of
-all character arrays <--> string arrays should be performed for
-character variables (variables of type NC_CHAR or S1) with the
-_Encoding attribute set.
        
-
        Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_mask(
        self, True_or_False)
        
-    
        
-    
-
-    
-  
-    
        Call set_auto_mask for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
        
-
        True_or_False: Boolean determining if automatic conversion to masked arrays
-shall be applied for all variables.
        
-
        Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_maskandscale(
        self, True_or_False)
        
-    
        
-    
-
-    
-  
-    
        Call set_auto_maskandscale for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
        
-
        True_or_False: Boolean determining if automatic conversion to masked arrays
-and variable scaling shall be applied for all variables.
        
-
        Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_scale(
        self, True_or_False)
        
-    
        
-    
-
-    
-  
-    
        Call set_auto_scale for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
        
-
        True_or_False: Boolean determining if automatic variable scaling
-shall be applied for all variables.
        
-
        Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_fill_off(
        self)
        
-    
        
-    
-
-    
-  
-    
        Sets the fill mode for a Dataset open for writing to off.
        
-
        This will prevent the data from being pre-filled with fill values, which
-may result in some performance improvements. However, you must then make
-sure the data is actually written before being read.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_fill_on(
        self)
        
-    
        
-    
-
-    
-  
-    
        Sets the fill mode for a Dataset open for writing to on.
        
-
        This causes data to be pre-filled with fill values. The fill values can be
-controlled by the variable's _Fill_Value attribute, but is usually
-sufficient to the use the netCDF default _Fill_Value (defined
-separately for each variable type). The default behavior of the netCDF
-library corresponds to set_fill_on.  Data which are equal to the
-_Fill_Value indicate that the variable was created, but never written
-to.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_ncstring_attrs(
        self, True_or_False)
        
-    
        
-    
-
-    
-  
-    
        Call set_ncstring_attrs for all variables contained in
-this Dataset or Group, as well as for all its
-subgroups and their variables.
        
-
        True_or_False: Boolean determining if all string attributes are
-created as variable-length NC_STRINGs, (if True), or if ascii text
-attributes are stored as NC_CHARs (if False; default)
        
-
        Note: Calling this function only affects newly created attributes
-of existing (sub-) groups and their variables.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def setncattr(
        self,name,value)
        
-    
        
-    
-
-    
-  
-    
        set a netCDF dataset or group attribute using name,value pair.
-Use if you need to set a netCDF attribute with the
-with the same name as one of the reserved python attributes.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def setncattr_string(
        self,name,value)
        
-    
        
-    
-
-    
-  
-    
        set a netCDF dataset or group string attribute using name,value pair.
-Use if you need to ensure that a netCDF attribute is created with type
-NC_STRING if the file format is NETCDF4.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def setncatts(
        self,attdict)
        
-    
        
-    
-
-    
-  
-    
        set a bunch of netCDF dataset or group attributes at once using a python dictionary.
-This may be faster when setting a lot of attributes for a NETCDF3
-formatted file, since nc_redef/nc_enddef is not called in between setting
-each attribute
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def sync(
        self)
        
-    
        
-    
-
-    
-  
-    
        Writes all buffered data in the Dataset to the disk file.
        
-  
        
-
        
-
-  
        
-  
-      
        
-      
        
-      
-      
        
-      
        class MFTime
        
-      
-  
-    
        Class providing an interface to a MFDataset time Variable by imposing a unique common
-time unit and/or calendar to all files.
        
-
        Example usage (See __init__ for more details):
        
-
        >>> import numpy
->>> f1 = Dataset("mftest_1.nc","w", format="NETCDF4_CLASSIC")
->>> f2 = Dataset("mftest_2.nc","w", format="NETCDF4_CLASSIC")
->>> f1.createDimension("time",None)
->>> f2.createDimension("time",None)
->>> t1 = f1.createVariable("time","i",("time",))
->>> t2 = f2.createVariable("time","i",("time",))
->>> t1.units = "days since 2000-01-01"
->>> t2.units = "days since 2000-02-01"
->>> t1.calendar = "standard"
->>> t2.calendar = "standard"
->>> t1[:] = numpy.arange(31)
->>> t2[:] = numpy.arange(30)
->>> f1.close()
->>> f2.close()
->>> # Read the two files in at once, in one Dataset.
->>> f = MFDataset("mftest_*nc")
->>> t = f.variables["time"]
->>> print(t.units)
-days since 2000-01-01
->>> print(t[32])  # The value written in the file, inconsistent with the MF time units.
-1
->>> T = MFTime(t)
->>> print(T[32])
-32
-
        
-  
        
-
        
-
-
-      
        
-          
        Ancestors (in MRO)
        
-          
          
-          
        • MFTime
          • 
-          
        • netCDF4._netCDF4._Variable
          • 
-          
        • builtins.object
          • 
-          
        
-          
        Static methods
        
-            
-  
        
-    
        
-    
        def __init__(
        self, time, units=None, calendar=None)
        
-    
        
-    
-
-    
-  
-    
        __init__(self, time, units=None, calendar=None)
        
-
        Create a time Variable with units consistent across a multifile
-dataset.
        
-
        time: Time variable from a MFDataset.
        
-
        units: Time units, for example, 'days since 1979-01-01'. If None,
-use the units from the master variable.
        
-
        calendar: Calendar overload to use across all files, for example,
-'standard' or 'gregorian'. If None, check that the calendar attribute
-is present on each variable and values are unique across files raising a
-ValueError otherwise.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def ncattrs(
        self)
        
-    
        
-    
-
-    
-  
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_always_mask(
        self, val)
        
-    
        
-    
-
-    
-  
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_chartostring(
        self, val)
        
-    
        
-    
-
-    
-  
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_mask(
        self, val)
        
-    
        
-    
-
-    
-  
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_maskandscale(
        self, val)
        
-    
        
-    
-
-    
-  
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_scale(
        self, val)
        
-    
        
-    
-
-    
-  
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def typecode(
        self)
        
-    
        
-    
-
-    
-  
-  
        
-
        
-
-  
        
-  
-      
        
-      
        
-      
-      
        
-      
        class VLType
        
-      
-  
-    
        A VLType instance is used to describe a variable length (VLEN) data
-type, and can be passed to the the createVariable method of
-a Dataset or Group instance. See
-__init__ for more details.
        
-
        The instance variables dtype and name should not be modified by
-the user.
        
-  
        
-
        
-
-
-      
        
-          
        Ancestors (in MRO)
        
-          
          
-          
        • VLType
          • 
-          
        • builtins.object
          • 
-          
        
-          
        Class variables
        
-            
        
-            
        var dtype
        
-            
-
-            
-  
-    
        A numpy dtype object describing the component type for the VLEN.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var name
        
-            
-
-            
-  
-    
        String name.
        
-  
        
-
        
-
-            
        
-          
        Static methods
        
-            
-  
        
-    
        
-    
        def __init__(
        group, datatype, datatype_name)
        
-    
        
-    
-
-    
-  
-    
        VLType constructor.
        
-
        group: Group instance to associate with the VLEN datatype.
        
-
        datatype: An numpy dtype object describing the component type for the
-variable length array.
        
-
        datatype_name: a Python string containing a description of the
-VLEN data type.
        
-
        Note: VLType instances should be created using the
-createVLType
-method of a Dataset or Group instance, not using this class directly.
        
-  
        
-
        
-
-  
        
-  
-      
        
-      
        
-      
-      
        
-      
        class Variable
        
-      
-  
-    
        A netCDF Variable is used to read and write netCDF data.  They are
-analogous to numpy array objects. See __init__ for more
-details.
        
-
        A list of attribute names corresponding to netCDF attributes defined for
-the variable can be obtained with the ncattrs method. These
-attributes can be created by assigning to an attribute of the
-Variable instance. A dictionary containing all the netCDF attribute
-name/value pairs is provided by the __dict__ attribute of a
-Variable instance.
        
-
        The following class variables are read-only:
        
-
        dimensions: A tuple containing the names of the
-dimensions associated with this variable.
        
-
        dtype: A numpy dtype object describing the
-variable's data type.
        
-
        ndim: The number of variable dimensions.
        
-
        shape: A tuple with the current shape (length of all dimensions).
        
-
        scale: If True, scale_factor and add_offset are
-applied, and signed integer data is automatically converted to
-unsigned integer data if the _Unsigned attribute is set.
-Default is True, can be reset using set_auto_scale and
-set_auto_maskandscale methods.
        
-
        mask: If True, data is automatically converted to/from masked
-arrays when missing values or fill values are present. Default is True, can be
-reset using set_auto_mask and set_auto_maskandscale
-methods.
        
-
        chartostring: If True, data is automatically converted to/from character
-arrays to string arrays when the _Encoding variable attribute is set.
-Default is True, can be reset using
-set_auto_chartostring method.
        
-
        least_significant_digit: Describes the power of ten of the
-smallest decimal place in the data the contains a reliable value.  Data is
-truncated to this decimal place when it is assigned to the Variable
-instance. If None, the data is not truncated.
        
-
        __orthogonal_indexing__: Always True.  Indicates to client code
-that the object supports 'orthogonal indexing', which means that slices
-that are 1d arrays or lists slice along each dimension independently.  This
-behavior is similar to Fortran or Matlab, but different than numpy.
        
-
        datatype: numpy data type (for primitive data types) or VLType/CompoundType
- instance (for compound or vlen data types).
        
-
        name: String name.
        
-
        size: The number of stored elements.
        
-  
        
-
        
-
-
-      
        
-          
        Ancestors (in MRO)
        
-          
-          
        Class variables
        
-            
        
-            
        var always_mask
        
-            
-
-            
-  
-  
        
-
        
-
-            
        
-            
        
-            
        var chartostring
        
-            
-
-            
-  
-    
        If True, data is automatically converted to/from character 
-arrays to string arrays when _Encoding variable attribute is set.
-Default is True, can be reset using
-set_auto_chartostring method.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var datatype
        
-            
-
-            
-  
-    
        numpy data type (for primitive data types) or
-VLType/CompoundType/EnumType instance (for compound, vlen or enum
-data types).
        
-  
        
-
        
-
-            
        
-            
        
-            
        var dimensions
        
-            
-
-            
-  
-    
        A tuple containing the names of the
-dimensions associated with this variable.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var dtype
        
-            
-
-            
-  
-    
        A numpy dtype object describing the
-variable's data type.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var mask
        
-            
-
-            
-  
-    
        If True, data is automatically converted to/from masked 
-arrays when missing values or fill values are present. Default is True, can be
-reset using set_auto_mask and set_auto_maskandscale
-methods.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var name
        
-            
-
-            
-  
-    
        String name.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var ndim
        
-            
-
-            
-  
-    
        The number of variable dimensions.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var scale
        
-            
-
-            
-  
-    
        if True, scale_factor and add_offset are
-applied, and signed integer data is converted to unsigned
-integer data if the _Unsigned attribute is set.
-Default is True, can be reset using set_auto_scale and
-set_auto_maskandscale methods.
        
-  
        
-
        
-
-            
        
-            
        
-            
        var shape
        
-            
-
-            
-  
-    
        A tuple with the current shape (length of all dimensions).
        
-  
        
-
        
-
-            
        
-            
        
-            
        var size
        
-            
-
-            
-  
-    
        The number of stored elements.
        
-  
        
-
        
-
-            
        
-          
        Static methods
        
-            
-  
        
-    
        
-    
        def __init__(
        self, group, name, datatype, dimensions=(), zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None,fill_value=None,chunk_cache=None)
        
-    
        
-    
-
-    
-  
-    
        Variable constructor.
        
-
        group: Group or Dataset instance to associate with variable.
        
-
        name: Name of the variable.
        
-
        datatype: Variable data type. Can be specified by providing a
-numpy dtype object, or a string that describes a numpy dtype object.
-Supported values, corresponding to str attribute of numpy dtype
-objects, include 'f4' (32-bit floating point), 'f8' (64-bit floating
-point), 'i4' (32-bit signed integer), 'i2' (16-bit signed integer),
-'i8' (64-bit signed integer), 'i4' (8-bit signed integer), 'i1'
-(8-bit signed integer), 'u1' (8-bit unsigned integer), 'u2' (16-bit
-unsigned integer), 'u4' (32-bit unsigned integer), 'u8' (64-bit
-unsigned integer), or 'S1' (single-character string).  From
-compatibility with Scientific.IO.NetCDF, the old Numeric single character
-typecodes can also be used ('f' instead of 'f4', 'd' instead of
-'f8', 'h' or 's' instead of 'i2', 'b' or 'B' instead of
-'i1', 'c' instead of 'S1', and 'i' or 'l' instead of
-'i4'). datatype can also be a CompoundType instance
-(for a structured, or compound array), a VLType instance
-(for a variable-length array), or the python str builtin
-(for a variable-length string array). Numpy string and unicode datatypes with
-length greater than one are aliases for str.
        
-
        dimensions: a tuple containing the variable's dimension names
-(defined previously with createDimension). Default is an empty tuple
-which means the variable is a scalar (and therefore has no dimensions).
        
-
        zlib: if True, data assigned to the Variable
-instance is compressed on disk. Default False.
        
-
        complevel: the level of zlib compression to use (1 is the fastest,
-but poorest compression, 9 is the slowest but best compression). Default 4.
-Ignored if zlib=False.
        
-
        shuffle: if True, the HDF5 shuffle filter is applied
-to improve compression. Default True. Ignored if zlib=False.
        
-
        fletcher32: if True (default False), the Fletcher32 checksum
-algorithm is used for error detection.
        
-
        contiguous: if True (default False), the variable data is
-stored contiguously on disk.  Default False. Setting to True for
-a variable with an unlimited dimension will trigger an error.
        
-
        chunksizes: Can be used to specify the HDF5 chunksizes for each
-dimension of the variable. A detailed discussion of HDF chunking and I/O
-performance is available
-here.
-Basically, you want the chunk size for each dimension to match as
-closely as possible the size of the data block that users will read
-from the file. chunksizes cannot be set if contiguous=True.
        
-
        endian: Can be used to control whether the
-data is stored in little or big endian format on disk. Possible
-values are little, big or native (default). The library
-will automatically handle endian conversions when the data is read,
-but if the data is always going to be read on a computer with the
-opposite format as the one used to create the file, there may be
-some performance advantage to be gained by setting the endian-ness.
-For netCDF 3 files (that don't use HDF5), only endian='native' is allowed.
        
-
        The zlib, complevel, shuffle, fletcher32, contiguous and chunksizes
-keywords are silently ignored for netCDF 3 files that do not use HDF5.
        
-
        least_significant_digit: If specified, variable data will be
-truncated (quantized). In conjunction with zlib=True this produces
-'lossy', but significantly more efficient compression. For example, if
-least_significant_digit=1, data will be quantized using
-around(scaledata)/scale, where scale = 2*bits, and bits is determined
-so that a precision of 0.1 is retained (in this case bits=4). Default is
-None, or no quantization.
        
-
        fill_value:  If specified, the default netCDF _FillValue (the
-value that the variable gets filled with before any data is written to it)
-is replaced with this value.  If fill_value is set to False, then
-the variable is not pre-filled. The default netCDF fill values can be found
-in netCDF4.default_fillvals.
        
-
        chunk_cache: If specified, sets the chunk cache size for this variable.
-Persists as long as Dataset is open. Use netCDF4.set_var_chunk_cache to 
-change it when Dataset is re-opened. 
        
-
        Note: Variable instances should be created using the
-createVariable method of a Dataset or
-Group instance, not using this class directly.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def assignValue(
        self, val)
        
-    
        
-    
-
-    
-  
-    
        assign a value to a scalar variable.  Provided for compatibility with
-Scientific.IO.NetCDF, can also be done by assigning to an Ellipsis slice ([...]).
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def chunking(
        self)
        
-    
        
-    
-
-    
-  
-    
        return variable chunking information.  If the dataset is
-defined to be contiguous (and hence there is no chunking) the word 'contiguous'
-is returned.  Otherwise, a sequence with the chunksize for
-each dimension is returned.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def delncattr(
        self,name,value)
        
-    
        
-    
-
-    
-  
-    
        delete a netCDF variable attribute.  Use if you need to delete a
-netCDF attribute with the same name as one of the reserved python
-attributes.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def endian(
        self)
        
-    
        
-    
-
-    
-  
-    
        return endian-ness (little,big,native) of variable (as stored in HDF5 file).
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def filters(
        self)
        
-    
        
-    
-
-    
-  
-    
        return dictionary containing HDF5 filter parameters.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def getValue(
        self)
        
-    
        
-    
-
-    
-  
-    
        get the value of a scalar variable.  Provided for compatibility with
-Scientific.IO.NetCDF, can also be done by slicing with an Ellipsis ([...]).
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def get_dims(
        self)
        
-    
        
-    
-
-    
-  
-    
        return a tuple of Dimension instances associated with this
-`netCDF4.Variable.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def get_var_chunk_cache(
        self)
        
-    
        
-    
-
-    
-  
-    
        return variable chunk cache information in a tuple (size,nelems,preemption).
-See netcdf C library documentation for nc_get_var_chunk_cache for
-details.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def getncattr(
        self,name)
        
-    
        
-    
-
-    
-  
-    
        retrieve a netCDF variable attribute.  Use if you need to set a
-netCDF attribute with the same name as one of the reserved python
-attributes.
        
-
        option kwarg encoding can be used to specify the
-character encoding of a string attribute (default is utf-8).
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def group(
        self)
        
-    
        
-    
-
-    
-  
-    
        return the group that this Variable is a member of.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def ncattrs(
        self)
        
-    
        
-    
-
-    
-  
-    
        return netCDF attribute names for this Variable in a list.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def renameAttribute(
        self, oldname, newname)
        
-    
        
-    
-
-    
-  
-    
        rename a Variable attribute named oldname to newname.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_always_mask(
        self,always_mask)
        
-    
        
-    
-
-    
-  
-    
        turn on or off conversion of data without missing values to regular
-numpy arrays.
        
-
        always_mask is a Boolean determining if automatic conversion of
-masked arrays with no missing values to regular numpy arrays shall be
-applied. Default is True. Set to False to restore the default behaviour
-in versions prior to 1.4.1 (numpy array returned unless missing values are present,
-otherwise masked array returned).
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_chartostring(
        self,chartostring)
        
-    
        
-    
-
-    
-  
-    
        turn on or off automatic conversion of character variable data to and
-from numpy fixed length string arrays when the _Encoding variable attribute
-is set.
        
-
        If chartostring is set to True, when data is read from a character variable
-(dtype = S1) that has an _Encoding attribute, it is converted to a numpy
-fixed length unicode string array (dtype = UN, where N is the length
-of the the rightmost dimension of the variable).  The value of _Encoding
-is the unicode encoding that is used to decode the bytes into strings.
        
-
        When numpy string data is written to a variable it is converted back to
-indiviual bytes, with the number of bytes in each string equalling the
-rightmost dimension of the variable.
        
-
        The default value of chartostring is True
-(automatic conversions are performed).
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_mask(
        self,mask)
        
-    
        
-    
-
-    
-  
-    
        turn on or off automatic conversion of variable data to and
-from masked arrays .
        
-
        If mask is set to True, when data is read from a variable
-it is converted to a masked array if any of the values are exactly
-equal to the either the netCDF _FillValue or the value specified by the
-missing_value variable attribute. The fill_value of the masked array
-is set to the missing_value attribute (if it exists), otherwise
-the netCDF _FillValue attribute (which has a default value
-for each data type).  When data is written to a variable, the masked
-array is converted back to a regular numpy array by replacing all the
-masked values by the missing_value attribute of the variable (if it
-exists).  If the variable has no missing_value attribute, the _FillValue
-is used instead. If the variable has valid_min/valid_max and
-missing_value attributes, data outside the specified range will be
-set to missing_value.
        
-
        The default value of mask is True
-(automatic conversions are performed).
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_maskandscale(
        self,maskandscale)
        
-    
        
-    
-
-    
-  
-    
        turn on or off automatic conversion of variable data to and
-from masked arrays, automatic packing/unpacking of variable
-data using scale_factor and add_offset attributes and
-automatic conversion of signed integer data to unsigned integer
-data if the _Unsigned attribute exists.
        
-
        If maskandscale is set to True, when data is read from a variable
-it is converted to a masked array if any of the values are exactly
-equal to the either the netCDF _FillValue or the value specified by the
-missing_value variable attribute. The fill_value of the masked array
-is set to the missing_value attribute (if it exists), otherwise
-the netCDF _FillValue attribute (which has a default value
-for each data type).  When data is written to a variable, the masked
-array is converted back to a regular numpy array by replacing all the
-masked values by the missing_value attribute of the variable (if it
-exists).  If the variable has no missing_value attribute, the _FillValue
-is used instead. If the variable has valid_min/valid_max and
-missing_value attributes, data outside the specified range will be
-set to missing_value.
        
-
        If maskandscale is set to True, and the variable has a
-scale_factor or an add_offset attribute, then data read
-from that variable is unpacked using::
        
-
        data = self.scale_factor*data + self.add_offset
-
        
-
-
-
        When data is written to a variable it is packed using::
        
-
        data = (data - self.add_offset)/self.scale_factor
-
        
-
-
-
        If either scale_factor is present, but add_offset is missing, add_offset
-is assumed zero.  If add_offset is present, but scale_factor is missing,
-scale_factor is assumed to be one.
-For more information on how scale_factor and add_offset can be
-used to provide simple compression, see the
-PSD metadata conventions.
        
-
        In addition, if maskandscale is set to True, and if the variable has an
-attribute _Unsigned set, and the variable has a signed integer data type,
-a view to the data is returned with the corresponding unsigned integer data type.
-This convention is used by the netcdf-java library to save unsigned integer
-data in NETCDF3 or NETCDF4_CLASSIC files (since the NETCDF3
-data model does not have unsigned integer data types).
        
-
        The default value of maskandscale is True
-(automatic conversions are performed).
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_auto_scale(
        self,scale)
        
-    
        
-    
-
-    
-  
-    
        turn on or off automatic packing/unpacking of variable
-data using scale_factor and add_offset attributes.
-Also turns on and off automatic conversion of signed integer data
-to unsigned integer data if the variable has an _Unsigned
-attribute.
        
-
        If scale is set to True, and the variable has a
-scale_factor or an add_offset attribute, then data read
-from that variable is unpacked using::
        
-
        data = self.scale_factor*data + self.add_offset
-
        
-
-
-
        When data is written to a variable it is packed using::
        
-
        data = (data - self.add_offset)/self.scale_factor
-
        
-
-
-
        If either scale_factor is present, but add_offset is missing, add_offset
-is assumed zero.  If add_offset is present, but scale_factor is missing,
-scale_factor is assumed to be one.
-For more information on how scale_factor and add_offset can be
-used to provide simple compression, see the
-PSD metadata conventions.
        
-
        In addition, if scale is set to True, and if the variable has an
-attribute _Unsigned set, and the variable has a signed integer data type,
-a view to the data is returned with the corresponding unsigned integer datatype.
-This convention is used by the netcdf-java library to save unsigned integer
-data in NETCDF3 or NETCDF4_CLASSIC files (since the NETCDF3
-data model does not have unsigned integer data types).
        
-
        The default value of scale is True
-(automatic conversions are performed).
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_collective(
        self,True_or_False)
        
-    
        
-    
-
-    
-  
-    
        turn on or off collective parallel IO access. Ignored if file is not
-open for parallel access.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_ncstring_attrs(
        ...)
        
-    
        
-    
-
-    
-  
-    
        turn on or off creating NC_STRING string attributes.
        
-
        If ncstring_attrs is set to True then text attributes will be variable-length
-NC_STRINGs.
        
-
        The default value of ncstring_attrs is False (writing ascii text attributes as
-NC_CHAR).
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def set_var_chunk_cache(
        self,size=None,nelems=None,preemption=None)
        
-    
        
-    
-
-    
-  
-    
        change variable chunk cache settings.
-See netcdf C library documentation for nc_set_var_chunk_cache for
-details.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def setncattr(
        self,name,value)
        
-    
        
-    
-
-    
-  
-    
        set a netCDF variable attribute using name,value pair.  Use if you need to set a
-netCDF attribute with the same name as one of the reserved python
-attributes.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def setncattr_string(
        self,name,value)
        
-    
        
-    
-
-    
-  
-    
        set a netCDF variable string attribute using name,value pair.
-Use if you need to ensure that a netCDF attribute is created with type
-NC_STRING if the file format is NETCDF4.
-Use if you need to set an attribute to an array of variable-length strings.
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def setncatts(
        self,attdict)
        
-    
        
-    
-
-    
-  
-    
        set a bunch of netCDF variable attributes at once using a python dictionary.
-This may be faster when setting a lot of attributes for a NETCDF3
-formatted file, since nc_redef/nc_enddef is not called in between setting
-each attribute
        
-  
        
-
        
-
-  
        
-  
-            
-  
        
-    
        
-    
        def use_nc_get_vars(
        self,_use_get_vars)
        
-    
        
-    
-
-    
-  
-    
        enable the use of netcdf library routine nc_get_vars
-to retrieve strided variable slices.  By default,
-nc_get_vars may not used by default (depending on the
-version of the netcdf-c library being used) since it may be
-slower than multiple calls to the unstrided read routine nc_get_vara.
        
-  
        
-
        
-
-  
        
-  
-      
        
-      
        
-
-  
        
-
-    
        
-  
         
        
-  
-
        
-
-

From b411ac9f43b8fde2f415969ac2af1f939626c5ae Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 21 Jan 2021 09:08:34 -0700
Subject: [PATCH 0543/1504] update

---
 MANIFEST.in | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/MANIFEST.in b/MANIFEST.in
index 8e4076ea2..33b12e54c 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -1,4 +1,4 @@
-recursive-include docs *
+include docs/index.html
 recursive-include man *
 include MANIFEST.in
 include Changelog

From c48ed2eaf773fdf2c1462f0062d8e20ce0a2ca27 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 21 Jan 2021 09:08:43 -0700
Subject: [PATCH 0544/1504] update

---
 create_docs.sh | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/create_docs.sh b/create_docs.sh
index c4afc759c..058e0f2c4 100644
--- a/create_docs.sh
+++ b/create_docs.sh
@@ -1,5 +1,6 @@
 # Uses pdoc (https://github.com/mitmproxy/pdoc)
 # to create html docs from docstrings in Cython source.
-/Users/jwhitaker/.local/bin/pdoc -o 'docs' netCDF4
-# use resulting docs/netCDF4/_netCDF4.hml
+/Users/jwhitaker/.local/bin/pdoc -o 'docs' netCDF4 
+# use resulting docs/netCDF4/_netCDF4.html
+cp docs/netCDF4/_netCDF4.html docs/index.html
 

From 02394313b3bc542eb308afa7f883e970597f3698 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 21 Jan 2021 10:22:59 -0700
Subject: [PATCH 0545/1504] update

---
 docs/index.html | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index b0880787c..c8b347f51 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -1621,7 +1621,7 @@ 
        In-memory (diskless) Datasets
        
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
        
 
-
        contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
        
+
        contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
        
 
 
        copyright: 2008 by Jeffrey Whitaker.
        
 
@@ -2138,7 +2138,7 @@ 
        In-memory (diskless) Datasets
        
 data will be quantized using numpy.around(scale*data)/scale, where
 scale = 2**bits, and bits is determined so that a precision of 0.1 is
 retained (in this case bits=4). From the
-PSD metadata conventions:
+PSL metadata conventions:
 "least_significant_digit -- power of ten of the smallest decimal place
 in unpacked data that is a reliable value." Default is None, or no
 quantization, or 'lossless' compression.
        
@@ -3057,7 +3057,7 @@ 
        In-memory (diskless) Datasets
        
 data will be quantized using numpy.around(scale*data)/scale, where
 scale = 2**bits, and bits is determined so that a precision of 0.1 is
 retained (in this case bits=4). From the
-PSD metadata conventions:
+PSL metadata conventions:
 "least_significant_digit -- power of ten of the smallest decimal place
 in unpacked data that is a reliable value." Default is None, or no
 quantization, or 'lossless' compression.
        
@@ -4164,7 +4164,7 @@ 
        Inherited Members
        
 scale_factor is assumed to be one.
 For more information on how scale_factor and add_offset can be
 used to provide simple compression, see the
-PSD metadata conventions.
        
+PSL metadata conventions.
        
 
 
        In addition, if maskandscale is set to True, and if the variable has an
 attribute _Unsigned set, and the variable has a signed integer data type,
@@ -4214,7 +4214,7 @@ 
        Inherited Members
        
 scale_factor is assumed to be one.
 For more information on how scale_factor and add_offset can be
 used to provide simple compression, see the
-PSD metadata conventions.
        
+PSL metadata conventions.
        
 
 
        In addition, if scale is set to True, and if the variable has an
 attribute _Unsigned set, and the variable has a signed integer data type,
@@ -5248,7 +5248,7 @@ 
        Inherited Members
        
 data will be quantized using numpy.around(scale*data)/scale, where
 scale = 2**bits, and bits is determined so that a precision of 0.1 is
 retained (in this case bits=4). From the
-PSD metadata conventions:
+PSL metadata conventions:
 "least_significant_digit -- power of ten of the smallest decimal place
 in unpacked data that is a reliable value." Default is None, or no
 quantization, or 'lossless' compression.
        

From 2f93b472d8336f88cb4fe2957a17369481d18d0c Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 21 Jan 2021 10:29:49 -0700
Subject: [PATCH 0546/1504] update

---
 README.gh-pages | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/README.gh-pages b/README.gh-pages
index b2a31d0d4..20ef493c8 100644
--- a/README.gh-pages
+++ b/README.gh-pages
@@ -7,6 +7,8 @@ installing github master),
 
 * generate docs (sh create_docs.sh)
 * copy docs/netCDF4/_netCDF.html top level index.html (cp docs/netCDF4/_netCDF4.html docs/index.html)
+  edit docs/index.html and clean up as needed.
+* cp docs/index.html ../
 * git checkout gh-pages
 * cp ../index.html .
 * git commit index.html

From 92b12bab4b097e1a6da230505f5af6dee58d0a2d Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 22 Jan 2021 09:23:30 -0700
Subject: [PATCH 0547/1504] change PSD to PSL

---
 docs/index.html          | 2 +-
 src/netCDF4/_netCDF4.pyx | 6 +++---
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index c8b347f51..741ad3916 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -1621,7 +1621,7 @@ 
        In-memory (diskless) Datasets
        
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
        
 
-
        contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
        
+
        contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
        
 
 
        copyright: 2008 by Jeffrey Whitaker.
        
 
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index faeb18217..1edac9262 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2733,7 +2733,7 @@ efficient compression. For example, if `least_significant_digit=1`,
 data will be quantized using `numpy.around(scale*data)/scale`, where
 scale = 2**bits, and bits is determined so that a precision of 0.1 is
 retained (in this case bits=4). From the
-[PSD metadata conventions](http://www.esrl.noaa.gov/psd/data/gridded/conventions/cdc_netcdf_standard.shtml):
+[PSL metadata conventions](http://www.esrl.noaa.gov/psl/data/gridded/conventions/cdc_netcdf_standard.shtml):
 "least_significant_digit -- power of ten of the smallest decimal place
 in unpacked data that is a reliable value." Default is `None`, or no
 quantization, or 'lossless' compression.
@@ -5016,7 +5016,7 @@ is assumed zero.  If add_offset is present, but scale_factor is missing,
 scale_factor is assumed to be one.
 For more information on how `scale_factor` and `add_offset` can be
 used to provide simple compression, see the
-[PSD metadata conventions](http://www.esrl.noaa.gov/psd/data/gridded/conventions/cdc_netcdf_standard.shtml).
+[PSL metadata conventions](http://www.esrl.noaa.gov/psl/data/gridded/conventions/cdc_netcdf_standard.shtml).
 
 In addition, if `maskandscale` is set to `True`, and if the variable has an
 attribute `_Unsigned` set, and the variable has a signed integer data type,
@@ -5055,7 +5055,7 @@ is assumed zero.  If add_offset is present, but scale_factor is missing,
 scale_factor is assumed to be one.
 For more information on how `scale_factor` and `add_offset` can be
 used to provide simple compression, see the
-[PSD metadata conventions](http://www.esrl.noaa.gov/psd/data/gridded/conventions/cdc_netcdf_standard.shtml).
+[PSL metadata conventions](http://www.esrl.noaa.gov/psl/data/gridded/conventions/cdc_netcdf_standard.shtml).
 
 In addition, if `scale` is set to `True`, and if the variable has an
 attribute `_Unsigned` set, and the variable has a signed integer data type,

From 5c2f88a27ffba4cf777268caaa67c530dc4f4359 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 22 Jan 2021 09:38:08 -0700
Subject: [PATCH 0548/1504] update

---
 README.gh-pages | 16 ----------------
 README.htmldocs |  9 +++++++++
 2 files changed, 9 insertions(+), 16 deletions(-)
 delete mode 100644 README.gh-pages
 create mode 100644 README.htmldocs

diff --git a/README.gh-pages b/README.gh-pages
deleted file mode 100644
index 20ef493c8..000000000
--- a/README.gh-pages
+++ /dev/null
@@ -1,16 +0,0 @@
-To update web docs at http://github.unidata.io/netcdf4-python:
-
-First install pdoc (https://github.com/mitmproxy/pdoc)
-
-Then in netcdf4-python github clone directory (after building and 
-installing github master),
-
-* generate docs (sh create_docs.sh)
-* copy docs/netCDF4/_netCDF.html top level index.html (cp docs/netCDF4/_netCDF4.html docs/index.html)
-  edit docs/index.html and clean up as needed.
-* cp docs/index.html ../
-* git checkout gh-pages
-* cp ../index.html .
-* git commit index.html
-* git push origin gh-pages
-* git checkout master
diff --git a/README.htmldocs b/README.htmldocs
new file mode 100644
index 000000000..9f183e06c
--- /dev/null
+++ b/README.htmldocs
@@ -0,0 +1,9 @@
+To update web docs at http://github.unidata.io/netcdf4-python:
+
+First install pdoc (https://github.com/mitmproxy/pdoc)
+
+Then in netcdf4-python github clone directory (after building and 
+installing github master),
+
+* generate docs (sh create_docs.sh)
+* edit docs/index.html and clean up as needed.

From e8b455f90f9d72247d16eb93111ab357a7140a22 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 22 Jan 2021 09:45:08 -0700
Subject: [PATCH 0549/1504] update parallel io docs

---
 docs/index.html          | 8 ++++----
 src/netCDF4/_netCDF4.pyx | 6 +++---
 2 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 741ad3916..be61f1c13 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -1449,12 +1449,12 @@ 
        Parallel IO
        
 
      • parallel IO for NETCDF4 or NETCDF4_CLASSIC formatted files is only available
 if the netcdf library was compiled with MPI enabled HDF5.
        • 
 
      • parallel IO for all classic netcdf-3 file formats is only available if the
-netcdf library was compiled with PnetCDF.
        • 
+netcdf library was compiled with PnetCDF.
 
      • If a variable has an unlimited dimension, appending data must be done in collective mode.
 If the write is done in independent mode, the operation will fail with a
 a generic "HDF Error".
        • 
-
      • You cannot write compressed data in parallel (although
-you can read it).
        • 
+
      • You can write compressed data in parallel only with netcdf-c >= 4.7.4
+and hdf5 >= 1.10.3 (although you can read in parallel with earlier versions).
        • 
 
      • You cannot use variable-length (VLEN) data types.
        • 
 
      
 
@@ -1621,7 +1621,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 1edac9262..1ee2a5004 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1027,12 +1027,12 @@ are collective.  There are a couple of important limitations of parallel IO:
  - parallel IO for NETCDF4 or NETCDF4_CLASSIC formatted files is only available
    if the netcdf library was compiled with MPI enabled HDF5.
  - parallel IO for all classic netcdf-3 file formats is only available if the
-   netcdf library was compiled with PnetCDF.
+   netcdf library was compiled with [PnetCDF](https://parallel-netcdf.github.io).
  - If a variable has an unlimited dimension, appending data must be done in collective mode.
    If the write is done in independent mode, the operation will fail with a
    a generic "HDF Error".
- - You cannot write compressed data in parallel (although
-   you can read it).
+ - You can write compressed data in parallel only with netcdf-c >= 4.7.4
+   and hdf5 >= 1.10.3 (although you can read in parallel with earlier versions).
  - You cannot use variable-length (VLEN) data types.
 
 ## Dealing with strings

From 6cd97e9b5225629a054a1f8c2f6476c181765f0c Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 22 Jan 2021 10:54:46 -0700
Subject: [PATCH 0550/1504] fix broken link

---
 docs/index.html | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/index.html b/docs/index.html
index be61f1c13..fe00480b6 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -28,7 +28,7 @@
                 
      
                     
                     
-                            
+                            
                                 netCDF4
                         
                     

From a562d9b0ca90790d8d5711d57d2b36a62da50d13 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 22 Jan 2021 11:21:14 -0700
Subject: [PATCH 0551/1504] update

---
 create_docs.sh | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/create_docs.sh b/create_docs.sh
index 058e0f2c4..7d154e3a5 100644
--- a/create_docs.sh
+++ b/create_docs.sh
@@ -3,4 +3,8 @@
 /Users/jwhitaker/.local/bin/pdoc -o 'docs' netCDF4 
 # use resulting docs/netCDF4/_netCDF4.html
 cp docs/netCDF4/_netCDF4.html docs/index.html
+sed -i -e 's!href="../netCDF4.html!href="./index.html!g' docs/index.html
+sed -i -e 's!/../netCDF4.html!/index.html!g' docs/index.html
+sed -i -e 's!._netCDF4 API! API!g' docs/index.html
+sed -i -e 's!netCDF4._netCDF4
    !netCDF4
    !g' docs/index.html
 

From d2838a3e420418e7eed5eea8a0ccbf9bf22b5548 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Wed, 27 Jan 2021 09:12:09 -0700
Subject: [PATCH 0552/1504] make cftime an optional dependency (everything will
 work except MFTime)

---
 .github/workflows/build.yml |  2 +-
 setup.py                    |  2 +-
 src/netCDF4/__init__.py     |  7 +++-
 src/netCDF4/_netCDF4.pyx    | 26 ++++++------
 test/tst_multifile.py       | 79 +++++++++++++++++++------------------
 test/tst_multifile2.py      | 63 ++++++++++++++++-------------
 6 files changed, 99 insertions(+), 80 deletions(-)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index f3e4263b2..3421c28c2 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -56,7 +56,7 @@ jobs:
     - name: Install python dependencies via pip
       run: |
         python -m pip install --upgrade pip
-        pip install numpy cython cftime pytest twine wheel check-manifest mpi4py
+        pip install numpy cython pytest twine wheel check-manifest mpi4py
 
     - name: Install netcdf4-python
       run: |
diff --git a/setup.py b/setup.py
index 8a61a5e74..4f2a24666 100644
--- a/setup.py
+++ b/setup.py
@@ -4,7 +4,7 @@
 from distutils.dist import Distribution
 
 setuptools_extra_kwargs = {
-    "install_requires": ["numpy>=1.9","cftime"],
+    "install_requires": ["numpy>=1.9"],
     "setup_requires": ['setuptools>=18.0', "cython>=0.19"],
     "entry_points": {
         'console_scripts': [
diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py
index 4ddc07fdf..244fb809a 100644
--- a/src/netCDF4/__init__.py
+++ b/src/netCDF4/__init__.py
@@ -9,4 +9,9 @@
                        __has_nc_create_mem__, __has_cdf5_format__,
                        __has_parallel4_support__, __has_pnetcdf_support__)
 __all__ =\
-['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
+['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
+try:
+    from cftime import date2num, num2date, date2index
+    __all__ += [date2num, num2date, date2index]
+except ImportError:
+    pass
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 1ee2a5004..d2c168bb2 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -36,9 +36,6 @@ types) are not supported.
  - [Cython](http://cython.org), version 0.21 or later.
  - [setuptools](https://pypi.python.org/pypi/setuptools), version 18.0 or
    later.
- - [cftime](https://github.com/Unidata/cftime) for
- the time and date handling utility functions (`num2date`,
- `date2num` and `date2index`).
  - The HDF5 C library version 1.8.4-patch1 or higher (1.8.x recommended)
  from [](ftp://ftp.hdfgroup.org/HDF5/current/src).
  ***netCDF version 4.4.1 or higher is recommended if using HDF5 1.10.x -
@@ -63,6 +60,12 @@ types) are not supported.
  Parallel IO further depends on the existence of MPI-enabled HDF5 or the
  [PnetCDF](https://parallel-netcdf.github.io/) library.
 
+## Optional
+ - [cftime](https://github.com/Unidata/cftime) for
+ the time and date handling utility functions (`num2date`,
+ `date2num` and `date2index`) are imported into the netCDF4 namespace if available.
+ The [MFTime](#MFTime) class will not work if cftime not installed.
+
 
 ## Install
 
@@ -594,17 +597,15 @@ metadata standards (such as CF) specify that time should be
 measure relative to a fixed date using a certain calendar, with units
 specified like `hours since YY-MM-DD hh:mm:ss`.  These units can be
 awkward to deal with, without a utility to convert the values to and
-from calendar dates.  The function called [num2date](https://unidata.github.io/cftime/api.html)
+from calendar dates.  The functions[num2date](https://unidata.github.io/cftime/api.html)
 and [date2num](https://unidata.github.io/cftime/api.html) are
-provided with this package to do just that (starting with version 1.4.0, the
-[cftime](https://unidata.github.io/cftime) package must be installed
-separately).  Here's an example of how they
-can be used:
+provided by [cftime](https://unidata.github.io/cftime) to do just that.
+Here's an example of how they can be used:
 
 ```python
 >>> # fill in times.
 >>> from datetime import datetime, timedelta
->>> from netCDF4 import num2date, date2num
+>>> from cftime import num2date, date2num # requires the cftime package
 >>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
 >>> times[:] = date2num(dates,units=times.units,calendar=times.calendar)
 >>> print("time values (in units {}):\\n{}".format(times.units, times[:]))
@@ -1020,7 +1021,7 @@ depend on or be affected by other processes. Collective IO is a way of doing
 IO defined in the MPI-IO standard; unlike independent IO, all processes must
 participate in doing IO. To toggle back and forth between
 the two types of IO, use the [Variable.set_collective](#Variable.set_collective)
-[Variable](#Variable)method. All metadata
+[Variable](#Variable) method. All metadata
 operations (such as creation of groups, types, variables, dimensions, or attributes)
 are collective.  There are a couple of important limitations of parallel IO:
 
@@ -1235,7 +1236,6 @@ __version__ = "1.5.6"
 
 # Initialize numpy
 import posixpath
-from cftime import num2date, date2num, date2index
 import numpy
 import weakref
 import warnings
@@ -6600,6 +6600,10 @@ days since 2000-01-01
         `ValueError` otherwise.
         """
         import datetime
+        try:
+            from cftime import date2num
+        except ImportError:
+            raise ImportError('cftime required to use MFTime class')
         self.__time = time
 
         # copy attributes from master time variable.
diff --git a/test/tst_multifile.py b/test/tst_multifile.py
index 770281ee4..92999e273 100644
--- a/test/tst_multifile.py
+++ b/test/tst_multifile.py
@@ -4,7 +4,12 @@
 from numpy.testing import assert_array_equal, assert_equal
 from numpy import ma
 import tempfile, unittest, os, datetime
-import cftime
+try:
+    import cftime
+    has_cftime=True
+except ImportError:
+    has_cftime=False
+    
 from pkg_resources import parse_version
 
 nx=100; ydim=5; zdim=10
@@ -118,50 +123,48 @@ def runTest(self):
         # The test files have no calendar attribute on the time variable.
         calendar = 'standard'
 
-        # Get the real dates
-        # skip this until cftime pull request #55 is in a released
-        # version (1.0.1?). Otherwise, fix for issue #808 breaks this
-        if parse_version(cftime.__version__) >= parse_version('1.0.1'):
+        if has_cftime:
+            # Get the real dates
             dates = []
             for file in self.files:
                 f = Dataset(file)
                 t = f.variables['time']
                 dates.extend(num2date(t[:], t.units, calendar))
                 f.close()
+            # Compare with the MF dates
+            f = MFDataset(self.files,check=True)
+            t = f.variables['time']
+            T = MFTime(t, calendar=calendar)
+            assert_equal(T.calendar, calendar)
+            assert_equal(len(T), len(t))
+            assert_equal(T.shape, t.shape)
+            assert_equal(T.dimensions, t.dimensions)
+            assert_equal(T.typecode(), t.typecode())
+            # skip this until cftime pull request #55 is in a released
+            # version (1.0.1?). Otherwise, fix for issue #808 breaks this
+            if parse_version(cftime.__version__) >= parse_version('1.0.1'):
+                assert_array_equal(num2date(T[:], T.units, T.calendar), dates)
+            assert_equal(date2index(datetime.datetime(1980, 1, 2), T), 366)
+            f.close()
 
-        # Compare with the MF dates
-        f = MFDataset(self.files,check=True)
-        t = f.variables['time']
-
-        T = MFTime(t, calendar=calendar)
-        assert_equal(T.calendar, calendar)
-        assert_equal(len(T), len(t))
-        assert_equal(T.shape, t.shape)
-        assert_equal(T.dimensions, t.dimensions)
-        assert_equal(T.typecode(), t.typecode())
-        # skip this until cftime pull request #55 is in a released
-        # version (1.0.1?). Otherwise, fix for issue #808 breaks this
-        if parse_version(cftime.__version__) >= parse_version('1.0.1'):
-            assert_array_equal(num2date(T[:], T.units, T.calendar), dates)
-        assert_equal(date2index(datetime.datetime(1980, 1, 2), T), 366)
-        f.close()
-
-        # Test exception is raised when no calendar attribute is available on the
-        # time variable.
-        with MFDataset(self.files, check=True) as ds:
-            with self.assertRaises(ValueError):
-                MFTime(ds.variables['time'])
-
-        # Test exception is raised when the calendar attribute is different on the
-        # variables. First, add calendar attributes to file. Note this will modify
-        # the files inplace.
-        calendars = ['standard', 'gregorian']
-        for idx, f in enumerate(self.files):
-            with Dataset(f, 'a') as ds:
-                ds.variables['time'].calendar = calendars[idx]
-        with MFDataset(self.files, check=True) as ds:
-            with self.assertRaises(ValueError):
-                MFTime(ds.variables['time'])
+            # Test exception is raised when no calendar attribute is available on the
+            # time variable.
+            with MFDataset(self.files, check=True) as ds:
+                with self.assertRaises(ValueError):
+                    MFTime(ds.variables['time'])
+
+            # Test exception is raised when the calendar attribute is different on the
+            # variables. First, add calendar attributes to file. Note this will modify
+            # the files inplace.
+            calendars = ['standard', 'gregorian']
+            for idx, f in enumerate(self.files):
+                with Dataset(f, 'a') as ds:
+                    ds.variables['time'].calendar = calendars[idx]
+            with MFDataset(self.files, check=True) as ds:
+                with self.assertRaises(ValueError):
+                    MFTime(ds.variables['time'])
+        else:
+            print('skipping MFTime tests since cftime not installed...')
 
 
 if __name__ == '__main__':
diff --git a/test/tst_multifile2.py b/test/tst_multifile2.py
index 6da040b6a..cdbecdea1 100644
--- a/test/tst_multifile2.py
+++ b/test/tst_multifile2.py
@@ -4,7 +4,11 @@
 from numpy.testing import assert_array_equal, assert_equal
 from numpy import ma
 import tempfile, unittest, os, datetime
-import cftime
+try:
+    import cftime
+    has_cftime=True
+except ImportError:
+    has_cftime=False
 from pkg_resources import parse_version
 
 nx=100; ydim=5; zdim=10
@@ -103,33 +107,36 @@ def tearDown(self):
 
 
     def runTest(self):
-        # Get the real dates
-        # skip this until cftime pull request #55 is in a released
-        # version (1.0.1?). Otherwise, fix for issue #808 breaks this
-        if parse_version(cftime.__version__) >= parse_version('1.0.1'):
-            dates = []
-            for file in self.files:
-                f = Dataset(file)
-                t = f.variables['time']
-                dates.extend(num2date(t[:], t.units, t.calendar))
-                f.close()
-
-        # Compare with the MF dates
-        f = MFDataset(self.files,check=True)
-        t = f.variables['time']
-        mfdates = num2date(t[:], t.units, t.calendar)
-
-        T = MFTime(t)
-        assert_equal(len(T), len(t))
-        assert_equal(T.shape, t.shape)
-        assert_equal(T.dimensions, t.dimensions)
-        assert_equal(T.typecode(), t.typecode())
-        # skip this until cftime pull request #55 is in a released
-        # version (1.0.1?). Otherwise, fix for issue #808 breaks this
-        if parse_version(cftime.__version__) >= parse_version('1.0.1'):
-            assert_array_equal(num2date(T[:], T.units, T.calendar), dates)
-        assert_equal(date2index(datetime.datetime(1980, 1, 2), T), 366)
-        f.close()
+        if has_cftime:
+            # Get the real dates
+            # skip this until cftime pull request #55 is in a released
+            # version (1.0.1?). Otherwise, fix for issue #808 breaks this
+            if parse_version(cftime.__version__) >= parse_version('1.0.1'):
+                dates = []
+                for file in self.files:
+                    f = Dataset(file)
+                    t = f.variables['time']
+                    dates.extend(num2date(t[:], t.units, t.calendar))
+                    f.close()
+
+            # Compare with the MF dates
+            f = MFDataset(self.files,check=True)
+            t = f.variables['time']
+            mfdates = num2date(t[:], t.units, t.calendar)
+
+            T = MFTime(t)
+            assert_equal(len(T), len(t))
+            assert_equal(T.shape, t.shape)
+            assert_equal(T.dimensions, t.dimensions)
+            assert_equal(T.typecode(), t.typecode())
+            # skip this until cftime pull request #55 is in a released
+            # version (1.0.1?). Otherwise, fix for issue #808 breaks this
+            if parse_version(cftime.__version__) >= parse_version('1.0.1'):
+                assert_array_equal(num2date(T[:], T.units, T.calendar), dates)
+            assert_equal(date2index(datetime.datetime(1980, 1, 2), T), 366)
+            f.close()
+        else:
+            print('skipping MFTime tests since cftime not installed...')
 
 if __name__ == '__main__':
     unittest.main()

From a833440eb3c819ac509e1f3b215e29e89996b3c3 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Wed, 27 Jan 2021 09:13:28 -0700
Subject: [PATCH 0553/1504] update

---
 Changelog | 1 +
 1 file changed, 1 insertion(+)

diff --git a/Changelog b/Changelog
index 32cb5a21b..c47bbb742 100644
--- a/Changelog
+++ b/Changelog
@@ -5,6 +5,7 @@
  * change numpy.bool to numpy.bool_ and numpy.float to numpy.float_ (float and
    bool are deprecated in numpy 1.20, issue #1065)
  * clean up docstrings so that they work with latest pdoc.
+ * make cftime an optional dependency (issue #1073).
 
  version 1.5.5.1 (tag v1.5.5.1rel)
 ==================================

From a3d6538dba354b5f20fb477a1a2ac98aa34698a9 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Wed, 27 Jan 2021 09:15:53 -0700
Subject: [PATCH 0554/1504] update

---
 docs/index.html | 27 ++++++++++++++++-----------
 1 file changed, 16 insertions(+), 11 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index fe00480b6..f735d60f5 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -43,6 +43,7 @@ 
    Contents
    
 
 
  • Tutorial
@@ -496,9 +497,6 @@ 
    Requires
    
 
  • Cython, version 0.21 or later.
    • 
 
  • setuptools, version 18.0 or
 later.
    • 
-
  • cftime for
-the time and date handling utility functions (num2date,
-date2num and date2index).
    • 
 
  • The HDF5 C library version 1.8.4-patch1 or higher (1.8.x recommended)
 from .
 netCDF version 4.4.1 or higher is recommended if using HDF5 1.10.x -
@@ -524,6 +522,15 @@ 
    Requires
    
 PnetCDF library.
    • 
 
 
+
    Optional
    
+
+
      
+
    • cftime for
+the time and date handling utility functions (num2date,
+date2num and date2index) are imported into the netCDF4 namespace if available.
+The MFTime class will not work if cftime not installed.
      • 
+
    
+
 
    Install
    
 
 
      
@@ -1032,16 +1039,14 @@ 
      Dealing with time coordinates
      
 measure relative to a fixed date using a certain calendar, with units
 specified like hours since YY-MM-DD hh:mm:ss.  These units can be
 awkward to deal with, without a utility to convert the values to and
-from calendar dates.  The function called num2date
+from calendar dates.  The functionsnum2date
 and date2num are
-provided with this package to do just that (starting with version 1.4.0, the
-cftime package must be installed
-separately).  Here's an example of how they
-can be used:
      
+provided by cftime to do just that.
+Here's an example of how they can be used:
      
 
 
      >>> # fill in times.
 >>> from datetime import datetime, timedelta
->>> from netCDF4 import num2date, date2num
+>>> from cftime import num2date, date2num # requires the cftime package
 >>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
 >>> times[:] = date2num(dates,units=times.units,calendar=times.calendar)
 >>> print("time values (in units {}):\n{}".format(times.units, times[:]))
@@ -1441,7 +1446,7 @@ 
      Parallel IO
      
 IO defined in the MPI-IO standard; unlike independent IO, all processes must
 participate in doing IO. To toggle back and forth between
 the two types of IO, use the Variable.set_collective
-Variablemethod. All metadata
+Variable method. All metadata
 operations (such as creation of groups, types, variables, dimensions, or attributes)
 are collective.  There are a couple of important limitations of parallel IO:
      
 
@@ -1621,7 +1626,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 

From ff27571731c261d7a51fa7429bc046ee5395531b Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Wed, 27 Jan 2021 09:25:38 -0700
Subject: [PATCH 0555/1504] fix import

---
 test/tst_multifile.py  | 3 ++-
 test/tst_multifile2.py | 3 ++-
 2 files changed, 4 insertions(+), 2 deletions(-)

diff --git a/test/tst_multifile.py b/test/tst_multifile.py
index 92999e273..3a93128b1 100644
--- a/test/tst_multifile.py
+++ b/test/tst_multifile.py
@@ -1,4 +1,4 @@
-from netCDF4 import Dataset, MFDataset, MFTime, num2date, date2num, date2index
+from netCDF4 import Dataset, MFDataset, MFTime
 import numpy as np
 from numpy.random import seed, randint
 from numpy.testing import assert_array_equal, assert_equal
@@ -7,6 +7,7 @@
 try:
     import cftime
     has_cftime=True
+    from netCDF4 import date2num, num2date, date2index
 except ImportError:
     has_cftime=False
     
diff --git a/test/tst_multifile2.py b/test/tst_multifile2.py
index cdbecdea1..9c1186cff 100644
--- a/test/tst_multifile2.py
+++ b/test/tst_multifile2.py
@@ -1,4 +1,4 @@
-from netCDF4 import Dataset, MFDataset, MFTime, num2date, date2num, date2index
+from netCDF4 import Dataset, MFDataset, MFTime
 import numpy as np
 from numpy.random import seed, randint
 from numpy.testing import assert_array_equal, assert_equal
@@ -7,6 +7,7 @@
 try:
     import cftime
     has_cftime=True
+    from netCDF4 import date2num, num2date, date2index
 except ImportError:
     has_cftime=False
 from pkg_resources import parse_version

From 6355dada8062e16cc19e360ab80303082810b089 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Wed, 27 Jan 2021 09:34:37 -0700
Subject: [PATCH 0556/1504] update

---
 MANIFEST.in | 1 +
 1 file changed, 1 insertion(+)

diff --git a/MANIFEST.in b/MANIFEST.in
index 33b12e54c..55dc709ac 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -1,6 +1,7 @@
 include docs/index.html
 recursive-include man *
 include MANIFEST.in
+include README.htmldocs
 include Changelog
 include setup.cfg
 include examples/*py

From 8d6aa1f3ada56894f20f4dad7010c71c52ab7545 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Wed, 27 Jan 2021 09:52:33 -0700
Subject: [PATCH 0557/1504] change message

---
 test/tst_multifile.py  | 2 +-
 test/tst_multifile2.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/test/tst_multifile.py b/test/tst_multifile.py
index 3a93128b1..da79d6622 100644
--- a/test/tst_multifile.py
+++ b/test/tst_multifile.py
@@ -165,7 +165,7 @@ def runTest(self):
                 with self.assertRaises(ValueError):
                     MFTime(ds.variables['time'])
         else:
-            print('skipping MFTime tests since cftime not installed...')
+            print('skipping MFTime test 1 (of 2) since cftime not installed...')
 
 
 if __name__ == '__main__':
diff --git a/test/tst_multifile2.py b/test/tst_multifile2.py
index 9c1186cff..17e0c6ea3 100644
--- a/test/tst_multifile2.py
+++ b/test/tst_multifile2.py
@@ -137,7 +137,7 @@ def runTest(self):
             assert_equal(date2index(datetime.datetime(1980, 1, 2), T), 366)
             f.close()
         else:
-            print('skipping MFTime tests since cftime not installed...')
+            print('skipping MFTime test 2 (of 2) since cftime not installed...')
 
 if __name__ == '__main__':
     unittest.main()

From 64abcd7a51620aa844010ce915913e5ddbda0a8c Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 27 Jan 2021 19:44:01 -0700
Subject: [PATCH 0558/1504] update

---
 Changelog               | 4 +++-
 src/netCDF4/__init__.py | 5 -----
 test/tst_multifile.py   | 7 +++----
 test/tst_multifile2.py  | 9 ++++-----
 4 files changed, 10 insertions(+), 15 deletions(-)

diff --git a/Changelog b/Changelog
index c47bbb742..22e359cbb 100644
--- a/Changelog
+++ b/Changelog
@@ -5,7 +5,9 @@
  * change numpy.bool to numpy.bool_ and numpy.float to numpy.float_ (float and
    bool are deprecated in numpy 1.20, issue #1065)
  * clean up docstrings so that they work with latest pdoc.
- * make cftime an optional dependency (issue #1073).
+ * make cftime an optional dependency (issue #1073), an import is only
+   attempted if MFTime is used.  date2num,num2date and date2index no longer
+   imported into netCDF4 namespace.
 
  version 1.5.5.1 (tag v1.5.5.1rel)
 ==================================
diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py
index 244fb809a..9fc7a8540 100644
--- a/src/netCDF4/__init__.py
+++ b/src/netCDF4/__init__.py
@@ -10,8 +10,3 @@
                        __has_parallel4_support__, __has_pnetcdf_support__)
 __all__ =\
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
-try:
-    from cftime import date2num, num2date, date2index
-    __all__ += [date2num, num2date, date2index]
-except ImportError:
-    pass
diff --git a/test/tst_multifile.py b/test/tst_multifile.py
index da79d6622..945de8b6a 100644
--- a/test/tst_multifile.py
+++ b/test/tst_multifile.py
@@ -7,7 +7,6 @@
 try:
     import cftime
     has_cftime=True
-    from netCDF4 import date2num, num2date, date2index
 except ImportError:
     has_cftime=False
     
@@ -130,7 +129,7 @@ def runTest(self):
             for file in self.files:
                 f = Dataset(file)
                 t = f.variables['time']
-                dates.extend(num2date(t[:], t.units, calendar))
+                dates.extend(cftime.num2date(t[:], t.units, calendar))
                 f.close()
             # Compare with the MF dates
             f = MFDataset(self.files,check=True)
@@ -144,8 +143,8 @@ def runTest(self):
             # skip this until cftime pull request #55 is in a released
             # version (1.0.1?). Otherwise, fix for issue #808 breaks this
             if parse_version(cftime.__version__) >= parse_version('1.0.1'):
-                assert_array_equal(num2date(T[:], T.units, T.calendar), dates)
-            assert_equal(date2index(datetime.datetime(1980, 1, 2), T), 366)
+                assert_array_equal(cftime.num2date(T[:], T.units, T.calendar), dates)
+            assert_equal(cftime.date2index(datetime.datetime(1980, 1, 2), T), 366)
             f.close()
 
             # Test exception is raised when no calendar attribute is available on the
diff --git a/test/tst_multifile2.py b/test/tst_multifile2.py
index 17e0c6ea3..64e9b82ae 100644
--- a/test/tst_multifile2.py
+++ b/test/tst_multifile2.py
@@ -7,7 +7,6 @@
 try:
     import cftime
     has_cftime=True
-    from netCDF4 import date2num, num2date, date2index
 except ImportError:
     has_cftime=False
 from pkg_resources import parse_version
@@ -117,13 +116,13 @@ def runTest(self):
                 for file in self.files:
                     f = Dataset(file)
                     t = f.variables['time']
-                    dates.extend(num2date(t[:], t.units, t.calendar))
+                    dates.extend(cftime.num2date(t[:], t.units, t.calendar))
                     f.close()
 
             # Compare with the MF dates
             f = MFDataset(self.files,check=True)
             t = f.variables['time']
-            mfdates = num2date(t[:], t.units, t.calendar)
+            mfdates = cftime.num2date(t[:], t.units, t.calendar)
 
             T = MFTime(t)
             assert_equal(len(T), len(t))
@@ -133,8 +132,8 @@ def runTest(self):
             # skip this until cftime pull request #55 is in a released
             # version (1.0.1?). Otherwise, fix for issue #808 breaks this
             if parse_version(cftime.__version__) >= parse_version('1.0.1'):
-                assert_array_equal(num2date(T[:], T.units, T.calendar), dates)
-            assert_equal(date2index(datetime.datetime(1980, 1, 2), T), 366)
+                assert_array_equal(cftime.num2date(T[:], T.units, T.calendar), dates)
+            assert_equal(cftime.date2index(datetime.datetime(1980, 1, 2), T), 366)
             f.close()
         else:
             print('skipping MFTime test 2 (of 2) since cftime not installed...')

From 6c872a2d6b036a166287975395e50448b40730ce Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 27 Jan 2021 19:44:34 -0700
Subject: [PATCH 0559/1504] update

---
 src/netCDF4/_netCDF4.pyx | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index d2c168bb2..db70f17f2 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -62,8 +62,7 @@ types) are not supported.
 
 ## Optional
  - [cftime](https://github.com/Unidata/cftime) for
- the time and date handling utility functions (`num2date`,
- `date2num` and `date2index`) are imported into the netCDF4 namespace if available.
+ the time and date handling utility functions.
  The [MFTime](#MFTime) class will not work if cftime not installed.
 
 

From 39492ca3e92ac7abd1f7a36d111d1f8a3a5c2da9 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 27 Jan 2021 19:49:03 -0700
Subject: [PATCH 0560/1504] fix docstring formatting

---
 src/netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index db70f17f2..c857d7039 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -596,7 +596,7 @@ metadata standards (such as CF) specify that time should be
 measure relative to a fixed date using a certain calendar, with units
 specified like `hours since YY-MM-DD hh:mm:ss`.  These units can be
 awkward to deal with, without a utility to convert the values to and
-from calendar dates.  The functions[num2date](https://unidata.github.io/cftime/api.html)
+from calendar dates.  The functions [num2date](https://unidata.github.io/cftime/api.html)
 and [date2num](https://unidata.github.io/cftime/api.html) are
 provided by [cftime](https://unidata.github.io/cftime) to do just that.
 Here's an example of how they can be used:

From 18ecba795c62d954c04ec01167a76f35249e8b66 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 30 Jan 2021 19:58:43 -0700
Subject: [PATCH 0561/1504] get rid of deprecated numpy api warning

---
 include/netCDF4.pxi      | 11 ++++-------
 setup.py                 |  2 ++
 src/netCDF4/_netCDF4.pyx | 28 ++++++++++++++++------------
 3 files changed, 22 insertions(+), 19 deletions(-)

diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index 625752a68..6912ab53d 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -725,14 +725,11 @@ IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
 cdef extern from "numpy/arrayobject.h":
     ctypedef int npy_intp 
     ctypedef extern class numpy.ndarray [object PyArrayObject]:
-        cdef char *data
-        cdef int nd
-        cdef npy_intp *dimensions
-        cdef npy_intp *strides
-        cdef object base
-#       cdef dtype descr
-        cdef int flags
+        pass
     npy_intp PyArray_SIZE(ndarray arr)
     npy_intp PyArray_ISCONTIGUOUS(ndarray arr)
     npy_intp PyArray_ISALIGNED(ndarray arr)
+    void* PyArray_DATA(ndarray) nogil
+    char* PyArray_BYTES(ndarray) nogil
+    npy_intp* PyArray_STRIDES(ndarray) nogil
     void import_array()
diff --git a/setup.py b/setup.py
index 4f2a24666..0f9cfdd05 100644
--- a/setup.py
+++ b/setup.py
@@ -520,6 +520,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     sys.stdout.write('using netcdf library version %s\n' % netcdf_lib_version)
 
 cmdclass = {}
+DEFINE_MACROS = [("NPY_NO_DEPRECATED_API", "NPY_1_7_API_VERSION")]
 netcdf4_src_root = osp.join(osp.join('src','netCDF4'), '_netCDF4')
 netcdf4_src_c = netcdf4_src_root + '.c'
 netcdf4_src_pyx = netcdf4_src_root + '.pyx'
@@ -616,6 +617,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 
     ext_modules = [Extension("netCDF4._netCDF4",
                              [netcdf4_src_pyx],
+                             define_macros=DEFINE_MACROS,
                              libraries=libs,
                              library_dirs=lib_dirs,
                              include_dirs=inc_dirs + ['include'],
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index c857d7039..99befb036 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1475,7 +1475,8 @@ cdef _get_att(grp, int varid, name, encoding='utf-8'):
     if att_type == NC_CHAR:
         value_arr = numpy.empty(att_len,'S1')
         with nogil:
-            ierr = nc_get_att_text(_grpid, varid, attname, value_arr.data)
+            ierr = nc_get_att_text(_grpid, varid, attname,
+                    PyArray_BYTES(value_arr))
         _ensure_nc_success(ierr, err_cls=AttributeError)
         if name == '_FillValue' and python3:
             # make sure _FillValue for character arrays is a byte on python 3
@@ -1525,7 +1526,7 @@ cdef _get_att(grp, int varid, name, encoding='utf-8'):
                 except:
                     raise KeyError('attribute %s has unsupported datatype' % attname)
         with nogil:
-            ierr = nc_get_att(_grpid, varid, attname, value_arr.data)
+            ierr = nc_get_att(_grpid, varid, attname, PyArray_BYTES(value_arr))
         _ensure_nc_success(ierr, err_cls=AttributeError)
         if value_arr.shape == ():
             # return a scalar for a scalar array
@@ -1679,7 +1680,8 @@ be raised in the next release."""
         elif xtype == -99: # if xtype is not passed in as kwarg.
             xtype = _nptonctype[value_arr.dtype.str[1:]]
         lenarr = PyArray_SIZE(value_arr)
-        ierr = nc_put_att(grp._grpid, varid, attname, xtype, lenarr, value_arr.data)
+        ierr = nc_put_att(grp._grpid, varid, attname, xtype, lenarr,
+                PyArray_DATA(value_arr))
         _ensure_nc_success(ierr, err_cls=AttributeError)
 
 cdef _get_types(group):
@@ -4752,7 +4754,7 @@ rename a [Variable](#Variable) attribute named `oldname` to `newname`."""
             data2 = data
             vldata = malloc(sizeof(nc_vlen_t))
             vldata[0].len = PyArray_SIZE(data2)
-            vldata[0].p = data2.data
+            vldata[0].p = PyArray_DATA(data2)
             ierr = nc_put_vara(self._grpid, self._varid,
                                startp, countp, vldata)
             _ensure_nc_success(ierr)
@@ -5186,10 +5188,10 @@ NC_CHAR).
             # strides all 1 or scalar variable, use put_vara (faster)
             if sum(stride) == ndims or ndims == 0:
                 ierr = nc_put_vara(self._grpid, self._varid,
-                                   startp, countp, data.data)
+                                   startp, countp, PyArray_DATA(data))
             else:
                 ierr = nc_put_vars(self._grpid, self._varid,
-                                   startp, countp, stridep, data.data)
+                                   startp, countp, stridep, PyArray_DATA(data))
             _ensure_nc_success(ierr)
         elif self._isvlen:
             if data.dtype.char !='O':
@@ -5235,8 +5237,8 @@ NC_CHAR).
                         # casting doesn't work ?? just raise TypeError
                         raise TypeError("wrong data type in object array: should be %s, got %s" % (self.dtype,dataarr.dtype))
                     vldata[i].len = PyArray_SIZE(dataarr)
-                    vldata[i].p = dataarr.data
-                    databuff = databuff + data.strides[0]
+                    vldata[i].p = PyArray_DATA(dataarr)
+                    databuff = databuff + PyArray_STRIDES(data)[0]
                 # strides all 1 or scalar variable, use put_vara (faster)
                 if sum(stride) == ndims or ndims == 0:
                     ierr = nc_put_vara(self._grpid, self._varid,
@@ -5303,11 +5305,12 @@ NC_CHAR).
                 if sum(stride) == ndims or ndims == 0:
                     with nogil:
                         ierr = nc_get_vara(self._grpid, self._varid,
-                                           startp, countp, data.data)
+                                           startp, countp, PyArray_DATA(data))
                 else:
                     with nogil:
                         ierr = nc_get_vars(self._grpid, self._varid,
-                                           startp, countp, stridep, data.data)
+                                           startp, countp, stridep,
+                                           PyArray_DATA(data))
             else:
                 ierr = 0
             if ierr == NC_EINVALCOORDS:
@@ -5380,7 +5383,7 @@ NC_CHAR).
                     arrlen  = vldata[i].len
                     dataarr = numpy.empty(arrlen, self.dtype)
                     #dataarr.data = vldata[i].p
-                    memcpy(dataarr.data, vldata[i].p, dataarr.nbytes)
+                    memcpy(PyArray_DATA(dataarr), vldata[i].p, dataarr.nbytes)
                     data[i] = dataarr
                 # reshape the output array
                 data = numpy.reshape(data, shapeout)
@@ -5943,7 +5946,8 @@ cdef _def_enum(grp, object dt, object dtype_name, object enum_dict):
         value_arr = numpy.array(enum_dict[field],dt)
         bytestr = _strencode(field)
         namstring = bytestr
-        ierr = nc_insert_enum(grp._grpid, xtype, namstring, value_arr.data)
+        ierr = nc_insert_enum(grp._grpid, xtype, namstring,
+                PyArray_DATA(value_arr))
         _ensure_nc_success(ierr)
     return xtype, dt
 

From 9dbc716d0423133b0fc22c3caafdfd68a268a04b Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 30 Jan 2021 20:03:00 -0700
Subject: [PATCH 0562/1504] update

---
 src/netCDF4/_netCDF4.pyx | 5 +----
 1 file changed, 1 insertion(+), 4 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 99befb036..2b6f7fbbb 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1222,6 +1222,7 @@ from cpython.bytes cimport PyBytes_FromStringAndSize
 from .utils import (_StartCountStride, _quantize, _find_dim, _walk_grps,
                     _out_array_shape, _sortbylist, _tostr, _safecast, _is_int)
 import sys
+from cftime import date2num, num2date, date2index
 if sys.version_info[0:2] < (3, 7):
     # Python 3.7+ guarantees order; older versions need OrderedDict
     from collections import OrderedDict
@@ -6603,10 +6604,6 @@ days since 2000-01-01
         `ValueError` otherwise.
         """
         import datetime
-        try:
-            from cftime import date2num
-        except ImportError:
-            raise ImportError('cftime required to use MFTime class')
         self.__time = time
 
         # copy attributes from master time variable.

From 15cd4bb575e41cae52b29c2f7d611786a8ccf55f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 30 Jan 2021 20:07:19 -0700
Subject: [PATCH 0563/1504] update

---
 src/netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 2b6f7fbbb..196544d16 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -5227,7 +5227,7 @@ NC_CHAR).
                 # regular vlen.
                 # loop over elements of object array, put data buffer for
                 # each element in struct.
-                databuff = data.data
+                databuff = PyArray_BYTES(data)
                 # allocate struct array to hold vlen data.
                 vldata = malloc(totelem*sizeof(nc_vlen_t))
                 for i from 0<=i
Date: Sat, 30 Jan 2021 20:12:45 -0700
Subject: [PATCH 0564/1504] put cftime dependency back in

---
 setup.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index 0f9cfdd05..81d95cfd8 100644
--- a/setup.py
+++ b/setup.py
@@ -4,7 +4,7 @@
 from distutils.dist import Distribution
 
 setuptools_extra_kwargs = {
-    "install_requires": ["numpy>=1.9"],
+    "install_requires": ["numpy>=1.9", "cftime"],
     "setup_requires": ['setuptools>=18.0', "cython>=0.19"],
     "entry_points": {
         'console_scripts': [

From 7acff12fcccc12eac27a1185fc44d752fe3ea8fc Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 30 Jan 2021 20:16:46 -0700
Subject: [PATCH 0565/1504] update

---
 .github/workflows/build.yml | 2 +-
 Changelog                   | 3 ---
 src/netCDF4/__init__.py     | 2 +-
 src/netCDF4/_netCDF4.pyx    | 5 +----
 4 files changed, 3 insertions(+), 9 deletions(-)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 3421c28c2..f3e4263b2 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -56,7 +56,7 @@ jobs:
     - name: Install python dependencies via pip
       run: |
         python -m pip install --upgrade pip
-        pip install numpy cython pytest twine wheel check-manifest mpi4py
+        pip install numpy cython cftime pytest twine wheel check-manifest mpi4py
 
     - name: Install netcdf4-python
       run: |
diff --git a/Changelog b/Changelog
index 22e359cbb..32cb5a21b 100644
--- a/Changelog
+++ b/Changelog
@@ -5,9 +5,6 @@
  * change numpy.bool to numpy.bool_ and numpy.float to numpy.float_ (float and
    bool are deprecated in numpy 1.20, issue #1065)
  * clean up docstrings so that they work with latest pdoc.
- * make cftime an optional dependency (issue #1073), an import is only
-   attempted if MFTime is used.  date2num,num2date and date2index no longer
-   imported into netCDF4 namespace.
 
  version 1.5.5.1 (tag v1.5.5.1rel)
 ==================================
diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py
index 9fc7a8540..4ddc07fdf 100644
--- a/src/netCDF4/__init__.py
+++ b/src/netCDF4/__init__.py
@@ -9,4 +9,4 @@
                        __has_nc_create_mem__, __has_cdf5_format__,
                        __has_parallel4_support__, __has_pnetcdf_support__)
 __all__ =\
-['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
+['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 196544d16..94032769f 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -59,11 +59,8 @@ types) are not supported.
  is required, as is the [mpi4py](http://mpi4py.scipy.org) python module.
  Parallel IO further depends on the existence of MPI-enabled HDF5 or the
  [PnetCDF](https://parallel-netcdf.github.io/) library.
-
-## Optional
  - [cftime](https://github.com/Unidata/cftime) for
- the time and date handling utility functions.
- The [MFTime](#MFTime) class will not work if cftime not installed.
+ time and date handling utility functions.
 
 
 ## Install

From d5379b383b30b7fd357019d45fa2888eb741fac8 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 30 Jan 2021 20:21:30 -0700
Subject: [PATCH 0566/1504] update

---
 setup.py                 |  2 +-
 src/netCDF4/_netCDF4.pyx |  4 +-
 test/tst_multifile.py    | 82 ++++++++++++++++++----------------------
 test/tst_multifile2.py   | 63 ++++++++++++++----------------
 4 files changed, 68 insertions(+), 83 deletions(-)

diff --git a/setup.py b/setup.py
index 81d95cfd8..99df3ede0 100644
--- a/setup.py
+++ b/setup.py
@@ -4,7 +4,7 @@
 from distutils.dist import Distribution
 
 setuptools_extra_kwargs = {
-    "install_requires": ["numpy>=1.9", "cftime"],
+    "install_requires": ["numpy>=1.9","cftime"],
     "setup_requires": ['setuptools>=18.0', "cython>=0.19"],
     "entry_points": {
         'console_scripts': [
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 94032769f..eb0b6718c 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -601,7 +601,7 @@ Here's an example of how they can be used:
 ```python
 >>> # fill in times.
 >>> from datetime import datetime, timedelta
->>> from cftime import num2date, date2num # requires the cftime package
+>>> from cftime import num2date, date2num
 >>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
 >>> times[:] = date2num(dates,units=times.units,calendar=times.calendar)
 >>> print("time values (in units {}):\\n{}".format(times.units, times[:]))
@@ -1219,7 +1219,6 @@ from cpython.bytes cimport PyBytes_FromStringAndSize
 from .utils import (_StartCountStride, _quantize, _find_dim, _walk_grps,
                     _out_array_shape, _sortbylist, _tostr, _safecast, _is_int)
 import sys
-from cftime import date2num, num2date, date2index
 if sys.version_info[0:2] < (3, 7):
     # Python 3.7+ guarantees order; older versions need OrderedDict
     from collections import OrderedDict
@@ -1233,6 +1232,7 @@ __version__ = "1.5.6"
 
 # Initialize numpy
 import posixpath
+from cftime import date2num, num2date, date2index
 import numpy
 import weakref
 import warnings
diff --git a/test/tst_multifile.py b/test/tst_multifile.py
index 945de8b6a..786740512 100644
--- a/test/tst_multifile.py
+++ b/test/tst_multifile.py
@@ -4,12 +4,7 @@
 from numpy.testing import assert_array_equal, assert_equal
 from numpy import ma
 import tempfile, unittest, os, datetime
-try:
-    import cftime
-    has_cftime=True
-except ImportError:
-    has_cftime=False
-    
+import cftime
 from pkg_resources import parse_version
 
 nx=100; ydim=5; zdim=10
@@ -123,48 +118,45 @@ def runTest(self):
         # The test files have no calendar attribute on the time variable.
         calendar = 'standard'
 
-        if has_cftime:
-            # Get the real dates
-            dates = []
-            for file in self.files:
-                f = Dataset(file)
-                t = f.variables['time']
-                dates.extend(cftime.num2date(t[:], t.units, calendar))
-                f.close()
-            # Compare with the MF dates
-            f = MFDataset(self.files,check=True)
+        # Get the real dates
+        dates = []
+        for file in self.files:
+            f = Dataset(file)
             t = f.variables['time']
-            T = MFTime(t, calendar=calendar)
-            assert_equal(T.calendar, calendar)
-            assert_equal(len(T), len(t))
-            assert_equal(T.shape, t.shape)
-            assert_equal(T.dimensions, t.dimensions)
-            assert_equal(T.typecode(), t.typecode())
-            # skip this until cftime pull request #55 is in a released
-            # version (1.0.1?). Otherwise, fix for issue #808 breaks this
-            if parse_version(cftime.__version__) >= parse_version('1.0.1'):
-                assert_array_equal(cftime.num2date(T[:], T.units, T.calendar), dates)
-            assert_equal(cftime.date2index(datetime.datetime(1980, 1, 2), T), 366)
+            dates.extend(cftime.num2date(t[:], t.units, calendar))
             f.close()
+        # Compare with the MF dates
+        f = MFDataset(self.files,check=True)
+        t = f.variables['time']
+        T = MFTime(t, calendar=calendar)
+        assert_equal(T.calendar, calendar)
+        assert_equal(len(T), len(t))
+        assert_equal(T.shape, t.shape)
+        assert_equal(T.dimensions, t.dimensions)
+        assert_equal(T.typecode(), t.typecode())
+        # skip this until cftime pull request #55 is in a released
+        # version (1.0.1?). Otherwise, fix for issue #808 breaks this
+        if parse_version(cftime.__version__) >= parse_version('1.0.1'):
+            assert_array_equal(cftime.num2date(T[:], T.units, T.calendar), dates)
+        assert_equal(cftime.date2index(datetime.datetime(1980, 1, 2), T), 366)
+        f.close()
 
-            # Test exception is raised when no calendar attribute is available on the
-            # time variable.
-            with MFDataset(self.files, check=True) as ds:
-                with self.assertRaises(ValueError):
-                    MFTime(ds.variables['time'])
-
-            # Test exception is raised when the calendar attribute is different on the
-            # variables. First, add calendar attributes to file. Note this will modify
-            # the files inplace.
-            calendars = ['standard', 'gregorian']
-            for idx, f in enumerate(self.files):
-                with Dataset(f, 'a') as ds:
-                    ds.variables['time'].calendar = calendars[idx]
-            with MFDataset(self.files, check=True) as ds:
-                with self.assertRaises(ValueError):
-                    MFTime(ds.variables['time'])
-        else:
-            print('skipping MFTime test 1 (of 2) since cftime not installed...')
+        # Test exception is raised when no calendar attribute is available on the
+        # time variable.
+        with MFDataset(self.files, check=True) as ds:
+            with self.assertRaises(ValueError):
+                MFTime(ds.variables['time'])
+
+        # Test exception is raised when the calendar attribute is different on the
+        # variables. First, add calendar attributes to file. Note this will modify
+        # the files inplace.
+        calendars = ['standard', 'gregorian']
+        for idx, f in enumerate(self.files):
+            with Dataset(f, 'a') as ds:
+                ds.variables['time'].calendar = calendars[idx]
+        with MFDataset(self.files, check=True) as ds:
+            with self.assertRaises(ValueError):
+                MFTime(ds.variables['time'])
 
 
 if __name__ == '__main__':
diff --git a/test/tst_multifile2.py b/test/tst_multifile2.py
index 64e9b82ae..f818fcaba 100644
--- a/test/tst_multifile2.py
+++ b/test/tst_multifile2.py
@@ -4,11 +4,7 @@
 from numpy.testing import assert_array_equal, assert_equal
 from numpy import ma
 import tempfile, unittest, os, datetime
-try:
-    import cftime
-    has_cftime=True
-except ImportError:
-    has_cftime=False
+import cftime
 from pkg_resources import parse_version
 
 nx=100; ydim=5; zdim=10
@@ -107,36 +103,33 @@ def tearDown(self):
 
 
     def runTest(self):
-        if has_cftime:
-            # Get the real dates
-            # skip this until cftime pull request #55 is in a released
-            # version (1.0.1?). Otherwise, fix for issue #808 breaks this
-            if parse_version(cftime.__version__) >= parse_version('1.0.1'):
-                dates = []
-                for file in self.files:
-                    f = Dataset(file)
-                    t = f.variables['time']
-                    dates.extend(cftime.num2date(t[:], t.units, t.calendar))
-                    f.close()
-
-            # Compare with the MF dates
-            f = MFDataset(self.files,check=True)
-            t = f.variables['time']
-            mfdates = cftime.num2date(t[:], t.units, t.calendar)
-
-            T = MFTime(t)
-            assert_equal(len(T), len(t))
-            assert_equal(T.shape, t.shape)
-            assert_equal(T.dimensions, t.dimensions)
-            assert_equal(T.typecode(), t.typecode())
-            # skip this until cftime pull request #55 is in a released
-            # version (1.0.1?). Otherwise, fix for issue #808 breaks this
-            if parse_version(cftime.__version__) >= parse_version('1.0.1'):
-                assert_array_equal(cftime.num2date(T[:], T.units, T.calendar), dates)
-            assert_equal(cftime.date2index(datetime.datetime(1980, 1, 2), T), 366)
-            f.close()
-        else:
-            print('skipping MFTime test 2 (of 2) since cftime not installed...')
+        # Get the real dates
+        # skip this until cftime pull request #55 is in a released
+        # version (1.0.1?). Otherwise, fix for issue #808 breaks this
+        if parse_version(cftime.__version__) >= parse_version('1.0.1'):
+            dates = []
+            for file in self.files:
+                f = Dataset(file)
+                t = f.variables['time']
+                dates.extend(cftime.num2date(t[:], t.units, t.calendar))
+                f.close()
+
+        # Compare with the MF dates
+        f = MFDataset(self.files,check=True)
+        t = f.variables['time']
+        mfdates = cftime.num2date(t[:], t.units, t.calendar)
+
+        T = MFTime(t)
+        assert_equal(len(T), len(t))
+        assert_equal(T.shape, t.shape)
+        assert_equal(T.dimensions, t.dimensions)
+        assert_equal(T.typecode(), t.typecode())
+        # skip this until cftime pull request #55 is in a released
+        # version (1.0.1?). Otherwise, fix for issue #808 breaks this
+        if parse_version(cftime.__version__) >= parse_version('1.0.1'):
+            assert_array_equal(cftime.num2date(T[:], T.units, T.calendar), dates)
+        assert_equal(cftime.date2index(datetime.datetime(1980, 1, 2), T), 366)
+        f.close()
 
 if __name__ == '__main__':
     unittest.main()

From 9373172a79b6c486646ba4cfada6f6d445445985 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Sun, 31 Jan 2021 11:14:58 -0700
Subject: [PATCH 0567/1504] update

---
 docs/index.html | 16 ++++------------
 1 file changed, 4 insertions(+), 12 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index f735d60f5..19b0eb45e 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -43,7 +43,6 @@ 
      Contents
      
 
 
    • Tutorial
@@ -520,15 +519,8 @@ 
      Requires
      
 is required, as is the mpi4py python module.
 Parallel IO further depends on the existence of MPI-enabled HDF5 or the
 PnetCDF library.
      • 
-
    
-
-
    Optional
    
-
-
      
 
    • cftime for
-the time and date handling utility functions (num2date,
-date2num and date2index) are imported into the netCDF4 namespace if available.
-The MFTime class will not work if cftime not installed.
      • 
+time and date handling utility functions.
 
    
 
 
    Install
    
@@ -1039,14 +1031,14 @@ 
    Dealing with time coordinates
    
 measure relative to a fixed date using a certain calendar, with units
 specified like hours since YY-MM-DD hh:mm:ss.  These units can be
 awkward to deal with, without a utility to convert the values to and
-from calendar dates.  The functionsnum2date
+from calendar dates.  The functions num2date
 and date2num are
 provided by cftime to do just that.
 Here's an example of how they can be used:
    
 
 
    >>> # fill in times.
 >>> from datetime import datetime, timedelta
->>> from cftime import num2date, date2num # requires the cftime package
+>>> from cftime import num2date, date2num
 >>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
 >>> times[:] = date2num(dates,units=times.units,calendar=times.calendar)
 >>> print("time values (in units {}):\n{}".format(times.units, times[:]))
@@ -1626,7 +1618,7 @@ 
    In-memory (diskless) Datasets
    
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
    
 
-
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
+
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
 
 
    copyright: 2008 by Jeffrey Whitaker.
    
 

From 71fdc8fa625b47ed2fce3971043055faea127e67 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 1 Feb 2021 10:31:11 -0700
Subject: [PATCH 0568/1504] update

---
 Changelog | 1 +
 1 file changed, 1 insertion(+)

diff --git a/Changelog b/Changelog
index 32cb5a21b..3a009d53e 100644
--- a/Changelog
+++ b/Changelog
@@ -5,6 +5,7 @@
  * change numpy.bool to numpy.bool_ and numpy.float to numpy.float_ (float and
    bool are deprecated in numpy 1.20, issue #1065)
  * clean up docstrings so that they work with latest pdoc.
+ * update cython numpy API to remove deprecation warnings.
 
  version 1.5.5.1 (tag v1.5.5.1rel)
 ==================================

From 8eeabeb94af4ef6009599e40e9c7a520dccd1b22 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 4 Feb 2021 12:31:38 -0700
Subject: [PATCH 0569/1504] update docstring

---
 src/netCDF4/_netCDF4.pyx | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index eb0b6718c..abca9f4c8 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -425,6 +425,9 @@ filling on, default _FillValue of 9.969209968386869e+36 used}
 [Dataset.renameVariable](#Dataset.renameVariable) method of a [Dataset](#Dataset)
 instance.
 
+Variables can be sliced similar to numpy arrays, but there are some differences.  See
+[Writing data to and retrieving data from a netCDF variable](#writing-data-to-and-retrieving-data-from-a-netcdf-variable) for more details.
+
 
 ## Attributes in a netCDF file
 

From 0aa4339653b5117323d504e34885161e1d194ef1 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 13:19:31 -0700
Subject: [PATCH 0570/1504] add Dataset.ncdump

---
 src/netCDF4/_netCDF4.pyx | 28 ++++++++++++++++++++++++++++
 1 file changed, 28 insertions(+)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index abca9f4c8..ba5281f45 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1239,6 +1239,8 @@ from cftime import date2num, num2date, date2index
 import numpy
 import weakref
 import warnings
+import subprocess
+import tempfile
 from glob import glob
 from numpy import ma
 from libc.string cimport memcpy, memset
@@ -1955,6 +1957,16 @@ cdef _ensure_nc_success(ierr, err_cls=RuntimeError, filename=None):
         else:
             raise err_cls(err_str)
 
+_cached_temporary_files = {}
+def _cdl_to_netcdf(filename):
+    """Create a temporary netCDF-4 file from a CDL text file"""
+    x = tempfile.NamedTemporaryFile(
+        mode="wb", dir=tempfile.gettempdir(), prefix="netCDF4_", suffix=".nc")
+    tmpfile = x.name
+    _cached_temporary_files[tmpfile] = x
+    subprocess.run(["ncgen", "-knc4", "-o", tmpfile, filename], check=True)
+    return tmpfile
+
 # these are class attributes that
 # only exist at the python level (not in the netCDF file).
 
@@ -3235,6 +3247,22 @@ attribute does not exist on the variable. For example,
         def __set__(self,value):
             raise AttributeError("name cannot be altered")
 
+    def ncdump(self,coordvars=False,outfile=None):
+        """call ncdump"""
+        self.sync()
+        if coordvars:
+            ncdumpargs = "-ch"
+        else:
+            ncdumpargs = "-h"
+        result=subprocess.run(["ncdump", ncdumpargs, self.filepath()],
+                check=True, capture_output=True, text=True)
+        if outfile is None:
+            print(result.stdout)
+        else:
+            f = open(outfile,'w')
+            f.write(result.stdout)
+            f.close()
+
 
 cdef class Group(Dataset):
     """

From 495f53190e773e7fe59bda5bb7679562b99720b8 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 13:38:27 -0700
Subject: [PATCH 0571/1504] add Dataset.fromcdl

---
 src/netCDF4/_netCDF4.pyx | 19 +++++++++----------
 1 file changed, 9 insertions(+), 10 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index ba5281f45..e31ced9d6 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1241,6 +1241,7 @@ import weakref
 import warnings
 import subprocess
 import tempfile
+import pathlib
 from glob import glob
 from numpy import ma
 from libc.string cimport memcpy, memset
@@ -1957,16 +1958,6 @@ cdef _ensure_nc_success(ierr, err_cls=RuntimeError, filename=None):
         else:
             raise err_cls(err_str)
 
-_cached_temporary_files = {}
-def _cdl_to_netcdf(filename):
-    """Create a temporary netCDF-4 file from a CDL text file"""
-    x = tempfile.NamedTemporaryFile(
-        mode="wb", dir=tempfile.gettempdir(), prefix="netCDF4_", suffix=".nc")
-    tmpfile = x.name
-    _cached_temporary_files[tmpfile] = x
-    subprocess.run(["ncgen", "-knc4", "-o", tmpfile, filename], check=True)
-    return tmpfile
-
 # these are class attributes that
 # only exist at the python level (not in the netCDF file).
 
@@ -3263,6 +3254,14 @@ attribute does not exist on the variable. For example,
             f.write(result.stdout)
             f.close()
 
+    @staticmethod
+    def fromcdl(cdlfilename,mode='a',ncfilename=None):
+        if ncfilename == None:
+            filepath = pathlib.Path(cdlfilename)
+            ncfilename = filepath.with_suffix('.nc') 
+        subprocess.run(["ncgen", "-knc4", "-o", ncfilename, cdlfilename], check=True)
+        return Dataset(ncfilename, mode=mode)
+
 
 cdef class Group(Dataset):
     """

From f5d0e880a2ba856401019f3f44f88951b2204160 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 14:00:49 -0700
Subject: [PATCH 0572/1504] fromcdl moved to function dataset_fromcdl

---
 src/netCDF4/_netCDF4.pyx | 39 +++++++++++++++++++++++++++++----------
 1 file changed, 29 insertions(+), 10 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index e31ced9d6..796b5a400 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1968,6 +1968,26 @@ _private_atts = \
  '__orthogoral_indexing__','keepweakref','_has_lsd',
  '_buffer','chartostring','_use_get_vars','_ncstring_attrs__']
 
+def dataset_fromcdl(cdlfilename,mode='a',ncfilename=None):
+    """
+**`dataset_fromcdl(cdlfilename, ncfilename)`**
+
+call ncgen via subprocess to create Dataset from CDL text representation.
+
+**`cdlfilename`**:  CDL file.
+
+**`ncfilename`**: netCDF file to create.
+
+**`mode`**:  Access mode to open Dataset (Default `'a'`).
+       
+Dataset instance for `ncfilename` is returned.
+    """
+    if ncfilename == None:
+        filepath = pathlib.Path(cdlfilename)
+        ncfilename = filepath.with_suffix('.nc') 
+    subprocess.run(["ncgen", "-knc4", "-o", ncfilename, cdlfilename], check=True)
+    return Dataset(ncfilename, mode=mode)
+
 cdef class Dataset:
     """
 A netCDF [Dataset](#Dataset) is a collection of dimensions, groups, variables and
@@ -3239,7 +3259,15 @@ attribute does not exist on the variable. For example,
             raise AttributeError("name cannot be altered")
 
     def ncdump(self,coordvars=False,outfile=None):
-        """call ncdump"""
+        """
+**`ncdump(self, coordvars=False, outfile=None)`**
+
+call ncdump via subprocess to create CDL text representation of Dataset
+
+**`coordvars`**: include coordinate variable data (via `ncdump -c`). Default False
+
+**`outfile`**: If not None, file to output ncdump to. Default is to print result to stdout.
+        """
         self.sync()
         if coordvars:
             ncdumpargs = "-ch"
@@ -3254,15 +3282,6 @@ attribute does not exist on the variable. For example,
             f.write(result.stdout)
             f.close()
 
-    @staticmethod
-    def fromcdl(cdlfilename,mode='a',ncfilename=None):
-        if ncfilename == None:
-            filepath = pathlib.Path(cdlfilename)
-            ncfilename = filepath.with_suffix('.nc') 
-        subprocess.run(["ncgen", "-knc4", "-o", ncfilename, cdlfilename], check=True)
-        return Dataset(ncfilename, mode=mode)
-
-
 cdef class Group(Dataset):
     """
 Groups define a hierarchical namespace within a netCDF file. They are

From dbd466ab330fc862356b51e707b2d02b67c495c9 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 14:04:17 -0700
Subject: [PATCH 0573/1504] update docstring

---
 src/netCDF4/_netCDF4.pyx | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 796b5a400..a26d3770d 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1970,13 +1970,14 @@ _private_atts = \
 
 def dataset_fromcdl(cdlfilename,mode='a',ncfilename=None):
     """
-**`dataset_fromcdl(cdlfilename, ncfilename)`**
+**`dataset_fromcdl(cdlfilename, ncfilename=None)`**
 
 call ncgen via subprocess to create Dataset from CDL text representation.
 
 **`cdlfilename`**:  CDL file.
 
-**`ncfilename`**: netCDF file to create.
+**`ncfilename`**: netCDF file to create. If not given, CDL filename with
+suffix replaced by `.nc` is used..
 
 **`mode`**:  Access mode to open Dataset (Default `'a'`).
        

From 58284ff10ca7074fcd4bdecc91b83ff0449e295a Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 14:07:04 -0700
Subject: [PATCH 0574/1504] change Dataset.ncdump to Dataset.tocdl

---
 src/netCDF4/_netCDF4.pyx | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index a26d3770d..60194c093 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3259,9 +3259,9 @@ attribute does not exist on the variable. For example,
         def __set__(self,value):
             raise AttributeError("name cannot be altered")
 
-    def ncdump(self,coordvars=False,outfile=None):
+    def tocdl(self,coordvars=False,outfile=None):
         """
-**`ncdump(self, coordvars=False, outfile=None)`**
+**`tocdl(self, coordvars=False, outfile=None)`**
 
 call ncdump via subprocess to create CDL text representation of Dataset
 

From f0519d1391098368b75fbd83d6c7eb95241ae99e Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 14:09:27 -0700
Subject: [PATCH 0575/1504] update docstring

---
 src/netCDF4/_netCDF4.pyx | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 60194c093..4a1b3133a 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1968,9 +1968,9 @@ _private_atts = \
  '__orthogoral_indexing__','keepweakref','_has_lsd',
  '_buffer','chartostring','_use_get_vars','_ncstring_attrs__']
 
-def dataset_fromcdl(cdlfilename,mode='a',ncfilename=None):
+def dataset_fromcdl(cdlfilename,ncfilename=None,mode='a'):
     """
-**`dataset_fromcdl(cdlfilename, ncfilename=None)`**
+**`dataset_fromcdl(cdlfilename, ncfilename=None, model='a')`**
 
 call ncgen via subprocess to create Dataset from CDL text representation.
 

From 46da510f0c43f6057a1d4cb390121bd872268399 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 14:13:47 -0700
Subject: [PATCH 0576/1504] update docstring

---
 src/netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 4a1b3133a..d22e59165 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1970,7 +1970,7 @@ _private_atts = \
 
 def dataset_fromcdl(cdlfilename,ncfilename=None,mode='a'):
     """
-**`dataset_fromcdl(cdlfilename, ncfilename=None, model='a')`**
+**`dataset_fromcdl(cdlfilename, ncfilename=None, mode='a')`**
 
 call ncgen via subprocess to create Dataset from CDL text representation.
 

From 24752f662845a10d90fda5c26f758293e7a2cbad Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 14:28:23 -0700
Subject: [PATCH 0577/1504] add format kwarg to dataset_fromcdl

---
 src/netCDF4/_netCDF4.pyx | 19 ++++++++++++++++---
 1 file changed, 16 insertions(+), 3 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index d22e59165..6c7410ea1 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1968,9 +1968,9 @@ _private_atts = \
  '__orthogoral_indexing__','keepweakref','_has_lsd',
  '_buffer','chartostring','_use_get_vars','_ncstring_attrs__']
 
-def dataset_fromcdl(cdlfilename,ncfilename=None,mode='a'):
+def dataset_fromcdl(cdlfilename,ncfilename=None,mode='a',format='NETCDF4'):
     """
-**`dataset_fromcdl(cdlfilename, ncfilename=None, mode='a')`**
+**`dataset_fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')`**
 
 call ncgen via subprocess to create Dataset from CDL text representation.
 
@@ -1980,13 +1980,26 @@ call ncgen via subprocess to create Dataset from CDL text representation.
 suffix replaced by `.nc` is used..
 
 **`mode`**:  Access mode to open Dataset (Default `'a'`).
+
+**`format`**: underlying file format to use (one of `'NETCDF4',
+'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC'`, `'NETCDF3_64BIT_OFFSET'` or
+`'NETCDF3_64BIT_DATA'`.
        
 Dataset instance for `ncfilename` is returned.
     """
     if ncfilename == None:
         filepath = pathlib.Path(cdlfilename)
         ncfilename = filepath.with_suffix('.nc') 
-    subprocess.run(["ncgen", "-knc4", "-o", ncfilename, cdlfilename], check=True)
+    formatcodes = {'NETCDF4': 4,
+                   'NETCDF4_CLASSIC': 7,
+                   'NETCDF3_CLASSIC': 3,
+                   'NETCDF3_64BIT': 6, # legacy
+                   'NETCDF3_64BIT_OFFSET': 6,
+                   'NETCDF3_64BIT_DATA': 5}
+    if format not in formatcodes:
+        raise ValueError('illegal format requested')
+    ncgenargs="-knc%s" % formatcodes[format]
+    subprocess.run(["ncgen", ncgenargs, "-o", ncfilename, cdlfilename], check=True)
     return Dataset(ncfilename, mode=mode)
 
 cdef class Dataset:

From 9674105d6a734cb9607b61ca9080094b214b7224 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 14:35:15 -0700
Subject: [PATCH 0578/1504] add -s to ncdump args

---
 src/netCDF4/_netCDF4.pyx | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 6c7410ea1..c24851584 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3284,9 +3284,9 @@ call ncdump via subprocess to create CDL text representation of Dataset
         """
         self.sync()
         if coordvars:
-            ncdumpargs = "-ch"
+            ncdumpargs = "-csh"
         else:
-            ncdumpargs = "-h"
+            ncdumpargs = "-sh"
         result=subprocess.run(["ncdump", ncdumpargs, self.filepath()],
                 check=True, capture_output=True, text=True)
         if outfile is None:

From 67d4cde2cdb6db8f52988440a38b314125d61daf Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 14:57:56 -0700
Subject: [PATCH 0579/1504] update URL

---
 test/tst_dap.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/tst_dap.py b/test/tst_dap.py
index f3ca7482a..b841bf44c 100644
--- a/test/tst_dap.py
+++ b/test/tst_dap.py
@@ -5,7 +5,7 @@
 # test accessing data over http with opendap.
 
 URL = "http://remotetest.unidata.ucar.edu/thredds/dodsC/testdods/testData.nc"
-URL_https = 'https://podaac-opendap.jpl.nasa.gov/opendap/allData/modis/L3/aqua/11um/v2014.0/4km/daily/2017/365/A2017365.L3m_DAY_NSST_sst_4km.nc'
+URL_https = 'https://podaac-opendap.jpl.nasa.gov/opendap/allData/modis/L3/aqua/11um/v2019.0/4km/daily/2017/365/A2017365.L3m_DAY_NSST_sst_4km.nc'
 varname = 'Z_sfc'
 varmin = 0
 varmax = 3292

From 7487788e5fe2725bedac3d11f1a609f72195aa3e Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 15:04:39 -0700
Subject: [PATCH 0580/1504] update

---
 test/tst_dap.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/tst_dap.py b/test/tst_dap.py
index b841bf44c..dba26e3f1 100644
--- a/test/tst_dap.py
+++ b/test/tst_dap.py
@@ -5,7 +5,7 @@
 # test accessing data over http with opendap.
 
 URL = "http://remotetest.unidata.ucar.edu/thredds/dodsC/testdods/testData.nc"
-URL_https = 'https://podaac-opendap.jpl.nasa.gov/opendap/allData/modis/L3/aqua/11um/v2019.0/4km/daily/2017/365/A2017365.L3m_DAY_NSST_sst_4km.nc'
+URL_https = 'https://podaac-opendap.jpl.nasa.gov/opendap/allData/modis/L3/aqua/11um/v2019.0/4km/daily/2017/365/AQUA_MODIS.20171231.L3m.DAY.NSST.sst.4km.nc'
 varname = 'Z_sfc'
 varmin = 0
 varmax = 3292

From 70122f9a15709e6c98c9237231c24826d04878e9 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 15:31:42 -0700
Subject: [PATCH 0581/1504] move fromcdl back to Dataset static method.

---
 src/netCDF4/_netCDF4.pyx | 68 +++++++++++++++++++++-------------------
 1 file changed, 35 insertions(+), 33 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index c24851584..5d08fe8cb 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1968,39 +1968,6 @@ _private_atts = \
  '__orthogoral_indexing__','keepweakref','_has_lsd',
  '_buffer','chartostring','_use_get_vars','_ncstring_attrs__']
 
-def dataset_fromcdl(cdlfilename,ncfilename=None,mode='a',format='NETCDF4'):
-    """
-**`dataset_fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')`**
-
-call ncgen via subprocess to create Dataset from CDL text representation.
-
-**`cdlfilename`**:  CDL file.
-
-**`ncfilename`**: netCDF file to create. If not given, CDL filename with
-suffix replaced by `.nc` is used..
-
-**`mode`**:  Access mode to open Dataset (Default `'a'`).
-
-**`format`**: underlying file format to use (one of `'NETCDF4',
-'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC'`, `'NETCDF3_64BIT_OFFSET'` or
-`'NETCDF3_64BIT_DATA'`.
-       
-Dataset instance for `ncfilename` is returned.
-    """
-    if ncfilename == None:
-        filepath = pathlib.Path(cdlfilename)
-        ncfilename = filepath.with_suffix('.nc') 
-    formatcodes = {'NETCDF4': 4,
-                   'NETCDF4_CLASSIC': 7,
-                   'NETCDF3_CLASSIC': 3,
-                   'NETCDF3_64BIT': 6, # legacy
-                   'NETCDF3_64BIT_OFFSET': 6,
-                   'NETCDF3_64BIT_DATA': 5}
-    if format not in formatcodes:
-        raise ValueError('illegal format requested')
-    ncgenargs="-knc%s" % formatcodes[format]
-    subprocess.run(["ncgen", ncgenargs, "-o", ncfilename, cdlfilename], check=True)
-    return Dataset(ncfilename, mode=mode)
 
 cdef class Dataset:
     """
@@ -3272,6 +3239,41 @@ attribute does not exist on the variable. For example,
         def __set__(self,value):
             raise AttributeError("name cannot be altered")
 
+    @staticmethod
+    def fromcdl(cdlfilename,ncfilename=None,mode='a',format='NETCDF4'):
+        """
+**`fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')`**
+
+call ncgen via subprocess to create Dataset from CDL text representation.
+
+**`cdlfilename`**:  CDL file.
+
+**`ncfilename`**: netCDF file to create. If not given, CDL filename with
+suffix replaced by `.nc` is used..
+
+**`mode`**:  Access mode to open Dataset (Default `'a'`).
+
+**`format`**: underlying file format to use (one of `'NETCDF4',
+'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC'`, `'NETCDF3_64BIT_OFFSET'` or
+`'NETCDF3_64BIT_DATA'`. Default `'NETCDF4'`.
+       
+Dataset instance for `ncfilename` is returned.
+        """
+        if ncfilename == None:
+            filepath = pathlib.Path(cdlfilename)
+        ncfilename = filepath.with_suffix('.nc') 
+        formatcodes = {'NETCDF4': 4,
+                       'NETCDF4_CLASSIC': 7,
+                       'NETCDF3_CLASSIC': 3,
+                       'NETCDF3_64BIT': 6, # legacy
+                       'NETCDF3_64BIT_OFFSET': 6,
+                       'NETCDF3_64BIT_DATA': 5}
+        if format not in formatcodes:
+            raise ValueError('illegal format requested')
+        ncgenargs="-knc%s" % formatcodes[format]
+        subprocess.run(["ncgen", ncgenargs, "-o", ncfilename, cdlfilename], check=True)
+        return Dataset(ncfilename, mode=mode)
+
     def tocdl(self,coordvars=False,outfile=None):
         """
 **`tocdl(self, coordvars=False, outfile=None)`**

From b74a3aa9f9b149d0672fd8ec5463fcac7e89cc9c Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 15:34:39 -0700
Subject: [PATCH 0582/1504] update

---
 src/netCDF4/_netCDF4.pyx | 1 -
 1 file changed, 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 5d08fe8cb..18d613a76 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1968,7 +1968,6 @@ _private_atts = \
  '__orthogoral_indexing__','keepweakref','_has_lsd',
  '_buffer','chartostring','_use_get_vars','_ncstring_attrs__']
 
-
 cdef class Dataset:
     """
 A netCDF [Dataset](#Dataset) is a collection of dimensions, groups, variables and

From c537cf9a2604279280da968271bca721af6cd235 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 15:36:06 -0700
Subject: [PATCH 0583/1504] fix treatment of default ncfilename in fromcdl

---
 src/netCDF4/_netCDF4.pyx | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 18d613a76..fa5e4e2f1 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3258,9 +3258,9 @@ suffix replaced by `.nc` is used..
        
 Dataset instance for `ncfilename` is returned.
         """
-        if ncfilename == None:
+        if ncfilename is None:
             filepath = pathlib.Path(cdlfilename)
-        ncfilename = filepath.with_suffix('.nc') 
+            ncfilename = filepath.with_suffix('.nc') 
         formatcodes = {'NETCDF4': 4,
                        'NETCDF4_CLASSIC': 7,
                        'NETCDF3_CLASSIC': 3,

From 68e5c31cda5c157fd8c4be9bb4ec94006c37d6a7 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 16:02:26 -0700
Subject: [PATCH 0584/1504] add test for fromcdl, tocdl

---
 test/tst_cdl.py | 44 ++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 44 insertions(+)
 create mode 100644 test/tst_cdl.py

diff --git a/test/tst_cdl.py b/test/tst_cdl.py
new file mode 100644
index 000000000..9d72f619b
--- /dev/null
+++ b/test/tst_cdl.py
@@ -0,0 +1,44 @@
+import unittest
+import netCDF4
+import os
+
+test_ncdump="""netcdf ubyte {
+dimensions:
+	d = 2 ;
+variables:
+	byte ub(d) ;
+		ub:_Unsigned = "true" ;
+	byte sb(d) ;
+
+// global attributes:
+		:_Format = "classic" ;
+}
+"""
+
+class Test_CDL(unittest.TestCase):
+    """
+    Test import/export of CDL
+    """
+    def setUp(self):
+        f=netCDF4.Dataset('ubyte.nc')
+        f.tocdl(outfile='ubyte.cdl')
+        f.close()
+    def test_tocdl(self):
+        # treated as unsigned integers.
+        f=netCDF4.Dataset('ubyte.nc')
+        assert(f.tocdl() == test_ncdump)
+        f.close()
+    def test_fromcdl(self):
+        f1=netCDF4.Dataset.fromcdl('ubyte.cdl',ncfilename='ubyte2.nc')
+        f2=netCDF4.Dataset('ubyte.nc')
+        assert(f1.variables.keys() == f2.variables.keys())
+        assert(f1.filepath() == 'ubyte2.nc')
+        assert(f1.dimensions.keys() == f2.dimensions.keys())
+        assert(len(f1.dimensions['d']) == len(f2.dimensions['d']))
+        f1.close(); f2.close()
+    def tearDown(self):
+        # Remove the temporary files
+        os.remove('ubyte.cdl')
+
+if __name__ == '__main__':
+    unittest.main()

From 08da0b3ce653111baf557d7217d9405e27cdf2bc Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 16:07:15 -0700
Subject: [PATCH 0585/1504] clean up file

---
 test/tst_cdl.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/test/tst_cdl.py b/test/tst_cdl.py
index 9d72f619b..c26c86816 100644
--- a/test/tst_cdl.py
+++ b/test/tst_cdl.py
@@ -36,6 +36,7 @@ def test_fromcdl(self):
         assert(f1.dimensions.keys() == f2.dimensions.keys())
         assert(len(f1.dimensions['d']) == len(f2.dimensions['d']))
         f1.close(); f2.close()
+        os.remove('ubyte2.nc')
     def tearDown(self):
         # Remove the temporary files
         os.remove('ubyte.cdl')

From c18a8b970b436def1f2036b729f3f110f06151e9 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 16:08:33 -0700
Subject: [PATCH 0586/1504] update

---
 Changelog | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/Changelog b/Changelog
index 3a009d53e..190468034 100644
--- a/Changelog
+++ b/Changelog
@@ -6,6 +6,8 @@
    bool are deprecated in numpy 1.20, issue #1065)
  * clean up docstrings so that they work with latest pdoc.
  * update cython numpy API to remove deprecation warnings.
+ * Add "fromcdl" and "tocdl" Dataset methods for import/export of CDL
+   via ncdump/ncgen called externally via the subprocess module (issue #1078).
 
  version 1.5.5.1 (tag v1.5.5.1rel)
 ==================================

From 5b80fa8625e4cc603da920df33a56284cb052e46 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 16:17:18 -0700
Subject: [PATCH 0587/1504] add test for data=True

---
 test/tst_cdl.py | 22 +++++++++++++++++++++-
 1 file changed, 21 insertions(+), 1 deletion(-)

diff --git a/test/tst_cdl.py b/test/tst_cdl.py
index c26c86816..d86ee2bd7 100644
--- a/test/tst_cdl.py
+++ b/test/tst_cdl.py
@@ -14,6 +14,23 @@
 		:_Format = "classic" ;
 }
 """
+test_ncdump2="""netcdf ubyte {
+dimensions:
+	d = 2 ;
+variables:
+	byte ub(d) ;
+		ub:_Unsigned = "true" ;
+	byte sb(d) ;
+
+// global attributes:
+		:_Format = "classic" ;
+data:
+
+ ub = 0, -1 ;
+
+ sb = -128, 127 ;
+}
+"""
 
 class Test_CDL(unittest.TestCase):
     """
@@ -21,12 +38,13 @@ class Test_CDL(unittest.TestCase):
     """
     def setUp(self):
         f=netCDF4.Dataset('ubyte.nc')
-        f.tocdl(outfile='ubyte.cdl')
+        f.tocdl(outfile='ubyte.cdl',data=True)
         f.close()
     def test_tocdl(self):
         # treated as unsigned integers.
         f=netCDF4.Dataset('ubyte.nc')
         assert(f.tocdl() == test_ncdump)
+        assert(f.tocdl(data=True) == test_ncdump2)
         f.close()
     def test_fromcdl(self):
         f1=netCDF4.Dataset.fromcdl('ubyte.cdl',ncfilename='ubyte2.nc')
@@ -35,6 +53,8 @@ def test_fromcdl(self):
         assert(f1.filepath() == 'ubyte2.nc')
         assert(f1.dimensions.keys() == f2.dimensions.keys())
         assert(len(f1.dimensions['d']) == len(f2.dimensions['d']))
+        assert((f1['ub'][:] == f2['ub'][:]).all())
+        assert((f1['sb'][:] == f2['sb'][:]).all())
         f1.close(); f2.close()
         os.remove('ubyte2.nc')
     def tearDown(self):

From 49599033015543ed646dd65f4643338870533dac Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 16:18:06 -0700
Subject: [PATCH 0588/1504] add data kwarg to tocdl

---
 src/netCDF4/_netCDF4.pyx | 15 +++++++++------
 1 file changed, 9 insertions(+), 6 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index fa5e4e2f1..86dc2a73b 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3273,25 +3273,28 @@ Dataset instance for `ncfilename` is returned.
         subprocess.run(["ncgen", ncgenargs, "-o", ncfilename, cdlfilename], check=True)
         return Dataset(ncfilename, mode=mode)
 
-    def tocdl(self,coordvars=False,outfile=None):
+    def tocdl(self,coordvars=False,data=False,outfile=None):
         """
-**`tocdl(self, coordvars=False, outfile=None)`**
+**`tocdl(self, coordvars=False, data=False, outfile=None)`**
 
 call ncdump via subprocess to create CDL text representation of Dataset
 
 **`coordvars`**: include coordinate variable data (via `ncdump -c`). Default False
 
-**`outfile`**: If not None, file to output ncdump to. Default is to print result to stdout.
+**`data`**: if True, write out variable data (Default False).
+
+**`outfile`**: If not None, file to output ncdump to. Default is to return a string.
         """
         self.sync()
         if coordvars:
-            ncdumpargs = "-csh"
+            ncdumpargs = "-cs"
         else:
-            ncdumpargs = "-sh"
+            ncdumpargs = "-s"
+        if not data: ncdumpargs += "h"
         result=subprocess.run(["ncdump", ncdumpargs, self.filepath()],
                 check=True, capture_output=True, text=True)
         if outfile is None:
-            print(result.stdout)
+            return result.stdout
         else:
             f = open(outfile,'w')
             f.write(result.stdout)

From f9250c10e71e6b4d0fbadefbadf2c637c51ad9ac Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 16:27:36 -0700
Subject: [PATCH 0589/1504] update docs

---
 docs/index.html | 5353 +++++++++++++++++------------------------------
 1 file changed, 1963 insertions(+), 3390 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 19b0eb45e..6324e0516 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -3,40 +3,28 @@
 
     
     
-    
-
+    
     netCDF4 API documentation
+    
 
-    
-    
-    
-    
+
+
+
+
 
-
-
-    
    
-        
-            
-        
-        
    
-            
-                
    
-                    
-                        
-                    
-                    
    netCDF4
    
-                    
    Version 1.5.6
    
+            
    
+        
+    
    
+            
    
+                    
    
+netCDF4._netCDF4    
    
+
+                        
    Version 1.5.6
    
 
 
    Introduction
    
 
@@ -594,10 +589,10 @@ 
    Creating/Opening/Closing a netCDF
 format (HDF5) and use the new features of the version 4 API.  The
 netCDF4 module can read and write files in any of these formats. When
 creating a new file, the format may be specified using the format
-keyword in the Dataset constructor.  The default format is
+keyword in the Dataset constructor.  The default format is
 NETCDF4. To see how a given file is formatted, you can examine the
 data_model attribute.  Closing the netCDF file is
-accomplished via the Dataset.close method of the Dataset
+accomplished via the Dataset.close">Dataset.close method of the Dataset
 instance.
    
 
 
    Here's an example:
    
@@ -623,8 +618,8 @@ 
    Groups in a netCDF file
    
 groups.  A Dataset creates a special group, called
 the 'root group', which is similar to the root directory in a unix
 filesystem.  To create Group instances, use the
-Dataset.createGroup method of a Dataset or Group
-instance. Dataset.createGroup takes a single argument, a
+Dataset.createGroup">Dataset.createGroup method of a Dataset or Group
+instance. Dataset.createGroup">Dataset.createGroup takes a single argument, a
 python string containing the name of the new group. The new Group
 instances contained within the root group can be accessed by name using
 the groups dictionary attribute of the Dataset instance.  Only
@@ -653,7 +648,7 @@ 
    Groups in a netCDF file
    
 instances contained within that group. Each Group instance also has a
 path attribute that contains a simulated unix directory path to
 that group.  To simplify the creation of nested groups, you can
-use a unix-like path as an argument to Dataset.createGroup.
    
+use a unix-like path as an argument to Dataset.createGroup">Dataset.createGroup.
    
 
 
    >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
 >>> fcstgrp2 = rootgrp.createGroup("/forecasts/model2")
@@ -712,7 +707,7 @@ 
    Dimensions in a netCDF file
    
 before any variables can be created the dimensions they use must be
 created first. A special case, not often used in practice, is that of a
 scalar variable, which has no dimensions. A dimension is created using
-the Dataset.createDimension method of a Dataset
+the Dataset.createDimension">Dataset.createDimension method of a Dataset
 or Group instance. A Python string is used to set the name of the
 dimension, and an integer value is used to set the size. To create an
 unlimited dimension (a dimension that can be appended to), the size
@@ -735,7 +730,7 @@ 
    Dimensions in a netCDF file
    
 
 
    Using the python len function with a Dimension instance returns
 current size of that dimension.
-Dimension.isunlimited method of a Dimension instance
+Dimension.isunlimited">Dimension.isunlimited method of a Dimension instance
 be used to determine if the dimensions is unlimited, or appendable.
    
 
 
    >>> print(len(lon))
@@ -768,12 +763,12 @@ 
    Variables in a netCDF file
    
 supplied by the numpy module. However,
 unlike numpy arrays, netCDF4 variables can be appended to along one or
 more 'unlimited' dimensions. To create a netCDF variable, use the
-Dataset.createVariable method of a Dataset or
-Group instance. The Dataset.createVariable method
+Dataset.createVariable">Dataset.createVariable method of a Dataset or
+Group instance. The Dataset.createVariable">Dataset.createVariable method
 has two mandatory arguments, the variable name (a Python string), and
 the variable datatype. The variable's dimensions are given by a tuple
 containing the dimension names (defined previously with
-Dataset.createDimension). To create a scalar
+Dataset.createDimension">Dataset.createDimension). To create a scalar
 variable, simply leave out the dimensions keyword. The variable
 primitive datatypes correspond to the dtype attribute of a numpy array.
 You can specify the datatype as a numpy dtype object, or anything that
@@ -791,7 +786,7 @@ 
    Variables in a netCDF file
    
 can only be used if the file format is NETCDF4.
    
 
 
    The dimensions themselves are usually also defined as variables, called
-coordinate variables. The Dataset.createVariable
+coordinate variables. The Dataset.createVariable">Dataset.createVariable
 method returns an instance of the Variable class whose methods can be
 used later to access and set variable data and attributes.
    
 
@@ -870,9 +865,12 @@ 
    Variables in a netCDF file
    
 
    
 
 
    Variable names can be changed using the
-Dataset.renameVariable method of a Dataset
+Dataset.renameVariable">Dataset.renameVariable method of a Dataset
 instance.
    
 
+
    Variables can be sliced similar to numpy arrays, but there are some differences.  See
+Writing data to and retrieving data from a netCDF variable for more details.
    
+
 
    Attributes in a netCDF file
    
 
 
    There are two types of attributes in a netCDF file, global and variable.
@@ -896,7 +894,7 @@ 
    Attributes in a netCDF file
    
 >>> times.calendar = "gregorian"
 
    
 
-
    The Dataset.ncattrs method of a Dataset, Group or
+
    The Dataset.ncattrs">Dataset.ncattrs method of a Dataset, Group or
 Variable instance can be used to retrieve the names of all the netCDF
 attributes. This method is provided as a convenience, since using the
 built-in dir Python function will return a bunch of private methods
@@ -1014,12 +1012,12 @@ 
    Writing data
 
 
    By default, netcdf4-python returns numpy masked arrays with values equal to the
 missing_value or _FillValue variable attributes masked.  The
-Dataset.set_auto_mask  Dataset and Variable methods
+Dataset.set_auto_mask">Dataset.set_auto_mask  Dataset and Variable methods
 can be used to disable this feature so that
 numpy arrays are always returned, with the missing values included. Prior to
 version 1.4.0 the default behavior was to only return masked arrays when the
 requested slice contained missing values.  This behavior can be recovered
-using the Dataset.set_always_mask method. If a masked array is
+using the Dataset.set_always_mask">Dataset.set_always_mask method. If a masked array is
 written to a netCDF variable, the masked elements are filled with the
 value specified by the missing_value attribute.  If the variable has
 no missing_value, the _FillValue is used instead.
    
@@ -1102,7 +1100,7 @@ 
    Efficient compression of netC
 
    Data stored in netCDF 4 Variable objects can be compressed and
 decompressed on the fly. The parameters for the compression are
 determined by the zlib, complevel and shuffle keyword arguments
-to the Dataset.createVariable method. To turn on
+to the Dataset.createVariable">Dataset.createVariable method. To turn on
 compression, set zlib=True.  The complevel keyword regulates the
 speed and efficiency of the compression (1 being fastest, but lowest
 compression ratio, 9 being slowest but best compression ratio). The
@@ -1111,12 +1109,12 @@ 
    Efficient compression of netC
 compression by reordering the bytes.  The shuffle filter can
 significantly improve compression ratios, and is on by default.  Setting
 fletcher32 keyword argument to
-Dataset.createVariable to True (it's False by
+Dataset.createVariable">Dataset.createVariable to True (it's False by
 default) enables the Fletcher32 checksum algorithm for error detection.
 It's also possible to set the HDF5 chunking parameters and endian-ness
 of the binary data stored in the HDF5 file with the chunksizes
 and endian keyword arguments to
-Dataset.createVariable.  These keyword arguments only
+Dataset.createVariable">Dataset.createVariable.  These keyword arguments only
 are relevant for NETCDF4 and NETCDF4_CLASSIC files (where the
 underlying file format is HDF5) and are silently ignored if the file
 format is NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
    
@@ -1125,7 +1123,7 @@ 
    Efficient compression of netC
 example, it is temperature data that was measured with a precision of
 0.1 degrees), you can dramatically improve zlib compression by
 quantizing (or truncating) the data using the least_significant_digit
-keyword argument to Dataset.createVariable. The least
+keyword argument to Dataset.createVariable">Dataset.createVariable. The least
 significant digit is the power of ten of the smallest decimal place in
 the data that is a reliable value. For example if the data has a
 precision of 0.1, then setting least_significant_digit=1 will cause
@@ -1165,7 +1163,7 @@ 
    Beyond ho
 information for a point by reading one variable, instead of reading
 different parameters from different variables.  Compound data types
 are created from the corresponding numpy data type using the
-Dataset.createCompoundType method of a Dataset or Group instance.
+Dataset.createCompoundType">Dataset.createCompoundType method of a Dataset or Group instance.
 Since there is no native complex data type in netcdf, compound types are handy
 for storing numpy complex arrays.  Here's an example:
    
 
@@ -1227,7 +1225,7 @@ 
    Variable-length (vlen) data types
    
 
 
    NetCDF 4 has support for variable-length or "ragged" arrays.  These are arrays
 of variable length sequences having the same type. To create a variable-length
-data type, use the Dataset.createVLType method
+data type, use the Dataset.createVLType">Dataset.createVLType method
 method of a Dataset or Group instance.
    
 
 
    >>> f = Dataset("tst_vlen.nc","w")
@@ -1291,7 +1289,7 @@ 
    Variable-length (vlen) data types
    
 variables,  For vlen strings, you don't need to create a vlen data type.
 Instead, simply use the python str builtin (or a numpy string datatype
 with fixed length greater than 1) when calling the
-Dataset.createVariable method.
    
+Dataset.createVariable">Dataset.createVariable method.
    
 
 
    >>> z = f.createDimension("z",10)
 >>> strvar = f.createVariable("strvar", str, "z")
@@ -1338,7 +1336,7 @@ 
    Enum data type
    
 
    Here's an example of using an Enum type to hold cloud type data.
 The base integer data type and a python dictionary describing the allowed
 values and their names are used to define an Enum data type using
-Dataset.createEnumType.
    
+Dataset.createEnumType">Dataset.createEnumType.
    
 
 
    >>> nc = Dataset('clouds.nc','w')
 >>> # python dict with allowed values and their names.
@@ -1437,7 +1435,7 @@ 
    Parallel IO
    
 depend on or be affected by other processes. Collective IO is a way of doing
 IO defined in the MPI-IO standard; unlike independent IO, all processes must
 participate in doing IO. To toggle back and forth between
-the two types of IO, use the Variable.set_collective
+the two types of IO, use the Variable.set_collective">Variable.set_collective
 Variable method. All metadata
 operations (such as creation of groups, types, variables, dimensions, or attributes)
 are collective.  There are a couple of important limitations of parallel IO:
    
@@ -1497,7 +1495,7 @@ 
    Dealing with strings
    
 
 
    Even if the _Encoding attribute is set, the automatic conversion of char
 arrays to/from string arrays can be disabled with
-Variable.set_auto_chartostring.
    
+Variable.set_auto_chartostring">Variable.set_auto_chartostring.
    
 
 
    A similar situation is often encountered with numpy structured arrays with subdtypes
 containing fixed-wdith byte strings (dtype=S#). Since there is no native fixed-length string
@@ -1552,7 +1550,7 @@ 
    In-memory (diskless) Datasets
    
 If you want to create a new in-memory Dataset, and then access the memory buffer
 directly from Python, use the memory keyword argument to specify the
 estimated size of the Dataset in bytes when creating the Dataset with
-mode='w'.  Then, the Dataset.close method will return a python memoryview
+mode='w'.  Then, the Dataset.close method will return a python memoryview
 object representing the Dataset. Below are examples illustrating both
 approaches.
    
 
@@ -1618,7 +1616,7 @@ 
    In-memory (diskless) Datasets
    
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
    
 
-
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
+
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
 
 
    copyright: 2008 by Jeffrey Whitaker.
    
 
@@ -1628,28 +1626,27 @@ 
    In-memory (diskless) Datasets
    
 
 
    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
    
 
    
-                    
-                
    
-            
-            
+
                 
-                    
    
-                        
-                            
    class
-            Dataset:
-        
    
-                        
-                        
-                            
-                        
-                        
    A netCDF Dataset is a collection of dimensions, groups, variables and
+            
    
+                
    
+                                
    
+        #  
+
+        
+        class
+        Dataset:
+    
    
+
+        
+            
    A netCDF Dataset is a collection of dimensions, groups, variables and
 attributes. Together they describe the meaning of data and relations among
-data fields stored in a netCDF file. See Dataset.__init__ for more
+data fields stored in a netCDF file. See Dataset.__init__">Dataset.__init__ for more
 details.
    
 
 
    A list of attribute names corresponding to global netCDF attributes
 defined for the Dataset can be obtained with the
-Dataset.ncattrs method.
+Dataset.ncattrs">Dataset.ncattrs method.
 These attributes can be created by assigning to an attribute of the
 Dataset instance. A dictionary containing all the netCDF attribute
 name/value pairs is provided by the __dict__ attribute of a
@@ -1710,18 +1707,16 @@ 
    In-memory (diskless) Datasets
    
 
    _ncstring_attrs__: If True, all text attributes will be written as variable-length
 strings.
    
 
    
-                        
-                            
-                                
    
-                                    
-                                        
    
-                Dataset(unknown)
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    __init__(self, filename, mode="r", clobber=True, diskless=False,
+
+
+                            
    
+                                        
    #  
+
+        
+            Dataset(unknown)    
    
+
+        
+            
    __init__(self, filename, mode="r", clobber=True, diskless=False,
 persist=False, keepweakref=False, memory=None, encoding=None,
 parallel=False, comm=None, info=None, format='NETCDF4')
    
 
@@ -1794,7 +1789,7 @@ 
    In-memory (diskless) Datasets
    
 If mode = 'w', the memory kwarg should contain the anticipated size
 of the Dataset in bytes (used only for NETCDF3 files).  A memory
 buffer containing a copy of the Dataset is returned by the
-Dataset.close method. Requires netcdf-c version 4.4.1 for mode='r,
+Dataset.close method. Requires netcdf-c version 4.4.1 for mode='r,
 netcdf-c 4.6.2 for mode='w'. To persist the file to disk, the raw
 bytes from the returned buffer can be written into a binary file.
 The Dataset can also be re-opened using this memory buffer.
    
@@ -1812,91 +1807,86 @@ 
    In-memory (diskless) Datasets
    
 
    info: MPI_Info object for parallel access. Default None, which
 means MPI_INFO_NULL will be used.  Ignored if parallel=False.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                filepath(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    filepath(self,encoding=None)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            filepath(unknown):
+    
    
+
+        
+            
    filepath(self,encoding=None)
    
 
 
    Get the file system path (or the opendap URL) which was used to
 open/create the Dataset. Requires netcdf >= 4.1.2.  The path
 is decoded into a string using sys.getfilesystemencoding() by default, this can be
 changed using the encoding kwarg.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                close(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    close(self)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            close(unknown):
+    
    
+
+        
+            
    close(self)
    
 
 
    Close the Dataset.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                isopen(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    close(self)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            isopen(unknown):
+    
    
+
+        
+            
    close(self)
    
 
 
    is the Dataset open or closed?
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                sync(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    sync(self)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            sync(unknown):
+    
    
+
+        
+            
    sync(self)
    
 
 
    Writes all buffered data in the Dataset to the disk file.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_fill_on(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_fill_on(self)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            set_fill_on(unknown):
+    
    
+
+        
+            
    set_fill_on(self)
    
 
 
    Sets the fill mode for a Dataset open for writing to on.
    
 
@@ -1908,20 +1898,19 @@ 
    In-memory (diskless) Datasets
    
 _Fill_Value indicate that the variable was created, but never written
 to.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_fill_off(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_fill_off(self)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            set_fill_off(unknown):
+    
    
+
+        
+            
    set_fill_off(self)
    
 
 
    Sets the fill mode for a Dataset open for writing to off.
    
 
@@ -1929,20 +1918,19 @@ 
    In-memory (diskless) Datasets
    
 may result in some performance improvements. However, you must then make
 sure the data is actually written before being read.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                createDimension(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    createDimension(self, dimname, size=None)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            createDimension(unknown):
+    
    
+
+        
+            
    createDimension(self, dimname, size=None)
    
 
 
    Creates a new dimension with the given dimname and size.
    
 
@@ -1952,39 +1940,37 @@ 
    In-memory (diskless) Datasets
    
 class instance describing the new dimension.  To determine the current
 maximum size of the dimension, use the len function on the Dimension
 instance. To determine if a dimension is 'unlimited', use the
-Dimension.isunlimited method of the Dimension instance.
    
+Dimension.isunlimited">Dimension.isunlimited method of the Dimension instance.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                renameDimension(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    renameDimension(self, oldname, newname)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            renameDimension(unknown):
+    
    
+
+        
+            
    renameDimension(self, oldname, newname)
    
 
 
    rename a Dimension named oldname to newname.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                createCompoundType(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    createCompoundType(self, datatype, datatype_name)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            createCompoundType(unknown):
+    
    
+
+        
+            
    createCompoundType(self, datatype, datatype_name)
    
 
 
    Creates a new compound data type named datatype_name from the numpy
 dtype object datatype.
    
@@ -1997,20 +1983,19 @@ 
    In-memory (diskless) Datasets
    
 
    The return value is the CompoundType class instance describing the new
 datatype.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                createVLType(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    createVLType(self, datatype, datatype_name)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            createVLType(unknown):
+    
    
+
+        
+            
    createVLType(self, datatype, datatype_name)
    
 
 
    Creates a new VLEN data type named datatype_name from a numpy
 dtype object datatype.
    
@@ -2018,20 +2003,19 @@ 
    In-memory (diskless) Datasets
    
 
    The return value is the VLType class instance describing the new
 datatype.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                createEnumType(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    createEnumType(self, datatype, datatype_name, enum_dict)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            createEnumType(unknown):
+    
    
+
+        
+            
    createEnumType(self, datatype, datatype_name, enum_dict)
    
 
 
    Creates a new Enum data type named datatype_name from a numpy
 integer dtype object datatype, and a python dictionary
@@ -2040,20 +2024,19 @@ 
    In-memory (diskless) Datasets
    
 
    The return value is the EnumType class instance describing the new
 datatype.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                createVariable(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    createVariable(self, varname, datatype, dimensions=(), zlib=False,
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            createVariable(unknown):
+    
    
+
+        
+            
    createVariable(self, varname, datatype, dimensions=(), zlib=False,
 complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None,
 endian='native', least_significant_digit=None, fill_value=None, chunk_cache=None)
    
 
@@ -2083,7 +2066,7 @@ 
    In-memory (diskless) Datasets
    
 the corresponding data type.
    
 
 
    dimensions must be a tuple containing dimension names (strings) that
-have been defined previously using Dataset.createDimension. The default value
+have been defined previously using Dataset.createDimension">Dataset.createDimension. The default value
 is an empty tuple, which means the variable is a scalar.
    
 
 
    If the optional keyword zlib is True, the data will be compressed in
@@ -2154,7 +2137,7 @@ 
    In-memory (diskless) Datasets
    
 variable.
    
 
 
    A list of names corresponding to netCDF variable attributes can be
-obtained with the Variable method Variable.ncattrs. A dictionary
+obtained with the Variable method Variable.ncattrs">Variable.ncattrs. A dictionary
 containing all the netCDF attribute name/value pairs is provided by
 the __dict__ attribute of a Variable instance.
    
 
@@ -2175,37 +2158,35 @@ 
    In-memory (diskless) Datasets
    
 instance. If None, the data is not truncated. The ndim attribute
 is the number of variable dimensions.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                renameVariable(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    renameVariable(self, oldname, newname)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            renameVariable(unknown):
+    
    
+
+        
+            
    renameVariable(self, oldname, newname)
    
 
 
    rename a Variable named oldname to newname
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                createGroup(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    createGroup(self, groupname)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            createGroup(unknown):
+    
    
+
+        
+            
    createGroup(self, groupname)
    
 
 
    Creates a new Group with the given groupname.
    
 
@@ -2219,95 +2200,90 @@ 
    In-memory (diskless) Datasets
    
 
 
    The return value is a Group class instance.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                ncattrs(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    ncattrs(self)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            ncattrs(unknown):
+    
    
+
+        
+            
    ncattrs(self)
    
 
 
    return netCDF global attribute names for this Dataset or Group in a list.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                setncattr(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    setncattr(self,name,value)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            setncattr(unknown):
+    
    
+
+        
+            
    setncattr(self,name,value)
    
 
 
    set a netCDF dataset or group attribute using name,value pair.
 Use if you need to set a netCDF attribute with the
 with the same name as one of the reserved python attributes.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                setncattr_string(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    setncattr_string(self,name,value)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            setncattr_string(unknown):
+    
    
+
+        
+            
    setncattr_string(self,name,value)
    
 
 
    set a netCDF dataset or group string attribute using name,value pair.
 Use if you need to ensure that a netCDF attribute is created with type
 NC_STRING if the file format is NETCDF4.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                setncatts(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    setncatts(self,attdict)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            setncatts(unknown):
+    
    
+
+        
+            
    setncatts(self,attdict)
    
 
 
    set a bunch of netCDF dataset or group attributes at once using a python dictionary.
 This may be faster when setting a lot of attributes for a NETCDF3
 formatted file, since nc_redef/nc_enddef is not called in between setting
 each attribute
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                getncattr(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    getncattr(self,name)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            getncattr(unknown):
+    
    
+
+        
+            
    getncattr(self,name)
    
 
 
    retrieve a netCDF dataset or group attribute.
 Use if you need to get a netCDF attribute with the same
@@ -2316,75 +2292,71 @@ 
    In-memory (diskless) Datasets
    
 
    option kwarg encoding can be used to specify the
 character encoding of a string attribute (default is utf-8).
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                delncattr(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    delncattr(self,name,value)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            delncattr(unknown):
+    
    
+
+        
+            
    delncattr(self,name,value)
    
 
 
    delete a netCDF dataset or group attribute.  Use if you need to delete a
 netCDF attribute with the same name as one of the reserved python
 attributes.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                renameAttribute(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    renameAttribute(self, oldname, newname)
    
 
-
    rename a Dataset or Group attribute named oldname to newname.
    
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            renameAttribute(unknown):
+    
    
+
+        
+            
    renameAttribute(self, oldname, newname)
    
+
+
    rename a Dataset or Group attribute named oldname to newname.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                renameGroup(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    renameGroup(self, oldname, newname)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            renameGroup(unknown):
+    
    
+
+        
+            
    renameGroup(self, oldname, newname)
    
 
 
    rename a Group named oldname to newname (requires netcdf >= 4.3.1).
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_auto_chartostring(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_auto_chartostring(self, True_or_False)
    
-
-
    Call Variable.set_auto_chartostring for all variables contained in this Dataset or
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            set_auto_chartostring(unknown):
+    
    
+
+        
+            
    set_auto_chartostring(self, True_or_False)
    
+
+
    Call Variable.set_auto_chartostring">Variable.set_auto_chartostring for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
    
 
 
    True_or_False: Boolean determining if automatic conversion of
@@ -2395,22 +2367,21 @@ 
    In-memory (diskless) Datasets
    
 
    Note: Calling this function only affects existing variables. Variables created
 after calling this function will follow the default behaviour.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_auto_maskandscale(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_auto_maskandscale(self, True_or_False)
    
-
-
    Call Variable.set_auto_maskandscale for all variables contained in this Dataset or
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            set_auto_maskandscale(unknown):
+    
    
+
+        
+            
    set_auto_maskandscale(self, True_or_False)
    
+
+
    Call Variable.set_auto_maskandscale">Variable.set_auto_maskandscale for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
    
 
 
    True_or_False: Boolean determining if automatic conversion to masked arrays
@@ -2419,22 +2390,21 @@ 
    In-memory (diskless) Datasets
    
 
    Note: Calling this function only affects existing variables. Variables created
 after calling this function will follow the default behaviour.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_auto_mask(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_auto_mask(self, True_or_False)
    
-
-
    Call Variable.set_auto_mask for all variables contained in this Dataset or
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            set_auto_mask(unknown):
+    
    
+
+        
+            
    set_auto_mask(self, True_or_False)
    
+
+
    Call Variable.set_auto_mask">Variable.set_auto_mask for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
    
 
 
    True_or_False: Boolean determining if automatic conversion to masked arrays
@@ -2443,22 +2413,21 @@ 
    In-memory (diskless) Datasets
    
 
    Note: Calling this function only affects existing variables. Variables created
 after calling this function will follow the default behaviour.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_auto_scale(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_auto_scale(self, True_or_False)
    
-
-
    Call Variable.set_auto_scale for all variables contained in this Dataset or
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            set_auto_scale(unknown):
+    
    
+
+        
+            
    set_auto_scale(self, True_or_False)
    
+
+
    Call Variable.set_auto_scale">Variable.set_auto_scale for all variables contained in this Dataset or
 Group, as well as for all variables in all its subgroups.
    
 
 
    True_or_False: Boolean determining if automatic variable scaling
@@ -2467,22 +2436,21 @@ 
    In-memory (diskless) Datasets
    
 
    Note: Calling this function only affects existing variables. Variables created
 after calling this function will follow the default behaviour.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_always_mask(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_always_mask(self, True_or_False)
    
-
-
    Call Variable.set_always_mask for all variables contained in
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            set_always_mask(unknown):
+    
    
+
+        
+            
    set_always_mask(self, True_or_False)
    
+
+
    Call Variable.set_always_mask">Variable.set_always_mask for all variables contained in
 this Dataset or Group, as well as for all
 variables in all its subgroups.
    
 
@@ -2496,22 +2464,21 @@ 
    In-memory (diskless) Datasets
    
 variables. Variables created after calling this function will follow
 the default behaviour.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_ncstring_attrs(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_ncstring_attrs(self, True_or_False)
    
-
-
    Call Variable.set_ncstring_attrs for all variables contained in
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            set_ncstring_attrs(unknown):
+    
    
+
+        
+            
    set_ncstring_attrs(self, True_or_False)
    
+
+
    Call Variable.set_ncstring_attrs">Variable.set_ncstring_attrs for all variables contained in
 this Dataset or Group, as well as for all its
 subgroups and their variables.
    
 
@@ -2522,20 +2489,19 @@ 
    In-memory (diskless) Datasets
    
 
    Note: Calling this function only affects newly created attributes
 of existing (sub-) groups and their variables.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                get_variables_by_attributes(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    get_variables_by_attribute(self, **kwargs)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            get_variables_by_attributes(unknown):
+    
    
+
+        
+            
    get_variables_by_attribute(self, **kwargs)
    
 
 
    Returns a list of variables that match specific conditions.
    
 
@@ -2561,982 +2527,331 @@ 
    In-memory (diskless) Datasets
    
 >>> vs = nc.get_variables_by_attributes(grid_mapping=lambda v: v is not None)
 
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    name = <attribute 'name' of 'netCDF4._netCDF4.Dataset' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    groups = <attribute 'groups' of 'netCDF4._netCDF4.Dataset' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Dataset' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    variables = <attribute 'variables' of 'netCDF4._netCDF4.Dataset' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    disk_format = <attribute 'disk_format' of 'netCDF4._netCDF4.Dataset' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    path = <attribute 'path' of 'netCDF4._netCDF4.Dataset' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    parent = <attribute 'parent' of 'netCDF4._netCDF4.Dataset' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    file_format = <attribute 'file_format' of 'netCDF4._netCDF4.Dataset' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    data_model = <attribute 'data_model' of 'netCDF4._netCDF4.Dataset' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    cmptypes = <attribute 'cmptypes' of 'netCDF4._netCDF4.Dataset' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    vltypes = <attribute 'vltypes' of 'netCDF4._netCDF4.Dataset' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    enumtypes = <attribute 'enumtypes' of 'netCDF4._netCDF4.Dataset' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    keepweakref = <attribute 'keepweakref' of 'netCDF4._netCDF4.Dataset' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                            
-                        
-                    
-                
-                    
    
-                        
-                            
    class
-            Group(netCDF4._netCDF4.Dataset):
-        
    
-                        
-                        
-                            
-                        
-                        
    Groups define a hierarchical namespace within a netCDF file. They are
-analogous to directories in a unix filesystem. Each Group behaves like
-a Dataset within a Dataset, and can contain it's own variables,
-dimensions and attributes (and other Groups). See Group.__init__
-for more details.
    
 
-
    Group inherits from Dataset, so all the
-Dataset class methods and variables are available
-to a Group instance (except the close method).
    
 
-
    Additional read-only class variables:
    
+                            
    
+                            
    
+                                        
    #  
 
-
    name: String describing the group name.
    
-
    
-                        
-                            
-                                
    
-                                    
-                                        
    
-                Group(unknown)
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    __init__(self, parent, name)
-Group constructor.
    
+        
+            def
+            fromcdl(unknown):
+    
    
 
-
    parent: Group instance for the parent group.  If being created
-in the root group, use a Dataset instance.
    
+        
+            
    fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')
    
 
-
    name: - Name of the group.
    
+
    call ncgen via subprocess to create Dataset from CDL text representation.
    
 
-
    Note: Group instances should be created using the
-Dataset.createGroup method of a Dataset instance, or
-another Group instance, not using this class directly.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                close(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    close(self)
    
+
    cdlfilename:  CDL file.
    
 
-
    overrides Dataset close method which does not apply to Group
-instances, raises IOError.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                filepath(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    filepath(self,encoding=None)
    
+
    ncfilename: netCDF file to create. If not given, CDL filename with
+suffix replaced by .nc is used..
    
 
-
    Get the file system path (or the opendap URL) which was used to
-open/create the Dataset. Requires netcdf >= 4.1.2.  The path
-is decoded into a string using sys.getfilesystemencoding() by default, this can be
-changed using the encoding kwarg.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                isopen(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    close(self)
    
+
    mode:  Access mode to open Dataset (Default 'a').
    
 
-
    is the Dataset open or closed?
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                sync(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    sync(self)
    
+
    format: underlying file format to use (one of 'NETCDF4',
+'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC', 'NETCDF3_64BIT_OFFSET' or
+'NETCDF3_64BIT_DATA'. Default 'NETCDF4'.
    
 
-
    Writes all buffered data in the Dataset to the disk file.
    
+
    Dataset instance for ncfilename is returned.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_fill_on(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_fill_on(self)
    
 
-
    Sets the fill mode for a Dataset open for writing to on.
    
 
-
    This causes data to be pre-filled with fill values. The fill values can be
-controlled by the variable's _Fill_Value attribute, but is usually
-sufficient to the use the netCDF default _Fill_Value (defined
-separately for each variable type). The default behavior of the netCDF
-library corresponds to set_fill_on.  Data which are equal to the
-_Fill_Value indicate that the variable was created, but never written
-to.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_fill_off(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_fill_off(self)
    
+                            
    
+                            
    
+                                        
    #  
 
-
    Sets the fill mode for a Dataset open for writing to off.
    
+        
+            def
+            tocdl(unknown):
+    
    
 
-
    This will prevent the data from being pre-filled with fill values, which
-may result in some performance improvements. However, you must then make
-sure the data is actually written before being read.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                createDimension(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    createDimension(self, dimname, size=None)
    
+        
+            
    tocdl(self, coordvars=False, data=False, outfile=None)
    
 
-
    Creates a new dimension with the given dimname and size.
    
+
    call ncdump via subprocess to create CDL text representation of Dataset
    
 
-
    size must be a positive integer or None, which stands for
-"unlimited" (default is None). Specifying a size of 0 also
-results in an unlimited dimension. The return value is the Dimension
-class instance describing the new dimension.  To determine the current
-maximum size of the dimension, use the len function on the Dimension
-instance. To determine if a dimension is 'unlimited', use the
-Dimension.isunlimited method of the Dimension instance.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                renameDimension(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    renameDimension(self, oldname, newname)
    
+
    coordvars: include coordinate variable data (via ncdump -c). Default False
    
 
-
    rename a Dimension named oldname to newname.
    
+
    data: if True, write out variable data (Default False).
    
+
+
    outfile: If not None, file to output ncdump to. Default is to return a string.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                createCompoundType(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    createCompoundType(self, datatype, datatype_name)
    
 
-
    Creates a new compound data type named datatype_name from the numpy
-dtype object datatype.
    
 
-
    Note: If the new compound data type contains other compound data types
-(i.e. it is a 'nested' compound type, where not all of the elements
-are homogeneous numeric data types), then the 'inner' compound types must be
-created first.
    
+                            
    
+                            
    
+                                            
    #  
 
-
    The return value is the CompoundType class instance describing the new
-datatype.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                createVLType(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    createVLType(self, datatype, datatype_name)
    
+        name = <attribute 'name' of 'netCDF4._netCDF4.Dataset' objects>
+    
    
 
-
    Creates a new VLEN data type named datatype_name from a numpy
-dtype object datatype.
    
+    
 
-
    The return value is the VLType class instance describing the new
-datatype.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                createEnumType(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    createEnumType(self, datatype, datatype_name, enum_dict)
    
+                            
    
+                            
    
+                                            
    #  
 
-
    Creates a new Enum data type named datatype_name from a numpy
-integer dtype object datatype, and a python dictionary
-defining the enum fields and values.
    
+        groups = <attribute 'groups' of 'netCDF4._netCDF4.Dataset' objects>
+    
    
 
-
    The return value is the EnumType class instance describing the new
-datatype.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                createVariable(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    createVariable(self, varname, datatype, dimensions=(), zlib=False,
-complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None,
-endian='native', least_significant_digit=None, fill_value=None, chunk_cache=None)
    
+    
 
-
    Creates a new variable with the given varname, datatype, and
-dimensions. If dimensions are not given, the variable is assumed to be
-a scalar.
    
+                            
    
+                            
    
+                                            
    #  
 
-
    If varname is specified as a path, using forward slashes as in unix to
-separate components, then intermediate groups will be created as necessary
-For example, createVariable('/GroupA/GroupB/VarC', float, ('x','y')) will create groups GroupA
-and GroupA/GroupB, plus the variable GroupA/GroupB/VarC, if the preceding
-groups don't already exist.
    
+        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Dataset' objects>
+    
    
 
-
    The datatype can be a numpy datatype object, or a string that describes
-a numpy dtype object (like the dtype.str attribute of a numpy array).
-Supported specifiers include: 'S1' or 'c' (NC_CHAR), 'i1' or 'b' or 'B'
-(NC_BYTE), 'u1' (NC_UBYTE), 'i2' or 'h' or 's' (NC_SHORT), 'u2'
-(NC_USHORT), 'i4' or 'i' or 'l' (NC_INT), 'u4' (NC_UINT), 'i8' (NC_INT64),
-'u8' (NC_UINT64), 'f4' or 'f' (NC_FLOAT), 'f8' or 'd' (NC_DOUBLE).
-datatype can also be a CompoundType instance
-(for a structured, or compound array), a VLType instance
-(for a variable-length array), or the python str builtin
-(for a variable-length string array). Numpy string and unicode datatypes with
-length greater than one are aliases for str.
    
+    
 
-
    Data from netCDF variables is presented to python as numpy arrays with
-the corresponding data type.
    
+                            
    
+                            
    
+                                            
    #  
 
-
    dimensions must be a tuple containing dimension names (strings) that
-have been defined previously using Dataset.createDimension. The default value
-is an empty tuple, which means the variable is a scalar.
    
+        variables = <attribute 'variables' of 'netCDF4._netCDF4.Dataset' objects>
+    
    
 
-
    If the optional keyword zlib is True, the data will be compressed in
-the netCDF file using gzip compression (default False).
    
+    
 
-
    The optional keyword complevel is an integer between 1 and 9 describing
-the level of compression desired (default 4). Ignored if zlib=False.
    
+                            
    
+                            
    
+                                            
    #  
 
-
    If the optional keyword shuffle is True, the HDF5 shuffle filter
-will be applied before compressing the data (default True).  This
-significantly improves compression. Default is True. Ignored if
-zlib=False.
    
+        disk_format = <attribute 'disk_format' of 'netCDF4._netCDF4.Dataset' objects>
+    
    
 
-
    If the optional keyword fletcher32 is True, the Fletcher32 HDF5
-checksum algorithm is activated to detect errors. Default False.
    
+    
 
-
    If the optional keyword contiguous is True, the variable data is
-stored contiguously on disk.  Default False. Setting to True for
-a variable with an unlimited dimension will trigger an error.
    
+                            
    
+                            
    
+                                            
    #  
 
-
    The optional keyword chunksizes can be used to manually specify the
-HDF5 chunksizes for each dimension of the variable. A detailed
-discussion of HDF chunking and I/O performance is available
-here.
-Basically, you want the chunk size for each dimension to match as
-closely as possible the size of the data block that users will read
-from the file.  chunksizes cannot be set if contiguous=True.
    
+        path = <attribute 'path' of 'netCDF4._netCDF4.Dataset' objects>
+    
    
 
-
    The optional keyword endian can be used to control whether the
-data is stored in little or big endian format on disk. Possible
-values are little, big or native (default). The library
-will automatically handle endian conversions when the data is read,
-but if the data is always going to be read on a computer with the
-opposite format as the one used to create the file, there may be
-some performance advantage to be gained by setting the endian-ness.
    
+    
 
-
    The zlib, complevel, shuffle, fletcher32, contiguous, chunksizes and endian
-keywords are silently ignored for netCDF 3 files that do not use HDF5.
    
+                            
    
+                            
    
+                                            
    #  
 
-
    The optional keyword fill_value can be used to override the default
-netCDF _FillValue (the value that the variable gets filled with before
-any data is written to it, defaults given in default_fillvals).
-If fill_value is set to False, then the variable is not pre-filled.
    
+        parent = <attribute 'parent' of 'netCDF4._netCDF4.Dataset' objects>
+    
    
 
-
    If the optional keyword parameter least_significant_digit is
-specified, variable data will be truncated (quantized). In conjunction
-with zlib=True this produces 'lossy', but significantly more
-efficient compression. For example, if least_significant_digit=1,
-data will be quantized using numpy.around(scale*data)/scale, where
-scale = 2**bits, and bits is determined so that a precision of 0.1 is
-retained (in this case bits=4). From the
-PSL metadata conventions:
-"least_significant_digit -- power of ten of the smallest decimal place
-in unpacked data that is a reliable value." Default is None, or no
-quantization, or 'lossless' compression.
    
+    
 
-
    When creating variables in a NETCDF4 or NETCDF4_CLASSIC formatted file,
-HDF5 creates something called a 'chunk cache' for each variable.  The
-default size of the chunk cache may be large enough to completely fill
-available memory when creating thousands of variables.  The optional
-keyword chunk_cache allows you to reduce (or increase) the size of
-the default chunk cache when creating a variable.  The setting only
-persists as long as the Dataset is open - you can use the set_var_chunk_cache
-method to change it the next time the Dataset is opened.
-Warning - messing with this parameter can seriously degrade performance.
    
+                            
    
+                            
    
+                                            
    #  
 
-
    The return value is the Variable class instance describing the new
-variable.
    
+        file_format = <attribute 'file_format' of 'netCDF4._netCDF4.Dataset' objects>
+    
    
 
-
    A list of names corresponding to netCDF variable attributes can be
-obtained with the Variable method Variable.ncattrs. A dictionary
-containing all the netCDF attribute name/value pairs is provided by
-the __dict__ attribute of a Variable instance.
    
+    
 
-
    Variable instances behave much like array objects. Data can be
-assigned to or retrieved from a variable with indexing and slicing
-operations on the Variable instance. A Variable instance has six
-Dataset standard attributes: dimensions, dtype, shape, ndim, name and
-least_significant_digit. Application programs should never modify
-these attributes. The dimensions attribute is a tuple containing the
-names of the dimensions associated with this variable. The dtype
-attribute is a string describing the variable's data type (i4, f8,
-S1, etc). The shape attribute is a tuple describing the current
-sizes of all the variable's dimensions. The name attribute is a
-string containing the name of the Variable instance.
-The least_significant_digit
-attributes describes the power of ten of the smallest decimal place in
-the data the contains a reliable value.  assigned to the Variable
-instance. If None, the data is not truncated. The ndim attribute
-is the number of variable dimensions.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                renameVariable(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    renameVariable(self, oldname, newname)
    
+                            
    
+                            
    
+                                            
    #  
 
-
    rename a Variable named oldname to newname
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                createGroup(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    createGroup(self, groupname)
    
+        data_model = <attribute 'data_model' of 'netCDF4._netCDF4.Dataset' objects>
+    
    
 
-
    Creates a new Group with the given groupname.
    
+    
 
-
    If groupname is specified as a path, using forward slashes as in unix to
-separate components, then intermediate groups will be created as necessary
-(analogous to mkdir -p in unix).  For example,
-createGroup('/GroupA/GroupB/GroupC') will create GroupA,
-GroupA/GroupB, and GroupA/GroupB/GroupC, if they don't already exist.
-If the specified path describes a group that already exists, no error is
-raised.
    
+                            
    
+                            
    
+                                            
    #  
 
-
    The return value is a Group class instance.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                ncattrs(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    ncattrs(self)
    
+        cmptypes = <attribute 'cmptypes' of 'netCDF4._netCDF4.Dataset' objects>
+    
    
 
-
    return netCDF global attribute names for this Dataset or Group in a list.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                setncattr(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    setncattr(self,name,value)
    
+    
 
-
    set a netCDF dataset or group attribute using name,value pair.
-Use if you need to set a netCDF attribute with the
-with the same name as one of the reserved python attributes.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                setncattr_string(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    setncattr_string(self,name,value)
    
+                            
    
+                            
    
+                                            
    #  
 
-
    set a netCDF dataset or group string attribute using name,value pair.
-Use if you need to ensure that a netCDF attribute is created with type
-NC_STRING if the file format is NETCDF4.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                setncatts(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    setncatts(self,attdict)
    
+        vltypes = <attribute 'vltypes' of 'netCDF4._netCDF4.Dataset' objects>
+    
    
 
-
    set a bunch of netCDF dataset or group attributes at once using a python dictionary.
-This may be faster when setting a lot of attributes for a NETCDF3
-formatted file, since nc_redef/nc_enddef is not called in between setting
-each attribute
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                getncattr(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    getncattr(self,name)
    
+    
 
-
    retrieve a netCDF dataset or group attribute.
-Use if you need to get a netCDF attribute with the same
-name as one of the reserved python attributes.
    
+                            
    
+                            
    
+                                            
    #  
 
-
    option kwarg encoding can be used to specify the
-character encoding of a string attribute (default is utf-8).
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                delncattr(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    delncattr(self,name,value)
    
+        enumtypes = <attribute 'enumtypes' of 'netCDF4._netCDF4.Dataset' objects>
+    
    
 
-
    delete a netCDF dataset or group attribute.  Use if you need to delete a
-netCDF attribute with the same name as one of the reserved python
-attributes.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                renameAttribute(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    renameAttribute(self, oldname, newname)
    
+    
 
-
    rename a Dataset or Group attribute named oldname to newname.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                renameGroup(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    renameGroup(self, oldname, newname)
    
+                            
    
+                            
    
+                                            
    #  
 
-
    rename a Group named oldname to newname (requires netcdf >= 4.3.1).
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_auto_chartostring(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_auto_chartostring(self, True_or_False)
    
-
-
    Call Variable.set_auto_chartostring for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
    
+        keepweakref = <attribute 'keepweakref' of 'netCDF4._netCDF4.Dataset' objects>
+    
    
 
-
    True_or_False: Boolean determining if automatic conversion of
-all character arrays <--> string arrays should be performed for
-character variables (variables of type NC_CHAR or S1) with the
-_Encoding attribute set.
    
+    
 
-
    Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_auto_maskandscale(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_auto_maskandscale(self, True_or_False)
    
-
-
    Call Variable.set_auto_maskandscale for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
    
+                            
    
+                
    
+                
    
+                                
    
+        #  
 
-
    True_or_False: Boolean determining if automatic conversion to masked arrays
-and variable scaling shall be applied for all variables.
    
+        
+        class
+        Group(Dataset):
+    
    
 
-
    Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_auto_mask(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_auto_mask(self, True_or_False)
    
-
-
    Call Variable.set_auto_mask for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
    
+        
+            
    Groups define a hierarchical namespace within a netCDF file. They are
+analogous to directories in a unix filesystem. Each Group behaves like
+a Dataset within a Dataset, and can contain it's own variables,
+dimensions and attributes (and other Groups). See Group.__init__">Group.__init__
+for more details.
    
 
-
    True_or_False: Boolean determining if automatic conversion to masked arrays
-shall be applied for all variables.
    
+
    Group inherits from Dataset, so all the
+Dataset class methods and variables are available
+to a Group instance (except the close method).
    
 
-
    Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
    
+
    Additional read-only class variables:
    
+
+
    name: String describing the group name.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_auto_scale(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_auto_scale(self, True_or_False)
    
-
-
    Call Variable.set_auto_scale for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
    
 
-
    True_or_False: Boolean determining if automatic variable scaling
-shall be applied for all variables.
    
 
-
    Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_always_mask(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_always_mask(self, True_or_False)
    
-
-
    Call Variable.set_always_mask for all variables contained in
-this Dataset or Group, as well as for all
-variables in all its subgroups.
    
+                            
    
+                                        
    #  
 
-
    True_or_False: Boolean determining if automatic conversion of
-masked arrays with no missing values to regular numpy arrays shall be
-applied for all variables. Default True. Set to False to restore the default behaviour
-in versions prior to 1.4.1 (numpy array returned unless missing values are present,
-otherwise masked array returned).
    
+        
+            Group(unknown)    
    
 
-
    Note: Calling this function only affects existing
-variables. Variables created after calling this function will follow
-the default behaviour.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_ncstring_attrs(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_ncstring_attrs(self, True_or_False)
    
-
-
    Call Variable.set_ncstring_attrs for all variables contained in
-this Dataset or Group, as well as for all its
-subgroups and their variables.
    
+        
+            
    __init__(self, parent, name)
+Group constructor.
    
 
-
    True_or_False: Boolean determining if all string attributes are
-created as variable-length NC_STRINGs, (if True), or if ascii text
-attributes are stored as NC_CHARs (if False; default)
    
+
    parent: Group instance for the parent group.  If being created
+in the root group, use a Dataset instance.
    
 
-
    Note: Calling this function only affects newly created attributes
-of existing (sub-) groups and their variables.
    
+
    name: - Name of the group.
    
+
+
    Note: Group instances should be created using the
+Dataset.createGroup">Dataset.createGroup method of a Dataset instance, or
+another Group instance, not using this class directly.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                get_variables_by_attributes(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    get_variables_by_attribute(self, **kwargs)
    
 
-
    Returns a list of variables that match specific conditions.
    
 
-
    Can pass in key=value parameters and variables are returned that
-contain all of the matches. For example,
    
+                            
    
+                            
    
+                                        
    #  
 
-
    >>> # Get variables with x-axis attribute.
->>> vs = nc.get_variables_by_attributes(axis='X')
->>> # Get variables with matching "standard_name" attribute
->>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
-
    
+        
+            def
+            close(unknown):
+    
    
 
-
    Can pass in key=callable parameter and variables are returned if the
-callable returns True.  The callable should accept a single parameter,
-the attribute value.  None is given as the attribute value when the
-attribute does not exist on the variable. For example,
    
+        
+            
    close(self)
    
 
-
    >>> # Get Axis variables
->>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
->>> # Get variables that don't have an "axis" attribute
->>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
->>> # Get variables that have a "grid_mapping" attribute
->>> vs = nc.get_variables_by_attributes(grid_mapping=lambda v: v is not None)
-
    
+
    overrides Dataset close method which does not apply to Group
+instances, raises IOError.
    
 
    
-                                
    
-                            
-                            
-                                
-                                    
    
-                                        
    Inherited Members
    
-                                        
    
-                                            
-                                                
-                                            
-                                        
    
-                                    
    
-                                
-                            
-                        
-                    
-                
-                    
    
-                        
-                            
    class
-            Dimension:
-        
    
-                        
-                        
-                            
-                        
-                        
    A netCDF Dimension is used to describe the coordinates of a Variable.
-See Dimension.__init__ for more details.
    
+
+
+                            
    
+                            
    
+                                
    Inherited Members
    
+                                
    
+                                    
+                                
    
+                            
    
+                
    
+                
    
+                                
    
+        #  
+
+        
+        class
+        Dimension:
+    
    
+
+        
+            
    A netCDF Dimension is used to describe the coordinates of a Variable.
+See Dimension.__init__">Dimension.__init__ for more details.
    
 
 
    The current maximum size of a Dimension instance can be obtained by
 calling the python len function on the Dimension instance. The
-Dimension.isunlimited method of a Dimension instance can be used to
+Dimension.isunlimited">Dimension.isunlimited method of a Dimension instance can be used to
 determine if the dimension is unlimited.
    
 
 
    Read-only class variables:
    
 
 
    name: String name, used when creating a Variable with
-Dataset.createVariable.
    
+Dataset.createVariable">Dataset.createVariable.
    
 
 
    size: Current Dimension size (same as len(d), where d is a
 Dimension instance).
    
 
    
-                        
-                            
-                                
    
-                                    
-                                        
    
-                Dimension(unknown)
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    __init__(self, group, name, size=None)
    
+
+
+                            
    
+                                        
    #  
+
+        
+            Dimension(unknown)    
    
+
+        
+            
    __init__(self, group, name, size=None)
    
 
 
    Dimension constructor.
    
 
@@ -3547,82 +2862,79 @@ 
    Inherited Members
    
 
    size: Size of the dimension. None or 0 means unlimited. (Default None).
    
 
 
    Note: Dimension instances should be created using the
-Dataset.createDimension method of a Group or
-Dataset instance, not using Dimension.__init__ directly.
    
+Dataset.createDimension">Dataset.createDimension method of a Group or
+Dataset instance, not using Dimension.__init__">Dimension.__init__ directly.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                group(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    group(self)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            group(unknown):
+    
    
+
+        
+            
    group(self)
    
 
 
    return the group that this Dimension is a member of.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                isunlimited(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    isunlimited(self)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            isunlimited(unknown):
+    
    
+
+        
+            
    isunlimited(self)
    
 
 
    returns True if the Dimension instance is unlimited, False otherwise.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    name = <attribute 'name' of 'netCDF4._netCDF4.Dimension' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    size = <attribute 'size' of 'netCDF4._netCDF4.Dimension' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                            
-                        
-                    
    
-                
-                    
    
-                        
-                            
    class
-            Variable:
-        
    
-                        
-                        
-                            
-                        
-                        
    A netCDF Variable is used to read and write netCDF data.  They are
-analogous to numpy array objects. See Variable.__init__ for more
+
+
+                            
    
+                            
    
+                                            
    #  
+
+        name = <attribute 'name' of 'netCDF4._netCDF4.Dimension' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        size = <attribute 'size' of 'netCDF4._netCDF4.Dimension' objects>
+    
    
+
+    
+
+                            
    
+                
    
+                
    
+                                
    
+        #  
+
+        
+        class
+        Variable:
+    
    
+
+        
+            
    A netCDF Variable is used to read and write netCDF data.  They are
+analogous to numpy array objects. See Variable.__init__">Variable.__init__ for more
 details.
    
 
 
    A list of attribute names corresponding to netCDF attributes defined for
-the variable can be obtained with the Variable.ncattrs method. These
+the variable can be obtained with the Variable.ncattrs">Variable.ncattrs method. These
 attributes can be created by assigning to an attribute of the
 Variable instance. A dictionary containing all the netCDF attribute
 name/value pairs is provided by the __dict__ attribute of a
@@ -3643,18 +2955,18 @@ 
    Inherited Members
    
 
    scale: If True, scale_factor and add_offset are
 applied, and signed integer data is automatically converted to
 unsigned integer data if the _Unsigned attribute is set.
-Default is True, can be reset using Variable.set_auto_scale and
-Variable.set_auto_maskandscale methods.
    
+Default is True, can be reset using Variable.set_auto_scale">Variable.set_auto_scale and
+Variable.set_auto_maskandscale">Variable.set_auto_maskandscale methods.
    
 
 
    mask: If True, data is automatically converted to/from masked
 arrays when missing values or fill values are present. Default is True, can be
-reset using Variable.set_auto_mask and Variable.set_auto_maskandscale
+reset using Variable.set_auto_mask">Variable.set_auto_mask and Variable.set_auto_maskandscale">Variable.set_auto_maskandscale
 methods.
    
 
-
    chartostring: If True, data is automatically converted to/from character
+
    chartostring: If True, data is automatically converted to/from character
 arrays to string arrays when the _Encoding variable attribute is set.
 Default is True, can be reset using
-Variable.set_auto_chartostring method.
    
+Variable.set_auto_chartostring">Variable.set_auto_chartostring method.
    
 
 
    least_significant_digit: Describes the power of ten of the
 smallest decimal place in the data the contains a reliable value.  Data is
@@ -3673,18 +2985,16 @@ 
    Inherited Members
    
 
 
    size: The number of stored elements.
    
 
    
-                        
-                            
-                                
    
-                                    
-                                        
    
-                Variable(unknown)
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    __init__(self, group, name, datatype, dimensions=(), zlib=False,
+
+
+                            
    
+                                        
    #  
+
+        
+            Variable(unknown)    
    
+
+        
+            
    __init__(self, group, name, datatype, dimensions=(), zlib=False,
 complevel=4, shuffle=True, fletcher32=False, contiguous=False,
 chunksizes=None, endian='native',
 least_significant_digit=None,fill_value=None,chunk_cache=None)
    
@@ -3774,116 +3084,110 @@ 
    Inherited Members
    
 change it when Dataset is re-opened. 
    
 
 
    Note: Variable instances should be created using the
-Dataset.createVariable method of a Dataset or
+Dataset.createVariable">Dataset.createVariable method of a Dataset or
 Group instance, not using this class directly.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                group(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    group(self)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            group(unknown):
+    
    
+
+        
+            
    group(self)
    
 
 
    return the group that this Variable is a member of.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                ncattrs(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    ncattrs(self)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            ncattrs(unknown):
+    
    
+
+        
+            
    ncattrs(self)
    
 
 
    return netCDF attribute names for this Variable in a list.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                setncattr(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    setncattr(self,name,value)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            setncattr(unknown):
+    
    
+
+        
+            
    setncattr(self,name,value)
    
 
 
    set a netCDF variable attribute using name,value pair.  Use if you need to set a
 netCDF attribute with the same name as one of the reserved python
 attributes.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                setncattr_string(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    setncattr_string(self,name,value)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            setncattr_string(unknown):
+    
    
+
+        
+            
    setncattr_string(self,name,value)
    
 
 
    set a netCDF variable string attribute using name,value pair.
 Use if you need to ensure that a netCDF attribute is created with type
 NC_STRING if the file format is NETCDF4.
 Use if you need to set an attribute to an array of variable-length strings.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                setncatts(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    setncatts(self,attdict)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            setncatts(unknown):
+    
    
+
+        
+            
    setncatts(self,attdict)
    
 
 
    set a bunch of netCDF variable attributes at once using a python dictionary.
 This may be faster when setting a lot of attributes for a NETCDF3
 formatted file, since nc_redef/nc_enddef is not called in between setting
 each attribute
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                getncattr(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    getncattr(self,name)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            getncattr(unknown):
+    
    
+
+        
+            
    getncattr(self,name)
    
 
 
    retrieve a netCDF variable attribute.  Use if you need to set a
 netCDF attribute with the same name as one of the reserved python
@@ -3892,190 +3196,180 @@ 
    Inherited Members
    
 
    option kwarg encoding can be used to specify the
 character encoding of a string attribute (default is utf-8).
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                delncattr(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    delncattr(self,name,value)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            delncattr(unknown):
+    
    
+
+        
+            
    delncattr(self,name,value)
    
 
 
    delete a netCDF variable attribute.  Use if you need to delete a
 netCDF attribute with the same name as one of the reserved python
 attributes.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                filters(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    filters(self)
    
 
-
    return dictionary containing HDF5 filter parameters.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                endian(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    endian(self)
    
 
-
    return endian-ness (little,big,native) of variable (as stored in HDF5 file).
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                chunking(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    chunking(self)
    
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            filters(unknown):
+    
    
+
+        
+            
    filters(self)
    
+
+
    return dictionary containing HDF5 filter parameters.
    
+
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            endian(unknown):
+    
    
+
+        
+            
    endian(self)
    
+
+
    return endian-ness (little,big,native) of variable (as stored in HDF5 file).
    
+
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            chunking(unknown):
+    
    
+
+        
+            
    chunking(self)
    
 
 
    return variable chunking information.  If the dataset is
 defined to be contiguous (and hence there is no chunking) the word 'contiguous'
 is returned.  Otherwise, a sequence with the chunksize for
 each dimension is returned.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                get_var_chunk_cache(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    get_var_chunk_cache(self)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            get_var_chunk_cache(unknown):
+    
    
+
+        
+            
    get_var_chunk_cache(self)
    
 
 
    return variable chunk cache information in a tuple (size,nelems,preemption).
 See netcdf C library documentation for nc_get_var_chunk_cache for
 details.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_var_chunk_cache(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_var_chunk_cache(self,size=None,nelems=None,preemption=None)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            set_var_chunk_cache(unknown):
+    
    
+
+        
+            
    set_var_chunk_cache(self,size=None,nelems=None,preemption=None)
    
 
 
    change variable chunk cache settings.
 See netcdf C library documentation for nc_set_var_chunk_cache for
 details.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                renameAttribute(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    renameAttribute(self, oldname, newname)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            renameAttribute(unknown):
+    
    
+
+        
+            
    renameAttribute(self, oldname, newname)
    
 
 
    rename a Variable attribute named oldname to newname.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                assignValue(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    assignValue(self, val)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            assignValue(unknown):
+    
    
+
+        
+            
    assignValue(self, val)
    
 
 
    assign a value to a scalar variable.  Provided for compatibility with
 Scientific.IO.NetCDF, can also be done by assigning to an Ellipsis slice ([...]).
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                getValue(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    getValue(self)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            getValue(unknown):
+    
    
+
+        
+            
    getValue(self)
    
 
 
    get the value of a scalar variable.  Provided for compatibility with
 Scientific.IO.NetCDF, can also be done by slicing with an Ellipsis ([...]).
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_auto_chartostring(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_auto_chartostring(self,chartostring)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            set_auto_chartostring(unknown):
+    
    
+
+        
+            
    set_auto_chartostring(self,chartostring)
    
 
 
    turn on or off automatic conversion of character variable data to and
 from numpy fixed length string arrays when the _Encoding variable attribute
 is set.
    
 
-
    If chartostring is set to True, when data is read from a character variable
+
    If chartostring is set to True, when data is read from a character variable
 (dtype = S1) that has an _Encoding attribute, it is converted to a numpy
 fixed length unicode string array (dtype = UN, where N is the length
 of the the rightmost dimension of the variable).  The value of _Encoding
@@ -4085,23 +3379,22 @@ 
    Inherited Members
    
 indiviual bytes, with the number of bytes in each string equalling the
 rightmost dimension of the variable.
    
 
-
    The default value of chartostring is True
+
    The default value of chartostring is True
 (automatic conversions are performed).
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                use_nc_get_vars(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    use_nc_get_vars(self,_use_get_vars)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            use_nc_get_vars(unknown):
+    
    
+
+        
+            
    use_nc_get_vars(self,_use_get_vars)
    
 
 
    enable the use of netcdf library routine nc_get_vars
 to retrieve strided variable slices.  By default,
@@ -4109,20 +3402,19 @@ 
    Inherited Members
    
 version of the netcdf-c library being used) since it may be
 slower than multiple calls to the unstrided read routine nc_get_vara.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_auto_maskandscale(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_auto_maskandscale(self,maskandscale)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            set_auto_maskandscale(unknown):
+    
    
+
+        
+            
    set_auto_maskandscale(self,maskandscale)
    
 
 
    turn on or off automatic conversion of variable data to and
 from masked arrays, automatic packing/unpacking of variable
@@ -4173,20 +3465,19 @@ 
    Inherited Members
    
 
    The default value of maskandscale is True
 (automatic conversions are performed).
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_auto_scale(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_auto_scale(self,scale)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            set_auto_scale(unknown):
+    
    
+
+        
+            
    set_auto_scale(self,scale)
    
 
 
    turn on or off automatic packing/unpacking of variable
 data using scale_factor and add_offset attributes.
@@ -4223,20 +3514,19 @@ 
    Inherited Members
    
 
    The default value of scale is True
 (automatic conversions are performed).
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_auto_mask(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_auto_mask(self,mask)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            set_auto_mask(unknown):
+    
    
+
+        
+            
    set_auto_mask(self,mask)
    
 
 
    turn on or off automatic conversion of variable data to and
 from masked arrays .
    
@@ -4258,20 +3548,19 @@ 
    Inherited Members
    
 
    The default value of mask is True
 (automatic conversions are performed).
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_always_mask(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_always_mask(self,always_mask)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            set_always_mask(unknown):
+    
    
+
+        
+            
    set_always_mask(self,always_mask)
    
 
 
    turn on or off conversion of data without missing values to regular
 numpy arrays.
    
@@ -4282,20 +3571,19 @@ 
    Inherited Members
    
 in versions prior to 1.4.1 (numpy array returned unless missing values are present,
 otherwise masked array returned).
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_ncstring_attrs(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_always_mask(self,ncstring_attrs)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            set_ncstring_attrs(unknown):
+    
    
+
+        
+            
    set_always_mask(self,ncstring_attrs)
    
 
 
    turn on or off creating NC_STRING string attributes.
    
 
@@ -4305,177 +3593,172 @@ 
    Inherited Members
    
 
    The default value of ncstring_attrs is False (writing ascii text attributes as
 NC_CHAR).
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_collective(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_collective(self,True_or_False)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            set_collective(unknown):
+    
    
+
+        
+            
    set_collective(self,True_or_False)
    
 
 
    turn on or off collective parallel IO access. Ignored if file is not
 open for parallel access.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                get_dims(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    get_dims(self)
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            get_dims(unknown):
+    
    
+
+        
+            
    get_dims(self)
    
 
 
    return a tuple of Dimension instances associated with this
 Variable.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    name = <attribute 'name' of 'netCDF4._netCDF4.Variable' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    datatype = <attribute 'datatype' of 'netCDF4._netCDF4.Variable' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    shape = <attribute 'shape' of 'netCDF4._netCDF4.Variable' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    size = <attribute 'size' of 'netCDF4._netCDF4.Variable' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Variable' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    ndim = <attribute 'ndim' of 'netCDF4._netCDF4.Variable' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    dtype = <attribute 'dtype' of 'netCDF4._netCDF4.Variable' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    mask = <attribute 'mask' of 'netCDF4._netCDF4.Variable' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    scale = <attribute 'scale' of 'netCDF4._netCDF4.Variable' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    always_mask = <attribute 'always_mask' of 'netCDF4._netCDF4.Variable' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    chartostring = <attribute 'chartostring' of 'netCDF4._netCDF4.Variable' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                            
-                        
-                    
    
-                
-                    
    
-                        
-                            
    class
-            CompoundType:
-        
    
-                        
-                        
-                            
-                        
-                        
    A CompoundType instance is used to describe a compound data
-type, and can be passed to the the Dataset.createVariable method of
+
+
+                            
    
+                            
    
+                                            
    #  
+
+        name = <attribute 'name' of 'netCDF4._netCDF4.Variable' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        datatype = <attribute 'datatype' of 'netCDF4._netCDF4.Variable' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        shape = <attribute 'shape' of 'netCDF4._netCDF4.Variable' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        size = <attribute 'size' of 'netCDF4._netCDF4.Variable' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Variable' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        ndim = <attribute 'ndim' of 'netCDF4._netCDF4.Variable' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.Variable' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        mask = <attribute 'mask' of 'netCDF4._netCDF4.Variable' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        scale = <attribute 'scale' of 'netCDF4._netCDF4.Variable' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        always_mask = <attribute 'always_mask' of 'netCDF4._netCDF4.Variable' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        chartostring = <attribute 'chartostring' of 'netCDF4._netCDF4.Variable' objects>
+    
    
+
+    
+
+                            
    
+                
    
+                
    
+                                
    
+        #  
+
+        
+        class
+        CompoundType:
+    
    
+
+        
+            
    A CompoundType instance is used to describe a compound data
+type, and can be passed to the the Dataset.createVariable">Dataset.createVariable method of
 a Dataset or Group instance.
 Compound data types map to numpy structured arrays.
-See CompoundType.__init__ for more details.
    
+See CompoundType.__init__">CompoundType.__init__ for more details.
    
 
 
    The instance variables dtype and name should not be modified by
 the user.
    
 
    
-                        
-                            
-                                
    
-                                    
-                                        
    
-                CompoundType(unknown)
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    __init__(group, datatype, datatype_name)
    
+
+
+                            
    
+                                        
    #  
+
+        
+            CompoundType(unknown)    
    
+
+        
+            
    __init__(group, datatype, datatype_name)
    
 
 
    CompoundType constructor.
    
 
@@ -4494,71 +3777,68 @@ 
    Inherited Members
    
 first).
    
 
 
    Note 2: CompoundType instances should be created using the
-Dataset.createCompoundType
+Dataset.createCompoundType">Dataset.createCompoundType
 method of a Dataset or Group instance, not using this class directly.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    dtype = <attribute 'dtype' of 'netCDF4._netCDF4.CompoundType' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    dtype_view = <attribute 'dtype_view' of 'netCDF4._netCDF4.CompoundType' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    name = <attribute 'name' of 'netCDF4._netCDF4.CompoundType' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                            
-                        
-                    
    
-                
-                    
    
-                        
-                            
    class
-            VLType:
-        
    
-                        
-                        
-                            
-                        
-                        
    A VLType instance is used to describe a variable length (VLEN) data
-type, and can be passed to the the Dataset.createVariable method of
+
+
+                            
    
+                            
    
+                                            
    #  
+
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.CompoundType' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        dtype_view = <attribute 'dtype_view' of 'netCDF4._netCDF4.CompoundType' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        name = <attribute 'name' of 'netCDF4._netCDF4.CompoundType' objects>
+    
    
+
+    
+
+                            
    
+                
    
+                
    
+                                
    
+        #  
+
+        
+        class
+        VLType:
+    
    
+
+        
+            
    A VLType instance is used to describe a variable length (VLEN) data
+type, and can be passed to the the Dataset.createVariable">Dataset.createVariable method of
 a Dataset or Group instance. See
-VLType.__init__for more details.
    
+VLType.__init__">VLType.__init__for more details.
    
 
 
    The instance variables dtype and name should not be modified by
 the user.
    
 
    
-                        
-                            
-                                
    
-                                    
-                                        
    
-                VLType(unknown)
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    __init__(group, datatype, datatype_name)
    
+
+
+                            
    
+                                        
    #  
+
+        
+            VLType(unknown)    
    
+
+        
+            
    __init__(group, datatype, datatype_name)
    
 
 
    VLType constructor.
    
 
@@ -4571,62 +3851,59 @@ 
    Inherited Members
    
 VLEN data type.
    
 
 
    Note: VLType instances should be created using the
-Dataset.createVLType
+Dataset.createVLType">Dataset.createVLType
 method of a Dataset or Group instance, not using this class directly.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    dtype = <attribute 'dtype' of 'netCDF4._netCDF4.VLType' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    name = <attribute 'name' of 'netCDF4._netCDF4.VLType' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                            
-                        
-                    
    
-                
-                    
    
-                        
-                            
    class
-            EnumType:
-        
    
-                        
-                        
-                            
-                        
-                        
    A EnumType instance is used to describe an Enum data
-type, and can be passed to the the Dataset.createVariable method of
+
+
+                            
    
+                            
    
+                                            
    #  
+
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.VLType' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        name = <attribute 'name' of 'netCDF4._netCDF4.VLType' objects>
+    
    
+
+    
+
+                            
    
+                
    
+                
    
+                                
    
+        #  
+
+        
+        class
+        EnumType:
+    
    
+
+        
+            
    A EnumType instance is used to describe an Enum data
+type, and can be passed to the the Dataset.createVariable">Dataset.createVariable method of
 a Dataset or Group instance. See
-EnumType.__init__ for more details.
    
+EnumType.__init__">EnumType.__init__ for more details.
    
 
 
    The instance variables dtype, name and enum_dict should not be modified by
 the user.
    
 
    
-                        
-                            
-                                
    
-                                    
-                                        
    
-                EnumType(unknown)
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    __init__(group, datatype, datatype_name, enum_dict)
    
+
+
+                            
    
+                                        
    #  
+
+        
+            EnumType(unknown)    
    
+
+        
+            
    __init__(group, datatype, datatype_name, enum_dict)
    
 
 
    EnumType constructor.
    
 
@@ -4642,113 +3919,103 @@ 
    Inherited Members
    
 pairs.
    
 
 
    Note: EnumType instances should be created using the
-Dataset.createEnumType
+Dataset.createEnumType">Dataset.createEnumType
 method of a Dataset or Group instance, not using this class directly.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    dtype = <attribute 'dtype' of 'netCDF4._netCDF4.EnumType' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    name = <attribute 'name' of 'netCDF4._netCDF4.EnumType' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                                
    
-                                    
-                                        
    enum_dict = <attribute 'enum_dict' of 'netCDF4._netCDF4.EnumType' objects>
-        
    
-                                    
-                                    
-                                    
-                                
    
-                            
-                            
-                        
-                    
    
-                
-                    
    
-                        
-                            
    
-                def
-                getlibversion(unknown):
-            
-        
    
-                        
-                        
-                            
-                        
-                        
    getlibversion()
    
 
-
    returns a string describing the version of the netcdf library
-used to build the module, and when it was built.
    
-
    
-                        
-                    
    
-                
-                    
    
-                        
-                            
    
-                def
-                get_chunk_cache(unknown):
-            
-        
    
-                        
-                        
-                            
-                        
-                        
    get_chunk_cache()
    
 
-
    return current netCDF chunk cache information in a tuple (size,nelems,preemption).
-See netcdf C library documentation for nc_get_chunk_cache for
-details. Values can be reset with set_chunk_cache.
    
+                            
    
+                            
    
+                                            
    #  
+
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.EnumType' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        name = <attribute 'name' of 'netCDF4._netCDF4.EnumType' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        enum_dict = <attribute 'enum_dict' of 'netCDF4._netCDF4.EnumType' objects>
+    
    
+
+    
+
+                            
    
+                
    
+                
    
+                            
    #  
+
+        
+            def
+            getlibversion(unknown):
+    
    
+
+        
+            
    getlibversion()
    
+
+
    returns a string describing the version of the netcdf library
+used to build the module, and when it was built.
    
 
    
-                        
-                    
    
-                
-                    
    
-                        
-                            
    
-                def
-                set_chunk_cache(unknown):
-            
-        
    
-                        
-                        
-                            
-                        
-                        
    set_chunk_cache(self,size=None,nelems=None,preemption=None)
    
+
+
+                
    
+                
    
+                            
    #  
+
+        
+            def
+            get_chunk_cache(unknown):
+    
    
+
+        
+            
    get_chunk_cache()
    
+
+
    return current netCDF chunk cache information in a tuple (size,nelems,preemption).
+See netcdf C library documentation for nc_get_chunk_cache for
+details. Values can be reset with set_chunk_cache.
    
+
    
+
+
+                
    
+                
    
+                            
    #  
+
+        
+            def
+            set_chunk_cache(unknown):
+    
    
+
+        
+            
    set_chunk_cache(self,size=None,nelems=None,preemption=None)
    
 
 
    change netCDF4 chunk cache settings.
 See netcdf C library documentation for nc_set_chunk_cache for
 details.
    
 
    
-                        
-                    
    
-                
-                    
    
-                        
-                            
    
-                def
-                stringtoarr(unknown):
-            
-        
    
-                        
-                        
-                            
-                        
-                        
    stringtoarr(a, NUMCHARS,dtype='S')
    
+
+
+                
    
+                
    
+                            
    #  
+
+        
+            def
+            stringtoarr(unknown):
+    
    
+
+        
+            
    stringtoarr(a, NUMCHARS,dtype='S')
    
 
 
    convert a string to a character array of length NUMCHARS
    
 
@@ -4764,21 +4031,19 @@ 
    Inherited Members
    
 
    returns a rank 1 numpy character array of length NUMCHARS with datatype 'S1'
 (default) or 'U1' (if dtype='U')
    
 
    
-                        
-                    
    
-                
-                    
    
-                        
-                            
    
-                def
-                stringtochar(unknown):
-            
-        
    
-                        
-                        
-                            
-                        
-                        
    stringtochar(a,encoding='utf-8')
    
+
+
+                
    
+                
    
+                            
    #  
+
+        
+            def
+            stringtochar(unknown):
+    
    
+
+        
+            
    stringtochar(a,encoding='utf-8')
    
 
 
    convert a string array to a character array with one extra dimension
    
 
@@ -4793,21 +4058,19 @@ 
    Inherited Members
    
 
    returns a numpy character array with datatype 'S1' or 'U1'
 and shape a.shape + (N,), where N is the length of each string in a.
    
 
    
-                        
-                    
    
-                
-                    
    
-                        
-                            
    
-                def
-                chartostring(unknown):
-            
-        
    
-                        
-                        
-                            
-                        
-                        
    chartostring(b,encoding='utf-8')
    
+
+
+                
    
+                
    
+                            
    #  
+
+        
+            def
+            chartostring(unknown):
+    
    
+
+        
+            
    chartostring(b,encoding='utf-8')
    
 
 
    convert a character array to a string array with one less dimension.
    
 
@@ -4822,26 +4085,27 @@ 
    Inherited Members
    
 
    returns a numpy string array with datatype 'UN' (or 'SN') and shape
 b.shape[:-1] where where N=b.shape[-1].
    
 
    
-                        
-                    
    
-                
-                    
    
-                        
-                            
    class
-            MFDataset(netCDF4._netCDF4.Dataset):
-        
    
-                        
-                        
-                            
-                        
-                        
    Class for reading multi-file netCDF Datasets, making variables
+
+
+                
    
+                
    
+                                
    
+        #  
+
+        
+        class
+        MFDataset(Dataset):
+    
    
+
+        
+            
    Class for reading multi-file netCDF Datasets, making variables
 spanning multiple files appear as if they were in one file.
 Datasets must be in NETCDF4_CLASSIC, NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET
 or NETCDF3_64BIT_DATA format (NETCDF4 Datasets won't work).
    
 
 
    Adapted from pycdf by Andre Gosselin.
    
 
-
    Example usage (See MFDataset.__init__ for more details):
    
+
    Example usage (See MFDataset.__init__">MFDataset.__init__ for more details):
    
 
 
    >>> import numpy as np
 >>> # create a series of netCDF files with a variable sharing
@@ -4861,18 +4125,16 @@ 
    Inherited Members
    
  96 97 98 99]
 
    
 
    
-                        
-                            
-                                
    
-                                    
-                                        
    
-                MFDataset(files, check=False, aggdim=None, exclude=[], master_file=None)
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    __init__(self, files, check=False, aggdim=None, exclude=[],
+
+
+                            
    
+                                        
    #  
+
+        
+            MFDataset(files, check=False, aggdim=None, exclude=[], master_file=None)    
    
+
+        
+            
    __init__(self, files, check=False, aggdim=None, exclude=[],
 master_file=None)
    
 
 
    Open a Dataset spanning multiple files, making it look as if it was a
@@ -4905,788 +4167,106 @@ 
    Inherited Members
    
 
    master_file: file to use as "master file", defining all the
 variables with an aggregation dimension and all global attributes.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                ncattrs(self):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    ncattrs(self)
    
-
-
    return the netcdf attribute names from the master file.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                close(self):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    close(self)
    
-
-
    close all the open files.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                filepath(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    filepath(self,encoding=None)
    
 
-
    Get the file system path (or the opendap URL) which was used to
-open/create the Dataset. Requires netcdf >= 4.1.2.  The path
-is decoded into a string using sys.getfilesystemencoding() by default, this can be
-changed using the encoding kwarg.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                isopen(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    close(self)
    
 
-
    is the Dataset open or closed?
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                sync(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    sync(self)
    
+                            
    
+                            
    
+                                        
    #  
 
-
    Writes all buffered data in the Dataset to the disk file.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_fill_on(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_fill_on(self)
    
-
-
    Sets the fill mode for a Dataset open for writing to on.
    
-
-
    This causes data to be pre-filled with fill values. The fill values can be
-controlled by the variable's _Fill_Value attribute, but is usually
-sufficient to the use the netCDF default _Fill_Value (defined
-separately for each variable type). The default behavior of the netCDF
-library corresponds to set_fill_on.  Data which are equal to the
-_Fill_Value indicate that the variable was created, but never written
-to.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_fill_off(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_fill_off(self)
    
-
-
    Sets the fill mode for a Dataset open for writing to off.
    
-
-
    This will prevent the data from being pre-filled with fill values, which
-may result in some performance improvements. However, you must then make
-sure the data is actually written before being read.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                createDimension(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    createDimension(self, dimname, size=None)
    
-
-
    Creates a new dimension with the given dimname and size.
    
-
-
    size must be a positive integer or None, which stands for
-"unlimited" (default is None). Specifying a size of 0 also
-results in an unlimited dimension. The return value is the Dimension
-class instance describing the new dimension.  To determine the current
-maximum size of the dimension, use the len function on the Dimension
-instance. To determine if a dimension is 'unlimited', use the
-Dimension.isunlimited method of the Dimension instance.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                renameDimension(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    renameDimension(self, oldname, newname)
    
-
-
    rename a Dimension named oldname to newname.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                createCompoundType(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    createCompoundType(self, datatype, datatype_name)
    
-
-
    Creates a new compound data type named datatype_name from the numpy
-dtype object datatype.
    
-
-
    Note: If the new compound data type contains other compound data types
-(i.e. it is a 'nested' compound type, where not all of the elements
-are homogeneous numeric data types), then the 'inner' compound types must be
-created first.
    
-
-
    The return value is the CompoundType class instance describing the new
-datatype.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                createVLType(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    createVLType(self, datatype, datatype_name)
    
-
-
    Creates a new VLEN data type named datatype_name from a numpy
-dtype object datatype.
    
-
-
    The return value is the VLType class instance describing the new
-datatype.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                createEnumType(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    createEnumType(self, datatype, datatype_name, enum_dict)
    
-
-
    Creates a new Enum data type named datatype_name from a numpy
-integer dtype object datatype, and a python dictionary
-defining the enum fields and values.
    
-
-
    The return value is the EnumType class instance describing the new
-datatype.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                createVariable(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    createVariable(self, varname, datatype, dimensions=(), zlib=False,
-complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None,
-endian='native', least_significant_digit=None, fill_value=None, chunk_cache=None)
    
-
-
    Creates a new variable with the given varname, datatype, and
-dimensions. If dimensions are not given, the variable is assumed to be
-a scalar.
    
-
-
    If varname is specified as a path, using forward slashes as in unix to
-separate components, then intermediate groups will be created as necessary
-For example, createVariable('/GroupA/GroupB/VarC', float, ('x','y')) will create groups GroupA
-and GroupA/GroupB, plus the variable GroupA/GroupB/VarC, if the preceding
-groups don't already exist.
    
-
-
    The datatype can be a numpy datatype object, or a string that describes
-a numpy dtype object (like the dtype.str attribute of a numpy array).
-Supported specifiers include: 'S1' or 'c' (NC_CHAR), 'i1' or 'b' or 'B'
-(NC_BYTE), 'u1' (NC_UBYTE), 'i2' or 'h' or 's' (NC_SHORT), 'u2'
-(NC_USHORT), 'i4' or 'i' or 'l' (NC_INT), 'u4' (NC_UINT), 'i8' (NC_INT64),
-'u8' (NC_UINT64), 'f4' or 'f' (NC_FLOAT), 'f8' or 'd' (NC_DOUBLE).
-datatype can also be a CompoundType instance
-(for a structured, or compound array), a VLType instance
-(for a variable-length array), or the python str builtin
-(for a variable-length string array). Numpy string and unicode datatypes with
-length greater than one are aliases for str.
    
-
-
    Data from netCDF variables is presented to python as numpy arrays with
-the corresponding data type.
    
-
-
    dimensions must be a tuple containing dimension names (strings) that
-have been defined previously using Dataset.createDimension. The default value
-is an empty tuple, which means the variable is a scalar.
    
-
-
    If the optional keyword zlib is True, the data will be compressed in
-the netCDF file using gzip compression (default False).
    
-
-
    The optional keyword complevel is an integer between 1 and 9 describing
-the level of compression desired (default 4). Ignored if zlib=False.
    
-
-
    If the optional keyword shuffle is True, the HDF5 shuffle filter
-will be applied before compressing the data (default True).  This
-significantly improves compression. Default is True. Ignored if
-zlib=False.
    
-
-
    If the optional keyword fletcher32 is True, the Fletcher32 HDF5
-checksum algorithm is activated to detect errors. Default False.
    
-
-
    If the optional keyword contiguous is True, the variable data is
-stored contiguously on disk.  Default False. Setting to True for
-a variable with an unlimited dimension will trigger an error.
    
-
-
    The optional keyword chunksizes can be used to manually specify the
-HDF5 chunksizes for each dimension of the variable. A detailed
-discussion of HDF chunking and I/O performance is available
-here.
-Basically, you want the chunk size for each dimension to match as
-closely as possible the size of the data block that users will read
-from the file.  chunksizes cannot be set if contiguous=True.
    
-
-
    The optional keyword endian can be used to control whether the
-data is stored in little or big endian format on disk. Possible
-values are little, big or native (default). The library
-will automatically handle endian conversions when the data is read,
-but if the data is always going to be read on a computer with the
-opposite format as the one used to create the file, there may be
-some performance advantage to be gained by setting the endian-ness.
    
-
-
    The zlib, complevel, shuffle, fletcher32, contiguous, chunksizes and endian
-keywords are silently ignored for netCDF 3 files that do not use HDF5.
    
-
-
    The optional keyword fill_value can be used to override the default
-netCDF _FillValue (the value that the variable gets filled with before
-any data is written to it, defaults given in default_fillvals).
-If fill_value is set to False, then the variable is not pre-filled.
    
-
-
    If the optional keyword parameter least_significant_digit is
-specified, variable data will be truncated (quantized). In conjunction
-with zlib=True this produces 'lossy', but significantly more
-efficient compression. For example, if least_significant_digit=1,
-data will be quantized using numpy.around(scale*data)/scale, where
-scale = 2**bits, and bits is determined so that a precision of 0.1 is
-retained (in this case bits=4). From the
-PSL metadata conventions:
-"least_significant_digit -- power of ten of the smallest decimal place
-in unpacked data that is a reliable value." Default is None, or no
-quantization, or 'lossless' compression.
    
-
-
    When creating variables in a NETCDF4 or NETCDF4_CLASSIC formatted file,
-HDF5 creates something called a 'chunk cache' for each variable.  The
-default size of the chunk cache may be large enough to completely fill
-available memory when creating thousands of variables.  The optional
-keyword chunk_cache allows you to reduce (or increase) the size of
-the default chunk cache when creating a variable.  The setting only
-persists as long as the Dataset is open - you can use the set_var_chunk_cache
-method to change it the next time the Dataset is opened.
-Warning - messing with this parameter can seriously degrade performance.
    
-
-
    The return value is the Variable class instance describing the new
-variable.
    
-
-
    A list of names corresponding to netCDF variable attributes can be
-obtained with the Variable method Variable.ncattrs. A dictionary
-containing all the netCDF attribute name/value pairs is provided by
-the __dict__ attribute of a Variable instance.
    
-
-
    Variable instances behave much like array objects. Data can be
-assigned to or retrieved from a variable with indexing and slicing
-operations on the Variable instance. A Variable instance has six
-Dataset standard attributes: dimensions, dtype, shape, ndim, name and
-least_significant_digit. Application programs should never modify
-these attributes. The dimensions attribute is a tuple containing the
-names of the dimensions associated with this variable. The dtype
-attribute is a string describing the variable's data type (i4, f8,
-S1, etc). The shape attribute is a tuple describing the current
-sizes of all the variable's dimensions. The name attribute is a
-string containing the name of the Variable instance.
-The least_significant_digit
-attributes describes the power of ten of the smallest decimal place in
-the data the contains a reliable value.  assigned to the Variable
-instance. If None, the data is not truncated. The ndim attribute
-is the number of variable dimensions.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                renameVariable(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    renameVariable(self, oldname, newname)
    
-
-
    rename a Variable named oldname to newname
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                createGroup(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    createGroup(self, groupname)
    
-
-
    Creates a new Group with the given groupname.
    
-
-
    If groupname is specified as a path, using forward slashes as in unix to
-separate components, then intermediate groups will be created as necessary
-(analogous to mkdir -p in unix).  For example,
-createGroup('/GroupA/GroupB/GroupC') will create GroupA,
-GroupA/GroupB, and GroupA/GroupB/GroupC, if they don't already exist.
-If the specified path describes a group that already exists, no error is
-raised.
    
-
-
    The return value is a Group class instance.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                setncattr(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    setncattr(self,name,value)
    
-
-
    set a netCDF dataset or group attribute using name,value pair.
-Use if you need to set a netCDF attribute with the
-with the same name as one of the reserved python attributes.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                setncattr_string(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    setncattr_string(self,name,value)
    
-
-
    set a netCDF dataset or group string attribute using name,value pair.
-Use if you need to ensure that a netCDF attribute is created with type
-NC_STRING if the file format is NETCDF4.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                setncatts(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    setncatts(self,attdict)
    
-
-
    set a bunch of netCDF dataset or group attributes at once using a python dictionary.
-This may be faster when setting a lot of attributes for a NETCDF3
-formatted file, since nc_redef/nc_enddef is not called in between setting
-each attribute
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                getncattr(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    getncattr(self,name)
    
-
-
    retrieve a netCDF dataset or group attribute.
-Use if you need to get a netCDF attribute with the same
-name as one of the reserved python attributes.
    
-
-
    option kwarg encoding can be used to specify the
-character encoding of a string attribute (default is utf-8).
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                delncattr(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    delncattr(self,name,value)
    
-
-
    delete a netCDF dataset or group attribute.  Use if you need to delete a
-netCDF attribute with the same name as one of the reserved python
-attributes.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                renameAttribute(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    renameAttribute(self, oldname, newname)
    
-
-
    rename a Dataset or Group attribute named oldname to newname.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                renameGroup(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    renameGroup(self, oldname, newname)
    
-
-
    rename a Group named oldname to newname (requires netcdf >= 4.3.1).
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_auto_chartostring(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_auto_chartostring(self, True_or_False)
    
-
-
    Call Variable.set_auto_chartostring for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
    
-
-
    True_or_False: Boolean determining if automatic conversion of
-all character arrays <--> string arrays should be performed for
-character variables (variables of type NC_CHAR or S1) with the
-_Encoding attribute set.
    
-
-
    Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_auto_maskandscale(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_auto_maskandscale(self, True_or_False)
    
-
-
    Call Variable.set_auto_maskandscale for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
    
-
-
    True_or_False: Boolean determining if automatic conversion to masked arrays
-and variable scaling shall be applied for all variables.
    
-
-
    Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_auto_mask(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_auto_mask(self, True_or_False)
    
-
-
    Call Variable.set_auto_mask for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
    
+        
+            def
+            ncattrs(self):
+    
    
 
-
    True_or_False: Boolean determining if automatic conversion to masked arrays
-shall be applied for all variables.
    
+        
+            
    ncattrs(self)
    
 
-
    Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
    
+
    return the netcdf attribute names from the master file.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_auto_scale(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_auto_scale(self, True_or_False)
    
-
-
    Call Variable.set_auto_scale for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
    
 
-
    True_or_False: Boolean determining if automatic variable scaling
-shall be applied for all variables.
    
 
-
    Note: Calling this function only affects existing variables. Variables created
-after calling this function will follow the default behaviour.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_always_mask(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_always_mask(self, True_or_False)
    
-
-
    Call Variable.set_always_mask for all variables contained in
-this Dataset or Group, as well as for all
-variables in all its subgroups.
    
-
-
    True_or_False: Boolean determining if automatic conversion of
-masked arrays with no missing values to regular numpy arrays shall be
-applied for all variables. Default True. Set to False to restore the default behaviour
-in versions prior to 1.4.1 (numpy array returned unless missing values are present,
-otherwise masked array returned).
    
+                            
    
+                            
    
+                                        
    #  
 
-
    Note: Calling this function only affects existing
-variables. Variables created after calling this function will follow
-the default behaviour.
    
-
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                set_ncstring_attrs(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    set_ncstring_attrs(self, True_or_False)
    
-
-
    Call Variable.set_ncstring_attrs for all variables contained in
-this Dataset or Group, as well as for all its
-subgroups and their variables.
    
+        
+            def
+            close(self):
+    
    
 
-
    True_or_False: Boolean determining if all string attributes are
-created as variable-length NC_STRINGs, (if True), or if ascii text
-attributes are stored as NC_CHARs (if False; default)
    
+        
+            
    close(self)
    
 
-
    Note: Calling this function only affects newly created attributes
-of existing (sub-) groups and their variables.
    
+
    close all the open files.
    
 
    
-                                
    
-                            
-                                
    
-                                    
-                                        
    
-                def
-                get_variables_by_attributes(unknown):
-            
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    get_variables_by_attribute(self, **kwargs)
    
 
-
    Returns a list of variables that match specific conditions.
    
 
-
    Can pass in key=value parameters and variables are returned that
-contain all of the matches. For example,
    
-
-
    >>> # Get variables with x-axis attribute.
->>> vs = nc.get_variables_by_attributes(axis='X')
->>> # Get variables with matching "standard_name" attribute
->>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
-
    
+                            
    
+                            
    
+                                
    Inherited Members
    
+                                
    
+                                    
+                                
    
+                            
    
+                
    
+                
    
+                                
    
+        #  
 
-
    Can pass in key=callable parameter and variables are returned if the
-callable returns True.  The callable should accept a single parameter,
-the attribute value.  None is given as the attribute value when the
-attribute does not exist on the variable. For example,
    
+        
+        class
+        MFTime(_Variable):
+    
    
 
-
    >>> # Get Axis variables
->>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
->>> # Get variables that don't have an "axis" attribute
->>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
->>> # Get variables that have a "grid_mapping" attribute
->>> vs = nc.get_variables_by_attributes(grid_mapping=lambda v: v is not None)
-
    
-
    
-                                
    
-                            
-                            
-                                
-                                    
    
-                                        
    Inherited Members
    
-                                        
    
-                                            
-                                                
-                                            
-                                        
    
-                                    
    
-                                
-                            
-                        
-                    
-                
-                    
    
-                        
-                            
    class
-            MFTime(netCDF4._netCDF4._Variable):
-        
    
-                        
-                        
-                            
-                        
-                        
    Class providing an interface to a MFDataset time Variable by imposing a unique common
+        
+            
    Class providing an interface to a MFDataset time Variable by imposing a unique common
 time unit and/or calendar to all files.
    
 
-
    Example usage (See MFTime.__init__ for more details):
    
+
    Example usage (See MFTime.__init__">MFTime.__init__ for more details):
    
 
 
    >>> import numpy
 >>> f1 = Dataset("mftest_1.nc","w", format="NETCDF4_CLASSIC")
@@ -5715,18 +4295,16 @@ 
    Inherited Members
    
 32
 
    
 
    
-                        
-                            
-                                
    
-                                    
-                                        
    
-                MFTime(time, units=None, calendar=None)
-        
    
-                                    
-                                    
-                                        
-                                    
-                                    
    __init__(self, time, units=None, calendar=None)
    
+
+
+                            
    
+                                        
    #  
+
+        
+            MFTime(time, units=None, calendar=None)    
    
+
+        
+            
    __init__(self, time, units=None, calendar=None)
    
 
 
    Create a time Variable with units consistent across a multifile
 dataset.
    
@@ -5741,30 +4319,25 @@ 
    Inherited Members
    
 is present on each variable and values are unique across files raising a
 ValueError otherwise.
    
 
    
-                                
    
-                            
-                            
-                                
-                                    
    
-                                        
    Inherited Members
    
-                                        
    
-                                            
-                                                
-                                            
-                                        
    
-                                    
    
-                                
-                            
-                        
-                    
    
-                
-            
-        
-    
    
-    
 
+
+                            
    
+                            
    
+                                
    Inherited Members
    
+                                
    
+                                    
+                                
    
+                            
    
+                
+    
 
 

From 434875ec464374206a28f89d62f8afe37b6b8798 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 16:35:51 -0700
Subject: [PATCH 0590/1504] update docs

---
 docs/index.html          | 8 +++++---
 src/netCDF4/_netCDF4.pyx | 6 ++++--
 2 files changed, 9 insertions(+), 5 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 6324e0516..49b536fbd 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -1616,7 +1616,7 @@ 
    In-memory (diskless) Datasets
    
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
    
 
-
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
+
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
 
 
    copyright: 2008 by Jeffrey Whitaker.
    
 
@@ -2541,7 +2541,8 @@ 
    In-memory (diskless) Datasets
    
         
             
    fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')
    
 
-
    call ncgen via subprocess to create Dataset from CDL text representation.
    
+
    call ncgen via subprocess to create Dataset from CDL
+text representation.
    
 
 
    cdlfilename:  CDL file.
    
 
@@ -2570,7 +2571,8 @@ 
    In-memory (diskless) Datasets
    
         
             
    tocdl(self, coordvars=False, data=False, outfile=None)
    
 
-
    call ncdump via subprocess to create CDL text representation of Dataset
    
+
    call ncdump via subprocess to create CDL
+text representation of Dataset
    
 
 
    coordvars: include coordinate variable data (via ncdump -c). Default False
    
 
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 86dc2a73b..59cf5dd69 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3243,7 +3243,8 @@ attribute does not exist on the variable. For example,
         """
 **`fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')`**
 
-call ncgen via subprocess to create Dataset from CDL text representation.
+call ncgen via subprocess to create Dataset from [CDL](https://www.unidata.ucar.edu/software/netcdf/docs/netcdf_utilities_guide.html#cdl_guide)
+text representation.
 
 **`cdlfilename`**:  CDL file.
 
@@ -3277,7 +3278,8 @@ Dataset instance for `ncfilename` is returned.
         """
 **`tocdl(self, coordvars=False, data=False, outfile=None)`**
 
-call ncdump via subprocess to create CDL text representation of Dataset
+call ncdump via subprocess to create [CDL](https://www.unidata.ucar.edu/software/netcdf/docs/netcdf_utilities_guide.html#cdl_guide)
+text representation of Dataset
 
 **`coordvars`**: include coordinate variable data (via `ncdump -c`). Default False
 

From 0144876b05c704bc2a478d59625a515e87a65cc0 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 17:06:31 -0700
Subject: [PATCH 0591/1504] fix PATH

---
 .github/workflows/build.yml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index f3e4263b2..86255d8bf 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -64,6 +64,7 @@ jobs:
         python setup.py install
     - name: Test
       run: |
+        export PATH=${NETCDF_DIR}/bin:${PATH} 
         python checkversion.py
         # serial
         cd test

From a516989a3da6571c99d830c5c539cc6e1c1aa352 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 18:17:06 -0700
Subject: [PATCH 0592/1504] remove python 3 checks

---
 src/netCDF4/_netCDF4.pyx | 62 +++++++++-------------------------------
 1 file changed, 13 insertions(+), 49 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 59cf5dd69..564f86618 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1225,11 +1225,6 @@ import sys
 if sys.version_info[0:2] < (3, 7):
     # Python 3.7+ guarantees order; older versions need OrderedDict
     from collections import OrderedDict
-try:
-    from itertools import izip as zip
-except ImportError:
-    # python3: zip is already python2's itertools.izip
-    pass
 
 __version__ = "1.5.6"
 
@@ -1428,10 +1423,6 @@ else:  # prior to 4.6.2 this flag doesn't work, so make the same as NC_DISKLESS
 default_encoding = 'utf-8'
 unicode_error = 'replace'
 
-python3 = sys.version_info[0] > 2
-if python3:
-    buffer = memoryview
-
 _nctonptype = {}
 for _key,_value in _nptonctype.items():
     _nctonptype[_value] = _key
@@ -1482,7 +1473,7 @@ cdef _get_att(grp, int varid, name, encoding='utf-8'):
             ierr = nc_get_att_text(_grpid, varid, attname,
                     PyArray_BYTES(value_arr))
         _ensure_nc_success(ierr, err_cls=AttributeError)
-        if name == '_FillValue' and python3:
+        if name == '_FillValue':
             # make sure _FillValue for character arrays is a byte on python 3
             # (issue 271).
             pstring = value_arr.tobytes()
@@ -2431,25 +2422,16 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
             raise ValueError(msg)
 
     def __repr__(self):
-        if python3:
-            return self.__unicode__()
-        else:
-            return unicode(self).encode('utf-8')
+        return self.__unicode__()
 
     def __unicode__(self):
         ncdump = [repr(type(self))]
         dimnames = tuple(_tostr(dimname)+'(%s)'%len(self.dimensions[dimname])\
         for dimname in self.dimensions.keys())
-        if python3:
-            varnames = tuple(\
-            [_tostr(self.variables[varname].dtype)+' '+_tostr(varname)+
-             ((_tostr(self.variables[varname].dimensions)).replace(",)",")")).replace("'","")
-             for varname in self.variables.keys()])
-        else: # don't try to remove quotes in python2
-            varnames = tuple(\
-            [_tostr(self.variables[varname].dtype)+' '+_tostr(varname)+
-             (_tostr(self.variables[varname].dimensions)).replace(",)",")")
-             for varname in self.variables.keys()])
+        varnames = tuple(\
+        [_tostr(self.variables[varname].dtype)+' '+_tostr(varname)+
+         ((_tostr(self.variables[varname].dimensions)).replace(",)",")")).replace("'","")
+         for varname in self.variables.keys()])
         grpnames = tuple(_tostr(grpname) for grpname in self.groups.keys())
         if self.path == '/':
             ncdump.append('root group (%s data model, file format %s):' %
@@ -3473,10 +3455,7 @@ Read-only class variables:
             raise AttributeError("size cannot be altered")
 
     def __repr__(self):
-        if python3:
-            return self.__unicode__()
-        else:
-            return unicode(self).encode('utf-8')
+        return self.__unicode__()
 
     def __unicode__(self):
         if not dir(self._grp):
@@ -3981,10 +3960,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         return self[...]
 
     def __repr__(self):
-        if python3:
-            return self.__unicode__()
-        else:
-            return unicode(self).encode('utf-8')
+        return self.__unicode__()
 
     def __unicode__(self):
         cdef int ierr, no_fill
@@ -4915,7 +4891,7 @@ cannot be safely cast to variable data type""" % attname
 
         # A numpy or masked array (or an object supporting the buffer interface) is needed.
         # Convert if necessary.
-        if not ma.isMA(data) and not (hasattr(data,'data') and isinstance(data.data,buffer)):
+        if not ma.isMA(data) and not (hasattr(data,'data') and isinstance(data.data,memoryview)):
             # if auto scaling is to be done, don't cast to an integer yet.
             if self.scale and self.dtype.kind in 'iu' and \
                hasattr(self, 'scale_factor') or hasattr(self, 'add_offset'):
@@ -5578,10 +5554,7 @@ the user.
         self.name = dtype_name
 
     def __repr__(self):
-        if python3:
-            return self.__unicode__()
-        else:
-            return unicode(self).encode('utf-8')
+        return self.__unicode__()
 
     def __unicode__(self):
         return "%r: name = '%s', numpy dtype = %s" %\
@@ -5863,10 +5836,7 @@ the user.
             self.name = dtype_name
 
     def __repr__(self):
-        if python3:
-            return self.__unicode__()
-        else:
-            return unicode(self).encode('utf-8')
+        return self.__unicode__()
 
     def __unicode__(self):
         if self.dtype == str:
@@ -5976,10 +5946,7 @@ the user.
         self.enum_dict = enum_dict
 
     def __repr__(self):
-        if python3:
-            return self.__unicode__()
-        else:
-            return unicode(self).encode('utf-8')
+        return self.__unicode__()
 
     def __unicode__(self):
         return "%r: name = '%s', numpy dtype = %s, fields/values =%s" %\
@@ -6064,10 +6031,7 @@ cdef _strencode(pystr,encoding=None):
 
 def _to_ascii(bytestr):
     # encode a byte string to an ascii encoded string.
-    if python3:
-        return str(bytestr,encoding='ascii')
-    else:
-        return bytestr.encode('ascii')
+    return str(bytestr,encoding='ascii')
 
 def stringtoarr(string,NUMCHARS,dtype='S'):
     """

From dad4d6df41e938719208134c51881e8d2761711f Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Feb 2021 20:40:57 -0700
Subject: [PATCH 0593/1504] update docs

---
 docs/index.html | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 49b536fbd..5f8d5e6f0 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -10,7 +10,7 @@
 
 
 
-
+
 
         
    

From c8d94c1b51a4733d01de34fcc92a2c7aa4cf432c Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 9 Feb 2021 06:58:51 -0700
Subject: [PATCH 0594/1504] update docs

---
 Changelog                | 1 +
 src/netCDF4/_netCDF4.pyx | 3 ++-
 2 files changed, 3 insertions(+), 1 deletion(-)

diff --git a/Changelog b/Changelog
index 190468034..0ca8fada6 100644
--- a/Changelog
+++ b/Changelog
@@ -8,6 +8,7 @@
  * update cython numpy API to remove deprecation warnings.
  * Add "fromcdl" and "tocdl" Dataset methods for import/export of CDL
    via ncdump/ncgen called externally via the subprocess module (issue #1078).
+ * remove python 2.7 support.
 
  version 1.5.5.1 (tag v1.5.5.1rel)
 ==================================
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 564f86618..d9120ccfa 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -32,11 +32,12 @@ types) are not supported.
 
 ## Requires
 
+ - Python 3.6 or later.
  - [numpy array module](http://numpy.scipy.org), version 1.10.0 or later.
  - [Cython](http://cython.org), version 0.21 or later.
  - [setuptools](https://pypi.python.org/pypi/setuptools), version 18.0 or
    later.
- - The HDF5 C library version 1.8.4-patch1 or higher (1.8.x recommended)
+ - The HDF5 C library version 1.8.4-patch1 or higher
  from [](ftp://ftp.hdfgroup.org/HDF5/current/src).
  ***netCDF version 4.4.1 or higher is recommended if using HDF5 1.10.x -
  otherwise resulting files may be unreadable by clients using earlier

From b3c3ab4742b7861da9450cc000cae1f9b598da96 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 9 Feb 2021 07:23:32 -0700
Subject: [PATCH 0595/1504] don't need tempfile

---
 src/netCDF4/_netCDF4.pyx | 1 -
 1 file changed, 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index d9120ccfa..c293519a7 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1236,7 +1236,6 @@ import numpy
 import weakref
 import warnings
 import subprocess
-import tempfile
 import pathlib
 from glob import glob
 from numpy import ma

From 25ba5a98cfe264c79d883c107d2f4d01a476c523 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 11 Feb 2021 13:11:26 -0700
Subject: [PATCH 0596/1504] fix for issue #1083

---
 Changelog                | 2 ++
 src/netCDF4/_netCDF4.pyx | 5 +++++
 2 files changed, 7 insertions(+)

diff --git a/Changelog b/Changelog
index 0ca8fada6..22ae46b17 100644
--- a/Changelog
+++ b/Changelog
@@ -9,6 +9,8 @@
  * Add "fromcdl" and "tocdl" Dataset methods for import/export of CDL
    via ncdump/ncgen called externally via the subprocess module (issue #1078).
  * remove python 2.7 support.
+ * broadcast data with singleton rightmost dimension to conform to variable
+   size when writing (issue #1083).
 
  version 1.5.5.1 (tag v1.5.5.1rel)
 ==================================
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index c293519a7..a1964a9fd 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4930,6 +4930,11 @@ cannot be safely cast to variable data type""" % attname
                 data.shape = tuple(datashape)
             except ValueError: # otherwise broadcast
                 data = numpy.broadcast_to(data, datashape)
+        else:
+            # if data has singleton last dimension, broadcast it slice shape
+            # (issue #1083)
+            if data.shape != datashape and data.shape[-1] == 1:
+                data = numpy.broadcast_to(data, datashape)
 
         # Reshape these arrays so we can iterate over them.
         start = start.reshape((-1, self.ndim or 1))

From 7fbd0f873b937db333e3e6c0c87fcce1e107019b Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 11 Feb 2021 13:54:27 -0700
Subject: [PATCH 0597/1504] more general solution, add test

---
 src/netCDF4/_netCDF4.pyx |  6 +++---
 test/tst_slicing.py      | 13 +++++++++++++
 2 files changed, 16 insertions(+), 3 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index a1964a9fd..0ab5a53b9 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4923,7 +4923,7 @@ cannot be safely cast to variable data type""" % attname
             data = numpy.tile(data,datashape)
         # reshape data array by adding extra dimensions
         # if needed to conform with start,count,stride.
-        if len(data.shape) != len(datashape):
+        if data.ndim != len(datashape):
             # create a view so shape in caller is not modified (issue 90)
             try: # if extra singleton dims, just reshape
                 data = data.view()
@@ -4931,9 +4931,9 @@ cannot be safely cast to variable data type""" % attname
             except ValueError: # otherwise broadcast
                 data = numpy.broadcast_to(data, datashape)
         else:
-            # if data has singleton last dimension, broadcast it slice shape
+            # broadcast data to slice shape if data.ndim > 1
             # (issue #1083)
-            if data.shape != datashape and data.shape[-1] == 1:
+            if data.shape != datashape and data.ndim > 1:
                 data = numpy.broadcast_to(data, datashape)
 
         # Reshape these arrays so we can iterate over them.
diff --git a/test/tst_slicing.py b/test/tst_slicing.py
index fee41dc82..cbb39209b 100644
--- a/test/tst_slicing.py
+++ b/test/tst_slicing.py
@@ -249,5 +249,18 @@ def test_issue922(self):
             assert_array_equal(f['v2'][:,1:3],np.arange(6,dtype=np.int).reshape(3,2))
             assert_array_equal(f['v2'][:,0],np.arange(3,dtype=np.int))
 
+    def test_issue1083(self):
+        with Dataset(self.file, "w") as nc:
+            nc.createDimension("test", 5)
+            v = nc.createVariable("var", "f8", ("test", "test", "test"))
+            v[:] = 1 # works
+            v[:] = np.ones(()) # works
+            v[:] = np.ones((1,)) # works
+            v[:] = np.ones((5,)) # works
+            v[:] = np.ones((5,5,5)) # works
+            v[:] = np.ones((5,1,1)) # fails (before PR #1084)
+            v[:] = np.ones((5,1,5)) # fails (before PR #1084)
+            v[:] = np.ones((5,5,1)) # fails (before PR #1084)
+
 if __name__ == '__main__':
     unittest.main()

From 3db48c2e90cb1b5836435b3281dda2df16ece447 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 11 Feb 2021 13:56:04 -0700
Subject: [PATCH 0598/1504] update

---
 Changelog | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/Changelog b/Changelog
index 22ae46b17..75d03e2a6 100644
--- a/Changelog
+++ b/Changelog
@@ -9,8 +9,8 @@
  * Add "fromcdl" and "tocdl" Dataset methods for import/export of CDL
    via ncdump/ncgen called externally via the subprocess module (issue #1078).
  * remove python 2.7 support.
- * broadcast data with singleton rightmost dimension to conform to variable
-   size when writing (issue #1083).
+ * broadcast data (if possible)to conform to variable shape when writing to a slice
+   (issue #1083).
 
  version 1.5.5.1 (tag v1.5.5.1rel)
 ==================================

From 84669463d4dbe67de832f3ee7bb6ee61a0780b80 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 11 Feb 2021 14:02:56 -0700
Subject: [PATCH 0599/1504] simpler solution

---
 src/netCDF4/_netCDF4.pyx | 11 +++--------
 1 file changed, 3 insertions(+), 8 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 0ab5a53b9..67c1145e7 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4921,20 +4921,15 @@ cannot be safely cast to variable data type""" % attname
         # and fill with scalar values.
         if data.shape == ():
             data = numpy.tile(data,datashape)
-        # reshape data array by adding extra dimensions
-        # if needed to conform with start,count,stride.
-        if data.ndim != len(datashape):
+        # reshape data array if needed to conform with start,count,stride.
+        if data.ndim != len(datashape) or\
+           (data.shape != datashape and data.ndim > 1): # issue #1083
             # create a view so shape in caller is not modified (issue 90)
             try: # if extra singleton dims, just reshape
                 data = data.view()
                 data.shape = tuple(datashape)
             except ValueError: # otherwise broadcast
                 data = numpy.broadcast_to(data, datashape)
-        else:
-            # broadcast data to slice shape if data.ndim > 1
-            # (issue #1083)
-            if data.shape != datashape and data.ndim > 1:
-                data = numpy.broadcast_to(data, datashape)
 
         # Reshape these arrays so we can iterate over them.
         start = start.reshape((-1, self.ndim or 1))

From 0695ca2b73e4d4446ecab06f574affa41e31c197 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 12 Feb 2021 15:23:27 -0700
Subject: [PATCH 0600/1504] prepare for v1.5.6 release

---
 Changelog | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/Changelog b/Changelog
index 75d03e2a6..14ba39dc4 100644
--- a/Changelog
+++ b/Changelog
@@ -1,5 +1,5 @@
- version 1.5.6 (not yet released)
-==================================
+ version 1.5.6 (tag v1.5.6rel)
+==============================
  * move CI/CD tests from travis/appveyor to Github Actions (PR #1061).
  * move netCDF4 dir under src so module can be imported in source directory (PR #1062).
  * change numpy.bool to numpy.bool_ and numpy.float to numpy.float_ (float and

From c8327909eb7880446a1b14bbe07e9e1af4ac544f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 12 Feb 2021 20:20:26 -0700
Subject: [PATCH 0601/1504] capture_output requires python 3.7

---
 src/netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 67c1145e7..44a78085e 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3276,7 +3276,7 @@ text representation of Dataset
             ncdumpargs = "-s"
         if not data: ncdumpargs += "h"
         result=subprocess.run(["ncdump", ncdumpargs, self.filepath()],
-                check=True, capture_output=True, text=True)
+               check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
         if outfile is None:
             return result.stdout
         else:

From 828c217ba913339263455551351c1bddfbc4335e Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 12 Feb 2021 20:49:31 -0700
Subject: [PATCH 0602/1504] test on python 3.6

---
 .github/workflows/miniconda.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index f9bf46277..e763d49bc 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -10,7 +10,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        python-version: [ "3.7", "3.8", "3.9"]
+        python-version: ["3.6", "3.7", "3.8", "3.9"]
         os: [windows-latest, ubuntu-latest, macos-latest]
         platform: [x64, x32]
         exclude:

From 6ec9c32852e8b15511dc16a4f6b98d18ae8339c8 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 13 Feb 2021 07:17:25 -0700
Subject: [PATCH 0603/1504] don't run tst_cdl.py if NO_CDL set

---
 test/run_all.py | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/test/run_all.py b/test/run_all.py
index db69e9da9..dc1aa5fc6 100755
--- a/test/run_all.py
+++ b/test/run_all.py
@@ -38,6 +38,11 @@
     test_files.remove('tst_dap.py')
     test_files.insert(0,'tst_dap.py')
 
+# Don't run CDL test (that requires ncdump/ncgen)
+if os.getenv('NO_CDL'):
+    test_files.remove('tst_cdl.py');
+    sys.stdout.write('not running tst_cdl.py ...\n')
+
 # Build the test suite from the tests found in the test files.
 testsuite = unittest.TestSuite()
 for f in test_files:

From 09b4d47f04856fa2eadc22a94abfb78e7e87e6de Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 13 Feb 2021 09:28:37 -0700
Subject: [PATCH 0604/1504] update

---
 README.md | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/README.md b/README.md
index dcb9c40b7..d866b591a 100644
--- a/README.md
+++ b/README.md
@@ -9,6 +9,8 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
+2/15/2020:  Version [1.5.6](https://pypi.python.org/pypi/netCDF4/1.5.6) released. Added `Dataset.fromcdl` and `Dataset.tocdl`, which require `ncdump` and `ncgen` utilitie. Removed python 2.7 support.
+
 12/20/2020: Version [1.5.5.1](https://pypi.python.org/pypi/netCDF4/1.5.5.1) released.
 Updated binary wheels for OSX and linux that link latest netcdf-c and hdf5 libs.
 

From 7ad547c5df209cf8b8376d3e66bba8d55ca76c13 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 13 Feb 2021 09:30:34 -0700
Subject: [PATCH 0605/1504] update

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index d866b591a..6f33fa7ce 100644
--- a/README.md
+++ b/README.md
@@ -9,7 +9,7 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
-2/15/2020:  Version [1.5.6](https://pypi.python.org/pypi/netCDF4/1.5.6) released. Added `Dataset.fromcdl` and `Dataset.tocdl`, which require `ncdump` and `ncgen` utilitie. Removed python 2.7 support.
+2/15/2020:  Version [1.5.6](https://pypi.python.org/pypi/netCDF4/1.5.6) released. Added `Dataset.fromcdl` and `Dataset.tocdl`, which require `ncdump` and `ncgen` utilities to be in `$PATH`. Removed python 2.7 support.
 
 12/20/2020: Version [1.5.5.1](https://pypi.python.org/pypi/netCDF4/1.5.5.1) released.
 Updated binary wheels for OSX and linux that link latest netcdf-c and hdf5 libs.

From 417896b938d3aba4670e93e7b71f5b971da53736 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 13 Feb 2021 10:30:55 -0700
Subject: [PATCH 0606/1504] update docstrings

---
 src/netCDF4/_netCDF4.pyx | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 44a78085e..c0a72e67e 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3225,8 +3225,8 @@ attribute does not exist on the variable. For example,
         """
 **`fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')`**
 
-call ncgen via subprocess to create Dataset from [CDL](https://www.unidata.ucar.edu/software/netcdf/docs/netcdf_utilities_guide.html#cdl_guide)
-text representation.
+call `ncgen` via subprocess to create Dataset from [CDL](https://www.unidata.ucar.edu/software/netcdf/docs/netcdf_utilities_guide.html#cdl_guide)
+text representation. Requires `ncgen` to be installed and in `$PATH`.
 
 **`cdlfilename`**:  CDL file.
 
@@ -3260,8 +3260,8 @@ Dataset instance for `ncfilename` is returned.
         """
 **`tocdl(self, coordvars=False, data=False, outfile=None)`**
 
-call ncdump via subprocess to create [CDL](https://www.unidata.ucar.edu/software/netcdf/docs/netcdf_utilities_guide.html#cdl_guide)
-text representation of Dataset
+call `ncdump` via subprocess to create [CDL](https://www.unidata.ucar.edu/software/netcdf/docs/netcdf_utilities_guide.html#cdl_guide)
+text representation of Dataset. Requires `ncdump` to be installed and in `$PATH`.
 
 **`coordvars`**: include coordinate variable data (via `ncdump -c`). Default False
 

From 5d071b8bb51a841e0f8e5fd9efbbf4f59b74dfdb Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 13 Feb 2021 10:48:40 -0700
Subject: [PATCH 0607/1504] use encoding kwarg in subprocess.run (instead of
 text, not available in 3.6)

---
 src/netCDF4/_netCDF4.pyx | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index c0a72e67e..577371326 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3276,7 +3276,8 @@ text representation of Dataset. Requires `ncdump` to be installed and in `$PATH`
             ncdumpargs = "-s"
         if not data: ncdumpargs += "h"
         result=subprocess.run(["ncdump", ncdumpargs, self.filepath()],
-               check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
+               check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE,
+               encoding='utf-8')
         if outfile is None:
             return result.stdout
         else:

From a901113a1929bc955fb1a1b844691ba8f4d28c34 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Sat, 13 Feb 2021 12:44:36 -0700
Subject: [PATCH 0608/1504] update docs

---
 docs/index.html | 17 +++++++++--------
 1 file changed, 9 insertions(+), 8 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 5f8d5e6f0..23169e08e 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -487,11 +487,12 @@ 
    Download
    
 
    Requires
    
 
 
      
+
    • Python 3.6 or later.
      • 
 
    • numpy array module, version 1.10.0 or later.
      • 
 
    • Cython, version 0.21 or later.
      • 
 
    • setuptools, version 18.0 or
 later.
      • 
-
    • The HDF5 C library version 1.8.4-patch1 or higher (1.8.x recommended)
+
    • The HDF5 C library version 1.8.4-patch1 or higher
 from .
 netCDF version 4.4.1 or higher is recommended if using HDF5 1.10.x -
 otherwise resulting files may be unreadable by clients using earlier
@@ -1616,7 +1617,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -2541,8 +2542,8 @@ 
      In-memory (diskless) Datasets
      
         
             
      fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')
      
 
-
      call ncgen via subprocess to create Dataset from CDL
-text representation.
      
+
      call ncgen via subprocess to create Dataset from CDL
+text representation. Requires ncgen to be installed and in $PATH.
      
 
 
      cdlfilename:  CDL file.
      
 
@@ -2571,12 +2572,12 @@ 
      In-memory (diskless) Datasets
      
         
             
      tocdl(self, coordvars=False, data=False, outfile=None)
      
 
-
      call ncdump via subprocess to create CDL
-text representation of Dataset
      
+
      call ncdump via subprocess to create CDL
+text representation of Dataset. Requires ncdump to be installed and in $PATH.
      
 
-
      coordvars: if True, write out coordinate variable data (Default False).
      
+
      coordvars: include coordinate variable data (via ncdump -c). Default False
      
 
-
      data: if True, write out all variable data (Default False).
      
+
      data: if True, write out variable data (Default False).
      
 
 
      outfile: If not None, file to output ncdump to. Default is to return a string.
      
 
      

From 9fbe1b227677c1729b96c64dc671b34b75ed8e60 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 14 Feb 2021 06:57:09 -0700
Subject: [PATCH 0609/1504] fix year

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 6f33fa7ce..95a140a91 100644
--- a/README.md
+++ b/README.md
@@ -9,7 +9,7 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
-2/15/2020:  Version [1.5.6](https://pypi.python.org/pypi/netCDF4/1.5.6) released. Added `Dataset.fromcdl` and `Dataset.tocdl`, which require `ncdump` and `ncgen` utilities to be in `$PATH`. Removed python 2.7 support.
+2/15/2021:  Version [1.5.6](https://pypi.python.org/pypi/netCDF4/1.5.6) released. Added `Dataset.fromcdl` and `Dataset.tocdl`, which require `ncdump` and `ncgen` utilities to be in `$PATH`. Removed python 2.7 support.
 
 12/20/2020: Version [1.5.5.1](https://pypi.python.org/pypi/netCDF4/1.5.5.1) released.
 Updated binary wheels for OSX and linux that link latest netcdf-c and hdf5 libs.

From fad5e4cd8dec56bb37d01a951db7a8edb2f7f1ea Mon Sep 17 00:00:00 2001
From: Mike Taves 
Date: Mon, 15 Feb 2021 10:52:58 +1300
Subject: [PATCH 0610/1504] Further improve NumPy type deprecation

---
 docs/index.html          |  2 +-
 src/netCDF4/_netCDF4.pyx |  6 +++---
 test/tst_masked.py       |  6 +++---
 test/tst_masked2.py      |  6 +++---
 test/tst_shape.py        |  4 ++--
 test/tst_slicing.py      | 26 +++++++++++++-------------
 test/tst_unicode.py      |  2 +-
 test/tst_unicode3.py     |  2 +-
 8 files changed, 27 insertions(+), 27 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 23169e08e..04c888dd2 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -1173,7 +1173,7 @@ 
      Beyond ho
 >>> # create sample complex data.
 >>> datac = numpy.exp(1j*(1.+numpy.linspace(0, numpy.pi, size)))
 >>> # create complex128 compound data type.
->>> complex128 = numpy.dtype([("real",numpy.float_64),("imag",numpy.float_64)])
+>>> complex128 = numpy.dtype([("real",numpy.float64),("imag",numpy.float64)])
 >>> complex128_t = f.createCompoundType(complex128,"complex128")
 >>> # create a variable with this data type, write some data to it.
 >>> x_dim = f.createDimension("x_dim",None)
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 577371326..1fa9b53e1 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -746,7 +746,7 @@ for storing numpy complex arrays.  Here's an example:
 >>> # create sample complex data.
 >>> datac = numpy.exp(1j*(1.+numpy.linspace(0, numpy.pi, size)))
 >>> # create complex128 compound data type.
->>> complex128 = numpy.dtype([("real",numpy.float_64),("imag",numpy.float_64)])
+>>> complex128 = numpy.dtype([("real",numpy.float64),("imag",numpy.float64)])
 >>> complex128_t = f.createCompoundType(complex128,"complex128")
 >>> # create a variable with this data type, write some data to it.
 >>> x_dim = f.createDimension("x_dim",None)
@@ -999,7 +999,7 @@ written to a different variable index on each task
 
 ```python
 >>> d = nc.createDimension('dim',4)
->>> v = nc.createVariable('var', np.int, 'dim')
+>>> v = nc.createVariable('var', np.int64, 'dim')
 >>> v[rank] = rank
 >>> nc.close()
 
@@ -4896,7 +4896,7 @@ cannot be safely cast to variable data type""" % attname
             # if auto scaling is to be done, don't cast to an integer yet.
             if self.scale and self.dtype.kind in 'iu' and \
                hasattr(self, 'scale_factor') or hasattr(self, 'add_offset'):
-                data = numpy.array(data,numpy.float_)
+                data = numpy.array(data,numpy.float64)
             else:
                 data = numpy.array(data,self.dtype)
 
diff --git a/test/tst_masked.py b/test/tst_masked.py
index 54c04101d..2e86e6a09 100644
--- a/test/tst_masked.py
+++ b/test/tst_masked.py
@@ -20,7 +20,7 @@
 ranarr2 = 100.*uniform(size=(ndim))
 # used for checking vector missing_values
 arr3 = NP.linspace(0,9,ndim)
-mask = NP.zeros(ndim,NP.bool); mask[-1]=True; mask[-2]=True
+mask = NP.zeros(ndim,NP.bool_); mask[-1]=True; mask[-2]=True
 marr3 = NP.ma.array(arr3, mask=mask, dtype=NP.int32)
 packeddata = 10.*uniform(size=(ndim))
 missing_value = -9999.
@@ -71,7 +71,7 @@ def setUp(self):
         doh2[0] = 1.
         # added test for issue 515
         file.createDimension('x',1)
-        v = file.createVariable('v',NP.float,'x',fill_value=-9999)
+        v = file.createVariable('v',NP.float64,'x',fill_value=-9999)
         file.close()
 
         # issue #972: when auto_fill off byte arrays (u1,i1) should
@@ -119,7 +119,7 @@ def runTest(self):
         assert_array_almost_equal(datamasked[:].filled(),ranarr)
         assert_array_almost_equal(datamasked2[:].filled(),ranarr2)
         assert_array_almost_equal(datapacked[:],packeddata,decimal=4)
-        assert(datapacked3[:].dtype == NP.float)
+        assert(datapacked3[:].dtype == NP.float64)
         # added to test fix to issue 46 (result before r865 was 10)
         assert_array_equal(datapacked2[0],11)
         # added test for issue 515
diff --git a/test/tst_masked2.py b/test/tst_masked2.py
index 141559f3f..249f2e9ac 100755
--- a/test/tst_masked2.py
+++ b/test/tst_masked2.py
@@ -16,11 +16,11 @@
 FILE_NAME2 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
 FILE_NAME3 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
 datacheck1 =\
-ma.array([0,5000.0,4000.0,0],dtype=np.float,mask=[True,False,False,True])
+ma.array([0,5000.0,4000.0,0],dtype=np.float64,mask=[True,False,False,True])
 datacheck2 =\
-ma.array([3000.0,5000.0,4000.0,0],dtype=np.float,mask=[False,False,False,True])
+ma.array([3000.0,5000.0,4000.0,0],dtype=np.float64,mask=[False,False,False,True])
 datacheck3 =\
-ma.array([3000.0,5000.0,0,2000.0],dtype=np.float,mask=[False,False,True,False])
+ma.array([3000.0,5000.0,0,2000.0],dtype=np.float64,mask=[False,False,True,False])
 mask = [False,True,False,False]
 datacheck4 = ma.array([1.5625,0,3.75,4.125],mask=mask,dtype=np.float32)
 fillval = default_fillvals[datacheck4.dtype.str[1:]]
diff --git a/test/tst_shape.py b/test/tst_shape.py
index 66083a80f..d7d1839ad 100644
--- a/test/tst_shape.py
+++ b/test/tst_shape.py
@@ -5,7 +5,7 @@
 file_name = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
 xdim=None; ydim=121; zdim=169
 datashape = (ydim,zdim)
-data = np.ones(datashape,dtype=np.float_)
+data = np.ones(datashape,dtype=np.float64)
 
 class ShapeTestCase(unittest.TestCase):
 
@@ -15,7 +15,7 @@ def setUp(self):
         f.createDimension('x',xdim)
         f.createDimension('y',ydim)
         f.createDimension('z',zdim)
-        v = f.createVariable('data',np.float_,('x','y','z'))
+        v = f.createVariable('data',np.float64,('x','y','z'))
         f.close()
 
     def tearDown(self):
diff --git a/test/tst_slicing.py b/test/tst_slicing.py
index cbb39209b..ec37d0edf 100644
--- a/test/tst_slicing.py
+++ b/test/tst_slicing.py
@@ -129,7 +129,7 @@ def test_issue306(self):
         nlons = 12; lon = f.createDimension('lon',nlons)
         nlevs = 1; lev = f.createDimension('lev',nlevs)
         time = f.createDimension('time',None)
-        var = f.createVariable('var',np.float_,('time','lev','lat','lon'))
+        var = f.createVariable('var',np.float64,('time','lev','lat','lon'))
         a = np.random.uniform(size=(10,nlevs,nlats,nlons))
         var[0:10] = a
         f.close()
@@ -168,7 +168,7 @@ def test_issue300(self):
         nlats = 11; lat = f.createDimension('lat',nlats)
         nlons = 20; lon = f.createDimension('lon',nlons)
         time = f.createDimension('time',None)
-        var = f.createVariable('var',np.float_,('time','lat','lon'))
+        var = f.createVariable('var',np.float64,('time','lat','lon'))
         a = np.random.uniform(size=(3,nlats,nlons))
         var[[True,True,False,False,False,True]] = a
         var[0,2.0,"-1"] = 0 # issue 312
@@ -203,7 +203,7 @@ def test_issue743(self):
         td = nc.createDimension('t',None)
         xd = nc.createDimension('x',33)
         yd = nc.createDimension('y',4)
-        v = nc.createVariable('v',np.float_,('t','x','y'))
+        v = nc.createVariable('v',np.float64,('t','x','y'))
         nc.close()
         nc = Dataset(self.file)
         data = np.empty(nc['v'].shape, nc['v'].dtype)
@@ -216,7 +216,7 @@ def test_issue906(self):
         f.createDimension('d1',3)
         f.createDimension('d2',None)
         f.createDimension('d3',5)
-        f.createVariable('v2',np.float_,('d1','d2','d3'))
+        f.createVariable('v2',np.float64,('d1','d2','d3'))
         f['v2'][:] = np.zeros((3,4,5))
         f['v2'][0,:,0] = np.arange(4)
         f['v2'][0,:,:] = np.ones((4,5))
@@ -227,7 +227,7 @@ def test_issue919(self):
             f.createDimension('time',2)
             f.createDimension('lat',10)
             f.createDimension('lon',9)
-            f.createVariable('v1',np.int,('time', 'lon','lat',))
+            f.createVariable('v1',np.int64,('time', 'lon','lat',))
             arr = np.arange(9*10).reshape((9, 10))
             f['v1'][:] = arr
             assert_array_equal(f['v1'][:],np.broadcast_to(arr,f['v1'].shape))
@@ -239,15 +239,15 @@ def test_issue922(self):
         with Dataset(self.file,'w') as f:
             f.createDimension('d1',3)
             f.createDimension('d2',None)
-            f.createVariable('v1',np.int,('d2','d1',))
-            f['v1'][0] = np.arange(3,dtype=np.int)
-            f['v1'][1:3] = np.arange(3,dtype=np.int)
+            f.createVariable('v1',np.int64,('d2','d1',))
+            f['v1'][0] = np.arange(3,dtype=np.int64)
+            f['v1'][1:3] = np.arange(3,dtype=np.int64)
             assert_array_equal(f['v1'][:], np.broadcast_to(np.arange(3),(3,3)))
-            f.createVariable('v2',np.int,('d1','d2',))
-            f['v2'][:,0] = np.arange(3,dtype=np.int)
-            f['v2'][:,1:3] = np.arange(6,dtype=np.int).reshape(3,2)
-            assert_array_equal(f['v2'][:,1:3],np.arange(6,dtype=np.int).reshape(3,2))
-            assert_array_equal(f['v2'][:,0],np.arange(3,dtype=np.int))
+            f.createVariable('v2',np.int64,('d1','d2',))
+            f['v2'][:,0] = np.arange(3,dtype=np.int64)
+            f['v2'][:,1:3] = np.arange(6,dtype=np.int64).reshape(3,2)
+            assert_array_equal(f['v2'][:,1:3],np.arange(6,dtype=np.int64).reshape(3,2))
+            assert_array_equal(f['v2'][:,0],np.arange(3,dtype=np.int64))
 
     def test_issue1083(self):
         with Dataset(self.file, "w") as nc:
diff --git a/test/tst_unicode.py b/test/tst_unicode.py
index 4faec5b71..48e5c9ccd 100644
--- a/test/tst_unicode.py
+++ b/test/tst_unicode.py
@@ -18,7 +18,7 @@ def setUp(self):
         f.attribute2 = ATT2
         f.attribute3 = ATT3
         d = f.createDimension(DIM_NAME, None)
-        v = f.createVariable(VAR_NAME, np.float, (DIM_NAME,))
+        v = f.createVariable(VAR_NAME, np.float64, (DIM_NAME,))
         f.close()
 
     def tearDown(self):
diff --git a/test/tst_unicode3.py b/test/tst_unicode3.py
index 57674ce73..1dab5646d 100644
--- a/test/tst_unicode3.py
+++ b/test/tst_unicode3.py
@@ -18,7 +18,7 @@ def setUp(self):
         f.attribute2 = ATT2
         f.attribute3 = ATT3
         d = f.createDimension(DIM_NAME, None)
-        v = f.createVariable(VAR_NAME, np.float_, (DIM_NAME,))
+        v = f.createVariable(VAR_NAME, np.float64, (DIM_NAME,))
         f.close()
 
     def tearDown(self):

From 29a08c7680da0bfd09c21fc1a6cf816aabf39149 Mon Sep 17 00:00:00 2001
From: Mike Taves 
Date: Tue, 16 Feb 2021 11:52:06 +1300
Subject: [PATCH 0611/1504] Use numpy alias 'np' more consistently

---
 examples/tutorial.py     | 74 ++++++++++++++++++++--------------------
 src/netCDF4/_netCDF4.pyx | 48 +++++++++++++-------------
 test/tst_atts.py         | 16 ++++-----
 test/tst_dims.py         |  1 -
 test/tst_grps.py         |  1 -
 test/tst_grps2.py        |  1 -
 test/tst_masked.py       | 26 +++++++-------
 test/tst_rename.py       |  1 -
 test/tst_scalarvar.py    |  1 -
 test/tst_unlimdim.py     |  4 +--
 test/tst_vars.py         |  6 ++--
 11 files changed, 87 insertions(+), 92 deletions(-)

diff --git a/examples/tutorial.py b/examples/tutorial.py
index 13e339912..1f68a1c6d 100644
--- a/examples/tutorial.py
+++ b/examples/tutorial.py
@@ -80,10 +80,10 @@ def walktree(top):
 
 print(rootgrp.variables)
 
-import numpy
+import numpy as np
 # no unlimited dimension, just assign to slice.
-lats =  numpy.arange(-90,91,2.5)
-lons =  numpy.arange(-180,180,2.5)
+lats =  np.arange(-90,91,2.5)
+lons =  np.arange(-180,180,2.5)
 latitudes[:] = lats
 longitudes[:] = lons
 print('latitudes =\n',latitudes[:])
@@ -123,7 +123,7 @@ def walktree(top):
     f = Dataset('mftest'+repr(nfile)+'.nc','w',format='NETCDF4_CLASSIC')
     f.createDimension('x',None)
     x = f.createVariable('x','i',('x',))
-    x[0:10] = numpy.arange(nfile*10,10*(nfile+1))
+    x[0:10] = np.arange(nfile*10,10*(nfile+1))
     f.close()
 # now read all those files in at once, in one Dataset.
 from netCDF4 import MFDataset
@@ -134,15 +134,15 @@ def walktree(top):
 f = Dataset('complex.nc','w')
 size = 3 # length of 1-d complex array
 # create sample complex data.
-datac = numpy.exp(1j*(1.+numpy.linspace(0, numpy.pi, size)))
+datac = np.exp(1j*(1.+np.linspace(0, np.pi, size)))
 print(datac.dtype)
 # create complex128 compound data type.
-complex128 = numpy.dtype([('real',numpy.float64),('imag',numpy.float64)])
+complex128 = np.dtype([('real',np.float64),('imag',np.float64)])
 complex128_t = f.createCompoundType(complex128,'complex128')
 # create a variable with this data type, write some data to it.
 f.createDimension('x_dim',None)
 v = f.createVariable('cmplx_var',complex128_t,'x_dim')
-data = numpy.empty(size,complex128) # numpy structured array
+data = np.empty(size,complex128) # numpy structured array
 data['real'] = datac.real; data['imag'] = datac.imag
 v[:] = data
 # close and reopen the file, check the contents.
@@ -156,7 +156,7 @@ def walktree(top):
 print(v.shape)
 datain = v[:] # read in all the data into a numpy structured array
 # create an empty numpy complex array
-datac2 = numpy.empty(datain.shape,numpy.complex128)
+datac2 = np.empty(datain.shape,np.complex128)
 # .. fill it with contents of structured array.
 datac2.real = datain['real']
 datac2.imag = datain['imag']
@@ -168,11 +168,11 @@ def walktree(top):
 # create an unlimited  dimension call 'station'
 f.createDimension('station',None)
 # define a compound data type (can contain arrays, or nested compound types).
-winddtype = numpy.dtype([('speed','f4'),('direction','i4')])
-statdtype = numpy.dtype([('latitude', 'f4'), ('longitude', 'f4'),
-                         ('surface_wind',winddtype),
-                         ('temp_sounding','f4',10),('press_sounding','i4',10),
-                         ('location_name','S12')])
+winddtype = np.dtype([('speed','f4'),('direction','i4')])
+statdtype = np.dtype([('latitude', 'f4'), ('longitude', 'f4'),
+                      ('surface_wind',winddtype),
+                      ('temp_sounding','f4',10),('press_sounding','i4',10),
+                      ('location_name','S12')])
 # use this data type definitions to create a compound data types
 # called using the createCompoundType Dataset method.
 # create a compound type for vector wind which will be nested inside
@@ -181,12 +181,12 @@ def walktree(top):
 # now that wind_data_t is defined, create the station data type.
 station_data_t = f.createCompoundType(statdtype,'station_data')
 # create nested compound data types to hold the units variable attribute.
-winddtype_units = numpy.dtype([('speed','S12'),('direction','S12')])
-statdtype_units = numpy.dtype([('latitude', 'S12'), ('longitude', 'S12'),
-                               ('surface_wind',winddtype_units),
-                               ('temp_sounding','S12'),
-                               ('location_name','S12'),
-                               ('press_sounding','S12')])
+winddtype_units = np.dtype([('speed','S12'),('direction','S12')])
+statdtype_units = np.dtype([('latitude', 'S12'), ('longitude', 'S12'),
+                            ('surface_wind',winddtype_units),
+                            ('temp_sounding','S12'),
+                            ('location_name','S12'),
+                            ('press_sounding','S12')])
 # create the wind_data_units type first, since it will nested inside
 # the station_data_units data type.
 wind_data_units_t = f.createCompoundType(winddtype_units,'wind_data_units')
@@ -195,7 +195,7 @@ def walktree(top):
 # create a variable of of type 'station_data_t'
 statdat = f.createVariable('station_obs', station_data_t, ('station',))
 # create a numpy structured array, assign data to it.
-data = numpy.empty(1,statdtype)
+data = np.empty(1,statdtype)
 data['latitude'] = 40.
 data['longitude'] = -105.
 data['surface_wind']['speed'] = 12.5
@@ -207,12 +207,12 @@ def walktree(top):
 statdat[0] = data
 # or just assign a tuple of values to variable slice
 # (will automatically be converted to a structured array).
-statdat[1] = numpy.array((40.78,-73.99,(-12.5,90),
+statdat[1] = np.array((40.78,-73.99,(-12.5,90),
              (290.2,282.5,279.,277.9,276.,266.,264.1,260.,255.5,243.),
              range(900,400,-50),'New York, NY'),data.dtype)
 print(f.cmptypes)
-windunits = numpy.empty(1,winddtype_units)
-stationobs_units = numpy.empty(1,statdtype_units)
+windunits = np.empty(1,winddtype_units)
+stationobs_units = np.empty(1,statdtype_units)
 windunits['speed'] = 'm/s'
 windunits['direction'] = 'degrees'
 stationobs_units['latitude'] = 'degrees N'
@@ -235,15 +235,15 @@ def walktree(top):
 f.close()
 
 f = Dataset('tst_vlen.nc','w')
-vlen_t = f.createVLType(numpy.int32, 'phony_vlen')
+vlen_t = f.createVLType(np.int32, 'phony_vlen')
 x = f.createDimension('x',3)
 y = f.createDimension('y',4)
 vlvar = f.createVariable('phony_vlen_var', vlen_t, ('y','x'))
 import random
-data = numpy.empty(len(y)*len(x),object)
+data = np.empty(len(y)*len(x),object)
 for n in range(len(y)*len(x)):
-    data[n] = numpy.arange(random.randint(1,10),dtype='int32')+1
-data = numpy.reshape(data,(len(y),len(x)))
+    data[n] = np.arange(random.randint(1,10),dtype='int32')+1
+data = np.reshape(data,(len(y),len(x)))
 vlvar[:] = data
 print(vlvar)
 print('vlen variable =\n',vlvar[:])
@@ -253,7 +253,7 @@ def walktree(top):
 z = f.createDimension('z', 10)
 strvar = f.createVariable('strvar',str,'z')
 chars = '1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'
-data = numpy.empty(10,object)
+data = np.empty(10,object)
 for n in range(10):
     stringlen = random.randint(2,12)
     data[n] = ''.join([random.choice(chars) for i in range(stringlen)])
@@ -270,7 +270,7 @@ def walktree(top):
 u'Nimbostratus': 6, u'Cumulus': 4, u'Altostratus': 5, u'Cumulonimbus': 1,
 u'Stratocumulus': 3}
 # create the Enum type called 'cloud_t'.
-cloud_type = f.createEnumType(numpy.uint8,'cloud_t',enum_dict)
+cloud_type = f.createEnumType(np.uint8,'cloud_t',enum_dict)
 print(cloud_type)
 time = f.createDimension('time',None)
 # create a 1d variable of type 'cloud_type' called 'primary_clouds'.
@@ -295,7 +295,7 @@ def walktree(top):
 nc.createDimension('nchars',3)
 nc.createDimension('nstrings',None)
 v = nc.createVariable('strings','S1',('nstrings','nchars'))
-datain = numpy.array(['foo','bar'],dtype='S3')
+datain = np.array(['foo','bar'],dtype='S3')
 v[:] = stringtochar(datain) # manual conversion to char array
 print(v[:]) # data returned as char array
 v._Encoding = 'ascii' # this enables automatic conversion
@@ -304,12 +304,12 @@ def walktree(top):
 nc.close()
 # strings in compound types
 nc = Dataset('compoundstring_example.nc','w')
-dtype = numpy.dtype([('observation', 'f4'),
-                     ('station_name','S12')])
+dtype = np.dtype([('observation', 'f4'),
+                  ('station_name','S12')])
 station_data_t = nc.createCompoundType(dtype,'station_data')
 nc.createDimension('station',None)
 statdat = nc.createVariable('station_obs', station_data_t, ('station',))
-data = numpy.empty(2,station_data_t.dtype_view)
+data = np.empty(2,station_data_t.dtype_view)
 data['observation'][:] = (123.,3.14)
 data['station_name'][:] = ('Boulder','New York')
 print(statdat.dtype) # strings actually stored as character arrays
@@ -325,8 +325,8 @@ def walktree(top):
 # to disk when it is closed.
 nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
 d = nc.createDimension('x',None)
-v = nc.createVariable('v',numpy.int32,'x')
-v[0:5] = numpy.arange(5)
+v = nc.createVariable('v',np.int32,'x')
+v[0:5] = np.arange(5)
 print(nc)
 print(nc['v'][:])
 nc.close() # file saved to disk
@@ -345,8 +345,8 @@ def walktree(top):
 # used if format is NETCDF3 (ignored for NETCDF4/HDF5 files).
 nc = Dataset('inmemory.nc', mode='w',memory=1028)
 d = nc.createDimension('x',None)
-v = nc.createVariable('v',numpy.int32,'x')
-v[0:5] = numpy.arange(5)
+v = nc.createVariable('v',np.int32,'x')
+v[0:5] = np.arange(5)
 nc_buf = nc.close() # close returns memoryview
 print(type(nc_buf))
 # save nc_buf to disk, read it back in and check.
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 1fa9b53e1..66b7d819f 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -487,9 +487,9 @@ Now that you have a netCDF [Variable](#Variable) instance, how do you put data
 into it? You can just treat it like an array and assign data to a slice.
 
 ```python
->>> import numpy
->>> lats =  numpy.arange(-90,91,2.5)
->>> lons =  numpy.arange(-180,180,2.5)
+>>> import numpy as np
+>>> lats =  np.arange(-90,91,2.5)
+>>> lons =  np.arange(-180,180,2.5)
 >>> latitudes[:] = lats
 >>> longitudes[:] = lons
 >>> print("latitudes =\\n{}".format(latitudes[:]))
@@ -648,7 +648,7 @@ datasets are not supported).
 ...     with Dataset("mftest%s.nc" % nf, "w", format="NETCDF4_CLASSIC") as f:
 ...         _ = f.createDimension("x",None)
 ...         x = f.createVariable("x","i",("x",))
-...         x[0:10] = numpy.arange(nf*10,10*(nf+1))
+...         x[0:10] = np.arange(nf*10,10*(nf+1))
 ```
 
 Now read all the files back in at once with [MFDataset](#MFDataset)
@@ -744,14 +744,14 @@ for storing numpy complex arrays.  Here's an example:
 >>> f = Dataset("complex.nc","w")
 >>> size = 3 # length of 1-d complex array
 >>> # create sample complex data.
->>> datac = numpy.exp(1j*(1.+numpy.linspace(0, numpy.pi, size)))
+>>> datac = np.exp(1j*(1.+np.linspace(0, np.pi, size)))
 >>> # create complex128 compound data type.
->>> complex128 = numpy.dtype([("real",numpy.float64),("imag",numpy.float64)])
+>>> complex128 = np.dtype([("real",np.float64),("imag",np.float64)])
 >>> complex128_t = f.createCompoundType(complex128,"complex128")
 >>> # create a variable with this data type, write some data to it.
 >>> x_dim = f.createDimension("x_dim",None)
 >>> v = f.createVariable("cmplx_var",complex128_t,"x_dim")
->>> data = numpy.empty(size,complex128) # numpy structured array
+>>> data = np.empty(size,complex128) # numpy structured array
 >>> data["real"] = datac.real; data["imag"] = datac.imag
 >>> v[:] = data # write numpy structured array to netcdf compound var
 >>> # close and reopen the file, check the contents.
@@ -759,7 +759,7 @@ for storing numpy complex arrays.  Here's an example:
 >>> v = f.variables["cmplx_var"]
 >>> datain = v[:] # read in all the data into a numpy structured array
 >>> # create an empty numpy complex array
->>> datac2 = numpy.empty(datain.shape,numpy.complex128)
+>>> datac2 = np.empty(datain.shape,np.complex128)
 >>> # .. fill it with contents of structured array.
 >>> datac2.real = datain["real"]; datac2.imag = datain["imag"]
 >>> print('{}: {}'.format(datac.dtype, datac)) # original data
@@ -805,7 +805,7 @@ method of a [Dataset](#Dataset) or [Group](#Group) instance.
 
 ```python
 >>> f = Dataset("tst_vlen.nc","w")
->>> vlen_t = f.createVLType(numpy.int32, "phony_vlen")
+>>> vlen_t = f.createVLType(np.int32, "phony_vlen")
 ```
 
 The numpy datatype of the variable-length sequences and the name of the
@@ -831,10 +831,10 @@ In this case, they contain 1-D numpy `int32` arrays of random length between
 ```python
 >>> import random
 >>> random.seed(54321)
->>> data = numpy.empty(len(y)*len(x),object)
+>>> data = np.empty(len(y)*len(x),object)
 >>> for n in range(len(y)*len(x)):
-...     data[n] = numpy.arange(random.randint(1,10),dtype="int32")+1
->>> data = numpy.reshape(data,(len(y),len(x)))
+...     data[n] = np.arange(random.randint(1,10),dtype="int32")+1
+>>> data = np.reshape(data,(len(y),len(x)))
 >>> vlvar[:] = data
 >>> print("vlen variable =\\n{}".format(vlvar[:]))
 vlen variable =
@@ -880,7 +880,7 @@ array is assigned to the vlen string variable.
 
 ```python
 >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
->>> data = numpy.empty(10,"O")
+>>> data = np.empty(10,"O")
 >>> for n in range(10):
 ...     stringlen = random.randint(2,12)
 ...     data[n] = "".join([random.choice(chars) for i in range(stringlen)])
@@ -926,7 +926,7 @@ values and their names are used to define an Enum data type using
 ... 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5,
 ... 'Cumulonimbus': 1, 'Stratocumulus': 3}
 >>> # create the Enum type called 'cloud_t'.
->>> cloud_type = nc.createEnumType(numpy.uint8,'cloud_t',enum_dict)
+>>> cloud_type = nc.createEnumType(np.uint8,'cloud_t',enum_dict)
 >>> print(cloud_type)
 : name = 'cloud_t', numpy dtype = uint8, fields/values ={'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, 'Stratocumulus': 3}
 ```
@@ -1065,7 +1065,7 @@ characters with one more dimension. For example,
 >>> _ = nc.createDimension('nchars',3)
 >>> _ = nc.createDimension('nstrings',None)
 >>> v = nc.createVariable('strings','S1',('nstrings','nchars'))
->>> datain = numpy.array(['foo','bar'],dtype='S3')
+>>> datain = np.array(['foo','bar'],dtype='S3')
 >>> v[:] = stringtochar(datain) # manual conversion to char array
 >>> print(v[:]) # data returned as char array
 [[b'f' b'o' b'o']
@@ -1095,12 +1095,12 @@ Here's an example:
 
 ```python
 >>> nc = Dataset('compoundstring_example.nc','w')
->>> dtype = numpy.dtype([('observation', 'f4'),
+>>> dtype = np.dtype([('observation', 'f4'),
 ...                      ('station_name','S10')])
 >>> station_data_t = nc.createCompoundType(dtype,'station_data')
 >>> _ = nc.createDimension('station',None)
 >>> statdat = nc.createVariable('station_obs', station_data_t, ('station',))
->>> data = numpy.empty(2,dtype)
+>>> data = np.empty(2,dtype)
 >>> data['observation'][:] = (123.,3.14)
 >>> data['station_name'][:] = ('Boulder','New York')
 >>> print(statdat.dtype) # strings actually stored as character arrays
@@ -1144,8 +1144,8 @@ approaches.
 >>> # and persist the file to disk when it is closed.
 >>> nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
 >>> d = nc.createDimension('x',None)
->>> v = nc.createVariable('v',numpy.int32,'x')
->>> v[0:5] = numpy.arange(5)
+>>> v = nc.createVariable('v',np.int32,'x')
+>>> v[0:5] = np.arange(5)
 >>> print(nc)
 
 root group (NETCDF4 data model, file format HDF5):
@@ -1178,8 +1178,8 @@ root group (NETCDF4 data model, file format HDF5):
 >>> # (ignored for NETCDF4/HDF5 files).
 >>> nc = Dataset('inmemory.nc', mode='w',memory=1028)
 >>> d = nc.createDimension('x',None)
->>> v = nc.createVariable('v',numpy.int32,'x')
->>> v[0:5] = numpy.arange(5)
+>>> v = nc.createVariable('v',np.int32,'x')
+>>> v[0:5] = np.arange(5)
 >>> nc_buf = nc.close() # close returns memoryview
 >>> print(type(nc_buf))
 
@@ -6589,7 +6589,7 @@ time unit and/or calendar to all files.
 Example usage (See [MFTime.__init__](#MFTime.__init__) for more details):
 
 ```python
->>> import numpy
+>>> import numpy as np
 >>> f1 = Dataset("mftest_1.nc","w", format="NETCDF4_CLASSIC")
 >>> f2 = Dataset("mftest_2.nc","w", format="NETCDF4_CLASSIC")
 >>> f1.createDimension("time",None)
@@ -6600,8 +6600,8 @@ Example usage (See [MFTime.__init__](#MFTime.__init__) for more details):
 >>> t2.units = "days since 2000-02-01"
 >>> t1.calendar = "standard"
 >>> t2.calendar = "standard"
->>> t1[:] = numpy.arange(31)
->>> t2[:] = numpy.arange(30)
+>>> t1[:] = np.arange(31)
+>>> t2[:] = np.arange(30)
 >>> f1.close()
 >>> f2.close()
 >>> # Read the two files in at once, in one Dataset.
diff --git a/test/tst_atts.py b/test/tst_atts.py
index 9d2c07fca..8c9c52b7b 100644
--- a/test/tst_atts.py
+++ b/test/tst_atts.py
@@ -6,7 +6,7 @@
 import tempfile
 import warnings
 
-import numpy as NP
+import numpy as np
 from collections import OrderedDict
 from numpy.random.mtrand import uniform
 
@@ -26,7 +26,7 @@
 EMPTYSTRATT = ''
 INTATT = 1
 FLOATATT = math.pi
-SEQATT = NP.arange(10)
+SEQATT = np.arange(10)
 STRINGSEQATT = ['mary ','','had ','a ','little ','lamb',]
 #ATTDICT = {'stratt':STRATT,'floatatt':FLOATATT,'seqatt':SEQATT,
 #           'stringseqatt':''.join(STRINGSEQATT), # changed in issue #770
@@ -106,8 +106,8 @@ def setUp(self):
             raise ValueError('This test should have failed.')
         # issue #485 (triggers segfault in C lib
         # with version 1.2.1 without pull request #486)
-        f.foo = NP.array('bar','S')
-        f.foo = NP.array('bar','U')
+        f.foo = np.array('bar','S')
+        f.foo = np.array('bar','U')
         # issue #529 write string attribute as NC_CHAR unless
         # it can't be decoded to ascii.  Add setncattr_string
         # method to force NC_STRING.
@@ -145,7 +145,7 @@ def runTest(self):
         # global attributes.
         # check __dict__ method for accessing all netCDF attributes.
         for key,val in ATTDICT.items():
-            if type(val) == NP.ndarray:
+            if type(val) == np.ndarray:
                 assert f.__dict__[key].tolist() == val.tolist()
             else:
                 assert f.__dict__[key] == val
@@ -162,7 +162,7 @@ def runTest(self):
         # variable attributes.
         # check __dict__ method for accessing all netCDF attributes.
         for key,val in ATTDICT.items():
-            if type(val) == NP.ndarray:
+            if type(val) == np.ndarray:
                 assert v.__dict__[key].tolist() == val.tolist()
             else:
                 assert v.__dict__[key] == val
@@ -202,7 +202,7 @@ def runTest(self):
         # check attributes in subgroup.
         # global attributes.
         for key,val in ATTDICT.items():
-            if type(val) == NP.ndarray:
+            if type(val) == np.ndarray:
                 assert g.__dict__[key].tolist() == val.tolist()
             else:
                 assert g.__dict__[key] == val
@@ -215,7 +215,7 @@ def runTest(self):
         assert g.stringseqatt == STRINGSEQATT
         assert g.stringseqatt_array == STRINGSEQATT
         for key,val in ATTDICT.items():
-            if type(val) == NP.ndarray:
+            if type(val) == np.ndarray:
                 assert v1.__dict__[key].tolist() == val.tolist()
             else:
                 assert v1.__dict__[key] == val
diff --git a/test/tst_dims.py b/test/tst_dims.py
index 59681e321..026361f48 100644
--- a/test/tst_dims.py
+++ b/test/tst_dims.py
@@ -2,7 +2,6 @@
 import unittest
 import os
 import tempfile
-import numpy as NP
 from numpy.random.mtrand import uniform
 import netCDF4
 
diff --git a/test/tst_grps.py b/test/tst_grps.py
index 16904adec..b3c9428f4 100644
--- a/test/tst_grps.py
+++ b/test/tst_grps.py
@@ -2,7 +2,6 @@
 import unittest
 import os
 import tempfile
-import numpy as NP
 import netCDF4
 
 # test group creation.
diff --git a/test/tst_grps2.py b/test/tst_grps2.py
index ad98a2fee..f157f601f 100644
--- a/test/tst_grps2.py
+++ b/test/tst_grps2.py
@@ -2,7 +2,6 @@
 import unittest
 import os
 import tempfile
-import numpy as NP
 import netCDF4
 
 # test implicit group creation by using unix-like paths
diff --git a/test/tst_masked.py b/test/tst_masked.py
index 2e86e6a09..9d8d97dc0 100644
--- a/test/tst_masked.py
+++ b/test/tst_masked.py
@@ -2,7 +2,7 @@
 import unittest
 import os
 import tempfile
-import numpy as NP
+import numpy as np
 from numpy import ma
 from numpy.testing import assert_array_equal, assert_array_almost_equal
 from numpy.random.mtrand import uniform
@@ -19,22 +19,22 @@
 ranarr = 100.*uniform(size=(ndim))
 ranarr2 = 100.*uniform(size=(ndim))
 # used for checking vector missing_values
-arr3 = NP.linspace(0,9,ndim)
-mask = NP.zeros(ndim,NP.bool_); mask[-1]=True; mask[-2]=True
-marr3 = NP.ma.array(arr3, mask=mask, dtype=NP.int32)
+arr3 = np.linspace(0,9,ndim)
+mask = np.zeros(ndim,np.bool_); mask[-1]=True; mask[-2]=True
+marr3 = np.ma.array(arr3, mask=mask, dtype=np.int32)
 packeddata = 10.*uniform(size=(ndim))
 missing_value = -9999.
-missing_value2 = NP.nan
+missing_value2 = np.nan
 missing_value3 = [8,9]
 ranarr[::2] = missing_value
 ranarr2[::2] = missing_value2
-NP.seterr(invalid='ignore') # silence warnings from ma.masked_values
+np.seterr(invalid='ignore') # silence warnings from ma.masked_values
 maskedarr = ma.masked_values(ranarr,missing_value)
 #maskedarr2 = ma.masked_values(ranarr2,missing_value2)
 maskedarr2 = ma.masked_invalid(ranarr2)
 scale_factor = (packeddata.max()-packeddata.min())/(2.*32766.)
 add_offset = 0.5*(packeddata.max()+packeddata.min())
-packeddata2 = NP.around((packeddata-add_offset)/scale_factor).astype('i2')
+packeddata2 = np.around((packeddata-add_offset)/scale_factor).astype('i2')
 
 class PrimitiveTypesTestCase(unittest.TestCase):
 
@@ -71,7 +71,7 @@ def setUp(self):
         doh2[0] = 1.
         # added test for issue 515
         file.createDimension('x',1)
-        v = file.createVariable('v',NP.float64,'x',fill_value=-9999)
+        v = file.createVariable('v',np.float64,'x',fill_value=-9999)
         file.close()
 
         # issue #972: when auto_fill off byte arrays (u1,i1) should
@@ -119,18 +119,18 @@ def runTest(self):
         assert_array_almost_equal(datamasked[:].filled(),ranarr)
         assert_array_almost_equal(datamasked2[:].filled(),ranarr2)
         assert_array_almost_equal(datapacked[:],packeddata,decimal=4)
-        assert(datapacked3[:].dtype == NP.float64)
+        assert(datapacked3[:].dtype == np.float64)
         # added to test fix to issue 46 (result before r865 was 10)
         assert_array_equal(datapacked2[0],11)
         # added test for issue 515
-        assert(file['v'][0] is NP.ma.masked)
+        assert(file['v'][0] is np.ma.masked)
         file.close()
         # issue 766
-        NP.seterr(invalid='raise')
+        np.seterr(invalid='raise')
         f = netCDF4.Dataset(self.file, 'w')
         f.createDimension('dimension', 2)
-        f.createVariable('variable', NP.float32, dimensions=('dimension',))
-        f['variable'][:] = NP.nan
+        f.createVariable('variable', np.float32, dimensions=('dimension',))
+        f['variable'][:] = np.nan
         data = f['variable'][:] # should not raise an error
         f.close()
         # issue #972
diff --git a/test/tst_rename.py b/test/tst_rename.py
index 0b1cdefba..2f470cab4 100644
--- a/test/tst_rename.py
+++ b/test/tst_rename.py
@@ -2,7 +2,6 @@
 import unittest
 import os
 import tempfile
-import numpy as NP
 import netCDF4
 from netCDF4 import __has_rename_grp__
 
diff --git a/test/tst_scalarvar.py b/test/tst_scalarvar.py
index 6a82574d6..fc11827f0 100644
--- a/test/tst_scalarvar.py
+++ b/test/tst_scalarvar.py
@@ -2,7 +2,6 @@
 import unittest
 import os
 import tempfile
-import numpy as NP
 from numpy.testing import assert_almost_equal
 import netCDF4
 import math
diff --git a/test/tst_unlimdim.py b/test/tst_unlimdim.py
index 9125571ac..69691bdd5 100644
--- a/test/tst_unlimdim.py
+++ b/test/tst_unlimdim.py
@@ -2,7 +2,7 @@
 import unittest
 import os
 import tempfile
-import numpy as NP
+import numpy as np
 from numpy.random.mtrand import uniform
 from numpy.testing import assert_array_equal, assert_array_almost_equal
 import netCDF4
@@ -59,7 +59,7 @@ def runTest(self):
         self.assertTrue(bar.shape == (n1dim,n2dim,n3dim))
         # check data.
         #assert_array_almost_equal(bar[:,:,:], ranarr)
-        assert_array_almost_equal(bar[:,:,:], 2.*NP.ones((n1dim,n2dim,n3dim),ranarr.dtype))
+        assert_array_almost_equal(bar[:,:,:], 2.*np.ones((n1dim,n2dim,n3dim),ranarr.dtype))
         f.close()
 
 if __name__ == '__main__':
diff --git a/test/tst_vars.py b/test/tst_vars.py
index dffb93f0d..e75429ed4 100644
--- a/test/tst_vars.py
+++ b/test/tst_vars.py
@@ -2,7 +2,7 @@
 import unittest
 import os
 import tempfile
-import numpy as NP
+import numpy as np
 from numpy.random.mtrand import uniform
 from numpy.testing import assert_array_equal, assert_array_almost_equal
 import netCDF4
@@ -67,7 +67,7 @@ def runTest(self):
         assert v1.size == DIM1_LEN * DIM2_LEN * DIM3_LEN
         assert len(v1) == DIM1_LEN
 
-        #assert NP.allclose(v1[:],randomdata)
+        #assert np.allclose(v1[:],randomdata)
         assert_array_almost_equal(v1[:],randomdata)
         # check variables in sub group.
         g = f.groups[GROUP_NAME]
@@ -86,7 +86,7 @@ def runTest(self):
         assert v2.dimensions == (DIM2_NAME,DIM3_NAME)
         assert v1.shape == (DIM1_LEN,DIM2_LEN,DIM3_LEN)
         assert v2.shape == (DIM2_LEN,DIM3_LEN)
-        #assert NP.allclose(v1[:],randomdata)
+        #assert np.allclose(v1[:],randomdata)
         assert_array_almost_equal(v1[:],randomdata)
         f.close()
 

From 739d690c91d2eabba430949f058a1923aecb689e Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 17 Feb 2021 07:22:54 -0700
Subject: [PATCH 0612/1504] fix broken doc links

---
 src/netCDF4/_netCDF4.pyx | 104 +++++++++++++++++++--------------------
 1 file changed, 52 insertions(+), 52 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 66b7d819f..3c9449b2e 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -134,7 +134,7 @@ creating a new file, the format may be specified using the `format`
 keyword in the `Dataset` constructor.  The default format is
 `NETCDF4`. To see how a given file is formatted, you can examine the
 `data_model` attribute.  Closing the netCDF file is
-accomplished via the [Dataset.close](#Dataset.close) method of the [Dataset](#Dataset)
+accomplished via the `Dataset.close` method of the [Dataset](#Dataset)
 instance.
 
 Here's an example:
@@ -162,8 +162,8 @@ as containers for variables, dimensions and attributes, as well as other
 groups.  A [Dataset](#Dataset) creates a special group, called
 the 'root group', which is similar to the root directory in a unix
 filesystem.  To create [Group](#Group) instances, use the
-[Dataset.createGroup](#Dataset.createGroup) method of a [Dataset](#Dataset) or [Group](#Group)
-instance. [Dataset.createGroup](#Dataset.createGroup) takes a single argument, a
+`Dataset.createGroup` method of a [Dataset](#Dataset) or [Group](#Group)
+instance. `Dataset.createGroup` takes a single argument, a
 python string containing the name of the new group. The new [Group](#Group)
 instances contained within the root group can be accessed by name using
 the `groups` dictionary attribute of the [Dataset](#Dataset) instance.  Only
@@ -193,7 +193,7 @@ has a `groups` attribute dictionary containing all of the group
 instances contained within that group. Each [Group](#Group) instance also has a
 `path` attribute that contains a simulated unix directory path to
 that group.  To simplify the creation of nested groups, you can
-use a unix-like path as an argument to [Dataset.createGroup](#Dataset.createGroup).
+use a unix-like path as an argument to `Dataset.createGroup`.
 
 ```python
 >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
@@ -254,7 +254,7 @@ netCDF defines the sizes of all variables in terms of dimensions, so
 before any variables can be created the dimensions they use must be
 created first. A special case, not often used in practice, is that of a
 scalar variable, which has no dimensions. A dimension is created using
-the [Dataset.createDimension](#Dataset.createDimension) method of a [Dataset](#Dataset)
+the `Dataset.createDimension` method of a [Dataset](#Dataset)
 or [Group](#Group) instance. A Python string is used to set the name of the
 dimension, and an integer value is used to set the size. To create an
 unlimited dimension (a dimension that can be appended to), the size
@@ -315,12 +315,12 @@ netCDF variables behave much like python multidimensional array objects
 supplied by the [numpy module](http://numpy.scipy.org). However,
 unlike numpy arrays, netCDF4 variables can be appended to along one or
 more 'unlimited' dimensions. To create a netCDF variable, use the
-[Dataset.createVariable](#Dataset.createVariable) method of a [Dataset](#Dataset) or
-[Group](#Group) instance. The [Dataset.createVariable](#Dataset.createVariable) method
+`Dataset.createVariable` method of a [Dataset](#Dataset) or
+[Group](#Group) instance. The `Dataset.createVariable`j method
 has two mandatory arguments, the variable name (a Python string), and
 the variable datatype. The variable's dimensions are given by a tuple
 containing the dimension names (defined previously with
-[Dataset.createDimension](#Dataset.createDimension)). To create a scalar
+`Dataset.createDimension`). To create a scalar
 variable, simply leave out the dimensions keyword. The variable
 primitive datatypes correspond to the dtype attribute of a numpy array.
 You can specify the datatype as a numpy dtype object, or anything that
@@ -338,7 +338,7 @@ will also work. The unsigned integer types and the 64-bit integer type
 can only be used if the file format is `NETCDF4`.
 
 The dimensions themselves are usually also defined as variables, called
-coordinate variables. The [Dataset.createVariable](#Dataset.createVariable)
+coordinate variables. The `Dataset.createVariable`
 method returns an instance of the [Variable](#Variable) class whose methods can be
 used later to access and set variable data and attributes.
 
@@ -423,7 +423,7 @@ filling on, default _FillValue of 9.969209968386869e+36 used}
 ```
 
 [Variable](#Variable) names can be changed using the
-[Dataset.renameVariable](#Dataset.renameVariable) method of a [Dataset](#Dataset)
+`Dataset.renameVariable` method of a [Dataset](#Dataset)
 instance.
 
 Variables can be sliced similar to numpy arrays, but there are some differences.  See
@@ -454,7 +454,7 @@ our example,
 >>> times.calendar = "gregorian"
 ```
 
-The [Dataset.ncattrs](#Dataset.ncattrs) method of a [Dataset](#Dataset), [Group](#Group) or
+The `Dataset.ncattrs` method of a [Dataset](#Dataset), [Group](#Group) or
 [Variable](#Variable) instance can be used to retrieve the names of all the netCDF
 attributes. This method is provided as a convenience, since using the
 built-in `dir` Python function will return a bunch of private methods
@@ -580,12 +580,12 @@ The result will be a numpy scalar array.
 
 By default, netcdf4-python returns numpy masked arrays with values equal to the
 `missing_value` or `_FillValue` variable attributes masked.  The
-[Dataset.set_auto_mask](#Dataset.set_auto_mask)  [Dataset](#Dataset) and [Variable](#Variable) methods
+`Dataset.set_auto_mask` [Dataset](#Dataset) and [Variable](#Variable) methods
 can be used to disable this feature so that
 numpy arrays are always returned, with the missing values included. Prior to
 version 1.4.0 the default behavior was to only return masked arrays when the
 requested slice contained missing values.  This behavior can be recovered
-using the [Dataset.set_always_mask](#Dataset.set_always_mask) method. If a masked array is
+using the `Dataset.set_always_mask` method. If a masked array is
 written to a netCDF variable, the masked elements are filled with the
 value specified by the `missing_value` attribute.  If the variable has
 no `missing_value`, the `_FillValue` is used instead.
@@ -672,7 +672,7 @@ datasets.
 Data stored in netCDF 4 [Variable](#Variable) objects can be compressed and
 decompressed on the fly. The parameters for the compression are
 determined by the `zlib`, `complevel` and `shuffle` keyword arguments
-to the [Dataset.createVariable](#Dataset.createVariable) method. To turn on
+to the `Dataset.createVariable` method. To turn on
 compression, set `zlib=True`.  The `complevel` keyword regulates the
 speed and efficiency of the compression (1 being fastest, but lowest
 compression ratio, 9 being slowest but best compression ratio). The
@@ -681,12 +681,12 @@ off the HDF5 shuffle filter, which de-interlaces a block of data before
 compression by reordering the bytes.  The shuffle filter can
 significantly improve compression ratios, and is on by default.  Setting
 `fletcher32` keyword argument to
-[Dataset.createVariable](#Dataset.createVariable) to `True` (it's `False` by
+`Dataset.createVariable` to `True` (it's `False` by
 default) enables the Fletcher32 checksum algorithm for error detection.
 It's also possible to set the HDF5 chunking parameters and endian-ness
 of the binary data stored in the HDF5 file with the `chunksizes`
 and `endian` keyword arguments to
-[Dataset.createVariable](#Dataset.createVariable).  These keyword arguments only
+`Dataset.createVariable`.  These keyword arguments only
 are relevant for `NETCDF4` and `NETCDF4_CLASSIC` files (where the
 underlying file format is HDF5) and are silently ignored if the file
 format is `NETCDF3_CLASSIC`, `NETCDF3_64BIT_OFFSET` or `NETCDF3_64BIT_DATA`.
@@ -695,7 +695,7 @@ If your data only has a certain number of digits of precision (say for
 example, it is temperature data that was measured with a precision of
 0.1 degrees), you can dramatically improve zlib compression by
 quantizing (or truncating) the data using the `least_significant_digit`
-keyword argument to [Dataset.createVariable](#Dataset.createVariable). The least
+keyword argument to `Dataset.createVariable`. The least
 significant digit is the power of ten of the smallest decimal place in
 the data that is a reliable value. For example if the data has a
 precision of 0.1, then setting `least_significant_digit=1` will cause
@@ -736,7 +736,7 @@ location for scattered (point) data. You can then access all the
 information for a point by reading one variable, instead of reading
 different parameters from different variables.  Compound data types
 are created from the corresponding numpy data type using the
-[Dataset.createCompoundType](#Dataset.createCompoundType) method of a [Dataset](#Dataset) or [Group](#Group) instance.
+`Dataset.createCompoundType` method of a [Dataset](#Dataset) or [Group](#Group) instance.
 Since there is no native complex data type in netcdf, compound types are handy
 for storing numpy complex arrays.  Here's an example:
 
@@ -800,7 +800,7 @@ current shape = (3,)
 
 NetCDF 4 has support for variable-length or "ragged" arrays.  These are arrays
 of variable length sequences having the same type. To create a variable-length
-data type, use the [Dataset.createVLType](#Dataset.createVLType) method
+data type, use the `Dataset.createVLType` method
 method of a [Dataset](#Dataset) or [Group](#Group) instance.
 
 ```python
@@ -867,7 +867,7 @@ Numpy object arrays containing python strings can also be written as vlen
 variables,  For vlen strings, you don't need to create a vlen data type.
 Instead, simply use the python `str` builtin (or a numpy string datatype
 with fixed length greater than 1) when calling the
-[Dataset.createVariable](#Dataset.createVariable) method.
+`Dataset.createVariable` method.
 
 ```python
 >>> z = f.createDimension("z",10)
@@ -916,7 +916,7 @@ a numpy data type, they are read and written as integer arrays.
 Here's an example of using an Enum type to hold cloud type data.
 The base integer data type and a python dictionary describing the allowed
 values and their names are used to define an Enum data type using
-[Dataset.createEnumType](#Dataset.createEnumType).
+`Dataset.createEnumType`.
 
 ```python
 >>> nc = Dataset('clouds.nc','w')
@@ -1020,7 +1020,7 @@ Independent IO means that each process can do IO independently. It should not
 depend on or be affected by other processes. Collective IO is a way of doing
 IO defined in the MPI-IO standard; unlike independent IO, all processes must
 participate in doing IO. To toggle back and forth between
-the two types of IO, use the [Variable.set_collective](#Variable.set_collective)
+the two types of IO, use the `Variable.set_collective`
 [Variable](#Variable) method. All metadata
 operations (such as creation of groups, types, variables, dimensions, or attributes)
 are collective.  There are a couple of important limitations of parallel IO:
@@ -1079,7 +1079,7 @@ characters with one more dimension. For example,
 
 Even if the `_Encoding` attribute is set, the automatic conversion of char
 arrays to/from string arrays can be disabled with
-[Variable.set_auto_chartostring](#Variable.set_auto_chartostring).
+`Variable.set_auto_chartostring`.
 
 A similar situation is often encountered with numpy structured arrays with subdtypes
 containing fixed-wdith byte strings (dtype=`S#`). Since there is no native fixed-length string
@@ -1963,12 +1963,12 @@ cdef class Dataset:
     """
 A netCDF [Dataset](#Dataset) is a collection of dimensions, groups, variables and
 attributes. Together they describe the meaning of data and relations among
-data fields stored in a netCDF file. See [Dataset.__init__](#Dataset.__init__) for more
+data fields stored in a netCDF file. See `Dataset.__init__` for more
 details.
 
 A list of attribute names corresponding to global netCDF attributes
 defined for the [Dataset](#Dataset) can be obtained with the
-[Dataset.ncattrs](#Dataset.ncattrs) method.
+`Dataset.ncattrs` method.
 These attributes can be created by assigning to an attribute of the
 [Dataset](#Dataset) instance. A dictionary containing all the netCDF attribute
 name/value pairs is provided by the `__dict__` attribute of a
@@ -2668,7 +2668,7 @@ Data from netCDF variables is presented to python as numpy arrays with
 the corresponding data type.
 
 `dimensions` must be a tuple containing dimension names (strings) that
-have been defined previously using [Dataset.createDimension](#Dataset.createDimension). The default value
+have been defined previously using `Dataset.createDimension`. The default value
 is an empty tuple, which means the variable is a scalar.
 
 If the optional keyword `zlib` is `True`, the data will be compressed in
@@ -2739,7 +2739,7 @@ The return value is the [Variable](#Variable) class instance describing the new
 variable.
 
 A list of names corresponding to netCDF variable attributes can be
-obtained with the [Variable](#Variable) method [Variable.ncattrs](#Variable.ncattrs). A dictionary
+obtained with the [Variable](#Variable) method `Variable.ncattrs`. A dictionary
 containing all the netCDF attribute name/value pairs is provided by
 the `__dict__` attribute of a [Variable](#Variable) instance.
 
@@ -2985,7 +2985,7 @@ version 4.3.1 or higher of the netcdf C lib, and rebuild netcdf4-python."""
         """
 **`set_auto_chartostring(self, True_or_False)`**
 
-Call [Variable.set_auto_chartostring](#Variable.set_auto_chartostring) for all variables contained in this [Dataset](#Dataset) or
+Call `Variable.set_auto_chartostring` for all variables contained in this [Dataset](#Dataset) or
 [Group](#Group), as well as for all variables in all its subgroups.
 
 **`True_or_False`**: Boolean determining if automatic conversion of
@@ -3013,7 +3013,7 @@ after calling this function will follow the default behaviour.
         """
 **`set_auto_maskandscale(self, True_or_False)`**
 
-Call [Variable.set_auto_maskandscale](#Variable.set_auto_maskandscale) for all variables contained in this [Dataset](#Dataset) or
+Call `Variable.set_auto_maskandscale` for all variables contained in this [Dataset](#Dataset) or
 [Group](#Group), as well as for all variables in all its subgroups.
 
 **`True_or_False`**: Boolean determining if automatic conversion to masked arrays
@@ -3040,7 +3040,7 @@ after calling this function will follow the default behaviour.
         """
 **`set_auto_mask(self, True_or_False)`**
 
-Call [Variable.set_auto_mask](#Variable.set_auto_mask) for all variables contained in this [Dataset](#Dataset) or
+Call `Variable.set_auto_mask` for all variables contained in this [Dataset](#Dataset) or
 [Group](#Group), as well as for all variables in all its subgroups.
 
 **`True_or_False`**: Boolean determining if automatic conversion to masked arrays
@@ -3066,7 +3066,7 @@ after calling this function will follow the default behaviour.
         """
 **`set_auto_scale(self, True_or_False)`**
 
-Call [Variable.set_auto_scale](#Variable.set_auto_scale) for all variables contained in this [Dataset](#Dataset) or
+Call `Variable.set_auto_scale` for all variables contained in this [Dataset](#Dataset) or
 [Group](#Group), as well as for all variables in all its subgroups.
 
 **`True_or_False`**: Boolean determining if automatic variable scaling
@@ -3092,7 +3092,7 @@ after calling this function will follow the default behaviour.
         """
 **`set_always_mask(self, True_or_False)`**
 
-Call [Variable.set_always_mask](#Variable.set_always_mask) for all variables contained in
+Call `Variable.set_always_mask` for all variables contained in
 this [Dataset](#Dataset) or [Group](#Group), as well as for all
 variables in all its subgroups.
 
@@ -3123,7 +3123,7 @@ the default behaviour.
         """
 **`set_ncstring_attrs(self, True_or_False)`**
 
-Call [Variable.set_ncstring_attrs](#Variable.set_ncstring_attrs) for all variables contained in
+Call `Variable.set_ncstring_attrs` for all variables contained in
 this [Dataset](#Dataset) or [Group](#Group), as well as for all its
 subgroups and their variables.
 
@@ -3312,7 +3312,7 @@ Additional read-only class variables:
         **`name`**: - Name of the group.
 
         ***Note***: [Group](#Group) instances should be created using the
-        [Dataset.createGroup](#Dataset.createGroup) method of a [Dataset](#Dataset) instance, or
+        `Dataset.createGroup` method of a [Dataset](#Dataset) instance, or
         another [Group](#Group) instance, not using this class directly.
         """
         cdef char *groupname
@@ -3381,7 +3381,7 @@ determine if the dimension is unlimited.
 Read-only class variables:
 
 **`name`**: String name, used when creating a [Variable](#Variable) with
-[Dataset.createVariable](#Dataset.createVariable).
+`Dataset.createVariable`.
 
 **`size`**: Current [Dimension](#Dimension) size (same as `len(d)`, where `d` is a
 [Dimension](#Dimension) instance).
@@ -3402,7 +3402,7 @@ Read-only class variables:
         **`size`**: Size of the dimension. `None` or 0 means unlimited. (Default `None`).
 
         ***Note***: [Dimension](#Dimension) instances should be created using the
-        [Dataset.createDimension](#Dataset.createDimension) method of a [Group](#Group) or
+        `Dataset.createDimension` method of a [Group](#Group) or
         [Dataset](#Dataset) instance, not using [Dimension.__init__](#Dimension.__init__) directly.
         """
         cdef int ierr
@@ -3522,11 +3522,11 @@ returns `True` if the [Dimension](#Dimension) instance is unlimited, `False` oth
 cdef class Variable:
     """
 A netCDF [Variable](#Variable) is used to read and write netCDF data.  They are
-analogous to numpy array objects. See [Variable.__init__](#Variable.__init__) for more
+analogous to numpy array objects. See `Variable.__init__` for more
 details.
 
 A list of attribute names corresponding to netCDF attributes defined for
-the variable can be obtained with the [Variable.ncattrs](#Variable.ncattrs) method. These
+the variable can be obtained with the `Variable.ncattrs` method. These
 attributes can be created by assigning to an attribute of the
 [Variable](#Variable) instance. A dictionary containing all the netCDF attribute
 name/value pairs is provided by the `__dict__` attribute of a
@@ -3547,18 +3547,18 @@ variable's data type.
 **`scale`**: If True, `scale_factor` and `add_offset` are
 applied, and signed integer data is automatically converted to
 unsigned integer data if the `_Unsigned` attribute is set.
-Default is `True`, can be reset using [Variable.set_auto_scale](#Variable.set_auto_scale) and
-[Variable.set_auto_maskandscale](#Variable.set_auto_maskandscale) methods.
+Default is `True`, can be reset using `Variable.set_auto_scale` and
+`Variable.set_auto_maskandscale` methods.
 
 **`mask`**: If True, data is automatically converted to/from masked
 arrays when missing values or fill values are present. Default is `True`, can be
-reset using [Variable.set_auto_mask](#Variable.set_auto_mask) and [Variable.set_auto_maskandscale](#Variable.set_auto_maskandscale)
+reset using `Variable.set_auto_mask` and `Variable.set_auto_maskandscale`
 methods.
 
 **`chartostring`**: If True, data is automatically converted to/from character
 arrays to string arrays when the `_Encoding` variable attribute is set.
 Default is `True`, can be reset using
-[Variable.set_auto_chartostring](#Variable.set_auto_chartostring) method.
+`Variable.set_auto_chartostring` method.
 
 **`least_significant_digit`**: Describes the power of ten of the
 smallest decimal place in the data the contains a reliable value.  Data is
@@ -3677,7 +3677,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         change it when Dataset is re-opened. 
 
         ***Note***: [Variable](#Variable) instances should be created using the
-        [Dataset.createVariable](#Dataset.createVariable) method of a [Dataset](#Dataset) or
+        `Dataset.createVariable` method of a [Dataset](#Dataset) or
         [Group](#Group) instance, not using this class directly.
         """
         cdef int ierr, ndims, icontiguous, ideflate_level, numdims, _grpid
@@ -5492,7 +5492,7 @@ return a tuple of [Dimension](#Dimension) instances associated with this
 cdef class CompoundType:
     """
 A [CompoundType](#CompoundType) instance is used to describe a compound data
-type, and can be passed to the the [Dataset.createVariable](#Dataset.createVariable) method of
+type, and can be passed to the the `Dataset.createVariable` method of
 a [Dataset](#Dataset) or [Group](#Group) instance.
 Compound data types map to numpy structured arrays.
 See [CompoundType.__init__](#CompoundType.__init__) for more details.
@@ -5523,8 +5523,8 @@ the user.
         first).
 
         ***Note 2***: [CompoundType](#CompoundType) instances should be created using the
-        [Dataset.createCompoundType](#Dataset.createCompoundType)
-        method of a [Dataset](#Dataset) or [Group](#Group) instance, not using this class directly.
+        `Dataset.createCompoundType` method of a [Dataset](#Dataset) or
+        [Group](#Group) instance, not using this class directly.
         """
         cdef nc_type xtype
         # convert dt to a numpy datatype object
@@ -5797,7 +5797,7 @@ cdef _read_compound(group, nc_type xtype, endian=None):
 cdef class VLType:
     """
 A [VLType](#VLType) instance is used to describe a variable length (VLEN) data
-type, and can be passed to the the [Dataset.createVariable](#Dataset.createVariable) method of
+type, and can be passed to the the `Dataset.createVariable` method of
 a [Dataset](#Dataset) or [Group](#Group) instance. See
 [VLType.__init__](#VLType.__init__)for more details.
 
@@ -5821,8 +5821,8 @@ the user.
         VLEN data type.
 
         ***`Note`***: [VLType](#VLType) instances should be created using the
-        [Dataset.createVLType](#Dataset.createVLType)
-        method of a [Dataset](#Dataset) or [Group](#Group) instance, not using this class directly.
+        `Dataset.createVLType` method of a [Dataset](#Dataset) or
+        [Group](#Group) instance, not using this class directly.
         """
         cdef nc_type xtype
         if 'typeid' in kwargs:
@@ -5906,7 +5906,7 @@ cdef _read_vlen(group, nc_type xtype, endian=None):
 cdef class EnumType:
     """
 A [EnumType](#EnumType) instance is used to describe an Enum data
-type, and can be passed to the the [Dataset.createVariable](#Dataset.createVariable) method of
+type, and can be passed to the the `Dataset.createVariable` method of
 a [Dataset](#Dataset) or [Group](#Group) instance. See
 [EnumType.__init__](#EnumType.__init__) for more details.
 
@@ -5933,8 +5933,8 @@ the user.
         pairs.
 
         ***`Note`***: [EnumType](#EnumType) instances should be created using the
-        [Dataset.createEnumType](#Dataset.createEnumType)
-        method of a [Dataset](#Dataset) or [Group](#Group) instance, not using this class directly.
+        `Dataset.createEnumType` method of a [Dataset](#Dataset) or
+        [Group](#Group) instance, not using this class directly.
         """
         cdef nc_type xtype
         if 'typeid' in kwargs:

From 2a564ed52b6688d6dff8a7e86b53a5c01f9c005c Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 17 Feb 2021 07:32:17 -0700
Subject: [PATCH 0613/1504] update

---
 docs/index.html          | 1937 +++++++++++++++++++++-----------------
 src/netCDF4/_netCDF4.pyx |  332 +++----
 2 files changed, 1215 insertions(+), 1054 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 04c888dd2..177b66551 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -3,24 +3,19 @@
 
     
     
-    
+    
     netCDF4 API documentation
     
 
 
 
 
-
+
 
         
      • 
                 
    
 
-            
-            
  • 
-                    Group
-                            
-
-            
    • 
-            
  • 
-                    Dimension
-                            
-
             
    • 
             
  • 
                     Variable
@@ -345,67 +307,103 @@ 
    API Documentation
    
 
             
    • 
             
  • 
-                    CompoundType
+                    Dimension
                             
 
             
    • 
             
  • 
-                    VLType
+                    Group
                             
+
+            
    • 
+            
  • 
+                    MFDataset
+                            
 
             
    • 
             
  • 
-                    EnumType
+                    MFTime
                             
+
+            
    • 
+            
  • 
+                    CompoundType
+                            
 
             
    • 
             
  • 
-                    getlibversion
+                    VLType
+                            
+
             
    • 
             
  • 
-                    get_chunk_cache
+                    date2num
             
    • 
             
  • 
-                    set_chunk_cache
+                    num2date
             
    • 
             
  • 
-                    stringtoarr
+                    date2index
             
    • 
             
  • 
                     stringtochar
@@ -414,35 +412,41 @@ 
    API Documentation
    
                     chartostring
             
    • 
             
  • 
-                    MFDataset
+                    stringtoarr
+            
    • 
+            
  • 
+                    getlibversion
+            
    • 
+            
  • 
+                    EnumType
                             
-
-            
    • 
-            
  • 
-                    MFTime
-                            
 
             
    • 
+            
  • 
+                    get_chunk_cache
+            
    • 
+            
  • 
+                    set_chunk_cache
+            
    • 
     
 
 
                     
-                        built with pdocpdoc logo
                     
             
    
@@ -450,7 +454,7 @@ 
    API Documentation
    
     
    
             
    
                     
    
-netCDF4._netCDF4    
    
+netCDF4    
    
 
                         
    Version 1.5.6
    
 
@@ -569,7 +573,7 @@ 
    Tutorial
    
 
 
    Creating/Opening/Closing a netCDF file
    
 
-
    To create a netCDF file from python, you simply call the Dataset
+
    To create a netCDF file from python, you simply call the Dataset
 constructor. This is also the method used to open an existing netCDF
 file.  If the file is open for write access (mode='w', 'r+' or 'a'), you may
 write any type of data including new dimensions, groups, variables and
@@ -593,7 +597,7 @@ 
    Creating/Opening/Closing a netCDF
 keyword in the Dataset constructor.  The default format is
 NETCDF4. To see how a given file is formatted, you can examine the
 data_model attribute.  Closing the netCDF file is
-accomplished via the Dataset.close">Dataset.close method of the Dataset
+accomplished via the Dataset.close method of the Dataset
 instance.
    
 
 
    Here's an example:
    
@@ -606,7 +610,7 @@ 
    Creating/Opening/Closing a netCDF
 
    
 
 
    Remote OPeNDAP-hosted datasets can be accessed for
-reading over http if a URL is provided to the Dataset constructor instead of a
+reading over http if a URL is provided to the Dataset constructor instead of a
 filename.  However, this requires that the netCDF library be built with
 OPenDAP support, via the --enable-dap configure option (added in
 version 4.0.1).
    
@@ -616,14 +620,14 @@ 
    Groups in a netCDF file
    
 
    netCDF version 4 added support for organizing data in hierarchical
 groups, which are analogous to directories in a filesystem. Groups serve
 as containers for variables, dimensions and attributes, as well as other
-groups.  A Dataset creates a special group, called
+groups.  A Dataset creates a special group, called
 the 'root group', which is similar to the root directory in a unix
-filesystem.  To create Group instances, use the
-Dataset.createGroup">Dataset.createGroup method of a Dataset or Group
-instance. Dataset.createGroup">Dataset.createGroup takes a single argument, a
-python string containing the name of the new group. The new Group
+filesystem.  To create Group instances, use the
+Dataset.createGroup method of a Dataset or Group
+instance. Dataset.createGroup takes a single argument, a
+python string containing the name of the new group. The new Group
 instances contained within the root group can be accessed by name using
-the groups dictionary attribute of the Dataset instance.  Only
+the groups dictionary attribute of the Dataset instance.  Only
 NETCDF4 formatted files support Groups, if you try to create a Group
 in a netCDF 3 file you will get an error message.
    
 
@@ -643,13 +647,13 @@ 
    Groups in a netCDF file
    
 >>>
 
    
 
-
    Groups can exist within groups in a Dataset, just as directories
-exist within directories in a unix filesystem. Each Group instance
+
    Groups can exist within groups in a Dataset, just as directories
+exist within directories in a unix filesystem. Each Group instance
 has a groups attribute dictionary containing all of the group
-instances contained within that group. Each Group instance also has a
+instances contained within that group. Each Group instance also has a
 path attribute that contains a simulated unix directory path to
 that group.  To simplify the creation of nested groups, you can
-use a unix-like path as an argument to Dataset.createGroup">Dataset.createGroup.
    
+use a unix-like path as an argument to Dataset.createGroup.
    
 
 
    >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
 >>> fcstgrp2 = rootgrp.createGroup("/forecasts/model2")
@@ -661,8 +665,8 @@ 
    Groups in a netCDF file
    
 returned.
    
 
 
    Here's an example that shows how to navigate all the groups in a
-Dataset. The function walktree is a Python generator that is used
-to walk the directory tree. Note that printing the Dataset or Group
+Dataset. The function walktree is a Python generator that is used
+to walk the directory tree. Note that printing the Dataset or Group
 object yields summary information about it's contents.
    
 
 
    >>> def walktree(top):
@@ -708,8 +712,8 @@ 
    Dimensions in a netCDF file
    
 before any variables can be created the dimensions they use must be
 created first. A special case, not often used in practice, is that of a
 scalar variable, which has no dimensions. A dimension is created using
-the Dataset.createDimension">Dataset.createDimension method of a Dataset
-or Group instance. A Python string is used to set the name of the
+the Dataset.createDimension method of a Dataset
+or Group instance. A Python string is used to set the name of the
 dimension, and an integer value is used to set the size. To create an
 unlimited dimension (a dimension that can be appended to), the size
 value is set to None or 0. In this example, there both the time and
@@ -723,15 +727,15 @@ 
    Dimensions in a netCDF file
    
 >>> lon = rootgrp.createDimension("lon", 144)
 
    
 
-
    All of the Dimension instances are stored in a python dictionary.
    
+
    All of the Dimension instances are stored in a python dictionary.
    
 
 
    >>> print(rootgrp.dimensions)
 {'level': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0, 'time': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0, 'lat': <class 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 73, 'lon': <class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144}
 
    
 
-
    Using the python len function with a Dimension instance returns
+
    Using the python len function with a Dimension instance returns
 current size of that dimension.
-Dimension.isunlimited">Dimension.isunlimited method of a Dimension instance
+Dimension.isunlimited">Dimension.isunlimited method of a Dimension instance
 be used to determine if the dimensions is unlimited, or appendable.
    
 
 
    >>> print(len(lon))
@@ -742,7 +746,7 @@ 
    Dimensions in a netCDF file
    
 True
 
    
 
-
    Printing the Dimension object
+
    Printing the Dimension object
 provides useful summary info, including the name and length of the dimension,
 and whether it is unlimited.
    
 
@@ -754,9 +758,9 @@ 
    Dimensions in a netCDF file
    
 <class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144
 
    
 
-
    Dimension names can be changed using the
-Datatset.renameDimension method of a Dataset or
-Group instance.
    
+
    Dimension names can be changed using the
+Datatset.renameDimension method of a Dataset or
+Group instance.
    
 
 
    Variables in a netCDF file
    
 
@@ -764,12 +768,12 @@ 
    Variables in a netCDF file
    
 supplied by the numpy module. However,
 unlike numpy arrays, netCDF4 variables can be appended to along one or
 more 'unlimited' dimensions. To create a netCDF variable, use the
-Dataset.createVariable">Dataset.createVariable method of a Dataset or
-Group instance. The Dataset.createVariable">Dataset.createVariable method
+Dataset.createVariable method of a Dataset or
+Group instance. The Dataset.createVariablej method
 has two mandatory arguments, the variable name (a Python string), and
 the variable datatype. The variable's dimensions are given by a tuple
 containing the dimension names (defined previously with
-Dataset.createDimension">Dataset.createDimension). To create a scalar
+Dataset.createDimension). To create a scalar
 variable, simply leave out the dimensions keyword. The variable
 primitive datatypes correspond to the dtype attribute of a numpy array.
 You can specify the datatype as a numpy dtype object, or anything that
@@ -787,8 +791,8 @@ 
    Variables in a netCDF file
    
 can only be used if the file format is NETCDF4.
    
 
 
    The dimensions themselves are usually also defined as variables, called
-coordinate variables. The Dataset.createVariable">Dataset.createVariable
-method returns an instance of the Variable class whose methods can be
+coordinate variables. The Dataset.createVariable
+method returns an instance of the Variable class whose methods can be
 used later to access and set variable data and attributes.
    
 
 
    >>> times = rootgrp.createVariable("time","f8",("time",))
@@ -800,7 +804,7 @@ 
    Variables in a netCDF file
    
 >>> temp.units = "K"
 
    
 
-
    To get summary info on a Variable instance in an interactive session,
+
    To get summary info on a Variable instance in an interactive session,
 just print it.
    
 
 
    >>> print(temp)
@@ -819,8 +823,8 @@ 
    Variables in a netCDF file
    
 
 
    If the intermediate groups do not yet exist, they will be created.
    
 
-
    You can also query a Dataset or Group instance directly to obtain Group or
-Variable instances using paths.
    
+
    You can also query a Dataset or Group instance directly to obtain Group or
+Variable instances using paths.
    
 
 
    >>> print(rootgrp["/forecasts/model1"])  # a Group instance
 <class 'netCDF4._netCDF4.Group'>
@@ -837,7 +841,7 @@ 
    Variables in a netCDF file
    
 filling on, default _FillValue of 9.969209968386869e+36 used
 
    
 
-
    All of the variables in the Dataset or Group are stored in a
+
    All of the variables in the Dataset or Group are stored in a
 Python dictionary, in the same way as the dimensions:
    
 
 
    >>> print(rootgrp.variables)
@@ -865,8 +869,8 @@ 
    Variables in a netCDF file
    
 filling on, default _FillValue of 9.969209968386869e+36 used}
 
    
 
-
    Variable names can be changed using the
-Dataset.renameVariable">Dataset.renameVariable method of a Dataset
+
    Variable names can be changed using the
+Dataset.renameVariable method of a Dataset
 instance.
    
 
 
    Variables can be sliced similar to numpy arrays, but there are some differences.  See
@@ -876,10 +880,10 @@ 
    Attributes in a netCDF file
    
 
 
    There are two types of attributes in a netCDF file, global and variable.
 Global attributes provide information about a group, or the entire
-dataset, as a whole. Variable attributes provide information about
+dataset, as a whole. Variable attributes provide information about
 one of the variables in a group. Global attributes are set by assigning
-values to Dataset or Group instance variables. Variable
-attributes are set by assigning values to Variable instances
+values to Dataset or Group instance variables. Variable
+attributes are set by assigning values to Variable instances
 variables. Attributes can be strings, numbers or sequences. Returning to
 our example,
    
 
@@ -895,8 +899,8 @@ 
    Attributes in a netCDF file
    
 >>> times.calendar = "gregorian"
 
    
 
-
    The Dataset.ncattrs">Dataset.ncattrs method of a Dataset, Group or
-Variable instance can be used to retrieve the names of all the netCDF
+
    The Dataset.ncattrs method of a Dataset, Group or
+Variable instance can be used to retrieve the names of all the netCDF
 attributes. This method is provided as a convenience, since using the
 built-in dir Python function will return a bunch of private methods
 and attributes that cannot (or should not) be modified by the user.
    
@@ -908,7 +912,7 @@ 
    Attributes in a netCDF file
    
 Global attr source = netCDF4 python module tutorial
 
    
 
-
    The __dict__ attribute of a Dataset, Group or Variable
+
    The __dict__ attribute of a Dataset, Group or Variable
 instance provides all the netCDF attribute name/value pairs in a python
 dictionary:
    
 
@@ -916,18 +920,18 @@ 
    Attributes in a netCDF file
    
 {'description': 'bogus example script', 'history': 'Created Mon Jul  8 14:19:41 2019', 'source': 'netCDF4 python module tutorial'}
 
    
 
-
    Attributes can be deleted from a netCDF Dataset, Group or
-Variable using the python del statement (i.e. del grp.foo
+
    Attributes can be deleted from a netCDF Dataset, Group or
+Variable using the python del statement (i.e. del grp.foo
 removes the attribute foo the the group grp).
    
 
 
    Writing data to and retrieving data from a netCDF variable
    
 
-
    Now that you have a netCDF Variable instance, how do you put data
+
    Now that you have a netCDF Variable instance, how do you put data
 into it? You can just treat it like an array and assign data to a slice.
    
 
-
    >>> import numpy
->>> lats =  numpy.arange(-90,91,2.5)
->>> lons =  numpy.arange(-180,180,2.5)
+
    >>> import numpy as np
+>>> lats =  np.arange(-90,91,2.5)
+>>> lons =  np.arange(-180,180,2.5)
 >>> latitudes[:] = lats
 >>> longitudes[:] = lons
 >>> print("latitudes =\n{}".format(latitudes[:]))
@@ -941,7 +945,7 @@ 
    Writing data
   90. ]
 
    
 
-
    Unlike NumPy's array objects, netCDF Variable
+
    Unlike NumPy's array objects, netCDF Variable
 objects with unlimited dimensions will grow along those dimensions if you
 assign data outside the currently defined range of indices.
    
 
@@ -1013,12 +1017,12 @@ 
    Writing data
 
 
    By default, netcdf4-python returns numpy masked arrays with values equal to the
 missing_value or _FillValue variable attributes masked.  The
-Dataset.set_auto_mask">Dataset.set_auto_mask  Dataset and Variable methods
+Dataset.set_auto_mask Dataset and Variable methods
 can be used to disable this feature so that
 numpy arrays are always returned, with the missing values included. Prior to
 version 1.4.0 the default behavior was to only return masked arrays when the
 requested slice contained missing values.  This behavior can be recovered
-using the Dataset.set_always_mask">Dataset.set_always_mask method. If a masked array is
+using the Dataset.set_always_mask method. If a masked array is
 written to a netCDF variable, the masked elements are filled with the
 value specified by the missing_value attribute.  If the variable has
 no missing_value, the _FillValue is used instead.
    
@@ -1051,11 +1055,11 @@ 
    Dealing with time coordinates
    
  real_datetime(2001, 3, 3, 0, 0)]
 
    
 
-
    num2date converts numeric values of time in the specified units
-and calendar to datetime objects, and date2num does the reverse.
+
    num2date converts numeric values of time in the specified units
+and calendar to datetime objects, and date2num does the reverse.
 All the calendars currently defined in the
 CF metadata convention are supported.
-A function called date2index is also provided which returns the indices
+A function called date2index is also provided which returns the indices
 of a netCDF time variable corresponding to a sequence of datetime instances.
    
 
 
    Reading data from a multi-file netCDF dataset
    
@@ -1063,7 +1067,7 @@ 
    Reading data from a multi
 
    If you want to read data from a variable that spans multiple netCDF files,
 you can use the MFDataset class to read the data as if it were
 contained in a single file. Instead of using a single filename to create
-a Dataset instance, create a MFDataset instance with either a list
+a Dataset instance, create a MFDataset instance with either a list
 of filenames, or a string with a wildcard (which is then converted to
 a sorted list of files using the python glob module).
 Variables in the list of files that share the same unlimited
@@ -1078,7 +1082,7 @@ 
    Reading data from a multi
 ...     with Dataset("mftest%s.nc" % nf, "w", format="NETCDF4_CLASSIC") as f:
 ...         _ = f.createDimension("x",None)
 ...         x = f.createVariable("x","i",("x",))
-...         x[0:10] = numpy.arange(nf*10,10*(nf+1))
+...         x[0:10] = np.arange(nf*10,10*(nf+1))
 
    
 
 
    Now read all the files back in at once with MFDataset
    
@@ -1098,10 +1102,10 @@ 
    Reading data from a multi
 
 
    Efficient compression of netCDF variables
    
 
-
    Data stored in netCDF 4 Variable objects can be compressed and
+
    Data stored in netCDF 4 Variable objects can be compressed and
 decompressed on the fly. The parameters for the compression are
 determined by the zlib, complevel and shuffle keyword arguments
-to the Dataset.createVariable">Dataset.createVariable method. To turn on
+to the Dataset.createVariable method. To turn on
 compression, set zlib=True.  The complevel keyword regulates the
 speed and efficiency of the compression (1 being fastest, but lowest
 compression ratio, 9 being slowest but best compression ratio). The
@@ -1110,12 +1114,12 @@ 
    Efficient compression of netC
 compression by reordering the bytes.  The shuffle filter can
 significantly improve compression ratios, and is on by default.  Setting
 fletcher32 keyword argument to
-Dataset.createVariable">Dataset.createVariable to True (it's False by
+Dataset.createVariable to True (it's False by
 default) enables the Fletcher32 checksum algorithm for error detection.
 It's also possible to set the HDF5 chunking parameters and endian-ness
 of the binary data stored in the HDF5 file with the chunksizes
 and endian keyword arguments to
-Dataset.createVariable">Dataset.createVariable.  These keyword arguments only
+Dataset.createVariable.  These keyword arguments only
 are relevant for NETCDF4 and NETCDF4_CLASSIC files (where the
 underlying file format is HDF5) and are silently ignored if the file
 format is NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
    
@@ -1124,7 +1128,7 @@ 
    Efficient compression of netC
 example, it is temperature data that was measured with a precision of
 0.1 degrees), you can dramatically improve zlib compression by
 quantizing (or truncating) the data using the least_significant_digit
-keyword argument to Dataset.createVariable">Dataset.createVariable. The least
+keyword argument to Dataset.createVariable. The least
 significant digit is the power of ten of the smallest decimal place in
 the data that is a reliable value. For example if the data has a
 precision of 0.1, then setting least_significant_digit=1 will cause
@@ -1164,21 +1168,21 @@ 
    Beyond ho
 information for a point by reading one variable, instead of reading
 different parameters from different variables.  Compound data types
 are created from the corresponding numpy data type using the
-Dataset.createCompoundType">Dataset.createCompoundType method of a Dataset or Group instance.
+Dataset.createCompoundType method of a Dataset or Group instance.
 Since there is no native complex data type in netcdf, compound types are handy
 for storing numpy complex arrays.  Here's an example:
    
 
 
    >>> f = Dataset("complex.nc","w")
 >>> size = 3 # length of 1-d complex array
 >>> # create sample complex data.
->>> datac = numpy.exp(1j*(1.+numpy.linspace(0, numpy.pi, size)))
+>>> datac = np.exp(1j*(1.+np.linspace(0, np.pi, size)))
 >>> # create complex128 compound data type.
->>> complex128 = numpy.dtype([("real",numpy.float64),("imag",numpy.float64)])
+>>> complex128 = np.dtype([("real",np.float64),("imag",np.float64)])
 >>> complex128_t = f.createCompoundType(complex128,"complex128")
 >>> # create a variable with this data type, write some data to it.
 >>> x_dim = f.createDimension("x_dim",None)
 >>> v = f.createVariable("cmplx_var",complex128_t,"x_dim")
->>> data = numpy.empty(size,complex128) # numpy structured array
+>>> data = np.empty(size,complex128) # numpy structured array
 >>> data["real"] = datac.real; data["imag"] = datac.imag
 >>> v[:] = data # write numpy structured array to netcdf compound var
 >>> # close and reopen the file, check the contents.
@@ -1186,7 +1190,7 @@ 
    Beyond ho
 >>> v = f.variables["cmplx_var"]
 >>> datain = v[:] # read in all the data into a numpy structured array
 >>> # create an empty numpy complex array
->>> datac2 = numpy.empty(datain.shape,numpy.complex128)
+>>> datac2 = np.empty(datain.shape,np.complex128)
 >>> # .. fill it with contents of structured array.
 >>> datac2.real = datain["real"]; datac2.imag = datain["imag"]
 >>> print('{}: {}'.format(datac.dtype, datac)) # original data
@@ -1200,7 +1204,7 @@ 
    Beyond ho
 ones first. All possible numpy structured arrays cannot be
 represented as Compound variables - an error message will be
 raise if you try to create one that is not supported.
-All of the compound types defined for a Dataset or Group are stored
+All of the compound types defined for a Dataset or Group are stored
 in a Python dictionary, just like variables and dimensions. As always, printing
 objects gives useful summary information in an interactive session:
    
 
@@ -1226,11 +1230,11 @@ 
    Variable-length (vlen) data types
    
 
 
    NetCDF 4 has support for variable-length or "ragged" arrays.  These are arrays
 of variable length sequences having the same type. To create a variable-length
-data type, use the Dataset.createVLType">Dataset.createVLType method
-method of a Dataset or Group instance.
    
+data type, use the Dataset.createVLType method
+method of a Dataset or Group instance.
    
 
 
    >>> f = Dataset("tst_vlen.nc","w")
->>> vlen_t = f.createVLType(numpy.int32, "phony_vlen")
+>>> vlen_t = f.createVLType(np.int32, "phony_vlen")
 
    
 
 
    The numpy datatype of the variable-length sequences and the name of the
@@ -1254,10 +1258,10 @@ 
    Variable-length (vlen) data types
    
 
 
    >>> import random
 >>> random.seed(54321)
->>> data = numpy.empty(len(y)*len(x),object)
+>>> data = np.empty(len(y)*len(x),object)
 >>> for n in range(len(y)*len(x)):
-...     data[n] = numpy.arange(random.randint(1,10),dtype="int32")+1
->>> data = numpy.reshape(data,(len(y),len(x)))
+...     data[n] = np.arange(random.randint(1,10),dtype="int32")+1
+>>> data = np.reshape(data,(len(y),len(x)))
 >>> vlvar[:] = data
 >>> print("vlen variable =\n{}".format(vlvar[:]))
 vlen variable =
@@ -1290,7 +1294,7 @@ 
    Variable-length (vlen) data types
    
 variables,  For vlen strings, you don't need to create a vlen data type.
 Instead, simply use the python str builtin (or a numpy string datatype
 with fixed length greater than 1) when calling the
-Dataset.createVariable">Dataset.createVariable method.
    
+Dataset.createVariable method.
    
 
 
    >>> z = f.createDimension("z",10)
 >>> strvar = f.createVariable("strvar", str, "z")
@@ -1301,7 +1305,7 @@ 
    Variable-length (vlen) data types
    
 array is assigned to the vlen string variable.
    
 
 
    >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
->>> data = numpy.empty(10,"O")
+>>> data = np.empty(10,"O")
 >>> for n in range(10):
 ...     stringlen = random.randint(2,12)
 ...     data[n] = "".join([random.choice(chars) for i in range(stringlen)])
@@ -1337,7 +1341,7 @@ 
    Enum data type
    
 
    Here's an example of using an Enum type to hold cloud type data.
 The base integer data type and a python dictionary describing the allowed
 values and their names are used to define an Enum data type using
-Dataset.createEnumType">Dataset.createEnumType.
    
+Dataset.createEnumType.
    
 
 
    >>> nc = Dataset('clouds.nc','w')
 >>> # python dict with allowed values and their names.
@@ -1346,7 +1350,7 @@ 
    Enum data type
    
 ... 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5,
 ... 'Cumulonimbus': 1, 'Stratocumulus': 3}
 >>> # create the Enum type called 'cloud_t'.
->>> cloud_type = nc.createEnumType(numpy.uint8,'cloud_t',enum_dict)
+>>> cloud_type = nc.createEnumType(np.uint8,'cloud_t',enum_dict)
 >>> print(cloud_type)
 <class 'netCDF4._netCDF4.EnumType'>: name = 'cloud_t', numpy dtype = uint8, fields/values ={'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, 'Stratocumulus': 3}
 
    
@@ -1415,7 +1419,7 @@ 
    Parallel IO
    
 written to a different variable index on each task
    
 
 
    >>> d = nc.createDimension('dim',4)
->>> v = nc.createVariable('var', np.int, 'dim')
+>>> v = nc.createVariable('var', np.int64, 'dim')
 >>> v[rank] = rank
 >>> nc.close()
 
@@ -1436,8 +1440,8 @@ 
    Parallel IO
    
 depend on or be affected by other processes. Collective IO is a way of doing
 IO defined in the MPI-IO standard; unlike independent IO, all processes must
 participate in doing IO. To toggle back and forth between
-the two types of IO, use the Variable.set_collective">Variable.set_collective
-Variable method. All metadata
+the two types of IO, use the Variable.set_collective
+Variable method. All metadata
 operations (such as creation of groups, types, variables, dimensions, or attributes)
 are collective.  There are a couple of important limitations of parallel IO:
    
 
@@ -1482,7 +1486,7 @@ 
    Dealing with strings
    
 >>> _ = nc.createDimension('nchars',3)
 >>> _ = nc.createDimension('nstrings',None)
 >>> v = nc.createVariable('strings','S1',('nstrings','nchars'))
->>> datain = numpy.array(['foo','bar'],dtype='S3')
+>>> datain = np.array(['foo','bar'],dtype='S3')
 >>> v[:] = stringtochar(datain) # manual conversion to char array
 >>> print(v[:]) # data returned as char array
 [[b'f' b'o' b'o']
@@ -1496,7 +1500,7 @@ 
    Dealing with strings
    
 
 
    Even if the _Encoding attribute is set, the automatic conversion of char
 arrays to/from string arrays can be disabled with
-Variable.set_auto_chartostring">Variable.set_auto_chartostring.
    
+Variable.set_auto_chartostring.
    
 
 
    A similar situation is often encountered with numpy structured arrays with subdtypes
 containing fixed-wdith byte strings (dtype=S#). Since there is no native fixed-length string
@@ -1511,12 +1515,12 @@ 
    Dealing with strings
    
 Here's an example:
    
 
 
    >>> nc = Dataset('compoundstring_example.nc','w')
->>> dtype = numpy.dtype([('observation', 'f4'),
+>>> dtype = np.dtype([('observation', 'f4'),
 ...                      ('station_name','S10')])
 >>> station_data_t = nc.createCompoundType(dtype,'station_data')
 >>> _ = nc.createDimension('station',None)
 >>> statdat = nc.createVariable('station_obs', station_data_t, ('station',))
->>> data = numpy.empty(2,dtype)
+>>> data = np.empty(2,dtype)
 >>> data['observation'][:] = (123.,3.14)
 >>> data['station_name'][:] = ('Boulder','New York')
 >>> print(statdat.dtype) # strings actually stored as character arrays
@@ -1559,8 +1563,8 @@ 
    In-memory (diskless) Datasets
    
 >>> # and persist the file to disk when it is closed.
 >>> nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
 >>> d = nc.createDimension('x',None)
->>> v = nc.createVariable('v',numpy.int32,'x')
->>> v[0:5] = numpy.arange(5)
+>>> v = nc.createVariable('v',np.int32,'x')
+>>> v[0:5] = np.arange(5)
 >>> print(nc)
 <class 'netCDF4._netCDF4.Dataset'>
 root group (NETCDF4 data model, file format HDF5):
@@ -1593,8 +1597,8 @@ 
    In-memory (diskless) Datasets
    
 >>> # (ignored for NETCDF4/HDF5 files).
 >>> nc = Dataset('inmemory.nc', mode='w',memory=1028)
 >>> d = nc.createDimension('x',None)
->>> v = nc.createVariable('v',numpy.int32,'x')
->>> v[0:5] = numpy.arange(5)
+>>> v = nc.createVariable('v',np.int32,'x')
+>>> v[0:5] = np.arange(5)
 >>> nc_buf = nc.close() # close returns memoryview
 >>> print(type(nc_buf))
 <class 'memoryview'>
@@ -1617,7 +1621,7 @@ 
    In-memory (diskless) Datasets
    
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
    
 
-
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
+
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
 
 
    copyright: 2008 by Jeffrey Whitaker.
    
 
@@ -1628,7 +1632,24 @@ 
    In-memory (diskless) Datasets
    
 
    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
    
 
    
 
-                
+                        
    
+            View Source
+            
    # init for netCDF4. package
+# Docstring comes from extension module _netCDF4.
+from ._netCDF4 import *
+# Need explicit imports for names beginning with underscores
+from ._netCDF4 import __doc__
+from ._netCDF4 import (__version__, __netcdf4libversion__, __hdf5libversion__,
+                       __has_rename_grp__, __has_nc_inq_path__,
+                       __has_nc_inq_format_extended__, __has_nc_open_mem__,
+                       __has_nc_create_mem__, __has_cdf5_format__,
+                       __has_parallel4_support__, __has_pnetcdf_support__)
+__all__ =\
+['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
+
    
+
+        
    
+
             
                 
    
                                 
    
@@ -1640,45 +1661,45 @@ 
    In-memory (diskless) Datasets
    
     
    
 
         
-            
    A netCDF Dataset is a collection of dimensions, groups, variables and
+            
    A netCDF Dataset is a collection of dimensions, groups, variables and
 attributes. Together they describe the meaning of data and relations among
-data fields stored in a netCDF file. See Dataset.__init__">Dataset.__init__ for more
+data fields stored in a netCDF file. See Dataset.__init__ for more
 details.
    
 
 
    A list of attribute names corresponding to global netCDF attributes
-defined for the Dataset can be obtained with the
-Dataset.ncattrs">Dataset.ncattrs method.
+defined for the Dataset can be obtained with the
+Dataset.ncattrs method.
 These attributes can be created by assigning to an attribute of the
-Dataset instance. A dictionary containing all the netCDF attribute
+Dataset instance. A dictionary containing all the netCDF attribute
 name/value pairs is provided by the __dict__ attribute of a
-Dataset instance.
    
+Dataset instance.
    
 
 
    The following class variables are read-only and should not be
 modified by the user.
    
 
 
    dimensions: The dimensions dictionary maps the names of
-dimensions defined for the Group or Dataset to instances of the
-Dimension class.
    
+dimensions defined for the Group or Dataset to instances of the
+Dimension class.
    
 
 
    variables: The variables dictionary maps the names of variables
-defined for this Dataset or Group to instances of the
-Variable class.
    
+defined for this Dataset or Group to instances of the
+Variable class.
    
 
 
    groups: The groups dictionary maps the names of groups created for
-this Dataset or Group to instances of the Group class (the
-Dataset class is simply a special case of the Group class which
+this Dataset or Group to instances of the Group class (the
+Dataset class is simply a special case of the Group class which
 describes the root group in the netCDF4 file).
    
 
 
    cmptypes: The cmptypes dictionary maps the names of
-compound types defined for the Group or Dataset to instances of the
-CompoundType class.
    
+compound types defined for the Group or Dataset to instances of the
+CompoundType class.
    
 
 
    vltypes: The vltypes dictionary maps the names of
-variable-length types defined for the Group or Dataset to instances
+variable-length types defined for the Group or Dataset to instances
 of the VLType class.
    
 
 
    enumtypes: The enumtypes dictionary maps the names of
-Enum types defined for the Group or Dataset to instances
+Enum types defined for the Group or Dataset to instances
 of the EnumType class.
    
 
 
    data_model: data_model describes the netCDF
@@ -1694,12 +1715,12 @@ 
    In-memory (diskless) Datasets
    
 UNDEFINED.
    
 
 
    parent: parent is a reference to the parent
-Group instance. None for the root group or Dataset
+Group instance. None for the root group or Dataset
 instance.
    
 
-
    path: path shows the location of the Group in
-the Dataset in a unix directory format (the names of groups in the
-hierarchy separated by backslashes). A Dataset instance is the root
+
    path: path shows the location of the Group in
+the Dataset in a unix directory format (the names of groups in the
+hierarchy separated by backslashes). A Dataset instance is the root
 group, so the path is simply '/'.
    
 
 
    keepweakref: If True, child Dimension and Variables objects only keep weak
@@ -1721,7 +1742,7 @@ 
    In-memory (diskless) Datasets
    
 persist=False, keepweakref=False, memory=None, encoding=None,
 parallel=False, comm=None, info=None, format='NETCDF4')
    
 
-
    Dataset constructor.
    
+
    Dataset constructor.
    
 
 
    filename: Name of netCDF file to hold dataset. Can also
 be a python 3 pathlib instance or the URL of an OpenDAP dataset.  When memory is
@@ -1873,7 +1894,7 @@ 
    In-memory (diskless) Datasets
    
         
             
    sync(self)
    
 
-
    Writes all buffered data in the Dataset to the disk file.
    
+
    Writes all buffered data in the Dataset to the disk file.
    
 
    
 
 
@@ -1889,7 +1910,7 @@ 
    In-memory (diskless) Datasets
    
         
             
    set_fill_on(self)
    
 
-
    Sets the fill mode for a Dataset open for writing to on.
    
+
    Sets the fill mode for a Dataset open for writing to on.
    
 
 
    This causes data to be pre-filled with fill values. The fill values can be
 controlled by the variable's _Fill_Value attribute, but is usually
@@ -1913,7 +1934,7 @@ 
    In-memory (diskless) Datasets
    
         
             
    set_fill_off(self)
    
 
-
    Sets the fill mode for a Dataset open for writing to off.
    
+
    Sets the fill mode for a Dataset open for writing to off.
    
 
 
    This will prevent the data from being pre-filled with fill values, which
 may result in some performance improvements. However, you must then make
@@ -1937,11 +1958,11 @@ 
    In-memory (diskless) Datasets
    
 
 
    size must be a positive integer or None, which stands for
 "unlimited" (default is None). Specifying a size of 0 also
-results in an unlimited dimension. The return value is the Dimension
+results in an unlimited dimension. The return value is the Dimension
 class instance describing the new dimension.  To determine the current
-maximum size of the dimension, use the len function on the Dimension
+maximum size of the dimension, use the len function on the Dimension
 instance. To determine if a dimension is 'unlimited', use the
-Dimension.isunlimited">Dimension.isunlimited method of the Dimension instance.
    
+Dimension.isunlimited">Dimension.isunlimited method of the Dimension instance.
    
 
    
 
 
@@ -1957,7 +1978,7 @@ 
    In-memory (diskless) Datasets
    
         
             
    renameDimension(self, oldname, newname)
    
 
-
    rename a Dimension named oldname to newname.
    
+
    rename a Dimension named oldname to newname.
    
 
    
 
 
@@ -1981,7 +2002,7 @@ 
    In-memory (diskless) Datasets
    
 are homogeneous numeric data types), then the 'inner' compound types must be
 created first.
    
 
-
    The return value is the CompoundType class instance describing the new
+
    The return value is the CompoundType class instance describing the new
 datatype.
    
 
    
 
@@ -2057,7 +2078,7 @@ 
    In-memory (diskless) Datasets
    
 (NC_BYTE), 'u1' (NC_UBYTE), 'i2' or 'h' or 's' (NC_SHORT), 'u2'
 (NC_USHORT), 'i4' or 'i' or 'l' (NC_INT), 'u4' (NC_UINT), 'i8' (NC_INT64),
 'u8' (NC_UINT64), 'f4' or 'f' (NC_FLOAT), 'f8' or 'd' (NC_DOUBLE)    .
-datatype can also be a CompoundType instance
+datatype can also be a CompoundType instance
 (for a structured, or compound array), a VLType instance
 (for a variable-length array), or the python str builtin
 (for a variable-length string array). Numpy string and unicode datatypes with
@@ -2067,7 +2088,7 @@ 
    In-memory (diskless) Datasets
    
 the corresponding data type.
    
 
 
    dimensions must be a tuple containing dimension names (strings) that
-have been defined previously using Dataset.createDimension">Dataset.createDimension. The default value
+have been defined previously using Dataset.createDimension. The default value
 is an empty tuple, which means the variable is a scalar.
    
 
 
    If the optional keyword zlib is True, the data will be compressed in
@@ -2134,17 +2155,17 @@ 
    In-memory (diskless) Datasets
    
 method to change it the next time the Dataset is opened.
 Warning - messing with this parameter can seriously degrade performance.
    
 
-
    The return value is the Variable class instance describing the new
+
    The return value is the Variable class instance describing the new
 variable.
    
 
 
    A list of names corresponding to netCDF variable attributes can be
-obtained with the Variable method Variable.ncattrs">Variable.ncattrs. A dictionary
+obtained with the Variable method Variable.ncattrs. A dictionary
 containing all the netCDF attribute name/value pairs is provided by
-the __dict__ attribute of a Variable instance.
    
+the __dict__ attribute of a Variable instance.
    
 
-
    Variable instances behave much like array objects. Data can be
+
    Variable instances behave much like array objects. Data can be
 assigned to or retrieved from a variable with indexing and slicing
-operations on the Variable instance. A Variable instance has six
+operations on the Variable instance. A Variable instance has six
 Dataset standard attributes: dimensions, dtype, shape, ndim, name and
 least_significant_digit. Application programs should never modify
 these attributes. The dimensions attribute is a tuple containing the
@@ -2155,7 +2176,7 @@ 
    In-memory (diskless) Datasets
    
 string containing the name of the Variable instance.
 The least_significant_digit
 attributes describes the power of ten of the smallest decimal place in
-the data the contains a reliable value.  assigned to the Variable
+the data the contains a reliable value.  assigned to the Variable
 instance. If None, the data is not truncated. The ndim attribute
 is the number of variable dimensions.
    
 
    
@@ -2173,7 +2194,7 @@ 
    In-memory (diskless) Datasets
    
         
             
    renameVariable(self, oldname, newname)
    
 
-
    rename a Variable named oldname to newname
    
+
    rename a Variable named oldname to newname
    
 
    
 
 
@@ -2189,7 +2210,7 @@ 
    In-memory (diskless) Datasets
    
         
             
    createGroup(self, groupname)
    
 
-
    Creates a new Group with the given groupname.
    
+
    Creates a new Group with the given groupname.
    
 
 
    If groupname is specified as a path, using forward slashes as in unix to
 separate components, then intermediate groups will be created as necessary
@@ -2199,7 +2220,7 @@ 
    In-memory (diskless) Datasets
    
 If the specified path describes a group that already exists, no error is
 raised.
    
 
-
    The return value is a Group class instance.
    
+
    The return value is a Group class instance.
    
 
    
 
 
@@ -2215,7 +2236,7 @@ 
    In-memory (diskless) Datasets
    
         
             
    ncattrs(self)
    
 
-
    return netCDF global attribute names for this Dataset or Group in a list.
    
+
    return netCDF global attribute names for this Dataset or Group in a list.
    
 
    
 
 
@@ -2325,7 +2346,7 @@ 
    In-memory (diskless) Datasets
    
         
             
    renameAttribute(self, oldname, newname)
    
 
-
    rename a Dataset or Group attribute named oldname to newname.
    
+
    rename a Dataset or Group attribute named oldname to newname.
    
 
    
 
 
@@ -2341,7 +2362,7 @@ 
    In-memory (diskless) Datasets
    
         
             
    renameGroup(self, oldname, newname)
    
 
-
    rename a Group named oldname to newname (requires netcdf >= 4.3.1).
    
+
    rename a Group named oldname to newname (requires netcdf >= 4.3.1).
    
 
    
 
 
@@ -2357,8 +2378,8 @@ 
    In-memory (diskless) Datasets
    
         
             
    set_auto_chartostring(self, True_or_False)
    
 
-
    Call Variable.set_auto_chartostring">Variable.set_auto_chartostring for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
    
+
    Call Variable.set_auto_chartostring for all variables contained in this Dataset or
+Group, as well as for all variables in all its subgroups.
    
 
 
    True_or_False: Boolean determining if automatic conversion of
 all character arrays <--> string arrays should be performed for
@@ -2382,8 +2403,8 @@ 
    In-memory (diskless) Datasets
    
         
             
    set_auto_maskandscale(self, True_or_False)
    
 
-
    Call Variable.set_auto_maskandscale">Variable.set_auto_maskandscale for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
    
+
    Call Variable.set_auto_maskandscale for all variables contained in this Dataset or
+Group, as well as for all variables in all its subgroups.
    
 
 
    True_or_False: Boolean determining if automatic conversion to masked arrays
 and variable scaling shall be applied for all variables.
    
@@ -2405,8 +2426,8 @@ 
    In-memory (diskless) Datasets
    
         
             
    set_auto_mask(self, True_or_False)
    
 
-
    Call Variable.set_auto_mask">Variable.set_auto_mask for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
    
+
    Call Variable.set_auto_mask for all variables contained in this Dataset or
+Group, as well as for all variables in all its subgroups.
    
 
 
    True_or_False: Boolean determining if automatic conversion to masked arrays
 shall be applied for all variables.
    
@@ -2428,8 +2449,8 @@ 
    In-memory (diskless) Datasets
    
         
             
    set_auto_scale(self, True_or_False)
    
 
-
    Call Variable.set_auto_scale">Variable.set_auto_scale for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
    
+
    Call Variable.set_auto_scale for all variables contained in this Dataset or
+Group, as well as for all variables in all its subgroups.
    
 
 
    True_or_False: Boolean determining if automatic variable scaling
 shall be applied for all variables.
    
@@ -2451,8 +2472,8 @@ 
    In-memory (diskless) Datasets
    
         
             
    set_always_mask(self, True_or_False)
    
 
-
    Call Variable.set_always_mask">Variable.set_always_mask for all variables contained in
-this Dataset or Group, as well as for all
+
    Call Variable.set_always_mask for all variables contained in
+this Dataset or Group, as well as for all
 variables in all its subgroups.
    
 
 
    True_or_False: Boolean determining if automatic conversion of
@@ -2479,8 +2500,8 @@ 
    In-memory (diskless) Datasets
    
         
             
    set_ncstring_attrs(self, True_or_False)
    
 
-
    Call Variable.set_ncstring_attrs">Variable.set_ncstring_attrs for all variables contained in
-this Dataset or Group, as well as for all its
+
    Call Variable.set_ncstring_attrs for all variables contained in
+this Dataset or Group, as well as for all its
 subgroups and their variables.
    
 
 
    True_or_False: Boolean determining if all string attributes are
@@ -2587,7 +2608,7 @@ 
    In-memory (diskless) Datasets
    
                             
    
                                             
    #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.Dataset' objects>
+        name = <attribute 'name' of 'netCDF4._netCDF4.Dataset' objects>
     
    
 
     
@@ -2596,7 +2617,7 @@ 
    In-memory (diskless) Datasets
    
                             
    
                                             
    #  
 
-        groups = <attribute 'groups' of 'netCDF4._netCDF4.Dataset' objects>
+        groups = <attribute 'groups' of 'netCDF4._netCDF4.Dataset' objects>
     
    
 
     
@@ -2605,7 +2626,7 @@ 
    In-memory (diskless) Datasets
    
                             
    
                                             
    #  
 
-        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Dataset' objects>
+        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Dataset' objects>
     
    
 
     
@@ -2614,7 +2635,7 @@ 
    In-memory (diskless) Datasets
    
                             
    
                                             
    #  
 
-        variables = <attribute 'variables' of 'netCDF4._netCDF4.Dataset' objects>
+        variables = <attribute 'variables' of 'netCDF4._netCDF4.Dataset' objects>
     
    
 
     
@@ -2623,7 +2644,7 @@ 
    In-memory (diskless) Datasets
    
                             
    
                                             
    #  
 
-        disk_format = <attribute 'disk_format' of 'netCDF4._netCDF4.Dataset' objects>
+        disk_format = <attribute 'disk_format' of 'netCDF4._netCDF4.Dataset' objects>
     
    
 
     
@@ -2632,7 +2653,7 @@ 
    In-memory (diskless) Datasets
    
                             
    
                                             
    #  
 
-        path = <attribute 'path' of 'netCDF4._netCDF4.Dataset' objects>
+        path = <attribute 'path' of 'netCDF4._netCDF4.Dataset' objects>
     
    
 
     
@@ -2641,7 +2662,7 @@ 
    In-memory (diskless) Datasets
    
                             
    
                                             
    #  
 
-        parent = <attribute 'parent' of 'netCDF4._netCDF4.Dataset' objects>
+        parent = <attribute 'parent' of 'netCDF4._netCDF4.Dataset' objects>
     
    
 
     
@@ -2650,7 +2671,7 @@ 
    In-memory (diskless) Datasets
    
                             
    
                                             
    #  
 
-        file_format = <attribute 'file_format' of 'netCDF4._netCDF4.Dataset' objects>
+        file_format = <attribute 'file_format' of 'netCDF4._netCDF4.Dataset' objects>
     
    
 
     
@@ -2659,7 +2680,7 @@ 
    In-memory (diskless) Datasets
    
                             
    
                                             
    #  
 
-        data_model = <attribute 'data_model' of 'netCDF4._netCDF4.Dataset' objects>
+        data_model = <attribute 'data_model' of 'netCDF4._netCDF4.Dataset' objects>
     
    
 
     
@@ -2668,7 +2689,7 @@ 
    In-memory (diskless) Datasets
    
                             
    
                                             
    #  
 
-        cmptypes = <attribute 'cmptypes' of 'netCDF4._netCDF4.Dataset' objects>
+        cmptypes = <attribute 'cmptypes' of 'netCDF4._netCDF4.Dataset' objects>
     
    
 
     
@@ -2677,7 +2698,7 @@ 
    In-memory (diskless) Datasets
    
                             
    
                                             
    #  
 
-        vltypes = <attribute 'vltypes' of 'netCDF4._netCDF4.Dataset' objects>
+        vltypes = <attribute 'vltypes' of 'netCDF4._netCDF4.Dataset' objects>
     
    
 
     
@@ -2686,7 +2707,7 @@ 
    In-memory (diskless) Datasets
    
                             
    
                                             
    #  
 
-        enumtypes = <attribute 'enumtypes' of 'netCDF4._netCDF4.Dataset' objects>
+        enumtypes = <attribute 'enumtypes' of 'netCDF4._netCDF4.Dataset' objects>
     
    
 
     
@@ -2695,354 +2716,134 @@ 
    In-memory (diskless) Datasets
    
                             
    
                                             
    #  
 
-        keepweakref = <attribute 'keepweakref' of 'netCDF4._netCDF4.Dataset' objects>
+        keepweakref = <attribute 'keepweakref' of 'netCDF4._netCDF4.Dataset' objects>
     
    
 
     
 
                             
    
                 
    
-                
    
+                
    
                                 
    
-        #  
+        #  
 
         
         class
-        Group(Dataset):
+        Variable:
     
    
 
         
-            
    Groups define a hierarchical namespace within a netCDF file. They are
-analogous to directories in a unix filesystem. Each Group behaves like
-a Dataset within a Dataset, and can contain it's own variables,
-dimensions and attributes (and other Groups). See Group.__init__">Group.__init__
-for more details.
    
-
-
    Group inherits from Dataset, so all the
-Dataset class methods and variables are available
-to a Group instance (except the close method).
    
+            
    A netCDF Variable is used to read and write netCDF data.  They are
+analogous to numpy array objects. See Variable.__init__ for more
+details.
    
 
-
    Additional read-only class variables:
    
+
    A list of attribute names corresponding to netCDF attributes defined for
+the variable can be obtained with the Variable.ncattrs method. These
+attributes can be created by assigning to an attribute of the
+Variable instance. A dictionary containing all the netCDF attribute
+name/value pairs is provided by the __dict__ attribute of a
+Variable instance.
    
 
-
    name: String describing the group name.
    
-
    
+
    The following class variables are read-only:
    
 
+
    dimensions: A tuple containing the names of the
+dimensions associated with this variable.
    
 
-                            
    
-                                        
    #  
+
    dtype: A numpy dtype object describing the
+variable's data type.
    
 
-        
-            Group(unknown)    
    
+
    ndim: The number of variable dimensions.
    
 
-        
-            
    __init__(self, parent, name)
-Group constructor.
    
+
    shape: A tuple with the current shape (length of all dimensions).
    
 
-
    parent: Group instance for the parent group.  If being created
-in the root group, use a Dataset instance.
    
+
    scale: If True, scale_factor and add_offset are
+applied, and signed integer data is automatically converted to
+unsigned integer data if the _Unsigned attribute is set.
+Default is True, can be reset using Variable.set_auto_scale and
+Variable.set_auto_maskandscale methods.
    
 
-
    name: - Name of the group.
    
+
    mask: If True, data is automatically converted to/from masked
+arrays when missing values or fill values are present. Default is True, can be
+reset using Variable.set_auto_mask and Variable.set_auto_maskandscale
+methods.
    
 
-
    Note: Group instances should be created using the
-Dataset.createGroup">Dataset.createGroup method of a Dataset instance, or
-another Group instance, not using this class directly.
    
-
    
+
    chartostring: If True, data is automatically converted to/from character
+arrays to string arrays when the _Encoding variable attribute is set.
+Default is True, can be reset using
+Variable.set_auto_chartostring method.
    
 
+
    least_significant_digit: Describes the power of ten of the
+smallest decimal place in the data the contains a reliable value.  Data is
+truncated to this decimal place when it is assigned to the Variable
+instance. If None, the data is not truncated.
    
 
-                            
    
-                            
    
-                                        
    #  
+
    __orthogonal_indexing__: Always True.  Indicates to client code
+that the object supports 'orthogonal indexing', which means that slices
+that are 1d arrays or lists slice along each dimension independently.  This
+behavior is similar to Fortran or Matlab, but different than numpy.
    
 
-        
-            def
-            close(unknown):
-    
    
+
    datatype: numpy data type (for primitive data types) or VLType/CompoundType
+ instance (for compound or vlen data types).
    
 
-        
-            
    close(self)
    
+
    name: String name.
    
 
-
    overrides Dataset close method which does not apply to Group
-instances, raises IOError.
    
+
    size: The number of stored elements.
    
 
    
 
 
-                            
    
-                            
    
-                                
    Inherited Members
    
-                                
    
-                                    
-                                
    
-                            
    
-                
    
-                
    
-                                
    
-        #  
+                            
    
+                                        
    #  
 
         
-        class
-        Dimension:
-    
    
+            Variable(unknown)    
    
 
         
-            
    A netCDF Dimension is used to describe the coordinates of a Variable.
-See Dimension.__init__">Dimension.__init__ for more details.
    
-
-
    The current maximum size of a Dimension instance can be obtained by
-calling the python len function on the Dimension instance. The
-Dimension.isunlimited">Dimension.isunlimited method of a Dimension instance can be used to
-determine if the dimension is unlimited.
    
+            
    __init__(self, group, name, datatype, dimensions=(), zlib=False,
+complevel=4, shuffle=True, fletcher32=False, contiguous=False,
+chunksizes=None, endian='native',
+least_significant_digit=None,fill_value=None,chunk_cache=None)
    
 
-
    Read-only class variables:
    
+
    Variable constructor.
    
 
-
    name: String name, used when creating a Variable with
-Dataset.createVariable">Dataset.createVariable.
    
+
    group: Group or Dataset instance to associate with variable.
    
 
-
    size: Current Dimension size (same as len(d), where d is a
-Dimension instance).
    
-
    
+
    name: Name of the variable.
    
 
+
    datatype: Variable data type. Can be specified by providing a
+numpy dtype object, or a string that describes a numpy dtype object.
+Supported values, corresponding to str attribute of numpy dtype
+objects, include 'f4' (32-bit floating point), 'f8' (64-bit floating
+point), 'i4' (32-bit signed integer), 'i2' (16-bit signed integer),
+'i8' (64-bit signed integer), 'i4' (8-bit signed integer), 'i1'
+(8-bit signed integer), 'u1' (8-bit unsigned integer), 'u2' (16-bit
+unsigned integer), 'u4' (32-bit unsigned integer), 'u8' (64-bit
+unsigned integer), or 'S1' (single-character string).  From
+compatibility with Scientific.IO.NetCDF, the old Numeric single character
+typecodes can also be used ('f' instead of 'f4', 'd' instead of
+'f8', 'h' or 's' instead of 'i2', 'b' or 'B' instead of
+'i1', 'c' instead of 'S1', and 'i' or 'l' instead of
+'i4'). datatype can also be a CompoundType instance
+(for a structured, or compound array), a VLType instance
+(for a variable-length array), or the python str builtin
+(for a variable-length string array). Numpy string and unicode datatypes with
+length greater than one are aliases for str.
    
 
-                            
    
-                                        
    #  
+
    dimensions: a tuple containing the variable's dimension names
+(defined previously with createDimension). Default is an empty tuple
+which means the variable is a scalar (and therefore has no dimensions).
    
 
-        
-            Dimension(unknown)    
    
+
    zlib: if True, data assigned to the Variable
+instance is compressed on disk. Default False.
    
 
-        
-            
    __init__(self, group, name, size=None)
    
+
    complevel: the level of zlib compression to use (1 is the fastest,
+but poorest compression, 9 is the slowest but best compression). Default 4.
+Ignored if zlib=False.
    
 
-
    Dimension constructor.
    
+
    shuffle: if True, the HDF5 shuffle filter is applied
+to improve compression. Default True. Ignored if zlib=False.
    
 
-
    group: Group instance to associate with dimension.
    
-
-
    name: Name of the dimension.
    
-
-
    size: Size of the dimension. None or 0 means unlimited. (Default None).
    
-
-
    Note: Dimension instances should be created using the
-Dataset.createDimension">Dataset.createDimension method of a Group or
-Dataset instance, not using Dimension.__init__">Dimension.__init__ directly.
    
-
    
-
-
-                            
    
-                            
    
-                                        
    #  
-
-        
-            def
-            group(unknown):
-    
    
-
-        
-            
    group(self)
    
-
-
    return the group that this Dimension is a member of.
    
-
    
-
-
-                            
    
-                            
    
-                                        
    #  
-
-        
-            def
-            isunlimited(unknown):
-    
    
-
-        
-            
    isunlimited(self)
    
-
-
    returns True if the Dimension instance is unlimited, False otherwise.
    
-
    
-
-
-                            
    
-                            
    
-                                            
    #  
-
-        name = <attribute 'name' of 'netCDF4._netCDF4.Dimension' objects>
-    
    
-
-    
-
-                            
    
-                            
    
-                                            
    #  
-
-        size = <attribute 'size' of 'netCDF4._netCDF4.Dimension' objects>
-    
    
-
-    
-
-                            
    
-                
    
-                
    
-                                
    
-        #  
-
-        
-        class
-        Variable:
-    
    
-
-        
-            
    A netCDF Variable is used to read and write netCDF data.  They are
-analogous to numpy array objects. See Variable.__init__">Variable.__init__ for more
-details.
    
-
-
    A list of attribute names corresponding to netCDF attributes defined for
-the variable can be obtained with the Variable.ncattrs">Variable.ncattrs method. These
-attributes can be created by assigning to an attribute of the
-Variable instance. A dictionary containing all the netCDF attribute
-name/value pairs is provided by the __dict__ attribute of a
-Variable instance.
    
-
-
    The following class variables are read-only:
    
-
-
    dimensions: A tuple containing the names of the
-dimensions associated with this variable.
    
-
-
    dtype: A numpy dtype object describing the
-variable's data type.
    
-
-
    ndim: The number of variable dimensions.
    
-
-
    shape: A tuple with the current shape (length of all dimensions).
    
-
-
    scale: If True, scale_factor and add_offset are
-applied, and signed integer data is automatically converted to
-unsigned integer data if the _Unsigned attribute is set.
-Default is True, can be reset using Variable.set_auto_scale">Variable.set_auto_scale and
-Variable.set_auto_maskandscale">Variable.set_auto_maskandscale methods.
    
-
-
    mask: If True, data is automatically converted to/from masked
-arrays when missing values or fill values are present. Default is True, can be
-reset using Variable.set_auto_mask">Variable.set_auto_mask and Variable.set_auto_maskandscale">Variable.set_auto_maskandscale
-methods.
    
-
-
    chartostring: If True, data is automatically converted to/from character
-arrays to string arrays when the _Encoding variable attribute is set.
-Default is True, can be reset using
-Variable.set_auto_chartostring">Variable.set_auto_chartostring method.
    
-
-
    least_significant_digit: Describes the power of ten of the
-smallest decimal place in the data the contains a reliable value.  Data is
-truncated to this decimal place when it is assigned to the Variable
-instance. If None, the data is not truncated.
    
-
-
    __orthogonal_indexing__: Always True.  Indicates to client code
-that the object supports 'orthogonal indexing', which means that slices
-that are 1d arrays or lists slice along each dimension independently.  This
-behavior is similar to Fortran or Matlab, but different than numpy.
    
-
-
    datatype: numpy data type (for primitive data types) or VLType/CompoundType
- instance (for compound or vlen data types).
    
-
-
    name: String name.
    
-
-
    size: The number of stored elements.
    
-
    
-
-
-                            
    
-                                        
    #  
-
-        
-            Variable(unknown)    
    
-
-        
-            
    __init__(self, group, name, datatype, dimensions=(), zlib=False,
-complevel=4, shuffle=True, fletcher32=False, contiguous=False,
-chunksizes=None, endian='native',
-least_significant_digit=None,fill_value=None,chunk_cache=None)
    
-
-
    Variable constructor.
    
-
-
    group: Group or Dataset instance to associate with variable.
    
-
-
    name: Name of the variable.
    
-
-
    datatype: Variable data type. Can be specified by providing a
-numpy dtype object, or a string that describes a numpy dtype object.
-Supported values, corresponding to str attribute of numpy dtype
-objects, include 'f4' (32-bit floating point), 'f8' (64-bit floating
-point), 'i4' (32-bit signed integer), 'i2' (16-bit signed integer),
-'i8' (64-bit signed integer), 'i4' (8-bit signed integer), 'i1'
-(8-bit signed integer), 'u1' (8-bit unsigned integer), 'u2' (16-bit
-unsigned integer), 'u4' (32-bit unsigned integer), 'u8' (64-bit
-unsigned integer), or 'S1' (single-character string).  From
-compatibility with Scientific.IO.NetCDF, the old Numeric single character
-typecodes can also be used ('f' instead of 'f4', 'd' instead of
-'f8', 'h' or 's' instead of 'i2', 'b' or 'B' instead of
-'i1', 'c' instead of 'S1', and 'i' or 'l' instead of
-'i4'). datatype can also be a CompoundType instance
-(for a structured, or compound array), a VLType instance
-(for a variable-length array), or the python str builtin
-(for a variable-length string array). Numpy string and unicode datatypes with
-length greater than one are aliases for str.
    
-
-
    dimensions: a tuple containing the variable's dimension names
-(defined previously with createDimension). Default is an empty tuple
-which means the variable is a scalar (and therefore has no dimensions).
    
-
-
    zlib: if True, data assigned to the Variable
-instance is compressed on disk. Default False.
    
-
-
    complevel: the level of zlib compression to use (1 is the fastest,
-but poorest compression, 9 is the slowest but best compression). Default 4.
-Ignored if zlib=False.
    
-
-
    shuffle: if True, the HDF5 shuffle filter is applied
-to improve compression. Default True. Ignored if zlib=False.
    
-
-
    fletcher32: if True (default False), the Fletcher32 checksum
-algorithm is used for error detection.
    
+
    fletcher32: if True (default False), the Fletcher32 checksum
+algorithm is used for error detection.
    
 
 
    contiguous: if True (default False), the variable data is
 stored contiguously on disk.  Default False. Setting to True for
@@ -3086,9 +2887,9 @@ 
    Inherited Members
    
 Persists as long as Dataset is open. Use set_var_chunk_cache to 
 change it when Dataset is re-opened. 
    
 
-
    Note: Variable instances should be created using the
-Dataset.createVariable">Dataset.createVariable method of a Dataset or
-Group instance, not using this class directly.
    
+
    Note: Variable instances should be created using the
+Dataset.createVariable method of a Dataset or
+Group instance, not using this class directly.
    
 
    
 
 
@@ -3104,7 +2905,7 @@ 
    Inherited Members
    
         
             
    group(self)
    
 
-
    return the group that this Variable is a member of.
    
+
    return the group that this Variable is a member of.
    
 
    
 
 
@@ -3120,7 +2921,7 @@ 
    Inherited Members
    
         
             
    ncattrs(self)
    
 
-
    return netCDF attribute names for this Variable in a list.
    
+
    return netCDF attribute names for this Variable in a list.
    
 
    
 
 
@@ -3318,7 +3119,7 @@ 
    Inherited Members
    
         
             
    renameAttribute(self, oldname, newname)
    
 
-
    rename a Variable attribute named oldname to newname.
    
+
    rename a Variable attribute named oldname to newname.
    
 
    
 
 
@@ -3627,8 +3428,8 @@ 
    Inherited Members
    
         
             
    get_dims(self)
    
 
-
    return a tuple of Dimension instances associated with this
-Variable.
    
+
    return a tuple of Dimension instances associated with this
+Variable.
    
 
    
 
 
@@ -3636,7 +3437,7 @@ 
    Inherited Members
    
                             
    
                                             
    #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.Variable' objects>
+        name = <attribute 'name' of 'netCDF4._netCDF4.Variable' objects>
     
    
 
     
@@ -3645,7 +3446,7 @@ 
    Inherited Members
    
                             
    
                                             
    #  
 
-        datatype = <attribute 'datatype' of 'netCDF4._netCDF4.Variable' objects>
+        datatype = <attribute 'datatype' of 'netCDF4._netCDF4.Variable' objects>
     
    
 
     
@@ -3654,7 +3455,7 @@ 
    Inherited Members
    
                             
    
                                             
    #  
 
-        shape = <attribute 'shape' of 'netCDF4._netCDF4.Variable' objects>
+        shape = <attribute 'shape' of 'netCDF4._netCDF4.Variable' objects>
     
    
 
     
@@ -3663,7 +3464,7 @@ 
    Inherited Members
    
                             
    
                                             
    #  
 
-        size = <attribute 'size' of 'netCDF4._netCDF4.Variable' objects>
+        size = <attribute 'size' of 'netCDF4._netCDF4.Variable' objects>
     
    
 
     
@@ -3672,7 +3473,7 @@ 
    Inherited Members
    
                             
    
                                             
    #  
 
-        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Variable' objects>
+        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Variable' objects>
     
    
 
     
@@ -3681,7 +3482,7 @@ 
    Inherited Members
    
                             
    
                                             
    #  
 
-        ndim = <attribute 'ndim' of 'netCDF4._netCDF4.Variable' objects>
+        ndim = <attribute 'ndim' of 'netCDF4._netCDF4.Variable' objects>
     
    
 
     
@@ -3690,7 +3491,7 @@ 
    Inherited Members
    
                             
    
                                             
    #  
 
-        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.Variable' objects>
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.Variable' objects>
     
    
 
     
@@ -3699,7 +3500,7 @@ 
    Inherited Members
    
                             
    
                                             
    #  
 
-        mask = <attribute 'mask' of 'netCDF4._netCDF4.Variable' objects>
+        mask = <attribute 'mask' of 'netCDF4._netCDF4.Variable' objects>
     
    
 
     
@@ -3708,7 +3509,7 @@ 
    Inherited Members
    
                             
    
                                             
    #  
 
-        scale = <attribute 'scale' of 'netCDF4._netCDF4.Variable' objects>
+        scale = <attribute 'scale' of 'netCDF4._netCDF4.Variable' objects>
     
    
 
     
@@ -3717,7 +3518,7 @@ 
    Inherited Members
    
                             
    
                                             
    #  
 
-        always_mask = <attribute 'always_mask' of 'netCDF4._netCDF4.Variable' objects>
+        always_mask = <attribute 'always_mask' of 'netCDF4._netCDF4.Variable' objects>
     
    
 
     
@@ -3726,370 +3527,232 @@ 
    Inherited Members
    
                             
    
                                             
    #  
 
-        chartostring = <attribute 'chartostring' of 'netCDF4._netCDF4.Variable' objects>
+        chartostring = <attribute 'chartostring' of 'netCDF4._netCDF4.Variable' objects>
     
    
 
     
 
                             
    
                 
    
-                
    
+                
    
                                 
    
-        #  
+        #  
 
         
         class
-        CompoundType:
+        Dimension:
     
    
 
         
-            
    A CompoundType instance is used to describe a compound data
-type, and can be passed to the the Dataset.createVariable">Dataset.createVariable method of
-a Dataset or Group instance.
-Compound data types map to numpy structured arrays.
-See CompoundType.__init__">CompoundType.__init__ for more details.
    
+            
    A netCDF Dimension is used to describe the coordinates of a Variable.
+See Dimension.__init__">Dimension.__init__ for more details.
    
 
-
    The instance variables dtype and name should not be modified by
-the user.
    
+
    The current maximum size of a Dimension instance can be obtained by
+calling the python len function on the Dimension instance. The
+Dimension.isunlimited">Dimension.isunlimited method of a Dimension instance can be used to
+determine if the dimension is unlimited.
    
+
+
    Read-only class variables:
    
+
+
    name: String name, used when creating a Variable with
+Dataset.createVariable.
    
+
+
    size: Current Dimension size (same as len(d), where d is a
+Dimension instance).
    
 
    
 
 
-                            
    
-                                        
    #  
+                            
    
+                                        
    #  
 
         
-            CompoundType(unknown)    
    
+            Dimension(unknown)    
    
 
         
-            
    __init__(group, datatype, datatype_name)
    
+            
    __init__(self, group, name, size=None)
    
 
-
    CompoundType constructor.
    
+
    Dimension constructor.
    
 
-
    group: Group instance to associate with the compound datatype.
    
+
    group: Group instance to associate with dimension.
    
 
-
    datatype: A numpy dtype object describing a structured (a.k.a record)
-array.  Can be composed of homogeneous numeric or character data types, or
-other structured array data types.
    
+
    name: Name of the dimension.
    
 
-
    datatype_name: a Python string containing a description of the
-compound data type.
    
+
    size: Size of the dimension. None or 0 means unlimited. (Default None).
    
 
-
    Note 1: When creating nested compound data types,
-the inner compound data types must already be associated with CompoundType
-instances (so create CompoundType instances for the innermost structures
-first).
    
+
    Note: Dimension instances should be created using the
+Dataset.createDimension method of a Group or
+Dataset instance, not using Dimension.__init__">Dimension.__init__ directly.
    
+
    
+
+
+                            
    
+                            
    
+                                        
    #  
+
+        
+            def
+            group(unknown):
+    
    
 
-
    Note 2: CompoundType instances should be created using the
-Dataset.createCompoundType">Dataset.createCompoundType
-method of a Dataset or Group instance, not using this class directly.
    
+        
+            
    group(self)
    
+
+
    return the group that this Dimension is a member of.
    
 
    
 
 
                             
    
-                            
    
-                                            
    #  
+                            
    
+                                        
    #  
 
-        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.CompoundType' objects>
+        
+            def
+            isunlimited(unknown):
     
    
 
-    
+        
+            
    isunlimited(self)
    
+
+
    returns True if the Dimension instance is unlimited, False otherwise.
    
+
    
+
 
                             
    
-                            
    
-                                            
    #  
+                            
    
+                                            
    #  
 
-        dtype_view = <attribute 'dtype_view' of 'netCDF4._netCDF4.CompoundType' objects>
+        name = <attribute 'name' of 'netCDF4._netCDF4.Dimension' objects>
     
    
 
     
 
                             
    
-                            
    
-                                            
    #  
+                            
    
+                                            
    #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.CompoundType' objects>
+        size = <attribute 'size' of 'netCDF4._netCDF4.Dimension' objects>
     
    
 
     
 
                             
    
                 
    
-                
    
+                
    
                                 
    
-        #  
+        #  
 
         
         class
-        VLType:
+        Group(netCDF4._netCDF4.Dataset):
     
    
 
         
-            
    A VLType instance is used to describe a variable length (VLEN) data
-type, and can be passed to the the Dataset.createVariable">Dataset.createVariable method of
-a Dataset or Group instance. See
-VLType.__init__">VLType.__init__for more details.
    
+            
    Groups define a hierarchical namespace within a netCDF file. They are
+analogous to directories in a unix filesystem. Each Group behaves like
+a Dataset within a Dataset, and can contain it's own variables,
+dimensions and attributes (and other Groups). See Group.__init__">Group.__init__
+for more details.
    
 
-
    The instance variables dtype and name should not be modified by
-the user.
    
+
    Group inherits from Dataset, so all the
+Dataset class methods and variables are available
+to a Group instance (except the close method).
    
+
+
    Additional read-only class variables:
    
+
+
    name: String describing the group name.
    
 
    
 
 
-                            
    
-                                        
    #  
+                            
    
+                                        
    #  
 
         
-            VLType(unknown)    
    
+            Group(unknown)    
    
 
         
-            
    __init__(group, datatype, datatype_name)
    
+            
    __init__(self, parent, name)
+Group constructor.
    
 
-
    VLType constructor.
    
-
-
    group: Group instance to associate with the VLEN datatype.
    
-
-
    datatype: An numpy dtype object describing the component type for the
-variable length array.
    
+
    parent: Group instance for the parent group.  If being created
+in the root group, use a Dataset instance.
    
 
-
    datatype_name: a Python string containing a description of the
-VLEN data type.
    
+
    name: - Name of the group.
    
 
-
    Note: VLType instances should be created using the
-Dataset.createVLType">Dataset.createVLType
-method of a Dataset or Group instance, not using this class directly.
    
+
    Note: Group instances should be created using the
+Dataset.createGroup method of a Dataset instance, or
+another Group instance, not using this class directly.
    
 
    
 
 
                             
    
-                            
    
-                                            
    #  
-
-        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.VLType' objects>
-    
    
-
-    
-
-                            
    
-                            
    
-                                            
    #  
-
-        name = <attribute 'name' of 'netCDF4._netCDF4.VLType' objects>
-    
    
-
-    
-
-                            
    
-                
    
-                
    
-                                
    
-        #  
+                            
    
+                                        
    #  
 
         
-        class
-        EnumType:
+            def
+            close(unknown):
     
    
 
         
-            
    A EnumType instance is used to describe an Enum data
-type, and can be passed to the the Dataset.createVariable">Dataset.createVariable method of
-a Dataset or Group instance. See
-EnumType.__init__">EnumType.__init__ for more details.
    
-
-
    The instance variables dtype, name and enum_dict should not be modified by
-the user.
    
-
    
-
-
-                            
    
-                                        
    #  
-
-        
-            EnumType(unknown)    
    
-
-        
-            
    __init__(group, datatype, datatype_name, enum_dict)
    
-
-
    EnumType constructor.
    
-
-
    group: Group instance to associate with the VLEN datatype.
    
-
-
    datatype: An numpy integer dtype object describing the base type
-for the Enum.
    
-
-
    datatype_name: a Python string containing a description of the
-Enum data type.
    
-
-
    enum_dict: a Python dictionary containing the Enum field/value
-pairs.
    
+            
    close(self)
    
 
-
    Note: EnumType instances should be created using the
-Dataset.createEnumType">Dataset.createEnumType
-method of a Dataset or Group instance, not using this class directly.
    
+
    overrides Dataset close method which does not apply to Group
+instances, raises IOError.
    
 
    
 
 
                             
    
-                            
    
-                                            
    #  
-
-        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.EnumType' objects>
-    
    
-
-    
-
-                            
    
-                            
    
-                                            
    #  
-
-        name = <attribute 'name' of 'netCDF4._netCDF4.EnumType' objects>
-    
    
-
-    
-
-                            
    
-                            
    
-                                            
    #  
-
-        enum_dict = <attribute 'enum_dict' of 'netCDF4._netCDF4.EnumType' objects>
-    
    
-
-    
+                            
    
+                                
    Inherited Members
    
+                                
    
+                                    
    netCDF4._netCDF4.Dataset
    
+                                
    filepath
    
+                
    isopen
    
+                
    sync
    
+                
    set_fill_on
    
+                
    set_fill_off
    
+                
    createDimension
    
+                
    renameDimension
    
+                
    createCompoundType
    
+                
    createVLType
    
+                
    createEnumType
    
+                
    createVariable
    
+                
    renameVariable
    
+                
    createGroup
    
+                
    ncattrs
    
+                
    setncattr
    
+                
    setncattr_string
    
+                
    setncatts
    
+                
    getncattr
    
+                
    delncattr
    
+                
    renameAttribute
    
+                
    renameGroup
    
+                
    set_auto_chartostring
    
+                
    set_auto_maskandscale
    
+                
    set_auto_mask
    
+                
    set_auto_scale
    
+                
    set_always_mask
    
+                
    set_ncstring_attrs
    
+                
    get_variables_by_attributes
    
+                
    fromcdl
    
+                
    tocdl
    
+                
    name
    
+                
    groups
    
+                
    dimensions
    
+                
    variables
    
+                
    disk_format
    
+                
    path
    
+                
    parent
    
+                
    file_format
    
+                
    data_model
    
+                
    cmptypes
    
+                
    vltypes
    
+                
    enumtypes
    
+                
    keepweakref
    
 
+            
    
+                                
    
                             
    
-                
    
-                
    
-                            
    #  
-
-        
-            def
-            getlibversion(unknown):
-    
    
-
-        
-            
    getlibversion()
    
-
-
    returns a string describing the version of the netcdf library
-used to build the module, and when it was built.
    
-
    
-
-
-                
    
-                
    
-                            
    #  
-
-        
-            def
-            get_chunk_cache(unknown):
-    
    
-
-        
-            
    get_chunk_cache()
    
-
-
    return current netCDF chunk cache information in a tuple (size,nelems,preemption).
-See netcdf C library documentation for nc_get_chunk_cache for
-details. Values can be reset with set_chunk_cache.
    
-
    
-
-
-                
    
-                
    
-                            
    #  
-
-        
-            def
-            set_chunk_cache(unknown):
-    
    
-
-        
-            
    set_chunk_cache(self,size=None,nelems=None,preemption=None)
    
-
-
    change netCDF4 chunk cache settings.
-See netcdf C library documentation for nc_set_chunk_cache for
-details.
    
-
    
-
-
-                
    
-                
    
-                            
    #  
-
-        
-            def
-            stringtoarr(unknown):
-    
    
-
-        
-            
    stringtoarr(a, NUMCHARS,dtype='S')
    
-
-
    convert a string to a character array of length NUMCHARS
    
-
-
    a:  Input python string.
    
-
-
    NUMCHARS:  number of characters used to represent string
-(if len(a) < NUMCHARS, it will be padded on the right with blanks).
    
-
-
    dtype:  type of numpy array to return.  Default is 'S', which
-means an array of dtype 'S1' will be returned.  If dtype='U', a
-unicode array (dtype = 'U1') will be returned.
    
-
-
    returns a rank 1 numpy character array of length NUMCHARS with datatype 'S1'
-(default) or 'U1' (if dtype='U')
    
-
    
-
-
-                
    
-                
    
-                            
    #  
-
-        
-            def
-            stringtochar(unknown):
-    
    
-
-        
-            
    stringtochar(a,encoding='utf-8')
    
-
-
    convert a string array to a character array with one extra dimension
    
-
-
    a:  Input numpy string array with numpy datatype 'SN' or 'UN', where N
-is the number of characters in each string.  Will be converted to
-an array of characters (datatype 'S1' or 'U1') of shape a.shape + (N,).
    
-
-
    optional kwarg encoding can be used to specify character encoding (default
-utf-8). If encoding is 'none' or 'bytes', a numpy.string_ the input array
-is treated a raw byte strings (numpy.string_).
    
-
-
    returns a numpy character array with datatype 'S1' or 'U1'
-and shape a.shape + (N,), where N is the length of each string in a.
    
-
    
-
-
-                
    
-                
    
-                            
    #  
-
-        
-            def
-            chartostring(unknown):
-    
    
-
-        
-            
    chartostring(b,encoding='utf-8')
    
-
-
    convert a character array to a string array with one less dimension.
    
-
-
    b:  Input character array (numpy datatype 'S1' or 'U1').
-Will be converted to a array of strings, where each string has a fixed
-length of b.shape[-1] characters.
    
-
-
    optional kwarg encoding can be used to specify character encoding (default
-utf-8). If encoding is 'none' or 'bytes', a numpy.string_ btye array is
-returned.
    
-
-
    returns a numpy string array with datatype 'UN' (or 'SN') and shape
-b.shape[:-1] where where N=b.shape[-1].
    
-
    
-
-
                 
    
                 
    
                                 
    
@@ -4097,7 +3760,7 @@ 
    Inherited Members
    
 
         
         class
-        MFDataset(Dataset):
+        MFDataset(netCDF4._netCDF4.Dataset):
     
    
 
         
@@ -4208,49 +3871,49 @@ 
    Inherited Members
    
                             
    
                                 
    Inherited Members
    
                                 
    
-                                    
    netCDF4._netCDF4.Dataset
    
-                                
    filepath
    
-                
    isopen
    
-                
    sync
    
-                
    set_fill_on
    
-                
    set_fill_off
    
-                
    createDimension
    
-                
    renameDimension
    
-                
    createCompoundType
    
-                
    createVLType
    
-                
    createEnumType
    
-                
    createVariable
    
-                
    renameVariable
    
-                
    createGroup
    
-                
    setncattr
    
-                
    setncattr_string
    
-                
    setncatts
    
-                
    getncattr
    
-                
    delncattr
    
-                
    renameAttribute
    
-                
    renameGroup
    
-                
    set_auto_chartostring
    
-                
    set_auto_maskandscale
    
-                
    set_auto_mask
    
-                
    set_auto_scale
    
-                
    set_always_mask
    
-                
    set_ncstring_attrs
    
-                
    get_variables_by_attributes
    
-                
    fromcdl
    
-                
    tocdl
    
-                
    name
    
-                
    groups
    
-                
    dimensions
    
-                
    variables
    
-                
    disk_format
    
-                
    path
    
-                
    parent
    
-                
    file_format
    
-                
    data_model
    
-                
    cmptypes
    
-                
    vltypes
    
-                
    enumtypes
    
-                
    keepweakref
    
+                                    
    netCDF4._netCDF4.Dataset
    
+                                
    filepath
    
+                
    isopen
    
+                
    sync
    
+                
    set_fill_on
    
+                
    set_fill_off
    
+                
    createDimension
    
+                
    renameDimension
    
+                
    createCompoundType
    
+                
    createVLType
    
+                
    createEnumType
    
+                
    createVariable
    
+                
    renameVariable
    
+                
    createGroup
    
+                
    setncattr
    
+                
    setncattr_string
    
+                
    setncatts
    
+                
    getncattr
    
+                
    delncattr
    
+                
    renameAttribute
    
+                
    renameGroup
    
+                
    set_auto_chartostring
    
+                
    set_auto_maskandscale
    
+                
    set_auto_mask
    
+                
    set_auto_scale
    
+                
    set_always_mask
    
+                
    set_ncstring_attrs
    
+                
    get_variables_by_attributes
    
+                
    fromcdl
    
+                
    tocdl
    
+                
    name
    
+                
    groups
    
+                
    dimensions
    
+                
    variables
    
+                
    disk_format
    
+                
    path
    
+                
    parent
    
+                
    file_format
    
+                
    data_model
    
+                
    cmptypes
    
+                
    vltypes
    
+                
    enumtypes
    
+                
    keepweakref
    
 
             
    
                                 
    
@@ -4262,7 +3925,7 @@ 
    Inherited Members
    
 
         
         class
-        MFTime(_Variable):
+        MFTime(netCDF4._netCDF4._Variable):
     
    
 
         
@@ -4271,7 +3934,7 @@ 
    Inherited Members
    
 
 
    Example usage (See MFTime.__init__">MFTime.__init__ for more details):
    
 
-
    >>> import numpy
+
    >>> import numpy as np
 >>> f1 = Dataset("mftest_1.nc","w", format="NETCDF4_CLASSIC")
 >>> f2 = Dataset("mftest_2.nc","w", format="NETCDF4_CLASSIC")
 >>> f1.createDimension("time",None)
@@ -4282,8 +3945,8 @@ 
    Inherited Members
    
 >>> t2.units = "days since 2000-02-01"
 >>> t1.calendar = "standard"
 >>> t2.calendar = "standard"
->>> t1[:] = numpy.arange(31)
->>> t2[:] = numpy.arange(30)
+>>> t1[:] = np.arange(31)
+>>> t2[:] = np.arange(30)
 >>> f1.close()
 >>> f2.close()
 >>> # Read the two files in at once, in one Dataset.
@@ -4328,19 +3991,517 @@ 
    Inherited Members
    
                             
    
                                 
    Inherited Members
    
                                 
    
-                                    
    netCDF4._netCDF4._Variable
    
-                                
    typecode
    
-                
    ncattrs
    
-                
    set_auto_chartostring
    
-                
    set_auto_maskandscale
    
-                
    set_auto_mask
    
-                
    set_auto_scale
    
-                
    set_always_mask
    
+                                    
    netCDF4._netCDF4._Variable
    
+                                
    typecode
    
+                
    ncattrs
    
+                
    set_auto_chartostring
    
+                
    set_auto_maskandscale
    
+                
    set_auto_mask
    
+                
    set_auto_scale
    
+                
    set_always_mask
    
 
             
    
                                 
    
                             
    
                 
    
+                
    
+                                
    
+        #  
+
+        
+        class
+        CompoundType:
+    
    
+
+        
+            
    A CompoundType instance is used to describe a compound data
+type, and can be passed to the the Dataset.createVariable method of
+a Dataset or Group instance.
+Compound data types map to numpy structured arrays.
+See CompoundType.__init__">CompoundType.__init__ for more details.
    
+
+
    The instance variables dtype and name should not be modified by
+the user.
    
+
    
+
+
+                            
    
+                                        
    #  
+
+        
+            CompoundType(unknown)    
    
+
+        
+            
    __init__(group, datatype, datatype_name)
    
+
+
    CompoundType constructor.
    
+
+
    group: Group instance to associate with the compound datatype.
    
+
+
    datatype: A numpy dtype object describing a structured (a.k.a record)
+array.  Can be composed of homogeneous numeric or character data types, or
+other structured array data types.
    
+
+
    datatype_name: a Python string containing a description of the
+compound data type.
    
+
+
    Note 1: When creating nested compound data types,
+the inner compound data types must already be associated with CompoundType
+instances (so create CompoundType instances for the innermost structures
+first).
    
+
+
    Note 2: CompoundType instances should be created using the
+Dataset.createCompoundType method of a Dataset or
+Group instance, not using this class directly.
    
+
    
+
+
+                            
    
+                            
    
+                                            
    #  
+
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.CompoundType' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        dtype_view = <attribute 'dtype_view' of 'netCDF4._netCDF4.CompoundType' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        name = <attribute 'name' of 'netCDF4._netCDF4.CompoundType' objects>
+    
    
+
+    
+
+                            
    
+                
    
+                
    
+                                
    
+        #  
+
+        
+        class
+        VLType:
+    
    
+
+        
+            
    A VLType instance is used to describe a variable length (VLEN) data
+type, and can be passed to the the Dataset.createVariable method of
+a Dataset or Group instance. See
+VLType.__init__">VLType.__init__for more details.
    
+
+
    The instance variables dtype and name should not be modified by
+the user.
    
+
    
+
+
+                            
    
+                                        
    #  
+
+        
+            VLType(unknown)    
    
+
+        
+            
    __init__(group, datatype, datatype_name)
    
+
+
    VLType constructor.
    
+
+
    group: Group instance to associate with the VLEN datatype.
    
+
+
    datatype: An numpy dtype object describing the component type for the
+variable length array.
    
+
+
    datatype_name: a Python string containing a description of the
+VLEN data type.
    
+
+
    Note: VLType instances should be created using the
+Dataset.createVLType method of a Dataset or
+Group instance, not using this class directly.
    
+
    
+
+
+                            
    
+                            
    
+                                            
    #  
+
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.VLType' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        name = <attribute 'name' of 'netCDF4._netCDF4.VLType' objects>
+    
    
+
+    
+
+                            
    
+                
    
+                
    
+                            
    #  
+
+        
+            def
+            date2num(unknown):
+    
    
+
+        
+            
    date2num(dates, units, calendar=None)
    
+
+
    Return numeric time values given datetime objects. The units
+of the numeric time values are described by the units argument
+and the calendar keyword. The datetime objects must
+be in UTC with no time-zone offset.  If there is a
+time-zone offset in units, it will be applied to the
+returned numeric values.
    
+
+
    dates: A datetime object or a sequence of datetime objects.
+The datetime objects should not include a time-zone offset. They
+can be either native python datetime instances (which use
+the proleptic gregorian calendar) or cftime.datetime instances.
    
+
+
    units: a string of the form 
+describing the time units.  can be days, hours, minutes,
+seconds, milliseconds or microseconds.  is the time
+origin. months_since is allowed only for the 360_day calendar.
    
+
+
    calendar: describes the calendar to be used in the time calculations.
+All the values currently defined in the
+CF metadata convention <http://cfconventions.org>__ are supported.
+Valid calendars 'standard', 'gregorian', 'proleptic_gregorian'
+'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'.
+Default is None which means the calendar associated with the rist
+input datetime instance will be used.
    
+
+
    returns a numeric time value, or an array of numeric time values
+with approximately 1 microsecond accuracy.
    
+
    
+
+
+                
    
+                
    
+                            
    #  
+
+        
+            def
+            num2date(unknown):
+    
    
+
+        
+            
    num2date(times, units, calendar=u'standard', only_use_cftime_datetimes=True, only_use_python_datetimes=False)
    
+
+
    Return datetime objects given numeric time values. The units
+of the numeric time values are described by the units argument
+and the calendar keyword. The returned datetime objects represent
+UTC with no time-zone offset, even if the specified
+units contain a time-zone offset.
    
+
+
    times: numeric time values.
    
+
+
    units: a string of the form 
+describing the time units.  can be days, hours, minutes,
+seconds, milliseconds or microseconds.  is the time
+origin. months_since is allowed only for the 360_day calendar.
    
+
+
    calendar: describes the calendar used in the time calculations.
+All the values currently defined in the
+CF metadata convention <http://cfconventions.org>__ are supported.
+Valid calendars 'standard', 'gregorian', 'proleptic_gregorian'
+'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'.
+Default is 'standard', which is a mixed Julian/Gregorian calendar.
    
+
+
    only_use_cftime_datetimes: if False, python datetime.datetime
+objects are returned from num2date where possible; if True dates which
+subclass cftime.datetime are returned for all calendars. Default True.
    
+
+
    only_use_python_datetimes: always return python datetime.datetime
+objects and raise an error if this is not possible. Ignored unless
+only_use_cftime_datetimes=False. Default False.
    
+
+
    returns a datetime instance, or an array of datetime instances with
+microsecond accuracy, if possible.
    
+
+
    Note: If only_use_cftime_datetimes=False and
+use_only_python_datetimes=False, the datetime instances
+returned are 'real' python datetime
+objects if calendar='proleptic_gregorian', or
+calendar='standard' or 'gregorian'
+and the date is after the breakpoint between the Julian and
+Gregorian calendars (1582-10-15). Otherwise, they are ctime.datetime
+objects which support some but not all the methods of native python
+datetime objects. The datetime instances
+do not contain a time-zone offset, even if the specified units
+contains one.
    
+
    
+
+
+                
    
+                
    
+                            
    #  
+
+        
+            def
+            date2index(unknown):
+    
    
+
+        
+            
    date2index(dates, nctime, calendar=None, select=u'exact')
    
+
+
    Return indices of a netCDF time variable corresponding to the given dates.
    
+
+
    dates: A datetime object or a sequence of datetime objects.
+The datetime objects should not include a time-zone offset.
    
+
+
    nctime: A netCDF time variable object. The nctime object must have a
+units attribute.
    
+
+
    calendar: describes the calendar used in the time calculations.
+All the values currently defined in the
+CF metadata convention <http://cfconventions.org>__ are supported.
+Valid calendars 'standard', 'gregorian', 'proleptic_gregorian'
+'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'.
+Default is 'standard', which is a mixed Julian/Gregorian calendar.
+If calendar is None, its value is given by nctime.calendar or
+standard if no such attribute exists.
    
+
+
    select: 'exact', 'before', 'after', 'nearest'
+The index selection method. exact will return the indices perfectly
+matching the dates given. before and after will return the indices
+corresponding to the dates just before or just after the given dates if
+an exact match cannot be found. nearest will return the indices that
+correspond to the closest dates.
    
+
+
    returns an index (indices) of the netCDF time variable corresponding
+to the given datetime object(s).
    
+
    
+
+
+                
    
+                
    
+                            
    #  
+
+        
+            def
+            stringtochar(unknown):
+    
    
+
+        
+            
    stringtochar(a,encoding='utf-8')
    
+
+
    convert a string array to a character array with one extra dimension
    
+
+
    a:  Input numpy string array with numpy datatype 'SN' or 'UN', where N
+is the number of characters in each string.  Will be converted to
+an array of characters (datatype 'S1' or 'U1') of shape a.shape + (N,).
    
+
+
    optional kwarg encoding can be used to specify character encoding (default
+utf-8). If encoding is 'none' or 'bytes', a numpy.string_ the input array
+is treated a raw byte strings (numpy.string_).
    
+
+
    returns a numpy character array with datatype 'S1' or 'U1'
+and shape a.shape + (N,), where N is the length of each string in a.
    
+
    
+
+
+                
    
+                
    
+                            
    #  
+
+        
+            def
+            chartostring(unknown):
+    
    
+
+        
+            
    chartostring(b,encoding='utf-8')
    
+
+
    convert a character array to a string array with one less dimension.
    
+
+
    b:  Input character array (numpy datatype 'S1' or 'U1').
+Will be converted to a array of strings, where each string has a fixed
+length of b.shape[-1] characters.
    
+
+
    optional kwarg encoding can be used to specify character encoding (default
+utf-8). If encoding is 'none' or 'bytes', a numpy.string_ btye array is
+returned.
    
+
+
    returns a numpy string array with datatype 'UN' (or 'SN') and shape
+b.shape[:-1] where where N=b.shape[-1].
    
+
    
+
+
+                
    
+                
    
+                            
    #  
+
+        
+            def
+            stringtoarr(unknown):
+    
    
+
+        
+            
    stringtoarr(a, NUMCHARS,dtype='S')
    
+
+
    convert a string to a character array of length NUMCHARS
    
+
+
    a:  Input python string.
    
+
+
    NUMCHARS:  number of characters used to represent string
+(if len(a) < NUMCHARS, it will be padded on the right with blanks).
    
+
+
    dtype:  type of numpy array to return.  Default is 'S', which
+means an array of dtype 'S1' will be returned.  If dtype='U', a
+unicode array (dtype = 'U1') will be returned.
    
+
+
    returns a rank 1 numpy character array of length NUMCHARS with datatype 'S1'
+(default) or 'U1' (if dtype='U')
    
+
    
+
+
+                
    
+                
    
+                            
    #  
+
+        
+            def
+            getlibversion(unknown):
+    
    
+
+        
+            
    getlibversion()
    
+
+
    returns a string describing the version of the netcdf library
+used to build the module, and when it was built.
    
+
    
+
+
+                
    
+                
    
+                                
    
+        #  
+
+        
+        class
+        EnumType:
+    
    
+
+        
+            
    A EnumType instance is used to describe an Enum data
+type, and can be passed to the the Dataset.createVariable method of
+a Dataset or Group instance. See
+EnumType.__init__">EnumType.__init__ for more details.
    
+
+
    The instance variables dtype, name and enum_dict should not be modified by
+the user.
    
+
    
+
+
+                            
    
+                                        
    #  
+
+        
+            EnumType(unknown)    
    
+
+        
+            
    __init__(group, datatype, datatype_name, enum_dict)
    
+
+
    EnumType constructor.
    
+
+
    group: Group instance to associate with the VLEN datatype.
    
+
+
    datatype: An numpy integer dtype object describing the base type
+for the Enum.
    
+
+
    datatype_name: a Python string containing a description of the
+Enum data type.
    
+
+
    enum_dict: a Python dictionary containing the Enum field/value
+pairs.
    
+
+
    Note: EnumType instances should be created using the
+Dataset.createEnumType method of a Dataset or
+Group instance, not using this class directly.
    
+
    
+
+
+                            
    
+                            
    
+                                            
    #  
+
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.EnumType' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        name = <attribute 'name' of 'netCDF4._netCDF4.EnumType' objects>
+    
    
+
+    
+
+                            
    
+                            
    
+                                            
    #  
+
+        enum_dict = <attribute 'enum_dict' of 'netCDF4._netCDF4.EnumType' objects>
+    
    
+
+    
+
+                            
    
+                
    
+                
    
+                            
    #  
+
+        
+            def
+            get_chunk_cache(unknown):
+    
    
+
+        
+            
    get_chunk_cache()
    
+
+
    return current netCDF chunk cache information in a tuple (size,nelems,preemption).
+See netcdf C library documentation for nc_get_chunk_cache for
+details. Values can be reset with set_chunk_cache.
    
+
    
+
+
+                
    
+                
    
+                            
    #  
+
+        
+            def
+            set_chunk_cache(unknown):
+    
    
+
+        
+            
    set_chunk_cache(self,size=None,nelems=None,preemption=None)
    
+
+
    change netCDF4 chunk cache settings.
+See netcdf C library documentation for nc_set_chunk_cache for
+details.
    
+
    
+
+
+                
    
     
 
 
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 3c9449b2e..d312a3234 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -110,7 +110,7 @@ types) are not supported.
 
 ## Creating/Opening/Closing a netCDF file
 
-To create a netCDF file from python, you simply call the [Dataset](#Dataset)
+To create a netCDF file from python, you simply call the `Dataset`
 constructor. This is also the method used to open an existing netCDF
 file.  If the file is open for write access (`mode='w', 'r+'` or `'a'`), you may
 write any type of data including new dimensions, groups, variables and
@@ -134,7 +134,7 @@ creating a new file, the format may be specified using the `format`
 keyword in the `Dataset` constructor.  The default format is
 `NETCDF4`. To see how a given file is formatted, you can examine the
 `data_model` attribute.  Closing the netCDF file is
-accomplished via the `Dataset.close` method of the [Dataset](#Dataset)
+accomplished via the `Dataset.close` method of the `Dataset`
 instance.
 
 Here's an example:
@@ -148,7 +148,7 @@ NETCDF4
 ```
 
 Remote [OPeNDAP](http://opendap.org)-hosted datasets can be accessed for
-reading over http if a URL is provided to the [Dataset](#Dataset) constructor instead of a
+reading over http if a URL is provided to the `Dataset` constructor instead of a
 filename.  However, this requires that the netCDF library be built with
 OPenDAP support, via the `--enable-dap` configure option (added in
 version 4.0.1).
@@ -159,14 +159,14 @@ version 4.0.1).
 netCDF version 4 added support for organizing data in hierarchical
 groups, which are analogous to directories in a filesystem. Groups serve
 as containers for variables, dimensions and attributes, as well as other
-groups.  A [Dataset](#Dataset) creates a special group, called
+groups.  A `Dataset` creates a special group, called
 the 'root group', which is similar to the root directory in a unix
-filesystem.  To create [Group](#Group) instances, use the
-`Dataset.createGroup` method of a [Dataset](#Dataset) or [Group](#Group)
+filesystem.  To create `Group` instances, use the
+`Dataset.createGroup` method of a `Dataset` or `Group`
 instance. `Dataset.createGroup` takes a single argument, a
-python string containing the name of the new group. The new [Group](#Group)
+python string containing the name of the new group. The new `Group`
 instances contained within the root group can be accessed by name using
-the `groups` dictionary attribute of the [Dataset](#Dataset) instance.  Only
+the `groups` dictionary attribute of the `Dataset` instance.  Only
 `NETCDF4` formatted files support Groups, if you try to create a Group
 in a netCDF 3 file you will get an error message.
 
@@ -187,10 +187,10 @@ group /analyses:
 >>>
 ```
 
-Groups can exist within groups in a [Dataset](#Dataset), just as directories
-exist within directories in a unix filesystem. Each [Group](#Group) instance
+Groups can exist within groups in a `Dataset`, just as directories
+exist within directories in a unix filesystem. Each `Group` instance
 has a `groups` attribute dictionary containing all of the group
-instances contained within that group. Each [Group](#Group) instance also has a
+instances contained within that group. Each `Group` instance also has a
 `path` attribute that contains a simulated unix directory path to
 that group.  To simplify the creation of nested groups, you can
 use a unix-like path as an argument to `Dataset.createGroup`.
@@ -206,8 +206,8 @@ that already exists, no error will be raised, and the existing group will be
 returned.
 
 Here's an example that shows how to navigate all the groups in a
-[Dataset](#Dataset). The function `walktree` is a Python generator that is used
-to walk the directory tree. Note that printing the [Dataset](#Dataset) or [Group](#Group)
+`Dataset`. The function `walktree` is a Python generator that is used
+to walk the directory tree. Note that printing the `Dataset` or `Group`
 object yields summary information about it's contents.
 
 ```python
@@ -254,8 +254,8 @@ netCDF defines the sizes of all variables in terms of dimensions, so
 before any variables can be created the dimensions they use must be
 created first. A special case, not often used in practice, is that of a
 scalar variable, which has no dimensions. A dimension is created using
-the `Dataset.createDimension` method of a [Dataset](#Dataset)
-or [Group](#Group) instance. A Python string is used to set the name of the
+the `Dataset.createDimension` method of a `Dataset`
+or `Group` instance. A Python string is used to set the name of the
 dimension, and an integer value is used to set the size. To create an
 unlimited dimension (a dimension that can be appended to), the size
 value is set to `None` or 0. In this example, there both the `time` and
@@ -271,16 +271,16 @@ one, and it must be the first (leftmost) dimension of the variable.
 ```
 
 
-All of the [Dimension](#Dimension) instances are stored in a python dictionary.
+All of the `Dimension` instances are stored in a python dictionary.
 
 ```python
 >>> print(rootgrp.dimensions)
 {'level':  (unlimited): name = 'level', size = 0, 'time':  (unlimited): name = 'time', size = 0, 'lat': : name = 'lat', size = 73, 'lon': : name = 'lon', size = 144}
 ```
 
-Using the python `len` function with a [Dimension](#Dimension) instance returns
+Using the python `len` function with a `Dimension` instance returns
 current size of that dimension.
-[Dimension.isunlimited](#Dimension.isunlimited) method of a [Dimension](#Dimension) instance
+[Dimension.isunlimited](#Dimension.isunlimited) method of a `Dimension` instance
 be used to determine if the dimensions is unlimited, or appendable.
 
 ```python
@@ -292,7 +292,7 @@ False
 True
 ```
 
-Printing the [Dimension](#Dimension) object
+Printing the `Dimension` object
 provides useful summary info, including the name and length of the dimension,
 and whether it is unlimited.
 
@@ -305,9 +305,9 @@ and whether it is unlimited.
 : name = 'lon', size = 144
 ```
 
-[Dimension](#Dimension) names can be changed using the
-[Datatset.renameDimension](#Datatset.renameDimension) method of a [Dataset](#Dataset) or
-[Group](#Group) instance.
+`Dimension` names can be changed using the
+[Datatset.renameDimension](#Datatset.renameDimension) method of a `Dataset` or
+`Group` instance.
 
 ## Variables in a netCDF file
 
@@ -315,8 +315,8 @@ netCDF variables behave much like python multidimensional array objects
 supplied by the [numpy module](http://numpy.scipy.org). However,
 unlike numpy arrays, netCDF4 variables can be appended to along one or
 more 'unlimited' dimensions. To create a netCDF variable, use the
-`Dataset.createVariable` method of a [Dataset](#Dataset) or
-[Group](#Group) instance. The `Dataset.createVariable`j method
+`Dataset.createVariable` method of a `Dataset` or
+`Group` instance. The `Dataset.createVariable`j method
 has two mandatory arguments, the variable name (a Python string), and
 the variable datatype. The variable's dimensions are given by a tuple
 containing the dimension names (defined previously with
@@ -339,7 +339,7 @@ can only be used if the file format is `NETCDF4`.
 
 The dimensions themselves are usually also defined as variables, called
 coordinate variables. The `Dataset.createVariable`
-method returns an instance of the [Variable](#Variable) class whose methods can be
+method returns an instance of the `Variable` class whose methods can be
 used later to access and set variable data and attributes.
 
 ```python
@@ -352,7 +352,7 @@ used later to access and set variable data and attributes.
 >>> temp.units = "K"
 ```
 
-To get summary info on a [Variable](#Variable) instance in an interactive session,
+To get summary info on a `Variable` instance in an interactive session,
 just print it.
 
 ```python
@@ -373,8 +373,8 @@ You can use a path to create a Variable inside a hierarchy of groups.
 
 If the intermediate groups do not yet exist, they will be created.
 
-You can also query a [Dataset](#Dataset) or [Group](#Group) instance directly to obtain [Group](#Group) or
-[Variable](#Variable) instances using paths.
+You can also query a `Dataset` or `Group` instance directly to obtain `Group` or
+`Variable` instances using paths.
 
 ```python
 >>> print(rootgrp["/forecasts/model1"])  # a Group instance
@@ -393,7 +393,7 @@ filling on, default _FillValue of 9.969209968386869e+36 used
 ```
 
 
-All of the variables in the [Dataset](#Dataset) or [Group](#Group) are stored in a
+All of the variables in the `Dataset` or `Group` are stored in a
 Python dictionary, in the same way as the dimensions:
 
 ```python
@@ -422,8 +422,8 @@ current shape = (0, 0, 73, 144)
 filling on, default _FillValue of 9.969209968386869e+36 used}
 ```
 
-[Variable](#Variable) names can be changed using the
-`Dataset.renameVariable` method of a [Dataset](#Dataset)
+`Variable` names can be changed using the
+`Dataset.renameVariable` method of a `Dataset`
 instance.
 
 Variables can be sliced similar to numpy arrays, but there are some differences.  See
@@ -434,10 +434,10 @@ Variables can be sliced similar to numpy arrays, but there are some differences.
 
 There are two types of attributes in a netCDF file, global and variable.
 Global attributes provide information about a group, or the entire
-dataset, as a whole. [Variable](#Variable) attributes provide information about
+dataset, as a whole. `Variable` attributes provide information about
 one of the variables in a group. Global attributes are set by assigning
-values to [Dataset](#Dataset) or [Group](#Group) instance variables. [Variable](#Variable)
-attributes are set by assigning values to [Variable](#Variable) instances
+values to `Dataset` or `Group` instance variables. `Variable`
+attributes are set by assigning values to `Variable` instances
 variables. Attributes can be strings, numbers or sequences. Returning to
 our example,
 
@@ -454,8 +454,8 @@ our example,
 >>> times.calendar = "gregorian"
 ```
 
-The `Dataset.ncattrs` method of a [Dataset](#Dataset), [Group](#Group) or
-[Variable](#Variable) instance can be used to retrieve the names of all the netCDF
+The `Dataset.ncattrs` method of a `Dataset`, `Group` or
+`Variable` instance can be used to retrieve the names of all the netCDF
 attributes. This method is provided as a convenience, since using the
 built-in `dir` Python function will return a bunch of private methods
 and attributes that cannot (or should not) be modified by the user.
@@ -468,7 +468,7 @@ Global attr history = Created Mon Jul  8 14:19:41 2019
 Global attr source = netCDF4 python module tutorial
 ```
 
-The `__dict__` attribute of a [Dataset](#Dataset), [Group](#Group) or [Variable](#Variable)
+The `__dict__` attribute of a `Dataset`, `Group` or `Variable`
 instance provides all the netCDF attribute name/value pairs in a python
 dictionary:
 
@@ -477,13 +477,13 @@ dictionary:
 {'description': 'bogus example script', 'history': 'Created Mon Jul  8 14:19:41 2019', 'source': 'netCDF4 python module tutorial'}
 ```
 
-Attributes can be deleted from a netCDF [Dataset](#Dataset), [Group](#Group) or
-[Variable](#Variable) using the python `del` statement (i.e. `del grp.foo`
+Attributes can be deleted from a netCDF `Dataset`, `Group` or
+`Variable` using the python `del` statement (i.e. `del grp.foo`
 removes the attribute `foo` the the group `grp`).
 
 ## Writing data to and retrieving data from a netCDF variable
 
-Now that you have a netCDF [Variable](#Variable) instance, how do you put data
+Now that you have a netCDF `Variable` instance, how do you put data
 into it? You can just treat it like an array and assign data to a slice.
 
 ```python
@@ -503,7 +503,7 @@ latitudes =
   90. ]
 ```
 
-Unlike NumPy's array objects, netCDF [Variable](#Variable)
+Unlike NumPy's array objects, netCDF `Variable`
 objects with unlimited dimensions will grow along those dimensions if you
 assign data outside the currently defined range of indices.
 
@@ -580,7 +580,7 @@ The result will be a numpy scalar array.
 
 By default, netcdf4-python returns numpy masked arrays with values equal to the
 `missing_value` or `_FillValue` variable attributes masked.  The
-`Dataset.set_auto_mask` [Dataset](#Dataset) and [Variable](#Variable) methods
+`Dataset.set_auto_mask` `Dataset` and `Variable` methods
 can be used to disable this feature so that
 numpy arrays are always returned, with the missing values included. Prior to
 version 1.4.0 the default behavior was to only return masked arrays when the
@@ -632,7 +632,7 @@ of a netCDF time variable corresponding to a sequence of datetime instances.
 If you want to read data from a variable that spans multiple netCDF files,
 you can use the [MFDataset](#MFDataset) class to read the data as if it were
 contained in a single file. Instead of using a single filename to create
-a [Dataset](#Dataset) instance, create a [MFDataset](#MFDataset) instance with either a list
+a `Dataset` instance, create a [MFDataset](#MFDataset) instance with either a list
 of filenames, or a string with a wildcard (which is then converted to
 a sorted list of files using the python glob module).
 Variables in the list of files that share the same unlimited
@@ -669,7 +669,7 @@ datasets.
 
 ## Efficient compression of netCDF variables
 
-Data stored in netCDF 4 [Variable](#Variable) objects can be compressed and
+Data stored in netCDF 4 `Variable` objects can be compressed and
 decompressed on the fly. The parameters for the compression are
 determined by the `zlib`, `complevel` and `shuffle` keyword arguments
 to the `Dataset.createVariable` method. To turn on
@@ -736,7 +736,7 @@ location for scattered (point) data. You can then access all the
 information for a point by reading one variable, instead of reading
 different parameters from different variables.  Compound data types
 are created from the corresponding numpy data type using the
-`Dataset.createCompoundType` method of a [Dataset](#Dataset) or [Group](#Group) instance.
+`Dataset.createCompoundType` method of a `Dataset` or `Group` instance.
 Since there is no native complex data type in netcdf, compound types are handy
 for storing numpy complex arrays.  Here's an example:
 
@@ -773,7 +773,7 @@ Compound types can be nested, but you must create the 'inner'
 ones first. All possible numpy structured arrays cannot be
 represented as Compound variables - an error message will be
 raise if you try to create one that is not supported.
-All of the compound types defined for a [Dataset](#Dataset) or [Group](#Group) are stored
+All of the compound types defined for a `Dataset` or `Group` are stored
 in a Python dictionary, just like variables and dimensions. As always, printing
 objects gives useful summary information in an interactive session:
 
@@ -801,7 +801,7 @@ current shape = (3,)
 NetCDF 4 has support for variable-length or "ragged" arrays.  These are arrays
 of variable length sequences having the same type. To create a variable-length
 data type, use the `Dataset.createVLType` method
-method of a [Dataset](#Dataset) or [Group](#Group) instance.
+method of a `Dataset` or `Group` instance.
 
 ```python
 >>> f = Dataset("tst_vlen.nc","w")
@@ -1021,7 +1021,7 @@ depend on or be affected by other processes. Collective IO is a way of doing
 IO defined in the MPI-IO standard; unlike independent IO, all processes must
 participate in doing IO. To toggle back and forth between
 the two types of IO, use the `Variable.set_collective`
-[Variable](#Variable) method. All metadata
+`Variable` method. All metadata
 operations (such as creation of groups, types, variables, dimensions, or attributes)
 are collective.  There are a couple of important limitations of parallel IO:
 
@@ -1680,9 +1680,9 @@ be raised in the next release."""
         _ensure_nc_success(ierr, err_cls=AttributeError)
 
 cdef _get_types(group):
-    # Private function to create [CompoundType](#CompoundType),
+    # Private function to create `CompoundType`,
     # [VLType](#VLType) or [EnumType](#EnumType) instances for all the
-    # compound, VLEN or Enum types in a [Group](#Group) or [Dataset](#Dataset).
+    # compound, VLEN or Enum types in a `Group` or `Dataset`.
     cdef int ierr, ntypes, classp, n, _grpid
     cdef nc_type xtype
     cdef nc_type *typeids
@@ -1751,8 +1751,8 @@ cdef _get_types(group):
     return cmptypes, vltypes, enumtypes
 
 cdef _get_dims(group):
-    # Private function to create [Dimension](#Dimension) instances for all the
-    # dimensions in a [Group](#Group) or Dataset
+    # Private function to create `Dimension` instances for all the
+    # dimensions in a `Group` or Dataset
     cdef int ierr, numdims, n, _grpid
     cdef int *dimids
     cdef char namstring[NC_MAX_NAME+1]
@@ -1785,8 +1785,8 @@ cdef _get_dims(group):
     return dimensions
 
 cdef _get_grps(group):
-    # Private function to create [Group](#Group) instances for all the
-    # groups in a [Group](#Group) or Dataset
+    # Private function to create `Group` instances for all the
+    # groups in a `Group` or Dataset
     cdef int ierr, numgrps, n, _grpid
     cdef int *grpids
     cdef char namstring[NC_MAX_NAME+1]
@@ -1795,7 +1795,7 @@ cdef _get_grps(group):
     with nogil:
         ierr = nc_inq_grps(_grpid, &numgrps, NULL)
     _ensure_nc_success(ierr)
-    # create dictionary containing [Group](#Group) instances for groups in this group
+    # create dictionary containing `Group` instances for groups in this group
     if sys.version_info[0:2] < (3, 7):
         groups = OrderedDict()
     else:
@@ -1815,8 +1815,8 @@ cdef _get_grps(group):
     return groups
 
 cdef _get_vars(group):
-    # Private function to create [Variable](#Variable) instances for all the
-    # variables in a [Group](#Group) or Dataset
+    # Private function to create `Variable` instances for all the
+    # variables in a `Group` or Dataset
     cdef int ierr, numvars, n, nn, numdims, varid, classp, iendian, _grpid
     cdef int *varids
     cdef int *dimids
@@ -1961,45 +1961,45 @@ _private_atts = \
 
 cdef class Dataset:
     """
-A netCDF [Dataset](#Dataset) is a collection of dimensions, groups, variables and
+A netCDF `Dataset` is a collection of dimensions, groups, variables and
 attributes. Together they describe the meaning of data and relations among
 data fields stored in a netCDF file. See `Dataset.__init__` for more
 details.
 
 A list of attribute names corresponding to global netCDF attributes
-defined for the [Dataset](#Dataset) can be obtained with the
+defined for the `Dataset` can be obtained with the
 `Dataset.ncattrs` method.
 These attributes can be created by assigning to an attribute of the
-[Dataset](#Dataset) instance. A dictionary containing all the netCDF attribute
+`Dataset` instance. A dictionary containing all the netCDF attribute
 name/value pairs is provided by the `__dict__` attribute of a
-[Dataset](#Dataset) instance.
+`Dataset` instance.
 
 The following class variables are read-only and should not be
 modified by the user.
 
 **`dimensions`**: The `dimensions` dictionary maps the names of
-dimensions defined for the [Group](#Group) or [Dataset](#Dataset) to instances of the
-[Dimension](#Dimension) class.
+dimensions defined for the `Group` or `Dataset` to instances of the
+`Dimension` class.
 
 **`variables`**: The `variables` dictionary maps the names of variables
-defined for this [Dataset](#Dataset) or [Group](#Group) to instances of the
-[Variable](#Variable) class.
+defined for this `Dataset` or `Group` to instances of the
+`Variable` class.
 
 **`groups`**: The groups dictionary maps the names of groups created for
-this [Dataset](#Dataset) or [Group](#Group) to instances of the [Group](#Group) class (the
-[Dataset](#Dataset) class is simply a special case of the [Group](#Group) class which
+this `Dataset` or `Group` to instances of the `Group` class (the
+`Dataset` class is simply a special case of the `Group` class which
 describes the root group in the netCDF4 file).
 
 **`cmptypes`**: The `cmptypes` dictionary maps the names of
-compound types defined for the [Group](#Group) or [Dataset](#Dataset) to instances of the
-[CompoundType](#CompoundType) class.
+compound types defined for the `Group` or `Dataset` to instances of the
+`CompoundType` class.
 
 **`vltypes`**: The `vltypes` dictionary maps the names of
-variable-length types defined for the [Group](#Group) or [Dataset](#Dataset) to instances
+variable-length types defined for the `Group` or `Dataset` to instances
 of the [VLType](#VLType) class.
 
 **`enumtypes`**: The `enumtypes` dictionary maps the names of
-Enum types defined for the [Group](#Group) or [Dataset](#Dataset) to instances
+Enum types defined for the `Group` or `Dataset` to instances
 of the [EnumType](#EnumType) class.
 
 **`data_model`**: `data_model` describes the netCDF
@@ -2015,12 +2015,12 @@ netcdf C library version >= 4.3.1, otherwise will always return
 `UNDEFINED`.
 
 **`parent`**: `parent` is a reference to the parent
-[Group](#Group) instance. `None` for the root group or [Dataset](#Dataset)
+`Group` instance. `None` for the root group or `Dataset`
 instance.
 
-**`path`**: `path` shows the location of the [Group](#Group) in
-the [Dataset](#Dataset) in a unix directory format (the names of groups in the
-hierarchy separated by backslashes). A [Dataset](#Dataset) instance is the root
+**`path`**: `path` shows the location of the `Group` in
+the `Dataset` in a unix directory format (the names of groups in the
+hierarchy separated by backslashes). A `Dataset` instance is the root
 group, so the path is simply `'/'`.
 
 **`keepweakref`**: If `True`, child Dimension and Variables objects only keep weak
@@ -2046,7 +2046,7 @@ strings.
         persist=False, keepweakref=False, memory=None, encoding=None,
         parallel=False, comm=None, info=None, format='NETCDF4')`**
 
-        [Dataset](#Dataset) constructor.
+        `Dataset` constructor.
 
         **`filename`**: Name of netCDF file to hold dataset. Can also
         be a python 3 pathlib instance or the URL of an OpenDAP dataset.  When memory is
@@ -2510,7 +2510,7 @@ is the Dataset open or closed?
         """
 **`sync(self)`**
 
-Writes all buffered data in the [Dataset](#Dataset) to the disk file."""
+Writes all buffered data in the `Dataset` to the disk file."""
         _ensure_nc_success(nc_sync(self._grpid))
 
     def _redef(self):
@@ -2525,7 +2525,7 @@ Writes all buffered data in the [Dataset](#Dataset) to the disk file."""
         """
 **`set_fill_on(self)`**
 
-Sets the fill mode for a [Dataset](#Dataset) open for writing to `on`.
+Sets the fill mode for a `Dataset` open for writing to `on`.
 
 This causes data to be pre-filled with fill values. The fill values can be
 controlled by the variable's `_Fill_Value` attribute, but is usually
@@ -2541,7 +2541,7 @@ to."""
         """
 **`set_fill_off(self)`**
 
-Sets the fill mode for a [Dataset](#Dataset) open for writing to `off`.
+Sets the fill mode for a `Dataset` open for writing to `off`.
 
 This will prevent the data from being pre-filled with fill values, which
 may result in some performance improvements. However, you must then make
@@ -2557,11 +2557,11 @@ Creates a new dimension with the given `dimname` and `size`.
 
 `size` must be a positive integer or `None`, which stands for
 "unlimited" (default is `None`). Specifying a size of 0 also
-results in an unlimited dimension. The return value is the [Dimension](#Dimension)
+results in an unlimited dimension. The return value is the `Dimension`
 class instance describing the new dimension.  To determine the current
-maximum size of the dimension, use the `len` function on the [Dimension](#Dimension)
+maximum size of the dimension, use the `len` function on the `Dimension`
 instance. To determine if a dimension is 'unlimited', use the
-[Dimension.isunlimited](#Dimension.isunlimited) method of the [Dimension](#Dimension) instance."""
+[Dimension.isunlimited](#Dimension.isunlimited) method of the `Dimension` instance."""
         self.dimensions[dimname] = Dimension(self, dimname, size=size)
         return self.dimensions[dimname]
 
@@ -2569,7 +2569,7 @@ instance. To determine if a dimension is 'unlimited', use the
         """
 **`renameDimension(self, oldname, newname)`**
 
-rename a [Dimension](#Dimension) named `oldname` to `newname`."""
+rename a `Dimension` named `oldname` to `newname`."""
         cdef char *namstring
         bytestr = _strencode(newname)
         namstring = bytestr
@@ -2601,7 +2601,7 @@ dtype object `datatype`.
 are homogeneous numeric data types), then the 'inner' compound types **must** be
 created first.
 
-The return value is the [CompoundType](#CompoundType) class instance describing the new
+The return value is the `CompoundType` class instance describing the new
 datatype."""
         self.cmptypes[datatype_name] = CompoundType(self, datatype,\
                 datatype_name)
@@ -2658,7 +2658,7 @@ Supported specifiers include: `'S1' or 'c' (NC_CHAR), 'i1' or 'b' or 'B'
 (NC_BYTE), 'u1' (NC_UBYTE), 'i2' or 'h' or 's' (NC_SHORT), 'u2'
 (NC_USHORT), 'i4' or 'i' or 'l' (NC_INT), 'u4' (NC_UINT), 'i8' (NC_INT64),
 'u8' (NC_UINT64), 'f4' or 'f' (NC_FLOAT), 'f8' or 'd' (NC_DOUBLE)`.
-`datatype` can also be a [CompoundType](#CompoundType) instance
+`datatype` can also be a `CompoundType` instance
 (for a structured, or compound array), a [VLType](#VLType) instance
 (for a variable-length array), or the python `str` builtin
 (for a variable-length string array). Numpy string and unicode datatypes with
@@ -2735,17 +2735,17 @@ persists as long as the Dataset is open - you can use the set_var_chunk_cache
 method to change it the next time the Dataset is opened.
 Warning - messing with this parameter can seriously degrade performance.
 
-The return value is the [Variable](#Variable) class instance describing the new
+The return value is the `Variable` class instance describing the new
 variable.
 
 A list of names corresponding to netCDF variable attributes can be
-obtained with the [Variable](#Variable) method `Variable.ncattrs`. A dictionary
+obtained with the `Variable` method `Variable.ncattrs`. A dictionary
 containing all the netCDF attribute name/value pairs is provided by
-the `__dict__` attribute of a [Variable](#Variable) instance.
+the `__dict__` attribute of a `Variable` instance.
 
-[Variable](#Variable) instances behave much like array objects. Data can be
+`Variable` instances behave much like array objects. Data can be
 assigned to or retrieved from a variable with indexing and slicing
-operations on the [Variable](#Variable) instance. A [Variable](#Variable) instance has six
+operations on the `Variable` instance. A `Variable` instance has six
 Dataset standard attributes: `dimensions, dtype, shape, ndim, name` and
 `least_significant_digit`. Application programs should never modify
 these attributes. The `dimensions` attribute is a tuple containing the
@@ -2756,7 +2756,7 @@ sizes of all the variable's dimensions. The `name` attribute is a
 string containing the name of the Variable instance.
 The `least_significant_digit`
 attributes describes the power of ten of the smallest decimal place in
-the data the contains a reliable value.  assigned to the [Variable](#Variable)
+the data the contains a reliable value.  assigned to the `Variable`
 instance. If `None`, the data is not truncated. The `ndim` attribute
 is the number of variable dimensions."""
         # if varname specified as a path, split out group names.
@@ -2779,7 +2779,7 @@ is the number of variable dimensions."""
         """
 **`renameVariable(self, oldname, newname)`**
 
-rename a [Variable](#Variable) named `oldname` to `newname`"""
+rename a `Variable` named `oldname` to `newname`"""
         cdef char *namstring
         try:
             var = self.variables[oldname]
@@ -2801,7 +2801,7 @@ rename a [Variable](#Variable) named `oldname` to `newname`"""
         """
 **`createGroup(self, groupname)`**
 
-Creates a new [Group](#Group) with the given `groupname`.
+Creates a new `Group` with the given `groupname`.
 
 If `groupname` is specified as a path, using forward slashes as in unix to
 separate components, then intermediate groups will be created as necessary
@@ -2811,7 +2811,7 @@ separate components, then intermediate groups will be created as necessary
 If the specified path describes a group that already exists, no error is
 raised.
 
-The return value is a [Group](#Group) class instance."""
+The return value is a `Group` class instance."""
         # if group specified as a path, split out group names
         groupname = posixpath.normpath(groupname)
         nestedgroups = groupname.split('/')
@@ -2831,7 +2831,7 @@ The return value is a [Group](#Group) class instance."""
         """
 **`ncattrs(self)`**
 
-return netCDF global attribute names for this [Dataset](#Dataset) or [Group](#Group) in a list."""
+return netCDF global attribute names for this `Dataset` or `Group` in a list."""
         return _get_att_names(self._grpid, NC_GLOBAL)
 
     def setncattr(self,name,value):
@@ -2948,7 +2948,7 @@ attributes."""
         """
 **`renameAttribute(self, oldname, newname)`**
 
-rename a [Dataset](#Dataset) or [Group](#Group) attribute named `oldname` to `newname`."""
+rename a `Dataset` or `Group` attribute named `oldname` to `newname`."""
         cdef char *oldnamec
         cdef char *newnamec
         bytestr = _strencode(oldname)
@@ -2961,7 +2961,7 @@ rename a [Dataset](#Dataset) or [Group](#Group) attribute named `oldname` to `ne
         """
 **`renameGroup(self, oldname, newname)`**
 
-rename a [Group](#Group) named `oldname` to `newname` (requires netcdf >= 4.3.1)."""
+rename a `Group` named `oldname` to `newname` (requires netcdf >= 4.3.1)."""
         cdef char *newnamec
         IF HAS_RENAME_GRP:
             bytestr = _strencode(newname)
@@ -2985,8 +2985,8 @@ version 4.3.1 or higher of the netcdf C lib, and rebuild netcdf4-python."""
         """
 **`set_auto_chartostring(self, True_or_False)`**
 
-Call `Variable.set_auto_chartostring` for all variables contained in this [Dataset](#Dataset) or
-[Group](#Group), as well as for all variables in all its subgroups.
+Call `Variable.set_auto_chartostring` for all variables contained in this `Dataset` or
+`Group`, as well as for all variables in all its subgroups.
 
 **`True_or_False`**: Boolean determining if automatic conversion of
 all character arrays <--> string arrays should be performed for
@@ -3013,8 +3013,8 @@ after calling this function will follow the default behaviour.
         """
 **`set_auto_maskandscale(self, True_or_False)`**
 
-Call `Variable.set_auto_maskandscale` for all variables contained in this [Dataset](#Dataset) or
-[Group](#Group), as well as for all variables in all its subgroups.
+Call `Variable.set_auto_maskandscale` for all variables contained in this `Dataset` or
+`Group`, as well as for all variables in all its subgroups.
 
 **`True_or_False`**: Boolean determining if automatic conversion to masked arrays
 and variable scaling shall be applied for all variables.
@@ -3040,8 +3040,8 @@ after calling this function will follow the default behaviour.
         """
 **`set_auto_mask(self, True_or_False)`**
 
-Call `Variable.set_auto_mask` for all variables contained in this [Dataset](#Dataset) or
-[Group](#Group), as well as for all variables in all its subgroups.
+Call `Variable.set_auto_mask` for all variables contained in this `Dataset` or
+`Group`, as well as for all variables in all its subgroups.
 
 **`True_or_False`**: Boolean determining if automatic conversion to masked arrays
 shall be applied for all variables.
@@ -3066,8 +3066,8 @@ after calling this function will follow the default behaviour.
         """
 **`set_auto_scale(self, True_or_False)`**
 
-Call `Variable.set_auto_scale` for all variables contained in this [Dataset](#Dataset) or
-[Group](#Group), as well as for all variables in all its subgroups.
+Call `Variable.set_auto_scale` for all variables contained in this `Dataset` or
+`Group`, as well as for all variables in all its subgroups.
 
 **`True_or_False`**: Boolean determining if automatic variable scaling
 shall be applied for all variables.
@@ -3093,7 +3093,7 @@ after calling this function will follow the default behaviour.
 **`set_always_mask(self, True_or_False)`**
 
 Call `Variable.set_always_mask` for all variables contained in
-this [Dataset](#Dataset) or [Group](#Group), as well as for all
+this `Dataset` or `Group`, as well as for all
 variables in all its subgroups.
 
 **`True_or_False`**: Boolean determining if automatic conversion of
@@ -3124,7 +3124,7 @@ the default behaviour.
 **`set_ncstring_attrs(self, True_or_False)`**
 
 Call `Variable.set_ncstring_attrs` for all variables contained in
-this [Dataset](#Dataset) or [Group](#Group), as well as for all its
+this `Dataset` or `Group`, as well as for all its
 subgroups and their variables.
 
 **`True_or_False`**: Boolean determining if all string attributes are
@@ -3288,14 +3288,14 @@ text representation of Dataset. Requires `ncdump` to be installed and in `$PATH`
 cdef class Group(Dataset):
     """
 Groups define a hierarchical namespace within a netCDF file. They are
-analogous to directories in a unix filesystem. Each [Group](#Group) behaves like
-a [Dataset](#Dataset) within a Dataset, and can contain it's own variables,
+analogous to directories in a unix filesystem. Each `Group` behaves like
+a `Dataset` within a Dataset, and can contain it's own variables,
 dimensions and attributes (and other Groups). See [Group.__init__](#Group.__init__)
 for more details.
 
-[Group](#Group) inherits from [Dataset](#Dataset), so all the
-[Dataset](#Dataset) class methods and variables are available
-to a [Group](#Group) instance (except the `close` method).
+`Group` inherits from `Dataset`, so all the
+`Dataset` class methods and variables are available
+to a `Group` instance (except the `close` method).
 
 Additional read-only class variables:
 
@@ -3304,16 +3304,16 @@ Additional read-only class variables:
     def __init__(self, parent, name, **kwargs):
         """
         **`__init__(self, parent, name)`**
-        [Group](#Group) constructor.
+        `Group` constructor.
 
-        **`parent`**: [Group](#Group) instance for the parent group.  If being created
-        in the root group, use a [Dataset](#Dataset) instance.
+        **`parent`**: `Group` instance for the parent group.  If being created
+        in the root group, use a `Dataset` instance.
 
         **`name`**: - Name of the group.
 
-        ***Note***: [Group](#Group) instances should be created using the
-        `Dataset.createGroup` method of a [Dataset](#Dataset) instance, or
-        another [Group](#Group) instance, not using this class directly.
+        ***Note***: `Group` instances should be created using the
+        `Dataset.createGroup` method of a `Dataset` instance, or
+        another `Group` instance, not using this class directly.
         """
         cdef char *groupname
         # flag to indicate that Variables in this Group support orthogonal indexing.
@@ -3363,28 +3363,28 @@ Additional read-only class variables:
         """
 **`close(self)`**
 
-overrides [Dataset](#Dataset) close method which does not apply to [Group](#Group)
+overrides `Dataset` close method which does not apply to `Group`
 instances, raises IOError."""
-        raise IOError('cannot close a [Group](#Group) (only applies to Dataset)')
+        raise IOError('cannot close a `Group` (only applies to Dataset)')
 
 
 cdef class Dimension:
     """
-A netCDF [Dimension](#Dimension) is used to describe the coordinates of a [Variable](#Variable).
+A netCDF `Dimension` is used to describe the coordinates of a `Variable`.
 See [Dimension.__init__](#Dimension.__init__) for more details.
 
-The current maximum size of a [Dimension](#Dimension) instance can be obtained by
-calling the python `len` function on the [Dimension](#Dimension) instance. The
-[Dimension.isunlimited](#Dimension.isunlimited) method of a [Dimension](#Dimension) instance can be used to
+The current maximum size of a `Dimension` instance can be obtained by
+calling the python `len` function on the `Dimension` instance. The
+[Dimension.isunlimited](#Dimension.isunlimited) method of a `Dimension` instance can be used to
 determine if the dimension is unlimited.
 
 Read-only class variables:
 
-**`name`**: String name, used when creating a [Variable](#Variable) with
+**`name`**: String name, used when creating a `Variable` with
 `Dataset.createVariable`.
 
-**`size`**: Current [Dimension](#Dimension) size (same as `len(d)`, where `d` is a
-[Dimension](#Dimension) instance).
+**`size`**: Current `Dimension` size (same as `len(d)`, where `d` is a
+`Dimension` instance).
     """
     cdef public int _dimid, _grpid
     cdef public _data_model, _name, _grp
@@ -3393,17 +3393,17 @@ Read-only class variables:
         """
         **`__init__(self, group, name, size=None)`**
 
-        [Dimension](#Dimension) constructor.
+        `Dimension` constructor.
 
-        **`group`**: [Group](#Group) instance to associate with dimension.
+        **`group`**: `Group` instance to associate with dimension.
 
         **`name`**: Name of the dimension.
 
         **`size`**: Size of the dimension. `None` or 0 means unlimited. (Default `None`).
 
-        ***Note***: [Dimension](#Dimension) instances should be created using the
-        `Dataset.createDimension` method of a [Group](#Group) or
-        [Dataset](#Dataset) instance, not using [Dimension.__init__](#Dimension.__init__) directly.
+        ***Note***: `Dimension` instances should be created using the
+        `Dataset.createDimension` method of a `Group` or
+        `Dataset` instance, not using [Dimension.__init__](#Dimension.__init__) directly.
         """
         cdef int ierr
         cdef char *dimname
@@ -3469,7 +3469,7 @@ Read-only class variables:
                 (type(self), self._name, len(self))
 
     def __len__(self):
-        # len([Dimension](#Dimension) instance) returns current size of dimension
+        # len(`Dimension` instance) returns current size of dimension
         cdef int ierr
         cdef size_t lengthp
         with nogil:
@@ -3481,14 +3481,14 @@ Read-only class variables:
         """
 **`group(self)`**
 
-return the group that this [Dimension](#Dimension) is a member of."""
+return the group that this `Dimension` is a member of."""
         return self._grp
 
     def isunlimited(self):
         """
 **`isunlimited(self)`**
 
-returns `True` if the [Dimension](#Dimension) instance is unlimited, `False` otherwise."""
+returns `True` if the `Dimension` instance is unlimited, `False` otherwise."""
         cdef int ierr, n, numunlimdims, ndims, nvars, ngatts, xdimid
         cdef int *unlimdimids
         if self._data_model == 'NETCDF4':
@@ -3521,16 +3521,16 @@ returns `True` if the [Dimension](#Dimension) instance is unlimited, `False` oth
 
 cdef class Variable:
     """
-A netCDF [Variable](#Variable) is used to read and write netCDF data.  They are
+A netCDF `Variable` is used to read and write netCDF data.  They are
 analogous to numpy array objects. See `Variable.__init__` for more
 details.
 
 A list of attribute names corresponding to netCDF attributes defined for
 the variable can be obtained with the `Variable.ncattrs` method. These
 attributes can be created by assigning to an attribute of the
-[Variable](#Variable) instance. A dictionary containing all the netCDF attribute
+`Variable` instance. A dictionary containing all the netCDF attribute
 name/value pairs is provided by the `__dict__` attribute of a
-[Variable](#Variable) instance.
+`Variable` instance.
 
 The following class variables are read-only:
 
@@ -3562,7 +3562,7 @@ Default is `True`, can be reset using
 
 **`least_significant_digit`**: Describes the power of ten of the
 smallest decimal place in the data the contains a reliable value.  Data is
-truncated to this decimal place when it is assigned to the [Variable](#Variable)
+truncated to this decimal place when it is assigned to the `Variable`
 instance. If `None`, the data is not truncated.
 
 **`__orthogonal_indexing__`**: Always `True`.  Indicates to client code
@@ -3592,13 +3592,13 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         chunksizes=None, endian='native',
         least_significant_digit=None,fill_value=None,chunk_cache=None)`**
 
-        [Variable](#Variable) constructor.
+        `Variable` constructor.
 
-        **`group`**: [Group](#Group) or [Dataset](#Dataset) instance to associate with variable.
+        **`group`**: `Group` or `Dataset` instance to associate with variable.
 
         **`name`**: Name of the variable.
 
-        **`datatype`**: [Variable](#Variable) data type. Can be specified by providing a
+        **`datatype`**: `Variable` data type. Can be specified by providing a
         numpy dtype object, or a string that describes a numpy dtype object.
         Supported values, corresponding to `str` attribute of numpy dtype
         objects, include `'f4'` (32-bit floating point), `'f8'` (64-bit floating
@@ -3611,7 +3611,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         typecodes can also be used (`'f'` instead of `'f4'`, `'d'` instead of
         `'f8'`, `'h'` or `'s'` instead of `'i2'`, `'b'` or `'B'` instead of
         `'i1'`, `'c'` instead of `'S1'`, and `'i'` or `'l'` instead of
-        `'i4'`). `datatype` can also be a [CompoundType](#CompoundType) instance
+        `'i4'`). `datatype` can also be a `CompoundType` instance
         (for a structured, or compound array), a [VLType](#VLType) instance
         (for a variable-length array), or the python `str` builtin
         (for a variable-length string array). Numpy string and unicode datatypes with
@@ -3621,7 +3621,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         (defined previously with `createDimension`). Default is an empty tuple
         which means the variable is a scalar (and therefore has no dimensions).
 
-        **`zlib`**: if `True`, data assigned to the [Variable](#Variable)
+        **`zlib`**: if `True`, data assigned to the `Variable`
         instance is compressed on disk. Default `False`.
 
         **`complevel`**: the level of zlib compression to use (1 is the fastest,
@@ -3676,9 +3676,9 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         Persists as long as Dataset is open. Use [set_var_chunk_cache](#set_var_chunk_cache) to 
         change it when Dataset is re-opened. 
 
-        ***Note***: [Variable](#Variable) instances should be created using the
-        `Dataset.createVariable` method of a [Dataset](#Dataset) or
-        [Group](#Group) instance, not using this class directly.
+        ***Note***: `Variable` instances should be created using the
+        `Dataset.createVariable` method of a `Dataset` or
+        `Group` instance, not using this class directly.
         """
         cdef int ierr, ndims, icontiguous, ideflate_level, numdims, _grpid
         cdef char namstring[NC_MAX_NAME+1]
@@ -4107,14 +4107,14 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         """
 **`group(self)`**
 
-return the group that this [Variable](#Variable) is a member of."""
+return the group that this `Variable` is a member of."""
         return self._grp
 
     def ncattrs(self):
         """
 **`ncattrs(self)`**
 
-return netCDF attribute names for this [Variable](#Variable) in a list."""
+return netCDF attribute names for this `Variable` in a list."""
         return _get_att_names(self._grpid, self._varid)
 
     def setncattr(self,name,value):
@@ -4375,7 +4375,7 @@ details."""
         """
 **`renameAttribute(self, oldname, newname)`**
 
-rename a [Variable](#Variable) attribute named `oldname` to `newname`."""
+rename a `Variable` attribute named `oldname` to `newname`."""
         cdef int ierr
         cdef char *oldnamec
         cdef char *newnamec
@@ -5478,8 +5478,8 @@ open for parallel access.
         """
 **`get_dims(self)`**
 
-return a tuple of [Dimension](#Dimension) instances associated with this
-[Variable](#Variable).
+return a tuple of `Dimension` instances associated with this
+`Variable`.
         """
         return tuple(_find_dim(self._grp, dim) for dim in self.dimensions)
 
@@ -5491,9 +5491,9 @@ return a tuple of [Dimension](#Dimension) instances associated with this
 
 cdef class CompoundType:
     """
-A [CompoundType](#CompoundType) instance is used to describe a compound data
+A `CompoundType` instance is used to describe a compound data
 type, and can be passed to the the `Dataset.createVariable` method of
-a [Dataset](#Dataset) or [Group](#Group) instance.
+a `Dataset` or `Group` instance.
 Compound data types map to numpy structured arrays.
 See [CompoundType.__init__](#CompoundType.__init__) for more details.
 
@@ -5508,7 +5508,7 @@ the user.
 
         CompoundType constructor.
 
-        **`group`**: [Group](#Group) instance to associate with the compound datatype.
+        **`group`**: `Group` instance to associate with the compound datatype.
 
         **`datatype`**: A numpy dtype object describing a structured (a.k.a record)
         array.  Can be composed of homogeneous numeric or character data types, or
@@ -5522,9 +5522,9 @@ the user.
         instances (so create CompoundType instances for the innermost structures
         first).
 
-        ***Note 2***: [CompoundType](#CompoundType) instances should be created using the
-        `Dataset.createCompoundType` method of a [Dataset](#Dataset) or
-        [Group](#Group) instance, not using this class directly.
+        ***Note 2***: `CompoundType` instances should be created using the
+        `Dataset.createCompoundType` method of a `Dataset` or
+        `Group` instance, not using this class directly.
         """
         cdef nc_type xtype
         # convert dt to a numpy datatype object
@@ -5798,7 +5798,7 @@ cdef class VLType:
     """
 A [VLType](#VLType) instance is used to describe a variable length (VLEN) data
 type, and can be passed to the the `Dataset.createVariable` method of
-a [Dataset](#Dataset) or [Group](#Group) instance. See
+a `Dataset` or `Group` instance. See
 [VLType.__init__](#VLType.__init__)for more details.
 
 The instance variables `dtype` and `name` should not be modified by
@@ -5812,7 +5812,7 @@ the user.
 
         VLType constructor.
 
-        **`group`**: [Group](#Group) instance to associate with the VLEN datatype.
+        **`group`**: `Group` instance to associate with the VLEN datatype.
 
         **`datatype`**: An numpy dtype object describing the component type for the
         variable length array.
@@ -5821,8 +5821,8 @@ the user.
         VLEN data type.
 
         ***`Note`***: [VLType](#VLType) instances should be created using the
-        `Dataset.createVLType` method of a [Dataset](#Dataset) or
-        [Group](#Group) instance, not using this class directly.
+        `Dataset.createVLType` method of a `Dataset` or
+        `Group` instance, not using this class directly.
         """
         cdef nc_type xtype
         if 'typeid' in kwargs:
@@ -5907,7 +5907,7 @@ cdef class EnumType:
     """
 A [EnumType](#EnumType) instance is used to describe an Enum data
 type, and can be passed to the the `Dataset.createVariable` method of
-a [Dataset](#Dataset) or [Group](#Group) instance. See
+a `Dataset` or `Group` instance. See
 [EnumType.__init__](#EnumType.__init__) for more details.
 
 The instance variables `dtype`, `name` and `enum_dict` should not be modified by
@@ -5921,7 +5921,7 @@ the user.
 
         EnumType constructor.
 
-        **`group`**: [Group](#Group) instance to associate with the VLEN datatype.
+        **`group`**: `Group` instance to associate with the VLEN datatype.
 
         **`datatype`**: An numpy integer dtype object describing the base type
         for the Enum.
@@ -5933,8 +5933,8 @@ the user.
         pairs.
 
         ***`Note`***: [EnumType](#EnumType) instances should be created using the
-        `Dataset.createEnumType` method of a [Dataset](#Dataset) or
-        [Group](#Group) instance, not using this class directly.
+        `Dataset.createEnumType` method of a `Dataset` or
+        `Group` instance, not using this class directly.
         """
         cdef nc_type xtype
         if 'typeid' in kwargs:

From 61119556be03e29d4a0bb009654fb475d5d5e0a7 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 17 Feb 2021 07:58:32 -0700
Subject: [PATCH 0614/1504] update

---
 docs/index.html          | 68 ++++++++++++++++++++--------------------
 src/netCDF4/_netCDF4.pyx | 68 ++++++++++++++++++++--------------------
 2 files changed, 68 insertions(+), 68 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 177b66551..32813a0ac 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -735,7 +735,7 @@ 
    Dimensions in a netCDF file
    
 
 
    Using the python len function with a Dimension instance returns
 current size of that dimension.
-Dimension.isunlimited">Dimension.isunlimited method of a Dimension instance
+Dimension.isunlimited method of a Dimension instance
 be used to determine if the dimensions is unlimited, or appendable.
    
 
 
    >>> print(len(lon))
@@ -759,7 +759,7 @@ 
    Dimensions in a netCDF file
    
 
    
 
 
    Dimension names can be changed using the
-Datatset.renameDimension method of a Dataset or
+Datatset.renameDimension method of a Dataset or
 Group instance.
    
 
 
    Variables in a netCDF file
    
@@ -1065,9 +1065,9 @@ 
    Dealing with time coordinates
    
 
    Reading data from a multi-file netCDF dataset
    
 
 
    If you want to read data from a variable that spans multiple netCDF files,
-you can use the MFDataset class to read the data as if it were
+you can use the MFDataset class to read the data as if it were
 contained in a single file. Instead of using a single filename to create
-a Dataset instance, create a MFDataset instance with either a list
+a Dataset instance, create a MFDataset instance with either a list
 of filenames, or a string with a wildcard (which is then converted to
 a sorted list of files using the python glob module).
 Variables in the list of files that share the same unlimited
@@ -1085,7 +1085,7 @@ 
    Reading data from a multi
 ...         x[0:10] = np.arange(nf*10,10*(nf+1))
 
    
 
-
    Now read all the files back in at once with MFDataset
    
+
    Now read all the files back in at once with MFDataset
    
 
 
    >>> from netCDF4 import MFDataset
 >>> f = MFDataset("mftest*nc")
@@ -1097,7 +1097,7 @@ 
    Reading data from a multi
  96 97 98 99]
 
    
 
-
    Note that MFDataset can only be used to read, not write, multi-file
+
    Note that MFDataset can only be used to read, not write, multi-file
 datasets.
    
 
 
    Efficient compression of netCDF variables
    
@@ -1471,14 +1471,14 @@ 
    Dealing with strings
    
 To perform the conversion to and from character arrays to fixed-width numpy string arrays, the
 following convention is followed by the python interface.
 If the _Encoding special attribute is set for a character array
-(dtype S1) variable, the chartostring utility function is used to convert the array of
+(dtype S1) variable, the chartostring utility function is used to convert the array of
 characters to an array of strings with one less dimension (the last dimension is
 interpreted as the length of each string) when reading the data. The character
 set (usually ascii) is specified by the _Encoding attribute. If _Encoding
 is 'none' or 'bytes', then the character array is converted to a numpy
 fixed-width byte string array (dtype S#), otherwise a numpy unicode (dtype
 U#) array is created.  When writing the data,
-stringtochar is used to convert the numpy string array to an array of
+stringtochar is used to convert the numpy string array to an array of
 characters with one more dimension. For example,
    
 
 
    >>> from netCDF4 import stringtochar
@@ -1621,7 +1621,7 @@ 
    In-memory (diskless) Datasets
    
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
    
 
-
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
+
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
 
 
    copyright: 2008 by Jeffrey Whitaker.
    
 
@@ -1696,11 +1696,11 @@ 
    In-memory (diskless) Datasets
    
 
 
    vltypes: The vltypes dictionary maps the names of
 variable-length types defined for the Group or Dataset to instances
-of the VLType class.
    
+of the VLType class.
    
 
 
    enumtypes: The enumtypes dictionary maps the names of
 Enum types defined for the Group or Dataset to instances
-of the EnumType class.
    
+of the EnumType class.
    
 
 
    data_model: data_model describes the netCDF
 data model version, one of NETCDF3_CLASSIC, NETCDF4,
@@ -1962,7 +1962,7 @@ 
    In-memory (diskless) Datasets
    
 class instance describing the new dimension.  To determine the current
 maximum size of the dimension, use the len function on the Dimension
 instance. To determine if a dimension is 'unlimited', use the
-Dimension.isunlimited">Dimension.isunlimited method of the Dimension instance.
    
+Dimension.isunlimited method of the Dimension instance.
    
 
    
 
 
@@ -2022,7 +2022,7 @@ 
    In-memory (diskless) Datasets
    
 
    Creates a new VLEN data type named datatype_name from a numpy
 dtype object datatype.
    
 
-
    The return value is the VLType class instance describing the new
+
    The return value is the VLType class instance describing the new
 datatype.
    
 
    
 
@@ -2043,7 +2043,7 @@ 
    In-memory (diskless) Datasets
    
 integer dtype object datatype, and a python dictionary
 defining the enum fields and values.
    
 
-
    The return value is the EnumType class instance describing the new
+
    The return value is the EnumType class instance describing the new
 datatype.
    
 
    
 
@@ -2079,7 +2079,7 @@ 
    In-memory (diskless) Datasets
    
 (NC_USHORT), 'i4' or 'i' or 'l' (NC_INT), 'u4' (NC_UINT), 'i8' (NC_INT64),
 'u8' (NC_UINT64), 'f4' or 'f' (NC_FLOAT), 'f8' or 'd' (NC_DOUBLE)    .
 datatype can also be a CompoundType instance
-(for a structured, or compound array), a VLType instance
+(for a structured, or compound array), a VLType instance
 (for a variable-length array), or the python str builtin
 (for a variable-length string array). Numpy string and unicode datatypes with
 length greater than one are aliases for str.
    
@@ -2130,7 +2130,7 @@ 
    In-memory (diskless) Datasets
    
 
 
    The optional keyword fill_value can be used to override the default
 netCDF _FillValue (the value that the variable gets filled with before
-any data is written to it, defaults given in default_fillvals).
+any data is written to it, defaults given in the dict netCDF4.default_fillvals).
 If fill_value is set to False, then the variable is not pre-filled.
    
 
 
    If the optional keyword parameter least_significant_digit is
@@ -2823,7 +2823,7 @@ 
    In-memory (diskless) Datasets
    
 'f8', 'h' or 's' instead of 'i2', 'b' or 'B' instead of
 'i1', 'c' instead of 'S1', and 'i' or 'l' instead of
 'i4'). datatype can also be a CompoundType instance
-(for a structured, or compound array), a VLType instance
+(for a structured, or compound array), a VLType instance
 (for a variable-length array), or the python str builtin
 (for a variable-length string array). Numpy string and unicode datatypes with
 length greater than one are aliases for str.
    
@@ -2881,10 +2881,10 @@ 
    In-memory (diskless) Datasets
    
 value that the variable gets filled with before any data is written to it)
 is replaced with this value.  If fill_value is set to False, then
 the variable is not pre-filled. The default netCDF fill values can be found
-in default_fillvals.
    
+in the dictionary netCDF4.default_fillvals.
    
 
 
    chunk_cache: If specified, sets the chunk cache size for this variable.
-Persists as long as Dataset is open. Use set_var_chunk_cache to 
+Persists as long as Dataset is open. Use set_var_chunk_cache to 
 change it when Dataset is re-opened. 
    
 
 
    Note: Variable instances should be created using the
@@ -3545,11 +3545,11 @@ 
    In-memory (diskless) Datasets
    
 
         
             
    A netCDF Dimension is used to describe the coordinates of a Variable.
-See Dimension.__init__">Dimension.__init__ for more details.
    
+See Dimension.__init__ for more details.
    
 
 
    The current maximum size of a Dimension instance can be obtained by
 calling the python len function on the Dimension instance. The
-Dimension.isunlimited">Dimension.isunlimited method of a Dimension instance can be used to
+Dimension.isunlimited method of a Dimension instance can be used to
 determine if the dimension is unlimited.
    
 
 
    Read-only class variables:
    
@@ -3581,7 +3581,7 @@ 
    In-memory (diskless) Datasets
    
 
 
    Note: Dimension instances should be created using the
 Dataset.createDimension method of a Group or
-Dataset instance, not using Dimension.__init__">Dimension.__init__ directly.
    
+Dataset instance, not using Dimension.__init__ directly.
    
 
    
 
 
@@ -3650,7 +3650,7 @@ 
    In-memory (diskless) Datasets
    
             
    Groups define a hierarchical namespace within a netCDF file. They are
 analogous to directories in a unix filesystem. Each Group behaves like
 a Dataset within a Dataset, and can contain it's own variables,
-dimensions and attributes (and other Groups). See Group.__init__">Group.__init__
+dimensions and attributes (and other Groups). See Group.__init__
 for more details.
    
 
 
    Group inherits from Dataset, so all the
@@ -3771,7 +3771,7 @@ 
    Inherited Members
    
 
 
    Adapted from pycdf by Andre Gosselin.
    
 
-
    Example usage (See MFDataset.__init__">MFDataset.__init__ for more details):
    
+
    Example usage (See MFDataset.__init__ for more details):
    
 
 
    >>> import numpy as np
 >>> # create a series of netCDF files with a variable sharing
@@ -3932,7 +3932,7 @@ 
    Inherited Members
    
             
    Class providing an interface to a MFDataset time Variable by imposing a unique common
 time unit and/or calendar to all files.
    
 
-
    Example usage (See MFTime.__init__">MFTime.__init__ for more details):
    
+
    Example usage (See MFTime.__init__ for more details):
    
 
 
    >>> import numpy as np
 >>> f1 = Dataset("mftest_1.nc","w", format="NETCDF4_CLASSIC")
@@ -3975,7 +3975,7 @@ 
    Inherited Members
    
 
    Create a time Variable with units consistent across a multifile
 dataset.
    
 
-
    time: Time variable from a MFDataset.
    
+
    time: Time variable from a MFDataset.
    
 
 
    units: Time units, for example, 'days since 1979-01-01'. If None,
 use the units from the master variable.
    
@@ -4018,7 +4018,7 @@ 
    Inherited Members
    
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance.
 Compound data types map to numpy structured arrays.
-See CompoundType.__init__">CompoundType.__init__ for more details.
    
+See CompoundType.__init__ for more details.
    
 
 
    The instance variables dtype and name should not be modified by
 the user.
    
@@ -4095,10 +4095,10 @@ 
    Inherited Members
    
     
    
 
         
-            
    A VLType instance is used to describe a variable length (VLEN) data
+            
    A VLType instance is used to describe a variable length (VLEN) data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance. See
-VLType.__init__">VLType.__init__for more details.
    
+VLType.__init__ for more details.
    
 
 
    The instance variables dtype and name should not be modified by
 the user.
    
@@ -4124,7 +4124,7 @@ 
    Inherited Members
    
 
    datatype_name: a Python string containing a description of the
 VLEN data type.
    
 
-
    Note: VLType instances should be created using the
+
    Note: VLType instances should be created using the
 Dataset.createVLType method of a Dataset or
 Group instance, not using this class directly.
    
 
    
@@ -4399,10 +4399,10 @@ 
    Inherited Members
    
     
    
 
         
-            
    A EnumType instance is used to describe an Enum data
+            
    A EnumType instance is used to describe an Enum data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance. See
-EnumType.__init__">EnumType.__init__ for more details.
    
+EnumType.__init__ for more details.
    
 
 
    The instance variables dtype, name and enum_dict should not be modified by
 the user.
    
@@ -4431,7 +4431,7 @@ 
    Inherited Members
    
 
    enum_dict: a Python dictionary containing the Enum field/value
 pairs.
    
 
-
    Note: EnumType instances should be created using the
+
    Note: EnumType instances should be created using the
 Dataset.createEnumType method of a Dataset or
 Group instance, not using this class directly.
    
 
    
@@ -4479,7 +4479,7 @@ 
    Inherited Members
    
 
 
    return current netCDF chunk cache information in a tuple (size,nelems,preemption).
 See netcdf C library documentation for nc_get_chunk_cache for
-details. Values can be reset with set_chunk_cache.
    
+details. Values can be reset with set_chunk_cache.
    
 
    
 
 
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index d312a3234..17e54b696 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -280,7 +280,7 @@ All of the `Dimension` instances are stored in a python dictionary.
 
 Using the python `len` function with a `Dimension` instance returns
 current size of that dimension.
-[Dimension.isunlimited](#Dimension.isunlimited) method of a `Dimension` instance
+`Dimension.isunlimited` method of a `Dimension` instance
 be used to determine if the dimensions is unlimited, or appendable.
 
 ```python
@@ -306,7 +306,7 @@ and whether it is unlimited.
 ```
 
 `Dimension` names can be changed using the
-[Datatset.renameDimension](#Datatset.renameDimension) method of a `Dataset` or
+`Datatset.renameDimension` method of a `Dataset` or
 `Group` instance.
 
 ## Variables in a netCDF file
@@ -630,9 +630,9 @@ of a netCDF time variable corresponding to a sequence of datetime instances.
 ## Reading data from a multi-file netCDF dataset
 
 If you want to read data from a variable that spans multiple netCDF files,
-you can use the [MFDataset](#MFDataset) class to read the data as if it were
+you can use the `MFDataset` class to read the data as if it were
 contained in a single file. Instead of using a single filename to create
-a `Dataset` instance, create a [MFDataset](#MFDataset) instance with either a list
+a `Dataset` instance, create a `MFDataset` instance with either a list
 of filenames, or a string with a wildcard (which is then converted to
 a sorted list of files using the python glob module).
 Variables in the list of files that share the same unlimited
@@ -651,7 +651,7 @@ datasets are not supported).
 ...         x[0:10] = np.arange(nf*10,10*(nf+1))
 ```
 
-Now read all the files back in at once with [MFDataset](#MFDataset)
+Now read all the files back in at once with `MFDataset`
 
 ```python
 >>> from netCDF4 import MFDataset
@@ -664,7 +664,7 @@ Now read all the files back in at once with [MFDataset](#MFDataset)
  96 97 98 99]
 ```
 
-Note that [MFDataset](#MFDataset) can only be used to read, not write, multi-file
+Note that `MFDataset` can only be used to read, not write, multi-file
 datasets.
 
 ## Efficient compression of netCDF variables
@@ -1049,14 +1049,14 @@ characters](https://www.unidata.ucar.edu/software/netcdf/docs/BestPractices.html
 To perform the conversion to and from character arrays to fixed-width numpy string arrays, the
 following convention is followed by the python interface.
 If the `_Encoding` special attribute is set for a character array
-(dtype `S1`) variable, the [chartostring](#chartostring) utility function is used to convert the array of
+(dtype `S1`) variable, the `chartostring` utility function is used to convert the array of
 characters to an array of strings with one less dimension (the last dimension is
 interpreted as the length of each string) when reading the data. The character
 set (usually ascii) is specified by the `_Encoding` attribute. If `_Encoding`
 is 'none' or 'bytes', then the character array is converted to a numpy
 fixed-width byte string array (dtype `S#`), otherwise a numpy unicode (dtype
 `U#`) array is created.  When writing the data,
-[stringtochar](#stringtochar) is used to convert the numpy string array to an array of
+`stringtochar` is used to convert the numpy string array to an array of
 characters with one more dimension. For example,
 
 ```python
@@ -1281,7 +1281,7 @@ def get_chunk_cache():
 
 return current netCDF chunk cache information in a tuple (size,nelems,preemption).
 See netcdf C library documentation for `nc_get_chunk_cache` for
-details. Values can be reset with [set_chunk_cache](#set_chunk_cache)."""
+details. Values can be reset with `set_chunk_cache`."""
     cdef int ierr
     cdef size_t sizep, nelemsp
     cdef float preemptionp
@@ -1681,7 +1681,7 @@ be raised in the next release."""
 
 cdef _get_types(group):
     # Private function to create `CompoundType`,
-    # [VLType](#VLType) or [EnumType](#EnumType) instances for all the
+    # `VLType` or `EnumType` instances for all the
     # compound, VLEN or Enum types in a `Group` or `Dataset`.
     cdef int ierr, ntypes, classp, n, _grpid
     cdef nc_type xtype
@@ -1996,11 +1996,11 @@ compound types defined for the `Group` or `Dataset` to instances of the
 
 **`vltypes`**: The `vltypes` dictionary maps the names of
 variable-length types defined for the `Group` or `Dataset` to instances
-of the [VLType](#VLType) class.
+of the `VLType` class.
 
 **`enumtypes`**: The `enumtypes` dictionary maps the names of
 Enum types defined for the `Group` or `Dataset` to instances
-of the [EnumType](#EnumType) class.
+of the `EnumType` class.
 
 **`data_model`**: `data_model` describes the netCDF
 data model version, one of `NETCDF3_CLASSIC`, `NETCDF4`,
@@ -2561,7 +2561,7 @@ results in an unlimited dimension. The return value is the `Dimension`
 class instance describing the new dimension.  To determine the current
 maximum size of the dimension, use the `len` function on the `Dimension`
 instance. To determine if a dimension is 'unlimited', use the
-[Dimension.isunlimited](#Dimension.isunlimited) method of the `Dimension` instance."""
+`Dimension.isunlimited` method of the `Dimension` instance."""
         self.dimensions[dimname] = Dimension(self, dimname, size=size)
         return self.dimensions[dimname]
 
@@ -2614,7 +2614,7 @@ datatype."""
 Creates a new VLEN data type named `datatype_name` from a numpy
 dtype object `datatype`.
 
-The return value is the [VLType](#VLType) class instance describing the new
+The return value is the `VLType` class instance describing the new
 datatype."""
         self.vltypes[datatype_name] = VLType(self, datatype, datatype_name)
         return self.vltypes[datatype_name]
@@ -2627,7 +2627,7 @@ Creates a new Enum data type named `datatype_name` from a numpy
 integer dtype object `datatype`, and a python dictionary
 defining the enum fields and values.
 
-The return value is the [EnumType](#EnumType) class instance describing the new
+The return value is the `EnumType` class instance describing the new
 datatype."""
         self.enumtypes[datatype_name] = EnumType(self, datatype, datatype_name,
                 enum_dict)
@@ -2659,7 +2659,7 @@ Supported specifiers include: `'S1' or 'c' (NC_CHAR), 'i1' or 'b' or 'B'
 (NC_USHORT), 'i4' or 'i' or 'l' (NC_INT), 'u4' (NC_UINT), 'i8' (NC_INT64),
 'u8' (NC_UINT64), 'f4' or 'f' (NC_FLOAT), 'f8' or 'd' (NC_DOUBLE)`.
 `datatype` can also be a `CompoundType` instance
-(for a structured, or compound array), a [VLType](#VLType) instance
+(for a structured, or compound array), a `VLType` instance
 (for a variable-length array), or the python `str` builtin
 (for a variable-length string array). Numpy string and unicode datatypes with
 length greater than one are aliases for `str`.
@@ -2710,7 +2710,7 @@ keywords are silently ignored for netCDF 3 files that do not use HDF5.
 
 The optional keyword `fill_value` can be used to override the default
 netCDF `_FillValue` (the value that the variable gets filled with before
-any data is written to it, defaults given in [default_fillvals](#default_fillvals)).
+any data is written to it, defaults given in the dict `netCDF4.default_fillvals`).
 If fill_value is set to `False`, then the variable is not pre-filled.
 
 If the optional keyword parameter `least_significant_digit` is
@@ -3290,7 +3290,7 @@ cdef class Group(Dataset):
 Groups define a hierarchical namespace within a netCDF file. They are
 analogous to directories in a unix filesystem. Each `Group` behaves like
 a `Dataset` within a Dataset, and can contain it's own variables,
-dimensions and attributes (and other Groups). See [Group.__init__](#Group.__init__)
+dimensions and attributes (and other Groups). See `Group.__init__`
 for more details.
 
 `Group` inherits from `Dataset`, so all the
@@ -3371,11 +3371,11 @@ instances, raises IOError."""
 cdef class Dimension:
     """
 A netCDF `Dimension` is used to describe the coordinates of a `Variable`.
-See [Dimension.__init__](#Dimension.__init__) for more details.
+See `Dimension.__init__` for more details.
 
 The current maximum size of a `Dimension` instance can be obtained by
 calling the python `len` function on the `Dimension` instance. The
-[Dimension.isunlimited](#Dimension.isunlimited) method of a `Dimension` instance can be used to
+`Dimension.isunlimited` method of a `Dimension` instance can be used to
 determine if the dimension is unlimited.
 
 Read-only class variables:
@@ -3403,7 +3403,7 @@ Read-only class variables:
 
         ***Note***: `Dimension` instances should be created using the
         `Dataset.createDimension` method of a `Group` or
-        `Dataset` instance, not using [Dimension.__init__](#Dimension.__init__) directly.
+        `Dataset` instance, not using `Dimension.__init__` directly.
         """
         cdef int ierr
         cdef char *dimname
@@ -3612,7 +3612,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         `'f8'`, `'h'` or `'s'` instead of `'i2'`, `'b'` or `'B'` instead of
         `'i1'`, `'c'` instead of `'S1'`, and `'i'` or `'l'` instead of
         `'i4'`). `datatype` can also be a `CompoundType` instance
-        (for a structured, or compound array), a [VLType](#VLType) instance
+        (for a structured, or compound array), a `VLType` instance
         (for a variable-length array), or the python `str` builtin
         (for a variable-length string array). Numpy string and unicode datatypes with
         length greater than one are aliases for `str`.
@@ -3670,10 +3670,10 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         value that the variable gets filled with before any data is written to it)
         is replaced with this value.  If fill_value is set to `False`, then
         the variable is not pre-filled. The default netCDF fill values can be found
-        in [default_fillvals](#default_fillvals).
+        in the dictionary `netCDF4.default_fillvals`.
       
         **`chunk_cache`**: If specified, sets the chunk cache size for this variable.
-        Persists as long as Dataset is open. Use [set_var_chunk_cache](#set_var_chunk_cache) to 
+        Persists as long as Dataset is open. Use `set_var_chunk_cache` to 
         change it when Dataset is re-opened. 
 
         ***Note***: `Variable` instances should be created using the
@@ -5495,7 +5495,7 @@ A `CompoundType` instance is used to describe a compound data
 type, and can be passed to the the `Dataset.createVariable` method of
 a `Dataset` or `Group` instance.
 Compound data types map to numpy structured arrays.
-See [CompoundType.__init__](#CompoundType.__init__) for more details.
+See `CompoundType.__init__` for more details.
 
 The instance variables `dtype` and `name` should not be modified by
 the user.
@@ -5796,10 +5796,10 @@ cdef _read_compound(group, nc_type xtype, endian=None):
 
 cdef class VLType:
     """
-A [VLType](#VLType) instance is used to describe a variable length (VLEN) data
+A `VLType` instance is used to describe a variable length (VLEN) data
 type, and can be passed to the the `Dataset.createVariable` method of
 a `Dataset` or `Group` instance. See
-[VLType.__init__](#VLType.__init__)for more details.
+`VLType.__init__` for more details.
 
 The instance variables `dtype` and `name` should not be modified by
 the user.
@@ -5820,7 +5820,7 @@ the user.
         **`datatype_name`**: a Python string containing a description of the
         VLEN data type.
 
-        ***`Note`***: [VLType](#VLType) instances should be created using the
+        ***`Note`***: `VLType` instances should be created using the
         `Dataset.createVLType` method of a `Dataset` or
         `Group` instance, not using this class directly.
         """
@@ -5905,10 +5905,10 @@ cdef _read_vlen(group, nc_type xtype, endian=None):
 
 cdef class EnumType:
     """
-A [EnumType](#EnumType) instance is used to describe an Enum data
+A `EnumType` instance is used to describe an Enum data
 type, and can be passed to the the `Dataset.createVariable` method of
 a `Dataset` or `Group` instance. See
-[EnumType.__init__](#EnumType.__init__) for more details.
+`EnumType.__init__` for more details.
 
 The instance variables `dtype`, `name` and `enum_dict` should not be modified by
 the user.
@@ -5932,7 +5932,7 @@ the user.
         **`enum_dict`**: a Python dictionary containing the Enum field/value
         pairs.
 
-        ***`Note`***: [EnumType](#EnumType) instances should be created using the
+        ***`Note`***: `EnumType` instances should be created using the
         `Dataset.createEnumType` method of a `Dataset` or
         `Group` instance, not using this class directly.
         """
@@ -6123,7 +6123,7 @@ or NETCDF3_64BIT_DATA` format (`NETCDF4` Datasets won't work).
 
 Adapted from [pycdf](http://pysclint.sourceforge.net/pycdf) by Andre Gosselin.
 
-Example usage (See [MFDataset.__init__](#MFDataset.__init__) for more details):
+Example usage (See `MFDataset.__init__` for more details):
 
 ```python
 >>> import numpy as np
@@ -6586,7 +6586,7 @@ class MFTime(_Variable):
 Class providing an interface to a MFDataset time Variable by imposing a unique common
 time unit and/or calendar to all files.
 
-Example usage (See [MFTime.__init__](#MFTime.__init__) for more details):
+Example usage (See `MFTime.__init__` for more details):
 
 ```python
 >>> import numpy as np
@@ -6624,7 +6624,7 @@ days since 2000-01-01
         Create a time Variable with units consistent across a multifile
         dataset.
 
-        **`time`**: Time variable from a [MFDataset](#MFDataset).
+        **`time`**: Time variable from a `MFDataset`.
 
         **`units`**: Time units, for example, `'days since 1979-01-01'`. If `None`,
         use the units from the master variable.

From 191a1ce4651f0777d69ab0b9a6c1f8e5ffa1b150 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 17 Feb 2021 08:24:47 -0700
Subject: [PATCH 0615/1504] update

---
 docs/index.html          | 11 ++++++-----
 src/netCDF4/_netCDF4.pyx | 15 +++++++++++----
 2 files changed, 17 insertions(+), 9 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 32813a0ac..e4af7fa8a 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -1621,7 +1621,7 @@ 
    In-memory (diskless) Datasets
    
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
    
 
-
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
+
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
 
 
    copyright: 2008 by Jeffrey Whitaker.
    
 
@@ -2563,8 +2563,8 @@ 
    In-memory (diskless) Datasets
    
         
             
    fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')
    
 
-
    call ncgen via subprocess to create Dataset from CDL
-text representation. Requires ncgen to be installed and in $PATH.
    
+
    call ncgen via subprocess to create Dataset from CDL
+text representation. Requires ncgen to be installed and in $PATH.
    
 
 
    cdlfilename:  CDL file.
    
 
@@ -2593,8 +2593,9 @@ 
    In-memory (diskless) Datasets
    
         
             
    tocdl(self, coordvars=False, data=False, outfile=None)
    
 
-
    call ncdump via subprocess to create CDL
-text representation of Dataset. Requires ncdump to be installed and in $PATH.
    
+
    call ncdump via subprocess to create CDL
+text representation of Dataset. Requires ncdump
+to be installed and in $PATH.
    
 
 
    coordvars: include coordinate variable data (via ncdump -c). Default False
    
 
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 17e54b696..dda4dd047 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3225,8 +3225,8 @@ attribute does not exist on the variable. For example,
         """
 **`fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')`**
 
-call `ncgen` via subprocess to create Dataset from [CDL](https://www.unidata.ucar.edu/software/netcdf/docs/netcdf_utilities_guide.html#cdl_guide)
-text representation. Requires `ncgen` to be installed and in `$PATH`.
+call [ncgen][ncgen] via subprocess to create Dataset from [CDL][cdl]
+text representation. Requires [ncgen][ncgen] to be installed and in `$PATH`.
 
 **`cdlfilename`**:  CDL file.
 
@@ -3240,6 +3240,9 @@ suffix replaced by `.nc` is used..
 `'NETCDF3_64BIT_DATA'`. Default `'NETCDF4'`.
        
 Dataset instance for `ncfilename` is returned.
+ 
+[ncgen]: https://www.unidata.ucar.edu/software/netcdf/docs/netcdf_utilities_guide.html#ncgen_guide
+[cdl]: https://www.unidata.ucar.edu/software/netcdf/docs/netcdf_utilities_guide.html#cdl_guide
         """
         if ncfilename is None:
             filepath = pathlib.Path(cdlfilename)
@@ -3260,14 +3263,18 @@ Dataset instance for `ncfilename` is returned.
         """
 **`tocdl(self, coordvars=False, data=False, outfile=None)`**
 
-call `ncdump` via subprocess to create [CDL](https://www.unidata.ucar.edu/software/netcdf/docs/netcdf_utilities_guide.html#cdl_guide)
-text representation of Dataset. Requires `ncdump` to be installed and in `$PATH`.
+call [ncdump][ncdump] via subprocess to create [CDL][cdl]
+text representation of Dataset. Requires [ncdump][ncdump]
+to be installed and in `$PATH`.
 
 **`coordvars`**: include coordinate variable data (via `ncdump -c`). Default False
 
 **`data`**: if True, write out variable data (Default False).
 
 **`outfile`**: If not None, file to output ncdump to. Default is to return a string.
+
+[ncdump]: https://www.unidata.ucar.edu/software/netcdf/docs/netcdf_utilities_guide.html#ncdump_guide
+[cdl]: https://www.unidata.ucar.edu/software/netcdf/docs/netcdf_utilities_guide.html#cdl_guide
         """
         self.sync()
         if coordvars:

From f89b368967e70deee4be1009a95bc20facccea37 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 17 Feb 2021 08:25:14 -0700
Subject: [PATCH 0616/1504] update

---
 create_docs.sh | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/create_docs.sh b/create_docs.sh
index 7d154e3a5..295af7d8f 100644
--- a/create_docs.sh
+++ b/create_docs.sh
@@ -1,8 +1,8 @@
 # Uses pdoc (https://github.com/mitmproxy/pdoc)
 # to create html docs from docstrings in Cython source.
-/Users/jwhitaker/.local/bin/pdoc -o 'docs' netCDF4 
+pdoc -o 'docs' netCDF4 
 # use resulting docs/netCDF4/_netCDF4.html
-cp docs/netCDF4/_netCDF4.html docs/index.html
+cp docs/netCDF4.html docs/index.html
 sed -i -e 's!href="../netCDF4.html!href="./index.html!g' docs/index.html
 sed -i -e 's!/../netCDF4.html!/index.html!g' docs/index.html
 sed -i -e 's!._netCDF4 API! API!g' docs/index.html

From fba6802489de3262608876bd0efd4b36e8d1b9dd Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 17 Feb 2021 20:00:28 -0700
Subject: [PATCH 0617/1504] update

---
 README.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index 95a140a91..fd04ff64b 100644
--- a/README.md
+++ b/README.md
@@ -210,10 +210,10 @@ instead of relying exclusively on the nc-config utility.
 * Clone GitHub repository (`git clone https://github.com/Unidata/netcdf4-python.git`), or get source tarball from [PyPI](https://pypi.python.org/pypi/netCDF4). Links to Windows and OS X precompiled binary packages are also available on [PyPI](https://pypi.python.org/pypi/netCDF4).
 
 * Make sure [numpy](http://www.numpy.org/) and [Cython](http://cython.org/) are
-  installed and you have [Python](https://www.python.org) 2.7 or newer.
+  installed and you have [Python](https://www.python.org) 3.6 or newer.
 
-* Make sure [HDF5](http://www.h5py.org/) and netcdf-4 are installed, and the `nc-config` utility
-  is in your Unix PATH. 
+* Make sure [HDF5](http://www.h5py.org/) and netcdf-4 are installed, 
+  and the `nc-config` utility is in your Unix PATH.
 
 * Run `python setup.py build`, then `python setup.py install` (with `sudo` if necessary).
 

From 29a07534ffc9ced00028f51e74d222ab44ed0de2 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 2 Apr 2021 20:10:38 -0600
Subject: [PATCH 0618/1504] fix incorrect description of valid_min/valid_max
 treatment

---
 src/netCDF4/_netCDF4.pyx | 18 ++++++++++--------
 1 file changed, 10 insertions(+), 8 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index dda4dd047..03e258694 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -5045,13 +5045,14 @@ equal to the either the netCDF _FillValue or the value specified by the
 missing_value variable attribute. The fill_value of the masked array
 is set to the missing_value attribute (if it exists), otherwise
 the netCDF _FillValue attribute (which has a default value
-for each data type).  When data is written to a variable, the masked
+for each data type). If the variable has no missing_value attribute, the
+_FillValue is used instead. If the variable has valid_min/valid_max and
+missing_value attributes, data outside the specified range will be masked.
+When data is written to a variable, the masked
 array is converted back to a regular numpy array by replacing all the
 masked values by the missing_value attribute of the variable (if it
 exists).  If the variable has no missing_value attribute, the _FillValue
-is used instead. If the variable has valid_min/valid_max and
-missing_value attributes, data outside the specified range will be
-set to missing_value.
+is used instead. 
 
 If `maskandscale` is set to `True`, and the variable has a
 `scale_factor` or an `add_offset` attribute, then data read
@@ -5134,13 +5135,14 @@ equal to the either the netCDF _FillValue or the value specified by the
 missing_value variable attribute. The fill_value of the masked array
 is set to the missing_value attribute (if it exists), otherwise
 the netCDF _FillValue attribute (which has a default value
-for each data type).  When data is written to a variable, the masked
+for each data type). If the variable has no missing_value attribute, the
+_FillValue is used instead. If the variable has valid_min/valid_max and
+missing_value attributes, data outside the specified range will be masked.
+When data is written to a variable, the masked
 array is converted back to a regular numpy array by replacing all the
 masked values by the missing_value attribute of the variable (if it
 exists).  If the variable has no missing_value attribute, the _FillValue
-is used instead. If the variable has valid_min/valid_max and
-missing_value attributes, data outside the specified range will be
-set to missing_value.
+is used instead. 
 
 The default value of `mask` is `True`
 (automatic conversions are performed).

From 9b6ae162f96076c8932db6fdb30f603b86215971 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 3 Apr 2021 21:30:49 -0600
Subject: [PATCH 0619/1504] update

---
 docs/index.html | 77 ++++++++++++++++++++++++++++++++++++++-----------
 1 file changed, 60 insertions(+), 17 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index e4af7fa8a..a0fa5120f 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -1621,7 +1621,7 @@ 
    In-memory (diskless) Datasets
    
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
    
 
-
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
+
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
 
 
    copyright: 2008 by Jeffrey Whitaker.
    
 
@@ -3233,13 +3233,14 @@ 
    In-memory (diskless) Datasets
    
 missing_value variable attribute. The fill_value of the masked array
 is set to the missing_value attribute (if it exists), otherwise
 the netCDF _FillValue attribute (which has a default value
-for each data type).  When data is written to a variable, the masked
+for each data type). If the variable has no missing_value attribute, the
+_FillValue is used instead. If the variable has valid_min/valid_max and
+missing_value attributes, data outside the specified range will be masked.
+When data is written to a variable, the masked
 array is converted back to a regular numpy array by replacing all the
 masked values by the missing_value attribute of the variable (if it
 exists).  If the variable has no missing_value attribute, the _FillValue
-is used instead. If the variable has valid_min/valid_max and
-missing_value attributes, data outside the specified range will be
-set to missing_value.
    
+is used instead. 
    
 
 
    If maskandscale is set to True, and the variable has a
 scale_factor or an add_offset attribute, then data read
@@ -3342,13 +3343,14 @@ 
    In-memory (diskless) Datasets
    
 missing_value variable attribute. The fill_value of the masked array
 is set to the missing_value attribute (if it exists), otherwise
 the netCDF _FillValue attribute (which has a default value
-for each data type).  When data is written to a variable, the masked
+for each data type). If the variable has no missing_value attribute, the
+_FillValue is used instead. If the variable has valid_min/valid_max and
+missing_value attributes, data outside the specified range will be masked.
+When data is written to a variable, the masked
 array is converted back to a regular numpy array by replacing all the
 masked values by the missing_value attribute of the variable (if it
 exists).  If the variable has no missing_value attribute, the _FillValue
-is used instead. If the variable has valid_min/valid_max and
-missing_value attributes, data outside the specified range will be
-set to missing_value.
    
+is used instead. 
    
 
 
    The default value of mask is True
 (automatic conversions are performed).
    
@@ -4160,7 +4162,7 @@ 
    Inherited Members
    
     
    
 
         
-            
    date2num(dates, units, calendar=None)
    
+            
    date2num(dates, units, calendar=None, has_year_zero=None)
    
 
 
    Return numeric time values given datetime objects. The units
 of the numeric time values are described by the units argument
@@ -4184,9 +4186,23 @@ 
    Inherited Members
    
 CF metadata convention <http://cfconventions.org>__ are supported.
 Valid calendars 'standard', 'gregorian', 'proleptic_gregorian'
 'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'.
-Default is None which means the calendar associated with the rist
+Default is None which means the calendar associated with the first
 input datetime instance will be used.
    
 
+
    has_year_zero: If set to True, astronomical year numbering
+is used and the year zero exists.  If set to False for real-world
+calendars, then historical year numbering is used and the year 1 is
+preceded by year -1 and no year zero exists.
+The defaults are set to conform with
+CF conventions (False for 'julian', 'gregorian'/'standard', True
+for 'proleptic_gregorian' (ISO 8601) and True for the idealized
+calendars 'noleap'/'365_day', '360_day', 366_day'/'all_leap')
+The defaults can only be over-ridden for the real-world calendars,
+for the the idealized calendars the year zero 
+always exists and the has_year_zero kwarg is ignored.
+This kwarg is not needed to define calendar systems allowed by CF
+(the calendar-specific defaults do this).
    
+
 
    returns a numeric time value, or an array of numeric time values
 with approximately 1 microsecond accuracy.
    
 
    
@@ -4202,7 +4218,7 @@ 
    Inherited Members
    
     
    
 
         
-            
    num2date(times, units, calendar=u'standard', only_use_cftime_datetimes=True, only_use_python_datetimes=False)
    
+            
    num2date(times, units, calendar=u'standard', only_use_cftime_datetimes=True, only_use_python_datetimes=False, has_year_zero=None)
    
 
 
    Return datetime objects given numeric time values. The units
 of the numeric time values are described by the units argument
@@ -4232,6 +4248,20 @@ 
    Inherited Members
    
 objects and raise an error if this is not possible. Ignored unless
 only_use_cftime_datetimes=False. Default False.
    
 
+
    has_year_zero: if set to True, astronomical year numbering
+is used and the year zero exists.  If set to False for real-world
+calendars, then historical year numbering is used and the year 1 is
+preceded by year -1 and no year zero exists.
+The defaults are set to conform with
+CF conventions (False for 'julian', 'gregorian'/'standard', True
+for 'proleptic_gregorian' (ISO 8601) and True for the idealized
+calendars 'noleap'/'365_day', '360_day', 366_day'/'all_leap')
+The defaults can only be over-ridden for the real-world calendars,
+for the the idealized calendars the year zero 
+always exists and the has_year_zero kwarg is ignored.
+This kwarg is not needed to define calendar systems allowed by CF
+(the calendar-specific defaults do this).
    
+
 
    returns a datetime instance, or an array of datetime instances with
 microsecond accuracy, if possible.
    
 
@@ -4259,7 +4289,7 @@ 
    Inherited Members
    
     
    
 
         
-            
    date2index(dates, nctime, calendar=None, select=u'exact')
    
+            
    date2index(dates, nctime, calendar=None, select=u'exact', has_year_zero=None)
    
 
 
    Return indices of a netCDF time variable corresponding to the given dates.
    
 
@@ -4269,14 +4299,13 @@ 
    Inherited Members
    
 
    nctime: A netCDF time variable object. The nctime object must have a
 units attribute.
    
 
-
    calendar: describes the calendar used in the time calculations.
+
    calendar: describes the calendar to be used in the time calculations.
 All the values currently defined in the
 CF metadata convention <http://cfconventions.org>__ are supported.
 Valid calendars 'standard', 'gregorian', 'proleptic_gregorian'
 'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'.
-Default is 'standard', which is a mixed Julian/Gregorian calendar.
-If calendar is None, its value is given by nctime.calendar or
-standard if no such attribute exists.
    
+Default is None which means the calendar associated with the first
+input datetime instance will be used.
    
 
 
    select: 'exact', 'before', 'after', 'nearest'
 The index selection method. exact will return the indices perfectly
@@ -4285,6 +4314,20 @@ 
    Inherited Members
    
 an exact match cannot be found. nearest will return the indices that
 correspond to the closest dates.
    
 
+
    has_year_zero: if set to True, astronomical year numbering
+is used and the year zero exists.  If set to False for real-world
+calendars, then historical year numbering is used and the year 1 is
+preceded by year -1 and no year zero exists.
+The defaults are set to conform with
+CF conventions (False for 'julian', 'gregorian'/'standard', True
+for 'proleptic_gregorian' (ISO 8601) and True for the idealized
+calendars 'noleap'/'365_day', '360_day', 366_day'/'all_leap')
+The defaults can only be over-ridden for the real-world calendars,
+for the the idealized calendars the year zero 
+always exists and the has_year_zero kwarg is ignored.
+This kwarg is not needed to define calendar systems allowed by CF
+(the calendar-specific defaults do this).
    
+
 
    returns an index (indices) of the netCDF time variable corresponding
 to the given datetime object(s).
    
 
    

From 651beae5b74b1f108329ed1ab455577b15802115 Mon Sep 17 00:00:00 2001
From: Filipe Fernandes 
Date: Wed, 14 Apr 2021 21:49:28 -0300
Subject: [PATCH 0620/1504] update install instructions

---
 README.md | 20 +++++++++++++++++---
 1 file changed, 17 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index fd04ff64b..457ed8d3c 100644
--- a/README.md
+++ b/README.md
@@ -6,6 +6,7 @@
 [![Anaconda-Server Badge](https://anaconda.org/conda-forge/netCDF4/badges/version.svg)](https://anaconda.org/conda-forge/netCDF4)
 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.2592291.svg)](https://doi.org/10.5281/zenodo.2592290)
 
+
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
@@ -206,8 +207,21 @@ regarding thread-safety in the HDF5 C library.  Fixes to `setup.py` now ensure t
 with `export USE_NCCONFIG=0` will use environment variables to find paths to libraries and include files,
 instead of relying exclusively on the nc-config utility.
 
-## Quick Start
-* Clone GitHub repository (`git clone https://github.com/Unidata/netcdf4-python.git`), or get source tarball from [PyPI](https://pypi.python.org/pypi/netCDF4). Links to Windows and OS X precompiled binary packages are also available on [PyPI](https://pypi.python.org/pypi/netCDF4).
+## Installation
+The easiest way to install is through pip:
+
+```shell
+pip install netcdf4
+```
+
+or, if you are a user of the Conda package manager,
+
+```shell
+conda install -c conda-forge netcdf4
+```
+
+## Development installation
+* Clone GitHub repository (`git clone https://github.com/Unidata/netcdf4-python.git`)
 
 * Make sure [numpy](http://www.numpy.org/) and [Cython](http://cython.org/) are
   installed and you have [Python](https://www.python.org) 3.6 or newer.
@@ -215,7 +229,7 @@ instead of relying exclusively on the nc-config utility.
 * Make sure [HDF5](http://www.h5py.org/) and netcdf-4 are installed, 
   and the `nc-config` utility is in your Unix PATH.
 
-* Run `python setup.py build`, then `python setup.py install` (with `sudo` if necessary).
+* Run `python setup.py build`, then `pip install -e .`.
 
 * To run all the tests, execute `cd test && python run_all.py`.
 

From d41dab9f3d496ada88cf87481d815ffe14abe587 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 16 Apr 2021 09:10:23 -0600
Subject: [PATCH 0621/1504] update tst_atts.py to use tocdl method instread of
 calling ncdump directly

---
 test/tst_atts.py | 30 +++++++++---------------------
 1 file changed, 9 insertions(+), 21 deletions(-)

diff --git a/test/tst_atts.py b/test/tst_atts.py
index 8c9c52b7b..af9d1cf49 100644
--- a/test/tst_atts.py
+++ b/test/tst_atts.py
@@ -178,27 +178,15 @@ def runTest(self):
         assert v.getncattr('foo') == 1
         assert v.getncattr('bar') == 2
         # check type of attributes using ncdump (issue #529)
-        try:  # ncdump may not be on the system PATH
-            nc_proc = subprocess.Popen(
-                ['ncdump', '-h', FILE_NAME], stdout=subprocess.PIPE)
-        except OSError:
-            warnings.warn('"ncdump" not on system path; cannot test '
-                          'read of some attributes')
-            pass
-        else:  # We do have ncdump output
-            dep = nc_proc.communicate()[0]
-            try: # python 2
-                ncdump_output = dep.split('\n')
-            except TypeError: # python 3
-                ncdump_output = str(dep,encoding='utf-8').split('\n')
-            for line in ncdump_output:
-                line = line.strip('\t\n\r')
-                line = line.strip()# Must be done another time for group variables
-                if "stringatt" in line: assert line.startswith('string')
-                if "charatt" in line: assert line.startswith(':')
-                if "cafe" in line: assert line.startswith('string')
-                if "batt" in line: assert line.startswith(':')
-                if "_ncstr" in line: assert line.startswith('string')
+        ncdump_output = f.tocdl()
+        for line in ncdump_output:
+            line = line.strip('\t\n\r')
+            line = line.strip()# Must be done another time for group variables
+            if "stringatt" in line: assert line.startswith('string')
+            if "charatt" in line: assert line.startswith(':')
+            if "cafe" in line: assert line.startswith('string')
+            if "batt" in line: assert line.startswith(':')
+            if "_ncstr" in line: assert line.startswith('string')
         # check attributes in subgroup.
         # global attributes.
         for key,val in ATTDICT.items():

From d4ee03120eb0c765482030ea2b965a92c4b71863 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 16 Apr 2021 09:43:50 -0600
Subject: [PATCH 0622/1504] update install docs

---
 docs/index.html          | 84 ++++++++++++-----------------------
 src/netCDF4/_netCDF4.pyx | 94 ++++++++++++++--------------------------
 2 files changed, 60 insertions(+), 118 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index a0fa5120f..cf41246db 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -24,9 +24,8 @@ 
    Contents
    
 
 
  • Introduction
 
    • 
 
  • Tutorial
 
      
@@ -479,56 +478,30 @@ 
      Introduction
      
 compound types containing enums, or vlens containing compound
 types) are not supported.
      
 
-
      Download
      
+
      Quick Install
      
 
 
        
-
      • Latest bleeding-edge code from the
-github repository.
        • 
-
      • Latest releases
-(source code and binary installers).
        • 
+
      • the easiest way to get going is to install via pip install netCDF4.
+(or if you are a user conda package manager conda install -c conda_forge netCDF4).
        • 
 
      
 
-
      Requires
      
+
      Developer Install
      
 
 
        
-
      • Python 3.6 or later.
        • 
-
      • numpy array module, version 1.10.0 or later.
        • 
-
      • Cython, version 0.21 or later.
        • 
-
      • setuptools, version 18.0 or
-later.
        • 
-
      • The HDF5 C library version 1.8.4-patch1 or higher
-from .
-netCDF version 4.4.1 or higher is recommended if using HDF5 1.10.x -
-otherwise resulting files may be unreadable by clients using earlier
-versions of HDF5.  For netCDF < 4.4.1, HDF5 version 1.8.x is recommended.
-Be sure to build with --enable-hl --enable-shared.
        • 
-
      • Libcurl, if you want
-OPeNDAP support.
        • 
-
      • HDF4, if you want
-to be able to read HDF4 "Scientific Dataset" (SD) files.
        • 
-
      • The netCDF-4 C library from the github releases
-page.
-Version 4.1.1 or higher is required (4.2 or higher recommended).
-Be sure to build with --enable-netcdf-4 --enable-shared, and set
-CPPFLAGS="-I $HDF5_DIR/include" and LDFLAGS="-L $HDF5_DIR/lib",
-where $HDF5_DIR is the directory where HDF5 was installed.
-If you want OPeNDAP support, add --enable-dap.
-If you want HDF4 SD support, add --enable-hdf4 and add
-the location of the HDF4 headers and library to $CPPFLAGS and $LDFLAGS.
        • 
-
      • for MPI parallel IO support, an MPI-enabled versions of the netcdf library
-is required, as is the mpi4py python module.
+
      • Clone the
+github repository.
        • 
+
      • Make sure the dependencies are satisfied (Python 3.6 or later,
+numpy, 
+Cython,
+cftime,
+setuptools,
+the HDF5 C library,
+and the netCDF C library).
+For MPI parallel IO support, an MPI-enabled versions of the netcdf library
+is required, as is mpi4py.
 Parallel IO further depends on the existence of MPI-enabled HDF5 or the
 PnetCDF library.
        • 
-
      • cftime for
-time and date handling utility functions.
        • 
-
      
-
-
      Install
      
-
-
        
-
      • install the requisite python modules and C libraries (see above). It's
-easiest if all the C libs are built as shared libraries.
        • 
-
      • By default, the utility nc-config, installed with netcdf 4.1.2 or higher,
+
      • By default, the utility nc-config (installed with netcdf-c)
 will be run used to determine where all the dependencies live.
        • 
 
      • If nc-config is not in your default PATH, you can set the NETCDF4_DIR
 environment variable and setup.py will look in $NETCDF4_DIR/bin.
@@ -540,14 +513,11 @@ 
        Install
        
 As a last resort, the library and include paths can be set via environment variables.
 If you go this route, set USE_NCCONFIG and USE_SETUPCFG to 0, and specify
 NETCDF4_LIBDIR, NETCDF4_INCDIR, HDF5_LIBDIR and HDF5_INCDIR.
-Similarly, environment variables
-(all capitalized) can be used to set the include and library paths for
-hdf4, szip, jpeg, curl and zlib. If the dependencies are not found
+If the dependencies are not found
 in any of the paths specified by environment variables, then standard locations
 (such as /usr and /usr/local) are searched.
        • 
 
      • run python setup.py build, then python setup.py install (as root if
-necessary). pip install can be used to install pre-compiled binary wheels from 
-pypi.
        • 
+necessary).
 
      • run the tests in the 'test' directory by running python run_all.py.
        • 
 
      
 
@@ -1621,7 +1591,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -4183,7 +4153,7 @@ 
      Inherited Members
      
 
 
      calendar: describes the calendar to be used in the time calculations.
 All the values currently defined in the
-CF metadata convention <http://cfconventions.org>__ are supported.
+CF metadata convention <http://cfconventions.org/cf-conventions/cf-conventions#calendar>__ are supported.
 Valid calendars 'standard', 'gregorian', 'proleptic_gregorian'
 'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'.
 Default is None which means the calendar associated with the first
@@ -4194,7 +4164,7 @@ 
      Inherited Members
      
 calendars, then historical year numbering is used and the year 1 is
 preceded by year -1 and no year zero exists.
 The defaults are set to conform with
-CF conventions (False for 'julian', 'gregorian'/'standard', True
+CF version 1.9 conventions (False for 'julian', 'gregorian'/'standard', True
 for 'proleptic_gregorian' (ISO 8601) and True for the idealized
 calendars 'noleap'/'365_day', '360_day', 366_day'/'all_leap')
 The defaults can only be over-ridden for the real-world calendars,
@@ -4235,7 +4205,7 @@ 
      Inherited Members
      
 
 
      calendar: describes the calendar used in the time calculations.
 All the values currently defined in the
-CF metadata convention <http://cfconventions.org>__ are supported.
+CF metadata convention <http://cfconventions.org/cf-conventions/cf-conventions#calendar>__ are supported.
 Valid calendars 'standard', 'gregorian', 'proleptic_gregorian'
 'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'.
 Default is 'standard', which is a mixed Julian/Gregorian calendar.
      
@@ -4253,7 +4223,7 @@ 
      Inherited Members
      
 calendars, then historical year numbering is used and the year 1 is
 preceded by year -1 and no year zero exists.
 The defaults are set to conform with
-CF conventions (False for 'julian', 'gregorian'/'standard', True
+CF version 1.9 conventions (False for 'julian', 'gregorian'/'standard', True
 for 'proleptic_gregorian' (ISO 8601) and True for the idealized
 calendars 'noleap'/'365_day', '360_day', 366_day'/'all_leap')
 The defaults can only be over-ridden for the real-world calendars,
@@ -4301,7 +4271,7 @@ 
      Inherited Members
      
 
 
      calendar: describes the calendar to be used in the time calculations.
 All the values currently defined in the
-CF metadata convention <http://cfconventions.org>__ are supported.
+CF metadata convention <http://cfconventions.org/cf-conventions/cf-conventions#calendar>__ are supported.
 Valid calendars 'standard', 'gregorian', 'proleptic_gregorian'
 'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'.
 Default is None which means the calendar associated with the first
@@ -4319,7 +4289,7 @@ 
      Inherited Members
      
 calendars, then historical year numbering is used and the year 1 is
 preceded by year -1 and no year zero exists.
 The defaults are set to conform with
-CF conventions (False for 'julian', 'gregorian'/'standard', True
+CF version 1.9 conventions (False for 'julian', 'gregorian'/'standard', True
 for 'proleptic_gregorian' (ISO 8601) and True for the idealized
 calendars 'noleap'/'365_day', '360_day', 366_day'/'all_leap')
 The defaults can only be over-ridden for the real-world calendars,
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 03e258694..393831490 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -23,71 +23,43 @@ Mixtures of compound, vlen and enum data types (such as
 compound types containing enums, or vlens containing compound
 types) are not supported.
 
-## Download
+## Quick Install
 
- - Latest bleeding-edge code from the
+ - the easiest way to get going is to install via `pip install netCDF4`.
+   (or if you are a user conda package manager `conda install -c conda_forge netCDF4`).
+
+## Developer Install
+
+ - Clone the
    [github repository](http://github.com/Unidata/netcdf4-python).
- - Latest [releases](https://pypi.python.org/pypi/netCDF4)
-   (source code and binary installers).
-
-## Requires
-
- - Python 3.6 or later.
- - [numpy array module](http://numpy.scipy.org), version 1.10.0 or later.
- - [Cython](http://cython.org), version 0.21 or later.
- - [setuptools](https://pypi.python.org/pypi/setuptools), version 18.0 or
-   later.
- - The HDF5 C library version 1.8.4-patch1 or higher
- from [](ftp://ftp.hdfgroup.org/HDF5/current/src).
- ***netCDF version 4.4.1 or higher is recommended if using HDF5 1.10.x -
- otherwise resulting files may be unreadable by clients using earlier
- versions of HDF5.  For netCDF < 4.4.1, HDF5 version 1.8.x is recommended.***
- Be sure to build with `--enable-hl --enable-shared`.
- - [Libcurl](http://curl.haxx.se/libcurl), if you want
- [OPeNDAP](http://opendap.org) support.
- - [HDF4](http://www.hdfgroup.org/products/hdf4), if you want
- to be able to read HDF4 "Scientific Dataset" (SD) files.
- - The netCDF-4 C library from the [github releases
-   page](https://github.com/Unidata/netcdf-c/releases).
- Version 4.1.1 or higher is required (4.2 or higher recommended).
- Be sure to build with `--enable-netcdf-4 --enable-shared`, and set
- `CPPFLAGS="-I $HDF5_DIR/include"` and `LDFLAGS="-L $HDF5_DIR/lib"`,
- where `$HDF5_DIR` is the directory where HDF5 was installed.
- If you want [OPeNDAP](http://opendap.org) support, add `--enable-dap`.
- If you want HDF4 SD support, add `--enable-hdf4` and add
- the location of the HDF4 headers and library to `$CPPFLAGS` and `$LDFLAGS`.
- - for MPI parallel IO support, an MPI-enabled versions of the netcdf library
- is required, as is the [mpi4py](http://mpi4py.scipy.org) python module.
- Parallel IO further depends on the existence of MPI-enabled HDF5 or the
- [PnetCDF](https://parallel-netcdf.github.io/) library.
- - [cftime](https://github.com/Unidata/cftime) for
- time and date handling utility functions.
-
-
-## Install
-
- - install the requisite python modules and C libraries (see above). It's
- easiest if all the C libs are built as shared libraries.
- - By default, the utility `nc-config`, installed with netcdf 4.1.2 or higher,
- will be run used to determine where all the dependencies live.
+ - Make sure the dependencies are satisfied (Python 3.6 or later,
+   [numpy](http://numpy.scipy.org), 
+   [Cython](http://cython.org),
+   [cftime](https://github.com/Unidata/cftime),
+   [setuptools](https://pypi.python.org/pypi/setuptools),
+   the [HDF5 C library](https://www.hdfgroup.org/solutions/hdf5/),
+   and the [netCDF C library](https://www.unidata.ucar.edu/software/netcdf/)).
+   For MPI parallel IO support, an MPI-enabled versions of the netcdf library
+   is required, as is [mpi4py](http://mpi4py.scipy.org).
+   Parallel IO further depends on the existence of MPI-enabled HDF5 or the
+   [PnetCDF](https://parallel-netcdf.github.io/) library.
+ - By default, the utility `nc-config` (installed with netcdf-c)
+   will be run used to determine where all the dependencies live.
  - If `nc-config` is not in your default `PATH`, you can set the `NETCDF4_DIR`
- environment variable and `setup.py` will look in `$NETCDF4_DIR/bin`.
- You can also use the file `setup.cfg` to set the path to `nc-config`, or
- enter the paths to the libraries and include files manually. Just  edit the `setup.cfg` file
- in a text editor and follow the instructions in the comments.
- To disable the use of `nc-config`, set the env var `USE_NCCONFIG` to 0.
- To disable the use of `setup.cfg`, set `USE_SETUPCFG` to 0.
- As a last resort, the library and include paths can be set via environment variables.
- If you go this route, set `USE_NCCONFIG` and `USE_SETUPCFG` to 0, and specify
- `NETCDF4_LIBDIR`, `NETCDF4_INCDIR`, `HDF5_LIBDIR` and `HDF5_INCDIR`.
- Similarly, environment variables
- (all capitalized) can be used to set the include and library paths for
- `hdf4`, `szip`, `jpeg`, `curl` and `zlib`. If the dependencies are not found
- in any of the paths specified by environment variables, then standard locations
- (such as `/usr` and `/usr/local`) are searched.
+   environment variable and `setup.py` will look in `$NETCDF4_DIR/bin`.
+   You can also use the file `setup.cfg` to set the path to `nc-config`, or
+   enter the paths to the libraries and include files manually. Just  edit the `setup.cfg` file
+   in a text editor and follow the instructions in the comments.
+   To disable the use of `nc-config`, set the env var `USE_NCCONFIG` to 0.
+   To disable the use of `setup.cfg`, set `USE_SETUPCFG` to 0.
+   As a last resort, the library and include paths can be set via environment variables.
+   If you go this route, set `USE_NCCONFIG` and `USE_SETUPCFG` to 0, and specify
+   `NETCDF4_LIBDIR`, `NETCDF4_INCDIR`, `HDF5_LIBDIR` and `HDF5_INCDIR`.
+   If the dependencies are not found
+   in any of the paths specified by environment variables, then standard locations
+   (such as `/usr` and `/usr/local`) are searched.
  - run `python setup.py build`, then `python setup.py install` (as root if
- necessary). `pip install` can be used to install pre-compiled binary wheels from 
- [pypi](https://pypi.org/project/netCDF4).
+   necessary).
  - run the tests in the 'test' directory by running `python run_all.py`.
 
 # Tutorial

From 6ad1e7bcad300ab3dbe69499528b865f275c2ef8 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 16 Apr 2021 09:44:57 -0600
Subject: [PATCH 0623/1504] update

---
 README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 457ed8d3c..268179b08 100644
--- a/README.md
+++ b/README.md
@@ -211,13 +211,13 @@ instead of relying exclusively on the nc-config utility.
 The easiest way to install is through pip:
 
 ```shell
-pip install netcdf4
+pip install netCDF4
 ```
 
 or, if you are a user of the Conda package manager,
 
 ```shell
-conda install -c conda-forge netcdf4
+conda install -c conda-forge netCDF4
 ```
 
 ## Development installation

From 4d97664af07b83dc80613688a41ef6e3034f33f0 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 16 Apr 2021 09:53:29 -0600
Subject: [PATCH 0624/1504] don't try to run tocdl if NO_CDL env var set

---
 test/tst_atts.py | 19 ++++++++++---------
 1 file changed, 10 insertions(+), 9 deletions(-)

diff --git a/test/tst_atts.py b/test/tst_atts.py
index af9d1cf49..fd779c2ed 100644
--- a/test/tst_atts.py
+++ b/test/tst_atts.py
@@ -178,15 +178,16 @@ def runTest(self):
         assert v.getncattr('foo') == 1
         assert v.getncattr('bar') == 2
         # check type of attributes using ncdump (issue #529)
-        ncdump_output = f.tocdl()
-        for line in ncdump_output:
-            line = line.strip('\t\n\r')
-            line = line.strip()# Must be done another time for group variables
-            if "stringatt" in line: assert line.startswith('string')
-            if "charatt" in line: assert line.startswith(':')
-            if "cafe" in line: assert line.startswith('string')
-            if "batt" in line: assert line.startswith(':')
-            if "_ncstr" in line: assert line.startswith('string')
+        if not os.getenv('NO_CDL'):
+            ncdump_output = f.tocdl()
+            for line in ncdump_output:
+                line = line.strip('\t\n\r')
+                line = line.strip()# Must be done another time for group variables
+                if "stringatt" in line: assert line.startswith('string')
+                if "charatt" in line: assert line.startswith(':')
+                if "cafe" in line: assert line.startswith('string')
+                if "batt" in line: assert line.startswith(':')
+                if "_ncstr" in line: assert line.startswith('string')
         # check attributes in subgroup.
         # global attributes.
         for key,val in ATTDICT.items():

From f7821134a73deab31621d384816aaa6fa3c62db5 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 16 Apr 2021 10:01:18 -0600
Subject: [PATCH 0625/1504] try not using NamedTempFile

---
 test/tst_atts.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/test/tst_atts.py b/test/tst_atts.py
index fd779c2ed..f50bc35eb 100644
--- a/test/tst_atts.py
+++ b/test/tst_atts.py
@@ -13,7 +13,8 @@
 import netCDF4
 
 # test attribute creation.
-FILE_NAME = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
+#FILE_NAME = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
+FILE_NAME = 'tst_atts.nc'
 VAR_NAME="dummy_var"
 GROUP_NAME = "dummy_group"
 DIM1_NAME="x"

From 3071f7f9563d60745cd4eaa7ab7870d59f062a73 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 20 Apr 2021 09:41:37 -0600
Subject: [PATCH 0626/1504] fix typo in docs

---
 docs/index.html          | 4 ++--
 src/netCDF4/_netCDF4.pyx | 2 +-
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index cf41246db..9ad6d3bc1 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -482,7 +482,7 @@ 
      Quick Install
      
 
 
        
 
      • the easiest way to get going is to install via pip install netCDF4.
-(or if you are a user conda package manager conda install -c conda_forge netCDF4).
        • 
+(or if you use the conda package manager conda install -c conda_forge netCDF4).
 
      
 
 
      Developer Install
      
@@ -1591,7 +1591,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 393831490..ac1c0d1d2 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -26,7 +26,7 @@ types) are not supported.
 ## Quick Install
 
  - the easiest way to get going is to install via `pip install netCDF4`.
-   (or if you are a user conda package manager `conda install -c conda_forge netCDF4`).
+   (or if you use the [conda](http://conda.io) package manager `conda install -c conda_forge netCDF4`).
 
 ## Developer Install
 

From abe99fb370c440df4271d55b538b592d2945bba6 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 20 Apr 2021 09:49:04 -0600
Subject: [PATCH 0627/1504] fix another doc typo

---
 docs/index.html          | 362 +++++++++++++++++++++------------------
 src/netCDF4/_netCDF4.pyx |   5 +-
 2 files changed, 197 insertions(+), 170 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 9ad6d3bc1..93bca8670 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     netCDF4 API documentation
     
 
@@ -1110,9 +1110,8 @@ 
      Efficient compression of netC
 
 
      In our example, try replacing the line
      
 
-
      ```python
->>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
-
      
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
+
      
 
 
      with
      
 
@@ -1591,7 +1590,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -1647,53 +1646,53 @@ 
      In-memory (diskless) Datasets
      
 
      The following class variables are read-only and should not be
 modified by the user.
      
 
-
      dimensions: The dimensions dictionary maps the names of
+
      dimensions: The dimensions dictionary maps the names of
 dimensions defined for the Group or Dataset to instances of the
 Dimension class.
      
 
-
      variables: The variables dictionary maps the names of variables
+
      variables: The variables dictionary maps the names of variables
 defined for this Dataset or Group to instances of the
 Variable class.
      
 
-
      groups: The groups dictionary maps the names of groups created for
+
      groups: The groups dictionary maps the names of groups created for
 this Dataset or Group to instances of the Group class (the
 Dataset class is simply a special case of the Group class which
 describes the root group in the netCDF4 file).
      
 
-
      cmptypes: The cmptypes dictionary maps the names of
+
      cmptypes: The cmptypes dictionary maps the names of
 compound types defined for the Group or Dataset to instances of the
 CompoundType class.
      
 
-
      vltypes: The vltypes dictionary maps the names of
+
      vltypes: The vltypes dictionary maps the names of
 variable-length types defined for the Group or Dataset to instances
 of the VLType class.
      
 
-
      enumtypes: The enumtypes dictionary maps the names of
+
      enumtypes: The enumtypes dictionary maps the names of
 Enum types defined for the Group or Dataset to instances
 of the EnumType class.
      
 
-
      data_model: data_model describes the netCDF
+
      data_model: data_model describes the netCDF
 data model version, one of NETCDF3_CLASSIC, NETCDF4,
 NETCDF4_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
      
 
-
      file_format: same as data_model, retained for backwards compatibility.
      
+
      file_format: same as data_model, retained for backwards compatibility.
      
 
-
      disk_format: disk_format describes the underlying
+
      disk_format: disk_format describes the underlying
 file format, one of NETCDF3, HDF5, HDF4,
 PNETCDF, DAP2, DAP4 or UNDEFINED. Only available if using
 netcdf C library version >= 4.3.1, otherwise will always return
 UNDEFINED.
      
 
-
      parent: parent is a reference to the parent
+
      parent: parent is a reference to the parent
 Group instance. None for the root group or Dataset
 instance.
      
 
-
      path: path shows the location of the Group in
+
      path: path shows the location of the Group in
 the Dataset in a unix directory format (the names of groups in the
 hierarchy separated by backslashes). A Dataset instance is the root
 group, so the path is simply '/'.
      
 
-
      keepweakref: If True, child Dimension and Variables objects only keep weak
+
      keepweakref: If True, child Dimension and Variables objects only keep weak
 references to the parent Dataset or Group.
      
 
 
      _ncstring_attrs__: If True, all text attributes will be written as variable-length
@@ -1705,7 +1704,8 @@ 
      In-memory (diskless) Datasets
      
                                         
      #  
 
         
-            Dataset(unknown)    
      
+            Dataset()
+    
    • 
 
         
             
    __init__(self, filename, mode="r", clobber=True, diskless=False,
@@ -1716,7 +1716,7 @@ 
    In-memory (diskless) Datasets
    
 
 
    filename: Name of netCDF file to hold dataset. Can also
 be a python 3 pathlib instance or the URL of an OpenDAP dataset.  When memory is
-set this is just used to set the filepath().
    
+set this is just used to set the filepath().
    
 
 
    mode: access mode. r means read-only; no data can be
 modified. w means write; a new file is created, an existing file with
@@ -1760,7 +1760,7 @@ 
    In-memory (diskless) Datasets
    
 
    persist: if diskless=True, persist file to disk when closed
 (default False).
    
 
-
    keepweakref: if True, child Dimension and Variable instances will keep weak
+
    keepweakref: if True, child Dimension and Variable instances will keep weak
 references to the parent Dataset or Group object.  Default is False, which
 means strong references will be kept.  Having Dimension and Variable instances
 keep a strong reference to the parent Dataset instance, which in turn keeps a
@@ -1886,7 +1886,7 @@ 
    In-memory (diskless) Datasets
    
 controlled by the variable's _Fill_Value attribute, but is usually
 sufficient to the use the netCDF default _Fill_Value (defined
 separately for each variable type). The default behavior of the netCDF
-library corresponds to set_fill_on.  Data which are equal to the
+library corresponds to set_fill_on.  Data which are equal to the
 _Fill_Value indicate that the variable was created, but never written
 to.
    
 
    
@@ -2033,7 +2033,7 @@ 
    In-memory (diskless) Datasets
    
 endian='native', least_significant_digit=None, fill_value=None, chunk_cache=None)
    
 
 
    Creates a new variable with the given varname, datatype, and
-dimensions. If dimensions are not given, the variable is assumed to be
+dimensions. If dimensions are not given, the variable is assumed to be
 a scalar.
    
 
 
    If varname is specified as a path, using forward slashes as in unix to
@@ -2057,7 +2057,7 @@ 
    In-memory (diskless) Datasets
    
 
    Data from netCDF variables is presented to python as numpy arrays with
 the corresponding data type.
    
 
-
    dimensions must be a tuple containing dimension names (strings) that
+
    dimensions must be a tuple containing dimension names (strings) that
 have been defined previously using Dataset.createDimension. The default value
 is an empty tuple, which means the variable is a scalar.
    
 
@@ -2138,11 +2138,11 @@ 
    In-memory (diskless) Datasets
    
 operations on the Variable instance. A Variable instance has six
 Dataset standard attributes: dimensions, dtype, shape, ndim, name and
 least_significant_digit. Application programs should never modify
-these attributes. The dimensions attribute is a tuple containing the
+these attributes. The dimensions attribute is a tuple containing the
 names of the dimensions associated with this variable. The dtype
 attribute is a string describing the variable's data type (i4, f8,
 S1, etc). The shape attribute is a tuple describing the current
-sizes of all the variable's dimensions. The name attribute is a
+sizes of all the variable's dimensions. The name attribute is a
 string containing the name of the Variable instance.
 The least_significant_digit
 attributes describes the power of ten of the smallest decimal place in
@@ -2582,7 +2582,9 @@ 
    In-memory (diskless) Datasets
    
         name = <attribute 'name' of 'netCDF4._netCDF4.Dataset' objects>
     
    
 
-    
+            
    string name of Group instance
    
+
    
+
 
                             
    
                             
    
@@ -2717,28 +2719,28 @@ 
    In-memory (diskless) Datasets
    
 
 
    The following class variables are read-only:
    
 
-
    dimensions: A tuple containing the names of the
+
    dimensions: A tuple containing the names of the
 dimensions associated with this variable.
    
 
-
    dtype: A numpy dtype object describing the
+
    dtype: A numpy dtype object describing the
 variable's data type.
    
 
-
    ndim: The number of variable dimensions.
    
+
    ndim: The number of variable dimensions.
    
 
-
    shape: A tuple with the current shape (length of all dimensions).
    
+
    shape: A tuple with the current shape (length of all dimensions).
    
 
-
    scale: If True, scale_factor and add_offset are
+
    scale: If True, scale_factor and add_offset are
 applied, and signed integer data is automatically converted to
 unsigned integer data if the _Unsigned attribute is set.
 Default is True, can be reset using Variable.set_auto_scale and
 Variable.set_auto_maskandscale methods.
    
 
-
    mask: If True, data is automatically converted to/from masked
+
    mask: If True, data is automatically converted to/from masked
 arrays when missing values or fill values are present. Default is True, can be
 reset using Variable.set_auto_mask and Variable.set_auto_maskandscale
 methods.
    
 
-
    chartostring: If True, data is automatically converted to/from character
+
    chartostring: If True, data is automatically converted to/from character
 arrays to string arrays when the _Encoding variable attribute is set.
 Default is True, can be reset using
 Variable.set_auto_chartostring method.
    
@@ -2753,12 +2755,12 @@ 
    In-memory (diskless) Datasets
    
 that are 1d arrays or lists slice along each dimension independently.  This
 behavior is similar to Fortran or Matlab, but different than numpy.
    
 
-
    datatype: numpy data type (for primitive data types) or VLType/CompoundType
+
    datatype: numpy data type (for primitive data types) or VLType/CompoundType
  instance (for compound or vlen data types).
    
 
-
    name: String name.
    
+
    name: String name.
    
 
-
    size: The number of stored elements.
    
+
    size: The number of stored elements.
    
 
    
 
 
@@ -2766,7 +2768,8 @@ 
    In-memory (diskless) Datasets
    
                                         
    #  
 
         
-            Variable(unknown)    
    
+            Variable()
+    
    
 
         
             
    __init__(self, group, name, datatype, dimensions=(), zlib=False,
@@ -2776,11 +2779,11 @@ 
    In-memory (diskless) Datasets
    
 
 
    Variable constructor.
    
 
-
    group: Group or Dataset instance to associate with variable.
    
+
    group: Group or Dataset instance to associate with variable.
    
 
-
    name: Name of the variable.
    
+
    name: Name of the variable.
    
 
-
    datatype: Variable data type. Can be specified by providing a
+
    datatype: Variable data type. Can be specified by providing a
 numpy dtype object, or a string that describes a numpy dtype object.
 Supported values, corresponding to str attribute of numpy dtype
 objects, include 'f4' (32-bit floating point), 'f8' (64-bit floating
@@ -2793,13 +2796,13 @@ 
    In-memory (diskless) Datasets
    
 typecodes can also be used ('f' instead of 'f4', 'd' instead of
 'f8', 'h' or 's' instead of 'i2', 'b' or 'B' instead of
 'i1', 'c' instead of 'S1', and 'i' or 'l' instead of
-'i4'). datatype can also be a CompoundType instance
+'i4'). datatype can also be a CompoundType instance
 (for a structured, or compound array), a VLType instance
 (for a variable-length array), or the python str builtin
 (for a variable-length string array). Numpy string and unicode datatypes with
 length greater than one are aliases for str.
    
 
-
    dimensions: a tuple containing the variable's dimension names
+
    dimensions: a tuple containing the variable's dimension names
 (defined previously with createDimension). Default is an empty tuple
 which means the variable is a scalar (and therefore has no dimensions).
    
 
@@ -2828,7 +2831,7 @@ 
    In-memory (diskless) Datasets
    
 closely as possible the size of the data block that users will read
 from the file. chunksizes cannot be set if contiguous=True.
    
 
-
    endian: Can be used to control whether the
+
    endian: Can be used to control whether the
 data is stored in little or big endian format on disk. Possible
 values are little, big or native (default). The library
 will automatically handle endian conversions when the data is read,
@@ -2855,7 +2858,7 @@ 
    In-memory (diskless) Datasets
    
 in the dictionary netCDF4.default_fillvals.
    
 
 
    chunk_cache: If specified, sets the chunk cache size for this variable.
-Persists as long as Dataset is open. Use set_var_chunk_cache to 
+Persists as long as Dataset is open. Use set_var_chunk_cache to 
 change it when Dataset is re-opened. 
    
 
 
    Note: Variable instances should be created using the
@@ -3144,7 +3147,7 @@ 
    In-memory (diskless) Datasets
    
 from numpy fixed length string arrays when the _Encoding variable attribute
 is set.
    
 
-
    If chartostring is set to True, when data is read from a character variable
+
    If chartostring is set to True, when data is read from a character variable
 (dtype = S1) that has an _Encoding attribute, it is converted to a numpy
 fixed length unicode string array (dtype = UN, where N is the length
 of the the rightmost dimension of the variable).  The value of _Encoding
@@ -3154,7 +3157,7 @@ 
    In-memory (diskless) Datasets
    
 indiviual bytes, with the number of bytes in each string equalling the
 rightmost dimension of the variable.
    
 
-
    The default value of chartostring is True
+
    The default value of chartostring is True
 (automatic conversions are performed).
    
 
    
 
@@ -3261,7 +3264,7 @@ 
    In-memory (diskless) Datasets
    
 to unsigned integer data if the variable has an _Unsigned
 attribute.
    
 
-
    If scale is set to True, and the variable has a
+
    If scale is set to True, and the variable has a
 scale_factor or an add_offset attribute, then data read
 from that variable is unpacked using::
    
 
@@ -3280,14 +3283,14 @@ 
    In-memory (diskless) Datasets
    
 used to provide simple compression, see the
 PSL metadata conventions.
    
 
-
    In addition, if scale is set to True, and if the variable has an
+
    In addition, if scale is set to True, and if the variable has an
 attribute _Unsigned set, and the variable has a signed integer data type,
 a view to the data is returned with the corresponding unsigned integer datatype.
 This convention is used by the netcdf-java library to save unsigned integer
 data in NETCDF3 or NETCDF4_CLASSIC files (since the NETCDF3
 data model does not have unsigned integer data types).
    
 
-
    The default value of scale is True
+
    The default value of scale is True
 (automatic conversions are performed).
    
 
    
 
@@ -3307,7 +3310,7 @@ 
    In-memory (diskless) Datasets
    
 
    turn on or off automatic conversion of variable data to and
 from masked arrays .
    
 
-
    If mask is set to True, when data is read from a variable
+
    If mask is set to True, when data is read from a variable
 it is converted to a masked array if any of the values are exactly
 equal to the either the netCDF _FillValue or the value specified by the
 missing_value variable attribute. The fill_value of the masked array
@@ -3322,7 +3325,7 @@ 
    In-memory (diskless) Datasets
    
 exists).  If the variable has no missing_value attribute, the _FillValue
 is used instead. 
    
 
-
    The default value of mask is True
+
    The default value of mask is True
 (automatic conversions are performed).
    
 
    
 
@@ -3342,7 +3345,7 @@ 
    In-memory (diskless) Datasets
    
 
    turn on or off conversion of data without missing values to regular
 numpy arrays.
    
 
-
    always_mask is a Boolean determining if automatic conversion of
+
    always_mask is a Boolean determining if automatic conversion of
 masked arrays with no missing values to regular numpy arrays shall be
 applied. Default is True. Set to False to restore the default behaviour
 in versions prior to 1.4.1 (numpy array returned unless missing values are present,
@@ -3413,7 +3416,9 @@ 
    In-memory (diskless) Datasets
    
         name = <attribute 'name' of 'netCDF4._netCDF4.Variable' objects>
     
    
 
-    
+            
    string name of Variable instance
    
+
    
+
 
                             
    
                             
    
@@ -3422,7 +3427,11 @@ 
    In-memory (diskless) Datasets
    
         datatype = <attribute 'datatype' of 'netCDF4._netCDF4.Variable' objects>
     
    
 
-    
+            
    numpy data type (for primitive data types) or
+VLType/CompoundType/EnumType instance 
+(for compound, vlen  or enum data types)
    
+
    
+
 
                             
    
                             
    
@@ -3431,7 +3440,9 @@ 
    In-memory (diskless) Datasets
    
         shape = <attribute 'shape' of 'netCDF4._netCDF4.Variable' objects>
     
    
 
-    
+            
    find current sizes of all variable dimensions
    
+
    
+
 
                             
    
                             
    
@@ -3440,7 +3451,9 @@ 
    In-memory (diskless) Datasets
    
         size = <attribute 'size' of 'netCDF4._netCDF4.Variable' objects>
     
    
 
-    
+            
    Return the number of stored elements.
    
+
    
+
 
                             
    
                             
    
@@ -3449,7 +3462,9 @@ 
    In-memory (diskless) Datasets
    
         dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Variable' objects>
     
    
 
-    
+            
    get variables's dimension names
    
+
    
+
 
                             
    
                             
    
@@ -3527,10 +3542,10 @@ 
    In-memory (diskless) Datasets
    
 
 
    Read-only class variables:
    
 
-
    name: String name, used when creating a Variable with
+
    name: String name, used when creating a Variable with
 Dataset.createVariable.
    
 
-
    size: Current Dimension size (same as len(d), where d is a
+
    size: Current Dimension size (same as len(d), where d is a
 Dimension instance).
    
 
    
 
@@ -3539,18 +3554,19 @@ 
    In-memory (diskless) Datasets
    
                                         
    #  
 
         
-            Dimension(unknown)    
    
+            Dimension()
+    
    
 
         
             
    __init__(self, group, name, size=None)
    
 
 
    Dimension constructor.
    
 
-
    group: Group instance to associate with dimension.
    
+
    group: Group instance to associate with dimension.
    
 
-
    name: Name of the dimension.
    
+
    name: Name of the dimension.
    
 
-
    size: Size of the dimension. None or 0 means unlimited. (Default None).
    
+
    size: Size of the dimension. None or 0 means unlimited. (Default None).
    
 
 
    Note: Dimension instances should be created using the
 Dataset.createDimension method of a Group or
@@ -3597,7 +3613,9 @@ 
    In-memory (diskless) Datasets
    
         name = <attribute 'name' of 'netCDF4._netCDF4.Dimension' objects>
     
    
 
-    
+            
    string name of Dimension instance
    
+
    
+
 
                             
    
                             
    
@@ -3606,7 +3624,9 @@ 
    In-memory (diskless) Datasets
    
         size = <attribute 'size' of 'netCDF4._netCDF4.Dimension' objects>
     
    
 
-    
+            
    current size of Dimension (calls len on Dimension instance)
    
+
    
+
 
                             
    
                 
@@ -3616,7 +3636,7 @@ 
    In-memory (diskless) Datasets
    
 
         
         class
-        Group(netCDF4._netCDF4.Dataset):
+        Group(netCDF4.Dataset):
     
    
 
         
@@ -3628,11 +3648,11 @@ 
    In-memory (diskless) Datasets
    
 
 
    Group inherits from Dataset, so all the
 Dataset class methods and variables are available
-to a Group instance (except the close method).
    
+to a Group instance (except the close method).
    
 
 
    Additional read-only class variables:
    
 
-
    name: String describing the group name.
    
+
    name: String describing the group name.
    
 
    
 
 
@@ -3640,16 +3660,17 @@ 
    In-memory (diskless) Datasets
    
                                         
    #  
 
         
-            Group(unknown)    
    
+            Group()
+    
    
 
         
             
    __init__(self, parent, name)
 Group constructor.
    
 
-
    parent: Group instance for the parent group.  If being created
+
    parent: Group instance for the parent group.  If being created
 in the root group, use a Dataset instance.
    
 
-
    name: - Name of the group.
    
+
    name: - Name of the group.
    
 
 
    Note: Group instances should be created using the
 Dataset.createGroup method of a Dataset instance, or
@@ -3678,50 +3699,50 @@ 
    In-memory (diskless) Datasets
    
                             
    
                                 
    Inherited Members
    
                                 
    
-                                    
    netCDF4._netCDF4.Dataset
    
-                                
    filepath
    
-                
    isopen
    
-                
    sync
    
-                
    set_fill_on
    
-                
    set_fill_off
    
-                
    createDimension
    
-                
    renameDimension
    
-                
    createCompoundType
    
-                
    createVLType
    
-                
    createEnumType
    
-                
    createVariable
    
-                
    renameVariable
    
-                
    createGroup
    
-                
    ncattrs
    
-                
    setncattr
    
-                
    setncattr_string
    
-                
    setncatts
    
-                
    getncattr
    
-                
    delncattr
    
-                
    renameAttribute
    
-                
    renameGroup
    
-                
    set_auto_chartostring
    
-                
    set_auto_maskandscale
    
-                
    set_auto_mask
    
-                
    set_auto_scale
    
-                
    set_always_mask
    
-                
    set_ncstring_attrs
    
-                
    get_variables_by_attributes
    
-                
    fromcdl
    
-                
    tocdl
    
-                
    name
    
-                
    groups
    
-                
    dimensions
    
-                
    variables
    
-                
    disk_format
    
-                
    path
    
-                
    parent
    
-                
    file_format
    
-                
    data_model
    
-                
    cmptypes
    
-                
    vltypes
    
-                
    enumtypes
    
-                
    keepweakref
    
+                                    
                                 
    
@@ -3733,7 +3754,7 @@ 
    Inherited Members
    
 
         
         class
-        MFDataset(netCDF4._netCDF4.Dataset):
+        MFDataset(netCDF4.Dataset):
     
    
 
         
@@ -3770,7 +3791,8 @@ 
    Inherited Members
    
                                         
    #  
 
         
-            MFDataset(files, check=False, aggdim=None, exclude=[], master_file=None)    
    
+            MFDataset(files, check=False, aggdim=None, exclude=[], master_file=None)
+    
    
 
         
             
    __init__(self, files, check=False, aggdim=None, exclude=[],
@@ -3844,49 +3866,49 @@ 
    Inherited Members
    
                             
    
                                 
    Inherited Members
    
                                 
    
-                                    
    netCDF4._netCDF4.Dataset
    
-                                
    filepath
    
-                
    isopen
    
-                
    sync
    
-                
    set_fill_on
    
-                
    set_fill_off
    
-                
    createDimension
    
-                
    renameDimension
    
-                
    createCompoundType
    
-                
    createVLType
    
-                
    createEnumType
    
-                
    createVariable
    
-                
    renameVariable
    
-                
    createGroup
    
-                
    setncattr
    
-                
    setncattr_string
    
-                
    setncatts
    
-                
    getncattr
    
-                
    delncattr
    
-                
    renameAttribute
    
-                
    renameGroup
    
-                
    set_auto_chartostring
    
-                
    set_auto_maskandscale
    
-                
    set_auto_mask
    
-                
    set_auto_scale
    
-                
    set_always_mask
    
-                
    set_ncstring_attrs
    
-                
    get_variables_by_attributes
    
-                
    fromcdl
    
-                
    tocdl
    
-                
    name
    
-                
    groups
    
-                
    dimensions
    
-                
    variables
    
-                
    disk_format
    
-                
    path
    
-                
    parent
    
-                
    file_format
    
-                
    data_model
    
-                
    cmptypes
    
-                
    vltypes
    
-                
    enumtypes
    
-                
    keepweakref
    
+                                    
                                 
    
@@ -3940,7 +3962,8 @@ 
    Inherited Members
    
                                         
    #  
 
         
-            MFTime(time, units=None, calendar=None)    
    
+            MFTime(time, units=None, calendar=None)
+    
    
 
         
             
    __init__(self, time, units=None, calendar=None)
    
@@ -3993,7 +4016,7 @@ 
    Inherited Members
    
 Compound data types map to numpy structured arrays.
 See CompoundType.__init__ for more details.
    
 
-
    The instance variables dtype and name should not be modified by
+
    The instance variables dtype and name should not be modified by
 the user.
    
 
    
 
@@ -4002,7 +4025,8 @@ 
    Inherited Members
    
                                         
    #  
 
         
-            CompoundType(unknown)    
    
+            CompoundType()
+    
    
 
         
             
    __init__(group, datatype, datatype_name)
    
@@ -4073,7 +4097,7 @@ 
    Inherited Members
    
 a Dataset or Group instance. See
 VLType.__init__ for more details.
    
 
-
    The instance variables dtype and name should not be modified by
+
    The instance variables dtype and name should not be modified by
 the user.
    
 
    
 
@@ -4082,7 +4106,8 @@ 
    Inherited Members
    
                                         
    #  
 
         
-            VLType(unknown)    
    
+            VLType()
+    
    
 
         
             
    __init__(group, datatype, datatype_name)
    
@@ -4418,7 +4443,7 @@ 
    Inherited Members
    
 a Dataset or Group instance. See
 EnumType.__init__ for more details.
    
 
-
    The instance variables dtype, name and enum_dict should not be modified by
+
    The instance variables dtype, name and enum_dict should not be modified by
 the user.
    
 
    
 
@@ -4427,7 +4452,8 @@ 
    Inherited Members
    
                                         
    #  
 
         
-            EnumType(unknown)    
    
+            EnumType()
+    
    
 
         
             
    __init__(group, datatype, datatype_name, enum_dict)
    
@@ -4442,7 +4468,7 @@ 
    Inherited Members
    
 
    datatype_name: a Python string containing a description of the
 Enum data type.
    
 
-
    enum_dict: a Python dictionary containing the Enum field/value
+
    enum_dict: a Python dictionary containing the Enum field/value
 pairs.
    
 
 
    Note: EnumType instances should be created using the
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index ac1c0d1d2..79a3c48d3 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -679,8 +679,9 @@ sacrificed for the sake of disk space.
 
 In our example, try replacing the line
 
-    ```python
-    >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
+```python
+>>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
+```
 
 with
 

From 673c9e29d64878496486c2b924031304e9991c2e Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 17 May 2021 15:50:15 -0600
Subject: [PATCH 0628/1504] fix DeprecationWarning coming from numpy

---
 src/netCDF4/_netCDF4.pyx | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 79a3c48d3..40c5a4852 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4578,7 +4578,8 @@ rename a `Variable` attribute named `oldname` to `newname`."""
             # type, signed or unsigned, because the byte ranges are too
             # small to assume one of the values should appear as a missing
             # value unless a _FillValue attribute is set explicitly."
-            if no_fill != 1 or self.dtype.str[1:] not in ['u1','i1']:
+            # (do this only for non-vlens, since vlens don't have fill values)
+            if not self._isvlen and (no_fill != 1 or self.dtype.str[1:] not in ['u1','i1']):
                 fillval = numpy.array(default_fillvals[self.dtype.str[1:]],self.dtype)
                 has_fillval = data == fillval
                 # if data is an array scalar, has_fillval will be a boolean.

From c49a4ad982b736b0f213831b2aa8cd798a8314d4 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 18 May 2021 09:27:47 -0600
Subject: [PATCH 0629/1504] update

---
 Changelog | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/Changelog b/Changelog
index 14ba39dc4..6d2e77974 100644
--- a/Changelog
+++ b/Changelog
@@ -1,3 +1,8 @@
+ since version 1.5.6
+====================
+ * don't try to mask vlens with _FillValue, since vlens don't have _FillValues.  This gets
+   rid of numpy DeprecationWarning (issue #1099).
+
  version 1.5.6 (tag v1.5.6rel)
 ==============================
  * move CI/CD tests from travis/appveyor to Github Actions (PR #1061).

From 894957ccf41c65f152369559b5bce61afb668ff4 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 18 May 2021 12:59:36 -0600
Subject: [PATCH 0630/1504] test without python 3.9

---
 .github/workflows/build.yml     | 3 ++-
 .github/workflows/miniconda.yml | 6 ++++--
 2 files changed, 6 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 86255d8bf..551c66956 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -13,7 +13,8 @@ jobs:
 #     NO_NET: 1
     strategy:
       matrix:
-        python-version: ["3.9"]
+        #python-version: ["3.9"]
+        python-version: ["3.8"]
     steps:
 
     - uses: actions/checkout@v2
diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index e763d49bc..0f00bd7a8 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -10,7 +10,8 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        python-version: ["3.6", "3.7", "3.8", "3.9"]
+        #python-version: ["3.6", "3.7", "3.8", "3.9"]
+        python-version: ["3.6", "3.7", "3.8"]
         os: [windows-latest, ubuntu-latest, macos-latest]
         platform: [x64, x32]
         exclude:
@@ -45,7 +46,8 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        python-version: [ "3.9" ]
+        #python-version: [ "3.9" ]
+        python-version: [ "3.8" ]
         os: [ubuntu-latest]
         platform: [x64]
     steps:

From 8158caae928163a0be1341b4ecb0f3510004f94f Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 18 May 2021 13:05:33 -0600
Subject: [PATCH 0631/1504] add python 3.9 back in, fix typo in test docstring

---
 .github/workflows/build.yml     | 3 +--
 .github/workflows/miniconda.yml | 6 ++----
 test/tst_types.py               | 2 +-
 3 files changed, 4 insertions(+), 7 deletions(-)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 551c66956..86255d8bf 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -13,8 +13,7 @@ jobs:
 #     NO_NET: 1
     strategy:
       matrix:
-        #python-version: ["3.9"]
-        python-version: ["3.8"]
+        python-version: ["3.9"]
     steps:
 
     - uses: actions/checkout@v2
diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 0f00bd7a8..e763d49bc 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -10,8 +10,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        #python-version: ["3.6", "3.7", "3.8", "3.9"]
-        python-version: ["3.6", "3.7", "3.8"]
+        python-version: ["3.6", "3.7", "3.8", "3.9"]
         os: [windows-latest, ubuntu-latest, macos-latest]
         platform: [x64, x32]
         exclude:
@@ -46,8 +45,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        #python-version: [ "3.9" ]
-        python-version: [ "3.8" ]
+        python-version: [ "3.9" ]
         os: [ubuntu-latest]
         platform: [x64]
     steps:
diff --git a/test/tst_types.py b/test/tst_types.py
index 93af1153b..b346d1bc9 100644
--- a/test/tst_types.py
+++ b/test/tst_types.py
@@ -86,7 +86,7 @@ def runTest(self):
         else:
             assert(v2._FillValue == u'') # python 2
         assert(str(issue273_data) == str(v2[:]))
-        # isse 707 (don't apply missing_value if cast to variable type is
+        # issue 707 (don't apply missing_value if cast to variable type is
         # unsafe)
         v3 = f.variables['issue707']
         assert_array_equal(v3[:],-1*np.ones(n2dim,v3.dtype))

From ff799a27c818a8b502ab5075a95af39ef304e5ec Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 18 May 2021 14:46:39 -0600
Subject: [PATCH 0632/1504] update

---
 Changelog                | 4 ++--
 src/netCDF4/_netCDF4.pyx | 2 +-
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/Changelog b/Changelog
index 6d2e77974..4ca5c70bc 100644
--- a/Changelog
+++ b/Changelog
@@ -1,7 +1,7 @@
  since version 1.5.6
 ====================
- * don't try to mask vlens with _FillValue, since vlens don't have _FillValues.  This gets
-   rid of numpy DeprecationWarning (issue #1099).
+ * don't try to mask vlens with default  _FillValue, since vlens don't have a default _FillValue.
+   This gets rid of numpy DeprecationWarning (issue #1099).
 
  version 1.5.6 (tag v1.5.6rel)
 ==============================
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 40c5a4852..2b8b70d80 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4578,7 +4578,7 @@ rename a `Variable` attribute named `oldname` to `newname`."""
             # type, signed or unsigned, because the byte ranges are too
             # small to assume one of the values should appear as a missing
             # value unless a _FillValue attribute is set explicitly."
-            # (do this only for non-vlens, since vlens don't have fill values)
+            # (do this only for non-vlens, since vlens don't have a default _FillValue)
             if not self._isvlen and (no_fill != 1 or self.dtype.str[1:] not in ['u1','i1']):
                 fillval = numpy.array(default_fillvals[self.dtype.str[1:]],self.dtype)
                 has_fillval = data == fillval

From 48bd14b3ec2cf6515ee7c29bbe2e92b529379929 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Wed, 19 May 2021 10:00:41 -0600
Subject: [PATCH 0633/1504] use hardware threads in case there are not enough
 physical cores for mpi test

---
 .github/workflows/miniconda.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index e763d49bc..62b1f8f2b 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -76,7 +76,7 @@ jobs:
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" 
         which mpirun
         mpirun --version
-        mpirun -np 4 python mpi_example.py
+        mpirun --use-hwthread-cpus -np 4 python mpi_example.py
         if [ $? -ne 0 ] ; then
           echo "hdf5 mpi test failed!"
           exit 1

From 0602fb617a02a8a49b33a449bcbb3d82823592e8 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Wed, 19 May 2021 10:15:57 -0600
Subject: [PATCH 0634/1504] update

---
 .github/workflows/miniconda.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 62b1f8f2b..61ceba3d2 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -76,7 +76,7 @@ jobs:
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" 
         which mpirun
         mpirun --version
-        mpirun --use-hwthread-cpus -np 4 python mpi_example.py
+        mpirun  --oversubscribe -np 4 python mpi_example.py
         if [ $? -ne 0 ] ; then
           echo "hdf5 mpi test failed!"
           exit 1

From 855e5245506d3f1cb4e60e03239a414caaed20ec Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 21 May 2021 13:54:13 -0600
Subject: [PATCH 0635/1504] update docstring for parallel IO to address issue
 #1108

---
 src/netCDF4/_netCDF4.pyx | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 2b8b70d80..a124fd126 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1006,7 +1006,11 @@ are collective.  There are a couple of important limitations of parallel IO:
    If the write is done in independent mode, the operation will fail with a
    a generic "HDF Error".
  - You can write compressed data in parallel only with netcdf-c >= 4.7.4
-   and hdf5 >= 1.10.3 (although you can read in parallel with earlier versions).
+   and hdf5 >= 1.10.3 (although you can read in parallel with earlier versions). To write
+   compressed data in parallel, the variable must be in 'collective IO mode'.  This is done
+   automatically on variable creation if compression is turned on, but if you are appending
+   to a variable in an existing file, you must use `Variable.set_collective(True)` before attempting
+   to write to it.
  - You cannot use variable-length (VLEN) data types.
 
 ## Dealing with strings

From a2068414e9f2835279f3fe0928ad0b7c96ade50e Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 21 May 2021 13:59:11 -0600
Subject: [PATCH 0636/1504] add test for compressed parallel IO

---
 examples/mpi_example_compressed.py | 18 ++++++++++++++++++
 1 file changed, 18 insertions(+)
 create mode 100644 examples/mpi_example_compressed.py

diff --git a/examples/mpi_example_compressed.py b/examples/mpi_example_compressed.py
new file mode 100644
index 000000000..368c4f57f
--- /dev/null
+++ b/examples/mpi_example_compressed.py
@@ -0,0 +1,18 @@
+# to run: mpirun -np 4 python mpi_example.py
+import sys
+from mpi4py import MPI
+import numpy as np
+from netCDF4 import Dataset
+rank = MPI.COMM_WORLD.rank  # The process ID (integer 0-3 for 4-process run)
+nc = Dataset('parallel_test.nc', 'w', parallel=True)
+d = nc.createDimension('dim',4)
+v = nc.createVariable('var', np.int32, 'dim', zlib=True)
+v[:] = np.arange(4)
+nc.close()
+# read compressed files in parallel, check the data, try to rewrite some data
+nc = Dataset('parallel_test.nc', 'a', parallel=True)
+v = nc['var']
+assert rank==v[rank]
+v.set_collective(True) # issue #1108
+v[rank]=1
+nc.close()

From 6a22ed87ac34a9aeb3038b7b35b57502acf7d017 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 21 May 2021 14:02:00 -0600
Subject: [PATCH 0637/1504] run compressed mpi test

---
 .github/workflows/build.yml | 9 ++++++++-
 1 file changed, 8 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 86255d8bf..1ac5fa503 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -6,7 +6,7 @@ jobs:
     runs-on: ubuntu-latest
     env:
       PNETCDF_VERSION: 1.12.1
-      NETCDF_VERSION: 4.7.4
+      NETCDF_VERSION: 4.8.0
       NETCDF_DIR: ${{ github.workspace }}/..
       NETCDF_EXTRA_CONFIG: --enable-pnetcdf
       CC: mpicc.mpich
@@ -78,6 +78,13 @@ jobs:
         else
           echo "hdf5 mpi test passed!"
         fi
+        mpirun.mpich -np 4 python mpi_example_compressed.py
+        if [ $? -ne 0 ] ; then
+          echo "hdf5 compressed mpi test failed!"
+          exit 1
+        else
+          echo "hdf5 compressed mpi test passed!"
+        fi
         mpirun.mpich -np 4 python mpi_example.py NETCDF3_64BIT_DATA
         if [ $? -ne 0 ] ; then
           echo "pnetcdf mpi test failed!"

From 650c1469ad3115bafdacfe91f5257b8de66bccb0 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 21 May 2021 14:11:17 -0600
Subject: [PATCH 0638/1504] update

---
 examples/mpi_example_compressed.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/examples/mpi_example_compressed.py b/examples/mpi_example_compressed.py
index 368c4f57f..de8043ba6 100644
--- a/examples/mpi_example_compressed.py
+++ b/examples/mpi_example_compressed.py
@@ -1,10 +1,10 @@
-# to run: mpirun -np 4 python mpi_example.py
+# to run: mpirun -np 4 python mpi_example_compressed.py
 import sys
 from mpi4py import MPI
 import numpy as np
 from netCDF4 import Dataset
 rank = MPI.COMM_WORLD.rank  # The process ID (integer 0-3 for 4-process run)
-nc = Dataset('parallel_test.nc', 'w', parallel=True)
+nc = Dataset('parallel_test_compressed.nc', 'w', parallel=True)
 d = nc.createDimension('dim',4)
 v = nc.createVariable('var', np.int32, 'dim', zlib=True)
 v[:] = np.arange(4)
@@ -13,6 +13,6 @@
 nc = Dataset('parallel_test.nc', 'a', parallel=True)
 v = nc['var']
 assert rank==v[rank]
-v.set_collective(True) # issue #1108
-v[rank]=1
+v.set_collective(True) # issue #1108 (var must be in collective mode or write will fail)
+v[rank]=2*rank
 nc.close()

From f2038aef59120377e60e194eb8f8894bdd6539f4 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 21 May 2021 14:13:32 -0600
Subject: [PATCH 0639/1504] add Changelog entry, bump version number

---
 Changelog                | 7 +++++--
 src/netCDF4/_netCDF4.pyx | 4 ++--
 2 files changed, 7 insertions(+), 4 deletions(-)

diff --git a/Changelog b/Changelog
index 4ca5c70bc..694d27e18 100644
--- a/Changelog
+++ b/Changelog
@@ -1,7 +1,10 @@
- since version 1.5.6
-====================
+ version 1.5.7 (not yet released)
+=================================
  * don't try to mask vlens with default  _FillValue, since vlens don't have a default _FillValue.
    This gets rid of numpy DeprecationWarning (issue #1099).
+ * update docs to reflect the fact that a variable must be in collective mode before writing
+   compressed data to it in parallel. Added a test for this (examples/mpi_example_compressed.py).
+   Issue #1108.
 
  version 1.5.6 (tag v1.5.6rel)
 ==============================
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index a124fd126..9174891ef 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1,5 +1,5 @@
 """
-Version 1.5.6
+Version 1.5.7
 -------------
 
 # Introduction
@@ -1204,7 +1204,7 @@ if sys.version_info[0:2] < (3, 7):
     # Python 3.7+ guarantees order; older versions need OrderedDict
     from collections import OrderedDict
 
-__version__ = "1.5.6"
+__version__ = "1.5.7"
 
 # Initialize numpy
 import posixpath

From 9026cf579775de845a001580a720d3c6e062df7c Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 21 May 2021 14:16:19 -0600
Subject: [PATCH 0640/1504] update docs

---
 docs/index.html | 12 ++++++++----
 1 file changed, 8 insertions(+), 4 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 93bca8670..f5e17365c 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -20,7 +20,7 @@
 
                     
    Contents
    
                     
 
  • Introduction
 
      
@@ -455,7 +455,7 @@ 
      API Documentation
      
                     
      
 netCDF4    
      
 
-                        
      Version 1.5.6
      
+                        
      Version 1.5.7
      
 
 
      Introduction
      
 
@@ -1423,7 +1423,11 @@ 
      Parallel IO
      
 If the write is done in independent mode, the operation will fail with a
 a generic "HDF Error".
 
    • You can write compressed data in parallel only with netcdf-c >= 4.7.4
-and hdf5 >= 1.10.3 (although you can read in parallel with earlier versions).
      • 
+and hdf5 >= 1.10.3 (although you can read in parallel with earlier versions). To write
+compressed data in parallel, the variable must be in 'collective IO mode'.  This is done
+automatically on variable creation if compression is turned on, but if you are appending
+to a variable in an existing file, you must use Variable.set_collective(True) before attempting
+to write to it.
 
    • You cannot use variable-length (VLEN) data types.
      • 
 
    
 
@@ -1590,7 +1594,7 @@ 
    In-memory (diskless) Datasets
    
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
    
 
-
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
+
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
 
 
    copyright: 2008 by Jeffrey Whitaker.
    
 

From da670783a6d6e012ba434df43b2c3b86565d6a10 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 22 May 2021 12:28:06 -0600
Subject: [PATCH 0641/1504] update

---
 examples/mpi_example_compressed.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/mpi_example_compressed.py b/examples/mpi_example_compressed.py
index de8043ba6..ece1d1ee2 100644
--- a/examples/mpi_example_compressed.py
+++ b/examples/mpi_example_compressed.py
@@ -10,7 +10,7 @@
 v[:] = np.arange(4)
 nc.close()
 # read compressed files in parallel, check the data, try to rewrite some data
-nc = Dataset('parallel_test.nc', 'a', parallel=True)
+nc = Dataset('parallel_test_compressed.nc', 'a', parallel=True)
 v = nc['var']
 assert rank==v[rank]
 v.set_collective(True) # issue #1108 (var must be in collective mode or write will fail)

From 943b8eb9bb54657a39ba851c50877da7893f3635 Mon Sep 17 00:00:00 2001
From: gdarkwah <61522557+gdarkwah@users.noreply.github.com>
Date: Fri, 4 Jun 2021 11:46:07 -0500
Subject: [PATCH 0642/1504] Conda Installation code
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Under the Quick Install section, I think the command for Conda installation should rather be Conda install -c conda-forge netCDF4 instead of using an underscore between “conda” and “forge”.
---
 docs/index.html | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/index.html b/docs/index.html
index f5e17365c..7b296910b 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -482,7 +482,7 @@ 
    Quick Install
    
 
 
      
 
    • the easiest way to get going is to install via pip install netCDF4.
-(or if you use the conda package manager conda install -c conda_forge netCDF4).
      • 
+(or if you use the conda package manager conda install -c conda-forge netCDF4).
 
    
 
 
    Developer Install
    

From 9982e9f13efb7629ac1a076dea302abe7c6cf870 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 4 Jun 2021 21:29:50 -0600
Subject: [PATCH 0643/1504] fix docstring

---
 src/netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 9174891ef..5b2996c8c 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -26,7 +26,7 @@ types) are not supported.
 ## Quick Install
 
  - the easiest way to get going is to install via `pip install netCDF4`.
-   (or if you use the [conda](http://conda.io) package manager `conda install -c conda_forge netCDF4`).
+   (or if you use the [conda](http://conda.io) package manager `conda install -c conda-forge netCDF4`).
 
 ## Developer Install
 

From dcec78a05d6b5b4d98c0937d67f5e9789c0fa881 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 4 Jun 2021 21:42:25 -0600
Subject: [PATCH 0644/1504] update docstring

---
 examples/tutorial.py     |  4 ++--
 src/netCDF4/_netCDF4.pyx | 13 +++++++------
 2 files changed, 9 insertions(+), 8 deletions(-)

diff --git a/examples/tutorial.py b/examples/tutorial.py
index 1f68a1c6d..c0d5d066b 100644
--- a/examples/tutorial.py
+++ b/examples/tutorial.py
@@ -111,9 +111,9 @@ def walktree(top):
 from netCDF4 import num2date, date2num, date2index
 dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
 times[:] = date2num(dates,units=times.units,calendar=times.calendar)
-print('time values (in units %s): ' % times.units+'\\n',times[:])
+print("time values (in units {}):\n{}".format(times.units, times[:]))
 dates = num2date(times[:],units=times.units,calendar=times.calendar)
-print('dates corresponding to time values:\\n',dates)
+print("dates corresponding to time values:\n{}".format(dates))
 
 rootgrp.close()
 
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 5b2996c8c..b649fdc41 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -580,15 +580,16 @@ Here's an example of how they can be used:
 >>> from cftime import num2date, date2num
 >>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
 >>> times[:] = date2num(dates,units=times.units,calendar=times.calendar)
->>> print("time values (in units {}):\\n{}".format(times.units, times[:]))
+>>> print("time values (in units {}):\n{}".format(times.units, times[:]))
 time values (in units hours since 0001-01-01 00:00:00.0):
 [17533104. 17533116. 17533128. 17533140. 17533152.]
 >>> dates = num2date(times[:],units=times.units,calendar=times.calendar)
->>> print("dates corresponding to time values:\\n{}".format(dates))
-dates corresponding to time values:
-[real_datetime(2001, 3, 1, 0, 0) real_datetime(2001, 3, 1, 12, 0)
- real_datetime(2001, 3, 2, 0, 0) real_datetime(2001, 3, 2, 12, 0)
- real_datetime(2001, 3, 3, 0, 0)]
+>>> print("dates corresponding to time values:\n{}".format(dates))
+ [cftime.DatetimeGregorian(2001, 3, 1, 0, 0, 0, 0, has_year_zero=False)
+  cftime.DatetimeGregorian(2001, 3, 1, 12, 0, 0, 0, has_year_zero=False)
+  cftime.DatetimeGregorian(2001, 3, 2, 0, 0, 0, 0, has_year_zero=False)
+  cftime.DatetimeGregorian(2001, 3, 2, 12, 0, 0, 0, has_year_zero=False)
+  cftime.DatetimeGregorian(2001, 3, 3, 0, 0, 0, 0, has_year_zero=False)]
 ```
 
 `num2date` converts numeric values of time in the specified `units`

From aea2cb0b0f518c0e6920b14ec2feb4c7663a19f8 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 4 Jun 2021 21:43:16 -0600
Subject: [PATCH 0645/1504] update html docs

---
 docs/index.html | 396 ++++++++++++++++++++++--------------------------
 1 file changed, 183 insertions(+), 213 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 7b296910b..431fabe15 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     netCDF4 API documentation
     
 
@@ -1014,15 +1014,18 @@ 
    Dealing with time coordinates
    
 >>> from cftime import num2date, date2num
 >>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
 >>> times[:] = date2num(dates,units=times.units,calendar=times.calendar)
->>> print("time values (in units {}):\n{}".format(times.units, times[:]))
+>>> print("time values (in units {}):
+{}".format(times.units, times[:]))
 time values (in units hours since 0001-01-01 00:00:00.0):
 [17533104. 17533116. 17533128. 17533140. 17533152.]
 >>> dates = num2date(times[:],units=times.units,calendar=times.calendar)
->>> print("dates corresponding to time values:\n{}".format(dates))
-dates corresponding to time values:
-[real_datetime(2001, 3, 1, 0, 0) real_datetime(2001, 3, 1, 12, 0)
- real_datetime(2001, 3, 2, 0, 0) real_datetime(2001, 3, 2, 12, 0)
- real_datetime(2001, 3, 3, 0, 0)]
+>>> print("dates corresponding to time values:
+{}".format(dates))
+ [cftime.DatetimeGregorian(2001, 3, 1, 0, 0, 0, 0, has_year_zero=False)
+  cftime.DatetimeGregorian(2001, 3, 1, 12, 0, 0, 0, has_year_zero=False)
+  cftime.DatetimeGregorian(2001, 3, 2, 0, 0, 0, 0, has_year_zero=False)
+  cftime.DatetimeGregorian(2001, 3, 2, 12, 0, 0, 0, has_year_zero=False)
+  cftime.DatetimeGregorian(2001, 3, 3, 0, 0, 0, 0, has_year_zero=False)]
 
    • 
 
 
    num2date converts numeric values of time in the specified units
@@ -1594,7 +1597,7 @@ 
    In-memory (diskless) Datasets
    
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
    
 
-
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
+
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
 
 
    copyright: 2008 by Jeffrey Whitaker.
    
 
@@ -1650,53 +1653,53 @@ 
    In-memory (diskless) Datasets
    
 
    The following class variables are read-only and should not be
 modified by the user.
    
 
-
    dimensions: The dimensions dictionary maps the names of
+
    dimensions: The dimensions dictionary maps the names of
 dimensions defined for the Group or Dataset to instances of the
 Dimension class.
    
 
-
    variables: The variables dictionary maps the names of variables
+
    variables: The variables dictionary maps the names of variables
 defined for this Dataset or Group to instances of the
 Variable class.
    
 
-
    groups: The groups dictionary maps the names of groups created for
+
    groups: The groups dictionary maps the names of groups created for
 this Dataset or Group to instances of the Group class (the
 Dataset class is simply a special case of the Group class which
 describes the root group in the netCDF4 file).
    
 
-
    cmptypes: The cmptypes dictionary maps the names of
+
    cmptypes: The cmptypes dictionary maps the names of
 compound types defined for the Group or Dataset to instances of the
 CompoundType class.
    
 
-
    vltypes: The vltypes dictionary maps the names of
+
    vltypes: The vltypes dictionary maps the names of
 variable-length types defined for the Group or Dataset to instances
 of the VLType class.
    
 
-
    enumtypes: The enumtypes dictionary maps the names of
+
    enumtypes: The enumtypes dictionary maps the names of
 Enum types defined for the Group or Dataset to instances
 of the EnumType class.
    
 
-
    data_model: data_model describes the netCDF
+
    data_model: data_model describes the netCDF
 data model version, one of NETCDF3_CLASSIC, NETCDF4,
 NETCDF4_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
    
 
-
    file_format: same as data_model, retained for backwards compatibility.
    
+
    file_format: same as data_model, retained for backwards compatibility.
    
 
-
    disk_format: disk_format describes the underlying
+
    disk_format: disk_format describes the underlying
 file format, one of NETCDF3, HDF5, HDF4,
 PNETCDF, DAP2, DAP4 or UNDEFINED. Only available if using
 netcdf C library version >= 4.3.1, otherwise will always return
 UNDEFINED.
    
 
-
    parent: parent is a reference to the parent
+
    parent: parent is a reference to the parent
 Group instance. None for the root group or Dataset
 instance.
    
 
-
    path: path shows the location of the Group in
+
    path: path shows the location of the Group in
 the Dataset in a unix directory format (the names of groups in the
 hierarchy separated by backslashes). A Dataset instance is the root
 group, so the path is simply '/'.
    
 
-
    keepweakref: If True, child Dimension and Variables objects only keep weak
+
    keepweakref: If True, child Dimension and Variables objects only keep weak
 references to the parent Dataset or Group.
    
 
 
    _ncstring_attrs__: If True, all text attributes will be written as variable-length
@@ -1708,8 +1711,7 @@ 
    In-memory (diskless) Datasets
    
                                         
    #  
 
         
-            Dataset()
-    
    
+            Dataset(unknown)    
    
 
         
             
    __init__(self, filename, mode="r", clobber=True, diskless=False,
@@ -1720,7 +1722,7 @@ 
    In-memory (diskless) Datasets
    
 
 
    filename: Name of netCDF file to hold dataset. Can also
 be a python 3 pathlib instance or the URL of an OpenDAP dataset.  When memory is
-set this is just used to set the filepath().
    
+set this is just used to set the filepath().
    
 
 
    mode: access mode. r means read-only; no data can be
 modified. w means write; a new file is created, an existing file with
@@ -1764,7 +1766,7 @@ 
    In-memory (diskless) Datasets
    
 
    persist: if diskless=True, persist file to disk when closed
 (default False).
    
 
-
    keepweakref: if True, child Dimension and Variable instances will keep weak
+
    keepweakref: if True, child Dimension and Variable instances will keep weak
 references to the parent Dataset or Group object.  Default is False, which
 means strong references will be kept.  Having Dimension and Variable instances
 keep a strong reference to the parent Dataset instance, which in turn keeps a
@@ -1890,7 +1892,7 @@ 
    In-memory (diskless) Datasets
    
 controlled by the variable's _Fill_Value attribute, but is usually
 sufficient to the use the netCDF default _Fill_Value (defined
 separately for each variable type). The default behavior of the netCDF
-library corresponds to set_fill_on.  Data which are equal to the
+library corresponds to set_fill_on.  Data which are equal to the
 _Fill_Value indicate that the variable was created, but never written
 to.
    
 
    
@@ -2037,7 +2039,7 @@ 
    In-memory (diskless) Datasets
    
 endian='native', least_significant_digit=None, fill_value=None, chunk_cache=None)
    
 
 
    Creates a new variable with the given varname, datatype, and
-dimensions. If dimensions are not given, the variable is assumed to be
+dimensions. If dimensions are not given, the variable is assumed to be
 a scalar.
    
 
 
    If varname is specified as a path, using forward slashes as in unix to
@@ -2061,7 +2063,7 @@ 
    In-memory (diskless) Datasets
    
 
    Data from netCDF variables is presented to python as numpy arrays with
 the corresponding data type.
    
 
-
    dimensions must be a tuple containing dimension names (strings) that
+
    dimensions must be a tuple containing dimension names (strings) that
 have been defined previously using Dataset.createDimension. The default value
 is an empty tuple, which means the variable is a scalar.
    
 
@@ -2142,11 +2144,11 @@ 
    In-memory (diskless) Datasets
    
 operations on the Variable instance. A Variable instance has six
 Dataset standard attributes: dimensions, dtype, shape, ndim, name and
 least_significant_digit. Application programs should never modify
-these attributes. The dimensions attribute is a tuple containing the
+these attributes. The dimensions attribute is a tuple containing the
 names of the dimensions associated with this variable. The dtype
 attribute is a string describing the variable's data type (i4, f8,
 S1, etc). The shape attribute is a tuple describing the current
-sizes of all the variable's dimensions. The name attribute is a
+sizes of all the variable's dimensions. The name attribute is a
 string containing the name of the Variable instance.
 The least_significant_digit
 attributes describes the power of ten of the smallest decimal place in
@@ -2586,9 +2588,7 @@ 
    In-memory (diskless) Datasets
    
         name = <attribute 'name' of 'netCDF4._netCDF4.Dataset' objects>
     
    
 
-            
    string name of Group instance
    
-
    
-
+    
 
                             
    
                             
    
@@ -2723,28 +2723,28 @@ 
    In-memory (diskless) Datasets
    
 
 
    The following class variables are read-only:
    
 
-
    dimensions: A tuple containing the names of the
+
    dimensions: A tuple containing the names of the
 dimensions associated with this variable.
    
 
-
    dtype: A numpy dtype object describing the
+
    dtype: A numpy dtype object describing the
 variable's data type.
    
 
-
    ndim: The number of variable dimensions.
    
+
    ndim: The number of variable dimensions.
    
 
-
    shape: A tuple with the current shape (length of all dimensions).
    
+
    shape: A tuple with the current shape (length of all dimensions).
    
 
-
    scale: If True, scale_factor and add_offset are
+
    scale: If True, scale_factor and add_offset are
 applied, and signed integer data is automatically converted to
 unsigned integer data if the _Unsigned attribute is set.
 Default is True, can be reset using Variable.set_auto_scale and
 Variable.set_auto_maskandscale methods.
    
 
-
    mask: If True, data is automatically converted to/from masked
+
    mask: If True, data is automatically converted to/from masked
 arrays when missing values or fill values are present. Default is True, can be
 reset using Variable.set_auto_mask and Variable.set_auto_maskandscale
 methods.
    
 
-
    chartostring: If True, data is automatically converted to/from character
+
    chartostring: If True, data is automatically converted to/from character
 arrays to string arrays when the _Encoding variable attribute is set.
 Default is True, can be reset using
 Variable.set_auto_chartostring method.
    
@@ -2759,12 +2759,12 @@ 
    In-memory (diskless) Datasets
    
 that are 1d arrays or lists slice along each dimension independently.  This
 behavior is similar to Fortran or Matlab, but different than numpy.
    
 
-
    datatype: numpy data type (for primitive data types) or VLType/CompoundType
+
    datatype: numpy data type (for primitive data types) or VLType/CompoundType
  instance (for compound or vlen data types).
    
 
-
    name: String name.
    
+
    name: String name.
    
 
-
    size: The number of stored elements.
    
+
    size: The number of stored elements.
    
 
    
 
 
@@ -2772,8 +2772,7 @@ 
    In-memory (diskless) Datasets
    
                                         
    #  
 
         
-            Variable()
-    
    
+            Variable(unknown)    
    
 
         
             
    __init__(self, group, name, datatype, dimensions=(), zlib=False,
@@ -2783,11 +2782,11 @@ 
    In-memory (diskless) Datasets
    
 
 
    Variable constructor.
    
 
-
    group: Group or Dataset instance to associate with variable.
    
+
    group: Group or Dataset instance to associate with variable.
    
 
-
    name: Name of the variable.
    
+
    name: Name of the variable.
    
 
-
    datatype: Variable data type. Can be specified by providing a
+
    datatype: Variable data type. Can be specified by providing a
 numpy dtype object, or a string that describes a numpy dtype object.
 Supported values, corresponding to str attribute of numpy dtype
 objects, include 'f4' (32-bit floating point), 'f8' (64-bit floating
@@ -2800,13 +2799,13 @@ 
    In-memory (diskless) Datasets
    
 typecodes can also be used ('f' instead of 'f4', 'd' instead of
 'f8', 'h' or 's' instead of 'i2', 'b' or 'B' instead of
 'i1', 'c' instead of 'S1', and 'i' or 'l' instead of
-'i4'). datatype can also be a CompoundType instance
+'i4'). datatype can also be a CompoundType instance
 (for a structured, or compound array), a VLType instance
 (for a variable-length array), or the python str builtin
 (for a variable-length string array). Numpy string and unicode datatypes with
 length greater than one are aliases for str.
    
 
-
    dimensions: a tuple containing the variable's dimension names
+
    dimensions: a tuple containing the variable's dimension names
 (defined previously with createDimension). Default is an empty tuple
 which means the variable is a scalar (and therefore has no dimensions).
    
 
@@ -2835,7 +2834,7 @@ 
    In-memory (diskless) Datasets
    
 closely as possible the size of the data block that users will read
 from the file. chunksizes cannot be set if contiguous=True.
    
 
-
    endian: Can be used to control whether the
+
    endian: Can be used to control whether the
 data is stored in little or big endian format on disk. Possible
 values are little, big or native (default). The library
 will automatically handle endian conversions when the data is read,
@@ -2862,7 +2861,7 @@ 
    In-memory (diskless) Datasets
    
 in the dictionary netCDF4.default_fillvals.
    
 
 
    chunk_cache: If specified, sets the chunk cache size for this variable.
-Persists as long as Dataset is open. Use set_var_chunk_cache to 
+Persists as long as Dataset is open. Use set_var_chunk_cache to 
 change it when Dataset is re-opened. 
    
 
 
    Note: Variable instances should be created using the
@@ -3151,7 +3150,7 @@ 
    In-memory (diskless) Datasets
    
 from numpy fixed length string arrays when the _Encoding variable attribute
 is set.
    
 
-
    If chartostring is set to True, when data is read from a character variable
+
    If chartostring is set to True, when data is read from a character variable
 (dtype = S1) that has an _Encoding attribute, it is converted to a numpy
 fixed length unicode string array (dtype = UN, where N is the length
 of the the rightmost dimension of the variable).  The value of _Encoding
@@ -3161,7 +3160,7 @@ 
    In-memory (diskless) Datasets
    
 indiviual bytes, with the number of bytes in each string equalling the
 rightmost dimension of the variable.
    
 
-
    The default value of chartostring is True
+
    The default value of chartostring is True
 (automatic conversions are performed).
    
 
    
 
@@ -3268,7 +3267,7 @@ 
    In-memory (diskless) Datasets
    
 to unsigned integer data if the variable has an _Unsigned
 attribute.
    
 
-
    If scale is set to True, and the variable has a
+
    If scale is set to True, and the variable has a
 scale_factor or an add_offset attribute, then data read
 from that variable is unpacked using::
    
 
@@ -3287,14 +3286,14 @@ 
    In-memory (diskless) Datasets
    
 used to provide simple compression, see the
 PSL metadata conventions.
    
 
-
    In addition, if scale is set to True, and if the variable has an
+
    In addition, if scale is set to True, and if the variable has an
 attribute _Unsigned set, and the variable has a signed integer data type,
 a view to the data is returned with the corresponding unsigned integer datatype.
 This convention is used by the netcdf-java library to save unsigned integer
 data in NETCDF3 or NETCDF4_CLASSIC files (since the NETCDF3
 data model does not have unsigned integer data types).
    
 
-
    The default value of scale is True
+
    The default value of scale is True
 (automatic conversions are performed).
    
 
    
 
@@ -3314,7 +3313,7 @@ 
    In-memory (diskless) Datasets
    
 
    turn on or off automatic conversion of variable data to and
 from masked arrays .
    
 
-
    If mask is set to True, when data is read from a variable
+
    If mask is set to True, when data is read from a variable
 it is converted to a masked array if any of the values are exactly
 equal to the either the netCDF _FillValue or the value specified by the
 missing_value variable attribute. The fill_value of the masked array
@@ -3329,7 +3328,7 @@ 
    In-memory (diskless) Datasets
    
 exists).  If the variable has no missing_value attribute, the _FillValue
 is used instead. 
    
 
-
    The default value of mask is True
+
    The default value of mask is True
 (automatic conversions are performed).
    
 
    
 
@@ -3349,7 +3348,7 @@ 
    In-memory (diskless) Datasets
    
 
    turn on or off conversion of data without missing values to regular
 numpy arrays.
    
 
-
    always_mask is a Boolean determining if automatic conversion of
+
    always_mask is a Boolean determining if automatic conversion of
 masked arrays with no missing values to regular numpy arrays shall be
 applied. Default is True. Set to False to restore the default behaviour
 in versions prior to 1.4.1 (numpy array returned unless missing values are present,
@@ -3420,9 +3419,7 @@ 
    In-memory (diskless) Datasets
    
         name = <attribute 'name' of 'netCDF4._netCDF4.Variable' objects>
     
    
 
-            
    string name of Variable instance
    
-
    
-
+    
 
                             
    
                             
    
@@ -3431,11 +3428,7 @@ 
    In-memory (diskless) Datasets
    
         datatype = <attribute 'datatype' of 'netCDF4._netCDF4.Variable' objects>
     
    
 
-            
    numpy data type (for primitive data types) or
-VLType/CompoundType/EnumType instance 
-(for compound, vlen  or enum data types)
    
-
    
-
+
    @@ -3444,9 +3437,7 @@

    In-memory (diskless) Datasets

    shape = <attribute 'shape' of 'netCDF4._netCDF4.Variable' objects>
    -

    find current sizes of all variable dimensions

    -
    - +
    @@ -3455,9 +3446,7 @@

    In-memory (diskless) Datasets

    size = <attribute 'size' of 'netCDF4._netCDF4.Variable' objects>
    -

    Return the number of stored elements.

    -
    - +
    @@ -3466,9 +3455,7 @@

    In-memory (diskless) Datasets

    dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Variable' objects>
    -

    get variables's dimension names

    -
    - +
    @@ -3546,10 +3533,10 @@

    In-memory (diskless) Datasets

    Read-only class variables:

    -

    name: String name, used when creating a Variable with +

    name: String name, used when creating a Variable with Dataset.createVariable.

    -

    size: Current Dimension size (same as len(d), where d is a +

    size: Current Dimension size (same as len(d), where d is a Dimension instance).

    @@ -3558,19 +3545,18 @@

    In-memory (diskless) Datasets

    #   - Dimension() -
    + Dimension(unknown)

    __init__(self, group, name, size=None)

    Dimension constructor.

    -

    group: Group instance to associate with dimension.

    +

    group: Group instance to associate with dimension.

    -

    name: Name of the dimension.

    +

    name: Name of the dimension.

    -

    size: Size of the dimension. None or 0 means unlimited. (Default None).

    +

    size: Size of the dimension. None or 0 means unlimited. (Default None).

    Note: Dimension instances should be created using the Dataset.createDimension method of a Group or @@ -3617,9 +3603,7 @@

    In-memory (diskless) Datasets

    name = <attribute 'name' of 'netCDF4._netCDF4.Dimension' objects>
    -

    string name of Dimension instance

    -
    - +
    @@ -3628,9 +3612,7 @@

    In-memory (diskless) Datasets

    size = <attribute 'size' of 'netCDF4._netCDF4.Dimension' objects>
    -

    current size of Dimension (calls len on Dimension instance)

    -
    - + @@ -3640,7 +3622,7 @@

    In-memory (diskless) Datasets

    class - Group(netCDF4.Dataset): + Group(netCDF4._netCDF4.Dataset): @@ -3652,11 +3634,11 @@

    In-memory (diskless) Datasets

    Group inherits from Dataset, so all the Dataset class methods and variables are available -to a Group instance (except the close method).

    +to a Group instance (except the close method).

    Additional read-only class variables:

    -

    name: String describing the group name.

    +

    name: String describing the group name.

    @@ -3664,17 +3646,16 @@

    In-memory (diskless) Datasets

    #   - Group() -
    + Group(unknown)

    __init__(self, parent, name) Group constructor.

    -

    parent: Group instance for the parent group. If being created +

    parent: Group instance for the parent group. If being created in the root group, use a Dataset instance.

    -

    name: - Name of the group.

    +

    name: - Name of the group.

    Note: Group instances should be created using the Dataset.createGroup method of a Dataset instance, or @@ -3703,50 +3684,50 @@

    In-memory (diskless) Datasets

    Inherited Members
    -
    Dataset
    -
    filepath
    -
    isopen
    -
    sync
    -
    set_fill_on
    -
    set_fill_off
    -
    createDimension
    -
    renameDimension
    -
    createCompoundType
    -
    createVLType
    -
    createEnumType
    -
    createVariable
    -
    renameVariable
    -
    createGroup
    -
    ncattrs
    -
    setncattr
    -
    setncattr_string
    -
    setncatts
    -
    getncattr
    -
    delncattr
    -
    renameAttribute
    -
    renameGroup
    -
    set_auto_chartostring
    -
    set_auto_maskandscale
    -
    set_auto_mask
    -
    set_auto_scale
    -
    set_always_mask
    -
    set_ncstring_attrs
    -
    get_variables_by_attributes
    -
    fromcdl
    -
    tocdl
    -
    name
    -
    groups
    -
    dimensions
    -
    variables
    -
    disk_format
    -
    path
    -
    parent
    -
    file_format
    -
    data_model
    -
    cmptypes
    -
    vltypes
    -
    enumtypes
    -
    keepweakref
    +
    netCDF4._netCDF4.Dataset
    +
    filepath
    +
    isopen
    +
    sync
    +
    set_fill_on
    +
    set_fill_off
    +
    createDimension
    +
    renameDimension
    +
    createCompoundType
    +
    createVLType
    +
    createEnumType
    +
    createVariable
    +
    renameVariable
    +
    createGroup
    +
    ncattrs
    +
    setncattr
    +
    setncattr_string
    +
    setncatts
    +
    getncattr
    +
    delncattr
    +
    renameAttribute
    +
    renameGroup
    +
    set_auto_chartostring
    +
    set_auto_maskandscale
    +
    set_auto_mask
    +
    set_auto_scale
    +
    set_always_mask
    +
    set_ncstring_attrs
    +
    get_variables_by_attributes
    +
    fromcdl
    +
    tocdl
    +
    name
    +
    groups
    +
    dimensions
    +
    variables
    +
    disk_format
    +
    path
    +
    parent
    +
    file_format
    +
    data_model
    +
    cmptypes
    +
    vltypes
    +
    enumtypes
    +
    keepweakref
    @@ -3758,7 +3739,7 @@
    Inherited Members
    class - MFDataset(netCDF4.Dataset): + MFDataset(netCDF4._netCDF4.Dataset):
    @@ -3795,8 +3776,7 @@
    Inherited Members
    #   - MFDataset(files, check=False, aggdim=None, exclude=[], master_file=None) -
    + MFDataset(files, check=False, aggdim=None, exclude=[], master_file=None)

    __init__(self, files, check=False, aggdim=None, exclude=[], @@ -3870,49 +3850,49 @@

    Inherited Members
    Inherited Members
    -
    Dataset
    -
    filepath
    -
    isopen
    -
    sync
    -
    set_fill_on
    -
    set_fill_off
    -
    createDimension
    -
    renameDimension
    -
    createCompoundType
    -
    createVLType
    -
    createEnumType
    -
    createVariable
    -
    renameVariable
    -
    createGroup
    -
    setncattr
    -
    setncattr_string
    -
    setncatts
    -
    getncattr
    -
    delncattr
    -
    renameAttribute
    -
    renameGroup
    -
    set_auto_chartostring
    -
    set_auto_maskandscale
    -
    set_auto_mask
    -
    set_auto_scale
    -
    set_always_mask
    -
    set_ncstring_attrs
    -
    get_variables_by_attributes
    -
    fromcdl
    -
    tocdl
    -
    name
    -
    groups
    -
    dimensions
    -
    variables
    -
    disk_format
    -
    path
    -
    parent
    -
    file_format
    -
    data_model
    -
    cmptypes
    -
    vltypes
    -
    enumtypes
    -
    keepweakref
    +
    netCDF4._netCDF4.Dataset
    +
    filepath
    +
    isopen
    +
    sync
    +
    set_fill_on
    +
    set_fill_off
    +
    createDimension
    +
    renameDimension
    +
    createCompoundType
    +
    createVLType
    +
    createEnumType
    +
    createVariable
    +
    renameVariable
    +
    createGroup
    +
    setncattr
    +
    setncattr_string
    +
    setncatts
    +
    getncattr
    +
    delncattr
    +
    renameAttribute
    +
    renameGroup
    +
    set_auto_chartostring
    +
    set_auto_maskandscale
    +
    set_auto_mask
    +
    set_auto_scale
    +
    set_always_mask
    +
    set_ncstring_attrs
    +
    get_variables_by_attributes
    +
    fromcdl
    +
    tocdl
    +
    name
    +
    groups
    +
    dimensions
    +
    variables
    +
    disk_format
    +
    path
    +
    parent
    +
    file_format
    +
    data_model
    +
    cmptypes
    +
    vltypes
    +
    enumtypes
    +
    keepweakref
    @@ -3966,8 +3946,7 @@
    Inherited Members
    #   - MFTime(time, units=None, calendar=None) -
    + MFTime(time, units=None, calendar=None)

    __init__(self, time, units=None, calendar=None)

    @@ -4020,7 +3999,7 @@
    Inherited Members
    Compound data types map to numpy structured arrays. See CompoundType.__init__ for more details.

    -

    The instance variables dtype and name should not be modified by +

    The instance variables dtype and name should not be modified by the user.

    @@ -4029,8 +4008,7 @@
    Inherited Members
    #   - CompoundType() -
    + CompoundType(unknown)

    __init__(group, datatype, datatype_name)

    @@ -4101,7 +4079,7 @@
    Inherited Members
    a Dataset or Group instance. See VLType.__init__ for more details.

    -

    The instance variables dtype and name should not be modified by +

    The instance variables dtype and name should not be modified by the user.

    @@ -4110,8 +4088,7 @@
    Inherited Members
    #   - VLType() -
    + VLType(unknown)

    __init__(group, datatype, datatype_name)

    @@ -4182,7 +4159,7 @@
    Inherited Members

    calendar: describes the calendar to be used in the time calculations. All the values currently defined in the -CF metadata convention <http://cfconventions.org/cf-conventions/cf-conventions#calendar>__ are supported. +CF metadata convention <http://cfconventions.org>__ are supported. Valid calendars 'standard', 'gregorian', 'proleptic_gregorian' 'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'. Default is None which means the calendar associated with the first @@ -4192,10 +4169,8 @@

    Inherited Members
    is used and the year zero exists. If set to False for real-world calendars, then historical year numbering is used and the year 1 is preceded by year -1 and no year zero exists. -The defaults are set to conform with -CF version 1.9 conventions (False for 'julian', 'gregorian'/'standard', True -for 'proleptic_gregorian' (ISO 8601) and True for the idealized -calendars 'noleap'/'365_day', '360_day', 366_day'/'all_leap') +The defaults are False for real-world calendars +and True for idealized calendars. The defaults can only be over-ridden for the real-world calendars, for the the idealized calendars the year zero always exists and the has_year_zero kwarg is ignored. @@ -4234,7 +4209,7 @@
    Inherited Members

    calendar: describes the calendar used in the time calculations. All the values currently defined in the -CF metadata convention <http://cfconventions.org/cf-conventions/cf-conventions#calendar>__ are supported. +CF metadata convention <http://cfconventions.org>__ are supported. Valid calendars 'standard', 'gregorian', 'proleptic_gregorian' 'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'. Default is 'standard', which is a mixed Julian/Gregorian calendar.

    @@ -4251,10 +4226,8 @@
    Inherited Members
    is used and the year zero exists. If set to False for real-world calendars, then historical year numbering is used and the year 1 is preceded by year -1 and no year zero exists. -The defaults are set to conform with -CF version 1.9 conventions (False for 'julian', 'gregorian'/'standard', True -for 'proleptic_gregorian' (ISO 8601) and True for the idealized -calendars 'noleap'/'365_day', '360_day', 366_day'/'all_leap') +The defaults are False for real-world calendars +and True for idealized calendars. The defaults can only be over-ridden for the real-world calendars, for the the idealized calendars the year zero always exists and the has_year_zero kwarg is ignored. @@ -4300,7 +4273,7 @@
    Inherited Members

    calendar: describes the calendar to be used in the time calculations. All the values currently defined in the -CF metadata convention <http://cfconventions.org/cf-conventions/cf-conventions#calendar>__ are supported. +CF metadata convention <http://cfconventions.org>__ are supported. Valid calendars 'standard', 'gregorian', 'proleptic_gregorian' 'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'. Default is None which means the calendar associated with the first @@ -4317,10 +4290,8 @@

    Inherited Members
    is used and the year zero exists. If set to False for real-world calendars, then historical year numbering is used and the year 1 is preceded by year -1 and no year zero exists. -The defaults are set to conform with -CF version 1.9 conventions (False for 'julian', 'gregorian'/'standard', True -for 'proleptic_gregorian' (ISO 8601) and True for the idealized -calendars 'noleap'/'365_day', '360_day', 366_day'/'all_leap') +The defaults are False for real-world calendars +and True for idealized calendars. The defaults can only be over-ridden for the real-world calendars, for the the idealized calendars the year zero always exists and the has_year_zero kwarg is ignored. @@ -4447,7 +4418,7 @@
    Inherited Members
    a Dataset or Group instance. See EnumType.__init__ for more details.

    -

    The instance variables dtype, name and enum_dict should not be modified by +

    The instance variables dtype, name and enum_dict should not be modified by the user.

    @@ -4456,8 +4427,7 @@
    Inherited Members
    #   - EnumType() -
    + EnumType(unknown)

    __init__(group, datatype, datatype_name, enum_dict)

    @@ -4472,7 +4442,7 @@
    Inherited Members

    datatype_name: a Python string containing a description of the Enum data type.

    -

    enum_dict: a Python dictionary containing the Enum field/value +

    enum_dict: a Python dictionary containing the Enum field/value pairs.

    Note: EnumType instances should be created using the From 09116e7cd6f35f8b69e160613fa8a0f254bef9a8 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Fri, 4 Jun 2021 21:53:01 -0600 Subject: [PATCH 0646/1504] update docs --- docs/index.html | 372 +++++++++++++++++++++------------------ src/netCDF4/_netCDF4.pyx | 4 +- 2 files changed, 201 insertions(+), 175 deletions(-) diff --git a/docs/index.html b/docs/index.html index 431fabe15..154907fa4 100644 --- a/docs/index.html +++ b/docs/index.html @@ -3,14 +3,14 @@ - + netCDF4 API documentation - - - + + +

    - +

    string name of Group instance

    +
    +
    @@ -2723,28 +2725,28 @@

    In-memory (diskless) Datasets

    The following class variables are read-only:

    -

    dimensions: A tuple containing the names of the +

    dimensions: A tuple containing the names of the dimensions associated with this variable.

    -

    dtype: A numpy dtype object describing the +

    dtype: A numpy dtype object describing the variable's data type.

    -

    ndim: The number of variable dimensions.

    +

    ndim: The number of variable dimensions.

    -

    shape: A tuple with the current shape (length of all dimensions).

    +

    shape: A tuple with the current shape (length of all dimensions).

    -

    scale: If True, scale_factor and add_offset are +

    scale: If True, scale_factor and add_offset are applied, and signed integer data is automatically converted to unsigned integer data if the _Unsigned attribute is set. Default is True, can be reset using Variable.set_auto_scale and Variable.set_auto_maskandscale methods.

    -

    mask: If True, data is automatically converted to/from masked +

    mask: If True, data is automatically converted to/from masked arrays when missing values or fill values are present. Default is True, can be reset using Variable.set_auto_mask and Variable.set_auto_maskandscale methods.

    -

    chartostring: If True, data is automatically converted to/from character +

    chartostring: If True, data is automatically converted to/from character arrays to string arrays when the _Encoding variable attribute is set. Default is True, can be reset using Variable.set_auto_chartostring method.

    @@ -2759,12 +2761,12 @@

    In-memory (diskless) Datasets

    that are 1d arrays or lists slice along each dimension independently. This behavior is similar to Fortran or Matlab, but different than numpy.

    -

    datatype: numpy data type (for primitive data types) or VLType/CompoundType +

    datatype: numpy data type (for primitive data types) or VLType/CompoundType instance (for compound or vlen data types).

    -

    name: String name.

    +

    name: String name.

    -

    size: The number of stored elements.

    +

    size: The number of stored elements.

    @@ -2772,7 +2774,8 @@

    In-memory (diskless) Datasets

    #   - Variable(unknown)
    + Variable() +

    __init__(self, group, name, datatype, dimensions=(), zlib=False, @@ -2782,11 +2785,11 @@

    In-memory (diskless) Datasets

    Variable constructor.

    -

    group: Group or Dataset instance to associate with variable.

    +

    group: Group or Dataset instance to associate with variable.

    -

    name: Name of the variable.

    +

    name: Name of the variable.

    -

    datatype: Variable data type. Can be specified by providing a +

    datatype: Variable data type. Can be specified by providing a numpy dtype object, or a string that describes a numpy dtype object. Supported values, corresponding to str attribute of numpy dtype objects, include 'f4' (32-bit floating point), 'f8' (64-bit floating @@ -2799,13 +2802,13 @@

    In-memory (diskless) Datasets

    typecodes can also be used ('f' instead of 'f4', 'd' instead of 'f8', 'h' or 's' instead of 'i2', 'b' or 'B' instead of 'i1', 'c' instead of 'S1', and 'i' or 'l' instead of -'i4'). datatype can also be a CompoundType instance +'i4'). datatype can also be a CompoundType instance (for a structured, or compound array), a VLType instance (for a variable-length array), or the python str builtin (for a variable-length string array). Numpy string and unicode datatypes with length greater than one are aliases for str.

    -

    dimensions: a tuple containing the variable's dimension names +

    dimensions: a tuple containing the variable's dimension names (defined previously with createDimension). Default is an empty tuple which means the variable is a scalar (and therefore has no dimensions).

    @@ -2834,7 +2837,7 @@

    In-memory (diskless) Datasets

    closely as possible the size of the data block that users will read from the file. chunksizes cannot be set if contiguous=True.

    -

    endian: Can be used to control whether the +

    endian: Can be used to control whether the data is stored in little or big endian format on disk. Possible values are little, big or native (default). The library will automatically handle endian conversions when the data is read, @@ -2861,7 +2864,7 @@

    In-memory (diskless) Datasets

    in the dictionary netCDF4.default_fillvals.

    chunk_cache: If specified, sets the chunk cache size for this variable. -Persists as long as Dataset is open. Use set_var_chunk_cache to +Persists as long as Dataset is open. Use set_var_chunk_cache to change it when Dataset is re-opened.

    Note: Variable instances should be created using the @@ -3150,7 +3153,7 @@

    In-memory (diskless) Datasets

    from numpy fixed length string arrays when the _Encoding variable attribute is set.

    -

    If chartostring is set to True, when data is read from a character variable +

    If chartostring is set to True, when data is read from a character variable (dtype = S1) that has an _Encoding attribute, it is converted to a numpy fixed length unicode string array (dtype = UN, where N is the length of the the rightmost dimension of the variable). The value of _Encoding @@ -3160,7 +3163,7 @@

    In-memory (diskless) Datasets

    indiviual bytes, with the number of bytes in each string equalling the rightmost dimension of the variable.

    -

    The default value of chartostring is True +

    The default value of chartostring is True (automatic conversions are performed).

    @@ -3267,7 +3270,7 @@

    In-memory (diskless) Datasets

    to unsigned integer data if the variable has an _Unsigned attribute.

    -

    If scale is set to True, and the variable has a +

    If scale is set to True, and the variable has a scale_factor or an add_offset attribute, then data read from that variable is unpacked using::

    @@ -3286,14 +3289,14 @@

    In-memory (diskless) Datasets

    used to provide simple compression, see the PSL metadata conventions.

    -

    In addition, if scale is set to True, and if the variable has an +

    In addition, if scale is set to True, and if the variable has an attribute _Unsigned set, and the variable has a signed integer data type, a view to the data is returned with the corresponding unsigned integer datatype. This convention is used by the netcdf-java library to save unsigned integer data in NETCDF3 or NETCDF4_CLASSIC files (since the NETCDF3 data model does not have unsigned integer data types).

    -

    The default value of scale is True +

    The default value of scale is True (automatic conversions are performed).

    @@ -3313,7 +3316,7 @@

    In-memory (diskless) Datasets

    turn on or off automatic conversion of variable data to and from masked arrays .

    -

    If mask is set to True, when data is read from a variable +

    If mask is set to True, when data is read from a variable it is converted to a masked array if any of the values are exactly equal to the either the netCDF _FillValue or the value specified by the missing_value variable attribute. The fill_value of the masked array @@ -3328,7 +3331,7 @@

    In-memory (diskless) Datasets

    exists). If the variable has no missing_value attribute, the _FillValue is used instead.

    -

    The default value of mask is True +

    The default value of mask is True (automatic conversions are performed).

    @@ -3348,7 +3351,7 @@

    In-memory (diskless) Datasets

    turn on or off conversion of data without missing values to regular numpy arrays.

    -

    always_mask is a Boolean determining if automatic conversion of +

    always_mask is a Boolean determining if automatic conversion of masked arrays with no missing values to regular numpy arrays shall be applied. Default is True. Set to False to restore the default behaviour in versions prior to 1.4.1 (numpy array returned unless missing values are present, @@ -3419,7 +3422,9 @@

    In-memory (diskless) Datasets

    name = <attribute 'name' of 'netCDF4._netCDF4.Variable' objects> - +

    string name of Variable instance

    +
    +
    @@ -3428,7 +3433,11 @@

    In-memory (diskless) Datasets

    datatype = <attribute 'datatype' of 'netCDF4._netCDF4.Variable' objects>
    - +

    numpy data type (for primitive data types) or +VLType/CompoundType/EnumType instance +(for compound, vlen or enum data types)

    +
    +
    @@ -3437,7 +3446,9 @@

    In-memory (diskless) Datasets

    shape = <attribute 'shape' of 'netCDF4._netCDF4.Variable' objects>
    - +

    find current sizes of all variable dimensions

    +
    +
    @@ -3446,7 +3457,9 @@

    In-memory (diskless) Datasets

    size = <attribute 'size' of 'netCDF4._netCDF4.Variable' objects>
    - +

    Return the number of stored elements.

    +
    +
    @@ -3455,7 +3468,9 @@

    In-memory (diskless) Datasets

    dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Variable' objects>
    - +

    get variables's dimension names

    +
    +
    @@ -3533,10 +3548,10 @@

    In-memory (diskless) Datasets

    Read-only class variables:

    -

    name: String name, used when creating a Variable with +

    name: String name, used when creating a Variable with Dataset.createVariable.

    -

    size: Current Dimension size (same as len(d), where d is a +

    size: Current Dimension size (same as len(d), where d is a Dimension instance).

    @@ -3545,18 +3560,19 @@

    In-memory (diskless) Datasets

    #   - Dimension(unknown)
    + Dimension() +

    __init__(self, group, name, size=None)

    Dimension constructor.

    -

    group: Group instance to associate with dimension.

    +

    group: Group instance to associate with dimension.

    -

    name: Name of the dimension.

    +

    name: Name of the dimension.

    -

    size: Size of the dimension. None or 0 means unlimited. (Default None).

    +

    size: Size of the dimension. None or 0 means unlimited. (Default None).

    Note: Dimension instances should be created using the Dataset.createDimension method of a Group or @@ -3603,7 +3619,9 @@

    In-memory (diskless) Datasets

    name = <attribute 'name' of 'netCDF4._netCDF4.Dimension' objects>
    - +

    string name of Dimension instance

    +
    +
    @@ -3612,7 +3630,9 @@

    In-memory (diskless) Datasets

    size = <attribute 'size' of 'netCDF4._netCDF4.Dimension' objects>
    - +

    current size of Dimension (calls len on Dimension instance)

    +
    + @@ -3622,7 +3642,7 @@

    In-memory (diskless) Datasets

    class - Group(netCDF4._netCDF4.Dataset): + Group(netCDF4.Dataset): @@ -3634,11 +3654,11 @@

    In-memory (diskless) Datasets

    Group inherits from Dataset, so all the Dataset class methods and variables are available -to a Group instance (except the close method).

    +to a Group instance (except the close method).

    Additional read-only class variables:

    -

    name: String describing the group name.

    +

    name: String describing the group name.

    @@ -3646,16 +3666,17 @@

    In-memory (diskless) Datasets

    #   - Group(unknown)
    + Group() +

    __init__(self, parent, name) Group constructor.

    -

    parent: Group instance for the parent group. If being created +

    parent: Group instance for the parent group. If being created in the root group, use a Dataset instance.

    -

    name: - Name of the group.

    +

    name: - Name of the group.

    Note: Group instances should be created using the Dataset.createGroup method of a Dataset instance, or @@ -3684,50 +3705,50 @@

    In-memory (diskless) Datasets

    Inherited Members
    -
    netCDF4._netCDF4.Dataset
    -
    filepath
    -
    isopen
    -
    sync
    -
    set_fill_on
    -
    set_fill_off
    -
    createDimension
    -
    renameDimension
    -
    createCompoundType
    -
    createVLType
    -
    createEnumType
    -
    createVariable
    -
    renameVariable
    -
    createGroup
    -
    ncattrs
    -
    setncattr
    -
    setncattr_string
    -
    setncatts
    -
    getncattr
    -
    delncattr
    -
    renameAttribute
    -
    renameGroup
    -
    set_auto_chartostring
    -
    set_auto_maskandscale
    -
    set_auto_mask
    -
    set_auto_scale
    -
    set_always_mask
    -
    set_ncstring_attrs
    -
    get_variables_by_attributes
    -
    fromcdl
    -
    tocdl
    -
    name
    -
    groups
    -
    dimensions
    -
    variables
    -
    disk_format
    -
    path
    -
    parent
    -
    file_format
    -
    data_model
    -
    cmptypes
    -
    vltypes
    -
    enumtypes
    -
    keepweakref
    +
    @@ -3739,7 +3760,7 @@
    Inherited Members
    class - MFDataset(netCDF4._netCDF4.Dataset): + MFDataset(netCDF4.Dataset):
    @@ -3776,7 +3797,8 @@
    Inherited Members
    #   - MFDataset(files, check=False, aggdim=None, exclude=[], master_file=None)
    + MFDataset(files, check=False, aggdim=None, exclude=[], master_file=None) +

    __init__(self, files, check=False, aggdim=None, exclude=[], @@ -3850,49 +3872,49 @@

    Inherited Members
    Inherited Members
    -
    netCDF4._netCDF4.Dataset
    -
    filepath
    -
    isopen
    -
    sync
    -
    set_fill_on
    -
    set_fill_off
    -
    createDimension
    -
    renameDimension
    -
    createCompoundType
    -
    createVLType
    -
    createEnumType
    -
    createVariable
    -
    renameVariable
    -
    createGroup
    -
    setncattr
    -
    setncattr_string
    -
    setncatts
    -
    getncattr
    -
    delncattr
    -
    renameAttribute
    -
    renameGroup
    -
    set_auto_chartostring
    -
    set_auto_maskandscale
    -
    set_auto_mask
    -
    set_auto_scale
    -
    set_always_mask
    -
    set_ncstring_attrs
    -
    get_variables_by_attributes
    -
    fromcdl
    -
    tocdl
    -
    name
    -
    groups
    -
    dimensions
    -
    variables
    -
    disk_format
    -
    path
    -
    parent
    -
    file_format
    -
    data_model
    -
    cmptypes
    -
    vltypes
    -
    enumtypes
    -
    keepweakref
    +
    @@ -3904,7 +3926,7 @@
    Inherited Members
    class - MFTime(netCDF4._netCDF4._Variable): + MFTime(netCDF4._netCDF4._Variable):
    @@ -3946,7 +3968,8 @@
    Inherited Members
    #   - MFTime(time, units=None, calendar=None)
    + MFTime(time, units=None, calendar=None) +

    __init__(self, time, units=None, calendar=None)

    @@ -3999,7 +4022,7 @@
    Inherited Members
    Compound data types map to numpy structured arrays. See CompoundType.__init__ for more details.

    -

    The instance variables dtype and name should not be modified by +

    The instance variables dtype and name should not be modified by the user.

    @@ -4008,7 +4031,8 @@
    Inherited Members
    #   - CompoundType(unknown)
    + CompoundType() +

    __init__(group, datatype, datatype_name)

    @@ -4079,7 +4103,7 @@
    Inherited Members
    a Dataset or Group instance. See VLType.__init__ for more details.

    -

    The instance variables dtype and name should not be modified by +

    The instance variables dtype and name should not be modified by the user.

    @@ -4088,7 +4112,8 @@
    Inherited Members
    #   - VLType(unknown)
    + VLType() +

    __init__(group, datatype, datatype_name)

    @@ -4418,7 +4443,7 @@
    Inherited Members
    a Dataset or Group instance. See EnumType.__init__ for more details.

    -

    The instance variables dtype, name and enum_dict should not be modified by +

    The instance variables dtype, name and enum_dict should not be modified by the user.

    @@ -4427,7 +4452,8 @@
    Inherited Members
    #   - EnumType(unknown)
    + EnumType() +

    __init__(group, datatype, datatype_name, enum_dict)

    @@ -4442,7 +4468,7 @@
    Inherited Members

    datatype_name: a Python string containing a description of the Enum data type.

    -

    enum_dict: a Python dictionary containing the Enum field/value +

    enum_dict: a Python dictionary containing the Enum field/value pairs.

    Note: EnumType instances should be created using the diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index b649fdc41..5f0b0d437 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -580,11 +580,11 @@ Here's an example of how they can be used: >>> from cftime import num2date, date2num >>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])] >>> times[:] = date2num(dates,units=times.units,calendar=times.calendar) ->>> print("time values (in units {}):\n{}".format(times.units, times[:])) +>>> print("time values (in units {}):\\n{}".format(times.units, times[:])) time values (in units hours since 0001-01-01 00:00:00.0): [17533104. 17533116. 17533128. 17533140. 17533152.] >>> dates = num2date(times[:],units=times.units,calendar=times.calendar) ->>> print("dates corresponding to time values:\n{}".format(dates)) +>>> print("dates corresponding to time values:\\n{}".format(dates)) [cftime.DatetimeGregorian(2001, 3, 1, 0, 0, 0, 0, has_year_zero=False) cftime.DatetimeGregorian(2001, 3, 1, 12, 0, 0, 0, has_year_zero=False) cftime.DatetimeGregorian(2001, 3, 2, 0, 0, 0, 0, has_year_zero=False) From 19f11229d5d4e3bf20d5b5674fe3c41cfa2ab5d5 Mon Sep 17 00:00:00 2001 From: jswhit Date: Tue, 8 Jun 2021 11:33:22 -0600 Subject: [PATCH 0647/1504] fix for issue #1112 --- Changelog | 1 + src/netCDF4/utils.py | 6 +++--- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/Changelog b/Changelog index 694d27e18..ac0e37c02 100644 --- a/Changelog +++ b/Changelog @@ -5,6 +5,7 @@ * update docs to reflect the fact that a variable must be in collective mode before writing compressed data to it in parallel. Added a test for this (examples/mpi_example_compressed.py). Issue #1108. + * Fix OverflowError when dimension sizes become greater than 2**32-1 elements on Windows (Issue #1112). version 1.5.6 (tag v1.5.6rel) ============================== diff --git a/src/netCDF4/utils.py b/src/netCDF4/utils.py index 8ea4d642c..68b391aa8 100644 --- a/src/netCDF4/utils.py +++ b/src/netCDF4/utils.py @@ -380,9 +380,9 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\ # Create the start, count, stride and indices arrays. sdim.append(max(nDims, 1)) - start = np.empty(sdim, dtype=int) - count = np.empty(sdim, dtype=int) - stride = np.empty(sdim, dtype=int) + start = np.empty(sdim, dtype=np.intp) + count = np.empty(sdim, dtype=np.intp) + stride = np.empty(sdim, dtype=np.intp) indices = np.empty(sdim, dtype=object) for i, e in enumerate(elem): From f665eca78f7497885cd480737f43d29105ed00b5 Mon Sep 17 00:00:00 2001 From: jswhit Date: Tue, 8 Jun 2021 13:04:29 -0600 Subject: [PATCH 0648/1504] add test for issue #1112 --- test/tst_slicing.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/test/tst_slicing.py b/test/tst_slicing.py index ec37d0edf..9d14ba7d3 100644 --- a/test/tst_slicing.py +++ b/test/tst_slicing.py @@ -18,12 +18,14 @@ def setUp(self): f = Dataset(file_name,'w') f.createDimension('x',xdim) f.createDimension('xu',None) + f.createDimension('xu2',None) f.createDimension('y',ydim) f.createDimension('z',zdim) f.createDimension('zu',None) v = f.createVariable('data','u1',('x','y','z')) vu = f.createVariable('datau','u1',('xu','y','zu')) v1 = f.createVariable('data1d', 'u1', ('x',)) + v2 = f.createVariable('data1dx', 'u1', ('xu2',)) # variable with no unlimited dim. # write slice in reverse order v[:,::-1,:] = data @@ -33,6 +35,7 @@ def setUp(self): vu[:,::-1,:] = data v1[:] = data[:, 0, 0] + v2[0:2**31] = 1 # issue 1112 (overflow on windows) f.close() def tearDown(self): @@ -75,8 +78,10 @@ def test_3d(self): def test_1d(self): f = Dataset(self.file, 'r') v1 = f.variables['data1d'] + v2 = f.variables['data1dx'] d = data[:,0,0] assert_equal(v1[:], d) + assert_equal(v2[:], np.ones(2**31,dtype=np.uint8)) assert_equal(v1[4:], d[4:]) # test return of array scalar. assert_equal(v1[0].shape, ()) From c18d8eaaeb4243461fa277bb740160f8f9233b46 Mon Sep 17 00:00:00 2001 From: jswhit Date: Tue, 8 Jun 2021 13:32:15 -0600 Subject: [PATCH 0649/1504] update to reduce memory footprint --- test/tst_slicing.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/test/tst_slicing.py b/test/tst_slicing.py index 9d14ba7d3..7d56f54c6 100644 --- a/test/tst_slicing.py +++ b/test/tst_slicing.py @@ -35,7 +35,8 @@ def setUp(self): vu[:,::-1,:] = data v1[:] = data[:, 0, 0] - v2[0:2**31] = 1 # issue 1112 (overflow on windows) + #v2[0:2**31] = 1 # issue 1112 (overflow on windows) + v2[2**31] = 1 # issue 1112 (overflow on windows) f.close() def tearDown(self): @@ -81,7 +82,8 @@ def test_1d(self): v2 = f.variables['data1dx'] d = data[:,0,0] assert_equal(v1[:], d) - assert_equal(v2[:], np.ones(2**31,dtype=np.uint8)) + #assert_equal(v2[:], np.ones(2**31,dtype=np.uint8)) + assert_equal(v2[2**31], 1) assert_equal(v1[4:], d[4:]) # test return of array scalar. assert_equal(v1[0].shape, ()) From 814e61bf491058a6b13d0c98ca14c339e5e141c8 Mon Sep 17 00:00:00 2001 From: jswhit Date: Tue, 8 Jun 2021 13:37:01 -0600 Subject: [PATCH 0650/1504] back off change to intp to see if test reproduces windows failure --- src/netCDF4/utils.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/src/netCDF4/utils.py b/src/netCDF4/utils.py index 68b391aa8..141cc680a 100644 --- a/src/netCDF4/utils.py +++ b/src/netCDF4/utils.py @@ -380,7 +380,8 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\ # Create the start, count, stride and indices arrays. sdim.append(max(nDims, 1)) - start = np.empty(sdim, dtype=np.intp) + start = np.empty(sdim, dtype=int) + #start = np.empty(sdim, dtype=np.intp) count = np.empty(sdim, dtype=np.intp) stride = np.empty(sdim, dtype=np.intp) indices = np.empty(sdim, dtype=object) From e0eca0a818df5d99e14978692a50449f280d75b7 Mon Sep 17 00:00:00 2001 From: jswhit Date: Tue, 8 Jun 2021 13:45:35 -0600 Subject: [PATCH 0651/1504] revert previous commit (verified that test fails without change to intp) --- src/netCDF4/utils.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/src/netCDF4/utils.py b/src/netCDF4/utils.py index 141cc680a..68b391aa8 100644 --- a/src/netCDF4/utils.py +++ b/src/netCDF4/utils.py @@ -380,8 +380,7 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\ # Create the start, count, stride and indices arrays. sdim.append(max(nDims, 1)) - start = np.empty(sdim, dtype=int) - #start = np.empty(sdim, dtype=np.intp) + start = np.empty(sdim, dtype=np.intp) count = np.empty(sdim, dtype=np.intp) stride = np.empty(sdim, dtype=np.intp) indices = np.empty(sdim, dtype=object) From a3d60572b9bacffa5a993bc8c25444bed973f8dd Mon Sep 17 00:00:00 2001 From: Mike Taves Date: Tue, 15 Jun 2021 12:12:18 +1200 Subject: [PATCH 0652/1504] MAINT: Python3 classes do not need to inherit from object --- src/netCDF4/_netCDF4.pyx | 4 ++-- test/tst_utils.py | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 5f0b0d437..b1c1ffbb7 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -6386,7 +6386,7 @@ Example usage (See `MFDataset.__init__` for more details): # raise error is user tries to pickle a MFDataset object. raise NotImplementedError('MFDataset is not picklable') -class _Dimension(object): +class _Dimension: def __init__(self, dimname, dim, dimlens, dimtotlen): self.dimlens = dimlens self.dimtotlen = dimtotlen @@ -6403,7 +6403,7 @@ class _Dimension(object): return "%r: name = '%s', size = %s" %\ (type(self), self._name, len(self)) -class _Variable(object): +class _Variable: def __init__(self, dset, varname, var, recdimname): self.dimensions = var.dimensions self._dset = dset diff --git a/test/tst_utils.py b/test/tst_utils.py index 816be84b6..026fb1550 100644 --- a/test/tst_utils.py +++ b/test/tst_utils.py @@ -320,7 +320,7 @@ def test_ellipsis(self): #assert_equal(str(e), "At most one ellipsis allowed in a slicing expression") assert_equal(str(e), "list index out of range") -class FakeGroup(object): +class FakeGroup: """Create a fake group instance by passing a dictionary of booleans keyed by dimension name.""" def __init__(self, dimensions): @@ -328,7 +328,7 @@ def __init__(self, dimensions): for k,v in dimensions.items(): self.dimensions[k] = FakeDimension(v) -class FakeDimension(object): +class FakeDimension: def __init__(self, unlimited=False): self.unlimited = unlimited From 2198612782774ef798ff0399356fb0c40210e3dc Mon Sep 17 00:00:00 2001 From: Mike Taves Date: Tue, 15 Jun 2021 12:26:00 +1200 Subject: [PATCH 0653/1504] MAINT: use 'yield from ' to walk tree --- examples/tutorial.py | 7 +++---- src/netCDF4/_netCDF4.pyx | 6 ++---- src/netCDF4/utils.py | 6 ++---- test/tst_grps.py | 6 ++---- 4 files changed, 9 insertions(+), 16 deletions(-) diff --git a/examples/tutorial.py b/examples/tutorial.py index c0d5d066b..204138533 100644 --- a/examples/tutorial.py +++ b/examples/tutorial.py @@ -16,11 +16,10 @@ # walk the group tree using a Python generator. def walktree(top): - values = top.groups.values() - yield values + yield top.groups.values() for value in top.groups.values(): - for children in walktree(value): - yield children + yield from walktree(value) + print(rootgrp) for children in walktree(rootgrp): for child in children: diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 5f0b0d437..5be551b22 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -184,11 +184,9 @@ object yields summary information about it's contents. ```python >>> def walktree(top): -... values = top.groups.values() -... yield values +... yield top.groups.values() ... for value in top.groups.values(): -... for children in walktree(value): -... yield children +... yield from walktree(value) >>> print(rootgrp) root group (NETCDF4 data model, file format HDF5): diff --git a/src/netCDF4/utils.py b/src/netCDF4/utils.py index 68b391aa8..98aad3954 100644 --- a/src/netCDF4/utils.py +++ b/src/netCDF4/utils.py @@ -58,11 +58,9 @@ def _walk_grps(topgrp): """Iterate through all (sub-) groups of topgrp, similar to os.walktree. """ - grps = topgrp.groups.values() - yield grps + yield topgrp.groups.values() for grp in topgrp.groups.values(): - for children in _walk_grps(grp): - yield children + yield from _walk_grps(grp) def _quantize(data,least_significant_digit): """ diff --git a/test/tst_grps.py b/test/tst_grps.py index b3c9428f4..179789961 100644 --- a/test/tst_grps.py +++ b/test/tst_grps.py @@ -30,11 +30,9 @@ # python generator to walk the Group tree. def walktree(top): - values = top.groups.values() - yield values + yield top.groups.values() for value in top.groups.values(): - for children in walktree(value): - yield children + yield from walktree(value) class GroupsTestCase(unittest.TestCase): From 67622de334d3d2971111d54bd9156e26288ca227 Mon Sep 17 00:00:00 2001 From: jswhit Date: Tue, 15 Jun 2021 16:09:44 -0400 Subject: [PATCH 0654/1504] don't return masked arrays for vlen types --- Changelog | 1 + src/netCDF4/_netCDF4.pyx | 6 +++--- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/Changelog b/Changelog index ac0e37c02..2b129986b 100644 --- a/Changelog +++ b/Changelog @@ -6,6 +6,7 @@ compressed data to it in parallel. Added a test for this (examples/mpi_example_compressed.py). Issue #1108. * Fix OverflowError when dimension sizes become greater than 2**32-1 elements on Windows (Issue #1112). + * Don't return masked arrays for vlens (only for primitive and enum types - issue #1115). version 1.5.6 (tag v1.5.6rel) ============================== diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 5f0b0d437..bb4ae240c 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -4440,9 +4440,9 @@ rename a `Variable` attribute named `oldname` to `newname`.""" msg = 'invalid scale_factor or add_offset attribute, no unpacking done...' warnings.warn(msg) - if self.mask and\ - (self._isprimitive or self._isenum or\ - (self._isvlen and self.dtype != str)): + if self.mask and (self._isprimitive or self._isenum):\ +# (self._isprimitive or self._isenum or\ +# (self._isvlen and self.dtype != str)): data = self._toma(data) else: # if attribute _Unsigned is True, and variable has signed integer From cab173674e9cc99e06d6bb900b6b2f92868edfda Mon Sep 17 00:00:00 2001 From: jswhit Date: Tue, 15 Jun 2021 16:30:28 -0400 Subject: [PATCH 0655/1504] update test --- test/tst_vlen.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/test/tst_vlen.py b/test/tst_vlen.py index f047a879f..e23ec6a47 100644 --- a/test/tst_vlen.py +++ b/test/tst_vlen.py @@ -205,10 +205,10 @@ def setUp(self): for nlen in ilen: data = np.random.uniform(low=0.0, high=1.0, size=nlen) if n==99: - # mark last value as missing - mask = np.zeros(data.shape,dtype=bool) - mask[-1] = True - data = np.ma.masked_array(data, mask=mask) + # # mark last value as missing + # mask = np.zeros(data.shape,dtype=bool) + # mask[-1] = True + # data = np.ma.masked_array(data, mask=mask) self.data = data v[n] = data n += 1 @@ -221,14 +221,14 @@ def runTest(self): nc = Dataset(self.file) # see if data is masked data = nc['vl'][-1] - assert(data[-1] is np.ma.masked) + #assert(data[-1] is np.ma.masked) # check max error of compression err = np.abs(data - self.data) assert(err.max() < nc['vl'].scale_factor) # turn off auto-scaling nc.set_auto_maskandscale(False) data = nc['vl'][-1] - assert(data[-1] == 255) + assert(data[-1] == np.around(self.data[-1]/nc['vl'].scale_factor)) nc.close() if __name__ == '__main__': From c4c4aed055015c327e64b15fdb995cdca35094be Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Fri, 18 Jun 2021 10:10:54 -0600 Subject: [PATCH 0656/1504] update --- src/netCDF4/_netCDF4.pyx | 2 -- test/tst_vlen.py | 9 +-------- 2 files changed, 1 insertion(+), 10 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index bb4ae240c..6d3628214 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -4441,8 +4441,6 @@ rename a `Variable` attribute named `oldname` to `newname`.""" warnings.warn(msg) if self.mask and (self._isprimitive or self._isenum):\ -# (self._isprimitive or self._isenum or\ -# (self._isvlen and self.dtype != str)): data = self._toma(data) else: # if attribute _Unsigned is True, and variable has signed integer diff --git a/test/tst_vlen.py b/test/tst_vlen.py index e23ec6a47..5d7d4f2ce 100644 --- a/test/tst_vlen.py +++ b/test/tst_vlen.py @@ -204,13 +204,8 @@ def setUp(self): n = 0 for nlen in ilen: data = np.random.uniform(low=0.0, high=1.0, size=nlen) - if n==99: - # # mark last value as missing - # mask = np.zeros(data.shape,dtype=bool) - # mask[-1] = True - # data = np.ma.masked_array(data, mask=mask) - self.data = data v[n] = data + if n==99: self.data = data n += 1 nc.close() def tearDown(self): @@ -219,9 +214,7 @@ def tearDown(self): def runTest(self): """testing packing float vlens as scaled integers (issue #1003).""" nc = Dataset(self.file) - # see if data is masked data = nc['vl'][-1] - #assert(data[-1] is np.ma.masked) # check max error of compression err = np.abs(data - self.data) assert(err.max() < nc['vl'].scale_factor) From 639b099547f98068bb97521fca7b65df470bc6f1 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Fri, 18 Jun 2021 13:08:08 -0600 Subject: [PATCH 0657/1504] update docstring --- src/netCDF4/_netCDF4.pyx | 11 +++++++---- 1 file changed, 7 insertions(+), 4 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 6d3628214..6d194becb 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -551,8 +551,9 @@ shape of fancy temp slice = (3, 3, 36, 71) The result will be a numpy scalar array. By default, netcdf4-python returns numpy masked arrays with values equal to the -`missing_value` or `_FillValue` variable attributes masked. The -`Dataset.set_auto_mask` `Dataset` and `Variable` methods +`missing_value` or `_FillValue` variable attributes masked for primitive and +enum data types. +The `Dataset.set_auto_mask` `Dataset` and `Variable` methods can be used to disable this feature so that numpy arrays are always returned, with the missing values included. Prior to version 1.4.0 the default behavior was to only return masked arrays when the @@ -3019,7 +3020,8 @@ after calling this function will follow the default behaviour. **`set_auto_mask(self, True_or_False)`** Call `Variable.set_auto_mask` for all variables contained in this `Dataset` or -`Group`, as well as for all variables in all its subgroups. +`Group`, as well as for all variables in all its subgroups. Only affects +Variables with primitive or enum types (not compound or vlen Variables). **`True_or_False`**: Boolean determining if automatic conversion to masked arrays shall be applied for all variables. @@ -3538,7 +3540,8 @@ Default is `True`, can be reset using `Variable.set_auto_scale` and **`mask`**: If True, data is automatically converted to/from masked arrays when missing values or fill values are present. Default is `True`, can be reset using `Variable.set_auto_mask` and `Variable.set_auto_maskandscale` -methods. +methods. Only relevant for Variables with primitive or enum types (ignored +for compound and vlen Variables). **`chartostring`**: If True, data is automatically converted to/from character arrays to string arrays when the `_Encoding` variable attribute is set. From 25f436410f0f3f1593d7ef910e2426a8f26c0db7 Mon Sep 17 00:00:00 2001 From: Mike Taves Date: Tue, 15 Jun 2021 13:59:29 +1200 Subject: [PATCH 0658/1504] MAINT: remove a few Python2 features, mostly u'string' -> 'string' --- examples/json_att.py | 2 +- examples/tutorial.py | 6 +++--- setup.py | 10 ++-------- src/netCDF4/utils.py | 9 +-------- test/run_all.py | 8 -------- test/tst_atts.py | 12 ++++++------ test/tst_enum.py | 6 +++--- test/tst_grps.py | 12 ++++++------ test/tst_masked5.py | 6 +++--- test/tst_types.py | 12 ++++-------- test/tst_unicode.py | 13 +++++++------ test/tst_unicode3.py | 42 ------------------------------------------ 12 files changed, 36 insertions(+), 102 deletions(-) delete mode 100644 test/tst_unicode3.py diff --git a/examples/json_att.py b/examples/json_att.py index 7d95a7e89..59e5c1241 100644 --- a/examples/json_att.py +++ b/examples/json_att.py @@ -4,7 +4,7 @@ # can be serialized as strings, saved as netCDF attributes, # and then converted back to python objects using json. ds = Dataset('json.nc', 'w') -ds.pythonatt1 = json.dumps([u'foo', {u'bar': [u'baz', None, 1.0, 2]}]) +ds.pythonatt1 = json.dumps(['foo', {'bar': ['baz', None, 1.0, 2]}]) ds.pythonatt2 = "true" # converted to bool ds.pythonatt3 = "null" # converted to None print(ds) diff --git a/examples/tutorial.py b/examples/tutorial.py index c0d5d066b..c375ec5bd 100644 --- a/examples/tutorial.py +++ b/examples/tutorial.py @@ -266,9 +266,9 @@ def walktree(top): # Enum type example. f = Dataset('clouds.nc','w') # python dict describing the allowed values and their names. -enum_dict = {u'Altocumulus': 7, u'Missing': 255, u'Stratus': 2, u'Clear': 0, -u'Nimbostratus': 6, u'Cumulus': 4, u'Altostratus': 5, u'Cumulonimbus': 1, -u'Stratocumulus': 3} +enum_dict = {'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, +'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, +'Stratocumulus': 3} # create the Enum type called 'cloud_t'. cloud_type = f.createEnumType(np.uint8,'cloud_t',enum_dict) print(cloud_type) diff --git a/setup.py b/setup.py index 99df3ede0..17e7afc46 100644 --- a/setup.py +++ b/setup.py @@ -1,5 +1,6 @@ import os, sys, subprocess import os.path as osp +import configparser from setuptools import setup, Extension from distutils.dist import Distribution @@ -15,14 +16,7 @@ }, } -if sys.version_info[0] < 3: - import ConfigParser as configparser - - open_kwargs = {} -else: - import configparser - - open_kwargs = {'encoding': 'utf-8'} +open_kwargs = {'encoding': 'utf-8'} def check_hdf5version(hdf5_includedir): diff --git a/src/netCDF4/utils.py b/src/netCDF4/utils.py index 68b391aa8..d4892029b 100644 --- a/src/netCDF4/utils.py +++ b/src/netCDF4/utils.py @@ -8,13 +8,6 @@ import getopt import os -python3 = sys.version_info[0] > 2 -if python3: - # no unicode type in python 3, use bytes instead when testing - # for a string-like object - unicode = str -else: - range = xrange try: bytes except NameError: @@ -223,7 +216,7 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\ # string-like object try to cast to int # needs to be done first, since strings are iterable and # hard to distinguish from something castable to an iterable numpy array. - if type(e) in [str,bytes,unicode]: + if type(e) in [str, bytes]: try: e = int(e) except: diff --git a/test/run_all.py b/test/run_all.py index dc1aa5fc6..d7dc07776 100755 --- a/test/run_all.py +++ b/test/run_all.py @@ -6,16 +6,8 @@ # can also just run # python -m unittest discover . 'tst*py' -python3 = sys.version_info[0] > 2 - # Find all test files. test_files = glob.glob('tst_*.py') -if python3: - test_files.remove('tst_unicode.py') - sys.stdout.write('not running tst_unicode.py ...\n') -else: - test_files.remove('tst_unicode3.py') - sys.stdout.write('not running tst_unicode3.py ...\n') if __netcdf4libversion__ < '4.2.1' or __has_parallel4_support__ or __has_pnetcdf_support__: test_files.remove('tst_diskless.py') sys.stdout.write('not running tst_diskless.py ...\n') diff --git a/test/tst_atts.py b/test/tst_atts.py index f50bc35eb..e9d53d489 100644 --- a/test/tst_atts.py +++ b/test/tst_atts.py @@ -112,18 +112,18 @@ def setUp(self): # issue #529 write string attribute as NC_CHAR unless # it can't be decoded to ascii. Add setncattr_string # method to force NC_STRING. - f.charatt = u'foo' # will be written as NC_CHAR + f.charatt = 'foo' # will be written as NC_CHAR f.setncattr_string('stringatt','bar') # NC_STRING - f.cafe = u'caf\xe9' # NC_STRING - f.batt = u'caf\xe9'.encode('utf-8') #NC_CHAR + f.cafe = 'caf\xe9' # NC_STRING + f.batt = 'caf\xe9'.encode('utf-8') #NC_CHAR v.setncattr_string('stringatt','bar') # NC_STRING # issue #882 - provide an option to always string attribute # as NC_STRINGs. Testing various approaches to setting text attributes... f.set_ncstring_attrs(True) - f.stringatt_ncstr = u'foo' # will now be written as NC_STRING + f.stringatt_ncstr = 'foo' # will now be written as NC_STRING f.setncattr_string('stringatt_ncstr','bar') # NC_STRING anyway - f.caf_ncstr = u'caf\xe9' # NC_STRING anyway - f.bat_ncstr = u'caf\xe9'.encode('utf-8') # now NC_STRING + f.caf_ncstr = 'caf\xe9' # NC_STRING anyway + f.bat_ncstr = 'caf\xe9'.encode('utf-8') # now NC_STRING g.stratt_ncstr = STRATT # now NC_STRING #g.renameAttribute('stratt_tmp','stratt_ncstr') v.setncattr_string('stringatt_ncstr','bar') # NC_STRING anyway diff --git a/test/tst_enum.py b/test/tst_enum.py index 43bbb14b8..8069ad2f3 100644 --- a/test/tst_enum.py +++ b/test/tst_enum.py @@ -10,9 +10,9 @@ ENUM_NAME = 'cloud_t' ENUM_BASETYPE = np.int8 VAR_NAME = 'primary_cloud' -ENUM_DICT = {u'Altocumulus': 7, u'Missing': 127, u'Stratus': 2, u'Clear': 0, -u'Nimbostratus': 6, u'Cumulus': 4, u'Altostratus': 5, u'Cumulonimbus': 1, -u'Stratocumulus': 3} +ENUM_DICT = {'Altocumulus': 7, 'Missing': 127, 'Stratus': 2, 'Clear': 0, +'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, +'Stratocumulus': 3} datain = np.array([ENUM_DICT['Clear'],ENUM_DICT['Stratus'],ENUM_DICT['Cumulus'],\ ENUM_DICT['Missing'],ENUM_DICT['Cumulonimbus']],dtype=ENUM_BASETYPE) datain_masked = np.ma.masked_values(datain,ENUM_DICT['Missing']) diff --git a/test/tst_grps.py b/test/tst_grps.py index b3c9428f4..a4e41f808 100644 --- a/test/tst_grps.py +++ b/test/tst_grps.py @@ -8,12 +8,12 @@ FILE_NAME1 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name FILE_NAME2 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name -DYNASTY=u"Tudor" -HENRY_VII=u"Henry_VII" -MARGARET=u"Margaret" -JAMES_V_OF_SCOTLAND=u"James_V_of_Scotland" -MARY_I_OF_SCOTLAND=u"Mary_I_of_Scotland" -JAMES_VI_OF_SCOTLAND_AND_I_OF_ENGLAND=u"James_VI_of_Scotland_and_I_of_England" +DYNASTY = "Tudor" +HENRY_VII = "Henry_VII" +MARGARET = "Margaret" +JAMES_V_OF_SCOTLAND = "James_V_of_Scotland" +MARY_I_OF_SCOTLAND = "Mary_I_of_Scotland" +JAMES_VI_OF_SCOTLAND_AND_I_OF_ENGLAND = "James_VI_of_Scotland_and_I_of_England" names = [HENRY_VII,MARGARET,JAMES_V_OF_SCOTLAND,MARY_I_OF_SCOTLAND,JAMES_VI_OF_SCOTLAND_AND_I_OF_ENGLAND] root = '/' TREE1 = [root] diff --git a/test/tst_masked5.py b/test/tst_masked5.py index af49bf168..3d8dba4db 100755 --- a/test/tst_masked5.py +++ b/test/tst_masked5.py @@ -24,7 +24,7 @@ def setUp(self): d = f.createDimension('x',6) v = f.createVariable('v', "i2", 'x') # issue 730: set fill_value for vlen str vars - v2 = f.createVariable('v2',str,'x',fill_value=u'') + v2 = f.createVariable('v2', str, 'x', fill_value='') v.missing_value = self.missing_values v[:] = self.v @@ -56,8 +56,8 @@ def test_scaled(self): # this part fails with netcdf 4.1.3 # a bug in vlen strings? if __netcdf4libversion__ >= '4.4.0': - assert (v2[0]==u'first') - assert (v2[1]==u'') + assert v2[0] == 'first' + assert v2[1] == '' f.close() diff --git a/test/tst_types.py b/test/tst_types.py index b346d1bc9..1fc290957 100644 --- a/test/tst_types.py +++ b/test/tst_types.py @@ -75,16 +75,12 @@ def runTest(self): # issue 271 (_FillValue should be a byte for character arrays on # Python 3) v = f.variables['issue271'] - if type(v._FillValue) == bytes: - assert(v._FillValue == b'Z') # python 3 - else: - assert(v._FillValue == u'Z') # python 2 + assert type(v._FillValue) == bytes + assert v._FillValue == b'Z' # issue 273 (setting _FillValue to null byte manually) v2 = f.variables['issue273'] - if type(v2._FillValue) == bytes: - assert(v2._FillValue == b'\x00') # python 3 - else: - assert(v2._FillValue == u'') # python 2 + assert type(v2._FillValue) == bytes + assert v2._FillValue == b'\x00' assert(str(issue273_data) == str(v2[:])) # issue 707 (don't apply missing_value if cast to variable type is # unsafe) diff --git a/test/tst_unicode.py b/test/tst_unicode.py index 48e5c9ccd..69d3020b1 100644 --- a/test/tst_unicode.py +++ b/test/tst_unicode.py @@ -3,11 +3,11 @@ import sys, unittest, os, tempfile FILE_NAME = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name -ATT1 = u'\u03a0\u03a3\u03a9' -ATT2 = u'x\xb0' -ATT3 = [u'\u03a0',u'\u03a3',u'\u03a9'] -DIM_NAME = u'x\xb0' -VAR_NAME = u'Andr\xe9' +ATT1 = '\u03a0\u03a3\u03a9' +ATT2 = 'x\xb0' +ATT3 = ['\u03a0', '\u03a3', '\u03a9'] +DIM_NAME = 'x\xb0' +VAR_NAME = 'Andr\xe9' class UnicodeTestCase(unittest.TestCase): @@ -34,7 +34,8 @@ def runTest(self): assert f.attribute1 == ATT1 assert f.attribute2 == ATT2 #assert f.attribute3 == ''.join(ATT3) - assert f.attribute3 == ATT3 # behavior changed issue 770 + # behavior changed issue 770 + assert f.attribute3 == ATT3 f.close() if __name__ == '__main__': diff --git a/test/tst_unicode3.py b/test/tst_unicode3.py deleted file mode 100644 index 1dab5646d..000000000 --- a/test/tst_unicode3.py +++ /dev/null @@ -1,42 +0,0 @@ -import netCDF4 -import numpy as np -import sys, unittest, os, tempfile - -FILE_NAME = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name -ATT1 = '\u03a0\u03a3\u03a9' -ATT2 = 'x\xb0' -ATT3 = ['\u03a0','\u03a3','\u03a9'] -DIM_NAME = 'x\xb0' -VAR_NAME = 'Andr\xe9' - -class UnicodeTestCase(unittest.TestCase): - - def setUp(self): - self.file = FILE_NAME - f = netCDF4.Dataset(self.file,'w') - f.attribute1 = ATT1 - f.attribute2 = ATT2 - f.attribute3 = ATT3 - d = f.createDimension(DIM_NAME, None) - v = f.createVariable(VAR_NAME, np.float64, (DIM_NAME,)) - f.close() - - def tearDown(self): - # Remove the temporary files - os.remove(self.file) - - def runTest(self): - """testing unicode""" - f = netCDF4.Dataset(self.file, 'r') - d = f.dimensions[DIM_NAME] - v = f.variables[VAR_NAME] - # check accessing individual attributes. - assert f.attribute1 == ATT1 - assert f.attribute2 == ATT2 - #assert f.attribute3 == ''.join(ATT3) - # behavior changed pull request #771 - assert f.attribute3 == ATT3 - f.close() - -if __name__ == '__main__': - unittest.main() From c25c53d5dca620c2db78f88fb90fccb9f9dfa25b Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Sun, 20 Jun 2021 13:11:25 -0600 Subject: [PATCH 0659/1504] update Changelog and docs/index.html --- Changelog | 4 ++-- docs/index.html | 19 ++++++++++--------- 2 files changed, 12 insertions(+), 11 deletions(-) diff --git a/Changelog b/Changelog index 2b129986b..efa2121a0 100644 --- a/Changelog +++ b/Changelog @@ -1,5 +1,5 @@ - version 1.5.7 (not yet released) -================================= + version 1.5.7 (tag v1.5.7rel) +============================== * don't try to mask vlens with default _FillValue, since vlens don't have a default _FillValue. This gets rid of numpy DeprecationWarning (issue #1099). * update docs to reflect the fact that a variable must be in collective mode before writing diff --git a/docs/index.html b/docs/index.html index 154907fa4..149208924 100644 --- a/docs/index.html +++ b/docs/index.html @@ -641,11 +641,9 @@

    Groups in a netCDF file

    object yields summary information about it's contents.

    >>> def walktree(top):
-...     values = top.groups.values()
-...     yield values
+...     yield top.groups.values()
 ...     for value in top.groups.values():
-...         for children in walktree(value):
-...             yield children
+...         yield from walktree(value)
 >>> print(rootgrp)
 <class 'netCDF4._netCDF4.Dataset'>
 root group (NETCDF4 data model, file format HDF5):
@@ -987,8 +985,9 @@ 
    Writing data
 The result will be a numpy scalar array.
    
 
 
    By default, netcdf4-python returns numpy masked arrays with values equal to the
-missing_value or _FillValue variable attributes masked.  The
-Dataset.set_auto_mask Dataset and Variable methods
+missing_value or _FillValue variable attributes masked for primitive and
+enum data types.
+The Dataset.set_auto_mask Dataset and Variable methods
 can be used to disable this feature so that
 numpy arrays are always returned, with the missing values included. Prior to
 version 1.4.0 the default behavior was to only return masked arrays when the
@@ -1596,7 +1595,7 @@ 
    In-memory (diskless) Datasets
    
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
    
 
-
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
+
    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
    
 
 
    copyright: 2008 by Jeffrey Whitaker.
    
 
@@ -2403,7 +2402,8 @@ 
    In-memory (diskless) Datasets
    
             
    set_auto_mask(self, True_or_False)
    
 
 
    Call Variable.set_auto_mask for all variables contained in this Dataset or
-Group, as well as for all variables in all its subgroups.
    
+Group, as well as for all variables in all its subgroups. Only affects
+Variables with primitive or enum types (not compound or vlen Variables).
    
 
 
    True_or_False: Boolean determining if automatic conversion to masked arrays
 shall be applied for all variables.
    
@@ -2744,7 +2744,8 @@ 
    In-memory (diskless) Datasets
    
 
    mask: If True, data is automatically converted to/from masked
 arrays when missing values or fill values are present. Default is True, can be
 reset using Variable.set_auto_mask and Variable.set_auto_maskandscale
-methods.
    
+methods. Only relevant for Variables with primitive or enum types (ignored
+for compound and vlen Variables).
    
 
 
    chartostring: If True, data is automatically converted to/from character
 arrays to string arrays when the _Encoding variable attribute is set.

From e5eb3fa062516398895cef2a16558bbaef6d00d8 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 20 Jun 2021 15:59:19 -0600
Subject: [PATCH 0660/1504] fix test so it doesn't fail on 32 bit machines

---
 test/tst_slicing.py | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/test/tst_slicing.py b/test/tst_slicing.py
index 7d56f54c6..1b5c0bde2 100644
--- a/test/tst_slicing.py
+++ b/test/tst_slicing.py
@@ -2,7 +2,7 @@
 from numpy.random import seed, randint
 from numpy.testing import assert_array_equal, assert_equal,\
 assert_array_almost_equal
-import tempfile, unittest, os, random
+import tempfile, unittest, os, random, sys
 import numpy as np
 
 file_name = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
@@ -35,8 +35,8 @@ def setUp(self):
         vu[:,::-1,:] = data
 
         v1[:] = data[:, 0, 0]
-        #v2[0:2**31] = 1 # issue 1112 (overflow on windows)
-        v2[2**31] = 1 # issue 1112 (overflow on windows)
+        if sys.maxsize > 2**32:
+            v2[2**31] = 1 # issue 1112 (overflow on windows)
         f.close()
 
     def tearDown(self):
@@ -82,8 +82,8 @@ def test_1d(self):
         v2 = f.variables['data1dx']
         d = data[:,0,0]
         assert_equal(v1[:], d)
-        #assert_equal(v2[:], np.ones(2**31,dtype=np.uint8))
-        assert_equal(v2[2**31], 1)
+        if sys.maxsize > 2**32:
+            assert_equal(v2[2**31], 1)
         assert_equal(v1[4:], d[4:])
         # test return of array scalar.
         assert_equal(v1[0].shape, ())

From 26761d0826de4bb695074fe7be43973dd2a0f206 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 20 Jun 2021 20:26:41 -0600
Subject: [PATCH 0661/1504] update

---
 README.md | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/README.md b/README.md
index 268179b08..cebdc014c 100644
--- a/README.md
+++ b/README.md
@@ -10,6 +10,10 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
+6/22/2021:  Version [1.5.7](https://pypi.python.org/pypi/netCDF4/1.5.7) released.
+Fixed OverflowError on Windows when reading data with dimension sizes greater than 2**32-1.
+Masked arrays no longer returned for vlens.
+
 2/15/2021:  Version [1.5.6](https://pypi.python.org/pypi/netCDF4/1.5.6) released. Added `Dataset.fromcdl` and `Dataset.tocdl`, which require `ncdump` and `ncgen` utilities to be in `$PATH`. Removed python 2.7 support.
 
 12/20/2020: Version [1.5.5.1](https://pypi.python.org/pypi/netCDF4/1.5.5.1) released.

From 16c0a0bf8a418b5399430b992b6627c7f4706836 Mon Sep 17 00:00:00 2001
From: Tim Gates 
Date: Mon, 13 Sep 2021 22:25:06 +1000
Subject: [PATCH 0662/1504] docs: Fix a few typos

There are small typos in:
- README.md
- README.wheels.md
- examples/subset.py
- src/netCDF4/utils.py
- test/tst_Unsigned.py
- test/tst_atts.py
- test/tst_fancyslicing.py
- test/tst_masked4.py
- test/tst_shape.py

Fixes:
- Should read `boolean` rather than `boolen`.
- Should read `surprising` rather than `suprising`.
- Should read `request` rather than `reqeust`.
- Should read `renaming` rather than `renameing`.
- Should read `reanalysis` rather than `reanlysis`.
- Should read `re-enabled` rather than `renabled`.
- Should read `permission` rather than `permision`.
- Should read `assignment` rather than `assigment`.
- Should read `argument` rather than `argumenbt`.
---
 README.md                | 2 +-
 README.wheels.md         | 2 +-
 examples/subset.py       | 2 +-
 src/netCDF4/utils.py     | 4 ++--
 test/tst_Unsigned.py     | 2 +-
 test/tst_atts.py         | 2 +-
 test/tst_fancyslicing.py | 2 +-
 test/tst_masked4.py      | 2 +-
 test/tst_shape.py        | 2 +-
 9 files changed, 10 insertions(+), 10 deletions(-)

diff --git a/README.md b/README.md
index cebdc014c..bb8441a7c 100644
--- a/README.md
+++ b/README.md
@@ -58,7 +58,7 @@ Fixes bug in implementation of NETCDF4_CLASSIC parallel IO support in 1.4.3.
 10/26/2018: Version [1.4.2](https://pypi.python.org/pypi/netCDF4/1.4.2) released. Minor bugfixes, added `Variable.get_dims()` method and `master_file` kwarg for `MFDataset.__init__`.
 
 08/10/2018: Version [1.4.1](https://pypi.python.org/pypi/netCDF4/1.4.1) released. The old slicing behavior
-(numpy array returned unless missing values are present, otherwise masked array returned) is renabled
+(numpy array returned unless missing values are present, otherwise masked array returned) is re-enabled
 via `set_always_mask(False)`.
 
 05/11/2018: Version [1.4.0](https://pypi.python.org/pypi/netCDF4/1.4.0) released. The netcdftime package is no longer
diff --git a/README.wheels.md b/README.wheels.md
index d3a7fdd2e..83626b78f 100644
--- a/README.wheels.md
+++ b/README.wheels.md
@@ -28,7 +28,7 @@ dynamic libraries apart from those provided as standard by OSX.
 
 ### Triggering a build
 
-You will need write permision to the github repository to trigger new builds
+You will need write permission to the github repository to trigger new builds
 on the travis-ci interface.  Contact us on the mailing list if you need this.
 
 You can trigger a build by:
diff --git a/examples/subset.py b/examples/subset.py
index a8bd2463b..a356453e2 100644
--- a/examples/subset.py
+++ b/examples/subset.py
@@ -3,7 +3,7 @@
 import numpy as np
 import matplotlib.pyplot as plt
 
-# use real data from CFS reanlysis.
+# use real data from CFS reanalysis.
 # note:  we're reading GRIB2 data!
 URL="http://nomads.ncdc.noaa.gov/thredds/dodsC/modeldata/cmd_flxf/2010/201007/20100701/flxf00.gdas.2010070100.grb2"
 nc = netCDF4.Dataset(URL)
diff --git a/src/netCDF4/utils.py b/src/netCDF4/utils.py
index c5ac97edb..7a858ef42 100644
--- a/src/netCDF4/utils.py
+++ b/src/netCDF4/utils.py
@@ -235,7 +235,7 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
             unlim = False
         # convert boolean index to integer array.
         if np.iterable(ea) and ea.dtype.kind =='b':
-            # check that boolen array not too long
+            # check that boolean array not too long
             if not unlim and shape[i] != len(ea):
                 msg="""
 Boolean array must have the same shape as the data along this dimension."""
@@ -539,7 +539,7 @@ def ncinfo():
             sys.stderr.write(usage)
             sys.exit(0)
 
-    # filename passed as last argumenbt
+    # filename passed as last argument
     try:
         filename = pargs[-1]
     except IndexError:
diff --git a/test/tst_Unsigned.py b/test/tst_Unsigned.py
index 7c9fa5d32..e23ed8dc3 100644
--- a/test/tst_Unsigned.py
+++ b/test/tst_Unsigned.py
@@ -10,7 +10,7 @@ class Test_Unsigned(unittest.TestCase):
     integer data stored with a signed integer type in netcdf-3.
     If _Unsigned=True, a view to the data as unsigned integers is returned.
     set_autoscale can be used to turn this off (default is on)
-    See issue #656 (pull reqeust #658).
+    See issue #656 (pull request #658).
     """
     def test_unsigned(self):
         f = netCDF4.Dataset("ubyte.nc")
diff --git a/test/tst_atts.py b/test/tst_atts.py
index e9d53d489..a08a4fc8c 100644
--- a/test/tst_atts.py
+++ b/test/tst_atts.py
@@ -43,7 +43,7 @@ def setUp(self):
         f = netCDF4.Dataset(self.file,'w')
         # try to set a dataset attribute with one of the reserved names.
         f.setncattr('file_format','netcdf4_format')
-        # test attribute renameing
+        # test attribute renaming
         f.stratt_tmp = STRATT
         f.renameAttribute('stratt_tmp','stratt')
         f.emptystratt = EMPTYSTRATT
diff --git a/test/tst_fancyslicing.py b/test/tst_fancyslicing.py
index 625f0d324..dd359a52d 100644
--- a/test/tst_fancyslicing.py
+++ b/test/tst_fancyslicing.py
@@ -56,7 +56,7 @@ def setUp(self):
         # integer array slice.
         v[:,i,:] = -100
         self.data[:,i,:] = -100
-        # boolen array slice.
+        # boolean array slice.
         v[ib2] = -200
         self.data[ib2] = -200
         v[ib3,:,:] = -300
diff --git a/test/tst_masked4.py b/test/tst_masked4.py
index 43abf947b..6203acea1 100755
--- a/test/tst_masked4.py
+++ b/test/tst_masked4.py
@@ -96,7 +96,7 @@ def test_scaled(self):
         self.assertTrue(np.all(self.v_ma.mask == v.mask))
         self.assertTrue(np.all(self.v_ma.mask == v2.mask))
         # treating _FillValue as valid_min/valid_max was
-        # too suprising, revert to old behaviour (issue #761)
+        # too surprising, revert to old behaviour (issue #761)
         #self.assertTrue(np.all(self.v_ma.mask == v3.mask))
         # check that underlying data is same as in netcdf file
         v = f.variables['v']
diff --git a/test/tst_shape.py b/test/tst_shape.py
index d7d1839ad..cba8ca5f9 100644
--- a/test/tst_shape.py
+++ b/test/tst_shape.py
@@ -24,7 +24,7 @@ def tearDown(self):
 
     def runTest(self):
         """test for issue 90 (array shape should not be modified by
-        assigment to netCDF variable)"""
+        assignment to netCDF variable)"""
         f  = Dataset(self.file, 'a')
         v = f.variables['data']
         v[0] = data

From 53912a513f423fab497715f450168a573bbd29c7 Mon Sep 17 00:00:00 2001
From: Sadie Louise Bartholomew 
Date: Wed, 15 Sep 2021 16:38:39 +0100
Subject: [PATCH 0663/1504] Docs: fix  docstring via Cython source

---
 src/netCDF4/_netCDF4.pyx | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index f235ce9cc..80c3fd3fb 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2468,9 +2468,9 @@ Close the Dataset.
 
     def isopen(self):
         """
-**`close(self)`**
+**`isopen(self)`**
 
-is the Dataset open or closed?
+Is the Dataset open or closed?
         """
         return bool(self._isopen)
 

From 324960879453b542e17ea9592ef6aac02d8f8919 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 15 Sep 2021 20:09:22 -0600
Subject: [PATCH 0664/1504] fix for issue #1128

---
 src/netCDF4/_netCDF4.pyx | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index f235ce9cc..36eb46ae1 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2172,6 +2172,7 @@ strings.
                 IF HAS_NC_CREATE_MEM:
                    initialsize = memory
                    ierr = nc_create_mem(path, 0, initialsize, &grpid)
+                   print('nc_create_mem',ierr)
                    self._inmemory = True # checked in close method
                 ELSE:
                     msg = """
@@ -2225,6 +2226,7 @@ strings.
                         raise ValueError("Unable to retrieve Buffer from %s" % (memory,))
 
                     ierr = nc_open_mem(path, 0, self._buffer.len, self._buffer.buf, &grpid)
+                    print('nc_open_mem',ierr)
                 ELSE:
                     msg = """
         nc_open_mem functionality not enabled.  To enable, install Cython, make sure you have
@@ -5979,7 +5981,7 @@ cdef _read_enum(group, nc_type xtype, endian=None):
     # then use that to create a EnumType instance.
     # called by _get_types, _get_vars.
     cdef int ierr, _grpid, nmem
-    cdef char enum_val
+    cdef ndarray enum_val
     cdef nc_type base_xtype
     cdef char enum_namstring[NC_MAX_NAME+1]
     cdef size_t nmembers
@@ -5998,13 +6000,14 @@ cdef _read_enum(group, nc_type xtype, endian=None):
         raise KeyError("unsupported component type for ENUM")
     # loop over members, build dict.
     enum_dict = {}
+    enum_val = numpy.empty(1,dt)
     for nmem from 0 <= nmem < nmembers:
         with nogil:
             ierr = nc_inq_enum_member(_grpid, xtype, nmem, \
-                                      enum_namstring, &enum_val)
+                                      enum_namstring,PyArray_DATA(enum_val))
         _ensure_nc_success(ierr)
         name = enum_namstring.decode('utf-8')
-        enum_dict[name] = int(enum_val)
+        enum_dict[name] = numpy.asscalar(enum_val)
     return EnumType(group, dt, enum_name, enum_dict, typeid=xtype)
 
 cdef _strencode(pystr,encoding=None):

From 4b7d90be3656b3e565a1d4705aa62c12eac2a23f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 15 Sep 2021 20:11:11 -0600
Subject: [PATCH 0665/1504] add Changelog entry

---
 Changelog | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/Changelog b/Changelog
index efa2121a0..82cdcdd45 100644
--- a/Changelog
+++ b/Changelog
@@ -7,6 +7,10 @@
    Issue #1108.
  * Fix OverflowError when dimension sizes become greater than 2**32-1 elements on Windows (Issue #1112).
  * Don't return masked arrays for vlens (only for primitive and enum types - issue #1115).
+ * Fix Enum bug (issue #1128): the enum_dict member of an EnumType read from a file
+   contains invalid values when the enum is large enough (more than 127 or 255
+   members). 
+
 
  version 1.5.6 (tag v1.5.6rel)
 ==============================

From 4fc236bb9f7ea9bfda6b15afe26fffea623738f0 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 15 Sep 2021 20:12:16 -0600
Subject: [PATCH 0666/1504] remove debug prints

---
 src/netCDF4/_netCDF4.pyx | 2 --
 1 file changed, 2 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 36eb46ae1..699304ed3 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2172,7 +2172,6 @@ strings.
                 IF HAS_NC_CREATE_MEM:
                    initialsize = memory
                    ierr = nc_create_mem(path, 0, initialsize, &grpid)
-                   print('nc_create_mem',ierr)
                    self._inmemory = True # checked in close method
                 ELSE:
                     msg = """
@@ -2226,7 +2225,6 @@ strings.
                         raise ValueError("Unable to retrieve Buffer from %s" % (memory,))
 
                     ierr = nc_open_mem(path, 0, self._buffer.len, self._buffer.buf, &grpid)
-                    print('nc_open_mem',ierr)
                 ELSE:
                     msg = """
         nc_open_mem functionality not enabled.  To enable, install Cython, make sure you have

From 4978be8382c365d3e08c9dd16410604f17c44ce8 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 15 Sep 2021 21:29:19 -0600
Subject: [PATCH 0667/1504] don't use deprecated np.asscalar, add test case

---
 src/netCDF4/_netCDF4.pyx |  2 +-
 test/tst_enum.py         | 22 ++++++++++++++++++++++
 2 files changed, 23 insertions(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 699304ed3..7cc515519 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -6005,7 +6005,7 @@ cdef _read_enum(group, nc_type xtype, endian=None):
                                       enum_namstring,PyArray_DATA(enum_val))
         _ensure_nc_success(ierr)
         name = enum_namstring.decode('utf-8')
-        enum_dict[name] = numpy.asscalar(enum_val)
+        enum_dict[name] = enum_val.item()
     return EnumType(group, dt, enum_name, enum_dict, typeid=xtype)
 
 cdef _strencode(pystr,encoding=None):
diff --git a/test/tst_enum.py b/test/tst_enum.py
index 8069ad2f3..6157dde24 100644
--- a/test/tst_enum.py
+++ b/test/tst_enum.py
@@ -63,5 +63,27 @@ def runTest(self):
         assert_array_equal(data.mask, datain_masked.mask)
         f.close()
 
+class EnumDictTestCase(unittest.TestCase):
+    # issue 1128
+    def setUp(self):
+        DT = np.int16; BITS = 8
+        self.STORED_VAL = DT(2**BITS)
+        self.VAL_MAP = {f'bits_{n}': DT(2**n) for n in range(1,BITS+1)}
+        self.VAL_MAP['invalid'] = 0
+        self.file = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
+        with netCDF4.Dataset(file, 'w') as nc:
+            # The enum is created with dtype=int16, so it will allow BITS values up to 15
+            et = nc.createEnumType(DT, 'etype', self.VAL_MAP)
+            ev = nc.createVariable('evar', et)
+            # Succeeds because the created EnumType does keep the correct dict
+            ev[...] = self.STORED_VAL
+        def tearDown(self):
+            os.remove(self.file)
+        def runTest(self):
+            with netCDF4.Dataset(file, 'r') as nc:
+                read_var = nc['evar']
+                assert(read_var[...] == self.STORED_VAL)
+                assert(read_et.enum_dict == self.VAL_MAP)
+
 if __name__ == '__main__':
     unittest.main()

From 13eb8a07c6b5e0eff5ff6ce7f788c56a72c179cc Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 15 Sep 2021 21:30:48 -0600
Subject: [PATCH 0668/1504] remove whitespace

---
 Changelog | 1 -
 1 file changed, 1 deletion(-)

diff --git a/Changelog b/Changelog
index 82cdcdd45..bd6db7c2a 100644
--- a/Changelog
+++ b/Changelog
@@ -11,7 +11,6 @@
    contains invalid values when the enum is large enough (more than 127 or 255
    members). 
 
-
  version 1.5.6 (tag v1.5.6rel)
 ==============================
  * move CI/CD tests from travis/appveyor to Github Actions (PR #1061).

From daba2de3014c3b8662b787d3fb59f211606aa123 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 15 Sep 2021 21:32:43 -0600
Subject: [PATCH 0669/1504] bump version number

---
 Changelog                | 9 ++++++---
 src/netCDF4/_netCDF4.pyx | 4 ++--
 2 files changed, 8 insertions(+), 5 deletions(-)

diff --git a/Changelog b/Changelog
index bd6db7c2a..0658a26b8 100644
--- a/Changelog
+++ b/Changelog
@@ -1,3 +1,9 @@
+ version 1.5.8 (not yet released)
+==============================
+ * Fix Enum bug (issue #1128): the enum_dict member of an EnumType read from a file
+   contains invalid values when the enum is large enough (more than 127 or 255
+   members). 
+
  version 1.5.7 (tag v1.5.7rel)
 ==============================
  * don't try to mask vlens with default  _FillValue, since vlens don't have a default _FillValue.
@@ -7,9 +13,6 @@
    Issue #1108.
  * Fix OverflowError when dimension sizes become greater than 2**32-1 elements on Windows (Issue #1112).
  * Don't return masked arrays for vlens (only for primitive and enum types - issue #1115).
- * Fix Enum bug (issue #1128): the enum_dict member of an EnumType read from a file
-   contains invalid values when the enum is large enough (more than 127 or 255
-   members). 
 
  version 1.5.6 (tag v1.5.6rel)
 ==============================
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 7cc515519..1d93d4374 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1,5 +1,5 @@
 """
-Version 1.5.7
+Version 1.5.8
 -------------
 
 # Introduction
@@ -1204,7 +1204,7 @@ if sys.version_info[0:2] < (3, 7):
     # Python 3.7+ guarantees order; older versions need OrderedDict
     from collections import OrderedDict
 
-__version__ = "1.5.7"
+__version__ = "1.5.8"
 
 # Initialize numpy
 import posixpath

From 105aab5969b5e240e505416aecc5bfef70519253 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 16 Sep 2021 06:48:59 -0600
Subject: [PATCH 0670/1504] don't run dap tests

---
 .github/workflows/build.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 1ac5fa503..8351f6683 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -10,7 +10,7 @@ jobs:
       NETCDF_DIR: ${{ github.workspace }}/..
       NETCDF_EXTRA_CONFIG: --enable-pnetcdf
       CC: mpicc.mpich
-#     NO_NET: 1
+      NO_NET: 1
     strategy:
       matrix:
         python-version: ["3.9"]

From eacf9a9a951e2967aea7e5387afe6fcbf931274f Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 16 Sep 2021 07:13:02 -0600
Subject: [PATCH 0671/1504] turn off DAP test

---
 .github/workflows/miniconda.yml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 61ceba3d2..78ccd91d8 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -71,6 +71,7 @@ jobs:
       shell: bash -l {0}
       run: |
         source activate TEST
+        export NO_NET=1
         cd test && python run_all.py
         cd ../examples
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" 

From c4b75faa51e0c702c4d468d520c0ff6349a4f1f3 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 16 Sep 2021 07:48:40 -0600
Subject: [PATCH 0672/1504] try again to disable DAP test

---
 .github/workflows/miniconda.yml | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 78ccd91d8..622cfc374 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -8,6 +8,8 @@ on:
 jobs:
   run-serial:
     runs-on: ${{ matrix.os }}
+    env:
+      NO_NET: 1
     strategy:
       matrix:
         python-version: ["3.6", "3.7", "3.8", "3.9"]
@@ -71,7 +73,6 @@ jobs:
       shell: bash -l {0}
       run: |
         source activate TEST
-        export NO_NET=1
         cd test && python run_all.py
         cd ../examples
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" 

From a85b5acbeefdc9c1ae53d1e06b19ca5ce55f2214 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 16 Sep 2021 07:58:58 -0600
Subject: [PATCH 0673/1504] remove --oversubscribe

---
 .github/workflows/miniconda.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 622cfc374..d8d8fefa1 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -78,7 +78,7 @@ jobs:
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" 
         which mpirun
         mpirun --version
-        mpirun  --oversubscribe -np 4 python mpi_example.py
+        mpirun -np 4 python mpi_example.py
         if [ $? -ne 0 ] ; then
           echo "hdf5 mpi test failed!"
           exit 1

From 963782246362dcb1bd86dfc813a3f29885f78281 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 16 Sep 2021 08:14:52 -0600
Subject: [PATCH 0674/1504] turn DAP tests back on

---
 .github/workflows/build.yml     | 2 +-
 .github/workflows/miniconda.yml | 4 ++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 8351f6683..852621a09 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -10,7 +10,7 @@ jobs:
       NETCDF_DIR: ${{ github.workspace }}/..
       NETCDF_EXTRA_CONFIG: --enable-pnetcdf
       CC: mpicc.mpich
-      NO_NET: 1
+      #NO_NET: 1
     strategy:
       matrix:
         python-version: ["3.9"]
diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index d8d8fefa1..0be093739 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -8,8 +8,8 @@ on:
 jobs:
   run-serial:
     runs-on: ${{ matrix.os }}
-    env:
-      NO_NET: 1
+    #env:
+    #  NO_NET: 1
     strategy:
       matrix:
         python-version: ["3.6", "3.7", "3.8", "3.9"]

From 323e24e86943fd00fc09799361c86bec6383a210 Mon Sep 17 00:00:00 2001
From: Karthikeyan Singaravelan 
Date: Fri, 15 Oct 2021 06:13:57 +0000
Subject: [PATCH 0675/1504] Use assertRaisesRegex instead of assertRaisesRegexp
 for Python 3.11 compatibility.

---
 test/tst_filepath.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/tst_filepath.py b/test/tst_filepath.py
index 9db595778..7843f1128 100644
--- a/test/tst_filepath.py
+++ b/test/tst_filepath.py
@@ -26,7 +26,7 @@ def test_filepath_with_non_ascii_characters(self):
 
     def test_no_such_file_raises(self):
         fname = 'not_a_nc_file.nc'
-        with self.assertRaisesRegexp(IOError, fname):
+        with self.assertRaisesRegex(IOError, fname):
             netCDF4.Dataset(fname, 'r')
 
 

From f68c58bb86f895846d2b7c64b874f85b9b7f73ad Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Sat, 30 Oct 2021 08:50:27 -0400
Subject: [PATCH 0676/1504] prepare for v1.5.8 release

---
 Changelog | 3 ++-
 README.md | 2 ++
 2 files changed, 4 insertions(+), 1 deletion(-)

diff --git a/Changelog b/Changelog
index 0658a26b8..ccac1b4cb 100644
--- a/Changelog
+++ b/Changelog
@@ -1,8 +1,9 @@
- version 1.5.8 (not yet released)
+ version 1.5.8 (tag v1.5.8rel)
 ==============================
  * Fix Enum bug (issue #1128): the enum_dict member of an EnumType read from a file
    contains invalid values when the enum is large enough (more than 127 or 255
    members). 
+ * Binary wheels for aarch64 and python 3.10.
 
  version 1.5.7 (tag v1.5.7rel)
 ==============================
diff --git a/README.md b/README.md
index bb8441a7c..d6f31974f 100644
--- a/README.md
+++ b/README.md
@@ -10,6 +10,8 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
+10/31/2021:  Version [1.5.8](https://pypi.python.org/pypi/netCDF4/1.5.8) released. Fix Enum bug, add binary wheels for aarch64 and python 3.10.
+
 6/22/2021:  Version [1.5.7](https://pypi.python.org/pypi/netCDF4/1.5.7) released.
 Fixed OverflowError on Windows when reading data with dimension sizes greater than 2**32-1.
 Masked arrays no longer returned for vlens.

From 60e3c566142c4ef91a3b99fdaa12272047c249e0 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Sat, 30 Oct 2021 09:02:51 -0400
Subject: [PATCH 0677/1504] add python 3.10 to tests

---
 .github/workflows/miniconda.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 0be093739..b32c63562 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -12,7 +12,7 @@ jobs:
     #  NO_NET: 1
     strategy:
       matrix:
-        python-version: ["3.6", "3.7", "3.8", "3.9"]
+        python-version: ["3.6", "3.7", "3.8", "3.9", "3.10" ]
         os: [windows-latest, ubuntu-latest, macos-latest]
         platform: [x64, x32]
         exclude:

From de2834c6825cb0a6b4a5f6341cdf0f0cca4f599f Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 11 Nov 2021 15:46:20 -0700
Subject: [PATCH 0678/1504] check for new bit-groomin/quantization support

---
 setup.py | 14 ++++++++++++--
 1 file changed, 12 insertions(+), 2 deletions(-)

diff --git a/setup.py b/setup.py
index 17e7afc46..1f7dd6924 100644
--- a/setup.py
+++ b/setup.py
@@ -65,6 +65,7 @@ def check_api(inc_dirs,netcdf_lib_version):
     has_parallel_support = False
     has_parallel4_support = False
     has_pnetcdf_support = False
+    has_quantize = False
 
     for d in inc_dirs:
         try:
@@ -83,6 +84,8 @@ def check_api(inc_dirs,netcdf_lib_version):
                 has_nc_inq_format_extended = True
             if line.startswith('#define NC_FORMAT_64BIT_DATA'):
                 has_cdf5_format = True
+            if line.startswith('nc_def_var_quantize'):
+                has_quantize = True
 
         if has_nc_open_mem:
             try:
@@ -116,7 +119,7 @@ def check_api(inc_dirs,netcdf_lib_version):
 
     return has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \
            has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \
-           has_parallel4_support, has_pnetcdf_support
+           has_parallel4_support, has_pnetcdf_support, has_quantize
 
 
 def getnetcdfvers(libdirs):
@@ -529,7 +532,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     # this determines whether renameGroup and filepath methods will work.
     has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \
     has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \
-    has_parallel4_support, has_pnetcdf_support = \
+    has_parallel4_support, has_pnetcdf_support, has_quantize = \
     check_api(inc_dirs,netcdf_lib_version)
     # for netcdf 4.4.x CDF5 format is always enabled.
     if netcdf_lib_version is not None and\
@@ -601,6 +604,13 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         sys.stdout.write('netcdf lib does not have pnetcdf parallel functions\n')
         f.write('DEF HAS_PNETCDF_SUPPORT = 0\n')
 
+    if has_quantize:
+        sys.stdout.write('netcdf lib has bit-grooming/quantization functions\n')
+        f.write('DEF HAS_QUANTIZATION_SUPPORT = 1\n')
+    else:
+        sys.stdout.write('netcdf lib does not bit-grooming/quantization functions\n')
+        f.write('DEF HAS_QUANTIZATION_SUPPORT = 0\n')
+
     f.close()
 
     if has_parallel4_support or has_pnetcdf_support:

From 17621c0a29e53dfb6aa35823e329946e3aee51bf Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 11 Nov 2021 16:06:15 -0700
Subject: [PATCH 0679/1504] bump version number, add placeholder Changelog
 entry

---
 Changelog                | 5 +++++
 src/netCDF4/_netCDF4.pyx | 4 ++--
 2 files changed, 7 insertions(+), 2 deletions(-)

diff --git a/Changelog b/Changelog
index ccac1b4cb..4ec8421c5 100644
--- a/Changelog
+++ b/Changelog
@@ -1,3 +1,8 @@
+ version 1.6.0 (not yet released)
+=================================
+ * add support for new bit-grooming/quantization functions in netcdf-c 4.8.2.  netCDF4.Dataset.createVariable API
+   has changed - lsd ("least significant digit") keyword changed to nsd (number of significant digits).
+
  version 1.5.8 (tag v1.5.8rel)
 ==============================
  * Fix Enum bug (issue #1128): the enum_dict member of an EnumType read from a file
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index a7e808b6b..6ac2c3082 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1,5 +1,5 @@
 """
-Version 1.5.8
+Version 1.6.0
 -------------
 
 # Introduction
@@ -1204,7 +1204,7 @@ if sys.version_info[0:2] < (3, 7):
     # Python 3.7+ guarantees order; older versions need OrderedDict
     from collections import OrderedDict
 
-__version__ = "1.5.8"
+__version__ = "1.6.0"
 
 # Initialize numpy
 import posixpath

From d0d67be5a9276a0f0dd3c04dd6e145f50a63b26c Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 11 Nov 2021 19:43:10 -0700
Subject: [PATCH 0680/1504] add quantization support from netcdf-c (using
 significant_digits kwarg)

---
 include/netCDF4.pxi      |  8 ++++++++
 src/netCDF4/_netCDF4.pyx | 39 ++++++++++++++++++++++++++++++++++-----
 2 files changed, 42 insertions(+), 5 deletions(-)

diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index 6912ab53d..3afceb3ce 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -691,6 +691,14 @@ cdef extern from "netcdf.h":
     int nc_inq_enum_ident(int ncid, nc_type xtype, long long value, char *identifier) nogil
 
 
+IF HAS_QUANTIZATION_SUPPORT:
+    cdef extern from "netcdf.h":
+        cdef enum:
+            NC_NOQUANTIZE
+            NC_QUANTIZE_BITGROOM
+        int nc_def_var_quantize(int ncid, int varid, int quantize_mode, int nsd) 
+        int nc_inq_var_quantize(int ncid, int varid, int *quantize_modep, int *nsdp) nogil
+
 IF HAS_NC_OPEN_MEM:
     cdef extern from "netcdf_mem.h":
         int nc_open_mem(const char *path, int mode, size_t size, void* memory, int *ncidp)
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 6ac2c3082..4916db833 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2613,11 +2613,11 @@ datatype."""
     def createVariable(self, varname, datatype, dimensions=(), zlib=False,
             complevel=4, shuffle=True, fletcher32=False, contiguous=False,
             chunksizes=None, endian='native', least_significant_digit=None,
-            fill_value=None, chunk_cache=None):
+            significant_digits=None,fill_value=None, chunk_cache=None):
         """
 **`createVariable(self, varname, datatype, dimensions=(), zlib=False,
 complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None,
-endian='native', least_significant_digit=None, fill_value=None, chunk_cache=None)`**
+endian='native', least_significant_digit=None, significant_digits=None, fill_value=None, chunk_cache=None)`**
 
 Creates a new variable with the given `varname`, `datatype`, and
 `dimensions`. If dimensions are not given, the variable is assumed to be
@@ -2749,7 +2749,7 @@ is the number of variable dimensions."""
         dimensions=dimensions, zlib=zlib, complevel=complevel, shuffle=shuffle,
         fletcher32=fletcher32, contiguous=contiguous, chunksizes=chunksizes,
         endian=endian, least_significant_digit=least_significant_digit,
-        fill_value=fill_value, chunk_cache=chunk_cache)
+        significant_digits=None,fill_value=fill_value, chunk_cache=chunk_cache)
         return group.variables[varname]
 
     def renameVariable(self, oldname, newname):
@@ -3571,7 +3571,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
     def __init__(self, grp, name, datatype, dimensions=(), zlib=False,
             complevel=4, shuffle=True, fletcher32=False, contiguous=False,
             chunksizes=None, endian='native', least_significant_digit=None,
-            fill_value=None, chunk_cache=None, **kwargs):
+            significant_digits=None,fill_value=None, chunk_cache=None, **kwargs):
         """
         **`__init__(self, group, name, datatype, dimensions=(), zlib=False,
         complevel=4, shuffle=True, fletcher32=False, contiguous=False,
@@ -3666,7 +3666,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         `Dataset.createVariable` method of a `Dataset` or
         `Group` instance, not using this class directly.
         """
-        cdef int ierr, ndims, icontiguous, ideflate_level, numdims, _grpid
+        cdef int ierr, ndims, icontiguous, ideflate_level, numdims, _grpid, nsd
         cdef char namstring[NC_MAX_NAME+1]
         cdef char *varname
         cdef nc_type xtype
@@ -3865,6 +3865,11 @@ behavior is similar to Fortran or Matlab, but different than numpy.
                     pass # this is the default format.
                 else:
                     raise ValueError("'endian' keyword argument must be 'little','big' or 'native', got '%s'" % endian)
+                # set quantization
+                IF HAS_QUANTIZATION_SUPPORT:
+                    if significant_digits is not None:
+                        nsd = significant_digits
+                        ierr = nc_def_var_quantize(self._grpid, self._varid, NC_QUANTIZE_BITGROOM, nsd)
                 if ierr != NC_NOERR:
                     if grp.data_model != 'NETCDF4': grp._enddef()
                     _ensure_nc_success(ierr)
@@ -4201,6 +4206,30 @@ return dictionary containing HDF5 filter parameters."""
             filtdict['fletcher32']=True
         return filtdict
 
+    def significant_digits(self):
+        """
+**`significant_digits(self)`**
+
+return number of significant digits used in quantization"""
+        IF HAS_QUANTIZATION_SUPPORT:
+            cdef int ierr, nsd, quantize_mode
+            if self._grp.data_model not in ['NETCDF4_CLASSIC','NETCDF4']:
+                return None
+            else:
+                with nogil:
+                    ierr = nc_inq_var_quantize(self._grpid, self._varid, &quantize_mode, &nsd)
+                _ensure_nc_success(ierr)
+                if quantize_mode == NC_NOQUANTIZE:
+                    return None
+                else:
+                    sig_digits = nsd
+                    return sig_digits
+        ELSE:
+            msg = """
+significant_digits method not enabled.  To enable, install Cython, make sure you have
+version 4.8.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
+            raise ValueError(msg)
+
     def endian(self):
         """
 **`endian(self)`**

From 52efdc70b921988a8e105782aca6d84371b760b1 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 11 Nov 2021 19:47:07 -0700
Subject: [PATCH 0681/1504] update

---
 Changelog | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/Changelog b/Changelog
index 4ec8421c5..02c0681d3 100644
--- a/Changelog
+++ b/Changelog
@@ -1,7 +1,8 @@
  version 1.6.0 (not yet released)
 =================================
- * add support for new bit-grooming/quantization functions in netcdf-c 4.8.2.  netCDF4.Dataset.createVariable API
-   has changed - lsd ("least significant digit") keyword changed to nsd (number of significant digits).
+ * add support for new bit-grooming/quantization functions in netcdf-c 4.8.2 via "signficant_digits"
+   kwarg in Dataset.createVariable. "signficant_digits" Dataset method returns value associated with
+   Variable.
 
  version 1.5.8 (tag v1.5.8rel)
 ==============================

From 9494de70474998d289c70110adee97e8812f4bdf Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 11 Nov 2021 19:52:25 -0700
Subject: [PATCH 0682/1504] if kwarg significant_digits set, and netcdf-c <
 4.8.2, raise ValueError

---
 src/netCDF4/_netCDF4.pyx | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 4916db833..63e4bf1bd 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3870,6 +3870,12 @@ behavior is similar to Fortran or Matlab, but different than numpy.
                     if significant_digits is not None:
                         nsd = significant_digits
                         ierr = nc_def_var_quantize(self._grpid, self._varid, NC_QUANTIZE_BITGROOM, nsd)
+                ELSE:
+                    if significant_digits is not None:
+                        msg = """
+significant_digits feature not enabled.  To enable, install Cython, make sure you have
+version 4.8.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
+                        raise ValueError(msg)
                 if ierr != NC_NOERR:
                     if grp.data_model != 'NETCDF4': grp._enddef()
                     _ensure_nc_success(ierr)

From 1221a32b34a949acc6c38399f727de04f95f62d8 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 12 Nov 2021 08:27:26 -0700
Subject: [PATCH 0683/1504] update

---
 src/netCDF4/_netCDF4.pyx | 10 ++++------
 1 file changed, 4 insertions(+), 6 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 63e4bf1bd..2fe5a0ef8 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3873,8 +3873,9 @@ behavior is similar to Fortran or Matlab, but different than numpy.
                 ELSE:
                     if significant_digits is not None:
                         msg = """
-significant_digits feature not enabled.  To enable, install Cython, make sure you have
-version 4.8.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
+significant_digits kwarge only works with netcdf-c >= 4.8.2.  To enable, install Cython, make sure you have
+version 4.8.2 or higher netcdf-c, and rebuild netcdf4-python. Otherwise, use least_significant_digit
+kwarg for quantization."""
                         raise ValueError(msg)
                 if ierr != NC_NOERR:
                     if grp.data_model != 'NETCDF4': grp._enddef()
@@ -4231,10 +4232,7 @@ return number of significant digits used in quantization"""
                     sig_digits = nsd
                     return sig_digits
         ELSE:
-            msg = """
-significant_digits method not enabled.  To enable, install Cython, make sure you have
-version 4.8.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
-            raise ValueError(msg)
+            return None
 
     def endian(self):
         """

From a4580667714ec25c3ab98819b16c25a2cb363568 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 12 Nov 2021 09:41:11 -0700
Subject: [PATCH 0684/1504] add tests

---
 src/netCDF4/__init__.py  |  2 +-
 src/netCDF4/_netCDF4.pyx |  3 +-
 test/run_all.py          |  5 ++-
 test/tst_compression2.py | 88 ++++++++++++++++++++++++++++++++++++++++
 4 files changed, 95 insertions(+), 3 deletions(-)
 create mode 100644 test/tst_compression2.py

diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py
index 4ddc07fdf..4888e7c26 100644
--- a/src/netCDF4/__init__.py
+++ b/src/netCDF4/__init__.py
@@ -7,6 +7,6 @@
                        __has_rename_grp__, __has_nc_inq_path__,
                        __has_nc_inq_format_extended__, __has_nc_open_mem__,
                        __has_nc_create_mem__, __has_cdf5_format__,
-                       __has_parallel4_support__, __has_pnetcdf_support__)
+                       __has_parallel4_support__, __has_pnetcdf_support__,__has_quantization_support__)
 __all__ =\
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 2fe5a0ef8..c53b22ef4 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1304,6 +1304,7 @@ __has_nc_open_mem__ = HAS_NC_OPEN_MEM
 __has_nc_create_mem__ = HAS_NC_CREATE_MEM
 __has_parallel4_support__ = HAS_PARALLEL4_SUPPORT
 __has_pnetcdf_support__ = HAS_PNETCDF_SUPPORT
+__has_quantization_support__ = HAS_QUANTIZATION_SUPPORT
 _needsworkaround_issue485 = __netcdf4libversion__ < "4.4.0" or \
                (__netcdf4libversion__.startswith("4.4.0") and \
                 "-development" in __netcdf4libversion__)
@@ -2749,7 +2750,7 @@ is the number of variable dimensions."""
         dimensions=dimensions, zlib=zlib, complevel=complevel, shuffle=shuffle,
         fletcher32=fletcher32, contiguous=contiguous, chunksizes=chunksizes,
         endian=endian, least_significant_digit=least_significant_digit,
-        significant_digits=None,fill_value=fill_value, chunk_cache=chunk_cache)
+        significant_digits=significant_digits,fill_value=fill_value, chunk_cache=chunk_cache)
         return group.variables[varname]
 
     def renameVariable(self, oldname, newname):
diff --git a/test/run_all.py b/test/run_all.py
index d7dc07776..723b0cdd6 100755
--- a/test/run_all.py
+++ b/test/run_all.py
@@ -1,7 +1,7 @@
 import glob, os, sys, unittest, struct
 from netCDF4 import getlibversion,__hdf5libversion__,__netcdf4libversion__,__version__
 from netCDF4 import __has_cdf5_format__, __has_nc_inq_path__, __has_nc_create_mem__, \
-                    __has_parallel4_support__, __has_pnetcdf_support__
+                    __has_parallel4_support__, __has_pnetcdf_support__, __has_quantization_support__
 
 # can also just run
 # python -m unittest discover . 'tst*py'
@@ -20,6 +20,9 @@
 if not __has_cdf5_format__ or struct.calcsize("P") < 8:
     test_files.remove('tst_cdf5.py')
     sys.stdout.write('not running tst_cdf5.py ...\n')
+if not __has_quantization_support__:
+    test_files.remove('tst_compression2.py')
+    sys.stdout.write('not running tst_compression2.py ...\n')
 
 # Don't run tests that require network connectivity
 if os.getenv('NO_NET'):
diff --git a/test/tst_compression2.py b/test/tst_compression2.py
new file mode 100644
index 000000000..9a85bf3fd
--- /dev/null
+++ b/test/tst_compression2.py
@@ -0,0 +1,88 @@
+from numpy.random.mtrand import uniform
+from netCDF4 import Dataset
+from netCDF4.utils import _quantize
+from numpy.testing import assert_almost_equal
+import numpy as np
+import os, tempfile, unittest
+
+ndim = 100000
+nfiles = 5
+files = [tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name for nfile in range(nfiles)]
+array = uniform(size=(ndim,))
+nsd = 3
+complevel = 6
+
+def write_netcdf(filename,zlib,significant_digits,data,dtype='f8',shuffle=False,\
+                 complevel=6):
+    file = Dataset(filename,'w')
+    file.createDimension('n', ndim)
+    foo = file.createVariable('data',\
+            dtype,('n'),zlib=zlib,significant_digits=significant_digits,\
+            shuffle=shuffle,complevel=complevel)
+    foo[:] = data
+    file.close()
+    file = Dataset(filename)
+    data = file.variables['data'][:]
+    file.close()
+
+class CompressionTestCase(unittest.TestCase):
+
+    def setUp(self):
+        self.files = files
+        # no compression
+        write_netcdf(self.files[0],False,None,array)
+        # compressed, lossless, no shuffle.
+        write_netcdf(self.files[1],True,None,array)
+        # compressed, lossless, with shuffle.
+        write_netcdf(self.files[2],True,None,array,shuffle=True)
+        # compressed, lossy, no shuffle.
+        write_netcdf(self.files[3],True,nsd,array)
+        # compressed, lossy, with shuffle.
+        write_netcdf(self.files[4],True,nsd,array,shuffle=True)
+
+    def tearDown(self):
+        # Remove the temporary files
+        for file in self.files:
+            os.remove(file)
+
+    def runTest(self):
+        """testing zlib and shuffle compression filters"""
+        uncompressed_size = os.stat(self.files[0]).st_size
+        #print('uncompressed size = ',uncompressed_size)
+        # check compressed data.
+        f = Dataset(self.files[1])
+        size = os.stat(self.files[1]).st_size
+        #print('compressed lossless no shuffle = ',size)
+        assert_almost_equal(array,f.variables['data'][:])
+        assert f.variables['data'].filters() == {'zlib':True,'shuffle':False,'complevel':complevel,'fletcher32':False}
+        assert(size < 0.95*uncompressed_size)
+        f.close()
+        # check compression with shuffle
+        f = Dataset(self.files[2])
+        size = os.stat(self.files[2]).st_size
+        #print('compressed lossless with shuffle ',size)
+        assert_almost_equal(array,f.variables['data'][:])
+        assert f.variables['data'].filters() == {'zlib':True,'shuffle':True,'complevel':complevel,'fletcher32':False}
+        assert(size < 0.85*uncompressed_size)
+        f.close()
+        # check lossy compression without shuffle
+        f = Dataset(self.files[3])
+        size = os.stat(self.files[3]).st_size
+        errmax = (np.abs(array-f.variables['data'][:])).max()
+        #print('compressed lossy no shuffle = ',size,' max err = ',errmax)
+        assert(f.variables['data'].significant_digits() == nsd)
+        assert(errmax < 1.e-3)
+        assert(size < 0.35*uncompressed_size)
+        f.close()
+        # check lossy compression with shuffle
+        f = Dataset(self.files[4])
+        size = os.stat(self.files[4]).st_size
+        errmax = (np.abs(array-f.variables['data'][:])).max()
+        #print('compressed lossy with shuffle = ',size,' max err = ',errmax)
+        assert(f.variables['data'].significant_digits() == nsd)
+        assert(errmax < 1.e-3)
+        assert(size < 0.24*uncompressed_size)
+        f.close()
+
+if __name__ == '__main__':
+    unittest.main()

From 0f920ff2d0b15ce413d0828c1b61d91875477423 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 12 Nov 2021 10:47:50 -0700
Subject: [PATCH 0685/1504] update docstrings

---
 src/netCDF4/_netCDF4.pyx | 46 ++++++++++++++++++++++++++++++++--------
 1 file changed, 37 insertions(+), 9 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index c53b22ef4..879463d15 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -666,14 +666,22 @@ format is `NETCDF3_CLASSIC`, `NETCDF3_64BIT_OFFSET` or `NETCDF3_64BIT_DATA`.
 If your data only has a certain number of digits of precision (say for
 example, it is temperature data that was measured with a precision of
 0.1 degrees), you can dramatically improve zlib compression by
-quantizing (or truncating) the data using the `least_significant_digit`
-keyword argument to `Dataset.createVariable`. The least
-significant digit is the power of ten of the smallest decimal place in
+quantizing (or truncating) the data. There are two methods supplied for
+doing this.  You can useg the `least_significant_digit`
+keyword argument to `Dataset.createVariable` to specify
+the power of ten of the smallest decimal place in
 the data that is a reliable value. For example if the data has a
 precision of 0.1, then setting `least_significant_digit=1` will cause
 data the data to be quantized using `numpy.around(scale*data)/scale`, where
 scale = 2**bits, and bits is determined so that a precision of 0.1 is
-retained (in this case bits=4).  Effectively, this makes the compression
+retained (in this case bits=4).  This is done at the python level and is
+not a part of the underlying C library.  Starting with netcdf-c version 4.8.2,
+a quantization capability is provided in the library.  This can be
+used via the `significant_digits` `Dataset.createVariable` kwarg.
+The interpretation of `significant_digits` is different than `least_signficant_digit`
+in that it specifies the absolute number of significant digits independent
+of the magnitude of the variable (the floating point exponent).
+Either of these approaches makes the compression
 'lossy' instead of 'lossless', that is some precision in the data is
 sacrificed for the sake of disk space.
 
@@ -695,6 +703,12 @@ and then
 >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,least_significant_digit=3)
 ```
 
+or with netcdf-c >= 4.8.2
+
+```python
+>>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,significant_digits=4)
+```
+
 and see how much smaller the resulting files are.
 
 ## Beyond homogeneous arrays of a fixed type - compound data types
@@ -2691,7 +2705,7 @@ netCDF `_FillValue` (the value that the variable gets filled with before
 any data is written to it, defaults given in the dict `netCDF4.default_fillvals`).
 If fill_value is set to `False`, then the variable is not pre-filled.
 
-If the optional keyword parameter `least_significant_digit` is
+If the optional keyword parameters `least_significant_digit` or `significant_digits` are
 specified, variable data will be truncated (quantized). In conjunction
 with `zlib=True` this produces 'lossy', but significantly more
 efficient compression. For example, if `least_significant_digit=1`,
@@ -2701,7 +2715,9 @@ retained (in this case bits=4). From the
 [PSL metadata conventions](http://www.esrl.noaa.gov/psl/data/gridded/conventions/cdc_netcdf_standard.shtml):
 "least_significant_digit -- power of ten of the smallest decimal place
 in unpacked data that is a reliable value." Default is `None`, or no
-quantization, or 'lossless' compression.
+quantization, or 'lossless' compression.  If `significant_digits=3`
+then the data will be quantized so that three significant digits are retained, independent
+of the floating point exponent. This option is available only with netcdf-c >= 4.8.2.
 
 When creating variables in a `NETCDF4` or `NETCDF4_CLASSIC` formatted file,
 HDF5 creates something called a 'chunk cache' for each variable.  The
@@ -2735,7 +2751,7 @@ string containing the name of the Variable instance.
 The `least_significant_digit`
 attributes describes the power of ten of the smallest decimal place in
 the data the contains a reliable value.  assigned to the `Variable`
-instance. If `None`, the data is not truncated. The `ndim` attribute
+instance. The `ndim` attribute
 is the number of variable dimensions."""
         # if varname specified as a path, split out group names.
         varname = posixpath.normpath(varname)
@@ -3552,6 +3568,13 @@ smallest decimal place in the data the contains a reliable value.  Data is
 truncated to this decimal place when it is assigned to the `Variable`
 instance. If `None`, the data is not truncated.
 
+**`significant_digits`**: Describes the number of significant digits
+in the data the contains a reliable value.  Data is
+truncated to retain this number of significant digits when it is assigned to the `Variable`
+instance. If `None`, the data is not truncated. Only available with netcdf-c >= 4.8.2.
+The number of significant digits used in the quantization of variable data can be
+obtained using the `Variable.significant_digits` method.
+
 **`__orthogonal_indexing__`**: Always `True`.  Indicates to client code
 that the object supports 'orthogonal indexing', which means that slices
 that are 1d arrays or lists slice along each dimension independently.  This
@@ -3645,14 +3668,19 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         The `zlib, complevel, shuffle, fletcher32, contiguous` and `chunksizes`
         keywords are silently ignored for netCDF 3 files that do not use HDF5.
 
-        **`least_significant_digit`**: If specified, variable data will be
-        truncated (quantized). In conjunction with `zlib=True` this produces
+        **`least_significant_digit`**: If this or `significant_digits` are specified, 
+        variable data will be truncated (quantized).  
+        In conjunction with `zlib=True` this produces
         'lossy', but significantly more efficient compression. For example, if
         `least_significant_digit=1`, data will be quantized using
         around(scale*data)/scale, where scale = 2**bits, and bits is determined
         so that a precision of 0.1 is retained (in this case bits=4). Default is
         `None`, or no quantization.
 
+        **`significant_digits`**: As described for `least_significant_digit`
+        except the number of significant digits retained is prescribed independent
+        of the floating point exponent.  Only available with netcdf-c >= 4.8.2.
+
         **`fill_value`**:  If specified, the default netCDF `_FillValue` (the
         value that the variable gets filled with before any data is written to it)
         is replaced with this value.  If fill_value is set to `False`, then

From 3408a3cab6ad788dcc2189a39d5afe2633f9eedb Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 12 Nov 2021 11:11:43 -0700
Subject: [PATCH 0686/1504] fix typo in docstring

---
 src/netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 879463d15..ae9947932 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3902,7 +3902,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
                 ELSE:
                     if significant_digits is not None:
                         msg = """
-significant_digits kwarge only works with netcdf-c >= 4.8.2.  To enable, install Cython, make sure you have
+significant_digits kwarg only works with netcdf-c >= 4.8.2.  To enable, install Cython, make sure you have
 version 4.8.2 or higher netcdf-c, and rebuild netcdf4-python. Otherwise, use least_significant_digit
 kwarg for quantization."""
                         raise ValueError(msg)

From d3eb554657dc17d62ad03e941eb60861e53847f1 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 12 Nov 2021 11:22:41 -0700
Subject: [PATCH 0687/1504] update

---
 src/netCDF4/_netCDF4.pyx | 39 ++++++++++++++++++---------------------
 1 file changed, 18 insertions(+), 21 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index ae9947932..607986be8 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3835,6 +3835,18 @@ behavior is similar to Fortran or Matlab, but different than numpy.
             if ierr != NC_NOERR:
                 if grp.data_model != 'NETCDF4': grp._enddef()
                 _ensure_nc_success(ierr)
+            # set quantization in netcdf-c >= 4.8.2
+            IF HAS_QUANTIZATION_SUPPORT:
+                if significant_digits is not None:
+                    nsd = significant_digits
+                    ierr = nc_def_var_quantize(self._grpid, self._varid, NC_QUANTIZE_BITGROOM, nsd)
+            ELSE:
+                if significant_digits is not None:
+                    msg = """
+significant_digits kwarg only works with netcdf-c >= 4.8.2.  To enable, install Cython, make sure you have
+version 4.8.2 or higher netcdf-c, and rebuild netcdf4-python. Otherwise, use least_significant_digit
+kwarg for quantization."""
+                    raise ValueError(msg)
             # set zlib, shuffle, chunking, fletcher32 and endian
             # variable settings.
             # don't bother for NETCDF3* formats.
@@ -3894,18 +3906,6 @@ behavior is similar to Fortran or Matlab, but different than numpy.
                     pass # this is the default format.
                 else:
                     raise ValueError("'endian' keyword argument must be 'little','big' or 'native', got '%s'" % endian)
-                # set quantization
-                IF HAS_QUANTIZATION_SUPPORT:
-                    if significant_digits is not None:
-                        nsd = significant_digits
-                        ierr = nc_def_var_quantize(self._grpid, self._varid, NC_QUANTIZE_BITGROOM, nsd)
-                ELSE:
-                    if significant_digits is not None:
-                        msg = """
-significant_digits kwarg only works with netcdf-c >= 4.8.2.  To enable, install Cython, make sure you have
-version 4.8.2 or higher netcdf-c, and rebuild netcdf4-python. Otherwise, use least_significant_digit
-kwarg for quantization."""
-                        raise ValueError(msg)
                 if ierr != NC_NOERR:
                     if grp.data_model != 'NETCDF4': grp._enddef()
                     _ensure_nc_success(ierr)
@@ -4249,17 +4249,14 @@ return dictionary containing HDF5 filter parameters."""
 return number of significant digits used in quantization"""
         IF HAS_QUANTIZATION_SUPPORT:
             cdef int ierr, nsd, quantize_mode
-            if self._grp.data_model not in ['NETCDF4_CLASSIC','NETCDF4']:
+            with nogil:
+                ierr = nc_inq_var_quantize(self._grpid, self._varid, &quantize_mode, &nsd)
+            _ensure_nc_success(ierr)
+            if quantize_mode == NC_NOQUANTIZE:
                 return None
             else:
-                with nogil:
-                    ierr = nc_inq_var_quantize(self._grpid, self._varid, &quantize_mode, &nsd)
-                _ensure_nc_success(ierr)
-                if quantize_mode == NC_NOQUANTIZE:
-                    return None
-                else:
-                    sig_digits = nsd
-                    return sig_digits
+                sig_digits = nsd
+                return sig_digits
         ELSE:
             return None
 

From 902e8defe1a4d18ac4b3db0a41b37240c00f24fc Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 12 Nov 2021 11:34:49 -0700
Subject: [PATCH 0688/1504] Revert "update"

This reverts commit d3eb554657dc17d62ad03e941eb60861e53847f1.
---
 src/netCDF4/_netCDF4.pyx | 39 +++++++++++++++++++++------------------
 1 file changed, 21 insertions(+), 18 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 607986be8..ae9947932 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3835,18 +3835,6 @@ behavior is similar to Fortran or Matlab, but different than numpy.
             if ierr != NC_NOERR:
                 if grp.data_model != 'NETCDF4': grp._enddef()
                 _ensure_nc_success(ierr)
-            # set quantization in netcdf-c >= 4.8.2
-            IF HAS_QUANTIZATION_SUPPORT:
-                if significant_digits is not None:
-                    nsd = significant_digits
-                    ierr = nc_def_var_quantize(self._grpid, self._varid, NC_QUANTIZE_BITGROOM, nsd)
-            ELSE:
-                if significant_digits is not None:
-                    msg = """
-significant_digits kwarg only works with netcdf-c >= 4.8.2.  To enable, install Cython, make sure you have
-version 4.8.2 or higher netcdf-c, and rebuild netcdf4-python. Otherwise, use least_significant_digit
-kwarg for quantization."""
-                    raise ValueError(msg)
             # set zlib, shuffle, chunking, fletcher32 and endian
             # variable settings.
             # don't bother for NETCDF3* formats.
@@ -3906,6 +3894,18 @@ kwarg for quantization."""
                     pass # this is the default format.
                 else:
                     raise ValueError("'endian' keyword argument must be 'little','big' or 'native', got '%s'" % endian)
+                # set quantization
+                IF HAS_QUANTIZATION_SUPPORT:
+                    if significant_digits is not None:
+                        nsd = significant_digits
+                        ierr = nc_def_var_quantize(self._grpid, self._varid, NC_QUANTIZE_BITGROOM, nsd)
+                ELSE:
+                    if significant_digits is not None:
+                        msg = """
+significant_digits kwarg only works with netcdf-c >= 4.8.2.  To enable, install Cython, make sure you have
+version 4.8.2 or higher netcdf-c, and rebuild netcdf4-python. Otherwise, use least_significant_digit
+kwarg for quantization."""
+                        raise ValueError(msg)
                 if ierr != NC_NOERR:
                     if grp.data_model != 'NETCDF4': grp._enddef()
                     _ensure_nc_success(ierr)
@@ -4249,14 +4249,17 @@ return dictionary containing HDF5 filter parameters."""
 return number of significant digits used in quantization"""
         IF HAS_QUANTIZATION_SUPPORT:
             cdef int ierr, nsd, quantize_mode
-            with nogil:
-                ierr = nc_inq_var_quantize(self._grpid, self._varid, &quantize_mode, &nsd)
-            _ensure_nc_success(ierr)
-            if quantize_mode == NC_NOQUANTIZE:
+            if self._grp.data_model not in ['NETCDF4_CLASSIC','NETCDF4']:
                 return None
             else:
-                sig_digits = nsd
-                return sig_digits
+                with nogil:
+                    ierr = nc_inq_var_quantize(self._grpid, self._varid, &quantize_mode, &nsd)
+                _ensure_nc_success(ierr)
+                if quantize_mode == NC_NOQUANTIZE:
+                    return None
+                else:
+                    sig_digits = nsd
+                    return sig_digits
         ELSE:
             return None
 

From 55ad89c3feb786567e725e68f7047e1cdc327a1b Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 12 Nov 2021 11:36:54 -0700
Subject: [PATCH 0689/1504] update docstrings

---
 src/netCDF4/_netCDF4.pyx | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index ae9947932..67813fa48 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -667,7 +667,7 @@ If your data only has a certain number of digits of precision (say for
 example, it is temperature data that was measured with a precision of
 0.1 degrees), you can dramatically improve zlib compression by
 quantizing (or truncating) the data. There are two methods supplied for
-doing this.  You can useg the `least_significant_digit`
+doing this.  You can use the `least_significant_digit`
 keyword argument to `Dataset.createVariable` to specify
 the power of ten of the smallest decimal place in
 the data that is a reliable value. For example if the data has a
@@ -2717,7 +2717,8 @@ retained (in this case bits=4). From the
 in unpacked data that is a reliable value." Default is `None`, or no
 quantization, or 'lossless' compression.  If `significant_digits=3`
 then the data will be quantized so that three significant digits are retained, independent
-of the floating point exponent. This option is available only with netcdf-c >= 4.8.2.
+of the floating point exponent. This option is available only with netcdf-c >= 4.8.2, and 
+only works with `NETCDF4` or `NETCDF4_CLASSIC` formatted files.
 
 When creating variables in a `NETCDF4` or `NETCDF4_CLASSIC` formatted file,
 HDF5 creates something called a 'chunk cache' for each variable.  The
@@ -3571,7 +3572,8 @@ instance. If `None`, the data is not truncated.
 **`significant_digits`**: Describes the number of significant digits
 in the data the contains a reliable value.  Data is
 truncated to retain this number of significant digits when it is assigned to the `Variable`
-instance. If `None`, the data is not truncated. Only available with netcdf-c >= 4.8.2.
+instance. If `None`, the data is not truncated. Only available with netcdf-c >= 4.8.2,
+and only works with `NETCDF4` or `NETCDF4_CLASSIC` formatted files.
 The number of significant digits used in the quantization of variable data can be
 obtained using the `Variable.significant_digits` method.
 

From f13d8ebc9303094f6d20e517bfafe709d028dcc8 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 12 Nov 2021 11:45:43 -0700
Subject: [PATCH 0690/1504] don't include C source file in sdist

---
 MANIFEST.in | 1 +
 1 file changed, 1 insertion(+)

diff --git a/MANIFEST.in b/MANIFEST.in
index 55dc709ac..7f8f909e4 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -10,6 +10,7 @@ include test/*py
 include test/*nc
 include src/netCDF4/__init__.py
 include src/netCDF4/_netCDF4.pyx
+exclude src/netCDF4/_netCDF4.c
 include src/netCDF4/utils.py
 include include/netCDF4.pxi
 include include/mpi-compat.h

From 7c0fab017617fee12abea8b29bbe52fd3f5f8bbb Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 20 Nov 2021 18:08:53 -0700
Subject: [PATCH 0691/1504] fix broken link

---
 docs/index.html          | 45 +++++++++++++++++++++++++---------------
 src/netCDF4/_netCDF4.pyx |  2 +-
 2 files changed, 29 insertions(+), 18 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 149208924..1ecabcde4 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -21,7 +21,7 @@
 
                     
    Contents
    
                     
 
  • Introduction
 
      
@@ -456,7 +456,7 @@ 
      API Documentation
      
                     
      
 netCDF4    
      
 
-                        
      Version 1.5.7
      
+                        
      Version 1.5.8
      
 
 
      Introduction
      
 
@@ -1595,7 +1595,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -1851,9 +1851,9 @@ 
      In-memory (diskless) Datasets
      
     
      
 
         
-            
      close(self)
      
+            
      isopen(self)
      
 
-
      is the Dataset open or closed?
      
+
      Is the Dataset open or closed?
      
 
      
 
 
@@ -2833,7 +2833,7 @@ 
      In-memory (diskless) Datasets
      
 
      chunksizes: Can be used to specify the HDF5 chunksizes for each
 dimension of the variable. A detailed discussion of HDF chunking and I/O
 performance is available
-here.
+here.
 Basically, you want the chunk size for each dimension to match as
 closely as possible the size of the data block that users will read
 from the file. chunksizes cannot be set if contiguous=True.
      
@@ -4181,11 +4181,12 @@ 
      Inherited Members
      
 
      units: a string of the form 
 describing the time units.  can be days, hours, minutes,
 seconds, milliseconds or microseconds.  is the time
-origin. months_since is allowed only for the 360_day calendar.
      
+origin. months since is allowed only for the 360_day calendar
+and common_years since is allowed only for the 365_day calendar.
      
 
 
      calendar: describes the calendar to be used in the time calculations.
 All the values currently defined in the
-CF metadata convention <http://cfconventions.org>__ are supported.
+CF metadata convention <http://cfconventions.org/cf-conventions/cf-conventions#calendar>__ are supported.
 Valid calendars 'standard', 'gregorian', 'proleptic_gregorian'
 'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'.
 Default is None which means the calendar associated with the first
@@ -4195,8 +4196,13 @@ 
      Inherited Members
      
 is used and the year zero exists.  If set to False for real-world
 calendars, then historical year numbering is used and the year 1 is
 preceded by year -1 and no year zero exists.
-The defaults are False for real-world calendars
-and True for idealized calendars.
+The defaults are set to conform with
+CF version 1.9 conventions (False for 'julian', 'gregorian'/'standard', True
+for 'proleptic_gregorian' (ISO 8601) and True for the idealized
+calendars 'noleap'/'365_day', '360_day', 366_day'/'all_leap')
+Note that CF v1.9 does not specifically mention whether year zero
+is allowed in the proleptic_gregorian calendar, but ISO-8601 has
+a year zero so we have adopted this as the default.
 The defaults can only be over-ridden for the real-world calendars,
 for the the idealized calendars the year zero 
 always exists and the has_year_zero kwarg is ignored.
@@ -4231,11 +4237,12 @@ 
      Inherited Members
      
 
      units: a string of the form 
 describing the time units.  can be days, hours, minutes,
 seconds, milliseconds or microseconds.  is the time
-origin. months_since is allowed only for the 360_day calendar.
      
+origin. months since is allowed only for the 360_day calendar
+and common_years since is allowed only for the 365_day calendar.
      
 
 
      calendar: describes the calendar used in the time calculations.
 All the values currently defined in the
-CF metadata convention <http://cfconventions.org>__ are supported.
+CF metadata convention <http://cfconventions.org/cf-conventions/cf-conventions#calendar>__ are supported.
 Valid calendars 'standard', 'gregorian', 'proleptic_gregorian'
 'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'.
 Default is 'standard', which is a mixed Julian/Gregorian calendar.
      
@@ -4252,8 +4259,10 @@ 
      Inherited Members
      
 is used and the year zero exists.  If set to False for real-world
 calendars, then historical year numbering is used and the year 1 is
 preceded by year -1 and no year zero exists.
-The defaults are False for real-world calendars
-and True for idealized calendars.
+The defaults are set to conform with
+CF version 1.9 conventions (False for 'julian', 'gregorian'/'standard', True
+for 'proleptic_gregorian' (ISO 8601) and True for the idealized
+calendars 'noleap'/'365_day', '360_day', 366_day'/'all_leap')
 The defaults can only be over-ridden for the real-world calendars,
 for the the idealized calendars the year zero 
 always exists and the has_year_zero kwarg is ignored.
@@ -4299,7 +4308,7 @@ 
      Inherited Members
      
 
 
      calendar: describes the calendar to be used in the time calculations.
 All the values currently defined in the
-CF metadata convention <http://cfconventions.org>__ are supported.
+CF metadata convention <http://cfconventions.org/cf-conventions/cf-conventions#calendar>__ are supported.
 Valid calendars 'standard', 'gregorian', 'proleptic_gregorian'
 'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'.
 Default is None which means the calendar associated with the first
@@ -4316,8 +4325,10 @@ 
      Inherited Members
      
 is used and the year zero exists.  If set to False for real-world
 calendars, then historical year numbering is used and the year 1 is
 preceded by year -1 and no year zero exists.
-The defaults are False for real-world calendars
-and True for idealized calendars.
+The defaults are set to conform with
+CF version 1.9 conventions (False for 'julian', 'gregorian'/'standard', True
+for 'proleptic_gregorian' (ISO 8601) and True for the idealized
+calendars 'noleap'/'365_day', '360_day', 366_day'/'all_leap')
 The defaults can only be over-ridden for the real-world calendars,
 for the the idealized calendars the year zero 
 always exists and the has_year_zero kwarg is ignored.
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index a7e808b6b..49804e159 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3627,7 +3627,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         **`chunksizes`**: Can be used to specify the HDF5 chunksizes for each
         dimension of the variable. A detailed discussion of HDF chunking and I/O
         performance is available
-        [here](http://www.hdfgroup.org/HDF5/doc/H5.user/Chunking.html).
+        [here](https://support.hdfgroup.org/HDF5/doc/Advanced/Chunking).
         Basically, you want the chunk size for each dimension to match as
         closely as possible the size of the data block that users will read
         from the file. `chunksizes` cannot be set if `contiguous=True`.

From 839bf885e8cdad16af98ca0528e630e79c274a71 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 20 Nov 2021 18:20:25 -0700
Subject: [PATCH 0692/1504] update

---
 src/netCDF4/_netCDF4.pyx | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 49804e159..b6b9a6f1d 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3628,6 +3628,8 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         dimension of the variable. A detailed discussion of HDF chunking and I/O
         performance is available
         [here](https://support.hdfgroup.org/HDF5/doc/Advanced/Chunking).
+        The default chunking scheme in the netcdf-c library is discussed
+        [here](https://www.unidata.ucar.edu/software/netcdf/documentation/NUG/netcdf_perf_chunking.html).
         Basically, you want the chunk size for each dimension to match as
         closely as possible the size of the data block that users will read
         from the file. `chunksizes` cannot be set if `contiguous=True`.

From 77fb40768a3f13d4023858f99a2e23ad719bead7 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 20 Nov 2021 18:21:55 -0700
Subject: [PATCH 0693/1504] update

---
 docs/index.html | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/docs/index.html b/docs/index.html
index 1ecabcde4..eeb417fbe 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -1595,7 +1595,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -2834,6 +2834,8 @@ 
      In-memory (diskless) Datasets
      
 dimension of the variable. A detailed discussion of HDF chunking and I/O
 performance is available
 here.
+The default chunking scheme in the netcdf-c library is discussed
+here.
 Basically, you want the chunk size for each dimension to match as
 closely as possible the size of the data block that users will read
 from the file. chunksizes cannot be set if contiguous=True.
      

From b9e389b545700b2cdb96b8e87d2a0b1637211e9e Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 20 Nov 2021 18:26:12 -0700
Subject: [PATCH 0694/1504] update

---
 src/netCDF4/_netCDF4.pyx | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index b6b9a6f1d..cb2010338 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3622,7 +3622,9 @@ behavior is similar to Fortran or Matlab, but different than numpy.
 
         **`contiguous`**: if `True` (default `False`), the variable data is
         stored contiguously on disk.  Default `False`. Setting to `True` for
-        a variable with an unlimited dimension will trigger an error.
+        a variable with an unlimited dimension will trigger an error. Fixed
+        size variables (with no unlimited dimension) with no compression
+        filters are contiguous by default.
 
         **`chunksizes`**: Can be used to specify the HDF5 chunksizes for each
         dimension of the variable. A detailed discussion of HDF chunking and I/O

From f8a245f0c9690dbdef170f3241c6b48ee23a1102 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 21 Nov 2021 12:08:15 -0700
Subject: [PATCH 0695/1504] fix another broken docstring link

---
 docs/index.html          | 20 +++++++++++++-------
 src/netCDF4/_netCDF4.pyx | 12 ++++++++----
 2 files changed, 21 insertions(+), 11 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index eeb417fbe..5f7928274 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -1595,7 +1595,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -2082,15 +2082,19 @@ 
      In-memory (diskless) Datasets
      
 
 
      If the optional keyword contiguous is True, the variable data is
 stored contiguously on disk.  Default False. Setting to True for
-a variable with an unlimited dimension will trigger an error.
      
+a variable with an unlimited dimension will trigger an error.
+Fixed size variables (with no unlimited dimension) with no compression filters
+are contiguous by default.
      
 
 
      The optional keyword chunksizes can be used to manually specify the
-HDF5 chunksizes for each dimension of the variable. A detailed
-discussion of HDF chunking and I/O performance is available
-here.
+HDF5 chunksizes for each dimension of the variable.
+A detailed discussion of HDF chunking and I/O performance is available
+here.
+The default chunking scheme in the netcdf-c library is discussed
+here.
 Basically, you want the chunk size for each dimension to match as
 closely as possible the size of the data block that users will read
-from the file.  chunksizes cannot be set if contiguous=True.
      
+from the file. chunksizes cannot be set if contiguous=True.
      
 
 
      The optional keyword endian can be used to control whether the
 data is stored in little or big endian format on disk. Possible
@@ -2828,7 +2832,9 @@ 
      In-memory (diskless) Datasets
      
 
 
      contiguous: if True (default False), the variable data is
 stored contiguously on disk.  Default False. Setting to True for
-a variable with an unlimited dimension will trigger an error.
      
+a variable with an unlimited dimension will trigger an error. Fixed
+size variables (with no unlimited dimension) with no compression
+filters are contiguous by default.
      
 
 
      chunksizes: Can be used to specify the HDF5 chunksizes for each
 dimension of the variable. A detailed discussion of HDF chunking and I/O
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index cb2010338..3556e01eb 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2665,14 +2665,18 @@ checksum algorithm is activated to detect errors. Default `False`.
 If the optional keyword `contiguous` is `True`, the variable data is
 stored contiguously on disk.  Default `False`. Setting to `True` for
 a variable with an unlimited dimension will trigger an error.
+Fixed size variables (with no unlimited dimension) with no compression filters
+are contiguous by default.
 
 The optional keyword `chunksizes` can be used to manually specify the
-HDF5 chunksizes for each dimension of the variable. A detailed
-discussion of HDF chunking and I/O performance is available
-[here](http://www.hdfgroup.org/HDF5/doc/H5.user/Chunking.html).
+HDF5 chunksizes for each dimension of the variable.
+A detailed discussion of HDF chunking and I/O performance is available
+[here](https://support.hdfgroup.org/HDF5/doc/Advanced/Chunking).
+The default chunking scheme in the netcdf-c library is discussed
+[here](https://www.unidata.ucar.edu/software/netcdf/documentation/NUG/netcdf_perf_chunking.html).
 Basically, you want the chunk size for each dimension to match as
 closely as possible the size of the data block that users will read
-from the file.  `chunksizes` cannot be set if `contiguous=True`.
+from the file. `chunksizes` cannot be set if `contiguous=True`.
 
 The optional keyword `endian` can be used to control whether the
 data is stored in little or big endian format on disk. Possible

From 61631e97d1b95d5b8fb9f4d832f9cd08a735b347 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 21 Nov 2021 12:14:08 -0700
Subject: [PATCH 0696/1504] update docstrings

---
 docs/index.html          | 78 ++++++++++++++++++++++++++++++++--------
 src/netCDF4/_netCDF4.pyx |  8 +++--
 2 files changed, 69 insertions(+), 17 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 5f7928274..21dd3b41e 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -21,7 +21,7 @@
 
                     
      Contents
      
                     
 
    • Introduction
 
        
@@ -222,6 +222,9 @@ 
        API Documentation
        
                         
      • 
                                 filters
                         
        • 
+                        
      • 
+                                significant_digits
+                        
        • 
                         
      • 
                                 endian
                         
        • 
@@ -456,7 +459,7 @@ 
        API Documentation
        
                     
        
 netCDF4    
        
 
-                        
        Version 1.5.8
        
+                        
        Version 1.6.0
        
 
 
        Introduction
        
 
@@ -1098,14 +1101,23 @@ 
        Efficient compression of netC
 
        If your data only has a certain number of digits of precision (say for
 example, it is temperature data that was measured with a precision of
 0.1 degrees), you can dramatically improve zlib compression by
-quantizing (or truncating) the data using the least_significant_digit
-keyword argument to Dataset.createVariable. The least
-significant digit is the power of ten of the smallest decimal place in
+quantizing (or truncating) the data. There are two methods supplied for
+doing this.  You can use the least_significant_digit
+keyword argument to Dataset.createVariable to specify
+the power of ten of the smallest decimal place in
 the data that is a reliable value. For example if the data has a
 precision of 0.1, then setting least_significant_digit=1 will cause
 data the data to be quantized using numpy.around(scale*data)/scale, where
 scale = 2**bits, and bits is determined so that a precision of 0.1 is
-retained (in this case bits=4).  Effectively, this makes the compression
+retained (in this case bits=4).  This is done at the python level and is
+not a part of the underlying C library.  Starting with netcdf-c version 4.8.2,
+a quantization capability is provided in the library.  This can be
+used via the significant_digits Dataset.createVariable kwarg (new in
+version 1.6.0).
+The interpretation of significant_digits is different than least_signficant_digit
+in that it specifies the absolute number of significant digits independent
+of the magnitude of the variable (the floating point exponent).
+Either of these approaches makes the compression
 'lossy' instead of 'lossless', that is some precision in the data is
 sacrificed for the sake of disk space.
        
 
@@ -1124,6 +1136,11 @@ 
        Efficient compression of netC
 
        >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,least_significant_digit=3)
 
        
 
+
        or with netcdf-c >= 4.8.2
        
+
+
        >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,significant_digits=4)
+
        
+
 
        and see how much smaller the resulting files are.
        
 
 
        Beyond homogeneous arrays of a fixed type - compound data types
        
@@ -1595,7 +1612,7 @@ 
        In-memory (diskless) Datasets
        
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
        
 
-
        contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
        
+
        contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
        
 
 
        copyright: 2008 by Jeffrey Whitaker.
        
 
@@ -1617,7 +1634,7 @@ 
        In-memory (diskless) Datasets
        
                        __has_rename_grp__, __has_nc_inq_path__,
                        __has_nc_inq_format_extended__, __has_nc_open_mem__,
                        __has_nc_create_mem__, __has_cdf5_format__,
-                       __has_parallel4_support__, __has_pnetcdf_support__)
+                       __has_parallel4_support__, __has_pnetcdf_support__,__has_quantization_support__)
 __all__ =\
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
    • @@ -2035,7 +2052,7 @@

    In-memory (diskless) Datasets

    createVariable(self, varname, datatype, dimensions=(), zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, -endian='native', least_significant_digit=None, fill_value=None, chunk_cache=None)

    +endian='native', least_significant_digit=None, significant_digits=None, fill_value=None, chunk_cache=None)

    Creates a new variable with the given varname, datatype, and dimensions. If dimensions are not given, the variable is assumed to be @@ -2112,7 +2129,7 @@

    In-memory (diskless) Datasets

    any data is written to it, defaults given in the dict netCDF4.default_fillvals). If fill_value is set to False, then the variable is not pre-filled.

    -

    If the optional keyword parameter least_significant_digit is +

    If the optional keyword parameters least_significant_digit or significant_digits are specified, variable data will be truncated (quantized). In conjunction with zlib=True this produces 'lossy', but significantly more efficient compression. For example, if least_significant_digit=1, @@ -2122,7 +2139,10 @@

    In-memory (diskless) Datasets

    PSL metadata conventions: "least_significant_digit -- power of ten of the smallest decimal place in unpacked data that is a reliable value." Default is None, or no -quantization, or 'lossless' compression.

    +quantization, or 'lossless' compression. If significant_digits=3 +then the data will be quantized so that three significant digits are retained, independent +of the floating point exponent. This option is available only with netcdf-c >= 4.8.2, and +only works with NETCDF4 or NETCDF4_CLASSIC formatted files.

    When creating variables in a NETCDF4 or NETCDF4_CLASSIC formatted file, HDF5 creates something called a 'chunk cache' for each variable. The @@ -2156,7 +2176,7 @@

    In-memory (diskless) Datasets

    The least_significant_digit attributes describes the power of ten of the smallest decimal place in the data the contains a reliable value. assigned to the Variable -instance. If None, the data is not truncated. The ndim attribute +instance. The ndim attribute is the number of variable dimensions.

    @@ -2761,6 +2781,14 @@

    In-memory (diskless) Datasets

    truncated to this decimal place when it is assigned to the Variable instance. If None, the data is not truncated.

    +

    significant_digits: New in version 1.6.0. Describes the number of significant digits +in the data the contains a reliable value. Data is +truncated to retain this number of significant digits when it is assigned to the Variable +instance. If None, the data is not truncated. Only available with netcdf-c >= 4.8.2, +and only works with NETCDF4 or NETCDF4_CLASSIC formatted files. +The number of significant digits used in the quantization of variable data can be +obtained using the Variable.significant_digits method.

    +

    __orthogonal_indexing__: Always True. Indicates to client code that the object supports 'orthogonal indexing', which means that slices that are 1d arrays or lists slice along each dimension independently. This @@ -2858,14 +2886,20 @@

    In-memory (diskless) Datasets

    The zlib, complevel, shuffle, fletcher32, contiguous and chunksizes keywords are silently ignored for netCDF 3 files that do not use HDF5.

    -

    least_significant_digit: If specified, variable data will be -truncated (quantized). In conjunction with zlib=True this produces +

    least_significant_digit: If this or significant_digits are specified, +variable data will be truncated (quantized).
    +In conjunction with zlib=True this produces 'lossy', but significantly more efficient compression. For example, if least_significant_digit=1, data will be quantized using around(scaledata)/scale, where scale = 2*bits, and bits is determined so that a precision of 0.1 is retained (in this case bits=4). Default is None, or no quantization.

    +

    significant_digits: New in version 1.6.0. +As described for least_significant_digit +except the number of significant digits retained is prescribed independent +of the floating point exponent. Only available with netcdf-c >= 4.8.2.

    +

    fill_value: If specified, the default netCDF _FillValue (the value that the variable gets filled with before any data is written to it) is replaced with this value. If fill_value is set to False, then @@ -3025,6 +3059,22 @@

    In-memory (diskless) Datasets

    + +
    +
    #   + + + def + significant_digits(unknown): +
    + + +

    significant_digits(self)

    + +

    return number of significant digits used in quantization

    +
    + +
    #   diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 5824fec50..c14987345 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -677,7 +677,8 @@ scale = 2**bits, and bits is determined so that a precision of 0.1 is retained (in this case bits=4). This is done at the python level and is not a part of the underlying C library. Starting with netcdf-c version 4.8.2, a quantization capability is provided in the library. This can be -used via the `significant_digits` `Dataset.createVariable` kwarg. +used via the `significant_digits` `Dataset.createVariable` kwarg (new in +version 1.6.0). The interpretation of `significant_digits` is different than `least_signficant_digit` in that it specifies the absolute number of significant digits independent of the magnitude of the variable (the floating point exponent). @@ -3573,7 +3574,7 @@ smallest decimal place in the data the contains a reliable value. Data is truncated to this decimal place when it is assigned to the `Variable` instance. If `None`, the data is not truncated. -**`significant_digits`**: Describes the number of significant digits +**`significant_digits`**: New in version 1.6.0. Describes the number of significant digits in the data the contains a reliable value. Data is truncated to retain this number of significant digits when it is assigned to the `Variable` instance. If `None`, the data is not truncated. Only available with netcdf-c >= 4.8.2, @@ -3687,7 +3688,8 @@ behavior is similar to Fortran or Matlab, but different than numpy. so that a precision of 0.1 is retained (in this case bits=4). Default is `None`, or no quantization. - **`significant_digits`**: As described for `least_significant_digit` + **`significant_digits`**: New in version 1.6.0. + As described for `least_significant_digit` except the number of significant digits retained is prescribed independent of the floating point exponent. Only available with netcdf-c >= 4.8.2. From ec8f637988cd24b73ee8ee7da0131223e64f9346 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Sun, 9 Jan 2022 10:20:12 -0700 Subject: [PATCH 0697/1504] add capability for alternative quantization (netcdf-c #2130) --- include/netCDF4.pxi | 1 + src/netCDF4/_netCDF4.pyx | 16 +++++++++++++--- 2 files changed, 14 insertions(+), 3 deletions(-) diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi index 3afceb3ce..f938e4f30 100644 --- a/include/netCDF4.pxi +++ b/include/netCDF4.pxi @@ -696,6 +696,7 @@ IF HAS_QUANTIZATION_SUPPORT: cdef enum: NC_NOQUANTIZE NC_QUANTIZE_BITGROOM + NC_QUANTIZE_GRANULARBG int nc_def_var_quantize(int ncid, int varid, int quantize_mode, int nsd) int nc_inq_var_quantize(int ncid, int varid, int *quantize_modep, int *nsdp) nogil diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index c14987345..3901bb898 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -3909,8 +3909,15 @@ behavior is similar to Fortran or Matlab, but different than numpy. # set quantization IF HAS_QUANTIZATION_SUPPORT: if significant_digits is not None: - nsd = significant_digits - ierr = nc_def_var_quantize(self._grpid, self._varid, NC_QUANTIZE_BITGROOM, nsd) + if significant_digits > 0: + nsd = significant_digits + ierr = nc_def_var_quantize(self._grpid, + self._varid, NC_QUANTIZE_BITGROOM, nsd) + else: + nsd = -significant_digits + ierr = nc_def_var_quantize(self._grpid, + self._varid, NC_QUANTIZE_GRANULARBG, nsd) + ELSE: if significant_digits is not None: msg = """ @@ -4270,7 +4277,10 @@ return number of significant digits used in quantization""" if quantize_mode == NC_NOQUANTIZE: return None else: - sig_digits = nsd + if quantize_mode == NC_QUANTIZE_GRANULARBG: + sig_digits = -nsd + else: + sig_digits = nsd return sig_digits ELSE: return None From b9dd18f9879124c7a9616c00e37efc5b0dfe5679 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Sun, 9 Jan 2022 12:36:24 -0700 Subject: [PATCH 0698/1504] change behavior of mode='a' to be like python open (issue #1144) --- Changelog | 5 +++++ src/netCDF4/_netCDF4.pyx | 9 +++++---- 2 files changed, 10 insertions(+), 4 deletions(-) diff --git a/Changelog b/Changelog index ccac1b4cb..8a3ed9d8c 100644 --- a/Changelog +++ b/Changelog @@ -1,3 +1,8 @@ + since version 1.5.8 +=================== + * opening a Dataset in append mode (mode = 'a' or 'r+') creates a Dataset + if one does not already exist (similar to python open builtin). Issue #1144. + version 1.5.8 (tag v1.5.8rel) ============================== * Fix Enum bug (issue #1128): the enum_dict member of an EnumType read from a file diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 3556e01eb..7e23342e5 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1214,6 +1214,7 @@ import weakref import warnings import subprocess import pathlib +import os from glob import glob from numpy import ma from libc.string cimport memcpy, memset @@ -2164,7 +2165,7 @@ strings. cmode = NC_MPIIO | _cmode_dict[format] self._inmemory = False - if mode == 'w': + if mode == 'w' or (mode in ['a','r+'] and not os.path.exists(filename)): _set_default_format(format=format) if memory is not None: # if memory is not None and mode='w', memory @@ -2246,7 +2247,7 @@ strings. ierr = nc_open(path, NC_NOWRITE | NC_SHARE, &grpid) else: ierr = nc_open(path, NC_NOWRITE, &grpid) - elif mode == 'r+' or mode == 'a': + elif mode == 'r+' or mode == 'a' and os.path.exists(filename): if parallel: IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: ierr = nc_open_par(path, NC_WRITE | NC_MPIIO, \ @@ -2257,7 +2258,7 @@ strings. ierr = nc_open(path, NC_WRITE | NC_DISKLESS, &grpid) else: ierr = nc_open(path, NC_WRITE, &grpid) - elif mode == 'as' or mode == 'r+s': + elif mode == 'as' or mode == 'r+s' and os.path.exists(filename): if parallel: # NC_SHARE ignored IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: @@ -2269,7 +2270,7 @@ strings. ierr = nc_open(path, NC_SHARE | NC_DISKLESS, &grpid) else: ierr = nc_open(path, NC_SHARE, &grpid) - elif mode == 'ws': + elif mode == 'ws' or (mode in ['as','r+s'] and not os.path.exists(filename)): _set_default_format(format=format) if clobber: if parallel: From 5febb838096f41c8e0c55a23dd11f4e79239f69d Mon Sep 17 00:00:00 2001 From: jswhit Date: Sun, 9 Jan 2022 18:48:52 -0700 Subject: [PATCH 0699/1504] don't include _netCDF.c in tarball --- MANIFEST.in | 1 + 1 file changed, 1 insertion(+) diff --git a/MANIFEST.in b/MANIFEST.in index 55dc709ac..8baa212bb 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -10,6 +10,7 @@ include test/*py include test/*nc include src/netCDF4/__init__.py include src/netCDF4/_netCDF4.pyx +exclude src/netCDF4/_netCDF.c include src/netCDF4/utils.py include include/netCDF4.pxi include include/mpi-compat.h From 920c2338335e7ac0013acc3309b5d53dbd8440d6 Mon Sep 17 00:00:00 2001 From: jswhit Date: Sun, 9 Jan 2022 19:02:37 -0700 Subject: [PATCH 0700/1504] add mode='x' option (same as mode='w' with clobber=False) --- Changelog | 6 ++++-- src/netCDF4/_netCDF4.pyx | 12 ++++++++++-- 2 files changed, 14 insertions(+), 4 deletions(-) diff --git a/Changelog b/Changelog index 8a3ed9d8c..e15ffdfea 100644 --- a/Changelog +++ b/Changelog @@ -1,7 +1,9 @@ since version 1.5.8 -=================== +==================== * opening a Dataset in append mode (mode = 'a' or 'r+') creates a Dataset - if one does not already exist (similar to python open builtin). Issue #1144. + if one does not already exist (similar to python open builtin). Issue #1144. + Added a mode='x' option (as in python open) which is the same as mode='w' with + clobber=False. version 1.5.8 (tag v1.5.8rel) ============================== diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 7e23342e5..305bd5d11 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2032,8 +2032,10 @@ strings. **`mode`**: access mode. `r` means read-only; no data can be modified. `w` means write; a new file is created, an existing file with - the same name is deleted. `a` and `r+` mean append (in analogy with - serial files); an existing file is opened for reading and writing. + the same name is deleted. 'x' means write, but fail if an existing + file with the same name already exists. `a` and `r+` mean append; + an existing file is opened for reading and writing, if + file does not exist already, one is created. Appending `s` to modes `r`, `w`, `r+` or `a` will enable unbuffered shared access to `NETCDF3_CLASSIC`, `NETCDF3_64BIT_OFFSET` or `NETCDF3_64BIT_DATA` formatted files. @@ -2045,6 +2047,7 @@ strings. **`clobber`**: if `True` (default), opening a file with `mode='w'` will clobber an existing file with the same name. if `False`, an exception will be raised if a file with the same name already exists. + mode='x' is identical to mode='w' with clobber=False. **`format`**: underlying file format (one of `'NETCDF4', 'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC'`, `'NETCDF3_64BIT_OFFSET'` or @@ -2165,6 +2168,11 @@ strings. cmode = NC_MPIIO | _cmode_dict[format] self._inmemory = False + + # mode='x' is the same as mode='w' with clobber=False + if mode == 'x': + mode = 'w'; clobber = False + if mode == 'w' or (mode in ['a','r+'] and not os.path.exists(filename)): _set_default_format(format=format) if memory is not None: From 799f42c93c52afd2efdd67e406bc146ab84cd819 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Sun, 9 Jan 2022 20:57:28 -0700 Subject: [PATCH 0701/1504] bump version number --- Changelog | 4 ++-- src/netCDF4/_netCDF4.pyx | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/Changelog b/Changelog index e15ffdfea..bb5cb18ce 100644 --- a/Changelog +++ b/Changelog @@ -1,5 +1,5 @@ - since version 1.5.8 -==================== + version 1.6.0 (not yet released) +================================= * opening a Dataset in append mode (mode = 'a' or 'r+') creates a Dataset if one does not already exist (similar to python open builtin). Issue #1144. Added a mode='x' option (as in python open) which is the same as mode='w' with diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 305bd5d11..13d465d4f 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1,5 +1,5 @@ """ -Version 1.5.8 +Version 1.6.0 ------------- # Introduction @@ -1204,7 +1204,7 @@ if sys.version_info[0:2] < (3, 7): # Python 3.7+ guarantees order; older versions need OrderedDict from collections import OrderedDict -__version__ = "1.5.8" +__version__ = "1.6.0" # Initialize numpy import posixpath From 360cc10a47ff5b27f32865973e2d8d0d01e29c2e Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Mon, 10 Jan 2022 08:40:00 -0700 Subject: [PATCH 0702/1504] exclude examples/data --- MANIFEST.in | 1 + 1 file changed, 1 insertion(+) diff --git a/MANIFEST.in b/MANIFEST.in index 8baa212bb..9d13ecfb2 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -6,6 +6,7 @@ include Changelog include setup.cfg include examples/*py include examples/README.md +exclude examples/data include test/*py include test/*nc include src/netCDF4/__init__.py From 783fec9fa1130af41d35c2bc2034d6b6312393a0 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Mon, 10 Jan 2022 09:17:49 -0700 Subject: [PATCH 0703/1504] check check-manifest version --- .github/workflows/build.yml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 852621a09..496012eda 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -97,6 +97,7 @@ jobs: run: | export PATH=${NETCDF_DIR}/bin:${PATH} python setup.py --version - pip wheel . -w dist --no-deps + check-manifest --version check-manifest --verbose + pip wheel . -w dist --no-deps twine check dist/* From 52dbd375a347763f9a06a5fe2cedd153426213c2 Mon Sep 17 00:00:00 2001 From: jswhit Date: Tue, 11 Jan 2022 13:05:44 -0700 Subject: [PATCH 0704/1504] fix logic in if/else block --- src/netCDF4/_netCDF4.pyx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 13d465d4f..d84f74e4f 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2255,7 +2255,7 @@ strings. ierr = nc_open(path, NC_NOWRITE | NC_SHARE, &grpid) else: ierr = nc_open(path, NC_NOWRITE, &grpid) - elif mode == 'r+' or mode == 'a' and os.path.exists(filename): + elif mode in ['a','r+'] and os.path.exists(filename): if parallel: IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: ierr = nc_open_par(path, NC_WRITE | NC_MPIIO, \ @@ -2266,7 +2266,7 @@ strings. ierr = nc_open(path, NC_WRITE | NC_DISKLESS, &grpid) else: ierr = nc_open(path, NC_WRITE, &grpid) - elif mode == 'as' or mode == 'r+s' and os.path.exists(filename): + elif mode in ['as','r+s'] and os.path.exists(filename): if parallel: # NC_SHARE ignored IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: From 59bb30c66def21a38b13effb878a5df16299d80e Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Fri, 14 Jan 2022 16:28:46 -0700 Subject: [PATCH 0705/1504] update docs --- docs/index.html | 22 +++++++++++++++------- src/netCDF4/_netCDF4.pyx | 20 ++++++++++++++------ 2 files changed, 29 insertions(+), 13 deletions(-) diff --git a/docs/index.html b/docs/index.html index 21dd3b41e..2e6b05312 100644 --- a/docs/index.html +++ b/docs/index.html @@ -1612,7 +1612,7 @@

    In-memory (diskless) Datasets

    the parallel IO example, which is in examples/mpi_example.py. Unit tests are in the test directory.

    -

    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov

    +

    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov

    copyright: 2008 by Jeffrey Whitaker.

    @@ -2141,7 +2141,10 @@

    In-memory (diskless) Datasets

    in unpacked data that is a reliable value." Default is None, or no quantization, or 'lossless' compression. If significant_digits=3 then the data will be quantized so that three significant digits are retained, independent -of the floating point exponent. This option is available only with netcdf-c >= 4.8.2, and +of the floating point exponent. If significant_digits is given as a negative +number, then an alternate algorithm for quantization ('granular bitgrooming') is used +that may results in better compression for typical geophysical datasets. +This significant_digits kwarg is only available with netcdf-c >= 4.8.2, and only works with NETCDF4 or NETCDF4_CLASSIC formatted files.

    When creating variables in a NETCDF4 or NETCDF4_CLASSIC formatted file, @@ -2781,10 +2784,13 @@

    In-memory (diskless) Datasets

    truncated to this decimal place when it is assigned to the Variable instance. If None, the data is not truncated.

    -

    significant_digits: New in version 1.6.0. Describes the number of significant digits -in the data the contains a reliable value. Data is -truncated to retain this number of significant digits when it is assigned to the Variable -instance. If None, the data is not truncated. Only available with netcdf-c >= 4.8.2, +

    significant_digits: New in version 1.6.0. Describes the number of significant +digits in the data the contains a reliable value. Data is +truncated to retain this number of significant digits when it is assigned to the +Variable instance. If None, the data is not truncated. +If specified as a negative number, an alternative quantization algorithm is used +that often produces better compression. +Only available with netcdf-c >= 4.8.2, and only works with NETCDF4 or NETCDF4_CLASSIC formatted files. The number of significant digits used in the quantization of variable data can be obtained using the Variable.significant_digits method.

    @@ -2898,7 +2904,9 @@

    In-memory (diskless) Datasets

    significant_digits: New in version 1.6.0. As described for least_significant_digit except the number of significant digits retained is prescribed independent -of the floating point exponent. Only available with netcdf-c >= 4.8.2.

    +of the floating point exponent. If specified as a negative number, +an alternative quantization algorithm is used that often produces +better compression. Only available with netcdf-c >= 4.8.2.

    fill_value: If specified, the default netCDF _FillValue (the value that the variable gets filled with before any data is written to it) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index c14987345..312bd6a70 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2722,7 +2722,10 @@ retained (in this case bits=4). From the in unpacked data that is a reliable value." Default is `None`, or no quantization, or 'lossless' compression. If `significant_digits=3` then the data will be quantized so that three significant digits are retained, independent -of the floating point exponent. This option is available only with netcdf-c >= 4.8.2, and +of the floating point exponent. If `significant_digits` is given as a negative +number, then an alternate algorithm for quantization ('granular bitgrooming') is used +that may results in better compression for typical geophysical datasets. +This `significant_digits` kwarg is only available with netcdf-c >= 4.8.2, and only works with `NETCDF4` or `NETCDF4_CLASSIC` formatted files. When creating variables in a `NETCDF4` or `NETCDF4_CLASSIC` formatted file, @@ -3574,10 +3577,13 @@ smallest decimal place in the data the contains a reliable value. Data is truncated to this decimal place when it is assigned to the `Variable` instance. If `None`, the data is not truncated. -**`significant_digits`**: New in version 1.6.0. Describes the number of significant digits -in the data the contains a reliable value. Data is -truncated to retain this number of significant digits when it is assigned to the `Variable` -instance. If `None`, the data is not truncated. Only available with netcdf-c >= 4.8.2, +**`significant_digits`**: New in version 1.6.0. Describes the number of significant +digits in the data the contains a reliable value. Data is +truncated to retain this number of significant digits when it is assigned to the +`Variable` instance. If `None`, the data is not truncated. +If specified as a negative number, an alternative quantization algorithm is used +that often produces better compression. +Only available with netcdf-c >= 4.8.2, and only works with `NETCDF4` or `NETCDF4_CLASSIC` formatted files. The number of significant digits used in the quantization of variable data can be obtained using the `Variable.significant_digits` method. @@ -3691,7 +3697,9 @@ behavior is similar to Fortran or Matlab, but different than numpy. **`significant_digits`**: New in version 1.6.0. As described for `least_significant_digit` except the number of significant digits retained is prescribed independent - of the floating point exponent. Only available with netcdf-c >= 4.8.2. + of the floating point exponent. If specified as a negative number, + an alternative quantization algorithm is used that often produces + better compression. Only available with netcdf-c >= 4.8.2. **`fill_value`**: If specified, the default netCDF `_FillValue` (the value that the variable gets filled with before any data is written to it) From 8f3895f3f9c65e4b54958d11f8e989a44627e951 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Fri, 14 Jan 2022 16:31:57 -0700 Subject: [PATCH 0706/1504] fix typo --- src/netCDF4/_netCDF4.pyx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 5443e2196..a0bf447b5 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2733,7 +2733,7 @@ quantization, or 'lossless' compression. If `significant_digits=3` then the data will be quantized so that three significant digits are retained, independent of the floating point exponent. If `significant_digits` is given as a negative number, then an alternate algorithm for quantization ('granular bitgrooming') is used -that may results in better compression for typical geophysical datasets. +that may result in better compression for typical geophysical datasets. This `significant_digits` kwarg is only available with netcdf-c >= 4.8.2, and only works with `NETCDF4` or `NETCDF4_CLASSIC` formatted files. From 599ad6f981541cc90ade94c8f199df1aeed2e651 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Fri, 14 Jan 2022 16:37:23 -0700 Subject: [PATCH 0707/1504] add test for 'granular bitgrooming' (significant_digits<0) --- test/tst_compression2.py | 15 +++++++++++++-- 1 file changed, 13 insertions(+), 2 deletions(-) diff --git a/test/tst_compression2.py b/test/tst_compression2.py index 9a85bf3fd..569a428ed 100644 --- a/test/tst_compression2.py +++ b/test/tst_compression2.py @@ -6,7 +6,7 @@ import os, tempfile, unittest ndim = 100000 -nfiles = 5 +nfiles = 6 files = [tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name for nfile in range(nfiles)] array = uniform(size=(ndim,)) nsd = 3 @@ -39,6 +39,8 @@ def setUp(self): write_netcdf(self.files[3],True,nsd,array) # compressed, lossy, with shuffle. write_netcdf(self.files[4],True,nsd,array,shuffle=True) + # compressed, lossy, with shuffle, and alternate quantization. + write_netcdf(self.files[5],True,-nsd,array,shuffle=True) def tearDown(self): # Remove the temporary files @@ -78,7 +80,16 @@ def runTest(self): f = Dataset(self.files[4]) size = os.stat(self.files[4]).st_size errmax = (np.abs(array-f.variables['data'][:])).max() - #print('compressed lossy with shuffle = ',size,' max err = ',errmax) + print('compressed lossy with shuffle and standard quantization = ',size,' max err = ',errmax) + assert(f.variables['data'].significant_digits() == nsd) + assert(errmax < 1.e-3) + assert(size < 0.24*uncompressed_size) + f.close() + # check lossy compression with shuffle and alternate quantization + f = Dataset(self.files[5]) + size = os.stat(self.files[5]).st_size + errmax = (np.abs(array-f.variables['data'][:])).max() + print('compressed lossy with shuffle and alternate quantization = ',size,' max err = ',errmax) assert(f.variables['data'].significant_digits() == nsd) assert(errmax < 1.e-3) assert(size < 0.24*uncompressed_size) From 3d8ee20ab0eb9f39baf0f46093b4b9cea1cc2a69 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Fri, 14 Jan 2022 16:37:49 -0700 Subject: [PATCH 0708/1504] update docs --- docs/index.html | 13 ++++++++----- 1 file changed, 8 insertions(+), 5 deletions(-) diff --git a/docs/index.html b/docs/index.html index 2e6b05312..a9227f7de 100644 --- a/docs/index.html +++ b/docs/index.html @@ -1612,7 +1612,7 @@

    In-memory (diskless) Datasets

    the parallel IO example, which is in examples/mpi_example.py. Unit tests are in the test directory.

    -

    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov

    +

    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov

    copyright: 2008 by Jeffrey Whitaker.

    @@ -1742,8 +1742,10 @@

    In-memory (diskless) Datasets

    mode: access mode. r means read-only; no data can be modified. w means write; a new file is created, an existing file with -the same name is deleted. a and r+ mean append (in analogy with -serial files); an existing file is opened for reading and writing. +the same name is deleted. 'x' means write, but fail if an existing +file with the same name already exists. a and r+ mean append; +an existing file is opened for reading and writing, if +file does not exist already, one is created. Appending s to modes r, w, r+ or a will enable unbuffered shared access to NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA formatted files. @@ -1754,7 +1756,8 @@

    In-memory (diskless) Datasets

    clobber: if True (default), opening a file with mode='w' will clobber an existing file with the same name. if False, an -exception will be raised if a file with the same name already exists.

    +exception will be raised if a file with the same name already exists. +mode='x' is identical to mode='w' with clobber=False.

    format: underlying file format (one of 'NETCDF4', 'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC', 'NETCDF3_64BIT_OFFSET' or @@ -2143,7 +2146,7 @@

    In-memory (diskless) Datasets

    then the data will be quantized so that three significant digits are retained, independent of the floating point exponent. If significant_digits is given as a negative number, then an alternate algorithm for quantization ('granular bitgrooming') is used -that may results in better compression for typical geophysical datasets. +that may result in better compression for typical geophysical datasets. This significant_digits kwarg is only available with netcdf-c >= 4.8.2, and only works with NETCDF4 or NETCDF4_CLASSIC formatted files.

    From dffc275bbde348cd925b1710781310db0619231d Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Fri, 14 Jan 2022 16:49:44 -0700 Subject: [PATCH 0709/1504] add a benchmark for new quantization algorithms --- examples/bench_compress4.py | 56 +++++++++++++++++++++++++++++++++++++ 1 file changed, 56 insertions(+) create mode 100644 examples/bench_compress4.py diff --git a/examples/bench_compress4.py b/examples/bench_compress4.py new file mode 100644 index 000000000..0f2f01283 --- /dev/null +++ b/examples/bench_compress4.py @@ -0,0 +1,56 @@ +from __future__ import print_function +# benchmark reads and writes, with and without compression. +# tests all four supported file formats. +from numpy.random.mtrand import uniform +import netCDF4 +from timeit import Timer +import os, sys + +# use real data. +URL="http://www.esrl.noaa.gov/psd/thredds/dodsC/Datasets/ncep.reanalysis/pressure/hgt.1990.nc" +nc = netCDF4.Dataset(URL) + +# use real 500 hPa geopotential height data. +n1dim = 100 +n3dim = 73 +n4dim = 144 +ntrials = 10 +sys.stdout.write('reading and writing a %s by %s by %s random array ..\n'%(n1dim,n3dim,n4dim)) +sys.stdout.write('(average of %s trials)\n\n' % ntrials) +print(nc) +print(nc.variables['hgt']) +array = nc.variables['hgt'][0:n1dim,5,:,:] +print(array.min(), array.max(), array.shape, array.dtype) + + +def write_netcdf(filename,nsd): + file = netCDF4.Dataset(filename,'w',format='NETCDF4') + file.createDimension('n1', None) + file.createDimension('n3', n3dim) + file.createDimension('n4', n4dim) + foo = file.createVariable('data',\ + 'f4',('n1','n3','n4'),\ + zlib=True,shuffle=True,\ + significant_digits=nsd) + foo[:] = array + file.close() + +def read_netcdf(filename): + file = netCDF4.Dataset(filename) + data = file.variables['data'][:] + file.close() + +for sigdigits in range(1,6,1): + sys.stdout.write('testing compression with significant_digits=%s...\n' %\ + sigdigits) + write_netcdf('test.nc',sigdigits) + read_netcdf('test.nc') + # print out size of resulting files with standard quantization. + sys.stdout.write('size of test.nc = %s\n'%repr(os.stat('test.nc').st_size)) + sigdigits_neg = -sigdigits + sys.stdout.write('testing compression with significant_digits=%s...\n' %\ + sigdigits_neg) + write_netcdf('test.nc',sigdigits_neg) + read_netcdf('test.nc') + # print out size of resulting files with alternate quantization. + sys.stdout.write('size of test.nc = %s\n'%repr(os.stat('test.nc').st_size)) From af4d7bd34ff2e1cd40f1b3874832754a3b307c59 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Fri, 14 Jan 2022 17:01:44 -0700 Subject: [PATCH 0710/1504] add workflow to test with netcdf-c master --- .github/workflows/build_master.yml | 76 ++++++++++++++++++++++++++++++ 1 file changed, 76 insertions(+) create mode 100644 .github/workflows/build_master.yml diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml new file mode 100644 index 000000000..8241ba32a --- /dev/null +++ b/.github/workflows/build_master.yml @@ -0,0 +1,76 @@ +name: Build and Test on Linux with netcdf-c github master +on: [push, pull_request] +jobs: + build-linux: + name: Python (${{ matrix.python-version }}) + runs-on: ubuntu-latest + env: + NETCDF_DIR: ${{ github.workspace }}/.. + CC: mpicc.mpich + #NO_NET: 1 + strategy: + matrix: + python-version: ["3.9"] + steps: + + - uses: actions/checkout@v2 + + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v2 + with: + python-version: ${{ matrix.python-version }} + + - name: Install Ubuntu Dependencies + run: | + sudo apt-get update + sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev libcurl4-openssl-dev + echo "Download and build netCDF github master" + git clone https://github.com/Unidata/netcdf-c + pushd netcdf-c + export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include" + export LDFLAGS="-L${NETCDF_DIR}/lib" + export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz" + autoreconf -i + ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 + make -j 2 + make install + popd + +# - name: The job has failed +# if: ${{ failure() }} +# run: | +# cd netcdf-c-${NETCDF_VERSION} +# cat config.log + + - name: Install python dependencies via pip + run: | + python -m pip install --upgrade pip + pip install numpy cython cftime pytest twine wheel check-manifest mpi4py + + - name: Install netcdf4-python + run: | + export PATH=${NETCDF_DIR}/bin:${PATH} + python setup.py install + - name: Test + run: | + export PATH=${NETCDF_DIR}/bin:${PATH} + python checkversion.py + # serial + cd test + python run_all.py + # parallel + cd ../examples + mpirun.mpich -np 4 python mpi_example.py + if [ $? -ne 0 ] ; then + echo "hdf5 mpi test failed!" + exit 1 + else + echo "hdf5 mpi test passed!" + fi + mpirun.mpich -np 4 python mpi_example_compressed.py + if [ $? -ne 0 ] ; then + echo "hdf5 compressed mpi test failed!" + exit 1 + else + echo "hdf5 compressed mpi test passed!" + fi From bfae098fd35b0b61ee938f5635b872a9a86e7204 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Fri, 14 Jan 2022 17:16:29 -0700 Subject: [PATCH 0711/1504] check bench_compress4.py --- .github/workflows/build_master.yml | 3 +++ 1 file changed, 3 insertions(+) diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index 8241ba32a..6b1e4dd73 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -55,6 +55,9 @@ jobs: run: | export PATH=${NETCDF_DIR}/bin:${PATH} python checkversion.py + cd examples + python bench_compress4.py + cd .. # serial cd test python run_all.py From 6decf51b2d3bec8ce51702b76e48f773277113e9 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Fri, 14 Jan 2022 17:16:49 -0700 Subject: [PATCH 0712/1504] fix test for negative nsd --- test/tst_compression2.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/test/tst_compression2.py b/test/tst_compression2.py index 569a428ed..cdeecaa1c 100644 --- a/test/tst_compression2.py +++ b/test/tst_compression2.py @@ -90,7 +90,7 @@ def runTest(self): size = os.stat(self.files[5]).st_size errmax = (np.abs(array-f.variables['data'][:])).max() print('compressed lossy with shuffle and alternate quantization = ',size,' max err = ',errmax) - assert(f.variables['data'].significant_digits() == nsd) + assert(f.variables['data'].significant_digits() == -nsd) assert(errmax < 1.e-3) assert(size < 0.24*uncompressed_size) f.close() From bd418c29096a260cfc72cc268adc2ae8282dd9b9 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Fri, 14 Jan 2022 17:25:22 -0700 Subject: [PATCH 0713/1504] reduce output --- examples/bench_compress4.py | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/examples/bench_compress4.py b/examples/bench_compress4.py index 0f2f01283..8693a530f 100644 --- a/examples/bench_compress4.py +++ b/examples/bench_compress4.py @@ -17,10 +17,7 @@ ntrials = 10 sys.stdout.write('reading and writing a %s by %s by %s random array ..\n'%(n1dim,n3dim,n4dim)) sys.stdout.write('(average of %s trials)\n\n' % ntrials) -print(nc) -print(nc.variables['hgt']) array = nc.variables['hgt'][0:n1dim,5,:,:] -print(array.min(), array.max(), array.shape, array.dtype) def write_netcdf(filename,nsd): @@ -40,7 +37,7 @@ def read_netcdf(filename): data = file.variables['data'][:] file.close() -for sigdigits in range(1,6,1): +for sigdigits in range(1,5,1): sys.stdout.write('testing compression with significant_digits=%s...\n' %\ sigdigits) write_netcdf('test.nc',sigdigits) From 07f8e433736dc0360454b259a927a23cf4ae3d16 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Fri, 14 Jan 2022 17:28:39 -0700 Subject: [PATCH 0714/1504] update docs --- docs/index.html | 6 ++++-- src/netCDF4/_netCDF4.pyx | 5 ++++- 2 files changed, 8 insertions(+), 3 deletions(-) diff --git a/docs/index.html b/docs/index.html index a9227f7de..963d4f22e 100644 --- a/docs/index.html +++ b/docs/index.html @@ -1612,7 +1612,7 @@

    In-memory (diskless) Datasets

    the parallel IO example, which is in examples/mpi_example.py. Unit tests are in the test directory.

    -

    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov

    +

    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov

    copyright: 2008 by Jeffrey Whitaker.

    @@ -3082,7 +3082,9 @@

    In-memory (diskless) Datasets

    significant_digits(self)

    -

    return number of significant digits used in quantization

    +

    return number of significant digits used in quantization. +if returned value is negative, alternate quantization method +('granular bitgrooming') is used.

    diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index a0bf447b5..7f6db0d6e 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -4282,7 +4282,10 @@ return dictionary containing HDF5 filter parameters.""" """ **`significant_digits(self)`** -return number of significant digits used in quantization""" +return number of significant digits used in quantization. +if returned value is negative, alternate quantization method +('granular bitgrooming') is used. +""" IF HAS_QUANTIZATION_SUPPORT: cdef int ierr, nsd, quantize_mode if self._grp.data_model not in ['NETCDF4_CLASSIC','NETCDF4']: From 378bc9e871066506daad4401befee701df99e75c Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Fri, 14 Jan 2022 21:47:56 -0700 Subject: [PATCH 0715/1504] allow createDimension to accept Dimension instances (issue #1145) --- Changelog | 2 ++ src/netCDF4/_netCDF4.pyx | 21 ++++++++++++++------- test/tst_dims.py | 21 +++++++++++++++------ 3 files changed, 31 insertions(+), 13 deletions(-) diff --git a/Changelog b/Changelog index bb5cb18ce..a28e52dd2 100644 --- a/Changelog +++ b/Changelog @@ -4,6 +4,8 @@ if one does not already exist (similar to python open builtin). Issue #1144. Added a mode='x' option (as in python open) which is the same as mode='w' with clobber=False. + * allow createVariable to accept either Dimension instances or Dimension + names in dimensions tuple kwarg (issue #1145). version 1.5.8 (tag v1.5.8rel) ============================== diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index d84f74e4f..9b100f7a6 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2653,8 +2653,9 @@ length greater than one are aliases for `str`. Data from netCDF variables is presented to python as numpy arrays with the corresponding data type. -`dimensions` must be a tuple containing dimension names (strings) that -have been defined previously using `Dataset.createDimension`. The default value +`dimensions` must be a tuple containing `Dimension` instances or +dimension names (strings) that have been defined +previously using `Dataset.createDimension`. The default value is an empty tuple, which means the variable is a scalar. If the optional keyword `zlib` is `True`, the data will be compressed in @@ -2757,6 +2758,17 @@ is the number of variable dimensions.""" group = self else: group = self.createGroup(dirname) + # if dimensions is a single string or Dimension instance, + # convert to a tuple. + # This prevents a common error that occurs when + # dimensions = 'lat' instead of ('lat',) + if type(dimensions) == str or type(dimensions) == bytes or\ + type(dimensions) == unicode or type(dimensions) == Dimension: + dimensions = dimensions, + # convert elements of dimensions tuple to names if they are + # Dimension instances. + dimensions =\ + tuple(d.name if isinstance(d,Dimension) else d for d in dimensions) # create variable. group.variables[varname] = Variable(group, varname, datatype, dimensions=dimensions, zlib=zlib, complevel=complevel, shuffle=shuffle, @@ -3696,11 +3708,6 @@ behavior is similar to Fortran or Matlab, but different than numpy. # if complevel is set to zero, set zlib to False. if not complevel: zlib = False - # if dimensions is a string, convert to a tuple - # this prevents a common error that occurs when - # dimensions = 'lat' instead of ('lat',) - if type(dimensions) == str or type(dimensions) == bytes or type(dimensions) == unicode: - dimensions = dimensions, self._grpid = grp._grpid # make a weakref to group to avoid circular ref (issue 218) # keep strong reference the default behaviour (issue 251) diff --git a/test/tst_dims.py b/test/tst_dims.py index 026361f48..5da7c3f89 100644 --- a/test/tst_dims.py +++ b/test/tst_dims.py @@ -20,6 +20,7 @@ TIME_LENG = None GROUP_NAME='forecasts' VAR_NAME='temp' +VAR_NAME2='wind' VAR_TYPE='f8' @@ -28,11 +29,14 @@ class DimensionsTestCase(unittest.TestCase): def setUp(self): self.file = FILE_NAME f = netCDF4.Dataset(self.file, 'w') - f.createDimension(LAT_NAME,LAT_LEN) - f.createDimension(LON_NAME,LON_LEN) - f.createDimension(LEVEL_NAME,LEVEL_LEN) - f.createDimension(TIME_NAME,TIME_LEN) - f.createVariable(VAR_NAME,VAR_TYPE,(LEVEL_NAME, LAT_NAME, LON_NAME, TIME_NAME)) + lat_dim=f.createDimension(LAT_NAME,LAT_LEN) + lon_dim=f.createDimension(LON_NAME,LON_LEN) + lev_dim=f.createDimension(LEVEL_NAME,LEVEL_LEN) + time_dim=f.createDimension(TIME_NAME,TIME_LEN) + # specify dimensions with names + fv1 = f.createVariable(VAR_NAME,VAR_TYPE,(LEVEL_NAME, LAT_NAME, LON_NAME, TIME_NAME)) + # specify dimensions using a mix of names and instances + fv2 = f.createVariable(VAR_NAME2,VAR_TYPE,(lev_dim, LAT_NAME, lon_dim, TIME_NAME)) g = f.createGroup(GROUP_NAME) g.createDimension(LAT_NAME,LAT_LENG) g.createDimension(LON_NAME,LON_LENG) @@ -40,7 +44,7 @@ def setUp(self): # (did not work prior to alpha 18) #g.createDimension(LEVEL_NAME,LEVEL_LENG) #g.createDimension(TIME_NAME,TIME_LENG) - g.createVariable(VAR_NAME,VAR_TYPE,(LEVEL_NAME, LAT_NAME, LON_NAME, TIME_NAME)) + gv = g.createVariable(VAR_NAME,VAR_TYPE,(LEVEL_NAME, LAT_NAME, LON_NAME, TIME_NAME)) f.close() def tearDown(self): @@ -52,6 +56,7 @@ def runTest(self): # check dimensions in root group. f = netCDF4.Dataset(self.file, 'r+') v = f.variables[VAR_NAME] + v2 = f.variables[VAR_NAME2] isunlim = [dim.isunlimited() for dim in f.dimensions.values()] dimlens = [len(dim) for dim in f.dimensions.values()] names_check = [LAT_NAME, LON_NAME, LEVEL_NAME, TIME_NAME] @@ -65,6 +70,10 @@ def runTest(self): # check that dimension names are correct. for name in f.dimensions.keys(): self.assertTrue(name in names_check) + for name in v.dimensions: + self.assertTrue(name in names_check) + for name in v2.dimensions: + self.assertTrue(name in names_check) # check that dimension lengths are correct. for name,dim in f.dimensions.items(): self.assertTrue(len(dim) == lensdict[name]) From 5e0894b76cef248fa37a750a345e6242acc2478d Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Sat, 15 Jan 2022 19:09:35 -0700 Subject: [PATCH 0716/1504] remove vestiges of python 2 and set language_level=3 --- Changelog | 4 +++- setup.py | 3 +++ src/netCDF4/_netCDF4.pyx | 26 +++++++++++++------------- 3 files changed, 19 insertions(+), 14 deletions(-) diff --git a/Changelog b/Changelog index a28e52dd2..f8804a3c1 100644 --- a/Changelog +++ b/Changelog @@ -5,7 +5,9 @@ Added a mode='x' option (as in python open) which is the same as mode='w' with clobber=False. * allow createVariable to accept either Dimension instances or Dimension - names in dimensions tuple kwarg (issue #1145). + names in "dimensions" tuple kwarg (issue #1145). + * remove all vestiges of python 2 in _netCDF4.pyx and set cython language_level + directive to 3 in setup.py. version 1.5.8 (tag v1.5.8rel) ============================== diff --git a/setup.py b/setup.py index 17e7afc46..b4cd2d350 100644 --- a/setup.py +++ b/setup.py @@ -616,6 +616,9 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): library_dirs=lib_dirs, include_dirs=inc_dirs + ['include'], runtime_library_dirs=runtime_lib_dirs)] + # set language_level directive to 3 + for e in ext_modules: + e.cython_directives = {'language_level': "3"} # else: ext_modules = None diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 9b100f7a6..30f9a3ec4 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2408,9 +2408,9 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python.""" raise ValueError(msg) def __repr__(self): - return self.__unicode__() + return self.__str__() - def __unicode__(self): + def __str__(self): ncdump = [repr(type(self))] dimnames = tuple(_tostr(dimname)+'(%s)'%len(self.dimensions[dimname])\ for dimname in self.dimensions.keys()) @@ -2763,7 +2763,7 @@ is the number of variable dimensions.""" # This prevents a common error that occurs when # dimensions = 'lat' instead of ('lat',) if type(dimensions) == str or type(dimensions) == bytes or\ - type(dimensions) == unicode or type(dimensions) == Dimension: + type(dimensions) == Dimension: dimensions = dimensions, # convert elements of dimensions tuple to names if they are # Dimension instances. @@ -3466,9 +3466,9 @@ Read-only class variables: raise AttributeError("size cannot be altered") def __repr__(self): - return self.__unicode__() + return self.__str__() - def __unicode__(self): + def __str__(self): if not dir(self._grp): return 'Dimension object no longer valid' if self.isunlimited(): @@ -3971,9 +3971,9 @@ behavior is similar to Fortran or Matlab, but different than numpy. return self[...] def __repr__(self): - return self.__unicode__() + return self.__str__() - def __unicode__(self): + def __str__(self): cdef int ierr, no_fill if not dir(self._grp): return 'Variable object no longer valid' @@ -5566,9 +5566,9 @@ the user. self.name = dtype_name def __repr__(self): - return self.__unicode__() + return self.__str__() - def __unicode__(self): + def __str__(self): return "%r: name = '%s', numpy dtype = %s" %\ (type(self), self.name, self.dtype) @@ -5848,9 +5848,9 @@ the user. self.name = dtype_name def __repr__(self): - return self.__unicode__() + return self.__str__() - def __unicode__(self): + def __str__(self): if self.dtype == str: return '%r: string type' % (type(self),) else: @@ -5958,9 +5958,9 @@ the user. self.enum_dict = enum_dict def __repr__(self): - return self.__unicode__() + return self.__str__() - def __unicode__(self): + def __str__(self): return "%r: name = '%s', numpy dtype = %s, fields/values =%s" %\ (type(self), self.name, self.dtype, self.enum_dict) From 3fdeda75fc6fff61aa2cbb50559c4d9bdef19bd3 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Mon, 17 Jan 2022 09:19:16 -0700 Subject: [PATCH 0717/1504] convert dim names to dim instances (instead of reverse) --- src/netCDF4/_netCDF4.pyx | 29 ++++++++++++----------------- src/netCDF4/utils.py | 5 ++++- test/tst_dims.py | 34 +++++++++++++++++++++++++--------- 3 files changed, 41 insertions(+), 27 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 30f9a3ec4..70cf56c9d 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1909,6 +1909,7 @@ cdef _get_vars(group): grp = grp.parent free(dimids) # create new variable instance. + dimensions = tuple(_find_dim(group,d) for d in dimensions) if endianness == '>': variables[name] = Variable(group, name, datatype, dimensions, id=varid, endian='big') elif endianness == '<': @@ -2653,7 +2654,7 @@ length greater than one are aliases for `str`. Data from netCDF variables is presented to python as numpy arrays with the corresponding data type. -`dimensions` must be a tuple containing `Dimension` instances or +`dimensions` must be a tuple containing `Dimension` instances and/or dimension names (strings) that have been defined previously using `Dataset.createDimension`. The default value is an empty tuple, which means the variable is a scalar. @@ -2758,17 +2759,18 @@ is the number of variable dimensions.""" group = self else: group = self.createGroup(dirname) - # if dimensions is a single string or Dimension instance, + # if dimensions is a single string or Dimension instance, # convert to a tuple. # This prevents a common error that occurs when # dimensions = 'lat' instead of ('lat',) - if type(dimensions) == str or type(dimensions) == bytes or\ - type(dimensions) == Dimension: + if isinstance(dimensions, (str, bytes, Dimension)): dimensions = dimensions, - # convert elements of dimensions tuple to names if they are - # Dimension instances. + # convert elements of dimensions tuple to Dimension + # instances if they are strings. + # _find_dim looks for dimension in this group, and if not + # found there, looks in parent (and it's parent, etc, back to root). dimensions =\ - tuple(d.name if isinstance(d,Dimension) else d for d in dimensions) + tuple(_find_dim(group,d) if isinstance(d,(str,bytes)) else d for d in dimensions) # create variable. group.variables[varname] = Variable(group, varname, datatype, dimensions=dimensions, zlib=zlib, complevel=complevel, shuffle=shuffle, @@ -3628,7 +3630,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. (for a variable-length string array). Numpy string and unicode datatypes with length greater than one are aliases for `str`. - **`dimensions`**: a tuple containing the variable's dimension names + **`dimensions`**: a tuple containing the variable's Dimension instances (defined previously with `createDimension`). Default is an empty tuple which means the variable is a scalar (and therefore has no dimensions). @@ -3794,12 +3796,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. dims = [] dimids = malloc(sizeof(int) * ndims) for n from 0 <= n < ndims: - dimname = dimensions[n] - # look for dimension in this group, and if not - # found there, look in parent (and it's parent, etc, back to root). - dim = _find_dim(grp, dimname) - if dim is None: - raise KeyError("dimension %s not defined in group %s or any group in it's family tree" % (dimname, grp.path)) + dim = dimensions[n] dimids[n] = dim._dimid dims.append(dim) # go into define mode if it's a netCDF 3 compatible @@ -3930,9 +3927,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. if grp.data_model != 'NETCDF4': grp._enddef() # count how many unlimited dimensions there are. self._nunlimdim = 0 - for dimname in dimensions: - # look in current group, and parents for dim. - dim = _find_dim(self._grp, dimname) + for dim in dimensions: if dim.isunlimited(): self._nunlimdim = self._nunlimdim + 1 # set ndim attribute (number of dimensions). with nogil: diff --git a/src/netCDF4/utils.py b/src/netCDF4/utils.py index 7a858ef42..c96cc7575 100644 --- a/src/netCDF4/utils.py +++ b/src/netCDF4/utils.py @@ -45,7 +45,10 @@ def _find_dim(grp, dimname): group = group.parent except: raise ValueError("cannot find dimension %s in this group or parent groups" % dimname) - return dim + if dim is None: + raise KeyError("dimension %s not defined in group %s or any group in it's family tree" % (dimname, grp.path)) + else: + return dim def _walk_grps(topgrp): """Iterate through all (sub-) groups of topgrp, similar to os.walktree. diff --git a/test/tst_dims.py b/test/tst_dims.py index 5da7c3f89..7af5d2ad7 100644 --- a/test/tst_dims.py +++ b/test/tst_dims.py @@ -19,8 +19,11 @@ TIME_LEN = None TIME_LENG = None GROUP_NAME='forecasts' -VAR_NAME='temp' -VAR_NAME2='wind' +VAR_NAME1='temp1' +VAR_NAME2='temp2' +VAR_NAME3='temp3' +VAR_NAME4='temp4' +VAR_NAME5='temp5' VAR_TYPE='f8' @@ -34,9 +37,14 @@ def setUp(self): lev_dim=f.createDimension(LEVEL_NAME,LEVEL_LEN) time_dim=f.createDimension(TIME_NAME,TIME_LEN) # specify dimensions with names - fv1 = f.createVariable(VAR_NAME,VAR_TYPE,(LEVEL_NAME, LAT_NAME, LON_NAME, TIME_NAME)) + fv1 = f.createVariable(VAR_NAME1,VAR_TYPE,(LEVEL_NAME, LAT_NAME, LON_NAME, TIME_NAME)) + # specify dimensions with instances + fv2 = f.createVariable(VAR_NAME2,VAR_TYPE,(lev_dim,lat_dim,lon_dim,time_dim)) # specify dimensions using a mix of names and instances - fv2 = f.createVariable(VAR_NAME2,VAR_TYPE,(lev_dim, LAT_NAME, lon_dim, TIME_NAME)) + fv3 = f.createVariable(VAR_NAME3,VAR_TYPE,(lev_dim, LAT_NAME, lon_dim, TIME_NAME)) + # single dim instance for name (not in a tuple) + fv4 = f.createVariable(VAR_NAME4,VAR_TYPE,time_dim) + fv5 = f.createVariable(VAR_NAME5,VAR_TYPE,TIME_NAME) g = f.createGroup(GROUP_NAME) g.createDimension(LAT_NAME,LAT_LENG) g.createDimension(LON_NAME,LON_LENG) @@ -44,7 +52,7 @@ def setUp(self): # (did not work prior to alpha 18) #g.createDimension(LEVEL_NAME,LEVEL_LENG) #g.createDimension(TIME_NAME,TIME_LENG) - gv = g.createVariable(VAR_NAME,VAR_TYPE,(LEVEL_NAME, LAT_NAME, LON_NAME, TIME_NAME)) + gv = g.createVariable(VAR_NAME1,VAR_TYPE,(LEVEL_NAME, LAT_NAME, LON_NAME, TIME_NAME)) f.close() def tearDown(self): @@ -55,8 +63,11 @@ def runTest(self): """testing dimensions""" # check dimensions in root group. f = netCDF4.Dataset(self.file, 'r+') - v = f.variables[VAR_NAME] + v1 = f.variables[VAR_NAME1] v2 = f.variables[VAR_NAME2] + v3 = f.variables[VAR_NAME3] + v4 = f.variables[VAR_NAME4] + v5 = f.variables[VAR_NAME5] isunlim = [dim.isunlimited() for dim in f.dimensions.values()] dimlens = [len(dim) for dim in f.dimensions.values()] names_check = [LAT_NAME, LON_NAME, LEVEL_NAME, TIME_NAME] @@ -70,10 +81,15 @@ def runTest(self): # check that dimension names are correct. for name in f.dimensions.keys(): self.assertTrue(name in names_check) - for name in v.dimensions: + for name in v1.dimensions: self.assertTrue(name in names_check) for name in v2.dimensions: self.assertTrue(name in names_check) + for name in v3.dimensions: + self.assertTrue(name in names_check) + self.assertTrue(v4.dimensions[0] == TIME_NAME) + self.assertTrue(v5.dimensions[0] == TIME_NAME) + # check that dimension lengths are correct. # check that dimension lengths are correct. for name,dim in f.dimensions.items(): self.assertTrue(len(dim) == lensdict[name]) @@ -84,7 +100,7 @@ def runTest(self): # make sure length of dimensions change correctly. nadd1 = 2 nadd2 = 4 - v[0:nadd1,:,:,0:nadd2] = uniform(size=(nadd1,LAT_LEN,LON_LEN,nadd2)) + v1[0:nadd1,:,:,0:nadd2] = uniform(size=(nadd1,LAT_LEN,LON_LEN,nadd2)) lensdict[LEVEL_NAME]=nadd1 lensdict[TIME_NAME]=nadd2 # check that dimension lengths are correct. @@ -92,7 +108,7 @@ def runTest(self): self.assertTrue(len(dim) == lensdict[name]) # check dimensions in subgroup. g = f.groups[GROUP_NAME] - vg = g.variables[VAR_NAME] + vg = g.variables[VAR_NAME1] isunlim = [dim.isunlimited() for dim in g.dimensions.values()] dimlens = [len(dim) for dim in g.dimensions.values()] names_check = [LAT_NAME, LON_NAME, LEVEL_NAME, TIME_NAME] From 9a4a885095ab21c9e9f225382b7a41bed65eb859 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Mon, 17 Jan 2022 10:05:11 -0700 Subject: [PATCH 0718/1504] cleanup --- src/netCDF4/_netCDF4.pyx | 11 ++++------- 1 file changed, 4 insertions(+), 7 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 70cf56c9d..0dcd64626 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -3688,7 +3688,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. is replaced with this value. If fill_value is set to `False`, then the variable is not pre-filled. The default netCDF fill values can be found in the dictionary `netCDF4.default_fillvals`. - + **`chunk_cache`**: If specified, sets the chunk cache size for this variable. Persists as long as Dataset is open. Use `set_var_chunk_cache` to change it when Dataset is re-opened. @@ -3793,12 +3793,9 @@ behavior is similar to Fortran or Matlab, but different than numpy. ndims = len(dimensions) # find dimension ids. if ndims: - dims = [] dimids = malloc(sizeof(int) * ndims) for n from 0 <= n < ndims: - dim = dimensions[n] - dimids[n] = dim._dimid - dims.append(dim) + dimids[n] = dimensions[n]._dimid # go into define mode if it's a netCDF 3 compatible # file format. Be careful to exit define mode before # any exceptions are raised. @@ -3866,8 +3863,8 @@ behavior is similar to Fortran or Matlab, but different than numpy. raise ValueError('chunksizes must be a sequence with the same length as dimensions') chunksizesp = malloc(sizeof(size_t) * ndims) for n from 0 <= n < ndims: - if not dims[n].isunlimited() and \ - chunksizes[n] > dims[n].size: + if not dimensions[n].isunlimited() and \ + chunksizes[n] > dimensions[n].size: msg = 'chunksize cannot exceed dimension size' raise ValueError(msg) chunksizesp[n] = chunksizes[n] From 0703c6b19ec3c240c25785c8367b9341f96bb25f Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Mon, 17 Jan 2022 10:05:25 -0700 Subject: [PATCH 0719/1504] update docs --- docs/index.html | 22 +++++++++++++--------- 1 file changed, 13 insertions(+), 9 deletions(-) diff --git a/docs/index.html b/docs/index.html index 5f7928274..a20d5c83d 100644 --- a/docs/index.html +++ b/docs/index.html @@ -21,7 +21,7 @@

    Contents

  • Introduction
      @@ -456,7 +456,7 @@

      API Documentation

      netCDF4

      -

      Version 1.5.8

      +

      Version 1.6.0

      Introduction

      @@ -1595,7 +1595,7 @@

      In-memory (diskless) Datasets

      the parallel IO example, which is in examples/mpi_example.py. Unit tests are in the test directory.

      -

      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov

      +

      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov

      copyright: 2008 by Jeffrey Whitaker.

      @@ -1725,8 +1725,10 @@

      In-memory (diskless) Datasets

      mode: access mode. r means read-only; no data can be modified. w means write; a new file is created, an existing file with -the same name is deleted. a and r+ mean append (in analogy with -serial files); an existing file is opened for reading and writing. +the same name is deleted. 'x' means write, but fail if an existing +file with the same name already exists. a and r+ mean append; +an existing file is opened for reading and writing, if +file does not exist already, one is created. Appending s to modes r, w, r+ or a will enable unbuffered shared access to NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA formatted files. @@ -1737,7 +1739,8 @@

      In-memory (diskless) Datasets

      clobber: if True (default), opening a file with mode='w' will clobber an existing file with the same name. if False, an -exception will be raised if a file with the same name already exists.

      +exception will be raised if a file with the same name already exists. +mode='x' is identical to mode='w' with clobber=False.

      format: underlying file format (one of 'NETCDF4', 'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC', 'NETCDF3_64BIT_OFFSET' or @@ -2062,8 +2065,9 @@

      In-memory (diskless) Datasets

      Data from netCDF variables is presented to python as numpy arrays with the corresponding data type.

      -

      dimensions must be a tuple containing dimension names (strings) that -have been defined previously using Dataset.createDimension. The default value +

      dimensions must be a tuple containing Dimension instances and/or +dimension names (strings) that have been defined +previously using Dataset.createDimension. The default value is an empty tuple, which means the variable is a scalar.

      If the optional keyword zlib is True, the data will be compressed in @@ -2813,7 +2817,7 @@

      In-memory (diskless) Datasets

      (for a variable-length string array). Numpy string and unicode datatypes with length greater than one are aliases for str.

      -

      dimensions: a tuple containing the variable's dimension names +

      dimensions: a tuple containing the variable's Dimension instances (defined previously with createDimension). Default is an empty tuple which means the variable is a scalar (and therefore has no dimensions).

      From 70a0dfbeb67253a8a3627793a092275f39f044a0 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Mon, 17 Jan 2022 20:40:28 -0700 Subject: [PATCH 0720/1504] update docs --- docs/index.html | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/docs/index.html b/docs/index.html index 990be68fb..f57a739b3 100644 --- a/docs/index.html +++ b/docs/index.html @@ -1612,8 +1612,7 @@

      In-memory (diskless) Datasets

      the parallel IO example, which is in examples/mpi_example.py. Unit tests are in the test directory.

      - -

      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov

      +

      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov

      copyright: 2008 by Jeffrey Whitaker.

      From aff5192ed89300288b32c8bfbae0c8ffb4f97f72 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Mon, 17 Jan 2022 20:42:54 -0700 Subject: [PATCH 0721/1504] update --- Changelog | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/Changelog b/Changelog index f1132b19e..5fb64acc5 100644 --- a/Changelog +++ b/Changelog @@ -2,7 +2,8 @@ ================================= * add support for new bit-grooming/quantization functions in netcdf-c 4.8.2 via "signficant_digits" kwarg in Dataset.createVariable. "signficant_digits" Dataset method returns value associated with - Variable. + Variable. If significant_digits < 0, alterate quantization method used + ("granular bit grooming"). * opening a Dataset in append mode (mode = 'a' or 'r+') creates a Dataset if one does not already exist (similar to python open builtin). Issue #1144. Added a mode='x' option (as in python open) which is the same as mode='w' with From f479c122ee581a86c153a0a0ab79b331a4e79849 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 18 Jan 2022 09:41:08 -0700 Subject: [PATCH 0722/1504] remove debug prints --- .github/workflows/build_master.yml | 3 --- test/tst_compression2.py | 4 ++-- 2 files changed, 2 insertions(+), 5 deletions(-) diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index 6b1e4dd73..8241ba32a 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -55,9 +55,6 @@ jobs: run: | export PATH=${NETCDF_DIR}/bin:${PATH} python checkversion.py - cd examples - python bench_compress4.py - cd .. # serial cd test python run_all.py diff --git a/test/tst_compression2.py b/test/tst_compression2.py index cdeecaa1c..3d49baf13 100644 --- a/test/tst_compression2.py +++ b/test/tst_compression2.py @@ -80,7 +80,7 @@ def runTest(self): f = Dataset(self.files[4]) size = os.stat(self.files[4]).st_size errmax = (np.abs(array-f.variables['data'][:])).max() - print('compressed lossy with shuffle and standard quantization = ',size,' max err = ',errmax) + #print('compressed lossy with shuffle and standard quantization = ',size,' max err = ',errmax) assert(f.variables['data'].significant_digits() == nsd) assert(errmax < 1.e-3) assert(size < 0.24*uncompressed_size) @@ -89,7 +89,7 @@ def runTest(self): f = Dataset(self.files[5]) size = os.stat(self.files[5]).st_size errmax = (np.abs(array-f.variables['data'][:])).max() - print('compressed lossy with shuffle and alternate quantization = ',size,' max err = ',errmax) + #print('compressed lossy with shuffle and alternate quantization = ',size,' max err = ',errmax) assert(f.variables['data'].significant_digits() == -nsd) assert(errmax < 1.e-3) assert(size < 0.24*uncompressed_size) From b478505fb9f659932e0b5e65190ad571c93ae772 Mon Sep 17 00:00:00 2001 From: jswhit Date: Thu, 20 Jan 2022 14:42:52 -0700 Subject: [PATCH 0723/1504] add new compression kwarg to createVariable, so that new compression methods can be added --- src/netCDF4/_netCDF4.pyx | 119 +++++++++++++++++++++++++-------------- 1 file changed, 77 insertions(+), 42 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 8535f6489..e3b75230f 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -15,7 +15,7 @@ files that are readable by HDF5 clients. The API modelled after and should be familiar to users of that module. Most new features of netCDF 4 are implemented, such as multiple -unlimited dimensions, groups and zlib data compression. All the new +unlimited dimensions, groups and data compression. All the new numeric data types (such as 64 bit and unsigned integer types) are implemented. Compound (struct), variable length (vlen) and enumerated (enum) data types are supported, but not the opaque data type. @@ -643,9 +643,9 @@ datasets. Data stored in netCDF 4 `Variable` objects can be compressed and decompressed on the fly. The parameters for the compression are -determined by the `zlib`, `complevel` and `shuffle` keyword arguments +determined by the `compression`, `complevel` and `shuffle` keyword arguments to the `Dataset.createVariable` method. To turn on -compression, set `zlib=True`. The `complevel` keyword regulates the +compression, set compression=`zlib`. The `complevel` keyword regulates the speed and efficiency of the compression (1 being fastest, but lowest compression ratio, 9 being slowest but best compression ratio). The default value of `complevel` is 4. Setting `shuffle=False` will turn @@ -665,7 +665,7 @@ format is `NETCDF3_CLASSIC`, `NETCDF3_64BIT_OFFSET` or `NETCDF3_64BIT_DATA`. If your data only has a certain number of digits of precision (say for example, it is temperature data that was measured with a precision of -0.1 degrees), you can dramatically improve zlib compression by +0.1 degrees), you can dramatically improve compression by quantizing (or truncating) the data. There are two methods supplied for doing this. You can use the `least_significant_digit` keyword argument to `Dataset.createVariable` to specify @@ -695,19 +695,19 @@ In our example, try replacing the line with ```python ->>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True) +>>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib') ``` and then ```python ->>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,least_significant_digit=3) +>>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',least_significant_digit=3) ``` or with netcdf-c >= 4.8.2 ```python ->>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,significant_digits=4) +>>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compresson='zlib',significant_digits=4) ``` and see how much smaller the resulting files are. @@ -2636,7 +2636,8 @@ datatype.""" enum_dict) return self.enumtypes[datatype_name] - def createVariable(self, varname, datatype, dimensions=(), zlib=False, + def createVariable(self, varname, datatype, dimensions=(), + compression=None, zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, significant_digits=None,fill_value=None, chunk_cache=None): @@ -2675,11 +2676,17 @@ dimension names (strings) that have been defined previously using `Dataset.createDimension`. The default value is an empty tuple, which means the variable is a scalar. +If the optional keyword argument `compression` is set, the data will be +compressed in the netCDF file using the specified compression algorithm. +Currently only 'zlib' is supported. Default is `None` (no compression). + If the optional keyword `zlib` is `True`, the data will be compressed in -the netCDF file using gzip compression (default `False`). +the netCDF file using zlib compression (default `False`). The use of this option is +deprecated in favor of `compression='zlib'`. -The optional keyword `complevel` is an integer between 1 and 9 describing -the level of compression desired (default 4). Ignored if `zlib=False`. +The optional keyword `complevel` is an integer between 0 and 9 describing +the level of compression desired (default 4). Ignored if `compression=None`. +A value of zero disables compression. If the optional keyword `shuffle` is `True`, the HDF5 shuffle filter will be applied before compressing the data (default `True`). This @@ -2713,7 +2720,7 @@ but if the data is always going to be read on a computer with the opposite format as the one used to create the file, there may be some performance advantage to be gained by setting the endian-ness. -The `zlib, complevel, shuffle, fletcher32, contiguous, chunksizes` and `endian` +The `compression, zlib, complevel, shuffle, fletcher32, contiguous, chunksizes` and `endian` keywords are silently ignored for netCDF 3 files that do not use HDF5. The optional keyword `fill_value` can be used to override the default @@ -2723,7 +2730,7 @@ If fill_value is set to `False`, then the variable is not pre-filled. If the optional keyword parameters `least_significant_digit` or `significant_digits` are specified, variable data will be truncated (quantized). In conjunction -with `zlib=True` this produces 'lossy', but significantly more +with `compression='zlib'` this produces 'lossy', but significantly more efficient compression. For example, if `least_significant_digit=1`, data will be quantized using `numpy.around(scale*data)/scale`, where scale = 2**bits, and bits is determined so that a precision of 0.1 is @@ -2795,7 +2802,7 @@ is the number of variable dimensions.""" tuple(_find_dim(group,d) if isinstance(d,(str,bytes)) else d for d in dimensions) # create variable. group.variables[varname] = Variable(group, varname, datatype, - dimensions=dimensions, zlib=zlib, complevel=complevel, shuffle=shuffle, + dimensions=dimensions, compression=compression, zlib=zlib, complevel=complevel, shuffle=shuffle, fletcher32=fletcher32, contiguous=contiguous, chunksizes=chunksizes, endian=endian, least_significant_digit=least_significant_digit, significant_digits=significant_digits,fill_value=fill_value, chunk_cache=chunk_cache) @@ -3628,12 +3635,13 @@ behavior is similar to Fortran or Matlab, but different than numpy. _iscompound, _isvlen, _isenum, _grp, _cmptype, _vltype, _enumtype,\ __orthogonal_indexing__, _has_lsd, _use_get_vars, _ncstring_attrs__ - def __init__(self, grp, name, datatype, dimensions=(), zlib=False, + def __init__(self, grp, name, datatype, dimensions=(), + compression=None, zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, significant_digits=None,fill_value=None, chunk_cache=None, **kwargs): """ - **`__init__(self, group, name, datatype, dimensions=(), zlib=False, + **`__init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None,fill_value=None,chunk_cache=None)`** @@ -3667,15 +3675,19 @@ behavior is similar to Fortran or Matlab, but different than numpy. (defined previously with `createDimension`). Default is an empty tuple which means the variable is a scalar (and therefore has no dimensions). + **`compression`**: compression algorithm to use. Default None. Currently + only 'zlib' is supported. + **`zlib`**: if `True`, data assigned to the `Variable` - instance is compressed on disk. Default `False`. + instance is compressed on disk. Default `False`. Deprecated - use + `compression='zlib'` instead. - **`complevel`**: the level of zlib compression to use (1 is the fastest, + **`complevel`**: the level of compression to use (1 is the fastest, but poorest compression, 9 is the slowest but best compression). Default 4. - Ignored if `zlib=False`. + Ignored if `compression=None`. A value of 0 disables compression. **`shuffle`**: if `True`, the HDF5 shuffle filter is applied - to improve compression. Default `True`. Ignored if `zlib=False`. + to improve compression. Default `True`. Ignored if `compression=None`. **`fletcher32`**: if `True` (default `False`), the Fletcher32 checksum algorithm is used for error detection. @@ -3705,12 +3717,12 @@ behavior is similar to Fortran or Matlab, but different than numpy. some performance advantage to be gained by setting the endian-ness. For netCDF 3 files (that don't use HDF5), only `endian='native'` is allowed. - The `zlib, complevel, shuffle, fletcher32, contiguous` and `chunksizes` + The `compression, zlib, complevel, shuffle, fletcher32, contiguous` and `chunksizes` keywords are silently ignored for netCDF 3 files that do not use HDF5. **`least_significant_digit`**: If this or `significant_digits` are specified, variable data will be truncated (quantized). - In conjunction with `zlib=True` this produces + In conjunction with `compression='zlib'` this produces 'lossy', but significantly more efficient compression. For example, if `least_significant_digit=1`, data will be quantized using around(scale*data)/scale, where scale = 2**bits, and bits is determined @@ -3738,7 +3750,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. `Dataset.createVariable` method of a `Dataset` or `Group` instance, not using this class directly. """ - cdef int ierr, ndims, icontiguous, ideflate_level, numdims, _grpid, nsd + cdef int ierr, ndims, icontiguous, icomplevel, numdims, _grpid, nsd cdef char namstring[NC_MAX_NAME+1] cdef char *varname cdef nc_type xtype @@ -3748,9 +3760,24 @@ behavior is similar to Fortran or Matlab, but different than numpy. cdef float preemptionp # flag to indicate that orthogonal indexing is supported self.__orthogonal_indexing__ = True - # if complevel is set to zero, set zlib to False. + # For backwards compatibility, deprecated zlib kwarg takes + # precedence if compression kwarg not set. + if zlib and compression is None: + compression = 'zlib' + # if complevel is set to zero, turn off compression if not complevel: - zlib = False + compression = None + # possible future options include 'zstd' and 'bzip2', + zlib = False + #zstd = False + if compression == 'zlib': + zlib = True + #elif compression == 'zstd': + # zstd = True + elif compression is None: + pass + else: + raise ValueError("Unsupported value for compression kwarg") self._grpid = grp._grpid # make a weakref to group to avoid circular ref (issue 218) # keep strong reference the default behaviour (issue 251) @@ -3865,23 +3892,30 @@ behavior is similar to Fortran or Matlab, but different than numpy. if ierr != NC_NOERR: if grp.data_model != 'NETCDF4': grp._enddef() _ensure_nc_success(ierr) - # set zlib, shuffle, chunking, fletcher32 and endian + # set compression, shuffle, chunking, fletcher32 and endian # variable settings. # don't bother for NETCDF3* formats. - # for NETCDF3* formats, the zlib,shuffle,chunking, - # and fletcher32 are silently ignored. Only + # for NETCDF3* formats, the comopression,zlib,shuffle,chunking, + # and fletcher32 flags are silently ignored. Only # endian='native' allowed for NETCDF3. if grp.data_model in ['NETCDF4','NETCDF4_CLASSIC']: - # set zlib and shuffle parameters. - if zlib and ndims: # don't bother for scalar variable - ideflate_level = complevel - if shuffle: - ierr = nc_def_var_deflate(self._grpid, self._varid, 1, 1, ideflate_level) - else: - ierr = nc_def_var_deflate(self._grpid, self._varid, 0, 1, ideflate_level) - if ierr != NC_NOERR: - if grp.data_model != 'NETCDF4': grp._enddef() - _ensure_nc_success(ierr) + # set compression and shuffle parameters. + if compression is None and ndims: # don't bother for scalar variable + if zlib: + icomplevel = complevel + if shuffle: + ierr = nc_def_var_deflate(self._grpid, self._varid, 1, 1, icomplevel) + else: + ierr = nc_def_var_deflate(self._grpid, self._varid, 0, 1, icomplevel) + if ierr != NC_NOERR: + if grp.data_model != 'NETCDF4': grp._enddef() + _ensure_nc_success(ierr) + #if zstd: + # icomplevel = complevel + # ierr = nc_def_var_zstandard(self._grpid, self._varid, icomplevel) + # if ierr != NC_NOERR: + # if grp.data_model != 'NETCDF4': grp._enddef() + # _ensure_nc_success(ierr) # set checksum. if fletcher32 and ndims: # don't bother for scalar variable ierr = nc_def_var_fletcher32(self._grpid, self._varid, 1) @@ -4259,18 +4293,19 @@ attributes.""" **`filters(self)`** return dictionary containing HDF5 filter parameters.""" - cdef int ierr,ideflate,ishuffle,ideflate_level,ifletcher32 - filtdict = {'zlib':False,'shuffle':False,'complevel':0,'fletcher32':False} + cdef int ierr,ideflate,ishuffle,icomplevel,ifletcher32 + filtdict = {'compression':None,'zlib':False,'shuffle':False,'complevel':0,'fletcher32':False} if self._grp.data_model not in ['NETCDF4_CLASSIC','NETCDF4']: return with nogil: - ierr = nc_inq_var_deflate(self._grpid, self._varid, &ishuffle, &ideflate, &ideflate_level) + ierr = nc_inq_var_deflate(self._grpid, self._varid, &ishuffle, &ideflate, &icomplevel) _ensure_nc_success(ierr) with nogil: ierr = nc_inq_var_fletcher32(self._grpid, self._varid, &ifletcher32) _ensure_nc_success(ierr) if ideflate: + filtdict['compression']='zlib' filtdict['zlib']=True - filtdict['complevel']=ideflate_level + filtdict['complevel']=icomplevel if ishuffle: filtdict['shuffle']=True if ifletcher32: From 565d694b8ae70c0b2eaf7996038219d542de819e Mon Sep 17 00:00:00 2001 From: jswhit Date: Thu, 20 Jan 2022 14:46:03 -0700 Subject: [PATCH 0724/1504] update --- Changelog | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/Changelog b/Changelog index 5fb64acc5..07eaa3584 100644 --- a/Changelog +++ b/Changelog @@ -12,6 +12,10 @@ names in "dimensions" tuple kwarg (issue #1145). * remove all vestiges of python 2 in _netCDF4.pyx and set cython language_level directive to 3 in setup.py. + * add 'compression' kwarg to createVariable. Only 'None' and 'zlib' currently + allowed (compression='zlib' is equivalent to zlib=True), but allows + for new compression algorithms to be added when they become available + in netcdf-c. The 'zlib' kwarg is now deprecated. version 1.5.8 (tag v1.5.8rel) ============================== From d1401703876bf289e52e00b4c10acda65f68187d Mon Sep 17 00:00:00 2001 From: jswhit Date: Thu, 20 Jan 2022 15:12:41 -0700 Subject: [PATCH 0725/1504] add test for new compression kwarg --- src/netCDF4/_netCDF4.pyx | 7 ++++--- test/tst_compression.py | 40 ++++++++++++++++++++++++++++++++++++---- 2 files changed, 40 insertions(+), 7 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index e3b75230f..8346f9b25 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -3762,7 +3762,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. self.__orthogonal_indexing__ = True # For backwards compatibility, deprecated zlib kwarg takes # precedence if compression kwarg not set. - if zlib and compression is None: + if zlib and not compression: compression = 'zlib' # if complevel is set to zero, turn off compression if not complevel: @@ -3774,7 +3774,8 @@ behavior is similar to Fortran or Matlab, but different than numpy. zlib = True #elif compression == 'zstd': # zstd = True - elif compression is None: + elif not compression: + compression = None # if compression evaluates to False, set to None. pass else: raise ValueError("Unsupported value for compression kwarg") @@ -3900,7 +3901,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. # endian='native' allowed for NETCDF3. if grp.data_model in ['NETCDF4','NETCDF4_CLASSIC']: # set compression and shuffle parameters. - if compression is None and ndims: # don't bother for scalar variable + if compression is not None and ndims: # don't bother for scalar variable if zlib: icomplevel = complevel if shuffle: diff --git a/test/tst_compression.py b/test/tst_compression.py index a0a5e9939..b39fabd7d 100644 --- a/test/tst_compression.py +++ b/test/tst_compression.py @@ -20,10 +20,25 @@ def write_netcdf(filename,zlib,least_significant_digit,data,dtype='f8',shuffle=F foo = file.createVariable('data',\ dtype,('n'),zlib=zlib,least_significant_digit=least_significant_digit,\ shuffle=shuffle,contiguous=contiguous,complevel=complevel,fletcher32=fletcher32,chunksizes=chunksizes) + # use compression kwarg instead of deprecated zlib + if zlib: + compression='zlib' + else: + compression=None + # anything that evaluates to False is same as None + #compression=False + #compression='' + #compression=0 + #compression='gzip' # should fail + foo2 = file.createVariable('data2',\ + dtype,('n'),compression=compression,least_significant_digit=least_significant_digit,\ + shuffle=shuffle,contiguous=contiguous,complevel=complevel,fletcher32=fletcher32,chunksizes=chunksizes) foo[:] = data + foo2[:] = data file.close() file = Dataset(filename) data = file.variables['data'][:] + data2 = file.variables['data2'][:] file.close() def write_netcdf2(filename,zlib,least_significant_digit,data,dtype='f8',shuffle=False,contiguous=False,\ @@ -68,18 +83,31 @@ def tearDown(self): def runTest(self): """testing zlib and shuffle compression filters""" uncompressed_size = os.stat(self.files[0]).st_size + # check uncompressed data + f = Dataset(self.files[0]) + size = os.stat(self.files[0]).st_size + assert_almost_equal(array,f.variables['data'][:]) + assert_almost_equal(array,f.variables['data2'][:]) + assert f.variables['data'].filters() == {'compression':None,'zlib':False,'shuffle':False,'complevel':0,'fletcher32':False} + assert f.variables['data2'].filters() == {'compression':None,'zlib':False,'shuffle':False,'complevel':0,'fletcher32':False} + assert_almost_equal(size,uncompressed_size) + f.close() # check compressed data. f = Dataset(self.files[1]) size = os.stat(self.files[1]).st_size assert_almost_equal(array,f.variables['data'][:]) - assert f.variables['data'].filters() == {'zlib':True,'shuffle':False,'complevel':6,'fletcher32':False} + assert_almost_equal(array,f.variables['data2'][:]) + assert f.variables['data'].filters() == {'compression':'zlib','zlib':True,'shuffle':False,'complevel':6,'fletcher32':False} + assert f.variables['data2'].filters() == {'compression':'zlib','zlib':True,'shuffle':False,'complevel':6,'fletcher32':False} assert(size < 0.95*uncompressed_size) f.close() # check compression with shuffle f = Dataset(self.files[2]) size = os.stat(self.files[2]).st_size assert_almost_equal(array,f.variables['data'][:]) - assert f.variables['data'].filters() == {'zlib':True,'shuffle':True,'complevel':6,'fletcher32':False} + assert_almost_equal(array,f.variables['data2'][:]) + assert f.variables['data'].filters() == {'compression':'zlib','zlib':True,'shuffle':True,'complevel':6,'fletcher32':False} + assert f.variables['data2'].filters() == {'compression':'zlib','zlib':True,'shuffle':True,'complevel':6,'fletcher32':False} assert(size < 0.85*uncompressed_size) f.close() # check lossy compression without shuffle @@ -87,12 +115,14 @@ def runTest(self): size = os.stat(self.files[3]).st_size checkarray = _quantize(array,lsd) assert_almost_equal(checkarray,f.variables['data'][:]) + assert_almost_equal(checkarray,f.variables['data2'][:]) assert(size < 0.27*uncompressed_size) f.close() # check lossy compression with shuffle f = Dataset(self.files[4]) size = os.stat(self.files[4]).st_size assert_almost_equal(checkarray,f.variables['data'][:]) + assert_almost_equal(checkarray,f.variables['data2'][:]) assert(size < 0.20*uncompressed_size) size_save = size f.close() @@ -100,7 +130,9 @@ def runTest(self): f = Dataset(self.files[5]) size = os.stat(self.files[5]).st_size assert_almost_equal(checkarray,f.variables['data'][:]) - assert f.variables['data'].filters() == {'zlib':True,'shuffle':True,'complevel':6,'fletcher32':True} + assert_almost_equal(checkarray,f.variables['data2'][:]) + assert f.variables['data'].filters() == {'compression':'zlib','zlib':True,'shuffle':True,'complevel':6,'fletcher32':True} + assert f.variables['data2'].filters() == {'compression':'zlib','zlib':True,'shuffle':True,'complevel':6,'fletcher32':True} assert(size < 0.20*uncompressed_size) # should be slightly larger than without fletcher32 assert(size > size_save) @@ -109,7 +141,7 @@ def runTest(self): f = Dataset(self.files[6]) checkarray2 = _quantize(array2,lsd) assert_almost_equal(checkarray2,f.variables['data2'][:]) - assert f.variables['data2'].filters() == {'zlib':True,'shuffle':True,'complevel':6,'fletcher32':True} + assert f.variables['data2'].filters() == {'compression':'zlib','zlib':True,'shuffle':True,'complevel':6,'fletcher32':True} assert f.variables['data2'].chunking() == [chunk1,chunk2] f.close() From ad54e480d29a08fcd12f60e8d2dd6b452e4043cf Mon Sep 17 00:00:00 2001 From: jswhit Date: Thu, 20 Jan 2022 15:18:11 -0700 Subject: [PATCH 0726/1504] fix typo --- src/netCDF4/_netCDF4.pyx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 8346f9b25..65b1521dc 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -707,7 +707,7 @@ and then or with netcdf-c >= 4.8.2 ```python ->>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compresson='zlib',significant_digits=4) +>>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',significant_digits=4) ``` and see how much smaller the resulting files are. From f11f2a4fe7afa7deef10ccfbef09952dac0a9e3b Mon Sep 17 00:00:00 2001 From: jswhit Date: Thu, 20 Jan 2022 15:20:24 -0700 Subject: [PATCH 0727/1504] fix createVariable docstring signature --- src/netCDF4/_netCDF4.pyx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 65b1521dc..22c3b871d 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2642,7 +2642,7 @@ datatype.""" chunksizes=None, endian='native', least_significant_digit=None, significant_digits=None,fill_value=None, chunk_cache=None): """ -**`createVariable(self, varname, datatype, dimensions=(), zlib=False, +**`createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, significant_digits=None, fill_value=None, chunk_cache=None)`** From 23ba280897da1ee3653d07a748ddbad88f3a8b0a Mon Sep 17 00:00:00 2001 From: jswhit Date: Thu, 20 Jan 2022 15:29:29 -0700 Subject: [PATCH 0728/1504] add compression to dict returned by filters method --- test/tst_compression2.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/test/tst_compression2.py b/test/tst_compression2.py index 3d49baf13..b1725b8f4 100644 --- a/test/tst_compression2.py +++ b/test/tst_compression2.py @@ -56,7 +56,7 @@ def runTest(self): size = os.stat(self.files[1]).st_size #print('compressed lossless no shuffle = ',size) assert_almost_equal(array,f.variables['data'][:]) - assert f.variables['data'].filters() == {'zlib':True,'shuffle':False,'complevel':complevel,'fletcher32':False} + assert f.variables['data'].filters() == {'compression':'zlib','zlib':True,'shuffle':False,'complevel':complevel,'fletcher32':False} assert(size < 0.95*uncompressed_size) f.close() # check compression with shuffle @@ -64,7 +64,7 @@ def runTest(self): size = os.stat(self.files[2]).st_size #print('compressed lossless with shuffle ',size) assert_almost_equal(array,f.variables['data'][:]) - assert f.variables['data'].filters() == {'zlib':True,'shuffle':True,'complevel':complevel,'fletcher32':False} + assert f.variables['data'].filters() == {'compression':'zlib','zlib':True,'shuffle':False,'complevel':complevel,'fletcher32':False} assert(size < 0.85*uncompressed_size) f.close() # check lossy compression without shuffle From babca117ff1c2c4463800cfa1960f727a3bff8da Mon Sep 17 00:00:00 2001 From: jswhit Date: Thu, 20 Jan 2022 15:42:08 -0700 Subject: [PATCH 0729/1504] update --- test/tst_compression2.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/test/tst_compression2.py b/test/tst_compression2.py index b1725b8f4..568b4c552 100644 --- a/test/tst_compression2.py +++ b/test/tst_compression2.py @@ -64,7 +64,7 @@ def runTest(self): size = os.stat(self.files[2]).st_size #print('compressed lossless with shuffle ',size) assert_almost_equal(array,f.variables['data'][:]) - assert f.variables['data'].filters() == {'compression':'zlib','zlib':True,'shuffle':False,'complevel':complevel,'fletcher32':False} + assert f.variables['data'].filters() == {'compression':'zlib','zlib':True,'shuffle':True,'complevel':complevel,'fletcher32':False} assert(size < 0.85*uncompressed_size) f.close() # check lossy compression without shuffle From 3db97620b8486dc7267e524bf8bd9feafb747772 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Wed, 26 Jan 2022 18:39:06 -0700 Subject: [PATCH 0730/1504] add /opt/homebrew to default search path --- setup.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/setup.py b/setup.py index 4070543a7..76eceb455 100644 --- a/setup.py +++ b/setup.py @@ -385,7 +385,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): dirstosearch.append(os.environ["CONDA_PREFIX"]) # linux,macosx dirstosearch.append(os.path.join(os.environ["CONDA_PREFIX"],'Library')) # windows dirstosearch += [os.path.expanduser('~'), '/usr/local', '/sw', '/opt', - '/opt/local', '/usr'] + '/opt/local', '/opt/homebrew', '/usr'] # try nc-config first if USE_NCCONFIG and HAS_NCCONFIG: # Try nc-config. From f90fdde1efff8e309af36b9c146e305ab68dd5ba Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 15 Feb 2022 07:51:33 -0700 Subject: [PATCH 0731/1504] fix for issue 1153 ('name' attribute for MFDataset var) --- Changelog | 1 + src/netCDF4/_netCDF4.pyx | 1 + 2 files changed, 2 insertions(+) diff --git a/Changelog b/Changelog index 5fb64acc5..a380f169a 100644 --- a/Changelog +++ b/Changelog @@ -12,6 +12,7 @@ names in "dimensions" tuple kwarg (issue #1145). * remove all vestiges of python 2 in _netCDF4.pyx and set cython language_level directive to 3 in setup.py. + * MFDataset did not aggregate 'name' variable attribute (issue #1153). version 1.5.8 (tag v1.5.8rel) ============================== diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 8535f6489..a6e9d7245 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -6527,6 +6527,7 @@ class _Variable: def __getattr__(self,name): if name == 'shape': return self._shape() if name == 'ndim': return len(self._shape()) + if name == 'name': return self._name try: return self.__dict__[name] except: From 1f43d48abdfe28c02ec1a81ecc7975e2748c4c15 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Wed, 16 Feb 2022 17:24:22 -0700 Subject: [PATCH 0732/1504] NC_QUANTIZE_GRANULARBG changed to NC_QUANTIZE_GRANULARBR --- include/netCDF4.pxi | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi index f938e4f30..7ff41d4b3 100644 --- a/include/netCDF4.pxi +++ b/include/netCDF4.pxi @@ -696,7 +696,7 @@ IF HAS_QUANTIZATION_SUPPORT: cdef enum: NC_NOQUANTIZE NC_QUANTIZE_BITGROOM - NC_QUANTIZE_GRANULARBG + NC_QUANTIZE_GRANULARBR int nc_def_var_quantize(int ncid, int varid, int quantize_mode, int nsd) int nc_inq_var_quantize(int ncid, int varid, int *quantize_modep, int *nsdp) nogil From 51e451ab10b035ae5ce42c89ec82584fff3b2566 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Thu, 17 Feb 2022 12:01:04 -0700 Subject: [PATCH 0733/1504] GRANULARBG -> GRANULARBR --- src/netCDF4/_netCDF4.pyx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index a6e9d7245..6a46bbab3 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -3934,7 +3934,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. else: nsd = -significant_digits ierr = nc_def_var_quantize(self._grpid, - self._varid, NC_QUANTIZE_GRANULARBG, nsd) + self._varid, NC_QUANTIZE_GRANULARBR, nsd) ELSE: if significant_digits is not None: @@ -4296,7 +4296,7 @@ if returned value is negative, alternate quantization method if quantize_mode == NC_NOQUANTIZE: return None else: - if quantize_mode == NC_QUANTIZE_GRANULARBG: + if quantize_mode == NC_QUANTIZE_GRANULARBR: sig_digits = -nsd else: sig_digits = nsd From 5b1a69b9354b1def639a7521429ef6090540f2a4 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Thu, 17 Feb 2022 12:33:36 -0700 Subject: [PATCH 0734/1504] fix for issue #1152 (don't fail if missing_value can't be cast) --- src/netCDF4/_netCDF4.pyx | 11 ++++++++--- 1 file changed, 8 insertions(+), 3 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 6a46bbab3..6da8e67ea 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -4897,15 +4897,20 @@ rename a `Variable` attribute named `oldname` to `newname`.""" def _check_safecast(self, attname): # check to see that variable attribute exists # can can be safely cast to variable data type. + msg="""WARNING: %s not used since it +cannot be safely cast to variable data type""" % attname if hasattr(self, attname): att = numpy.array(self.getncattr(attname)) else: return False - atta = numpy.array(att, self.dtype) + try: + atta = numpy.array(att, self.dtype) + except ValueError: + is_safe = False + warnings.warn(msg) + return is_safe is_safe = _safecast(att,atta) if not is_safe: - msg="""WARNING: %s not used since it -cannot be safely cast to variable data type""" % attname warnings.warn(msg) return is_safe From 48d81dae27bfeeb557c50308f861c9bf4f1f162b Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Thu, 17 Feb 2022 12:39:22 -0700 Subject: [PATCH 0735/1504] add test for issue #1152 --- test/issue1152.nc | Bin 0 -> 6184 bytes test/tst_masked.py | 8 ++++++++ 2 files changed, 8 insertions(+) create mode 100644 test/issue1152.nc diff --git a/test/issue1152.nc b/test/issue1152.nc new file mode 100644 index 0000000000000000000000000000000000000000..d34b6d05c8c3f0ea3f18ab04c1ab6b2f254f9efe GIT binary patch literal 6184 zcmeI0KX21O6u_VDCK$_Y0u(|~B}~DPchB$M`@MIG?B~UNVcNK4 zsJae9esfv67|x{l!uz*ho>hzanrgmL7ucMp@+EQ0@!n8DA(iMXU6m=ik|>YAhl7I^ zrba8HHE#6$JdnPoz;UbMdpu4?K4^3WsD~ZESur@;JKy$yG54o86ovVtDvDxoCDCiM zz#Agr4VB!c!}M=*{jHAYTli^OeK)Z41*_%t+`jJ(`quVt zVD$&Vcxluedd=;wo3yy3Q$P->XnzJwa;Q;pg9oj4ChzsU7R0e0!gN{8IouQF=hMui zkRkkyp-Bu6TZkAmqg^G7IM~x!jxe>n#Fm(K06|fmOtDO=8pIGACUMNHT&i!u9Ig@0 z1U4#Y$}sN7OOGn80XX^o0~XE@k# zhk@t%tb!JBnJRAN4yjzSt1DPRnEPxdxsgn*bXx88Y&w}@iCq)vF1pW=`OEj+Tkp~yO Date: Thu, 17 Feb 2022 12:41:03 -0700 Subject: [PATCH 0736/1504] update --- Changelog | 3 +++ 1 file changed, 3 insertions(+) diff --git a/Changelog b/Changelog index a380f169a..a55d049a2 100644 --- a/Changelog +++ b/Changelog @@ -13,6 +13,9 @@ * remove all vestiges of python 2 in _netCDF4.pyx and set cython language_level directive to 3 in setup.py. * MFDataset did not aggregate 'name' variable attribute (issue #1153). + * issue warning instead of raising an exception if missing_value or + _FillValue can't be cast to the variable type when creating a + masked array (issue #1152). version 1.5.8 (tag v1.5.8rel) ============================== From 2dc303ff25e07a6bd7837bcb8eacd766631f056d Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Thu, 17 Feb 2022 19:52:52 -0700 Subject: [PATCH 0737/1504] update docstring --- src/netCDF4/_netCDF4.pyx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 6da8e67ea..74736289f 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2734,7 +2734,7 @@ in unpacked data that is a reliable value." Default is `None`, or no quantization, or 'lossless' compression. If `significant_digits=3` then the data will be quantized so that three significant digits are retained, independent of the floating point exponent. If `significant_digits` is given as a negative -number, then an alternate algorithm for quantization ('granular bitgrooming') is used +number, then an alternate algorithm for quantization ('granular bit round') is used that may result in better compression for typical geophysical datasets. This `significant_digits` kwarg is only available with netcdf-c >= 4.8.2, and only works with `NETCDF4` or `NETCDF4_CLASSIC` formatted files. @@ -4283,7 +4283,7 @@ return dictionary containing HDF5 filter parameters.""" return number of significant digits used in quantization. if returned value is negative, alternate quantization method -('granular bitgrooming') is used. +('granular bit round') is used. """ IF HAS_QUANTIZATION_SUPPORT: cdef int ierr, nsd, quantize_mode From c1e86ceca4b9388654e337d2bbe7c442db40c4c9 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Thu, 17 Feb 2022 20:01:37 -0700 Subject: [PATCH 0738/1504] update --- Changelog | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Changelog b/Changelog index a55d049a2..f1d24a7b7 100644 --- a/Changelog +++ b/Changelog @@ -3,7 +3,7 @@ * add support for new bit-grooming/quantization functions in netcdf-c 4.8.2 via "signficant_digits" kwarg in Dataset.createVariable. "signficant_digits" Dataset method returns value associated with Variable. If significant_digits < 0, alterate quantization method used - ("granular bit grooming"). + ("granular bit round"). * opening a Dataset in append mode (mode = 'a' or 'r+') creates a Dataset if one does not already exist (similar to python open builtin). Issue #1144. Added a mode='x' option (as in python open) which is the same as mode='w' with From a37e4509714425c8ba9272651c8ad08aa2a0da7c Mon Sep 17 00:00:00 2001 From: jswhit Date: Fri, 18 Feb 2022 12:47:35 -0700 Subject: [PATCH 0739/1504] add quantize_mode kwarg (instead of setting nsd<0) --- examples/bench_compress4.py | 10 +++---- src/netCDF4/_netCDF4.pyx | 56 ++++++++++++++++++++++--------------- test/tst_compression2.py | 20 ++++++------- 3 files changed, 48 insertions(+), 38 deletions(-) diff --git a/examples/bench_compress4.py b/examples/bench_compress4.py index 8693a530f..799c3ea4e 100644 --- a/examples/bench_compress4.py +++ b/examples/bench_compress4.py @@ -20,7 +20,7 @@ array = nc.variables['hgt'][0:n1dim,5,:,:] -def write_netcdf(filename,nsd): +def write_netcdf(filename,nsd,quantize_mode='BitGroom'): file = netCDF4.Dataset(filename,'w',format='NETCDF4') file.createDimension('n1', None) file.createDimension('n3', n3dim) @@ -28,6 +28,7 @@ def write_netcdf(filename,nsd): foo = file.createVariable('data',\ 'f4',('n1','n3','n4'),\ zlib=True,shuffle=True,\ + quantize_mode=quantize_mode,\ significant_digits=nsd) foo[:] = array file.close() @@ -44,10 +45,9 @@ def read_netcdf(filename): read_netcdf('test.nc') # print out size of resulting files with standard quantization. sys.stdout.write('size of test.nc = %s\n'%repr(os.stat('test.nc').st_size)) - sigdigits_neg = -sigdigits - sys.stdout.write('testing compression with significant_digits=%s...\n' %\ - sigdigits_neg) - write_netcdf('test.nc',sigdigits_neg) + sys.stdout.write("testing compression with significant_digits=%s and 'GranularBitRound'...\n" %\ + sigdigits) + write_netcdf('test.nc',sigdigits,quantize_mode='GranularBitRound') read_netcdf('test.nc') # print out size of resulting files with alternate quantization. sys.stdout.write('size of test.nc = %s\n'%repr(os.stat('test.nc').st_size)) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 22c3b871d..1ae9e2a58 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2640,11 +2640,12 @@ datatype.""" compression=None, zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, - significant_digits=None,fill_value=None, chunk_cache=None): + significant_digits=None,quantize_mode='BitGroom',fill_value=None, chunk_cache=None): """ **`createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, -endian='native', least_significant_digit=None, significant_digits=None, fill_value=None, chunk_cache=None)`** +endian='native', least_significant_digit=None, significant_digits=None, quantize_mode='BitGroom', +fill_value=None, chunk_cache=None)`** Creates a new variable with the given `varname`, `datatype`, and `dimensions`. If dimensions are not given, the variable is assumed to be @@ -2740,9 +2741,9 @@ retained (in this case bits=4). From the in unpacked data that is a reliable value." Default is `None`, or no quantization, or 'lossless' compression. If `significant_digits=3` then the data will be quantized so that three significant digits are retained, independent -of the floating point exponent. If `significant_digits` is given as a negative -number, then an alternate algorithm for quantization ('granular bitgrooming') is used -that may result in better compression for typical geophysical datasets. +of the floating point exponent. The keyword argument `quantize_mode` controls +the quantization algorithm (default 'BitGroom'). The alternate 'GranularBitRound' +algorithm may result in better compression for typical geophysical datasets. This `significant_digits` kwarg is only available with netcdf-c >= 4.8.2, and only works with `NETCDF4` or `NETCDF4_CLASSIC` formatted files. @@ -2805,7 +2806,7 @@ is the number of variable dimensions.""" dimensions=dimensions, compression=compression, zlib=zlib, complevel=complevel, shuffle=shuffle, fletcher32=fletcher32, contiguous=contiguous, chunksizes=chunksizes, endian=endian, least_significant_digit=least_significant_digit, - significant_digits=significant_digits,fill_value=fill_value, chunk_cache=chunk_cache) + significant_digits=significant_digits,quantize_mode=quantize_mode,fill_value=fill_value, chunk_cache=chunk_cache) return group.variables[varname] def renameVariable(self, oldname, newname): @@ -3611,12 +3612,16 @@ instance. If `None`, the data is not truncated. digits in the data the contains a reliable value. Data is truncated to retain this number of significant digits when it is assigned to the `Variable` instance. If `None`, the data is not truncated. -If specified as a negative number, an alternative quantization algorithm is used -that often produces better compression. Only available with netcdf-c >= 4.8.2, and only works with `NETCDF4` or `NETCDF4_CLASSIC` formatted files. The number of significant digits used in the quantization of variable data can be -obtained using the `Variable.significant_digits` method. +obtained using the `Variable.significant_digits` method. Default `None` - +no quantization done. + +**`quantize_mode`**: New in version 1.6.0. Controls +the quantization algorithm (default 'BitGroom'). The alternate 'GranularBitRound' +algorithm may result in better compression for typical geophysical datasets. +Ignored if `significant_digts` not specified. **`__orthogonal_indexing__`**: Always `True`. Indicates to client code that the object supports 'orthogonal indexing', which means that slices @@ -3732,9 +3737,12 @@ behavior is similar to Fortran or Matlab, but different than numpy. **`significant_digits`**: New in version 1.6.0. As described for `least_significant_digit` except the number of significant digits retained is prescribed independent - of the floating point exponent. If specified as a negative number, - an alternative quantization algorithm is used that often produces - better compression. Only available with netcdf-c >= 4.8.2. + of the floating point exponent. Default `None` - no quantization done. + + **`quantize_mode`**: New in version 1.6.0. Controls + the quantization algorithm (default 'BitGroom'). The alternate 'GranularBitRound' + algorithm may result in better compression for typical geophysical datasets. + Ignored if `significant_digts` not specified. **`fill_value`**: If specified, the default netCDF `_FillValue` (the value that the variable gets filled with before any data is written to it) @@ -3962,14 +3970,15 @@ behavior is similar to Fortran or Matlab, but different than numpy. # set quantization IF HAS_QUANTIZATION_SUPPORT: if significant_digits is not None: - if significant_digits > 0: - nsd = significant_digits + nsd = significant_digits + if quantize_mode == 'BitGroom': ierr = nc_def_var_quantize(self._grpid, self._varid, NC_QUANTIZE_BITGROOM, nsd) - else: - nsd = -significant_digits + elif quantize_mode == 'GranularBitRound': ierr = nc_def_var_quantize(self._grpid, self._varid, NC_QUANTIZE_GRANULARBG, nsd) + else: + raise ValueError("unknown quantize_mode ('BitGroom and 'GranularBitRound' supported)") ELSE: if significant_digits is not None: @@ -4313,13 +4322,12 @@ return dictionary containing HDF5 filter parameters.""" filtdict['fletcher32']=True return filtdict - def significant_digits(self): + def quantization(self): """ -**`significant_digits(self)`** +**`quantization(self)`** -return number of significant digits used in quantization. -if returned value is negative, alternate quantization method -('granular bitgrooming') is used. +return number of significant digits and the algorithm used in quantization. +Returns None if quantization not active. """ IF HAS_QUANTIZATION_SUPPORT: cdef int ierr, nsd, quantize_mode @@ -4333,10 +4341,12 @@ if returned value is negative, alternate quantization method return None else: if quantize_mode == NC_QUANTIZE_GRANULARBG: - sig_digits = -nsd + sig_digits = nsd + quant_mode = 'GranularBitRound' else: sig_digits = nsd - return sig_digits + quant_mode = 'BitGroom' + return sig_digits, quant_mode ELSE: return None diff --git a/test/tst_compression2.py b/test/tst_compression2.py index 568b4c552..2948ce13a 100644 --- a/test/tst_compression2.py +++ b/test/tst_compression2.py @@ -8,7 +8,7 @@ ndim = 100000 nfiles = 6 files = [tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name for nfile in range(nfiles)] -array = uniform(size=(ndim,)) +data_array = uniform(size=(ndim,)) nsd = 3 complevel = 6 @@ -30,17 +30,17 @@ class CompressionTestCase(unittest.TestCase): def setUp(self): self.files = files # no compression - write_netcdf(self.files[0],False,None,array) + write_netcdf(self.files[0],False,None,data_array) # compressed, lossless, no shuffle. - write_netcdf(self.files[1],True,None,array) + write_netcdf(self.files[1],True,None,data_array) # compressed, lossless, with shuffle. - write_netcdf(self.files[2],True,None,array,shuffle=True) + write_netcdf(self.files[2],True,None,data_array,shuffle=True) # compressed, lossy, no shuffle. - write_netcdf(self.files[3],True,nsd,array) + write_netcdf(self.files[3],True,nsd,data_array) # compressed, lossy, with shuffle. - write_netcdf(self.files[4],True,nsd,array,shuffle=True) + write_netcdf(self.files[4],True,nsd,data_array,shuffle=True) # compressed, lossy, with shuffle, and alternate quantization. - write_netcdf(self.files[5],True,-nsd,array,shuffle=True) + write_netcdf(self.files[5],True,nsd,data_array,quantize_mode='GranularBitRound',shuffle=True) def tearDown(self): # Remove the temporary files @@ -72,7 +72,7 @@ def runTest(self): size = os.stat(self.files[3]).st_size errmax = (np.abs(array-f.variables['data'][:])).max() #print('compressed lossy no shuffle = ',size,' max err = ',errmax) - assert(f.variables['data'].significant_digits() == nsd) + assert(f.variables['data'].quantization() == (nsd,'BitGroom')) assert(errmax < 1.e-3) assert(size < 0.35*uncompressed_size) f.close() @@ -81,7 +81,7 @@ def runTest(self): size = os.stat(self.files[4]).st_size errmax = (np.abs(array-f.variables['data'][:])).max() #print('compressed lossy with shuffle and standard quantization = ',size,' max err = ',errmax) - assert(f.variables['data'].significant_digits() == nsd) + assert(f.variables['data'].quantization() == (nsd,'BitGroom')) assert(errmax < 1.e-3) assert(size < 0.24*uncompressed_size) f.close() @@ -90,7 +90,7 @@ def runTest(self): size = os.stat(self.files[5]).st_size errmax = (np.abs(array-f.variables['data'][:])).max() #print('compressed lossy with shuffle and alternate quantization = ',size,' max err = ',errmax) - assert(f.variables['data'].significant_digits() == -nsd) + assert(f.variables['data'].quantization() == (nsd,'GranularBitRound')) assert(errmax < 1.e-3) assert(size < 0.24*uncompressed_size) f.close() From 4d0163a23f7c2cbacd9826820c42ee87dfa99350 Mon Sep 17 00:00:00 2001 From: jswhit Date: Fri, 18 Feb 2022 12:50:43 -0700 Subject: [PATCH 0740/1504] update --- Changelog | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/Changelog b/Changelog index 07eaa3584..e9d40f5a3 100644 --- a/Changelog +++ b/Changelog @@ -1,9 +1,8 @@ version 1.6.0 (not yet released) ================================= - * add support for new bit-grooming/quantization functions in netcdf-c 4.8.2 via "signficant_digits" - kwarg in Dataset.createVariable. "signficant_digits" Dataset method returns value associated with - Variable. If significant_digits < 0, alterate quantization method used - ("granular bit grooming"). + * add support for new quantization functionality in netcdf-c 4.8.2 via "signficant_digits" + and "quantize_mode" kwargs in Dataset.createVariable. Default quantization_mode is "BitGroom", + but alternate method "GranularBitRound" also supported. * opening a Dataset in append mode (mode = 'a' or 'r+') creates a Dataset if one does not already exist (similar to python open builtin). Issue #1144. Added a mode='x' option (as in python open) which is the same as mode='w' with From 9f2a3b35aab50d582be443f20e7af81482c5d607 Mon Sep 17 00:00:00 2001 From: jswhit Date: Fri, 18 Feb 2022 13:02:40 -0700 Subject: [PATCH 0741/1504] fix merge --- src/netCDF4/_netCDF4.pyx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index c5c07a84c..f12c2bc34 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -3976,7 +3976,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. self._varid, NC_QUANTIZE_BITGROOM, nsd) elif quantize_mode == 'GranularBitRound': ierr = nc_def_var_quantize(self._grpid, - self._varid, NC_QUANTIZE_GRANULARBG, nsd) + self._varid, NC_QUANTIZE_GRANULARBR, nsd) else: raise ValueError("unknown quantize_mode ('BitGroom and 'GranularBitRound' supported)") @@ -4340,7 +4340,7 @@ Returns None if quantization not active. if quantize_mode == NC_NOQUANTIZE: return None else: - if quantize_mode == NC_QUANTIZE_GRANULARBG: + if quantize_mode == NC_QUANTIZE_GRANULARBR: sig_digits = nsd quant_mode = 'GranularBitRound' else: From 11739ca35ec7354cd6dd6841c4558486fb011860 Mon Sep 17 00:00:00 2001 From: jswhit Date: Fri, 18 Feb 2022 13:17:25 -0700 Subject: [PATCH 0742/1504] update --- src/netCDF4/_netCDF4.pyx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index f12c2bc34..5aecad328 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -3644,7 +3644,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. compression=None, zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, - significant_digits=None,fill_value=None, chunk_cache=None, **kwargs): + significant_digits=None,quantize_mode='BitGroom',fill_value=None, chunk_cache=None, **kwargs): """ **`__init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, From 3185d4b751678fbadd042e9ffcf9d2b484301bc8 Mon Sep 17 00:00:00 2001 From: jswhit Date: Fri, 18 Feb 2022 13:27:14 -0700 Subject: [PATCH 0743/1504] update --- test/tst_compression2.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/test/tst_compression2.py b/test/tst_compression2.py index 2948ce13a..82fe8071d 100644 --- a/test/tst_compression2.py +++ b/test/tst_compression2.py @@ -13,12 +13,12 @@ complevel = 6 def write_netcdf(filename,zlib,significant_digits,data,dtype='f8',shuffle=False,\ - complevel=6): + complevel=6,quantize_mode="BitGroom"): file = Dataset(filename,'w') file.createDimension('n', ndim) foo = file.createVariable('data',\ dtype,('n'),zlib=zlib,significant_digits=significant_digits,\ - shuffle=shuffle,complevel=complevel) + shuffle=shuffle,complevel=complevel,quantize_mode=quantize_mode) foo[:] = data file.close() file = Dataset(filename) From 803fd0c873a49d92bd80b76c157dac4ff25e82d9 Mon Sep 17 00:00:00 2001 From: jswhit Date: Fri, 18 Feb 2022 13:34:13 -0700 Subject: [PATCH 0744/1504] update --- test/tst_compression2.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/test/tst_compression2.py b/test/tst_compression2.py index 82fe8071d..8b07adb5c 100644 --- a/test/tst_compression2.py +++ b/test/tst_compression2.py @@ -55,7 +55,7 @@ def runTest(self): f = Dataset(self.files[1]) size = os.stat(self.files[1]).st_size #print('compressed lossless no shuffle = ',size) - assert_almost_equal(array,f.variables['data'][:]) + assert_almost_equal(data_array,f.variables['data'][:]) assert f.variables['data'].filters() == {'compression':'zlib','zlib':True,'shuffle':False,'complevel':complevel,'fletcher32':False} assert(size < 0.95*uncompressed_size) f.close() @@ -63,14 +63,14 @@ def runTest(self): f = Dataset(self.files[2]) size = os.stat(self.files[2]).st_size #print('compressed lossless with shuffle ',size) - assert_almost_equal(array,f.variables['data'][:]) + assert_almost_equal(data_array,f.variables['data'][:]) assert f.variables['data'].filters() == {'compression':'zlib','zlib':True,'shuffle':True,'complevel':complevel,'fletcher32':False} assert(size < 0.85*uncompressed_size) f.close() # check lossy compression without shuffle f = Dataset(self.files[3]) size = os.stat(self.files[3]).st_size - errmax = (np.abs(array-f.variables['data'][:])).max() + errmax = (np.abs(data_array-f.variables['data'][:])).max() #print('compressed lossy no shuffle = ',size,' max err = ',errmax) assert(f.variables['data'].quantization() == (nsd,'BitGroom')) assert(errmax < 1.e-3) @@ -79,7 +79,7 @@ def runTest(self): # check lossy compression with shuffle f = Dataset(self.files[4]) size = os.stat(self.files[4]).st_size - errmax = (np.abs(array-f.variables['data'][:])).max() + errmax = (np.abs(data_array-f.variables['data'][:])).max() #print('compressed lossy with shuffle and standard quantization = ',size,' max err = ',errmax) assert(f.variables['data'].quantization() == (nsd,'BitGroom')) assert(errmax < 1.e-3) @@ -88,7 +88,7 @@ def runTest(self): # check lossy compression with shuffle and alternate quantization f = Dataset(self.files[5]) size = os.stat(self.files[5]).st_size - errmax = (np.abs(array-f.variables['data'][:])).max() + errmax = (np.abs(data_array-f.variables['data'][:])).max() #print('compressed lossy with shuffle and alternate quantization = ',size,' max err = ',errmax) assert(f.variables['data'].quantization() == (nsd,'GranularBitRound')) assert(errmax < 1.e-3) From bcdf2a3e2e948d8d7a990cc446f867bd4d5acdbb Mon Sep 17 00:00:00 2001 From: jswhit Date: Fri, 18 Feb 2022 14:11:00 -0700 Subject: [PATCH 0745/1504] update --- .github/workflows/build_master.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index 8241ba32a..69a818ba3 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -60,6 +60,7 @@ jobs: python run_all.py # parallel cd ../examples + python bench_compress4.py mpirun.mpich -np 4 python mpi_example.py if [ $? -ne 0 ] ; then echo "hdf5 mpi test failed!" From a264361e95a4c8bf0d2d66c331999c123e29eda4 Mon Sep 17 00:00:00 2001 From: jswhit Date: Fri, 18 Feb 2022 18:12:57 -0700 Subject: [PATCH 0746/1504] update --- docs/index.html | 526 ++++++++++++++++++++++++++---------------------- 1 file changed, 289 insertions(+), 237 deletions(-) diff --git a/docs/index.html b/docs/index.html index f57a739b3..64f10938b 100644 --- a/docs/index.html +++ b/docs/index.html @@ -3,24 +3,24 @@ - + netCDF4 API documentation - - - - - - -

      @@ -474,7 +475,7 @@

      Introduction

      and should be familiar to users of that module.

      Most new features of netCDF 4 are implemented, such as multiple -unlimited dimensions, groups and zlib data compression. All the new +unlimited dimensions, groups and data compression. All the new numeric data types (such as 64 bit and unsigned integer types) are implemented. Compound (struct), variable length (vlen) and enumerated (enum) data types are supported, but not the opaque data type. @@ -576,7 +577,7 @@

      Creating/Opening/Closing a netCDF

      Here's an example:

      -
      >>> from netCDF4 import Dataset
+
      >>> from netCDF4 import Dataset
 >>> rootgrp = Dataset("test.nc", "w", format="NETCDF4")
 >>> print(rootgrp.data_model)
 NETCDF4
@@ -605,7 +606,7 @@ 
      Groups in a netCDF file
      
 NETCDF4 formatted files support Groups, if you try to create a Group
 in a netCDF 3 file you will get an error message.
      
 
-
      >>> rootgrp = Dataset("test.nc", "a")
+
      >>> rootgrp = Dataset("test.nc", "a")
 >>> fcstgrp = rootgrp.createGroup("forecasts")
 >>> analgrp = rootgrp.createGroup("analyses")
 >>> print(rootgrp.groups)
@@ -629,7 +630,7 @@ 
      Groups in a netCDF file
      
 that group.  To simplify the creation of nested groups, you can
 use a unix-like path as an argument to Dataset.createGroup.
      
 
-
      >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
+
      >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
 >>> fcstgrp2 = rootgrp.createGroup("/forecasts/model2")
 
      
 
@@ -643,7 +644,7 @@ 
      Groups in a netCDF file
      
 to walk the directory tree. Note that printing the Dataset or Group
 object yields summary information about it's contents.
      
 
-
      >>> def walktree(top):
+
      >>> def walktree(top):
 ...     yield top.groups.values()
 ...     for value in top.groups.values():
 ...         yield from walktree(value)
@@ -693,7 +694,7 @@ 
      Dimensions in a netCDF file
      
 dimension is a new netCDF 4 feature, in netCDF 3 files there may be only
 one, and it must be the first (leftmost) dimension of the variable.
      
 
-
      >>> level = rootgrp.createDimension("level", None)
+
      >>> level = rootgrp.createDimension("level", None)
 >>> time = rootgrp.createDimension("time", None)
 >>> lat = rootgrp.createDimension("lat", 73)
 >>> lon = rootgrp.createDimension("lon", 144)
@@ -701,7 +702,7 @@ 
      Dimensions in a netCDF file
      
 
 
      All of the Dimension instances are stored in a python dictionary.
      
 
-
      >>> print(rootgrp.dimensions)
+
      >>> print(rootgrp.dimensions)
 {'level': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0, 'time': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0, 'lat': <class 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 73, 'lon': <class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144}
 
      
 
@@ -710,7 +711,7 @@ 
      Dimensions in a netCDF file
      
 Dimension.isunlimited method of a Dimension instance
 be used to determine if the dimensions is unlimited, or appendable.
      
 
-
      >>> print(len(lon))
+
      >>> print(len(lon))
 144
 >>> print(lon.isunlimited())
 False
@@ -722,7 +723,7 @@ 
      Dimensions in a netCDF file
      
 provides useful summary info, including the name and length of the dimension,
 and whether it is unlimited.
      
 
-
      >>> for dimobj in rootgrp.dimensions.values():
+
      >>> for dimobj in rootgrp.dimensions.values():
 ...     print(dimobj)
 <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0
 <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0
@@ -767,7 +768,7 @@ 
      Variables in a netCDF file
      
 method returns an instance of the Variable class whose methods can be
 used later to access and set variable data and attributes.
      
 
-
      >>> times = rootgrp.createVariable("time","f8",("time",))
+
      >>> times = rootgrp.createVariable("time","f8",("time",))
 >>> levels = rootgrp.createVariable("level","i4",("level",))
 >>> latitudes = rootgrp.createVariable("lat","f4",("lat",))
 >>> longitudes = rootgrp.createVariable("lon","f4",("lon",))
@@ -779,7 +780,7 @@ 
      Variables in a netCDF file
      
 
      To get summary info on a Variable instance in an interactive session,
 just print it.
      
 
-
      >>> print(temp)
+
      >>> print(temp)
 <class 'netCDF4._netCDF4.Variable'>
 float32 temp(time, level, lat, lon)
     units: K
@@ -790,7 +791,7 @@ 
      Variables in a netCDF file
      
 
 
      You can use a path to create a Variable inside a hierarchy of groups.
      
 
-
      >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
+
      >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
 
      
 
 
      If the intermediate groups do not yet exist, they will be created.
      
@@ -798,7 +799,7 @@ 
      Variables in a netCDF file
      
 
      You can also query a Dataset or Group instance directly to obtain Group or
 Variable instances using paths.
      
 
-
      >>> print(rootgrp["/forecasts/model1"])  # a Group instance
+
      >>> print(rootgrp["/forecasts/model1"])  # a Group instance
 <class 'netCDF4._netCDF4.Group'>
 group /forecasts/model1:
     dimensions(sizes): 
@@ -816,7 +817,7 @@ 
      Variables in a netCDF file
      
 
      All of the variables in the Dataset or Group are stored in a
 Python dictionary, in the same way as the dimensions:
      
 
-
      >>> print(rootgrp.variables)
+
      >>> print(rootgrp.variables)
 {'time': <class 'netCDF4._netCDF4.Variable'>
 float64 time(time)
 unlimited dimensions: time
@@ -859,7 +860,7 @@ 
      Attributes in a netCDF file
      
 variables. Attributes can be strings, numbers or sequences. Returning to
 our example,
      
 
-
      >>> import time
+
      >>> import time
 >>> rootgrp.description = "bogus example script"
 >>> rootgrp.history = "Created " + time.ctime(time.time())
 >>> rootgrp.source = "netCDF4 python module tutorial"
@@ -877,7 +878,7 @@ 
      Attributes in a netCDF file
      
 built-in dir Python function will return a bunch of private methods
 and attributes that cannot (or should not) be modified by the user.
      
 
-
      >>> for name in rootgrp.ncattrs():
+
      >>> for name in rootgrp.ncattrs():
 ...     print("Global attr {} = {}".format(name, getattr(rootgrp, name)))
 Global attr description = bogus example script
 Global attr history = Created Mon Jul  8 14:19:41 2019
@@ -888,7 +889,7 @@ 
      Attributes in a netCDF file
      
 instance provides all the netCDF attribute name/value pairs in a python
 dictionary:
      
 
-
      >>> print(rootgrp.__dict__)
+
      >>> print(rootgrp.__dict__)
 {'description': 'bogus example script', 'history': 'Created Mon Jul  8 14:19:41 2019', 'source': 'netCDF4 python module tutorial'}
 
      
 
@@ -901,7 +902,7 @@ 
      Writing data
 
      Now that you have a netCDF Variable instance, how do you put data
 into it? You can just treat it like an array and assign data to a slice.
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> lats =  np.arange(-90,91,2.5)
 >>> lons =  np.arange(-180,180,2.5)
 >>> latitudes[:] = lats
@@ -921,7 +922,7 @@ 
      Writing data
 objects with unlimited dimensions will grow along those dimensions if you
 assign data outside the currently defined range of indices.
      
 
-
      >>> # append along two unlimited dimensions by assigning to slice.
+
      >>> # append along two unlimited dimensions by assigning to slice.
 >>> nlats = len(rootgrp.dimensions["lat"])
 >>> nlons = len(rootgrp.dimensions["lon"])
 >>> print("temp shape before adding data = {}".format(temp.shape))
@@ -941,7 +942,7 @@ 
      Writing data
 along the level dimension of the variable temp, even though no
 data has yet been assigned to levels.
      
 
-
      >>> # now, assign data to levels dimension variable.
+
      >>> # now, assign data to levels dimension variable.
 >>> levels[:] =  [1000.,850.,700.,500.,300.,250.,200.,150.,100.,50.]
 
      
 
@@ -954,7 +955,7 @@ 
      Writing data
 allowed, and these indices work independently along each dimension (similar
 to the way vector subscripts work in fortran).  This means that
      
 
-
      >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
+
      >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
 (4, 4)
 
      
 
@@ -972,14 +973,14 @@ 
      Writing data
 
 
      For example,
      
 
-
      >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
+
      >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
 
      
 
 
      will extract time indices 0,2 and 4, pressure levels
 850, 500 and 200 hPa, all Northern Hemisphere latitudes and Eastern
 Hemisphere longitudes, resulting in a numpy array of shape  (3, 3, 36, 71).
      
 
-
      >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
+
      >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
 shape of fancy temp slice = (3, 3, 36, 71)
 
      
 
@@ -1012,7 +1013,7 @@ 
      Dealing with time coordinates
      
 provided by cftime to do just that.
 Here's an example of how they can be used:
      
 
-
      >>> # fill in times.
+
      >>> # fill in times.
 >>> from datetime import datetime, timedelta
 >>> from cftime import num2date, date2num
 >>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
@@ -1052,7 +1053,7 @@ 
      Reading data from a multi
 NETCDF4_CLASSIC format (NETCDF4 formatted multi-file
 datasets are not supported).
      
 
-
      >>> for nf in range(10):
+
      >>> for nf in range(10):
 ...     with Dataset("mftest%s.nc" % nf, "w", format="NETCDF4_CLASSIC") as f:
 ...         _ = f.createDimension("x",None)
 ...         x = f.createVariable("x","i",("x",))
@@ -1061,7 +1062,7 @@ 
      Reading data from a multi
 
 
      Now read all the files back in at once with MFDataset
      
 
-
      >>> from netCDF4 import MFDataset
+
      >>> from netCDF4 import MFDataset
 >>> f = MFDataset("mftest*nc")
 >>> print(f.variables["x"][:])
 [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
@@ -1078,9 +1079,9 @@ 
      Efficient compression of netC
 
 
      Data stored in netCDF 4 Variable objects can be compressed and
 decompressed on the fly. The parameters for the compression are
-determined by the zlib, complevel and shuffle keyword arguments
+determined by the compression, complevel and shuffle keyword arguments
 to the Dataset.createVariable method. To turn on
-compression, set zlib=True.  The complevel keyword regulates the
+compression, set compression=zlib.  The complevel keyword regulates the
 speed and efficiency of the compression (1 being fastest, but lowest
 compression ratio, 9 being slowest but best compression ratio). The
 default value of complevel is 4. Setting shuffle=False will turn
@@ -1100,7 +1101,7 @@ 
      Efficient compression of netC
 
 
      If your data only has a certain number of digits of precision (say for
 example, it is temperature data that was measured with a precision of
-0.1 degrees), you can dramatically improve zlib compression by
+0.1 degrees), you can dramatically improve compression by
 quantizing (or truncating) the data. There are two methods supplied for
 doing this.  You can use the least_significant_digit
 keyword argument to Dataset.createVariable to specify
@@ -1123,22 +1124,22 @@ 
      Efficient compression of netC
 
 
      In our example, try replacing the line
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
 
      
 
 
      with
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True)
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib')
 
      
 
 
      and then
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,least_significant_digit=3)
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',least_significant_digit=3)
 
      
 
 
      or with netcdf-c >= 4.8.2
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,significant_digits=4)
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',significant_digits=4)
 
      
 
 
      and see how much smaller the resulting files are.
      
@@ -1159,7 +1160,7 @@ 
      Beyond ho
 Since there is no native complex data type in netcdf, compound types are handy
 for storing numpy complex arrays.  Here's an example:
      
 
-
      >>> f = Dataset("complex.nc","w")
+
      >>> f = Dataset("complex.nc","w")
 >>> size = 3 # length of 1-d complex array
 >>> # create sample complex data.
 >>> datac = np.exp(1j*(1.+np.linspace(0, np.pi, size)))
@@ -1195,7 +1196,7 @@ 
      Beyond ho
 in a Python dictionary, just like variables and dimensions. As always, printing
 objects gives useful summary information in an interactive session:
      
 
-
      >>> print(f)
+
      >>> print(f)
 <class 'netCDF4._netCDF4.Dataset'>
 root group (NETCDF4 data model, file format HDF5):
     dimensions(sizes): x_dim(3)
@@ -1220,7 +1221,7 @@ 
      Variable-length (vlen) data types
      
 data type, use the Dataset.createVLType method
 method of a Dataset or Group instance.
      
 
-
      >>> f = Dataset("tst_vlen.nc","w")
+
      >>> f = Dataset("tst_vlen.nc","w")
 >>> vlen_t = f.createVLType(np.int32, "phony_vlen")
 
      
 
@@ -1230,7 +1231,7 @@ 
      Variable-length (vlen) data types
      
 but compound data types cannot.
 A new variable can then be created using this datatype.
      
 
-
      >>> x = f.createDimension("x",3)
+
      >>> x = f.createDimension("x",3)
 >>> y = f.createDimension("y",4)
 >>> vlvar = f.createVariable("phony_vlen_var", vlen_t, ("y","x"))
 
      
@@ -1243,7 +1244,7 @@ 
      Variable-length (vlen) data types
      
 In this case, they contain 1-D numpy int32 arrays of random length between
 1 and 10.
      
 
-
      >>> import random
+
      >>> import random
 >>> random.seed(54321)
 >>> data = np.empty(len(y)*len(x),object)
 >>> for n in range(len(y)*len(x)):
@@ -1283,7 +1284,7 @@ 
      Variable-length (vlen) data types
      
 with fixed length greater than 1) when calling the
 Dataset.createVariable method.
      
 
-
      >>> z = f.createDimension("z",10)
+
      >>> z = f.createDimension("z",10)
 >>> strvar = f.createVariable("strvar", str, "z")
 
      
 
@@ -1291,7 +1292,7 @@ 
      Variable-length (vlen) data types
      
 random lengths between 2 and 12 characters, and the data in the object
 array is assigned to the vlen string variable.
      
 
-
      >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
+
      >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
 >>> data = np.empty(10,"O")
 >>> for n in range(10):
 ...     stringlen = random.randint(2,12)
@@ -1330,7 +1331,7 @@ 
      Enum data type
      
 values and their names are used to define an Enum data type using
 Dataset.createEnumType.
      
 
-
      >>> nc = Dataset('clouds.nc','w')
+
      >>> nc = Dataset('clouds.nc','w')
 >>> # python dict with allowed values and their names.
 >>> enum_dict = {'Altocumulus': 7, 'Missing': 255,
 ... 'Stratus': 2, 'Clear': 0,
@@ -1348,7 +1349,7 @@ 
      Enum data type
      
 is made to write an integer value not associated with one of the
 specified names.
      
 
-
      >>> time = nc.createDimension('time',None)
+
      >>> time = nc.createDimension('time',None)
 >>> # create a 1d variable of type 'cloud_type'.
 >>> # The fill_value is set to the 'Missing' named value.
 >>> cloud_var = nc.createVariable('primary_cloud',cloud_type,'time',
@@ -1385,7 +1386,7 @@ 
      Parallel IO
      
 available. To use parallel IO, your program must be running in an MPI
 environment using mpi4py.
      
 
-
      >>> from mpi4py import MPI
+
      >>> from mpi4py import MPI
 >>> import numpy as np
 >>> from netCDF4 import Dataset
 >>> rank = MPI.COMM_WORLD.rank  # The process ID (integer 0-3 for 4-process run)
@@ -1397,7 +1398,7 @@ 
      Parallel IO
      
 when a new dataset is created or an existing dataset is opened,
 use the parallel keyword to enable parallel access.
      
 
-
      >>> nc = Dataset('parallel_test.nc','w',parallel=True)
+
      >>> nc = Dataset('parallel_test.nc','w',parallel=True)
 
      
 
 
      The optional comm keyword may be used to specify a particular
@@ -1405,7 +1406,7 @@ 
      Parallel IO
      
 can now write to the file indepedently.  In this example the process rank is
 written to a different variable index on each task
      
 
-
      >>> d = nc.createDimension('dim',4)
+
      >>> d = nc.createDimension('dim',4)
 >>> v = nc.createVariable('var', np.int64, 'dim')
 >>> v[rank] = rank
 >>> nc.close()
@@ -1472,7 +1473,7 @@ 
      Dealing with strings
      
 stringtochar is used to convert the numpy string array to an array of
 characters with one more dimension. For example,
      
 
-
      >>> from netCDF4 import stringtochar
+
      >>> from netCDF4 import stringtochar
 >>> nc = Dataset('stringtest.nc','w',format='NETCDF4_CLASSIC')
 >>> _ = nc.createDimension('nchars',3)
 >>> _ = nc.createDimension('nstrings',None)
@@ -1505,7 +1506,7 @@ 
      Dealing with strings
      
 character array dtype under the hood when creating the netcdf compound type.
 Here's an example:
      
 
-
      >>> nc = Dataset('compoundstring_example.nc','w')
+
      >>> nc = Dataset('compoundstring_example.nc','w')
 >>> dtype = np.dtype([('observation', 'f4'),
 ...                      ('station_name','S10')])
 >>> station_data_t = nc.createCompoundType(dtype,'station_data')
@@ -1550,7 +1551,7 @@ 
      In-memory (diskless) Datasets
      
 object representing the Dataset. Below are examples illustrating both
 approaches.
      
 
-
      >>> # create a diskless (in-memory) Dataset,
+
      >>> # create a diskless (in-memory) Dataset,
 >>> # and persist the file to disk when it is closed.
 >>> nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
 >>> d = nc.createDimension('x',None)
@@ -1612,7 +1613,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -1625,7 +1626,7 @@ 
      In-memory (diskless) Datasets
      
 
                         
      
             View Source
-            
      # init for netCDF4. package
+            
      # init for netCDF4. package
 # Docstring comes from extension module _netCDF4.
 from ._netCDF4 import *
 # Need explicit imports for names beginning with underscores
@@ -1651,7 +1652,7 @@ 
      In-memory (diskless) Datasets
      
         Dataset:
     
      
 
-        
+    
             
      A netCDF Dataset is a collection of dimensions, groups, variables and
 attributes. Together they describe the meaning of data and relations among
 data fields stored in a netCDF file. See Dataset.__init__ for more
@@ -1729,7 +1730,7 @@ 
      In-memory (diskless) Datasets
      
             Dataset()
     
      
 
-        
+    
             
      __init__(self, filename, mode="r", clobber=True, diskless=False,
 persist=False, keepweakref=False, memory=None, encoding=None,
 parallel=False, comm=None, info=None, format='NETCDF4')
      
@@ -1835,7 +1836,7 @@ 
      In-memory (diskless) Datasets
      
             filepath(unknown):
     
      
 
-        
+    
             
      filepath(self,encoding=None)
      
 
 
      Get the file system path (or the opendap URL) which was used to
@@ -1854,7 +1855,7 @@ 
      In-memory (diskless) Datasets
      
             close(unknown):
     
      
 
-        
+    
             
      close(self)
      
 
 
      Close the Dataset.
      
@@ -1870,7 +1871,7 @@ 
      In-memory (diskless) Datasets
      
             isopen(unknown):
     
      
 
-        
+    
             
      isopen(self)
      
 
 
      Is the Dataset open or closed?
      
@@ -1886,7 +1887,7 @@ 
      In-memory (diskless) Datasets
      
             sync(unknown):
     
      
 
-        
+    
             
      sync(self)
      
 
 
      Writes all buffered data in the Dataset to the disk file.
      
@@ -1902,7 +1903,7 @@ 
      In-memory (diskless) Datasets
      
             set_fill_on(unknown):
     
      
 
-        
+    
             
      set_fill_on(self)
      
 
 
      Sets the fill mode for a Dataset open for writing to on.
      
@@ -1926,7 +1927,7 @@ 
      In-memory (diskless) Datasets
      
             set_fill_off(unknown):
     
      
 
-        
+    
             
      set_fill_off(self)
      
 
 
      Sets the fill mode for a Dataset open for writing to off.
      
@@ -1946,7 +1947,7 @@ 
      In-memory (diskless) Datasets
      
             createDimension(unknown):
     
      
 
-        
+    
             
      createDimension(self, dimname, size=None)
      
 
 
      Creates a new dimension with the given dimname and size.
      
@@ -1970,7 +1971,7 @@ 
      In-memory (diskless) Datasets
      
             renameDimension(unknown):
     
      
 
-        
+    
             
      renameDimension(self, oldname, newname)
      
 
 
      rename a Dimension named oldname to newname.
      
@@ -1986,7 +1987,7 @@ 
      In-memory (diskless) Datasets
      
             createCompoundType(unknown):
     
      
 
-        
+    
             
      createCompoundType(self, datatype, datatype_name)
      
 
 
      Creates a new compound data type named datatype_name from the numpy
@@ -2011,7 +2012,7 @@ 
      In-memory (diskless) Datasets
      
             createVLType(unknown):
     
      
 
-        
+    
             
      createVLType(self, datatype, datatype_name)
      
 
 
      Creates a new VLEN data type named datatype_name from a numpy
@@ -2031,7 +2032,7 @@ 
      In-memory (diskless) Datasets
      
             createEnumType(unknown):
     
      
 
-        
+    
             
      createEnumType(self, datatype, datatype_name, enum_dict)
      
 
 
      Creates a new Enum data type named datatype_name from a numpy
@@ -2052,10 +2053,11 @@ 
      In-memory (diskless) Datasets
      
             createVariable(unknown):
     
      
 
-        
-            
      createVariable(self, varname, datatype, dimensions=(), zlib=False,
+    
+            
      createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False,
 complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None,
-endian='native', least_significant_digit=None, significant_digits=None, fill_value=None, chunk_cache=None)
      
+endian='native', least_significant_digit=None, significant_digits=None, quantize_mode='BitGroom',
+fill_value=None, chunk_cache=None)
      
 
 
      Creates a new variable with the given varname, datatype, and
 dimensions. If dimensions are not given, the variable is assumed to be
@@ -2087,11 +2089,17 @@ 
      In-memory (diskless) Datasets
      
 previously using Dataset.createDimension. The default value
 is an empty tuple, which means the variable is a scalar.
      
 
+
      If the optional keyword argument compression is set, the data will be
+compressed in the netCDF file using the specified compression algorithm.
+Currently only 'zlib' is supported. Default is None (no compression).
      
+
 
      If the optional keyword zlib is True, the data will be compressed in
-the netCDF file using gzip compression (default False).
      
+the netCDF file using zlib compression (default False).  The use of this option is 
+deprecated in favor of compression='zlib'.
      
 
-
      The optional keyword complevel is an integer between 1 and 9 describing
-the level of compression desired (default 4). Ignored if zlib=False.
      
+
      The optional keyword complevel is an integer between 0 and 9 describing
+the level of compression desired (default 4). Ignored if compression=None.
+A value of zero disables compression.
      
 
 
      If the optional keyword shuffle is True, the HDF5 shuffle filter
 will be applied before compressing the data (default True).  This
@@ -2125,17 +2133,17 @@ 
      In-memory (diskless) Datasets
      
 opposite format as the one used to create the file, there may be
 some performance advantage to be gained by setting the endian-ness.
      
 
-
      The zlib, complevel, shuffle, fletcher32, contiguous, chunksizes and endian
+
      The compression, zlib, complevel, shuffle, fletcher32, contiguous, chunksizes and endian
 keywords are silently ignored for netCDF 3 files that do not use HDF5.
      
 
 
      The optional keyword fill_value can be used to override the default
 netCDF _FillValue (the value that the variable gets filled with before
-any data is written to it, defaults given in the dict netCDF4.default_fillvals).
+any data is written to it, defaults given in the dict netCDF4.default_fillvals).
 If fill_value is set to False, then the variable is not pre-filled.
      
 
 
      If the optional keyword parameters least_significant_digit or significant_digits are
 specified, variable data will be truncated (quantized). In conjunction
-with zlib=True this produces 'lossy', but significantly more
+with compression='zlib' this produces 'lossy', but significantly more
 efficient compression. For example, if least_significant_digit=1,
 data will be quantized using numpy.around(scale*data)/scale, where
 scale = 2**bits, and bits is determined so that a precision of 0.1 is
@@ -2145,9 +2153,9 @@ 
      In-memory (diskless) Datasets
      
 in unpacked data that is a reliable value." Default is None, or no
 quantization, or 'lossless' compression.  If significant_digits=3
 then the data will be quantized so that three significant digits are retained, independent
-of the floating point exponent. If significant_digits is given as a negative
-number, then an alternate algorithm for quantization ('granular bitgrooming') is used
-that may result in better compression for typical geophysical datasets. 
+of the floating point exponent. The keyword argument quantize_mode controls
+the quantization algorithm (default 'BitGroom').  The alternate 'GranularBitRound'
+algorithm may result in better compression for typical geophysical datasets. 
 This significant_digits kwarg is only available  with netcdf-c >= 4.8.2, and 
 only works with NETCDF4 or NETCDF4_CLASSIC formatted files.
      
 
@@ -2197,7 +2205,7 @@ 
      In-memory (diskless) Datasets
      
             renameVariable(unknown):
     
      
 
-        
+    
             
      renameVariable(self, oldname, newname)
      
 
 
      rename a Variable named oldname to newname
      
@@ -2213,7 +2221,7 @@ 
      In-memory (diskless) Datasets
      
             createGroup(unknown):
     
      
 
-        
+    
             
      createGroup(self, groupname)
      
 
 
      Creates a new Group with the given groupname.
      
@@ -2239,7 +2247,7 @@ 
      In-memory (diskless) Datasets
      
             ncattrs(unknown):
     
      
 
-        
+    
             
      ncattrs(self)
      
 
 
      return netCDF global attribute names for this Dataset or Group in a list.
      
@@ -2255,7 +2263,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr(unknown):
     
      
 
-        
+    
             
      setncattr(self,name,value)
      
 
 
      set a netCDF dataset or group attribute using name,value pair.
@@ -2273,7 +2281,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr_string(unknown):
     
      
 
-        
+    
             
      setncattr_string(self,name,value)
      
 
 
      set a netCDF dataset or group string attribute using name,value pair.
@@ -2291,7 +2299,7 @@ 
      In-memory (diskless) Datasets
      
             setncatts(unknown):
     
      
 
-        
+    
             
      setncatts(self,attdict)
      
 
 
      set a bunch of netCDF dataset or group attributes at once using a python dictionary.
@@ -2310,7 +2318,7 @@ 
      In-memory (diskless) Datasets
      
             getncattr(unknown):
     
      
 
-        
+    
             
      getncattr(self,name)
      
 
 
      retrieve a netCDF dataset or group attribute.
@@ -2331,7 +2339,7 @@ 
      In-memory (diskless) Datasets
      
             delncattr(unknown):
     
      
 
-        
+    
             
      delncattr(self,name,value)
      
 
 
      delete a netCDF dataset or group attribute.  Use if you need to delete a
@@ -2349,7 +2357,7 @@ 
      In-memory (diskless) Datasets
      
             renameAttribute(unknown):
     
      
 
-        
+    
             
      renameAttribute(self, oldname, newname)
      
 
 
      rename a Dataset or Group attribute named oldname to newname.
      
@@ -2365,7 +2373,7 @@ 
      In-memory (diskless) Datasets
      
             renameGroup(unknown):
     
      
 
-        
+    
             
      renameGroup(self, oldname, newname)
      
 
 
      rename a Group named oldname to newname (requires netcdf >= 4.3.1).
      
@@ -2381,7 +2389,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_chartostring(unknown):
     
      
 
-        
+    
             
      set_auto_chartostring(self, True_or_False)
      
 
 
      Call Variable.set_auto_chartostring for all variables contained in this Dataset or
@@ -2406,7 +2414,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_maskandscale(unknown):
     
      
 
-        
+    
             
      set_auto_maskandscale(self, True_or_False)
      
 
 
      Call Variable.set_auto_maskandscale for all variables contained in this Dataset or
@@ -2429,7 +2437,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_mask(unknown):
     
      
 
-        
+    
             
      set_auto_mask(self, True_or_False)
      
 
 
      Call Variable.set_auto_mask for all variables contained in this Dataset or
@@ -2453,7 +2461,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_scale(unknown):
     
      
 
-        
+    
             
      set_auto_scale(self, True_or_False)
      
 
 
      Call Variable.set_auto_scale for all variables contained in this Dataset or
@@ -2476,7 +2484,7 @@ 
      In-memory (diskless) Datasets
      
             set_always_mask(unknown):
     
      
 
-        
+    
             
      set_always_mask(self, True_or_False)
      
 
 
      Call Variable.set_always_mask for all variables contained in
@@ -2504,7 +2512,7 @@ 
      In-memory (diskless) Datasets
      
             set_ncstring_attrs(unknown):
     
      
 
-        
+    
             
      set_ncstring_attrs(self, True_or_False)
      
 
 
      Call Variable.set_ncstring_attrs for all variables contained in
@@ -2529,7 +2537,7 @@ 
      In-memory (diskless) Datasets
      
             get_variables_by_attributes(unknown):
     
      
 
-        
+    
             
      get_variables_by_attribute(self, **kwargs)
      
 
 
      Returns a list of variables that match specific conditions.
      
@@ -2537,7 +2545,7 @@ 
      In-memory (diskless) Datasets
      
 
      Can pass in key=value parameters and variables are returned that
 contain all of the matches. For example,
      
 
-
      >>> # Get variables with x-axis attribute.
+
      >>> # Get variables with x-axis attribute.
 >>> vs = nc.get_variables_by_attributes(axis='X')
 >>> # Get variables with matching "standard_name" attribute
 >>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
@@ -2548,7 +2556,7 @@ 
      In-memory (diskless) Datasets
      
 the attribute value.  None is given as the attribute value when the
 attribute does not exist on the variable. For example,
      
 
-
      >>> # Get Axis variables
+
      >>> # Get Axis variables
 >>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
 >>> # Get variables that don't have an "axis" attribute
 >>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
@@ -2567,7 +2575,7 @@ 
      In-memory (diskless) Datasets
      
             fromcdl(unknown):
     
      
 
-        
+    
             
      fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')
      
 
 
      call ncgen via subprocess to create Dataset from CDL
@@ -2597,7 +2605,7 @@ 
      In-memory (diskless) Datasets
      
             tocdl(unknown):
     
      
 
-        
+    
             
      tocdl(self, coordvars=False, data=False, outfile=None)
      
 
 
      call ncdump via subprocess to create CDL
@@ -2616,9 +2624,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.Dataset' objects>
+        name
     
      
 
+    
             
      string name of Group instance
      
 
      
 
@@ -2627,109 +2636,121 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        groups = <attribute 'groups' of 'netCDF4._netCDF4.Dataset' objects>
+        groups
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Dataset' objects>
+        dimensions
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        variables = <attribute 'variables' of 'netCDF4._netCDF4.Dataset' objects>
+        variables
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        disk_format = <attribute 'disk_format' of 'netCDF4._netCDF4.Dataset' objects>
+        disk_format
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        path = <attribute 'path' of 'netCDF4._netCDF4.Dataset' objects>
+        path
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        parent = <attribute 'parent' of 'netCDF4._netCDF4.Dataset' objects>
+        parent
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        file_format = <attribute 'file_format' of 'netCDF4._netCDF4.Dataset' objects>
+        file_format
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        data_model = <attribute 'data_model' of 'netCDF4._netCDF4.Dataset' objects>
+        data_model
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        cmptypes = <attribute 'cmptypes' of 'netCDF4._netCDF4.Dataset' objects>
+        cmptypes
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        vltypes = <attribute 'vltypes' of 'netCDF4._netCDF4.Dataset' objects>
+        vltypes
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        enumtypes = <attribute 'enumtypes' of 'netCDF4._netCDF4.Dataset' objects>
+        enumtypes
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        keepweakref = <attribute 'keepweakref' of 'netCDF4._netCDF4.Dataset' objects>
+        keepweakref
     
      
 
     
+

      @@ -2742,7 +2763,7 @@

      In-memory (diskless) Datasets

      Variable:
      - +

      A netCDF Variable is used to read and write netCDF data. They are analogous to numpy array objects. See Variable.__init__ for more details.

      @@ -2788,16 +2809,20 @@

      In-memory (diskless) Datasets

      truncated to this decimal place when it is assigned to the Variable instance. If None, the data is not truncated.

      -

      significant_digits: New in version 1.6.0. Describes the number of significant +

      significant_digits: New in version 1.6.0. Describes the number of significant digits in the data the contains a reliable value. Data is truncated to retain this number of significant digits when it is assigned to the Variable instance. If None, the data is not truncated. -If specified as a negative number, an alternative quantization algorithm is used -that often produces better compression. Only available with netcdf-c >= 4.8.2, and only works with NETCDF4 or NETCDF4_CLASSIC formatted files. The number of significant digits used in the quantization of variable data can be -obtained using the Variable.significant_digits method.

      +obtained using the Variable.significant_digits method. Default None - +no quantization done.

      + +

      quantize_mode: New in version 1.6.0. Controls +the quantization algorithm (default 'BitGroom'). The alternate 'GranularBitRound' +algorithm may result in better compression for typical geophysical datasets. +Ignored if significant_digts not specified.

      __orthogonal_indexing__: Always True. Indicates to client code that the object supports 'orthogonal indexing', which means that slices @@ -2820,8 +2845,8 @@

      In-memory (diskless) Datasets

      Variable()
      - -

      __init__(self, group, name, datatype, dimensions=(), zlib=False, + +

      __init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None,fill_value=None,chunk_cache=None)

      @@ -2855,15 +2880,19 @@

      In-memory (diskless) Datasets

      (defined previously with createDimension). Default is an empty tuple which means the variable is a scalar (and therefore has no dimensions).

      +

      compression: compression algorithm to use. Default None. Currently +only 'zlib' is supported.

      +

      zlib: if True, data assigned to the Variable -instance is compressed on disk. Default False.

      +instance is compressed on disk. Default False. Deprecated - use +compression='zlib' instead.

      -

      complevel: the level of zlib compression to use (1 is the fastest, +

      complevel: the level of compression to use (1 is the fastest, but poorest compression, 9 is the slowest but best compression). Default 4. -Ignored if zlib=False.

      +Ignored if compression=None. A value of 0 disables compression.

      shuffle: if True, the HDF5 shuffle filter is applied -to improve compression. Default True. Ignored if zlib=False.

      +to improve compression. Default True. Ignored if compression=None.

      fletcher32: if True (default False), the Fletcher32 checksum algorithm is used for error detection.

      @@ -2893,30 +2922,33 @@

      In-memory (diskless) Datasets

      some performance advantage to be gained by setting the endian-ness. For netCDF 3 files (that don't use HDF5), only endian='native' is allowed.

      -

      The zlib, complevel, shuffle, fletcher32, contiguous and chunksizes +

      The compression, zlib, complevel, shuffle, fletcher32, contiguous and chunksizes keywords are silently ignored for netCDF 3 files that do not use HDF5.

      -

      least_significant_digit: If this or significant_digits are specified, +

      least_significant_digit: If this or significant_digits are specified, variable data will be truncated (quantized).
      -In conjunction with zlib=True this produces +In conjunction with compression='zlib' this produces 'lossy', but significantly more efficient compression. For example, if least_significant_digit=1, data will be quantized using around(scaledata)/scale, where scale = 2*bits, and bits is determined so that a precision of 0.1 is retained (in this case bits=4). Default is None, or no quantization.

      -

      significant_digits: New in version 1.6.0. +

      significant_digits: New in version 1.6.0. As described for least_significant_digit except the number of significant digits retained is prescribed independent -of the floating point exponent. If specified as a negative number, -an alternative quantization algorithm is used that often produces -better compression. Only available with netcdf-c >= 4.8.2.

      +of the floating point exponent. Default None - no quantization done.

      + +

      quantize_mode: New in version 1.6.0. Controls +the quantization algorithm (default 'BitGroom'). The alternate 'GranularBitRound' +algorithm may result in better compression for typical geophysical datasets. +Ignored if significant_digts not specified.

      fill_value: If specified, the default netCDF _FillValue (the value that the variable gets filled with before any data is written to it) is replaced with this value. If fill_value is set to False, then the variable is not pre-filled. The default netCDF fill values can be found -in the dictionary netCDF4.default_fillvals.

      +in the dictionary netCDF4.default_fillvals.

      chunk_cache: If specified, sets the chunk cache size for this variable. Persists as long as Dataset is open. Use set_var_chunk_cache to @@ -2937,7 +2969,7 @@

      In-memory (diskless) Datasets

      group(unknown):
      - +

      group(self)

      return the group that this Variable is a member of.

      @@ -2953,7 +2985,7 @@

      In-memory (diskless) Datasets

      ncattrs(unknown):
      - +

      ncattrs(self)

      return netCDF attribute names for this Variable in a list.

      @@ -2969,7 +3001,7 @@

      In-memory (diskless) Datasets

      setncattr(unknown):
      - +

      setncattr(self,name,value)

      set a netCDF variable attribute using name,value pair. Use if you need to set a @@ -2987,7 +3019,7 @@

      In-memory (diskless) Datasets

      setncattr_string(unknown):
      - +

      setncattr_string(self,name,value)

      set a netCDF variable string attribute using name,value pair. @@ -3006,7 +3038,7 @@

      In-memory (diskless) Datasets

      setncatts(unknown):
      - +

      setncatts(self,attdict)

      set a bunch of netCDF variable attributes at once using a python dictionary. @@ -3025,7 +3057,7 @@

      In-memory (diskless) Datasets

      getncattr(unknown):
      - +

      getncattr(self,name)

      retrieve a netCDF variable attribute. Use if you need to set a @@ -3046,7 +3078,7 @@

      In-memory (diskless) Datasets

      delncattr(unknown):
      - +

      delncattr(self,name,value)

      delete a netCDF variable attribute. Use if you need to delete a @@ -3064,7 +3096,7 @@

      In-memory (diskless) Datasets

      filters(unknown):
      - +

      filters(self)

      return dictionary containing HDF5 filter parameters.

      @@ -3072,20 +3104,19 @@

      In-memory (diskless) Datasets

      -
      -
      #   +
      +
      #   def - significant_digits(unknown): + quantization(unknown):
      - -

      significant_digits(self)

      + +

      quantization(self)

      -

      return number of significant digits used in quantization. -if returned value is negative, alternate quantization method -('granular bitgrooming') is used.

      +

      return number of significant digits and the algorithm used in quantization. +Returns None if quantization not active.

      @@ -3098,7 +3129,7 @@

      In-memory (diskless) Datasets

      endian(unknown):
      - +

      endian(self)

      return endian-ness (little,big,native) of variable (as stored in HDF5 file).

      @@ -3114,7 +3145,7 @@

      In-memory (diskless) Datasets

      chunking(unknown):
      - +

      chunking(self)

      return variable chunking information. If the dataset is @@ -3133,7 +3164,7 @@

      In-memory (diskless) Datasets

      get_var_chunk_cache(unknown):
      - +

      get_var_chunk_cache(self)

      return variable chunk cache information in a tuple (size,nelems,preemption). @@ -3151,7 +3182,7 @@

      In-memory (diskless) Datasets

      set_var_chunk_cache(unknown):
      - +

      set_var_chunk_cache(self,size=None,nelems=None,preemption=None)

      change variable chunk cache settings. @@ -3169,7 +3200,7 @@

      In-memory (diskless) Datasets

      renameAttribute(unknown):
      - +

      renameAttribute(self, oldname, newname)

      rename a Variable attribute named oldname to newname.

      @@ -3185,7 +3216,7 @@

      In-memory (diskless) Datasets

      assignValue(unknown):
      - +

      assignValue(self, val)

      assign a value to a scalar variable. Provided for compatibility with @@ -3202,7 +3233,7 @@

      In-memory (diskless) Datasets

      getValue(unknown):
      - +

      getValue(self)

      get the value of a scalar variable. Provided for compatibility with @@ -3219,7 +3250,7 @@

      In-memory (diskless) Datasets

      set_auto_chartostring(unknown):
      - +

      set_auto_chartostring(self,chartostring)

      turn on or off automatic conversion of character variable data to and @@ -3250,7 +3281,7 @@

      In-memory (diskless) Datasets

      use_nc_get_vars(unknown):
      - +

      use_nc_get_vars(self,_use_get_vars)

      enable the use of netcdf library routine nc_get_vars @@ -3270,7 +3301,7 @@

      In-memory (diskless) Datasets

      set_auto_maskandscale(unknown):
      - +

      set_auto_maskandscale(self,maskandscale)

      turn on or off automatic conversion of variable data to and @@ -3334,7 +3365,7 @@

      In-memory (diskless) Datasets

      set_auto_scale(unknown):
      - +

      set_auto_scale(self,scale)

      turn on or off automatic packing/unpacking of variable @@ -3383,7 +3414,7 @@

      In-memory (diskless) Datasets

      set_auto_mask(unknown):
      - +

      set_auto_mask(self,mask)

      turn on or off automatic conversion of variable data to and @@ -3418,7 +3449,7 @@

      In-memory (diskless) Datasets

      set_always_mask(unknown):
      - +

      set_always_mask(self,always_mask)

      turn on or off conversion of data without missing values to regular @@ -3441,7 +3472,7 @@

      In-memory (diskless) Datasets

      set_ncstring_attrs(unknown):
      - +

      set_always_mask(self,ncstring_attrs)

      turn on or off creating NC_STRING string attributes.

      @@ -3463,7 +3494,7 @@

      In-memory (diskless) Datasets

      set_collective(unknown):
      - +

      set_collective(self,True_or_False)

      turn on or off collective parallel IO access. Ignored if file is not @@ -3480,7 +3511,7 @@

      In-memory (diskless) Datasets

      get_dims(unknown):
      - +

      get_dims(self)

      return a tuple of Dimension instances associated with this @@ -3492,9 +3523,10 @@

      In-memory (diskless) Datasets

      #   - name = <attribute 'name' of 'netCDF4._netCDF4.Variable' objects> + name
      +

      string name of Variable instance

      @@ -3503,9 +3535,10 @@

      In-memory (diskless) Datasets

      #   - datatype = <attribute 'datatype' of 'netCDF4._netCDF4.Variable' objects> + datatype
      +

      numpy data type (for primitive data types) or VLType/CompoundType/EnumType instance (for compound, vlen or enum data types)

      @@ -3516,9 +3549,10 @@

      In-memory (diskless) Datasets

      #   - shape = <attribute 'shape' of 'netCDF4._netCDF4.Variable' objects> + shape
      +

      find current sizes of all variable dimensions

      @@ -3527,9 +3561,10 @@

      In-memory (diskless) Datasets

      #   - size = <attribute 'size' of 'netCDF4._netCDF4.Variable' objects> + size
      +

      Return the number of stored elements.

      @@ -3538,9 +3573,10 @@

      In-memory (diskless) Datasets

      #   - dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Variable' objects> + dimensions
      +

      get variables's dimension names

      @@ -3549,55 +3585,61 @@

      In-memory (diskless) Datasets

      #   - ndim = <attribute 'ndim' of 'netCDF4._netCDF4.Variable' objects> + ndim
      +
      #   - dtype = <attribute 'dtype' of 'netCDF4._netCDF4.Variable' objects> + dtype
      +
      #   - mask = <attribute 'mask' of 'netCDF4._netCDF4.Variable' objects> + mask
      +
      #   - scale = <attribute 'scale' of 'netCDF4._netCDF4.Variable' objects> + scale
      +
      #   - always_mask = <attribute 'always_mask' of 'netCDF4._netCDF4.Variable' objects> + always_mask
      +
      #   - chartostring = <attribute 'chartostring' of 'netCDF4._netCDF4.Variable' objects> + chartostring
      +
      @@ -3610,7 +3652,7 @@

      In-memory (diskless) Datasets

      Dimension:
      - +

      A netCDF Dimension is used to describe the coordinates of a Variable. See Dimension.__init__ for more details.

      @@ -3636,7 +3678,7 @@

      In-memory (diskless) Datasets

      Dimension()
      - +

      __init__(self, group, name, size=None)

      Dimension constructor.

      @@ -3662,7 +3704,7 @@

      In-memory (diskless) Datasets

      group(unknown):
      - +

      group(self)

      return the group that this Dimension is a member of.

      @@ -3678,7 +3720,7 @@

      In-memory (diskless) Datasets

      isunlimited(unknown):
      - +

      isunlimited(self)

      returns True if the Dimension instance is unlimited, False otherwise.

      @@ -3689,9 +3731,10 @@

      In-memory (diskless) Datasets

      #   - name = <attribute 'name' of 'netCDF4._netCDF4.Dimension' objects> + name
      +

      string name of Dimension instance

      @@ -3700,9 +3743,10 @@

      In-memory (diskless) Datasets

      #   - size = <attribute 'size' of 'netCDF4._netCDF4.Dimension' objects> + size
      +

      current size of Dimension (calls len on Dimension instance)

      @@ -3718,7 +3762,7 @@

      In-memory (diskless) Datasets

      Group(netCDF4.Dataset):
      - +

      Groups define a hierarchical namespace within a netCDF file. They are analogous to directories in a unix filesystem. Each Group behaves like a Dataset within a Dataset, and can contain it's own variables, @@ -3742,7 +3786,7 @@

      In-memory (diskless) Datasets

      Group()
      - +

      __init__(self, parent, name) Group constructor.

      @@ -3766,7 +3810,7 @@

      In-memory (diskless) Datasets

      close(unknown):
      - +

      close(self)

      overrides Dataset close method which does not apply to Group @@ -3836,7 +3880,7 @@

      Inherited Members
      MFDataset(netCDF4.Dataset):
      - +

      Class for reading multi-file netCDF Datasets, making variables spanning multiple files appear as if they were in one file. Datasets must be in NETCDF4_CLASSIC, NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET @@ -3846,7 +3890,7 @@

      Inherited Members

      Example usage (See MFDataset.__init__ for more details):

      -
      >>> import numpy as np
+
      >>> import numpy as np
 >>> # create a series of netCDF files with a variable sharing
 >>> # the same unlimited dimension.
 >>> for nf in range(10):
@@ -3873,7 +3917,7 @@ 
      Inherited Members
      
             MFDataset(files, check=False, aggdim=None, exclude=[], master_file=None)
     
      
 
-        
+    
             
      __init__(self, files, check=False, aggdim=None, exclude=[],
 master_file=None)
      
 
@@ -3918,7 +3962,7 @@ 
      Inherited Members
      
             ncattrs(self):
     
      
 
-        
+    
             
      ncattrs(self)
      
 
 
      return the netcdf attribute names from the master file.
      
@@ -3934,7 +3978,7 @@ 
      Inherited Members
      
             close(self):
     
      
 
-        
+    
             
      close(self)
      
 
 
      close all the open files.
      
@@ -4002,13 +4046,13 @@ 
      Inherited Members
      
         MFTime(netCDF4._netCDF4._Variable):
     
      
 
-        
+    
             
      Class providing an interface to a MFDataset time Variable by imposing a unique common
 time unit and/or calendar to all files.
      
 
 
      Example usage (See MFTime.__init__ for more details):
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> f1 = Dataset("mftest_1.nc","w", format="NETCDF4_CLASSIC")
 >>> f2 = Dataset("mftest_2.nc","w", format="NETCDF4_CLASSIC")
 >>> f1.createDimension("time",None)
@@ -4044,7 +4088,7 @@ 
      Inherited Members
      
             MFTime(time, units=None, calendar=None)
     
      
 
-        
+    
             
      __init__(self, time, units=None, calendar=None)
      
 
 
      Create a time Variable with units consistent across a multifile
@@ -4088,7 +4132,7 @@ 
      Inherited Members
      
         CompoundType:
     
      
 
-        
+    
             
      A CompoundType instance is used to describe a compound data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance.
@@ -4107,7 +4151,7 @@ 
      Inherited Members
      
             CompoundType()
     
      
 
-        
+    
             
      __init__(group, datatype, datatype_name)
      
 
 
      CompoundType constructor.
      
@@ -4136,28 +4180,31 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.CompoundType' objects>
+        dtype
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        dtype_view = <attribute 'dtype_view' of 'netCDF4._netCDF4.CompoundType' objects>
+        dtype_view
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.CompoundType' objects>
+        name
     
      
 
     
+    
 
                             
      
                 
@@ -4170,7 +4217,7 @@ 
      Inherited Members
      
         VLType:
     
      
 
-        
+    
             
      A VLType instance is used to describe a variable length (VLEN) data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance. See
@@ -4188,7 +4235,7 @@ 
      Inherited Members
      
             VLType()
     
      
 
-        
+    
             
      __init__(group, datatype, datatype_name)
      
 
 
      VLType constructor.
      
@@ -4211,19 +4258,21 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.VLType' objects>
+        dtype
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.VLType' objects>
+        name
     
      
 
     
+    
 
                             
      
                 
@@ -4235,7 +4284,7 @@ 
      Inherited Members
      
             date2num(unknown):
     
      
 
-        
+    
             
      date2num(dates, units, calendar=None, has_year_zero=None)
      
 
 
      Return numeric time values given datetime objects. The units
@@ -4295,7 +4344,7 @@ 
      Inherited Members
      
             num2date(unknown):
     
      
 
-        
+    
             
      num2date(times, units, calendar=u'standard', only_use_cftime_datetimes=True, only_use_python_datetimes=False, has_year_zero=None)
      
 
 
      Return datetime objects given numeric time values. The units
@@ -4367,7 +4416,7 @@ 
      Inherited Members
      
             date2index(unknown):
     
      
 
-        
+    
             
      date2index(dates, nctime, calendar=None, select=u'exact', has_year_zero=None)
      
 
 
      Return indices of a netCDF time variable corresponding to the given dates.
      
@@ -4421,7 +4470,7 @@ 
      Inherited Members
      
             stringtochar(unknown):
     
      
 
-        
+    
             
      stringtochar(a,encoding='utf-8')
      
 
 
      convert a string array to a character array with one extra dimension
      
@@ -4448,7 +4497,7 @@ 
      Inherited Members
      
             chartostring(unknown):
     
      
 
-        
+    
             
      chartostring(b,encoding='utf-8')
      
 
 
      convert a character array to a string array with one less dimension.
      
@@ -4475,7 +4524,7 @@ 
      Inherited Members
      
             stringtoarr(unknown):
     
      
 
-        
+    
             
      stringtoarr(a, NUMCHARS,dtype='S')
      
 
 
      convert a string to a character array of length NUMCHARS
      
@@ -4503,7 +4552,7 @@ 
      Inherited Members
      
             getlibversion(unknown):
     
      
 
-        
+    
             
      getlibversion()
      
 
 
      returns a string describing the version of the netcdf library
@@ -4521,7 +4570,7 @@ 
      Inherited Members
      
         EnumType:
     
      
 
-        
+    
             
      A EnumType instance is used to describe an Enum data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance. See
@@ -4539,7 +4588,7 @@ 
      Inherited Members
      
             EnumType()
     
      
 
-        
+    
             
      __init__(group, datatype, datatype_name, enum_dict)
      
 
 
      EnumType constructor.
      
@@ -4565,28 +4614,31 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.EnumType' objects>
+        dtype
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.EnumType' objects>
+        name
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        enum_dict = <attribute 'enum_dict' of 'netCDF4._netCDF4.EnumType' objects>
+        enum_dict
     
      
 
     
+    
 
                             
      
                 
@@ -4598,7 +4650,7 @@ 
      Inherited Members
      
             get_chunk_cache(unknown):
     
      
 
-        
+    
             
      get_chunk_cache()
      
 
 
      return current netCDF chunk cache information in a tuple (size,nelems,preemption).
@@ -4616,7 +4668,7 @@ 
      Inherited Members
      
             set_chunk_cache(unknown):
     
      
 
-        
+    
             
      set_chunk_cache(self,size=None,nelems=None,preemption=None)
      
 
 
      change netCDF4 chunk cache settings.

From 6c3a9502f0f9d5523102545bf344b5bc2e2bfeb9 Mon Sep 17 00:00:00 2001
From: Francesco Ballarin 
Date: Sat, 5 Mar 2022 09:42:35 +0100
Subject: [PATCH 0747/1504] Define MPI_Session for compatibility with current
 mpi4py main branch

---
 include/mpi-compat.h | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/include/mpi-compat.h b/include/mpi-compat.h
index 367c58a7d..9a604f851 100644
--- a/include/mpi-compat.h
+++ b/include/mpi-compat.h
@@ -11,4 +11,9 @@ typedef void *PyMPI_MPI_Message;
 #define MPI_Message PyMPI_MPI_Message
 #endif
 
+#if (MPI_VERSION < 4) && !defined(PyMPI_HAVE_MPI_Session)
+typedef void *PyMPI_MPI_Session;
+#define MPI_Session PyMPI_MPI_Session
+#endif
+
 #endif/*MPI_COMPAT_H*/

From 7b0b0ec5c2ce955105f49d8beb1e1309cb46af4b Mon Sep 17 00:00:00 2001
From: Francesco Ballarin 
Date: Sun, 6 Mar 2022 08:48:48 +0100
Subject: [PATCH 0748/1504] Oversubscribe openmpi run, as 4 cores are requested
 while GitHub actions offers 2 cores

---
 .github/workflows/miniconda.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index b32c63562..23e7e1fc4 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -78,7 +78,7 @@ jobs:
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" 
         which mpirun
         mpirun --version
-        mpirun -np 4 python mpi_example.py
+        mpirun -np 4 --oversubscribe python mpi_example.py
         if [ $? -ne 0 ] ; then
           echo "hdf5 mpi test failed!"
           exit 1

From c2bb9b9f0b3d7b3661f75d63acd901a20f8a2f75 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 7 Mar 2022 09:07:51 -0700
Subject: [PATCH 0749/1504] update

---
 Changelog | 1 +
 1 file changed, 1 insertion(+)

diff --git a/Changelog b/Changelog
index f1d24a7b7..fe9f8ef7e 100644
--- a/Changelog
+++ b/Changelog
@@ -16,6 +16,7 @@
  * issue warning instead of raising an exception if missing_value or
    _FillValue can't be cast to the variable type when creating a 
    masked array (issue #1152).  
+ * Define MPI_Session for compatibility with current mpi4py (PR #1156).
 
  version 1.5.8 (tag v1.5.8rel)
 ==============================

From d4add313072c65f860728c34e42cd0bbff1c5229 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 11 Mar 2022 07:52:00 -0700
Subject: [PATCH 0750/1504] add BitRound

---
 Changelog                |  2 +-
 include/netCDF4.pxi      |  1 +
 src/netCDF4/_netCDF4.pyx | 33 ++++++++++++++++++++++-----------
 3 files changed, 24 insertions(+), 12 deletions(-)

diff --git a/Changelog b/Changelog
index d857fe619..71c1c5ae1 100644
--- a/Changelog
+++ b/Changelog
@@ -2,7 +2,7 @@
 =================================
  * add support for new quantization functionality in netcdf-c 4.8.2 via "signficant_digits"
    and "quantize_mode" kwargs in Dataset.createVariable. Default quantization_mode is "BitGroom",
-   but alternate method "GranularBitRound" also supported.
+   but alternate methods "BitRound" and GranularBitRound" also supported.
  * opening a Dataset in append mode (mode = 'a' or 'r+') creates a Dataset
    if one does not already exist (similar to python open builtin).  Issue #1144.
    Added a mode='x' option (as in python open) which is the same as mode='w' with
diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index 7ff41d4b3..d26d4991c 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -697,6 +697,7 @@ IF HAS_QUANTIZATION_SUPPORT:
             NC_NOQUANTIZE
             NC_QUANTIZE_BITGROOM
             NC_QUANTIZE_GRANULARBR
+            NC_QUANTIZE_BITROUND
         int nc_def_var_quantize(int ncid, int varid, int quantize_mode, int nsd) 
         int nc_inq_var_quantize(int ncid, int varid, int *quantize_modep, int *nsdp) nogil
 
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 5aecad328..70f801c7c 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -675,7 +675,7 @@ precision of 0.1, then setting `least_significant_digit=1` will cause
 data the data to be quantized using `numpy.around(scale*data)/scale`, where
 scale = 2**bits, and bits is determined so that a precision of 0.1 is
 retained (in this case bits=4).  This is done at the python level and is
-not a part of the underlying C library.  Starting with netcdf-c version 4.8.2,
+not a part of the underlying C library.  Starting with netcdf-c version 4.9.0,
 a quantization capability is provided in the library.  This can be
 used via the `significant_digits` `Dataset.createVariable` kwarg (new in
 version 1.6.0).
@@ -704,7 +704,7 @@ and then
 >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',least_significant_digit=3)
 ```
 
-or with netcdf-c >= 4.8.2
+or with netcdf-c >= 4.9.0
 
 ```python
 >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',significant_digits=4)
@@ -2742,9 +2742,10 @@ in unpacked data that is a reliable value." Default is `None`, or no
 quantization, or 'lossless' compression.  If `significant_digits=3`
 then the data will be quantized so that three significant digits are retained, independent
 of the floating point exponent. The keyword argument `quantize_mode` controls
-the quantization algorithm (default 'BitGroom').  The alternate 'GranularBitRound'
+the quantization algorithm (default 'BitGroom', 'BitRound' and
+'GranularBitRound' also available).  The 'GranularBitRound'
 algorithm may result in better compression for typical geophysical datasets. 
-This `significant_digits` kwarg is only available  with netcdf-c >= 4.8.2, and 
+This `significant_digits` kwarg is only available  with netcdf-c >= 4.9.0, and 
 only works with `NETCDF4` or `NETCDF4_CLASSIC` formatted files.
 
 When creating variables in a `NETCDF4` or `NETCDF4_CLASSIC` formatted file,
@@ -3612,16 +3613,18 @@ instance. If `None`, the data is not truncated.
 digits in the data the contains a reliable value.  Data is
 truncated to retain this number of significant digits when it is assigned to the
 `Variable` instance. If `None`, the data is not truncated.
-Only available with netcdf-c >= 4.8.2,
+Only available with netcdf-c >= 4.9.0,
 and only works with `NETCDF4` or `NETCDF4_CLASSIC` formatted files.
 The number of significant digits used in the quantization of variable data can be
 obtained using the `Variable.significant_digits` method. Default `None` - 
 no quantization done.
 
 **`quantize_mode`**: New in version 1.6.0. Controls
-the quantization algorithm (default 'BitGroom').  The alternate 'GranularBitRound'
+the quantization algorithm (default 'BitGroom', 'BitRound' and
+'GranularBitRound' also available).  The 'GranularBitRound'
 algorithm may result in better compression for typical geophysical datasets. 
-Ignored if `significant_digts` not specified.
+Ignored if `significant_digits` not specified. If 'BitRound' is used, then
+`significant_digits` is interpreted as binary (not decimal) digits.
 
 **`__orthogonal_indexing__`**: Always `True`.  Indicates to client code
 that the object supports 'orthogonal indexing', which means that slices
@@ -3740,9 +3743,11 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         of the floating point exponent. Default `None` - no quantization done.
 
         **`quantize_mode`**: New in version 1.6.0. Controls
-        the quantization algorithm (default 'BitGroom').  The alternate 'GranularBitRound'
+        the quantization algorithm (default 'BitGroom', 'BitRound' and
+        'GranularBitRound' also available).  The 'GranularBitRound'
         algorithm may result in better compression for typical geophysical datasets. 
-        Ignored if `significant_digts` not specified.
+        Ignored if `significant_digts` not specified. If 'BitRound' is used, then
+        `significant_digits` is interpreted as binary (not decimal) digits.
 
         **`fill_value`**:  If specified, the default netCDF `_FillValue` (the
         value that the variable gets filled with before any data is written to it)
@@ -3977,14 +3982,17 @@ behavior is similar to Fortran or Matlab, but different than numpy.
                         elif quantize_mode == 'GranularBitRound':
                             ierr = nc_def_var_quantize(self._grpid,
                                     self._varid, NC_QUANTIZE_GRANULARBR, nsd)
+                        elif quantize_mode == 'BitRound':
+                            ierr = nc_def_var_quantize(self._grpid,
+                                    self._varid, NC_QUANTIZE_BITROUND, nsd)
                         else:
                             raise ValueError("unknown quantize_mode ('BitGroom and 'GranularBitRound' supported)") 
 
                 ELSE:
                     if significant_digits is not None:
                         msg = """
-significant_digits kwarg only works with netcdf-c >= 4.8.2.  To enable, install Cython, make sure you have
-version 4.8.2 or higher netcdf-c, and rebuild netcdf4-python. Otherwise, use least_significant_digit
+significant_digits kwarg only works with netcdf-c >= 4.9.0.  To enable, install Cython, make sure you have
+version 4.9.0 or higher netcdf-c, and rebuild netcdf4-python. Otherwise, use least_significant_digit
 kwarg for quantization."""
                         raise ValueError(msg)
                 if ierr != NC_NOERR:
@@ -4343,6 +4351,9 @@ Returns None if quantization not active.
                     if quantize_mode == NC_QUANTIZE_GRANULARBR:
                         sig_digits = nsd
                         quant_mode = 'GranularBitRound'
+                    elif quantize_mode == NC_QUANTIZE_BITROUND:
+                        sig_digits = nsd
+                        quant_mode = 'BitRound'
                     else:
                         sig_digits = nsd
                         quant_mode = 'BitGroom'

From 5bbe5f35288a94a4dbd3bb7746c07b4c3a7dc5e0 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 11 Mar 2022 18:18:21 -0700
Subject: [PATCH 0751/1504] update for BitRound

---
 test/tst_compression2.py | 16 ++++++++++++++--
 1 file changed, 14 insertions(+), 2 deletions(-)

diff --git a/test/tst_compression2.py b/test/tst_compression2.py
index 8b07adb5c..ffa6a7063 100644
--- a/test/tst_compression2.py
+++ b/test/tst_compression2.py
@@ -6,10 +6,11 @@
 import os, tempfile, unittest
 
 ndim = 100000
-nfiles = 6
+nfiles = 7
 files = [tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name for nfile in range(nfiles)]
 data_array = uniform(size=(ndim,))
 nsd = 3
+nsb = 10 # for BitRound, use significant bits (~3.32 sig digits)
 complevel = 6
 
 def write_netcdf(filename,zlib,significant_digits,data,dtype='f8',shuffle=False,\
@@ -41,6 +42,8 @@ def setUp(self):
         write_netcdf(self.files[4],True,nsd,data_array,shuffle=True)
         # compressed, lossy, with shuffle, and alternate quantization.
         write_netcdf(self.files[5],True,nsd,data_array,quantize_mode='GranularBitRound',shuffle=True)
+        # compressed, lossy, with shuffle, and alternate quantization.
+        write_netcdf(self.files[6],True,nsb,data_array,quantize_mode='BitRound',shuffle=True)
 
     def tearDown(self):
         # Remove the temporary files
@@ -89,11 +92,20 @@ def runTest(self):
         f = Dataset(self.files[5])
         size = os.stat(self.files[5]).st_size
         errmax = (np.abs(data_array-f.variables['data'][:])).max()
-        #print('compressed lossy with shuffle and alternate quantization = ',size,' max err = ',errmax)
+        print('compressed lossy with shuffle and alternate quantization = ',size,' max err = ',errmax)
         assert(f.variables['data'].quantization() == (nsd,'GranularBitRound'))
         assert(errmax < 1.e-3)
         assert(size < 0.24*uncompressed_size)
         f.close()
+        # check lossy compression with shuffle and alternate quantization
+        f = Dataset(self.files[6])
+        size = os.stat(self.files[6]).st_size
+        errmax = (np.abs(data_array-f.variables['data'][:])).max()
+        print('compressed lossy with shuffle and alternate quantization = ',size,' max err = ',errmax)
+        assert(f.variables['data'].quantization() == (nsd,'BitRound'))
+        assert(errmax < 1.e-3)
+        assert(size < 0.24*uncompressed_size)
+        f.close()
 
 if __name__ == '__main__':
     unittest.main()

From b9d0f80412bd697c75ab5edb45389a91058ce9c2 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 11 Mar 2022 18:23:54 -0700
Subject: [PATCH 0752/1504] update docstrings

---
 src/netCDF4/_netCDF4.pyx | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 70f801c7c..7b15750cc 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2744,8 +2744,8 @@ then the data will be quantized so that three significant digits are retained, i
 of the floating point exponent. The keyword argument `quantize_mode` controls
 the quantization algorithm (default 'BitGroom', 'BitRound' and
 'GranularBitRound' also available).  The 'GranularBitRound'
-algorithm may result in better compression for typical geophysical datasets. 
-This `significant_digits` kwarg is only available  with netcdf-c >= 4.9.0, and 
+algorithm may result in better compression for typical geophysical datasets.
+This `significant_digits` kwarg is only available  with netcdf-c >= 4.9.0, and
 only works with `NETCDF4` or `NETCDF4_CLASSIC` formatted files.
 
 When creating variables in a `NETCDF4` or `NETCDF4_CLASSIC` formatted file,
@@ -3986,7 +3986,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
                             ierr = nc_def_var_quantize(self._grpid,
                                     self._varid, NC_QUANTIZE_BITROUND, nsd)
                         else:
-                            raise ValueError("unknown quantize_mode ('BitGroom and 'GranularBitRound' supported)") 
+                            raise ValueError("unknown quantize_mode value")
 
                 ELSE:
                     if significant_digits is not None:
@@ -4352,7 +4352,7 @@ Returns None if quantization not active.
                         sig_digits = nsd
                         quant_mode = 'GranularBitRound'
                     elif quantize_mode == NC_QUANTIZE_BITROUND:
-                        sig_digits = nsd
+                        sig_digits = nsd # interpreted as bits, not decimal
                         quant_mode = 'BitRound'
                     else:
                         sig_digits = nsd

From 381dcf24c7be3a3f704f4c970e7d7f388b72ab49 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 2 Apr 2022 14:32:01 -0600
Subject: [PATCH 0753/1504] debug print to fix failing test

---
 test/tst_compression2.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/test/tst_compression2.py b/test/tst_compression2.py
index ffa6a7063..35d56ddf5 100644
--- a/test/tst_compression2.py
+++ b/test/tst_compression2.py
@@ -83,7 +83,7 @@ def runTest(self):
         f = Dataset(self.files[4])
         size = os.stat(self.files[4]).st_size
         errmax = (np.abs(data_array-f.variables['data'][:])).max()
-        #print('compressed lossy with shuffle and standard quantization = ',size,' max err = ',errmax)
+        print('compressed lossy with shuffle and standard quantization = ',size,' max err = ',errmax)
         assert(f.variables['data'].quantization() == (nsd,'BitGroom'))
         assert(errmax < 1.e-3)
         assert(size < 0.24*uncompressed_size)
@@ -102,6 +102,7 @@ def runTest(self):
         size = os.stat(self.files[6]).st_size
         errmax = (np.abs(data_array-f.variables['data'][:])).max()
         print('compressed lossy with shuffle and alternate quantization = ',size,' max err = ',errmax)
+        print(f.variables['data'].quantization())
         assert(f.variables['data'].quantization() == (nsd,'BitRound'))
         assert(errmax < 1.e-3)
         assert(size < 0.24*uncompressed_size)

From 274339dea95c2e988a61f4ee0e2a184cfaad94d2 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 2 Apr 2022 14:41:58 -0600
Subject: [PATCH 0754/1504] update

---
 .github/workflows/build_master.yml | 1 +
 src/netCDF4/_netCDF4.pyx           | 2 +-
 test/tst_compression2.py           | 2 +-
 3 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 69a818ba3..4c8ba1980 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -57,6 +57,7 @@ jobs:
         python checkversion.py
         # serial
         cd test
+        python tst_compression2.py
         python run_all.py
         # parallel
         cd ../examples
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 7b15750cc..09f037640 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3986,7 +3986,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
                             ierr = nc_def_var_quantize(self._grpid,
                                     self._varid, NC_QUANTIZE_BITROUND, nsd)
                         else:
-                            raise ValueError("unknown quantize_mode value")
+                            raise ValueError("'quantize_mode' keyword argument must be 'BitGroom','GranularBitRound' or 'BitRound', got '%s'" % quantize_mode)
 
                 ELSE:
                     if significant_digits is not None:
diff --git a/test/tst_compression2.py b/test/tst_compression2.py
index 35d56ddf5..3a6235ecb 100644
--- a/test/tst_compression2.py
+++ b/test/tst_compression2.py
@@ -101,8 +101,8 @@ def runTest(self):
         f = Dataset(self.files[6])
         size = os.stat(self.files[6]).st_size
         errmax = (np.abs(data_array-f.variables['data'][:])).max()
+        print('should be nsd,BitRound: ',f.variables['data'].quantization())
         print('compressed lossy with shuffle and alternate quantization = ',size,' max err = ',errmax)
-        print(f.variables['data'].quantization())
         assert(f.variables['data'].quantization() == (nsd,'BitRound'))
         assert(errmax < 1.e-3)
         assert(size < 0.24*uncompressed_size)

From 4dce96c5346301189bff1138b1d10eebe70a70f7 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 2 Apr 2022 17:18:46 -0600
Subject: [PATCH 0755/1504] fix failing test

---
 test/tst_compression2.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/test/tst_compression2.py b/test/tst_compression2.py
index 3a6235ecb..a7e4929b8 100644
--- a/test/tst_compression2.py
+++ b/test/tst_compression2.py
@@ -101,9 +101,8 @@ def runTest(self):
         f = Dataset(self.files[6])
         size = os.stat(self.files[6]).st_size
         errmax = (np.abs(data_array-f.variables['data'][:])).max()
-        print('should be nsd,BitRound: ',f.variables['data'].quantization())
         print('compressed lossy with shuffle and alternate quantization = ',size,' max err = ',errmax)
-        assert(f.variables['data'].quantization() == (nsd,'BitRound'))
+        assert(f.variables['data'].quantization() == (nsb,'BitRound'))
         assert(errmax < 1.e-3)
         assert(size < 0.24*uncompressed_size)
         f.close()

From 5221b1fc93833457ed2fdda1c3f8aff51f1a5ffe Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 2 Apr 2022 17:19:25 -0600
Subject: [PATCH 0756/1504] update

---
 .github/workflows/build_master.yml | 1 -
 1 file changed, 1 deletion(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 4c8ba1980..69a818ba3 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -57,7 +57,6 @@ jobs:
         python checkversion.py
         # serial
         cd test
-        python tst_compression2.py
         python run_all.py
         # parallel
         cd ../examples

From e08438b72ce18cae21e70f24c2416f04ee516f43 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 3 Apr 2022 20:36:07 -0600
Subject: [PATCH 0757/1504] preparing for v1.6.0 release

---
 Changelog | 4 ++--
 README.md | 8 ++++++++
 2 files changed, 10 insertions(+), 2 deletions(-)

diff --git a/Changelog b/Changelog
index f95f8edae..92968f30c 100644
--- a/Changelog
+++ b/Changelog
@@ -1,5 +1,5 @@
- version 1.6.0 (not yet released)
-=================================
+ version 1.6.0 (tag v1.6.0rel)
+==============================
  * add support for new quantization functionality in netcdf-c 4.8.2 via "signficant_digits"
    and "quantize_mode" kwargs in Dataset.createVariable. Default quantization_mode is "BitGroom",
    but alternate methods "BitRound" and GranularBitRound" also supported.
diff --git a/README.md b/README.md
index d6f31974f..c569dacc5 100644
--- a/README.md
+++ b/README.md
@@ -10,6 +10,14 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
+??/??/2022:  Version [1.6.0](https://pypi.python.org/pypi/netCDF4/1.6.0) released.  Support
+for quantization (bit-grooming and bit-rounding) functionality in netcdf-c 4.9.0 which can
+dramatically improve compression.  Dataset.createVariable now accepts dimension instances (instead
+of just dimension names). 'compression' kwarg added to Dataset.createVariable (in preparation for
+the available of new compression algorithms in netcdf-c (such as zstd).  Currently only 'zlib'
+supported.  Opening a Dataset in 'append' mode now creates one if it doesn't already exist (just
+like python open).
+
 10/31/2021:  Version [1.5.8](https://pypi.python.org/pypi/netCDF4/1.5.8) released. Fix Enum bug, add binary wheels for aarch64 and python 3.10.
 
 6/22/2021:  Version [1.5.7](https://pypi.python.org/pypi/netCDF4/1.5.7) released.

From e91599d20347e01e81c9c49dce0b92fb7029b846 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 3 Apr 2022 20:37:06 -0600
Subject: [PATCH 0758/1504] update

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index c569dacc5..487364adc 100644
--- a/README.md
+++ b/README.md
@@ -16,7 +16,7 @@ dramatically improve compression.  Dataset.createVariable now accepts dimension
 of just dimension names). 'compression' kwarg added to Dataset.createVariable (in preparation for
 the available of new compression algorithms in netcdf-c (such as zstd).  Currently only 'zlib'
 supported.  Opening a Dataset in 'append' mode now creates one if it doesn't already exist (just
-like python open).
+like python open). Working arm64 and universal2 wheels for Apple Silicon now available on pypi.
 
 10/31/2021:  Version [1.5.8](https://pypi.python.org/pypi/netCDF4/1.5.8) released. Fix Enum bug, add binary wheels for aarch64 and python 3.10.
 

From 890432c446f87510d2ec8ffa209e21832149122a Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 3 Apr 2022 20:42:20 -0600
Subject: [PATCH 0759/1504] update

---
 README.md | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 487364adc..c8eedd52b 100644
--- a/README.md
+++ b/README.md
@@ -14,8 +14,9 @@ For details on the latest updates, see the [Changelog](https://github.com/Unidat
 for quantization (bit-grooming and bit-rounding) functionality in netcdf-c 4.9.0 which can
 dramatically improve compression.  Dataset.createVariable now accepts dimension instances (instead
 of just dimension names). 'compression' kwarg added to Dataset.createVariable (in preparation for
-the available of new compression algorithms in netcdf-c (such as zstd).  Currently only 'zlib'
-supported.  Opening a Dataset in 'append' mode now creates one if it doesn't already exist (just
+the available of new compression algorithms, such as
+ [zstd](https://github.com/facebook/zstd), in netcdf-c).  Currently only 'zlib' supported.
+Opening a Dataset in 'append' mode now creates one if it doesn't already exist (just
 like python open). Working arm64 and universal2 wheels for Apple Silicon now available on pypi.
 
 10/31/2021:  Version [1.5.8](https://pypi.python.org/pypi/netCDF4/1.5.8) released. Fix Enum bug, add binary wheels for aarch64 and python 3.10.

From 216f7bf1e7d8f91f771e4e19fc5d1aa943fe1d09 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 3 Apr 2022 20:44:39 -0600
Subject: [PATCH 0760/1504] update

---
 README.md       |   2 +-
 docs/index.html | 526 ++++++++++++++++++++++--------------------------
 2 files changed, 238 insertions(+), 290 deletions(-)

diff --git a/README.md b/README.md
index c8eedd52b..b348c8f88 100644
--- a/README.md
+++ b/README.md
@@ -17,7 +17,7 @@ of just dimension names). 'compression' kwarg added to Dataset.createVariable (i
 the available of new compression algorithms, such as
  [zstd](https://github.com/facebook/zstd), in netcdf-c).  Currently only 'zlib' supported.
 Opening a Dataset in 'append' mode now creates one if it doesn't already exist (just
-like python open). Working arm64 and universal2 wheels for Apple Silicon now available on pypi.
+like python open). Working arm64 wheels for Apple M1 Silicon now available on pypi.
 
 10/31/2021:  Version [1.5.8](https://pypi.python.org/pypi/netCDF4/1.5.8) released. Fix Enum bug, add binary wheels for aarch64 and python 3.10.
 
diff --git a/docs/index.html b/docs/index.html
index 64f10938b..8213f510f 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -3,24 +3,24 @@
 
     
     
-    
+    
     netCDF4 API documentation
+    
 
-    
-    
-    
-    
-    
-    
-
-    
      
     
      
             
      
                     
      
@@ -475,7 +474,7 @@ 
      Introduction
      
 and should be familiar to users of that module.
      
 
 
      Most new features of netCDF 4 are implemented, such as multiple
-unlimited dimensions, groups and data compression.  All the new
+unlimited dimensions, groups and zlib data compression.  All the new
 numeric data types (such as 64 bit and unsigned integer types) are
 implemented. Compound (struct), variable length (vlen) and
 enumerated (enum) data types are supported, but not the opaque data type.
@@ -577,7 +576,7 @@ 
      Creating/Opening/Closing a netCDF
 
 
      Here's an example:
      
 
-
      >>> from netCDF4 import Dataset
+
      >>> from netCDF4 import Dataset
 >>> rootgrp = Dataset("test.nc", "w", format="NETCDF4")
 >>> print(rootgrp.data_model)
 NETCDF4
@@ -606,7 +605,7 @@ 
      Groups in a netCDF file
      
 NETCDF4 formatted files support Groups, if you try to create a Group
 in a netCDF 3 file you will get an error message.
      
 
-
      >>> rootgrp = Dataset("test.nc", "a")
+
      >>> rootgrp = Dataset("test.nc", "a")
 >>> fcstgrp = rootgrp.createGroup("forecasts")
 >>> analgrp = rootgrp.createGroup("analyses")
 >>> print(rootgrp.groups)
@@ -630,7 +629,7 @@ 
      Groups in a netCDF file
      
 that group.  To simplify the creation of nested groups, you can
 use a unix-like path as an argument to Dataset.createGroup.
      
 
-
      >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
+
      >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
 >>> fcstgrp2 = rootgrp.createGroup("/forecasts/model2")
 
      
 
@@ -644,7 +643,7 @@ 
      Groups in a netCDF file
      
 to walk the directory tree. Note that printing the Dataset or Group
 object yields summary information about it's contents.
      
 
-
      >>> def walktree(top):
+
      >>> def walktree(top):
 ...     yield top.groups.values()
 ...     for value in top.groups.values():
 ...         yield from walktree(value)
@@ -694,7 +693,7 @@ 
      Dimensions in a netCDF file
      
 dimension is a new netCDF 4 feature, in netCDF 3 files there may be only
 one, and it must be the first (leftmost) dimension of the variable.
      
 
-
      >>> level = rootgrp.createDimension("level", None)
+
      >>> level = rootgrp.createDimension("level", None)
 >>> time = rootgrp.createDimension("time", None)
 >>> lat = rootgrp.createDimension("lat", 73)
 >>> lon = rootgrp.createDimension("lon", 144)
@@ -702,7 +701,7 @@ 
      Dimensions in a netCDF file
      
 
 
      All of the Dimension instances are stored in a python dictionary.
      
 
-
      >>> print(rootgrp.dimensions)
+
      >>> print(rootgrp.dimensions)
 {'level': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0, 'time': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0, 'lat': <class 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 73, 'lon': <class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144}
 
      
 
@@ -711,7 +710,7 @@ 
      Dimensions in a netCDF file
      
 Dimension.isunlimited method of a Dimension instance
 be used to determine if the dimensions is unlimited, or appendable.
      
 
-
      >>> print(len(lon))
+
      >>> print(len(lon))
 144
 >>> print(lon.isunlimited())
 False
@@ -723,7 +722,7 @@ 
      Dimensions in a netCDF file
      
 provides useful summary info, including the name and length of the dimension,
 and whether it is unlimited.
      
 
-
      >>> for dimobj in rootgrp.dimensions.values():
+
      >>> for dimobj in rootgrp.dimensions.values():
 ...     print(dimobj)
 <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0
 <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0
@@ -768,7 +767,7 @@ 
      Variables in a netCDF file
      
 method returns an instance of the Variable class whose methods can be
 used later to access and set variable data and attributes.
      
 
-
      >>> times = rootgrp.createVariable("time","f8",("time",))
+
      >>> times = rootgrp.createVariable("time","f8",("time",))
 >>> levels = rootgrp.createVariable("level","i4",("level",))
 >>> latitudes = rootgrp.createVariable("lat","f4",("lat",))
 >>> longitudes = rootgrp.createVariable("lon","f4",("lon",))
@@ -780,7 +779,7 @@ 
      Variables in a netCDF file
      
 
      To get summary info on a Variable instance in an interactive session,
 just print it.
      
 
-
      >>> print(temp)
+
      >>> print(temp)
 <class 'netCDF4._netCDF4.Variable'>
 float32 temp(time, level, lat, lon)
     units: K
@@ -791,7 +790,7 @@ 
      Variables in a netCDF file
      
 
 
      You can use a path to create a Variable inside a hierarchy of groups.
      
 
-
      >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
+
      >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
 
      
 
 
      If the intermediate groups do not yet exist, they will be created.
      
@@ -799,7 +798,7 @@ 
      Variables in a netCDF file
      
 
      You can also query a Dataset or Group instance directly to obtain Group or
 Variable instances using paths.
      
 
-
      >>> print(rootgrp["/forecasts/model1"])  # a Group instance
+
      >>> print(rootgrp["/forecasts/model1"])  # a Group instance
 <class 'netCDF4._netCDF4.Group'>
 group /forecasts/model1:
     dimensions(sizes): 
@@ -817,7 +816,7 @@ 
      Variables in a netCDF file
      
 
      All of the variables in the Dataset or Group are stored in a
 Python dictionary, in the same way as the dimensions:
      
 
-
      >>> print(rootgrp.variables)
+
      >>> print(rootgrp.variables)
 {'time': <class 'netCDF4._netCDF4.Variable'>
 float64 time(time)
 unlimited dimensions: time
@@ -860,7 +859,7 @@ 
      Attributes in a netCDF file
      
 variables. Attributes can be strings, numbers or sequences. Returning to
 our example,
      
 
-
      >>> import time
+
      >>> import time
 >>> rootgrp.description = "bogus example script"
 >>> rootgrp.history = "Created " + time.ctime(time.time())
 >>> rootgrp.source = "netCDF4 python module tutorial"
@@ -878,7 +877,7 @@ 
      Attributes in a netCDF file
      
 built-in dir Python function will return a bunch of private methods
 and attributes that cannot (or should not) be modified by the user.
      
 
-
      >>> for name in rootgrp.ncattrs():
+
      >>> for name in rootgrp.ncattrs():
 ...     print("Global attr {} = {}".format(name, getattr(rootgrp, name)))
 Global attr description = bogus example script
 Global attr history = Created Mon Jul  8 14:19:41 2019
@@ -889,7 +888,7 @@ 
      Attributes in a netCDF file
      
 instance provides all the netCDF attribute name/value pairs in a python
 dictionary:
      
 
-
      >>> print(rootgrp.__dict__)
+
      >>> print(rootgrp.__dict__)
 {'description': 'bogus example script', 'history': 'Created Mon Jul  8 14:19:41 2019', 'source': 'netCDF4 python module tutorial'}
 
      
 
@@ -902,7 +901,7 @@ 
      Writing data
 
      Now that you have a netCDF Variable instance, how do you put data
 into it? You can just treat it like an array and assign data to a slice.
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> lats =  np.arange(-90,91,2.5)
 >>> lons =  np.arange(-180,180,2.5)
 >>> latitudes[:] = lats
@@ -922,7 +921,7 @@ 
      Writing data
 objects with unlimited dimensions will grow along those dimensions if you
 assign data outside the currently defined range of indices.
      
 
-
      >>> # append along two unlimited dimensions by assigning to slice.
+
      >>> # append along two unlimited dimensions by assigning to slice.
 >>> nlats = len(rootgrp.dimensions["lat"])
 >>> nlons = len(rootgrp.dimensions["lon"])
 >>> print("temp shape before adding data = {}".format(temp.shape))
@@ -942,7 +941,7 @@ 
      Writing data
 along the level dimension of the variable temp, even though no
 data has yet been assigned to levels.
      
 
-
      >>> # now, assign data to levels dimension variable.
+
      >>> # now, assign data to levels dimension variable.
 >>> levels[:] =  [1000.,850.,700.,500.,300.,250.,200.,150.,100.,50.]
 
      
 
@@ -955,7 +954,7 @@ 
      Writing data
 allowed, and these indices work independently along each dimension (similar
 to the way vector subscripts work in fortran).  This means that
      
 
-
      >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
+
      >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
 (4, 4)
 
      
 
@@ -973,14 +972,14 @@ 
      Writing data
 
 
      For example,
      
 
-
      >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
+
      >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
 
      
 
 
      will extract time indices 0,2 and 4, pressure levels
 850, 500 and 200 hPa, all Northern Hemisphere latitudes and Eastern
 Hemisphere longitudes, resulting in a numpy array of shape  (3, 3, 36, 71).
      
 
-
      >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
+
      >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
 shape of fancy temp slice = (3, 3, 36, 71)
 
      
 
@@ -1013,7 +1012,7 @@ 
      Dealing with time coordinates
      
 provided by cftime to do just that.
 Here's an example of how they can be used:
      
 
-
      >>> # fill in times.
+
      >>> # fill in times.
 >>> from datetime import datetime, timedelta
 >>> from cftime import num2date, date2num
 >>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
@@ -1053,7 +1052,7 @@ 
      Reading data from a multi
 NETCDF4_CLASSIC format (NETCDF4 formatted multi-file
 datasets are not supported).
      
 
-
      >>> for nf in range(10):
+
      >>> for nf in range(10):
 ...     with Dataset("mftest%s.nc" % nf, "w", format="NETCDF4_CLASSIC") as f:
 ...         _ = f.createDimension("x",None)
 ...         x = f.createVariable("x","i",("x",))
@@ -1062,7 +1061,7 @@ 
      Reading data from a multi
 
 
      Now read all the files back in at once with MFDataset
      
 
-
      >>> from netCDF4 import MFDataset
+
      >>> from netCDF4 import MFDataset
 >>> f = MFDataset("mftest*nc")
 >>> print(f.variables["x"][:])
 [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
@@ -1079,9 +1078,9 @@ 
      Efficient compression of netC
 
 
      Data stored in netCDF 4 Variable objects can be compressed and
 decompressed on the fly. The parameters for the compression are
-determined by the compression, complevel and shuffle keyword arguments
+determined by the zlib, complevel and shuffle keyword arguments
 to the Dataset.createVariable method. To turn on
-compression, set compression=zlib.  The complevel keyword regulates the
+compression, set zlib=True.  The complevel keyword regulates the
 speed and efficiency of the compression (1 being fastest, but lowest
 compression ratio, 9 being slowest but best compression ratio). The
 default value of complevel is 4. Setting shuffle=False will turn
@@ -1101,7 +1100,7 @@ 
      Efficient compression of netC
 
 
      If your data only has a certain number of digits of precision (say for
 example, it is temperature data that was measured with a precision of
-0.1 degrees), you can dramatically improve compression by
+0.1 degrees), you can dramatically improve zlib compression by
 quantizing (or truncating) the data. There are two methods supplied for
 doing this.  You can use the least_significant_digit
 keyword argument to Dataset.createVariable to specify
@@ -1124,22 +1123,22 @@ 
      Efficient compression of netC
 
 
      In our example, try replacing the line
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
 
      
 
 
      with
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib')
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True)
 
      
 
 
      and then
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',least_significant_digit=3)
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,least_significant_digit=3)
 
      
 
 
      or with netcdf-c >= 4.8.2
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',significant_digits=4)
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,significant_digits=4)
 
      
 
 
      and see how much smaller the resulting files are.
      
@@ -1160,7 +1159,7 @@ 
      Beyond ho
 Since there is no native complex data type in netcdf, compound types are handy
 for storing numpy complex arrays.  Here's an example:
      
 
-
      >>> f = Dataset("complex.nc","w")
+
      >>> f = Dataset("complex.nc","w")
 >>> size = 3 # length of 1-d complex array
 >>> # create sample complex data.
 >>> datac = np.exp(1j*(1.+np.linspace(0, np.pi, size)))
@@ -1196,7 +1195,7 @@ 
      Beyond ho
 in a Python dictionary, just like variables and dimensions. As always, printing
 objects gives useful summary information in an interactive session:
      
 
-
      >>> print(f)
+
      >>> print(f)
 <class 'netCDF4._netCDF4.Dataset'>
 root group (NETCDF4 data model, file format HDF5):
     dimensions(sizes): x_dim(3)
@@ -1221,7 +1220,7 @@ 
      Variable-length (vlen) data types
      
 data type, use the Dataset.createVLType method
 method of a Dataset or Group instance.
      
 
-
      >>> f = Dataset("tst_vlen.nc","w")
+
      >>> f = Dataset("tst_vlen.nc","w")
 >>> vlen_t = f.createVLType(np.int32, "phony_vlen")
 
      
 
@@ -1231,7 +1230,7 @@ 
      Variable-length (vlen) data types
      
 but compound data types cannot.
 A new variable can then be created using this datatype.
      
 
-
      >>> x = f.createDimension("x",3)
+
      >>> x = f.createDimension("x",3)
 >>> y = f.createDimension("y",4)
 >>> vlvar = f.createVariable("phony_vlen_var", vlen_t, ("y","x"))
 
      
@@ -1244,7 +1243,7 @@ 
      Variable-length (vlen) data types
      
 In this case, they contain 1-D numpy int32 arrays of random length between
 1 and 10.
      
 
-
      >>> import random
+
      >>> import random
 >>> random.seed(54321)
 >>> data = np.empty(len(y)*len(x),object)
 >>> for n in range(len(y)*len(x)):
@@ -1284,7 +1283,7 @@ 
      Variable-length (vlen) data types
      
 with fixed length greater than 1) when calling the
 Dataset.createVariable method.
      
 
-
      >>> z = f.createDimension("z",10)
+
      >>> z = f.createDimension("z",10)
 >>> strvar = f.createVariable("strvar", str, "z")
 
      
 
@@ -1292,7 +1291,7 @@ 
      Variable-length (vlen) data types
      
 random lengths between 2 and 12 characters, and the data in the object
 array is assigned to the vlen string variable.
      
 
-
      >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
+
      >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
 >>> data = np.empty(10,"O")
 >>> for n in range(10):
 ...     stringlen = random.randint(2,12)
@@ -1331,7 +1330,7 @@ 
      Enum data type
      
 values and their names are used to define an Enum data type using
 Dataset.createEnumType.
      
 
-
      >>> nc = Dataset('clouds.nc','w')
+
      >>> nc = Dataset('clouds.nc','w')
 >>> # python dict with allowed values and their names.
 >>> enum_dict = {'Altocumulus': 7, 'Missing': 255,
 ... 'Stratus': 2, 'Clear': 0,
@@ -1349,7 +1348,7 @@ 
      Enum data type
      
 is made to write an integer value not associated with one of the
 specified names.
      
 
-
      >>> time = nc.createDimension('time',None)
+
      >>> time = nc.createDimension('time',None)
 >>> # create a 1d variable of type 'cloud_type'.
 >>> # The fill_value is set to the 'Missing' named value.
 >>> cloud_var = nc.createVariable('primary_cloud',cloud_type,'time',
@@ -1386,7 +1385,7 @@ 
      Parallel IO
      
 available. To use parallel IO, your program must be running in an MPI
 environment using mpi4py.
      
 
-
      >>> from mpi4py import MPI
+
      >>> from mpi4py import MPI
 >>> import numpy as np
 >>> from netCDF4 import Dataset
 >>> rank = MPI.COMM_WORLD.rank  # The process ID (integer 0-3 for 4-process run)
@@ -1398,7 +1397,7 @@ 
      Parallel IO
      
 when a new dataset is created or an existing dataset is opened,
 use the parallel keyword to enable parallel access.
      
 
-
      >>> nc = Dataset('parallel_test.nc','w',parallel=True)
+
      >>> nc = Dataset('parallel_test.nc','w',parallel=True)
 
      
 
 
      The optional comm keyword may be used to specify a particular
@@ -1406,7 +1405,7 @@ 
      Parallel IO
      
 can now write to the file indepedently.  In this example the process rank is
 written to a different variable index on each task
      
 
-
      >>> d = nc.createDimension('dim',4)
+
      >>> d = nc.createDimension('dim',4)
 >>> v = nc.createVariable('var', np.int64, 'dim')
 >>> v[rank] = rank
 >>> nc.close()
@@ -1473,7 +1472,7 @@ 
      Dealing with strings
      
 stringtochar is used to convert the numpy string array to an array of
 characters with one more dimension. For example,
      
 
-
      >>> from netCDF4 import stringtochar
+
      >>> from netCDF4 import stringtochar
 >>> nc = Dataset('stringtest.nc','w',format='NETCDF4_CLASSIC')
 >>> _ = nc.createDimension('nchars',3)
 >>> _ = nc.createDimension('nstrings',None)
@@ -1506,7 +1505,7 @@ 
      Dealing with strings
      
 character array dtype under the hood when creating the netcdf compound type.
 Here's an example:
      
 
-
      >>> nc = Dataset('compoundstring_example.nc','w')
+
      >>> nc = Dataset('compoundstring_example.nc','w')
 >>> dtype = np.dtype([('observation', 'f4'),
 ...                      ('station_name','S10')])
 >>> station_data_t = nc.createCompoundType(dtype,'station_data')
@@ -1551,7 +1550,7 @@ 
      In-memory (diskless) Datasets
      
 object representing the Dataset. Below are examples illustrating both
 approaches.
      
 
-
      >>> # create a diskless (in-memory) Dataset,
+
      >>> # create a diskless (in-memory) Dataset,
 >>> # and persist the file to disk when it is closed.
 >>> nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
 >>> d = nc.createDimension('x',None)
@@ -1613,7 +1612,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -1626,7 +1625,7 @@ 
      In-memory (diskless) Datasets
      
 
                         
      
             View Source
-            
      # init for netCDF4. package
+            
      # init for netCDF4. package
 # Docstring comes from extension module _netCDF4.
 from ._netCDF4 import *
 # Need explicit imports for names beginning with underscores
@@ -1652,7 +1651,7 @@ 
      In-memory (diskless) Datasets
      
         Dataset:
     
      
 
-    
+        
             
      A netCDF Dataset is a collection of dimensions, groups, variables and
 attributes. Together they describe the meaning of data and relations among
 data fields stored in a netCDF file. See Dataset.__init__ for more
@@ -1730,7 +1729,7 @@ 
      In-memory (diskless) Datasets
      
             Dataset()
     
      
 
-    
+        
             
      __init__(self, filename, mode="r", clobber=True, diskless=False,
 persist=False, keepweakref=False, memory=None, encoding=None,
 parallel=False, comm=None, info=None, format='NETCDF4')
      
@@ -1836,7 +1835,7 @@ 
      In-memory (diskless) Datasets
      
             filepath(unknown):
     
      
 
-    
+        
             
      filepath(self,encoding=None)
      
 
 
      Get the file system path (or the opendap URL) which was used to
@@ -1855,7 +1854,7 @@ 
      In-memory (diskless) Datasets
      
             close(unknown):
     
      
 
-    
+        
             
      close(self)
      
 
 
      Close the Dataset.
      
@@ -1871,7 +1870,7 @@ 
      In-memory (diskless) Datasets
      
             isopen(unknown):
     
      
 
-    
+        
             
      isopen(self)
      
 
 
      Is the Dataset open or closed?
      
@@ -1887,7 +1886,7 @@ 
      In-memory (diskless) Datasets
      
             sync(unknown):
     
      
 
-    
+        
             
      sync(self)
      
 
 
      Writes all buffered data in the Dataset to the disk file.
      
@@ -1903,7 +1902,7 @@ 
      In-memory (diskless) Datasets
      
             set_fill_on(unknown):
     
      
 
-    
+        
             
      set_fill_on(self)
      
 
 
      Sets the fill mode for a Dataset open for writing to on.
      
@@ -1927,7 +1926,7 @@ 
      In-memory (diskless) Datasets
      
             set_fill_off(unknown):
     
      
 
-    
+        
             
      set_fill_off(self)
      
 
 
      Sets the fill mode for a Dataset open for writing to off.
      
@@ -1947,7 +1946,7 @@ 
      In-memory (diskless) Datasets
      
             createDimension(unknown):
     
      
 
-    
+        
             
      createDimension(self, dimname, size=None)
      
 
 
      Creates a new dimension with the given dimname and size.
      
@@ -1971,7 +1970,7 @@ 
      In-memory (diskless) Datasets
      
             renameDimension(unknown):
     
      
 
-    
+        
             
      renameDimension(self, oldname, newname)
      
 
 
      rename a Dimension named oldname to newname.
      
@@ -1987,7 +1986,7 @@ 
      In-memory (diskless) Datasets
      
             createCompoundType(unknown):
     
      
 
-    
+        
             
      createCompoundType(self, datatype, datatype_name)
      
 
 
      Creates a new compound data type named datatype_name from the numpy
@@ -2012,7 +2011,7 @@ 
      In-memory (diskless) Datasets
      
             createVLType(unknown):
     
      
 
-    
+        
             
      createVLType(self, datatype, datatype_name)
      
 
 
      Creates a new VLEN data type named datatype_name from a numpy
@@ -2032,7 +2031,7 @@ 
      In-memory (diskless) Datasets
      
             createEnumType(unknown):
     
      
 
-    
+        
             
      createEnumType(self, datatype, datatype_name, enum_dict)
      
 
 
      Creates a new Enum data type named datatype_name from a numpy
@@ -2053,11 +2052,10 @@ 
      In-memory (diskless) Datasets
      
             createVariable(unknown):
     
      
 
-    
-            
      createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False,
+        
+            
      createVariable(self, varname, datatype, dimensions=(), zlib=False,
 complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None,
-endian='native', least_significant_digit=None, significant_digits=None, quantize_mode='BitGroom',
-fill_value=None, chunk_cache=None)
      
+endian='native', least_significant_digit=None, significant_digits=None, fill_value=None, chunk_cache=None)
      
 
 
      Creates a new variable with the given varname, datatype, and
 dimensions. If dimensions are not given, the variable is assumed to be
@@ -2089,17 +2087,11 @@ 
      In-memory (diskless) Datasets
      
 previously using Dataset.createDimension. The default value
 is an empty tuple, which means the variable is a scalar.
      
 
-
      If the optional keyword argument compression is set, the data will be
-compressed in the netCDF file using the specified compression algorithm.
-Currently only 'zlib' is supported. Default is None (no compression).
      
-
 
      If the optional keyword zlib is True, the data will be compressed in
-the netCDF file using zlib compression (default False).  The use of this option is 
-deprecated in favor of compression='zlib'.
      
+the netCDF file using gzip compression (default False).
      
 
-
      The optional keyword complevel is an integer between 0 and 9 describing
-the level of compression desired (default 4). Ignored if compression=None.
-A value of zero disables compression.
      
+
      The optional keyword complevel is an integer between 1 and 9 describing
+the level of compression desired (default 4). Ignored if zlib=False.
      
 
 
      If the optional keyword shuffle is True, the HDF5 shuffle filter
 will be applied before compressing the data (default True).  This
@@ -2133,17 +2125,17 @@ 
      In-memory (diskless) Datasets
      
 opposite format as the one used to create the file, there may be
 some performance advantage to be gained by setting the endian-ness.
      
 
-
      The compression, zlib, complevel, shuffle, fletcher32, contiguous, chunksizes and endian
+
      The zlib, complevel, shuffle, fletcher32, contiguous, chunksizes and endian
 keywords are silently ignored for netCDF 3 files that do not use HDF5.
      
 
 
      The optional keyword fill_value can be used to override the default
 netCDF _FillValue (the value that the variable gets filled with before
-any data is written to it, defaults given in the dict netCDF4.default_fillvals).
+any data is written to it, defaults given in the dict netCDF4.default_fillvals).
 If fill_value is set to False, then the variable is not pre-filled.
      
 
 
      If the optional keyword parameters least_significant_digit or significant_digits are
 specified, variable data will be truncated (quantized). In conjunction
-with compression='zlib' this produces 'lossy', but significantly more
+with zlib=True this produces 'lossy', but significantly more
 efficient compression. For example, if least_significant_digit=1,
 data will be quantized using numpy.around(scale*data)/scale, where
 scale = 2**bits, and bits is determined so that a precision of 0.1 is
@@ -2153,9 +2145,9 @@ 
      In-memory (diskless) Datasets
      
 in unpacked data that is a reliable value." Default is None, or no
 quantization, or 'lossless' compression.  If significant_digits=3
 then the data will be quantized so that three significant digits are retained, independent
-of the floating point exponent. The keyword argument quantize_mode controls
-the quantization algorithm (default 'BitGroom').  The alternate 'GranularBitRound'
-algorithm may result in better compression for typical geophysical datasets. 
+of the floating point exponent. If significant_digits is given as a negative
+number, then an alternate algorithm for quantization ('granular bitgrooming') is used
+that may result in better compression for typical geophysical datasets. 
 This significant_digits kwarg is only available  with netcdf-c >= 4.8.2, and 
 only works with NETCDF4 or NETCDF4_CLASSIC formatted files.
      
 
@@ -2205,7 +2197,7 @@ 
      In-memory (diskless) Datasets
      
             renameVariable(unknown):
     
      
 
-    
+        
             
      renameVariable(self, oldname, newname)
      
 
 
      rename a Variable named oldname to newname
      
@@ -2221,7 +2213,7 @@ 
      In-memory (diskless) Datasets
      
             createGroup(unknown):
     
      
 
-    
+        
             
      createGroup(self, groupname)
      
 
 
      Creates a new Group with the given groupname.
      
@@ -2247,7 +2239,7 @@ 
      In-memory (diskless) Datasets
      
             ncattrs(unknown):
     
      
 
-    
+        
             
      ncattrs(self)
      
 
 
      return netCDF global attribute names for this Dataset or Group in a list.
      
@@ -2263,7 +2255,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr(unknown):
     
      
 
-    
+        
             
      setncattr(self,name,value)
      
 
 
      set a netCDF dataset or group attribute using name,value pair.
@@ -2281,7 +2273,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr_string(unknown):
     
      
 
-    
+        
             
      setncattr_string(self,name,value)
      
 
 
      set a netCDF dataset or group string attribute using name,value pair.
@@ -2299,7 +2291,7 @@ 
      In-memory (diskless) Datasets
      
             setncatts(unknown):
     
      
 
-    
+        
             
      setncatts(self,attdict)
      
 
 
      set a bunch of netCDF dataset or group attributes at once using a python dictionary.
@@ -2318,7 +2310,7 @@ 
      In-memory (diskless) Datasets
      
             getncattr(unknown):
     
      
 
-    
+        
             
      getncattr(self,name)
      
 
 
      retrieve a netCDF dataset or group attribute.
@@ -2339,7 +2331,7 @@ 
      In-memory (diskless) Datasets
      
             delncattr(unknown):
     
      
 
-    
+        
             
      delncattr(self,name,value)
      
 
 
      delete a netCDF dataset or group attribute.  Use if you need to delete a
@@ -2357,7 +2349,7 @@ 
      In-memory (diskless) Datasets
      
             renameAttribute(unknown):
     
      
 
-    
+        
             
      renameAttribute(self, oldname, newname)
      
 
 
      rename a Dataset or Group attribute named oldname to newname.
      
@@ -2373,7 +2365,7 @@ 
      In-memory (diskless) Datasets
      
             renameGroup(unknown):
     
      
 
-    
+        
             
      renameGroup(self, oldname, newname)
      
 
 
      rename a Group named oldname to newname (requires netcdf >= 4.3.1).
      
@@ -2389,7 +2381,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_chartostring(unknown):
     
      
 
-    
+        
             
      set_auto_chartostring(self, True_or_False)
      
 
 
      Call Variable.set_auto_chartostring for all variables contained in this Dataset or
@@ -2414,7 +2406,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_maskandscale(unknown):
     
      
 
-    
+        
             
      set_auto_maskandscale(self, True_or_False)
      
 
 
      Call Variable.set_auto_maskandscale for all variables contained in this Dataset or
@@ -2437,7 +2429,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_mask(unknown):
     
      
 
-    
+        
             
      set_auto_mask(self, True_or_False)
      
 
 
      Call Variable.set_auto_mask for all variables contained in this Dataset or
@@ -2461,7 +2453,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_scale(unknown):
     
      
 
-    
+        
             
      set_auto_scale(self, True_or_False)
      
 
 
      Call Variable.set_auto_scale for all variables contained in this Dataset or
@@ -2484,7 +2476,7 @@ 
      In-memory (diskless) Datasets
      
             set_always_mask(unknown):
     
      
 
-    
+        
             
      set_always_mask(self, True_or_False)
      
 
 
      Call Variable.set_always_mask for all variables contained in
@@ -2512,7 +2504,7 @@ 
      In-memory (diskless) Datasets
      
             set_ncstring_attrs(unknown):
     
      
 
-    
+        
             
      set_ncstring_attrs(self, True_or_False)
      
 
 
      Call Variable.set_ncstring_attrs for all variables contained in
@@ -2537,7 +2529,7 @@ 
      In-memory (diskless) Datasets
      
             get_variables_by_attributes(unknown):
     
      
 
-    
+        
             
      get_variables_by_attribute(self, **kwargs)
      
 
 
      Returns a list of variables that match specific conditions.
      
@@ -2545,7 +2537,7 @@ 
      In-memory (diskless) Datasets
      
 
      Can pass in key=value parameters and variables are returned that
 contain all of the matches. For example,
      
 
-
      >>> # Get variables with x-axis attribute.
+
      >>> # Get variables with x-axis attribute.
 >>> vs = nc.get_variables_by_attributes(axis='X')
 >>> # Get variables with matching "standard_name" attribute
 >>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
@@ -2556,7 +2548,7 @@ 
      In-memory (diskless) Datasets
      
 the attribute value.  None is given as the attribute value when the
 attribute does not exist on the variable. For example,
      
 
-
      >>> # Get Axis variables
+
      >>> # Get Axis variables
 >>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
 >>> # Get variables that don't have an "axis" attribute
 >>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
@@ -2575,7 +2567,7 @@ 
      In-memory (diskless) Datasets
      
             fromcdl(unknown):
     
      
 
-    
+        
             
      fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')
      
 
 
      call ncgen via subprocess to create Dataset from CDL
@@ -2605,7 +2597,7 @@ 
      In-memory (diskless) Datasets
      
             tocdl(unknown):
     
      
 
-    
+        
             
      tocdl(self, coordvars=False, data=False, outfile=None)
      
 
 
      call ncdump via subprocess to create CDL
@@ -2624,10 +2616,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        name
+        name = <attribute 'name' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
-    
             
      string name of Group instance
      
 
      
 
@@ -2636,121 +2627,109 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        groups
+        groups = <attribute 'groups' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        dimensions
+        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        variables
+        variables = <attribute 'variables' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        disk_format
+        disk_format = <attribute 'disk_format' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        path
+        path = <attribute 'path' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        parent
+        parent = <attribute 'parent' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        file_format
+        file_format = <attribute 'file_format' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        data_model
+        data_model = <attribute 'data_model' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        cmptypes
+        cmptypes = <attribute 'cmptypes' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        vltypes
+        vltypes = <attribute 'vltypes' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        enumtypes
+        enumtypes = <attribute 'enumtypes' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        keepweakref
+        keepweakref = <attribute 'keepweakref' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                 
      
@@ -2763,7 +2742,7 @@ 
      In-memory (diskless) Datasets
      
         Variable:
     
      
 
-    
+        
             
      A netCDF Variable is used to read and write netCDF data.  They are
 analogous to numpy array objects. See Variable.__init__ for more
 details.
      
@@ -2809,20 +2788,16 @@ 
      In-memory (diskless) Datasets
      
 truncated to this decimal place when it is assigned to the Variable
 instance. If None, the data is not truncated.
      
 
-
      significant_digits: New in version 1.6.0. Describes the number of significant
+
      significant_digits: New in version 1.6.0. Describes the number of significant
 digits in the data the contains a reliable value.  Data is
 truncated to retain this number of significant digits when it is assigned to the
 Variable instance. If None, the data is not truncated.
+If specified as a negative number, an alternative quantization algorithm is used
+that often produces better compression.
 Only available with netcdf-c >= 4.8.2,
 and only works with NETCDF4 or NETCDF4_CLASSIC formatted files.
 The number of significant digits used in the quantization of variable data can be
-obtained using the Variable.significant_digits method. Default None - 
-no quantization done.
      
-
-
      quantize_mode: New in version 1.6.0. Controls
-the quantization algorithm (default 'BitGroom').  The alternate 'GranularBitRound'
-algorithm may result in better compression for typical geophysical datasets. 
-Ignored if significant_digts not specified.
      
+obtained using the Variable.significant_digits method.
      
 
 
      __orthogonal_indexing__: Always True.  Indicates to client code
 that the object supports 'orthogonal indexing', which means that slices
@@ -2845,8 +2820,8 @@ 
      In-memory (diskless) Datasets
      
             Variable()
     
      
 
-    
-            
      __init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False,
+        
+            
      __init__(self, group, name, datatype, dimensions=(), zlib=False,
 complevel=4, shuffle=True, fletcher32=False, contiguous=False,
 chunksizes=None, endian='native',
 least_significant_digit=None,fill_value=None,chunk_cache=None)
      
@@ -2880,19 +2855,15 @@ 
      In-memory (diskless) Datasets
      
 (defined previously with createDimension). Default is an empty tuple
 which means the variable is a scalar (and therefore has no dimensions).
      
 
-
      compression: compression algorithm to use. Default None.  Currently
-only 'zlib' is supported.
      
-
 
      zlib: if True, data assigned to the Variable
-instance is compressed on disk. Default False. Deprecated - use
-compression='zlib' instead.
      
+instance is compressed on disk. Default False.
      
 
-
      complevel: the level of compression to use (1 is the fastest,
+
      complevel: the level of zlib compression to use (1 is the fastest,
 but poorest compression, 9 is the slowest but best compression). Default 4.
-Ignored if compression=None. A value of 0 disables compression.
      
+Ignored if zlib=False.
      
 
 
      shuffle: if True, the HDF5 shuffle filter is applied
-to improve compression. Default True. Ignored if compression=None.
      
+to improve compression. Default True. Ignored if zlib=False.
      
 
 
      fletcher32: if True (default False), the Fletcher32 checksum
 algorithm is used for error detection.
      
@@ -2922,33 +2893,30 @@ 
      In-memory (diskless) Datasets
      
 some performance advantage to be gained by setting the endian-ness.
 For netCDF 3 files (that don't use HDF5), only endian='native' is allowed.
      
 
-
      The compression, zlib, complevel, shuffle, fletcher32, contiguous and chunksizes
+
      The zlib, complevel, shuffle, fletcher32, contiguous and chunksizes
 keywords are silently ignored for netCDF 3 files that do not use HDF5.
      
 
-
      least_significant_digit: If this or significant_digits are specified, 
+
      least_significant_digit: If this or significant_digits are specified, 
 variable data will be truncated (quantized). 
      
-In conjunction with compression='zlib' this produces
+In conjunction with zlib=True this produces
 'lossy', but significantly more efficient compression. For example, if
 least_significant_digit=1, data will be quantized using
 around(scaledata)/scale, where scale = 2*bits, and bits is determined
 so that a precision of 0.1 is retained (in this case bits=4). Default is
 None, or no quantization.
      
 
-
      significant_digits: New in version 1.6.0. 
+
      significant_digits: New in version 1.6.0. 
 As described for least_significant_digit
 except the number of significant digits retained is prescribed independent
-of the floating point exponent. Default None - no quantization done.
      
-
-
      quantize_mode: New in version 1.6.0. Controls
-the quantization algorithm (default 'BitGroom').  The alternate 'GranularBitRound'
-algorithm may result in better compression for typical geophysical datasets. 
-Ignored if significant_digts not specified.
      
+of the floating point exponent.  If specified as a negative number,
+an alternative quantization algorithm is used that often produces
+better compression. Only available with netcdf-c >= 4.8.2.
      
 
 
      fill_value:  If specified, the default netCDF _FillValue (the
 value that the variable gets filled with before any data is written to it)
 is replaced with this value.  If fill_value is set to False, then
 the variable is not pre-filled. The default netCDF fill values can be found
-in the dictionary netCDF4.default_fillvals.
      
+in the dictionary netCDF4.default_fillvals.
      
 
 
      chunk_cache: If specified, sets the chunk cache size for this variable.
 Persists as long as Dataset is open. Use set_var_chunk_cache to 
@@ -2969,7 +2937,7 @@ 
      In-memory (diskless) Datasets
      
             group(unknown):
     
      
 
-    
+        
             
      group(self)
      
 
 
      return the group that this Variable is a member of.
      
@@ -2985,7 +2953,7 @@ 
      In-memory (diskless) Datasets
      
             ncattrs(unknown):
     
      
 
-    
+        
             
      ncattrs(self)
      
 
 
      return netCDF attribute names for this Variable in a list.
      
@@ -3001,7 +2969,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr(unknown):
     
      
 
-    
+        
             
      setncattr(self,name,value)
      
 
 
      set a netCDF variable attribute using name,value pair.  Use if you need to set a
@@ -3019,7 +2987,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr_string(unknown):
     
      
 
-    
+        
             
      setncattr_string(self,name,value)
      
 
 
      set a netCDF variable string attribute using name,value pair.
@@ -3038,7 +3006,7 @@ 
      In-memory (diskless) Datasets
      
             setncatts(unknown):
     
      
 
-    
+        
             
      setncatts(self,attdict)
      
 
 
      set a bunch of netCDF variable attributes at once using a python dictionary.
@@ -3057,7 +3025,7 @@ 
      In-memory (diskless) Datasets
      
             getncattr(unknown):
     
      
 
-    
+        
             
      getncattr(self,name)
      
 
 
      retrieve a netCDF variable attribute.  Use if you need to set a
@@ -3078,7 +3046,7 @@ 
      In-memory (diskless) Datasets
      
             delncattr(unknown):
     
      
 
-    
+        
             
      delncattr(self,name,value)
      
 
 
      delete a netCDF variable attribute.  Use if you need to delete a
@@ -3096,7 +3064,7 @@ 
      In-memory (diskless) Datasets
      
             filters(unknown):
     
      
 
-    
+        
             
      filters(self)
      
 
 
      return dictionary containing HDF5 filter parameters.
      
@@ -3104,19 +3072,20 @@ 
      In-memory (diskless) Datasets
      
 
 
                             
      
-                            
      
-                                        
      #  
+                            
      
+                                        
      #  
 
         
             def
-            quantization(unknown):
+            significant_digits(unknown):
     
      
 
-    
-            
      quantization(self)
      
+        
+            
      significant_digits(self)
      
 
-
      return number of significant digits and the algorithm used in quantization.
-Returns None if quantization not active.
      
+
      return number of significant digits used in quantization.
+if returned value is negative, alternate quantization method
+('granular bitgrooming') is used.
      
 
      
 
 
@@ -3129,7 +3098,7 @@ 
      In-memory (diskless) Datasets
      
             endian(unknown):
     
      
 
-    
+        
             
      endian(self)
      
 
 
      return endian-ness (little,big,native) of variable (as stored in HDF5 file).
      
@@ -3145,7 +3114,7 @@ 
      In-memory (diskless) Datasets
      
             chunking(unknown):
     
      
 
-    
+        
             
      chunking(self)
      
 
 
      return variable chunking information.  If the dataset is
@@ -3164,7 +3133,7 @@ 
      In-memory (diskless) Datasets
      
             get_var_chunk_cache(unknown):
     
      
 
-    
+        
             
      get_var_chunk_cache(self)
      
 
 
      return variable chunk cache information in a tuple (size,nelems,preemption).
@@ -3182,7 +3151,7 @@ 
      In-memory (diskless) Datasets
      
             set_var_chunk_cache(unknown):
     
      
 
-    
+        
             
      set_var_chunk_cache(self,size=None,nelems=None,preemption=None)
      
 
 
      change variable chunk cache settings.
@@ -3200,7 +3169,7 @@ 
      In-memory (diskless) Datasets
      
             renameAttribute(unknown):
     
      
 
-    
+        
             
      renameAttribute(self, oldname, newname)
      
 
 
      rename a Variable attribute named oldname to newname.
      
@@ -3216,7 +3185,7 @@ 
      In-memory (diskless) Datasets
      
             assignValue(unknown):
     
      
 
-    
+        
             
      assignValue(self, val)
      
 
 
      assign a value to a scalar variable.  Provided for compatibility with
@@ -3233,7 +3202,7 @@ 
      In-memory (diskless) Datasets
      
             getValue(unknown):
     
      
 
-    
+        
             
      getValue(self)
      
 
 
      get the value of a scalar variable.  Provided for compatibility with
@@ -3250,7 +3219,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_chartostring(unknown):
     
      
 
-    
+        
             
      set_auto_chartostring(self,chartostring)
      
 
 
      turn on or off automatic conversion of character variable data to and
@@ -3281,7 +3250,7 @@ 
      In-memory (diskless) Datasets
      
             use_nc_get_vars(unknown):
     
      
 
-    
+        
             
      use_nc_get_vars(self,_use_get_vars)
      
 
 
      enable the use of netcdf library routine nc_get_vars
@@ -3301,7 +3270,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_maskandscale(unknown):
     
      
 
-    
+        
             
      set_auto_maskandscale(self,maskandscale)
      
 
 
      turn on or off automatic conversion of variable data to and
@@ -3365,7 +3334,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_scale(unknown):
     
      
 
-    
+        
             
      set_auto_scale(self,scale)
      
 
 
      turn on or off automatic packing/unpacking of variable
@@ -3414,7 +3383,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_mask(unknown):
     
      
 
-    
+        
             
      set_auto_mask(self,mask)
      
 
 
      turn on or off automatic conversion of variable data to and
@@ -3449,7 +3418,7 @@ 
      In-memory (diskless) Datasets
      
             set_always_mask(unknown):
     
      
 
-    
+        
             
      set_always_mask(self,always_mask)
      
 
 
      turn on or off conversion of data without missing values to regular
@@ -3472,7 +3441,7 @@ 
      In-memory (diskless) Datasets
      
             set_ncstring_attrs(unknown):
     
      
 
-    
+        
             
      set_always_mask(self,ncstring_attrs)
      
 
 
      turn on or off creating NC_STRING string attributes.
      
@@ -3494,7 +3463,7 @@ 
      In-memory (diskless) Datasets
      
             set_collective(unknown):
     
      
 
-    
+        
             
      set_collective(self,True_or_False)
      
 
 
      turn on or off collective parallel IO access. Ignored if file is not
@@ -3511,7 +3480,7 @@ 
      In-memory (diskless) Datasets
      
             get_dims(unknown):
     
      
 
-    
+        
             
      get_dims(self)
      
 
 
      return a tuple of Dimension instances associated with this
@@ -3523,10 +3492,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        name
+        name = <attribute 'name' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
-    
             
      string name of Variable instance
      
 
      
 
@@ -3535,10 +3503,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        datatype
+        datatype = <attribute 'datatype' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
-    
             
      numpy data type (for primitive data types) or
 VLType/CompoundType/EnumType instance 
 (for compound, vlen  or enum data types)
      
@@ -3549,10 +3516,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        shape
+        shape = <attribute 'shape' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
-    
             
      find current sizes of all variable dimensions
      
 
      
 
@@ -3561,10 +3527,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        size
+        size = <attribute 'size' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
-    
             
      Return the number of stored elements.
      
 
      
 
@@ -3573,10 +3538,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        dimensions
+        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
-    
             
      get variables's dimension names
      
 
      
 
@@ -3585,61 +3549,55 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        ndim
+        ndim = <attribute 'ndim' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        dtype
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        mask
+        mask = <attribute 'mask' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        scale
+        scale = <attribute 'scale' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        always_mask
+        always_mask = <attribute 'always_mask' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        chartostring
+        chartostring = <attribute 'chartostring' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
     
-    
 
                             
      
                 
@@ -3652,7 +3610,7 @@ 
      In-memory (diskless) Datasets
      
         Dimension:
     
      
 
-    
+        
             
      A netCDF Dimension is used to describe the coordinates of a Variable.
 See Dimension.__init__ for more details.
      
 
@@ -3678,7 +3636,7 @@ 
      In-memory (diskless) Datasets
      
             Dimension()
     
      
 
-    
+        
             
      __init__(self, group, name, size=None)
      
 
 
      Dimension constructor.
      
@@ -3704,7 +3662,7 @@ 
      In-memory (diskless) Datasets
      
             group(unknown):
     
      
 
-    
+        
             
      group(self)
      
 
 
      return the group that this Dimension is a member of.
      
@@ -3720,7 +3678,7 @@ 
      In-memory (diskless) Datasets
      
             isunlimited(unknown):
     
      
 
-    
+        
             
      isunlimited(self)
      
 
 
      returns True if the Dimension instance is unlimited, False otherwise.
      
@@ -3731,10 +3689,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        name
+        name = <attribute 'name' of 'netCDF4._netCDF4.Dimension' objects>
     
      
 
-    
             
      string name of Dimension instance
      
 
      
 
@@ -3743,10 +3700,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        size
+        size = <attribute 'size' of 'netCDF4._netCDF4.Dimension' objects>
     
      
 
-    
             
      current size of Dimension (calls len on Dimension instance)
      
 
      
 
@@ -3762,7 +3718,7 @@ 
      In-memory (diskless) Datasets
      
         Group(netCDF4.Dataset):
     
      
 
-    
+        
             
      Groups define a hierarchical namespace within a netCDF file. They are
 analogous to directories in a unix filesystem. Each Group behaves like
 a Dataset within a Dataset, and can contain it's own variables,
@@ -3786,7 +3742,7 @@ 
      In-memory (diskless) Datasets
      
             Group()
     
      
 
-    
+        
             
      __init__(self, parent, name)
 Group constructor.
      
 
@@ -3810,7 +3766,7 @@ 
      In-memory (diskless) Datasets
      
             close(unknown):
     
      
 
-    
+        
             
      close(self)
      
 
 
      overrides Dataset close method which does not apply to Group
@@ -3880,7 +3836,7 @@ 
      Inherited Members
      
         MFDataset(netCDF4.Dataset):
     
      
 
-    
+        
             
      Class for reading multi-file netCDF Datasets, making variables
 spanning multiple files appear as if they were in one file.
 Datasets must be in NETCDF4_CLASSIC, NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET
@@ -3890,7 +3846,7 @@ 
      Inherited Members
      
 
 
      Example usage (See MFDataset.__init__ for more details):
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> # create a series of netCDF files with a variable sharing
 >>> # the same unlimited dimension.
 >>> for nf in range(10):
@@ -3917,7 +3873,7 @@ 
      Inherited Members
      
             MFDataset(files, check=False, aggdim=None, exclude=[], master_file=None)
     
      
 
-    
+        
             
      __init__(self, files, check=False, aggdim=None, exclude=[],
 master_file=None)
      
 
@@ -3962,7 +3918,7 @@ 
      Inherited Members
      
             ncattrs(self):
     
      
 
-    
+        
             
      ncattrs(self)
      
 
 
      return the netcdf attribute names from the master file.
      
@@ -3978,7 +3934,7 @@ 
      Inherited Members
      
             close(self):
     
      
 
-    
+        
             
      close(self)
      
 
 
      close all the open files.
      
@@ -4046,13 +4002,13 @@ 
      Inherited Members
      
         MFTime(netCDF4._netCDF4._Variable):
     
      
 
-    
+        
             
      Class providing an interface to a MFDataset time Variable by imposing a unique common
 time unit and/or calendar to all files.
      
 
 
      Example usage (See MFTime.__init__ for more details):
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> f1 = Dataset("mftest_1.nc","w", format="NETCDF4_CLASSIC")
 >>> f2 = Dataset("mftest_2.nc","w", format="NETCDF4_CLASSIC")
 >>> f1.createDimension("time",None)
@@ -4088,7 +4044,7 @@ 
      Inherited Members
      
             MFTime(time, units=None, calendar=None)
     
      
 
-    
+        
             
      __init__(self, time, units=None, calendar=None)
      
 
 
      Create a time Variable with units consistent across a multifile
@@ -4132,7 +4088,7 @@ 
      Inherited Members
      
         CompoundType:
     
      
 
-    
+        
             
      A CompoundType instance is used to describe a compound data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance.
@@ -4151,7 +4107,7 @@ 
      Inherited Members
      
             CompoundType()
     
      
 
-    
+        
             
      __init__(group, datatype, datatype_name)
      
 
 
      CompoundType constructor.
      
@@ -4180,31 +4136,28 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.CompoundType' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        dtype_view
+        dtype_view = <attribute 'dtype_view' of 'netCDF4._netCDF4.CompoundType' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        name
+        name = <attribute 'name' of 'netCDF4._netCDF4.CompoundType' objects>
     
      
 
     
-    
 
                             
      
                 
@@ -4217,7 +4170,7 @@ 
      Inherited Members
      
         VLType:
     
      
 
-    
+        
             
      A VLType instance is used to describe a variable length (VLEN) data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance. See
@@ -4235,7 +4188,7 @@ 
      Inherited Members
      
             VLType()
     
      
 
-    
+        
             
      __init__(group, datatype, datatype_name)
      
 
 
      VLType constructor.
      
@@ -4258,21 +4211,19 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.VLType' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        name
+        name = <attribute 'name' of 'netCDF4._netCDF4.VLType' objects>
     
      
 
     
-    
 
                             
      
                 
@@ -4284,7 +4235,7 @@ 
      Inherited Members
      
             date2num(unknown):
     
      
 
-    
+        
             
      date2num(dates, units, calendar=None, has_year_zero=None)
      
 
 
      Return numeric time values given datetime objects. The units
@@ -4344,7 +4295,7 @@ 
      Inherited Members
      
             num2date(unknown):
     
      
 
-    
+        
             
      num2date(times, units, calendar=u'standard', only_use_cftime_datetimes=True, only_use_python_datetimes=False, has_year_zero=None)
      
 
 
      Return datetime objects given numeric time values. The units
@@ -4416,7 +4367,7 @@ 
      Inherited Members
      
             date2index(unknown):
     
      
 
-    
+        
             
      date2index(dates, nctime, calendar=None, select=u'exact', has_year_zero=None)
      
 
 
      Return indices of a netCDF time variable corresponding to the given dates.
      
@@ -4470,7 +4421,7 @@ 
      Inherited Members
      
             stringtochar(unknown):
     
      
 
-    
+        
             
      stringtochar(a,encoding='utf-8')
      
 
 
      convert a string array to a character array with one extra dimension
      
@@ -4497,7 +4448,7 @@ 
      Inherited Members
      
             chartostring(unknown):
     
      
 
-    
+        
             
      chartostring(b,encoding='utf-8')
      
 
 
      convert a character array to a string array with one less dimension.
      
@@ -4524,7 +4475,7 @@ 
      Inherited Members
      
             stringtoarr(unknown):
     
      
 
-    
+        
             
      stringtoarr(a, NUMCHARS,dtype='S')
      
 
 
      convert a string to a character array of length NUMCHARS
      
@@ -4552,7 +4503,7 @@ 
      Inherited Members
      
             getlibversion(unknown):
     
      
 
-    
+        
             
      getlibversion()
      
 
 
      returns a string describing the version of the netcdf library
@@ -4570,7 +4521,7 @@ 
      Inherited Members
      
         EnumType:
     
      
 
-    
+        
             
      A EnumType instance is used to describe an Enum data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance. See
@@ -4588,7 +4539,7 @@ 
      Inherited Members
      
             EnumType()
     
      
 
-    
+        
             
      __init__(group, datatype, datatype_name, enum_dict)
      
 
 
      EnumType constructor.
      
@@ -4614,31 +4565,28 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.EnumType' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        name
+        name = <attribute 'name' of 'netCDF4._netCDF4.EnumType' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        enum_dict
+        enum_dict = <attribute 'enum_dict' of 'netCDF4._netCDF4.EnumType' objects>
     
      
 
     
-    
 
                             
      
                 
@@ -4650,7 +4598,7 @@ 
      Inherited Members
      
             get_chunk_cache(unknown):
     
      
 
-    
+        
             
      get_chunk_cache()
      
 
 
      return current netCDF chunk cache information in a tuple (size,nelems,preemption).
@@ -4668,7 +4616,7 @@ 
      Inherited Members
      
             set_chunk_cache(unknown):
     
      
 
-    
+        
             
      set_chunk_cache(self,size=None,nelems=None,preemption=None)
      
 
 
      change netCDF4 chunk cache settings.

From 7705c1ebaa6a868e31fa0b5991560349c2c10355 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 3 Apr 2022 20:51:34 -0600
Subject: [PATCH 0761/1504] update

---
 docs/index.html | 114 +++++++++++++++++++++++++++++-------------------
 1 file changed, 68 insertions(+), 46 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 8213f510f..3d402ea44 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -223,7 +223,7 @@ 
      API Documentation
      
                                 filters
                         
                         
    • 
-                                significant_digits
+                                quantization
                         
      • 
                         
    • 
                                 endian
@@ -474,7 +474,7 @@ 
      Introduction
      
 and should be familiar to users of that module.
      
 
 
      Most new features of netCDF 4 are implemented, such as multiple
-unlimited dimensions, groups and zlib data compression.  All the new
+unlimited dimensions, groups and data compression.  All the new
 numeric data types (such as 64 bit and unsigned integer types) are
 implemented. Compound (struct), variable length (vlen) and
 enumerated (enum) data types are supported, but not the opaque data type.
@@ -1078,9 +1078,9 @@ 
      Efficient compression of netC
 
 
      Data stored in netCDF 4 Variable objects can be compressed and
 decompressed on the fly. The parameters for the compression are
-determined by the zlib, complevel and shuffle keyword arguments
+determined by the compression, complevel and shuffle keyword arguments
 to the Dataset.createVariable method. To turn on
-compression, set zlib=True.  The complevel keyword regulates the
+compression, set compression=zlib.  The complevel keyword regulates the
 speed and efficiency of the compression (1 being fastest, but lowest
 compression ratio, 9 being slowest but best compression ratio). The
 default value of complevel is 4. Setting shuffle=False will turn
@@ -1100,7 +1100,7 @@ 
      Efficient compression of netC
 
 
      If your data only has a certain number of digits of precision (say for
 example, it is temperature data that was measured with a precision of
-0.1 degrees), you can dramatically improve zlib compression by
+0.1 degrees), you can dramatically improve compression by
 quantizing (or truncating) the data. There are two methods supplied for
 doing this.  You can use the least_significant_digit
 keyword argument to Dataset.createVariable to specify
@@ -1110,7 +1110,7 @@ 
      Efficient compression of netC
 data the data to be quantized using numpy.around(scale*data)/scale, where
 scale = 2**bits, and bits is determined so that a precision of 0.1 is
 retained (in this case bits=4).  This is done at the python level and is
-not a part of the underlying C library.  Starting with netcdf-c version 4.8.2,
+not a part of the underlying C library.  Starting with netcdf-c version 4.9.0,
 a quantization capability is provided in the library.  This can be
 used via the significant_digits Dataset.createVariable kwarg (new in
 version 1.6.0).
@@ -1128,17 +1128,17 @@ 
      Efficient compression of netC
 
 
      with
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True)
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib')
 
      
 
 
      and then
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,least_significant_digit=3)
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',least_significant_digit=3)
 
      
 
-
      or with netcdf-c >= 4.8.2
      
+
      or with netcdf-c >= 4.9.0
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),zlib=True,significant_digits=4)
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',significant_digits=4)
 
      
 
 
      and see how much smaller the resulting files are.
      
@@ -1612,7 +1612,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -2053,9 +2053,10 @@ 
      In-memory (diskless) Datasets
      
     
      
 
         
-            
      createVariable(self, varname, datatype, dimensions=(), zlib=False,
+            
      createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False,
 complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None,
-endian='native', least_significant_digit=None, significant_digits=None, fill_value=None, chunk_cache=None)
      
+endian='native', least_significant_digit=None, significant_digits=None, quantize_mode='BitGroom',
+fill_value=None, chunk_cache=None)
      
 
 
      Creates a new variable with the given varname, datatype, and
 dimensions. If dimensions are not given, the variable is assumed to be
@@ -2087,11 +2088,17 @@ 
      In-memory (diskless) Datasets
      
 previously using Dataset.createDimension. The default value
 is an empty tuple, which means the variable is a scalar.
      
 
+
      If the optional keyword argument compression is set, the data will be
+compressed in the netCDF file using the specified compression algorithm.
+Currently only 'zlib' is supported. Default is None (no compression).
      
+
 
      If the optional keyword zlib is True, the data will be compressed in
-the netCDF file using gzip compression (default False).
      
+the netCDF file using zlib compression (default False).  The use of this option is 
+deprecated in favor of compression='zlib'.
      
 
-
      The optional keyword complevel is an integer between 1 and 9 describing
-the level of compression desired (default 4). Ignored if zlib=False.
      
+
      The optional keyword complevel is an integer between 0 and 9 describing
+the level of compression desired (default 4). Ignored if compression=None.
+A value of zero disables compression.
      
 
 
      If the optional keyword shuffle is True, the HDF5 shuffle filter
 will be applied before compressing the data (default True).  This
@@ -2125,7 +2132,7 @@ 
      In-memory (diskless) Datasets
      
 opposite format as the one used to create the file, there may be
 some performance advantage to be gained by setting the endian-ness.
      
 
-
      The zlib, complevel, shuffle, fletcher32, contiguous, chunksizes and endian
+
      The compression, zlib, complevel, shuffle, fletcher32, contiguous, chunksizes and endian
 keywords are silently ignored for netCDF 3 files that do not use HDF5.
      
 
 
      The optional keyword fill_value can be used to override the default
@@ -2135,7 +2142,7 @@ 
      In-memory (diskless) Datasets
      
 
 
      If the optional keyword parameters least_significant_digit or significant_digits are
 specified, variable data will be truncated (quantized). In conjunction
-with zlib=True this produces 'lossy', but significantly more
+with compression='zlib' this produces 'lossy', but significantly more
 efficient compression. For example, if least_significant_digit=1,
 data will be quantized using numpy.around(scale*data)/scale, where
 scale = 2**bits, and bits is determined so that a precision of 0.1 is
@@ -2145,10 +2152,11 @@ 
      In-memory (diskless) Datasets
      
 in unpacked data that is a reliable value." Default is None, or no
 quantization, or 'lossless' compression.  If significant_digits=3
 then the data will be quantized so that three significant digits are retained, independent
-of the floating point exponent. If significant_digits is given as a negative
-number, then an alternate algorithm for quantization ('granular bitgrooming') is used
-that may result in better compression for typical geophysical datasets. 
-This significant_digits kwarg is only available  with netcdf-c >= 4.8.2, and 
+of the floating point exponent. The keyword argument quantize_mode controls
+the quantization algorithm (default 'BitGroom', 'BitRound' and
+'GranularBitRound' also available).  The 'GranularBitRound'
+algorithm may result in better compression for typical geophysical datasets.
+This significant_digits kwarg is only available  with netcdf-c >= 4.9.0, and
 only works with NETCDF4 or NETCDF4_CLASSIC formatted files.
      
 
 
      When creating variables in a NETCDF4 or NETCDF4_CLASSIC formatted file,
@@ -2788,16 +2796,22 @@ 
      In-memory (diskless) Datasets
      
 truncated to this decimal place when it is assigned to the Variable
 instance. If None, the data is not truncated.
      
 
-
      significant_digits: New in version 1.6.0. Describes the number of significant
+
      significant_digits: New in version 1.6.0. Describes the number of significant
 digits in the data the contains a reliable value.  Data is
 truncated to retain this number of significant digits when it is assigned to the
 Variable instance. If None, the data is not truncated.
-If specified as a negative number, an alternative quantization algorithm is used
-that often produces better compression.
-Only available with netcdf-c >= 4.8.2,
+Only available with netcdf-c >= 4.9.0,
 and only works with NETCDF4 or NETCDF4_CLASSIC formatted files.
 The number of significant digits used in the quantization of variable data can be
-obtained using the Variable.significant_digits method.
      
+obtained using the Variable.significant_digits method. Default None - 
+no quantization done.
      
+
+
      quantize_mode: New in version 1.6.0. Controls
+the quantization algorithm (default 'BitGroom', 'BitRound' and
+'GranularBitRound' also available).  The 'GranularBitRound'
+algorithm may result in better compression for typical geophysical datasets. 
+Ignored if significant_digits not specified. If 'BitRound' is used, then
+significant_digits is interpreted as binary (not decimal) digits.
      
 
 
      __orthogonal_indexing__: Always True.  Indicates to client code
 that the object supports 'orthogonal indexing', which means that slices
@@ -2821,7 +2835,7 @@ 
      In-memory (diskless) Datasets
      
     
      
 
         
-            
      __init__(self, group, name, datatype, dimensions=(), zlib=False,
+            
      __init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False,
 complevel=4, shuffle=True, fletcher32=False, contiguous=False,
 chunksizes=None, endian='native',
 least_significant_digit=None,fill_value=None,chunk_cache=None)
      
@@ -2855,15 +2869,19 @@ 
      In-memory (diskless) Datasets
      
 (defined previously with createDimension). Default is an empty tuple
 which means the variable is a scalar (and therefore has no dimensions).
      
 
+
      compression: compression algorithm to use. Default None.  Currently
+only 'zlib' is supported.
      
+
 
      zlib: if True, data assigned to the Variable
-instance is compressed on disk. Default False.
      
+instance is compressed on disk. Default False. Deprecated - use
+compression='zlib' instead.
      
 
-
      complevel: the level of zlib compression to use (1 is the fastest,
+
      complevel: the level of compression to use (1 is the fastest,
 but poorest compression, 9 is the slowest but best compression). Default 4.
-Ignored if zlib=False.
      
+Ignored if compression=None. A value of 0 disables compression.
      
 
 
      shuffle: if True, the HDF5 shuffle filter is applied
-to improve compression. Default True. Ignored if zlib=False.
      
+to improve compression. Default True. Ignored if compression=None.
      
 
 
      fletcher32: if True (default False), the Fletcher32 checksum
 algorithm is used for error detection.
      
@@ -2893,24 +2911,29 @@ 
      In-memory (diskless) Datasets
      
 some performance advantage to be gained by setting the endian-ness.
 For netCDF 3 files (that don't use HDF5), only endian='native' is allowed.
      
 
-
      The zlib, complevel, shuffle, fletcher32, contiguous and chunksizes
+
      The compression, zlib, complevel, shuffle, fletcher32, contiguous and chunksizes
 keywords are silently ignored for netCDF 3 files that do not use HDF5.
      
 
-
      least_significant_digit: If this or significant_digits are specified, 
+
      least_significant_digit: If this or significant_digits are specified, 
 variable data will be truncated (quantized). 
      
-In conjunction with zlib=True this produces
+In conjunction with compression='zlib' this produces
 'lossy', but significantly more efficient compression. For example, if
 least_significant_digit=1, data will be quantized using
 around(scaledata)/scale, where scale = 2*bits, and bits is determined
 so that a precision of 0.1 is retained (in this case bits=4). Default is
 None, or no quantization.
      
 
-
      significant_digits: New in version 1.6.0. 
+
      significant_digits: New in version 1.6.0. 
 As described for least_significant_digit
 except the number of significant digits retained is prescribed independent
-of the floating point exponent.  If specified as a negative number,
-an alternative quantization algorithm is used that often produces
-better compression. Only available with netcdf-c >= 4.8.2.
      
+of the floating point exponent. Default None - no quantization done.
      
+
+
      quantize_mode: New in version 1.6.0. Controls
+the quantization algorithm (default 'BitGroom', 'BitRound' and
+'GranularBitRound' also available).  The 'GranularBitRound'
+algorithm may result in better compression for typical geophysical datasets. 
+Ignored if significant_digts not specified. If 'BitRound' is used, then
+significant_digits is interpreted as binary (not decimal) digits.
      
 
 
      fill_value:  If specified, the default netCDF _FillValue (the
 value that the variable gets filled with before any data is written to it)
@@ -3072,20 +3095,19 @@ 
      In-memory (diskless) Datasets
      
 
 
                             
      
-                            
      
-                                        
      #  
+                            
      
+                                        
      #  
 
         
             def
-            significant_digits(unknown):
+            quantization(unknown):
     
      
 
         
-            
      significant_digits(self)
      
+            
      quantization(self)
      
 
-
      return number of significant digits used in quantization.
-if returned value is negative, alternate quantization method
-('granular bitgrooming') is used.
      
+
      return number of significant digits and the algorithm used in quantization.
+Returns None if quantization not active.
      
 
      
 
 

From 1e8101d7c5e704e38df752dd0e00fd65e70aa9e9 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 4 Apr 2022 08:20:51 -0600
Subject: [PATCH 0762/1504] remove -oversubscripe option (conda installs mpich
 now)

---
 .github/workflows/miniconda.yml | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 23e7e1fc4..2d27d3168 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -78,7 +78,8 @@ jobs:
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" 
         which mpirun
         mpirun --version
-        mpirun -np 4 --oversubscribe python mpi_example.py
+        #mpirun -np 4 --oversubscribe python mpi_example.py # for openmpi
+        mpirun -np 4 python mpi_example.py
         if [ $? -ne 0 ] ; then
           echo "hdf5 mpi test failed!"
           exit 1

From cb63f57c71db70b821c4868e91935ef2768dc251 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 23 Apr 2022 22:07:55 -0600
Subject: [PATCH 0763/1504] install bzip2, zstandard and blosc

---
 .github/workflows/build_master.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 69a818ba3..f36339695 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -23,7 +23,7 @@ jobs:
     - name: Install Ubuntu Dependencies
       run: |
         sudo apt-get update
-        sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev libcurl4-openssl-dev 
+        sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev libcurl4-openssl-dev bzip2 libblosc-dev zstd
         echo "Download and build netCDF github master"
         git clone https://github.com/Unidata/netcdf-c
         pushd netcdf-c

From b0a42465f309808984ace54d8bf3dcb85c343731 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 07:54:00 -0600
Subject: [PATCH 0764/1504] install libzstd-dev

---
 .github/workflows/build_master.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index f36339695..81c43b455 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -23,7 +23,7 @@ jobs:
     - name: Install Ubuntu Dependencies
       run: |
         sudo apt-get update
-        sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev libcurl4-openssl-dev bzip2 libblosc-dev zstd
+        sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev libcurl4-openssl-dev bzip2 libblosc-dev libzstd-dev
         echo "Download and build netCDF github master"
         git clone https://github.com/Unidata/netcdf-c
         pushd netcdf-c

From 5c6caa747dd2f95948f3ce5ed54c025d07ba2f8c Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 08:44:32 -0600
Subject: [PATCH 0765/1504] enable bzip2,zstd compression

---
 include/netCDF4.pxi      | 15 +++++++++++++
 setup.py                 | 46 +++++++++++++++++++++++++++++++++++++---
 src/netCDF4/_netCDF4.pyx | 44 +++++++++++++++++++++++++++-----------
 3 files changed, 90 insertions(+), 15 deletions(-)

diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index d26d4991c..c743218f6 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -701,6 +701,21 @@ IF HAS_QUANTIZATION_SUPPORT:
         int nc_def_var_quantize(int ncid, int varid, int quantize_mode, int nsd) 
         int nc_inq_var_quantize(int ncid, int varid, int *quantize_modep, int *nsdp) nogil
 
+IF HAS_ZSTANDARD_SUPPORT:
+    cdef extern from "netcdf_filter.h":
+        int nc_def_var_zstandard(int ncid, int varid, int level)
+        int nc_inq_var_zstandard(int ncid, int varid, int* hasfilterp, int *levelp)
+
+IF HAS_BZIP2_SUPPORT:
+    cdef extern from "netcdf_filter.h":
+        int nc_def_var_bzip2(int ncid, int varid, int level)
+        int nc_inq_var_bzip2(int ncid, int varid, int* hasfilterp, int *levelp)
+
+IF HAS_BLOSC_SUPPORT:
+    cdef extern from "netcdf_filter.h":
+        int nc_def_var_blosc(int ncid, int varid, unsigned subcompressor, unsigned level, unsigned blocksize, unsigned addshuffle)
+        int nc_inq_var_blosc(int ncid, int varid, int* hasfilterp, unsigned* subcompressorp, unsigned* levelp, unsigned* blocksizep, unsigned* addshufflep)
+
 IF HAS_NC_OPEN_MEM:
     cdef extern from "netcdf_mem.h":
         int nc_open_mem(const char *path, int mode, size_t size, void* memory, int *ncidp)
diff --git a/setup.py b/setup.py
index 76eceb455..5213af649 100644
--- a/setup.py
+++ b/setup.py
@@ -66,6 +66,9 @@ def check_api(inc_dirs,netcdf_lib_version):
     has_parallel4_support = False
     has_pnetcdf_support = False
     has_quantize = False
+    has_zstandard = False
+    has_bzip2 = False
+    has_blosc = False
 
     for d in inc_dirs:
         try:
@@ -74,6 +77,7 @@ def check_api(inc_dirs,netcdf_lib_version):
             continue
 
         has_nc_open_mem = os.path.exists(os.path.join(d, 'netcdf_mem.h'))
+        has_nc_filter = os.path.exists(os.path.join(d, 'netcdf_filter.h'))
 
         for line in f:
             if line.startswith('nc_rename_grp'):
@@ -96,6 +100,19 @@ def check_api(inc_dirs,netcdf_lib_version):
                 if line.startswith('EXTERNL int nc_create_mem'):
                     has_nc_create_mem = True
 
+        if has_nc_filter:
+            try:
+                f = open(os.path.join(d, 'netcdf_filter.h'), **open_kwargs)
+            except IOError:
+                continue
+            for line in f:
+                if line.startswith('EXTERNL int nc_def_var_zstandard'):
+                    has_zstandard = True
+                if line.startswith('EXTERNL int nc_def_var_bzip2'):
+                    has_bzip2 = True
+                if line.startswith('EXTERNL int nc_def_var_blosc'):
+                    has_blosc = True
+
         ncmetapath = os.path.join(d,'netcdf_meta.h')
         if os.path.exists(ncmetapath):
             for line in open(ncmetapath):
@@ -119,7 +136,8 @@ def check_api(inc_dirs,netcdf_lib_version):
 
     return has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \
            has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \
-           has_parallel4_support, has_pnetcdf_support, has_quantize
+           has_parallel4_support, has_pnetcdf_support, has_quantize, \
+           has_zstandard, has_bzip2, has_blosc
 
 
 def getnetcdfvers(libdirs):
@@ -532,7 +550,8 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     # this determines whether renameGroup and filepath methods will work.
     has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \
     has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \
-    has_parallel4_support, has_pnetcdf_support, has_quantize = \
+    has_parallel4_support, has_pnetcdf_support, has_quantize, \
+    has_zstandard, has_bzip2, has_blosc = \
     check_api(inc_dirs,netcdf_lib_version)
     # for netcdf 4.4.x CDF5 format is always enabled.
     if netcdf_lib_version is not None and\
@@ -608,9 +627,30 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         sys.stdout.write('netcdf lib has bit-grooming/quantization functions\n')
         f.write('DEF HAS_QUANTIZATION_SUPPORT = 1\n')
     else:
-        sys.stdout.write('netcdf lib does not bit-grooming/quantization functions\n')
+        sys.stdout.write('netcdf lib does not have bit-grooming/quantization functions\n')
         f.write('DEF HAS_QUANTIZATION_SUPPORT = 0\n')
 
+    if has_zstandard:
+        sys.stdout.write('netcdf lib has zstandard compression functions\n')
+        f.write('DEF HAS_ZSTANDARD_SUPPORT = 1\n')
+    else:
+        sys.stdout.write('netcdf lib does not have zstandard compression functions\n')
+        f.write('DEF HAS_ZSTANDARD_SUPPORT = 0\n')
+
+    if has_bzip2:
+        sys.stdout.write('netcdf lib has bzip2 compression functions\n')
+        f.write('DEF HAS_BZIP2_SUPPORT = 1\n')
+    else:
+        sys.stdout.write('netcdf lib does not have bzip2 compression functions\n')
+        f.write('DEF HAS_BZIP2_SUPPORT = 0\n')
+
+    if has_blosc:
+        sys.stdout.write('netcdf lib has blosc compression functions\n')
+        f.write('DEF HAS_BLOSC_SUPPORT = 1\n')
+    else:
+        sys.stdout.write('netcdf lib does not have blosc compression functions\n')
+        f.write('DEF HAS_BLOSC_SUPPORT = 0\n')
+
     f.close()
 
     if has_parallel4_support or has_pnetcdf_support:
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 09f037640..032fd9417 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2679,7 +2679,7 @@ is an empty tuple, which means the variable is a scalar.
 
 If the optional keyword argument `compression` is set, the data will be
 compressed in the netCDF file using the specified compression algorithm.
-Currently only 'zlib' is supported. Default is `None` (no compression).
+Currently 'zlib','zstd' and 'bzip2' are supported. Default is `None` (no compression).
 
 If the optional keyword `zlib` is `True`, the data will be compressed in
 the netCDF file using zlib compression (default `False`).  The use of this option is 
@@ -3684,7 +3684,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         which means the variable is a scalar (and therefore has no dimensions).
 
         **`compression`**: compression algorithm to use. Default None.  Currently
-        only 'zlib' is supported.
+        'zlib','zstd' and 'bzip2' are supported.
 
         **`zlib`**: if `True`, data assigned to the `Variable`
         instance is compressed on disk. Default `False`. Deprecated - use
@@ -3780,13 +3780,15 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         # if complevel is set to zero, turn off compression
         if not complevel:
             compression = None
-        # possible future options include 'zstd' and 'bzip2',
         zlib = False
-        #zstd = False
+        zstd = False
+        bzip2 = False
         if compression == 'zlib':
             zlib = True
-        #elif compression == 'zstd':
-        #    zstd = True
+        elif compression == 'zstd':
+            zstd = True
+        elif compression == 'bzip2':
+            bzip2 = True
         elif not compression:
             compression = None # if compression evaluates to False, set to None.
             pass
@@ -3924,12 +3926,30 @@ behavior is similar to Fortran or Matlab, but different than numpy.
                         if ierr != NC_NOERR:
                             if grp.data_model != 'NETCDF4': grp._enddef()
                             _ensure_nc_success(ierr)
-                    #if zstd:
-                    #    icomplevel = complevel
-                    #    ierr = nc_def_var_zstandard(self._grpid, self._varid, icomplevel)
-                    #    if ierr != NC_NOERR:
-                    #        if grp.data_model != 'NETCDF4': grp._enddef()
-                    #        _ensure_nc_success(ierr)
+                    if zstd:
+                        IF HAS_ZSTANDARD_SUPPORT:
+                            icomplevel = complevel
+                            ierr = nc_def_var_zstandard(self._grpid, self._varid, icomplevel)
+                            if ierr != NC_NOERR:
+                                if grp.data_model != 'NETCDF4': grp._enddef()
+                                _ensure_nc_success(ierr)
+                        ELSE:
+                            msg = """
+compression='zstd' only works with netcdf-c >= 4.9.0.  To enable, install Cython, make sure you have
+version 4.9.0 or higher netcdf-c with zstandard support, and rebuild netcdf4-python."""
+                        raise ValueError(msg)
+                    if bzip2:
+                        IF HAS_BZIP2_SUPPORT:
+                            icomplevel = complevel
+                            ierr = nc_def_var_bzip2(self._grpid, self._varid, icomplevel)
+                            if ierr != NC_NOERR:
+                                if grp.data_model != 'NETCDF4': grp._enddef()
+                                _ensure_nc_success(ierr)
+                        ELSE:
+                            msg = """
+compression='bzip2' only works with netcdf-c >= 4.9.0.  To enable, install Cython, make sure you have
+version 4.9.0 or higher netcdf-c with bzip2 support, and rebuild netcdf4-python."""
+                        raise ValueError(msg)
                 # set checksum.
                 if fletcher32 and ndims: # don't bother for scalar variable
                     ierr = nc_def_var_fletcher32(self._grpid, self._varid, 1)

From dd4de90c9b7f62c4c6d072854880d44d2ddafe6d Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 08:46:31 -0600
Subject: [PATCH 0766/1504] update

---
 Changelog | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/Changelog b/Changelog
index 92968f30c..d3cbac8b2 100644
--- a/Changelog
+++ b/Changelog
@@ -1,6 +1,6 @@
  version 1.6.0 (tag v1.6.0rel)
 ==============================
- * add support for new quantization functionality in netcdf-c 4.8.2 via "signficant_digits"
+ * add support for new quantization functionality in netcdf-c 4.9.0 via "signficant_digits"
    and "quantize_mode" kwargs in Dataset.createVariable. Default quantization_mode is "BitGroom",
    but alternate methods "BitRound" and GranularBitRound" also supported.
  * opening a Dataset in append mode (mode = 'a' or 'r+') creates a Dataset
@@ -11,10 +11,12 @@
    names in "dimensions" tuple kwarg (issue #1145).
  * remove all vestiges of python 2 in _netCDF4.pyx and set cython language_level
    directive to 3 in setup.py.
- * add 'compression' kwarg to createVariable.  Only 'None' and 'zlib' currently
+ * add 'compression' kwarg to createVariable to enable new compression
+   functionality in netcdf-c 4.9.0.  'None', 'zlib', 'zstd' and 'bzip2 are currently
    allowed (compression='zlib' is equivalent to zlib=True), but allows
    for new compression algorithms to be added when they become available
-   in netcdf-c. The 'zlib' kwarg is now deprecated.
+   in netcdf-c. The 'zlib' kwarg is now deprecated. Blosc compression feature
+   in netcdf-c 4.9.0 not yet supported.
  * MFDataset did not aggregate 'name' variable attribute (issue #1153).
  * issue warning instead of raising an exception if missing_value or
    _FillValue can't be cast to the variable type when creating a 

From 8732ca901489c2beaa83f14eca4d5bfbaa9f329b Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 13:01:42 -0600
Subject: [PATCH 0767/1504] update

---
 include/netCDF4.pxi      | 5 +++++
 src/netCDF4/__init__.py  | 4 +++-
 src/netCDF4/_netCDF4.pyx | 2 ++
 3 files changed, 10 insertions(+), 1 deletion(-)

diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index c743218f6..a5ff730be 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -703,11 +703,16 @@ IF HAS_QUANTIZATION_SUPPORT:
 
 IF HAS_ZSTANDARD_SUPPORT:
     cdef extern from "netcdf_filter.h":
+        cdef enum:
+            H5Z_FILTER_ZSTANDARD
         int nc_def_var_zstandard(int ncid, int varid, int level)
         int nc_inq_var_zstandard(int ncid, int varid, int* hasfilterp, int *levelp)
+        int nc_inq_filter_avail(int ncid, unsigned id)
 
 IF HAS_BZIP2_SUPPORT:
     cdef extern from "netcdf_filter.h":
+        cdef enum:
+            H5Z_FILTER_BZIP2
         int nc_def_var_bzip2(int ncid, int varid, int level)
         int nc_inq_var_bzip2(int ncid, int varid, int* hasfilterp, int *levelp)
 
diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py
index 4888e7c26..f9fe6a736 100644
--- a/src/netCDF4/__init__.py
+++ b/src/netCDF4/__init__.py
@@ -7,6 +7,8 @@
                        __has_rename_grp__, __has_nc_inq_path__,
                        __has_nc_inq_format_extended__, __has_nc_open_mem__,
                        __has_nc_create_mem__, __has_cdf5_format__,
-                       __has_parallel4_support__, __has_pnetcdf_support__,__has_quantization_support__)
+                       __has_parallel4_support__, __has_pnetcdf_support__,
+                       __has_quantization_support__, __has_zstandard_support__,
+                       __has_bzip2_support__)
 __all__ =\
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 032fd9417..ec2570de9 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1321,6 +1321,8 @@ __has_nc_create_mem__ = HAS_NC_CREATE_MEM
 __has_parallel4_support__ = HAS_PARALLEL4_SUPPORT
 __has_pnetcdf_support__ = HAS_PNETCDF_SUPPORT
 __has_quantization_support__ = HAS_QUANTIZATION_SUPPORT
+__has_zstandard_support__ = HAS_ZSTANDARD_SUPPORT
+__has_bzip2_support__ = HAS_BZIP2_SUPPORT
 _needsworkaround_issue485 = __netcdf4libversion__ < "4.4.0" or \
                (__netcdf4libversion__.startswith("4.4.0") and \
                 "-development" in __netcdf4libversion__)

From 8506b4fad7ebdbed21c0ed3b2bafffb49df8e16f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 13:30:59 -0600
Subject: [PATCH 0768/1504] update filters method

---
 src/netCDF4/_netCDF4.pyx | 17 +++++++++++++++--
 1 file changed, 15 insertions(+), 2 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index ec2570de9..0c9e0febc 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4334,7 +4334,9 @@ attributes."""
 
 return dictionary containing HDF5 filter parameters."""
         cdef int ierr,ideflate,ishuffle,icomplevel,ifletcher32
-        filtdict = {'compression':None,'zlib':False,'shuffle':False,'complevel':0,'fletcher32':False}
+        cdef int izstd=0
+        cdef int ibzip2=0
+        filtdict = {'zlib':False,'zstd':False,'bzip2':False,'shuffle':False,'complevel':0,'fletcher32':False}
         if self._grp.data_model not in ['NETCDF4_CLASSIC','NETCDF4']: return
         with nogil:
             ierr = nc_inq_var_deflate(self._grpid, self._varid, &ishuffle, &ideflate, &icomplevel)
@@ -4342,10 +4344,21 @@ return dictionary containing HDF5 filter parameters."""
         with nogil:
             ierr = nc_inq_var_fletcher32(self._grpid, self._varid, &ifletcher32)
         _ensure_nc_success(ierr)
+        IF HAS_ZSTANDARD_SUPPORT:
+            ierr = nc_inq_var_zstandard(self._grpid, self._varid, &izstd, &icomplevel)
+            _ensure_nc_success(ierr)
+        IF HAS_BZIP2_SUPPORT:
+            ierr = nc_inq_var_bzip2(self._grpid, self._varid, &ibzip2, &icomplevel)
+            _ensure_nc_success(ierr)
         if ideflate:
-            filtdict['compression']='zlib'
             filtdict['zlib']=True
             filtdict['complevel']=icomplevel
+        if izstd:
+            filtdict['zstd']=True
+            filtdict['complevel']=icomplevel
+        if ibzip2:
+            filtdict['bzip2']=True
+            filtdict['complevel']=icomplevel
         if ishuffle:
             filtdict['shuffle']=True
         if ifletcher32:

From 9815b3f0c4975e1dbdac5e6221989c2ff6a852d7 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 13:31:48 -0600
Subject: [PATCH 0769/1504] update

---
 test/tst_compression.py                         | 17 ++++++++++-------
 ...compression2.py => tst_compression_quant.py} |  7 ++++---
 2 files changed, 14 insertions(+), 10 deletions(-)
 rename test/{tst_compression2.py => tst_compression_quant.py} (93%)

diff --git a/test/tst_compression.py b/test/tst_compression.py
index b39fabd7d..3aa672017 100644
--- a/test/tst_compression.py
+++ b/test/tst_compression.py
@@ -97,8 +97,8 @@ def runTest(self):
         size = os.stat(self.files[1]).st_size
         assert_almost_equal(array,f.variables['data'][:])
         assert_almost_equal(array,f.variables['data2'][:])
-        assert f.variables['data'].filters() == {'compression':'zlib','zlib':True,'shuffle':False,'complevel':6,'fletcher32':False}
-        assert f.variables['data2'].filters() == {'compression':'zlib','zlib':True,'shuffle':False,'complevel':6,'fletcher32':False}
+        assert f.variables['data'].filters() == {'zlib':True,'shuffle':False,'complevel':6,'fletcher32':False}
+        assert f.variables['data2'].filters() == {'zlib':True,'shuffle':False,'complevel':6,'fletcher32':False}
         assert(size < 0.95*uncompressed_size)
         f.close()
         # check compression with shuffle
@@ -106,8 +106,8 @@ def runTest(self):
         size = os.stat(self.files[2]).st_size
         assert_almost_equal(array,f.variables['data'][:])
         assert_almost_equal(array,f.variables['data2'][:])
-        assert f.variables['data'].filters() == {'compression':'zlib','zlib':True,'shuffle':True,'complevel':6,'fletcher32':False}
-        assert f.variables['data2'].filters() == {'compression':'zlib','zlib':True,'shuffle':True,'complevel':6,'fletcher32':False}
+        assert f.variables['data'].filters() == {'zlib':True,'shuffle':True,'complevel':6,'fletcher32':False}
+        assert f.variables['data2'].filters() == {'zlib':True,'shuffle':True,'complevel':6,'fletcher32':False}
         assert(size < 0.85*uncompressed_size)
         f.close()
         # check lossy compression without shuffle
@@ -131,8 +131,10 @@ def runTest(self):
         size = os.stat(self.files[5]).st_size
         assert_almost_equal(checkarray,f.variables['data'][:])
         assert_almost_equal(checkarray,f.variables['data2'][:])
-        assert f.variables['data'].filters() == {'compression':'zlib','zlib':True,'shuffle':True,'complevel':6,'fletcher32':True}
-        assert f.variables['data2'].filters() == {'compression':'zlib','zlib':True,'shuffle':True,'complevel':6,'fletcher32':True}
+        assert f.variables['data'].filters() ==\
+        {'zlib':True,'zstd':False,'bzip2':False,'shuffle':True,'complevel':6,'fletcher32':True}
+        assert f.variables['data2'].filters() ==\
+        {'zlib':True,'zstd':False,'bzip2':False,'shuffle':True,'complevel':6,'fletcher32':True}
         assert(size < 0.20*uncompressed_size)
         # should be slightly larger than without fletcher32
         assert(size > size_save)
@@ -141,7 +143,8 @@ def runTest(self):
         f = Dataset(self.files[6])
         checkarray2 = _quantize(array2,lsd)
         assert_almost_equal(checkarray2,f.variables['data2'][:])
-        assert f.variables['data2'].filters() == {'compression':'zlib','zlib':True,'shuffle':True,'complevel':6,'fletcher32':True}
+        assert f.variables['data2'].filters() ==\
+        {'zlib':True,'zstd':False,'bzip2':False,'shuffle':True,'complevel':6,'fletcher32':True}
         assert f.variables['data2'].chunking() == [chunk1,chunk2]
         f.close()
 
diff --git a/test/tst_compression2.py b/test/tst_compression_quant.py
similarity index 93%
rename from test/tst_compression2.py
rename to test/tst_compression_quant.py
index a7e4929b8..3fb42c298 100644
--- a/test/tst_compression2.py
+++ b/test/tst_compression_quant.py
@@ -1,6 +1,5 @@
 from numpy.random.mtrand import uniform
 from netCDF4 import Dataset
-from netCDF4.utils import _quantize
 from numpy.testing import assert_almost_equal
 import numpy as np
 import os, tempfile, unittest
@@ -59,7 +58,8 @@ def runTest(self):
         size = os.stat(self.files[1]).st_size
         #print('compressed lossless no shuffle = ',size)
         assert_almost_equal(data_array,f.variables['data'][:])
-        assert f.variables['data'].filters() == {'compression':'zlib','zlib':True,'shuffle':False,'complevel':complevel,'fletcher32':False}
+        assert f.variables['data'].filters() ==\
+        {'zlib':True,'zstd':False,'bzip2':False,'shuffle':False,'complevel':complevel,'fletcher32':False}
         assert(size < 0.95*uncompressed_size)
         f.close()
         # check compression with shuffle
@@ -67,7 +67,8 @@ def runTest(self):
         size = os.stat(self.files[2]).st_size
         #print('compressed lossless with shuffle ',size)
         assert_almost_equal(data_array,f.variables['data'][:])
-        assert f.variables['data'].filters() == {'compression':'zlib','zlib':True,'shuffle':True,'complevel':complevel,'fletcher32':False}
+        assert f.variables['data'].filters() ==\
+        {'zlib':True,'zstd':False,'bzip2':False,'shuffle':True,'complevel':complevel,'fletcher32':False}
         assert(size < 0.85*uncompressed_size)
         f.close()
         # check lossy compression without shuffle

From b9d02bcfc29dc577347a4ed9ca683b8daa56fc54 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 13:32:15 -0600
Subject: [PATCH 0770/1504] tests for zstd and bzip2 filters

---
 test/tst_compression_bzip2.py | 53 +++++++++++++++++++++++++++++++++++
 test/tst_compression_zstd.py  | 53 +++++++++++++++++++++++++++++++++++
 2 files changed, 106 insertions(+)
 create mode 100644 test/tst_compression_bzip2.py
 create mode 100644 test/tst_compression_zstd.py

diff --git a/test/tst_compression_bzip2.py b/test/tst_compression_bzip2.py
new file mode 100644
index 000000000..56c8e0f5b
--- /dev/null
+++ b/test/tst_compression_bzip2.py
@@ -0,0 +1,53 @@
+from numpy.random.mtrand import uniform
+from netCDF4 import Dataset
+from numpy.testing import assert_almost_equal
+import os, tempfile, unittest
+
+ndim = 100000
+filename1 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
+filename2 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
+array = uniform(size=(ndim,))
+
+def write_netcdf(filename,dtype='f8',complevel=6):
+    nc = Dataset(filename,'w')
+    nc.createDimension('n', ndim)
+    foo = nc.createVariable('data2',\
+            dtype,('n'),compression='bzip2',complevel=complevel)
+    foo[:] = array
+    nc.close()
+
+class CompressionTestCase(unittest.TestCase):
+
+    def setUp(self):
+        self.filename1 = filename1
+        self.filename2 = filename2
+        write_netcdf(self.filename1,complevel=0) # no compression
+        write_netcdf(self.filename2,complevel=4) # with compression
+
+    def tearDown(self):
+        # Remove the temporary files
+        os.remove(self.filename1)
+        os.remove(self.filename2)
+
+    def runTest(self):
+        uncompressed_size = os.stat(self.filename1).st_size
+        # check uncompressed data
+        f = Dataset(self.filename)
+        size = os.stat(self.filename1).st_size
+        assert_almost_equal(array,f.variables['data'][:])
+        assert f.variables['data'].filters() ==\
+        {'zlib':False,'zstd':False,'bzip2':False,'shuffle':False,'complevel':0,'fletcher32':False}
+        assert_almost_equal(size,uncompressed_size)
+        f.close()
+        # check compressed data.
+        f = Dataset(self.filename2)
+        size = os.stat(self.filename2).st_size
+        assert_almost_equal(array,f.variables['data'][:])
+        assert f.variables['data'].filters() ==\
+        {'zlib':False,'zstd':False,'bzip2':True,'shuffle':False,'complevel':4,'fletcher32':False}
+        print(size, uncompressed_size)
+        assert(size < 0.95*uncompressed_size)
+        f.close()
+
+if __name__ == '__main__':
+    unittest.main()
diff --git a/test/tst_compression_zstd.py b/test/tst_compression_zstd.py
new file mode 100644
index 000000000..f3a1873a2
--- /dev/null
+++ b/test/tst_compression_zstd.py
@@ -0,0 +1,53 @@
+from numpy.random.mtrand import uniform
+from netCDF4 import Dataset
+from numpy.testing import assert_almost_equal
+import os, tempfile, unittest
+
+ndim = 100000
+filename1 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
+filename2 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
+array = uniform(size=(ndim,))
+
+def write_netcdf(filename,dtype='f8',complevel=6):
+    nc = Dataset(filename,'w')
+    nc.createDimension('n', ndim)
+    foo = nc.createVariable('data2',\
+            dtype,('n'),compression='zstd',complevel=complevel)
+    foo[:] = array
+    nc.close()
+
+class CompressionTestCase(unittest.TestCase):
+
+    def setUp(self):
+        self.filename1 = filename1
+        self.filename2 = filename2
+        write_netcdf(self.filename1,complevel=0) # no compression
+        write_netcdf(self.filename2,complevel=4) # with compression
+
+    def tearDown(self):
+        # Remove the temporary files
+        os.remove(self.filename1)
+        os.remove(self.filename2)
+
+    def runTest(self):
+        uncompressed_size = os.stat(self.filename1).st_size
+        # check uncompressed data
+        f = Dataset(self.filename)
+        size = os.stat(self.filename1).st_size
+        assert_almost_equal(array,f.variables['data'][:])
+        assert f.variables['data'].filters() ==\
+        {'zlib':False,'zstd':False,'bzip2':False,'shuffle':False,'complevel':0,'fletcher32':False}
+        assert_almost_equal(size,uncompressed_size)
+        f.close()
+        # check compressed data.
+        f = Dataset(self.filename2)
+        size = os.stat(self.filename2).st_size
+        assert_almost_equal(array,f.variables['data'][:])
+        assert f.variables['data'].filters() ==\
+        {'zlib':False,'zstd':True,'bzip2':False,'shuffle':False,'complevel':4,'fletcher32':False}
+        print(size, uncompressed_size)
+        assert(size < 0.95*uncompressed_size)
+        f.close()
+
+if __name__ == '__main__':
+    unittest.main()

From 57aec6634d21e9a7eafc3389ba1413ac22319a78 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 13:32:40 -0600
Subject: [PATCH 0771/1504] update

---
 test/run_all.py | 14 +++++++++++---
 1 file changed, 11 insertions(+), 3 deletions(-)

diff --git a/test/run_all.py b/test/run_all.py
index 723b0cdd6..df462c10d 100755
--- a/test/run_all.py
+++ b/test/run_all.py
@@ -1,7 +1,9 @@
 import glob, os, sys, unittest, struct
 from netCDF4 import getlibversion,__hdf5libversion__,__netcdf4libversion__,__version__
 from netCDF4 import __has_cdf5_format__, __has_nc_inq_path__, __has_nc_create_mem__, \
-                    __has_parallel4_support__, __has_pnetcdf_support__, __has_quantization_support__
+                    __has_parallel4_support__, __has_pnetcdf_support__, \
+                    __has_zstandard_support__, __has_bzip2_support__, \
+                    __has_blosc_support__,__has_quantization_support__
 
 # can also just run
 # python -m unittest discover . 'tst*py'
@@ -21,8 +23,14 @@
     test_files.remove('tst_cdf5.py')
     sys.stdout.write('not running tst_cdf5.py ...\n')
 if not __has_quantization_support__:
-    test_files.remove('tst_compression2.py')
-    sys.stdout.write('not running tst_compression2.py ...\n')
+    test_files.remove('tst_compression_quant.py')
+    sys.stdout.write('not running tst_compression_quant.py ...\n')
+if not __has_zstandard_support__:
+    test_files.remove('tst_compression_zstd.py')
+    sys.stdout.write('not running tst_compression_quant.py ...\n')
+if not __has_bzip2_support__:
+    test_files.remove('tst_compression_bzip2.py')
+    sys.stdout.write('not running tst_compression_bzip2.py ...\n')
 
 # Don't run tests that require network connectivity
 if os.getenv('NO_NET'):

From 977a016f054a868e981c0b331b861d34366e8ffc Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 15:32:52 -0600
Subject: [PATCH 0772/1504] add __has_blosc_support__

---
 src/netCDF4/_netCDF4.pyx | 1 +
 1 file changed, 1 insertion(+)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 0c9e0febc..bf0350596 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1323,6 +1323,7 @@ __has_pnetcdf_support__ = HAS_PNETCDF_SUPPORT
 __has_quantization_support__ = HAS_QUANTIZATION_SUPPORT
 __has_zstandard_support__ = HAS_ZSTANDARD_SUPPORT
 __has_bzip2_support__ = HAS_BZIP2_SUPPORT
+__has_blosc_support__ = HAS_BLOSC_SUPPORT
 _needsworkaround_issue485 = __netcdf4libversion__ < "4.4.0" or \
                (__netcdf4libversion__.startswith("4.4.0") and \
                 "-development" in __netcdf4libversion__)

From be86c9a3d5320408222b152e3205cb7bdb7917d3 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 15:35:30 -0600
Subject: [PATCH 0773/1504] add __has_blosc_support__

---
 src/netCDF4/__init__.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py
index f9fe6a736..b79cf6323 100644
--- a/src/netCDF4/__init__.py
+++ b/src/netCDF4/__init__.py
@@ -9,6 +9,6 @@
                        __has_nc_create_mem__, __has_cdf5_format__,
                        __has_parallel4_support__, __has_pnetcdf_support__,
                        __has_quantization_support__, __has_zstandard_support__,
-                       __has_bzip2_support__)
+                       __has_bzip2_support__, __has_blosc_support__)
 __all__ =\
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']

From 55cc3657b4060b2bdf1c135342e54747c992e535 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 15:47:26 -0600
Subject: [PATCH 0774/1504] update

---
 test/tst_compression.py | 15 ++++++++++-----
 1 file changed, 10 insertions(+), 5 deletions(-)

diff --git a/test/tst_compression.py b/test/tst_compression.py
index 3aa672017..9c9bd4929 100644
--- a/test/tst_compression.py
+++ b/test/tst_compression.py
@@ -88,8 +88,10 @@ def runTest(self):
         size = os.stat(self.files[0]).st_size
         assert_almost_equal(array,f.variables['data'][:])
         assert_almost_equal(array,f.variables['data2'][:])
-        assert f.variables['data'].filters() == {'compression':None,'zlib':False,'shuffle':False,'complevel':0,'fletcher32':False}
-        assert f.variables['data2'].filters() == {'compression':None,'zlib':False,'shuffle':False,'complevel':0,'fletcher32':False}
+        assert f.variables['data'].filters() ==\
+        {'zlib':False,'zstd':False,'bzip2':False,'shuffle':False,'complevel':0,'fletcher32':False}
+        assert f.variables['data2'].filters() ==\
+        {'zlib':False,'zstd':False,'bzip2':False,'shuffle':False,'complevel':0,'fletcher32':False}
         assert_almost_equal(size,uncompressed_size)
         f.close()
         # check compressed data.
@@ -97,7 +99,8 @@ def runTest(self):
         size = os.stat(self.files[1]).st_size
         assert_almost_equal(array,f.variables['data'][:])
         assert_almost_equal(array,f.variables['data2'][:])
-        assert f.variables['data'].filters() == {'zlib':True,'shuffle':False,'complevel':6,'fletcher32':False}
+        assert f.variables['data'].filters() ==\
+        {'zlib':True,'zstd':False,'bzip2':False,'shuffle':False,'complevel':6,'fletcher32':False}
         assert f.variables['data2'].filters() == {'zlib':True,'shuffle':False,'complevel':6,'fletcher32':False}
         assert(size < 0.95*uncompressed_size)
         f.close()
@@ -106,8 +109,10 @@ def runTest(self):
         size = os.stat(self.files[2]).st_size
         assert_almost_equal(array,f.variables['data'][:])
         assert_almost_equal(array,f.variables['data2'][:])
-        assert f.variables['data'].filters() == {'zlib':True,'shuffle':True,'complevel':6,'fletcher32':False}
-        assert f.variables['data2'].filters() == {'zlib':True,'shuffle':True,'complevel':6,'fletcher32':False}
+        assert f.variables['data'].filters() ==\
+        {'zlib':True,'zstd':False,'bzip2':False,'shuffle':True,'complevel':6,'fletcher32':False}
+        assert f.variables['data2'].filters() ==\
+        {'zlib':True,'zstd':False,'bzip2':False,'shuffle':True,'complevel':6,'fletcher32':False}
         assert(size < 0.85*uncompressed_size)
         f.close()
         # check lossy compression without shuffle

From ac7d4ce5ac992b7a6c2b50ad50044fc807cab1af Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 16:01:07 -0600
Subject: [PATCH 0775/1504] update

---
 test/tst_compression.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/test/tst_compression.py b/test/tst_compression.py
index 9c9bd4929..f10ec9a9f 100644
--- a/test/tst_compression.py
+++ b/test/tst_compression.py
@@ -101,7 +101,8 @@ def runTest(self):
         assert_almost_equal(array,f.variables['data2'][:])
         assert f.variables['data'].filters() ==\
         {'zlib':True,'zstd':False,'bzip2':False,'shuffle':False,'complevel':6,'fletcher32':False}
-        assert f.variables['data2'].filters() == {'zlib':True,'shuffle':False,'complevel':6,'fletcher32':False}
+        assert f.variables['data2'].filters() ==\
+        {'zlib':True,'zstd':False,'bzip2':False,'shuffle':False,'complevel':6,'fletcher32':False}
         assert(size < 0.95*uncompressed_size)
         f.close()
         # check compression with shuffle

From 4adc53efb3edb424e08d15a51060524671d32070 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 16:19:06 -0600
Subject: [PATCH 0776/1504] update

---
 src/netCDF4/_netCDF4.pyx      |  4 ++--
 test/tst_compression_bzip2.py |  7 +++----
 test/tst_compression_zstd.py  | 11 +++++------
 3 files changed, 10 insertions(+), 12 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index bf0350596..802b42791 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3940,7 +3940,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
                             msg = """
 compression='zstd' only works with netcdf-c >= 4.9.0.  To enable, install Cython, make sure you have
 version 4.9.0 or higher netcdf-c with zstandard support, and rebuild netcdf4-python."""
-                        raise ValueError(msg)
+                            raise ValueError(msg)
                     if bzip2:
                         IF HAS_BZIP2_SUPPORT:
                             icomplevel = complevel
@@ -3952,7 +3952,7 @@ version 4.9.0 or higher netcdf-c with zstandard support, and rebuild netcdf4-pyt
                             msg = """
 compression='bzip2' only works with netcdf-c >= 4.9.0.  To enable, install Cython, make sure you have
 version 4.9.0 or higher netcdf-c with bzip2 support, and rebuild netcdf4-python."""
-                        raise ValueError(msg)
+                            raise ValueError(msg)
                 # set checksum.
                 if fletcher32 and ndims: # don't bother for scalar variable
                     ierr = nc_def_var_fletcher32(self._grpid, self._varid, 1)
diff --git a/test/tst_compression_bzip2.py b/test/tst_compression_bzip2.py
index 56c8e0f5b..a8154e88a 100644
--- a/test/tst_compression_bzip2.py
+++ b/test/tst_compression_bzip2.py
@@ -11,7 +11,7 @@
 def write_netcdf(filename,dtype='f8',complevel=6):
     nc = Dataset(filename,'w')
     nc.createDimension('n', ndim)
-    foo = nc.createVariable('data2',\
+    foo = nc.createVariable('data',\
             dtype,('n'),compression='bzip2',complevel=complevel)
     foo[:] = array
     nc.close()
@@ -32,7 +32,7 @@ def tearDown(self):
     def runTest(self):
         uncompressed_size = os.stat(self.filename1).st_size
         # check uncompressed data
-        f = Dataset(self.filename)
+        f = Dataset(self.filename1)
         size = os.stat(self.filename1).st_size
         assert_almost_equal(array,f.variables['data'][:])
         assert f.variables['data'].filters() ==\
@@ -45,8 +45,7 @@ def runTest(self):
         assert_almost_equal(array,f.variables['data'][:])
         assert f.variables['data'].filters() ==\
         {'zlib':False,'zstd':False,'bzip2':True,'shuffle':False,'complevel':4,'fletcher32':False}
-        print(size, uncompressed_size)
-        assert(size < 0.95*uncompressed_size)
+        assert(size < 0.96*uncompressed_size)
         f.close()
 
 if __name__ == '__main__':
diff --git a/test/tst_compression_zstd.py b/test/tst_compression_zstd.py
index f3a1873a2..95292b4bf 100644
--- a/test/tst_compression_zstd.py
+++ b/test/tst_compression_zstd.py
@@ -11,7 +11,7 @@
 def write_netcdf(filename,dtype='f8',complevel=6):
     nc = Dataset(filename,'w')
     nc.createDimension('n', ndim)
-    foo = nc.createVariable('data2',\
+    foo = nc.createVariable('data',\
             dtype,('n'),compression='zstd',complevel=complevel)
     foo[:] = array
     nc.close()
@@ -32,7 +32,7 @@ def tearDown(self):
     def runTest(self):
         uncompressed_size = os.stat(self.filename1).st_size
         # check uncompressed data
-        f = Dataset(self.filename)
+        f = Dataset(self.filename1)
         size = os.stat(self.filename1).st_size
         assert_almost_equal(array,f.variables['data'][:])
         assert f.variables['data'].filters() ==\
@@ -43,10 +43,9 @@ def runTest(self):
         f = Dataset(self.filename2)
         size = os.stat(self.filename2).st_size
         assert_almost_equal(array,f.variables['data'][:])
-        assert f.variables['data'].filters() ==\
-        {'zlib':False,'zstd':True,'bzip2':False,'shuffle':False,'complevel':4,'fletcher32':False}
-        print(size, uncompressed_size)
-        assert(size < 0.95*uncompressed_size)
+        #assert f.variables['data'].filters() ==\
+        #{'zlib':False,'zstd':True,'bzip2':False,'shuffle':False,'complevel':4,'fletcher32':False}
+        assert(size < 0.96*uncompressed_size)
         f.close()
 
 if __name__ == '__main__':

From 5e76baf9a19a73a0035d23fe431ef9ac6aa224b0 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 16:24:58 -0600
Subject: [PATCH 0777/1504] update

---
 test/tst_compression_zstd.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/test/tst_compression_zstd.py b/test/tst_compression_zstd.py
index 95292b4bf..4114976b5 100644
--- a/test/tst_compression_zstd.py
+++ b/test/tst_compression_zstd.py
@@ -43,8 +43,9 @@ def runTest(self):
         f = Dataset(self.filename2)
         size = os.stat(self.filename2).st_size
         assert_almost_equal(array,f.variables['data'][:])
-        #assert f.variables['data'].filters() ==\
-        #{'zlib':False,'zstd':True,'bzip2':False,'shuffle':False,'complevel':4,'fletcher32':False}
+        #print(f.variables['data'].filters())
+        assert f.variables['data'].filters() ==\
+        {'zlib':False,'zstd':True,'bzip2':False,'shuffle':False,'complevel':4,'fletcher32':False}
         assert(size < 0.96*uncompressed_size)
         f.close()
 

From c82723bbc48a133e9469b94c8c093b9e6d31a356 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 16:47:23 -0600
Subject: [PATCH 0778/1504] fix complevel in filters method

---
 src/netCDF4/_netCDF4.pyx     | 12 +++++++-----
 test/tst_compression_zstd.py |  1 -
 2 files changed, 7 insertions(+), 6 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 802b42791..0a564c4ad 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4334,7 +4334,7 @@ attributes."""
 **`filters(self)`**
 
 return dictionary containing HDF5 filter parameters."""
-        cdef int ierr,ideflate,ishuffle,icomplevel,ifletcher32
+        cdef int ierr,ideflate,ishuffle,icomplevel,icomplevel_zstd,icomplevel_bzip2,ifletcher32
         cdef int izstd=0
         cdef int ibzip2=0
         filtdict = {'zlib':False,'zstd':False,'bzip2':False,'shuffle':False,'complevel':0,'fletcher32':False}
@@ -4346,20 +4346,22 @@ return dictionary containing HDF5 filter parameters."""
             ierr = nc_inq_var_fletcher32(self._grpid, self._varid, &ifletcher32)
         _ensure_nc_success(ierr)
         IF HAS_ZSTANDARD_SUPPORT:
-            ierr = nc_inq_var_zstandard(self._grpid, self._varid, &izstd, &icomplevel)
+            ierr = nc_inq_var_zstandard(self._grpid, self._varid, &izstd,\
+                    &icomplevel_zstd)
             _ensure_nc_success(ierr)
         IF HAS_BZIP2_SUPPORT:
-            ierr = nc_inq_var_bzip2(self._grpid, self._varid, &ibzip2, &icomplevel)
+            ierr = nc_inq_var_bzip2(self._grpid, self._varid, &ibzip2,\
+                    &icomplevel_bzip2)
             _ensure_nc_success(ierr)
         if ideflate:
             filtdict['zlib']=True
             filtdict['complevel']=icomplevel
         if izstd:
             filtdict['zstd']=True
-            filtdict['complevel']=icomplevel
+            filtdict['complevel']=icomplevel_zstd
         if ibzip2:
             filtdict['bzip2']=True
-            filtdict['complevel']=icomplevel
+            filtdict['complevel']=icomplevel_bzip2
         if ishuffle:
             filtdict['shuffle']=True
         if ifletcher32:
diff --git a/test/tst_compression_zstd.py b/test/tst_compression_zstd.py
index 4114976b5..c270ee4eb 100644
--- a/test/tst_compression_zstd.py
+++ b/test/tst_compression_zstd.py
@@ -43,7 +43,6 @@ def runTest(self):
         f = Dataset(self.filename2)
         size = os.stat(self.filename2).st_size
         assert_almost_equal(array,f.variables['data'][:])
-        #print(f.variables['data'].filters())
         assert f.variables['data'].filters() ==\
         {'zlib':False,'zstd':True,'bzip2':False,'shuffle':False,'complevel':4,'fletcher32':False}
         assert(size < 0.96*uncompressed_size)

From 846cf450be653a8f53ff3eb1560a26229fc6a107 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 17:03:15 -0600
Subject: [PATCH 0779/1504] install filter plugins

---
 .github/workflows/build_master.yml | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 81c43b455..619ad7bbf 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -34,6 +34,8 @@ jobs:
         ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 
         make -j 2
         make install
+        mkdir -p /usr/local/hdf5/lib
+        /bin/cp -R plugins/.libs/* /usr/local/hdf5/lib
         popd
 
 #   - name: The job has failed

From 1bd6a801db3ba6eec541d998d0c7f7dc524e79a1 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 17:21:33 -0600
Subject: [PATCH 0780/1504] update

---
 .github/workflows/build_master.yml | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 619ad7bbf..b4b74bb8b 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -34,8 +34,6 @@ jobs:
         ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 
         make -j 2
         make install
-        mkdir -p /usr/local/hdf5/lib
-        /bin/cp -R plugins/.libs/* /usr/local/hdf5/lib
         popd
 
 #   - name: The job has failed
@@ -56,6 +54,7 @@ jobs:
     - name: Test
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
+        export HDF5_PLUGIN_PATH=${NETCDF_DIR}/plugins/.libs
         python checkversion.py
         # serial
         cd test

From 96e993be578b701495334c065cd02b1e674a6c27 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 17:48:30 -0600
Subject: [PATCH 0781/1504] update

---
 .github/workflows/build_master.yml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index b4b74bb8b..97c0a40c8 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -55,6 +55,7 @@ jobs:
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
         export HDF5_PLUGIN_PATH=${NETCDF_DIR}/plugins/.libs
+        ls -l $HDF5_PLUGIN_PATH
         python checkversion.py
         # serial
         cd test

From 2a1beed18fc71b15e1aa84f4761831c63865da35 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 18:25:45 -0600
Subject: [PATCH 0782/1504] update

---
 .github/workflows/build_master.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 97c0a40c8..9a609188d 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -54,7 +54,7 @@ jobs:
     - name: Test
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
-        export HDF5_PLUGIN_PATH=${NETCDF_DIR}/plugins/.libs
+        export HDF5_PLUGIN_PATH=${NETCDF_DIR}/netcdf4-python/plugins/.libs
         ls -l $HDF5_PLUGIN_PATH
         python checkversion.py
         # serial

From 4c8c427fc4eb7b8efc4c8bbdab568eed1cb70e53 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 18:58:21 -0600
Subject: [PATCH 0783/1504] update

---
 .github/workflows/build_master.yml | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 9a609188d..e4903e29d 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -54,7 +54,7 @@ jobs:
     - name: Test
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
-        export HDF5_PLUGIN_PATH=${NETCDF_DIR}/netcdf4-python/plugins/.libs
+        export HDF5_PLUGIN_PATH=${NETCDF_DIR}/../netcdf-c/plugins/.libs
         ls -l $HDF5_PLUGIN_PATH
         python checkversion.py
         # serial
@@ -62,7 +62,6 @@ jobs:
         python run_all.py
         # parallel
         cd ../examples
-        python bench_compress4.py
         mpirun.mpich -np 4 python mpi_example.py
         if [ $? -ne 0 ] ; then
           echo "hdf5 mpi test failed!"

From bd25b57af948757f01a4f3fbb16e5b8b98815297 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 19:08:29 -0600
Subject: [PATCH 0784/1504] update

---
 .github/workflows/build_master.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index e4903e29d..5673a308f 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -54,7 +54,7 @@ jobs:
     - name: Test
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
-        export HDF5_PLUGIN_PATH=${NETCDF_DIR}/../netcdf-c/plugins/.libs
+        export HDF5_PLUGIN_PATH=${NETCDF_DIR}/netcdf-c/plugins/.libs
         ls -l $HDF5_PLUGIN_PATH
         python checkversion.py
         # serial

From 9b1b48446e4dd0be10afaaaf6efa411aa5ccc057 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 19:16:51 -0600
Subject: [PATCH 0785/1504] update

---
 .github/workflows/build_master.yml | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 5673a308f..1c9e78315 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -23,7 +23,7 @@ jobs:
     - name: Install Ubuntu Dependencies
       run: |
         sudo apt-get update
-        sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev libcurl4-openssl-dev bzip2 libblosc-dev libzstd-dev
+        sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
         echo "Download and build netCDF github master"
         git clone https://github.com/Unidata/netcdf-c
         pushd netcdf-c
@@ -34,6 +34,8 @@ jobs:
         ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 
         make -j 2
         make install
+        pwd
+        ls -l plugins/.libs
         popd
 
 #   - name: The job has failed

From 57b884406be71f8e4b5c99f3f3867ff43d579152 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 19:22:28 -0600
Subject: [PATCH 0786/1504] update

---
 .github/workflows/build_master.yml | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 1c9e78315..285b9b3f6 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -35,7 +35,8 @@ jobs:
         make -j 2
         make install
         pwd
-        ls -l plugins/.libs
+        mkdir ${NETCDF_DIR}/hdf5_plugins
+        /bin/mv -f plugins ${NETCDF_DIR}
         popd
 
 #   - name: The job has failed
@@ -56,7 +57,7 @@ jobs:
     - name: Test
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
-        export HDF5_PLUGIN_PATH=${NETCDF_DIR}/netcdf-c/plugins/.libs
+        export HDF5_PLUGIN_PATH=${NETCDF_DIR}/plugins/.libs
         ls -l $HDF5_PLUGIN_PATH
         python checkversion.py
         # serial

From 489d0308f21df6e97ec77db3d4915eedb8075308 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 19:28:12 -0600
Subject: [PATCH 0787/1504] add blosc compressors

---
 .github/workflows/build_master.yml |  1 -
 Changelog                          | 10 ++--
 src/netCDF4/_netCDF4.pyx           | 83 +++++++++++++++++++++++++-----
 3 files changed, 76 insertions(+), 18 deletions(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 285b9b3f6..35e6d43fb 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -58,7 +58,6 @@ jobs:
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
         export HDF5_PLUGIN_PATH=${NETCDF_DIR}/plugins/.libs
-        ls -l $HDF5_PLUGIN_PATH
         python checkversion.py
         # serial
         cd test
diff --git a/Changelog b/Changelog
index d3cbac8b2..bbb3dfe03 100644
--- a/Changelog
+++ b/Changelog
@@ -12,11 +12,11 @@
  * remove all vestiges of python 2 in _netCDF4.pyx and set cython language_level
    directive to 3 in setup.py.
  * add 'compression' kwarg to createVariable to enable new compression
-   functionality in netcdf-c 4.9.0.  'None', 'zlib', 'zstd' and 'bzip2 are currently
-   allowed (compression='zlib' is equivalent to zlib=True), but allows
-   for new compression algorithms to be added when they become available
-   in netcdf-c. The 'zlib' kwarg is now deprecated. Blosc compression feature
-   in netcdf-c 4.9.0 not yet supported.
+   functionality in netcdf-c 4.9.0.  'None','zlib','zstd','bzip2'
+   'blosc_lz','blosc_lz4','blosc_lz4hc','blosc_zlib','blosc_zstd' and 
+   'blosc_snappy' are currently supported. 'blosc_shuffle' and
+   'blosc_blocksize' kwargs also added.
+   compression='zlib' is equivalent to (the now deprecated) zlib=True.
  * MFDataset did not aggregate 'name' variable attribute (issue #1153).
  * issue warning instead of raising an exception if missing_value or
    _FillValue can't be cast to the variable type when creating a 
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 0a564c4ad..b686716f0 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2641,7 +2641,8 @@ datatype."""
 
     def createVariable(self, varname, datatype, dimensions=(), 
             compression=None, zlib=False,
-            complevel=4, shuffle=True, fletcher32=False, contiguous=False,
+            complevel=4, shuffle=True,
+            blosc_shuffle=0, blosc_blocksize=0, fletcher32=False, contiguous=False,
             chunksizes=None, endian='native', least_significant_digit=None,
             significant_digits=None,quantize_mode='BitGroom',fill_value=None, chunk_cache=None):
         """
@@ -2682,7 +2683,9 @@ is an empty tuple, which means the variable is a scalar.
 
 If the optional keyword argument `compression` is set, the data will be
 compressed in the netCDF file using the specified compression algorithm.
-Currently 'zlib','zstd' and 'bzip2' are supported. Default is `None` (no compression).
+Currently 'zlib','zstd','bzip2','blosc_' are supported
+(where  can be one of lz,lz4,lz4hc,zlib,zstd,snappy).
+Default is `None` (no compression).
 
 If the optional keyword `zlib` is `True`, the data will be compressed in
 the netCDF file using zlib compression (default `False`).  The use of this option is 
@@ -2697,6 +2700,12 @@ will be applied before compressing the data (default `True`).  This
 significantly improves compression. Default is `True`. Ignored if
 `zlib=False`.
 
+The optional kwargs 'blosc_shuffle` and `blosc_blocksize` are ignored
+unless the blosc compressor is used. `blosc_shuffle` can be 0 (no shuffle),
+1 (byte-wise shuffle) or 2 (bit-wise shuffle). Default is 0. `blosc_blocksize`
+is the tunable blosc blocksize in bytes (Default 0 means the blocksize is
+chosen internally).
+
 If the optional keyword `fletcher32` is `True`, the Fletcher32 HDF5
 checksum algorithm is activated to detect errors. Default `False`.
 
@@ -3648,12 +3657,13 @@ behavior is similar to Fortran or Matlab, but different than numpy.
 
     def __init__(self, grp, name, datatype, dimensions=(),
             compression=None, zlib=False,
-            complevel=4, shuffle=True, fletcher32=False, contiguous=False,
+            complevel=4, shuffle=True, blosc_shuffle=0, blosc_blocksize=0, 
+            fletcher32=False, contiguous=False,
             chunksizes=None, endian='native', least_significant_digit=None,
             significant_digits=None,quantize_mode='BitGroom',fill_value=None, chunk_cache=None, **kwargs):
         """
         **`__init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False,
-        complevel=4, shuffle=True, fletcher32=False, contiguous=False,
+        complevel=4, shuffle=True, blosc_shuffle=0, blosc_blocksize=0, fletcher32=False, contiguous=False,
         chunksizes=None, endian='native',
         least_significant_digit=None,fill_value=None,chunk_cache=None)`**
 
@@ -3687,7 +3697,9 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         which means the variable is a scalar (and therefore has no dimensions).
 
         **`compression`**: compression algorithm to use. Default None.  Currently
-        'zlib','zstd' and 'bzip2' are supported.
+        'zlib','zstd','bzip2','blosc_' are supported
+        (where  can be one of lz,lz4,lz4hc,zlib,zstd,snappy).
+        Default is `None` (no compression).
 
         **`zlib`**: if `True`, data assigned to the `Variable`
         instance is compressed on disk. Default `False`. Deprecated - use
@@ -3700,6 +3712,14 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         **`shuffle`**: if `True`, the HDF5 shuffle filter is applied
         to improve compression. Default `True`. Ignored if `compression=None`.
 
+        **`blosc_shuffle`**: shuffle filter inside blosc compressor (only
+        relevant if compression kwarg set to one of the blosc compressors).
+        Can be 0 (no blosc shuffle), 1 (bytewise shuffle) or 2 (bitwise
+        shuffle)). Default is 0.
+
+        **`blosc_blocksize`**: tunable blocksize in bytes for blosc
+        compressors. Default of 0 means blosc library chooses a blocksize.
+
         **`fletcher32`**: if `True` (default `False`), the Fletcher32 checksum
         algorithm is used for error detection.
 
@@ -3731,8 +3751,8 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         The `compression, zlib, complevel, shuffle, fletcher32, contiguous` and `chunksizes`
         keywords are silently ignored for netCDF 3 files that do not use HDF5.
 
-        **`least_significant_digit`**: If this or `significant_digits` are specified, 
-        variable data will be truncated (quantized).  
+        **`least_significant_digit`**: If this or `significant_digits` are specified,
+        variable data will be truncated (quantized).
         In conjunction with `compression='zlib'` this produces
         'lossy', but significantly more efficient compression. For example, if
         `least_significant_digit=1`, data will be quantized using
@@ -3740,7 +3760,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         so that a precision of 0.1 is retained (in this case bits=4). Default is
         `None`, or no quantization.
 
-        **`significant_digits`**: New in version 1.6.0. 
+        **`significant_digits`**: New in version 1.6.0.
         As described for `least_significant_digit`
         except the number of significant digits retained is prescribed independent
         of the floating point exponent. Default `None` - no quantization done.
@@ -3748,7 +3768,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         **`quantize_mode`**: New in version 1.6.0. Controls
         the quantization algorithm (default 'BitGroom', 'BitRound' and
         'GranularBitRound' also available).  The 'GranularBitRound'
-        algorithm may result in better compression for typical geophysical datasets. 
+        algorithm may result in better compression for typical geophysical datasets.
         Ignored if `significant_digts` not specified. If 'BitRound' is used, then
         `significant_digits` is interpreted as binary (not decimal) digits.
 
@@ -3759,14 +3779,15 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         in the dictionary `netCDF4.default_fillvals`.
 
         **`chunk_cache`**: If specified, sets the chunk cache size for this variable.
-        Persists as long as Dataset is open. Use `set_var_chunk_cache` to 
-        change it when Dataset is re-opened. 
+        Persists as long as Dataset is open. Use `set_var_chunk_cache` to
+        change it when Dataset is re-opened.
 
         ***Note***: `Variable` instances should be created using the
         `Dataset.createVariable` method of a `Dataset` or
         `Group` instance, not using this class directly.
         """
-        cdef int ierr, ndims, icontiguous, icomplevel, numdims, _grpid, nsd
+        cdef int ierr, ndims, icontiguous, icomplevel, numdims, _grpid, nsd,\
+                 iblosc_blocksize,iblosc_compressor,iblosc_shuffle
         cdef char namstring[NC_MAX_NAME+1]
         cdef char *varname
         cdef nc_type xtype
@@ -3786,12 +3807,30 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         zlib = False
         zstd = False
         bzip2 = False
+        blosc_lz = False
+        blosc_lz4 = False
+        blosc_lz4hc = False
+        blosc_snappy = False
+        blosc_zlib = False
+        blosc_zstd = False
         if compression == 'zlib':
             zlib = True
         elif compression == 'zstd':
             zstd = True
         elif compression == 'bzip2':
             bzip2 = True
+        elif compression == 'blosc_lz':
+            blosc_lz = True
+        elif compression == 'blosc_lz':
+            blosc_lz4 = True
+        elif compression == 'blosc_lz4hc':
+            blosc_lz4hc = True
+        elif compression == 'blosc_snappy':
+            blosc_snappy = True
+        elif compression == 'blosc_zlib':
+            blosc_zlib = True
+        elif compression == 'blosc_zstd':
+            blosc_zstd = True
         elif not compression:
             compression = None # if compression evaluates to False, set to None.
             pass
@@ -3953,6 +3992,26 @@ version 4.9.0 or higher netcdf-c with zstandard support, and rebuild netcdf4-pyt
 compression='bzip2' only works with netcdf-c >= 4.9.0.  To enable, install Cython, make sure you have
 version 4.9.0 or higher netcdf-c with bzip2 support, and rebuild netcdf4-python."""
                             raise ValueError(msg)
+                    if blosc_lz or blosc_lz4 or blosc_lz4hc or blosc_zlib or\
+                       blosc_zstd or blosc_snappy:
+                        IF HAS_BLOSC_SUPPORT:
+                            icomplevel = complevel
+                            blosc_dict={'blosc_lz':0,'blosc_lz4':1,'blosc_lz4hc':2,'blosc_snappy':3,'blosc_zlib':4,'blosc_zstd':5}
+                            iblosc_compression = blosc_dict[compression]
+                            iblosc_shuffle = blosc_shuffle
+                            iblosc_blocksize = blosc_blocksize
+                            ierr = nc_def_var_blosc(self._grpid, self._varid,\
+                                    iblosc_compressor,\
+                                    icomplevel,iblosc_blocksize,\
+                                    iblosc_shuffle)
+                            if ierr != NC_NOERR:
+                                if grp.data_model != 'NETCDF4': grp._enddef()
+                                _ensure_nc_success(ierr)
+                        ELSE:
+                            msg = """
+compression='blosc_*' only works with netcdf-c >= 4.9.0.  To enable, install Cython, make sure you have
+version 4.9.0 or higher netcdf-c with blosc support, and rebuild netcdf4-python."""
+                            raise ValueError(msg)
                 # set checksum.
                 if fletcher32 and ndims: # don't bother for scalar variable
                     ierr = nc_def_var_fletcher32(self._grpid, self._varid, 1)

From 72f18f623650650372c0d4e4773211e2fa219c30 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 19:42:23 -0600
Subject: [PATCH 0788/1504] update blosc stuff

---
 src/netCDF4/_netCDF4.pyx | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index b686716f0..1b4b08a3f 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3786,8 +3786,8 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         `Dataset.createVariable` method of a `Dataset` or
         `Group` instance, not using this class directly.
         """
-        cdef int ierr, ndims, icontiguous, icomplevel, numdims, _grpid, nsd,\
-                 iblosc_blocksize,iblosc_compressor,iblosc_shuffle
+        cdef int ierr, ndims, icontiguous, icomplevel, numdims, _grpid, nsd,
+        cdef unsigned iblosc_complevel,iblosc_blocksize,iblosc_compressor,iblosc_shuffle
         cdef char namstring[NC_MAX_NAME+1]
         cdef char *varname
         cdef nc_type xtype
@@ -3821,7 +3821,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
             bzip2 = True
         elif compression == 'blosc_lz':
             blosc_lz = True
-        elif compression == 'blosc_lz':
+        elif compression == 'blosc_lz4':
             blosc_lz4 = True
         elif compression == 'blosc_lz4hc':
             blosc_lz4hc = True
@@ -3995,14 +3995,14 @@ version 4.9.0 or higher netcdf-c with bzip2 support, and rebuild netcdf4-python.
                     if blosc_lz or blosc_lz4 or blosc_lz4hc or blosc_zlib or\
                        blosc_zstd or blosc_snappy:
                         IF HAS_BLOSC_SUPPORT:
-                            icomplevel = complevel
                             blosc_dict={'blosc_lz':0,'blosc_lz4':1,'blosc_lz4hc':2,'blosc_snappy':3,'blosc_zlib':4,'blosc_zstd':5}
                             iblosc_compression = blosc_dict[compression]
                             iblosc_shuffle = blosc_shuffle
                             iblosc_blocksize = blosc_blocksize
+                            iblosc_complevel = complevel
                             ierr = nc_def_var_blosc(self._grpid, self._varid,\
                                     iblosc_compressor,\
-                                    icomplevel,iblosc_blocksize,\
+                                    iblosc_complevel,iblosc_blocksize,\
                                     iblosc_shuffle)
                             if ierr != NC_NOERR:
                                 if grp.data_model != 'NETCDF4': grp._enddef()

From 67137892246e79451359810e8783cbb0c31162c3 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 20:26:02 -0600
Subject: [PATCH 0789/1504] test for blosc compression

---
 src/netCDF4/_netCDF4.pyx      | 24 ++++++++++++----
 test/tst_compression.py       | 18 ++++++------
 test/tst_compression_blosc.py | 54 +++++++++++++++++++++++++++++++++++
 test/tst_compression_bzip2.py |  4 +--
 test/tst_compression_quant.py |  4 +--
 test/tst_compression_zstd.py  |  4 +--
 6 files changed, 88 insertions(+), 20 deletions(-)
 create mode 100644 test/tst_compression_blosc.py

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 1b4b08a3f..5bb4bffc5 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1369,6 +1369,9 @@ _format_dict  = {'NETCDF3_CLASSIC' : NC_FORMAT_CLASSIC,
 _cmode_dict  = {'NETCDF3_CLASSIC' : NC_CLASSIC_MODEL,
                 'NETCDF4_CLASSIC' : NC_CLASSIC_MODEL | NC_NETCDF4,
                 'NETCDF4'         : NC_NETCDF4}
+# dicts for blosc compressors.
+_blosc_dict={'blosc_lz':0,'blosc_lz4':1,'blosc_lz4hc':2,'blosc_snappy':3,'blosc_zlib':4,'blosc_zstd':5}
+_blosc_dict_inv = {v: k for k, v in _blosc_dict.items()}
 IF HAS_CDF5_FORMAT:
     # NETCDF3_64BIT deprecated, saved for compatibility.
     # use NETCDF3_64BIT_OFFSET instead.
@@ -2817,6 +2820,7 @@ is the number of variable dimensions."""
         # create variable.
         group.variables[varname] = Variable(group, varname, datatype,
         dimensions=dimensions, compression=compression, zlib=zlib, complevel=complevel, shuffle=shuffle,
+        blosc_shuffle=blosc_shuffle,blosc_blocksize=blosc_blocksize,
         fletcher32=fletcher32, contiguous=contiguous, chunksizes=chunksizes,
         endian=endian, least_significant_digit=least_significant_digit,
         significant_digits=significant_digits,quantize_mode=quantize_mode,fill_value=fill_value, chunk_cache=chunk_cache)
@@ -3657,7 +3661,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
 
     def __init__(self, grp, name, datatype, dimensions=(),
             compression=None, zlib=False,
-            complevel=4, shuffle=True, blosc_shuffle=0, blosc_blocksize=0, 
+            complevel=4, shuffle=True, blosc_shuffle=0, blosc_blocksize=0,
             fletcher32=False, contiguous=False,
             chunksizes=None, endian='native', least_significant_digit=None,
             significant_digits=None,quantize_mode='BitGroom',fill_value=None, chunk_cache=None, **kwargs):
@@ -3787,7 +3791,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         `Group` instance, not using this class directly.
         """
         cdef int ierr, ndims, icontiguous, icomplevel, numdims, _grpid, nsd,
-        cdef unsigned iblosc_complevel,iblosc_blocksize,iblosc_compressor,iblosc_shuffle
+        cdef unsigned int iblosc_complevel,iblosc_blocksize,iblosc_compressor,iblosc_shuffle
         cdef char namstring[NC_MAX_NAME+1]
         cdef char *varname
         cdef nc_type xtype
@@ -3995,8 +3999,7 @@ version 4.9.0 or higher netcdf-c with bzip2 support, and rebuild netcdf4-python.
                     if blosc_lz or blosc_lz4 or blosc_lz4hc or blosc_zlib or\
                        blosc_zstd or blosc_snappy:
                         IF HAS_BLOSC_SUPPORT:
-                            blosc_dict={'blosc_lz':0,'blosc_lz4':1,'blosc_lz4hc':2,'blosc_snappy':3,'blosc_zlib':4,'blosc_zstd':5}
-                            iblosc_compression = blosc_dict[compression]
+                            iblosc_compressor = _blosc_dict[compression]
                             iblosc_shuffle = blosc_shuffle
                             iblosc_blocksize = blosc_blocksize
                             iblosc_complevel = complevel
@@ -4396,7 +4399,9 @@ return dictionary containing HDF5 filter parameters."""
         cdef int ierr,ideflate,ishuffle,icomplevel,icomplevel_zstd,icomplevel_bzip2,ifletcher32
         cdef int izstd=0
         cdef int ibzip2=0
-        filtdict = {'zlib':False,'zstd':False,'bzip2':False,'shuffle':False,'complevel':0,'fletcher32':False}
+        cdef int iblosc=0
+        cdef unsigned int iblosc_complevel,iblosc_blocksize,iblosc_compressor,iblosc_shuffle
+        filtdict = {'zlib':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
         if self._grp.data_model not in ['NETCDF4_CLASSIC','NETCDF4']: return
         with nogil:
             ierr = nc_inq_var_deflate(self._grpid, self._varid, &ishuffle, &ideflate, &icomplevel)
@@ -4412,6 +4417,10 @@ return dictionary containing HDF5 filter parameters."""
             ierr = nc_inq_var_bzip2(self._grpid, self._varid, &ibzip2,\
                     &icomplevel_bzip2)
             _ensure_nc_success(ierr)
+        IF HAS_BLOSC_SUPPORT:
+            ierr = nc_inq_var_blosc(self._grpid, self._varid, &iblosc,\
+                    &iblosc_compressor,&iblosc_complevel,&iblosc_blocksize,&iblosc_shuffle)
+            _ensure_nc_success(ierr)
         if ideflate:
             filtdict['zlib']=True
             filtdict['complevel']=icomplevel
@@ -4421,6 +4430,11 @@ return dictionary containing HDF5 filter parameters."""
         if ibzip2:
             filtdict['bzip2']=True
             filtdict['complevel']=icomplevel_bzip2
+        if iblosc:
+            #filtdict['blosc']=True
+            blosc_compressor = iblosc_compressor
+            filtdict['blosc']={'compressor':_blosc_dict_inv[blosc_compressor],'shuffle':iblosc_shuffle,'blocksize':iblosc_blocksize}
+            filtdict['complevel']=iblosc_complevel
         if ishuffle:
             filtdict['shuffle']=True
         if ifletcher32:
diff --git a/test/tst_compression.py b/test/tst_compression.py
index f10ec9a9f..c47422910 100644
--- a/test/tst_compression.py
+++ b/test/tst_compression.py
@@ -89,9 +89,9 @@ def runTest(self):
         assert_almost_equal(array,f.variables['data'][:])
         assert_almost_equal(array,f.variables['data2'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':False,'zstd':False,'bzip2':False,'shuffle':False,'complevel':0,'fletcher32':False}
+        {'zlib':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
         assert f.variables['data2'].filters() ==\
-        {'zlib':False,'zstd':False,'bzip2':False,'shuffle':False,'complevel':0,'fletcher32':False}
+        {'zlib':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
         assert_almost_equal(size,uncompressed_size)
         f.close()
         # check compressed data.
@@ -100,9 +100,9 @@ def runTest(self):
         assert_almost_equal(array,f.variables['data'][:])
         assert_almost_equal(array,f.variables['data2'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':True,'zstd':False,'bzip2':False,'shuffle':False,'complevel':6,'fletcher32':False}
+        {'zlib':True,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':6,'fletcher32':False}
         assert f.variables['data2'].filters() ==\
-        {'zlib':True,'zstd':False,'bzip2':False,'shuffle':False,'complevel':6,'fletcher32':False}
+        {'zlib':True,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':6,'fletcher32':False}
         assert(size < 0.95*uncompressed_size)
         f.close()
         # check compression with shuffle
@@ -111,9 +111,9 @@ def runTest(self):
         assert_almost_equal(array,f.variables['data'][:])
         assert_almost_equal(array,f.variables['data2'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':True,'zstd':False,'bzip2':False,'shuffle':True,'complevel':6,'fletcher32':False}
+        {'zlib':True,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':False}
         assert f.variables['data2'].filters() ==\
-        {'zlib':True,'zstd':False,'bzip2':False,'shuffle':True,'complevel':6,'fletcher32':False}
+        {'zlib':True,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':False}
         assert(size < 0.85*uncompressed_size)
         f.close()
         # check lossy compression without shuffle
@@ -138,9 +138,9 @@ def runTest(self):
         assert_almost_equal(checkarray,f.variables['data'][:])
         assert_almost_equal(checkarray,f.variables['data2'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':True,'zstd':False,'bzip2':False,'shuffle':True,'complevel':6,'fletcher32':True}
+        {'zlib':True,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':True}
         assert f.variables['data2'].filters() ==\
-        {'zlib':True,'zstd':False,'bzip2':False,'shuffle':True,'complevel':6,'fletcher32':True}
+        {'zlib':True,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':True}
         assert(size < 0.20*uncompressed_size)
         # should be slightly larger than without fletcher32
         assert(size > size_save)
@@ -150,7 +150,7 @@ def runTest(self):
         checkarray2 = _quantize(array2,lsd)
         assert_almost_equal(checkarray2,f.variables['data2'][:])
         assert f.variables['data2'].filters() ==\
-        {'zlib':True,'zstd':False,'bzip2':False,'shuffle':True,'complevel':6,'fletcher32':True}
+        {'zlib':True,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':True}
         assert f.variables['data2'].chunking() == [chunk1,chunk2]
         f.close()
 
diff --git a/test/tst_compression_blosc.py b/test/tst_compression_blosc.py
new file mode 100644
index 000000000..4324f26c1
--- /dev/null
+++ b/test/tst_compression_blosc.py
@@ -0,0 +1,54 @@
+from numpy.random.mtrand import uniform
+from netCDF4 import Dataset
+from numpy.testing import assert_almost_equal
+import os, tempfile, unittest
+
+ndim = 100000
+filename1 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
+filename2 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
+array = uniform(size=(ndim,))
+
+def write_netcdf(filename,dtype='f8',complevel=6):
+    nc = Dataset(filename,'w')
+    nc.createDimension('n', ndim)
+    foo = nc.createVariable('data',\
+            dtype,('n'),compression='blosc_lz4',blosc_shuffle=2,complevel=complevel)
+    foo[:] = array
+    nc.close()
+
+class CompressionTestCase(unittest.TestCase):
+
+    def setUp(self):
+        self.filename1 = filename1
+        self.filename2 = filename2
+        write_netcdf(self.filename1,complevel=0) # no compression
+        write_netcdf(self.filename2,complevel=4) # with compression
+
+    def tearDown(self):
+        # Remove the temporary files
+        os.remove(self.filename1)
+        os.remove(self.filename2)
+
+    def runTest(self):
+        uncompressed_size = os.stat(self.filename1).st_size
+        # check uncompressed data
+        f = Dataset(self.filename1)
+        size = os.stat(self.filename1).st_size
+        assert_almost_equal(array,f.variables['data'][:])
+        assert f.variables['data'].filters() ==\
+        {'zlib':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
+        assert_almost_equal(size,uncompressed_size)
+        f.close()
+        # check compressed data.
+        f = Dataset(self.filename2)
+        size = os.stat(self.filename2).st_size
+        assert_almost_equal(array,f.variables['data'][:])
+        dtest= {'zlib': False, 'zstd': False, 'bzip2': False, 'blosc':\
+        {'compressor': 'blosc_lz4', 'shuffle': 2, 'blocksize': 800000},\
+        'shuffle': False, 'complevel': 4, 'fletcher32': False}
+        assert f.variables['data'].filters() == dtest
+        assert(size < 0.96*uncompressed_size)
+        f.close()
+
+if __name__ == '__main__':
+    unittest.main()
diff --git a/test/tst_compression_bzip2.py b/test/tst_compression_bzip2.py
index a8154e88a..8a162f20c 100644
--- a/test/tst_compression_bzip2.py
+++ b/test/tst_compression_bzip2.py
@@ -36,7 +36,7 @@ def runTest(self):
         size = os.stat(self.filename1).st_size
         assert_almost_equal(array,f.variables['data'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':False,'zstd':False,'bzip2':False,'shuffle':False,'complevel':0,'fletcher32':False}
+        {'zlib':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
         assert_almost_equal(size,uncompressed_size)
         f.close()
         # check compressed data.
@@ -44,7 +44,7 @@ def runTest(self):
         size = os.stat(self.filename2).st_size
         assert_almost_equal(array,f.variables['data'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':False,'zstd':False,'bzip2':True,'shuffle':False,'complevel':4,'fletcher32':False}
+        {'zlib':False,'zstd':False,'bzip2':True,'blosc':False,'shuffle':False,'complevel':4,'fletcher32':False}
         assert(size < 0.96*uncompressed_size)
         f.close()
 
diff --git a/test/tst_compression_quant.py b/test/tst_compression_quant.py
index 3fb42c298..9a44420c3 100644
--- a/test/tst_compression_quant.py
+++ b/test/tst_compression_quant.py
@@ -59,7 +59,7 @@ def runTest(self):
         #print('compressed lossless no shuffle = ',size)
         assert_almost_equal(data_array,f.variables['data'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':True,'zstd':False,'bzip2':False,'shuffle':False,'complevel':complevel,'fletcher32':False}
+        {'zlib':True,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':complevel,'fletcher32':False}
         assert(size < 0.95*uncompressed_size)
         f.close()
         # check compression with shuffle
@@ -68,7 +68,7 @@ def runTest(self):
         #print('compressed lossless with shuffle ',size)
         assert_almost_equal(data_array,f.variables['data'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':True,'zstd':False,'bzip2':False,'shuffle':True,'complevel':complevel,'fletcher32':False}
+        {'zlib':True,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':complevel,'fletcher32':False}
         assert(size < 0.85*uncompressed_size)
         f.close()
         # check lossy compression without shuffle
diff --git a/test/tst_compression_zstd.py b/test/tst_compression_zstd.py
index c270ee4eb..cd9d270ef 100644
--- a/test/tst_compression_zstd.py
+++ b/test/tst_compression_zstd.py
@@ -36,7 +36,7 @@ def runTest(self):
         size = os.stat(self.filename1).st_size
         assert_almost_equal(array,f.variables['data'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':False,'zstd':False,'bzip2':False,'shuffle':False,'complevel':0,'fletcher32':False}
+        {'zlib':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
         assert_almost_equal(size,uncompressed_size)
         f.close()
         # check compressed data.
@@ -44,7 +44,7 @@ def runTest(self):
         size = os.stat(self.filename2).st_size
         assert_almost_equal(array,f.variables['data'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':False,'zstd':True,'bzip2':False,'shuffle':False,'complevel':4,'fletcher32':False}
+        {'zlib':False,'zstd':True,'bzip2':False,'blosc':False,'shuffle':False,'complevel':4,'fletcher32':False}
         assert(size < 0.96*uncompressed_size)
         f.close()
 

From 79cad3858bcb86d9d7631ad1df692d19b51767cf Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 20:26:28 -0600
Subject: [PATCH 0790/1504] update docs

---
 docs/index.html | 42 +++++++++++++++++++++++++++++++-----------
 1 file changed, 31 insertions(+), 11 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 3d402ea44..5304c3111 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -1612,7 +1612,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -1634,7 +1634,9 @@ 
      In-memory (diskless) Datasets
      
                        __has_rename_grp__, __has_nc_inq_path__,
                        __has_nc_inq_format_extended__, __has_nc_open_mem__,
                        __has_nc_create_mem__, __has_cdf5_format__,
-                       __has_parallel4_support__, __has_pnetcdf_support__,__has_quantization_support__)
+                       __has_parallel4_support__, __has_pnetcdf_support__,
+                       __has_quantization_support__, __has_zstandard_support__,
+                       __has_bzip2_support__, __has_blosc_support__)
 __all__ =\
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
 
      
@@ -2090,7 +2092,9 @@ 
      In-memory (diskless) Datasets
      
 
 
      If the optional keyword argument compression is set, the data will be
 compressed in the netCDF file using the specified compression algorithm.
-Currently only 'zlib' is supported. Default is None (no compression).
      
+Currently 'zlib','zstd','bzip2','blosc_' are supported
+(where  can be one of lz,lz4,lz4hc,zlib,zstd,snappy).
+Default is None (no compression).
      
 
 
      If the optional keyword zlib is True, the data will be compressed in
 the netCDF file using zlib compression (default False).  The use of this option is 
@@ -2105,6 +2109,12 @@ 
      In-memory (diskless) Datasets
      
 significantly improves compression. Default is True. Ignored if
 zlib=False.
      
 
+
      The optional kwargs 'blosc_shuffleandblosc_blocksizeare ignored
+unless the blosc compressor is used.blosc_shufflecan be 0 (no shuffle),
+1 (byte-wise shuffle) or 2 (bit-wise shuffle). Default is 0.blosc_blocksize`
+is the tunable blosc blocksize in bytes (Default 0 means the blocksize is
+chosen internally).
      
+
 
      If the optional keyword fletcher32 is True, the Fletcher32 HDF5
 checksum algorithm is activated to detect errors. Default False.
      
 
@@ -2836,7 +2846,7 @@ 
      In-memory (diskless) Datasets
      
 
         
             
      __init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False,
-complevel=4, shuffle=True, fletcher32=False, contiguous=False,
+complevel=4, shuffle=True, blosc_shuffle=0, blosc_blocksize=0, fletcher32=False, contiguous=False,
 chunksizes=None, endian='native',
 least_significant_digit=None,fill_value=None,chunk_cache=None)
      
 
@@ -2870,7 +2880,9 @@ 
      In-memory (diskless) Datasets
      
 which means the variable is a scalar (and therefore has no dimensions).
      
 
 
      compression: compression algorithm to use. Default None.  Currently
-only 'zlib' is supported.
      
+'zlib','zstd','bzip2','blosc_' are supported
+(where  can be one of lz,lz4,lz4hc,zlib,zstd,snappy).
+Default is None (no compression).
      
 
 
      zlib: if True, data assigned to the Variable
 instance is compressed on disk. Default False. Deprecated - use
@@ -2883,6 +2895,14 @@ 
      In-memory (diskless) Datasets
      
 
      shuffle: if True, the HDF5 shuffle filter is applied
 to improve compression. Default True. Ignored if compression=None.
      
 
+
      blosc_shuffle: shuffle filter inside blosc compressor (only
+relevant if compression kwarg set to one of the blosc compressors).
+Can be 0 (no blosc shuffle), 1 (bytewise shuffle) or 2 (bitwise
+shuffle)). Default is 0.
      
+
+
      blosc_blocksize: tunable blocksize in bytes for blosc
+compressors. Default of 0 means blosc library chooses a blocksize.
      
+
 
      fletcher32: if True (default False), the Fletcher32 checksum
 algorithm is used for error detection.
      
 
@@ -2914,8 +2934,8 @@ 
      In-memory (diskless) Datasets
      
 
      The compression, zlib, complevel, shuffle, fletcher32, contiguous and chunksizes
 keywords are silently ignored for netCDF 3 files that do not use HDF5.
      
 
-
      least_significant_digit: If this or significant_digits are specified, 
-variable data will be truncated (quantized). 
      
+
      least_significant_digit: If this or significant_digits are specified,
+variable data will be truncated (quantized).
 In conjunction with compression='zlib' this produces
 'lossy', but significantly more efficient compression. For example, if
 least_significant_digit=1, data will be quantized using
@@ -2923,7 +2943,7 @@ 
      In-memory (diskless) Datasets
      
 so that a precision of 0.1 is retained (in this case bits=4). Default is
 None, or no quantization.
      
 
-
      significant_digits: New in version 1.6.0. 
+
      significant_digits: New in version 1.6.0.
 As described for least_significant_digit
 except the number of significant digits retained is prescribed independent
 of the floating point exponent. Default None - no quantization done.
      
@@ -2931,7 +2951,7 @@ 
      In-memory (diskless) Datasets
      
 
      quantize_mode: New in version 1.6.0. Controls
 the quantization algorithm (default 'BitGroom', 'BitRound' and
 'GranularBitRound' also available).  The 'GranularBitRound'
-algorithm may result in better compression for typical geophysical datasets. 
+algorithm may result in better compression for typical geophysical datasets.
 Ignored if significant_digts not specified. If 'BitRound' is used, then
 significant_digits is interpreted as binary (not decimal) digits.
      
 
@@ -2942,8 +2962,8 @@ 
      In-memory (diskless) Datasets
      
 in the dictionary netCDF4.default_fillvals.
      
 
 
      chunk_cache: If specified, sets the chunk cache size for this variable.
-Persists as long as Dataset is open. Use set_var_chunk_cache to 
-change it when Dataset is re-opened. 
      
+Persists as long as Dataset is open. Use set_var_chunk_cache to
+change it when Dataset is re-opened.
      
 
 
      Note: Variable instances should be created using the
 Dataset.createVariable method of a Dataset or

From bb03d0d088d7d6585c8f303932984b3a0b718cd3 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 20:38:18 -0600
Subject: [PATCH 0791/1504] update docstring

---
 docs/index.html          | 14 ++++++--------
 src/netCDF4/_netCDF4.pyx | 12 +++++-------
 2 files changed, 11 insertions(+), 15 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 5304c3111..0fba2894e 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -1612,7 +1612,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -2092,9 +2092,8 @@ 
      In-memory (diskless) Datasets
      
 
 
      If the optional keyword argument compression is set, the data will be
 compressed in the netCDF file using the specified compression algorithm.
-Currently 'zlib','zstd','bzip2','blosc_' are supported
-(where  can be one of lz,lz4,lz4hc,zlib,zstd,snappy).
-Default is None (no compression).
      
+Currently zlib,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,blosc_zlib,blosc_zstd
+and blosc_snappy are supported. Default is None (no compression).
      
 
 
      If the optional keyword zlib is True, the data will be compressed in
 the netCDF file using zlib compression (default False).  The use of this option is 
@@ -2879,10 +2878,9 @@ 
      In-memory (diskless) Datasets
      
 (defined previously with createDimension). Default is an empty tuple
 which means the variable is a scalar (and therefore has no dimensions).
      
 
-
      compression: compression algorithm to use. Default None.  Currently
-'zlib','zstd','bzip2','blosc_' are supported
-(where  can be one of lz,lz4,lz4hc,zlib,zstd,snappy).
-Default is None (no compression).
      
+
      compression: compression algorithm to use. Default None. 
      
+Currently zlib,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,blosc_zlib,blosc_zstd
+and blosc_snappy are supported. Default is None (no compression).
      
 
 
      zlib: if True, data assigned to the Variable
 instance is compressed on disk. Default False. Deprecated - use
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 5bb4bffc5..8c79020d8 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2686,9 +2686,8 @@ is an empty tuple, which means the variable is a scalar.
 
 If the optional keyword argument `compression` is set, the data will be
 compressed in the netCDF file using the specified compression algorithm.
-Currently 'zlib','zstd','bzip2','blosc_' are supported
-(where  can be one of lz,lz4,lz4hc,zlib,zstd,snappy).
-Default is `None` (no compression).
+Currently zlib,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,blosc_zlib,blosc_zstd
+and blosc_snappy are supported. Default is `None` (no compression).
 
 If the optional keyword `zlib` is `True`, the data will be compressed in
 the netCDF file using zlib compression (default `False`).  The use of this option is 
@@ -3700,10 +3699,9 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         (defined previously with `createDimension`). Default is an empty tuple
         which means the variable is a scalar (and therefore has no dimensions).
 
-        **`compression`**: compression algorithm to use. Default None.  Currently
-        'zlib','zstd','bzip2','blosc_' are supported
-        (where  can be one of lz,lz4,lz4hc,zlib,zstd,snappy).
-        Default is `None` (no compression).
+        **`compression`**: compression algorithm to use. Default None.  
+        Currently zlib,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,blosc_zlib,blosc_zstd
+        and blosc_snappy are supported. Default is `None` (no compression).
 
         **`zlib`**: if `True`, data assigned to the `Variable`
         instance is compressed on disk. Default `False`. Deprecated - use

From c2fcf145d8fc64dea02345eef3e794a50ea93663 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 24 Apr 2022 20:49:38 -0600
Subject: [PATCH 0792/1504] update docstrings

---
 docs/index.html          | 20 +++++++++++---------
 src/netCDF4/_netCDF4.pyx | 14 ++++++++------
 2 files changed, 19 insertions(+), 15 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 0fba2894e..3e00dd2f9 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -1612,7 +1612,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -2092,8 +2092,9 @@ 
      In-memory (diskless) Datasets
      
 
 
      If the optional keyword argument compression is set, the data will be
 compressed in the netCDF file using the specified compression algorithm.
-Currently zlib,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,blosc_zlib,blosc_zstd
-and blosc_snappy are supported. Default is None (no compression).
      
+Currently zlib,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,
+blosc_zlib,blosc_zstd and blosc_snappy are supported.
+Default is None (no compression).
      
 
 
      If the optional keyword zlib is True, the data will be compressed in
 the netCDF file using zlib compression (default False).  The use of this option is 
@@ -2108,9 +2109,9 @@ 
      In-memory (diskless) Datasets
      
 significantly improves compression. Default is True. Ignored if
 zlib=False.
      
 
-
      The optional kwargs 'blosc_shuffleandblosc_blocksizeare ignored
-unless the blosc compressor is used.blosc_shufflecan be 0 (no shuffle),
-1 (byte-wise shuffle) or 2 (bit-wise shuffle). Default is 0.blosc_blocksize`
+
      The optional kwargs blosc_shuffle and blosc_blocksize are ignored
+unless the blosc compressor is used. blosc_shuffle can be 0 (no shuffle),
+1 (byte-wise shuffle) or 2 (bit-wise shuffle). Default is 0. blosc_blocksize
 is the tunable blosc blocksize in bytes (Default 0 means the blocksize is
 chosen internally).
      
 
@@ -2878,9 +2879,10 @@ 
      In-memory (diskless) Datasets
      
 (defined previously with createDimension). Default is an empty tuple
 which means the variable is a scalar (and therefore has no dimensions).
      
 
-
      compression: compression algorithm to use. Default None. 
      
-Currently zlib,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,blosc_zlib,blosc_zstd
-and blosc_snappy are supported. Default is None (no compression).
      
+
      compression: compression algorithm to use. 
+Currently zlib,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,
+blosc_zlib,blosc_zstd and blosc_snappy are supported.
+Default is None (no compression).
      
 
 
      zlib: if True, data assigned to the Variable
 instance is compressed on disk. Default False. Deprecated - use
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 8c79020d8..8ca25e00d 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2686,8 +2686,9 @@ is an empty tuple, which means the variable is a scalar.
 
 If the optional keyword argument `compression` is set, the data will be
 compressed in the netCDF file using the specified compression algorithm.
-Currently zlib,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,blosc_zlib,blosc_zstd
-and blosc_snappy are supported. Default is `None` (no compression).
+Currently `zlib`,`zstd`,`bzip2`,`blosc_lz`,`blosc_lz4`,`blosc_lz4hc`,
+`blosc_zlib`,`blosc_zstd` and `blosc_snappy` are supported.
+Default is `None` (no compression).
 
 If the optional keyword `zlib` is `True`, the data will be compressed in
 the netCDF file using zlib compression (default `False`).  The use of this option is 
@@ -2702,7 +2703,7 @@ will be applied before compressing the data (default `True`).  This
 significantly improves compression. Default is `True`. Ignored if
 `zlib=False`.
 
-The optional kwargs 'blosc_shuffle` and `blosc_blocksize` are ignored
+The optional kwargs `blosc_shuffle` and `blosc_blocksize` are ignored
 unless the blosc compressor is used. `blosc_shuffle` can be 0 (no shuffle),
 1 (byte-wise shuffle) or 2 (bit-wise shuffle). Default is 0. `blosc_blocksize`
 is the tunable blosc blocksize in bytes (Default 0 means the blocksize is
@@ -3699,9 +3700,10 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         (defined previously with `createDimension`). Default is an empty tuple
         which means the variable is a scalar (and therefore has no dimensions).
 
-        **`compression`**: compression algorithm to use. Default None.  
-        Currently zlib,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,blosc_zlib,blosc_zstd
-        and blosc_snappy are supported. Default is `None` (no compression).
+        **`compression`**: compression algorithm to use. 
+        Currently `zlib`,`zstd`,`bzip2`,`blosc_lz`,`blosc_lz4`,`blosc_lz4hc`,
+        `blosc_zlib`,`blosc_zstd` and `blosc_snappy` are supported.
+        Default is `None` (no compression).
 
         **`zlib`**: if `True`, data assigned to the `Variable`
         instance is compressed on disk. Default `False`. Deprecated - use

From c23fc9ed23c4d5d1666e16678c5a03251a692156 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 25 Apr 2022 06:47:30 -0600
Subject: [PATCH 0793/1504] remove blosc test if blosc filter not supported

---
 test/run_all.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/test/run_all.py b/test/run_all.py
index df462c10d..447045950 100755
--- a/test/run_all.py
+++ b/test/run_all.py
@@ -31,6 +31,9 @@
 if not __has_bzip2_support__:
     test_files.remove('tst_compression_bzip2.py')
     sys.stdout.write('not running tst_compression_bzip2.py ...\n')
+if not __has_blosc_support__:
+    test_files.remove('tst_compression_blosc.py')
+    sys.stdout.write('not running tst_compression_bzip2.py ...\n')
 
 # Don't run tests that require network connectivity
 if os.getenv('NO_NET'):

From 4ec13583b2c26c8d10facfbbf1b6b5efd767608c Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 25 Apr 2022 08:30:17 -0600
Subject: [PATCH 0794/1504] update docs

---
 docs/index.html          | 14 +++++++++++---
 src/netCDF4/_netCDF4.pyx | 12 ++++++++++--
 2 files changed, 21 insertions(+), 5 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 3e00dd2f9..4787881a1 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -1612,7 +1612,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -2094,7 +2094,11 @@ 
      In-memory (diskless) Datasets
      
 compressed in the netCDF file using the specified compression algorithm.
 Currently zlib,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,
 blosc_zlib,blosc_zstd and blosc_snappy are supported.
-Default is None (no compression).
      
+Default is None (no compression).  All of the compressors except
+zlib use the HDF5 plugin architecture, which requires that the
+environment variable HDF5_PLUGIN_PATH be set to the location of the
+plugins built by netcdf-c (unless the plugins are installed in the
+default location /usr/local/hdf5/lib).
      
 
 
      If the optional keyword zlib is True, the data will be compressed in
 the netCDF file using zlib compression (default False).  The use of this option is 
@@ -2882,7 +2886,11 @@ 
      In-memory (diskless) Datasets
      
 
      compression: compression algorithm to use. 
 Currently zlib,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,
 blosc_zlib,blosc_zstd and blosc_snappy are supported.
-Default is None (no compression).
      
+Default is None (no compression).  All of the compressors except
+zlib use the HDF5 plugin architecture, which requires that the
+environment variable HDF5_PLUGIN_PATH be set to the location of the
+plugins built by netcdf-c (unless the plugins are installed in the
+default location /usr/local/hdf5/lib).
      
 
 
      zlib: if True, data assigned to the Variable
 instance is compressed on disk. Default False. Deprecated - use
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 8ca25e00d..761f3aab6 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2688,7 +2688,11 @@ If the optional keyword argument `compression` is set, the data will be
 compressed in the netCDF file using the specified compression algorithm.
 Currently `zlib`,`zstd`,`bzip2`,`blosc_lz`,`blosc_lz4`,`blosc_lz4hc`,
 `blosc_zlib`,`blosc_zstd` and `blosc_snappy` are supported.
-Default is `None` (no compression).
+Default is `None` (no compression).  All of the compressors except
+`zlib` use the HDF5 plugin architecture, which requires that the
+environment variable `HDF5_PLUGIN_PATH` be set to the location of the
+plugins built by netcdf-c (unless the plugins are installed in the
+default location `/usr/local/hdf5/lib`).
 
 If the optional keyword `zlib` is `True`, the data will be compressed in
 the netCDF file using zlib compression (default `False`).  The use of this option is 
@@ -3703,7 +3707,11 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         **`compression`**: compression algorithm to use. 
         Currently `zlib`,`zstd`,`bzip2`,`blosc_lz`,`blosc_lz4`,`blosc_lz4hc`,
         `blosc_zlib`,`blosc_zstd` and `blosc_snappy` are supported.
-        Default is `None` (no compression).
+        Default is `None` (no compression).  All of the compressors except
+        `zlib` use the HDF5 plugin architecture, which requires that the
+        environment variable `HDF5_PLUGIN_PATH` be set to the location of the
+        plugins built by netcdf-c (unless the plugins are installed in the
+        default location `/usr/local/hdf5/lib`).
 
         **`zlib`**: if `True`, data assigned to the `Variable`
         instance is compressed on disk. Default `False`. Deprecated - use

From 2b1a4bd325f834cfa5630dbd7c08b65e66c086ba Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 25 Apr 2022 14:02:56 -0600
Subject: [PATCH 0795/1504] update

---
 README.md | 8 +++-----
 1 file changed, 3 insertions(+), 5 deletions(-)

diff --git a/README.md b/README.md
index b348c8f88..5158284a3 100644
--- a/README.md
+++ b/README.md
@@ -13,11 +13,9 @@ For details on the latest updates, see the [Changelog](https://github.com/Unidat
 ??/??/2022:  Version [1.6.0](https://pypi.python.org/pypi/netCDF4/1.6.0) released.  Support
 for quantization (bit-grooming and bit-rounding) functionality in netcdf-c 4.9.0 which can
 dramatically improve compression.  Dataset.createVariable now accepts dimension instances (instead
-of just dimension names). 'compression' kwarg added to Dataset.createVariable (in preparation for
-the available of new compression algorithms, such as
- [zstd](https://github.com/facebook/zstd), in netcdf-c).  Currently only 'zlib' supported.
-Opening a Dataset in 'append' mode now creates one if it doesn't already exist (just
-like python open). Working arm64 wheels for Apple M1 Silicon now available on pypi.
+of just dimension names). 'compression' kwarg added to Dataset.createVariable to support 
+new compression algorithms available in netcdf-c 4.9.0 through HDF5 filter plugsins (such
+as zstd, bzip and blosc). Working arm64 wheels for Apple M1 Silicon now available on pypi.
 
 10/31/2021:  Version [1.5.8](https://pypi.python.org/pypi/netCDF4/1.5.8) released. Fix Enum bug, add binary wheels for aarch64 and python 3.10.
 

From ec91dff9a815db5646f35657fd01dad40cbbbdd1 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 25 Apr 2022 20:45:58 -0600
Subject: [PATCH 0796/1504] update

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 5158284a3..99171e273 100644
--- a/README.md
+++ b/README.md
@@ -15,7 +15,7 @@ for quantization (bit-grooming and bit-rounding) functionality in netcdf-c 4.9.0
 dramatically improve compression.  Dataset.createVariable now accepts dimension instances (instead
 of just dimension names). 'compression' kwarg added to Dataset.createVariable to support 
 new compression algorithms available in netcdf-c 4.9.0 through HDF5 filter plugsins (such
-as zstd, bzip and blosc). Working arm64 wheels for Apple M1 Silicon now available on pypi.
+as zstd, bzip2 and blosc). Working arm64 wheels for Apple M1 Silicon now available on pypi.
 
 10/31/2021:  Version [1.5.8](https://pypi.python.org/pypi/netCDF4/1.5.8) released. Fix Enum bug, add binary wheels for aarch64 and python 3.10.
 

From 4dee2b8e7b7f1ae79b74f212d4df7a3abfdd69e6 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 27 Apr 2022 07:35:01 -0600
Subject: [PATCH 0797/1504] remove snappy support in blosc (since it's
 deprecated)

---
 src/netCDF4/_netCDF4.pyx | 15 ++++++++-------
 1 file changed, 8 insertions(+), 7 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 761f3aab6..1625da1a2 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2687,7 +2687,7 @@ is an empty tuple, which means the variable is a scalar.
 If the optional keyword argument `compression` is set, the data will be
 compressed in the netCDF file using the specified compression algorithm.
 Currently `zlib`,`zstd`,`bzip2`,`blosc_lz`,`blosc_lz4`,`blosc_lz4hc`,
-`blosc_zlib`,`blosc_zstd` and `blosc_snappy` are supported.
+`blosc_zlib` and `blosc_zstd` are supported.
 Default is `None` (no compression).  All of the compressors except
 `zlib` use the HDF5 plugin architecture, which requires that the
 environment variable `HDF5_PLUGIN_PATH` be set to the location of the
@@ -3706,7 +3706,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
 
         **`compression`**: compression algorithm to use. 
         Currently `zlib`,`zstd`,`bzip2`,`blosc_lz`,`blosc_lz4`,`blosc_lz4hc`,
-        `blosc_zlib`,`blosc_zstd` and `blosc_snappy` are supported.
+        `blosc_zlib` and `blosc_zstd` are supported.
         Default is `None` (no compression).  All of the compressors except
         `zlib` use the HDF5 plugin architecture, which requires that the
         environment variable `HDF5_PLUGIN_PATH` be set to the location of the
@@ -3822,7 +3822,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         blosc_lz = False
         blosc_lz4 = False
         blosc_lz4hc = False
-        blosc_snappy = False
+        #blosc_snappy = False
         blosc_zlib = False
         blosc_zstd = False
         if compression == 'zlib':
@@ -3837,8 +3837,8 @@ behavior is similar to Fortran or Matlab, but different than numpy.
             blosc_lz4 = True
         elif compression == 'blosc_lz4hc':
             blosc_lz4hc = True
-        elif compression == 'blosc_snappy':
-            blosc_snappy = True
+        #elif compression == 'blosc_snappy':
+        #    blosc_snappy = True
         elif compression == 'blosc_zlib':
             blosc_zlib = True
         elif compression == 'blosc_zstd':
@@ -4004,8 +4004,9 @@ version 4.9.0 or higher netcdf-c with zstandard support, and rebuild netcdf4-pyt
 compression='bzip2' only works with netcdf-c >= 4.9.0.  To enable, install Cython, make sure you have
 version 4.9.0 or higher netcdf-c with bzip2 support, and rebuild netcdf4-python."""
                             raise ValueError(msg)
-                    if blosc_lz or blosc_lz4 or blosc_lz4hc or blosc_zlib or\
-                       blosc_zstd or blosc_snappy:
+                    if blosc_lz or blosc_lz4 or blosc_lz4hc or blosc_zlib or
+                       blosc_zstd:
+                       #blosc_zstd or blosc_snappy:
                         IF HAS_BLOSC_SUPPORT:
                             iblosc_compressor = _blosc_dict[compression]
                             iblosc_shuffle = blosc_shuffle

From de62007b4354801d3b5073bdd612fa5b6fd0dfcf Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 27 Apr 2022 07:46:50 -0600
Subject: [PATCH 0798/1504] test all blosc filters

---
 test/tst_compression_blosc.py | 73 ++++++++++++++++++++++-------------
 1 file changed, 47 insertions(+), 26 deletions(-)

diff --git a/test/tst_compression_blosc.py b/test/tst_compression_blosc.py
index 4324f26c1..591a4c260 100644
--- a/test/tst_compression_blosc.py
+++ b/test/tst_compression_blosc.py
@@ -4,50 +4,71 @@
 import os, tempfile, unittest
 
 ndim = 100000
-filename1 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
-filename2 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
-array = uniform(size=(ndim,))
+filename = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
+datarr = uniform(size=(ndim,))
 
 def write_netcdf(filename,dtype='f8',complevel=6):
     nc = Dataset(filename,'w')
     nc.createDimension('n', ndim)
     foo = nc.createVariable('data',\
+            dtype,('n'),compression=None)
+    foo_lz = nc.createVariable('data_lz',\
+            dtype,('n'),compression='blosc_lz',blosc_shuffle=2,complevel=complevel)
+    foo_lz4 = nc.createVariable('data_lz4',\
             dtype,('n'),compression='blosc_lz4',blosc_shuffle=2,complevel=complevel)
-    foo[:] = array
+    foo_lz4hc = nc.createVariable('data_lz4hc',\
+            dtype,('n'),compression='blosc_lz4hc',blosc_shuffle=2,complevel=complevel)
+    foo_zlib = nc.createVariable('data_zlib',\
+            dtype,('n'),compression='blosc_zlib',blosc_shuffle=2,complevel=complevel)
+    foo_zstd = nc.createVariable('data_zstd',\
+            dtype,('n'),compression='blosc_zstd',blosc_shuffle=2,complevel=complevel)
+    foo_lz[:] = datarr
+    foo_lz4[:] = datarr
+    foo_lz4hc[:] = datarr
+    foo_zlib[:] = datarr
+    foo_zstd[:] = datarr
     nc.close()
 
 class CompressionTestCase(unittest.TestCase):
 
     def setUp(self):
-        self.filename1 = filename1
-        self.filename2 = filename2
-        write_netcdf(self.filename1,complevel=0) # no compression
-        write_netcdf(self.filename2,complevel=4) # with compression
+        self.filename = filename
+        write_netcdf(self.filename,complevel=4) # with compression
 
     def tearDown(self):
         # Remove the temporary files
-        os.remove(self.filename1)
-        os.remove(self.filename2)
+        os.remove(self.filename)
 
     def runTest(self):
-        uncompressed_size = os.stat(self.filename1).st_size
-        # check uncompressed data
-        f = Dataset(self.filename1)
-        size = os.stat(self.filename1).st_size
-        assert_almost_equal(array,f.variables['data'][:])
+        f = Dataset(self.filename)
+        assert_almost_equal(datarr,f.variables['data'][:])
         assert f.variables['data'].filters() ==\
         {'zlib':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
-        assert_almost_equal(size,uncompressed_size)
-        f.close()
-        # check compressed data.
-        f = Dataset(self.filename2)
-        size = os.stat(self.filename2).st_size
-        assert_almost_equal(array,f.variables['data'][:])
-        dtest= {'zlib': False, 'zstd': False, 'bzip2': False, 'blosc':\
-        {'compressor': 'blosc_lz4', 'shuffle': 2, 'blocksize': 800000},\
-        'shuffle': False, 'complevel': 4, 'fletcher32': False}
-        assert f.variables['data'].filters() == dtest
-        assert(size < 0.96*uncompressed_size)
+        assert_almost_equal(datarr,f.variables['data_lz'][:])
+        dtest = {'zlib': False, 'zstd': False, 'bzip2': False, 'blosc':
+                {'compressor': 'blosc_lz', 'shuffle': 2, 'blocksize': 800000},
+                'shuffle': False, 'complevel': 4, 'fletcher32': False}
+        assert f.variables['data_lz'].filters() == dtest
+        assert_almost_equal(datarr,f.variables['data_lz4'][:])
+        dtest = {'zlib': False, 'zstd': False, 'bzip2': False, 'blosc':
+                {'compressor': 'blosc_lz4', 'shuffle': 2, 'blocksize': 800000},
+                'shuffle': False, 'complevel': 4, 'fletcher32': False}
+        assert f.variables['data_lz4'].filters() == dtest
+        assert_almost_equal(datarr,f.variables['data_lz4hc'][:])
+        dtest = {'zlib': False, 'zstd': False, 'bzip2': False, 'blosc':
+                {'compressor': 'blosc_lz4hc', 'shuffle': 2, 'blocksize': 800000},
+                'shuffle': False, 'complevel': 4, 'fletcher32': False}
+        assert f.variables['data_lz4hc'].filters() == dtest
+        assert_almost_equal(datarr,f.variables['data_zlib'][:])
+        dtest = {'zlib': False, 'zstd': False, 'bzip2': False, 'blosc':
+                {'compressor': 'blosc_zlib', 'shuffle': 2, 'blocksize': 800000},
+                'shuffle': False, 'complevel': 4, 'fletcher32': False}
+        assert f.variables['data_zlib'].filters() == dtest
+        assert_almost_equal(datarr,f.variables['data_zstd'][:])
+        dtest = {'zlib': False, 'zstd': False, 'bzip2': False, 'blosc':
+                {'compressor': 'blosc_zstd', 'shuffle': 2, 'blocksize': 800000},
+                'shuffle': False, 'complevel': 4, 'fletcher32': False}
+        assert f.variables['data_zstd'].filters() == dtest
         f.close()
 
 if __name__ == '__main__':

From 313524f16e58ec1c5a9b00ea7e23d27b5452288c Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 27 Apr 2022 07:51:28 -0600
Subject: [PATCH 0799/1504] turn blosc shuffle on by default (as in pytables)

---
 src/netCDF4/_netCDF4.pyx | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 1625da1a2..da328d18b 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2645,7 +2645,7 @@ datatype."""
     def createVariable(self, varname, datatype, dimensions=(), 
             compression=None, zlib=False,
             complevel=4, shuffle=True,
-            blosc_shuffle=0, blosc_blocksize=0, fletcher32=False, contiguous=False,
+            blosc_shuffle=1, blosc_blocksize=0, fletcher32=False, contiguous=False,
             chunksizes=None, endian='native', least_significant_digit=None,
             significant_digits=None,quantize_mode='BitGroom',fill_value=None, chunk_cache=None):
         """
@@ -2709,7 +2709,7 @@ significantly improves compression. Default is `True`. Ignored if
 
 The optional kwargs `blosc_shuffle` and `blosc_blocksize` are ignored
 unless the blosc compressor is used. `blosc_shuffle` can be 0 (no shuffle),
-1 (byte-wise shuffle) or 2 (bit-wise shuffle). Default is 0. `blosc_blocksize`
+1 (byte-wise shuffle) or 2 (bit-wise shuffle). Default is 1. `blosc_blocksize`
 is the tunable blosc blocksize in bytes (Default 0 means the blocksize is
 chosen internally).
 
@@ -3665,13 +3665,13 @@ behavior is similar to Fortran or Matlab, but different than numpy.
 
     def __init__(self, grp, name, datatype, dimensions=(),
             compression=None, zlib=False,
-            complevel=4, shuffle=True, blosc_shuffle=0, blosc_blocksize=0,
+            complevel=4, shuffle=True, blosc_shuffle=1, blosc_blocksize=0,
             fletcher32=False, contiguous=False,
             chunksizes=None, endian='native', least_significant_digit=None,
             significant_digits=None,quantize_mode='BitGroom',fill_value=None, chunk_cache=None, **kwargs):
         """
         **`__init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False,
-        complevel=4, shuffle=True, blosc_shuffle=0, blosc_blocksize=0, fletcher32=False, contiguous=False,
+        complevel=4, shuffle=True, blosc_shuffle=1, blosc_blocksize=0, fletcher32=False, contiguous=False,
         chunksizes=None, endian='native',
         least_significant_digit=None,fill_value=None,chunk_cache=None)`**
 
@@ -3727,7 +3727,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         **`blosc_shuffle`**: shuffle filter inside blosc compressor (only
         relevant if compression kwarg set to one of the blosc compressors).
         Can be 0 (no blosc shuffle), 1 (bytewise shuffle) or 2 (bitwise
-        shuffle)). Default is 0.
+        shuffle)). Default is 1.
 
         **`blosc_blocksize`**: tunable blocksize in bytes for blosc
         compressors. Default of 0 means blosc library chooses a blocksize.

From c29d9c23471e08505ea61338bfbb9b9c04d8db94 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 27 Apr 2022 08:10:17 -0600
Subject: [PATCH 0800/1504] update

---
 src/netCDF4/_netCDF4.pyx | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index da328d18b..6b8744741 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4004,9 +4004,7 @@ version 4.9.0 or higher netcdf-c with zstandard support, and rebuild netcdf4-pyt
 compression='bzip2' only works with netcdf-c >= 4.9.0.  To enable, install Cython, make sure you have
 version 4.9.0 or higher netcdf-c with bzip2 support, and rebuild netcdf4-python."""
                             raise ValueError(msg)
-                    if blosc_lz or blosc_lz4 or blosc_lz4hc or blosc_zlib or
-                       blosc_zstd:
-                       #blosc_zstd or blosc_snappy:
+                    if blosc_zstd or blosc_lz or blosc_lz4 or blosc_lz4hc or blosc_zlib:
                         IF HAS_BLOSC_SUPPORT:
                             iblosc_compressor = _blosc_dict[compression]
                             iblosc_shuffle = blosc_shuffle

From dbd6450761d5fd64f0f8169af3f9e2082f2874bc Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 27 Apr 2022 09:15:53 -0600
Subject: [PATCH 0801/1504] update

---
 Changelog | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/Changelog b/Changelog
index bbb3dfe03..e8272c510 100644
--- a/Changelog
+++ b/Changelog
@@ -13,8 +13,8 @@
    directive to 3 in setup.py.
  * add 'compression' kwarg to createVariable to enable new compression
    functionality in netcdf-c 4.9.0.  'None','zlib','zstd','bzip2'
-   'blosc_lz','blosc_lz4','blosc_lz4hc','blosc_zlib','blosc_zstd' and 
-   'blosc_snappy' are currently supported. 'blosc_shuffle' and
+   'blosc_lz','blosc_lz4','blosc_lz4hc','blosc_zlib' and 'blosc_zstd'
+   are currently supported. 'blosc_shuffle' and
    'blosc_blocksize' kwargs also added.
    compression='zlib' is equivalent to (the now deprecated) zlib=True.
  * MFDataset did not aggregate 'name' variable attribute (issue #1153).

From f896a2a3cf099710094c4f7e35c0907e8dbd66be Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 27 Apr 2022 09:18:02 -0600
Subject: [PATCH 0802/1504] update docs

---
 docs/index.html | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 4787881a1..cf86fbfa2 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -1612,7 +1612,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -2093,7 +2093,7 @@ 
      In-memory (diskless) Datasets
      
 
      If the optional keyword argument compression is set, the data will be
 compressed in the netCDF file using the specified compression algorithm.
 Currently zlib,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,
-blosc_zlib,blosc_zstd and blosc_snappy are supported.
+blosc_zlib and blosc_zstd are supported.
 Default is None (no compression).  All of the compressors except
 zlib use the HDF5 plugin architecture, which requires that the
 environment variable HDF5_PLUGIN_PATH be set to the location of the
@@ -2115,7 +2115,7 @@ 
      In-memory (diskless) Datasets
      
 
 
      The optional kwargs blosc_shuffle and blosc_blocksize are ignored
 unless the blosc compressor is used. blosc_shuffle can be 0 (no shuffle),
-1 (byte-wise shuffle) or 2 (bit-wise shuffle). Default is 0. blosc_blocksize
+1 (byte-wise shuffle) or 2 (bit-wise shuffle). Default is 1. blosc_blocksize
 is the tunable blosc blocksize in bytes (Default 0 means the blocksize is
 chosen internally).
      
 
@@ -2850,7 +2850,7 @@ 
      In-memory (diskless) Datasets
      
 
         
             
      __init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False,
-complevel=4, shuffle=True, blosc_shuffle=0, blosc_blocksize=0, fletcher32=False, contiguous=False,
+complevel=4, shuffle=True, blosc_shuffle=1, blosc_blocksize=0, fletcher32=False, contiguous=False,
 chunksizes=None, endian='native',
 least_significant_digit=None,fill_value=None,chunk_cache=None)
      
 
@@ -2885,7 +2885,7 @@ 
      In-memory (diskless) Datasets
      
 
 
      compression: compression algorithm to use. 
 Currently zlib,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,
-blosc_zlib,blosc_zstd and blosc_snappy are supported.
+blosc_zlib and blosc_zstd are supported.
 Default is None (no compression).  All of the compressors except
 zlib use the HDF5 plugin architecture, which requires that the
 environment variable HDF5_PLUGIN_PATH be set to the location of the
@@ -2906,7 +2906,7 @@ 
      In-memory (diskless) Datasets
      
 
      blosc_shuffle: shuffle filter inside blosc compressor (only
 relevant if compression kwarg set to one of the blosc compressors).
 Can be 0 (no blosc shuffle), 1 (bytewise shuffle) or 2 (bitwise
-shuffle)). Default is 0.
      
+shuffle)). Default is 1.
      
 
 
      blosc_blocksize: tunable blocksize in bytes for blosc
 compressors. Default of 0 means blosc library chooses a blocksize.
      

From f4ec3f265c905e230492b503024056b54325df8a Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Wed, 27 Apr 2022 11:47:26 -0600
Subject: [PATCH 0803/1504] update docstrings

---
 src/netCDF4/_netCDF4.pyx | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 6b8744741..abe44b7b8 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2055,7 +2055,7 @@ strings.
 
         **`mode`**: access mode. `r` means read-only; no data can be
         modified. `w` means write; a new file is created, an existing file with
-        the same name is deleted. 'x' means write, but fail if an existing
+        the same name is deleted. `x` means write, but fail if an existing
         file with the same name already exists. `a` and `r+` mean append; 
         an existing file is opened for reading and writing, if 
         file does not exist already, one is created.
@@ -2070,7 +2070,7 @@ strings.
         **`clobber`**: if `True` (default), opening a file with `mode='w'`
         will clobber an existing file with the same name.  if `False`, an
         exception will be raised if a file with the same name already exists.
-        mode='x' is identical to mode='w' with clobber=False.
+        mode=`x` is identical to mode=`w` with clobber=False.
 
         **`format`**: underlying file format (one of `'NETCDF4',
         'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC'`, `'NETCDF3_64BIT_OFFSET'` or
@@ -2113,14 +2113,14 @@ strings.
         rendered unusable when the parent Dataset instance is garbage collected.
 
         **`memory`**: if not `None`, create or open an in-memory Dataset.
-        If mode = 'r', the memory kwarg must contain a memory buffer object
+        If mode = `r`, the memory kwarg must contain a memory buffer object
         (an object that supports the python buffer interface).
         The Dataset will then be created with contents taken from this block of memory.
-        If mode = 'w', the memory kwarg should contain the anticipated size
+        If mode = `w`, the memory kwarg should contain the anticipated size
         of the Dataset in bytes (used only for NETCDF3 files).  A memory
         buffer containing a copy of the Dataset is returned by the
-        `Dataset.close` method. Requires netcdf-c version 4.4.1 for mode='r,
-        netcdf-c 4.6.2 for mode='w'. To persist the file to disk, the raw
+        `Dataset.close` method. Requires netcdf-c version 4.4.1 for mode=`r`
+        netcdf-c 4.6.2 for mode=`w`. To persist the file to disk, the raw
         bytes from the returned buffer can be written into a binary file.
         The Dataset can also be re-opened using this memory buffer.
 
@@ -2334,7 +2334,7 @@ strings.
                 else:
                     ierr = nc_create(path, NC_SHARE | NC_NOCLOBBER, &grpid)
         else:
-            raise ValueError("mode must be 'w', 'r', 'a' or 'r+', got '%s'" % mode)
+            raise ValueError("mode must be 'w', 'x', 'r', 'a' or 'r+', got '%s'" % mode)
 
         _ensure_nc_success(ierr, err_cls=IOError, filename=path)
 

From 7c6893add230254bd52de6b6efa5e464d64be3a2 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 29 Apr 2022 12:27:59 -0600
Subject: [PATCH 0804/1504] dont fail in filter method if plugin not found

---
 src/netCDF4/_netCDF4.pyx | 10 ++++++----
 1 file changed, 6 insertions(+), 4 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index abe44b7b8..145e36a7c 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4419,15 +4419,18 @@ return dictionary containing HDF5 filter parameters."""
         IF HAS_ZSTANDARD_SUPPORT:
             ierr = nc_inq_var_zstandard(self._grpid, self._varid, &izstd,\
                     &icomplevel_zstd)
-            _ensure_nc_success(ierr)
+            if ierr != 0: izstd=0
+            # _ensure_nc_success(ierr)
         IF HAS_BZIP2_SUPPORT:
             ierr = nc_inq_var_bzip2(self._grpid, self._varid, &ibzip2,\
                     &icomplevel_bzip2)
-            _ensure_nc_success(ierr)
+            if ierr != 0: ibzip2=0
+            #_ensure_nc_success(ierr)
         IF HAS_BLOSC_SUPPORT:
             ierr = nc_inq_var_blosc(self._grpid, self._varid, &iblosc,\
                     &iblosc_compressor,&iblosc_complevel,&iblosc_blocksize,&iblosc_shuffle)
-            _ensure_nc_success(ierr)
+            if ierr != 0: iblosc=0
+            #_ensure_nc_success(ierr)
         if ideflate:
             filtdict['zlib']=True
             filtdict['complevel']=icomplevel
@@ -4438,7 +4441,6 @@ return dictionary containing HDF5 filter parameters."""
             filtdict['bzip2']=True
             filtdict['complevel']=icomplevel_bzip2
         if iblosc:
-            #filtdict['blosc']=True
             blosc_compressor = iblosc_compressor
             filtdict['blosc']={'compressor':_blosc_dict_inv[blosc_compressor],'shuffle':iblosc_shuffle,'blocksize':iblosc_blocksize}
             filtdict['complevel']=iblosc_complevel

From 534fc0ef0ad7011ddd26e5b3daef3dc49281a331 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 29 Apr 2022 13:18:11 -0600
Subject: [PATCH 0805/1504] update

---
 Changelog | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/Changelog b/Changelog
index e8272c510..2128d23bd 100644
--- a/Changelog
+++ b/Changelog
@@ -17,6 +17,8 @@
    are currently supported. 'blosc_shuffle' and
    'blosc_blocksize' kwargs also added.
    compression='zlib' is equivalent to (the now deprecated) zlib=True.
+   Using new compressors requires setting HDF5_PLUGIN_PATH to point to 
+   the installation location of the netcdf-c filter plugins.
  * MFDataset did not aggregate 'name' variable attribute (issue #1153).
  * issue warning instead of raising an exception if missing_value or
    _FillValue can't be cast to the variable type when creating a 

From 97a70f802b1ee72e52cd369a6501080bd0225ed8 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 3 May 2022 13:32:36 -0700
Subject: [PATCH 0806/1504] add szip compression support

---
 include/netCDF4.pxi          |  9 +++++--
 setup.py                     | 14 +++++++++--
 src/netCDF4/_netCDF4.pyx     | 48 ++++++++++++++++++++++++++++++------
 test/run_all.py              |  6 ++++-
 test/tst_compression_szip.py | 45 +++++++++++++++++++++++++++++++++
 5 files changed, 109 insertions(+), 13 deletions(-)
 create mode 100644 test/tst_compression_szip.py

diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index a5ff730be..8be538234 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -216,8 +216,6 @@ cdef extern from "netcdf.h":
         NC_ENDIAN_NATIVE 
         NC_ENDIAN_LITTLE 
         NC_ENDIAN_BIG 
-        NC_SZIP_EC_OPTION_MASK  # entropy encoding
-        NC_SZIP_NN_OPTION_MASK  # nearest neighbor encoding
     const_char_ptr *nc_inq_libvers() nogil
     const_char_ptr *nc_strerror(int ncerr)
     int nc_create(char *path, int cmode, int *ncidp)
@@ -701,6 +699,13 @@ IF HAS_QUANTIZATION_SUPPORT:
         int nc_def_var_quantize(int ncid, int varid, int quantize_mode, int nsd) 
         int nc_inq_var_quantize(int ncid, int varid, int *quantize_modep, int *nsdp) nogil
 
+IF HAS_SZIP_SUPPORT:
+    cdef extern from "netcdf.h":
+        int nc_def_var_quantize(int ncid, int varid, int quantize_mode, int nsd) 
+        int nc_inq_var_quantize(int ncid, int varid, int *quantize_modep, int *nsdp) nogil
+        int nc_def_var_szip(int ncid, int varid, int options_mask, int pixels_per_bloc)
+        int nc_inq_var_szip(int ncid, int varid, int *options_maskp, int *pixels_per_blockp)
+
 IF HAS_ZSTANDARD_SUPPORT:
     cdef extern from "netcdf_filter.h":
         cdef enum:
diff --git a/setup.py b/setup.py
index 5213af649..9cf48528e 100644
--- a/setup.py
+++ b/setup.py
@@ -65,6 +65,7 @@ def check_api(inc_dirs,netcdf_lib_version):
     has_parallel_support = False
     has_parallel4_support = False
     has_pnetcdf_support = False
+    has_szip_support = False
     has_quantize = False
     has_zstandard = False
     has_bzip2 = False
@@ -124,6 +125,8 @@ def check_api(inc_dirs,netcdf_lib_version):
                     has_parallel4_support = bool(int(line.split()[2]))
                 if line.startswith('#define NC_HAS_PNETCDF'):
                     has_pnetcdf_support = bool(int(line.split()[2]))
+                if line.startswith('#define NC_HAS_SZIP_WRITE'):
+                    has_szip_support = bool(int(line.split()[2]))
         # NC_HAS_PARALLEL4 missing in 4.6.1 (issue #964)
         if not has_parallel4_support and has_parallel_support and not has_pnetcdf_support:
             has_parallel4_support = True
@@ -136,7 +139,7 @@ def check_api(inc_dirs,netcdf_lib_version):
 
     return has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \
            has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \
-           has_parallel4_support, has_pnetcdf_support, has_quantize, \
+           has_parallel4_support, has_pnetcdf_support, has_szip_support, has_quantize, \
            has_zstandard, has_bzip2, has_blosc
 
 
@@ -550,7 +553,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     # this determines whether renameGroup and filepath methods will work.
     has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \
     has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \
-    has_parallel4_support, has_pnetcdf_support, has_quantize, \
+    has_parallel4_support, has_pnetcdf_support, has_szip_support, has_quantize, \
     has_zstandard, has_bzip2, has_blosc = \
     check_api(inc_dirs,netcdf_lib_version)
     # for netcdf 4.4.x CDF5 format is always enabled.
@@ -651,6 +654,13 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         sys.stdout.write('netcdf lib does not have blosc compression functions\n')
         f.write('DEF HAS_BLOSC_SUPPORT = 0\n')
 
+    if has_szip_support:
+        sys.stdout.write('netcdf lib has szip compression functions\n')
+        f.write('DEF HAS_SZIP_SUPPORT = 1\n')
+    else:
+        sys.stdout.write('netcdf lib does not have szip compression functions\n')
+        f.write('DEF HAS_SZIP_SUPPORT = 0\n')
+
     f.close()
 
     if has_parallel4_support or has_pnetcdf_support:
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 145e36a7c..415bdcd2d 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1372,6 +1372,8 @@ _cmode_dict  = {'NETCDF3_CLASSIC' : NC_CLASSIC_MODEL,
 # dicts for blosc compressors.
 _blosc_dict={'blosc_lz':0,'blosc_lz4':1,'blosc_lz4hc':2,'blosc_snappy':3,'blosc_zlib':4,'blosc_zstd':5}
 _blosc_dict_inv = {v: k for k, v in _blosc_dict.items()}
+_szip_dict = {'ec': 4, 'nn': 32}
+_szip_dict_inv = {v: k for k, v in _szip_dict.items()}
 IF HAS_CDF5_FORMAT:
     # NETCDF3_64BIT deprecated, saved for compatibility.
     # use NETCDF3_64BIT_OFFSET instead.
@@ -2645,12 +2647,14 @@ datatype."""
     def createVariable(self, varname, datatype, dimensions=(), 
             compression=None, zlib=False,
             complevel=4, shuffle=True,
+            szip_mask='nn',szip_pixels_per_block=8,
             blosc_shuffle=1, blosc_blocksize=0, fletcher32=False, contiguous=False,
             chunksizes=None, endian='native', least_significant_digit=None,
             significant_digits=None,quantize_mode='BitGroom',fill_value=None, chunk_cache=None):
         """
 **`createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False,
 complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None,
+szip_mask='nn', szip_pixels_per_block=8, blosc_shuffle=1, blosc_blocksize=0,
 endian='native', least_significant_digit=None, significant_digits=None, quantize_mode='BitGroom',
 fill_value=None, chunk_cache=None)`**
 
@@ -2686,10 +2690,10 @@ is an empty tuple, which means the variable is a scalar.
 
 If the optional keyword argument `compression` is set, the data will be
 compressed in the netCDF file using the specified compression algorithm.
-Currently `zlib`,`zstd`,`bzip2`,`blosc_lz`,`blosc_lz4`,`blosc_lz4hc`,
+Currently `zlib`,`szip`, `zstd`,`bzip2`,`blosc_lz`,`blosc_lz4`,`blosc_lz4hc`,
 `blosc_zlib` and `blosc_zstd` are supported.
 Default is `None` (no compression).  All of the compressors except
-`zlib` use the HDF5 plugin architecture, which requires that the
+`zlib` and `szip` use the HDF5 plugin architecture, which requires that the
 environment variable `HDF5_PLUGIN_PATH` be set to the location of the
 plugins built by netcdf-c (unless the plugins are installed in the
 default location `/usr/local/hdf5/lib`).
@@ -2703,7 +2707,7 @@ the level of compression desired (default 4). Ignored if `compression=None`.
 A value of zero disables compression.
 
 If the optional keyword `shuffle` is `True`, the HDF5 shuffle filter
-will be applied before compressing the data (default `True`).  This
+will be applied before compressing the data with zlib (default `True`).  This
 significantly improves compression. Default is `True`. Ignored if
 `zlib=False`.
 
@@ -2824,6 +2828,7 @@ is the number of variable dimensions."""
         # create variable.
         group.variables[varname] = Variable(group, varname, datatype,
         dimensions=dimensions, compression=compression, zlib=zlib, complevel=complevel, shuffle=shuffle,
+        szip_mask=szip_mask, szip_pixels_per_block=szip_pixels_per_block,
         blosc_shuffle=blosc_shuffle,blosc_blocksize=blosc_blocksize,
         fletcher32=fletcher32, contiguous=contiguous, chunksizes=chunksizes,
         endian=endian, least_significant_digit=least_significant_digit,
@@ -3665,13 +3670,15 @@ behavior is similar to Fortran or Matlab, but different than numpy.
 
     def __init__(self, grp, name, datatype, dimensions=(),
             compression=None, zlib=False,
-            complevel=4, shuffle=True, blosc_shuffle=1, blosc_blocksize=0,
+            complevel=4, shuffle=True, szip_mask='nn', szip_pixels_per_block=8,
+            blosc_shuffle=1, blosc_blocksize=0,
             fletcher32=False, contiguous=False,
             chunksizes=None, endian='native', least_significant_digit=None,
             significant_digits=None,quantize_mode='BitGroom',fill_value=None, chunk_cache=None, **kwargs):
         """
         **`__init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False,
-        complevel=4, shuffle=True, blosc_shuffle=1, blosc_blocksize=0, fletcher32=False, contiguous=False,
+        complevel=4, shuffle=True, szip_mask='nn', szip_pixels_per_block=8,
+        blosc_shuffle=1, blosc_blocksize=0, fletcher32=False, contiguous=False,
         chunksizes=None, endian='native',
         least_significant_digit=None,fill_value=None,chunk_cache=None)`**
 
@@ -3705,7 +3712,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         which means the variable is a scalar (and therefore has no dimensions).
 
         **`compression`**: compression algorithm to use. 
-        Currently `zlib`,`zstd`,`bzip2`,`blosc_lz`,`blosc_lz4`,`blosc_lz4hc`,
+        Currently `zlib`,`szip`, `zstd`,`bzip2`,`blosc_lz`,`blosc_lz4`,`blosc_lz4hc`,
         `blosc_zlib` and `blosc_zstd` are supported.
         Default is `None` (no compression).  All of the compressors except
         `zlib` use the HDF5 plugin architecture, which requires that the
@@ -3722,7 +3729,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         Ignored if `compression=None`. A value of 0 disables compression.
 
         **`shuffle`**: if `True`, the HDF5 shuffle filter is applied
-        to improve compression. Default `True`. Ignored if `compression=None`.
+        to improve zlib compression. Default `True`. Ignored unless `compression = 'zlib'`.
 
         **`blosc_shuffle`**: shuffle filter inside blosc compressor (only
         relevant if compression kwarg set to one of the blosc compressors).
@@ -3800,6 +3807,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         """
         cdef int ierr, ndims, icontiguous, icomplevel, numdims, _grpid, nsd,
         cdef unsigned int iblosc_complevel,iblosc_blocksize,iblosc_compressor,iblosc_shuffle
+        cdef int iszip_mask, iszip_pixels_per_block
         cdef char namstring[NC_MAX_NAME+1]
         cdef char *varname
         cdef nc_type xtype
@@ -3817,6 +3825,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         if not complevel:
             compression = None
         zlib = False
+        szip = False
         zstd = False
         bzip2 = False
         blosc_lz = False
@@ -3827,6 +3836,8 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         blosc_zstd = False
         if compression == 'zlib':
             zlib = True
+        elif compression == 'szip':
+            szip = True
         elif compression == 'zstd':
             zstd = True
         elif compression == 'bzip2':
@@ -3980,6 +3991,18 @@ behavior is similar to Fortran or Matlab, but different than numpy.
                         if ierr != NC_NOERR:
                             if grp.data_model != 'NETCDF4': grp._enddef()
                             _ensure_nc_success(ierr)
+                    if szip:
+                        IF HAS_SZIP_SUPPORT:
+                            iszip_mask = _szip_dict[szip_mask]
+                            iszip_pixels_per_block = szip_pixels_per_block
+                            ierr = nc_def_var_szip(self._grpid, self._varid, iszip_mask, iszip_pixels_per_block)
+                            if ierr != NC_NOERR:
+                                if grp.data_model != 'NETCDF4': grp._enddef()
+                                _ensure_nc_success(ierr)
+                        ELSE:
+                            msg = """
+compression='szip' only works if linked version of hdf5 has szip functionality enabled"""
+                            raise ValueError(msg)
                     if zstd:
                         IF HAS_ZSTANDARD_SUPPORT:
                             icomplevel = complevel
@@ -4407,8 +4430,10 @@ return dictionary containing HDF5 filter parameters."""
         cdef int izstd=0
         cdef int ibzip2=0
         cdef int iblosc=0
+        cdef int iszip=0
         cdef unsigned int iblosc_complevel,iblosc_blocksize,iblosc_compressor,iblosc_shuffle
-        filtdict = {'zlib':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
+        cdef int iszip_mask, iszip_pixels_per_block
+        filtdict = {'zlib':False,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
         if self._grp.data_model not in ['NETCDF4_CLASSIC','NETCDF4']: return
         with nogil:
             ierr = nc_inq_var_deflate(self._grpid, self._varid, &ishuffle, &ideflate, &icomplevel)
@@ -4431,6 +4456,11 @@ return dictionary containing HDF5 filter parameters."""
                     &iblosc_compressor,&iblosc_complevel,&iblosc_blocksize,&iblosc_shuffle)
             if ierr != 0: iblosc=0
             #_ensure_nc_success(ierr)
+        IF HAS_SZIP_SUPPORT:
+            ierr = nc_inq_var_szip(self._grpid, self._varid, &iszip_mask,\
+                    &iszip_pixels_per_block)
+            if ierr != 0: iszip=0
+            #_ensure_nc_success(ierr)
         if ideflate:
             filtdict['zlib']=True
             filtdict['complevel']=icomplevel
@@ -4444,6 +4474,8 @@ return dictionary containing HDF5 filter parameters."""
             blosc_compressor = iblosc_compressor
             filtdict['blosc']={'compressor':_blosc_dict_inv[blosc_compressor],'shuffle':iblosc_shuffle,'blocksize':iblosc_blocksize}
             filtdict['complevel']=iblosc_complevel
+        if iszip:
+            filtdict['szip']={'mask':_szip_dict_inv[iszip_mask],'pixels_per_block':iszip_pixels_per_block}
         if ishuffle:
             filtdict['shuffle']=True
         if ifletcher32:
diff --git a/test/run_all.py b/test/run_all.py
index 447045950..a76764d97 100755
--- a/test/run_all.py
+++ b/test/run_all.py
@@ -3,7 +3,8 @@
 from netCDF4 import __has_cdf5_format__, __has_nc_inq_path__, __has_nc_create_mem__, \
                     __has_parallel4_support__, __has_pnetcdf_support__, \
                     __has_zstandard_support__, __has_bzip2_support__, \
-                    __has_blosc_support__,__has_quantization_support__
+                    __has_blosc_support__,__has_quantization_support__,\
+                    __has_szip_support__
 
 # can also just run
 # python -m unittest discover . 'tst*py'
@@ -34,6 +35,9 @@
 if not __has_blosc_support__:
     test_files.remove('tst_compression_blosc.py')
     sys.stdout.write('not running tst_compression_bzip2.py ...\n')
+if not __has_szip_support__:
+    test_files.remove('tst_compression_szip.py')
+    sys.stdout.write('not running tst_compression_szip.py ...\n')
 
 # Don't run tests that require network connectivity
 if os.getenv('NO_NET'):
diff --git a/test/tst_compression_szip.py b/test/tst_compression_szip.py
new file mode 100644
index 000000000..a09cffbba
--- /dev/null
+++ b/test/tst_compression_szip.py
@@ -0,0 +1,45 @@
+from numpy.random.mtrand import uniform
+from netCDF4 import Dataset
+from numpy.testing import assert_almost_equal
+import os, tempfile, unittest
+
+ndim = 100000
+filename = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
+datarr = uniform(size=(ndim,))
+
+def write_netcdf(filename,dtype='f8'):
+    nc = Dataset(filename,'w')
+    nc.createDimension('n', ndim)
+    foo = nc.createVariable('data',\
+            dtype,('n'),compression=None)
+    foo_szip = nc.createVariable('data_szip',\
+            dtype,('n'),compression='szip',szip_mask='ec',szip_pixels_per_block=32)
+    foo[:] = datarr
+    foo_szip[:] = datarr
+    nc.close()
+
+class CompressionTestCase(unittest.TestCase):
+
+    def setUp(self):
+        self.filename = filename
+        write_netcdf(self.filename)
+
+    def tearDown(self):
+        # Remove the temporary files
+        os.remove(self.filename)
+
+    def runTest(self):
+        f = Dataset(self.filename)
+        assert_almost_equal(datarr,f.variables['data'][:])
+        assert f.variables['data'].filters() ==\
+        {'zlib':False,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
+        assert_almost_equal(datarr,f.variables['data_szip'][:])
+        dtest = {'zlib': False, 'zstd': False, 'bzip2': False, 'blosc': False, 'szip':
+                {'mask': 'ec', 'pixels_per_block': 32},
+                'shuffle': False, 'complevel': 4, 'fletcher32': False}
+        print(f.variables['data_szip'].filters())
+        #assert f.variables['data_szip'].filters() == dtest
+        f.close()
+
+if __name__ == '__main__':
+    unittest.main()

From 9647a7df07112750d26f1d18481359fa461a4e18 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 3 May 2022 13:33:48 -0700
Subject: [PATCH 0807/1504] add szip support

---
 src/netCDF4/__init__.py  | 2 +-
 src/netCDF4/_netCDF4.pyx | 1 +
 2 files changed, 2 insertions(+), 1 deletion(-)

diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py
index b79cf6323..f518b128e 100644
--- a/src/netCDF4/__init__.py
+++ b/src/netCDF4/__init__.py
@@ -9,6 +9,6 @@
                        __has_nc_create_mem__, __has_cdf5_format__,
                        __has_parallel4_support__, __has_pnetcdf_support__,
                        __has_quantization_support__, __has_zstandard_support__,
-                       __has_bzip2_support__, __has_blosc_support__)
+                       __has_bzip2_support__, __has_blosc_support__, __has_szip_support__)
 __all__ =\
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 415bdcd2d..8ac8dbd61 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1324,6 +1324,7 @@ __has_quantization_support__ = HAS_QUANTIZATION_SUPPORT
 __has_zstandard_support__ = HAS_ZSTANDARD_SUPPORT
 __has_bzip2_support__ = HAS_BZIP2_SUPPORT
 __has_blosc_support__ = HAS_BLOSC_SUPPORT
+__has_szip_support__ = HAS_SZIP_SUPPORT
 _needsworkaround_issue485 = __netcdf4libversion__ < "4.4.0" or \
                (__netcdf4libversion__.startswith("4.4.0") and \
                 "-development" in __netcdf4libversion__)

From 16c220661211658512bc7e3461bbd492d953fef2 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 3 May 2022 13:47:20 -0700
Subject: [PATCH 0808/1504] update

---
 src/netCDF4/_netCDF4.pyx      | 24 ++++++++++++------------
 test/tst_compression.py       | 18 +++++++++---------
 test/tst_compression_blosc.py | 12 ++++++------
 test/tst_compression_bzip2.py |  4 ++--
 test/tst_compression_szip.py  |  4 ++--
 test/tst_compression_zstd.py  |  4 ++--
 6 files changed, 33 insertions(+), 33 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 8ac8dbd61..938514c15 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1370,7 +1370,7 @@ _format_dict  = {'NETCDF3_CLASSIC' : NC_FORMAT_CLASSIC,
 _cmode_dict  = {'NETCDF3_CLASSIC' : NC_CLASSIC_MODEL,
                 'NETCDF4_CLASSIC' : NC_CLASSIC_MODEL | NC_NETCDF4,
                 'NETCDF4'         : NC_NETCDF4}
-# dicts for blosc compressors.
+# dicts for blosc, szip compressors.
 _blosc_dict={'blosc_lz':0,'blosc_lz4':1,'blosc_lz4hc':2,'blosc_snappy':3,'blosc_zlib':4,'blosc_zstd':5}
 _blosc_dict_inv = {v: k for k, v in _blosc_dict.items()}
 _szip_dict = {'ec': 4, 'nn': 32}
@@ -2648,14 +2648,14 @@ datatype."""
     def createVariable(self, varname, datatype, dimensions=(), 
             compression=None, zlib=False,
             complevel=4, shuffle=True,
-            szip_mask='nn',szip_pixels_per_block=8,
+            szip_coding='nn',szip_pixels_per_block=8,
             blosc_shuffle=1, blosc_blocksize=0, fletcher32=False, contiguous=False,
             chunksizes=None, endian='native', least_significant_digit=None,
             significant_digits=None,quantize_mode='BitGroom',fill_value=None, chunk_cache=None):
         """
 **`createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False,
 complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None,
-szip_mask='nn', szip_pixels_per_block=8, blosc_shuffle=1, blosc_blocksize=0,
+szip_coding='nn', szip_pixels_per_block=8, blosc_shuffle=1, blosc_blocksize=0,
 endian='native', least_significant_digit=None, significant_digits=None, quantize_mode='BitGroom',
 fill_value=None, chunk_cache=None)`**
 
@@ -2829,7 +2829,7 @@ is the number of variable dimensions."""
         # create variable.
         group.variables[varname] = Variable(group, varname, datatype,
         dimensions=dimensions, compression=compression, zlib=zlib, complevel=complevel, shuffle=shuffle,
-        szip_mask=szip_mask, szip_pixels_per_block=szip_pixels_per_block,
+        szip_coding=szip_coding, szip_pixels_per_block=szip_pixels_per_block,
         blosc_shuffle=blosc_shuffle,blosc_blocksize=blosc_blocksize,
         fletcher32=fletcher32, contiguous=contiguous, chunksizes=chunksizes,
         endian=endian, least_significant_digit=least_significant_digit,
@@ -3671,14 +3671,14 @@ behavior is similar to Fortran or Matlab, but different than numpy.
 
     def __init__(self, grp, name, datatype, dimensions=(),
             compression=None, zlib=False,
-            complevel=4, shuffle=True, szip_mask='nn', szip_pixels_per_block=8,
+            complevel=4, shuffle=True, szip_coding='nn', szip_pixels_per_block=8,
             blosc_shuffle=1, blosc_blocksize=0,
             fletcher32=False, contiguous=False,
             chunksizes=None, endian='native', least_significant_digit=None,
             significant_digits=None,quantize_mode='BitGroom',fill_value=None, chunk_cache=None, **kwargs):
         """
         **`__init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False,
-        complevel=4, shuffle=True, szip_mask='nn', szip_pixels_per_block=8,
+        complevel=4, shuffle=True, szip_coding='nn', szip_pixels_per_block=8,
         blosc_shuffle=1, blosc_blocksize=0, fletcher32=False, contiguous=False,
         chunksizes=None, endian='native',
         least_significant_digit=None,fill_value=None,chunk_cache=None)`**
@@ -3808,7 +3808,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         """
         cdef int ierr, ndims, icontiguous, icomplevel, numdims, _grpid, nsd,
         cdef unsigned int iblosc_complevel,iblosc_blocksize,iblosc_compressor,iblosc_shuffle
-        cdef int iszip_mask, iszip_pixels_per_block
+        cdef int iszip_coding, iszip_pixels_per_block
         cdef char namstring[NC_MAX_NAME+1]
         cdef char *varname
         cdef nc_type xtype
@@ -3994,9 +3994,9 @@ behavior is similar to Fortran or Matlab, but different than numpy.
                             _ensure_nc_success(ierr)
                     if szip:
                         IF HAS_SZIP_SUPPORT:
-                            iszip_mask = _szip_dict[szip_mask]
+                            iszip_coding = _szip_dict[szip_coding]
                             iszip_pixels_per_block = szip_pixels_per_block
-                            ierr = nc_def_var_szip(self._grpid, self._varid, iszip_mask, iszip_pixels_per_block)
+                            ierr = nc_def_var_szip(self._grpid, self._varid, iszip_coding, iszip_pixels_per_block)
                             if ierr != NC_NOERR:
                                 if grp.data_model != 'NETCDF4': grp._enddef()
                                 _ensure_nc_success(ierr)
@@ -4433,7 +4433,7 @@ return dictionary containing HDF5 filter parameters."""
         cdef int iblosc=0
         cdef int iszip=0
         cdef unsigned int iblosc_complevel,iblosc_blocksize,iblosc_compressor,iblosc_shuffle
-        cdef int iszip_mask, iszip_pixels_per_block
+        cdef int iszip_coding, iszip_pixels_per_block
         filtdict = {'zlib':False,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
         if self._grp.data_model not in ['NETCDF4_CLASSIC','NETCDF4']: return
         with nogil:
@@ -4458,7 +4458,7 @@ return dictionary containing HDF5 filter parameters."""
             if ierr != 0: iblosc=0
             #_ensure_nc_success(ierr)
         IF HAS_SZIP_SUPPORT:
-            ierr = nc_inq_var_szip(self._grpid, self._varid, &iszip_mask,\
+            ierr = nc_inq_var_szip(self._grpid, self._varid, &iszip_coding,\
                     &iszip_pixels_per_block)
             if ierr != 0: iszip=0
             #_ensure_nc_success(ierr)
@@ -4476,7 +4476,7 @@ return dictionary containing HDF5 filter parameters."""
             filtdict['blosc']={'compressor':_blosc_dict_inv[blosc_compressor],'shuffle':iblosc_shuffle,'blocksize':iblosc_blocksize}
             filtdict['complevel']=iblosc_complevel
         if iszip:
-            filtdict['szip']={'mask':_szip_dict_inv[iszip_mask],'pixels_per_block':iszip_pixels_per_block}
+            filtdict['szip']={'coding':_szip_dict_inv[iszip_coding],'pixels_per_block':iszip_pixels_per_block}
         if ishuffle:
             filtdict['shuffle']=True
         if ifletcher32:
diff --git a/test/tst_compression.py b/test/tst_compression.py
index c47422910..f28ed0b96 100644
--- a/test/tst_compression.py
+++ b/test/tst_compression.py
@@ -89,9 +89,9 @@ def runTest(self):
         assert_almost_equal(array,f.variables['data'][:])
         assert_almost_equal(array,f.variables['data2'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
+        {'zlib':False,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
         assert f.variables['data2'].filters() ==\
-        {'zlib':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
+        {'zlib':False,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
         assert_almost_equal(size,uncompressed_size)
         f.close()
         # check compressed data.
@@ -100,9 +100,9 @@ def runTest(self):
         assert_almost_equal(array,f.variables['data'][:])
         assert_almost_equal(array,f.variables['data2'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':True,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':6,'fletcher32':False}
+        {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':6,'fletcher32':False}
         assert f.variables['data2'].filters() ==\
-        {'zlib':True,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':6,'fletcher32':False}
+        {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':6,'fletcher32':False}
         assert(size < 0.95*uncompressed_size)
         f.close()
         # check compression with shuffle
@@ -111,9 +111,9 @@ def runTest(self):
         assert_almost_equal(array,f.variables['data'][:])
         assert_almost_equal(array,f.variables['data2'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':True,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':False}
+        {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':False}
         assert f.variables['data2'].filters() ==\
-        {'zlib':True,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':False}
+        {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':False}
         assert(size < 0.85*uncompressed_size)
         f.close()
         # check lossy compression without shuffle
@@ -138,9 +138,9 @@ def runTest(self):
         assert_almost_equal(checkarray,f.variables['data'][:])
         assert_almost_equal(checkarray,f.variables['data2'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':True,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':True}
+        {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':True}
         assert f.variables['data2'].filters() ==\
-        {'zlib':True,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':True}
+        {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':True}
         assert(size < 0.20*uncompressed_size)
         # should be slightly larger than without fletcher32
         assert(size > size_save)
@@ -150,7 +150,7 @@ def runTest(self):
         checkarray2 = _quantize(array2,lsd)
         assert_almost_equal(checkarray2,f.variables['data2'][:])
         assert f.variables['data2'].filters() ==\
-        {'zlib':True,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':True}
+        {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':True}
         assert f.variables['data2'].chunking() == [chunk1,chunk2]
         f.close()
 
diff --git a/test/tst_compression_blosc.py b/test/tst_compression_blosc.py
index 591a4c260..66ca0e9e4 100644
--- a/test/tst_compression_blosc.py
+++ b/test/tst_compression_blosc.py
@@ -43,29 +43,29 @@ def runTest(self):
         f = Dataset(self.filename)
         assert_almost_equal(datarr,f.variables['data'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
+        {'zlib':False,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
         assert_almost_equal(datarr,f.variables['data_lz'][:])
-        dtest = {'zlib': False, 'zstd': False, 'bzip2': False, 'blosc':
+        dtest = {'zlib': False, 'szip':False, 'zstd': False, 'bzip2': False, 'blosc':
                 {'compressor': 'blosc_lz', 'shuffle': 2, 'blocksize': 800000},
                 'shuffle': False, 'complevel': 4, 'fletcher32': False}
         assert f.variables['data_lz'].filters() == dtest
         assert_almost_equal(datarr,f.variables['data_lz4'][:])
-        dtest = {'zlib': False, 'zstd': False, 'bzip2': False, 'blosc':
+        dtest = {'zlib': False, 'szip':False, 'zstd': False, 'bzip2': False, 'blosc':
                 {'compressor': 'blosc_lz4', 'shuffle': 2, 'blocksize': 800000},
                 'shuffle': False, 'complevel': 4, 'fletcher32': False}
         assert f.variables['data_lz4'].filters() == dtest
         assert_almost_equal(datarr,f.variables['data_lz4hc'][:])
-        dtest = {'zlib': False, 'zstd': False, 'bzip2': False, 'blosc':
+        dtest = {'zlib': False, 'szip':False, 'zstd': False, 'bzip2': False, 'blosc':
                 {'compressor': 'blosc_lz4hc', 'shuffle': 2, 'blocksize': 800000},
                 'shuffle': False, 'complevel': 4, 'fletcher32': False}
         assert f.variables['data_lz4hc'].filters() == dtest
         assert_almost_equal(datarr,f.variables['data_zlib'][:])
-        dtest = {'zlib': False, 'zstd': False, 'bzip2': False, 'blosc':
+        dtest = {'zlib': False, 'szip':False, 'zstd': False, 'bzip2': False, 'blosc':
                 {'compressor': 'blosc_zlib', 'shuffle': 2, 'blocksize': 800000},
                 'shuffle': False, 'complevel': 4, 'fletcher32': False}
         assert f.variables['data_zlib'].filters() == dtest
         assert_almost_equal(datarr,f.variables['data_zstd'][:])
-        dtest = {'zlib': False, 'zstd': False, 'bzip2': False, 'blosc':
+        dtest = {'zlib': False, 'szip':False, 'zstd': False, 'bzip2': False, 'blosc':
                 {'compressor': 'blosc_zstd', 'shuffle': 2, 'blocksize': 800000},
                 'shuffle': False, 'complevel': 4, 'fletcher32': False}
         assert f.variables['data_zstd'].filters() == dtest
diff --git a/test/tst_compression_bzip2.py b/test/tst_compression_bzip2.py
index 8a162f20c..89de4086c 100644
--- a/test/tst_compression_bzip2.py
+++ b/test/tst_compression_bzip2.py
@@ -36,7 +36,7 @@ def runTest(self):
         size = os.stat(self.filename1).st_size
         assert_almost_equal(array,f.variables['data'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
+        {'zlib':False,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
         assert_almost_equal(size,uncompressed_size)
         f.close()
         # check compressed data.
@@ -44,7 +44,7 @@ def runTest(self):
         size = os.stat(self.filename2).st_size
         assert_almost_equal(array,f.variables['data'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':False,'zstd':False,'bzip2':True,'blosc':False,'shuffle':False,'complevel':4,'fletcher32':False}
+        {'zlib':False,'szip':False,'zstd':False,'bzip2':True,'blosc':False,'shuffle':False,'complevel':4,'fletcher32':False}
         assert(size < 0.96*uncompressed_size)
         f.close()
 
diff --git a/test/tst_compression_szip.py b/test/tst_compression_szip.py
index a09cffbba..e62c8b177 100644
--- a/test/tst_compression_szip.py
+++ b/test/tst_compression_szip.py
@@ -13,7 +13,7 @@ def write_netcdf(filename,dtype='f8'):
     foo = nc.createVariable('data',\
             dtype,('n'),compression=None)
     foo_szip = nc.createVariable('data_szip',\
-            dtype,('n'),compression='szip',szip_mask='ec',szip_pixels_per_block=32)
+            dtype,('n'),compression='szip',szip_coding='ec',szip_pixels_per_block=32)
     foo[:] = datarr
     foo_szip[:] = datarr
     nc.close()
@@ -35,7 +35,7 @@ def runTest(self):
         {'zlib':False,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
         assert_almost_equal(datarr,f.variables['data_szip'][:])
         dtest = {'zlib': False, 'zstd': False, 'bzip2': False, 'blosc': False, 'szip':
-                {'mask': 'ec', 'pixels_per_block': 32},
+                {'coding': 'ec', 'pixels_per_block': 32},
                 'shuffle': False, 'complevel': 4, 'fletcher32': False}
         print(f.variables['data_szip'].filters())
         #assert f.variables['data_szip'].filters() == dtest
diff --git a/test/tst_compression_zstd.py b/test/tst_compression_zstd.py
index cd9d270ef..2745e03ba 100644
--- a/test/tst_compression_zstd.py
+++ b/test/tst_compression_zstd.py
@@ -36,7 +36,7 @@ def runTest(self):
         size = os.stat(self.filename1).st_size
         assert_almost_equal(array,f.variables['data'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
+        {'zlib':False,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
         assert_almost_equal(size,uncompressed_size)
         f.close()
         # check compressed data.
@@ -44,7 +44,7 @@ def runTest(self):
         size = os.stat(self.filename2).st_size
         assert_almost_equal(array,f.variables['data'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':False,'zstd':True,'bzip2':False,'blosc':False,'shuffle':False,'complevel':4,'fletcher32':False}
+        {'zlib':False,'szip':False,'zstd':True,'bzip2':False,'blosc':False,'shuffle':False,'complevel':4,'fletcher32':False}
         assert(size < 0.96*uncompressed_size)
         f.close()
 

From 0ee4be01cf9e17765a31dc003ebd4e4ec62c1d09 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 3 May 2022 13:56:26 -0700
Subject: [PATCH 0809/1504] update

---
 test/tst_compression_quant.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/test/tst_compression_quant.py b/test/tst_compression_quant.py
index 9a44420c3..898f84f71 100644
--- a/test/tst_compression_quant.py
+++ b/test/tst_compression_quant.py
@@ -59,7 +59,7 @@ def runTest(self):
         #print('compressed lossless no shuffle = ',size)
         assert_almost_equal(data_array,f.variables['data'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':True,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':complevel,'fletcher32':False}
+        {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':complevel,'fletcher32':False}
         assert(size < 0.95*uncompressed_size)
         f.close()
         # check compression with shuffle
@@ -68,7 +68,7 @@ def runTest(self):
         #print('compressed lossless with shuffle ',size)
         assert_almost_equal(data_array,f.variables['data'][:])
         assert f.variables['data'].filters() ==\
-        {'zlib':True,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':complevel,'fletcher32':False}
+        {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':complevel,'fletcher32':False}
         assert(size < 0.85*uncompressed_size)
         f.close()
         # check lossy compression without shuffle

From fbc6cc2ef12817863ae235f3593811a5261ab29e Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 3 May 2022 14:05:21 -0700
Subject: [PATCH 0810/1504] update

---
 Changelog                    | 8 ++++----
 README.md                    | 2 +-
 test/tst_compression_szip.py | 5 +++--
 3 files changed, 8 insertions(+), 7 deletions(-)

diff --git a/Changelog b/Changelog
index 2128d23bd..eebb7f378 100644
--- a/Changelog
+++ b/Changelog
@@ -12,12 +12,12 @@
  * remove all vestiges of python 2 in _netCDF4.pyx and set cython language_level
    directive to 3 in setup.py.
  * add 'compression' kwarg to createVariable to enable new compression
-   functionality in netcdf-c 4.9.0.  'None','zlib','zstd','bzip2'
+   functionality in netcdf-c 4.9.0.  'None','zlib','szip','zstd','bzip2'
    'blosc_lz','blosc_lz4','blosc_lz4hc','blosc_zlib' and 'blosc_zstd'
-   are currently supported. 'blosc_shuffle' and
-   'blosc_blocksize' kwargs also added.
+   are currently supported. 'blosc_shuffle', 'blosc_blocksize',
+   'szip_mask' and 'szip_pixels_per_block' kwargs also added.
    compression='zlib' is equivalent to (the now deprecated) zlib=True.
-   Using new compressors requires setting HDF5_PLUGIN_PATH to point to 
+   Using new compressors (except 'szip') requires setting HDF5_PLUGIN_PATH to point to 
    the installation location of the netcdf-c filter plugins.
  * MFDataset did not aggregate 'name' variable attribute (issue #1153).
  * issue warning instead of raising an exception if missing_value or
diff --git a/README.md b/README.md
index 99171e273..dc85804ba 100644
--- a/README.md
+++ b/README.md
@@ -15,7 +15,7 @@ for quantization (bit-grooming and bit-rounding) functionality in netcdf-c 4.9.0
 dramatically improve compression.  Dataset.createVariable now accepts dimension instances (instead
 of just dimension names). 'compression' kwarg added to Dataset.createVariable to support 
 new compression algorithms available in netcdf-c 4.9.0 through HDF5 filter plugsins (such
-as zstd, bzip2 and blosc). Working arm64 wheels for Apple M1 Silicon now available on pypi.
+as zstd, bzip2 and blosc) as well as szip. Working arm64 wheels for Apple M1 Silicon now available on pypi.
 
 10/31/2021:  Version [1.5.8](https://pypi.python.org/pypi/netCDF4/1.5.8) released. Fix Enum bug, add binary wheels for aarch64 and python 3.10.
 
diff --git a/test/tst_compression_szip.py b/test/tst_compression_szip.py
index e62c8b177..c51efb745 100644
--- a/test/tst_compression_szip.py
+++ b/test/tst_compression_szip.py
@@ -34,11 +34,12 @@ def runTest(self):
         assert f.variables['data'].filters() ==\
         {'zlib':False,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
         assert_almost_equal(datarr,f.variables['data_szip'][:])
-        dtest = {'zlib': False, 'zstd': False, 'bzip2': False, 'blosc': False, 'szip':
+        dtest = {'zlib': False, 'szip':
                 {'coding': 'ec', 'pixels_per_block': 32},
+                'zstd': False, 'bzip2': False, 'blosc': False, 
                 'shuffle': False, 'complevel': 4, 'fletcher32': False}
         print(f.variables['data_szip'].filters())
-        #assert f.variables['data_szip'].filters() == dtest
+        assert f.variables['data_szip'].filters() == dtest
         f.close()
 
 if __name__ == '__main__':

From 8d0f0f6b5a9913ffbf522875d7a33385dafee8d7 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 3 May 2022 14:12:05 -0700
Subject: [PATCH 0811/1504] try to debug inq_var_szip error

---
 src/netCDF4/_netCDF4.pyx | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 938514c15..682073b5b 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4460,8 +4460,8 @@ return dictionary containing HDF5 filter parameters."""
         IF HAS_SZIP_SUPPORT:
             ierr = nc_inq_var_szip(self._grpid, self._varid, &iszip_coding,\
                     &iszip_pixels_per_block)
-            if ierr != 0: iszip=0
-            #_ensure_nc_success(ierr)
+            #if ierr != 0: iszip=0
+            _ensure_nc_success(ierr)
         if ideflate:
             filtdict['zlib']=True
             filtdict['complevel']=icomplevel

From a9e5ced5ae98a56b0e482e748cecc1ccfb8e2412 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 3 May 2022 14:19:30 -0700
Subject: [PATCH 0812/1504] update

---
 src/netCDF4/_netCDF4.pyx | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 682073b5b..cb80b72b4 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4460,7 +4460,10 @@ return dictionary containing HDF5 filter parameters."""
         IF HAS_SZIP_SUPPORT:
             ierr = nc_inq_var_szip(self._grpid, self._varid, &iszip_coding,\
                     &iszip_pixels_per_block)
-            #if ierr != 0: iszip=0
+            if ierr != 0:
+                iszip=0
+            else:
+                iszip=1
             _ensure_nc_success(ierr)
         if ideflate:
             filtdict['zlib']=True

From 7a48b10dd42069dca2d4f8b5d64de14d1cd61960 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 3 May 2022 14:38:08 -0700
Subject: [PATCH 0813/1504] update

---
 src/netCDF4/_netCDF4.pyx | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index cb80b72b4..1a22f8fab 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4479,7 +4479,9 @@ return dictionary containing HDF5 filter parameters."""
             filtdict['blosc']={'compressor':_blosc_dict_inv[blosc_compressor],'shuffle':iblosc_shuffle,'blocksize':iblosc_blocksize}
             filtdict['complevel']=iblosc_complevel
         if iszip:
-            filtdict['szip']={'coding':_szip_dict_inv[iszip_coding],'pixels_per_block':iszip_pixels_per_block}
+            print(iszip_coding, iszip_pixels_per_block)
+            szip_coding = iszip_coding
+            filtdict['szip']={'coding':_szip_dict_inv[szip_coding],'pixels_per_block':iszip_pixels_per_block}
         if ishuffle:
             filtdict['shuffle']=True
         if ifletcher32:

From 2e1a2a27baf1e07a9a347fa3d9e32d304cb0281d Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 3 May 2022 15:33:54 -0700
Subject: [PATCH 0814/1504] update

---
 src/netCDF4/_netCDF4.pyx | 14 ++++++++++----
 1 file changed, 10 insertions(+), 4 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 1a22f8fab..188d56956 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3994,7 +3994,11 @@ behavior is similar to Fortran or Matlab, but different than numpy.
                             _ensure_nc_success(ierr)
                     if szip:
                         IF HAS_SZIP_SUPPORT:
-                            iszip_coding = _szip_dict[szip_coding]
+                            try:
+                                iszip_coding = _szip_dict[szip_coding]
+                            except KeyError:
+                                msg="unknown szip coding ('ec' or 'nn' supported)"
+                                raise ValueError(msg)
                             iszip_pixels_per_block = szip_pixels_per_block
                             ierr = nc_def_var_szip(self._grpid, self._varid, iszip_coding, iszip_pixels_per_block)
                             if ierr != NC_NOERR:
@@ -4463,8 +4467,11 @@ return dictionary containing HDF5 filter parameters."""
             if ierr != 0:
                 iszip=0
             else:
-                iszip=1
-            _ensure_nc_success(ierr)
+                if iszip_coding:
+                    iszip=1
+                else:
+                    iszip=0
+            #_ensure_nc_success(ierr)
         if ideflate:
             filtdict['zlib']=True
             filtdict['complevel']=icomplevel
@@ -4479,7 +4486,6 @@ return dictionary containing HDF5 filter parameters."""
             filtdict['blosc']={'compressor':_blosc_dict_inv[blosc_compressor],'shuffle':iblosc_shuffle,'blocksize':iblosc_blocksize}
             filtdict['complevel']=iblosc_complevel
         if iszip:
-            print(iszip_coding, iszip_pixels_per_block)
             szip_coding = iszip_coding
             filtdict['szip']={'coding':_szip_dict_inv[szip_coding],'pixels_per_block':iszip_pixels_per_block}
         if ishuffle:

From c1b100c6e4d5170ef0f3949d409bac20909bbeaf Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 3 May 2022 16:22:08 -0700
Subject: [PATCH 0815/1504] update

---
 test/tst_compression_szip.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/tst_compression_szip.py b/test/tst_compression_szip.py
index c51efb745..0f69c779a 100644
--- a/test/tst_compression_szip.py
+++ b/test/tst_compression_szip.py
@@ -39,7 +39,7 @@ def runTest(self):
                 'zstd': False, 'bzip2': False, 'blosc': False, 
                 'shuffle': False, 'complevel': 4, 'fletcher32': False}
         print(f.variables['data_szip'].filters())
-        assert f.variables['data_szip'].filters() == dtest
+        #assert f.variables['data_szip'].filters() == dtest
         f.close()
 
 if __name__ == '__main__':

From 39743f6817a9ec4d2a3bba61ecd42ee41714a237 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 3 May 2022 22:21:19 -0700
Subject: [PATCH 0816/1504] update

---
 test/tst_compression_szip.py | 8 ++------
 1 file changed, 2 insertions(+), 6 deletions(-)

diff --git a/test/tst_compression_szip.py b/test/tst_compression_szip.py
index 0f69c779a..874ed3821 100644
--- a/test/tst_compression_szip.py
+++ b/test/tst_compression_szip.py
@@ -34,12 +34,8 @@ def runTest(self):
         assert f.variables['data'].filters() ==\
         {'zlib':False,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
         assert_almost_equal(datarr,f.variables['data_szip'][:])
-        dtest = {'zlib': False, 'szip':
-                {'coding': 'ec', 'pixels_per_block': 32},
-                'zstd': False, 'bzip2': False, 'blosc': False, 
-                'shuffle': False, 'complevel': 4, 'fletcher32': False}
-        print(f.variables['data_szip'].filters())
-        #assert f.variables['data_szip'].filters() == dtest
+        dtest = {'zlib': False, 'szip': {'coding': 'ec', 'pixels_per_block': 32}, 'zstd': False, 'bzip2': False, 'blosc': False, 'shuffle': False, 'complevel': 0, 'fletcher32': False}
+        assert f.variables['data_szip'].filters() == dtest
         f.close()
 
 if __name__ == '__main__':

From ed4644cd1794bddd8f2bfc8eb5bf284f3ea9658c Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Wed, 4 May 2022 07:29:13 -0700
Subject: [PATCH 0817/1504] update docs

---
 README.md                |   4 +-
 docs/index.html          | 480 +++++++++++++++++++++------------------
 src/netCDF4/_netCDF4.pyx |  21 +-
 3 files changed, 284 insertions(+), 221 deletions(-)

diff --git a/README.md b/README.md
index dc85804ba..7615d10d1 100644
--- a/README.md
+++ b/README.md
@@ -13,9 +13,9 @@ For details on the latest updates, see the [Changelog](https://github.com/Unidat
 ??/??/2022:  Version [1.6.0](https://pypi.python.org/pypi/netCDF4/1.6.0) released.  Support
 for quantization (bit-grooming and bit-rounding) functionality in netcdf-c 4.9.0 which can
 dramatically improve compression.  Dataset.createVariable now accepts dimension instances (instead
-of just dimension names). 'compression' kwarg added to Dataset.createVariable to support 
+of just dimension names). 'compression' kwarg added to Dataset.createVariable to support szip as well as
 new compression algorithms available in netcdf-c 4.9.0 through HDF5 filter plugsins (such
-as zstd, bzip2 and blosc) as well as szip. Working arm64 wheels for Apple M1 Silicon now available on pypi.
+as zstd, bzip2 and blosc). Working arm64 wheels for Apple M1 Silicon now available on pypi.
 
 10/31/2021:  Version [1.5.8](https://pypi.python.org/pypi/netCDF4/1.5.8) released. Fix Enum bug, add binary wheels for aarch64 and python 3.10.
 
diff --git a/docs/index.html b/docs/index.html
index cf86fbfa2..99c42d903 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -3,24 +3,24 @@
 
     
     
-    
+    
     netCDF4 API documentation
-    
 
-
-
-
-
-
-        
     
      
             
      
                     
      
@@ -576,7 +577,7 @@ 
      Creating/Opening/Closing a netCDF
 
 
      Here's an example:
      
 
-
      >>> from netCDF4 import Dataset
+
      >>> from netCDF4 import Dataset
 >>> rootgrp = Dataset("test.nc", "w", format="NETCDF4")
 >>> print(rootgrp.data_model)
 NETCDF4
@@ -605,7 +606,7 @@ 
      Groups in a netCDF file
      
 NETCDF4 formatted files support Groups, if you try to create a Group
 in a netCDF 3 file you will get an error message.
      
 
-
      >>> rootgrp = Dataset("test.nc", "a")
+
      >>> rootgrp = Dataset("test.nc", "a")
 >>> fcstgrp = rootgrp.createGroup("forecasts")
 >>> analgrp = rootgrp.createGroup("analyses")
 >>> print(rootgrp.groups)
@@ -629,7 +630,7 @@ 
      Groups in a netCDF file
      
 that group.  To simplify the creation of nested groups, you can
 use a unix-like path as an argument to Dataset.createGroup.
      
 
-
      >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
+
      >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
 >>> fcstgrp2 = rootgrp.createGroup("/forecasts/model2")
 
      
 
@@ -643,7 +644,7 @@ 
      Groups in a netCDF file
      
 to walk the directory tree. Note that printing the Dataset or Group
 object yields summary information about it's contents.
      
 
-
      >>> def walktree(top):
+
      >>> def walktree(top):
 ...     yield top.groups.values()
 ...     for value in top.groups.values():
 ...         yield from walktree(value)
@@ -693,7 +694,7 @@ 
      Dimensions in a netCDF file
      
 dimension is a new netCDF 4 feature, in netCDF 3 files there may be only
 one, and it must be the first (leftmost) dimension of the variable.
      
 
-
      >>> level = rootgrp.createDimension("level", None)
+
      >>> level = rootgrp.createDimension("level", None)
 >>> time = rootgrp.createDimension("time", None)
 >>> lat = rootgrp.createDimension("lat", 73)
 >>> lon = rootgrp.createDimension("lon", 144)
@@ -701,7 +702,7 @@ 
      Dimensions in a netCDF file
      
 
 
      All of the Dimension instances are stored in a python dictionary.
      
 
-
      >>> print(rootgrp.dimensions)
+
      >>> print(rootgrp.dimensions)
 {'level': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0, 'time': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0, 'lat': <class 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 73, 'lon': <class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144}
 
      
 
@@ -710,7 +711,7 @@ 
      Dimensions in a netCDF file
      
 Dimension.isunlimited method of a Dimension instance
 be used to determine if the dimensions is unlimited, or appendable.
      
 
-
      >>> print(len(lon))
+
      >>> print(len(lon))
 144
 >>> print(lon.isunlimited())
 False
@@ -722,7 +723,7 @@ 
      Dimensions in a netCDF file
      
 provides useful summary info, including the name and length of the dimension,
 and whether it is unlimited.
      
 
-
      >>> for dimobj in rootgrp.dimensions.values():
+
      >>> for dimobj in rootgrp.dimensions.values():
 ...     print(dimobj)
 <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0
 <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0
@@ -767,7 +768,7 @@ 
      Variables in a netCDF file
      
 method returns an instance of the Variable class whose methods can be
 used later to access and set variable data and attributes.
      
 
-
      >>> times = rootgrp.createVariable("time","f8",("time",))
+
      >>> times = rootgrp.createVariable("time","f8",("time",))
 >>> levels = rootgrp.createVariable("level","i4",("level",))
 >>> latitudes = rootgrp.createVariable("lat","f4",("lat",))
 >>> longitudes = rootgrp.createVariable("lon","f4",("lon",))
@@ -779,7 +780,7 @@ 
      Variables in a netCDF file
      
 
      To get summary info on a Variable instance in an interactive session,
 just print it.
      
 
-
      >>> print(temp)
+
      >>> print(temp)
 <class 'netCDF4._netCDF4.Variable'>
 float32 temp(time, level, lat, lon)
     units: K
@@ -790,7 +791,7 @@ 
      Variables in a netCDF file
      
 
 
      You can use a path to create a Variable inside a hierarchy of groups.
      
 
-
      >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
+
      >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
 
      
 
 
      If the intermediate groups do not yet exist, they will be created.
      
@@ -798,7 +799,7 @@ 
      Variables in a netCDF file
      
 
      You can also query a Dataset or Group instance directly to obtain Group or
 Variable instances using paths.
      
 
-
      >>> print(rootgrp["/forecasts/model1"])  # a Group instance
+
      >>> print(rootgrp["/forecasts/model1"])  # a Group instance
 <class 'netCDF4._netCDF4.Group'>
 group /forecasts/model1:
     dimensions(sizes): 
@@ -816,7 +817,7 @@ 
      Variables in a netCDF file
      
 
      All of the variables in the Dataset or Group are stored in a
 Python dictionary, in the same way as the dimensions:
      
 
-
      >>> print(rootgrp.variables)
+
      >>> print(rootgrp.variables)
 {'time': <class 'netCDF4._netCDF4.Variable'>
 float64 time(time)
 unlimited dimensions: time
@@ -859,7 +860,7 @@ 
      Attributes in a netCDF file
      
 variables. Attributes can be strings, numbers or sequences. Returning to
 our example,
      
 
-
      >>> import time
+
      >>> import time
 >>> rootgrp.description = "bogus example script"
 >>> rootgrp.history = "Created " + time.ctime(time.time())
 >>> rootgrp.source = "netCDF4 python module tutorial"
@@ -877,7 +878,7 @@ 
      Attributes in a netCDF file
      
 built-in dir Python function will return a bunch of private methods
 and attributes that cannot (or should not) be modified by the user.
      
 
-
      >>> for name in rootgrp.ncattrs():
+
      >>> for name in rootgrp.ncattrs():
 ...     print("Global attr {} = {}".format(name, getattr(rootgrp, name)))
 Global attr description = bogus example script
 Global attr history = Created Mon Jul  8 14:19:41 2019
@@ -888,7 +889,7 @@ 
      Attributes in a netCDF file
      
 instance provides all the netCDF attribute name/value pairs in a python
 dictionary:
      
 
-
      >>> print(rootgrp.__dict__)
+
      >>> print(rootgrp.__dict__)
 {'description': 'bogus example script', 'history': 'Created Mon Jul  8 14:19:41 2019', 'source': 'netCDF4 python module tutorial'}
 
      
 
@@ -901,7 +902,7 @@ 
      Writing data
 
      Now that you have a netCDF Variable instance, how do you put data
 into it? You can just treat it like an array and assign data to a slice.
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> lats =  np.arange(-90,91,2.5)
 >>> lons =  np.arange(-180,180,2.5)
 >>> latitudes[:] = lats
@@ -921,7 +922,7 @@ 
      Writing data
 objects with unlimited dimensions will grow along those dimensions if you
 assign data outside the currently defined range of indices.
      
 
-
      >>> # append along two unlimited dimensions by assigning to slice.
+
      >>> # append along two unlimited dimensions by assigning to slice.
 >>> nlats = len(rootgrp.dimensions["lat"])
 >>> nlons = len(rootgrp.dimensions["lon"])
 >>> print("temp shape before adding data = {}".format(temp.shape))
@@ -941,7 +942,7 @@ 
      Writing data
 along the level dimension of the variable temp, even though no
 data has yet been assigned to levels.
      
 
-
      >>> # now, assign data to levels dimension variable.
+
      >>> # now, assign data to levels dimension variable.
 >>> levels[:] =  [1000.,850.,700.,500.,300.,250.,200.,150.,100.,50.]
 
      
 
@@ -954,7 +955,7 @@ 
      Writing data
 allowed, and these indices work independently along each dimension (similar
 to the way vector subscripts work in fortran).  This means that
      
 
-
      >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
+
      >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
 (4, 4)
 
      
 
@@ -972,14 +973,14 @@ 
      Writing data
 
 
      For example,
      
 
-
      >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
+
      >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
 
      
 
 
      will extract time indices 0,2 and 4, pressure levels
 850, 500 and 200 hPa, all Northern Hemisphere latitudes and Eastern
 Hemisphere longitudes, resulting in a numpy array of shape  (3, 3, 36, 71).
      
 
-
      >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
+
      >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
 shape of fancy temp slice = (3, 3, 36, 71)
 
      
 
@@ -1012,7 +1013,7 @@ 
      Dealing with time coordinates
      
 provided by cftime to do just that.
 Here's an example of how they can be used:
      
 
-
      >>> # fill in times.
+
      >>> # fill in times.
 >>> from datetime import datetime, timedelta
 >>> from cftime import num2date, date2num
 >>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
@@ -1052,7 +1053,7 @@ 
      Reading data from a multi
 NETCDF4_CLASSIC format (NETCDF4 formatted multi-file
 datasets are not supported).
      
 
-
      >>> for nf in range(10):
+
      >>> for nf in range(10):
 ...     with Dataset("mftest%s.nc" % nf, "w", format="NETCDF4_CLASSIC") as f:
 ...         _ = f.createDimension("x",None)
 ...         x = f.createVariable("x","i",("x",))
@@ -1061,7 +1062,7 @@ 
      Reading data from a multi
 
 
      Now read all the files back in at once with MFDataset
      
 
-
      >>> from netCDF4 import MFDataset
+
      >>> from netCDF4 import MFDataset
 >>> f = MFDataset("mftest*nc")
 >>> print(f.variables["x"][:])
 [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
@@ -1123,22 +1124,22 @@ 
      Efficient compression of netC
 
 
      In our example, try replacing the line
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
 
      
 
 
      with
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib')
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib')
 
      
 
 
      and then
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',least_significant_digit=3)
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',least_significant_digit=3)
 
      
 
 
      or with netcdf-c >= 4.9.0
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',significant_digits=4)
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',significant_digits=4)
 
      
 
 
      and see how much smaller the resulting files are.
      
@@ -1159,7 +1160,7 @@ 
      Beyond ho
 Since there is no native complex data type in netcdf, compound types are handy
 for storing numpy complex arrays.  Here's an example:
      
 
-
      >>> f = Dataset("complex.nc","w")
+
      >>> f = Dataset("complex.nc","w")
 >>> size = 3 # length of 1-d complex array
 >>> # create sample complex data.
 >>> datac = np.exp(1j*(1.+np.linspace(0, np.pi, size)))
@@ -1195,7 +1196,7 @@ 
      Beyond ho
 in a Python dictionary, just like variables and dimensions. As always, printing
 objects gives useful summary information in an interactive session:
      
 
-
      >>> print(f)
+
      >>> print(f)
 <class 'netCDF4._netCDF4.Dataset'>
 root group (NETCDF4 data model, file format HDF5):
     dimensions(sizes): x_dim(3)
@@ -1220,7 +1221,7 @@ 
      Variable-length (vlen) data types
      
 data type, use the Dataset.createVLType method
 method of a Dataset or Group instance.
      
 
-
      >>> f = Dataset("tst_vlen.nc","w")
+
      >>> f = Dataset("tst_vlen.nc","w")
 >>> vlen_t = f.createVLType(np.int32, "phony_vlen")
 
      
 
@@ -1230,7 +1231,7 @@ 
      Variable-length (vlen) data types
      
 but compound data types cannot.
 A new variable can then be created using this datatype.
      
 
-
      >>> x = f.createDimension("x",3)
+
      >>> x = f.createDimension("x",3)
 >>> y = f.createDimension("y",4)
 >>> vlvar = f.createVariable("phony_vlen_var", vlen_t, ("y","x"))
 
      
@@ -1243,7 +1244,7 @@ 
      Variable-length (vlen) data types
      
 In this case, they contain 1-D numpy int32 arrays of random length between
 1 and 10.
      
 
-
      >>> import random
+
      >>> import random
 >>> random.seed(54321)
 >>> data = np.empty(len(y)*len(x),object)
 >>> for n in range(len(y)*len(x)):
@@ -1283,7 +1284,7 @@ 
      Variable-length (vlen) data types
      
 with fixed length greater than 1) when calling the
 Dataset.createVariable method.
      
 
-
      >>> z = f.createDimension("z",10)
+
      >>> z = f.createDimension("z",10)
 >>> strvar = f.createVariable("strvar", str, "z")
 
      
 
@@ -1291,7 +1292,7 @@ 
      Variable-length (vlen) data types
      
 random lengths between 2 and 12 characters, and the data in the object
 array is assigned to the vlen string variable.
      
 
-
      >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
+
      >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
 >>> data = np.empty(10,"O")
 >>> for n in range(10):
 ...     stringlen = random.randint(2,12)
@@ -1330,7 +1331,7 @@ 
      Enum data type
      
 values and their names are used to define an Enum data type using
 Dataset.createEnumType.
      
 
-
      >>> nc = Dataset('clouds.nc','w')
+
      >>> nc = Dataset('clouds.nc','w')
 >>> # python dict with allowed values and their names.
 >>> enum_dict = {'Altocumulus': 7, 'Missing': 255,
 ... 'Stratus': 2, 'Clear': 0,
@@ -1348,7 +1349,7 @@ 
      Enum data type
      
 is made to write an integer value not associated with one of the
 specified names.
      
 
-
      >>> time = nc.createDimension('time',None)
+
      >>> time = nc.createDimension('time',None)
 >>> # create a 1d variable of type 'cloud_type'.
 >>> # The fill_value is set to the 'Missing' named value.
 >>> cloud_var = nc.createVariable('primary_cloud',cloud_type,'time',
@@ -1385,7 +1386,7 @@ 
      Parallel IO
      
 available. To use parallel IO, your program must be running in an MPI
 environment using mpi4py.
      
 
-
      >>> from mpi4py import MPI
+
      >>> from mpi4py import MPI
 >>> import numpy as np
 >>> from netCDF4 import Dataset
 >>> rank = MPI.COMM_WORLD.rank  # The process ID (integer 0-3 for 4-process run)
@@ -1397,7 +1398,7 @@ 
      Parallel IO
      
 when a new dataset is created or an existing dataset is opened,
 use the parallel keyword to enable parallel access.
      
 
-
      >>> nc = Dataset('parallel_test.nc','w',parallel=True)
+
      >>> nc = Dataset('parallel_test.nc','w',parallel=True)
 
      
 
 
      The optional comm keyword may be used to specify a particular
@@ -1405,7 +1406,7 @@ 
      Parallel IO
      
 can now write to the file indepedently.  In this example the process rank is
 written to a different variable index on each task
      
 
-
      >>> d = nc.createDimension('dim',4)
+
      >>> d = nc.createDimension('dim',4)
 >>> v = nc.createVariable('var', np.int64, 'dim')
 >>> v[rank] = rank
 >>> nc.close()
@@ -1472,7 +1473,7 @@ 
      Dealing with strings
      
 stringtochar is used to convert the numpy string array to an array of
 characters with one more dimension. For example,
      
 
-
      >>> from netCDF4 import stringtochar
+
      >>> from netCDF4 import stringtochar
 >>> nc = Dataset('stringtest.nc','w',format='NETCDF4_CLASSIC')
 >>> _ = nc.createDimension('nchars',3)
 >>> _ = nc.createDimension('nstrings',None)
@@ -1505,7 +1506,7 @@ 
      Dealing with strings
      
 character array dtype under the hood when creating the netcdf compound type.
 Here's an example:
      
 
-
      >>> nc = Dataset('compoundstring_example.nc','w')
+
      >>> nc = Dataset('compoundstring_example.nc','w')
 >>> dtype = np.dtype([('observation', 'f4'),
 ...                      ('station_name','S10')])
 >>> station_data_t = nc.createCompoundType(dtype,'station_data')
@@ -1550,7 +1551,7 @@ 
      In-memory (diskless) Datasets
      
 object representing the Dataset. Below are examples illustrating both
 approaches.
      
 
-
      >>> # create a diskless (in-memory) Dataset,
+
      >>> # create a diskless (in-memory) Dataset,
 >>> # and persist the file to disk when it is closed.
 >>> nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
 >>> d = nc.createDimension('x',None)
@@ -1612,7 +1613,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -1625,7 +1626,7 @@ 
      In-memory (diskless) Datasets
      
 
                         
      
             View Source
-            
      # init for netCDF4. package
+            
      # init for netCDF4. package
 # Docstring comes from extension module _netCDF4.
 from ._netCDF4 import *
 # Need explicit imports for names beginning with underscores
@@ -1636,7 +1637,7 @@ 
      In-memory (diskless) Datasets
      
                        __has_nc_create_mem__, __has_cdf5_format__,
                        __has_parallel4_support__, __has_pnetcdf_support__,
                        __has_quantization_support__, __has_zstandard_support__,
-                       __has_bzip2_support__, __has_blosc_support__)
+                       __has_bzip2_support__, __has_blosc_support__, __has_szip_support__)
 __all__ =\
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
 
      
@@ -1653,7 +1654,7 @@ 
      In-memory (diskless) Datasets
      
         Dataset:
     
      
 
-        
+    
             
      A netCDF Dataset is a collection of dimensions, groups, variables and
 attributes. Together they describe the meaning of data and relations among
 data fields stored in a netCDF file. See Dataset.__init__ for more
@@ -1731,7 +1732,7 @@ 
      In-memory (diskless) Datasets
      
             Dataset()
     
      
 
-        
+    
             
      __init__(self, filename, mode="r", clobber=True, diskless=False,
 persist=False, keepweakref=False, memory=None, encoding=None,
 parallel=False, comm=None, info=None, format='NETCDF4')
      
@@ -1744,7 +1745,7 @@ 
      In-memory (diskless) Datasets
      
 
 
      mode: access mode. r means read-only; no data can be
 modified. w means write; a new file is created, an existing file with
-the same name is deleted. 'x' means write, but fail if an existing
+the same name is deleted. x means write, but fail if an existing
 file with the same name already exists. a and r+ mean append; 
 an existing file is opened for reading and writing, if 
 file does not exist already, one is created.
@@ -1759,7 +1760,7 @@ 
      In-memory (diskless) Datasets
      
 
      clobber: if True (default), opening a file with mode='w'
 will clobber an existing file with the same name.  if False, an
 exception will be raised if a file with the same name already exists.
-mode='x' is identical to mode='w' with clobber=False.
      
+mode=x is identical to mode=w with clobber=False.
      
 
 
      format: underlying file format (one of 'NETCDF4',
 'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC', 'NETCDF3_64BIT_OFFSET' or
@@ -1802,14 +1803,14 @@ 
      In-memory (diskless) Datasets
      
 rendered unusable when the parent Dataset instance is garbage collected.
      
 
 
      memory: if not None, create or open an in-memory Dataset.
-If mode = 'r', the memory kwarg must contain a memory buffer object
+If mode = r, the memory kwarg must contain a memory buffer object
 (an object that supports the python buffer interface).
 The Dataset will then be created with contents taken from this block of memory.
-If mode = 'w', the memory kwarg should contain the anticipated size
+If mode = w, the memory kwarg should contain the anticipated size
 of the Dataset in bytes (used only for NETCDF3 files).  A memory
 buffer containing a copy of the Dataset is returned by the
-Dataset.close method. Requires netcdf-c version 4.4.1 for mode='r,
-netcdf-c 4.6.2 for mode='w'. To persist the file to disk, the raw
+Dataset.close method. Requires netcdf-c version 4.4.1 for mode=r
+netcdf-c 4.6.2 for mode=w. To persist the file to disk, the raw
 bytes from the returned buffer can be written into a binary file.
 The Dataset can also be re-opened using this memory buffer.
      
 
@@ -1837,7 +1838,7 @@ 
      In-memory (diskless) Datasets
      
             filepath(unknown):
     
      
 
-        
+    
             
      filepath(self,encoding=None)
      
 
 
      Get the file system path (or the opendap URL) which was used to
@@ -1856,7 +1857,7 @@ 
      In-memory (diskless) Datasets
      
             close(unknown):
     
      
 
-        
+    
             
      close(self)
      
 
 
      Close the Dataset.
      
@@ -1872,7 +1873,7 @@ 
      In-memory (diskless) Datasets
      
             isopen(unknown):
     
      
 
-        
+    
             
      isopen(self)
      
 
 
      Is the Dataset open or closed?
      
@@ -1888,7 +1889,7 @@ 
      In-memory (diskless) Datasets
      
             sync(unknown):
     
      
 
-        
+    
             
      sync(self)
      
 
 
      Writes all buffered data in the Dataset to the disk file.
      
@@ -1904,7 +1905,7 @@ 
      In-memory (diskless) Datasets
      
             set_fill_on(unknown):
     
      
 
-        
+    
             
      set_fill_on(self)
      
 
 
      Sets the fill mode for a Dataset open for writing to on.
      
@@ -1928,7 +1929,7 @@ 
      In-memory (diskless) Datasets
      
             set_fill_off(unknown):
     
      
 
-        
+    
             
      set_fill_off(self)
      
 
 
      Sets the fill mode for a Dataset open for writing to off.
      
@@ -1948,7 +1949,7 @@ 
      In-memory (diskless) Datasets
      
             createDimension(unknown):
     
      
 
-        
+    
             
      createDimension(self, dimname, size=None)
      
 
 
      Creates a new dimension with the given dimname and size.
      
@@ -1972,7 +1973,7 @@ 
      In-memory (diskless) Datasets
      
             renameDimension(unknown):
     
      
 
-        
+    
             
      renameDimension(self, oldname, newname)
      
 
 
      rename a Dimension named oldname to newname.
      
@@ -1988,7 +1989,7 @@ 
      In-memory (diskless) Datasets
      
             createCompoundType(unknown):
     
      
 
-        
+    
             
      createCompoundType(self, datatype, datatype_name)
      
 
 
      Creates a new compound data type named datatype_name from the numpy
@@ -2013,7 +2014,7 @@ 
      In-memory (diskless) Datasets
      
             createVLType(unknown):
     
      
 
-        
+    
             
      createVLType(self, datatype, datatype_name)
      
 
 
      Creates a new VLEN data type named datatype_name from a numpy
@@ -2033,7 +2034,7 @@ 
      In-memory (diskless) Datasets
      
             createEnumType(unknown):
     
      
 
-        
+    
             
      createEnumType(self, datatype, datatype_name, enum_dict)
      
 
 
      Creates a new Enum data type named datatype_name from a numpy
@@ -2054,9 +2055,10 @@ 
      In-memory (diskless) Datasets
      
             createVariable(unknown):
     
      
 
-        
+    
             
      createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False,
 complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None,
+szip_coding='nn', szip_pixels_per_block=8, blosc_shuffle=1, blosc_blocksize=0,
 endian='native', least_significant_digit=None, significant_digits=None, quantize_mode='BitGroom',
 fill_value=None, chunk_cache=None)
      
 
@@ -2092,10 +2094,10 @@ 
      In-memory (diskless) Datasets
      
 
 
      If the optional keyword argument compression is set, the data will be
 compressed in the netCDF file using the specified compression algorithm.
-Currently zlib,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,
+Currently zlib,szip,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,
 blosc_zlib and blosc_zstd are supported.
 Default is None (no compression).  All of the compressors except
-zlib use the HDF5 plugin architecture, which requires that the
+zlib and szip use the HDF5 plugin architecture, which requires that the
 environment variable HDF5_PLUGIN_PATH be set to the location of the
 plugins built by netcdf-c (unless the plugins are installed in the
 default location /usr/local/hdf5/lib).
      
@@ -2109,7 +2111,7 @@ 
      In-memory (diskless) Datasets
      
 A value of zero disables compression.
      
 
 
      If the optional keyword shuffle is True, the HDF5 shuffle filter
-will be applied before compressing the data (default True).  This
+will be applied before compressing the data with zlib (default True).  This
 significantly improves compression. Default is True. Ignored if
 zlib=False.
      
 
@@ -2119,6 +2121,11 @@ 
      In-memory (diskless) Datasets
      
 is the tunable blosc blocksize in bytes (Default 0 means the blocksize is
 chosen internally).
      
 
+
      The optional kwargs szip_coding and szip_pixels_per_block are ignored
+unless the szip compressor is used. szip_coding can be ec (entropy coding)
+or nn (nearest neighbor coding). Default is nn. szip_pixels_per_block
+can be 4, 8, 16 or 32 (default 8).
      
+
 
      If the optional keyword fletcher32 is True, the Fletcher32 HDF5
 checksum algorithm is activated to detect errors. Default False.
      
 
@@ -2151,7 +2158,7 @@ 
      In-memory (diskless) Datasets
      
 
 
      The optional keyword fill_value can be used to override the default
 netCDF _FillValue (the value that the variable gets filled with before
-any data is written to it, defaults given in the dict netCDF4.default_fillvals).
+any data is written to it, defaults given in the dict netCDF4.default_fillvals).
 If fill_value is set to False, then the variable is not pre-filled.
      
 
 
      If the optional keyword parameters least_significant_digit or significant_digits are
@@ -2219,7 +2226,7 @@ 
      In-memory (diskless) Datasets
      
             renameVariable(unknown):
     
      
 
-        
+    
             
      renameVariable(self, oldname, newname)
      
 
 
      rename a Variable named oldname to newname
      
@@ -2235,7 +2242,7 @@ 
      In-memory (diskless) Datasets
      
             createGroup(unknown):
     
      
 
-        
+    
             
      createGroup(self, groupname)
      
 
 
      Creates a new Group with the given groupname.
      
@@ -2261,7 +2268,7 @@ 
      In-memory (diskless) Datasets
      
             ncattrs(unknown):
     
      
 
-        
+    
             
      ncattrs(self)
      
 
 
      return netCDF global attribute names for this Dataset or Group in a list.
      
@@ -2277,7 +2284,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr(unknown):
     
      
 
-        
+    
             
      setncattr(self,name,value)
      
 
 
      set a netCDF dataset or group attribute using name,value pair.
@@ -2295,7 +2302,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr_string(unknown):
     
      
 
-        
+    
             
      setncattr_string(self,name,value)
      
 
 
      set a netCDF dataset or group string attribute using name,value pair.
@@ -2313,7 +2320,7 @@ 
      In-memory (diskless) Datasets
      
             setncatts(unknown):
     
      
 
-        
+    
             
      setncatts(self,attdict)
      
 
 
      set a bunch of netCDF dataset or group attributes at once using a python dictionary.
@@ -2332,7 +2339,7 @@ 
      In-memory (diskless) Datasets
      
             getncattr(unknown):
     
      
 
-        
+    
             
      getncattr(self,name)
      
 
 
      retrieve a netCDF dataset or group attribute.
@@ -2353,7 +2360,7 @@ 
      In-memory (diskless) Datasets
      
             delncattr(unknown):
     
      
 
-        
+    
             
      delncattr(self,name,value)
      
 
 
      delete a netCDF dataset or group attribute.  Use if you need to delete a
@@ -2371,7 +2378,7 @@ 
      In-memory (diskless) Datasets
      
             renameAttribute(unknown):
     
      
 
-        
+    
             
      renameAttribute(self, oldname, newname)
      
 
 
      rename a Dataset or Group attribute named oldname to newname.
      
@@ -2387,7 +2394,7 @@ 
      In-memory (diskless) Datasets
      
             renameGroup(unknown):
     
      
 
-        
+    
             
      renameGroup(self, oldname, newname)
      
 
 
      rename a Group named oldname to newname (requires netcdf >= 4.3.1).
      
@@ -2403,7 +2410,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_chartostring(unknown):
     
      
 
-        
+    
             
      set_auto_chartostring(self, True_or_False)
      
 
 
      Call Variable.set_auto_chartostring for all variables contained in this Dataset or
@@ -2428,7 +2435,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_maskandscale(unknown):
     
      
 
-        
+    
             
      set_auto_maskandscale(self, True_or_False)
      
 
 
      Call Variable.set_auto_maskandscale for all variables contained in this Dataset or
@@ -2451,7 +2458,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_mask(unknown):
     
      
 
-        
+    
             
      set_auto_mask(self, True_or_False)
      
 
 
      Call Variable.set_auto_mask for all variables contained in this Dataset or
@@ -2475,7 +2482,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_scale(unknown):
     
      
 
-        
+    
             
      set_auto_scale(self, True_or_False)
      
 
 
      Call Variable.set_auto_scale for all variables contained in this Dataset or
@@ -2498,7 +2505,7 @@ 
      In-memory (diskless) Datasets
      
             set_always_mask(unknown):
     
      
 
-        
+    
             
      set_always_mask(self, True_or_False)
      
 
 
      Call Variable.set_always_mask for all variables contained in
@@ -2526,7 +2533,7 @@ 
      In-memory (diskless) Datasets
      
             set_ncstring_attrs(unknown):
     
      
 
-        
+    
             
      set_ncstring_attrs(self, True_or_False)
      
 
 
      Call Variable.set_ncstring_attrs for all variables contained in
@@ -2551,7 +2558,7 @@ 
      In-memory (diskless) Datasets
      
             get_variables_by_attributes(unknown):
     
      
 
-        
+    
             
      get_variables_by_attribute(self, **kwargs)
      
 
 
      Returns a list of variables that match specific conditions.
      
@@ -2559,7 +2566,7 @@ 
      In-memory (diskless) Datasets
      
 
      Can pass in key=value parameters and variables are returned that
 contain all of the matches. For example,
      
 
-
      >>> # Get variables with x-axis attribute.
+
      >>> # Get variables with x-axis attribute.
 >>> vs = nc.get_variables_by_attributes(axis='X')
 >>> # Get variables with matching "standard_name" attribute
 >>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
@@ -2570,7 +2577,7 @@ 
      In-memory (diskless) Datasets
      
 the attribute value.  None is given as the attribute value when the
 attribute does not exist on the variable. For example,
      
 
-
      >>> # Get Axis variables
+
      >>> # Get Axis variables
 >>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
 >>> # Get variables that don't have an "axis" attribute
 >>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
@@ -2589,7 +2596,7 @@ 
      In-memory (diskless) Datasets
      
             fromcdl(unknown):
     
      
 
-        
+    
             
      fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')
      
 
 
      call ncgen via subprocess to create Dataset from CDL
@@ -2619,7 +2626,7 @@ 
      In-memory (diskless) Datasets
      
             tocdl(unknown):
     
      
 
-        
+    
             
      tocdl(self, coordvars=False, data=False, outfile=None)
      
 
 
      call ncdump via subprocess to create CDL
@@ -2638,9 +2645,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.Dataset' objects>
+        name
     
      
 
+    
             
      string name of Group instance
      
 
      
 
@@ -2649,109 +2657,121 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        groups = <attribute 'groups' of 'netCDF4._netCDF4.Dataset' objects>
+        groups
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Dataset' objects>
+        dimensions
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        variables = <attribute 'variables' of 'netCDF4._netCDF4.Dataset' objects>
+        variables
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        disk_format = <attribute 'disk_format' of 'netCDF4._netCDF4.Dataset' objects>
+        disk_format
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        path = <attribute 'path' of 'netCDF4._netCDF4.Dataset' objects>
+        path
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        parent = <attribute 'parent' of 'netCDF4._netCDF4.Dataset' objects>
+        parent
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        file_format = <attribute 'file_format' of 'netCDF4._netCDF4.Dataset' objects>
+        file_format
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        data_model = <attribute 'data_model' of 'netCDF4._netCDF4.Dataset' objects>
+        data_model
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        cmptypes = <attribute 'cmptypes' of 'netCDF4._netCDF4.Dataset' objects>
+        cmptypes
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        vltypes = <attribute 'vltypes' of 'netCDF4._netCDF4.Dataset' objects>
+        vltypes
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        enumtypes = <attribute 'enumtypes' of 'netCDF4._netCDF4.Dataset' objects>
+        enumtypes
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        keepweakref = <attribute 'keepweakref' of 'netCDF4._netCDF4.Dataset' objects>
+        keepweakref
     
      
 
     
+    
 
                             
      
                 
      
@@ -2764,7 +2784,7 @@ 
      In-memory (diskless) Datasets
      
         Variable:
     
      
 
-        
+    
             
      A netCDF Variable is used to read and write netCDF data.  They are
 analogous to numpy array objects. See Variable.__init__ for more
 details.
      
@@ -2848,9 +2868,10 @@ 
      In-memory (diskless) Datasets
      
             Variable()
     
      
 
-        
+    
             
      __init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False,
-complevel=4, shuffle=True, blosc_shuffle=1, blosc_blocksize=0, fletcher32=False, contiguous=False,
+complevel=4, shuffle=True, szip_coding='nn', szip_pixels_per_block=8,
+blosc_shuffle=1, blosc_blocksize=0, fletcher32=False, contiguous=False,
 chunksizes=None, endian='native',
 least_significant_digit=None,fill_value=None,chunk_cache=None)
      
 
@@ -2884,7 +2905,7 @@ 
      In-memory (diskless) Datasets
      
 which means the variable is a scalar (and therefore has no dimensions).
      
 
 
      compression: compression algorithm to use. 
-Currently zlib,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,
+Currently zlib,szip,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,
 blosc_zlib and blosc_zstd are supported.
 Default is None (no compression).  All of the compressors except
 zlib use the HDF5 plugin architecture, which requires that the
@@ -2898,18 +2919,26 @@ 
      In-memory (diskless) Datasets
      
 
 
      complevel: the level of compression to use (1 is the fastest,
 but poorest compression, 9 is the slowest but best compression). Default 4.
-Ignored if compression=None. A value of 0 disables compression.
      
+Ignored if compression=None or szip. A value of 0 disables compression.
      
 
 
      shuffle: if True, the HDF5 shuffle filter is applied
-to improve compression. Default True. Ignored if compression=None.
      
+to improve zlib compression. Default True. Ignored unless compression = 'zlib'.
      
 
 
      blosc_shuffle: shuffle filter inside blosc compressor (only
 relevant if compression kwarg set to one of the blosc compressors).
 Can be 0 (no blosc shuffle), 1 (bytewise shuffle) or 2 (bitwise
-shuffle)). Default is 1.
      
+shuffle)). Default is 1. Ignored if blosc compressor not used.
      
 
 
      blosc_blocksize: tunable blocksize in bytes for blosc
-compressors. Default of 0 means blosc library chooses a blocksize.
      
+compressors. Default of 0 means blosc library chooses a blocksize.
+Ignored if blosc compressor not used.
      
+
+
      szip_coding: szip coding method. Can be ec (entropy coding)
+or nn (nearest neighbor coding). Default is nn.
+Ignored if szip compressor not used.
      
+
+
      szip_pixels_per_block: Can be 4,8,16 or 32 (Default 8). 
+Ignored if szip compressor not used.
      
 
 
      fletcher32: if True (default False), the Fletcher32 checksum
 algorithm is used for error detection.
      
@@ -2967,7 +2996,7 @@ 
      In-memory (diskless) Datasets
      
 value that the variable gets filled with before any data is written to it)
 is replaced with this value.  If fill_value is set to False, then
 the variable is not pre-filled. The default netCDF fill values can be found
-in the dictionary netCDF4.default_fillvals.
      
+in the dictionary netCDF4.default_fillvals.
      
 
 
      chunk_cache: If specified, sets the chunk cache size for this variable.
 Persists as long as Dataset is open. Use set_var_chunk_cache to
@@ -2988,7 +3017,7 @@ 
      In-memory (diskless) Datasets
      
             group(unknown):
     
      
 
-        
+    
             
      group(self)
      
 
 
      return the group that this Variable is a member of.
      
@@ -3004,7 +3033,7 @@ 
      In-memory (diskless) Datasets
      
             ncattrs(unknown):
     
      
 
-        
+    
             
      ncattrs(self)
      
 
 
      return netCDF attribute names for this Variable in a list.
      
@@ -3020,7 +3049,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr(unknown):
     
      
 
-        
+    
             
      setncattr(self,name,value)
      
 
 
      set a netCDF variable attribute using name,value pair.  Use if you need to set a
@@ -3038,7 +3067,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr_string(unknown):
     
      
 
-        
+    
             
      setncattr_string(self,name,value)
      
 
 
      set a netCDF variable string attribute using name,value pair.
@@ -3057,7 +3086,7 @@ 
      In-memory (diskless) Datasets
      
             setncatts(unknown):
     
      
 
-        
+    
             
      setncatts(self,attdict)
      
 
 
      set a bunch of netCDF variable attributes at once using a python dictionary.
@@ -3076,7 +3105,7 @@ 
      In-memory (diskless) Datasets
      
             getncattr(unknown):
     
      
 
-        
+    
             
      getncattr(self,name)
      
 
 
      retrieve a netCDF variable attribute.  Use if you need to set a
@@ -3097,7 +3126,7 @@ 
      In-memory (diskless) Datasets
      
             delncattr(unknown):
     
      
 
-        
+    
             
      delncattr(self,name,value)
      
 
 
      delete a netCDF variable attribute.  Use if you need to delete a
@@ -3115,7 +3144,7 @@ 
      In-memory (diskless) Datasets
      
             filters(unknown):
     
      
 
-        
+    
             
      filters(self)
      
 
 
      return dictionary containing HDF5 filter parameters.
      
@@ -3131,7 +3160,7 @@ 
      In-memory (diskless) Datasets
      
             quantization(unknown):
     
      
 
-        
+    
             
      quantization(self)
      
 
 
      return number of significant digits and the algorithm used in quantization.
@@ -3148,7 +3177,7 @@ 
      In-memory (diskless) Datasets
      
             endian(unknown):
     
      
 
-        
+    
             
      endian(self)
      
 
 
      return endian-ness (little,big,native) of variable (as stored in HDF5 file).
      
@@ -3164,7 +3193,7 @@ 
      In-memory (diskless) Datasets
      
             chunking(unknown):
     
      
 
-        
+    
             
      chunking(self)
      
 
 
      return variable chunking information.  If the dataset is
@@ -3183,7 +3212,7 @@ 
      In-memory (diskless) Datasets
      
             get_var_chunk_cache(unknown):
     
      
 
-        
+    
             
      get_var_chunk_cache(self)
      
 
 
      return variable chunk cache information in a tuple (size,nelems,preemption).
@@ -3201,7 +3230,7 @@ 
      In-memory (diskless) Datasets
      
             set_var_chunk_cache(unknown):
     
      
 
-        
+    
             
      set_var_chunk_cache(self,size=None,nelems=None,preemption=None)
      
 
 
      change variable chunk cache settings.
@@ -3219,7 +3248,7 @@ 
      In-memory (diskless) Datasets
      
             renameAttribute(unknown):
     
      
 
-        
+    
             
      renameAttribute(self, oldname, newname)
      
 
 
      rename a Variable attribute named oldname to newname.
      
@@ -3235,7 +3264,7 @@ 
      In-memory (diskless) Datasets
      
             assignValue(unknown):
     
      
 
-        
+    
             
      assignValue(self, val)
      
 
 
      assign a value to a scalar variable.  Provided for compatibility with
@@ -3252,7 +3281,7 @@ 
      In-memory (diskless) Datasets
      
             getValue(unknown):
     
      
 
-        
+    
             
      getValue(self)
      
 
 
      get the value of a scalar variable.  Provided for compatibility with
@@ -3269,7 +3298,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_chartostring(unknown):
     
      
 
-        
+    
             
      set_auto_chartostring(self,chartostring)
      
 
 
      turn on or off automatic conversion of character variable data to and
@@ -3300,7 +3329,7 @@ 
      In-memory (diskless) Datasets
      
             use_nc_get_vars(unknown):
     
      
 
-        
+    
             
      use_nc_get_vars(self,_use_get_vars)
      
 
 
      enable the use of netcdf library routine nc_get_vars
@@ -3320,7 +3349,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_maskandscale(unknown):
     
      
 
-        
+    
             
      set_auto_maskandscale(self,maskandscale)
      
 
 
      turn on or off automatic conversion of variable data to and
@@ -3384,7 +3413,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_scale(unknown):
     
      
 
-        
+    
             
      set_auto_scale(self,scale)
      
 
 
      turn on or off automatic packing/unpacking of variable
@@ -3433,7 +3462,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_mask(unknown):
     
      
 
-        
+    
             
      set_auto_mask(self,mask)
      
 
 
      turn on or off automatic conversion of variable data to and
@@ -3468,7 +3497,7 @@ 
      In-memory (diskless) Datasets
      
             set_always_mask(unknown):
     
      
 
-        
+    
             
      set_always_mask(self,always_mask)
      
 
 
      turn on or off conversion of data without missing values to regular
@@ -3491,7 +3520,7 @@ 
      In-memory (diskless) Datasets
      
             set_ncstring_attrs(unknown):
     
      
 
-        
+    
             
      set_always_mask(self,ncstring_attrs)
      
 
 
      turn on or off creating NC_STRING string attributes.
      
@@ -3513,7 +3542,7 @@ 
      In-memory (diskless) Datasets
      
             set_collective(unknown):
     
      
 
-        
+    
             
      set_collective(self,True_or_False)
      
 
 
      turn on or off collective parallel IO access. Ignored if file is not
@@ -3530,7 +3559,7 @@ 
      In-memory (diskless) Datasets
      
             get_dims(unknown):
     
      
 
-        
+    
             
      get_dims(self)
      
 
 
      return a tuple of Dimension instances associated with this
@@ -3542,9 +3571,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.Variable' objects>
+        name
     
      
 
+    
             
      string name of Variable instance
      
 
      
 
@@ -3553,9 +3583,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        datatype = <attribute 'datatype' of 'netCDF4._netCDF4.Variable' objects>
+        datatype
     
      
 
+    
             
      numpy data type (for primitive data types) or
 VLType/CompoundType/EnumType instance 
 (for compound, vlen  or enum data types)
      
@@ -3566,9 +3597,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        shape = <attribute 'shape' of 'netCDF4._netCDF4.Variable' objects>
+        shape
     
      
 
+    
             
      find current sizes of all variable dimensions
      
 
      
 
@@ -3577,9 +3609,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        size = <attribute 'size' of 'netCDF4._netCDF4.Variable' objects>
+        size
     
      
 
+    
             
      Return the number of stored elements.
      
 
      
 
@@ -3588,9 +3621,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Variable' objects>
+        dimensions
     
      
 
+    
             
      get variables's dimension names
      
 
      
 
@@ -3599,55 +3633,61 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        ndim = <attribute 'ndim' of 'netCDF4._netCDF4.Variable' objects>
+        ndim
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.Variable' objects>
+        dtype
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        mask = <attribute 'mask' of 'netCDF4._netCDF4.Variable' objects>
+        mask
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        scale = <attribute 'scale' of 'netCDF4._netCDF4.Variable' objects>
+        scale
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        always_mask = <attribute 'always_mask' of 'netCDF4._netCDF4.Variable' objects>
+        always_mask
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        chartostring = <attribute 'chartostring' of 'netCDF4._netCDF4.Variable' objects>
+        chartostring
     
      
 
     
+    
 
                             
      
                 
@@ -3660,7 +3700,7 @@ 
      In-memory (diskless) Datasets
      
         Dimension:
     
      
 
-        
+    
             
      A netCDF Dimension is used to describe the coordinates of a Variable.
 See Dimension.__init__ for more details.
      
 
@@ -3686,7 +3726,7 @@ 
      In-memory (diskless) Datasets
      
             Dimension()
     
      
 
-        
+    
             
      __init__(self, group, name, size=None)
      
 
 
      Dimension constructor.
      
@@ -3712,7 +3752,7 @@ 
      In-memory (diskless) Datasets
      
             group(unknown):
     
      
 
-        
+    
             
      group(self)
      
 
 
      return the group that this Dimension is a member of.
      
@@ -3728,7 +3768,7 @@ 
      In-memory (diskless) Datasets
      
             isunlimited(unknown):
     
      
 
-        
+    
             
      isunlimited(self)
      
 
 
      returns True if the Dimension instance is unlimited, False otherwise.
      
@@ -3739,9 +3779,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.Dimension' objects>
+        name
     
      
 
+    
             
      string name of Dimension instance
      
 
      
 
@@ -3750,9 +3791,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        size = <attribute 'size' of 'netCDF4._netCDF4.Dimension' objects>
+        size
     
      
 
+    
             
      current size of Dimension (calls len on Dimension instance)
      
 
      
 
@@ -3768,7 +3810,7 @@ 
      In-memory (diskless) Datasets
      
         Group(netCDF4.Dataset):
     
      
 
-        
+    
             
      Groups define a hierarchical namespace within a netCDF file. They are
 analogous to directories in a unix filesystem. Each Group behaves like
 a Dataset within a Dataset, and can contain it's own variables,
@@ -3792,7 +3834,7 @@ 
      In-memory (diskless) Datasets
      
             Group()
     
      
 
-        
+    
             
      __init__(self, parent, name)
 Group constructor.
      
 
@@ -3816,7 +3858,7 @@ 
      In-memory (diskless) Datasets
      
             close(unknown):
     
      
 
-        
+    
             
      close(self)
      
 
 
      overrides Dataset close method which does not apply to Group
@@ -3886,7 +3928,7 @@ 
      Inherited Members
      
         MFDataset(netCDF4.Dataset):
     
      
 
-        
+    
             
      Class for reading multi-file netCDF Datasets, making variables
 spanning multiple files appear as if they were in one file.
 Datasets must be in NETCDF4_CLASSIC, NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET
@@ -3896,7 +3938,7 @@ 
      Inherited Members
      
 
 
      Example usage (See MFDataset.__init__ for more details):
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> # create a series of netCDF files with a variable sharing
 >>> # the same unlimited dimension.
 >>> for nf in range(10):
@@ -3923,7 +3965,7 @@ 
      Inherited Members
      
             MFDataset(files, check=False, aggdim=None, exclude=[], master_file=None)
     
      
 
-        
+    
             
      __init__(self, files, check=False, aggdim=None, exclude=[],
 master_file=None)
      
 
@@ -3968,7 +4010,7 @@ 
      Inherited Members
      
             ncattrs(self):
     
      
 
-        
+    
             
      ncattrs(self)
      
 
 
      return the netcdf attribute names from the master file.
      
@@ -3984,7 +4026,7 @@ 
      Inherited Members
      
             close(self):
     
      
 
-        
+    
             
      close(self)
      
 
 
      close all the open files.
      
@@ -4052,13 +4094,13 @@ 
      Inherited Members
      
         MFTime(netCDF4._netCDF4._Variable):
     
      
 
-        
+    
             
      Class providing an interface to a MFDataset time Variable by imposing a unique common
 time unit and/or calendar to all files.
      
 
 
      Example usage (See MFTime.__init__ for more details):
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> f1 = Dataset("mftest_1.nc","w", format="NETCDF4_CLASSIC")
 >>> f2 = Dataset("mftest_2.nc","w", format="NETCDF4_CLASSIC")
 >>> f1.createDimension("time",None)
@@ -4094,7 +4136,7 @@ 
      Inherited Members
      
             MFTime(time, units=None, calendar=None)
     
      
 
-        
+    
             
      __init__(self, time, units=None, calendar=None)
      
 
 
      Create a time Variable with units consistent across a multifile
@@ -4138,7 +4180,7 @@ 
      Inherited Members
      
         CompoundType:
     
      
 
-        
+    
             
      A CompoundType instance is used to describe a compound data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance.
@@ -4157,7 +4199,7 @@ 
      Inherited Members
      
             CompoundType()
     
      
 
-        
+    
             
      __init__(group, datatype, datatype_name)
      
 
 
      CompoundType constructor.
      
@@ -4186,28 +4228,31 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.CompoundType' objects>
+        dtype
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        dtype_view = <attribute 'dtype_view' of 'netCDF4._netCDF4.CompoundType' objects>
+        dtype_view
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.CompoundType' objects>
+        name
     
      
 
     
+    
 
                             
      
                 
@@ -4220,7 +4265,7 @@ 
      Inherited Members
      
         VLType:
     
      
 
-        
+    
             
      A VLType instance is used to describe a variable length (VLEN) data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance. See
@@ -4238,7 +4283,7 @@ 
      Inherited Members
      
             VLType()
     
      
 
-        
+    
             
      __init__(group, datatype, datatype_name)
      
 
 
      VLType constructor.
      
@@ -4261,19 +4306,21 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.VLType' objects>
+        dtype
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.VLType' objects>
+        name
     
      
 
     
+    
 
                             
      
                 
@@ -4285,7 +4332,7 @@ 
      Inherited Members
      
             date2num(unknown):
     
      
 
-        
+    
             
      date2num(dates, units, calendar=None, has_year_zero=None)
      
 
 
      Return numeric time values given datetime objects. The units
@@ -4345,7 +4392,7 @@ 
      Inherited Members
      
             num2date(unknown):
     
      
 
-        
+    
             
      num2date(times, units, calendar=u'standard', only_use_cftime_datetimes=True, only_use_python_datetimes=False, has_year_zero=None)
      
 
 
      Return datetime objects given numeric time values. The units
@@ -4417,7 +4464,7 @@ 
      Inherited Members
      
             date2index(unknown):
     
      
 
-        
+    
             
      date2index(dates, nctime, calendar=None, select=u'exact', has_year_zero=None)
      
 
 
      Return indices of a netCDF time variable corresponding to the given dates.
      
@@ -4471,7 +4518,7 @@ 
      Inherited Members
      
             stringtochar(unknown):
     
      
 
-        
+    
             
      stringtochar(a,encoding='utf-8')
      
 
 
      convert a string array to a character array with one extra dimension
      
@@ -4498,7 +4545,7 @@ 
      Inherited Members
      
             chartostring(unknown):
     
      
 
-        
+    
             
      chartostring(b,encoding='utf-8')
      
 
 
      convert a character array to a string array with one less dimension.
      
@@ -4525,7 +4572,7 @@ 
      Inherited Members
      
             stringtoarr(unknown):
     
      
 
-        
+    
             
      stringtoarr(a, NUMCHARS,dtype='S')
      
 
 
      convert a string to a character array of length NUMCHARS
      
@@ -4553,7 +4600,7 @@ 
      Inherited Members
      
             getlibversion(unknown):
     
      
 
-        
+    
             
      getlibversion()
      
 
 
      returns a string describing the version of the netcdf library
@@ -4571,7 +4618,7 @@ 
      Inherited Members
      
         EnumType:
     
      
 
-        
+    
             
      A EnumType instance is used to describe an Enum data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance. See
@@ -4589,7 +4636,7 @@ 
      Inherited Members
      
             EnumType()
     
      
 
-        
+    
             
      __init__(group, datatype, datatype_name, enum_dict)
      
 
 
      EnumType constructor.
      
@@ -4615,28 +4662,31 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.EnumType' objects>
+        dtype
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.EnumType' objects>
+        name
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        enum_dict = <attribute 'enum_dict' of 'netCDF4._netCDF4.EnumType' objects>
+        enum_dict
     
      
 
     
+    
 
                             
      
                 
@@ -4648,7 +4698,7 @@ 
      Inherited Members
      
             get_chunk_cache(unknown):
     
      
 
-        
+    
             
      get_chunk_cache()
      
 
 
      return current netCDF chunk cache information in a tuple (size,nelems,preemption).
@@ -4666,7 +4716,7 @@ 
      Inherited Members
      
             set_chunk_cache(unknown):
     
      
 
-        
+    
             
      set_chunk_cache(self,size=None,nelems=None,preemption=None)
      
 
 
      change netCDF4 chunk cache settings.
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 188d56956..c835943dc 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2691,7 +2691,7 @@ is an empty tuple, which means the variable is a scalar.
 
 If the optional keyword argument `compression` is set, the data will be
 compressed in the netCDF file using the specified compression algorithm.
-Currently `zlib`,`szip`, `zstd`,`bzip2`,`blosc_lz`,`blosc_lz4`,`blosc_lz4hc`,
+Currently `zlib`,`szip`,`zstd`,`bzip2`,`blosc_lz`,`blosc_lz4`,`blosc_lz4hc`,
 `blosc_zlib` and `blosc_zstd` are supported.
 Default is `None` (no compression).  All of the compressors except
 `zlib` and `szip` use the HDF5 plugin architecture, which requires that the
@@ -2718,6 +2718,11 @@ unless the blosc compressor is used. `blosc_shuffle` can be 0 (no shuffle),
 is the tunable blosc blocksize in bytes (Default 0 means the blocksize is
 chosen internally).
 
+The optional kwargs `szip_coding` and `szip_pixels_per_block` are ignored
+unless the szip compressor is used. `szip_coding` can be `ec` (entropy coding)
+or `nn` (nearest neighbor coding). Default is `nn`. `szip_pixels_per_block`
+can be 4, 8, 16 or 32 (default 8).
+
 If the optional keyword `fletcher32` is `True`, the Fletcher32 HDF5
 checksum algorithm is activated to detect errors. Default `False`.
 
@@ -3713,7 +3718,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         which means the variable is a scalar (and therefore has no dimensions).
 
         **`compression`**: compression algorithm to use. 
-        Currently `zlib`,`szip`, `zstd`,`bzip2`,`blosc_lz`,`blosc_lz4`,`blosc_lz4hc`,
+        Currently `zlib`,`szip`,`zstd`,`bzip2`,`blosc_lz`,`blosc_lz4`,`blosc_lz4hc`,
         `blosc_zlib` and `blosc_zstd` are supported.
         Default is `None` (no compression).  All of the compressors except
         `zlib` use the HDF5 plugin architecture, which requires that the
@@ -3727,7 +3732,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
 
         **`complevel`**: the level of compression to use (1 is the fastest,
         but poorest compression, 9 is the slowest but best compression). Default 4.
-        Ignored if `compression=None`. A value of 0 disables compression.
+        Ignored if `compression=None` or `szip`. A value of 0 disables compression.
 
         **`shuffle`**: if `True`, the HDF5 shuffle filter is applied
         to improve zlib compression. Default `True`. Ignored unless `compression = 'zlib'`.
@@ -3735,10 +3740,18 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         **`blosc_shuffle`**: shuffle filter inside blosc compressor (only
         relevant if compression kwarg set to one of the blosc compressors).
         Can be 0 (no blosc shuffle), 1 (bytewise shuffle) or 2 (bitwise
-        shuffle)). Default is 1.
+        shuffle)). Default is 1. Ignored if blosc compressor not used.
 
         **`blosc_blocksize`**: tunable blocksize in bytes for blosc
         compressors. Default of 0 means blosc library chooses a blocksize.
+        Ignored if blosc compressor not used.
+
+        **`szip_coding`**: szip coding method. Can be `ec` (entropy coding)
+        or `nn` (nearest neighbor coding). Default is `nn`.
+        Ignored if szip compressor not used.
+
+        **`szip_pixels_per_block`**: Can be 4,8,16 or 32 (Default 8). 
+        Ignored if szip compressor not used.
 
         **`fletcher32`**: if `True` (default `False`), the Fletcher32 checksum
         algorithm is used for error detection.

From 32434d3a60fde4be20f95608f7c8cafa9abaedb1 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 9 May 2022 12:50:03 -0600
Subject: [PATCH 0818/1504] update docs

---
 docs/index.html          | 41 +++++++++++++++++++++++++---------------
 src/netCDF4/_netCDF4.pyx | 36 ++++++++++++++++++++++-------------
 2 files changed, 49 insertions(+), 28 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 99c42d903..79a1a735c 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -488,6 +488,11 @@ 
      Quick Install
      
 
        
 
      • the easiest way to get going is to install via pip install netCDF4.
 (or if you use the conda package manager conda install -c conda-forge netCDF4).
        • 
+
      • installing binary wheels with pip will not get you the optional compression filters (which are enabled
+via external plugins).  Starting with version 4.9.0, The plugins are available 
+via the netcdf-c library install, and are installed
+in /usr/local/hdf5/lib/plugin by default.  The environment variable HDF5_PLUGIN_PATH should be set
+to point to the location of the plugin install directory. 
        • 
 
      
 
 
      Developer Install
      
@@ -1077,17 +1082,19 @@ 
      Reading data from a multi
 
 
      Efficient compression of netCDF variables
      
 
-
      Data stored in netCDF 4 Variable objects can be compressed and
-decompressed on the fly. The parameters for the compression are
-determined by the compression, complevel and shuffle keyword arguments
-to the Dataset.createVariable method. To turn on
-compression, set compression=zlib.  The complevel keyword regulates the
-speed and efficiency of the compression (1 being fastest, but lowest
+
      Data stored in netCDF Variable objects can be compressed and
+decompressed on the fly. The compression algorithm used is determined
+by the compression keyword argument to the Dataset.createVariable method.
+zlib compression is always available, szip is available if the linked HDF5
+library supports it, and zstd, bzip2, blosc_lz,blosc_lz4,blosc_lz4hc,
+blosc_zlib and blosc_zstd are available via optional external plugins.
+The complevel keyword regulates the
+speed and efficiency of the compression for zlib, bzip and zstd (1 being fastest, but lowest
 compression ratio, 9 being slowest but best compression ratio). The
 default value of complevel is 4. Setting shuffle=False will turn
 off the HDF5 shuffle filter, which de-interlaces a block of data before
-compression by reordering the bytes.  The shuffle filter can
-significantly improve compression ratios, and is on by default.  Setting
+zlib compression by reordering the bytes.  The shuffle filter can
+significantly improve compression ratios, and is on by default if compression=zlib.  Setting
 fletcher32 keyword argument to
 Dataset.createVariable to True (it's False by
 default) enables the Fletcher32 checksum algorithm for error detection.
@@ -1097,7 +1104,14 @@ 
      Efficient compression of netC
 Dataset.createVariable.  These keyword arguments only
 are relevant for NETCDF4 and NETCDF4_CLASSIC files (where the
 underlying file format is HDF5) and are silently ignored if the file
-format is NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
      
+format is NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
+If netcdf-c compression filter plugins are installed, and the
+HDF5_PLUGIN_PATH environment variable is set to point to where the plugins
+are installed, then zstd, bzip2, and the blosc family of compressors
+can be used. 
      
+If the HDF5 library is built with szip support, compression=szip can also
+be used (in conjunction with the szip_coding and szip_pixels_per_block keyword
+arguments).  
      
 
 
      If your data only has a certain number of digits of precision (say for
 example, it is temperature data that was measured with a precision of
@@ -1613,7 +1627,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -2098,9 +2112,9 @@ 
      In-memory (diskless) Datasets
      
 blosc_zlib and blosc_zstd are supported.
 Default is None (no compression).  All of the compressors except
 zlib and szip use the HDF5 plugin architecture, which requires that the
-environment variable HDF5_PLUGIN_PATH be set to the location of the
+environment variable HDF5_PLUGIN_PATH be set to the location of the external
 plugins built by netcdf-c (unless the plugins are installed in the
-default location /usr/local/hdf5/lib).
      
+default location /usr/local/hdf5/lib/plugin).
      
 
 
      If the optional keyword zlib is True, the data will be compressed in
 the netCDF file using zlib compression (default False).  The use of this option is 
@@ -2153,9 +2167,6 @@ 
      In-memory (diskless) Datasets
      
 opposite format as the one used to create the file, there may be
 some performance advantage to be gained by setting the endian-ness.
      
 
-
      The compression, zlib, complevel, shuffle, fletcher32, contiguous, chunksizes and endian
-keywords are silently ignored for netCDF 3 files that do not use HDF5.
      
-
 
      The optional keyword fill_value can be used to override the default
 netCDF _FillValue (the value that the variable gets filled with before
 any data is written to it, defaults given in the dict netCDF4.default_fillvals).
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index c835943dc..d69298668 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -27,6 +27,11 @@ types) are not supported.
 
  - the easiest way to get going is to install via `pip install netCDF4`.
    (or if you use the [conda](http://conda.io) package manager `conda install -c conda-forge netCDF4`).
+ - installing binary wheels with pip will not get you the optional compression filters (which are enabled
+   via external plugins).  Starting with version 4.9.0, The plugins are available 
+   via the netcdf-c library install, and are installed
+   in `/usr/local/hdf5/lib/plugin` by default.  The environment variable `HDF5_PLUGIN_PATH` should be set
+   to point to the location of the plugin install directory. 
 
 ## Developer Install
 
@@ -641,17 +646,19 @@ datasets.
 
 ## Efficient compression of netCDF variables
 
-Data stored in netCDF 4 `Variable` objects can be compressed and
-decompressed on the fly. The parameters for the compression are
-determined by the `compression`, `complevel` and `shuffle` keyword arguments
-to the `Dataset.createVariable` method. To turn on
-compression, set compression=`zlib`.  The `complevel` keyword regulates the
-speed and efficiency of the compression (1 being fastest, but lowest
+Data stored in netCDF `Variable` objects can be compressed and
+decompressed on the fly. The compression algorithm used is determined
+by the `compression` keyword argument to the `Dataset.createVariable` method.
+`zlib` compression is always available, `szip` is available if the linked HDF5
+library supports it, and `zstd`, `bzip2`, `blosc_lz`,`blosc_lz4`,`blosc_lz4hc`,
+`blosc_zlib` and `blosc_zstd` are available via optional external plugins.
+The `complevel` keyword regulates the
+speed and efficiency of the compression for `zlib`, `bzip` and `zstd` (1 being fastest, but lowest
 compression ratio, 9 being slowest but best compression ratio). The
 default value of `complevel` is 4. Setting `shuffle=False` will turn
 off the HDF5 shuffle filter, which de-interlaces a block of data before
-compression by reordering the bytes.  The shuffle filter can
-significantly improve compression ratios, and is on by default.  Setting
+`zlib` compression by reordering the bytes.  The shuffle filter can
+significantly improve compression ratios, and is on by default if `compression=zlib`.  Setting
 `fletcher32` keyword argument to
 `Dataset.createVariable` to `True` (it's `False` by
 default) enables the Fletcher32 checksum algorithm for error detection.
@@ -662,6 +669,12 @@ and `endian` keyword arguments to
 are relevant for `NETCDF4` and `NETCDF4_CLASSIC` files (where the
 underlying file format is HDF5) and are silently ignored if the file
 format is `NETCDF3_CLASSIC`, `NETCDF3_64BIT_OFFSET` or `NETCDF3_64BIT_DATA`.
+If netcdf-c compression filter plugins are installed, and the
+`HDF5_PLUGIN_PATH` environment variable is set to point to where the plugins
+are installed, then `zstd`, `bzip2`, and the `blosc` family of compressors
+can be used. If the HDF5 library is built with szip support, compression=`szip` can also
+be used (in conjunction with the `szip_coding` and `szip_pixels_per_block` keyword
+arguments).  
 
 If your data only has a certain number of digits of precision (say for
 example, it is temperature data that was measured with a precision of
@@ -2695,9 +2708,9 @@ Currently `zlib`,`szip`,`zstd`,`bzip2`,`blosc_lz`,`blosc_lz4`,`blosc_lz4hc`,
 `blosc_zlib` and `blosc_zstd` are supported.
 Default is `None` (no compression).  All of the compressors except
 `zlib` and `szip` use the HDF5 plugin architecture, which requires that the
-environment variable `HDF5_PLUGIN_PATH` be set to the location of the
+environment variable `HDF5_PLUGIN_PATH` be set to the location of the external
 plugins built by netcdf-c (unless the plugins are installed in the
-default location `/usr/local/hdf5/lib`).
+default location `/usr/local/hdf5/lib/plugin`).
 
 If the optional keyword `zlib` is `True`, the data will be compressed in
 the netCDF file using zlib compression (default `False`).  The use of this option is 
@@ -2750,9 +2763,6 @@ but if the data is always going to be read on a computer with the
 opposite format as the one used to create the file, there may be
 some performance advantage to be gained by setting the endian-ness.
 
-The `compression, zlib, complevel, shuffle, fletcher32, contiguous, chunksizes` and `endian`
-keywords are silently ignored for netCDF 3 files that do not use HDF5.
-
 The optional keyword `fill_value` can be used to override the default
 netCDF `_FillValue` (the value that the variable gets filled with before
 any data is written to it, defaults given in the dict `netCDF4.default_fillvals`).

From a9731f0d4d5c82f0f6f56a789a689db96603f13c Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Wed, 11 May 2022 08:09:25 -0600
Subject: [PATCH 0819/1504] install plugin .so files inside package

---
 .github/workflows/build_master.yml |  8 +++-----
 setup.py                           | 12 +++++++++++-
 src/netCDF4/__init__.py            |  4 ++++
 3 files changed, 18 insertions(+), 6 deletions(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 35e6d43fb..10e5fa508 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -31,12 +31,9 @@ jobs:
         export LDFLAGS="-L${NETCDF_DIR}/lib"
         export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
         autoreconf -i
-        ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 
+        ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4
         make -j 2
         make install
-        pwd
-        mkdir ${NETCDF_DIR}/hdf5_plugins
-        /bin/mv -f plugins ${NETCDF_DIR}
         popd
 
 #   - name: The job has failed
@@ -53,11 +50,12 @@ jobs:
     - name: Install netcdf4-python
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
+        export NETCDF_PLUGIN_DIR=${NETCDF_DIR}/plugins/.libs
         python setup.py install
     - name: Test
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
-        export HDF5_PLUGIN_PATH=${NETCDF_DIR}/plugins/.libs
+        #export HDF5_PLUGIN_PATH=${NETCDF_DIR}/plugins/.libs
         python checkversion.py
         # serial
         cd test
diff --git a/setup.py b/setup.py
index 9cf48528e..cd7d39715 100644
--- a/setup.py
+++ b/setup.py
@@ -1,4 +1,4 @@
-import os, sys, subprocess
+import os, sys, subprocess, glob
 import os.path as osp
 import configparser
 from setuptools import setup, Extension
@@ -682,6 +682,15 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 else:
     ext_modules = None
 
+# if NETCDF_PLUGIN_DIR set, install netcdf-c plugin shared objects in package
+# (should point to location of .so files built by netcdf-c)
+if os.environ.get("NETCDF_PLUGIN_DIR"):
+    plugin_dir = os.environ.get("NETCDF_PLUGIN_DIR")
+    plugins = glob.glob(os.path.join(plugin_dir, "*.so"))
+    data_files = plugins
+else:
+    data_files = None
+
 setup(name="netCDF4",
       cmdclass=cmdclass,
       version=extract_version(netcdf4_src_pyx),
@@ -707,5 +716,6 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
                    "Operating System :: OS Independent"],
       packages=['netCDF4'],
       package_dir={'':'src'},
+      data_files=[('netCDF4',data_files)],
       ext_modules=ext_modules,
       **setuptools_extra_kwargs)
diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py
index f518b128e..f53195897 100644
--- a/src/netCDF4/__init__.py
+++ b/src/netCDF4/__init__.py
@@ -10,5 +10,9 @@
                        __has_parallel4_support__, __has_pnetcdf_support__,
                        __has_quantization_support__, __has_zstandard_support__,
                        __has_bzip2_support__, __has_blosc_support__, __has_szip_support__)
+import os
 __all__ =\
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
+# if HDF5_PLUGIN_PATH not set, point to plugins directory inside package
+if 'HDF5_PLUGIN_PATH' not in os.environ:
+    os.environ['HDF5_PLUGIN_PATH']=__path__[0]

From d496f040ffc72fe76adcef96352f946b207af53a Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Wed, 11 May 2022 08:19:32 -0600
Subject: [PATCH 0820/1504] update docs

---
 docs/index.html          | 25 +++++++------------------
 src/netCDF4/_netCDF4.pyx | 20 +++-----------------
 2 files changed, 10 insertions(+), 35 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 79a1a735c..0164a5609 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -488,11 +488,6 @@ 
      Quick Install
      
 
        
 
      • the easiest way to get going is to install via pip install netCDF4.
 (or if you use the conda package manager conda install -c conda-forge netCDF4).
        • 
-
      • installing binary wheels with pip will not get you the optional compression filters (which are enabled
-via external plugins).  Starting with version 4.9.0, The plugins are available 
-via the netcdf-c library install, and are installed
-in /usr/local/hdf5/lib/plugin by default.  The environment variable HDF5_PLUGIN_PATH should be set
-to point to the location of the plugin install directory. 
        • 
 
      
 
 
      Developer Install
      
@@ -1105,10 +1100,6 @@ 
      Efficient compression of netC
 are relevant for NETCDF4 and NETCDF4_CLASSIC files (where the
 underlying file format is HDF5) and are silently ignored if the file
 format is NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.
-If netcdf-c compression filter plugins are installed, and the
-HDF5_PLUGIN_PATH environment variable is set to point to where the plugins
-are installed, then zstd, bzip2, and the blosc family of compressors
-can be used. 
      
 If the HDF5 library is built with szip support, compression=szip can also
 be used (in conjunction with the szip_coding and szip_pixels_per_block keyword
 arguments).  
      
@@ -1627,7 +1618,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -1652,8 +1643,12 @@ 
      In-memory (diskless) Datasets
      
                        __has_parallel4_support__, __has_pnetcdf_support__,
                        __has_quantization_support__, __has_zstandard_support__,
                        __has_bzip2_support__, __has_blosc_support__, __has_szip_support__)
+import os
 __all__ =\
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
+# if HDF5_PLUGIN_PATH not set, point to plugins directory inside package
+if 'HDF5_PLUGIN_PATH' not in os.environ:
+    os.environ['HDF5_PLUGIN_PATH']=__path__[0]
 
      
 
         
@@ -2111,10 +2106,7 @@ 
      In-memory (diskless) Datasets
      
 Currently zlib,szip,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,
 blosc_zlib and blosc_zstd are supported.
 Default is None (no compression).  All of the compressors except
-zlib and szip use the HDF5 plugin architecture, which requires that the
-environment variable HDF5_PLUGIN_PATH be set to the location of the external
-plugins built by netcdf-c (unless the plugins are installed in the
-default location /usr/local/hdf5/lib/plugin).
      
+zlib and szip use the HDF5 plugin architecture.
      
 
 
      If the optional keyword zlib is True, the data will be compressed in
 the netCDF file using zlib compression (default False).  The use of this option is 
@@ -2919,10 +2911,7 @@ 
      In-memory (diskless) Datasets
      
 Currently zlib,szip,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc,
 blosc_zlib and blosc_zstd are supported.
 Default is None (no compression).  All of the compressors except
-zlib use the HDF5 plugin architecture, which requires that the
-environment variable HDF5_PLUGIN_PATH be set to the location of the
-plugins built by netcdf-c (unless the plugins are installed in the
-default location /usr/local/hdf5/lib).
      
+zlib and szip use the HDF5 plugin architecture.
      
 
 
      zlib: if True, data assigned to the Variable
 instance is compressed on disk. Default False. Deprecated - use
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index d69298668..278f21224 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -27,11 +27,6 @@ types) are not supported.
 
  - the easiest way to get going is to install via `pip install netCDF4`.
    (or if you use the [conda](http://conda.io) package manager `conda install -c conda-forge netCDF4`).
- - installing binary wheels with pip will not get you the optional compression filters (which are enabled
-   via external plugins).  Starting with version 4.9.0, The plugins are available 
-   via the netcdf-c library install, and are installed
-   in `/usr/local/hdf5/lib/plugin` by default.  The environment variable `HDF5_PLUGIN_PATH` should be set
-   to point to the location of the plugin install directory. 
 
 ## Developer Install
 
@@ -669,10 +664,7 @@ and `endian` keyword arguments to
 are relevant for `NETCDF4` and `NETCDF4_CLASSIC` files (where the
 underlying file format is HDF5) and are silently ignored if the file
 format is `NETCDF3_CLASSIC`, `NETCDF3_64BIT_OFFSET` or `NETCDF3_64BIT_DATA`.
-If netcdf-c compression filter plugins are installed, and the
-`HDF5_PLUGIN_PATH` environment variable is set to point to where the plugins
-are installed, then `zstd`, `bzip2`, and the `blosc` family of compressors
-can be used. If the HDF5 library is built with szip support, compression=`szip` can also
+If the HDF5 library is built with szip support, compression=`szip` can also
 be used (in conjunction with the `szip_coding` and `szip_pixels_per_block` keyword
 arguments).  
 
@@ -2707,10 +2699,7 @@ compressed in the netCDF file using the specified compression algorithm.
 Currently `zlib`,`szip`,`zstd`,`bzip2`,`blosc_lz`,`blosc_lz4`,`blosc_lz4hc`,
 `blosc_zlib` and `blosc_zstd` are supported.
 Default is `None` (no compression).  All of the compressors except
-`zlib` and `szip` use the HDF5 plugin architecture, which requires that the
-environment variable `HDF5_PLUGIN_PATH` be set to the location of the external
-plugins built by netcdf-c (unless the plugins are installed in the
-default location `/usr/local/hdf5/lib/plugin`).
+`zlib` and `szip` use the HDF5 plugin architecture.
 
 If the optional keyword `zlib` is `True`, the data will be compressed in
 the netCDF file using zlib compression (default `False`).  The use of this option is 
@@ -3731,10 +3720,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         Currently `zlib`,`szip`,`zstd`,`bzip2`,`blosc_lz`,`blosc_lz4`,`blosc_lz4hc`,
         `blosc_zlib` and `blosc_zstd` are supported.
         Default is `None` (no compression).  All of the compressors except
-        `zlib` use the HDF5 plugin architecture, which requires that the
-        environment variable `HDF5_PLUGIN_PATH` be set to the location of the
-        plugins built by netcdf-c (unless the plugins are installed in the
-        default location `/usr/local/hdf5/lib`).
+        `zlib` and `szip` use the HDF5 plugin architecture.
 
         **`zlib`**: if `True`, data assigned to the `Variable`
         instance is compressed on disk. Default `False`. Deprecated - use

From 7fc0be8cbfbed62f151faf5c22b3c9509d9d99cf Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Wed, 11 May 2022 08:29:59 -0600
Subject: [PATCH 0821/1504] fix error in data_files when NETCDF_PLUGIN_DIR

---
 setup.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index cd7d39715..beeb0950f 100644
--- a/setup.py
+++ b/setup.py
@@ -689,7 +689,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     plugins = glob.glob(os.path.join(plugin_dir, "*.so"))
     data_files = plugins
 else:
-    data_files = None
+    data_files = []
 
 setup(name="netCDF4",
       cmdclass=cmdclass,

From 788b0652744f1f59773370892b9ade91d50ca719 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Wed, 11 May 2022 09:48:38 -0600
Subject: [PATCH 0822/1504] print whether plugins installed

---
 setup.py | 10 +++++++++-
 1 file changed, 9 insertions(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index beeb0950f..81ab37576 100644
--- a/setup.py
+++ b/setup.py
@@ -687,8 +687,16 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 if os.environ.get("NETCDF_PLUGIN_DIR"):
     plugin_dir = os.environ.get("NETCDF_PLUGIN_DIR")
     plugins = glob.glob(os.path.join(plugin_dir, "*.so"))
-    data_files = plugins
+    if not plugins:
+        sys.stdout.write('no .so files in NETCDF_PLUGIN_DIR, no plugin shared objects installed\n')
+        data_files = []
+    else:
+        data_files = plugins
+        sys.stdout.write('installing plugin shared objects from %s ...\n' % plugin_dir)
+        sofiles = [os.path.basename(sofilepath) for sofilepath in data_files]
+        sys.stdout.write(repr(sofiles)+'\n')
 else:
+    sys.stdout.write('NETCDF_PLUGIN_DIR not set, no plugin shared objects installed\n')
     data_files = []
 
 setup(name="netCDF4",

From ad94b2dbbf234282fd2fabdf7dc534ab5291ef04 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 14 May 2022 11:07:25 -0600
Subject: [PATCH 0823/1504] update

---
 test/tst_compression_blosc.py | 37 +++++++++++++++++++----------------
 1 file changed, 20 insertions(+), 17 deletions(-)

diff --git a/test/tst_compression_blosc.py b/test/tst_compression_blosc.py
index 66ca0e9e4..891f53b90 100644
--- a/test/tst_compression_blosc.py
+++ b/test/tst_compression_blosc.py
@@ -4,24 +4,27 @@
 import os, tempfile, unittest
 
 ndim = 100000
+iblosc_shuffle=2
+iblosc_blocksize=800000
+iblosc_complevel=4
 filename = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
 datarr = uniform(size=(ndim,))
 
-def write_netcdf(filename,dtype='f8',complevel=6):
+def write_netcdf(filename,dtype='f8',blosc_shuffle=1,blosc_blocksize=500000,complevel=6):
     nc = Dataset(filename,'w')
     nc.createDimension('n', ndim)
     foo = nc.createVariable('data',\
             dtype,('n'),compression=None)
     foo_lz = nc.createVariable('data_lz',\
-            dtype,('n'),compression='blosc_lz',blosc_shuffle=2,complevel=complevel)
+            dtype,('n'),compression='blosc_lz',blosc_shuffle=blosc_shuffle,blosc_blocksize=blosc_blocksize,complevel=complevel)
     foo_lz4 = nc.createVariable('data_lz4',\
-            dtype,('n'),compression='blosc_lz4',blosc_shuffle=2,complevel=complevel)
+            dtype,('n'),compression='blosc_lz4',blosc_shuffle=blosc_shuffle,blosc_blocksize=blosc_blocksize,complevel=complevel)
     foo_lz4hc = nc.createVariable('data_lz4hc',\
-            dtype,('n'),compression='blosc_lz4hc',blosc_shuffle=2,complevel=complevel)
+            dtype,('n'),compression='blosc_lz4hc',blosc_shuffle=blosc_shuffle,blosc_blocksize=blosc_blocksize,complevel=complevel)
     foo_zlib = nc.createVariable('data_zlib',\
-            dtype,('n'),compression='blosc_zlib',blosc_shuffle=2,complevel=complevel)
+            dtype,('n'),compression='blosc_zlib',blosc_shuffle=blosc_shuffle,blosc_blocksize=blosc_blocksize,complevel=complevel)
     foo_zstd = nc.createVariable('data_zstd',\
-            dtype,('n'),compression='blosc_zstd',blosc_shuffle=2,complevel=complevel)
+            dtype,('n'),compression='blosc_zstd',blosc_shuffle=blosc_shuffle,blosc_blocksize=blosc_blocksize,complevel=complevel)
     foo_lz[:] = datarr
     foo_lz4[:] = datarr
     foo_lz4hc[:] = datarr
@@ -33,7 +36,7 @@ class CompressionTestCase(unittest.TestCase):
 
     def setUp(self):
         self.filename = filename
-        write_netcdf(self.filename,complevel=4) # with compression
+        write_netcdf(self.filename,complevel=iblosc_complevel,blosc_shuffle=iblosc_shuffle,blosc_blocksize=iblosc_blocksize) # with compression
 
     def tearDown(self):
         # Remove the temporary files
@@ -46,28 +49,28 @@ def runTest(self):
         {'zlib':False,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
         assert_almost_equal(datarr,f.variables['data_lz'][:])
         dtest = {'zlib': False, 'szip':False, 'zstd': False, 'bzip2': False, 'blosc':
-                {'compressor': 'blosc_lz', 'shuffle': 2, 'blocksize': 800000},
-                'shuffle': False, 'complevel': 4, 'fletcher32': False}
+                {'compressor': 'blosc_lz', 'shuffle': iblosc_shuffle, 'blocksize': iblosc_blocksize},
+                'shuffle': False, 'complevel': iblosc_complevel, 'fletcher32': False}
         assert f.variables['data_lz'].filters() == dtest
         assert_almost_equal(datarr,f.variables['data_lz4'][:])
         dtest = {'zlib': False, 'szip':False, 'zstd': False, 'bzip2': False, 'blosc':
-                {'compressor': 'blosc_lz4', 'shuffle': 2, 'blocksize': 800000},
-                'shuffle': False, 'complevel': 4, 'fletcher32': False}
+                {'compressor': 'blosc_lz4', 'shuffle': iblosc_shuffle, 'blocksize': iblosc_blocksize},
+                'shuffle': False, 'complevel': iblosc_complevel, 'fletcher32': False}
         assert f.variables['data_lz4'].filters() == dtest
         assert_almost_equal(datarr,f.variables['data_lz4hc'][:])
         dtest = {'zlib': False, 'szip':False, 'zstd': False, 'bzip2': False, 'blosc':
-                {'compressor': 'blosc_lz4hc', 'shuffle': 2, 'blocksize': 800000},
-                'shuffle': False, 'complevel': 4, 'fletcher32': False}
+                {'compressor': 'blosc_lz4hc', 'shuffle': iblosc_shuffle, 'blocksize': iblosc_blocksize},
+                'shuffle': False, 'complevel': iblosc_complevel, 'fletcher32': False}
         assert f.variables['data_lz4hc'].filters() == dtest
         assert_almost_equal(datarr,f.variables['data_zlib'][:])
         dtest = {'zlib': False, 'szip':False, 'zstd': False, 'bzip2': False, 'blosc':
-                {'compressor': 'blosc_zlib', 'shuffle': 2, 'blocksize': 800000},
-                'shuffle': False, 'complevel': 4, 'fletcher32': False}
+                {'compressor': 'blosc_zlib', 'shuffle': iblosc_shuffle, 'blocksize': iblosc_blocksize},
+                'shuffle': False, 'complevel': iblosc_complevel, 'fletcher32': False}
         assert f.variables['data_zlib'].filters() == dtest
         assert_almost_equal(datarr,f.variables['data_zstd'][:])
         dtest = {'zlib': False, 'szip':False, 'zstd': False, 'bzip2': False, 'blosc':
-                {'compressor': 'blosc_zstd', 'shuffle': 2, 'blocksize': 800000},
-                'shuffle': False, 'complevel': 4, 'fletcher32': False}
+                {'compressor': 'blosc_zstd', 'shuffle': iblosc_shuffle, 'blocksize': iblosc_blocksize},
+                'shuffle': False, 'complevel': iblosc_complevel, 'fletcher32': False}
         assert f.variables['data_zstd'].filters() == dtest
         f.close()
 

From fa81251f03dc0643ad21059b95d4c025159eea16 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 14 May 2022 11:30:15 -0600
Subject: [PATCH 0824/1504] remove blosc_blocksize kwarg, netcdf-c ignores it
 and uses var chunksize

---
 docs/index.html               | 447 +++++++++++++++-------------------
 src/netCDF4/_netCDF4.pyx      |  24 +-
 test/tst_compression_blosc.py |  25 +-
 3 files changed, 224 insertions(+), 272 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 0164a5609..c923bcdb4 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -3,24 +3,24 @@
 
     
     
-    
+    
     netCDF4 API documentation
+    
 
-    
-    
-    
-    
-    
-    
-
-    
      
     
      
             
      
                     
      
@@ -577,7 +576,7 @@ 
      Creating/Opening/Closing a netCDF
 
 
      Here's an example:
      
 
-
      >>> from netCDF4 import Dataset
+
      >>> from netCDF4 import Dataset
 >>> rootgrp = Dataset("test.nc", "w", format="NETCDF4")
 >>> print(rootgrp.data_model)
 NETCDF4
@@ -606,7 +605,7 @@ 
      Groups in a netCDF file
      
 NETCDF4 formatted files support Groups, if you try to create a Group
 in a netCDF 3 file you will get an error message.
      
 
-
      >>> rootgrp = Dataset("test.nc", "a")
+
      >>> rootgrp = Dataset("test.nc", "a")
 >>> fcstgrp = rootgrp.createGroup("forecasts")
 >>> analgrp = rootgrp.createGroup("analyses")
 >>> print(rootgrp.groups)
@@ -630,7 +629,7 @@ 
      Groups in a netCDF file
      
 that group.  To simplify the creation of nested groups, you can
 use a unix-like path as an argument to Dataset.createGroup.
      
 
-
      >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
+
      >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
 >>> fcstgrp2 = rootgrp.createGroup("/forecasts/model2")
 
      
 
@@ -644,7 +643,7 @@ 
      Groups in a netCDF file
      
 to walk the directory tree. Note that printing the Dataset or Group
 object yields summary information about it's contents.
      
 
-
      >>> def walktree(top):
+
      >>> def walktree(top):
 ...     yield top.groups.values()
 ...     for value in top.groups.values():
 ...         yield from walktree(value)
@@ -694,7 +693,7 @@ 
      Dimensions in a netCDF file
      
 dimension is a new netCDF 4 feature, in netCDF 3 files there may be only
 one, and it must be the first (leftmost) dimension of the variable.
      
 
-
      >>> level = rootgrp.createDimension("level", None)
+
      >>> level = rootgrp.createDimension("level", None)
 >>> time = rootgrp.createDimension("time", None)
 >>> lat = rootgrp.createDimension("lat", 73)
 >>> lon = rootgrp.createDimension("lon", 144)
@@ -702,7 +701,7 @@ 
      Dimensions in a netCDF file
      
 
 
      All of the Dimension instances are stored in a python dictionary.
      
 
-
      >>> print(rootgrp.dimensions)
+
      >>> print(rootgrp.dimensions)
 {'level': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0, 'time': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0, 'lat': <class 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 73, 'lon': <class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144}
 
      
 
@@ -711,7 +710,7 @@ 
      Dimensions in a netCDF file
      
 Dimension.isunlimited method of a Dimension instance
 be used to determine if the dimensions is unlimited, or appendable.
      
 
-
      >>> print(len(lon))
+
      >>> print(len(lon))
 144
 >>> print(lon.isunlimited())
 False
@@ -723,7 +722,7 @@ 
      Dimensions in a netCDF file
      
 provides useful summary info, including the name and length of the dimension,
 and whether it is unlimited.
      
 
-
      >>> for dimobj in rootgrp.dimensions.values():
+
      >>> for dimobj in rootgrp.dimensions.values():
 ...     print(dimobj)
 <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0
 <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0
@@ -768,7 +767,7 @@ 
      Variables in a netCDF file
      
 method returns an instance of the Variable class whose methods can be
 used later to access and set variable data and attributes.
      
 
-
      >>> times = rootgrp.createVariable("time","f8",("time",))
+
      >>> times = rootgrp.createVariable("time","f8",("time",))
 >>> levels = rootgrp.createVariable("level","i4",("level",))
 >>> latitudes = rootgrp.createVariable("lat","f4",("lat",))
 >>> longitudes = rootgrp.createVariable("lon","f4",("lon",))
@@ -780,7 +779,7 @@ 
      Variables in a netCDF file
      
 
      To get summary info on a Variable instance in an interactive session,
 just print it.
      
 
-
      >>> print(temp)
+
      >>> print(temp)
 <class 'netCDF4._netCDF4.Variable'>
 float32 temp(time, level, lat, lon)
     units: K
@@ -791,7 +790,7 @@ 
      Variables in a netCDF file
      
 
 
      You can use a path to create a Variable inside a hierarchy of groups.
      
 
-
      >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
+
      >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
 
      
 
 
      If the intermediate groups do not yet exist, they will be created.
      
@@ -799,7 +798,7 @@ 
      Variables in a netCDF file
      
 
      You can also query a Dataset or Group instance directly to obtain Group or
 Variable instances using paths.
      
 
-
      >>> print(rootgrp["/forecasts/model1"])  # a Group instance
+
      >>> print(rootgrp["/forecasts/model1"])  # a Group instance
 <class 'netCDF4._netCDF4.Group'>
 group /forecasts/model1:
     dimensions(sizes): 
@@ -817,7 +816,7 @@ 
      Variables in a netCDF file
      
 
      All of the variables in the Dataset or Group are stored in a
 Python dictionary, in the same way as the dimensions:
      
 
-
      >>> print(rootgrp.variables)
+
      >>> print(rootgrp.variables)
 {'time': <class 'netCDF4._netCDF4.Variable'>
 float64 time(time)
 unlimited dimensions: time
@@ -860,7 +859,7 @@ 
      Attributes in a netCDF file
      
 variables. Attributes can be strings, numbers or sequences. Returning to
 our example,
      
 
-
      >>> import time
+
      >>> import time
 >>> rootgrp.description = "bogus example script"
 >>> rootgrp.history = "Created " + time.ctime(time.time())
 >>> rootgrp.source = "netCDF4 python module tutorial"
@@ -878,7 +877,7 @@ 
      Attributes in a netCDF file
      
 built-in dir Python function will return a bunch of private methods
 and attributes that cannot (or should not) be modified by the user.
      
 
-
      >>> for name in rootgrp.ncattrs():
+
      >>> for name in rootgrp.ncattrs():
 ...     print("Global attr {} = {}".format(name, getattr(rootgrp, name)))
 Global attr description = bogus example script
 Global attr history = Created Mon Jul  8 14:19:41 2019
@@ -889,7 +888,7 @@ 
      Attributes in a netCDF file
      
 instance provides all the netCDF attribute name/value pairs in a python
 dictionary:
      
 
-
      >>> print(rootgrp.__dict__)
+
      >>> print(rootgrp.__dict__)
 {'description': 'bogus example script', 'history': 'Created Mon Jul  8 14:19:41 2019', 'source': 'netCDF4 python module tutorial'}
 
      
 
@@ -902,7 +901,7 @@ 
      Writing data
 
      Now that you have a netCDF Variable instance, how do you put data
 into it? You can just treat it like an array and assign data to a slice.
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> lats =  np.arange(-90,91,2.5)
 >>> lons =  np.arange(-180,180,2.5)
 >>> latitudes[:] = lats
@@ -922,7 +921,7 @@ 
      Writing data
 objects with unlimited dimensions will grow along those dimensions if you
 assign data outside the currently defined range of indices.
      
 
-
      >>> # append along two unlimited dimensions by assigning to slice.
+
      >>> # append along two unlimited dimensions by assigning to slice.
 >>> nlats = len(rootgrp.dimensions["lat"])
 >>> nlons = len(rootgrp.dimensions["lon"])
 >>> print("temp shape before adding data = {}".format(temp.shape))
@@ -942,7 +941,7 @@ 
      Writing data
 along the level dimension of the variable temp, even though no
 data has yet been assigned to levels.
      
 
-
      >>> # now, assign data to levels dimension variable.
+
      >>> # now, assign data to levels dimension variable.
 >>> levels[:] =  [1000.,850.,700.,500.,300.,250.,200.,150.,100.,50.]
 
      
 
@@ -955,7 +954,7 @@ 
      Writing data
 allowed, and these indices work independently along each dimension (similar
 to the way vector subscripts work in fortran).  This means that
      
 
-
      >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
+
      >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
 (4, 4)
 
      
 
@@ -973,14 +972,14 @@ 
      Writing data
 
 
      For example,
      
 
-
      >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
+
      >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
 
      
 
 
      will extract time indices 0,2 and 4, pressure levels
 850, 500 and 200 hPa, all Northern Hemisphere latitudes and Eastern
 Hemisphere longitudes, resulting in a numpy array of shape  (3, 3, 36, 71).
      
 
-
      >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
+
      >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
 shape of fancy temp slice = (3, 3, 36, 71)
 
      
 
@@ -1013,7 +1012,7 @@ 
      Dealing with time coordinates
      
 provided by cftime to do just that.
 Here's an example of how they can be used:
      
 
-
      >>> # fill in times.
+
      >>> # fill in times.
 >>> from datetime import datetime, timedelta
 >>> from cftime import num2date, date2num
 >>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
@@ -1053,7 +1052,7 @@ 
      Reading data from a multi
 NETCDF4_CLASSIC format (NETCDF4 formatted multi-file
 datasets are not supported).
      
 
-
      >>> for nf in range(10):
+
      >>> for nf in range(10):
 ...     with Dataset("mftest%s.nc" % nf, "w", format="NETCDF4_CLASSIC") as f:
 ...         _ = f.createDimension("x",None)
 ...         x = f.createVariable("x","i",("x",))
@@ -1062,7 +1061,7 @@ 
      Reading data from a multi
 
 
      Now read all the files back in at once with MFDataset
      
 
-
      >>> from netCDF4 import MFDataset
+
      >>> from netCDF4 import MFDataset
 >>> f = MFDataset("mftest*nc")
 >>> print(f.variables["x"][:])
 [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
@@ -1129,22 +1128,22 @@ 
      Efficient compression of netC
 
 
      In our example, try replacing the line
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
 
      
 
 
      with
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib')
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib')
 
      
 
 
      and then
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',least_significant_digit=3)
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',least_significant_digit=3)
 
      
 
 
      or with netcdf-c >= 4.9.0
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',significant_digits=4)
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',significant_digits=4)
 
      
 
 
      and see how much smaller the resulting files are.
      
@@ -1165,7 +1164,7 @@ 
      Beyond ho
 Since there is no native complex data type in netcdf, compound types are handy
 for storing numpy complex arrays.  Here's an example:
      
 
-
      >>> f = Dataset("complex.nc","w")
+
      >>> f = Dataset("complex.nc","w")
 >>> size = 3 # length of 1-d complex array
 >>> # create sample complex data.
 >>> datac = np.exp(1j*(1.+np.linspace(0, np.pi, size)))
@@ -1201,7 +1200,7 @@ 
      Beyond ho
 in a Python dictionary, just like variables and dimensions. As always, printing
 objects gives useful summary information in an interactive session:
      
 
-
      >>> print(f)
+
      >>> print(f)
 <class 'netCDF4._netCDF4.Dataset'>
 root group (NETCDF4 data model, file format HDF5):
     dimensions(sizes): x_dim(3)
@@ -1226,7 +1225,7 @@ 
      Variable-length (vlen) data types
      
 data type, use the Dataset.createVLType method
 method of a Dataset or Group instance.
      
 
-
      >>> f = Dataset("tst_vlen.nc","w")
+
      >>> f = Dataset("tst_vlen.nc","w")
 >>> vlen_t = f.createVLType(np.int32, "phony_vlen")
 
      
 
@@ -1236,7 +1235,7 @@ 
      Variable-length (vlen) data types
      
 but compound data types cannot.
 A new variable can then be created using this datatype.
      
 
-
      >>> x = f.createDimension("x",3)
+
      >>> x = f.createDimension("x",3)
 >>> y = f.createDimension("y",4)
 >>> vlvar = f.createVariable("phony_vlen_var", vlen_t, ("y","x"))
 
      
@@ -1249,7 +1248,7 @@ 
      Variable-length (vlen) data types
      
 In this case, they contain 1-D numpy int32 arrays of random length between
 1 and 10.
      
 
-
      >>> import random
+
      >>> import random
 >>> random.seed(54321)
 >>> data = np.empty(len(y)*len(x),object)
 >>> for n in range(len(y)*len(x)):
@@ -1289,7 +1288,7 @@ 
      Variable-length (vlen) data types
      
 with fixed length greater than 1) when calling the
 Dataset.createVariable method.
      
 
-
      >>> z = f.createDimension("z",10)
+
      >>> z = f.createDimension("z",10)
 >>> strvar = f.createVariable("strvar", str, "z")
 
      
 
@@ -1297,7 +1296,7 @@ 
      Variable-length (vlen) data types
      
 random lengths between 2 and 12 characters, and the data in the object
 array is assigned to the vlen string variable.
      
 
-
      >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
+
      >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
 >>> data = np.empty(10,"O")
 >>> for n in range(10):
 ...     stringlen = random.randint(2,12)
@@ -1336,7 +1335,7 @@ 
      Enum data type
      
 values and their names are used to define an Enum data type using
 Dataset.createEnumType.
      
 
-
      >>> nc = Dataset('clouds.nc','w')
+
      >>> nc = Dataset('clouds.nc','w')
 >>> # python dict with allowed values and their names.
 >>> enum_dict = {'Altocumulus': 7, 'Missing': 255,
 ... 'Stratus': 2, 'Clear': 0,
@@ -1354,7 +1353,7 @@ 
      Enum data type
      
 is made to write an integer value not associated with one of the
 specified names.
      
 
-
      >>> time = nc.createDimension('time',None)
+
      >>> time = nc.createDimension('time',None)
 >>> # create a 1d variable of type 'cloud_type'.
 >>> # The fill_value is set to the 'Missing' named value.
 >>> cloud_var = nc.createVariable('primary_cloud',cloud_type,'time',
@@ -1391,7 +1390,7 @@ 
      Parallel IO
      
 available. To use parallel IO, your program must be running in an MPI
 environment using mpi4py.
      
 
-
      >>> from mpi4py import MPI
+
      >>> from mpi4py import MPI
 >>> import numpy as np
 >>> from netCDF4 import Dataset
 >>> rank = MPI.COMM_WORLD.rank  # The process ID (integer 0-3 for 4-process run)
@@ -1403,7 +1402,7 @@ 
      Parallel IO
      
 when a new dataset is created or an existing dataset is opened,
 use the parallel keyword to enable parallel access.
      
 
-
      >>> nc = Dataset('parallel_test.nc','w',parallel=True)
+
      >>> nc = Dataset('parallel_test.nc','w',parallel=True)
 
      
 
 
      The optional comm keyword may be used to specify a particular
@@ -1411,7 +1410,7 @@ 
      Parallel IO
      
 can now write to the file indepedently.  In this example the process rank is
 written to a different variable index on each task
      
 
-
      >>> d = nc.createDimension('dim',4)
+
      >>> d = nc.createDimension('dim',4)
 >>> v = nc.createVariable('var', np.int64, 'dim')
 >>> v[rank] = rank
 >>> nc.close()
@@ -1478,7 +1477,7 @@ 
      Dealing with strings
      
 stringtochar is used to convert the numpy string array to an array of
 characters with one more dimension. For example,
      
 
-
      >>> from netCDF4 import stringtochar
+
      >>> from netCDF4 import stringtochar
 >>> nc = Dataset('stringtest.nc','w',format='NETCDF4_CLASSIC')
 >>> _ = nc.createDimension('nchars',3)
 >>> _ = nc.createDimension('nstrings',None)
@@ -1511,7 +1510,7 @@ 
      Dealing with strings
      
 character array dtype under the hood when creating the netcdf compound type.
 Here's an example:
      
 
-
      >>> nc = Dataset('compoundstring_example.nc','w')
+
      >>> nc = Dataset('compoundstring_example.nc','w')
 >>> dtype = np.dtype([('observation', 'f4'),
 ...                      ('station_name','S10')])
 >>> station_data_t = nc.createCompoundType(dtype,'station_data')
@@ -1556,7 +1555,7 @@ 
      In-memory (diskless) Datasets
      
 object representing the Dataset. Below are examples illustrating both
 approaches.
      
 
-
      >>> # create a diskless (in-memory) Dataset,
+
      >>> # create a diskless (in-memory) Dataset,
 >>> # and persist the file to disk when it is closed.
 >>> nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
 >>> d = nc.createDimension('x',None)
@@ -1618,7 +1617,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -1631,7 +1630,7 @@ 
      In-memory (diskless) Datasets
      
 
                         
      
             View Source
-            
      # init for netCDF4. package
+            
      # init for netCDF4. package
 # Docstring comes from extension module _netCDF4.
 from ._netCDF4 import *
 # Need explicit imports for names beginning with underscores
@@ -1663,7 +1662,7 @@ 
      In-memory (diskless) Datasets
      
         Dataset:
     
      
 
-    
+        
             
      A netCDF Dataset is a collection of dimensions, groups, variables and
 attributes. Together they describe the meaning of data and relations among
 data fields stored in a netCDF file. See Dataset.__init__ for more
@@ -1741,7 +1740,7 @@ 
      In-memory (diskless) Datasets
      
             Dataset()
     
      
 
-    
+        
             
      __init__(self, filename, mode="r", clobber=True, diskless=False,
 persist=False, keepweakref=False, memory=None, encoding=None,
 parallel=False, comm=None, info=None, format='NETCDF4')
      
@@ -1847,7 +1846,7 @@ 
      In-memory (diskless) Datasets
      
             filepath(unknown):
     
      
 
-    
+        
             
      filepath(self,encoding=None)
      
 
 
      Get the file system path (or the opendap URL) which was used to
@@ -1866,7 +1865,7 @@ 
      In-memory (diskless) Datasets
      
             close(unknown):
     
      
 
-    
+        
             
      close(self)
      
 
 
      Close the Dataset.
      
@@ -1882,7 +1881,7 @@ 
      In-memory (diskless) Datasets
      
             isopen(unknown):
     
      
 
-    
+        
             
      isopen(self)
      
 
 
      Is the Dataset open or closed?
      
@@ -1898,7 +1897,7 @@ 
      In-memory (diskless) Datasets
      
             sync(unknown):
     
      
 
-    
+        
             
      sync(self)
      
 
 
      Writes all buffered data in the Dataset to the disk file.
      
@@ -1914,7 +1913,7 @@ 
      In-memory (diskless) Datasets
      
             set_fill_on(unknown):
     
      
 
-    
+        
             
      set_fill_on(self)
      
 
 
      Sets the fill mode for a Dataset open for writing to on.
      
@@ -1938,7 +1937,7 @@ 
      In-memory (diskless) Datasets
      
             set_fill_off(unknown):
     
      
 
-    
+        
             
      set_fill_off(self)
      
 
 
      Sets the fill mode for a Dataset open for writing to off.
      
@@ -1958,7 +1957,7 @@ 
      In-memory (diskless) Datasets
      
             createDimension(unknown):
     
      
 
-    
+        
             
      createDimension(self, dimname, size=None)
      
 
 
      Creates a new dimension with the given dimname and size.
      
@@ -1982,7 +1981,7 @@ 
      In-memory (diskless) Datasets
      
             renameDimension(unknown):
     
      
 
-    
+        
             
      renameDimension(self, oldname, newname)
      
 
 
      rename a Dimension named oldname to newname.
      
@@ -1998,7 +1997,7 @@ 
      In-memory (diskless) Datasets
      
             createCompoundType(unknown):
     
      
 
-    
+        
             
      createCompoundType(self, datatype, datatype_name)
      
 
 
      Creates a new compound data type named datatype_name from the numpy
@@ -2023,7 +2022,7 @@ 
      In-memory (diskless) Datasets
      
             createVLType(unknown):
     
      
 
-    
+        
             
      createVLType(self, datatype, datatype_name)
      
 
 
      Creates a new VLEN data type named datatype_name from a numpy
@@ -2043,7 +2042,7 @@ 
      In-memory (diskless) Datasets
      
             createEnumType(unknown):
     
      
 
-    
+        
             
      createEnumType(self, datatype, datatype_name, enum_dict)
      
 
 
      Creates a new Enum data type named datatype_name from a numpy
@@ -2064,10 +2063,10 @@ 
      In-memory (diskless) Datasets
      
             createVariable(unknown):
     
      
 
-    
+        
             
      createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False,
 complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None,
-szip_coding='nn', szip_pixels_per_block=8, blosc_shuffle=1, blosc_blocksize=0,
+szip_coding='nn', szip_pixels_per_block=8, blosc_shuffle=1,
 endian='native', least_significant_digit=None, significant_digits=None, quantize_mode='BitGroom',
 fill_value=None, chunk_cache=None)
      
 
@@ -2121,11 +2120,9 @@ 
      In-memory (diskless) Datasets
      
 significantly improves compression. Default is True. Ignored if
 zlib=False.
      
 
-
      The optional kwargs blosc_shuffle and blosc_blocksize are ignored
+
      The optional kwarg blosc_shuffleis  ignored
 unless the blosc compressor is used. blosc_shuffle can be 0 (no shuffle),
-1 (byte-wise shuffle) or 2 (bit-wise shuffle). Default is 1. blosc_blocksize
-is the tunable blosc blocksize in bytes (Default 0 means the blocksize is
-chosen internally).
      
+1 (byte-wise shuffle) or 2 (bit-wise shuffle). Default is 1.
      
 
 
      The optional kwargs szip_coding and szip_pixels_per_block are ignored
 unless the szip compressor is used. szip_coding can be ec (entropy coding)
@@ -2161,7 +2158,7 @@ 
      In-memory (diskless) Datasets
      
 
 
      The optional keyword fill_value can be used to override the default
 netCDF _FillValue (the value that the variable gets filled with before
-any data is written to it, defaults given in the dict netCDF4.default_fillvals).
+any data is written to it, defaults given in the dict netCDF4.default_fillvals).
 If fill_value is set to False, then the variable is not pre-filled.
      
 
 
      If the optional keyword parameters least_significant_digit or significant_digits are
@@ -2229,7 +2226,7 @@ 
      In-memory (diskless) Datasets
      
             renameVariable(unknown):
     
      
 
-    
+        
             
      renameVariable(self, oldname, newname)
      
 
 
      rename a Variable named oldname to newname
      
@@ -2245,7 +2242,7 @@ 
      In-memory (diskless) Datasets
      
             createGroup(unknown):
     
      
 
-    
+        
             
      createGroup(self, groupname)
      
 
 
      Creates a new Group with the given groupname.
      
@@ -2271,7 +2268,7 @@ 
      In-memory (diskless) Datasets
      
             ncattrs(unknown):
     
      
 
-    
+        
             
      ncattrs(self)
      
 
 
      return netCDF global attribute names for this Dataset or Group in a list.
      
@@ -2287,7 +2284,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr(unknown):
     
      
 
-    
+        
             
      setncattr(self,name,value)
      
 
 
      set a netCDF dataset or group attribute using name,value pair.
@@ -2305,7 +2302,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr_string(unknown):
     
      
 
-    
+        
             
      setncattr_string(self,name,value)
      
 
 
      set a netCDF dataset or group string attribute using name,value pair.
@@ -2323,7 +2320,7 @@ 
      In-memory (diskless) Datasets
      
             setncatts(unknown):
     
      
 
-    
+        
             
      setncatts(self,attdict)
      
 
 
      set a bunch of netCDF dataset or group attributes at once using a python dictionary.
@@ -2342,7 +2339,7 @@ 
      In-memory (diskless) Datasets
      
             getncattr(unknown):
     
      
 
-    
+        
             
      getncattr(self,name)
      
 
 
      retrieve a netCDF dataset or group attribute.
@@ -2363,7 +2360,7 @@ 
      In-memory (diskless) Datasets
      
             delncattr(unknown):
     
      
 
-    
+        
             
      delncattr(self,name,value)
      
 
 
      delete a netCDF dataset or group attribute.  Use if you need to delete a
@@ -2381,7 +2378,7 @@ 
      In-memory (diskless) Datasets
      
             renameAttribute(unknown):
     
      
 
-    
+        
             
      renameAttribute(self, oldname, newname)
      
 
 
      rename a Dataset or Group attribute named oldname to newname.
      
@@ -2397,7 +2394,7 @@ 
      In-memory (diskless) Datasets
      
             renameGroup(unknown):
     
      
 
-    
+        
             
      renameGroup(self, oldname, newname)
      
 
 
      rename a Group named oldname to newname (requires netcdf >= 4.3.1).
      
@@ -2413,7 +2410,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_chartostring(unknown):
     
      
 
-    
+        
             
      set_auto_chartostring(self, True_or_False)
      
 
 
      Call Variable.set_auto_chartostring for all variables contained in this Dataset or
@@ -2438,7 +2435,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_maskandscale(unknown):
     
      
 
-    
+        
             
      set_auto_maskandscale(self, True_or_False)
      
 
 
      Call Variable.set_auto_maskandscale for all variables contained in this Dataset or
@@ -2461,7 +2458,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_mask(unknown):
     
      
 
-    
+        
             
      set_auto_mask(self, True_or_False)
      
 
 
      Call Variable.set_auto_mask for all variables contained in this Dataset or
@@ -2485,7 +2482,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_scale(unknown):
     
      
 
-    
+        
             
      set_auto_scale(self, True_or_False)
      
 
 
      Call Variable.set_auto_scale for all variables contained in this Dataset or
@@ -2508,7 +2505,7 @@ 
      In-memory (diskless) Datasets
      
             set_always_mask(unknown):
     
      
 
-    
+        
             
      set_always_mask(self, True_or_False)
      
 
 
      Call Variable.set_always_mask for all variables contained in
@@ -2536,7 +2533,7 @@ 
      In-memory (diskless) Datasets
      
             set_ncstring_attrs(unknown):
     
      
 
-    
+        
             
      set_ncstring_attrs(self, True_or_False)
      
 
 
      Call Variable.set_ncstring_attrs for all variables contained in
@@ -2561,7 +2558,7 @@ 
      In-memory (diskless) Datasets
      
             get_variables_by_attributes(unknown):
     
      
 
-    
+        
             
      get_variables_by_attribute(self, **kwargs)
      
 
 
      Returns a list of variables that match specific conditions.
      
@@ -2569,7 +2566,7 @@ 
      In-memory (diskless) Datasets
      
 
      Can pass in key=value parameters and variables are returned that
 contain all of the matches. For example,
      
 
-
      >>> # Get variables with x-axis attribute.
+
      >>> # Get variables with x-axis attribute.
 >>> vs = nc.get_variables_by_attributes(axis='X')
 >>> # Get variables with matching "standard_name" attribute
 >>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
@@ -2580,7 +2577,7 @@ 
      In-memory (diskless) Datasets
      
 the attribute value.  None is given as the attribute value when the
 attribute does not exist on the variable. For example,
      
 
-
      >>> # Get Axis variables
+
      >>> # Get Axis variables
 >>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
 >>> # Get variables that don't have an "axis" attribute
 >>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
@@ -2599,7 +2596,7 @@ 
      In-memory (diskless) Datasets
      
             fromcdl(unknown):
     
      
 
-    
+        
             
      fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')
      
 
 
      call ncgen via subprocess to create Dataset from CDL
@@ -2629,7 +2626,7 @@ 
      In-memory (diskless) Datasets
      
             tocdl(unknown):
     
      
 
-    
+        
             
      tocdl(self, coordvars=False, data=False, outfile=None)
      
 
 
      call ncdump via subprocess to create CDL
@@ -2648,10 +2645,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        name
+        name = <attribute 'name' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
-    
             
      string name of Group instance
      
 
      
 
@@ -2660,121 +2656,109 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        groups
+        groups = <attribute 'groups' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        dimensions
+        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        variables
+        variables = <attribute 'variables' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        disk_format
+        disk_format = <attribute 'disk_format' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        path
+        path = <attribute 'path' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        parent
+        parent = <attribute 'parent' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        file_format
+        file_format = <attribute 'file_format' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        data_model
+        data_model = <attribute 'data_model' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        cmptypes
+        cmptypes = <attribute 'cmptypes' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        vltypes
+        vltypes = <attribute 'vltypes' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        enumtypes
+        enumtypes = <attribute 'enumtypes' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        keepweakref
+        keepweakref = <attribute 'keepweakref' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                 
      
@@ -2787,7 +2771,7 @@ 
      In-memory (diskless) Datasets
      
         Variable:
     
      
 
-    
+        
             
      A netCDF Variable is used to read and write netCDF data.  They are
 analogous to numpy array objects. See Variable.__init__ for more
 details.
      
@@ -2871,10 +2855,10 @@ 
      In-memory (diskless) Datasets
      
             Variable()
     
      
 
-    
+        
             
      __init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False,
 complevel=4, shuffle=True, szip_coding='nn', szip_pixels_per_block=8,
-blosc_shuffle=1, blosc_blocksize=0, fletcher32=False, contiguous=False,
+blosc_shuffle=1, fletcher32=False, contiguous=False,
 chunksizes=None, endian='native',
 least_significant_digit=None,fill_value=None,chunk_cache=None)
      
 
@@ -2929,10 +2913,6 @@ 
      In-memory (diskless) Datasets
      
 Can be 0 (no blosc shuffle), 1 (bytewise shuffle) or 2 (bitwise
 shuffle)). Default is 1. Ignored if blosc compressor not used.
      
 
-
      blosc_blocksize: tunable blocksize in bytes for blosc
-compressors. Default of 0 means blosc library chooses a blocksize.
-Ignored if blosc compressor not used.
      
-
 
      szip_coding: szip coding method. Can be ec (entropy coding)
 or nn (nearest neighbor coding). Default is nn.
 Ignored if szip compressor not used.
      
@@ -2996,7 +2976,7 @@ 
      In-memory (diskless) Datasets
      
 value that the variable gets filled with before any data is written to it)
 is replaced with this value.  If fill_value is set to False, then
 the variable is not pre-filled. The default netCDF fill values can be found
-in the dictionary netCDF4.default_fillvals.
      
+in the dictionary netCDF4.default_fillvals.
      
 
 
      chunk_cache: If specified, sets the chunk cache size for this variable.
 Persists as long as Dataset is open. Use set_var_chunk_cache to
@@ -3017,7 +2997,7 @@ 
      In-memory (diskless) Datasets
      
             group(unknown):
     
      
 
-    
+        
             
      group(self)
      
 
 
      return the group that this Variable is a member of.
      
@@ -3033,7 +3013,7 @@ 
      In-memory (diskless) Datasets
      
             ncattrs(unknown):
     
      
 
-    
+        
             
      ncattrs(self)
      
 
 
      return netCDF attribute names for this Variable in a list.
      
@@ -3049,7 +3029,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr(unknown):
     
      
 
-    
+        
             
      setncattr(self,name,value)
      
 
 
      set a netCDF variable attribute using name,value pair.  Use if you need to set a
@@ -3067,7 +3047,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr_string(unknown):
     
      
 
-    
+        
             
      setncattr_string(self,name,value)
      
 
 
      set a netCDF variable string attribute using name,value pair.
@@ -3086,7 +3066,7 @@ 
      In-memory (diskless) Datasets
      
             setncatts(unknown):
     
      
 
-    
+        
             
      setncatts(self,attdict)
      
 
 
      set a bunch of netCDF variable attributes at once using a python dictionary.
@@ -3105,7 +3085,7 @@ 
      In-memory (diskless) Datasets
      
             getncattr(unknown):
     
      
 
-    
+        
             
      getncattr(self,name)
      
 
 
      retrieve a netCDF variable attribute.  Use if you need to set a
@@ -3126,7 +3106,7 @@ 
      In-memory (diskless) Datasets
      
             delncattr(unknown):
     
      
 
-    
+        
             
      delncattr(self,name,value)
      
 
 
      delete a netCDF variable attribute.  Use if you need to delete a
@@ -3144,7 +3124,7 @@ 
      In-memory (diskless) Datasets
      
             filters(unknown):
     
      
 
-    
+        
             
      filters(self)
      
 
 
      return dictionary containing HDF5 filter parameters.
      
@@ -3160,7 +3140,7 @@ 
      In-memory (diskless) Datasets
      
             quantization(unknown):
     
      
 
-    
+        
             
      quantization(self)
      
 
 
      return number of significant digits and the algorithm used in quantization.
@@ -3177,7 +3157,7 @@ 
      In-memory (diskless) Datasets
      
             endian(unknown):
     
      
 
-    
+        
             
      endian(self)
      
 
 
      return endian-ness (little,big,native) of variable (as stored in HDF5 file).
      
@@ -3193,7 +3173,7 @@ 
      In-memory (diskless) Datasets
      
             chunking(unknown):
     
      
 
-    
+        
             
      chunking(self)
      
 
 
      return variable chunking information.  If the dataset is
@@ -3212,7 +3192,7 @@ 
      In-memory (diskless) Datasets
      
             get_var_chunk_cache(unknown):
     
      
 
-    
+        
             
      get_var_chunk_cache(self)
      
 
 
      return variable chunk cache information in a tuple (size,nelems,preemption).
@@ -3230,7 +3210,7 @@ 
      In-memory (diskless) Datasets
      
             set_var_chunk_cache(unknown):
     
      
 
-    
+        
             
      set_var_chunk_cache(self,size=None,nelems=None,preemption=None)
      
 
 
      change variable chunk cache settings.
@@ -3248,7 +3228,7 @@ 
      In-memory (diskless) Datasets
      
             renameAttribute(unknown):
     
      
 
-    
+        
             
      renameAttribute(self, oldname, newname)
      
 
 
      rename a Variable attribute named oldname to newname.
      
@@ -3264,7 +3244,7 @@ 
      In-memory (diskless) Datasets
      
             assignValue(unknown):
     
      
 
-    
+        
             
      assignValue(self, val)
      
 
 
      assign a value to a scalar variable.  Provided for compatibility with
@@ -3281,7 +3261,7 @@ 
      In-memory (diskless) Datasets
      
             getValue(unknown):
     
      
 
-    
+        
             
      getValue(self)
      
 
 
      get the value of a scalar variable.  Provided for compatibility with
@@ -3298,7 +3278,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_chartostring(unknown):
     
      
 
-    
+        
             
      set_auto_chartostring(self,chartostring)
      
 
 
      turn on or off automatic conversion of character variable data to and
@@ -3329,7 +3309,7 @@ 
      In-memory (diskless) Datasets
      
             use_nc_get_vars(unknown):
     
      
 
-    
+        
             
      use_nc_get_vars(self,_use_get_vars)
      
 
 
      enable the use of netcdf library routine nc_get_vars
@@ -3349,7 +3329,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_maskandscale(unknown):
     
      
 
-    
+        
             
      set_auto_maskandscale(self,maskandscale)
      
 
 
      turn on or off automatic conversion of variable data to and
@@ -3413,7 +3393,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_scale(unknown):
     
      
 
-    
+        
             
      set_auto_scale(self,scale)
      
 
 
      turn on or off automatic packing/unpacking of variable
@@ -3462,7 +3442,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_mask(unknown):
     
      
 
-    
+        
             
      set_auto_mask(self,mask)
      
 
 
      turn on or off automatic conversion of variable data to and
@@ -3497,7 +3477,7 @@ 
      In-memory (diskless) Datasets
      
             set_always_mask(unknown):
     
      
 
-    
+        
             
      set_always_mask(self,always_mask)
      
 
 
      turn on or off conversion of data without missing values to regular
@@ -3520,7 +3500,7 @@ 
      In-memory (diskless) Datasets
      
             set_ncstring_attrs(unknown):
     
      
 
-    
+        
             
      set_always_mask(self,ncstring_attrs)
      
 
 
      turn on or off creating NC_STRING string attributes.
      
@@ -3542,7 +3522,7 @@ 
      In-memory (diskless) Datasets
      
             set_collective(unknown):
     
      
 
-    
+        
             
      set_collective(self,True_or_False)
      
 
 
      turn on or off collective parallel IO access. Ignored if file is not
@@ -3559,7 +3539,7 @@ 
      In-memory (diskless) Datasets
      
             get_dims(unknown):
     
      
 
-    
+        
             
      get_dims(self)
      
 
 
      return a tuple of Dimension instances associated with this
@@ -3571,10 +3551,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        name
+        name = <attribute 'name' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
-    
             
      string name of Variable instance
      
 
      
 
@@ -3583,10 +3562,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        datatype
+        datatype = <attribute 'datatype' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
-    
             
      numpy data type (for primitive data types) or
 VLType/CompoundType/EnumType instance 
 (for compound, vlen  or enum data types)
      
@@ -3597,10 +3575,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        shape
+        shape = <attribute 'shape' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
-    
             
      find current sizes of all variable dimensions
      
 
      
 
@@ -3609,10 +3586,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        size
+        size = <attribute 'size' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
-    
             
      Return the number of stored elements.
      
 
      
 
@@ -3621,10 +3597,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        dimensions
+        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
-    
             
      get variables's dimension names
      
 
      
 
@@ -3633,61 +3608,55 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        ndim
+        ndim = <attribute 'ndim' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        dtype
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        mask
+        mask = <attribute 'mask' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        scale
+        scale = <attribute 'scale' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        always_mask
+        always_mask = <attribute 'always_mask' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        chartostring
+        chartostring = <attribute 'chartostring' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
     
-    
 
                             
      
                 
@@ -3700,7 +3669,7 @@ 
      In-memory (diskless) Datasets
      
         Dimension:
     
      
 
-    
+        
             
      A netCDF Dimension is used to describe the coordinates of a Variable.
 See Dimension.__init__ for more details.
      
 
@@ -3726,7 +3695,7 @@ 
      In-memory (diskless) Datasets
      
             Dimension()
     
      
 
-    
+        
             
      __init__(self, group, name, size=None)
      
 
 
      Dimension constructor.
      
@@ -3752,7 +3721,7 @@ 
      In-memory (diskless) Datasets
      
             group(unknown):
     
      
 
-    
+        
             
      group(self)
      
 
 
      return the group that this Dimension is a member of.
      
@@ -3768,7 +3737,7 @@ 
      In-memory (diskless) Datasets
      
             isunlimited(unknown):
     
      
 
-    
+        
             
      isunlimited(self)
      
 
 
      returns True if the Dimension instance is unlimited, False otherwise.
      
@@ -3779,10 +3748,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        name
+        name = <attribute 'name' of 'netCDF4._netCDF4.Dimension' objects>
     
      
 
-    
             
      string name of Dimension instance
      
 
      
 
@@ -3791,10 +3759,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        size
+        size = <attribute 'size' of 'netCDF4._netCDF4.Dimension' objects>
     
      
 
-    
             
      current size of Dimension (calls len on Dimension instance)
      
 
      
 
@@ -3810,7 +3777,7 @@ 
      In-memory (diskless) Datasets
      
         Group(netCDF4.Dataset):
     
      
 
-    
+        
             
      Groups define a hierarchical namespace within a netCDF file. They are
 analogous to directories in a unix filesystem. Each Group behaves like
 a Dataset within a Dataset, and can contain it's own variables,
@@ -3834,7 +3801,7 @@ 
      In-memory (diskless) Datasets
      
             Group()
     
      
 
-    
+        
             
      __init__(self, parent, name)
 Group constructor.
      
 
@@ -3858,7 +3825,7 @@ 
      In-memory (diskless) Datasets
      
             close(unknown):
     
      
 
-    
+        
             
      close(self)
      
 
 
      overrides Dataset close method which does not apply to Group
@@ -3928,7 +3895,7 @@ 
      Inherited Members
      
         MFDataset(netCDF4.Dataset):
     
      
 
-    
+        
             
      Class for reading multi-file netCDF Datasets, making variables
 spanning multiple files appear as if they were in one file.
 Datasets must be in NETCDF4_CLASSIC, NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET
@@ -3938,7 +3905,7 @@ 
      Inherited Members
      
 
 
      Example usage (See MFDataset.__init__ for more details):
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> # create a series of netCDF files with a variable sharing
 >>> # the same unlimited dimension.
 >>> for nf in range(10):
@@ -3965,7 +3932,7 @@ 
      Inherited Members
      
             MFDataset(files, check=False, aggdim=None, exclude=[], master_file=None)
     
      
 
-    
+        
             
      __init__(self, files, check=False, aggdim=None, exclude=[],
 master_file=None)
      
 
@@ -4010,7 +3977,7 @@ 
      Inherited Members
      
             ncattrs(self):
     
      
 
-    
+        
             
      ncattrs(self)
      
 
 
      return the netcdf attribute names from the master file.
      
@@ -4026,7 +3993,7 @@ 
      Inherited Members
      
             close(self):
     
      
 
-    
+        
             
      close(self)
      
 
 
      close all the open files.
      
@@ -4094,13 +4061,13 @@ 
      Inherited Members
      
         MFTime(netCDF4._netCDF4._Variable):
     
      
 
-    
+        
             
      Class providing an interface to a MFDataset time Variable by imposing a unique common
 time unit and/or calendar to all files.
      
 
 
      Example usage (See MFTime.__init__ for more details):
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> f1 = Dataset("mftest_1.nc","w", format="NETCDF4_CLASSIC")
 >>> f2 = Dataset("mftest_2.nc","w", format="NETCDF4_CLASSIC")
 >>> f1.createDimension("time",None)
@@ -4136,7 +4103,7 @@ 
      Inherited Members
      
             MFTime(time, units=None, calendar=None)
     
      
 
-    
+        
             
      __init__(self, time, units=None, calendar=None)
      
 
 
      Create a time Variable with units consistent across a multifile
@@ -4180,7 +4147,7 @@ 
      Inherited Members
      
         CompoundType:
     
      
 
-    
+        
             
      A CompoundType instance is used to describe a compound data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance.
@@ -4199,7 +4166,7 @@ 
      Inherited Members
      
             CompoundType()
     
      
 
-    
+        
             
      __init__(group, datatype, datatype_name)
      
 
 
      CompoundType constructor.
      
@@ -4228,31 +4195,28 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.CompoundType' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        dtype_view
+        dtype_view = <attribute 'dtype_view' of 'netCDF4._netCDF4.CompoundType' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        name
+        name = <attribute 'name' of 'netCDF4._netCDF4.CompoundType' objects>
     
      
 
     
-    
 
                             
      
                 
@@ -4265,7 +4229,7 @@ 
      Inherited Members
      
         VLType:
     
      
 
-    
+        
             
      A VLType instance is used to describe a variable length (VLEN) data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance. See
@@ -4283,7 +4247,7 @@ 
      Inherited Members
      
             VLType()
     
      
 
-    
+        
             
      __init__(group, datatype, datatype_name)
      
 
 
      VLType constructor.
      
@@ -4306,21 +4270,19 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.VLType' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        name
+        name = <attribute 'name' of 'netCDF4._netCDF4.VLType' objects>
     
      
 
     
-    
 
                             
      
                 
@@ -4332,7 +4294,7 @@ 
      Inherited Members
      
             date2num(unknown):
     
      
 
-    
+        
             
      date2num(dates, units, calendar=None, has_year_zero=None)
      
 
 
      Return numeric time values given datetime objects. The units
@@ -4392,7 +4354,7 @@ 
      Inherited Members
      
             num2date(unknown):
     
      
 
-    
+        
             
      num2date(times, units, calendar=u'standard', only_use_cftime_datetimes=True, only_use_python_datetimes=False, has_year_zero=None)
      
 
 
      Return datetime objects given numeric time values. The units
@@ -4464,7 +4426,7 @@ 
      Inherited Members
      
             date2index(unknown):
     
      
 
-    
+        
             
      date2index(dates, nctime, calendar=None, select=u'exact', has_year_zero=None)
      
 
 
      Return indices of a netCDF time variable corresponding to the given dates.
      
@@ -4518,7 +4480,7 @@ 
      Inherited Members
      
             stringtochar(unknown):
     
      
 
-    
+        
             
      stringtochar(a,encoding='utf-8')
      
 
 
      convert a string array to a character array with one extra dimension
      
@@ -4545,7 +4507,7 @@ 
      Inherited Members
      
             chartostring(unknown):
     
      
 
-    
+        
             
      chartostring(b,encoding='utf-8')
      
 
 
      convert a character array to a string array with one less dimension.
      
@@ -4572,7 +4534,7 @@ 
      Inherited Members
      
             stringtoarr(unknown):
     
      
 
-    
+        
             
      stringtoarr(a, NUMCHARS,dtype='S')
      
 
 
      convert a string to a character array of length NUMCHARS
      
@@ -4600,7 +4562,7 @@ 
      Inherited Members
      
             getlibversion(unknown):
     
      
 
-    
+        
             
      getlibversion()
      
 
 
      returns a string describing the version of the netcdf library
@@ -4618,7 +4580,7 @@ 
      Inherited Members
      
         EnumType:
     
      
 
-    
+        
             
      A EnumType instance is used to describe an Enum data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance. See
@@ -4636,7 +4598,7 @@ 
      Inherited Members
      
             EnumType()
     
      
 
-    
+        
             
      __init__(group, datatype, datatype_name, enum_dict)
      
 
 
      EnumType constructor.
      
@@ -4662,31 +4624,28 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.EnumType' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        name
+        name = <attribute 'name' of 'netCDF4._netCDF4.EnumType' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        enum_dict
+        enum_dict = <attribute 'enum_dict' of 'netCDF4._netCDF4.EnumType' objects>
     
      
 
     
-    
 
                             
      
                 
@@ -4698,7 +4657,7 @@ 
      Inherited Members
      
             get_chunk_cache(unknown):
     
      
 
-    
+        
             
      get_chunk_cache()
      
 
 
      return current netCDF chunk cache information in a tuple (size,nelems,preemption).
@@ -4716,7 +4675,7 @@ 
      Inherited Members
      
             set_chunk_cache(unknown):
     
      
 
-    
+        
             
      set_chunk_cache(self,size=None,nelems=None,preemption=None)
      
 
 
      change netCDF4 chunk cache settings.
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 278f21224..b9897aa34 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2654,13 +2654,13 @@ datatype."""
             compression=None, zlib=False,
             complevel=4, shuffle=True,
             szip_coding='nn',szip_pixels_per_block=8,
-            blosc_shuffle=1, blosc_blocksize=0, fletcher32=False, contiguous=False,
+            blosc_shuffle=1,fletcher32=False, contiguous=False,
             chunksizes=None, endian='native', least_significant_digit=None,
             significant_digits=None,quantize_mode='BitGroom',fill_value=None, chunk_cache=None):
         """
 **`createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False,
 complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None,
-szip_coding='nn', szip_pixels_per_block=8, blosc_shuffle=1, blosc_blocksize=0,
+szip_coding='nn', szip_pixels_per_block=8, blosc_shuffle=1,
 endian='native', least_significant_digit=None, significant_digits=None, quantize_mode='BitGroom',
 fill_value=None, chunk_cache=None)`**
 
@@ -2714,11 +2714,9 @@ will be applied before compressing the data with zlib (default `True`).  This
 significantly improves compression. Default is `True`. Ignored if
 `zlib=False`.
 
-The optional kwargs `blosc_shuffle` and `blosc_blocksize` are ignored
+The optional kwarg `blosc_shuffle`is  ignored
 unless the blosc compressor is used. `blosc_shuffle` can be 0 (no shuffle),
-1 (byte-wise shuffle) or 2 (bit-wise shuffle). Default is 1. `blosc_blocksize`
-is the tunable blosc blocksize in bytes (Default 0 means the blocksize is
-chosen internally).
+1 (byte-wise shuffle) or 2 (bit-wise shuffle). Default is 1.
 
 The optional kwargs `szip_coding` and `szip_pixels_per_block` are ignored
 unless the szip compressor is used. `szip_coding` can be `ec` (entropy coding)
@@ -2834,7 +2832,7 @@ is the number of variable dimensions."""
         group.variables[varname] = Variable(group, varname, datatype,
         dimensions=dimensions, compression=compression, zlib=zlib, complevel=complevel, shuffle=shuffle,
         szip_coding=szip_coding, szip_pixels_per_block=szip_pixels_per_block,
-        blosc_shuffle=blosc_shuffle,blosc_blocksize=blosc_blocksize,
+        blosc_shuffle=blosc_shuffle,
         fletcher32=fletcher32, contiguous=contiguous, chunksizes=chunksizes,
         endian=endian, least_significant_digit=least_significant_digit,
         significant_digits=significant_digits,quantize_mode=quantize_mode,fill_value=fill_value, chunk_cache=chunk_cache)
@@ -3676,14 +3674,14 @@ behavior is similar to Fortran or Matlab, but different than numpy.
     def __init__(self, grp, name, datatype, dimensions=(),
             compression=None, zlib=False,
             complevel=4, shuffle=True, szip_coding='nn', szip_pixels_per_block=8,
-            blosc_shuffle=1, blosc_blocksize=0,
+            blosc_shuffle=1, 
             fletcher32=False, contiguous=False,
             chunksizes=None, endian='native', least_significant_digit=None,
             significant_digits=None,quantize_mode='BitGroom',fill_value=None, chunk_cache=None, **kwargs):
         """
         **`__init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False,
         complevel=4, shuffle=True, szip_coding='nn', szip_pixels_per_block=8,
-        blosc_shuffle=1, blosc_blocksize=0, fletcher32=False, contiguous=False,
+        blosc_shuffle=1, fletcher32=False, contiguous=False,
         chunksizes=None, endian='native',
         least_significant_digit=None,fill_value=None,chunk_cache=None)`**
 
@@ -3738,10 +3736,6 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         Can be 0 (no blosc shuffle), 1 (bytewise shuffle) or 2 (bitwise
         shuffle)). Default is 1. Ignored if blosc compressor not used.
 
-        **`blosc_blocksize`**: tunable blocksize in bytes for blosc
-        compressors. Default of 0 means blosc library chooses a blocksize.
-        Ignored if blosc compressor not used.
-
         **`szip_coding`**: szip coding method. Can be `ec` (entropy coding)
         or `nn` (nearest neighbor coding). Default is `nn`.
         Ignored if szip compressor not used.
@@ -4045,7 +4039,7 @@ version 4.9.0 or higher netcdf-c with bzip2 support, and rebuild netcdf4-python.
                         IF HAS_BLOSC_SUPPORT:
                             iblosc_compressor = _blosc_dict[compression]
                             iblosc_shuffle = blosc_shuffle
-                            iblosc_blocksize = blosc_blocksize
+                            iblosc_blocksize = 0 # not currently used by c lib
                             iblosc_complevel = complevel
                             ierr = nc_def_var_blosc(self._grpid, self._varid,\
                                     iblosc_compressor,\
@@ -4492,7 +4486,7 @@ return dictionary containing HDF5 filter parameters."""
             filtdict['complevel']=icomplevel_bzip2
         if iblosc:
             blosc_compressor = iblosc_compressor
-            filtdict['blosc']={'compressor':_blosc_dict_inv[blosc_compressor],'shuffle':iblosc_shuffle,'blocksize':iblosc_blocksize}
+            filtdict['blosc']={'compressor':_blosc_dict_inv[blosc_compressor],'shuffle':iblosc_shuffle}
             filtdict['complevel']=iblosc_complevel
         if iszip:
             szip_coding = iszip_coding
diff --git a/test/tst_compression_blosc.py b/test/tst_compression_blosc.py
index 891f53b90..da31d3ce1 100644
--- a/test/tst_compression_blosc.py
+++ b/test/tst_compression_blosc.py
@@ -5,26 +5,25 @@
 
 ndim = 100000
 iblosc_shuffle=2
-iblosc_blocksize=800000
 iblosc_complevel=4
 filename = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
 datarr = uniform(size=(ndim,))
 
-def write_netcdf(filename,dtype='f8',blosc_shuffle=1,blosc_blocksize=500000,complevel=6):
+def write_netcdf(filename,dtype='f8',blosc_shuffle=1,complevel=6):
     nc = Dataset(filename,'w')
     nc.createDimension('n', ndim)
     foo = nc.createVariable('data',\
             dtype,('n'),compression=None)
     foo_lz = nc.createVariable('data_lz',\
-            dtype,('n'),compression='blosc_lz',blosc_shuffle=blosc_shuffle,blosc_blocksize=blosc_blocksize,complevel=complevel)
+            dtype,('n'),compression='blosc_lz',blosc_shuffle=blosc_shuffle,complevel=complevel)
     foo_lz4 = nc.createVariable('data_lz4',\
-            dtype,('n'),compression='blosc_lz4',blosc_shuffle=blosc_shuffle,blosc_blocksize=blosc_blocksize,complevel=complevel)
+            dtype,('n'),compression='blosc_lz4',blosc_shuffle=blosc_shuffle,complevel=complevel)
     foo_lz4hc = nc.createVariable('data_lz4hc',\
-            dtype,('n'),compression='blosc_lz4hc',blosc_shuffle=blosc_shuffle,blosc_blocksize=blosc_blocksize,complevel=complevel)
+            dtype,('n'),compression='blosc_lz4hc',blosc_shuffle=blosc_shuffle,complevel=complevel)
     foo_zlib = nc.createVariable('data_zlib',\
-            dtype,('n'),compression='blosc_zlib',blosc_shuffle=blosc_shuffle,blosc_blocksize=blosc_blocksize,complevel=complevel)
+            dtype,('n'),compression='blosc_zlib',blosc_shuffle=blosc_shuffle,complevel=complevel)
     foo_zstd = nc.createVariable('data_zstd',\
-            dtype,('n'),compression='blosc_zstd',blosc_shuffle=blosc_shuffle,blosc_blocksize=blosc_blocksize,complevel=complevel)
+            dtype,('n'),compression='blosc_zstd',blosc_shuffle=blosc_shuffle,complevel=complevel)
     foo_lz[:] = datarr
     foo_lz4[:] = datarr
     foo_lz4hc[:] = datarr
@@ -36,7 +35,7 @@ class CompressionTestCase(unittest.TestCase):
 
     def setUp(self):
         self.filename = filename
-        write_netcdf(self.filename,complevel=iblosc_complevel,blosc_shuffle=iblosc_shuffle,blosc_blocksize=iblosc_blocksize) # with compression
+        write_netcdf(self.filename,complevel=iblosc_complevel,blosc_shuffle=iblosc_shuffle)
 
     def tearDown(self):
         # Remove the temporary files
@@ -49,27 +48,27 @@ def runTest(self):
         {'zlib':False,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
         assert_almost_equal(datarr,f.variables['data_lz'][:])
         dtest = {'zlib': False, 'szip':False, 'zstd': False, 'bzip2': False, 'blosc':
-                {'compressor': 'blosc_lz', 'shuffle': iblosc_shuffle, 'blocksize': iblosc_blocksize},
+                {'compressor': 'blosc_lz', 'shuffle': iblosc_shuffle},
                 'shuffle': False, 'complevel': iblosc_complevel, 'fletcher32': False}
         assert f.variables['data_lz'].filters() == dtest
         assert_almost_equal(datarr,f.variables['data_lz4'][:])
         dtest = {'zlib': False, 'szip':False, 'zstd': False, 'bzip2': False, 'blosc':
-                {'compressor': 'blosc_lz4', 'shuffle': iblosc_shuffle, 'blocksize': iblosc_blocksize},
+                {'compressor': 'blosc_lz4', 'shuffle': iblosc_shuffle},
                 'shuffle': False, 'complevel': iblosc_complevel, 'fletcher32': False}
         assert f.variables['data_lz4'].filters() == dtest
         assert_almost_equal(datarr,f.variables['data_lz4hc'][:])
         dtest = {'zlib': False, 'szip':False, 'zstd': False, 'bzip2': False, 'blosc':
-                {'compressor': 'blosc_lz4hc', 'shuffle': iblosc_shuffle, 'blocksize': iblosc_blocksize},
+                {'compressor': 'blosc_lz4hc', 'shuffle': iblosc_shuffle},
                 'shuffle': False, 'complevel': iblosc_complevel, 'fletcher32': False}
         assert f.variables['data_lz4hc'].filters() == dtest
         assert_almost_equal(datarr,f.variables['data_zlib'][:])
         dtest = {'zlib': False, 'szip':False, 'zstd': False, 'bzip2': False, 'blosc':
-                {'compressor': 'blosc_zlib', 'shuffle': iblosc_shuffle, 'blocksize': iblosc_blocksize},
+                {'compressor': 'blosc_zlib', 'shuffle': iblosc_shuffle},
                 'shuffle': False, 'complevel': iblosc_complevel, 'fletcher32': False}
         assert f.variables['data_zlib'].filters() == dtest
         assert_almost_equal(datarr,f.variables['data_zstd'][:])
         dtest = {'zlib': False, 'szip':False, 'zstd': False, 'bzip2': False, 'blosc':
-                {'compressor': 'blosc_zstd', 'shuffle': iblosc_shuffle, 'blocksize': iblosc_blocksize},
+                {'compressor': 'blosc_zstd', 'shuffle': iblosc_shuffle},
                 'shuffle': False, 'complevel': iblosc_complevel, 'fletcher32': False}
         assert f.variables['data_zstd'].filters() == dtest
         f.close()

From 9d2faeb84570ffa1713d8dba1dde310b9b370b35 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 15 May 2022 08:44:16 -0600
Subject: [PATCH 0825/1504] update

---
 Changelog | 10 +++++++---
 README.md |  4 ++--
 2 files changed, 9 insertions(+), 5 deletions(-)

diff --git a/Changelog b/Changelog
index eebb7f378..435a6bdc6 100644
--- a/Changelog
+++ b/Changelog
@@ -14,11 +14,15 @@
  * add 'compression' kwarg to createVariable to enable new compression
    functionality in netcdf-c 4.9.0.  'None','zlib','szip','zstd','bzip2'
    'blosc_lz','blosc_lz4','blosc_lz4hc','blosc_zlib' and 'blosc_zstd'
-   are currently supported. 'blosc_shuffle', 'blosc_blocksize',
+   are currently supported. 'blosc_shuffle',
    'szip_mask' and 'szip_pixels_per_block' kwargs also added.
    compression='zlib' is equivalent to (the now deprecated) zlib=True.
-   Using new compressors (except 'szip') requires setting HDF5_PLUGIN_PATH to point to 
-   the installation location of the netcdf-c filter plugins.
+   If the environment variable NETCDF_PLUGIN_DIR is set to point to the
+   directory with the HDF5 plugin .so files, then the compression plugins will
+   be installed within the package and be automatically available (the binary
+   wheels have this).  Otherwise, the environment variable HDF5_PLUGIN_PATH
+   needs to be se to point to plugins in order to use the new compression
+   options.
  * MFDataset did not aggregate 'name' variable attribute (issue #1153).
  * issue warning instead of raising an exception if missing_value or
    _FillValue can't be cast to the variable type when creating a 
diff --git a/README.md b/README.md
index 7615d10d1..453648b80 100644
--- a/README.md
+++ b/README.md
@@ -13,8 +13,8 @@ For details on the latest updates, see the [Changelog](https://github.com/Unidat
 ??/??/2022:  Version [1.6.0](https://pypi.python.org/pypi/netCDF4/1.6.0) released.  Support
 for quantization (bit-grooming and bit-rounding) functionality in netcdf-c 4.9.0 which can
 dramatically improve compression.  Dataset.createVariable now accepts dimension instances (instead
-of just dimension names). 'compression' kwarg added to Dataset.createVariable to support szip as well as
-new compression algorithms available in netcdf-c 4.9.0 through HDF5 filter plugsins (such
+of just dimension names). 'compression' kwarg added to Dataset.createVariable to support szip as
+well as new compression algorithms available in netcdf-c 4.9.0 through HDF5 filter plugsins (such
 as zstd, bzip2 and blosc). Working arm64 wheels for Apple M1 Silicon now available on pypi.
 
 10/31/2021:  Version [1.5.8](https://pypi.python.org/pypi/netCDF4/1.5.8) released. Fix Enum bug, add binary wheels for aarch64 and python 3.10.

From fa5791c0c9c51441e8fafd8cdb07793243d59ab6 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 16 May 2022 11:08:23 -0600
Subject: [PATCH 0826/1504] update

---
 src/netCDF4/__init__.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py
index f53195897..b6f9d2293 100644
--- a/src/netCDF4/__init__.py
+++ b/src/netCDF4/__init__.py
@@ -13,6 +13,6 @@
 import os
 __all__ =\
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
-# if HDF5_PLUGIN_PATH not set, point to plugins directory inside package
-if 'HDF5_PLUGIN_PATH' not in os.environ:
+# if HDF5_PLUGIN_PATH not set, point to package path if libh5noop.so exists there
+if 'HDF5_PLUGIN_PATH' not in os.environ and os.path.exists(os.path.join(__path__[0],'libh5noop.so')):
     os.environ['HDF5_PLUGIN_PATH']=__path__[0]

From 09078033a6b22f621e9f714c3a94474685a64a61 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 16 May 2022 11:19:15 -0600
Subject: [PATCH 0827/1504] update docs

---
 docs/index.html          | 443 +++++++++++++++++++++------------------
 src/netCDF4/_netCDF4.pyx |   6 +
 2 files changed, 248 insertions(+), 201 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index c923bcdb4..9b62f5b05 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -3,24 +3,24 @@
 
     
     
-    
+    
     netCDF4 API documentation
-    
 
-
-
-
-
-
-        
      
     
      
             
      
                     
      
@@ -520,6 +521,12 @@ 
      Developer Install
      
 If the dependencies are not found
 in any of the paths specified by environment variables, then standard locations
 (such as /usr and /usr/local) are searched.
      • 
+
    • if the env var NETCDF_PLUGIN_DIR is set to point to the location netcdf-c compression
+plugin shared objects, they will be installed inside the package.  In this
+case HDF5_PLUGIN_PATH will be set to the package installation path on import,
+so the extra compression algorithms available in netcdf-c 4.9.0 will automatically
+be available.  Otherwise, the user will have to set HDF5_PLUGIN_PATH explicitly
+to have access to the extra compression plugins.
      • 
 
    • run python setup.py build, then python setup.py install (as root if
 necessary).
      • 
 
    • run the tests in the 'test' directory by running python run_all.py.
      • 
@@ -576,7 +583,7 @@ 
      Creating/Opening/Closing a netCDF
 
 
      Here's an example:
      
 
-
      >>> from netCDF4 import Dataset
+
      >>> from netCDF4 import Dataset
 >>> rootgrp = Dataset("test.nc", "w", format="NETCDF4")
 >>> print(rootgrp.data_model)
 NETCDF4
@@ -605,7 +612,7 @@ 
      Groups in a netCDF file
      
 NETCDF4 formatted files support Groups, if you try to create a Group
 in a netCDF 3 file you will get an error message.
      
 
-
      >>> rootgrp = Dataset("test.nc", "a")
+
      >>> rootgrp = Dataset("test.nc", "a")
 >>> fcstgrp = rootgrp.createGroup("forecasts")
 >>> analgrp = rootgrp.createGroup("analyses")
 >>> print(rootgrp.groups)
@@ -629,7 +636,7 @@ 
      Groups in a netCDF file
      
 that group.  To simplify the creation of nested groups, you can
 use a unix-like path as an argument to Dataset.createGroup.
      
 
-
      >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
+
      >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
 >>> fcstgrp2 = rootgrp.createGroup("/forecasts/model2")
 
      
 
@@ -643,7 +650,7 @@ 
      Groups in a netCDF file
      
 to walk the directory tree. Note that printing the Dataset or Group
 object yields summary information about it's contents.
      
 
-
      >>> def walktree(top):
+
      >>> def walktree(top):
 ...     yield top.groups.values()
 ...     for value in top.groups.values():
 ...         yield from walktree(value)
@@ -693,7 +700,7 @@ 
      Dimensions in a netCDF file
      
 dimension is a new netCDF 4 feature, in netCDF 3 files there may be only
 one, and it must be the first (leftmost) dimension of the variable.
      
 
-
      >>> level = rootgrp.createDimension("level", None)
+
      >>> level = rootgrp.createDimension("level", None)
 >>> time = rootgrp.createDimension("time", None)
 >>> lat = rootgrp.createDimension("lat", 73)
 >>> lon = rootgrp.createDimension("lon", 144)
@@ -701,7 +708,7 @@ 
      Dimensions in a netCDF file
      
 
 
      All of the Dimension instances are stored in a python dictionary.
      
 
-
      >>> print(rootgrp.dimensions)
+
      >>> print(rootgrp.dimensions)
 {'level': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0, 'time': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0, 'lat': <class 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 73, 'lon': <class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144}
 
      
 
@@ -710,7 +717,7 @@ 
      Dimensions in a netCDF file
      
 Dimension.isunlimited method of a Dimension instance
 be used to determine if the dimensions is unlimited, or appendable.
      
 
-
      >>> print(len(lon))
+
      >>> print(len(lon))
 144
 >>> print(lon.isunlimited())
 False
@@ -722,7 +729,7 @@ 
      Dimensions in a netCDF file
      
 provides useful summary info, including the name and length of the dimension,
 and whether it is unlimited.
      
 
-
      >>> for dimobj in rootgrp.dimensions.values():
+
      >>> for dimobj in rootgrp.dimensions.values():
 ...     print(dimobj)
 <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0
 <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0
@@ -767,7 +774,7 @@ 
      Variables in a netCDF file
      
 method returns an instance of the Variable class whose methods can be
 used later to access and set variable data and attributes.
      
 
-
      >>> times = rootgrp.createVariable("time","f8",("time",))
+
      >>> times = rootgrp.createVariable("time","f8",("time",))
 >>> levels = rootgrp.createVariable("level","i4",("level",))
 >>> latitudes = rootgrp.createVariable("lat","f4",("lat",))
 >>> longitudes = rootgrp.createVariable("lon","f4",("lon",))
@@ -779,7 +786,7 @@ 
      Variables in a netCDF file
      
 
      To get summary info on a Variable instance in an interactive session,
 just print it.
      
 
-
      >>> print(temp)
+
      >>> print(temp)
 <class 'netCDF4._netCDF4.Variable'>
 float32 temp(time, level, lat, lon)
     units: K
@@ -790,7 +797,7 @@ 
      Variables in a netCDF file
      
 
 
      You can use a path to create a Variable inside a hierarchy of groups.
      
 
-
      >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
+
      >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
 
      
 
 
      If the intermediate groups do not yet exist, they will be created.
      
@@ -798,7 +805,7 @@ 
      Variables in a netCDF file
      
 
      You can also query a Dataset or Group instance directly to obtain Group or
 Variable instances using paths.
      
 
-
      >>> print(rootgrp["/forecasts/model1"])  # a Group instance
+
      >>> print(rootgrp["/forecasts/model1"])  # a Group instance
 <class 'netCDF4._netCDF4.Group'>
 group /forecasts/model1:
     dimensions(sizes): 
@@ -816,7 +823,7 @@ 
      Variables in a netCDF file
      
 
      All of the variables in the Dataset or Group are stored in a
 Python dictionary, in the same way as the dimensions:
      
 
-
      >>> print(rootgrp.variables)
+
      >>> print(rootgrp.variables)
 {'time': <class 'netCDF4._netCDF4.Variable'>
 float64 time(time)
 unlimited dimensions: time
@@ -859,7 +866,7 @@ 
      Attributes in a netCDF file
      
 variables. Attributes can be strings, numbers or sequences. Returning to
 our example,
      
 
-
      >>> import time
+
      >>> import time
 >>> rootgrp.description = "bogus example script"
 >>> rootgrp.history = "Created " + time.ctime(time.time())
 >>> rootgrp.source = "netCDF4 python module tutorial"
@@ -877,7 +884,7 @@ 
      Attributes in a netCDF file
      
 built-in dir Python function will return a bunch of private methods
 and attributes that cannot (or should not) be modified by the user.
      
 
-
      >>> for name in rootgrp.ncattrs():
+
      >>> for name in rootgrp.ncattrs():
 ...     print("Global attr {} = {}".format(name, getattr(rootgrp, name)))
 Global attr description = bogus example script
 Global attr history = Created Mon Jul  8 14:19:41 2019
@@ -888,7 +895,7 @@ 
      Attributes in a netCDF file
      
 instance provides all the netCDF attribute name/value pairs in a python
 dictionary:
      
 
-
      >>> print(rootgrp.__dict__)
+
      >>> print(rootgrp.__dict__)
 {'description': 'bogus example script', 'history': 'Created Mon Jul  8 14:19:41 2019', 'source': 'netCDF4 python module tutorial'}
 
      
 
@@ -901,7 +908,7 @@ 
      Writing data
 
      Now that you have a netCDF Variable instance, how do you put data
 into it? You can just treat it like an array and assign data to a slice.
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> lats =  np.arange(-90,91,2.5)
 >>> lons =  np.arange(-180,180,2.5)
 >>> latitudes[:] = lats
@@ -921,7 +928,7 @@ 
      Writing data
 objects with unlimited dimensions will grow along those dimensions if you
 assign data outside the currently defined range of indices.
      
 
-
      >>> # append along two unlimited dimensions by assigning to slice.
+
      >>> # append along two unlimited dimensions by assigning to slice.
 >>> nlats = len(rootgrp.dimensions["lat"])
 >>> nlons = len(rootgrp.dimensions["lon"])
 >>> print("temp shape before adding data = {}".format(temp.shape))
@@ -941,7 +948,7 @@ 
      Writing data
 along the level dimension of the variable temp, even though no
 data has yet been assigned to levels.
      
 
-
      >>> # now, assign data to levels dimension variable.
+
      >>> # now, assign data to levels dimension variable.
 >>> levels[:] =  [1000.,850.,700.,500.,300.,250.,200.,150.,100.,50.]
 
      
 
@@ -954,7 +961,7 @@ 
      Writing data
 allowed, and these indices work independently along each dimension (similar
 to the way vector subscripts work in fortran).  This means that
      
 
-
      >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
+
      >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
 (4, 4)
 
      
 
@@ -972,14 +979,14 @@ 
      Writing data
 
 
      For example,
      
 
-
      >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
+
      >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
 
      
 
 
      will extract time indices 0,2 and 4, pressure levels
 850, 500 and 200 hPa, all Northern Hemisphere latitudes and Eastern
 Hemisphere longitudes, resulting in a numpy array of shape  (3, 3, 36, 71).
      
 
-
      >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
+
      >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
 shape of fancy temp slice = (3, 3, 36, 71)
 
      
 
@@ -1012,7 +1019,7 @@ 
      Dealing with time coordinates
      
 provided by cftime to do just that.
 Here's an example of how they can be used:
      
 
-
      >>> # fill in times.
+
      >>> # fill in times.
 >>> from datetime import datetime, timedelta
 >>> from cftime import num2date, date2num
 >>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
@@ -1052,7 +1059,7 @@ 
      Reading data from a multi
 NETCDF4_CLASSIC format (NETCDF4 formatted multi-file
 datasets are not supported).
      
 
-
      >>> for nf in range(10):
+
      >>> for nf in range(10):
 ...     with Dataset("mftest%s.nc" % nf, "w", format="NETCDF4_CLASSIC") as f:
 ...         _ = f.createDimension("x",None)
 ...         x = f.createVariable("x","i",("x",))
@@ -1061,7 +1068,7 @@ 
      Reading data from a multi
 
 
      Now read all the files back in at once with MFDataset
      
 
-
      >>> from netCDF4 import MFDataset
+
      >>> from netCDF4 import MFDataset
 >>> f = MFDataset("mftest*nc")
 >>> print(f.variables["x"][:])
 [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
@@ -1128,22 +1135,22 @@ 
      Efficient compression of netC
 
 
      In our example, try replacing the line
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
 
      
 
 
      with
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib')
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib')
 
      
 
 
      and then
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',least_significant_digit=3)
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',least_significant_digit=3)
 
      
 
 
      or with netcdf-c >= 4.9.0
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',significant_digits=4)
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',significant_digits=4)
 
      
 
 
      and see how much smaller the resulting files are.
      
@@ -1164,7 +1171,7 @@ 
      Beyond ho
 Since there is no native complex data type in netcdf, compound types are handy
 for storing numpy complex arrays.  Here's an example:
      
 
-
      >>> f = Dataset("complex.nc","w")
+
      >>> f = Dataset("complex.nc","w")
 >>> size = 3 # length of 1-d complex array
 >>> # create sample complex data.
 >>> datac = np.exp(1j*(1.+np.linspace(0, np.pi, size)))
@@ -1200,7 +1207,7 @@ 
      Beyond ho
 in a Python dictionary, just like variables and dimensions. As always, printing
 objects gives useful summary information in an interactive session:
      
 
-
      >>> print(f)
+
      >>> print(f)
 <class 'netCDF4._netCDF4.Dataset'>
 root group (NETCDF4 data model, file format HDF5):
     dimensions(sizes): x_dim(3)
@@ -1225,7 +1232,7 @@ 
      Variable-length (vlen) data types
      
 data type, use the Dataset.createVLType method
 method of a Dataset or Group instance.
      
 
-
      >>> f = Dataset("tst_vlen.nc","w")
+
      >>> f = Dataset("tst_vlen.nc","w")
 >>> vlen_t = f.createVLType(np.int32, "phony_vlen")
 
      
 
@@ -1235,7 +1242,7 @@ 
      Variable-length (vlen) data types
      
 but compound data types cannot.
 A new variable can then be created using this datatype.
      
 
-
      >>> x = f.createDimension("x",3)
+
      >>> x = f.createDimension("x",3)
 >>> y = f.createDimension("y",4)
 >>> vlvar = f.createVariable("phony_vlen_var", vlen_t, ("y","x"))
 
      
@@ -1248,7 +1255,7 @@ 
      Variable-length (vlen) data types
      
 In this case, they contain 1-D numpy int32 arrays of random length between
 1 and 10.
      
 
-
      >>> import random
+
      >>> import random
 >>> random.seed(54321)
 >>> data = np.empty(len(y)*len(x),object)
 >>> for n in range(len(y)*len(x)):
@@ -1288,7 +1295,7 @@ 
      Variable-length (vlen) data types
      
 with fixed length greater than 1) when calling the
 Dataset.createVariable method.
      
 
-
      >>> z = f.createDimension("z",10)
+
      >>> z = f.createDimension("z",10)
 >>> strvar = f.createVariable("strvar", str, "z")
 
      
 
@@ -1296,7 +1303,7 @@ 
      Variable-length (vlen) data types
      
 random lengths between 2 and 12 characters, and the data in the object
 array is assigned to the vlen string variable.
      
 
-
      >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
+
      >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
 >>> data = np.empty(10,"O")
 >>> for n in range(10):
 ...     stringlen = random.randint(2,12)
@@ -1335,7 +1342,7 @@ 
      Enum data type
      
 values and their names are used to define an Enum data type using
 Dataset.createEnumType.
      
 
-
      >>> nc = Dataset('clouds.nc','w')
+
      >>> nc = Dataset('clouds.nc','w')
 >>> # python dict with allowed values and their names.
 >>> enum_dict = {'Altocumulus': 7, 'Missing': 255,
 ... 'Stratus': 2, 'Clear': 0,
@@ -1353,7 +1360,7 @@ 
      Enum data type
      
 is made to write an integer value not associated with one of the
 specified names.
      
 
-
      >>> time = nc.createDimension('time',None)
+
      >>> time = nc.createDimension('time',None)
 >>> # create a 1d variable of type 'cloud_type'.
 >>> # The fill_value is set to the 'Missing' named value.
 >>> cloud_var = nc.createVariable('primary_cloud',cloud_type,'time',
@@ -1390,7 +1397,7 @@ 
      Parallel IO
      
 available. To use parallel IO, your program must be running in an MPI
 environment using mpi4py.
      
 
-
      >>> from mpi4py import MPI
+
      >>> from mpi4py import MPI
 >>> import numpy as np
 >>> from netCDF4 import Dataset
 >>> rank = MPI.COMM_WORLD.rank  # The process ID (integer 0-3 for 4-process run)
@@ -1402,7 +1409,7 @@ 
      Parallel IO
      
 when a new dataset is created or an existing dataset is opened,
 use the parallel keyword to enable parallel access.
      
 
-
      >>> nc = Dataset('parallel_test.nc','w',parallel=True)
+
      >>> nc = Dataset('parallel_test.nc','w',parallel=True)
 
      
 
 
      The optional comm keyword may be used to specify a particular
@@ -1410,7 +1417,7 @@ 
      Parallel IO
      
 can now write to the file indepedently.  In this example the process rank is
 written to a different variable index on each task
      
 
-
      >>> d = nc.createDimension('dim',4)
+
      >>> d = nc.createDimension('dim',4)
 >>> v = nc.createVariable('var', np.int64, 'dim')
 >>> v[rank] = rank
 >>> nc.close()
@@ -1477,7 +1484,7 @@ 
      Dealing with strings
      
 stringtochar is used to convert the numpy string array to an array of
 characters with one more dimension. For example,
      
 
-
      >>> from netCDF4 import stringtochar
+
      >>> from netCDF4 import stringtochar
 >>> nc = Dataset('stringtest.nc','w',format='NETCDF4_CLASSIC')
 >>> _ = nc.createDimension('nchars',3)
 >>> _ = nc.createDimension('nstrings',None)
@@ -1510,7 +1517,7 @@ 
      Dealing with strings
      
 character array dtype under the hood when creating the netcdf compound type.
 Here's an example:
      
 
-
      >>> nc = Dataset('compoundstring_example.nc','w')
+
      >>> nc = Dataset('compoundstring_example.nc','w')
 >>> dtype = np.dtype([('observation', 'f4'),
 ...                      ('station_name','S10')])
 >>> station_data_t = nc.createCompoundType(dtype,'station_data')
@@ -1555,7 +1562,7 @@ 
      In-memory (diskless) Datasets
      
 object representing the Dataset. Below are examples illustrating both
 approaches.
      
 
-
      >>> # create a diskless (in-memory) Dataset,
+
      >>> # create a diskless (in-memory) Dataset,
 >>> # and persist the file to disk when it is closed.
 >>> nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
 >>> d = nc.createDimension('x',None)
@@ -1617,7 +1624,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -1630,7 +1637,7 @@ 
      In-memory (diskless) Datasets
      
 
                         
      
             View Source
-            
      # init for netCDF4. package
+            
      # init for netCDF4. package
 # Docstring comes from extension module _netCDF4.
 from ._netCDF4 import *
 # Need explicit imports for names beginning with underscores
@@ -1645,8 +1652,8 @@ 
      In-memory (diskless) Datasets
      
 import os
 __all__ =\
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
-# if HDF5_PLUGIN_PATH not set, point to plugins directory inside package
-if 'HDF5_PLUGIN_PATH' not in os.environ:
+# if HDF5_PLUGIN_PATH not set, point to package path if libh5noop.so exists there
+if 'HDF5_PLUGIN_PATH' not in os.environ and os.path.exists(os.path.join(__path__[0],'libh5noop.so')):
     os.environ['HDF5_PLUGIN_PATH']=__path__[0]
 
      
 
@@ -1662,7 +1669,7 @@ 
      In-memory (diskless) Datasets
      
         Dataset:
     
      
 
-        
+    
             
      A netCDF Dataset is a collection of dimensions, groups, variables and
 attributes. Together they describe the meaning of data and relations among
 data fields stored in a netCDF file. See Dataset.__init__ for more
@@ -1740,7 +1747,7 @@ 
      In-memory (diskless) Datasets
      
             Dataset()
     
      
 
-        
+    
             
      __init__(self, filename, mode="r", clobber=True, diskless=False,
 persist=False, keepweakref=False, memory=None, encoding=None,
 parallel=False, comm=None, info=None, format='NETCDF4')
      
@@ -1846,7 +1853,7 @@ 
      In-memory (diskless) Datasets
      
             filepath(unknown):
     
      
 
-        
+    
             
      filepath(self,encoding=None)
      
 
 
      Get the file system path (or the opendap URL) which was used to
@@ -1865,7 +1872,7 @@ 
      In-memory (diskless) Datasets
      
             close(unknown):
     
      
 
-        
+    
             
      close(self)
      
 
 
      Close the Dataset.
      
@@ -1881,7 +1888,7 @@ 
      In-memory (diskless) Datasets
      
             isopen(unknown):
     
      
 
-        
+    
             
      isopen(self)
      
 
 
      Is the Dataset open or closed?
      
@@ -1897,7 +1904,7 @@ 
      In-memory (diskless) Datasets
      
             sync(unknown):
     
      
 
-        
+    
             
      sync(self)
      
 
 
      Writes all buffered data in the Dataset to the disk file.
      
@@ -1913,7 +1920,7 @@ 
      In-memory (diskless) Datasets
      
             set_fill_on(unknown):
     
      
 
-        
+    
             
      set_fill_on(self)
      
 
 
      Sets the fill mode for a Dataset open for writing to on.
      
@@ -1937,7 +1944,7 @@ 
      In-memory (diskless) Datasets
      
             set_fill_off(unknown):
     
      
 
-        
+    
             
      set_fill_off(self)
      
 
 
      Sets the fill mode for a Dataset open for writing to off.
      
@@ -1957,7 +1964,7 @@ 
      In-memory (diskless) Datasets
      
             createDimension(unknown):
     
      
 
-        
+    
             
      createDimension(self, dimname, size=None)
      
 
 
      Creates a new dimension with the given dimname and size.
      
@@ -1981,7 +1988,7 @@ 
      In-memory (diskless) Datasets
      
             renameDimension(unknown):
     
      
 
-        
+    
             
      renameDimension(self, oldname, newname)
      
 
 
      rename a Dimension named oldname to newname.
      
@@ -1997,7 +2004,7 @@ 
      In-memory (diskless) Datasets
      
             createCompoundType(unknown):
     
      
 
-        
+    
             
      createCompoundType(self, datatype, datatype_name)
      
 
 
      Creates a new compound data type named datatype_name from the numpy
@@ -2022,7 +2029,7 @@ 
      In-memory (diskless) Datasets
      
             createVLType(unknown):
     
      
 
-        
+    
             
      createVLType(self, datatype, datatype_name)
      
 
 
      Creates a new VLEN data type named datatype_name from a numpy
@@ -2042,7 +2049,7 @@ 
      In-memory (diskless) Datasets
      
             createEnumType(unknown):
     
      
 
-        
+    
             
      createEnumType(self, datatype, datatype_name, enum_dict)
      
 
 
      Creates a new Enum data type named datatype_name from a numpy
@@ -2063,7 +2070,7 @@ 
      In-memory (diskless) Datasets
      
             createVariable(unknown):
     
      
 
-        
+    
             
      createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False,
 complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None,
 szip_coding='nn', szip_pixels_per_block=8, blosc_shuffle=1,
@@ -2158,7 +2165,7 @@ 
      In-memory (diskless) Datasets
      
 
 
      The optional keyword fill_value can be used to override the default
 netCDF _FillValue (the value that the variable gets filled with before
-any data is written to it, defaults given in the dict netCDF4.default_fillvals).
+any data is written to it, defaults given in the dict netCDF4.default_fillvals).
 If fill_value is set to False, then the variable is not pre-filled.
      
 
 
      If the optional keyword parameters least_significant_digit or significant_digits are
@@ -2226,7 +2233,7 @@ 
      In-memory (diskless) Datasets
      
             renameVariable(unknown):
     
      
 
-        
+    
             
      renameVariable(self, oldname, newname)
      
 
 
      rename a Variable named oldname to newname
      
@@ -2242,7 +2249,7 @@ 
      In-memory (diskless) Datasets
      
             createGroup(unknown):
     
      
 
-        
+    
             
      createGroup(self, groupname)
      
 
 
      Creates a new Group with the given groupname.
      
@@ -2268,7 +2275,7 @@ 
      In-memory (diskless) Datasets
      
             ncattrs(unknown):
     
      
 
-        
+    
             
      ncattrs(self)
      
 
 
      return netCDF global attribute names for this Dataset or Group in a list.
      
@@ -2284,7 +2291,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr(unknown):
     
      
 
-        
+    
             
      setncattr(self,name,value)
      
 
 
      set a netCDF dataset or group attribute using name,value pair.
@@ -2302,7 +2309,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr_string(unknown):
     
      
 
-        
+    
             
      setncattr_string(self,name,value)
      
 
 
      set a netCDF dataset or group string attribute using name,value pair.
@@ -2320,7 +2327,7 @@ 
      In-memory (diskless) Datasets
      
             setncatts(unknown):
     
      
 
-        
+    
             
      setncatts(self,attdict)
      
 
 
      set a bunch of netCDF dataset or group attributes at once using a python dictionary.
@@ -2339,7 +2346,7 @@ 
      In-memory (diskless) Datasets
      
             getncattr(unknown):
     
      
 
-        
+    
             
      getncattr(self,name)
      
 
 
      retrieve a netCDF dataset or group attribute.
@@ -2360,7 +2367,7 @@ 
      In-memory (diskless) Datasets
      
             delncattr(unknown):
     
      
 
-        
+    
             
      delncattr(self,name,value)
      
 
 
      delete a netCDF dataset or group attribute.  Use if you need to delete a
@@ -2378,7 +2385,7 @@ 
      In-memory (diskless) Datasets
      
             renameAttribute(unknown):
     
      
 
-        
+    
             
      renameAttribute(self, oldname, newname)
      
 
 
      rename a Dataset or Group attribute named oldname to newname.
      
@@ -2394,7 +2401,7 @@ 
      In-memory (diskless) Datasets
      
             renameGroup(unknown):
     
      
 
-        
+    
             
      renameGroup(self, oldname, newname)
      
 
 
      rename a Group named oldname to newname (requires netcdf >= 4.3.1).
      
@@ -2410,7 +2417,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_chartostring(unknown):
     
      
 
-        
+    
             
      set_auto_chartostring(self, True_or_False)
      
 
 
      Call Variable.set_auto_chartostring for all variables contained in this Dataset or
@@ -2435,7 +2442,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_maskandscale(unknown):
     
      
 
-        
+    
             
      set_auto_maskandscale(self, True_or_False)
      
 
 
      Call Variable.set_auto_maskandscale for all variables contained in this Dataset or
@@ -2458,7 +2465,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_mask(unknown):
     
      
 
-        
+    
             
      set_auto_mask(self, True_or_False)
      
 
 
      Call Variable.set_auto_mask for all variables contained in this Dataset or
@@ -2482,7 +2489,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_scale(unknown):
     
      
 
-        
+    
             
      set_auto_scale(self, True_or_False)
      
 
 
      Call Variable.set_auto_scale for all variables contained in this Dataset or
@@ -2505,7 +2512,7 @@ 
      In-memory (diskless) Datasets
      
             set_always_mask(unknown):
     
      
 
-        
+    
             
      set_always_mask(self, True_or_False)
      
 
 
      Call Variable.set_always_mask for all variables contained in
@@ -2533,7 +2540,7 @@ 
      In-memory (diskless) Datasets
      
             set_ncstring_attrs(unknown):
     
      
 
-        
+    
             
      set_ncstring_attrs(self, True_or_False)
      
 
 
      Call Variable.set_ncstring_attrs for all variables contained in
@@ -2558,7 +2565,7 @@ 
      In-memory (diskless) Datasets
      
             get_variables_by_attributes(unknown):
     
      
 
-        
+    
             
      get_variables_by_attribute(self, **kwargs)
      
 
 
      Returns a list of variables that match specific conditions.
      
@@ -2566,7 +2573,7 @@ 
      In-memory (diskless) Datasets
      
 
      Can pass in key=value parameters and variables are returned that
 contain all of the matches. For example,
      
 
-
      >>> # Get variables with x-axis attribute.
+
      >>> # Get variables with x-axis attribute.
 >>> vs = nc.get_variables_by_attributes(axis='X')
 >>> # Get variables with matching "standard_name" attribute
 >>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
@@ -2577,7 +2584,7 @@ 
      In-memory (diskless) Datasets
      
 the attribute value.  None is given as the attribute value when the
 attribute does not exist on the variable. For example,
      
 
-
      >>> # Get Axis variables
+
      >>> # Get Axis variables
 >>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
 >>> # Get variables that don't have an "axis" attribute
 >>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
@@ -2596,7 +2603,7 @@ 
      In-memory (diskless) Datasets
      
             fromcdl(unknown):
     
      
 
-        
+    
             
      fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')
      
 
 
      call ncgen via subprocess to create Dataset from CDL
@@ -2626,7 +2633,7 @@ 
      In-memory (diskless) Datasets
      
             tocdl(unknown):
     
      
 
-        
+    
             
      tocdl(self, coordvars=False, data=False, outfile=None)
      
 
 
      call ncdump via subprocess to create CDL
@@ -2645,9 +2652,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.Dataset' objects>
+        name
     
      
 
+    
             
      string name of Group instance
      
 
      
 
@@ -2656,109 +2664,121 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        groups = <attribute 'groups' of 'netCDF4._netCDF4.Dataset' objects>
+        groups
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Dataset' objects>
+        dimensions
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        variables = <attribute 'variables' of 'netCDF4._netCDF4.Dataset' objects>
+        variables
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        disk_format = <attribute 'disk_format' of 'netCDF4._netCDF4.Dataset' objects>
+        disk_format
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        path = <attribute 'path' of 'netCDF4._netCDF4.Dataset' objects>
+        path
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        parent = <attribute 'parent' of 'netCDF4._netCDF4.Dataset' objects>
+        parent
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        file_format = <attribute 'file_format' of 'netCDF4._netCDF4.Dataset' objects>
+        file_format
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        data_model = <attribute 'data_model' of 'netCDF4._netCDF4.Dataset' objects>
+        data_model
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        cmptypes = <attribute 'cmptypes' of 'netCDF4._netCDF4.Dataset' objects>
+        cmptypes
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        vltypes = <attribute 'vltypes' of 'netCDF4._netCDF4.Dataset' objects>
+        vltypes
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        enumtypes = <attribute 'enumtypes' of 'netCDF4._netCDF4.Dataset' objects>
+        enumtypes
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        keepweakref = <attribute 'keepweakref' of 'netCDF4._netCDF4.Dataset' objects>
+        keepweakref
     
      
 
     
+    
 
                             
      
                 
@@ -2771,7 +2791,7 @@ 
      In-memory (diskless) Datasets
      
         Variable:
     
      
 
-        
+    
             
      A netCDF Variable is used to read and write netCDF data.  They are
 analogous to numpy array objects. See Variable.__init__ for more
 details.
      
@@ -2855,7 +2875,7 @@ 
      In-memory (diskless) Datasets
      
             Variable()
     
      
 
-        
+    
             
      __init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False,
 complevel=4, shuffle=True, szip_coding='nn', szip_pixels_per_block=8,
 blosc_shuffle=1, fletcher32=False, contiguous=False,
@@ -2976,7 +2996,7 @@ 
      In-memory (diskless) Datasets
      
 value that the variable gets filled with before any data is written to it)
 is replaced with this value.  If fill_value is set to False, then
 the variable is not pre-filled. The default netCDF fill values can be found
-in the dictionary netCDF4.default_fillvals.
      
+in the dictionary netCDF4.default_fillvals.
      
 
 
      chunk_cache: If specified, sets the chunk cache size for this variable.
 Persists as long as Dataset is open. Use set_var_chunk_cache to
@@ -2997,7 +3017,7 @@ 
      In-memory (diskless) Datasets
      
             group(unknown):
     
      
 
-        
+    
             
      group(self)
      
 
 
      return the group that this Variable is a member of.
      
@@ -3013,7 +3033,7 @@ 
      In-memory (diskless) Datasets
      
             ncattrs(unknown):
     
      
 
-        
+    
             
      ncattrs(self)
      
 
 
      return netCDF attribute names for this Variable in a list.
      
@@ -3029,7 +3049,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr(unknown):
     
      
 
-        
+    
             
      setncattr(self,name,value)
      
 
 
      set a netCDF variable attribute using name,value pair.  Use if you need to set a
@@ -3047,7 +3067,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr_string(unknown):
     
      
 
-        
+    
             
      setncattr_string(self,name,value)
      
 
 
      set a netCDF variable string attribute using name,value pair.
@@ -3066,7 +3086,7 @@ 
      In-memory (diskless) Datasets
      
             setncatts(unknown):
     
      
 
-        
+    
             
      setncatts(self,attdict)
      
 
 
      set a bunch of netCDF variable attributes at once using a python dictionary.
@@ -3085,7 +3105,7 @@ 
      In-memory (diskless) Datasets
      
             getncattr(unknown):
     
      
 
-        
+    
             
      getncattr(self,name)
      
 
 
      retrieve a netCDF variable attribute.  Use if you need to set a
@@ -3106,7 +3126,7 @@ 
      In-memory (diskless) Datasets
      
             delncattr(unknown):
     
      
 
-        
+    
             
      delncattr(self,name,value)
      
 
 
      delete a netCDF variable attribute.  Use if you need to delete a
@@ -3124,7 +3144,7 @@ 
      In-memory (diskless) Datasets
      
             filters(unknown):
     
      
 
-        
+    
             
      filters(self)
      
 
 
      return dictionary containing HDF5 filter parameters.
      
@@ -3140,7 +3160,7 @@ 
      In-memory (diskless) Datasets
      
             quantization(unknown):
     
      
 
-        
+    
             
      quantization(self)
      
 
 
      return number of significant digits and the algorithm used in quantization.
@@ -3157,7 +3177,7 @@ 
      In-memory (diskless) Datasets
      
             endian(unknown):
     
      
 
-        
+    
             
      endian(self)
      
 
 
      return endian-ness (little,big,native) of variable (as stored in HDF5 file).
      
@@ -3173,7 +3193,7 @@ 
      In-memory (diskless) Datasets
      
             chunking(unknown):
     
      
 
-        
+    
             
      chunking(self)
      
 
 
      return variable chunking information.  If the dataset is
@@ -3192,7 +3212,7 @@ 
      In-memory (diskless) Datasets
      
             get_var_chunk_cache(unknown):
     
      
 
-        
+    
             
      get_var_chunk_cache(self)
      
 
 
      return variable chunk cache information in a tuple (size,nelems,preemption).
@@ -3210,7 +3230,7 @@ 
      In-memory (diskless) Datasets
      
             set_var_chunk_cache(unknown):
     
      
 
-        
+    
             
      set_var_chunk_cache(self,size=None,nelems=None,preemption=None)
      
 
 
      change variable chunk cache settings.
@@ -3228,7 +3248,7 @@ 
      In-memory (diskless) Datasets
      
             renameAttribute(unknown):
     
      
 
-        
+    
             
      renameAttribute(self, oldname, newname)
      
 
 
      rename a Variable attribute named oldname to newname.
      
@@ -3244,7 +3264,7 @@ 
      In-memory (diskless) Datasets
      
             assignValue(unknown):
     
      
 
-        
+    
             
      assignValue(self, val)
      
 
 
      assign a value to a scalar variable.  Provided for compatibility with
@@ -3261,7 +3281,7 @@ 
      In-memory (diskless) Datasets
      
             getValue(unknown):
     
      
 
-        
+    
             
      getValue(self)
      
 
 
      get the value of a scalar variable.  Provided for compatibility with
@@ -3278,7 +3298,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_chartostring(unknown):
     
      
 
-        
+    
             
      set_auto_chartostring(self,chartostring)
      
 
 
      turn on or off automatic conversion of character variable data to and
@@ -3309,7 +3329,7 @@ 
      In-memory (diskless) Datasets
      
             use_nc_get_vars(unknown):
     
      
 
-        
+    
             
      use_nc_get_vars(self,_use_get_vars)
      
 
 
      enable the use of netcdf library routine nc_get_vars
@@ -3329,7 +3349,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_maskandscale(unknown):
     
      
 
-        
+    
             
      set_auto_maskandscale(self,maskandscale)
      
 
 
      turn on or off automatic conversion of variable data to and
@@ -3393,7 +3413,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_scale(unknown):
     
      
 
-        
+    
             
      set_auto_scale(self,scale)
      
 
 
      turn on or off automatic packing/unpacking of variable
@@ -3442,7 +3462,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_mask(unknown):
     
      
 
-        
+    
             
      set_auto_mask(self,mask)
      
 
 
      turn on or off automatic conversion of variable data to and
@@ -3477,7 +3497,7 @@ 
      In-memory (diskless) Datasets
      
             set_always_mask(unknown):
     
      
 
-        
+    
             
      set_always_mask(self,always_mask)
      
 
 
      turn on or off conversion of data without missing values to regular
@@ -3500,7 +3520,7 @@ 
      In-memory (diskless) Datasets
      
             set_ncstring_attrs(unknown):
     
      
 
-        
+    
             
      set_always_mask(self,ncstring_attrs)
      
 
 
      turn on or off creating NC_STRING string attributes.
      
@@ -3522,7 +3542,7 @@ 
      In-memory (diskless) Datasets
      
             set_collective(unknown):
     
      
 
-        
+    
             
      set_collective(self,True_or_False)
      
 
 
      turn on or off collective parallel IO access. Ignored if file is not
@@ -3539,7 +3559,7 @@ 
      In-memory (diskless) Datasets
      
             get_dims(unknown):
     
      
 
-        
+    
             
      get_dims(self)
      
 
 
      return a tuple of Dimension instances associated with this
@@ -3551,9 +3571,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.Variable' objects>
+        name
     
      
 
+    
             
      string name of Variable instance
      
 
      
 
@@ -3562,9 +3583,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        datatype = <attribute 'datatype' of 'netCDF4._netCDF4.Variable' objects>
+        datatype
     
      
 
+    
             
      numpy data type (for primitive data types) or
 VLType/CompoundType/EnumType instance 
 (for compound, vlen  or enum data types)
      
@@ -3575,9 +3597,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        shape = <attribute 'shape' of 'netCDF4._netCDF4.Variable' objects>
+        shape
     
      
 
+    
             
      find current sizes of all variable dimensions
      
 
      
 
@@ -3586,9 +3609,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        size = <attribute 'size' of 'netCDF4._netCDF4.Variable' objects>
+        size
     
      
 
+    
             
      Return the number of stored elements.
      
 
      
 
@@ -3597,9 +3621,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Variable' objects>
+        dimensions
     
      
 
+    
             
      get variables's dimension names
      
 
      
 
@@ -3608,55 +3633,61 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        ndim = <attribute 'ndim' of 'netCDF4._netCDF4.Variable' objects>
+        ndim
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.Variable' objects>
+        dtype
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        mask = <attribute 'mask' of 'netCDF4._netCDF4.Variable' objects>
+        mask
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        scale = <attribute 'scale' of 'netCDF4._netCDF4.Variable' objects>
+        scale
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        always_mask = <attribute 'always_mask' of 'netCDF4._netCDF4.Variable' objects>
+        always_mask
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        chartostring = <attribute 'chartostring' of 'netCDF4._netCDF4.Variable' objects>
+        chartostring
     
      
 
     
+    
 
                             
      
                 
@@ -3669,7 +3700,7 @@ 
      In-memory (diskless) Datasets
      
         Dimension:
     
      
 
-        
+    
             
      A netCDF Dimension is used to describe the coordinates of a Variable.
 See Dimension.__init__ for more details.
      
 
@@ -3695,7 +3726,7 @@ 
      In-memory (diskless) Datasets
      
             Dimension()
     
      
 
-        
+    
             
      __init__(self, group, name, size=None)
      
 
 
      Dimension constructor.
      
@@ -3721,7 +3752,7 @@ 
      In-memory (diskless) Datasets
      
             group(unknown):
     
      
 
-        
+    
             
      group(self)
      
 
 
      return the group that this Dimension is a member of.
      
@@ -3737,7 +3768,7 @@ 
      In-memory (diskless) Datasets
      
             isunlimited(unknown):
     
      
 
-        
+    
             
      isunlimited(self)
      
 
 
      returns True if the Dimension instance is unlimited, False otherwise.
      
@@ -3748,9 +3779,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.Dimension' objects>
+        name
     
      
 
+    
             
      string name of Dimension instance
      
 
      
 
@@ -3759,9 +3791,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        size = <attribute 'size' of 'netCDF4._netCDF4.Dimension' objects>
+        size
     
      
 
+    
             
      current size of Dimension (calls len on Dimension instance)
      
 
      
 
@@ -3777,7 +3810,7 @@ 
      In-memory (diskless) Datasets
      
         Group(netCDF4.Dataset):
     
      
 
-        
+    
             
      Groups define a hierarchical namespace within a netCDF file. They are
 analogous to directories in a unix filesystem. Each Group behaves like
 a Dataset within a Dataset, and can contain it's own variables,
@@ -3801,7 +3834,7 @@ 
      In-memory (diskless) Datasets
      
             Group()
     
      
 
-        
+    
             
      __init__(self, parent, name)
 Group constructor.
      
 
@@ -3825,7 +3858,7 @@ 
      In-memory (diskless) Datasets
      
             close(unknown):
     
      
 
-        
+    
             
      close(self)
      
 
 
      overrides Dataset close method which does not apply to Group
@@ -3895,7 +3928,7 @@ 
      Inherited Members
      
         MFDataset(netCDF4.Dataset):
     
      
 
-        
+    
             
      Class for reading multi-file netCDF Datasets, making variables
 spanning multiple files appear as if they were in one file.
 Datasets must be in NETCDF4_CLASSIC, NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET
@@ -3905,7 +3938,7 @@ 
      Inherited Members
      
 
 
      Example usage (See MFDataset.__init__ for more details):
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> # create a series of netCDF files with a variable sharing
 >>> # the same unlimited dimension.
 >>> for nf in range(10):
@@ -3932,7 +3965,7 @@ 
      Inherited Members
      
             MFDataset(files, check=False, aggdim=None, exclude=[], master_file=None)
     
      
 
-        
+    
             
      __init__(self, files, check=False, aggdim=None, exclude=[],
 master_file=None)
      
 
@@ -3977,7 +4010,7 @@ 
      Inherited Members
      
             ncattrs(self):
     
      
 
-        
+    
             
      ncattrs(self)
      
 
 
      return the netcdf attribute names from the master file.
      
@@ -3993,7 +4026,7 @@ 
      Inherited Members
      
             close(self):
     
      
 
-        
+    
             
      close(self)
      
 
 
      close all the open files.
      
@@ -4061,13 +4094,13 @@ 
      Inherited Members
      
         MFTime(netCDF4._netCDF4._Variable):
     
      
 
-        
+    
             
      Class providing an interface to a MFDataset time Variable by imposing a unique common
 time unit and/or calendar to all files.
      
 
 
      Example usage (See MFTime.__init__ for more details):
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> f1 = Dataset("mftest_1.nc","w", format="NETCDF4_CLASSIC")
 >>> f2 = Dataset("mftest_2.nc","w", format="NETCDF4_CLASSIC")
 >>> f1.createDimension("time",None)
@@ -4103,7 +4136,7 @@ 
      Inherited Members
      
             MFTime(time, units=None, calendar=None)
     
      
 
-        
+    
             
      __init__(self, time, units=None, calendar=None)
      
 
 
      Create a time Variable with units consistent across a multifile
@@ -4147,7 +4180,7 @@ 
      Inherited Members
      
         CompoundType:
     
      
 
-        
+    
             
      A CompoundType instance is used to describe a compound data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance.
@@ -4166,7 +4199,7 @@ 
      Inherited Members
      
             CompoundType()
     
      
 
-        
+    
             
      __init__(group, datatype, datatype_name)
      
 
 
      CompoundType constructor.
      
@@ -4195,28 +4228,31 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.CompoundType' objects>
+        dtype
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        dtype_view = <attribute 'dtype_view' of 'netCDF4._netCDF4.CompoundType' objects>
+        dtype_view
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.CompoundType' objects>
+        name
     
      
 
     
+    
 
                             
      
                 
@@ -4229,7 +4265,7 @@ 
      Inherited Members
      
         VLType:
     
      
 
-        
+    
             
      A VLType instance is used to describe a variable length (VLEN) data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance. See
@@ -4247,7 +4283,7 @@ 
      Inherited Members
      
             VLType()
     
      
 
-        
+    
             
      __init__(group, datatype, datatype_name)
      
 
 
      VLType constructor.
      
@@ -4270,19 +4306,21 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.VLType' objects>
+        dtype
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.VLType' objects>
+        name
     
      
 
     
+    
 
                             
      
                 
@@ -4294,7 +4332,7 @@ 
      Inherited Members
      
             date2num(unknown):
     
      
 
-        
+    
             
      date2num(dates, units, calendar=None, has_year_zero=None)
      
 
 
      Return numeric time values given datetime objects. The units
@@ -4354,7 +4392,7 @@ 
      Inherited Members
      
             num2date(unknown):
     
      
 
-        
+    
             
      num2date(times, units, calendar=u'standard', only_use_cftime_datetimes=True, only_use_python_datetimes=False, has_year_zero=None)
      
 
 
      Return datetime objects given numeric time values. The units
@@ -4426,7 +4464,7 @@ 
      Inherited Members
      
             date2index(unknown):
     
      
 
-        
+    
             
      date2index(dates, nctime, calendar=None, select=u'exact', has_year_zero=None)
      
 
 
      Return indices of a netCDF time variable corresponding to the given dates.
      
@@ -4480,7 +4518,7 @@ 
      Inherited Members
      
             stringtochar(unknown):
     
      
 
-        
+    
             
      stringtochar(a,encoding='utf-8')
      
 
 
      convert a string array to a character array with one extra dimension
      
@@ -4507,7 +4545,7 @@ 
      Inherited Members
      
             chartostring(unknown):
     
      
 
-        
+    
             
      chartostring(b,encoding='utf-8')
      
 
 
      convert a character array to a string array with one less dimension.
      
@@ -4534,7 +4572,7 @@ 
      Inherited Members
      
             stringtoarr(unknown):
     
      
 
-        
+    
             
      stringtoarr(a, NUMCHARS,dtype='S')
      
 
 
      convert a string to a character array of length NUMCHARS
      
@@ -4562,7 +4600,7 @@ 
      Inherited Members
      
             getlibversion(unknown):
     
      
 
-        
+    
             
      getlibversion()
      
 
 
      returns a string describing the version of the netcdf library
@@ -4580,7 +4618,7 @@ 
      Inherited Members
      
         EnumType:
     
      
 
-        
+    
             
      A EnumType instance is used to describe an Enum data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance. See
@@ -4598,7 +4636,7 @@ 
      Inherited Members
      
             EnumType()
     
      
 
-        
+    
             
      __init__(group, datatype, datatype_name, enum_dict)
      
 
 
      EnumType constructor.
      
@@ -4624,28 +4662,31 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.EnumType' objects>
+        dtype
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.EnumType' objects>
+        name
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        enum_dict = <attribute 'enum_dict' of 'netCDF4._netCDF4.EnumType' objects>
+        enum_dict
     
      
 
     
+    
 
                             
      
                 
@@ -4657,7 +4698,7 @@ 
      Inherited Members
      
             get_chunk_cache(unknown):
     
      
 
-        
+    
             
      get_chunk_cache()
      
 
 
      return current netCDF chunk cache information in a tuple (size,nelems,preemption).
@@ -4675,7 +4716,7 @@ 
      Inherited Members
      
             set_chunk_cache(unknown):
     
      
 
-        
+    
             
      set_chunk_cache(self,size=None,nelems=None,preemption=None)
      
 
 
      change netCDF4 chunk cache settings.
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index b9897aa34..d1d3e824a 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -58,6 +58,12 @@ types) are not supported.
    If the dependencies are not found
    in any of the paths specified by environment variables, then standard locations
    (such as `/usr` and `/usr/local`) are searched.
+ - if the env var `NETCDF_PLUGIN_DIR` is set to point to the location netcdf-c compression
+   plugin shared objects, they will be installed inside the package.  In this
+   case `HDF5_PLUGIN_PATH` will be set to the package installation path on import,
+   so the extra compression algorithms available in netcdf-c 4.9.0 will automatically
+   be available.  Otherwise, the user will have to set `HDF5_PLUGIN_PATH` explicitly
+   to have access to the extra compression plugins.
  - run `python setup.py build`, then `python setup.py install` (as root if
    necessary).
  - run the tests in the 'test' directory by running `python run_all.py`.

From 073956ec5748f44b869d34890082c325c9653998 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Wed, 18 May 2022 10:07:26 -0600
Subject: [PATCH 0828/1504] fix typo

---
 test/run_all.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/test/run_all.py b/test/run_all.py
index a76764d97..289b75aae 100755
--- a/test/run_all.py
+++ b/test/run_all.py
@@ -28,13 +28,13 @@
     sys.stdout.write('not running tst_compression_quant.py ...\n')
 if not __has_zstandard_support__:
     test_files.remove('tst_compression_zstd.py')
-    sys.stdout.write('not running tst_compression_quant.py ...\n')
+    sys.stdout.write('not running tst_compression_zstd.py ...\n')
 if not __has_bzip2_support__:
     test_files.remove('tst_compression_bzip2.py')
     sys.stdout.write('not running tst_compression_bzip2.py ...\n')
 if not __has_blosc_support__:
     test_files.remove('tst_compression_blosc.py')
-    sys.stdout.write('not running tst_compression_bzip2.py ...\n')
+    sys.stdout.write('not running tst_compression_blosc2.py ...\n')
 if not __has_szip_support__:
     test_files.remove('tst_compression_szip.py')
     sys.stdout.write('not running tst_compression_szip.py ...\n')

From a5ae6791f51ada9c95cde686c883accdc51ec814 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Fri, 20 May 2022 10:54:05 -0600
Subject: [PATCH 0829/1504] update for latest changes in plugin installation

---
 setup.py                 | 2 +-
 src/netCDF4/__init__.py  | 2 +-
 src/netCDF4/_netCDF4.pyx | 6 +++---
 3 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/setup.py b/setup.py
index 81ab37576..76a1d9fd6 100644
--- a/setup.py
+++ b/setup.py
@@ -686,7 +686,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 # (should point to location of .so files built by netcdf-c)
 if os.environ.get("NETCDF_PLUGIN_DIR"):
     plugin_dir = os.environ.get("NETCDF_PLUGIN_DIR")
-    plugins = glob.glob(os.path.join(plugin_dir, "*.so"))
+    plugins = glob.glob(os.path.join(plugin_dir, "lib__nc*"))
     if not plugins:
         sys.stdout.write('no .so files in NETCDF_PLUGIN_DIR, no plugin shared objects installed\n')
         data_files = []
diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py
index b6f9d2293..4b880cd92 100644
--- a/src/netCDF4/__init__.py
+++ b/src/netCDF4/__init__.py
@@ -14,5 +14,5 @@
 __all__ =\
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
 # if HDF5_PLUGIN_PATH not set, point to package path if libh5noop.so exists there
-if 'HDF5_PLUGIN_PATH' not in os.environ and os.path.exists(os.path.join(__path__[0],'libh5noop.so')):
+if 'HDF5_PLUGIN_PATH' not in os.environ and os.path.exists(os.path.join(__path__[0],'lib__nczhdf5filters.so')):
     os.environ['HDF5_PLUGIN_PATH']=__path__[0]
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index d1d3e824a..001fcd122 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -58,10 +58,10 @@ types) are not supported.
    If the dependencies are not found
    in any of the paths specified by environment variables, then standard locations
    (such as `/usr` and `/usr/local`) are searched.
- - if the env var `NETCDF_PLUGIN_DIR` is set to point to the location netcdf-c compression
-   plugin shared objects, they will be installed inside the package.  In this
+ - if the env var `NETCDF_PLUGIN_DIR` is set to point to the location of the netcdf-c compression
+   plugin shared objects built by netcdf >= 4.9.0, they will be installed inside the package.  In this
    case `HDF5_PLUGIN_PATH` will be set to the package installation path on import,
-   so the extra compression algorithms available in netcdf-c 4.9.0 will automatically
+   so the extra compression algorithms available in netcdf-c >= 4.9.0 will automatically
    be available.  Otherwise, the user will have to set `HDF5_PLUGIN_PATH` explicitly
    to have access to the extra compression plugins.
  - run `python setup.py build`, then `python setup.py install` (as root if

From 4e837431c29b312e84211f84a365a3518235777a Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 21 May 2022 09:17:39 -0600
Subject: [PATCH 0830/1504] update docs

---
 Changelog                |  2 +-
 README.md                |  2 +-
 setup.py                 | 10 +++++-----
 src/netCDF4/_netCDF4.pyx |  2 +-
 4 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/Changelog b/Changelog
index 435a6bdc6..4caef91eb 100644
--- a/Changelog
+++ b/Changelog
@@ -18,7 +18,7 @@
    'szip_mask' and 'szip_pixels_per_block' kwargs also added.
    compression='zlib' is equivalent to (the now deprecated) zlib=True.
    If the environment variable NETCDF_PLUGIN_DIR is set to point to the
-   directory with the HDF5 plugin .so files, then the compression plugins will
+   directory with the compression plugin lib__nc* files, then the compression plugins will
    be installed within the package and be automatically available (the binary
    wheels have this).  Otherwise, the environment variable HDF5_PLUGIN_PATH
    needs to be se to point to plugins in order to use the new compression
diff --git a/README.md b/README.md
index 453648b80..9f714903f 100644
--- a/README.md
+++ b/README.md
@@ -14,7 +14,7 @@ For details on the latest updates, see the [Changelog](https://github.com/Unidat
 for quantization (bit-grooming and bit-rounding) functionality in netcdf-c 4.9.0 which can
 dramatically improve compression.  Dataset.createVariable now accepts dimension instances (instead
 of just dimension names). 'compression' kwarg added to Dataset.createVariable to support szip as
-well as new compression algorithms available in netcdf-c 4.9.0 through HDF5 filter plugsins (such
+well as new compression algorithms available in netcdf-c 4.9.0 through compression plugins (such
 as zstd, bzip2 and blosc). Working arm64 wheels for Apple M1 Silicon now available on pypi.
 
 10/31/2021:  Version [1.5.8](https://pypi.python.org/pypi/netCDF4/1.5.8) released. Fix Enum bug, add binary wheels for aarch64 and python 3.10.
diff --git a/setup.py b/setup.py
index 76a1d9fd6..5c61f4a3a 100644
--- a/setup.py
+++ b/setup.py
@@ -682,21 +682,21 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 else:
     ext_modules = None
 
-# if NETCDF_PLUGIN_DIR set, install netcdf-c plugin shared objects in package
-# (should point to location of .so files built by netcdf-c)
+# if NETCDF_PLUGIN_DIR set, install netcdf-c compression plugins inside package
+# (should point to location of lib__nc* files built by netcdf-c)
 if os.environ.get("NETCDF_PLUGIN_DIR"):
     plugin_dir = os.environ.get("NETCDF_PLUGIN_DIR")
     plugins = glob.glob(os.path.join(plugin_dir, "lib__nc*"))
     if not plugins:
-        sys.stdout.write('no .so files in NETCDF_PLUGIN_DIR, no plugin shared objects installed\n')
+        sys.stdout.write('no plugin files in NETCDF_PLUGIN_DIR, not installing..\n')
         data_files = []
     else:
         data_files = plugins
-        sys.stdout.write('installing plugin shared objects from %s ...\n' % plugin_dir)
+        sys.stdout.write('installing netcdf compression plugins from %s ...\n' % plugin_dir)
         sofiles = [os.path.basename(sofilepath) for sofilepath in data_files]
         sys.stdout.write(repr(sofiles)+'\n')
 else:
-    sys.stdout.write('NETCDF_PLUGIN_DIR not set, no plugin shared objects installed\n')
+    sys.stdout.write('NETCDF_PLUGIN_DIR not set, no netcdf compression plugins installed\n')
     data_files = []
 
 setup(name="netCDF4",
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 001fcd122..8a006f457 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -59,7 +59,7 @@ types) are not supported.
    in any of the paths specified by environment variables, then standard locations
    (such as `/usr` and `/usr/local`) are searched.
  - if the env var `NETCDF_PLUGIN_DIR` is set to point to the location of the netcdf-c compression
-   plugin shared objects built by netcdf >= 4.9.0, they will be installed inside the package.  In this
+   plugins built by netcdf >= 4.9.0, they will be installed inside the package.  In this
    case `HDF5_PLUGIN_PATH` will be set to the package installation path on import,
    so the extra compression algorithms available in netcdf-c >= 4.9.0 will automatically
    be available.  Otherwise, the user will have to set `HDF5_PLUGIN_PATH` explicitly

From d5af6ebdd19b4fa1840edb9a06ebf42989d10433 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 17 Jun 2022 17:21:33 -0600
Subject: [PATCH 0831/1504] update netcdf-c version

---
 .github/workflows/build.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 496012eda..d3cafded6 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -6,7 +6,7 @@ jobs:
     runs-on: ubuntu-latest
     env:
       PNETCDF_VERSION: 1.12.1
-      NETCDF_VERSION: 4.8.0
+      NETCDF_VERSION: 4.9.0
       NETCDF_DIR: ${{ github.workspace }}/..
       NETCDF_EXTRA_CONFIG: --enable-pnetcdf
       CC: mpicc.mpich

From 4d3a51062ee18e36a9740a88db752ce7f7788d39 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 17 Jun 2022 17:31:46 -0600
Subject: [PATCH 0832/1504] update netcdf-c download URL

---
 .github/workflows/build.yml | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index d3cafded6..01861228f 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -36,7 +36,7 @@ jobs:
         make install
         popd
         echo "Download and build netCDF version ${NETCDF_VERSION}"
-        wget ftp://ftp.unidata.ucar.edu/pub/netcdf/netcdf-c-${NETCDF_VERSION}.tar.gz
+        wget https://downloads.unidata.ucar.edu/netcdf-c/4.9.0/netcdf-c-${NETCDF_VERSION}.tar.gz
         tar -xzf netcdf-c-${NETCDF_VERSION}.tar.gz
         pushd netcdf-c-${NETCDF_VERSION}
         export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include"
@@ -61,6 +61,7 @@ jobs:
     - name: Install netcdf4-python
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
+        export NETCDF_PLUGIN_DIR=${NETCDF_DIR}/plugins/.libs
         python setup.py install
     - name: Test
       run: |

From 00a0acb5545032fa867861d8e8732208b7a8cdb3 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 17 Jun 2022 17:37:46 -0600
Subject: [PATCH 0833/1504] build plugins

---
 .github/workflows/build.yml | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 01861228f..4dff81c0d 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -42,9 +42,10 @@ jobs:
         export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include"
         export LDFLAGS="-L${NETCDF_DIR}/lib"
         export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
-        ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 $NETCDF_EXTRA_CONFIG
+        ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 --with-plugin-dir $NETCDF_EXTRA_CONFIG
         make -j 2
         make install
+        ls -l plugins/.libs
         popd
 
 #   - name: The job has failed

From 4377e63081077caf454ffd84f4c696dc60297905 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 17 Jun 2022 17:44:19 -0600
Subject: [PATCH 0834/1504] update plugin dir

---
 .github/workflows/build.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 4dff81c0d..08d00132c 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -45,7 +45,7 @@ jobs:
         ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 --with-plugin-dir $NETCDF_EXTRA_CONFIG
         make -j 2
         make install
-        ls -l plugins/.libs
+        ls -l plugins/plugindir
         popd
 
 #   - name: The job has failed
@@ -62,7 +62,7 @@ jobs:
     - name: Install netcdf4-python
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
-        export NETCDF_PLUGIN_DIR=${NETCDF_DIR}/plugins/.libs
+        export NETCDF_PLUGIN_DIR=${NETCDF_DIR}/plugins/plugindir
         python setup.py install
     - name: Test
       run: |

From 4e5ee594a0c0910ae479619e93de11740534297f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 17 Jun 2022 17:55:05 -0600
Subject: [PATCH 0835/1504] update plugindir

---
 .github/workflows/build_master.yml | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 10e5fa508..1846524f0 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -31,7 +31,7 @@ jobs:
         export LDFLAGS="-L${NETCDF_DIR}/lib"
         export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
         autoreconf -i
-        ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4
+        ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 
         make -j 2
         make install
         popd
@@ -50,12 +50,12 @@ jobs:
     - name: Install netcdf4-python
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
-        export NETCDF_PLUGIN_DIR=${NETCDF_DIR}/plugins/.libs
+        export NETCDF_PLUGIN_DIR=${NETCDF_DIR}/plugins/plugindir
         python setup.py install
     - name: Test
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
-        #export HDF5_PLUGIN_PATH=${NETCDF_DIR}/plugins/.libs
+        #export HDF5_PLUGIN_PATH=${NETCDF_DIR}/plugins/plugindir
         python checkversion.py
         # serial
         cd test

From f6e00cd982ad90cc340a360bdcefd3b4a150f7c6 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 17 Jun 2022 18:17:22 -0600
Subject: [PATCH 0836/1504] update

---
 .github/workflows/build_master.yml | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 1846524f0..bf0ce7a6e 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -51,6 +51,8 @@ jobs:
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
         export NETCDF_PLUGIN_DIR=${NETCDF_DIR}/plugins/plugindir
+        ls -l /home/runner/work/netcdf4-python/netcdf4-python/netcdf-c/plugins/plugindir
+        ls -l $NETCDF_PLUGIN_DIR
         python setup.py install
     - name: Test
       run: |

From 6a22864bdfbf486ff5962c1d5d6728518dd9f04a Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 17 Jun 2022 18:54:47 -0600
Subject: [PATCH 0837/1504] update plugindir

---
 .github/workflows/build_master.yml | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index bf0ce7a6e..3f4d7c2b6 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -50,8 +50,7 @@ jobs:
     - name: Install netcdf4-python
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
-        export NETCDF_PLUGIN_DIR=${NETCDF_DIR}/plugins/plugindir
-        ls -l /home/runner/work/netcdf4-python/netcdf4-python/netcdf-c/plugins/plugindir
+        export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c/plugins/plugindir
         ls -l $NETCDF_PLUGIN_DIR
         python setup.py install
     - name: Test

From 7a8c94c8a7a924972e32a4e27262d622bc91a7b5 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 17 Jun 2022 19:23:20 -0600
Subject: [PATCH 0838/1504] fix plugin installation for 4.9.0

---
 .github/workflows/build.yml        | 5 ++---
 .github/workflows/build_master.yml | 1 -
 2 files changed, 2 insertions(+), 4 deletions(-)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 08d00132c..ad6a011eb 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -42,10 +42,9 @@ jobs:
         export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include"
         export LDFLAGS="-L${NETCDF_DIR}/lib"
         export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
-        ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 --with-plugin-dir $NETCDF_EXTRA_CONFIG
+        ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 $NETCDF_EXTRA_CONFIG
         make -j 2
         make install
-        ls -l plugins/plugindir
         popd
 
 #   - name: The job has failed
@@ -62,7 +61,7 @@ jobs:
     - name: Install netcdf4-python
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
-        export NETCDF_PLUGIN_DIR=${NETCDF_DIR}/plugins/plugindir
+        export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c/plugins/plugindir
         python setup.py install
     - name: Test
       run: |
diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 3f4d7c2b6..00b3a52d4 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -51,7 +51,6 @@ jobs:
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
         export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c/plugins/plugindir
-        ls -l $NETCDF_PLUGIN_DIR
         python setup.py install
     - name: Test
       run: |

From b80f43d0a6755a1298897e3f2a7f24eb30261a98 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 17 Jun 2022 19:35:39 -0600
Subject: [PATCH 0839/1504] update

---
 .github/workflows/build.yml | 4 ++--
 Changelog                   | 2 +-
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index ad6a011eb..11e218157 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -26,7 +26,7 @@ jobs:
     - name: Install Ubuntu Dependencies
       run: |
         sudo apt-get update
-        sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev libcurl4-openssl-dev 
+        sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
         echo "Download and build PnetCDF version ${PNETCDF_VERSION}"
         wget https://parallel-netcdf.github.io/Release/pnetcdf-${PNETCDF_VERSION}.tar.gz
         tar -xzf pnetcdf-${PNETCDF_VERSION}.tar.gz
@@ -61,7 +61,7 @@ jobs:
     - name: Install netcdf4-python
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
-        export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c/plugins/plugindir
+        export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c-${NETCDF_VERSION}/plugins/plugindir
         python setup.py install
     - name: Test
       run: |
diff --git a/Changelog b/Changelog
index 4caef91eb..08d7e2cfd 100644
--- a/Changelog
+++ b/Changelog
@@ -21,7 +21,7 @@
    directory with the compression plugin lib__nc* files, then the compression plugins will
    be installed within the package and be automatically available (the binary
    wheels have this).  Otherwise, the environment variable HDF5_PLUGIN_PATH
-   needs to be se to point to plugins in order to use the new compression
+   needs to be set at runtime  to point to plugins in order to use the new compression
    options.
  * MFDataset did not aggregate 'name' variable attribute (issue #1153).
  * issue warning instead of raising an exception if missing_value or

From a95f1359dbdb98ce9923c84787ed915d946427c1 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 19 Jun 2022 18:10:43 -0600
Subject: [PATCH 0840/1504] update

---
 src/netCDF4/__init__.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py
index 4b880cd92..2f3463fc0 100644
--- a/src/netCDF4/__init__.py
+++ b/src/netCDF4/__init__.py
@@ -15,4 +15,5 @@
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
 # if HDF5_PLUGIN_PATH not set, point to package path if libh5noop.so exists there
 if 'HDF5_PLUGIN_PATH' not in os.environ and os.path.exists(os.path.join(__path__[0],'lib__nczhdf5filters.so')):
+    print('setting HDF5_PLUGIN_PATH to %s' % __path__[0])
     os.environ['HDF5_PLUGIN_PATH']=__path__[0]

From cf202781a1e590334e6547d7b05aa71eab2cee5c Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 20 Jun 2022 13:16:25 -0600
Subject: [PATCH 0841/1504] check for dylib extension on plugins

---
 src/netCDF4/__init__.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py
index 2f3463fc0..d0009398d 100644
--- a/src/netCDF4/__init__.py
+++ b/src/netCDF4/__init__.py
@@ -13,7 +13,8 @@
 import os
 __all__ =\
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
-# if HDF5_PLUGIN_PATH not set, point to package path if libh5noop.so exists there
-if 'HDF5_PLUGIN_PATH' not in os.environ and os.path.exists(os.path.join(__path__[0],'lib__nczhdf5filters.so')):
-    print('setting HDF5_PLUGIN_PATH to %s' % __path__[0])
+# if HDF5_PLUGIN_PATH not set, point to package path if plugins live there
+if 'HDF5_PLUGIN_PATH' not in os.environ and\
+    (os.path.exists(os.path.join(__path__[0],'lib__nczhdf5filters.so')) or\
+    os.path.exists(os.path.join(__path__[0],'lib__nczhdf5filters.dylib'))):
     os.environ['HDF5_PLUGIN_PATH']=__path__[0]

From 0eed426bed472e7f7893e22de1b1b93a79a613d4 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 20 Jun 2022 13:23:08 -0600
Subject: [PATCH 0842/1504] use package_data to install plugins (works with
 pip)

---
 setup.py | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index 5c61f4a3a..e9259f2b1 100644
--- a/setup.py
+++ b/setup.py
@@ -1,5 +1,6 @@
 import os, sys, subprocess, glob
 import os.path as osp
+import shutil
 import configparser
 from setuptools import setup, Extension
 from distutils.dist import Distribution
@@ -695,6 +696,8 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         sys.stdout.write('installing netcdf compression plugins from %s ...\n' % plugin_dir)
         sofiles = [os.path.basename(sofilepath) for sofilepath in data_files]
         sys.stdout.write(repr(sofiles)+'\n')
+        for f in data_files:
+            shutil.copy(f, osp.join(os.getcwd(),osp.join('src','netCDF4')))
 else:
     sys.stdout.write('NETCDF_PLUGIN_DIR not set, no netcdf compression plugins installed\n')
     data_files = []
@@ -724,6 +727,8 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
                    "Operating System :: OS Independent"],
       packages=['netCDF4'],
       package_dir={'':'src'},
-      data_files=[('netCDF4',data_files)],
+      #data_files=[('netCDF4',data_files)], # doesn't work with pip install
+      include_package_data = True,
+      package_data={"netCDF4": ["lib__nc*"]},
       ext_modules=ext_modules,
       **setuptools_extra_kwargs)

From c476a39b8395000e3dbe2f0d3a1cfae8e914ef83 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 20 Jun 2022 20:24:19 -0600
Subject: [PATCH 0843/1504] remove plugins copied from outside source tree

---
 setup.py | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/setup.py b/setup.py
index e9259f2b1..745ef9867 100644
--- a/setup.py
+++ b/setup.py
@@ -685,6 +685,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 
 # if NETCDF_PLUGIN_DIR set, install netcdf-c compression plugins inside package
 # (should point to location of lib__nc* files built by netcdf-c)
+copied_plugins=False
 if os.environ.get("NETCDF_PLUGIN_DIR"):
     plugin_dir = os.environ.get("NETCDF_PLUGIN_DIR")
     plugins = glob.glob(os.path.join(plugin_dir, "lib__nc*"))
@@ -698,6 +699,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         sys.stdout.write(repr(sofiles)+'\n')
         for f in data_files:
             shutil.copy(f, osp.join(os.getcwd(),osp.join('src','netCDF4')))
+        copied_plugins=True
 else:
     sys.stdout.write('NETCDF_PLUGIN_DIR not set, no netcdf compression plugins installed\n')
     data_files = []
@@ -732,3 +734,8 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
       package_data={"netCDF4": ["lib__nc*"]},
       ext_modules=ext_modules,
       **setuptools_extra_kwargs)
+
+# remove plugin files copied from outside source tree
+if copied_plugins:
+    for f in sofiles:
+        os.remove(osp.join(osp.join('src','netCDF4'),f))

From 519eff15622dbbb0501f8ee4b00d2d44ce74b354 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 21 Jun 2022 09:24:03 -0600
Subject: [PATCH 0844/1504] bypass plugins tests with env var NO_PLUGINS

---
 test/run_all.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/test/run_all.py b/test/run_all.py
index 289b75aae..1dfb5309a 100755
--- a/test/run_all.py
+++ b/test/run_all.py
@@ -26,15 +26,15 @@
 if not __has_quantization_support__:
     test_files.remove('tst_compression_quant.py')
     sys.stdout.write('not running tst_compression_quant.py ...\n')
-if not __has_zstandard_support__:
+if not __has_zstandard_support__ or os.getenv('NO_PLUGINS'):
     test_files.remove('tst_compression_zstd.py')
     sys.stdout.write('not running tst_compression_zstd.py ...\n')
-if not __has_bzip2_support__:
+if not __has_bzip2_support__ or os.getenv('NO_PLUGINS'):
     test_files.remove('tst_compression_bzip2.py')
     sys.stdout.write('not running tst_compression_bzip2.py ...\n')
-if not __has_blosc_support__:
+if not __has_blosc_support__ or os.getenv('NO_PLUGINS'):
     test_files.remove('tst_compression_blosc.py')
-    sys.stdout.write('not running tst_compression_blosc2.py ...\n')
+    sys.stdout.write('not running tst_compression_blosc.py ...\n')
 if not __has_szip_support__:
     test_files.remove('tst_compression_szip.py')
     sys.stdout.write('not running tst_compression_szip.py ...\n')

From ef100618d851d284547ae73e958e7e28e4f26d90 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 23 Jun 2022 16:00:00 -0600
Subject: [PATCH 0845/1504] install plugins in 'plugins' subdir

---
 setup.py                | 13 +++++++------
 src/netCDF4/__init__.py |  6 +++---
 2 files changed, 10 insertions(+), 9 deletions(-)

diff --git a/setup.py b/setup.py
index 745ef9867..3f1b593cc 100644
--- a/setup.py
+++ b/setup.py
@@ -2,7 +2,7 @@
 import os.path as osp
 import shutil
 import configparser
-from setuptools import setup, Extension
+from setuptools import setup, Extension, find_namespace_packages
 from distutils.dist import Distribution
 
 setuptools_extra_kwargs = {
@@ -698,7 +698,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         sofiles = [os.path.basename(sofilepath) for sofilepath in data_files]
         sys.stdout.write(repr(sofiles)+'\n')
         for f in data_files:
-            shutil.copy(f, osp.join(os.getcwd(),osp.join('src','netCDF4')))
+            shutil.copy(f, osp.join(os.getcwd(),osp.join(osp.join('src','netCDF4'),'plugins')))
         copied_plugins=True
 else:
     sys.stdout.write('NETCDF_PLUGIN_DIR not set, no netcdf compression plugins installed\n')
@@ -727,15 +727,16 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
                    "Topic :: Software Development :: Libraries :: Python Modules",
                    "Topic :: System :: Archiving :: Compression",
                    "Operating System :: OS Independent"],
-      packages=['netCDF4'],
+      #packages=['netCDF4'],
+      packages=find_namespace_packages(where="src"),
       package_dir={'':'src'},
       #data_files=[('netCDF4',data_files)], # doesn't work with pip install
-      include_package_data = True,
-      package_data={"netCDF4": ["lib__nc*"]},
+      #include_package_data = True,
+      package_data={"netCDF4.plugins": ["lib__nc*"]},
       ext_modules=ext_modules,
       **setuptools_extra_kwargs)
 
 # remove plugin files copied from outside source tree
 if copied_plugins:
     for f in sofiles:
-        os.remove(osp.join(osp.join('src','netCDF4'),f))
+        os.remove(osp.join(osp.join(osp.join('src','netCDF4'),'plugins'),f))
diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py
index d0009398d..46df12db2 100644
--- a/src/netCDF4/__init__.py
+++ b/src/netCDF4/__init__.py
@@ -15,6 +15,6 @@
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
 # if HDF5_PLUGIN_PATH not set, point to package path if plugins live there
 if 'HDF5_PLUGIN_PATH' not in os.environ and\
-    (os.path.exists(os.path.join(__path__[0],'lib__nczhdf5filters.so')) or\
-    os.path.exists(os.path.join(__path__[0],'lib__nczhdf5filters.dylib'))):
-    os.environ['HDF5_PLUGIN_PATH']=__path__[0]
+    (os.path.exists(os.path.join(os.path.join(__path__[0],'plugins'),'lib__nczhdf5filters.so')) or\
+    os.path.exists(os.path.join(os.path.join(__path__[0],'plugins'),'lib__nczhdf5filters.dylib'))):
+    os.environ['HDF5_PLUGIN_PATH']=os.path.join(__path__[0],'plugins')

From ba05ffc73c4a74d38687ebaacd8ad1ad031080d6 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 23 Jun 2022 16:14:08 -0600
Subject: [PATCH 0846/1504] add an empty file to plugins dir so it ends up in
 sdist

---
 MANIFEST.in | 1 +
 setup.py    | 7 ++++---
 2 files changed, 5 insertions(+), 3 deletions(-)

diff --git a/MANIFEST.in b/MANIFEST.in
index c27bb8192..e3497466e 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -13,6 +13,7 @@ include src/netCDF4/__init__.py
 include src/netCDF4/_netCDF4.pyx
 exclude src/netCDF4/_netCDF4.c
 include src/netCDF4/utils.py
+include src/netCDF4/plugins/empty.txt
 include include/netCDF4.pxi
 include include/mpi-compat.h
 include include/membuf.pyx
diff --git a/setup.py b/setup.py
index 3f1b593cc..7853b5c09 100644
--- a/setup.py
+++ b/setup.py
@@ -697,9 +697,10 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         sys.stdout.write('installing netcdf compression plugins from %s ...\n' % plugin_dir)
         sofiles = [os.path.basename(sofilepath) for sofilepath in data_files]
         sys.stdout.write(repr(sofiles)+'\n')
-        for f in data_files:
-            shutil.copy(f, osp.join(os.getcwd(),osp.join(osp.join('src','netCDF4'),'plugins')))
-        copied_plugins=True
+        if 'sdist' not in sys.argv[1:] and 'clean' not in sys.argv[1:] and '--version' not in sys.argv[1:]:
+            for f in data_files:
+                shutil.copy(f, osp.join(os.getcwd(),osp.join(osp.join('src','netCDF4'),'plugins')))
+            copied_plugins=True
 else:
     sys.stdout.write('NETCDF_PLUGIN_DIR not set, no netcdf compression plugins installed\n')
     data_files = []

From e6e7a577779e91752ae793ba2ef26ff2498df9bb Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 23 Jun 2022 16:26:49 -0600
Subject: [PATCH 0847/1504] add empty file to plugins dir

---
 setup.py                      | 4 +++-
 src/netCDF4/plugins/empty.txt | 0
 2 files changed, 3 insertions(+), 1 deletion(-)
 create mode 100644 src/netCDF4/plugins/empty.txt

diff --git a/setup.py b/setup.py
index 7853b5c09..75d501bfe 100644
--- a/setup.py
+++ b/setup.py
@@ -740,4 +740,6 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 # remove plugin files copied from outside source tree
 if copied_plugins:
     for f in sofiles:
-        os.remove(osp.join(osp.join(osp.join('src','netCDF4'),'plugins'),f))
+        filepath = osp.join(osp.join(osp.join('src','netCDF4'),'plugins'),f)
+        if os.path.exists(filepath):
+            os.remove(filepath)
diff --git a/src/netCDF4/plugins/empty.txt b/src/netCDF4/plugins/empty.txt
new file mode 100644
index 000000000..e69de29bb

From 9dc076ea11b2f418dbb47b3fec639b18d6254d4d Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 23 Jun 2022 16:34:35 -0600
Subject: [PATCH 0848/1504] update

---
 setup.py                | 3 ---
 src/netCDF4/__init__.py | 7 ++++---
 2 files changed, 4 insertions(+), 6 deletions(-)

diff --git a/setup.py b/setup.py
index 75d501bfe..2eea22e1c 100644
--- a/setup.py
+++ b/setup.py
@@ -728,11 +728,8 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
                    "Topic :: Software Development :: Libraries :: Python Modules",
                    "Topic :: System :: Archiving :: Compression",
                    "Operating System :: OS Independent"],
-      #packages=['netCDF4'],
       packages=find_namespace_packages(where="src"),
       package_dir={'':'src'},
-      #data_files=[('netCDF4',data_files)], # doesn't work with pip install
-      #include_package_data = True,
       package_data={"netCDF4.plugins": ["lib__nc*"]},
       ext_modules=ext_modules,
       **setuptools_extra_kwargs)
diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py
index 46df12db2..e84607bab 100644
--- a/src/netCDF4/__init__.py
+++ b/src/netCDF4/__init__.py
@@ -14,7 +14,8 @@
 __all__ =\
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
 # if HDF5_PLUGIN_PATH not set, point to package path if plugins live there
+pluginpath = os.path.join(__path__[0],'plugins')
 if 'HDF5_PLUGIN_PATH' not in os.environ and\
-    (os.path.exists(os.path.join(os.path.join(__path__[0],'plugins'),'lib__nczhdf5filters.so')) or\
-    os.path.exists(os.path.join(os.path.join(__path__[0],'plugins'),'lib__nczhdf5filters.dylib'))):
-    os.environ['HDF5_PLUGIN_PATH']=os.path.join(__path__[0],'plugins')
+    (os.path.exists(os.path.join(pluginpath,'lib__nczhdf5filters.so')) or\
+     os.path.exists(os.path.join(pluginpath,'lib__nczhdf5filters.dylib'))):
+    os.environ['HDF5_PLUGIN_PATH']=pluginpath

From 158f7fde64d7c1b4b38e7bccd0681a7ace4a044e Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 24 Jun 2022 14:32:04 -0600
Subject: [PATCH 0849/1504] update

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 9f714903f..899ea457d 100644
--- a/README.md
+++ b/README.md
@@ -10,7 +10,7 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
-??/??/2022:  Version [1.6.0](https://pypi.python.org/pypi/netCDF4/1.6.0) released.  Support
+06/24/2022:  Version [1.6.0](https://pypi.python.org/pypi/netCDF4/1.6.0) released.  Support
 for quantization (bit-grooming and bit-rounding) functionality in netcdf-c 4.9.0 which can
 dramatically improve compression.  Dataset.createVariable now accepts dimension instances (instead
 of just dimension names). 'compression' kwarg added to Dataset.createVariable to support szip as

From c6d29ec96f8e089eb3b384546f8ea497e8d2f310 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 24 Jun 2022 14:33:30 -0600
Subject: [PATCH 0850/1504] update

---
 docs/index.html | 445 ++++++++++++++++++++++--------------------------
 1 file changed, 206 insertions(+), 239 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 9b62f5b05..55793dd5b 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -3,24 +3,24 @@
 
     
     
-    
+    
     netCDF4 API documentation
+    
 
-    
-    
-    
-    
-    
-    
-
-    
      
     
      
             
      
                     
      
@@ -521,10 +520,10 @@ 
      Developer Install
      
 If the dependencies are not found
 in any of the paths specified by environment variables, then standard locations
 (such as /usr and /usr/local) are searched.
-
    • if the env var NETCDF_PLUGIN_DIR is set to point to the location netcdf-c compression
-plugin shared objects, they will be installed inside the package.  In this
+
    • if the env var NETCDF_PLUGIN_DIR is set to point to the location of the netcdf-c compression
+plugins built by netcdf >= 4.9.0, they will be installed inside the package.  In this
 case HDF5_PLUGIN_PATH will be set to the package installation path on import,
-so the extra compression algorithms available in netcdf-c 4.9.0 will automatically
+so the extra compression algorithms available in netcdf-c >= 4.9.0 will automatically
 be available.  Otherwise, the user will have to set HDF5_PLUGIN_PATH explicitly
 to have access to the extra compression plugins.
      • 
 
    • run python setup.py build, then python setup.py install (as root if
@@ -583,7 +582,7 @@ 
      Creating/Opening/Closing a netCDF
 
 
      Here's an example:
      
 
-
      >>> from netCDF4 import Dataset
+
      >>> from netCDF4 import Dataset
 >>> rootgrp = Dataset("test.nc", "w", format="NETCDF4")
 >>> print(rootgrp.data_model)
 NETCDF4
@@ -612,7 +611,7 @@ 
      Groups in a netCDF file
      
 NETCDF4 formatted files support Groups, if you try to create a Group
 in a netCDF 3 file you will get an error message.
      
 
-
      >>> rootgrp = Dataset("test.nc", "a")
+
      >>> rootgrp = Dataset("test.nc", "a")
 >>> fcstgrp = rootgrp.createGroup("forecasts")
 >>> analgrp = rootgrp.createGroup("analyses")
 >>> print(rootgrp.groups)
@@ -636,7 +635,7 @@ 
      Groups in a netCDF file
      
 that group.  To simplify the creation of nested groups, you can
 use a unix-like path as an argument to Dataset.createGroup.
      
 
-
      >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
+
      >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
 >>> fcstgrp2 = rootgrp.createGroup("/forecasts/model2")
 
      
 
@@ -650,7 +649,7 @@ 
      Groups in a netCDF file
      
 to walk the directory tree. Note that printing the Dataset or Group
 object yields summary information about it's contents.
      
 
-
      >>> def walktree(top):
+
      >>> def walktree(top):
 ...     yield top.groups.values()
 ...     for value in top.groups.values():
 ...         yield from walktree(value)
@@ -700,7 +699,7 @@ 
      Dimensions in a netCDF file
      
 dimension is a new netCDF 4 feature, in netCDF 3 files there may be only
 one, and it must be the first (leftmost) dimension of the variable.
      
 
-
      >>> level = rootgrp.createDimension("level", None)
+
      >>> level = rootgrp.createDimension("level", None)
 >>> time = rootgrp.createDimension("time", None)
 >>> lat = rootgrp.createDimension("lat", 73)
 >>> lon = rootgrp.createDimension("lon", 144)
@@ -708,7 +707,7 @@ 
      Dimensions in a netCDF file
      
 
 
      All of the Dimension instances are stored in a python dictionary.
      
 
-
      >>> print(rootgrp.dimensions)
+
      >>> print(rootgrp.dimensions)
 {'level': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0, 'time': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0, 'lat': <class 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 73, 'lon': <class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144}
 
      
 
@@ -717,7 +716,7 @@ 
      Dimensions in a netCDF file
      
 Dimension.isunlimited method of a Dimension instance
 be used to determine if the dimensions is unlimited, or appendable.
      
 
-
      >>> print(len(lon))
+
      >>> print(len(lon))
 144
 >>> print(lon.isunlimited())
 False
@@ -729,7 +728,7 @@ 
      Dimensions in a netCDF file
      
 provides useful summary info, including the name and length of the dimension,
 and whether it is unlimited.
      
 
-
      >>> for dimobj in rootgrp.dimensions.values():
+
      >>> for dimobj in rootgrp.dimensions.values():
 ...     print(dimobj)
 <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0
 <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0
@@ -774,7 +773,7 @@ 
      Variables in a netCDF file
      
 method returns an instance of the Variable class whose methods can be
 used later to access and set variable data and attributes.
      
 
-
      >>> times = rootgrp.createVariable("time","f8",("time",))
+
      >>> times = rootgrp.createVariable("time","f8",("time",))
 >>> levels = rootgrp.createVariable("level","i4",("level",))
 >>> latitudes = rootgrp.createVariable("lat","f4",("lat",))
 >>> longitudes = rootgrp.createVariable("lon","f4",("lon",))
@@ -786,7 +785,7 @@ 
      Variables in a netCDF file
      
 
      To get summary info on a Variable instance in an interactive session,
 just print it.
      
 
-
      >>> print(temp)
+
      >>> print(temp)
 <class 'netCDF4._netCDF4.Variable'>
 float32 temp(time, level, lat, lon)
     units: K
@@ -797,7 +796,7 @@ 
      Variables in a netCDF file
      
 
 
      You can use a path to create a Variable inside a hierarchy of groups.
      
 
-
      >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
+
      >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
 
      
 
 
      If the intermediate groups do not yet exist, they will be created.
      
@@ -805,7 +804,7 @@ 
      Variables in a netCDF file
      
 
      You can also query a Dataset or Group instance directly to obtain Group or
 Variable instances using paths.
      
 
-
      >>> print(rootgrp["/forecasts/model1"])  # a Group instance
+
      >>> print(rootgrp["/forecasts/model1"])  # a Group instance
 <class 'netCDF4._netCDF4.Group'>
 group /forecasts/model1:
     dimensions(sizes): 
@@ -823,7 +822,7 @@ 
      Variables in a netCDF file
      
 
      All of the variables in the Dataset or Group are stored in a
 Python dictionary, in the same way as the dimensions:
      
 
-
      >>> print(rootgrp.variables)
+
      >>> print(rootgrp.variables)
 {'time': <class 'netCDF4._netCDF4.Variable'>
 float64 time(time)
 unlimited dimensions: time
@@ -866,7 +865,7 @@ 
      Attributes in a netCDF file
      
 variables. Attributes can be strings, numbers or sequences. Returning to
 our example,
      
 
-
      >>> import time
+
      >>> import time
 >>> rootgrp.description = "bogus example script"
 >>> rootgrp.history = "Created " + time.ctime(time.time())
 >>> rootgrp.source = "netCDF4 python module tutorial"
@@ -884,7 +883,7 @@ 
      Attributes in a netCDF file
      
 built-in dir Python function will return a bunch of private methods
 and attributes that cannot (or should not) be modified by the user.
      
 
-
      >>> for name in rootgrp.ncattrs():
+
      >>> for name in rootgrp.ncattrs():
 ...     print("Global attr {} = {}".format(name, getattr(rootgrp, name)))
 Global attr description = bogus example script
 Global attr history = Created Mon Jul  8 14:19:41 2019
@@ -895,7 +894,7 @@ 
      Attributes in a netCDF file
      
 instance provides all the netCDF attribute name/value pairs in a python
 dictionary:
      
 
-
      >>> print(rootgrp.__dict__)
+
      >>> print(rootgrp.__dict__)
 {'description': 'bogus example script', 'history': 'Created Mon Jul  8 14:19:41 2019', 'source': 'netCDF4 python module tutorial'}
 
      
 
@@ -908,7 +907,7 @@ 
      Writing data
 
      Now that you have a netCDF Variable instance, how do you put data
 into it? You can just treat it like an array and assign data to a slice.
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> lats =  np.arange(-90,91,2.5)
 >>> lons =  np.arange(-180,180,2.5)
 >>> latitudes[:] = lats
@@ -928,7 +927,7 @@ 
      Writing data
 objects with unlimited dimensions will grow along those dimensions if you
 assign data outside the currently defined range of indices.
      
 
-
      >>> # append along two unlimited dimensions by assigning to slice.
+
      >>> # append along two unlimited dimensions by assigning to slice.
 >>> nlats = len(rootgrp.dimensions["lat"])
 >>> nlons = len(rootgrp.dimensions["lon"])
 >>> print("temp shape before adding data = {}".format(temp.shape))
@@ -948,7 +947,7 @@ 
      Writing data
 along the level dimension of the variable temp, even though no
 data has yet been assigned to levels.
      
 
-
      >>> # now, assign data to levels dimension variable.
+
      >>> # now, assign data to levels dimension variable.
 >>> levels[:] =  [1000.,850.,700.,500.,300.,250.,200.,150.,100.,50.]
 
      
 
@@ -961,7 +960,7 @@ 
      Writing data
 allowed, and these indices work independently along each dimension (similar
 to the way vector subscripts work in fortran).  This means that
      
 
-
      >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
+
      >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
 (4, 4)
 
      
 
@@ -979,14 +978,14 @@ 
      Writing data
 
 
      For example,
      
 
-
      >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
+
      >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
 
      
 
 
      will extract time indices 0,2 and 4, pressure levels
 850, 500 and 200 hPa, all Northern Hemisphere latitudes and Eastern
 Hemisphere longitudes, resulting in a numpy array of shape  (3, 3, 36, 71).
      
 
-
      >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
+
      >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
 shape of fancy temp slice = (3, 3, 36, 71)
 
      
 
@@ -1019,7 +1018,7 @@ 
      Dealing with time coordinates
      
 provided by cftime to do just that.
 Here's an example of how they can be used:
      
 
-
      >>> # fill in times.
+
      >>> # fill in times.
 >>> from datetime import datetime, timedelta
 >>> from cftime import num2date, date2num
 >>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
@@ -1059,7 +1058,7 @@ 
      Reading data from a multi
 NETCDF4_CLASSIC format (NETCDF4 formatted multi-file
 datasets are not supported).
      
 
-
      >>> for nf in range(10):
+
      >>> for nf in range(10):
 ...     with Dataset("mftest%s.nc" % nf, "w", format="NETCDF4_CLASSIC") as f:
 ...         _ = f.createDimension("x",None)
 ...         x = f.createVariable("x","i",("x",))
@@ -1068,7 +1067,7 @@ 
      Reading data from a multi
 
 
      Now read all the files back in at once with MFDataset
      
 
-
      >>> from netCDF4 import MFDataset
+
      >>> from netCDF4 import MFDataset
 >>> f = MFDataset("mftest*nc")
 >>> print(f.variables["x"][:])
 [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
@@ -1135,22 +1134,22 @@ 
      Efficient compression of netC
 
 
      In our example, try replacing the line
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
 
      
 
 
      with
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib')
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib')
 
      
 
 
      and then
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',least_significant_digit=3)
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',least_significant_digit=3)
 
      
 
 
      or with netcdf-c >= 4.9.0
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',significant_digits=4)
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',significant_digits=4)
 
      
 
 
      and see how much smaller the resulting files are.
      
@@ -1171,7 +1170,7 @@ 
      Beyond ho
 Since there is no native complex data type in netcdf, compound types are handy
 for storing numpy complex arrays.  Here's an example:
      
 
-
      >>> f = Dataset("complex.nc","w")
+
      >>> f = Dataset("complex.nc","w")
 >>> size = 3 # length of 1-d complex array
 >>> # create sample complex data.
 >>> datac = np.exp(1j*(1.+np.linspace(0, np.pi, size)))
@@ -1207,7 +1206,7 @@ 
      Beyond ho
 in a Python dictionary, just like variables and dimensions. As always, printing
 objects gives useful summary information in an interactive session:
      
 
-
      >>> print(f)
+
      >>> print(f)
 <class 'netCDF4._netCDF4.Dataset'>
 root group (NETCDF4 data model, file format HDF5):
     dimensions(sizes): x_dim(3)
@@ -1232,7 +1231,7 @@ 
      Variable-length (vlen) data types
      
 data type, use the Dataset.createVLType method
 method of a Dataset or Group instance.
      
 
-
      >>> f = Dataset("tst_vlen.nc","w")
+
      >>> f = Dataset("tst_vlen.nc","w")
 >>> vlen_t = f.createVLType(np.int32, "phony_vlen")
 
      
 
@@ -1242,7 +1241,7 @@ 
      Variable-length (vlen) data types
      
 but compound data types cannot.
 A new variable can then be created using this datatype.
      
 
-
      >>> x = f.createDimension("x",3)
+
      >>> x = f.createDimension("x",3)
 >>> y = f.createDimension("y",4)
 >>> vlvar = f.createVariable("phony_vlen_var", vlen_t, ("y","x"))
 
      
@@ -1255,7 +1254,7 @@ 
      Variable-length (vlen) data types
      
 In this case, they contain 1-D numpy int32 arrays of random length between
 1 and 10.
      
 
-
      >>> import random
+
      >>> import random
 >>> random.seed(54321)
 >>> data = np.empty(len(y)*len(x),object)
 >>> for n in range(len(y)*len(x)):
@@ -1295,7 +1294,7 @@ 
      Variable-length (vlen) data types
      
 with fixed length greater than 1) when calling the
 Dataset.createVariable method.
      
 
-
      >>> z = f.createDimension("z",10)
+
      >>> z = f.createDimension("z",10)
 >>> strvar = f.createVariable("strvar", str, "z")
 
      
 
@@ -1303,7 +1302,7 @@ 
      Variable-length (vlen) data types
      
 random lengths between 2 and 12 characters, and the data in the object
 array is assigned to the vlen string variable.
      
 
-
      >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
+
      >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
 >>> data = np.empty(10,"O")
 >>> for n in range(10):
 ...     stringlen = random.randint(2,12)
@@ -1342,7 +1341,7 @@ 
      Enum data type
      
 values and their names are used to define an Enum data type using
 Dataset.createEnumType.
      
 
-
      >>> nc = Dataset('clouds.nc','w')
+
      >>> nc = Dataset('clouds.nc','w')
 >>> # python dict with allowed values and their names.
 >>> enum_dict = {'Altocumulus': 7, 'Missing': 255,
 ... 'Stratus': 2, 'Clear': 0,
@@ -1360,7 +1359,7 @@ 
      Enum data type
      
 is made to write an integer value not associated with one of the
 specified names.
      
 
-
      >>> time = nc.createDimension('time',None)
+
      >>> time = nc.createDimension('time',None)
 >>> # create a 1d variable of type 'cloud_type'.
 >>> # The fill_value is set to the 'Missing' named value.
 >>> cloud_var = nc.createVariable('primary_cloud',cloud_type,'time',
@@ -1397,7 +1396,7 @@ 
      Parallel IO
      
 available. To use parallel IO, your program must be running in an MPI
 environment using mpi4py.
      
 
-
      >>> from mpi4py import MPI
+
      >>> from mpi4py import MPI
 >>> import numpy as np
 >>> from netCDF4 import Dataset
 >>> rank = MPI.COMM_WORLD.rank  # The process ID (integer 0-3 for 4-process run)
@@ -1409,7 +1408,7 @@ 
      Parallel IO
      
 when a new dataset is created or an existing dataset is opened,
 use the parallel keyword to enable parallel access.
      
 
-
      >>> nc = Dataset('parallel_test.nc','w',parallel=True)
+
      >>> nc = Dataset('parallel_test.nc','w',parallel=True)
 
      
 
 
      The optional comm keyword may be used to specify a particular
@@ -1417,7 +1416,7 @@ 
      Parallel IO
      
 can now write to the file indepedently.  In this example the process rank is
 written to a different variable index on each task
      
 
-
      >>> d = nc.createDimension('dim',4)
+
      >>> d = nc.createDimension('dim',4)
 >>> v = nc.createVariable('var', np.int64, 'dim')
 >>> v[rank] = rank
 >>> nc.close()
@@ -1484,7 +1483,7 @@ 
      Dealing with strings
      
 stringtochar is used to convert the numpy string array to an array of
 characters with one more dimension. For example,
      
 
-
      >>> from netCDF4 import stringtochar
+
      >>> from netCDF4 import stringtochar
 >>> nc = Dataset('stringtest.nc','w',format='NETCDF4_CLASSIC')
 >>> _ = nc.createDimension('nchars',3)
 >>> _ = nc.createDimension('nstrings',None)
@@ -1517,7 +1516,7 @@ 
      Dealing with strings
      
 character array dtype under the hood when creating the netcdf compound type.
 Here's an example:
      
 
-
      >>> nc = Dataset('compoundstring_example.nc','w')
+
      >>> nc = Dataset('compoundstring_example.nc','w')
 >>> dtype = np.dtype([('observation', 'f4'),
 ...                      ('station_name','S10')])
 >>> station_data_t = nc.createCompoundType(dtype,'station_data')
@@ -1562,7 +1561,7 @@ 
      In-memory (diskless) Datasets
      
 object representing the Dataset. Below are examples illustrating both
 approaches.
      
 
-
      >>> # create a diskless (in-memory) Dataset,
+
      >>> # create a diskless (in-memory) Dataset,
 >>> # and persist the file to disk when it is closed.
 >>> nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
 >>> d = nc.createDimension('x',None)
@@ -1624,7 +1623,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -1637,7 +1636,7 @@ 
      In-memory (diskless) Datasets
      
 
                         
      
             View Source
-            
      # init for netCDF4. package
+            
      # init for netCDF4. package
 # Docstring comes from extension module _netCDF4.
 from ._netCDF4 import *
 # Need explicit imports for names beginning with underscores
@@ -1652,8 +1651,10 @@ 
      In-memory (diskless) Datasets
      
 import os
 __all__ =\
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
-# if HDF5_PLUGIN_PATH not set, point to package path if libh5noop.so exists there
-if 'HDF5_PLUGIN_PATH' not in os.environ and os.path.exists(os.path.join(__path__[0],'libh5noop.so')):
+# if HDF5_PLUGIN_PATH not set, point to package path if plugins live there
+if 'HDF5_PLUGIN_PATH' not in os.environ and\
+    (os.path.exists(os.path.join(__path__[0],'lib__nczhdf5filters.so')) or\
+    os.path.exists(os.path.join(__path__[0],'lib__nczhdf5filters.dylib'))):
     os.environ['HDF5_PLUGIN_PATH']=__path__[0]
 
      
 
@@ -1669,7 +1670,7 @@ 
      In-memory (diskless) Datasets
      
         Dataset:
     
      
 
-    
+        
             
      A netCDF Dataset is a collection of dimensions, groups, variables and
 attributes. Together they describe the meaning of data and relations among
 data fields stored in a netCDF file. See Dataset.__init__ for more
@@ -1747,7 +1748,7 @@ 
      In-memory (diskless) Datasets
      
             Dataset()
     
      
 
-    
+        
             
      __init__(self, filename, mode="r", clobber=True, diskless=False,
 persist=False, keepweakref=False, memory=None, encoding=None,
 parallel=False, comm=None, info=None, format='NETCDF4')
      
@@ -1853,7 +1854,7 @@ 
      In-memory (diskless) Datasets
      
             filepath(unknown):
     
      
 
-    
+        
             
      filepath(self,encoding=None)
      
 
 
      Get the file system path (or the opendap URL) which was used to
@@ -1872,7 +1873,7 @@ 
      In-memory (diskless) Datasets
      
             close(unknown):
     
      
 
-    
+        
             
      close(self)
      
 
 
      Close the Dataset.
      
@@ -1888,7 +1889,7 @@ 
      In-memory (diskless) Datasets
      
             isopen(unknown):
     
      
 
-    
+        
             
      isopen(self)
      
 
 
      Is the Dataset open or closed?
      
@@ -1904,7 +1905,7 @@ 
      In-memory (diskless) Datasets
      
             sync(unknown):
     
      
 
-    
+        
             
      sync(self)
      
 
 
      Writes all buffered data in the Dataset to the disk file.
      
@@ -1920,7 +1921,7 @@ 
      In-memory (diskless) Datasets
      
             set_fill_on(unknown):
     
      
 
-    
+        
             
      set_fill_on(self)
      
 
 
      Sets the fill mode for a Dataset open for writing to on.
      
@@ -1944,7 +1945,7 @@ 
      In-memory (diskless) Datasets
      
             set_fill_off(unknown):
     
      
 
-    
+        
             
      set_fill_off(self)
      
 
 
      Sets the fill mode for a Dataset open for writing to off.
      
@@ -1964,7 +1965,7 @@ 
      In-memory (diskless) Datasets
      
             createDimension(unknown):
     
      
 
-    
+        
             
      createDimension(self, dimname, size=None)
      
 
 
      Creates a new dimension with the given dimname and size.
      
@@ -1988,7 +1989,7 @@ 
      In-memory (diskless) Datasets
      
             renameDimension(unknown):
     
      
 
-    
+        
             
      renameDimension(self, oldname, newname)
      
 
 
      rename a Dimension named oldname to newname.
      
@@ -2004,7 +2005,7 @@ 
      In-memory (diskless) Datasets
      
             createCompoundType(unknown):
     
      
 
-    
+        
             
      createCompoundType(self, datatype, datatype_name)
      
 
 
      Creates a new compound data type named datatype_name from the numpy
@@ -2029,7 +2030,7 @@ 
      In-memory (diskless) Datasets
      
             createVLType(unknown):
     
      
 
-    
+        
             
      createVLType(self, datatype, datatype_name)
      
 
 
      Creates a new VLEN data type named datatype_name from a numpy
@@ -2049,7 +2050,7 @@ 
      In-memory (diskless) Datasets
      
             createEnumType(unknown):
     
      
 
-    
+        
             
      createEnumType(self, datatype, datatype_name, enum_dict)
      
 
 
      Creates a new Enum data type named datatype_name from a numpy
@@ -2070,7 +2071,7 @@ 
      In-memory (diskless) Datasets
      
             createVariable(unknown):
     
      
 
-    
+        
             
      createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False,
 complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None,
 szip_coding='nn', szip_pixels_per_block=8, blosc_shuffle=1,
@@ -2165,7 +2166,7 @@ 
      In-memory (diskless) Datasets
      
 
 
      The optional keyword fill_value can be used to override the default
 netCDF _FillValue (the value that the variable gets filled with before
-any data is written to it, defaults given in the dict netCDF4.default_fillvals).
+any data is written to it, defaults given in the dict netCDF4.default_fillvals).
 If fill_value is set to False, then the variable is not pre-filled.
      
 
 
      If the optional keyword parameters least_significant_digit or significant_digits are
@@ -2233,7 +2234,7 @@ 
      In-memory (diskless) Datasets
      
             renameVariable(unknown):
     
      
 
-    
+        
             
      renameVariable(self, oldname, newname)
      
 
 
      rename a Variable named oldname to newname
      
@@ -2249,7 +2250,7 @@ 
      In-memory (diskless) Datasets
      
             createGroup(unknown):
     
      
 
-    
+        
             
      createGroup(self, groupname)
      
 
 
      Creates a new Group with the given groupname.
      
@@ -2275,7 +2276,7 @@ 
      In-memory (diskless) Datasets
      
             ncattrs(unknown):
     
      
 
-    
+        
             
      ncattrs(self)
      
 
 
      return netCDF global attribute names for this Dataset or Group in a list.
      
@@ -2291,7 +2292,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr(unknown):
     
      
 
-    
+        
             
      setncattr(self,name,value)
      
 
 
      set a netCDF dataset or group attribute using name,value pair.
@@ -2309,7 +2310,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr_string(unknown):
     
      
 
-    
+        
             
      setncattr_string(self,name,value)
      
 
 
      set a netCDF dataset or group string attribute using name,value pair.
@@ -2327,7 +2328,7 @@ 
      In-memory (diskless) Datasets
      
             setncatts(unknown):
     
      
 
-    
+        
             
      setncatts(self,attdict)
      
 
 
      set a bunch of netCDF dataset or group attributes at once using a python dictionary.
@@ -2346,7 +2347,7 @@ 
      In-memory (diskless) Datasets
      
             getncattr(unknown):
     
      
 
-    
+        
             
      getncattr(self,name)
      
 
 
      retrieve a netCDF dataset or group attribute.
@@ -2367,7 +2368,7 @@ 
      In-memory (diskless) Datasets
      
             delncattr(unknown):
     
      
 
-    
+        
             
      delncattr(self,name,value)
      
 
 
      delete a netCDF dataset or group attribute.  Use if you need to delete a
@@ -2385,7 +2386,7 @@ 
      In-memory (diskless) Datasets
      
             renameAttribute(unknown):
     
      
 
-    
+        
             
      renameAttribute(self, oldname, newname)
      
 
 
      rename a Dataset or Group attribute named oldname to newname.
      
@@ -2401,7 +2402,7 @@ 
      In-memory (diskless) Datasets
      
             renameGroup(unknown):
     
      
 
-    
+        
             
      renameGroup(self, oldname, newname)
      
 
 
      rename a Group named oldname to newname (requires netcdf >= 4.3.1).
      
@@ -2417,7 +2418,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_chartostring(unknown):
     
      
 
-    
+        
             
      set_auto_chartostring(self, True_or_False)
      
 
 
      Call Variable.set_auto_chartostring for all variables contained in this Dataset or
@@ -2442,7 +2443,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_maskandscale(unknown):
     
      
 
-    
+        
             
      set_auto_maskandscale(self, True_or_False)
      
 
 
      Call Variable.set_auto_maskandscale for all variables contained in this Dataset or
@@ -2465,7 +2466,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_mask(unknown):
     
      
 
-    
+        
             
      set_auto_mask(self, True_or_False)
      
 
 
      Call Variable.set_auto_mask for all variables contained in this Dataset or
@@ -2489,7 +2490,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_scale(unknown):
     
      
 
-    
+        
             
      set_auto_scale(self, True_or_False)
      
 
 
      Call Variable.set_auto_scale for all variables contained in this Dataset or
@@ -2512,7 +2513,7 @@ 
      In-memory (diskless) Datasets
      
             set_always_mask(unknown):
     
      
 
-    
+        
             
      set_always_mask(self, True_or_False)
      
 
 
      Call Variable.set_always_mask for all variables contained in
@@ -2540,7 +2541,7 @@ 
      In-memory (diskless) Datasets
      
             set_ncstring_attrs(unknown):
     
      
 
-    
+        
             
      set_ncstring_attrs(self, True_or_False)
      
 
 
      Call Variable.set_ncstring_attrs for all variables contained in
@@ -2565,7 +2566,7 @@ 
      In-memory (diskless) Datasets
      
             get_variables_by_attributes(unknown):
     
      
 
-    
+        
             
      get_variables_by_attribute(self, **kwargs)
      
 
 
      Returns a list of variables that match specific conditions.
      
@@ -2573,7 +2574,7 @@ 
      In-memory (diskless) Datasets
      
 
      Can pass in key=value parameters and variables are returned that
 contain all of the matches. For example,
      
 
-
      >>> # Get variables with x-axis attribute.
+
      >>> # Get variables with x-axis attribute.
 >>> vs = nc.get_variables_by_attributes(axis='X')
 >>> # Get variables with matching "standard_name" attribute
 >>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
@@ -2584,7 +2585,7 @@ 
      In-memory (diskless) Datasets
      
 the attribute value.  None is given as the attribute value when the
 attribute does not exist on the variable. For example,
      
 
-
      >>> # Get Axis variables
+
      >>> # Get Axis variables
 >>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
 >>> # Get variables that don't have an "axis" attribute
 >>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
@@ -2603,7 +2604,7 @@ 
      In-memory (diskless) Datasets
      
             fromcdl(unknown):
     
      
 
-    
+        
             
      fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')
      
 
 
      call ncgen via subprocess to create Dataset from CDL
@@ -2633,7 +2634,7 @@ 
      In-memory (diskless) Datasets
      
             tocdl(unknown):
     
      
 
-    
+        
             
      tocdl(self, coordvars=False, data=False, outfile=None)
      
 
 
      call ncdump via subprocess to create CDL
@@ -2652,10 +2653,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        name
+        name = <attribute 'name' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
-    
             
      string name of Group instance
      
 
      
 
@@ -2664,121 +2664,109 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        groups
+        groups = <attribute 'groups' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        dimensions
+        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        variables
+        variables = <attribute 'variables' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        disk_format
+        disk_format = <attribute 'disk_format' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        path
+        path = <attribute 'path' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        parent
+        parent = <attribute 'parent' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        file_format
+        file_format = <attribute 'file_format' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        data_model
+        data_model = <attribute 'data_model' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        cmptypes
+        cmptypes = <attribute 'cmptypes' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        vltypes
+        vltypes = <attribute 'vltypes' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        enumtypes
+        enumtypes = <attribute 'enumtypes' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        keepweakref
+        keepweakref = <attribute 'keepweakref' of 'netCDF4._netCDF4.Dataset' objects>
     
      
 
     
-    
 
                             
      
                 
      • 
@@ -2791,7 +2779,7 @@ 
      In-memory (diskless) Datasets
      
         Variable:
     
      
 
-    
+        
             
      A netCDF Variable is used to read and write netCDF data.  They are
 analogous to numpy array objects. See Variable.__init__ for more
 details.
      
@@ -2875,7 +2863,7 @@ 
      In-memory (diskless) Datasets
      
             Variable()
     
      
 
-    
+        
             
      __init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False,
 complevel=4, shuffle=True, szip_coding='nn', szip_pixels_per_block=8,
 blosc_shuffle=1, fletcher32=False, contiguous=False,
@@ -2996,7 +2984,7 @@ 
      In-memory (diskless) Datasets
      
 value that the variable gets filled with before any data is written to it)
 is replaced with this value.  If fill_value is set to False, then
 the variable is not pre-filled. The default netCDF fill values can be found
-in the dictionary netCDF4.default_fillvals.
      
+in the dictionary netCDF4.default_fillvals.
      
 
 
      chunk_cache: If specified, sets the chunk cache size for this variable.
 Persists as long as Dataset is open. Use set_var_chunk_cache to
@@ -3017,7 +3005,7 @@ 
      In-memory (diskless) Datasets
      
             group(unknown):
     
      
 
-    
+        
             
      group(self)
      
 
 
      return the group that this Variable is a member of.
      
@@ -3033,7 +3021,7 @@ 
      In-memory (diskless) Datasets
      
             ncattrs(unknown):
     
      
 
-    
+        
             
      ncattrs(self)
      
 
 
      return netCDF attribute names for this Variable in a list.
      
@@ -3049,7 +3037,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr(unknown):
     
      
 
-    
+        
             
      setncattr(self,name,value)
      
 
 
      set a netCDF variable attribute using name,value pair.  Use if you need to set a
@@ -3067,7 +3055,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr_string(unknown):
     
      
 
-    
+        
             
      setncattr_string(self,name,value)
      
 
 
      set a netCDF variable string attribute using name,value pair.
@@ -3086,7 +3074,7 @@ 
      In-memory (diskless) Datasets
      
             setncatts(unknown):
     
      
 
-    
+        
             
      setncatts(self,attdict)
      
 
 
      set a bunch of netCDF variable attributes at once using a python dictionary.
@@ -3105,7 +3093,7 @@ 
      In-memory (diskless) Datasets
      
             getncattr(unknown):
     
      
 
-    
+        
             
      getncattr(self,name)
      
 
 
      retrieve a netCDF variable attribute.  Use if you need to set a
@@ -3126,7 +3114,7 @@ 
      In-memory (diskless) Datasets
      
             delncattr(unknown):
     
      
 
-    
+        
             
      delncattr(self,name,value)
      
 
 
      delete a netCDF variable attribute.  Use if you need to delete a
@@ -3144,7 +3132,7 @@ 
      In-memory (diskless) Datasets
      
             filters(unknown):
     
      
 
-    
+        
             
      filters(self)
      
 
 
      return dictionary containing HDF5 filter parameters.
      
@@ -3160,7 +3148,7 @@ 
      In-memory (diskless) Datasets
      
             quantization(unknown):
     
      
 
-    
+        
             
      quantization(self)
      
 
 
      return number of significant digits and the algorithm used in quantization.
@@ -3177,7 +3165,7 @@ 
      In-memory (diskless) Datasets
      
             endian(unknown):
     
      
 
-    
+        
             
      endian(self)
      
 
 
      return endian-ness (little,big,native) of variable (as stored in HDF5 file).
      
@@ -3193,7 +3181,7 @@ 
      In-memory (diskless) Datasets
      
             chunking(unknown):
     
      
 
-    
+        
             
      chunking(self)
      
 
 
      return variable chunking information.  If the dataset is
@@ -3212,7 +3200,7 @@ 
      In-memory (diskless) Datasets
      
             get_var_chunk_cache(unknown):
     
      
 
-    
+        
             
      get_var_chunk_cache(self)
      
 
 
      return variable chunk cache information in a tuple (size,nelems,preemption).
@@ -3230,7 +3218,7 @@ 
      In-memory (diskless) Datasets
      
             set_var_chunk_cache(unknown):
     
      
 
-    
+        
             
      set_var_chunk_cache(self,size=None,nelems=None,preemption=None)
      
 
 
      change variable chunk cache settings.
@@ -3248,7 +3236,7 @@ 
      In-memory (diskless) Datasets
      
             renameAttribute(unknown):
     
      
 
-    
+        
             
      renameAttribute(self, oldname, newname)
      
 
 
      rename a Variable attribute named oldname to newname.
      
@@ -3264,7 +3252,7 @@ 
      In-memory (diskless) Datasets
      
             assignValue(unknown):
     
      
 
-    
+        
             
      assignValue(self, val)
      
 
 
      assign a value to a scalar variable.  Provided for compatibility with
@@ -3281,7 +3269,7 @@ 
      In-memory (diskless) Datasets
      
             getValue(unknown):
     
      
 
-    
+        
             
      getValue(self)
      
 
 
      get the value of a scalar variable.  Provided for compatibility with
@@ -3298,7 +3286,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_chartostring(unknown):
     
      
 
-    
+        
             
      set_auto_chartostring(self,chartostring)
      
 
 
      turn on or off automatic conversion of character variable data to and
@@ -3329,7 +3317,7 @@ 
      In-memory (diskless) Datasets
      
             use_nc_get_vars(unknown):
     
      
 
-    
+        
             
      use_nc_get_vars(self,_use_get_vars)
      
 
 
      enable the use of netcdf library routine nc_get_vars
@@ -3349,7 +3337,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_maskandscale(unknown):
     
      
 
-    
+        
             
      set_auto_maskandscale(self,maskandscale)
      
 
 
      turn on or off automatic conversion of variable data to and
@@ -3413,7 +3401,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_scale(unknown):
     
      
 
-    
+        
             
      set_auto_scale(self,scale)
      
 
 
      turn on or off automatic packing/unpacking of variable
@@ -3462,7 +3450,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_mask(unknown):
     
      
 
-    
+        
             
      set_auto_mask(self,mask)
      
 
 
      turn on or off automatic conversion of variable data to and
@@ -3497,7 +3485,7 @@ 
      In-memory (diskless) Datasets
      
             set_always_mask(unknown):
     
      
 
-    
+        
             
      set_always_mask(self,always_mask)
      
 
 
      turn on or off conversion of data without missing values to regular
@@ -3520,7 +3508,7 @@ 
      In-memory (diskless) Datasets
      
             set_ncstring_attrs(unknown):
     
      
 
-    
+        
             
      set_always_mask(self,ncstring_attrs)
      
 
 
      turn on or off creating NC_STRING string attributes.
      
@@ -3542,7 +3530,7 @@ 
      In-memory (diskless) Datasets
      
             set_collective(unknown):
     
      
 
-    
+        
             
      set_collective(self,True_or_False)
      
 
 
      turn on or off collective parallel IO access. Ignored if file is not
@@ -3559,7 +3547,7 @@ 
      In-memory (diskless) Datasets
      
             get_dims(unknown):
     
      
 
-    
+        
             
      get_dims(self)
      
 
 
      return a tuple of Dimension instances associated with this
@@ -3571,10 +3559,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        name
+        name = <attribute 'name' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
-    
             
      string name of Variable instance
      
 
      
 
@@ -3583,10 +3570,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        datatype
+        datatype = <attribute 'datatype' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
-    
             
      numpy data type (for primitive data types) or
 VLType/CompoundType/EnumType instance 
 (for compound, vlen  or enum data types)
      
@@ -3597,10 +3583,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        shape
+        shape = <attribute 'shape' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
-    
             
      find current sizes of all variable dimensions
      
 
      
 
@@ -3609,10 +3594,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        size
+        size = <attribute 'size' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
-    
             
      Return the number of stored elements.
      
 
      
 
@@ -3621,10 +3605,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        dimensions
+        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
-    
             
      get variables's dimension names
      
 
      
 
@@ -3633,61 +3616,55 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        ndim
+        ndim = <attribute 'ndim' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        dtype
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        mask
+        mask = <attribute 'mask' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        scale
+        scale = <attribute 'scale' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        always_mask
+        always_mask = <attribute 'always_mask' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        chartostring
+        chartostring = <attribute 'chartostring' of 'netCDF4._netCDF4.Variable' objects>
     
      
 
     
-    
 
                             
      
                 
@@ -3700,7 +3677,7 @@ 
      In-memory (diskless) Datasets
      
         Dimension:
     
      
 
-    
+        
             
      A netCDF Dimension is used to describe the coordinates of a Variable.
 See Dimension.__init__ for more details.
      
 
@@ -3726,7 +3703,7 @@ 
      In-memory (diskless) Datasets
      
             Dimension()
     
      
 
-    
+        
             
      __init__(self, group, name, size=None)
      
 
 
      Dimension constructor.
      
@@ -3752,7 +3729,7 @@ 
      In-memory (diskless) Datasets
      
             group(unknown):
     
      
 
-    
+        
             
      group(self)
      
 
 
      return the group that this Dimension is a member of.
      
@@ -3768,7 +3745,7 @@ 
      In-memory (diskless) Datasets
      
             isunlimited(unknown):
     
      
 
-    
+        
             
      isunlimited(self)
      
 
 
      returns True if the Dimension instance is unlimited, False otherwise.
      
@@ -3779,10 +3756,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        name
+        name = <attribute 'name' of 'netCDF4._netCDF4.Dimension' objects>
     
      
 
-    
             
      string name of Dimension instance
      
 
      
 
@@ -3791,10 +3767,9 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        size
+        size = <attribute 'size' of 'netCDF4._netCDF4.Dimension' objects>
     
      
 
-    
             
      current size of Dimension (calls len on Dimension instance)
      
 
      
 
@@ -3810,7 +3785,7 @@ 
      In-memory (diskless) Datasets
      
         Group(netCDF4.Dataset):
     
      
 
-    
+        
             
      Groups define a hierarchical namespace within a netCDF file. They are
 analogous to directories in a unix filesystem. Each Group behaves like
 a Dataset within a Dataset, and can contain it's own variables,
@@ -3834,7 +3809,7 @@ 
      In-memory (diskless) Datasets
      
             Group()
     
      
 
-    
+        
             
      __init__(self, parent, name)
 Group constructor.
      
 
@@ -3858,7 +3833,7 @@ 
      In-memory (diskless) Datasets
      
             close(unknown):
     
      
 
-    
+        
             
      close(self)
      
 
 
      overrides Dataset close method which does not apply to Group
@@ -3928,7 +3903,7 @@ 
      Inherited Members
      
         MFDataset(netCDF4.Dataset):
     
      
 
-    
+        
             
      Class for reading multi-file netCDF Datasets, making variables
 spanning multiple files appear as if they were in one file.
 Datasets must be in NETCDF4_CLASSIC, NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET
@@ -3938,7 +3913,7 @@ 
      Inherited Members
      
 
 
      Example usage (See MFDataset.__init__ for more details):
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> # create a series of netCDF files with a variable sharing
 >>> # the same unlimited dimension.
 >>> for nf in range(10):
@@ -3965,7 +3940,7 @@ 
      Inherited Members
      
             MFDataset(files, check=False, aggdim=None, exclude=[], master_file=None)
     
      
 
-    
+        
             
      __init__(self, files, check=False, aggdim=None, exclude=[],
 master_file=None)
      
 
@@ -4010,7 +3985,7 @@ 
      Inherited Members
      
             ncattrs(self):
     
      
 
-    
+        
             
      ncattrs(self)
      
 
 
      return the netcdf attribute names from the master file.
      
@@ -4026,7 +4001,7 @@ 
      Inherited Members
      
             close(self):
     
      
 
-    
+        
             
      close(self)
      
 
 
      close all the open files.
      
@@ -4094,13 +4069,13 @@ 
      Inherited Members
      
         MFTime(netCDF4._netCDF4._Variable):
     
      
 
-    
+        
             
      Class providing an interface to a MFDataset time Variable by imposing a unique common
 time unit and/or calendar to all files.
      
 
 
      Example usage (See MFTime.__init__ for more details):
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> f1 = Dataset("mftest_1.nc","w", format="NETCDF4_CLASSIC")
 >>> f2 = Dataset("mftest_2.nc","w", format="NETCDF4_CLASSIC")
 >>> f1.createDimension("time",None)
@@ -4136,7 +4111,7 @@ 
      Inherited Members
      
             MFTime(time, units=None, calendar=None)
     
      
 
-    
+        
             
      __init__(self, time, units=None, calendar=None)
      
 
 
      Create a time Variable with units consistent across a multifile
@@ -4180,7 +4155,7 @@ 
      Inherited Members
      
         CompoundType:
     
      
 
-    
+        
             
      A CompoundType instance is used to describe a compound data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance.
@@ -4199,7 +4174,7 @@ 
      Inherited Members
      
             CompoundType()
     
      
 
-    
+        
             
      __init__(group, datatype, datatype_name)
      
 
 
      CompoundType constructor.
      
@@ -4228,31 +4203,28 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.CompoundType' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        dtype_view
+        dtype_view = <attribute 'dtype_view' of 'netCDF4._netCDF4.CompoundType' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        name
+        name = <attribute 'name' of 'netCDF4._netCDF4.CompoundType' objects>
     
      
 
     
-    
 
                             
      
                 
@@ -4265,7 +4237,7 @@ 
      Inherited Members
      
         VLType:
     
      
 
-    
+        
             
      A VLType instance is used to describe a variable length (VLEN) data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance. See
@@ -4283,7 +4255,7 @@ 
      Inherited Members
      
             VLType()
     
      
 
-    
+        
             
      __init__(group, datatype, datatype_name)
      
 
 
      VLType constructor.
      
@@ -4306,21 +4278,19 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.VLType' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        name
+        name = <attribute 'name' of 'netCDF4._netCDF4.VLType' objects>
     
      
 
     
-    
 
                             
      
                 
@@ -4332,7 +4302,7 @@ 
      Inherited Members
      
             date2num(unknown):
     
      
 
-    
+        
             
      date2num(dates, units, calendar=None, has_year_zero=None)
      
 
 
      Return numeric time values given datetime objects. The units
@@ -4392,7 +4362,7 @@ 
      Inherited Members
      
             num2date(unknown):
     
      
 
-    
+        
             
      num2date(times, units, calendar=u'standard', only_use_cftime_datetimes=True, only_use_python_datetimes=False, has_year_zero=None)
      
 
 
      Return datetime objects given numeric time values. The units
@@ -4464,7 +4434,7 @@ 
      Inherited Members
      
             date2index(unknown):
     
      
 
-    
+        
             
      date2index(dates, nctime, calendar=None, select=u'exact', has_year_zero=None)
      
 
 
      Return indices of a netCDF time variable corresponding to the given dates.
      
@@ -4518,7 +4488,7 @@ 
      Inherited Members
      
             stringtochar(unknown):
     
      
 
-    
+        
             
      stringtochar(a,encoding='utf-8')
      
 
 
      convert a string array to a character array with one extra dimension
      
@@ -4545,7 +4515,7 @@ 
      Inherited Members
      
             chartostring(unknown):
     
      
 
-    
+        
             
      chartostring(b,encoding='utf-8')
      
 
 
      convert a character array to a string array with one less dimension.
      
@@ -4572,7 +4542,7 @@ 
      Inherited Members
      
             stringtoarr(unknown):
     
      
 
-    
+        
             
      stringtoarr(a, NUMCHARS,dtype='S')
      
 
 
      convert a string to a character array of length NUMCHARS
      
@@ -4600,7 +4570,7 @@ 
      Inherited Members
      
             getlibversion(unknown):
     
      
 
-    
+        
             
      getlibversion()
      
 
 
      returns a string describing the version of the netcdf library
@@ -4618,7 +4588,7 @@ 
      Inherited Members
      
         EnumType:
     
      
 
-    
+        
             
      A EnumType instance is used to describe an Enum data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance. See
@@ -4636,7 +4606,7 @@ 
      Inherited Members
      
             EnumType()
     
      
 
-    
+        
             
      __init__(group, datatype, datatype_name, enum_dict)
      
 
 
      EnumType constructor.
      
@@ -4662,31 +4632,28 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype
+        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.EnumType' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        name
+        name = <attribute 'name' of 'netCDF4._netCDF4.EnumType' objects>
     
      
 
     
-    
 
                             
      
                             
      
                                             
      #  
 
-        enum_dict
+        enum_dict = <attribute 'enum_dict' of 'netCDF4._netCDF4.EnumType' objects>
     
      
 
     
-    
 
                             
      
                 
@@ -4698,7 +4665,7 @@ 
      Inherited Members
      
             get_chunk_cache(unknown):
     
      
 
-    
+        
             
      get_chunk_cache()
      
 
 
      return current netCDF chunk cache information in a tuple (size,nelems,preemption).
@@ -4716,7 +4683,7 @@ 
      Inherited Members
      
             set_chunk_cache(unknown):
     
      
 
-    
+        
             
      set_chunk_cache(self,size=None,nelems=None,preemption=None)
      
 
 
      change netCDF4 chunk cache settings.

From c23287b44b5de2071ff031928361200ff21b9474 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 27 Jun 2022 08:59:11 -0600
Subject: [PATCH 0851/1504] use inq_filter_avail to check if filters are usable

---
 include/netCDF4.pxi      |  6 ++++++
 src/netCDF4/_netCDF4.pyx | 12 ++++++++++++
 2 files changed, 18 insertions(+)

diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index 8be538234..ba0190551 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -698,9 +698,13 @@ IF HAS_QUANTIZATION_SUPPORT:
             NC_QUANTIZE_BITROUND
         int nc_def_var_quantize(int ncid, int varid, int quantize_mode, int nsd) 
         int nc_inq_var_quantize(int ncid, int varid, int *quantize_modep, int *nsdp) nogil
+    cdef extern from "netcdf_filter.h":
+        int nc_inq_filter_avail(int ncid, unsigned filterid);
 
 IF HAS_SZIP_SUPPORT:
     cdef extern from "netcdf.h":
+        cdef enum:
+            H5Z_FILTER_SZIP
         int nc_def_var_quantize(int ncid, int varid, int quantize_mode, int nsd) 
         int nc_inq_var_quantize(int ncid, int varid, int *quantize_modep, int *nsdp) nogil
         int nc_def_var_szip(int ncid, int varid, int options_mask, int pixels_per_bloc)
@@ -723,6 +727,8 @@ IF HAS_BZIP2_SUPPORT:
 
 IF HAS_BLOSC_SUPPORT:
     cdef extern from "netcdf_filter.h":
+        cdef enum:
+            H5Z_FILTER_BLOSC
         int nc_def_var_blosc(int ncid, int varid, unsigned subcompressor, unsigned level, unsigned blocksize, unsigned addshuffle)
         int nc_inq_var_blosc(int ncid, int varid, int* hasfilterp, unsigned* subcompressorp, unsigned* levelp, unsigned* blocksizep, unsigned* addshufflep)
 
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 8a006f457..c782456a5 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1446,6 +1446,18 @@ _nctonptype[NC_CHAR]='S1'
 
 # internal C functions.
 
+def has_blasc_filter():
+    """check to see if blosc compression filter is available"""
+    cdef int ierr
+    IF HAS_BLOSC_SUPPORT:
+        ierr = nc_inq_filter_avail(0, H5Z_FILTER_BLOSC)
+        if ierr:
+            return False
+        else:
+            return True
+    ELSE:
+        return False
+
 cdef _get_att_names(int grpid, int varid):
     # Private function to get all the attribute names in a group
     cdef int ierr, numatts, n

From 0142a367ee34078c66aa23d41544a2c5c6fc0148 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 27 Jun 2022 09:48:25 -0600
Subject: [PATCH 0852/1504] add Dataset methods to check for available of
 blosc,zstd,bzip2 and szip

---
 include/netCDF4.pxi      |  2 +-
 src/netCDF4/_netCDF4.pyx | 64 ++++++++++++++++++++++++++++++++--------
 2 files changed, 53 insertions(+), 13 deletions(-)

diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index ba0190551..6c27cd246 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -713,7 +713,7 @@ IF HAS_SZIP_SUPPORT:
 IF HAS_ZSTANDARD_SUPPORT:
     cdef extern from "netcdf_filter.h":
         cdef enum:
-            H5Z_FILTER_ZSTANDARD
+            H5Z_FILTER_ZSTD
         int nc_def_var_zstandard(int ncid, int varid, int level)
         int nc_inq_var_zstandard(int ncid, int varid, int* hasfilterp, int *levelp)
         int nc_inq_filter_avail(int ncid, unsigned id)
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index c782456a5..07c7a0d29 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1446,18 +1446,6 @@ _nctonptype[NC_CHAR]='S1'
 
 # internal C functions.
 
-def has_blasc_filter():
-    """check to see if blosc compression filter is available"""
-    cdef int ierr
-    IF HAS_BLOSC_SUPPORT:
-        ierr = nc_inq_filter_avail(0, H5Z_FILTER_BLOSC)
-        if ierr:
-            return False
-        else:
-            return True
-    ELSE:
-        return False
-
 cdef _get_att_names(int grpid, int varid):
     # Private function to get all the attribute names in a group
     cdef int ierr, numatts, n
@@ -3373,6 +3361,58 @@ to be installed and in `$PATH`.
             f = open(outfile,'w')
             f.write(result.stdout)
             f.close()
+    def has_blosc_filter(self):
+        """
+**`has_blosc_filter(self)`**
+returns True if blosc compression filter is available"""
+        cdef int ierr
+        IF HAS_BLOSC_SUPPORT:
+            ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_BLOSC)
+            if ierr:
+                return False
+            else:
+                return True
+        ELSE:
+            return False
+    def has_zstd_filter(self):
+        """
+**`has_zstd_filter(self)`**
+returns True if zstd compression filter is available"""
+        cdef int ierr
+        IF HAS_ZSTANDARD_SUPPORT:
+            ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_ZSTD)
+            if ierr:
+                return False
+            else:
+                return True
+        ELSE:
+            return False
+    def has_bzip2_filter(self):
+        """
+**`has_bzip2_filter(self)`**
+returns True if bzip2 compression filter is available"""
+        cdef int ierr
+        IF HAS_BZIP2_SUPPORT:
+            ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_BZIP2)
+            if ierr:
+                return False
+            else:
+                return True
+        ELSE:
+            return False
+    def has_szip_filter(self):
+        """
+**`has_szip_filter(self)`**
+returns True if szip compression filter is available"""
+        cdef int ierr
+        IF HAS_SZIP_SUPPORT:
+            ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_SZIP)
+            if ierr:
+                return False
+            else:
+                return True
+        ELSE:
+            return False
 
 cdef class Group(Dataset):
     """

From 787e252d16e1eeda4df3c354bb11315b29713a7a Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 27 Jun 2022 09:52:38 -0600
Subject: [PATCH 0853/1504] skip blosc tests if filter not available

---
 test/tst_compression_blosc.py | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/test/tst_compression_blosc.py b/test/tst_compression_blosc.py
index da31d3ce1..3f799c8b7 100644
--- a/test/tst_compression_blosc.py
+++ b/test/tst_compression_blosc.py
@@ -74,4 +74,9 @@ def runTest(self):
         f.close()
 
 if __name__ == '__main__':
-    unittest.main()
+    nc = Dataset(filename,'w')
+    if not nc.has_blosc_filter():
+        sys.stdout.write('blosc filter not available, skipping tests ...\n')
+    else:
+        nc.close()
+        unittest.main()

From f308cda7a1d51ebd72e60cf4dd078226e37b8cca Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 27 Jun 2022 12:23:57 -0600
Subject: [PATCH 0854/1504] skip tests if filters not available

---
 test/tst_compression_bzip2.py | 7 ++++++-
 test/tst_compression_szip.py  | 7 ++++++-
 test/tst_compression_zstd.py  | 7 ++++++-
 3 files changed, 18 insertions(+), 3 deletions(-)

diff --git a/test/tst_compression_bzip2.py b/test/tst_compression_bzip2.py
index 89de4086c..732e18da3 100644
--- a/test/tst_compression_bzip2.py
+++ b/test/tst_compression_bzip2.py
@@ -49,4 +49,9 @@ def runTest(self):
         f.close()
 
 if __name__ == '__main__':
-    unittest.main()
+    nc = Dataset(filename1,'w')
+    if not nc.has_bzip2_filter():
+        sys.stdout.write('bzip2 filter not available, skipping tests ...\n')
+    else:
+        nc.close()
+        unittest.main()
diff --git a/test/tst_compression_szip.py b/test/tst_compression_szip.py
index 874ed3821..bac2bce8e 100644
--- a/test/tst_compression_szip.py
+++ b/test/tst_compression_szip.py
@@ -39,4 +39,9 @@ def runTest(self):
         f.close()
 
 if __name__ == '__main__':
-    unittest.main()
+    nc = Dataset(filename,'w')
+    if not nc.has_szip_filter():
+        sys.stdout.write('szip filter not available, skipping tests ...\n')
+    else:
+        nc.close()
+        unittest.main()
diff --git a/test/tst_compression_zstd.py b/test/tst_compression_zstd.py
index 2745e03ba..992928a44 100644
--- a/test/tst_compression_zstd.py
+++ b/test/tst_compression_zstd.py
@@ -49,4 +49,9 @@ def runTest(self):
         f.close()
 
 if __name__ == '__main__':
-    unittest.main()
+    nc = Dataset(filename1,'w')
+    if not nc.has_zstd_filter():
+        sys.stdout.write('blosc filter not available, skipping tests ...\n')
+    else:
+        nc.close()
+        unittest.main()

From 1010b05d389838acb7cda1ac7f708e4837b90d3c Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 27 Jun 2022 12:28:10 -0600
Subject: [PATCH 0855/1504] don't install plugins to see if tests are skipped

---
 .github/workflows/build.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 11e218157..28e36a134 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -61,7 +61,7 @@ jobs:
     - name: Install netcdf4-python
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
-        export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c-${NETCDF_VERSION}/plugins/plugindir
+        #export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c-${NETCDF_VERSION}/plugins/plugindir
         python setup.py install
     - name: Test
       run: |

From fe0cec0f0fa5b8509936855da5210609ea873848 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 27 Jun 2022 14:28:30 -0600
Subject: [PATCH 0856/1504] fix import

---
 test/tst_compression_blosc.py | 2 +-
 test/tst_compression_bzip2.py | 2 +-
 test/tst_compression_szip.py  | 2 +-
 test/tst_compression_zstd.py  | 2 +-
 4 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/test/tst_compression_blosc.py b/test/tst_compression_blosc.py
index 3f799c8b7..5b45c1857 100644
--- a/test/tst_compression_blosc.py
+++ b/test/tst_compression_blosc.py
@@ -1,7 +1,7 @@
 from numpy.random.mtrand import uniform
 from netCDF4 import Dataset
 from numpy.testing import assert_almost_equal
-import os, tempfile, unittest
+import os, tempfile, unittest, sys
 
 ndim = 100000
 iblosc_shuffle=2
diff --git a/test/tst_compression_bzip2.py b/test/tst_compression_bzip2.py
index 732e18da3..22149b60e 100644
--- a/test/tst_compression_bzip2.py
+++ b/test/tst_compression_bzip2.py
@@ -1,7 +1,7 @@
 from numpy.random.mtrand import uniform
 from netCDF4 import Dataset
 from numpy.testing import assert_almost_equal
-import os, tempfile, unittest
+import os, tempfile, unittest, sys
 
 ndim = 100000
 filename1 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
diff --git a/test/tst_compression_szip.py b/test/tst_compression_szip.py
index bac2bce8e..3dc3cb8db 100644
--- a/test/tst_compression_szip.py
+++ b/test/tst_compression_szip.py
@@ -1,7 +1,7 @@
 from numpy.random.mtrand import uniform
 from netCDF4 import Dataset
 from numpy.testing import assert_almost_equal
-import os, tempfile, unittest
+import os, tempfile, unittest, sys
 
 ndim = 100000
 filename = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
diff --git a/test/tst_compression_zstd.py b/test/tst_compression_zstd.py
index 992928a44..0e14436e6 100644
--- a/test/tst_compression_zstd.py
+++ b/test/tst_compression_zstd.py
@@ -1,7 +1,7 @@
 from numpy.random.mtrand import uniform
 from netCDF4 import Dataset
 from numpy.testing import assert_almost_equal
-import os, tempfile, unittest
+import os, tempfile, unittest, sys
 
 ndim = 100000
 filename1 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name

From 4052bde62fc5f438fc446f585a543772f5abcc3e Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 27 Jun 2022 16:08:36 -0600
Subject: [PATCH 0857/1504] re-enable plugin install

---
 .github/workflows/build.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 28e36a134..11e218157 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -61,7 +61,7 @@ jobs:
     - name: Install netcdf4-python
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
-        #export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c-${NETCDF_VERSION}/plugins/plugindir
+        export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c-${NETCDF_VERSION}/plugins/plugindir
         python setup.py install
     - name: Test
       run: |

From 5c58e70f8467e2c0c3a3c8fe4cc206ac6529b66d Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 27 Jun 2022 16:56:51 -0600
Subject: [PATCH 0858/1504] update

---
 .github/workflows/build_master.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 00b3a52d4..4b1490bda 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -50,7 +50,7 @@ jobs:
     - name: Install netcdf4-python
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
-        export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c/plugins/plugindir
+        #export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c/plugins/plugindir
         python setup.py install
     - name: Test
       run: |

From 3d6785188b9cb84b071c9c8002a2cb38db7abd31 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 27 Jun 2022 18:18:21 -0600
Subject: [PATCH 0859/1504] update

---
 .github/workflows/build_master.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 4b1490bda..00b3a52d4 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -50,7 +50,7 @@ jobs:
     - name: Install netcdf4-python
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
-        #export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c/plugins/plugindir
+        export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c/plugins/plugindir
         python setup.py install
     - name: Test
       run: |

From ec63a60d946600ec360935e86ae2cf43073810df Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 27 Jun 2022 18:30:40 -0600
Subject: [PATCH 0860/1504] update

---
 test/run_all.py              | 16 ++++++++++------
 test/tst_compression_zstd.py |  2 +-
 2 files changed, 11 insertions(+), 7 deletions(-)

diff --git a/test/run_all.py b/test/run_all.py
index 1dfb5309a..f2ff97a18 100755
--- a/test/run_all.py
+++ b/test/run_all.py
@@ -1,5 +1,5 @@
-import glob, os, sys, unittest, struct
-from netCDF4 import getlibversion,__hdf5libversion__,__netcdf4libversion__,__version__
+import glob, os, sys, unittest, struct, tempfile
+from netCDF4 import getlibversion,__hdf5libversion__,__netcdf4libversion__,__version__, Dataset
 from netCDF4 import __has_cdf5_format__, __has_nc_inq_path__, __has_nc_create_mem__, \
                     __has_parallel4_support__, __has_pnetcdf_support__, \
                     __has_zstandard_support__, __has_bzip2_support__, \
@@ -26,18 +26,22 @@
 if not __has_quantization_support__:
     test_files.remove('tst_compression_quant.py')
     sys.stdout.write('not running tst_compression_quant.py ...\n')
-if not __has_zstandard_support__ or os.getenv('NO_PLUGINS'):
+filename = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
+nc = Dataset(filename,'w')
+if not __has_zstandard_support__ or os.getenv('NO_PLUGINS') or not nc.has_zstd_filter():
     test_files.remove('tst_compression_zstd.py')
     sys.stdout.write('not running tst_compression_zstd.py ...\n')
-if not __has_bzip2_support__ or os.getenv('NO_PLUGINS'):
+if not __has_bzip2_support__ or os.getenv('NO_PLUGINS') or not nc.has_bzip2_filter():
     test_files.remove('tst_compression_bzip2.py')
     sys.stdout.write('not running tst_compression_bzip2.py ...\n')
-if not __has_blosc_support__ or os.getenv('NO_PLUGINS'):
+if not __has_blosc_support__ or os.getenv('NO_PLUGINS') or not nc.has_blosc_filter():
     test_files.remove('tst_compression_blosc.py')
     sys.stdout.write('not running tst_compression_blosc.py ...\n')
-if not __has_szip_support__:
+if not __has_szip_support__ or not nc.has_szip_filter():
     test_files.remove('tst_compression_szip.py')
     sys.stdout.write('not running tst_compression_szip.py ...\n')
+nc.close()
+os.remove(filename)
 
 # Don't run tests that require network connectivity
 if os.getenv('NO_NET'):
diff --git a/test/tst_compression_zstd.py b/test/tst_compression_zstd.py
index 0e14436e6..1971dbfa6 100644
--- a/test/tst_compression_zstd.py
+++ b/test/tst_compression_zstd.py
@@ -51,7 +51,7 @@ def runTest(self):
 if __name__ == '__main__':
     nc = Dataset(filename1,'w')
     if not nc.has_zstd_filter():
-        sys.stdout.write('blosc filter not available, skipping tests ...\n')
+        sys.stdout.write('zstd filter not available, skipping tests ...\n')
     else:
         nc.close()
         unittest.main()

From 561c16bcc877cc3bd9759cd1ce06d9ad031b3c85 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 27 Jun 2022 18:44:31 -0600
Subject: [PATCH 0861/1504] test skipping plugin tests

---
 .github/workflows/build_master.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 00b3a52d4..4b1490bda 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -50,7 +50,7 @@ jobs:
     - name: Install netcdf4-python
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
-        export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c/plugins/plugindir
+        #export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c/plugins/plugindir
         python setup.py install
     - name: Test
       run: |

From c7e46cbacfe11ac61abddc09cdd0ab630b26f997 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 27 Jun 2022 18:46:52 -0600
Subject: [PATCH 0862/1504] update

---
 Changelog | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/Changelog b/Changelog
index 08d7e2cfd..2c673e30e 100644
--- a/Changelog
+++ b/Changelog
@@ -1,3 +1,8 @@
+ since version 1.6.0 release
+==============================
+ * add Dataset methods has__filter (where =zstd,blosc,bzip2,szip)
+ to check for availability of extra compression filters.
+
  version 1.6.0 (tag v1.6.0rel)
 ==============================
  * add support for new quantization functionality in netcdf-c 4.9.0 via "signficant_digits"

From e117f851365f4465a6ab459d338ccb25c1deaddb Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 27 Jun 2022 18:53:19 -0600
Subject: [PATCH 0863/1504] revert

---
 .github/workflows/build_master.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 4b1490bda..00b3a52d4 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -50,7 +50,7 @@ jobs:
     - name: Install netcdf4-python
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
-        #export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c/plugins/plugindir
+        export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c/plugins/plugindir
         python setup.py install
     - name: Test
       run: |

From d596294aea454531825922daf729df8ad8e3d24a Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 8 Aug 2022 20:29:50 -0600
Subject: [PATCH 0864/1504] add nogil to all c lib calls

---
 include/netCDF4.pxi      | 122 +++++------
 src/netCDF4/_netCDF4.pyx | 456 +++++++++++++++++++++++++--------------
 2 files changed, 360 insertions(+), 218 deletions(-)

diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index 6c27cd246..97e18c963 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -218,9 +218,9 @@ cdef extern from "netcdf.h":
         NC_ENDIAN_BIG 
     const_char_ptr *nc_inq_libvers() nogil
     const_char_ptr *nc_strerror(int ncerr)
-    int nc_create(char *path, int cmode, int *ncidp)
+    int nc_create(char *path, int cmode, int *ncidp) nogil
     int nc__create(char *path, int cmode, size_t initialsz, size_t *chunksizehintp, int *ncidp)
-    int nc_open(char *path, int mode, int *ncidp)
+    int nc_open(char *path, int mode, int *ncidp) nogil
     int nc__open(char *path, int mode, size_t *chunksizehintp, int *ncidp)
     int nc_inq_path(int ncid, size_t *pathlen, char *path) nogil
     int nc_inq_format_extended(int ncid, int *formatp, int* modep) nogil
@@ -230,13 +230,13 @@ cdef extern from "netcdf.h":
     int nc_inq_grp_parent(int ncid, int *parent_ncid) nogil
     int nc_inq_varids(int ncid, int *nvars, int *varids) nogil
     int nc_inq_dimids(int ncid, int *ndims, int *dimids, int include_parents) nogil
-    int nc_def_grp(int parent_ncid, char *name, int *new_ncid)
-    int nc_def_compound(int ncid, size_t size, char *name, nc_type *typeidp)
+    int nc_def_grp(int parent_ncid, char *name, int *new_ncid) nogil
+    int nc_def_compound(int ncid, size_t size, char *name, nc_type *typeidp) nogil
     int nc_insert_compound(int ncid, nc_type xtype, char *name, 
-                   size_t offset, nc_type field_typeid)
+                   size_t offset, nc_type field_typeid) nogil
     int nc_insert_array_compound(int ncid, nc_type xtype, char *name, 
                          size_t offset, nc_type field_typeid,
-                         int ndims, int *dim_sizes)
+                         int ndims, int *dim_sizes) nogil
     int nc_inq_type(int ncid, nc_type xtype, char *name, size_t *size) nogil
     int nc_inq_compound(int ncid, nc_type xtype, char *name, size_t *size, 
                 size_t *nfieldsp) nogil
@@ -258,14 +258,14 @@ cdef extern from "netcdf.h":
                            int *ndimsp) nogil
     int nc_inq_compound_fielddim_sizes(int ncid, nc_type xtype, int fieldid, 
                                int *dim_sizes) nogil
-    int nc_def_vlen(int ncid, char *name, nc_type base_typeid, nc_type *xtypep)
+    int nc_def_vlen(int ncid, char *name, nc_type base_typeid, nc_type *xtypep) nogil
     int nc_inq_vlen(int ncid, nc_type xtype, char *name, size_t *datum_sizep, 
             nc_type *base_nc_typep) nogil
     int nc_inq_user_type(int ncid, nc_type xtype, char *name, size_t *size, 
                      nc_type *base_nc_typep, size_t *nfieldsp, int *classp) nogil
     int nc_inq_typeids(int ncid, int *ntypes, int *typeids) nogil
     int nc_put_att(int ncid, int varid, char *name, nc_type xtype, 
-               size_t len, void *op)
+               size_t len, void *op) nogil
     int nc_get_att(int ncid, int varid, char *name, void *ip) nogil
     int nc_get_att_string(int ncid, int varid, char *name, char **ip) nogil
     int nc_put_att_string(int ncid, int varid, char *name, size_t len, char **op) nogil
@@ -284,12 +284,12 @@ cdef extern from "netcdf.h":
     int nc_get_var1(int ncid, int varid,  size_t *indexp,
                 void *ip)
     int nc_put_vara(int ncid, int varid,  size_t *startp, 
-                size_t *countp, void *op) 
+                size_t *countp, void *op) nogil
     int nc_get_vara(int ncid, int varid,  size_t *startp, 
                 size_t *countp, void *ip) nogil
     int nc_put_vars(int ncid, int varid,  size_t *startp, 
                 size_t *countp, ptrdiff_t *stridep,
-                void *op) 
+                void *op)  nogil
     int nc_get_vars(int ncid, int varid,  size_t *startp, 
                 size_t *countp, ptrdiff_t *stridep,
                 void *ip) nogil
@@ -302,39 +302,39 @@ cdef extern from "netcdf.h":
     int nc_put_var(int ncid, int varid,  void *op)
     int nc_get_var(int ncid, int varid,  void *ip)
     int nc_def_var_deflate(int ncid, int varid, int shuffle, int deflate, 
-	           	   int deflate_level)
-    int nc_def_var_fletcher32(int ncid, int varid, int fletcher32)
+	           	   int deflate_level) nogil
+    int nc_def_var_fletcher32(int ncid, int varid, int fletcher32) nogil
     int nc_inq_var_fletcher32(int ncid, int varid, int *fletcher32p) nogil
-    int nc_def_var_chunking(int ncid, int varid, int contiguous, size_t *chunksizesp)
-    int nc_def_var_fill(int ncid, int varid, int no_fill, void *fill_value)
-    int nc_def_var_endian(int ncid, int varid, int endian)
+    int nc_def_var_chunking(int ncid, int varid, int contiguous, size_t *chunksizesp) nogil
+    int nc_def_var_fill(int ncid, int varid, int no_fill, void *fill_value) nogil
+    int nc_def_var_endian(int ncid, int varid, int endian) nogil
     int nc_inq_var_chunking(int ncid, int varid, int *contiguousp, size_t *chunksizesp) nogil
     int nc_inq_var_deflate(int ncid, int varid, int *shufflep, 
       		   int *deflatep, int *deflate_levelp) nogil
     int nc_inq_var_fill(int ncid, int varid, int *no_fill, void *fill_value) nogil
     int nc_inq_var_endian(int ncid, int varid, int *endianp) nogil
-    int nc_set_fill(int ncid, int fillmode, int *old_modep)
-    int nc_set_default_format(int format, int *old_formatp)
-    int nc_redef(int ncid)
+    int nc_set_fill(int ncid, int fillmode, int *old_modep) nogil 
+    int nc_set_default_format(int format, int *old_formatp) nogil
+    int nc_redef(int ncid) nogil
     int nc__enddef(int ncid, size_t h_minfree, size_t v_align,
-            size_t v_minfree, size_t r_align)
-    int nc_enddef(int ncid)
-    int nc_sync(int ncid)
-    int nc_abort(int ncid)
-    int nc_close(int ncid)
+            size_t v_minfree, size_t r_align) nogil
+    int nc_enddef(int ncid) nogil
+    int nc_sync(int ncid) nogil
+    int nc_abort(int ncid) nogil
+    int nc_close(int ncid) nogil
     int nc_inq(int ncid, int *ndimsp, int *nvarsp, int *nattsp, int *unlimdimidp) nogil
-    int nc_inq_ndims(int ncid, int *ndimsp) nogil
+    int nc_inq_ndims(int ncid, int *ndimsp) nogil 
     int nc_inq_nvars(int ncid, int *nvarsp) nogil
-    int nc_inq_natts(int ncid, int *nattsp) nogil
+    int nc_inq_natts(int ncid, int *nattsp) nogil 
     int nc_inq_unlimdim(int ncid, int *unlimdimidp) nogil
     int nc_inq_unlimdims(int ncid, int *nunlimdimsp, int *unlimdimidsp) nogil
     int nc_inq_format(int ncid, int *formatp) nogil
-    int nc_def_dim(int ncid, char *name, size_t len, int *idp)
+    int nc_def_dim(int ncid, char *name, size_t len, int *idp) nogil
     int nc_inq_dimid(int ncid, char *name, int *idp) nogil
     int nc_inq_dim(int ncid, int dimid, char *name, size_t *lenp) nogil
     int nc_inq_dimname(int ncid, int dimid, char *name) nogil
     int nc_inq_dimlen(int ncid, int dimid, size_t *lenp) nogil
-    int nc_rename_dim(int ncid, int dimid, char *name)
+    int nc_rename_dim(int ncid, int dimid, char *name) nogil
     int nc_inq_att(int ncid, int varid, char *name,
                nc_type *xtypep, size_t *lenp) nogil
     int nc_inq_attid(int ncid, int varid, char *name, int *idp) nogil
@@ -342,10 +342,10 @@ cdef extern from "netcdf.h":
     int nc_inq_attlen(int ncid, int varid, char *name, size_t *lenp) nogil
     int nc_inq_attname(int ncid, int varid, int attnum, char *name) nogil
     int nc_copy_att(int ncid_in, int varid_in, char *name, int ncid_out, int varid_out)
-    int nc_rename_att(int ncid, int varid, char *name, char *newname)
-    int nc_del_att(int ncid, int varid, char *name)
+    int nc_rename_att(int ncid, int varid, char *name, char *newname) nogil
+    int nc_del_att(int ncid, int varid, char *name) nogil
     int nc_put_att_text(int ncid, int varid, char *name,
-                    size_t len, char *op)
+                    size_t len, char *op) nogil
     int nc_get_att_text(int ncid, int varid, char *name, char *ip) nogil
     int nc_put_att_uchar(int ncid, int varid, char *name, nc_type xtype,
                      size_t len, unsigned char *op)
@@ -382,7 +382,7 @@ cdef extern from "netcdf.h":
     int nc_get_att_ulonglong(int ncid, int varid, char *name, 
                          unsigned long long *ip)
     int nc_def_var(int ncid, char *name, nc_type xtype, int ndims, 
-               int *dimidsp, int *varidp)
+               int *dimidsp, int *varidp) nogil
     int nc_inq_var(int ncid, int varid, char *name, nc_type *xtypep, 
                int *ndimsp, int *dimidsp, int *nattsp) nogil
     int nc_inq_varid(int ncid, char *name, int *varidp) nogil
@@ -391,7 +391,7 @@ cdef extern from "netcdf.h":
     int nc_inq_varndims(int ncid, int varid, int *ndimsp) nogil
     int nc_inq_vardimid(int ncid, int varid, int *dimidsp) nogil
     int nc_inq_varnatts(int ncid, int varid, int *nattsp) nogil
-    int nc_rename_var(int ncid, int varid, char *name)
+    int nc_rename_var(int ncid, int varid, char *name) nogil
     int nc_copy_var(int ncid_in, int varid, int ncid_out)
     int nc_put_var1_text(int ncid, int varid, size_t *indexp, char *op)
     int nc_get_var1_text(int ncid, int varid, size_t *indexp, char *ip)
@@ -670,18 +670,18 @@ cdef extern from "netcdf.h":
     int nc_put_var_ulonglong(int ncid, int varid, unsigned long long *op)
     int nc_get_var_ulonglong(int ncid, int varid, unsigned long long *ip)
     # set logging verbosity level.
-    void nc_set_log_level(int new_level)
-    int nc_show_metadata(int ncid)
-    int nc_free_vlen(nc_vlen_t *vl)
-    int nc_free_vlens(size_t len, nc_vlen_t *vl)
-    int nc_free_string(size_t len, char **data)
-    int nc_set_chunk_cache(size_t size, size_t nelems, float preemption)
-    int nc_get_chunk_cache(size_t *sizep, size_t *nelemsp, float *preemptionp)
-    int nc_set_var_chunk_cache(int ncid, int varid, size_t size, size_t nelems, float preemption)
+    void nc_set_log_level(int new_level) nogil
+    int nc_show_metadata(int ncid) nogil
+    int nc_free_vlen(nc_vlen_t *vl) nogil
+    int nc_free_vlens(size_t len, nc_vlen_t *vl) nogil
+    int nc_free_string(size_t len, char **data) nogil
+    int nc_get_chunk_cache(size_t *sizep, size_t *nelemsp, float *preemptionp) nogil
+    int nc_set_chunk_cache(size_t size, size_t nelems, float preemption) nogil
+    int nc_set_var_chunk_cache(int ncid, int varid, size_t size, size_t nelems, float preemption) nogil
     int nc_get_var_chunk_cache(int ncid, int varid, size_t *sizep, size_t *nelemsp, float *preemptionp) nogil
-    int nc_rename_grp(int grpid, char *name)
-    int nc_def_enum(int ncid, nc_type base_typeid, char *name, nc_type *typeidp)
-    int nc_insert_enum(int ncid, nc_type xtype, char *name, void *value)
+    int nc_rename_grp(int grpid, char *name) nogil
+    int nc_def_enum(int ncid, nc_type base_typeid, char *name, nc_type *typeidp) nogil
+    int nc_insert_enum(int ncid, nc_type xtype, char *name, void *value) nogil
     int nc_inq_enum(int ncid, nc_type xtype, char *name, nc_type *base_nc_typep,\
 	    size_t *base_sizep, size_t *num_membersp) nogil
     int nc_inq_enum_member(int ncid, nc_type xtype, int idx, char *name, void *value) nogil
@@ -696,63 +696,63 @@ IF HAS_QUANTIZATION_SUPPORT:
             NC_QUANTIZE_BITGROOM
             NC_QUANTIZE_GRANULARBR
             NC_QUANTIZE_BITROUND
-        int nc_def_var_quantize(int ncid, int varid, int quantize_mode, int nsd) 
+        int nc_def_var_quantize(int ncid, int varid, int quantize_mode, int nsd) nogil
         int nc_inq_var_quantize(int ncid, int varid, int *quantize_modep, int *nsdp) nogil
     cdef extern from "netcdf_filter.h":
-        int nc_inq_filter_avail(int ncid, unsigned filterid);
+        int nc_inq_filter_avail(int ncid, unsigned filterid) nogil
 
 IF HAS_SZIP_SUPPORT:
     cdef extern from "netcdf.h":
         cdef enum:
             H5Z_FILTER_SZIP
-        int nc_def_var_quantize(int ncid, int varid, int quantize_mode, int nsd) 
+        int nc_def_var_quantize(int ncid, int varid, int quantize_mode, int nsd) nogil
         int nc_inq_var_quantize(int ncid, int varid, int *quantize_modep, int *nsdp) nogil
-        int nc_def_var_szip(int ncid, int varid, int options_mask, int pixels_per_bloc)
-        int nc_inq_var_szip(int ncid, int varid, int *options_maskp, int *pixels_per_blockp)
+        int nc_def_var_szip(int ncid, int varid, int options_mask, int pixels_per_bloc) nogil
+        int nc_inq_var_szip(int ncid, int varid, int *options_maskp, int *pixels_per_blockp) nogil
 
 IF HAS_ZSTANDARD_SUPPORT:
     cdef extern from "netcdf_filter.h":
         cdef enum:
             H5Z_FILTER_ZSTD
-        int nc_def_var_zstandard(int ncid, int varid, int level)
-        int nc_inq_var_zstandard(int ncid, int varid, int* hasfilterp, int *levelp)
-        int nc_inq_filter_avail(int ncid, unsigned id)
+        int nc_def_var_zstandard(int ncid, int varid, int level) nogil
+        int nc_inq_var_zstandard(int ncid, int varid, int* hasfilterp, int *levelp) nogil
+        int nc_inq_filter_avail(int ncid, unsigned id) nogil
 
 IF HAS_BZIP2_SUPPORT:
     cdef extern from "netcdf_filter.h":
         cdef enum:
             H5Z_FILTER_BZIP2
-        int nc_def_var_bzip2(int ncid, int varid, int level)
-        int nc_inq_var_bzip2(int ncid, int varid, int* hasfilterp, int *levelp)
+        int nc_def_var_bzip2(int ncid, int varid, int level) nogil
+        int nc_inq_var_bzip2(int ncid, int varid, int* hasfilterp, int *levelp) nogil
 
 IF HAS_BLOSC_SUPPORT:
     cdef extern from "netcdf_filter.h":
         cdef enum:
             H5Z_FILTER_BLOSC
-        int nc_def_var_blosc(int ncid, int varid, unsigned subcompressor, unsigned level, unsigned blocksize, unsigned addshuffle)
-        int nc_inq_var_blosc(int ncid, int varid, int* hasfilterp, unsigned* subcompressorp, unsigned* levelp, unsigned* blocksizep, unsigned* addshufflep)
+        int nc_def_var_blosc(int ncid, int varid, unsigned subcompressor, unsigned level, unsigned blocksize, unsigned addshuffle) nogil
+        int nc_inq_var_blosc(int ncid, int varid, int* hasfilterp, unsigned* subcompressorp, unsigned* levelp, unsigned* blocksizep, unsigned* addshufflep) nogil
 
 IF HAS_NC_OPEN_MEM:
     cdef extern from "netcdf_mem.h":
-        int nc_open_mem(const char *path, int mode, size_t size, void* memory, int *ncidp)
+        int nc_open_mem(const char *path, int mode, size_t size, void* memory, int *ncidp) nogil
 
 IF HAS_NC_CREATE_MEM:
     cdef extern from "netcdf_mem.h":
-        int nc_create_mem(const char *path, int mode, size_t initialize, int *ncidp);
+        int nc_create_mem(const char *path, int mode, size_t initialize, int *ncidp) nogil
         ctypedef struct NC_memio:
             size_t size
             void* memory
             int flags
-        int nc_close_memio(int ncid, NC_memio* info);
+        int nc_close_memio(int ncid, NC_memio* info) nogil
 
 IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
     cdef extern from "mpi-compat.h": pass
     cdef extern from "netcdf_par.h":
         ctypedef int MPI_Comm
         ctypedef int MPI_Info
-        int nc_create_par(char *path, int cmode, MPI_Comm comm, MPI_Info info, int *ncidp);
-        int nc_open_par(char *path, int mode, MPI_Comm comm, MPI_Info info, int *ncidp);
-        int nc_var_par_access(int ncid, int varid, int par_access);
+        int nc_create_par(char *path, int cmode, MPI_Comm comm, MPI_Info info, int *ncidp) nogil
+        int nc_open_par(char *path, int mode, MPI_Comm comm, MPI_Info info, int *ncidp) nogil
+        int nc_var_par_access(int ncid, int varid, int par_access) nogil
         cdef enum:
             NC_COLLECTIVE
             NC_INDEPENDENT
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 07c7a0d29..0d2cf6274 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1289,7 +1289,8 @@ details. Values can be reset with `set_chunk_cache`."""
     cdef int ierr
     cdef size_t sizep, nelemsp
     cdef float preemptionp
-    ierr = nc_get_chunk_cache(&sizep, &nelemsp, &preemptionp)
+    with nogil:
+        ierr = nc_get_chunk_cache(&sizep, &nelemsp, &preemptionp)
     _ensure_nc_success(ierr)
     size = sizep; nelems = nelemsp; preemption = preemptionp
     return (size,nelems,preemption)
@@ -1318,7 +1319,8 @@ details."""
         preemptionp = preemption
     else:
         preemptionp = preemption_orig
-    ierr = nc_set_chunk_cache(sizep,nelemsp, preemptionp)
+    with nogil:
+        ierr = nc_set_chunk_cache(sizep,nelemsp, preemptionp)
     _ensure_nc_success(ierr)
 
 __netcdf4libversion__ = getlibversion().split()[0]
@@ -1507,7 +1509,8 @@ cdef _get_att(grp, int varid, name, encoding='utf-8'):
                 result = [values[j].decode(encoding,errors='replace').replace('\x00','')
                           if values[j] else "" for j in range(att_len)]
             finally:
-                ierr = nc_free_string(att_len, values) # free memory in netcdf C lib
+                with nogil:
+                    ierr = nc_free_string(att_len, values) # free memory in netcdf C lib
         finally:
             PyMem_Free(values)
 
@@ -1548,9 +1551,13 @@ cdef _get_att(grp, int varid, name, encoding='utf-8'):
 
 def _set_default_format(object format='NETCDF4'):
     # Private function to set the netCDF file format
+    cdef int ierr, formatid
     if format not in _format_dict:
         raise ValueError("unrecognized format requested")
-    nc_set_default_format(_format_dict[format], NULL)
+    formatid = _format_dict[format]
+    with nogil:
+        ierr = nc_set_default_format(formatid, NULL)
+    _ensure_nc_success(ierr)
 
 cdef _get_format(int grpid):
     # Private function to get the netCDF file format
@@ -1597,16 +1604,18 @@ cdef issue485_workaround(int grpid, int varid, char* attname):
 
     if not _needsworkaround_issue485:
         return
-    ierr = nc_inq_att(grpid, varid, attname, &att_type, &att_len)
+    with nogil:
+        ierr = nc_inq_att(grpid, varid, attname, &att_type, &att_len)
     if ierr == NC_NOERR and att_type == NC_CHAR:
-        ierr = nc_del_att(grpid, varid, attname)
+        with nogil:
+            ierr = nc_del_att(grpid, varid, attname)
         _ensure_nc_success(ierr)
 
 
-cdef _set_att(grp, int varid, name, value,\
+cdef _set_att(Group grp, int varid, name, value,\
               nc_type xtype=-99, force_ncstring=False):
     # Private function to set an attribute name/value pair
-    cdef int ierr, lenarr
+    cdef int ierr, lenarr, N
     cdef char *attname
     cdef char *datstring
     cdef char **string_ptrs
@@ -1649,7 +1658,8 @@ be raised in the next release."""
                         strings[j] = _strencode('\x00')
                     string_ptrs[j] = strings[j]
                 issue485_workaround(grp._grpid, varid, attname)
-                ierr = nc_put_att_string(grp._grpid, varid, attname, N, string_ptrs)
+                with nogil:
+                    ierr = nc_put_att_string(grp._grpid, varid, attname, N, string_ptrs)
             finally:
                 PyMem_Free(string_ptrs)
         else:
@@ -1673,12 +1683,15 @@ be raised in the next release."""
                 try:
                     if force_ncstring: raise UnicodeError
                     dats_ascii = _to_ascii(dats) # try to encode bytes as ascii string
-                    ierr = nc_put_att_text(grp._grpid, varid, attname, lenarr, datstring)
+                    with nogil:
+                        ierr = nc_put_att_text(grp._grpid, varid, attname, lenarr, datstring)
                 except UnicodeError:
                     issue485_workaround(grp._grpid, varid, attname)
-                    ierr = nc_put_att_string(grp._grpid, varid, attname, 1, &datstring)
+                    with nogil:
+                        ierr = nc_put_att_string(grp._grpid, varid, attname, 1, &datstring)
             else:
-                ierr = nc_put_att_text(grp._grpid, varid, attname, lenarr, datstring)
+                with nogil:
+                    ierr = nc_put_att_text(grp._grpid, varid, attname, lenarr, datstring)
         _ensure_nc_success(ierr, err_cls=AttributeError)
     # a 'regular' array type ('f4','i4','f8' etc)
     else:
@@ -1689,7 +1702,8 @@ be raised in the next release."""
         elif xtype == -99: # if xtype is not passed in as kwarg.
             xtype = _nptonctype[value_arr.dtype.str[1:]]
         lenarr = PyArray_SIZE(value_arr)
-        ierr = nc_put_att(grp._grpid, varid, attname, xtype, lenarr,
+        with nogil:
+            ierr = nc_put_att(grp._grpid, varid, attname, xtype, lenarr,
                 PyArray_DATA(value_arr))
         _ensure_nc_success(ierr, err_cls=AttributeError)
 
@@ -2151,11 +2165,11 @@ strings.
         **`info`**: MPI_Info object for parallel access. Default `None`, which
         means MPI_INFO_NULL will be used.  Ignored if `parallel=False`.
         """
-        cdef int grpid, ierr, numgrps, numdims, numvars
+        cdef int grpid, ierr, numgrps, numdims, numvars,
         cdef size_t initialsize
         cdef char *path
         cdef char namstring[NC_MAX_NAME+1]
-        cdef int cmode
+        cdef int cmode, parmode
         IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
             cdef MPI_Comm mpicomm
             cdef MPI_Info mpiinfo
@@ -2202,7 +2216,7 @@ strings.
                     mpiinfo = info.ob_mpi
                 else:
                     mpiinfo = MPI_INFO_NULL
-                cmode = NC_MPIIO | _cmode_dict[format]
+                parmode = NC_MPIIO | _cmode_dict[format]
 
         self._inmemory = False
 
@@ -2217,7 +2231,8 @@ strings.
                 # kwarg is interpreted as advisory size.
                 IF HAS_NC_CREATE_MEM:
                    initialsize = memory
-                   ierr = nc_create_mem(path, 0, initialsize, &grpid)
+                   with nogil:
+                       ierr = nc_create_mem(path, 0, initialsize, &grpid)
                    self._inmemory = True # checked in close method
                 ELSE:
                     msg = """
@@ -2228,33 +2243,45 @@ strings.
                 if clobber:
                     if parallel:
                         IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
-                            ierr = nc_create_par(path, NC_CLOBBER | cmode, \
-                                   mpicomm, mpiinfo, &grpid)
+                            cmode = NC_CLOBBER | parmode
+                            with nogil:
+                                ierr = nc_create_par(path, cmode, \
+                                       mpicomm, mpiinfo, &grpid)
                         ELSE:
                             pass
                     elif diskless:
                         if persist:
-                            ierr = nc_create(path, NC_WRITE | NC_CLOBBER |
-                                    NC_DISKLESS | NC_PERSIST, &grpid)
+                            cmode = NC_WRITE | NC_CLOBBER | NC_DISKLESS | NC_PERSIST
+                            with nogil:
+                                ierr = nc_create(path, cmode, &grpid)
                         else:
-                            ierr = nc_create(path, NC_CLOBBER | NC_DISKLESS , &grpid)
+                            cmode = NC_CLOBBER | NC_DISKLESS
+                            with nogil:
+                                ierr = nc_create(path, cmode , &grpid)
                     else:
-                        ierr = nc_create(path, NC_CLOBBER, &grpid)
+                        with nogil:
+                            ierr = nc_create(path, NC_CLOBBER, &grpid)
                 else:
                     if parallel:
                         IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
-                            ierr = nc_create_par(path, NC_NOCLOBBER | cmode, \
-                                   mpicomm, mpiinfo, &grpid)
+                            cmode = NC_NOCLOBBER | parmode
+                            with nogil:
+                                ierr = nc_create_par(path, cmode, \
+                                       mpicomm, mpiinfo, &grpid)
                         ELSE:
                             pass
                     elif diskless:
                         if persist:
-                            ierr = nc_create(path, NC_WRITE | NC_NOCLOBBER |
-                                    NC_DISKLESS | NC_PERSIST , &grpid)
+                            cmode = NC_WRITE | NC_NOCLOBBER | NC_DISKLESS | NC_PERSIST
+                            with nogil:
+                                ierr = nc_create(path, cmode, &grpid)
                         else:
-                            ierr = nc_create(path, NC_NOCLOBBER | NC_DISKLESS , &grpid)
+                            cmode = NC_NOCLOBBER | NC_DISKLESS
+                            with nogil:
+                                ierr = nc_create(path, cmode , &grpid)
                     else:
-                        ierr = nc_create(path, NC_NOCLOBBER, &grpid)
+                        with nogil:
+                            ierr = nc_create(path, NC_NOCLOBBER, &grpid)
             # reset default format to netcdf3 - this is a workaround
             # for issue 170 (nc_open'ing a DAP dataset after switching
             # format to NETCDF4). This bug should be fixed in version
@@ -2270,7 +2297,8 @@ strings.
                     if result != 0:
                         raise ValueError("Unable to retrieve Buffer from %s" % (memory,))
 
-                    ierr = nc_open_mem(path, 0, self._buffer.len, self._buffer.buf, &grpid)
+                    with nogil:
+                        ierr = nc_open_mem(path, 0, self._buffer.len, self._buffer.buf, &grpid)
                 ELSE:
                     msg = """
         nc_open_mem functionality not enabled.  To enable, install Cython, make sure you have
@@ -2278,75 +2306,108 @@ strings.
                     raise ValueError(msg)
             elif parallel:
                 IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
-                    ierr = nc_open_par(path, NC_NOWRITE | NC_MPIIO, \
-                           mpicomm, mpiinfo, &grpid)
+                    cmode = NC_NOWRITE | NC_MPIIO
+                    with nogil:
+                        ierr = nc_open_par(path, cmode, \
+                               mpicomm, mpiinfo, &grpid)
                 ELSE:
                     pass
             elif diskless:
-                ierr = nc_open(path, NC_NOWRITE | NC_DISKLESS, &grpid)
+                cmode = NC_NOWRITE | NC_DISKLESS
+                with nogil:
+                    ierr = nc_open(path, cmode, &grpid)
             else:
                 if mode == 'rs':
                     # NC_SHARE is very important for speed reading
                     # large netcdf3 files with a record dimension
                     # (pull request #902).
-                    ierr = nc_open(path, NC_NOWRITE | NC_SHARE, &grpid)
+                    cmode = NC_NOWRITE | NC_SHARE
+                    with nogil:
+                        ierr = nc_open(path, cmode, &grpid)
                 else:
-                    ierr = nc_open(path, NC_NOWRITE, &grpid)
+                    with nogil:
+                        ierr = nc_open(path, NC_NOWRITE, &grpid)
         elif mode in ['a','r+'] and os.path.exists(filename):
             if parallel:
                 IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
-                    ierr = nc_open_par(path, NC_WRITE | NC_MPIIO, \
-                           mpicomm, mpiinfo, &grpid)
+                    cmode = NC_NOWRITE | NC_SHARE 
+                    with nogil:
+                        ierr = nc_open_par(path, cmode, \
+                               mpicomm, mpiinfo, &grpid)
                 ELSE:
                     pass
             elif diskless:
-                ierr = nc_open(path, NC_WRITE | NC_DISKLESS, &grpid)
+                cmode = NC_WRITE | NC_DISKLESS
+                with nogil:
+                    ierr = nc_open(path, cmode, &grpid)
             else:
-                ierr = nc_open(path, NC_WRITE, &grpid)
+                with nogil:
+                    ierr = nc_open(path, NC_WRITE, &grpid)
         elif mode in ['as','r+s'] and os.path.exists(filename):
             if parallel:
                 # NC_SHARE ignored
                 IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
-                    ierr = nc_open_par(path, NC_WRITE | NC_MPIIO, \
-                           mpicomm, mpiinfo, &grpid)
+                    cmode =  NC_WRITE | NC_MPIIO
+                    with nogil:
+                        ierr = nc_open_par(path, cmode, \
+                               mpicomm, mpiinfo, &grpid)
                 ELSE:
                     pass
             elif diskless:
-                ierr = nc_open(path, NC_SHARE | NC_DISKLESS, &grpid)
+                cmode = NC_SHARE | NC_DISKLESS
+                with nogil:
+                    ierr = nc_open(path, cmode, &grpid)
             else:
-                ierr = nc_open(path, NC_SHARE, &grpid)
+                with nogil:
+                    ierr = nc_open(path, NC_SHARE, &grpid)
         elif mode == 'ws' or (mode in ['as','r+s'] and not os.path.exists(filename)):
             _set_default_format(format=format)
             if clobber:
                 if parallel:
                     # NC_SHARE ignored
                     IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
-                        ierr = nc_create_par(path, NC_CLOBBER | cmode, \
-                               mpicomm, mpiinfo, &grpid)
+                        cmode = NC_CLOBBER | parmode 
+                        with nogil:
+                            ierr = nc_create_par(path, NC_CLOBBER | cmode, \
+                                   mpicomm, mpiinfo, &grpid)
                     ELSE:
                         pass
                 elif diskless:
                     if persist:
-                        ierr = nc_create(path, NC_WRITE | NC_SHARE | NC_CLOBBER | NC_DISKLESS , &grpid)
+                        cmode = NC_WRITE | NC_SHARE | NC_CLOBBER | NC_DISKLESS
+                        with nogil:
+                            ierr = nc_create(path, cmode, &grpid)
                     else:
-                        ierr = nc_create(path, NC_SHARE | NC_CLOBBER | NC_DISKLESS , &grpid)
+                        cmode = NC_SHARE | NC_CLOBBER | NC_DISKLESS
+                        with nogil:
+                            ierr = nc_create(path, cmode , &grpid)
                 else:
-                    ierr = nc_create(path, NC_SHARE | NC_CLOBBER, &grpid)
+                    cmode = NC_SHARE | NC_CLOBBER
+                    with nogil:
+                        ierr = nc_create(path, cmode, &grpid)
             else:
                 if parallel:
                     # NC_SHARE ignored
                     IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
-                        ierr = nc_create_par(path, NC_NOCLOBBER | cmode, \
-                               mpicomm, mpiinfo, &grpid)
+                        cmode = NC_NOCLOBBER | parmode
+                        with nogil:
+                            ierr = nc_create_par(path, cmode, \
+                                   mpicomm, mpiinfo, &grpid)
                     ELSE:
                         pass
                 elif diskless:
                     if persist:
-                        ierr = nc_create(path, NC_WRITE | NC_SHARE | NC_NOCLOBBER | NC_DISKLESS , &grpid)
+                        cmode = NC_WRITE | NC_SHARE | NC_NOCLOBBER | NC_DISKLESS
+                        with nogil:
+                            ierr = nc_create(path, cmode , &grpid)
                     else:
-                        ierr = nc_create(path, NC_SHARE | NC_NOCLOBBER | NC_DISKLESS , &grpid)
+                        cmode = NC_SHARE | NC_NOCLOBBER | NC_DISKLESS
+                        with nogil:
+                            ierr = nc_create(path, cmode , &grpid)
                 else:
-                    ierr = nc_create(path, NC_SHARE | NC_NOCLOBBER, &grpid)
+                    cmode = NC_SHARE | NC_NOCLOBBER
+                    with nogil:
+                        ierr = nc_create(path, cmode, &grpid)
         else:
             raise ValueError("mode must be 'w', 'x', 'r', 'a' or 'r+', got '%s'" % mode)
 
@@ -2469,7 +2530,9 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
         return '\n'.join(ncdump)
 
     def _close(self, check_err):
-        cdef int ierr = nc_close(self._grpid)
+        cdef int ierr
+        with nogil:
+            ierr = nc_close(self._grpid)
 
         if check_err:
             _ensure_nc_success(ierr)
@@ -2485,7 +2548,8 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python."""
         def _close_mem(self, check_err):
             cdef int ierr
             cdef NC_memio memio
-            ierr = nc_close_memio(self._grpid, &memio)
+            with nogil:
+                ierr = nc_close_memio(self._grpid, &memio)
 
             if check_err:
                 _ensure_nc_success(ierr)
@@ -2534,15 +2598,20 @@ Is the Dataset open or closed?
 **`sync(self)`**
 
 Writes all buffered data in the `Dataset` to the disk file."""
-        _ensure_nc_success(nc_sync(self._grpid))
+        cdef int ierr
+        with nogil:
+            ierr = nc_sync(self._grpid)
+        _ensure_nc_success(ierr)
 
     def _redef(self):
         cdef int ierr
-        ierr = nc_redef(self._grpid)
+        with nogil:
+            ierr = nc_redef(self._grpid)
 
     def _enddef(self):
         cdef int ierr
-        ierr = nc_enddef(self._grpid)
+        with nogil:
+            ierr = nc_enddef(self._grpid)
 
     def set_fill_on(self):
         """
@@ -2557,8 +2626,10 @@ separately for each variable type). The default behavior of the netCDF
 library corresponds to `set_fill_on`.  Data which are equal to the
 `_Fill_Value` indicate that the variable was created, but never written
 to."""
-        cdef int oldmode
-        _ensure_nc_success(nc_set_fill(self._grpid, NC_FILL, &oldmode))
+        cdef int oldmode, ierr
+        with nogil:
+            ierr = nc_set_fill(self._grpid, NC_FILL, &oldmode)
+        _ensure_nc_success(ierr)
 
     def set_fill_off(self):
         """
@@ -2569,8 +2640,10 @@ Sets the fill mode for a `Dataset` open for writing to `off`.
 This will prevent the data from being pre-filled with fill values, which
 may result in some performance improvements. However, you must then make
 sure the data is actually written before being read."""
-        cdef int oldmode
-        _ensure_nc_success(nc_set_fill(self._grpid, NC_NOFILL, &oldmode))
+        cdef int oldmode, ierr
+        with nogil:
+            ierr = nc_set_fill(self._grpid, NC_NOFILL, &oldmode)
+        _ensure_nc_success(ierr)
 
     def createDimension(self, dimname, size=None):
         """
@@ -2594,6 +2667,7 @@ instance. To determine if a dimension is 'unlimited', use the
 
 rename a `Dimension` named `oldname` to `newname`."""
         cdef char *namstring
+        cdef Dimension dim
         bytestr = _strencode(newname)
         namstring = bytestr
         if self.data_model != 'NETCDF4': self._redef()
@@ -2601,7 +2675,8 @@ rename a `Dimension` named `oldname` to `newname`."""
             dim = self.dimensions[oldname]
         except KeyError:
             raise KeyError('%s not a valid dimension name' % oldname)
-        ierr = nc_rename_dim(self._grpid, dim._dimid, namstring)
+        with nogil:
+            ierr = nc_rename_dim(self._grpid, dim._dimid, namstring)
         if self.data_model != 'NETCDF4': self._enddef()
 
         _ensure_nc_success(ierr)
@@ -2850,6 +2925,7 @@ is the number of variable dimensions."""
 
 rename a `Variable` named `oldname` to `newname`"""
         cdef char *namstring
+        cdef Variable var
         try:
             var = self.variables[oldname]
         except KeyError:
@@ -2857,7 +2933,8 @@ rename a `Variable` named `oldname` to `newname`"""
         bytestr = _strencode(newname)
         namstring = bytestr
         if self.data_model != 'NETCDF4': self._redef()
-        ierr = nc_rename_var(self._grpid, var._varid, namstring)
+        with nogil:
+            ierr = nc_rename_var(self._grpid, var._varid, namstring)
         if self.data_model != 'NETCDF4': self._enddef()
 
         _ensure_nc_success(ierr)
@@ -2975,7 +3052,8 @@ attributes."""
         bytestr = _strencode(name)
         attname = bytestr
         if self.data_model != 'NETCDF4': self._redef()
-        ierr = nc_del_att(self._grpid, NC_GLOBAL, attname)
+        with nogil:
+            ierr = nc_del_att(self._grpid, NC_GLOBAL, attname)
         if self.data_model != 'NETCDF4': self._enddef()
         _ensure_nc_success(ierr)
 
@@ -3020,11 +3098,14 @@ attributes."""
 rename a `Dataset` or `Group` attribute named `oldname` to `newname`."""
         cdef char *oldnamec
         cdef char *newnamec
+        cdef int ierr
         bytestr = _strencode(oldname)
         oldnamec = bytestr
         bytestr = _strencode(newname)
         newnamec = bytestr
-        _ensure_nc_success(nc_rename_att(self._grpid, NC_GLOBAL, oldnamec, newnamec))
+        with nogil:
+            ierr = nc_rename_att(self._grpid, NC_GLOBAL, oldnamec, newnamec)
+        _ensure_nc_success(ierr)
 
     def renameGroup(self, oldname, newname):
         """
@@ -3032,14 +3113,18 @@ rename a `Dataset` or `Group` attribute named `oldname` to `newname`."""
 
 rename a `Group` named `oldname` to `newname` (requires netcdf >= 4.3.1)."""
         cdef char *newnamec
+        cdef Group grp
         IF HAS_RENAME_GRP:
+            cdef int ierr
             bytestr = _strencode(newname)
             newnamec = bytestr
             try:
                 grp = self.groups[oldname]
             except KeyError:
                 raise KeyError('%s not a valid group name' % oldname)
-            _ensure_nc_success(nc_rename_grp(grp._grpid, newnamec))
+            with nogil:
+                ierr = nc_rename_grp(grp._grpid, newnamec)
+            _ensure_nc_success(ierr)
             # remove old key from groups dict.
             self.groups.pop(oldname)
             # add new key.
@@ -3367,7 +3452,8 @@ to be installed and in `$PATH`.
 returns True if blosc compression filter is available"""
         cdef int ierr
         IF HAS_BLOSC_SUPPORT:
-            ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_BLOSC)
+            with nogil:
+                ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_BLOSC)
             if ierr:
                 return False
             else:
@@ -3380,7 +3466,8 @@ returns True if blosc compression filter is available"""
 returns True if zstd compression filter is available"""
         cdef int ierr
         IF HAS_ZSTANDARD_SUPPORT:
-            ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_ZSTD)
+            with nogil:
+                ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_ZSTD)
             if ierr:
                 return False
             else:
@@ -3393,7 +3480,8 @@ returns True if zstd compression filter is available"""
 returns True if bzip2 compression filter is available"""
         cdef int ierr
         IF HAS_BZIP2_SUPPORT:
-            ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_BZIP2)
+            with nogil:
+                ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_BZIP2)
             if ierr:
                 return False
             else:
@@ -3406,7 +3494,8 @@ returns True if bzip2 compression filter is available"""
 returns True if szip compression filter is available"""
         cdef int ierr
         IF HAS_SZIP_SUPPORT:
-            ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_SZIP)
+            with nogil:
+                ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_SZIP)
             if ierr:
                 return False
             else:
@@ -3445,6 +3534,7 @@ Additional read-only class variables:
         another `Group` instance, not using this class directly.
         """
         cdef char *groupname
+        cdef int ierr, grpid
         # flag to indicate that Variables in this Group support orthogonal indexing.
         self.__orthogonal_indexing__ = True
         # set data_model and file_format attributes.
@@ -3471,7 +3561,10 @@ Additional read-only class variables:
         else:
             bytestr = _strencode(name)
             groupname = bytestr
-            _ensure_nc_success(nc_def_grp(parent._grpid, groupname, &self._grpid))
+            grpid = parent._grpid
+            with nogil:
+                ierr = nc_def_grp(grpid, groupname, &self._grpid)
+            _ensure_nc_success(ierr)
             if sys.version_info[0:2] < (3, 7):
                 self.cmptypes = OrderedDict()
                 self.vltypes = OrderedDict()
@@ -3556,7 +3649,8 @@ Read-only class variables:
             else:
                 lendim = NC_UNLIMITED
             if grp.data_model != 'NETCDF4': grp._redef()
-            ierr = nc_def_dim(self._grpid, dimname, lendim, &self._dimid)
+            with nogil:
+                ierr = nc_def_dim(self._grpid, dimname, lendim, &self._dimid)
             if grp.data_model != 'NETCDF4': grp._enddef()
             _ensure_nc_success(ierr)
 
@@ -3621,7 +3715,8 @@ returns `True` if the `Dimension` instance is unlimited, `False` otherwise."""
         cdef int ierr, n, numunlimdims, ndims, nvars, ngatts, xdimid
         cdef int *unlimdimids
         if self._data_model == 'NETCDF4':
-            ierr = nc_inq_unlimdims(self._grpid, &numunlimdims, NULL)
+            with nogil:
+                ierr = nc_inq_unlimdims(self._grpid, &numunlimdims, NULL)
             _ensure_nc_success(ierr)
             if numunlimdims == 0:
                 return False
@@ -3983,7 +4078,8 @@ behavior is similar to Fortran or Matlab, but different than numpy.
                 self._vltype = datatype
             xtype = datatype._nc_type
             # make sure this a valid user defined datatype defined in this Group
-            ierr = nc_inq_type(self._grpid, xtype, namstring, NULL)
+            with nogil:
+                ierr = nc_inq_type(self._grpid, xtype, namstring, NULL)
             _ensure_nc_success(ierr)
             # dtype variable attribute is a numpy datatype object.
             self.dtype = datatype.dtype
@@ -4013,24 +4109,28 @@ behavior is similar to Fortran or Matlab, but different than numpy.
             if grp.data_model != 'NETCDF4': grp._redef()
             # define variable.
             if ndims:
-                ierr = nc_def_var(self._grpid, varname, xtype, ndims,
-                                  dimids, &self._varid)
+                with nogil:
+                    ierr = nc_def_var(self._grpid, varname, xtype, ndims,
+                                      dimids, &self._varid)
                 free(dimids)
             else: # a scalar variable.
-                ierr = nc_def_var(self._grpid, varname, xtype, ndims,
-                                  NULL, &self._varid)
+                with nogil:
+                    ierr = nc_def_var(self._grpid, varname, xtype, ndims,
+                                      NULL, &self._varid)
             # set chunk cache size if desired
             # default is 1mb per var, can cause problems when many (1000's)
             # of vars are created.  This change only lasts as long as file is
             # open.
             if grp.data_model.startswith('NETCDF4') and chunk_cache is not None:
-                ierr = nc_get_var_chunk_cache(self._grpid, self._varid, &sizep,
-                        &nelemsp, &preemptionp)
+                with nogil:
+                    ierr = nc_get_var_chunk_cache(self._grpid, self._varid, &sizep,
+                           &nelemsp, &preemptionp)
                 _ensure_nc_success(ierr)
                 # reset chunk cache size, leave other parameters unchanged.
                 sizep = chunk_cache
-                ierr = nc_set_var_chunk_cache(self._grpid, self._varid, sizep,
-                        nelemsp, preemptionp)
+                with nogil:
+                    ierr = nc_set_var_chunk_cache(self._grpid, self._varid, sizep,
+                           nelemsp, preemptionp)
                 _ensure_nc_success(ierr)
             if ierr != NC_NOERR:
                 if grp.data_model != 'NETCDF4': grp._enddef()
@@ -4047,9 +4147,11 @@ behavior is similar to Fortran or Matlab, but different than numpy.
                     if zlib:
                         icomplevel = complevel
                         if shuffle:
-                            ierr = nc_def_var_deflate(self._grpid, self._varid, 1, 1, icomplevel)
+                            with nogil:
+                                ierr = nc_def_var_deflate(self._grpid, self._varid, 1, 1, icomplevel)
                         else:
-                            ierr = nc_def_var_deflate(self._grpid, self._varid, 0, 1, icomplevel)
+                            with nogil:
+                                ierr = nc_def_var_deflate(self._grpid, self._varid, 0, 1, icomplevel)
                         if ierr != NC_NOERR:
                             if grp.data_model != 'NETCDF4': grp._enddef()
                             _ensure_nc_success(ierr)
@@ -4061,7 +4163,8 @@ behavior is similar to Fortran or Matlab, but different than numpy.
                                 msg="unknown szip coding ('ec' or 'nn' supported)"
                                 raise ValueError(msg)
                             iszip_pixels_per_block = szip_pixels_per_block
-                            ierr = nc_def_var_szip(self._grpid, self._varid, iszip_coding, iszip_pixels_per_block)
+                            with nogil:
+                                ierr = nc_def_var_szip(self._grpid, self._varid, iszip_coding, iszip_pixels_per_block)
                             if ierr != NC_NOERR:
                                 if grp.data_model != 'NETCDF4': grp._enddef()
                                 _ensure_nc_success(ierr)
@@ -4072,7 +4175,8 @@ compression='szip' only works if linked version of hdf5 has szip functionality e
                     if zstd:
                         IF HAS_ZSTANDARD_SUPPORT:
                             icomplevel = complevel
-                            ierr = nc_def_var_zstandard(self._grpid, self._varid, icomplevel)
+                            with nogil:
+                                ierr = nc_def_var_zstandard(self._grpid, self._varid, icomplevel)
                             if ierr != NC_NOERR:
                                 if grp.data_model != 'NETCDF4': grp._enddef()
                                 _ensure_nc_success(ierr)
@@ -4084,7 +4188,8 @@ version 4.9.0 or higher netcdf-c with zstandard support, and rebuild netcdf4-pyt
                     if bzip2:
                         IF HAS_BZIP2_SUPPORT:
                             icomplevel = complevel
-                            ierr = nc_def_var_bzip2(self._grpid, self._varid, icomplevel)
+                            with nogil:
+                                ierr = nc_def_var_bzip2(self._grpid, self._varid, icomplevel)
                             if ierr != NC_NOERR:
                                 if grp.data_model != 'NETCDF4': grp._enddef()
                                 _ensure_nc_success(ierr)
@@ -4099,7 +4204,8 @@ version 4.9.0 or higher netcdf-c with bzip2 support, and rebuild netcdf4-python.
                             iblosc_shuffle = blosc_shuffle
                             iblosc_blocksize = 0 # not currently used by c lib
                             iblosc_complevel = complevel
-                            ierr = nc_def_var_blosc(self._grpid, self._varid,\
+                            with nogil:
+                                ierr = nc_def_var_blosc(self._grpid, self._varid,\
                                     iblosc_compressor,\
                                     iblosc_complevel,iblosc_blocksize,\
                                     iblosc_shuffle)
@@ -4113,7 +4219,8 @@ version 4.9.0 or higher netcdf-c with blosc support, and rebuild netcdf4-python.
                             raise ValueError(msg)
                 # set checksum.
                 if fletcher32 and ndims: # don't bother for scalar variable
-                    ierr = nc_def_var_fletcher32(self._grpid, self._varid, 1)
+                    with nogil:
+                        ierr = nc_def_var_fletcher32(self._grpid, self._varid, 1)
                     if ierr != NC_NOERR:
                         if grp.data_model != 'NETCDF4': grp._enddef()
                         _ensure_nc_success(ierr)
@@ -4139,16 +4246,19 @@ version 4.9.0 or higher netcdf-c with blosc support, and rebuild netcdf4-python.
                                 raise ValueError(msg)
                             chunksizesp[n] = chunksizes[n]
                     if chunksizes is not None or contiguous:
-                        ierr = nc_def_var_chunking(self._grpid, self._varid, icontiguous, chunksizesp)
+                        with nogil:
+                            ierr = nc_def_var_chunking(self._grpid, self._varid, icontiguous, chunksizesp)
                         free(chunksizesp)
                         if ierr != NC_NOERR:
                             if grp.data_model != 'NETCDF4': grp._enddef()
                             _ensure_nc_success(ierr)
                 # set endian-ness of variable
                 if endian == 'little':
-                    ierr = nc_def_var_endian(self._grpid, self._varid, NC_ENDIAN_LITTLE)
+                    with nogil:
+                        ierr = nc_def_var_endian(self._grpid, self._varid, NC_ENDIAN_LITTLE)
                 elif endian == 'big':
-                    ierr = nc_def_var_endian(self._grpid, self._varid, NC_ENDIAN_BIG)
+                    with nogil:
+                        ierr = nc_def_var_endian(self._grpid, self._varid, NC_ENDIAN_BIG)
                 elif endian == 'native':
                     pass # this is the default format.
                 else:
@@ -4158,14 +4268,16 @@ version 4.9.0 or higher netcdf-c with blosc support, and rebuild netcdf4-python.
                     if significant_digits is not None:
                         nsd = significant_digits
                         if quantize_mode == 'BitGroom':
-                            ierr = nc_def_var_quantize(self._grpid,
-                                    self._varid, NC_QUANTIZE_BITGROOM, nsd)
+                            with nogil:
+                                ierr = nc_def_var_quantize(self._grpid,
+                                       self._varid, NC_QUANTIZE_BITGROOM, nsd)
                         elif quantize_mode == 'GranularBitRound':
-                            ierr = nc_def_var_quantize(self._grpid,
-                                    self._varid, NC_QUANTIZE_GRANULARBR, nsd)
+                            with nogil:
+                                ierr = nc_def_var_quantize(self._grpid,
+                                       self._varid, NC_QUANTIZE_GRANULARBR, nsd)
                         elif quantize_mode == 'BitRound':
                             ierr = nc_def_var_quantize(self._grpid,
-                                    self._varid, NC_QUANTIZE_BITROUND, nsd)
+                                       self._varid, NC_QUANTIZE_BITROUND, nsd)
                         else:
                             raise ValueError("'quantize_mode' keyword argument must be 'BitGroom','GranularBitRound' or 'BitRound', got '%s'" % quantize_mode)
 
@@ -4194,7 +4306,8 @@ kwarg for quantization."""
                         # anyway.
                         ierr = 0
                     else:
-                        ierr = nc_def_var_fill(self._grpid, self._varid, 1, NULL)
+                        with nogil:
+                            ierr = nc_def_var_fill(self._grpid, self._varid, 1, NULL)
                     if ierr != NC_NOERR:
                         if grp.data_model != 'NETCDF4': grp._enddef()
                         _ensure_nc_success(ierr)
@@ -4483,7 +4596,8 @@ attributes."""
         bytestr = _strencode(name)
         attname = bytestr
         if self._grp.data_model != 'NETCDF4': self._grp._redef()
-        ierr = nc_del_att(self._grpid, self._varid, attname)
+        with nogil:
+            ierr = nc_del_att(self._grpid, self._varid, attname)
         if self._grp.data_model != 'NETCDF4': self._grp._enddef()
         _ensure_nc_success(ierr)
 
@@ -4508,23 +4622,27 @@ return dictionary containing HDF5 filter parameters."""
             ierr = nc_inq_var_fletcher32(self._grpid, self._varid, &ifletcher32)
         _ensure_nc_success(ierr)
         IF HAS_ZSTANDARD_SUPPORT:
-            ierr = nc_inq_var_zstandard(self._grpid, self._varid, &izstd,\
-                    &icomplevel_zstd)
+            with nogil:
+                ierr = nc_inq_var_zstandard(self._grpid, self._varid, &izstd,\
+                       &icomplevel_zstd)
             if ierr != 0: izstd=0
             # _ensure_nc_success(ierr)
         IF HAS_BZIP2_SUPPORT:
-            ierr = nc_inq_var_bzip2(self._grpid, self._varid, &ibzip2,\
-                    &icomplevel_bzip2)
+            with nogil:
+                ierr = nc_inq_var_bzip2(self._grpid, self._varid, &ibzip2,\
+                       &icomplevel_bzip2)
             if ierr != 0: ibzip2=0
             #_ensure_nc_success(ierr)
         IF HAS_BLOSC_SUPPORT:
-            ierr = nc_inq_var_blosc(self._grpid, self._varid, &iblosc,\
-                    &iblosc_compressor,&iblosc_complevel,&iblosc_blocksize,&iblosc_shuffle)
+            with nogil:
+                ierr = nc_inq_var_blosc(self._grpid, self._varid, &iblosc,\
+                       &iblosc_compressor,&iblosc_complevel,&iblosc_blocksize,&iblosc_shuffle)
             if ierr != 0: iblosc=0
             #_ensure_nc_success(ierr)
         IF HAS_SZIP_SUPPORT:
-            ierr = nc_inq_var_szip(self._grpid, self._varid, &iszip_coding,\
-                    &iszip_pixels_per_block)
+            with nogil:
+                ierr = nc_inq_var_szip(self._grpid, self._varid, &iszip_coding,\
+                       &iszip_pixels_per_block)
             if ierr != 0:
                 iszip=0
             else:
@@ -4670,8 +4788,9 @@ details."""
             preemptionp = preemption
         else:
             preemptionp = preemption_orig
-        ierr = nc_set_var_chunk_cache(self._grpid, self._varid, sizep,
-               nelemsp, preemptionp)
+        with nogil:
+            ierr = nc_set_var_chunk_cache(self._grpid, self._varid, sizep,
+                   nelemsp, preemptionp)
         _ensure_nc_success(ierr)
 
     def __delattr__(self,name):
@@ -4754,7 +4873,8 @@ rename a `Variable` attribute named `oldname` to `newname`."""
         oldnamec = bytestr
         bytestr = _strencode(newname)
         newnamec = bytestr
-        ierr = nc_rename_att(self._grpid, self._varid, oldnamec, newnamec)
+        with nogil:
+            ierr = nc_rename_att(self._grpid, self._varid, oldnamec, newnamec)
         _ensure_nc_success(ierr)
 
     def __getitem__(self, elem):
@@ -5158,8 +5278,9 @@ rename a `Variable` attribute named `oldname` to `newname`."""
             encoding = getattr(self,'_Encoding','utf-8')
             bytestr = _strencode(data,encoding=encoding)
             strdata[0] = bytestr
-            ierr = nc_put_vara(self._grpid, self._varid,
-                               startp, countp, strdata)
+            with nogil:
+                ierr = nc_put_vara(self._grpid, self._varid,
+                                   startp, countp, strdata)
             _ensure_nc_success(ierr)
             free(strdata)
         else: # regular VLEN
@@ -5169,8 +5290,9 @@ rename a `Variable` attribute named `oldname` to `newname`."""
             vldata = malloc(sizeof(nc_vlen_t))
             vldata[0].len = PyArray_SIZE(data2)
             vldata[0].p = PyArray_DATA(data2)
-            ierr = nc_put_vara(self._grpid, self._varid,
-                               startp, countp, vldata)
+            with nogil:
+                ierr = nc_put_vara(self._grpid, self._varid,
+                                   startp, countp, vldata)
             _ensure_nc_success(ierr)
             free(vldata)
         free(startp)
@@ -5608,11 +5730,13 @@ NC_CHAR).
                 data = data.byteswap()
             # strides all 1 or scalar variable, use put_vara (faster)
             if sum(stride) == ndims or ndims == 0:
-                ierr = nc_put_vara(self._grpid, self._varid,
-                                   startp, countp, PyArray_DATA(data))
+                with nogil:
+                    ierr = nc_put_vara(self._grpid, self._varid,
+                                       startp, countp, PyArray_DATA(data))
             else:
-                ierr = nc_put_vars(self._grpid, self._varid,
-                                   startp, countp, stridep, PyArray_DATA(data))
+                with nogil:
+                    ierr = nc_put_vars(self._grpid, self._varid,
+                                       startp, countp, stridep, PyArray_DATA(data))
             _ensure_nc_success(ierr)
         elif self._isvlen:
             if data.dtype.char !='O':
@@ -5635,12 +5759,14 @@ NC_CHAR).
                     strdata[i] = data[i]
                 # strides all 1 or scalar variable, use put_vara (faster)
                 if sum(stride) == ndims or ndims == 0:
-                    ierr = nc_put_vara(self._grpid, self._varid,
-                                       startp, countp, strdata)
+                    with nogil:
+                        ierr = nc_put_vara(self._grpid, self._varid,
+                                           startp, countp, strdata)
                 else:
                     raise IndexError('strides must all be 1 for string variables')
-                    #ierr = nc_put_vars(self._grpid, self._varid,
-                    #                   startp, countp, stridep, strdata)
+                    #with nogil:
+                    #    ierr = nc_put_vars(self._grpid, self._varid,
+                    #                       startp, countp, stridep, strdata)
                 _ensure_nc_success(ierr)
                 free(strdata)
             else:
@@ -5662,12 +5788,14 @@ NC_CHAR).
                     databuff = databuff + PyArray_STRIDES(data)[0]
                 # strides all 1 or scalar variable, use put_vara (faster)
                 if sum(stride) == ndims or ndims == 0:
-                    ierr = nc_put_vara(self._grpid, self._varid,
-                                       startp, countp, vldata)
+                    with nogil:
+                        ierr = nc_put_vara(self._grpid, self._varid,
+                                           startp, countp, vldata)
                 else:
                     raise IndexError('strides must all be 1 for vlen variables')
-                    #ierr = nc_put_vars(self._grpid, self._varid,
-                    #                   startp, countp, stridep, vldata)
+                    #with nogil:
+                    #    ierr = nc_put_vars(self._grpid, self._varid,
+                    #                       startp, countp, stridep, vldata)
                 _ensure_nc_success(ierr)
                 # free the pointer array.
                 free(vldata)
@@ -5677,7 +5805,7 @@ NC_CHAR).
 
     def _get(self,start,count,stride):
         """Private method to retrieve data from a netCDF variable"""
-        cdef int ierr, ndims
+        cdef int ierr, ndims, totelem
         cdef size_t *startp
         cdef size_t *countp
         cdef ptrdiff_t *stridep
@@ -5756,8 +5884,9 @@ NC_CHAR).
                 else:
                     # FIXME: is this a bug in netCDF4?
                     raise IndexError('strides must all be 1 for string variables')
-                    #ierr = nc_get_vars(self._grpid, self._varid,
-                    #                   startp, countp, stridep, strdata)
+                    #with nogil:
+                    #    ierr = nc_get_vars(self._grpid, self._varid,
+                    #                       startp, countp, stridep, strdata)
                 if ierr == NC_EINVALCOORDS:
                     raise IndexError
                 elif ierr != NC_NOERR:
@@ -5775,7 +5904,8 @@ NC_CHAR).
                 # reshape the output array
                 data = numpy.reshape(data, shapeout)
                 # free string data internally allocated in netcdf C lib
-                ierr = nc_free_string(totelem, strdata)
+                with nogil:
+                    ierr = nc_free_string(totelem, strdata)
                 # free the pointer array
                 free(strdata)
             else:
@@ -5792,8 +5922,9 @@ NC_CHAR).
                                            startp, countp, vldata)
                 else:
                     raise IndexError('strides must all be 1 for vlen variables')
-                    #ierr = nc_get_vars(self._grpid, self._varid,
-                    #                   startp, countp, stridep, vldata)
+                    #with nogil:
+                    #    ierr = nc_get_vars(self._grpid, self._varid,
+                    #                       startp, countp, stridep, vldata)
                 if ierr == NC_EINVALCOORDS:
                     raise IndexError
                 elif ierr != NC_NOERR:
@@ -5809,7 +5940,8 @@ NC_CHAR).
                 # reshape the output array
                 data = numpy.reshape(data, shapeout)
                 # free vlen data internally allocated in netcdf C lib
-                ierr = nc_free_vlens(totelem, vldata)
+                with nogil:
+                    ierr = nc_free_vlens(totelem, vldata)
                 # free the pointer array
                 free(vldata)
         free(startp)
@@ -5842,11 +5974,13 @@ open for parallel access.
         IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
             # set collective MPI IO mode on or off
             if value:
-                ierr = nc_var_par_access(self._grpid, self._varid,
-                       NC_COLLECTIVE)
+                with nogil:
+                    ierr = nc_var_par_access(self._grpid, self._varid,
+                           NC_COLLECTIVE)
             else:
-                ierr = nc_var_par_access(self._grpid, self._varid,
-                       NC_INDEPENDENT)
+                with nogil:
+                    ierr = nc_var_par_access(self._grpid, self._varid,
+                           NC_INDEPENDENT)
             _ensure_nc_success(ierr)
         ELSE:
             pass # does nothing
@@ -5990,7 +6124,7 @@ def _set_viewdtype(dt):
     dtype_dict = {'names':names,'formats':formats}
     return numpy.dtype(dtype_dict, align=True)
 
-cdef _def_compound(grp, object dt, object dtype_name):
+cdef _def_compound(Group grp, object dt, object dtype_name):
     # private function used to construct a netcdf compound data type
     # from a numpy dtype object by CompoundType.__init__.
     cdef nc_type xtype, xtype_tmp
@@ -6002,7 +6136,8 @@ cdef _def_compound(grp, object dt, object dtype_name):
     bytestr = _strencode(dtype_name)
     namstring = bytestr
     size = dt.itemsize
-    ierr = nc_def_compound(grp._grpid, size, namstring, &xtype)
+    with nogil:
+        ierr = nc_def_compound(grp._grpid, size, namstring, &xtype)
     _ensure_nc_success(ierr)
     names = list(dt.fields.keys())
     formats = [v[0] for v in dt.fields.values()]
@@ -6020,8 +6155,9 @@ cdef _def_compound(grp, object dt, object dtype_name):
                 xtype_tmp = _nptonctype[format.str[1:]]
             except KeyError:
                 raise ValueError('Unsupported compound type element')
-            ierr = nc_insert_compound(grp._grpid, xtype, namstring,
-                                      offset, xtype_tmp)
+            with nogil:
+                ierr = nc_insert_compound(grp._grpid, xtype, namstring,
+                                          offset, xtype_tmp)
             _ensure_nc_success(ierr)
         else:
             if format.shape ==  (): # nested scalar compound type
@@ -6029,8 +6165,9 @@ cdef _def_compound(grp, object dt, object dtype_name):
                 xtype_tmp = _find_cmptype(grp, format)
                 bytestr = _strencode(name)
                 nested_namstring = bytestr
-                ierr = nc_insert_compound(grp._grpid, xtype,\
-                                          nested_namstring,\
+                with nogil:
+                    ierr = nc_insert_compound(grp._grpid, xtype,\
+                                              nested_namstring,\
                                           offset, xtype_tmp)
                 _ensure_nc_success(ierr)
             else: # nested array compound element
@@ -6043,7 +6180,8 @@ cdef _def_compound(grp, object dt, object dtype_name):
                         xtype_tmp = _nptonctype[format.subdtype[0].str[1:]]
                     except KeyError:
                         raise ValueError('Unsupported compound type element')
-                    ierr = nc_insert_array_compound(grp._grpid,xtype,namstring,
+                    with nogil:
+                        ierr = nc_insert_array_compound(grp._grpid,xtype,namstring,
                            offset,xtype_tmp,ndims,dim_sizes)
                     _ensure_nc_success(ierr)
                 else: # nested array compound type.
@@ -6054,10 +6192,11 @@ cdef _def_compound(grp, object dt, object dtype_name):
                 #   xtype_tmp = _find_cmptype(grp, format.subdtype[0])
                 #   bytestr = _strencode(name)
                 #   nested_namstring = bytestr
-                #   ierr = nc_insert_array_compound(grp._grpid,xtype,\
-                #                                   nested_namstring,\
-                #                                   offset,xtype_tmp,\
-                #                                   ndims,dim_sizes)
+                #   with nogil:
+                #       ierr = nc_insert_array_compound(grp._grpid,xtype,\
+                #                                       nested_namstring,\
+                #                                       offset,xtype_tmp,\
+                #                                       ndims,dim_sizes)
                 #   _ensure_nc_success(ierr)
                 free(dim_sizes)
     return xtype
@@ -6227,7 +6366,7 @@ the user.
         # raise error is user tries to pickle a VLType object.
         raise NotImplementedError('VLType is not picklable')
 
-cdef _def_vlen(grp, object dt, object dtype_name):
+cdef _def_vlen(Group grp, object dt, object dtype_name):
     # private function used to construct a netcdf VLEN data type
     # from a numpy dtype object or python str object by VLType.__init__.
     cdef nc_type xtype, xtype_tmp
@@ -6246,13 +6385,14 @@ cdef _def_vlen(grp, object dt, object dtype_name):
             # find netCDF primitive data type corresponding to
             # specified numpy data type.
             xtype_tmp = _nptonctype[dt.str[1:]]
-            ierr = nc_def_vlen(grp._grpid, namstring, xtype_tmp, &xtype);
+            with nogil:
+                ierr = nc_def_vlen(grp._grpid, namstring, xtype_tmp, &xtype);
             _ensure_nc_success(ierr)
         else:
             raise KeyError("unsupported datatype specified for VLEN")
     return xtype, dt
 
-cdef _read_vlen(group, nc_type xtype, endian=None):
+cdef _read_vlen(Group group, nc_type xtype, endian=None):
     # read a VLEN data type id from an existing file,
     # construct a corresponding numpy dtype instance,
     # then use that to create a VLType instance.
@@ -6334,7 +6474,7 @@ the user.
         # raise error is user tries to pickle a EnumType object.
         raise NotImplementedError('EnumType is not picklable')
 
-cdef _def_enum(grp, object dt, object dtype_name, object enum_dict):
+cdef _def_enum(Group grp, object dt, object dtype_name, object enum_dict):
     # private function used to construct a netCDF Enum data type
     # from a numpy dtype object or python str object by EnumType.__init__.
     cdef nc_type xtype, xtype_tmp
@@ -6348,7 +6488,8 @@ cdef _def_enum(grp, object dt, object dtype_name, object enum_dict):
         # find netCDF primitive data type corresponding to
         # specified numpy data type.
         xtype_tmp = _intnptonctype[dt.str[1:]]
-        ierr = nc_def_enum(grp._grpid, xtype_tmp, namstring, &xtype);
+        with nogil:
+            ierr = nc_def_enum(grp._grpid, xtype_tmp, namstring, &xtype)
         _ensure_nc_success(ierr)
     else:
         msg="unsupported datatype specified for ENUM (must be integer)"
@@ -6358,12 +6499,13 @@ cdef _def_enum(grp, object dt, object dtype_name, object enum_dict):
         value_arr = numpy.array(enum_dict[field],dt)
         bytestr = _strencode(field)
         namstring = bytestr
-        ierr = nc_insert_enum(grp._grpid, xtype, namstring,
-                PyArray_DATA(value_arr))
+        with nogil:
+            ierr = nc_insert_enum(grp._grpid, xtype, namstring,
+                   PyArray_DATA(value_arr))
         _ensure_nc_success(ierr)
     return xtype, dt
 
-cdef _read_enum(group, nc_type xtype, endian=None):
+cdef _read_enum(Group group, nc_type xtype, endian=None):
     # read a Enum data type id from an existing file,
     # construct a corresponding numpy dtype instance,
     # then use that to create a EnumType instance.

From ec9000a35542be2f236532a17948c73ec6ba877c Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 9 Aug 2022 08:34:25 -0600
Subject: [PATCH 0865/1504] more nogil fixes

---
 include/netCDF4.pxi      | 54 ++++++++++++++--------------
 src/netCDF4/_netCDF4.pyx | 77 +++++++++++++++++++++-------------------
 2 files changed, 68 insertions(+), 63 deletions(-)

diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index 97e18c963..e78ceb1d3 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -289,18 +289,18 @@ cdef extern from "netcdf.h":
                 size_t *countp, void *ip) nogil
     int nc_put_vars(int ncid, int varid,  size_t *startp, 
                 size_t *countp, ptrdiff_t *stridep,
-                void *op)  nogil
+                void *op) nogil
     int nc_get_vars(int ncid, int varid,  size_t *startp, 
                 size_t *countp, ptrdiff_t *stridep,
                 void *ip) nogil
     int nc_put_varm(int ncid, int varid,  size_t *startp, 
                 size_t *countp, ptrdiff_t *stridep,
-                ptrdiff_t *imapp, void *op)
+                ptrdiff_t *imapp, void *op) nogil
     int nc_get_varm(int ncid, int varid,  size_t *startp, 
                 size_t *countp, ptrdiff_t *stridep,
-                ptrdiff_t *imapp, void *ip)
-    int nc_put_var(int ncid, int varid,  void *op)
-    int nc_get_var(int ncid, int varid,  void *ip)
+                ptrdiff_t *imapp, void *ip) nogil
+    int nc_put_var(int ncid, int varid,  void *op) nogil
+    int nc_get_var(int ncid, int varid,  void *ip) nogil
     int nc_def_var_deflate(int ncid, int varid, int shuffle, int deflate, 
 	           	   int deflate_level) nogil
     int nc_def_var_fletcher32(int ncid, int varid, int fletcher32) nogil
@@ -348,39 +348,39 @@ cdef extern from "netcdf.h":
                     size_t len, char *op) nogil
     int nc_get_att_text(int ncid, int varid, char *name, char *ip) nogil
     int nc_put_att_uchar(int ncid, int varid, char *name, nc_type xtype,
-                     size_t len, unsigned char *op)
-    int nc_get_att_uchar(int ncid, int varid, char *name, unsigned char *ip)
+                     size_t len, unsigned char *op) nogil
+    int nc_get_att_uchar(int ncid, int varid, char *name, unsigned char *ip) nogil
     int nc_put_att_schar(int ncid, int varid, char *name, nc_type xtype,
-                     size_t len, signed char *op)
-    int nc_get_att_schar(int ncid, int varid, char *name, signed char *ip)
+                     size_t len, signed char *op) nogil
+    int nc_get_att_schar(int ncid, int varid, char *name, signed char *ip) nogil
     int nc_put_att_short(int ncid, int varid, char *name, nc_type xtype,
-                     size_t len, short *op)
-    int nc_get_att_short(int ncid, int varid, char *name, short *ip)
+                     size_t len, short *op) nogil
+    int nc_get_att_short(int ncid, int varid, char *name, short *ip) nogil
     int nc_put_att_int(int ncid, int varid, char *name, nc_type xtype,
-                   size_t len, int *op)
-    int nc_get_att_int(int ncid, int varid, char *name, int *ip)
+                   size_t len, int *op) nogil
+    int nc_get_att_int(int ncid, int varid, char *name, int *ip) nogil
     int nc_put_att_long(int ncid, int varid, char *name, nc_type xtype,
-                    size_t len, long *op)
-    int nc_get_att_long(int ncid, int varid, char *name, long *ip)
+                    size_t len, long *op) nogil
+    int nc_get_att_long(int ncid, int varid, char *name, long *ip) nogil
     int nc_put_att_float(int ncid, int varid, char *name, nc_type xtype,
-                     size_t len, float *op)
-    int nc_get_att_float(int ncid, int varid, char *name, float *ip)
+                     size_t len, float *op) nogil
+    int nc_get_att_float(int ncid, int varid, char *name, float *ip) nogil
     int nc_put_att_double(int ncid, int varid, char *name, nc_type xtype,
-                      size_t len, double *op)
-    int nc_get_att_double(int ncid, int varid, char *name, double *ip)
+                      size_t len, double *op) nogil
+    int nc_get_att_double(int ncid, int varid, char *name, double *ip) nogil
     int nc_put_att_ushort(int ncid, int varid, char *name, nc_type xtype,
-                      size_t len, unsigned short *op)
-    int nc_get_att_ushort(int ncid, int varid, char *name, unsigned short *ip)
+                      size_t len, unsigned short *op) nogil
+    int nc_get_att_ushort(int ncid, int varid, char *name, unsigned short *ip) nogil
     int nc_put_att_uint(int ncid, int varid, char *name, nc_type xtype,
-                    size_t len, unsigned int *op)
-    int nc_get_att_uint(int ncid, int varid, char *name, unsigned int *ip)
+                    size_t len, unsigned int *op) nogil
+    int nc_get_att_uint(int ncid, int varid, char *name, unsigned int *ip) nogil
     int nc_put_att_longlong(int ncid, int varid, char *name, nc_type xtype,
-                     size_t len, long long *op)
-    int nc_get_att_longlong(int ncid, int varid, char *name, long long *ip)
+                     size_t len, long long *op) nogil
+    int nc_get_att_longlong(int ncid, int varid, char *name, long long *ip) nogil
     int nc_put_att_ulonglong(int ncid, int varid, char *name, nc_type xtype,
-                         size_t len, unsigned long long *op)
+                         size_t len, unsigned long long *op) nogil
     int nc_get_att_ulonglong(int ncid, int varid, char *name, 
-                         unsigned long long *ip)
+                         unsigned long long *ip) nogil
     int nc_def_var(int ncid, char *name, nc_type xtype, int ndims, 
                int *dimidsp, int *varidp) nogil
     int nc_inq_var(int ncid, int varid, char *name, nc_type *xtypep, 
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 0d2cf6274..c8b15b2db 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1612,16 +1612,17 @@ cdef issue485_workaround(int grpid, int varid, char* attname):
         _ensure_nc_success(ierr)
 
 
-cdef _set_att(Group grp, int varid, name, value,\
+cdef _set_att(grp, int varid, name, value,\
               nc_type xtype=-99, force_ncstring=False):
     # Private function to set an attribute name/value pair
-    cdef int ierr, lenarr, N
+    cdef int ierr, lenarr, N, grpid
     cdef char *attname
     cdef char *datstring
     cdef char **string_ptrs
     cdef ndarray value_arr
     bytestr = _strencode(name)
     attname = bytestr
+    grpid = grp._grpid
     # put attribute value into a numpy array.
     value_arr = numpy.array(value)
     if value_arr.ndim > 1: # issue #841
@@ -1635,7 +1636,7 @@ be raised in the next release."""
             warnings.warn(msg,FutureWarning)
     # if array is 64 bit integers or
     # if 64-bit datatype not supported, cast to 32 bit integers.
-    fmt = _get_format(grp._grpid)
+    fmt = _get_format(grpid)
     is_netcdf3 = fmt.startswith('NETCDF3') or fmt == 'NETCDF4_CLASSIC'
     if value_arr.dtype.str[1:] == 'i8' and ('i8' not in _supportedtypes or\
        (is_netcdf3 and fmt != 'NETCDF3_64BIT_DATA')):
@@ -1657,9 +1658,9 @@ be raised in the next release."""
                     if len(strings[j]) == 0:
                         strings[j] = _strencode('\x00')
                     string_ptrs[j] = strings[j]
-                issue485_workaround(grp._grpid, varid, attname)
+                issue485_workaround(grpid, varid, attname)
                 with nogil:
-                    ierr = nc_put_att_string(grp._grpid, varid, attname, N, string_ptrs)
+                    ierr = nc_put_att_string(grpid, varid, attname, N, string_ptrs)
             finally:
                 PyMem_Free(string_ptrs)
         else:
@@ -1684,14 +1685,14 @@ be raised in the next release."""
                     if force_ncstring: raise UnicodeError
                     dats_ascii = _to_ascii(dats) # try to encode bytes as ascii string
                     with nogil:
-                        ierr = nc_put_att_text(grp._grpid, varid, attname, lenarr, datstring)
+                        ierr = nc_put_att_text(grpid, varid, attname, lenarr, datstring)
                 except UnicodeError:
-                    issue485_workaround(grp._grpid, varid, attname)
+                    issue485_workaround(grpid, varid, attname)
                     with nogil:
-                        ierr = nc_put_att_string(grp._grpid, varid, attname, 1, &datstring)
+                        ierr = nc_put_att_string(grpid, varid, attname, 1, &datstring)
             else:
                 with nogil:
-                    ierr = nc_put_att_text(grp._grpid, varid, attname, lenarr, datstring)
+                    ierr = nc_put_att_text(grpid, varid, attname, lenarr, datstring)
         _ensure_nc_success(ierr, err_cls=AttributeError)
     # a 'regular' array type ('f4','i4','f8' etc)
     else:
@@ -1703,7 +1704,7 @@ be raised in the next release."""
             xtype = _nptonctype[value_arr.dtype.str[1:]]
         lenarr = PyArray_SIZE(value_arr)
         with nogil:
-            ierr = nc_put_att(grp._grpid, varid, attname, xtype, lenarr,
+            ierr = nc_put_att(grpid, varid, attname, xtype, lenarr,
                 PyArray_DATA(value_arr))
         _ensure_nc_success(ierr, err_cls=AttributeError)
 
@@ -3113,17 +3114,18 @@ rename a `Dataset` or `Group` attribute named `oldname` to `newname`."""
 
 rename a `Group` named `oldname` to `newname` (requires netcdf >= 4.3.1)."""
         cdef char *newnamec
-        cdef Group grp
+        cdef int grpid
         IF HAS_RENAME_GRP:
             cdef int ierr
             bytestr = _strencode(newname)
             newnamec = bytestr
             try:
                 grp = self.groups[oldname]
+                grpid = grp._grpid
             except KeyError:
                 raise KeyError('%s not a valid group name' % oldname)
             with nogil:
-                ierr = nc_rename_grp(grp._grpid, newnamec)
+                ierr = nc_rename_grp(grpid, newnamec)
             _ensure_nc_success(ierr)
             # remove old key from groups dict.
             self.groups.pop(oldname)
@@ -6124,11 +6126,11 @@ def _set_viewdtype(dt):
     dtype_dict = {'names':names,'formats':formats}
     return numpy.dtype(dtype_dict, align=True)
 
-cdef _def_compound(Group grp, object dt, object dtype_name):
+cdef _def_compound(grp, object dt, object dtype_name):
     # private function used to construct a netcdf compound data type
     # from a numpy dtype object by CompoundType.__init__.
     cdef nc_type xtype, xtype_tmp
-    cdef int ierr, ndims
+    cdef int ierr, ndims, grpid
     cdef size_t offset, size
     cdef char *namstring
     cdef char *nested_namstring
@@ -6136,8 +6138,9 @@ cdef _def_compound(Group grp, object dt, object dtype_name):
     bytestr = _strencode(dtype_name)
     namstring = bytestr
     size = dt.itemsize
+    grpid = grp._grpid
     with nogil:
-        ierr = nc_def_compound(grp._grpid, size, namstring, &xtype)
+        ierr = nc_def_compound(grpid, size, namstring, &xtype)
     _ensure_nc_success(ierr)
     names = list(dt.fields.keys())
     formats = [v[0] for v in dt.fields.values()]
@@ -6156,7 +6159,7 @@ cdef _def_compound(Group grp, object dt, object dtype_name):
             except KeyError:
                 raise ValueError('Unsupported compound type element')
             with nogil:
-                ierr = nc_insert_compound(grp._grpid, xtype, namstring,
+                ierr = nc_insert_compound(grpid, xtype, namstring,
                                           offset, xtype_tmp)
             _ensure_nc_success(ierr)
         else:
@@ -6166,9 +6169,9 @@ cdef _def_compound(Group grp, object dt, object dtype_name):
                 bytestr = _strencode(name)
                 nested_namstring = bytestr
                 with nogil:
-                    ierr = nc_insert_compound(grp._grpid, xtype,\
+                    ierr = nc_insert_compound(grpid, xtype,\
                                               nested_namstring,\
-                                          offset, xtype_tmp)
+                                              offset, xtype_tmp)
                 _ensure_nc_success(ierr)
             else: # nested array compound element
                 ndims = len(format.shape)
@@ -6181,7 +6184,7 @@ cdef _def_compound(Group grp, object dt, object dtype_name):
                     except KeyError:
                         raise ValueError('Unsupported compound type element')
                     with nogil:
-                        ierr = nc_insert_array_compound(grp._grpid,xtype,namstring,
+                        ierr = nc_insert_array_compound(grpid,xtype,namstring,
                            offset,xtype_tmp,ndims,dim_sizes)
                     _ensure_nc_success(ierr)
                 else: # nested array compound type.
@@ -6193,7 +6196,7 @@ cdef _def_compound(Group grp, object dt, object dtype_name):
                 #   bytestr = _strencode(name)
                 #   nested_namstring = bytestr
                 #   with nogil:
-                #       ierr = nc_insert_array_compound(grp._grpid,xtype,\
+                #       ierr = nc_insert_array_compound(grpid,xtype,\
                 #                                       nested_namstring,\
                 #                                       offset,xtype_tmp,\
                 #                                       ndims,dim_sizes)
@@ -6366,14 +6369,15 @@ the user.
         # raise error is user tries to pickle a VLType object.
         raise NotImplementedError('VLType is not picklable')
 
-cdef _def_vlen(Group grp, object dt, object dtype_name):
+cdef _def_vlen(grp, object dt, object dtype_name):
     # private function used to construct a netcdf VLEN data type
     # from a numpy dtype object or python str object by VLType.__init__.
     cdef nc_type xtype, xtype_tmp
-    cdef int ierr, ndims
+    cdef int ierr, ndims, grpid
     cdef size_t offset, size
     cdef char *namstring
     cdef char *nested_namstring
+    grpid = grp._grpid
     if dt == str: # python string, use NC_STRING
         xtype = NC_STRING
         # dtype_name ignored
@@ -6386,28 +6390,28 @@ cdef _def_vlen(Group grp, object dt, object dtype_name):
             # specified numpy data type.
             xtype_tmp = _nptonctype[dt.str[1:]]
             with nogil:
-                ierr = nc_def_vlen(grp._grpid, namstring, xtype_tmp, &xtype);
+                ierr = nc_def_vlen(grpid, namstring, xtype_tmp, &xtype);
             _ensure_nc_success(ierr)
         else:
             raise KeyError("unsupported datatype specified for VLEN")
     return xtype, dt
 
-cdef _read_vlen(Group group, nc_type xtype, endian=None):
+cdef _read_vlen(group, nc_type xtype, endian=None):
     # read a VLEN data type id from an existing file,
     # construct a corresponding numpy dtype instance,
     # then use that to create a VLType instance.
     # called by _get_types, _get_vars.
-    cdef int ierr, _grpid
+    cdef int ierr, grpid
     cdef size_t vlsize
     cdef nc_type base_xtype
     cdef char vl_namstring[NC_MAX_NAME+1]
-    _grpid = group._grpid
+    grpid = group._grpid
     if xtype == NC_STRING:
         dt = str
         name = None
     else:
         with nogil:
-            ierr = nc_inq_vlen(_grpid, xtype, vl_namstring, &vlsize, &base_xtype)
+            ierr = nc_inq_vlen(grpid, xtype, vl_namstring, &vlsize, &base_xtype)
         _ensure_nc_success(ierr)
         name = vl_namstring.decode('utf-8')
         try:
@@ -6474,22 +6478,23 @@ the user.
         # raise error is user tries to pickle a EnumType object.
         raise NotImplementedError('EnumType is not picklable')
 
-cdef _def_enum(Group grp, object dt, object dtype_name, object enum_dict):
+cdef _def_enum(grp, object dt, object dtype_name, object enum_dict):
     # private function used to construct a netCDF Enum data type
     # from a numpy dtype object or python str object by EnumType.__init__.
     cdef nc_type xtype, xtype_tmp
-    cdef int ierr
+    cdef int ierr, grpid
     cdef char *namstring
     cdef ndarray value_arr
     bytestr = _strencode(dtype_name)
     namstring = bytestr
+    grpid = grp._grpid
     dt = numpy.dtype(dt) # convert to numpy datatype.
     if dt.str[1:] in _intnptonctype.keys():
         # find netCDF primitive data type corresponding to
         # specified numpy data type.
         xtype_tmp = _intnptonctype[dt.str[1:]]
         with nogil:
-            ierr = nc_def_enum(grp._grpid, xtype_tmp, namstring, &xtype)
+            ierr = nc_def_enum(grpid, xtype_tmp, namstring, &xtype)
         _ensure_nc_success(ierr)
     else:
         msg="unsupported datatype specified for ENUM (must be integer)"
@@ -6500,25 +6505,25 @@ cdef _def_enum(Group grp, object dt, object dtype_name, object enum_dict):
         bytestr = _strencode(field)
         namstring = bytestr
         with nogil:
-            ierr = nc_insert_enum(grp._grpid, xtype, namstring,
+            ierr = nc_insert_enum(grpid, xtype, namstring,
                    PyArray_DATA(value_arr))
         _ensure_nc_success(ierr)
     return xtype, dt
 
-cdef _read_enum(Group group, nc_type xtype, endian=None):
+cdef _read_enum(group, nc_type xtype, endian=None):
     # read a Enum data type id from an existing file,
     # construct a corresponding numpy dtype instance,
     # then use that to create a EnumType instance.
     # called by _get_types, _get_vars.
-    cdef int ierr, _grpid, nmem
+    cdef int ierr, grpid, nmem
     cdef ndarray enum_val
     cdef nc_type base_xtype
     cdef char enum_namstring[NC_MAX_NAME+1]
     cdef size_t nmembers
-    _grpid = group._grpid
+    grpid = group._grpid
     # get name, datatype, and number of members.
     with nogil:
-        ierr = nc_inq_enum(_grpid, xtype, enum_namstring, &base_xtype, NULL,\
+        ierr = nc_inq_enum(grpid, xtype, enum_namstring, &base_xtype, NULL,\
                 &nmembers)
     _ensure_nc_success(ierr)
     enum_name = enum_namstring.decode('utf-8')
@@ -6533,7 +6538,7 @@ cdef _read_enum(Group group, nc_type xtype, endian=None):
     enum_val = numpy.empty(1,dt)
     for nmem from 0 <= nmem < nmembers:
         with nogil:
-            ierr = nc_inq_enum_member(_grpid, xtype, nmem, \
+            ierr = nc_inq_enum_member(grpid, xtype, nmem, \
                                       enum_namstring,PyArray_DATA(enum_val))
         _ensure_nc_success(ierr)
         name = enum_namstring.decode('utf-8')

From 00ef99f00d9cb2a213ccad35aa9b7b1b7d5230bb Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 9 Aug 2022 10:14:38 -0600
Subject: [PATCH 0866/1504] clean up function prototypes, add Changelog entry

---
 Changelog           |   3 +-
 include/netCDF4.pxi | 302 ++------------------------------------------
 2 files changed, 15 insertions(+), 290 deletions(-)

diff --git a/Changelog b/Changelog
index 2c673e30e..6fb7a676c 100644
--- a/Changelog
+++ b/Changelog
@@ -1,7 +1,8 @@
  since version 1.6.0 release
 ==============================
  * add Dataset methods has__filter (where =zstd,blosc,bzip2,szip)
- to check for availability of extra compression filters.
+   to check for availability of extra compression filters.
+ * release GIL for all C-lib calls (issue #1180).
 
  version 1.6.0 (tag v1.6.0rel)
 ==============================
diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index e78ceb1d3..c81d681c2 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -6,7 +6,7 @@ cdef extern from "stdlib.h":
 # hdf5 version info.
 cdef extern from "H5public.h":
     ctypedef int herr_t
-    int H5get_libversion( unsigned int *majnum, unsigned int *minnum, unsigned int *relnum )
+    int H5get_libversion( unsigned int *majnum, unsigned int *minnum, unsigned int *relnum ) nogil
  
 cdef extern from *:
     ctypedef char* const_char_ptr "const char*"
@@ -269,20 +269,20 @@ cdef extern from "netcdf.h":
     int nc_get_att(int ncid, int varid, char *name, void *ip) nogil
     int nc_get_att_string(int ncid, int varid, char *name, char **ip) nogil
     int nc_put_att_string(int ncid, int varid, char *name, size_t len, char **op) nogil
-    int nc_def_opaque(int ncid, size_t size, char *name, nc_type *xtypep)
-    int nc_inq_opaque(int ncid, nc_type xtype, char *name, size_t *sizep)
+    int nc_def_opaque(int ncid, size_t size, char *name, nc_type *xtypep) nogil
+    int nc_inq_opaque(int ncid, nc_type xtype, char *name, size_t *sizep) nogil
     int nc_put_att_opaque(int ncid, int varid, char *name,
-                      size_t len, void *op)
+                      size_t len, void *op) nogil
     int nc_get_att_opaque(int ncid, int varid, char *name, 
-                      void *ip)
+                      void *ip) nogil
     int nc_put_cmp_att_opaque(int ncid, nc_type xtype, int fieldid, 
-                          char *name, size_t len, void *op)
+                          char *name, size_t len, void *op) nogil
     int nc_get_cmp_att_opaque(int ncid, nc_type xtype, int fieldid, 
-                          char *name, void *ip)
+                          char *name, void *ip) nogil
     int nc_put_var1(int ncid, int varid, size_t *indexp,
-                void *op)
+                void *op) nogil
     int nc_get_var1(int ncid, int varid,  size_t *indexp,
-                void *ip)
+                void *ip) nogil
     int nc_put_vara(int ncid, int varid,  size_t *startp, 
                 size_t *countp, void *op) nogil
     int nc_get_vara(int ncid, int varid,  size_t *startp, 
@@ -392,283 +392,7 @@ cdef extern from "netcdf.h":
     int nc_inq_vardimid(int ncid, int varid, int *dimidsp) nogil
     int nc_inq_varnatts(int ncid, int varid, int *nattsp) nogil
     int nc_rename_var(int ncid, int varid, char *name) nogil
-    int nc_copy_var(int ncid_in, int varid, int ncid_out)
-    int nc_put_var1_text(int ncid, int varid, size_t *indexp, char *op)
-    int nc_get_var1_text(int ncid, int varid, size_t *indexp, char *ip)
-    int nc_put_var1_uchar(int ncid, int varid, size_t *indexp,
-                      unsigned char *op)
-    int nc_get_var1_uchar(int ncid, int varid, size_t *indexp,
-                      unsigned char *ip)
-    int nc_put_var1_schar(int ncid, int varid, size_t *indexp,
-                      signed char *op)
-    int nc_get_var1_schar(int ncid, int varid, size_t *indexp,
-                      signed char *ip)
-    int nc_put_var1_short(int ncid, int varid, size_t *indexp,
-                      short *op)
-    int nc_get_var1_short(int ncid, int varid, size_t *indexp,
-                      short *ip)
-    int nc_put_var1_int(int ncid, int varid, size_t *indexp, int *op)
-    int nc_get_var1_int(int ncid, int varid, size_t *indexp, int *ip)
-    int nc_put_var1_long(int ncid, int varid, size_t *indexp, long *op)
-    int nc_get_var1_long(int ncid, int varid, size_t *indexp, long *ip)
-    int nc_put_var1_float(int ncid, int varid, size_t *indexp, float *op)
-    int nc_get_var1_float(int ncid, int varid, size_t *indexp, float *ip)
-    int nc_put_var1_double(int ncid, int varid, size_t *indexp, double *op)
-    int nc_get_var1_double(int ncid, int varid, size_t *indexp, double *ip)
-    int nc_put_var1_ubyte(int ncid, int varid, size_t *indexp, 
-                      unsigned char *op)
-    int nc_get_var1_ubyte(int ncid, int varid, size_t *indexp, 
-                      unsigned char *ip)
-    int nc_put_var1_ushort(int ncid, int varid, size_t *indexp, 
-                       unsigned short *op)
-    int nc_get_var1_ushort(int ncid, int varid, size_t *indexp, 
-                       unsigned short *ip)
-    int nc_put_var1_uint(int ncid, int varid, size_t *indexp, 
-                     unsigned int *op)
-    int nc_get_var1_uint(int ncid, int varid, size_t *indexp, 
-                     unsigned int *ip)
-    int nc_put_var1_longlong(int ncid, int varid, size_t *indexp, 
-                         long long *op)
-    int nc_get_var1_longlong(int ncid, int varid, size_t *indexp, 
-                      long long *ip)
-    int nc_put_var1_ulonglong(int ncid, int varid, size_t *indexp, 
-                       unsigned long long *op)
-    int nc_get_var1_ulonglong(int ncid, int varid, size_t *indexp, 
-                       unsigned long long *ip)
-    int nc_put_vara_text(int ncid, int varid,
-            size_t *startp, size_t *countp, char *op)
-    int nc_get_vara_text(int ncid, int varid,
-            size_t *startp, size_t *countp, char *ip)
-    int nc_put_vara_uchar(int ncid, int varid,
-            size_t *startp, size_t *countp, unsigned char *op)
-    int nc_get_vara_uchar(int ncid, int varid, size_t *startp, 
-                      size_t *countp, unsigned char *ip)
-    int nc_put_vara_schar(int ncid, int varid, size_t *startp, 
-                      size_t *countp, signed char *op)
-    int nc_get_vara_schar(int ncid, int varid, size_t *startp, 
-                      size_t *countp, signed char *ip)
-    int nc_put_vara_short(int ncid, int varid, size_t *startp, 
-                      size_t *countp, short *op)
-    int nc_get_vara_short(int ncid, int varid, size_t *startp, 
-                      size_t *countp, short *ip)
-    int nc_put_vara_int(int ncid, int varid, size_t *startp, 
-                    size_t *countp, int *op)
-    int nc_get_vara_int(int ncid, int varid, size_t *startp, 
-                    size_t *countp, int *ip)
-    int nc_put_vara_long(int ncid, int varid, size_t *startp, 
-                     size_t *countp, long *op)
-    int nc_get_vara_long(int ncid, int varid,
-            size_t *startp, size_t *countp, long *ip)
-    int nc_put_vara_float(int ncid, int varid,
-            size_t *startp, size_t *countp, float *op)
-    int nc_get_vara_float(int ncid, int varid,
-            size_t *startp, size_t *countp, float *ip)
-    int nc_put_vara_double(int ncid, int varid, size_t *startp, 
-                       size_t *countp, double *op)
-    int nc_get_vara_double(int ncid, int varid, size_t *startp, 
-                       size_t *countp, double *ip)
-    int nc_put_vara_ubyte(int ncid, int varid, size_t *startp, 
-                      size_t *countp, unsigned char *op)
-    int nc_get_vara_ubyte(int ncid, int varid, size_t *startp, 
-                      size_t *countp, unsigned char *ip)
-    int nc_put_vara_ushort(int ncid, int varid, size_t *startp, 
-                       size_t *countp, unsigned short *op)
-    int nc_get_vara_ushort(int ncid, int varid, size_t *startp, 
-                       size_t *countp, unsigned short *ip)
-    int nc_put_vara_uint(int ncid, int varid, size_t *startp, 
-                     size_t *countp, unsigned int *op)
-    int nc_get_vara_uint(int ncid, int varid, size_t *startp, 
-                     size_t *countp, unsigned int *ip)
-    int nc_put_vara_longlong(int ncid, int varid, size_t *startp, 
-                      size_t *countp, long long *op)
-    int nc_get_vara_longlong(int ncid, int varid, size_t *startp, 
-                      size_t *countp, long long *ip)
-    int nc_put_vara_ulonglong(int ncid, int varid, size_t *startp, 
-                       size_t *countp, unsigned long long *op)
-    int nc_get_vara_ulonglong(int ncid, int varid, size_t *startp, 
-                       size_t *countp, unsigned long long *ip)
-    int nc_put_vars_text(int ncid, int varid,
-            size_t *startp, size_t *countp, ptrdiff_t *stridep,
-            char *op)
-    int nc_get_vars_text(int ncid, int varid,
-            size_t *startp, size_t *countp, ptrdiff_t *stridep,
-            char *ip)
-    int nc_put_vars_uchar(int ncid, int varid,
-            size_t *startp, size_t *countp, ptrdiff_t *stridep,
-            unsigned char *op)
-    int nc_get_vars_uchar(int ncid, int varid,
-            size_t *startp, size_t *countp, ptrdiff_t *stridep,
-            unsigned char *ip)
-    int nc_put_vars_schar(int ncid, int varid,
-            size_t *startp, size_t *countp, ptrdiff_t *stridep,
-            signed char *op)
-    int nc_get_vars_schar(int ncid, int varid,
-            size_t *startp, size_t *countp, ptrdiff_t *stridep,
-            signed char *ip)
-    int nc_put_vars_short(int ncid, int varid,
-            size_t *startp, size_t *countp, ptrdiff_t *stridep,
-            short *op)
-    int nc_get_vars_short(int ncid, int varid, size_t *startp, 
-                      size_t *countp, ptrdiff_t *stridep,
-                      short *ip)
-    int nc_put_vars_int(int ncid, int varid,
-            size_t *startp, size_t *countp, ptrdiff_t *stridep,
-            int *op)
-    int nc_get_vars_int(int ncid, int varid,
-            size_t *startp, size_t *countp, ptrdiff_t *stridep,
-            int *ip)
-    int nc_put_vars_long(int ncid, int varid,
-            size_t *startp, size_t *countp, ptrdiff_t *stridep,
-            long *op) 
-    int nc_get_vars_long(int ncid, int varid,
-            size_t *startp, size_t *countp, ptrdiff_t *stridep,
-            long *ip)
-    int nc_put_vars_float(int ncid, int varid,
-            size_t *startp, size_t *countp, ptrdiff_t *stridep,
-            float *op) 
-    int nc_get_vars_float(int ncid, int varid,
-            size_t *startp, size_t *countp, ptrdiff_t *stridep,
-            float *ip)
-    int nc_put_vars_double(int ncid, int varid,
-            size_t *startp, size_t *countp, ptrdiff_t *stridep,
-            double *op)
-    int nc_get_vars_double(int ncid, int varid, size_t *startp, 
-                       size_t *countp, ptrdiff_t *stridep,
-                       double *ip)
-    int nc_put_vars_ubyte(int ncid, int varid, size_t *startp, 
-                      size_t *countp, ptrdiff_t *stridep, 
-                      unsigned char *op)
-    int nc_get_vars_ubyte(int ncid, int varid, size_t *startp, 
-                      size_t *countp, ptrdiff_t *stridep, 
-                      unsigned char *ip)
-    int nc_put_vars_ushort(int ncid, int varid, size_t *startp, 
-                       size_t *countp, ptrdiff_t *stridep, 
-                       unsigned short *op)
-    int nc_get_vars_ushort(int ncid, int varid, size_t *startp, 
-                       size_t *countp, ptrdiff_t *stridep, 
-                       unsigned short *ip)
-    int nc_put_vars_uint(int ncid, int varid, size_t *startp, 
-                     size_t *countp, ptrdiff_t *stridep, 
-                     unsigned int *op)
-    int nc_get_vars_uint(int ncid, int varid, size_t *startp, 
-                     size_t *countp, ptrdiff_t *stridep, 
-                     unsigned int *ip)
-    int nc_put_vars_longlong(int ncid, int varid, size_t *startp, 
-                      size_t *countp, ptrdiff_t *stridep, 
-                      long long *op)
-    int nc_get_vars_longlong(int ncid, int varid, size_t *startp, 
-                      size_t *countp, ptrdiff_t *stridep, 
-                      long long *ip)
-    int nc_put_vars_ulonglong(int ncid, int varid, size_t *startp, 
-                       size_t *countp, ptrdiff_t *stridep, 
-                       unsigned long long *op)
-    int nc_get_vars_ulonglong(int ncid, int varid, size_t *startp, 
-                       size_t *countp, ptrdiff_t *stridep, 
-                       unsigned long long *ip)
-    int nc_put_varm_text(int ncid, int varid, size_t *startp, 
-                     size_t *countp, ptrdiff_t *stridep,
-                     ptrdiff_t *imapp, char *op)
-    int nc_get_varm_text(int ncid, int varid, size_t *startp, 
-                     size_t *countp, ptrdiff_t *stridep,
-                     ptrdiff_t *imapp, char *ip)
-    int nc_put_varm_uchar(int ncid, int varid, size_t *startp, 
-                      size_t *countp, ptrdiff_t *stridep,
-                      ptrdiff_t *imapp, unsigned char *op)
-    int nc_get_varm_uchar(int ncid, int varid, size_t *startp, 
-                      size_t *countp, ptrdiff_t *stridep,
-                      ptrdiff_t *imapp, unsigned char *ip)
-    int nc_put_varm_schar(int ncid, int varid, size_t *startp, 
-                      size_t *countp, ptrdiff_t *stridep,
-                      ptrdiff_t *imapp, signed char *op)
-    int nc_get_varm_schar(int ncid, int varid, size_t *startp, 
-                      size_t *countp, ptrdiff_t *stridep,
-                      ptrdiff_t *imapp, signed char *ip)
-    int nc_put_varm_short(int ncid, int varid, size_t *startp, 
-                      size_t *countp, ptrdiff_t *stridep,
-                      ptrdiff_t *imapp, short *op)
-    int nc_get_varm_short(int ncid, int varid, size_t *startp, 
-                      size_t *countp, ptrdiff_t *stridep,
-                      ptrdiff_t *imapp, short *ip)
-    int nc_put_varm_int(int ncid, int varid, size_t *startp, 
-                    size_t *countp, ptrdiff_t *stridep,
-                    ptrdiff_t *imapp, int *op)
-    int nc_get_varm_int(int ncid, int varid, size_t *startp, 
-                    size_t *countp, ptrdiff_t *stridep,
-                    ptrdiff_t *imapp, int *ip)
-    int nc_put_varm_long(int ncid, int varid, size_t *startp, 
-                     size_t *countp, ptrdiff_t *stridep,
-                     ptrdiff_t *imapp, long *op)
-    int nc_get_varm_long(int ncid, int varid, size_t *startp, 
-                     size_t *countp, ptrdiff_t *stridep,
-                     ptrdiff_t *imapp, long *ip)
-    int nc_put_varm_float(int ncid, int varid,size_t *startp, 
-                      size_t *countp, ptrdiff_t *stridep,
-                      ptrdiff_t *imapp, float *op)
-    int nc_get_varm_float(int ncid, int varid,size_t *startp, 
-                      size_t *countp, ptrdiff_t *stridep,
-                      ptrdiff_t *imapp, float *ip)
-    int nc_put_varm_double(int ncid, int varid, size_t *startp, 
-                       size_t *countp, ptrdiff_t *stridep,
-                       ptrdiff_t *imapp, double *op)
-    int nc_get_varm_double(int ncid, int varid, size_t *startp, 
-                       size_t *countp, ptrdiff_t *stridep,
-                       ptrdiff_t * imapp, double *ip)
-    int nc_put_varm_ubyte(int ncid, int varid, size_t *startp, 
-                      size_t *countp, ptrdiff_t *stridep, 
-                      ptrdiff_t * imapp, unsigned char *op)
-    int nc_get_varm_ubyte(int ncid, int varid, size_t *startp, 
-                      size_t *countp, ptrdiff_t *stridep, 
-                      ptrdiff_t * imapp, unsigned char *ip)
-    int nc_put_varm_ushort(int ncid, int varid, size_t *startp, 
-                       size_t *countp, ptrdiff_t *stridep, 
-                       ptrdiff_t * imapp, unsigned short *op)
-    int nc_get_varm_ushort(int ncid, int varid, size_t *startp, 
-                       size_t *countp, ptrdiff_t *stridep, 
-                       ptrdiff_t * imapp, unsigned short *ip)
-    int nc_put_varm_uint(int ncid, int varid, size_t *startp, 
-                     size_t *countp, ptrdiff_t *stridep, 
-                     ptrdiff_t * imapp, unsigned int *op)
-    int nc_get_varm_uint(int ncid, int varid, size_t *startp, 
-                     size_t *countp, ptrdiff_t *stridep, 
-                     ptrdiff_t * imapp, unsigned int *ip)
-    int nc_put_varm_longlong(int ncid, int varid, size_t *startp, 
-                      size_t *countp, ptrdiff_t *stridep, 
-                      ptrdiff_t * imapp, long long *op)
-    int nc_get_varm_longlong(int ncid, int varid, size_t *startp, 
-                      size_t *countp, ptrdiff_t *stridep, 
-                      ptrdiff_t * imapp, long long *ip)
-    int nc_put_varm_ulonglong(int ncid, int varid, size_t *startp, 
-                       size_t *countp, ptrdiff_t *stridep, 
-                       ptrdiff_t * imapp, unsigned long long *op)
-    int nc_get_varm_ulonglong(int ncid, int varid, size_t *startp, 
-                       size_t *countp, ptrdiff_t *stridep, 
-                       ptrdiff_t * imapp, unsigned long long *ip)
-    int nc_put_var_text(int ncid, int varid, char *op)
-    int nc_get_var_text(int ncid, int varid, char *ip)
-    int nc_put_var_uchar(int ncid, int varid, unsigned char *op)
-    int nc_get_var_uchar(int ncid, int varid, unsigned char *ip)
-    int nc_put_var_schar(int ncid, int varid, signed char *op)
-    int nc_get_var_schar(int ncid, int varid, signed char *ip)
-    int nc_put_var_short(int ncid, int varid, short *op)
-    int nc_get_var_short(int ncid, int varid, short *ip)
-    int nc_put_var_int(int ncid, int varid, int *op)
-    int nc_get_var_int(int ncid, int varid, int *ip)
-    int nc_put_var_long(int ncid, int varid, long *op)
-    int nc_get_var_long(int ncid, int varid, long *ip)
-    int nc_put_var_float(int ncid, int varid, float *op)
-    int nc_get_var_float(int ncid, int varid, float *ip)
-    int nc_put_var_double(int ncid, int varid, double *op)
-    int nc_get_var_double(int ncid, int varid, double *ip)
-    int nc_put_var_ubyte(int ncid, int varid, unsigned char *op)
-    int nc_get_var_ubyte(int ncid, int varid, unsigned char *ip)
-    int nc_put_var_ushort(int ncid, int varid, unsigned short *op)
-    int nc_get_var_ushort(int ncid, int varid, unsigned short *ip)
-    int nc_put_var_uint(int ncid, int varid, unsigned int *op)
-    int nc_get_var_uint(int ncid, int varid, unsigned int *ip)
-    int nc_put_var_longlong(int ncid, int varid, long long *op)
-    int nc_get_var_longlong(int ncid, int varid, long long *ip)
-    int nc_put_var_ulonglong(int ncid, int varid, unsigned long long *op)
-    int nc_get_var_ulonglong(int ncid, int varid, unsigned long long *ip)
+    int nc_copy_var(int ncid_in, int varid, int ncid_out) nogil
     # set logging verbosity level.
     void nc_set_log_level(int new_level) nogil
     int nc_show_metadata(int ncid) nogil
@@ -767,9 +491,9 @@ cdef extern from "numpy/arrayobject.h":
     ctypedef int npy_intp 
     ctypedef extern class numpy.ndarray [object PyArrayObject]:
         pass
-    npy_intp PyArray_SIZE(ndarray arr)
-    npy_intp PyArray_ISCONTIGUOUS(ndarray arr)
-    npy_intp PyArray_ISALIGNED(ndarray arr)
+    npy_intp PyArray_SIZE(ndarray arr) nogil
+    npy_intp PyArray_ISCONTIGUOUS(ndarray arr) nogil
+    npy_intp PyArray_ISALIGNED(ndarray arr) nogil
     void* PyArray_DATA(ndarray) nogil
     char* PyArray_BYTES(ndarray) nogil
     npy_intp* PyArray_STRIDES(ndarray) nogil

From 3db05a636401884827d624ec6c15953c5d7e148b Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 9 Aug 2022 16:58:01 -0600
Subject: [PATCH 0867/1504] update

---
 include/netCDF4.pxi      | 45 ----------------------------------------
 src/netCDF4/_netCDF4.pyx |  6 ++++--
 2 files changed, 4 insertions(+), 47 deletions(-)

diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index c81d681c2..c6c6ac134 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -126,10 +126,7 @@ cdef extern from "netcdf.h":
         NC_FORMAT_DAP4
         NC_FORMAT_PNETCDF
         NC_FORMAT_UNDEFINED
-        # Let nc__create() or nc__open() figure out
-        # as suitable chunk size.
         NC_SIZEHINT_DEFAULT 
-        # In nc__enddef(), align to the chunk size.
         NC_ALIGN_CHUNK 
         # 'size' argument to ncdimdef for an unlimited dimension
         NC_UNLIMITED 
@@ -219,9 +216,7 @@ cdef extern from "netcdf.h":
     const_char_ptr *nc_inq_libvers() nogil
     const_char_ptr *nc_strerror(int ncerr)
     int nc_create(char *path, int cmode, int *ncidp) nogil
-    int nc__create(char *path, int cmode, size_t initialsz, size_t *chunksizehintp, int *ncidp)
     int nc_open(char *path, int mode, int *ncidp) nogil
-    int nc__open(char *path, int mode, size_t *chunksizehintp, int *ncidp)
     int nc_inq_path(int ncid, size_t *pathlen, char *path) nogil
     int nc_inq_format_extended(int ncid, int *formatp, int* modep) nogil
     int nc_inq_ncid(int ncid, char *name, int *grp_ncid) nogil
@@ -316,8 +311,6 @@ cdef extern from "netcdf.h":
     int nc_set_fill(int ncid, int fillmode, int *old_modep) nogil 
     int nc_set_default_format(int format, int *old_formatp) nogil
     int nc_redef(int ncid) nogil
-    int nc__enddef(int ncid, size_t h_minfree, size_t v_align,
-            size_t v_minfree, size_t r_align) nogil
     int nc_enddef(int ncid) nogil
     int nc_sync(int ncid) nogil
     int nc_abort(int ncid) nogil
@@ -347,40 +340,6 @@ cdef extern from "netcdf.h":
     int nc_put_att_text(int ncid, int varid, char *name,
                     size_t len, char *op) nogil
     int nc_get_att_text(int ncid, int varid, char *name, char *ip) nogil
-    int nc_put_att_uchar(int ncid, int varid, char *name, nc_type xtype,
-                     size_t len, unsigned char *op) nogil
-    int nc_get_att_uchar(int ncid, int varid, char *name, unsigned char *ip) nogil
-    int nc_put_att_schar(int ncid, int varid, char *name, nc_type xtype,
-                     size_t len, signed char *op) nogil
-    int nc_get_att_schar(int ncid, int varid, char *name, signed char *ip) nogil
-    int nc_put_att_short(int ncid, int varid, char *name, nc_type xtype,
-                     size_t len, short *op) nogil
-    int nc_get_att_short(int ncid, int varid, char *name, short *ip) nogil
-    int nc_put_att_int(int ncid, int varid, char *name, nc_type xtype,
-                   size_t len, int *op) nogil
-    int nc_get_att_int(int ncid, int varid, char *name, int *ip) nogil
-    int nc_put_att_long(int ncid, int varid, char *name, nc_type xtype,
-                    size_t len, long *op) nogil
-    int nc_get_att_long(int ncid, int varid, char *name, long *ip) nogil
-    int nc_put_att_float(int ncid, int varid, char *name, nc_type xtype,
-                     size_t len, float *op) nogil
-    int nc_get_att_float(int ncid, int varid, char *name, float *ip) nogil
-    int nc_put_att_double(int ncid, int varid, char *name, nc_type xtype,
-                      size_t len, double *op) nogil
-    int nc_get_att_double(int ncid, int varid, char *name, double *ip) nogil
-    int nc_put_att_ushort(int ncid, int varid, char *name, nc_type xtype,
-                      size_t len, unsigned short *op) nogil
-    int nc_get_att_ushort(int ncid, int varid, char *name, unsigned short *ip) nogil
-    int nc_put_att_uint(int ncid, int varid, char *name, nc_type xtype,
-                    size_t len, unsigned int *op) nogil
-    int nc_get_att_uint(int ncid, int varid, char *name, unsigned int *ip) nogil
-    int nc_put_att_longlong(int ncid, int varid, char *name, nc_type xtype,
-                     size_t len, long long *op) nogil
-    int nc_get_att_longlong(int ncid, int varid, char *name, long long *ip) nogil
-    int nc_put_att_ulonglong(int ncid, int varid, char *name, nc_type xtype,
-                         size_t len, unsigned long long *op) nogil
-    int nc_get_att_ulonglong(int ncid, int varid, char *name, 
-                         unsigned long long *ip) nogil
     int nc_def_var(int ncid, char *name, nc_type xtype, int ndims, 
                int *dimidsp, int *varidp) nogil
     int nc_inq_var(int ncid, int varid, char *name, nc_type *xtypep, 
@@ -392,10 +351,6 @@ cdef extern from "netcdf.h":
     int nc_inq_vardimid(int ncid, int varid, int *dimidsp) nogil
     int nc_inq_varnatts(int ncid, int varid, int *nattsp) nogil
     int nc_rename_var(int ncid, int varid, char *name) nogil
-    int nc_copy_var(int ncid_in, int varid, int ncid_out) nogil
-    # set logging verbosity level.
-    void nc_set_log_level(int new_level) nogil
-    int nc_show_metadata(int ncid) nogil
     int nc_free_vlen(nc_vlen_t *vl) nogil
     int nc_free_vlens(size_t len, nc_vlen_t *vl) nogil
     int nc_free_string(size_t len, char **data) nogil
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index c8b15b2db..6d8b120c5 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1265,7 +1265,8 @@ ELSE:
 def _gethdf5libversion():
     cdef unsigned int majorvers, minorvers, releasevers
     cdef herr_t ierr
-    ierr = H5get_libversion( &majorvers, &minorvers, &releasevers)
+    with nogil:
+        ierr = H5get_libversion( &majorvers, &minorvers, &releasevers)
     if ierr < 0:
         raise RuntimeError('error getting HDF5 library version info')
     return '%d.%d.%d' % (majorvers,minorvers,releasevers)
@@ -4614,7 +4615,8 @@ return dictionary containing HDF5 filter parameters."""
         cdef int iblosc=0
         cdef int iszip=0
         cdef unsigned int iblosc_complevel,iblosc_blocksize,iblosc_compressor,iblosc_shuffle
-        cdef int iszip_coding, iszip_pixels_per_block
+        cdef int iszip_coding=0
+        cdef int iszip_pixels_per_block=0
         filtdict = {'zlib':False,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
         if self._grp.data_model not in ['NETCDF4_CLASSIC','NETCDF4']: return
         with nogil:

From c4f2a95d6183785dfa354ce707b62ed035648831 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 9 Aug 2022 16:58:36 -0600
Subject: [PATCH 0868/1504] empty commit to trigger github actions


From b4a233bfc797ac2213d5f4b302281eeec40fd2fc Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Wed, 10 Aug 2022 11:29:45 -0600
Subject: [PATCH 0869/1504] try keeping GIL for nc_open_par and nc_create_par
 (MPI tests failing)

---
 src/netCDF4/_netCDF4.pyx | 21 ++++++++++++++-------
 1 file changed, 14 insertions(+), 7 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 6d8b120c5..eb0195daa 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2246,7 +2246,8 @@ strings.
                     if parallel:
                         IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                             cmode = NC_CLOBBER | parmode
-                            with nogil:
+                            #with nogil:
+                            if 1:
                                 ierr = nc_create_par(path, cmode, \
                                        mpicomm, mpiinfo, &grpid)
                         ELSE:
@@ -2267,7 +2268,8 @@ strings.
                     if parallel:
                         IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                             cmode = NC_NOCLOBBER | parmode
-                            with nogil:
+                            #with nogil:
+                            if 1:
                                 ierr = nc_create_par(path, cmode, \
                                        mpicomm, mpiinfo, &grpid)
                         ELSE:
@@ -2309,7 +2311,8 @@ strings.
             elif parallel:
                 IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                     cmode = NC_NOWRITE | NC_MPIIO
-                    with nogil:
+                    #with nogil:
+                    if 1:
                         ierr = nc_open_par(path, cmode, \
                                mpicomm, mpiinfo, &grpid)
                 ELSE:
@@ -2333,7 +2336,8 @@ strings.
             if parallel:
                 IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                     cmode = NC_NOWRITE | NC_SHARE 
-                    with nogil:
+                    #with nogil:
+                    if 1:
                         ierr = nc_open_par(path, cmode, \
                                mpicomm, mpiinfo, &grpid)
                 ELSE:
@@ -2350,7 +2354,8 @@ strings.
                 # NC_SHARE ignored
                 IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                     cmode =  NC_WRITE | NC_MPIIO
-                    with nogil:
+                    #with nogil:
+                    if 1:
                         ierr = nc_open_par(path, cmode, \
                                mpicomm, mpiinfo, &grpid)
                 ELSE:
@@ -2369,7 +2374,8 @@ strings.
                     # NC_SHARE ignored
                     IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                         cmode = NC_CLOBBER | parmode 
-                        with nogil:
+                        #with nogil:
+                        if 1:
                             ierr = nc_create_par(path, NC_CLOBBER | cmode, \
                                    mpicomm, mpiinfo, &grpid)
                     ELSE:
@@ -2392,7 +2398,8 @@ strings.
                     # NC_SHARE ignored
                     IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                         cmode = NC_NOCLOBBER | parmode
-                        with nogil:
+                        #with nogil:
+                        if 1:
                             ierr = nc_create_par(path, cmode, \
                                    mpicomm, mpiinfo, &grpid)
                     ELSE:

From ce14571f42af79145ef1d6582ebf3e3c48e126dc Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Wed, 10 Aug 2022 17:42:53 -0600
Subject: [PATCH 0870/1504] try not releasing GIL for nc_put_var

---
 src/netCDF4/_netCDF4.pyx | 27 +++++++++++----------------
 1 file changed, 11 insertions(+), 16 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index eb0195daa..50fcf186d 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2246,8 +2246,7 @@ strings.
                     if parallel:
                         IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                             cmode = NC_CLOBBER | parmode
-                            #with nogil:
-                            if 1:
+                            with nogil:
                                 ierr = nc_create_par(path, cmode, \
                                        mpicomm, mpiinfo, &grpid)
                         ELSE:
@@ -2268,8 +2267,7 @@ strings.
                     if parallel:
                         IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                             cmode = NC_NOCLOBBER | parmode
-                            #with nogil:
-                            if 1:
+                            with nogil:
                                 ierr = nc_create_par(path, cmode, \
                                        mpicomm, mpiinfo, &grpid)
                         ELSE:
@@ -2311,8 +2309,7 @@ strings.
             elif parallel:
                 IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                     cmode = NC_NOWRITE | NC_MPIIO
-                    #with nogil:
-                    if 1:
+                    with nogil:
                         ierr = nc_open_par(path, cmode, \
                                mpicomm, mpiinfo, &grpid)
                 ELSE:
@@ -2336,8 +2333,7 @@ strings.
             if parallel:
                 IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                     cmode = NC_NOWRITE | NC_SHARE 
-                    #with nogil:
-                    if 1:
+                    with nogil:
                         ierr = nc_open_par(path, cmode, \
                                mpicomm, mpiinfo, &grpid)
                 ELSE:
@@ -2354,8 +2350,7 @@ strings.
                 # NC_SHARE ignored
                 IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                     cmode =  NC_WRITE | NC_MPIIO
-                    #with nogil:
-                    if 1:
+                    with nogil:
                         ierr = nc_open_par(path, cmode, \
                                mpicomm, mpiinfo, &grpid)
                 ELSE:
@@ -2374,8 +2369,7 @@ strings.
                     # NC_SHARE ignored
                     IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                         cmode = NC_CLOBBER | parmode 
-                        #with nogil:
-                        if 1:
+                        with nogil:
                             ierr = nc_create_par(path, NC_CLOBBER | cmode, \
                                    mpicomm, mpiinfo, &grpid)
                     ELSE:
@@ -2398,8 +2392,7 @@ strings.
                     # NC_SHARE ignored
                     IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
                         cmode = NC_NOCLOBBER | parmode
-                        #with nogil:
-                        if 1:
+                        with nogil:
                             ierr = nc_create_par(path, cmode, \
                                    mpicomm, mpiinfo, &grpid)
                     ELSE:
@@ -5741,11 +5734,13 @@ NC_CHAR).
                 data = data.byteswap()
             # strides all 1 or scalar variable, use put_vara (faster)
             if sum(stride) == ndims or ndims == 0:
-                with nogil:
+                #with nogil:
+                if 1:
                     ierr = nc_put_vara(self._grpid, self._varid,
                                        startp, countp, PyArray_DATA(data))
             else:
-                with nogil:
+                #with nogil:
+                if 1:
                     ierr = nc_put_vars(self._grpid, self._varid,
                                        startp, countp, stridep, PyArray_DATA(data))
             _ensure_nc_success(ierr)

From 0b4f90a00fe3df62342f63072df1a5b5cb866c5e Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 11 Aug 2022 08:53:45 -0600
Subject: [PATCH 0871/1504] update

---
 src/netCDF4/_netCDF4.pyx | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 50fcf186d..6d8b120c5 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -5734,13 +5734,11 @@ NC_CHAR).
                 data = data.byteswap()
             # strides all 1 or scalar variable, use put_vara (faster)
             if sum(stride) == ndims or ndims == 0:
-                #with nogil:
-                if 1:
+                with nogil:
                     ierr = nc_put_vara(self._grpid, self._varid,
                                        startp, countp, PyArray_DATA(data))
             else:
-                #with nogil:
-                if 1:
+                with nogil:
                     ierr = nc_put_vars(self._grpid, self._varid,
                                        startp, countp, stridep, PyArray_DATA(data))
             _ensure_nc_success(ierr)

From db12ab166e9ea1fb18159f468fe7740a7f9b1e9a Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 11 Aug 2022 08:53:59 -0600
Subject: [PATCH 0872/1504] comment out failing part of test

---
 examples/mpi_example.py | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/examples/mpi_example.py b/examples/mpi_example.py
index 0bebfe675..643ea5b01 100644
--- a/examples/mpi_example.py
+++ b/examples/mpi_example.py
@@ -27,16 +27,17 @@
 assert rank==nc['var'][rank]
 nc.close()
 # reopen the file in append mode, modify the data on the last rank.
-nc = Dataset('parallel_test.nc', 'a',parallel=True, comm=MPI.COMM_WORLD,
+#nc = Dataset('parallel_test.nc', 'a',parallel=True, comm=MPI.COMM_WORLD,
         info=MPI.Info())
-if rank == 3: v[rank] = 2*rank
-nc.close()
+#if rank == 3: v[rank] = 2*rank
+#nc.close()
 # reopen the file read-only again, check the data.
 # leave out the comm and info kwargs to check that the defaults
 # (MPI_COMM_WORLD and MPI_INFO_NULL) work.
 nc = Dataset('parallel_test.nc', parallel=True)
 if rank == 3:
-    assert 2*rank==nc['var'][rank]
+    #assert 2*rank==nc['var'][rank]
+    assert rank==nc['var'][rank]
 else:
     assert rank==nc['var'][rank]
 nc.close()

From 60f0ef55063748a5e9d065fde4bbd1670a1145df Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 11 Aug 2022 08:57:58 -0600
Subject: [PATCH 0873/1504] fix typo

---
 examples/mpi_example.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/mpi_example.py b/examples/mpi_example.py
index 643ea5b01..6c80f90cf 100644
--- a/examples/mpi_example.py
+++ b/examples/mpi_example.py
@@ -28,7 +28,7 @@
 nc.close()
 # reopen the file in append mode, modify the data on the last rank.
 #nc = Dataset('parallel_test.nc', 'a',parallel=True, comm=MPI.COMM_WORLD,
-        info=MPI.Info())
+#        info=MPI.Info())
 #if rank == 3: v[rank] = 2*rank
 #nc.close()
 # reopen the file read-only again, check the data.

From 52e9f6341bc0395cfa4229cb41b77d523afd1ee8 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 11 Aug 2022 09:13:34 -0600
Subject: [PATCH 0874/1504] comment out failing part

---
 examples/mpi_example_compressed.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/mpi_example_compressed.py b/examples/mpi_example_compressed.py
index ece1d1ee2..4ccabbfd1 100644
--- a/examples/mpi_example_compressed.py
+++ b/examples/mpi_example_compressed.py
@@ -14,5 +14,5 @@
 v = nc['var']
 assert rank==v[rank]
 v.set_collective(True) # issue #1108 (var must be in collective mode or write will fail)
-v[rank]=2*rank
+#v[rank]=2*rank
 nc.close()

From 86c05a948cd3356b3b02bd900fcca72d696dd989 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 11 Aug 2022 09:21:36 -0600
Subject: [PATCH 0875/1504] update

---
 examples/mpi_example.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/examples/mpi_example.py b/examples/mpi_example.py
index 6c80f90cf..af31f90ee 100644
--- a/examples/mpi_example.py
+++ b/examples/mpi_example.py
@@ -27,10 +27,10 @@
 assert rank==nc['var'][rank]
 nc.close()
 # reopen the file in append mode, modify the data on the last rank.
-#nc = Dataset('parallel_test.nc', 'a',parallel=True, comm=MPI.COMM_WORLD,
-#        info=MPI.Info())
+nc = Dataset('parallel_test.nc', 'a',parallel=True, comm=MPI.COMM_WORLD,
+             info=MPI.Info())
 #if rank == 3: v[rank] = 2*rank
-#nc.close()
+nc.close()
 # reopen the file read-only again, check the data.
 # leave out the comm and info kwargs to check that the defaults
 # (MPI_COMM_WORLD and MPI_INFO_NULL) work.

From a8a712684c44b2c2c4a08488c75eb53cd408ece8 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 11 Aug 2022 09:35:41 -0600
Subject: [PATCH 0876/1504] fix bug introduced in releasing gil for nc_open_par

---
 examples/mpi_example.py            | 4 ++--
 examples/mpi_example_compressed.py | 2 +-
 src/netCDF4/_netCDF4.pyx           | 2 +-
 3 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/examples/mpi_example.py b/examples/mpi_example.py
index af31f90ee..8d18a8408 100644
--- a/examples/mpi_example.py
+++ b/examples/mpi_example.py
@@ -29,14 +29,14 @@
 # reopen the file in append mode, modify the data on the last rank.
 nc = Dataset('parallel_test.nc', 'a',parallel=True, comm=MPI.COMM_WORLD,
              info=MPI.Info())
-#if rank == 3: v[rank] = 2*rank
+if rank == 3: v[rank] = 2*rank
 nc.close()
 # reopen the file read-only again, check the data.
 # leave out the comm and info kwargs to check that the defaults
 # (MPI_COMM_WORLD and MPI_INFO_NULL) work.
 nc = Dataset('parallel_test.nc', parallel=True)
 if rank == 3:
-    #assert 2*rank==nc['var'][rank]
+    assert 2*rank==nc['var'][rank]
     assert rank==nc['var'][rank]
 else:
     assert rank==nc['var'][rank]
diff --git a/examples/mpi_example_compressed.py b/examples/mpi_example_compressed.py
index 4ccabbfd1..ece1d1ee2 100644
--- a/examples/mpi_example_compressed.py
+++ b/examples/mpi_example_compressed.py
@@ -14,5 +14,5 @@
 v = nc['var']
 assert rank==v[rank]
 v.set_collective(True) # issue #1108 (var must be in collective mode or write will fail)
-#v[rank]=2*rank
+v[rank]=2*rank
 nc.close()
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 6d8b120c5..5b916b429 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -2332,7 +2332,7 @@ strings.
         elif mode in ['a','r+'] and os.path.exists(filename):
             if parallel:
                 IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
-                    cmode = NC_NOWRITE | NC_SHARE 
+                    cmode = NC_WRITE | NC_MPIIO
                     with nogil:
                         ierr = nc_open_par(path, cmode, \
                                mpicomm, mpiinfo, &grpid)

From 9499bd8fb3e481e579400de8cead8672e435d42c Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 11 Aug 2022 10:22:34 -0600
Subject: [PATCH 0877/1504] update

---
 examples/mpi_example.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/examples/mpi_example.py b/examples/mpi_example.py
index 8d18a8408..0bebfe675 100644
--- a/examples/mpi_example.py
+++ b/examples/mpi_example.py
@@ -28,7 +28,7 @@
 nc.close()
 # reopen the file in append mode, modify the data on the last rank.
 nc = Dataset('parallel_test.nc', 'a',parallel=True, comm=MPI.COMM_WORLD,
-             info=MPI.Info())
+        info=MPI.Info())
 if rank == 3: v[rank] = 2*rank
 nc.close()
 # reopen the file read-only again, check the data.
@@ -37,7 +37,6 @@
 nc = Dataset('parallel_test.nc', parallel=True)
 if rank == 3:
     assert 2*rank==nc['var'][rank]
-    assert rank==nc['var'][rank]
 else:
     assert rank==nc['var'][rank]
 nc.close()

From 2809d601235969421b204aa84644c745b295bb69 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Thu, 11 Aug 2022 11:20:37 -0600
Subject: [PATCH 0878/1504] fix uninitialized error warnings

---
 src/netCDF4/_netCDF4.pyx | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 5b916b429..0efc54df3 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4609,14 +4609,19 @@ attributes."""
 **`filters(self)`**
 
 return dictionary containing HDF5 filter parameters."""
-        cdef int ierr,ideflate,ishuffle,icomplevel,icomplevel_zstd,icomplevel_bzip2,ifletcher32
+        cdef int ierr,ideflate,ishuffle,icomplevel,ifletcher32
         cdef int izstd=0
         cdef int ibzip2=0
         cdef int iblosc=0
         cdef int iszip=0
-        cdef unsigned int iblosc_complevel,iblosc_blocksize,iblosc_compressor,iblosc_shuffle
         cdef int iszip_coding=0
         cdef int iszip_pixels_per_block=0
+        cdef int icomplevel_zstd=0 
+        cdef int icomplevel_bzip2=0 
+        cdef unsigned int iblosc_shuffle=0
+        cdef unsigned int iblosc_compressor=0
+        cdef unsigned int iblosc_blocksize=0
+        cdef unsigned int iblosc_complevel=0
         filtdict = {'zlib':False,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':0,'fletcher32':False}
         if self._grp.data_model not in ['NETCDF4_CLASSIC','NETCDF4']: return
         with nogil:

From 3a819942173df8fc2758624b316090029ea3548f Mon Sep 17 00:00:00 2001
From: Mark Harfouche 
Date: Mon, 22 Aug 2022 23:45:53 -0400
Subject: [PATCH 0879/1504] Add support for nc_set_alignment and
 nc_get_alignment

---
 Changelog                |   2 +
 include/netCDF4.pxi      |   5 ++
 setup.py                 |  18 ++++-
 src/netCDF4/_netCDF4.pyx |  47 ++++++++++++
 test/tst_alignment.py    | 156 +++++++++++++++++++++++++++++++++++++++
 5 files changed, 224 insertions(+), 4 deletions(-)
 create mode 100644 test/tst_alignment.py

diff --git a/Changelog b/Changelog
index 6fb7a676c..6b3946e48 100644
--- a/Changelog
+++ b/Changelog
@@ -3,6 +3,8 @@
  * add Dataset methods has__filter (where =zstd,blosc,bzip2,szip)
    to check for availability of extra compression filters.
  * release GIL for all C-lib calls (issue #1180).
+ * Add support for nc_set_alignment and nc_get_alignment to control alignment
+   of data within HDF5 files.
 
  version 1.6.0 (tag v1.6.0rel)
 ==============================
diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index c6c6ac134..60afc1538 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -441,6 +441,11 @@ IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT:
             NC_MPIPOSIX
             NC_PNETCDF
 
+IF HAS_SET_ALIGNMENT:
+    cdef extern from "netcdf.h":
+        int nc_set_alignment(int threshold, int alignment)
+        int nc_get_alignment(int *threshold, int *alignment)
+
 # taken from numpy.pxi in numpy 1.0rc2.
 cdef extern from "numpy/arrayobject.h":
     ctypedef int npy_intp 
diff --git a/setup.py b/setup.py
index 2eea22e1c..ec1dc2bc8 100644
--- a/setup.py
+++ b/setup.py
@@ -71,6 +71,7 @@ def check_api(inc_dirs,netcdf_lib_version):
     has_zstandard = False
     has_bzip2 = False
     has_blosc = False
+    has_set_alignment = False
 
     for d in inc_dirs:
         try:
@@ -92,6 +93,8 @@ def check_api(inc_dirs,netcdf_lib_version):
                 has_cdf5_format = True
             if line.startswith('nc_def_var_quantize'):
                 has_quantize = True
+            if line.startswith('nc_set_alignment'):
+                has_set_alignment = True
 
         if has_nc_open_mem:
             try:
@@ -141,7 +144,7 @@ def check_api(inc_dirs,netcdf_lib_version):
     return has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \
            has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \
            has_parallel4_support, has_pnetcdf_support, has_szip_support, has_quantize, \
-           has_zstandard, has_bzip2, has_blosc
+           has_zstandard, has_bzip2, has_blosc, has_set_alignment
 
 
 def getnetcdfvers(libdirs):
@@ -228,7 +231,7 @@ def extract_version(CYTHON_FNAME):
 
 setup_cfg = 'setup.cfg'
 # contents of setup.cfg will override env vars, unless
-# USE_SETUPCFG evaluates to False. 
+# USE_SETUPCFG evaluates to False.
 ncconfig = None
 use_ncconfig = None
 if USE_SETUPCFG and os.path.exists(setup_cfg):
@@ -338,7 +341,7 @@ def extract_version(CYTHON_FNAME):
 elif USE_NCCONFIG is None:
     # if nc-config exists, and USE_NCCONFIG not set, try to use it.
     if HAS_NCCONFIG: USE_NCCONFIG=True
-#elif USE_NCCONFIG is None: 
+#elif USE_NCCONFIG is None:
 #    USE_NCCONFIG = False # don't try to use nc-config if USE_NCCONFIG not set
 
 try:
@@ -555,7 +558,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \
     has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \
     has_parallel4_support, has_pnetcdf_support, has_szip_support, has_quantize, \
-    has_zstandard, has_bzip2, has_blosc = \
+    has_zstandard, has_bzip2, has_blosc, has_set_alignment = \
     check_api(inc_dirs,netcdf_lib_version)
     # for netcdf 4.4.x CDF5 format is always enabled.
     if netcdf_lib_version is not None and\
@@ -662,6 +665,13 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         sys.stdout.write('netcdf lib does not have szip compression functions\n')
         f.write('DEF HAS_SZIP_SUPPORT = 0\n')
 
+    if has_set_alignment:
+        sys.stdout.write('netcdf lib has nc_set_alignment function\n')
+        f.write('DEF HAS_SET_ALIGNMENT = 1\n')
+    else:
+        sys.stdout.write('netcdf lib does not have nc_set_alignment function\n')
+        f.write('DEF HAS_SET_ALIGNMENT = 0\n')
+
     f.close()
 
     if has_parallel4_support or has_pnetcdf_support:
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 0efc54df3..ba7db81f8 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1324,6 +1324,52 @@ details."""
         ierr = nc_set_chunk_cache(sizep,nelemsp, preemptionp)
     _ensure_nc_success(ierr)
 
+IF HAS_SET_ALIGNMENT:
+    def get_alignment():
+        """
+    **`get_alignment()`**
+
+    return current netCDF alignment within HDF5 files in a tuple
+    (threshold,alignment). See netcdf C library documentation for
+    `nc_get_alignment` for details. Values can be reset with
+    `set_alignment`.
+
+    This function was added in netcdf 4.9.0."""
+        cdef int ierr
+        cdef int thresholdp, alignmentp
+        ierr = nc_get_alignment(&thresholdp, &alignmentp)
+        _ensure_nc_success(ierr)
+        threshold = thresholdp
+        alignment = alignmentp
+        return (threshold,alignment)
+
+    def set_alignment(threshold, alignment):
+        """
+    **`set_alignment(threshold,alignment)`**
+
+    Change the HDF5 file alignment.
+    See netcdf C library documentation for `nc_set_alignment` for
+    details.
+
+    This function was added in netcdf 4.9.0."""
+        cdef int ierr
+        cdef int thresholdp, alignmentp
+        thresholdp = threshold
+        alignmentp = alignment
+
+        ierr = nc_set_alignment(thresholdp, alignmentp)
+        _ensure_nc_success(ierr)
+ELSE:
+    def get_alignment():
+        raise RuntimeError(
+            "This function requires netcdf4 4.9.0+ to be used at compile time"
+        )
+
+    def set_alignment(threshold, alignment):
+        raise RuntimeError(
+            "This function requires netcdf4 4.9.0+ to be used at compile time"
+        )
+
 __netcdf4libversion__ = getlibversion().split()[0]
 __hdf5libversion__ = _gethdf5libversion()
 __has_rename_grp__ = HAS_RENAME_GRP
@@ -1339,6 +1385,7 @@ __has_zstandard_support__ = HAS_ZSTANDARD_SUPPORT
 __has_bzip2_support__ = HAS_BZIP2_SUPPORT
 __has_blosc_support__ = HAS_BLOSC_SUPPORT
 __has_szip_support__ = HAS_SZIP_SUPPORT
+__has_set_alignment__ = HAS_SET_ALIGNMENT
 _needsworkaround_issue485 = __netcdf4libversion__ < "4.4.0" or \
                (__netcdf4libversion__.startswith("4.4.0") and \
                 "-development" in __netcdf4libversion__)
diff --git a/test/tst_alignment.py b/test/tst_alignment.py
new file mode 100644
index 000000000..c20ed4173
--- /dev/null
+++ b/test/tst_alignment.py
@@ -0,0 +1,156 @@
+import numpy as np
+from netCDF4 import set_alignment, get_alignment, Dataset
+import netCDF4
+import os
+import subprocess
+import tempfile
+import unittest
+
+# During testing, sometimes development versions are used.
+# They may be written as 4.9.1-development
+libversion_no_development = netCDF4.__netcdf4libversion__.split('-')[0]
+libversion = tuple(int(v) for v in libversion_no_development.split('.'))
+has_alignment = (libversion[0] > 4) or (
+    libversion[0] == 4 and (libversion[1] >= 9)
+)
+try:
+    has_h5ls = subprocess.check_call(['h5ls', '--version'], stdout=subprocess.PIPE) == 0
+except Exception:
+    has_h5ls = False
+
+file_name = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
+
+
+class AlignmentTestCase(unittest.TestCase):
+    def setUp(self):
+        self.file = file_name
+
+        # This is a global variable in netcdf4, it must be set before File
+        # creation
+        if has_alignment:
+            set_alignment(1024, 4096)
+            assert get_alignment() == (1024, 4096)
+
+        f = Dataset(self.file, 'w')
+        f.createDimension('x', 4096)
+        # Create many datasets so that we decrease the chance of
+        # the dataset being randomly aligned
+        for i in range(10):
+            f.createVariable(f'data{i:02d}', np.float64, ('x',))
+            v = f.variables[f'data{i:02d}']
+            v[...] = 0
+        f.close()
+        if has_alignment:
+            # ensure to reset the alignment to 1 (default values) so as not to
+            # disrupt other tests
+            set_alignment(1, 1)
+            assert get_alignment() == (1, 1)
+
+    def test_version_settings(self):
+        if has_alignment:
+            # One should always be able to set the alignment to 1, 1
+            set_alignment(1, 1)
+            assert get_alignment() == (1, 1)
+        else:
+            with self.assertRaises(RuntimeError):
+                set_alignment(1, 1)
+            with self.assertRaises(RuntimeError):
+                get_alignment()
+
+    # if we have no support for alignment, we have no guarantees on
+    # how the data can be aligned
+    @unittest.skipIf(
+        not has_h5ls,
+        "h5ls not found."
+    )
+    @unittest.skipIf(
+        not has_alignment,
+        "No support for set_alignment in libnetcdf."
+    )
+    def test_setting_alignment(self):
+        # We choose to use h5ls instead of h5py since h5ls is very likely
+        # to be installed alongside the rest of the tooling required to build
+        # netcdf4-python
+        # Output from h5ls is expected to look like:
+        """
+Opened "/tmp/tmpqexgozg1.nc" with sec2 driver.
+data00                   Dataset {4096/4096}
+    Attribute: DIMENSION_LIST {1}
+        Type:      variable length of
+                   object reference
+    Attribute: _Netcdf4Coordinates {1}
+        Type:      32-bit little-endian integer
+    Location:  1:563
+    Links:     1
+    Storage:   32768 logical bytes, 32768 allocated bytes, 100.00% utilization
+    Type:      IEEE 64-bit little-endian float
+    Address:   8192
+data01                   Dataset {4096/4096}
+    Attribute: DIMENSION_LIST {1}
+        Type:      variable length of
+                   object reference
+    Attribute: _Netcdf4Coordinates {1}
+        Type:      32-bit little-endian integer
+    Location:  1:1087
+    Links:     1
+    Storage:   32768 logical bytes, 32768 allocated bytes, 100.00% utilization
+    Type:      IEEE 64-bit little-endian float
+    Address:   40960
+[...]
+x                        Dataset {4096/4096}
+    Attribute: CLASS scalar
+        Type:      16-byte null-terminated ASCII string
+    Attribute: NAME scalar
+        Type:      64-byte null-terminated ASCII string
+    Attribute: REFERENCE_LIST {10}
+        Type:      struct {
+                   "dataset"          +0    object reference
+                   "dimension"        +8    32-bit little-endian unsigned integer
+               } 16 bytes
+    Attribute: _Netcdf4Dimid scalar
+        Type:      32-bit little-endian integer
+    Location:  1:239
+    Links:     1
+    Storage:   16384 logical bytes, 0 allocated bytes
+    Type:      IEEE 32-bit big-endian float
+    Address:   18446744073709551615
+"""
+        h5ls_results = subprocess.check_output(
+            ["h5ls", "--verbose", "--address", "--simple", self.file]
+        ).decode()
+
+        addresses = {
+            f'data{i:02d}': -1
+            for i in range(10)
+        }
+
+        data_variable = None
+        for line in h5ls_results.split('\n'):
+            if not line.startswith(' '):
+                data_variable = line.split(' ')[0]
+            # only process the data variables we care to inpsect
+            if data_variable not in addresses:
+                continue
+            line = line.strip()
+            if line.startswith('Address:'):
+                address = int(line.split(':')[1].strip())
+                addresses[data_variable] = address
+
+        for key, address in addresses.items():
+            is_aligned = (address % 4096) == 0
+            assert is_aligned, f"{key} is not aligned. Address = 0x{address:x}"
+
+        # Alternative implementation in h5py
+        # import h5py
+        # with h5py.File(self.file, 'r') as h5file:
+        #     for i in range(10):
+        #         v = h5file[f'data{i:02d}']
+        #         assert (dataset.id.get_offset() % 4096) == 0
+
+    def tearDown(self):
+        # Remove the temporary files
+        os.remove(self.file)
+
+
+if __name__ == '__main__':
+    unittest.main()

From ea5dfbcb0910de753b27cc0b647cedfed5b3a939 Mon Sep 17 00:00:00 2001
From: Filipe Fernandes 
Date: Wed, 31 Aug 2022 13:12:36 -0300
Subject: [PATCH 0880/1504] test previous release of zlib

---
 .github/workflows/miniconda.yml | 48 ++++++++++++++++++++-------------
 1 file changed, 29 insertions(+), 19 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 2d27d3168..ce8c7accc 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -18,29 +18,35 @@ jobs:
         exclude:
           - os: macos-latest  
             platform: x32
+      fail-fast: false
+
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
 
-    - name: Setup Conda
-      uses: s-weigand/setup-conda@v1
+    - name: Setup Micromamba
+      uses: mamba-org/provision-with-micromamba@v13
       with:
-        activate-conda: false
-        conda-channels: conda-forge
+        environment-file: false
 
     - name: Python ${{ matrix.python-version }}
       shell: bash -l {0}
       run: |
-        conda create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest hdf5 libnetcdf cftime --strict-channel-priority
-        source activate TEST
+        micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest hdf5 libnetcdf cftime "zlib=1.2.11" --channel conda-forge
+        micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         pip install -e . --no-deps --force-reinstall
-        conda info --all
-        conda list
+
+    - name: Debug conda
+      shell: bash -l {0}
+      run: |
+        micromamba activate TEST
+        micromamba info --all
+        micromamba list
 
     - name: Tests
       shell: bash -l {0}
       run: |
-        source activate TEST
+        micromamba activate TEST
         cd test && python run_all.py
 
   run-mpi:
@@ -53,26 +59,30 @@ jobs:
     steps:
     - uses: actions/checkout@v2
 
-    - name: Setup Conda
-      uses: s-weigand/setup-conda@v1
+    - name: Setup Micromamba
+      uses: mamba-org/provision-with-micromamba@main
       with:
-        activate-conda: false
-        conda-channels: conda-forge
+        environment-file: false
 
     - name: Python ${{ matrix.python-version }}
       shell: bash -l {0}
       run: |
-        conda create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest mpi4py hdf5=*=mpi* libnetcdf=*=mpi* cftime --strict-channel-priority
-        source activate TEST
+        micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest mpi4py hdf5=*=mpi* libnetcdf=*=mpi* cftime --channel conda-forge
+        micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         pip install -e . --no-deps --force-reinstall
-        conda info --all
-        conda list
+
+    - name: Debug conda
+      shell: bash -l {0}
+      run: |
+        micromamba activate TEST
+        micromamba info --all
+        micromamba list
 
     - name: Tests
       shell: bash -l {0}
       run: |
-        source activate TEST
+        micromamba activate TEST
         cd test && python run_all.py
         cd ../examples
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" 

From 2ccba6f3f23e962665dafd4b75c1508cbc0e2f16 Mon Sep 17 00:00:00 2001
From: Filipe 
Date: Wed, 31 Aug 2022 16:55:29 -0300
Subject: [PATCH 0881/1504] Update .github/workflows/miniconda.yml

Co-authored-by: Mark Harfouche 
---
 .github/workflows/miniconda.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index ce8c7accc..1dbb1b7fd 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -31,7 +31,7 @@ jobs:
     - name: Python ${{ matrix.python-version }}
       shell: bash -l {0}
       run: |
-        micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest hdf5 libnetcdf cftime "zlib=1.2.11" --channel conda-forge
+        micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest hdf5 libnetcdf cftime zlib --channel conda-forge
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         pip install -e . --no-deps --force-reinstall

From 136dc639a154fd7169452b0ee4b8cf34e89cf8c6 Mon Sep 17 00:00:00 2001
From: Filipe 
Date: Wed, 31 Aug 2022 16:55:39 -0300
Subject: [PATCH 0882/1504] Update .github/workflows/miniconda.yml

Co-authored-by: Mark Harfouche 
---
 .github/workflows/miniconda.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 1dbb1b7fd..601fbda04 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -67,7 +67,7 @@ jobs:
     - name: Python ${{ matrix.python-version }}
       shell: bash -l {0}
       run: |
-        micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest mpi4py hdf5=*=mpi* libnetcdf=*=mpi* cftime --channel conda-forge
+        micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest mpi4py hdf5=*=mpi* libnetcdf=*=mpi* cftime zlib --channel conda-forge
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         pip install -e . --no-deps --force-reinstall

From adc840fac4f9e50d3a3441effaa8958c8a6c2b62 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 10 Sep 2022 19:13:28 -0600
Subject: [PATCH 0883/1504] prepare for v1.6.1 release

---
 Changelog                | 2 +-
 README.md                | 5 +++++
 src/netCDF4/_netCDF4.pyx | 2 +-
 3 files changed, 7 insertions(+), 2 deletions(-)

diff --git a/Changelog b/Changelog
index 6b3946e48..a66c27cd9 100644
--- a/Changelog
+++ b/Changelog
@@ -1,4 +1,4 @@
- since version 1.6.0 release
+ version 1.6.1 (tag v1.6.1rel)
 ==============================
  * add Dataset methods has__filter (where =zstd,blosc,bzip2,szip)
    to check for availability of extra compression filters.
diff --git a/README.md b/README.md
index 899ea457d..fa6621534 100644
--- a/README.md
+++ b/README.md
@@ -10,6 +10,11 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
+09/18/2022:  Version [1.6.1](https://pypi.python.org/pypi/netCDF4/1.6.1) released.  GIL now
+released for all C lib calls, `set_alignment` and `get_alignment` module functions
+added to modify/retrieve HDF5 data alignment properties. Added `Dataset` methods to 
+query availability of optional compression filters.
+
 06/24/2022:  Version [1.6.0](https://pypi.python.org/pypi/netCDF4/1.6.0) released.  Support
 for quantization (bit-grooming and bit-rounding) functionality in netcdf-c 4.9.0 which can
 dramatically improve compression.  Dataset.createVariable now accepts dimension instances (instead
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index ba7db81f8..dd4599b92 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1230,7 +1230,7 @@ if sys.version_info[0:2] < (3, 7):
     # Python 3.7+ guarantees order; older versions need OrderedDict
     from collections import OrderedDict
 
-__version__ = "1.6.0"
+__version__ = "1.6.1"
 
 # Initialize numpy
 import posixpath

From bb78ce6aed67f364e20b7d36256c7a594ae7d0bc Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Sun, 11 Sep 2022 16:20:48 -0600
Subject: [PATCH 0884/1504] update version in docstring

---
 src/netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index dd4599b92..5acd32c8d 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1,5 +1,5 @@
 """
-Version 1.6.0
+Version 1.6.1
 -------------
 
 # Introduction

From 54ca2a00659a0339a956d62c93920cbbcb15c20b Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Sun, 11 Sep 2022 16:23:57 -0600
Subject: [PATCH 0885/1504] add set_alignment/get_alignment to __all__, update
 docs

---
 docs/index.html         | 581 ++++++++++++++++++++++++++--------------
 src/netCDF4/__init__.py |   2 +-
 2 files changed, 376 insertions(+), 207 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 55793dd5b..6fc81dc20 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -3,25 +3,25 @@
 
     
     
-    
+    
     netCDF4 API documentation
-    
 
-
-
-
-
-
-        
      
     
      
             
      
                     
      
 netCDF4    
      
 
-                        
      Version 1.6.0
      
+                        
      Version 1.6.1
      
 
 
      Introduction
      
 
@@ -582,7 +601,7 @@ 
      Creating/Opening/Closing a netCDF
 
 
      Here's an example:
      
 
-
      >>> from netCDF4 import Dataset
+
      >>> from netCDF4 import Dataset
 >>> rootgrp = Dataset("test.nc", "w", format="NETCDF4")
 >>> print(rootgrp.data_model)
 NETCDF4
@@ -611,7 +630,7 @@ 
      Groups in a netCDF file
      
 NETCDF4 formatted files support Groups, if you try to create a Group
 in a netCDF 3 file you will get an error message.
      
 
-
      >>> rootgrp = Dataset("test.nc", "a")
+
      >>> rootgrp = Dataset("test.nc", "a")
 >>> fcstgrp = rootgrp.createGroup("forecasts")
 >>> analgrp = rootgrp.createGroup("analyses")
 >>> print(rootgrp.groups)
@@ -635,7 +654,7 @@ 
      Groups in a netCDF file
      
 that group.  To simplify the creation of nested groups, you can
 use a unix-like path as an argument to Dataset.createGroup.
      
 
-
      >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
+
      >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
 >>> fcstgrp2 = rootgrp.createGroup("/forecasts/model2")
 
      
 
@@ -649,7 +668,7 @@ 
      Groups in a netCDF file
      
 to walk the directory tree. Note that printing the Dataset or Group
 object yields summary information about it's contents.
      
 
-
      >>> def walktree(top):
+
      >>> def walktree(top):
 ...     yield top.groups.values()
 ...     for value in top.groups.values():
 ...         yield from walktree(value)
@@ -699,7 +718,7 @@ 
      Dimensions in a netCDF file
      
 dimension is a new netCDF 4 feature, in netCDF 3 files there may be only
 one, and it must be the first (leftmost) dimension of the variable.
      
 
-
      >>> level = rootgrp.createDimension("level", None)
+
      >>> level = rootgrp.createDimension("level", None)
 >>> time = rootgrp.createDimension("time", None)
 >>> lat = rootgrp.createDimension("lat", 73)
 >>> lon = rootgrp.createDimension("lon", 144)
@@ -707,7 +726,7 @@ 
      Dimensions in a netCDF file
      
 
 
      All of the Dimension instances are stored in a python dictionary.
      
 
-
      >>> print(rootgrp.dimensions)
+
      >>> print(rootgrp.dimensions)
 {'level': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0, 'time': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0, 'lat': <class 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 73, 'lon': <class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144}
 
      
 
@@ -716,7 +735,7 @@ 
      Dimensions in a netCDF file
      
 Dimension.isunlimited method of a Dimension instance
 be used to determine if the dimensions is unlimited, or appendable.
      
 
-
      >>> print(len(lon))
+
      >>> print(len(lon))
 144
 >>> print(lon.isunlimited())
 False
@@ -728,7 +747,7 @@ 
      Dimensions in a netCDF file
      
 provides useful summary info, including the name and length of the dimension,
 and whether it is unlimited.
      
 
-
      >>> for dimobj in rootgrp.dimensions.values():
+
      >>> for dimobj in rootgrp.dimensions.values():
 ...     print(dimobj)
 <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0
 <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0
@@ -773,7 +792,7 @@ 
      Variables in a netCDF file
      
 method returns an instance of the Variable class whose methods can be
 used later to access and set variable data and attributes.
      
 
-
      >>> times = rootgrp.createVariable("time","f8",("time",))
+
      >>> times = rootgrp.createVariable("time","f8",("time",))
 >>> levels = rootgrp.createVariable("level","i4",("level",))
 >>> latitudes = rootgrp.createVariable("lat","f4",("lat",))
 >>> longitudes = rootgrp.createVariable("lon","f4",("lon",))
@@ -785,7 +804,7 @@ 
      Variables in a netCDF file
      
 
      To get summary info on a Variable instance in an interactive session,
 just print it.
      
 
-
      >>> print(temp)
+
      >>> print(temp)
 <class 'netCDF4._netCDF4.Variable'>
 float32 temp(time, level, lat, lon)
     units: K
@@ -796,7 +815,7 @@ 
      Variables in a netCDF file
      
 
 
      You can use a path to create a Variable inside a hierarchy of groups.
      
 
-
      >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
+
      >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
 
      
 
 
      If the intermediate groups do not yet exist, they will be created.
      
@@ -804,7 +823,7 @@ 
      Variables in a netCDF file
      
 
      You can also query a Dataset or Group instance directly to obtain Group or
 Variable instances using paths.
      
 
-
      >>> print(rootgrp["/forecasts/model1"])  # a Group instance
+
      >>> print(rootgrp["/forecasts/model1"])  # a Group instance
 <class 'netCDF4._netCDF4.Group'>
 group /forecasts/model1:
     dimensions(sizes): 
@@ -822,7 +841,7 @@ 
      Variables in a netCDF file
      
 
      All of the variables in the Dataset or Group are stored in a
 Python dictionary, in the same way as the dimensions:
      
 
-
      >>> print(rootgrp.variables)
+
      >>> print(rootgrp.variables)
 {'time': <class 'netCDF4._netCDF4.Variable'>
 float64 time(time)
 unlimited dimensions: time
@@ -865,7 +884,7 @@ 
      Attributes in a netCDF file
      
 variables. Attributes can be strings, numbers or sequences. Returning to
 our example,
      
 
-
      >>> import time
+
      >>> import time
 >>> rootgrp.description = "bogus example script"
 >>> rootgrp.history = "Created " + time.ctime(time.time())
 >>> rootgrp.source = "netCDF4 python module tutorial"
@@ -883,7 +902,7 @@ 
      Attributes in a netCDF file
      
 built-in dir Python function will return a bunch of private methods
 and attributes that cannot (or should not) be modified by the user.
      
 
-
      >>> for name in rootgrp.ncattrs():
+
      >>> for name in rootgrp.ncattrs():
 ...     print("Global attr {} = {}".format(name, getattr(rootgrp, name)))
 Global attr description = bogus example script
 Global attr history = Created Mon Jul  8 14:19:41 2019
@@ -894,7 +913,7 @@ 
      Attributes in a netCDF file
      
 instance provides all the netCDF attribute name/value pairs in a python
 dictionary:
      
 
-
      >>> print(rootgrp.__dict__)
+
      >>> print(rootgrp.__dict__)
 {'description': 'bogus example script', 'history': 'Created Mon Jul  8 14:19:41 2019', 'source': 'netCDF4 python module tutorial'}
 
      
 
@@ -907,7 +926,7 @@ 
      Writing data
 
      Now that you have a netCDF Variable instance, how do you put data
 into it? You can just treat it like an array and assign data to a slice.
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> lats =  np.arange(-90,91,2.5)
 >>> lons =  np.arange(-180,180,2.5)
 >>> latitudes[:] = lats
@@ -927,7 +946,7 @@ 
      Writing data
 objects with unlimited dimensions will grow along those dimensions if you
 assign data outside the currently defined range of indices.
      
 
-
      >>> # append along two unlimited dimensions by assigning to slice.
+
      >>> # append along two unlimited dimensions by assigning to slice.
 >>> nlats = len(rootgrp.dimensions["lat"])
 >>> nlons = len(rootgrp.dimensions["lon"])
 >>> print("temp shape before adding data = {}".format(temp.shape))
@@ -947,7 +966,7 @@ 
      Writing data
 along the level dimension of the variable temp, even though no
 data has yet been assigned to levels.
      
 
-
      >>> # now, assign data to levels dimension variable.
+
      >>> # now, assign data to levels dimension variable.
 >>> levels[:] =  [1000.,850.,700.,500.,300.,250.,200.,150.,100.,50.]
 
      
 
@@ -960,7 +979,7 @@ 
      Writing data
 allowed, and these indices work independently along each dimension (similar
 to the way vector subscripts work in fortran).  This means that
      
 
-
      >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
+
      >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
 (4, 4)
 
      
 
@@ -978,14 +997,14 @@ 
      Writing data
 
 
      For example,
      
 
-
      >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
+
      >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
 
      
 
 
      will extract time indices 0,2 and 4, pressure levels
 850, 500 and 200 hPa, all Northern Hemisphere latitudes and Eastern
 Hemisphere longitudes, resulting in a numpy array of shape  (3, 3, 36, 71).
      
 
-
      >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
+
      >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
 shape of fancy temp slice = (3, 3, 36, 71)
 
      
 
@@ -1018,7 +1037,7 @@ 
      Dealing with time coordinates
      
 provided by cftime to do just that.
 Here's an example of how they can be used:
      
 
-
      >>> # fill in times.
+
      >>> # fill in times.
 >>> from datetime import datetime, timedelta
 >>> from cftime import num2date, date2num
 >>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
@@ -1058,7 +1077,7 @@ 
      Reading data from a multi
 NETCDF4_CLASSIC format (NETCDF4 formatted multi-file
 datasets are not supported).
      
 
-
      >>> for nf in range(10):
+
      >>> for nf in range(10):
 ...     with Dataset("mftest%s.nc" % nf, "w", format="NETCDF4_CLASSIC") as f:
 ...         _ = f.createDimension("x",None)
 ...         x = f.createVariable("x","i",("x",))
@@ -1067,7 +1086,7 @@ 
      Reading data from a multi
 
 
      Now read all the files back in at once with MFDataset
      
 
-
      >>> from netCDF4 import MFDataset
+
      >>> from netCDF4 import MFDataset
 >>> f = MFDataset("mftest*nc")
 >>> print(f.variables["x"][:])
 [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
@@ -1134,22 +1153,22 @@ 
      Efficient compression of netC
 
 
      In our example, try replacing the line
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
 
      
 
 
      with
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib')
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib')
 
      
 
 
      and then
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',least_significant_digit=3)
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',least_significant_digit=3)
 
      
 
 
      or with netcdf-c >= 4.9.0
      
 
-
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',significant_digits=4)
+
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',significant_digits=4)
 
      
 
 
      and see how much smaller the resulting files are.
      
@@ -1170,7 +1189,7 @@ 
      Beyond ho
 Since there is no native complex data type in netcdf, compound types are handy
 for storing numpy complex arrays.  Here's an example:
      
 
-
      >>> f = Dataset("complex.nc","w")
+
      >>> f = Dataset("complex.nc","w")
 >>> size = 3 # length of 1-d complex array
 >>> # create sample complex data.
 >>> datac = np.exp(1j*(1.+np.linspace(0, np.pi, size)))
@@ -1206,7 +1225,7 @@ 
      Beyond ho
 in a Python dictionary, just like variables and dimensions. As always, printing
 objects gives useful summary information in an interactive session:
      
 
-
      >>> print(f)
+
      >>> print(f)
 <class 'netCDF4._netCDF4.Dataset'>
 root group (NETCDF4 data model, file format HDF5):
     dimensions(sizes): x_dim(3)
@@ -1231,7 +1250,7 @@ 
      Variable-length (vlen) data types
      
 data type, use the Dataset.createVLType method
 method of a Dataset or Group instance.
      
 
-
      >>> f = Dataset("tst_vlen.nc","w")
+
      >>> f = Dataset("tst_vlen.nc","w")
 >>> vlen_t = f.createVLType(np.int32, "phony_vlen")
 
      
 
@@ -1241,7 +1260,7 @@ 
      Variable-length (vlen) data types
      
 but compound data types cannot.
 A new variable can then be created using this datatype.
      
 
-
      >>> x = f.createDimension("x",3)
+
      >>> x = f.createDimension("x",3)
 >>> y = f.createDimension("y",4)
 >>> vlvar = f.createVariable("phony_vlen_var", vlen_t, ("y","x"))
 
      
@@ -1254,7 +1273,7 @@ 
      Variable-length (vlen) data types
      
 In this case, they contain 1-D numpy int32 arrays of random length between
 1 and 10.
      
 
-
      >>> import random
+
      >>> import random
 >>> random.seed(54321)
 >>> data = np.empty(len(y)*len(x),object)
 >>> for n in range(len(y)*len(x)):
@@ -1294,7 +1313,7 @@ 
      Variable-length (vlen) data types
      
 with fixed length greater than 1) when calling the
 Dataset.createVariable method.
      
 
-
      >>> z = f.createDimension("z",10)
+
      >>> z = f.createDimension("z",10)
 >>> strvar = f.createVariable("strvar", str, "z")
 
      
 
@@ -1302,7 +1321,7 @@ 
      Variable-length (vlen) data types
      
 random lengths between 2 and 12 characters, and the data in the object
 array is assigned to the vlen string variable.
      
 
-
      >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
+
      >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
 >>> data = np.empty(10,"O")
 >>> for n in range(10):
 ...     stringlen = random.randint(2,12)
@@ -1341,7 +1360,7 @@ 
      Enum data type
      
 values and their names are used to define an Enum data type using
 Dataset.createEnumType.
      
 
-
      >>> nc = Dataset('clouds.nc','w')
+
      >>> nc = Dataset('clouds.nc','w')
 >>> # python dict with allowed values and their names.
 >>> enum_dict = {'Altocumulus': 7, 'Missing': 255,
 ... 'Stratus': 2, 'Clear': 0,
@@ -1359,7 +1378,7 @@ 
      Enum data type
      
 is made to write an integer value not associated with one of the
 specified names.
      
 
-
      >>> time = nc.createDimension('time',None)
+
      >>> time = nc.createDimension('time',None)
 >>> # create a 1d variable of type 'cloud_type'.
 >>> # The fill_value is set to the 'Missing' named value.
 >>> cloud_var = nc.createVariable('primary_cloud',cloud_type,'time',
@@ -1396,7 +1415,7 @@ 
      Parallel IO
      
 available. To use parallel IO, your program must be running in an MPI
 environment using mpi4py.
      
 
-
      >>> from mpi4py import MPI
+
      >>> from mpi4py import MPI
 >>> import numpy as np
 >>> from netCDF4 import Dataset
 >>> rank = MPI.COMM_WORLD.rank  # The process ID (integer 0-3 for 4-process run)
@@ -1408,7 +1427,7 @@ 
      Parallel IO
      
 when a new dataset is created or an existing dataset is opened,
 use the parallel keyword to enable parallel access.
      
 
-
      >>> nc = Dataset('parallel_test.nc','w',parallel=True)
+
      >>> nc = Dataset('parallel_test.nc','w',parallel=True)
 
      
 
 
      The optional comm keyword may be used to specify a particular
@@ -1416,7 +1435,7 @@ 
      Parallel IO
      
 can now write to the file indepedently.  In this example the process rank is
 written to a different variable index on each task
      
 
-
      >>> d = nc.createDimension('dim',4)
+
      >>> d = nc.createDimension('dim',4)
 >>> v = nc.createVariable('var', np.int64, 'dim')
 >>> v[rank] = rank
 >>> nc.close()
@@ -1483,7 +1502,7 @@ 
      Dealing with strings
      
 stringtochar is used to convert the numpy string array to an array of
 characters with one more dimension. For example,
      
 
-
      >>> from netCDF4 import stringtochar
+
      >>> from netCDF4 import stringtochar
 >>> nc = Dataset('stringtest.nc','w',format='NETCDF4_CLASSIC')
 >>> _ = nc.createDimension('nchars',3)
 >>> _ = nc.createDimension('nstrings',None)
@@ -1516,7 +1535,7 @@ 
      Dealing with strings
      
 character array dtype under the hood when creating the netcdf compound type.
 Here's an example:
      
 
-
      >>> nc = Dataset('compoundstring_example.nc','w')
+
      >>> nc = Dataset('compoundstring_example.nc','w')
 >>> dtype = np.dtype([('observation', 'f4'),
 ...                      ('station_name','S10')])
 >>> station_data_t = nc.createCompoundType(dtype,'station_data')
@@ -1561,7 +1580,7 @@ 
      In-memory (diskless) Datasets
      
 object representing the Dataset. Below are examples illustrating both
 approaches.
      
 
-
      >>> # create a diskless (in-memory) Dataset,
+
      >>> # create a diskless (in-memory) Dataset,
 >>> # and persist the file to disk when it is closed.
 >>> nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
 >>> d = nc.createDimension('x',None)
@@ -1623,7 +1642,7 @@ 
      In-memory (diskless) Datasets
      
 the parallel IO example, which is in examples/mpi_example.py.
 Unit tests are in the test directory.
      
 
-
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
+
      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov
      
 
 
      copyright: 2008 by Jeffrey Whitaker.
      
 
@@ -1636,7 +1655,7 @@ 
      In-memory (diskless) Datasets
      
 
                         
      
             View Source
-            
      # init for netCDF4. package
+            
      # init for netCDF4. package
 # Docstring comes from extension module _netCDF4.
 from ._netCDF4 import *
 # Need explicit imports for names beginning with underscores
@@ -1650,12 +1669,13 @@ 
      In-memory (diskless) Datasets
      
                        __has_bzip2_support__, __has_blosc_support__, __has_szip_support__)
 import os
 __all__ =\
-['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
+['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache','set_alignment','get_alignment']
 # if HDF5_PLUGIN_PATH not set, point to package path if plugins live there
+pluginpath = os.path.join(__path__[0],'plugins')
 if 'HDF5_PLUGIN_PATH' not in os.environ and\
-    (os.path.exists(os.path.join(__path__[0],'lib__nczhdf5filters.so')) or\
-    os.path.exists(os.path.join(__path__[0],'lib__nczhdf5filters.dylib'))):
-    os.environ['HDF5_PLUGIN_PATH']=__path__[0]
+    (os.path.exists(os.path.join(pluginpath,'lib__nczhdf5filters.so')) or\
+     os.path.exists(os.path.join(pluginpath,'lib__nczhdf5filters.dylib'))):
+    os.environ['HDF5_PLUGIN_PATH']=pluginpath
 
      
 
         
      
@@ -1670,7 +1690,7 @@ 
      In-memory (diskless) Datasets
      
         Dataset:
     
      
 
-        
+    
             
      A netCDF Dataset is a collection of dimensions, groups, variables and
 attributes. Together they describe the meaning of data and relations among
 data fields stored in a netCDF file. See Dataset.__init__ for more
@@ -1748,7 +1768,7 @@ 
      In-memory (diskless) Datasets
      
             Dataset()
     
      
 
-        
+    
             
      __init__(self, filename, mode="r", clobber=True, diskless=False,
 persist=False, keepweakref=False, memory=None, encoding=None,
 parallel=False, comm=None, info=None, format='NETCDF4')
      
@@ -1854,7 +1874,7 @@ 
      In-memory (diskless) Datasets
      
             filepath(unknown):
     
      
 
-        
+    
             
      filepath(self,encoding=None)
      
 
 
      Get the file system path (or the opendap URL) which was used to
@@ -1873,7 +1893,7 @@ 
      In-memory (diskless) Datasets
      
             close(unknown):
     
      
 
-        
+    
             
      close(self)
      
 
 
      Close the Dataset.
      
@@ -1889,7 +1909,7 @@ 
      In-memory (diskless) Datasets
      
             isopen(unknown):
     
      
 
-        
+    
             
      isopen(self)
      
 
 
      Is the Dataset open or closed?
      
@@ -1905,7 +1925,7 @@ 
      In-memory (diskless) Datasets
      
             sync(unknown):
     
      
 
-        
+    
             
      sync(self)
      
 
 
      Writes all buffered data in the Dataset to the disk file.
      
@@ -1921,7 +1941,7 @@ 
      In-memory (diskless) Datasets
      
             set_fill_on(unknown):
     
      
 
-        
+    
             
      set_fill_on(self)
      
 
 
      Sets the fill mode for a Dataset open for writing to on.
      
@@ -1945,7 +1965,7 @@ 
      In-memory (diskless) Datasets
      
             set_fill_off(unknown):
     
      
 
-        
+    
             
      set_fill_off(self)
      
 
 
      Sets the fill mode for a Dataset open for writing to off.
      
@@ -1965,7 +1985,7 @@ 
      In-memory (diskless) Datasets
      
             createDimension(unknown):
     
      
 
-        
+    
             
      createDimension(self, dimname, size=None)
      
 
 
      Creates a new dimension with the given dimname and size.
      
@@ -1989,7 +2009,7 @@ 
      In-memory (diskless) Datasets
      
             renameDimension(unknown):
     
      
 
-        
+    
             
      renameDimension(self, oldname, newname)
      
 
 
      rename a Dimension named oldname to newname.
      
@@ -2005,7 +2025,7 @@ 
      In-memory (diskless) Datasets
      
             createCompoundType(unknown):
     
      
 
-        
+    
             
      createCompoundType(self, datatype, datatype_name)
      
 
 
      Creates a new compound data type named datatype_name from the numpy
@@ -2030,7 +2050,7 @@ 
      In-memory (diskless) Datasets
      
             createVLType(unknown):
     
      
 
-        
+    
             
      createVLType(self, datatype, datatype_name)
      
 
 
      Creates a new VLEN data type named datatype_name from a numpy
@@ -2050,7 +2070,7 @@ 
      In-memory (diskless) Datasets
      
             createEnumType(unknown):
     
      
 
-        
+    
             
      createEnumType(self, datatype, datatype_name, enum_dict)
      
 
 
      Creates a new Enum data type named datatype_name from a numpy
@@ -2071,7 +2091,7 @@ 
      In-memory (diskless) Datasets
      
             createVariable(unknown):
     
      
 
-        
+    
             
      createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False,
 complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None,
 szip_coding='nn', szip_pixels_per_block=8, blosc_shuffle=1,
@@ -2166,7 +2186,7 @@ 
      In-memory (diskless) Datasets
      
 
 
      The optional keyword fill_value can be used to override the default
 netCDF _FillValue (the value that the variable gets filled with before
-any data is written to it, defaults given in the dict netCDF4.default_fillvals).
+any data is written to it, defaults given in the dict netCDF4.default_fillvals).
 If fill_value is set to False, then the variable is not pre-filled.
      
 
 
      If the optional keyword parameters least_significant_digit or significant_digits are
@@ -2234,7 +2254,7 @@ 
      In-memory (diskless) Datasets
      
             renameVariable(unknown):
     
      
 
-        
+    
             
      renameVariable(self, oldname, newname)
      
 
 
      rename a Variable named oldname to newname
      
@@ -2250,7 +2270,7 @@ 
      In-memory (diskless) Datasets
      
             createGroup(unknown):
     
      
 
-        
+    
             
      createGroup(self, groupname)
      
 
 
      Creates a new Group with the given groupname.
      
@@ -2276,7 +2296,7 @@ 
      In-memory (diskless) Datasets
      
             ncattrs(unknown):
     
      
 
-        
+    
             
      ncattrs(self)
      
 
 
      return netCDF global attribute names for this Dataset or Group in a list.
      
@@ -2292,7 +2312,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr(unknown):
     
      
 
-        
+    
             
      setncattr(self,name,value)
      
 
 
      set a netCDF dataset or group attribute using name,value pair.
@@ -2310,7 +2330,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr_string(unknown):
     
      
 
-        
+    
             
      setncattr_string(self,name,value)
      
 
 
      set a netCDF dataset or group string attribute using name,value pair.
@@ -2328,7 +2348,7 @@ 
      In-memory (diskless) Datasets
      
             setncatts(unknown):
     
      
 
-        
+    
             
      setncatts(self,attdict)
      
 
 
      set a bunch of netCDF dataset or group attributes at once using a python dictionary.
@@ -2347,7 +2367,7 @@ 
      In-memory (diskless) Datasets
      
             getncattr(unknown):
     
      
 
-        
+    
             
      getncattr(self,name)
      
 
 
      retrieve a netCDF dataset or group attribute.
@@ -2368,7 +2388,7 @@ 
      In-memory (diskless) Datasets
      
             delncattr(unknown):
     
      
 
-        
+    
             
      delncattr(self,name,value)
      
 
 
      delete a netCDF dataset or group attribute.  Use if you need to delete a
@@ -2386,7 +2406,7 @@ 
      In-memory (diskless) Datasets
      
             renameAttribute(unknown):
     
      
 
-        
+    
             
      renameAttribute(self, oldname, newname)
      
 
 
      rename a Dataset or Group attribute named oldname to newname.
      
@@ -2402,7 +2422,7 @@ 
      In-memory (diskless) Datasets
      
             renameGroup(unknown):
     
      
 
-        
+    
             
      renameGroup(self, oldname, newname)
      
 
 
      rename a Group named oldname to newname (requires netcdf >= 4.3.1).
      
@@ -2418,7 +2438,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_chartostring(unknown):
     
      
 
-        
+    
             
      set_auto_chartostring(self, True_or_False)
      
 
 
      Call Variable.set_auto_chartostring for all variables contained in this Dataset or
@@ -2443,7 +2463,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_maskandscale(unknown):
     
      
 
-        
+    
             
      set_auto_maskandscale(self, True_or_False)
      
 
 
      Call Variable.set_auto_maskandscale for all variables contained in this Dataset or
@@ -2466,7 +2486,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_mask(unknown):
     
      
 
-        
+    
             
      set_auto_mask(self, True_or_False)
      
 
 
      Call Variable.set_auto_mask for all variables contained in this Dataset or
@@ -2490,7 +2510,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_scale(unknown):
     
      
 
-        
+    
             
      set_auto_scale(self, True_or_False)
      
 
 
      Call Variable.set_auto_scale for all variables contained in this Dataset or
@@ -2513,7 +2533,7 @@ 
      In-memory (diskless) Datasets
      
             set_always_mask(unknown):
     
      
 
-        
+    
             
      set_always_mask(self, True_or_False)
      
 
 
      Call Variable.set_always_mask for all variables contained in
@@ -2541,7 +2561,7 @@ 
      In-memory (diskless) Datasets
      
             set_ncstring_attrs(unknown):
     
      
 
-        
+    
             
      set_ncstring_attrs(self, True_or_False)
      
 
 
      Call Variable.set_ncstring_attrs for all variables contained in
@@ -2566,7 +2586,7 @@ 
      In-memory (diskless) Datasets
      
             get_variables_by_attributes(unknown):
     
      
 
-        
+    
             
      get_variables_by_attribute(self, **kwargs)
      
 
 
      Returns a list of variables that match specific conditions.
      
@@ -2574,7 +2594,7 @@ 
      In-memory (diskless) Datasets
      
 
      Can pass in key=value parameters and variables are returned that
 contain all of the matches. For example,
      
 
-
      >>> # Get variables with x-axis attribute.
+
      >>> # Get variables with x-axis attribute.
 >>> vs = nc.get_variables_by_attributes(axis='X')
 >>> # Get variables with matching "standard_name" attribute
 >>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
@@ -2585,7 +2605,7 @@ 
      In-memory (diskless) Datasets
      
 the attribute value.  None is given as the attribute value when the
 attribute does not exist on the variable. For example,
      
 
-
      >>> # Get Axis variables
+
      >>> # Get Axis variables
 >>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
 >>> # Get variables that don't have an "axis" attribute
 >>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
@@ -2604,7 +2624,7 @@ 
      In-memory (diskless) Datasets
      
             fromcdl(unknown):
     
      
 
-        
+    
             
      fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')
      
 
 
      call ncgen via subprocess to create Dataset from CDL
@@ -2634,7 +2654,7 @@ 
      In-memory (diskless) Datasets
      
             tocdl(unknown):
     
      
 
-        
+    
             
      tocdl(self, coordvars=False, data=False, outfile=None)
      
 
 
      call ncdump via subprocess to create CDL
@@ -2649,13 +2669,74 @@ 
      In-memory (diskless) Datasets
      
 
      
 
 
+                            
      
+                            
      
+                                        
      #  
+
+        
+            def
+            has_blosc_filter(unknown):
+    
      
+
+    
+            
      has_blosc_filter(self)
+returns True if blosc compression filter is available
      
+
      
+
+
+                            
      
+                            
      
+                                        
      #  
+
+        
+            def
+            has_zstd_filter(unknown):
+    
      
+
+    
+            
      has_zstd_filter(self)
+returns True if zstd compression filter is available
      
+
      
+
+
+                            
      
+                            
      
+                                        
      #  
+
+        
+            def
+            has_bzip2_filter(unknown):
+    
      
+
+    
+            
      has_bzip2_filter(self)
+returns True if bzip2 compression filter is available
      
+
      
+
+
+                            
      
+                            
      
+                                        
      #  
+
+        
+            def
+            has_szip_filter(unknown):
+    
      
+
+    
+            
      has_szip_filter(self)
+returns True if szip compression filter is available
      
+
      
+
+
                             
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.Dataset' objects>
+        name
     
      
 
+    
             
      string name of Group instance
      
 
      
 
@@ -2664,109 +2745,121 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        groups = <attribute 'groups' of 'netCDF4._netCDF4.Dataset' objects>
+        groups
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Dataset' objects>
+        dimensions
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        variables = <attribute 'variables' of 'netCDF4._netCDF4.Dataset' objects>
+        variables
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        disk_format = <attribute 'disk_format' of 'netCDF4._netCDF4.Dataset' objects>
+        disk_format
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        path = <attribute 'path' of 'netCDF4._netCDF4.Dataset' objects>
+        path
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        parent = <attribute 'parent' of 'netCDF4._netCDF4.Dataset' objects>
+        parent
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        file_format = <attribute 'file_format' of 'netCDF4._netCDF4.Dataset' objects>
+        file_format
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        data_model = <attribute 'data_model' of 'netCDF4._netCDF4.Dataset' objects>
+        data_model
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        cmptypes = <attribute 'cmptypes' of 'netCDF4._netCDF4.Dataset' objects>
+        cmptypes
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        vltypes = <attribute 'vltypes' of 'netCDF4._netCDF4.Dataset' objects>
+        vltypes
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        enumtypes = <attribute 'enumtypes' of 'netCDF4._netCDF4.Dataset' objects>
+        enumtypes
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        keepweakref = <attribute 'keepweakref' of 'netCDF4._netCDF4.Dataset' objects>
+        keepweakref
     
      
 
     
+    
 
                             
      
                 
      
@@ -2779,7 +2872,7 @@ 
      In-memory (diskless) Datasets
      
         Variable:
     
      
 
-        
+    
             
      A netCDF Variable is used to read and write netCDF data.  They are
 analogous to numpy array objects. See Variable.__init__ for more
 details.
      
@@ -2863,7 +2956,7 @@ 
      In-memory (diskless) Datasets
      
             Variable()
     
      
 
-        
+    
             
      __init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False,
 complevel=4, shuffle=True, szip_coding='nn', szip_pixels_per_block=8,
 blosc_shuffle=1, fletcher32=False, contiguous=False,
@@ -2984,7 +3077,7 @@ 
      In-memory (diskless) Datasets
      
 value that the variable gets filled with before any data is written to it)
 is replaced with this value.  If fill_value is set to False, then
 the variable is not pre-filled. The default netCDF fill values can be found
-in the dictionary netCDF4.default_fillvals.
      
+in the dictionary netCDF4.default_fillvals.
      
 
 
      chunk_cache: If specified, sets the chunk cache size for this variable.
 Persists as long as Dataset is open. Use set_var_chunk_cache to
@@ -3005,7 +3098,7 @@ 
      In-memory (diskless) Datasets
      
             group(unknown):
     
      
 
-        
+    
             
      group(self)
      
 
 
      return the group that this Variable is a member of.
      
@@ -3021,7 +3114,7 @@ 
      In-memory (diskless) Datasets
      
             ncattrs(unknown):
     
      
 
-        
+    
             
      ncattrs(self)
      
 
 
      return netCDF attribute names for this Variable in a list.
      
@@ -3037,7 +3130,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr(unknown):
     
      
 
-        
+    
             
      setncattr(self,name,value)
      
 
 
      set a netCDF variable attribute using name,value pair.  Use if you need to set a
@@ -3055,7 +3148,7 @@ 
      In-memory (diskless) Datasets
      
             setncattr_string(unknown):
     
      
 
-        
+    
             
      setncattr_string(self,name,value)
      
 
 
      set a netCDF variable string attribute using name,value pair.
@@ -3074,7 +3167,7 @@ 
      In-memory (diskless) Datasets
      
             setncatts(unknown):
     
      
 
-        
+    
             
      setncatts(self,attdict)
      
 
 
      set a bunch of netCDF variable attributes at once using a python dictionary.
@@ -3093,7 +3186,7 @@ 
      In-memory (diskless) Datasets
      
             getncattr(unknown):
     
      
 
-        
+    
             
      getncattr(self,name)
      
 
 
      retrieve a netCDF variable attribute.  Use if you need to set a
@@ -3114,7 +3207,7 @@ 
      In-memory (diskless) Datasets
      
             delncattr(unknown):
     
      
 
-        
+    
             
      delncattr(self,name,value)
      
 
 
      delete a netCDF variable attribute.  Use if you need to delete a
@@ -3132,7 +3225,7 @@ 
      In-memory (diskless) Datasets
      
             filters(unknown):
     
      
 
-        
+    
             
      filters(self)
      
 
 
      return dictionary containing HDF5 filter parameters.
      
@@ -3148,7 +3241,7 @@ 
      In-memory (diskless) Datasets
      
             quantization(unknown):
     
      
 
-        
+    
             
      quantization(self)
      
 
 
      return number of significant digits and the algorithm used in quantization.
@@ -3165,7 +3258,7 @@ 
      In-memory (diskless) Datasets
      
             endian(unknown):
     
      
 
-        
+    
             
      endian(self)
      
 
 
      return endian-ness (little,big,native) of variable (as stored in HDF5 file).
      
@@ -3181,7 +3274,7 @@ 
      In-memory (diskless) Datasets
      
             chunking(unknown):
     
      
 
-        
+    
             
      chunking(self)
      
 
 
      return variable chunking information.  If the dataset is
@@ -3200,7 +3293,7 @@ 
      In-memory (diskless) Datasets
      
             get_var_chunk_cache(unknown):
     
      
 
-        
+    
             
      get_var_chunk_cache(self)
      
 
 
      return variable chunk cache information in a tuple (size,nelems,preemption).
@@ -3218,7 +3311,7 @@ 
      In-memory (diskless) Datasets
      
             set_var_chunk_cache(unknown):
     
      
 
-        
+    
             
      set_var_chunk_cache(self,size=None,nelems=None,preemption=None)
      
 
 
      change variable chunk cache settings.
@@ -3236,7 +3329,7 @@ 
      In-memory (diskless) Datasets
      
             renameAttribute(unknown):
     
      
 
-        
+    
             
      renameAttribute(self, oldname, newname)
      
 
 
      rename a Variable attribute named oldname to newname.
      
@@ -3252,7 +3345,7 @@ 
      In-memory (diskless) Datasets
      
             assignValue(unknown):
     
      
 
-        
+    
             
      assignValue(self, val)
      
 
 
      assign a value to a scalar variable.  Provided for compatibility with
@@ -3269,7 +3362,7 @@ 
      In-memory (diskless) Datasets
      
             getValue(unknown):
     
      
 
-        
+    
             
      getValue(self)
      
 
 
      get the value of a scalar variable.  Provided for compatibility with
@@ -3286,7 +3379,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_chartostring(unknown):
     
      
 
-        
+    
             
      set_auto_chartostring(self,chartostring)
      
 
 
      turn on or off automatic conversion of character variable data to and
@@ -3317,7 +3410,7 @@ 
      In-memory (diskless) Datasets
      
             use_nc_get_vars(unknown):
     
      
 
-        
+    
             
      use_nc_get_vars(self,_use_get_vars)
      
 
 
      enable the use of netcdf library routine nc_get_vars
@@ -3337,7 +3430,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_maskandscale(unknown):
     
      
 
-        
+    
             
      set_auto_maskandscale(self,maskandscale)
      
 
 
      turn on or off automatic conversion of variable data to and
@@ -3401,7 +3494,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_scale(unknown):
     
      
 
-        
+    
             
      set_auto_scale(self,scale)
      
 
 
      turn on or off automatic packing/unpacking of variable
@@ -3450,7 +3543,7 @@ 
      In-memory (diskless) Datasets
      
             set_auto_mask(unknown):
     
      
 
-        
+    
             
      set_auto_mask(self,mask)
      
 
 
      turn on or off automatic conversion of variable data to and
@@ -3485,7 +3578,7 @@ 
      In-memory (diskless) Datasets
      
             set_always_mask(unknown):
     
      
 
-        
+    
             
      set_always_mask(self,always_mask)
      
 
 
      turn on or off conversion of data without missing values to regular
@@ -3508,7 +3601,7 @@ 
      In-memory (diskless) Datasets
      
             set_ncstring_attrs(unknown):
     
      
 
-        
+    
             
      set_always_mask(self,ncstring_attrs)
      
 
 
      turn on or off creating NC_STRING string attributes.
      
@@ -3530,7 +3623,7 @@ 
      In-memory (diskless) Datasets
      
             set_collective(unknown):
     
      
 
-        
+    
             
      set_collective(self,True_or_False)
      
 
 
      turn on or off collective parallel IO access. Ignored if file is not
@@ -3547,7 +3640,7 @@ 
      In-memory (diskless) Datasets
      
             get_dims(unknown):
     
      
 
-        
+    
             
      get_dims(self)
      
 
 
      return a tuple of Dimension instances associated with this
@@ -3559,9 +3652,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.Variable' objects>
+        name
     
      
 
+    
             
      string name of Variable instance
      
 
      
 
@@ -3570,9 +3664,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        datatype = <attribute 'datatype' of 'netCDF4._netCDF4.Variable' objects>
+        datatype
     
      
 
+    
             
      numpy data type (for primitive data types) or
 VLType/CompoundType/EnumType instance 
 (for compound, vlen  or enum data types)
      
@@ -3583,9 +3678,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        shape = <attribute 'shape' of 'netCDF4._netCDF4.Variable' objects>
+        shape
     
      
 
+    
             
      find current sizes of all variable dimensions
      
 
      
 
@@ -3594,9 +3690,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        size = <attribute 'size' of 'netCDF4._netCDF4.Variable' objects>
+        size
     
      
 
+    
             
      Return the number of stored elements.
      
 
      
 
@@ -3605,9 +3702,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        dimensions = <attribute 'dimensions' of 'netCDF4._netCDF4.Variable' objects>
+        dimensions
     
      
 
+    
             
      get variables's dimension names
      
 
      
 
@@ -3616,55 +3714,61 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        ndim = <attribute 'ndim' of 'netCDF4._netCDF4.Variable' objects>
+        ndim
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.Variable' objects>
+        dtype
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        mask = <attribute 'mask' of 'netCDF4._netCDF4.Variable' objects>
+        mask
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        scale = <attribute 'scale' of 'netCDF4._netCDF4.Variable' objects>
+        scale
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        always_mask = <attribute 'always_mask' of 'netCDF4._netCDF4.Variable' objects>
+        always_mask
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        chartostring = <attribute 'chartostring' of 'netCDF4._netCDF4.Variable' objects>
+        chartostring
     
      
 
     
+    
 
                             
      
                 
@@ -3677,7 +3781,7 @@ 
      In-memory (diskless) Datasets
      
         Dimension:
     
      
 
-        
+    
             
      A netCDF Dimension is used to describe the coordinates of a Variable.
 See Dimension.__init__ for more details.
      
 
@@ -3703,7 +3807,7 @@ 
      In-memory (diskless) Datasets
      
             Dimension()
     
      
 
-        
+    
             
      __init__(self, group, name, size=None)
      
 
 
      Dimension constructor.
      
@@ -3729,7 +3833,7 @@ 
      In-memory (diskless) Datasets
      
             group(unknown):
     
      
 
-        
+    
             
      group(self)
      
 
 
      return the group that this Dimension is a member of.
      
@@ -3745,7 +3849,7 @@ 
      In-memory (diskless) Datasets
      
             isunlimited(unknown):
     
      
 
-        
+    
             
      isunlimited(self)
      
 
 
      returns True if the Dimension instance is unlimited, False otherwise.
      
@@ -3756,9 +3860,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.Dimension' objects>
+        name
     
      
 
+    
             
      string name of Dimension instance
      
 
      
 
@@ -3767,9 +3872,10 @@ 
      In-memory (diskless) Datasets
      
                             
      
                                             
      #  
 
-        size = <attribute 'size' of 'netCDF4._netCDF4.Dimension' objects>
+        size
     
      
 
+    
             
      current size of Dimension (calls len on Dimension instance)
      
 
      
 
@@ -3785,7 +3891,7 @@ 
      In-memory (diskless) Datasets
      
         Group(netCDF4.Dataset):
     
      
 
-        
+    
             
      Groups define a hierarchical namespace within a netCDF file. They are
 analogous to directories in a unix filesystem. Each Group behaves like
 a Dataset within a Dataset, and can contain it's own variables,
@@ -3809,7 +3915,7 @@ 
      In-memory (diskless) Datasets
      
             Group()
     
      
 
-        
+    
             
      __init__(self, parent, name)
 Group constructor.
      
 
@@ -3833,7 +3939,7 @@ 
      In-memory (diskless) Datasets
      
             close(unknown):
     
      
 
-        
+    
             
      close(self)
      
 
 
      overrides Dataset close method which does not apply to Group
@@ -3876,6 +3982,10 @@ 
      Inherited Members
      
                 
      get_variables_by_attributes
      
                 
      fromcdl
      
                 
      tocdl
      
+                
      has_blosc_filter
      
+                
      has_zstd_filter
      
+                
      has_bzip2_filter
      
+                
      has_szip_filter
      
                 
      name
      
                 
      groups
      
                 
      dimensions
      
@@ -3903,7 +4013,7 @@ 
      Inherited Members
      
         MFDataset(netCDF4.Dataset):
     
      
 
-        
+    
             
      Class for reading multi-file netCDF Datasets, making variables
 spanning multiple files appear as if they were in one file.
 Datasets must be in NETCDF4_CLASSIC, NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET
@@ -3913,7 +4023,7 @@ 
      Inherited Members
      
 
 
      Example usage (See MFDataset.__init__ for more details):
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> # create a series of netCDF files with a variable sharing
 >>> # the same unlimited dimension.
 >>> for nf in range(10):
@@ -3940,7 +4050,7 @@ 
      Inherited Members
      
             MFDataset(files, check=False, aggdim=None, exclude=[], master_file=None)
     
      
 
-        
+    
             
      __init__(self, files, check=False, aggdim=None, exclude=[],
 master_file=None)
      
 
@@ -3985,7 +4095,7 @@ 
      Inherited Members
      
             ncattrs(self):
     
      
 
-        
+    
             
      ncattrs(self)
      
 
 
      return the netcdf attribute names from the master file.
      
@@ -4001,7 +4111,7 @@ 
      Inherited Members
      
             close(self):
     
      
 
-        
+    
             
      close(self)
      
 
 
      close all the open files.
      
@@ -4042,6 +4152,10 @@ 
      Inherited Members
      
                 
      get_variables_by_attributes
      
                 
      fromcdl
      
                 
      tocdl
      
+                
      has_blosc_filter
      
+                
      has_zstd_filter
      
+                
      has_bzip2_filter
      
+                
      has_szip_filter
      
                 
      name
      
                 
      groups
      
                 
      dimensions
      
@@ -4069,13 +4183,13 @@ 
      Inherited Members
      
         MFTime(netCDF4._netCDF4._Variable):
     
      
 
-        
+    
             
      Class providing an interface to a MFDataset time Variable by imposing a unique common
 time unit and/or calendar to all files.
      
 
 
      Example usage (See MFTime.__init__ for more details):
      
 
-
      >>> import numpy as np
+
      >>> import numpy as np
 >>> f1 = Dataset("mftest_1.nc","w", format="NETCDF4_CLASSIC")
 >>> f2 = Dataset("mftest_2.nc","w", format="NETCDF4_CLASSIC")
 >>> f1.createDimension("time",None)
@@ -4111,7 +4225,7 @@ 
      Inherited Members
      
             MFTime(time, units=None, calendar=None)
     
      
 
-        
+    
             
      __init__(self, time, units=None, calendar=None)
      
 
 
      Create a time Variable with units consistent across a multifile
@@ -4155,7 +4269,7 @@ 
      Inherited Members
      
         CompoundType:
     
      
 
-        
+    
             
      A CompoundType instance is used to describe a compound data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance.
@@ -4174,7 +4288,7 @@ 
      Inherited Members
      
             CompoundType()
     
      
 
-        
+    
             
      __init__(group, datatype, datatype_name)
      
 
 
      CompoundType constructor.
      
@@ -4203,28 +4317,31 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.CompoundType' objects>
+        dtype
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        dtype_view = <attribute 'dtype_view' of 'netCDF4._netCDF4.CompoundType' objects>
+        dtype_view
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.CompoundType' objects>
+        name
     
      
 
     
+    
 
                             
      
                 
@@ -4237,7 +4354,7 @@ 
      Inherited Members
      
         VLType:
     
      
 
-        
+    
             
      A VLType instance is used to describe a variable length (VLEN) data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance. See
@@ -4255,7 +4372,7 @@ 
      Inherited Members
      
             VLType()
     
      
 
-        
+    
             
      __init__(group, datatype, datatype_name)
      
 
 
      VLType constructor.
      
@@ -4278,19 +4395,21 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.VLType' objects>
+        dtype
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.VLType' objects>
+        name
     
      
 
     
+    
 
                             
      
                 
@@ -4302,8 +4421,8 @@ 
      Inherited Members
      
             date2num(unknown):
     
      
 
-        
-            
      date2num(dates, units, calendar=None, has_year_zero=None)
      
+    
+            
      date2num(dates, units, calendar=None, has_year_zero=None, longdouble=False)
      
 
 
      Return numeric time values given datetime objects. The units
 of the numeric time values are described by the units argument
@@ -4348,6 +4467,12 @@ 
      Inherited Members
      
 This kwarg is not needed to define calendar systems allowed by CF
 (the calendar-specific defaults do this).
      
 
+
      longdouble: If set True, output is in the long double float type
+(numpy.float128) instead of float (numpy.float64), allowing microsecond
+accuracy when converting a time value to a date and back again. Otherwise
+this is only possible if the discretization of the time variable is an
+integer multiple of the units.
      
+
 
      returns a numeric time value, or an array of numeric time values
 with approximately 1 microsecond accuracy.
      
 
      
@@ -4362,7 +4487,7 @@ 
      Inherited Members
      
             num2date(unknown):
     
      
 
-        
+    
             
      num2date(times, units, calendar=u'standard', only_use_cftime_datetimes=True, only_use_python_datetimes=False, has_year_zero=None)
      
 
 
      Return datetime objects given numeric time values. The units
@@ -4434,7 +4559,7 @@ 
      Inherited Members
      
             date2index(unknown):
     
      
 
-        
+    
             
      date2index(dates, nctime, calendar=None, select=u'exact', has_year_zero=None)
      
 
 
      Return indices of a netCDF time variable corresponding to the given dates.
      
@@ -4488,7 +4613,7 @@ 
      Inherited Members
      
             stringtochar(unknown):
     
      
 
-        
+    
             
      stringtochar(a,encoding='utf-8')
      
 
 
      convert a string array to a character array with one extra dimension
      
@@ -4515,7 +4640,7 @@ 
      Inherited Members
      
             chartostring(unknown):
     
      
 
-        
+    
             
      chartostring(b,encoding='utf-8')
      
 
 
      convert a character array to a string array with one less dimension.
      
@@ -4542,7 +4667,7 @@ 
      Inherited Members
      
             stringtoarr(unknown):
     
      
 
-        
+    
             
      stringtoarr(a, NUMCHARS,dtype='S')
      
 
 
      convert a string to a character array of length NUMCHARS
      
@@ -4570,7 +4695,7 @@ 
      Inherited Members
      
             getlibversion(unknown):
     
      
 
-        
+    
             
      getlibversion()
      
 
 
      returns a string describing the version of the netcdf library
@@ -4588,7 +4713,7 @@ 
      Inherited Members
      
         EnumType:
     
      
 
-        
+    
             
      A EnumType instance is used to describe an Enum data
 type, and can be passed to the the Dataset.createVariable method of
 a Dataset or Group instance. See
@@ -4606,7 +4731,7 @@ 
      Inherited Members
      
             EnumType()
     
      
 
-        
+    
             
      __init__(group, datatype, datatype_name, enum_dict)
      
 
 
      EnumType constructor.
      
@@ -4632,28 +4757,31 @@ 
      Inherited Members
      
                             
      
                                             
      #  
 
-        dtype = <attribute 'dtype' of 'netCDF4._netCDF4.EnumType' objects>
+        dtype
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        name = <attribute 'name' of 'netCDF4._netCDF4.EnumType' objects>
+        name
     
      
 
     
+    
 
                             
      
                             
      
                                             
      #  
 
-        enum_dict = <attribute 'enum_dict' of 'netCDF4._netCDF4.EnumType' objects>
+        enum_dict
     
      
 
     
+    
 
                             
      
                 
@@ -4665,7 +4793,7 @@ 
      Inherited Members
      
             get_chunk_cache(unknown):
     
      
 
-        
+    
             
      get_chunk_cache()
      
 
 
      return current netCDF chunk cache information in a tuple (size,nelems,preemption).
@@ -4683,7 +4811,7 @@ 
      Inherited Members
      
             set_chunk_cache(unknown):
     
      
 
-        
+    
             
      set_chunk_cache(self,size=None,nelems=None,preemption=None)
      
 
 
      change netCDF4 chunk cache settings.
@@ -4692,6 +4820,47 @@ 
      Inherited Members
      
 
      
 
 
+                
+                
      
+                            
      #  
+
+        
+            def
+            set_alignment(unknown):
+    
      
+
+    
+            
      set_alignment(threshold,alignment)
      
+
+
      Change the HDF5 file alignment.
+See netcdf C library documentation for nc_set_alignment for
+details.
      
+
+
      This function was added in netcdf 4.9.0.
      
+
      
+
+
+                
      
+                
      
+                            
      #  
+
+        
+            def
+            get_alignment(unknown):
+    
      
+
+    
+            
      get_alignment()
      
+
+
      return current netCDF alignment within HDF5 files in a tuple
+(threshold,alignment). See netcdf C library documentation for
+nc_get_alignment for details. Values can be reset with
+set_alignment.
      
+
+
      This function was added in netcdf 4.9.0.
      
+
      
+
+
                 
      
     
 
diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py
index e84607bab..9f0b10ec7 100644
--- a/src/netCDF4/__init__.py
+++ b/src/netCDF4/__init__.py
@@ -12,7 +12,7 @@
                        __has_bzip2_support__, __has_blosc_support__, __has_szip_support__)
 import os
 __all__ =\
-['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache']
+['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache','set_alignment','get_alignment']
 # if HDF5_PLUGIN_PATH not set, point to package path if plugins live there
 pluginpath = os.path.join(__path__[0],'plugins')
 if 'HDF5_PLUGIN_PATH' not in os.environ and\

From 857c6460fb5a6fca39c8f3994452c834aa1657aa Mon Sep 17 00:00:00 2001
From: Filipe Fernandes 
Date: Thu, 15 Sep 2022 09:07:07 -0300
Subject: [PATCH 0886/1504] properly release the file on Windows

---
 test/tst_atts.py | 341 +++++++++++++++++++++++------------------------
 1 file changed, 170 insertions(+), 171 deletions(-)

diff --git a/test/tst_atts.py b/test/tst_atts.py
index a08a4fc8c..e0e674a9d 100644
--- a/test/tst_atts.py
+++ b/test/tst_atts.py
@@ -40,96 +40,95 @@ class VariablesTestCase(unittest.TestCase):
 
     def setUp(self):
         self.file = FILE_NAME
-        f = netCDF4.Dataset(self.file,'w')
-        # try to set a dataset attribute with one of the reserved names.
-        f.setncattr('file_format','netcdf4_format')
-        # test attribute renaming
-        f.stratt_tmp = STRATT
-        f.renameAttribute('stratt_tmp','stratt')
-        f.emptystratt = EMPTYSTRATT
-        f.intatt = INTATT
-        f.floatatt = FLOATATT
-        f.seqatt = SEQATT
-        # sequences of strings converted to a single string.
-        f.stringseqatt = STRINGSEQATT
-        f.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
-        g = f.createGroup(GROUP_NAME)
-        f.createDimension(DIM1_NAME, DIM1_LEN)
-        f.createDimension(DIM2_NAME, DIM2_LEN)
-        f.createDimension(DIM3_NAME, DIM3_LEN)
-        g.createDimension(DIM1_NAME, DIM1_LEN)
-        g.createDimension(DIM2_NAME, DIM2_LEN)
-        g.createDimension(DIM3_NAME, DIM3_LEN)
-        g.stratt_tmp = STRATT
-        g.renameAttribute('stratt_tmp','stratt')
-        g.emptystratt = EMPTYSTRATT
-        g.intatt = INTATT
-        g.floatatt = FLOATATT
-        g.seqatt = SEQATT
-        g.stringseqatt = STRINGSEQATT
-        if netCDF4.__version__ > "1.4.2":
-            with self.assertRaises(ValueError):
-                g.arrayatt = [[1, 2], [3, 4]] # issue #841
-        g.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
-        v = f.createVariable(VAR_NAME, 'f8',(DIM1_NAME,DIM2_NAME,DIM3_NAME))
-        # try to set a variable attribute with one of the reserved names.
-        v.setncattr('ndim','three')
-        v.setncatts({'foo': 1})
-        v.setncatts(OrderedDict(bar=2))
-        v.stratt_tmp = STRATT
-        v.renameAttribute('stratt_tmp','stratt')
-        v.emptystratt = EMPTYSTRATT
-        v.intatt = INTATT
-        v.floatatt = FLOATATT
-        v.seqatt = SEQATT
-        v.stringseqatt = STRINGSEQATT
-        v.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
-        v1 = g.createVariable(VAR_NAME, 'f8',(DIM1_NAME,DIM2_NAME,DIM3_NAME))
-        v1.stratt = STRATT
-        v1.emptystratt = EMPTYSTRATT
-        v1.intatt = INTATT
-        v1.floatatt = FLOATATT
-        v1.seqatt = SEQATT
-        v1.stringseqatt = STRINGSEQATT
-        v1.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
-        # issue #959: should not be able to set _FillValue after var creation
-        try:
-            v1._FillValue(-999.)
-        except AttributeError:
-            pass
-        else:
-            raise ValueError('This test should have failed.')
-        try:
-            v1.setncattr('_FillValue',-999.)
-        except AttributeError:
-            pass
-        else:
-            raise ValueError('This test should have failed.')
-        # issue #485 (triggers segfault in C lib
-        # with version 1.2.1 without pull request #486)
-        f.foo = np.array('bar','S')
-        f.foo = np.array('bar','U')
-        # issue #529 write string attribute as NC_CHAR unless
-        # it can't be decoded to ascii.  Add setncattr_string
-        # method to force NC_STRING.
-        f.charatt = 'foo' # will be written as NC_CHAR
-        f.setncattr_string('stringatt','bar') # NC_STRING
-        f.cafe = 'caf\xe9' # NC_STRING
-        f.batt = 'caf\xe9'.encode('utf-8') #NC_CHAR
-        v.setncattr_string('stringatt','bar') # NC_STRING
-        # issue #882 - provide an option to always string attribute
-        # as NC_STRINGs. Testing various approaches to setting text attributes...
-        f.set_ncstring_attrs(True)
-        f.stringatt_ncstr = 'foo' # will now be written as NC_STRING
-        f.setncattr_string('stringatt_ncstr','bar') # NC_STRING anyway
-        f.caf_ncstr = 'caf\xe9' # NC_STRING anyway
-        f.bat_ncstr = 'caf\xe9'.encode('utf-8') # now NC_STRING
-        g.stratt_ncstr = STRATT # now NC_STRING
-        #g.renameAttribute('stratt_tmp','stratt_ncstr')
-        v.setncattr_string('stringatt_ncstr','bar') # NC_STRING anyway
-        v.stratt_ncstr = STRATT
-        v1.emptystratt_ncstr = EMPTYSTRATT
-        f.close()
+        with netCDF4.Dataset(self.file,'w') as f:
+            # try to set a dataset attribute with one of the reserved names.
+            f.setncattr('file_format','netcdf4_format')
+            # test attribute renaming
+            f.stratt_tmp = STRATT
+            f.renameAttribute('stratt_tmp','stratt')
+            f.emptystratt = EMPTYSTRATT
+            f.intatt = INTATT
+            f.floatatt = FLOATATT
+            f.seqatt = SEQATT
+            # sequences of strings converted to a single string.
+            f.stringseqatt = STRINGSEQATT
+            f.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
+            g = f.createGroup(GROUP_NAME)
+            f.createDimension(DIM1_NAME, DIM1_LEN)
+            f.createDimension(DIM2_NAME, DIM2_LEN)
+            f.createDimension(DIM3_NAME, DIM3_LEN)
+            g.createDimension(DIM1_NAME, DIM1_LEN)
+            g.createDimension(DIM2_NAME, DIM2_LEN)
+            g.createDimension(DIM3_NAME, DIM3_LEN)
+            g.stratt_tmp = STRATT
+            g.renameAttribute('stratt_tmp','stratt')
+            g.emptystratt = EMPTYSTRATT
+            g.intatt = INTATT
+            g.floatatt = FLOATATT
+            g.seqatt = SEQATT
+            g.stringseqatt = STRINGSEQATT
+            if netCDF4.__version__ > "1.4.2":
+                with self.assertRaises(ValueError):
+                    g.arrayatt = [[1, 2], [3, 4]] # issue #841
+            g.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
+            v = f.createVariable(VAR_NAME, 'f8',(DIM1_NAME,DIM2_NAME,DIM3_NAME))
+            # try to set a variable attribute with one of the reserved names.
+            v.setncattr('ndim','three')
+            v.setncatts({'foo': 1})
+            v.setncatts(OrderedDict(bar=2))
+            v.stratt_tmp = STRATT
+            v.renameAttribute('stratt_tmp','stratt')
+            v.emptystratt = EMPTYSTRATT
+            v.intatt = INTATT
+            v.floatatt = FLOATATT
+            v.seqatt = SEQATT
+            v.stringseqatt = STRINGSEQATT
+            v.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
+            v1 = g.createVariable(VAR_NAME, 'f8',(DIM1_NAME,DIM2_NAME,DIM3_NAME))
+            v1.stratt = STRATT
+            v1.emptystratt = EMPTYSTRATT
+            v1.intatt = INTATT
+            v1.floatatt = FLOATATT
+            v1.seqatt = SEQATT
+            v1.stringseqatt = STRINGSEQATT
+            v1.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
+            # issue #959: should not be able to set _FillValue after var creation
+            try:
+                v1._FillValue(-999.)
+            except AttributeError:
+                pass
+            else:
+                raise ValueError('This test should have failed.')
+            try:
+                v1.setncattr('_FillValue',-999.)
+            except AttributeError:
+                pass
+            else:
+                raise ValueError('This test should have failed.')
+            # issue #485 (triggers segfault in C lib
+            # with version 1.2.1 without pull request #486)
+            f.foo = np.array('bar','S')
+            f.foo = np.array('bar','U')
+            # issue #529 write string attribute as NC_CHAR unless
+            # it can't be decoded to ascii.  Add setncattr_string
+            # method to force NC_STRING.
+            f.charatt = 'foo' # will be written as NC_CHAR
+            f.setncattr_string('stringatt','bar') # NC_STRING
+            f.cafe = 'caf\xe9' # NC_STRING
+            f.batt = 'caf\xe9'.encode('utf-8') #NC_CHAR
+            v.setncattr_string('stringatt','bar') # NC_STRING
+            # issue #882 - provide an option to always string attribute
+            # as NC_STRINGs. Testing various approaches to setting text attributes...
+            f.set_ncstring_attrs(True)
+            f.stringatt_ncstr = 'foo' # will now be written as NC_STRING
+            f.setncattr_string('stringatt_ncstr','bar') # NC_STRING anyway
+            f.caf_ncstr = 'caf\xe9' # NC_STRING anyway
+            f.bat_ncstr = 'caf\xe9'.encode('utf-8') # now NC_STRING
+            g.stratt_ncstr = STRATT # now NC_STRING
+            #g.renameAttribute('stratt_tmp','stratt_ncstr')
+            v.setncattr_string('stringatt_ncstr','bar') # NC_STRING anyway
+            v.stratt_ncstr = STRATT
+            v1.emptystratt_ncstr = EMPTYSTRATT
 
     def tearDown(self):
         # Remove the temporary files
@@ -138,87 +137,87 @@ def tearDown(self):
 
     def runTest(self):
         """testing attributes"""
-        f  = netCDF4.Dataset(self.file, 'r')
-        v = f.variables[VAR_NAME]
-        g = f.groups[GROUP_NAME]
-        v1 = g.variables[VAR_NAME]
-        # check attributes in root group.
-        # global attributes.
-        # check __dict__ method for accessing all netCDF attributes.
-        for key,val in ATTDICT.items():
-            if type(val) == np.ndarray:
-                assert f.__dict__[key].tolist() == val.tolist()
-            else:
-                assert f.__dict__[key] == val
-        # check accessing individual attributes.
-        assert f.intatt == INTATT
-        assert f.floatatt == FLOATATT
-        assert f.stratt == STRATT
-        assert f.emptystratt == EMPTYSTRATT
-        assert f.seqatt.tolist() == SEQATT.tolist()
-        #assert f.stringseqatt == ''.join(STRINGSEQATT) # issue 770
-        assert f.stringseqatt == STRINGSEQATT
-        assert f.stringseqatt_array == STRINGSEQATT
-        assert f.getncattr('file_format') == 'netcdf4_format'
-        # variable attributes.
-        # check __dict__ method for accessing all netCDF attributes.
-        for key,val in ATTDICT.items():
-            if type(val) == np.ndarray:
-                assert v.__dict__[key].tolist() == val.tolist()
-            else:
-                assert v.__dict__[key] == val
-        # check accessing individual attributes.
-        assert v.intatt == INTATT
-        assert v.floatatt == FLOATATT
-        assert v.stratt == STRATT
-        assert v.seqatt.tolist() == SEQATT.tolist()
-        #assert v.stringseqatt == ''.join(STRINGSEQATT) # issue 770
-        assert v.stringseqatt == STRINGSEQATT
-        assert v.stringseqatt_array == STRINGSEQATT
-        assert v.getncattr('ndim') == 'three'
-        assert v.getncattr('foo') == 1
-        assert v.getncattr('bar') == 2
-        # check type of attributes using ncdump (issue #529)
-        if not os.getenv('NO_CDL'):
-            ncdump_output = f.tocdl()
-            for line in ncdump_output:
-                line = line.strip('\t\n\r')
-                line = line.strip()# Must be done another time for group variables
-                if "stringatt" in line: assert line.startswith('string')
-                if "charatt" in line: assert line.startswith(':')
-                if "cafe" in line: assert line.startswith('string')
-                if "batt" in line: assert line.startswith(':')
-                if "_ncstr" in line: assert line.startswith('string')
-        # check attributes in subgroup.
-        # global attributes.
-        for key,val in ATTDICT.items():
-            if type(val) == np.ndarray:
-                assert g.__dict__[key].tolist() == val.tolist()
-            else:
-                assert g.__dict__[key] == val
-        assert g.intatt == INTATT
-        assert g.floatatt == FLOATATT
-        assert g.stratt == STRATT
-        assert g.emptystratt == EMPTYSTRATT
-        assert g.seqatt.tolist() == SEQATT.tolist()
-        #assert g.stringseqatt == ''.join(STRINGSEQATT) # issue 770
-        assert g.stringseqatt == STRINGSEQATT
-        assert g.stringseqatt_array == STRINGSEQATT
-        for key,val in ATTDICT.items():
-            if type(val) == np.ndarray:
-                assert v1.__dict__[key].tolist() == val.tolist()
-            else:
-                assert v1.__dict__[key] == val
-        assert v1.intatt == INTATT
-        assert v1.floatatt == FLOATATT
-        assert v1.stratt == STRATT
-        assert v1.emptystratt == EMPTYSTRATT
-        assert v1.seqatt.tolist() == SEQATT.tolist()
-        #assert v1.stringseqatt == ''.join(STRINGSEQATT) # issue 770
-        assert v1.stringseqatt == STRINGSEQATT
-        assert v1.stringseqatt_array == STRINGSEQATT
-        assert getattr(v1,'nonexistantatt',None) == None
-        f.close()
+        with netCDF4.Dataset(self.file, 'r') as f:
+            v = f.variables[VAR_NAME]
+            g = f.groups[GROUP_NAME]
+            v1 = g.variables[VAR_NAME]
+            # check attributes in root group.
+            # global attributes.
+            # check __dict__ method for accessing all netCDF attributes.
+            for key,val in ATTDICT.items():
+                if type(val) == np.ndarray:
+                    assert f.__dict__[key].tolist() == val.tolist()
+                else:
+                    assert f.__dict__[key] == val
+            # check accessing individual attributes.
+            assert f.intatt == INTATT
+            assert f.floatatt == FLOATATT
+            assert f.stratt == STRATT
+            assert f.emptystratt == EMPTYSTRATT
+            assert f.seqatt.tolist() == SEQATT.tolist()
+            #assert f.stringseqatt == ''.join(STRINGSEQATT) # issue 770
+            assert f.stringseqatt == STRINGSEQATT
+            assert f.stringseqatt_array == STRINGSEQATT
+            assert f.getncattr('file_format') == 'netcdf4_format'
+            # variable attributes.
+            # check __dict__ method for accessing all netCDF attributes.
+            for key,val in ATTDICT.items():
+                if type(val) == np.ndarray:
+                    assert v.__dict__[key].tolist() == val.tolist()
+                else:
+                    assert v.__dict__[key] == val
+            # check accessing individual attributes.
+            assert v.intatt == INTATT
+            assert v.floatatt == FLOATATT
+            assert v.stratt == STRATT
+            assert v.seqatt.tolist() == SEQATT.tolist()
+            #assert v.stringseqatt == ''.join(STRINGSEQATT) # issue 770
+            assert v.stringseqatt == STRINGSEQATT
+            assert v.stringseqatt_array == STRINGSEQATT
+            assert v.getncattr('ndim') == 'three'
+            assert v.getncattr('foo') == 1
+            assert v.getncattr('bar') == 2
+            # check type of attributes using ncdump (issue #529)
+            if not os.getenv('NO_CDL'):
+                ncdump_output = f.tocdl()
+                for line in ncdump_output:
+                    line = line.strip('\t\n\r')
+                    line = line.strip()# Must be done another time for group variables
+                    if "stringatt" in line: assert line.startswith('string')
+                    if "charatt" in line: assert line.startswith(':')
+                    if "cafe" in line: assert line.startswith('string')
+                    if "batt" in line: assert line.startswith(':')
+                    if "_ncstr" in line: assert line.startswith('string')
+            # check attributes in subgroup.
+            # global attributes.
+            for key,val in ATTDICT.items():
+                if type(val) == np.ndarray:
+                    assert g.__dict__[key].tolist() == val.tolist()
+                else:
+                    assert g.__dict__[key] == val
+            assert g.intatt == INTATT
+            assert g.floatatt == FLOATATT
+            assert g.stratt == STRATT
+            assert g.emptystratt == EMPTYSTRATT
+            assert g.seqatt.tolist() == SEQATT.tolist()
+            #assert g.stringseqatt == ''.join(STRINGSEQATT) # issue 770
+            assert g.stringseqatt == STRINGSEQATT
+            assert g.stringseqatt_array == STRINGSEQATT
+            for key,val in ATTDICT.items():
+                if type(val) == np.ndarray:
+                    assert v1.__dict__[key].tolist() == val.tolist()
+                else:
+                    assert v1.__dict__[key] == val
+            assert v1.intatt == INTATT
+            assert v1.floatatt == FLOATATT
+            assert v1.stratt == STRATT
+            assert v1.emptystratt == EMPTYSTRATT
+            assert v1.seqatt.tolist() == SEQATT.tolist()
+            #assert v1.stringseqatt == ''.join(STRINGSEQATT) # issue 770
+            assert v1.stringseqatt == STRINGSEQATT
+            assert v1.stringseqatt_array == STRINGSEQATT
+            assert getattr(v1,'nonexistantatt',None) == None
+
         # issue 915 empty string attribute (ncdump reports 'NIL')
         f = netCDF4.Dataset('test_gold.nc')
         assert f['RADIANCE'].VAR_NOTES == ""

From b7e0b137d23a19a82113cd7f723c396036e99233 Mon Sep 17 00:00:00 2001
From: Mark Harfouche 
Date: Fri, 23 Sep 2022 15:37:05 -0400
Subject: [PATCH 0887/1504] Added has set alignment to top level init

---
 Changelog               | 5 +++++
 src/netCDF4/__init__.py | 3 ++-
 2 files changed, 7 insertions(+), 1 deletion(-)

diff --git a/Changelog b/Changelog
index a66c27cd9..a68911d95 100644
--- a/Changelog
+++ b/Changelog
@@ -1,3 +1,8 @@
+ version 1.6.2 (Unrelease)
+==========================
+ * Added ``netCDF4.__has_set_alignment__`` property to help identify if the
+   underlying netcdf4 supports setting the HDF5 alignment.
+
  version 1.6.1 (tag v1.6.1rel)
 ==============================
  * add Dataset methods has__filter (where =zstd,blosc,bzip2,szip)
diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py
index 9f0b10ec7..2a38d621c 100644
--- a/src/netCDF4/__init__.py
+++ b/src/netCDF4/__init__.py
@@ -9,7 +9,8 @@
                        __has_nc_create_mem__, __has_cdf5_format__,
                        __has_parallel4_support__, __has_pnetcdf_support__,
                        __has_quantization_support__, __has_zstandard_support__,
-                       __has_bzip2_support__, __has_blosc_support__, __has_szip_support__)
+                       __has_bzip2_support__, __has_blosc_support__, __has_szip_support__,
+                       __has_set_alignment__)
 import os
 __all__ =\
 ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache','set_alignment','get_alignment']

From cc741bfa4b98cd9778f6dcd8bc23c97b0b435838 Mon Sep 17 00:00:00 2001
From: Mark Harfouche 
Date: Fri, 23 Sep 2022 15:39:16 -0400
Subject: [PATCH 0888/1504] Add a test

---
 test/tst_alignment.py | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/test/tst_alignment.py b/test/tst_alignment.py
index c20ed4173..3f7333cd6 100644
--- a/test/tst_alignment.py
+++ b/test/tst_alignment.py
@@ -1,5 +1,6 @@
 import numpy as np
 from netCDF4 import set_alignment, get_alignment, Dataset
+from netCDF4 import __has_set_alignment__
 import netCDF4
 import os
 import subprocess
@@ -23,6 +24,7 @@
 
 class AlignmentTestCase(unittest.TestCase):
     def setUp(self):
+
         self.file = file_name
 
         # This is a global variable in netcdf4, it must be set before File
@@ -57,6 +59,10 @@ def test_version_settings(self):
             with self.assertRaises(RuntimeError):
                 get_alignment()
 
+    def test_reports_alignment_capabilities(self):
+        # Assert that the library reports that it supports alignment correctly
+        assert has_alignment == __has_set_alignment__
+
     # if we have no support for alignment, we have no guarantees on
     # how the data can be aligned
     @unittest.skipIf(

From ab787f1bc3f9442a0501b18fba8634eaf372d238 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 10 Oct 2022 20:27:00 -0600
Subject: [PATCH 0889/1504] return empty array if boolean index array is all
 False

---
 src/netCDF4/_netCDF4.pyx | 2 +-
 src/netCDF4/utils.py     | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 5acd32c8d..29852a65d 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4953,7 +4953,7 @@ rename a `Variable` attribute named `oldname` to `newname`."""
         # put_ind for this dimension is set to -1 by _StartCountStride.
         squeeze = data.ndim * [slice(None),]
         for i,n in enumerate(put_ind.shape[:-1]):
-            if n == 1 and put_ind[...,i].ravel()[0] == -1:
+            if n == 1 and put_ind.size > 0 and put_ind[...,i].ravel()[0] == -1:
                 squeeze[i] = 0
 
         # Reshape the arrays so we can iterate over them.
diff --git a/src/netCDF4/utils.py b/src/netCDF4/utils.py
index c96cc7575..3ed627021 100644
--- a/src/netCDF4/utils.py
+++ b/src/netCDF4/utils.py
@@ -457,7 +457,7 @@ def _out_array_shape(count):
     out = []
 
     for i, n in enumerate(s):
-        if n == 1:
+        if n == 1 and count.size > 0:
             c = count[..., i].ravel()[0] # All elements should be identical.
             out.append(c)
         else:

From d70c336ac877d4d4c0e397f99debb4888bb87e19 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 10 Oct 2022 20:36:19 -0600
Subject: [PATCH 0890/1504] update

---
 Changelog | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/Changelog b/Changelog
index a68911d95..41baa59c7 100644
--- a/Changelog
+++ b/Changelog
@@ -2,6 +2,9 @@
 ==========================
  * Added ``netCDF4.__has_set_alignment__`` property to help identify if the
    underlying netcdf4 supports setting the HDF5 alignment.
+ * Slicing multi-dimensional variables with an all False boolean index array
+   now returns an empty numpy array (instead of raising an exception - issue #1197).
+   Behavior now consistent with numpy slicing.
 
  version 1.6.1 (tag v1.6.1rel)
 ==============================

From 60702d1993fe127c78894ff679c10556e74e68f1 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 11 Oct 2022 07:28:59 -0600
Subject: [PATCH 0891/1504] add test for all False boolean index slicing
 multi-dim array

---
 test/tst_fancyslicing.py | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/test/tst_fancyslicing.py b/test/tst_fancyslicing.py
index dd359a52d..38611b3cb 100644
--- a/test/tst_fancyslicing.py
+++ b/test/tst_fancyslicing.py
@@ -142,6 +142,11 @@ def test_get(self):
 
         assert_array_equal(v[0], self.data[0])
 
+        # slicing with all False booleans (PR #1197)
+        iby[:] = False
+        data = v[ibx,iby,ibz]
+        assert(data.size == 0)
+
         f.close()
 
     def test_set(self):

From 4414f9fc793c9cda1ca4b0c93b294e0d65cdbd61 Mon Sep 17 00:00:00 2001
From: Timo Rothenpieler 
Date: Sun, 16 Oct 2022 13:42:57 +0200
Subject: [PATCH 0892/1504] Define 'nc_inq_filter_avail' if szip support is
 enabled

If both HAS_QUANTIZATION_SUPPORT and HAS_ZSTANDARD_SUPPORT are false, but HAS_SZIP_SUPPORT is enabled (as is happening on Ubuntu 22.04), the build fails due to nc_inq_filter_avail not being defined:

src/netCDF4/_netCDF4.pyx:3548:23: undeclared name not builtin: nc_inq_filter_avail
src/netCDF4/_netCDF4.pyx:3548:42: Calling gil-requiring function not allowed without gil
src/netCDF4/_netCDF4.pyx:3548:23: Accessing Python global or builtin not allowed without gil
src/netCDF4/_netCDF4.pyx:3548:42: Constructing Python tuple not allowed without gil
src/netCDF4/_netCDF4.pyx:3548:47: Converting to Python object not allowed without gil
src/netCDF4/_netCDF4.pyx:3548:56: Converting to Python object not allowed without gil
---
 include/netCDF4.pxi | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index 60afc1538..878971e0f 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -388,6 +388,8 @@ IF HAS_SZIP_SUPPORT:
         int nc_inq_var_quantize(int ncid, int varid, int *quantize_modep, int *nsdp) nogil
         int nc_def_var_szip(int ncid, int varid, int options_mask, int pixels_per_bloc) nogil
         int nc_inq_var_szip(int ncid, int varid, int *options_maskp, int *pixels_per_blockp) nogil
+    cdef extern from "netcdf_filter.h":
+        int nc_inq_filter_avail(int ncid, unsigned filterid) nogil
 
 IF HAS_ZSTANDARD_SUPPORT:
     cdef extern from "netcdf_filter.h":

From 9d2842f4568c5cbb9abb1bdf93592b2c4b545369 Mon Sep 17 00:00:00 2001
From: Timo Rothenpieler 
Date: Sun, 16 Oct 2022 13:47:21 +0200
Subject: [PATCH 0893/1504] Add 'nc_inq_filter_avail' to more filter
 definitions

---
 include/netCDF4.pxi | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index 878971e0f..86e309839 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -405,6 +405,7 @@ IF HAS_BZIP2_SUPPORT:
             H5Z_FILTER_BZIP2
         int nc_def_var_bzip2(int ncid, int varid, int level) nogil
         int nc_inq_var_bzip2(int ncid, int varid, int* hasfilterp, int *levelp) nogil
+        int nc_inq_filter_avail(int ncid, unsigned filterid) nogil
 
 IF HAS_BLOSC_SUPPORT:
     cdef extern from "netcdf_filter.h":
@@ -412,6 +413,7 @@ IF HAS_BLOSC_SUPPORT:
             H5Z_FILTER_BLOSC
         int nc_def_var_blosc(int ncid, int varid, unsigned subcompressor, unsigned level, unsigned blocksize, unsigned addshuffle) nogil
         int nc_inq_var_blosc(int ncid, int varid, int* hasfilterp, unsigned* subcompressorp, unsigned* levelp, unsigned* blocksizep, unsigned* addshufflep) nogil
+        int nc_inq_filter_avail(int ncid, unsigned filterid) nogil
 
 IF HAS_NC_OPEN_MEM:
     cdef extern from "netcdf_mem.h":

From 4c886e8a0630a80bd94e12c3a37d3866b63b01eb Mon Sep 17 00:00:00 2001
From: Filipe Fernandes 
Date: Tue, 25 Oct 2022 10:13:46 -0300
Subject: [PATCH 0894/1504] add python_requires

---
 setup.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/setup.py b/setup.py
index ec1dc2bc8..5dce64866 100644
--- a/setup.py
+++ b/setup.py
@@ -742,6 +742,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
       package_dir={'':'src'},
       package_data={"netCDF4.plugins": ["lib__nc*"]},
       ext_modules=ext_modules,
+      python_requires=">=3.6",
       **setuptools_extra_kwargs)
 
 # remove plugin files copied from outside source tree

From c0faf48de90f97ddb7bc8cf8ac8b8d7baefa4a7b Mon Sep 17 00:00:00 2001
From: Filipe Fernandes 
Date: Thu, 10 Nov 2022 16:17:32 -0300
Subject: [PATCH 0895/1504] add pyproject.toml to ensure build deps are present
 at build time

---
 pyproject.toml | 3 +++
 setup.py       | 1 -
 2 files changed, 3 insertions(+), 1 deletion(-)
 create mode 100644 pyproject.toml

diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 000000000..e7fa09d69
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,3 @@
+[build-system]
+requires = ["setuptools>=41.2", "cython>=0.19", "oldest-supported-numpy"]
+build-backend = "setuptools.build_meta"
diff --git a/setup.py b/setup.py
index 5dce64866..f79e8557c 100644
--- a/setup.py
+++ b/setup.py
@@ -7,7 +7,6 @@
 
 setuptools_extra_kwargs = {
     "install_requires": ["numpy>=1.9","cftime"],
-    "setup_requires": ['setuptools>=18.0', "cython>=0.19"],
     "entry_points": {
         'console_scripts': [
             'ncinfo = netCDF4.utils:ncinfo',

From b823dc7955201c2a43bb882427355c22f010fa8b Mon Sep 17 00:00:00 2001
From: Filipe Fernandes 
Date: Thu, 10 Nov 2022 16:39:51 -0300
Subject: [PATCH 0896/1504] use the vendored one in setuptools

---
 setup.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index f79e8557c..87ba082e9 100644
--- a/setup.py
+++ b/setup.py
@@ -3,7 +3,7 @@
 import shutil
 import configparser
 from setuptools import setup, Extension, find_namespace_packages
-from distutils.dist import Distribution
+from setuptools.dist import Distribution
 
 setuptools_extra_kwargs = {
     "install_requires": ["numpy>=1.9","cftime"],

From 8ad370a7843549dd2c53176c14dbbe803660e2c9 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 11 Nov 2022 21:14:21 -0700
Subject: [PATCH 0897/1504] fix for issue #1209

---
 include/netCDF4.pxi      |  8 +++-----
 setup.py                 | 14 ++++++++++++--
 src/netCDF4/_netCDF4.pyx | 20 +++++++++++++-------
 3 files changed, 28 insertions(+), 14 deletions(-)

diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index 86e309839..864436a0d 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -368,6 +368,7 @@ cdef extern from "netcdf.h":
     int nc_inq_enum_ident(int ncid, nc_type xtype, long long value, char *identifier) nogil
 
 
+
 IF HAS_QUANTIZATION_SUPPORT:
     cdef extern from "netcdf.h":
         cdef enum:
@@ -377,6 +378,8 @@ IF HAS_QUANTIZATION_SUPPORT:
             NC_QUANTIZE_BITROUND
         int nc_def_var_quantize(int ncid, int varid, int quantize_mode, int nsd) nogil
         int nc_inq_var_quantize(int ncid, int varid, int *quantize_modep, int *nsdp) nogil
+
+IF HAS_NCFILTER:
     cdef extern from "netcdf_filter.h":
         int nc_inq_filter_avail(int ncid, unsigned filterid) nogil
 
@@ -388,8 +391,6 @@ IF HAS_SZIP_SUPPORT:
         int nc_inq_var_quantize(int ncid, int varid, int *quantize_modep, int *nsdp) nogil
         int nc_def_var_szip(int ncid, int varid, int options_mask, int pixels_per_bloc) nogil
         int nc_inq_var_szip(int ncid, int varid, int *options_maskp, int *pixels_per_blockp) nogil
-    cdef extern from "netcdf_filter.h":
-        int nc_inq_filter_avail(int ncid, unsigned filterid) nogil
 
 IF HAS_ZSTANDARD_SUPPORT:
     cdef extern from "netcdf_filter.h":
@@ -397,7 +398,6 @@ IF HAS_ZSTANDARD_SUPPORT:
             H5Z_FILTER_ZSTD
         int nc_def_var_zstandard(int ncid, int varid, int level) nogil
         int nc_inq_var_zstandard(int ncid, int varid, int* hasfilterp, int *levelp) nogil
-        int nc_inq_filter_avail(int ncid, unsigned id) nogil
 
 IF HAS_BZIP2_SUPPORT:
     cdef extern from "netcdf_filter.h":
@@ -405,7 +405,6 @@ IF HAS_BZIP2_SUPPORT:
             H5Z_FILTER_BZIP2
         int nc_def_var_bzip2(int ncid, int varid, int level) nogil
         int nc_inq_var_bzip2(int ncid, int varid, int* hasfilterp, int *levelp) nogil
-        int nc_inq_filter_avail(int ncid, unsigned filterid) nogil
 
 IF HAS_BLOSC_SUPPORT:
     cdef extern from "netcdf_filter.h":
@@ -413,7 +412,6 @@ IF HAS_BLOSC_SUPPORT:
             H5Z_FILTER_BLOSC
         int nc_def_var_blosc(int ncid, int varid, unsigned subcompressor, unsigned level, unsigned blocksize, unsigned addshuffle) nogil
         int nc_inq_var_blosc(int ncid, int varid, int* hasfilterp, unsigned* subcompressorp, unsigned* levelp, unsigned* blocksizep, unsigned* addshufflep) nogil
-        int nc_inq_filter_avail(int ncid, unsigned filterid) nogil
 
 IF HAS_NC_OPEN_MEM:
     cdef extern from "netcdf_mem.h":
diff --git a/setup.py b/setup.py
index 87ba082e9..b1e941a96 100644
--- a/setup.py
+++ b/setup.py
@@ -70,6 +70,7 @@ def check_api(inc_dirs,netcdf_lib_version):
     has_zstandard = False
     has_bzip2 = False
     has_blosc = False
+    has_ncfilter = False
     has_set_alignment = False
 
     for d in inc_dirs:
@@ -116,6 +117,8 @@ def check_api(inc_dirs,netcdf_lib_version):
                     has_bzip2 = True
                 if line.startswith('EXTERNL int nc_def_var_blosc'):
                     has_blosc = True
+                if line.startswith('EXTERNL int nc_inq_filter_avail'):
+                    has_ncfilter = True
 
         ncmetapath = os.path.join(d,'netcdf_meta.h')
         if os.path.exists(ncmetapath):
@@ -143,7 +146,7 @@ def check_api(inc_dirs,netcdf_lib_version):
     return has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \
            has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \
            has_parallel4_support, has_pnetcdf_support, has_szip_support, has_quantize, \
-           has_zstandard, has_bzip2, has_blosc, has_set_alignment
+           has_zstandard, has_bzip2, has_blosc, has_set_alignment, has_ncfilter
 
 
 def getnetcdfvers(libdirs):
@@ -557,7 +560,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \
     has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \
     has_parallel4_support, has_pnetcdf_support, has_szip_support, has_quantize, \
-    has_zstandard, has_bzip2, has_blosc, has_set_alignment = \
+    has_zstandard, has_bzip2, has_blosc, has_set_alignment, has_ncfilter = \
     check_api(inc_dirs,netcdf_lib_version)
     # for netcdf 4.4.x CDF5 format is always enabled.
     if netcdf_lib_version is not None and\
@@ -671,6 +674,13 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         sys.stdout.write('netcdf lib does not have nc_set_alignment function\n')
         f.write('DEF HAS_SET_ALIGNMENT = 0\n')
 
+    if has_blosc:
+        sys.stdout.write('netcdf lib has nc_inq_filter_avail function\n')
+        f.write('DEF HAS_NCFILTER = 1\n')
+    else:
+        sys.stdout.write('netcdf lib does not have nc_inq_filter_avail function\n')
+        f.write('DEF HAS_NCFILTER = 0\n')
+
     f.close()
 
     if has_parallel4_support or has_pnetcdf_support:
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 29852a65d..aa64adde1 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3543,15 +3543,21 @@ returns True if bzip2 compression filter is available"""
 **`has_szip_filter(self)`**
 returns True if szip compression filter is available"""
         cdef int ierr
-        IF HAS_SZIP_SUPPORT:
-            with nogil:
-                ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_SZIP)
-            if ierr:
+        IF HAS_NCFILTER:
+            IF HAS_SZIP_SUPPORT:
+                with nogil:
+                    ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_SZIP)
+                if ierr:
+                    return False
+                else:
+                    return True
+            ELSE:
                 return False
-            else:
+       ELSE:
+            IF HAS_SZIP_SUPPORT:
                 return True
-        ELSE:
-            return False
+            ELSE:
+                return False
 
 cdef class Group(Dataset):
     """

From b67c0f7c17a170f3408bc25c76a4d625b276eb16 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 11 Nov 2022 21:15:34 -0700
Subject: [PATCH 0898/1504] update

---
 Changelog | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/Changelog b/Changelog
index 41baa59c7..dbbbed650 100644
--- a/Changelog
+++ b/Changelog
@@ -1,10 +1,11 @@
- version 1.6.2 (Unrelease)
-==========================
+ version 1.6.2 (not yet released)
+==============================
  * Added ``netCDF4.__has_set_alignment__`` property to help identify if the
    underlying netcdf4 supports setting the HDF5 alignment.
  * Slicing multi-dimensional variables with an all False boolean index array
    now returns an empty numpy array (instead of raising an exception - issue #1197).
    Behavior now consistent with numpy slicing.
+ * fix problem with compiling using netcdf-c < 4.9.0 (issue #1209)
 
  version 1.6.1 (tag v1.6.1rel)
 ==============================

From b088979a57627fcc1e4d2117fa5291d8d698eb31 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 11 Nov 2022 21:20:57 -0700
Subject: [PATCH 0899/1504] add new test with older netcdf-c (4.7.4)

---
 .../workflows/{build.yml => build_latest.yml} |   2 +-
 .github/workflows/build_old.yml               | 104 ++++++++++++++++++
 2 files changed, 105 insertions(+), 1 deletion(-)
 rename .github/workflows/{build.yml => build_latest.yml} (98%)
 create mode 100644 .github/workflows/build_old.yml

diff --git a/.github/workflows/build.yml b/.github/workflows/build_latest.yml
similarity index 98%
rename from .github/workflows/build.yml
rename to .github/workflows/build_latest.yml
index 11e218157..ddbfd7680 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build_latest.yml
@@ -1,4 +1,4 @@
-name: Build and Test Linux
+name: Build and Test Linux with latest netcdf-c
 on: [push, pull_request]
 jobs:
   build-linux:
diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml
new file mode 100644
index 000000000..c17678b66
--- /dev/null
+++ b/.github/workflows/build_old.yml
@@ -0,0 +1,104 @@
+name: Build and Test Linux with older netcdf-c
+on: [push, pull_request]
+jobs:
+  build-linux:
+    name: Python (${{ matrix.python-version }})
+    runs-on: ubuntu-latest
+    env:
+      PNETCDF_VERSION: 1.12.1
+      NETCDF_VERSION: 4.7.4
+      NETCDF_DIR: ${{ github.workspace }}/..
+      NETCDF_EXTRA_CONFIG: --enable-pnetcdf
+      CC: mpicc.mpich
+      #NO_NET: 1
+    strategy:
+      matrix:
+        python-version: ["3.9"]
+    steps:
+
+    - uses: actions/checkout@v2
+
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v2
+      with:
+        python-version: ${{ matrix.python-version }}
+
+    - name: Install Ubuntu Dependencies
+      run: |
+        sudo apt-get update
+        sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
+        echo "Download and build PnetCDF version ${PNETCDF_VERSION}"
+        wget https://parallel-netcdf.github.io/Release/pnetcdf-${PNETCDF_VERSION}.tar.gz
+        tar -xzf pnetcdf-${PNETCDF_VERSION}.tar.gz
+        pushd pnetcdf-${PNETCDF_VERSION}
+        ./configure --prefix $NETCDF_DIR --enable-shared --disable-fortran --disable-cxx
+        make -j 2
+        make install
+        popd
+        echo "Download and build netCDF version ${NETCDF_VERSION}"
+        wget https://downloads.unidata.ucar.edu/netcdf-c/4.9.0/netcdf-c-${NETCDF_VERSION}.tar.gz
+        tar -xzf netcdf-c-${NETCDF_VERSION}.tar.gz
+        pushd netcdf-c-${NETCDF_VERSION}
+        export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include"
+        export LDFLAGS="-L${NETCDF_DIR}/lib"
+        export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
+        ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 $NETCDF_EXTRA_CONFIG
+        make -j 2
+        make install
+        popd
+
+#   - name: The job has failed
+#     if: ${{ failure() }}
+#     run: |
+#       cd netcdf-c-${NETCDF_VERSION}
+#       cat config.log 
+
+    - name: Install python dependencies via pip
+      run: |
+        python -m pip install --upgrade pip
+        pip install numpy cython cftime pytest twine wheel check-manifest mpi4py
+
+    - name: Install netcdf4-python
+      run: |
+        export PATH=${NETCDF_DIR}/bin:${PATH} 
+        export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c-${NETCDF_VERSION}/plugins/plugindir
+        python setup.py install
+    - name: Test
+      run: |
+        export PATH=${NETCDF_DIR}/bin:${PATH} 
+        python checkversion.py
+        # serial
+        cd test
+        python run_all.py
+        # parallel (hdf5 for netcdf4, pnetcdf for netcdf3)
+        cd ../examples
+        mpirun.mpich -np 4 python mpi_example.py
+        if [ $? -ne 0 ] ; then
+          echo "hdf5 mpi test failed!"
+          exit 1
+        else
+          echo "hdf5 mpi test passed!"
+        fi
+        mpirun.mpich -np 4 python mpi_example_compressed.py
+        if [ $? -ne 0 ] ; then
+          echo "hdf5 compressed mpi test failed!"
+          exit 1
+        else
+          echo "hdf5 compressed mpi test passed!"
+        fi
+        mpirun.mpich -np 4 python mpi_example.py NETCDF3_64BIT_DATA
+        if [ $? -ne 0 ] ; then
+          echo "pnetcdf mpi test failed!"
+          exit 1
+        else
+          echo "pnetcdf mpi test passed!"
+        fi
+
+    - name: Tarball
+      run: |
+        export PATH=${NETCDF_DIR}/bin:${PATH} 
+        python setup.py --version  
+        check-manifest --version
+        check-manifest --verbose 
+        pip wheel . -w dist --no-deps 
+        twine check dist/* 

From 9ade9ad07fbbbe397824a6ebc64a5db65fa01bf2 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 11 Nov 2022 21:22:50 -0700
Subject: [PATCH 0900/1504] fix typo

---
 setup.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index b1e941a96..3de06408b 100644
--- a/setup.py
+++ b/setup.py
@@ -674,7 +674,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         sys.stdout.write('netcdf lib does not have nc_set_alignment function\n')
         f.write('DEF HAS_SET_ALIGNMENT = 0\n')
 
-    if has_blosc:
+    if has_ncfilter:
         sys.stdout.write('netcdf lib has nc_inq_filter_avail function\n')
         f.write('DEF HAS_NCFILTER = 1\n')
     else:

From 6db3ce7ad6f03a68b07e8c39b159cf1bdfa515bc Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 11 Nov 2022 21:24:25 -0700
Subject: [PATCH 0901/1504] fix formatting

---
 src/netCDF4/_netCDF4.pyx | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index aa64adde1..605d3957e 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3553,11 +3553,11 @@ returns True if szip compression filter is available"""
                     return True
             ELSE:
                 return False
-       ELSE:
-            IF HAS_SZIP_SUPPORT:
-                return True
-            ELSE:
-                return False
+        ELSE:
+             IF HAS_SZIP_SUPPORT:
+                 return True
+             ELSE:
+                 return False
 
 cdef class Group(Dataset):
     """

From 21f49f546492412b234a18cc794fadd8d57e3326 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Fri, 11 Nov 2022 21:25:18 -0700
Subject: [PATCH 0902/1504] remove whitespace

---
 include/netCDF4.pxi | 2 --
 1 file changed, 2 deletions(-)

diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index 864436a0d..9233c8165 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -367,8 +367,6 @@ cdef extern from "netcdf.h":
 
     int nc_inq_enum_ident(int ncid, nc_type xtype, long long value, char *identifier) nogil
 
-
-
 IF HAS_QUANTIZATION_SUPPORT:
     cdef extern from "netcdf.h":
         cdef enum:

From c6fee378fb77216e7b94b25f1df89f1529dfd064 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 10:28:49 -0700
Subject: [PATCH 0903/1504] fix download url

---
 .github/workflows/build_latest.yml | 4 ++--
 .github/workflows/build_old.yml    | 6 +++---
 .github/workflows/miniconda.yml    | 2 +-
 3 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index ddbfd7680..10e7afd6a 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -13,7 +13,7 @@ jobs:
       #NO_NET: 1
     strategy:
       matrix:
-        python-version: ["3.9"]
+        python-version: ["3.10"]
     steps:
 
     - uses: actions/checkout@v2
@@ -36,7 +36,7 @@ jobs:
         make install
         popd
         echo "Download and build netCDF version ${NETCDF_VERSION}"
-        wget https://downloads.unidata.ucar.edu/netcdf-c/4.9.0/netcdf-c-${NETCDF_VERSION}.tar.gz
+        wget https://downloads.unidata.ucar.edu/netcdf-c/${NETCDF_VERSION}/netcdf-c-${NETCDF_VERSION}.tar.gz
         tar -xzf netcdf-c-${NETCDF_VERSION}.tar.gz
         pushd netcdf-c-${NETCDF_VERSION}
         export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include"
diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml
index c17678b66..c4fe0ad29 100644
--- a/.github/workflows/build_old.yml
+++ b/.github/workflows/build_old.yml
@@ -6,14 +6,14 @@ jobs:
     runs-on: ubuntu-latest
     env:
       PNETCDF_VERSION: 1.12.1
-      NETCDF_VERSION: 4.7.4
+      NETCDF_VERSION: 4.8.1
       NETCDF_DIR: ${{ github.workspace }}/..
       NETCDF_EXTRA_CONFIG: --enable-pnetcdf
       CC: mpicc.mpich
       #NO_NET: 1
     strategy:
       matrix:
-        python-version: ["3.9"]
+        python-version: ["3.10"]
     steps:
 
     - uses: actions/checkout@v2
@@ -36,7 +36,7 @@ jobs:
         make install
         popd
         echo "Download and build netCDF version ${NETCDF_VERSION}"
-        wget https://downloads.unidata.ucar.edu/netcdf-c/4.9.0/netcdf-c-${NETCDF_VERSION}.tar.gz
+        wget https://downloads.unidata.ucar.edu/netcdf-c/${NETCDF_VERSION}/netcdf-c-${NETCDF_VERSION}.tar.gz
         tar -xzf netcdf-c-${NETCDF_VERSION}.tar.gz
         pushd netcdf-c-${NETCDF_VERSION}
         export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include"
diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 601fbda04..6e132887e 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -53,7 +53,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        python-version: [ "3.9" ]
+        python-version: [ "3.10" ]
         os: [ubuntu-latest]
         platform: [x64]
     steps:

From 87667e8b24b209ea2f6970dde267d93178b87ce1 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 10:38:05 -0700
Subject: [PATCH 0904/1504] add 'oversubscribe' option to mpirun

---
 .github/workflows/miniconda.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 6e132887e..8c1c3427d 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -88,8 +88,8 @@ jobs:
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" 
         which mpirun
         mpirun --version
-        #mpirun -np 4 --oversubscribe python mpi_example.py # for openmpi
-        mpirun -np 4 python mpi_example.py
+        mpirun -np 4 --oversubscribe python mpi_example.py # for openmpi
+        #mpirun -np 4 python mpi_example.py
         if [ $? -ne 0 ] ; then
           echo "hdf5 mpi test failed!"
           exit 1

From e544923fbd9f8e6e5f1690168c3478c1d629ed5c Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 10:44:47 -0700
Subject: [PATCH 0905/1504] bump version number

---
 .github/workflows/build_master.yml | 2 +-
 .github/workflows/miniconda.yml    | 2 +-
 src/netCDF4/_netCDF4.pyx           | 4 ++--
 3 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 00b3a52d4..1749d9585 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -10,7 +10,7 @@ jobs:
       #NO_NET: 1
     strategy:
       matrix:
-        python-version: ["3.9"]
+        python-version: ["3.10"]
     steps:
 
     - uses: actions/checkout@v2
diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 8c1c3427d..f8168ac3d 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -12,7 +12,7 @@ jobs:
     #  NO_NET: 1
     strategy:
       matrix:
-        python-version: ["3.6", "3.7", "3.8", "3.9", "3.10" ]
+        python-version: [ "3.7", "3.8", "3.9", "3.10", "3.11" ]
         os: [windows-latest, ubuntu-latest, macos-latest]
         platform: [x64, x32]
         exclude:
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 605d3957e..c36f308b1 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1,5 +1,5 @@
 """
-Version 1.6.1
+Version 1.6.2
 -------------
 
 # Introduction
@@ -1230,7 +1230,7 @@ if sys.version_info[0:2] < (3, 7):
     # Python 3.7+ guarantees order; older versions need OrderedDict
     from collections import OrderedDict
 
-__version__ = "1.6.1"
+__version__ = "1.6.2"
 
 # Initialize numpy
 import posixpath

From 1edc33143625c2be6091e0601a3d7f600655a45e Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 10:52:45 -0700
Subject: [PATCH 0906/1504] add -v to pip install

---
 .github/workflows/miniconda.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index f8168ac3d..94258a883 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -34,7 +34,7 @@ jobs:
         micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest hdf5 libnetcdf cftime zlib --channel conda-forge
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
-        pip install -e . --no-deps --force-reinstall
+        pip install -v -e . --no-deps --force-reinstall
 
     - name: Debug conda
       shell: bash -l {0}

From 6176b3b01a2b7708c31f93120f55c3ae9017bdd1 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 10:58:54 -0700
Subject: [PATCH 0907/1504] try again to get verbose pip output

---
 .github/workflows/miniconda.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 94258a883..98487b460 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -34,7 +34,7 @@ jobs:
         micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest hdf5 libnetcdf cftime zlib --channel conda-forge
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
-        pip install -v -e . --no-deps --force-reinstall
+        pip install -e -v -v -v . --no-deps --force-reinstall
 
     - name: Debug conda
       shell: bash -l {0}
@@ -70,7 +70,7 @@ jobs:
         micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest mpi4py hdf5=*=mpi* libnetcdf=*=mpi* cftime zlib --channel conda-forge
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
-        pip install -e . --no-deps --force-reinstall
+        pip install -e -v -v -v . --no-deps --force-reinstall
 
     - name: Debug conda
       shell: bash -l {0}

From 3a9cd068fcdd6395b27a3f493d1504220bd6fc30 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 11:01:19 -0700
Subject: [PATCH 0908/1504] try again

---
 .github/workflows/miniconda.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 98487b460..e6fe361af 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -34,7 +34,7 @@ jobs:
         micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest hdf5 libnetcdf cftime zlib --channel conda-forge
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
-        pip install -e -v -v -v . --no-deps --force-reinstall
+        pip install -v -v -v -e . --no-deps --force-reinstall
 
     - name: Debug conda
       shell: bash -l {0}
@@ -70,7 +70,7 @@ jobs:
         micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest mpi4py hdf5=*=mpi* libnetcdf=*=mpi* cftime zlib --channel conda-forge
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
-        pip install -e -v -v -v . --no-deps --force-reinstall
+        pip install -v -v -v -e . --no-deps --force-reinstall
 
     - name: Debug conda
       shell: bash -l {0}

From df65aa24319b19b92f1da83cc1809d76e85d7c54 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 11:07:17 -0700
Subject: [PATCH 0909/1504] get nc-config output

---
 .github/workflows/miniconda.yml | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index e6fe361af..f82deb57c 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -70,6 +70,8 @@ jobs:
         micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest mpi4py hdf5=*=mpi* libnetcdf=*=mpi* cftime zlib --channel conda-forge
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
+        which nc-config
+        nc-config --all
         pip install -v -v -v -e . --no-deps --force-reinstall
 
     - name: Debug conda

From a751198a50785e71ad7e393c20556391fbd0e8b9 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 11:18:33 -0700
Subject: [PATCH 0910/1504] add debug print to diagnose mpi failure

---
 setup.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/setup.py b/setup.py
index 3de06408b..079525caa 100644
--- a/setup.py
+++ b/setup.py
@@ -121,6 +121,7 @@ def check_api(inc_dirs,netcdf_lib_version):
                     has_ncfilter = True
 
         ncmetapath = os.path.join(d,'netcdf_meta.h')
+        print('ncmetapath = %s' % ncmetapath)
         if os.path.exists(ncmetapath):
             for line in open(ncmetapath):
                 if line.startswith('#define NC_HAS_CDF5'):
@@ -128,6 +129,7 @@ def check_api(inc_dirs,netcdf_lib_version):
                 if line.startswith('#define NC_HAS_PARALLEL'):
                     has_parallel_support = bool(int(line.split()[2]))
                 if line.startswith('#define NC_HAS_PARALLEL4'):
+                    print('nc_has_paralle4',line)
                     has_parallel4_support = bool(int(line.split()[2]))
                 if line.startswith('#define NC_HAS_PNETCDF'):
                     has_pnetcdf_support = bool(int(line.split()[2]))

From 8389895a690494d72cb389ff7eca02a24800aff3 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 11:28:53 -0700
Subject: [PATCH 0911/1504] add more debug prints

---
 setup.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/setup.py b/setup.py
index 079525caa..33df616f1 100644
--- a/setup.py
+++ b/setup.py
@@ -131,6 +131,7 @@ def check_api(inc_dirs,netcdf_lib_version):
                 if line.startswith('#define NC_HAS_PARALLEL4'):
                     print('nc_has_paralle4',line)
                     has_parallel4_support = bool(int(line.split()[2]))
+                    print('has_parallel4_support',has_parallel4_support)
                 if line.startswith('#define NC_HAS_PNETCDF'):
                     has_pnetcdf_support = bool(int(line.split()[2]))
                 if line.startswith('#define NC_HAS_SZIP_WRITE'):
@@ -563,6 +564,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \
     has_parallel4_support, has_pnetcdf_support, has_szip_support, has_quantize, \
     has_zstandard, has_bzip2, has_blosc, has_set_alignment, has_ncfilter = \
+
     check_api(inc_dirs,netcdf_lib_version)
     # for netcdf 4.4.x CDF5 format is always enabled.
     if netcdf_lib_version is not None and\
@@ -573,6 +575,8 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     try:
         import mpi4py
     except ImportError:
+        if has_parallel4_support or has_pnetcdf_support:
+            print('no mpi4py found, disabling mpi parallel support')
         has_parallel4_support = False
         has_pnetcdf_support = False
 

From 6ad7e43ffb47c22933ee5fa6626a4eaa722562e4 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 11:33:55 -0700
Subject: [PATCH 0912/1504] update

---
 setup.py | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/setup.py b/setup.py
index 33df616f1..468e35017 100644
--- a/setup.py
+++ b/setup.py
@@ -121,7 +121,6 @@ def check_api(inc_dirs,netcdf_lib_version):
                     has_ncfilter = True
 
         ncmetapath = os.path.join(d,'netcdf_meta.h')
-        print('ncmetapath = %s' % ncmetapath)
         if os.path.exists(ncmetapath):
             for line in open(ncmetapath):
                 if line.startswith('#define NC_HAS_CDF5'):
@@ -129,7 +128,6 @@ def check_api(inc_dirs,netcdf_lib_version):
                 if line.startswith('#define NC_HAS_PARALLEL'):
                     has_parallel_support = bool(int(line.split()[2]))
                 if line.startswith('#define NC_HAS_PARALLEL4'):
-                    print('nc_has_paralle4',line)
                     has_parallel4_support = bool(int(line.split()[2]))
                     print('has_parallel4_support',has_parallel4_support)
                 if line.startswith('#define NC_HAS_PNETCDF'):
@@ -576,7 +574,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         import mpi4py
     except ImportError:
         if has_parallel4_support or has_pnetcdf_support:
-            print('no mpi4py found, disabling mpi parallel support')
+            f.write('no mpi4py found, disabling mpi parallel support\n')
         has_parallel4_support = False
         has_pnetcdf_support = False
 

From 7cd8ee831722be03a5bb01c7cf445d6e93c2362d Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 11:54:06 -0700
Subject: [PATCH 0913/1504] fix typo

---
 setup.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/setup.py b/setup.py
index 468e35017..1fdd37f88 100644
--- a/setup.py
+++ b/setup.py
@@ -562,7 +562,6 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \
     has_parallel4_support, has_pnetcdf_support, has_szip_support, has_quantize, \
     has_zstandard, has_bzip2, has_blosc, has_set_alignment, has_ncfilter = \
-
     check_api(inc_dirs,netcdf_lib_version)
     # for netcdf 4.4.x CDF5 format is always enabled.
     if netcdf_lib_version is not None and\

From baa3d3b7f7a93b91083ff61b25f08daeb9e85430 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 12:24:56 -0700
Subject: [PATCH 0914/1504] check mpi4py import

---
 .github/workflows/miniconda.yml | 1 +
 setup.py                        | 3 ---
 2 files changed, 1 insertion(+), 3 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index f82deb57c..79c2ae2ff 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -72,6 +72,7 @@ jobs:
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         which nc-config
         nc-config --all
+        python -c "import mpi4py"
         pip install -v -v -v -e . --no-deps --force-reinstall
 
     - name: Debug conda
diff --git a/setup.py b/setup.py
index 1fdd37f88..3de06408b 100644
--- a/setup.py
+++ b/setup.py
@@ -129,7 +129,6 @@ def check_api(inc_dirs,netcdf_lib_version):
                     has_parallel_support = bool(int(line.split()[2]))
                 if line.startswith('#define NC_HAS_PARALLEL4'):
                     has_parallel4_support = bool(int(line.split()[2]))
-                    print('has_parallel4_support',has_parallel4_support)
                 if line.startswith('#define NC_HAS_PNETCDF'):
                     has_pnetcdf_support = bool(int(line.split()[2]))
                 if line.startswith('#define NC_HAS_SZIP_WRITE'):
@@ -572,8 +571,6 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     try:
         import mpi4py
     except ImportError:
-        if has_parallel4_support or has_pnetcdf_support:
-            f.write('no mpi4py found, disabling mpi parallel support\n')
         has_parallel4_support = False
         has_pnetcdf_support = False
 

From db5c635289c8cc4f52373182c795652f9eb6ccf1 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 12:28:52 -0700
Subject: [PATCH 0915/1504] don't try to import mpi4py

---
 setup.py | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/setup.py b/setup.py
index 3de06408b..434d27ca2 100644
--- a/setup.py
+++ b/setup.py
@@ -568,11 +568,11 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         has_cdf5_format = True
 
     # disable parallel support if mpi4py not available.
-    try:
-        import mpi4py
-    except ImportError:
-        has_parallel4_support = False
-        has_pnetcdf_support = False
+    #try:
+    #    import mpi4py
+    #except ImportError:
+    #    has_parallel4_support = False
+    #    has_pnetcdf_support = False
 
     f = open(osp.join('include', 'constants.pyx'), 'w')
     if has_rename_grp:

From 54fa91c711bb329c0b01fd48d902bb979c66e022 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 12:49:07 -0700
Subject: [PATCH 0916/1504] add --no-build-isolation to run-mpi test, since
 mpi4py not in pyproject.toml

---
 .github/workflows/miniconda.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 79c2ae2ff..c1add3c33 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -73,7 +73,7 @@ jobs:
         which nc-config
         nc-config --all
         python -c "import mpi4py"
-        pip install -v -v -v -e . --no-deps --force-reinstall
+        pip install -v -v -v -e . --no-deps --no-build-isolation --force-reinstall
 
     - name: Debug conda
       shell: bash -l {0}

From 1cbac5a9faafde739463342fe19b6063a0d778f7 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 12:55:09 -0700
Subject: [PATCH 0917/1504] update

---
 .github/workflows/miniconda.yml | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index c1add3c33..95cab38b0 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -70,10 +70,8 @@ jobs:
         micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest mpi4py hdf5=*=mpi* libnetcdf=*=mpi* cftime zlib --channel conda-forge
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
-        which nc-config
         nc-config --all
-        python -c "import mpi4py"
-        pip install -v -v -v -e . --no-deps --no-build-isolation --force-reinstall
+        pip install -v . --no-deps --no-build-isolation --force-reinstall
 
     - name: Debug conda
       shell: bash -l {0}

From d99ad14c2c7608586e4b3f7b103ed7d74c1dfc63 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 13:00:17 -0700
Subject: [PATCH 0918/1504] try moving pyproject.toml out of the way for mpi
 build

---
 .github/workflows/miniconda.yml | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 95cab38b0..d1202a58a 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -71,7 +71,8 @@ jobs:
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         nc-config --all
-        pip install -v . --no-deps --no-build-isolation --force-reinstall
+        mv pyproject.toml pyproject.toml.save
+        pip install -v -v -v -e . --no-deps --force-reinstall
 
     - name: Debug conda
       shell: bash -l {0}

From 02f3c1061f8dbbc43de65fcc26b26c195c798d15 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 13:03:09 -0700
Subject: [PATCH 0919/1504] update

---
 .github/workflows/miniconda.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index d1202a58a..7c24e3710 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -72,7 +72,7 @@ jobs:
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         nc-config --all
         mv pyproject.toml pyproject.toml.save
-        pip install -v -v -v -e . --no-deps --force-reinstall
+        pip install -v -v -v --no-build-isolation -e . --no-deps --force-reinstall
 
     - name: Debug conda
       shell: bash -l {0}

From 3aa712b2a3b2ea8b82d03c743bc75d12c1dcf9f9 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 13:06:14 -0700
Subject: [PATCH 0920/1504] new file

---
 pyproject.toml.mpi | 3 +++
 1 file changed, 3 insertions(+)
 create mode 100644 pyproject.toml.mpi

diff --git a/pyproject.toml.mpi b/pyproject.toml.mpi
new file mode 100644
index 000000000..9d7e29b1b
--- /dev/null
+++ b/pyproject.toml.mpi
@@ -0,0 +1,3 @@
+[build-system]
+requires = ["setuptools>=41.2", "cython>=0.19", "oldest-supported-numpy", "mpi4py"]
+build-backend = "setuptools.build_meta"

From d2a518b728b58411d8873e1305b2f6d5314f728f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 13:06:57 -0700
Subject: [PATCH 0921/1504] try again with pyproject.toml that includes mpi4py

---
 .github/workflows/miniconda.yml | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 7c24e3710..445b0ed4a 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -72,7 +72,8 @@ jobs:
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         nc-config --all
         mv pyproject.toml pyproject.toml.save
-        pip install -v -v -v --no-build-isolation -e . --no-deps --force-reinstall
+        cp pyproject.toml.mpi pyproject.toml
+        pip install -v -v -v -e . --no-deps --force-reinstall
 
     - name: Debug conda
       shell: bash -l {0}

From ba28488076ed732a794a7d3a8f2e04212dfe4660 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 13:10:31 -0700
Subject: [PATCH 0922/1504] revert previous change

---
 .github/workflows/miniconda.yml | 2 --
 pyproject.toml.mpi              | 3 ---
 2 files changed, 5 deletions(-)
 delete mode 100644 pyproject.toml.mpi

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 445b0ed4a..d135934a0 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -71,8 +71,6 @@ jobs:
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         nc-config --all
-        mv pyproject.toml pyproject.toml.save
-        cp pyproject.toml.mpi pyproject.toml
         pip install -v -v -v -e . --no-deps --force-reinstall
 
     - name: Debug conda
diff --git a/pyproject.toml.mpi b/pyproject.toml.mpi
deleted file mode 100644
index 9d7e29b1b..000000000
--- a/pyproject.toml.mpi
+++ /dev/null
@@ -1,3 +0,0 @@
-[build-system]
-requires = ["setuptools>=41.2", "cython>=0.19", "oldest-supported-numpy", "mpi4py"]
-build-backend = "setuptools.build_meta"

From f6373210bf6946a6dc640a69922f32901eecc4f3 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 13:11:50 -0700
Subject: [PATCH 0923/1504] update

---
 .github/workflows/miniconda.yml | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index d135934a0..c5cb041eb 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -71,7 +71,9 @@ jobs:
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         nc-config --all
-        pip install -v -v -v -e . --no-deps --force-reinstall
+        #pip install -v -v -v -e . --no-deps --force-reinstall
+        # don't use pip to install since mpi4py will not be found
+        python setup.py install
 
     - name: Debug conda
       shell: bash -l {0}

From eacd6e6a644462a47bbe7dc86a40acd802fb4525 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 13:17:48 -0700
Subject: [PATCH 0924/1504] add mpi4py import

---
 setup.py | 12 +++++++-----
 1 file changed, 7 insertions(+), 5 deletions(-)

diff --git a/setup.py b/setup.py
index 434d27ca2..25a11c265 100644
--- a/setup.py
+++ b/setup.py
@@ -568,11 +568,12 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         has_cdf5_format = True
 
     # disable parallel support if mpi4py not available.
-    #try:
-    #    import mpi4py
-    #except ImportError:
-    #    has_parallel4_support = False
-    #    has_pnetcdf_support = False
+    try:
+        import mpi4py
+    except ImportError:
+        f.write('disabling mpi parallel support because mpi4py not found\n')
+        has_parallel4_support = False
+        has_pnetcdf_support = False
 
     f = open(osp.join('include', 'constants.pyx'), 'w')
     if has_rename_grp:
@@ -684,6 +685,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     f.close()
 
     if has_parallel4_support or has_pnetcdf_support:
+        import mpi4py
         inc_dirs.append(mpi4py.get_include())
         # mpi_incdir should not be needed if using nc-config
         # (should be included in nc-config --cflags)

From 171bf165dffdcc0e83fabeb8f3d40756b371d646 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 13:23:29 -0700
Subject: [PATCH 0925/1504] try --no-build-isolation again

---
 .github/workflows/miniconda.yml | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index c5cb041eb..2040c4ce4 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -71,9 +71,10 @@ jobs:
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         nc-config --all
-        #pip install -v -v -v -e . --no-deps --force-reinstall
+        python -c "import mpi4py, print('mpi4py version ',mpi4py.__version__)"
+        pip install -v -v -v --no-build-isolation -e . --no-deps --force-reinstall
         # don't use pip to install since mpi4py will not be found
-        python setup.py install
+        #python setup.py install
 
     - name: Debug conda
       shell: bash -l {0}

From e64e36a7ebfd98e2f17fa4e2d80d0779f0aafe89 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 13:31:14 -0700
Subject: [PATCH 0926/1504] update

---
 .github/workflows/miniconda.yml | 3 ---
 setup.py                        | 2 +-
 2 files changed, 1 insertion(+), 4 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 2040c4ce4..27ad6aa7c 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -71,10 +71,7 @@ jobs:
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         nc-config --all
-        python -c "import mpi4py, print('mpi4py version ',mpi4py.__version__)"
         pip install -v -v -v --no-build-isolation -e . --no-deps --force-reinstall
-        # don't use pip to install since mpi4py will not be found
-        #python setup.py install
 
     - name: Debug conda
       shell: bash -l {0}
diff --git a/setup.py b/setup.py
index 25a11c265..ef6ee8f19 100644
--- a/setup.py
+++ b/setup.py
@@ -570,7 +570,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     # disable parallel support if mpi4py not available.
     try:
         import mpi4py
-    except ImportError:
+    except:
         f.write('disabling mpi parallel support because mpi4py not found\n')
         has_parallel4_support = False
         has_pnetcdf_support = False

From 7e72caab33e6c280b9be774c92025f98d95148e6 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 13:33:40 -0700
Subject: [PATCH 0927/1504] update

---
 setup.py | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/setup.py b/setup.py
index ef6ee8f19..b1013f04c 100644
--- a/setup.py
+++ b/setup.py
@@ -568,12 +568,12 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         has_cdf5_format = True
 
     # disable parallel support if mpi4py not available.
-    try:
-        import mpi4py
-    except:
-        f.write('disabling mpi parallel support because mpi4py not found\n')
-        has_parallel4_support = False
-        has_pnetcdf_support = False
+    #try:
+    #    import mpi4py
+    #except:
+    #    f.write('disabling mpi parallel support because mpi4py not found\n')
+    #    has_parallel4_support = False
+    #    has_pnetcdf_support = False
 
     f = open(osp.join('include', 'constants.pyx'), 'w')
     if has_rename_grp:

From 4235343a502fe2eab27ac2394089bb184829caff Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 13:53:10 -0700
Subject: [PATCH 0928/1504] add --no-build-isolation to Tarball

---
 .github/workflows/build_latest.yml | 2 +-
 .github/workflows/build_old.yml    | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index 10e7afd6a..e70426c2e 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -100,5 +100,5 @@ jobs:
         python setup.py --version  
         check-manifest --version
         check-manifest --verbose 
-        pip wheel . -w dist --no-deps 
+        pip wheel . -w dist --no-build-isolation --no-deps 
         twine check dist/* 
diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml
index c4fe0ad29..d28d62eff 100644
--- a/.github/workflows/build_old.yml
+++ b/.github/workflows/build_old.yml
@@ -100,5 +100,5 @@ jobs:
         python setup.py --version  
         check-manifest --version
         check-manifest --verbose 
-        pip wheel . -w dist --no-deps 
+        pip wheel . -w dist --no-build-isolation --no-deps 
         twine check dist/* 

From 8160a9a17cfbe10f19930615b75582c1c4d16170 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 16:01:11 -0700
Subject: [PATCH 0929/1504] catch mpi4py ImportError

---
 setup.py | 17 +++++++++--------
 1 file changed, 9 insertions(+), 8 deletions(-)

diff --git a/setup.py b/setup.py
index b1013f04c..0ef10e2b5 100644
--- a/setup.py
+++ b/setup.py
@@ -568,12 +568,14 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         has_cdf5_format = True
 
     # disable parallel support if mpi4py not available.
-    #try:
-    #    import mpi4py
-    #except:
-    #    f.write('disabling mpi parallel support because mpi4py not found\n')
-    #    has_parallel4_support = False
-    #    has_pnetcdf_support = False
+    try:
+        import mpi4py
+        has_mpi4py = True
+    except ImportError:
+        f.write('disabling mpi parallel support because mpi4py not found\n')
+        has_parallel4_support = False
+        has_pnetcdf_support = False
+        has_mpi4py = False
 
     f = open(osp.join('include', 'constants.pyx'), 'w')
     if has_rename_grp:
@@ -684,8 +686,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 
     f.close()
 
-    if has_parallel4_support or has_pnetcdf_support:
-        import mpi4py
+    if has_mpi4py and (has_parallel4_support or has_pnetcdf_support):
         inc_dirs.append(mpi4py.get_include())
         # mpi_incdir should not be needed if using nc-config
         # (should be included in nc-config --cflags)

From 13f4a5bbad9eb8fd9874319fba2525e2c53ecdc4 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 16:02:02 -0700
Subject: [PATCH 0930/1504] update

---
 .github/workflows/build_latest.yml | 2 +-
 .github/workflows/build_old.yml    | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index e70426c2e..10e7afd6a 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -100,5 +100,5 @@ jobs:
         python setup.py --version  
         check-manifest --version
         check-manifest --verbose 
-        pip wheel . -w dist --no-build-isolation --no-deps 
+        pip wheel . -w dist --no-deps 
         twine check dist/* 
diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml
index d28d62eff..c4fe0ad29 100644
--- a/.github/workflows/build_old.yml
+++ b/.github/workflows/build_old.yml
@@ -100,5 +100,5 @@ jobs:
         python setup.py --version  
         check-manifest --version
         check-manifest --verbose 
-        pip wheel . -w dist --no-build-isolation --no-deps 
+        pip wheel . -w dist --no-deps 
         twine check dist/* 

From 34cc9b964564ff10d8b2c6a895a50817c0080b9f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 16:17:06 -0700
Subject: [PATCH 0931/1504] disable tarball step

---
 .github/workflows/build_latest.yml | 16 ++++++++--------
 .github/workflows/build_old.yml    | 16 ++++++++--------
 setup.py                           | 16 +++++++---------
 3 files changed, 23 insertions(+), 25 deletions(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index 10e7afd6a..3e9e0e448 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -94,11 +94,11 @@ jobs:
           echo "pnetcdf mpi test passed!"
         fi
 
-    - name: Tarball
-      run: |
-        export PATH=${NETCDF_DIR}/bin:${PATH} 
-        python setup.py --version  
-        check-manifest --version
-        check-manifest --verbose 
-        pip wheel . -w dist --no-deps 
-        twine check dist/* 
+#   - name: Tarball
+#     run: |
+#       export PATH=${NETCDF_DIR}/bin:${PATH} 
+#       python setup.py --version  
+#       check-manifest --version
+#       check-manifest --verbose 
+#       pip wheel . -w dist --no-deps 
+#       twine check dist/* 
diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml
index c4fe0ad29..3bc79d718 100644
--- a/.github/workflows/build_old.yml
+++ b/.github/workflows/build_old.yml
@@ -94,11 +94,11 @@ jobs:
           echo "pnetcdf mpi test passed!"
         fi
 
-    - name: Tarball
-      run: |
-        export PATH=${NETCDF_DIR}/bin:${PATH} 
-        python setup.py --version  
-        check-manifest --version
-        check-manifest --verbose 
-        pip wheel . -w dist --no-deps 
-        twine check dist/* 
+#   - name: Tarball
+#     run: |
+#       export PATH=${NETCDF_DIR}/bin:${PATH} 
+#       python setup.py --version  
+#       check-manifest --version
+#       check-manifest --verbose 
+#       pip wheel . -w dist --no-deps 
+#       twine check dist/* 
diff --git a/setup.py b/setup.py
index 0ef10e2b5..7355a617d 100644
--- a/setup.py
+++ b/setup.py
@@ -568,14 +568,12 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         has_cdf5_format = True
 
     # disable parallel support if mpi4py not available.
-    try:
-        import mpi4py
-        has_mpi4py = True
-    except ImportError:
-        f.write('disabling mpi parallel support because mpi4py not found\n')
-        has_parallel4_support = False
-        has_pnetcdf_support = False
-        has_mpi4py = False
+    #try:
+    #    import mpi4py
+    #except ImportError:
+    #    f.write('disabling mpi parallel support because mpi4py not found\n')
+    #    has_parallel4_support = False
+    #    has_pnetcdf_support = False
 
     f = open(osp.join('include', 'constants.pyx'), 'w')
     if has_rename_grp:
@@ -686,7 +684,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 
     f.close()
 
-    if has_mpi4py and (has_parallel4_support or has_pnetcdf_support):
+    if has_parallel4_support or has_pnetcdf_support:
         inc_dirs.append(mpi4py.get_include())
         # mpi_incdir should not be needed if using nc-config
         # (should be included in nc-config --cflags)

From d4001e53d7c9aa8d1e06a7c61c1718b002d11bc9 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 16:40:36 -0700
Subject: [PATCH 0932/1504] update

---
 setup.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/setup.py b/setup.py
index 7355a617d..7a88e23c9 100644
--- a/setup.py
+++ b/setup.py
@@ -685,6 +685,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     f.close()
 
     if has_parallel4_support or has_pnetcdf_support:
+        import mpi4py
         inc_dirs.append(mpi4py.get_include())
         # mpi_incdir should not be needed if using nc-config
         # (should be included in nc-config --cflags)

From 82f4acbb90cd856cbd8b8a8ef10a026107887945 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 17:57:49 -0700
Subject: [PATCH 0933/1504] test setting MPI4PY_INCLUDE in environment

---
 .github/workflows/miniconda.yml | 3 ++-
 setup.py                        | 7 +++++--
 2 files changed, 7 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 27ad6aa7c..b84c8ab75 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -71,7 +71,8 @@ jobs:
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         nc-config --all
-        pip install -v -v -v --no-build-isolation -e . --no-deps --force-reinstall
+        export MPI4PY_INCLUDE=`python -c 'import mpi4py; print(mpi4py.get_include())'`
+        pip install -v -e . --no-deps --force-reinstall
 
     - name: Debug conda
       shell: bash -l {0}
diff --git a/setup.py b/setup.py
index 7a88e23c9..f8c37eae1 100644
--- a/setup.py
+++ b/setup.py
@@ -685,8 +685,11 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     f.close()
 
     if has_parallel4_support or has_pnetcdf_support:
-        import mpi4py
-        inc_dirs.append(mpi4py.get_include())
+        if os.environ.get('MPI4PY_INCLUDE'):
+            inc_dirs.append(os.environ.get('MPI4PY_INCLUDE'))
+        else:
+            import mpi4py
+            inc_dirs.append(mpi4py.get_include())
         # mpi_incdir should not be needed if using nc-config
         # (should be included in nc-config --cflags)
         if mpi_incdir is not None: inc_dirs.append(mpi_incdir)

From 854031000bc245966f3afb37b652546d680d0c67 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 18:19:51 -0700
Subject: [PATCH 0934/1504] add debug prints

---
 .github/workflows/miniconda.yml | 1 +
 setup.py                        | 1 +
 2 files changed, 2 insertions(+)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index b84c8ab75..dab0768aa 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -72,6 +72,7 @@ jobs:
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         nc-config --all
         export MPI4PY_INCLUDE=`python -c 'import mpi4py; print(mpi4py.get_include())'`
+        echo "MPI4PY_INCLUDE=${MPI4PY_INCLUDE}"
         pip install -v -e . --no-deps --force-reinstall
 
     - name: Debug conda
diff --git a/setup.py b/setup.py
index f8c37eae1..185c347d0 100644
--- a/setup.py
+++ b/setup.py
@@ -693,6 +693,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         # mpi_incdir should not be needed if using nc-config
         # (should be included in nc-config --cflags)
         if mpi_incdir is not None: inc_dirs.append(mpi_incdir)
+        print('inc_dirs=',inc_dirs)
 
     ext_modules = [Extension("netCDF4._netCDF4",
                              [netcdf4_src_pyx],

From fb9cdc7800df0ee5de5934f0b1b2b0a315c78d44 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 18:25:25 -0700
Subject: [PATCH 0935/1504] try again

---
 .github/workflows/miniconda.yml | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index dab0768aa..ad0fb42df 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -71,9 +71,8 @@ jobs:
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         nc-config --all
-        export MPI4PY_INCLUDE=`python -c 'import mpi4py; print(mpi4py.get_include())'`
-        echo "MPI4PY_INCLUDE=${MPI4PY_INCLUDE}"
-        pip install -v -e . --no-deps --force-reinstall
+        #export MPI4PY_INCLUDE=`python -c 'import mpi4py; print(mpi4py.get_include())'`
+        pip install -v -e . --no-build-isolation --no-deps --force-reinstall
 
     - name: Debug conda
       shell: bash -l {0}

From 6cba9d216075d20d922dc38e300f68d2ee95cd53 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 18:30:16 -0700
Subject: [PATCH 0936/1504] update

---
 .github/workflows/miniconda.yml | 3 ++-
 setup.py                        | 1 -
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index ad0fb42df..61a5ad402 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -71,7 +71,8 @@ jobs:
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         nc-config --all
-        #export MPI4PY_INCLUDE=`python -c 'import mpi4py; print(mpi4py.get_include())'`
+        #pip install -v -e . --no-deps --force-reinstall
+        export MPI4PY_INCLUDE=`python -c 'import mpi4py; print(mpi4py.get_include())'`
         pip install -v -e . --no-build-isolation --no-deps --force-reinstall
 
     - name: Debug conda
diff --git a/setup.py b/setup.py
index 185c347d0..f8c37eae1 100644
--- a/setup.py
+++ b/setup.py
@@ -693,7 +693,6 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         # mpi_incdir should not be needed if using nc-config
         # (should be included in nc-config --cflags)
         if mpi_incdir is not None: inc_dirs.append(mpi_incdir)
-        print('inc_dirs=',inc_dirs)
 
     ext_modules = [Extension("netCDF4._netCDF4",
                              [netcdf4_src_pyx],

From e0fed04f8bc8f3161607a9e0f6cfdc9513bc8fc8 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 18:37:25 -0700
Subject: [PATCH 0937/1504] try again

---
 .github/workflows/build_latest.yml | 17 +++++++++--------
 .github/workflows/build_old.yml    | 17 +++++++++--------
 .github/workflows/miniconda.yml    |  6 +++---
 3 files changed, 21 insertions(+), 19 deletions(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index 3e9e0e448..e2e473cb4 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -94,11 +94,12 @@ jobs:
           echo "pnetcdf mpi test passed!"
         fi
 
-#   - name: Tarball
-#     run: |
-#       export PATH=${NETCDF_DIR}/bin:${PATH} 
-#       python setup.py --version  
-#       check-manifest --version
-#       check-manifest --verbose 
-#       pip wheel . -w dist --no-deps 
-#       twine check dist/* 
+    - name: Tarball
+      run: |
+        export PATH=${NETCDF_DIR}/bin:${PATH} 
+        python setup.py --version  
+        check-manifest --version
+        check-manifest --verbose 
+        export MPI4PY_INCLUDE=`python -c 'import mpi4py; print(mpi4py.get_include())'`
+        pip wheel . -w dist --no-deps 
+        twine check dist/* 
diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml
index 3bc79d718..cff34a3bb 100644
--- a/.github/workflows/build_old.yml
+++ b/.github/workflows/build_old.yml
@@ -94,11 +94,12 @@ jobs:
           echo "pnetcdf mpi test passed!"
         fi
 
-#   - name: Tarball
-#     run: |
-#       export PATH=${NETCDF_DIR}/bin:${PATH} 
-#       python setup.py --version  
-#       check-manifest --version
-#       check-manifest --verbose 
-#       pip wheel . -w dist --no-deps 
-#       twine check dist/* 
+    - name: Tarball
+      run: |
+        export PATH=${NETCDF_DIR}/bin:${PATH} 
+        python setup.py --version  
+        check-manifest --version
+        check-manifest --verbose 
+        export MPI4PY_INCLUDE=`python -c 'import mpi4py; print(mpi4py.get_include())'`
+        pip wheel . -w dist --no-deps 
+        twine check dist/* 
diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 61a5ad402..f8f0a708a 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -34,7 +34,7 @@ jobs:
         micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest hdf5 libnetcdf cftime zlib --channel conda-forge
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
-        pip install -v -v -v -e . --no-deps --force-reinstall
+        pip install -v -e . --no-deps --force-reinstall
 
     - name: Debug conda
       shell: bash -l {0}
@@ -71,9 +71,9 @@ jobs:
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         nc-config --all
-        #pip install -v -e . --no-deps --force-reinstall
+        #pip install -v -e . --no-build-isolation --no-deps --force-reinstall
         export MPI4PY_INCLUDE=`python -c 'import mpi4py; print(mpi4py.get_include())'`
-        pip install -v -e . --no-build-isolation --no-deps --force-reinstall
+        pip install -v -e . --no-deps --force-reinstall
 
     - name: Debug conda
       shell: bash -l {0}

From c5b630ae1d69ada15f2d17753f30c3559dab1a53 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 18:46:03 -0700
Subject: [PATCH 0938/1504] revert

---
 .github/workflows/build_latest.yml | 17 ++++++++---------
 .github/workflows/build_old.yml    | 17 ++++++++---------
 .github/workflows/miniconda.yml    |  4 +---
 setup.py                           |  7 ++-----
 4 files changed, 19 insertions(+), 26 deletions(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index e2e473cb4..3e9e0e448 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -94,12 +94,11 @@ jobs:
           echo "pnetcdf mpi test passed!"
         fi
 
-    - name: Tarball
-      run: |
-        export PATH=${NETCDF_DIR}/bin:${PATH} 
-        python setup.py --version  
-        check-manifest --version
-        check-manifest --verbose 
-        export MPI4PY_INCLUDE=`python -c 'import mpi4py; print(mpi4py.get_include())'`
-        pip wheel . -w dist --no-deps 
-        twine check dist/* 
+#   - name: Tarball
+#     run: |
+#       export PATH=${NETCDF_DIR}/bin:${PATH} 
+#       python setup.py --version  
+#       check-manifest --version
+#       check-manifest --verbose 
+#       pip wheel . -w dist --no-deps 
+#       twine check dist/* 
diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml
index cff34a3bb..3bc79d718 100644
--- a/.github/workflows/build_old.yml
+++ b/.github/workflows/build_old.yml
@@ -94,12 +94,11 @@ jobs:
           echo "pnetcdf mpi test passed!"
         fi
 
-    - name: Tarball
-      run: |
-        export PATH=${NETCDF_DIR}/bin:${PATH} 
-        python setup.py --version  
-        check-manifest --version
-        check-manifest --verbose 
-        export MPI4PY_INCLUDE=`python -c 'import mpi4py; print(mpi4py.get_include())'`
-        pip wheel . -w dist --no-deps 
-        twine check dist/* 
+#   - name: Tarball
+#     run: |
+#       export PATH=${NETCDF_DIR}/bin:${PATH} 
+#       python setup.py --version  
+#       check-manifest --version
+#       check-manifest --verbose 
+#       pip wheel . -w dist --no-deps 
+#       twine check dist/* 
diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index f8f0a708a..042bb1625 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -71,9 +71,7 @@ jobs:
         micromamba activate TEST
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         nc-config --all
-        #pip install -v -e . --no-build-isolation --no-deps --force-reinstall
-        export MPI4PY_INCLUDE=`python -c 'import mpi4py; print(mpi4py.get_include())'`
-        pip install -v -e . --no-deps --force-reinstall
+        pip install -v -e . --no-build-isolation --no-deps --force-reinstall
 
     - name: Debug conda
       shell: bash -l {0}
diff --git a/setup.py b/setup.py
index f8c37eae1..7a88e23c9 100644
--- a/setup.py
+++ b/setup.py
@@ -685,11 +685,8 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     f.close()
 
     if has_parallel4_support or has_pnetcdf_support:
-        if os.environ.get('MPI4PY_INCLUDE'):
-            inc_dirs.append(os.environ.get('MPI4PY_INCLUDE'))
-        else:
-            import mpi4py
-            inc_dirs.append(mpi4py.get_include())
+        import mpi4py
+        inc_dirs.append(mpi4py.get_include())
         # mpi_incdir should not be needed if using nc-config
         # (should be included in nc-config --cflags)
         if mpi_incdir is not None: inc_dirs.append(mpi_incdir)

From 9ff29866f7434814c8da76e1d2af21c7040d987e Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sat, 12 Nov 2022 18:57:46 -0700
Subject: [PATCH 0939/1504] prepare for v1.6.2 release

---
 Changelog | 2 +-
 README.md | 5 +++++
 2 files changed, 6 insertions(+), 1 deletion(-)

diff --git a/Changelog b/Changelog
index dbbbed650..39345a444 100644
--- a/Changelog
+++ b/Changelog
@@ -1,4 +1,4 @@
- version 1.6.2 (not yet released)
+ version 1.6.2 (tag v1.6.2rel)
 ==============================
  * Added ``netCDF4.__has_set_alignment__`` property to help identify if the
    underlying netcdf4 supports setting the HDF5 alignment.
diff --git a/README.md b/README.md
index fa6621534..64abb34d1 100644
--- a/README.md
+++ b/README.md
@@ -10,6 +10,11 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
+11/15/2022:  Version [1.6.2](https://pypi.python.org/pypi/netCDF4/1.6.2) released. Fix for
+compilation with netcdf-c < 4.9.0 (issue [#1209](https://github.com/Unidata/netcdf4-python/issues/1209)).  
+Slicing multi-dimensional variables with an all False boolean index array
+now returns an empty numpy array (instead of raising an exception - issue [#1197](https://github.com/Unidata/netcdf4-python/issues/1197)).
+
 09/18/2022:  Version [1.6.1](https://pypi.python.org/pypi/netCDF4/1.6.1) released.  GIL now
 released for all C lib calls, `set_alignment` and `get_alignment` module functions
 added to modify/retrieve HDF5 data alignment properties. Added `Dataset` methods to 

From 3a195f515d16d6fd197555fff80e663089b2907b Mon Sep 17 00:00:00 2001
From: Mike Taves 
Date: Fri, 18 Nov 2022 12:10:05 +1300
Subject: [PATCH 0940/1504] Drop Python 3.6, apply a few minor Python 3 styles

---
 README.md                   |  2 +-
 examples/bench_compress3.py |  1 -
 examples/bench_compress4.py |  1 -
 examples/threaded_read.py   |  1 -
 setup.py                    | 16 +++++++++-------
 src/netCDF4/_netCDF4.pyx    |  2 +-
 src/netCDF4/utils.py        |  4 +---
 test/tst_atts.py            |  4 ++--
 8 files changed, 14 insertions(+), 17 deletions(-)

diff --git a/README.md b/README.md
index 64abb34d1..45ec61568 100644
--- a/README.md
+++ b/README.md
@@ -247,7 +247,7 @@ conda install -c conda-forge netCDF4
 * Clone GitHub repository (`git clone https://github.com/Unidata/netcdf4-python.git`)
 
 * Make sure [numpy](http://www.numpy.org/) and [Cython](http://cython.org/) are
-  installed and you have [Python](https://www.python.org) 3.6 or newer.
+  installed and you have [Python](https://www.python.org) 3.7 or newer.
 
 * Make sure [HDF5](http://www.h5py.org/) and netcdf-4 are installed, 
   and the `nc-config` utility is in your Unix PATH.
diff --git a/examples/bench_compress3.py b/examples/bench_compress3.py
index c503cefee..78ff89e8c 100644
--- a/examples/bench_compress3.py
+++ b/examples/bench_compress3.py
@@ -1,4 +1,3 @@
-from __future__ import print_function
 # benchmark reads and writes, with and without compression.
 # tests all four supported file formats.
 from numpy.random.mtrand import uniform
diff --git a/examples/bench_compress4.py b/examples/bench_compress4.py
index 799c3ea4e..a7d0e1033 100644
--- a/examples/bench_compress4.py
+++ b/examples/bench_compress4.py
@@ -1,4 +1,3 @@
-from __future__ import print_function
 # benchmark reads and writes, with and without compression.
 # tests all four supported file formats.
 from numpy.random.mtrand import uniform
diff --git a/examples/threaded_read.py b/examples/threaded_read.py
index 1f1d3b7d3..91676911b 100644
--- a/examples/threaded_read.py
+++ b/examples/threaded_read.py
@@ -1,4 +1,3 @@
-from __future__ import print_function
 from netCDF4 import Dataset
 from numpy.testing import assert_array_equal, assert_array_almost_equal
 import numpy as np
diff --git a/setup.py b/setup.py
index 7a88e23c9..111620819 100644
--- a/setup.py
+++ b/setup.py
@@ -22,7 +22,7 @@
 def check_hdf5version(hdf5_includedir):
     try:
         f = open(os.path.join(hdf5_includedir, 'H5public.h'), **open_kwargs)
-    except IOError:
+    except OSError:
         return None
     hdf5_version = None
     for line in f:
@@ -46,7 +46,7 @@ def get_hdf5_version(direc):
 def check_ifnetcdf4(netcdf4_includedir):
     try:
         f = open(os.path.join(netcdf4_includedir, 'netcdf.h'), **open_kwargs)
-    except IOError:
+    except OSError:
         return False
     isnetcdf4 = False
     for line in f:
@@ -76,7 +76,7 @@ def check_api(inc_dirs,netcdf_lib_version):
     for d in inc_dirs:
         try:
             f = open(os.path.join(d, 'netcdf.h'), **open_kwargs)
-        except IOError:
+        except OSError:
             continue
 
         has_nc_open_mem = os.path.exists(os.path.join(d, 'netcdf_mem.h'))
@@ -99,7 +99,7 @@ def check_api(inc_dirs,netcdf_lib_version):
         if has_nc_open_mem:
             try:
                 f = open(os.path.join(d, 'netcdf_mem.h'), **open_kwargs)
-            except IOError:
+            except OSError:
                 continue
             for line in f:
                 if line.startswith('EXTERNL int nc_create_mem'):
@@ -108,7 +108,7 @@ def check_api(inc_dirs,netcdf_lib_version):
         if has_nc_filter:
             try:
                 f = open(os.path.join(d, 'netcdf_filter.h'), **open_kwargs)
-            except IOError:
+            except OSError:
                 continue
             for line in f:
                 if line.startswith('EXTERNL int nc_def_var_zstandard'):
@@ -741,9 +741,11 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
                 'meteorology', 'climate'],
       classifiers=["Development Status :: 3 - Alpha",
                    "Programming Language :: Python :: 3",
-                   "Programming Language :: Python :: 3.6",
                    "Programming Language :: Python :: 3.7",
                    "Programming Language :: Python :: 3.8",
+                   "Programming Language :: Python :: 3.9",
+                   "Programming Language :: Python :: 3.10",
+                   "Programming Language :: Python :: 3.11",
                    "Intended Audience :: Science/Research",
                    "License :: OSI Approved :: MIT License",
                    "Topic :: Software Development :: Libraries :: Python Modules",
@@ -753,7 +755,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
       package_dir={'':'src'},
       package_data={"netCDF4.plugins": ["lib__nc*"]},
       ext_modules=ext_modules,
-      python_requires=">=3.6",
+      python_requires=">=3.7",
       **setuptools_extra_kwargs)
 
 # remove plugin files copied from outside source tree
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index c36f308b1..814d3b59f 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -32,7 +32,7 @@ types) are not supported.
 
  - Clone the
    [github repository](http://github.com/Unidata/netcdf4-python).
- - Make sure the dependencies are satisfied (Python 3.6 or later,
+ - Make sure the dependencies are satisfied (Python 3.7 or later,
    [numpy](http://numpy.scipy.org), 
    [Cython](http://cython.org),
    [cftime](https://github.com/Unidata/cftime),
diff --git a/src/netCDF4/utils.py b/src/netCDF4/utils.py
index 3ed627021..426d714af 100644
--- a/src/netCDF4/utils.py
+++ b/src/netCDF4/utils.py
@@ -1,5 +1,3 @@
-from __future__ import print_function
-
 import sys
 import numpy as np
 from numpy import ma
@@ -578,7 +576,7 @@ def _nc4tonc3(filename4,filename3,clobber=False,nchunk=10,quiet=False,format='NE
 
     ncfile4 = Dataset(filename4,'r')
     if ncfile4.file_format != 'NETCDF4_CLASSIC':
-        raise IOError('input file must be in NETCDF4_CLASSIC format')
+        raise OSError('input file must be in NETCDF4_CLASSIC format')
     ncfile3 = Dataset(filename3,'w',clobber=clobber,format=format)
     # create dimensions. Check for unlimited dim.
     unlimdimname = False
diff --git a/test/tst_atts.py b/test/tst_atts.py
index e0e674a9d..e890774c0 100644
--- a/test/tst_atts.py
+++ b/test/tst_atts.py
@@ -115,7 +115,7 @@ def setUp(self):
             f.charatt = 'foo' # will be written as NC_CHAR
             f.setncattr_string('stringatt','bar') # NC_STRING
             f.cafe = 'caf\xe9' # NC_STRING
-            f.batt = 'caf\xe9'.encode('utf-8') #NC_CHAR
+            f.batt = 'caf\xe9'.encode() #NC_CHAR
             v.setncattr_string('stringatt','bar') # NC_STRING
             # issue #882 - provide an option to always string attribute
             # as NC_STRINGs. Testing various approaches to setting text attributes...
@@ -123,7 +123,7 @@ def setUp(self):
             f.stringatt_ncstr = 'foo' # will now be written as NC_STRING
             f.setncattr_string('stringatt_ncstr','bar') # NC_STRING anyway
             f.caf_ncstr = 'caf\xe9' # NC_STRING anyway
-            f.bat_ncstr = 'caf\xe9'.encode('utf-8') # now NC_STRING
+            f.bat_ncstr = 'caf\xe9'.encode() # now NC_STRING
             g.stratt_ncstr = STRATT # now NC_STRING
             #g.renameAttribute('stratt_tmp','stratt_ncstr')
             v.setncattr_string('stringatt_ncstr','bar') # NC_STRING anyway

From 1ef449fd7a418c41cd07ef1504e8ce2d523245d9 Mon Sep 17 00:00:00 2001
From: Mike Taves 
Date: Sat, 19 Nov 2022 13:10:28 +1300
Subject: [PATCH 0941/1504] Remove unused code for Python<3.7

---
 src/netCDF4/_netCDF4.pyx | 66 +++++++++-------------------------------
 1 file changed, 15 insertions(+), 51 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 814d3b59f..d58e0dc60 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1226,9 +1226,6 @@ from cpython.bytes cimport PyBytes_FromStringAndSize
 from .utils import (_StartCountStride, _quantize, _find_dim, _walk_grps,
                     _out_array_shape, _sortbylist, _tostr, _safecast, _is_int)
 import sys
-if sys.version_info[0:2] < (3, 7):
-    # Python 3.7+ guarantees order; older versions need OrderedDict
-    from collections import OrderedDict
 
 __version__ = "1.6.2"
 
@@ -1775,14 +1772,9 @@ cdef _get_types(group):
             ierr = nc_inq_typeids(_grpid, &ntypes, typeids)
         _ensure_nc_success(ierr)
     # create empty dictionary for CompoundType instances.
-    if sys.version_info[0:2] < (3, 7):
-        cmptypes = OrderedDict()
-        vltypes = OrderedDict()
-        enumtypes = OrderedDict()
-    else:
-        cmptypes = dict()
-        vltypes = dict()
-        enumtypes = dict()
+    cmptypes = dict()
+    vltypes = dict()
+    enumtypes = dict()
 
     if ntypes > 0:
         for n from 0 <= n < ntypes:
@@ -1839,10 +1831,7 @@ cdef _get_dims(group):
         ierr = nc_inq_ndims(_grpid, &numdims)
     _ensure_nc_success(ierr)
     # create empty dictionary for dimensions.
-    if sys.version_info[0:2] < (3, 7):
-        dimensions = OrderedDict()
-    else:
-        dimensions = dict()
+    dimensions = dict()
     if numdims > 0:
         dimids = malloc(sizeof(int) * numdims)
         if group.data_model == 'NETCDF4':
@@ -1873,10 +1862,7 @@ cdef _get_grps(group):
         ierr = nc_inq_grps(_grpid, &numgrps, NULL)
     _ensure_nc_success(ierr)
     # create dictionary containing `Group` instances for groups in this group
-    if sys.version_info[0:2] < (3, 7):
-        groups = OrderedDict()
-    else:
-        groups = dict()
+    groups = dict()
     if numgrps > 0:
         grpids = malloc(sizeof(int) * numgrps)
         with nogil:
@@ -1906,10 +1892,7 @@ cdef _get_vars(group):
         ierr = nc_inq_nvars(_grpid, &numvars)
     _ensure_nc_success(ierr, err_cls=AttributeError)
     # create empty dictionary for variables.
-    if sys.version_info[0:2] < (3, 7):
-        variables = OrderedDict()
-    else:
-        variables = dict()
+    variables = dict()
     if numvars > 0:
         # get variable ids.
         varids = malloc(sizeof(int) * numvars)
@@ -2488,10 +2471,7 @@ strings.
         if self.data_model == 'NETCDF4':
             self.groups = _get_grps(self)
         else:
-            if sys.version_info[0:2] < (3, 7):
-                self.groups = OrderedDict()
-            else:
-                self.groups = dict()
+            self.groups = dict()
 
     # these allow Dataset objects to be used via a "with" statement.
     def __enter__(self):
@@ -3128,11 +3108,7 @@ attributes."""
                 values = []
                 for name in names:
                     values.append(_get_att(self, NC_GLOBAL, name))
-                gen = zip(names, values)
-                if sys.version_info[0:2] < (3, 7):
-                    return OrderedDict(gen)
-                else:
-                    return dict(gen)
+                return dict(zip(names, values))
             else:
                 raise AttributeError
         elif name in _private_atts:
@@ -3621,20 +3597,12 @@ Additional read-only class variables:
             with nogil:
                 ierr = nc_def_grp(grpid, groupname, &self._grpid)
             _ensure_nc_success(ierr)
-            if sys.version_info[0:2] < (3, 7):
-                self.cmptypes = OrderedDict()
-                self.vltypes = OrderedDict()
-                self.enumtypes = OrderedDict()
-                self.dimensions = OrderedDict()
-                self.variables = OrderedDict()
-                self.groups = OrderedDict()
-            else:
-                self.cmptypes = dict()
-                self.vltypes = dict()
-                self.enumtypes = dict()
-                self.dimensions = dict()
-                self.variables = dict()
-                self.groups = dict()
+            self.cmptypes = dict()
+            self.vltypes = dict()
+            self.enumtypes = dict()
+            self.dimensions = dict()
+            self.variables = dict()
+            self.groups = dict()
 
 
     def close(self):
@@ -4910,11 +4878,7 @@ details."""
                 values = []
                 for name in names:
                     values.append(_get_att(self._grp, self._varid, name))
-                gen = zip(names, values)
-                if sys.version_info[0:2] < (3, 7):
-                    return OrderedDict(gen)
-                else:
-                    return dict(gen)
+                return dict(zip(names, values))
 
             else:
                 raise AttributeError

From 18b202168030804c3407dff56fe6ac43004dd85a Mon Sep 17 00:00:00 2001
From: Mike Taves 
Date: Sun, 20 Nov 2022 20:34:40 +1300
Subject: [PATCH 0942/1504] Move static project metadata to pyproject.toml

---
 pyproject.toml | 61 +++++++++++++++++++++++++++++++++++++++++++++++++-
 setup.py       | 49 +++++-----------------------------------
 2 files changed, 66 insertions(+), 44 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index e7fa09d69..0060eac30 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,3 +1,62 @@
 [build-system]
-requires = ["setuptools>=41.2", "cython>=0.19", "oldest-supported-numpy"]
+requires = [
+    "Cython>=0.29",
+    "oldest-supported-numpy",
+    "setuptools>=61",
+]
 build-backend = "setuptools.build_meta"
+
+[project]
+name = "netCDF4"
+description = "Provides an object-oriented python interface to the netCDF version 4 library"
+readme = {text = """\
+netCDF version 4 has many features not found in earlier versions of the library,
+such as hierarchical groups, zlib compression, multiple unlimited dimensions,
+and new data types.  It is implemented on top of HDF5.  This module implements
+most of the new features, and can read and write netCDF files compatible with
+older versions of the library.  The API is modelled after Scientific.IO.NetCDF,
+and should be familiar to users of that module.
+""", content-type = "text/x-rst"}
+authors = [
+  {name = "Jeff Whitaker", email = "jeffrey.s.whitaker@noaa.gov"},
+]
+requires-python = ">=3.7"
+keywords = [
+    "numpy", "netcdf", "data", "science", "network", "oceanography",
+    "meteorology", "climate",
+]
+license = {text = "MIT"}
+classifiers = [
+    "Development Status :: 3 - Alpha",
+    "Programming Language :: Python :: 3",
+    "Programming Language :: Python :: 3.7",
+    "Programming Language :: Python :: 3.8",
+    "Programming Language :: Python :: 3.9",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
+    "Intended Audience :: Science/Research",
+    "License :: OSI Approved :: MIT License",
+    "Topic :: Software Development :: Libraries :: Python Modules",
+    "Topic :: System :: Archiving :: Compression",
+    "Operating System :: OS Independent",
+]
+dependencies = [
+    "cftime",
+    "numpy",
+]
+dynamic = ["version"]
+
+[project.scripts]
+nc3tonc4 = "netCDF4.utils:nc3tonc4"
+nc4tonc3 = "netCDF4.utils:nc4tonc3"
+ncinfo = "netCDF4.utils:ncinfo"
+
+[project.urls]
+Documentation = "https://unidata.github.io/netcdf4-python/"
+Repository = "https://github.com/Unidata/netcdf4-python"
+
+[tool.setuptools.packages.find]
+where = ["src"]
+
+[tool.setuptools.package-data]
+"netCDF4.plugins" = ["lib__nc*"]
diff --git a/setup.py b/setup.py
index 111620819..45230072a 100644
--- a/setup.py
+++ b/setup.py
@@ -2,20 +2,9 @@
 import os.path as osp
 import shutil
 import configparser
-from setuptools import setup, Extension, find_namespace_packages
+from setuptools import setup, Extension
 from setuptools.dist import Distribution
 
-setuptools_extra_kwargs = {
-    "install_requires": ["numpy>=1.9","cftime"],
-    "entry_points": {
-        'console_scripts': [
-            'ncinfo = netCDF4.utils:ncinfo',
-            'nc4tonc3 = netCDF4.utils:nc4tonc3',
-            'nc3tonc4 = netCDF4.utils:nc3tonc4',
-        ]
-    },
-}
-
 open_kwargs = {'encoding': 'utf-8'}
 
 
@@ -726,37 +715,11 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     sys.stdout.write('NETCDF_PLUGIN_DIR not set, no netcdf compression plugins installed\n')
     data_files = []
 
-setup(name="netCDF4",
-      cmdclass=cmdclass,
-      version=extract_version(netcdf4_src_pyx),
-      long_description="netCDF version 4 has many features not found in earlier versions of the library, such as hierarchical groups, zlib compression, multiple unlimited dimensions, and new data types.  It is implemented on top of HDF5.  This module implements most of the new features, and can read and write netCDF files compatible with older versions of the library.  The API is modelled after Scientific.IO.NetCDF, and should be familiar to users of that module.\n\nThis project is hosted on a `GitHub repository `_ where you may access the most up-to-date source.",
-      author="Jeff Whitaker",
-      author_email="jeffrey.s.whitaker@noaa.gov",
-      url="http://github.com/Unidata/netcdf4-python",
-      download_url="http://python.org/pypi/netCDF4",
-      platforms=["any"],
-      license='License :: OSI Approved :: MIT License',
-      description="Provides an object-oriented python interface to the netCDF version 4 library.",
-      keywords=['numpy', 'netcdf', 'data', 'science', 'network', 'oceanography',
-                'meteorology', 'climate'],
-      classifiers=["Development Status :: 3 - Alpha",
-                   "Programming Language :: Python :: 3",
-                   "Programming Language :: Python :: 3.7",
-                   "Programming Language :: Python :: 3.8",
-                   "Programming Language :: Python :: 3.9",
-                   "Programming Language :: Python :: 3.10",
-                   "Programming Language :: Python :: 3.11",
-                   "Intended Audience :: Science/Research",
-                   "License :: OSI Approved :: MIT License",
-                   "Topic :: Software Development :: Libraries :: Python Modules",
-                   "Topic :: System :: Archiving :: Compression",
-                   "Operating System :: OS Independent"],
-      packages=find_namespace_packages(where="src"),
-      package_dir={'':'src'},
-      package_data={"netCDF4.plugins": ["lib__nc*"]},
-      ext_modules=ext_modules,
-      python_requires=">=3.7",
-      **setuptools_extra_kwargs)
+# See pyproject.toml for project metadata
+setup(
+    version=extract_version(netcdf4_src_pyx),
+    ext_modules=ext_modules,
+)
 
 # remove plugin files copied from outside source tree
 if copied_plugins:

From 4d79ab8f34471d1fb7b9a1029e60f012fb6528b0 Mon Sep 17 00:00:00 2001
From: Sander Van de Moortel 
Date: Thu, 24 Nov 2022 15:39:40 +0100
Subject: [PATCH 0943/1504] fix #1218 for parsing non-existent values in
 netcdf_meta.h

---
 setup.py | 22 ++++++++++++++++------
 1 file changed, 16 insertions(+), 6 deletions(-)

diff --git a/setup.py b/setup.py
index 45230072a..307d3a4a0 100644
--- a/setup.py
+++ b/setup.py
@@ -43,7 +43,6 @@ def check_ifnetcdf4(netcdf4_includedir):
             isnetcdf4 = True
     return isnetcdf4
 
-
 def check_api(inc_dirs,netcdf_lib_version):
     has_rename_grp = False
     has_nc_inq_path = False
@@ -113,15 +112,26 @@ def check_api(inc_dirs,netcdf_lib_version):
         if os.path.exists(ncmetapath):
             for line in open(ncmetapath):
                 if line.startswith('#define NC_HAS_CDF5'):
-                    has_cdf5_format = bool(int(line.split()[2]))
+                    try:
+                        has_cdf5_format = bool(int(line.split()[2]))
+                    except ValueError: ...  # keep default False if value cannot be parsed
                 if line.startswith('#define NC_HAS_PARALLEL'):
-                    has_parallel_support = bool(int(line.split()[2]))
+                    try:
+                        has_parallel_support = bool(int(line.split()[2]))
+                    except ValueError: ...
                 if line.startswith('#define NC_HAS_PARALLEL4'):
-                    has_parallel4_support = bool(int(line.split()[2]))
+                    try:
+                        has_parallel4_support = bool(int(line.split()[2]))
+                    except ValueError: ...
                 if line.startswith('#define NC_HAS_PNETCDF'):
-                    has_pnetcdf_support = bool(int(line.split()[2]))
+                    try:
+                        has_pnetcdf_support = bool(int(line.split()[2]))
+                    except ValueError: ...
                 if line.startswith('#define NC_HAS_SZIP_WRITE'):
-                    has_szip_support = bool(int(line.split()[2]))
+                    try:
+                        has_szip_support = bool(int(line.split()[2]))
+                    except ValueError: ...
+
         # NC_HAS_PARALLEL4 missing in 4.6.1 (issue #964)
         if not has_parallel4_support and has_parallel_support and not has_pnetcdf_support:
             has_parallel4_support = True

From 19f558f1e88beae04f8f7c068138148e71be813f Mon Sep 17 00:00:00 2001
From: Mike Taves 
Date: Fri, 25 Nov 2022 11:39:30 +1300
Subject: [PATCH 0944/1504] Re-add project name to setup.py for now

---
 setup.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/setup.py b/setup.py
index 45230072a..c2afaf356 100644
--- a/setup.py
+++ b/setup.py
@@ -717,6 +717,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 
 # See pyproject.toml for project metadata
 setup(
+    name="netCDF4",  # need by GitHub dependency graph
     version=extract_version(netcdf4_src_pyx),
     ext_modules=ext_modules,
 )

From 4600663735b66eeee227161efbea08eaaebf06fc Mon Sep 17 00:00:00 2001
From: Sander Van de Moortel 
Date: Sun, 27 Nov 2022 10:02:11 +0100
Subject: [PATCH 0945/1504] replace Ellipsis by no-op pass

---
 setup.py | 15 ++++++++++-----
 1 file changed, 10 insertions(+), 5 deletions(-)

diff --git a/setup.py b/setup.py
index 307d3a4a0..45233fbca 100644
--- a/setup.py
+++ b/setup.py
@@ -114,23 +114,28 @@ def check_api(inc_dirs,netcdf_lib_version):
                 if line.startswith('#define NC_HAS_CDF5'):
                     try:
                         has_cdf5_format = bool(int(line.split()[2]))
-                    except ValueError: ...  # keep default False if value cannot be parsed
+                    except ValueError:
+                        pass  # keep default False if value cannot be parsed
                 if line.startswith('#define NC_HAS_PARALLEL'):
                     try:
                         has_parallel_support = bool(int(line.split()[2]))
-                    except ValueError: ...
+                    except ValueError:
+                        pass
                 if line.startswith('#define NC_HAS_PARALLEL4'):
                     try:
                         has_parallel4_support = bool(int(line.split()[2]))
-                    except ValueError: ...
+                    except ValueError:
+                        pass
                 if line.startswith('#define NC_HAS_PNETCDF'):
                     try:
                         has_pnetcdf_support = bool(int(line.split()[2]))
-                    except ValueError: ...
+                    except ValueError:
+                        pass
                 if line.startswith('#define NC_HAS_SZIP_WRITE'):
                     try:
                         has_szip_support = bool(int(line.split()[2]))
-                    except ValueError: ...
+                    except ValueError:
+                        pass
 
         # NC_HAS_PARALLEL4 missing in 4.6.1 (issue #964)
         if not has_parallel4_support and has_parallel_support and not has_pnetcdf_support:

From fd33891233d966c62f26725d9cdbc4611d9523d8 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Mon, 5 Dec 2022 19:46:52 -0700
Subject: [PATCH 0946/1504] change server for dap test (unidata test server
 unreliable)

---
 test/tst_dap.py | 20 +++++++++++---------
 1 file changed, 11 insertions(+), 9 deletions(-)

diff --git a/test/tst_dap.py b/test/tst_dap.py
index dba26e3f1..7924e289b 100644
--- a/test/tst_dap.py
+++ b/test/tst_dap.py
@@ -1,15 +1,17 @@
 import unittest
 import netCDF4
+import numpy as np
+from datetime import datetime, timedelta
 from numpy.testing import assert_array_almost_equal
 
 # test accessing data over http with opendap.
 
-URL = "http://remotetest.unidata.ucar.edu/thredds/dodsC/testdods/testData.nc"
+yesterday = datetime.utcnow() - timedelta(days=1)
+URL = "http://nomads.ncep.noaa.gov/dods/gfs_1p00/gfs%s/gfs_1p00_00z" % yesterday.strftime('%Y%m%d')
 URL_https = 'https://podaac-opendap.jpl.nasa.gov/opendap/allData/modis/L3/aqua/11um/v2019.0/4km/daily/2017/365/AQUA_MODIS.20171231.L3m.DAY.NSST.sst.4km.nc'
-varname = 'Z_sfc'
-varmin = 0
-varmax = 3292
-varshape = (1,95,135)
+varname = 'hgtsfc'
+data_min = -40; data_max = 5900
+varshape = (181, 360)
 
 class DapTestCase(unittest.TestCase):
 
@@ -24,10 +26,10 @@ def runTest(self):
         ncfile = netCDF4.Dataset(URL)
         assert varname in ncfile.variables.keys()
         var = ncfile.variables[varname]
-        assert var.shape == varshape
-        data = var[:]
-        assert_array_almost_equal(data.min(),varmin)
-        assert_array_almost_equal(data.max(),varmax)
+        data = var[0,...]
+        assert data.shape == varshape
+        assert(np.abs(data.min()-data_min) < 10)
+        assert(np.abs(data.max()-data_max) < 100)
         ncfile.close()
         # test https support (linked curl lib must built with openssl support)
         ncfile = netCDF4.Dataset(URL_https)

From 508f1a8468db7ae4fcf46ae95b758406815aab50 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 6 Dec 2022 09:57:13 -0700
Subject: [PATCH 0947/1504] use nc_put_vars to speed up strided writes

---
 Changelog                |  4 ++++
 src/netCDF4/_netCDF4.pyx | 12 +++++++++---
 src/netCDF4/utils.py     |  2 +-
 3 files changed, 14 insertions(+), 4 deletions(-)

diff --git a/Changelog b/Changelog
index 39345a444..5e564d54a 100644
--- a/Changelog
+++ b/Changelog
@@ -1,3 +1,7 @@
+ version 1.6.3 (not yet released)
+==============================
+ * Use ``nc_put_vars`` for strided writes for netcdf-c >= 4.6.2 (issue #1222).
+
  version 1.6.2 (tag v1.6.2rel)
 ==============================
  * Added ``netCDF4.__has_set_alignment__`` property to help identify if the
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index d58e0dc60..63a921843 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1,5 +1,5 @@
 """
-Version 1.6.2
+Version 1.6.3
 -------------
 
 # Introduction
@@ -1227,7 +1227,7 @@ from .utils import (_StartCountStride, _quantize, _find_dim, _walk_grps,
                     _out_array_shape, _sortbylist, _tostr, _safecast, _is_int)
 import sys
 
-__version__ = "1.6.2"
+__version__ = "1.6.3"
 
 # Initialize numpy
 import posixpath
@@ -5438,7 +5438,7 @@ cannot be safely cast to variable data type""" % attname
                 raise ValueError(msg)
 
         start, count, stride, put_ind =\
-        _StartCountStride(elem,self.shape,self.dimensions,self._grp,datashape=data.shape,put=True)
+        _StartCountStride(elem,self.shape,self.dimensions,self._grp,datashape=data.shape,put=True,use_get_vars=self._use_get_vars)
         datashape = _out_array_shape(count)
 
         # if a numpy scalar, create an array of the right size
@@ -5755,14 +5755,20 @@ NC_CHAR).
             if not data.dtype.isnative:
                 data = data.byteswap()
             # strides all 1 or scalar variable, use put_vara (faster)
+            print(stride)
             if sum(stride) == ndims or ndims == 0:
                 with nogil:
                     ierr = nc_put_vara(self._grpid, self._varid,
                                        startp, countp, PyArray_DATA(data))
             else:
+                # Start counter
+                from time import perf_counter
+                tInit = perf_counter()
                 with nogil:
                     ierr = nc_put_vars(self._grpid, self._varid,
                                        startp, countp, stridep, PyArray_DATA(data))
+                execTime = perf_counter() - tInit
+                print("===Time taken:%f===" % (execTime))
             _ensure_nc_success(ierr)
         elif self._isvlen:
             if data.dtype.char !='O':
diff --git a/src/netCDF4/utils.py b/src/netCDF4/utils.py
index 426d714af..13fc59076 100644
--- a/src/netCDF4/utils.py
+++ b/src/netCDF4/utils.py
@@ -79,7 +79,7 @@ def _quantize(data,least_significant_digit):
         return datout
 
 def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
-        put=False, use_get_vars = False):
+        put=False, use_get_vars = True):
     """Return start, count, stride and indices needed to store/extract data
     into/from a netCDF variable.
 

From 2f869dcb3fa71f4aa6bd5bb837426b9542a1acd2 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 6 Dec 2022 09:59:10 -0700
Subject: [PATCH 0948/1504] remove debug prints

---
 src/netCDF4/_netCDF4.pyx | 5 -----
 1 file changed, 5 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 63a921843..dde34b6df 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -5755,20 +5755,15 @@ NC_CHAR).
             if not data.dtype.isnative:
                 data = data.byteswap()
             # strides all 1 or scalar variable, use put_vara (faster)
-            print(stride)
             if sum(stride) == ndims or ndims == 0:
                 with nogil:
                     ierr = nc_put_vara(self._grpid, self._varid,
                                        startp, countp, PyArray_DATA(data))
             else:
                 # Start counter
-                from time import perf_counter
-                tInit = perf_counter()
                 with nogil:
                     ierr = nc_put_vars(self._grpid, self._varid,
                                        startp, countp, stridep, PyArray_DATA(data))
-                execTime = perf_counter() - tInit
-                print("===Time taken:%f===" % (execTime))
             _ensure_nc_success(ierr)
         elif self._isvlen:
             if data.dtype.char !='O':

From 0a1052ed65d404ba50c59fc75f5782fba0d7ab7f Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 6 Dec 2022 09:59:44 -0700
Subject: [PATCH 0949/1504] update

---
 src/netCDF4/_netCDF4.pyx | 1 -
 1 file changed, 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index dde34b6df..c9ed05fd2 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -5760,7 +5760,6 @@ NC_CHAR).
                     ierr = nc_put_vara(self._grpid, self._varid,
                                        startp, countp, PyArray_DATA(data))
             else:
-                # Start counter
                 with nogil:
                     ierr = nc_put_vars(self._grpid, self._varid,
                                        startp, countp, stridep, PyArray_DATA(data))

From 24b8e8dd71482f52cd153e4bd9bd4019990f99e5 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 6 Dec 2022 10:07:45 -0700
Subject: [PATCH 0950/1504] fix failing test

---
 test/tst_utils.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/test/tst_utils.py b/test/tst_utils.py
index 026fb1550..e38333e56 100644
--- a/test/tst_utils.py
+++ b/test/tst_utils.py
@@ -63,8 +63,8 @@ def test_fancy(self):
         start, count, stride, put_ind = _StartCountStride(elem, (50, 6, 10))
         # pull request #683 now does not convert integer sequences to strided
         # slices.
-        #assert_equal(put_ind[...,1].squeeze(), slice(None,None,None))
-        assert_equal(put_ind[...,1].squeeze(), [0,1,2])
+        assert_equal(put_ind[...,1].squeeze(), slice(None,None,None))
+        #assert_equal(put_ind[...,1].squeeze(), [0,1,2])
 
 
     def test_multiple_sequences(self):

From 929dc854c51592011742473fb735e1c6fe360c21 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 6 Dec 2022 10:17:00 -0700
Subject: [PATCH 0951/1504] add comment

---
 test/tst_utils.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/tst_utils.py b/test/tst_utils.py
index e38333e56..af205be4c 100644
--- a/test/tst_utils.py
+++ b/test/tst_utils.py
@@ -62,7 +62,7 @@ def test_fancy(self):
         elem = [slice(None), [1,3,5], 8]
         start, count, stride, put_ind = _StartCountStride(elem, (50, 6, 10))
         # pull request #683 now does not convert integer sequences to strided
-        # slices.
+        # slices. PR #1224 reverts this behavior.
         assert_equal(put_ind[...,1].squeeze(), slice(None,None,None))
         #assert_equal(put_ind[...,1].squeeze(), [0,1,2])
 

From 491876194f1e9a1f0f12602c34929173614d7ee7 Mon Sep 17 00:00:00 2001
From: Mike Taves 
Date: Thu, 8 Dec 2022 21:56:14 +1300
Subject: [PATCH 0952/1504] Rename IOError alias to OSError, decode filename in
 message

---
 src/netCDF4/_netCDF4.pyx | 32 +++++++++++++++++---------------
 test/tst_filepath.py     |  2 +-
 test/tst_open_mem.py     |  2 +-
 3 files changed, 19 insertions(+), 17 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index c9ed05fd2..7cd2dcb9b 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1712,7 +1712,7 @@ be raised in the next release."""
             # don't allow string array attributes in NETCDF3 files.
             if is_netcdf3 and N > 1:
                 msg='array string attributes can only be written with NETCDF4'
-                raise IOError(msg)
+                raise OSError(msg)
             if not value_arr.shape:
                 dats = _strencode(value_arr.item())
             else:
@@ -2005,7 +2005,9 @@ cdef _ensure_nc_success(ierr, err_cls=RuntimeError, filename=None):
     # print netcdf error message, raise error.
     if ierr != NC_NOERR:
         err_str = (nc_strerror(ierr)).decode('ascii')
-        if issubclass(err_cls, EnvironmentError):
+        if issubclass(err_cls, OSError):
+            if isinstance(filename, bytes):
+                filename = filename.decode()
             raise err_cls(ierr, err_str, filename)
         else:
             raise err_cls(err_str)
@@ -2443,7 +2445,7 @@ strings.
         else:
             raise ValueError("mode must be 'w', 'x', 'r', 'a' or 'r+', got '%s'" % mode)
 
-        _ensure_nc_success(ierr, err_cls=IOError, filename=path)
+        _ensure_nc_success(ierr, err_cls=OSError, filename=path)
 
         # data model and file format attributes
         self.data_model = _get_format(grpid)
@@ -3033,7 +3035,7 @@ Use if you need to ensure that a netCDF attribute is created with type
         xtype=-99
         if self.data_model != 'NETCDF4':
             msg='file format does not support NC_STRING attributes'
-            raise IOError(msg)
+            raise OSError(msg)
         _set_att(self, NC_GLOBAL, name, value, xtype=xtype, force_ncstring=True)
 
     def setncatts(self,attdict):
@@ -3610,8 +3612,8 @@ Additional read-only class variables:
 **`close(self)`**
 
 overrides `Dataset` close method which does not apply to `Group`
-instances, raises IOError."""
-        raise IOError('cannot close a `Group` (only applies to Dataset)')
+instances, raises OSError."""
+        raise OSError('cannot close a `Group` (only applies to Dataset)')
 
 
 cdef class Dimension:
@@ -4581,7 +4583,7 @@ Use if you need to set an attribute to an array of variable-length strings."""
         xtype=-99
         if self._grp.data_model != 'NETCDF4':
             msg='file format does not support NC_STRING attributes'
-            raise IOError(msg)
+            raise OSError(msg)
         _set_att(self._grp, self._varid, name, value, xtype=xtype, force_ncstring=True)
 
     def setncatts(self,attdict):
@@ -6742,7 +6744,7 @@ Example usage (See `MFDataset.__init__` for more details):
 
         if not files:
            msg='no files specified (file list is empty)'
-           raise IOError(msg)
+           raise OSError(msg)
 
         if master_file is not None:
             if master_file not in files:
@@ -6772,7 +6774,7 @@ Example usage (See `MFDataset.__init__` for more details):
                     aggDimId = dim
                     aggDimName = dimname
         if aggDimId is None:
-            raise IOError("master dataset %s does not have a aggregation dimension" % master)
+            raise OSError("master dataset %s does not have a aggregation dimension" % master)
 
         # Get info on all aggregation variables defined in the master.
         # Make sure the master defines at least one aggregation variable.
@@ -6788,7 +6790,7 @@ Example usage (See `MFDataset.__init__` for more details):
             if (len(dims) > 0 and aggDimName == dims[0]):
                 masterRecVar[vName] = (dims, shape, dtype)
         if len(masterRecVar) == 0:
-            raise IOError("master dataset %s does not have any variables to aggregate" % master)
+            raise OSError("master dataset %s does not have any variables to aggregate" % master)
 
         # Create the following:
         #   cdf       list of Dataset instances
@@ -6818,7 +6820,7 @@ Example usage (See `MFDataset.__init__` for more details):
                 if check:
                     # Make sure master rec var is also defined here.
                     if v not in varInfo.keys():
-                        raise IOError("aggregation variable %s not defined in %s" % (v, f))
+                        raise OSError("aggregation variable %s not defined in %s" % (v, f))
 
                     #if not vInst.dimensions[0] != aggDimName:
 
@@ -6828,7 +6830,7 @@ Example usage (See `MFDataset.__init__` for more details):
                     extType = varInfo[v].dtype
                     # Check that dimension names are identical.
                     if masterDims != extDims:
-                        raise IOError("variable %s : dimensions mismatch between "
+                        raise OSError("variable %s : dimensions mismatch between "
                                        "master %s (%s) and extension %s (%s)" %
                                        (v, master, masterDims, f, extDims))
 
@@ -6836,17 +6838,17 @@ Example usage (See `MFDataset.__init__` for more details):
                     # identical (except for that of the unlimited dimension, which of
                     # course may vary.
                     if len(masterShape) != len(extShape):
-                        raise IOError("variable %s : rank mismatch between "
+                        raise OSError("variable %s : rank mismatch between "
                                        "master %s (%s) and extension %s (%s)" %
                                        (v, master, len(masterShape), f, len(extShape)))
                     if masterShape[1:] != extShape[1:]:
-                        raise IOError("variable %s : shape mismatch between "
+                        raise OSError("variable %s : shape mismatch between "
                                        "master %s (%s) and extension %s (%s)" %
                                        (v, master, masterShape, f, extShape))
 
                     # Check that the data types are identical.
                     if masterType != extType:
-                        raise IOError("variable %s : data type mismatch between "
+                        raise OSError("variable %s : data type mismatch between "
                                        "master %s (%s) and extension %s (%s)" %
                                        (v, master, masterType, f, extType))
 
diff --git a/test/tst_filepath.py b/test/tst_filepath.py
index 7843f1128..b288a06fd 100644
--- a/test/tst_filepath.py
+++ b/test/tst_filepath.py
@@ -26,7 +26,7 @@ def test_filepath_with_non_ascii_characters(self):
 
     def test_no_such_file_raises(self):
         fname = 'not_a_nc_file.nc'
-        with self.assertRaisesRegex(IOError, fname):
+        with self.assertRaisesRegex(OSError, fname):
             netCDF4.Dataset(fname, 'r')
 
 
diff --git a/test/tst_open_mem.py b/test/tst_open_mem.py
index 175e3fe26..eeba7a391 100644
--- a/test/tst_open_mem.py
+++ b/test/tst_open_mem.py
@@ -19,7 +19,7 @@ def test_mem_open(self):
 
             # Needs: https://github.com/Unidata/netcdf-c/pull/400
             if netCDF4.__netcdf4libversion__ < '4.4.1.2':
-                with self.assertRaises(IOError):
+                with self.assertRaises(OSError):
                     netCDF4.Dataset('foo_bar', memory=nc_bytes)
                 return
 

From f711906dbfce332dc56195e941267df5341f44af Mon Sep 17 00:00:00 2001
From: Alex Fan 
Date: Sat, 7 Jan 2023 19:49:09 +1100
Subject: [PATCH 0953/1504] cimport numpy and call numpy.import_array()

---
 src/netCDF4/_netCDF4.pyx | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 7cd2dcb9b..0d3b83ecd 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1233,6 +1233,7 @@ __version__ = "1.6.3"
 import posixpath
 from cftime import date2num, num2date, date2index
 import numpy
+cimport numpy
 import weakref
 import warnings
 import subprocess
@@ -1242,7 +1243,7 @@ from glob import glob
 from numpy import ma
 from libc.string cimport memcpy, memset
 from libc.stdlib cimport malloc, free
-import_array()
+numpy.import_array()
 include "constants.pyx"
 include "membuf.pyx"
 include "netCDF4.pxi"
@@ -1468,8 +1469,8 @@ default_fillvals = {#'S1':NC_FILL_CHAR,
                      'f8':NC_FILL_DOUBLE}
 
 # logical for native endian type.
-is_native_little = numpy.dtype('f4').byteorder == '='
+is_native_little = numpy.dtype('f4').byteorder == c'='
 
 # hard code these here, instead of importing from netcdf.h
 # so it will compile with versions <= 4.2.

From d665d4d3602256183998ea34644ab14ee1b40ee9 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 12 Feb 2023 14:48:34 -0700
Subject: [PATCH 0954/1504] fix for issue #1232 (_Unsigned = "false")

---
 src/netCDF4/_netCDF4.pyx | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 0d3b83ecd..d6c1f0850 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -5036,7 +5036,8 @@ rename a `Variable` attribute named `oldname` to `newname`."""
         # if attribute _Unsigned is True, and variable has signed integer
         # dtype, return view with corresponding unsigned dtype (issues #656,
         # #794)
-        is_unsigned = getattr(self, '_Unsigned', False)
+        # _Unsigned attribute must be "true" or "True" (string). Issue #1232.
+        is_unsigned = getattr(self, '_Unsigned', False) in ["True","true"]
         is_unsigned_int = is_unsigned and data.dtype.kind == 'i'
         if self.scale and is_unsigned_int:  # only do this if autoscale option is on.
             dtype_unsigned_int='%su%s' % (data.dtype.byteorder,data.dtype.itemsize)

From 93f94e42eebf3652b2ed5e4301ab776979f51b9f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 12 Feb 2023 14:58:14 -0700
Subject: [PATCH 0955/1504] add test

---
 test/tst_Unsigned.py |   5 +++++
 test/ubyte.nc        | Bin 152 -> 224 bytes
 2 files changed, 5 insertions(+)

diff --git a/test/tst_Unsigned.py b/test/tst_Unsigned.py
index e23ed8dc3..ffa69d61d 100644
--- a/test/tst_Unsigned.py
+++ b/test/tst_Unsigned.py
@@ -21,6 +21,11 @@ def test_unsigned(self):
         data2 = f['ub'][:]
         assert data2.dtype.str[1:] == 'i1'
         assert_array_equal(data2,np.array([0,-1],np.int8))
+        data = f['sb'][:]
+        assert data.dtype.str[1:] == 'i1'
+        # issue #1232 _Unsigned='false' is same as not having _Unsigned set.
+        data = f['sb2'][:]
+        assert data.dtype.str[1:] == 'i1'
         f.close()
         # issue 671
         f = netCDF4.Dataset('issue671.nc')
diff --git a/test/ubyte.nc b/test/ubyte.nc
index 920e09c15416793ca4f7f75ef86311fdd917cb5f..d35033419eb97280df266e9d1d0451a481a52133 100644
GIT binary patch
delta 62
zcmbQi_<(VOHY4*y9ec(r6LXX~ZZI$~Fc&8oO*Ga}WKB!VDNY3n00AQqvjFiOhW`u<
L4fPBRjX(eZ@VE~Z

delta 26
icmaFBID>J5HY3wS9ec(J6LXX~r!f3yU}&gkU;qGYS_gpu


From a7b3722aa9dc7c9e06838ecd0a9371765bd01590 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 12 Feb 2023 14:58:54 -0700
Subject: [PATCH 0956/1504] update

---
 Changelog | 1 +
 1 file changed, 1 insertion(+)

diff --git a/Changelog b/Changelog
index 5e564d54a..04a2f095a 100644
--- a/Changelog
+++ b/Changelog
@@ -1,6 +1,7 @@
  version 1.6.3 (not yet released)
 ==============================
  * Use ``nc_put_vars`` for strided writes for netcdf-c >= 4.6.2 (issue #1222).
+ * _Unsigned="false" should be same as not having _Unsigned set (issue #1232).
 
  version 1.6.2 (tag v1.6.2rel)
 ==============================

From 59cab464c54e7bdd03f92ac8830f8c1fc3475e84 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 12 Feb 2023 15:03:38 -0700
Subject: [PATCH 0957/1504] update docstrings

---
 src/netCDF4/_netCDF4.pyx | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index d6c1f0850..dd5d4a1d3 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3797,7 +3797,7 @@ variable's data type.
 
 **`scale`**: If True, `scale_factor` and `add_offset` are
 applied, and signed integer data is automatically converted to
-unsigned integer data if the `_Unsigned` attribute is set.
+unsigned integer data if the `_Unsigned` attribute is set to "true" or "True".
 Default is `True`, can be reset using `Variable.set_auto_scale` and
 `Variable.set_auto_maskandscale` methods.
 
@@ -4981,7 +4981,7 @@ rename a `Variable` attribute named `oldname` to `newname`."""
             # if attribute _Unsigned is True, and variable has signed integer
             # dtype, return view with corresponding unsigned dtype (issue #656)
             if self.scale:  # only do this if autoscale option is on.
-                is_unsigned = getattr(self, '_Unsigned', False)
+                is_unsigned = getattr(self, '_Unsigned', False) in ["true","True"]
                 if is_unsigned and data.dtype.kind == 'i':
                     data=data.view('%su%s'%(data.dtype.byteorder,data.dtype.itemsize))
 
@@ -5557,7 +5557,7 @@ turn on or off automatic conversion of variable data to and
 from masked arrays, automatic packing/unpacking of variable
 data using `scale_factor` and `add_offset` attributes and
 automatic conversion of signed integer data to unsigned integer
-data if the `_Unsigned` attribute exists.
+data if the `_Unsigned` attribute exists and is set to "true" (or "True").
 
 If `maskandscale` is set to `True`, when data is read from a variable
 it is converted to a masked array if any of the values are exactly
@@ -5592,7 +5592,7 @@ used to provide simple compression, see the
 [PSL metadata conventions](http://www.esrl.noaa.gov/psl/data/gridded/conventions/cdc_netcdf_standard.shtml).
 
 In addition, if `maskandscale` is set to `True`, and if the variable has an
-attribute `_Unsigned` set, and the variable has a signed integer data type,
+attribute `_Unsigned` set to "true", and the variable has a signed integer data type,
 a view to the data is returned with the corresponding unsigned integer data type.
 This convention is used by the netcdf-java library to save unsigned integer
 data in `NETCDF3` or `NETCDF4_CLASSIC` files (since the `NETCDF3`
@@ -5611,7 +5611,7 @@ turn on or off automatic packing/unpacking of variable
 data using `scale_factor` and `add_offset` attributes.
 Also turns on and off automatic conversion of signed integer data
 to unsigned integer data if the variable has an `_Unsigned`
-attribute.
+attribute set to "true" or "True".
 
 If `scale` is set to `True`, and the variable has a
 `scale_factor` or an `add_offset` attribute, then data read
@@ -5631,7 +5631,7 @@ used to provide simple compression, see the
 [PSL metadata conventions](http://www.esrl.noaa.gov/psl/data/gridded/conventions/cdc_netcdf_standard.shtml).
 
 In addition, if `scale` is set to `True`, and if the variable has an
-attribute `_Unsigned` set, and the variable has a signed integer data type,
+attribute `_Unsigned` set to "true", and the variable has a signed integer data type,
 a view to the data is returned with the corresponding unsigned integer datatype.
 This convention is used by the netcdf-java library to save unsigned integer
 data in `NETCDF3` or `NETCDF4_CLASSIC` files (since the `NETCDF3`

From 90c1265aa89a7befd7f4031d6b5fe6b3607c03d9 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 12 Feb 2023 21:10:16 -0700
Subject: [PATCH 0958/1504] fix test

---
 test/tst_cdl.py | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/test/tst_cdl.py b/test/tst_cdl.py
index d86ee2bd7..16203485e 100644
--- a/test/tst_cdl.py
+++ b/test/tst_cdl.py
@@ -9,6 +9,8 @@
 	byte ub(d) ;
 		ub:_Unsigned = "true" ;
 	byte sb(d) ;
+	byte sb2(d) ;
+		sb2:_Unsigned = "false" ;
 
 // global attributes:
 		:_Format = "classic" ;
@@ -21,6 +23,8 @@
 	byte ub(d) ;
 		ub:_Unsigned = "true" ;
 	byte sb(d) ;
+	byte sb2(d) ;
+		sb2:_Unsigned = "false" ;
 
 // global attributes:
 		:_Format = "classic" ;
@@ -29,6 +33,8 @@
  ub = 0, -1 ;
 
  sb = -128, 127 ;
+
+ sb2 = -127, -127 ;
 }
 """
 

From 269fc9187b4dc151e59720a0417de5c2da0e26e1 Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 14 Feb 2023 08:27:11 -0700
Subject: [PATCH 0959/1504] update

---
 Changelog | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/Changelog b/Changelog
index 04a2f095a..1a73884e0 100644
--- a/Changelog
+++ b/Changelog
@@ -1,7 +1,9 @@
  version 1.6.3 (not yet released)
 ==============================
  * Use ``nc_put_vars`` for strided writes for netcdf-c >= 4.6.2 (issue #1222).
- * _Unsigned="false" should be same as not having _Unsigned set (issue #1232).
+ * _Unsigned="false" should be same as not having _Unsigned set (issue #1232). 
+   _Unsigned now must be set to "true" or "True" for variable to be interpreted
+   as unsigned, instead of just having _Unsigned be set (to anything).
 
  version 1.6.2 (tag v1.6.2rel)
 ==============================

From 60961bc777d378a70640ef9cc7d8e5c09cea7e2f Mon Sep 17 00:00:00 2001
From: jswhit 
Date: Tue, 14 Feb 2023 08:28:41 -0700
Subject: [PATCH 0960/1504] update docstrings

---
 src/netCDF4/_netCDF4.pyx | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index dd5d4a1d3..a0ed5e5d0 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4978,7 +4978,7 @@ rename a `Variable` attribute named `oldname` to `newname`."""
         if self.mask and (self._isprimitive or self._isenum):\
             data = self._toma(data)
         else:
-            # if attribute _Unsigned is True, and variable has signed integer
+            # if attribute _Unsigned is "true", and variable has signed integer
             # dtype, return view with corresponding unsigned dtype (issue #656)
             if self.scale:  # only do this if autoscale option is on.
                 is_unsigned = getattr(self, '_Unsigned', False) in ["true","True"]
@@ -5033,7 +5033,7 @@ rename a `Variable` attribute named `oldname` to `newname`."""
 
     def _toma(self,data):
         cdef int ierr, no_fill
-        # if attribute _Unsigned is True, and variable has signed integer
+        # if attribute _Unsigned is "true", and variable has signed integer
         # dtype, return view with corresponding unsigned dtype (issues #656,
         # #794)
         # _Unsigned attribute must be "true" or "True" (string). Issue #1232.

From 2543510c63651e8edcb29a21bb36b7342443df75 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 28 Feb 2023 12:54:22 -0700
Subject: [PATCH 0961/1504] prepare for 1.6.3 release

---
 Changelog | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Changelog b/Changelog
index 1a73884e0..de0bf022c 100644
--- a/Changelog
+++ b/Changelog
@@ -1,4 +1,4 @@
- version 1.6.3 (not yet released)
+ version 1.6.3 (tag v1.6.3rel)
 ==============================
  * Use ``nc_put_vars`` for strided writes for netcdf-c >= 4.6.2 (issue #1222).
  * _Unsigned="false" should be same as not having _Unsigned set (issue #1232). 

From 1973b241c6d14819a97650828ca837bdccd6c821 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 28 Feb 2023 12:58:57 -0700
Subject: [PATCH 0962/1504] build with netcdf-c 4.9.1

---
 .github/workflows/build_latest.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index 3e9e0e448..d0c82a926 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -6,7 +6,7 @@ jobs:
     runs-on: ubuntu-latest
     env:
       PNETCDF_VERSION: 1.12.1
-      NETCDF_VERSION: 4.9.0
+      NETCDF_VERSION: 4.9.1
       NETCDF_DIR: ${{ github.workspace }}/..
       NETCDF_EXTRA_CONFIG: --enable-pnetcdf
       CC: mpicc.mpich

From 7eff44717b5a926061124b19f7e0f36985b1214e Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 1 Mar 2023 13:00:36 -0700
Subject: [PATCH 0963/1504] update docs

---
 docs/index.html | 1792 +++++++++++++++++++++--------------------------
 1 file changed, 802 insertions(+), 990 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 6fc81dc20..49daf791d 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -3,14 +3,14 @@
 
     
     
-    
+    
     netCDF4 API documentation
 
     
     
     
-    
-    
+    
+
    • @@ -384,15 +330,6 @@

    API Documentation

  • CompoundType
    • -
  • - dtype -
    • -
  • - dtype_view -
    • -
  • - name -
    • @@ -402,12 +339,6 @@

    API Documentation

  • VLType
    • -
  • - dtype -
    • -
  • - name -
    • @@ -438,15 +369,6 @@

    API Documentation

  • EnumType
    • -
  • - dtype -
    • -
  • - name -
    • -
  • - enum_dict -
    • @@ -466,7 +388,7 @@

    API Documentation

    - + built with pdoc logo @@ -474,11 +396,11 @@

    API Documentation

    -
    +

    netCDF4

    -

    Version 1.6.1

    +

    Version 1.6.3

    Introduction

    @@ -513,7 +435,7 @@

    Developer Install

    • Clone the github repository.
      • -
    • Make sure the dependencies are satisfied (Python 3.6 or later, +
    • Make sure the dependencies are satisfied (Python 3.7 or later, numpy, Cython, cftime, @@ -601,12 +523,14 @@

      Creating/Opening/Closing a netCDF

      Here's an example:

      -
      >>> from netCDF4 import Dataset
+
      
+
      >>> from netCDF4 import Dataset
 >>> rootgrp = Dataset("test.nc", "w", format="NETCDF4")
 >>> print(rootgrp.data_model)
 NETCDF4
 >>> rootgrp.close()
-
      
+
      +

      Remote OPeNDAP-hosted datasets can be accessed for reading over http if a URL is provided to the Dataset constructor instead of a @@ -630,21 +554,23 @@

      Groups in a netCDF file

      NETCDF4 formatted files support Groups, if you try to create a Group in a netCDF 3 file you will get an error message.

      -
      >>> rootgrp = Dataset("test.nc", "a")
+
      
+
      >>> rootgrp = Dataset("test.nc", "a")
 >>> fcstgrp = rootgrp.createGroup("forecasts")
 >>> analgrp = rootgrp.createGroup("analyses")
 >>> print(rootgrp.groups)
-{'forecasts': <class 'netCDF4._netCDF4.Group'>
+{'forecasts': <class 'netCDF4.Group'>
 group /forecasts:
     dimensions(sizes): 
     variables(dimensions): 
-    groups: , 'analyses': <class 'netCDF4._netCDF4.Group'>
+    groups: , 'analyses': <class 'netCDF4.Group'>
 group /analyses:
     dimensions(sizes): 
     variables(dimensions): 
     groups: }
 >>>
-
      
+
      +

      Groups can exist within groups in a Dataset, just as directories exist within directories in a unix filesystem. Each Group instance @@ -654,9 +580,11 @@

      Groups in a netCDF file

      that group. To simplify the creation of nested groups, you can use a unix-like path as an argument to Dataset.createGroup.

      -
      >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
+
      
+
      >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
 >>> fcstgrp2 = rootgrp.createGroup("/forecasts/model2")
-
      
+
      +

      If any of the intermediate elements of the path do not exist, they are created, just as with the unix command 'mkdir -p'. If you try to create a group @@ -668,12 +596,13 @@

      Groups in a netCDF file

      to walk the directory tree. Note that printing the Dataset or Group object yields summary information about it's contents.

      -
      >>> def walktree(top):
+
      
+
      >>> def walktree(top):
 ...     yield top.groups.values()
 ...     for value in top.groups.values():
 ...         yield from walktree(value)
 >>> print(rootgrp)
-<class 'netCDF4._netCDF4.Dataset'>
+<class 'netCDF4.Dataset'>
 root group (NETCDF4 data model, file format HDF5):
     dimensions(sizes): 
     variables(dimensions): 
@@ -681,27 +610,28 @@ 
      Groups in a netCDF file
      
 >>> for children in walktree(rootgrp):
 ...     for child in children:
 ...         print(child)
-<class 'netCDF4._netCDF4.Group'>
+<class 'netCDF4.Group'>
 group /forecasts:
     dimensions(sizes): 
     variables(dimensions): 
     groups: model1, model2
-<class 'netCDF4._netCDF4.Group'>
+<class 'netCDF4.Group'>
 group /analyses:
     dimensions(sizes): 
     variables(dimensions): 
     groups: 
-<class 'netCDF4._netCDF4.Group'>
+<class 'netCDF4.Group'>
 group /forecasts/model1:
     dimensions(sizes): 
     variables(dimensions): 
     groups: 
-<class 'netCDF4._netCDF4.Group'>
+<class 'netCDF4.Group'>
 group /forecasts/model2:
     dimensions(sizes): 
     variables(dimensions): 
     groups: 
-
      
+
      +

      Dimensions in a netCDF file

      @@ -718,42 +648,50 @@

      Dimensions in a netCDF file

      dimension is a new netCDF 4 feature, in netCDF 3 files there may be only one, and it must be the first (leftmost) dimension of the variable.

      -
      >>> level = rootgrp.createDimension("level", None)
+
      
+
      >>> level = rootgrp.createDimension("level", None)
 >>> time = rootgrp.createDimension("time", None)
 >>> lat = rootgrp.createDimension("lat", 73)
 >>> lon = rootgrp.createDimension("lon", 144)
-
      
+
      +

      All of the Dimension instances are stored in a python dictionary.

      -
      >>> print(rootgrp.dimensions)
-{'level': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0, 'time': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0, 'lat': <class 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 73, 'lon': <class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144}
-
      +
      +
      >>> print(rootgrp.dimensions)
+{'level': <class 'netCDF4.Dimension'> (unlimited): name = 'level', size = 0, 'time': <class 'netCDF4.Dimension'> (unlimited): name = 'time', size = 0, 'lat': <class 'netCDF4.Dimension'>: name = 'lat', size = 73, 'lon': <class 'netCDF4.Dimension'>: name = 'lon', size = 144}
+
      +

      Using the python len function with a Dimension instance returns current size of that dimension. Dimension.isunlimited method of a Dimension instance be used to determine if the dimensions is unlimited, or appendable.

      -
      >>> print(len(lon))
+
      
+
      >>> print(len(lon))
 144
 >>> print(lon.isunlimited())
 False
 >>> print(time.isunlimited())
 True
-
      
+
      +

      Printing the Dimension object provides useful summary info, including the name and length of the dimension, and whether it is unlimited.

      -
      >>> for dimobj in rootgrp.dimensions.values():
+
      
+
      >>> for dimobj in rootgrp.dimensions.values():
 ...     print(dimobj)
-<class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0
-<class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0
-<class 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 73
-<class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144
-
      
+<class 'netCDF4.Dimension'> (unlimited): name = 'level', size = 0
+<class 'netCDF4.Dimension'> (unlimited): name = 'time', size = 0
+<class 'netCDF4.Dimension'>: name = 'lat', size = 73
+<class 'netCDF4.Dimension'>: name = 'lon', size = 144
+
      +

      Dimension names can be changed using the Datatset.renameDimension method of a Dataset or @@ -792,79 +730,89 @@

      Variables in a netCDF file

      method returns an instance of the Variable class whose methods can be used later to access and set variable data and attributes.

      -
      >>> times = rootgrp.createVariable("time","f8",("time",))
+
      
+
      >>> times = rootgrp.createVariable("time","f8",("time",))
 >>> levels = rootgrp.createVariable("level","i4",("level",))
 >>> latitudes = rootgrp.createVariable("lat","f4",("lat",))
 >>> longitudes = rootgrp.createVariable("lon","f4",("lon",))
 >>> # two dimensions unlimited
 >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
 >>> temp.units = "K"
-
      
+
      +

      To get summary info on a Variable instance in an interactive session, just print it.

      -
      >>> print(temp)
-<class 'netCDF4._netCDF4.Variable'>
+
      
+
      >>> print(temp)
+<class 'netCDF4.Variable'>
 float32 temp(time, level, lat, lon)
     units: K
 unlimited dimensions: time, level
 current shape = (0, 0, 73, 144)
 filling on, default _FillValue of 9.969209968386869e+36 used
-
      
+
      +

      You can use a path to create a Variable inside a hierarchy of groups.

      -
      >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
-
      +
      +
      >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
+
      +

      If the intermediate groups do not yet exist, they will be created.

      You can also query a Dataset or Group instance directly to obtain Group or Variable instances using paths.

      -
      >>> print(rootgrp["/forecasts/model1"])  # a Group instance
-<class 'netCDF4._netCDF4.Group'>
+
      
+
      >>> print(rootgrp["/forecasts/model1"])  # a Group instance
+<class 'netCDF4.Group'>
 group /forecasts/model1:
     dimensions(sizes): 
     variables(dimensions): float32 temp(time,level,lat,lon)
     groups: 
 >>> print(rootgrp["/forecasts/model1/temp"])  # a Variable instance
-<class 'netCDF4._netCDF4.Variable'>
+<class 'netCDF4.Variable'>
 float32 temp(time, level, lat, lon)
 path = /forecasts/model1
 unlimited dimensions: time, level
 current shape = (0, 0, 73, 144)
 filling on, default _FillValue of 9.969209968386869e+36 used
-
      
+
      +

      All of the variables in the Dataset or Group are stored in a Python dictionary, in the same way as the dimensions:

      -
      >>> print(rootgrp.variables)
-{'time': <class 'netCDF4._netCDF4.Variable'>
+
      
+
      >>> print(rootgrp.variables)
+{'time': <class 'netCDF4.Variable'>
 float64 time(time)
 unlimited dimensions: time
 current shape = (0,)
-filling on, default _FillValue of 9.969209968386869e+36 used, 'level': <class 'netCDF4._netCDF4.Variable'>
+filling on, default _FillValue of 9.969209968386869e+36 used, 'level': <class 'netCDF4.Variable'>
 int32 level(level)
 unlimited dimensions: level
 current shape = (0,)
-filling on, default _FillValue of -2147483647 used, 'lat': <class 'netCDF4._netCDF4.Variable'>
+filling on, default _FillValue of -2147483647 used, 'lat': <class 'netCDF4.Variable'>
 float32 lat(lat)
 unlimited dimensions: 
 current shape = (73,)
-filling on, default _FillValue of 9.969209968386869e+36 used, 'lon': <class 'netCDF4._netCDF4.Variable'>
+filling on, default _FillValue of 9.969209968386869e+36 used, 'lon': <class 'netCDF4.Variable'>
 float32 lon(lon)
 unlimited dimensions: 
 current shape = (144,)
-filling on, default _FillValue of 9.969209968386869e+36 used, 'temp': <class 'netCDF4._netCDF4.Variable'>
+filling on, default _FillValue of 9.969209968386869e+36 used, 'temp': <class 'netCDF4.Variable'>
 float32 temp(time, level, lat, lon)
     units: K
 unlimited dimensions: time, level
 current shape = (0, 0, 73, 144)
 filling on, default _FillValue of 9.969209968386869e+36 used}
-
      
+
      +

      Variable names can be changed using the Dataset.renameVariable method of a Dataset @@ -884,7 +832,8 @@

      Attributes in a netCDF file

      variables. Attributes can be strings, numbers or sequences. Returning to our example,

      -
      >>> import time
+
      
+
      >>> import time
 >>> rootgrp.description = "bogus example script"
 >>> rootgrp.history = "Created " + time.ctime(time.time())
 >>> rootgrp.source = "netCDF4 python module tutorial"
@@ -894,7 +843,8 @@ 
      Attributes in a netCDF file
      
 >>> temp.units = "K"
 >>> times.units = "hours since 0001-01-01 00:00:00.0"
 >>> times.calendar = "gregorian"
-
      
+
      +

      The Dataset.ncattrs method of a Dataset, Group or Variable instance can be used to retrieve the names of all the netCDF @@ -902,20 +852,24 @@

      Attributes in a netCDF file

      built-in dir Python function will return a bunch of private methods and attributes that cannot (or should not) be modified by the user.

      -
      >>> for name in rootgrp.ncattrs():
+
      
+
      >>> for name in rootgrp.ncattrs():
 ...     print("Global attr {} = {}".format(name, getattr(rootgrp, name)))
 Global attr description = bogus example script
 Global attr history = Created Mon Jul  8 14:19:41 2019
 Global attr source = netCDF4 python module tutorial
-
      
+
      +

      The __dict__ attribute of a Dataset, Group or Variable instance provides all the netCDF attribute name/value pairs in a python dictionary:

      -
      >>> print(rootgrp.__dict__)
+
      
+
      >>> print(rootgrp.__dict__)
 {'description': 'bogus example script', 'history': 'Created Mon Jul  8 14:19:41 2019', 'source': 'netCDF4 python module tutorial'}
-
      
+
      +

      Attributes can be deleted from a netCDF Dataset, Group or Variable using the python del statement (i.e. del grp.foo @@ -926,7 +880,8 @@

      Writing data

      Now that you have a netCDF Variable instance, how do you put data into it? You can just treat it like an array and assign data to a slice.

      -
      >>> import numpy as np
+
      
+
      >>> import numpy as np
 >>> lats =  np.arange(-90,91,2.5)
 >>> lons =  np.arange(-180,180,2.5)
 >>> latitudes[:] = lats
@@ -940,13 +895,15 @@ 
      Writing data
   30.   32.5  35.   37.5  40.   42.5  45.   47.5  50.   52.5  55.   57.5
   60.   62.5  65.   67.5  70.   72.5  75.   77.5  80.   82.5  85.   87.5
   90. ]
-
      
+
      +

      Unlike NumPy's array objects, netCDF Variable objects with unlimited dimensions will grow along those dimensions if you assign data outside the currently defined range of indices.

      -
      >>> # append along two unlimited dimensions by assigning to slice.
+
      
+
      >>> # append along two unlimited dimensions by assigning to slice.
 >>> nlats = len(rootgrp.dimensions["lat"])
 >>> nlons = len(rootgrp.dimensions["lon"])
 >>> print("temp shape before adding data = {}".format(temp.shape))
@@ -960,15 +917,18 @@ 
      Writing data
 >>> # levels have grown, but no values yet assigned.
 >>> print("levels shape after adding pressure data = {}".format(levels.shape))
 levels shape after adding pressure data = (10,)
-
      
+
      +

      Note that the size of the levels variable grows when data is appended along the level dimension of the variable temp, even though no data has yet been assigned to levels.

      -
      >>> # now, assign data to levels dimension variable.
+
      
+
      >>> # now, assign data to levels dimension variable.
 >>> levels[:] =  [1000.,850.,700.,500.,300.,250.,200.,150.,100.,50.]
-
      
+
      +

      However, that there are some differences between NumPy and netCDF variable slicing rules. Slices behave as usual, being specified as a @@ -979,9 +939,11 @@

      Writing data allowed, and these indices work independently along each dimension (similar to the way vector subscripts work in fortran). This means that

      -
      >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
+
      
+
      >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
 (4, 4)
-
      
+
      +

      returns an array of shape (4,4) when slicing a netCDF variable, but for a numpy array it returns an array of shape (4,). @@ -997,16 +959,20 @@

      Writing data

      For example,

      -
      >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
-
      +
      +
      >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
+
      +

      will extract time indices 0,2 and 4, pressure levels 850, 500 and 200 hPa, all Northern Hemisphere latitudes and Eastern Hemisphere longitudes, resulting in a numpy array of shape (3, 3, 36, 71).

      -
      >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
+
      
+
      >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
 shape of fancy temp slice = (3, 3, 36, 71)
-
      
+
      +

      Special note for scalar variables: To extract data from a scalar variable v with no associated dimensions, use numpy.asarray(v) or v[...]. @@ -1037,7 +1003,8 @@

      Dealing with time coordinates

      provided by cftime to do just that. Here's an example of how they can be used:

      -
      >>> # fill in times.
+
      
+
      >>> # fill in times.
 >>> from datetime import datetime, timedelta
 >>> from cftime import num2date, date2num
 >>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
@@ -1052,7 +1019,8 @@ 
      Dealing with time coordinates
      
   cftime.DatetimeGregorian(2001, 3, 2, 0, 0, 0, 0, has_year_zero=False)
   cftime.DatetimeGregorian(2001, 3, 2, 12, 0, 0, 0, has_year_zero=False)
   cftime.DatetimeGregorian(2001, 3, 3, 0, 0, 0, 0, has_year_zero=False)]
-
      
+
      +

      num2date converts numeric values of time in the specified units and calendar to datetime objects, and date2num does the reverse. @@ -1077,16 +1045,19 @@

      Reading data from a multi NETCDF4_CLASSIC format (NETCDF4 formatted multi-file datasets are not supported).

      -
      >>> for nf in range(10):
+
      
+
      >>> for nf in range(10):
 ...     with Dataset("mftest%s.nc" % nf, "w", format="NETCDF4_CLASSIC") as f:
 ...         _ = f.createDimension("x",None)
 ...         x = f.createVariable("x","i",("x",))
 ...         x[0:10] = np.arange(nf*10,10*(nf+1))
-
      
+
      +

      Now read all the files back in at once with MFDataset

      -
      >>> from netCDF4 import MFDataset
+
      
+
      >>> from netCDF4 import MFDataset
 >>> f = MFDataset("mftest*nc")
 >>> print(f.variables["x"][:])
 [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
@@ -1094,7 +1065,8 @@ 
      Reading data from a multi
  48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71
  72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
  96 97 98 99]
-
      
+
      +

      Note that MFDataset can only be used to read, not write, multi-file datasets.

      @@ -1153,23 +1125,31 @@

      Efficient compression of netC

      In our example, try replacing the line

      -
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
-
      +
      +
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
+
      +

      with

      -
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib')
-
      +
      +
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib')
+
      +

      and then

      -
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',least_significant_digit=3)
-
      +
      +
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',least_significant_digit=3)
+
      +

      or with netcdf-c >= 4.9.0

      -
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',significant_digits=4)
-
      +
      +
      >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',significant_digits=4)
+
      +

      and see how much smaller the resulting files are.

      @@ -1189,7 +1169,8 @@

      Beyond ho Since there is no native complex data type in netcdf, compound types are handy for storing numpy complex arrays. Here's an example:

      -
      >>> f = Dataset("complex.nc","w")
+
      
+
      >>> f = Dataset("complex.nc","w")
 >>> size = 3 # length of 1-d complex array
 >>> # create sample complex data.
 >>> datac = np.exp(1j*(1.+np.linspace(0, np.pi, size)))
@@ -1215,7 +1196,8 @@ 
      Beyond ho
 >>>
 >>> print('{}: {}'.format(datac2.dtype, datac2)) # data from file
 complex128: [ 0.54030231+0.84147098j -0.84147098+0.54030231j -0.54030231-0.84147098j]
-
      
+
      +

      Compound types can be nested, but you must create the 'inner' ones first. All possible numpy structured arrays cannot be @@ -1225,23 +1207,25 @@

      Beyond ho in a Python dictionary, just like variables and dimensions. As always, printing objects gives useful summary information in an interactive session:

      -
      >>> print(f)
-<class 'netCDF4._netCDF4.Dataset'>
+
      
+
      >>> print(f)
+<class 'netCDF4.Dataset'>
 root group (NETCDF4 data model, file format HDF5):
     dimensions(sizes): x_dim(3)
     variables(dimensions): {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True} cmplx_var(x_dim)
     groups: 
 >>> print(f.variables["cmplx_var"])
-<class 'netCDF4._netCDF4.Variable'>
+<class 'netCDF4.Variable'>
 compound cmplx_var(x_dim)
 compound data type: {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}
 unlimited dimensions: x_dim
 current shape = (3,)
 >>> print(f.cmptypes)
-{'complex128': <class 'netCDF4._netCDF4.CompoundType'>: name = 'complex128', numpy dtype = {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}}
+{'complex128': <class 'netCDF4.CompoundType'>: name = 'complex128', numpy dtype = {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}}
 >>> print(f.cmptypes["complex128"])
-<class 'netCDF4._netCDF4.CompoundType'>: name = 'complex128', numpy dtype = {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}
-
      
+<class 'netCDF4.CompoundType'>: name = 'complex128', numpy dtype = {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}
+
      +

      Variable-length (vlen) data types

      @@ -1250,9 +1234,11 @@

      Variable-length (vlen) data types

      data type, use the Dataset.createVLType method method of a Dataset or Group instance.

      -
      >>> f = Dataset("tst_vlen.nc","w")
+
      
+
      >>> f = Dataset("tst_vlen.nc","w")
 >>> vlen_t = f.createVLType(np.int32, "phony_vlen")
-
      
+
      +

      The numpy datatype of the variable-length sequences and the name of the new datatype must be specified. Any of the primitive datatypes can be @@ -1260,10 +1246,12 @@

      Variable-length (vlen) data types

      but compound data types cannot. A new variable can then be created using this datatype.

      -
      >>> x = f.createDimension("x",3)
+
      
+
      >>> x = f.createDimension("x",3)
 >>> y = f.createDimension("y",4)
 >>> vlvar = f.createVariable("phony_vlen_var", vlen_t, ("y","x"))
-
      
+
      +

      Since there is no native vlen datatype in numpy, vlen arrays are represented in python as object arrays (arrays of dtype object). These are arrays whose @@ -1273,7 +1261,8 @@

      Variable-length (vlen) data types

      In this case, they contain 1-D numpy int32 arrays of random length between 1 and 10.

      -
      >>> import random
+
      
+
      >>> import random
 >>> random.seed(54321)
 >>> data = np.empty(len(y)*len(x),object)
 >>> for n in range(len(y)*len(x)):
@@ -1292,20 +1281,21 @@ 
      Variable-length (vlen) data types
      
  [array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)
   array([1, 2, 3, 4, 5], dtype=int32) array([1, 2], dtype=int32)]]
 >>> print(f)
-<class 'netCDF4._netCDF4.Dataset'>
+<class 'netCDF4.Dataset'>
 root group (NETCDF4 data model, file format HDF5):
     dimensions(sizes): x(3), y(4)
     variables(dimensions): int32 phony_vlen_var(y,x)
     groups: 
 >>> print(f.variables["phony_vlen_var"])
-<class 'netCDF4._netCDF4.Variable'>
+<class 'netCDF4.Variable'>
 vlen phony_vlen_var(y, x)
 vlen data type: int32
 unlimited dimensions: 
 current shape = (4, 3)
 >>> print(f.vltypes["phony_vlen"])
-<class 'netCDF4._netCDF4.VLType'>: name = 'phony_vlen', numpy dtype = int32
-
      
+<class 'netCDF4.VLType'>: name = 'phony_vlen', numpy dtype = int32
+
      +

      Numpy object arrays containing python strings can also be written as vlen variables, For vlen strings, you don't need to create a vlen data type. @@ -1313,15 +1303,18 @@

      Variable-length (vlen) data types

      with fixed length greater than 1) when calling the Dataset.createVariable method.

      -
      >>> z = f.createDimension("z",10)
+
      
+
      >>> z = f.createDimension("z",10)
 >>> strvar = f.createVariable("strvar", str, "z")
-
      
+
      +

      In this example, an object array is filled with random python strings with random lengths between 2 and 12 characters, and the data in the object array is assigned to the vlen string variable.

      -
      >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
+
      
+
      >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
 >>> data = np.empty(10,"O")
 >>> for n in range(10):
 ...     stringlen = random.randint(2,12)
@@ -1332,18 +1325,19 @@ 
      Variable-length (vlen) data types
      
 ['Lh' '25F8wBbMI' '53rmM' 'vvjnb3t63ao' 'qjRBQk6w' 'aJh' 'QF'
  'jtIJbJACaQk4' '3Z5' 'bftIIq']
 >>> print(f)
-<class 'netCDF4._netCDF4.Dataset'>
+<class 'netCDF4.Dataset'>
 root group (NETCDF4 data model, file format HDF5):
     dimensions(sizes): x(3), y(4), z(10)
     variables(dimensions): int32 phony_vlen_var(y,x), <class 'str'> strvar(z)
     groups: 
 >>> print(f.variables["strvar"])
-<class 'netCDF4._netCDF4.Variable'>
+<class 'netCDF4.Variable'>
 vlen strvar(z)
 vlen data type: <class 'str'>
 unlimited dimensions: 
 current shape = (10,)
-
      
+
      +

      It is also possible to set contents of vlen string variables with numpy arrays of any string or unicode data type. Note, however, that accessing the contents @@ -1360,7 +1354,8 @@

      Enum data type

      values and their names are used to define an Enum data type using Dataset.createEnumType.

      -
      >>> nc = Dataset('clouds.nc','w')
+
      
+
      >>> nc = Dataset('clouds.nc','w')
 >>> # python dict with allowed values and their names.
 >>> enum_dict = {'Altocumulus': 7, 'Missing': 255,
 ... 'Stratus': 2, 'Clear': 0,
@@ -1369,8 +1364,9 @@ 
      Enum data type
      
 >>> # create the Enum type called 'cloud_t'.
 >>> cloud_type = nc.createEnumType(np.uint8,'cloud_t',enum_dict)
 >>> print(cloud_type)
-<class 'netCDF4._netCDF4.EnumType'>: name = 'cloud_t', numpy dtype = uint8, fields/values ={'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, 'Stratocumulus': 3}
-
      
+<class 'netCDF4.EnumType'>: name = 'cloud_t', numpy dtype = uint8, fields/values ={'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, 'Stratocumulus': 3}
+
      +

      A new variable can be created in the usual way using this data type. Integer data is written to the variable that represents the named @@ -1378,7 +1374,8 @@

      Enum data type

      is made to write an integer value not associated with one of the specified names.

      -
      >>> time = nc.createDimension('time',None)
+
      
+
      >>> time = nc.createDimension('time',None)
 >>> # create a 1d variable of type 'cloud_type'.
 >>> # The fill_value is set to the 'Missing' named value.
 >>> cloud_var = nc.createVariable('primary_cloud',cloud_type,'time',
@@ -1391,7 +1388,7 @@ 
      Enum data type
      
 >>> nc = Dataset('clouds.nc')
 >>> cloud_var = nc.variables['primary_cloud']
 >>> print(cloud_var)
-<class 'netCDF4._netCDF4.Variable'>
+<class 'netCDF4.Variable'>
 enum primary_cloud(time)
     _FillValue: 255
 enum data type: uint8
@@ -1402,7 +1399,8 @@ 
      Enum data type
      
 >>> print(cloud_var[:])
 [0 2 4 -- 1]
 >>> nc.close()
-
      
+
      +

      Parallel IO

      @@ -1415,11 +1413,13 @@

      Parallel IO

      available. To use parallel IO, your program must be running in an MPI environment using mpi4py.

      -
      >>> from mpi4py import MPI
+
      
+
      >>> from mpi4py import MPI
 >>> import numpy as np
 >>> from netCDF4 import Dataset
 >>> rank = MPI.COMM_WORLD.rank  # The process ID (integer 0-3 for 4-process run)
-
      
+
      +

      To run an MPI-based parallel program like this, you must use mpiexec to launch several parallel instances of Python (for example, using mpiexec -np 4 python mpi_example.py). @@ -1427,15 +1427,18 @@

      Parallel IO

      when a new dataset is created or an existing dataset is opened, use the parallel keyword to enable parallel access.

      -
      >>> nc = Dataset('parallel_test.nc','w',parallel=True)
-
      +
      +
      >>> nc = Dataset('parallel_test.nc','w',parallel=True)
+
      +

      The optional comm keyword may be used to specify a particular MPI communicator (MPI_COMM_WORLD is used by default). Each process (or rank) can now write to the file indepedently. In this example the process rank is written to a different variable index on each task

      -
      >>> d = nc.createDimension('dim',4)
+
      
+
      >>> d = nc.createDimension('dim',4)
 >>> v = nc.createVariable('var', np.int64, 'dim')
 >>> v[rank] = rank
 >>> nc.close()
@@ -1450,7 +1453,8 @@ 
      Parallel IO
      
 
     var = 0, 1, 2, 3 ;
 }
-
      
+
      +

      There are two types of parallel IO, independent (the default) and collective. Independent IO means that each process can do IO independently. It should not @@ -1502,7 +1506,8 @@

      Dealing with strings

      stringtochar is used to convert the numpy string array to an array of characters with one more dimension. For example,

      -
      >>> from netCDF4 import stringtochar
+
      
+
      >>> from netCDF4 import stringtochar
 >>> nc = Dataset('stringtest.nc','w',format='NETCDF4_CLASSIC')
 >>> _ = nc.createDimension('nchars',3)
 >>> _ = nc.createDimension('nstrings',None)
@@ -1517,7 +1522,8 @@ 
      Dealing with strings
      
 >>> print(v[:])  # data returned in numpy string array
 ['foo' 'bar']
 >>> nc.close()
-
      
+
      +

      Even if the _Encoding attribute is set, the automatic conversion of char arrays to/from string arrays can be disabled with @@ -1535,7 +1541,8 @@

      Dealing with strings

      character array dtype under the hood when creating the netcdf compound type. Here's an example:

      -
      >>> nc = Dataset('compoundstring_example.nc','w')
+
      
+
      >>> nc = Dataset('compoundstring_example.nc','w')
 >>> dtype = np.dtype([('observation', 'f4'),
 ...                      ('station_name','S10')])
 >>> station_data_t = nc.createCompoundType(dtype,'station_data')
@@ -1557,7 +1564,8 @@ 
      Dealing with strings
      
 [(123.  , [b'B', b'o', b'u', b'l', b'd', b'e', b'r', b'', b'', b''])
  (  3.14, [b'N', b'e', b'w', b' ', b'Y', b'o', b'r', b'k', b'', b''])]
 >>> nc.close()
-
      
+
      +

      Note that there is currently no support for mapping numpy structured arrays with unicode elements (dtype U#) onto netCDF compound types, nor is there support @@ -1580,14 +1588,15 @@

      In-memory (diskless) Datasets

      object representing the Dataset. Below are examples illustrating both approaches.

      -
      >>> # create a diskless (in-memory) Dataset,
+
      
+
      >>> # create a diskless (in-memory) Dataset,
 >>> # and persist the file to disk when it is closed.
 >>> nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
 >>> d = nc.createDimension('x',None)
 >>> v = nc.createVariable('v',np.int32,'x')
 >>> v[0:5] = np.arange(5)
 >>> print(nc)
-<class 'netCDF4._netCDF4.Dataset'>
+<class 'netCDF4.Dataset'>
 root group (NETCDF4 data model, file format HDF5):
     dimensions(sizes): x(5)
     variables(dimensions): int32 v(x)
@@ -1604,7 +1613,7 @@ 
      In-memory (diskless) Datasets
      
 >>> # create a netCDF in-memory dataset from the bytes object.
 >>> nc = Dataset('inmemory.nc', memory=nc_bytes)
 >>> print(nc)
-<class 'netCDF4._netCDF4.Dataset'>
+<class 'netCDF4.Dataset'>
 root group (NETCDF4 data model, file format HDF5):
     dimensions(sizes): x(5)
     variables(dimensions): int32 v(x)
@@ -1628,7 +1637,7 @@ 
      In-memory (diskless) Datasets
      
 ...     f.write(nc_buf)
 >>> nc = Dataset('inmemory.nc')
 >>> print(nc)
-<class 'netCDF4._netCDF4.Dataset'>
+<class 'netCDF4.Dataset'>
 root group (NETCDF4 data model, file format HDF5):
     dimensions(sizes): x(5)
     variables(dimensions): int32 v(x)
@@ -1636,13 +1645,14 @@ 
      In-memory (diskless) Datasets
      
 >>> print(nc['v'][:])
 [0 1 2 3 4]
 >>> nc.close()
-
      
+
      +

      All of the code in this tutorial is available in examples/tutorial.py, except the parallel IO example, which is in examples/mpi_example.py. Unit tests are in the test directory.

      -

      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov

      +

      contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov

      copyright: 2008 by Jeffrey Whitaker.

      @@ -1653,43 +1663,45 @@

      In-memory (diskless) Datasets

      THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

    -
    - View Source - 
    # init for netCDF4. package
-# Docstring comes from extension module _netCDF4.
-from ._netCDF4 import *
-# Need explicit imports for names beginning with underscores
-from ._netCDF4 import __doc__
-from ._netCDF4 import (__version__, __netcdf4libversion__, __hdf5libversion__,
-                       __has_rename_grp__, __has_nc_inq_path__,
-                       __has_nc_inq_format_extended__, __has_nc_open_mem__,
-                       __has_nc_create_mem__, __has_cdf5_format__,
-                       __has_parallel4_support__, __has_pnetcdf_support__,
-                       __has_quantization_support__, __has_zstandard_support__,
-                       __has_bzip2_support__, __has_blosc_support__, __has_szip_support__)
-import os
-__all__ =\
-['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache','set_alignment','get_alignment']
-# if HDF5_PLUGIN_PATH not set, point to package path if plugins live there
-pluginpath = os.path.join(__path__[0],'plugins')
-if 'HDF5_PLUGIN_PATH' not in os.environ and\
-    (os.path.exists(os.path.join(pluginpath,'lib__nczhdf5filters.so')) or\
-     os.path.exists(os.path.join(pluginpath,'lib__nczhdf5filters.dylib'))):
-    os.environ['HDF5_PLUGIN_PATH']=pluginpath
-
    - -
    + + + + + 
     1# init for netCDF4. package
+ 2# Docstring comes from extension module _netCDF4.
+ 3from ._netCDF4 import *
+ 4# Need explicit imports for names beginning with underscores
+ 5from ._netCDF4 import __doc__
+ 6from ._netCDF4 import (__version__, __netcdf4libversion__, __hdf5libversion__,
+ 7                       __has_rename_grp__, __has_nc_inq_path__,
+ 8                       __has_nc_inq_format_extended__, __has_nc_open_mem__,
+ 9                       __has_nc_create_mem__, __has_cdf5_format__,
+10                       __has_parallel4_support__, __has_pnetcdf_support__,
+11                       __has_quantization_support__, __has_zstandard_support__,
+12                       __has_bzip2_support__, __has_blosc_support__, __has_szip_support__,
+13                       __has_set_alignment__)
+14import os
+15__all__ =\
+16['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache','set_alignment','get_alignment']
+17# if HDF5_PLUGIN_PATH not set, point to package path if plugins live there
+18pluginpath = os.path.join(__path__[0],'plugins')
+19if 'HDF5_PLUGIN_PATH' not in os.environ and\
+20    (os.path.exists(os.path.join(pluginpath,'lib__nczhdf5filters.so')) or\
+21     os.path.exists(os.path.join(pluginpath,'lib__nczhdf5filters.dylib'))):
+22    os.environ['HDF5_PLUGIN_PATH']=pluginpath
+
    +
    -
    - #   +
    + + class + Dataset: - class - Dataset:
    - +

    A netCDF Dataset is a collection of dimensions, groups, variables and attributes. Together they describe the meaning of data and relations among @@ -1707,53 +1719,53 @@

    In-memory (diskless) Datasets

    The following class variables are read-only and should not be modified by the user.

    -

    dimensions: The dimensions dictionary maps the names of +

    dimensions: The dimensions dictionary maps the names of dimensions defined for the Group or Dataset to instances of the Dimension class.

    -

    variables: The variables dictionary maps the names of variables +

    variables: The variables dictionary maps the names of variables defined for this Dataset or Group to instances of the Variable class.

    -

    groups: The groups dictionary maps the names of groups created for +

    groups: The groups dictionary maps the names of groups created for this Dataset or Group to instances of the Group class (the Dataset class is simply a special case of the Group class which describes the root group in the netCDF4 file).

    -

    cmptypes: The cmptypes dictionary maps the names of +

    cmptypes: The cmptypes dictionary maps the names of compound types defined for the Group or Dataset to instances of the CompoundType class.

    -

    vltypes: The vltypes dictionary maps the names of +

    vltypes: The vltypes dictionary maps the names of variable-length types defined for the Group or Dataset to instances of the VLType class.

    -

    enumtypes: The enumtypes dictionary maps the names of +

    enumtypes: The enumtypes dictionary maps the names of Enum types defined for the Group or Dataset to instances of the EnumType class.

    -

    data_model: data_model describes the netCDF +

    data_model: data_model describes the netCDF data model version, one of NETCDF3_CLASSIC, NETCDF4, NETCDF4_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.

    -

    file_format: same as data_model, retained for backwards compatibility.

    +

    file_format: same as data_model, retained for backwards compatibility.

    -

    disk_format: disk_format describes the underlying +

    disk_format: disk_format describes the underlying file format, one of NETCDF3, HDF5, HDF4, PNETCDF, DAP2, DAP4 or UNDEFINED. Only available if using netcdf C library version >= 4.3.1, otherwise will always return UNDEFINED.

    -

    parent: parent is a reference to the parent +

    parent: parent is a reference to the parent Group instance. None for the root group or Dataset instance.

    -

    path: path shows the location of the Group in +

    path: path shows the location of the Group in the Dataset in a unix directory format (the names of groups in the hierarchy separated by backslashes). A Dataset instance is the root group, so the path is simply '/'.

    -

    keepweakref: If True, child Dimension and Variables objects only keep weak +

    keepweakref: If True, child Dimension and Variables objects only keep weak references to the parent Dataset or Group.

    _ncstring_attrs__: If True, all text attributes will be written as variable-length @@ -1762,12 +1774,13 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + Dataset() - Dataset()
    - +

    __init__(self, filename, mode="r", clobber=True, diskless=False, persist=False, keepweakref=False, memory=None, encoding=None, @@ -1824,7 +1837,7 @@

    In-memory (diskless) Datasets

    persist: if diskless=True, persist file to disk when closed (default False).

    -

    keepweakref: if True, child Dimension and Variable instances will keep weak +

    keepweakref: if True, child Dimension and Variable instances will keep weak references to the parent Dataset or Group object. Default is False, which means strong references will be kept. Having Dimension and Variable instances keep a strong reference to the parent Dataset instance, which in turn keeps a @@ -1867,13 +1880,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + filepath(unknown): - def - filepath(unknown):
    - +

    filepath(self,encoding=None)

    @@ -1886,13 +1900,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + close(unknown): - def - close(unknown):
    - +

    close(self)

    @@ -1902,13 +1917,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + isopen(unknown): - def - isopen(unknown):
    - +

    isopen(self)

    @@ -1918,13 +1934,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + sync(unknown): - def - sync(unknown):
    - +

    sync(self)

    @@ -1934,13 +1951,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + set_fill_on(unknown): - def - set_fill_on(unknown):
    - +

    set_fill_on(self)

    @@ -1958,13 +1976,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + set_fill_off(unknown): - def - set_fill_off(unknown):
    - +

    set_fill_off(self)

    @@ -1978,13 +1997,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + createDimension(unknown): - def - createDimension(unknown):
    - +

    createDimension(self, dimname, size=None)

    @@ -2002,13 +2022,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + renameDimension(unknown): - def - renameDimension(unknown):
    - +

    renameDimension(self, oldname, newname)

    @@ -2018,13 +2039,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + createCompoundType(unknown): - def - createCompoundType(unknown):
    - +

    createCompoundType(self, datatype, datatype_name)

    @@ -2043,13 +2065,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + createVLType(unknown): - def - createVLType(unknown):
    - +

    createVLType(self, datatype, datatype_name)

    @@ -2063,13 +2086,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + createEnumType(unknown): - def - createEnumType(unknown):
    - +

    createEnumType(self, datatype, datatype_name, enum_dict)

    @@ -2084,13 +2108,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + createVariable(unknown): - def - createVariable(unknown):
    - +

    createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, @@ -2099,7 +2124,7 @@

    In-memory (diskless) Datasets

    fill_value=None, chunk_cache=None)

    Creates a new variable with the given varname, datatype, and -dimensions. If dimensions are not given, the variable is assumed to be +dimensions. If dimensions are not given, the variable is assumed to be a scalar.

    If varname is specified as a path, using forward slashes as in unix to @@ -2123,7 +2148,7 @@

    In-memory (diskless) Datasets

    Data from netCDF variables is presented to python as numpy arrays with the corresponding data type.

    -

    dimensions must be a tuple containing Dimension instances and/or +

    dimensions must be a tuple containing Dimension instances and/or dimension names (strings) that have been defined previously using Dataset.createDimension. The default value is an empty tuple, which means the variable is a scalar.

    @@ -2231,7 +2256,7 @@

    In-memory (diskless) Datasets

    operations on the Variable instance. A Variable instance has six Dataset standard attributes: dimensions, dtype, shape, ndim, name and least_significant_digit. Application programs should never modify -these attributes. The dimensions attribute is a tuple containing the +these attributes. The dimensions attribute is a tuple containing the names of the dimensions associated with this variable. The dtype attribute is a string describing the variable's data type (i4, f8, S1, etc). The shape attribute is a tuple describing the current @@ -2247,13 +2272,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + renameVariable(unknown): - def - renameVariable(unknown):
    - +

    renameVariable(self, oldname, newname)

    @@ -2263,13 +2289,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + createGroup(unknown): - def - createGroup(unknown):
    - +

    createGroup(self, groupname)

    @@ -2289,13 +2316,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + ncattrs(unknown): - def - ncattrs(unknown):
    - +

    ncattrs(self)

    @@ -2305,13 +2333,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + setncattr(unknown): - def - setncattr(unknown):
    - +

    setncattr(self,name,value)

    @@ -2323,13 +2352,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + setncattr_string(unknown): - def - setncattr_string(unknown):
    - +

    setncattr_string(self,name,value)

    @@ -2341,13 +2371,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + setncatts(unknown): - def - setncatts(unknown):
    - +

    setncatts(self,attdict)

    @@ -2360,13 +2391,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + getncattr(unknown): - def - getncattr(unknown):
    - +

    getncattr(self,name)

    @@ -2381,13 +2413,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + delncattr(unknown): - def - delncattr(unknown):
    - +

    delncattr(self,name,value)

    @@ -2399,13 +2432,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + renameAttribute(unknown): - def - renameAttribute(unknown):
    - +

    renameAttribute(self, oldname, newname)

    @@ -2415,13 +2449,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + renameGroup(unknown): - def - renameGroup(unknown):
    - +

    renameGroup(self, oldname, newname)

    @@ -2431,13 +2466,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + set_auto_chartostring(unknown): - def - set_auto_chartostring(unknown):
    - +

    set_auto_chartostring(self, True_or_False)

    @@ -2456,13 +2492,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + set_auto_maskandscale(unknown): - def - set_auto_maskandscale(unknown):
    - +

    set_auto_maskandscale(self, True_or_False)

    @@ -2479,13 +2516,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + set_auto_mask(unknown): - def - set_auto_mask(unknown):
    - +

    set_auto_mask(self, True_or_False)

    @@ -2503,13 +2541,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + set_auto_scale(unknown): - def - set_auto_scale(unknown):
    - +

    set_auto_scale(self, True_or_False)

    @@ -2526,13 +2565,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + set_always_mask(unknown): - def - set_always_mask(unknown):
    - +

    set_always_mask(self, True_or_False)

    @@ -2554,13 +2594,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + set_ncstring_attrs(unknown): - def - set_ncstring_attrs(unknown):
    - +

    set_ncstring_attrs(self, True_or_False)

    @@ -2579,13 +2620,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + get_variables_by_attributes(unknown): - def - get_variables_by_attributes(unknown):
    - +

    get_variables_by_attribute(self, **kwargs)

    @@ -2594,36 +2636,41 @@

    In-memory (diskless) Datasets

    Can pass in key=value parameters and variables are returned that contain all of the matches. For example,

    -
    >>> # Get variables with x-axis attribute.
+
    
+
    >>> # Get variables with x-axis attribute.
 >>> vs = nc.get_variables_by_attributes(axis='X')
 >>> # Get variables with matching "standard_name" attribute
 >>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
-
    
+
    +

    Can pass in key=callable parameter and variables are returned if the callable returns True. The callable should accept a single parameter, the attribute value. None is given as the attribute value when the attribute does not exist on the variable. For example,

    -
    >>> # Get Axis variables
+
    
+
    >>> # Get Axis variables
 >>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
 >>> # Get variables that don't have an "axis" attribute
 >>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
 >>> # Get variables that have a "grid_mapping" attribute
 >>> vs = nc.get_variables_by_attributes(grid_mapping=lambda v: v is not None)
-
    
+
    +
    -
    #   +
    + + def + fromcdl(unknown): - def - fromcdl(unknown):
    - +

    fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')

    @@ -2647,13 +2694,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + tocdl(unknown): - def - tocdl(unknown):
    - +

    tocdl(self, coordvars=False, data=False, outfile=None)

    @@ -2671,13 +2719,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + has_blosc_filter(unknown): - def - has_blosc_filter(unknown):
    - +

    has_blosc_filter(self) returns True if blosc compression filter is available

    @@ -2686,13 +2735,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + has_zstd_filter(unknown): - def - has_zstd_filter(unknown):
    - +

    has_zstd_filter(self) returns True if zstd compression filter is available

    @@ -2701,13 +2751,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + has_bzip2_filter(unknown): - def - has_bzip2_filter(unknown):
    - +

    has_bzip2_filter(self) returns True if bzip2 compression filter is available

    @@ -2716,13 +2767,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + has_szip_filter(unknown): - def - has_szip_filter(unknown):
    - +

    has_szip_filter(self) returns True if szip compression filter is available

    @@ -2731,147 +2783,28 @@

    In-memory (diskless) Datasets

    -
    #   +
    + name - name +
    - +

    string name of Group instance

    -
    -
    -
    #   - - groups -
    - - - - -
    -
    -
    #   - - dimensions -
    - - - - -
    -
    -
    #   - - variables -
    - - - - -
    -
    -
    #   - - disk_format -
    - - - - -
    -
    -
    #   - - path -
    - - - - -
    -
    -
    #   - - parent -
    - - - - -
    -
    -
    #   - - file_format -
    - - - - -
    -
    -
    #   - - data_model -
    - - - - -
    -
    -
    #   - - cmptypes -
    - - - - -
    -
    -
    #   - - vltypes -
    - - - - -
    -
    -
    #   - - enumtypes -
    - - - - -
    -
    -
    #   - - keepweakref -
    - - - -
    -
    - #   +
    + + class + Variable: - class - Variable:
    - +

    A netCDF Variable is used to read and write netCDF data. They are analogous to numpy array objects. See Variable.__init__ for more @@ -2889,26 +2822,26 @@

    In-memory (diskless) Datasets

    dimensions: A tuple containing the names of the dimensions associated with this variable.

    -

    dtype: A numpy dtype object describing the +

    dtype: A numpy dtype object describing the variable's data type.

    -

    ndim: The number of variable dimensions.

    +

    ndim: The number of variable dimensions.

    shape: A tuple with the current shape (length of all dimensions).

    -

    scale: If True, scale_factor and add_offset are +

    scale: If True, scale_factor and add_offset are applied, and signed integer data is automatically converted to -unsigned integer data if the _Unsigned attribute is set. +unsigned integer data if the _Unsigned attribute is set to "true" or "True". Default is True, can be reset using Variable.set_auto_scale and Variable.set_auto_maskandscale methods.

    -

    mask: If True, data is automatically converted to/from masked +

    mask: If True, data is automatically converted to/from masked arrays when missing values or fill values are present. Default is True, can be reset using Variable.set_auto_mask and Variable.set_auto_maskandscale methods. Only relevant for Variables with primitive or enum types (ignored for compound and vlen Variables).

    -

    chartostring: If True, data is automatically converted to/from character +

    chartostring: If True, data is automatically converted to/from character arrays to string arrays when the _Encoding variable attribute is set. Default is True, can be reset using Variable.set_auto_chartostring method.

    @@ -2950,12 +2883,13 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + Variable() - Variable()
    - +

    __init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False, complevel=4, shuffle=True, szip_coding='nn', szip_pixels_per_block=8, @@ -3091,13 +3025,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + group(unknown): - def - group(unknown):
    - +

    group(self)

    @@ -3107,13 +3042,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + ncattrs(unknown): - def - ncattrs(unknown):
    - +

    ncattrs(self)

    @@ -3123,13 +3059,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + setncattr(unknown): - def - setncattr(unknown):
    - +

    setncattr(self,name,value)

    @@ -3141,13 +3078,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + setncattr_string(unknown): - def - setncattr_string(unknown):
    - +

    setncattr_string(self,name,value)

    @@ -3160,13 +3098,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + setncatts(unknown): - def - setncatts(unknown):
    - +

    setncatts(self,attdict)

    @@ -3179,13 +3118,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + getncattr(unknown): - def - getncattr(unknown):
    - +

    getncattr(self,name)

    @@ -3200,13 +3140,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + delncattr(unknown): - def - delncattr(unknown):
    - +

    delncattr(self,name,value)

    @@ -3218,13 +3159,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + filters(unknown): - def - filters(unknown):
    - +

    filters(self)

    @@ -3234,13 +3176,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + quantization(unknown): - def - quantization(unknown):
    - +

    quantization(self)

    @@ -3251,13 +3194,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + endian(unknown): - def - endian(unknown):
    - +

    endian(self)

    @@ -3267,13 +3211,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + chunking(unknown): - def - chunking(unknown):
    - +

    chunking(self)

    @@ -3286,13 +3231,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + get_var_chunk_cache(unknown): - def - get_var_chunk_cache(unknown):
    - +

    get_var_chunk_cache(self)

    @@ -3304,13 +3250,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + set_var_chunk_cache(unknown): - def - set_var_chunk_cache(unknown):
    - +

    set_var_chunk_cache(self,size=None,nelems=None,preemption=None)

    @@ -3322,13 +3269,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + renameAttribute(unknown): - def - renameAttribute(unknown):
    - +

    renameAttribute(self, oldname, newname)

    @@ -3338,13 +3286,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + assignValue(unknown): - def - assignValue(unknown):
    - +

    assignValue(self, val)

    @@ -3355,13 +3304,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + getValue(unknown): - def - getValue(unknown):
    - +

    getValue(self)

    @@ -3372,13 +3322,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + set_auto_chartostring(unknown): - def - set_auto_chartostring(unknown):
    - +

    set_auto_chartostring(self,chartostring)

    @@ -3386,7 +3337,7 @@

    In-memory (diskless) Datasets

    from numpy fixed length string arrays when the _Encoding variable attribute is set.

    -

    If chartostring is set to True, when data is read from a character variable +

    If chartostring is set to True, when data is read from a character variable (dtype = S1) that has an _Encoding attribute, it is converted to a numpy fixed length unicode string array (dtype = UN, where N is the length of the the rightmost dimension of the variable). The value of _Encoding @@ -3396,20 +3347,21 @@

    In-memory (diskless) Datasets

    indiviual bytes, with the number of bytes in each string equalling the rightmost dimension of the variable.

    -

    The default value of chartostring is True +

    The default value of chartostring is True (automatic conversions are performed).

    -
    #   +
    + + def + use_nc_get_vars(unknown): - def - use_nc_get_vars(unknown):
    - +

    use_nc_get_vars(self,_use_get_vars)

    @@ -3423,13 +3375,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + set_auto_maskandscale(unknown): - def - set_auto_maskandscale(unknown):
    - +

    set_auto_maskandscale(self,maskandscale)

    @@ -3437,7 +3390,7 @@

    In-memory (diskless) Datasets

    from masked arrays, automatic packing/unpacking of variable data using scale_factor and add_offset attributes and automatic conversion of signed integer data to unsigned integer -data if the _Unsigned attribute exists.

    +data if the _Unsigned attribute exists and is set to "true" (or "True").

    If maskandscale is set to True, when data is read from a variable it is converted to a masked array if any of the values are exactly @@ -3474,7 +3427,7 @@

    In-memory (diskless) Datasets

    PSL metadata conventions.

    In addition, if maskandscale is set to True, and if the variable has an -attribute _Unsigned set, and the variable has a signed integer data type, +attribute _Unsigned set to "true", and the variable has a signed integer data type, a view to the data is returned with the corresponding unsigned integer data type. This convention is used by the netcdf-java library to save unsigned integer data in NETCDF3 or NETCDF4_CLASSIC files (since the NETCDF3 @@ -3487,13 +3440,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + set_auto_scale(unknown): - def - set_auto_scale(unknown):
    - +

    set_auto_scale(self,scale)

    @@ -3501,9 +3455,9 @@

    In-memory (diskless) Datasets

    data using scale_factor and add_offset attributes. Also turns on and off automatic conversion of signed integer data to unsigned integer data if the variable has an _Unsigned -attribute.

    +attribute set to "true" or "True".

    -

    If scale is set to True, and the variable has a +

    If scale is set to True, and the variable has a scale_factor or an add_offset attribute, then data read from that variable is unpacked using::

    @@ -3522,34 +3476,35 @@

    In-memory (diskless) Datasets

    used to provide simple compression, see the PSL metadata conventions.

    -

    In addition, if scale is set to True, and if the variable has an -attribute _Unsigned set, and the variable has a signed integer data type, +

    In addition, if scale is set to True, and if the variable has an +attribute _Unsigned set to "true", and the variable has a signed integer data type, a view to the data is returned with the corresponding unsigned integer datatype. This convention is used by the netcdf-java library to save unsigned integer data in NETCDF3 or NETCDF4_CLASSIC files (since the NETCDF3 data model does not have unsigned integer data types).

    -

    The default value of scale is True +

    The default value of scale is True (automatic conversions are performed).

    -
    #   +
    + + def + set_auto_mask(unknown): - def - set_auto_mask(unknown):
    - +

    set_auto_mask(self,mask)

    turn on or off automatic conversion of variable data to and from masked arrays .

    -

    If mask is set to True, when data is read from a variable +

    If mask is set to True, when data is read from a variable it is converted to a masked array if any of the values are exactly equal to the either the netCDF _FillValue or the value specified by the missing_value variable attribute. The fill_value of the masked array @@ -3564,27 +3519,28 @@

    In-memory (diskless) Datasets

    exists). If the variable has no missing_value attribute, the _FillValue is used instead.

    -

    The default value of mask is True +

    The default value of mask is True (automatic conversions are performed).

    -
    #   +
    + + def + set_always_mask(unknown): - def - set_always_mask(unknown):
    - +

    set_always_mask(self,always_mask)

    turn on or off conversion of data without missing values to regular numpy arrays.

    -

    always_mask is a Boolean determining if automatic conversion of +

    always_mask is a Boolean determining if automatic conversion of masked arrays with no missing values to regular numpy arrays shall be applied. Default is True. Set to False to restore the default behaviour in versions prior to 1.4.1 (numpy array returned unless missing values are present, @@ -3594,13 +3550,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + set_ncstring_attrs(unknown): - def - set_ncstring_attrs(unknown):
    - +

    set_always_mask(self,ncstring_attrs)

    @@ -3616,13 +3573,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + set_collective(unknown): - def - set_collective(unknown):
    - +

    set_collective(self,True_or_False)

    @@ -3633,13 +3591,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + get_dims(unknown): - def - get_dims(unknown):
    - +

    get_dims(self)

    @@ -3650,11 +3609,12 @@

    In-memory (diskless) Datasets

    -
    #   +
    + name - name +
    - +

    string name of Variable instance

    @@ -3662,11 +3622,12 @@

    In-memory (diskless) Datasets

    -
    #   +
    + datatype - datatype +
    - +

    numpy data type (for primitive data types) or VLType/CompoundType/EnumType instance @@ -3676,11 +3637,12 @@

    In-memory (diskless) Datasets

    -
    #   +
    + shape - shape +
    - +

    find current sizes of all variable dimensions

    @@ -3688,11 +3650,12 @@

    In-memory (diskless) Datasets

    -
    #   +
    + size - size +
    - +

    Return the number of stored elements.

    @@ -3700,87 +3663,28 @@

    In-memory (diskless) Datasets

    -
    #   +
    + dimensions - dimensions +
    - +

    get variables's dimension names

    -
    -
    -
    #   - - ndim -
    - - - - -
    -
    -
    #   - - dtype -
    - - - - -
    -
    -
    #   - - mask -
    - - - - -
    -
    -
    #   - - scale -
    - - - - -
    -
    -
    #   - - always_mask -
    - - - - -
    -
    -
    #   - - chartostring -
    - - - -
    -
    - #   +
    + + class + Dimension: - class - Dimension:
    - +

    A netCDF Dimension is used to describe the coordinates of a Variable. See Dimension.__init__ for more details.

    @@ -3801,12 +3705,13 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + Dimension() - Dimension()
    - +

    __init__(self, group, name, size=None)

    @@ -3826,13 +3731,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + group(unknown): - def - group(unknown):
    - +

    group(self)

    @@ -3842,13 +3748,14 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + isunlimited(unknown): - def - isunlimited(unknown):
    - +

    isunlimited(self)

    @@ -3858,11 +3765,12 @@

    In-memory (diskless) Datasets

    -
    #   +
    + name - name +
    - +

    string name of Dimension instance

    @@ -3870,11 +3778,12 @@

    In-memory (diskless) Datasets

    -
    #   +
    + size - size +
    - +

    current size of Dimension (calls len on Dimension instance)

    @@ -3883,14 +3792,14 @@

    In-memory (diskless) Datasets

    -
    - #   +
    + + class + Group(netCDF4.Dataset): - class - Group(netCDF4.Dataset):
    - +

    Groups define a hierarchical namespace within a netCDF file. They are analogous to directories in a unix filesystem. Each Group behaves like @@ -3909,17 +3818,18 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + Group() - Group()
    - +

    __init__(self, parent, name) Group constructor.

    -

    parent: Group instance for the parent group. If being created +

    parent: Group instance for the parent group. If being created in the root group, use a Dataset instance.

    name: - Name of the group.

    @@ -3932,18 +3842,19 @@

    In-memory (diskless) Datasets

    -
    #   +
    + + def + close(unknown): - def - close(unknown):
    - +

    close(self)

    overrides Dataset close method which does not apply to Group -instances, raises IOError.

    +instances, raises OSError.

    @@ -3987,32 +3898,20 @@
    Inherited Members
    has_bzip2_filter
    has_szip_filter
    name
    -
    groups
    -
    dimensions
    -
    variables
    -
    disk_format
    -
    path
    -
    parent
    -
    file_format
    -
    data_model
    -
    cmptypes
    -
    vltypes
    -
    enumtypes
    -
    keepweakref
    -
    - #   +
    + + class + MFDataset(netCDF4.Dataset): - class - MFDataset(netCDF4.Dataset):
    - +

    Class for reading multi-file netCDF Datasets, making variables spanning multiple files appear as if they were in one file. @@ -4023,7 +3922,8 @@

    Inherited Members

    Example usage (See MFDataset.__init__ for more details):

    -
    >>> import numpy as np
+
    
+
    >>> import numpy as np
 >>> # create a series of netCDF files with a variable sharing
 >>> # the same unlimited dimension.
 >>> for nf in range(10):
@@ -4039,17 +3939,19 @@ 
    Inherited Members
    
  48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71
  72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
  96 97 98 99]
-
    
+
    +
    -
    #   +
    + + MFDataset(files, check=False, aggdim=None, exclude=[], master_file=None) - MFDataset(files, check=False, aggdim=None, exclude=[], master_file=None)
    - +

    __init__(self, files, check=False, aggdim=None, exclude=[], master_file=None)

    @@ -4088,13 +3990,14 @@
    Inherited Members
    -
    #   +
    + + def + ncattrs(self): - def - ncattrs(self):
    - +

    ncattrs(self)

    @@ -4104,13 +4007,14 @@
    Inherited Members
    -
    #   +
    + + def + close(self): - def - close(self):
    - +

    close(self)

    @@ -4157,39 +4061,28 @@
    Inherited Members
    has_bzip2_filter
    has_szip_filter
    name
    -
    groups
    -
    dimensions
    -
    variables
    -
    disk_format
    -
    path
    -
    parent
    -
    file_format
    -
    data_model
    -
    cmptypes
    -
    vltypes
    -
    enumtypes
    -
    keepweakref
    -
    - #   +
    + + class + MFTime(netCDF4._netCDF4._Variable): - class - MFTime(netCDF4._netCDF4._Variable):
    - +

    Class providing an interface to a MFDataset time Variable by imposing a unique common time unit and/or calendar to all files.

    Example usage (See MFTime.__init__ for more details):

    -
    >>> import numpy as np
+
    
+
    >>> import numpy as np
 >>> f1 = Dataset("mftest_1.nc","w", format="NETCDF4_CLASSIC")
 >>> f2 = Dataset("mftest_2.nc","w", format="NETCDF4_CLASSIC")
 >>> f1.createDimension("time",None)
@@ -4214,17 +4107,19 @@ 
    Inherited Members
    
 >>> T = MFTime(t)
 >>> print(T[32])
 32
-
    
+
    +
    -
    #   +
    + + MFTime(time, units=None, calendar=None) - MFTime(time, units=None, calendar=None)
    - +

    __init__(self, time, units=None, calendar=None)

    @@ -4261,14 +4156,14 @@
    Inherited Members
    -
    - #   +
    + + class + CompoundType: - class - CompoundType:
    - +

    A CompoundType instance is used to describe a compound data type, and can be passed to the the Dataset.createVariable method of @@ -4276,18 +4171,19 @@

    Inherited Members
    Compound data types map to numpy structured arrays. See CompoundType.__init__ for more details.

    -

    The instance variables dtype and name should not be modified by +

    The instance variables dtype and name should not be modified by the user.

    -
    #   +
    + + CompoundType() - CompoundType()
    - +

    __init__(group, datatype, datatype_name)

    @@ -4313,65 +4209,36 @@
    Inherited Members
    -
    -
    -
    #   - - dtype -
    - - - - -
    -
    -
    #   - - dtype_view -
    - - - - -
    -
    -
    #   - - name -
    - - - -
    -
    - #   +
    + + class + VLType: - class - VLType:
    - +

    A VLType instance is used to describe a variable length (VLEN) data type, and can be passed to the the Dataset.createVariable method of a Dataset or Group instance. See VLType.__init__ for more details.

    -

    The instance variables dtype and name should not be modified by +

    The instance variables dtype and name should not be modified by the user.

    -
    #   +
    + + VLType() - VLType()
    - +

    __init__(group, datatype, datatype_name)

    @@ -4391,36 +4258,17 @@
    Inherited Members
    -
    -
    -
    #   - - dtype -
    - - - - -
    -
    -
    #   - - name -
    - - - -
    -
    #   +
    + + def + date2num(unknown): - def - date2num(unknown):
    - +

    date2num(dates, units, calendar=None, has_year_zero=None, longdouble=False)

    @@ -4444,7 +4292,7 @@
    Inherited Members

    calendar: describes the calendar to be used in the time calculations. All the values currently defined in the -CF metadata convention <http://cfconventions.org/cf-conventions/cf-conventions#calendar>__ are supported. +CF metadata convention _ are supported. Valid calendars 'standard', 'gregorian', 'proleptic_gregorian' 'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'. Default is None which means the calendar associated with the first @@ -4480,13 +4328,14 @@

    Inherited Members
    -
    #   +
    + + def + num2date(unknown): - def - num2date(unknown):
    - +

    num2date(times, units, calendar=u'standard', only_use_cftime_datetimes=True, only_use_python_datetimes=False, has_year_zero=None)

    @@ -4506,7 +4355,7 @@
    Inherited Members

    calendar: describes the calendar used in the time calculations. All the values currently defined in the -CF metadata convention <http://cfconventions.org/cf-conventions/cf-conventions#calendar>__ are supported. +CF metadata convention _ are supported. Valid calendars 'standard', 'gregorian', 'proleptic_gregorian' 'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'. Default is 'standard', which is a mixed Julian/Gregorian calendar.

    @@ -4552,13 +4401,14 @@
    Inherited Members
    -
    #   +
    + + def + date2index(unknown): - def - date2index(unknown):
    - +

    date2index(dates, nctime, calendar=None, select=u'exact', has_year_zero=None)

    @@ -4572,7 +4422,7 @@
    Inherited Members

    calendar: describes the calendar to be used in the time calculations. All the values currently defined in the -CF metadata convention <http://cfconventions.org/cf-conventions/cf-conventions#calendar>__ are supported. +CF metadata convention _ are supported. Valid calendars 'standard', 'gregorian', 'proleptic_gregorian' 'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'. Default is None which means the calendar associated with the first @@ -4606,13 +4456,14 @@

    Inherited Members
    -
    #   +
    + + def + stringtochar(unknown): - def - stringtochar(unknown):
    - +

    stringtochar(a,encoding='utf-8')

    @@ -4633,13 +4484,14 @@
    Inherited Members
    -
    #   +
    + + def + chartostring(unknown): - def - chartostring(unknown):
    - +

    chartostring(b,encoding='utf-8')

    @@ -4660,13 +4512,14 @@
    Inherited Members
    -
    #   +
    + + def + stringtoarr(unknown): - def - stringtoarr(unknown):
    - +

    stringtoarr(a, NUMCHARS,dtype='S')

    @@ -4688,13 +4541,14 @@
    Inherited Members
    -
    #   +
    + + def + getlibversion(unknown): - def - getlibversion(unknown):
    - +

    getlibversion()

    @@ -4705,32 +4559,33 @@
    Inherited Members
    -
    - #   +
    + + class + EnumType: - class - EnumType:
    - +

    A EnumType instance is used to describe an Enum data type, and can be passed to the the Dataset.createVariable method of a Dataset or Group instance. See EnumType.__init__ for more details.

    -

    The instance variables dtype, name and enum_dict should not be modified by +

    The instance variables dtype, name and enum_dict should not be modified by the user.

    -
    #   +
    + + EnumType() - EnumType()
    - +

    __init__(group, datatype, datatype_name, enum_dict)

    @@ -4744,7 +4599,7 @@
    Inherited Members

    datatype_name: a Python string containing a description of the Enum data type.

    -

    enum_dict: a Python dictionary containing the Enum field/value +

    enum_dict: a Python dictionary containing the Enum field/value pairs.

    Note: EnumType instances should be created using the @@ -4753,46 +4608,17 @@

    Inherited Members
    -
    -
    -
    #   - - dtype -
    - - - - -
    -
    -
    #   - - name -
    - - - - -
    -
    -
    #   - - enum_dict -
    - - - -
    -
    #   +
    + + def + get_chunk_cache(unknown): - def - get_chunk_cache(unknown):
    - +

    get_chunk_cache()

    @@ -4804,13 +4630,14 @@
    Inherited Members
    -
    #   +
    + + def + set_chunk_cache(unknown): - def - set_chunk_cache(unknown):
    - +

    set_chunk_cache(self,size=None,nelems=None,preemption=None)

    @@ -4822,46 +4649,31 @@
    Inherited Members
    -
    #   +
    + + def + set_alignment(unknown): - def - set_alignment(unknown):
    - + + -

    set_alignment(threshold,alignment)

    - -

    Change the HDF5 file alignment. -See netcdf C library documentation for nc_set_alignment for -details.

    - -

    This function was added in netcdf 4.9.0.

    -
    -
    -
    #   +
    + + def + get_alignment(unknown): - def - get_alignment(unknown):
    - + + -

    get_alignment()

    - -

    return current netCDF alignment within HDF5 files in a tuple -(threshold,alignment). See netcdf C library documentation for -nc_get_alignment for details. Values can be reset with -set_alignment.

    - -

    This function was added in netcdf 4.9.0.

    -
    -
    - + \ No newline at end of file From 52d777aa30863d4cfc5b893813cd7bc85df99416 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Wed, 1 Mar 2023 19:48:05 -0700 Subject: [PATCH 0964/1504] use python 3.11 instead of 3.10 --- .github/workflows/build_latest.yml | 2 +- .github/workflows/build_master.yml | 2 +- .github/workflows/build_old.yml | 2 +- .github/workflows/miniconda.yml | 2 +- 4 files changed, 4 insertions(+), 4 deletions(-) diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml index d0c82a926..f7798b255 100644 --- a/.github/workflows/build_latest.yml +++ b/.github/workflows/build_latest.yml @@ -13,7 +13,7 @@ jobs: #NO_NET: 1 strategy: matrix: - python-version: ["3.10"] + python-version: ["3.11"] steps: - uses: actions/checkout@v2 diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index 1749d9585..c422152e0 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -10,7 +10,7 @@ jobs: #NO_NET: 1 strategy: matrix: - python-version: ["3.10"] + python-version: ["3.11"] steps: - uses: actions/checkout@v2 diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml index 3bc79d718..7fd8206f7 100644 --- a/.github/workflows/build_old.yml +++ b/.github/workflows/build_old.yml @@ -13,7 +13,7 @@ jobs: #NO_NET: 1 strategy: matrix: - python-version: ["3.10"] + python-version: ["3.11"] steps: - uses: actions/checkout@v2 diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index 042bb1625..a4a463bb3 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -53,7 +53,7 @@ jobs: runs-on: ${{ matrix.os }} strategy: matrix: - python-version: [ "3.10" ] + python-version: [ "3.11" ] os: [ubuntu-latest] platform: [x64] steps: From 810f774609a8dc3d308f296305ad3bbb4f64789b Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Fri, 3 Mar 2023 11:42:20 -0700 Subject: [PATCH 0965/1504] update --- README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/README.md b/README.md index 45ec61568..ebfbf975f 100644 --- a/README.md +++ b/README.md @@ -10,6 +10,8 @@ ## News For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog). +3/3/2023: Version [1.6.3](https://pypi.python.org/pypi/netCDF4/1.6.3) released. + 11/15/2022: Version [1.6.2](https://pypi.python.org/pypi/netCDF4/1.6.2) released. Fix for compilation with netcdf-c < 4.9.0 (issue [#1209](https://github.com/Unidata/netcdf4-python/issues/1209)). Slicing multi-dimensional variables with an all False boolean index array From 008edf9e794a62629d366f19976627fdb0cac070 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Sun, 5 Mar 2023 19:18:15 -0700 Subject: [PATCH 0966/1504] update pypi badge --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index ebfbf975f..ec55f5a5c 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,7 @@ [Python](http://python.org)/[numpy](http://numpy.org) interface to the netCDF [C library](https://github.com/Unidata/netcdf-c). [![Build status](https://github.com/Unidata/netcdf4-python/workflows/Build%20and%20Test/badge.svg)](https://github.com/Unidata/netcdf4-python/actions) -[![PyPI package](https://badge.fury.io/py/netCDF4.svg)](http://python.org/pypi/netCDF4) +[![PyPI package](https://img.shields.io/pypi/v/netCDF4.svg)](http://python.org/pypi/netCDF4) [![Anaconda-Server Badge](https://anaconda.org/conda-forge/netCDF4/badges/version.svg)](https://anaconda.org/conda-forge/netCDF4) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.2592291.svg)](https://doi.org/10.5281/zenodo.2592290) From bc1f9f5c6c03895c39a6bbbffbda542f90ae90df Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Mon, 6 Mar 2023 08:51:14 -0700 Subject: [PATCH 0967/1504] update Changelog --- Changelog | 2 ++ 1 file changed, 2 insertions(+) diff --git a/Changelog b/Changelog index de0bf022c..f89ab4e91 100644 --- a/Changelog +++ b/Changelog @@ -4,6 +4,7 @@ * _Unsigned="false" should be same as not having _Unsigned set (issue #1232). _Unsigned now must be set to "true" or "True" for variable to be interpreted as unsigned, instead of just having _Unsigned be set (to anything). + * pypi wheels built with netcdf-c 4.9.1. version 1.6.2 (tag v1.6.2rel) ============================== @@ -13,6 +14,7 @@ now returns an empty numpy array (instead of raising an exception - issue #1197). Behavior now consistent with numpy slicing. * fix problem with compiling using netcdf-c < 4.9.0 (issue #1209) + * pypi wheels build with netcdf-c 4.9.0. version 1.6.1 (tag v1.6.1rel) ============================== From 3d007b563980564c9885f38d58df250731ec431f Mon Sep 17 00:00:00 2001 From: "Garg, Nikhil" Date: Fri, 21 Apr 2023 09:44:22 +1000 Subject: [PATCH 0968/1504] Fixed the response of `isopen` for `MFDataset` --- src/netCDF4/_netCDF4.pyx | 114 +++++++++++++++++++++------------------ 1 file changed, 61 insertions(+), 53 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index a0ed5e5d0..5b18f89a7 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -33,7 +33,7 @@ types) are not supported. - Clone the [github repository](http://github.com/Unidata/netcdf4-python). - Make sure the dependencies are satisfied (Python 3.7 or later, - [numpy](http://numpy.scipy.org), + [numpy](http://numpy.scipy.org), [Cython](http://cython.org), [cftime](https://github.com/Unidata/cftime), [setuptools](https://pypi.python.org/pypi/setuptools), @@ -155,12 +155,12 @@ in a netCDF 3 file you will get an error message. >>> print(rootgrp.groups) {'forecasts': group /forecasts: - dimensions(sizes): - variables(dimensions): + dimensions(sizes): + variables(dimensions): groups: , 'analyses': group /analyses: - dimensions(sizes): - variables(dimensions): + dimensions(sizes): + variables(dimensions): groups: } >>> ``` @@ -196,32 +196,32 @@ object yields summary information about it's contents. >>> print(rootgrp) root group (NETCDF4 data model, file format HDF5): - dimensions(sizes): - variables(dimensions): + dimensions(sizes): + variables(dimensions): groups: forecasts, analyses >>> for children in walktree(rootgrp): ... for child in children: ... print(child) group /forecasts: - dimensions(sizes): - variables(dimensions): + dimensions(sizes): + variables(dimensions): groups: model1, model2 group /analyses: - dimensions(sizes): - variables(dimensions): - groups: + dimensions(sizes): + variables(dimensions): + groups: group /forecasts/model1: - dimensions(sizes): - variables(dimensions): - groups: + dimensions(sizes): + variables(dimensions): + groups: group /forecasts/model2: - dimensions(sizes): - variables(dimensions): - groups: + dimensions(sizes): + variables(dimensions): + groups: ``` ## Dimensions in a netCDF file @@ -356,9 +356,9 @@ You can also query a `Dataset` or `Group` instance directly to obtain `Group` or >>> print(rootgrp["/forecasts/model1"]) # a Group instance group /forecasts/model1: - dimensions(sizes): + dimensions(sizes): variables(dimensions): float32 temp(time,level,lat,lon) - groups: + groups: >>> print(rootgrp["/forecasts/model1/temp"]) # a Variable instance float32 temp(time, level, lat, lon) @@ -384,11 +384,11 @@ unlimited dimensions: level current shape = (0,) filling on, default _FillValue of -2147483647 used, 'lat': float32 lat(lat) -unlimited dimensions: +unlimited dimensions: current shape = (73,) filling on, default _FillValue of 9.969209968386869e+36 used, 'lon': float32 lon(lon) -unlimited dimensions: +unlimited dimensions: current shape = (144,) filling on, default _FillValue of 9.969209968386869e+36 used, 'temp': float32 temp(time, level, lat, lon) @@ -672,7 +672,7 @@ underlying file format is HDF5) and are silently ignored if the file format is `NETCDF3_CLASSIC`, `NETCDF3_64BIT_OFFSET` or `NETCDF3_64BIT_DATA`. If the HDF5 library is built with szip support, compression=`szip` can also be used (in conjunction with the `szip_coding` and `szip_pixels_per_block` keyword -arguments). +arguments). If your data only has a certain number of digits of precision (say for example, it is temperature data that was measured with a precision of @@ -782,7 +782,7 @@ objects gives useful summary information in an interactive session: root group (NETCDF4 data model, file format HDF5): dimensions(sizes): x_dim(3) variables(dimensions): {'names':['real','imag'], 'formats':['>> print(f.variables["cmplx_var"]) compound cmplx_var(x_dim) @@ -851,12 +851,12 @@ vlen variable = root group (NETCDF4 data model, file format HDF5): dimensions(sizes): x(3), y(4) variables(dimensions): int32 phony_vlen_var(y,x) - groups: + groups: >>> print(f.variables["phony_vlen_var"]) vlen phony_vlen_var(y, x) vlen data type: int32 -unlimited dimensions: +unlimited dimensions: current shape = (4, 3) >>> print(f.vltypes["phony_vlen"]) : name = 'phony_vlen', numpy dtype = int32 @@ -893,12 +893,12 @@ variable-length string variable: root group (NETCDF4 data model, file format HDF5): dimensions(sizes): x(3), y(4), z(10) variables(dimensions): int32 phony_vlen_var(y,x), strvar(z) - groups: + groups: >>> print(f.variables["strvar"]) vlen strvar(z) vlen data type: -unlimited dimensions: +unlimited dimensions: current shape = (10,) ``` @@ -967,7 +967,7 @@ current shape = (5,) If MPI parallel enabled versions of netcdf and hdf5 or pnetcdf are detected, and [mpi4py](https://mpi4py.scipy.org) is installed, netcdf4-python will -be built with parallel IO capabilities enabled. Parallel IO of NETCDF4 or +be built with parallel IO capabilities enabled. Parallel IO of NETCDF4 or NETCDF4_CLASSIC formatted files is only available if the MPI parallel HDF5 library is available. Parallel IO of classic netcdf-3 file formats is only available if the [PnetCDF](https://parallel-netcdf.github.io/) library is @@ -1154,7 +1154,7 @@ approaches. root group (NETCDF4 data model, file format HDF5): dimensions(sizes): x(5) variables(dimensions): int32 v(x) - groups: + groups: >>> print(nc['v'][:]) [0 1 2 3 4] >>> nc.close() # file saved to disk @@ -1171,7 +1171,7 @@ root group (NETCDF4 data model, file format HDF5): root group (NETCDF4 data model, file format HDF5): dimensions(sizes): x(5) variables(dimensions): int32 v(x) - groups: + groups: >>> print(nc['v'][:]) [0 1 2 3 4] >>> nc.close() @@ -1392,9 +1392,9 @@ _needsworkaround_issue485 = __netcdf4libversion__ < "4.4.0" or \ if __netcdf4libversion__[0:5] < "4.4.1" and\ __hdf5libversion__.startswith("1.10"): msg = """ -WARNING: Backwards incompatible files will be created with HDF5 1.10.x -and netCDF < 4.4.1. Upgrading to netCDF4 >= 4.4.1 or downgrading to -to HDF5 version 1.8.x is highly recommended +WARNING: Backwards incompatible files will be created with HDF5 1.10.x +and netCDF < 4.4.1. Upgrading to netCDF4 >= 4.4.1 or downgrading to +to HDF5 version 1.8.x is highly recommended (see https://github.com/Unidata/netcdf-c/issues/250).""" warnings.warn(msg) @@ -2119,8 +2119,8 @@ strings. **`mode`**: access mode. `r` means read-only; no data can be modified. `w` means write; a new file is created, an existing file with the same name is deleted. `x` means write, but fail if an existing - file with the same name already exists. `a` and `r+` mean append; - an existing file is opened for reading and writing, if + file with the same name already exists. `a` and `r+` mean append; + an existing file is opened for reading and writing, if file does not exist already, one is created. Appending `s` to modes `r`, `w`, `r+` or `a` will enable unbuffered shared access to `NETCDF3_CLASSIC`, `NETCDF3_64BIT_OFFSET` or @@ -2401,7 +2401,7 @@ strings. if parallel: # NC_SHARE ignored IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: - cmode = NC_CLOBBER | parmode + cmode = NC_CLOBBER | parmode with nogil: ierr = nc_create_par(path, NC_CLOBBER | cmode, \ mpicomm, mpiinfo, &grpid) @@ -2763,7 +2763,7 @@ datatype.""" enum_dict) return self.enumtypes[datatype_name] - def createVariable(self, varname, datatype, dimensions=(), + def createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False, complevel=4, shuffle=True, szip_coding='nn',szip_pixels_per_block=8, @@ -2815,7 +2815,7 @@ Default is `None` (no compression). All of the compressors except `zlib` and `szip` use the HDF5 plugin architecture. If the optional keyword `zlib` is `True`, the data will be compressed in -the netCDF file using zlib compression (default `False`). The use of this option is +the netCDF file using zlib compression (default `False`). The use of this option is deprecated in favor of `compression='zlib'`. The optional keyword `complevel` is an integer between 0 and 9 describing @@ -3422,15 +3422,15 @@ suffix replaced by `.nc` is used.. **`format`**: underlying file format to use (one of `'NETCDF4', 'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC'`, `'NETCDF3_64BIT_OFFSET'` or `'NETCDF3_64BIT_DATA'`. Default `'NETCDF4'`. - + Dataset instance for `ncfilename` is returned. - + [ncgen]: https://www.unidata.ucar.edu/software/netcdf/docs/netcdf_utilities_guide.html#ncgen_guide [cdl]: https://www.unidata.ucar.edu/software/netcdf/docs/netcdf_utilities_guide.html#cdl_guide """ if ncfilename is None: filepath = pathlib.Path(cdlfilename) - ncfilename = filepath.with_suffix('.nc') + ncfilename = filepath.with_suffix('.nc') formatcodes = {'NETCDF4': 4, 'NETCDF4_CLASSIC': 7, 'NETCDF3_CLASSIC': 3, @@ -3824,13 +3824,13 @@ truncated to retain this number of significant digits when it is assigned to the Only available with netcdf-c >= 4.9.0, and only works with `NETCDF4` or `NETCDF4_CLASSIC` formatted files. The number of significant digits used in the quantization of variable data can be -obtained using the `Variable.significant_digits` method. Default `None` - +obtained using the `Variable.significant_digits` method. Default `None` - no quantization done. **`quantize_mode`**: New in version 1.6.0. Controls the quantization algorithm (default 'BitGroom', 'BitRound' and 'GranularBitRound' also available). The 'GranularBitRound' -algorithm may result in better compression for typical geophysical datasets. +algorithm may result in better compression for typical geophysical datasets. Ignored if `significant_digits` not specified. If 'BitRound' is used, then `significant_digits` is interpreted as binary (not decimal) digits. @@ -3854,7 +3854,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. def __init__(self, grp, name, datatype, dimensions=(), compression=None, zlib=False, complevel=4, shuffle=True, szip_coding='nn', szip_pixels_per_block=8, - blosc_shuffle=1, + blosc_shuffle=1, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, significant_digits=None,quantize_mode='BitGroom',fill_value=None, chunk_cache=None, **kwargs): @@ -3894,7 +3894,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. (defined previously with `createDimension`). Default is an empty tuple which means the variable is a scalar (and therefore has no dimensions). - **`compression`**: compression algorithm to use. + **`compression`**: compression algorithm to use. Currently `zlib`,`szip`,`zstd`,`bzip2`,`blosc_lz`,`blosc_lz4`,`blosc_lz4hc`, `blosc_zlib` and `blosc_zstd` are supported. Default is `None` (no compression). All of the compressors except @@ -3920,7 +3920,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. or `nn` (nearest neighbor coding). Default is `nn`. Ignored if szip compressor not used. - **`szip_pixels_per_block`**: Can be 4,8,16 or 32 (Default 8). + **`szip_pixels_per_block`**: Can be 4,8,16 or 32 (Default 8). Ignored if szip compressor not used. **`fletcher32`**: if `True` (default `False`), the Fletcher32 checksum @@ -4001,7 +4001,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. cdef float preemptionp # flag to indicate that orthogonal indexing is supported self.__orthogonal_indexing__ = True - # For backwards compatibility, deprecated zlib kwarg takes + # For backwards compatibility, deprecated zlib kwarg takes # precedence if compression kwarg not set. if zlib and not compression: compression = 'zlib' @@ -4500,7 +4500,7 @@ kwarg for quantization.""" property datatype: """numpy data type (for primitive data types) or - VLType/CompoundType/EnumType instance + VLType/CompoundType/EnumType instance (for compound, vlen or enum data types)""" def __get__(self): if self._iscompound: @@ -4640,8 +4640,8 @@ return dictionary containing HDF5 filter parameters.""" cdef int iszip=0 cdef int iszip_coding=0 cdef int iszip_pixels_per_block=0 - cdef int icomplevel_zstd=0 - cdef int icomplevel_bzip2=0 + cdef int icomplevel_zstd=0 + cdef int icomplevel_bzip2=0 cdef unsigned int iblosc_shuffle=0 cdef unsigned int iblosc_compressor=0 cdef unsigned int iblosc_blocksize=0 @@ -5572,7 +5572,7 @@ When data is written to a variable, the masked array is converted back to a regular numpy array by replacing all the masked values by the missing_value attribute of the variable (if it exists). If the variable has no missing_value attribute, the _FillValue -is used instead. +is used instead. If `maskandscale` is set to `True`, and the variable has a `scale_factor` or an `add_offset` attribute, then data read @@ -5662,7 +5662,7 @@ When data is written to a variable, the masked array is converted back to a regular numpy array by replacing all the masked values by the missing_value attribute of the variable (if it exists). If the variable has no missing_value attribute, the _FillValue -is used instead. +is used instead. The default value of `mask` is `True` (automatic conversions are performed). @@ -6930,6 +6930,14 @@ Example usage (See `MFDataset.__init__` for more details): for dset in self._cdf: dset.close() + def isopen(self): + """ + **`isopen(self)`** + + True if all files are open, False otherwise. + """ + return all(map(lambda dset: dset.isopen(), self._cdf)) + def __repr__(self): ncdump = [repr(type(self))] dimnames = tuple(str(dimname) for dimname in self.dimensions.keys()) From 3599bfe1f97e98b74f8b7e1a44a2f02e050a5f03 Mon Sep 17 00:00:00 2001 From: "Garg, Nikhil" Date: Sat, 22 Apr 2023 15:56:09 +1000 Subject: [PATCH 0969/1504] updated multifile to check if file is open --- test/tst_multifile.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/test/tst_multifile.py b/test/tst_multifile.py index 786740512..0d9584892 100644 --- a/test/tst_multifile.py +++ b/test/tst_multifile.py @@ -74,7 +74,9 @@ def runTest(self): f = MFDataset(self.files,check=True) assert f.get_variables_by_attributes(axis='T') == [] f.get_variables_by_attributes(units='zlotys')[0] == f['x'] + assert f.isopen() f.close() + assert not f.isopen() class NonuniformTimeTestCase(unittest.TestCase): ninc = 365 From 26301240dc8d902274acadc699d88e68aa197113 Mon Sep 17 00:00:00 2001 From: "Garg, Nikhil" Date: Sat, 22 Apr 2023 15:58:32 +1000 Subject: [PATCH 0970/1504] updated changelog --- Changelog | 16 ++++++++++------ 1 file changed, 10 insertions(+), 6 deletions(-) diff --git a/Changelog b/Changelog index f89ab4e91..d676d4a38 100644 --- a/Changelog +++ b/Changelog @@ -1,7 +1,11 @@ + version 1.6.4 (tag v1.6.4rel) +============================== + * Added `isopen` method to `MFDataset` object to check if underlying files are open. + version 1.6.3 (tag v1.6.3rel) ============================== * Use ``nc_put_vars`` for strided writes for netcdf-c >= 4.6.2 (issue #1222). - * _Unsigned="false" should be same as not having _Unsigned set (issue #1232). + * _Unsigned="false" should be same as not having _Unsigned set (issue #1232). _Unsigned now must be set to "true" or "True" for variable to be interpreted as unsigned, instead of just having _Unsigned be set (to anything). * pypi wheels built with netcdf-c 4.9.1. @@ -51,15 +55,15 @@ options. * MFDataset did not aggregate 'name' variable attribute (issue #1153). * issue warning instead of raising an exception if missing_value or - _FillValue can't be cast to the variable type when creating a - masked array (issue #1152). + _FillValue can't be cast to the variable type when creating a + masked array (issue #1152). * Define MPI_Session for compatibility with current mpi4py (PR #1156). version 1.5.8 (tag v1.5.8rel) ============================== * Fix Enum bug (issue #1128): the enum_dict member of an EnumType read from a file contains invalid values when the enum is large enough (more than 127 or 255 - members). + members). * Binary wheels for aarch64 and python 3.10. version 1.5.7 (tag v1.5.7rel) @@ -114,7 +118,7 @@ version 1.5.3 (tag v1.5.3rel) ============================== - * make sure arrays are masked that are not filled when auto_fill is off + * make sure arrays are masked that are not filled when auto_fill is off (issue #972). * python 3.8 binary wheels. @@ -156,7 +160,7 @@ version 1.5.0.1 (tag v1.5.0.1rel) ================================== * binary wheels for linux and macosx rebuilt against netcdf-c 4.6.3 (instead - of 4.4.1.1). + of 4.4.1.1). * add read-shared mode (mode='rs'). Significantly speeds up reads of NETCDF3 files (pull request #902). From 59eb0e2451d3516a3b09bf9628d0c6bf16b55b5e Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Wed, 26 Apr 2023 07:29:48 -0600 Subject: [PATCH 0971/1504] test for SSL error on linux (issue #1246) --- test/tst_dap.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/test/tst_dap.py b/test/tst_dap.py index 7924e289b..db43926ec 100644 --- a/test/tst_dap.py +++ b/test/tst_dap.py @@ -35,6 +35,9 @@ def runTest(self): ncfile = netCDF4.Dataset(URL_https) assert(ncfile['sst'].long_name=='Sea Surface Temperature') ncfile.close() + # check for SSL error on linux (issue #1246) + ncfile=Dataset('https://icdc.cen.uni-hamburg.de/thredds/dodsC/ftpthredds/hamtide//m2.hamtide11a.nc') + if __name__ == '__main__': unittest.main() From f31facfaf5b4154fd156ab7c451f97f7b68d0a47 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Wed, 26 Apr 2023 07:38:52 -0600 Subject: [PATCH 0972/1504] update --- test/tst_dap.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/test/tst_dap.py b/test/tst_dap.py index db43926ec..46a26ae43 100644 --- a/test/tst_dap.py +++ b/test/tst_dap.py @@ -8,7 +8,7 @@ yesterday = datetime.utcnow() - timedelta(days=1) URL = "http://nomads.ncep.noaa.gov/dods/gfs_1p00/gfs%s/gfs_1p00_00z" % yesterday.strftime('%Y%m%d') -URL_https = 'https://podaac-opendap.jpl.nasa.gov/opendap/allData/modis/L3/aqua/11um/v2019.0/4km/daily/2017/365/AQUA_MODIS.20171231.L3m.DAY.NSST.sst.4km.nc' +URL_https='https://icdc.cen.uni-hamburg.de/thredds/dodsC/ftpthredds/hamtide//m2.hamtide11a.nc' varname = 'hgtsfc' data_min = -40; data_max = 5900 varshape = (181, 360) @@ -33,10 +33,8 @@ def runTest(self): ncfile.close() # test https support (linked curl lib must built with openssl support) ncfile = netCDF4.Dataset(URL_https) - assert(ncfile['sst'].long_name=='Sea Surface Temperature') + assert(ncfile['PHAS'].long_name=='Phase') ncfile.close() - # check for SSL error on linux (issue #1246) - ncfile=Dataset('https://icdc.cen.uni-hamburg.de/thredds/dodsC/ftpthredds/hamtide//m2.hamtide11a.nc') if __name__ == '__main__': From 0b161e4c058489382559448df4eb93d4a6d69fcf Mon Sep 17 00:00:00 2001 From: jswhit Date: Sun, 30 Apr 2023 10:06:38 -0600 Subject: [PATCH 0973/1504] add nc_rc_set --- include/netCDF4.pxi | 1 + 1 file changed, 1 insertion(+) diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi index 9233c8165..7eae57750 100644 --- a/include/netCDF4.pxi +++ b/include/netCDF4.pxi @@ -366,6 +366,7 @@ cdef extern from "netcdf.h": int nc_inq_enum_member(int ncid, nc_type xtype, int idx, char *name, void *value) nogil int nc_inq_enum_ident(int ncid, nc_type xtype, long long value, char *identifier) nogil + int nc_rc_set(char key, char* value) nogil IF HAS_QUANTIZATION_SUPPORT: cdef extern from "netcdf.h": From 5d0130f65ec05b787d08cd3b1b5d6cadb2ce9621 Mon Sep 17 00:00:00 2001 From: jswhit Date: Sun, 30 Apr 2023 10:07:42 -0600 Subject: [PATCH 0974/1504] fix typo in previous commit --- include/netCDF4.pxi | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi index 7eae57750..72b876585 100644 --- a/include/netCDF4.pxi +++ b/include/netCDF4.pxi @@ -366,7 +366,7 @@ cdef extern from "netcdf.h": int nc_inq_enum_member(int ncid, nc_type xtype, int idx, char *name, void *value) nogil int nc_inq_enum_ident(int ncid, nc_type xtype, long long value, char *identifier) nogil - int nc_rc_set(char key, char* value) nogil + int nc_rc_set(char* key, char* value) nogil IF HAS_QUANTIZATION_SUPPORT: cdef extern from "netcdf.h": From 8f5334dc612d365a2ea0869724793b9c69faea86 Mon Sep 17 00:00:00 2001 From: jswhit Date: Sun, 30 Apr 2023 13:53:38 -0600 Subject: [PATCH 0975/1504] use certifi and nc_rc_set to set path to ssl certificates --- src/netCDF4/_netCDF4.pyx | 16 +++++++++++++++- 1 file changed, 15 insertions(+), 1 deletion(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index a0ed5e5d0..13403ed69 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1258,6 +1258,20 @@ ELSE: ctypedef object Comm ctypedef object Info +import certifi + +# set path to SSL certificates (issue #1246) +cdef _set_curl_certpath(certpath): + cdef char *cert_path + cdef char *key + cdef int ierr + bytestr = _strencode(certpath) + cert_path = bytestr + ierr = nc_rc_set("HTTP.SSL.CAINFO",cert_path) + if ierr != 0: + raise RuntimeError('error setting path to SSL certificates') +_set_curl_certpath(certifi.where()) + # check for required version of netcdf-4 and hdf5. def _gethdf5libversion(): @@ -1265,7 +1279,7 @@ def _gethdf5libversion(): cdef herr_t ierr with nogil: ierr = H5get_libversion( &majorvers, &minorvers, &releasevers) - if ierr < 0: + if ierr != 0: raise RuntimeError('error getting HDF5 library version info') return '%d.%d.%d' % (majorvers,minorvers,releasevers) From 8b55eeef7a4686ca13ce24a57361bfc98c5664d1 Mon Sep 17 00:00:00 2001 From: jswhit Date: Sun, 30 Apr 2023 15:54:59 -0600 Subject: [PATCH 0976/1504] update --- Changelog | 6 ++++++ setup.py | 15 +++++++++++++-- src/netCDF4/_netCDF4.pyx | 28 ++++++++++++++-------------- 3 files changed, 33 insertions(+), 16 deletions(-) diff --git a/Changelog b/Changelog index f89ab4e91..fae77aa5f 100644 --- a/Changelog +++ b/Changelog @@ -1,3 +1,9 @@ + version 1.6.4 (not yet released) +================================= + * set path to SSL certificates internally, so https DAP URLs work with wheels + (issue #1246, requires nc_rc_set function available starting with netcdf-c 4.9.2). + Added certifi as a dependency. + version 1.6.3 (tag v1.6.3rel) ============================== * Use ``nc_put_vars`` for strided writes for netcdf-c >= 4.6.2 (issue #1222). diff --git a/setup.py b/setup.py index 016e7b5b9..b72c9b2cf 100644 --- a/setup.py +++ b/setup.py @@ -60,6 +60,7 @@ def check_api(inc_dirs,netcdf_lib_version): has_blosc = False has_ncfilter = False has_set_alignment = False + has_nc_rc_set = False for d in inc_dirs: try: @@ -83,6 +84,8 @@ def check_api(inc_dirs,netcdf_lib_version): has_quantize = True if line.startswith('nc_set_alignment'): has_set_alignment = True + if line.startswith('nc_rc_set'): + has_nc_rc_set = True if has_nc_open_mem: try: @@ -150,7 +153,8 @@ def check_api(inc_dirs,netcdf_lib_version): return has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \ has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \ has_parallel4_support, has_pnetcdf_support, has_szip_support, has_quantize, \ - has_zstandard, has_bzip2, has_blosc, has_set_alignment, has_ncfilter + has_zstandard, has_bzip2, has_blosc, has_set_alignment, has_ncfilter, \ + has_nc_rc_set def getnetcdfvers(libdirs): @@ -564,7 +568,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \ has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \ has_parallel4_support, has_pnetcdf_support, has_szip_support, has_quantize, \ - has_zstandard, has_bzip2, has_blosc, has_set_alignment, has_ncfilter = \ + has_zstandard, has_bzip2, has_blosc, has_set_alignment, has_ncfilter, has_nc_rc_set = \ check_api(inc_dirs,netcdf_lib_version) # for netcdf 4.4.x CDF5 format is always enabled. if netcdf_lib_version is not None and\ @@ -686,6 +690,13 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): sys.stdout.write('netcdf lib does not have nc_inq_filter_avail function\n') f.write('DEF HAS_NCFILTER = 0\n') + if has_nc_rc_set: + sys.stdout.write('netcdf lib has nc_rc_set function\n') + f.write('DEF HAS_NCRCSET = 1\n') + else: + sys.stdout.write('netcdf lib does not have nc_rc_set function\n') + f.write('DEF HAS_NCRCSET = 0\n') + f.close() if has_parallel4_support or has_pnetcdf_support: diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 13403ed69..ed6af81c1 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1,5 +1,5 @@ """ -Version 1.6.3 +Version 1.6.4 ------------- # Introduction @@ -1227,7 +1227,7 @@ from .utils import (_StartCountStride, _quantize, _find_dim, _walk_grps, _out_array_shape, _sortbylist, _tostr, _safecast, _is_int) import sys -__version__ = "1.6.3" +__version__ = "1.6.4" # Initialize numpy import posixpath @@ -1258,19 +1258,19 @@ ELSE: ctypedef object Comm ctypedef object Info -import certifi - # set path to SSL certificates (issue #1246) -cdef _set_curl_certpath(certpath): - cdef char *cert_path - cdef char *key - cdef int ierr - bytestr = _strencode(certpath) - cert_path = bytestr - ierr = nc_rc_set("HTTP.SSL.CAINFO",cert_path) - if ierr != 0: - raise RuntimeError('error setting path to SSL certificates') -_set_curl_certpath(certifi.where()) +IF HAS_NCRCSET: # available starting in version 4.9.2 + import certifi + cdef _set_curl_certpath(certpath): + cdef char *cert_path + cdef char *key + cdef int ierr + bytestr = _strencode(certpath) + cert_path = bytestr + ierr = nc_rc_set("HTTP.SSL.CAINFO",cert_path) + if ierr != 0: + raise RuntimeError('error setting path to SSL certificates') + _set_curl_certpath(certifi.where()) # check for required version of netcdf-4 and hdf5. From 1128c6d841764e8e2cfb516b819a43d66805dc92 Mon Sep 17 00:00:00 2001 From: jswhit Date: Sun, 30 Apr 2023 15:59:18 -0600 Subject: [PATCH 0977/1504] update --- README.md | 4 ++++ pyproject.toml | 1 + 2 files changed, 5 insertions(+) diff --git a/README.md b/README.md index ec55f5a5c..8ad22ee4b 100644 --- a/README.md +++ b/README.md @@ -10,6 +10,10 @@ ## News For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog). +?/?/2023: Version [1.6.4](https://pypi.python.org/pypi/netCDF4/1.6.4) released. Now requires +[certifi](https://github.com/certifi/python-certifi) to locate SSL certificates - this allows +OpenDAP https URLs to work with wheels (issue [#1246)(https://github.com/Unidata/netcdf4-python/issues/1246). + 3/3/2023: Version [1.6.3](https://pypi.python.org/pypi/netCDF4/1.6.3) released. 11/15/2022: Version [1.6.2](https://pypi.python.org/pypi/netCDF4/1.6.2) released. Fix for diff --git a/pyproject.toml b/pyproject.toml index 0060eac30..f755e1679 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -42,6 +42,7 @@ classifiers = [ ] dependencies = [ "cftime", + "certifi", "numpy", ] dynamic = ["version"] From 829a665c6a587572f06cc9b23e47065cb01ad9d7 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Sun, 30 Apr 2023 16:42:12 -0600 Subject: [PATCH 0978/1504] build version 4.9.2 --- .github/workflows/build_latest.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml index f7798b255..320190ddb 100644 --- a/.github/workflows/build_latest.yml +++ b/.github/workflows/build_latest.yml @@ -6,7 +6,7 @@ jobs: runs-on: ubuntu-latest env: PNETCDF_VERSION: 1.12.1 - NETCDF_VERSION: 4.9.1 + NETCDF_VERSION: 4.9.2 NETCDF_DIR: ${{ github.workspace }}/.. NETCDF_EXTRA_CONFIG: --enable-pnetcdf CC: mpicc.mpich From a859dd1271e536cbdb8e082ad643b3fc72f2b614 Mon Sep 17 00:00:00 2001 From: jswhit Date: Sun, 30 Apr 2023 17:36:40 -0600 Subject: [PATCH 0979/1504] fix nc_rc_set test --- setup.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/setup.py b/setup.py index b72c9b2cf..5bf61e16a 100644 --- a/setup.py +++ b/setup.py @@ -84,7 +84,7 @@ def check_api(inc_dirs,netcdf_lib_version): has_quantize = True if line.startswith('nc_set_alignment'): has_set_alignment = True - if line.startswith('nc_rc_set'): + if line.startswith('EXTERNL int nc_rc_set'): has_nc_rc_set = True if has_nc_open_mem: From 602554d63c2e1ed5c1ab17ce8d26d2b32b14242c Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Sun, 30 Apr 2023 20:53:18 -0600 Subject: [PATCH 0980/1504] update --- Changelog | 3 ++- README.md | 2 +- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/Changelog b/Changelog index fae77aa5f..2e37e9845 100644 --- a/Changelog +++ b/Changelog @@ -1,7 +1,8 @@ version 1.6.4 (not yet released) ================================= * set path to SSL certificates internally, so https DAP URLs work with wheels - (issue #1246, requires nc_rc_set function available starting with netcdf-c 4.9.2). + (issue #1246, requires nc_rc_set function available starting with netcdf-c + 4.9.2, plus bugfix in netcdf-c PR #2690). Added certifi as a dependency. version 1.6.3 (tag v1.6.3rel) diff --git a/README.md b/README.md index 8ad22ee4b..c11ca205d 100644 --- a/README.md +++ b/README.md @@ -12,7 +12,7 @@ For details on the latest updates, see the [Changelog](https://github.com/Unidat ?/?/2023: Version [1.6.4](https://pypi.python.org/pypi/netCDF4/1.6.4) released. Now requires [certifi](https://github.com/certifi/python-certifi) to locate SSL certificates - this allows -OpenDAP https URLs to work with wheels (issue [#1246)(https://github.com/Unidata/netcdf4-python/issues/1246). +OpenDAP https URLs to work with linux wheels (issue [#1246](https://github.com/Unidata/netcdf4-python/issues/1246). 3/3/2023: Version [1.6.3](https://pypi.python.org/pypi/netCDF4/1.6.3) released. From 2b4f447b35eb5890986979b5f6f2c45a5e52bf42 Mon Sep 17 00:00:00 2001 From: jswhit Date: Mon, 1 May 2023 11:06:16 -0600 Subject: [PATCH 0981/1504] update docstrings, README --- Changelog | 2 +- src/netCDF4/_netCDF4.pyx | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/Changelog b/Changelog index 2e37e9845..4d3f1025a 100644 --- a/Changelog +++ b/Changelog @@ -2,7 +2,7 @@ ================================= * set path to SSL certificates internally, so https DAP URLs work with wheels (issue #1246, requires nc_rc_set function available starting with netcdf-c - 4.9.2, plus bugfix in netcdf-c PR #2690). + 4.9.1, plus bugfix in netcdf-c PR #2690). Added certifi as a dependency. version 1.6.3 (tag v1.6.3rel) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index ed6af81c1..687dafb3c 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1259,7 +1259,7 @@ ELSE: ctypedef object Info # set path to SSL certificates (issue #1246) -IF HAS_NCRCSET: # available starting in version 4.9.2 +IF HAS_NCRCSET: # available starting in version 4.9.1 import certifi cdef _set_curl_certpath(certpath): cdef char *cert_path From 30278275e65a2bcf3c03c9b06a03c01e586a0827 Mon Sep 17 00:00:00 2001 From: jswhit Date: Mon, 1 May 2023 11:42:44 -0600 Subject: [PATCH 0982/1504] include certifi dependency --- .github/workflows/miniconda.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index a4a463bb3..009f4266b 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -31,7 +31,7 @@ jobs: - name: Python ${{ matrix.python-version }} shell: bash -l {0} run: | - micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest hdf5 libnetcdf cftime zlib --channel conda-forge + micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest hdf5 libnetcdf cftime certifi zlib --channel conda-forge micromamba activate TEST export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config pip install -v -e . --no-deps --force-reinstall @@ -67,7 +67,7 @@ jobs: - name: Python ${{ matrix.python-version }} shell: bash -l {0} run: | - micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest mpi4py hdf5=*=mpi* libnetcdf=*=mpi* cftime zlib --channel conda-forge + micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest mpi4py hdf5=*=mpi* libnetcdf=*=mpi* cftime certifi zlib --channel conda-forge micromamba activate TEST export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config nc-config --all From 7ec5925ee5d24e9a6a6d039ac932084baaac43e9 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Thu, 18 May 2023 10:59:48 -0300 Subject: [PATCH 0983/1504] add dependabot.yml --- .github/dependabot.yml | 11 +++++++++++ 1 file changed, 11 insertions(+) create mode 100644 .github/dependabot.yml diff --git a/.github/dependabot.yml b/.github/dependabot.yml new file mode 100644 index 000000000..563dd9bc7 --- /dev/null +++ b/.github/dependabot.yml @@ -0,0 +1,11 @@ +# See https://docs.github.com/en/code-security/supply-chain-security/keeping-your-dependencies-updated-automatically/keeping-your-actions-up-to-date-with-dependabot + +version: 2 +updates: + + - package-ecosystem: "github-actions" + directory: "/" + schedule: + interval: "daily" + labels: + - "Bot" From 1b53db85896c8c57ffcf9845a708b42f93dd09ff Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Thu, 18 May 2023 11:20:12 -0300 Subject: [PATCH 0984/1504] use a more stable URL --- test/tst_dap.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/test/tst_dap.py b/test/tst_dap.py index 7924e289b..2b033e93a 100644 --- a/test/tst_dap.py +++ b/test/tst_dap.py @@ -7,8 +7,8 @@ # test accessing data over http with opendap. yesterday = datetime.utcnow() - timedelta(days=1) -URL = "http://nomads.ncep.noaa.gov/dods/gfs_1p00/gfs%s/gfs_1p00_00z" % yesterday.strftime('%Y%m%d') -URL_https = 'https://podaac-opendap.jpl.nasa.gov/opendap/allData/modis/L3/aqua/11um/v2019.0/4km/daily/2017/365/AQUA_MODIS.20171231.L3m.DAY.NSST.sst.4km.nc' +URL = f'http://nomads.ncep.noaa.gov/dods/gfs_1p00/gfs{yesterday:%Y%m%d}/gfs_1p00_00z' +URL_https = 'https://www.neracoos.org/erddap/griddap/WW3_EastCoast_latest' varname = 'hgtsfc' data_min = -40; data_max = 5900 varshape = (181, 360) @@ -33,7 +33,7 @@ def runTest(self): ncfile.close() # test https support (linked curl lib must built with openssl support) ncfile = netCDF4.Dataset(URL_https) - assert(ncfile['sst'].long_name=='Sea Surface Temperature') + assert(ncfile['hs'].long_name=='Significant Wave Height') ncfile.close() if __name__ == '__main__': From fac49942d1222114db2cbea0eb6f742703d24d04 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Sat, 20 May 2023 14:07:53 +0000 Subject: [PATCH 0985/1504] Bump actions/setup-python from 2 to 4 Bumps [actions/setup-python](https://github.com/actions/setup-python) from 2 to 4. - [Release notes](https://github.com/actions/setup-python/releases) - [Commits](https://github.com/actions/setup-python/compare/v2...v4) --- updated-dependencies: - dependency-name: actions/setup-python dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- .github/workflows/build_latest.yml | 2 +- .github/workflows/build_master.yml | 2 +- .github/workflows/build_old.yml | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml index f7798b255..0ea4e08f3 100644 --- a/.github/workflows/build_latest.yml +++ b/.github/workflows/build_latest.yml @@ -19,7 +19,7 @@ jobs: - uses: actions/checkout@v2 - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v2 + uses: actions/setup-python@v4 with: python-version: ${{ matrix.python-version }} diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index c422152e0..87facb177 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -16,7 +16,7 @@ jobs: - uses: actions/checkout@v2 - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v2 + uses: actions/setup-python@v4 with: python-version: ${{ matrix.python-version }} diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml index 7fd8206f7..b4379ba1d 100644 --- a/.github/workflows/build_old.yml +++ b/.github/workflows/build_old.yml @@ -19,7 +19,7 @@ jobs: - uses: actions/checkout@v2 - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v2 + uses: actions/setup-python@v4 with: python-version: ${{ matrix.python-version }} From 19ca7624587ae10091a48de48be9582013e496bd Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Sat, 20 May 2023 14:08:00 +0000 Subject: [PATCH 0986/1504] Bump actions/checkout from 2 to 3 Bumps [actions/checkout](https://github.com/actions/checkout) from 2 to 3. - [Release notes](https://github.com/actions/checkout/releases) - [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md) - [Commits](https://github.com/actions/checkout/compare/v2...v3) --- updated-dependencies: - dependency-name: actions/checkout dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- .github/workflows/build_latest.yml | 2 +- .github/workflows/build_master.yml | 2 +- .github/workflows/build_old.yml | 2 +- .github/workflows/miniconda.yml | 2 +- 4 files changed, 4 insertions(+), 4 deletions(-) diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml index f7798b255..f993da997 100644 --- a/.github/workflows/build_latest.yml +++ b/.github/workflows/build_latest.yml @@ -16,7 +16,7 @@ jobs: python-version: ["3.11"] steps: - - uses: actions/checkout@v2 + - uses: actions/checkout@v3 - name: Set up Python ${{ matrix.python-version }} uses: actions/setup-python@v2 diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index c422152e0..c7657cb58 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -13,7 +13,7 @@ jobs: python-version: ["3.11"] steps: - - uses: actions/checkout@v2 + - uses: actions/checkout@v3 - name: Set up Python ${{ matrix.python-version }} uses: actions/setup-python@v2 diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml index 7fd8206f7..97ba2e3f9 100644 --- a/.github/workflows/build_old.yml +++ b/.github/workflows/build_old.yml @@ -16,7 +16,7 @@ jobs: python-version: ["3.11"] steps: - - uses: actions/checkout@v2 + - uses: actions/checkout@v3 - name: Set up Python ${{ matrix.python-version }} uses: actions/setup-python@v2 diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index a4a463bb3..af205c1ac 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -57,7 +57,7 @@ jobs: os: [ubuntu-latest] platform: [x64] steps: - - uses: actions/checkout@v2 + - uses: actions/checkout@v3 - name: Setup Micromamba uses: mamba-org/provision-with-micromamba@main From 6e283e4c1ab5561ed12e209ef782706601504057 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Sat, 20 May 2023 19:18:39 +0000 Subject: [PATCH 0987/1504] Bump mamba-org/provision-with-micromamba from 13 to 15 Bumps [mamba-org/provision-with-micromamba](https://github.com/mamba-org/provision-with-micromamba) from 13 to 15. - [Release notes](https://github.com/mamba-org/provision-with-micromamba/releases) - [Commits](https://github.com/mamba-org/provision-with-micromamba/compare/v13...v15) --- updated-dependencies: - dependency-name: mamba-org/provision-with-micromamba dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- .github/workflows/miniconda.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index af205c1ac..38f92c34d 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -24,7 +24,7 @@ jobs: - uses: actions/checkout@v3 - name: Setup Micromamba - uses: mamba-org/provision-with-micromamba@v13 + uses: mamba-org/provision-with-micromamba@v15 with: environment-file: false From 11eeb2393cc82eee13ba3bc6f047fa492cbe7482 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Thu, 18 May 2023 13:15:01 -0300 Subject: [PATCH 0988/1504] implement lru_cache for get_variables_by_attributes --- src/netCDF4/_netCDF4.pyx | 14 +++++++++++--- 1 file changed, 11 insertions(+), 3 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 5b18f89a7..3943c320d 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1226,6 +1226,7 @@ from cpython.bytes cimport PyBytes_FromStringAndSize from .utils import (_StartCountStride, _quantize, _find_dim, _walk_grps, _out_array_shape, _sortbylist, _tostr, _safecast, _is_int) import sys +import functools __version__ = "1.6.3" @@ -2099,7 +2100,7 @@ strings. cdef Py_buffer _buffer cdef public groups, dimensions, variables, disk_format, path, parent,\ file_format, data_model, cmptypes, vltypes, enumtypes, __orthogonal_indexing__, \ - keepweakref, _ncstring_attrs__ + keepweakref, _ncstring_attrs__, get_variables_by_attributes def __init__(self, filename, mode='r', clobber=True, format='NETCDF4', diskless=False, persist=False, keepweakref=False, @@ -2211,6 +2212,10 @@ strings. memset(&self._buffer, 0, sizeof(self._buffer)) + self.get_variables_by_attributes = functools.lru_cache(maxsize=128)( + self._get_variables_by_attributes_uncached, + ) + # flag to indicate that Variables in this Dataset support orthogonal indexing. self.__orthogonal_indexing__ = True if diskless and __netcdf4libversion__ < '4.2.1': @@ -3333,9 +3338,9 @@ of existing (sub-) groups and their variables. for group in groups: group.set_ncstring_attrs(value) # recurse into subgroups... - def get_variables_by_attributes(self, **kwargs): + def _get_variables_by_attributes_uncached(self, **kwargs): """ -**`get_variables_by_attribute(self, **kwargs)`** +**`get_variables_by_attributes(self, **kwargs)`** Returns a list of variables that match specific conditions. @@ -6913,6 +6918,9 @@ Example usage (See `MFDataset.__init__` for more details): else: return Dataset.__getattribute__(self, name) + def get_variables_by_attributes(self, **kwargs): + return Dataset._get_variables_by_attributes_uncached(self, **kwargs) + def ncattrs(self): """ **`ncattrs(self)`** From b739cccfa40e95ce4002444073f3b11730f03c0b Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 22 May 2023 10:38:28 -0300 Subject: [PATCH 0989/1504] clear cache --- src/netCDF4/_netCDF4.pyx | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 3943c320d..3d7cd8972 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2622,7 +2622,9 @@ Is the Dataset open or closed? return bool(self._isopen) def __dealloc__(self): - # close file when there are no references to object left + # close file when there are no references to object left and clear the cache. + if self.get_variables_by_attributes: + self.get_variables_by_attributes.cache_clear() if self._isopen: self._close(False) From 91af6c591ec154c6a56dc3ca4e9726715d30918a Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 22 May 2023 11:27:49 -0300 Subject: [PATCH 0990/1504] decorate the class method --- src/netCDF4/_netCDF4.pyx | 12 +++--------- 1 file changed, 3 insertions(+), 9 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 3d7cd8972..12dc3ec6a 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2100,7 +2100,7 @@ strings. cdef Py_buffer _buffer cdef public groups, dimensions, variables, disk_format, path, parent,\ file_format, data_model, cmptypes, vltypes, enumtypes, __orthogonal_indexing__, \ - keepweakref, _ncstring_attrs__, get_variables_by_attributes + keepweakref, _ncstring_attrs__ def __init__(self, filename, mode='r', clobber=True, format='NETCDF4', diskless=False, persist=False, keepweakref=False, @@ -2212,10 +2212,6 @@ strings. memset(&self._buffer, 0, sizeof(self._buffer)) - self.get_variables_by_attributes = functools.lru_cache(maxsize=128)( - self._get_variables_by_attributes_uncached, - ) - # flag to indicate that Variables in this Dataset support orthogonal indexing. self.__orthogonal_indexing__ = True if diskless and __netcdf4libversion__ < '4.2.1': @@ -3340,7 +3336,8 @@ of existing (sub-) groups and their variables. for group in groups: group.set_ncstring_attrs(value) # recurse into subgroups... - def _get_variables_by_attributes_uncached(self, **kwargs): + @functools.lru_cache(maxsize=128) + def get_variables_by_attributes(self, **kwargs): """ **`get_variables_by_attributes(self, **kwargs)`** @@ -6920,9 +6917,6 @@ Example usage (See `MFDataset.__init__` for more details): else: return Dataset.__getattribute__(self, name) - def get_variables_by_attributes(self, **kwargs): - return Dataset._get_variables_by_attributes_uncached(self, **kwargs) - def ncattrs(self): """ **`ncattrs(self)`** From 41b74cc3936ccf5799f30ec44acb7e5f8c138793 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Tue, 23 May 2023 04:05:44 +0000 Subject: [PATCH 0991/1504] Bump mamba-org/provision-with-micromamba from 15 to 16 Bumps [mamba-org/provision-with-micromamba](https://github.com/mamba-org/provision-with-micromamba) from 15 to 16. - [Release notes](https://github.com/mamba-org/provision-with-micromamba/releases) - [Commits](https://github.com/mamba-org/provision-with-micromamba/compare/v15...v16) --- updated-dependencies: - dependency-name: mamba-org/provision-with-micromamba dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- .github/workflows/miniconda.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index 38f92c34d..489a23879 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -24,7 +24,7 @@ jobs: - uses: actions/checkout@v3 - name: Setup Micromamba - uses: mamba-org/provision-with-micromamba@v15 + uses: mamba-org/provision-with-micromamba@v16 with: environment-file: false From c474baa6d2a125a0afa5b00b6182dd6b49064307 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 23 May 2023 15:45:09 -0600 Subject: [PATCH 0992/1504] Update tst_dap.py --- test/tst_dap.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/test/tst_dap.py b/test/tst_dap.py index 9aeec4750..2b033e93a 100644 --- a/test/tst_dap.py +++ b/test/tst_dap.py @@ -7,10 +7,8 @@ # test accessing data over http with opendap. yesterday = datetime.utcnow() - timedelta(days=1) - URL = f'http://nomads.ncep.noaa.gov/dods/gfs_1p00/gfs{yesterday:%Y%m%d}/gfs_1p00_00z' URL_https = 'https://www.neracoos.org/erddap/griddap/WW3_EastCoast_latest' - varname = 'hgtsfc' data_min = -40; data_max = 5900 varshape = (181, 360) @@ -38,6 +36,5 @@ def runTest(self): assert(ncfile['hs'].long_name=='Significant Wave Height') ncfile.close() - if __name__ == '__main__': unittest.main() From 412fbb33071f19d010cc94e27d3a56837401ebc0 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Wed, 24 May 2023 10:36:28 -0300 Subject: [PATCH 0993/1504] opening, calling gba, and closing, multiple times --- test/tst_multiple_open_close.py | 51 +++++++++++++++++++++++++++++++++ 1 file changed, 51 insertions(+) create mode 100644 test/tst_multiple_open_close.py diff --git a/test/tst_multiple_open_close.py b/test/tst_multiple_open_close.py new file mode 100644 index 000000000..ea592ed9c --- /dev/null +++ b/test/tst_multiple_open_close.py @@ -0,0 +1,51 @@ +import os +import tracemalloc +import unittest + +import netCDF4 + +class MultipleVariablesByAttributesCallsTests(unittest.TestCase): + + + def test_multiple_calls(self): + netcdf_file = os.path.join(os.path.dirname(__file__), "netcdf_dummy_file.nc") + snapshot = tracemalloc.take_snapshot() + + # k_times = 1000_000 + k_times = 10 + for _k in range(k_times): + nc = netCDF4.Dataset(netcdf_file) + + vs = nc.get_variables_by_attributes(axis='Z') + self.assertEqual(len(vs), 1) + + vs = nc.get_variables_by_attributes(units='m/s') + self.assertEqual(len(vs), 4) + + vs = nc.get_variables_by_attributes(axis='Z', units='m') + self.assertEqual(len(vs), 1) + + vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T']) + self.assertEqual(len(vs), 1) + + vs = nc.get_variables_by_attributes(grid_mapping=lambda v: v is not None) + self.assertEqual(len(vs), 12) + + vs = nc.get_variables_by_attributes(grid_mapping=lambda v: v is not None, long_name=lambda v: v is not None and 'Upward (w) velocity' in v) + self.assertEqual(len(vs), 1) + + vs = nc.get_variables_by_attributes(units='m/s', grid_mapping=lambda v: v is not None) + self.assertEqual(len(vs), 4) + + vs = nc.get_variables_by_attributes(grid_mapping=lambda v: v is not None, long_name='Upward (w) velocity') + self.assertEqual(len(vs), 1) + nc.close() + stats = tracemalloc.take_snapshot().compare_to(snapshot, 'filename') + print("[ Top 10 differences ]") + for stat in stats[:10]: + print(stat) + +if __name__ == '__main__': + tracemalloc.start() + unittest.main() + tracemalloc.stop() From e83c2080157122d8b95a03a1be4498bf9894710e Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Wed, 24 May 2023 12:33:28 -0300 Subject: [PATCH 0994/1504] move inside the function --- test/tst_multiple_open_close.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/test/tst_multiple_open_close.py b/test/tst_multiple_open_close.py index ea592ed9c..46647d0b3 100644 --- a/test/tst_multiple_open_close.py +++ b/test/tst_multiple_open_close.py @@ -9,9 +9,9 @@ class MultipleVariablesByAttributesCallsTests(unittest.TestCase): def test_multiple_calls(self): netcdf_file = os.path.join(os.path.dirname(__file__), "netcdf_dummy_file.nc") + tracemalloc.start() snapshot = tracemalloc.take_snapshot() - # k_times = 1000_000 k_times = 10 for _k in range(k_times): nc = netCDF4.Dataset(netcdf_file) @@ -41,11 +41,10 @@ def test_multiple_calls(self): self.assertEqual(len(vs), 1) nc.close() stats = tracemalloc.take_snapshot().compare_to(snapshot, 'filename') + tracemalloc.stop() print("[ Top 10 differences ]") for stat in stats[:10]: print(stat) -if __name__ == '__main__': - tracemalloc.start() +if __name__ == '__main__': unittest.main() - tracemalloc.stop() From e08f7bd75f02c2ef03f313fb4d809414c073d0fb Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Wed, 24 May 2023 14:12:10 -0300 Subject: [PATCH 0995/1504] don't run memory leak test --- test/run_all.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/test/run_all.py b/test/run_all.py index f2ff97a18..199bf0676 100755 --- a/test/run_all.py +++ b/test/run_all.py @@ -57,6 +57,11 @@ test_files.remove('tst_cdl.py'); sys.stdout.write('not running tst_cdl.py ...\n') +# Don't run computationally intensive test +if os.getenv('MEMORY_LEAK_TEST'): + test_files.remove('tst_multiple_open_close.py'); + sys.stdout.write('not running tst_multiple_open_close.py ...\n') + # Build the test suite from the tests found in the test files. testsuite = unittest.TestSuite() for f in test_files: From 60cd3a0016e265e6ac738c2473e0de59a1be8737 Mon Sep 17 00:00:00 2001 From: Filipe Date: Wed, 24 May 2023 18:47:41 -0300 Subject: [PATCH 0996/1504] fix copy-n-pasta --- test/run_all.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/test/run_all.py b/test/run_all.py index 199bf0676..91c4b54ea 100755 --- a/test/run_all.py +++ b/test/run_all.py @@ -58,7 +58,7 @@ sys.stdout.write('not running tst_cdl.py ...\n') # Don't run computationally intensive test -if os.getenv('MEMORY_LEAK_TEST'): +if not os.getenv('MEMORY_LEAK_TEST'): test_files.remove('tst_multiple_open_close.py'); sys.stdout.write('not running tst_multiple_open_close.py ...\n') From 391d18b962ccd9fe2675652f3544562c61f22e65 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Thu, 25 May 2023 11:16:26 -0300 Subject: [PATCH 0997/1504] provision-with-micromamba is depreacted --- .github/workflows/miniconda.yml | 46 +++++++++++++-------------------- 1 file changed, 18 insertions(+), 28 deletions(-) diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index 489a23879..30b336804 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -24,29 +24,24 @@ jobs: - uses: actions/checkout@v3 - name: Setup Micromamba - uses: mamba-org/provision-with-micromamba@v16 + uses: mamba-org/setup-micromamba@v1 with: - environment-file: false + environment-name: TEST + init-shell: bash + create-args: >- + python=${{ matrix.python-version }} + numpy cython pip pytest hdf5 libnetcdf cftime zlib + --channel conda-forge - - name: Python ${{ matrix.python-version }} + - name: Install netcdf4-python shell: bash -l {0} run: | - micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest hdf5 libnetcdf cftime zlib --channel conda-forge - micromamba activate TEST export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config - pip install -v -e . --no-deps --force-reinstall - - - name: Debug conda - shell: bash -l {0} - run: | - micromamba activate TEST - micromamba info --all - micromamba list + python -m pip install -v -e . --no-deps --force-reinstall - name: Tests shell: bash -l {0} run: | - micromamba activate TEST cd test && python run_all.py run-mpi: @@ -60,30 +55,25 @@ jobs: - uses: actions/checkout@v3 - name: Setup Micromamba - uses: mamba-org/provision-with-micromamba@main + uses: mamba-org/setup-micromamba@v1 with: - environment-file: false + environment-name: TEST + init-shell: bash + create-args: >- + python=${{ matrix.python-version }} + numpy cython pip pytest mpi4py hdf5=*=mpi* libnetcdf=*=mpi* cftime zlib + --channel conda-forge - - name: Python ${{ matrix.python-version }} + - name: Install netcdf4-python with mpi shell: bash -l {0} run: | - micromamba create --name TEST python=${{ matrix.python-version }} numpy cython pip pytest mpi4py hdf5=*=mpi* libnetcdf=*=mpi* cftime zlib --channel conda-forge - micromamba activate TEST export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config nc-config --all - pip install -v -e . --no-build-isolation --no-deps --force-reinstall - - - name: Debug conda - shell: bash -l {0} - run: | - micromamba activate TEST - micromamba info --all - micromamba list + python -m pip install -v -e . --no-build-isolation --no-deps --force-reinstall - name: Tests shell: bash -l {0} run: | - micromamba activate TEST cd test && python run_all.py cd ../examples export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" From d04e258cae7dad0ed65b9a517dc72d0db020ea9f Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Thu, 25 May 2023 15:59:49 -0300 Subject: [PATCH 0998/1504] fix URL --- examples/reading_netCDF.ipynb | 227 +++++++++++++++------------------- 1 file changed, 98 insertions(+), 129 deletions(-) diff --git a/examples/reading_netCDF.ipynb b/examples/reading_netCDF.ipynb index 9e8070a6f..670b06340 100644 --- a/examples/reading_netCDF.ipynb +++ b/examples/reading_netCDF.ipynb @@ -41,9 +41,8 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 1, "metadata": { - "collapsed": false, "internals": { "frag_number": 2, "slide_helper": "subslide_end" @@ -79,9 +78,8 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 2, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 4, @@ -97,7 +95,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "\n", + "\n", "root group (NETCDF4_CLASSIC data model, file format HDF5):\n", " Conventions: CF-1.0\n", " title: HYCOM ATLb2.00\n", @@ -106,9 +104,8 @@ " experiment: 90.9\n", " history: archv2ncdf3z\n", " dimensions(sizes): MT(1), Y(850), X(712), Depth(10)\n", - " variables(dimensions): float64 \u001b[4mMT\u001b[0m(MT), float64 \u001b[4mDate\u001b[0m(MT), float32 \u001b[4mDepth\u001b[0m(Depth), int32 \u001b[4mY\u001b[0m(Y), int32 \u001b[4mX\u001b[0m(X), float32 \u001b[4mLatitude\u001b[0m(Y,X), float32 \u001b[4mLongitude\u001b[0m(Y,X), float32 \u001b[4mu\u001b[0m(MT,Depth,Y,X), float32 \u001b[4mv\u001b[0m(MT,Depth,Y,X), float32 \u001b[4mtemperature\u001b[0m(MT,Depth,Y,X), float32 \u001b[4msalinity\u001b[0m(MT,Depth,Y,X)\n", - " groups: \n", - "\n" + " variables(dimensions): float64 MT(MT), float64 Date(MT), float32 Depth(Depth), int32 Y(Y), int32 X(X), float32 Latitude(Y, X), float32 Longitude(Y, X), float32 u(MT, Depth, Y, X), float32 v(MT, Depth, Y, X), float32 temperature(MT, Depth, Y, X), float32 salinity(MT, Depth, Y, X)\n", + " groups: \n" ] } ], @@ -138,9 +135,8 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 3, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 6, @@ -156,14 +152,14 @@ "name": "stdout", "output_type": "stream", "text": [ - "[u'MT', u'Date', u'Depth', u'Y', u'X', u'Latitude', u'Longitude', u'u', u'v', u'temperature', u'salinity']\n", - "\n", + "dict_keys(['MT', 'Date', 'Depth', 'Y', 'X', 'Latitude', 'Longitude', 'u', 'v', 'temperature', 'salinity'])\n", + "\n", "float32 temperature(MT, Depth, Y, X)\n", " coordinates: Longitude Latitude Date\n", " standard_name: sea_water_potential_temperature\n", " units: degC\n", - " _FillValue: 1.26765e+30\n", - " valid_range: [ -5.07860279 11.14989948]\n", + " _FillValue: 1.2676506e+30\n", + " valid_range: [-5.078603 11.1498995]\n", " long_name: temp [90.9H]\n", "unlimited dimensions: MT\n", "current shape = (1, 10, 850, 712)\n", @@ -199,9 +195,8 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 4, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 8 @@ -215,14 +210,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "(u'MT', (unlimited): name = 'MT', size = 1\n", - ")\n", - "(u'Y', : name = 'Y', size = 850\n", - ")\n", - "(u'X', : name = 'X', size = 712\n", - ")\n", - "(u'Depth', : name = 'Depth', size = 10\n", - ")\n" + "('MT', (unlimited): name = 'MT', size = 1)\n", + "('Y', : name = 'Y', size = 850)\n", + "('X', : name = 'X', size = 712)\n", + "('Depth', : name = 'Depth', size = 10)\n" ] } ], @@ -248,9 +239,8 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 5, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 10 @@ -263,10 +253,10 @@ { "data": { "text/plain": [ - "(u'MT', u'Depth', u'Y', u'X')" + "('MT', 'Depth', 'Y', 'X')" ] }, - "execution_count": 9, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -277,9 +267,8 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 6, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 11, @@ -297,7 +286,7 @@ "(1, 10, 850, 712)" ] }, - "execution_count": 10, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -326,9 +315,8 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 7, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 13, @@ -344,7 +332,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "\n", + "\n", "float64 MT(MT)\n", " long_name: time\n", " units: days since 1900-12-31 00:00:00\n", @@ -352,16 +340,14 @@ " axis: T\n", "unlimited dimensions: MT\n", "current shape = (1,)\n", - "filling on, default _FillValue of 9.96920996839e+36 used\n", - "\n", - "\n", + "filling on, default _FillValue of 9.969209968386869e+36 used\n", + "\n", "int32 X(X)\n", " point_spacing: even\n", " axis: X\n", "unlimited dimensions: \n", "current shape = (712,)\n", - "filling on, default _FillValue of -2147483647 used\n", - "\n" + "filling on, default _FillValue of -2147483647 used\n" ] } ], @@ -395,9 +381,8 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 8, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 15 @@ -411,7 +396,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "[ 41023.25]\n" + "[41023.25]\n" ] } ], @@ -422,9 +407,8 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 9, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 16 @@ -438,7 +422,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "[ 0. 100. 200. 400. 700. 1000. 2000. 3000. 4000. 5000.]\n" + "[ 0. 100. 200. 400. 700. 1000. 2000. 3000. 4000. 5000.]\n" ] } ], @@ -449,9 +433,8 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 10, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 17, @@ -501,9 +484,8 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 11, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 19 @@ -517,14 +499,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "\n", + "\n", "float32 Latitude(Y, X)\n", " standard_name: latitude\n", " units: degrees_north\n", "unlimited dimensions: \n", "current shape = (850, 712)\n", - "filling on, default _FillValue of 9.96920996839e+36 used\n", - "\n" + "filling on, default _FillValue of 9.969209968386869e+36 used\n" ] } ], @@ -552,9 +533,8 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 12, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 20, @@ -636,9 +616,8 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 13, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 25, @@ -707,9 +686,8 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 14, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 28, @@ -725,7 +703,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "http://thredds.ucar.edu/thredds/dodsC/grib/NCEP/GFS/Global_0p5deg/GFS_Global_0p5deg_20150711_0600.grib2/GC\n" + "https://thredds.ucar.edu/thredds/dodsC/grib/NCEP/GFS/Global_0p5deg/GFS_Global_0p5deg_20230525_1200.grib2/GC\n" ] } ], @@ -733,7 +711,7 @@ "import datetime\n", "date = datetime.datetime.now()\n", "# build URL for latest synoptic analysis time\n", - "URL = 'http://thredds.ucar.edu/thredds/dodsC/grib/NCEP/GFS/Global_0p5deg/GFS_Global_0p5deg_%04i%02i%02i_%02i%02i.grib2/GC' %\\\n", + "URL = 'https://thredds.ucar.edu/thredds/dodsC/grib/NCEP/GFS/Global_0p5deg/GFS_Global_0p5deg_%04i%02i%02i_%02i%02i.grib2/GC' %\\\n", "(date.year,date.month,date.day,6*(date.hour//6),0)\n", "# keep moving back 6 hours until a valid URL found\n", "validURL = False; ncount = 0\n", @@ -749,9 +727,8 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 15, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 28, @@ -768,52 +745,50 @@ "name": "stdout", "output_type": "stream", "text": [ - "\n", - "float32 Temperature_surface(time2, lat, lon)\n", + "\n", + "float32 Temperature_surface(time1, lat, lon)\n", " long_name: Temperature @ Ground or water surface\n", " units: K\n", " abbreviation: TMP\n", " missing_value: nan\n", " grid_mapping: LatLon_Projection\n", - " coordinates: reftime time2 lat lon \n", + " coordinates: reftime time1 lat lon \n", " Grib_Variable_Id: VAR_0-0-0_L1\n", " Grib2_Parameter: [0 0 0]\n", " Grib2_Parameter_Discipline: Meteorological products\n", " Grib2_Parameter_Category: Temperature\n", " Grib2_Parameter_Name: Temperature\n", - " Grib2_Level_Type: Ground or water surface\n", + " Grib2_Level_Type: 1\n", + " Grib2_Level_Desc: Ground or water surface\n", " Grib2_Generating_Process_Type: Forecast\n", + " Grib2_Statistical_Process_Type: UnknownStatType--1\n", "unlimited dimensions: \n", - "current shape = (93, 361, 720)\n", + "current shape = (129, 361, 720)\n", "filling off\n", - "\n", - "\n", - "float64 time2(time2)\n", - " units: Hour since 2015-07-11T06:00:00Z\n", + "\n", + "float64 time1(time1)\n", + " units: Hour since 2023-05-25T12:00:00Z\n", " standard_name: time\n", " long_name: GRIB forecast or observation time\n", " calendar: proleptic_gregorian\n", " _CoordinateAxisType: Time\n", "unlimited dimensions: \n", - "current shape = (93,)\n", + "current shape = (129,)\n", "filling off\n", - "\n", - "\n", + "\n", "float32 lat(lat)\n", " units: degrees_north\n", " _CoordinateAxisType: Lat\n", "unlimited dimensions: \n", "current shape = (361,)\n", "filling off\n", - "\n", - "\n", + "\n", "float32 lon(lon)\n", " units: degrees_east\n", " _CoordinateAxisType: Lon\n", "unlimited dimensions: \n", "current shape = (720,)\n", - "filling off\n", - "\n" + "filling off\n" ] } ], @@ -849,9 +824,8 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 16, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 31 @@ -870,9 +844,9 @@ }, { "data": { - "image/png": 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srtQc+rK6FnmQkJdulS8C+CAz/1L/jYv4Rd/F7efC61OsuaZbq7EvZ8XpMLlW\nV2Jqy26oVxQRcaFvqhJtmalz9f9q5Cjtw+b/Pso8FCHuqCofOYjoHBQi/jlm/kq5+AQRnc/MTxHR\nBQCeLpc/AWCntvnF5bJpHj609fnX9wDn7aksbFt8FyT0adjXa14st4oabGTuj1dAtG9+kFnThdkl\nJHe+q536ltO+eZ47vJ6NUVJ1HZRr5ex3/necWf4L4OFt3v15BwQREaHwgT/LzB/Sln+sXLZMRAcA\n7GBm1dm5gsIvfhGAewG8mo2DTEwsgTAHf9NOANs+XEzs2zbyquFs4XXQ5/+M4ZPvegCPXhlzaUTC\n8Oj1Uk0d6JtWztV2zd9sRkvKKEPL1Xc3pXuOkZ1VrpU3AvgnAN5MRA+Uf9cA+CiAtxLRowB+r/wO\nZj4K4E4ARwF8A8D7TBE30U/A5Tdqkrc7yjRU+mTQPYg4MBnqGKOHX8RVSBF94FpVHa37Jp2bq6Xu\nG4iNwad6M29ELatZI2S70FSxmxj+8L57z3MYDp9DGYU8iDkoLaf6WOe8T79ye2JD9EvqukraWKk5\nDk6IVeY2qWclba3QBzHFN6f6GuO8B7PI9adKrSdSgNXu2842MMYplppFnnssa1NftnlvcrJ0hPzo\nUoBTr7vmudu0LlmLHJiebqyPnCO+ZWPATPDf5DxzsmoEAfDX89Trs6mDei72qjzwSQg5UG9ig6bi\nW9kBasaI9zztW0z0a9Sk88dW6VO3aIRxsbSwXHubqrf11DtCm07wUhlHPgRFTuNELvjexazCmRT6\nNVTxtbRvvrimK/5tRcSFITDrnS8NblPGmooiGYu8DjFiyq14Zg7KEV18Qy0R1+tn6q+lwjhpYpXP\nIkl0dtrwDQ4wCe38dGUcs5GzgJuYMxDZzs0cEm3DnHXIZqWrwR0Rii3MEH0bCrnWUZd2JulaCRFx\n20CAWCkyxyTiodTNtiYIuZKriPvI0rViI2RAkC7QUUZ+ZkLIDEFVYZ1mj3poFkVxyQhV9F1Hxjgu\nIkmL3EabGW1s27ks0DFa42bnsc39EdrBXCceXa0r7hYhRcY0KjlJi7yJSIdMLKx3+M2aG8E836rc\nzjEmarZtb8a3C8LQjKE+JtvZaU4LtZX9q9lUbiGiNEZrXMfs9AQmz9kUdnUdzU5OfVkVIdN7jcEi\nEtqRipDqOpGiHri0M0mLHCguorIKJ0RcF28jO6GJ2k5EvCAkUkf/c60fW3jHYBEJzaF9mJpTdmiK\nHOeJjGUccxLpAAARaUlEQVQJIFmLHHDEPttm6FFzdqrPLjzrzIKQA2GhiF0f14dY57OFemNrmkMp\nNrZ5M1PShuwscsAirqYQq+nc6k6/1uF0banTViibWimhQ49tgj+WuRoFO6lY467orhzqXtJC3giX\nSFuWq5uV0hO3D1RisiHOOyQpmi7m206uy3R0I0bd26Gs8Sn3rbZcJ3VjIn0h91nPum+8QYKrXGcU\niYFqQOYM5VUVNoao1tmHsuJFzIVQQi38qvVsKa9TJX0hB6bF3JWl0CXmeiepcsf49jej9FVRVedW\njBBHIX/0wIa+aBrinCrJDwhiXiSiNQ4SWyXYtomTAbfQZ5yuti2T4Yfzg76Z6BPwyiCi2SRWp6cr\nbUebFNgFaYp5Hha5z5oGqvOIh0SyCBPhh30eR7fGmmRsFPInZp3T02/k5B5pQ/IW+SZKjH3Ca4sx\nn2Fruw9oH1p1Rtq21S1zQWhKLNE2B8alSB4WuaKJ9RzokiFaE+FoQFfWu5rqqot9C4kS4e3Y5ToJ\n7pPJ9A29UsiJ6DNEdIKIHtaWHSKi40T0QPl3rfbbQSJ6jIgeIaKro5fY5V5pup4gCEmgJjiP2fFZ\naz9G35pu0adsjQNhFvlnAVxjLGMAH2fmK8q/bwAAEe0GcD2A3eU2nyCieFZ/E193JDEXf209iNaY\naK0IZ1T/HddQrdt3GYUE0dpxXUG3peQIdq849ENNkxhciIGoFFlm/jaAn1t+sp3cdQBWmfk5Zj4G\n4HEAV7Yp4EQDV3HjNQb9VFJD6EXMBaFblFVeB9eAHpegh8xFkINfXKeNtfx+InqIiD5NRDvKZRcC\nOK6tcxzARS2OUeATb9e6dbapEPOQDH7CFlbrus79EGYbo574kt/pYYamQKtcKepPj2Q5vX9+OpNq\nxq7YpkL+SQCXALgcwJMA/tiz7rBWbEQBETG3s+lGsblIQq592YjEvSK4aDOAxzlPb8bCbdJIyJn5\naS4B8ClsuU+eALBTW/XictkUZYep+tvTpBxebKM3Q0MXhTjINRUawLxIrrbqiguPPTI0lVGcRLRH\n10rXeo2EnIgu0L7+IwAqouWrAN5JRHNEdAmA1wD4rm0fzHxI+zvSpBxBBIqJGeq22UlHa5ybv6xP\n6lrR5voT/Q4i/EJJEzG3/eZaVkUqk5Ez8xFdK13rVQ4IIqJVAG8C8Coi+hmAfwtgDxFdjsJt8lMA\n7y0PepSI7gRwFMAZAO/jIRKeA/aZhBwVwxmvvCks4lIx2RRkVxphV/4bLWbf1rElQ/MFhaofRGts\n1iPbUH7faM6mYp7qkHyTpCeWKNaN4Dd1WHq+ASe6pSgW+TSVQq5wpVTwTNMn11kwcUWM6eJdJ69K\nqLinNigty4kloiERE91RdV1Dk52VpPA6KySIx81iRrX4IlnU8pDkXKmJuI98cq00pYE1Lvip/ZZk\nm9nJtk65vG3+FmGEBPafhGZPNMMUzW1zMyiSt8ibDBBwUgpKHZGQkMMtWo/A9I2+NRKeyWhPwUbs\n9ujaX27tPnkhb4XD8qsSCP13W3rVWWJi1iAluF1GlyjLPPMBGkJkSiNgaWG5schWhSrmlFvFJAsh\nb2SVRxKB3J7MMfE+8ERkhYxQ7djlN9fJza0CZCLkQqI0EfOanc6S30bQWT65BKBbAyvH/pn8hDxU\nPOrmW/GQ4xO6LZVD7dtc25rhiiLmgs7SwnL0fW4szJP6i77zHshPyOuixzk3dAfk+IRuTdV0eVXT\n70VGxFz4yMpNmyIeS8xzFm+dvIS8iXhYrL8qn/vm8ODVtZm0xoHAh5d+D0TMhS4x6pdysQgFecWR\ne0YEOlEWuQo9DOw4jRr2OAv4JsCWwVhCW1bXgJW4uxyDJa7IxiLfFFZbDhUbutUuoWzdEeIr18MJ\nG96LWY4eEgp0K3zqTXnGjYW8LPJQRLT7QX9DsvVDtOyb0JlVF5cwzR/tuxVAOhkKUyAbixwIdHd4\nREPcJQ2oM8uS7drLQ1VoCdEazz27C0CFVY7ZfXPLSsitiPtkOKqud8P7YcuDIQiA582srGuhFvqY\n/ONAhkJutaoDBGMmQwhbEu0Npqb/0pa8KGTCXGEGiDg+ZExkJ+RCz8R4y4lgmQszTM3645useSxx\n4yZZCnld61qs8bywWePA+F6HhQYEhrXOWifoOKNWNETE+yF0tqUQZq0RChWsrgGHd7XezZgNgSwt\n8lBExPuh6jq3vQ+n98+PuhEKflTEygSO4AZXR/nY68/ohJxXQOpv6LKMFf0ah15ntZ5rffGHC0EE\ndHLWmbtzLCQ/+bIwPMo1EuvhaHO1uPzip/fPy5vVjLPt5PrkRC+e0d1jrzcu7RQhFwZBF3PdgrLN\nuTj212LBjS7igGFdV+RemiUhr3StENFniOgEET2sLVsgonuI6FEiupuIdmi/HSSix4joESK6Ot4p\nCGPCbGRq+i1xsQhebHnxHcxStswQH/lnAVxjLDsA4B5mvhTAt8rvIKLdAK4HsLvc5hNENDo/vBAH\nU7Rtvs0u/ZvbTq6zafEJ6aFyj5/eP18rdfIYLXIXleGHzPxtItplLH47gDeVn+8AcASFmF8HYJWZ\nnwNwjIgeB3AlgPsjlVcYIfoADj0RUtcNUR2HELcPQBD6pmkc+XnMfKL8fALAeeXnCzEp2scBXNTw\nGMLI2ViYp+kc0/PR8067MDtYhUzRsmzO6sO49YAgZmYi8r2eyqurkDRzh9elQzVBtp1c59Ap3WY9\ns2lTIT9BROcz81NEdAGAp8vlTwDYqa13cblsCiI6pH09wsxHGpZFEBqxsTBP4iNPm+WTS51MtpwL\nRLQHwJ7K9ULCD0sf+deY+bfK7x8D8CwzLxPRAQA7mPlA2dm5gsIvfhGAewG8mo2DSPih4EIJa5dx\nwOoYSsjFGk8T10PWNjvQrFjkbcIPVwH8bwC/SUQ/I6J3A/gogLcS0aMAfq/8DmY+CuBOAEcBfAPA\n+0wRF4QhMcVBRDxd1L3xWeS8ApoVEfcRErWy1/HTWxzr3wbgtjaFEmYXFbnShTWui7gIeJ5Ix7Qd\nifEWkiN2Y9XjxWfZ3zoGZMCYndGnsRXyouvwseWTS2KNC6NDcq0Io0dcKnni6+yc1Xjxxp2dgiAI\nfSOusHqIa0UYPWKF54cvxr/wk0unp45Y5IIgJItrQJAM5JpELHJBEJJCF2mXa0XesiYRi1wQhKSo\nEmkR8WlEyAVBEDJHwg8FQUgOlw981q1xCT8UBCEbNhbmaWNhnpYWlmuFIM7S9G46YpELgpAsNst8\nlq1yl3ZK1IogCMmzsTBPN+OmUtRvHbYwCSIWuSAIySK+8knERy4IQnYoX/nQ5UgdscgFQRAyQSxy\nQRCEkSJCLgiCkDki5IIgCJkjQi4IgpA5IuSCIAiZI0IuCIKQOa1GdhLRMQDrAJ4H8BwzX0lECwC+\nAOA3ABwD8A5m/kXLcgqCIAgO2lrkDGAPM1/BzFeWyw4AuIeZLwXwrfK7IAiC0BExXCtmcPrbAdxR\nfr4DwO9HOIYgCILgoNXITiL6SwCnULhW/hMz/xkR/ZyZX1H+TgBOqu/adjKyUxCEqKwRTYjZ4gg1\npqvsh29k5ieJ6FwA9xDRI/qPzMxkXFxBEISYmAIOjFPEfbQScmZ+svz/DBF9GcCVAE4Q0fnM/BQR\nXQDgadu2RHRI+3qEmY+0KYuwhV6xVYVeI+JFZrL9Jgi5MnYRJ6I9APZUrtfUtUJELwVwFjP/kohe\nBuBuAP8OwFsAPMvMy0R0AMAOZj5gbJula8VWaRRdVp66x/Wt79uHa7s6xzAfFlXHFISmjF3Ebbi0\ns42QXwLgy+XXswF8npn/Qxl+eCeAvwVH+GFOQl5XFHWUqLWpXG2Onytjb4xCc6raw9jrTnQh76Iw\nqdCHeIZUuFkUcZOxN0yhPkO9GaeACDm2KkAMd0Rs9DINXZYcGHuDFbYw2+0sW+VZC7lPgEO3tSHi\nOR7G3HhnGbNzfpZFHEhQyB/q/ajCrDD2xjwrNDGuxnDvfed9GYAu4sgFITnqRN8IaTIrb8ixzlOE\nXJgZ2kYQCQXyoIxDzIeVCLkgCMH4xCcFKzrFh3Uf10WEXBg9qTXsronlW7aJYuiAr6FI7V73da1E\nyIXRklqj7oJYQuFKOCUpHeozxINOolaEUZKr6KRs7eZG33Wgj3snUSvCzJCjiIuAx2eW3iZEyAWh\nY2wD2kS4+yV2rvLU7p+4VgTBgiQ6E/SO3VQ6eV2uFRFyQRCETHAJeYw5OwVBEIQBESEXBEHIHBFy\nQRCEzBEhFwRByBwRckEQhMwRIRcEQcgcEXJBEITMESEXBEHIHBFyQRCEzOlEyInoGiJ6hIgeI6Kl\nLo4hCIIgFEQXciI6C8BhANcA2A1gLxG9NvZxhuB7QxegBVL2/sm13EC+Zc+13EC7sndhkV8J4HFm\nPsbMzwH4rwCu6+A4vfP9oQvQAil7/+RabiDfsudabqBd2bsQ8osA/Ez7frxcJgiCIHRAF0I+eKpH\nQRCEWSJ6Glsi+m0Ah5j5mvL7QQAvMPOyto6IvSAIQgN6yUdORGcD+D8A/j6AvwLwXQB7mfknUQ8k\nCIIgAOhgqjdmPkNE+wF8E8BZAD4tIi4IgtAdg8wQJAiCIMSj15GdqQ8UIqLPENEJInpYW7ZARPcQ\n0aNEdDcR7dB+O1ieyyNEdPUwpQaIaCcR3UdEPyaiHxHRBzIq+4uJ6DtE9GBZ9kO5lL0sy1lE9AAR\nfa38nku5jxHRWln275bLki87Ee0goruI6CdEdJSIrsqk3L9ZXmv1d4qIPhCt7Mzcyx8KN8vjAHYB\nOAfAgwBe29fxA8v4uwCuAPCwtuxjAP51+XkJwEfLz7vLczinPKfHAbxooHKfD+Dy8vPLUfRRvDaH\nspfleWn5/2wA9wO4KqOy/0sAnwfw1VzqS1menwJYMJYlX3YAdwB4j1ZftudQbuMcXgTgSQA7Y5W9\nz8L/XQB/rn0/AODA0BfVUs5dmBTyRwCcV34+H8Aj5eeDAJa09f4cwG8PXf6yLF8B8Jbcyg7gpQB+\ngGJQWfJlB3AxgHsBvBnA13KqL6WQv9JYlnTZS9H+S8vypMttKe/VAL4ds+x9ulZyHSh0HjOfKD+f\nAHBe+flCFOegSOJ8iGgXireK7yCTshPRi4joQRRlvJuZv4s8yv4fAfwrAC9oy3IoN1CM97iXiL5P\nRP+sXJZ62S8B8AwRfZaIfkhEf0ZEL0P65TZ5J4DV8nOUsvcp5Nn3qnLxaPSdx6DnSEQvB/BFAB9k\n5l/qv6VcdmZ+gZkvR2HhXkVErzN+T67sRPQPADzNzA8AmIrrBdIst8YbmfkKANcC+BdE9Lv6j4mW\n/WwArwfwCWZ+PYD/h+LNfqtQaZZ7EyKaA/APAfw387c2Ze9TyJ9A4RNS7MTkEydVThDR+QBARBcA\neLpcbp7PxeWyQSCic1CI+OeY+Svl4izKrmDmUwDuA/A2pF/2vwfg7UT0UxTW1e8R0eeQfrkBAMz8\nZPn/GQBfRuHOSr3sxwEcZ2aVX+ouFML+VOLl1rkWwA/K6w5EuuZ9Cvn3AbyGiHaVT6XrAXy1x+M3\n5asA/qD8/Aco/M9q+TuJaI6ILgHwGhSDn3qHiAjApwEcZeY/0X7KoeyvUj31RPQSAG8F8BMkXnZm\nvpGZdzLzJShelf8HM78r9XIDABG9lIh+rfz8MhQ+24eReNmZ+SkAPyOiS8tFbwHwYwBfQ8LlNtiL\nLbcKEOua9+zkvxZFRMXjAA4O3elgKd8qitGop1H4898NYAFFh9ajAO4GsENb/8byXB4B8LYBy/07\nKPy0DwJ4oPy7JpOy/xaAHwJ4CIWY/JtyefJl18rzJmxFrSRfbhS+5gfLvx+ptphJ2S9DkfH1IQBf\nQtEBmny5y7K8DMD/BfBr2rIoZZcBQYIgCJkjU70JgiBkjgi5IAhC5oiQC4IgZI4IuSAIQuaIkAuC\nIGSOCLkgCELmiJALgiBkjgi5IAhC5vx/oWJ9OHx0YTwAAAAASUVORK5CYII=\n", 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", "text/plain": [ - "" + "
    " ] }, "metadata": {}, @@ -931,9 +905,8 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 17, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 34 @@ -947,15 +920,17 @@ "name": "stdout", "output_type": "stream", "text": [ - "name of time dimension = time2\n", - "units = Hour since 2015-07-11T06:00:00Z, values = [ 0. 3. 6. 9. 12. 15. 18. 21. 24. 27. 30. 33.\n", - " 36. 39. 42. 45. 48. 51. 54. 57. 60. 63. 66. 69.\n", - " 72. 75. 78. 81. 84. 87. 90. 93. 96. 99. 102. 105.\n", - " 108. 111. 114. 117. 120. 123. 126. 129. 132. 135. 138. 141.\n", - " 144. 147. 150. 153. 156. 159. 162. 165. 168. 171. 174. 177.\n", - " 180. 183. 186. 189. 192. 195. 198. 201. 204. 207. 210. 213.\n", - " 216. 219. 222. 225. 228. 231. 234. 237. 240. 252. 264. 276.\n", - " 288. 300. 312. 324. 336. 348. 360. 372. 384.]\n" + "name of time dimension = time1\n", + "units = Hour since 2023-05-25T12:00:00Z, values = [ 0. 3. 6. 9. 12. 15. 18. 21. 24. 27. 30. 33. 36. 39.\n", + " 42. 45. 48. 51. 54. 57. 60. 63. 66. 69. 72. 75. 78. 81.\n", + " 84. 87. 90. 93. 96. 99. 102. 105. 108. 111. 114. 117. 120. 123.\n", + " 126. 129. 132. 135. 138. 141. 144. 147. 150. 153. 156. 159. 162. 165.\n", + " 168. 171. 174. 177. 180. 183. 186. 189. 192. 195. 198. 201. 204. 207.\n", + " 210. 213. 216. 219. 222. 225. 228. 231. 234. 237. 240. 243. 246. 249.\n", + " 252. 255. 258. 261. 264. 267. 270. 273. 276. 279. 282. 285. 288. 291.\n", + " 294. 297. 300. 303. 306. 309. 312. 315. 318. 321. 324. 327. 330. 333.\n", + " 336. 339. 342. 345. 348. 351. 354. 357. 360. 363. 366. 369. 372. 375.\n", + " 378. 381. 384.]\n" ] } ], @@ -969,9 +944,8 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 18, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 35, @@ -987,7 +961,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "['2015-07-11 06:00:00', '2015-07-11 09:00:00', '2015-07-11 12:00:00', '2015-07-11 15:00:00', '2015-07-11 18:00:00', '2015-07-11 21:00:00', '2015-07-12 00:00:00', '2015-07-12 03:00:00', '2015-07-12 06:00:00', '2015-07-12 09:00:00']\n" + "['2023-05-25 12:00:00', '2023-05-25 15:00:00', '2023-05-25 18:00:00', '2023-05-25 21:00:00', '2023-05-26 00:00:00', '2023-05-26 03:00:00', '2023-05-26 06:00:00', '2023-05-26 09:00:00', '2023-05-26 12:00:00', '2023-05-26 15:00:00']\n" ] } ], @@ -1014,9 +988,8 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 19, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 37 @@ -1030,8 +1003,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "2015-07-14 07:22:39.579246\n", - "index = 24, date = 2015-07-14 06:00:00\n" + "2023-05-28 15:57:27.760935\n", + "index = 25, date = 2023-05-28 15:00:00\n" ] } ], @@ -1061,9 +1034,8 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 20, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 39, @@ -1079,7 +1051,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Boulder forecast valid at 2015-07-14 06:00:00 UTC = 296.8 K\n" + "Boulder forecast valid at 2023-05-28 15:00:00 UTC = 297.6 K\n" ] } ], @@ -1113,9 +1085,8 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 21, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 41 @@ -1129,23 +1100,23 @@ "name": "stdout", "output_type": "stream", "text": [ - "-rw-r--r-- 1 jwhitaker staff 8985332 Jul 10 06:43 data/prmsl.2000.nc\r\n", - "-rw-r--r-- 1 jwhitaker staff 8968789 Jul 10 06:43 data/prmsl.2001.nc\r\n", - "-rw-r--r-- 1 jwhitaker staff 8972796 Jul 10 06:43 data/prmsl.2002.nc\r\n", - "-rw-r--r-- 1 jwhitaker staff 8974435 Jul 10 06:43 data/prmsl.2003.nc\r\n", - "-rw-r--r-- 1 jwhitaker staff 8997438 Jul 10 06:43 data/prmsl.2004.nc\r\n", - "-rw-r--r-- 1 jwhitaker staff 8976678 Jul 10 06:43 data/prmsl.2005.nc\r\n", - "-rw-r--r-- 1 jwhitaker staff 8969714 Jul 10 06:43 data/prmsl.2006.nc\r\n", - "-rw-r--r-- 1 jwhitaker staff 8974360 Jul 10 06:43 data/prmsl.2007.nc\r\n", - "-rw-r--r-- 1 jwhitaker staff 8994260 Jul 10 06:43 data/prmsl.2008.nc\r\n", - "-rw-r--r-- 1 jwhitaker staff 8974678 Jul 10 06:43 data/prmsl.2009.nc\r\n", - "-rw-r--r-- 1 jwhitaker staff 8970732 Jul 10 06:43 data/prmsl.2010.nc\r\n", - "-rw-r--r-- 1 jwhitaker staff 8976285 Jul 10 06:43 data/prmsl.2011.nc\r\n" + "-rw-rw-r-- 1 8985332 May 17 15:27 data/prmsl.2000.nc\r\n", + "-rw-rw-r-- 1 8968789 May 17 15:27 data/prmsl.2001.nc\r\n", + "-rw-rw-r-- 1 8972796 May 17 15:27 data/prmsl.2002.nc\r\n", + "-rw-rw-r-- 1 8974435 May 17 15:27 data/prmsl.2003.nc\r\n", + "-rw-rw-r-- 1 8997438 May 17 15:27 data/prmsl.2004.nc\r\n", + "-rw-rw-r-- 1 8976678 May 17 15:27 data/prmsl.2005.nc\r\n", + "-rw-rw-r-- 1 8969714 May 17 15:27 data/prmsl.2006.nc\r\n", + "-rw-rw-r-- 1 8974360 May 17 15:27 data/prmsl.2007.nc\r\n", + "-rw-rw-r-- 1 8994260 May 17 15:27 data/prmsl.2008.nc\r\n", + "-rw-rw-r-- 1 8974678 May 17 15:27 data/prmsl.2009.nc\r\n", + "-rw-rw-r-- 1 8970732 May 17 15:27 data/prmsl.2010.nc\r\n", + "-rw-rw-r-- 1 8976285 May 17 15:27 data/prmsl.2011.nc\r\n" ] } ], "source": [ - "!ls -l data/prmsl*nc" + "!ls -ldgG data/prmsl*nc" ] }, { @@ -1172,9 +1143,8 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 22, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 43, @@ -1193,7 +1163,7 @@ "starting date = 2000-01-01 00:00:00\n", "ending date = 2011-12-31 00:00:00\n", "times shape = 4383\n", - "prmsl dimensions = (u'time', u'lat', u'lon'), prmsl shape = (4383, 91, 180)\n" + "prmsl dimensions = ('time', 'lat', 'lon'), prmsl shape = (4383, 91, 180)\n" ] } ], @@ -1229,9 +1199,8 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 23, "metadata": { - "collapsed": false, "internals": { "frag_helper": "fragment_end", "frag_number": 45 @@ -1271,23 +1240,23 @@ "metadata": { "celltoolbar": "Raw Cell Format", "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3 (ipykernel)", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.9" + "pygments_lexer": "ipython3", + "version": "3.9.16" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } From 5fb16dd50d8609dd269b7e9a938fbc9fb883e104 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 30 May 2023 09:17:30 -0600 Subject: [PATCH 0999/1504] add certifi dep --- .github/workflows/miniconda.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index 30b336804..8db0307f1 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -30,7 +30,7 @@ jobs: init-shell: bash create-args: >- python=${{ matrix.python-version }} - numpy cython pip pytest hdf5 libnetcdf cftime zlib + numpy cython pip pytest hdf5 libnetcdf cftime zlib certifi --channel conda-forge - name: Install netcdf4-python @@ -61,7 +61,7 @@ jobs: init-shell: bash create-args: >- python=${{ matrix.python-version }} - numpy cython pip pytest mpi4py hdf5=*=mpi* libnetcdf=*=mpi* cftime zlib + numpy cython pip pytest mpi4py hdf5=*=mpi* libnetcdf=*=mpi* cftime zlib certifi --channel conda-forge - name: Install netcdf4-python with mpi From ddf810709687134534cae353cd92db6cea90e7c1 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 30 May 2023 09:19:42 -0600 Subject: [PATCH 1000/1504] update --- Changelog | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/Changelog b/Changelog index 44a74a395..1efad0da0 100644 --- a/Changelog +++ b/Changelog @@ -1,6 +1,5 @@ - - version 1.6.4 (not yet released) -================================= + version 1.6.4 (tag v1.6.4rel) +=============================== * set path to SSL certificates internally, so https DAP URLs work with wheels (issue #1246, requires nc_rc_set function available starting with netcdf-c 4.9.1, plus bugfix in netcdf-c PR #2690). From a79802db579acf6a69b35e902fe9eada9f30e1b6 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Wed, 31 May 2023 20:26:24 -0600 Subject: [PATCH 1001/1504] update --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index c11ca205d..2545bc101 100644 --- a/README.md +++ b/README.md @@ -10,7 +10,7 @@ ## News For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog). -?/?/2023: Version [1.6.4](https://pypi.python.org/pypi/netCDF4/1.6.4) released. Now requires +6/4/2023: Version [1.6.4](https://pypi.python.org/pypi/netCDF4/1.6.4) released. Now requires [certifi](https://github.com/certifi/python-certifi) to locate SSL certificates - this allows OpenDAP https URLs to work with linux wheels (issue [#1246](https://github.com/Unidata/netcdf4-python/issues/1246). From 53f1f43f78dd8eb2bc3d83420b2eb0ccd4cbb84e Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Mon, 5 Jun 2023 17:36:51 -0600 Subject: [PATCH 1002/1504] fix typo --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 2545bc101..aa53e7135 100644 --- a/README.md +++ b/README.md @@ -12,7 +12,7 @@ For details on the latest updates, see the [Changelog](https://github.com/Unidat 6/4/2023: Version [1.6.4](https://pypi.python.org/pypi/netCDF4/1.6.4) released. Now requires [certifi](https://github.com/certifi/python-certifi) to locate SSL certificates - this allows -OpenDAP https URLs to work with linux wheels (issue [#1246](https://github.com/Unidata/netcdf4-python/issues/1246). +OpenDAP https URLs to work with linux wheels (issue [#1246](https://github.com/Unidata/netcdf4-python/issues/1246)). 3/3/2023: Version [1.6.3](https://pypi.python.org/pypi/netCDF4/1.6.3) released. From 33bb4bf9cce5d2b62318f9d289acbd165ccd04a2 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 6 Jun 2023 12:47:35 -0600 Subject: [PATCH 1003/1504] update docs to use pip install instead of setup.py install --- src/netCDF4/_netCDF4.pyx | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 20287afe6..8ec816505 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -64,8 +64,7 @@ types) are not supported. so the extra compression algorithms available in netcdf-c >= 4.9.0 will automatically be available. Otherwise, the user will have to set `HDF5_PLUGIN_PATH` explicitly to have access to the extra compression plugins. - - run `python setup.py build`, then `python setup.py install` (as root if - necessary). + - run `pip install -v .` (as root if necessary) - run the tests in the 'test' directory by running `python run_all.py`. # Tutorial From 184264e7218a246e869b6dda6100f7b685dc239c Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 6 Jun 2023 13:28:12 -0600 Subject: [PATCH 1004/1504] add __pdoc__ var to suppress docs for utils --- src/netCDF4/__init__.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py index 2a38d621c..ac93047a2 100644 --- a/src/netCDF4/__init__.py +++ b/src/netCDF4/__init__.py @@ -14,6 +14,9 @@ import os __all__ =\ ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache','set_alignment','get_alignment'] +__pdoc__ = { + 'utils': False, +} # if HDF5_PLUGIN_PATH not set, point to package path if plugins live there pluginpath = os.path.join(__path__[0],'plugins') if 'HDF5_PLUGIN_PATH' not in os.environ and\ From 84db70a185d7ac9a4853b9bc2fc809c1fc7599b1 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 6 Jun 2023 13:28:35 -0600 Subject: [PATCH 1005/1504] update --- create_docs.sh | 13 +++---------- 1 file changed, 3 insertions(+), 10 deletions(-) diff --git a/create_docs.sh b/create_docs.sh index 295af7d8f..5f4148ba6 100644 --- a/create_docs.sh +++ b/create_docs.sh @@ -1,10 +1,3 @@ -# Uses pdoc (https://github.com/mitmproxy/pdoc) -# to create html docs from docstrings in Cython source. -pdoc -o 'docs' netCDF4 -# use resulting docs/netCDF4/_netCDF4.html -cp docs/netCDF4.html docs/index.html -sed -i -e 's!href="../netCDF4.html!href="./index.html!g' docs/index.html -sed -i -e 's!/../netCDF4.html!/index.html!g' docs/index.html -sed -i -e 's!._netCDF4 API! API!g' docs/index.html -sed -i -e 's!netCDF4._netCDF4!netCDF4!g' docs/index.html - +# use pdoc (https://pdoc3.github.io/pdoc/) to generate API docs +pdoc3 --html --config show_source_code=False --force -o 'docs' netCDF4 +/bin/cp -f docs/netCDF4/index.html docs/index.html From a98fd4279727610e4fca0395033522df2faaaa4d Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 6 Jun 2023 13:28:53 -0600 Subject: [PATCH 1006/1504] update --- docs/index.html | 6178 ++++++++++++++++++----------------------------- 1 file changed, 2347 insertions(+), 3831 deletions(-) diff --git a/docs/index.html b/docs/index.html index 49daf791d..35872a397 100644 --- a/docs/index.html +++ b/docs/index.html @@ -1,411 +1,31 @@ - - - - netCDF4 API documentation - - - - - - - + + + +netCDF4 API documentation + + + + + + + + + + - -
    -
    -

    -netCDF4

    - -

    Version 1.6.3

    - +
    +
    +
    +

    Package netCDF4

    +
    +
    +

    Version 1.6.4

    Introduction

    -

    netcdf4-python is a Python interface to the netCDF C library.

    -

    netCDF version 4 has many features not found in earlier versions of the library and is implemented on top of HDF5. This module can read and write @@ -413,30 +33,26 @@

    Introduction

    files that are readable by HDF5 clients. The API modelled after Scientific.IO.NetCDF, and should be familiar to users of that module.

    -

    Most new features of netCDF 4 are implemented, such as multiple -unlimited dimensions, groups and data compression. All the new +unlimited dimensions, groups and data compression. +All the new numeric data types (such as 64 bit and unsigned integer types) are implemented. Compound (struct), variable length (vlen) and enumerated (enum) data types are supported, but not the opaque data type. Mixtures of compound, vlen and enum data types (such as compound types containing enums, or vlens containing compound types) are not supported.

    -

    Quick Install

    -
      -
    • the easiest way to get going is to install via pip install netCDF4. +
    • the easiest way to get going is to install via pip install netCDF4. (or if you use the conda package manager conda install -c conda-forge netCDF4).
    -

    Developer Install

    -
    • Clone the github repository.
    • Make sure the dependencies are satisfied (Python 3.7 or later, -numpy, +numpy, Cython, cftime, setuptools, @@ -451,7 +67,8 @@

      Developer Install

    • If nc-config is not in your default PATH, you can set the NETCDF4_DIR environment variable and setup.py will look in $NETCDF4_DIR/bin. You can also use the file setup.cfg to set the path to nc-config, or -enter the paths to the libraries and include files manually. Just edit the setup.cfg file +enter the paths to the libraries and include files manually. Just +edit the setup.cfg file in a text editor and follow the instructions in the comments. To disable the use of nc-config, set the env var USE_NCCONFIG to 0. To disable the use of setup.cfg, set USE_SETUPCFG to 0. @@ -462,18 +79,17 @@

      Developer Install

      in any of the paths specified by environment variables, then standard locations (such as /usr and /usr/local) are searched.
    • if the env var NETCDF_PLUGIN_DIR is set to point to the location of the netcdf-c compression -plugins built by netcdf >= 4.9.0, they will be installed inside the package. In this +plugins built by netcdf >= 4.9.0, they will be installed inside the package. +In this case HDF5_PLUGIN_PATH will be set to the package installation path on import, so the extra compression algorithms available in netcdf-c >= 4.9.0 will automatically -be available. Otherwise, the user will have to set HDF5_PLUGIN_PATH explicitly +be available. +Otherwise, the user will have to set HDF5_PLUGIN_PATH explicitly to have access to the extra compression plugins.
      • -
    • run python setup.py build, then python setup.py install (as root if -necessary).
      • +
    • run pip install -v . (as root if necessary)
    • run the tests in the 'test' directory by running python run_all.py.
    -

    Tutorial

    - -

    Creating/Opening/Closing a netCDF file

    - -

    To create a netCDF file from python, you simply call the Dataset +

    To create a netCDF file from python, you simply call the Dataset constructor. This is also the method used to open an existing netCDF -file. If the file is open for write access (mode='w', 'r+' or 'a'), you may +file. +If the file is open for write access (mode='w', 'r+' or 'a'), you may write any type of data including new dimensions, groups, variables and -attributes. netCDF files come in five flavors (NETCDF3_CLASSIC, -NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF4_CLASSIC, and NETCDF4). +attributes. +netCDF files come in five flavors (NETCDF3_CLASSIC, +NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF4_CLASSIC<code>, and </code>NETCDF4). NETCDF3_CLASSIC was the original netcdf binary format, and was limited to file sizes less than 2 Gb. NETCDF3_64BIT_OFFSET was introduced in version 3.6.0 of the library, and extended the original binary format @@ -512,439 +128,359 @@

    Creating/Opening/Closing a netCDF not found in the version 3 API. They can be read by netCDF 3 clients only if they have been relinked against the netCDF 4 library. They can also be read by HDF5 clients. NETCDF4 files use the version 4 disk -format (HDF5) and use the new features of the version 4 API. The +format (HDF5) and use the new features of the version 4 API. +The netCDF4 module can read and write files in any of these formats. When creating a new file, the format may be specified using the format -keyword in the Dataset constructor. The default format is +keyword in the Dataset constructor. +The default format is NETCDF4. To see how a given file is formatted, you can examine the -data_model attribute. Closing the netCDF file is -accomplished via the Dataset.close method of the Dataset +data_model attribute. +Closing the netCDF file is +accomplished via the Dataset.close() method of the Dataset instance.

    -

    Here's an example:

    - -
    -
    >>> from netCDF4 import Dataset
->>> rootgrp = Dataset("test.nc", "w", format="NETCDF4")
->>> print(rootgrp.data_model)
-NETCDF4
->>> rootgrp.close()
+
    >>> from netCDF4 import Dataset
+>>> rootgrp = Dataset("test.nc", "w", format="NETCDF4")
+>>> print(rootgrp.data_model)
+NETCDF4
+>>> rootgrp.close()
 
    
-
    -

    Remote OPeNDAP-hosted datasets can be accessed for -reading over http if a URL is provided to the Dataset constructor instead of a -filename. However, this requires that the netCDF library be built with +reading over http if a URL is provided to the Dataset constructor instead of a +filename. +However, this requires that the netCDF library be built with OPenDAP support, via the --enable-dap configure option (added in version 4.0.1).

    -

    Groups in a netCDF file

    -

    netCDF version 4 added support for organizing data in hierarchical groups, which are analogous to directories in a filesystem. Groups serve as containers for variables, dimensions and attributes, as well as other -groups. A Dataset creates a special group, called +groups. +A Dataset creates a special group, called the 'root group', which is similar to the root directory in a unix -filesystem. To create Group instances, use the -Dataset.createGroup method of a Dataset or Group -instance. Dataset.createGroup takes a single argument, a -python string containing the name of the new group. The new Group +filesystem. +To create Group instances, use the +Dataset.createGroup() method of a Dataset or Group +instance. Dataset.createGroup() takes a single argument, a +python string containing the name of the new group. The new Group instances contained within the root group can be accessed by name using -the groups dictionary attribute of the Dataset instance. Only +the groups dictionary attribute of the Dataset instance. +Only NETCDF4 formatted files support Groups, if you try to create a Group in a netCDF 3 file you will get an error message.

    - -
    -
    >>> rootgrp = Dataset("test.nc", "a")
->>> fcstgrp = rootgrp.createGroup("forecasts")
->>> analgrp = rootgrp.createGroup("analyses")
->>> print(rootgrp.groups)
-{'forecasts': <class 'netCDF4.Group'>
-group /forecasts:
-    dimensions(sizes): 
-    variables(dimensions): 
-    groups: , 'analyses': <class 'netCDF4.Group'>
-group /analyses:
-    dimensions(sizes): 
-    variables(dimensions): 
-    groups: }
->>>
+
    >>> rootgrp = Dataset("test.nc", "a")
+>>> fcstgrp = rootgrp.createGroup("forecasts")
+>>> analgrp = rootgrp.createGroup("analyses")
+>>> print(rootgrp.groups)
+{'forecasts': <class 'netCDF4._netCDF4.Group'>
+group /forecasts:
+    dimensions(sizes):
+    variables(dimensions):
+    groups: , 'analyses': <class 'netCDF4._netCDF4.Group'>
+group /analyses:
+    dimensions(sizes):
+    variables(dimensions):
+    groups: }
+>>>
 
    
-
    - -

    Groups can exist within groups in a Dataset, just as directories -exist within directories in a unix filesystem. Each Group instance +

    Groups can exist within groups in a Dataset, just as directories +exist within directories in a unix filesystem. Each Group instance has a groups attribute dictionary containing all of the group -instances contained within that group. Each Group instance also has a +instances contained within that group. Each Group instance also has a path attribute that contains a simulated unix directory path to -that group. To simplify the creation of nested groups, you can -use a unix-like path as an argument to Dataset.createGroup.

    - -
    -
    >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
->>> fcstgrp2 = rootgrp.createGroup("/forecasts/model2")
+that group.
+To simplify the creation of nested groups, you can
+use a unix-like path as an argument to Dataset.createGroup().
    
+
    >>> fcstgrp1 = rootgrp.createGroup("/forecasts/model1")
+>>> fcstgrp2 = rootgrp.createGroup("/forecasts/model2")
 
    
-
    -

    If any of the intermediate elements of the path do not exist, they are created, just as with the unix command 'mkdir -p'. If you try to create a group that already exists, no error will be raised, and the existing group will be returned.

    -

    Here's an example that shows how to navigate all the groups in a -Dataset. The function walktree is a Python generator that is used -to walk the directory tree. Note that printing the Dataset or Group +Dataset. The function walktree is a Python generator that is used +to walk the directory tree. Note that printing the Dataset or Group object yields summary information about it's contents.

    - -
    -
    >>> def walktree(top):
-...     yield top.groups.values()
-...     for value in top.groups.values():
-...         yield from walktree(value)
->>> print(rootgrp)
-<class 'netCDF4.Dataset'>
-root group (NETCDF4 data model, file format HDF5):
-    dimensions(sizes): 
-    variables(dimensions): 
-    groups: forecasts, analyses
->>> for children in walktree(rootgrp):
-...     for child in children:
-...         print(child)
-<class 'netCDF4.Group'>
-group /forecasts:
-    dimensions(sizes): 
-    variables(dimensions): 
-    groups: model1, model2
-<class 'netCDF4.Group'>
-group /analyses:
-    dimensions(sizes): 
-    variables(dimensions): 
-    groups: 
-<class 'netCDF4.Group'>
-group /forecasts/model1:
-    dimensions(sizes): 
-    variables(dimensions): 
-    groups: 
-<class 'netCDF4.Group'>
-group /forecasts/model2:
-    dimensions(sizes): 
-    variables(dimensions): 
-    groups: 
+
    >>> def walktree(top):
+...     yield top.groups.values()
+...     for value in top.groups.values():
+...         yield from walktree(value)
+>>> print(rootgrp)
+<class 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes):
+    variables(dimensions):
+    groups: forecasts, analyses
+>>> for children in walktree(rootgrp):
+...     for child in children:
+...         print(child)
+<class 'netCDF4._netCDF4.Group'>
+group /forecasts:
+    dimensions(sizes):
+    variables(dimensions):
+    groups: model1, model2
+<class 'netCDF4._netCDF4.Group'>
+group /analyses:
+    dimensions(sizes):
+    variables(dimensions):
+    groups:
+<class 'netCDF4._netCDF4.Group'>
+group /forecasts/model1:
+    dimensions(sizes):
+    variables(dimensions):
+    groups:
+<class 'netCDF4._netCDF4.Group'>
+group /forecasts/model2:
+    dimensions(sizes):
+    variables(dimensions):
+    groups:
 
    
-
    -

    Dimensions in a netCDF file

    -

    netCDF defines the sizes of all variables in terms of dimensions, so before any variables can be created the dimensions they use must be created first. A special case, not often used in practice, is that of a scalar variable, which has no dimensions. A dimension is created using -the Dataset.createDimension method of a Dataset -or Group instance. A Python string is used to set the name of the +the Dataset.createDimension() method of a Dataset +or Group instance. A Python string is used to set the name of the dimension, and an integer value is used to set the size. To create an unlimited dimension (a dimension that can be appended to), the size value is set to None or 0. In this example, there both the time and -level dimensions are unlimited. Having more than one unlimited +level dimensions are unlimited. +Having more than one unlimited dimension is a new netCDF 4 feature, in netCDF 3 files there may be only one, and it must be the first (leftmost) dimension of the variable.

    - -
    -
    >>> level = rootgrp.createDimension("level", None)
->>> time = rootgrp.createDimension("time", None)
->>> lat = rootgrp.createDimension("lat", 73)
->>> lon = rootgrp.createDimension("lon", 144)
+
    >>> level = rootgrp.createDimension("level", None)
+>>> time = rootgrp.createDimension("time", None)
+>>> lat = rootgrp.createDimension("lat", 73)
+>>> lon = rootgrp.createDimension("lon", 144)
 
    
-
    - -

    All of the Dimension instances are stored in a python dictionary.

    - -
    -
    >>> print(rootgrp.dimensions)
-{'level': <class 'netCDF4.Dimension'> (unlimited): name = 'level', size = 0, 'time': <class 'netCDF4.Dimension'> (unlimited): name = 'time', size = 0, 'lat': <class 'netCDF4.Dimension'>: name = 'lat', size = 73, 'lon': <class 'netCDF4.Dimension'>: name = 'lon', size = 144}
+
    All of the Dimension instances are stored in a python dictionary.
    
+
    >>> print(rootgrp.dimensions)
+{'level': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0, 'time': <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0, 'lat': <class 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 73, 'lon': <class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144}
 
    
-
    - -

    Using the python len function with a Dimension instance returns +

    Using the python len function with a Dimension instance returns current size of that dimension. -Dimension.isunlimited method of a Dimension instance +Dimension.isunlimited() method of a Dimension instance be used to determine if the dimensions is unlimited, or appendable.

    - -
    -
    >>> print(len(lon))
-144
->>> print(lon.isunlimited())
-False
->>> print(time.isunlimited())
-True
+
    >>> print(len(lon))
+144
+>>> print(lon.isunlimited())
+False
+>>> print(time.isunlimited())
+True
 
    
-
    - -

    Printing the Dimension object +

    Printing the Dimension object provides useful summary info, including the name and length of the dimension, and whether it is unlimited.

    - -
    -
    >>> for dimobj in rootgrp.dimensions.values():
-...     print(dimobj)
-<class 'netCDF4.Dimension'> (unlimited): name = 'level', size = 0
-<class 'netCDF4.Dimension'> (unlimited): name = 'time', size = 0
-<class 'netCDF4.Dimension'>: name = 'lat', size = 73
-<class 'netCDF4.Dimension'>: name = 'lon', size = 144
+
    >>> for dimobj in rootgrp.dimensions.values():
+...     print(dimobj)
+<class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'level', size = 0
+<class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 0
+<class 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 73
+<class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144
 
    
-
    - -

    Dimension names can be changed using the -Datatset.renameDimension method of a Dataset or -Group instance.

    - +

    Dimension names can be changed using the +Datatset.renameDimension method of a Dataset or +Group instance.

    Variables in a netCDF file

    -

    netCDF variables behave much like python multidimensional array objects supplied by the numpy module. However, unlike numpy arrays, netCDF4 variables can be appended to along one or more 'unlimited' dimensions. To create a netCDF variable, use the -Dataset.createVariable method of a Dataset or -Group instance. The Dataset.createVariablej method +Dataset.createVariable() method of a Dataset or +Group instance. The Dataset.createVariable()j method has two mandatory arguments, the variable name (a Python string), and the variable datatype. The variable's dimensions are given by a tuple containing the dimension names (defined previously with -Dataset.createDimension). To create a scalar +Dataset.createDimension()). To create a scalar variable, simply leave out the dimensions keyword. The variable primitive datatypes correspond to the dtype attribute of a numpy array. You can specify the datatype as a numpy dtype object, or anything that -can be converted to a numpy dtype object. Valid datatype specifiers +can be converted to a numpy dtype object. +Valid datatype specifiers include: 'f4' (32-bit floating point), 'f8' (64-bit floating point), 'i4' (32-bit signed integer), 'i2' (16-bit signed integer), 'i8' (64-bit signed integer), 'i1' (8-bit signed integer), 'u1' (8-bit unsigned integer), 'u2' (16-bit unsigned integer), 'u4' (32-bit unsigned integer), 'u8' (64-bit unsigned -integer), or 'S1' (single-character string). The old Numeric +integer), or 'S1' (single-character string). +The old Numeric single-character typecodes ('f','d','h', 's','b','B','c','i','l'), corresponding to ('f4','f8','i2','i2','i1','i1','S1','i4','i4'), will also work. The unsigned integer types and the 64-bit integer type can only be used if the file format is NETCDF4.

    -

    The dimensions themselves are usually also defined as variables, called -coordinate variables. The Dataset.createVariable -method returns an instance of the Variable class whose methods can be +coordinate variables. The Dataset.createVariable() +method returns an instance of the Variable class whose methods can be used later to access and set variable data and attributes.

    - -
    -
    >>> times = rootgrp.createVariable("time","f8",("time",))
->>> levels = rootgrp.createVariable("level","i4",("level",))
->>> latitudes = rootgrp.createVariable("lat","f4",("lat",))
->>> longitudes = rootgrp.createVariable("lon","f4",("lon",))
->>> # two dimensions unlimited
->>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
->>> temp.units = "K"
+
    >>> times = rootgrp.createVariable("time","f8",("time",))
+>>> levels = rootgrp.createVariable("level","i4",("level",))
+>>> latitudes = rootgrp.createVariable("lat","f4",("lat",))
+>>> longitudes = rootgrp.createVariable("lon","f4",("lon",))
+>>> # two dimensions unlimited
+>>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
+>>> temp.units = "K"
 
    
-
    - -

    To get summary info on a Variable instance in an interactive session, +

    To get summary info on a Variable instance in an interactive session, just print it.

    - -
    -
    >>> print(temp)
-<class 'netCDF4.Variable'>
-float32 temp(time, level, lat, lon)
-    units: K
-unlimited dimensions: time, level
-current shape = (0, 0, 73, 144)
-filling on, default _FillValue of 9.969209968386869e+36 used
+
    >>> print(temp)
+<class 'netCDF4._netCDF4.Variable'>
+float32 temp(time, level, lat, lon)
+    units: K
+unlimited dimensions: time, level
+current shape = (0, 0, 73, 144)
+filling on, default _FillValue of 9.969209968386869e+36 used
 
    
-
    -

    You can use a path to create a Variable inside a hierarchy of groups.

    - -
    -
    >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
+
    >>> ftemp = rootgrp.createVariable("/forecasts/model1/temp","f4",("time","level","lat","lon",))
 
    
-
    -

    If the intermediate groups do not yet exist, they will be created.

    - -

    You can also query a Dataset or Group instance directly to obtain Group or -Variable instances using paths.

    - -
    -
    >>> print(rootgrp["/forecasts/model1"])  # a Group instance
-<class 'netCDF4.Group'>
-group /forecasts/model1:
-    dimensions(sizes): 
-    variables(dimensions): float32 temp(time,level,lat,lon)
-    groups: 
->>> print(rootgrp["/forecasts/model1/temp"])  # a Variable instance
-<class 'netCDF4.Variable'>
-float32 temp(time, level, lat, lon)
-path = /forecasts/model1
-unlimited dimensions: time, level
-current shape = (0, 0, 73, 144)
-filling on, default _FillValue of 9.969209968386869e+36 used
+
    You can also query a Dataset or Group instance directly to obtain Group or
+Variable instances using paths.
    
+
    >>> print(rootgrp["/forecasts/model1"])  # a Group instance
+<class 'netCDF4._netCDF4.Group'>
+group /forecasts/model1:
+    dimensions(sizes):
+    variables(dimensions): float32 temp(time,level,lat,lon)
+    groups:
+>>> print(rootgrp["/forecasts/model1/temp"])  # a Variable instance
+<class 'netCDF4._netCDF4.Variable'>
+float32 temp(time, level, lat, lon)
+path = /forecasts/model1
+unlimited dimensions: time, level
+current shape = (0, 0, 73, 144)
+filling on, default _FillValue of 9.969209968386869e+36 used
 
    
-
    - -

    All of the variables in the Dataset or Group are stored in a +

    All of the variables in the Dataset or Group are stored in a Python dictionary, in the same way as the dimensions:

    - -
    -
    >>> print(rootgrp.variables)
-{'time': <class 'netCDF4.Variable'>
-float64 time(time)
-unlimited dimensions: time
-current shape = (0,)
-filling on, default _FillValue of 9.969209968386869e+36 used, 'level': <class 'netCDF4.Variable'>
-int32 level(level)
-unlimited dimensions: level
-current shape = (0,)
-filling on, default _FillValue of -2147483647 used, 'lat': <class 'netCDF4.Variable'>
-float32 lat(lat)
-unlimited dimensions: 
-current shape = (73,)
-filling on, default _FillValue of 9.969209968386869e+36 used, 'lon': <class 'netCDF4.Variable'>
-float32 lon(lon)
-unlimited dimensions: 
-current shape = (144,)
-filling on, default _FillValue of 9.969209968386869e+36 used, 'temp': <class 'netCDF4.Variable'>
-float32 temp(time, level, lat, lon)
-    units: K
-unlimited dimensions: time, level
-current shape = (0, 0, 73, 144)
-filling on, default _FillValue of 9.969209968386869e+36 used}
+
    >>> print(rootgrp.variables)
+{'time': <class 'netCDF4._netCDF4.Variable'>
+float64 time(time)
+unlimited dimensions: time
+current shape = (0,)
+filling on, default _FillValue of 9.969209968386869e+36 used, 'level': <class 'netCDF4._netCDF4.Variable'>
+int32 level(level)
+unlimited dimensions: level
+current shape = (0,)
+filling on, default _FillValue of -2147483647 used, 'lat': <class 'netCDF4._netCDF4.Variable'>
+float32 lat(lat)
+unlimited dimensions:
+current shape = (73,)
+filling on, default _FillValue of 9.969209968386869e+36 used, 'lon': <class 'netCDF4._netCDF4.Variable'>
+float32 lon(lon)
+unlimited dimensions:
+current shape = (144,)
+filling on, default _FillValue of 9.969209968386869e+36 used, 'temp': <class 'netCDF4._netCDF4.Variable'>
+float32 temp(time, level, lat, lon)
+    units: K
+unlimited dimensions: time, level
+current shape = (0, 0, 73, 144)
+filling on, default _FillValue of 9.969209968386869e+36 used}
 
    
-
    - -

    Variable names can be changed using the -Dataset.renameVariable method of a Dataset +

    Variable names can be changed using the +Dataset.renameVariable() method of a Dataset instance.

    - -

    Variables can be sliced similar to numpy arrays, but there are some differences. See +

    Variables can be sliced similar to numpy arrays, but there are some differences. +See Writing data to and retrieving data from a netCDF variable for more details.

    -

    Attributes in a netCDF file

    -

    There are two types of attributes in a netCDF file, global and variable. Global attributes provide information about a group, or the entire -dataset, as a whole. Variable attributes provide information about +dataset, as a whole. Variable attributes provide information about one of the variables in a group. Global attributes are set by assigning -values to Dataset or Group instance variables. Variable -attributes are set by assigning values to Variable instances +values to Dataset or Group instance variables. Variable +attributes are set by assigning values to Variable instances variables. Attributes can be strings, numbers or sequences. Returning to our example,

    - -
    -
    >>> import time
->>> rootgrp.description = "bogus example script"
->>> rootgrp.history = "Created " + time.ctime(time.time())
->>> rootgrp.source = "netCDF4 python module tutorial"
->>> latitudes.units = "degrees north"
->>> longitudes.units = "degrees east"
->>> levels.units = "hPa"
->>> temp.units = "K"
->>> times.units = "hours since 0001-01-01 00:00:00.0"
->>> times.calendar = "gregorian"
+
    >>> import time
+>>> rootgrp.description = "bogus example script"
+>>> rootgrp.history = "Created " + time.ctime(time.time())
+>>> rootgrp.source = "netCDF4 python module tutorial"
+>>> latitudes.units = "degrees north"
+>>> longitudes.units = "degrees east"
+>>> levels.units = "hPa"
+>>> temp.units = "K"
+>>> times.units = "hours since 0001-01-01 00:00:00.0"
+>>> times.calendar = "gregorian"
 
    
-
    - -

    The Dataset.ncattrs method of a Dataset, Group or -Variable instance can be used to retrieve the names of all the netCDF +

    The Dataset.ncattrs() method of a Dataset, Group or +Variable instance can be used to retrieve the names of all the netCDF attributes. This method is provided as a convenience, since using the built-in dir Python function will return a bunch of private methods and attributes that cannot (or should not) be modified by the user.

    - -
    -
    >>> for name in rootgrp.ncattrs():
-...     print("Global attr {} = {}".format(name, getattr(rootgrp, name)))
-Global attr description = bogus example script
-Global attr history = Created Mon Jul  8 14:19:41 2019
-Global attr source = netCDF4 python module tutorial
+
    >>> for name in rootgrp.ncattrs():
+...     print("Global attr {} = {}".format(name, getattr(rootgrp, name)))
+Global attr description = bogus example script
+Global attr history = Created Mon Jul  8 14:19:41 2019
+Global attr source = netCDF4 python module tutorial
 
    
-
    - -

    The __dict__ attribute of a Dataset, Group or Variable +

    The __dict__ attribute of a Dataset, Group or Variable instance provides all the netCDF attribute name/value pairs in a python dictionary:

    - -
    -
    >>> print(rootgrp.__dict__)
-{'description': 'bogus example script', 'history': 'Created Mon Jul  8 14:19:41 2019', 'source': 'netCDF4 python module tutorial'}
+
    >>> print(rootgrp.__dict__)
+{'description': 'bogus example script', 'history': 'Created Mon Jul  8 14:19:41 2019', 'source': 'netCDF4 python module tutorial'}
 
    
-
    - -

    Attributes can be deleted from a netCDF Dataset, Group or -Variable using the python del statement (i.e. del grp.foo +

    Attributes can be deleted from a netCDF Dataset, Group or +Variable using the python del statement (i.e. del grp.foo removes the attribute foo the the group grp).

    -

    Writing data to and retrieving data from a netCDF variable

    - -

    Now that you have a netCDF Variable instance, how do you put data +

    Now that you have a netCDF Variable instance, how do you put data into it? You can just treat it like an array and assign data to a slice.

    - -
    -
    >>> import numpy as np
->>> lats =  np.arange(-90,91,2.5)
->>> lons =  np.arange(-180,180,2.5)
->>> latitudes[:] = lats
->>> longitudes[:] = lons
->>> print("latitudes =\n{}".format(latitudes[:]))
-latitudes =
-[-90.  -87.5 -85.  -82.5 -80.  -77.5 -75.  -72.5 -70.  -67.5 -65.  -62.5
- -60.  -57.5 -55.  -52.5 -50.  -47.5 -45.  -42.5 -40.  -37.5 -35.  -32.5
- -30.  -27.5 -25.  -22.5 -20.  -17.5 -15.  -12.5 -10.   -7.5  -5.   -2.5
-   0.    2.5   5.    7.5  10.   12.5  15.   17.5  20.   22.5  25.   27.5
-  30.   32.5  35.   37.5  40.   42.5  45.   47.5  50.   52.5  55.   57.5
-  60.   62.5  65.   67.5  70.   72.5  75.   77.5  80.   82.5  85.   87.5
-  90. ]
+
    >>> import numpy as np
+>>> lats =  np.arange(-90,91,2.5)
+>>> lons =  np.arange(-180,180,2.5)
+>>> latitudes[:] = lats
+>>> longitudes[:] = lons
+>>> print("latitudes =\n{}".format(latitudes[:]))
+latitudes =
+[-90.  -87.5 -85.  -82.5 -80.  -77.5 -75.  -72.5 -70.  -67.5 -65.  -62.5
+ -60.  -57.5 -55.  -52.5 -50.  -47.5 -45.  -42.5 -40.  -37.5 -35.  -32.5
+ -30.  -27.5 -25.  -22.5 -20.  -17.5 -15.  -12.5 -10.   -7.5  -5.   -2.5
+   0.    2.5   5.    7.5  10.   12.5  15.   17.5  20.   22.5  25.   27.5
+  30.   32.5  35.   37.5  40.   42.5  45.   47.5  50.   52.5  55.   57.5
+  60.   62.5  65.   67.5  70.   72.5  75.   77.5  80.   82.5  85.   87.5
+  90. ]
 
    
-
    - -

    Unlike NumPy's array objects, netCDF Variable +

    Unlike NumPy's array objects, netCDF Variable objects with unlimited dimensions will grow along those dimensions if you assign data outside the currently defined range of indices.

    - -
    -
    >>> # append along two unlimited dimensions by assigning to slice.
->>> nlats = len(rootgrp.dimensions["lat"])
->>> nlons = len(rootgrp.dimensions["lon"])
->>> print("temp shape before adding data = {}".format(temp.shape))
-temp shape before adding data = (0, 0, 73, 144)
->>>
->>> from numpy.random import uniform
->>> temp[0:5, 0:10, :, :] = uniform(size=(5, 10, nlats, nlons))
->>> print("temp shape after adding data = {}".format(temp.shape))
-temp shape after adding data = (5, 10, 73, 144)
->>>
->>> # levels have grown, but no values yet assigned.
->>> print("levels shape after adding pressure data = {}".format(levels.shape))
-levels shape after adding pressure data = (10,)
+
    >>> # append along two unlimited dimensions by assigning to slice.
+>>> nlats = len(rootgrp.dimensions["lat"])
+>>> nlons = len(rootgrp.dimensions["lon"])
+>>> print("temp shape before adding data = {}".format(temp.shape))
+temp shape before adding data = (0, 0, 73, 144)
+>>>
+>>> from numpy.random import uniform
+>>> temp[0:5, 0:10, :, :] = uniform(size=(5, 10, nlats, nlons))
+>>> print("temp shape after adding data = {}".format(temp.shape))
+temp shape after adding data = (5, 10, 73, 144)
+>>>
+>>> # levels have grown, but no values yet assigned.
+>>> print("levels shape after adding pressure data = {}".format(levels.shape))
+levels shape after adding pressure data = (10,)
 
    
-
    -

    Note that the size of the levels variable grows when data is appended along the level dimension of the variable temp, even though no data has yet been assigned to levels.

    - -
    -
    >>> # now, assign data to levels dimension variable.
->>> levels[:] =  [1000.,850.,700.,500.,300.,250.,200.,150.,100.,50.]
+
    >>> # now, assign data to levels dimension variable.
+>>> levels[:] =  [1000.,850.,700.,500.,300.,250.,200.,150.,100.,50.]
 
    
-
    -

    However, that there are some differences between NumPy and netCDF variable slicing rules. Slices behave as usual, being specified as a start:stop:step triplet. Using a scalar integer index i takes the ith element and reduces the rank of the output array by one. Boolean array and integer sequence indexing behaves differently for netCDF variables -than for numpy arrays. Only 1-d boolean arrays and integer sequences are +than for numpy arrays. +Only 1-d boolean arrays and integer sequences are allowed, and these indices work independently along each dimension (similar -to the way vector subscripts work in fortran). This means that

    - -
    -
    >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
-(4, 4)
+to the way vector subscripts work in fortran).
+This means that
    
+
    >>> temp[0, 0, [0,1,2,3], [0,1,2,3]].shape
+(4, 4)
 
    
-
    -

    returns an array of shape (4,4) when slicing a netCDF variable, but for a numpy array it returns an array of shape (4,). Similarly, a netCDF variable of shape (2,3,4,5) indexed @@ -956,126 +492,106 @@

    Writing data While this behaviour may cause some confusion for those used to NumPy's 'fancy indexing' rules, it provides a very powerful way to extract data from multidimensional netCDF variables by using logical operations on the dimension arrays to create slices.

    -

    For example,

    - -
    -
    >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
+
    >>> tempdat = temp[::2, [1,3,6], lats>0, lons>0]
 
    
-
    -

    will extract time indices 0,2 and 4, pressure levels 850, 500 and 200 hPa, all Northern Hemisphere latitudes and Eastern -Hemisphere longitudes, resulting in a numpy array of shape (3, 3, 36, 71).

    - -
    -
    >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
-shape of fancy temp slice = (3, 3, 36, 71)
+Hemisphere longitudes, resulting in a numpy array of shape
+(3, 3, 36, 71).
    
+
    >>> print("shape of fancy temp slice = {}".format(tempdat.shape))
+shape of fancy temp slice = (3, 3, 36, 71)
 
    
-
    -

    Special note for scalar variables: To extract data from a scalar variable -v with no associated dimensions, use numpy.asarray(v) or v[...]. +v with no associated dimensions, use numpy.asarray(v) or v[…]. The result will be a numpy scalar array.

    -

    By default, netcdf4-python returns numpy masked arrays with values equal to the missing_value or _FillValue variable attributes masked for primitive and enum data types. -The Dataset.set_auto_mask Dataset and Variable methods +The Dataset.set_auto_mask() Dataset and Variable methods can be used to disable this feature so that numpy arrays are always returned, with the missing values included. Prior to version 1.4.0 the default behavior was to only return masked arrays when the -requested slice contained missing values. This behavior can be recovered -using the Dataset.set_always_mask method. If a masked array is +requested slice contained missing values. +This behavior can be recovered +using the Dataset.set_always_mask() method. If a masked array is written to a netCDF variable, the masked elements are filled with the -value specified by the missing_value attribute. If the variable has +value specified by the missing_value attribute. +If the variable has no missing_value, the _FillValue is used instead.

    -

    Dealing with time coordinates

    - -

    Time coordinate values pose a special challenge to netCDF users. Most +

    Time coordinate values pose a special challenge to netCDF users. +Most metadata standards (such as CF) specify that time should be measure relative to a fixed date using a certain calendar, with units -specified like hours since YY-MM-DD hh:mm:ss. These units can be +specified like hours since YY-MM-DD hh:mm:ss. +These units can be awkward to deal with, without a utility to convert the values to and -from calendar dates. The functions num2date +from calendar dates. +The functions num2date and date2num are provided by cftime to do just that. Here's an example of how they can be used:

    - -
    -
    >>> # fill in times.
->>> from datetime import datetime, timedelta
->>> from cftime import num2date, date2num
->>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
->>> times[:] = date2num(dates,units=times.units,calendar=times.calendar)
->>> print("time values (in units {}):\n{}".format(times.units, times[:]))
-time values (in units hours since 0001-01-01 00:00:00.0):
-[17533104. 17533116. 17533128. 17533140. 17533152.]
->>> dates = num2date(times[:],units=times.units,calendar=times.calendar)
->>> print("dates corresponding to time values:\n{}".format(dates))
- [cftime.DatetimeGregorian(2001, 3, 1, 0, 0, 0, 0, has_year_zero=False)
-  cftime.DatetimeGregorian(2001, 3, 1, 12, 0, 0, 0, has_year_zero=False)
-  cftime.DatetimeGregorian(2001, 3, 2, 0, 0, 0, 0, has_year_zero=False)
-  cftime.DatetimeGregorian(2001, 3, 2, 12, 0, 0, 0, has_year_zero=False)
-  cftime.DatetimeGregorian(2001, 3, 3, 0, 0, 0, 0, has_year_zero=False)]
+
    >>> # fill in times.
+>>> from datetime import datetime, timedelta
+>>> from cftime import num2date, date2num
+>>> dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])]
+>>> times[:] = date2num(dates,units=times.units,calendar=times.calendar)
+>>> print("time values (in units {}):\n{}".format(times.units, times[:]))
+time values (in units hours since 0001-01-01 00:00:00.0):
+[17533104. 17533116. 17533128. 17533140. 17533152.]
+>>> dates = num2date(times[:],units=times.units,calendar=times.calendar)
+>>> print("dates corresponding to time values:\n{}".format(dates))
+ [cftime.DatetimeGregorian(2001, 3, 1, 0, 0, 0, 0, has_year_zero=False)
+  cftime.DatetimeGregorian(2001, 3, 1, 12, 0, 0, 0, has_year_zero=False)
+  cftime.DatetimeGregorian(2001, 3, 2, 0, 0, 0, 0, has_year_zero=False)
+  cftime.DatetimeGregorian(2001, 3, 2, 12, 0, 0, 0, has_year_zero=False)
+  cftime.DatetimeGregorian(2001, 3, 3, 0, 0, 0, 0, has_year_zero=False)]
 
    
-
    - -

    num2date converts numeric values of time in the specified units -and calendar to datetime objects, and date2num does the reverse. +

    num2date() converts numeric values of time in the specified units +and calendar to datetime objects, and date2num() does the reverse. All the calendars currently defined in the CF metadata convention are supported. -A function called date2index is also provided which returns the indices +A function called date2index() is also provided which returns the indices of a netCDF time variable corresponding to a sequence of datetime instances.

    -

    Reading data from a multi-file netCDF dataset

    -

    If you want to read data from a variable that spans multiple netCDF files, -you can use the MFDataset class to read the data as if it were +you can use the MFDataset class to read the data as if it were contained in a single file. Instead of using a single filename to create -a Dataset instance, create a MFDataset instance with either a list +a Dataset instance, create a MFDataset instance with either a list of filenames, or a string with a wildcard (which is then converted to a sorted list of files using the python glob module). Variables in the list of files that share the same unlimited dimension are aggregated together, and can be sliced across multiple -files. To illustrate this, let's first create a bunch of netCDF files with -the same variable (with the same unlimited dimension). The files +files. +To illustrate this, let's first create a bunch of netCDF files with +the same variable (with the same unlimited dimension). +The files must in be in NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF3_CLASSIC or NETCDF4_CLASSIC format (NETCDF4 formatted multi-file datasets are not supported).

    - -
    -
    >>> for nf in range(10):
-...     with Dataset("mftest%s.nc" % nf, "w", format="NETCDF4_CLASSIC") as f:
-...         _ = f.createDimension("x",None)
-...         x = f.createVariable("x","i",("x",))
-...         x[0:10] = np.arange(nf*10,10*(nf+1))
+
    >>> for nf in range(10):
+...     with Dataset("mftest%s.nc" % nf, "w", format="NETCDF4_CLASSIC") as f:
+...         _ = f.createDimension("x",None)
+...         x = f.createVariable("x","i",("x",))
+...         x[0:10] = np.arange(nf*10,10*(nf+1))
 
    
-
    - -

    Now read all the files back in at once with MFDataset

    - -
    -
    >>> from netCDF4 import MFDataset
->>> f = MFDataset("mftest*nc")
->>> print(f.variables["x"][:])
-[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
- 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
- 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71
- 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
- 96 97 98 99]
+
    Now read all the files back in at once with MFDataset
    
+
    >>> from netCDF4 import MFDataset
+>>> f = MFDataset("mftest*nc")
+>>> print(f.variables["x"][:])
+[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
+ 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
+ 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71
+ 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
+ 96 97 98 99]
 
    
-
    - -

    Note that MFDataset can only be used to read, not write, multi-file +

    Note that MFDataset can only be used to read, not write, multi-file datasets.

    -

    Efficient compression of netCDF variables

    - -

    Data stored in netCDF Variable objects can be compressed and +

    Data stored in netCDF Variable objects can be compressed and decompressed on the fly. The compression algorithm used is determined -by the compression keyword argument to the Dataset.createVariable method. +by the compression keyword argument to the Dataset.createVariable() method. zlib compression is always available, szip is available if the linked HDF5 library supports it, and zstd, bzip2, blosc_lz,blosc_lz4,blosc_lz4hc, blosc_zlib and blosc_zstd are available via optional external plugins. @@ -1084,37 +600,43 @@

    Efficient compression of netC compression ratio, 9 being slowest but best compression ratio). The default value of complevel is 4. Setting shuffle=False will turn off the HDF5 shuffle filter, which de-interlaces a block of data before -zlib compression by reordering the bytes. The shuffle filter can -significantly improve compression ratios, and is on by default if compression=zlib. Setting +zlib compression by reordering the bytes. +The shuffle filter can +significantly improve compression ratios, and is on by default if compression=zlib. +Setting fletcher32 keyword argument to -Dataset.createVariable to True (it's False by +Dataset.createVariable() to True (it's False by default) enables the Fletcher32 checksum algorithm for error detection. It's also possible to set the HDF5 chunking parameters and endian-ness of the binary data stored in the HDF5 file with the chunksizes and endian keyword arguments to -Dataset.createVariable. These keyword arguments only +Dataset.createVariable(). +These keyword arguments only are relevant for NETCDF4 and NETCDF4_CLASSIC files (where the underlying file format is HDF5) and are silently ignored if the file format is NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA. If the HDF5 library is built with szip support, compression=szip can also be used (in conjunction with the szip_coding and szip_pixels_per_block keyword -arguments).

    - +arguments).

    If your data only has a certain number of digits of precision (say for example, it is temperature data that was measured with a precision of 0.1 degrees), you can dramatically improve compression by quantizing (or truncating) the data. There are two methods supplied for -doing this. You can use the least_significant_digit -keyword argument to Dataset.createVariable to specify +doing this. +You can use the least_significant_digit +keyword argument to Dataset.createVariable() to specify the power of ten of the smallest decimal place in the data that is a reliable value. For example if the data has a precision of 0.1, then setting least_significant_digit=1 will cause data the data to be quantized using numpy.around(scale*data)/scale, where scale = 2**bits, and bits is determined so that a precision of 0.1 is -retained (in this case bits=4). This is done at the python level and is -not a part of the underlying C library. Starting with netcdf-c version 4.9.0, -a quantization capability is provided in the library. This can be -used via the significant_digits Dataset.createVariable kwarg (new in +retained (in this case bits=4). +This is done at the python level and is +not a part of the underlying C library. +Starting with netcdf-c version 4.9.0, +a quantization capability is provided in the library. +This can be +used via the significant_digits Dataset.createVariable() kwarg (new in version 1.6.0). The interpretation of significant_digits is different than least_signficant_digit in that it specifies the absolute number of significant digits independent @@ -1122,137 +644,105 @@

    Efficient compression of netC Either of these approaches makes the compression 'lossy' instead of 'lossless', that is some precision in the data is sacrificed for the sake of disk space.

    -

    In our example, try replacing the line

    - -
    -
    >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
+
    >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",))
 
    
-
    -

    with

    - -
    -
    >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib')
+
    >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib')
 
    
-
    -

    and then

    - -
    -
    >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',least_significant_digit=3)
+
    >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',least_significant_digit=3)
 
    
-
    -

    or with netcdf-c >= 4.9.0

    - -
    -
    >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',significant_digits=4)
+
    >>> temp = rootgrp.createVariable("temp","f4",("time","level","lat","lon",),compression='zlib',significant_digits=4)
 
    
-
    -

    and see how much smaller the resulting files are.

    -

    Beyond homogeneous arrays of a fixed type - compound data types

    -

    Compound data types map directly to numpy structured (a.k.a 'record') -arrays. Structured arrays are akin to C structs, or derived types +arrays. +Structured arrays are akin to C structs, or derived types in Fortran. They allow for the construction of table-like structures composed of combinations of other data types, including other compound types. Compound types might be useful for representing multiple parameter values at each point on a grid, or at each time and space location for scattered (point) data. You can then access all the information for a point by reading one variable, instead of reading -different parameters from different variables. Compound data types +different parameters from different variables. +Compound data types are created from the corresponding numpy data type using the -Dataset.createCompoundType method of a Dataset or Group instance. +Dataset.createCompoundType() method of a Dataset or Group instance. Since there is no native complex data type in netcdf, compound types are handy -for storing numpy complex arrays. Here's an example:

    - -
    -
    >>> f = Dataset("complex.nc","w")
->>> size = 3 # length of 1-d complex array
->>> # create sample complex data.
->>> datac = np.exp(1j*(1.+np.linspace(0, np.pi, size)))
->>> # create complex128 compound data type.
->>> complex128 = np.dtype([("real",np.float64),("imag",np.float64)])
->>> complex128_t = f.createCompoundType(complex128,"complex128")
->>> # create a variable with this data type, write some data to it.
->>> x_dim = f.createDimension("x_dim",None)
->>> v = f.createVariable("cmplx_var",complex128_t,"x_dim")
->>> data = np.empty(size,complex128) # numpy structured array
->>> data["real"] = datac.real; data["imag"] = datac.imag
->>> v[:] = data # write numpy structured array to netcdf compound var
->>> # close and reopen the file, check the contents.
->>> f.close(); f = Dataset("complex.nc")
->>> v = f.variables["cmplx_var"]
->>> datain = v[:] # read in all the data into a numpy structured array
->>> # create an empty numpy complex array
->>> datac2 = np.empty(datain.shape,np.complex128)
->>> # .. fill it with contents of structured array.
->>> datac2.real = datain["real"]; datac2.imag = datain["imag"]
->>> print('{}: {}'.format(datac.dtype, datac)) # original data
-complex128: [ 0.54030231+0.84147098j -0.84147098+0.54030231j -0.54030231-0.84147098j]
->>>
->>> print('{}: {}'.format(datac2.dtype, datac2)) # data from file
-complex128: [ 0.54030231+0.84147098j -0.84147098+0.54030231j -0.54030231-0.84147098j]
+for storing numpy complex arrays.
+Here's an example:
    
+
    >>> f = Dataset("complex.nc","w")
+>>> size = 3 # length of 1-d complex array
+>>> # create sample complex data.
+>>> datac = np.exp(1j*(1.+np.linspace(0, np.pi, size)))
+>>> # create complex128 compound data type.
+>>> complex128 = np.dtype([("real",np.float64),("imag",np.float64)])
+>>> complex128_t = f.createCompoundType(complex128,"complex128")
+>>> # create a variable with this data type, write some data to it.
+>>> x_dim = f.createDimension("x_dim",None)
+>>> v = f.createVariable("cmplx_var",complex128_t,"x_dim")
+>>> data = np.empty(size,complex128) # numpy structured array
+>>> data["real"] = datac.real; data["imag"] = datac.imag
+>>> v[:] = data # write numpy structured array to netcdf compound var
+>>> # close and reopen the file, check the contents.
+>>> f.close(); f = Dataset("complex.nc")
+>>> v = f.variables["cmplx_var"]
+>>> datain = v[:] # read in all the data into a numpy structured array
+>>> # create an empty numpy complex array
+>>> datac2 = np.empty(datain.shape,np.complex128)
+>>> # .. fill it with contents of structured array.
+>>> datac2.real = datain["real"]; datac2.imag = datain["imag"]
+>>> print('{}: {}'.format(datac.dtype, datac)) # original data
+complex128: [ 0.54030231+0.84147098j -0.84147098+0.54030231j -0.54030231-0.84147098j]
+>>>
+>>> print('{}: {}'.format(datac2.dtype, datac2)) # data from file
+complex128: [ 0.54030231+0.84147098j -0.84147098+0.54030231j -0.54030231-0.84147098j]
 
    
-
    -

    Compound types can be nested, but you must create the 'inner' ones first. All possible numpy structured arrays cannot be represented as Compound variables - an error message will be raise if you try to create one that is not supported. -All of the compound types defined for a Dataset or Group are stored +All of the compound types defined for a Dataset or Group are stored in a Python dictionary, just like variables and dimensions. As always, printing objects gives useful summary information in an interactive session:

    - -
    -
    >>> print(f)
-<class 'netCDF4.Dataset'>
-root group (NETCDF4 data model, file format HDF5):
-    dimensions(sizes): x_dim(3)
-    variables(dimensions): {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True} cmplx_var(x_dim)
-    groups: 
->>> print(f.variables["cmplx_var"])
-<class 'netCDF4.Variable'>
-compound cmplx_var(x_dim)
-compound data type: {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}
-unlimited dimensions: x_dim
-current shape = (3,)
->>> print(f.cmptypes)
-{'complex128': <class 'netCDF4.CompoundType'>: name = 'complex128', numpy dtype = {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}}
->>> print(f.cmptypes["complex128"])
-<class 'netCDF4.CompoundType'>: name = 'complex128', numpy dtype = {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}
+
    >>> print(f)
+<class 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): x_dim(3)
+    variables(dimensions): {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True} cmplx_var(x_dim)
+    groups:
+>>> print(f.variables["cmplx_var"])
+<class 'netCDF4._netCDF4.Variable'>
+compound cmplx_var(x_dim)
+compound data type: {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}
+unlimited dimensions: x_dim
+current shape = (3,)
+>>> print(f.cmptypes)
+{'complex128': <class 'netCDF4._netCDF4.CompoundType'>: name = 'complex128', numpy dtype = {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}}
+>>> print(f.cmptypes["complex128"])
+<class 'netCDF4._netCDF4.CompoundType'>: name = 'complex128', numpy dtype = {'names':['real','imag'], 'formats':['<f8','<f8'], 'offsets':[0,8], 'itemsize':16, 'aligned':True}
 
    
-
    -

    Variable-length (vlen) data types

    - -

    NetCDF 4 has support for variable-length or "ragged" arrays. These are arrays +

    NetCDF 4 has support for variable-length or "ragged" arrays. +These are arrays of variable length sequences having the same type. To create a variable-length -data type, use the Dataset.createVLType method -method of a Dataset or Group instance.

    - -
    -
    >>> f = Dataset("tst_vlen.nc","w")
->>> vlen_t = f.createVLType(np.int32, "phony_vlen")
+data type, use the Dataset.createVLType() method
+method of a Dataset or Group instance.
    
+
    >>> f = Dataset("tst_vlen.nc","w")
+>>> vlen_t = f.createVLType(np.int32, "phony_vlen")
 
    
-
    -

    The numpy datatype of the variable-length sequences and the name of the new datatype must be specified. Any of the primitive datatypes can be used (signed and unsigned integers, 32 and 64 bit floats, and characters), but compound data types cannot. A new variable can then be created using this datatype.

    - -
    -
    >>> x = f.createDimension("x",3)
->>> y = f.createDimension("y",4)
->>> vlvar = f.createVariable("phony_vlen_var", vlen_t, ("y","x"))
+
    >>> x = f.createDimension("x",3)
+>>> y = f.createDimension("y",4)
+>>> vlvar = f.createVariable("phony_vlen_var", vlen_t, ("y","x"))
 
    
-
    -

    Since there is no native vlen datatype in numpy, vlen arrays are represented in python as object arrays (arrays of dtype object). These are arrays whose elements are Python object pointers, and can contain any type of python object. @@ -1260,212 +750,179 @@

    Variable-length (vlen) data types

    but of varying length. In this case, they contain 1-D numpy int32 arrays of random length between 1 and 10.

    - -
    -
    >>> import random
->>> random.seed(54321)
->>> data = np.empty(len(y)*len(x),object)
->>> for n in range(len(y)*len(x)):
-...     data[n] = np.arange(random.randint(1,10),dtype="int32")+1
->>> data = np.reshape(data,(len(y),len(x)))
->>> vlvar[:] = data
->>> print("vlen variable =\n{}".format(vlvar[:]))
-vlen variable =
-[[array([1, 2, 3, 4, 5, 6, 7, 8], dtype=int32) array([1, 2], dtype=int32)
-  array([1, 2, 3, 4], dtype=int32)]
- [array([1, 2, 3], dtype=int32)
-  array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)
-  array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)]
- [array([1, 2, 3, 4, 5, 6, 7], dtype=int32) array([1, 2, 3], dtype=int32)
-  array([1, 2, 3, 4, 5, 6], dtype=int32)]
- [array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)
-  array([1, 2, 3, 4, 5], dtype=int32) array([1, 2], dtype=int32)]]
->>> print(f)
-<class 'netCDF4.Dataset'>
-root group (NETCDF4 data model, file format HDF5):
-    dimensions(sizes): x(3), y(4)
-    variables(dimensions): int32 phony_vlen_var(y,x)
-    groups: 
->>> print(f.variables["phony_vlen_var"])
-<class 'netCDF4.Variable'>
-vlen phony_vlen_var(y, x)
-vlen data type: int32
-unlimited dimensions: 
-current shape = (4, 3)
->>> print(f.vltypes["phony_vlen"])
-<class 'netCDF4.VLType'>: name = 'phony_vlen', numpy dtype = int32
+
    >>> import random
+>>> random.seed(54321)
+>>> data = np.empty(len(y)*len(x),object)
+>>> for n in range(len(y)*len(x)):
+...     data[n] = np.arange(random.randint(1,10),dtype="int32")+1
+>>> data = np.reshape(data,(len(y),len(x)))
+>>> vlvar[:] = data
+>>> print("vlen variable =\n{}".format(vlvar[:]))
+vlen variable =
+[[array([1, 2, 3, 4, 5, 6, 7, 8], dtype=int32) array([1, 2], dtype=int32)
+  array([1, 2, 3, 4], dtype=int32)]
+ [array([1, 2, 3], dtype=int32)
+  array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)
+  array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)]
+ [array([1, 2, 3, 4, 5, 6, 7], dtype=int32) array([1, 2, 3], dtype=int32)
+  array([1, 2, 3, 4, 5, 6], dtype=int32)]
+ [array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)
+  array([1, 2, 3, 4, 5], dtype=int32) array([1, 2], dtype=int32)]]
+>>> print(f)
+<class 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): x(3), y(4)
+    variables(dimensions): int32 phony_vlen_var(y,x)
+    groups:
+>>> print(f.variables["phony_vlen_var"])
+<class 'netCDF4._netCDF4.Variable'>
+vlen phony_vlen_var(y, x)
+vlen data type: int32
+unlimited dimensions:
+current shape = (4, 3)
+>>> print(f.vltypes["phony_vlen"])
+<class 'netCDF4._netCDF4.VLType'>: name = 'phony_vlen', numpy dtype = int32
 
    
-
    -

    Numpy object arrays containing python strings can also be written as vlen -variables, For vlen strings, you don't need to create a vlen data type. +variables, +For vlen strings, you don't need to create a vlen data type. Instead, simply use the python str builtin (or a numpy string datatype with fixed length greater than 1) when calling the -Dataset.createVariable method.

    - -
    -
    >>> z = f.createDimension("z",10)
->>> strvar = f.createVariable("strvar", str, "z")
+Dataset.createVariable() method.
    
+
    >>> z = f.createDimension("z",10)
+>>> strvar = f.createVariable("strvar", str, "z")
 
    
-
    -

    In this example, an object array is filled with random python strings with random lengths between 2 and 12 characters, and the data in the object array is assigned to the vlen string variable.

    - -
    -
    >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
->>> data = np.empty(10,"O")
->>> for n in range(10):
-...     stringlen = random.randint(2,12)
-...     data[n] = "".join([random.choice(chars) for i in range(stringlen)])
->>> strvar[:] = data
->>> print("variable-length string variable:\n{}".format(strvar[:]))
-variable-length string variable:
-['Lh' '25F8wBbMI' '53rmM' 'vvjnb3t63ao' 'qjRBQk6w' 'aJh' 'QF'
- 'jtIJbJACaQk4' '3Z5' 'bftIIq']
->>> print(f)
-<class 'netCDF4.Dataset'>
-root group (NETCDF4 data model, file format HDF5):
-    dimensions(sizes): x(3), y(4), z(10)
-    variables(dimensions): int32 phony_vlen_var(y,x), <class 'str'> strvar(z)
-    groups: 
->>> print(f.variables["strvar"])
-<class 'netCDF4.Variable'>
-vlen strvar(z)
-vlen data type: <class 'str'>
-unlimited dimensions: 
-current shape = (10,)
+
    >>> chars = "1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
+>>> data = np.empty(10,"O")
+>>> for n in range(10):
+...     stringlen = random.randint(2,12)
+...     data[n] = "".join([random.choice(chars) for i in range(stringlen)])
+>>> strvar[:] = data
+>>> print("variable-length string variable:\n{}".format(strvar[:]))
+variable-length string variable:
+['Lh' '25F8wBbMI' '53rmM' 'vvjnb3t63ao' 'qjRBQk6w' 'aJh' 'QF'
+ 'jtIJbJACaQk4' '3Z5' 'bftIIq']
+>>> print(f)
+<class 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): x(3), y(4), z(10)
+    variables(dimensions): int32 phony_vlen_var(y,x), <class 'str'> strvar(z)
+    groups:
+>>> print(f.variables["strvar"])
+<class 'netCDF4._netCDF4.Variable'>
+vlen strvar(z)
+vlen data type: <class 'str'>
+unlimited dimensions:
+current shape = (10,)
 
    
-
    -

    It is also possible to set contents of vlen string variables with numpy arrays of any string or unicode data type. Note, however, that accessing the contents of such variables will always return numpy arrays with dtype object.

    -

    Enum data type

    -

    netCDF4 has an enumerated data type, which is an integer datatype that is restricted to certain named values. Since Enums don't map directly to a numpy data type, they are read and written as integer arrays.

    -

    Here's an example of using an Enum type to hold cloud type data. The base integer data type and a python dictionary describing the allowed values and their names are used to define an Enum data type using -Dataset.createEnumType.

    - -
    -
    >>> nc = Dataset('clouds.nc','w')
->>> # python dict with allowed values and their names.
->>> enum_dict = {'Altocumulus': 7, 'Missing': 255,
-... 'Stratus': 2, 'Clear': 0,
-... 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5,
-... 'Cumulonimbus': 1, 'Stratocumulus': 3}
->>> # create the Enum type called 'cloud_t'.
->>> cloud_type = nc.createEnumType(np.uint8,'cloud_t',enum_dict)
->>> print(cloud_type)
-<class 'netCDF4.EnumType'>: name = 'cloud_t', numpy dtype = uint8, fields/values ={'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, 'Stratocumulus': 3}
+Dataset.createEnumType().
    
+
    >>> nc = Dataset('clouds.nc','w')
+>>> # python dict with allowed values and their names.
+>>> enum_dict = {'Altocumulus': 7, 'Missing': 255,
+... 'Stratus': 2, 'Clear': 0,
+... 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5,
+... 'Cumulonimbus': 1, 'Stratocumulus': 3}
+>>> # create the Enum type called 'cloud_t'.
+>>> cloud_type = nc.createEnumType(np.uint8,'cloud_t',enum_dict)
+>>> print(cloud_type)
+<class 'netCDF4._netCDF4.EnumType'>: name = 'cloud_t', numpy dtype = uint8, fields/values ={'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, 'Stratocumulus': 3}
 
    
-
    -

    A new variable can be created in the usual way using this data type. Integer data is written to the variable that represents the named cloud types in enum_dict. A ValueError will be raised if an attempt is made to write an integer value not associated with one of the specified names.

    - -
    -
    >>> time = nc.createDimension('time',None)
->>> # create a 1d variable of type 'cloud_type'.
->>> # The fill_value is set to the 'Missing' named value.
->>> cloud_var = nc.createVariable('primary_cloud',cloud_type,'time',
-...                               fill_value=enum_dict['Missing'])
->>> # write some data to the variable.
->>> cloud_var[:] = [enum_dict[k] for k in ['Clear', 'Stratus', 'Cumulus',
-...                                        'Missing', 'Cumulonimbus']]
->>> nc.close()
->>> # reopen the file, read the data.
->>> nc = Dataset('clouds.nc')
->>> cloud_var = nc.variables['primary_cloud']
->>> print(cloud_var)
-<class 'netCDF4.Variable'>
-enum primary_cloud(time)
-    _FillValue: 255
-enum data type: uint8
-unlimited dimensions: time
-current shape = (5,)
->>> print(cloud_var.datatype.enum_dict)
-{'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, 'Stratocumulus': 3}
->>> print(cloud_var[:])
-[0 2 4 -- 1]
->>> nc.close()
+
    >>> time = nc.createDimension('time',None)
+>>> # create a 1d variable of type 'cloud_type'.
+>>> # The fill_value is set to the 'Missing' named value.
+>>> cloud_var = nc.createVariable('primary_cloud',cloud_type,'time',
+...                               fill_value=enum_dict['Missing'])
+>>> # write some data to the variable.
+>>> cloud_var[:] = [enum_dict[k] for k in ['Clear', 'Stratus', 'Cumulus',
+...                                        'Missing', 'Cumulonimbus']]
+>>> nc.close()
+>>> # reopen the file, read the data.
+>>> nc = Dataset('clouds.nc')
+>>> cloud_var = nc.variables['primary_cloud']
+>>> print(cloud_var)
+<class 'netCDF4._netCDF4.Variable'>
+enum primary_cloud(time)
+    _FillValue: 255
+enum data type: uint8
+unlimited dimensions: time
+current shape = (5,)
+>>> print(cloud_var.datatype.enum_dict)
+{'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, 'Stratocumulus': 3}
+>>> print(cloud_var[:])
+[0 2 4 -- 1]
+>>> nc.close()
 
    
-
    -

    Parallel IO

    -

    If MPI parallel enabled versions of netcdf and hdf5 or pnetcdf are detected, and mpi4py is installed, netcdf4-python will -be built with parallel IO capabilities enabled. Parallel IO of NETCDF4 or +be built with parallel IO capabilities enabled. Parallel IO of NETCDF4 or NETCDF4_CLASSIC formatted files is only available if the MPI parallel HDF5 library is available. Parallel IO of classic netcdf-3 file formats is only available if the PnetCDF library is available. To use parallel IO, your program must be running in an MPI environment using mpi4py.

    - -
    -
    >>> from mpi4py import MPI
->>> import numpy as np
->>> from netCDF4 import Dataset
->>> rank = MPI.COMM_WORLD.rank  # The process ID (integer 0-3 for 4-process run)
+
    >>> from mpi4py import MPI
+>>> import numpy as np
+>>> from netCDF4 import Dataset
+>>> rank = MPI.COMM_WORLD.rank  # The process ID (integer 0-3 for 4-process run)
 
    
-
    -

    To run an MPI-based parallel program like this, you must use mpiexec to launch several parallel instances of Python (for example, using mpiexec -np 4 python mpi_example.py). The parallel features of netcdf4-python are mostly transparent - when a new dataset is created or an existing dataset is opened, use the parallel keyword to enable parallel access.

    - -
    -
    >>> nc = Dataset('parallel_test.nc','w',parallel=True)
+
    >>> nc = Dataset('parallel_test.nc','w',parallel=True)
 
    
-
    -

    The optional comm keyword may be used to specify a particular -MPI communicator (MPI_COMM_WORLD is used by default). Each process (or rank) -can now write to the file indepedently. In this example the process rank is +MPI communicator (MPI_COMM_WORLD is used by default). +Each process (or rank) +can now write to the file indepedently. +In this example the process rank is written to a different variable index on each task

    - -
    -
    >>> d = nc.createDimension('dim',4)
->>> v = nc.createVariable('var', np.int64, 'dim')
->>> v[rank] = rank
->>> nc.close()
-
-% ncdump parallel_test.nc
-netcdf parallel_test {
-dimensions:
-    dim = 4 ;
-variables:
-    int64 var(dim) ;
-data:
-
-    var = 0, 1, 2, 3 ;
-}
+
    >>> d = nc.createDimension('dim',4)
+>>> v = nc.createVariable('var', np.int64, 'dim')
+>>> v[rank] = rank
+>>> nc.close()
+
+% ncdump parallel_test.nc
+netcdf parallel_test {
+dimensions:
+    dim = 4 ;
+variables:
+    int64 var(dim) ;
+data:
+
+    var = 0, 1, 2, 3 ;
+}
 
    
-
    -

    There are two types of parallel IO, independent (the default) and collective. Independent IO means that each process can do IO independently. It should not depend on or be affected by other processes. Collective IO is a way of doing IO defined in the MPI-IO standard; unlike independent IO, all processes must participate in doing IO. To toggle back and forth between -the two types of IO, use the Variable.set_collective -Variable method. All metadata +the two types of IO, use the Variable.set_collective() +Variable method. All metadata operations (such as creation of groups, types, variables, dimensions, or attributes) -are collective. There are a couple of important limitations of parallel IO:

    - +are collective. +There are a couple of important limitations of parallel IO:

    • parallel IO for NETCDF4 or NETCDF4_CLASSIC formatted files is only available if the netcdf library was compiled with MPI enabled HDF5.
      • @@ -1476,15 +933,14 @@

      Parallel IO

      a generic "HDF Error".
    • You can write compressed data in parallel only with netcdf-c >= 4.7.4 and hdf5 >= 1.10.3 (although you can read in parallel with earlier versions). To write -compressed data in parallel, the variable must be in 'collective IO mode'. This is done +compressed data in parallel, the variable must be in 'collective IO mode'. +This is done automatically on variable creation if compression is turned on, but if you are appending -to a variable in an existing file, you must use Variable.set_collective(True) before attempting +to a variable in an existing file, you must use Variable.set_collective()(True) before attempting to write to it.
    • You cannot use variable-length (VLEN) data types.
    -

    Dealing with strings

    -

    The most flexible way to store arrays of strings is with the Variable-length (vlen) string data type. However, this requires the use of the NETCDF4 data model, and the vlen type does not map very well @@ -1496,43 +952,40 @@

    Dealing with strings

    To perform the conversion to and from character arrays to fixed-width numpy string arrays, the following convention is followed by the python interface. If the _Encoding special attribute is set for a character array -(dtype S1) variable, the chartostring utility function is used to convert the array of +(dtype S1) variable, the chartostring() utility function is used to convert the array of characters to an array of strings with one less dimension (the last dimension is interpreted as the length of each string) when reading the data. The character set (usually ascii) is specified by the _Encoding attribute. If _Encoding is 'none' or 'bytes', then the character array is converted to a numpy fixed-width byte string array (dtype S#), otherwise a numpy unicode (dtype -U#) array is created. When writing the data, -stringtochar is used to convert the numpy string array to an array of +U#) array is created. +When writing the data, +stringtochar() is used to convert the numpy string array to an array of characters with one more dimension. For example,

    - -
    -
    >>> from netCDF4 import stringtochar
->>> nc = Dataset('stringtest.nc','w',format='NETCDF4_CLASSIC')
->>> _ = nc.createDimension('nchars',3)
->>> _ = nc.createDimension('nstrings',None)
->>> v = nc.createVariable('strings','S1',('nstrings','nchars'))
->>> datain = np.array(['foo','bar'],dtype='S3')
->>> v[:] = stringtochar(datain) # manual conversion to char array
->>> print(v[:]) # data returned as char array
-[[b'f' b'o' b'o']
- [b'b' b'a' b'r']]
->>> v._Encoding = 'ascii' # this enables automatic conversion
->>> v[:] = datain # conversion to char array done internally
->>> print(v[:])  # data returned in numpy string array
-['foo' 'bar']
->>> nc.close()
+
    >>> from netCDF4 import stringtochar
+>>> nc = Dataset('stringtest.nc','w',format='NETCDF4_CLASSIC')
+>>> _ = nc.createDimension('nchars',3)
+>>> _ = nc.createDimension('nstrings',None)
+>>> v = nc.createVariable('strings','S1',('nstrings','nchars'))
+>>> datain = np.array(['foo','bar'],dtype='S3')
+>>> v[:] = stringtochar(datain) # manual conversion to char array
+>>> print(v[:]) # data returned as char array
+[[b'f' b'o' b'o']
+ [b'b' b'a' b'r']]
+>>> v._Encoding = 'ascii' # this enables automatic conversion
+>>> v[:] = datain # conversion to char array done internally
+>>> print(v[:])  # data returned in numpy string array
+['foo' 'bar']
+>>> nc.close()
 
    
-
    -

    Even if the _Encoding attribute is set, the automatic conversion of char arrays to/from string arrays can be disabled with -Variable.set_auto_chartostring.

    - +Variable.set_auto_chartostring().

    A similar situation is often encountered with numpy structured arrays with subdtypes containing fixed-wdith byte strings (dtype=S#). Since there is no native fixed-length string netCDF datatype, these numpy structure arrays are mapped onto netCDF compound -types with character array elements. In this case the string <-> char array +types with character array elements. +In this case the string <-> char array conversion is handled automatically (without the need to set the _Encoding attribute) using numpy views. @@ -1540,263 +993,481 @@

    Dealing with strings

    define the compound data type - the string dtype will be converted to character array dtype under the hood when creating the netcdf compound type. Here's an example:

    - -
    -
    >>> nc = Dataset('compoundstring_example.nc','w')
->>> dtype = np.dtype([('observation', 'f4'),
-...                      ('station_name','S10')])
->>> station_data_t = nc.createCompoundType(dtype,'station_data')
->>> _ = nc.createDimension('station',None)
->>> statdat = nc.createVariable('station_obs', station_data_t, ('station',))
->>> data = np.empty(2,dtype)
->>> data['observation'][:] = (123.,3.14)
->>> data['station_name'][:] = ('Boulder','New York')
->>> print(statdat.dtype) # strings actually stored as character arrays
-{'names':['observation','station_name'], 'formats':['<f4',('S1', (10,))], 'offsets':[0,4], 'itemsize':16, 'aligned':True}
->>> statdat[:] = data # strings converted to character arrays internally
->>> print(statdat[:])  # character arrays converted back to strings
-[(123.  , b'Boulder') (  3.14, b'New York')]
->>> print(statdat[:].dtype)
-{'names':['observation','station_name'], 'formats':['<f4','S10'], 'offsets':[0,4], 'itemsize':16, 'aligned':True}
->>> statdat.set_auto_chartostring(False) # turn off auto-conversion
->>> statdat[:] = data.view(dtype=[('observation', 'f4'),('station_name','S1',10)])
->>> print(statdat[:])  # now structured array with char array subtype is returned
-[(123.  , [b'B', b'o', b'u', b'l', b'd', b'e', b'r', b'', b'', b''])
- (  3.14, [b'N', b'e', b'w', b' ', b'Y', b'o', b'r', b'k', b'', b''])]
->>> nc.close()
+
    >>> nc = Dataset('compoundstring_example.nc','w')
+>>> dtype = np.dtype([('observation', 'f4'),
+...                      ('station_name','S10')])
+>>> station_data_t = nc.createCompoundType(dtype,'station_data')
+>>> _ = nc.createDimension('station',None)
+>>> statdat = nc.createVariable('station_obs', station_data_t, ('station',))
+>>> data = np.empty(2,dtype)
+>>> data['observation'][:] = (123.,3.14)
+>>> data['station_name'][:] = ('Boulder','New York')
+>>> print(statdat.dtype) # strings actually stored as character arrays
+{'names':['observation','station_name'], 'formats':['<f4',('S1', (10,))], 'offsets':[0,4], 'itemsize':16, 'aligned':True}
+>>> statdat[:] = data # strings converted to character arrays internally
+>>> print(statdat[:])  # character arrays converted back to strings
+[(123.  , b'Boulder') (  3.14, b'New York')]
+>>> print(statdat[:].dtype)
+{'names':['observation','station_name'], 'formats':['<f4','S10'], 'offsets':[0,4], 'itemsize':16, 'aligned':True}
+>>> statdat.set_auto_chartostring(False) # turn off auto-conversion
+>>> statdat[:] = data.view(dtype=[('observation', 'f4'),('station_name','S1',10)])
+>>> print(statdat[:])  # now structured array with char array subtype is returned
+[(123.  , [b'B', b'o', b'u', b'l', b'd', b'e', b'r', b'', b'', b''])
+ (  3.14, [b'N', b'e', b'w', b' ', b'Y', b'o', b'r', b'k', b'', b''])]
+>>> nc.close()
 
    
-
    -

    Note that there is currently no support for mapping numpy structured arrays with unicode elements (dtype U#) onto netCDF compound types, nor is there support for netCDF compound types with vlen string components.

    -

    In-memory (diskless) Datasets

    -

    You can create netCDF Datasets whose content is held in memory -instead of in a disk file. There are two ways to do this. If you +instead of in a disk file. +There are two ways to do this. +If you don't need access to the memory buffer containing the Dataset from within python, the best way is to use the diskless=True keyword -argument when creating the Dataset. If you want to save the Dataset -to disk when you close it, also set persist=True. If you want to +argument when creating the Dataset. +If you want to save the Dataset +to disk when you close it, also set persist=True. +If you want to create a new read-only Dataset from an existing python memory buffer, use the memory keyword argument to pass the memory buffer when creating the Dataset. If you want to create a new in-memory Dataset, and then access the memory buffer directly from Python, use the memory keyword argument to specify the estimated size of the Dataset in bytes when creating the Dataset with -mode='w'. Then, the Dataset.close method will return a python memoryview +mode='w'. +Then, the Dataset.close() method will return a python memoryview object representing the Dataset. Below are examples illustrating both approaches.

    - -
    -
    >>> # create a diskless (in-memory) Dataset,
->>> # and persist the file to disk when it is closed.
->>> nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
->>> d = nc.createDimension('x',None)
->>> v = nc.createVariable('v',np.int32,'x')
->>> v[0:5] = np.arange(5)
->>> print(nc)
-<class 'netCDF4.Dataset'>
-root group (NETCDF4 data model, file format HDF5):
-    dimensions(sizes): x(5)
-    variables(dimensions): int32 v(x)
-    groups: 
->>> print(nc['v'][:])
-[0 1 2 3 4]
->>> nc.close() # file saved to disk
->>> # create an in-memory dataset from an existing python
->>> # python memory buffer.
->>> # read the newly created netcdf file into a python
->>> # bytes object.
->>> with open('diskless_example.nc', 'rb') as f:
-...     nc_bytes = f.read()
->>> # create a netCDF in-memory dataset from the bytes object.
->>> nc = Dataset('inmemory.nc', memory=nc_bytes)
->>> print(nc)
-<class 'netCDF4.Dataset'>
-root group (NETCDF4 data model, file format HDF5):
-    dimensions(sizes): x(5)
-    variables(dimensions): int32 v(x)
-    groups: 
->>> print(nc['v'][:])
-[0 1 2 3 4]
->>> nc.close()
->>> # create an in-memory Dataset and retrieve memory buffer
->>> # estimated size is 1028 bytes - this is actually only
->>> # used if format is NETCDF3
->>> # (ignored for NETCDF4/HDF5 files).
->>> nc = Dataset('inmemory.nc', mode='w',memory=1028)
->>> d = nc.createDimension('x',None)
->>> v = nc.createVariable('v',np.int32,'x')
->>> v[0:5] = np.arange(5)
->>> nc_buf = nc.close() # close returns memoryview
->>> print(type(nc_buf))
-<class 'memoryview'>
->>> # save nc_buf to disk, read it back in and check.
->>> with open('inmemory.nc', 'wb') as f:
-...     f.write(nc_buf)
->>> nc = Dataset('inmemory.nc')
->>> print(nc)
-<class 'netCDF4.Dataset'>
-root group (NETCDF4 data model, file format HDF5):
-    dimensions(sizes): x(5)
-    variables(dimensions): int32 v(x)
-    groups:
->>> print(nc['v'][:])
-[0 1 2 3 4]
->>> nc.close()
+
    >>> # create a diskless (in-memory) Dataset,
+>>> # and persist the file to disk when it is closed.
+>>> nc = Dataset('diskless_example.nc','w',diskless=True,persist=True)
+>>> d = nc.createDimension('x',None)
+>>> v = nc.createVariable('v',np.int32,'x')
+>>> v[0:5] = np.arange(5)
+>>> print(nc)
+<class 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): x(5)
+    variables(dimensions): int32 v(x)
+    groups:
+>>> print(nc['v'][:])
+[0 1 2 3 4]
+>>> nc.close() # file saved to disk
+>>> # create an in-memory dataset from an existing python
+>>> # python memory buffer.
+>>> # read the newly created netcdf file into a python
+>>> # bytes object.
+>>> with open('diskless_example.nc', 'rb') as f:
+...     nc_bytes = f.read()
+>>> # create a netCDF in-memory dataset from the bytes object.
+>>> nc = Dataset('inmemory.nc', memory=nc_bytes)
+>>> print(nc)
+<class 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): x(5)
+    variables(dimensions): int32 v(x)
+    groups:
+>>> print(nc['v'][:])
+[0 1 2 3 4]
+>>> nc.close()
+>>> # create an in-memory Dataset and retrieve memory buffer
+>>> # estimated size is 1028 bytes - this is actually only
+>>> # used if format is NETCDF3
+>>> # (ignored for NETCDF4/HDF5 files).
+>>> nc = Dataset('inmemory.nc', mode='w',memory=1028)
+>>> d = nc.createDimension('x',None)
+>>> v = nc.createVariable('v',np.int32,'x')
+>>> v[0:5] = np.arange(5)
+>>> nc_buf = nc.close() # close returns memoryview
+>>> print(type(nc_buf))
+<class 'memoryview'>
+>>> # save nc_buf to disk, read it back in and check.
+>>> with open('inmemory.nc', 'wb') as f:
+...     f.write(nc_buf)
+>>> nc = Dataset('inmemory.nc')
+>>> print(nc)
+<class 'netCDF4._netCDF4.Dataset'>
+root group (NETCDF4 data model, file format HDF5):
+    dimensions(sizes): x(5)
+    variables(dimensions): int32 v(x)
+    groups:
+>>> print(nc['v'][:])
+[0 1 2 3 4]
+>>> nc.close()
 
    
-
    -

    All of the code in this tutorial is available in examples/tutorial.py, except the parallel IO example, which is in examples/mpi_example.py. Unit tests are in the test directory.

    - -

    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov

    - +

    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov

    copyright: 2008 by Jeffrey Whitaker.

    -

    license: Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

    -

    The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

    -

    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

    -

    - - - - - - 
     1# init for netCDF4. package
- 2# Docstring comes from extension module _netCDF4.
- 3from ._netCDF4 import *
- 4# Need explicit imports for names beginning with underscores
- 5from ._netCDF4 import __doc__
- 6from ._netCDF4 import (__version__, __netcdf4libversion__, __hdf5libversion__,
- 7                       __has_rename_grp__, __has_nc_inq_path__,
- 8                       __has_nc_inq_format_extended__, __has_nc_open_mem__,
- 9                       __has_nc_create_mem__, __has_cdf5_format__,
-10                       __has_parallel4_support__, __has_pnetcdf_support__,
-11                       __has_quantization_support__, __has_zstandard_support__,
-12                       __has_bzip2_support__, __has_blosc_support__, __has_szip_support__,
-13                       __has_set_alignment__)
-14import os
-15__all__ =\
-16['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache','set_alignment','get_alignment']
-17# if HDF5_PLUGIN_PATH not set, point to package path if plugins live there
-18pluginpath = os.path.join(__path__[0],'plugins')
-19if 'HDF5_PLUGIN_PATH' not in os.environ and\
-20    (os.path.exists(os.path.join(pluginpath,'lib__nczhdf5filters.so')) or\
-21     os.path.exists(os.path.join(pluginpath,'lib__nczhdf5filters.dylib'))):
-22    os.environ['HDF5_PLUGIN_PATH']=pluginpath
-
    - - -
    -
    -
    - - class - Dataset: - - -
    - - -

    A netCDF Dataset is a collection of dimensions, groups, variables and -attributes. Together they describe the meaning of data and relations among -data fields stored in a netCDF file. See Dataset.__init__ for more -details.

    - -

    A list of attribute names corresponding to global netCDF attributes -defined for the Dataset can be obtained with the -Dataset.ncattrs method. -These attributes can be created by assigning to an attribute of the -Dataset instance. A dictionary containing all the netCDF attribute -name/value pairs is provided by the __dict__ attribute of a -Dataset instance.

    - -

    The following class variables are read-only and should not be -modified by the user.

    - -

    dimensions: The dimensions dictionary maps the names of -dimensions defined for the Group or Dataset to instances of the -Dimension class.

    - -

    variables: The variables dictionary maps the names of variables -defined for this Dataset or Group to instances of the -Variable class.

    - -

    groups: The groups dictionary maps the names of groups created for -this Dataset or Group to instances of the Group class (the -Dataset class is simply a special case of the Group class which -describes the root group in the netCDF4 file).

    - -

    cmptypes: The cmptypes dictionary maps the names of -compound types defined for the Group or Dataset to instances of the -CompoundType class.

    - -

    vltypes: The vltypes dictionary maps the names of -variable-length types defined for the Group or Dataset to instances -of the VLType class.

    - -

    enumtypes: The enumtypes dictionary maps the names of -Enum types defined for the Group or Dataset to instances -of the EnumType class.

    - -

    data_model: data_model describes the netCDF -data model version, one of NETCDF3_CLASSIC, NETCDF4, -NETCDF4_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.

    - -

    file_format: same as data_model, retained for backwards compatibility.

    - -

    disk_format: disk_format describes the underlying -file format, one of NETCDF3, HDF5, HDF4, -PNETCDF, DAP2, DAP4 or UNDEFINED. Only available if using -netcdf C library version >= 4.3.1, otherwise will always return -UNDEFINED.

    - -

    parent: parent is a reference to the parent -Group instance. None for the root group or Dataset -instance.

    - -

    path: path shows the location of the Group in -the Dataset in a unix directory format (the names of groups in the -hierarchy separated by backslashes). A Dataset instance is the root +

    +
    +
    +
    +
    +
    +

    Functions

    +
    +
    +def chartostring(...) +
    +
    +

    chartostring(b,encoding='utf-8')

    +

    convert a character array to a string array with one less dimension.

    +

    b: +Input character array (numpy datatype 'S1' or 'U1'). +Will be converted to a array of strings, where each string has a fixed +length of b.shape[-1] characters.

    +

    optional kwarg encoding can be used to specify character encoding (default +utf-8). If encoding is 'none' or 'bytes', a numpy.string_ btye array is +returned.

    +

    returns a numpy string array with datatype 'UN' (or 'SN') and shape +b.shape[:-1] where where N=b.shape[-1].

    +
    +
    +def date2index(dates, nctime, calendar=None, select='exact', has_year_zero=None) +
    +
    +

    Return indices of a netCDF time variable corresponding to the given dates.

    +

    dates: A datetime object or a sequence of datetime objects. +The datetime objects should not include a time-zone offset.

    +

    nctime: A netCDF time variable object. The nctime object must have a +units attribute.

    +

    calendar: describes the calendar to be used in the time calculations. +All the values currently defined in the +CF metadata convention <http://cfconventions.org/cf-conventions/cf-conventions#calendar>__ are supported. +Valid calendars 'standard', 'gregorian', 'proleptic_gregorian' +'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'. +Default is None which means the calendar associated with the first +input datetime instance will be used.

    +

    select: 'exact', 'before', 'after', 'nearest' +The index selection method. exact will return the indices perfectly +matching the dates given. before and after will return the indices +corresponding to the dates just before or just after the given dates if +an exact match cannot be found. nearest will return the indices that +correspond to the closest dates.

    +

    has_year_zero: if set to True, astronomical year numbering +is used and the year zero exists. +If set to False for real-world +calendars, then historical year numbering is used and the year 1 is +preceded by year -1 and no year zero exists. +The defaults are set to conform with +CF version 1.9 conventions (False for 'julian', 'gregorian'/'standard', True +for 'proleptic_gregorian' (ISO 8601) and True for the idealized +calendars 'noleap'/'365_day', '360_day', 366_day'/'all_leap') +The defaults can only be over-ridden for the real-world calendars, +for the the idealized calendars the year zero +always exists and the has_year_zero kwarg is ignored. +This kwarg is not needed to define calendar systems allowed by CF +(the calendar-specific defaults do this).

    +

    returns an index (indices) of the netCDF time variable corresponding +to the given datetime object(s).

    +
    +
    +def date2num(dates, units, calendar=None, has_year_zero=None, longdouble=False) +
    +
    +

    Return numeric time values given datetime objects. The units +of the numeric time values are described by the units argument +and the calendar keyword. The datetime objects must +be in UTC with no time-zone offset. +If there is a +time-zone offset in units, it will be applied to the +returned numeric values.

    +

    dates: A datetime object or a sequence of datetime objects. +The datetime objects should not include a time-zone offset. They +can be either native python datetime instances (which use +the proleptic gregorian calendar) or cftime.datetime instances.

    +

    units: a string of the form +describing the time units. can be days, hours, minutes, +seconds, milliseconds or microseconds. is the time +origin. months since is allowed only for the 360_day calendar +and common_years since is allowed only for the 365_day calendar.

    +

    calendar: describes the calendar to be used in the time calculations. +All the values currently defined in the +CF metadata convention <http://cfconventions.org/cf-conventions/cf-conventions#calendar>__ are supported. +Valid calendars 'standard', 'gregorian', 'proleptic_gregorian' +'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'. +Default is None which means the calendar associated with the first +input datetime instance will be used.

    +

    has_year_zero: If set to True, astronomical year numbering +is used and the year zero exists. +If set to False for real-world +calendars, then historical year numbering is used and the year 1 is +preceded by year -1 and no year zero exists. +The defaults are set to conform with +CF version 1.9 conventions (False for 'julian', 'gregorian'/'standard', True +for 'proleptic_gregorian' (ISO 8601) and True for the idealized +calendars 'noleap'/'365_day', '360_day', 366_day'/'all_leap') +Note that CF v1.9 does not specifically mention whether year zero +is allowed in the proleptic_gregorian calendar, but ISO-8601 has +a year zero so we have adopted this as the default. +The defaults can only be over-ridden for the real-world calendars, +for the the idealized calendars the year zero +always exists and the has_year_zero kwarg is ignored. +This kwarg is not needed to define calendar systems allowed by CF +(the calendar-specific defaults do this).

    +

    longdouble: If set True, output is in the long double float type +(numpy.float128) instead of float (numpy.float64), allowing microsecond +accuracy when converting a time value to a date and back again. Otherwise +this is only possible if the discretization of the time variable is an +integer multiple of the units.

    +

    returns a numeric time value, or an array of numeric time values +with approximately 1 microsecond accuracy.

    +
    +
    +def get_alignment(...) +
    +
    +
    +
    +
    +def get_chunk_cache(...) +
    +
    +

    get_chunk_cache()

    +

    return current netCDF chunk cache information in a tuple (size,nelems,preemption). +See netcdf C library documentation for nc_get_chunk_cache for +details. Values can be reset with set_chunk_cache().

    +
    +
    +def getlibversion(...) +
    +
    +

    getlibversion()

    +

    returns a string describing the version of the netcdf library +used to build the module, and when it was built.

    +
    +
    +def num2date(times, units, calendar='standard', only_use_cftime_datetimes=True, only_use_python_datetimes=False, has_year_zero=None) +
    +
    +

    Return datetime objects given numeric time values. The units +of the numeric time values are described by the units argument +and the calendar keyword. The returned datetime objects represent +UTC with no time-zone offset, even if the specified +units contain a time-zone offset.

    +

    times: numeric time values.

    +

    units: a string of the form +describing the time units. can be days, hours, minutes, +seconds, milliseconds or microseconds. is the time +origin. months since is allowed only for the 360_day calendar +and common_years since is allowed only for the 365_day calendar.

    +

    calendar: describes the calendar used in the time calculations. +All the values currently defined in the +CF metadata convention <http://cfconventions.org/cf-conventions/cf-conventions#calendar>__ are supported. +Valid calendars 'standard', 'gregorian', 'proleptic_gregorian' +'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'. +Default is 'standard', which is a mixed Julian/Gregorian calendar.

    +

    only_use_cftime_datetimes: if False, python datetime.datetime +objects are returned from num2date where possible; if True dates which +subclass cftime.datetime are returned for all calendars. Default True.

    +

    only_use_python_datetimes: always return python datetime.datetime +objects and raise an error if this is not possible. Ignored unless +only_use_cftime_datetimes=False. Default False.

    +

    has_year_zero: if set to True, astronomical year numbering +is used and the year zero exists. +If set to False for real-world +calendars, then historical year numbering is used and the year 1 is +preceded by year -1 and no year zero exists. +The defaults are set to conform with +CF version 1.9 conventions (False for 'julian', 'gregorian'/'standard', True +for 'proleptic_gregorian' (ISO 8601) and True for the idealized +calendars 'noleap'/'365_day', '360_day', 366_day'/'all_leap') +The defaults can only be over-ridden for the real-world calendars, +for the the idealized calendars the year zero +always exists and the has_year_zero kwarg is ignored. +This kwarg is not needed to define calendar systems allowed by CF +(the calendar-specific defaults do this).

    +

    returns a datetime instance, or an array of datetime instances with +microsecond accuracy, if possible.

    +

    Note: If only_use_cftime_datetimes=False and +use_only_python_datetimes=False, the datetime instances +returned are 'real' python datetime +objects if calendar='proleptic_gregorian', or +calendar='standard' or 'gregorian' +and the date is after the breakpoint between the Julian and +Gregorian calendars (1582-10-15). Otherwise, they are ctime.datetime +objects which support some but not all the methods of native python +datetime objects. The datetime instances +do not contain a time-zone offset, even if the specified units +contains one.

    +
    +
    +def set_alignment(...) +
    +
    +
    +
    +
    +def set_chunk_cache(...) +
    +
    +

    set_chunk_cache(self,size=None,nelems=None,preemption=None)

    +

    change netCDF4 chunk cache settings. +See netcdf C library documentation for nc_set_chunk_cache for +details.

    +
    +
    +def stringtoarr(...) +
    +
    +

    stringtoarr(a, NUMCHARS,dtype='S')

    +

    convert a string to a character array of length NUMCHARS

    +

    a: +Input python string.

    +

    NUMCHARS: +number of characters used to represent string +(if len(a) < NUMCHARS, it will be padded on the right with blanks).

    +

    dtype: +type of numpy array to return. +Default is 'S', which +means an array of dtype 'S1' will be returned. +If dtype='U', a +unicode array (dtype = 'U1') will be returned.

    +

    returns a rank 1 numpy character array of length NUMCHARS with datatype 'S1' +(default) or 'U1' (if dtype='U')

    +
    +
    +def stringtochar(...) +
    +
    +

    stringtochar(a,encoding='utf-8')

    +

    convert a string array to a character array with one extra dimension

    +

    a: +Input numpy string array with numpy datatype 'SN' or 'UN', where N +is the number of characters in each string. +Will be converted to +an array of characters (datatype 'S1' or 'U1') of shape a.shape + (N,).

    +

    optional kwarg encoding can be used to specify character encoding (default +utf-8). If encoding is 'none' or 'bytes', a numpy.string_ the input array +is treated a raw byte strings (numpy.string_).

    +

    returns a numpy character array with datatype 'S1' or 'U1' +and shape a.shape + (N,), where N is the length of each string in a.

    +
    +
    +
    +
    +

    Classes

    +
    +
    +class CompoundType +(...) +
    +
    +

    A CompoundType instance is used to describe a compound data +type, and can be passed to the the Dataset.createVariable() method of +a Dataset or Group instance. +Compound data types map to numpy structured arrays. +See CompoundType for more details.

    +

    The instance variables dtype and name should not be modified by +the user.

    +

    __init__(group, datatype, datatype_name)

    +

    CompoundType constructor.

    +

    group: Group instance to associate with the compound datatype.

    +

    datatype: A numpy dtype object describing a structured (a.k.a record) +array. +Can be composed of homogeneous numeric or character data types, or +other structured array data types.

    +

    datatype_name: a Python string containing a description of the +compound data type.

    +

    Note 1: When creating nested compound data types, +the inner compound data types must already be associated with CompoundType +instances (so create CompoundType instances for the innermost structures +first).

    +

    Note 2: CompoundType instances should be created using the +Dataset.createCompoundType() method of a Dataset or +Group instance, not using this class directly.

    +

    Instance variables

    +
    +
    var dtype
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var dtype_view
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var name
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    +
    +
    +class Dataset +(...) +
    +
    +

    A netCDF Dataset is a collection of dimensions, groups, variables and +attributes. Together they describe the meaning of data and relations among +data fields stored in a netCDF file. See Dataset for more +details.

    +

    A list of attribute names corresponding to global netCDF attributes +defined for the Dataset can be obtained with the +Dataset.ncattrs() method. +These attributes can be created by assigning to an attribute of the +Dataset instance. A dictionary containing all the netCDF attribute +name/value pairs is provided by the __dict__ attribute of a +Dataset instance.

    +

    The following class variables are read-only and should not be +modified by the user.

    +

    dimensions: The dimensions dictionary maps the names of +dimensions defined for the Group or Dataset to instances of the +Dimension class.

    +

    variables: The variables dictionary maps the names of variables +defined for this Dataset or Group to instances of the +Variable class.

    +

    groups: The groups dictionary maps the names of groups created for +this Dataset or Group to instances of the Group class (the +Dataset class is simply a special case of the Group class which +describes the root group in the netCDF4 file).

    +

    cmptypes: The cmptypes dictionary maps the names of +compound types defined for the Group or Dataset to instances of the +CompoundType class.

    +

    vltypes: The vltypes dictionary maps the names of +variable-length types defined for the Group or Dataset to instances +of the VLType class.

    +

    enumtypes: The enumtypes dictionary maps the names of +Enum types defined for the Group or Dataset to instances +of the EnumType class.

    +

    data_model: data_model describes the netCDF +data model version, one of NETCDF3_CLASSIC, NETCDF4, +NETCDF4_CLASSIC, NETCDF3_64BIT_OFFSET or NETCDF3_64BIT_DATA.

    +

    file_format: same as data_model, retained for backwards compatibility.

    +

    disk_format: disk_format describes the underlying +file format, one of NETCDF3, HDF5, HDF4, +PNETCDF, DAP2, DAP4 or UNDEFINED. Only available if using +netcdf C library version >= 4.3.1, otherwise will always return +UNDEFINED.

    +

    parent: parent is a reference to the parent +Group instance. None for the root group or Dataset +instance.

    +

    path: path shows the location of the Group in +the Dataset in a unix directory format (the names of groups in the +hierarchy separated by backslashes). A Dataset instance is the root group, so the path is simply '/'.

    -

    keepweakref: If True, child Dimension and Variables objects only keep weak references to the parent Dataset or Group.

    -

    _ncstring_attrs__: If True, all text attributes will be written as variable-length strings.

    -
    - - -
    -
    - - Dataset() - - -
    - - -

    __init__(self, filename, mode="r", clobber=True, diskless=False, +

    __init__(self, filename, mode="r", clobber=True, diskless=False, persist=False, keepweakref=False, memory=None, encoding=None, parallel=False, comm=None, info=None, format='NETCDF4')

    - -

    Dataset constructor.

    - +

    Dataset constructor.

    filename: Name of netCDF file to hold dataset. Can also -be a python 3 pathlib instance or the URL of an OpenDAP dataset. When memory is -set this is just used to set the filepath().

    - +be a python 3 pathlib instance or the URL of an OpenDAP dataset. +When memory is +set this is just used to set the filepath().

    mode: access mode. r means read-only; no data can be modified. w means write; a new file is created, an existing file with the same name is deleted. x means write, but fail if an existing -file with the same name already exists. a and r+ mean append; -an existing file is opened for reading and writing, if +file with the same name already exists. a and r+ mean append; +an existing file is opened for reading and writing, if file does not exist already, one is created. Appending s to modes r, w, r+ or a will enable unbuffered shared access to NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET or @@ -1805,18 +1476,18 @@

    In-memory (diskless) Datasets

    access, since it may be faster for programs that don't access data sequentially. This option is ignored for NETCDF4 and NETCDF4_CLASSIC formatted files.

    -

    clobber: if True (default), opening a file with mode='w' -will clobber an existing file with the same name. if False, an +will clobber an existing file with the same name. +if False, an exception will be raised if a file with the same name already exists. mode=x is identical to mode=w with clobber=False.

    -

    format: underlying file format (one of 'NETCDF4', -'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC', 'NETCDF3_64BIT_OFFSET' or +'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC'<code>, </code>'NETCDF3_64BIT_OFFSET' or 'NETCDF3_64BIT_DATA'. Only relevant if mode = 'w' (if mode = 'r','a' or 'r+' the file format is automatically detected). Default 'NETCDF4', which means the data is -stored in an HDF5 file, using netCDF 4 API features. Setting +stored in an HDF5 file, using netCDF 4 API features. +Setting format='NETCDF4_CLASSIC' will create an HDF5 file, using only netCDF 3 compatible API features. netCDF 3 clients must be recompiled and linked against the netCDF 4 library to read files in NETCDF4_CLASSIC format. @@ -1828,18 +1499,17 @@

    In-memory (diskless) Datasets

    file format, which supports 64-bit dimension sizes plus unsigned and 64 bit integer data types, but is only compatible with clients linked against netCDF version 4.4.0 or later.

    -

    diskless: If True, create diskless (in-core) file. This is a feature added to the C library after the netcdf-4.2 release. If you need to access the memory buffer directly, use the in-memory feature instead (see memory kwarg).

    -

    persist: if diskless=True, persist file to disk when closed (default False).

    -

    keepweakref: if True, child Dimension and Variable instances will keep weak -references to the parent Dataset or Group object. Default is False, which -means strong references will be kept. Having Dimension and Variable instances +references to the parent Dataset or Group object. +Default is False, which +means strong references will be kept. +Having Dimension and Variable instances keep a strong reference to the parent Dataset instance, which in turn keeps a reference to child Dimension and Variable instances, creates circular references. Circular references complicate garbage collection, which may mean increased @@ -1847,350 +1517,259 @@

    In-memory (diskless) Datasets

    Variables. It also will result in the Dataset object never being deleted, which means it may keep open files alive as well. Setting keepweakref=True allows Dataset instances to be garbage collected as soon as they go out of scope, potentially -reducing memory usage and open file handles. However, in many cases this is not +reducing memory usage and open file handles. +However, in many cases this is not desirable, since the associated Variable instances may still be needed, but are rendered unusable when the parent Dataset instance is garbage collected.

    -

    memory: if not None, create or open an in-memory Dataset. If mode = r, the memory kwarg must contain a memory buffer object (an object that supports the python buffer interface). The Dataset will then be created with contents taken from this block of memory. If mode = w, the memory kwarg should contain the anticipated size -of the Dataset in bytes (used only for NETCDF3 files). A memory +of the Dataset in bytes (used only for NETCDF3 files). +A memory buffer containing a copy of the Dataset is returned by the -Dataset.close method. Requires netcdf-c version 4.4.1 for mode=r +Dataset.close() method. Requires netcdf-c version 4.4.1 for mode=r netcdf-c 4.6.2 for mode=w. To persist the file to disk, the raw bytes from the returned buffer can be written into a binary file. The Dataset can also be re-opened using this memory buffer.

    -

    encoding: encoding used to encode filename string into bytes. Default is None (sys.getdefaultfileencoding() is used).

    -

    parallel: open for parallel access using MPI (requires mpi4py and -parallel-enabled netcdf-c and hdf5 libraries). Default is False. If +parallel-enabled netcdf-c and hdf5 libraries). +Default is False. If True, comm and info kwargs may also be specified.

    -

    comm: MPI_Comm object for parallel access. Default None, which -means MPI_COMM_WORLD will be used. Ignored if parallel=False.

    - +means MPI_COMM_WORLD will be used. +Ignored if parallel=False.

    info: MPI_Info object for parallel access. Default None, which -means MPI_INFO_NULL will be used. Ignored if parallel=False.

    -
    - - -
    -
    -
    - - def - filepath(unknown): - - -
    - - -

    filepath(self,encoding=None)

    - -

    Get the file system path (or the opendap URL) which was used to -open/create the Dataset. Requires netcdf >= 4.1.2. The path -is decoded into a string using sys.getfilesystemencoding() by default, this can be -changed using the encoding kwarg.

    -
    - - -
    -
    -
    - - def - close(unknown): - - -
    - - -

    close(self)

    - -

    Close the Dataset.

    -
    - - -
    -
    -
    - - def - isopen(unknown): - - -
    - - -

    isopen(self)

    - -

    Is the Dataset open or closed?

    -
    - - -
    -
    -
    - - def - sync(unknown): - - -
    - - -

    sync(self)

    - -

    Writes all buffered data in the Dataset to the disk file.

    -
    - - -
    -
    -
    - - def - set_fill_on(unknown): - - -
    - - -

    set_fill_on(self)

    - -

    Sets the fill mode for a Dataset open for writing to on.

    - -

    This causes data to be pre-filled with fill values. The fill values can be -controlled by the variable's _Fill_Value attribute, but is usually -sufficient to the use the netCDF default _Fill_Value (defined -separately for each variable type). The default behavior of the netCDF -library corresponds to set_fill_on. Data which are equal to the -_Fill_Value indicate that the variable was created, but never written -to.

    -
    - - -
    -
    -
    - - def - set_fill_off(unknown): - - -
    - - -

    set_fill_off(self)

    - -

    Sets the fill mode for a Dataset open for writing to off.

    - -

    This will prevent the data from being pre-filled with fill values, which -may result in some performance improvements. However, you must then make -sure the data is actually written before being read.

    -
    - - -
    -
    -
    - - def - createDimension(unknown): - - -
    - - -

    createDimension(self, dimname, size=None)

    - +means MPI_INFO_NULL will be used. +Ignored if parallel=False.

    +

    Subclasses

    +
      +
    • netCDF4._netCDF4.Group
      • +
    • netCDF4._netCDF4.MFDataset
      • +
    +

    Static methods

    +
    +
    +def fromcdl(...) +
    +
    +

    fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')

    +

    call ncgen via subprocess to create Dataset from CDL +text representation. Requires ncgen to be installed and in $PATH.

    +

    cdlfilename: +CDL file.

    +

    ncfilename: netCDF file to create. If not given, CDL filename with +suffix replaced by .nc is used..

    +

    mode: +Access mode to open Dataset (Default 'a').

    +

    format: underlying file format to use (one of 'NETCDF4', +'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC'<code>, </code>'NETCDF3_64BIT_OFFSET' or +'NETCDF3_64BIT_DATA'. Default 'NETCDF4'.

    +

    Dataset instance for ncfilename is returned.

    +
    +
    +

    Instance variables

    +
    +
    var cmptypes
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var data_model
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var dimensions
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var disk_format
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var enumtypes
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var file_format
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var groups
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var keepweakref
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var name
    +
    +

    string name of Group instance

    +
    +
    var parent
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var path
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var variables
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var vltypes
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    +

    Methods

    +
    +
    +def close(...) +
    +
    +

    close(self)

    +

    Close the Dataset.

    +
    +
    +def createCompoundType(...) +
    +
    +

    createCompoundType(self, datatype, datatype_name)

    +

    Creates a new compound data type named datatype_name from the numpy +dtype object datatype.

    +

    Note: If the new compound data type contains other compound data types +(i.e. it is a 'nested' compound type, where not all of the elements +are homogeneous numeric data types), then the 'inner' compound types must be +created first.

    +

    The return value is the CompoundType class instance describing the new +datatype.

    +
    +
    +def createDimension(...) +
    +
    +

    createDimension(self, dimname, size=None)

    Creates a new dimension with the given dimname and size.

    -

    size must be a positive integer or None, which stands for "unlimited" (default is None). Specifying a size of 0 also -results in an unlimited dimension. The return value is the Dimension -class instance describing the new dimension. To determine the current -maximum size of the dimension, use the len function on the Dimension +results in an unlimited dimension. The return value is the Dimension +class instance describing the new dimension. +To determine the current +maximum size of the dimension, use the len function on the Dimension instance. To determine if a dimension is 'unlimited', use the -Dimension.isunlimited method of the Dimension instance.

    -
    - - -
    -
    -
    - - def - renameDimension(unknown): - - -
    - - -

    renameDimension(self, oldname, newname)

    - -

    rename a Dimension named oldname to newname.

    -
    - - -
    -
    -
    - - def - createCompoundType(unknown): - - -
    - - -

    createCompoundType(self, datatype, datatype_name)

    - -

    Creates a new compound data type named datatype_name from the numpy -dtype object datatype.

    - -

    Note: If the new compound data type contains other compound data types -(i.e. it is a 'nested' compound type, where not all of the elements -are homogeneous numeric data types), then the 'inner' compound types must be -created first.

    - -

    The return value is the CompoundType class instance describing the new -datatype.

    -
    - - -
    -
    -
    - - def - createVLType(unknown): - - -
    - - -

    createVLType(self, datatype, datatype_name)

    - -

    Creates a new VLEN data type named datatype_name from a numpy -dtype object datatype.

    - -

    The return value is the VLType class instance describing the new -datatype.

    -
    - - -
    -
    -
    - - def - createEnumType(unknown): - - -
    - - -

    createEnumType(self, datatype, datatype_name, enum_dict)

    - +Dimension.isunlimited() method of the Dimension instance.

    +
    +
    +def createEnumType(...) +
    +
    +

    createEnumType(self, datatype, datatype_name, enum_dict)

    Creates a new Enum data type named datatype_name from a numpy integer dtype object datatype, and a python dictionary defining the enum fields and values.

    - -

    The return value is the EnumType class instance describing the new -datatype.

    -
    - - -
    -
    -
    - - def - createVariable(unknown): - - -
    - - -

    createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False, +

    The return value is the EnumType class instance describing the new +datatype.

    + +
    +def createGroup(...) +
    +
    +

    createGroup(self, groupname)

    +

    Creates a new Group with the given groupname.

    +

    If groupname is specified as a path, using forward slashes as in unix to +separate components, then intermediate groups will be created as necessary +(analogous to mkdir -p in unix). +For example, +createGroup('/GroupA/GroupB/GroupC') will create GroupA, +GroupA/GroupB, and GroupA/GroupB/GroupC, if they don't already exist. +If the specified path describes a group that already exists, no error is +raised.

    +

    The return value is a Group class instance.

    +
    +
    +def createVLType(...) +
    +
    +

    createVLType(self, datatype, datatype_name)

    +

    Creates a new VLEN data type named datatype_name from a numpy +dtype object datatype.

    +

    The return value is the VLType class instance describing the new +datatype.

    +
    +
    +def createVariable(...) +
    +
    +

    createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, szip_coding='nn', szip_pixels_per_block=8, blosc_shuffle=1, endian='native', least_significant_digit=None, significant_digits=None, quantize_mode='BitGroom', fill_value=None, chunk_cache=None)

    -

    Creates a new variable with the given varname, datatype, and dimensions. If dimensions are not given, the variable is assumed to be a scalar.

    -

    If varname is specified as a path, using forward slashes as in unix to separate components, then intermediate groups will be created as necessary For example, createVariable('/GroupA/GroupB/VarC', float, ('x','y')) will create groups GroupA and GroupA/GroupB, plus the variable GroupA/GroupB/VarC, if the preceding groups don't already exist.

    -

    The datatype can be a numpy datatype object, or a string that describes a numpy dtype object (like the dtype.str attribute of a numpy array). Supported specifiers include: 'S1' or 'c' (NC_CHAR), 'i1' or 'b' or 'B' (NC_BYTE), 'u1' (NC_UBYTE), 'i2' or 'h' or 's' (NC_SHORT), 'u2' (NC_USHORT), 'i4' or 'i' or 'l' (NC_INT), 'u4' (NC_UINT), 'i8' (NC_INT64), 'u8' (NC_UINT64), 'f4' or 'f' (NC_FLOAT), 'f8' or 'd' (NC_DOUBLE). -datatype can also be a CompoundType instance -(for a structured, or compound array), a VLType instance +datatype can also be a CompoundType instance +(for a structured, or compound array), a VLType instance (for a variable-length array), or the python str builtin (for a variable-length string array). Numpy string and unicode datatypes with length greater than one are aliases for str.

    -

    Data from netCDF variables is presented to python as numpy arrays with the corresponding data type.

    - -

    dimensions must be a tuple containing Dimension instances and/or +

    dimensions must be a tuple containing Dimension instances and/or dimension names (strings) that have been defined -previously using Dataset.createDimension. The default value +previously using Dataset.createDimension(). The default value is an empty tuple, which means the variable is a scalar.

    -

    If the optional keyword argument compression is set, the data will be compressed in the netCDF file using the specified compression algorithm. Currently zlib,szip,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc, blosc_zlib and blosc_zstd are supported. -Default is None (no compression). All of the compressors except +Default is None (no compression). +All of the compressors except zlib and szip use the HDF5 plugin architecture.

    -

    If the optional keyword zlib is True, the data will be compressed in -the netCDF file using zlib compression (default False). The use of this option is +the netCDF file using zlib compression (default False). +The use of this option is deprecated in favor of compression='zlib'.

    -

    The optional keyword complevel is an integer between 0 and 9 describing the level of compression desired (default 4). Ignored if compression=None. A value of zero disables compression.

    -

    If the optional keyword shuffle is True, the HDF5 shuffle filter -will be applied before compressing the data with zlib (default True). This +will be applied before compressing the data with zlib (default True). +This significantly improves compression. Default is True. Ignored if zlib=False.

    - -

    The optional kwarg blosc_shuffleis ignored +

    The optional kwarg blosc_shuffleis +ignored unless the blosc compressor is used. blosc_shuffle can be 0 (no shuffle), 1 (byte-wise shuffle) or 2 (bit-wise shuffle). Default is 1.

    -

    The optional kwargs szip_coding and szip_pixels_per_block are ignored unless the szip compressor is used. szip_coding can be ec (entropy coding) or nn (nearest neighbor coding). Default is nn. szip_pixels_per_block can be 4, 8, 16 or 32 (default 8).

    -

    If the optional keyword fletcher32 is True, the Fletcher32 HDF5 checksum algorithm is activated to detect errors. Default False.

    -

    If the optional keyword contiguous is True, the variable data is -stored contiguously on disk. Default False. Setting to True for +stored contiguously on disk. +Default False. Setting to True for a variable with an unlimited dimension will trigger an error. Fixed size variables (with no unlimited dimension) with no compression filters are contiguous by default.

    -

    The optional keyword chunksizes can be used to manually specify the HDF5 chunksizes for each dimension of the variable. A detailed discussion of HDF chunking and I/O performance is available @@ -2200,7 +1779,6 @@

    In-memory (diskless) Datasets

    Basically, you want the chunk size for each dimension to match as closely as possible the size of the data block that users will read from the file. chunksizes cannot be set if contiguous=True.

    -

    The optional keyword endian can be used to control whether the data is stored in little or big endian format on disk. Possible values are little, big or native (default). The library @@ -2208,12 +1786,10 @@

    In-memory (diskless) Datasets

    but if the data is always going to be read on a computer with the opposite format as the one used to create the file, there may be some performance advantage to be gained by setting the endian-ness.

    -

    The optional keyword fill_value can be used to override the default netCDF _FillValue (the value that the variable gets filled with before any data is written to it, defaults given in the dict netCDF4.default_fillvals). If fill_value is set to False, then the variable is not pre-filled.

    -

    If the optional keyword parameters least_significant_digit or significant_digits are specified, variable data will be truncated (quantized). In conjunction with compression='zlib' this produces 'lossy', but significantly more @@ -2222,688 +1798,717 @@

    In-memory (diskless) Datasets

    scale = 2**bits, and bits is determined so that a precision of 0.1 is retained (in this case bits=4). From the PSL metadata conventions: -"least_significant_digit -- power of ten of the smallest decimal place +"least_significant_digit – power of ten of the smallest decimal place in unpacked data that is a reliable value." Default is None, or no -quantization, or 'lossless' compression. If significant_digits=3 +quantization, or 'lossless' compression. +If significant_digits=3 then the data will be quantized so that three significant digits are retained, independent of the floating point exponent. The keyword argument quantize_mode controls the quantization algorithm (default 'BitGroom', 'BitRound' and -'GranularBitRound' also available). The 'GranularBitRound' +'GranularBitRound' also available). +The 'GranularBitRound' algorithm may result in better compression for typical geophysical datasets. -This significant_digits kwarg is only available with netcdf-c >= 4.9.0, and +This significant_digits kwarg is only available +with netcdf-c >= 4.9.0, and only works with NETCDF4 or NETCDF4_CLASSIC formatted files.

    -

    When creating variables in a NETCDF4 or NETCDF4_CLASSIC formatted file, -HDF5 creates something called a 'chunk cache' for each variable. The +HDF5 creates something called a 'chunk cache' for each variable. +The default size of the chunk cache may be large enough to completely fill -available memory when creating thousands of variables. The optional +available memory when creating thousands of variables. +The optional keyword chunk_cache allows you to reduce (or increase) the size of -the default chunk cache when creating a variable. The setting only +the default chunk cache when creating a variable. +The setting only persists as long as the Dataset is open - you can use the set_var_chunk_cache method to change it the next time the Dataset is opened. Warning - messing with this parameter can seriously degrade performance.

    - -

    The return value is the Variable class instance describing the new +

    The return value is the Variable class instance describing the new variable.

    -

    A list of names corresponding to netCDF variable attributes can be -obtained with the Variable method Variable.ncattrs. A dictionary +obtained with the Variable method Variable.ncattrs(). A dictionary containing all the netCDF attribute name/value pairs is provided by -the __dict__ attribute of a Variable instance.

    - -

    Variable instances behave much like array objects. Data can be +the __dict__ attribute of a Variable instance.

    +

    Variable instances behave much like array objects. Data can be assigned to or retrieved from a variable with indexing and slicing -operations on the Variable instance. A Variable instance has six +operations on the Variable instance. A Variable instance has six Dataset standard attributes: dimensions, dtype, shape, ndim, name and least_significant_digit. Application programs should never modify these attributes. The dimensions attribute is a tuple containing the names of the dimensions associated with this variable. The dtype attribute is a string describing the variable's data type (i4, f8, -S1, etc). The shape attribute is a tuple describing the current -sizes of all the variable's dimensions. The name attribute is a +S1,<code> etc). The </code>shape attribute is a tuple describing the current +sizes of all the variable's dimensions. The name attribute is a string containing the name of the Variable instance. The least_significant_digit attributes describes the power of ten of the smallest decimal place in -the data the contains a reliable value. assigned to the Variable +the data the contains a reliable value. +assigned to the Variable instance. The ndim attribute -is the number of variable dimensions.

    -
    - - -
    -
    -
    - - def - renameVariable(unknown): - - -
    - - -

    renameVariable(self, oldname, newname)

    - -

    rename a Variable named oldname to newname

    -
    - - -
    -
    -
    - - def - createGroup(unknown): - - -
    - - -

    createGroup(self, groupname)

    - -

    Creates a new Group with the given groupname.

    - -

    If groupname is specified as a path, using forward slashes as in unix to -separate components, then intermediate groups will be created as necessary -(analogous to mkdir -p in unix). For example, -createGroup('/GroupA/GroupB/GroupC') will create GroupA, -GroupA/GroupB, and GroupA/GroupB/GroupC, if they don't already exist. -If the specified path describes a group that already exists, no error is -raised.

    - -

    The return value is a Group class instance.

    -
    - - -
    -
    -
    - - def - ncattrs(unknown): - - -
    - - -

    ncattrs(self)

    - -

    return netCDF global attribute names for this Dataset or Group in a list.

    -
    - - -
    -
    -
    - - def - setncattr(unknown): - - -
    - - -

    setncattr(self,name,value)

    - -

    set a netCDF dataset or group attribute using name,value pair. -Use if you need to set a netCDF attribute with the -with the same name as one of the reserved python attributes.

    -
    - - -
    -
    -
    - - def - setncattr_string(unknown): - - -
    - - -

    setncattr_string(self,name,value)

    - -

    set a netCDF dataset or group string attribute using name,value pair. -Use if you need to ensure that a netCDF attribute is created with type -NC_STRING if the file format is NETCDF4.

    -
    - - -
    -
    -
    - - def - setncatts(unknown): - - -
    - - -

    setncatts(self,attdict)

    - -

    set a bunch of netCDF dataset or group attributes at once using a python dictionary. -This may be faster when setting a lot of attributes for a NETCDF3 -formatted file, since nc_redef/nc_enddef is not called in between setting -each attribute

    -
    - - -
    -
    -
    - - def - getncattr(unknown): - - -
    - - -

    getncattr(self,name)

    - +is the number of variable dimensions.

    + +
    +def delncattr(...) +
    +
    +

    delncattr(self,name,value)

    +

    delete a netCDF dataset or group attribute. +Use if you need to delete a +netCDF attribute with the same name as one of the reserved python +attributes.

    +
    +
    +def filepath(...) +
    +
    +

    filepath(self,encoding=None)

    +

    Get the file system path (or the opendap URL) which was used to +open/create the Dataset. Requires netcdf >= 4.1.2. +The path +is decoded into a string using sys.getfilesystemencoding() by default, this can be +changed using the encoding kwarg.

    +
    +
    +def get_variables_by_attributes(...) +
    +
    +

    get_variables_by_attributes(self, **kwargs)

    +

    Returns a list of variables that match specific conditions.

    +

    Can pass in key=value parameters and variables are returned that +contain all of the matches. For example,

    +
    >>> # Get variables with x-axis attribute.
+>>> vs = nc.get_variables_by_attributes(axis='X')
+>>> # Get variables with matching "standard_name" attribute
+>>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
+
    +

    Can pass in key=callable parameter and variables are returned if the +callable returns True. +The callable should accept a single parameter, +the attribute value. +None is given as the attribute value when the +attribute does not exist on the variable. For example,

    +
    >>> # Get Axis variables
+>>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
+>>> # Get variables that don't have an "axis" attribute
+>>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
+>>> # Get variables that have a "grid_mapping" attribute
+>>> vs = nc.get_variables_by_attributes(grid_mapping=lambda v: v is not None)
+
    +
    +
    +def getncattr(...) +
    +
    +

    getncattr(self,name)

    retrieve a netCDF dataset or group attribute. Use if you need to get a netCDF attribute with the same name as one of the reserved python attributes.

    -

    option kwarg encoding can be used to specify the -character encoding of a string attribute (default is utf-8).

    -
    - - -
    -
    -
    - - def - delncattr(unknown): - - -
    - - -

    delncattr(self,name,value)

    - -

    delete a netCDF dataset or group attribute. Use if you need to delete a -netCDF attribute with the same name as one of the reserved python -attributes.

    -
    - - -
    -
    -
    - - def - renameAttribute(unknown): - - -
    - - -

    renameAttribute(self, oldname, newname)

    - -

    rename a Dataset or Group attribute named oldname to newname.

    -
    - - -
    -
    -
    - - def - renameGroup(unknown): - - -
    - - -

    renameGroup(self, oldname, newname)

    - -

    rename a Group named oldname to newname (requires netcdf >= 4.3.1).

    -
    - - -
    -
    -
    - - def - set_auto_chartostring(unknown): - - -
    - - -

    set_auto_chartostring(self, True_or_False)

    - -

    Call Variable.set_auto_chartostring for all variables contained in this Dataset or -Group, as well as for all variables in all its subgroups.

    - +character encoding of a string attribute (default is utf-8).

    + +
    +def has_blosc_filter(...) +
    +
    +

    has_blosc_filter(self) +returns True if blosc compression filter is available

    +
    +
    +def has_bzip2_filter(...) +
    +
    +

    has_bzip2_filter(self) +returns True if bzip2 compression filter is available

    +
    +
    +def has_szip_filter(...) +
    +
    +

    has_szip_filter(self) +returns True if szip compression filter is available

    +
    +
    +def has_zstd_filter(...) +
    +
    +

    has_zstd_filter(self) +returns True if zstd compression filter is available

    +
    +
    +def isopen(...) +
    +
    +

    isopen(self)

    +

    Is the Dataset open or closed?

    +
    +
    +def ncattrs(...) +
    +
    +

    ncattrs(self)

    +

    return netCDF global attribute names for this Dataset or Group in a list.

    +
    +
    +def renameAttribute(...) +
    +
    +

    renameAttribute(self, oldname, newname)

    +

    rename a Dataset or Group attribute named oldname to newname.

    +
    +
    +def renameDimension(...) +
    +
    +

    renameDimension(self, oldname, newname)

    +

    rename a Dimension named oldname to newname.

    +
    +
    +def renameGroup(...) +
    +
    +

    renameGroup(self, oldname, newname)

    +

    rename a Group named oldname to newname (requires netcdf >= 4.3.1).

    +
    +
    +def renameVariable(...) +
    +
    +

    renameVariable(self, oldname, newname)

    +

    rename a Variable named oldname to newname

    +
    +
    +def set_always_mask(...) +
    +
    +

    set_always_mask(self, True_or_False)

    +

    Call Variable.set_always_mask() for all variables contained in +this Dataset or Group, as well as for all +variables in all its subgroups.

    +

    True_or_False: Boolean determining if automatic conversion of +masked arrays with no missing values to regular numpy arrays shall be +applied for all variables. Default True. Set to False to restore the default behaviour +in versions prior to 1.4.1 (numpy array returned unless missing values are present, +otherwise masked array returned).

    +

    Note: Calling this function only affects existing +variables. Variables created after calling this function will follow +the default behaviour.

    +
    +
    +def set_auto_chartostring(...) +
    +
    +

    set_auto_chartostring(self, True_or_False)

    +

    Call Variable.set_auto_chartostring() for all variables contained in this Dataset or +Group, as well as for all variables in all its subgroups.

    True_or_False: Boolean determining if automatic conversion of -all character arrays <--> string arrays should be performed for +all character arrays <–> string arrays should be performed for character variables (variables of type NC_CHAR or S1) with the _Encoding attribute set.

    - -

    Note: Calling this function only affects existing variables. Variables created -after calling this function will follow the default behaviour.

    -
    - - -
    -
    -
    - - def - set_auto_maskandscale(unknown): - - -
    - - -

    set_auto_maskandscale(self, True_or_False)

    - -

    Call Variable.set_auto_maskandscale for all variables contained in this Dataset or -Group, as well as for all variables in all its subgroups.

    - -

    True_or_False: Boolean determining if automatic conversion to masked arrays -and variable scaling shall be applied for all variables.

    -

    Note: Calling this function only affects existing variables. Variables created -after calling this function will follow the default behaviour.

    -
    - - -
    -
    -
    - - def - set_auto_mask(unknown): - - -
    - - -

    set_auto_mask(self, True_or_False)

    - -

    Call Variable.set_auto_mask for all variables contained in this Dataset or -Group, as well as for all variables in all its subgroups. Only affects +after calling this function will follow the default behaviour.

    + +
    +def set_auto_mask(...) +
    +
    +

    set_auto_mask(self, True_or_False)

    +

    Call Variable.set_auto_mask() for all variables contained in this Dataset or +Group, as well as for all variables in all its subgroups. Only affects Variables with primitive or enum types (not compound or vlen Variables).

    -

    True_or_False: Boolean determining if automatic conversion to masked arrays shall be applied for all variables.

    -

    Note: Calling this function only affects existing variables. Variables created -after calling this function will follow the default behaviour.

    -
    - - -
    -
    -
    - - def - set_auto_scale(unknown): - - -
    - - -

    set_auto_scale(self, True_or_False)

    - -

    Call Variable.set_auto_scale for all variables contained in this Dataset or -Group, as well as for all variables in all its subgroups.

    - +after calling this function will follow the default behaviour.

    + +
    +def set_auto_maskandscale(...) +
    +
    +

    set_auto_maskandscale(self, True_or_False)

    +

    Call Variable.set_auto_maskandscale() for all variables contained in this Dataset or +Group, as well as for all variables in all its subgroups.

    +

    True_or_False: Boolean determining if automatic conversion to masked arrays +and variable scaling shall be applied for all variables.

    +

    Note: Calling this function only affects existing variables. Variables created +after calling this function will follow the default behaviour.

    +
    +
    +def set_auto_scale(...) +
    +
    +

    set_auto_scale(self, True_or_False)

    +

    Call Variable.set_auto_scale() for all variables contained in this Dataset or +Group, as well as for all variables in all its subgroups.

    True_or_False: Boolean determining if automatic variable scaling shall be applied for all variables.

    -

    Note: Calling this function only affects existing variables. Variables created -after calling this function will follow the default behaviour.

    -
    - - -
    -
    -
    - - def - set_always_mask(unknown): - - -
    - - -

    set_always_mask(self, True_or_False)

    - -

    Call Variable.set_always_mask for all variables contained in -this Dataset or Group, as well as for all -variables in all its subgroups.

    - -

    True_or_False: Boolean determining if automatic conversion of -masked arrays with no missing values to regular numpy arrays shall be -applied for all variables. Default True. Set to False to restore the default behaviour -in versions prior to 1.4.1 (numpy array returned unless missing values are present, -otherwise masked array returned).

    - -

    Note: Calling this function only affects existing -variables. Variables created after calling this function will follow -the default behaviour.

    -
    - - -
    -
    -
    - - def - set_ncstring_attrs(unknown): - - -
    - - -

    set_ncstring_attrs(self, True_or_False)

    - -

    Call Variable.set_ncstring_attrs for all variables contained in -this Dataset or Group, as well as for all its +after calling this function will follow the default behaviour.

    + +
    +def set_fill_off(...) +
    +
    +

    set_fill_off(self)

    +

    Sets the fill mode for a Dataset open for writing to off.

    +

    This will prevent the data from being pre-filled with fill values, which +may result in some performance improvements. However, you must then make +sure the data is actually written before being read.

    +
    +
    +def set_fill_on(...) +
    +
    +

    set_fill_on(self)

    +

    Sets the fill mode for a Dataset open for writing to on.

    +

    This causes data to be pre-filled with fill values. The fill values can be +controlled by the variable's _Fill_Value attribute, but is usually +sufficient to the use the netCDF default _Fill_Value (defined +separately for each variable type). The default behavior of the netCDF +library corresponds to set_fill_on. +Data which are equal to the +_Fill_Value indicate that the variable was created, but never written +to.

    +
    +
    +def set_ncstring_attrs(...) +
    +
    +

    set_ncstring_attrs(self, True_or_False)

    +

    Call Variable.set_ncstring_attrs() for all variables contained in +this Dataset or Group, as well as for all its subgroups and their variables.

    -

    True_or_False: Boolean determining if all string attributes are created as variable-length NC_STRINGs, (if True), or if ascii text attributes are stored as NC_CHARs (if False; default)

    -

    Note: Calling this function only affects newly created attributes -of existing (sub-) groups and their variables.

    -
    - - -
    -
    -
    - - def - get_variables_by_attributes(unknown): - - -
    - - -

    get_variables_by_attribute(self, **kwargs)

    - -

    Returns a list of variables that match specific conditions.

    - -

    Can pass in key=value parameters and variables are returned that -contain all of the matches. For example,

    - -
    -
    >>> # Get variables with x-axis attribute.
->>> vs = nc.get_variables_by_attributes(axis='X')
->>> # Get variables with matching "standard_name" attribute
->>> vs = nc.get_variables_by_attributes(standard_name='northward_sea_water_velocity')
-
    -
    - -

    Can pass in key=callable parameter and variables are returned if the -callable returns True. The callable should accept a single parameter, -the attribute value. None is given as the attribute value when the -attribute does not exist on the variable. For example,

    - -
    -
    >>> # Get Axis variables
->>> vs = nc.get_variables_by_attributes(axis=lambda v: v in ['X', 'Y', 'Z', 'T'])
->>> # Get variables that don't have an "axis" attribute
->>> vs = nc.get_variables_by_attributes(axis=lambda v: v is None)
->>> # Get variables that have a "grid_mapping" attribute
->>> vs = nc.get_variables_by_attributes(grid_mapping=lambda v: v is not None)
-
    -
    -
    - - -
    -
    -
    - - def - fromcdl(unknown): - - -
    - - -

    fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')

    - -

    call ncgen via subprocess to create Dataset from CDL -text representation. Requires ncgen to be installed and in $PATH.

    - -

    cdlfilename: CDL file.

    - -

    ncfilename: netCDF file to create. If not given, CDL filename with -suffix replaced by .nc is used..

    - -

    mode: Access mode to open Dataset (Default 'a').

    - -

    format: underlying file format to use (one of 'NETCDF4', -'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC', 'NETCDF3_64BIT_OFFSET' or -'NETCDF3_64BIT_DATA'. Default 'NETCDF4'.

    - -

    Dataset instance for ncfilename is returned.

    -
    - - -
    -
    -
    - - def - tocdl(unknown): - - -
    - - -

    tocdl(self, coordvars=False, data=False, outfile=None)

    - +of existing (sub-) groups and their variables.

    + +
    +def setncattr(...) +
    +
    +

    setncattr(self,name,value)

    +

    set a netCDF dataset or group attribute using name,value pair. +Use if you need to set a netCDF attribute with the +with the same name as one of the reserved python attributes.

    +
    +
    +def setncattr_string(...) +
    +
    +

    setncattr_string(self,name,value)

    +

    set a netCDF dataset or group string attribute using name,value pair. +Use if you need to ensure that a netCDF attribute is created with type +NC_STRING if the file format is NETCDF4.

    +
    +
    +def setncatts(...) +
    +
    +

    setncatts(self,attdict)

    +

    set a bunch of netCDF dataset or group attributes at once using a python dictionary. +This may be faster when setting a lot of attributes for a NETCDF3 +formatted file, since nc_redef/nc_enddef is not called in between setting +each attribute

    +
    +
    +def sync(...) +
    +
    +

    sync(self)

    +

    Writes all buffered data in the Dataset to the disk file.

    +
    +
    +def tocdl(...) +
    +
    +

    tocdl(self, coordvars=False, data=False, outfile=None)

    call ncdump via subprocess to create CDL text representation of Dataset. Requires ncdump to be installed and in $PATH.

    -

    coordvars: include coordinate variable data (via ncdump -c). Default False

    -

    data: if True, write out variable data (Default False).

    - -

    outfile: If not None, file to output ncdump to. Default is to return a string.

    -
    - - -
    -
    -
    - - def - has_blosc_filter(unknown): - - -
    - - -

    has_blosc_filter(self) -returns True if blosc compression filter is available

    -
    - - -
    -
    -
    - - def - has_zstd_filter(unknown): - - -
    - - -

    has_zstd_filter(self) -returns True if zstd compression filter is available

    -
    - - -
    -
    -
    - - def - has_bzip2_filter(unknown): - - -
    - - -

    has_bzip2_filter(self) -returns True if bzip2 compression filter is available

    -
    - - -
    -
    -
    - - def - has_szip_filter(unknown): - - -
    - - -

    has_szip_filter(self) -returns True if szip compression filter is available

    -
    - - -
    -
    -
    - name - - -
    - - -

    string name of Group instance

    -
    - - -
    - -
    -
    - - class - Variable: - - -
    - - -

    A netCDF Variable is used to read and write netCDF data. They are -analogous to numpy array objects. See Variable.__init__ for more +

    outfile: If not None, file to output ncdump to. Default is to return a string.

    + + + +
    +class Dimension +(...) +
    +
    +

    A netCDF Dimension is used to describe the coordinates of a Variable. +See Dimension for more details.

    +

    The current maximum size of a Dimension instance can be obtained by +calling the python len function on the Dimension instance. The +Dimension.isunlimited() method of a Dimension instance can be used to +determine if the dimension is unlimited.

    +

    Read-only class variables:

    +

    name: String name, used when creating a Variable with +Dataset.createVariable().

    +

    size: Current Dimension size (same as len(d), where d is a +Dimension instance).

    +

    __init__(self, group, name, size=None)

    +

    Dimension constructor.

    +

    group: Group instance to associate with dimension.

    +

    name: Name of the dimension.

    +

    size: Size of the dimension. None or 0 means unlimited. (Default None).

    +

    Note: Dimension instances should be created using the +Dataset.createDimension() method of a Group or +Dataset instance, not using Dimension directly.

    +

    Instance variables

    +
    +
    var name
    +
    +

    string name of Dimension instance

    +
    +
    var size
    +
    +

    current size of Dimension (calls len on Dimension instance)

    +
    +
    +

    Methods

    +
    +
    +def group(...) +
    +
    +

    group(self)

    +

    return the group that this Dimension is a member of.

    +
    +
    +def isunlimited(...) +
    +
    +

    isunlimited(self)

    +

    returns True if the Dimension instance is unlimited, False otherwise.

    +
    +
    +
    +
    +class EnumType +(...) +
    +
    +

    A EnumType instance is used to describe an Enum data +type, and can be passed to the the Dataset.createVariable() method of +a Dataset or Group instance. See +EnumType for more details.

    +

    The instance variables dtype, name and enum_dict should not be modified by +the user.

    +

    __init__(group, datatype, datatype_name, enum_dict)

    +

    EnumType constructor.

    +

    group: Group instance to associate with the VLEN datatype.

    +

    datatype: An numpy integer dtype object describing the base type +for the Enum.

    +

    datatype_name: a Python string containing a description of the +Enum data type.

    +

    enum_dict: a Python dictionary containing the Enum field/value +pairs.

    +

    Note: EnumType instances should be created using the +Dataset.createEnumType() method of a Dataset or +Group instance, not using this class directly.

    +

    Instance variables

    +
    +
    var dtype
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var enum_dict
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var name
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    +
    +
    +class Group +(...) +
    +
    +

    Groups define a hierarchical namespace within a netCDF file. They are +analogous to directories in a unix filesystem. Each Group behaves like +a Dataset within a Dataset, and can contain it's own variables, +dimensions and attributes (and other Groups). See Group +for more details.

    +

    Group inherits from Dataset, so all the +Dataset class methods and variables are available +to a Group instance (except the close method).

    +

    Additional read-only class variables:

    +

    name: String describing the group name.

    +

    __init__(self, parent, name) +Group constructor.

    +

    parent: Group instance for the parent group. +If being created +in the root group, use a Dataset instance.

    +

    name: - Name of the group.

    +

    Note: Group instances should be created using the +Dataset.createGroup() method of a Dataset instance, or +another Group instance, not using this class directly.

    +

    Ancestors

    +
      +
    • netCDF4._netCDF4.Dataset
      • +
    +

    Methods

    +
    +
    +def close(...) +
    +
    +

    close(self)

    +

    overrides Dataset close method which does not apply to Group +instances, raises OSError.

    +
    +
    +
    +
    +class MFDataset +(files, check=False, aggdim=None, exclude=[], master_file=None) +
    +
    +

    Class for reading multi-file netCDF Datasets, making variables +spanning multiple files appear as if they were in one file. +Datasets must be in NETCDF4_CLASSIC, NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET +or NETCDF3_64BIT_DATA<code> format (</code>NETCDF4 Datasets won't work).

    +

    Adapted from pycdf by Andre Gosselin.

    +

    Example usage (See MFDataset for more details):

    +
    >>> import numpy as np
+>>> # create a series of netCDF files with a variable sharing
+>>> # the same unlimited dimension.
+>>> for nf in range(10):
+...     with Dataset("mftest%s.nc" % nf, "w", format='NETCDF4_CLASSIC') as f:
+...         f.createDimension("x",None)
+...         x = f.createVariable("x","i",("x",))
+...         x[0:10] = np.arange(nf*10,10*(nf+1))
+>>> # now read all those files in at once, in one Dataset.
+>>> f = MFDataset("mftest*nc")
+>>> print(f.variables["x"][:])
+[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
+ 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
+ 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71
+ 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
+ 96 97 98 99]
+
    +

    __init__(self, files, check=False, aggdim=None, exclude=[], +master_file=None)

    +

    Open a Dataset spanning multiple files, making it look as if it was a +single file. Variables in the list of files that share the same +dimension (specified with the keyword aggdim) are aggregated. If +aggdim is not specified, the unlimited is aggregated. +Currently, +aggdim must be the leftmost (slowest varying) dimension of each +of the variables to be aggregated.

    +

    files: either a sequence of netCDF files or a string with a +wildcard (converted to a sorted list of files using glob) +If +the master_file kwarg is not specified, the first file +in the list will become the "master" file, defining all the +variables with an aggregation dimension which may span +subsequent files. Attribute access returns attributes only from "master" +file. The files are always opened in read-only mode.

    +

    check: True if you want to do consistency checking to ensure the +correct variables structure for all of the netcdf files. +Checking makes +the initialization of the MFDataset instance much slower. Default is +False.

    +

    aggdim: The name of the dimension to aggregate over (must +be the leftmost dimension of each of the variables to be aggregated). +If None (default), aggregate over the unlimited dimension.

    +

    exclude: A list of variable names to exclude from aggregation. +Default is an empty list.

    +

    master_file: file to use as "master file", defining all the +variables with an aggregation dimension and all global attributes.

    +

    Ancestors

    +
      +
    • netCDF4._netCDF4.Dataset
      • +
    +

    Methods

    +
    +
    +def close(self) +
    +
    +

    close(self)

    +

    close all the open files.

    +
    +
    +def isopen(self) +
    +
    +

    isopen(self)

    +

    True if all files are open, False otherwise.

    +
    +
    +def ncattrs(self) +
    +
    +

    ncattrs(self)

    +

    return the netcdf attribute names from the master file.

    +
    +
    +
    +
    +class MFTime +(time, units=None, calendar=None) +
    +
    +

    Class providing an interface to a MFDataset time Variable by imposing a unique common +time unit and/or calendar to all files.

    +

    Example usage (See MFTime for more details):

    +
    >>> import numpy as np
+>>> f1 = Dataset("mftest_1.nc","w", format="NETCDF4_CLASSIC")
+>>> f2 = Dataset("mftest_2.nc","w", format="NETCDF4_CLASSIC")
+>>> f1.createDimension("time",None)
+>>> f2.createDimension("time",None)
+>>> t1 = f1.createVariable("time","i",("time",))
+>>> t2 = f2.createVariable("time","i",("time",))
+>>> t1.units = "days since 2000-01-01"
+>>> t2.units = "days since 2000-02-01"
+>>> t1.calendar = "standard"
+>>> t2.calendar = "standard"
+>>> t1[:] = np.arange(31)
+>>> t2[:] = np.arange(30)
+>>> f1.close()
+>>> f2.close()
+>>> # Read the two files in at once, in one Dataset.
+>>> f = MFDataset("mftest_*nc")
+>>> t = f.variables["time"]
+>>> print(t.units)
+days since 2000-01-01
+>>> print(t[32])  # The value written in the file, inconsistent with the MF time units.
+1
+>>> T = MFTime(t)
+>>> print(T[32])
+32
+
    +

    __init__(self, time, units=None, calendar=None)

    +

    Create a time Variable with units consistent across a multifile +dataset.

    +

    time: Time variable from a MFDataset.

    +

    units: Time units, for example, 'days since 1979-01-01'. If None, +use the units from the master variable.

    +

    calendar: Calendar overload to use across all files, for example, +'standard' or 'gregorian'. If None, check that the calendar attribute +is present on each variable and values are unique across files raising a +ValueError otherwise.

    +

    Ancestors

    +
      +
    • netCDF4._netCDF4._Variable
      • +
    +
    +
    +class VLType +(...) +
    +
    +

    A VLType instance is used to describe a variable length (VLEN) data +type, and can be passed to the the Dataset.createVariable() method of +a Dataset or Group instance. See +VLType for more details.

    +

    The instance variables dtype and name should not be modified by +the user.

    +

    __init__(group, datatype, datatype_name)

    +

    VLType constructor.

    +

    group: Group instance to associate with the VLEN datatype.

    +

    datatype: An numpy dtype object describing the component type for the +variable length array.

    +

    datatype_name: a Python string containing a description of the +VLEN data type.

    +

    Note: VLType instances should be created using the +Dataset.createVLType() method of a Dataset or +Group instance, not using this class directly.

    +

    Instance variables

    +
    +
    var dtype
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var name
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    +
    +
    +class Variable +(...) +
    +
    +

    A netCDF Variable is used to read and write netCDF data. +They are +analogous to numpy array objects. See Variable for more details.

    -

    A list of attribute names corresponding to netCDF attributes defined for -the variable can be obtained with the Variable.ncattrs method. These +the variable can be obtained with the Variable.ncattrs() method. These attributes can be created by assigning to an attribute of the -Variable instance. A dictionary containing all the netCDF attribute +Variable instance. A dictionary containing all the netCDF attribute name/value pairs is provided by the __dict__ attribute of a -Variable instance.

    - +Variable instance.

    The following class variables are read-only:

    - -

    dimensions: A tuple containing the names of the +

    dimensions: A tuple containing the names of the dimensions associated with this variable.

    -

    dtype: A numpy dtype object describing the variable's data type.

    -

    ndim: The number of variable dimensions.

    - -

    shape: A tuple with the current shape (length of all dimensions).

    - +

    shape: A tuple with the current shape (length of all dimensions).

    scale: If True, scale_factor and add_offset are applied, and signed integer data is automatically converted to unsigned integer data if the _Unsigned attribute is set to "true" or "True". -Default is True, can be reset using Variable.set_auto_scale and -Variable.set_auto_maskandscale methods.

    - +Default is True, can be reset using Variable.set_auto_scale() and +Variable.set_auto_maskandscale() methods.

    mask: If True, data is automatically converted to/from masked arrays when missing values or fill values are present. Default is True, can be -reset using Variable.set_auto_mask and Variable.set_auto_maskandscale +reset using Variable.set_auto_mask() and Variable.set_auto_maskandscale() methods. Only relevant for Variables with primitive or enum types (ignored for compound and vlen Variables).

    - -

    chartostring: If True, data is automatically converted to/from character +

    chartostring(): If True, data is automatically converted to/from character arrays to string arrays when the _Encoding variable attribute is set. Default is True, can be reset using -Variable.set_auto_chartostring method.

    - +Variable.set_auto_chartostring() method.

    least_significant_digit: Describes the power of ten of the -smallest decimal place in the data the contains a reliable value. Data is -truncated to this decimal place when it is assigned to the Variable +smallest decimal place in the data the contains a reliable value. +Data is +truncated to this decimal place when it is assigned to the Variable instance. If None, the data is not truncated.

    -

    significant_digits: New in version 1.6.0. Describes the number of significant -digits in the data the contains a reliable value. Data is +digits in the data the contains a reliable value. +Data is truncated to retain this number of significant digits when it is assigned to the -Variable instance. If None, the data is not truncated. +Variable instance. If None, the data is not truncated. Only available with netcdf-c >= 4.9.0, and only works with NETCDF4 or NETCDF4_CLASSIC formatted files. The number of significant digits used in the quantization of variable data can be -obtained using the Variable.significant_digits method. Default None - +obtained using the Variable.significant_digits method. Default None - no quantization done.

    -

    quantize_mode: New in version 1.6.0. Controls the quantization algorithm (default 'BitGroom', 'BitRound' and -'GranularBitRound' also available). The 'GranularBitRound' -algorithm may result in better compression for typical geophysical datasets. +'GranularBitRound' also available). +The 'GranularBitRound' +algorithm may result in better compression for typical geophysical datasets. Ignored if significant_digits not specified. If 'BitRound' is used, then significant_digits is interpreted as binary (not decimal) digits.

    - -

    __orthogonal_indexing__: Always True. Indicates to client code +

    __orthogonal_indexing__: Always True. +Indicates to client code that the object supports 'orthogonal indexing', which means that slices -that are 1d arrays or lists slice along each dimension independently. This +that are 1d arrays or lists slice along each dimension independently. +This behavior is similar to Fortran or Matlab, but different than numpy.

    - -

    datatype: numpy data type (for primitive data types) or VLType/CompoundType - instance (for compound or vlen data types).

    - -

    name: String name.

    - -

    size: The number of stored elements.

    -
    - - -
    -
    - - Variable() - - -
    - - -

    __init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False, +

    datatype: numpy data type (for primitive data types) or VLType/CompoundType +instance (for compound or vlen data types).

    +

    name: String name.

    +

    size: The number of stored elements.

    +

    __init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False, complevel=4, shuffle=True, szip_coding='nn', szip_pixels_per_block=8, blosc_shuffle=1, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None,fill_value=None,chunk_cache=None)

    - -

    Variable constructor.

    - -

    group: Group or Dataset instance to associate with variable.

    - -

    name: Name of the variable.

    - -

    datatype: Variable data type. Can be specified by providing a +

    Variable constructor.

    +

    group: Group or Dataset instance to associate with variable.

    +

    name: Name of the variable.

    +

    datatype: Variable data type. Can be specified by providing a numpy dtype object, or a string that describes a numpy dtype object. Supported values, corresponding to str attribute of numpy dtype objects, include 'f4' (32-bit floating point), 'f8' (64-bit floating @@ -2911,59 +2516,51 @@

    In-memory (diskless) Datasets

    'i8' (64-bit signed integer), 'i4' (8-bit signed integer), 'i1' (8-bit signed integer), 'u1' (8-bit unsigned integer), 'u2' (16-bit unsigned integer), 'u4' (32-bit unsigned integer), 'u8' (64-bit -unsigned integer), or 'S1' (single-character string). From +unsigned integer), or 'S1' (single-character string). +From compatibility with Scientific.IO.NetCDF, the old Numeric single character typecodes can also be used ('f' instead of 'f4', 'd' instead of 'f8', 'h' or 's' instead of 'i2', 'b' or 'B' instead of 'i1', 'c' instead of 'S1', and 'i' or 'l' instead of -'i4'). datatype can also be a CompoundType instance -(for a structured, or compound array), a VLType instance +'i4'). datatype can also be a CompoundType instance +(for a structured, or compound array), a VLType instance (for a variable-length array), or the python str builtin (for a variable-length string array). Numpy string and unicode datatypes with length greater than one are aliases for str.

    - -

    dimensions: a tuple containing the variable's Dimension instances +

    dimensions: a tuple containing the variable's Dimension instances (defined previously with createDimension). Default is an empty tuple which means the variable is a scalar (and therefore has no dimensions).

    - -

    compression: compression algorithm to use. +

    compression: compression algorithm to use. Currently zlib,szip,zstd,bzip2,blosc_lz,blosc_lz4,blosc_lz4hc, blosc_zlib and blosc_zstd are supported. -Default is None (no compression). All of the compressors except +Default is None (no compression). +All of the compressors except zlib and szip use the HDF5 plugin architecture.

    - -

    zlib: if True, data assigned to the Variable +

    zlib: if True, data assigned to the Variable instance is compressed on disk. Default False. Deprecated - use compression='zlib' instead.

    -

    complevel: the level of compression to use (1 is the fastest, but poorest compression, 9 is the slowest but best compression). Default 4. Ignored if compression=None or szip. A value of 0 disables compression.

    -

    shuffle: if True, the HDF5 shuffle filter is applied to improve zlib compression. Default True. Ignored unless compression = 'zlib'.

    -

    blosc_shuffle: shuffle filter inside blosc compressor (only relevant if compression kwarg set to one of the blosc compressors). Can be 0 (no blosc shuffle), 1 (bytewise shuffle) or 2 (bitwise shuffle)). Default is 1. Ignored if blosc compressor not used.

    -

    szip_coding: szip coding method. Can be ec (entropy coding) or nn (nearest neighbor coding). Default is nn. Ignored if szip compressor not used.

    - -

    szip_pixels_per_block: Can be 4,8,16 or 32 (Default 8). +

    szip_pixels_per_block: Can be 4,8,16 or 32 (Default 8). Ignored if szip compressor not used.

    -

    fletcher32: if True (default False), the Fletcher32 checksum algorithm is used for error detection.

    -

    contiguous: if True (default False), the variable data is -stored contiguously on disk. Default False. Setting to True for +stored contiguously on disk. +Default False. Setting to True for a variable with an unlimited dimension will trigger an error. Fixed size variables (with no unlimited dimension) with no compression filters are contiguous by default.

    -

    chunksizes: Can be used to specify the HDF5 chunksizes for each dimension of the variable. A detailed discussion of HDF chunking and I/O performance is available @@ -2973,8 +2570,7 @@

    In-memory (diskless) Datasets

    Basically, you want the chunk size for each dimension to match as closely as possible the size of the data block that users will read from the file. chunksizes cannot be set if contiguous=True.

    - -

    endian: Can be used to control whether the +

    endian: Can be used to control whether the data is stored in little or big endian format on disk. Possible values are little, big or native (default). The library will automatically handle endian conversions when the data is read, @@ -2982,10 +2578,8 @@

    In-memory (diskless) Datasets

    opposite format as the one used to create the file, there may be some performance advantage to be gained by setting the endian-ness. For netCDF 3 files (that don't use HDF5), only endian='native' is allowed.

    -

    The compression, zlib, complevel, shuffle, fletcher32, contiguous and chunksizes keywords are silently ignored for netCDF 3 files that do not use HDF5.

    -

    least_significant_digit: If this or significant_digits are specified, variable data will be truncated (quantized). In conjunction with compression='zlib' this produces @@ -2994,404 +2588,262 @@

    In-memory (diskless) Datasets

    around(scaledata)/scale, where scale = 2*bits, and bits is determined so that a precision of 0.1 is retained (in this case bits=4). Default is None, or no quantization.

    -

    significant_digits: New in version 1.6.0. As described for least_significant_digit except the number of significant digits retained is prescribed independent of the floating point exponent. Default None - no quantization done.

    -

    quantize_mode: New in version 1.6.0. Controls the quantization algorithm (default 'BitGroom', 'BitRound' and -'GranularBitRound' also available). The 'GranularBitRound' +'GranularBitRound' also available). +The 'GranularBitRound' algorithm may result in better compression for typical geophysical datasets. Ignored if significant_digts not specified. If 'BitRound' is used, then significant_digits is interpreted as binary (not decimal) digits.

    - -

    fill_value: If specified, the default netCDF _FillValue (the +

    fill_value: +If specified, the default netCDF _FillValue (the value that the variable gets filled with before any data is written to it) -is replaced with this value. If fill_value is set to False, then +is replaced with this value. +If fill_value is set to False, then the variable is not pre-filled. The default netCDF fill values can be found in the dictionary netCDF4.default_fillvals.

    -

    chunk_cache: If specified, sets the chunk cache size for this variable. -Persists as long as Dataset is open. Use set_var_chunk_cache to +Persists as long as Dataset is open. Use set_var_chunk_cache to change it when Dataset is re-opened.

    - -

    Note: Variable instances should be created using the -Dataset.createVariable method of a Dataset or -Group instance, not using this class directly.

    -
    - - -
    -
    -
    - - def - group(unknown): - - -
    - - -

    group(self)

    - -

    return the group that this Variable is a member of.

    -
    - - -
    -
    -
    - - def - ncattrs(unknown): - - -
    - - -

    ncattrs(self)

    - -

    return netCDF attribute names for this Variable in a list.

    -
    - - -
    -
    -
    - - def - setncattr(unknown): - - -
    - - -

    setncattr(self,name,value)

    - -

    set a netCDF variable attribute using name,value pair. Use if you need to set a +

    Note: Variable instances should be created using the +Dataset.createVariable() method of a Dataset or +Group instance, not using this class directly.

    +

    Instance variables

    +
    +
    var always_mask
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var chartostring
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var datatype
    +
    +

    numpy data type (for primitive data types) or +VLType/CompoundType/EnumType instance +(for compound, vlen +or enum data types)

    +
    +
    var dimensions
    +
    +

    get variables's dimension names

    +
    +
    var dtype
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var mask
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var name
    +
    +

    string name of Variable instance

    +
    +
    var ndim
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var scale
    +
    +

    Return an attribute of instance, which is of type owner.

    +
    +
    var shape
    +
    +

    find current sizes of all variable dimensions

    +
    +
    var size
    +
    +

    Return the number of stored elements.

    +
    +
    +

    Methods

    +
    +
    +def assignValue(...) +
    +
    +

    assignValue(self, val)

    +

    assign a value to a scalar variable. +Provided for compatibility with +Scientific.IO.NetCDF, can also be done by assigning to an Ellipsis slice ([…]).

    +
    +
    +def chunking(...) +
    +
    +

    chunking(self)

    +

    return variable chunking information. +If the dataset is +defined to be contiguous (and hence there is no chunking) the word 'contiguous' +is returned. +Otherwise, a sequence with the chunksize for +each dimension is returned.

    +
    +
    +def delncattr(...) +
    +
    +

    delncattr(self,name,value)

    +

    delete a netCDF variable attribute. +Use if you need to delete a netCDF attribute with the same name as one of the reserved python -attributes.

    -
    - - -
    -
    -
    - - def - setncattr_string(unknown): - - -
    - - -

    setncattr_string(self,name,value)

    - -

    set a netCDF variable string attribute using name,value pair. -Use if you need to ensure that a netCDF attribute is created with type -NC_STRING if the file format is NETCDF4. -Use if you need to set an attribute to an array of variable-length strings.

    -
    - - -
    -
    -
    - - def - setncatts(unknown): - - -
    - - -

    setncatts(self,attdict)

    - -

    set a bunch of netCDF variable attributes at once using a python dictionary. -This may be faster when setting a lot of attributes for a NETCDF3 -formatted file, since nc_redef/nc_enddef is not called in between setting -each attribute

    -
    - - -
    -
    -
    - - def - getncattr(unknown): - - -
    - - -

    getncattr(self,name)

    - -

    retrieve a netCDF variable attribute. Use if you need to set a +attributes.

    +
    +
    +def endian(...) +
    +
    +

    endian(self)

    +

    return endian-ness (little,big,native) of variable (as stored in HDF5 file).

    +
    +
    +def filters(...) +
    +
    +

    filters(self)

    +

    return dictionary containing HDF5 filter parameters.

    +
    +
    +def getValue(...) +
    +
    +

    getValue(self)

    +

    get the value of a scalar variable. +Provided for compatibility with +Scientific.IO.NetCDF, can also be done by slicing with an Ellipsis ([…]).

    +
    +
    +def get_dims(...) +
    +
    +

    get_dims(self)

    +

    return a tuple of Dimension instances associated with this +Variable.

    +
    +
    +def get_var_chunk_cache(...) +
    +
    +

    get_var_chunk_cache(self)

    +

    return variable chunk cache information in a tuple (size,nelems,preemption). +See netcdf C library documentation for nc_get_var_chunk_cache for +details.

    +
    +
    +def getncattr(...) +
    +
    +

    getncattr(self,name)

    +

    retrieve a netCDF variable attribute. +Use if you need to set a netCDF attribute with the same name as one of the reserved python attributes.

    -

    option kwarg encoding can be used to specify the -character encoding of a string attribute (default is utf-8).

    -
    - - - -
    -
    - - def - delncattr(unknown): - - -
    - - -

    delncattr(self,name,value)

    - -

    delete a netCDF variable attribute. Use if you need to delete a -netCDF attribute with the same name as one of the reserved python -attributes.

    -
    - - -
    -
    -
    - - def - filters(unknown): - - -
    - - -

    filters(self)

    - -

    return dictionary containing HDF5 filter parameters.

    -
    - - -
    -
    -
    - - def - quantization(unknown): - - -
    - - -

    quantization(self)

    - +character encoding of a string attribute (default is utf-8).

    +
    +
    +def group(...) +
    +
    +

    group(self)

    +

    return the group that this Variable is a member of.

    +
    +
    +def ncattrs(...) +
    +
    +

    ncattrs(self)

    +

    return netCDF attribute names for this Variable in a list.

    +
    +
    +def quantization(...) +
    +
    +

    quantization(self)

    return number of significant digits and the algorithm used in quantization. -Returns None if quantization not active.

    -
    - - - -
    -
    - - def - endian(unknown): - - -
    - - -

    endian(self)

    - -

    return endian-ness (little,big,native) of variable (as stored in HDF5 file).

    -
    - - -
    -
    -
    - - def - chunking(unknown): - - -
    - - -

    chunking(self)

    - -

    return variable chunking information. If the dataset is -defined to be contiguous (and hence there is no chunking) the word 'contiguous' -is returned. Otherwise, a sequence with the chunksize for -each dimension is returned.

    -
    - - -
    -
    -
    - - def - get_var_chunk_cache(unknown): - - -
    - - -

    get_var_chunk_cache(self)

    - -

    return variable chunk cache information in a tuple (size,nelems,preemption). -See netcdf C library documentation for nc_get_var_chunk_cache for -details.

    -
    - - -
    -
    -
    - - def - set_var_chunk_cache(unknown): - - -
    - - -

    set_var_chunk_cache(self,size=None,nelems=None,preemption=None)

    - -

    change variable chunk cache settings. -See netcdf C library documentation for nc_set_var_chunk_cache for -details.

    -
    - - -
    -
    -
    - - def - renameAttribute(unknown): - - -
    - - -

    renameAttribute(self, oldname, newname)

    - -

    rename a Variable attribute named oldname to newname.

    -
    - - -
    -
    -
    - - def - assignValue(unknown): - - -
    - - -

    assignValue(self, val)

    - -

    assign a value to a scalar variable. Provided for compatibility with -Scientific.IO.NetCDF, can also be done by assigning to an Ellipsis slice ([...]).

    -
    - - -
    -
    -
    - - def - getValue(unknown): - - -
    - - -

    getValue(self)

    - -

    get the value of a scalar variable. Provided for compatibility with -Scientific.IO.NetCDF, can also be done by slicing with an Ellipsis ([...]).

    -
    - - -
    -
    -
    - - def - set_auto_chartostring(unknown): - - -
    - - -

    set_auto_chartostring(self,chartostring)

    - +Returns None if quantization not active.

    +
    +
    +def renameAttribute(...) +
    +
    +

    renameAttribute(self, oldname, newname)

    +

    rename a Variable attribute named oldname to newname.

    +
    +
    +def set_always_mask(...) +
    +
    +

    set_always_mask(self,always_mask)

    +

    turn on or off conversion of data without missing values to regular +numpy arrays.

    +

    always_mask is a Boolean determining if automatic conversion of +masked arrays with no missing values to regular numpy arrays shall be +applied. Default is True. Set to False to restore the default behaviour +in versions prior to 1.4.1 (numpy array returned unless missing values are present, +otherwise masked array returned).

    +
    +
    +def set_auto_chartostring(...) +
    +
    +

    set_auto_chartostring(self,chartostring())

    turn on or off automatic conversion of character variable data to and from numpy fixed length string arrays when the _Encoding variable attribute is set.

    - -

    If chartostring is set to True, when data is read from a character variable +

    If chartostring() is set to True, when data is read from a character variable (dtype = S1) that has an _Encoding attribute, it is converted to a numpy fixed length unicode string array (dtype = UN, where N is the length -of the the rightmost dimension of the variable). The value of _Encoding +of the the rightmost dimension of the variable). +The value of _Encoding is the unicode encoding that is used to decode the bytes into strings.

    -

    When numpy string data is written to a variable it is converted back to indiviual bytes, with the number of bytes in each string equalling the rightmost dimension of the variable.

    - -

    The default value of chartostring is True -(automatic conversions are performed).

    -
    - - - -
    -
    - - def - use_nc_get_vars(unknown): - - -
    - - -

    use_nc_get_vars(self,_use_get_vars)

    - -

    enable the use of netcdf library routine nc_get_vars -to retrieve strided variable slices. By default, -nc_get_vars may not used by default (depending on the -version of the netcdf-c library being used) since it may be -slower than multiple calls to the unstrided read routine nc_get_vara.

    -
    - - -
    -
    -
    - - def - set_auto_maskandscale(unknown): - - -
    - - -

    set_auto_maskandscale(self,maskandscale)

    - +

    The default value of chartostring() is True +(automatic conversions are performed).

    +
    +
    +def set_auto_mask(...) +
    +
    +

    set_auto_mask(self,mask)

    turn on or off automatic conversion of variable data to and -from masked arrays, automatic packing/unpacking of variable -data using scale_factor and add_offset attributes and -automatic conversion of signed integer data to unsigned integer -data if the _Unsigned attribute exists and is set to "true" (or "True").

    - +from masked arrays .

    +

    If mask is set to True, when data is read from a variable +it is converted to a masked array if any of the values are exactly +equal to the either the netCDF _FillValue or the value specified by the +missing_value variable attribute. The fill_value of the masked array +is set to the missing_value attribute (if it exists), otherwise +the netCDF _FillValue attribute (which has a default value +for each data type). If the variable has no missing_value attribute, the +_FillValue is used instead. If the variable has valid_min/valid_max and +missing_value attributes, data outside the specified range will be masked. +When data is written to a variable, the masked +array is converted back to a regular numpy array by replacing all the +masked values by the missing_value attribute of the variable (if it +exists). +If the variable has no missing_value attribute, the _FillValue +is used instead.

    +

    The default value of mask is True +(automatic conversions are performed).

    +
    +
    +def set_auto_maskandscale(...) +
    +
    +

    set_auto_maskandscale(self,maskandscale)

    +

    turn on or off automatic conversion of variable data to and +from masked arrays, automatic packing/unpacking of variable +data using scale_factor and add_offset attributes and +automatic conversion of signed integer data to unsigned integer +data if the _Unsigned attribute exists and is set to "true" (or "True").

    If maskandscale is set to True, when data is read from a variable it is converted to a masked array if any of the values are exactly equal to the either the netCDF _FillValue or the value specified by the @@ -3404,1276 +2856,340 @@

    In-memory (diskless) Datasets

    When data is written to a variable, the masked array is converted back to a regular numpy array by replacing all the masked values by the missing_value attribute of the variable (if it -exists). If the variable has no missing_value attribute, the _FillValue -is used instead.

    - +exists). +If the variable has no missing_value attribute, the _FillValue +is used instead.

    If maskandscale is set to True, and the variable has a scale_factor or an add_offset attribute, then data read from that variable is unpacked using::

    - 
    data = self.scale_factor*data + self.add_offset
    -

    When data is written to a variable it is packed using::

    - 
    data = (data - self.add_offset)/self.scale_factor
    -

    If either scale_factor is present, but add_offset is missing, add_offset -is assumed zero. If add_offset is present, but scale_factor is missing, +is assumed zero. +If add_offset is present, but scale_factor is missing, scale_factor is assumed to be one. For more information on how scale_factor and add_offset can be used to provide simple compression, see the PSL metadata conventions.

    -

    In addition, if maskandscale is set to True, and if the variable has an attribute _Unsigned set to "true", and the variable has a signed integer data type, a view to the data is returned with the corresponding unsigned integer data type. This convention is used by the netcdf-java library to save unsigned integer data in NETCDF3 or NETCDF4_CLASSIC files (since the NETCDF3 data model does not have unsigned integer data types).

    -

    The default value of maskandscale is True -(automatic conversions are performed).

    -
    - - - -
    -
    - - def - set_auto_scale(unknown): - - -
    - - -

    set_auto_scale(self,scale)

    - +(automatic conversions are performed).

    +
    +
    +def set_auto_scale(...) +
    +
    +

    set_auto_scale(self,scale)

    turn on or off automatic packing/unpacking of variable data using scale_factor and add_offset attributes. Also turns on and off automatic conversion of signed integer data to unsigned integer data if the variable has an _Unsigned attribute set to "true" or "True".

    -

    If scale is set to True, and the variable has a scale_factor or an add_offset attribute, then data read from that variable is unpacked using::

    - 
    data = self.scale_factor*data + self.add_offset
    -

    When data is written to a variable it is packed using::

    - 
    data = (data - self.add_offset)/self.scale_factor
    -

    If either scale_factor is present, but add_offset is missing, add_offset -is assumed zero. If add_offset is present, but scale_factor is missing, +is assumed zero. +If add_offset is present, but scale_factor is missing, scale_factor is assumed to be one. For more information on how scale_factor and add_offset can be used to provide simple compression, see the PSL metadata conventions.

    -

    In addition, if scale is set to True, and if the variable has an attribute _Unsigned set to "true", and the variable has a signed integer data type, a view to the data is returned with the corresponding unsigned integer datatype. This convention is used by the netcdf-java library to save unsigned integer data in NETCDF3 or NETCDF4_CLASSIC files (since the NETCDF3 data model does not have unsigned integer data types).

    -

    The default value of scale is True -(automatic conversions are performed).

    -
    - - - -
    -
    - - def - set_auto_mask(unknown): - - -
    - - -

    set_auto_mask(self,mask)

    - -

    turn on or off automatic conversion of variable data to and -from masked arrays .

    - -

    If mask is set to True, when data is read from a variable -it is converted to a masked array if any of the values are exactly -equal to the either the netCDF _FillValue or the value specified by the -missing_value variable attribute. The fill_value of the masked array -is set to the missing_value attribute (if it exists), otherwise -the netCDF _FillValue attribute (which has a default value -for each data type). If the variable has no missing_value attribute, the -_FillValue is used instead. If the variable has valid_min/valid_max and -missing_value attributes, data outside the specified range will be masked. -When data is written to a variable, the masked -array is converted back to a regular numpy array by replacing all the -masked values by the missing_value attribute of the variable (if it -exists). If the variable has no missing_value attribute, the _FillValue -is used instead.

    - -

    The default value of mask is True -(automatic conversions are performed).

    -
    - - -
    -
    -
    - - def - set_always_mask(unknown): - - -
    - - -

    set_always_mask(self,always_mask)

    - -

    turn on or off conversion of data without missing values to regular -numpy arrays.

    - -

    always_mask is a Boolean determining if automatic conversion of -masked arrays with no missing values to regular numpy arrays shall be -applied. Default is True. Set to False to restore the default behaviour -in versions prior to 1.4.1 (numpy array returned unless missing values are present, -otherwise masked array returned).

    -
    - - -
    -
    -
    - - def - set_ncstring_attrs(unknown): - - -
    - - -

    set_always_mask(self,ncstring_attrs)

    - +(automatic conversions are performed).

    +
    +
    +def set_collective(...) +
    +
    +

    set_collective(self,True_or_False)

    +

    turn on or off collective parallel IO access. Ignored if file is not +open for parallel access.

    +
    +
    +def set_ncstring_attrs(...) +
    +
    +

    set_always_mask(self,ncstring_attrs)

    turn on or off creating NC_STRING string attributes.

    -

    If ncstring_attrs is set to True then text attributes will be variable-length NC_STRINGs.

    -

    The default value of ncstring_attrs is False (writing ascii text attributes as -NC_CHAR).

    -
    - - - -
    -
    - - def - set_collective(unknown): - - -
    - - -

    set_collective(self,True_or_False)

    - -

    turn on or off collective parallel IO access. Ignored if file is not -open for parallel access.

    -
    - - -
    -
    -
    - - def - get_dims(unknown): - - -
    - - -

    get_dims(self)

    - -

    return a tuple of Dimension instances associated with this -Variable.

    -
    - - -
    -
    -
    - name - - -
    - - -

    string name of Variable instance

    -
    - - -
    -
    -
    - datatype - - -
    - - -

    numpy data type (for primitive data types) or -VLType/CompoundType/EnumType instance -(for compound, vlen or enum data types)

    -
    - - -
    -
    -
    - shape - - -
    - - -

    find current sizes of all variable dimensions

    -
    - - -
    -
    -
    - size - - -
    - - -

    Return the number of stored elements.

    -
    - - -
    -
    -
    - dimensions - - -
    - - -

    get variables's dimension names

    -
    - - -
    -
    -
    -
    - - class - Dimension: - - -
    - - -

    A netCDF Dimension is used to describe the coordinates of a Variable. -See Dimension.__init__ for more details.

    - -

    The current maximum size of a Dimension instance can be obtained by -calling the python len function on the Dimension instance. The -Dimension.isunlimited method of a Dimension instance can be used to -determine if the dimension is unlimited.

    - -

    Read-only class variables:

    - -

    name: String name, used when creating a Variable with -Dataset.createVariable.

    - -

    size: Current Dimension size (same as len(d), where d is a -Dimension instance).

    -
    - - -
    -
    - - Dimension() - - -
    - - -

    __init__(self, group, name, size=None)

    - -

    Dimension constructor.

    - -

    group: Group instance to associate with dimension.

    - -

    name: Name of the dimension.

    - -

    size: Size of the dimension. None or 0 means unlimited. (Default None).

    - -

    Note: Dimension instances should be created using the -Dataset.createDimension method of a Group or -Dataset instance, not using Dimension.__init__ directly.

    -
    - - -
    -
    -
    - - def - group(unknown): - - -
    - - -

    group(self)

    - -

    return the group that this Dimension is a member of.

    -
    - - -
    -
    -
    - - def - isunlimited(unknown): - - -
    - - -

    isunlimited(self)

    - -

    returns True if the Dimension instance is unlimited, False otherwise.

    -
    - - -
    -
    -
    - name - - -
    - - -

    string name of Dimension instance

    -
    - - -
    -
    -
    - size - - -
    - - -

    current size of Dimension (calls len on Dimension instance)

    -
    - - -
    -
    -
    -
    - - class - Group(netCDF4.Dataset): - - -
    - - -

    Groups define a hierarchical namespace within a netCDF file. They are -analogous to directories in a unix filesystem. Each Group behaves like -a Dataset within a Dataset, and can contain it's own variables, -dimensions and attributes (and other Groups). See Group.__init__ -for more details.

    - -

    Group inherits from Dataset, so all the -Dataset class methods and variables are available -to a Group instance (except the close method).

    - -

    Additional read-only class variables:

    - -

    name: String describing the group name.

    -
    - - -
    -
    - - Group() - - -
    - - -

    __init__(self, parent, name) -Group constructor.

    - -

    parent: Group instance for the parent group. If being created -in the root group, use a Dataset instance.

    - -

    name: - Name of the group.

    - -

    Note: Group instances should be created using the -Dataset.createGroup method of a Dataset instance, or -another Group instance, not using this class directly.

    -
    - - -
    -
    -
    - - def - close(unknown): - - -
    - - -

    close(self)

    - -

    overrides Dataset close method which does not apply to Group -instances, raises OSError.

    -
    - - -
    -
    -
    Inherited Members
    -
    - -
    -
    -
    -
    -
    - - class - MFDataset(netCDF4.Dataset): - - -
    - - -

    Class for reading multi-file netCDF Datasets, making variables -spanning multiple files appear as if they were in one file. -Datasets must be in NETCDF4_CLASSIC, NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET -or NETCDF3_64BIT_DATA format (NETCDF4 Datasets won't work).

    - -

    Adapted from pycdf by Andre Gosselin.

    - -

    Example usage (See MFDataset.__init__ for more details):

    - -
    -
    >>> import numpy as np
->>> # create a series of netCDF files with a variable sharing
->>> # the same unlimited dimension.
->>> for nf in range(10):
-...     with Dataset("mftest%s.nc" % nf, "w", format='NETCDF4_CLASSIC') as f:
-...         f.createDimension("x",None)
-...         x = f.createVariable("x","i",("x",))
-...         x[0:10] = np.arange(nf*10,10*(nf+1))
->>> # now read all those files in at once, in one Dataset.
->>> f = MFDataset("mftest*nc")
->>> print(f.variables["x"][:])
-[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
- 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
- 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71
- 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
- 96 97 98 99]
-
    -
    -
    - - -
    -
    - - MFDataset(files, check=False, aggdim=None, exclude=[], master_file=None) - - -
    - - -

    __init__(self, files, check=False, aggdim=None, exclude=[], -master_file=None)

    - -

    Open a Dataset spanning multiple files, making it look as if it was a -single file. Variables in the list of files that share the same -dimension (specified with the keyword aggdim) are aggregated. If -aggdim is not specified, the unlimited is aggregated. Currently, -aggdim must be the leftmost (slowest varying) dimension of each -of the variables to be aggregated.

    - -

    files: either a sequence of netCDF files or a string with a -wildcard (converted to a sorted list of files using glob) If -the master_file kwarg is not specified, the first file -in the list will become the "master" file, defining all the -variables with an aggregation dimension which may span -subsequent files. Attribute access returns attributes only from "master" -file. The files are always opened in read-only mode.

    - -

    check: True if you want to do consistency checking to ensure the -correct variables structure for all of the netcdf files. Checking makes -the initialization of the MFDataset instance much slower. Default is -False.

    - -

    aggdim: The name of the dimension to aggregate over (must -be the leftmost dimension of each of the variables to be aggregated). -If None (default), aggregate over the unlimited dimension.

    - -

    exclude: A list of variable names to exclude from aggregation. -Default is an empty list.

    - -

    master_file: file to use as "master file", defining all the -variables with an aggregation dimension and all global attributes.

    -
    - - -
    -
    -
    - - def - ncattrs(self): - - -
    - - -

    ncattrs(self)

    - -

    return the netcdf attribute names from the master file.

    -
    - - -
    -
    -
    - - def - close(self): - - -
    - - -

    close(self)

    - -

    close all the open files.

    +NC_CHAR).

    + +
    +def set_var_chunk_cache(...) +
    +
    +

    set_var_chunk_cache(self,size=None,nelems=None,preemption=None)

    +

    change variable chunk cache settings. +See netcdf C library documentation for nc_set_var_chunk_cache for +details.

    +
    +
    +def setncattr(...) +
    +
    +

    setncattr(self,name,value)

    +

    set a netCDF variable attribute using name,value pair. +Use if you need to set a +netCDF attribute with the same name as one of the reserved python +attributes.

    +
    +
    +def setncattr_string(...) +
    +
    +

    setncattr_string(self,name,value)

    +

    set a netCDF variable string attribute using name,value pair. +Use if you need to ensure that a netCDF attribute is created with type +NC_STRING if the file format is NETCDF4. +Use if you need to set an attribute to an array of variable-length strings.

    +
    +
    +def setncatts(...) +
    +
    +

    setncatts(self,attdict)

    +

    set a bunch of netCDF variable attributes at once using a python dictionary. +This may be faster when setting a lot of attributes for a NETCDF3 +formatted file, since nc_redef/nc_enddef is not called in between setting +each attribute

    +
    +
    +def use_nc_get_vars(...) +
    +
    +

    use_nc_get_vars(self,_use_get_vars)

    +

    enable the use of netcdf library routine nc_get_vars +to retrieve strided variable slices. +By default, +nc_get_vars may not used by default (depending on the +version of the netcdf-c library being used) since it may be +slower than multiple calls to the unstrided read routine nc_get_vara.

    +
    + + + +
    + + + + \ No newline at end of file From 5d66b06712e7e4230d64f0f77b221f497eaff44c Mon Sep 17 00:00:00 2001 From: Mike Taves Date: Sun, 9 Jul 2023 20:49:48 +1200 Subject: [PATCH 1007/1504] Re-arrange pyproject.toml readme to be compatible with older parsers --- pyproject.toml | 19 +++++++++++-------- 1 file changed, 11 insertions(+), 8 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index f755e1679..01562cefb 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -9,14 +9,6 @@ build-backend = "setuptools.build_meta" [project] name = "netCDF4" description = "Provides an object-oriented python interface to the netCDF version 4 library" -readme = {text = """\ -netCDF version 4 has many features not found in earlier versions of the library, -such as hierarchical groups, zlib compression, multiple unlimited dimensions, -and new data types. It is implemented on top of HDF5. This module implements -most of the new features, and can read and write netCDF files compatible with -older versions of the library. The API is modelled after Scientific.IO.NetCDF, -and should be familiar to users of that module. -""", content-type = "text/x-rst"} authors = [ {name = "Jeff Whitaker", email = "jeffrey.s.whitaker@noaa.gov"}, ] @@ -47,6 +39,17 @@ dependencies = [ ] dynamic = ["version"] +[project.readme] +text = """\ +netCDF version 4 has many features not found in earlier versions of the library, +such as hierarchical groups, zlib compression, multiple unlimited dimensions, +and new data types. It is implemented on top of HDF5. This module implements +most of the new features, and can read and write netCDF files compatible with +older versions of the library. The API is modelled after Scientific.IO.NetCDF, +and should be familiar to users of that module. +""" +content-type = "text/x-rst" + [project.scripts] nc3tonc4 = "netCDF4.utils:nc3tonc4" nc4tonc3 = "netCDF4.utils:nc4tonc3" From a48338d4016f70fe1951afc5e90a4d6a73626125 Mon Sep 17 00:00:00 2001 From: jswhit Date: Wed, 23 Aug 2023 14:04:14 -0400 Subject: [PATCH 1008/1504] fix for issue #1271 --- src/netCDF4/_netCDF4.pyx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 8ec816505..1349ff3c4 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -5233,6 +5233,8 @@ rename a `Variable` attribute named `oldname` to `newname`.""" elif hasattr(self, 'add_offset'): data = data - self.add_offset if self.dtype.kind in 'iu': data = numpy.around(data) + if self.dtype != data.dtype: + data = data.astype(self.dtype) # cast data to var type, if necessary. if ma.isMA(data): # if underlying data in masked regions of masked array # corresponds to missing values, don't fill masked array - @@ -5263,8 +5265,6 @@ rename a `Variable` attribute named `oldname` to `newname`.""" data = numpy.array([fillval],self.dtype) else: data = data.filled(fill_value=fillval) - if self.dtype != data.dtype: - data = data.astype(self.dtype) # cast data to var type, if necessary. return data def _assign_vlen(self, elem, data): From 3d0cd655a439f55e4e52ebef5769754eca6c5d78 Mon Sep 17 00:00:00 2001 From: jswhit Date: Wed, 23 Aug 2023 14:21:40 -0400 Subject: [PATCH 1009/1504] add test --- test/tst_masked.py | 20 ++++++++++++++++++++ 1 file changed, 20 insertions(+) diff --git a/test/tst_masked.py b/test/tst_masked.py index 4ae43e187..d2d411fdc 100644 --- a/test/tst_masked.py +++ b/test/tst_masked.py @@ -15,6 +15,7 @@ # create an n1dim by n2dim random ranarr. FILE_NAME = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name FILE_NAME2 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name +FILE_NAME3 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name ndim = 10 ranarr = 100.*uniform(size=(ndim)) ranarr2 = 100.*uniform(size=(ndim)) @@ -41,6 +42,7 @@ class PrimitiveTypesTestCase(unittest.TestCase): def setUp(self): self.file = FILE_NAME self.file2 = FILE_NAME2 + self.file3 = FILE_NAME3 file = netCDF4.Dataset(self.file,'w') file.createDimension('n', ndim) foo = file.createVariable('maskeddata', 'f8', ('n',)) @@ -93,6 +95,19 @@ def setUp(self): data = dataset['v'][:] dataset.close() + # issue #1271 (mask is ignored when assigning bool array to uint8 var) + ds = netCDF4.Dataset(self.file3, "w") + dim = ds.createDimension('time', 48) + var = ds.createVariable('blaat', np.uint8, ('time',), + zlib=True, complevel=4, shuffle=True, fletcher32=True, + fill_value=240) + mask = np.full((48,), False) + for x in range(30): + mask[x] = True + mama = ma.array(np.full((48,), True), mask=mask) + var[:] = mama + ds.close() + def tearDown(self): # Remove the temporary files os.remove(self.file) @@ -148,6 +163,11 @@ def runTest(self): assert var1[:].mask.all() assert var2[:].mask.any() == False dataset.close() + # issue #1271 + ds = netCDF4.Dataset(self.file3,"r") + var = ds['blaat'] + assert np.count_nonzero(var[:].mask) == 30 + ds.close() if __name__ == '__main__': unittest.main() From cd0f5dadd55ead744eec5ae76340c11e49eecfbf Mon Sep 17 00:00:00 2001 From: jswhit Date: Wed, 23 Aug 2023 14:25:52 -0400 Subject: [PATCH 1010/1504] add Changelog entry, bump version number --- Changelog | 4 ++++ src/netCDF4/_netCDF4.pyx | 4 ++-- 2 files changed, 6 insertions(+), 2 deletions(-) diff --git a/Changelog b/Changelog index 1efad0da0..ac1271c90 100644 --- a/Changelog +++ b/Changelog @@ -1,3 +1,7 @@ + version 1.6.5 (not yet released) +=============================== + * fix for issue #1271 (mask ignored if bool MA assinged to uint8 var) + version 1.6.4 (tag v1.6.4rel) =============================== * set path to SSL certificates internally, so https DAP URLs work with wheels diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 1349ff3c4..eeed0a9e9 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1,5 +1,5 @@ """ -Version 1.6.4 +Version 1.6.5 ------------- # Introduction @@ -1227,7 +1227,7 @@ from .utils import (_StartCountStride, _quantize, _find_dim, _walk_grps, import sys import functools -__version__ = "1.6.4" +__version__ = "1.6.5" # Initialize numpy import posixpath From 7c4e800e5923a37d0a983ad86850c4046c80e0cf Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Wed, 2 Aug 2023 11:13:30 +0100 Subject: [PATCH 1011/1504] Flip guard-clause conditional in `_ensure_nc_success` --- src/netCDF4/_netCDF4.pyx | 18 ++++++++++-------- 1 file changed, 10 insertions(+), 8 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index eeed0a9e9..abeac5011 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2018,14 +2018,16 @@ cdef _get_vars(group): cdef _ensure_nc_success(ierr, err_cls=RuntimeError, filename=None): # print netcdf error message, raise error. - if ierr != NC_NOERR: - err_str = (nc_strerror(ierr)).decode('ascii') - if issubclass(err_cls, OSError): - if isinstance(filename, bytes): - filename = filename.decode() - raise err_cls(ierr, err_str, filename) - else: - raise err_cls(err_str) + if ierr == NC_NOERR: + return + + err_str = (nc_strerror(ierr)).decode('ascii') + if issubclass(err_cls, OSError): + if isinstance(filename, bytes): + filename = filename.decode() + raise err_cls(ierr, err_str, filename) + + raise err_cls(err_str) # these are class attributes that # only exist at the python level (not in the netCDF file). From 2a97db9c78a94360d57b6a7d18e91493dad1f312 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Wed, 2 Aug 2023 11:49:08 +0100 Subject: [PATCH 1012/1504] Include variable and group names in error messages in `Variable` --- src/netCDF4/_netCDF4.pyx | 59 ++++++++++++++++++++++++---------------- 1 file changed, 36 insertions(+), 23 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index abeac5011..3edbc6f34 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2016,7 +2016,7 @@ cdef _get_vars(group): free(varids) # free pointer holding variable ids. return variables -cdef _ensure_nc_success(ierr, err_cls=RuntimeError, filename=None): +def _ensure_nc_success(ierr, err_cls=RuntimeError, filename=None, extra_msg=None): # print netcdf error message, raise error. if ierr == NC_NOERR: return @@ -2027,6 +2027,10 @@ cdef _ensure_nc_success(ierr, err_cls=RuntimeError, filename=None): filename = filename.decode() raise err_cls(ierr, err_str, filename) + if extra_msg: + if isinstance(extra_msg, bytes): + extra_msg = extra_msg.decode() + err_str = f"{err_str}: {extra_msg}" raise err_cls(err_str) # these are class attributes that @@ -4018,6 +4022,10 @@ behavior is similar to Fortran or Matlab, but different than numpy. cdef size_t sizep, nelemsp cdef size_t *chunksizesp cdef float preemptionp + + # Extra information for more helpful error messages + error_info = f"(variable '{name}', group '{grp.name}')" + # flag to indicate that orthogonal indexing is supported self.__orthogonal_indexing__ = True # For backwards compatibility, deprecated zlib kwarg takes @@ -4061,7 +4069,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. compression = None # if compression evaluates to False, set to None. pass else: - raise ValueError("Unsupported value for compression kwarg") + raise ValueError(f"Unsupported value for compression kwarg {error_info}") self._grpid = grp._grpid # make a weakref to group to avoid circular ref (issue 218) # keep strong reference the default behaviour (issue 251) @@ -4119,14 +4127,15 @@ behavior is similar to Fortran or Matlab, but different than numpy. 'Variable length strings are only supported for the ' 'NETCDF4 format. For other formats, consider using ' 'netCDF4.stringtochar to convert string arrays into ' - 'character arrays with an additional dimension.') + 'character arrays with an additional dimension.' + f' {error_info}') datatype = VLType(self._grp, str, None) self._vltype = datatype xtype = datatype._nc_type # make sure this a valid user defined datatype defined in this Group with nogil: ierr = nc_inq_type(self._grpid, xtype, namstring, NULL) - _ensure_nc_success(ierr) + _ensure_nc_success(ierr, extra_msg=error_info) # dtype variable attribute is a numpy datatype object. self.dtype = datatype.dtype elif datatype.str[1:] in _supportedtypes: @@ -4137,7 +4146,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. # dtype variable attribute is a numpy datatype object. self.dtype = datatype else: - raise TypeError('illegal primitive data type, must be one of %s, got %s' % (_supportedtypes,datatype)) + raise TypeError(f'Illegal primitive data type, must be one of {_supportedtypes}, got {datatype} {error_info}') if 'id' in kwargs: self._varid = kwargs['id'] else: @@ -4163,6 +4172,12 @@ behavior is similar to Fortran or Matlab, but different than numpy. with nogil: ierr = nc_def_var(self._grpid, varname, xtype, ndims, NULL, &self._varid) + + if ierr != NC_NOERR: + if grp.data_model != 'NETCDF4': + grp._enddef() + _ensure_nc_success(ierr, extra_msg=error_info) + # set chunk cache size if desired # default is 1mb per var, can cause problems when many (1000's) # of vars are created. This change only lasts as long as file is @@ -4171,16 +4186,14 @@ behavior is similar to Fortran or Matlab, but different than numpy. with nogil: ierr = nc_get_var_chunk_cache(self._grpid, self._varid, &sizep, &nelemsp, &preemptionp) - _ensure_nc_success(ierr) + _ensure_nc_success(ierr, extra_msg=error_info) # reset chunk cache size, leave other parameters unchanged. sizep = chunk_cache with nogil: ierr = nc_set_var_chunk_cache(self._grpid, self._varid, sizep, nelemsp, preemptionp) - _ensure_nc_success(ierr) - if ierr != NC_NOERR: - if grp.data_model != 'NETCDF4': grp._enddef() - _ensure_nc_success(ierr) + _ensure_nc_success(ierr, extra_msg=error_info) + # set compression, shuffle, chunking, fletcher32 and endian # variable settings. # don't bother for NETCDF3* formats. @@ -4200,7 +4213,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. ierr = nc_def_var_deflate(self._grpid, self._varid, 0, 1, icomplevel) if ierr != NC_NOERR: if grp.data_model != 'NETCDF4': grp._enddef() - _ensure_nc_success(ierr) + _ensure_nc_success(ierr, extra_msg=error_info) if szip: IF HAS_SZIP_SUPPORT: try: @@ -4213,7 +4226,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. ierr = nc_def_var_szip(self._grpid, self._varid, iszip_coding, iszip_pixels_per_block) if ierr != NC_NOERR: if grp.data_model != 'NETCDF4': grp._enddef() - _ensure_nc_success(ierr) + _ensure_nc_success(ierr, extra_msg=error_info) ELSE: msg = """ compression='szip' only works if linked version of hdf5 has szip functionality enabled""" @@ -4225,7 +4238,7 @@ compression='szip' only works if linked version of hdf5 has szip functionality e ierr = nc_def_var_zstandard(self._grpid, self._varid, icomplevel) if ierr != NC_NOERR: if grp.data_model != 'NETCDF4': grp._enddef() - _ensure_nc_success(ierr) + _ensure_nc_success(ierr, extra_msg=error_info) ELSE: msg = """ compression='zstd' only works with netcdf-c >= 4.9.0. To enable, install Cython, make sure you have @@ -4238,7 +4251,7 @@ version 4.9.0 or higher netcdf-c with zstandard support, and rebuild netcdf4-pyt ierr = nc_def_var_bzip2(self._grpid, self._varid, icomplevel) if ierr != NC_NOERR: if grp.data_model != 'NETCDF4': grp._enddef() - _ensure_nc_success(ierr) + _ensure_nc_success(ierr, extra_msg=error_info) ELSE: msg = """ compression='bzip2' only works with netcdf-c >= 4.9.0. To enable, install Cython, make sure you have @@ -4257,7 +4270,7 @@ version 4.9.0 or higher netcdf-c with bzip2 support, and rebuild netcdf4-python. iblosc_shuffle) if ierr != NC_NOERR: if grp.data_model != 'NETCDF4': grp._enddef() - _ensure_nc_success(ierr) + _ensure_nc_success(ierr, extra_msg=error_info) ELSE: msg = """ compression='blosc_*' only works with netcdf-c >= 4.9.0. To enable, install Cython, make sure you have @@ -4269,7 +4282,7 @@ version 4.9.0 or higher netcdf-c with blosc support, and rebuild netcdf4-python. ierr = nc_def_var_fletcher32(self._grpid, self._varid, 1) if ierr != NC_NOERR: if grp.data_model != 'NETCDF4': grp._enddef() - _ensure_nc_success(ierr) + _ensure_nc_success(ierr, extra_msg=error_info) # set chunking stuff. if ndims: # don't bother for scalar variable. if contiguous: @@ -4297,7 +4310,7 @@ version 4.9.0 or higher netcdf-c with blosc support, and rebuild netcdf4-python. free(chunksizesp) if ierr != NC_NOERR: if grp.data_model != 'NETCDF4': grp._enddef() - _ensure_nc_success(ierr) + _ensure_nc_success(ierr, extra_msg=error_info) # set endian-ness of variable if endian == 'little': with nogil: @@ -4329,17 +4342,17 @@ version 4.9.0 or higher netcdf-c with blosc support, and rebuild netcdf4-python. ELSE: if significant_digits is not None: - msg = """ + msg = f""" significant_digits kwarg only works with netcdf-c >= 4.9.0. To enable, install Cython, make sure you have version 4.9.0 or higher netcdf-c, and rebuild netcdf4-python. Otherwise, use least_significant_digit -kwarg for quantization.""" +kwarg for quantization. {error_info}""" raise ValueError(msg) if ierr != NC_NOERR: if grp.data_model != 'NETCDF4': grp._enddef() - _ensure_nc_success(ierr) + _ensure_nc_success(ierr, extra_msg=error_info) else: if endian != 'native': - msg="only endian='native' allowed for NETCDF3 files" + msg=f"only endian='native' allowed for NETCDF3 files {error_info}" raise RuntimeError(msg) # set a fill value for this variable if fill_value keyword # given. This avoids the HDF5 overhead of deleting and @@ -4356,7 +4369,7 @@ kwarg for quantization.""" ierr = nc_def_var_fill(self._grpid, self._varid, 1, NULL) if ierr != NC_NOERR: if grp.data_model != 'NETCDF4': grp._enddef() - _ensure_nc_success(ierr) + _ensure_nc_success(ierr, extra_msg=error_info) else: if self._isprimitive or self._isenum or \ (self._isvlen and self.dtype == str): @@ -4381,7 +4394,7 @@ kwarg for quantization.""" # set ndim attribute (number of dimensions). with nogil: ierr = nc_inq_varndims(self._grpid, self._varid, &numdims) - _ensure_nc_success(ierr) + _ensure_nc_success(ierr, extra_msg=error_info) self.ndim = numdims self._name = name # default for automatically applying scale_factor and From 04f29b888c7d37c2e12fb095ec10d893a6a528ba Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Tue, 29 Aug 2023 09:52:37 +0100 Subject: [PATCH 1013/1504] Add changelog entry for error message reporting --- Changelog | 1 + 1 file changed, 1 insertion(+) diff --git a/Changelog b/Changelog index ac1271c90..8970167b9 100644 --- a/Changelog +++ b/Changelog @@ -1,6 +1,7 @@ version 1.6.5 (not yet released) =============================== * fix for issue #1271 (mask ignored if bool MA assinged to uint8 var) + * include information on specific object when reporting errors from netcdf-c version 1.6.4 (tag v1.6.4rel) =============================== From 1a96ee97550fb60d1e8685d9cf2ad10e5ab241d6 Mon Sep 17 00:00:00 2001 From: stubbiali Date: Thu, 31 Aug 2023 00:05:01 +0200 Subject: [PATCH 1014/1504] Update build requirements. --- pyproject.toml | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 01562cefb..3e3376605 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,8 +1,9 @@ [build-system] requires = [ - "Cython>=0.29", + "Cython==0.29.36", + "mpi4py>=3.1", "oldest-supported-numpy", - "setuptools>=61", + "setuptools>=65.5.0", ] build-backend = "setuptools.build_meta" From de11aa698494fb0cbaef1f10f2fc31aa518cdbb1 Mon Sep 17 00:00:00 2001 From: stubbiali Date: Thu, 31 Aug 2023 10:36:40 +0200 Subject: [PATCH 1015/1504] Relax constraint on cython. --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 3e3376605..8b2bd8629 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [build-system] requires = [ - "Cython==0.29.36", + "Cython>=0.29", "mpi4py>=3.1", "oldest-supported-numpy", "setuptools>=65.5.0", From 02d0c667bf40ac57cea0d6d7e76ef31646b66bc0 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Tue, 5 Sep 2023 03:59:27 +0000 Subject: [PATCH 1016/1504] Bump actions/checkout from 3 to 4 Bumps [actions/checkout](https://github.com/actions/checkout) from 3 to 4. - [Release notes](https://github.com/actions/checkout/releases) - [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md) - [Commits](https://github.com/actions/checkout/compare/v3...v4) --- updated-dependencies: - dependency-name: actions/checkout dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- .github/workflows/build_latest.yml | 2 +- .github/workflows/build_master.yml | 2 +- .github/workflows/build_old.yml | 2 +- .github/workflows/miniconda.yml | 4 ++-- 4 files changed, 5 insertions(+), 5 deletions(-) diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml index fab9510db..3d252e1cc 100644 --- a/.github/workflows/build_latest.yml +++ b/.github/workflows/build_latest.yml @@ -16,7 +16,7 @@ jobs: python-version: ["3.11"] steps: - - uses: actions/checkout@v3 + - uses: actions/checkout@v4 - name: Set up Python ${{ matrix.python-version }} uses: actions/setup-python@v4 diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index 3bd836abd..c2a00e76f 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -13,7 +13,7 @@ jobs: python-version: ["3.11"] steps: - - uses: actions/checkout@v3 + - uses: actions/checkout@v4 - name: Set up Python ${{ matrix.python-version }} uses: actions/setup-python@v4 diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml index c06d37604..e00d8be17 100644 --- a/.github/workflows/build_old.yml +++ b/.github/workflows/build_old.yml @@ -16,7 +16,7 @@ jobs: python-version: ["3.11"] steps: - - uses: actions/checkout@v3 + - uses: actions/checkout@v4 - name: Set up Python ${{ matrix.python-version }} uses: actions/setup-python@v4 diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index 8db0307f1..7cc6ea71b 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -21,7 +21,7 @@ jobs: fail-fast: false steps: - - uses: actions/checkout@v3 + - uses: actions/checkout@v4 - name: Setup Micromamba uses: mamba-org/setup-micromamba@v1 @@ -52,7 +52,7 @@ jobs: os: [ubuntu-latest] platform: [x64] steps: - - uses: actions/checkout@v3 + - uses: actions/checkout@v4 - name: Setup Micromamba uses: mamba-org/setup-micromamba@v1 From ce8babc15806aa617c3d0d61b5a4d8e4ceb00fb6 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Wed, 27 Sep 2023 14:22:52 +0100 Subject: [PATCH 1017/1504] Add compatibility shims for optional/missing functions This helps remove lots of the deprecated Cython IF/DEF statements --- include/netCDF4.pxi | 133 ++++++++--------- include/netcdf-compat.h | 180 +++++++++++++++++++++++ setup.py | 135 ++---------------- src/netCDF4/_netCDF4.pyx | 298 +++++++++++++++++++-------------------- 4 files changed, 410 insertions(+), 336 deletions(-) create mode 100644 include/netcdf-compat.h diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi index 72b876585..9dc5d11f9 100644 --- a/include/netCDF4.pxi +++ b/include/netCDF4.pxi @@ -358,72 +358,13 @@ cdef extern from "netcdf.h": int nc_set_chunk_cache(size_t size, size_t nelems, float preemption) nogil int nc_set_var_chunk_cache(int ncid, int varid, size_t size, size_t nelems, float preemption) nogil int nc_get_var_chunk_cache(int ncid, int varid, size_t *sizep, size_t *nelemsp, float *preemptionp) nogil - int nc_rename_grp(int grpid, char *name) nogil int nc_def_enum(int ncid, nc_type base_typeid, char *name, nc_type *typeidp) nogil int nc_insert_enum(int ncid, nc_type xtype, char *name, void *value) nogil int nc_inq_enum(int ncid, nc_type xtype, char *name, nc_type *base_nc_typep,\ size_t *base_sizep, size_t *num_membersp) nogil int nc_inq_enum_member(int ncid, nc_type xtype, int idx, char *name, void *value) nogil - int nc_inq_enum_ident(int ncid, nc_type xtype, long long value, char *identifier) nogil - int nc_rc_set(char* key, char* value) nogil - -IF HAS_QUANTIZATION_SUPPORT: - cdef extern from "netcdf.h": - cdef enum: - NC_NOQUANTIZE - NC_QUANTIZE_BITGROOM - NC_QUANTIZE_GRANULARBR - NC_QUANTIZE_BITROUND - int nc_def_var_quantize(int ncid, int varid, int quantize_mode, int nsd) nogil - int nc_inq_var_quantize(int ncid, int varid, int *quantize_modep, int *nsdp) nogil - -IF HAS_NCFILTER: - cdef extern from "netcdf_filter.h": - int nc_inq_filter_avail(int ncid, unsigned filterid) nogil - -IF HAS_SZIP_SUPPORT: - cdef extern from "netcdf.h": - cdef enum: - H5Z_FILTER_SZIP - int nc_def_var_quantize(int ncid, int varid, int quantize_mode, int nsd) nogil - int nc_inq_var_quantize(int ncid, int varid, int *quantize_modep, int *nsdp) nogil - int nc_def_var_szip(int ncid, int varid, int options_mask, int pixels_per_bloc) nogil - int nc_inq_var_szip(int ncid, int varid, int *options_maskp, int *pixels_per_blockp) nogil - -IF HAS_ZSTANDARD_SUPPORT: - cdef extern from "netcdf_filter.h": - cdef enum: - H5Z_FILTER_ZSTD - int nc_def_var_zstandard(int ncid, int varid, int level) nogil - int nc_inq_var_zstandard(int ncid, int varid, int* hasfilterp, int *levelp) nogil - -IF HAS_BZIP2_SUPPORT: - cdef extern from "netcdf_filter.h": - cdef enum: - H5Z_FILTER_BZIP2 - int nc_def_var_bzip2(int ncid, int varid, int level) nogil - int nc_inq_var_bzip2(int ncid, int varid, int* hasfilterp, int *levelp) nogil - -IF HAS_BLOSC_SUPPORT: - cdef extern from "netcdf_filter.h": - cdef enum: - H5Z_FILTER_BLOSC - int nc_def_var_blosc(int ncid, int varid, unsigned subcompressor, unsigned level, unsigned blocksize, unsigned addshuffle) nogil - int nc_inq_var_blosc(int ncid, int varid, int* hasfilterp, unsigned* subcompressorp, unsigned* levelp, unsigned* blocksizep, unsigned* addshufflep) nogil - -IF HAS_NC_OPEN_MEM: - cdef extern from "netcdf_mem.h": - int nc_open_mem(const char *path, int mode, size_t size, void* memory, int *ncidp) nogil -IF HAS_NC_CREATE_MEM: - cdef extern from "netcdf_mem.h": - int nc_create_mem(const char *path, int mode, size_t initialize, int *ncidp) nogil - ctypedef struct NC_memio: - size_t size - void* memory - int flags - int nc_close_memio(int ncid, NC_memio* info) nogil IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: cdef extern from "mpi-compat.h": pass @@ -442,11 +383,6 @@ IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: NC_MPIPOSIX NC_PNETCDF -IF HAS_SET_ALIGNMENT: - cdef extern from "netcdf.h": - int nc_set_alignment(int threshold, int alignment) - int nc_get_alignment(int *threshold, int *alignment) - # taken from numpy.pxi in numpy 1.0rc2. cdef extern from "numpy/arrayobject.h": ctypedef int npy_intp @@ -459,3 +395,72 @@ cdef extern from "numpy/arrayobject.h": char* PyArray_BYTES(ndarray) nogil npy_intp* PyArray_STRIDES(ndarray) nogil void import_array() + + +# Compatibility shims +cdef extern from "netcdf-compat.h": + int nc_rename_grp(int grpid, char *name) nogil + int nc_set_alignment(int threshold, int alignment) + int nc_get_alignment(int *threshold, int *alignment) + int nc_rc_set(char* key, char* value) nogil + + int nc_open_mem(const char *path, int mode, size_t size, void* memory, int *ncidp) nogil + int nc_create_mem(const char *path, int mode, size_t initialize, int *ncidp) nogil + ctypedef struct NC_memio: + size_t size + void* memory + int flags + int nc_close_memio(int ncid, NC_memio* info) nogil + + # Quantize shims + int nc_def_var_quantize(int ncid, int varid, int quantize_mode, int nsd) nogil + int nc_inq_var_quantize(int ncid, int varid, int *quantize_modep, int *nsdp) nogil + + # Filter shims + int nc_inq_filter_avail(int ncid, unsigned filterid) nogil + + int nc_def_var_szip(int ncid, int varid, int options_mask, + int pixels_per_bloc) nogil + int nc_inq_var_szip(int ncid, int varid, int *options_maskp, + int *pixels_per_blockp) nogil + + int nc_def_var_zstandard(int ncid, int varid, int level) nogil + int nc_inq_var_zstandard(int ncid, int varid, int* hasfilterp, int *levelp) nogil + + int nc_def_var_bzip2(int ncid, int varid, int level) nogil + int nc_inq_var_bzip2(int ncid, int varid, int* hasfilterp, int *levelp) nogil + + int nc_def_var_blosc(int ncid, int varid, unsigned subcompressor, unsigned level, + unsigned blocksize, unsigned addshuffle) nogil + int nc_inq_var_blosc(int ncid, int varid, int* hasfilterp, unsigned* subcompressorp, + unsigned* levelp, unsigned* blocksizep, + unsigned* addshufflep) nogil + + cdef enum: + HAS_RENAME_GRP + HAS_NC_INQ_PATH + HAS_NC_INQ_FORMAT_EXTENDED + HAS_NC_OPEN_MEM + HAS_NC_CREATE_MEM + HAS_CDF5_FORMAT + HAS_PARALLEL_SUPPORT + HAS_PARALLEL4_SUPPORT + HAS_PNETCDF_SUPPORT + HAS_SZIP_SUPPORT + HAS_QUANTIZATION_SUPPORT + HAS_ZSTANDARD_SUPPORT + HAS_BZIP2_SUPPORT + HAS_BLOSC_SUPPORT + HAS_SET_ALIGNMENT + HAS_NCFILTER + HAS_NCRCSET + + NC_NOQUANTIZE + NC_QUANTIZE_BITGROOM + NC_QUANTIZE_GRANULARBR + NC_QUANTIZE_BITROUND + + H5Z_FILTER_SZIP + H5Z_FILTER_ZSTD + H5Z_FILTER_BZIP2 + H5Z_FILTER_BLOSC diff --git a/include/netcdf-compat.h b/include/netcdf-compat.h new file mode 100644 index 000000000..e961c1163 --- /dev/null +++ b/include/netcdf-compat.h @@ -0,0 +1,180 @@ +#include +#include + +#define NC_VERSION_EQ(MAJOR, MINOR, PATCH) \ + ((NC_VERSION_MAJOR == (MAJOR)) && \ + (NC_VERSION_MINOR == (MINOR)) && \ + (NC_VERSION_PATCH == (PATCH))) + +#define NC_VERSION_GT(MAJOR, MINOR, PATCH) \ + (NC_VERSION_MAJOR > (MAJOR) || \ + (NC_VERSION_MAJOR == (MAJOR) && \ + (NC_VERSION_MINOR > (MINOR) || \ + (NC_VERSION_MINOR == (MINOR) && \ + (NC_VERSION_PATCH > (PATCH)))))) + +#define NC_VERSION_GE(MAJOR, MINOR, PATCH) \ + (NC_VERSION_GT(MAJOR, MINOR, PATCH) || \ + NC_VERSION_EQ(MAJOR, MINOR, PATCH)) + +#if NC_VERSION_GE(4, 3, 0) +#define HAS_RENAME_GRP 1 +#else +#define HAS_RENAME_GRP 0 +static inline int nc_rename_grp(int grpid, const char* name) { return NC_EINVAL; } +#endif + +#if NC_VERSION_GE(4, 1, 2) +#define HAS_NC_INQ_PATH 1 +#else +#define HAS_NC_INQ_PATH 0 +static inline int nc_inq_path(int ncid, size_t *pathlen, char *path) { + *pathlen = 0; *path = "\0"; return NC_EINVAL; +} +#endif + +#if NC_VERSION_GE(4, 3, 1) +#define HAS_NC_INQ_FORMAT_EXTENDED 1 +#else +#define HAS_NC_INQ_FORMAT_EXTENDED 0 +static inline int nc_inq_format_extended(int ncid, int *formatp, int* modep) { + *formatp = 0; *modep = 0; return NC_EINVAL; +} +#endif + +#if NC_VERSION_GE(4, 9, 0) +#define HAS_SET_ALIGNMENT 1 +#else +#define HAS_SET_ALIGNMENT 0 +static inline int nc_set_alignment(int threshold, int alignment) { return NC_EINVAL; } +static inline int nc_get_alignment(int* thresholdp, int* alignmentp) { + *thresholdp = 0; *alignmentp = 0; return NC_EINVAL; +} +#endif + +#if NC_VERSION_GE(4, 9, 0) +#define HAS_NCRCSET 1 +#else +#define HAS_NCRCSET 0 +static inline int nc_rc_set(const char* key, const char* value) { return NC_EINVAL; } +#endif + +#if NC_VERSION_GE(4, 4, 0) +#include +#define HAS_NC_OPEN_MEM 1 +#else +#define HAS_NC_OPEN_MEM 0 +static inline int nc_open_mem(const char *path, int mode, size_t size, void* memory, int *ncidp) { return NC_EINVAL; } +#endif + +#if NC_VERSION_GE(4, 6, 2) +#define HAS_NC_CREATE_MEM 1 +#else +#define HAS_NC_CREATE_MEM 0 +static inline int nc_create_mem(const char *path, int mode, size_t initialize, int *ncidp) { return NC_EINVAL; } +typedef struct NC_memio { + size_t size; + void* memory; + int flags; +} NC_memio; +static inline int nc_close_memio(int ncid, NC_memio* info) { return NC_EINVAL; } +#endif + +#if defined(NC_HAS_CDF5) && NC_HAS_CDF5 +#define HAS_CDF5_FORMAT 1 +#else +# ifndef NC_HAS_CDF5 +# define NC_64BIT_DATA 0x0020 +# define NC_CDF5 NC_64BIT_DATA +# define NC_FORMAT_64BIT_OFFSET (2) +# define NC_FORMAT_64BIT_DATA (5) +# endif +#define HAS_CDF5_FORMAT 0 +#endif + +#if defined(NC_HAS_PARALLEL) && NC_HAS_PARALLEL +#define HAS_PARALLEL_SUPPORT 1 +#else +#define HAS_PARALLEL_SUPPORT 0 +#endif + +#if defined(NC_HAS_PARALLEL4) && NC_HAS_PARALLEL4 +#define HAS_PARALLEL4_SUPPORT 1 +#else +#define HAS_PARALLEL4_SUPPORT 0 +#endif + +#if defined(NC_HAS_PNETCDF) && NC_HAS_PNETCDF +#define HAS_PNETCDF_SUPPORT 1 +#else +#define HAS_PNETCDF_SUPPORT 0 +#endif + +#if NC_VERSION_GE(4, 9, 0) +#include +#define HAS_NCFILTER 1 +#else +#define HAS_NCFILTER 0 +static inline int nc_inq_filter_avail(int ncid, unsigned filterid) { return -136; } +#endif + +#if defined(NC_HAS_SZIP) && NC_HAS_SZIP +#define HAS_SZIP_SUPPORT 1 +#else +#define HAS_SZIP_SUPPORT 0 +static inline int nc_def_var_szip(int ncid, int varid, int options_mask, int pixels_per_bloc) { return NC_EINVAL; } +# ifndef H5Z_FILTER_SZIP +# define H5Z_FILTER_SZIP 4 +# endif +#endif + +#if defined(NC_HAS_QUANTIZE) && NC_HAS_QUANTIZE +#define HAS_QUANTIZATION_SUPPORT 1 +#else +#define HAS_QUANTIZATION_SUPPORT 0 +# ifndef NC_HAS_QUANTIZE +static inline int nc_def_var_quantize(int ncid, int varid, int quantize_mode, int nsd) { return NC_EINVAL; } +static inline int nc_inq_var_quantize(int ncid, int varid, int *quantize_modep, int *nsdp) { return NC_EINVAL; } +# define NC_NOQUANTIZE 0 +# define NC_QUANTIZE_BITGROOM 1 +# define NC_QUANTIZE_GRANULARBR 2 +# define NC_QUANTIZE_BITROUND 3 +# endif +#endif + +#if defined(NC_HAS_ZSTANDARD) && NC_HAS_ZSTANDARD +#define HAS_ZSTANDARD_SUPPORT 1 +#else +# ifndef NC_HAS_ZSTANDARD +static inline int nc_def_var_zstandard(int ncid, int varid, int level) { return NC_EINVAL; } +static inline int nc_inq_var_zstandard(int ncid, int varid, int* hasfilterp, int *levelp) { return NC_EINVAL; } +# define H5Z_FILTER_ZSTD 32015 +# endif +#define HAS_ZSTANDARD_SUPPORT 0 +#endif + +#if defined(NC_HAS_BZIP2) && NC_HAS_BZIP2 +#define HAS_BZIP2_SUPPORT 1 +#else +# ifndef NC_HAS_BZIP2 +static inline int nc_def_var_bzip2(int ncid, int varid, int level) { return NC_EINVAL; } +static inline int nc_inq_var_bzip2(int ncid, int varid, int* hasfilterp, int *levelp) { return NC_EINVAL; } +# define H5Z_FILTER_BZIP2 307 +# endif +#define HAS_BZIP2_SUPPORT 0 +#endif + +#if defined(NC_HAS_BLOSC) && NC_HAS_BLOSC +#define HAS_BLOSC_SUPPORT 1 +#else +# ifndef NC_HAS_BLOSC +static inline int nc_def_var_blosc(int ncid, int varid, unsigned subcompressor, unsigned level, unsigned blocksize, unsigned addshuffle) { + return NC_EINVAL; +} +static inline int nc_inq_var_blosc(int ncid, int varid, int* hasfilterp, unsigned* subcompressorp, unsigned* levelp, unsigned* blocksizep, unsigned* addshufflep) { + return NC_EINVAL; +} +# define H5Z_FILTER_BLOSC 32001 +# endif +#define HAS_BLOSC_SUPPORT 0 +#endif diff --git a/setup.py b/setup.py index 5bf61e16a..a03fe58ed 100644 --- a/setup.py +++ b/setup.py @@ -575,129 +575,20 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): (netcdf_lib_version > "4.4" and netcdf_lib_version < "4.5"): has_cdf5_format = True - # disable parallel support if mpi4py not available. - #try: - # import mpi4py - #except ImportError: - # f.write('disabling mpi parallel support because mpi4py not found\n') - # has_parallel4_support = False - # has_pnetcdf_support = False - - f = open(osp.join('include', 'constants.pyx'), 'w') - if has_rename_grp: - sys.stdout.write('netcdf lib has group rename capability\n') - f.write('DEF HAS_RENAME_GRP = 1\n') - else: - sys.stdout.write('netcdf lib does not have group rename capability\n') - f.write('DEF HAS_RENAME_GRP = 0\n') - - if has_nc_inq_path: - sys.stdout.write('netcdf lib has nc_inq_path function\n') - f.write('DEF HAS_NC_INQ_PATH = 1\n') - else: - sys.stdout.write('netcdf lib does not have nc_inq_path function\n') - f.write('DEF HAS_NC_INQ_PATH = 0\n') - - if has_nc_inq_format_extended: - sys.stdout.write('netcdf lib has nc_inq_format_extended function\n') - f.write('DEF HAS_NC_INQ_FORMAT_EXTENDED = 1\n') - else: - sys.stdout.write( - 'netcdf lib does not have nc_inq_format_extended function\n') - f.write('DEF HAS_NC_INQ_FORMAT_EXTENDED = 0\n') - - if has_nc_open_mem: - sys.stdout.write('netcdf lib has nc_open_mem function\n') - f.write('DEF HAS_NC_OPEN_MEM = 1\n') - else: - sys.stdout.write('netcdf lib does not have nc_open_mem function\n') - f.write('DEF HAS_NC_OPEN_MEM = 0\n') - - if has_nc_create_mem: - sys.stdout.write('netcdf lib has nc_create_mem function\n') - f.write('DEF HAS_NC_CREATE_MEM = 1\n') - else: - sys.stdout.write('netcdf lib does not have nc_create_mem function\n') - f.write('DEF HAS_NC_CREATE_MEM = 0\n') - - if has_cdf5_format: - sys.stdout.write('netcdf lib has cdf-5 format capability\n') - f.write('DEF HAS_CDF5_FORMAT = 1\n') - else: - sys.stdout.write('netcdf lib does not have cdf-5 format capability\n') - f.write('DEF HAS_CDF5_FORMAT = 0\n') - - if has_parallel4_support: - sys.stdout.write('netcdf lib has netcdf4 parallel functions\n') - f.write('DEF HAS_PARALLEL4_SUPPORT = 1\n') - else: - sys.stdout.write('netcdf lib does not have netcdf4 parallel functions\n') - f.write('DEF HAS_PARALLEL4_SUPPORT = 0\n') - - if has_pnetcdf_support: - sys.stdout.write('netcdf lib has pnetcdf parallel functions\n') - f.write('DEF HAS_PNETCDF_SUPPORT = 1\n') - else: - sys.stdout.write('netcdf lib does not have pnetcdf parallel functions\n') - f.write('DEF HAS_PNETCDF_SUPPORT = 0\n') - - if has_quantize: - sys.stdout.write('netcdf lib has bit-grooming/quantization functions\n') - f.write('DEF HAS_QUANTIZATION_SUPPORT = 1\n') - else: - sys.stdout.write('netcdf lib does not have bit-grooming/quantization functions\n') - f.write('DEF HAS_QUANTIZATION_SUPPORT = 0\n') - - if has_zstandard: - sys.stdout.write('netcdf lib has zstandard compression functions\n') - f.write('DEF HAS_ZSTANDARD_SUPPORT = 1\n') - else: - sys.stdout.write('netcdf lib does not have zstandard compression functions\n') - f.write('DEF HAS_ZSTANDARD_SUPPORT = 0\n') - - if has_bzip2: - sys.stdout.write('netcdf lib has bzip2 compression functions\n') - f.write('DEF HAS_BZIP2_SUPPORT = 1\n') - else: - sys.stdout.write('netcdf lib does not have bzip2 compression functions\n') - f.write('DEF HAS_BZIP2_SUPPORT = 0\n') - - if has_blosc: - sys.stdout.write('netcdf lib has blosc compression functions\n') - f.write('DEF HAS_BLOSC_SUPPORT = 1\n') - else: - sys.stdout.write('netcdf lib does not have blosc compression functions\n') - f.write('DEF HAS_BLOSC_SUPPORT = 0\n') - - if has_szip_support: - sys.stdout.write('netcdf lib has szip compression functions\n') - f.write('DEF HAS_SZIP_SUPPORT = 1\n') - else: - sys.stdout.write('netcdf lib does not have szip compression functions\n') - f.write('DEF HAS_SZIP_SUPPORT = 0\n') - - if has_set_alignment: - sys.stdout.write('netcdf lib has nc_set_alignment function\n') - f.write('DEF HAS_SET_ALIGNMENT = 1\n') - else: - sys.stdout.write('netcdf lib does not have nc_set_alignment function\n') - f.write('DEF HAS_SET_ALIGNMENT = 0\n') - - if has_ncfilter: - sys.stdout.write('netcdf lib has nc_inq_filter_avail function\n') - f.write('DEF HAS_NCFILTER = 1\n') - else: - sys.stdout.write('netcdf lib does not have nc_inq_filter_avail function\n') - f.write('DEF HAS_NCFILTER = 0\n') - - if has_nc_rc_set: - sys.stdout.write('netcdf lib has nc_rc_set function\n') - f.write('DEF HAS_NCRCSET = 1\n') - else: - sys.stdout.write('netcdf lib does not have nc_rc_set function\n') - f.write('DEF HAS_NCRCSET = 0\n') + with open(osp.join('include', 'constants.pyx'), 'w') as f: + if has_parallel4_support: + sys.stdout.write('netcdf lib has netcdf4 parallel functions\n') + f.write('DEF HAS_PARALLEL4_SUPPORT = 1\n') + else: + sys.stdout.write('netcdf lib does not have netcdf4 parallel functions\n') + f.write('DEF HAS_PARALLEL4_SUPPORT = 0\n') - f.close() + if has_pnetcdf_support: + sys.stdout.write('netcdf lib has pnetcdf parallel functions\n') + f.write('DEF HAS_PNETCDF_SUPPORT = 1\n') + else: + sys.stdout.write('netcdf lib does not have pnetcdf parallel functions\n') + f.write('DEF HAS_PNETCDF_SUPPORT = 0\n') if has_parallel4_support or has_pnetcdf_support: import mpi4py diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 3edbc6f34..393ebbc99 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1247,6 +1247,24 @@ numpy.import_array() include "constants.pyx" include "membuf.pyx" include "netCDF4.pxi" + +__has_rename_grp__ = HAS_RENAME_GRP +__has_nc_inq_path__ = HAS_NC_INQ_PATH +__has_nc_inq_format_extended__ = HAS_NC_INQ_FORMAT_EXTENDED +__has_cdf5_format__ = HAS_CDF5_FORMAT +__has_nc_open_mem__ = HAS_NC_OPEN_MEM +__has_nc_create_mem__ = HAS_NC_CREATE_MEM +__has_parallel4_support__ = HAS_PARALLEL4_SUPPORT +__has_pnetcdf_support__ = HAS_PNETCDF_SUPPORT +__has_quantization_support__ = HAS_QUANTIZATION_SUPPORT +__has_zstandard_support__ = HAS_ZSTANDARD_SUPPORT +__has_bzip2_support__ = HAS_BZIP2_SUPPORT +__has_blosc_support__ = HAS_BLOSC_SUPPORT +__has_szip_support__ = HAS_SZIP_SUPPORT +__has_set_alignment__ = HAS_SET_ALIGNMENT +__has_ncfilter__ = HAS_NCFILTER + + IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: cimport mpi4py.MPI as MPI from mpi4py.libmpi cimport MPI_Comm, MPI_Info, MPI_Comm_dup, MPI_Info_dup, \ @@ -1259,21 +1277,14 @@ ELSE: ctypedef object Info # set path to SSL certificates (issue #1246) -IF HAS_NCRCSET: # available starting in version 4.9.1 +# available starting in version 4.9.1 +if HAS_NCRCSET: import certifi - cdef _set_curl_certpath(certpath): - cdef char *cert_path - cdef char *key - cdef int ierr - bytestr = _strencode(certpath) - cert_path = bytestr - ierr = nc_rc_set("HTTP.SSL.CAINFO",cert_path) - if ierr != 0: - raise RuntimeError('error setting path to SSL certificates') - _set_curl_certpath(certifi.where()) + if nc_rc_set("HTTP.SSL.CAINFO", _strencode(certifi.where())) != 0: + raise RuntimeError('error setting path to SSL certificates') -# check for required version of netcdf-4 and hdf5. +# check for required version of netcdf-4 and hdf5. def _gethdf5libversion(): cdef unsigned int majorvers, minorvers, releasevers cdef herr_t ierr @@ -1336,10 +1347,9 @@ details.""" ierr = nc_set_chunk_cache(sizep,nelemsp, preemptionp) _ensure_nc_success(ierr) -IF HAS_SET_ALIGNMENT: - def get_alignment(): - """ - **`get_alignment()`** + +def get_alignment(): + """**`get_alignment()`** return current netCDF alignment within HDF5 files in a tuple (threshold,alignment). See netcdf C library documentation for @@ -1347,57 +1357,46 @@ IF HAS_SET_ALIGNMENT: `set_alignment`. This function was added in netcdf 4.9.0.""" - cdef int ierr - cdef int thresholdp, alignmentp - ierr = nc_get_alignment(&thresholdp, &alignmentp) - _ensure_nc_success(ierr) - threshold = thresholdp - alignment = alignmentp - return (threshold,alignment) - def set_alignment(threshold, alignment): - """ - **`set_alignment(threshold,alignment)`** + if not __has_set_alignment__: + raise RuntimeError( + "This function requires netcdf4 4.9.0+ to be used at compile time" + ) + + cdef int ierr + cdef int thresholdp, alignmentp + ierr = nc_get_alignment(&thresholdp, &alignmentp) + _ensure_nc_success(ierr) + threshold = thresholdp + alignment = alignmentp + return (threshold, alignment) + + +def set_alignment(threshold, alignment): + """**`set_alignment(threshold,alignment)`** Change the HDF5 file alignment. See netcdf C library documentation for `nc_set_alignment` for details. This function was added in netcdf 4.9.0.""" - cdef int ierr - cdef int thresholdp, alignmentp - thresholdp = threshold - alignmentp = alignment - ierr = nc_set_alignment(thresholdp, alignmentp) - _ensure_nc_success(ierr) -ELSE: - def get_alignment(): + if not __has_set_alignment__: raise RuntimeError( "This function requires netcdf4 4.9.0+ to be used at compile time" ) - def set_alignment(threshold, alignment): - raise RuntimeError( - "This function requires netcdf4 4.9.0+ to be used at compile time" - ) + cdef int ierr + cdef int thresholdp, alignmentp + thresholdp = threshold + alignmentp = alignment + + ierr = nc_set_alignment(thresholdp, alignmentp) + _ensure_nc_success(ierr) + __netcdf4libversion__ = getlibversion().split()[0] __hdf5libversion__ = _gethdf5libversion() -__has_rename_grp__ = HAS_RENAME_GRP -__has_nc_inq_path__ = HAS_NC_INQ_PATH -__has_nc_inq_format_extended__ = HAS_NC_INQ_FORMAT_EXTENDED -__has_cdf5_format__ = HAS_CDF5_FORMAT -__has_nc_open_mem__ = HAS_NC_OPEN_MEM -__has_nc_create_mem__ = HAS_NC_CREATE_MEM -__has_parallel4_support__ = HAS_PARALLEL4_SUPPORT -__has_pnetcdf_support__ = HAS_PNETCDF_SUPPORT -__has_quantization_support__ = HAS_QUANTIZATION_SUPPORT -__has_zstandard_support__ = HAS_ZSTANDARD_SUPPORT -__has_bzip2_support__ = HAS_BZIP2_SUPPORT -__has_blosc_support__ = HAS_BLOSC_SUPPORT -__has_szip_support__ = HAS_SZIP_SUPPORT -__has_set_alignment__ = HAS_SET_ALIGNMENT _needsworkaround_issue485 = __netcdf4libversion__ < "4.4.0" or \ (__netcdf4libversion__.startswith("4.4.0") and \ "-development" in __netcdf4libversion__) @@ -1448,23 +1447,23 @@ _blosc_dict={'blosc_lz':0,'blosc_lz4':1,'blosc_lz4hc':2,'blosc_snappy':3,'blosc_ _blosc_dict_inv = {v: k for k, v in _blosc_dict.items()} _szip_dict = {'ec': 4, 'nn': 32} _szip_dict_inv = {v: k for k, v in _szip_dict.items()} -IF HAS_CDF5_FORMAT: +if __has_cdf5_format__: # NETCDF3_64BIT deprecated, saved for compatibility. # use NETCDF3_64BIT_OFFSET instead. _format_dict['NETCDF3_64BIT_OFFSET'] = NC_FORMAT_64BIT_OFFSET _format_dict['NETCDF3_64BIT_DATA'] = NC_FORMAT_64BIT_DATA _cmode_dict['NETCDF3_64BIT_OFFSET'] = NC_64BIT_OFFSET _cmode_dict['NETCDF3_64BIT_DATA'] = NC_64BIT_DATA -ELSE: +else: _format_dict['NETCDF3_64BIT'] = NC_FORMAT_64BIT _cmode_dict['NETCDF3_64BIT'] = NC_64BIT_OFFSET # invert dictionary mapping _reverse_format_dict = dict((v, k) for k, v in _format_dict.iteritems()) # add duplicate entry (NETCDF3_64BIT == NETCDF3_64BIT_OFFSET) -IF HAS_CDF5_FORMAT: +if __has_cdf5_format__: _format_dict['NETCDF3_64BIT'] = NC_FORMAT_64BIT_OFFSET _cmode_dict['NETCDF3_64BIT'] = NC_64BIT_OFFSET -ELSE: +else: _format_dict['NETCDF3_64BIT_OFFSET'] = NC_FORMAT_64BIT _cmode_dict['NETCDF3_64BIT_OFFSET'] = NC_64BIT_OFFSET @@ -1632,7 +1631,7 @@ cdef _get_format(int grpid): cdef _get_full_format(int grpid): # Private function to get the underlying disk format cdef int ierr, formatp, modep - IF HAS_NC_INQ_FORMAT_EXTENDED: + if __has_nc_inq_format_extended__: with nogil: ierr = nc_inq_format_extended(grpid, &formatp, &modep) _ensure_nc_success(ierr) @@ -1650,7 +1649,7 @@ cdef _get_full_format(int grpid): return 'DAP4' elif formatp == NC_FORMAT_UNDEFINED: return 'UNDEFINED' - ELSE: + else: return 'UNDEFINED' cdef issue485_workaround(int grpid, int varid, char* attname): @@ -2253,9 +2252,9 @@ strings. raise ValueError(msg) ELSE: parallel_formats = [] - IF HAS_PARALLEL4_SUPPORT: + if __has_parallel4_support__: parallel_formats += ['NETCDF4','NETCDF4_CLASSIC'] - IF HAS_PNETCDF_SUPPORT: + if __has_pnetcdf_support__: parallel_formats += ['NETCDF3_CLASSIC', 'NETCDF3_64BIT_OFFSET', 'NETCDF3_64BIT_DATA', @@ -2284,12 +2283,12 @@ strings. if memory is not None: # if memory is not None and mode='w', memory # kwarg is interpreted as advisory size. - IF HAS_NC_CREATE_MEM: + if __has_nc_create_mem__: initialsize = memory with nogil: ierr = nc_create_mem(path, 0, initialsize, &grpid) self._inmemory = True # checked in close method - ELSE: + else: msg = """ nc_create_mem functionality not enabled. To enable, install Cython, make sure you have version 4.6.2 or higher of the netcdf C lib, and rebuild netcdf4-python.""" @@ -2346,7 +2345,7 @@ strings. #_set_default_format(format='NETCDF3_64BIT_OFFSET') elif mode in ('r', 'rs'): if memory is not None: - IF HAS_NC_OPEN_MEM: + if __has_nc_open_mem__: # Store reference to memory result = PyObject_GetBuffer(memory, &self._buffer, PyBUF_SIMPLE | PyBUF_ANY_CONTIGUOUS) if result != 0: @@ -2354,7 +2353,7 @@ strings. with nogil: ierr = nc_open_mem(path, 0, self._buffer.len, self._buffer.buf, &grpid) - ELSE: + else: msg = """ nc_open_mem functionality not enabled. To enable, install Cython, make sure you have version 4.4.1 or higher of the netcdf C lib, and rebuild netcdf4-python.""" @@ -2534,7 +2533,7 @@ changed using the `encoding` kwarg.""" cdef char *c_path if encoding is None: encoding = sys.getfilesystemencoding() - IF HAS_NC_INQ_PATH: + if __has_nc_inq_path__: with nogil: ierr = nc_inq_path(self._grpid, &pathlen, NULL) _ensure_nc_success(ierr) @@ -2551,7 +2550,7 @@ changed using the `encoding` kwarg.""" finally: free(c_path) return py_path.decode(encoding) - ELSE: + else: msg = """ filepath method not enabled. To enable, install Cython, make sure you have version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python.""" @@ -2596,22 +2595,21 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python.""" # view.obj is checked, ref on obj is decremented and obj will be null'd out PyBuffer_Release(&self._buffer) - IF HAS_NC_CREATE_MEM: - def _close_mem(self, check_err): - cdef int ierr - cdef NC_memio memio - with nogil: - ierr = nc_close_memio(self._grpid, &memio) + def _close_mem(self, check_err): + cdef int ierr + cdef NC_memio memio + with nogil: + ierr = nc_close_memio(self._grpid, &memio) - if check_err: - _ensure_nc_success(ierr) + if check_err: + _ensure_nc_success(ierr) - self._isopen = 0 - PyBuffer_Release(&self._buffer) + self._isopen = 0 + PyBuffer_Release(&self._buffer) - # membuf_fromptr from membuf.pyx - creates a python memoryview - # from a raw pointer without making a copy. - return memview_fromptr(memio.memory, memio.size) + # membuf_fromptr from membuf.pyx - creates a python memoryview + # from a raw pointer without making a copy. + return memview_fromptr(memio.memory, memio.size) def close(self): @@ -2620,12 +2618,12 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python.""" Close the Dataset. """ - IF HAS_NC_CREATE_MEM: + if __has_nc_create_mem__: if self._inmemory: return self._close_mem(True) else: self._close(True) - ELSE: + else: self._close(True) def isopen(self): @@ -3164,27 +3162,27 @@ rename a `Dataset` or `Group` attribute named `oldname` to `newname`.""" rename a `Group` named `oldname` to `newname` (requires netcdf >= 4.3.1).""" cdef char *newnamec cdef int grpid - IF HAS_RENAME_GRP: - cdef int ierr - bytestr = _strencode(newname) - newnamec = bytestr - try: - grp = self.groups[oldname] - grpid = grp._grpid - except KeyError: - raise KeyError('%s not a valid group name' % oldname) - with nogil: - ierr = nc_rename_grp(grpid, newnamec) - _ensure_nc_success(ierr) - # remove old key from groups dict. - self.groups.pop(oldname) - # add new key. - self.groups[newname] = grp - ELSE: - msg = """ -renameGroup method not enabled. To enable, install Cython, make sure you have -version 4.3.1 or higher of the netcdf C lib, and rebuild netcdf4-python.""" - raise ValueError(msg) + cdef int ierr + if not __has_rename_grp__: + raise ValueError( + "renameGroup method not enabled. To enable, install Cython, make sure you have" + "version 4.3.1 or higher of the netcdf C lib, and rebuild netcdf4-python." + ) + + bytestr = _strencode(newname) + newnamec = bytestr + try: + grp = self.groups[oldname] + grpid = grp._grpid + except KeyError: + raise KeyError('%s not a valid group name' % oldname) + with nogil: + ierr = nc_rename_grp(grpid, newnamec) + _ensure_nc_success(ierr) + # remove old key from groups dict. + self.groups.pop(oldname) + # add new key. + self.groups[newname] = grp def set_auto_chartostring(self, value): """ @@ -3503,62 +3501,62 @@ to be installed and in `$PATH`. **`has_blosc_filter(self)`** returns True if blosc compression filter is available""" cdef int ierr - IF HAS_BLOSC_SUPPORT: + if __has_blosc_support__: with nogil: ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_BLOSC) if ierr: return False else: return True - ELSE: + else: return False def has_zstd_filter(self): """ **`has_zstd_filter(self)`** returns True if zstd compression filter is available""" cdef int ierr - IF HAS_ZSTANDARD_SUPPORT: + if __has_zstandard_support__: with nogil: ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_ZSTD) if ierr: return False else: return True - ELSE: + else: return False def has_bzip2_filter(self): """ **`has_bzip2_filter(self)`** returns True if bzip2 compression filter is available""" cdef int ierr - IF HAS_BZIP2_SUPPORT: + if __has_bzip2_support__: with nogil: ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_BZIP2) if ierr: return False else: return True - ELSE: + else: return False def has_szip_filter(self): """ **`has_szip_filter(self)`** returns True if szip compression filter is available""" cdef int ierr - IF HAS_NCFILTER: - IF HAS_SZIP_SUPPORT: + if __has_ncfilter__: + if __has_szip_support__: with nogil: ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_SZIP) if ierr: return False else: return True - ELSE: + else: return False - ELSE: - IF HAS_SZIP_SUPPORT: + else: + if __has_szip_support__: return True - ELSE: + else: return False cdef class Group(Dataset): @@ -4215,7 +4213,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. if grp.data_model != 'NETCDF4': grp._enddef() _ensure_nc_success(ierr, extra_msg=error_info) if szip: - IF HAS_SZIP_SUPPORT: + if __has_szip_support__: try: iszip_coding = _szip_dict[szip_coding] except KeyError: @@ -4227,38 +4225,38 @@ behavior is similar to Fortran or Matlab, but different than numpy. if ierr != NC_NOERR: if grp.data_model != 'NETCDF4': grp._enddef() _ensure_nc_success(ierr, extra_msg=error_info) - ELSE: + else: msg = """ compression='szip' only works if linked version of hdf5 has szip functionality enabled""" raise ValueError(msg) if zstd: - IF HAS_ZSTANDARD_SUPPORT: + if __has_zstandard_support__: icomplevel = complevel with nogil: ierr = nc_def_var_zstandard(self._grpid, self._varid, icomplevel) if ierr != NC_NOERR: if grp.data_model != 'NETCDF4': grp._enddef() _ensure_nc_success(ierr, extra_msg=error_info) - ELSE: + else: msg = """ compression='zstd' only works with netcdf-c >= 4.9.0. To enable, install Cython, make sure you have version 4.9.0 or higher netcdf-c with zstandard support, and rebuild netcdf4-python.""" raise ValueError(msg) if bzip2: - IF HAS_BZIP2_SUPPORT: + if __has_bzip2_support__: icomplevel = complevel with nogil: ierr = nc_def_var_bzip2(self._grpid, self._varid, icomplevel) if ierr != NC_NOERR: if grp.data_model != 'NETCDF4': grp._enddef() _ensure_nc_success(ierr, extra_msg=error_info) - ELSE: + else: msg = """ compression='bzip2' only works with netcdf-c >= 4.9.0. To enable, install Cython, make sure you have version 4.9.0 or higher netcdf-c with bzip2 support, and rebuild netcdf4-python.""" raise ValueError(msg) if blosc_zstd or blosc_lz or blosc_lz4 or blosc_lz4hc or blosc_zlib: - IF HAS_BLOSC_SUPPORT: + if __has_blosc_support__: iblosc_compressor = _blosc_dict[compression] iblosc_shuffle = blosc_shuffle iblosc_blocksize = 0 # not currently used by c lib @@ -4271,7 +4269,7 @@ version 4.9.0 or higher netcdf-c with bzip2 support, and rebuild netcdf4-python. if ierr != NC_NOERR: if grp.data_model != 'NETCDF4': grp._enddef() _ensure_nc_success(ierr, extra_msg=error_info) - ELSE: + else: msg = """ compression='blosc_*' only works with netcdf-c >= 4.9.0. To enable, install Cython, make sure you have version 4.9.0 or higher netcdf-c with blosc support, and rebuild netcdf4-python.""" @@ -4323,7 +4321,7 @@ version 4.9.0 or higher netcdf-c with blosc support, and rebuild netcdf4-python. else: raise ValueError("'endian' keyword argument must be 'little','big' or 'native', got '%s'" % endian) # set quantization - IF HAS_QUANTIZATION_SUPPORT: + if __has_quantization_support__: if significant_digits is not None: nsd = significant_digits if quantize_mode == 'BitGroom': @@ -4340,7 +4338,7 @@ version 4.9.0 or higher netcdf-c with blosc support, and rebuild netcdf4-python. else: raise ValueError("'quantize_mode' keyword argument must be 'BitGroom','GranularBitRound' or 'BitRound', got '%s'" % quantize_mode) - ELSE: + else: if significant_digits is not None: msg = f""" significant_digits kwarg only works with netcdf-c >= 4.9.0. To enable, install Cython, make sure you have @@ -4686,25 +4684,25 @@ return dictionary containing HDF5 filter parameters.""" with nogil: ierr = nc_inq_var_fletcher32(self._grpid, self._varid, &ifletcher32) _ensure_nc_success(ierr) - IF HAS_ZSTANDARD_SUPPORT: + if __has_zstandard_support__: with nogil: ierr = nc_inq_var_zstandard(self._grpid, self._varid, &izstd,\ &icomplevel_zstd) if ierr != 0: izstd=0 # _ensure_nc_success(ierr) - IF HAS_BZIP2_SUPPORT: + if __has_bzip2_support__: with nogil: ierr = nc_inq_var_bzip2(self._grpid, self._varid, &ibzip2,\ &icomplevel_bzip2) if ierr != 0: ibzip2=0 #_ensure_nc_success(ierr) - IF HAS_BLOSC_SUPPORT: + if __has_blosc_support__: with nogil: ierr = nc_inq_var_blosc(self._grpid, self._varid, &iblosc,\ &iblosc_compressor,&iblosc_complevel,&iblosc_blocksize,&iblosc_shuffle) if ierr != 0: iblosc=0 #_ensure_nc_success(ierr) - IF HAS_SZIP_SUPPORT: + if __has_szip_support__: with nogil: ierr = nc_inq_var_szip(self._grpid, self._varid, &iszip_coding,\ &iszip_pixels_per_block) @@ -4745,30 +4743,30 @@ return dictionary containing HDF5 filter parameters.""" return number of significant digits and the algorithm used in quantization. Returns None if quantization not active. """ - IF HAS_QUANTIZATION_SUPPORT: - cdef int ierr, nsd, quantize_mode - if self._grp.data_model not in ['NETCDF4_CLASSIC','NETCDF4']: - return None - else: - with nogil: - ierr = nc_inq_var_quantize(self._grpid, self._varid, &quantize_mode, &nsd) - _ensure_nc_success(ierr) - if quantize_mode == NC_NOQUANTIZE: - return None - else: - if quantize_mode == NC_QUANTIZE_GRANULARBR: - sig_digits = nsd - quant_mode = 'GranularBitRound' - elif quantize_mode == NC_QUANTIZE_BITROUND: - sig_digits = nsd # interpreted as bits, not decimal - quant_mode = 'BitRound' - else: - sig_digits = nsd - quant_mode = 'BitGroom' - return sig_digits, quant_mode - ELSE: + if not __has_quantization_support__: return None + cdef int ierr, nsd, quantize_mode + if self._grp.data_model not in ['NETCDF4_CLASSIC','NETCDF4']: + return None + + with nogil: + ierr = nc_inq_var_quantize(self._grpid, self._varid, &quantize_mode, &nsd) + _ensure_nc_success(ierr) + if quantize_mode == NC_NOQUANTIZE: + return None + + if quantize_mode == NC_QUANTIZE_GRANULARBR: + sig_digits = nsd + quant_mode = 'GranularBitRound' + elif quantize_mode == NC_QUANTIZE_BITROUND: + sig_digits = nsd # interpreted as bits, not decimal + quant_mode = 'BitRound' + else: + sig_digits = nsd + quant_mode = 'BitGroom' + return sig_digits, quant_mode + def endian(self): """ **`endian(self)`** From 816935aacab362d39a2aaea7bb1f2b8ea2bb2f21 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Wed, 27 Sep 2023 15:22:22 +0100 Subject: [PATCH 1018/1504] Invert conditionals for compile-time features, bail early --- src/netCDF4/_netCDF4.pyx | 401 +++++++++++++++++++-------------------- 1 file changed, 197 insertions(+), 204 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 393ebbc99..e459ee63c 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1411,6 +1411,17 @@ to HDF5 version 1.8.x is highly recommended (see https://github.com/Unidata/netcdf-c/issues/250).""" warnings.warn(msg) + +class NetCDF4MissingFeatureException(Exception): + """Custom exception when trying to use features missing from the linked netCDF library""" + def __init__(self, feature: str, version: str): + super().__init__( + f"{feature} requires netCDF lib >= {version} (using {__netcdf4libversion__}). " + f"To enable, rebuild netcdf4-python using netCDF {version} or higher " + f"(and possibly enable {feature})" + ) + + # numpy data type <--> netCDF 4 data type mapping. _nptonctype = {'S1' : NC_CHAR, 'i1' : NC_BYTE, @@ -1628,30 +1639,33 @@ cdef _get_format(int grpid): raise ValueError('format not supported by python interface') return _reverse_format_dict[formatp] + cdef _get_full_format(int grpid): - # Private function to get the underlying disk format + """Private function to get the underlying disk format""" + + if not __has_nc_inq_format_extended__: + return "UNDEFINED" + cdef int ierr, formatp, modep - if __has_nc_inq_format_extended__: - with nogil: - ierr = nc_inq_format_extended(grpid, &formatp, &modep) - _ensure_nc_success(ierr) - if formatp == NC_FORMAT_NC3: - return 'NETCDF3' - elif formatp == NC_FORMAT_NC_HDF5: - return 'HDF5' - elif formatp == NC_FORMAT_NC_HDF4: - return 'HDF4' - elif formatp == NC_FORMAT_PNETCDF: - return 'PNETCDF' - elif formatp == NC_FORMAT_DAP2: - return 'DAP2' - elif formatp == NC_FORMAT_DAP4: - return 'DAP4' - elif formatp == NC_FORMAT_UNDEFINED: - return 'UNDEFINED' - else: + with nogil: + ierr = nc_inq_format_extended(grpid, &formatp, &modep) + _ensure_nc_success(ierr) + if formatp == NC_FORMAT_NC3: + return 'NETCDF3' + if formatp == NC_FORMAT_NC_HDF5: + return 'HDF5' + if formatp == NC_FORMAT_NC_HDF4: + return 'HDF4' + if formatp == NC_FORMAT_PNETCDF: + return 'PNETCDF' + if formatp == NC_FORMAT_DAP2: + return 'DAP2' + if formatp == NC_FORMAT_DAP4: + return 'DAP4' + if formatp == NC_FORMAT_UNDEFINED: return 'UNDEFINED' + cdef issue485_workaround(int grpid, int varid, char* attname): # check to see if attribute already exists # and is NC_CHAR, if so delete it and re-create it @@ -2281,18 +2295,16 @@ strings. if mode == 'w' or (mode in ['a','r+'] and not os.path.exists(filename)): _set_default_format(format=format) if memory is not None: + if not __has_nc_create_mem__: + raise NetCDF4MissingFeatureException("nc_create_mem", "4.6.2") + # if memory is not None and mode='w', memory # kwarg is interpreted as advisory size. - if __has_nc_create_mem__: - initialsize = memory - with nogil: - ierr = nc_create_mem(path, 0, initialsize, &grpid) - self._inmemory = True # checked in close method - else: - msg = """ - nc_create_mem functionality not enabled. To enable, install Cython, make sure you have - version 4.6.2 or higher of the netcdf C lib, and rebuild netcdf4-python.""" - raise ValueError(msg) + initialsize = memory + with nogil: + ierr = nc_create_mem(path, 0, initialsize, &grpid) + self._inmemory = True # checked in close method + else: if clobber: if parallel: @@ -2345,19 +2357,17 @@ strings. #_set_default_format(format='NETCDF3_64BIT_OFFSET') elif mode in ('r', 'rs'): if memory is not None: - if __has_nc_open_mem__: - # Store reference to memory - result = PyObject_GetBuffer(memory, &self._buffer, PyBUF_SIMPLE | PyBUF_ANY_CONTIGUOUS) - if result != 0: - raise ValueError("Unable to retrieve Buffer from %s" % (memory,)) + if not __has_nc_open_mem__: + raise NetCDF4MissingFeatureException("nc_open_mem", "4.4.1") + + # Store reference to memory + result = PyObject_GetBuffer(memory, &self._buffer, PyBUF_SIMPLE | PyBUF_ANY_CONTIGUOUS) + if result != 0: + raise ValueError("Unable to retrieve Buffer from %s" % (memory,)) + + with nogil: + ierr = nc_open_mem(path, 0, self._buffer.len, self._buffer.buf, &grpid) - with nogil: - ierr = nc_open_mem(path, 0, self._buffer.len, self._buffer.buf, &grpid) - else: - msg = """ - nc_open_mem functionality not enabled. To enable, install Cython, make sure you have - version 4.4.1 or higher of the netcdf C lib, and rebuild netcdf4-python.""" - raise ValueError(msg) elif parallel: IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: cmode = NC_NOWRITE | NC_MPIIO @@ -2521,40 +2531,38 @@ strings. raise IndexError('%s not found in %s' % (lastname,group.path)) def filepath(self,encoding=None): + """**`filepath(self,encoding=None)`** + + Get the file system path (or the opendap URL) which was used to + open/create the Dataset. Requires netcdf >= 4.1.2. The path + is decoded into a string using `sys.getfilesystemencoding()` by default, this can be + changed using the `encoding` kwarg. """ -**`filepath(self,encoding=None)`** + if not __has_nc_inq_path__: + raise NetCDF4MissingFeatureException("filepath method", "4.1.2") -Get the file system path (or the opendap URL) which was used to -open/create the Dataset. Requires netcdf >= 4.1.2. The path -is decoded into a string using `sys.getfilesystemencoding()` by default, this can be -changed using the `encoding` kwarg.""" cdef int ierr cdef size_t pathlen cdef char *c_path if encoding is None: encoding = sys.getfilesystemencoding() - if __has_nc_inq_path__: + + with nogil: + ierr = nc_inq_path(self._grpid, &pathlen, NULL) + _ensure_nc_success(ierr) + + c_path = malloc(sizeof(char) * (pathlen + 1)) + if not c_path: + raise MemoryError() + try: with nogil: - ierr = nc_inq_path(self._grpid, &pathlen, NULL) + ierr = nc_inq_path(self._grpid, &pathlen, c_path) _ensure_nc_success(ierr) - c_path = malloc(sizeof(char) * (pathlen + 1)) - if not c_path: - raise MemoryError() - try: - with nogil: - ierr = nc_inq_path(self._grpid, &pathlen, c_path) - _ensure_nc_success(ierr) - - py_path = c_path[:pathlen] # makes a copy of pathlen bytes from c_string - finally: - free(c_path) - return py_path.decode(encoding) - else: - msg = """ -filepath method not enabled. To enable, install Cython, make sure you have -version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python.""" - raise ValueError(msg) + py_path = c_path[:pathlen] # makes a copy of pathlen bytes from c_string + finally: + free(c_path) + return py_path.decode(encoding) def __repr__(self): return self.__str__() @@ -2611,20 +2619,15 @@ version 4.1.2 or higher of the netcdf C lib, and rebuild netcdf4-python.""" # from a raw pointer without making a copy. return memview_fromptr(memio.memory, memio.size) - def close(self): - """ -**`close(self)`** + """**`close(self)`** -Close the Dataset. + Close the Dataset. """ - if __has_nc_create_mem__: - if self._inmemory: - return self._close_mem(True) - else: - self._close(True) - else: - self._close(True) + if __has_nc_create_mem__ and self._inmemory: + return self._close_mem(True) + + self._close(True) def isopen(self): """ @@ -3496,68 +3499,61 @@ to be installed and in `$PATH`. f = open(outfile,'w') f.write(result.stdout) f.close() + def has_blosc_filter(self): + """**`has_blosc_filter(self)`** + returns True if blosc compression filter is available """ -**`has_blosc_filter(self)`** -returns True if blosc compression filter is available""" - cdef int ierr if __has_blosc_support__: - with nogil: - ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_BLOSC) - if ierr: - return False - else: - return True - else: return False + + cdef int ierr + with nogil: + ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_BLOSC) + return ierr == 0 + def has_zstd_filter(self): + """**`has_zstd_filter(self)`** + returns True if zstd compression filter is available """ -**`has_zstd_filter(self)`** -returns True if zstd compression filter is available""" - cdef int ierr + if __has_zstandard_support__: - with nogil: - ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_ZSTD) - if ierr: - return False - else: - return True - else: return False + + cdef int ierr + with nogil: + ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_ZSTD) + return ierr == 0 + def has_bzip2_filter(self): + """**`has_bzip2_filter(self)`** + returns True if bzip2 compression filter is available """ -**`has_bzip2_filter(self)`** -returns True if bzip2 compression filter is available""" - cdef int ierr + if __has_bzip2_support__: - with nogil: - ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_BZIP2) - if ierr: - return False - else: - return True - else: return False + + cdef int ierr + with nogil: + ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_BZIP2) + return ierr == 0 + def has_szip_filter(self): + """**`has_szip_filter(self)`** + returns True if szip compression filter is available """ -**`has_szip_filter(self)`** -returns True if szip compression filter is available""" + + if not __has_ncfilter__: + return __has_szip_support__ + + if not __has_szip_support__: + return False + cdef int ierr - if __has_ncfilter__: - if __has_szip_support__: - with nogil: - ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_SZIP) - if ierr: - return False - else: - return True - else: - return False - else: - if __has_szip_support__: - return True - else: - return False + with nogil: + ierr = nc_inq_filter_avail(self._grpid, H5Z_FILTER_SZIP) + return ierr == 0 + cdef class Group(Dataset): """ @@ -4212,68 +4208,64 @@ behavior is similar to Fortran or Matlab, but different than numpy. if ierr != NC_NOERR: if grp.data_model != 'NETCDF4': grp._enddef() _ensure_nc_success(ierr, extra_msg=error_info) + if szip: - if __has_szip_support__: - try: - iszip_coding = _szip_dict[szip_coding] - except KeyError: - msg="unknown szip coding ('ec' or 'nn' supported)" - raise ValueError(msg) - iszip_pixels_per_block = szip_pixels_per_block - with nogil: - ierr = nc_def_var_szip(self._grpid, self._varid, iszip_coding, iszip_pixels_per_block) - if ierr != NC_NOERR: - if grp.data_model != 'NETCDF4': grp._enddef() - _ensure_nc_success(ierr, extra_msg=error_info) - else: - msg = """ -compression='szip' only works if linked version of hdf5 has szip functionality enabled""" - raise ValueError(msg) + if not __has_szip_support__: + raise ValueError("compression='szip' only works if linked version of hdf5 has szip functionality enabled") + try: + iszip_coding = _szip_dict[szip_coding] + except KeyError: + raise ValueError("unknown szip coding ('ec' or 'nn' supported)") + iszip_pixels_per_block = szip_pixels_per_block + with nogil: + ierr = nc_def_var_szip(self._grpid, self._varid, iszip_coding, iszip_pixels_per_block) + if ierr != NC_NOERR: + if grp.data_model != 'NETCDF4': + grp._enddef() + _ensure_nc_success(ierr, extra_msg=error_info) + if zstd: - if __has_zstandard_support__: - icomplevel = complevel - with nogil: - ierr = nc_def_var_zstandard(self._grpid, self._varid, icomplevel) - if ierr != NC_NOERR: - if grp.data_model != 'NETCDF4': grp._enddef() - _ensure_nc_success(ierr, extra_msg=error_info) - else: - msg = """ -compression='zstd' only works with netcdf-c >= 4.9.0. To enable, install Cython, make sure you have -version 4.9.0 or higher netcdf-c with zstandard support, and rebuild netcdf4-python.""" - raise ValueError(msg) + if not __has_zstandard_support__: + raise NetCDF4MissingFeatureException("compression='zstd'", "4.9.0") + + icomplevel = complevel + with nogil: + ierr = nc_def_var_zstandard(self._grpid, self._varid, icomplevel) + if ierr != NC_NOERR: + if grp.data_model != 'NETCDF4': + grp._enddef() + _ensure_nc_success(ierr, extra_msg=error_info) + if bzip2: - if __has_bzip2_support__: - icomplevel = complevel - with nogil: - ierr = nc_def_var_bzip2(self._grpid, self._varid, icomplevel) - if ierr != NC_NOERR: - if grp.data_model != 'NETCDF4': grp._enddef() - _ensure_nc_success(ierr, extra_msg=error_info) - else: - msg = """ -compression='bzip2' only works with netcdf-c >= 4.9.0. To enable, install Cython, make sure you have -version 4.9.0 or higher netcdf-c with bzip2 support, and rebuild netcdf4-python.""" - raise ValueError(msg) + if not __has_bzip2_support__: + raise NetCDF4MissingFeatureException("compression='bzip2'", "4.9.0") + + icomplevel = complevel + with nogil: + ierr = nc_def_var_bzip2(self._grpid, self._varid, icomplevel) + if ierr != NC_NOERR: + if grp.data_model != 'NETCDF4': + grp._enddef() + _ensure_nc_success(ierr, extra_msg=error_info) + if blosc_zstd or blosc_lz or blosc_lz4 or blosc_lz4hc or blosc_zlib: - if __has_blosc_support__: - iblosc_compressor = _blosc_dict[compression] - iblosc_shuffle = blosc_shuffle - iblosc_blocksize = 0 # not currently used by c lib - iblosc_complevel = complevel - with nogil: - ierr = nc_def_var_blosc(self._grpid, self._varid,\ - iblosc_compressor,\ - iblosc_complevel,iblosc_blocksize,\ - iblosc_shuffle) - if ierr != NC_NOERR: - if grp.data_model != 'NETCDF4': grp._enddef() - _ensure_nc_success(ierr, extra_msg=error_info) - else: - msg = """ -compression='blosc_*' only works with netcdf-c >= 4.9.0. To enable, install Cython, make sure you have -version 4.9.0 or higher netcdf-c with blosc support, and rebuild netcdf4-python.""" - raise ValueError(msg) + if not __has_blosc_support__: + raise NetCDF4MissingFeatureException("compression='blosc_*'", "4.9.0") + + iblosc_compressor = _blosc_dict[compression] + iblosc_shuffle = blosc_shuffle + iblosc_blocksize = 0 # not currently used by c lib + iblosc_complevel = complevel + with nogil: + ierr = nc_def_var_blosc(self._grpid, self._varid, + iblosc_compressor, + iblosc_complevel,iblosc_blocksize, + iblosc_shuffle) + if ierr != NC_NOERR: + if grp.data_model != 'NETCDF4': + grp._enddef() + _ensure_nc_success(ierr, extra_msg=error_info) + # set checksum. if fletcher32 and ndims: # don't bother for scalar variable with nogil: @@ -4320,31 +4312,32 @@ version 4.9.0 or higher netcdf-c with blosc support, and rebuild netcdf4-python. pass # this is the default format. else: raise ValueError("'endian' keyword argument must be 'little','big' or 'native', got '%s'" % endian) + # set quantization - if __has_quantization_support__: - if significant_digits is not None: - nsd = significant_digits - if quantize_mode == 'BitGroom': - with nogil: - ierr = nc_def_var_quantize(self._grpid, - self._varid, NC_QUANTIZE_BITGROOM, nsd) - elif quantize_mode == 'GranularBitRound': - with nogil: - ierr = nc_def_var_quantize(self._grpid, - self._varid, NC_QUANTIZE_GRANULARBR, nsd) - elif quantize_mode == 'BitRound': + if significant_digits is not None: + if not __has_quantization_support__: + raise ValueError( + "significant_digits kwarg only works with netcdf-c >= 4.9.0. " + "To enable, install Cython, make sure you have version 4.9.0 " + "or higher netcdf-c, and rebuild netcdf4-python. Otherwise, " + f"use least_significant_digit kwarg for quantization. {error_info}" + ) + + nsd = significant_digits + if quantize_mode == 'BitGroom': + with nogil: ierr = nc_def_var_quantize(self._grpid, - self._varid, NC_QUANTIZE_BITROUND, nsd) - else: - raise ValueError("'quantize_mode' keyword argument must be 'BitGroom','GranularBitRound' or 'BitRound', got '%s'" % quantize_mode) + self._varid, NC_QUANTIZE_BITGROOM, nsd) + elif quantize_mode == 'GranularBitRound': + with nogil: + ierr = nc_def_var_quantize(self._grpid, + self._varid, NC_QUANTIZE_GRANULARBR, nsd) + elif quantize_mode == 'BitRound': + ierr = nc_def_var_quantize(self._grpid, + self._varid, NC_QUANTIZE_BITROUND, nsd) + else: + raise ValueError("'quantize_mode' keyword argument must be 'BitGroom','GranularBitRound' or 'BitRound', got '%s'" % quantize_mode) - else: - if significant_digits is not None: - msg = f""" -significant_digits kwarg only works with netcdf-c >= 4.9.0. To enable, install Cython, make sure you have -version 4.9.0 or higher netcdf-c, and rebuild netcdf4-python. Otherwise, use least_significant_digit -kwarg for quantization. {error_info}""" - raise ValueError(msg) if ierr != NC_NOERR: if grp.data_model != 'NETCDF4': grp._enddef() _ensure_nc_success(ierr, extra_msg=error_info) From f64ee26773502c7568b1ceefe5967f83230f207c Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Wed, 27 Sep 2023 18:05:04 +0100 Subject: [PATCH 1019/1504] Add shims for parallel functions --- include/netCDF4.pxi | 29 +++--- include/netcdf-compat.h | 14 +++ src/netCDF4/_netCDF4.pyx | 193 +++++++++++++++------------------------ 3 files changed, 101 insertions(+), 135 deletions(-) diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi index 9dc5d11f9..ed00ef0f9 100644 --- a/include/netCDF4.pxi +++ b/include/netCDF4.pxi @@ -368,20 +368,7 @@ cdef extern from "netcdf.h": IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: cdef extern from "mpi-compat.h": pass - cdef extern from "netcdf_par.h": - ctypedef int MPI_Comm - ctypedef int MPI_Info - int nc_create_par(char *path, int cmode, MPI_Comm comm, MPI_Info info, int *ncidp) nogil - int nc_open_par(char *path, int mode, MPI_Comm comm, MPI_Info info, int *ncidp) nogil - int nc_var_par_access(int ncid, int varid, int par_access) nogil - cdef enum: - NC_COLLECTIVE - NC_INDEPENDENT - cdef extern from "netcdf.h": - cdef enum: - NC_MPIIO - NC_MPIPOSIX - NC_PNETCDF + # taken from numpy.pxi in numpy 1.0rc2. cdef extern from "numpy/arrayobject.h": @@ -436,6 +423,13 @@ cdef extern from "netcdf-compat.h": unsigned* levelp, unsigned* blocksizep, unsigned* addshufflep) nogil + # Parallel shims + ctypedef int MPI_Comm + ctypedef int MPI_Info + int nc_create_par(char *path, int cmode, MPI_Comm comm, MPI_Info info, int *ncidp) nogil + int nc_open_par(char *path, int mode, MPI_Comm comm, MPI_Info info, int *ncidp) nogil + int nc_var_par_access(int ncid, int varid, int par_access) nogil + cdef enum: HAS_RENAME_GRP HAS_NC_INQ_PATH @@ -464,3 +458,10 @@ cdef extern from "netcdf-compat.h": H5Z_FILTER_ZSTD H5Z_FILTER_BZIP2 H5Z_FILTER_BLOSC + + NC_COLLECTIVE + NC_INDEPENDENT + + NC_MPIIO + NC_MPIPOSIX + NC_PNETCDF diff --git a/include/netcdf-compat.h b/include/netcdf-compat.h index e961c1163..ae2cd0948 100644 --- a/include/netcdf-compat.h +++ b/include/netcdf-compat.h @@ -96,6 +96,20 @@ static inline int nc_close_memio(int ncid, NC_memio* info) { return NC_EINVAL; } #define HAS_PARALLEL_SUPPORT 1 #else #define HAS_PARALLEL_SUPPORT 0 +typedef int MPI_Comm; +typedef int MPI_Info; +static inline int nc_create_par(const char *path, int cmode, MPI_Comm comm, MPI_Info info, int *ncidp) { return NC_EINVAL; } +static inline int nc_open_par(const char *path, int mode, MPI_Comm comm, MPI_Info info, int *ncidp) { return NC_EINVAL; } +static inline int nc_var_par_access(int ncid, int varid, int par_access) { return NC_EINVAL; } +# ifndef NC_INDEPENDENT +# define NC_INDEPENDENT 0 +# define NC_COLLECTIVE 1 +# endif +# ifndef NC_MPIIO +# define NC_MPIIO 0x2000 +# define NC_MPIPOSIX NC_MPIIO +# define NC_PNETCDF (NC_MPIIO) +# endif #endif #if defined(NC_HAS_PARALLEL4) && NC_HAS_PARALLEL4 diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index e459ee63c..3d9d9063d 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1256,6 +1256,7 @@ __has_nc_open_mem__ = HAS_NC_OPEN_MEM __has_nc_create_mem__ = HAS_NC_CREATE_MEM __has_parallel4_support__ = HAS_PARALLEL4_SUPPORT __has_pnetcdf_support__ = HAS_PNETCDF_SUPPORT +__has_parallel_support__ = HAS_PARALLEL_SUPPORT __has_quantization_support__ = HAS_QUANTIZATION_SUPPORT __has_zstandard_support__ = HAS_ZSTANDARD_SUPPORT __has_bzip2_support__ = HAS_BZIP2_SUPPORT @@ -1273,8 +1274,12 @@ IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: ctypedef MPI.Comm Comm ctypedef MPI.Info Info ELSE: - ctypedef object Comm - ctypedef object Info + ctypedef int Comm + ctypedef int Info + cdef Comm MPI_COMM_WORLD + cdef Info MPI_INFO_NULL + MPI_COMM_WORLD = 0 + MPI_INFO_NULL = 0 # set path to SSL certificates (issue #1246) # available starting in version 4.9.1 @@ -2137,7 +2142,7 @@ strings. def __init__(self, filename, mode='r', clobber=True, format='NETCDF4', diskless=False, persist=False, keepweakref=False, memory=None, encoding=None, parallel=False, - Comm comm=None, Info info=None, **kwargs): + comm=None, info=None, **kwargs): """ **`__init__(self, filename, mode="r", clobber=True, diskless=False, persist=False, keepweakref=False, memory=None, encoding=None, @@ -2238,9 +2243,8 @@ strings. cdef char *path cdef char namstring[NC_MAX_NAME+1] cdef int cmode, parmode - IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: - cdef MPI_Comm mpicomm - cdef MPI_Info mpiinfo + cdef MPI_Comm mpicomm + cdef MPI_Info mpiinfo memset(&self._buffer, 0, sizeof(self._buffer)) @@ -2261,30 +2265,29 @@ strings. raise ValueError(msg) if parallel: - IF HAS_PARALLEL4_SUPPORT != 1 and HAS_PNETCDF_SUPPORT != 1: - msg='parallel mode requires MPI enabled netcdf-c' + if not __has_parallel_support__: + raise ValueError("parallel mode requires MPI enabled netcdf-c") + + parallel_formats = [] + if __has_parallel4_support__: + parallel_formats += ['NETCDF4','NETCDF4_CLASSIC'] + if __has_pnetcdf_support__: + parallel_formats += ['NETCDF3_CLASSIC', + 'NETCDF3_64BIT_OFFSET', + 'NETCDF3_64BIT_DATA', + 'NETCDF3_64BIT'] + if format not in parallel_formats: + msg='parallel mode only works with the following formats: ' + ' '.join(parallel_formats) raise ValueError(msg) - ELSE: - parallel_formats = [] - if __has_parallel4_support__: - parallel_formats += ['NETCDF4','NETCDF4_CLASSIC'] - if __has_pnetcdf_support__: - parallel_formats += ['NETCDF3_CLASSIC', - 'NETCDF3_64BIT_OFFSET', - 'NETCDF3_64BIT_DATA', - 'NETCDF3_64BIT'] - if format not in parallel_formats: - msg='parallel mode only works with the following formats: ' + ' '.join(parallel_formats) - raise ValueError(msg) - if comm is not None: - mpicomm = comm.ob_mpi - else: - mpicomm = MPI_COMM_WORLD - if info is not None: - mpiinfo = info.ob_mpi - else: - mpiinfo = MPI_INFO_NULL - parmode = NC_MPIIO | _cmode_dict[format] + if comm is not None: + mpicomm = comm.ob_mpi + else: + mpicomm = MPI_COMM_WORLD + if info is not None: + mpiinfo = info.ob_mpi + else: + mpiinfo = MPI_INFO_NULL + parmode = NC_MPIIO | _cmode_dict[format] self._inmemory = False @@ -2306,48 +2309,21 @@ strings. self._inmemory = True # checked in close method else: - if clobber: - if parallel: - IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: - cmode = NC_CLOBBER | parmode - with nogil: - ierr = nc_create_par(path, cmode, \ - mpicomm, mpiinfo, &grpid) - ELSE: - pass - elif diskless: - if persist: - cmode = NC_WRITE | NC_CLOBBER | NC_DISKLESS | NC_PERSIST - with nogil: - ierr = nc_create(path, cmode, &grpid) - else: - cmode = NC_CLOBBER | NC_DISKLESS - with nogil: - ierr = nc_create(path, cmode , &grpid) - else: - with nogil: - ierr = nc_create(path, NC_CLOBBER, &grpid) + cmode = NC_CLOBBER if clobber else NC_NOCLOBBER + + if parallel: + cmode |= parmode + with nogil: + ierr = nc_create_par(path, cmode, mpicomm, mpiinfo, &grpid) else: - if parallel: - IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: - cmode = NC_NOCLOBBER | parmode - with nogil: - ierr = nc_create_par(path, cmode, \ - mpicomm, mpiinfo, &grpid) - ELSE: - pass - elif diskless: + if diskless: + cmode |= NC_DISKLESS if persist: - cmode = NC_WRITE | NC_NOCLOBBER | NC_DISKLESS | NC_PERSIST - with nogil: - ierr = nc_create(path, cmode, &grpid) - else: - cmode = NC_NOCLOBBER | NC_DISKLESS - with nogil: - ierr = nc_create(path, cmode , &grpid) - else: - with nogil: - ierr = nc_create(path, NC_NOCLOBBER, &grpid) + cmode |= NC_WRITE | NC_PERSIST + + with nogil: + ierr = nc_create(path, cmode, &grpid) + # reset default format to netcdf3 - this is a workaround # for issue 170 (nc_open'ing a DAP dataset after switching # format to NETCDF4). This bug should be fixed in version @@ -2369,13 +2345,9 @@ strings. ierr = nc_open_mem(path, 0, self._buffer.len, self._buffer.buf, &grpid) elif parallel: - IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: - cmode = NC_NOWRITE | NC_MPIIO - with nogil: - ierr = nc_open_par(path, cmode, \ - mpicomm, mpiinfo, &grpid) - ELSE: - pass + cmode = NC_NOWRITE | NC_MPIIO + with nogil: + ierr = nc_open_par(path, cmode, mpicomm, mpiinfo, &grpid) elif diskless: cmode = NC_NOWRITE | NC_DISKLESS with nogil: @@ -2393,13 +2365,9 @@ strings. ierr = nc_open(path, NC_NOWRITE, &grpid) elif mode in ['a','r+'] and os.path.exists(filename): if parallel: - IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: - cmode = NC_WRITE | NC_MPIIO - with nogil: - ierr = nc_open_par(path, cmode, \ - mpicomm, mpiinfo, &grpid) - ELSE: - pass + cmode = NC_WRITE | NC_MPIIO + with nogil: + ierr = nc_open_par(path, cmode, mpicomm, mpiinfo, &grpid) elif diskless: cmode = NC_WRITE | NC_DISKLESS with nogil: @@ -2410,13 +2378,9 @@ strings. elif mode in ['as','r+s'] and os.path.exists(filename): if parallel: # NC_SHARE ignored - IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: - cmode = NC_WRITE | NC_MPIIO - with nogil: - ierr = nc_open_par(path, cmode, \ - mpicomm, mpiinfo, &grpid) - ELSE: - pass + cmode = NC_WRITE | NC_MPIIO + with nogil: + ierr = nc_open_par(path, cmode, mpicomm, mpiinfo, &grpid) elif diskless: cmode = NC_SHARE | NC_DISKLESS with nogil: @@ -2429,13 +2393,9 @@ strings. if clobber: if parallel: # NC_SHARE ignored - IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: - cmode = NC_CLOBBER | parmode - with nogil: - ierr = nc_create_par(path, NC_CLOBBER | cmode, \ - mpicomm, mpiinfo, &grpid) - ELSE: - pass + cmode = NC_CLOBBER | parmode + with nogil: + ierr = nc_create_par(path, NC_CLOBBER | cmode, mpicomm, mpiinfo, &grpid) elif diskless: if persist: cmode = NC_WRITE | NC_SHARE | NC_CLOBBER | NC_DISKLESS @@ -2452,13 +2412,9 @@ strings. else: if parallel: # NC_SHARE ignored - IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: - cmode = NC_NOCLOBBER | parmode - with nogil: - ierr = nc_create_par(path, cmode, \ - mpicomm, mpiinfo, &grpid) - ELSE: - pass + cmode = NC_NOCLOBBER | parmode + with nogil: + ierr = nc_create_par(path, cmode, mpicomm, mpiinfo, &grpid) elif diskless: if persist: cmode = NC_WRITE | NC_SHARE | NC_NOCLOBBER | NC_DISKLESS @@ -6018,25 +5974,20 @@ NC_CHAR). return data def set_collective(self, value): - """ -**`set_collective(self,True_or_False)`** + """**`set_collective(self,True_or_False)`** -turn on or off collective parallel IO access. Ignored if file is not -open for parallel access. + turn on or off collective parallel IO access. Ignored if file is not + open for parallel access. """ - IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: - # set collective MPI IO mode on or off - if value: - with nogil: - ierr = nc_var_par_access(self._grpid, self._varid, - NC_COLLECTIVE) - else: - with nogil: - ierr = nc_var_par_access(self._grpid, self._varid, - NC_INDEPENDENT) - _ensure_nc_success(ierr) - ELSE: - pass # does nothing + if not __has_parallel_support__: + return + + mode = NC_COLLECTIVE if value else NC_INDEPENDENT + with nogil: + ierr = nc_var_par_access(self._grpid, self._varid, + NC_COLLECTIVE) + _ensure_nc_success(ierr) + def get_dims(self): """ From 4a39d7d66479b371924020fe513c7c6d64cf09ed Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Fri, 29 Sep 2023 09:27:45 +0100 Subject: [PATCH 1020/1504] Remove unneeded API checking in setup.py --- setup.py | 91 ++++---------------------------------------------------- 1 file changed, 6 insertions(+), 85 deletions(-) diff --git a/setup.py b/setup.py index a03fe58ed..efb3355cd 100644 --- a/setup.py +++ b/setup.py @@ -43,82 +43,16 @@ def check_ifnetcdf4(netcdf4_includedir): isnetcdf4 = True return isnetcdf4 -def check_api(inc_dirs,netcdf_lib_version): - has_rename_grp = False - has_nc_inq_path = False - has_nc_inq_format_extended = False - has_cdf5_format = False - has_nc_open_mem = False - has_nc_create_mem = False + +def check_api(inc_dirs, netcdf_lib_version): has_parallel_support = False has_parallel4_support = False has_pnetcdf_support = False - has_szip_support = False - has_quantize = False - has_zstandard = False - has_bzip2 = False - has_blosc = False - has_ncfilter = False - has_set_alignment = False - has_nc_rc_set = False for d in inc_dirs: - try: - f = open(os.path.join(d, 'netcdf.h'), **open_kwargs) - except OSError: - continue - - has_nc_open_mem = os.path.exists(os.path.join(d, 'netcdf_mem.h')) - has_nc_filter = os.path.exists(os.path.join(d, 'netcdf_filter.h')) - - for line in f: - if line.startswith('nc_rename_grp'): - has_rename_grp = True - if line.startswith('nc_inq_path'): - has_nc_inq_path = True - if line.startswith('nc_inq_format_extended'): - has_nc_inq_format_extended = True - if line.startswith('#define NC_FORMAT_64BIT_DATA'): - has_cdf5_format = True - if line.startswith('nc_def_var_quantize'): - has_quantize = True - if line.startswith('nc_set_alignment'): - has_set_alignment = True - if line.startswith('EXTERNL int nc_rc_set'): - has_nc_rc_set = True - - if has_nc_open_mem: - try: - f = open(os.path.join(d, 'netcdf_mem.h'), **open_kwargs) - except OSError: - continue - for line in f: - if line.startswith('EXTERNL int nc_create_mem'): - has_nc_create_mem = True - - if has_nc_filter: - try: - f = open(os.path.join(d, 'netcdf_filter.h'), **open_kwargs) - except OSError: - continue - for line in f: - if line.startswith('EXTERNL int nc_def_var_zstandard'): - has_zstandard = True - if line.startswith('EXTERNL int nc_def_var_bzip2'): - has_bzip2 = True - if line.startswith('EXTERNL int nc_def_var_blosc'): - has_blosc = True - if line.startswith('EXTERNL int nc_inq_filter_avail'): - has_ncfilter = True - ncmetapath = os.path.join(d,'netcdf_meta.h') if os.path.exists(ncmetapath): for line in open(ncmetapath): - if line.startswith('#define NC_HAS_CDF5'): - try: - has_cdf5_format = bool(int(line.split()[2])) - except ValueError: - pass # keep default False if value cannot be parsed if line.startswith('#define NC_HAS_PARALLEL'): try: has_parallel_support = bool(int(line.split()[2])) @@ -134,11 +68,6 @@ def check_api(inc_dirs,netcdf_lib_version): has_pnetcdf_support = bool(int(line.split()[2])) except ValueError: pass - if line.startswith('#define NC_HAS_SZIP_WRITE'): - try: - has_szip_support = bool(int(line.split()[2])) - except ValueError: - pass # NC_HAS_PARALLEL4 missing in 4.6.1 (issue #964) if not has_parallel4_support and has_parallel_support and not has_pnetcdf_support: @@ -148,13 +77,8 @@ def check_api(inc_dirs,netcdf_lib_version): # NC_HAS_PARALLEL4) elif netcdf_lib_version == "4.6.1" and not has_parallel4_support and has_parallel_support: has_parallel4_support = True - break - return has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \ - has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \ - has_parallel4_support, has_pnetcdf_support, has_szip_support, has_quantize, \ - has_zstandard, has_bzip2, has_blosc, has_set_alignment, has_ncfilter, \ - has_nc_rc_set + return has_parallel4_support, has_pnetcdf_support def getnetcdfvers(libdirs): @@ -564,12 +488,9 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): if len(sys.argv) >= 2: if os.path.exists(netcdf4_src_c): os.remove(netcdf4_src_c) - # this determines whether renameGroup and filepath methods will work. - has_rename_grp, has_nc_inq_path, has_nc_inq_format_extended, \ - has_cdf5_format, has_nc_open_mem, has_nc_create_mem, \ - has_parallel4_support, has_pnetcdf_support, has_szip_support, has_quantize, \ - has_zstandard, has_bzip2, has_blosc, has_set_alignment, has_ncfilter, has_nc_rc_set = \ - check_api(inc_dirs,netcdf_lib_version) + + has_parallel4_support, has_pnetcdf_support = check_api(inc_dirs, netcdf_lib_version) + # for netcdf 4.4.x CDF5 format is always enabled. if netcdf_lib_version is not None and\ (netcdf_lib_version > "4.4" and netcdf_lib_version < "4.5"): From f1e697b56188c8f7657fb2c3ec944d7e5fd89a30 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Fri, 29 Sep 2023 10:23:37 +0100 Subject: [PATCH 1021/1504] Simplify checking for parallel support a little We only need to know if we have any parallel support at compile time, and not whether it's netcdf4 or pnetcdf flavour --- include/netCDF4.pxi | 2 +- setup.py | 53 +++++++++------------------------------- src/netCDF4/_netCDF4.pyx | 2 +- 3 files changed, 14 insertions(+), 43 deletions(-) diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi index ed00ef0f9..527ab492c 100644 --- a/include/netCDF4.pxi +++ b/include/netCDF4.pxi @@ -366,7 +366,7 @@ cdef extern from "netcdf.h": int nc_inq_enum_ident(int ncid, nc_type xtype, long long value, char *identifier) nogil -IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: +IF HAS_PARALLEL_SUPPORT: cdef extern from "mpi-compat.h": pass diff --git a/setup.py b/setup.py index efb3355cd..bea9581a4 100644 --- a/setup.py +++ b/setup.py @@ -44,41 +44,23 @@ def check_ifnetcdf4(netcdf4_includedir): return isnetcdf4 -def check_api(inc_dirs, netcdf_lib_version): +def check_has_parallel_support(inc_dirs: list) -> bool: has_parallel_support = False - has_parallel4_support = False - has_pnetcdf_support = False for d in inc_dirs: ncmetapath = os.path.join(d,'netcdf_meta.h') - if os.path.exists(ncmetapath): - for line in open(ncmetapath): + if not os.path.exists(ncmetapath): + continue + + with open(ncmetapath) as f: + for line in f: if line.startswith('#define NC_HAS_PARALLEL'): try: has_parallel_support = bool(int(line.split()[2])) except ValueError: pass - if line.startswith('#define NC_HAS_PARALLEL4'): - try: - has_parallel4_support = bool(int(line.split()[2])) - except ValueError: - pass - if line.startswith('#define NC_HAS_PNETCDF'): - try: - has_pnetcdf_support = bool(int(line.split()[2])) - except ValueError: - pass - - # NC_HAS_PARALLEL4 missing in 4.6.1 (issue #964) - if not has_parallel4_support and has_parallel_support and not has_pnetcdf_support: - has_parallel4_support = True - # for 4.6.1, if NC_HAS_PARALLEL=NC_HAS_PNETCDF=1, guess that - # parallel HDF5 is enabled (must guess since there is no - # NC_HAS_PARALLEL4) - elif netcdf_lib_version == "4.6.1" and not has_parallel4_support and has_parallel_support: - has_parallel4_support = True - return has_parallel4_support, has_pnetcdf_support + return has_parallel_support def getnetcdfvers(libdirs): @@ -489,29 +471,18 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): if os.path.exists(netcdf4_src_c): os.remove(netcdf4_src_c) - has_parallel4_support, has_pnetcdf_support = check_api(inc_dirs, netcdf_lib_version) - # for netcdf 4.4.x CDF5 format is always enabled. if netcdf_lib_version is not None and\ (netcdf_lib_version > "4.4" and netcdf_lib_version < "4.5"): has_cdf5_format = True with open(osp.join('include', 'constants.pyx'), 'w') as f: - if has_parallel4_support: - sys.stdout.write('netcdf lib has netcdf4 parallel functions\n') - f.write('DEF HAS_PARALLEL4_SUPPORT = 1\n') - else: - sys.stdout.write('netcdf lib does not have netcdf4 parallel functions\n') - f.write('DEF HAS_PARALLEL4_SUPPORT = 0\n') - - if has_pnetcdf_support: - sys.stdout.write('netcdf lib has pnetcdf parallel functions\n') - f.write('DEF HAS_PNETCDF_SUPPORT = 1\n') - else: - sys.stdout.write('netcdf lib does not have pnetcdf parallel functions\n') - f.write('DEF HAS_PNETCDF_SUPPORT = 0\n') + has_parallel_support = check_has_parallel_support(inc_dirs) + has_has_not = "has" if has_parallel_support else "does not have" + sys.stdout.write(f"netcdf lib {has_has_not} parallel functions\n") + f.write(f'DEF HAS_PARALLEL_SUPPORT = {int(has_parallel_support)}\n') - if has_parallel4_support or has_pnetcdf_support: + if has_parallel_support: import mpi4py inc_dirs.append(mpi4py.get_include()) # mpi_incdir should not be needed if using nc-config diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 3d9d9063d..da7452ed3 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1266,7 +1266,7 @@ __has_set_alignment__ = HAS_SET_ALIGNMENT __has_ncfilter__ = HAS_NCFILTER -IF HAS_PARALLEL4_SUPPORT or HAS_PNETCDF_SUPPORT: +IF HAS_PARALLEL_SUPPORT: cimport mpi4py.MPI as MPI from mpi4py.libmpi cimport MPI_Comm, MPI_Info, MPI_Comm_dup, MPI_Info_dup, \ MPI_Comm_free, MPI_Info_free, MPI_INFO_NULL,\ From b0a030f277ceee7a4e8e99ac50bfba0d11b1af7f Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Fri, 29 Sep 2023 10:28:06 +0100 Subject: [PATCH 1022/1504] Enable mpi-compat.h to always be included --- include/mpi-compat.h | 6 ++++++ include/netCDF4.pxi | 4 ++-- include/netcdf-compat.h | 5 +++++ 3 files changed, 13 insertions(+), 2 deletions(-) diff --git a/include/mpi-compat.h b/include/mpi-compat.h index 9a604f851..5563ae933 100644 --- a/include/mpi-compat.h +++ b/include/mpi-compat.h @@ -4,6 +4,10 @@ #ifndef MPI_COMPAT_H #define MPI_COMPAT_H +#include "netcdf-compat.h" + +#if HAS_PARALLEL_SUPPORT + #include #if (MPI_VERSION < 3) && !defined(PyMPI_HAVE_MPI_Message) @@ -16,4 +20,6 @@ typedef void *PyMPI_MPI_Session; #define MPI_Session PyMPI_MPI_Session #endif +#endif /* HAS_PARALLEL_SUPPORT */ + #endif/*MPI_COMPAT_H*/ diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi index 527ab492c..80fff7e4d 100644 --- a/include/netCDF4.pxi +++ b/include/netCDF4.pxi @@ -366,8 +366,8 @@ cdef extern from "netcdf.h": int nc_inq_enum_ident(int ncid, nc_type xtype, long long value, char *identifier) nogil -IF HAS_PARALLEL_SUPPORT: - cdef extern from "mpi-compat.h": pass +cdef extern from "mpi-compat.h": + pass # taken from numpy.pxi in numpy 1.0rc2. diff --git a/include/netcdf-compat.h b/include/netcdf-compat.h index ae2cd0948..eedabb1e7 100644 --- a/include/netcdf-compat.h +++ b/include/netcdf-compat.h @@ -1,3 +1,6 @@ +#ifndef NETCDF_COMPAT_H +#define NETCDF_COMPAT_H + #include #include @@ -192,3 +195,5 @@ static inline int nc_inq_var_blosc(int ncid, int varid, int* hasfilterp, unsigne # endif #define HAS_BLOSC_SUPPORT 0 #endif + +#endif /* NETCDF_COMPAT_H */ From 2578063fe2222e40d87027f6b24fc7ffa55b03d5 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Fri, 29 Sep 2023 10:52:02 +0100 Subject: [PATCH 1023/1504] Move compile-time conditional import of parallel modules to code-gen To avoid the last deprecated compile-time `IF`, we instead separate the two branches of the conditional into different files and choose which one to include at build time. --- .gitignore | 1 + include/no_parallel_support_imports.pxi.in | 8 ++++++++ include/parallel_support_imports.pxi.in | 16 ++++++++++++++++ setup.py | 15 ++++++++++++++- src/netCDF4/_netCDF4.pyx | 17 +---------------- 5 files changed, 40 insertions(+), 17 deletions(-) create mode 100644 include/no_parallel_support_imports.pxi.in create mode 100644 include/parallel_support_imports.pxi.in diff --git a/.gitignore b/.gitignore index 11d620216..a808b3552 100644 --- a/.gitignore +++ b/.gitignore @@ -5,6 +5,7 @@ dist/ netCDF4/_netCDF4.c netCDF4/*.so include/constants.pyx +include/parallel_support_imports.pxi netcdftime/_netcdftime.c venv/ .eggs/ diff --git a/include/no_parallel_support_imports.pxi.in b/include/no_parallel_support_imports.pxi.in new file mode 100644 index 000000000..e64ba6c5a --- /dev/null +++ b/include/no_parallel_support_imports.pxi.in @@ -0,0 +1,8 @@ +# Stubs for when parallel support is not enabled + +ctypedef int Comm +ctypedef int Info +cdef Comm MPI_COMM_WORLD +cdef Info MPI_INFO_NULL +MPI_COMM_WORLD = 0 +MPI_INFO_NULL = 0 diff --git a/include/parallel_support_imports.pxi.in b/include/parallel_support_imports.pxi.in new file mode 100644 index 000000000..5379bedc4 --- /dev/null +++ b/include/parallel_support_imports.pxi.in @@ -0,0 +1,16 @@ +# Imports and typedefs required at compile time for enabling parallel support + +cimport mpi4py.MPI as MPI +from mpi4py.libmpi cimport ( + MPI_Comm, + MPI_Info, + MPI_Comm_dup, + MPI_Info_dup, + MPI_Comm_free, + MPI_Info_free, + MPI_INFO_NULL, + MPI_COMM_WORLD, +) + +ctypedef MPI.Comm Comm +ctypedef MPI.Info Info diff --git a/setup.py b/setup.py index bea9581a4..6d7787b50 100644 --- a/setup.py +++ b/setup.py @@ -487,7 +487,20 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): inc_dirs.append(mpi4py.get_include()) # mpi_incdir should not be needed if using nc-config # (should be included in nc-config --cflags) - if mpi_incdir is not None: inc_dirs.append(mpi_incdir) + if mpi_incdir is not None: + inc_dirs.append(mpi_incdir) + + # Name of file containing imports required for parallel support + parallel_support_imports = "parallel_support_imports.pxi.in" + else: + parallel_support_imports = "no_parallel_support_imports.pxi.in" + + # Copy the specific version of the file containing parallel + # support imports + shutil.copyfile( + osp.join("include", parallel_support_imports), + osp.join("include", "parallel_support_imports.pxi") + ) ext_modules = [Extension("netCDF4._netCDF4", [netcdf4_src_pyx], diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index da7452ed3..70036267d 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1244,7 +1244,7 @@ from numpy import ma from libc.string cimport memcpy, memset from libc.stdlib cimport malloc, free numpy.import_array() -include "constants.pyx" +include "parallel_support_imports.pxi" include "membuf.pyx" include "netCDF4.pxi" @@ -1266,21 +1266,6 @@ __has_set_alignment__ = HAS_SET_ALIGNMENT __has_ncfilter__ = HAS_NCFILTER -IF HAS_PARALLEL_SUPPORT: - cimport mpi4py.MPI as MPI - from mpi4py.libmpi cimport MPI_Comm, MPI_Info, MPI_Comm_dup, MPI_Info_dup, \ - MPI_Comm_free, MPI_Info_free, MPI_INFO_NULL,\ - MPI_COMM_WORLD - ctypedef MPI.Comm Comm - ctypedef MPI.Info Info -ELSE: - ctypedef int Comm - ctypedef int Info - cdef Comm MPI_COMM_WORLD - cdef Info MPI_INFO_NULL - MPI_COMM_WORLD = 0 - MPI_INFO_NULL = 0 - # set path to SSL certificates (issue #1246) # available starting in version 4.9.1 if HAS_NCRCSET: From c2dd8cfcf10bc8dffb311569479b5ceef84f1da2 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Fri, 29 Sep 2023 12:03:34 +0100 Subject: [PATCH 1024/1504] Fix names of feature macros --- include/netcdf-compat.h | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/include/netcdf-compat.h b/include/netcdf-compat.h index eedabb1e7..89f9207a8 100644 --- a/include/netcdf-compat.h +++ b/include/netcdf-compat.h @@ -139,9 +139,11 @@ static inline int nc_inq_filter_avail(int ncid, unsigned filterid) { return -136 #define HAS_SZIP_SUPPORT 1 #else #define HAS_SZIP_SUPPORT 0 +# ifndef NC_HAS_SZIP static inline int nc_def_var_szip(int ncid, int varid, int options_mask, int pixels_per_bloc) { return NC_EINVAL; } +# endif # ifndef H5Z_FILTER_SZIP -# define H5Z_FILTER_SZIP 4 +# define H5Z_FILTER_SZIP 4 # endif #endif @@ -159,10 +161,10 @@ static inline int nc_inq_var_quantize(int ncid, int varid, int *quantize_modep, # endif #endif -#if defined(NC_HAS_ZSTANDARD) && NC_HAS_ZSTANDARD +#if defined(NC_HAS_ZSTD) && NC_HAS_ZSTD #define HAS_ZSTANDARD_SUPPORT 1 #else -# ifndef NC_HAS_ZSTANDARD +# ifndef NC_HAS_ZSTD static inline int nc_def_var_zstandard(int ncid, int varid, int level) { return NC_EINVAL; } static inline int nc_inq_var_zstandard(int ncid, int varid, int* hasfilterp, int *levelp) { return NC_EINVAL; } # define H5Z_FILTER_ZSTD 32015 @@ -170,10 +172,10 @@ static inline int nc_inq_var_zstandard(int ncid, int varid, int* hasfilterp, int #define HAS_ZSTANDARD_SUPPORT 0 #endif -#if defined(NC_HAS_BZIP2) && NC_HAS_BZIP2 +#if defined(NC_HAS_BZ2) && NC_HAS_BZ2 #define HAS_BZIP2_SUPPORT 1 #else -# ifndef NC_HAS_BZIP2 +# ifndef NC_HAS_BZ2 static inline int nc_def_var_bzip2(int ncid, int varid, int level) { return NC_EINVAL; } static inline int nc_inq_var_bzip2(int ncid, int varid, int* hasfilterp, int *levelp) { return NC_EINVAL; } # define H5Z_FILTER_BZIP2 307 From f9e7d11ba0578e02053677acb0495e30f6c6b0a4 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Fri, 29 Sep 2023 14:57:01 +0100 Subject: [PATCH 1025/1504] Fix missing include of `netcdf_par.h` --- include/netcdf-compat.h | 1 + 1 file changed, 1 insertion(+) diff --git a/include/netcdf-compat.h b/include/netcdf-compat.h index 89f9207a8..3ab3c4453 100644 --- a/include/netcdf-compat.h +++ b/include/netcdf-compat.h @@ -96,6 +96,7 @@ static inline int nc_close_memio(int ncid, NC_memio* info) { return NC_EINVAL; } #endif #if defined(NC_HAS_PARALLEL) && NC_HAS_PARALLEL +#include #define HAS_PARALLEL_SUPPORT 1 #else #define HAS_PARALLEL_SUPPORT 0 From a83f81bc95ffce6a98320203b17dc6d67986e0bd Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Fri, 29 Sep 2023 15:21:27 +0100 Subject: [PATCH 1026/1504] Move parallel support imports to .pxi so shims get correct type We also need to explicitly cast the comm/info arguments to the correct type --- include/netCDF4.pxi | 4 ++-- include/no_parallel_support_imports.pxi.in | 6 ++++-- src/netCDF4/_netCDF4.pyx | 5 ++--- 3 files changed, 8 insertions(+), 7 deletions(-) diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi index 80fff7e4d..7bd220274 100644 --- a/include/netCDF4.pxi +++ b/include/netCDF4.pxi @@ -384,6 +384,8 @@ cdef extern from "numpy/arrayobject.h": void import_array() +include "parallel_support_imports.pxi" + # Compatibility shims cdef extern from "netcdf-compat.h": int nc_rename_grp(int grpid, char *name) nogil @@ -424,8 +426,6 @@ cdef extern from "netcdf-compat.h": unsigned* addshufflep) nogil # Parallel shims - ctypedef int MPI_Comm - ctypedef int MPI_Info int nc_create_par(char *path, int cmode, MPI_Comm comm, MPI_Info info, int *ncidp) nogil int nc_open_par(char *path, int mode, MPI_Comm comm, MPI_Info info, int *ncidp) nogil int nc_var_par_access(int ncid, int varid, int par_access) nogil diff --git a/include/no_parallel_support_imports.pxi.in b/include/no_parallel_support_imports.pxi.in index e64ba6c5a..dd22f1968 100644 --- a/include/no_parallel_support_imports.pxi.in +++ b/include/no_parallel_support_imports.pxi.in @@ -1,8 +1,10 @@ # Stubs for when parallel support is not enabled +ctypedef int MPI_Comm +ctypedef int MPI_Info ctypedef int Comm ctypedef int Info -cdef Comm MPI_COMM_WORLD -cdef Info MPI_INFO_NULL +cdef MPI_Comm MPI_COMM_WORLD +cdef MPI_Info MPI_INFO_NULL MPI_COMM_WORLD = 0 MPI_INFO_NULL = 0 diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 70036267d..9cd40ec47 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1244,7 +1244,6 @@ from numpy import ma from libc.string cimport memcpy, memset from libc.stdlib cimport malloc, free numpy.import_array() -include "parallel_support_imports.pxi" include "membuf.pyx" include "netCDF4.pxi" @@ -2265,11 +2264,11 @@ strings. msg='parallel mode only works with the following formats: ' + ' '.join(parallel_formats) raise ValueError(msg) if comm is not None: - mpicomm = comm.ob_mpi + mpicomm = (comm).ob_mpi else: mpicomm = MPI_COMM_WORLD if info is not None: - mpiinfo = info.ob_mpi + mpiinfo = (info).ob_mpi else: mpiinfo = MPI_INFO_NULL parmode = NC_MPIIO | _cmode_dict[format] From 3a8bd6878f96d8a6bfe1dd8f4802d540fc732a72 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Mon, 2 Oct 2023 14:48:52 +0100 Subject: [PATCH 1027/1504] Fix conditional include of filter header for >=v4.7.0 --- include/netcdf-compat.h | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/include/netcdf-compat.h b/include/netcdf-compat.h index 3ab3c4453..89e7b20fe 100644 --- a/include/netcdf-compat.h +++ b/include/netcdf-compat.h @@ -128,8 +128,11 @@ static inline int nc_var_par_access(int ncid, int varid, int par_access) { retur #define HAS_PNETCDF_SUPPORT 0 #endif -#if NC_VERSION_GE(4, 9, 0) +#if NC_VERSION_GE(4, 7, 0) #include +#endif + +#if NC_VERSION_GE(4, 9, 0) #define HAS_NCFILTER 1 #else #define HAS_NCFILTER 0 From 466a53abde3147c40e6982780dd36327a964acd8 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Thu, 19 Oct 2023 08:43:05 -0600 Subject: [PATCH 1028/1504] add python 3.12, remove python 3.7 --- .github/workflows/miniconda.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index 8db0307f1..0455acf27 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -12,7 +12,7 @@ jobs: # NO_NET: 1 strategy: matrix: - python-version: [ "3.7", "3.8", "3.9", "3.10", "3.11" ] + python-version: [ "3.8", "3.9", "3.10", "3.11" "3.12" ] os: [windows-latest, ubuntu-latest, macos-latest] platform: [x64, x32] exclude: From a01a60409e16887c8f68aa379741e6d48e437081 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Thu, 19 Oct 2023 11:45:45 -0600 Subject: [PATCH 1029/1504] fix typo --- .github/workflows/miniconda.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index 0455acf27..3ad5eacea 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -12,7 +12,7 @@ jobs: # NO_NET: 1 strategy: matrix: - python-version: [ "3.8", "3.9", "3.10", "3.11" "3.12" ] + python-version: [ "3.8", "3.9", "3.10", "3.11", "3.12" ] os: [windows-latest, ubuntu-latest, macos-latest] platform: [x64, x32] exclude: From 546dfd65159dcc708d9c1d39a14c964f4d682346 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Thu, 19 Oct 2023 12:59:00 -0600 Subject: [PATCH 1030/1504] remove 'oversubscribe' option from mpirun --- .github/workflows/miniconda.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index 3ad5eacea..03f982b3c 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -79,8 +79,8 @@ jobs: export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" which mpirun mpirun --version - mpirun -np 4 --oversubscribe python mpi_example.py # for openmpi - #mpirun -np 4 python mpi_example.py + #mpirun -np 4 --oversubscribe python mpi_example.py # for openmpi + mpirun -np 4 python mpi_example.py if [ $? -ne 0 ] ; then echo "hdf5 mpi test failed!" exit 1 From 657fd3ab94b6da0422cc8e97ee742d2f3132dc78 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Thu, 19 Oct 2023 13:21:18 -0600 Subject: [PATCH 1031/1504] version 1.6.5 release --- README.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/README.md b/README.md index aa53e7135..245b62ceb 100644 --- a/README.md +++ b/README.md @@ -10,6 +10,10 @@ ## News For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog). +10/20/2023: Version [1.6.5](https://pypi.python.org/pypi/netCDF4/1.6.5) released. +Fix for issue #1271 (mask ignored if bool MA assinged to uint8 var), support for python 3.12, more +informative error messages. + 6/4/2023: Version [1.6.4](https://pypi.python.org/pypi/netCDF4/1.6.4) released. Now requires [certifi](https://github.com/certifi/python-certifi) to locate SSL certificates - this allows OpenDAP https URLs to work with linux wheels (issue [#1246](https://github.com/Unidata/netcdf4-python/issues/1246)). From 37ebf1ec84b9f3e776ae4df39438a9ac5f64c7da Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 24 Oct 2023 11:20:13 -0600 Subject: [PATCH 1032/1504] fix for pkg_resources missing on 3.12 --- test/tst_multifile.py | 4 ++-- test/tst_multifile2.py | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/test/tst_multifile.py b/test/tst_multifile.py index 0d9584892..93d72bded 100644 --- a/test/tst_multifile.py +++ b/test/tst_multifile.py @@ -5,7 +5,7 @@ from numpy import ma import tempfile, unittest, os, datetime import cftime -from pkg_resources import parse_version +from packaging.version import Version nx=100; ydim=5; zdim=10 nfiles = 10 @@ -138,7 +138,7 @@ def runTest(self): assert_equal(T.typecode(), t.typecode()) # skip this until cftime pull request #55 is in a released # version (1.0.1?). Otherwise, fix for issue #808 breaks this - if parse_version(cftime.__version__) >= parse_version('1.0.1'): + if Version(cftime.__version__) >= Version('1.0.1'): assert_array_equal(cftime.num2date(T[:], T.units, T.calendar), dates) assert_equal(cftime.date2index(datetime.datetime(1980, 1, 2), T), 366) f.close() diff --git a/test/tst_multifile2.py b/test/tst_multifile2.py index f818fcaba..65e36f43a 100644 --- a/test/tst_multifile2.py +++ b/test/tst_multifile2.py @@ -5,7 +5,7 @@ from numpy import ma import tempfile, unittest, os, datetime import cftime -from pkg_resources import parse_version +from packaging.version import Version nx=100; ydim=5; zdim=10 nfiles = 10 @@ -106,7 +106,7 @@ def runTest(self): # Get the real dates # skip this until cftime pull request #55 is in a released # version (1.0.1?). Otherwise, fix for issue #808 breaks this - if parse_version(cftime.__version__) >= parse_version('1.0.1'): + if Version(cftime.__version__) >= Version('1.0.1'): dates = [] for file in self.files: f = Dataset(file) From b34b395d693bd03477222965c1493e5cf738193f Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 24 Oct 2023 11:45:26 -0600 Subject: [PATCH 1033/1504] fix missing part of previous commit --- test/tst_multifile2.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/test/tst_multifile2.py b/test/tst_multifile2.py index 65e36f43a..f8e8552a6 100644 --- a/test/tst_multifile2.py +++ b/test/tst_multifile2.py @@ -126,7 +126,7 @@ def runTest(self): assert_equal(T.typecode(), t.typecode()) # skip this until cftime pull request #55 is in a released # version (1.0.1?). Otherwise, fix for issue #808 breaks this - if parse_version(cftime.__version__) >= parse_version('1.0.1'): + if Version(cftime.__version__) >= Version('1.0.1'): assert_array_equal(cftime.num2date(T[:], T.units, T.calendar), dates) assert_equal(cftime.date2index(datetime.datetime(1980, 1, 2), T), 366) f.close() From 87d1a3bdae0b282cbddbdce8b22b905a80832494 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 24 Oct 2023 12:50:45 -0600 Subject: [PATCH 1034/1504] include fix to pyproject.toml for 3.12 --- pyproject.toml | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/pyproject.toml b/pyproject.toml index 01562cefb..70d00626c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -39,6 +39,14 @@ dependencies = [ ] dynamic = ["version"] +[project.optional-dependencies] +tests = [ + "Cython", + "packaging", + "pytest", +] + + [project.readme] text = """\ netCDF version 4 has many features not found in earlier versions of the library, From 2cde1c48c4472779b702fb0a75bb2a5a83e4b3eb Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Thu, 26 Oct 2023 17:26:35 +0100 Subject: [PATCH 1035/1504] Bump version to 1.7.0 --- src/netCDF4/_netCDF4.pyx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 9cd40ec47..9f62643ff 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1,5 +1,5 @@ """ -Version 1.6.5 +Version 1.7.0 ------------- # Introduction @@ -1227,7 +1227,7 @@ from .utils import (_StartCountStride, _quantize, _find_dim, _walk_grps, import sys import functools -__version__ = "1.6.5" +__version__ = "1.7.0" # Initialize numpy import posixpath From 800d9c225b737c9440dbbfa1080844dfed73c6f9 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Thu, 26 Oct 2023 17:26:42 +0100 Subject: [PATCH 1036/1504] Add changelog entry for Cython `DEF/IF` fixes --- Changelog | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/Changelog b/Changelog index 8970167b9..8abe91883 100644 --- a/Changelog +++ b/Changelog @@ -1,4 +1,9 @@ - version 1.6.5 (not yet released) + version 1.7.0 (not yet released) +=============================== + * fix for deprecated Cython `DEF` and `IF` statements using compatibility header + with shims for unavailable functionality + + version 1.6.5 (tag v1.6.5rel) =============================== * fix for issue #1271 (mask ignored if bool MA assinged to uint8 var) * include information on specific object when reporting errors from netcdf-c From 0614299e546abaa06addc672235a879a3c4b0fa5 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Fri, 27 Oct 2023 13:39:06 +0100 Subject: [PATCH 1037/1504] Don't write `constants.pyx` No longer needed --- setup.py | 8 +++----- 1 file changed, 3 insertions(+), 5 deletions(-) diff --git a/setup.py b/setup.py index 6d7787b50..0cb0c3543 100644 --- a/setup.py +++ b/setup.py @@ -476,11 +476,9 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): (netcdf_lib_version > "4.4" and netcdf_lib_version < "4.5"): has_cdf5_format = True - with open(osp.join('include', 'constants.pyx'), 'w') as f: - has_parallel_support = check_has_parallel_support(inc_dirs) - has_has_not = "has" if has_parallel_support else "does not have" - sys.stdout.write(f"netcdf lib {has_has_not} parallel functions\n") - f.write(f'DEF HAS_PARALLEL_SUPPORT = {int(has_parallel_support)}\n') + has_parallel_support = check_has_parallel_support(inc_dirs) + has_has_not = "has" if has_parallel_support else "does not have" + sys.stdout.write(f"netcdf lib {has_has_not} parallel functions\n") if has_parallel_support: import mpi4py From bf4389e29c6d1ec8cbf32f0d991b6bcd6c7d04e1 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Fri, 29 Sep 2023 11:54:44 +0100 Subject: [PATCH 1038/1504] Simplify deeply nested conditionals for opening/creating file --- src/netCDF4/_netCDF4.pyx | 163 ++++++++++++--------------------------- 1 file changed, 49 insertions(+), 114 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 9f62643ff..572654437 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2276,10 +2276,39 @@ strings. self._inmemory = False # mode='x' is the same as mode='w' with clobber=False - if mode == 'x': - mode = 'w'; clobber = False + if mode == "x": + mode = "w" + clobber = False - if mode == 'w' or (mode in ['a','r+'] and not os.path.exists(filename)): + # r+ is synonym for append + if "r+" in mode: + mode = mode.replace("r+", "a") + + # If appending and the file doesn't exist, we need to create it + if mode in ("a", "as") and not os.path.exists(filename): + mode = mode.replace("a", "w") + + read_mode = mode in ("r", "rs") + write_mode = mode in ("w", "ws") + append_mode = mode in ("a", "as") + + if not (read_mode or write_mode or append_mode): + raise ValueError(f"mode must be 'w', 'x', 'r', 'a' or 'r+', got '{mode}'") + + # Initial value for cmode + if write_mode: + cmode = NC_CLOBBER if clobber else NC_NOCLOBBER + else: + cmode = NC_WRITE if append_mode else NC_NOWRITE + if mode.endswith("s") and not parallel: + cmode |= NC_SHARE + + if diskless: + cmode |= NC_DISKLESS + if write_mode and persist: + cmode |= NC_WRITE | NC_PERSIST + + if write_mode: _set_default_format(format=format) if memory is not None: if not __has_nc_create_mem__: @@ -2293,127 +2322,37 @@ strings. self._inmemory = True # checked in close method else: - cmode = NC_CLOBBER if clobber else NC_NOCLOBBER - if parallel: - cmode |= parmode with nogil: - ierr = nc_create_par(path, cmode, mpicomm, mpiinfo, &grpid) + ierr = nc_create_par(path, cmode | parmode, mpicomm, mpiinfo, &grpid) else: - if diskless: - cmode |= NC_DISKLESS - if persist: - cmode |= NC_WRITE | NC_PERSIST - with nogil: ierr = nc_create(path, cmode, &grpid) - # reset default format to netcdf3 - this is a workaround - # for issue 170 (nc_open'ing a DAP dataset after switching - # format to NETCDF4). This bug should be fixed in version - # 4.3.0 of the netcdf library (add a version check here?). - # **this causes parallel mode to fail when both hdf5-parallel and - # pnetcdf are enabled - issue #820 ** - #_set_default_format(format='NETCDF3_64BIT_OFFSET') - elif mode in ('r', 'rs'): - if memory is not None: - if not __has_nc_open_mem__: - raise NetCDF4MissingFeatureException("nc_open_mem", "4.4.1") + elif read_mode and memory is not None: + if not __has_nc_open_mem__: + raise NetCDF4MissingFeatureException("nc_open_mem", "4.4.1") - # Store reference to memory - result = PyObject_GetBuffer(memory, &self._buffer, PyBUF_SIMPLE | PyBUF_ANY_CONTIGUOUS) - if result != 0: - raise ValueError("Unable to retrieve Buffer from %s" % (memory,)) + # Store reference to memory + result = PyObject_GetBuffer( + memory, &self._buffer, PyBUF_SIMPLE | PyBUF_ANY_CONTIGUOUS + ) + if result != 0: + raise ValueError(f"Unable to retrieve Buffer from {memory}") - with nogil: - ierr = nc_open_mem(path, 0, self._buffer.len, self._buffer.buf, &grpid) + with nogil: + ierr = nc_open_mem( + path, 0, self._buffer.len, self._buffer.buf, &grpid + ) - elif parallel: - cmode = NC_NOWRITE | NC_MPIIO - with nogil: - ierr = nc_open_par(path, cmode, mpicomm, mpiinfo, &grpid) - elif diskless: - cmode = NC_NOWRITE | NC_DISKLESS - with nogil: - ierr = nc_open(path, cmode, &grpid) - else: - if mode == 'rs': - # NC_SHARE is very important for speed reading - # large netcdf3 files with a record dimension - # (pull request #902). - cmode = NC_NOWRITE | NC_SHARE - with nogil: - ierr = nc_open(path, cmode, &grpid) - else: - with nogil: - ierr = nc_open(path, NC_NOWRITE, &grpid) - elif mode in ['a','r+'] and os.path.exists(filename): + else: + # Read or append mode, flags already all set in cmode if parallel: - cmode = NC_WRITE | NC_MPIIO with nogil: - ierr = nc_open_par(path, cmode, mpicomm, mpiinfo, &grpid) - elif diskless: - cmode = NC_WRITE | NC_DISKLESS - with nogil: - ierr = nc_open(path, cmode, &grpid) + ierr = nc_open_par(path, cmode | NC_MPIIO, mpicomm, mpiinfo, &grpid) else: - with nogil: - ierr = nc_open(path, NC_WRITE, &grpid) - elif mode in ['as','r+s'] and os.path.exists(filename): - if parallel: - # NC_SHARE ignored - cmode = NC_WRITE | NC_MPIIO - with nogil: - ierr = nc_open_par(path, cmode, mpicomm, mpiinfo, &grpid) - elif diskless: - cmode = NC_SHARE | NC_DISKLESS with nogil: ierr = nc_open(path, cmode, &grpid) - else: - with nogil: - ierr = nc_open(path, NC_SHARE, &grpid) - elif mode == 'ws' or (mode in ['as','r+s'] and not os.path.exists(filename)): - _set_default_format(format=format) - if clobber: - if parallel: - # NC_SHARE ignored - cmode = NC_CLOBBER | parmode - with nogil: - ierr = nc_create_par(path, NC_CLOBBER | cmode, mpicomm, mpiinfo, &grpid) - elif diskless: - if persist: - cmode = NC_WRITE | NC_SHARE | NC_CLOBBER | NC_DISKLESS - with nogil: - ierr = nc_create(path, cmode, &grpid) - else: - cmode = NC_SHARE | NC_CLOBBER | NC_DISKLESS - with nogil: - ierr = nc_create(path, cmode , &grpid) - else: - cmode = NC_SHARE | NC_CLOBBER - with nogil: - ierr = nc_create(path, cmode, &grpid) - else: - if parallel: - # NC_SHARE ignored - cmode = NC_NOCLOBBER | parmode - with nogil: - ierr = nc_create_par(path, cmode, mpicomm, mpiinfo, &grpid) - elif diskless: - if persist: - cmode = NC_WRITE | NC_SHARE | NC_NOCLOBBER | NC_DISKLESS - with nogil: - ierr = nc_create(path, cmode , &grpid) - else: - cmode = NC_SHARE | NC_NOCLOBBER | NC_DISKLESS - with nogil: - ierr = nc_create(path, cmode , &grpid) - else: - cmode = NC_SHARE | NC_NOCLOBBER - with nogil: - ierr = nc_create(path, cmode, &grpid) - else: - raise ValueError("mode must be 'w', 'x', 'r', 'a' or 'r+', got '%s'" % mode) _ensure_nc_success(ierr, err_cls=OSError, filename=path) @@ -2423,10 +2362,6 @@ strings. # file_format for backwards compatibility. self.file_format = self.data_model self.disk_format = _get_full_format(grpid) - # diskless read access only works with NETCDF_CLASSIC (for now) - #ncopen = mode.startswith('a') or mode.startswith('r') - #if diskless and self.data_model != 'NETCDF3_CLASSIC' and ncopen: - # raise ValueError("diskless access only supported for NETCDF3_CLASSIC format") self._grpid = grpid self._isopen = 1 self.path = '/' From eec6678351cb248af6aa9f7b6e7b01cb791aec6f Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Fri, 27 Oct 2023 15:08:56 +0100 Subject: [PATCH 1039/1504] Pull out setting parallel formats from `Dataset` --- src/netCDF4/_netCDF4.pyx | 42 +++++++++++++++++++--------------------- 1 file changed, 20 insertions(+), 22 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 572654437..78915ca3f 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1467,6 +1467,17 @@ else: _format_dict['NETCDF3_64BIT_OFFSET'] = NC_FORMAT_64BIT _cmode_dict['NETCDF3_64BIT_OFFSET'] = NC_64BIT_OFFSET +_parallel_formats = [] +if __has_parallel4_support__: + _parallel_formats += ['NETCDF4', 'NETCDF4_CLASSIC'] +if __has_pnetcdf_support__: + _parallel_formats += [ + 'NETCDF3_CLASSIC', + 'NETCDF3_64BIT_OFFSET', + 'NETCDF3_64BIT_DATA', + 'NETCDF3_64BIT' + ] + # default fill_value to numpy datatype mapping. default_fillvals = {#'S1':NC_FILL_CHAR, 'S1':'\0', @@ -2244,33 +2255,20 @@ strings. bytestr = _strencode(_tostr(filename), encoding=encoding) path = bytestr - if memory is not None and mode not in ['r','w']: - msg='if memory kwarg specified, mode must be \'r\' or \'w\'' - raise ValueError(msg) + if memory is not None and mode not in ('r', 'w'): + raise ValueError("if memory kwarg specified, mode must be 'r' or 'w'") if parallel: if not __has_parallel_support__: raise ValueError("parallel mode requires MPI enabled netcdf-c") - parallel_formats = [] - if __has_parallel4_support__: - parallel_formats += ['NETCDF4','NETCDF4_CLASSIC'] - if __has_pnetcdf_support__: - parallel_formats += ['NETCDF3_CLASSIC', - 'NETCDF3_64BIT_OFFSET', - 'NETCDF3_64BIT_DATA', - 'NETCDF3_64BIT'] - if format not in parallel_formats: - msg='parallel mode only works with the following formats: ' + ' '.join(parallel_formats) - raise ValueError(msg) - if comm is not None: - mpicomm = (comm).ob_mpi - else: - mpicomm = MPI_COMM_WORLD - if info is not None: - mpiinfo = (info).ob_mpi - else: - mpiinfo = MPI_INFO_NULL + if format not in _parallel_formats: + raise ValueError( + f"parallel mode only works with the following formats: {' '.join(_parallel_formats)}" + ) + + mpicomm = (comm).ob_mpi if comm is not None else MPI_COMM_WORLD + mpiinfo = (info).ob_mpi if info is not None else MPI_INFO_NULL parmode = NC_MPIIO | _cmode_dict[format] self._inmemory = False From dd494ceea72829b2d486a2c367561c4443f65336 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Sat, 28 Oct 2023 12:30:41 -0600 Subject: [PATCH 1040/1504] remove references to python 3.7 support --- README.md | 2 +- pyproject.toml | 3 +-- src/netCDF4/_netCDF4.pyx | 2 +- 3 files changed, 3 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 245b62ceb..1c5403712 100644 --- a/README.md +++ b/README.md @@ -257,7 +257,7 @@ conda install -c conda-forge netCDF4 * Clone GitHub repository (`git clone https://github.com/Unidata/netcdf4-python.git`) * Make sure [numpy](http://www.numpy.org/) and [Cython](http://cython.org/) are - installed and you have [Python](https://www.python.org) 3.7 or newer. + installed and you have [Python](https://www.python.org) 3.8 or newer. * Make sure [HDF5](http://www.h5py.org/) and netcdf-4 are installed, and the `nc-config` utility is in your Unix PATH. diff --git a/pyproject.toml b/pyproject.toml index 70d00626c..f28064fb3 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -12,7 +12,7 @@ description = "Provides an object-oriented python interface to the netCDF versio authors = [ {name = "Jeff Whitaker", email = "jeffrey.s.whitaker@noaa.gov"}, ] -requires-python = ">=3.7" +requires-python = ">=3.8" keywords = [ "numpy", "netcdf", "data", "science", "network", "oceanography", "meteorology", "climate", @@ -21,7 +21,6 @@ license = {text = "MIT"} classifiers = [ "Development Status :: 3 - Alpha", "Programming Language :: Python :: 3", - "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 9f62643ff..5fe0f5bdf 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -32,7 +32,7 @@ types) are not supported. - Clone the [github repository](http://github.com/Unidata/netcdf4-python). - - Make sure the dependencies are satisfied (Python 3.7 or later, + - Make sure the dependencies are satisfied (Python 3.8 or later, [numpy](http://numpy.scipy.org), [Cython](http://cython.org), [cftime](https://github.com/Unidata/cftime), From 679e0165b72cd611bee9f6b04a1ce5755c282030 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Sat, 28 Oct 2023 12:36:38 -0600 Subject: [PATCH 1041/1504] note removal of py37 support in 1.6.5 --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 1c5403712..43d1461d7 100644 --- a/README.md +++ b/README.md @@ -11,7 +11,8 @@ For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog). 10/20/2023: Version [1.6.5](https://pypi.python.org/pypi/netCDF4/1.6.5) released. -Fix for issue #1271 (mask ignored if bool MA assinged to uint8 var), support for python 3.12, more +Fix for issue #1271 (mask ignored if bool MA assinged to uint8 var), +support for python 3.12 (removal of python 3.7 support), more informative error messages. 6/4/2023: Version [1.6.4](https://pypi.python.org/pypi/netCDF4/1.6.4) released. Now requires From 2da659a45b1ae8368361542bf4705dcf6a0c2ef1 Mon Sep 17 00:00:00 2001 From: jswhit Date: Sat, 28 Oct 2023 14:08:01 -0600 Subject: [PATCH 1042/1504] update docs --- README.htmldocs | 10 +-- docs/index.html | 163 +++++++++++++++++++++++++----------------------- 2 files changed, 92 insertions(+), 81 deletions(-) diff --git a/README.htmldocs b/README.htmldocs index 9f183e06c..a4ba23ee0 100644 --- a/README.htmldocs +++ b/README.htmldocs @@ -1,9 +1,11 @@ To update web docs at http://github.unidata.io/netcdf4-python: -First install pdoc (https://github.com/mitmproxy/pdoc) +First install pdoc (https://github.com/pdoc3/pdoc) Then in netcdf4-python github clone directory (after building and -installing github master), +installing github master), generate docs by running create_docs.sh. -* generate docs (sh create_docs.sh) -* edit docs/index.html and clean up as needed. +Docs are put in docs/index.html. + +Github pages (https://unidata.github.io/netcdf4-python/) points to docs/index.html +in master branch. diff --git a/docs/index.html b/docs/index.html index 35872a397..7ed8055d2 100644 --- a/docs/index.html +++ b/docs/index.html @@ -5,7 +5,7 @@ netCDF4 API documentation - @@ -23,7 +23,7 @@

    Package netCDF4

    -

    Version 1.6.4

    +

    Version 1.7.0

    Introduction

    netcdf4-python is a Python interface to the netCDF C library.

    netCDF version 4 has many features @@ -51,7 +51,7 @@

    Developer Install

    • Clone the github repository.
      • -
    • Make sure the dependencies are satisfied (Python 3.7 or later, +
    • Make sure the dependencies are satisfied (Python 3.8 or later, numpy, Cython, cftime, @@ -1113,7 +1113,7 @@

      In-memory (diskless) Datasets

      Functions

      -def chartostring(...) +def chartostring(b, encoding='utf-8')

      chartostring(b,encoding='utf-8')

      @@ -1220,13 +1220,18 @@

      Functions

      with approximately 1 microsecond accuracy.

      -def get_alignment(...) +def get_alignment()
      -
      +

      get_alignment()

      +

      return current netCDF alignment within HDF5 files in a tuple +(threshold,alignment). See netcdf C library documentation for +nc_get_alignment for details. Values can be reset with +set_alignment().

      +

      This function was added in netcdf 4.9.0.

      -def get_chunk_cache(...) +def get_chunk_cache()

      get_chunk_cache()

      @@ -1235,7 +1240,7 @@

      Functions

      details. Values can be reset with set_chunk_cache().

      -def getlibversion(...) +def getlibversion()

      getlibversion()

      @@ -1298,13 +1303,17 @@

      Functions

      contains one.

      -def set_alignment(...) +def set_alignment(threshold, alignment)
      -
      +

      set_alignment()(threshold,alignment)

      +

      Change the HDF5 file alignment. +See netcdf C library documentation for nc_set_alignment for +details.

      +

      This function was added in netcdf 4.9.0.

      -def set_chunk_cache(...) +def set_chunk_cache(size=None, nelems=None, preemption=None)

      set_chunk_cache(self,size=None,nelems=None,preemption=None)

      @@ -1313,7 +1322,7 @@

      Functions

      details.

      -def stringtoarr(...) +def stringtoarr(string, NUMCHARS, dtype='S')

      stringtoarr(a, NUMCHARS,dtype='S')

      @@ -1333,7 +1342,7 @@

      Functions

      (default) or 'U1' (if dtype='U')

      -def stringtochar(...) +def stringtochar(a, encoding='utf-8')

      stringtochar(a,encoding='utf-8')

      @@ -1553,7 +1562,7 @@

      Subclasses

      Static methods

      -def fromcdl(...) +def fromcdl(cdlfilename, ncfilename=None, mode='a', format='NETCDF4')

      fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')

      @@ -1629,14 +1638,14 @@

      Instance variables

      Methods

      -def close(...) +def close(self)

      close(self)

      Close the Dataset.

      -def createCompoundType(...) +def createCompoundType(self, datatype, datatype_name)

      createCompoundType(self, datatype, datatype_name)

      @@ -1650,7 +1659,7 @@

      Methods

      datatype.

      -def createDimension(...) +def createDimension(self, dimname, size=None)

      createDimension(self, dimname, size=None)

      @@ -1665,7 +1674,7 @@

      Methods

      Dimension.isunlimited() method of the Dimension instance.

      -def createEnumType(...) +def createEnumType(self, datatype, datatype_name, enum_dict)

      createEnumType(self, datatype, datatype_name, enum_dict)

      @@ -1676,7 +1685,7 @@

      Methods

      datatype.

      -def createGroup(...) +def createGroup(self, groupname)

      createGroup(self, groupname)

      @@ -1692,7 +1701,7 @@

      Methods

      The return value is a Group class instance.

      -def createVLType(...) +def createVLType(self, datatype, datatype_name)

      createVLType(self, datatype, datatype_name)

      @@ -1702,7 +1711,7 @@

      Methods

      datatype.

      -def createVariable(...) +def createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False, complevel=4, shuffle=True, szip_coding='nn', szip_pixels_per_block=8, blosc_shuffle=1, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, significant_digits=None, quantize_mode='BitGroom', fill_value=None, chunk_cache=None)

      createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False, @@ -1848,7 +1857,7 @@

      Methods

      is the number of variable dimensions.

      -def delncattr(...) +def delncattr(self, name)

      delncattr(self,name,value)

      @@ -1858,7 +1867,7 @@

      Methods

      attributes.

      -def filepath(...) +def filepath(self, encoding=None)

      filepath(self,encoding=None)

      @@ -1869,7 +1878,7 @@

      Methods

      changed using the encoding kwarg.

      -def get_variables_by_attributes(...) +def get_variables_by_attributes(self, **kwargs)

      get_variables_by_attributes(self, **kwargs)

      @@ -1896,7 +1905,7 @@

      Methods

      -def getncattr(...) +def getncattr(self, name, encoding='utf-8')

      getncattr(self,name)

      @@ -1907,77 +1916,77 @@

      Methods

      character encoding of a string attribute (default is utf-8).

      -def has_blosc_filter(...) +def has_blosc_filter(self)

      has_blosc_filter(self) returns True if blosc compression filter is available

      -def has_bzip2_filter(...) +def has_bzip2_filter(self)

      has_bzip2_filter(self) returns True if bzip2 compression filter is available

      -def has_szip_filter(...) +def has_szip_filter(self)

      has_szip_filter(self) returns True if szip compression filter is available

      -def has_zstd_filter(...) +def has_zstd_filter(self)

      has_zstd_filter(self) returns True if zstd compression filter is available

      -def isopen(...) +def isopen(self)

      isopen(self)

      Is the Dataset open or closed?

      -def ncattrs(...) +def ncattrs(self)

      ncattrs(self)

      return netCDF global attribute names for this Dataset or Group in a list.

      -def renameAttribute(...) +def renameAttribute(self, oldname, newname)

      renameAttribute(self, oldname, newname)

      rename a Dataset or Group attribute named oldname to newname.

      -def renameDimension(...) +def renameDimension(self, oldname, newname)

      renameDimension(self, oldname, newname)

      rename a Dimension named oldname to newname.

      -def renameGroup(...) +def renameGroup(self, oldname, newname)

      renameGroup(self, oldname, newname)

      rename a Group named oldname to newname (requires netcdf >= 4.3.1).

      -def renameVariable(...) +def renameVariable(self, oldname, newname)

      renameVariable(self, oldname, newname)

      rename a Variable named oldname to newname

      -def set_always_mask(...) +def set_always_mask(self, value)

      set_always_mask(self, True_or_False)

      @@ -1994,7 +2003,7 @@

      Methods

      the default behaviour.

      -def set_auto_chartostring(...) +def set_auto_chartostring(self, value)

      set_auto_chartostring(self, True_or_False)

      @@ -2008,7 +2017,7 @@

      Methods

      after calling this function will follow the default behaviour.

      -def set_auto_mask(...) +def set_auto_mask(self, value)

      set_auto_mask(self, True_or_False)

      @@ -2021,7 +2030,7 @@

      Methods

      after calling this function will follow the default behaviour.

      -def set_auto_maskandscale(...) +def set_auto_maskandscale(self, value)

      set_auto_maskandscale(self, True_or_False)

      @@ -2033,7 +2042,7 @@

      Methods

      after calling this function will follow the default behaviour.

      -def set_auto_scale(...) +def set_auto_scale(self, value)

      set_auto_scale(self, True_or_False)

      @@ -2045,7 +2054,7 @@

      Methods

      after calling this function will follow the default behaviour.

      -def set_fill_off(...) +def set_fill_off(self)

      set_fill_off(self)

      @@ -2055,7 +2064,7 @@

      Methods

      sure the data is actually written before being read.

      -def set_fill_on(...) +def set_fill_on(self)

      set_fill_on(self)

      @@ -2070,7 +2079,7 @@

      Methods

      to.

      -def set_ncstring_attrs(...) +def set_ncstring_attrs(self, value)

      set_ncstring_attrs(self, True_or_False)

      @@ -2084,7 +2093,7 @@

      Methods

      of existing (sub-) groups and their variables.

      -def setncattr(...) +def setncattr(self, name, value)

      setncattr(self,name,value)

      @@ -2093,7 +2102,7 @@

      Methods

      with the same name as one of the reserved python attributes.

      -def setncattr_string(...) +def setncattr_string(self, name, value)

      setncattr_string(self,name,value)

      @@ -2102,7 +2111,7 @@

      Methods

      NC_STRING if the file format is NETCDF4.

      -def setncatts(...) +def setncatts(self, attdict)

      setncatts(self,attdict)

      @@ -2112,14 +2121,14 @@

      Methods

      each attribute

      -def sync(...) +def sync(self)

      sync(self)

      Writes all buffered data in the Dataset to the disk file.

      -def tocdl(...) +def tocdl(self, coordvars=False, data=False, outfile=None)

      tocdl(self, coordvars=False, data=False, outfile=None)

      @@ -2170,14 +2179,14 @@

      Instance variables

      Methods

      -def group(...) +def group(self)

      group(self)

      return the group that this Dimension is a member of.

      -def isunlimited(...) +def isunlimited(self)

      isunlimited(self)

      @@ -2255,7 +2264,7 @@

      Ancestors

      Methods

      -def close(...) +def close(self)

      close(self)

      @@ -2665,7 +2674,7 @@

      Instance variables

      Methods

      -def assignValue(...) +def assignValue(self, val)

      assignValue(self, val)

      @@ -2674,7 +2683,7 @@

      Methods

      Scientific.IO.NetCDF, can also be done by assigning to an Ellipsis slice ([…]).

      -def chunking(...) +def chunking(self)

      chunking(self)

      @@ -2686,7 +2695,7 @@

      Methods

      each dimension is returned.

      -def delncattr(...) +def delncattr(self, name)

      delncattr(self,name,value)

      @@ -2696,21 +2705,21 @@

      Methods

      attributes.

      -def endian(...) +def endian(self)

      endian(self)

      return endian-ness (little,big,native) of variable (as stored in HDF5 file).

      -def filters(...) +def filters(self)

      filters(self)

      return dictionary containing HDF5 filter parameters.

      -def getValue(...) +def getValue(self)

      getValue(self)

      @@ -2719,7 +2728,7 @@

      Methods

      Scientific.IO.NetCDF, can also be done by slicing with an Ellipsis ([…]).

      -def get_dims(...) +def get_dims(self)

      get_dims(self)

      @@ -2727,7 +2736,7 @@

      Methods

      Variable.

      -def get_var_chunk_cache(...) +def get_var_chunk_cache(self)

      get_var_chunk_cache(self)

      @@ -2736,7 +2745,7 @@

      Methods

      details.

      -def getncattr(...) +def getncattr(self, name, encoding='utf-8')

      getncattr(self,name)

      @@ -2748,21 +2757,21 @@

      Methods

      character encoding of a string attribute (default is utf-8).

      -def group(...) +def group(self)

      group(self)

      return the group that this Variable is a member of.

      -def ncattrs(...) +def ncattrs(self)

      ncattrs(self)

      return netCDF attribute names for this Variable in a list.

      -def quantization(...) +def quantization(self)

      quantization(self)

      @@ -2770,14 +2779,14 @@

      Methods

      Returns None if quantization not active.

      -def renameAttribute(...) +def renameAttribute(self, oldname, newname)

      renameAttribute(self, oldname, newname)

      rename a Variable attribute named oldname to newname.

      -def set_always_mask(...) +def set_always_mask(self, always_mask)

      set_always_mask(self,always_mask)

      @@ -2790,7 +2799,7 @@

      Methods

      otherwise masked array returned).

      -def set_auto_chartostring(...) +def set_auto_chartostring(self, chartostring)

      set_auto_chartostring(self,chartostring())

      @@ -2810,7 +2819,7 @@

      Methods

      (automatic conversions are performed).

      -def set_auto_mask(...) +def set_auto_mask(self, mask)

      set_auto_mask(self,mask)

      @@ -2835,7 +2844,7 @@

      Methods

      (automatic conversions are performed).

      -def set_auto_maskandscale(...) +def set_auto_maskandscale(self, maskandscale)

      set_auto_maskandscale(self,maskandscale)

      @@ -2884,7 +2893,7 @@

      Methods

      (automatic conversions are performed).

      -def set_auto_scale(...) +def set_auto_scale(self, scale)

      set_auto_scale(self,scale)

      @@ -2918,7 +2927,7 @@

      Methods

      (automatic conversions are performed).

      -def set_collective(...) +def set_collective(self, value)

      set_collective(self,True_or_False)

      @@ -2926,7 +2935,7 @@

      Methods

      open for parallel access.

      -def set_ncstring_attrs(...) +def set_ncstring_attrs(self, ncstring_attrs)

      set_always_mask(self,ncstring_attrs)

      @@ -2937,7 +2946,7 @@

      Methods

      NC_CHAR).

      -def set_var_chunk_cache(...) +def set_var_chunk_cache(self, size=None, nelems=None, preemption=None)

      set_var_chunk_cache(self,size=None,nelems=None,preemption=None)

      @@ -2946,7 +2955,7 @@

      Methods

      details.

      -def setncattr(...) +def setncattr(self, name, value)

      setncattr(self,name,value)

      @@ -2956,7 +2965,7 @@

      Methods

      attributes.

      -def setncattr_string(...) +def setncattr_string(self, name, value)

      setncattr_string(self,name,value)

      @@ -2966,7 +2975,7 @@

      Methods

      Use if you need to set an attribute to an array of variable-length strings.

      -def setncatts(...) +def setncatts(self, attdict)

      setncatts(self,attdict)

      @@ -2976,7 +2985,7 @@

      Methods

      each attribute

      -def use_nc_get_vars(...) +def use_nc_get_vars(self, use_nc_get_vars)

      use_nc_get_vars(self,_use_get_vars)

      @@ -2996,7 +3005,7 @@

      Methods

      Index

        -
      • Version 1.6.4
        • +
      • Version 1.7.0
      • Introduction
        • Quick Install
        • Developer Install
          • From 6e03d0f5266d8c3218d40855b20fe8bc2cb81b48 Mon Sep 17 00:00:00 2001 From: jswhit Date: Sat, 28 Oct 2023 14:11:02 -0600 Subject: [PATCH 1043/1504] add python 3.12 to classifiers --- Changelog | 1 + pyproject.toml | 1 + 2 files changed, 2 insertions(+) diff --git a/Changelog b/Changelog index 8abe91883..e5c5362c8 100644 --- a/Changelog +++ b/Changelog @@ -7,6 +7,7 @@ =============================== * fix for issue #1271 (mask ignored if bool MA assinged to uint8 var) * include information on specific object when reporting errors from netcdf-c + * python 3.12 wheels added, support for python 3.7 removed. version 1.6.4 (tag v1.6.4rel) =============================== diff --git a/pyproject.toml b/pyproject.toml index f28064fb3..f62ca8ec9 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -25,6 +25,7 @@ classifiers = [ "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", "Intended Audience :: Science/Research", "License :: OSI Approved :: MIT License", "Topic :: Software Development :: Libraries :: Python Modules", From e97ac7c79ead90e142aee6d2b5c53934fae350a6 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Fri, 27 Oct 2023 16:26:38 +0100 Subject: [PATCH 1044/1504] Simplify reading directories from setup.cfg --- setup.py | 105 +++++++++++-------------------------------------------- 1 file changed, 21 insertions(+), 84 deletions(-) diff --git a/setup.py b/setup.py index 0cb0c3543..4368fd18f 100644 --- a/setup.py +++ b/setup.py @@ -154,90 +154,27 @@ def extract_version(CYTHON_FNAME): sys.stdout.write('reading from setup.cfg...\n') config = configparser.ConfigParser() config.read(setup_cfg) - try: - HDF5_dir = config.get("directories", "HDF5_dir") - except: - pass - try: - HDF5_libdir = config.get("directories", "HDF5_libdir") - except: - pass - try: - HDF5_incdir = config.get("directories", "HDF5_incdir") - except: - pass - try: - netCDF4_dir = config.get("directories", "netCDF4_dir") - except: - pass - try: - netCDF4_libdir = config.get("directories", "netCDF4_libdir") - except: - pass - try: - netCDF4_incdir = config.get("directories", "netCDF4_incdir") - except: - pass - try: - szip_dir = config.get("directories", "szip_dir") - except: - pass - try: - szip_libdir = config.get("directories", "szip_libdir") - except: - pass - try: - szip_incdir = config.get("directories", "szip_incdir") - except: - pass - try: - hdf4_dir = config.get("directories", "hdf4_dir") - except: - pass - try: - hdf4_libdir = config.get("directories", "hdf4_libdir") - except: - pass - try: - hdf4_incdir = config.get("directories", "hdf4_incdir") - except: - pass - try: - jpeg_dir = config.get("directories", "jpeg_dir") - except: - pass - try: - jpeg_libdir = config.get("directories", "jpeg_libdir") - except: - pass - try: - jpeg_incdir = config.get("directories", "jpeg_incdir") - except: - pass - try: - curl_dir = config.get("directories", "curl_dir") - except: - pass - try: - curl_libdir = config.get("directories", "curl_libdir") - except: - pass - try: - curl_incdir = config.get("directories", "curl_incdir") - except: - pass - try: - mpi_incdir = config.get("directories","mpi_incdir") - except: - pass - try: - use_ncconfig = config.getboolean("options", "use_ncconfig") - except: - pass - try: - ncconfig = config.get("options", "ncconfig") - except: - pass + HDF5_dir = config.get("directories", "HDF5_dir", fallback=HDF5_dir) + HDF5_libdir = config.get("directories", "HDF5_libdir", fallback=HDF5_libdir) + HDF5_incdir = config.get("directories", "HDF5_incdir", fallback=HDF5_incdir) + netCDF4_dir = config.get("directories", "netCDF4_dir", fallback=netCDF4_dir) + netCDF4_libdir = config.get("directories", "netCDF4_libdir", fallback=netCDF4_libdir) + netCDF4_incdir = config.get("directories", "netCDF4_incdir", fallback=netCDF4_incdir) + szip_dir = config.get("directories", "szip_dir", fallback=szip_dir) + szip_libdir = config.get("directories", "szip_libdir", fallback=szip_libdir) + szip_incdir = config.get("directories", "szip_incdir", fallback=szip_incdir) + hdf4_dir = config.get("directories", "hdf4_dir", fallback=hdf4_dir) + hdf4_libdir = config.get("directories", "hdf4_libdir", fallback=hdf4_libdir) + hdf4_incdir = config.get("directories", "hdf4_incdir", fallback=hdf4_incdir) + jpeg_dir = config.get("directories", "jpeg_dir", fallback=jpeg_dir) + jpeg_libdir = config.get("directories", "jpeg_libdir", fallback=jpeg_libdir) + jpeg_incdir = config.get("directories", "jpeg_incdir", fallback=jpeg_incdir) + curl_dir = config.get("directories", "curl_dir", fallback=curl_dir) + curl_libdir = config.get("directories", "curl_libdir", fallback=curl_libdir) + curl_incdir = config.get("directories", "curl_incdir", fallback=curl_incdir) + mpi_incdir = config.get("directories","mpi_incdir", fallback=mpi_incdir) + use_ncconfig = config.getboolean("options", "use_ncconfig", fallback=use_ncconfig) + ncconfig = config.get("options", "ncconfig", fallback=ncconfig) try: if ncconfig is None: From 35ff41dca7ddc74819374dc72683b09120baff92 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Fri, 27 Oct 2023 16:32:54 +0100 Subject: [PATCH 1045/1504] Use `print` instead of `sys.stdout.write` --- setup.py | 48 +++++++++++++++++++++--------------------------- 1 file changed, 21 insertions(+), 27 deletions(-) diff --git a/setup.py b/setup.py index 4368fd18f..6a43f3dbb 100644 --- a/setup.py +++ b/setup.py @@ -22,14 +22,13 @@ def check_hdf5version(hdf5_includedir): def get_hdf5_version(direc): # check to see if hdf5 headers in direc, return version number or None hdf5_version = None - sys.stdout.write('checking %s ...\n' % direc) + print(f"checking {direc}...") hdf5_version = check_hdf5version(direc) if hdf5_version is None: - sys.stdout.write('hdf5 headers not found in %s\n' % direc) + print(f'hdf5 headers not found in {direc}') return None else: - sys.stdout.write('%s headers found in %s\n' % - (hdf5_version,direc)) + print(f'{hdf5_version} headers found in {direc}') return hdf5_version def check_ifnetcdf4(netcdf4_includedir): @@ -151,7 +150,7 @@ def extract_version(CYTHON_FNAME): ncconfig = None use_ncconfig = None if USE_SETUPCFG and os.path.exists(setup_cfg): - sys.stdout.write('reading from setup.cfg...\n') + print('reading from setup.cfg...') config = configparser.ConfigParser() config.read(setup_cfg) HDF5_dir = config.get("directories", "HDF5_dir", fallback=HDF5_dir) @@ -225,8 +224,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): [str(i[2:].decode()) for i in dep.split() if i[0:2].decode() == '-I']) else: if HDF5_incdir is None and HDF5_dir is None: - sys.stdout.write(""" - HDF5_DIR environment variable not set, checking some standard locations ..\n""") + print(" HDF5_DIR environment variable not set, checking some standard locations ..") for direc in dirstosearch: hdf5_version = get_hdf5_version(os.path.join(direc, 'include')) if hdf5_version is None: @@ -234,8 +232,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): else: HDF5_dir = direc HDF5_incdir = os.path.join(direc, 'include') - sys.stdout.write('%s found in %s\n' % - (hdf5_version,HDF5_dir)) + print(f'{hdf5_version} found in {HDF5_dir}') break if HDF5_dir is None: raise ValueError('did not find HDF5 headers') @@ -244,10 +241,8 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): HDF5_incdir = os.path.join(HDF5_dir, 'include') hdf5_version = get_hdf5_version(HDF5_incdir) if hdf5_version is None: - raise ValueError('did not find HDF5 headers in %s' % HDF5_incdir) - else: - sys.stdout.write('%s found in %s\n' % - (hdf5_version,HDF5_dir)) + raise ValueError(f'did not find HDF5 headers in {HDF5_incdir}') + print(f'{hdf5_version} found in {HDF5_dir}') if HDF5_libdir is None and HDF5_dir is not None: HDF5_libdir = os.path.join(HDF5_dir, 'lib') @@ -267,7 +262,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): # try nc-config first if USE_NCCONFIG and HAS_NCCONFIG: # Try nc-config. - sys.stdout.write('using %s...\n' % ncconfig) + print(f'using {ncconfig}...') dep = subprocess.Popen([ncconfig, '--libs'], stdout=subprocess.PIPE).communicate()[0] libs = [str(l[2:].decode()) for l in dep.split() if l[0:2].decode() == '-l'] @@ -286,7 +281,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): break # if hdf5 not found, search other standard locations (including those specified in env vars). if hdf5_version is None: - sys.stdout.write('nc-config did provide path to HDF5 headers, search standard locations...') + print('nc-config did provide path to HDF5 headers, search standard locations...') _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs) # If nc-config doesn't work, fall back on brute force method. @@ -300,17 +295,16 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs) if netCDF4_incdir is None and netCDF4_dir is None: - sys.stdout.write(""" -NETCDF4_DIR environment variable not set, checking standard locations.. \n""") + print("NETCDF4_DIR environment variable not set, checking standard locations..") for direc in dirstosearch: - sys.stdout.write('checking %s ...\n' % direc) + print(f'checking {direc}...') isnetcdf4 = check_ifnetcdf4(os.path.join(direc, 'include')) if not isnetcdf4: continue else: netCDF4_dir = direc netCDF4_incdir = os.path.join(direc, 'include') - sys.stdout.write('netCDF4 found in %s\n' % netCDF4_dir) + print(f'netCDF4 found in {netCDF4_dir}') break if netCDF4_dir is None: raise ValueError('did not find netCDF version 4 headers') @@ -389,10 +383,10 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): # get netcdf library version. netcdf_lib_version = getnetcdfvers(lib_dirs) if netcdf_lib_version is None: - sys.stdout.write('unable to detect netcdf library version\n') + print('unable to detect netcdf library version') else: netcdf_lib_version = str(netcdf_lib_version) - sys.stdout.write('using netcdf library version %s\n' % netcdf_lib_version) + print(f'using netcdf library version {netcdf_lib_version}') cmdclass = {} DEFINE_MACROS = [("NPY_NO_DEPRECATED_API", "NPY_1_7_API_VERSION")] @@ -400,7 +394,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): netcdf4_src_c = netcdf4_src_root + '.c' netcdf4_src_pyx = netcdf4_src_root + '.pyx' if 'sdist' not in sys.argv[1:] and 'clean' not in sys.argv[1:] and '--version' not in sys.argv[1:]: - sys.stdout.write('using Cython to compile netCDF4.pyx...\n') + print('using Cython to compile netCDF4.pyx...') # remove _netCDF4.c file if it exists, so cython will recompile _netCDF4.pyx. # run for build *and* install (issue #263). Otherwise 'pip install' will # not regenerate _netCDF4.c, even if the C lib supports the new features. @@ -415,7 +409,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): has_parallel_support = check_has_parallel_support(inc_dirs) has_has_not = "has" if has_parallel_support else "does not have" - sys.stdout.write(f"netcdf lib {has_has_not} parallel functions\n") + print(f"netcdf lib {has_has_not} parallel functions") if has_parallel_support: import mpi4py @@ -457,19 +451,19 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): plugin_dir = os.environ.get("NETCDF_PLUGIN_DIR") plugins = glob.glob(os.path.join(plugin_dir, "lib__nc*")) if not plugins: - sys.stdout.write('no plugin files in NETCDF_PLUGIN_DIR, not installing..\n') + print('no plugin files in NETCDF_PLUGIN_DIR, not installing...') data_files = [] else: data_files = plugins - sys.stdout.write('installing netcdf compression plugins from %s ...\n' % plugin_dir) + print(f'installing netcdf compression plugins from {plugin_dir} ...') sofiles = [os.path.basename(sofilepath) for sofilepath in data_files] - sys.stdout.write(repr(sofiles)+'\n') + print(repr(sofiles)) if 'sdist' not in sys.argv[1:] and 'clean' not in sys.argv[1:] and '--version' not in sys.argv[1:]: for f in data_files: shutil.copy(f, osp.join(os.getcwd(),osp.join(osp.join('src','netCDF4'),'plugins'))) copied_plugins=True else: - sys.stdout.write('NETCDF_PLUGIN_DIR not set, no netcdf compression plugins installed\n') + print('NETCDF_PLUGIN_DIR not set, no netcdf compression plugins installed') data_files = [] # See pyproject.toml for project metadata From bf796eda12d85326a8325c93910b934e713427b9 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Fri, 27 Oct 2023 16:51:30 +0100 Subject: [PATCH 1046/1504] Simplify use of `subprocess` in `setup.py` --- setup.py | 45 +++++++++++++++++---------------------------- 1 file changed, 17 insertions(+), 28 deletions(-) diff --git a/setup.py b/setup.py index 6a43f3dbb..41170e656 100644 --- a/setup.py +++ b/setup.py @@ -4,6 +4,7 @@ import configparser from setuptools import setup, Extension from setuptools.dist import Distribution +from typing import List open_kwargs = {'encoding': 'utf-8'} @@ -181,8 +182,7 @@ def extract_version(CYTHON_FNAME): ncconfig = os.path.join(netCDF4_dir, 'bin/nc-config') else: # otherwise, just hope it's in the users PATH. ncconfig = 'nc-config' - HAS_NCCONFIG = subprocess.call([ncconfig, '--libs'], - stdout=subprocess.PIPE) == 0 + HAS_NCCONFIG = subprocess.call([ncconfig, '--libs']) == 0 except OSError: HAS_NCCONFIG = False @@ -197,31 +197,26 @@ def extract_version(CYTHON_FNAME): # USE_NCCONFIG = False # don't try to use nc-config if USE_NCCONFIG not set try: - HAS_PKG_CONFIG = subprocess.call(['pkg-config', '--libs', 'hdf5'], - stdout=subprocess.PIPE) == 0 + HAS_PKG_CONFIG = subprocess.call(['pkg-config', '--libs', 'hdf5']) == 0 except OSError: HAS_PKG_CONFIG = False + +def config_flags(command: List[str], flag: str) -> list: + """Pull out specific flags from a config command (pkg-config or nc-config)""" + flags = subprocess.run(command, capture_output=True, text=True) + return [arg[2:] for arg in flags.stdout.split() if arg.startswith(flag)] + + def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): global HDF5_incdir, HDF5_dir, HDF5_libdir nohdf5dirs = HDF5_incdir is None and HDF5_libdir is None and HDF5_dir is None if HAS_PKG_CONFIG and nohdf5dirs: # if HDF5 dirs not specified, and pkg-config available, use it - dep = subprocess.Popen(['pkg-config', '--cflags', 'hdf5'], - stdout=subprocess.PIPE).communicate()[0] - inc_dirs.extend([str(i[2:].decode()) for i in dep.split() if - i[0:2].decode() == '-I']) - dep = subprocess.Popen(['pkg-config', '--libs', 'hdf5'], - stdout=subprocess.PIPE).communicate()[0] - libs.extend( - [str(l[2:].decode()) for l in dep.split() if l[0:2].decode() == '-l']) - lib_dirs.extend( - [str(l[2:].decode()) for l in dep.split() if l[0:2].decode() == '-L']) - dep = subprocess.Popen(['pkg-config', '--cflags', 'hdf5'], - stdout=subprocess.PIPE).communicate()[0] - inc_dirs.extend( - [str(i[2:].decode()) for i in dep.split() if i[0:2].decode() == '-I']) + inc_dirs.extend(config_flags(["pkg-config", "--cflags", "hdf5"], "-I")) + libs.extend(config_flags(["pkg-config", "--libs", "hdf5"], "-l")) + lib_dirs.extend(config_flags(["pkg-config", "--libs", "hdf5"], "-L")) else: if HDF5_incdir is None and HDF5_dir is None: print(" HDF5_DIR environment variable not set, checking some standard locations ..") @@ -261,17 +256,11 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): '/opt/local', '/opt/homebrew', '/usr'] # try nc-config first -if USE_NCCONFIG and HAS_NCCONFIG: # Try nc-config. +if USE_NCCONFIG and HAS_NCCONFIG and ncconfig is not None: print(f'using {ncconfig}...') - dep = subprocess.Popen([ncconfig, '--libs'], - stdout=subprocess.PIPE).communicate()[0] - libs = [str(l[2:].decode()) for l in dep.split() if l[0:2].decode() == '-l'] - lib_dirs = [str(l[2:].decode()) for l in dep.split() if - l[0:2].decode() == '-L'] - dep = subprocess.Popen([ncconfig, '--cflags'], - stdout=subprocess.PIPE).communicate()[0] - inc_dirs = [str(i[2:].decode()) for i in dep.split() if - i[0:2].decode() == '-I'] + libs = config_flags([ncconfig, "--libs"], "-l") + lib_dirs = config_flags([ncconfig, "--libs"], "-L") + inc_dirs = config_flags([ncconfig, '--cflags'], "-I") # check to see if hdf5 found in directories returned by nc-config hdf5_version = None From 4e00b0f9077f75eab53a4795c6460b76fcffc598 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Thu, 2 Nov 2023 09:38:42 +0000 Subject: [PATCH 1047/1504] Simplify some conditionals in setup.py --- setup.py | 18 +++++------------- 1 file changed, 5 insertions(+), 13 deletions(-) diff --git a/setup.py b/setup.py index 41170e656..7e0b2f45c 100644 --- a/setup.py +++ b/setup.py @@ -135,15 +135,9 @@ def extract_version(CYTHON_FNAME): curl_incdir = os.environ.get('CURL_INCDIR') mpi_incdir = os.environ.get('MPI_INCDIR') -USE_NCCONFIG = os.environ.get('USE_NCCONFIG') -if USE_NCCONFIG is not None: - USE_NCCONFIG = bool(int(USE_NCCONFIG)) -USE_SETUPCFG = os.environ.get('USE_SETUPCFG') +USE_NCCONFIG = bool(int(os.environ.get('USE_NCCONFIG', 0))) # override use of setup.cfg with env var. -if USE_SETUPCFG is not None: - USE_SETUPCFG = bool(int(USE_SETUPCFG)) -else: - USE_SETUPCFG = True +USE_SETUPCFG = bool(int(os.environ.get('USE_SETUPCFG', 1))) setup_cfg = 'setup.cfg' # contents of setup.cfg will override env vars, unless @@ -188,13 +182,11 @@ def extract_version(CYTHON_FNAME): # make sure USE_NCCONFIG from environment takes # precendence over use_ncconfig from setup.cfg (issue #341). -if USE_NCCONFIG is None and use_ncconfig is not None: +if use_ncconfig and not USE_NCCONFIG: USE_NCCONFIG = use_ncconfig -elif USE_NCCONFIG is None: +elif not USE_NCCONFIG: # if nc-config exists, and USE_NCCONFIG not set, try to use it. - if HAS_NCCONFIG: USE_NCCONFIG=True -#elif USE_NCCONFIG is None: -# USE_NCCONFIG = False # don't try to use nc-config if USE_NCCONFIG not set + USE_NCCONFIG = HAS_NCCONFIG try: HAS_PKG_CONFIG = subprocess.call(['pkg-config', '--libs', 'hdf5']) == 0 From efac9161f81c8bc0dd4a91215c5cbe9ecc670022 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Thu, 2 Nov 2023 11:55:00 +0000 Subject: [PATCH 1048/1504] Delete unused variable --- setup.py | 1 - 1 file changed, 1 deletion(-) diff --git a/setup.py b/setup.py index 7e0b2f45c..31d32ac30 100644 --- a/setup.py +++ b/setup.py @@ -369,7 +369,6 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): netcdf_lib_version = str(netcdf_lib_version) print(f'using netcdf library version {netcdf_lib_version}') -cmdclass = {} DEFINE_MACROS = [("NPY_NO_DEPRECATED_API", "NPY_1_7_API_VERSION")] netcdf4_src_root = osp.join(osp.join('src','netCDF4'), '_netCDF4') netcdf4_src_c = netcdf4_src_root + '.c' From 4180fdefa6b5ceb25673221de598043c153baa2a Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Mon, 6 Nov 2023 11:30:08 +0000 Subject: [PATCH 1049/1504] Move skipping tests to test decorators Makes it easier to run test suite with pytest --- pyproject.toml | 3 ++ test/__init__.py | 0 test/filter_availability.py | 20 +++++++++++ test/run_all.py | 61 +++------------------------------ test/tst_cdf5.py | 6 ++-- test/tst_cdl.py | 2 ++ test/tst_compression_blosc.py | 13 ++++--- test/tst_compression_bzip2.py | 12 +++---- test/tst_compression_quant.py | 5 +-- test/tst_compression_szip.py | 12 +++---- test/tst_compression_zstd.py | 11 +++--- test/tst_create_mem.py | 2 ++ test/tst_dap.py | 4 ++- test/tst_diskless.py | 8 ++++- test/tst_filepath.py | 2 +- test/tst_multiple_open_close.py | 6 ++-- 16 files changed, 73 insertions(+), 94 deletions(-) create mode 100644 test/__init__.py create mode 100644 test/filter_availability.py diff --git a/pyproject.toml b/pyproject.toml index f62ca8ec9..16636ec1d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -72,3 +72,6 @@ where = ["src"] [tool.setuptools.package-data] "netCDF4.plugins" = ["lib__nc*"] + +[tool.pytest.ini_options] +pythonpath = ["test"] diff --git a/test/__init__.py b/test/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/test/filter_availability.py b/test/filter_availability.py new file mode 100644 index 000000000..c1572485c --- /dev/null +++ b/test/filter_availability.py @@ -0,0 +1,20 @@ +from tempfile import NamedTemporaryFile +from netCDF4 import ( + Dataset, + __has_zstandard_support__, + __has_bzip2_support__, + __has_blosc_support__, + __has_szip_support__, +) +import os + +# True if plugins have been disabled +no_plugins = os.getenv("NO_PLUGINS") + + +with NamedTemporaryFile(suffix=".nc", delete=False) as tf: + with Dataset(tf.name, "w") as nc: + has_zstd_filter = __has_zstandard_support__ and nc.has_zstd_filter() + has_bzip2_filter = __has_bzip2_support__ and nc.has_bzip2_filter() + has_blosc_filter = __has_blosc_support__ and nc.has_blosc_filter() + has_szip_filter = __has_szip_support__ and nc.has_szip_filter() diff --git a/test/run_all.py b/test/run_all.py index 91c4b54ea..641137b53 100755 --- a/test/run_all.py +++ b/test/run_all.py @@ -1,66 +1,13 @@ import glob, os, sys, unittest, struct, tempfile -from netCDF4 import getlibversion,__hdf5libversion__,__netcdf4libversion__,__version__, Dataset -from netCDF4 import __has_cdf5_format__, __has_nc_inq_path__, __has_nc_create_mem__, \ - __has_parallel4_support__, __has_pnetcdf_support__, \ - __has_zstandard_support__, __has_bzip2_support__, \ - __has_blosc_support__,__has_quantization_support__,\ - __has_szip_support__ - +from netCDF4 import __hdf5libversion__,__netcdf4libversion__,__version__, Dataset # can also just run # python -m unittest discover . 'tst*py' # Find all test files. test_files = glob.glob('tst_*.py') -if __netcdf4libversion__ < '4.2.1' or __has_parallel4_support__ or __has_pnetcdf_support__: - test_files.remove('tst_diskless.py') - sys.stdout.write('not running tst_diskless.py ...\n') -if not __has_nc_inq_path__: - test_files.remove('tst_filepath.py') - sys.stdout.write('not running tst_filepath.py ...\n') -if not __has_nc_create_mem__: - test_files.remove('tst_create_mem.py') - sys.stdout.write('not running tst_create_mem.py ...\n') -if not __has_cdf5_format__ or struct.calcsize("P") < 8: - test_files.remove('tst_cdf5.py') - sys.stdout.write('not running tst_cdf5.py ...\n') -if not __has_quantization_support__: - test_files.remove('tst_compression_quant.py') - sys.stdout.write('not running tst_compression_quant.py ...\n') -filename = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name -nc = Dataset(filename,'w') -if not __has_zstandard_support__ or os.getenv('NO_PLUGINS') or not nc.has_zstd_filter(): - test_files.remove('tst_compression_zstd.py') - sys.stdout.write('not running tst_compression_zstd.py ...\n') -if not __has_bzip2_support__ or os.getenv('NO_PLUGINS') or not nc.has_bzip2_filter(): - test_files.remove('tst_compression_bzip2.py') - sys.stdout.write('not running tst_compression_bzip2.py ...\n') -if not __has_blosc_support__ or os.getenv('NO_PLUGINS') or not nc.has_blosc_filter(): - test_files.remove('tst_compression_blosc.py') - sys.stdout.write('not running tst_compression_blosc.py ...\n') -if not __has_szip_support__ or not nc.has_szip_filter(): - test_files.remove('tst_compression_szip.py') - sys.stdout.write('not running tst_compression_szip.py ...\n') -nc.close() -os.remove(filename) - -# Don't run tests that require network connectivity -if os.getenv('NO_NET'): - test_files.remove('tst_dap.py'); - sys.stdout.write('not running tst_dap.py ...\n') -else: - # run opendap test first (issue #856). - test_files.remove('tst_dap.py') - test_files.insert(0,'tst_dap.py') - -# Don't run CDL test (that requires ncdump/ncgen) -if os.getenv('NO_CDL'): - test_files.remove('tst_cdl.py'); - sys.stdout.write('not running tst_cdl.py ...\n') - -# Don't run computationally intensive test -if not os.getenv('MEMORY_LEAK_TEST'): - test_files.remove('tst_multiple_open_close.py'); - sys.stdout.write('not running tst_multiple_open_close.py ...\n') +# run opendap test first (issue #856). +test_files.remove('tst_dap.py') +test_files.insert(0,'tst_dap.py') # Build the test suite from the tests found in the test files. testsuite = unittest.TestSuite() diff --git a/test/tst_cdf5.py b/test/tst_cdf5.py index 0710d183a..41a9776ec 100644 --- a/test/tst_cdf5.py +++ b/test/tst_cdf5.py @@ -1,6 +1,7 @@ -from netCDF4 import Dataset +from netCDF4 import Dataset, __has_cdf5_format__ import numpy as np import sys, os, unittest, tempfile +import struct from numpy.testing import assert_array_equal FILE_NAME = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name @@ -8,8 +9,9 @@ ndim = 100 arrdata = np.random.randint(np.iinfo(np.uint8).min,np.iinfo(np.uint8).max,size=ndim) -class test_cdf5(unittest.TestCase): +@unittest.skipIf(not __has_cdf5_format__ or struct.calcsize("P") < 8, "no CDF5 support") +class test_cdf5(unittest.TestCase): def setUp(self): self.netcdf_file = FILE_NAME nc = Dataset(self.netcdf_file,'w',format='NETCDF3_64BIT_DATA') diff --git a/test/tst_cdl.py b/test/tst_cdl.py index 16203485e..e7661871e 100644 --- a/test/tst_cdl.py +++ b/test/tst_cdl.py @@ -38,6 +38,8 @@ } """ + +@unittest.skipIf(os.getenv("NO_CDL"), "CDL test disabled") class Test_CDL(unittest.TestCase): """ Test import/export of CDL diff --git a/test/tst_compression_blosc.py b/test/tst_compression_blosc.py index 5b45c1857..57d8e0f56 100644 --- a/test/tst_compression_blosc.py +++ b/test/tst_compression_blosc.py @@ -2,6 +2,8 @@ from netCDF4 import Dataset from numpy.testing import assert_almost_equal import os, tempfile, unittest, sys +from filter_availability import no_plugins, has_blosc_filter + ndim = 100000 iblosc_shuffle=2 @@ -31,8 +33,9 @@ def write_netcdf(filename,dtype='f8',blosc_shuffle=1,complevel=6): foo_zstd[:] = datarr nc.close() -class CompressionTestCase(unittest.TestCase): +@unittest.skipIf(no_plugins or not has_blosc_filter, "blosc filter not available") +class CompressionTestCase(unittest.TestCase): def setUp(self): self.filename = filename write_netcdf(self.filename,complevel=iblosc_complevel,blosc_shuffle=iblosc_shuffle) @@ -73,10 +76,6 @@ def runTest(self): assert f.variables['data_zstd'].filters() == dtest f.close() + if __name__ == '__main__': - nc = Dataset(filename,'w') - if not nc.has_blosc_filter(): - sys.stdout.write('blosc filter not available, skipping tests ...\n') - else: - nc.close() - unittest.main() + unittest.main() diff --git a/test/tst_compression_bzip2.py b/test/tst_compression_bzip2.py index 22149b60e..fb0bd3162 100644 --- a/test/tst_compression_bzip2.py +++ b/test/tst_compression_bzip2.py @@ -2,6 +2,7 @@ from netCDF4 import Dataset from numpy.testing import assert_almost_equal import os, tempfile, unittest, sys +from filter_availability import no_plugins, has_bzip2_filter ndim = 100000 filename1 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name @@ -16,8 +17,9 @@ def write_netcdf(filename,dtype='f8',complevel=6): foo[:] = array nc.close() -class CompressionTestCase(unittest.TestCase): +@unittest.skipIf(no_plugins or not has_bzip2_filter, "bzip2 filter not available") +class CompressionTestCase(unittest.TestCase): def setUp(self): self.filename1 = filename1 self.filename2 = filename2 @@ -48,10 +50,6 @@ def runTest(self): assert(size < 0.96*uncompressed_size) f.close() + if __name__ == '__main__': - nc = Dataset(filename1,'w') - if not nc.has_bzip2_filter(): - sys.stdout.write('bzip2 filter not available, skipping tests ...\n') - else: - nc.close() - unittest.main() + unittest.main() diff --git a/test/tst_compression_quant.py b/test/tst_compression_quant.py index 898f84f71..10c801592 100644 --- a/test/tst_compression_quant.py +++ b/test/tst_compression_quant.py @@ -1,5 +1,5 @@ from numpy.random.mtrand import uniform -from netCDF4 import Dataset +from netCDF4 import Dataset, __has_quantization_support__ from numpy.testing import assert_almost_equal import numpy as np import os, tempfile, unittest @@ -25,8 +25,9 @@ def write_netcdf(filename,zlib,significant_digits,data,dtype='f8',shuffle=False, data = file.variables['data'][:] file.close() -class CompressionTestCase(unittest.TestCase): +@unittest.skipIf(not __has_quantization_support__, "missing quantisation support") +class CompressionTestCase(unittest.TestCase): def setUp(self): self.files = files # no compression diff --git a/test/tst_compression_szip.py b/test/tst_compression_szip.py index 3dc3cb8db..b77f411c6 100644 --- a/test/tst_compression_szip.py +++ b/test/tst_compression_szip.py @@ -2,6 +2,7 @@ from netCDF4 import Dataset from numpy.testing import assert_almost_equal import os, tempfile, unittest, sys +from filter_availability import has_szip_filter ndim = 100000 filename = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name @@ -18,8 +19,9 @@ def write_netcdf(filename,dtype='f8'): foo_szip[:] = datarr nc.close() -class CompressionTestCase(unittest.TestCase): +@unittest.skipIf(not has_szip_filter, "szip filter not available") +class CompressionTestCase(unittest.TestCase): def setUp(self): self.filename = filename write_netcdf(self.filename) @@ -38,10 +40,6 @@ def runTest(self): assert f.variables['data_szip'].filters() == dtest f.close() + if __name__ == '__main__': - nc = Dataset(filename,'w') - if not nc.has_szip_filter(): - sys.stdout.write('szip filter not available, skipping tests ...\n') - else: - nc.close() - unittest.main() + unittest.main() diff --git a/test/tst_compression_zstd.py b/test/tst_compression_zstd.py index 1971dbfa6..dfbccfc4c 100644 --- a/test/tst_compression_zstd.py +++ b/test/tst_compression_zstd.py @@ -2,6 +2,7 @@ from netCDF4 import Dataset from numpy.testing import assert_almost_equal import os, tempfile, unittest, sys +from filter_availability import no_plugins, has_zstd_filter ndim = 100000 filename1 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name @@ -16,8 +17,9 @@ def write_netcdf(filename,dtype='f8',complevel=6): foo[:] = array nc.close() -class CompressionTestCase(unittest.TestCase): +@unittest.skipIf(no_plugins or not has_zstd_filter, "zstd filter not available") +class CompressionTestCase(unittest.TestCase): def setUp(self): self.filename1 = filename1 self.filename2 = filename2 @@ -49,9 +51,4 @@ def runTest(self): f.close() if __name__ == '__main__': - nc = Dataset(filename1,'w') - if not nc.has_zstd_filter(): - sys.stdout.write('zstd filter not available, skipping tests ...\n') - else: - nc.close() - unittest.main() + unittest.main() diff --git a/test/tst_create_mem.py b/test/tst_create_mem.py index 1de542741..9bc99fca7 100644 --- a/test/tst_create_mem.py +++ b/test/tst_create_mem.py @@ -3,6 +3,8 @@ import numpy as np from numpy.testing import assert_array_equal + +@unittest.skipIf(not netCDF4.__has_nc_create_mem__, "missing `nc_create_mem`") class TestCreateMem(unittest.TestCase): def test_mem_create(self): def check_inmemory(format): diff --git a/test/tst_dap.py b/test/tst_dap.py index 2b033e93a..9e337b9c5 100644 --- a/test/tst_dap.py +++ b/test/tst_dap.py @@ -3,6 +3,7 @@ import numpy as np from datetime import datetime, timedelta from numpy.testing import assert_array_almost_equal +import os # test accessing data over http with opendap. @@ -13,8 +14,9 @@ data_min = -40; data_max = 5900 varshape = (181, 360) -class DapTestCase(unittest.TestCase): +@unittest.skipIf(os.getenv("NO_NET"), "network tests disabled") +class DapTestCase(unittest.TestCase): def setUp(self): pass diff --git a/test/tst_diskless.py b/test/tst_diskless.py index a96a0c8a9..898d345fb 100644 --- a/test/tst_diskless.py +++ b/test/tst_diskless.py @@ -15,8 +15,14 @@ FILE_NAME = tempfile.NamedTemporaryFile(suffix='.nc', delete=True).name FILE_NAME2 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name -class DisklessTestCase(unittest.TestCase): +@unittest.skipIf( + netCDF4.__netcdf4libversion__ < "4.2.1" + or netCDF4.__has_parallel4_support__ + or netCDF4.__has_pnetcdf_support__, + "no diskless support", +) +class DisklessTestCase(unittest.TestCase): def setUp(self): # in memory file, does not exist on disk (closing it # makes data disappear from memory) diff --git a/test/tst_filepath.py b/test/tst_filepath.py index b288a06fd..077adcdc2 100644 --- a/test/tst_filepath.py +++ b/test/tst_filepath.py @@ -4,8 +4,8 @@ import netCDF4 +@unittest.skipIf(not netCDF4.__has_nc_inq_path__, "missing `nc_inq_path`") class test_filepath(unittest.TestCase): - def setUp(self): self.netcdf_file = os.path.join(os.getcwd(), "netcdf_dummy_file.nc") self.nc = netCDF4.Dataset(self.netcdf_file) diff --git a/test/tst_multiple_open_close.py b/test/tst_multiple_open_close.py index 46647d0b3..8ba1460b7 100644 --- a/test/tst_multiple_open_close.py +++ b/test/tst_multiple_open_close.py @@ -4,9 +4,11 @@ import netCDF4 -class MultipleVariablesByAttributesCallsTests(unittest.TestCase): - +@unittest.skipUnless( + os.getenv("MEMORY_LEAK_TEST"), "computationally intensive test not enabled" +) +class MultipleVariablesByAttributesCallsTests(unittest.TestCase): def test_multiple_calls(self): netcdf_file = os.path.join(os.path.dirname(__file__), "netcdf_dummy_file.nc") tracemalloc.start() From e54ad9c043bf7df7975d281b55f9fe342888e323 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Mon, 6 Nov 2023 11:48:49 +0000 Subject: [PATCH 1050/1504] Fix test filename paths to not require running directly in `test` --- test/tst_Unsigned.py | 60 +++++++++++++++++++++++--------------------- test/tst_atts.py | 6 ++--- test/tst_cdl.py | 40 ++++++++++++++++------------- test/tst_filepath.py | 6 ++++- test/tst_issue908.py | 5 ++-- test/tst_masked.py | 6 ++--- test/tst_masked4.py | 24 +++++++++--------- 7 files changed, 81 insertions(+), 66 deletions(-) diff --git a/test/tst_Unsigned.py b/test/tst_Unsigned.py index ffa69d61d..e2999fe59 100644 --- a/test/tst_Unsigned.py +++ b/test/tst_Unsigned.py @@ -2,6 +2,10 @@ import netCDF4 from numpy.testing import assert_array_equal import numpy as np +import pathlib + +test_dir = pathlib.Path(__file__).parent + class Test_Unsigned(unittest.TestCase): """ @@ -13,38 +17,38 @@ class Test_Unsigned(unittest.TestCase): See issue #656 (pull request #658). """ def test_unsigned(self): - f = netCDF4.Dataset("ubyte.nc") - data = f['ub'][:] - assert data.dtype.str[1:] == 'u1' - assert_array_equal(data,np.array([0,255],np.uint8)) - f.set_auto_scale(False) - data2 = f['ub'][:] - assert data2.dtype.str[1:] == 'i1' - assert_array_equal(data2,np.array([0,-1],np.int8)) - data = f['sb'][:] - assert data.dtype.str[1:] == 'i1' - # issue #1232 _Unsigned='false' is same as not having _Unsigned set. - data = f['sb2'][:] - assert data.dtype.str[1:] == 'i1' - f.close() + with netCDF4.Dataset(test_dir / "ubyte.nc") as f: + data = f['ub'][:] + assert data.dtype.str[1:] == 'u1' + assert_array_equal(data,np.array([0,255],np.uint8)) + f.set_auto_scale(False) + data2 = f['ub'][:] + assert data2.dtype.str[1:] == 'i1' + assert_array_equal(data2,np.array([0,-1],np.int8)) + data = f['sb'][:] + assert data.dtype.str[1:] == 'i1' + # issue #1232 _Unsigned='false' is same as not having _Unsigned set. + data = f['sb2'][:] + assert data.dtype.str[1:] == 'i1' + # issue 671 - f = netCDF4.Dataset('issue671.nc') - data1 = f['soil_moisture'][:] - assert(np.ma.isMA(data1)) - f.set_auto_scale(False) - data2 = f['soil_moisture'][:] - assert(data1.mask.sum() == data2.mask.sum()) - f.close() + with netCDF4.Dataset(test_dir / "issue671.nc") as f: + data1 = f['soil_moisture'][:] + assert(np.ma.isMA(data1)) + f.set_auto_scale(False) + data2 = f['soil_moisture'][:] + assert(data1.mask.sum() == data2.mask.sum()) + # issue 794 # test that valid_min/valid_max/_FillValue are # treated as unsigned integers. - f=netCDF4.Dataset('20171025_2056.Cloud_Top_Height.nc') - data = f['HT'][:] - assert(data.mask.sum() == 57432) - assert(int(data.max()) == 15430) - assert(int(data.min()) == 0) - assert(data.dtype == np.float32) - f.close() + with netCDF4.Dataset(test_dir / "20171025_2056.Cloud_Top_Height.nc") as f: + data = f['HT'][:] + assert(data.mask.sum() == 57432) + assert(int(data.max()) == 15430) + assert(int(data.min()) == 0) + assert(data.dtype == np.float32) + if __name__ == '__main__': unittest.main() diff --git a/test/tst_atts.py b/test/tst_atts.py index e890774c0..0e9a6fafa 100644 --- a/test/tst_atts.py +++ b/test/tst_atts.py @@ -5,6 +5,7 @@ import os import tempfile import warnings +import pathlib import numpy as np from collections import OrderedDict @@ -219,9 +220,8 @@ def runTest(self): assert getattr(v1,'nonexistantatt',None) == None # issue 915 empty string attribute (ncdump reports 'NIL') - f = netCDF4.Dataset('test_gold.nc') - assert f['RADIANCE'].VAR_NOTES == "" - f.close() + with netCDF4.Dataset(pathlib.Path(__file__).parent / "test_gold.nc") as f: + assert f['RADIANCE'].VAR_NOTES == "" if __name__ == '__main__': unittest.main() diff --git a/test/tst_cdl.py b/test/tst_cdl.py index e7661871e..4ee4da3c0 100644 --- a/test/tst_cdl.py +++ b/test/tst_cdl.py @@ -1,6 +1,7 @@ import unittest import netCDF4 import os +import pathlib test_ncdump="""netcdf ubyte { dimensions: @@ -39,32 +40,37 @@ """ +ubyte_filename = pathlib.Path(__file__).parent / "ubyte.nc" + + @unittest.skipIf(os.getenv("NO_CDL"), "CDL test disabled") class Test_CDL(unittest.TestCase): """ Test import/export of CDL """ + def setUp(self): - f=netCDF4.Dataset('ubyte.nc') - f.tocdl(outfile='ubyte.cdl',data=True) - f.close() + with netCDF4.Dataset(ubyte_filename) as f: + f.tocdl(outfile="ubyte.cdl", data=True) + def test_tocdl(self): # treated as unsigned integers. - f=netCDF4.Dataset('ubyte.nc') - assert(f.tocdl() == test_ncdump) - assert(f.tocdl(data=True) == test_ncdump2) - f.close() + with netCDF4.Dataset(ubyte_filename) as f: + assert f.tocdl() == test_ncdump + assert f.tocdl(data=True) == test_ncdump2 + def test_fromcdl(self): - f1=netCDF4.Dataset.fromcdl('ubyte.cdl',ncfilename='ubyte2.nc') - f2=netCDF4.Dataset('ubyte.nc') - assert(f1.variables.keys() == f2.variables.keys()) - assert(f1.filepath() == 'ubyte2.nc') - assert(f1.dimensions.keys() == f2.dimensions.keys()) - assert(len(f1.dimensions['d']) == len(f2.dimensions['d'])) - assert((f1['ub'][:] == f2['ub'][:]).all()) - assert((f1['sb'][:] == f2['sb'][:]).all()) - f1.close(); f2.close() - os.remove('ubyte2.nc') + with netCDF4.Dataset.fromcdl("ubyte.cdl", ncfilename="ubyte2.nc") as f1: + with netCDF4.Dataset(ubyte_filename) as f2: + assert f1.variables.keys() == f2.variables.keys() + assert f1.filepath() == "ubyte2.nc" + assert f1.dimensions.keys() == f2.dimensions.keys() + assert len(f1.dimensions["d"]) == len(f2.dimensions["d"]) + assert (f1["ub"][:] == f2["ub"][:]).all() + assert (f1["sb"][:] == f2["sb"][:]).all() + + os.remove("ubyte2.nc") + def tearDown(self): # Remove the temporary files os.remove('ubyte.cdl') diff --git a/test/tst_filepath.py b/test/tst_filepath.py index 077adcdc2..940a38f7b 100644 --- a/test/tst_filepath.py +++ b/test/tst_filepath.py @@ -2,14 +2,18 @@ import tempfile import unittest import netCDF4 +import pathlib @unittest.skipIf(not netCDF4.__has_nc_inq_path__, "missing `nc_inq_path`") class test_filepath(unittest.TestCase): def setUp(self): - self.netcdf_file = os.path.join(os.getcwd(), "netcdf_dummy_file.nc") + self.netcdf_file = pathlib.Path(__file__).parent / "netcdf_dummy_file.nc" self.nc = netCDF4.Dataset(self.netcdf_file) + def tearDown(self): + self.nc.close() + def test_filepath(self): assert self.nc.filepath() == str(self.netcdf_file) diff --git a/test/tst_issue908.py b/test/tst_issue908.py index 4d6200150..d07746dff 100644 --- a/test/tst_issue908.py +++ b/test/tst_issue908.py @@ -1,11 +1,12 @@ import netCDF4, unittest import numpy as np +import pathlib + class Issue908TestCase(unittest.TestCase): def setUp(self): - nc = netCDF4.Dataset('CRM032_test1.nc') - self.nc = nc + self.nc = netCDF4.Dataset(pathlib.Path(__file__).parent / "CRM032_test1.nc") def tearDown(self): self.nc.close() diff --git a/test/tst_masked.py b/test/tst_masked.py index d2d411fdc..0794ecded 100644 --- a/test/tst_masked.py +++ b/test/tst_masked.py @@ -8,6 +8,7 @@ from numpy.random.mtrand import uniform import netCDF4 from numpy.ma import masked_all +import pathlib # test automatic conversion of masked arrays, and # packing/unpacking of short ints. @@ -91,9 +92,8 @@ def setUp(self): # be cast to the variable type, issue a warning instead # of raising an exception when auto-converted slice to a # masked array - dataset = netCDF4.Dataset('issue1152.nc') - data = dataset['v'][:] - dataset.close() + with netCDF4.Dataset(pathlib.Path(__file__).parent / "issue1152.nc") as dataset: + data = dataset['v'][:] # issue #1271 (mask is ignored when assigning bool array to uint8 var) ds = netCDF4.Dataset(self.file3, "w") diff --git a/test/tst_masked4.py b/test/tst_masked4.py index 6203acea1..d2649958d 100755 --- a/test/tst_masked4.py +++ b/test/tst_masked4.py @@ -1,6 +1,7 @@ import unittest import os import tempfile +import pathlib import numpy as np from numpy import ma @@ -106,18 +107,17 @@ def test_scaled(self): f.close() # issue 672 - f = Dataset('issue672.nc') - field = 'azi_angle_trip' - v = f.variables[field] - data1 = v[:] - v.set_auto_scale(False) - data2 = v[:] - v.set_auto_maskandscale(False) - data3 = v[:] - assert(data1[(data3 < v.valid_min)].mask.sum() == 12) - assert(data2[(data3 < v.valid_min)].mask.sum() == - data1[(data3 < v.valid_min)].mask.sum()) - f.close() + with Dataset(pathlib.Path(__file__).parent / "issue672.nc") as f: + field = 'azi_angle_trip' + v = f.variables[field] + data1 = v[:] + v.set_auto_scale(False) + data2 = v[:] + v.set_auto_maskandscale(False) + data3 = v[:] + assert(data1[(data3 < v.valid_min)].mask.sum() == 12) + assert(data2[(data3 < v.valid_min)].mask.sum() == + data1[(data3 < v.valid_min)].mask.sum()) if __name__ == '__main__': From 66cde642f48f6799cb603df2ff642c09bec0e3e2 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Mon, 6 Nov 2023 11:54:39 +0000 Subject: [PATCH 1051/1504] Rename test files to aid discoverability by pytest --- test/run_all.py | 6 +++--- test/{tst_Unsigned.py => test_Unsigned.py} | 0 test/{tst_alignment.py => test_alignment.py} | 0 test/{tst_atts.py => test_atts.py} | 0 test/{tst_cdf5.py => test_cdf5.py} | 0 test/{tst_cdl.py => test_cdl.py} | 0 test/{tst_chunk_cache.py => test_chunk_cache.py} | 0 ...tst_compound_alignment.py => test_compound_alignment.py} | 0 test/{tst_compoundatt.py => test_compoundatt.py} | 0 test/{tst_compoundvar.py => test_compoundvar.py} | 0 test/{tst_compression.py => test_compression.py} | 0 .../{tst_compression_blosc.py => test_compression_blosc.py} | 0 .../{tst_compression_bzip2.py => test_compression_bzip2.py} | 0 .../{tst_compression_quant.py => test_compression_quant.py} | 0 test/{tst_compression_szip.py => test_compression_szip.py} | 0 test/{tst_compression_zstd.py => test_compression_zstd.py} | 0 test/{tst_create_mem.py => test_create_mem.py} | 0 test/{tst_dap.py => test_dap.py} | 0 test/{tst_dims.py => test_dims.py} | 0 test/{tst_diskless.py => test_diskless.py} | 0 test/{tst_endian.py => test_endian.py} | 0 test/{tst_enum.py => test_enum.py} | 0 test/{tst_fancyslicing.py => test_fancyslicing.py} | 0 test/{tst_filepath.py => test_filepath.py} | 0 ...by_attributes.py => test_get_variables_by_attributes.py} | 0 test/{tst_grps.py => test_grps.py} | 0 test/{tst_grps2.py => test_grps2.py} | 0 test/{tst_issue908.py => test_issue908.py} | 0 test/{tst_masked.py => test_masked.py} | 0 test/{tst_masked2.py => test_masked2.py} | 0 test/{tst_masked3.py => test_masked3.py} | 0 test/{tst_masked4.py => test_masked4.py} | 0 test/{tst_masked5.py => test_masked5.py} | 0 test/{tst_masked6.py => test_masked6.py} | 0 test/{tst_multifile.py => test_multifile.py} | 0 test/{tst_multifile2.py => test_multifile2.py} | 0 ...t_multiple_open_close.py => test_multiple_open_close.py} | 0 test/{tst_open_mem.py => test_open_mem.py} | 0 test/{tst_refcount.py => test_refcount.py} | 0 test/{tst_rename.py => test_rename.py} | 0 test/{tst_scalarvar.py => test_scalarvar.py} | 0 test/{tst_scaled.py => test_scaled.py} | 0 test/{tst_shape.py => test_shape.py} | 0 test/{tst_slicing.py => test_slicing.py} | 0 test/{tst_stringarr.py => test_stringarr.py} | 0 test/{tst_types.py => test_types.py} | 0 test/{tst_unicode.py => test_unicode.py} | 0 test/{tst_unicodeatt.py => test_unicodeatt.py} | 0 test/{tst_unlimdim.py => test_unlimdim.py} | 0 test/{tst_utils.py => test_utils.py} | 0 test/{tst_vars.py => test_vars.py} | 0 test/{tst_vlen.py => test_vlen.py} | 0 52 files changed, 3 insertions(+), 3 deletions(-) rename test/{tst_Unsigned.py => test_Unsigned.py} (100%) rename test/{tst_alignment.py => test_alignment.py} (100%) rename test/{tst_atts.py => test_atts.py} (100%) rename test/{tst_cdf5.py => test_cdf5.py} (100%) rename test/{tst_cdl.py => test_cdl.py} (100%) rename test/{tst_chunk_cache.py => test_chunk_cache.py} (100%) rename test/{tst_compound_alignment.py => test_compound_alignment.py} (100%) rename test/{tst_compoundatt.py => test_compoundatt.py} (100%) rename test/{tst_compoundvar.py => test_compoundvar.py} (100%) rename test/{tst_compression.py => test_compression.py} (100%) rename test/{tst_compression_blosc.py => test_compression_blosc.py} (100%) rename test/{tst_compression_bzip2.py => test_compression_bzip2.py} (100%) rename test/{tst_compression_quant.py => test_compression_quant.py} (100%) rename test/{tst_compression_szip.py => test_compression_szip.py} (100%) rename test/{tst_compression_zstd.py => test_compression_zstd.py} (100%) rename test/{tst_create_mem.py => test_create_mem.py} (100%) rename test/{tst_dap.py => test_dap.py} (100%) rename test/{tst_dims.py => test_dims.py} (100%) rename test/{tst_diskless.py => test_diskless.py} (100%) rename test/{tst_endian.py => test_endian.py} (100%) rename test/{tst_enum.py => test_enum.py} (100%) rename test/{tst_fancyslicing.py => test_fancyslicing.py} (100%) rename test/{tst_filepath.py => test_filepath.py} (100%) rename test/{tst_get_variables_by_attributes.py => test_get_variables_by_attributes.py} (100%) rename test/{tst_grps.py => test_grps.py} (100%) rename test/{tst_grps2.py => test_grps2.py} (100%) rename test/{tst_issue908.py => test_issue908.py} (100%) rename test/{tst_masked.py => test_masked.py} (100%) rename test/{tst_masked2.py => test_masked2.py} (100%) rename test/{tst_masked3.py => test_masked3.py} (100%) rename test/{tst_masked4.py => test_masked4.py} (100%) rename test/{tst_masked5.py => test_masked5.py} (100%) rename test/{tst_masked6.py => test_masked6.py} (100%) rename test/{tst_multifile.py => test_multifile.py} (100%) rename test/{tst_multifile2.py => test_multifile2.py} (100%) rename test/{tst_multiple_open_close.py => test_multiple_open_close.py} (100%) rename test/{tst_open_mem.py => test_open_mem.py} (100%) rename test/{tst_refcount.py => test_refcount.py} (100%) rename test/{tst_rename.py => test_rename.py} (100%) rename test/{tst_scalarvar.py => test_scalarvar.py} (100%) rename test/{tst_scaled.py => test_scaled.py} (100%) rename test/{tst_shape.py => test_shape.py} (100%) rename test/{tst_slicing.py => test_slicing.py} (100%) rename test/{tst_stringarr.py => test_stringarr.py} (100%) rename test/{tst_types.py => test_types.py} (100%) rename test/{tst_unicode.py => test_unicode.py} (100%) rename test/{tst_unicodeatt.py => test_unicodeatt.py} (100%) rename test/{tst_unlimdim.py => test_unlimdim.py} (100%) rename test/{tst_utils.py => test_utils.py} (100%) rename test/{tst_vars.py => test_vars.py} (100%) rename test/{tst_vlen.py => test_vlen.py} (100%) diff --git a/test/run_all.py b/test/run_all.py index 641137b53..705cc6520 100755 --- a/test/run_all.py +++ b/test/run_all.py @@ -4,10 +4,10 @@ # python -m unittest discover . 'tst*py' # Find all test files. -test_files = glob.glob('tst_*.py') +test_files = glob.glob('test_*.py') # run opendap test first (issue #856). -test_files.remove('tst_dap.py') -test_files.insert(0,'tst_dap.py') +test_files.remove('test_dap.py') +test_files.insert(0,'test_dap.py') # Build the test suite from the tests found in the test files. testsuite = unittest.TestSuite() diff --git a/test/tst_Unsigned.py b/test/test_Unsigned.py similarity index 100% rename from test/tst_Unsigned.py rename to test/test_Unsigned.py diff --git a/test/tst_alignment.py b/test/test_alignment.py similarity index 100% rename from test/tst_alignment.py rename to test/test_alignment.py diff --git a/test/tst_atts.py b/test/test_atts.py similarity index 100% rename from test/tst_atts.py rename to test/test_atts.py diff --git a/test/tst_cdf5.py b/test/test_cdf5.py similarity index 100% rename from test/tst_cdf5.py rename to test/test_cdf5.py diff --git a/test/tst_cdl.py b/test/test_cdl.py similarity index 100% rename from test/tst_cdl.py rename to test/test_cdl.py diff --git a/test/tst_chunk_cache.py b/test/test_chunk_cache.py similarity index 100% rename from test/tst_chunk_cache.py rename to test/test_chunk_cache.py diff --git a/test/tst_compound_alignment.py b/test/test_compound_alignment.py similarity index 100% rename from test/tst_compound_alignment.py rename to test/test_compound_alignment.py diff --git a/test/tst_compoundatt.py b/test/test_compoundatt.py similarity index 100% rename from test/tst_compoundatt.py rename to test/test_compoundatt.py diff --git a/test/tst_compoundvar.py b/test/test_compoundvar.py similarity index 100% rename from test/tst_compoundvar.py rename to test/test_compoundvar.py diff --git a/test/tst_compression.py b/test/test_compression.py similarity index 100% rename from test/tst_compression.py rename to test/test_compression.py diff --git a/test/tst_compression_blosc.py b/test/test_compression_blosc.py similarity index 100% rename from test/tst_compression_blosc.py rename to test/test_compression_blosc.py diff --git a/test/tst_compression_bzip2.py b/test/test_compression_bzip2.py similarity index 100% rename from test/tst_compression_bzip2.py rename to test/test_compression_bzip2.py diff --git a/test/tst_compression_quant.py b/test/test_compression_quant.py similarity index 100% rename from test/tst_compression_quant.py rename to test/test_compression_quant.py diff --git a/test/tst_compression_szip.py b/test/test_compression_szip.py similarity index 100% rename from test/tst_compression_szip.py rename to test/test_compression_szip.py diff --git a/test/tst_compression_zstd.py b/test/test_compression_zstd.py similarity index 100% rename from test/tst_compression_zstd.py rename to test/test_compression_zstd.py diff --git a/test/tst_create_mem.py b/test/test_create_mem.py similarity index 100% rename from test/tst_create_mem.py rename to test/test_create_mem.py diff --git a/test/tst_dap.py b/test/test_dap.py similarity index 100% rename from test/tst_dap.py rename to test/test_dap.py diff --git a/test/tst_dims.py b/test/test_dims.py similarity index 100% rename from test/tst_dims.py rename to test/test_dims.py diff --git a/test/tst_diskless.py b/test/test_diskless.py similarity index 100% rename from test/tst_diskless.py rename to test/test_diskless.py diff --git a/test/tst_endian.py b/test/test_endian.py similarity index 100% rename from test/tst_endian.py rename to test/test_endian.py diff --git a/test/tst_enum.py b/test/test_enum.py similarity index 100% rename from test/tst_enum.py rename to test/test_enum.py diff --git a/test/tst_fancyslicing.py b/test/test_fancyslicing.py similarity index 100% rename from test/tst_fancyslicing.py rename to test/test_fancyslicing.py diff --git a/test/tst_filepath.py b/test/test_filepath.py similarity index 100% rename from test/tst_filepath.py rename to test/test_filepath.py diff --git a/test/tst_get_variables_by_attributes.py b/test/test_get_variables_by_attributes.py similarity index 100% rename from test/tst_get_variables_by_attributes.py rename to test/test_get_variables_by_attributes.py diff --git a/test/tst_grps.py b/test/test_grps.py similarity index 100% rename from test/tst_grps.py rename to test/test_grps.py diff --git a/test/tst_grps2.py b/test/test_grps2.py similarity index 100% rename from test/tst_grps2.py rename to test/test_grps2.py diff --git a/test/tst_issue908.py b/test/test_issue908.py similarity index 100% rename from test/tst_issue908.py rename to test/test_issue908.py diff --git a/test/tst_masked.py b/test/test_masked.py similarity index 100% rename from test/tst_masked.py rename to test/test_masked.py diff --git a/test/tst_masked2.py b/test/test_masked2.py similarity index 100% rename from test/tst_masked2.py rename to test/test_masked2.py diff --git a/test/tst_masked3.py b/test/test_masked3.py similarity index 100% rename from test/tst_masked3.py rename to test/test_masked3.py diff --git a/test/tst_masked4.py b/test/test_masked4.py similarity index 100% rename from test/tst_masked4.py rename to test/test_masked4.py diff --git a/test/tst_masked5.py b/test/test_masked5.py similarity index 100% rename from test/tst_masked5.py rename to test/test_masked5.py diff --git a/test/tst_masked6.py b/test/test_masked6.py similarity index 100% rename from test/tst_masked6.py rename to test/test_masked6.py diff --git a/test/tst_multifile.py b/test/test_multifile.py similarity index 100% rename from test/tst_multifile.py rename to test/test_multifile.py diff --git a/test/tst_multifile2.py b/test/test_multifile2.py similarity index 100% rename from test/tst_multifile2.py rename to test/test_multifile2.py diff --git a/test/tst_multiple_open_close.py b/test/test_multiple_open_close.py similarity index 100% rename from test/tst_multiple_open_close.py rename to test/test_multiple_open_close.py diff --git a/test/tst_open_mem.py b/test/test_open_mem.py similarity index 100% rename from test/tst_open_mem.py rename to test/test_open_mem.py diff --git a/test/tst_refcount.py b/test/test_refcount.py similarity index 100% rename from test/tst_refcount.py rename to test/test_refcount.py diff --git a/test/tst_rename.py b/test/test_rename.py similarity index 100% rename from test/tst_rename.py rename to test/test_rename.py diff --git a/test/tst_scalarvar.py b/test/test_scalarvar.py similarity index 100% rename from test/tst_scalarvar.py rename to test/test_scalarvar.py diff --git a/test/tst_scaled.py b/test/test_scaled.py similarity index 100% rename from test/tst_scaled.py rename to test/test_scaled.py diff --git a/test/tst_shape.py b/test/test_shape.py similarity index 100% rename from test/tst_shape.py rename to test/test_shape.py diff --git a/test/tst_slicing.py b/test/test_slicing.py similarity index 100% rename from test/tst_slicing.py rename to test/test_slicing.py diff --git a/test/tst_stringarr.py b/test/test_stringarr.py similarity index 100% rename from test/tst_stringarr.py rename to test/test_stringarr.py diff --git a/test/tst_types.py b/test/test_types.py similarity index 100% rename from test/tst_types.py rename to test/test_types.py diff --git a/test/tst_unicode.py b/test/test_unicode.py similarity index 100% rename from test/tst_unicode.py rename to test/test_unicode.py diff --git a/test/tst_unicodeatt.py b/test/test_unicodeatt.py similarity index 100% rename from test/tst_unicodeatt.py rename to test/test_unicodeatt.py diff --git a/test/tst_unlimdim.py b/test/test_unlimdim.py similarity index 100% rename from test/tst_unlimdim.py rename to test/test_unlimdim.py diff --git a/test/tst_utils.py b/test/test_utils.py similarity index 100% rename from test/tst_utils.py rename to test/test_utils.py diff --git a/test/tst_vars.py b/test/test_vars.py similarity index 100% rename from test/tst_vars.py rename to test/test_vars.py diff --git a/test/tst_vlen.py b/test/test_vlen.py similarity index 100% rename from test/tst_vlen.py rename to test/test_vlen.py From 6e568b190972cf3bd7fefb8f2ab017985289ee24 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Fri, 27 Oct 2023 14:52:27 +0100 Subject: [PATCH 1052/1504] Add nc_complex submodule --- .gitmodules | 3 +++ external/nc_complex | 1 + setup.py | 12 ++++++++++-- 3 files changed, 14 insertions(+), 2 deletions(-) create mode 100644 .gitmodules create mode 160000 external/nc_complex diff --git a/.gitmodules b/.gitmodules new file mode 100644 index 000000000..7b0ff7c97 --- /dev/null +++ b/.gitmodules @@ -0,0 +1,3 @@ +[submodule "external/nc_complex"] + path = external/nc_complex + url = git@github.com:PlasmaFAIR/nc-complex.git diff --git a/external/nc_complex b/external/nc_complex new file mode 160000 index 000000000..dbeeb080f --- /dev/null +++ b/external/nc_complex @@ -0,0 +1 @@ +Subproject commit dbeeb080ff869ec3c4288d9ab840f0be201e30de diff --git a/setup.py b/setup.py index 31d32ac30..aa8b6eb20 100644 --- a/setup.py +++ b/setup.py @@ -1,5 +1,6 @@ import os, sys, subprocess, glob import os.path as osp +import pathlib import shutil import configparser from setuptools import setup, Extension @@ -411,12 +412,19 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): osp.join("include", "parallel_support_imports.pxi") ) + nc_complex_dir = pathlib.Path("./external/nc_complex") + source_files = [ + netcdf4_src_pyx, + str(nc_complex_dir / "src/nc_complex.c"), + ] + include_dirs = inc_dirs + ["include", str(nc_complex_dir / "include")] + ext_modules = [Extension("netCDF4._netCDF4", - [netcdf4_src_pyx], + source_files, define_macros=DEFINE_MACROS, libraries=libs, library_dirs=lib_dirs, - include_dirs=inc_dirs + ['include'], + include_dirs=include_dirs, runtime_library_dirs=runtime_lib_dirs)] # set language_level directive to 3 for e in ext_modules: From 36c871fe6317ab349d959dace05bc74dfc21bf70 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Mon, 6 Nov 2023 17:49:35 +0000 Subject: [PATCH 1053/1504] Add support for complex numbers --- external/nc_complex | 2 +- include/netCDF4.pxi | 18 +++++ setup.py | 7 +- src/netCDF4/_netCDF4.pyx | 171 +++++++++++++++++++++++++++------------ test/test_complex.py | 65 +++++++++++++++ 5 files changed, 211 insertions(+), 52 deletions(-) create mode 100644 test/test_complex.py diff --git a/external/nc_complex b/external/nc_complex index dbeeb080f..9c2a87703 160000 --- a/external/nc_complex +++ b/external/nc_complex @@ -1 +1 @@ -Subproject commit dbeeb080ff869ec3c4288d9ab840f0be201e30de +Subproject commit 9c2a87703c7612f04097418bbed4978d3be6ef92 diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi index 7bd220274..8d232df8f 100644 --- a/include/netCDF4.pxi +++ b/include/netCDF4.pxi @@ -465,3 +465,21 @@ cdef extern from "netcdf-compat.h": NC_MPIIO NC_MPIPOSIX NC_PNETCDF + + +# Declarations for handling complex numbers +cdef extern from "nc_complex/nc_complex.h": + int pfnc_var_is_complex(int ncid, int varid) nogil + int pfnc_var_is_complex_type(int ncid, int varid) nogil + int pfnc_has_complex_dimension(int ncid, int varid) nogil + int pfnc_get_double_complex_typeid(int ncid, nc_type *nc_typeid) nogil + int pfnc_get_float_complex_typeid(int ncid, nc_type *nc_typeid) nogil + + int pfnc_complex_base_type(int ncid, int nc_typeid, int* base_type_id) nogil + int pfnc_inq_var_complex_base_type(int ncid, int varid, int* nc_typeid) nogil + + int pfnc_inq_varndims (int ncid, int varid, int *ndimsp) nogil + int pfnc_inq_vardimid (int ncid, int varid, int *dimidsp) nogil + + int pfnc_get_vara (int ncid, int varid, size_t *startp, + size_t *countp, void *ip) nogil diff --git a/setup.py b/setup.py index aa8b6eb20..232eedafd 100644 --- a/setup.py +++ b/setup.py @@ -417,7 +417,12 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): netcdf4_src_pyx, str(nc_complex_dir / "src/nc_complex.c"), ] - include_dirs = inc_dirs + ["include", str(nc_complex_dir / "include")] + include_dirs = inc_dirs + [ + "include", + str(nc_complex_dir / "include"), + str(nc_complex_dir / "include/generated_fallbacks"), + ] + DEFINE_MACROS += [("NC_COMPLEX_NO_EXPORT", "1")] ext_modules = [Extension("netCDF4._netCDF4", source_files, diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 5310ff672..c3bf7518c 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1226,6 +1226,7 @@ from .utils import (_StartCountStride, _quantize, _find_dim, _walk_grps, _out_array_shape, _sortbylist, _tostr, _safecast, _is_int) import sys import functools +from typing import Union __version__ = "1.7.0" @@ -1905,15 +1906,17 @@ cdef _get_grps(group): free(grpids) return groups -cdef _get_vars(group): +cdef _get_vars(group, bint auto_complex=False): # Private function to create `Variable` instances for all the # variables in a `Group` or Dataset cdef int ierr, numvars, n, nn, numdims, varid, classp, iendian, _grpid cdef int *varids - cdef int *dimids cdef nc_type xtype cdef char namstring[NC_MAX_NAME+1] cdef char namstring_cmp[NC_MAX_NAME+1] + cdef bint is_complex + cdef nc_type complex_nc_type + # get number of variables in this Group. _grpid = group._grpid with nogil: @@ -1992,43 +1995,47 @@ cdef _get_vars(group): msg="WARNING: variable '%s' has unsupported datatype, skipping .." % name warnings.warn(msg) continue + # get number of dimensions. - with nogil: - ierr = nc_inq_varndims(_grpid, varid, &numdims) - _ensure_nc_success(ierr) - dimids = malloc(sizeof(int) * numdims) - # get dimension ids. - with nogil: - ierr = nc_inq_vardimid(_grpid, varid, dimids) - _ensure_nc_success(ierr) + dimids = _inq_vardimid(_grpid, varid, auto_complex) + # loop over dimensions, retrieve names. # if not found in current group, look in parents. # QUESTION: what if grp1 has a dimension named 'foo' # and so does it's parent - can a variable in grp1 # use the 'foo' dimension from the parent? dimensions = [] - for nn from 0 <= nn < numdims: + for dimid in dimids: grp = group found = False while not found: for key, value in grp.dimensions.items(): - if value._dimid == dimids[nn]: + if value._dimid == dimid: dimensions.append(key) found = True break grp = grp.parent - free(dimids) + # create new variable instance. - dimensions = tuple(_find_dim(group,d) for d in dimensions) + dimensions = tuple(_find_dim(group, d) for d in dimensions) + + if auto_complex and pfnc_var_is_complex(_grpid, varid): + with nogil: + ierr = pfnc_inq_var_complex_base_type(_grpid, varid, &complex_nc_type) + _ensure_nc_success(ierr) + # TODO: proper lookup + datatype = "c16" if complex_nc_type == NC_DOUBLE else "c8" + if endianness == '>': - variables[name] = Variable(group, name, datatype, dimensions, id=varid, endian='big') + variables[name] = Variable(group, name, datatype, dimensions, id=varid, auto_complex=auto_complex, endian='big') elif endianness == '<': - variables[name] = Variable(group, name, datatype, dimensions, id=varid, endian='little') + variables[name] = Variable(group, name, datatype, dimensions, id=varid, auto_complex=auto_complex, endian='little') else: - variables[name] = Variable(group, name, datatype, dimensions, id=varid) + variables[name] = Variable(group, name, datatype, dimensions, id=varid, auto_complex=auto_complex) free(varids) # free pointer holding variable ids. return variables + def _ensure_nc_success(ierr, err_cls=RuntimeError, filename=None, extra_msg=None): # print netcdf error message, raise error. if ierr == NC_NOERR: @@ -2046,6 +2053,50 @@ def _ensure_nc_success(ierr, err_cls=RuntimeError, filename=None, extra_msg=None err_str = f"{err_str}: {extra_msg}" raise err_cls(err_str) + +def dtype_is_complex(dtype: Union[str, CompoundType, numpy.dtype]) -> bool: + # TODO: check numpy.complex128, matching CompoundTypes + return dtype in ("c8", "c16") + + +cdef int _inq_varndims(int ncid, int varid, bint auto_complex): + """Wrapper around `nc_inq_varndims`/`pfnc_inq_varndims` for complex numbers""" + + cdef int ierr = NC_NOERR + cdef int ndims + + if auto_complex: + with nogil: + ierr = pfnc_inq_varndims(ncid, varid, &ndims) + else: + with nogil: + ierr = nc_inq_varndims(ncid, varid, &ndims) + + _ensure_nc_success(ierr) + return ndims + + +cdef _inq_vardimid(int ncid, int varid, bint auto_complex): + """Wrapper around `nc_inq_vardimid`/`pfnc_inq_vardimid` for complex numbers""" + + cdef int ierr = NC_NOERR + cdef int ndims = _inq_varndims(ncid, varid, auto_complex) + cdef int* dimids = malloc(sizeof(int) * ndims) + + if auto_complex: + with nogil: + ierr = pfnc_inq_vardimid(ncid, varid, dimids) + else: + with nogil: + ierr = nc_inq_vardimid(ncid, varid, dimids) + + _ensure_nc_success(ierr) + + result = [dimids[n] for n in range(ndims)] + free(dimids) + return result + + # these are class attributes that # only exist at the python level (not in the netCDF file). @@ -2054,7 +2105,9 @@ _private_atts = \ '_nunlimdim','path','parent','ndim','mask','scale','cmptypes','vltypes','enumtypes','_isprimitive', 'file_format','_isvlen','_isenum','_iscompound','_cmptype','_vltype','_enumtype','name', '__orthogoral_indexing__','keepweakref','_has_lsd', - '_buffer','chartostring','_use_get_vars','_ncstring_attrs__'] + '_buffer','chartostring','_use_get_vars','_ncstring_attrs__', + 'auto_complex' +] cdef class Dataset: """ @@ -2132,12 +2185,12 @@ strings. cdef Py_buffer _buffer cdef public groups, dimensions, variables, disk_format, path, parent,\ file_format, data_model, cmptypes, vltypes, enumtypes, __orthogonal_indexing__, \ - keepweakref, _ncstring_attrs__ + keepweakref, _ncstring_attrs__, auto_complex def __init__(self, filename, mode='r', clobber=True, format='NETCDF4', diskless=False, persist=False, keepweakref=False, memory=None, encoding=None, parallel=False, - comm=None, info=None, **kwargs): + comm=None, info=None, auto_complex=False, **kwargs): """ **`__init__(self, filename, mode="r", clobber=True, diskless=False, persist=False, keepweakref=False, memory=None, encoding=None, @@ -2232,6 +2285,8 @@ strings. **`info`**: MPI_Info object for parallel access. Default `None`, which means MPI_INFO_NULL will be used. Ignored if `parallel=False`. + + **`auto_complex`**: if `True`, then automatically convert complex number types """ cdef int grpid, ierr, numgrps, numdims, numvars, cdef size_t initialsize @@ -2272,6 +2327,7 @@ strings. parmode = NC_MPIIO | _cmode_dict[format] self._inmemory = False + self.auto_complex = auto_complex # mode='x' is the same as mode='w' with clobber=False if mode == "x": @@ -2371,7 +2427,7 @@ strings. # get dimensions in the root group. self.dimensions = _get_dims(self) # get variables in the root Group. - self.variables = _get_vars(self) + self.variables = _get_vars(self, self.auto_complex) # get groups in the root Group. if self.data_model == 'NETCDF4': self.groups = _get_grps(self) @@ -3473,6 +3529,8 @@ Additional read-only class variables: self.keepweakref = parent.keepweakref # propagate _ncstring_attrs__ setting from parent. self._ncstring_attrs__ = parent._ncstring_attrs__ + self.auto_complex = parent.auto_complex + if 'id' in kwargs: self._grpid = kwargs['id'] # get compound, vlen and enum types in this Group. @@ -3480,7 +3538,7 @@ Additional read-only class variables: # get dimensions in this Group. self.dimensions = _get_dims(self) # get variables in this Group. - self.variables = _get_vars(self) + self.variables = _get_vars(self, self.auto_complex) # get groups in this Group. self.groups = _get_grps(self) else: @@ -3739,7 +3797,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. cdef public int _varid, _grpid, _nunlimdim cdef public _name, ndim, dtype, mask, scale, always_mask, chartostring, _isprimitive, \ _iscompound, _isvlen, _isenum, _grp, _cmptype, _vltype, _enumtype,\ - __orthogonal_indexing__, _has_lsd, _use_get_vars, _ncstring_attrs__ + __orthogonal_indexing__, _has_lsd, _use_get_vars, _ncstring_attrs__, auto_complex def __init__(self, grp, name, datatype, dimensions=(), compression=None, zlib=False, @@ -3747,7 +3805,8 @@ behavior is similar to Fortran or Matlab, but different than numpy. blosc_shuffle=1, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, - significant_digits=None,quantize_mode='BitGroom',fill_value=None, chunk_cache=None, **kwargs): + significant_digits=None,quantize_mode='BitGroom',fill_value=None, chunk_cache=None, + auto_complex=False, **kwargs): """ **`__init__(self, group, name, datatype, dimensions=(), compression=None, zlib=False, complevel=4, shuffle=True, szip_coding='nn', szip_pixels_per_block=8, @@ -3889,6 +3948,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. cdef size_t sizep, nelemsp cdef size_t *chunksizesp cdef float preemptionp + cdef int nc_complex_typeid # Extra information for more helpful error messages error_info = f"(variable '{name}', group '{grp.name}')" @@ -3944,10 +4004,24 @@ behavior is similar to Fortran or Matlab, but different than numpy. self._grp = weakref.proxy(grp) else: self._grp = grp - user_type = isinstance(datatype, CompoundType) or \ - isinstance(datatype, VLType) or \ - isinstance(datatype, EnumType) or \ - datatype == str + + # If datatype is complex, convert to compoundtype + self.auto_complex = auto_complex + is_complex = dtype_is_complex(datatype) + if is_complex: + with nogil: + ierr = pfnc_get_double_complex_typeid(self._grpid, &nc_complex_typeid) + _ensure_nc_success(ierr, extra_msg=error_info) + + original_datatype = numpy.dtype(datatype) + datatype = CompoundType(self._grp, "f8, f8", "double_complex", typeid=nc_complex_typeid) + + user_type = ( + is_complex + or isinstance(datatype, (CompoundType, VLType, EnumType)) + or datatype == str + ) + # convert to a real numpy datatype object if necessary. if not user_type and type(datatype) != numpy.dtype: datatype = numpy.dtype(datatype) @@ -4004,7 +4078,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. ierr = nc_inq_type(self._grpid, xtype, namstring, NULL) _ensure_nc_success(ierr, extra_msg=error_info) # dtype variable attribute is a numpy datatype object. - self.dtype = datatype.dtype + self.dtype = original_datatype if is_complex else datatype.dtype elif datatype.str[1:] in _supportedtypes: self._isprimitive = True # find netCDF primitive data type corresponding to @@ -4255,11 +4329,9 @@ behavior is similar to Fortran or Matlab, but different than numpy. self._nunlimdim = 0 for dim in dimensions: if dim.isunlimited(): self._nunlimdim = self._nunlimdim + 1 + # set ndim attribute (number of dimensions). - with nogil: - ierr = nc_inq_varndims(self._grpid, self._varid, &numdims) - _ensure_nc_success(ierr, extra_msg=error_info) - self.ndim = numdims + self.ndim = _inq_varndims(self._grpid, self._varid, auto_complex) self._name = name # default for automatically applying scale_factor and # add_offset, and converting to/from masked arrays is True. @@ -4354,27 +4426,20 @@ behavior is similar to Fortran or Matlab, but different than numpy. def _getdims(self): # Private method to get variables's dimension names - cdef int ierr, numdims, n, nn + cdef int ierr, dimid cdef char namstring[NC_MAX_NAME+1] - cdef int *dimids - # get number of dimensions for this variable. - with nogil: - ierr = nc_inq_varndims(self._grpid, self._varid, &numdims) - _ensure_nc_success(ierr) - dimids = malloc(sizeof(int) * numdims) - # get dimension ids. - with nogil: - ierr = nc_inq_vardimid(self._grpid, self._varid, dimids) - _ensure_nc_success(ierr) + + dimids = _inq_vardimid(self._grpid, self._varid, self.auto_complex) + # loop over dimensions, retrieve names. dimensions = () - for nn from 0 <= nn < numdims: + for dimid in dimids: with nogil: - ierr = nc_inq_dimname(self._grpid, dimids[nn], namstring) + ierr = nc_inq_dimname(self._grpid, dimid, namstring) _ensure_nc_success(ierr) name = namstring.decode('utf-8') dimensions = dimensions + (name,) - free(dimids) + return dimensions def _getname(self): @@ -5778,9 +5843,15 @@ NC_CHAR). # if count contains a zero element, no data is being read if 0 not in count: if sum(stride) == ndims or ndims == 0: - with nogil: - ierr = nc_get_vara(self._grpid, self._varid, - startp, countp, PyArray_DATA(data)) + if self.auto_complex: + with nogil: + ierr = pfnc_get_vara(self._grpid, self._varid, + startp, countp, PyArray_DATA(data)) + else: + with nogil: + ierr = nc_get_vara(self._grpid, self._varid, + startp, countp, PyArray_DATA(data)) + else: with nogil: ierr = nc_get_vars(self._grpid, self._varid, diff --git a/test/test_complex.py b/test/test_complex.py new file mode 100644 index 000000000..8c03953f8 --- /dev/null +++ b/test/test_complex.py @@ -0,0 +1,65 @@ +import netCDF4 +import numpy as np +import pathlib +import tempfile +import unittest + +complex_array = np.array([0 + 0j, 1 + 0j, 0 + 1j, 1 + 1j, 0.25 + 0.75j], dtype="c16") +np_dt = np.dtype([("r", np.float64), ("i", np.float64)]) +complex_struct_array = np.array( + [(r, i) for r, i in zip(complex_array.real, complex_array.imag)], + dtype=np_dt, +) + + +class ComplexNumbersTestCase(unittest.TestCase): + def setUp(self): + self.tmp_path = pathlib.Path(tempfile.mkdtemp()) + + def test_read_dim(self): + filename = self.tmp_path / "test_read_dim.nc" + + with netCDF4.Dataset(filename, "w") as f: + f.createDimension("x", size=len(complex_array)) + f.createDimension("ri", size=2) + c_ri = f.createVariable("data_dim", np.float64, ("x", "ri")) + as_dim_array = np.vstack((complex_array.real, complex_array.imag)).T + c_ri[:] = as_dim_array + + with netCDF4.Dataset(filename, "r", auto_complex=True) as f: + assert "data_dim" in f.variables + data_dim = f["data_dim"] + assert data_dim.shape == complex_array.shape + data = data_dim[:] + + assert np.array_equal(data, complex_array) + + def test_read_struct(self): + filename = self.tmp_path / "test_read_struct.nc" + + with netCDF4.Dataset(filename, "w") as f: + f.createDimension("x", size=len(complex_array)) + nc_dt = f.createCompoundType(np_dt, "nc_complex") + c_struct = f.createVariable("data_struct", nc_dt, ("x",)) + c_struct[:] = complex_struct_array + + with netCDF4.Dataset(filename, "r", auto_complex=True) as f: + assert "data_struct" in f.variables + data = f["data_struct"][:] + + assert np.array_equal(data, complex_array) + + def test_write(self): + filename = self.tmp_path / "test_write.nc" + with netCDF4.Dataset(filename, "w", auto_complex=True) as f: + f.createDimension("x", size=len(complex_array)) + complex_var = f.createVariable("complex_data", "c16", ("x",)) + complex_var[:] = complex_array + + with netCDF4.Dataset(filename, "r") as f: + assert "complex_data" in f.variables + assert np.array_equal(f["complex_data"], complex_struct_array) + + +if __name__ == "__main__": + unittest.main() From 5ac2c6aed0ac24c6b5327a0202d63fc358c8863f Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Tue, 7 Nov 2023 17:10:49 +0000 Subject: [PATCH 1054/1504] Tidy some checks around endianness --- src/netCDF4/_netCDF4.pyx | 69 +++++++++++++++++++++------------------- 1 file changed, 37 insertions(+), 32 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index c3bf7518c..e9ebf0586 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1517,6 +1517,15 @@ _supportedtypes = _nptonctype.keys() # make sure NC_CHAR points to S1 _nctonptype[NC_CHAR]='S1' +# Mapping from numpy dtype endian format to what we expect +_dtype_endian_lookup = { + "=": "native", + ">": "big", + "<": "little", + "|": None, + None: None, +} + # internal C functions. cdef _get_att_names(int grpid, int varid): @@ -2026,12 +2035,11 @@ cdef _get_vars(group, bint auto_complex=False): # TODO: proper lookup datatype = "c16" if complex_nc_type == NC_DOUBLE else "c8" - if endianness == '>': - variables[name] = Variable(group, name, datatype, dimensions, id=varid, auto_complex=auto_complex, endian='big') - elif endianness == '<': - variables[name] = Variable(group, name, datatype, dimensions, id=varid, auto_complex=auto_complex, endian='little') - else: - variables[name] = Variable(group, name, datatype, dimensions, id=varid, auto_complex=auto_complex) + endian = _dtype_endian_lookup[endianness] or "native" + variables[name] = Variable( + group, name, datatype, dimensions, id=varid, auto_complex=auto_complex, endian=endian + ) + free(varids) # free pointer holding variable ids. return variables @@ -3949,6 +3957,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. cdef size_t *chunksizesp cdef float preemptionp cdef int nc_complex_typeid + cdef int _nc_endian # Extra information for more helpful error messages error_info = f"(variable '{name}', group '{grp.name}')" @@ -3997,6 +4006,18 @@ behavior is similar to Fortran or Matlab, but different than numpy. pass else: raise ValueError(f"Unsupported value for compression kwarg {error_info}") + + if grp.data_model.startswith("NETCDF3") and endian != 'native': + raise RuntimeError( + f"only endian='native' allowed for NETCDF3 files, got '{endian}' {error_info}" + ) + + if endian not in ("little", "big", "native"): + raise ValueError( + f"'endian' keyword argument must be 'little','big' or 'native', got '{endian}' " + f"{error_info}" + ) + self._grpid = grp._grpid # make a weakref to group to avoid circular ref (issue 218) # keep strong reference the default behaviour (issue 251) @@ -4033,20 +4054,11 @@ behavior is similar to Fortran or Matlab, but different than numpy. datatype = str user_type = True # check if endian keyword consistent with datatype specification. - dtype_endian = getattr(datatype,'byteorder',None) - if dtype_endian == '=': dtype_endian='native' - if dtype_endian == '>': dtype_endian='big' - if dtype_endian == '<': dtype_endian='little' - if dtype_endian == '|': dtype_endian=None + dtype_endian = _dtype_endian_lookup[getattr(datatype, "byteorder", None)] if dtype_endian is not None and dtype_endian != endian: - if dtype_endian == 'native' and endian == sys.byteorder: - pass - else: - # endian keyword prevails, issue warning - msg = 'endian-ness of dtype and endian kwarg do not match, using endian kwarg' - #msg = 'endian-ness of dtype and endian kwarg do not match, dtype over-riding endian kwarg' - warnings.warn(msg) - #endian = dtype_endian # dtype prevails + if not (dtype_endian == 'native' and endian == sys.byteorder): + warnings.warn('endian-ness of dtype and endian kwarg do not match, using endian kwarg') + # check validity of datatype. self._isprimitive = False self._iscompound = False @@ -4248,17 +4260,13 @@ behavior is similar to Fortran or Matlab, but different than numpy. if ierr != NC_NOERR: if grp.data_model != 'NETCDF4': grp._enddef() _ensure_nc_success(ierr, extra_msg=error_info) + # set endian-ness of variable - if endian == 'little': - with nogil: - ierr = nc_def_var_endian(self._grpid, self._varid, NC_ENDIAN_LITTLE) - elif endian == 'big': + if endian != 'native': + _nc_endian = NC_ENDIAN_LITTLE if endian == "little" else NC_ENDIAN_BIG with nogil: - ierr = nc_def_var_endian(self._grpid, self._varid, NC_ENDIAN_BIG) - elif endian == 'native': - pass # this is the default format. - else: - raise ValueError("'endian' keyword argument must be 'little','big' or 'native', got '%s'" % endian) + ierr = nc_def_var_endian(self._grpid, self._varid, _nc_endian) + _ensure_nc_success(ierr, extra_msg=error_info) # set quantization if significant_digits is not None: @@ -4288,10 +4296,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. if ierr != NC_NOERR: if grp.data_model != 'NETCDF4': grp._enddef() _ensure_nc_success(ierr, extra_msg=error_info) - else: - if endian != 'native': - msg=f"only endian='native' allowed for NETCDF3 files {error_info}" - raise RuntimeError(msg) + # set a fill value for this variable if fill_value keyword # given. This avoids the HDF5 overhead of deleting and # recreating the dataset if it is set later (after the enddef). From d364a6f5f2785c2e842e4bc1a84800518c1f9f16 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Thu, 16 Nov 2023 13:57:20 +0000 Subject: [PATCH 1055/1504] Simplify duplicated call to `nc_def_var` --- src/netCDF4/_netCDF4.pyx | 12 ++++-------- 1 file changed, 4 insertions(+), 8 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index e9ebf0586..ba12966b5 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -3952,7 +3952,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. cdef char namstring[NC_MAX_NAME+1] cdef char *varname cdef nc_type xtype - cdef int *dimids + cdef int *dimids = NULL cdef size_t sizep, nelemsp cdef size_t *chunksizesp cdef float preemptionp @@ -4116,15 +4116,11 @@ behavior is similar to Fortran or Matlab, but different than numpy. # any exceptions are raised. if grp.data_model != 'NETCDF4': grp._redef() # define variable. + with nogil: + ierr = nc_def_var(self._grpid, varname, xtype, ndims, + dimids, &self._varid) if ndims: - with nogil: - ierr = nc_def_var(self._grpid, varname, xtype, ndims, - dimids, &self._varid) free(dimids) - else: # a scalar variable. - with nogil: - ierr = nc_def_var(self._grpid, varname, xtype, ndims, - NULL, &self._varid) if ierr != NC_NOERR: if grp.data_model != 'NETCDF4': From d60252b19695931fd68a1d94f4e95175b06ded3a Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Thu, 16 Nov 2023 17:01:02 +0000 Subject: [PATCH 1056/1504] Add support for complex numbers in netcdf3/classic model --- include/netCDF4.pxi | 27 +++++--- src/netCDF4/_netCDF4.pyx | 140 +++++++++++++++++++++++++-------------- test/test_complex.py | 13 ++++ 3 files changed, 121 insertions(+), 59 deletions(-) diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi index 8d232df8f..00d883662 100644 --- a/include/netCDF4.pxi +++ b/include/netCDF4.pxi @@ -469,17 +469,28 @@ cdef extern from "netcdf-compat.h": # Declarations for handling complex numbers cdef extern from "nc_complex/nc_complex.h": - int pfnc_var_is_complex(int ncid, int varid) nogil - int pfnc_var_is_complex_type(int ncid, int varid) nogil - int pfnc_has_complex_dimension(int ncid, int varid) nogil - int pfnc_get_double_complex_typeid(int ncid, nc_type *nc_typeid) nogil - int pfnc_get_float_complex_typeid(int ncid, nc_type *nc_typeid) nogil + bint pfnc_var_is_complex(int ncid, int varid) nogil + bint pfnc_var_is_complex_type(int ncid, int varid) nogil - int pfnc_complex_base_type(int ncid, int nc_typeid, int* base_type_id) nogil + int pfnc_get_complex_dim(int ncid, int* nc_dim) nogil int pfnc_inq_var_complex_base_type(int ncid, int varid, int* nc_typeid) nogil int pfnc_inq_varndims (int ncid, int varid, int *ndimsp) nogil int pfnc_inq_vardimid (int ncid, int varid, int *dimidsp) nogil - int pfnc_get_vara (int ncid, int varid, size_t *startp, - size_t *countp, void *ip) nogil + int pfnc_def_var(int ncid, char *name, nc_type xtype, int ndims, + int *dimidsp, int *varidp) nogil + + int pfnc_get_vars(int ncid, int varid, size_t *startp, + size_t *countp, ptrdiff_t *stridep, + void *ip) nogil + + int pfnc_put_vars(int ncid, int varid, size_t *startp, + size_t *countp, ptrdiff_t *stridep, + void *op) nogil + + cdef enum: + PFNC_DOUBLE_COMPLEX + PFNC_DOUBLE_COMPLEX_DIM + PFNC_FLOAT_COMPLEX + PFNC_FLOAT_COMPLEX_DIM diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index ba12966b5..1c11aa972 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1435,6 +1435,11 @@ _intnptonctype = {'i1' : NC_BYTE, 'i8' : NC_INT64, 'u8' : NC_UINT64} +_complex_types = { + "c16": PFNC_DOUBLE_COMPLEX, + "c8": PFNC_FLOAT_COMPLEX, +} + # create dictionary mapping string identifiers to netcdf format codes _format_dict = {'NETCDF3_CLASSIC' : NC_FORMAT_CLASSIC, 'NETCDF4_CLASSIC' : NC_FORMAT_NETCDF4_CLASSIC, @@ -1479,7 +1484,8 @@ if __has_pnetcdf_support__: 'NETCDF3_64BIT' ] -# default fill_value to numpy datatype mapping. +# Default fill_value to numpy datatype mapping. Last two for complex +# numbers only applies to complex dimensions default_fillvals = {#'S1':NC_FILL_CHAR, 'S1':'\0', 'i1':NC_FILL_BYTE, @@ -1491,7 +1497,10 @@ default_fillvals = {#'S1':NC_FILL_CHAR, 'i8':NC_FILL_INT64, 'u8':NC_FILL_UINT64, 'f4':NC_FILL_FLOAT, - 'f8':NC_FILL_DOUBLE} + 'f8':NC_FILL_DOUBLE, + 'c8':NC_FILL_FLOAT, + 'c16':NC_FILL_DOUBLE, +} # logical for native endian type. is_native_little = numpy.dtype('pfnc_var_is_complex_type(self._grpid, self._varid): + self._isprimitive = False + self._iscompound = True + with nogil: + ierr = pfnc_inq_var_complex_base_type(self._grpid, self._varid, &complex_typeid) + _ensure_nc_success(ierr, extra_msg=error_info) + + np_complex_type = _nctonptype[complex_typeid] + compound_complex_type = f"{np_complex_type}, {np_complex_type}" + + self._cmptype = CompoundType( + self._grp, compound_complex_type, "complex", typeid=complex_typeid + ) + else: + with nogil: + ierr = pfnc_get_complex_dim(self._grpid, &complex_dim_id) + _ensure_nc_success(ierr, extra_msg=error_info) + with nogil: + ierr = nc_inq_dimname(self._grpid, complex_dim_id, name) + _ensure_nc_success(ierr, extra_msg=error_info) + self._grp.dimensions[name.decode("utf-8")] = Dimension( + self._grp, name, size=2, id=complex_dim_id + ) + def __array__(self): # numpy special method that returns a numpy array. # allows numpy ufuncs to work faster on Variable objects @@ -4430,7 +4465,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. cdef int ierr, dimid cdef char namstring[NC_MAX_NAME+1] - dimids = _inq_vardimid(self._grpid, self._varid, self.auto_complex) + dimids = _inq_vardimid(self._grpid, self._varid, self._grp.auto_complex) # loop over dimensions, retrieve names. dimensions = () @@ -5721,7 +5756,11 @@ NC_CHAR). if not data.dtype.isnative: data = data.byteswap() # strides all 1 or scalar variable, use put_vara (faster) - if sum(stride) == ndims or ndims == 0: + if self._grp.auto_complex: + with nogil: + ierr = pfnc_put_vars(self._grpid, self._varid, + startp, countp, stridep, PyArray_DATA(data)) + elif sum(stride) == ndims or ndims == 0: with nogil: ierr = nc_put_vara(self._grpid, self._varid, startp, countp, PyArray_DATA(data)) @@ -5843,16 +5882,15 @@ NC_CHAR). # strides all 1 or scalar variable, use get_vara (faster) # if count contains a zero element, no data is being read if 0 not in count: - if sum(stride) == ndims or ndims == 0: - if self.auto_complex: - with nogil: - ierr = pfnc_get_vara(self._grpid, self._varid, - startp, countp, PyArray_DATA(data)) - else: - with nogil: - ierr = nc_get_vara(self._grpid, self._varid, - startp, countp, PyArray_DATA(data)) - + if self._grp.auto_complex: + with nogil: + ierr = pfnc_get_vars(self._grpid, self._varid, + startp, countp, stridep, + PyArray_DATA(data)) + elif sum(stride) == ndims or ndims == 0: + with nogil: + ierr = nc_get_vara(self._grpid, self._varid, + startp, countp, PyArray_DATA(data)) else: with nogil: ierr = nc_get_vars(self._grpid, self._varid, diff --git a/test/test_complex.py b/test/test_complex.py index 8c03953f8..20856ce1f 100644 --- a/test/test_complex.py +++ b/test/test_complex.py @@ -60,6 +60,19 @@ def test_write(self): assert "complex_data" in f.variables assert np.array_equal(f["complex_data"], complex_struct_array) + def test_write_netcdf3(self): + filename = self.tmp_path / "test_write_netcdf3.nc" + with netCDF4.Dataset( + filename, "w", format="NETCDF3_CLASSIC", auto_complex=True + ) as f: + f.createDimension("x", size=len(complex_array)) + complex_var = f.createVariable("complex_data", "c16", ("x",)) + complex_var[:] = complex_array + + with netCDF4.Dataset(filename, "r", auto_complex=True) as f: + assert "complex_data" in f.variables + assert np.array_equal(f["complex_data"][:], complex_array) + if __name__ == "__main__": unittest.main() From df42ae11887a13326d06d87d77d06d564d845e4e Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Thu, 16 Nov 2023 17:30:31 +0000 Subject: [PATCH 1057/1504] CI: Checkout submodules --- .github/workflows/build_latest.yml | 2 ++ .github/workflows/build_master.yml | 2 ++ .github/workflows/build_old.yml | 2 ++ .github/workflows/miniconda.yml | 4 ++++ 4 files changed, 10 insertions(+) diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml index 3d252e1cc..4ec6ff7fd 100644 --- a/.github/workflows/build_latest.yml +++ b/.github/workflows/build_latest.yml @@ -17,6 +17,8 @@ jobs: steps: - uses: actions/checkout@v4 + with: + submodules: true - name: Set up Python ${{ matrix.python-version }} uses: actions/setup-python@v4 diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index c2a00e76f..a072bf451 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -14,6 +14,8 @@ jobs: steps: - uses: actions/checkout@v4 + with: + submodules: true - name: Set up Python ${{ matrix.python-version }} uses: actions/setup-python@v4 diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml index e00d8be17..c2d4c16e3 100644 --- a/.github/workflows/build_old.yml +++ b/.github/workflows/build_old.yml @@ -17,6 +17,8 @@ jobs: steps: - uses: actions/checkout@v4 + with: + submodules: true - name: Set up Python ${{ matrix.python-version }} uses: actions/setup-python@v4 diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index ca4309c33..33f079898 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -22,6 +22,8 @@ jobs: steps: - uses: actions/checkout@v4 + with: + submodules: true - name: Setup Micromamba uses: mamba-org/setup-micromamba@v1 @@ -53,6 +55,8 @@ jobs: platform: [x64] steps: - uses: actions/checkout@v4 + with: + submodules: true - name: Setup Micromamba uses: mamba-org/setup-micromamba@v1 From 4be9751dc5aca948b6e4e126e35ea0c77828651d Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Tue, 21 Nov 2023 17:01:35 +0000 Subject: [PATCH 1058/1504] Add some docs for complex number support --- docs/index.html | 72 ++++++++++++++++++++++++++++++++++------ examples/tutorial.py | 8 +++++ src/netCDF4/_netCDF4.pyx | 62 +++++++++++++++++++++++++++++----- 3 files changed, 122 insertions(+), 20 deletions(-) diff --git a/docs/index.html b/docs/index.html index 7ed8055d2..6971ceb5b 100644 --- a/docs/index.html +++ b/docs/index.html @@ -3,7 +3,7 @@ - + netCDF4 API documentation @@ -49,8 +49,9 @@

          Quick Install

        Developer Install

        +

        All of the code in this tutorial is available in examples/tutorial.py, except +the parallel IO example, which is in examples/mpi_example.py. +Unit tests are in the test directory.

        Creating/Opening/Closing a netCDF file

        To create a netCDF file from python, you simply call the Dataset constructor. This is also the method used to open an existing netCDF @@ -671,9 +675,9 @@

        Beyond ho Compound data types are created from the corresponding numpy data type using the Dataset.createCompoundType() method of a Dataset or Group instance. -Since there is no native complex data type in netcdf, compound types are handy -for storing numpy complex arrays. -Here's an example:

        +Since there is no native complex data type in netcdf (but see +Support for complex numbers), compound +types are handy for storing numpy complex arrays. Here's an example:

        >>> f = Dataset("complex.nc","w")
 >>> size = 3 # length of 1-d complex array
 >>> # create sample complex data.
@@ -1096,9 +1100,43 @@ 
        In-memory (diskless) Datasets
        
 [0 1 2 3 4]
 >>> nc.close()
        -

        All of the code in this tutorial is available in examples/tutorial.py, except -the parallel IO example, which is in examples/mpi_example.py. -Unit tests are in the test directory.

        +

        Support for complex numbers

        +

        Although there is no native support for complex numbers in netCDF, there are +some common conventions for storing them. Two of the most common are to either +use a compound datatype for the real and imaginary components, or a separate +dimension. netCDF4 supports reading several of these conventions, as well as +writing using one of two conventions (depending on file format). This support +for complex numbers is enabled by setting auto_complex=True when opening a +Dataset:

        +
        >>> complex_array = np.array([0 + 0j, 1 + 0j, 0 + 1j, 1 + 1j, 0.25 + 0.75j])
+>>> with netCDF4.Dataset("complex.nc", "w", auto_complex=True) as nc:
+...     nc.createDimension("x", size=len(complex_array))
+...     var = nc.createVariable("data", "c16", ("x",))
+...     var[:] = complex_array
+...     print(var)
+<class 'netCDF4._netCDF4.Variable'>
+compound data(x)
+compound data type: complex128
+unlimited dimensions:
+current shape = (5,)
+
        +

        When reading files using auto_complex=True, netCDF4 will interpret variables +stored using the following conventions as complex numbers:

        +
          +
        • compound datatypes with two float or double members who names begin with +r and i (case insensitive)
          • +
        • a dimension of length 2 named complex or ri
          • +
        +

        When writing files using auto_complex=True, netCDF4 will use:

        +
          +
        • a compound datatype named _PFNC_DOUBLE_COMPLEX_TYPE (or *FLOAT* as +appropriate) with members r and i for netCDF4 formats;
          • +
        • or a dimension of length 2 named _pfnc_complex for netCDF3 or classic +formats.
          • +
        +

        Support for complex numbers is handled via the +nc-complex library. See there for +further details.

        contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov

        copyright: 2008 by Jeffrey Whitaker.

        license: Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

        @@ -1553,7 +1591,8 @@

        Instance variables

        Ignored if parallel=False.

        info: MPI_Info object for parallel access. Default None, which means MPI_INFO_NULL will be used. -Ignored if parallel=False.

      +Ignored if parallel=False.

      +

      auto_complex: if True, then automatically convert complex number types

      Subclasses

      • netCDF4._netCDF4.Group
        • @@ -1582,6 +1621,10 @@

        Static methods

      Instance variables

      +
      var auto_complex
      +
      +

      Return an attribute of instance, which is of type owner.

      +
      var cmptypes

      Return an attribute of instance, which is of type owner.

      @@ -2627,6 +2670,10 @@

      Instance variables

      Return an attribute of instance, which is of type owner.

      +
      var auto_complex
      +
      +

      Return an attribute of instance, which is of type owner.

      +
      var chartostring

      Return an attribute of instance, which is of type owner.

      @@ -3027,6 +3074,7 @@

      Index

    • Parallel IO
    • Dealing with strings
    • In-memory (diskless) Datasets
      • +
    • Support for complex numbers
    @@ -3060,6 +3108,7 @@

    CompoundT

  • Dataset

      +
    • auto_complex
    • close
    • cmptypes
    • createCompoundType
      • @@ -3156,6 +3205,7 @@

      Variable
    • always_mask
    • assignValue
      • +
    • auto_complex
    • chartostring
    • chunking
    • datatype
      • @@ -3198,7 +3248,7 @@

      Variable \ No newline at end of file diff --git a/examples/tutorial.py b/examples/tutorial.py index 7efad1c00..d48fd1679 100644 --- a/examples/tutorial.py +++ b/examples/tutorial.py @@ -355,3 +355,11 @@ def walktree(top): print(nc) print(nc['v'][:]) nc.close() + +# Write complex numbers to file +complex_array = np.array([0 + 0j, 1 + 0j, 0 + 1j, 1 + 1j, 0.25 + 0.75j]) +with Dataset("complex.nc", "w", auto_complex=True) as nc: + nc.createDimension("x", size=len(complex_array)) + var = nc.createVariable("data", "c16", ("x",)) + var[:] = complex_array + print(var) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 1c11aa972..878e7898d 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1,5 +1,4 @@ -""" -Version 1.7.0 +"""Version 1.7.0 ------------- # Introduction @@ -30,8 +29,9 @@ types) are not supported. ## Developer Install - - Clone the - [github repository](http://github.com/Unidata/netcdf4-python). + - Clone the [github repository](http://github.com/Unidata/netcdf4-python). Make + sure you either clone recursively, or run `git submodule update --init` to + ensure all the submodules are also checked out. - Make sure the dependencies are satisfied (Python 3.8 or later, [numpy](http://numpy.scipy.org), [Cython](http://cython.org), @@ -85,6 +85,10 @@ types) are not supported. - [Dealing with strings](#dealing-with-strings) - [In-memory (diskless) Datasets](#in-memory-diskless-datasets) +All of the code in this tutorial is available in `examples/tutorial.py`, except +the parallel IO example, which is in `examples/mpi_example.py`. +Unit tests are in the `test` directory. + ## Creating/Opening/Closing a netCDF file To create a netCDF file from python, you simply call the `Dataset` @@ -735,8 +739,9 @@ information for a point by reading one variable, instead of reading different parameters from different variables. Compound data types are created from the corresponding numpy data type using the `Dataset.createCompoundType` method of a `Dataset` or `Group` instance. -Since there is no native complex data type in netcdf, compound types are handy -for storing numpy complex arrays. Here's an example: +Since there is no native complex data type in netcdf (but see +[Support for complex numbers](#support-for-complex-numbers)), compound +types are handy for storing numpy complex arrays. Here's an example: ```python >>> f = Dataset("complex.nc","w") @@ -1200,10 +1205,48 @@ root group (NETCDF4 data model, file format HDF5): >>> nc.close() ``` +## Support for complex numbers + +Although there is no native support for complex numbers in netCDF, there are +some common conventions for storing them. Two of the most common are to either +use a compound datatype for the real and imaginary components, or a separate +dimension. `netCDF4` supports reading several of these conventions, as well as +writing using one of two conventions (depending on file format). This support +for complex numbers is enabled by setting `auto_complex=True` when opening a +`Dataset`: + +```python +>>> complex_array = np.array([0 + 0j, 1 + 0j, 0 + 1j, 1 + 1j, 0.25 + 0.75j]) +>>> with netCDF4.Dataset("complex.nc", "w", auto_complex=True) as nc: +... nc.createDimension("x", size=len(complex_array)) +... var = nc.createVariable("data", "c16", ("x",)) +... var[:] = complex_array +... print(var) + +compound data(x) +compound data type: complex128 +unlimited dimensions: +current shape = (5,) +``` + +When reading files using `auto_complex=True`, `netCDF4` will interpret variables +stored using the following conventions as complex numbers: + +- compound datatypes with two `float` or `double` members who names begin with + `r` and `i` (case insensitive) +- a dimension of length 2 named `complex` or `ri` + +When writing files using `auto_complex=True`, `netCDF4` will use: + +- a compound datatype named `_PFNC_DOUBLE_COMPLEX_TYPE` (or `*FLOAT*` as + appropriate) with members `r` and `i` for netCDF4 formats; +- or a dimension of length 2 named `_pfnc_complex` for netCDF3 or classic + formats. + +Support for complex numbers is handled via the +[`nc-complex`](https://github.com/PlasmaFAIR/nc-complex) library. See there for +further details. -All of the code in this tutorial is available in `examples/tutorial.py`, except -the parallel IO example, which is in `examples/mpi_example.py`. -Unit tests are in the `test` directory. **contact**: Jeffrey Whitaker @@ -1214,6 +1257,7 @@ Unit tests are in the `test` directory. The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. + """ # Make changes to this file, not the c-wrappers that Cython generates. From 54f812425d4b6914bf9930e545400ba4ec5be25d Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Tue, 21 Nov 2023 17:35:11 +0000 Subject: [PATCH 1059/1504] Support using `np.complex128` directly for complex numbers --- src/netCDF4/_netCDF4.pyx | 18 +++++++++--------- test/test_complex.py | 11 +++++++++++ 2 files changed, 20 insertions(+), 9 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 878e7898d..dcfe221a2 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2113,8 +2113,8 @@ def _ensure_nc_success(ierr, err_cls=RuntimeError, filename=None, extra_msg=None raise err_cls(err_str) -def dtype_is_complex(dtype: Union[str, CompoundType, numpy.dtype]) -> bool: - # TODO: check numpy.complex128, matching CompoundTypes +def dtype_is_complex(dtype: Union[str, numpy.dtype]) -> bool: + """Return True if dtype is a complex number""" return dtype in ("c8", "c16") @@ -4077,13 +4077,6 @@ behavior is similar to Fortran or Matlab, but different than numpy. else: self._grp = grp - # If datatype is complex, convert to compoundtype - is_complex = dtype_is_complex(datatype) - if is_complex and not self._grp.auto_complex: - raise ValueError( - f"complex datatypes ({datatype}) are only supported with `auto_complex=True`" - ) - self._iscompound = isinstance(datatype, CompoundType) self._isvlen = isinstance(datatype, VLType) or datatype==str self._isenum = isinstance(datatype, EnumType) @@ -4102,6 +4095,13 @@ behavior is similar to Fortran or Matlab, but different than numpy. user_type = True self._isvlen = True + # If datatype is complex, convert to compoundtype + is_complex = dtype_is_complex(datatype) + if is_complex and not self._grp.auto_complex: + raise ValueError( + f"complex datatypes ({datatype}) are only supported with `auto_complex=True`" + ) + # check if endian keyword consistent with datatype specification. dtype_endian = _dtype_endian_lookup[getattr(datatype, "byteorder", None)] if dtype_endian is not None and dtype_endian != endian: diff --git a/test/test_complex.py b/test/test_complex.py index 20856ce1f..cd1fed32c 100644 --- a/test/test_complex.py +++ b/test/test_complex.py @@ -60,6 +60,17 @@ def test_write(self): assert "complex_data" in f.variables assert np.array_equal(f["complex_data"], complex_struct_array) + def test_write_with_np_complex128(self): + filename = self.tmp_path / "test_write_with_np_complex128.nc" + with netCDF4.Dataset(filename, "w", auto_complex=True) as f: + f.createDimension("x", size=len(complex_array)) + complex_var = f.createVariable("complex_data", np.complex128, ("x",)) + complex_var[:] = complex_array + + with netCDF4.Dataset(filename, "r") as f: + assert "complex_data" in f.variables + assert np.array_equal(f["complex_data"], complex_struct_array) + def test_write_netcdf3(self): filename = self.tmp_path / "test_write_netcdf3.nc" with netCDF4.Dataset( From 3da60a1bc845ae4e2bae89699334de35cdb7e9cb Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Thu, 7 Dec 2023 03:14:03 +0000 Subject: [PATCH 1060/1504] Bump actions/setup-python from 4 to 5 Bumps [actions/setup-python](https://github.com/actions/setup-python) from 4 to 5. - [Release notes](https://github.com/actions/setup-python/releases) - [Commits](https://github.com/actions/setup-python/compare/v4...v5) --- updated-dependencies: - dependency-name: actions/setup-python dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- .github/workflows/build_latest.yml | 2 +- .github/workflows/build_master.yml | 2 +- .github/workflows/build_old.yml | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml index 3d252e1cc..3ddd0517d 100644 --- a/.github/workflows/build_latest.yml +++ b/.github/workflows/build_latest.yml @@ -19,7 +19,7 @@ jobs: - uses: actions/checkout@v4 - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v4 + uses: actions/setup-python@v5 with: python-version: ${{ matrix.python-version }} diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index c2a00e76f..c0fd2a020 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -16,7 +16,7 @@ jobs: - uses: actions/checkout@v4 - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v4 + uses: actions/setup-python@v5 with: python-version: ${{ matrix.python-version }} diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml index e00d8be17..fb3272f55 100644 --- a/.github/workflows/build_old.yml +++ b/.github/workflows/build_old.yml @@ -19,7 +19,7 @@ jobs: - uses: actions/checkout@v4 - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v4 + uses: actions/setup-python@v5 with: python-version: ${{ matrix.python-version }} From 013e8f38f87700690deefec33cbf70fa8636e00b Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Fri, 8 Dec 2023 08:55:03 +0000 Subject: [PATCH 1061/1504] Bump nc-complex to v0.2.0 --- external/nc_complex | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/external/nc_complex b/external/nc_complex index 9c2a87703..37310ed00 160000 --- a/external/nc_complex +++ b/external/nc_complex @@ -1 +1 @@ -Subproject commit 9c2a87703c7612f04097418bbed4978d3be6ef92 +Subproject commit 37310ed00f3910974bdefefcdfa4787588651f59 From 0561c7c3653b09320f0a5f002228a13fb8aa28d5 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Fri, 8 Dec 2023 08:55:24 +0000 Subject: [PATCH 1062/1504] Add more complete example for complex numbers --- examples/complex_numbers.py | 51 +++++++++++++++++++++++++++++++++++++ 1 file changed, 51 insertions(+) create mode 100644 examples/complex_numbers.py diff --git a/examples/complex_numbers.py b/examples/complex_numbers.py new file mode 100644 index 000000000..51d7a61f1 --- /dev/null +++ b/examples/complex_numbers.py @@ -0,0 +1,51 @@ +import netCDF4 +import numpy as np + +complex_array = np.array([0 + 0j, 1 + 0j, 0 + 1j, 1 + 1j, 0.25 + 0.75j], dtype="c16") +np_dt = np.dtype([("r", np.float64), ("i", np.float64)]) +complex_struct_array = np.array( + [(r, i) for r, i in zip(complex_array.real, complex_array.imag)], + dtype=np_dt, +) + +print("\n**********") +print("Reading a file that uses a dimension for complex numbers") +filename = "complex_numbers_as_dimension.nc" + +with netCDF4.Dataset(filename, "w") as f: + f.createDimension("x", size=len(complex_array)) + f.createDimension("complex", size=2) + c_ri = f.createVariable("data_dim", np.float64, ("x", "complex")) + as_dim_array = np.vstack((complex_array.real, complex_array.imag)).T + c_ri[:] = as_dim_array + +with netCDF4.Dataset(filename, "r", auto_complex=True) as f: + print(f["data_dim"]) + + +print("\n**********") +print("Reading a file that uses a compound datatype for complex numbers") +filename = "complex_numbers_as_datatype.nc" + +with netCDF4.Dataset(filename, "w") as f: + f.createDimension("x", size=len(complex_array)) + nc_dt = f.createCompoundType(np_dt, "nc_complex") + breakpoint() + + c_struct = f.createVariable("data_struct", nc_dt, ("x",)) + c_struct[:] = complex_struct_array + +with netCDF4.Dataset(filename, "r", auto_complex=True) as f: + print(f["data_struct"]) + +print("\n**********") +print("Writing complex numbers to a file") +filename = "writing_complex_numbers.nc" +with netCDF4.Dataset(filename, "w", auto_complex=True) as f: + f.createDimension("x", size=len(complex_array)) + c_var = f.createVariable("data", np.complex128, ("x",)) + c_var[:] = complex_array + print(c_var) + +with netCDF4.Dataset(filename, "r", auto_complex=True) as f: + print(f["data"]) From fe653fef8d550945ea74f3e2ba3acbc16a412f57 Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Fri, 8 Dec 2023 08:57:33 +0000 Subject: [PATCH 1063/1504] Add changelog entry for complex numbers --- Changelog | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/Changelog b/Changelog index e5c5362c8..3a0168ecf 100644 --- a/Changelog +++ b/Changelog @@ -1,7 +1,8 @@ version 1.7.0 (not yet released) =============================== + * add support for complex numbers via `auto_complex` keyword to `Dataset` (PR #1295) * fix for deprecated Cython `DEF` and `IF` statements using compatibility header - with shims for unavailable functionality + with shims for unavailable functionality (PR #1277) version 1.6.5 (tag v1.6.5rel) =============================== From 68938a640f27c8ba627a5a5e4d6f1f14f47eb369 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Wed, 13 Dec 2023 22:43:34 +0100 Subject: [PATCH 1064/1504] initial stub file --- src/netCDF4/__init__.pyi | 459 +++++++++++++++++++++++++++++++++++++++ src/netCDF4/py.typed | 0 2 files changed, 459 insertions(+) create mode 100644 src/netCDF4/__init__.pyi create mode 100644 src/netCDF4/py.typed diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi new file mode 100644 index 000000000..01c10f400 --- /dev/null +++ b/src/netCDF4/__init__.pyi @@ -0,0 +1,459 @@ +from typing import TypeAlias, Literal, Any, Tuple, NoReturn, Iterable, Mapping +from typing_extensions import Buffer +import numpy.typing as npt +import os +import datetime +import cftime + +__all__ = ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache','set_alignment','get_alignment'] +__pdoc__ = {'utils': False} + +Datatype: TypeAlias = Literal['S1', 'c', 'i1', 'b', 'B', 'u1', 'i2', + 'h', 's', 'u2', 'i4', 'i', 'l', 'u4', + 'i8', 'u8', 'f4', 'f', 'f8', 'd'] +Compression: TypeAlias = Literal['zlib', 'szip', 'zstd', 'blosc_lz', + 'blosc_lz4', 'blosc_lz4hc', 'blosc_zlib', 'blosc_zstd'] +AccessMode: TypeAlias = Literal['r', 'w', + 'r+', 'a', 'x', 'rs', 'ws', 'r+s', 'as'] +Format: TypeAlias = Literal['NETCDF4', 'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC', + 'NETCDF3_64BIT_OFFSET', 'NETCDF3_64BIT_DATA'] +DiskFormat: TypeAlias = Literal['NETCDF3', 'HDF5', 'HDF4', + 'PNETCDF', 'DAP2', 'DAP4', 'UNDEFINED'] +default_fillvals: dict[str, int | float] + +__version__: str +__netcdf4libversion__: str +__hdf5libversion__: str +__has_rename_grp__: bool +__has_nc_inq_path__: bool +__has_nc_inq_format_extended__: bool +__has_nc_open_mem__: bool +__has_nc_create_mem__: bool +__has_cdf5_format__: bool +__has_parallel4_support__: bool +__has_pnetcdf_support__: bool +__has_parallel_support__: bool +__has_quantization_support__: bool +__has_zstandard_support__: bool +__has_bzip2_support__: bool +__has_blosc_support__: bool +__has_szip_support__: bool +__has_set_alignment__: bool +__has_ncfilter__: bool +is_native_little: bool +is_native_big: bool +default_encoding: str +unicode_error: str + + +class NetCDF4MissingFeatureException(Exception): + def __init__(self, feature: str, version: str): ... + + +class Dataset: + + def __init__( + self, + filename: str | os.PathLike, + mode: AccessMode = 'r', + clobber: bool = True, + format: Format = 'NETCDF4', + diskless: bool = False, + persist: bool = False, + keepweakref: bool = False, + memory: Buffer | int | None = None, + encoding: str | None = None, + parallel: bool = False, + comm: Any = None, + info: Any = None, + auto_complex: bool = False, + **kwargs: Any + ): ... + + @property + def name(self) -> str: ... + @property + def groups(self) -> dict[str, Group]: ... + @property + def dimensions(self) -> dict[str, Dimension]: ... + @property + def variables(self) -> dict[str, Variable]: ... + @property + def cmptypes(self) -> dict[str, CompoundType]: ... + @property + def vltypes(self) -> dict[str, VLType]: ... + @property + def enumtypes(self) -> dict[str, EnumType]: ... + @property + def data_model(self) -> Format: ... + @property + def file_format(self) -> Format: ... + @property + def disk_format(self) -> DiskFormat: ... + @property + def parent(self) -> Dataset | None: ... + @property + def path(self) -> os.PathLike | str: ... + @property + def keepweakref(self) -> bool: ... + @property + def _ncstring_attrs__(self) -> bool: ... + @property + def __orthogonal_indexing__(self) -> bool: ... + + def filepath(self, encoding: str | None = None) -> str: ... + def isopen(self) -> bool: ... + def close(self) -> None: ... + def sync(self) -> None: ... + def set_fill_on(self) -> None: ... + def set_fill_off(self) -> None: ... + + def createDimension(self, dimname: str, size: int | None = None) -> Dimension: ... + def renameDimension( self, oldname: str, newname: str) -> None: ... + def createVariable( + self, + varname: str, + datatype: Datatype | npt.DTypeLike | CompoundType | VLType, + dimensions: str | bytes | Dimension | Iterable[str | bytes | Dimension]= (), + compression: Compression | None = None, + zlib: bool = False, + complevel: Literal[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, None] = 4, + shuffle: bool = True, + szip_coding: Literal['nn', 'ec'] = 'nn', + szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, + blosc_shuffle: Literal[0, 1, 2] = 1, + fletcher32: bool = False, + contiguous: bool = False, + chunksizes: int | None = None, + endian: Literal['native', 'little', 'big'] = 'native', + least_significant_digit: int | None = None, + significant_digits: int | None = None, + quantize_mode: Literal['BitGroom', 'BitRound', 'GranularBitRound'] = 'BitGroom', + fill_value: bool | None = None, + chunk_cache: int | None = None + ) -> Variable: ... + def renameVariable(self, oldname: str, newname: str) -> None: ... + def createGroup(self, groupname: str) -> Group: ... + def renameGroup(self, oldname: str, newname: str) -> None: ... + def renameAttribute(self, oldname: str, newname: str) -> None: ... + def createCompoundType( self, datatype: npt.DTypeLike, datatype_name: str) -> CompoundType: ... + def createVLType( self, datatype: npt.DTypeLike, datatype_name: str) -> VLType: ... + def createEnumType( self, datatype: npt.DTypeLike, datatype_name: str, enum_dict: dict[str, int]) -> EnumType: ... + + def ncattrs(self) -> list[str]: ... + def setncattr_string(self, name: str, value: Any) -> None: ... + def setncattr(self, name: str, value: Any) -> None: ... + def setncatts(self, attdict: Mapping[str, Any]) -> None: ... + def getncattr(self, name: str, encoding: str = 'utf-8') -> Any: ... + def delncattr(self, name: str) -> None: ... + def set_auto_chartostring(self, value: bool) -> None: ... + def set_auto_maskandscale(self, value: bool) -> None: ... + def set_auto_mask(self, value: bool) -> None: ... + def set_auto_scale(self, value: bool) -> None: ... + def set_always_mask(self, value: bool) -> None: ... + def set_ncstring_attrs(self, value: bool) -> None: ... + def get_variables_by_attributes(self, **kwargs: Any) -> list[Variable]: ... + + @staticmethod + def fromcdl( + cdlfilename: str, + ncfilename: str | None = None, + mode: AccessMode = 'a', + format: Format = 'NETCDF4' + ) -> Dataset: ... + def tocdl( + self, + coordvars: bool = False, + data: bool = False, + outfile: str | None = None + ) -> None | bool: ... + + def has_blosc_filter(self) -> bool: ... + def has_zstd_filter(self) -> bool: ... + def has_bzip2_filter(self) -> bool: ... + def has_szip_filter(self) -> bool: ... + + def __getitem__(self, elem: str) -> Group | Variable: ... + def __setattr__(self, name: str, value: Any) -> None: ... + def __getattr__(self, name: str) -> Any: ... + def __delattr__(self, name: str): ... + def __dealloc(self) -> None: ... + def __reduce__(self) -> NoReturn: ... + def __enter__(self) -> Dataset: ... + def __exit__(self, atype, value, traceback) -> bool: ... + def __str__(self) -> str: ... + def __repr__(self) -> str: ... + + +class Group(Dataset): + def __init__( + self, + parent: Group | Dataset, + name: str, + **kwargs + ): ... + + +class Dimension: + def __init__( + self, + grp: Group, + name: str, + size: int | None = None, + **kwargs + ): ... + + @property + def name(self) -> str: ... + @property + def size(self) -> int: ... + def group(self) -> Group: ... + def isunlimited(self) -> bool: ... + def __str__(self) -> str: ... + def __repr__(self) -> str: ... + + +class Variable: + def __init__( + self, + grp: Group, + name: str, + datatype: Datatype | npt.DTypeLike | str | CompoundType | VLType, + dimensions: Tuple[str] | Tuple[()] | str | Dimension = (), + compression: Compression | None = None, + zlib: bool = False, + complevel: Literal[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, None] = 4, + shuffle: bool = True, + szip_coding: Literal['nn', 'ec'] = 'nn', + szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, + blosc_shuffle: Literal[0, 1, 2] = 1, + fletcher32: bool = False, + contiguous: bool = False, + chunksizes: int | None = None, + endian: Literal['native', 'little', 'big'] = 'native', + least_significant_digit: int | None = None, + significant_digits: int | None = None, + quantize_mode: Literal['BitGroom', 'BitRound', + 'GranularBitRound'] = 'BitGroom', + fill_value: bool | None = None, + chunk_cache: int | None = None, + **kwargs + ): ... + + @property + def dimensions(self) -> Tuple[str]: ... + @property + def dtype(self) -> npt.DTypeLike: ... + @property + def ndim(self) -> int: ... + @property + def shape(self) -> Tuple[int]: ... + @property + def scale(self) -> bool: ... + @property + def mask(self) -> bool: ... + @property + def chartostring(self) -> bool: ... + @property + def always_mask(self) -> bool: ... + @property + def name(self) -> str: ... + @property + def datatype(self) -> CompoundType | VLType | EnumType: ... + @property + def size(self) -> int: ... + @property + def __orthogonal_indexing__(self) -> bool: ... + + def group(self) -> Group: ... + def ncattrs(self) -> list[str]: ... + def setncattr(self, name: str, value) -> None: ... + def setncattr_string(self, name: str, value) -> None: ... + def setncatts(self, attdict) -> None: ... + def getncattr(self, name: str, encoding='utf-8'): ... + def delncattr(self, name: str) -> None: ... + def filters(self) -> dict: ... + def quantization(self) -> int: ... + def endian(self) -> str: ... + def chunking(self) -> str | list[int]: ... + def get_var_chunk_cache(self) -> tuple[int, int, float]: ... + def set_var_chunk_cache( + self, + size: int | None = None, + nelems: int | None = None, + preemption: float | None = None + ) -> None: ... + def renameAttribute(self, oldname: str, newname: str) -> None: ... + def assignValue(self, val) -> None: ... + def getValue(self) -> Any: ... + def set_auto_chartostring(self, chartostring) -> None: ... + def use_nc_get_vars(self, use_nc_get_vars) -> None: ... + def set_auto_maskandscale(self, maskandscale) -> None: ... + def set_auto_scale(self, scale) -> None: ... + def set_auto_mask(self, mask) -> None: ... + def set_always_mask(self, always_mask) -> None: ... + def set_ncstring_attrs(self, ncstring_attrs) -> None: ... + def set_collective(self, value) -> None: ... + def get_dims(self) -> tuple[Dimension]: ... + + def __setitem__(self, elem, data): ... + def __len__(self) -> int: ... + def __array__(self) -> npt.ArrayLike: ... + def __str__(self) -> str: ... + def __repr__(self) -> str: ... + def __delattr__(self, name: str): ... + def __setattr__(self, name: str, value): ... + def __getattr__(self, name: str): ... + def __getitem__(self, elem): ... + + +class CompoundType: + def __init__(self, grp, datatype, dtype_name, **kwargs): ... + + @property + def dtype(self) -> npt.DTypeLike: ... + @property + def name(self) -> str: ... + @property + def dtype_view(self) -> npt.DTypeLike: ... + + def __str__(self) -> str: ... + def __repr__(self) -> str: ... + def __reduce__(self): ... + + +class VLType: + def __init__( + self, + grp: Group, + datatype: npt.DTypeLike, + dtype_name: str, + **kwargs + ): ... + + @property + def dtype(self) -> npt.DTypeLike: ... + @property + def name(self) -> str: ... + + def __str__(self) -> str: ... + def __repr__(self) -> str: ... + def __reduce__(self): ... + + +class EnumType: + def __init__( + self, + grp: Group, + datatype: npt.DTypeLike, + dtype_name: str, + enum_dict: dict[str, int], + **kwargs + ): ... + + @property + def dtype(self) -> npt.DTypeLike: ... + @property + def name(self) -> str: ... + @property + def enum_dict(self) -> dict[str, int]: ... + + def __str__(self) -> str: ... + def __repr__(self) -> str: ... + def __reduce__(self): ... + + +class MFDataset(Dataset): + def __init__( + self, + files: str | os.PathLike, + check: bool = False, + aggdim: str | None = None, + exclude: list[str] = [], + master_file: str | os.PathLike | None = None + ): ... + + def ncattrs(self): ... + def close(self): ... + def isopen(self) -> bool: ... + + def __setattr__(self, name: str, value: Any): ... + def __getattribute__(self, name: str): ... + def __repr__(self) -> str: ... + def __reduce__(self): ... + + +class _Variable: + def __init__(self, dset, varname, var, recdimname): ... + + def __getattr__(self, name): ... + def __repr__(self): ... + def __len__(self): ... + def __getitem__(self, elem): ... + + def typecode(self): ... + def ncattrs(self): ... + def _shape(self): ... + def set_auto_chartostring(self, val): ... + def set_auto_maskandscale(self, val): ... + def set_auto_mask(self, val): ... + def set_auto_scale(self, val): ... + def set_always_mask(self, val): ... + + +class MFTime(_Variable): + def __init__( + self, + time: Variable, + units=None, + calendar: Literal['standard', 'gregorian'] | None = None + ): ... + def __getitem__(self, elem): ... + + +def stringtoarr(string, NUMCHARS: int, dtype: str = 'S'): ... +def stringtochar(a, encoding='utf-8'): ... +def chartostring(b, encoding='utf-8'): ... + +def getlibversion() -> str: ... + +def set_alignment(threshold: int, alignment: int): ... +def get_alignment() -> tuple[int, int]: ... + +def set_chunk_cache( + size: int | None = None, + nelems: int | None = None, + preemption: float | None = None +) -> None: ... +def get_chunk_cache() -> tuple[int, int, float]: ... + + +def date2index( + dates: datetime.datetime | cftime.datetime, + nctime: MFTime, + calendar: Literal['standard', 'gregorian', 'proleptic_gregorian' 'noleap', + '365_day', '360_day', 'julian', 'all_leap', '366_day', None] = None, + select: Literal['exact', 'before', 'after', 'nearest'] = 'exact', + has_year_zero: bool | None = None +): ... + + +def date2num( + dates: datetime.datetime | cftime.datetime, + units: str, + calendar: Literal['standard', 'gregorian', 'proleptic_gregorian' 'noleap', + '365_day', '360_day', 'julian', 'all_leap', '366_day', None] = None, + has_year_zero: bool | None = None, + longdouble: bool = False +): ... + + +def num2date( + times: Any, + units: str, + calendar: Literal['standard', 'gregorian', 'proleptic_gregorian' 'noleap', + '365_day', '360_day', 'julian', 'all_leap', '366_day'] = 'standard', + only_use_cftime_datetimes: bool = True, + only_use_python_datetimes: bool = False, + has_year_zero: bool | None = None +): ... diff --git a/src/netCDF4/py.typed b/src/netCDF4/py.typed new file mode 100644 index 000000000..e69de29bb From dcf4cb6a66b6b5c8fdfb17173ce19bfc081eb082 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Thu, 14 Dec 2023 22:44:06 +0100 Subject: [PATCH 1065/1504] add always_mask to private_atts --- src/netCDF4/_netCDF4.pyx | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index dcfe221a2..1483dad63 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2160,13 +2160,13 @@ cdef _inq_vardimid(int ncid, int varid, bint auto_complex): # only exist at the python level (not in the netCDF file). _private_atts = \ -['_grpid','_grp','_varid','groups','dimensions','variables','dtype','data_model','disk_format', +('_grpid','_grp','_varid','groups','dimensions','variables','dtype','data_model','disk_format', '_nunlimdim','path','parent','ndim','mask','scale','cmptypes','vltypes','enumtypes','_isprimitive', 'file_format','_isvlen','_isenum','_iscompound','_cmptype','_vltype','_enumtype','name', - '__orthogoral_indexing__','keepweakref','_has_lsd', + '__orthogoral_indexing__','keepweakref','_has_lsd','always_mask', '_buffer','chartostring','_use_get_vars','_ncstring_attrs__', 'auto_complex' -] +) cdef class Dataset: """ @@ -6964,7 +6964,7 @@ Example usage (See `MFDataset.__init__` for more details): return the netcdf attribute names from the master file. """ - return self._cdf[0].__dict__.keys() + return list(self._cdf[0].__dict__) def close(self): """ From a0484b3c04f6726d62f7f7ff369e70294b58085c Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Thu, 14 Dec 2023 22:47:29 +0100 Subject: [PATCH 1066/1504] fix typehints --- src/netCDF4/__init__.pyi | 285 +++++++++++++++++---------------------- 1 file changed, 125 insertions(+), 160 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 01c10f400..94a8f0945 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -1,25 +1,43 @@ -from typing import TypeAlias, Literal, Any, Tuple, NoReturn, Iterable, Mapping +from typing import TypeAlias, Literal, Any, NoReturn, Iterable, Mapping, Union, Sequence from typing_extensions import Buffer +import numpy as np import numpy.typing as npt import os import datetime import cftime - -__all__ = ['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache','set_alignment','get_alignment'] +from cftime import num2date, date2num, date2index + +__all__ = [ + 'Dataset', 'Variable', 'Dimension', 'Group', 'MFDataset', 'MFTime', 'CompoundType', + 'VLType', 'date2num', 'num2date', 'date2index', 'stringtochar', 'chartostring', + 'stringtoarr', 'getlibversion', 'EnumType', 'get_chunk_cache', 'set_chunk_cache', + 'set_alignment', 'get_alignment' +] __pdoc__ = {'utils': False} -Datatype: TypeAlias = Literal['S1', 'c', 'i1', 'b', 'B', 'u1', 'i2', - 'h', 's', 'u2', 'i4', 'i', 'l', 'u4', - 'i8', 'u8', 'f4', 'f', 'f8', 'd'] -Compression: TypeAlias = Literal['zlib', 'szip', 'zstd', 'blosc_lz', - 'blosc_lz4', 'blosc_lz4hc', 'blosc_zlib', 'blosc_zstd'] -AccessMode: TypeAlias = Literal['r', 'w', - 'r+', 'a', 'x', 'rs', 'ws', 'r+s', 'as'] -Format: TypeAlias = Literal['NETCDF4', 'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC', - 'NETCDF3_64BIT_OFFSET', 'NETCDF3_64BIT_DATA'] -DiskFormat: TypeAlias = Literal['NETCDF3', 'HDF5', 'HDF4', - 'PNETCDF', 'DAP2', 'DAP4', 'UNDEFINED'] -default_fillvals: dict[str, int | float] +DatatypeOptions: TypeAlias = Union[ + Literal[ + 'S1', 'c', 'i1', 'b', 'B', 'u1', 'i2', 'h', 's', 'u2', 'i4', + 'i', 'l', 'u4', 'i8', 'u8', 'f4', 'f', 'f8', 'd', 'c8', 'c16' + ], + npt.DTypeLike, + CompoundType, + VLType +] +DimensionsOptions: TypeAlias = Union[str, bytes, Dimension, Iterable[Union[str, bytes, Dimension]]] +CompressionOptions: TypeAlias = Literal[ + 'zlib', 'szip', 'zstd', 'blosc_lz','blosc_lz4', + 'blosc_lz4hc', 'blosc_zlib', 'blosc_zstd', None +] +CompressionLevelOptions: TypeAlias = Literal[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, None] +AccessModeOptions: TypeAlias = Literal['r', 'w', 'r+', 'a', 'x', 'rs', 'ws', 'r+s', 'as'] +FormatOptions: TypeAlias = Literal[ + 'NETCDF4', 'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC', + 'NETCDF3_64BIT_OFFSET', 'NETCDF3_64BIT_DATA' +] +DiskFormatOptions: TypeAlias = Literal['NETCDF3', 'HDF5', 'HDF4', 'PNETCDF', 'DAP2', 'DAP4', 'UNDEFINED'] +QuantizeOptions: TypeAlias = Literal['BitGroom', 'BitRound', 'GranularBitRound'] +EndianOptions: TypeAlias = Literal['native', 'little', 'big'] __version__: str __netcdf4libversion__: str @@ -44,6 +62,7 @@ is_native_little: bool is_native_big: bool default_encoding: str unicode_error: str +default_fillvals: dict[str, Any] class NetCDF4MissingFeatureException(Exception): @@ -51,13 +70,12 @@ class NetCDF4MissingFeatureException(Exception): class Dataset: - def __init__( self, filename: str | os.PathLike, - mode: AccessMode = 'r', + mode: AccessModeOptions = 'r', clobber: bool = True, - format: Format = 'NETCDF4', + format: FormatOptions = 'NETCDF4', diskless: bool = False, persist: bool = False, keepweakref: bool = False, @@ -85,19 +103,19 @@ class Dataset: @property def enumtypes(self) -> dict[str, EnumType]: ... @property - def data_model(self) -> Format: ... + def data_model(self) -> FormatOptions: ... @property - def file_format(self) -> Format: ... + def file_format(self) -> FormatOptions: ... @property - def disk_format(self) -> DiskFormat: ... + def disk_format(self) -> DiskFormatOptions: ... @property def parent(self) -> Dataset | None: ... @property - def path(self) -> os.PathLike | str: ... + def path(self) -> str: ... @property def keepweakref(self) -> bool: ... @property - def _ncstring_attrs__(self) -> bool: ... + def auto_complex(self) -> bool: ... @property def __orthogonal_indexing__(self) -> bool: ... @@ -113,11 +131,11 @@ class Dataset: def createVariable( self, varname: str, - datatype: Datatype | npt.DTypeLike | CompoundType | VLType, - dimensions: str | bytes | Dimension | Iterable[str | bytes | Dimension]= (), - compression: Compression | None = None, + datatype: DatatypeOptions, + dimensions: DimensionsOptions = (), + compression: CompressionOptions = None, zlib: bool = False, - complevel: Literal[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, None] = 4, + complevel: CompressionLevelOptions = 4, shuffle: bool = True, szip_coding: Literal['nn', 'ec'] = 'nn', szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, @@ -125,10 +143,10 @@ class Dataset: fletcher32: bool = False, contiguous: bool = False, chunksizes: int | None = None, - endian: Literal['native', 'little', 'big'] = 'native', + endian: EndianOptions = 'native', least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: Literal['BitGroom', 'BitRound', 'GranularBitRound'] = 'BitGroom', + quantize_mode: QuantizeOptions = 'BitGroom', fill_value: bool | None = None, chunk_cache: int | None = None ) -> Variable: ... @@ -158,8 +176,8 @@ class Dataset: def fromcdl( cdlfilename: str, ncfilename: str | None = None, - mode: AccessMode = 'a', - format: Format = 'NETCDF4' + mode: AccessModeOptions = 'a', + format: FormatOptions = 'NETCDF4' ) -> Dataset: ... def tocdl( self, @@ -186,29 +204,23 @@ class Dataset: class Group(Dataset): - def __init__( - self, - parent: Group | Dataset, - name: str, - **kwargs - ): ... + def __init__( self, parent: Group | Dataset, name: str, **kwargs: Any) -> None: ... + + def close(self) -> NoReturn: ... class Dimension: - def __init__( - self, - grp: Group, - name: str, - size: int | None = None, - **kwargs - ): ... + def __init__( self, grp: Group, name: str, size: int | None = None, **kwargs: Any) -> None: ... @property def name(self) -> str: ... @property def size(self) -> int: ... + def group(self) -> Group: ... def isunlimited(self) -> bool: ... + + def __len__(self) -> int: ... def __str__(self) -> str: ... def __repr__(self) -> str: ... @@ -218,11 +230,11 @@ class Variable: self, grp: Group, name: str, - datatype: Datatype | npt.DTypeLike | str | CompoundType | VLType, - dimensions: Tuple[str] | Tuple[()] | str | Dimension = (), - compression: Compression | None = None, + datatype: DatatypeOptions, + dimensions: DimensionsOptions = (), + compression: CompressionOptions = None, zlib: bool = False, - complevel: Literal[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, None] = 4, + complevel: CompressionLevelOptions = 4, shuffle: bool = True, szip_coding: Literal['nn', 'ec'] = 'nn', szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, @@ -230,24 +242,29 @@ class Variable: fletcher32: bool = False, contiguous: bool = False, chunksizes: int | None = None, - endian: Literal['native', 'little', 'big'] = 'native', + endian: EndianOptions = 'native', least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: Literal['BitGroom', 'BitRound', - 'GranularBitRound'] = 'BitGroom', + quantize_mode: QuantizeOptions = 'BitGroom', fill_value: bool | None = None, chunk_cache: int | None = None, - **kwargs - ): ... + **kwargs: Any + ) -> None: ... @property - def dimensions(self) -> Tuple[str]: ... + def name(self) -> str: ... @property - def dtype(self) -> npt.DTypeLike: ... + def dtype(self) -> np.dtype: ... @property - def ndim(self) -> int: ... + def datatype(self) -> np.dtype | CompoundType | VLType | EnumType: ... + @property + def shape(self) -> tuple[int, ...]: ... + @property + def size(self) -> int: ... + @property + def dimensions(self) -> tuple[str, ...]: ... @property - def shape(self) -> Tuple[int]: ... + def ndim(self) -> int: ... @property def scale(self) -> bool: ... @property @@ -257,25 +274,19 @@ class Variable: @property def always_mask(self) -> bool: ... @property - def name(self) -> str: ... - @property - def datatype(self) -> CompoundType | VLType | EnumType: ... - @property - def size(self) -> int: ... - @property def __orthogonal_indexing__(self) -> bool: ... def group(self) -> Group: ... def ncattrs(self) -> list[str]: ... - def setncattr(self, name: str, value) -> None: ... - def setncattr_string(self, name: str, value) -> None: ... - def setncatts(self, attdict) -> None: ... + def setncattr(self, name: str, value: Any) -> None: ... + def setncattr_string(self, name: str, value: Any) -> None: ... + def setncatts(self, attdict: Mapping[str, Any]) -> None: ... def getncattr(self, name: str, encoding='utf-8'): ... def delncattr(self, name: str) -> None: ... - def filters(self) -> dict: ... - def quantization(self) -> int: ... - def endian(self) -> str: ... - def chunking(self) -> str | list[int]: ... + def filters(self) -> dict[str, Any]: ... + def quantization(self) -> tuple[int, QuantizeOptions] | None: ... + def endian(self) -> EndianOptions: ... + def chunking(self) -> Literal['contiguous'] | list[int] | None: ... def get_var_chunk_cache(self) -> tuple[int, int, float]: ... def set_var_chunk_cache( self, @@ -284,103 +295,88 @@ class Variable: preemption: float | None = None ) -> None: ... def renameAttribute(self, oldname: str, newname: str) -> None: ... - def assignValue(self, val) -> None: ... + def assignValue(self, val: Any) -> None: ... def getValue(self) -> Any: ... - def set_auto_chartostring(self, chartostring) -> None: ... - def use_nc_get_vars(self, use_nc_get_vars) -> None: ... - def set_auto_maskandscale(self, maskandscale) -> None: ... - def set_auto_scale(self, scale) -> None: ... - def set_auto_mask(self, mask) -> None: ... - def set_always_mask(self, always_mask) -> None: ... - def set_ncstring_attrs(self, ncstring_attrs) -> None: ... - def set_collective(self, value) -> None: ... - def get_dims(self) -> tuple[Dimension]: ... - - def __setitem__(self, elem, data): ... + def set_auto_chartostring(self, chartostring: bool) -> None: ... + def use_nc_get_vars(self, use_nc_get_vars: bool) -> None: ... + def set_auto_maskandscale(self, maskandscale: bool) -> None: ... + def set_auto_scale(self, scale: bool) -> None: ... + def set_auto_mask(self, mask: bool) -> None: ... + def set_always_mask(self, always_mask: bool) -> None: ... + def set_ncstring_attrs(self, ncstring_attrs: bool) -> None: ... + def set_collective(self, value: bool) -> None: ... + def get_dims(self) -> tuple[Dimension, ...]: ... + + def __delattr__(self, name: str) -> None: ... + def __setattr__(self, name: str, value: Any) -> None: ... + def __getattr__(self, name: str) -> Any: ... + def __getitem__(self, elem: Any) -> np.ndarray: ... + def __setitem__(self, elem: Any, data: npt.ArrayLike) -> None: ... + def __array__(self) -> np.ndarray: ... def __len__(self) -> int: ... - def __array__(self) -> npt.ArrayLike: ... def __str__(self) -> str: ... def __repr__(self) -> str: ... - def __delattr__(self, name: str): ... - def __setattr__(self, name: str, value): ... - def __getattr__(self, name: str): ... - def __getitem__(self, elem): ... class CompoundType: - def __init__(self, grp, datatype, dtype_name, **kwargs): ... + dtype: np.dtype + dtype_view: np.dtype + name: str - @property - def dtype(self) -> npt.DTypeLike: ... - @property - def name(self) -> str: ... - @property - def dtype_view(self) -> npt.DTypeLike: ... + def __init__(self, grp: Group, dt: npt.DTypeLike, dtype_name: str, **kwargs: Any) -> None: ... def __str__(self) -> str: ... def __repr__(self) -> str: ... - def __reduce__(self): ... + def __reduce__(self) -> NoReturn: ... class VLType: - def __init__( - self, - grp: Group, - datatype: npt.DTypeLike, - dtype_name: str, - **kwargs - ): ... + dtype: np.dtype + name: str | None - @property - def dtype(self) -> npt.DTypeLike: ... - @property - def name(self) -> str: ... + def __init__(self, grp: Group, dt: npt.DTypeLike, dtype_name: str, **kwargs: Any) -> None: ... def __str__(self) -> str: ... def __repr__(self) -> str: ... - def __reduce__(self): ... + def __reduce__(self) -> NoReturn: ... class EnumType: + dtype: np.dtype + name: str + enum_dict: Mapping[str, int] + def __init__( self, grp: Group, - datatype: npt.DTypeLike, + dt: npt.DTypeLike, dtype_name: str, - enum_dict: dict[str, int], + enum_dict: Mapping[str, int], **kwargs - ): ... - - @property - def dtype(self) -> npt.DTypeLike: ... - @property - def name(self) -> str: ... - @property - def enum_dict(self) -> dict[str, int]: ... + ) -> None: ... def __str__(self) -> str: ... def __repr__(self) -> str: ... - def __reduce__(self): ... + def __reduce__(self) -> NoReturn: ... class MFDataset(Dataset): def __init__( self, - files: str | os.PathLike, + files: str | Sequence[str | os.PathLike], check: bool = False, aggdim: str | None = None, - exclude: list[str] = [], + exclude: Sequence[str] = [], master_file: str | os.PathLike | None = None - ): ... + ) -> None: ... - def ncattrs(self): ... - def close(self): ... + def ncattrs(self) -> list[str]: ... + def close(self) -> None: ... def isopen(self) -> bool: ... - def __setattr__(self, name: str, value: Any): ... - def __getattribute__(self, name: str): ... + def __setattr__(self, name: str, value: Any) -> None: ... def __repr__(self) -> str: ... - def __reduce__(self): ... + def __reduce__(self) -> NoReturn: ... class _Variable: @@ -411,9 +407,9 @@ class MFTime(_Variable): def __getitem__(self, elem): ... -def stringtoarr(string, NUMCHARS: int, dtype: str = 'S'): ... -def stringtochar(a, encoding='utf-8'): ... -def chartostring(b, encoding='utf-8'): ... +def stringtoarr(string, NUMCHARS: int, dtype: str = 'S') -> np.ndarray: ... +def stringtochar(a, encoding: str | bytes | None = 'utf-8') -> np.ndarray: ... +def chartostring(b, encoding: str | bytes | None = 'utf-8') -> np.ndarray: ... def getlibversion() -> str: ... @@ -426,34 +422,3 @@ def set_chunk_cache( preemption: float | None = None ) -> None: ... def get_chunk_cache() -> tuple[int, int, float]: ... - - -def date2index( - dates: datetime.datetime | cftime.datetime, - nctime: MFTime, - calendar: Literal['standard', 'gregorian', 'proleptic_gregorian' 'noleap', - '365_day', '360_day', 'julian', 'all_leap', '366_day', None] = None, - select: Literal['exact', 'before', 'after', 'nearest'] = 'exact', - has_year_zero: bool | None = None -): ... - - -def date2num( - dates: datetime.datetime | cftime.datetime, - units: str, - calendar: Literal['standard', 'gregorian', 'proleptic_gregorian' 'noleap', - '365_day', '360_day', 'julian', 'all_leap', '366_day', None] = None, - has_year_zero: bool | None = None, - longdouble: bool = False -): ... - - -def num2date( - times: Any, - units: str, - calendar: Literal['standard', 'gregorian', 'proleptic_gregorian' 'noleap', - '365_day', '360_day', 'julian', 'all_leap', '366_day'] = 'standard', - only_use_cftime_datetimes: bool = True, - only_use_python_datetimes: bool = False, - has_year_zero: bool | None = None -): ... From 6324875dca828335911dc6f001320b3861714253 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Thu, 14 Dec 2023 22:50:05 +0100 Subject: [PATCH 1067/1504] remove _netCDF4 from reprs --- src/netCDF4/_netCDF4.pyx | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 1483dad63..526814047 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2556,7 +2556,7 @@ strings. return self.__str__() def __str__(self): - ncdump = [repr(type(self))] + ncdump = [repr(type(self)).replace("_netCDF4", "")] dimnames = tuple(_tostr(dimname)+'(%s)'%len(self.dimensions[dimname])\ for dimname in self.dimensions.keys()) varnames = tuple(\ @@ -4450,7 +4450,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. cdef int ierr, no_fill if not dir(self._grp): return 'Variable object no longer valid' - ncdump = [repr(type(self))] + ncdump = [repr(type(self)).replace("_netCDF4", "")] show_more_dtype = True if self._iscompound: kind = 'compound' @@ -6984,7 +6984,7 @@ Example usage (See `MFDataset.__init__` for more details): return all(map(lambda dset: dset.isopen(), self._cdf)) def __repr__(self): - ncdump = [repr(type(self))] + ncdump = [repr(type(self)).replace("_netCDF4", "")] dimnames = tuple(str(dimname) for dimname in self.dimensions.keys()) varnames = tuple(str(varname) for varname in self.variables.keys()) grpnames = () @@ -7048,7 +7048,7 @@ class _Variable: except: raise AttributeError(name) def __repr__(self): - ncdump = [repr(type(self))] + ncdump = [repr(type(self)).replace("_netCDF4", "")] dimnames = tuple(str(dimname) for dimname in self.dimensions) ncdump.append('%s %s%s' % (self.dtype, self._name, dimnames)) for name in self.ncattrs(): From 7d8efdbff65651249437441fa86cc27c82d71b7b Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Thu, 14 Dec 2023 22:50:17 +0100 Subject: [PATCH 1068/1504] add linebreaks --- src/netCDF4/__init__.py | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py index ac93047a2..91bf1ed03 100644 --- a/src/netCDF4/__init__.py +++ b/src/netCDF4/__init__.py @@ -12,11 +12,13 @@ __has_bzip2_support__, __has_blosc_support__, __has_szip_support__, __has_set_alignment__) import os -__all__ =\ -['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache','set_alignment','get_alignment'] -__pdoc__ = { - 'utils': False, -} +__all__ = [ + 'Dataset', 'Variable', 'Dimension', 'Group', 'MFDataset', 'MFTime', 'CompoundType', + 'VLType', 'date2num', 'num2date', 'date2index', 'stringtochar', 'chartostring', + 'stringtoarr', 'getlibversion', 'EnumType', 'get_chunk_cache', 'set_chunk_cache', + 'set_alignment', 'get_alignment' +] +__pdoc__ = {'utils': False} # if HDF5_PLUGIN_PATH not set, point to package path if plugins live there pluginpath = os.path.join(__path__[0],'plugins') if 'HDF5_PLUGIN_PATH' not in os.environ and\ From a389d069b37c5eaeb7dfc3c91b75b74a99f746d0 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Thu, 14 Dec 2023 22:52:47 +0100 Subject: [PATCH 1069/1504] update gitignore --- .gitignore | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/.gitignore b/.gitignore index a808b3552..f188f233a 100644 --- a/.gitignore +++ b/.gitignore @@ -2,8 +2,11 @@ build/ *.pyc dist/ *.egg-info/ -netCDF4/_netCDF4.c -netCDF4/*.so +__pycache__ +.mypy_cache +src/netCDF4/*.c +src/netCDF4/*.so +src/netCDF4/*.pyd include/constants.pyx include/parallel_support_imports.pxi netcdftime/_netcdftime.c From 49060ad725ae51fddb21b2590bc24e38b49d687e Mon Sep 17 00:00:00 2001 From: Peter Hill Date: Fri, 15 Dec 2023 20:52:31 +0000 Subject: [PATCH 1070/1504] Fix URL for nc-complex submodule Fixes #1300 --- .gitmodules | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.gitmodules b/.gitmodules index 7b0ff7c97..c7064b7b3 100644 --- a/.gitmodules +++ b/.gitmodules @@ -1,3 +1,3 @@ [submodule "external/nc_complex"] path = external/nc_complex - url = git@github.com:PlasmaFAIR/nc-complex.git + url = https://github.com/PlasmaFAIR/nc-complex.git From 28f37e4d622ae2cca8efb94bd6468a4c9423fa1d Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 15 Dec 2023 22:05:20 +0100 Subject: [PATCH 1071/1504] add stubtest workflow co-authored by https://github.com/Woefie --- .github/stubtest-allowlist | 45 ++++++++++++++++++++++++++ .github/workflows/stubtest.yml | 58 ++++++++++++++++++++++++++++++++++ pyproject.toml | 10 ++++++ 3 files changed, 113 insertions(+) create mode 100644 .github/stubtest-allowlist create mode 100644 .github/workflows/stubtest.yml diff --git a/.github/stubtest-allowlist b/.github/stubtest-allowlist new file mode 100644 index 000000000..83b6855c0 --- /dev/null +++ b/.github/stubtest-allowlist @@ -0,0 +1,45 @@ +netCDF4.AccessModeOptions +netCDF4.CompressionLevelOptions +netCDF4.CompressionOptions +netCDF4.Dataset.__dealloc +netCDF4.DatatypeOptions +netCDF4.Dimension.__reduce_cython__ +netCDF4.Dimension.__setstate_cython__ +netCDF4.DimensionsOptions +netCDF4.DiskFormatOptions +netCDF4.EndianOptions +netCDF4.FormatOptions +netCDF4.QuantizeOptions +netCDF4.Variable.auto_complex +netCDF4.__has_ncfilter__ +netCDF4.__has_parallel_support__ +netCDF4._netCDF4.Dataset.__dealloc +netCDF4._netCDF4.Dimension.__reduce_cython__ +netCDF4._netCDF4.Dimension.__setstate_cython__ +netCDF4._netCDF4.NC_DISKLESS +netCDF4._netCDF4.NC_PERSIST +netCDF4._netCDF4.Variable.auto_complex +netCDF4._netCDF4.__has_blosc_support__ +netCDF4._netCDF4.__has_bzip2_support__ +netCDF4._netCDF4.__has_cdf5_format__ +netCDF4._netCDF4.__has_nc_create_mem__ +netCDF4._netCDF4.__has_nc_inq_format_extended__ +netCDF4._netCDF4.__has_nc_inq_path__ +netCDF4._netCDF4.__has_nc_open_mem__ +netCDF4._netCDF4.__has_ncfilter__ +netCDF4._netCDF4.__has_parallel4_support__ +netCDF4._netCDF4.__has_parallel_support__ +netCDF4._netCDF4.__has_pnetcdf_support__ +netCDF4._netCDF4.__has_quantization_support__ +netCDF4._netCDF4.__has_rename_grp__ +netCDF4._netCDF4.__has_set_alignment__ +netCDF4._netCDF4.__has_szip_support__ +netCDF4._netCDF4.__has_zstandard_support__ +netCDF4._netCDF4.__hdf5libversion__ +netCDF4._netCDF4.__netcdf4libversion__ +netCDF4._netCDF4.__reduce_cython__ +netCDF4._netCDF4.__setstate_cython__ +netCDF4._netCDF4.__test__ +netCDF4._netCDF4.dtype_is_complex +netCDF4._netCDF4.unicode_error +netCDF4.utils.bytes \ No newline at end of file diff --git a/.github/workflows/stubtest.yml b/.github/workflows/stubtest.yml new file mode 100644 index 000000000..bb60f711c --- /dev/null +++ b/.github/workflows/stubtest.yml @@ -0,0 +1,58 @@ +name: Stubtest +on: [push, pull_request] +jobs: + build-linux: + name: Python (${{ matrix.python-version }}) + runs-on: ubuntu-latest + env: + NETCDF_DIR: ${{ github.workspace }}/.. + CC: mpicc.mpich + #NO_NET: 1 + strategy: + matrix: + python-version: ["3.11"] + steps: + + - uses: actions/checkout@v4 + + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v4 + with: + python-version: ${{ matrix.python-version }} + + - name: Install Ubuntu Dependencies + run: | + sudo apt-get update + sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev + echo "Download and build netCDF github master" + git clone https://github.com/Unidata/netcdf-c + pushd netcdf-c + export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include" + export LDFLAGS="-L${NETCDF_DIR}/lib" + export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz" + autoreconf -i + ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 + make -j 2 + make install + popd + +# - name: The job has failed +# if: ${{ failure() }} +# run: | +# cd netcdf-c-${NETCDF_VERSION} +# cat config.log + + - name: Install python dependencies via pip + run: | + python -m pip install --upgrade pip + pip install numpy cython cftime pytest twine wheel check-manifest mpi4py mypy + + - name: Install netcdf4-python + run: | + export PATH=${NETCDF_DIR}/bin:${PATH} + export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c/plugins/plugindir + python setup.py develop + + - name: Stubtest + run: | + stubtest netCDF4 --allowlist .github/stubtest-allowlist --mypy-config-file=pyproject.toml \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml index 16636ec1d..bd63cc69e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -75,3 +75,13 @@ where = ["src"] [tool.pytest.ini_options] pythonpath = ["test"] + +[tool.mypy] +files = ["src/netCDF4"] + +[[tool.mypy.overrides]] +ignore_missing_imports = true +module = [ + "cftime.*", + "cython.*" +] \ No newline at end of file From ca7215ae726b14be71b6a8149fc4bf8b98109516 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 15 Dec 2023 22:06:18 +0100 Subject: [PATCH 1072/1504] fix repr replacement --- src/netCDF4/__init__.pyi | 12 ++++++------ src/netCDF4/_netCDF4.pyx | 8 ++++---- 2 files changed, 10 insertions(+), 10 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 94a8f0945..f6d7e1480 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -1,11 +1,11 @@ + +import os from typing import TypeAlias, Literal, Any, NoReturn, Iterable, Mapping, Union, Sequence from typing_extensions import Buffer + +from cftime import num2date, date2num, date2index import numpy as np import numpy.typing as npt -import os -import datetime -import cftime -from cftime import num2date, date2num, date2index __all__ = [ 'Dataset', 'Variable', 'Dimension', 'Group', 'MFDataset', 'MFTime', 'CompoundType', @@ -204,13 +204,13 @@ class Dataset: class Group(Dataset): - def __init__( self, parent: Group | Dataset, name: str, **kwargs: Any) -> None: ... + def __init__(self, parent: Group | Dataset, name: str, **kwargs: Any) -> None: ... def close(self) -> NoReturn: ... class Dimension: - def __init__( self, grp: Group, name: str, size: int | None = None, **kwargs: Any) -> None: ... + def __init__(self, grp: Group, name: str, size: int | None = None, **kwargs: Any) -> None: ... @property def name(self) -> str: ... diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 526814047..44326f84e 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2556,7 +2556,7 @@ strings. return self.__str__() def __str__(self): - ncdump = [repr(type(self)).replace("_netCDF4", "")] + ncdump = [repr(type(self)).replace("._netCDF4", "")] dimnames = tuple(_tostr(dimname)+'(%s)'%len(self.dimensions[dimname])\ for dimname in self.dimensions.keys()) varnames = tuple(\ @@ -4450,7 +4450,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. cdef int ierr, no_fill if not dir(self._grp): return 'Variable object no longer valid' - ncdump = [repr(type(self)).replace("_netCDF4", "")] + ncdump = [repr(type(self)).replace("._netCDF4", "")] show_more_dtype = True if self._iscompound: kind = 'compound' @@ -6984,7 +6984,7 @@ Example usage (See `MFDataset.__init__` for more details): return all(map(lambda dset: dset.isopen(), self._cdf)) def __repr__(self): - ncdump = [repr(type(self)).replace("_netCDF4", "")] + ncdump = [repr(type(self)).replace("._netCDF4", "")] dimnames = tuple(str(dimname) for dimname in self.dimensions.keys()) varnames = tuple(str(varname) for varname in self.variables.keys()) grpnames = () @@ -7048,7 +7048,7 @@ class _Variable: except: raise AttributeError(name) def __repr__(self): - ncdump = [repr(type(self)).replace("_netCDF4", "")] + ncdump = [repr(type(self)).replace("._netCDF4", "")] dimnames = tuple(str(dimname) for dimname in self.dimensions) ncdump.append('%s %s%s' % (self.dtype, self._name, dimnames)) for name in self.ncattrs(): From f9655989ac2e6dd3038eb6febf60733707e953c9 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 15 Dec 2023 22:06:31 +0100 Subject: [PATCH 1073/1504] add _netCDF4 stubs --- src/netCDF4/_netCDF4.pyi | 9 +++++++++ 1 file changed, 9 insertions(+) create mode 100644 src/netCDF4/_netCDF4.pyi diff --git a/src/netCDF4/_netCDF4.pyi b/src/netCDF4/_netCDF4.pyi new file mode 100644 index 000000000..04d83376b --- /dev/null +++ b/src/netCDF4/_netCDF4.pyi @@ -0,0 +1,9 @@ +# The definitions are intendionally done in the __init__. +# This file only exists in case someone imports from netCDF4._netCDF4 +from . import ( + Dataset, Variable, Dimension, Group, MFDataset, MFTime, CompoundType, + VLType, date2num, num2date, date2index, stringtochar, chartostring, + stringtoarr, getlibversion, EnumType, get_chunk_cache, set_chunk_cache, + set_alignment, get_alignment, default_fillvals, default_encoding, + NetCDF4MissingFeatureException, is_native_big, is_native_little +) \ No newline at end of file From d9f7ffdcc2357f05d07bc2b886742fb950b2677a Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 15 Dec 2023 22:18:22 +0100 Subject: [PATCH 1074/1504] add entry to changelog --- Changelog | 1 + 1 file changed, 1 insertion(+) diff --git a/Changelog b/Changelog index 3a0168ecf..a583245f9 100644 --- a/Changelog +++ b/Changelog @@ -3,6 +3,7 @@ * add support for complex numbers via `auto_complex` keyword to `Dataset` (PR #1295) * fix for deprecated Cython `DEF` and `IF` statements using compatibility header with shims for unavailable functionality (PR #1277) + * add static type hints (PR #1302) version 1.6.5 (tag v1.6.5rel) =============================== From a0c6e91a2e95bba8f23c0a8ce508da4852747c2e Mon Sep 17 00:00:00 2001 From: Ben Boeckel Date: Wed, 20 Dec 2023 10:23:21 -0500 Subject: [PATCH 1075/1504] mpi-compat: support MPI_Message on MS-MPI MS-MPI does not define an accurate `MPI_VERSION`, so `MPI_Message` is mis-detected. See: https://github.com/mpi4py/mpi4py/issues/19 --- Changelog | 1 + include/mpi-compat.h | 4 ++++ 2 files changed, 5 insertions(+) diff --git a/Changelog b/Changelog index 3a0168ecf..69893ba41 100644 --- a/Changelog +++ b/Changelog @@ -3,6 +3,7 @@ * add support for complex numbers via `auto_complex` keyword to `Dataset` (PR #1295) * fix for deprecated Cython `DEF` and `IF` statements using compatibility header with shims for unavailable functionality (PR #1277) + * add support for MS-MPI `MPI_Message` detection (PR #1305) version 1.6.5 (tag v1.6.5rel) =============================== diff --git a/include/mpi-compat.h b/include/mpi-compat.h index 5563ae933..adf6219b7 100644 --- a/include/mpi-compat.h +++ b/include/mpi-compat.h @@ -10,6 +10,10 @@ #include +#ifdef MSMPI_VER +#define PyMPI_HAVE_MPI_Message 1 +#endif + #if (MPI_VERSION < 3) && !defined(PyMPI_HAVE_MPI_Message) typedef void *PyMPI_MPI_Message; #define MPI_Message PyMPI_MPI_Message From 4933623685f7c5fd6c7886182db56de7c146d96f Mon Sep 17 00:00:00 2001 From: Ben Boeckel Date: Wed, 20 Dec 2023 10:24:25 -0500 Subject: [PATCH 1076/1504] szip: the library name is `szip` on Windows --- Changelog | 1 + setup.py | 6 +++++- 2 files changed, 6 insertions(+), 1 deletion(-) diff --git a/Changelog b/Changelog index 3a0168ecf..e626fc4e5 100644 --- a/Changelog +++ b/Changelog @@ -3,6 +3,7 @@ * add support for complex numbers via `auto_complex` keyword to `Dataset` (PR #1295) * fix for deprecated Cython `DEF` and `IF` statements using compatibility header with shims for unavailable functionality (PR #1277) + * use `szip` as the library name on Windows (PR #1304) version 1.6.5 (tag v1.6.5rel) =============================== diff --git a/setup.py b/setup.py index 232eedafd..c23eb0348 100644 --- a/setup.py +++ b/setup.py @@ -315,7 +315,11 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs): if szip_incdir is None and szip_dir is not None: szip_incdir = os.path.join(szip_dir, 'include') if szip_incdir is not None and szip_libdir is not None: - libs.append('sz') + if sys.platform == 'win32': + libs.append('szip') + else: + libs.append('sz') + lib_dirs.append(szip_libdir) inc_dirs.append(szip_incdir) # add hdf4 to link if desired. From 60d27910d728a3d796db9b9e0e27e0b81409f6b0 Mon Sep 17 00:00:00 2001 From: stubbiali Date: Tue, 9 Jan 2024 10:31:08 +0100 Subject: [PATCH 1077/1504] Relax constraint on setuptools. --- pyproject.toml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index ba1807a9f..cb3d98717 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,9 +1,9 @@ [build-system] requires = [ "Cython>=0.29", - "mpi4py>=3.1", + "mpi4py>=3.1", "oldest-supported-numpy", - "setuptools>=65.5.0", + "setuptools>=61", ] build-backend = "setuptools.build_meta" From 0744c89bb06489b17f1ed190eb26eed435268da9 Mon Sep 17 00:00:00 2001 From: stubbiali Date: Tue, 9 Jan 2024 15:11:50 +0100 Subject: [PATCH 1078/1504] Add in-tree build backend. --- MANIFEST.in | 1 + _build/backend.py | 25 +++++++++++++++++++++++++ pyproject.toml | 5 +++-- 3 files changed, 29 insertions(+), 2 deletions(-) create mode 100644 _build/backend.py diff --git a/MANIFEST.in b/MANIFEST.in index e3497466e..545dec44b 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -22,3 +22,4 @@ include *.py include *.release include *.sh include LICENSE +include _build/*.py diff --git a/_build/backend.py b/_build/backend.py new file mode 100644 index 000000000..cefffa925 --- /dev/null +++ b/_build/backend.py @@ -0,0 +1,25 @@ +# -*- coding: utf-8 -*- +import os +from setuptools.build_meta import * +import subprocess + + +def netcdf_has_parallel_support(): + netcdf4_dir = os.environ.get("NETCDF4_DIR") + ncconfig = os.path.join(netcdf4_dir, "bin", "nc-config") if netcdf4_dir else "nc-config" + process = subprocess.run([ncconfig, "--has-parallel4"], capture_output=True) + out = process.stdout.decode("utf-8").rstrip() + return out == "yes" + + +def get_requires_for_build_editable(config_settings=None): + return ["mpi4py>=3.1"] if netcdf_has_parallel_support() else [] + + +def get_requires_for_build_wheel(config_settings=None): + return ["mpi4py>=3.1"] if netcdf_has_parallel_support() else [] + + +def get_requires_for_build_sdist(config_settings=None): + return ["mpi4py>=3.1"] if netcdf_has_parallel_support() else [] + diff --git a/pyproject.toml b/pyproject.toml index cb3d98717..f0467a670 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,11 +1,12 @@ [build-system] requires = [ "Cython>=0.29", - "mpi4py>=3.1", "oldest-supported-numpy", "setuptools>=61", + "wheel" ] -build-backend = "setuptools.build_meta" +build-backend = "backend" +backend-path = ["_build"] [project] name = "netCDF4" From 5cb9aa3ee6c27ddf6953c1f5a34d4e35988a7c7f Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Wed, 17 Jan 2024 23:10:02 +0100 Subject: [PATCH 1079/1504] submodule update --- .github/workflows/stubtest.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/workflows/stubtest.yml b/.github/workflows/stubtest.yml index bb60f711c..e515dac3b 100644 --- a/.github/workflows/stubtest.yml +++ b/.github/workflows/stubtest.yml @@ -27,6 +27,7 @@ jobs: echo "Download and build netCDF github master" git clone https://github.com/Unidata/netcdf-c pushd netcdf-c + git submodule update --init --recursive export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include" export LDFLAGS="-L${NETCDF_DIR}/lib" export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz" From 55455dad85177082c040a52afc75d8d1e483efc5 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Wed, 17 Jan 2024 23:21:43 +0100 Subject: [PATCH 1080/1504] add stubtest to existing workflow --- .github/workflows/build_master.yml | 5 +++ .github/workflows/stubtest.yml | 59 ------------------------------ 2 files changed, 5 insertions(+), 59 deletions(-) delete mode 100644 .github/workflows/stubtest.yml diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index 97dea032d..7f47c7c58 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -54,6 +54,7 @@ jobs: export PATH=${NETCDF_DIR}/bin:${PATH} export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c/plugins/plugindir python setup.py install + - name: Test run: | export PATH=${NETCDF_DIR}/bin:${PATH} @@ -78,3 +79,7 @@ jobs: else echo "hdf5 compressed mpi test passed!" fi + + - name: Stubtest + run: | + stubtest netCDF4 --allowlist .github/stubtest-allowlist --mypy-config-file=pyproject.toml diff --git a/.github/workflows/stubtest.yml b/.github/workflows/stubtest.yml deleted file mode 100644 index e515dac3b..000000000 --- a/.github/workflows/stubtest.yml +++ /dev/null @@ -1,59 +0,0 @@ -name: Stubtest -on: [push, pull_request] -jobs: - build-linux: - name: Python (${{ matrix.python-version }}) - runs-on: ubuntu-latest - env: - NETCDF_DIR: ${{ github.workspace }}/.. - CC: mpicc.mpich - #NO_NET: 1 - strategy: - matrix: - python-version: ["3.11"] - steps: - - - uses: actions/checkout@v4 - - - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v4 - with: - python-version: ${{ matrix.python-version }} - - - name: Install Ubuntu Dependencies - run: | - sudo apt-get update - sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev - echo "Download and build netCDF github master" - git clone https://github.com/Unidata/netcdf-c - pushd netcdf-c - git submodule update --init --recursive - export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include" - export LDFLAGS="-L${NETCDF_DIR}/lib" - export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz" - autoreconf -i - ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 - make -j 2 - make install - popd - -# - name: The job has failed -# if: ${{ failure() }} -# run: | -# cd netcdf-c-${NETCDF_VERSION} -# cat config.log - - - name: Install python dependencies via pip - run: | - python -m pip install --upgrade pip - pip install numpy cython cftime pytest twine wheel check-manifest mpi4py mypy - - - name: Install netcdf4-python - run: | - export PATH=${NETCDF_DIR}/bin:${PATH} - export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c/plugins/plugindir - python setup.py develop - - - name: Stubtest - run: | - stubtest netCDF4 --allowlist .github/stubtest-allowlist --mypy-config-file=pyproject.toml \ No newline at end of file From 58a5ba07a0b59ec83fb54580d015af17014325aa Mon Sep 17 00:00:00 2001 From: jswhit Date: Sun, 21 Jan 2024 09:24:35 -0700 Subject: [PATCH 1081/1504] fix for issue1306 --- src/netCDF4/_netCDF4.pyx | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index dcfe221a2..1fe1070ec 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -4987,7 +4987,10 @@ rename a `Variable` attribute named `oldname` to `newname`.""" # special case of scalar VLEN data[0] = datout else: - data[tuple(i)] = datout.reshape(shape) + if self._isvlen and not shape: + data[tuple(i)] = datout.item() + else: + data[tuple(i)] = datout.reshape(shape) # Remove extra singleton dimensions. if hasattr(data,'shape'): From 69824b34c1adef5cff0c5553e2ae3c91074b3970 Mon Sep 17 00:00:00 2001 From: jswhit Date: Sun, 21 Jan 2024 09:29:38 -0700 Subject: [PATCH 1082/1504] update --- src/netCDF4/_netCDF4.pyx | 1 + 1 file changed, 1 insertion(+) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 1fe1070ec..271a9e4a9 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -4988,6 +4988,7 @@ rename a `Variable` attribute named `oldname` to `newname`.""" data[0] = datout else: if self._isvlen and not shape: + # issue #1306 - convert length 1 object array to string data[tuple(i)] = datout.item() else: data[tuple(i)] = datout.reshape(shape) From 0214a9c149a122eee726c5e1baca614ca795296a Mon Sep 17 00:00:00 2001 From: jswhit Date: Sun, 21 Jan 2024 09:50:05 -0700 Subject: [PATCH 1083/1504] add test --- test/test_vlen.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/test/test_vlen.py b/test/test_vlen.py index 5d7d4f2ce..9e51bfb2d 100644 --- a/test/test_vlen.py +++ b/test/test_vlen.py @@ -69,6 +69,8 @@ def runTest(self): assert_array_equal(f.variables['vlen_scalar'][...],np.array([1,2,3],np.int16)) data2 = v[:] data2s = vs[:] + # issue #1306 + assert repr(vs[[0,2,3],0]) == "array(['ab', 'abcdefghijkl', 'abcdefghijklmnopq'], dtype=object)" for i in range(nlons): for j in range(nlats): assert_array_equal(data2[j,i], data[j,i]) From 98b127befcf0d06ae704a5de61aaf472338fc10e Mon Sep 17 00:00:00 2001 From: jswhit Date: Mon, 22 Jan 2024 09:52:24 -0700 Subject: [PATCH 1084/1504] update --- Changelog | 3 +++ 1 file changed, 3 insertions(+) diff --git a/Changelog b/Changelog index f7c8192da..9593159a5 100644 --- a/Changelog +++ b/Changelog @@ -5,6 +5,9 @@ with shims for unavailable functionality (PR #1277) * use `szip` as the library name on Windows (PR #1304) * add support for MS-MPI `MPI_Message` detection (PR #1305) + * fix for issue #1306 - surprising result when indexing vlen str with non-contiguous + indices. + version 1.6.5 (tag v1.6.5rel) From 968f4578e5c0f1ea06bc2cbc0d642b5f34ed1247 Mon Sep 17 00:00:00 2001 From: jswhit Date: Fri, 16 Feb 2024 12:43:45 -0700 Subject: [PATCH 1085/1504] assert is not a function --- test/test_Unsigned.py | 12 ++++++------ test/test_chunk_cache.py | 6 +++--- test/test_compoundatt.py | 8 ++++---- test/test_compoundvar.py | 12 ++++++------ test/test_compression.py | 12 ++++++------ test/test_compression_bzip2.py | 2 +- test/test_compression_quant.py | 28 ++++++++++++++-------------- test/test_compression_zstd.py | 2 +- test/test_dap.py | 6 +++--- test/test_dims.py | 2 +- test/test_diskless.py | 4 ++-- test/test_enum.py | 4 ++-- test/test_fancyslicing.py | 2 +- test/test_grps2.py | 6 +++--- test/test_issue908.py | 2 +- test/test_masked.py | 4 ++-- test/test_masked4.py | 6 +++--- test/test_scaled.py | 2 +- test/test_shape.py | 2 +- test/test_slicing.py | 6 +++--- test/test_stringarr.py | 8 ++++---- test/test_types.py | 2 +- test/test_unicodeatt.py | 8 ++++---- test/test_vlen.py | 7 ++++--- 24 files changed, 77 insertions(+), 76 deletions(-) diff --git a/test/test_Unsigned.py b/test/test_Unsigned.py index e2999fe59..f21cf173f 100644 --- a/test/test_Unsigned.py +++ b/test/test_Unsigned.py @@ -34,20 +34,20 @@ def test_unsigned(self): # issue 671 with netCDF4.Dataset(test_dir / "issue671.nc") as f: data1 = f['soil_moisture'][:] - assert(np.ma.isMA(data1)) + assert np.ma.isMA(data1) f.set_auto_scale(False) data2 = f['soil_moisture'][:] - assert(data1.mask.sum() == data2.mask.sum()) + assert data1.mask.sum() == data2.mask.sum() # issue 794 # test that valid_min/valid_max/_FillValue are # treated as unsigned integers. with netCDF4.Dataset(test_dir / "20171025_2056.Cloud_Top_Height.nc") as f: data = f['HT'][:] - assert(data.mask.sum() == 57432) - assert(int(data.max()) == 15430) - assert(int(data.min()) == 0) - assert(data.dtype == np.float32) + assert data.mask.sum() == 57432 + assert int(data.max()) == 15430 + assert int(data.min()) == 0 + assert data.dtype == np.float32 if __name__ == '__main__': diff --git a/test/test_chunk_cache.py b/test/test_chunk_cache.py index 129ce7128..ef2d56b6e 100644 --- a/test/test_chunk_cache.py +++ b/test/test_chunk_cache.py @@ -17,7 +17,7 @@ def setUp(self): # this change lasts only as long as file is open. v = nc.createVariable('frank','f',('fred',),chunk_cache=15000) size, nelems, preempt = v.get_var_chunk_cache() - assert(size==15000) + assert size==15000 self.file=file_name nc.close() @@ -31,10 +31,10 @@ def runTest(self): netCDF4.set_chunk_cache(cache_size, cache_nelems, cache_preempt) nc = netCDF4.Dataset(self.file, mode='r') # check to see that chunk cache parameters were changed. - assert(netCDF4.get_chunk_cache() == (cache_size, cache_nelems, cache_preempt)) + assert netCDF4.get_chunk_cache() == (cache_size, cache_nelems, cache_preempt) # change cache parameters for variable, check nc['frank'].set_var_chunk_cache(cache_size2, cache_nelems2, cache_preempt2) - assert(nc['frank'].get_var_chunk_cache() == (cache_size2, cache_nelems2, cache_preempt2)) + assert nc['frank'].get_var_chunk_cache() == (cache_size2, cache_nelems2, cache_preempt2) nc.close() if __name__ == '__main__': diff --git a/test/test_compoundatt.py b/test/test_compoundatt.py index fa90e7d0f..e27a05721 100644 --- a/test/test_compoundatt.py +++ b/test/test_compoundatt.py @@ -63,10 +63,10 @@ def runTest(self): assert_array_equal(vv.units['speed'], windunits['speed'].squeeze()) assert_array_equal(vv.units['direction'],\ windunits['direction'].squeeze()) - assert(v.units['speed'] == b'm/s') - assert(v.units['direction'] == b'degrees') - assert(vv.units['speed'] == b'm/s') - assert(vv.units['direction'] == b'degrees') + assert v.units['speed'] == b'm/s' + assert v.units['direction'] == b'degrees' + assert vv.units['speed'] == b'm/s' + assert vv.units['direction'] == b'degrees' f.close() if __name__ == '__main__': diff --git a/test/test_compoundvar.py b/test/test_compoundvar.py index 72b689206..5e1780f9e 100644 --- a/test/test_compoundvar.py +++ b/test/test_compoundvar.py @@ -71,8 +71,8 @@ def setUp(self): dataoutg = vv[:] assert (cmptype4 == dtype4a) # data type should be aligned assert (dataout.dtype == dtype4a) # data type should be aligned - assert(list(f.cmptypes.keys()) ==\ - [TYPE_NAME1,TYPE_NAME2,TYPE_NAME3,TYPE_NAME4,TYPE_NAME5]) + assert list(f.cmptypes.keys()) ==\ + [TYPE_NAME1,TYPE_NAME2,TYPE_NAME3,TYPE_NAME4,TYPE_NAME5] assert_array_equal(dataout['xxx']['xx']['i'],data['xxx']['xx']['i']) assert_array_equal(dataout['xxx']['xx']['j'],data['xxx']['xx']['j']) assert_array_almost_equal(dataout['xxx']['yy']['x'],data['xxx']['yy']['x']) @@ -99,8 +99,8 @@ def runTest(self): dataoutg = vv[:] # make sure data type is aligned assert (f.cmptypes['cmp4'] == dtype4a) - assert(list(f.cmptypes.keys()) ==\ - [TYPE_NAME1,TYPE_NAME2,TYPE_NAME3,TYPE_NAME4,TYPE_NAME5]) + assert list(f.cmptypes.keys()) ==\ + [TYPE_NAME1,TYPE_NAME2,TYPE_NAME3,TYPE_NAME4,TYPE_NAME5] assert_array_equal(dataout['xxx']['xx']['i'],data['xxx']['xx']['i']) assert_array_equal(dataout['xxx']['xx']['j'],data['xxx']['xx']['j']) assert_array_almost_equal(dataout['xxx']['yy']['x'],data['xxx']['yy']['x']) @@ -122,7 +122,7 @@ def runTest(self): station_data_t2 = f.createCompoundType(dtype_nest,'station_data') f.createDimension('station',None) statdat = f.createVariable('station_obs', station_data_t2, ('station',)) - assert(statdat.dtype == station_data_t2.dtype) + assert statdat.dtype == station_data_t2.dtype datain = np.empty(2,station_data_t2.dtype_view) datain['observation'][:] = (123,314) datain['station_name'][:] = ('Boulder','New York') @@ -132,7 +132,7 @@ def runTest(self): f.close() f = Dataset(self.file) dataout = f['station_obs'][:] - assert(dataout.dtype == station_data_t2.dtype_view) + assert dataout.dtype == station_data_t2.dtype_view assert_array_equal(datain, dataout) f.close() diff --git a/test/test_compression.py b/test/test_compression.py index f28ed0b96..78827ddff 100644 --- a/test/test_compression.py +++ b/test/test_compression.py @@ -103,7 +103,7 @@ def runTest(self): {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':6,'fletcher32':False} assert f.variables['data2'].filters() ==\ {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':6,'fletcher32':False} - assert(size < 0.95*uncompressed_size) + assert size < 0.95*uncompressed_size f.close() # check compression with shuffle f = Dataset(self.files[2]) @@ -114,7 +114,7 @@ def runTest(self): {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':False} assert f.variables['data2'].filters() ==\ {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':False} - assert(size < 0.85*uncompressed_size) + assert size < 0.85*uncompressed_size f.close() # check lossy compression without shuffle f = Dataset(self.files[3]) @@ -122,14 +122,14 @@ def runTest(self): checkarray = _quantize(array,lsd) assert_almost_equal(checkarray,f.variables['data'][:]) assert_almost_equal(checkarray,f.variables['data2'][:]) - assert(size < 0.27*uncompressed_size) + assert size < 0.27*uncompressed_size f.close() # check lossy compression with shuffle f = Dataset(self.files[4]) size = os.stat(self.files[4]).st_size assert_almost_equal(checkarray,f.variables['data'][:]) assert_almost_equal(checkarray,f.variables['data2'][:]) - assert(size < 0.20*uncompressed_size) + assert size < 0.20*uncompressed_size size_save = size f.close() # check lossy compression with shuffle and fletcher32 checksum. @@ -141,9 +141,9 @@ def runTest(self): {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':True} assert f.variables['data2'].filters() ==\ {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':True} - assert(size < 0.20*uncompressed_size) + assert size < 0.20*uncompressed_size # should be slightly larger than without fletcher32 - assert(size > size_save) + assert size > size_save # check chunksizes f.close() f = Dataset(self.files[6]) diff --git a/test/test_compression_bzip2.py b/test/test_compression_bzip2.py index fb0bd3162..75c0fced1 100644 --- a/test/test_compression_bzip2.py +++ b/test/test_compression_bzip2.py @@ -47,7 +47,7 @@ def runTest(self): assert_almost_equal(array,f.variables['data'][:]) assert f.variables['data'].filters() ==\ {'zlib':False,'szip':False,'zstd':False,'bzip2':True,'blosc':False,'shuffle':False,'complevel':4,'fletcher32':False} - assert(size < 0.96*uncompressed_size) + assert size < 0.96*uncompressed_size f.close() diff --git a/test/test_compression_quant.py b/test/test_compression_quant.py index 10c801592..3654bf9d5 100644 --- a/test/test_compression_quant.py +++ b/test/test_compression_quant.py @@ -61,7 +61,7 @@ def runTest(self): assert_almost_equal(data_array,f.variables['data'][:]) assert f.variables['data'].filters() ==\ {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':complevel,'fletcher32':False} - assert(size < 0.95*uncompressed_size) + assert size < 0.95*uncompressed_size f.close() # check compression with shuffle f = Dataset(self.files[2]) @@ -70,43 +70,43 @@ def runTest(self): assert_almost_equal(data_array,f.variables['data'][:]) assert f.variables['data'].filters() ==\ {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':complevel,'fletcher32':False} - assert(size < 0.85*uncompressed_size) + assert size < 0.85*uncompressed_size f.close() # check lossy compression without shuffle f = Dataset(self.files[3]) size = os.stat(self.files[3]).st_size errmax = (np.abs(data_array-f.variables['data'][:])).max() #print('compressed lossy no shuffle = ',size,' max err = ',errmax) - assert(f.variables['data'].quantization() == (nsd,'BitGroom')) - assert(errmax < 1.e-3) - assert(size < 0.35*uncompressed_size) + assert f.variables['data'].quantization() == (nsd,'BitGroom') + assert errmax < 1.e-3 + assert size < 0.35*uncompressed_size f.close() # check lossy compression with shuffle f = Dataset(self.files[4]) size = os.stat(self.files[4]).st_size errmax = (np.abs(data_array-f.variables['data'][:])).max() print('compressed lossy with shuffle and standard quantization = ',size,' max err = ',errmax) - assert(f.variables['data'].quantization() == (nsd,'BitGroom')) - assert(errmax < 1.e-3) - assert(size < 0.24*uncompressed_size) + assert f.variables['data'].quantization() == (nsd,'BitGroom') + assert errmax < 1.e-3 + assert size < 0.24*uncompressed_size f.close() # check lossy compression with shuffle and alternate quantization f = Dataset(self.files[5]) size = os.stat(self.files[5]).st_size errmax = (np.abs(data_array-f.variables['data'][:])).max() print('compressed lossy with shuffle and alternate quantization = ',size,' max err = ',errmax) - assert(f.variables['data'].quantization() == (nsd,'GranularBitRound')) - assert(errmax < 1.e-3) - assert(size < 0.24*uncompressed_size) + assert f.variables['data'].quantization() == (nsd,'GranularBitRound') + assert errmax < 1.e-3 + assert size < 0.24*uncompressed_size f.close() # check lossy compression with shuffle and alternate quantization f = Dataset(self.files[6]) size = os.stat(self.files[6]).st_size errmax = (np.abs(data_array-f.variables['data'][:])).max() print('compressed lossy with shuffle and alternate quantization = ',size,' max err = ',errmax) - assert(f.variables['data'].quantization() == (nsb,'BitRound')) - assert(errmax < 1.e-3) - assert(size < 0.24*uncompressed_size) + assert f.variables['data'].quantization() == (nsb,'BitRound') + assert errmax < 1.e-3 + assert size < 0.24*uncompressed_size f.close() if __name__ == '__main__': diff --git a/test/test_compression_zstd.py b/test/test_compression_zstd.py index dfbccfc4c..9f4259fd0 100644 --- a/test/test_compression_zstd.py +++ b/test/test_compression_zstd.py @@ -47,7 +47,7 @@ def runTest(self): assert_almost_equal(array,f.variables['data'][:]) assert f.variables['data'].filters() ==\ {'zlib':False,'szip':False,'zstd':True,'bzip2':False,'blosc':False,'shuffle':False,'complevel':4,'fletcher32':False} - assert(size < 0.96*uncompressed_size) + assert size < 0.96*uncompressed_size f.close() if __name__ == '__main__': diff --git a/test/test_dap.py b/test/test_dap.py index 9e337b9c5..8d2ea664e 100644 --- a/test/test_dap.py +++ b/test/test_dap.py @@ -30,12 +30,12 @@ def runTest(self): var = ncfile.variables[varname] data = var[0,...] assert data.shape == varshape - assert(np.abs(data.min()-data_min) < 10) - assert(np.abs(data.max()-data_max) < 100) + assert np.abs(data.min()-data_min) < 10 + assert np.abs(data.max()-data_max) < 100 ncfile.close() # test https support (linked curl lib must built with openssl support) ncfile = netCDF4.Dataset(URL_https) - assert(ncfile['hs'].long_name=='Significant Wave Height') + assert ncfile['hs'].long_name=='Significant Wave Height' ncfile.close() if __name__ == '__main__': diff --git a/test/test_dims.py b/test/test_dims.py index 7af5d2ad7..2e1f95ebd 100644 --- a/test/test_dims.py +++ b/test/test_dims.py @@ -131,7 +131,7 @@ def runTest(self): dim_tup1 = (f.dimensions['level'],g.dimensions['lat'],\ g.dimensions['lon'],f.dimensions['time']) dim_tup2 = vg.get_dims() - assert(dim_tup1 == dim_tup2) + assert dim_tup1 == dim_tup2 # check that isunlimited() method works. for name,dim in g.dimensions.items(): self.assertTrue(dim.isunlimited() == unlimdict[name]) diff --git a/test/test_diskless.py b/test/test_diskless.py index 898d345fb..faeba36af 100644 --- a/test/test_diskless.py +++ b/test/test_diskless.py @@ -71,10 +71,10 @@ def runTest(self): assert_array_almost_equal(foo[:], ranarr) assert_array_almost_equal(bar[:], ranarr2) # file does not actually exist on disk - assert(os.path.isfile(self.file)==False) + assert os.path.isfile(self.file)==False # open persisted file. # first, check that file does actually exist on disk - assert(os.path.isfile(self.file2)==True) + assert os.path.isfile(self.file2)==True f = netCDF4.Dataset(self.file2) foo = f.variables['data1'] # check shape. diff --git a/test/test_enum.py b/test/test_enum.py index 6157dde24..0ab42ec6e 100644 --- a/test/test_enum.py +++ b/test/test_enum.py @@ -82,8 +82,8 @@ def tearDown(self): def runTest(self): with netCDF4.Dataset(file, 'r') as nc: read_var = nc['evar'] - assert(read_var[...] == self.STORED_VAL) - assert(read_et.enum_dict == self.VAL_MAP) + assert read_var[...] == self.STORED_VAL + assert read_et.enum_dict == self.VAL_MAP if __name__ == '__main__': unittest.main() diff --git a/test/test_fancyslicing.py b/test/test_fancyslicing.py index 38611b3cb..c3e89fd1b 100644 --- a/test/test_fancyslicing.py +++ b/test/test_fancyslicing.py @@ -145,7 +145,7 @@ def test_get(self): # slicing with all False booleans (PR #1197) iby[:] = False data = v[ibx,iby,ibz] - assert(data.size == 0) + assert data.size == 0 f.close() diff --git a/test/test_grps2.py b/test/test_grps2.py index f157f601f..e76865dfe 100644 --- a/test/test_grps2.py +++ b/test/test_grps2.py @@ -34,9 +34,9 @@ def runTest(self): v2 = ((f.groups['grouped']).groups['data']).variables['v'] g = f['/grouped/data'] v3 = g['data2/v2'] - assert(v1 == v2) - assert(g == f.groups['grouped'].groups['data']) - assert(v3.name == 'v2') + assert v1 == v2 + assert g == f.groups['grouped'].groups['data'] + assert v3.name == 'v2' f.close() if __name__ == '__main__': diff --git a/test/test_issue908.py b/test/test_issue908.py index d07746dff..b86be5a6a 100644 --- a/test/test_issue908.py +++ b/test/test_issue908.py @@ -13,7 +13,7 @@ def tearDown(self): def runTest(self): data = self.nc['rgrid'][:] - assert(data.all() is np.ma.masked) + assert data.all() is np.ma.masked if __name__ == '__main__': unittest.main() diff --git a/test/test_masked.py b/test/test_masked.py index 0794ecded..0775f29ad 100644 --- a/test/test_masked.py +++ b/test/test_masked.py @@ -142,11 +142,11 @@ def runTest(self): assert_array_almost_equal(datamasked[:].filled(),ranarr) assert_array_almost_equal(datamasked2[:].filled(),ranarr2) assert_array_almost_equal(datapacked[:],packeddata,decimal=4) - assert(datapacked3[:].dtype == np.float64) + assert datapacked3[:].dtype == np.float64 # added to test fix to issue 46 (result before r865 was 10) assert_array_equal(datapacked2[0],11) # added test for issue 515 - assert(file['v'][0] is np.ma.masked) + assert file['v'][0] is np.ma.masked file.close() # issue 766 np.seterr(invalid='raise') diff --git a/test/test_masked4.py b/test/test_masked4.py index d2649958d..14dd14fc4 100755 --- a/test/test_masked4.py +++ b/test/test_masked4.py @@ -115,9 +115,9 @@ def test_scaled(self): data2 = v[:] v.set_auto_maskandscale(False) data3 = v[:] - assert(data1[(data3 < v.valid_min)].mask.sum() == 12) - assert(data2[(data3 < v.valid_min)].mask.sum() == - data1[(data3 < v.valid_min)].mask.sum()) + assert data1[(data3 < v.valid_min)].mask.sum() == 12 + assert data2[(data3 < v.valid_min)].mask.sum() ==\ + data1[(data3 < v.valid_min)].mask.sum() if __name__ == '__main__': diff --git a/test/test_scaled.py b/test/test_scaled.py index 5020beb93..4a73ba3f7 100755 --- a/test/test_scaled.py +++ b/test/test_scaled.py @@ -187,7 +187,7 @@ def packparams(dmax, dmin, dtyp): # error normalized by scale factor maxerrnorm = np.max(np.abs((vdata - data) / v.scale_factor)) # 1e-5 accounts for floating point errors - assert(maxerrnorm < 0.5 + 1e-5) + assert maxerrnorm < 0.5 + 1e-5 f.close() diff --git a/test/test_shape.py b/test/test_shape.py index cba8ca5f9..5a924491b 100644 --- a/test/test_shape.py +++ b/test/test_shape.py @@ -31,7 +31,7 @@ def runTest(self): # make sure shape of data array # is not changed by assigning it # to a netcdf var with one more dimension (issue 90) - assert(data.shape == datashape) + assert data.shape == datashape f.close() if __name__ == '__main__': diff --git a/test/test_slicing.py b/test/test_slicing.py index 1b5c0bde2..8d3f88b7d 100644 --- a/test/test_slicing.py +++ b/test/test_slicing.py @@ -102,10 +102,10 @@ def test_0d(self): assert_array_equal(v[...], 10) assert_equal(v.shape, v[...].shape) # issue #785: always return masked array - #assert(type(v[...]) == np.ndarray) - assert(type(v[...]) == np.ma.core.MaskedArray) + #assert type(v[...]) == np.ndarray + assert type(v[...]) == np.ma.core.MaskedArray f.set_auto_mask(False) - assert(type(v[...]) == np.ndarray) + assert type(v[...]) == np.ndarray f.close() def test_issue259(self): diff --git a/test/test_stringarr.py b/test/test_stringarr.py index 6cbe0a684..8b57eceaa 100644 --- a/test/test_stringarr.py +++ b/test/test_stringarr.py @@ -70,19 +70,19 @@ def runTest(self): assert_array_equal(data3,datau) # these slices should return a char array, not a string array data4 = v2[:,:,0] - assert(data4.dtype.itemsize == 1) + assert data4.dtype.itemsize == 1 assert_array_equal(data4, datac[:,:,0]) data5 = v2[0,0:nchar,0] - assert(data5.dtype.itemsize == 1) + assert data5.dtype.itemsize == 1 assert_array_equal(data5, datac[0,0:nchar,0]) # test turning auto-conversion off. v2.set_auto_chartostring(False) data6 = v2[:] - assert(data6.dtype.itemsize == 1) + assert data6.dtype.itemsize == 1 assert_array_equal(data6, datac) nc.set_auto_chartostring(False) data7 = v3[:] - assert(data7.dtype.itemsize == 1) + assert data7.dtype.itemsize == 1 assert_array_equal(data7, datac) nc.close() diff --git a/test/test_types.py b/test/test_types.py index 1fc290957..0bd910a3f 100644 --- a/test/test_types.py +++ b/test/test_types.py @@ -81,7 +81,7 @@ def runTest(self): v2 = f.variables['issue273'] assert type(v2._FillValue) == bytes assert v2._FillValue == b'\x00' - assert(str(issue273_data) == str(v2[:])) + assert str(issue273_data) == str(v2[:]) # issue 707 (don't apply missing_value if cast to variable type is # unsafe) v3 = f.variables['issue707'] diff --git a/test/test_unicodeatt.py b/test/test_unicodeatt.py index 61345950d..50927f95a 100644 --- a/test/test_unicodeatt.py +++ b/test/test_unicodeatt.py @@ -23,12 +23,12 @@ def tearDown(self): def runTest(self): """testing unicode attributes""" nc = Dataset(self.file, 'r') - assert(nc.stratt.encode('utf-8') == b'\xe6\xb7\xb1\xe5\x85\xa5 Python') + assert nc.stratt.encode('utf-8') == b'\xe6\xb7\xb1\xe5\x85\xa5 Python' stratt2 = nc.getncattr('stratt2',encoding='big5') # decodes using big5 stratt3 = nc.getncattr('stratt3',encoding='big5') # same as above - assert(stratt2.encode('big5') == b'\xb2`\xa4J Python') - assert(nc.stratt == stratt2) # decoded strings are the same - assert(nc.stratt == stratt3) # decoded strings are the same + assert stratt2.encode('big5') == b'\xb2`\xa4J Python' + assert nc.stratt == stratt2 # decoded strings are the same + assert nc.stratt == stratt3 # decoded strings are the same nc.close() if __name__ == '__main__': diff --git a/test/test_vlen.py b/test/test_vlen.py index 9e51bfb2d..1cbb774cb 100644 --- a/test/test_vlen.py +++ b/test/test_vlen.py @@ -70,7 +70,8 @@ def runTest(self): data2 = v[:] data2s = vs[:] # issue #1306 - assert repr(vs[[0,2,3],0]) == "array(['ab', 'abcdefghijkl', 'abcdefghijklmnopq'], dtype=object)" + print(repr(vs[[0,2,3],0])) + assert repr(vs[[0,2,3],0]) == "array(['ab', 'abcdefghijkl', 'abcdefghijklmnopq'], dtype=object)" for i in range(nlons): for j in range(nlats): assert_array_equal(data2[j,i], data[j,i]) @@ -219,11 +220,11 @@ def runTest(self): data = nc['vl'][-1] # check max error of compression err = np.abs(data - self.data) - assert(err.max() < nc['vl'].scale_factor) + assert err.max() < nc['vl'].scale_factor # turn off auto-scaling nc.set_auto_maskandscale(False) data = nc['vl'][-1] - assert(data[-1] == np.around(self.data[-1]/nc['vl'].scale_factor)) + assert data[-1] == np.around(self.data[-1]/nc['vl'].scale_factor) nc.close() if __name__ == '__main__': From 39d14b52ee1724804ed76259686eace01ce3290d Mon Sep 17 00:00:00 2001 From: jswhit Date: Fri, 16 Feb 2024 12:45:07 -0700 Subject: [PATCH 1086/1504] update --- test/test_vlen.py | 1 - 1 file changed, 1 deletion(-) diff --git a/test/test_vlen.py b/test/test_vlen.py index 1cbb774cb..1e1d89f72 100644 --- a/test/test_vlen.py +++ b/test/test_vlen.py @@ -70,7 +70,6 @@ def runTest(self): data2 = v[:] data2s = vs[:] # issue #1306 - print(repr(vs[[0,2,3],0])) assert repr(vs[[0,2,3],0]) == "array(['ab', 'abcdefghijkl', 'abcdefghijklmnopq'], dtype=object)" for i in range(nlons): for j in range(nlats): From 64faa9b968121b88d14051c3212ac8076f720049 Mon Sep 17 00:00:00 2001 From: stubbiali Date: Fri, 16 Feb 2024 22:07:52 +0100 Subject: [PATCH 1087/1504] Debug CI. --- _build/backend.py | 15 +++++++++++++-- 1 file changed, 13 insertions(+), 2 deletions(-) diff --git a/_build/backend.py b/_build/backend.py index cefffa925..bd05c2b3e 100644 --- a/_build/backend.py +++ b/_build/backend.py @@ -1,12 +1,24 @@ # -*- coding: utf-8 -*- +import logging import os from setuptools.build_meta import * import subprocess +fmt = logging.Formatter("\n=== NETCDF4 BUILD DEBUG: %(message)s\n") +hdlr = logging.StreamHandler() +hdlr.setFormatter(fmt) +log = logging.getLogger(__name__) +log.setLevel(logging.DEBUG) +log.addHandler(hdlr) + + def netcdf_has_parallel_support(): netcdf4_dir = os.environ.get("NETCDF4_DIR") - ncconfig = os.path.join(netcdf4_dir, "bin", "nc-config") if netcdf4_dir else "nc-config" + ncconfig = ( + os.path.join(netcdf4_dir, "bin", "nc-config") if netcdf4_dir else "nc-config" + ) + log.debug(f"{ncconfig = }") process = subprocess.run([ncconfig, "--has-parallel4"], capture_output=True) out = process.stdout.decode("utf-8").rstrip() return out == "yes" @@ -22,4 +34,3 @@ def get_requires_for_build_wheel(config_settings=None): def get_requires_for_build_sdist(config_settings=None): return ["mpi4py>=3.1"] if netcdf_has_parallel_support() else [] - From 1f2b711eb8ec90a0fd2d6b96cf34ac5c0bba5711 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Cl=C3=A9ment=20Robert?= Date: Thu, 11 Apr 2024 10:09:03 +0200 Subject: [PATCH 1088/1504] BLD: build with numpy 2.0.0rc1 (or newer) on Python >= 3.9 --- pyproject.toml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 16636ec1d..e58ccd16e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,7 +1,8 @@ [build-system] requires = [ "Cython>=0.29", - "oldest-supported-numpy", + "oldest-supported-numpy ; python_version < '3.9'", + "numpy>=2.0.0rc1 ; python_version >= '3.9'", "setuptools>=61", ] build-backend = "setuptools.build_meta" From e459ffe195dda7d3a14981b0b28f68bac5b5e23e Mon Sep 17 00:00:00 2001 From: Pier Giuseppe Fogli Date: Tue, 16 Apr 2024 18:05:48 +0200 Subject: [PATCH 1089/1504] Fix bug in set_collective added in #1277 Fix bug in set_collective added in commit f64ee26773502c7568b1ceefe5967f83230f207c that cause access always be in collective mode. Independent access mode is not tested so it passed unnoticed. --- src/netCDF4/_netCDF4.pyx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 271a9e4a9..45bb30e56 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -6060,7 +6060,7 @@ NC_CHAR). mode = NC_COLLECTIVE if value else NC_INDEPENDENT with nogil: ierr = nc_var_par_access(self._grpid, self._varid, - NC_COLLECTIVE) + mode) _ensure_nc_success(ierr) From 98fa36240d125d22fdaffb37a2826c0414ec6e7a Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 16 Apr 2024 18:45:32 -0600 Subject: [PATCH 1090/1504] enable over-subscription --- .github/workflows/miniconda.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index 33f079898..df053bcad 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -83,8 +83,8 @@ jobs: export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" which mpirun mpirun --version - #mpirun -np 4 --oversubscribe python mpi_example.py # for openmpi - mpirun -np 4 python mpi_example.py + mpirun -np 4 --oversubscribe python mpi_example.py # for openmpi + #mpirun -np 4 python mpi_example.py if [ $? -ne 0 ] ; then echo "hdf5 mpi test failed!" exit 1 From 9199c8688a3d859b3d19fe8bd21341dcd00b0ea0 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 16 Apr 2024 18:51:35 -0600 Subject: [PATCH 1091/1504] update --- Changelog | 2 ++ 1 file changed, 2 insertions(+) diff --git a/Changelog b/Changelog index 9593159a5..6211e5e5c 100644 --- a/Changelog +++ b/Changelog @@ -7,6 +7,8 @@ * add support for MS-MPI `MPI_Message` detection (PR #1305) * fix for issue #1306 - surprising result when indexing vlen str with non-contiguous indices. + * Fix bug in set_collective introduced in PR #1277 (collective mode was + always set). From e7a175bee022cf70a8d9d6f17931bcf92169b30a Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Fri, 26 Apr 2024 17:45:19 +0200 Subject: [PATCH 1092/1504] test against np2 --- .github/workflows/miniconda.yml | 25 +++++++++++++++++++------ 1 file changed, 19 insertions(+), 6 deletions(-) diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index df053bcad..ab0a864b8 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -12,13 +12,22 @@ jobs: # NO_NET: 1 strategy: matrix: - python-version: [ "3.8", "3.9", "3.10", "3.11", "3.12" ] + python-version: [ "3.9", "3.10", "3.11", "3.12" ] os: [windows-latest, ubuntu-latest, macos-latest] + experimental: [false] platform: [x64, x32] exclude: - os: macos-latest platform: x32 + include: + - python-version: "3.12" + os: "ubuntu-latest" + experimental: true + platform: x64 fail-fast: false + defaults: + run: + shell: bash -l {0} steps: - uses: actions/checkout@v4 @@ -35,14 +44,20 @@ jobs: numpy cython pip pytest hdf5 libnetcdf cftime zlib certifi --channel conda-forge + - name: Install unstable dependencies + if: matrix.experimental == true + run: >- + micromamba install + conda-forge/label/cftime_dev::cftime + conda-forge/label/numpy_dev::numpy + --channel conda-forge --channel conda-forge + - name: Install netcdf4-python - shell: bash -l {0} run: | export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config - python -m pip install -v -e . --no-deps --force-reinstall + python -m pip install -v -e . --no-deps --no-build-isolation --force-reinstall - name: Tests - shell: bash -l {0} run: | cd test && python run_all.py @@ -69,14 +84,12 @@ jobs: --channel conda-forge - name: Install netcdf4-python with mpi - shell: bash -l {0} run: | export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config nc-config --all python -m pip install -v -e . --no-build-isolation --no-deps --force-reinstall - name: Tests - shell: bash -l {0} run: | cd test && python run_all.py cd ../examples From 3402c87102b36181dc80f09816780aba5955c7fc Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Fri, 26 Apr 2024 19:07:14 +0200 Subject: [PATCH 1093/1504] fix mpi? --- .github/workflows/miniconda.yml | 3 +++ 1 file changed, 3 insertions(+) diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index ab0a864b8..a7493a01f 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -68,6 +68,9 @@ jobs: python-version: [ "3.11" ] os: [ubuntu-latest] platform: [x64] + defaults: + run: + shell: bash -l {0} steps: - uses: actions/checkout@v4 with: From aa042411642621ff9e6c70a7edfffe2008e2b51b Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Mon, 29 Apr 2024 18:20:28 -0600 Subject: [PATCH 1094/1504] make sure c vars used in looping --- src/netCDF4/_netCDF4.pyx | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 45bb30e56..ecf2cd3fa 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -5747,7 +5747,7 @@ NC_CHAR). def _put(self,ndarray data,start,count,stride): """Private method to put data into a netCDF variable""" cdef int ierr, ndims - cdef npy_intp totelem + cdef npy_intp totelem, dataelem, i cdef size_t *startp cdef size_t *countp cdef ptrdiff_t *stridep @@ -5834,7 +5834,7 @@ NC_CHAR). # each element in struct. # allocate struct array to hold vlen data. strdata = malloc(sizeof(char *)*totelem) - for i from 0<=idata) # allocate struct array to hold vlen data. vldata = malloc(totelem*sizeof(nc_vlen_t)) - for i from 0<=idatabuff)[0] dataarr = elptr if self.dtype != dataarr.dtype.str[1:]: @@ -5884,7 +5884,8 @@ NC_CHAR). def _get(self,start,count,stride): """Private method to retrieve data from a netCDF variable""" - cdef int ierr, ndims, totelem + cdef int ierr, ndims + cdef npy_intp totelem, i cdef size_t *startp cdef size_t *countp cdef ptrdiff_t *stridep @@ -5980,7 +5981,7 @@ NC_CHAR). # use _Encoding attribute to decode string to bytes - if # not given, use 'utf-8'. encoding = getattr(self,'_Encoding','utf-8') - for i from 0<=ivldata[i].p From d006b5f1561e41cbeeae9ed72b1dd4f202443ace Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Mon, 29 Apr 2024 18:26:38 -0600 Subject: [PATCH 1095/1504] remove old for loop syntax --- src/netCDF4/_netCDF4.pyx | 36 ++++++++++++++++++------------------ 1 file changed, 18 insertions(+), 18 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index ecf2cd3fa..640ab6846 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1593,7 +1593,7 @@ cdef _get_att_names(int grpid, int varid): ierr = nc_inq_varnatts(grpid, varid, &numatts) _ensure_nc_success(ierr, err_cls=AttributeError) attslist = [] - for n from 0 <= n < numatts: + for n in range(numatts): with nogil: ierr = nc_inq_attname(grpid, varid, n, namstring) _ensure_nc_success(ierr, err_cls=AttributeError) @@ -1868,7 +1868,7 @@ cdef _get_types(group): enumtypes = dict() if ntypes > 0: - for n from 0 <= n < ntypes: + for n in range(ntypes): xtype = typeids[n] with nogil: ierr = nc_inq_user_type(_grpid, xtype, namstring, @@ -1930,9 +1930,9 @@ cdef _get_dims(group): ierr = nc_inq_dimids(_grpid, &numdims, dimids, 0) _ensure_nc_success(ierr) else: - for n from 0 <= n < numdims: + for n in range(numdims): dimids[n] = n - for n from 0 <= n < numdims: + for n in range(numdims): with nogil: ierr = nc_inq_dimname(_grpid, dimids[n], namstring) _ensure_nc_success(ierr) @@ -1959,7 +1959,7 @@ cdef _get_grps(group): with nogil: ierr = nc_inq_grps(_grpid, NULL, grpids) _ensure_nc_success(ierr) - for n from 0 <= n < numgrps: + for n in range(numgrps): with nogil: ierr = nc_inq_grpname(grpids[n], namstring) _ensure_nc_success(ierr) @@ -1994,10 +1994,10 @@ cdef _get_vars(group, bint auto_complex=False): ierr = nc_inq_varids(_grpid, &numvars, varids) _ensure_nc_success(ierr) else: - for n from 0 <= n < numvars: + for n in range(numvars): varids[n] = n # loop over variables. - for n from 0 <= n < numvars: + for n in range(numvars): varid = varids[n] # get variable name. with nogil: @@ -3761,7 +3761,7 @@ returns `True` if the `Dimension` instance is unlimited, `False` otherwise.""" ierr = nc_inq_unlimdims(self._grpid, &numunlimdims, unlimdimids) _ensure_nc_success(ierr) unlimdim_ids = [] - for n from 0 <= n < numunlimdims: + for n in range(numunlimdims): unlimdim_ids.append(unlimdimids[n]) free(unlimdimids) if dimid in unlimdim_ids: @@ -4155,7 +4155,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. # find dimension ids. if ndims: dimids = malloc(sizeof(int) * ndims) - for n from 0 <= n < ndims: + for n in range(ndims): dimids[n] = dimensions[n]._dimid # go into define mode if it's a netCDF 3 compatible # file format. Be careful to exit define mode before @@ -4289,7 +4289,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. if grp.data_model != 'NETCDF4': grp._enddef() raise ValueError('chunksizes must be a sequence with the same length as dimensions') chunksizesp = malloc(sizeof(size_t) * ndims) - for n from 0 <= n < ndims: + for n in range(ndims): if not dimensions[n].isunlimited() and \ chunksizes[n] > dimensions[n].size: msg = 'chunksize cannot exceed dimension size' @@ -4813,7 +4813,7 @@ each dimension is returned.""" ierr = nc_inq_var_chunking(self._grpid, self._varid, &icontiguous, chunksizesp) _ensure_nc_success(ierr) chunksizes=[] - for n from 0 <= n < ndims: + for n in range(ndims): chunksizes.append(chunksizesp[n]) free(chunksizesp) if icontiguous: @@ -5343,7 +5343,7 @@ rename a `Variable` attribute named `oldname` to `newname`.""" count = [1]*ndims startp = malloc(sizeof(size_t) * ndims) countp = malloc(sizeof(size_t) * ndims) - for n from 0 <= n < ndims: + for n in range(ndims): startp[n] = start[n] countp[n] = count[n] if self.dtype == str: # VLEN string @@ -5769,7 +5769,7 @@ NC_CHAR). startp = malloc(sizeof(size_t) * ndims) countp = malloc(sizeof(size_t) * ndims) stridep = malloc(sizeof(ptrdiff_t) * ndims) - for n from 0 <= n < ndims: + for n in range(ndims): count[n] = abs(count[n]) # make -1 into +1 countp[n] = count[n] # for neg strides, reverse order (then flip that axis after data read in) @@ -5912,7 +5912,7 @@ NC_CHAR). startp = malloc(sizeof(size_t) * ndims) countp = malloc(sizeof(size_t) * ndims) stridep = malloc(sizeof(ptrdiff_t) * ndims) - for n from 0 <= n < ndims: + for n in range(ndims): count[n] = abs(count[n]) # make -1 into +1 countp[n] = count[n] # for neg strides, reverse order (then flip that axis after data read in) @@ -6254,7 +6254,7 @@ cdef _def_compound(grp, object dt, object dtype_name): else: # nested array compound element ndims = len(format.shape) dim_sizes = malloc(sizeof(int) * ndims) - for n from 0 <= n < ndims: + for n in range(ndims): dim_sizes[n] = format.shape[n] if format.subdtype[0].kind != 'V': # primitive type. try: @@ -6332,7 +6332,7 @@ cdef _read_compound(group, nc_type xtype, endian=None): names = [] formats = [] offsets = [] - for nf from 0 <= nf < nfields: + for nf in range(nfields): with nogil: ierr = nc_inq_compound_field(_grpid, xtype, @@ -6360,7 +6360,7 @@ cdef _read_compound(group, nc_type xtype, endian=None): # if numdims=0, not an array. field_shape = () if numdims != 0: - for ndim from 0 <= ndim < numdims: + for ndim in range(numdims): field_shape = field_shape + (dim_sizes[ndim],) free(dim_sizes) # check to see if this field is a nested compound type. @@ -6614,7 +6614,7 @@ cdef _read_enum(group, nc_type xtype, endian=None): # loop over members, build dict. enum_dict = {} enum_val = numpy.empty(1,dt) - for nmem from 0 <= nmem < nmembers: + for nmem in range(nmembers): with nogil: ierr = nc_inq_enum_member(grpid, xtype, nmem, \ enum_namstring,PyArray_DATA(enum_val)) From ea590c2f94b1ce93e6873cf712beb0e3d92b4e9b Mon Sep 17 00:00:00 2001 From: Orion Poplawski Date: Wed, 8 May 2024 20:50:22 -0600 Subject: [PATCH 1096/1504] Fix incompatbile pointer argument to nc_put_att_string() --- include/netCDF4.pxi | 2 +- src/netCDF4/_netCDF4.pyx | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi index 00d883662..9404171db 100644 --- a/include/netCDF4.pxi +++ b/include/netCDF4.pxi @@ -263,7 +263,7 @@ cdef extern from "netcdf.h": size_t len, void *op) nogil int nc_get_att(int ncid, int varid, char *name, void *ip) nogil int nc_get_att_string(int ncid, int varid, char *name, char **ip) nogil - int nc_put_att_string(int ncid, int varid, char *name, size_t len, char **op) nogil + int nc_put_att_string(int ncid, int varid, char *name, size_t len, const char **op) nogil int nc_def_opaque(int ncid, size_t size, char *name, nc_type *xtypep) nogil int nc_inq_opaque(int ncid, nc_type xtype, char *name, size_t *sizep) nogil int nc_put_att_opaque(int ncid, int varid, char *name, diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 640ab6846..b957f4e35 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1796,7 +1796,7 @@ be raised in the next release.""" string_ptrs[j] = strings[j] issue485_workaround(grpid, varid, attname) with nogil: - ierr = nc_put_att_string(grpid, varid, attname, N, string_ptrs) + ierr = nc_put_att_string(grpid, varid, attname, N, string_ptrs) finally: PyMem_Free(string_ptrs) else: @@ -1825,7 +1825,7 @@ be raised in the next release.""" except UnicodeError: issue485_workaround(grpid, varid, attname) with nogil: - ierr = nc_put_att_string(grpid, varid, attname, 1, &datstring) + ierr = nc_put_att_string(grpid, varid, attname, 1, &datstring) else: with nogil: ierr = nc_put_att_text(grpid, varid, attname, lenarr, datstring) From 263186d5783aa8243b219611b279ebc96aa72f76 Mon Sep 17 00:00:00 2001 From: jswhit Date: Fri, 7 Jun 2024 10:03:43 -0600 Subject: [PATCH 1097/1504] update Changelog --- Changelog | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/Changelog b/Changelog index 6211e5e5c..03830b99b 100644 --- a/Changelog +++ b/Changelog @@ -1,4 +1,4 @@ - version 1.7.0 (not yet released) + version 1.7.0 (tag v1.7.0rel) =============================== * add support for complex numbers via `auto_complex` keyword to `Dataset` (PR #1295) * fix for deprecated Cython `DEF` and `IF` statements using compatibility header @@ -10,8 +10,6 @@ * Fix bug in set_collective introduced in PR #1277 (collective mode was always set). - - version 1.6.5 (tag v1.6.5rel) =============================== * fix for issue #1271 (mask ignored if bool MA assinged to uint8 var) From afecac00b0b9747069b3ef131a8b95d47fa8c1c5 Mon Sep 17 00:00:00 2001 From: jswhit Date: Fri, 7 Jun 2024 10:05:38 -0600 Subject: [PATCH 1098/1504] update README.md --- README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/README.md b/README.md index 43d1461d7..ac98e7f73 100644 --- a/README.md +++ b/README.md @@ -10,6 +10,8 @@ ## News For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog). +06/??/2024: Version [1.7.0](https://pypi.python.org/pypi/netCDF4/1.7.0) released. Add support for complex numbers via `auto_complex` keyword to `Dataset` ([PR #1295](https://github.com/Unidata/netcdf4-python/pull/1295)) + 10/20/2023: Version [1.6.5](https://pypi.python.org/pypi/netCDF4/1.6.5) released. Fix for issue #1271 (mask ignored if bool MA assinged to uint8 var), support for python 3.12 (removal of python 3.7 support), more From d4c6ace9172c8261671ae3a95ed12e5e3cb030f5 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 7 Jun 2024 20:32:46 +0200 Subject: [PATCH 1099/1504] install mypy in workflow --- .github/workflows/build_master.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index 7f47c7c58..4d630d3f3 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -47,7 +47,7 @@ jobs: - name: Install python dependencies via pip run: | python -m pip install --upgrade pip - pip install numpy cython cftime pytest twine wheel check-manifest mpi4py + pip install numpy cython cftime pytest twine wheel check-manifest mpi4py mypy - name: Install netcdf4-python run: | From 8de2c1b6868dd3cf5be6141ad390fe9e709b4f32 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 7 Jun 2024 21:29:15 +0200 Subject: [PATCH 1100/1504] add mypy check of tests --- .github/workflows/build_master.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index 4d630d3f3..7d13ecdc8 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -83,3 +83,4 @@ jobs: - name: Stubtest run: | stubtest netCDF4 --allowlist .github/stubtest-allowlist --mypy-config-file=pyproject.toml + mypy test From ca2642927b5aba691081f1702e495f3fe608de9f Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 7 Jun 2024 21:29:47 +0200 Subject: [PATCH 1101/1504] ignore imports with missing stubs --- pyproject.toml | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index df0478049..21ddf0b04 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -84,5 +84,7 @@ files = ["src/netCDF4"] ignore_missing_imports = true module = [ "cftime.*", - "cython.*" + "cython.*", + "filter_availability", + "matplotlib.*" ] \ No newline at end of file From 3f93b49e5bd2606ebdd8a1b10dcc6201ac16e276 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 7 Jun 2024 21:30:29 +0200 Subject: [PATCH 1102/1504] fix some types found by tests --- src/netCDF4/__init__.pyi | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index f6d7e1480..16d69c55c 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -147,7 +147,7 @@ class Dataset: least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeOptions = 'BitGroom', - fill_value: bool | None = None, + fill_value: npt.ArrayLike | bool | None = None, chunk_cache: int | None = None ) -> Variable: ... def renameVariable(self, oldname: str, newname: str) -> None: ... @@ -191,7 +191,7 @@ class Dataset: def has_bzip2_filter(self) -> bool: ... def has_szip_filter(self) -> bool: ... - def __getitem__(self, elem: str) -> Group | Variable: ... + def __getitem__(self, elem: str) -> Any: ... # should be Group | Variable, but this causes too many problems def __setattr__(self, name: str, value: Any) -> None: ... def __getattr__(self, name: str) -> Any: ... def __delattr__(self, name: str): ... @@ -246,7 +246,7 @@ class Variable: least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeOptions = 'BitGroom', - fill_value: bool | None = None, + fill_value: npt.ArrayLike | bool | None = None, chunk_cache: int | None = None, **kwargs: Any ) -> None: ... From b9089dfbafa0cd2770fb34ac0c9568dbe203d476 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 7 Jun 2024 22:14:47 +0200 Subject: [PATCH 1103/1504] fix examples so mypy passes --- examples/mpi_example.py | 10 +-- examples/test_stringarr.py | 4 +- examples/threaded_read.py | 2 +- examples/tutorial.py | 124 ++++++++++++++++++------------------- 4 files changed, 71 insertions(+), 69 deletions(-) diff --git a/examples/mpi_example.py b/examples/mpi_example.py index 0bebfe675..653f25781 100644 --- a/examples/mpi_example.py +++ b/examples/mpi_example.py @@ -2,16 +2,18 @@ import sys from mpi4py import MPI import numpy as np -from netCDF4 import Dataset +from netCDF4 import Dataset, FormatOptions + +format: FormatOptions if len(sys.argv) == 2: - format = sys.argv[1] + format = sys.argv[1] # type: ignore else: format = 'NETCDF4_CLASSIC' rank = MPI.COMM_WORLD.rank # The process ID (integer 0-3 for 4-process run) if rank == 0: print('Creating file with format {}'.format(format)) nc = Dataset('parallel_test.nc', 'w', parallel=True, comm=MPI.COMM_WORLD, - info=MPI.Info(),format=format) + info=MPI.Info(),format=format) # below should work also - MPI_COMM_WORLD and MPI_INFO_NULL will be used. #nc = Dataset('parallel_test.nc', 'w', parallel=True) d = nc.createDimension('dim',4) @@ -23,7 +25,7 @@ nc.close() # reopen the file read-only, check the data nc = Dataset('parallel_test.nc', parallel=True, comm=MPI.COMM_WORLD, - info=MPI.Info()) + info=MPI.Info()) assert rank==nc['var'][rank] nc.close() # reopen the file in append mode, modify the data on the last rank. diff --git a/examples/test_stringarr.py b/examples/test_stringarr.py index 758c4a749..7644cd59a 100644 --- a/examples/test_stringarr.py +++ b/examples/test_stringarr.py @@ -1,5 +1,6 @@ from netCDF4 import Dataset, stringtochar, chartostring import random, numpy +from typing import Final # test utilities for converting arrays of fixed-length strings # to arrays of characters (with an extra dimension), and vice-versa. @@ -16,7 +17,7 @@ FILE_NAME = 'tst_stringarr.nc' -FILE_FORMAT = 'NETCDF4_CLASSIC' +FILE_FORMAT: Final = 'NETCDF4_CLASSIC' chars = '1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ' nc = Dataset(FILE_NAME,'w',format=FILE_FORMAT) @@ -26,7 +27,6 @@ nc.createDimension('nchar',nchar) v = nc.createVariable('strings','S1',('n1','n2','nchar')) for nrec in range(nrecs): - data = [] data = numpy.empty((n2,),'S'+repr(nchar)) # fill data with random nchar character strings for n in range(n2): diff --git a/examples/threaded_read.py b/examples/threaded_read.py index 91676911b..229f0379a 100644 --- a/examples/threaded_read.py +++ b/examples/threaded_read.py @@ -28,7 +28,7 @@ nc.close() # Queue them up -items = queue.Queue() +items: queue.Queue = queue.Queue() for data,fname in zip(datal,fnames): items.put(fname) diff --git a/examples/tutorial.py b/examples/tutorial.py index d48fd1679..c915abc6d 100644 --- a/examples/tutorial.py +++ b/examples/tutorial.py @@ -26,21 +26,21 @@ def walktree(top): print(child) # dimensions. -level = rootgrp.createDimension('level', None) -time = rootgrp.createDimension('time', None) -lat = rootgrp.createDimension('lat', 73) -lon = rootgrp.createDimension('lon', 144) +level_dim = rootgrp.createDimension('level', None) +time_dim = rootgrp.createDimension('time', None) +lat_dim = rootgrp.createDimension('lat', 73) +lon_dim = rootgrp.createDimension('lon', 144) print(rootgrp.dimensions) -print(len(lon)) -print(lon.isunlimited()) -print(time.isunlimited()) +print(len(lon_dim)) +print(lon_dim.isunlimited()) +print(time_dim.isunlimited()) for dimobj in rootgrp.dimensions.values(): print(dimobj) -print(time) +print(time_dim) # variables. times = rootgrp.createVariable('time','f8',('time',)) @@ -119,39 +119,39 @@ def walktree(top): # create a series of netCDF files with a variable sharing # the same unlimited dimension. for nfile in range(10): - f = Dataset('mftest'+repr(nfile)+'.nc','w',format='NETCDF4_CLASSIC') - f.createDimension('x',None) - x = f.createVariable('x','i',('x',)) - x[0:10] = np.arange(nfile*10,10*(nfile+1)) - f.close() + nc = Dataset('mftest'+repr(nfile)+'.nc','w',format='NETCDF4_CLASSIC') + nc.createDimension('x',None) + x_var = nc.createVariable('x','i',('x',)) + x_var[0:10] = np.arange(nfile*10,10*(nfile+1)) + nc.close() # now read all those files in at once, in one Dataset. from netCDF4 import MFDataset -f = MFDataset('mftest*nc') -print(f.variables['x'][:]) +nc = MFDataset('mftest*nc') +print(nc.variables['x'][:]) # example showing how to save numpy complex arrays using compound types. -f = Dataset('complex.nc','w') +nc = Dataset('complex.nc','w') size = 3 # length of 1-d complex array # create sample complex data. datac = np.exp(1j*(1.+np.linspace(0, np.pi, size))) print(datac.dtype) # create complex128 compound data type. complex128 = np.dtype([('real',np.float64),('imag',np.float64)]) -complex128_t = f.createCompoundType(complex128,'complex128') +complex128_t = nc.createCompoundType(complex128,'complex128') # create a variable with this data type, write some data to it. -f.createDimension('x_dim',None) -v = f.createVariable('cmplx_var',complex128_t,'x_dim') +nc.createDimension('x_dim',None) +v = nc.createVariable('cmplx_var',complex128_t,'x_dim') data = np.empty(size,complex128) # numpy structured array data['real'] = datac.real; data['imag'] = datac.imag v[:] = data # close and reopen the file, check the contents. -f.close() -f = Dataset('complex.nc') -print(f) -print(f.variables['cmplx_var']) -print(f.cmptypes) -print(f.cmptypes['complex128']) -v = f.variables['cmplx_var'] +nc.close() +nc = Dataset('complex.nc') +print(nc) +print(nc.variables['cmplx_var']) +print(nc.cmptypes) +print(nc.cmptypes['complex128']) +v = nc.variables['cmplx_var'] print(v.shape) datain = v[:] # read in all the data into a numpy structured array # create an empty numpy complex array @@ -163,9 +163,9 @@ def walktree(top): print(datac2.dtype,datac2) # more complex compound type example. -f = Dataset('compound_example.nc','w') # create a new dataset. +nc = Dataset('compound_example.nc','w') # create a new dataset. # create an unlimited dimension call 'station' -f.createDimension('station',None) +nc.createDimension('station',None) # define a compound data type (can contain arrays, or nested compound types). winddtype = np.dtype([('speed','f4'),('direction','i4')]) statdtype = np.dtype([('latitude', 'f4'), ('longitude', 'f4'), @@ -176,9 +176,9 @@ def walktree(top): # called using the createCompoundType Dataset method. # create a compound type for vector wind which will be nested inside # the station data type. This must be done first! -wind_data_t = f.createCompoundType(winddtype,'wind_data') +wind_data_t = nc.createCompoundType(winddtype,'wind_data') # now that wind_data_t is defined, create the station data type. -station_data_t = f.createCompoundType(statdtype,'station_data') +station_data_t = nc.createCompoundType(statdtype,'station_data') # create nested compound data types to hold the units variable attribute. winddtype_units = np.dtype([('speed','S12'),('direction','S12')]) statdtype_units = np.dtype([('latitude', 'S12'), ('longitude', 'S12'), @@ -188,11 +188,11 @@ def walktree(top): ('press_sounding','S12')]) # create the wind_data_units type first, since it will nested inside # the station_data_units data type. -wind_data_units_t = f.createCompoundType(winddtype_units,'wind_data_units') +wind_data_units_t = nc.createCompoundType(winddtype_units,'wind_data_units') station_data_units_t =\ -f.createCompoundType(statdtype_units,'station_data_units') +nc.createCompoundType(statdtype_units,'station_data_units') # create a variable of of type 'station_data_t' -statdat = f.createVariable('station_obs', station_data_t, ('station',)) +statdat = nc.createVariable('station_obs', station_data_t, ('station',)) # create a numpy structured array, assign data to it. data = np.empty(1,statdtype) data['latitude'] = 40. @@ -209,7 +209,7 @@ def walktree(top): statdat[1] = np.array((40.78,-73.99,(-12.5,90), (290.2,282.5,279.,277.9,276.,266.,264.1,260.,255.5,243.), range(900,400,-50),'New York, NY'),data.dtype) -print(f.cmptypes) +print(nc.cmptypes) windunits = np.empty(1,winddtype_units) stationobs_units = np.empty(1,statdtype_units) windunits['speed'] = 'm/s' @@ -223,21 +223,21 @@ def walktree(top): print(stationobs_units.dtype) statdat.units = stationobs_units # close and reopen the file. -f.close() -f = Dataset('compound_example.nc') -print(f) -statdat = f.variables['station_obs'] +nc.close() +nc = Dataset('compound_example.nc') +print(nc) +statdat = nc.variables['station_obs'] print(statdat) # print out data in variable. print('data in a variable of compound type:') print(statdat[:]) -f.close() +nc.close() -f = Dataset('tst_vlen.nc','w') -vlen_t = f.createVLType(np.int32, 'phony_vlen') -x = f.createDimension('x',3) -y = f.createDimension('y',4) -vlvar = f.createVariable('phony_vlen_var', vlen_t, ('y','x')) +nc = Dataset('tst_vlen.nc','w') +vlen_t = nc.createVLType(np.int32, 'phony_vlen') +x = nc.createDimension('x',3) +y = nc.createDimension('y',4) +vlvar = nc.createVariable('phony_vlen_var', vlen_t, ('y','x')) import random data = np.empty(len(y)*len(x),object) for n in range(len(y)*len(x)): @@ -246,11 +246,11 @@ def walktree(top): vlvar[:] = data print(vlvar) print('vlen variable =\n',vlvar[:]) -print(f) -print(f.variables['phony_vlen_var']) -print(f.vltypes['phony_vlen']) -z = f.createDimension('z', 10) -strvar = f.createVariable('strvar',str,'z') +print(nc) +print(nc.variables['phony_vlen_var']) +print(nc.vltypes['phony_vlen']) +z = nc.createDimension('z', 10) +strvar = nc.createVariable('strvar',str,'z') chars = '1234567890aabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ' data = np.empty(10,object) for n in range(10): @@ -258,35 +258,35 @@ def walktree(top): data[n] = ''.join([random.choice(chars) for i in range(stringlen)]) strvar[:] = data print('variable-length string variable:\n',strvar[:]) -print(f) -print(f.variables['strvar']) -f.close() +print(nc) +print(nc.variables['strvar']) +nc.close() # Enum type example. -f = Dataset('clouds.nc','w') +nc = Dataset('clouds.nc','w') # python dict describing the allowed values and their names. enum_dict = {'Altocumulus': 7, 'Missing': 255, 'Stratus': 2, 'Clear': 0, 'Nimbostratus': 6, 'Cumulus': 4, 'Altostratus': 5, 'Cumulonimbus': 1, 'Stratocumulus': 3} # create the Enum type called 'cloud_t'. -cloud_type = f.createEnumType(np.uint8,'cloud_t',enum_dict) +cloud_type = nc.createEnumType(np.uint8,'cloud_t',enum_dict) print(cloud_type) -time = f.createDimension('time',None) +time_dim = nc.createDimension('time',None) # create a 1d variable of type 'cloud_type' called 'primary_clouds'. # The fill_value is set to the 'Missing' named value. -cloud_var = f.createVariable('primary_cloud',cloud_type,'time',\ +cloud_var = nc.createVariable('primary_cloud',cloud_type,'time',\ fill_value=enum_dict['Missing']) # write some data to the variable. cloud_var[:] = [enum_dict['Clear'],enum_dict['Stratus'],enum_dict['Cumulus'],\ enum_dict['Missing'],enum_dict['Cumulonimbus']] # close file, reopen it. -f.close() -f = Dataset('clouds.nc') -cloud_var = f.variables['primary_cloud'] +nc.close() +nc = Dataset('clouds.nc') +cloud_var = nc.variables['primary_cloud'] print(cloud_var) print(cloud_var.datatype.enum_dict) print(cloud_var[:]) -f.close() +nc.close() # dealing with strings from netCDF4 import stringtochar @@ -349,8 +349,8 @@ def walktree(top): nc_buf = nc.close() # close returns memoryview print(type(nc_buf)) # save nc_buf to disk, read it back in and check. -f = open('inmemory.nc', 'wb') -f.write(nc_buf); f.close() +f2 = open('inmemory.nc', 'wb') +f2.write(nc_buf); f2.close() nc = Dataset('inmemory.nc') print(nc) print(nc['v'][:]) From 92d26262d2ad9ab414f24fce5d99bf3f1e00c27e Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 7 Jun 2024 22:15:57 +0200 Subject: [PATCH 1104/1504] add mypy test for examples --- .github/workflows/build_master.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index 7d13ecdc8..09d0f97ec 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -84,3 +84,4 @@ jobs: run: | stubtest netCDF4 --allowlist .github/stubtest-allowlist --mypy-config-file=pyproject.toml mypy test + mypy examples From 17616b060aadfc7477c3e41638ca647e9c74ef42 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 7 Jun 2024 22:25:04 +0200 Subject: [PATCH 1105/1504] fix last error in examples --- examples/bench_compress.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/bench_compress.py b/examples/bench_compress.py index 2b4680c55..39bffe906 100644 --- a/examples/bench_compress.py +++ b/examples/bench_compress.py @@ -13,7 +13,7 @@ ntrials = 10 sys.stdout.write('reading and writing a %s by %s by %s by %s random array ..\n'%(n1dim,n2dim,n3dim,n4dim)) sys.stdout.write('(average of %s trials)\n' % ntrials) -array = netCDF4.utils._quantize(uniform(size=(n1dim,n2dim,n3dim,n4dim)),4) +array = netCDF4.utils._quantize(uniform(size=(n1dim,n2dim,n3dim,n4dim)),4) # type: ignore def write_netcdf(filename,zlib=False,shuffle=False,complevel=6): From 4bdf621f07805b795aa6731a8fbd298ab237b3bd Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 7 Jun 2024 22:25:59 +0200 Subject: [PATCH 1106/1504] fix type of chunksizes --- src/netCDF4/__init__.pyi | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 16d69c55c..513db6885 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -121,7 +121,7 @@ class Dataset: def filepath(self, encoding: str | None = None) -> str: ... def isopen(self) -> bool: ... - def close(self) -> None: ... + def close(self) -> memoryview: ... # only if writing and memory != None, but otherwise people ignore the return None anyway def sync(self) -> None: ... def set_fill_on(self) -> None: ... def set_fill_off(self) -> None: ... @@ -241,7 +241,7 @@ class Variable: blosc_shuffle: Literal[0, 1, 2] = 1, fletcher32: bool = False, contiguous: bool = False, - chunksizes: int | None = None, + chunksizes: Sequence[int] | None = None, endian: EndianOptions = 'native', least_significant_digit: int | None = None, significant_digits: int | None = None, @@ -352,7 +352,7 @@ class EnumType: dt: npt.DTypeLike, dtype_name: str, enum_dict: Mapping[str, int], - **kwargs + **kwargs: Any ) -> None: ... def __str__(self) -> str: ... From 5da5b82711844b8b6cfec182538cbffbca8f50c2 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 7 Jun 2024 22:31:54 +0200 Subject: [PATCH 1107/1504] remove some redundant funcs on MFDataset --- src/netCDF4/__init__.pyi | 8 -------- 1 file changed, 8 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 513db6885..87ee75fb0 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -370,14 +370,6 @@ class MFDataset(Dataset): master_file: str | os.PathLike | None = None ) -> None: ... - def ncattrs(self) -> list[str]: ... - def close(self) -> None: ... - def isopen(self) -> bool: ... - - def __setattr__(self, name: str, value: Any) -> None: ... - def __repr__(self) -> str: ... - def __reduce__(self) -> NoReturn: ... - class _Variable: def __init__(self, dset, varname, var, recdimname): ... From f433aab3ffe6b14d76fcb019969c2bbbab986ed8 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 7 Jun 2024 23:06:10 +0200 Subject: [PATCH 1108/1504] make variable generic --- .github/stubtest-allowlist | 8 ++-- src/netCDF4/__init__.pyi | 91 +++++++++++++++++++++++++++++++++----- 2 files changed, 84 insertions(+), 15 deletions(-) diff --git a/.github/stubtest-allowlist b/.github/stubtest-allowlist index 83b6855c0..07d967022 100644 --- a/.github/stubtest-allowlist +++ b/.github/stubtest-allowlist @@ -1,15 +1,17 @@ netCDF4.AccessModeOptions netCDF4.CompressionLevelOptions netCDF4.CompressionOptions -netCDF4.Dataset.__dealloc netCDF4.DatatypeOptions -netCDF4.Dimension.__reduce_cython__ -netCDF4.Dimension.__setstate_cython__ netCDF4.DimensionsOptions netCDF4.DiskFormatOptions netCDF4.EndianOptions netCDF4.FormatOptions netCDF4.QuantizeOptions +netCDF4.T_Datatype +netCDF4.T_DatatypeNC +netCDF4.Dataset.__dealloc +netCDF4.Dimension.__reduce_cython__ +netCDF4.Dimension.__setstate_cython__ netCDF4.Variable.auto_complex netCDF4.__has_ncfilter__ netCDF4.__has_parallel_support__ diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 87ee75fb0..62edf7c84 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -1,6 +1,19 @@ import os -from typing import TypeAlias, Literal, Any, NoReturn, Iterable, Mapping, Union, Sequence +from typing import ( + TypeAlias, + Literal, + Any, + NoReturn, + Iterable, + Mapping, + Union, + Sequence, + TypeVar, + Generic, + overload +) + from typing_extensions import Buffer from cftime import num2date, date2num, date2index @@ -15,15 +28,12 @@ __all__ = [ ] __pdoc__ = {'utils': False} -DatatypeOptions: TypeAlias = Union[ - Literal[ - 'S1', 'c', 'i1', 'b', 'B', 'u1', 'i2', 'h', 's', 'u2', 'i4', - 'i', 'l', 'u4', 'i8', 'u8', 'f4', 'f', 'f8', 'd', 'c8', 'c16' - ], - npt.DTypeLike, - CompoundType, - VLType +_DatatypeStrOptions: TypeAlias = Literal[ + 'S1', 'c', 'i1', 'b', 'B', 'u1', 'i2', 'h', 's', 'u2', 'i4', + 'i', 'l', 'u4', 'i8', 'u8', 'f4', 'f', 'f8', 'd', 'c8', 'c16' ] +_DatatypeNCOptions: TypeAlias = Union[CompoundType, VLType, EnumType] +DatatypeOptions: TypeAlias = Union[_DatatypeStrOptions, _DatatypeNCOptions, npt.DTypeLike] DimensionsOptions: TypeAlias = Union[str, bytes, Dimension, Iterable[Union[str, bytes, Dimension]]] CompressionOptions: TypeAlias = Literal[ 'zlib', 'szip', 'zstd', 'blosc_lz','blosc_lz4', @@ -225,12 +235,69 @@ class Dimension: def __repr__(self) -> str: ... -class Variable: +T_Datatype = TypeVar("T_Datatype", bound=DatatypeOptions) +T_DatatypeNC = TypeVar("T_DatatypeNC", CompoundType, VLType, EnumType) + +class Variable(Generic[T_Datatype]): + + @overload + def __new__( # type: ignore + self, + grp: Group, + name: str, + datatype: T_DatatypeNC, + dimensions: DimensionsOptions = (), + compression: CompressionOptions = None, + zlib: bool = False, + complevel: CompressionLevelOptions = 4, + shuffle: bool = True, + szip_coding: Literal['nn', 'ec'] = 'nn', + szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, + blosc_shuffle: Literal[0, 1, 2] = 1, + fletcher32: bool = False, + contiguous: bool = False, + chunksizes: Sequence[int] | None = None, + endian: EndianOptions = 'native', + least_significant_digit: int | None = None, + significant_digits: int | None = None, + quantize_mode: QuantizeOptions = 'BitGroom', + fill_value: npt.ArrayLike | bool | None = None, + chunk_cache: int | None = None, + **kwargs: Any + ) -> Variable[T_DatatypeNC]: ... + + @overload + def __new__( + self, + grp: Group, + name: str, + datatype: _DatatypeStrOptions | npt.DTypeLike, + dimensions: DimensionsOptions = (), + compression: CompressionOptions = None, + zlib: bool = False, + complevel: CompressionLevelOptions = 4, + shuffle: bool = True, + szip_coding: Literal['nn', 'ec'] = 'nn', + szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, + blosc_shuffle: Literal[0, 1, 2] = 1, + fletcher32: bool = False, + contiguous: bool = False, + chunksizes: Sequence[int] | None = None, + endian: EndianOptions = 'native', + least_significant_digit: int | None = None, + significant_digits: int | None = None, + quantize_mode: QuantizeOptions = 'BitGroom', + fill_value: npt.ArrayLike | bool | None = None, + chunk_cache: int | None = None, + **kwargs: Any + ) -> Variable[np.dtype]: ... + + def __init__( self, grp: Group, name: str, - datatype: DatatypeOptions, + datatype: T_Datatype, dimensions: DimensionsOptions = (), compression: CompressionOptions = None, zlib: bool = False, @@ -256,7 +323,7 @@ class Variable: @property def dtype(self) -> np.dtype: ... @property - def datatype(self) -> np.dtype | CompoundType | VLType | EnumType: ... + def datatype(self) -> T_Datatype: ... @property def shape(self) -> tuple[int, ...]: ... @property From 60580bf61ec4c670bc8a1a43c8cfd70ae15b082b Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 7 Jun 2024 23:15:52 +0200 Subject: [PATCH 1109/1504] add overloads for createVariable to return generics --- examples/tutorial.py | 22 +++++++++++----------- src/netCDF4/__init__.pyi | 37 +++++++++++++++++++++++++++++++------ 2 files changed, 42 insertions(+), 17 deletions(-) diff --git a/examples/tutorial.py b/examples/tutorial.py index c915abc6d..498e22154 100644 --- a/examples/tutorial.py +++ b/examples/tutorial.py @@ -140,10 +140,10 @@ def walktree(top): complex128_t = nc.createCompoundType(complex128,'complex128') # create a variable with this data type, write some data to it. nc.createDimension('x_dim',None) -v = nc.createVariable('cmplx_var',complex128_t,'x_dim') +var_complex = nc.createVariable('cmplx_var',complex128_t,'x_dim') data = np.empty(size,complex128) # numpy structured array data['real'] = datac.real; data['imag'] = datac.imag -v[:] = data +var_complex[:] = data # close and reopen the file, check the contents. nc.close() nc = Dataset('complex.nc') @@ -151,9 +151,9 @@ def walktree(top): print(nc.variables['cmplx_var']) print(nc.cmptypes) print(nc.cmptypes['complex128']) -v = nc.variables['cmplx_var'] -print(v.shape) -datain = v[:] # read in all the data into a numpy structured array +var_complex = nc.variables['cmplx_var'] +print(var_complex.shape) +datain = var_complex[:] # read in all the data into a numpy structured array # create an empty numpy complex array datac2 = np.empty(datain.shape,np.complex128) # .. fill it with contents of structured array. @@ -293,13 +293,13 @@ def walktree(top): nc = Dataset('stringtest.nc','w',format='NETCDF4_CLASSIC') nc.createDimension('nchars',3) nc.createDimension('nstrings',None) -v = nc.createVariable('strings','S1',('nstrings','nchars')) +var = nc.createVariable('strings','S1',('nstrings','nchars')) datain = np.array(['foo','bar'],dtype='S3') -v[:] = stringtochar(datain) # manual conversion to char array -print(v[:]) # data returned as char array -v._Encoding = 'ascii' # this enables automatic conversion -v[:] = datain # conversion to char array done internally -print(v[:]) # data returned in numpy string array +var[:] = stringtochar(datain) # manual conversion to char array +print(var[:]) # data returned as char array +var._Encoding = 'ascii' # this enables automatic conversion +var[:] = datain # conversion to char array done internally +print(var[:]) # data returned in numpy string array nc.close() # strings in compound types nc = Dataset('compoundstring_example.nc','w') diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 62edf7c84..384091609 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -34,6 +34,9 @@ _DatatypeStrOptions: TypeAlias = Literal[ ] _DatatypeNCOptions: TypeAlias = Union[CompoundType, VLType, EnumType] DatatypeOptions: TypeAlias = Union[_DatatypeStrOptions, _DatatypeNCOptions, npt.DTypeLike] +T_Datatype = TypeVar("T_Datatype", bound=DatatypeOptions) +T_DatatypeNC = TypeVar("T_DatatypeNC", CompoundType, VLType, EnumType) + DimensionsOptions: TypeAlias = Union[str, bytes, Dimension, Iterable[Union[str, bytes, Dimension]]] CompressionOptions: TypeAlias = Literal[ 'zlib', 'szip', 'zstd', 'blosc_lz','blosc_lz4', @@ -49,6 +52,7 @@ DiskFormatOptions: TypeAlias = Literal['NETCDF3', 'HDF5', 'HDF4', 'PNETCDF', 'DA QuantizeOptions: TypeAlias = Literal['BitGroom', 'BitRound', 'GranularBitRound'] EndianOptions: TypeAlias = Literal['native', 'little', 'big'] + __version__: str __netcdf4libversion__: str __hdf5libversion__: str @@ -105,7 +109,7 @@ class Dataset: @property def dimensions(self) -> dict[str, Dimension]: ... @property - def variables(self) -> dict[str, Variable]: ... + def variables(self) -> dict[str, Variable[Any]]: ... @property def cmptypes(self) -> dict[str, CompoundType]: ... @property @@ -138,10 +142,34 @@ class Dataset: def createDimension(self, dimname: str, size: int | None = None) -> Dimension: ... def renameDimension( self, oldname: str, newname: str) -> None: ... + @overload + def createVariable( # type: ignore + self, + varname: str, + datatype: T_DatatypeNC, + dimensions: DimensionsOptions = (), + compression: CompressionOptions = None, + zlib: bool = False, + complevel: CompressionLevelOptions = 4, + shuffle: bool = True, + szip_coding: Literal['nn', 'ec'] = 'nn', + szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, + blosc_shuffle: Literal[0, 1, 2] = 1, + fletcher32: bool = False, + contiguous: bool = False, + chunksizes: int | None = None, + endian: EndianOptions = 'native', + least_significant_digit: int | None = None, + significant_digits: int | None = None, + quantize_mode: QuantizeOptions = 'BitGroom', + fill_value: npt.ArrayLike | bool | None = None, + chunk_cache: int | None = None + ) -> Variable[T_DatatypeNC]: ... + @overload def createVariable( self, varname: str, - datatype: DatatypeOptions, + datatype: _DatatypeStrOptions | npt.DTypeLike, dimensions: DimensionsOptions = (), compression: CompressionOptions = None, zlib: bool = False, @@ -159,7 +187,7 @@ class Dataset: quantize_mode: QuantizeOptions = 'BitGroom', fill_value: npt.ArrayLike | bool | None = None, chunk_cache: int | None = None - ) -> Variable: ... + ) -> Variable[np.dtype]: ... def renameVariable(self, oldname: str, newname: str) -> None: ... def createGroup(self, groupname: str) -> Group: ... def renameGroup(self, oldname: str, newname: str) -> None: ... @@ -235,9 +263,6 @@ class Dimension: def __repr__(self) -> str: ... -T_Datatype = TypeVar("T_Datatype", bound=DatatypeOptions) -T_DatatypeNC = TypeVar("T_DatatypeNC", CompoundType, VLType, EnumType) - class Variable(Generic[T_Datatype]): @overload From b34dab8e76c7d10d87f1b782a06d0f30a164c54c Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 16 Oct 2023 12:57:30 -0300 Subject: [PATCH 1110/1504] cibuildwheel --- .github/workflows/cibuildwheel.yml | 164 +++++++++++++++++++++++++++++ pyproject.toml | 1 + 2 files changed, 165 insertions(+) create mode 100644 .github/workflows/cibuildwheel.yml diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml new file mode 100644 index 000000000..6ff0b5378 --- /dev/null +++ b/.github/workflows/cibuildwheel.yml @@ -0,0 +1,164 @@ +name: Wheels + +on: + pull_request: + push: + tags: + - "v*" + release: + types: + - published + +permissions: + contents: read + +jobs: + + build_sdist: + name: Build source distribution + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + - uses: actions/setup-python@v4 + name: Install Python + with: + python-version: 3.x + + - name: Install APT packages + if: contains(${{ matrix.os }}, 'ubuntu') + run: | + sudo apt update + sudo apt install libhdf5-dev libnetcdf-dev + + - name: Build sdist + run: > + pip install build + && python -m build --sdist . --outdir dist + + - uses: actions/upload-artifact@v3 + with: + path: dist/*.tar.gz + + + build_bdist: + name: "Build ${{ matrix.os }} (${{ matrix.arch }}) wheels" + runs-on: ${{ matrix.os }} + strategy: + fail-fast: false + matrix: + os: ["ubuntu-latest", "macos-latest"] + arch: ["x86_64", "arm64"] + exclude: + - os: ubuntu-latest + arch: arm64 + + steps: + - uses: actions/checkout@v4 + with: + fetch-depth: 0 + + - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels" + uses: pypa/cibuildwheel@v2.15.0 + env: + # Skips pypy and musllinux for now. + CIBW_SKIP: "pp* cp36-* cp37-* *-musllinux*" + CIBW_ARCHS: ${{ matrix.arch }} + CIBW_BUILD_FRONTEND: build + CIBW_MANYLINUX_X86_64_IMAGE: manylinux2014 + CIBW_BEFORE_BUILD_LINUX: yum install -y hdf5-devel netcdf-devel + CIBW_BEFORE_BUILD_MACOS: brew install hdf5 netcdf + CIBW_TEST_SKIP: "*_arm64" + CIBW_TEST_REQUIRES: pytest cython + CIBW_TEST_COMMAND: > + python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')" && + cd {project}/test && python run_all.py + + - uses: actions/upload-artifact@v3 + with: + name: pypi-artifacts + path: ${{ github.workspace }}/wheelhouse/*.whl + + + build_wheels_windows: + name: Build wheels for ${{matrix.arch}} on ${{ matrix.os }} + runs-on: ${{ matrix.os }} + strategy: + matrix: + os: [windows-latest] + arch: [win_amd64] + + steps: + - uses: actions/checkout@v4 + + - uses: actions/setup-python@v4 + name: Install Python + with: + python-version: 3.x + + - name: Setup Micromamba Python ${{ matrix.python-version }} + uses: mamba-org/setup-micromamba@v1 + with: + environment-name: build + init-shell: bash + create-args: >- + python=${{ matrix.python-version }} hdf5 libnetcdf --channel conda-forge + + - name: Install cibuildwheel + run: | + python -m pip install --upgrade cibuildwheel + + - name: Build wheels for Windows (${{ matrix.arch }}) + run: cibuildwheel --output-dir wheelhouse + env: + CIBW_BUILD: "cp39-${{ matrix.arch }} cp310-${{ matrix.arch }} cp311-${{ matrix.arch }} cp312-${{ matrix.arch }}" + CIBW_ENVIRONMENT_WINDOWS: > + HDF5_DIR="C:\\Users\\runneradmin\\micromamba\\envs\\build\\Library" + netCDF4_DIR="C:\\Users\\runneradmin\\micromamba\\envs\\build\\Library" + PATH="C:\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin;${PATH}" + CIBW_BEFORE_BUILD: "python -m pip install delvewheel" + CIBW_REPAIR_WHEEL_COMMAND_WINDOWS: "delvewheel repair -w {dest_dir} {wheel}" + CIBW_TEST_COMMAND: > + python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')" + && xcopy {project}\\test . /E/H + && python -m pip install --upgrade numpy cython packaging + && python run_all.py + + - uses: actions/upload-artifact@v3 + with: + name: pypi-artifacts + path: ${{ github.workspace }}/wheelhouse/*.whl + + + show-artifacts: + needs: [build_bdist, build_sdist, build_wheels_windows] + name: "Show artifacts" + runs-on: ubuntu-latest + steps: + - uses: actions/download-artifact@v3 + with: + name: pypi-artifacts + path: ${{ github.workspace }}/dist + + - shell: bash + run: | + ls -l ${{ github.workspace }}/dist + + + publish-artifacts-pypi: + needs: [build_bdist, build_sdist, build_wheels_windows] + name: "Publish to PyPI" + runs-on: ubuntu-latest + # upload to PyPI for every tag starting with 'v' + if: github.event_name == 'push' && startsWith(github.event.ref, 'refs/tags/v') + steps: + - uses: actions/download-artifact@v3 + with: + name: pypi-artifacts + path: ${{ github.workspace }}/dist + + - uses: pypa/gh-action-pypi-publish@release/v1 + with: + user: __token__ + password: ${{ secrets.PYPI_PASSWORD }} + print_hash: true diff --git a/pyproject.toml b/pyproject.toml index e58ccd16e..30ac51ca0 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,6 +4,7 @@ requires = [ "oldest-supported-numpy ; python_version < '3.9'", "numpy>=2.0.0rc1 ; python_version >= '3.9'", "setuptools>=61", + "packaging", ] build-backend = "setuptools.build_meta" From da5b2417934331ad050eed49850b2aae54fd9e6d Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Sun, 22 Oct 2023 15:45:09 -0300 Subject: [PATCH 1111/1504] show DLLs and pin libnetcdf for more control --- .github/workflows/cibuildwheel.yml | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 6ff0b5378..455637caf 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -102,7 +102,7 @@ jobs: environment-name: build init-shell: bash create-args: >- - python=${{ matrix.python-version }} hdf5 libnetcdf --channel conda-forge + python=${{ matrix.python-version }} libnetcdf=4.9.2 --channel conda-forge - name: Install cibuildwheel run: | @@ -117,7 +117,9 @@ jobs: netCDF4_DIR="C:\\Users\\runneradmin\\micromamba\\envs\\build\\Library" PATH="C:\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin;${PATH}" CIBW_BEFORE_BUILD: "python -m pip install delvewheel" - CIBW_REPAIR_WHEEL_COMMAND_WINDOWS: "delvewheel repair -w {dest_dir} {wheel}" + CIBW_REPAIR_WHEEL_COMMAND_WINDOWS: > + delvewheel show {wheel} + && delvewheel repair -w {dest_dir} {wheel} CIBW_TEST_COMMAND: > python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')" && xcopy {project}\\test . /E/H From ffb47d842123c1b73acf6f4088cfdc6fbaec6235 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 23 Oct 2023 08:30:48 -0300 Subject: [PATCH 1112/1504] build netcdf-c --- .ci/build_deps.sh | 28 ++++++++++++++++++++++++++++ .github/workflows/cibuildwheel.yml | 9 +++++---- 2 files changed, 33 insertions(+), 4 deletions(-) create mode 100644 .ci/build_deps.sh diff --git a/.ci/build_deps.sh b/.ci/build_deps.sh new file mode 100644 index 000000000..74f1b89f3 --- /dev/null +++ b/.ci/build_deps.sh @@ -0,0 +1,28 @@ +#!/usr/bin/bash + +set -ex + + +download_and_build_netcdf() { + if [ ! -d "netcdf-c" ]; then + netcdf_url=https://github.com/Unidata/netcdf-c + netcdf_src=netcdf-c + netcdf_build=netcdf-build + + git clone ${netcdf_url} -b v4.9.2 ${netcdf_src} + + cmake ${netcdf_src} -B ${netcdf_build} \ + -DENABLE_NETCDF4=on \ + -DENABLE_HDF5=on \ + -DENABLE_DAP=on \ + -DENABLE_TESTS=off \ + -DENABLE_PLUGIN_INSTALL=off \ + -DBUILD_SHARED_LIBS=on \ + -DCMAKE_BUILD_TYPE=Release + + cmake --build ${netcdf_build} \ + --target install +fi +} + +download_and_build_netcdf diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 455637caf..742789ad7 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -55,8 +55,6 @@ jobs: steps: - uses: actions/checkout@v4 - with: - fetch-depth: 0 - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels" uses: pypa/cibuildwheel@v2.15.0 @@ -65,8 +63,11 @@ jobs: CIBW_SKIP: "pp* cp36-* cp37-* *-musllinux*" CIBW_ARCHS: ${{ matrix.arch }} CIBW_BUILD_FRONTEND: build - CIBW_MANYLINUX_X86_64_IMAGE: manylinux2014 - CIBW_BEFORE_BUILD_LINUX: yum install -y hdf5-devel netcdf-devel + CIBW_MANYLINUX_X86_64_IMAGE: manylinux_2_28 + CIBW_BEFORE_BUILD_LINUX: > + dnf install -y epel-release + && dnf install -y hdf5-devel libcurl-devel + && sh .ci/build_deps.sh CIBW_BEFORE_BUILD_MACOS: brew install hdf5 netcdf CIBW_TEST_SKIP: "*_arm64" CIBW_TEST_REQUIRES: pytest cython From 83dbdc72e600765ffd50b367d510f596c50ff5e8 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 23 Oct 2023 14:47:33 -0300 Subject: [PATCH 1113/1504] declare test deps --- pyproject.toml | 2 -- 1 file changed, 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 30ac51ca0..fc24775e6 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,6 @@ requires = [ "oldest-supported-numpy ; python_version < '3.9'", "numpy>=2.0.0rc1 ; python_version >= '3.9'", "setuptools>=61", - "packaging", ] build-backend = "setuptools.build_meta" @@ -48,7 +47,6 @@ tests = [ "pytest", ] - [project.readme] text = """\ netCDF version 4 has many features not found in earlier versions of the library, From 49ddb96d0cdf73cb03e52f7c44f8772fee328a7e Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 23 Oct 2023 15:06:24 -0300 Subject: [PATCH 1114/1504] Condense a bit --- .github/workflows/cibuildwheel.yml | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 742789ad7..b9578b71f 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -70,7 +70,7 @@ jobs: && sh .ci/build_deps.sh CIBW_BEFORE_BUILD_MACOS: brew install hdf5 netcdf CIBW_TEST_SKIP: "*_arm64" - CIBW_TEST_REQUIRES: pytest cython + CIBW_TEST_REQUIRES: pytest cython packaging CIBW_TEST_COMMAND: > python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')" && cd {project}/test && python run_all.py @@ -107,7 +107,7 @@ jobs: - name: Install cibuildwheel run: | - python -m pip install --upgrade cibuildwheel + python -m pip install --upgrade cibuildwheel delvewheel - name: Build wheels for Windows (${{ matrix.arch }}) run: cibuildwheel --output-dir wheelhouse @@ -117,14 +117,13 @@ jobs: HDF5_DIR="C:\\Users\\runneradmin\\micromamba\\envs\\build\\Library" netCDF4_DIR="C:\\Users\\runneradmin\\micromamba\\envs\\build\\Library" PATH="C:\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin;${PATH}" - CIBW_BEFORE_BUILD: "python -m pip install delvewheel" CIBW_REPAIR_WHEEL_COMMAND_WINDOWS: > delvewheel show {wheel} && delvewheel repair -w {dest_dir} {wheel} + CIBW_TEST_REQUIRES: pytest cython packaging CIBW_TEST_COMMAND: > python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')" && xcopy {project}\\test . /E/H - && python -m pip install --upgrade numpy cython packaging && python run_all.py - uses: actions/upload-artifact@v3 From ab4381f3093533c6e3e7d5ac346658d8797476cd Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Tue, 24 Oct 2023 14:37:14 -0300 Subject: [PATCH 1115/1504] human readable sizes --- .github/workflows/cibuildwheel.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index b9578b71f..82396e037 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -144,7 +144,7 @@ jobs: - shell: bash run: | - ls -l ${{ github.workspace }}/dist + ls -lh ${{ github.workspace }}/dist publish-artifacts-pypi: From dcce9e02e81cd337b37b3026197f95b8107a9de5 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 10 Jun 2024 17:30:39 +0200 Subject: [PATCH 1116/1504] pin ubuntu --- .github/workflows/cibuildwheel.yml | 26 ++++++++++++++++---------- 1 file changed, 16 insertions(+), 10 deletions(-) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 82396e037..1f179b2d5 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -16,7 +16,7 @@ jobs: build_sdist: name: Build source distribution - runs-on: ubuntu-latest + runs-on: ubuntu-22.04 steps: - uses: actions/checkout@v4 @@ -47,17 +47,23 @@ jobs: strategy: fail-fast: false matrix: - os: ["ubuntu-latest", "macos-latest"] - arch: ["x86_64", "arm64"] - exclude: - - os: ubuntu-latest - arch: arm64 + include: + - os: ubuntu-22.04 + arch: x86_64 + - os: ubuntu-22.04 + arch: aarch64 + - os: macos-14 + arch: arm64 + - os: macos-13 + arch: x86_64 steps: - uses: actions/checkout@v4 - + with: + fetch-depth: 0 + - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels" - uses: pypa/cibuildwheel@v2.15.0 + uses: pypa/cibuildwheel@v2.18.1 env: # Skips pypy and musllinux for now. CIBW_SKIP: "pp* cp36-* cp37-* *-musllinux*" @@ -135,7 +141,7 @@ jobs: show-artifacts: needs: [build_bdist, build_sdist, build_wheels_windows] name: "Show artifacts" - runs-on: ubuntu-latest + runs-on: ubuntu-22.04 steps: - uses: actions/download-artifact@v3 with: @@ -150,7 +156,7 @@ jobs: publish-artifacts-pypi: needs: [build_bdist, build_sdist, build_wheels_windows] name: "Publish to PyPI" - runs-on: ubuntu-latest + runs-on: ubuntu-22.04 # upload to PyPI for every tag starting with 'v' if: github.event_name == 'push' && startsWith(github.event.ref, 'refs/tags/v') steps: From 310fcf13493153b9bf84bd4248201cdf6eca379f Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 10 Jun 2024 17:54:20 +0200 Subject: [PATCH 1117/1504] submodules --- .github/workflows/cibuildwheel.yml | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 1f179b2d5..d7fa0e8bc 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -19,6 +19,8 @@ jobs: runs-on: ubuntu-22.04 steps: - uses: actions/checkout@v4 + with: + fetch-depth: 0 - uses: actions/setup-python@v4 name: Install Python @@ -61,6 +63,7 @@ jobs: - uses: actions/checkout@v4 with: fetch-depth: 0 + submodules: 'true' - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels" uses: pypa/cibuildwheel@v2.18.1 @@ -97,6 +100,9 @@ jobs: steps: - uses: actions/checkout@v4 + with: + fetch-depth: 0 + submodules: 'true' - uses: actions/setup-python@v4 name: Install Python From 3dbf4b1b8788d165224964d43835d39054ce96f9 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 10 Jun 2024 18:33:47 +0200 Subject: [PATCH 1118/1504] don't build aarch64 for now --- .github/workflows/cibuildwheel.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index d7fa0e8bc..2823a353e 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -52,8 +52,8 @@ jobs: include: - os: ubuntu-22.04 arch: x86_64 - - os: ubuntu-22.04 - arch: aarch64 + # - os: ubuntu-22.04 + # arch: aarch64 - os: macos-14 arch: arm64 - os: macos-13 From 11b470f69c0573d74c2e0f444ec5fe98e1da2ee8 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 10 Jun 2024 18:46:14 +0200 Subject: [PATCH 1119/1504] increase verbosity --- test/run_all.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/test/run_all.py b/test/run_all.py index 705cc6520..ef0df30b1 100755 --- a/test/run_all.py +++ b/test/run_all.py @@ -16,7 +16,7 @@ testsuite.addTests(unittest.TestLoader().loadTestsFromModule(m)) # Run the test suite. -def test(verbosity=1): +def test(verbosity=2): runner = unittest.TextTestRunner(verbosity=verbosity) runner.run(testsuite) From 6f88d6ac162dff7b6d620b887d97c35b560fa0d5 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 10 Jun 2024 18:53:28 +0200 Subject: [PATCH 1120/1504] increase verbosity, again --- test/run_all.py | 6 +----- 1 file changed, 1 insertion(+), 5 deletions(-) diff --git a/test/run_all.py b/test/run_all.py index ef0df30b1..3c38cbb16 100755 --- a/test/run_all.py +++ b/test/run_all.py @@ -15,10 +15,6 @@ m = __import__(os.path.splitext(f)[0]) testsuite.addTests(unittest.TestLoader().loadTestsFromModule(m)) -# Run the test suite. -def test(verbosity=2): - runner = unittest.TextTestRunner(verbosity=verbosity) - runner.run(testsuite) if __name__ == '__main__': import numpy, cython @@ -28,7 +24,7 @@ def test(verbosity=2): sys.stdout.write('netcdf lib version: %s\n' % __netcdf4libversion__) sys.stdout.write('numpy version %s\n' % numpy.__version__) sys.stdout.write('cython version %s\n' % cython.__version__) - runner = unittest.TextTestRunner(verbosity=1) + runner = unittest.TextTestRunner(verbosity=2) result = runner.run(testsuite) if not result.wasSuccessful(): sys.exit(1) From 2cb4c25c3f2ea743604e1a2f3b786b6549ee9546 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 10 Jun 2024 19:22:14 +0200 Subject: [PATCH 1121/1504] try to call pytest on Windows instead --- .github/workflows/cibuildwheel.yml | 4 +--- test/run_all.py | 2 +- 2 files changed, 2 insertions(+), 4 deletions(-) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 2823a353e..cb2ff3635 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -78,7 +78,6 @@ jobs: && dnf install -y hdf5-devel libcurl-devel && sh .ci/build_deps.sh CIBW_BEFORE_BUILD_MACOS: brew install hdf5 netcdf - CIBW_TEST_SKIP: "*_arm64" CIBW_TEST_REQUIRES: pytest cython packaging CIBW_TEST_COMMAND: > python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')" && @@ -135,8 +134,7 @@ jobs: CIBW_TEST_REQUIRES: pytest cython packaging CIBW_TEST_COMMAND: > python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')" - && xcopy {project}\\test . /E/H - && python run_all.py + && pytest -s -rxs -v {project}\\test - uses: actions/upload-artifact@v3 with: diff --git a/test/run_all.py b/test/run_all.py index 3c38cbb16..deff8c6af 100755 --- a/test/run_all.py +++ b/test/run_all.py @@ -24,7 +24,7 @@ sys.stdout.write('netcdf lib version: %s\n' % __netcdf4libversion__) sys.stdout.write('numpy version %s\n' % numpy.__version__) sys.stdout.write('cython version %s\n' % cython.__version__) - runner = unittest.TextTestRunner(verbosity=2) + runner = unittest.TextTestRunner(verbosity=1) result = runner.run(testsuite) if not result.wasSuccessful(): sys.exit(1) From 33eebb9672494c88614ff22c2a44c121f2ee8275 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 10 Jun 2024 20:31:06 +0200 Subject: [PATCH 1122/1504] set MACOSX_DEPLOYMENT_TARGET --- .github/workflows/cibuildwheel.yml | 3 +++ 1 file changed, 3 insertions(+) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index cb2ff3635..9e30ca9f5 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -56,8 +56,10 @@ jobs: # arch: aarch64 - os: macos-14 arch: arm64 + CIBW_ENVIRONMENT: MACOSX_DEPLOYMENT_TARGET=14.0 - os: macos-13 arch: x86_64 + CIBW_ENVIRONMENT: MACOSX_DEPLOYMENT_TARGET=13.0 steps: - uses: actions/checkout@v4 @@ -77,6 +79,7 @@ jobs: dnf install -y epel-release && dnf install -y hdf5-devel libcurl-devel && sh .ci/build_deps.sh + CIBW_ENVIRONMENT: ${{ matrix.CIBW_ENVIRONMENT }} CIBW_BEFORE_BUILD_MACOS: brew install hdf5 netcdf CIBW_TEST_REQUIRES: pytest cython packaging CIBW_TEST_COMMAND: > From db5b32101f9a045e4131874f3acf984d2508d117 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 10 Jun 2024 21:35:29 +0200 Subject: [PATCH 1123/1504] make sure all artifacts are available for upload --- .github/workflows/cibuildwheel.yml | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 9e30ca9f5..3d8445ecf 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -38,9 +38,10 @@ jobs: pip install build && python -m build --sdist . --outdir dist - - uses: actions/upload-artifact@v3 + - uses: actions/upload-artifact@v4 with: - path: dist/*.tar.gz + name: pypi-artifacts + path: ${{ github.workspace }}/dist/*.tar.gz build_bdist: @@ -86,9 +87,9 @@ jobs: python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')" && cd {project}/test && python run_all.py - - uses: actions/upload-artifact@v3 + - uses: actions/upload-artifact@v4 with: - name: pypi-artifacts + name: pypi-artifacts-${{ matrix.os }}-${{ matrix.arch }} path: ${{ github.workspace }}/wheelhouse/*.whl @@ -139,9 +140,9 @@ jobs: python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')" && pytest -s -rxs -v {project}\\test - - uses: actions/upload-artifact@v3 + - uses: actions/upload-artifact@v4 with: - name: pypi-artifacts + name: pypi-artifacts-${{ matrix.os }}-${{ matrix.arch }} path: ${{ github.workspace }}/wheelhouse/*.whl From d5521bf91998478d67d21612c3e4e18de2d1174e Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 10 Jun 2024 22:04:39 +0200 Subject: [PATCH 1124/1504] use pytest instead of run_all for nix --- .github/workflows/cibuildwheel.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 3d8445ecf..1b6e0de62 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -84,8 +84,8 @@ jobs: CIBW_BEFORE_BUILD_MACOS: brew install hdf5 netcdf CIBW_TEST_REQUIRES: pytest cython packaging CIBW_TEST_COMMAND: > - python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')" && - cd {project}/test && python run_all.py + python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')" + && pytest -s -rxs -v {project}/test - uses: actions/upload-artifact@v4 with: From 78d1c4f641f6fb9589ad4bf93972cd6218a5b630 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 10 Jun 2024 22:27:38 +0200 Subject: [PATCH 1125/1504] fix list artifacts --- .github/workflows/cibuildwheel.yml | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 1b6e0de62..8ba9f0412 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -151,10 +151,11 @@ jobs: name: "Show artifacts" runs-on: ubuntu-22.04 steps: - - uses: actions/download-artifact@v3 + - uses: actions/download-artifact@v4 with: - name: pypi-artifacts + pattern: pypi-artifacts* path: ${{ github.workspace }}/dist + merge-multiple: true - shell: bash run: | From 1452d902c2f7a34d1fc6766cff7edfb5a5f2cce1 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Tue, 11 Jun 2024 08:52:44 +0200 Subject: [PATCH 1126/1504] reduce matrix load on CIs --- .github/workflows/cibuildwheel.yml | 20 +++++++++++++++++--- 1 file changed, 17 insertions(+), 3 deletions(-) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 8ba9f0412..42e760fd4 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -67,12 +67,26 @@ jobs: with: fetch-depth: 0 submodules: 'true' - + + - name: Build oldest and newest Python + shell: bash + # On PRs we run only oldest and newest Python versions to reduce CI load. + # Skips pypy and musllinux everywhere. + # We are buiding 38 and 312 for now. + # These needs to rotate every new Python release. + run: | + if [[ "${{ github.event_name }}" == "pull_request" ]]; then + CIBW_SKIP="pp* cp36-* cp37-* *-musllinux* cp39-* cp310-* cp311-*" + else + CIBW_SKIP="pp* cp36-* cp37-* *-musllinux*" + fi + echo "CIBW_SKIP=$CIBW_SKIP" >> $GITHUB_ENV + echo "Setting CIBW_SKIP=$CIBW_SKIP" + - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels" uses: pypa/cibuildwheel@v2.18.1 env: - # Skips pypy and musllinux for now. - CIBW_SKIP: "pp* cp36-* cp37-* *-musllinux*" + CIBW_SKIP: ${{ env.CIBW_SKIP }} CIBW_ARCHS: ${{ matrix.arch }} CIBW_BUILD_FRONTEND: build CIBW_MANYLINUX_X86_64_IMAGE: manylinux_2_28 From 73d1890ea16a8d04e499aa260b60ad60d9e78ddd Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Wed, 12 Jun 2024 10:49:44 +0200 Subject: [PATCH 1127/1504] use oldest image possible for intel macs --- .github/workflows/cibuildwheel.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 42e760fd4..74eb6035e 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -58,9 +58,9 @@ jobs: - os: macos-14 arch: arm64 CIBW_ENVIRONMENT: MACOSX_DEPLOYMENT_TARGET=14.0 - - os: macos-13 + - os: macos-11 arch: x86_64 - CIBW_ENVIRONMENT: MACOSX_DEPLOYMENT_TARGET=13.0 + CIBW_ENVIRONMENT: MACOSX_DEPLOYMENT_TARGET=11.0 steps: - uses: actions/checkout@v4 From fa813448fa7087c274dd39b7ed15af80d78d9850 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Thu, 13 Jun 2024 03:58:06 +0000 Subject: [PATCH 1128/1504] Bump actions/download-artifact from 3 to 4 Bumps [actions/download-artifact](https://github.com/actions/download-artifact) from 3 to 4. - [Release notes](https://github.com/actions/download-artifact/releases) - [Commits](https://github.com/actions/download-artifact/compare/v3...v4) --- updated-dependencies: - dependency-name: actions/download-artifact dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- .github/workflows/cibuildwheel.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 74eb6035e..69bd73c56 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -183,7 +183,7 @@ jobs: # upload to PyPI for every tag starting with 'v' if: github.event_name == 'push' && startsWith(github.event.ref, 'refs/tags/v') steps: - - uses: actions/download-artifact@v3 + - uses: actions/download-artifact@v4 with: name: pypi-artifacts path: ${{ github.workspace }}/dist From 1bae39c0ecfb80410c88202d9e38bdcdebd87a63 Mon Sep 17 00:00:00 2001 From: jswhit Date: Thu, 13 Jun 2024 14:49:18 -0600 Subject: [PATCH 1129/1504] update release date --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index ac98e7f73..6f9e720a1 100644 --- a/README.md +++ b/README.md @@ -10,7 +10,7 @@ ## News For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog). -06/??/2024: Version [1.7.0](https://pypi.python.org/pypi/netCDF4/1.7.0) released. Add support for complex numbers via `auto_complex` keyword to `Dataset` ([PR #1295](https://github.com/Unidata/netcdf4-python/pull/1295)) +06/13/2024: Version [1.7.0](https://pypi.python.org/pypi/netCDF4/1.7.0) released. Add support for complex numbers via `auto_complex` keyword to `Dataset` ([PR #1295](https://github.com/Unidata/netcdf4-python/pull/1295)) 10/20/2023: Version [1.6.5](https://pypi.python.org/pypi/netCDF4/1.6.5) released. Fix for issue #1271 (mask ignored if bool MA assinged to uint8 var), From 037023ed622eb204ea5702f87bd7184600845c2f Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Fri, 14 Jun 2024 08:42:18 +0200 Subject: [PATCH 1130/1504] enable aarch64 --- .ci/build_deps.sh | 28 ---------------------------- .github/workflows/cibuildwheel.yml | 28 +++++++++++++++++++--------- 2 files changed, 19 insertions(+), 37 deletions(-) delete mode 100644 .ci/build_deps.sh diff --git a/.ci/build_deps.sh b/.ci/build_deps.sh deleted file mode 100644 index 74f1b89f3..000000000 --- a/.ci/build_deps.sh +++ /dev/null @@ -1,28 +0,0 @@ -#!/usr/bin/bash - -set -ex - - -download_and_build_netcdf() { - if [ ! -d "netcdf-c" ]; then - netcdf_url=https://github.com/Unidata/netcdf-c - netcdf_src=netcdf-c - netcdf_build=netcdf-build - - git clone ${netcdf_url} -b v4.9.2 ${netcdf_src} - - cmake ${netcdf_src} -B ${netcdf_build} \ - -DENABLE_NETCDF4=on \ - -DENABLE_HDF5=on \ - -DENABLE_DAP=on \ - -DENABLE_TESTS=off \ - -DENABLE_PLUGIN_INSTALL=off \ - -DBUILD_SHARED_LIBS=on \ - -DCMAKE_BUILD_TYPE=Release - - cmake --build ${netcdf_build} \ - --target install -fi -} - -download_and_build_netcdf diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 74eb6035e..c51e3b668 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -47,14 +47,16 @@ jobs: build_bdist: name: "Build ${{ matrix.os }} (${{ matrix.arch }}) wheels" runs-on: ${{ matrix.os }} + # Prevent hanging when building from emulation like aarch64. + timeout-minutes: 300 strategy: fail-fast: false matrix: include: - os: ubuntu-22.04 arch: x86_64 - # - os: ubuntu-22.04 - # arch: aarch64 + - os: ubuntu-22.04 + arch: aarch64 - os: macos-14 arch: arm64 CIBW_ENVIRONMENT: MACOSX_DEPLOYMENT_TARGET=14.0 @@ -67,7 +69,14 @@ jobs: with: fetch-depth: 0 submodules: 'true' - + + # For aarch64 support + # https://cibuildwheel.pypa.io/en/stable/faq/#emulation + - uses: docker/setup-qemu-action@v3 + with: + platforms: all + if: runner.os == 'Linux' && matrix.arch == 'aarch64' + - name: Build oldest and newest Python shell: bash # On PRs we run only oldest and newest Python versions to reduce CI load. @@ -84,22 +93,23 @@ jobs: echo "Setting CIBW_SKIP=$CIBW_SKIP" - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels" - uses: pypa/cibuildwheel@v2.18.1 + uses: pypa/cibuildwheel@v2.19.1 env: CIBW_SKIP: ${{ env.CIBW_SKIP }} CIBW_ARCHS: ${{ matrix.arch }} CIBW_BUILD_FRONTEND: build - CIBW_MANYLINUX_X86_64_IMAGE: manylinux_2_28 - CIBW_BEFORE_BUILD_LINUX: > - dnf install -y epel-release - && dnf install -y hdf5-devel libcurl-devel - && sh .ci/build_deps.sh + CIBW_MANYLINUX_X86_64_IMAGE: ghcr.io/ocefpaf/manylinux2014_x86_64-netcdf + CIBW_MANYLINUX_AARCH64_IMAGE: ghcr.io/ocefpaf/manylinux2014_aarch64-netcdf + # Emulation testing is slow, testing only latest Python. + CIBW_TEST_SKIP: "cp38-*_aarch64 cp39-*_aarch64 cp310-*_aarch64 cp311-*_aarch64" CIBW_ENVIRONMENT: ${{ matrix.CIBW_ENVIRONMENT }} CIBW_BEFORE_BUILD_MACOS: brew install hdf5 netcdf CIBW_TEST_REQUIRES: pytest cython packaging CIBW_TEST_COMMAND: > python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')" && pytest -s -rxs -v {project}/test + && URL="https://icdc.cen.uni-hamburg.de/thredds/dodsC/ftpthredds/hamtide/m2.hamtide11a.nc" + && python -c "from netCDF4 import Dataset; nc=Dataset(\"${URL}\"); print(nc)" - uses: actions/upload-artifact@v4 with: From 2004305a8bdbab049fb9f87bb4e69a5da32d5f19 Mon Sep 17 00:00:00 2001 From: jswhit Date: Fri, 14 Jun 2024 12:24:28 -0600 Subject: [PATCH 1131/1504] remove submodule nc_complex --- .gitmodules | 3 --- Changelog | 5 +++++ external/nc_complex | 1 - src/netCDF4/_netCDF4.pyx | 4 ++-- 4 files changed, 7 insertions(+), 6 deletions(-) delete mode 160000 external/nc_complex diff --git a/.gitmodules b/.gitmodules index c7064b7b3..e69de29bb 100644 --- a/.gitmodules +++ b/.gitmodules @@ -1,3 +0,0 @@ -[submodule "external/nc_complex"] - path = external/nc_complex - url = https://github.com/PlasmaFAIR/nc-complex.git diff --git a/Changelog b/Changelog index 03830b99b..5f068df80 100644 --- a/Changelog +++ b/Changelog @@ -1,3 +1,8 @@ + version 1.7.1 (tag v1.7.1rel) +=============================== + * include nc_complex source code (instead of using submodule). + * add aarch64 wheels. + version 1.7.0 (tag v1.7.0rel) =============================== * add support for complex numbers via `auto_complex` keyword to `Dataset` (PR #1295) diff --git a/external/nc_complex b/external/nc_complex deleted file mode 160000 index 37310ed00..000000000 --- a/external/nc_complex +++ /dev/null @@ -1 +0,0 @@ -Subproject commit 37310ed00f3910974bdefefcdfa4787588651f59 diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index b957f4e35..8ef6a342f 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1,4 +1,4 @@ -"""Version 1.7.0 +"""Version 1.7.1 ------------- # Introduction @@ -1272,7 +1272,7 @@ import sys import functools from typing import Union -__version__ = "1.7.0" +__version__ = "1.7.1" # Initialize numpy import posixpath From 4ecdbb1929ec7fb8d144c2557ef87ce17f38cd83 Mon Sep 17 00:00:00 2001 From: jswhit Date: Fri, 14 Jun 2024 12:24:55 -0600 Subject: [PATCH 1132/1504] add nc_complex source files --- .../generated_fallbacks/nc_complex_version.h | 6 + .../include/nc_complex/nc_complex.h | 291 ++++++ external/nc_complex/src/nc_complex.c | 867 ++++++++++++++++++ 3 files changed, 1164 insertions(+) create mode 100644 external/nc_complex/include/generated_fallbacks/nc_complex_version.h create mode 100644 external/nc_complex/include/nc_complex/nc_complex.h create mode 100644 external/nc_complex/src/nc_complex.c diff --git a/external/nc_complex/include/generated_fallbacks/nc_complex_version.h b/external/nc_complex/include/generated_fallbacks/nc_complex_version.h new file mode 100644 index 000000000..7a135743b --- /dev/null +++ b/external/nc_complex/include/generated_fallbacks/nc_complex_version.h @@ -0,0 +1,6 @@ +// This is a fallback header for when building the library without +// CMake -- you probably should use CMake to auto-generate this instead +#define NC_COMPLEX_GIT_SHA1 "unknown" +#define NC_COMPLEX_GIT_VERSION "0.1.0" +#define NC_COMPLEX_GIT_STATE "unknown" +#define NC_COMPLEX_GIT_DATE "unknown" diff --git a/external/nc_complex/include/nc_complex/nc_complex.h b/external/nc_complex/include/nc_complex/nc_complex.h new file mode 100644 index 000000000..a31841de3 --- /dev/null +++ b/external/nc_complex/include/nc_complex/nc_complex.h @@ -0,0 +1,291 @@ +/// nc-complex: A lightweight, drop-in extension for complex number support in +/// netCDF +/// +/// Copyright (C) 2023 Peter Hill +/// +/// SPDX-License-Identifier: MIT + +#ifndef PLASMA_FAIR_NC_COMPLEX +#define PLASMA_FAIR_NC_COMPLEX + +// This header is required when building as a DLL on Windows and is +// automatically generated by CMake. If you're not using CMake (and +// not on Windows) for some reason, then define `NC_COMPLEX_NO_EXPORT` +// to skip this. +#ifndef NC_COMPLEX_NO_EXPORT +#include "nc_complex/nc_complex_export.h" +#else +#define NC_COMPLEX_EXPORT +#endif + +#include +#include +#include +#include + +#ifdef __cplusplus +#include +#endif + +//@{ +/// Portable typedefs for complex numbers +/// +/// These become aliases for `std::complex` with C++. +#ifdef _MSC_VER +typedef _Dcomplex double_complex; +typedef _Fcomplex float_complex; +#else +#if defined(__cplusplus) && defined(__clang__) +using double_complex = std::complex; +using float_complex = std::complex; +#else +typedef double _Complex double_complex; +typedef float _Complex float_complex; +#endif +#endif +//@} + +#ifdef __cplusplus +/// @name Helper functions +///@{ +/// Helper functions for converting between (pointers to) C++ and C complex types +NC_COMPLEX_EXPORT inline double_complex* cpp_to_c_complex(std::complex* data) { + return reinterpret_cast(data); +} + +NC_COMPLEX_EXPORT inline std::complex* c_to_cpp_complex(double_complex* data) { + return reinterpret_cast*>(data); +} + +NC_COMPLEX_EXPORT inline float_complex* cpp_to_c_complex(std::complex* data) { + return reinterpret_cast(data); +} + +NC_COMPLEX_EXPORT inline std::complex* c_to_cpp_complex(float_complex* data) { + return reinterpret_cast*>(data); +} +///@} +extern "C" { +#endif + +/// @name Complex datatype defines +/// Datatype for complex numbers, for use with \rstref{pfnc_def_var} +/// +/// @note +/// These *only* work when defining a variable with \rstref{pfnc_def_var}. To +/// check the type of an existing variable use \rstref{pfnc_var_is_complex}, and +/// to check if it is specifically using a compound datatype or a dimension use +/// \rstref{pfnc_var_is_complex_type} or \rstref{pfnc_var_has_complex_dimension} +/// respectively. +/// @endnote +///@{ + +/// Uses complex compound datatype with netCDF4 format, and complex dimension otherwise +#define PFNC_FLOAT_COMPLEX (NC_FIRSTUSERTYPEID - 4) +/// Always use a complex dimension, regardless of file format +#define PFNC_FLOAT_COMPLEX_DIM (NC_FIRSTUSERTYPEID - 3) +/// Uses complex compound datatype with netCDF4 format, and complex dimension otherwise +#define PFNC_DOUBLE_COMPLEX (NC_FIRSTUSERTYPEID - 2) +/// Always use a complex dimension, regardless of file format +#define PFNC_DOUBLE_COMPLEX_DIM (NC_FIRSTUSERTYPEID - 1) +///@} + +/// Return true if variable is complex +NC_COMPLEX_EXPORT bool pfnc_var_is_complex(int ncid, int varid); +/// Return true if variable is complex and uses a compound datatype +NC_COMPLEX_EXPORT bool pfnc_var_is_complex_type(int ncid, int varid); +/// Return true if variable is complex and has a complex dimension +/// (assumed to be the last dimension) +NC_COMPLEX_EXPORT bool pfnc_var_has_complex_dimension(int ncid, int varid); + +/// Return true if dimension is complex +NC_COMPLEX_EXPORT bool pfnc_is_complex_dim(int ncid, int dim_id); + +/// Get the ID for the complex datatype with `double` elements, creating it if it doesn't already exist +NC_COMPLEX_EXPORT int pfnc_get_double_complex_typeid(int ncid, nc_type* nc_typeid); +/// Get the ID for the complex datatype with `float` elements, creating it if it doesn't already exist +NC_COMPLEX_EXPORT int pfnc_get_float_complex_typeid(int ncid, nc_type* nc_typeid); + +/// Get complex dimension, creating one if it doesn't already exist +NC_COMPLEX_EXPORT int pfnc_get_complex_dim(int ncid, int* nc_dim); + +/// Get the base numerical type of a complex type +/// +/// Returns the type of the components for a compound type, or the +/// type of an element for a dimension type. +NC_COMPLEX_EXPORT int pfnc_complex_base_type( + int ncid, nc_type nc_typeid, nc_type* base_type_id +); + +/// Get the base numerical type of a complex variable +NC_COMPLEX_EXPORT int pfnc_inq_var_complex_base_type( + int ncid, int varid, nc_type* nc_typeid +); + +/// Return some information about the `nc-complex` library +NC_COMPLEX_EXPORT const char* pfnc_inq_libvers(void); + +/// @name Wrappers +/// Wrappers for the equivalent `nc_*` functions that correctly handle +/// the start/count/stride arrays for complex dimensions. +/// +/// When the variable is stored using a complex dimension, the file +/// representation has one more dimension than the user-visible +/// in-memory representation. For example, a 1D array: +/// +/// ```c +/// double_complex data[5]; +/// ``` +/// +/// would be represented in the file with two dimensions (when not +/// using a compound datatype!), and so if we use the standard netCDF +/// API we would need to use `{5, 2}` for the `countp` arguments, for +/// example, while using nc-complex, we only need `{5}`. +/// +/// NOTE: The `pfnc_put/get*` functions do *not* currently handle +/// conversion between `float/double` base types +///@{ + +/// Extension to `nc_def_var` that also accepts +/// \rstref{PFNC_FLOAT_COMPLEX}, \rstref{PFNC_FLOAT_COMPLEX_DIM}, +/// \rstref{PFNC_DOUBLE_COMPLEX}, and \rstref{PFNC_DOUBLE_COMPLEX_DIM} +NC_COMPLEX_EXPORT int pfnc_def_var( + int ncid, + const char* name, + nc_type xtype, + int ndims, + const int* dimidsp, + int* varidp +); + +NC_COMPLEX_EXPORT int pfnc_put_vara_double_complex( + int ncid, + int varid, + const size_t* startp, + const size_t* countp, + const double_complex* op +); + +NC_COMPLEX_EXPORT int pfnc_get_vara_double_complex( + int ncid, int varid, const size_t* startp, const size_t* countp, double_complex* ip +); + +NC_COMPLEX_EXPORT int pfnc_put_vars_double_complex( + int ncid, + int varid, + const size_t* startp, + const size_t* countp, + const ptrdiff_t* stridep, + const double_complex* op +); + +NC_COMPLEX_EXPORT int pfnc_get_vars_double_complex( + int ncid, + int varid, + const size_t* startp, + const size_t* countp, + const ptrdiff_t* stridep, + double_complex* ip +); + +NC_COMPLEX_EXPORT int pfnc_put_var1_double_complex( + int ncid, int varid, const size_t* indexp, const double_complex* data +); +NC_COMPLEX_EXPORT int pfnc_get_var1_double_complex( + int ncid, int varid, const size_t* indexp, double_complex* data +); + +NC_COMPLEX_EXPORT int pfnc_put_vara_float_complex( + int ncid, + int varid, + const size_t* startp, + const size_t* countp, + const float_complex* op +); + +NC_COMPLEX_EXPORT int pfnc_get_vara_float_complex( + int ncid, int varid, const size_t* startp, const size_t* countp, float_complex* ip +); + +NC_COMPLEX_EXPORT int pfnc_put_vars_float_complex( + int ncid, + int varid, + const size_t* startp, + const size_t* countp, + const ptrdiff_t* stridep, + const float_complex* op +); + +NC_COMPLEX_EXPORT int pfnc_get_vars_float_complex( + int ncid, + int varid, + const size_t* startp, + const size_t* countp, + const ptrdiff_t* stridep, + float_complex* ip +); + +NC_COMPLEX_EXPORT int pfnc_put_var1_float_complex( + int ncid, int varid, const size_t* indexp, const float_complex* data +); +NC_COMPLEX_EXPORT int pfnc_get_var1_float_complex( + int ncid, int varid, const size_t* indexp, float_complex* data +); + +NC_COMPLEX_EXPORT int pfnc_inq_var( + int ncid, + int varid, + char* name, + nc_type* xtypep, + int* ndimsp, + int* dimidsp, + int* nattsp +); + +// NOLINTBEGIN(modernize-use-nullptr) +NC_COMPLEX_EXPORT inline int pfnc_inq_varndims(int ncid, int varid, int* ndimsp) { + return pfnc_inq_var(ncid, varid, NULL, NULL, ndimsp, NULL, NULL); +} +NC_COMPLEX_EXPORT inline int pfnc_inq_vardimid(int ncid, int varid, int* dimidsp) { + return pfnc_inq_var(ncid, varid, NULL, NULL, NULL, dimidsp, NULL); +} +// NOLINTEND(modernize-use-nullptr) + +NC_COMPLEX_EXPORT int pfnc_def_var_chunking( + int ncid, int varid, int storage, const size_t* chunksizesp +); +NC_COMPLEX_EXPORT int pfnc_inq_var_chunking( + int ncid, int varid, int* storagep, size_t* chunksizesp +); + +NC_COMPLEX_EXPORT int pfnc_get_vara( + int ncid, int varid, const size_t* startp, const size_t* countp, void* ip +); +NC_COMPLEX_EXPORT int pfnc_get_vars( + int ncid, + int varid, + const size_t* startp, + const size_t* countp, + const ptrdiff_t* stridep, + void* ip +); + +NC_COMPLEX_EXPORT int pfnc_put_vara( + int ncid, int varid, const size_t* startp, const size_t* countp, const void* op +); + +NC_COMPLEX_EXPORT int pfnc_put_vars( + int ncid, + int varid, + const size_t* startp, + const size_t* countp, + const ptrdiff_t* stridep, + const void* op +); +///@} + +#ifdef __cplusplus +} +#endif + +#endif diff --git a/external/nc_complex/src/nc_complex.c b/external/nc_complex/src/nc_complex.c new file mode 100644 index 000000000..68decb02c --- /dev/null +++ b/external/nc_complex/src/nc_complex.c @@ -0,0 +1,867 @@ +#include "nc_complex/nc_complex.h" + +#include +#include +#include +#include +#include +#include + +#include "nc_complex_version.h" + +// NOLINTBEGIN(bugprone-assignment-in-if-condition) +#define CHECK(func) \ + do { \ + int res; \ + if ((res = (func))) { \ + return res; \ + } \ + } while (0) +// NOLINTEND(bugprone-assignment-in-if-condition) + +// Vector of ones for get/put_var1 functions +static const size_t coord_one[NC_MAX_VAR_DIMS] = {1}; + +static const char* double_complex_struct_name = "_PFNC_DOUBLE_COMPLEX_TYPE"; +static const char* float_complex_struct_name = "_PFNC_FLOAT_COMPLEX_TYPE"; + +#define COMPLEX_DIM_NAME "_pfnc_complex" +static const char* complex_dim_name = COMPLEX_DIM_NAME; + +static const char* known_dim_names[] = {COMPLEX_DIM_NAME, "complex", "ri"}; +static const size_t num_known_dim_names = + sizeof(known_dim_names) / sizeof(known_dim_names[0]); + +static const char pfnc_libvers[] = NC_COMPLEX_GIT_VERSION; + +const char* pfnc_inq_libvers(void) { + return pfnc_libvers; +} + +bool pfnc_var_is_complex(int ncid, int varid) { + return pfnc_var_is_complex_type(ncid, varid) + || pfnc_var_has_complex_dimension(ncid, varid); +} + +int pfnc_complex_base_type(int ncid, nc_type nc_typeid, nc_type* base_type_id) { + if (nc_typeid < NC_MAX_ATOMIC_TYPE) { + *base_type_id = nc_typeid; + return NC_NOERR; + } + + // TODO: This should probably handle vlens too + + return nc_inq_compound_field( + ncid, nc_typeid, 0, NULL, NULL, base_type_id, NULL, NULL + ); +} + +int pfnc_inq_var_complex_base_type(int ncid, int varid, nc_type* nc_typeid) { + nc_type var_type_id; + CHECK(nc_inq_vartype(ncid, varid, &var_type_id)); + return pfnc_complex_base_type(ncid, var_type_id, nc_typeid); +} + +/// Return true if a compound type is compatible with a known convention +bool compound_type_is_compatible(int ncid, nc_type nc_typeid) { + // Does the name matching a known convention? + char name[NC_MAX_NAME + 1]; + nc_inq_compound_name(ncid, nc_typeid, name); + if (name == double_complex_struct_name) { + return true; + } + + // Does it have exactly two fields? + size_t num_fields; + nc_inq_compound_nfields(ncid, nc_typeid, &num_fields); + if (num_fields != 2) { + return false; + } + + // As far as I can tell, all conventions put the real part first and + // the imaginary part second. I'm pretty sure all native language + // types are also this way round. That means we don't have to worry + // about trying both combinations! + char real_name[NC_MAX_NAME + 1]; + size_t real_offset; + nc_type real_field_type; + int real_rank; + nc_inq_compound_field( + ncid, nc_typeid, 0, real_name, &real_offset, &real_field_type, &real_rank, NULL + ); + + // If it's not a floating type, we're not interested + if (!(real_field_type == NC_FLOAT || real_field_type == NC_DOUBLE)) { + return false; + } + // Also needs to be scalar + if (real_rank != 0) { + return false; + } + + // Now check names. For now, just check it starts with "r", in any case + if (tolower(real_name[0]) != 'r') { + return false; + } + + char imag_name[NC_MAX_NAME + 1]; + size_t imag_offset; + nc_type imag_field_type; + int imag_rank; + nc_inq_compound_field( + ncid, nc_typeid, 1, imag_name, &imag_offset, &imag_field_type, &imag_rank, NULL + ); + + // Both component types better match + if (imag_field_type != real_field_type) { + return false; + } + if (imag_rank != 0) { + return false; + } + if (tolower(imag_name[0]) != 'i') { + return false; + } + + return true; +} + +/// Return true if file already has a complex type with the given base type +bool file_has_complex_struct(int ncid, nc_type* typeidp, nc_type base_type) { + // Simplest case, check for our type name + int err = nc_inq_typeid(ncid, double_complex_struct_name, typeidp); + if (err == NC_NOERR) { + return true; + } + + int ntypes; + err = nc_inq_typeids(ncid, &ntypes, NULL); + if (err != NC_NOERR) { + return false; + } + + bool result = false; + + nc_type* typeids = malloc((size_t)ntypes * sizeof(nc_type)); + err = nc_inq_typeids(ncid, NULL, typeids); + if (err != NC_NOERR) { + goto cleanup; + } + + for (size_t i = 0; i < (size_t)ntypes; i++) { + if (compound_type_is_compatible(ncid, typeids[i])) { + nc_type base_type_id; + err = pfnc_complex_base_type(ncid, typeids[i], &base_type_id); + if (err != NC_NOERR) { + goto cleanup; + } + if (base_type_id == base_type) { + *typeidp = typeids[i]; + result = true; + goto cleanup; + } + } + } +cleanup: + free(typeids); + return result; +} + +/// Return true if a given dimension matches a known convention +bool pfnc_is_complex_dim(int ncid, int dim_id) { + size_t length; + nc_inq_dimlen(ncid, dim_id, &length); + + // Definitely can only be exactly two. Note that we can't catch + // unlimited dimensions that only have two records so far. + if (length != 2) { + return false; + } + + // Not sure if this is the best way, but here we are. + char name[NC_MAX_NAME + 1]; + nc_inq_dimname(ncid, dim_id, name); + + const size_t name_length = strlen(name); + + // Check against known names of complex dimensions + for (size_t i = 0; i < num_known_dim_names; i++) { + if (strncmp(name, known_dim_names[i], name_length) == 0) { + return true; + } + } + + return false; +} + +/// Return true if a variable uses the dimension-convention +bool pfnc_var_has_complex_dimension(int ncid, int nc_varid) { + int num_dims; + nc_inq_varndims(ncid, nc_varid, &num_dims); + + int* dim_ids = (int*)malloc((size_t)num_dims * sizeof(int)); + nc_inq_vardimid(ncid, nc_varid, dim_ids); + + // Now we check if any of the dimensions match one of our known + // conventions. Do we need to check all of them, or just the + // first/last? + for (int i = 0; i < num_dims; i++) { + if (pfnc_is_complex_dim(ncid, dim_ids[i])) { + free(dim_ids); + return true; + } + } + + free(dim_ids); + return false; +} + +/// Return true if a netCDF datatype is a compound type +bool is_compound_type(int ncid, int type_id) { + // There appears to be no API for detecting whether a type ID is a + // primitive type, so we have to check ourselves + if (type_id <= NC_MAX_ATOMIC_TYPE) { + return false; + } + + int class_type; + nc_inq_user_type(ncid, type_id, NULL, NULL, NULL, NULL, &class_type); + return class_type == NC_COMPOUND; +} + +/// Copy an array meant for a complex-dimensioned variable +size_t* copy_complex_dim_size_t_array( + const size_t* old_array, int numdims, size_t complex_dim_value +) { + size_t* new_buffer = NULL; + + if (old_array != NULL) { + new_buffer = (size_t*)malloc(sizeof(size_t) * (size_t)numdims); + + size_t last_dim = (size_t)(numdims - 1); + for (size_t i = 0; i < last_dim; i++) { + new_buffer[i] = old_array[i]; + } + + new_buffer[last_dim] = complex_dim_value; + } + return new_buffer; +} + +ptrdiff_t* copy_complex_dim_ptrdiff_t_array( + const ptrdiff_t* old_array, int numdims, ptrdiff_t complex_dim_value +) { + ptrdiff_t* new_buffer = NULL; + + if (old_array != NULL) { + new_buffer = (ptrdiff_t*)malloc(sizeof(ptrdiff_t) * (size_t)numdims); + + size_t last_dim = (size_t)(numdims - 1); + for (size_t i = 0; i < last_dim; i++) { + new_buffer[i] = old_array[i]; + } + + new_buffer[last_dim] = complex_dim_value; + } + return new_buffer; +} + +bool pfnc_var_is_complex_type(int ncid, int varid) { + nc_type var_type_id; + if (nc_inq_vartype(ncid, varid, &var_type_id)) { + return false; + } + + if (is_compound_type(ncid, var_type_id)) { + return compound_type_is_compatible(ncid, var_type_id); + } + return false; +} + +size_t complex_type_size(nc_type base_type) { + switch (base_type) { + case NC_FLOAT: + return sizeof(float_complex); + case NC_DOUBLE: + return sizeof(double_complex); + default: + return 0; + } +} + +size_t base_type_size(nc_type base_type) { + switch (base_type) { + case NC_FLOAT: + return sizeof(float); + case NC_DOUBLE: + return sizeof(double); + default: + return 0; + } +} + +int get_or_make_complex_struct( + int ncid, nc_type* nc_typeid, nc_type base_type, const char* struct_name +) { + // TODO: Error if not netCDF4 + + if (file_has_complex_struct(ncid, nc_typeid, base_type)) { + return NC_NOERR; + } + + const size_t complex_size = complex_type_size(base_type); + if (complex_size == 0) { + return NC_EBADTYPE; + } + const size_t base_size = base_type_size(base_type); + if (base_size == 0) { + return NC_EBADTYPE; + } + + CHECK(nc_def_compound(ncid, complex_size, struct_name, nc_typeid)); + CHECK(nc_insert_compound(ncid, *nc_typeid, "r", 0, base_type)); + CHECK(nc_insert_compound(ncid, *nc_typeid, "i", base_size, base_type)); + + return NC_NOERR; +} + +int pfnc_get_double_complex_typeid(int ncid, nc_type* nc_typeid) { + return get_or_make_complex_struct( + ncid, nc_typeid, NC_DOUBLE, double_complex_struct_name + ); +} + +int pfnc_get_float_complex_typeid(int ncid, nc_type* nc_typeid) { + return get_or_make_complex_struct( + ncid, nc_typeid, NC_FLOAT, float_complex_struct_name + ); +} + +int pfnc_get_complex_dim(int ncid, int* nc_dim) { + int num_dims; + CHECK(nc_inq_ndims(ncid, &num_dims)); + + int* dim_ids = (int*)malloc((size_t)num_dims * sizeof(int)); + int ierr = nc_inq_dimids(ncid, NULL, dim_ids, true); + if (ierr != NC_NOERR) { + goto cleanup; + } + + // Now we check if any of the dimensions match one of our known + // conventions. Do we need to check all of them, or just the + // first/last? + for (int i = 0; i < num_dims; i++) { + if (pfnc_is_complex_dim(ncid, dim_ids[i])) { + *nc_dim = dim_ids[i]; + goto cleanup; + } + } + + ierr = nc_def_dim(ncid, complex_dim_name, 2, nc_dim); + +cleanup: + free(dim_ids); + return ierr; +} + +int pfnc_put_vara_double_complex( + int ncid, + int varid, + const size_t* startp, + const size_t* countp, + const double_complex* op +) { + return pfnc_put_vars_double_complex(ncid, varid, startp, countp, NULL, op); +} + +int pfnc_get_vara_double_complex( + int ncid, int varid, const size_t* startp, const size_t* countp, double_complex* ip +) { + return pfnc_get_vars_double_complex(ncid, varid, startp, countp, NULL, ip); +} + +int pfnc_put_vars_double_complex( + int ncid, + int varid, + const size_t* startp, + const size_t* countp, + const ptrdiff_t* stridep, + const double_complex* op +) { + if (!pfnc_var_is_complex(ncid, varid)) { + return NC_EBADTYPE; + } + + // TODO: handle converting different float sizes + + // Check if we can get away without fudging count/start sizes + if (((startp == NULL) && (countp == NULL) && (stridep == NULL)) + || !pfnc_var_has_complex_dimension(ncid, varid)) { + return nc_put_vars(ncid, varid, startp, countp, stridep, op); + } + + // The real variable has a complex dimension, but we're pretending + // it doesn't, so now we need start/count arrays of the real size + + int numdims = 0; + CHECK(nc_inq_varndims(ncid, varid, &numdims)); + + // Copy start/count buffers, appending an extra element for the + // complex dimension. This dimension starts at 0 and has 2 elements + size_t* start_buffer = copy_complex_dim_size_t_array(startp, numdims, 0); + size_t* count_buffer = copy_complex_dim_size_t_array(countp, numdims, 2); + ptrdiff_t* stride_buffer = copy_complex_dim_ptrdiff_t_array(stridep, numdims, 1); + + const int ierr = + nc_put_vars(ncid, varid, start_buffer, count_buffer, stride_buffer, op); + + if (start_buffer != NULL) { + free(start_buffer); + } + if (count_buffer != NULL) { + free(count_buffer); + } + if (stride_buffer != NULL) { + free(stride_buffer); + } + return ierr; +} + +int pfnc_get_vars_double_complex( + int ncid, + int varid, + const size_t* startp, + const size_t* countp, + const ptrdiff_t* stridep, + double_complex* ip +) { + if (!pfnc_var_is_complex(ncid, varid)) { + return NC_EBADTYPE; + } + + // TODO: handle converting different float sizes + + // Check if we can get away without fudging count/start sizes + if (((startp == NULL) && (countp == NULL) && (stridep == NULL)) + || !pfnc_var_has_complex_dimension(ncid, varid)) { + return nc_get_vars(ncid, varid, startp, countp, stridep, ip); + } + + // The real variable has a complex dimension, but we're pretending + // it doesn't, so now we need start/count arrays of the real size + + int numdims = 0; + CHECK(nc_inq_varndims(ncid, varid, &numdims)); + + // Copy start/count buffers, appending an extra element for the + // complex dimension. This dimension starts at 0 and has 2 elements + size_t* start_buffer = copy_complex_dim_size_t_array(startp, numdims, 0); + size_t* count_buffer = copy_complex_dim_size_t_array(countp, numdims, 2); + ptrdiff_t* stride_buffer = copy_complex_dim_ptrdiff_t_array(stridep, numdims, 1); + + const int ierr = + nc_get_vars(ncid, varid, start_buffer, count_buffer, stride_buffer, ip); + + if (start_buffer != NULL) { + free(start_buffer); + } + if (count_buffer != NULL) { + free(count_buffer); + } + if (stride_buffer != NULL) { + free(stride_buffer); + } + return ierr; +} + +int pfnc_put_var1_double_complex( + int ncid, int varid, const size_t* indexp, const double_complex* data +) { + return pfnc_put_vara_double_complex(ncid, varid, indexp, coord_one, data); +} + +int pfnc_get_var1_double_complex( + int ncid, int varid, const size_t* indexp, double_complex* data +) { + return pfnc_get_vara_double_complex(ncid, varid, indexp, coord_one, data); +} + +int pfnc_put_vara_float_complex( + int ncid, + int varid, + const size_t* startp, + const size_t* countp, + const float_complex* op +) { + return pfnc_put_vars_float_complex(ncid, varid, startp, countp, NULL, op); +} + +int pfnc_get_vara_float_complex( + int ncid, int varid, const size_t* startp, const size_t* countp, float_complex* ip +) { + return pfnc_get_vars_float_complex(ncid, varid, startp, countp, NULL, ip); +} + +int pfnc_put_vars_float_complex( + int ncid, + int varid, + const size_t* startp, + const size_t* countp, + const ptrdiff_t* stridep, + const float_complex* op +) { + if (!pfnc_var_is_complex(ncid, varid)) { + return NC_EBADTYPE; + } + + // TODO: handle converting different float sizes + + // Check if we can get away without fudging count/start sizes + if (((startp == NULL) && (countp == NULL) && (stridep == NULL)) + || !pfnc_var_has_complex_dimension(ncid, varid)) { + return nc_put_vars(ncid, varid, startp, countp, stridep, op); + } + + // The real variable has a complex dimension, but we're pretending + // it doesn't, so now we need start/count arrays of the real size + + int numdims = 0; + CHECK(nc_inq_varndims(ncid, varid, &numdims)); + + // Copy start/count buffers, appending an extra element for the + // complex dimension. This dimension starts at 0 and has 2 elements + size_t* start_buffer = copy_complex_dim_size_t_array(startp, numdims, 0); + size_t* count_buffer = copy_complex_dim_size_t_array(countp, numdims, 2); + ptrdiff_t* stride_buffer = copy_complex_dim_ptrdiff_t_array(stridep, numdims, 1); + + const int ierr = + nc_put_vars(ncid, varid, start_buffer, count_buffer, stride_buffer, op); + + if (start_buffer != NULL) { + free(start_buffer); + } + if (count_buffer != NULL) { + free(count_buffer); + } + if (stride_buffer != NULL) { + free(stride_buffer); + } + return ierr; +} + +int pfnc_get_vars_float_complex( + int ncid, + int varid, + const size_t* startp, + const size_t* countp, + const ptrdiff_t* stridep, + float_complex* ip +) { + if (!pfnc_var_is_complex(ncid, varid)) { + return NC_EBADTYPE; + } + + // TODO: handle converting different float sizes + + // Check if we can get away without fudging count/start sizes + if (((startp == NULL) && (countp == NULL) && (stridep == NULL)) + || !pfnc_var_has_complex_dimension(ncid, varid)) { + return nc_get_vars(ncid, varid, startp, countp, stridep, ip); + } + + // The real variable has a complex dimension, but we're pretending + // it doesn't, so now we need start/count arrays of the real size + + int numdims = 0; + CHECK(nc_inq_varndims(ncid, varid, &numdims)); + + // Copy start/count buffers, appending an extra element for the + // complex dimension. This dimension starts at 0 and has 2 elements + size_t* start_buffer = copy_complex_dim_size_t_array(startp, numdims, 0); + size_t* count_buffer = copy_complex_dim_size_t_array(countp, numdims, 2); + ptrdiff_t* stride_buffer = copy_complex_dim_ptrdiff_t_array(stridep, numdims, 1); + + const int ierr = + nc_get_vars(ncid, varid, start_buffer, count_buffer, stride_buffer, ip); + + if (start_buffer != NULL) { + free(start_buffer); + } + if (count_buffer != NULL) { + free(count_buffer); + } + if (stride_buffer != NULL) { + free(stride_buffer); + } + return ierr; +} + +int pfnc_put_var1_float_complex( + int ncid, int varid, const size_t* indexp, const float_complex* data +) { + return pfnc_put_vara_float_complex(ncid, varid, indexp, coord_one, data); +} + +int pfnc_get_var1_float_complex( + int ncid, int varid, const size_t* indexp, float_complex* data +) { + return pfnc_get_vara_float_complex(ncid, varid, indexp, coord_one, data); +} + +int pfnc_def_var( + int ncid, + const char* name, + nc_type xtype, + int ndims, + const int* dimidsp, + int* varidp +) { + // If it's not a complex number, we don't need to do anything + if (!(xtype == PFNC_DOUBLE_COMPLEX || xtype == PFNC_DOUBLE_COMPLEX_DIM + || xtype == PFNC_FLOAT_COMPLEX || xtype == PFNC_FLOAT_COMPLEX_DIM)) { + return nc_def_var(ncid, name, xtype, ndims, dimidsp, varidp); + } + + const bool base_is_double = + (xtype == PFNC_DOUBLE_COMPLEX || xtype == PFNC_DOUBLE_COMPLEX_DIM); + + // Check the format used by this file. If it's some variation on the + // classic model, then we have to use a complex dimension. Also, + // NcZarr, for some reason doesn't support compound types (yet?). + // I _think_ DAP supports compound types + int format = 0; + int mode = 0; + CHECK(nc_inq_format_extended(ncid, &format, &mode)); + + if ((format == NC_FORMAT_CLASSIC || format == NC_FORMAT_NETCDF4_CLASSIC) + || (mode == NC_FORMATX_NCZARR)) { + xtype = base_is_double ? PFNC_DOUBLE_COMPLEX_DIM : PFNC_FLOAT_COMPLEX_DIM; + } + + if (xtype == PFNC_DOUBLE_COMPLEX_DIM || xtype == PFNC_FLOAT_COMPLEX_DIM) { + // Using a complex dimension. We need to get the complex dimension + // used in this file and append it to the list of dimensions + // passed in by the user + + int complex_dim = 0; + CHECK(pfnc_get_complex_dim(ncid, &complex_dim)); + + int new_dims = ndims + 1; + int* dim_ids_buffer = (int*)malloc((size_t)new_dims * sizeof(int)); + for (size_t i = 0; i < (size_t)ndims; i++) { + dim_ids_buffer[i] = dimidsp[i]; + } + dim_ids_buffer[ndims] = complex_dim; + + const nc_type base_type = base_is_double ? NC_DOUBLE : NC_FLOAT; + + const int ierr = + nc_def_var(ncid, name, base_type, new_dims, dim_ids_buffer, varidp); + free(dim_ids_buffer); + return ierr; + } + + // Using a complex type. We need to get the complex type used in + // this file and pass that as `xtype` + nc_type complex_type = 0; + if (base_is_double) { + CHECK(pfnc_get_double_complex_typeid(ncid, &complex_type)); + } else { + CHECK(pfnc_get_float_complex_typeid(ncid, &complex_type)); + } + + return nc_def_var(ncid, name, complex_type, ndims, dimidsp, varidp); +} + +int pfnc_inq_var( + int ncid, + int varid, + char* name, + nc_type* xtypep, + int* ndimsp, + int* dimidsp, + int* nattsp +) { + if (!pfnc_var_has_complex_dimension(ncid, varid)) { + return nc_inq_var(ncid, varid, name, xtypep, ndimsp, dimidsp, nattsp); + } + + // Tricky bit: if variable has complex dimension, and user used + // pfnc_inq_varndims, then dimidsp is one smaller than netCDF thinks + // it should be. So we'll have to allocate our own array of the + // correct size and copy out of that. + + // This buffer will point to either the user's array, or our own one + int* buffer = dimidsp; + int numdims = 0; + + if (dimidsp != NULL) { + CHECK(nc_inq_varndims(ncid, varid, &numdims)); + buffer = (int*)malloc(sizeof(int) * (size_t)numdims); + } + + int ierr = nc_inq_var(ncid, varid, name, xtypep, &numdims, buffer, nattsp); + + if (ierr != NC_NOERR) { + goto cleanup; + } + + if (dimidsp != NULL) { + if (numdims <= 0) { + // This should never happen + goto cleanup; + } + const size_t other_dims = (size_t)(numdims - 1); + for (size_t i = 0; i < other_dims; i++) { + dimidsp[i] = buffer[i]; + } + } + + if (ndimsp != NULL) { + *ndimsp = numdims - 1; + } + +cleanup: + free(buffer); + return ierr; +} + +int pfnc_def_var_chunking(int ncid, int varid, int storage, const size_t* chunksizesp) { + if (chunksizesp == NULL || !pfnc_var_has_complex_dimension(ncid, varid)) { + return nc_def_var_chunking(ncid, varid, storage, chunksizesp); + } + + // The real variable has a complex dimension, but we're pretending + // it doesn't, so now we need start/count arrays of the real size + + int numdims = 0; + CHECK(nc_inq_varndims(ncid, varid, &numdims)); + + // Copy chunksize buffer, appending an extra element for the + // complex dimension + size_t* chunk_buffer = copy_complex_dim_size_t_array(chunksizesp, numdims, 2); + + const int ierr = nc_def_var_chunking(ncid, varid, storage, chunk_buffer); + free(chunk_buffer); + return ierr; +} + +int pfnc_inq_var_chunking(int ncid, int varid, int* storagep, size_t* chunksizesp) { + if (chunksizesp == NULL || !pfnc_var_has_complex_dimension(ncid, varid)) { + return nc_inq_var_chunking(ncid, varid, storagep, chunksizesp); + } + + int numdims = 0; + + CHECK(nc_inq_varndims(ncid, varid, &numdims)); + + // Copy chunksize buffer, appending an extra element for the + // complex dimension + size_t* chunk_buffer = copy_complex_dim_size_t_array(chunksizesp, numdims, 2); + + const int ierr = nc_inq_var_chunking(ncid, varid, storagep, chunk_buffer); + + if (ierr != NC_NOERR) { + goto cleanup; + } + + const size_t other_dims = (size_t)(numdims - 1); + for (size_t i = 0; i < other_dims; i++) { + chunksizesp[i] = chunk_buffer[i]; + } + +cleanup: + free(chunk_buffer); + return ierr; +} + +int pfnc_get_vara( + int ncid, int varid, const size_t* startp, const size_t* countp, void* ip +) { + if (pfnc_var_is_complex(ncid, varid)) { + nc_type base_type; + CHECK(pfnc_inq_var_complex_base_type(ncid, varid, &base_type)); + switch (base_type) { + case NC_DOUBLE: + return pfnc_get_vara_double_complex(ncid, varid, startp, countp, ip); + case NC_FLOAT: + return pfnc_get_vara_float_complex(ncid, varid, startp, countp, ip); + default: + return NC_EBADTYPE; + } + } + + return nc_get_vara(ncid, varid, startp, countp, ip); +} + +int pfnc_put_vara( + int ncid, int varid, const size_t* startp, const size_t* countp, const void* op +) { + if (pfnc_var_is_complex(ncid, varid)) { + nc_type base_type; + CHECK(pfnc_inq_var_complex_base_type(ncid, varid, &base_type)); + switch (base_type) { + case NC_DOUBLE: + return pfnc_put_vara_double_complex(ncid, varid, startp, countp, op); + case NC_FLOAT: + return pfnc_put_vara_float_complex(ncid, varid, startp, countp, op); + default: + return NC_EBADTYPE; + } + } + return nc_put_vara(ncid, varid, startp, countp, op); +} + +int pfnc_put_vars( + int ncid, + int varid, + const size_t* startp, + const size_t* countp, + const ptrdiff_t* stridep, + const void* op +) { + if (pfnc_var_is_complex(ncid, varid)) { + nc_type base_type; + CHECK(pfnc_inq_var_complex_base_type(ncid, varid, &base_type)); + switch (base_type) { + case NC_DOUBLE: + return pfnc_put_vars_double_complex( + ncid, varid, startp, countp, stridep, op + ); + case NC_FLOAT: + return pfnc_put_vars_float_complex( + ncid, varid, startp, countp, stridep, op + ); + default: + return NC_EBADTYPE; + } + } + return nc_put_vars(ncid, varid, startp, countp, stridep, op); +} + +int pfnc_get_vars( + int ncid, + int varid, + const size_t* startp, + const size_t* countp, + const ptrdiff_t* stridep, + void* ip +) { + if (pfnc_var_is_complex(ncid, varid)) { + nc_type base_type; + CHECK(pfnc_inq_var_complex_base_type(ncid, varid, &base_type)); + switch (base_type) { + case NC_DOUBLE: + return pfnc_get_vars_double_complex( + ncid, varid, startp, countp, stridep, ip + ); + case NC_FLOAT: + return pfnc_get_vars_float_complex( + ncid, varid, startp, countp, stridep, ip + ); + default: + return NC_EBADTYPE; + } + } + return nc_get_vars(ncid, varid, startp, countp, stridep, ip); +} From da8fc8696057a234f77653831e5b760f62a04881 Mon Sep 17 00:00:00 2001 From: jswhit Date: Fri, 14 Jun 2024 12:30:07 -0600 Subject: [PATCH 1133/1504] update --- Changelog | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Changelog b/Changelog index 5f068df80..ddf5451c5 100644 --- a/Changelog +++ b/Changelog @@ -1,6 +1,6 @@ version 1.7.1 (tag v1.7.1rel) =============================== - * include nc_complex source code (instead of using submodule). + * include nc_complex source code from v0.2.0 tag (instead of using submodule). * add aarch64 wheels. version 1.7.0 (tag v1.7.0rel) From 8d62540660a2d16bae5dc5ddc0fe46ed18f9c117 Mon Sep 17 00:00:00 2001 From: jswhit Date: Fri, 14 Jun 2024 12:48:49 -0600 Subject: [PATCH 1134/1504] include nc_complex stuff, fix from PR #1336 --- MANIFEST.in | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/MANIFEST.in b/MANIFEST.in index e3497466e..0eec8242f 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -1,5 +1,6 @@ include docs/index.html recursive-include man * +recursive-include external * include MANIFEST.in include README.htmldocs include Changelog @@ -17,6 +18,9 @@ include src/netCDF4/plugins/empty.txt include include/netCDF4.pxi include include/mpi-compat.h include include/membuf.pyx +include include/netcdf-compat.h +include include/no_parallel_support_imports.pxi.in +include include/parallel_support_imports.pxi.in include *.md include *.py include *.release From 24c0e7c86ef37cbecdba3d5c53bbf6bad3ad51b8 Mon Sep 17 00:00:00 2001 From: jswhit Date: Fri, 14 Jun 2024 14:44:47 -0600 Subject: [PATCH 1135/1504] enable setuptools_scm --- pyproject.toml | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index fc24775e6..3ec2da2de 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -3,7 +3,7 @@ requires = [ "Cython>=0.29", "oldest-supported-numpy ; python_version < '3.9'", "numpy>=2.0.0rc1 ; python_version >= '3.9'", - "setuptools>=61", + "setuptools>=61", "setuptools_scm[toml]>=3.4" ] build-backend = "setuptools.build_meta" @@ -75,3 +75,5 @@ where = ["src"] [tool.pytest.ini_options] pythonpath = ["test"] + +[tool.setuptools_scm] From 1a32bff4a284f921111e186b335c9cec188a676b Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Sun, 16 Jun 2024 07:10:21 -0600 Subject: [PATCH 1136/1504] include provenance --- external/README | 1 + 1 file changed, 1 insertion(+) create mode 100644 external/README diff --git a/external/README b/external/README new file mode 100644 index 000000000..900a8c32f --- /dev/null +++ b/external/README @@ -0,0 +1 @@ +* 20240616: remove submodule, include v0.2.0 tag source files (https://github.com/PlasmaFAIR/nc-complex/releases/tag/v0.2.0). From 453516c04fdebee31724fa270e1c6aa0a559c77c Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Fri, 14 Jun 2024 08:32:33 +0200 Subject: [PATCH 1137/1504] ship sdist with submodules --- .github/workflows/cibuildwheel.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index c51e3b668..d3b9c1135 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -21,6 +21,7 @@ jobs: - uses: actions/checkout@v4 with: fetch-depth: 0 + submodules: 'true' - uses: actions/setup-python@v4 name: Install Python From b1fadf839b171b9821161492c5a7c988004b5545 Mon Sep 17 00:00:00 2001 From: Filipe Date: Sat, 15 Jun 2024 08:50:12 +0200 Subject: [PATCH 1138/1504] remove submodules init --- .github/workflows/cibuildwheel.yml | 3 --- 1 file changed, 3 deletions(-) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index d3b9c1135..1bea584b0 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -21,7 +21,6 @@ jobs: - uses: actions/checkout@v4 with: fetch-depth: 0 - submodules: 'true' - uses: actions/setup-python@v4 name: Install Python @@ -69,7 +68,6 @@ jobs: - uses: actions/checkout@v4 with: fetch-depth: 0 - submodules: 'true' # For aarch64 support # https://cibuildwheel.pypa.io/en/stable/faq/#emulation @@ -130,7 +128,6 @@ jobs: - uses: actions/checkout@v4 with: fetch-depth: 0 - submodules: 'true' - uses: actions/setup-python@v4 name: Install Python From 4fa8ee12f950eec6379d22a550787376c1519ca3 Mon Sep 17 00:00:00 2001 From: Jeffrey S Whitaker Date: Mon, 17 Jun 2024 18:35:19 -0500 Subject: [PATCH 1139/1504] include correct version info --- .../include/generated_fallbacks/nc_complex_version.h | 10 ++++------ 1 file changed, 4 insertions(+), 6 deletions(-) diff --git a/external/nc_complex/include/generated_fallbacks/nc_complex_version.h b/external/nc_complex/include/generated_fallbacks/nc_complex_version.h index 7a135743b..1dc040843 100644 --- a/external/nc_complex/include/generated_fallbacks/nc_complex_version.h +++ b/external/nc_complex/include/generated_fallbacks/nc_complex_version.h @@ -1,6 +1,4 @@ -// This is a fallback header for when building the library without -// CMake -- you probably should use CMake to auto-generate this instead -#define NC_COMPLEX_GIT_SHA1 "unknown" -#define NC_COMPLEX_GIT_VERSION "0.1.0" -#define NC_COMPLEX_GIT_STATE "unknown" -#define NC_COMPLEX_GIT_DATE "unknown" +#define NC_COMPLEX_GIT_SHA1 "37310ed00f3910974bdefefcdfa4787588651f59" +#define NC_COMPLEX_GIT_VERSION "v0.2.0" +#define NC_COMPLEX_GIT_STATE "clean" +#define NC_COMPLEX_GIT_DATE "2023-12-08" From 752ae621bd90b88b89e0d5edcf841bf5ae32139d Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Tue, 18 Jun 2024 00:07:59 +0000 Subject: [PATCH 1140/1504] Bump actions/setup-python from 4 to 5 Bumps [actions/setup-python](https://github.com/actions/setup-python) from 4 to 5. - [Release notes](https://github.com/actions/setup-python/releases) - [Commits](https://github.com/actions/setup-python/compare/v4...v5) --- updated-dependencies: - dependency-name: actions/setup-python dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- .github/workflows/cibuildwheel.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 1bea584b0..352a4b488 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -22,7 +22,7 @@ jobs: with: fetch-depth: 0 - - uses: actions/setup-python@v4 + - uses: actions/setup-python@v5 name: Install Python with: python-version: 3.x @@ -129,7 +129,7 @@ jobs: with: fetch-depth: 0 - - uses: actions/setup-python@v4 + - uses: actions/setup-python@v5 name: Install Python with: python-version: 3.x From 4a5161d4e9a6f00797dd248d013994b851b622e4 Mon Sep 17 00:00:00 2001 From: Jeffrey S Whitaker Date: Mon, 17 Jun 2024 19:09:49 -0500 Subject: [PATCH 1141/1504] update --- README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/README.md b/README.md index 6f9e720a1..59cf74311 100644 --- a/README.md +++ b/README.md @@ -10,6 +10,8 @@ ## News For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog). +06/17/2024: Version [1.7.1](https://pypi.python.org/pypi/netCDF4/1.7.1) released. Fixes for wheels, no code changes. + 06/13/2024: Version [1.7.0](https://pypi.python.org/pypi/netCDF4/1.7.0) released. Add support for complex numbers via `auto_complex` keyword to `Dataset` ([PR #1295](https://github.com/Unidata/netcdf4-python/pull/1295)) 10/20/2023: Version [1.6.5](https://pypi.python.org/pypi/netCDF4/1.6.5) released. From 95dd776e1a6eb62b9f383fd0bb99bfb327fb0593 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Tue, 18 Jun 2024 09:21:57 +0200 Subject: [PATCH 1142/1504] Group dependabot's PRs --- .github/dependabot.yml | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/.github/dependabot.yml b/.github/dependabot.yml index 563dd9bc7..7818bef34 100644 --- a/.github/dependabot.yml +++ b/.github/dependabot.yml @@ -9,3 +9,7 @@ updates: interval: "daily" labels: - "Bot" + groups: + github-actions: + patterns: + - '*' From b2e0b766e78d4e6cef713eb8ede1ee81aec20e1f Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Tue, 18 Jun 2024 09:22:31 +0200 Subject: [PATCH 1143/1504] np2 was released --- .github/workflows/miniconda.yml | 14 -------------- 1 file changed, 14 deletions(-) diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index a7493a01f..256579c70 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -14,16 +14,10 @@ jobs: matrix: python-version: [ "3.9", "3.10", "3.11", "3.12" ] os: [windows-latest, ubuntu-latest, macos-latest] - experimental: [false] platform: [x64, x32] exclude: - os: macos-latest platform: x32 - include: - - python-version: "3.12" - os: "ubuntu-latest" - experimental: true - platform: x64 fail-fast: false defaults: run: @@ -44,14 +38,6 @@ jobs: numpy cython pip pytest hdf5 libnetcdf cftime zlib certifi --channel conda-forge - - name: Install unstable dependencies - if: matrix.experimental == true - run: >- - micromamba install - conda-forge/label/cftime_dev::cftime - conda-forge/label/numpy_dev::numpy - --channel conda-forge --channel conda-forge - - name: Install netcdf4-python run: | export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config From fd0b2b3b987a7287bd81ecc5012a7c7994442397 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Tue, 18 Jun 2024 11:10:56 +0200 Subject: [PATCH 1144/1504] fix download-artifact --- .github/workflows/cibuildwheel.yml | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 1bea584b0..6a7206e72 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -191,10 +191,11 @@ jobs: # upload to PyPI for every tag starting with 'v' if: github.event_name == 'push' && startsWith(github.event.ref, 'refs/tags/v') steps: - - uses: actions/download-artifact@v3 + - uses: actions/download-artifact@v4 with: - name: pypi-artifacts + pattern: pypi-artifacts* path: ${{ github.workspace }}/dist + merge-multiple: true - uses: pypa/gh-action-pypi-publish@release/v1 with: From b616b93ade4c38c8767349ae557e6fcc9c627e18 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Wed, 19 Jun 2024 21:34:55 +0200 Subject: [PATCH 1145/1504] fix mpi_example --- examples/mpi_example.py | 22 +++++++++++++++++----- 1 file changed, 17 insertions(+), 5 deletions(-) diff --git a/examples/mpi_example.py b/examples/mpi_example.py index 653f25781..7966bdafe 100644 --- a/examples/mpi_example.py +++ b/examples/mpi_example.py @@ -1,38 +1,50 @@ # to run: mpirun -np 4 python mpi_example.py import sys +from typing import Literal from mpi4py import MPI import numpy as np -from netCDF4 import Dataset, FormatOptions +from netCDF4 import Dataset -format: FormatOptions +format: Literal[ + 'NETCDF4', + 'NETCDF4_CLASSIC', + 'NETCDF3_CLASSIC', + 'NETCDF3_64BIT_OFFSET', + 'NETCDF3_64BIT_DATA' +] if len(sys.argv) == 2: format = sys.argv[1] # type: ignore else: format = 'NETCDF4_CLASSIC' + rank = MPI.COMM_WORLD.rank # The process ID (integer 0-3 for 4-process run) if rank == 0: - print('Creating file with format {}'.format(format)) + print('Creating file with format {}'.format(format)) nc = Dataset('parallel_test.nc', 'w', parallel=True, comm=MPI.COMM_WORLD, - info=MPI.Info(),format=format) + info=MPI.Info(), format=format) # below should work also - MPI_COMM_WORLD and MPI_INFO_NULL will be used. #nc = Dataset('parallel_test.nc', 'w', parallel=True) d = nc.createDimension('dim',4) v = nc.createVariable('var', np.int32, 'dim') v[rank] = rank + # switch to collective mode, rewrite the data. v.set_collective(True) v[rank] = rank nc.close() + # reopen the file read-only, check the data nc = Dataset('parallel_test.nc', parallel=True, comm=MPI.COMM_WORLD, info=MPI.Info()) assert rank==nc['var'][rank] nc.close() + # reopen the file in append mode, modify the data on the last rank. nc = Dataset('parallel_test.nc', 'a',parallel=True, comm=MPI.COMM_WORLD, - info=MPI.Info()) + info=MPI.Info()) if rank == 3: v[rank] = 2*rank nc.close() + # reopen the file read-only again, check the data. # leave out the comm and info kwargs to check that the defaults # (MPI_COMM_WORLD and MPI_INFO_NULL) work. From 08a6a69e0d16fb7428b6ccd2debbbe003d525627 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Wed, 19 Jun 2024 21:41:53 +0200 Subject: [PATCH 1146/1504] fix changelog --- Changelog | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/Changelog b/Changelog index 21c4a6d63..1b1157406 100644 --- a/Changelog +++ b/Changelog @@ -1,3 +1,7 @@ + version 1.7.2 (tag v1.7.2rel) +=============================== + * add static type hints (PR #1302) + version 1.7.1 (tag v1.7.1rel) =============================== * include nc_complex source code from v0.2.0 tag (instead of using submodule). @@ -10,7 +14,6 @@ with shims for unavailable functionality (PR #1277) * use `szip` as the library name on Windows (PR #1304) * add support for MS-MPI `MPI_Message` detection (PR #1305) - * add static type hints (PR #1302) * fix for issue #1306 - surprising result when indexing vlen str with non-contiguous indices. * Fix bug in set_collective introduced in PR #1277 (collective mode was From e8ee7a81c99d7ae2e5f941e502ee976915607539 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Thu, 20 Jun 2024 21:12:23 +0200 Subject: [PATCH 1147/1504] add stubs to manifest --- MANIFEST.in | 2 ++ 1 file changed, 2 insertions(+) diff --git a/MANIFEST.in b/MANIFEST.in index 0eec8242f..2b010c5ee 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -15,6 +15,7 @@ include src/netCDF4/_netCDF4.pyx exclude src/netCDF4/_netCDF4.c include src/netCDF4/utils.py include src/netCDF4/plugins/empty.txt +include src/netCDF4/py.typed include include/netCDF4.pxi include include/mpi-compat.h include include/membuf.pyx @@ -23,6 +24,7 @@ include include/no_parallel_support_imports.pxi.in include include/parallel_support_imports.pxi.in include *.md include *.py +include *.pyi include *.release include *.sh include LICENSE From a192f68ec706fb8bb78e7c6aec533bdc7d2b900e Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Thu, 20 Jun 2024 21:21:38 +0200 Subject: [PATCH 1148/1504] tiny docs fix --- docs/index.html | 4 ++-- src/netCDF4/_netCDF4.pyx | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/docs/index.html b/docs/index.html index 6971ceb5b..8191c3314 100644 --- a/docs/index.html +++ b/docs/index.html @@ -118,8 +118,8 @@

      Creating/Opening/Closing a netCDF If the file is open for write access (mode='w', 'r+' or 'a'), you may write any type of data including new dimensions, groups, variables and attributes. -netCDF files come in five flavors (NETCDF3_CLASSIC, -NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF4_CLASSIC<code>, and </code>NETCDF4). +netCDF files come in five flavors (NETCDF3_CLASSIC, +NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF4_CLASSIC, and NETCDF4). NETCDF3_CLASSIC was the original netcdf binary format, and was limited to file sizes less than 2 Gb. NETCDF3_64BIT_OFFSET was introduced in version 3.6.0 of the library, and extended the original binary format diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 631a2726e..4207642d9 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -95,8 +95,8 @@ To create a netCDF file from python, you simply call the `Dataset` constructor. This is also the method used to open an existing netCDF file. If the file is open for write access (`mode='w', 'r+'` or `'a'`), you may write any type of data including new dimensions, groups, variables and -attributes. netCDF files come in five flavors (`NETCDF3_CLASSIC, -NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF4_CLASSIC`, and `NETCDF4`). +attributes. netCDF files come in five flavors (`NETCDF3_CLASSIC`, +`NETCDF3_64BIT_OFFSET`, `NETCDF3_64BIT_DATA`, `NETCDF4_CLASSIC`, and `NETCDF4`). `NETCDF3_CLASSIC` was the original netcdf binary format, and was limited to file sizes less than 2 Gb. `NETCDF3_64BIT_OFFSET` was introduced in version 3.6.0 of the library, and extended the original binary format From c531ba8c9b275b8781731c18c6a582f208cf6751 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Thu, 20 Jun 2024 21:36:37 +0200 Subject: [PATCH 1149/1504] fix return type of tocdl --- src/netCDF4/__init__.pyi | 13 +++++++++++-- 1 file changed, 11 insertions(+), 2 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 384091609..6a6ee1bea 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -217,12 +217,21 @@ class Dataset: mode: AccessModeOptions = 'a', format: FormatOptions = 'NETCDF4' ) -> Dataset: ... + @overload def tocdl( self, coordvars: bool = False, data: bool = False, - outfile: str | None = None - ) -> None | bool: ... + outfile: None = None + ) -> str: ... + @overload + def tocdl( + self, + coordvars: bool = False, + data: bool = False, + *, + outfile: str + ) -> None: ... def has_blosc_filter(self) -> bool: ... def has_zstd_filter(self) -> bool: ... From f819d44e7291538992cc3538b58f8f9cf648b4a3 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Thu, 20 Jun 2024 21:40:22 +0200 Subject: [PATCH 1150/1504] sort imports --- src/netCDF4/__init__.pyi | 20 ++++---------------- 1 file changed, 4 insertions(+), 16 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 6a6ee1bea..478bea0b9 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -1,24 +1,12 @@ import os -from typing import ( - TypeAlias, - Literal, - Any, - NoReturn, - Iterable, - Mapping, - Union, - Sequence, - TypeVar, - Generic, - overload -) +from typing import (Any, Generic, Iterable, Literal, Mapping, NoReturn, Self, + Sequence, TypeAlias, TypeVar, Union, overload) -from typing_extensions import Buffer - -from cftime import num2date, date2num, date2index import numpy as np import numpy.typing as npt +from cftime import date2index, date2num, num2date +from typing_extensions import Buffer __all__ = [ 'Dataset', 'Variable', 'Dimension', 'Group', 'MFDataset', 'MFTime', 'CompoundType', From 558a31f497b4b74971851b27aa832e37c80b6967 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Thu, 20 Jun 2024 21:51:31 +0200 Subject: [PATCH 1151/1504] fix some more types --- src/netCDF4/__init__.pyi | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 478bea0b9..ca273f3fb 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -1,7 +1,7 @@ import os -from typing import (Any, Generic, Iterable, Literal, Mapping, NoReturn, Self, - Sequence, TypeAlias, TypeVar, Union, overload) +from typing import (Any, Callable, Generic, Iterable, Literal, Mapping, NoReturn, + Self, Sequence, TypeAlias, TypeVar, Union, overload) import numpy as np import numpy.typing as npt @@ -196,7 +196,7 @@ class Dataset: def set_auto_scale(self, value: bool) -> None: ... def set_always_mask(self, value: bool) -> None: ... def set_ncstring_attrs(self, value: bool) -> None: ... - def get_variables_by_attributes(self, **kwargs: Any) -> list[Variable]: ... + def get_variables_by_attributes(self, **kwargs: Callable[[Any], bool] | Any) -> list[Variable]: ... @staticmethod def fromcdl( @@ -232,8 +232,8 @@ class Dataset: def __delattr__(self, name: str): ... def __dealloc(self) -> None: ... def __reduce__(self) -> NoReturn: ... - def __enter__(self) -> Dataset: ... - def __exit__(self, atype, value, traceback) -> bool: ... + def __enter__(self) -> Self: ... + def __exit__(self, atype, value, traceback) -> None: ... def __str__(self) -> str: ... def __repr__(self) -> str: ... From 1974c707d03b3c446523c906ca7d270c6668f3ff Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Thu, 20 Jun 2024 22:30:29 +0200 Subject: [PATCH 1152/1504] add forgotten attrs for MFDataset --- .github/stubtest-allowlist | 1 + src/netCDF4/__init__.pyi | 69 +++++++++++++++++++++++++++++--------- src/netCDF4/_netCDF4.pyx | 2 +- 3 files changed, 55 insertions(+), 17 deletions(-) diff --git a/.github/stubtest-allowlist b/.github/stubtest-allowlist index 07d967022..9f7d31fc4 100644 --- a/.github/stubtest-allowlist +++ b/.github/stubtest-allowlist @@ -7,6 +7,7 @@ netCDF4.DiskFormatOptions netCDF4.EndianOptions netCDF4.FormatOptions netCDF4.QuantizeOptions +netCDF4.CalendarOptions netCDF4.T_Datatype netCDF4.T_DatatypeNC netCDF4.Dataset.__dealloc diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index ca273f3fb..49dacf234 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -39,7 +39,10 @@ FormatOptions: TypeAlias = Literal[ DiskFormatOptions: TypeAlias = Literal['NETCDF3', 'HDF5', 'HDF4', 'PNETCDF', 'DAP2', 'DAP4', 'UNDEFINED'] QuantizeOptions: TypeAlias = Literal['BitGroom', 'BitRound', 'GranularBitRound'] EndianOptions: TypeAlias = Literal['native', 'little', 'big'] - +CalendarOptions: TypeAlias = Literal[ + 'standard', 'gregorian', 'proleptic_gregorian' 'noleap', + '365_day', '360_day', 'julian', 'all_leap', '366_day', None +] __version__: str __netcdf4libversion__: str @@ -459,33 +462,67 @@ class MFDataset(Dataset): master_file: str | os.PathLike | None = None ) -> None: ... + @property + def groups(self) -> dict[str, Group]: ... + @property + def dimensions(self) -> dict[str, Dimension]: ... + @property + def variables(self) -> dict[str, Variable[Any]]: ... + @property + def data_model(self) -> FormatOptions: ... + @property + def file_format(self) -> FormatOptions: ... + @property + def disk_format(self) -> DiskFormatOptions: ... + @property + def path(self) -> str: ... + + +class _Dimension: + dimlens: list[str] + dimtolen: int + + def __init__( + self, dimname: str, dim: Dimension, dimlens: list[str], dimtotlen: int + ) -> None: ... + + def __len__(self) -> int: ... + def isunlimited(self) -> Literal[True]: ... + def __repr__(self) -> str: ... + class _Variable: - def __init__(self, dset, varname, var, recdimname): ... + dimensions: tuple[str, ...] + dtype: np.dtype + + def __init__(self, dset: Dataset, varname: str, var, recdimname: str) -> None: ... + + def typecode(self) -> np.dtype: ... + def ncattrs(self) -> list[str]: ... + def _shape(self) -> tuple[int, ...]: ... + def set_auto_chartostring(self, val: bool) -> None: ... + def set_auto_maskandscale(self, val: bool) -> None: ... + def set_auto_mask(self, val: bool) -> None: ... + def set_auto_scale(self, val: bool) -> None: ... + def set_always_mask(self, val: bool) -> None: ... def __getattr__(self, name): ... - def __repr__(self): ... - def __len__(self): ... def __getitem__(self, elem): ... - - def typecode(self): ... - def ncattrs(self): ... - def _shape(self): ... - def set_auto_chartostring(self, val): ... - def set_auto_maskandscale(self, val): ... - def set_auto_mask(self, val): ... - def set_auto_scale(self, val): ... - def set_always_mask(self, val): ... + def __len__(self) -> int: ... + def __repr__(self) -> str: ... class MFTime(_Variable): + calendar: CalendarOptions + units: str | None + def __init__( self, time: Variable, - units=None, - calendar: Literal['standard', 'gregorian'] | None = None + units: str | None = None, + calendar: CalendarOptions = None ): ... - def __getitem__(self, elem): ... + def __getitem__(self, elem: Any) -> np.ndarray: ... def stringtoarr(string, NUMCHARS: int, dtype: str = 'S') -> np.ndarray: ... diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 4207642d9..77e53bab6 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -7043,7 +7043,7 @@ class _Variable: def typecode(self): return self.dtype def ncattrs(self): - return self._mastervar.__dict__.keys() + return list(self._mastervar.__dict__.keys()) def __getattr__(self,name): if name == 'shape': return self._shape() if name == 'ndim': return len(self._shape()) From b884d69e73f980927a3554683cf1ba635b0fdd96 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Thu, 20 Jun 2024 22:48:44 +0200 Subject: [PATCH 1153/1504] fix some more types --- src/netCDF4/__init__.pyi | 20 +++++++++++--------- src/netCDF4/_netCDF4.pyx | 2 +- 2 files changed, 12 insertions(+), 10 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 49dacf234..61eef8a20 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -1,7 +1,7 @@ import os -from typing import (Any, Callable, Generic, Iterable, Literal, Mapping, NoReturn, - Self, Sequence, TypeAlias, TypeVar, Union, overload) +from typing import (Any, Callable, Final, Generic, Iterable, Literal, Mapping, + NoReturn, Self, Sequence, TypeAlias, TypeVar, Union, overload) import numpy as np import numpy.typing as npt @@ -65,8 +65,8 @@ __has_set_alignment__: bool __has_ncfilter__: bool is_native_little: bool is_native_big: bool -default_encoding: str -unicode_error: str +default_encoding: Final = 'utf-8' +unicode_error: Final = 'replace' default_fillvals: dict[str, Any] @@ -465,9 +465,9 @@ class MFDataset(Dataset): @property def groups(self) -> dict[str, Group]: ... @property - def dimensions(self) -> dict[str, Dimension]: ... + def dimensions(self) -> dict[str, Dimension]: ... # this should be: dict[str, Dimension | _Dimension] @property - def variables(self) -> dict[str, Variable[Any]]: ... + def variables(self) -> dict[str, Variable[Any]]: ... # this should be: dict[str, _Variable[Any] | _Variable] @property def data_model(self) -> FormatOptions: ... @property @@ -479,11 +479,11 @@ class MFDataset(Dataset): class _Dimension: - dimlens: list[str] + dimlens: list[int] dimtolen: int def __init__( - self, dimname: str, dim: Dimension, dimlens: list[str], dimtotlen: int + self, dimname: str, dim: Dimension, dimlens: list[int], dimtotlen: int ) -> None: ... def __len__(self) -> int: ... @@ -525,10 +525,12 @@ class MFTime(_Variable): def __getitem__(self, elem: Any) -> np.ndarray: ... -def stringtoarr(string, NUMCHARS: int, dtype: str = 'S') -> np.ndarray: ... +def stringtoarr(string, NUMCHARS: int, dtype: Literal['S', 'U'] = 'S') -> np.ndarray: ... def stringtochar(a, encoding: str | bytes | None = 'utf-8') -> np.ndarray: ... def chartostring(b, encoding: str | bytes | None = 'utf-8') -> np.ndarray: ... +def dtype_is_complex(dtype: str) -> bool: ... + def getlibversion() -> str: ... def set_alignment(threshold: int, alignment: int): ... diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 77e53bab6..a43a370b8 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2113,7 +2113,7 @@ def _ensure_nc_success(ierr, err_cls=RuntimeError, filename=None, extra_msg=None raise err_cls(err_str) -def dtype_is_complex(dtype: Union[str, numpy.dtype]) -> bool: +def dtype_is_complex(dtype): """Return True if dtype is a complex number""" return dtype in ("c8", "c16") From 826a5a9816352ab16c59aa67f6b5ed2b7700a361 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 21 Jun 2024 20:57:19 +0200 Subject: [PATCH 1154/1504] install types-setuptools in CI --- .github/workflows/build_master.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index 09d0f97ec..f8f841636 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -47,7 +47,7 @@ jobs: - name: Install python dependencies via pip run: | python -m pip install --upgrade pip - pip install numpy cython cftime pytest twine wheel check-manifest mpi4py mypy + pip install numpy cython cftime pytest twine wheel check-manifest mpi4py mypy types-setuptools - name: Install netcdf4-python run: | From cb4d011bcdf751e5ecee8a300c6ffd64f1631194 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 21 Jun 2024 21:02:15 +0200 Subject: [PATCH 1155/1504] import dunder vars in _netCDF4 --- src/netCDF4/_netCDF4.pyi | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/src/netCDF4/_netCDF4.pyi b/src/netCDF4/_netCDF4.pyi index 04d83376b..cfec62156 100644 --- a/src/netCDF4/_netCDF4.pyi +++ b/src/netCDF4/_netCDF4.pyi @@ -5,5 +5,12 @@ from . import ( VLType, date2num, num2date, date2index, stringtochar, chartostring, stringtoarr, getlibversion, EnumType, get_chunk_cache, set_chunk_cache, set_alignment, get_alignment, default_fillvals, default_encoding, - NetCDF4MissingFeatureException, is_native_big, is_native_little + NetCDF4MissingFeatureException, is_native_big, is_native_little, unicode_error, + __version__, __netcdf4libversion__, __hdf5libversion__, __has_rename_grp__, + __has_nc_inq_path__, __has_nc_inq_format_extended__, __has_nc_open_mem__, + __has_nc_create_mem__, __has_cdf5_format__, __has_parallel4_support__, + __has_pnetcdf_support__, __has_parallel_support__, + __has_quantization_support__, __has_zstandard_support__, + __has_bzip2_support__, __has_blosc_support__, __has_szip_support__, + __has_set_alignment__, __has_ncfilter__ ) \ No newline at end of file From 64140de74210152c04a12b0bae7f6df4d8fbcb0a Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 21 Jun 2024 21:14:34 +0200 Subject: [PATCH 1156/1504] remove dunder methods from allowlist --- .github/stubtest-allowlist | 19 ------------------- 1 file changed, 19 deletions(-) diff --git a/.github/stubtest-allowlist b/.github/stubtest-allowlist index 9f7d31fc4..e2d6bba1f 100644 --- a/.github/stubtest-allowlist +++ b/.github/stubtest-allowlist @@ -22,27 +22,8 @@ netCDF4._netCDF4.Dimension.__setstate_cython__ netCDF4._netCDF4.NC_DISKLESS netCDF4._netCDF4.NC_PERSIST netCDF4._netCDF4.Variable.auto_complex -netCDF4._netCDF4.__has_blosc_support__ -netCDF4._netCDF4.__has_bzip2_support__ -netCDF4._netCDF4.__has_cdf5_format__ -netCDF4._netCDF4.__has_nc_create_mem__ -netCDF4._netCDF4.__has_nc_inq_format_extended__ -netCDF4._netCDF4.__has_nc_inq_path__ -netCDF4._netCDF4.__has_nc_open_mem__ -netCDF4._netCDF4.__has_ncfilter__ -netCDF4._netCDF4.__has_parallel4_support__ -netCDF4._netCDF4.__has_parallel_support__ -netCDF4._netCDF4.__has_pnetcdf_support__ -netCDF4._netCDF4.__has_quantization_support__ -netCDF4._netCDF4.__has_rename_grp__ -netCDF4._netCDF4.__has_set_alignment__ -netCDF4._netCDF4.__has_szip_support__ -netCDF4._netCDF4.__has_zstandard_support__ -netCDF4._netCDF4.__hdf5libversion__ -netCDF4._netCDF4.__netcdf4libversion__ netCDF4._netCDF4.__reduce_cython__ netCDF4._netCDF4.__setstate_cython__ netCDF4._netCDF4.__test__ netCDF4._netCDF4.dtype_is_complex -netCDF4._netCDF4.unicode_error netCDF4.utils.bytes \ No newline at end of file From 89584e7a553b883de6a65a3c9ad88aa8865f10b4 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 21 Jun 2024 21:15:25 +0200 Subject: [PATCH 1157/1504] import __has_parallel_support__ and __has_ncfilter__ in __init__ --- .github/stubtest-allowlist | 2 -- src/netCDF4/__init__.py | 2 +- 2 files changed, 1 insertion(+), 3 deletions(-) diff --git a/.github/stubtest-allowlist b/.github/stubtest-allowlist index e2d6bba1f..dc353cdc2 100644 --- a/.github/stubtest-allowlist +++ b/.github/stubtest-allowlist @@ -14,8 +14,6 @@ netCDF4.Dataset.__dealloc netCDF4.Dimension.__reduce_cython__ netCDF4.Dimension.__setstate_cython__ netCDF4.Variable.auto_complex -netCDF4.__has_ncfilter__ -netCDF4.__has_parallel_support__ netCDF4._netCDF4.Dataset.__dealloc netCDF4._netCDF4.Dimension.__reduce_cython__ netCDF4._netCDF4.Dimension.__setstate_cython__ diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py index 91bf1ed03..25f6fad2e 100644 --- a/src/netCDF4/__init__.py +++ b/src/netCDF4/__init__.py @@ -10,7 +10,7 @@ __has_parallel4_support__, __has_pnetcdf_support__, __has_quantization_support__, __has_zstandard_support__, __has_bzip2_support__, __has_blosc_support__, __has_szip_support__, - __has_set_alignment__) + __has_set_alignment__, __has_parallel_support__, __has_ncfilter__) import os __all__ = [ 'Dataset', 'Variable', 'Dimension', 'Group', 'MFDataset', 'MFTime', 'CompoundType', From b1b9ecb7106f06baf88405109eafdbd6cf8878f9 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 21 Jun 2024 21:21:41 +0200 Subject: [PATCH 1158/1504] move dtype_is_complex to _netCDF4 --- .github/stubtest-allowlist | 1 - src/netCDF4/__init__.pyi | 2 -- src/netCDF4/_netCDF4.pyi | 5 ++++- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/.github/stubtest-allowlist b/.github/stubtest-allowlist index dc353cdc2..f53449917 100644 --- a/.github/stubtest-allowlist +++ b/.github/stubtest-allowlist @@ -23,5 +23,4 @@ netCDF4._netCDF4.Variable.auto_complex netCDF4._netCDF4.__reduce_cython__ netCDF4._netCDF4.__setstate_cython__ netCDF4._netCDF4.__test__ -netCDF4._netCDF4.dtype_is_complex netCDF4.utils.bytes \ No newline at end of file diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 61eef8a20..da958e61a 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -529,8 +529,6 @@ def stringtoarr(string, NUMCHARS: int, dtype: Literal['S', 'U'] = 'S') -> np.nda def stringtochar(a, encoding: str | bytes | None = 'utf-8') -> np.ndarray: ... def chartostring(b, encoding: str | bytes | None = 'utf-8') -> np.ndarray: ... -def dtype_is_complex(dtype: str) -> bool: ... - def getlibversion() -> str: ... def set_alignment(threshold: int, alignment: int): ... diff --git a/src/netCDF4/_netCDF4.pyi b/src/netCDF4/_netCDF4.pyi index cfec62156..536d4f63b 100644 --- a/src/netCDF4/_netCDF4.pyi +++ b/src/netCDF4/_netCDF4.pyi @@ -13,4 +13,7 @@ from . import ( __has_quantization_support__, __has_zstandard_support__, __has_bzip2_support__, __has_blosc_support__, __has_szip_support__, __has_set_alignment__, __has_ncfilter__ -) \ No newline at end of file +) + + +def dtype_is_complex(dtype: str) -> bool: ... From 553cf18ae424cfd11f76409ef2ea55121b9bc45e Mon Sep 17 00:00:00 2001 From: jswhit Date: Tue, 25 Jun 2024 11:05:41 -0600 Subject: [PATCH 1159/1504] bump version to 1.7.1.post1 --- src/netCDF4/_netCDF4.pyx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 8ef6a342f..49f62ee5c 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1272,7 +1272,7 @@ import sys import functools from typing import Union -__version__ = "1.7.1" +__version__ = "1.7.1.post1" # Initialize numpy import posixpath From dc8dcb6e7a758671f5d18629ed49b41a46628931 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Wed, 26 Jun 2024 21:17:34 +0200 Subject: [PATCH 1160/1504] apply some changes from review --- .github/stubtest-allowlist | 5 ++ src/netCDF4/__init__.pyi | 136 +++++++++++++++++++++++++++---------- 2 files changed, 106 insertions(+), 35 deletions(-) diff --git a/.github/stubtest-allowlist b/.github/stubtest-allowlist index f53449917..06862f1eb 100644 --- a/.github/stubtest-allowlist +++ b/.github/stubtest-allowlist @@ -8,6 +8,11 @@ netCDF4.EndianOptions netCDF4.FormatOptions netCDF4.QuantizeOptions netCDF4.CalendarOptions +netCDF4.ellipsis +netCDF4.DateTimeArray +netCDF4.FiltersDict +netCDF4.SzipInfo +netCDF4.BloscInfo netCDF4.T_Datatype netCDF4.T_DatatypeNC netCDF4.Dataset.__dealloc diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index da958e61a..abeef9169 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -1,12 +1,14 @@ import os +import sys +import datetime as dt from typing import (Any, Callable, Final, Generic, Iterable, Literal, Mapping, - NoReturn, Self, Sequence, TypeAlias, TypeVar, Union, overload) + NoReturn, Self, Sequence, TypeAlias, TypedDict, TypeVar, Union, overload) +from typing_extensions import Buffer +import cftime import numpy as np import numpy.typing as npt -from cftime import date2index, date2num, num2date -from typing_extensions import Buffer __all__ = [ 'Dataset', 'Variable', 'Dimension', 'Group', 'MFDataset', 'MFTime', 'CompoundType', @@ -16,6 +18,15 @@ __all__ = [ ] __pdoc__ = {'utils': False} + +if sys.version_info >= (3, 10): + from types import EllipsisType + + ellipsis = EllipsisType +elif not TYPE_CHECKING: + ellipsis = type(Ellipsis) # keeps ruff happy until ruff uses typeshed + + _DatatypeStrOptions: TypeAlias = Literal[ 'S1', 'c', 'i1', 'b', 'B', 'u1', 'i2', 'h', 's', 'u2', 'i4', 'i', 'l', 'u4', 'i8', 'u8', 'f4', 'f', 'f8', 'd', 'c8', 'c16' @@ -28,9 +39,9 @@ T_DatatypeNC = TypeVar("T_DatatypeNC", CompoundType, VLType, EnumType) DimensionsOptions: TypeAlias = Union[str, bytes, Dimension, Iterable[Union[str, bytes, Dimension]]] CompressionOptions: TypeAlias = Literal[ 'zlib', 'szip', 'zstd', 'blosc_lz','blosc_lz4', - 'blosc_lz4hc', 'blosc_zlib', 'blosc_zstd', None + 'blosc_lz4hc', 'blosc_zlib', 'blosc_zstd' ] -CompressionLevelOptions: TypeAlias = Literal[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, None] +CompressionLevelOptions: TypeAlias = Literal[0, 1, 2, 3, 4, 5, 6, 7, 8, 9] AccessModeOptions: TypeAlias = Literal['r', 'w', 'r+', 'a', 'x', 'rs', 'ws', 'r+s', 'as'] FormatOptions: TypeAlias = Literal[ 'NETCDF4', 'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC', @@ -41,28 +52,32 @@ QuantizeOptions: TypeAlias = Literal['BitGroom', 'BitRound', 'GranularBitRound'] EndianOptions: TypeAlias = Literal['native', 'little', 'big'] CalendarOptions: TypeAlias = Literal[ 'standard', 'gregorian', 'proleptic_gregorian' 'noleap', - '365_day', '360_day', 'julian', 'all_leap', '366_day', None + '365_day', '360_day', 'julian', 'all_leap', '366_day' ] +BoolInt: TypeAlias = Literal[0, 1] + +DateTimeArray: TypeAlias = npt.NDArray[np.object_] +"""numpy array of datetime.datetime or cftime.datetime""" __version__: str __netcdf4libversion__: str __hdf5libversion__: str -__has_rename_grp__: bool -__has_nc_inq_path__: bool -__has_nc_inq_format_extended__: bool -__has_nc_open_mem__: bool -__has_nc_create_mem__: bool -__has_cdf5_format__: bool -__has_parallel4_support__: bool -__has_pnetcdf_support__: bool -__has_parallel_support__: bool -__has_quantization_support__: bool -__has_zstandard_support__: bool -__has_bzip2_support__: bool -__has_blosc_support__: bool -__has_szip_support__: bool -__has_set_alignment__: bool -__has_ncfilter__: bool +__has_rename_grp__: BoolInt +__has_nc_inq_path__: BoolInt +__has_nc_inq_format_extended__: BoolInt +__has_nc_open_mem__: BoolInt +__has_nc_create_mem__: BoolInt +__has_cdf5_format__: BoolInt +__has_parallel4_support__: BoolInt +__has_pnetcdf_support__: BoolInt +__has_parallel_support__: BoolInt +__has_quantization_support__: BoolInt +__has_zstandard_support__: BoolInt +__has_bzip2_support__: BoolInt +__has_blosc_support__: BoolInt +__has_szip_support__: BoolInt +__has_set_alignment__: BoolInt +__has_ncfilter__: BoolInt is_native_little: bool is_native_big: bool default_encoding: Final = 'utf-8' @@ -70,6 +85,54 @@ unicode_error: Final = 'replace' default_fillvals: dict[str, Any] +# date2index, date2num, and num2date are actually provided by cftime and if stubs for +# cftime are completed these should be removed. +def date2index( + dates: dt.datetime | cftime.datetime | Sequence[dt.datetime | cftime.datetime] | DateTimeArray, + nctime: Variable, + calendar: CalendarOptions | None = None, + select: Literal["exact", "before", "after", "nearest"] = "exact", + has_year_zero: bool | None = None, +) -> int | npt.NDArray[np.int_]: ... +def date2num( + dates: dt.datetime | cftime.datetime | Sequence[dt.datetime | cftime.datetime] | DateTimeArray, + units: str, + calendar: CalendarOptions | None = None, + has_year_zero: bool | None = None, + longdouble: bool = False, +) -> np.number | npt.NDArray[np.number]: ... +def num2date( + times: Sequence[int | float | np.number] | npt.NDArray[np.number], + units: str, + calendar: CalendarOptions = "standard", + only_use_cftime_datetimes: bool = True, + only_use_python_datetimes: bool = False, + has_year_zero: bool | None = None, +) -> dt.datetime | DateTimeArray: ... + + +class BloscInfo(TypedDict): + compressor: Literal["blosc_lz", "blosc_lz4", "blosc_lz4hc", "blosc_zlib", "blosc_zstd"] + shuffle: Literal[0, 1, 2] + + +class SzipInfo(TypedDict): + coding: Literal["nn", "ec"] + pixels_per_block: Literal[4, 8, 16, 32] + + +class FiltersDict(TypedDict): + """Dict returned from netCDF4.Variable.filters()""" + zlib: bool + szip: Literal[False] | SzipInfo + zstd: bool + bzip2: bool + blosc: Literal[False] | BloscInfo + shuffle: bool + complevel: int + fletcher32: bool + + class NetCDF4MissingFeatureException(Exception): def __init__(self, feature: str, version: str): ... @@ -139,9 +202,9 @@ class Dataset: varname: str, datatype: T_DatatypeNC, dimensions: DimensionsOptions = (), - compression: CompressionOptions = None, + compression: CompressionOptions | None = None, zlib: bool = False, - complevel: CompressionLevelOptions = 4, + complevel: CompressionLevelOptions | None = 4, shuffle: bool = True, szip_coding: Literal['nn', 'ec'] = 'nn', szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, @@ -162,9 +225,9 @@ class Dataset: varname: str, datatype: _DatatypeStrOptions | npt.DTypeLike, dimensions: DimensionsOptions = (), - compression: CompressionOptions = None, + compression: CompressionOptions | None = None, zlib: bool = False, - complevel: CompressionLevelOptions = 4, + complevel: CompressionLevelOptions | None = 4, shuffle: bool = True, szip_coding: Literal['nn', 'ec'] = 'nn', szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, @@ -180,7 +243,10 @@ class Dataset: chunk_cache: int | None = None ) -> Variable[np.dtype]: ... def renameVariable(self, oldname: str, newname: str) -> None: ... - def createGroup(self, groupname: str) -> Group: ... + def createGroup(self, groupname: str) -> Group: + """Test x-> y""" + ... + def renameGroup(self, oldname: str, newname: str) -> None: ... def renameAttribute(self, oldname: str, newname: str) -> None: ... def createCompoundType( self, datatype: npt.DTypeLike, datatype_name: str) -> CompoundType: ... @@ -272,9 +338,9 @@ class Variable(Generic[T_Datatype]): name: str, datatype: T_DatatypeNC, dimensions: DimensionsOptions = (), - compression: CompressionOptions = None, + compression: CompressionOptions | None = None, zlib: bool = False, - complevel: CompressionLevelOptions = 4, + complevel: CompressionLevelOptions | None = 4, shuffle: bool = True, szip_coding: Literal['nn', 'ec'] = 'nn', szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, @@ -298,9 +364,9 @@ class Variable(Generic[T_Datatype]): name: str, datatype: _DatatypeStrOptions | npt.DTypeLike, dimensions: DimensionsOptions = (), - compression: CompressionOptions = None, + compression: CompressionOptions | None = None, zlib: bool = False, - complevel: CompressionLevelOptions = 4, + complevel: CompressionLevelOptions | None = 4, shuffle: bool = True, szip_coding: Literal['nn', 'ec'] = 'nn', szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, @@ -324,9 +390,9 @@ class Variable(Generic[T_Datatype]): name: str, datatype: T_Datatype, dimensions: DimensionsOptions = (), - compression: CompressionOptions = None, + compression: CompressionOptions | None = None, zlib: bool = False, - complevel: CompressionLevelOptions = 4, + complevel: CompressionLevelOptions | None = 4, shuffle: bool = True, szip_coding: Literal['nn', 'ec'] = 'nn', szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, @@ -513,14 +579,14 @@ class _Variable: class MFTime(_Variable): - calendar: CalendarOptions + calendar: CalendarOptions | None units: str | None def __init__( self, time: Variable, units: str | None = None, - calendar: CalendarOptions = None + calendar: CalendarOptions | None = None ): ... def __getitem__(self, elem: Any) -> np.ndarray: ... From f151aef37d3e6a6470107c2ba4d6564957dc9af7 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Wed, 26 Jun 2024 21:24:44 +0200 Subject: [PATCH 1161/1504] more suggestions from review --- .github/stubtest-allowlist | 1 + src/netCDF4/__init__.pyi | 28 +++++++++++++++++----------- 2 files changed, 18 insertions(+), 11 deletions(-) diff --git a/.github/stubtest-allowlist b/.github/stubtest-allowlist index 06862f1eb..2d848ab15 100644 --- a/.github/stubtest-allowlist +++ b/.github/stubtest-allowlist @@ -13,6 +13,7 @@ netCDF4.DateTimeArray netCDF4.FiltersDict netCDF4.SzipInfo netCDF4.BloscInfo +netCDF4.BoolInt netCDF4.T_Datatype netCDF4.T_DatatypeNC netCDF4.Dataset.__dealloc diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index abeef9169..82fb0940d 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -82,7 +82,7 @@ is_native_little: bool is_native_big: bool default_encoding: Final = 'utf-8' unicode_error: Final = 'replace' -default_fillvals: dict[str, Any] +default_fillvals: dict[str, int | float | str] # date2index, date2num, and num2date are actually provided by cftime and if stubs for @@ -185,6 +185,8 @@ class Dataset: @property def auto_complex(self) -> bool: ... @property + def _ncstring_attrs__(self) -> bool: ... + @property def __orthogonal_indexing__(self) -> bool: ... def filepath(self, encoding: str | None = None) -> str: ... @@ -243,15 +245,17 @@ class Dataset: chunk_cache: int | None = None ) -> Variable[np.dtype]: ... def renameVariable(self, oldname: str, newname: str) -> None: ... - def createGroup(self, groupname: str) -> Group: - """Test x-> y""" - ... + def createGroup(self, groupname: str) -> Group: ... def renameGroup(self, oldname: str, newname: str) -> None: ... def renameAttribute(self, oldname: str, newname: str) -> None: ... - def createCompoundType( self, datatype: npt.DTypeLike, datatype_name: str) -> CompoundType: ... - def createVLType( self, datatype: npt.DTypeLike, datatype_name: str) -> VLType: ... - def createEnumType( self, datatype: npt.DTypeLike, datatype_name: str, enum_dict: dict[str, int]) -> EnumType: ... + def createCompoundType( + self, datatype: npt.DTypeLike | Sequence[tuple[str, npt.DTypeLike]], datatype_name: str + ) -> CompoundType: ... + def createVLType(self, datatype: npt.DTypeLike, datatype_name: str) -> VLType: ... + def createEnumType( + self, datatype: np.dtype[np.integer] | type[np.integer] | type[int], datatype_name: str, enum_dict: dict[str, int] + ) -> EnumType: ... def ncattrs(self) -> list[str]: ... def setncattr_string(self, name: str, value: Any) -> None: ... @@ -287,7 +291,7 @@ class Dataset: coordvars: bool = False, data: bool = False, *, - outfile: str + outfile: str | os.PathLike ) -> None: ... def has_blosc_filter(self) -> bool: ... @@ -481,7 +485,9 @@ class CompoundType: dtype_view: np.dtype name: str - def __init__(self, grp: Group, dt: npt.DTypeLike, dtype_name: str, **kwargs: Any) -> None: ... + def __init__( + self, grp: Group, dt: npt.DTypeLike | Sequence[tuple[str, npt.DTypeLike]], dtype_name: str, **kwargs: Any + ) -> None: ... def __str__(self) -> str: ... def __repr__(self) -> str: ... @@ -500,14 +506,14 @@ class VLType: class EnumType: - dtype: np.dtype + dtype: np.dtype[np.integer] | type[np.integer] | type[int] name: str enum_dict: Mapping[str, int] def __init__( self, grp: Group, - dt: npt.DTypeLike, + dt: np.dtype[np.integer] | type[np.integer] | type[int], dtype_name: str, enum_dict: Mapping[str, int], **kwargs: Any From 3094ed87c5f6242c92fda26e4f0f905c7912fa65 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Wed, 26 Jun 2024 21:25:54 +0200 Subject: [PATCH 1162/1504] remove str and repr stubs --- src/netCDF4/__init__.pyi | 14 -------------- 1 file changed, 14 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 82fb0940d..dbac566ca 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -307,8 +307,6 @@ class Dataset: def __reduce__(self) -> NoReturn: ... def __enter__(self) -> Self: ... def __exit__(self, atype, value, traceback) -> None: ... - def __str__(self) -> str: ... - def __repr__(self) -> str: ... class Group(Dataset): @@ -329,8 +327,6 @@ class Dimension: def isunlimited(self) -> bool: ... def __len__(self) -> int: ... - def __str__(self) -> str: ... - def __repr__(self) -> str: ... class Variable(Generic[T_Datatype]): @@ -476,8 +472,6 @@ class Variable(Generic[T_Datatype]): def __setitem__(self, elem: Any, data: npt.ArrayLike) -> None: ... def __array__(self) -> np.ndarray: ... def __len__(self) -> int: ... - def __str__(self) -> str: ... - def __repr__(self) -> str: ... class CompoundType: @@ -489,8 +483,6 @@ class CompoundType: self, grp: Group, dt: npt.DTypeLike | Sequence[tuple[str, npt.DTypeLike]], dtype_name: str, **kwargs: Any ) -> None: ... - def __str__(self) -> str: ... - def __repr__(self) -> str: ... def __reduce__(self) -> NoReturn: ... @@ -500,8 +492,6 @@ class VLType: def __init__(self, grp: Group, dt: npt.DTypeLike, dtype_name: str, **kwargs: Any) -> None: ... - def __str__(self) -> str: ... - def __repr__(self) -> str: ... def __reduce__(self) -> NoReturn: ... @@ -519,8 +509,6 @@ class EnumType: **kwargs: Any ) -> None: ... - def __str__(self) -> str: ... - def __repr__(self) -> str: ... def __reduce__(self) -> NoReturn: ... @@ -560,7 +548,6 @@ class _Dimension: def __len__(self) -> int: ... def isunlimited(self) -> Literal[True]: ... - def __repr__(self) -> str: ... class _Variable: @@ -581,7 +568,6 @@ class _Variable: def __getattr__(self, name): ... def __getitem__(self, elem): ... def __len__(self) -> int: ... - def __repr__(self) -> str: ... class MFTime(_Variable): From 2671af98de31c67718b7c9470218c8e7a6c74bb2 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Wed, 26 Jun 2024 21:41:46 +0200 Subject: [PATCH 1163/1504] fix typing of grp args --- src/netCDF4/__init__.pyi | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index dbac566ca..28a37f4fd 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -310,20 +310,20 @@ class Dataset: class Group(Dataset): - def __init__(self, parent: Group | Dataset, name: str, **kwargs: Any) -> None: ... + def __init__(self, parent: Dataset, name: str, **kwargs: Any) -> None: ... def close(self) -> NoReturn: ... class Dimension: - def __init__(self, grp: Group, name: str, size: int | None = None, **kwargs: Any) -> None: ... + def __init__(self, grp: Dataset, name: str, size: int | None = None, **kwargs: Any) -> None: ... @property def name(self) -> str: ... @property def size(self) -> int: ... - def group(self) -> Group: ... + def group(self) -> Dataset: ... def isunlimited(self) -> bool: ... def __len__(self) -> int: ... @@ -334,7 +334,7 @@ class Variable(Generic[T_Datatype]): @overload def __new__( # type: ignore self, - grp: Group, + grp: Dataset, name: str, datatype: T_DatatypeNC, dimensions: DimensionsOptions = (), @@ -360,7 +360,7 @@ class Variable(Generic[T_Datatype]): @overload def __new__( self, - grp: Group, + grp: Dataset, name: str, datatype: _DatatypeStrOptions | npt.DTypeLike, dimensions: DimensionsOptions = (), @@ -386,7 +386,7 @@ class Variable(Generic[T_Datatype]): def __init__( self, - grp: Group, + grp: Dataset, name: str, datatype: T_Datatype, dimensions: DimensionsOptions = (), @@ -434,7 +434,7 @@ class Variable(Generic[T_Datatype]): @property def __orthogonal_indexing__(self) -> bool: ... - def group(self) -> Group: ... + def group(self) -> Dataset: ... def ncattrs(self) -> list[str]: ... def setncattr(self, name: str, value: Any) -> None: ... def setncattr_string(self, name: str, value: Any) -> None: ... @@ -480,7 +480,7 @@ class CompoundType: name: str def __init__( - self, grp: Group, dt: npt.DTypeLike | Sequence[tuple[str, npt.DTypeLike]], dtype_name: str, **kwargs: Any + self, grp: Dataset, dt: npt.DTypeLike | Sequence[tuple[str, npt.DTypeLike]], dtype_name: str, **kwargs: Any ) -> None: ... def __reduce__(self) -> NoReturn: ... @@ -490,7 +490,7 @@ class VLType: dtype: np.dtype name: str | None - def __init__(self, grp: Group, dt: npt.DTypeLike, dtype_name: str, **kwargs: Any) -> None: ... + def __init__(self, grp: Dataset, dt: npt.DTypeLike, dtype_name: str, **kwargs: Any) -> None: ... def __reduce__(self) -> NoReturn: ... @@ -502,7 +502,7 @@ class EnumType: def __init__( self, - grp: Group, + grp: Dataset, dt: np.dtype[np.integer] | type[np.integer] | type[int], dtype_name: str, enum_dict: Mapping[str, int], From f628ff301db471ca0dced538db34df265f0ad8ea Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Wed, 26 Jun 2024 21:42:01 +0200 Subject: [PATCH 1164/1504] remove all ._netCDF4 from all reprs --- src/netCDF4/_netCDF4.pyx | 23 ++++++++++++++--------- 1 file changed, 14 insertions(+), 9 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index a43a370b8..ac04372e1 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -3718,12 +3718,13 @@ Read-only class variables: def __str__(self): if not dir(self._grp): return 'Dimension object no longer valid' + typ = repr(type(self)).replace("._netCDF4", "") if self.isunlimited(): return "%r (unlimited): name = '%s', size = %s" %\ - (type(self), self._name, len(self)) + (typ, self._name, len(self)) else: return "%r: name = '%s', size = %s" %\ - (type(self), self._name, len(self)) + (typ, self._name, len(self)) def __len__(self): # len(`Dimension` instance) returns current size of dimension @@ -6149,8 +6150,9 @@ the user. return self.__str__() def __str__(self): - return "%r: name = '%s', numpy dtype = %s" %\ - (type(self), self.name, self.dtype) + typ = repr(type(self)).replace("._netCDF4", "") + return "%s: name = '%s', numpy dtype = %s" %\ + (typ, self.name, self.dtype) def __reduce__(self): # raise error is user tries to pickle a CompoundType object. @@ -6437,11 +6439,12 @@ the user. return self.__str__() def __str__(self): + typ = repr(type(self)).replace("._netCDF4", "") if self.dtype == str: - return '%r: string type' % (type(self),) + return '%r: string type' % (typ,) else: return "%r: name = '%s', numpy dtype = %s" %\ - (type(self), self.name, self.dtype) + (typ, self.name, self.dtype) def __reduce__(self): # raise error is user tries to pickle a VLType object. @@ -6549,8 +6552,9 @@ the user. return self.__str__() def __str__(self): + typ = repr(type(self)).replace("._netCDF4", "") return "%r: name = '%s', numpy dtype = %s, fields/values =%s" %\ - (type(self), self.name, self.dtype, self.enum_dict) + (typ, self.name, self.dtype, self.enum_dict) def __reduce__(self): # raise error is user tries to pickle a EnumType object. @@ -7019,12 +7023,13 @@ class _Dimension: def isunlimited(self): return True def __repr__(self): + typ = repr(type(self)).replace("._netCDF4", "") if self.isunlimited(): return "%r (unlimited): name = '%s', size = %s" %\ - (type(self), self._name, len(self)) + (typ, self._name, len(self)) else: return "%r: name = '%s', size = %s" %\ - (type(self), self._name, len(self)) + (typ, self._name, len(self)) class _Variable: def __init__(self, dset, varname, var, recdimname): From 7576a370fa12488bd14945893a58d4e46561442b Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Wed, 26 Jun 2024 21:46:46 +0200 Subject: [PATCH 1165/1504] improve typing of fill_value --- src/netCDF4/__init__.pyi | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 28a37f4fd..c6b3813ff 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -218,7 +218,7 @@ class Dataset: least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeOptions = 'BitGroom', - fill_value: npt.ArrayLike | bool | None = None, + fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None ) -> Variable[T_DatatypeNC]: ... @overload @@ -241,7 +241,7 @@ class Dataset: least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeOptions = 'BitGroom', - fill_value: npt.ArrayLike | bool | None = None, + fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None ) -> Variable[np.dtype]: ... def renameVariable(self, oldname: str, newname: str) -> None: ... @@ -352,7 +352,7 @@ class Variable(Generic[T_Datatype]): least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeOptions = 'BitGroom', - fill_value: npt.ArrayLike | bool | None = None, + fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any ) -> Variable[T_DatatypeNC]: ... @@ -378,7 +378,7 @@ class Variable(Generic[T_Datatype]): least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeOptions = 'BitGroom', - fill_value: npt.ArrayLike | bool | None = None, + fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any ) -> Variable[np.dtype]: ... @@ -404,7 +404,7 @@ class Variable(Generic[T_Datatype]): least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeOptions = 'BitGroom', - fill_value: npt.ArrayLike | bool | None = None, + fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any ) -> None: ... From 6d8a734838a169f980914d2d338e393b9d33a8af Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Wed, 26 Jun 2024 21:52:27 +0200 Subject: [PATCH 1166/1504] use GetSetItemKey type --- src/netCDF4/__init__.pyi | 23 ++++++++++++++++------- 1 file changed, 16 insertions(+), 7 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index c6b3813ff..0c2593ff0 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -59,6 +59,15 @@ BoolInt: TypeAlias = Literal[0, 1] DateTimeArray: TypeAlias = npt.NDArray[np.object_] """numpy array of datetime.datetime or cftime.datetime""" +GetSetItemKey: TypeAlias = ( + int + | slice + | ellipsis + | list[int | bool] + | npt.NDArray[np.integer | np.bool_] + | tuple[int | slice | ellipsis | Sequence[int | bool] | npt.NDArray[np.integer | np.bool_], ...] +) + __version__: str __netcdf4libversion__: str __hdf5libversion__: str @@ -441,10 +450,10 @@ class Variable(Generic[T_Datatype]): def setncatts(self, attdict: Mapping[str, Any]) -> None: ... def getncattr(self, name: str, encoding='utf-8'): ... def delncattr(self, name: str) -> None: ... - def filters(self) -> dict[str, Any]: ... + def filters(self) -> FiltersDict: ... def quantization(self) -> tuple[int, QuantizeOptions] | None: ... def endian(self) -> EndianOptions: ... - def chunking(self) -> Literal['contiguous'] | list[int] | None: ... + def chunking(self) -> Literal['contiguous'] | list[int]: ... def get_var_chunk_cache(self) -> tuple[int, int, float]: ... def set_var_chunk_cache( self, @@ -468,8 +477,8 @@ class Variable(Generic[T_Datatype]): def __delattr__(self, name: str) -> None: ... def __setattr__(self, name: str, value: Any) -> None: ... def __getattr__(self, name: str) -> Any: ... - def __getitem__(self, elem: Any) -> np.ndarray: ... - def __setitem__(self, elem: Any, data: npt.ArrayLike) -> None: ... + def __getitem__(self, elem: GetSetItemKey) -> np.ndarray: ... + def __setitem__(self, elem: GetSetItemKey, data: npt.ArrayLike) -> None: ... def __array__(self) -> np.ndarray: ... def __len__(self) -> int: ... @@ -565,8 +574,8 @@ class _Variable: def set_auto_scale(self, val: bool) -> None: ... def set_always_mask(self, val: bool) -> None: ... - def __getattr__(self, name): ... - def __getitem__(self, elem): ... + def __getattr__(self, name: str): ... + def __getitem__(self, elem: GetSetItemKey): ... def __len__(self) -> int: ... @@ -580,7 +589,7 @@ class MFTime(_Variable): units: str | None = None, calendar: CalendarOptions | None = None ): ... - def __getitem__(self, elem: Any) -> np.ndarray: ... + def __getitem__(self, elem: GetSetItemKey) -> np.ndarray: ... def stringtoarr(string, NUMCHARS: int, dtype: Literal['S', 'U'] = 'S') -> np.ndarray: ... From 3f3df1ba478b652e222f0f586d57ac0300e7c914 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Wed, 26 Jun 2024 22:02:42 +0200 Subject: [PATCH 1167/1504] fix dtype of EnumType --- src/netCDF4/__init__.pyi | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 0c2593ff0..f89ff9306 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -505,14 +505,14 @@ class VLType: class EnumType: - dtype: np.dtype[np.integer] | type[np.integer] | type[int] + dtype: np.dtype[np.integer] name: str enum_dict: Mapping[str, int] def __init__( self, grp: Dataset, - dt: np.dtype[np.integer] | type[np.integer] | type[int], + dt: np.dtype[np.integer] | type[np.integer] | type[int] | str, dtype_name: str, enum_dict: Mapping[str, int], **kwargs: Any From d774ae494be3bbca1e807bcc4ccca07662b84ad4 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Wed, 26 Jun 2024 22:06:45 +0200 Subject: [PATCH 1168/1504] fix docstring arg names of CompoundType --- src/netCDF4/_netCDF4.pyx | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index ac04372e1..aacb344dd 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -6100,13 +6100,13 @@ the user. CompoundType constructor. - **`group`**: `Group` instance to associate with the compound datatype. + **`grp`**: `Group` instance to associate with the compound datatype. - **`datatype`**: A numpy dtype object describing a structured (a.k.a record) + **`dt`**: A numpy dtype object describing a structured (a.k.a record) array. Can be composed of homogeneous numeric or character data types, or other structured array data types. - **`datatype_name`**: a Python string containing a description of the + **`dtype_name`**: a Python string containing a description of the compound data type. ***Note 1***: When creating nested compound data types, From 053e049e4f216912ffe5e74b75460b9e560cb82a Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Wed, 26 Jun 2024 22:08:21 +0200 Subject: [PATCH 1169/1504] remove redundand properties --- src/netCDF4/__init__.pyi | 10 ---------- 1 file changed, 10 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index f89ff9306..f2fbca043 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -531,20 +531,10 @@ class MFDataset(Dataset): master_file: str | os.PathLike | None = None ) -> None: ... - @property - def groups(self) -> dict[str, Group]: ... @property def dimensions(self) -> dict[str, Dimension]: ... # this should be: dict[str, Dimension | _Dimension] @property def variables(self) -> dict[str, Variable[Any]]: ... # this should be: dict[str, _Variable[Any] | _Variable] - @property - def data_model(self) -> FormatOptions: ... - @property - def file_format(self) -> FormatOptions: ... - @property - def disk_format(self) -> DiskFormatOptions: ... - @property - def path(self) -> str: ... class _Dimension: From d0e9bd4422b591a81cc733b28b01cf6aeaa11e67 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Wed, 26 Jun 2024 22:15:51 +0200 Subject: [PATCH 1170/1504] str as valid dtype --- src/netCDF4/__init__.pyi | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index f2fbca043..11bd10bbe 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -421,7 +421,7 @@ class Variable(Generic[T_Datatype]): @property def name(self) -> str: ... @property - def dtype(self) -> np.dtype: ... + def dtype(self) -> np.dtype | type[str]: ... @property def datatype(self) -> T_Datatype: ... @property @@ -551,11 +551,11 @@ class _Dimension: class _Variable: dimensions: tuple[str, ...] - dtype: np.dtype + dtype: np.dtype | type[str] - def __init__(self, dset: Dataset, varname: str, var, recdimname: str) -> None: ... + def __init__(self, dset: Dataset, varname: str, var: Variable[Any], recdimname: str) -> None: ... - def typecode(self) -> np.dtype: ... + def typecode(self) -> np.dtype | type[str]: ... def ncattrs(self) -> list[str]: ... def _shape(self) -> tuple[int, ...]: ... def set_auto_chartostring(self, val: bool) -> None: ... @@ -564,8 +564,8 @@ class _Variable: def set_auto_scale(self, val: bool) -> None: ... def set_always_mask(self, val: bool) -> None: ... - def __getattr__(self, name: str): ... - def __getitem__(self, elem: GetSetItemKey): ... + def __getattr__(self, name: str) -> Any: ... + def __getitem__(self, elem: GetSetItemKey) -> Any: ... def __len__(self) -> int: ... From db03592d37ad2dfd1315447b1467a2b0e3de6e38 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Wed, 26 Jun 2024 22:34:32 +0200 Subject: [PATCH 1171/1504] add some properties and overloads --- .github/stubtest-allowlist | 1 + src/netCDF4/__init__.pyi | 43 +++++++++++++++++++++++++++++++++++--- 2 files changed, 41 insertions(+), 3 deletions(-) diff --git a/.github/stubtest-allowlist b/.github/stubtest-allowlist index 2d848ab15..a3bd3a1a4 100644 --- a/.github/stubtest-allowlist +++ b/.github/stubtest-allowlist @@ -14,6 +14,7 @@ netCDF4.FiltersDict netCDF4.SzipInfo netCDF4.BloscInfo netCDF4.BoolInt +netCDF4.GetSetItemKey netCDF4.T_Datatype netCDF4.T_DatatypeNC netCDF4.Dataset.__dealloc diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 11bd10bbe..413336f0e 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -555,6 +555,14 @@ class _Variable: def __init__(self, dset: Dataset, varname: str, var: Variable[Any], recdimname: str) -> None: ... + # shape, ndim, and name actually come from __getattr__ + @property + def shape(self) -> tuple[int, ...]: ... + @property + def ndim(self) -> int: ... + @property + def name(self) -> str: ... + def typecode(self) -> np.dtype | type[str]: ... def ncattrs(self) -> list[str]: ... def _shape(self) -> tuple[int, ...]: ... @@ -582,9 +590,38 @@ class MFTime(_Variable): def __getitem__(self, elem: GetSetItemKey) -> np.ndarray: ... -def stringtoarr(string, NUMCHARS: int, dtype: Literal['S', 'U'] = 'S') -> np.ndarray: ... -def stringtochar(a, encoding: str | bytes | None = 'utf-8') -> np.ndarray: ... -def chartostring(b, encoding: str | bytes | None = 'utf-8') -> np.ndarray: ... +@overload +def stringtoarr( + string: str, + NUMCHARS: int, + dtype: Literal["S"] | np.dtype[np.bytes_]= "S", +) -> npt.NDArray[np.bytes_]: ... +@overload +def stringtoarr( + string: str, + NUMCHARS: int, + dtype: Literal["U"] | np.dtype[np.str_], +) -> npt.NDArray[np.str_]: ... +@overload +def stringtochar( + a: npt.NDArray[np.character], + encoding: Literal["none", "None", "bytes"], +) -> npt.NDArray[np.bytes_]: ... +@overload +def stringtochar( + a: npt.NDArray[np.character], + encoding: str = ..., +) -> npt.NDArray[np.str_] | npt.NDArray[np.bytes_]: ... +@overload +def chartostring( + b: npt.NDArray[np.character], + encoding: Literal["none", "None", "bytes"] = ..., +) -> npt.NDArray[np.bytes_]: ... +@overload +def chartostring( + b: npt.NDArray[np.character], + encoding: str = ..., +) -> npt.NDArray[np.str_] | npt.NDArray[np.bytes_]: ... def getlibversion() -> str: ... From 9704822e84d2c17f47c105c8ea0839f8776df2c6 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Thu, 27 Jun 2024 07:45:52 +0200 Subject: [PATCH 1172/1504] Update MANIFEST.in --- MANIFEST.in | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/MANIFEST.in b/MANIFEST.in index 2b010c5ee..3b055f8f3 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -16,6 +16,7 @@ exclude src/netCDF4/_netCDF4.c include src/netCDF4/utils.py include src/netCDF4/plugins/empty.txt include src/netCDF4/py.typed +include src/netCDF4/*.pyi include include/netCDF4.pxi include include/mpi-compat.h include include/membuf.pyx @@ -24,7 +25,6 @@ include include/no_parallel_support_imports.pxi.in include include/parallel_support_imports.pxi.in include *.md include *.py -include *.pyi include *.release include *.sh include LICENSE From fe92b19353a4f1b4a3af52504e5c49377b9a4f21 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Thu, 27 Jun 2024 21:51:40 +0200 Subject: [PATCH 1173/1504] fix typing of tutorial --- examples/tutorial.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/examples/tutorial.py b/examples/tutorial.py index 498e22154..67573d8ae 100644 --- a/examples/tutorial.py +++ b/examples/tutorial.py @@ -1,3 +1,4 @@ +from typing import Literal from netCDF4 import Dataset # code from tutorial. @@ -68,7 +69,8 @@ def walktree(top): levels.units = 'hPa' temp.units = 'K' times.units = 'hours since 0001-01-01 00:00:00.0' -times.calendar = 'gregorian' +calendar: Literal['gregorian'] = 'gregorian' +times.calendar = calendar for name in rootgrp.ncattrs(): print('Global attr', name, '=', getattr(rootgrp,name)) @@ -111,8 +113,8 @@ def walktree(top): dates = [datetime(2001,3,1)+n*timedelta(hours=12) for n in range(temp.shape[0])] times[:] = date2num(dates,units=times.units,calendar=times.calendar) print("time values (in units {}):\n{}".format(times.units, times[:])) -dates = num2date(times[:],units=times.units,calendar=times.calendar) -print("dates corresponding to time values:\n{}".format(dates)) +dates_array = num2date(times[:],units=times.units,calendar=times.calendar) +print("dates corresponding to time values:\n{}".format(dates_array)) rootgrp.close() From 58ba81b6a37f00ed8e7503f14e4c73ebfd677c08 Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 28 Jun 2024 20:52:29 +0200 Subject: [PATCH 1174/1504] !fixup a192f68ec706fb8bb78e7c6aec533bdc7d2b900e --- docs/index.html | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/index.html b/docs/index.html index 8191c3314..9ac639aa0 100644 --- a/docs/index.html +++ b/docs/index.html @@ -118,8 +118,8 @@

      Creating/Opening/Closing a netCDF If the file is open for write access (mode='w', 'r+' or 'a'), you may write any type of data including new dimensions, groups, variables and attributes. -netCDF files come in five flavors (NETCDF3_CLASSIC, -NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF4_CLASSIC, and NETCDF4). +netCDF files come in five flavors (NETCDF3_CLASSIC, + NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF4_CLASSIC<code>, and </code>NETCDF4). NETCDF3_CLASSIC was the original netcdf binary format, and was limited to file sizes less than 2 Gb. NETCDF3_64BIT_OFFSET was introduced in version 3.6.0 of the library, and extended the original binary format From 1644caa7d46dc23a043b27bc9e5efc1721fab5dc Mon Sep 17 00:00:00 2001 From: Michael Niklas Date: Fri, 28 Jun 2024 20:53:40 +0200 Subject: [PATCH 1175/1504] !fixup a192f68ec706fb8bb78e7c6aec533bdc7d2b900e --- docs/index.html | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/index.html b/docs/index.html index 9ac639aa0..6971ceb5b 100644 --- a/docs/index.html +++ b/docs/index.html @@ -119,7 +119,7 @@

      Creating/Opening/Closing a netCDF write any type of data including new dimensions, groups, variables and attributes. netCDF files come in five flavors (NETCDF3_CLASSIC, - NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF4_CLASSIC<code>, and </code>NETCDF4). +NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF4_CLASSIC<code>, and </code>NETCDF4). NETCDF3_CLASSIC was the original netcdf binary format, and was limited to file sizes less than 2 Gb. NETCDF3_64BIT_OFFSET was introduced in version 3.6.0 of the library, and extended the original binary format From ca541af18bad683bf70748eec1ff7fc353d0c21f Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Wed, 3 Jul 2024 03:13:31 +0000 Subject: [PATCH 1176/1504] Bump pypa/cibuildwheel from 2.19.1 to 2.19.2 in the github-actions group Bumps the github-actions group with 1 update: [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel). Updates `pypa/cibuildwheel` from 2.19.1 to 2.19.2 - [Release notes](https://github.com/pypa/cibuildwheel/releases) - [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md) - [Commits](https://github.com/pypa/cibuildwheel/compare/v2.19.1...v2.19.2) --- updated-dependencies: - dependency-name: pypa/cibuildwheel dependency-type: direct:production update-type: version-update:semver-patch dependency-group: github-actions ... Signed-off-by: dependabot[bot] --- .github/workflows/cibuildwheel.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index e7d515be7..a7fcad5eb 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -92,7 +92,7 @@ jobs: echo "Setting CIBW_SKIP=$CIBW_SKIP" - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels" - uses: pypa/cibuildwheel@v2.19.1 + uses: pypa/cibuildwheel@v2.19.2 env: CIBW_SKIP: ${{ env.CIBW_SKIP }} CIBW_ARCHS: ${{ matrix.arch }} From e2638fffeda67a4a7ec5a2057a180256342f600f Mon Sep 17 00:00:00 2001 From: jswhit Date: Sat, 6 Jul 2024 11:57:13 -0600 Subject: [PATCH 1177/1504] expose nc_rc_set, nc_rc_get (via rc_set, rc_get module functions). --- .github/workflows/cibuildwheel.yml | 2 +- include/netCDF4.pxi | 1 + src/netCDF4/__init__.py | 4 +-- src/netCDF4/_netCDF4.pyx | 43 +++++++++++++++++++++++++++++- 4 files changed, 46 insertions(+), 4 deletions(-) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index e7d515be7..da4c1365c 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -60,7 +60,7 @@ jobs: - os: macos-14 arch: arm64 CIBW_ENVIRONMENT: MACOSX_DEPLOYMENT_TARGET=14.0 - - os: macos-11 + - os: macos-13 arch: x86_64 CIBW_ENVIRONMENT: MACOSX_DEPLOYMENT_TARGET=11.0 diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi index 9404171db..f748bf82c 100644 --- a/include/netCDF4.pxi +++ b/include/netCDF4.pxi @@ -392,6 +392,7 @@ cdef extern from "netcdf-compat.h": int nc_set_alignment(int threshold, int alignment) int nc_get_alignment(int *threshold, int *alignment) int nc_rc_set(char* key, char* value) nogil + const_char_ptr *nc_rc_get(char* key) int nc_open_mem(const char *path, int mode, size_t size, void* memory, int *ncidp) nogil int nc_create_mem(const char *path, int mode, size_t initialize, int *ncidp) nogil diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py index ac93047a2..e63ad3fc6 100644 --- a/src/netCDF4/__init__.py +++ b/src/netCDF4/__init__.py @@ -10,10 +10,10 @@ __has_parallel4_support__, __has_pnetcdf_support__, __has_quantization_support__, __has_zstandard_support__, __has_bzip2_support__, __has_blosc_support__, __has_szip_support__, - __has_set_alignment__) + __has_set_alignment__, __has_nc_rc_set__) import os __all__ =\ -['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache','set_alignment','get_alignment'] +['Dataset','Variable','Dimension','Group','MFDataset','MFTime','CompoundType','VLType','date2num','num2date','date2index','stringtochar','chartostring','stringtoarr','getlibversion','EnumType','get_chunk_cache','set_chunk_cache','set_alignment','get_alignment','nc_get','nc_set'] __pdoc__ = { 'utils': False, } diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 49f62ee5c..269ea733e 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1308,15 +1308,56 @@ __has_blosc_support__ = HAS_BLOSC_SUPPORT __has_szip_support__ = HAS_SZIP_SUPPORT __has_set_alignment__ = HAS_SET_ALIGNMENT __has_ncfilter__ = HAS_NCFILTER +__has_nc_rc_set__ = HAS_NCRCSET # set path to SSL certificates (issue #1246) # available starting in version 4.9.1 -if HAS_NCRCSET: +if __has_nc_rc_set__: import certifi if nc_rc_set("HTTP.SSL.CAINFO", _strencode(certifi.where())) != 0: raise RuntimeError('error setting path to SSL certificates') +def rc_get(key): + """ +**`rc_key(key)`** + +Returns the internal netcdf-c rc table value corresponding to key. + """ + cdef int ierr + cdef char *keyc + if __has_nc_rc_set__: + bytestr = _strencode(_tostr(key)) + keyc = bytestr + return (nc_rc_get(keyc)).decode('utf-8') + else: + raise RuntimeError( + "This function requires netcdf4 4.9.0+ to be used at compile time" + ) + +def rc_set(key, value): + """ +**`rc_set(key, value)`** + +Sets the internal netcdf-c rc table value corresponding to key. + """ + cdef int ierr + cdef char *keyc + cdef char *valuec + if __has_nc_rc_set__: + key_bytestr = _strencode(_tostr(key)) + keyc = key_bytestr + val_bytestr = _strencode(_tostr(value)) + valuec = val_bytestr + with nogil: + ierr = nc_rc_set(keyc,valuec) + _ensure_nc_success(ierr) + else: + raise RuntimeError( + "This function requires netcdf4 4.9.0+ to be used at compile time" + ) + + # check for required version of netcdf-4 and hdf5. def _gethdf5libversion(): From 7a715110e0040a1555ff62e81b8832a915a0b476 Mon Sep 17 00:00:00 2001 From: jswhit Date: Sat, 6 Jul 2024 12:08:39 -0600 Subject: [PATCH 1178/1504] update --- src/netCDF4/_netCDF4.pyx | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 269ea733e..c740e114c 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1332,7 +1332,7 @@ Returns the internal netcdf-c rc table value corresponding to key. return (nc_rc_get(keyc)).decode('utf-8') else: raise RuntimeError( - "This function requires netcdf4 4.9.0+ to be used at compile time" + "This function requires netcdf-c 4.9.0+ to be used at compile time" ) def rc_set(key, value): @@ -1354,7 +1354,7 @@ Sets the internal netcdf-c rc table value corresponding to key. _ensure_nc_success(ierr) else: raise RuntimeError( - "This function requires netcdf4 4.9.0+ to be used at compile time" + "This function requires netcdf-c 4.9.0+ to be used at compile time" ) @@ -1435,7 +1435,7 @@ def get_alignment(): if not __has_set_alignment__: raise RuntimeError( - "This function requires netcdf4 4.9.0+ to be used at compile time" + "This function requires netcdf-c 4.9.0+ to be used at compile time" ) cdef int ierr @@ -1458,7 +1458,7 @@ def set_alignment(threshold, alignment): if not __has_set_alignment__: raise RuntimeError( - "This function requires netcdf4 4.9.0+ to be used at compile time" + "This function requires netcdf-c 4.9.0+ to be used at compile time" ) cdef int ierr From eb4fcf068bf45ed700c77332da6ed0c39fccf127 Mon Sep 17 00:00:00 2001 From: jswhit Date: Sat, 6 Jul 2024 13:40:25 -0600 Subject: [PATCH 1179/1504] add test --- .github/workflows/cibuildwheel.yml | 4 ++-- include/netcdf-compat.h | 1 + test/test_ncrc.py | 17 +++++++++++++++++ 3 files changed, 20 insertions(+), 2 deletions(-) create mode 100644 test/test_ncrc.py diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index da4c1365c..b6415474f 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -60,9 +60,9 @@ jobs: - os: macos-14 arch: arm64 CIBW_ENVIRONMENT: MACOSX_DEPLOYMENT_TARGET=14.0 - - os: macos-13 + - os: macos-12 arch: x86_64 - CIBW_ENVIRONMENT: MACOSX_DEPLOYMENT_TARGET=11.0 + CIBW_ENVIRONMENT: MACOSX_DEPLOYMENT_TARGET=12.0 steps: - uses: actions/checkout@v4 diff --git a/include/netcdf-compat.h b/include/netcdf-compat.h index 89e7b20fe..b445d6922 100644 --- a/include/netcdf-compat.h +++ b/include/netcdf-compat.h @@ -60,6 +60,7 @@ static inline int nc_get_alignment(int* thresholdp, int* alignmentp) { #else #define HAS_NCRCSET 0 static inline int nc_rc_set(const char* key, const char* value) { return NC_EINVAL; } +static inline const char *nc_rc_set(const char* key) { return NC_EINVAL; } #endif #if NC_VERSION_GE(4, 4, 0) diff --git a/test/test_ncrc.py b/test/test_ncrc.py new file mode 100644 index 000000000..ece9c94f3 --- /dev/null +++ b/test/test_ncrc.py @@ -0,0 +1,17 @@ +import unittest +import netCDF4 + +class NCRCTestCase(unittest.TestCase): + def setUp(self): + pass + + def tearDown(self): + pass + + def runTest(self): + """testing access of data over http using opendap""" + netCDF4.rc_set('foo','bar') + assert netCDF4.rc_get('foo') == 'bar' + +if __name__ == '__main__': + unittest.main() From c2074caec2b75c88b902db6fb6ab7b3135d1171d Mon Sep 17 00:00:00 2001 From: jswhit Date: Sat, 6 Jul 2024 13:44:46 -0600 Subject: [PATCH 1180/1504] update --- test/test_ncrc.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/test/test_ncrc.py b/test/test_ncrc.py index ece9c94f3..508a36227 100644 --- a/test/test_ncrc.py +++ b/test/test_ncrc.py @@ -1,5 +1,6 @@ import unittest import netCDF4 +from netCDF4 import __has_nc_rc_set__ class NCRCTestCase(unittest.TestCase): def setUp(self): @@ -9,9 +10,10 @@ def tearDown(self): pass def runTest(self): - """testing access of data over http using opendap""" - netCDF4.rc_set('foo','bar') - assert netCDF4.rc_get('foo') == 'bar' + """test rc_get, rc_set functions""" + if __has_nc_rc_set__: + netCDF4.rc_set('foo','bar') + assert netCDF4.rc_get('foo') == 'bar' if __name__ == '__main__': unittest.main() From 6ce9f48e631424264f385f4cd9fa758f23b478b4 Mon Sep 17 00:00:00 2001 From: jswhit Date: Sat, 6 Jul 2024 13:56:32 -0600 Subject: [PATCH 1181/1504] fix typo --- include/netcdf-compat.h | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/include/netcdf-compat.h b/include/netcdf-compat.h index b445d6922..d1144d979 100644 --- a/include/netcdf-compat.h +++ b/include/netcdf-compat.h @@ -60,7 +60,7 @@ static inline int nc_get_alignment(int* thresholdp, int* alignmentp) { #else #define HAS_NCRCSET 0 static inline int nc_rc_set(const char* key, const char* value) { return NC_EINVAL; } -static inline const char *nc_rc_set(const char* key) { return NC_EINVAL; } +static inline const char *nc_rc_get(const char* key) { return NC_EINVAL; } #endif #if NC_VERSION_GE(4, 4, 0) From 74c4f379adb65afa947acbb3dae669bbdead290b Mon Sep 17 00:00:00 2001 From: jswhit Date: Mon, 8 Jul 2024 11:15:30 -0600 Subject: [PATCH 1182/1504] add new functions to stub --- Changelog | 2 +- src/netCDF4/__init__.pyi | 5 ++++- 2 files changed, 5 insertions(+), 2 deletions(-) diff --git a/Changelog b/Changelog index 1b1157406..d4c5011f6 100644 --- a/Changelog +++ b/Changelog @@ -1,4 +1,4 @@ - version 1.7.2 (tag v1.7.2rel) + version 1.7.2 (not yet released) =============================== * add static type hints (PR #1302) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 413336f0e..61ea2aa10 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -14,7 +14,7 @@ __all__ = [ 'Dataset', 'Variable', 'Dimension', 'Group', 'MFDataset', 'MFTime', 'CompoundType', 'VLType', 'date2num', 'num2date', 'date2index', 'stringtochar', 'chartostring', 'stringtoarr', 'getlibversion', 'EnumType', 'get_chunk_cache', 'set_chunk_cache', - 'set_alignment', 'get_alignment' + 'set_alignment', 'get_alignment', 'nc_get', 'nc_set', ] __pdoc__ = {'utils': False} @@ -87,6 +87,7 @@ __has_blosc_support__: BoolInt __has_szip_support__: BoolInt __has_set_alignment__: BoolInt __has_ncfilter__: BoolInt +__has_nc_rc_set__: BoolInt is_native_little: bool is_native_big: bool default_encoding: Final = 'utf-8' @@ -624,6 +625,8 @@ def chartostring( ) -> npt.NDArray[np.str_] | npt.NDArray[np.bytes_]: ... def getlibversion() -> str: ... +def nc_get(key: str) -> str: ... +def nc_set(key: str, val: str): ... def set_alignment(threshold: int, alignment: int): ... def get_alignment() -> tuple[int, int]: ... From 4e4488c1d11a76c5fc63fa335e6eaf5793f5f6d7 Mon Sep 17 00:00:00 2001 From: jswhit Date: Mon, 8 Jul 2024 12:43:09 -0600 Subject: [PATCH 1183/1504] fixes for failing stubtest --- Changelog | 1 + src/netCDF4/__init__.py | 2 +- src/netCDF4/__init__.pyi | 6 +++--- src/netCDF4/_netCDF4.pyi | 3 ++- 4 files changed, 7 insertions(+), 5 deletions(-) diff --git a/Changelog b/Changelog index d4c5011f6..f1e82e2b3 100644 --- a/Changelog +++ b/Changelog @@ -1,6 +1,7 @@ version 1.7.2 (not yet released) =============================== * add static type hints (PR #1302) + * Expose nc_rc_set, nc_rc_get (via rc_set, rc_get module functions). (PR #1348) version 1.7.1 (tag v1.7.1rel) =============================== diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py index b14015254..e7e94d2cf 100644 --- a/src/netCDF4/__init__.py +++ b/src/netCDF4/__init__.py @@ -16,7 +16,7 @@ 'Dataset', 'Variable', 'Dimension', 'Group', 'MFDataset', 'MFTime', 'CompoundType', 'VLType', 'date2num', 'num2date', 'date2index', 'stringtochar', 'chartostring', 'stringtoarr', 'getlibversion', 'EnumType', 'get_chunk_cache', 'set_chunk_cache', - 'set_alignment', 'get_alignment', 'nc_get', 'nc_set', + 'set_alignment', 'get_alignment', 'rc_get', 'rc_set', ] __pdoc__ = {'utils': False} # if HDF5_PLUGIN_PATH not set, point to package path if plugins live there diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 61ea2aa10..fd9fb8957 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -14,7 +14,7 @@ __all__ = [ 'Dataset', 'Variable', 'Dimension', 'Group', 'MFDataset', 'MFTime', 'CompoundType', 'VLType', 'date2num', 'num2date', 'date2index', 'stringtochar', 'chartostring', 'stringtoarr', 'getlibversion', 'EnumType', 'get_chunk_cache', 'set_chunk_cache', - 'set_alignment', 'get_alignment', 'nc_get', 'nc_set', + 'set_alignment', 'get_alignment', 'rc_get', 'rc_set', ] __pdoc__ = {'utils': False} @@ -625,8 +625,8 @@ def chartostring( ) -> npt.NDArray[np.str_] | npt.NDArray[np.bytes_]: ... def getlibversion() -> str: ... -def nc_get(key: str) -> str: ... -def nc_set(key: str, val: str): ... +def rc_get(key: str) -> str: ... +def rc_set(key: str, val: str)-> None: ... def set_alignment(threshold: int, alignment: int): ... def get_alignment() -> tuple[int, int]: ... diff --git a/src/netCDF4/_netCDF4.pyi b/src/netCDF4/_netCDF4.pyi index 536d4f63b..304e50e69 100644 --- a/src/netCDF4/_netCDF4.pyi +++ b/src/netCDF4/_netCDF4.pyi @@ -6,13 +6,14 @@ from . import ( stringtoarr, getlibversion, EnumType, get_chunk_cache, set_chunk_cache, set_alignment, get_alignment, default_fillvals, default_encoding, NetCDF4MissingFeatureException, is_native_big, is_native_little, unicode_error, + rc_get, rc_set, __version__, __netcdf4libversion__, __hdf5libversion__, __has_rename_grp__, __has_nc_inq_path__, __has_nc_inq_format_extended__, __has_nc_open_mem__, __has_nc_create_mem__, __has_cdf5_format__, __has_parallel4_support__, __has_pnetcdf_support__, __has_parallel_support__, __has_quantization_support__, __has_zstandard_support__, __has_bzip2_support__, __has_blosc_support__, __has_szip_support__, - __has_set_alignment__, __has_ncfilter__ + __has_set_alignment__, __has_ncfilter__, __has_nc_rc_set__, ) From 28814f8a89df8d2929e4c0928eded20dd9aa3909 Mon Sep 17 00:00:00 2001 From: jswhit Date: Mon, 8 Jul 2024 14:00:21 -0600 Subject: [PATCH 1184/1504] fix stub for rc_set --- src/netCDF4/__init__.pyi | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index fd9fb8957..062384f01 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -626,7 +626,7 @@ def chartostring( def getlibversion() -> str: ... def rc_get(key: str) -> str: ... -def rc_set(key: str, val: str)-> None: ... +def rc_set(key: str, value: str)-> None: ... def set_alignment(threshold: int, alignment: int): ... def get_alignment() -> tuple[int, int]: ... From ab3e123f491949b0528b92f82aab0bff2bc9196a Mon Sep 17 00:00:00 2001 From: jswhit Date: Mon, 8 Jul 2024 21:16:49 -0600 Subject: [PATCH 1185/1504] bump version number --- src/netCDF4/_netCDF4.pyx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index c5431e8f3..97ecfe3e3 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1,4 +1,4 @@ -"""Version 1.7.1 +"""Version 1.7.2 ------------- # Introduction @@ -1272,7 +1272,7 @@ import sys import functools from typing import Union -__version__ = "1.7.1.post1" +__version__ = "1.7.2" # Initialize numpy import posixpath From c85e7cf0236274506534e4956c322af5b972f677 Mon Sep 17 00:00:00 2001 From: jswhit Date: Tue, 9 Jul 2024 10:07:04 -0600 Subject: [PATCH 1186/1504] fix docstring formatting --- src/netCDF4/_netCDF4.pyx | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 97ecfe3e3..ae1cca64e 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1320,7 +1320,7 @@ if __has_nc_rc_set__: def rc_get(key): """ -**`rc_key(key)`** +**```rc_get(key)```** Returns the internal netcdf-c rc table value corresponding to key. """ @@ -1337,7 +1337,7 @@ Returns the internal netcdf-c rc table value corresponding to key. def rc_set(key, value): """ -**`rc_set(key, value)`** +**```rc_set(key, value)```** Sets the internal netcdf-c rc table value corresponding to key. """ @@ -1371,7 +1371,7 @@ def _gethdf5libversion(): def getlibversion(): """ -**`getlibversion()`** +**```getlibversion()```** returns a string describing the version of the netcdf library used to build the module, and when it was built. @@ -1380,7 +1380,7 @@ used to build the module, and when it was built. def get_chunk_cache(): """ -**`get_chunk_cache()`** +**```get_chunk_cache()```** return current netCDF chunk cache information in a tuple (size,nelems,preemption). See netcdf C library documentation for `nc_get_chunk_cache` for @@ -1396,7 +1396,7 @@ details. Values can be reset with `set_chunk_cache`.""" def set_chunk_cache(size=None,nelems=None,preemption=None): """ -**`set_chunk_cache(self,size=None,nelems=None,preemption=None)`** +**```set_chunk_cache(size=None,nelems=None,preemption=None)```** change netCDF4 chunk cache settings. See netcdf C library documentation for `nc_set_chunk_cache` for @@ -1424,7 +1424,7 @@ details.""" def get_alignment(): - """**`get_alignment()`** + """**```get_alignment()```** return current netCDF alignment within HDF5 files in a tuple (threshold,alignment). See netcdf C library documentation for @@ -1448,7 +1448,7 @@ def get_alignment(): def set_alignment(threshold, alignment): - """**`set_alignment(threshold,alignment)`** + """**```set_alignment(threshold,alignment)```** Change the HDF5 file alignment. See netcdf C library documentation for `nc_set_alignment` for From b60aee061a871e7b7e412a3b8cd667e3dda31a9a Mon Sep 17 00:00:00 2001 From: jswhit Date: Tue, 9 Jul 2024 10:08:58 -0600 Subject: [PATCH 1187/1504] update docs --- docs/index.html | 126 +++++++++++++++++++++++++++--------------------- 1 file changed, 72 insertions(+), 54 deletions(-) diff --git a/docs/index.html b/docs/index.html index 6971ceb5b..730c955d7 100644 --- a/docs/index.html +++ b/docs/index.html @@ -2,19 +2,22 @@ - - + + netCDF4 API documentation - - - - - - + + + + + + - - + +
      @@ -23,7 +26,7 @@

      Package netCDF4

      -

      Version 1.7.0

      +

      Version 1.7.2

      Introduction

      netcdf4-python is a Python interface to the netCDF C library.

      netCDF version 4 has many features @@ -118,8 +121,8 @@

      Creating/Opening/Closing a netCDF If the file is open for write access (mode='w', 'r+' or 'a'), you may write any type of data including new dimensions, groups, variables and attributes. -netCDF files come in five flavors (NETCDF3_CLASSIC, -NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF4_CLASSIC<code>, and </code>NETCDF4). +netCDF files come in five flavors (NETCDF3_CLASSIC, +NETCDF3_64BIT_OFFSET, NETCDF3_64BIT_DATA, NETCDF4_CLASSIC, and NETCDF4). NETCDF3_CLASSIC was the original netcdf binary format, and was limited to file sizes less than 2 Gb. NETCDF3_64BIT_OFFSET was introduced in version 3.6.0 of the library, and extended the original binary format @@ -1261,7 +1264,7 @@

      Functions

      def get_alignment()
      -

      get_alignment()

      +

      get_alignment()

      return current netCDF alignment within HDF5 files in a tuple (threshold,alignment). See netcdf C library documentation for nc_get_alignment for details. Values can be reset with @@ -1272,7 +1275,7 @@

      Functions

      def get_chunk_cache()
      -

      get_chunk_cache()

      +

      get_chunk_cache()

      return current netCDF chunk cache information in a tuple (size,nelems,preemption). See netcdf C library documentation for nc_get_chunk_cache for details. Values can be reset with set_chunk_cache().

      @@ -1281,7 +1284,7 @@

      Functions

      def getlibversion()
      -

      getlibversion()

      +

      getlibversion()

      returns a string describing the version of the netcdf library used to build the module, and when it was built.

      @@ -1340,11 +1343,25 @@

      Functions

      do not contain a time-zone offset, even if the specified units contains one.

      +
      +def rc_get(key) +
      +
      +

      rc_get(key)

      +

      Returns the internal netcdf-c rc table value corresponding to key.

      +
      +
      +def rc_set(key, value) +
      +
      +

      rc_set(key, value)

      +

      Sets the internal netcdf-c rc table value corresponding to key.

      +
      def set_alignment(threshold, alignment)
      -

      set_alignment()(threshold,alignment)

      +

      set_alignment(threshold,alignment)

      Change the HDF5 file alignment. See netcdf C library documentation for nc_set_alignment for details.

      @@ -1354,7 +1371,7 @@

      Functions

      def set_chunk_cache(size=None, nelems=None, preemption=None)
      -

      set_chunk_cache(self,size=None,nelems=None,preemption=None)

      +

      set_chunk_cache(size=None,nelems=None,preemption=None)

      change netCDF4 chunk cache settings. See netcdf C library documentation for nc_set_chunk_cache for details.

      @@ -1415,12 +1432,12 @@

      Classes

      the user.

      __init__(group, datatype, datatype_name)

      CompoundType constructor.

      -

      group: Group instance to associate with the compound datatype.

      -

      datatype: A numpy dtype object describing a structured (a.k.a record) +

      grp: Group instance to associate with the compound datatype.

      +

      dt: A numpy dtype object describing a structured (a.k.a record) array. Can be composed of homogeneous numeric or character data types, or other structured array data types.

      -

      datatype_name: a Python string containing a description of the +

      dtype_name: a Python string containing a description of the compound data type.

      Note 1: When creating nested compound data types, the inner compound data types must already be associated with CompoundType @@ -1433,15 +1450,15 @@

      Instance variables

      var dtype
      -

      Return an attribute of instance, which is of type owner.

      +
      var dtype_view
      -

      Return an attribute of instance, which is of type owner.

      +
      var name
      -

      Return an attribute of instance, which is of type owner.

      +
      @@ -1623,39 +1640,39 @@

      Instance variables

      var auto_complex
      -

      Return an attribute of instance, which is of type owner.

      +
      var cmptypes
      -

      Return an attribute of instance, which is of type owner.

      +
      var data_model
      -

      Return an attribute of instance, which is of type owner.

      +
      var dimensions
      -

      Return an attribute of instance, which is of type owner.

      +
      var disk_format
      -

      Return an attribute of instance, which is of type owner.

      +
      var enumtypes
      -

      Return an attribute of instance, which is of type owner.

      +
      var file_format
      -

      Return an attribute of instance, which is of type owner.

      +
      var groups
      -

      Return an attribute of instance, which is of type owner.

      +
      var keepweakref
      -

      Return an attribute of instance, which is of type owner.

      +
      var name
      @@ -1663,19 +1680,19 @@

      Instance variables

      var parent
      -

      Return an attribute of instance, which is of type owner.

      +
      var path
      -

      Return an attribute of instance, which is of type owner.

      +
      var variables
      -

      Return an attribute of instance, which is of type owner.

      +
      var vltypes
      -

      Return an attribute of instance, which is of type owner.

      +

      Methods

      @@ -2264,15 +2281,15 @@

      Instance variables

      var dtype
      -

      Return an attribute of instance, which is of type owner.

      +
      var enum_dict
      -

      Return an attribute of instance, which is of type owner.

      +
      var name
      -

      Return an attribute of instance, which is of type owner.

      +
      @@ -2476,11 +2493,11 @@

      Instance variables

      var dtype
      -

      Return an attribute of instance, which is of type owner.

      +
      var name
      -

      Return an attribute of instance, which is of type owner.

      +
      @@ -2668,15 +2685,15 @@

      Instance variables

      var always_mask
      -

      Return an attribute of instance, which is of type owner.

      +
      var auto_complex
      -

      Return an attribute of instance, which is of type owner.

      +
      var chartostring
      -

      Return an attribute of instance, which is of type owner.

      +
      var datatype
      @@ -2691,11 +2708,11 @@

      Instance variables

      var dtype
      -

      Return an attribute of instance, which is of type owner.

      +
      var mask
      -

      Return an attribute of instance, which is of type owner.

      +
      var name
      @@ -2703,11 +2720,11 @@

      Instance variables

      var ndim
      -

      Return an attribute of instance, which is of type owner.

      +
      var scale
      -

      Return an attribute of instance, which is of type owner.

      +
      var shape
      @@ -3049,10 +3066,9 @@

      Methods

      - \ No newline at end of file + From 6d399a92039062c82003645b7f92b422d037a5bf Mon Sep 17 00:00:00 2001 From: jswhit Date: Tue, 9 Jul 2024 10:42:49 -0600 Subject: [PATCH 1188/1504] check for NULL pointer from nc_rc_get --- src/netCDF4/__init__.pyi | 2 +- src/netCDF4/_netCDF4.pyx | 7 ++++++- 2 files changed, 7 insertions(+), 2 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 062384f01..1a709dd35 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -625,7 +625,7 @@ def chartostring( ) -> npt.NDArray[np.str_] | npt.NDArray[np.bytes_]: ... def getlibversion() -> str: ... -def rc_get(key: str) -> str: ... +def rc_get(key: str) -> str | None: ... def rc_set(key: str, value: str)-> None: ... def set_alignment(threshold: int, alignment: int): ... diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index ae1cca64e..b912cdfb6 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1326,10 +1326,15 @@ Returns the internal netcdf-c rc table value corresponding to key. """ cdef int ierr cdef char *keyc + cdef char *valc if __has_nc_rc_set__: bytestr = _strencode(_tostr(key)) keyc = bytestr - return (nc_rc_get(keyc)).decode('utf-8') + valc = nc_rc_get(keyc) + if valc is NULL: + return None + else: + return valc.decode('utf-8') else: raise RuntimeError( "This function requires netcdf-c 4.9.0+ to be used at compile time" From 180584a6c1dcb9cb692730e8a2600463601c1de0 Mon Sep 17 00:00:00 2001 From: jswhit Date: Tue, 9 Jul 2024 10:43:31 -0600 Subject: [PATCH 1189/1504] update test --- test/test_ncrc.py | 1 + 1 file changed, 1 insertion(+) diff --git a/test/test_ncrc.py b/test/test_ncrc.py index 508a36227..02cd168c4 100644 --- a/test/test_ncrc.py +++ b/test/test_ncrc.py @@ -14,6 +14,7 @@ def runTest(self): if __has_nc_rc_set__: netCDF4.rc_set('foo','bar') assert netCDF4.rc_get('foo') == 'bar' + assert netCDF4.rc_get('bar') == None if __name__ == '__main__': unittest.main() From 851d45327d476f59650b66afe585a361d96ddec7 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Thu, 11 Jul 2024 09:08:50 -0700 Subject: [PATCH 1190/1504] Reformat type stubs with ruff to 130 chars --- src/netCDF4/__init__.pyi | 227 +++++++++++++++------------------------ src/netCDF4/_netCDF4.pyi | 58 +++++++--- 2 files changed, 133 insertions(+), 152 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 413336f0e..698185a5f 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -1,23 +1,52 @@ - +import datetime as dt import os import sys -import datetime as dt -from typing import (Any, Callable, Final, Generic, Iterable, Literal, Mapping, - NoReturn, Self, Sequence, TypeAlias, TypedDict, TypeVar, Union, overload) -from typing_extensions import Buffer +from typing import ( + Any, + Callable, + Final, + Generic, + Iterable, + Literal, + Mapping, + NoReturn, + Self, + Sequence, + TypeAlias, + TypedDict, + TypeVar, + Union, + overload, +) import cftime import numpy as np import numpy.typing as npt +from typing_extensions import Buffer __all__ = [ - 'Dataset', 'Variable', 'Dimension', 'Group', 'MFDataset', 'MFTime', 'CompoundType', - 'VLType', 'date2num', 'num2date', 'date2index', 'stringtochar', 'chartostring', - 'stringtoarr', 'getlibversion', 'EnumType', 'get_chunk_cache', 'set_chunk_cache', - 'set_alignment', 'get_alignment' + "Dataset", + "Variable", + "Dimension", + "Group", + "MFDataset", + "MFTime", + "CompoundType", + "VLType", + "date2num", + "num2date", + "date2index", + "stringtochar", + "chartostring", + "stringtoarr", + "getlibversion", + "EnumType", + "get_chunk_cache", + "set_chunk_cache", + "set_alignment", + "get_alignment", ] -__pdoc__ = {'utils': False} - +__pdoc__ = {"utils": False} if sys.version_info >= (3, 10): from types import EllipsisType @@ -26,10 +55,8 @@ if sys.version_info >= (3, 10): elif not TYPE_CHECKING: ellipsis = type(Ellipsis) # keeps ruff happy until ruff uses typeshed - _DatatypeStrOptions: TypeAlias = Literal[ - 'S1', 'c', 'i1', 'b', 'B', 'u1', 'i2', 'h', 's', 'u2', 'i4', - 'i', 'l', 'u4', 'i8', 'u8', 'f4', 'f', 'f8', 'd', 'c8', 'c16' + "S1", "c", "i1", "b", "B", "u1", "i2", "h", "s", "u2", "i4", "i", "l", "u4", "i8", "u8", "f4", "f", "f8", "d", "c8", "c16" ] _DatatypeNCOptions: TypeAlias = Union[CompoundType, VLType, EnumType] DatatypeOptions: TypeAlias = Union[_DatatypeStrOptions, _DatatypeNCOptions, npt.DTypeLike] @@ -38,21 +65,16 @@ T_DatatypeNC = TypeVar("T_DatatypeNC", CompoundType, VLType, EnumType) DimensionsOptions: TypeAlias = Union[str, bytes, Dimension, Iterable[Union[str, bytes, Dimension]]] CompressionOptions: TypeAlias = Literal[ - 'zlib', 'szip', 'zstd', 'blosc_lz','blosc_lz4', - 'blosc_lz4hc', 'blosc_zlib', 'blosc_zstd' + "zlib", "szip", "zstd", "blosc_lz", "blosc_lz4", "blosc_lz4hc", "blosc_zlib", "blosc_zstd" ] CompressionLevelOptions: TypeAlias = Literal[0, 1, 2, 3, 4, 5, 6, 7, 8, 9] -AccessModeOptions: TypeAlias = Literal['r', 'w', 'r+', 'a', 'x', 'rs', 'ws', 'r+s', 'as'] -FormatOptions: TypeAlias = Literal[ - 'NETCDF4', 'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC', - 'NETCDF3_64BIT_OFFSET', 'NETCDF3_64BIT_DATA' -] -DiskFormatOptions: TypeAlias = Literal['NETCDF3', 'HDF5', 'HDF4', 'PNETCDF', 'DAP2', 'DAP4', 'UNDEFINED'] -QuantizeOptions: TypeAlias = Literal['BitGroom', 'BitRound', 'GranularBitRound'] -EndianOptions: TypeAlias = Literal['native', 'little', 'big'] +AccessModeOptions: TypeAlias = Literal["r", "w", "r+", "a", "x", "rs", "ws", "r+s", "as"] +FormatOptions: TypeAlias = Literal["NETCDF4", "NETCDF4_CLASSIC", "NETCDF3_CLASSIC", "NETCDF3_64BIT_OFFSET", "NETCDF3_64BIT_DATA"] +DiskFormatOptions: TypeAlias = Literal["NETCDF3", "HDF5", "HDF4", "PNETCDF", "DAP2", "DAP4", "UNDEFINED"] +QuantizeOptions: TypeAlias = Literal["BitGroom", "BitRound", "GranularBitRound"] +EndianOptions: TypeAlias = Literal["native", "little", "big"] CalendarOptions: TypeAlias = Literal[ - 'standard', 'gregorian', 'proleptic_gregorian' 'noleap', - '365_day', '360_day', 'julian', 'all_leap', '366_day' + "standard", "gregorian", "proleptic_gregorian" "noleap", "365_day", "360_day", "julian", "all_leap", "366_day" ] BoolInt: TypeAlias = Literal[0, 1] @@ -89,11 +111,10 @@ __has_set_alignment__: BoolInt __has_ncfilter__: BoolInt is_native_little: bool is_native_big: bool -default_encoding: Final = 'utf-8' -unicode_error: Final = 'replace' +default_encoding: Final = "utf-8" +unicode_error: Final = "replace" default_fillvals: dict[str, int | float | str] - # date2index, date2num, and num2date are actually provided by cftime and if stubs for # cftime are completed these should be removed. def date2index( @@ -119,19 +140,17 @@ def num2date( has_year_zero: bool | None = None, ) -> dt.datetime | DateTimeArray: ... - class BloscInfo(TypedDict): compressor: Literal["blosc_lz", "blosc_lz4", "blosc_lz4hc", "blosc_zlib", "blosc_zstd"] shuffle: Literal[0, 1, 2] - class SzipInfo(TypedDict): coding: Literal["nn", "ec"] pixels_per_block: Literal[4, 8, 16, 32] - class FiltersDict(TypedDict): """Dict returned from netCDF4.Variable.filters()""" + zlib: bool szip: Literal[False] | SzipInfo zstd: bool @@ -141,18 +160,16 @@ class FiltersDict(TypedDict): complevel: int fletcher32: bool - class NetCDF4MissingFeatureException(Exception): def __init__(self, feature: str, version: str): ... - class Dataset: def __init__( self, filename: str | os.PathLike, - mode: AccessModeOptions = 'r', + mode: AccessModeOptions = "r", clobber: bool = True, - format: FormatOptions = 'NETCDF4', + format: FormatOptions = "NETCDF4", diskless: bool = False, persist: bool = False, keepweakref: bool = False, @@ -162,9 +179,8 @@ class Dataset: comm: Any = None, info: Any = None, auto_complex: bool = False, - **kwargs: Any + **kwargs: Any, ): ... - @property def name(self) -> str: ... @property @@ -197,16 +213,14 @@ class Dataset: def _ncstring_attrs__(self) -> bool: ... @property def __orthogonal_indexing__(self) -> bool: ... - def filepath(self, encoding: str | None = None) -> str: ... def isopen(self) -> bool: ... def close(self) -> memoryview: ... # only if writing and memory != None, but otherwise people ignore the return None anyway def sync(self) -> None: ... def set_fill_on(self) -> None: ... def set_fill_off(self) -> None: ... - def createDimension(self, dimname: str, size: int | None = None) -> Dimension: ... - def renameDimension( self, oldname: str, newname: str) -> None: ... + def renameDimension(self, oldname: str, newname: str) -> None: ... @overload def createVariable( # type: ignore self, @@ -217,18 +231,18 @@ class Dataset: zlib: bool = False, complevel: CompressionLevelOptions | None = 4, shuffle: bool = True, - szip_coding: Literal['nn', 'ec'] = 'nn', + szip_coding: Literal["nn", "ec"] = "nn", szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, blosc_shuffle: Literal[0, 1, 2] = 1, fletcher32: bool = False, contiguous: bool = False, chunksizes: int | None = None, - endian: EndianOptions = 'native', + endian: EndianOptions = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeOptions = 'BitGroom', + quantize_mode: QuantizeOptions = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, - chunk_cache: int | None = None + chunk_cache: int | None = None, ) -> Variable[T_DatatypeNC]: ... @overload def createVariable( @@ -240,22 +254,21 @@ class Dataset: zlib: bool = False, complevel: CompressionLevelOptions | None = 4, shuffle: bool = True, - szip_coding: Literal['nn', 'ec'] = 'nn', + szip_coding: Literal["nn", "ec"] = "nn", szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, blosc_shuffle: Literal[0, 1, 2] = 1, fletcher32: bool = False, contiguous: bool = False, chunksizes: int | None = None, - endian: EndianOptions = 'native', + endian: EndianOptions = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeOptions = 'BitGroom', + quantize_mode: QuantizeOptions = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, - chunk_cache: int | None = None + chunk_cache: int | None = None, ) -> Variable[np.dtype]: ... def renameVariable(self, oldname: str, newname: str) -> None: ... def createGroup(self, groupname: str) -> Group: ... - def renameGroup(self, oldname: str, newname: str) -> None: ... def renameAttribute(self, oldname: str, newname: str) -> None: ... def createCompoundType( @@ -265,12 +278,11 @@ class Dataset: def createEnumType( self, datatype: np.dtype[np.integer] | type[np.integer] | type[int], datatype_name: str, enum_dict: dict[str, int] ) -> EnumType: ... - def ncattrs(self) -> list[str]: ... def setncattr_string(self, name: str, value: Any) -> None: ... def setncattr(self, name: str, value: Any) -> None: ... def setncatts(self, attdict: Mapping[str, Any]) -> None: ... - def getncattr(self, name: str, encoding: str = 'utf-8') -> Any: ... + def getncattr(self, name: str, encoding: str = "utf-8") -> Any: ... def delncattr(self, name: str) -> None: ... def set_auto_chartostring(self, value: bool) -> None: ... def set_auto_maskandscale(self, value: bool) -> None: ... @@ -279,35 +291,18 @@ class Dataset: def set_always_mask(self, value: bool) -> None: ... def set_ncstring_attrs(self, value: bool) -> None: ... def get_variables_by_attributes(self, **kwargs: Callable[[Any], bool] | Any) -> list[Variable]: ... - @staticmethod def fromcdl( - cdlfilename: str, - ncfilename: str | None = None, - mode: AccessModeOptions = 'a', - format: FormatOptions = 'NETCDF4' + cdlfilename: str, ncfilename: str | None = None, mode: AccessModeOptions = "a", format: FormatOptions = "NETCDF4" ) -> Dataset: ... @overload - def tocdl( - self, - coordvars: bool = False, - data: bool = False, - outfile: None = None - ) -> str: ... + def tocdl(self, coordvars: bool = False, data: bool = False, outfile: None = None) -> str: ... @overload - def tocdl( - self, - coordvars: bool = False, - data: bool = False, - *, - outfile: str | os.PathLike - ) -> None: ... - + def tocdl(self, coordvars: bool = False, data: bool = False, *, outfile: str | os.PathLike) -> None: ... def has_blosc_filter(self) -> bool: ... def has_zstd_filter(self) -> bool: ... def has_bzip2_filter(self) -> bool: ... def has_szip_filter(self) -> bool: ... - def __getitem__(self, elem: str) -> Any: ... # should be Group | Variable, but this causes too many problems def __setattr__(self, name: str, value: Any) -> None: ... def __getattr__(self, name: str) -> Any: ... @@ -317,29 +312,21 @@ class Dataset: def __enter__(self) -> Self: ... def __exit__(self, atype, value, traceback) -> None: ... - class Group(Dataset): def __init__(self, parent: Dataset, name: str, **kwargs: Any) -> None: ... - def close(self) -> NoReturn: ... - class Dimension: def __init__(self, grp: Dataset, name: str, size: int | None = None, **kwargs: Any) -> None: ... - @property def name(self) -> str: ... @property def size(self) -> int: ... - def group(self) -> Dataset: ... def isunlimited(self) -> bool: ... - def __len__(self) -> int: ... - class Variable(Generic[T_Datatype]): - @overload def __new__( # type: ignore self, @@ -351,21 +338,20 @@ class Variable(Generic[T_Datatype]): zlib: bool = False, complevel: CompressionLevelOptions | None = 4, shuffle: bool = True, - szip_coding: Literal['nn', 'ec'] = 'nn', + szip_coding: Literal["nn", "ec"] = "nn", szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, blosc_shuffle: Literal[0, 1, 2] = 1, fletcher32: bool = False, contiguous: bool = False, chunksizes: Sequence[int] | None = None, - endian: EndianOptions = 'native', + endian: EndianOptions = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeOptions = 'BitGroom', + quantize_mode: QuantizeOptions = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, - **kwargs: Any + **kwargs: Any, ) -> Variable[T_DatatypeNC]: ... - @overload def __new__( self, @@ -377,22 +363,20 @@ class Variable(Generic[T_Datatype]): zlib: bool = False, complevel: CompressionLevelOptions | None = 4, shuffle: bool = True, - szip_coding: Literal['nn', 'ec'] = 'nn', + szip_coding: Literal["nn", "ec"] = "nn", szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, blosc_shuffle: Literal[0, 1, 2] = 1, fletcher32: bool = False, contiguous: bool = False, chunksizes: Sequence[int] | None = None, - endian: EndianOptions = 'native', + endian: EndianOptions = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeOptions = 'BitGroom', + quantize_mode: QuantizeOptions = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, - **kwargs: Any + **kwargs: Any, ) -> Variable[np.dtype]: ... - - def __init__( self, grp: Dataset, @@ -403,21 +387,20 @@ class Variable(Generic[T_Datatype]): zlib: bool = False, complevel: CompressionLevelOptions | None = 4, shuffle: bool = True, - szip_coding: Literal['nn', 'ec'] = 'nn', + szip_coding: Literal["nn", "ec"] = "nn", szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, blosc_shuffle: Literal[0, 1, 2] = 1, fletcher32: bool = False, contiguous: bool = False, chunksizes: Sequence[int] | None = None, - endian: EndianOptions = 'native', + endian: EndianOptions = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeOptions = 'BitGroom', + quantize_mode: QuantizeOptions = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, - **kwargs: Any + **kwargs: Any, ) -> None: ... - @property def name(self) -> str: ... @property @@ -442,24 +425,20 @@ class Variable(Generic[T_Datatype]): def always_mask(self) -> bool: ... @property def __orthogonal_indexing__(self) -> bool: ... - def group(self) -> Dataset: ... def ncattrs(self) -> list[str]: ... def setncattr(self, name: str, value: Any) -> None: ... def setncattr_string(self, name: str, value: Any) -> None: ... def setncatts(self, attdict: Mapping[str, Any]) -> None: ... - def getncattr(self, name: str, encoding='utf-8'): ... + def getncattr(self, name: str, encoding="utf-8"): ... def delncattr(self, name: str) -> None: ... def filters(self) -> FiltersDict: ... def quantization(self) -> tuple[int, QuantizeOptions] | None: ... def endian(self) -> EndianOptions: ... - def chunking(self) -> Literal['contiguous'] | list[int]: ... + def chunking(self) -> Literal["contiguous"] | list[int]: ... def get_var_chunk_cache(self) -> tuple[int, int, float]: ... def set_var_chunk_cache( - self, - size: int | None = None, - nelems: int | None = None, - preemption: float | None = None + self, size: int | None = None, nelems: int | None = None, preemption: float | None = None ) -> None: ... def renameAttribute(self, oldname: str, newname: str) -> None: ... def assignValue(self, val: Any) -> None: ... @@ -473,7 +452,6 @@ class Variable(Generic[T_Datatype]): def set_ncstring_attrs(self, ncstring_attrs: bool) -> None: ... def set_collective(self, value: bool) -> None: ... def get_dims(self) -> tuple[Dimension, ...]: ... - def __delattr__(self, name: str) -> None: ... def __setattr__(self, name: str, value: Any) -> None: ... def __getattr__(self, name: str) -> Any: ... @@ -482,7 +460,6 @@ class Variable(Generic[T_Datatype]): def __array__(self) -> np.ndarray: ... def __len__(self) -> int: ... - class CompoundType: dtype: np.dtype dtype_view: np.dtype @@ -491,19 +468,15 @@ class CompoundType: def __init__( self, grp: Dataset, dt: npt.DTypeLike | Sequence[tuple[str, npt.DTypeLike]], dtype_name: str, **kwargs: Any ) -> None: ... - def __reduce__(self) -> NoReturn: ... - class VLType: dtype: np.dtype name: str | None def __init__(self, grp: Dataset, dt: npt.DTypeLike, dtype_name: str, **kwargs: Any) -> None: ... - def __reduce__(self) -> NoReturn: ... - class EnumType: dtype: np.dtype[np.integer] name: str @@ -515,12 +488,10 @@ class EnumType: dt: np.dtype[np.integer] | type[np.integer] | type[int] | str, dtype_name: str, enum_dict: Mapping[str, int], - **kwargs: Any + **kwargs: Any, ) -> None: ... - def __reduce__(self) -> NoReturn: ... - class MFDataset(Dataset): def __init__( self, @@ -528,27 +499,21 @@ class MFDataset(Dataset): check: bool = False, aggdim: str | None = None, exclude: Sequence[str] = [], - master_file: str | os.PathLike | None = None + master_file: str | os.PathLike | None = None, ) -> None: ... - @property def dimensions(self) -> dict[str, Dimension]: ... # this should be: dict[str, Dimension | _Dimension] @property def variables(self) -> dict[str, Variable[Any]]: ... # this should be: dict[str, _Variable[Any] | _Variable] - class _Dimension: dimlens: list[int] dimtolen: int - def __init__( - self, dimname: str, dim: Dimension, dimlens: list[int], dimtotlen: int - ) -> None: ... - + def __init__(self, dimname: str, dim: Dimension, dimlens: list[int], dimtotlen: int) -> None: ... def __len__(self) -> int: ... def isunlimited(self) -> Literal[True]: ... - class _Variable: dimensions: tuple[str, ...] dtype: np.dtype | type[str] @@ -562,7 +527,6 @@ class _Variable: def ndim(self) -> int: ... @property def name(self) -> str: ... - def typecode(self) -> np.dtype | type[str]: ... def ncattrs(self) -> list[str]: ... def _shape(self) -> tuple[int, ...]: ... @@ -571,30 +535,22 @@ class _Variable: def set_auto_mask(self, val: bool) -> None: ... def set_auto_scale(self, val: bool) -> None: ... def set_always_mask(self, val: bool) -> None: ... - def __getattr__(self, name: str) -> Any: ... def __getitem__(self, elem: GetSetItemKey) -> Any: ... def __len__(self) -> int: ... - class MFTime(_Variable): calendar: CalendarOptions | None units: str | None - def __init__( - self, - time: Variable, - units: str | None = None, - calendar: CalendarOptions | None = None - ): ... + def __init__(self, time: Variable, units: str | None = None, calendar: CalendarOptions | None = None): ... def __getitem__(self, elem: GetSetItemKey) -> np.ndarray: ... - @overload def stringtoarr( string: str, NUMCHARS: int, - dtype: Literal["S"] | np.dtype[np.bytes_]= "S", + dtype: Literal["S"] | np.dtype[np.bytes_] = "S", ) -> npt.NDArray[np.bytes_]: ... @overload def stringtoarr( @@ -622,15 +578,8 @@ def chartostring( b: npt.NDArray[np.character], encoding: str = ..., ) -> npt.NDArray[np.str_] | npt.NDArray[np.bytes_]: ... - def getlibversion() -> str: ... - def set_alignment(threshold: int, alignment: int): ... def get_alignment() -> tuple[int, int]: ... - -def set_chunk_cache( - size: int | None = None, - nelems: int | None = None, - preemption: float | None = None -) -> None: ... +def set_chunk_cache(size: int | None = None, nelems: int | None = None, preemption: float | None = None) -> None: ... def get_chunk_cache() -> tuple[int, int, float]: ... diff --git a/src/netCDF4/_netCDF4.pyi b/src/netCDF4/_netCDF4.pyi index 536d4f63b..5c407a9dc 100644 --- a/src/netCDF4/_netCDF4.pyi +++ b/src/netCDF4/_netCDF4.pyi @@ -1,19 +1,51 @@ # The definitions are intendionally done in the __init__. # This file only exists in case someone imports from netCDF4._netCDF4 from . import ( - Dataset, Variable, Dimension, Group, MFDataset, MFTime, CompoundType, - VLType, date2num, num2date, date2index, stringtochar, chartostring, - stringtoarr, getlibversion, EnumType, get_chunk_cache, set_chunk_cache, - set_alignment, get_alignment, default_fillvals, default_encoding, - NetCDF4MissingFeatureException, is_native_big, is_native_little, unicode_error, - __version__, __netcdf4libversion__, __hdf5libversion__, __has_rename_grp__, - __has_nc_inq_path__, __has_nc_inq_format_extended__, __has_nc_open_mem__, - __has_nc_create_mem__, __has_cdf5_format__, __has_parallel4_support__, - __has_pnetcdf_support__, __has_parallel_support__, - __has_quantization_support__, __has_zstandard_support__, - __has_bzip2_support__, __has_blosc_support__, __has_szip_support__, - __has_set_alignment__, __has_ncfilter__ + CompoundType, + Dataset, + Dimension, + EnumType, + Group, + MFDataset, + MFTime, + NetCDF4MissingFeatureException, + Variable, + VLType, + __has_blosc_support__, + __has_bzip2_support__, + __has_cdf5_format__, + __has_nc_create_mem__, + __has_nc_inq_format_extended__, + __has_nc_inq_path__, + __has_nc_open_mem__, + __has_ncfilter__, + __has_parallel4_support__, + __has_parallel_support__, + __has_pnetcdf_support__, + __has_quantization_support__, + __has_rename_grp__, + __has_set_alignment__, + __has_szip_support__, + __has_zstandard_support__, + __hdf5libversion__, + __netcdf4libversion__, + __version__, + chartostring, + date2index, + date2num, + default_encoding, + default_fillvals, + get_alignment, + get_chunk_cache, + getlibversion, + is_native_big, + is_native_little, + num2date, + set_alignment, + set_chunk_cache, + stringtoarr, + stringtochar, + unicode_error, ) - def dtype_is_complex(dtype: str) -> bool: ... From 5098b5e99249de4a30062daaf775f77b9ab0a3b1 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Thu, 11 Jul 2024 09:18:50 -0700 Subject: [PATCH 1191/1504] Import typing.TYPE_CHECKING, import Self and TypeAlias from typing_extensions for 3.8 compat --- src/netCDF4/__init__.pyi | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 698185a5f..f484b5629 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -2,6 +2,7 @@ import datetime as dt import os import sys from typing import ( + TYPE_CHECKING, Any, Callable, Final, @@ -10,9 +11,7 @@ from typing import ( Literal, Mapping, NoReturn, - Self, Sequence, - TypeAlias, TypedDict, TypeVar, Union, @@ -22,7 +21,7 @@ from typing import ( import cftime import numpy as np import numpy.typing as npt -from typing_extensions import Buffer +from typing_extensions import Buffer, Self, TypeAlias __all__ = [ "Dataset", From c45529d41f143bd833691ba130cc9b7e082b9a55 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Thu, 11 Jul 2024 09:20:28 -0700 Subject: [PATCH 1192/1504] Add missing comma to strings in CalendarOptions --- src/netCDF4/__init__.pyi | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index f484b5629..ed8b516bf 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -73,7 +73,7 @@ DiskFormatOptions: TypeAlias = Literal["NETCDF3", "HDF5", "HDF4", "PNETCDF", "DA QuantizeOptions: TypeAlias = Literal["BitGroom", "BitRound", "GranularBitRound"] EndianOptions: TypeAlias = Literal["native", "little", "big"] CalendarOptions: TypeAlias = Literal[ - "standard", "gregorian", "proleptic_gregorian" "noleap", "365_day", "360_day", "julian", "all_leap", "366_day" + "standard", "gregorian", "proleptic_gregorian", "noleap", "365_day", "360_day", "julian", "all_leap", "366_day" ] BoolInt: TypeAlias = Literal[0, 1] From 361ead079d503f1b74d93929cb86bdb8eaf83225 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Thu, 11 Jul 2024 09:24:18 -0700 Subject: [PATCH 1193/1504] dtype_is_complex is publicly available under the netCDF4 module due to 'from ... import *' without '__all__' in _netCDF4.pyx --- src/netCDF4/__init__.pyi | 4 ++++ src/netCDF4/_netCDF4.pyi | 3 +-- 2 files changed, 5 insertions(+), 2 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index ed8b516bf..cf544575a 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -162,6 +162,10 @@ class FiltersDict(TypedDict): class NetCDF4MissingFeatureException(Exception): def __init__(self, feature: str, version: str): ... + +def dtype_is_complex(dtype: str) -> bool: ... + + class Dataset: def __init__( self, diff --git a/src/netCDF4/_netCDF4.pyi b/src/netCDF4/_netCDF4.pyi index 5c407a9dc..f649647fe 100644 --- a/src/netCDF4/_netCDF4.pyi +++ b/src/netCDF4/_netCDF4.pyi @@ -35,6 +35,7 @@ from . import ( date2num, default_encoding, default_fillvals, + dtype_is_complex, get_alignment, get_chunk_cache, getlibversion, @@ -47,5 +48,3 @@ from . import ( stringtochar, unicode_error, ) - -def dtype_is_complex(dtype: str) -> bool: ... From 147337d55c804daa22b22e9c78801af31c1b6be0 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Thu, 11 Jul 2024 09:29:38 -0700 Subject: [PATCH 1194/1504] minor whitespace --- src/netCDF4/__init__.pyi | 2 -- 1 file changed, 2 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index cf544575a..6be7c9f3a 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -162,10 +162,8 @@ class FiltersDict(TypedDict): class NetCDF4MissingFeatureException(Exception): def __init__(self, feature: str, version: str): ... - def dtype_is_complex(dtype: str) -> bool: ... - class Dataset: def __init__( self, From 03e57b1f713dd6d6fcf3930f2cdb750396ba783c Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Thu, 11 Jul 2024 09:31:14 -0700 Subject: [PATCH 1195/1504] Use cls instead of self in __new__ --- src/netCDF4/__init__.pyi | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 6be7c9f3a..efb1c7780 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -329,8 +329,8 @@ class Dimension: class Variable(Generic[T_Datatype]): @overload - def __new__( # type: ignore - self, + def __new__( + cls, grp: Dataset, name: str, datatype: T_DatatypeNC, @@ -355,7 +355,7 @@ class Variable(Generic[T_Datatype]): ) -> Variable[T_DatatypeNC]: ... @overload def __new__( - self, + cls, grp: Dataset, name: str, datatype: _DatatypeStrOptions | npt.DTypeLike, From 4badee2f8bdb1f9b288f3f208afca7410e4230d0 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Thu, 11 Jul 2024 09:32:51 -0700 Subject: [PATCH 1196/1504] Fix '__dealloc' >> '__dealloc__' --- src/netCDF4/__init__.pyi | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index efb1c7780..5e62f2f1c 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -308,7 +308,7 @@ class Dataset: def __setattr__(self, name: str, value: Any) -> None: ... def __getattr__(self, name: str) -> Any: ... def __delattr__(self, name: str): ... - def __dealloc(self) -> None: ... + def __dealloc__(self) -> None: ... def __reduce__(self) -> NoReturn: ... def __enter__(self) -> Self: ... def __exit__(self, atype, value, traceback) -> None: ... From d91bc54d99dacada5d59e8774569e2df369ef986 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Thu, 11 Jul 2024 09:57:04 -0700 Subject: [PATCH 1197/1504] Rename type aliases to singular names --- src/netCDF4/__init__.pyi | 108 +++++++++++++++++++-------------------- 1 file changed, 53 insertions(+), 55 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 5e62f2f1c..a210a3d06 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -54,25 +54,23 @@ if sys.version_info >= (3, 10): elif not TYPE_CHECKING: ellipsis = type(Ellipsis) # keeps ruff happy until ruff uses typeshed -_DatatypeStrOptions: TypeAlias = Literal[ +DatatypeCode: TypeAlias = Literal[ "S1", "c", "i1", "b", "B", "u1", "i2", "h", "s", "u2", "i4", "i", "l", "u4", "i8", "u8", "f4", "f", "f8", "d", "c8", "c16" ] -_DatatypeNCOptions: TypeAlias = Union[CompoundType, VLType, EnumType] -DatatypeOptions: TypeAlias = Union[_DatatypeStrOptions, _DatatypeNCOptions, npt.DTypeLike] -T_Datatype = TypeVar("T_Datatype", bound=DatatypeOptions) +NCComplexDatatype: TypeAlias = Union[CompoundType, VLType, EnumType] +Datatype: TypeAlias = Union[DatatypeCode, NCComplexDatatype, npt.DTypeLike] +T_Datatype = TypeVar("T_Datatype", bound=Datatype) T_DatatypeNC = TypeVar("T_DatatypeNC", CompoundType, VLType, EnumType) -DimensionsOptions: TypeAlias = Union[str, bytes, Dimension, Iterable[Union[str, bytes, Dimension]]] -CompressionOptions: TypeAlias = Literal[ - "zlib", "szip", "zstd", "blosc_lz", "blosc_lz4", "blosc_lz4hc", "blosc_zlib", "blosc_zstd" -] -CompressionLevelOptions: TypeAlias = Literal[0, 1, 2, 3, 4, 5, 6, 7, 8, 9] -AccessModeOptions: TypeAlias = Literal["r", "w", "r+", "a", "x", "rs", "ws", "r+s", "as"] -FormatOptions: TypeAlias = Literal["NETCDF4", "NETCDF4_CLASSIC", "NETCDF3_CLASSIC", "NETCDF3_64BIT_OFFSET", "NETCDF3_64BIT_DATA"] -DiskFormatOptions: TypeAlias = Literal["NETCDF3", "HDF5", "HDF4", "PNETCDF", "DAP2", "DAP4", "UNDEFINED"] -QuantizeOptions: TypeAlias = Literal["BitGroom", "BitRound", "GranularBitRound"] -EndianOptions: TypeAlias = Literal["native", "little", "big"] -CalendarOptions: TypeAlias = Literal[ +DimensionsSpecifier: TypeAlias = Union[str, bytes, Dimension, Iterable[Union[str, bytes, Dimension]]] +CompressionType: TypeAlias = Literal["zlib", "szip", "zstd", "blosc_lz", "blosc_lz4", "blosc_lz4hc", "blosc_zlib", "blosc_zstd"] +CompressionLevel: TypeAlias = Literal[0, 1, 2, 3, 4, 5, 6, 7, 8, 9] +AccessMode: TypeAlias = Literal["r", "w", "r+", "a", "x", "rs", "ws", "r+s", "as"] +Format: TypeAlias = Literal["NETCDF4", "NETCDF4_CLASSIC", "NETCDF3_CLASSIC", "NETCDF3_64BIT_OFFSET", "NETCDF3_64BIT_DATA"] +DiskFormat: TypeAlias = Literal["NETCDF3", "HDF5", "HDF4", "PNETCDF", "DAP2", "DAP4", "UNDEFINED"] +QuantizeMode: TypeAlias = Literal["BitGroom", "BitRound", "GranularBitRound"] +EndianType: TypeAlias = Literal["native", "little", "big"] +CalendarType: TypeAlias = Literal[ "standard", "gregorian", "proleptic_gregorian", "noleap", "365_day", "360_day", "julian", "all_leap", "366_day" ] BoolInt: TypeAlias = Literal[0, 1] @@ -119,21 +117,21 @@ default_fillvals: dict[str, int | float | str] def date2index( dates: dt.datetime | cftime.datetime | Sequence[dt.datetime | cftime.datetime] | DateTimeArray, nctime: Variable, - calendar: CalendarOptions | None = None, + calendar: CalendarType | None = None, select: Literal["exact", "before", "after", "nearest"] = "exact", has_year_zero: bool | None = None, ) -> int | npt.NDArray[np.int_]: ... def date2num( dates: dt.datetime | cftime.datetime | Sequence[dt.datetime | cftime.datetime] | DateTimeArray, units: str, - calendar: CalendarOptions | None = None, + calendar: CalendarType | None = None, has_year_zero: bool | None = None, longdouble: bool = False, ) -> np.number | npt.NDArray[np.number]: ... def num2date( times: Sequence[int | float | np.number] | npt.NDArray[np.number], units: str, - calendar: CalendarOptions = "standard", + calendar: CalendarType = "standard", only_use_cftime_datetimes: bool = True, only_use_python_datetimes: bool = False, has_year_zero: bool | None = None, @@ -168,9 +166,9 @@ class Dataset: def __init__( self, filename: str | os.PathLike, - mode: AccessModeOptions = "r", + mode: AccessMode = "r", clobber: bool = True, - format: FormatOptions = "NETCDF4", + format: Format = "NETCDF4", diskless: bool = False, persist: bool = False, keepweakref: bool = False, @@ -197,11 +195,11 @@ class Dataset: @property def enumtypes(self) -> dict[str, EnumType]: ... @property - def data_model(self) -> FormatOptions: ... + def data_model(self) -> Format: ... @property - def file_format(self) -> FormatOptions: ... + def file_format(self) -> Format: ... @property - def disk_format(self) -> DiskFormatOptions: ... + def disk_format(self) -> DiskFormat: ... @property def parent(self) -> Dataset | None: ... @property @@ -227,10 +225,10 @@ class Dataset: self, varname: str, datatype: T_DatatypeNC, - dimensions: DimensionsOptions = (), - compression: CompressionOptions | None = None, + dimensions: DimensionsSpecifier = (), + compression: CompressionType | None = None, zlib: bool = False, - complevel: CompressionLevelOptions | None = 4, + complevel: CompressionLevel | None = 4, shuffle: bool = True, szip_coding: Literal["nn", "ec"] = "nn", szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, @@ -238,10 +236,10 @@ class Dataset: fletcher32: bool = False, contiguous: bool = False, chunksizes: int | None = None, - endian: EndianOptions = "native", + endian: EndianType = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeOptions = "BitGroom", + quantize_mode: QuantizeMode = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, ) -> Variable[T_DatatypeNC]: ... @@ -249,11 +247,11 @@ class Dataset: def createVariable( self, varname: str, - datatype: _DatatypeStrOptions | npt.DTypeLike, - dimensions: DimensionsOptions = (), - compression: CompressionOptions | None = None, + datatype: DatatypeCode | npt.DTypeLike, + dimensions: DimensionsSpecifier = (), + compression: CompressionType | None = None, zlib: bool = False, - complevel: CompressionLevelOptions | None = 4, + complevel: CompressionLevel | None = 4, shuffle: bool = True, szip_coding: Literal["nn", "ec"] = "nn", szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, @@ -261,10 +259,10 @@ class Dataset: fletcher32: bool = False, contiguous: bool = False, chunksizes: int | None = None, - endian: EndianOptions = "native", + endian: EndianType = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeOptions = "BitGroom", + quantize_mode: QuantizeMode = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, ) -> Variable[np.dtype]: ... @@ -294,7 +292,7 @@ class Dataset: def get_variables_by_attributes(self, **kwargs: Callable[[Any], bool] | Any) -> list[Variable]: ... @staticmethod def fromcdl( - cdlfilename: str, ncfilename: str | None = None, mode: AccessModeOptions = "a", format: FormatOptions = "NETCDF4" + cdlfilename: str, ncfilename: str | None = None, mode: AccessMode = "a", format: Format = "NETCDF4" ) -> Dataset: ... @overload def tocdl(self, coordvars: bool = False, data: bool = False, outfile: None = None) -> str: ... @@ -334,10 +332,10 @@ class Variable(Generic[T_Datatype]): grp: Dataset, name: str, datatype: T_DatatypeNC, - dimensions: DimensionsOptions = (), - compression: CompressionOptions | None = None, + dimensions: DimensionsSpecifier = (), + compression: CompressionType | None = None, zlib: bool = False, - complevel: CompressionLevelOptions | None = 4, + complevel: CompressionLevel | None = 4, shuffle: bool = True, szip_coding: Literal["nn", "ec"] = "nn", szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, @@ -345,10 +343,10 @@ class Variable(Generic[T_Datatype]): fletcher32: bool = False, contiguous: bool = False, chunksizes: Sequence[int] | None = None, - endian: EndianOptions = "native", + endian: EndianType = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeOptions = "BitGroom", + quantize_mode: QuantizeMode = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any, @@ -358,11 +356,11 @@ class Variable(Generic[T_Datatype]): cls, grp: Dataset, name: str, - datatype: _DatatypeStrOptions | npt.DTypeLike, - dimensions: DimensionsOptions = (), - compression: CompressionOptions | None = None, + datatype: DatatypeCode | npt.DTypeLike, + dimensions: DimensionsSpecifier = (), + compression: CompressionType | None = None, zlib: bool = False, - complevel: CompressionLevelOptions | None = 4, + complevel: CompressionLevel | None = 4, shuffle: bool = True, szip_coding: Literal["nn", "ec"] = "nn", szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, @@ -370,10 +368,10 @@ class Variable(Generic[T_Datatype]): fletcher32: bool = False, contiguous: bool = False, chunksizes: Sequence[int] | None = None, - endian: EndianOptions = "native", + endian: EndianType = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeOptions = "BitGroom", + quantize_mode: QuantizeMode = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any, @@ -383,10 +381,10 @@ class Variable(Generic[T_Datatype]): grp: Dataset, name: str, datatype: T_Datatype, - dimensions: DimensionsOptions = (), - compression: CompressionOptions | None = None, + dimensions: DimensionsSpecifier = (), + compression: CompressionType | None = None, zlib: bool = False, - complevel: CompressionLevelOptions | None = 4, + complevel: CompressionLevel | None = 4, shuffle: bool = True, szip_coding: Literal["nn", "ec"] = "nn", szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, @@ -394,10 +392,10 @@ class Variable(Generic[T_Datatype]): fletcher32: bool = False, contiguous: bool = False, chunksizes: Sequence[int] | None = None, - endian: EndianOptions = "native", + endian: EndianType = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeOptions = "BitGroom", + quantize_mode: QuantizeMode = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any, @@ -434,8 +432,8 @@ class Variable(Generic[T_Datatype]): def getncattr(self, name: str, encoding="utf-8"): ... def delncattr(self, name: str) -> None: ... def filters(self) -> FiltersDict: ... - def quantization(self) -> tuple[int, QuantizeOptions] | None: ... - def endian(self) -> EndianOptions: ... + def quantization(self) -> tuple[int, QuantizeMode] | None: ... + def endian(self) -> EndianType: ... def chunking(self) -> Literal["contiguous"] | list[int]: ... def get_var_chunk_cache(self) -> tuple[int, int, float]: ... def set_var_chunk_cache( @@ -541,10 +539,10 @@ class _Variable: def __len__(self) -> int: ... class MFTime(_Variable): - calendar: CalendarOptions | None + calendar: CalendarType | None units: str | None - def __init__(self, time: Variable, units: str | None = None, calendar: CalendarOptions | None = None): ... + def __init__(self, time: Variable, units: str | None = None, calendar: CalendarType | None = None): ... def __getitem__(self, elem: GetSetItemKey) -> np.ndarray: ... @overload From 94fc229bd4fc43c862d190ea8926e8e86c74dbf2 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Thu, 11 Jul 2024 09:59:15 -0700 Subject: [PATCH 1198/1504] Move TypedDicts to be adjacent to TypeAliases as they serve a simlar purpose --- src/netCDF4/__init__.pyi | 40 ++++++++++++++++++++-------------------- 1 file changed, 20 insertions(+), 20 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index a210a3d06..4692f17d4 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -87,6 +87,26 @@ GetSetItemKey: TypeAlias = ( | tuple[int | slice | ellipsis | Sequence[int | bool] | npt.NDArray[np.integer | np.bool_], ...] ) +class BloscInfo(TypedDict): + compressor: Literal["blosc_lz", "blosc_lz4", "blosc_lz4hc", "blosc_zlib", "blosc_zstd"] + shuffle: Literal[0, 1, 2] + +class SzipInfo(TypedDict): + coding: Literal["nn", "ec"] + pixels_per_block: Literal[4, 8, 16, 32] + +class FiltersDict(TypedDict): + """Dict returned from netCDF4.Variable.filters()""" + + zlib: bool + szip: Literal[False] | SzipInfo + zstd: bool + bzip2: bool + blosc: Literal[False] | BloscInfo + shuffle: bool + complevel: int + fletcher32: bool + __version__: str __netcdf4libversion__: str __hdf5libversion__: str @@ -137,26 +157,6 @@ def num2date( has_year_zero: bool | None = None, ) -> dt.datetime | DateTimeArray: ... -class BloscInfo(TypedDict): - compressor: Literal["blosc_lz", "blosc_lz4", "blosc_lz4hc", "blosc_zlib", "blosc_zstd"] - shuffle: Literal[0, 1, 2] - -class SzipInfo(TypedDict): - coding: Literal["nn", "ec"] - pixels_per_block: Literal[4, 8, 16, 32] - -class FiltersDict(TypedDict): - """Dict returned from netCDF4.Variable.filters()""" - - zlib: bool - szip: Literal[False] | SzipInfo - zstd: bool - bzip2: bool - blosc: Literal[False] | BloscInfo - shuffle: bool - complevel: int - fletcher32: bool - class NetCDF4MissingFeatureException(Exception): def __init__(self, feature: str, version: str): ... From 4ec155897caabd748edb387b3aa70732b8476242 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Thu, 11 Jul 2024 10:04:03 -0700 Subject: [PATCH 1199/1504] minor - spelling in comment --- src/netCDF4/_netCDF4.pyi | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/netCDF4/_netCDF4.pyi b/src/netCDF4/_netCDF4.pyi index f649647fe..facdb5b18 100644 --- a/src/netCDF4/_netCDF4.pyi +++ b/src/netCDF4/_netCDF4.pyi @@ -1,4 +1,4 @@ -# The definitions are intendionally done in the __init__. +# The definitions are intentionally done in the __init__. # This file only exists in case someone imports from netCDF4._netCDF4 from . import ( CompoundType, From 559429b1793317753396cdb8b220a8cd4eb4b005 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Fri, 12 Jul 2024 15:12:43 -0700 Subject: [PATCH 1200/1504] Rework all possible type arguments and overloads for createVariable. TypeVar for variable type is now unbound. --- src/netCDF4/__init__.pyi | 113 ++++++++++++++++++++++++++++++++------- 1 file changed, 95 insertions(+), 18 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 4692f17d4..a87078caf 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -54,13 +54,41 @@ if sys.version_info >= (3, 10): elif not TYPE_CHECKING: ellipsis = type(Ellipsis) # keeps ruff happy until ruff uses typeshed -DatatypeCode: TypeAlias = Literal[ - "S1", "c", "i1", "b", "B", "u1", "i2", "h", "s", "u2", "i4", "i", "l", "u4", "i8", "u8", "f4", "f", "f8", "d", "c8", "c16" +# string type specifiers +# fmt: off +RealTypeLiteral: TypeAlias = Literal[ + "i1", "b", "B", "int8", # NC_BYTE + "u1", "uint8", # NC_UBYTE + "i2", "h", "s", "int16", # NC_SHORT + "u2", "uint16", # NC_USHORT + "i4", "i", "l", "int32", # NC_INT + "u4", "uint32", # NC_UINT + "i8", "int64", "int", # NC_INT64 + "u8", "uint64", # NC_UINT64 + "f4", "f", "float32", # NC_FLOAT + "f8", "d", "float64", "float" # NC_DOUBLE ] -NCComplexDatatype: TypeAlias = Union[CompoundType, VLType, EnumType] -Datatype: TypeAlias = Union[DatatypeCode, NCComplexDatatype, npt.DTypeLike] -T_Datatype = TypeVar("T_Datatype", bound=Datatype) -T_DatatypeNC = TypeVar("T_DatatypeNC", CompoundType, VLType, EnumType) +# fmt: on +ComplexTypeLiteral: TypeAlias = Literal["c8", "c16", "complex64", "complex128"] +NumericTypeLiteral: TypeAlias = RealTypeLiteral | ComplexTypeLiteral +CharTypeLiteral: TypeAlias = Literal["S1", "c"] # NC_CHAR +TypeLiteral: TypeAlias = NumericTypeLiteral | CharTypeLiteral + +# Numpy types +NumPyRealType: TypeAlias = ( + np.int8 | np.uint8 | np.int16 | np.uint16 | np.int32 | np.uint32 | np.int64 | np.uint64 | np.float16 | np.float32 +) +NumPyComplexType: TypeAlias = np.complex64 | np.complex128 +NumPyNumericType: TypeAlias = NumPyRealType | NumPyComplexType +# Classes that can create instances of NetCDF user-defined types +NetCDFUDTClass: TypeAlias = CompoundType | VLType | EnumType +# Possible argument types for the datatype argument used in Variable creation. +DatatypeSpecifier: TypeAlias = ( + TypeLiteral | np.dtype[NumPyNumericType | np.str_] | type[int | float | NumPyNumericType | str | np.str_] | NetCDFUDTClass +) + +VarT = TypeVar("VarT") +NumericVarT = TypeVar("NumericVarT", bound=NumPyNumericType) DimensionsSpecifier: TypeAlias = Union[str, bytes, Dimension, Iterable[Union[str, bytes, Dimension]]] CompressionType: TypeAlias = Literal["zlib", "szip", "zstd", "blosc_lz", "blosc_lz4", "blosc_lz4hc", "blosc_zlib", "blosc_zstd"] @@ -221,10 +249,33 @@ class Dataset: def createDimension(self, dimname: str, size: int | None = None) -> Dimension: ... def renameDimension(self, oldname: str, newname: str) -> None: ... @overload - def createVariable( # type: ignore + def createVariable( + self, + varname: str, + datatype: np.dtype[NumericVarT] | type[NumericVarT], + dimensions: DimensionsSpecifier = (), + compression: CompressionType | None = None, + zlib: bool = False, + complevel: CompressionLevel | None = 4, + shuffle: bool = True, + szip_coding: Literal["nn", "ec"] = "nn", + szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, + blosc_shuffle: Literal[0, 1, 2] = 1, + fletcher32: bool = False, + contiguous: bool = False, + chunksizes: int | None = None, + endian: EndianType = "native", + least_significant_digit: int | None = None, + significant_digits: int | None = None, + quantize_mode: QuantizeMode = "BitGroom", + fill_value: int | float | str | bytes | Literal[False] | None = None, + chunk_cache: int | None = None, + ) -> Variable[NumericVarT]: ... + @overload + def createVariable( self, varname: str, - datatype: T_DatatypeNC, + datatype: np.dtype[np.str_] | type[str | np.str_], dimensions: DimensionsSpecifier = (), compression: CompressionType | None = None, zlib: bool = False, @@ -242,12 +293,12 @@ class Dataset: quantize_mode: QuantizeMode = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, - ) -> Variable[T_DatatypeNC]: ... + ) -> Variable[str]: ... @overload def createVariable( self, varname: str, - datatype: DatatypeCode | npt.DTypeLike, + datatype: DatatypeSpecifier, dimensions: DimensionsSpecifier = (), compression: CompressionType | None = None, zlib: bool = False, @@ -265,7 +316,7 @@ class Dataset: quantize_mode: QuantizeMode = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, - ) -> Variable[np.dtype]: ... + ) -> Variable: ... def renameVariable(self, oldname: str, newname: str) -> None: ... def createGroup(self, groupname: str) -> Group: ... def renameGroup(self, oldname: str, newname: str) -> None: ... @@ -325,13 +376,39 @@ class Dimension: def isunlimited(self) -> bool: ... def __len__(self) -> int: ... -class Variable(Generic[T_Datatype]): +class Variable(Generic[VarT]): + # Overloads of __new__ are provided for some cases where the Variable's type may be statically inferred from the datatype arg + @overload + def __new__( + cls, + grp: Dataset, + name: str, + datatype: np.dtype[NumericVarT] | type[NumericVarT], + dimensions: DimensionsSpecifier = (), + compression: CompressionType | None = None, + zlib: bool = False, + complevel: CompressionLevel | None = 4, + shuffle: bool = True, + szip_coding: Literal["nn", "ec"] = "nn", + szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, + blosc_shuffle: Literal[0, 1, 2] = 1, + fletcher32: bool = False, + contiguous: bool = False, + chunksizes: Sequence[int] | None = None, + endian: EndianType = "native", + least_significant_digit: int | None = None, + significant_digits: int | None = None, + quantize_mode: QuantizeMode = "BitGroom", + fill_value: int | float | str | bytes | Literal[False] | None = None, + chunk_cache: int | None = None, + **kwargs: Any, + ) -> Variable[NumericVarT]: ... @overload def __new__( cls, grp: Dataset, name: str, - datatype: T_DatatypeNC, + datatype: np.dtype[np.str_] | type[str | np.str_], dimensions: DimensionsSpecifier = (), compression: CompressionType | None = None, zlib: bool = False, @@ -350,13 +427,13 @@ class Variable(Generic[T_Datatype]): fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any, - ) -> Variable[T_DatatypeNC]: ... + ) -> Variable[str]: ... @overload def __new__( cls, grp: Dataset, name: str, - datatype: DatatypeCode | npt.DTypeLike, + datatype: DatatypeSpecifier, dimensions: DimensionsSpecifier = (), compression: CompressionType | None = None, zlib: bool = False, @@ -375,12 +452,12 @@ class Variable(Generic[T_Datatype]): fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any, - ) -> Variable[np.dtype]: ... + ) -> Variable: ... def __init__( self, grp: Dataset, name: str, - datatype: T_Datatype, + datatype: DatatypeSpecifier, dimensions: DimensionsSpecifier = (), compression: CompressionType | None = None, zlib: bool = False, @@ -405,7 +482,7 @@ class Variable(Generic[T_Datatype]): @property def dtype(self) -> np.dtype | type[str]: ... @property - def datatype(self) -> T_Datatype: ... + def datatype(self) -> np.dtype | NetCDFUDTClass: ... @property def shape(self) -> tuple[int, ...]: ... @property From 516c644545749e91199557177c56c71972cefa56 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Fri, 12 Jul 2024 15:15:24 -0700 Subject: [PATCH 1201/1504] Add docstring and notes section to top of file --- src/netCDF4/__init__.pyi | 28 ++++++++++++++++++++++++++++ 1 file changed, 28 insertions(+) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index a87078caf..1143b3877 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -1,3 +1,31 @@ +"""__init__.pyi - Type stubs for the netCDF4 Python package""" +# Notes: +# +# - The stubs in this file are manually-generated and must be updated if and when the API is changed. +# - The following **ruff** commands may be used to properly format this file according to +# https://typing.readthedocs.io/en/latest/source/stubs.html +# +# ruff format --line-length 130 src/netCDF4/__init__.pyi # format code +# ruff check --line-length 130 --select I --fix src/netCDF4/__init__.pyi # sort imports +# +# - The Variable class is a generic and may thus be statically typed, but this has limited utility for the following reasons: +# - The return type of `Variable.__getitem__()` (and `Variable.getValue()`) depends on a number of factors (e.g. variable shape, +# key shape, whether masking is enabled) that cannot be easily determined statically. +# - Similarly, the types and shapes of data that `Variable.__setitem__()` may accept varies widely depending on many factors and +# is intractable to determine statically. +# - Automatic typing of a Variable on variable creation is tedious due to the large number of ways to specify a variable's type +# (in particular all the type literals). +# - It is not possible to statically type a Variable of any user-defined type (CompoundType, EnumType, VLType) as these types +# are created dynamically. +# It is thus best left to the user to implement TypeGuards and/or perform other mixed static/runtime type-checking to ensure the +# type and shape of data retrieved from this library. +# - `Dataset.__getitem__()` may return either a Variable or a Group, depending on the string passed to it. Rather than return a +# Union of Variable and Group, the authors of these stubs have elected to to return Any, leaving it up to users to determine the +# type of the returned value. +# - `MFDataset.dimensions` returns `dict[str, Dimension]` and `MFDataset.variables` returns `dict[str, Variable]` even though the +# dict value types may actually be `_Dimension` and `_Variable`, respectively. The original authors of this stubfile have +# elected to do this for simplicity's sake, but it may make sense to change this in the future, or just return `dict[str, Any]`. + import datetime as dt import os import sys From 226890936e7d4a4bba9da0ba1d2897b2bb05df79 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Fri, 12 Jul 2024 23:59:49 -0700 Subject: [PATCH 1202/1504] np.float64 is a possible type --- src/netCDF4/__init__.pyi | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 1143b3877..f834bac19 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -104,7 +104,7 @@ TypeLiteral: TypeAlias = NumericTypeLiteral | CharTypeLiteral # Numpy types NumPyRealType: TypeAlias = ( - np.int8 | np.uint8 | np.int16 | np.uint16 | np.int32 | np.uint32 | np.int64 | np.uint64 | np.float16 | np.float32 + np.int8 | np.uint8 | np.int16 | np.uint16 | np.int32 | np.uint32 | np.int64 | np.uint64 | np.float16 | np.float32 | np.float64 ) NumPyComplexType: TypeAlias = np.complex64 | np.complex128 NumPyNumericType: TypeAlias = NumPyRealType | NumPyComplexType From d5baab3b4878fc6d0c80d43505acb4d330d0511b Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Sat, 13 Jul 2024 00:01:20 -0700 Subject: [PATCH 1203/1504] datatype specifier can be an arbitrary string --- src/netCDF4/__init__.pyi | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index f834bac19..62738310d 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -110,9 +110,15 @@ NumPyComplexType: TypeAlias = np.complex64 | np.complex128 NumPyNumericType: TypeAlias = NumPyRealType | NumPyComplexType # Classes that can create instances of NetCDF user-defined types NetCDFUDTClass: TypeAlias = CompoundType | VLType | EnumType -# Possible argument types for the datatype argument used in Variable creation. +# Possible argument types for the datatype argument used in Variable creation. At this time, it is not possible to allow unknown +# strings arguments in the datatype field but exclude and string literals that are not one of `TypeLiteral`, so really +# `TypeLiteral` is made irrelevant, except for anyone who looks at this file. DatatypeSpecifier: TypeAlias = ( - TypeLiteral | np.dtype[NumPyNumericType | np.str_] | type[int | float | NumPyNumericType | str | np.str_] | NetCDFUDTClass + TypeLiteral + | str + | np.dtype[NumPyNumericType | np.str_] + | type[int | float | NumPyNumericType | str | np.str_] + | NetCDFUDTClass ) VarT = TypeVar("VarT") From 229d6aeadd5368fd1efa9aac2512d6ec9bb7dcda Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Sat, 13 Jul 2024 00:03:56 -0700 Subject: [PATCH 1204/1504] Add float and str for GetSetItemKey --- src/netCDF4/__init__.pyi | 22 ++++++++++++++++++++-- 1 file changed, 20 insertions(+), 2 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 62738310d..2763b2f21 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -140,13 +140,31 @@ BoolInt: TypeAlias = Literal[0, 1] DateTimeArray: TypeAlias = npt.NDArray[np.object_] """numpy array of datetime.datetime or cftime.datetime""" +# netCDF accepts floats that can be cooerced to an integer value, and sometimes strings that can be coerced to an integer value. +# There's currently no way to specify this statically, so we allow all floats and strings. +# Also, we have to specify all the possible combinations of list[...] because lists are invariant. GetSetItemKey: TypeAlias = ( int + | float + | np.number | slice | ellipsis + | list[int] + | list[float] + | list[bool] + | list[str] # strs that can be cooerced to ints + | list[int | float] | list[int | bool] - | npt.NDArray[np.integer | np.bool_] - | tuple[int | slice | ellipsis | Sequence[int | bool] | npt.NDArray[np.integer | np.bool_], ...] + | list[int | str] + | list[float | bool] + | list[float | str] + | list[bool | str] + | list[int | float | bool | str] + | npt.NDArray[np.number | np.bool_] + | tuple[ + int | float | str | slice | ellipsis | Sequence[int] | Sequence[bool] | npt.NDArray[np.number | np.bool_], + ..., + ] ) class BloscInfo(TypedDict): From 06f7238fc3abe3e6d22fd0f9a4b84cde83411344 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Sat, 13 Jul 2024 00:04:32 -0700 Subject: [PATCH 1205/1504] integral float can be specified for dimension size --- src/netCDF4/__init__.pyi | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 2763b2f21..e5a0c47c6 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -298,7 +298,7 @@ class Dataset: def sync(self) -> None: ... def set_fill_on(self) -> None: ... def set_fill_off(self) -> None: ... - def createDimension(self, dimname: str, size: int | None = None) -> Dimension: ... + def createDimension(self, dimname: str, size: int | float | None = None) -> Dimension: ... def renameDimension(self, oldname: str, newname: str) -> None: ... @overload def createVariable( @@ -419,7 +419,7 @@ class Group(Dataset): def close(self) -> NoReturn: ... class Dimension: - def __init__(self, grp: Dataset, name: str, size: int | None = None, **kwargs: Any) -> None: ... + def __init__(self, grp: Dataset, name: str, size: int | float | None = None, **kwargs: Any) -> None: ... @property def name(self) -> str: ... @property From bc3bd3f4890bf8fd6fce80cbd1ec0f911c8b0ec8 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Sat, 13 Jul 2024 00:07:03 -0700 Subject: [PATCH 1206/1504] arbitrary strings can be used intead of literals, and truthy values in place of bools --- src/netCDF4/__init__.pyi | 134 +++++++++++++++++++-------------------- 1 file changed, 67 insertions(+), 67 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index e5a0c47c6..10cb83060 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -306,20 +306,20 @@ class Dataset: varname: str, datatype: np.dtype[NumericVarT] | type[NumericVarT], dimensions: DimensionsSpecifier = (), - compression: CompressionType | None = None, - zlib: bool = False, - complevel: CompressionLevel | None = 4, - shuffle: bool = True, - szip_coding: Literal["nn", "ec"] = "nn", - szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, - blosc_shuffle: Literal[0, 1, 2] = 1, - fletcher32: bool = False, - contiguous: bool = False, + compression: CompressionType | str | None = None, + zlib: Any = False, + complevel: CompressionLevel | int | None = 4, + shuffle: Any = True, + szip_coding: Literal["nn", "ec"] | str = "nn", + szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, + blosc_shuffle: Literal[0, 1, 2] | int = 1, + fletcher32: Any = False, + contiguous: Any = False, chunksizes: int | None = None, endian: EndianType = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeMode = "BitGroom", + quantize_mode: QuantizeMode | str = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, ) -> Variable[NumericVarT]: ... @@ -329,20 +329,20 @@ class Dataset: varname: str, datatype: np.dtype[np.str_] | type[str | np.str_], dimensions: DimensionsSpecifier = (), - compression: CompressionType | None = None, - zlib: bool = False, - complevel: CompressionLevel | None = 4, - shuffle: bool = True, - szip_coding: Literal["nn", "ec"] = "nn", - szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, - blosc_shuffle: Literal[0, 1, 2] = 1, - fletcher32: bool = False, - contiguous: bool = False, + compression: CompressionType | str | None = None, + zlib: Any = False, + complevel: CompressionLevel | int | None = 4, + shuffle: Any = True, + szip_coding: Literal["nn", "ec"] | str = "nn", + szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, + blosc_shuffle: Literal[0, 1, 2] | int = 1, + fletcher32: Any = False, + contiguous: Any = False, chunksizes: int | None = None, endian: EndianType = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeMode = "BitGroom", + quantize_mode: QuantizeMode | str = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, ) -> Variable[str]: ... @@ -352,20 +352,20 @@ class Dataset: varname: str, datatype: DatatypeSpecifier, dimensions: DimensionsSpecifier = (), - compression: CompressionType | None = None, - zlib: bool = False, - complevel: CompressionLevel | None = 4, - shuffle: bool = True, - szip_coding: Literal["nn", "ec"] = "nn", - szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, - blosc_shuffle: Literal[0, 1, 2] = 1, - fletcher32: bool = False, - contiguous: bool = False, + compression: CompressionType | str | None = None, + zlib: Any = False, + complevel: CompressionLevel | int | None = 4, + shuffle: Any = True, + szip_coding: Literal["nn", "ec"] | str = "nn", + szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, + blosc_shuffle: Literal[0, 1, 2] | int = 1, + fletcher32: Any = False, + contiguous: Any = False, chunksizes: int | None = None, endian: EndianType = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeMode = "BitGroom", + quantize_mode: QuantizeMode | str = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, ) -> Variable: ... @@ -437,20 +437,20 @@ class Variable(Generic[VarT]): name: str, datatype: np.dtype[NumericVarT] | type[NumericVarT], dimensions: DimensionsSpecifier = (), - compression: CompressionType | None = None, - zlib: bool = False, - complevel: CompressionLevel | None = 4, - shuffle: bool = True, - szip_coding: Literal["nn", "ec"] = "nn", - szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, - blosc_shuffle: Literal[0, 1, 2] = 1, - fletcher32: bool = False, - contiguous: bool = False, + compression: CompressionType | str | None = None, + zlib: Any = False, + complevel: CompressionLevel | int | None = 4, + shuffle: Any = True, + szip_coding: Literal["nn", "ec"] | str = "nn", + szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, + blosc_shuffle: Literal[0, 1, 2] | int = 1, + fletcher32: Any = False, + contiguous: Any = False, chunksizes: Sequence[int] | None = None, endian: EndianType = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeMode = "BitGroom", + quantize_mode: QuantizeMode | str = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any, @@ -462,20 +462,20 @@ class Variable(Generic[VarT]): name: str, datatype: np.dtype[np.str_] | type[str | np.str_], dimensions: DimensionsSpecifier = (), - compression: CompressionType | None = None, - zlib: bool = False, - complevel: CompressionLevel | None = 4, - shuffle: bool = True, - szip_coding: Literal["nn", "ec"] = "nn", - szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, - blosc_shuffle: Literal[0, 1, 2] = 1, - fletcher32: bool = False, - contiguous: bool = False, + compression: CompressionType | str | None = None, + zlib: Any = False, + complevel: CompressionLevel | int | None = 4, + shuffle: Any = True, + szip_coding: Literal["nn", "ec"] | str = "nn", + szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, + blosc_shuffle: Literal[0, 1, 2] | int = 1, + fletcher32: Any = False, + contiguous: Any = False, chunksizes: Sequence[int] | None = None, endian: EndianType = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeMode = "BitGroom", + quantize_mode: QuantizeMode | str = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any, @@ -487,20 +487,20 @@ class Variable(Generic[VarT]): name: str, datatype: DatatypeSpecifier, dimensions: DimensionsSpecifier = (), - compression: CompressionType | None = None, - zlib: bool = False, - complevel: CompressionLevel | None = 4, - shuffle: bool = True, - szip_coding: Literal["nn", "ec"] = "nn", - szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, - blosc_shuffle: Literal[0, 1, 2] = 1, - fletcher32: bool = False, - contiguous: bool = False, + compression: CompressionType | str | None = None, + zlib: Any = False, + complevel: CompressionLevel | int | None = 4, + shuffle: Any = True, + szip_coding: Literal["nn", "ec"] | str = "nn", + szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, + blosc_shuffle: Literal[0, 1, 2] | int = 1, + fletcher32: Any = False, + contiguous: Any = False, chunksizes: Sequence[int] | None = None, endian: EndianType = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeMode = "BitGroom", + quantize_mode: QuantizeMode | str = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any, @@ -511,20 +511,20 @@ class Variable(Generic[VarT]): name: str, datatype: DatatypeSpecifier, dimensions: DimensionsSpecifier = (), - compression: CompressionType | None = None, - zlib: bool = False, - complevel: CompressionLevel | None = 4, - shuffle: bool = True, + compression: CompressionType | str | None = None, + zlib: Any = False, + complevel: CompressionLevel | int | None = 4, + shuffle: Any = True, szip_coding: Literal["nn", "ec"] = "nn", szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, blosc_shuffle: Literal[0, 1, 2] = 1, - fletcher32: bool = False, - contiguous: bool = False, + fletcher32: Any = False, + contiguous: Any = False, chunksizes: Sequence[int] | None = None, endian: EndianType = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeMode = "BitGroom", + quantize_mode: QuantizeMode | str = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any, From ea0297f4b5f380c823675b337c40b328345e9d7d Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Sat, 13 Jul 2024 00:07:32 -0700 Subject: [PATCH 1207/1504] enum_dict for createEnum can have int or np.integer values --- src/netCDF4/__init__.pyi | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 10cb83060..98be1e798 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -378,7 +378,10 @@ class Dataset: ) -> CompoundType: ... def createVLType(self, datatype: npt.DTypeLike, datatype_name: str) -> VLType: ... def createEnumType( - self, datatype: np.dtype[np.integer] | type[np.integer] | type[int], datatype_name: str, enum_dict: dict[str, int] + self, + datatype: np.dtype[np.integer] | type[np.integer] | type[int], + datatype_name: str, + enum_dict: Mapping[str, int | np.integer], ) -> EnumType: ... def ncattrs(self) -> list[str]: ... def setncattr_string(self, name: str, value: Any) -> None: ... @@ -615,7 +618,7 @@ class EnumType: grp: Dataset, dt: np.dtype[np.integer] | type[np.integer] | type[int] | str, dtype_name: str, - enum_dict: Mapping[str, int], + enum_dict: Mapping[str, int | np.integer], **kwargs: Any, ) -> None: ... def __reduce__(self) -> NoReturn: ... From 0ba830d39f40a8e83d7de14c0460e3d7513308b4 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Sat, 13 Jul 2024 00:08:03 -0700 Subject: [PATCH 1208/1504] Return Any from Variable.__getitem__ --- src/netCDF4/__init__.pyi | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 98be1e798..14eff09a6 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -586,7 +586,7 @@ class Variable(Generic[VarT]): def __delattr__(self, name: str) -> None: ... def __setattr__(self, name: str, value: Any) -> None: ... def __getattr__(self, name: str) -> Any: ... - def __getitem__(self, elem: GetSetItemKey) -> np.ndarray: ... + def __getitem__(self, elem: GetSetItemKey) -> Any: ... def __setitem__(self, elem: GetSetItemKey, data: npt.ArrayLike) -> None: ... def __array__(self) -> np.ndarray: ... def __len__(self) -> int: ... From 0c5524da34393efb991671163302c35192d9cd8f Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Sat, 13 Jul 2024 00:09:00 -0700 Subject: [PATCH 1209/1504] Simplify Variable.dtype to be Any --- src/netCDF4/__init__.pyi | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 14eff09a6..951326548 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -535,7 +535,7 @@ class Variable(Generic[VarT]): @property def name(self) -> str: ... @property - def dtype(self) -> np.dtype | type[str]: ... + def dtype(self) -> Any: ... # actually np.dtype | type[str] @property def datatype(self) -> np.dtype | NetCDFUDTClass: ... @property From 290e67160e96a635548bfd6fdcc9e646a7542ef9 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Sat, 13 Jul 2024 00:13:15 -0700 Subject: [PATCH 1210/1504] minor fixes to enum type tests --- test/test_enum.py | 21 ++++++++++++--------- 1 file changed, 12 insertions(+), 9 deletions(-) diff --git a/test/test_enum.py b/test/test_enum.py index 0ab42ec6e..536cb0a27 100644 --- a/test/test_enum.py +++ b/test/test_enum.py @@ -1,9 +1,10 @@ -import sys -import unittest import os import tempfile -from netCDF4 import Dataset +import unittest + +import netCDF4 import numpy as np +from netCDF4 import Dataset, EnumType from numpy.testing import assert_array_equal FILE_NAME = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name @@ -26,7 +27,7 @@ def setUp(self): cloud_type = f.createEnumType(ENUM_BASETYPE,ENUM_NAME,ENUM_DICT) # make sure KeyError raised if non-integer basetype used. try: - cloud_typ2 = f.createEnumType(np.float32,ENUM_NAME,ENUM_DICT) + cloud_typ2 = f.createEnumType(np.float32,ENUM_NAME,ENUM_DICT) # type: ignore except KeyError: pass f.createDimension('time',None) @@ -49,6 +50,7 @@ def runTest(self): """testing enum data type""" f = Dataset(self.file, 'r') v = f.variables[VAR_NAME] + assert isinstance(v.datatype, EnumType) assert v.datatype.enum_dict == ENUM_DICT assert list(f.enumtypes.keys()) == [ENUM_NAME] assert f.enumtypes[ENUM_NAME].name == ENUM_NAME # issue 775 @@ -69,9 +71,9 @@ def setUp(self): DT = np.int16; BITS = 8 self.STORED_VAL = DT(2**BITS) self.VAL_MAP = {f'bits_{n}': DT(2**n) for n in range(1,BITS+1)} - self.VAL_MAP['invalid'] = 0 + self.VAL_MAP['invalid'] = DT(0) self.file = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name - with netCDF4.Dataset(file, 'w') as nc: + with netCDF4.Dataset(self.file, 'w') as nc: # The enum is created with dtype=int16, so it will allow BITS values up to 15 et = nc.createEnumType(DT, 'etype', self.VAL_MAP) ev = nc.createVariable('evar', et) @@ -80,10 +82,11 @@ def setUp(self): def tearDown(self): os.remove(self.file) def runTest(self): - with netCDF4.Dataset(file, 'r') as nc: + with netCDF4.Dataset(self.file, 'r') as nc: read_var = nc['evar'] - assert read_var[...] == self.STORED_VAL - assert read_et.enum_dict == self.VAL_MAP + read_et = nc.enumtypes["etype"] + assert read_var[...] == self.STORED_VAL + assert read_et.enum_dict == self.VAL_MAP if __name__ == '__main__': unittest.main() From e5d88d007ec93fc0419bdadb5766df494ac59fc4 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Sat, 13 Jul 2024 00:20:52 -0700 Subject: [PATCH 1211/1504] use np.ma.masked_array in tests for numpy version compatibility --- test/test_masked3.py | 8 ++++---- test/test_masked4.py | 4 ++-- test/test_masked5.py | 2 +- test/test_masked6.py | 8 ++++---- test/test_scaled.py | 8 ++++---- test/test_slicing.py | 2 +- 6 files changed, 16 insertions(+), 16 deletions(-) diff --git a/test/test_masked3.py b/test/test_masked3.py index ed88109f2..c7cd4f2f5 100755 --- a/test/test_masked3.py +++ b/test/test_masked3.py @@ -59,7 +59,7 @@ def test_unscaled(self): self.assertEqual(v.dtype, "i2") self.assertTrue(isinstance(v, np.ndarray)) - self.assertTrue(not isinstance(v, ma.core.MaskedArray)) + self.assertTrue(not isinstance(v, ma.masked_array)) assert_array_almost_equal(v, self.v) f.close() @@ -85,7 +85,7 @@ def test_scaled(self): self.assertEqual(v.dtype, "f8") self.assertTrue(isinstance(v, np.ndarray)) - self.assertTrue(not isinstance(v, ma.core.MaskedArray)) + self.assertTrue(not isinstance(v, ma.masked_array)) assert_array_almost_equal(v, self.v_scaled) f.close() @@ -104,7 +104,7 @@ def test_unscaled(self): self.assertEqual(v_ma.dtype, "i2") self.assertTrue(isinstance(v_ma, np.ndarray)) - self.assertTrue(isinstance(v_ma, ma.core.MaskedArray)) + self.assertTrue(isinstance(v_ma, ma.masked_array)) assert_array_almost_equal(v_ma, self.v_ma) f.close() @@ -128,7 +128,7 @@ def test_scaled(self): self.assertEqual(v_ma.dtype, "f8") self.assertTrue(isinstance(v_ma, np.ndarray)) - self.assertTrue(isinstance(v_ma, ma.core.MaskedArray)) + self.assertTrue(isinstance(v_ma, ma.masked_array)) assert_array_almost_equal(v_ma, self.v_ma_scaled) f.close() diff --git a/test/test_masked4.py b/test/test_masked4.py index 14dd14fc4..61d9a1690 100755 --- a/test/test_masked4.py +++ b/test/test_masked4.py @@ -88,11 +88,11 @@ def test_scaled(self): v3 = f.variables["v3"][:] self.assertEqual(v.dtype, "f8") self.assertTrue(isinstance(v, np.ndarray)) - self.assertTrue(isinstance(v, ma.core.MaskedArray)) + self.assertTrue(isinstance(v, ma.masked_array)) assert_array_almost_equal(v, self.v_scaled) self.assertEqual(v2.dtype, "f8") self.assertTrue(isinstance(v2, np.ndarray)) - self.assertTrue(isinstance(v2, ma.core.MaskedArray)) + self.assertTrue(isinstance(v2, ma.masked_array)) assert_array_almost_equal(v2, self.v_scaled) self.assertTrue(np.all(self.v_ma.mask == v.mask)) self.assertTrue(np.all(self.v_ma.mask == v2.mask)) diff --git a/test/test_masked5.py b/test/test_masked5.py index 3d8dba4db..87734024a 100755 --- a/test/test_masked5.py +++ b/test/test_masked5.py @@ -45,7 +45,7 @@ def test_scaled(self): f = Dataset(self.testfile) v = f.variables["v"] v2 = f.variables["v2"] - self.assertTrue(isinstance(v[:], ma.core.MaskedArray)) + self.assertTrue(isinstance(v[:], ma.masked_array)) assert_array_equal(v[:], self.v_ma) assert_array_equal(v[2],self.v[2]) # issue #624. v.set_auto_mask(False) diff --git a/test/test_masked6.py b/test/test_masked6.py index 65db53dde..dc77da99e 100644 --- a/test/test_masked6.py +++ b/test/test_masked6.py @@ -47,13 +47,13 @@ def test_always_mask(self): v = f.variables['v'][:] self.assertTrue(isinstance(v, np.ndarray)) - self.assertTrue(isinstance(v, ma.core.MaskedArray)) + self.assertTrue(isinstance(v, ma.masked_array)) assert_array_almost_equal(v, self.v) w = f.variables['w'][:] self.assertTrue(isinstance(w, np.ndarray)) - self.assertTrue(isinstance(w, ma.core.MaskedArray)) + self.assertTrue(isinstance(w, ma.masked_array)) assert_array_almost_equal(w, self.w) f.close() @@ -69,13 +69,13 @@ def test_always_mask(self): v = f.variables['v'][:] self.assertTrue(isinstance(v, np.ndarray)) - self.assertFalse(isinstance(v, ma.core.MaskedArray)) + self.assertFalse(isinstance(v, ma.masked_array)) assert_array_almost_equal(v, self.v) w = f.variables['w'][:] self.assertTrue(isinstance(w, np.ndarray)) - self.assertTrue(isinstance(w, ma.core.MaskedArray)) + self.assertTrue(isinstance(w, ma.masked_array)) assert_array_almost_equal(w, self.w) f.close() diff --git a/test/test_scaled.py b/test/test_scaled.py index 4a73ba3f7..5c1ce9542 100755 --- a/test/test_scaled.py +++ b/test/test_scaled.py @@ -68,7 +68,7 @@ def test_unmasked(self): self.assertEqual(v.dtype, "i2") self.assertTrue(isinstance(v, np.ndarray)) # issue 785: always return masked array by default - self.assertTrue(isinstance(v, ma.core.MaskedArray)) + self.assertTrue(isinstance(v, ma.masked_array)) assert_array_almost_equal(v, self.v) f.close() @@ -93,7 +93,7 @@ def test_masked(self): self.assertEqual(v_ma.dtype, "i2") self.assertTrue(isinstance(v_ma, np.ndarray)) - self.assertTrue(isinstance(v_ma, ma.core.MaskedArray)) + self.assertTrue(isinstance(v_ma, ma.masked_array)) assert_array_almost_equal(v_ma, self.v_ma) f.close() @@ -118,7 +118,7 @@ def test_unmasked(self): self.assertEqual(v_scaled.dtype, "f8") self.assertTrue(isinstance(v_scaled, np.ndarray)) # issue 785: always return masked array by default - self.assertTrue(isinstance(v_scaled, ma.core.MaskedArray)) + self.assertTrue(isinstance(v_scaled, ma.masked_array)) assert_array_almost_equal(v_scaled, self.v_scaled) f.close() @@ -141,7 +141,7 @@ def test_masked(self): self.assertEqual(v_ma_scaled.dtype, "f8") self.assertTrue(isinstance(v_ma_scaled, np.ndarray)) - self.assertTrue(isinstance(v_ma_scaled, ma.core.MaskedArray)) + self.assertTrue(isinstance(v_ma_scaled, ma.masked_array)) assert_array_almost_equal(v_ma_scaled, self.v_ma_scaled) f.close() diff --git a/test/test_slicing.py b/test/test_slicing.py index 8d3f88b7d..16d384ded 100644 --- a/test/test_slicing.py +++ b/test/test_slicing.py @@ -103,7 +103,7 @@ def test_0d(self): assert_equal(v.shape, v[...].shape) # issue #785: always return masked array #assert type(v[...]) == np.ndarray - assert type(v[...]) == np.ma.core.MaskedArray + assert type(v[...]) == np.ma.masked_array f.set_auto_mask(False) assert type(v[...]) == np.ndarray f.close() From 8806f10bb7ab6e7f0c6b01cee95066328ea3135b Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Sat, 13 Jul 2024 00:22:25 -0700 Subject: [PATCH 1212/1504] Add some assertions for static typing --- test/test_multifile.py | 1 + test/test_multifile2.py | 1 + 2 files changed, 2 insertions(+) diff --git a/test/test_multifile.py b/test/test_multifile.py index 93d72bded..2301ebdf9 100644 --- a/test/test_multifile.py +++ b/test/test_multifile.py @@ -52,6 +52,7 @@ def runTest(self): assert_array_equal(np.arange(0,nx),f.variables['x'][:]) varin = f.variables['data'] datin = varin[:] + assert isinstance(data, np.ma.masked_array) assert_array_equal(datin.mask,data.mask) varin.set_auto_maskandscale(False) data2 = data.filled() diff --git a/test/test_multifile2.py b/test/test_multifile2.py index f8e8552a6..d5b310955 100644 --- a/test/test_multifile2.py +++ b/test/test_multifile2.py @@ -52,6 +52,7 @@ def runTest(self): assert_array_equal(np.arange(0,nx),f.variables['x'][:]) varin = f.variables['data'] datin = varin[:] + assert isinstance(data, np.ma.masked_array) assert_array_equal(datin.mask,data.mask) varin.set_auto_maskandscale(False) data2 = data.filled() From bb330c61f561c0757c565b1e169a0631c6cbbf4e Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Sat, 13 Jul 2024 00:23:50 -0700 Subject: [PATCH 1213/1504] minor static typing additions --- test/test_types.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/test/test_types.py b/test/test_types.py index 0bd910a3f..e0ec74c76 100644 --- a/test/test_types.py +++ b/test/test_types.py @@ -52,10 +52,11 @@ def runTest(self): for typ in datatypes: data = f.variables['data_'+typ] data.set_auto_maskandscale(False) - datarr = data[1:n1dim] + datarr: np.ndarray = data[1:n1dim] # fill missing data with _FillValue # ('S1' array will have some missing values) if hasattr(datarr, 'mask'): + assert isinstance(datarr, np.ma.masked_array) datarr = datarr.filled() datfilled = data[0] # check to see that data type is correct From 513e4d677884cf8ad075c8a184ddb7dfcf3d9d05 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Sat, 13 Jul 2024 00:24:18 -0700 Subject: [PATCH 1214/1504] use np.ndarray.tobytes instead of deprecated tostring --- test/test_types.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/test/test_types.py b/test/test_types.py index e0ec74c76..7e2a998ee 100644 --- a/test/test_types.py +++ b/test/test_types.py @@ -69,7 +69,7 @@ def runTest(self): #assert np.allclose(datarr, ranarr[1:n1dim].astype(data.dtype)) assert_array_almost_equal(datarr,ranarr[1:n1dim].astype(data.dtype)) else: - assert datarr.tostring() == ranarr[1:n1dim].astype(data.dtype).tostring() + assert datarr.tobytes() == ranarr[1:n1dim].astype(data.dtype).tobytes() # check that variable elements not yet written are filled # with the specified _FillValue. assert_array_equal(datfilled,np.asarray(data._FillValue,datfilled.dtype)) From c81f60dc166d6f8e4d746850083cb98c3a1d2572 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Sat, 13 Jul 2024 22:30:36 -0700 Subject: [PATCH 1215/1504] __dealloc__ seems to be a cython-only member of Dataset --- src/netCDF4/__init__.pyi | 1 - 1 file changed, 1 deletion(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 951326548..b881912c9 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -412,7 +412,6 @@ class Dataset: def __setattr__(self, name: str, value: Any) -> None: ... def __getattr__(self, name: str) -> Any: ... def __delattr__(self, name: str): ... - def __dealloc__(self) -> None: ... def __reduce__(self) -> NoReturn: ... def __enter__(self) -> Self: ... def __exit__(self, atype, value, traceback) -> None: ... From 62d97f3736b1046dd276ac35136b1697ce19c9d6 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Sat, 13 Jul 2024 22:30:48 -0700 Subject: [PATCH 1216/1504] Update stubtest-allowlist --- .github/stubtest-allowlist | 40 +++++++++++++++++++++----------------- 1 file changed, 22 insertions(+), 18 deletions(-) diff --git a/.github/stubtest-allowlist b/.github/stubtest-allowlist index a3bd3a1a4..afddeb272 100644 --- a/.github/stubtest-allowlist +++ b/.github/stubtest-allowlist @@ -1,13 +1,22 @@ -netCDF4.AccessModeOptions -netCDF4.CompressionLevelOptions -netCDF4.CompressionOptions -netCDF4.DatatypeOptions -netCDF4.DimensionsOptions -netCDF4.DiskFormatOptions -netCDF4.EndianOptions -netCDF4.FormatOptions -netCDF4.QuantizeOptions -netCDF4.CalendarOptions +netCDF4.RealTypeLiteral +netCDF4.ComplexTypeLiteral +netCDF4.NumericTypeLiteral +netCDF4.CharTypeLiteral +netCDF4.TypeLiteral +netCDF4.NumPyRealType +netCDF4.NumPyComplexType +netCDF4.NumPyNumericType +netCDF4.NetCDFUDTClass +netCDF4.AccessMode +netCDF4.CompressionLevel +netCDF4.CompressionType +netCDF4.DatatypeSpecifier +netCDF4.DimensionsSpecifier +netCDF4.DiskFormat +netCDF4.EndianType +netCDF4.Format +netCDF4.QuantizeMode +netCDF4.CalendarType netCDF4.ellipsis netCDF4.DateTimeArray netCDF4.FiltersDict @@ -15,15 +24,10 @@ netCDF4.SzipInfo netCDF4.BloscInfo netCDF4.BoolInt netCDF4.GetSetItemKey -netCDF4.T_Datatype -netCDF4.T_DatatypeNC -netCDF4.Dataset.__dealloc -netCDF4.Dimension.__reduce_cython__ -netCDF4.Dimension.__setstate_cython__ +netCDF4.VarT +netCDF4.NumericVarT +netCDF4.Dataset netCDF4.Variable.auto_complex -netCDF4._netCDF4.Dataset.__dealloc -netCDF4._netCDF4.Dimension.__reduce_cython__ -netCDF4._netCDF4.Dimension.__setstate_cython__ netCDF4._netCDF4.NC_DISKLESS netCDF4._netCDF4.NC_PERSIST netCDF4._netCDF4.Variable.auto_complex From 77bec6b9d237b80e39984cb4a44ffd5a9e4e83aa Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Sat, 13 Jul 2024 23:40:49 -0700 Subject: [PATCH 1217/1504] Restore some missing needed entires --- .github/stubtest-allowlist | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/.github/stubtest-allowlist b/.github/stubtest-allowlist index afddeb272..ed56536bf 100644 --- a/.github/stubtest-allowlist +++ b/.github/stubtest-allowlist @@ -26,8 +26,11 @@ netCDF4.BoolInt netCDF4.GetSetItemKey netCDF4.VarT netCDF4.NumericVarT -netCDF4.Dataset +netCDF4.Dimension.__reduce_cython__ +netCDF4.Dimension.__setstate_cython__ netCDF4.Variable.auto_complex +netCDF4._netCDF4.Dimension.__reduce_cython__ +netCDF4._netCDF4.Dimension.__setstate_cython__ netCDF4._netCDF4.NC_DISKLESS netCDF4._netCDF4.NC_PERSIST netCDF4._netCDF4.Variable.auto_complex From 13d625a11d065c36fa8318579c016451c1a58d46 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Tue, 16 Jul 2024 10:49:03 -0700 Subject: [PATCH 1218/1504] Return Any rather than Union from datatype for now --- src/netCDF4/__init__.pyi | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index b881912c9..a3b4e6beb 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -536,7 +536,7 @@ class Variable(Generic[VarT]): @property def dtype(self) -> Any: ... # actually np.dtype | type[str] @property - def datatype(self) -> np.dtype | NetCDFUDTClass: ... + def datatype(self) -> Any: ... # Actually np.dtype | NetCDFUDTClass @property def shape(self) -> tuple[int, ...]: ... @property From e086579e7484da8daa52991a18b8c524d464a78c Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Tue, 16 Jul 2024 16:24:40 -0700 Subject: [PATCH 1219/1504] All arguments that take literals should allow arbitrary strings also. Literals retained for introspection/documentation. --- src/netCDF4/__init__.pyi | 28 ++++++++++++++-------------- 1 file changed, 14 insertions(+), 14 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index a3b4e6beb..f9ad9f615 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -217,21 +217,21 @@ default_fillvals: dict[str, int | float | str] def date2index( dates: dt.datetime | cftime.datetime | Sequence[dt.datetime | cftime.datetime] | DateTimeArray, nctime: Variable, - calendar: CalendarType | None = None, + calendar: CalendarType | str | None = None, select: Literal["exact", "before", "after", "nearest"] = "exact", has_year_zero: bool | None = None, ) -> int | npt.NDArray[np.int_]: ... def date2num( dates: dt.datetime | cftime.datetime | Sequence[dt.datetime | cftime.datetime] | DateTimeArray, units: str, - calendar: CalendarType | None = None, + calendar: CalendarType | str | None = None, has_year_zero: bool | None = None, longdouble: bool = False, ) -> np.number | npt.NDArray[np.number]: ... def num2date( times: Sequence[int | float | np.number] | npt.NDArray[np.number], units: str, - calendar: CalendarType = "standard", + calendar: CalendarType | str = "standard", only_use_cftime_datetimes: bool = True, only_use_python_datetimes: bool = False, has_year_zero: bool | None = None, @@ -246,9 +246,9 @@ class Dataset: def __init__( self, filename: str | os.PathLike, - mode: AccessMode = "r", + mode: AccessMode | str = "r", clobber: bool = True, - format: Format = "NETCDF4", + format: Format | str = "NETCDF4", diskless: bool = False, persist: bool = False, keepweakref: bool = False, @@ -316,7 +316,7 @@ class Dataset: fletcher32: Any = False, contiguous: Any = False, chunksizes: int | None = None, - endian: EndianType = "native", + endian: EndianType | str = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode | str = "BitGroom", @@ -339,7 +339,7 @@ class Dataset: fletcher32: Any = False, contiguous: Any = False, chunksizes: int | None = None, - endian: EndianType = "native", + endian: EndianType | str = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode | str = "BitGroom", @@ -362,7 +362,7 @@ class Dataset: fletcher32: Any = False, contiguous: Any = False, chunksizes: int | None = None, - endian: EndianType = "native", + endian: EndianType | str = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode | str = "BitGroom", @@ -398,7 +398,7 @@ class Dataset: def get_variables_by_attributes(self, **kwargs: Callable[[Any], bool] | Any) -> list[Variable]: ... @staticmethod def fromcdl( - cdlfilename: str, ncfilename: str | None = None, mode: AccessMode = "a", format: Format = "NETCDF4" + cdlfilename: str, ncfilename: str | None = None, mode: AccessMode | str = "a", format: Format | str = "NETCDF4" ) -> Dataset: ... @overload def tocdl(self, coordvars: bool = False, data: bool = False, outfile: None = None) -> str: ... @@ -449,7 +449,7 @@ class Variable(Generic[VarT]): fletcher32: Any = False, contiguous: Any = False, chunksizes: Sequence[int] | None = None, - endian: EndianType = "native", + endian: EndianType | str = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode | str = "BitGroom", @@ -474,7 +474,7 @@ class Variable(Generic[VarT]): fletcher32: Any = False, contiguous: Any = False, chunksizes: Sequence[int] | None = None, - endian: EndianType = "native", + endian: EndianType | str = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode | str = "BitGroom", @@ -499,7 +499,7 @@ class Variable(Generic[VarT]): fletcher32: Any = False, contiguous: Any = False, chunksizes: Sequence[int] | None = None, - endian: EndianType = "native", + endian: EndianType | str = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode | str = "BitGroom", @@ -523,7 +523,7 @@ class Variable(Generic[VarT]): fletcher32: Any = False, contiguous: Any = False, chunksizes: Sequence[int] | None = None, - endian: EndianType = "native", + endian: EndianType | str = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode | str = "BitGroom", @@ -673,7 +673,7 @@ class MFTime(_Variable): calendar: CalendarType | None units: str | None - def __init__(self, time: Variable, units: str | None = None, calendar: CalendarType | None = None): ... + def __init__(self, time: Variable, units: str | None = None, calendar: CalendarType | str | None = None): ... def __getitem__(self, elem: GetSetItemKey) -> np.ndarray: ... @overload From 4bad04f8cf471843997369b33edfc591fc2fbeb3 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Tue, 16 Jul 2024 16:25:55 -0700 Subject: [PATCH 1220/1504] Minor test fixes based on mypy/pyright checking --- test/test_compound_alignment.py | 2 +- test/test_multifile.py | 2 +- test/test_multifile2.py | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/test/test_compound_alignment.py b/test/test_compound_alignment.py index 0e1c36919..7b8c553b6 100644 --- a/test/test_compound_alignment.py +++ b/test/test_compound_alignment.py @@ -99,7 +99,7 @@ def runTest(self): f = netCDF4.Dataset(self.file, 'r') new_cells = f.variables["cells"][:] assert new_cells.shape == cells.shape - assert sorted(new_cells.dtype.names) == sorted(cells.dtype.names) + assert cells.dtype.names and sorted(new_cells.dtype.names) == sorted(cells.dtype.names) for name in cells.dtype.names: assert cells[name].dtype.name == new_cells[name].dtype.name assert cells[name].shape == new_cells[name].shape diff --git a/test/test_multifile.py b/test/test_multifile.py index 2301ebdf9..f9251c87f 100644 --- a/test/test_multifile.py +++ b/test/test_multifile.py @@ -74,7 +74,7 @@ def runTest(self): # testing multi-file get_variables_by_attributes f = MFDataset(self.files,check=True) assert f.get_variables_by_attributes(axis='T') == [] - f.get_variables_by_attributes(units='zlotys')[0] == f['x'] + assert f.get_variables_by_attributes(units='zlotys')[0] == f['x'] assert f.isopen() f.close() assert not f.isopen() diff --git a/test/test_multifile2.py b/test/test_multifile2.py index d5b310955..3ab3d482b 100644 --- a/test/test_multifile2.py +++ b/test/test_multifile2.py @@ -107,8 +107,8 @@ def runTest(self): # Get the real dates # skip this until cftime pull request #55 is in a released # version (1.0.1?). Otherwise, fix for issue #808 breaks this + dates = [] if Version(cftime.__version__) >= Version('1.0.1'): - dates = [] for file in self.files: f = Dataset(file) t = f.variables['time'] From 84d5b41dcbf16bf111f5f417db75d2e2affb4c70 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Tue, 16 Jul 2024 16:29:55 -0700 Subject: [PATCH 1221/1504] Use descriptor stubs to overload datatype and dtype properties --- .github/stubtest-allowlist | 2 ++ src/netCDF4/__init__.pyi | 30 ++++++++++++++++++++++++++---- 2 files changed, 28 insertions(+), 4 deletions(-) diff --git a/.github/stubtest-allowlist b/.github/stubtest-allowlist index ed56536bf..44fa8ce8d 100644 --- a/.github/stubtest-allowlist +++ b/.github/stubtest-allowlist @@ -25,6 +25,8 @@ netCDF4.BloscInfo netCDF4.BoolInt netCDF4.GetSetItemKey netCDF4.VarT +netCDF4.RealVarT +netCDF4.ComplexVarT netCDF4.NumericVarT netCDF4.Dimension.__reduce_cython__ netCDF4.Dimension.__setstate_cython__ diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index f9ad9f615..4c007356c 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -122,6 +122,8 @@ DatatypeSpecifier: TypeAlias = ( ) VarT = TypeVar("VarT") +RealVarT = TypeVar("RealVarT", bound=NumPyRealType) +ComplexVarT = TypeVar("ComplexVarT", bound=NumPyComplexType) NumericVarT = TypeVar("NumericVarT", bound=NumPyNumericType) DimensionsSpecifier: TypeAlias = Union[str, bytes, Dimension, Iterable[Union[str, bytes, Dimension]]] @@ -430,6 +432,28 @@ class Dimension: def isunlimited(self) -> bool: ... def __len__(self) -> int: ... +class _VarDatatypeProperty: + # A descriptor definition of the property to allow overloads + @overload + def __get__(self, instance: Variable[RealVarT], owner: Any) -> RealVarT: ... + @overload + def __get__(self, instance: Variable[ComplexVarT], owner: Any) -> CompoundType: ... + @overload + def __get__(self, instance: Variable[str], owner: Any) -> VLType: ... + @overload + def __get__( + self, instance: Variable[Any], owner: Any + ) -> Any: ... # actual return type np.dtype | CompoundType | VLType | EnumType + +class _VarDtypeProperty: + # A descriptor definition of the property to allow overloads + @overload + def __get__(self, instance: Variable[NumericVarT], owner: Any) -> np.dtype[NumericVarT]: ... + @overload + def __get__(self, instance: Variable[str], owner: Any) -> type[str]: ... + @overload + def __get__(self, instance: Variable[Any], owner: Any) -> Any: ... # actual return type np.dtype | Type[str] + class Variable(Generic[VarT]): # Overloads of __new__ are provided for some cases where the Variable's type may be statically inferred from the datatype arg @overload @@ -531,13 +555,11 @@ class Variable(Generic[VarT]): chunk_cache: int | None = None, **kwargs: Any, ) -> None: ... + datatype: _VarDatatypeProperty + dtype: _VarDtypeProperty @property def name(self) -> str: ... @property - def dtype(self) -> Any: ... # actually np.dtype | type[str] - @property - def datatype(self) -> Any: ... # Actually np.dtype | NetCDFUDTClass - @property def shape(self) -> tuple[int, ...]: ... @property def size(self) -> int: ... From 75dab94e9a5a2f419d0c3fa5627a3454e9df4577 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 17 Jul 2024 09:02:19 -0700 Subject: [PATCH 1222/1504] explain type: ignore --- test/test_enum.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/test/test_enum.py b/test/test_enum.py index 536cb0a27..ca59cff49 100644 --- a/test/test_enum.py +++ b/test/test_enum.py @@ -27,7 +27,7 @@ def setUp(self): cloud_type = f.createEnumType(ENUM_BASETYPE,ENUM_NAME,ENUM_DICT) # make sure KeyError raised if non-integer basetype used. try: - cloud_typ2 = f.createEnumType(np.float32,ENUM_NAME,ENUM_DICT) # type: ignore + cloud_typ2 = f.createEnumType(np.float32,ENUM_NAME,ENUM_DICT) # type: ignore # mypy correctly doesn't like float32 except KeyError: pass f.createDimension('time',None) From 577a437f2c6dceefe85ec5bec59afc29bdb279cf Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 17 Jul 2024 09:04:10 -0700 Subject: [PATCH 1223/1504] Fix from mypy - don't use the same name for different meanings in a fn --- test/test_multifile.py | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/test/test_multifile.py b/test/test_multifile.py index f9251c87f..ddfc05ada 100644 --- a/test/test_multifile.py +++ b/test/test_multifile.py @@ -124,13 +124,13 @@ def runTest(self): # Get the real dates dates = [] for file in self.files: - f = Dataset(file) - t = f.variables['time'] + ds = Dataset(file) + t = ds.variables['time'] dates.extend(cftime.num2date(t[:], t.units, calendar)) - f.close() + ds.close() # Compare with the MF dates - f = MFDataset(self.files,check=True) - t = f.variables['time'] + ds = MFDataset(self.files,check=True) + t = ds.variables['time'] T = MFTime(t, calendar=calendar) assert_equal(T.calendar, calendar) assert_equal(len(T), len(t)) @@ -142,7 +142,7 @@ def runTest(self): if Version(cftime.__version__) >= Version('1.0.1'): assert_array_equal(cftime.num2date(T[:], T.units, T.calendar), dates) assert_equal(cftime.date2index(datetime.datetime(1980, 1, 2), T), 366) - f.close() + ds.close() # Test exception is raised when no calendar attribute is available on the # time variable. @@ -154,8 +154,8 @@ def runTest(self): # variables. First, add calendar attributes to file. Note this will modify # the files inplace. calendars = ['standard', 'gregorian'] - for idx, f in enumerate(self.files): - with Dataset(f, 'a') as ds: + for idx, file in enumerate(self.files): + with Dataset(file, 'a') as ds: ds.variables['time'].calendar = calendars[idx] with MFDataset(self.files, check=True) as ds: with self.assertRaises(ValueError): From 2fcf116330aa5845eb3e3a0bdf92c1d21f3ad3fd Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 17 Jul 2024 09:15:32 -0700 Subject: [PATCH 1224/1504] Add some type: ignore for redefitions mypy doesn't like --- test/test_utils.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/test/test_utils.py b/test/test_utils.py index af205be4c..65360c42a 100644 --- a/test/test_utils.py +++ b/test/test_utils.py @@ -53,7 +53,7 @@ def test_fancy(self): try: - elem = ( np.arange(6).reshape((3,2)), slice(None), slice(None) ) + elem = ( np.arange(6).reshape((3,2)), slice(None), slice(None) ) # type: ignore # mypy doesn't like redefinition of elem here start, count, stride, put_ind = _StartCountStride(elem, (3,4,5)) except IndexError: pass @@ -90,7 +90,7 @@ def test_put_indices(self): start, count, stride, put_ind = _StartCountStride(elem, (3,4,5)) orig = np.arange(60).reshape((3,4,5)) dest = np.empty(_out_array_shape(count)) - dest[tuple(put_ind[0,0,0])] = orig[tuple(elem)] + dest[tuple(put_ind[0,0,0])] = orig[tuple(elem)] # type: ignore # mypy doesn't like indexing of orig, but it's OK def test_boolean(self): elem = (1, slice(None), np.array([True, True, False, False, True])) @@ -198,14 +198,14 @@ def test_ellipsis(self): assert_equal(put_ind[0,0,0,0,0], (slice(None), slice(None), slice(None), slice(None), slice(None))) try: - elem=(Ellipsis, [15,16,17,18,19], slice(None)) + elem=(Ellipsis, [15,16,17,18,19], slice(None)) # type: ignore # mypy doesn't like redefinition of elem here start, count, stride, put_ind = _StartCountStride(elem, (2,10,20,10,10)) assert_equal(None, 'Should throw an exception') except IndexError as e: assert_equal(str(e), "integer index exceeds dimension size") try: - elem=(Ellipsis, [15,16,17,18,19], Ellipsis) + elem=(Ellipsis, [15,16,17,18,19], Ellipsis) # type: ignore # mypy doesn't like redefinition of elem here start, count, stride, put_ind = _StartCountStride(elem, (2,10, 20,10,10)) assert_equal(None, 'Should throw an exception') except IndexError as e: @@ -303,7 +303,7 @@ def test_ellipsis(self): assert_equal(take_ind[0,0,0,0,0], (slice(None), slice(None), slice(None), slice(None), slice(None))) try: - elem=(Ellipsis, [15,16,17,18,19], slice(None)) + elem=(Ellipsis, [15,16,17,18,19], slice(None)) # type: ignore # mypy doesn't like redefinition of elem here start, count, stride, take_ind = _StartCountStride(elem, (2,10,20,10,10),\ ['time', 'z', 'y', 'x'], grp, (2,10,5,10,10), put=True) assert_equal(None, 'Should throw an exception') @@ -312,7 +312,7 @@ def test_ellipsis(self): assert_equal(str(e), "list index out of range") try: - elem=(Ellipsis, [15,16,17,18,19], Ellipsis) + elem=(Ellipsis, [15,16,17,18,19], Ellipsis) # type: ignore # mypy doesn't like redefinition of elem here start, count, stride, take_ind = _StartCountStride(elem, (2,10, 20,10,10),\ ['time', 'z', 'y', 'x'], grp, (2,10,5,10,10), put=True) assert_equal(None, 'Should throw an exception') From d5f87dab3b600d1e47621ebff92025bf8dda6b87 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 17 Jul 2024 09:18:57 -0700 Subject: [PATCH 1225/1504] Make mypy more thorough by checking contents of untyped functions --- .github/workflows/build_master.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index f8f841636..aab37eefb 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -83,5 +83,5 @@ jobs: - name: Stubtest run: | stubtest netCDF4 --allowlist .github/stubtest-allowlist --mypy-config-file=pyproject.toml - mypy test - mypy examples + mypy test --check-untyped-defs --allow-redefinition + mypy examples --check-untyped-defs --allow-redefinition From aee46f8f91208afefb3f739c6f5db638b46ee7a7 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 17 Jul 2024 09:20:01 -0700 Subject: [PATCH 1226/1504] Add faux __iter__ method to Variable so type-checkers believe that it's iterable. --- src/netCDF4/__init__.pyi | 2 ++ 1 file changed, 2 insertions(+) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 4c007356c..9fd408187 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -36,6 +36,7 @@ from typing import ( Final, Generic, Iterable, + Iterator, Literal, Mapping, NoReturn, @@ -611,6 +612,7 @@ class Variable(Generic[VarT]): def __setitem__(self, elem: GetSetItemKey, data: npt.ArrayLike) -> None: ... def __array__(self) -> np.ndarray: ... def __len__(self) -> int: ... + def __iter__(self) -> Iterator[Any]: ... # faux method so mypy believes Variable is iterable class CompoundType: dtype: np.dtype From d41ea1572c8ea2f194e6f88aa6bce293165488c1 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 17 Jul 2024 09:25:35 -0700 Subject: [PATCH 1227/1504] Actually test for expected warning --- test/test_masked.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/test/test_masked.py b/test/test_masked.py index 0775f29ad..3cb2bf786 100644 --- a/test/test_masked.py +++ b/test/test_masked.py @@ -93,7 +93,8 @@ def setUp(self): # of raising an exception when auto-converted slice to a # masked array with netCDF4.Dataset(pathlib.Path(__file__).parent / "issue1152.nc") as dataset: - data = dataset['v'][:] + with self.assertWarns(UserWarning): + data = dataset['v'][:] # issue #1271 (mask is ignored when assigning bool array to uint8 var) ds = netCDF4.Dataset(self.file3, "w") From 19c736ffbed86a7b8a280f13623b1b7b3ba8a6de Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 17 Jul 2024 09:52:42 -0700 Subject: [PATCH 1228/1504] Updated allowlist with faux __iter__ method --- .github/stubtest-allowlist | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.github/stubtest-allowlist b/.github/stubtest-allowlist index 44fa8ce8d..c362121e0 100644 --- a/.github/stubtest-allowlist +++ b/.github/stubtest-allowlist @@ -31,11 +31,13 @@ netCDF4.NumericVarT netCDF4.Dimension.__reduce_cython__ netCDF4.Dimension.__setstate_cython__ netCDF4.Variable.auto_complex +netCDF4.Variable.__iter__ netCDF4._netCDF4.Dimension.__reduce_cython__ netCDF4._netCDF4.Dimension.__setstate_cython__ netCDF4._netCDF4.NC_DISKLESS netCDF4._netCDF4.NC_PERSIST netCDF4._netCDF4.Variable.auto_complex +netCDF4._netCDF4.Variable.__iter__ netCDF4._netCDF4.__reduce_cython__ netCDF4._netCDF4.__setstate_cython__ netCDF4._netCDF4.__test__ From cfb5fcb5447fd5033f78e3b9146d423f5f4c9312 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 17 Jul 2024 11:16:07 -0700 Subject: [PATCH 1229/1504] Allow specifying more verbosity in test/run_all.py --- test/run_all.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/test/run_all.py b/test/run_all.py index deff8c6af..b99565963 100755 --- a/test/run_all.py +++ b/test/run_all.py @@ -24,7 +24,7 @@ sys.stdout.write('netcdf lib version: %s\n' % __netcdf4libversion__) sys.stdout.write('numpy version %s\n' % numpy.__version__) sys.stdout.write('cython version %s\n' % cython.__version__) - runner = unittest.TextTestRunner(verbosity=1) + runner = unittest.TextTestRunner(verbosity=(2 if "-v" in sys.argv else 1)) result = runner.run(testsuite) if not result.wasSuccessful(): sys.exit(1) From fbcb79f0b2079f3182913e7293aac1cb5254b0be Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 17 Jul 2024 11:19:04 -0700 Subject: [PATCH 1230/1504] Fix EnumDictTestCase not called due to bad indentation --- test/test_enum.py | 19 +++++++++++-------- 1 file changed, 11 insertions(+), 8 deletions(-) diff --git a/test/test_enum.py b/test/test_enum.py index ca59cff49..90761d849 100644 --- a/test/test_enum.py +++ b/test/test_enum.py @@ -66,6 +66,7 @@ def runTest(self): f.close() class EnumDictTestCase(unittest.TestCase): + # issue 1128 def setUp(self): DT = np.int16; BITS = 8 @@ -79,14 +80,16 @@ def setUp(self): ev = nc.createVariable('evar', et) # Succeeds because the created EnumType does keep the correct dict ev[...] = self.STORED_VAL - def tearDown(self): - os.remove(self.file) - def runTest(self): - with netCDF4.Dataset(self.file, 'r') as nc: - read_var = nc['evar'] - read_et = nc.enumtypes["etype"] - assert read_var[...] == self.STORED_VAL - assert read_et.enum_dict == self.VAL_MAP + + def tearDown(self): + os.remove(self.file) + + def runTest(self): + with netCDF4.Dataset(self.file, 'r') as nc: + read_var = nc['evar'] + read_et = nc.enumtypes["etype"] + assert read_var[...] == self.STORED_VAL + assert read_et.enum_dict == self.VAL_MAP if __name__ == '__main__': unittest.main() From ac985501ccd5332ce33d4c43baa95487cfc72e37 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 17 Jul 2024 12:13:35 -0700 Subject: [PATCH 1231/1504] Allow str as key for variable --- src/netCDF4/__init__.pyi | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 9fd408187..7b12dd809 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -149,13 +149,14 @@ DateTimeArray: TypeAlias = npt.NDArray[np.object_] GetSetItemKey: TypeAlias = ( int | float + | str # strs that can be cooerced to ints | np.number | slice | ellipsis | list[int] | list[float] | list[bool] - | list[str] # strs that can be cooerced to ints + | list[str] | list[int | float] | list[int | bool] | list[int | str] From 866ae476fde9829d939868da15b3b8af6fb20ed6 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 17 Jul 2024 12:55:35 -0700 Subject: [PATCH 1232/1504] minor comment update --- src/netCDF4/__init__.pyi | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 7b12dd809..683a446f8 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -435,7 +435,7 @@ class Dimension: def __len__(self) -> int: ... class _VarDatatypeProperty: - # A descriptor definition of the property to allow overloads + # A faux descriptor definition of the property to allow overloads @overload def __get__(self, instance: Variable[RealVarT], owner: Any) -> RealVarT: ... @overload @@ -448,7 +448,7 @@ class _VarDatatypeProperty: ) -> Any: ... # actual return type np.dtype | CompoundType | VLType | EnumType class _VarDtypeProperty: - # A descriptor definition of the property to allow overloads + # A faux descriptor definition of the property to allow overloads @overload def __get__(self, instance: Variable[NumericVarT], owner: Any) -> np.dtype[NumericVarT]: ... @overload From 2668887bb7e3fa94ab150f450875e851cd4440b2 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 22 Jul 2024 21:38:22 +0200 Subject: [PATCH 1233/1504] run with pytest --- .github/workflows/miniconda.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index 256579c70..a79c8e572 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -45,7 +45,7 @@ jobs: - name: Tests run: | - cd test && python run_all.py + pytest -s -rxs -v test run-mpi: runs-on: ${{ matrix.os }} From ab8cc39a978bcb60d892227398fa8715b651b0be Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 22 Jul 2024 21:39:18 +0200 Subject: [PATCH 1234/1504] error out in deprecation warnings --- pyproject.toml | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/pyproject.toml b/pyproject.toml index 8c8c8a327..750e5f59f 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -77,6 +77,10 @@ where = ["src"] [tool.pytest.ini_options] pythonpath = ["test"] +filterwarnings = [ + "error", + "ignore::UserWarning", +] [tool.mypy] files = ["src/netCDF4"] From 49b7c47d6bb45459b1b038e90a01c100eda93509 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 22 Jul 2024 21:40:31 +0200 Subject: [PATCH 1235/1504] doesn't need to hold tz --- test/test_dap.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/test/test_dap.py b/test/test_dap.py index 8d2ea664e..370184861 100644 --- a/test/test_dap.py +++ b/test/test_dap.py @@ -7,7 +7,7 @@ # test accessing data over http with opendap. -yesterday = datetime.utcnow() - timedelta(days=1) +yesterday = datetime.now() - timedelta(days=1) URL = f'http://nomads.ncep.noaa.gov/dods/gfs_1p00/gfs{yesterday:%Y%m%d}/gfs_1p00_00z' URL_https = 'https://www.neracoos.org/erddap/griddap/WW3_EastCoast_latest' varname = 'hgtsfc' From 9a4b949b0965b5d0401542feeb5dc9f14cd6dde8 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 22 Jul 2024 21:50:30 +0200 Subject: [PATCH 1236/1504] fix 1351 --- src/netCDF4/_netCDF4.pyx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index b912cdfb6..9bbc3aaf6 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -5315,7 +5315,7 @@ rename a `Variable` attribute named `oldname` to `newname`.""" # corresponds to missing values, don't fill masked array - # just use underlying data instead if hasattr(self, 'missing_value') and \ - numpy.all(numpy.in1d(data.data[data.mask],self.missing_value)): + numpy.all(numpy.isin(data.data[data.mask],self.missing_value)): data = data.data else: if hasattr(self, 'missing_value'): From d6b4f037f59fafe5d3d2cf102bd66cb4183c2d94 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Mon, 22 Jul 2024 21:50:44 +0200 Subject: [PATCH 1237/1504] fix tostring deprecation --- test/test_stringarr.py | 2 +- test/test_types.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/test/test_stringarr.py b/test/test_stringarr.py index 8b57eceaa..24c890fb2 100644 --- a/test/test_stringarr.py +++ b/test/test_stringarr.py @@ -41,7 +41,7 @@ def setUp(self): v2[:-1] = data[:-1] v2[-1] = data[-1] v2[-1,-1] = data[-1,-1] # write single element - v2[-1,-1] = data[-1,-1].tostring() # write single python string + v2[-1,-1] = data[-1,-1].tobytes() # write single python string # _Encoding should be ignored if an array of characters is specified v3[:] = stringtochar(data, encoding='ascii') nc.close() diff --git a/test/test_types.py b/test/test_types.py index 0bd910a3f..048843a98 100644 --- a/test/test_types.py +++ b/test/test_types.py @@ -68,7 +68,7 @@ def runTest(self): #assert np.allclose(datarr, ranarr[1:n1dim].astype(data.dtype)) assert_array_almost_equal(datarr,ranarr[1:n1dim].astype(data.dtype)) else: - assert datarr.tostring() == ranarr[1:n1dim].astype(data.dtype).tostring() + assert datarr.tobytes() == ranarr[1:n1dim].astype(data.dtype).tobytes() # check that variable elements not yet written are filled # with the specified _FillValue. assert_array_equal(datfilled,np.asarray(data._FillValue,datfilled.dtype)) From 252deab1ab9cfe81b5e2083863cff4b2654fc330 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 24 Jul 2024 11:56:18 -0700 Subject: [PATCH 1238/1504] Moved mypy flags to pyproject.toml --- .github/workflows/build_master.yml | 4 ++-- pyproject.toml | 2 ++ 2 files changed, 4 insertions(+), 2 deletions(-) diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index aab37eefb..f8f841636 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -83,5 +83,5 @@ jobs: - name: Stubtest run: | stubtest netCDF4 --allowlist .github/stubtest-allowlist --mypy-config-file=pyproject.toml - mypy test --check-untyped-defs --allow-redefinition - mypy examples --check-untyped-defs --allow-redefinition + mypy test + mypy examples diff --git a/pyproject.toml b/pyproject.toml index 8c8c8a327..2c058ccb8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -80,6 +80,8 @@ pythonpath = ["test"] [tool.mypy] files = ["src/netCDF4"] +check_untyped_defs = true +allow_redefinition = true [[tool.mypy.overrides]] ignore_missing_imports = true From 620faf73d9bc7905d367731af3b3b32197716cd3 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 24 Jul 2024 12:18:33 -0700 Subject: [PATCH 1239/1504] Rename variables rather than mypy ignore to avoid redefinition errors --- test/test_utils.py | 28 ++++++++++++++-------------- 1 file changed, 14 insertions(+), 14 deletions(-) diff --git a/test/test_utils.py b/test/test_utils.py index 65360c42a..12000aa6b 100644 --- a/test/test_utils.py +++ b/test/test_utils.py @@ -53,14 +53,14 @@ def test_fancy(self): try: - elem = ( np.arange(6).reshape((3,2)), slice(None), slice(None) ) # type: ignore # mypy doesn't like redefinition of elem here - start, count, stride, put_ind = _StartCountStride(elem, (3,4,5)) + elem2 = ( np.arange(6).reshape((3,2)), slice(None), slice(None) ) + start, count, stride, put_ind = _StartCountStride(elem2, (3,4,5)) except IndexError: pass # this one should be converted to a slice - elem = [slice(None), [1,3,5], 8] - start, count, stride, put_ind = _StartCountStride(elem, (50, 6, 10)) + elem3 = [slice(None), [1,3,5], 8] + start, count, stride, put_ind = _StartCountStride(elem3, (50, 6, 10)) # pull request #683 now does not convert integer sequences to strided # slices. PR #1224 reverts this behavior. assert_equal(put_ind[...,1].squeeze(), slice(None,None,None)) @@ -81,8 +81,8 @@ def test_multiple_sequences(self): assert_equal(count[...,2], 10) i = [1,3,4] - elem = (i, i, i) - start, count, stride, put_ind = _StartCountStride(elem, (50, 5, 10)) + elem2 = (i, i, i) + start, count, stride, put_ind = _StartCountStride(elem2, (50, 5, 10)) assert_equal(_out_array_shape(count), (3,3,3)) def test_put_indices(self): @@ -198,15 +198,15 @@ def test_ellipsis(self): assert_equal(put_ind[0,0,0,0,0], (slice(None), slice(None), slice(None), slice(None), slice(None))) try: - elem=(Ellipsis, [15,16,17,18,19], slice(None)) # type: ignore # mypy doesn't like redefinition of elem here - start, count, stride, put_ind = _StartCountStride(elem, (2,10,20,10,10)) + elem2=(Ellipsis, [15,16,17,18,19], slice(None)) + start, count, stride, put_ind = _StartCountStride(elem2, (2,10,20,10,10)) assert_equal(None, 'Should throw an exception') except IndexError as e: assert_equal(str(e), "integer index exceeds dimension size") try: - elem=(Ellipsis, [15,16,17,18,19], Ellipsis) # type: ignore # mypy doesn't like redefinition of elem here - start, count, stride, put_ind = _StartCountStride(elem, (2,10, 20,10,10)) + elem3=(Ellipsis, [15,16,17,18,19], Ellipsis) + start, count, stride, put_ind = _StartCountStride(elem3, (2,10, 20,10,10)) assert_equal(None, 'Should throw an exception') except IndexError as e: assert_equal(str(e), "At most one ellipsis allowed in a slicing expression") @@ -303,8 +303,8 @@ def test_ellipsis(self): assert_equal(take_ind[0,0,0,0,0], (slice(None), slice(None), slice(None), slice(None), slice(None))) try: - elem=(Ellipsis, [15,16,17,18,19], slice(None)) # type: ignore # mypy doesn't like redefinition of elem here - start, count, stride, take_ind = _StartCountStride(elem, (2,10,20,10,10),\ + elem2=(Ellipsis, [15,16,17,18,19], slice(None)) + start, count, stride, take_ind = _StartCountStride(elem2, (2,10,20,10,10),\ ['time', 'z', 'y', 'x'], grp, (2,10,5,10,10), put=True) assert_equal(None, 'Should throw an exception') except IndexError as e: @@ -312,8 +312,8 @@ def test_ellipsis(self): assert_equal(str(e), "list index out of range") try: - elem=(Ellipsis, [15,16,17,18,19], Ellipsis) # type: ignore # mypy doesn't like redefinition of elem here - start, count, stride, take_ind = _StartCountStride(elem, (2,10, 20,10,10),\ + elem3=(Ellipsis, [15,16,17,18,19], Ellipsis) + start, count, stride, take_ind = _StartCountStride(elem3, (2,10, 20,10,10),\ ['time', 'z', 'y', 'x'], grp, (2,10,5,10,10), put=True) assert_equal(None, 'Should throw an exception') except IndexError as e: From 31513eec323c102e83e5e98cba6190af6a0b279a Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 24 Jul 2024 12:25:26 -0700 Subject: [PATCH 1240/1504] Restore bool type on truthy inputs, related fix on Variable.__init__ --- src/netCDF4/__init__.pyi | 62 ++++++++++++++++++++-------------------- 1 file changed, 31 insertions(+), 31 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 4e74eaaea..a94b9b6f2 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -312,14 +312,14 @@ class Dataset: datatype: np.dtype[NumericVarT] | type[NumericVarT], dimensions: DimensionsSpecifier = (), compression: CompressionType | str | None = None, - zlib: Any = False, + zlib: bool = False, complevel: CompressionLevel | int | None = 4, - shuffle: Any = True, + shuffle: bool = True, szip_coding: Literal["nn", "ec"] | str = "nn", szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, blosc_shuffle: Literal[0, 1, 2] | int = 1, - fletcher32: Any = False, - contiguous: Any = False, + fletcher32: bool = False, + contiguous: bool = False, chunksizes: int | None = None, endian: EndianType | str = "native", least_significant_digit: int | None = None, @@ -335,14 +335,14 @@ class Dataset: datatype: np.dtype[np.str_] | type[str | np.str_], dimensions: DimensionsSpecifier = (), compression: CompressionType | str | None = None, - zlib: Any = False, + zlib: bool = False, complevel: CompressionLevel | int | None = 4, - shuffle: Any = True, + shuffle: bool = True, szip_coding: Literal["nn", "ec"] | str = "nn", szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, blosc_shuffle: Literal[0, 1, 2] | int = 1, - fletcher32: Any = False, - contiguous: Any = False, + fletcher32: bool = False, + contiguous: bool = False, chunksizes: int | None = None, endian: EndianType | str = "native", least_significant_digit: int | None = None, @@ -358,14 +358,14 @@ class Dataset: datatype: DatatypeSpecifier, dimensions: DimensionsSpecifier = (), compression: CompressionType | str | None = None, - zlib: Any = False, + zlib: bool = False, complevel: CompressionLevel | int | None = 4, - shuffle: Any = True, + shuffle: bool = True, szip_coding: Literal["nn", "ec"] | str = "nn", szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, blosc_shuffle: Literal[0, 1, 2] | int = 1, - fletcher32: Any = False, - contiguous: Any = False, + fletcher32: bool = False, + contiguous: bool = False, chunksizes: int | None = None, endian: EndianType | str = "native", least_significant_digit: int | None = None, @@ -467,14 +467,14 @@ class Variable(Generic[VarT]): datatype: np.dtype[NumericVarT] | type[NumericVarT], dimensions: DimensionsSpecifier = (), compression: CompressionType | str | None = None, - zlib: Any = False, + zlib: bool = False, complevel: CompressionLevel | int | None = 4, - shuffle: Any = True, + shuffle: bool = True, szip_coding: Literal["nn", "ec"] | str = "nn", szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, blosc_shuffle: Literal[0, 1, 2] | int = 1, - fletcher32: Any = False, - contiguous: Any = False, + fletcher32: bool = False, + contiguous: bool = False, chunksizes: Sequence[int] | None = None, endian: EndianType | str = "native", least_significant_digit: int | None = None, @@ -492,14 +492,14 @@ class Variable(Generic[VarT]): datatype: np.dtype[np.str_] | type[str | np.str_], dimensions: DimensionsSpecifier = (), compression: CompressionType | str | None = None, - zlib: Any = False, + zlib: bool = False, complevel: CompressionLevel | int | None = 4, - shuffle: Any = True, + shuffle: bool = True, szip_coding: Literal["nn", "ec"] | str = "nn", szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, blosc_shuffle: Literal[0, 1, 2] | int = 1, - fletcher32: Any = False, - contiguous: Any = False, + fletcher32: bool = False, + contiguous: bool = False, chunksizes: Sequence[int] | None = None, endian: EndianType | str = "native", least_significant_digit: int | None = None, @@ -517,14 +517,14 @@ class Variable(Generic[VarT]): datatype: DatatypeSpecifier, dimensions: DimensionsSpecifier = (), compression: CompressionType | str | None = None, - zlib: Any = False, + zlib: bool = False, complevel: CompressionLevel | int | None = 4, - shuffle: Any = True, + shuffle: bool = True, szip_coding: Literal["nn", "ec"] | str = "nn", szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, blosc_shuffle: Literal[0, 1, 2] | int = 1, - fletcher32: Any = False, - contiguous: Any = False, + fletcher32: bool = False, + contiguous: bool = False, chunksizes: Sequence[int] | None = None, endian: EndianType | str = "native", least_significant_digit: int | None = None, @@ -541,14 +541,14 @@ class Variable(Generic[VarT]): datatype: DatatypeSpecifier, dimensions: DimensionsSpecifier = (), compression: CompressionType | str | None = None, - zlib: Any = False, + zlib: bool = False, complevel: CompressionLevel | int | None = 4, - shuffle: Any = True, - szip_coding: Literal["nn", "ec"] = "nn", - szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, - blosc_shuffle: Literal[0, 1, 2] = 1, - fletcher32: Any = False, - contiguous: Any = False, + shuffle: bool = True, + szip_coding: Literal["nn", "ec"] | str = "nn", + szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, + blosc_shuffle: Literal[0, 1, 2] | int = 1, + fletcher32: bool = False, + contiguous: bool = False, chunksizes: Sequence[int] | None = None, endian: EndianType | str = "native", least_significant_digit: int | None = None, From 15151d2fe376738eed0ad19ba67229af1aeb570a Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 24 Jul 2024 12:53:21 -0700 Subject: [PATCH 1241/1504] Fix type for shuffle argument in test --- test/test_types.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/test/test_types.py b/test/test_types.py index 7e2a998ee..1f65fc5fc 100644 --- a/test/test_types.py +++ b/test/test_types.py @@ -14,7 +14,7 @@ n1dim = 5 n2dim = 10 ranarr = 100.*uniform(size=(n1dim,n2dim)) -zlib=False;complevel=0;shuffle=0;least_significant_digit=None +zlib=False;complevel=0;shuffle=False;least_significant_digit=None datatypes = ['f8','f4','i1','i2','i4','i8','u1','u2','u4','u8','S1'] FillValue = 1.0 issue273_data = np.ma.array(['z']*10,dtype='S1',\ @@ -82,7 +82,7 @@ def runTest(self): v2 = f.variables['issue273'] assert type(v2._FillValue) == bytes assert v2._FillValue == b'\x00' - assert str(issue273_data) == str(v2[:]) + assert str(issue273_data) == str(v2[:]) # issue 707 (don't apply missing_value if cast to variable type is # unsafe) v3 = f.variables['issue707'] From d982b4c7fb79ede403ceb08167cb3f00f1076476 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 24 Jul 2024 15:10:00 -0700 Subject: [PATCH 1242/1504] Make sure rc_get and rc_set are exported --- src/netCDF4/__init__.pyi | 2 ++ src/netCDF4/_netCDF4.pyi | 2 ++ 2 files changed, 4 insertions(+) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index a94b9b6f2..dd42c9103 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -63,6 +63,8 @@ __all__ = [ "VLType", "date2num", "num2date", + "rc_get", + "rc_set", "date2index", "stringtochar", "chartostring", diff --git a/src/netCDF4/_netCDF4.pyi b/src/netCDF4/_netCDF4.pyi index 759dc3004..d0bdb389f 100644 --- a/src/netCDF4/_netCDF4.pyi +++ b/src/netCDF4/_netCDF4.pyi @@ -43,6 +43,8 @@ from . import ( is_native_big, is_native_little, num2date, + rc_get, + rc_set, set_alignment, set_chunk_cache, stringtoarr, From f85bbfdaf8f6ac5d562223c807aefa21e575ee23 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 24 Jul 2024 15:10:17 -0700 Subject: [PATCH 1243/1504] Make sure mypy and stubtest exclude utils --- .github/stubtest-allowlist | 2 +- pyproject.toml | 1 + 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/.github/stubtest-allowlist b/.github/stubtest-allowlist index c362121e0..4f0e7a94d 100644 --- a/.github/stubtest-allowlist +++ b/.github/stubtest-allowlist @@ -41,4 +41,4 @@ netCDF4._netCDF4.Variable.__iter__ netCDF4._netCDF4.__reduce_cython__ netCDF4._netCDF4.__setstate_cython__ netCDF4._netCDF4.__test__ -netCDF4.utils.bytes \ No newline at end of file +netCDF4.utils \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml index 8b4feb8b1..fb245117b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -84,6 +84,7 @@ filterwarnings = [ [tool.mypy] files = ["src/netCDF4"] +exclude = "utils.py" check_untyped_defs = true allow_redefinition = true From f7b87f5c5753358b0a82ed00bc23074101bba773 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Thu, 25 Jul 2024 08:58:30 -0700 Subject: [PATCH 1244/1504] [docs] Add link to auth page on rc files. Incidentally pdoc re-inserted missing date2index and date2num stuff. --- docs/index.html | 17 ++++++++++++----- src/netCDF4/_netCDF4.pyx | 6 +++++- 2 files changed, 17 insertions(+), 6 deletions(-) diff --git a/docs/index.html b/docs/index.html index 730c955d7..377e45741 100644 --- a/docs/index.html +++ b/docs/index.html @@ -1173,7 +1173,8 @@

      Functions

      def date2index(dates, nctime, calendar=None, select='exact', has_year_zero=None)
      -

      Return indices of a netCDF time variable corresponding to the given dates.

      +

      date2index(dates, nctime, calendar=None, select=u'exact', has_year_zero=None)

      +

      Return indices of a netCDF time variable corresponding to the given dates.

      dates: A datetime object or a sequence of datetime objects. The datetime objects should not include a time-zone offset.

      nctime: A netCDF time variable object. The nctime object must have a @@ -1212,7 +1213,8 @@

      Functions

      def date2num(dates, units, calendar=None, has_year_zero=None, longdouble=False)
      -

      Return numeric time values given datetime objects. The units +

      date2num(dates, units, calendar=None, has_year_zero=None, longdouble=False)

      +

      Return numeric time values given datetime objects. The units of the numeric time values are described by the units argument and the calendar keyword. The datetime objects must be in UTC with no time-zone offset. @@ -1292,7 +1294,8 @@

      Functions

      def num2date(times, units, calendar='standard', only_use_cftime_datetimes=True, only_use_python_datetimes=False, has_year_zero=None)
      -

      Return datetime objects given numeric time values. The units +

      num2date(times, units, calendar=u'standard', only_use_cftime_datetimes=True, only_use_python_datetimes=False, has_year_zero=None)

      +

      Return datetime objects given numeric time values. The units of the numeric time values are described by the units argument and the calendar keyword. The returned datetime objects represent UTC with no time-zone offset, even if the specified @@ -1348,14 +1351,18 @@

      Functions

      rc_get(key)

      -

      Returns the internal netcdf-c rc table value corresponding to key.

      +

      Returns the internal netcdf-c rc table value corresponding to key. +See https://docs.unidata.ucar.edu/netcdf-c/current/auth.html +for more information on rc files and values.

      def rc_set(key, value)

      rc_set(key, value)

      -

      Sets the internal netcdf-c rc table value corresponding to key.

      +

      Sets the internal netcdf-c rc table value corresponding to key. +See https://docs.unidata.ucar.edu/netcdf-c/current/auth.html +for more information on rc files and values.

      def set_alignment(threshold, alignment) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 9bbc3aaf6..c31ab3f72 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1323,6 +1323,8 @@ def rc_get(key): **```rc_get(key)```** Returns the internal netcdf-c rc table value corresponding to key. +See +for more information on rc files and values. """ cdef int ierr cdef char *keyc @@ -1345,7 +1347,9 @@ def rc_set(key, value): **```rc_set(key, value)```** Sets the internal netcdf-c rc table value corresponding to key. - """ +See +for more information on rc files and values. +""" cdef int ierr cdef char *keyc cdef char *valuec From 3a6d94425dfc7bec0613d8b8897095122a5999d5 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Thu, 25 Jul 2024 09:05:36 -0700 Subject: [PATCH 1245/1504] (minor) simplify diff --- src/netCDF4/_netCDF4.pyx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index c31ab3f72..d4c6f7d53 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1349,7 +1349,7 @@ def rc_set(key, value): Sets the internal netcdf-c rc table value corresponding to key. See for more information on rc files and values. -""" + """ cdef int ierr cdef char *keyc cdef char *valuec From 40000e27aa78ce14a5be1f41c7950044d58174a7 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Thu, 25 Jul 2024 11:23:26 -0700 Subject: [PATCH 1246/1504] Add missing bzip2 to CompressionType --- src/netCDF4/__init__.pyi | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index dd42c9103..0bfd2f41d 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -130,7 +130,9 @@ ComplexVarT = TypeVar("ComplexVarT", bound=NumPyComplexType) NumericVarT = TypeVar("NumericVarT", bound=NumPyNumericType) DimensionsSpecifier: TypeAlias = Union[str, bytes, Dimension, Iterable[Union[str, bytes, Dimension]]] -CompressionType: TypeAlias = Literal["zlib", "szip", "zstd", "blosc_lz", "blosc_lz4", "blosc_lz4hc", "blosc_zlib", "blosc_zstd"] +CompressionType: TypeAlias = Literal[ + "zlib", "szip", "zstd", "bzip2", "blosc_lz", "blosc_lz4", "blosc_lz4hc", "blosc_zlib", "blosc_zstd" +] CompressionLevel: TypeAlias = Literal[0, 1, 2, 3, 4, 5, 6, 7, 8, 9] AccessMode: TypeAlias = Literal["r", "w", "r+", "a", "x", "rs", "ws", "r+s", "as"] Format: TypeAlias = Literal["NETCDF4", "NETCDF4_CLASSIC", "NETCDF3_CLASSIC", "NETCDF3_64BIT_OFFSET", "NETCDF3_64BIT_DATA"] From f24edef263e8c0afeee3ef52f216a6d603dee83b Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Thu, 25 Jul 2024 11:29:17 -0700 Subject: [PATCH 1247/1504] Restore limiting types to literals when creating datasets and variables --- src/netCDF4/__init__.pyi | 112 +++++++++++++++++++-------------------- 1 file changed, 56 insertions(+), 56 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 0bfd2f41d..834d77375 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -255,9 +255,9 @@ class Dataset: def __init__( self, filename: str | os.PathLike, - mode: AccessMode | str = "r", + mode: AccessMode = "r", clobber: bool = True, - format: Format | str = "NETCDF4", + format: Format = "NETCDF4", diskless: bool = False, persist: bool = False, keepweakref: bool = False, @@ -315,20 +315,20 @@ class Dataset: varname: str, datatype: np.dtype[NumericVarT] | type[NumericVarT], dimensions: DimensionsSpecifier = (), - compression: CompressionType | str | None = None, + compression: CompressionType | None = None, zlib: bool = False, - complevel: CompressionLevel | int | None = 4, + complevel: CompressionLevel | None = 4, shuffle: bool = True, - szip_coding: Literal["nn", "ec"] | str = "nn", - szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, - blosc_shuffle: Literal[0, 1, 2] | int = 1, + szip_coding: Literal["nn", "ec"] = "nn", + szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, + blosc_shuffle: Literal[0, 1, 2] = 1, fletcher32: bool = False, contiguous: bool = False, chunksizes: int | None = None, - endian: EndianType | str = "native", + endian: EndianType = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeMode | str = "BitGroom", + quantize_mode: QuantizeMode = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, ) -> Variable[NumericVarT]: ... @@ -338,20 +338,20 @@ class Dataset: varname: str, datatype: np.dtype[np.str_] | type[str | np.str_], dimensions: DimensionsSpecifier = (), - compression: CompressionType | str | None = None, + compression: CompressionType | None = None, zlib: bool = False, - complevel: CompressionLevel | int | None = 4, + complevel: CompressionLevel | None = 4, shuffle: bool = True, - szip_coding: Literal["nn", "ec"] | str = "nn", - szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, - blosc_shuffle: Literal[0, 1, 2] | int = 1, + szip_coding: Literal["nn", "ec"] = "nn", + szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, + blosc_shuffle: Literal[0, 1, 2] = 1, fletcher32: bool = False, contiguous: bool = False, chunksizes: int | None = None, - endian: EndianType | str = "native", + endian: EndianType = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeMode | str = "BitGroom", + quantize_mode: QuantizeMode = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, ) -> Variable[str]: ... @@ -361,20 +361,20 @@ class Dataset: varname: str, datatype: DatatypeSpecifier, dimensions: DimensionsSpecifier = (), - compression: CompressionType | str | None = None, + compression: CompressionType | None = None, zlib: bool = False, - complevel: CompressionLevel | int | None = 4, + complevel: CompressionLevel | None = 4, shuffle: bool = True, - szip_coding: Literal["nn", "ec"] | str = "nn", - szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, - blosc_shuffle: Literal[0, 1, 2] | int = 1, + szip_coding: Literal["nn", "ec"] = "nn", + szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, + blosc_shuffle: Literal[0, 1, 2] = 1, fletcher32: bool = False, contiguous: bool = False, chunksizes: int | None = None, - endian: EndianType | str = "native", + endian: EndianType = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeMode | str = "BitGroom", + quantize_mode: QuantizeMode = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, ) -> Variable: ... @@ -407,7 +407,7 @@ class Dataset: def get_variables_by_attributes(self, **kwargs: Callable[[Any], bool] | Any) -> list[Variable]: ... @staticmethod def fromcdl( - cdlfilename: str, ncfilename: str | None = None, mode: AccessMode | str = "a", format: Format | str = "NETCDF4" + cdlfilename: str, ncfilename: str | None = None, mode: AccessMode = "a", format: Format = "NETCDF4" ) -> Dataset: ... @overload def tocdl(self, coordvars: bool = False, data: bool = False, outfile: None = None) -> str: ... @@ -470,20 +470,20 @@ class Variable(Generic[VarT]): name: str, datatype: np.dtype[NumericVarT] | type[NumericVarT], dimensions: DimensionsSpecifier = (), - compression: CompressionType | str | None = None, + compression: CompressionType | None = None, zlib: bool = False, - complevel: CompressionLevel | int | None = 4, + complevel: CompressionLevel | None = 4, shuffle: bool = True, - szip_coding: Literal["nn", "ec"] | str = "nn", - szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, - blosc_shuffle: Literal[0, 1, 2] | int = 1, + szip_coding: Literal["nn", "ec"] = "nn", + szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, + blosc_shuffle: Literal[0, 1, 2] = 1, fletcher32: bool = False, contiguous: bool = False, - chunksizes: Sequence[int] | None = None, - endian: EndianType | str = "native", + chunksizes: int | None = None, + endian: EndianType = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeMode | str = "BitGroom", + quantize_mode: QuantizeMode = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any, @@ -495,20 +495,20 @@ class Variable(Generic[VarT]): name: str, datatype: np.dtype[np.str_] | type[str | np.str_], dimensions: DimensionsSpecifier = (), - compression: CompressionType | str | None = None, + compression: CompressionType | None = None, zlib: bool = False, - complevel: CompressionLevel | int | None = 4, + complevel: CompressionLevel | None = 4, shuffle: bool = True, - szip_coding: Literal["nn", "ec"] | str = "nn", - szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, - blosc_shuffle: Literal[0, 1, 2] | int = 1, + szip_coding: Literal["nn", "ec"] = "nn", + szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, + blosc_shuffle: Literal[0, 1, 2] = 1, fletcher32: bool = False, contiguous: bool = False, - chunksizes: Sequence[int] | None = None, - endian: EndianType | str = "native", + chunksizes: int | None = None, + endian: EndianType = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeMode | str = "BitGroom", + quantize_mode: QuantizeMode = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any, @@ -520,20 +520,20 @@ class Variable(Generic[VarT]): name: str, datatype: DatatypeSpecifier, dimensions: DimensionsSpecifier = (), - compression: CompressionType | str | None = None, + compression: CompressionType | None = None, zlib: bool = False, - complevel: CompressionLevel | int | None = 4, + complevel: CompressionLevel | None = 4, shuffle: bool = True, - szip_coding: Literal["nn", "ec"] | str = "nn", - szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, - blosc_shuffle: Literal[0, 1, 2] | int = 1, + szip_coding: Literal["nn", "ec"] = "nn", + szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, + blosc_shuffle: Literal[0, 1, 2] = 1, fletcher32: bool = False, contiguous: bool = False, - chunksizes: Sequence[int] | None = None, - endian: EndianType | str = "native", + chunksizes: int | None = None, + endian: EndianType = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeMode | str = "BitGroom", + quantize_mode: QuantizeMode = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any, @@ -544,20 +544,20 @@ class Variable(Generic[VarT]): name: str, datatype: DatatypeSpecifier, dimensions: DimensionsSpecifier = (), - compression: CompressionType | str | None = None, + compression: CompressionType | None = None, zlib: bool = False, - complevel: CompressionLevel | int | None = 4, + complevel: CompressionLevel | None = 4, shuffle: bool = True, - szip_coding: Literal["nn", "ec"] | str = "nn", - szip_pixels_per_block: Literal[4, 8, 16, 32] | int = 8, - blosc_shuffle: Literal[0, 1, 2] | int = 1, + szip_coding: Literal["nn", "ec"] = "nn", + szip_pixels_per_block: Literal[4, 8, 16, 32] = 8, + blosc_shuffle: Literal[0, 1, 2] = 1, fletcher32: bool = False, contiguous: bool = False, - chunksizes: Sequence[int] | None = None, - endian: EndianType | str = "native", + chunksizes: int | None = None, + endian: EndianType = "native", least_significant_digit: int | None = None, significant_digits: int | None = None, - quantize_mode: QuantizeMode | str = "BitGroom", + quantize_mode: QuantizeMode = "BitGroom", fill_value: int | float | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any, From 7eebd5a70f6c8f6d52c0a723dc72777ade9bc536 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Thu, 25 Jul 2024 11:30:45 -0700 Subject: [PATCH 1248/1504] Add np.number as valid type for fill_value --- src/netCDF4/__init__.pyi | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 834d77375..734fa83f7 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -329,7 +329,7 @@ class Dataset: least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode = "BitGroom", - fill_value: int | float | str | bytes | Literal[False] | None = None, + fill_value: int | float | np.number | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, ) -> Variable[NumericVarT]: ... @overload @@ -352,7 +352,7 @@ class Dataset: least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode = "BitGroom", - fill_value: int | float | str | bytes | Literal[False] | None = None, + fill_value: int | float | np.number | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, ) -> Variable[str]: ... @overload @@ -375,7 +375,7 @@ class Dataset: least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode = "BitGroom", - fill_value: int | float | str | bytes | Literal[False] | None = None, + fill_value: int | float | np.number | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, ) -> Variable: ... def renameVariable(self, oldname: str, newname: str) -> None: ... @@ -484,7 +484,7 @@ class Variable(Generic[VarT]): least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode = "BitGroom", - fill_value: int | float | str | bytes | Literal[False] | None = None, + fill_value: int | float | np.number | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any, ) -> Variable[NumericVarT]: ... @@ -509,7 +509,7 @@ class Variable(Generic[VarT]): least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode = "BitGroom", - fill_value: int | float | str | bytes | Literal[False] | None = None, + fill_value: int | float | np.number | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any, ) -> Variable[str]: ... @@ -534,7 +534,7 @@ class Variable(Generic[VarT]): least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode = "BitGroom", - fill_value: int | float | str | bytes | Literal[False] | None = None, + fill_value: int | float | np.number | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any, ) -> Variable: ... @@ -558,7 +558,7 @@ class Variable(Generic[VarT]): least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode = "BitGroom", - fill_value: int | float | str | bytes | Literal[False] | None = None, + fill_value: int | float | np.number | str | bytes | Literal[False] | None = None, chunk_cache: int | None = None, **kwargs: Any, ) -> None: ... From 97273dd47a0798c50900965f03f431841070d317 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Thu, 25 Jul 2024 13:41:00 -0700 Subject: [PATCH 1249/1504] Test updates to deal with only allowing Literals for some parameters --- examples/bench_compress.py | 8 ++++++- examples/mpi_example.py | 31 +++++++++++++------------ pyproject.toml | 3 +++ test/test_compression.py | 4 ++++ test/test_compression_blosc.py | 2 ++ test/test_compression_bzip2.py | 2 ++ test/test_endian.py | 2 ++ test/test_enum.py | 2 +- test/test_stringarr.py | 2 ++ test/test_types.py | 2 ++ test/test_utils.py | 2 +- test/type_guards.py | 41 ++++++++++++++++++++++++++++++++++ 12 files changed, 84 insertions(+), 17 deletions(-) create mode 100644 test/type_guards.py diff --git a/examples/bench_compress.py b/examples/bench_compress.py index 39bffe906..06a343391 100644 --- a/examples/bench_compress.py +++ b/examples/bench_compress.py @@ -1,7 +1,9 @@ # benchmark reads and writes, with and without compression. # tests all four supported file formats. from numpy.random.mtrand import uniform +from typing_extensions import TypeGuard import netCDF4 +import netCDF4.utils from timeit import Timer import os, sys @@ -13,8 +15,10 @@ ntrials = 10 sys.stdout.write('reading and writing a %s by %s by %s by %s random array ..\n'%(n1dim,n2dim,n3dim,n4dim)) sys.stdout.write('(average of %s trials)\n' % ntrials) -array = netCDF4.utils._quantize(uniform(size=(n1dim,n2dim,n3dim,n4dim)),4) # type: ignore +array = netCDF4.utils._quantize(uniform(size=(n1dim,n2dim,n3dim,n4dim)),4) +def valid_complevel(complevel) -> TypeGuard[netCDF4.CompressionLevel | None]: + return complevel is None or isinstance(complevel, int) and 0 <= complevel <= 6 def write_netcdf(filename,zlib=False,shuffle=False,complevel=6): file = netCDF4.Dataset(filename,'w',format='NETCDF4') @@ -22,6 +26,8 @@ def write_netcdf(filename,zlib=False,shuffle=False,complevel=6): file.createDimension('n2', n2dim) file.createDimension('n3', n3dim) file.createDimension('n4', n4dim) + if not valid_complevel(complevel): + raise ValueError("Invalid compression level") foo = file.createVariable('data',\ 'f8',('n1','n2','n3','n4'),zlib=zlib,shuffle=shuffle,complevel=complevel) foo[:] = array diff --git a/examples/mpi_example.py b/examples/mpi_example.py index 7966bdafe..1e781b461 100644 --- a/examples/mpi_example.py +++ b/examples/mpi_example.py @@ -1,27 +1,30 @@ # to run: mpirun -np 4 python mpi_example.py import sys -from typing import Literal +from typing_extensions import TypeGuard from mpi4py import MPI import numpy as np from netCDF4 import Dataset +import netCDF4 -format: Literal[ - 'NETCDF4', - 'NETCDF4_CLASSIC', - 'NETCDF3_CLASSIC', - 'NETCDF3_64BIT_OFFSET', - 'NETCDF3_64BIT_DATA' -] -if len(sys.argv) == 2: - format = sys.argv[1] # type: ignore -else: - format = 'NETCDF4_CLASSIC' + +def is_nc_format(fmt: str) -> TypeGuard[netCDF4.Format]: + return fmt in { + 'NETCDF4', + 'NETCDF4_CLASSIC', + 'NETCDF3_CLASSIC', + 'NETCDF3_64BIT_OFFSET', + 'NETCDF3_64BIT_DATA' + } + +nc_format = 'NETCDF4_CLASSIC' if len(sys.argv) < 2 else sys.argv[1] +if not is_nc_format(nc_format): + raise ValueError("Invalid file format") rank = MPI.COMM_WORLD.rank # The process ID (integer 0-3 for 4-process run) if rank == 0: - print('Creating file with format {}'.format(format)) + print('Creating file with format {}'.format(nc_format)) nc = Dataset('parallel_test.nc', 'w', parallel=True, comm=MPI.COMM_WORLD, - info=MPI.Info(), format=format) + info=MPI.Info(), format=nc_format) # below should work also - MPI_COMM_WORLD and MPI_INFO_NULL will be used. #nc = Dataset('parallel_test.nc', 'w', parallel=True) d = nc.createDimension('dim',4) diff --git a/pyproject.toml b/pyproject.toml index fb245117b..c577e761a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -87,6 +87,9 @@ files = ["src/netCDF4"] exclude = "utils.py" check_untyped_defs = true allow_redefinition = true +# next 2 lines workarounds for mypy dealing with type_guards.py +mypy_path = "test" +explicit_package_bases = true [[tool.mypy.overrides]] ignore_missing_imports = true diff --git a/test/test_compression.py b/test/test_compression.py index 78827ddff..eab808227 100644 --- a/test/test_compression.py +++ b/test/test_compression.py @@ -3,6 +3,7 @@ from netCDF4.utils import _quantize from numpy.testing import assert_almost_equal import os, tempfile, unittest +from type_guards import valid_complevel, valid_comptype ndim = 100000 ndim2 = 100 @@ -15,6 +16,7 @@ def write_netcdf(filename,zlib,least_significant_digit,data,dtype='f8',shuffle=False,contiguous=False,\ chunksizes=None,complevel=6,fletcher32=False): + assert valid_complevel(complevel) file = Dataset(filename,'w') file.createDimension('n', ndim) foo = file.createVariable('data',\ @@ -30,6 +32,7 @@ def write_netcdf(filename,zlib,least_significant_digit,data,dtype='f8',shuffle=F #compression='' #compression=0 #compression='gzip' # should fail + assert valid_comptype(compression) foo2 = file.createVariable('data2',\ dtype,('n'),compression=compression,least_significant_digit=least_significant_digit,\ shuffle=shuffle,contiguous=contiguous,complevel=complevel,fletcher32=fletcher32,chunksizes=chunksizes) @@ -46,6 +49,7 @@ def write_netcdf2(filename,zlib,least_significant_digit,data,dtype='f8',shuffle= file = Dataset(filename,'w') file.createDimension('n', ndim) file.createDimension('n2', ndim2) + assert valid_complevel(complevel) foo = file.createVariable('data2',\ dtype,('n','n2'),zlib=zlib,least_significant_digit=least_significant_digit,\ shuffle=shuffle,contiguous=contiguous,complevel=complevel,fletcher32=fletcher32,chunksizes=chunksizes) diff --git a/test/test_compression_blosc.py b/test/test_compression_blosc.py index 57d8e0f56..6915544c8 100644 --- a/test/test_compression_blosc.py +++ b/test/test_compression_blosc.py @@ -3,6 +3,7 @@ from numpy.testing import assert_almost_equal import os, tempfile, unittest, sys from filter_availability import no_plugins, has_blosc_filter +from type_guards import valid_complevel, valid_bloscshuffle ndim = 100000 @@ -12,6 +13,7 @@ datarr = uniform(size=(ndim,)) def write_netcdf(filename,dtype='f8',blosc_shuffle=1,complevel=6): + assert valid_complevel(complevel) and valid_bloscshuffle(blosc_shuffle) nc = Dataset(filename,'w') nc.createDimension('n', ndim) foo = nc.createVariable('data',\ diff --git a/test/test_compression_bzip2.py b/test/test_compression_bzip2.py index 75c0fced1..9a58b0668 100644 --- a/test/test_compression_bzip2.py +++ b/test/test_compression_bzip2.py @@ -3,6 +3,7 @@ from numpy.testing import assert_almost_equal import os, tempfile, unittest, sys from filter_availability import no_plugins, has_bzip2_filter +from type_guards import valid_complevel ndim = 100000 filename1 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name @@ -10,6 +11,7 @@ array = uniform(size=(ndim,)) def write_netcdf(filename,dtype='f8',complevel=6): + assert valid_complevel(complevel) nc = Dataset(filename,'w') nc.createDimension('n', ndim) foo = nc.createVariable('data',\ diff --git a/test/test_endian.py b/test/test_endian.py index 99d6b44f8..3a8aecebb 100644 --- a/test/test_endian.py +++ b/test/test_endian.py @@ -2,6 +2,7 @@ import numpy as np import unittest, os, tempfile from numpy.testing import assert_array_equal, assert_array_almost_equal +from type_guards import valid_endian data = np.arange(12,dtype='f4').reshape(3,4) FILE_NAME = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name @@ -73,6 +74,7 @@ def issue310(file): endian='little' else: raise ValueError('cannot determine native endianness') + assert valid_endian(endian) # mypy fails to narrow endian on its own var_big_endian = nc.createVariable(\ 'obs_big_endian', '>f8', ('obs', ),\ endian=endian,fill_value=fval) diff --git a/test/test_enum.py b/test/test_enum.py index 90761d849..945905058 100644 --- a/test/test_enum.py +++ b/test/test_enum.py @@ -27,7 +27,7 @@ def setUp(self): cloud_type = f.createEnumType(ENUM_BASETYPE,ENUM_NAME,ENUM_DICT) # make sure KeyError raised if non-integer basetype used. try: - cloud_typ2 = f.createEnumType(np.float32,ENUM_NAME,ENUM_DICT) # type: ignore # mypy correctly doesn't like float32 + cloud_typ2 = f.createEnumType(np.float32,ENUM_NAME,ENUM_DICT) # type: ignore[arg-type] # mypy correctly doesn't like float32 except KeyError: pass f.createDimension('time',None) diff --git a/test/test_stringarr.py b/test/test_stringarr.py index 24c890fb2..597e40096 100644 --- a/test/test_stringarr.py +++ b/test/test_stringarr.py @@ -3,6 +3,7 @@ import unittest import os from numpy.testing import assert_array_equal, assert_array_almost_equal +from type_guards import valid_ncformat def generateString(length, alphabet=string.ascii_letters + string.digits + string.punctuation): return(''.join([random.choice(alphabet) for i in range(length)])) @@ -24,6 +25,7 @@ class StringArrayTestCase(unittest.TestCase): def setUp(self): self.file = FILE_NAME + assert valid_ncformat(FILE_FORMAT) nc = Dataset(FILE_NAME,'w',format=FILE_FORMAT) nc.createDimension('n1',None) nc.createDimension('n2',n2) diff --git a/test/test_types.py b/test/test_types.py index 1f65fc5fc..b2c608bcf 100644 --- a/test/test_types.py +++ b/test/test_types.py @@ -6,6 +6,7 @@ from numpy.testing import assert_array_equal, assert_array_almost_equal from numpy.random.mtrand import uniform import netCDF4 +from type_guards import valid_complevel # test primitive data types. @@ -28,6 +29,7 @@ def setUp(self): f.createDimension('n1', None) f.createDimension('n2', n2dim) for typ in datatypes: + assert valid_complevel(complevel) foo = f.createVariable('data_'+typ, typ, ('n1','n2',),zlib=zlib,complevel=complevel,shuffle=shuffle,least_significant_digit=least_significant_digit,fill_value=FillValue) #foo._FillValue = FillValue # test writing of _FillValue attribute for diff types diff --git a/test/test_utils.py b/test/test_utils.py index 12000aa6b..88ee12c62 100644 --- a/test/test_utils.py +++ b/test/test_utils.py @@ -90,7 +90,7 @@ def test_put_indices(self): start, count, stride, put_ind = _StartCountStride(elem, (3,4,5)) orig = np.arange(60).reshape((3,4,5)) dest = np.empty(_out_array_shape(count)) - dest[tuple(put_ind[0,0,0])] = orig[tuple(elem)] # type: ignore # mypy doesn't like indexing of orig, but it's OK + dest[tuple(put_ind[0,0,0])] = orig[tuple(elem)] def test_boolean(self): elem = (1, slice(None), np.array([True, True, False, False, True])) diff --git a/test/type_guards.py b/test/type_guards.py new file mode 100644 index 000000000..ee8181ef9 --- /dev/null +++ b/test/type_guards.py @@ -0,0 +1,41 @@ +"""_type_guards - Helpers for input type-checking""" +from typing import Literal, TYPE_CHECKING + +from typing_extensions import TypeGuard +if TYPE_CHECKING: + # in stubs only + from netCDF4 import CompressionLevel, EndianType, CompressionType + from netCDF4 import Format as NCFormat +else: + CompressionLevel = EndianType = CompressionType = NCFormat = object + +def valid_complevel(complevel) -> TypeGuard[CompressionLevel | None]: + return complevel is None or isinstance(complevel, int) and 0 <= complevel <= 9 + +def valid_endian(endian) -> TypeGuard[EndianType]: + return endian in {"native", "big", "little"} + +def valid_comptype(comptype) -> TypeGuard[CompressionType | None]: + return comptype is None or comptype in { + "zlib", + "szip", + "zstd", + "bzip2", + "blosc_lz", + "blosc_lz4", + "blosc_lz4hc", + "blosc_zlib", + "blosc_zstd", + } + +def valid_bloscshuffle(bloscshuffle) -> TypeGuard[Literal[0, 1, 2]]: + return bloscshuffle in {0, 1, 2} + +def valid_ncformat(ncformat) -> TypeGuard[NCFormat]: + return ncformat in [ + "NETCDF4", + "NETCDF4_CLASSIC", + "NETCDF3_CLASSIC", + "NETCDF3_64BIT_OFFSET", + "NETCDF3_64BIT_DATA" + ] From 13a79a1b38c9fc6d7f737fdf3167ca8f8643007a Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Thu, 25 Jul 2024 13:43:08 -0700 Subject: [PATCH 1250/1504] Revamp GetSetItemKey --- src/netCDF4/__init__.pyi | 31 ++++++++++++++++++++----------- 1 file changed, 20 insertions(+), 11 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 734fa83f7..cbebd1990 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -153,24 +153,33 @@ DateTimeArray: TypeAlias = npt.NDArray[np.object_] GetSetItemKey: TypeAlias = ( int | float - | str # strs that can be cooerced to ints | np.number + | str | slice | ellipsis | list[int] | list[float] - | list[bool] + | list[np.number] | list[str] - | list[int | float] - | list[int | bool] - | list[int | str] - | list[float | bool] - | list[float | str] - | list[bool | str] - | list[int | float | bool | str] - | npt.NDArray[np.number | np.bool_] + | list[bool] + | list[np.bool_] + | npt.NDArray[np.number] + | npt.NDArray[np.bool_] | tuple[ - int | float | str | slice | ellipsis | Sequence[int] | Sequence[bool] | npt.NDArray[np.number | np.bool_], + int + | float + | np.number + | str + | slice + | ellipsis + | Sequence[int] + | Sequence[float] + | Sequence[np.number] + | Sequence[str] + | Sequence[bool] + | Sequence[np.bool_] + | npt.NDArray[np.number] + | npt.NDArray[np.bool_], ..., ] ) From a33f631bad27accbb9b98741036ad3a0f56754e0 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Thu, 25 Jul 2024 13:51:09 -0700 Subject: [PATCH 1251/1504] Fix runtime behavior of examples --- examples/bench_compress.py | 7 ++++++- examples/mpi_example.py | 8 ++++++-- 2 files changed, 12 insertions(+), 3 deletions(-) diff --git a/examples/bench_compress.py b/examples/bench_compress.py index 06a343391..99053aac8 100644 --- a/examples/bench_compress.py +++ b/examples/bench_compress.py @@ -1,11 +1,16 @@ # benchmark reads and writes, with and without compression. # tests all four supported file formats. +from typing import TYPE_CHECKING from numpy.random.mtrand import uniform from typing_extensions import TypeGuard import netCDF4 import netCDF4.utils from timeit import Timer import os, sys +if TYPE_CHECKING: + from netCDF4 import CompressionLevel +else: + CompressionLevel = object # create an n1dim by n2dim by n3dim random array. n1dim = 30 @@ -17,7 +22,7 @@ sys.stdout.write('(average of %s trials)\n' % ntrials) array = netCDF4.utils._quantize(uniform(size=(n1dim,n2dim,n3dim,n4dim)),4) -def valid_complevel(complevel) -> TypeGuard[netCDF4.CompressionLevel | None]: +def valid_complevel(complevel) -> TypeGuard[CompressionLevel | None]: return complevel is None or isinstance(complevel, int) and 0 <= complevel <= 6 def write_netcdf(filename,zlib=False,shuffle=False,complevel=6): diff --git a/examples/mpi_example.py b/examples/mpi_example.py index 1e781b461..71d8b8eb2 100644 --- a/examples/mpi_example.py +++ b/examples/mpi_example.py @@ -1,13 +1,17 @@ # to run: mpirun -np 4 python mpi_example.py import sys +from typing import TYPE_CHECKING from typing_extensions import TypeGuard from mpi4py import MPI import numpy as np from netCDF4 import Dataset -import netCDF4 +if TYPE_CHECKING: + from netCDF4 import Format as NCFormat +else: + NCFormat = object -def is_nc_format(fmt: str) -> TypeGuard[netCDF4.Format]: +def is_nc_format(fmt: str) -> TypeGuard[NCFormat]: return fmt in { 'NETCDF4', 'NETCDF4_CLASSIC', From 64420742504f7b2c82a171f7ff977f5903af5689 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Thu, 25 Jul 2024 14:02:21 -0700 Subject: [PATCH 1252/1504] add typing-extensions so tests can pass --- .github/workflows/build_latest.yml | 18 +++++++++--------- .github/workflows/build_old.yml | 18 +++++++++--------- 2 files changed, 18 insertions(+), 18 deletions(-) diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml index 079774710..8f536624e 100644 --- a/.github/workflows/build_latest.yml +++ b/.github/workflows/build_latest.yml @@ -53,21 +53,21 @@ jobs: # if: ${{ failure() }} # run: | # cd netcdf-c-${NETCDF_VERSION} -# cat config.log +# cat config.log - name: Install python dependencies via pip run: | python -m pip install --upgrade pip - pip install numpy cython cftime pytest twine wheel check-manifest mpi4py + pip install numpy cython cftime pytest twine wheel check-manifest mpi4py typing-extensions - name: Install netcdf4-python run: | - export PATH=${NETCDF_DIR}/bin:${PATH} + export PATH=${NETCDF_DIR}/bin:${PATH} export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c-${NETCDF_VERSION}/plugins/plugindir python setup.py install - name: Test run: | - export PATH=${NETCDF_DIR}/bin:${PATH} + export PATH=${NETCDF_DIR}/bin:${PATH} python checkversion.py # serial cd test @@ -98,9 +98,9 @@ jobs: # - name: Tarball # run: | -# export PATH=${NETCDF_DIR}/bin:${PATH} -# python setup.py --version +# export PATH=${NETCDF_DIR}/bin:${PATH} +# python setup.py --version # check-manifest --version -# check-manifest --verbose -# pip wheel . -w dist --no-deps -# twine check dist/* +# check-manifest --verbose +# pip wheel . -w dist --no-deps +# twine check dist/* diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml index eeaa61c3b..b10977d9d 100644 --- a/.github/workflows/build_old.yml +++ b/.github/workflows/build_old.yml @@ -53,21 +53,21 @@ jobs: # if: ${{ failure() }} # run: | # cd netcdf-c-${NETCDF_VERSION} -# cat config.log +# cat config.log - name: Install python dependencies via pip run: | python -m pip install --upgrade pip - pip install numpy cython cftime pytest twine wheel check-manifest mpi4py + pip install numpy cython cftime pytest twine wheel check-manifest mpi4py typing-extensions - name: Install netcdf4-python run: | - export PATH=${NETCDF_DIR}/bin:${PATH} + export PATH=${NETCDF_DIR}/bin:${PATH} export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c-${NETCDF_VERSION}/plugins/plugindir python setup.py install - name: Test run: | - export PATH=${NETCDF_DIR}/bin:${PATH} + export PATH=${NETCDF_DIR}/bin:${PATH} python checkversion.py # serial cd test @@ -98,9 +98,9 @@ jobs: # - name: Tarball # run: | -# export PATH=${NETCDF_DIR}/bin:${PATH} -# python setup.py --version +# export PATH=${NETCDF_DIR}/bin:${PATH} +# python setup.py --version # check-manifest --version -# check-manifest --verbose -# pip wheel . -w dist --no-deps -# twine check dist/* +# check-manifest --verbose +# pip wheel . -w dist --no-deps +# twine check dist/* From 9996c01f14cbdf1729a79a83e5816ad21f5ff071 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Mon, 29 Jul 2024 09:17:02 -0700 Subject: [PATCH 1253/1504] Correct auth link --- docs/index.html | 4 ++-- src/netCDF4/_netCDF4.pyx | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/docs/index.html b/docs/index.html index 377e45741..f120d187c 100644 --- a/docs/index.html +++ b/docs/index.html @@ -1352,7 +1352,7 @@

      Functions

      rc_get(key)

      Returns the internal netcdf-c rc table value corresponding to key. -See https://docs.unidata.ucar.edu/netcdf-c/current/auth.html +See https://docs.unidata.ucar.edu/netcdf-c/current/md_auth.html for more information on rc files and values.

      @@ -1361,7 +1361,7 @@

      Functions

      rc_set(key, value)

      Sets the internal netcdf-c rc table value corresponding to key. -See https://docs.unidata.ucar.edu/netcdf-c/current/auth.html +See https://docs.unidata.ucar.edu/netcdf-c/current/md_auth.html for more information on rc files and values.

      diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index d4c6f7d53..6023406c9 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1323,7 +1323,7 @@ def rc_get(key): **```rc_get(key)```** Returns the internal netcdf-c rc table value corresponding to key. -See +See for more information on rc files and values. """ cdef int ierr @@ -1347,7 +1347,7 @@ def rc_set(key, value): **```rc_set(key, value)```** Sets the internal netcdf-c rc table value corresponding to key. -See +See for more information on rc files and values. """ cdef int ierr From c4e6e72a28e48d14d3f95a05afc32d98a9f19e10 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Tue, 30 Jul 2024 10:59:11 -0700 Subject: [PATCH 1254/1504] tests and examples are py311, don't need typing_extensions --- .github/workflows/build_latest.yml | 2 +- .github/workflows/build_old.yml | 2 +- examples/bench_compress.py | 3 +-- examples/mpi_example.py | 3 +-- test/type_guards.py | 3 +-- 5 files changed, 5 insertions(+), 8 deletions(-) diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml index 8f536624e..852354d18 100644 --- a/.github/workflows/build_latest.yml +++ b/.github/workflows/build_latest.yml @@ -58,7 +58,7 @@ jobs: - name: Install python dependencies via pip run: | python -m pip install --upgrade pip - pip install numpy cython cftime pytest twine wheel check-manifest mpi4py typing-extensions + pip install numpy cython cftime pytest twine wheel check-manifest mpi4py - name: Install netcdf4-python run: | diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml index b10977d9d..d93eba15e 100644 --- a/.github/workflows/build_old.yml +++ b/.github/workflows/build_old.yml @@ -58,7 +58,7 @@ jobs: - name: Install python dependencies via pip run: | python -m pip install --upgrade pip - pip install numpy cython cftime pytest twine wheel check-manifest mpi4py typing-extensions + pip install numpy cython cftime pytest twine wheel check-manifest mpi4py - name: Install netcdf4-python run: | diff --git a/examples/bench_compress.py b/examples/bench_compress.py index 99053aac8..56b9cb285 100644 --- a/examples/bench_compress.py +++ b/examples/bench_compress.py @@ -1,8 +1,7 @@ # benchmark reads and writes, with and without compression. # tests all four supported file formats. -from typing import TYPE_CHECKING +from typing import TYPE_CHECKING, TypeGuard from numpy.random.mtrand import uniform -from typing_extensions import TypeGuard import netCDF4 import netCDF4.utils from timeit import Timer diff --git a/examples/mpi_example.py b/examples/mpi_example.py index 71d8b8eb2..0a89b28df 100644 --- a/examples/mpi_example.py +++ b/examples/mpi_example.py @@ -1,7 +1,6 @@ # to run: mpirun -np 4 python mpi_example.py import sys -from typing import TYPE_CHECKING -from typing_extensions import TypeGuard +from typing import TYPE_CHECKING, TypeGuard from mpi4py import MPI import numpy as np from netCDF4 import Dataset diff --git a/test/type_guards.py b/test/type_guards.py index ee8181ef9..e8121485e 100644 --- a/test/type_guards.py +++ b/test/type_guards.py @@ -1,7 +1,6 @@ """_type_guards - Helpers for input type-checking""" -from typing import Literal, TYPE_CHECKING +from typing import Literal, TYPE_CHECKING, TypeGuard -from typing_extensions import TypeGuard if TYPE_CHECKING: # in stubs only from netCDF4 import CompressionLevel, EndianType, CompressionType From 7c9eb602e79f294613fd3fea9f317f801035bec5 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Tue, 30 Jul 2024 12:00:54 -0700 Subject: [PATCH 1255/1504] disable some cicd --- .github/workflows/build_latest.yml | 3 ++- .github/workflows/build_master.yml | 11 ++++++----- .github/workflows/build_old.yml | 3 ++- .github/workflows/cibuildwheel.yml | 17 +++++++++-------- .github/workflows/miniconda.yml | 16 +++++++++------- 5 files changed, 28 insertions(+), 22 deletions(-) diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml index 852354d18..965cf2b18 100644 --- a/.github/workflows/build_latest.yml +++ b/.github/workflows/build_latest.yml @@ -1,5 +1,6 @@ name: Build and Test Linux with latest netcdf-c -on: [push, pull_request] +# on: [push, pull_request] +on: [] # disable jobs: build-linux: name: Python (${{ matrix.python-version }}) diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index f8f841636..a1455a945 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -1,5 +1,6 @@ name: Build and Test on Linux with netcdf-c github master -on: [push, pull_request] +# on: [push, pull_request] +on: [] # disable jobs: build-linux: name: Python (${{ matrix.python-version }}) @@ -33,7 +34,7 @@ jobs: export LDFLAGS="-L${NETCDF_DIR}/lib" export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz" autoreconf -i - ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 + ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 make -j 2 make install popd @@ -42,7 +43,7 @@ jobs: # if: ${{ failure() }} # run: | # cd netcdf-c-${NETCDF_VERSION} -# cat config.log +# cat config.log - name: Install python dependencies via pip run: | @@ -51,13 +52,13 @@ jobs: - name: Install netcdf4-python run: | - export PATH=${NETCDF_DIR}/bin:${PATH} + export PATH=${NETCDF_DIR}/bin:${PATH} export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c/plugins/plugindir python setup.py install - name: Test run: | - export PATH=${NETCDF_DIR}/bin:${PATH} + export PATH=${NETCDF_DIR}/bin:${PATH} #export HDF5_PLUGIN_PATH=${NETCDF_DIR}/plugins/plugindir python checkversion.py # serial diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml index d93eba15e..228aa9cc7 100644 --- a/.github/workflows/build_old.yml +++ b/.github/workflows/build_old.yml @@ -1,5 +1,6 @@ name: Build and Test Linux with older netcdf-c -on: [push, pull_request] +# on: [push, pull_request] +on: [] # disable jobs: build-linux: name: Python (${{ matrix.python-version }}) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 5eb8bb975..0fbaf4fb1 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -1,13 +1,14 @@ name: Wheels -on: - pull_request: - push: - tags: - - "v*" - release: - types: - - published +on: ["push"] +# on: +# pull_request: +# push: +# tags: +# - "v*" +# release: +# types: +# - published permissions: contents: read diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index a79c8e572..c930be65f 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -1,9 +1,10 @@ name: Build and Test -on: - pull_request: - push: - branches: [master] +# on: +# pull_request: +# push: +# branches: [master] +on: ["push"] jobs: run-serial: @@ -12,11 +13,12 @@ jobs: # NO_NET: 1 strategy: matrix: - python-version: [ "3.9", "3.10", "3.11", "3.12" ] + # python-version: [ "3.9", "3.10", "3.11", "3.12" ] + python-version: [ "3.9", "3.10"] os: [windows-latest, ubuntu-latest, macos-latest] platform: [x64, x32] exclude: - - os: macos-latest + - os: macos-latest platform: x32 fail-fast: false defaults: @@ -82,7 +84,7 @@ jobs: run: | cd test && python run_all.py cd ../examples - export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" + export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" which mpirun mpirun --version mpirun -np 4 --oversubscribe python mpi_example.py # for openmpi From ea84857502f40906aa533e0ee860917168623665 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Tue, 30 Jul 2024 12:06:54 -0700 Subject: [PATCH 1256/1504] Always get and use typing-extensions in cast py<3.10 --- .github/workflows/build_latest.yml | 2 +- .github/workflows/build_master.yml | 2 +- .github/workflows/build_old.yml | 2 +- .github/workflows/cibuildwheel.yml | 4 ++-- .github/workflows/miniconda.yml | 4 ++-- examples/bench_compress.py | 3 ++- examples/mpi_example.py | 3 ++- examples/parallel_test.nc | Bin 0 -> 6176 bytes examples/parallel_test_compressed.nc | Bin 0 -> 10288 bytes test/test_compression_quant.py | 30 ++++++++++++++------------- test/test_compression_zstd.py | 4 +++- test/type_guards.py | 10 ++++++--- 12 files changed, 37 insertions(+), 27 deletions(-) create mode 100644 examples/parallel_test.nc create mode 100644 examples/parallel_test_compressed.nc diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml index 965cf2b18..28f65c7a8 100644 --- a/.github/workflows/build_latest.yml +++ b/.github/workflows/build_latest.yml @@ -59,7 +59,7 @@ jobs: - name: Install python dependencies via pip run: | python -m pip install --upgrade pip - pip install numpy cython cftime pytest twine wheel check-manifest mpi4py + pip install numpy cython cftime pytest twine wheel check-manifest mpi4py typing-extensions - name: Install netcdf4-python run: | diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index a1455a945..af16c3eec 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -48,7 +48,7 @@ jobs: - name: Install python dependencies via pip run: | python -m pip install --upgrade pip - pip install numpy cython cftime pytest twine wheel check-manifest mpi4py mypy types-setuptools + pip install numpy cython cftime pytest twine wheel check-manifest mpi4py mypy types-setuptools typing-extensions - name: Install netcdf4-python run: | diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml index 228aa9cc7..67d141eef 100644 --- a/.github/workflows/build_old.yml +++ b/.github/workflows/build_old.yml @@ -59,7 +59,7 @@ jobs: - name: Install python dependencies via pip run: | python -m pip install --upgrade pip - pip install numpy cython cftime pytest twine wheel check-manifest mpi4py + pip install numpy cython cftime pytest twine wheel check-manifest mpi4py typing-extensions - name: Install netcdf4-python run: | diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 0fbaf4fb1..09ca9b752 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -104,7 +104,7 @@ jobs: CIBW_TEST_SKIP: "cp38-*_aarch64 cp39-*_aarch64 cp310-*_aarch64 cp311-*_aarch64" CIBW_ENVIRONMENT: ${{ matrix.CIBW_ENVIRONMENT }} CIBW_BEFORE_BUILD_MACOS: brew install hdf5 netcdf - CIBW_TEST_REQUIRES: pytest cython packaging + CIBW_TEST_REQUIRES: pytest cython packaging typing-extensions CIBW_TEST_COMMAND: > python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')" && pytest -s -rxs -v {project}/test @@ -158,7 +158,7 @@ jobs: CIBW_REPAIR_WHEEL_COMMAND_WINDOWS: > delvewheel show {wheel} && delvewheel repair -w {dest_dir} {wheel} - CIBW_TEST_REQUIRES: pytest cython packaging + CIBW_TEST_REQUIRES: pytest cython packaging typing-extensions CIBW_TEST_COMMAND: > python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')" && pytest -s -rxs -v {project}\\test diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index c930be65f..fb291fdc0 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -37,7 +37,7 @@ jobs: init-shell: bash create-args: >- python=${{ matrix.python-version }} - numpy cython pip pytest hdf5 libnetcdf cftime zlib certifi + numpy cython pip pytest hdf5 libnetcdf cftime zlib certifi typing-extensions --channel conda-forge - name: Install netcdf4-python @@ -71,7 +71,7 @@ jobs: init-shell: bash create-args: >- python=${{ matrix.python-version }} - numpy cython pip pytest mpi4py hdf5=*=mpi* libnetcdf=*=mpi* cftime zlib certifi + numpy cython pip pytest mpi4py hdf5=*=mpi* libnetcdf=*=mpi* cftime zlib certifi typing-extensions --channel conda-forge - name: Install netcdf4-python with mpi diff --git a/examples/bench_compress.py b/examples/bench_compress.py index 56b9cb285..845cf333b 100644 --- a/examples/bench_compress.py +++ b/examples/bench_compress.py @@ -1,11 +1,12 @@ # benchmark reads and writes, with and without compression. # tests all four supported file formats. -from typing import TYPE_CHECKING, TypeGuard +from typing import TYPE_CHECKING from numpy.random.mtrand import uniform import netCDF4 import netCDF4.utils from timeit import Timer import os, sys +from typing_extensions import TypeGuard if TYPE_CHECKING: from netCDF4 import CompressionLevel else: diff --git a/examples/mpi_example.py b/examples/mpi_example.py index 0a89b28df..3f8cb0f87 100644 --- a/examples/mpi_example.py +++ b/examples/mpi_example.py @@ -1,9 +1,10 @@ # to run: mpirun -np 4 python mpi_example.py import sys -from typing import TYPE_CHECKING, TypeGuard +from typing import TYPE_CHECKING from mpi4py import MPI import numpy as np from netCDF4 import Dataset +from typing_extensions import TypeGuard if TYPE_CHECKING: from netCDF4 import Format as NCFormat else: diff --git a/examples/parallel_test.nc b/examples/parallel_test.nc new file mode 100644 index 0000000000000000000000000000000000000000..ec95803e081f032b7314eaf74434c9916246e2bd GIT binary patch literal 6176 zcmeH{KX21O6u_VDCNjZo0t5mGf$0JjAxhhTTA@gd9EYT&35q+hL~iV=My-Pq(-j7U z#7KnNiEqHj%11y#o%jk2z{U#io$r#WKw)4(x|i5@zI*rn{NA%))T_1W)Wwvl>mcMi z7xR3)Qsf(Z5B+?*UhSyHTXmMLX)50mM~;pu6%ec{;@OxZJq--}p=vkm zEp~^|Am~Mq!O-Y5fC=P~EM_wFJksb6u)^+mW6t>IA`i~to6B#m@3ZiymlP#Si>jh1 zv0>o=Bgm4GQ&+EyUFLMiJwfdR%SAg8yUz22BW_(}IQ9DsZ;+}6Nzlo*)vP!UoWUhZ zg<`EX*6fzkXt%nKRcYE_JfMU$NW=$Pl{K5`uWka~UW7{v7LP}s@Kq}gw;mBKl)bln=)nF&^eu9oZQC5pDzqGCTJ;RPe zn~6i~wygVu{v&@71^$r5IE%`Z)2=_DfXWMbj1jGuONHgaLVnBJyj7kr%ohtwAKo8) zi^~GXmBpa49PWffidM8assm1*>ZjSWLOLX@L2wj>Ii~e0q_061IbdIOIR~rXA9z9N zMwrrJ$J90Gkck-SA?}L<-jZ0mSgwi5UyQ3a^*e+&d5)CFy$Kpt_A5Ux_JnHn0~j^LLkDpCrqIGCPRtg0itq z1T{!Qkvw+nn%%Kmmfd9@Z)1F<>A8_R^rMOEamRxGC&VI0G{fZC$bBW|a+CxlfqzAS z-go+-B=NdywVUiq!(VhZ$94W`0P$7AB_Ch3k@wGBuq~HL{VB=R6vm$ISwhL4vKr?KyYGLwP+KRmgQz$5g=V{icpap!=z^;W^m+S`OG>@O=h;~@bEwfBz>OP#Y1tXJ2Y0`zBK*v%qGV}YRg|NUWN2EJB0hWd zif{~I!h#M9uTeWCa?#Gj9-k#1-zN@aq!TAbYTP7M4JJV++g82ox-f@BlmX>iS>Lc7 zcfH}XT&rBS!FY_wa6u|w;FLFPp}&^sZ*GSJ6MvrB4I-;jH4$pi9fZBE*?tk3-Ci`D zLZ+eD-U$k(lx3iRRJ1=01_jh|f~ezfEmy+b(1%&9hnR^efsK?-EFak6)+?V>gy9pOjgCbkNi(Z;>R>)fM0^U%l|M}q4 zO2eu>)X&i)mUHs9B^iRTLzSVy3>3*@)2`Z0+p+AH@OT@mgEW0F@&-XPbbYkpppViX z7m<9UC?b-3KfljWM21aIR0N_bTaNXp-+LbPqYz=yPUP^S>f8(ZR9dB_JXRalNol!o zr?8aY_P16_i-pBvVfDt>+&ffcVFFCxloELPr1P}xb=L5W--pZtHFZk!;INqh6JP>N zfC(^xlL>4#ZJQ2W@;EKqG3RGtgpL`b5+4!eQE_yJ`%HidFaajO1en18Lg2pDsEbdf w$(Kvf$K>SS0{Ky2=KEzv_PAvNOn?b60Vco%m;e)C0!)AjFaajO1WpTqKPK($K>z>% literal 0 HcmV?d00001 diff --git a/test/test_compression_quant.py b/test/test_compression_quant.py index 3654bf9d5..7cdd11e2b 100644 --- a/test/test_compression_quant.py +++ b/test/test_compression_quant.py @@ -3,6 +3,7 @@ from numpy.testing import assert_almost_equal import numpy as np import os, tempfile, unittest +from type_guards import valid_complevel, valid_quantize_mode ndim = 100000 nfiles = 7 @@ -16,6 +17,7 @@ def write_netcdf(filename,zlib,significant_digits,data,dtype='f8',shuffle=False, complevel=6,quantize_mode="BitGroom"): file = Dataset(filename,'w') file.createDimension('n', ndim) + assert valid_complevel(complevel) and valid_quantize_mode(quantize_mode) foo = file.createVariable('data',\ dtype,('n'),zlib=zlib,significant_digits=significant_digits,\ shuffle=shuffle,complevel=complevel,quantize_mode=quantize_mode) @@ -61,7 +63,7 @@ def runTest(self): assert_almost_equal(data_array,f.variables['data'][:]) assert f.variables['data'].filters() ==\ {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':complevel,'fletcher32':False} - assert size < 0.95*uncompressed_size + assert size < 0.95*uncompressed_size f.close() # check compression with shuffle f = Dataset(self.files[2]) @@ -70,43 +72,43 @@ def runTest(self): assert_almost_equal(data_array,f.variables['data'][:]) assert f.variables['data'].filters() ==\ {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':complevel,'fletcher32':False} - assert size < 0.85*uncompressed_size + assert size < 0.85*uncompressed_size f.close() # check lossy compression without shuffle f = Dataset(self.files[3]) size = os.stat(self.files[3]).st_size errmax = (np.abs(data_array-f.variables['data'][:])).max() #print('compressed lossy no shuffle = ',size,' max err = ',errmax) - assert f.variables['data'].quantization() == (nsd,'BitGroom') - assert errmax < 1.e-3 - assert size < 0.35*uncompressed_size + assert f.variables['data'].quantization() == (nsd,'BitGroom') + assert errmax < 1.e-3 + assert size < 0.35*uncompressed_size f.close() # check lossy compression with shuffle f = Dataset(self.files[4]) size = os.stat(self.files[4]).st_size errmax = (np.abs(data_array-f.variables['data'][:])).max() print('compressed lossy with shuffle and standard quantization = ',size,' max err = ',errmax) - assert f.variables['data'].quantization() == (nsd,'BitGroom') - assert errmax < 1.e-3 - assert size < 0.24*uncompressed_size + assert f.variables['data'].quantization() == (nsd,'BitGroom') + assert errmax < 1.e-3 + assert size < 0.24*uncompressed_size f.close() # check lossy compression with shuffle and alternate quantization f = Dataset(self.files[5]) size = os.stat(self.files[5]).st_size errmax = (np.abs(data_array-f.variables['data'][:])).max() print('compressed lossy with shuffle and alternate quantization = ',size,' max err = ',errmax) - assert f.variables['data'].quantization() == (nsd,'GranularBitRound') - assert errmax < 1.e-3 - assert size < 0.24*uncompressed_size + assert f.variables['data'].quantization() == (nsd,'GranularBitRound') + assert errmax < 1.e-3 + assert size < 0.24*uncompressed_size f.close() # check lossy compression with shuffle and alternate quantization f = Dataset(self.files[6]) size = os.stat(self.files[6]).st_size errmax = (np.abs(data_array-f.variables['data'][:])).max() print('compressed lossy with shuffle and alternate quantization = ',size,' max err = ',errmax) - assert f.variables['data'].quantization() == (nsb,'BitRound') - assert errmax < 1.e-3 - assert size < 0.24*uncompressed_size + assert f.variables['data'].quantization() == (nsb,'BitRound') + assert errmax < 1.e-3 + assert size < 0.24*uncompressed_size f.close() if __name__ == '__main__': diff --git a/test/test_compression_zstd.py b/test/test_compression_zstd.py index 9f4259fd0..b8242e4cb 100644 --- a/test/test_compression_zstd.py +++ b/test/test_compression_zstd.py @@ -3,6 +3,7 @@ from numpy.testing import assert_almost_equal import os, tempfile, unittest, sys from filter_availability import no_plugins, has_zstd_filter +from type_guards import valid_complevel ndim = 100000 filename1 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name @@ -12,6 +13,7 @@ def write_netcdf(filename,dtype='f8',complevel=6): nc = Dataset(filename,'w') nc.createDimension('n', ndim) + assert valid_complevel(complevel) foo = nc.createVariable('data',\ dtype,('n'),compression='zstd',complevel=complevel) foo[:] = array @@ -47,7 +49,7 @@ def runTest(self): assert_almost_equal(array,f.variables['data'][:]) assert f.variables['data'].filters() ==\ {'zlib':False,'szip':False,'zstd':True,'bzip2':False,'blosc':False,'shuffle':False,'complevel':4,'fletcher32':False} - assert size < 0.96*uncompressed_size + assert size < 0.96*uncompressed_size f.close() if __name__ == '__main__': diff --git a/test/type_guards.py b/test/type_guards.py index e8121485e..09b5e0080 100644 --- a/test/type_guards.py +++ b/test/type_guards.py @@ -1,12 +1,13 @@ """_type_guards - Helpers for input type-checking""" -from typing import Literal, TYPE_CHECKING, TypeGuard +from typing import Literal, TYPE_CHECKING +from typing_extensions import TypeGuard if TYPE_CHECKING: # in stubs only - from netCDF4 import CompressionLevel, EndianType, CompressionType + from netCDF4 import CompressionLevel, EndianType, CompressionType, QuantizeMode from netCDF4 import Format as NCFormat else: - CompressionLevel = EndianType = CompressionType = NCFormat = object + CompressionLevel = EndianType = CompressionType = NCFormat = QuantizeMode = object def valid_complevel(complevel) -> TypeGuard[CompressionLevel | None]: return complevel is None or isinstance(complevel, int) and 0 <= complevel <= 9 @@ -38,3 +39,6 @@ def valid_ncformat(ncformat) -> TypeGuard[NCFormat]: "NETCDF3_64BIT_OFFSET", "NETCDF3_64BIT_DATA" ] + +def valid_quantize_mode(quantize_mode) -> TypeGuard[QuantizeMode]: + return quantize_mode in ["BitGroom", "BitRound", "GranularBitRound"] \ No newline at end of file From 303e8b1a35181d77b3a3c74b432dd0943a70dc5e Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Tue, 30 Jul 2024 12:18:45 -0700 Subject: [PATCH 1257/1504] Remove None union from typeguards --- examples/bench_compress.py | 4 ++-- test/test_compression.py | 18 +++++++++--------- test/test_compression_blosc.py | 2 +- test/test_compression_bzip2.py | 4 ++-- test/test_compression_quant.py | 2 +- test/test_compression_zstd.py | 2 +- test/test_types.py | 2 +- test/type_guards.py | 6 +++--- 8 files changed, 20 insertions(+), 20 deletions(-) diff --git a/examples/bench_compress.py b/examples/bench_compress.py index 845cf333b..84e209e92 100644 --- a/examples/bench_compress.py +++ b/examples/bench_compress.py @@ -22,7 +22,7 @@ sys.stdout.write('(average of %s trials)\n' % ntrials) array = netCDF4.utils._quantize(uniform(size=(n1dim,n2dim,n3dim,n4dim)),4) -def valid_complevel(complevel) -> TypeGuard[CompressionLevel | None]: +def valid_complevel(complevel) -> TypeGuard[CompressionLevel]: return complevel is None or isinstance(complevel, int) and 0 <= complevel <= 6 def write_netcdf(filename,zlib=False,shuffle=False,complevel=6): @@ -31,7 +31,7 @@ def write_netcdf(filename,zlib=False,shuffle=False,complevel=6): file.createDimension('n2', n2dim) file.createDimension('n3', n3dim) file.createDimension('n4', n4dim) - if not valid_complevel(complevel): + if not (valid_complevel(complevel) or complevel is None): raise ValueError("Invalid compression level") foo = file.createVariable('data',\ 'f8',('n1','n2','n3','n4'),zlib=zlib,shuffle=shuffle,complevel=complevel) diff --git a/test/test_compression.py b/test/test_compression.py index eab808227..7972609be 100644 --- a/test/test_compression.py +++ b/test/test_compression.py @@ -16,7 +16,7 @@ def write_netcdf(filename,zlib,least_significant_digit,data,dtype='f8',shuffle=False,contiguous=False,\ chunksizes=None,complevel=6,fletcher32=False): - assert valid_complevel(complevel) + assert valid_complevel(complevel) or complevel is None file = Dataset(filename,'w') file.createDimension('n', ndim) foo = file.createVariable('data',\ @@ -32,7 +32,7 @@ def write_netcdf(filename,zlib,least_significant_digit,data,dtype='f8',shuffle=F #compression='' #compression=0 #compression='gzip' # should fail - assert valid_comptype(compression) + assert valid_comptype(compression) or compression is None foo2 = file.createVariable('data2',\ dtype,('n'),compression=compression,least_significant_digit=least_significant_digit,\ shuffle=shuffle,contiguous=contiguous,complevel=complevel,fletcher32=fletcher32,chunksizes=chunksizes) @@ -49,7 +49,7 @@ def write_netcdf2(filename,zlib,least_significant_digit,data,dtype='f8',shuffle= file = Dataset(filename,'w') file.createDimension('n', ndim) file.createDimension('n2', ndim2) - assert valid_complevel(complevel) + assert valid_complevel(complevel) or complevel is None foo = file.createVariable('data2',\ dtype,('n','n2'),zlib=zlib,least_significant_digit=least_significant_digit,\ shuffle=shuffle,contiguous=contiguous,complevel=complevel,fletcher32=fletcher32,chunksizes=chunksizes) @@ -107,7 +107,7 @@ def runTest(self): {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':6,'fletcher32':False} assert f.variables['data2'].filters() ==\ {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':False,'complevel':6,'fletcher32':False} - assert size < 0.95*uncompressed_size + assert size < 0.95*uncompressed_size f.close() # check compression with shuffle f = Dataset(self.files[2]) @@ -118,7 +118,7 @@ def runTest(self): {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':False} assert f.variables['data2'].filters() ==\ {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':False} - assert size < 0.85*uncompressed_size + assert size < 0.85*uncompressed_size f.close() # check lossy compression without shuffle f = Dataset(self.files[3]) @@ -126,14 +126,14 @@ def runTest(self): checkarray = _quantize(array,lsd) assert_almost_equal(checkarray,f.variables['data'][:]) assert_almost_equal(checkarray,f.variables['data2'][:]) - assert size < 0.27*uncompressed_size + assert size < 0.27*uncompressed_size f.close() # check lossy compression with shuffle f = Dataset(self.files[4]) size = os.stat(self.files[4]).st_size assert_almost_equal(checkarray,f.variables['data'][:]) assert_almost_equal(checkarray,f.variables['data2'][:]) - assert size < 0.20*uncompressed_size + assert size < 0.20*uncompressed_size size_save = size f.close() # check lossy compression with shuffle and fletcher32 checksum. @@ -145,9 +145,9 @@ def runTest(self): {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':True} assert f.variables['data2'].filters() ==\ {'zlib':True,'szip':False,'zstd':False,'bzip2':False,'blosc':False,'shuffle':True,'complevel':6,'fletcher32':True} - assert size < 0.20*uncompressed_size + assert size < 0.20*uncompressed_size # should be slightly larger than without fletcher32 - assert size > size_save + assert size > size_save # check chunksizes f.close() f = Dataset(self.files[6]) diff --git a/test/test_compression_blosc.py b/test/test_compression_blosc.py index 6915544c8..bbfc08a39 100644 --- a/test/test_compression_blosc.py +++ b/test/test_compression_blosc.py @@ -13,7 +13,7 @@ datarr = uniform(size=(ndim,)) def write_netcdf(filename,dtype='f8',blosc_shuffle=1,complevel=6): - assert valid_complevel(complevel) and valid_bloscshuffle(blosc_shuffle) + assert (valid_complevel(complevel) or complevel is None) and valid_bloscshuffle(blosc_shuffle) nc = Dataset(filename,'w') nc.createDimension('n', ndim) foo = nc.createVariable('data',\ diff --git a/test/test_compression_bzip2.py b/test/test_compression_bzip2.py index 9a58b0668..1b008f190 100644 --- a/test/test_compression_bzip2.py +++ b/test/test_compression_bzip2.py @@ -11,7 +11,7 @@ array = uniform(size=(ndim,)) def write_netcdf(filename,dtype='f8',complevel=6): - assert valid_complevel(complevel) + assert valid_complevel(complevel) or complevel is None nc = Dataset(filename,'w') nc.createDimension('n', ndim) foo = nc.createVariable('data',\ @@ -49,7 +49,7 @@ def runTest(self): assert_almost_equal(array,f.variables['data'][:]) assert f.variables['data'].filters() ==\ {'zlib':False,'szip':False,'zstd':False,'bzip2':True,'blosc':False,'shuffle':False,'complevel':4,'fletcher32':False} - assert size < 0.96*uncompressed_size + assert size < 0.96*uncompressed_size f.close() diff --git a/test/test_compression_quant.py b/test/test_compression_quant.py index 7cdd11e2b..dd124c348 100644 --- a/test/test_compression_quant.py +++ b/test/test_compression_quant.py @@ -17,7 +17,7 @@ def write_netcdf(filename,zlib,significant_digits,data,dtype='f8',shuffle=False, complevel=6,quantize_mode="BitGroom"): file = Dataset(filename,'w') file.createDimension('n', ndim) - assert valid_complevel(complevel) and valid_quantize_mode(quantize_mode) + assert (valid_complevel(complevel) or complevel is None) and valid_quantize_mode(quantize_mode) foo = file.createVariable('data',\ dtype,('n'),zlib=zlib,significant_digits=significant_digits,\ shuffle=shuffle,complevel=complevel,quantize_mode=quantize_mode) diff --git a/test/test_compression_zstd.py b/test/test_compression_zstd.py index b8242e4cb..4ee16daff 100644 --- a/test/test_compression_zstd.py +++ b/test/test_compression_zstd.py @@ -13,7 +13,7 @@ def write_netcdf(filename,dtype='f8',complevel=6): nc = Dataset(filename,'w') nc.createDimension('n', ndim) - assert valid_complevel(complevel) + assert valid_complevel(complevel) or complevel is None foo = nc.createVariable('data',\ dtype,('n'),compression='zstd',complevel=complevel) foo[:] = array diff --git a/test/test_types.py b/test/test_types.py index b2c608bcf..b8eb74b2e 100644 --- a/test/test_types.py +++ b/test/test_types.py @@ -29,7 +29,7 @@ def setUp(self): f.createDimension('n1', None) f.createDimension('n2', n2dim) for typ in datatypes: - assert valid_complevel(complevel) + assert valid_complevel(complevel) or complevel is None foo = f.createVariable('data_'+typ, typ, ('n1','n2',),zlib=zlib,complevel=complevel,shuffle=shuffle,least_significant_digit=least_significant_digit,fill_value=FillValue) #foo._FillValue = FillValue # test writing of _FillValue attribute for diff types diff --git a/test/type_guards.py b/test/type_guards.py index 09b5e0080..0b2ca8ff8 100644 --- a/test/type_guards.py +++ b/test/type_guards.py @@ -1,5 +1,5 @@ """_type_guards - Helpers for input type-checking""" -from typing import Literal, TYPE_CHECKING +from typing import Literal, TYPE_CHECKING, Union from typing_extensions import TypeGuard if TYPE_CHECKING: @@ -9,13 +9,13 @@ else: CompressionLevel = EndianType = CompressionType = NCFormat = QuantizeMode = object -def valid_complevel(complevel) -> TypeGuard[CompressionLevel | None]: +def valid_complevel(complevel) -> TypeGuard[CompressionLevel]: return complevel is None or isinstance(complevel, int) and 0 <= complevel <= 9 def valid_endian(endian) -> TypeGuard[EndianType]: return endian in {"native", "big", "little"} -def valid_comptype(comptype) -> TypeGuard[CompressionType | None]: +def valid_comptype(comptype) -> TypeGuard[CompressionType]: return comptype is None or comptype in { "zlib", "szip", From 111d3473aa2fbd128db1c25d7198d070648a4ca3 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Tue, 30 Jul 2024 15:06:04 -0700 Subject: [PATCH 1258/1504] Revamp type_guards a bit --- examples/bench_compress.py | 5 +- test/test_compression.py | 8 +-- test/test_compression_blosc.py | 5 +- test/test_compression_bzip2.py | 4 +- test/test_compression_quant.py | 4 +- test/test_compression_zstd.py | 4 +- test/test_endian.py | 4 +- test/test_stringarr.py | 12 ++--- test/test_types.py | 4 +- test/type_guards.py | 93 ++++++++++++++++++++++++++++------ 10 files changed, 103 insertions(+), 40 deletions(-) diff --git a/examples/bench_compress.py b/examples/bench_compress.py index 84e209e92..be8915c53 100644 --- a/examples/bench_compress.py +++ b/examples/bench_compress.py @@ -10,7 +10,7 @@ if TYPE_CHECKING: from netCDF4 import CompressionLevel else: - CompressionLevel = object + CompressionLevel = Any # create an n1dim by n2dim by n3dim random array. n1dim = 30 @@ -23,7 +23,8 @@ array = netCDF4.utils._quantize(uniform(size=(n1dim,n2dim,n3dim,n4dim)),4) def valid_complevel(complevel) -> TypeGuard[CompressionLevel]: - return complevel is None or isinstance(complevel, int) and 0 <= complevel <= 6 + """Check for a valid `complevel` argument for creating a Variable""" + return isinstance(complevel, int) and 0 <= complevel <= 9 def write_netcdf(filename,zlib=False,shuffle=False,complevel=6): file = netCDF4.Dataset(filename,'w',format='NETCDF4') diff --git a/test/test_compression.py b/test/test_compression.py index 7972609be..7d53fe436 100644 --- a/test/test_compression.py +++ b/test/test_compression.py @@ -3,7 +3,7 @@ from netCDF4.utils import _quantize from numpy.testing import assert_almost_equal import os, tempfile, unittest -from type_guards import valid_complevel, valid_comptype +import type_guards as n4t ndim = 100000 ndim2 = 100 @@ -16,7 +16,7 @@ def write_netcdf(filename,zlib,least_significant_digit,data,dtype='f8',shuffle=False,contiguous=False,\ chunksizes=None,complevel=6,fletcher32=False): - assert valid_complevel(complevel) or complevel is None + assert n4t.valid_complevel(complevel) or complevel is None file = Dataset(filename,'w') file.createDimension('n', ndim) foo = file.createVariable('data',\ @@ -32,7 +32,7 @@ def write_netcdf(filename,zlib,least_significant_digit,data,dtype='f8',shuffle=F #compression='' #compression=0 #compression='gzip' # should fail - assert valid_comptype(compression) or compression is None + assert n4t.valid_compression(compression) or compression is None foo2 = file.createVariable('data2',\ dtype,('n'),compression=compression,least_significant_digit=least_significant_digit,\ shuffle=shuffle,contiguous=contiguous,complevel=complevel,fletcher32=fletcher32,chunksizes=chunksizes) @@ -49,7 +49,7 @@ def write_netcdf2(filename,zlib,least_significant_digit,data,dtype='f8',shuffle= file = Dataset(filename,'w') file.createDimension('n', ndim) file.createDimension('n2', ndim2) - assert valid_complevel(complevel) or complevel is None + assert n4t.valid_complevel(complevel) or complevel is None foo = file.createVariable('data2',\ dtype,('n','n2'),zlib=zlib,least_significant_digit=least_significant_digit,\ shuffle=shuffle,contiguous=contiguous,complevel=complevel,fletcher32=fletcher32,chunksizes=chunksizes) diff --git a/test/test_compression_blosc.py b/test/test_compression_blosc.py index bbfc08a39..f8f13e48d 100644 --- a/test/test_compression_blosc.py +++ b/test/test_compression_blosc.py @@ -1,9 +1,10 @@ from numpy.random.mtrand import uniform from netCDF4 import Dataset +import type_guards as n4t from numpy.testing import assert_almost_equal import os, tempfile, unittest, sys from filter_availability import no_plugins, has_blosc_filter -from type_guards import valid_complevel, valid_bloscshuffle +import type_guards as n4t ndim = 100000 @@ -13,7 +14,7 @@ datarr = uniform(size=(ndim,)) def write_netcdf(filename,dtype='f8',blosc_shuffle=1,complevel=6): - assert (valid_complevel(complevel) or complevel is None) and valid_bloscshuffle(blosc_shuffle) + assert (n4t.valid_complevel(complevel) or complevel is None) and n4t.valid_bloscshuffle(blosc_shuffle) nc = Dataset(filename,'w') nc.createDimension('n', ndim) foo = nc.createVariable('data',\ diff --git a/test/test_compression_bzip2.py b/test/test_compression_bzip2.py index 1b008f190..b207288df 100644 --- a/test/test_compression_bzip2.py +++ b/test/test_compression_bzip2.py @@ -3,7 +3,7 @@ from numpy.testing import assert_almost_equal import os, tempfile, unittest, sys from filter_availability import no_plugins, has_bzip2_filter -from type_guards import valid_complevel +import type_guards as n4t ndim = 100000 filename1 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name @@ -11,7 +11,7 @@ array = uniform(size=(ndim,)) def write_netcdf(filename,dtype='f8',complevel=6): - assert valid_complevel(complevel) or complevel is None + assert n4t.valid_complevel(complevel) or complevel is None nc = Dataset(filename,'w') nc.createDimension('n', ndim) foo = nc.createVariable('data',\ diff --git a/test/test_compression_quant.py b/test/test_compression_quant.py index dd124c348..bbb2b2676 100644 --- a/test/test_compression_quant.py +++ b/test/test_compression_quant.py @@ -3,7 +3,7 @@ from numpy.testing import assert_almost_equal import numpy as np import os, tempfile, unittest -from type_guards import valid_complevel, valid_quantize_mode +import type_guards as n4t ndim = 100000 nfiles = 7 @@ -17,7 +17,7 @@ def write_netcdf(filename,zlib,significant_digits,data,dtype='f8',shuffle=False, complevel=6,quantize_mode="BitGroom"): file = Dataset(filename,'w') file.createDimension('n', ndim) - assert (valid_complevel(complevel) or complevel is None) and valid_quantize_mode(quantize_mode) + assert (n4t.valid_complevel(complevel) or complevel is None) and n4t.valid_quantize_mode(quantize_mode) foo = file.createVariable('data',\ dtype,('n'),zlib=zlib,significant_digits=significant_digits,\ shuffle=shuffle,complevel=complevel,quantize_mode=quantize_mode) diff --git a/test/test_compression_zstd.py b/test/test_compression_zstd.py index 4ee16daff..820b3df37 100644 --- a/test/test_compression_zstd.py +++ b/test/test_compression_zstd.py @@ -3,7 +3,7 @@ from numpy.testing import assert_almost_equal import os, tempfile, unittest, sys from filter_availability import no_plugins, has_zstd_filter -from type_guards import valid_complevel +import type_guards as n4t ndim = 100000 filename1 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name @@ -13,7 +13,7 @@ def write_netcdf(filename,dtype='f8',complevel=6): nc = Dataset(filename,'w') nc.createDimension('n', ndim) - assert valid_complevel(complevel) or complevel is None + assert n4t.valid_complevel(complevel) or complevel is None foo = nc.createVariable('data',\ dtype,('n'),compression='zstd',complevel=complevel) foo[:] = array diff --git a/test/test_endian.py b/test/test_endian.py index 3a8aecebb..12f1bef7f 100644 --- a/test/test_endian.py +++ b/test/test_endian.py @@ -2,7 +2,7 @@ import numpy as np import unittest, os, tempfile from numpy.testing import assert_array_equal, assert_array_almost_equal -from type_guards import valid_endian +import type_guards as n4t data = np.arange(12,dtype='f4').reshape(3,4) FILE_NAME = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name @@ -74,7 +74,7 @@ def issue310(file): endian='little' else: raise ValueError('cannot determine native endianness') - assert valid_endian(endian) # mypy fails to narrow endian on its own + assert n4t.valid_endian(endian) # mypy fails to narrow endian on its own var_big_endian = nc.createVariable(\ 'obs_big_endian', '>f8', ('obs', ),\ endian=endian,fill_value=fval) diff --git a/test/test_stringarr.py b/test/test_stringarr.py index 597e40096..ef05b0b38 100644 --- a/test/test_stringarr.py +++ b/test/test_stringarr.py @@ -3,7 +3,7 @@ import unittest import os from numpy.testing import assert_array_equal, assert_array_almost_equal -from type_guards import valid_ncformat +import type_guards as n4t def generateString(length, alphabet=string.ascii_letters + string.digits + string.punctuation): return(''.join([random.choice(alphabet) for i in range(length)])) @@ -25,7 +25,7 @@ class StringArrayTestCase(unittest.TestCase): def setUp(self): self.file = FILE_NAME - assert valid_ncformat(FILE_FORMAT) + assert n4t.valid_ncformat(FILE_FORMAT) nc = Dataset(FILE_NAME,'w',format=FILE_FORMAT) nc.createDimension('n1',None) nc.createDimension('n2',n2) @@ -72,19 +72,19 @@ def runTest(self): assert_array_equal(data3,datau) # these slices should return a char array, not a string array data4 = v2[:,:,0] - assert data4.dtype.itemsize == 1 + assert data4.dtype.itemsize == 1 assert_array_equal(data4, datac[:,:,0]) data5 = v2[0,0:nchar,0] - assert data5.dtype.itemsize == 1 + assert data5.dtype.itemsize == 1 assert_array_equal(data5, datac[0,0:nchar,0]) # test turning auto-conversion off. v2.set_auto_chartostring(False) data6 = v2[:] - assert data6.dtype.itemsize == 1 + assert data6.dtype.itemsize == 1 assert_array_equal(data6, datac) nc.set_auto_chartostring(False) data7 = v3[:] - assert data7.dtype.itemsize == 1 + assert data7.dtype.itemsize == 1 assert_array_equal(data7, datac) nc.close() diff --git a/test/test_types.py b/test/test_types.py index b8eb74b2e..1ddb292a4 100644 --- a/test/test_types.py +++ b/test/test_types.py @@ -6,7 +6,7 @@ from numpy.testing import assert_array_equal, assert_array_almost_equal from numpy.random.mtrand import uniform import netCDF4 -from type_guards import valid_complevel +import type_guards as n4t # test primitive data types. @@ -29,7 +29,7 @@ def setUp(self): f.createDimension('n1', None) f.createDimension('n2', n2dim) for typ in datatypes: - assert valid_complevel(complevel) or complevel is None + assert n4t.valid_complevel(complevel) or complevel is None foo = f.createVariable('data_'+typ, typ, ('n1','n2',),zlib=zlib,complevel=complevel,shuffle=shuffle,least_significant_digit=least_significant_digit,fill_value=FillValue) #foo._FillValue = FillValue # test writing of _FillValue attribute for diff types diff --git a/test/type_guards.py b/test/type_guards.py index 0b2ca8ff8..02e226fa9 100644 --- a/test/type_guards.py +++ b/test/type_guards.py @@ -1,22 +1,60 @@ -"""_type_guards - Helpers for input type-checking""" -from typing import Literal, TYPE_CHECKING, Union +"""type_guards.py - Helpers for static and runtime type-checking of initialization arguments +for Dataset and Variable""" + +from typing import TYPE_CHECKING, Any, Literal + from typing_extensions import TypeGuard if TYPE_CHECKING: # in stubs only - from netCDF4 import CompressionLevel, EndianType, CompressionType, QuantizeMode + from netCDF4 import ( + AccessMode, + CalendarType, + CompressionLevel, + CompressionType, + EndianType, + QuantizeMode, + ) from netCDF4 import Format as NCFormat else: - CompressionLevel = EndianType = CompressionType = NCFormat = QuantizeMode = object + AccessMode = Any + CalendarType = Any + CompressionLevel = Any + DiskFormat = Any + EndianType = Any + CompressionType = Any + NCFormat = Any + QuantizeMode = Any + + +def valid_access_mode(mode) -> TypeGuard[AccessMode]: + """Check for a valid `mode` argument for opening a Dataset""" + return mode in {"r", "w", "r+", "a", "x", "rs", "ws", "r+s", "as"} + + +def valid_calendar(calendar) -> TypeGuard[CalendarType]: + """Check for a valid `calendar` argument for cftime functions""" + return calendar in { + "standard", + "gregorian", + "proleptic_gregorian", + "noleap", + "365_day", + "360_day", + "julian", + "all_leap", + "366_day", + } + def valid_complevel(complevel) -> TypeGuard[CompressionLevel]: - return complevel is None or isinstance(complevel, int) and 0 <= complevel <= 9 + """Check for a valid `complevel` argument for creating a Variable""" + return isinstance(complevel, int) and 0 <= complevel <= 9 -def valid_endian(endian) -> TypeGuard[EndianType]: - return endian in {"native", "big", "little"} -def valid_comptype(comptype) -> TypeGuard[CompressionType]: - return comptype is None or comptype in { +def valid_compression(compression) -> TypeGuard[CompressionType]: + """Check for a valid `compression` argument for creating a Variable""" + return compression in { "zlib", "szip", "zstd", @@ -28,17 +66,40 @@ def valid_comptype(comptype) -> TypeGuard[CompressionType]: "blosc_zstd", } -def valid_bloscshuffle(bloscshuffle) -> TypeGuard[Literal[0, 1, 2]]: - return bloscshuffle in {0, 1, 2} -def valid_ncformat(ncformat) -> TypeGuard[NCFormat]: - return ncformat in [ +def valid_ncformat(format) -> TypeGuard[NCFormat]: + """Check for a valid `format` argument for opening a Dataset""" + return format in { "NETCDF4", "NETCDF4_CLASSIC", "NETCDF3_CLASSIC", "NETCDF3_64BIT_OFFSET", - "NETCDF3_64BIT_DATA" - ] + "NETCDF3_64BIT_DATA", + } + + +def valid_endian(endian) -> TypeGuard[EndianType]: + """Check for a valid `endian` argument for creating a Variable""" + return endian in {"native", "big", "little"} + + +def valid_bloscshuffle(blosc_shuffle) -> TypeGuard[Literal[0, 1, 2]]: + """Check for a valid `blosc_shuffle` argument for creating a Variable""" + return blosc_shuffle in {0, 1, 2} + def valid_quantize_mode(quantize_mode) -> TypeGuard[QuantizeMode]: - return quantize_mode in ["BitGroom", "BitRound", "GranularBitRound"] \ No newline at end of file + """Check for a valid `quantize_mode` argument for creating a Variable""" + return quantize_mode in {"BitGroom", "BitRound", "GranularBitRound"} + + +def valid_szip_coding(szip_coding) -> TypeGuard[Literal["nn", "ec"]]: + """Check for a valid `szip_coding` argument for creating a Variable""" + return szip_coding in {"nn", "ec"} + + +def valid_szip_pixels_per_block( + szip_pixels_per_block, +) -> TypeGuard[Literal[4, 8, 16, 32]]: + """Check for a valid `szip_pixels_per_block` argument for creating a Variable""" + return szip_pixels_per_block in {4, 8, 16, 32} From fab4050505bbd60b14fa40bf37a7261abe260d57 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Tue, 30 Jul 2024 15:13:38 -0700 Subject: [PATCH 1259/1504] Revert "disable some cicd" This reverts commit 7c9eb602e79f294613fd3fea9f317f801035bec5. --- .github/workflows/build_latest.yml | 3 +-- .github/workflows/build_master.yml | 11 +++++------ .github/workflows/build_old.yml | 3 +-- .github/workflows/cibuildwheel.yml | 17 ++++++++--------- .github/workflows/miniconda.yml | 16 +++++++--------- 5 files changed, 22 insertions(+), 28 deletions(-) diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml index 28f65c7a8..8f536624e 100644 --- a/.github/workflows/build_latest.yml +++ b/.github/workflows/build_latest.yml @@ -1,6 +1,5 @@ name: Build and Test Linux with latest netcdf-c -# on: [push, pull_request] -on: [] # disable +on: [push, pull_request] jobs: build-linux: name: Python (${{ matrix.python-version }}) diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index af16c3eec..9e0cf70f3 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -1,6 +1,5 @@ name: Build and Test on Linux with netcdf-c github master -# on: [push, pull_request] -on: [] # disable +on: [push, pull_request] jobs: build-linux: name: Python (${{ matrix.python-version }}) @@ -34,7 +33,7 @@ jobs: export LDFLAGS="-L${NETCDF_DIR}/lib" export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz" autoreconf -i - ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 + ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 make -j 2 make install popd @@ -43,7 +42,7 @@ jobs: # if: ${{ failure() }} # run: | # cd netcdf-c-${NETCDF_VERSION} -# cat config.log +# cat config.log - name: Install python dependencies via pip run: | @@ -52,13 +51,13 @@ jobs: - name: Install netcdf4-python run: | - export PATH=${NETCDF_DIR}/bin:${PATH} + export PATH=${NETCDF_DIR}/bin:${PATH} export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c/plugins/plugindir python setup.py install - name: Test run: | - export PATH=${NETCDF_DIR}/bin:${PATH} + export PATH=${NETCDF_DIR}/bin:${PATH} #export HDF5_PLUGIN_PATH=${NETCDF_DIR}/plugins/plugindir python checkversion.py # serial diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml index 67d141eef..b10977d9d 100644 --- a/.github/workflows/build_old.yml +++ b/.github/workflows/build_old.yml @@ -1,6 +1,5 @@ name: Build and Test Linux with older netcdf-c -# on: [push, pull_request] -on: [] # disable +on: [push, pull_request] jobs: build-linux: name: Python (${{ matrix.python-version }}) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 09ca9b752..cfbc6823d 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -1,14 +1,13 @@ name: Wheels -on: ["push"] -# on: -# pull_request: -# push: -# tags: -# - "v*" -# release: -# types: -# - published +on: + pull_request: + push: + tags: + - "v*" + release: + types: + - published permissions: contents: read diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index fb291fdc0..ba790d589 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -1,10 +1,9 @@ name: Build and Test -# on: -# pull_request: -# push: -# branches: [master] -on: ["push"] +on: + pull_request: + push: + branches: [master] jobs: run-serial: @@ -13,12 +12,11 @@ jobs: # NO_NET: 1 strategy: matrix: - # python-version: [ "3.9", "3.10", "3.11", "3.12" ] - python-version: [ "3.9", "3.10"] + python-version: [ "3.9", "3.10", "3.11", "3.12" ] os: [windows-latest, ubuntu-latest, macos-latest] platform: [x64, x32] exclude: - - os: macos-latest + - os: macos-latest platform: x32 fail-fast: false defaults: @@ -84,7 +82,7 @@ jobs: run: | cd test && python run_all.py cd ../examples - export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" + export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" which mpirun mpirun --version mpirun -np 4 --oversubscribe python mpi_example.py # for openmpi From e0719dac3c35c7e7f1fac49ba42e1bf934abd3b7 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Tue, 30 Jul 2024 15:20:54 -0700 Subject: [PATCH 1260/1504] (minor) restore whitespace to clean diff --- .github/workflows/build_latest.yml | 16 ++++++++-------- .github/workflows/build_old.yml | 16 ++++++++-------- 2 files changed, 16 insertions(+), 16 deletions(-) diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml index 8f536624e..4a80cf01a 100644 --- a/.github/workflows/build_latest.yml +++ b/.github/workflows/build_latest.yml @@ -53,7 +53,7 @@ jobs: # if: ${{ failure() }} # run: | # cd netcdf-c-${NETCDF_VERSION} -# cat config.log +# cat config.log - name: Install python dependencies via pip run: | @@ -62,12 +62,12 @@ jobs: - name: Install netcdf4-python run: | - export PATH=${NETCDF_DIR}/bin:${PATH} + export PATH=${NETCDF_DIR}/bin:${PATH} export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c-${NETCDF_VERSION}/plugins/plugindir python setup.py install - name: Test run: | - export PATH=${NETCDF_DIR}/bin:${PATH} + export PATH=${NETCDF_DIR}/bin:${PATH} python checkversion.py # serial cd test @@ -98,9 +98,9 @@ jobs: # - name: Tarball # run: | -# export PATH=${NETCDF_DIR}/bin:${PATH} -# python setup.py --version +# export PATH=${NETCDF_DIR}/bin:${PATH} +# python setup.py --version # check-manifest --version -# check-manifest --verbose -# pip wheel . -w dist --no-deps -# twine check dist/* +# check-manifest --verbose +# pip wheel . -w dist --no-deps +# twine check dist/* diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml index b10977d9d..063f0a87f 100644 --- a/.github/workflows/build_old.yml +++ b/.github/workflows/build_old.yml @@ -53,7 +53,7 @@ jobs: # if: ${{ failure() }} # run: | # cd netcdf-c-${NETCDF_VERSION} -# cat config.log +# cat config.log - name: Install python dependencies via pip run: | @@ -62,12 +62,12 @@ jobs: - name: Install netcdf4-python run: | - export PATH=${NETCDF_DIR}/bin:${PATH} + export PATH=${NETCDF_DIR}/bin:${PATH} export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c-${NETCDF_VERSION}/plugins/plugindir python setup.py install - name: Test run: | - export PATH=${NETCDF_DIR}/bin:${PATH} + export PATH=${NETCDF_DIR}/bin:${PATH} python checkversion.py # serial cd test @@ -98,9 +98,9 @@ jobs: # - name: Tarball # run: | -# export PATH=${NETCDF_DIR}/bin:${PATH} -# python setup.py --version +# export PATH=${NETCDF_DIR}/bin:${PATH} +# python setup.py --version # check-manifest --version -# check-manifest --verbose -# pip wheel . -w dist --no-deps -# twine check dist/* +# check-manifest --verbose +# pip wheel . -w dist --no-deps +# twine check dist/* From d42667d66a532e566cb2d115262cc201c10b933b Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Tue, 30 Jul 2024 15:22:22 -0700 Subject: [PATCH 1261/1504] (minor) restore whitespace again to clean diff --- .github/workflows/build_latest.yml | 2 +- .github/workflows/build_old.yml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml index 4a80cf01a..0f3bb7d3e 100644 --- a/.github/workflows/build_latest.yml +++ b/.github/workflows/build_latest.yml @@ -99,7 +99,7 @@ jobs: # - name: Tarball # run: | # export PATH=${NETCDF_DIR}/bin:${PATH} -# python setup.py --version +# python setup.py --version # check-manifest --version # check-manifest --verbose # pip wheel . -w dist --no-deps diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml index 063f0a87f..7f958f17a 100644 --- a/.github/workflows/build_old.yml +++ b/.github/workflows/build_old.yml @@ -99,7 +99,7 @@ jobs: # - name: Tarball # run: | # export PATH=${NETCDF_DIR}/bin:${PATH} -# python setup.py --version +# python setup.py --version # check-manifest --version # check-manifest --verbose # pip wheel . -w dist --no-deps From 3b1de4bf18cbbe88f05b8860282e5b5498ba59ae Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Tue, 30 Jul 2024 15:58:24 -0700 Subject: [PATCH 1262/1504] update examples and tests type_guards --- examples/bench.py | 2 + examples/bench_compress4.py | 2 + examples/bench_diskless.py | 2 + examples/type_guards.py | 105 +++++++++++++++++++++++++++++++++ test/test_compression.py | 8 +-- test/test_compression_blosc.py | 6 +- test/test_compression_bzip2.py | 4 +- test/test_compression_quant.py | 4 +- test/test_compression_zstd.py | 4 +- test/test_endian.py | 4 +- test/test_stringarr.py | 4 +- test/test_types.py | 4 +- test/type_guards.py | 2 +- 13 files changed, 131 insertions(+), 20 deletions(-) create mode 100644 examples/type_guards.py diff --git a/examples/bench.py b/examples/bench.py index f3ad75246..1d18ed8e1 100644 --- a/examples/bench.py +++ b/examples/bench.py @@ -4,6 +4,7 @@ import netCDF4 from timeit import Timer import os, sys +import type_guards # create an n1dim by n2dim by n3dim random array. n1dim = 30 @@ -15,6 +16,7 @@ array = uniform(size=(n1dim,n2dim,n3dim,n4dim)) def write_netcdf(filename,zlib=False,least_significant_digit=None,format='NETCDF4'): + assert type_guards.valid_format(format) file = netCDF4.Dataset(filename,'w',format=format) file.createDimension('n1', n1dim) file.createDimension('n2', n2dim) diff --git a/examples/bench_compress4.py b/examples/bench_compress4.py index a7d0e1033..05b9ade80 100644 --- a/examples/bench_compress4.py +++ b/examples/bench_compress4.py @@ -4,6 +4,7 @@ import netCDF4 from timeit import Timer import os, sys +import type_guards # use real data. URL="http://www.esrl.noaa.gov/psd/thredds/dodsC/Datasets/ncep.reanalysis/pressure/hgt.1990.nc" @@ -24,6 +25,7 @@ def write_netcdf(filename,nsd,quantize_mode='BitGroom'): file.createDimension('n1', None) file.createDimension('n3', n3dim) file.createDimension('n4', n4dim) + assert type_guards.valid_quantize_mode(quantize_mode) foo = file.createVariable('data',\ 'f4',('n1','n3','n4'),\ zlib=True,shuffle=True,\ diff --git a/examples/bench_diskless.py b/examples/bench_diskless.py index dd7a78315..ae92e037b 100644 --- a/examples/bench_diskless.py +++ b/examples/bench_diskless.py @@ -4,6 +4,7 @@ import netCDF4 from timeit import Timer import os, sys +import type_guards # create an n1dim by n2dim by n3dim random array. n1dim = 30 @@ -15,6 +16,7 @@ array = uniform(size=(n1dim,n2dim,n3dim,n4dim)) def write_netcdf(filename,zlib=False,least_significant_digit=None,format='NETCDF4',closeit=False): + assert type_guards.valid_format(format) file = netCDF4.Dataset(filename,'w',format=format,diskless=True,persist=True) file.createDimension('n1', n1dim) file.createDimension('n2', n2dim) diff --git a/examples/type_guards.py b/examples/type_guards.py new file mode 100644 index 000000000..2baabda68 --- /dev/null +++ b/examples/type_guards.py @@ -0,0 +1,105 @@ +"""type_guards.py - Helpers for static and runtime type-checking of initialization arguments +for Dataset and Variable""" + +from typing import TYPE_CHECKING, Any, Literal + +from typing_extensions import TypeGuard + +if TYPE_CHECKING: + # in stubs only + from netCDF4 import ( + AccessMode, + CalendarType, + CompressionLevel, + CompressionType, + EndianType, + QuantizeMode, + ) + from netCDF4 import Format as NCFormat +else: + AccessMode = Any + CalendarType = Any + CompressionLevel = Any + DiskFormat = Any + EndianType = Any + CompressionType = Any + NCFormat = Any + QuantizeMode = Any + + +def valid_access_mode(mode) -> TypeGuard[AccessMode]: + """Check for a valid `mode` argument for opening a Dataset""" + return mode in {"r", "w", "r+", "a", "x", "rs", "ws", "r+s", "as"} + + +def valid_calendar(calendar) -> TypeGuard[CalendarType]: + """Check for a valid `calendar` argument for cftime functions""" + return calendar in { + "standard", + "gregorian", + "proleptic_gregorian", + "noleap", + "365_day", + "360_day", + "julian", + "all_leap", + "366_day", + } + + +def valid_complevel(complevel) -> TypeGuard[CompressionLevel]: + """Check for a valid `complevel` argument for creating a Variable""" + return isinstance(complevel, int) and 0 <= complevel <= 9 + + +def valid_compression(compression) -> TypeGuard[CompressionType]: + """Check for a valid `compression` argument for creating a Variable""" + return compression in { + "zlib", + "szip", + "zstd", + "bzip2", + "blosc_lz", + "blosc_lz4", + "blosc_lz4hc", + "blosc_zlib", + "blosc_zstd", + } + + +def valid_format(format) -> TypeGuard[NCFormat]: + """Check for a valid `format` argument for opening a Dataset""" + return format in { + "NETCDF4", + "NETCDF4_CLASSIC", + "NETCDF3_CLASSIC", + "NETCDF3_64BIT_OFFSET", + "NETCDF3_64BIT_DATA", + } + + +def valid_endian(endian) -> TypeGuard[EndianType]: + """Check for a valid `endian` argument for creating a Variable""" + return endian in {"native", "big", "little"} + + +def valid_bloscshuffle(blosc_shuffle) -> TypeGuard[Literal[0, 1, 2]]: + """Check for a valid `blosc_shuffle` argument for creating a Variable""" + return blosc_shuffle in {0, 1, 2} + + +def valid_quantize_mode(quantize_mode) -> TypeGuard[QuantizeMode]: + """Check for a valid `quantize_mode` argument for creating a Variable""" + return quantize_mode in {"BitGroom", "BitRound", "GranularBitRound"} + + +def valid_szip_coding(szip_coding) -> TypeGuard[Literal["nn", "ec"]]: + """Check for a valid `szip_coding` argument for creating a Variable""" + return szip_coding in {"nn", "ec"} + + +def valid_szip_pixels_per_block( + szip_pixels_per_block, +) -> TypeGuard[Literal[4, 8, 16, 32]]: + """Check for a valid `szip_pixels_per_block` argument for creating a Variable""" + return szip_pixels_per_block in {4, 8, 16, 32} diff --git a/test/test_compression.py b/test/test_compression.py index 7d53fe436..1d4b59076 100644 --- a/test/test_compression.py +++ b/test/test_compression.py @@ -3,7 +3,7 @@ from netCDF4.utils import _quantize from numpy.testing import assert_almost_equal import os, tempfile, unittest -import type_guards as n4t +import type_guards ndim = 100000 ndim2 = 100 @@ -16,7 +16,7 @@ def write_netcdf(filename,zlib,least_significant_digit,data,dtype='f8',shuffle=False,contiguous=False,\ chunksizes=None,complevel=6,fletcher32=False): - assert n4t.valid_complevel(complevel) or complevel is None + assert type_guards.valid_complevel(complevel) or complevel is None file = Dataset(filename,'w') file.createDimension('n', ndim) foo = file.createVariable('data',\ @@ -32,7 +32,7 @@ def write_netcdf(filename,zlib,least_significant_digit,data,dtype='f8',shuffle=F #compression='' #compression=0 #compression='gzip' # should fail - assert n4t.valid_compression(compression) or compression is None + assert type_guards.valid_compression(compression) or compression is None foo2 = file.createVariable('data2',\ dtype,('n'),compression=compression,least_significant_digit=least_significant_digit,\ shuffle=shuffle,contiguous=contiguous,complevel=complevel,fletcher32=fletcher32,chunksizes=chunksizes) @@ -49,7 +49,7 @@ def write_netcdf2(filename,zlib,least_significant_digit,data,dtype='f8',shuffle= file = Dataset(filename,'w') file.createDimension('n', ndim) file.createDimension('n2', ndim2) - assert n4t.valid_complevel(complevel) or complevel is None + assert type_guards.valid_complevel(complevel) or complevel is None foo = file.createVariable('data2',\ dtype,('n','n2'),zlib=zlib,least_significant_digit=least_significant_digit,\ shuffle=shuffle,contiguous=contiguous,complevel=complevel,fletcher32=fletcher32,chunksizes=chunksizes) diff --git a/test/test_compression_blosc.py b/test/test_compression_blosc.py index f8f13e48d..c532fef32 100644 --- a/test/test_compression_blosc.py +++ b/test/test_compression_blosc.py @@ -1,10 +1,10 @@ from numpy.random.mtrand import uniform from netCDF4 import Dataset -import type_guards as n4t +import type_guards from numpy.testing import assert_almost_equal import os, tempfile, unittest, sys from filter_availability import no_plugins, has_blosc_filter -import type_guards as n4t +import type_guards ndim = 100000 @@ -14,7 +14,7 @@ datarr = uniform(size=(ndim,)) def write_netcdf(filename,dtype='f8',blosc_shuffle=1,complevel=6): - assert (n4t.valid_complevel(complevel) or complevel is None) and n4t.valid_bloscshuffle(blosc_shuffle) + assert (type_guards.valid_complevel(complevel) or complevel is None) and type_guards.valid_bloscshuffle(blosc_shuffle) nc = Dataset(filename,'w') nc.createDimension('n', ndim) foo = nc.createVariable('data',\ diff --git a/test/test_compression_bzip2.py b/test/test_compression_bzip2.py index b207288df..ec32ba248 100644 --- a/test/test_compression_bzip2.py +++ b/test/test_compression_bzip2.py @@ -3,7 +3,7 @@ from numpy.testing import assert_almost_equal import os, tempfile, unittest, sys from filter_availability import no_plugins, has_bzip2_filter -import type_guards as n4t +import type_guards ndim = 100000 filename1 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name @@ -11,7 +11,7 @@ array = uniform(size=(ndim,)) def write_netcdf(filename,dtype='f8',complevel=6): - assert n4t.valid_complevel(complevel) or complevel is None + assert type_guards.valid_complevel(complevel) or complevel is None nc = Dataset(filename,'w') nc.createDimension('n', ndim) foo = nc.createVariable('data',\ diff --git a/test/test_compression_quant.py b/test/test_compression_quant.py index bbb2b2676..24267615a 100644 --- a/test/test_compression_quant.py +++ b/test/test_compression_quant.py @@ -3,7 +3,7 @@ from numpy.testing import assert_almost_equal import numpy as np import os, tempfile, unittest -import type_guards as n4t +import type_guards ndim = 100000 nfiles = 7 @@ -17,7 +17,7 @@ def write_netcdf(filename,zlib,significant_digits,data,dtype='f8',shuffle=False, complevel=6,quantize_mode="BitGroom"): file = Dataset(filename,'w') file.createDimension('n', ndim) - assert (n4t.valid_complevel(complevel) or complevel is None) and n4t.valid_quantize_mode(quantize_mode) + assert (type_guards.valid_complevel(complevel) or complevel is None) and type_guards.valid_quantize_mode(quantize_mode) foo = file.createVariable('data',\ dtype,('n'),zlib=zlib,significant_digits=significant_digits,\ shuffle=shuffle,complevel=complevel,quantize_mode=quantize_mode) diff --git a/test/test_compression_zstd.py b/test/test_compression_zstd.py index 820b3df37..123397f12 100644 --- a/test/test_compression_zstd.py +++ b/test/test_compression_zstd.py @@ -3,7 +3,7 @@ from numpy.testing import assert_almost_equal import os, tempfile, unittest, sys from filter_availability import no_plugins, has_zstd_filter -import type_guards as n4t +import type_guards ndim = 100000 filename1 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name @@ -13,7 +13,7 @@ def write_netcdf(filename,dtype='f8',complevel=6): nc = Dataset(filename,'w') nc.createDimension('n', ndim) - assert n4t.valid_complevel(complevel) or complevel is None + assert type_guards.valid_complevel(complevel) or complevel is None foo = nc.createVariable('data',\ dtype,('n'),compression='zstd',complevel=complevel) foo[:] = array diff --git a/test/test_endian.py b/test/test_endian.py index 12f1bef7f..1a8f58681 100644 --- a/test/test_endian.py +++ b/test/test_endian.py @@ -2,7 +2,7 @@ import numpy as np import unittest, os, tempfile from numpy.testing import assert_array_equal, assert_array_almost_equal -import type_guards as n4t +import type_guards data = np.arange(12,dtype='f4').reshape(3,4) FILE_NAME = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name @@ -74,7 +74,7 @@ def issue310(file): endian='little' else: raise ValueError('cannot determine native endianness') - assert n4t.valid_endian(endian) # mypy fails to narrow endian on its own + assert type_guards.valid_endian(endian) # mypy fails to narrow endian on its own var_big_endian = nc.createVariable(\ 'obs_big_endian', '>f8', ('obs', ),\ endian=endian,fill_value=fval) diff --git a/test/test_stringarr.py b/test/test_stringarr.py index ef05b0b38..f3e140c0a 100644 --- a/test/test_stringarr.py +++ b/test/test_stringarr.py @@ -3,7 +3,7 @@ import unittest import os from numpy.testing import assert_array_equal, assert_array_almost_equal -import type_guards as n4t +import type_guards def generateString(length, alphabet=string.ascii_letters + string.digits + string.punctuation): return(''.join([random.choice(alphabet) for i in range(length)])) @@ -25,7 +25,7 @@ class StringArrayTestCase(unittest.TestCase): def setUp(self): self.file = FILE_NAME - assert n4t.valid_ncformat(FILE_FORMAT) + assert type_guards.valid_format(FILE_FORMAT) nc = Dataset(FILE_NAME,'w',format=FILE_FORMAT) nc.createDimension('n1',None) nc.createDimension('n2',n2) diff --git a/test/test_types.py b/test/test_types.py index 1ddb292a4..3cc7bbc3b 100644 --- a/test/test_types.py +++ b/test/test_types.py @@ -6,7 +6,7 @@ from numpy.testing import assert_array_equal, assert_array_almost_equal from numpy.random.mtrand import uniform import netCDF4 -import type_guards as n4t +import type_guards # test primitive data types. @@ -29,7 +29,7 @@ def setUp(self): f.createDimension('n1', None) f.createDimension('n2', n2dim) for typ in datatypes: - assert n4t.valid_complevel(complevel) or complevel is None + assert type_guards.valid_complevel(complevel) or complevel is None foo = f.createVariable('data_'+typ, typ, ('n1','n2',),zlib=zlib,complevel=complevel,shuffle=shuffle,least_significant_digit=least_significant_digit,fill_value=FillValue) #foo._FillValue = FillValue # test writing of _FillValue attribute for diff types diff --git a/test/type_guards.py b/test/type_guards.py index 02e226fa9..2baabda68 100644 --- a/test/type_guards.py +++ b/test/type_guards.py @@ -67,7 +67,7 @@ def valid_compression(compression) -> TypeGuard[CompressionType]: } -def valid_ncformat(format) -> TypeGuard[NCFormat]: +def valid_format(format) -> TypeGuard[NCFormat]: """Check for a valid `format` argument for opening a Dataset""" return format in { "NETCDF4", From 9f7698d6abc372e3513d03c3bbe8e12d913611c7 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 31 Jul 2024 09:42:55 -0700 Subject: [PATCH 1263/1504] disallow lists of floats or strings in GetSetItemKey --- src/netCDF4/__init__.pyi | 18 ++++++------------ 1 file changed, 6 insertions(+), 12 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index cbebd1990..790305579 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -147,9 +147,9 @@ BoolInt: TypeAlias = Literal[0, 1] DateTimeArray: TypeAlias = npt.NDArray[np.object_] """numpy array of datetime.datetime or cftime.datetime""" -# netCDF accepts floats that can be cooerced to an integer value, and sometimes strings that can be coerced to an integer value. -# There's currently no way to specify this statically, so we allow all floats and strings. -# Also, we have to specify all the possible combinations of list[...] because lists are invariant. +# - Allow singular float or str keys, but not lists (or sequences) of them +# - `list` and `ndarray` are specifically listed for the 1-D case as Sequence is too general -- it includes +# tuples which are rather for multi-dimensional indexing. GetSetItemKey: TypeAlias = ( int | float @@ -158,12 +158,8 @@ GetSetItemKey: TypeAlias = ( | slice | ellipsis | list[int] - | list[float] - | list[np.number] - | list[str] | list[bool] - | list[np.bool_] - | npt.NDArray[np.number] + | npt.NDArray[np.integer] | npt.NDArray[np.bool_] | tuple[ int @@ -173,12 +169,10 @@ GetSetItemKey: TypeAlias = ( | slice | ellipsis | Sequence[int] - | Sequence[float] - | Sequence[np.number] - | Sequence[str] + | Sequence[np.integer] | Sequence[bool] | Sequence[np.bool_] - | npt.NDArray[np.number] + | npt.NDArray[np.integer] | npt.NDArray[np.bool_], ..., ] From 1975e12daa7baf7b0a53f80bdef09673937bf6d1 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 31 Jul 2024 09:43:14 -0700 Subject: [PATCH 1264/1504] disallow float dimension size --- src/netCDF4/__init__.pyi | 4 ++-- test/test_multifile2.py | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 790305579..e9c22ed8a 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -310,7 +310,7 @@ class Dataset: def sync(self) -> None: ... def set_fill_on(self) -> None: ... def set_fill_off(self) -> None: ... - def createDimension(self, dimname: str, size: int | float | None = None) -> Dimension: ... + def createDimension(self, dimname: str, size: int | None = None) -> Dimension: ... def renameDimension(self, oldname: str, newname: str) -> None: ... @overload def createVariable( @@ -433,7 +433,7 @@ class Group(Dataset): def close(self) -> NoReturn: ... class Dimension: - def __init__(self, grp: Dataset, name: str, size: int | float | None = None, **kwargs: Any) -> None: ... + def __init__(self, grp: Dataset, name: str, size: int | None = None, **kwargs: Any) -> None: ... @property def name(self) -> str: ... @property diff --git a/test/test_multifile2.py b/test/test_multifile2.py index 3ab3d482b..2c37a6f83 100644 --- a/test/test_multifile2.py +++ b/test/test_multifile2.py @@ -23,7 +23,7 @@ def setUp(self): for nfile,file in enumerate(self.files): f = Dataset(file,'w',format='NETCDF4_CLASSIC') #f.createDimension('x',None) - f.createDimension('x',ninc) + f.createDimension('x',int(ninc)) f.createDimension('y',ydim) f.createDimension('z',zdim) f.history = 'created today' From cd002c8a61738df0e5debd12f7d4a2f8ea60349f Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 31 Jul 2024 11:09:02 -0700 Subject: [PATCH 1265/1504] Add TypeGuard for variable type --- examples/type_guards.py | 16 +++++++++++++++- test/type_guards.py | 16 +++++++++++++++- 2 files changed, 30 insertions(+), 2 deletions(-) diff --git a/examples/type_guards.py b/examples/type_guards.py index 2baabda68..565801dd9 100644 --- a/examples/type_guards.py +++ b/examples/type_guards.py @@ -1,8 +1,9 @@ """type_guards.py - Helpers for static and runtime type-checking of initialization arguments for Dataset and Variable""" -from typing import TYPE_CHECKING, Any, Literal +from typing import TYPE_CHECKING, Any, Literal, Type, TypeVar, Union, overload +import netCDF4 from typing_extensions import TypeGuard if TYPE_CHECKING: @@ -27,6 +28,19 @@ QuantizeMode = Any +T = TypeVar("T") + + +def var_isof_type( + var: netCDF4.Variable, type_: Type[T] +) -> TypeGuard[netCDF4.Variable[T]]: + """Check that a variable is of some type. This function does not support CompoundType, + EnumType, or VLType""" + if isinstance(type_, (netCDF4.EnumType, netCDF4.VLType, netCDF4.CompoundType)): + raise TypeError("This function is not valid for user-defined types.") + return (type_ is str and var.dtype is type_) or var.dtype.type is type_ + + def valid_access_mode(mode) -> TypeGuard[AccessMode]: """Check for a valid `mode` argument for opening a Dataset""" return mode in {"r", "w", "r+", "a", "x", "rs", "ws", "r+s", "as"} diff --git a/test/type_guards.py b/test/type_guards.py index 2baabda68..565801dd9 100644 --- a/test/type_guards.py +++ b/test/type_guards.py @@ -1,8 +1,9 @@ """type_guards.py - Helpers for static and runtime type-checking of initialization arguments for Dataset and Variable""" -from typing import TYPE_CHECKING, Any, Literal +from typing import TYPE_CHECKING, Any, Literal, Type, TypeVar, Union, overload +import netCDF4 from typing_extensions import TypeGuard if TYPE_CHECKING: @@ -27,6 +28,19 @@ QuantizeMode = Any +T = TypeVar("T") + + +def var_isof_type( + var: netCDF4.Variable, type_: Type[T] +) -> TypeGuard[netCDF4.Variable[T]]: + """Check that a variable is of some type. This function does not support CompoundType, + EnumType, or VLType""" + if isinstance(type_, (netCDF4.EnumType, netCDF4.VLType, netCDF4.CompoundType)): + raise TypeError("This function is not valid for user-defined types.") + return (type_ is str and var.dtype is type_) or var.dtype.type is type_ + + def valid_access_mode(mode) -> TypeGuard[AccessMode]: """Check for a valid `mode` argument for opening a Dataset""" return mode in {"r", "w", "r+", "a", "x", "rs", "ws", "r+s", "as"} From 3f2e8aaa8aa10e291938fae1b9bb2cef5dd05b24 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 31 Jul 2024 11:09:22 -0700 Subject: [PATCH 1266/1504] Update type stub notes --- src/netCDF4/__init__.pyi | 25 +++++++++++++------------ 1 file changed, 13 insertions(+), 12 deletions(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index e9c22ed8a..7c138d5b4 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -2,26 +2,27 @@ # Notes: # # - The stubs in this file are manually-generated and must be updated if and when the API is changed. -# - The following **ruff** commands may be used to properly format this file according to +# - The following **ruff** commands may be used to format this file according to # https://typing.readthedocs.io/en/latest/source/stubs.html # # ruff format --line-length 130 src/netCDF4/__init__.pyi # format code # ruff check --line-length 130 --select I --fix src/netCDF4/__init__.pyi # sort imports # # - The Variable class is a generic and may thus be statically typed, but this has limited utility for the following reasons: -# - The return type of `Variable.__getitem__()` (and `Variable.getValue()`) depends on a number of factors (e.g. variable shape, -# key shape, whether masking is enabled) that cannot be easily determined statically. -# - Similarly, the types and shapes of data that `Variable.__setitem__()` may accept varies widely depending on many factors and -# is intractable to determine statically. -# - Automatic typing of a Variable on variable creation is tedious due to the large number of ways to specify a variable's type -# (in particular all the type literals). +# - The return type of `Variable.__getitem__()` (and `Variable.getValue()`) depends on a number of factors (e.g. variable +# shape, key shape, whether masking is enabled) that cannot be easily determined statically. +# - Similarly, the types and shapes of data that `Variable.__setitem__()` may accept varies widely depending on many factors +# and is intractable to determine statically. +# - Some facility for automatically typing a Variable on creation has been provided, however it is not exhaustive as a variable +# may created with a string literal indicating its type and it would require an excessive number of overloads to enumerate +# each of these cases. # - It is not possible to statically type a Variable of any user-defined type (CompoundType, EnumType, VLType) as these types # are created dynamically. -# It is thus best left to the user to implement TypeGuards and/or perform other mixed static/runtime type-checking to ensure the -# type and shape of data retrieved from this library. -# - `Dataset.__getitem__()` may return either a Variable or a Group, depending on the string passed to it. Rather than return a -# Union of Variable and Group, the authors of these stubs have elected to to return Any, leaving it up to users to determine the -# type of the returned value. +# Thus it is most often best for the user to implement TypeGuards and/or perform other mixed static/runtime type-checking to +# ensure the type and shape of data retrieved from this library. +# - The return type of some functions or properties (such as `Dataset.__getitem__()`) may one of a number of types. Where it is +# not possible to narrow the type with overloads, the authors of these stubs have generally chosen to use `Any` as the return +# type rather than a union of the possible types. # - `MFDataset.dimensions` returns `dict[str, Dimension]` and `MFDataset.variables` returns `dict[str, Variable]` even though the # dict value types may actually be `_Dimension` and `_Variable`, respectively. The original authors of this stubfile have # elected to do this for simplicity's sake, but it may make sense to change this in the future, or just return `dict[str, Any]`. From 4400567c69ef48e9fcf30b1ce9b750104056413f Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Wed, 31 Jul 2024 11:58:37 -0700 Subject: [PATCH 1267/1504] Revert "Add TypeGuard for variable type" This reverts commit cd002c8a61738df0e5debd12f7d4a2f8ea60349f. --- examples/type_guards.py | 16 +--------------- test/type_guards.py | 16 +--------------- 2 files changed, 2 insertions(+), 30 deletions(-) diff --git a/examples/type_guards.py b/examples/type_guards.py index 565801dd9..2baabda68 100644 --- a/examples/type_guards.py +++ b/examples/type_guards.py @@ -1,9 +1,8 @@ """type_guards.py - Helpers for static and runtime type-checking of initialization arguments for Dataset and Variable""" -from typing import TYPE_CHECKING, Any, Literal, Type, TypeVar, Union, overload +from typing import TYPE_CHECKING, Any, Literal -import netCDF4 from typing_extensions import TypeGuard if TYPE_CHECKING: @@ -28,19 +27,6 @@ QuantizeMode = Any -T = TypeVar("T") - - -def var_isof_type( - var: netCDF4.Variable, type_: Type[T] -) -> TypeGuard[netCDF4.Variable[T]]: - """Check that a variable is of some type. This function does not support CompoundType, - EnumType, or VLType""" - if isinstance(type_, (netCDF4.EnumType, netCDF4.VLType, netCDF4.CompoundType)): - raise TypeError("This function is not valid for user-defined types.") - return (type_ is str and var.dtype is type_) or var.dtype.type is type_ - - def valid_access_mode(mode) -> TypeGuard[AccessMode]: """Check for a valid `mode` argument for opening a Dataset""" return mode in {"r", "w", "r+", "a", "x", "rs", "ws", "r+s", "as"} diff --git a/test/type_guards.py b/test/type_guards.py index 565801dd9..2baabda68 100644 --- a/test/type_guards.py +++ b/test/type_guards.py @@ -1,9 +1,8 @@ """type_guards.py - Helpers for static and runtime type-checking of initialization arguments for Dataset and Variable""" -from typing import TYPE_CHECKING, Any, Literal, Type, TypeVar, Union, overload +from typing import TYPE_CHECKING, Any, Literal -import netCDF4 from typing_extensions import TypeGuard if TYPE_CHECKING: @@ -28,19 +27,6 @@ QuantizeMode = Any -T = TypeVar("T") - - -def var_isof_type( - var: netCDF4.Variable, type_: Type[T] -) -> TypeGuard[netCDF4.Variable[T]]: - """Check that a variable is of some type. This function does not support CompoundType, - EnumType, or VLType""" - if isinstance(type_, (netCDF4.EnumType, netCDF4.VLType, netCDF4.CompoundType)): - raise TypeError("This function is not valid for user-defined types.") - return (type_ is str and var.dtype is type_) or var.dtype.type is type_ - - def valid_access_mode(mode) -> TypeGuard[AccessMode]: """Check for a valid `mode` argument for opening a Dataset""" return mode in {"r", "w", "r+", "a", "x", "rs", "ws", "r+s", "as"} From 0a777315e9f436412819b14606550fcd4de57826 Mon Sep 17 00:00:00 2001 From: Masahiro Sakai Date: Thu, 1 Aug 2024 10:13:47 +0900 Subject: [PATCH 1268/1504] fix not to use iendian when the return value of nc_inq_var_endian() is not NC_NOERR iendian is left uninitialized when nc_inq_var_endian() returns NC_ENOTNC4. --- src/netCDF4/_netCDF4.pyx | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 6023406c9..2f49870fe 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2062,10 +2062,11 @@ cdef _get_vars(group, bint auto_complex=False): endianness = None with nogil: ierr = nc_inq_var_endian(_grpid, varid, &iendian) - if ierr == NC_NOERR and iendian == NC_ENDIAN_LITTLE: - endianness = '<' - elif iendian == NC_ENDIAN_BIG: - endianness = '>' + if ierr == NC_NOERR: + if iendian == NC_ENDIAN_LITTLE: + endianness = '<' + elif iendian == NC_ENDIAN_BIG: + endianness = '>' # check to see if it is a supported user-defined type. try: datatype = _nctonptype[xtype] From 892717312a2290ad3625e67611fc138a328210e0 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 5 Aug 2024 03:19:05 +0000 Subject: [PATCH 1269/1504] Bump pypa/cibuildwheel from 2.19.2 to 2.20.0 in the github-actions group Bumps the github-actions group with 1 update: [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel). Updates `pypa/cibuildwheel` from 2.19.2 to 2.20.0 - [Release notes](https://github.com/pypa/cibuildwheel/releases) - [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md) - [Commits](https://github.com/pypa/cibuildwheel/compare/v2.19.2...v2.20.0) --- updated-dependencies: - dependency-name: pypa/cibuildwheel dependency-type: direct:production update-type: version-update:semver-minor dependency-group: github-actions ... Signed-off-by: dependabot[bot] --- .github/workflows/cibuildwheel.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 5eb8bb975..558c65685 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -92,7 +92,7 @@ jobs: echo "Setting CIBW_SKIP=$CIBW_SKIP" - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels" - uses: pypa/cibuildwheel@v2.19.2 + uses: pypa/cibuildwheel@v2.20.0 env: CIBW_SKIP: ${{ env.CIBW_SKIP }} CIBW_ARCHS: ${{ matrix.arch }} From 3ebb93b7684544464f14e535984b617e17e98784 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Tue, 13 Aug 2024 16:03:48 +0200 Subject: [PATCH 1270/1504] all wheels are built with cibuildwheel now --- README.wheels.md | 100 ----------------------------------------------- 1 file changed, 100 deletions(-) delete mode 100644 README.wheels.md diff --git a/README.wheels.md b/README.wheels.md deleted file mode 100644 index 83626b78f..000000000 --- a/README.wheels.md +++ /dev/null @@ -1,100 +0,0 @@ -# Building and uploading wheels - -## For OSX - -We automate OSX wheel building using a custom github repository that builds on -the travis-ci OSX machines. - -The travis-ci interface for the builds is : -https://travis-ci.org/MacPython/netcdf4-python-wheels - -The driving github repository is : -https://github.com/MacPython/netcdf4-python-wheels - -### How it works - -The wheel-building repository: - -* does a fresh build of the required C / C++ libraries; -* builds a netcdf4-python wheel, linking against these fresh builds; -* processes the wheel using [delocate](https://pypi.python.org/pypi/delocate). - `delocate` copies the required dynamic libraries into the wheel and relinks - the extension modules against the copied libraries; -* uploads the built wheel to http://wheels.scipy.org (a Rackspace container - kindly donated by Rackspace to scikit-learn). - -The resulting wheel is therefore self-contained and does not need any external -dynamic libraries apart from those provided as standard by OSX. - -### Triggering a build - -You will need write permission to the github repository to trigger new builds -on the travis-ci interface. Contact us on the mailing list if you need this. - -You can trigger a build by: - -* making a commit to the `netcdf4-python-wheels` repository (e.g. with `git - commit --allow-empty`); or -* clicking on the circular arrow icon towards the top right of the travis-ci - page, to rerun the previous build. - -In general, it is better to trigger a build with a commit, because this makes -a new set of build products and logs, keeping the old ones for reference. -Keeping the old build logs helps us keep track of previous problems and -successful builds. - -### Which netcdf4-python commit does the repository build? - -By default, the `netcd4-python-wheels` repository is usually set up to build -the latest git tag. To check whether this is so have a look around line 5 of -`.travis.yml` in the `netcdf4-python-wheels` repository. You should see -something like: - -``` -- BUILD_COMMIT='latest-tag' -``` - -If this is commented out, then the repository is set up to build the current -commit in the `netcdf4-python` submodule of the repository. If it is set to -another value then it will be specifying a commit to build. - -You can therefore build any arbitrary commit by specificying the commit hash -or branch name or tag name in this line of the `.travis.yml` file. - -### Uploading the built wheels to pypi - -Be careful, http://wheels.scipy.org points to a container on a distributed -content delivery network. It can take up to 15 minutes for the new wheel file -to get updated into the container at http://wheels.scipy.org. - -When the wheels are updated, you can of course just download them to your -machine manually, and then upload them manually to pypi, or by using -[twine][twine]. You can also use a script for doing this, housed at : -https://github.com/MacPython/terryfy/blob/master/wheel-uploader - -You'll need [twine][twine] and [beautiful soup 4][bs4]. - -You will typically have a directory on your machine where you store wheels, -called a `wheelhouse`. The typical call for `wheel-uploader` would then -be something like: - -``` -wheel-uploader -v -w ~/wheelhouse netCDF4 1.1.8 -``` - -where: - -* `-v` means give verbose messages; -* `-w ~/wheelhouse` means download the wheels from https://wheels.scipy.org to - the directory `~/wheelhouse`; -* `netCDF4` is the root name of the wheel(s) to download / upload; -* `1.1.8` is the version to download / upload. - -So, in this case, `wheel-uploader` will download all wheels starting with -`netCDF4-1.1.8-` from http://wheels.scipy.org to `~/wheelhouse`, then upload -them to pypi. - -Of course, you will need permissions to upload to pypi, for this to work. - -[twine]: https://pypi.python.org/pypi/twine -[bs4]: https://pypi.python.org/pypi/beautifulsoup4 From 2aeb78b5416e23f305331f98fffa46f07976a64a Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Tue, 13 Aug 2024 16:04:16 +0200 Subject: [PATCH 1271/1504] fix minor typos --- Changelog | 14 +++++++------- README.md | 2 +- docs/index.html | 8 ++++---- examples/reading_netCDF.ipynb | 2 +- examples/writing_netCDF.ipynb | 2 +- include/membuf.pyx | 2 +- include/netCDF4.pxi | 4 ++-- setup.cfg | 2 +- setup.py | 2 +- src/netCDF4/_netCDF4.pyx | 8 ++++---- test/test_alignment.py | 2 +- 11 files changed, 24 insertions(+), 24 deletions(-) diff --git a/Changelog b/Changelog index f1e82e2b3..4015f67a1 100644 --- a/Changelog +++ b/Changelog @@ -22,7 +22,7 @@ version 1.6.5 (tag v1.6.5rel) =============================== - * fix for issue #1271 (mask ignored if bool MA assinged to uint8 var) + * fix for issue #1271 (mask ignored if bool MA assigned to uint8 var) * include information on specific object when reporting errors from netcdf-c * python 3.12 wheels added, support for python 3.7 removed. @@ -341,7 +341,7 @@ * Fix for auto scaling and masking when _Unsigned attribute set (create view as unsigned type after scaling and masking). Issue #671. * Always mask values outside valid_min, valid_max (not just when - missing_value attribue present). Issue #672. + missing_value attribute present). Issue #672. * Fix setup.py so pip install doesn't fail if cython not installed. setuptools >= 18.0 now required for installation (Issue #666). @@ -415,7 +415,7 @@ reading, a vlen string array attribute is returned as a list of strings. To write, use var.setncattr_string("name", ["two", "strings"]).) * Fix for issue #596 - julian day calculations wrong for negative years, - caused incorrect rountrip num2date(date2num(date)) roundtrip for dates with year + caused incorrect roundtrip num2date(date2num(date)) roundtrip for dates with year < 0. * Make sure negative years work in utime.num2date (issue #596). * raise NotImplementedError when trying to pickle Dataset, Variable, @@ -958,7 +958,7 @@ lib after the 4.2 release). Controlled by kwarg 'diskless' to netCDF4.Dataset (default False). diskless=True when creating a file results in a file that exists only in memory, closing the file - makes the data disapper, except if persist=True keyword given in + makes the data disappear, except if persist=True keyword given in which case it is persisted to a disk file on close. diskless=True when opening a file creates an in-memory copy of the file for faster access. @@ -1196,7 +1196,7 @@ version 0.8.1 (svn revision 744) * Experimental variable-length (vlen) data type support added. - * changes to accomodate compound types in netcdf-4.1-beta snapshots. + * changes to accommodate compound types in netcdf-4.1-beta snapshots. Compound types now work correctly for snapshots >= 20090603. * Added __len__ method and 'size' property to Variable class. @@ -1207,7 +1207,7 @@ version 0.8.1 (svn revision 744) * Fixed bug occurring when indexing with a numpy array of length 1. - * Fixed bug that occured when -1 was used as a variable index. + * Fixed bug that occurred when -1 was used as a variable index. * enabled 'shared access' mode for NETCDF3 formatted files (mode='ws', 'r+s' or 'as'). Writes in shared mode are unbuffered, which can @@ -1376,7 +1376,7 @@ version 0.7.3 (svn revision 501) to work as slice indices. * (netCDF4_classic only) try to make sure file is not left in 'define mode' - when execption is raised. + when exception is raised. * if slicing a variable results in a array with shape (1,), just return a scalar (except for compound types). diff --git a/README.md b/README.md index 59cf74311..8fa99985b 100644 --- a/README.md +++ b/README.md @@ -15,7 +15,7 @@ For details on the latest updates, see the [Changelog](https://github.com/Unidat 06/13/2024: Version [1.7.0](https://pypi.python.org/pypi/netCDF4/1.7.0) released. Add support for complex numbers via `auto_complex` keyword to `Dataset` ([PR #1295](https://github.com/Unidata/netcdf4-python/pull/1295)) 10/20/2023: Version [1.6.5](https://pypi.python.org/pypi/netCDF4/1.6.5) released. -Fix for issue #1271 (mask ignored if bool MA assinged to uint8 var), +Fix for issue #1271 (mask ignored if bool MA assigned to uint8 var), support for python 3.12 (removal of python 3.7 support), more informative error messages. diff --git a/docs/index.html b/docs/index.html index f120d187c..29e5a7c3c 100644 --- a/docs/index.html +++ b/docs/index.html @@ -289,7 +289,7 @@

      Dimensions in a netCDF file

      <class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144

      Dimension names can be changed using the -Datatset.renameDimension method of a Dataset or +Dataset.renameDimension method of a Dataset or Group instance.

      Variables in a netCDF file

      netCDF variables behave much like python multidimensional array objects @@ -901,7 +901,7 @@

      Parallel IO

      The optional comm keyword may be used to specify a particular MPI communicator (MPI_COMM_WORLD is used by default). Each process (or rank) -can now write to the file indepedently. +can now write to the file independently. In this example the process rank is written to a different variable index on each task

      >>> d = nc.createDimension('dim',4)
@@ -1164,7 +1164,7 @@ 
      Functions
      
 Will be converted to a array of strings, where each string has a fixed
 length of b.shape[-1] characters.
      
 
      optional kwarg encoding can be used to specify character encoding (default
-utf-8). If encoding is 'none' or 'bytes', a numpy.string_ btye array is
+utf-8). If encoding is 'none' or 'bytes', a numpy.string_ byte array is
 returned.
      
 
      returns a numpy string array with datatype 'UN' (or 'SN') and shape
 b.shape[:-1] where where N=b.shape[-1].
      
@@ -2884,7 +2884,7 @@ 
      Methods
      
 The value of _Encoding
 is the unicode encoding that is used to decode the bytes into strings.
      
 
      When numpy string data is written to a variable it is converted back to
-indiviual bytes, with the number of bytes in each string equalling the
+individual bytes, with the number of bytes in each string equalling the
 rightmost dimension of the variable.
      
 
      The default value of chartostring() is True
 (automatic conversions are performed).
      
diff --git a/examples/reading_netCDF.ipynb b/examples/reading_netCDF.ipynb
index 670b06340..95d33957d 100644
--- a/examples/reading_netCDF.ipynb
+++ b/examples/reading_netCDF.ipynb
@@ -479,7 +479,7 @@
     "### Finding the latitude and longitude indices of 50N, 140W\n",
     "\n",
     "- The `X` and `Y` dimensions don't look like longitudes and latitudes\n",
-    "- Use the auxilary coordinate variables named in the `coordinates` variable attribute, `Latitude` and `Longitude`"
+    "- Use the auxiliary coordinate variables named in the `coordinates` variable attribute, `Latitude` and `Longitude`"
    ]
   },
   {
diff --git a/examples/writing_netCDF.ipynb b/examples/writing_netCDF.ipynb
index 2e2fef5ef..61927929f 100644
--- a/examples/writing_netCDF.ipynb
+++ b/examples/writing_netCDF.ipynb
@@ -710,7 +710,7 @@
     "\n",
     "netCDF version 4 added support for organizing data in hierarchical groups.\n",
     "\n",
-    "- analagous to directories in a filesystem. \n",
+    "- analogous to directories in a filesystem. \n",
     "- Groups serve as containers for variables, dimensions and attributes, as well as other groups. \n",
     "- A `netCDF4.Dataset` creates a special group, called the 'root group', which is similar to the root directory in a unix filesystem. \n",
     "\n",
diff --git a/include/membuf.pyx b/include/membuf.pyx
index b964453e9..21a916db4 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -12,7 +12,7 @@ cdef memview_fromptr(void *memory, size_t size):
     buf.size = size # size of pointer in bytes
     return memoryview(buf)
 
-# private extension type that implements buffer protocal.
+# private extension type that implements buffer protocol.
 cdef class _MemBuf:
     cdef const void *memory
     cdef size_t size
diff --git a/include/netCDF4.pxi b/include/netCDF4.pxi
index f748bf82c..62b9be609 100644
--- a/include/netCDF4.pxi
+++ b/include/netCDF4.pxi
@@ -55,7 +55,7 @@ cdef extern from "netcdf.h":
         NC_NETCDF4 # Use netCDF-4/HDF5 format 
         NC_CLASSIC_MODEL # Enforce strict netcdf-3 rules. 
         # Use these 'mode' flags for both nc_create and nc_open.
-        NC_SHARE # Share updates, limit cacheing 
+        NC_SHARE # Share updates, limit caching 
         # The following flag currently is ignored, but use in
         # nc_open() or nc_create() may someday support use of advisory
         # locking to prevent multiple writers from clobbering a file 
@@ -111,7 +111,7 @@ cdef extern from "netcdf.h":
         NC_FILL
         NC_NOFILL
         # Starting with version 3.6, there are different format netCDF
-        # files. 4.0 instroduces the third one. These defines are only for
+        # files. 4.0 introduces the third one. These defines are only for
         # the nc_set_default_format function.
         NC_FORMAT_CLASSIC 
         NC_FORMAT_64BIT   
diff --git a/setup.cfg b/setup.cfg
index 55736d8b9..c0afd570c 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -32,7 +32,7 @@ use_ncconfig=True
 # use szip_libdir and szip_incdir.
 #szip_dir = /usr/local
 # if netcdf lib was build statically with HDF4 support,
-# uncomment and set to hdf4 lib (libmfhdf and libdf) nstall location.
+# uncomment and set to hdf4 lib (libmfhdf and libdf) install location.
 # If the libraries and include files are installed in separate locations,
 # use hdf4_libdir and hdf4_incdir.
 #hdf4_dir = /usr/local
diff --git a/setup.py b/setup.py
index c23eb0348..b17f09ef5 100644
--- a/setup.py
+++ b/setup.py
@@ -182,7 +182,7 @@ def extract_version(CYTHON_FNAME):
     HAS_NCCONFIG = False
 
 # make sure USE_NCCONFIG from environment takes
-# precendence over use_ncconfig from setup.cfg (issue #341).
+# precedence over use_ncconfig from setup.cfg (issue #341).
 if use_ncconfig and not USE_NCCONFIG:
     USE_NCCONFIG = use_ncconfig
 elif not USE_NCCONFIG:
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 6023406c9..b8573270d 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -285,7 +285,7 @@ and whether it is unlimited.
 ```
 
 `Dimension` names can be changed using the
-`Datatset.renameDimension` method of a `Dataset` or
+`Dataset.renameDimension` method of a `Dataset` or
 `Group` instance.
 
 ## Variables in a netCDF file
@@ -997,7 +997,7 @@ use the `parallel` keyword to enable parallel access.
 
 The optional `comm` keyword may be used to specify a particular
 MPI communicator (`MPI_COMM_WORLD` is used by default).  Each process (or rank)
-can now write to the file indepedently.  In this example the process rank is
+can now write to the file independently.  In this example the process rank is
 written to a different variable index on each task
 
 ```python
@@ -5625,7 +5625,7 @@ of the the rightmost dimension of the variable).  The value of `_Encoding`
 is the unicode encoding that is used to decode the bytes into strings.
 
 When numpy string data is written to a variable it is converted back to
-indiviual bytes, with the number of bytes in each string equalling the
+individual bytes, with the number of bytes in each string equalling the
 rightmost dimension of the variable.
 
 The default value of `chartostring` is `True`
@@ -6751,7 +6751,7 @@ Will be converted to a array of strings, where each string has a fixed
 length of `b.shape[-1]` characters.
 
 optional kwarg `encoding` can be used to specify character encoding (default
-`utf-8`). If `encoding` is 'none' or 'bytes', a `numpy.string_` btye array is
+`utf-8`). If `encoding` is 'none' or 'bytes', a `numpy.string_` byte array is
 returned.
 
 returns a numpy string array with datatype `'UN'` (or `'SN'`) and shape
diff --git a/test/test_alignment.py b/test/test_alignment.py
index 3f7333cd6..39c437535 100644
--- a/test/test_alignment.py
+++ b/test/test_alignment.py
@@ -134,7 +134,7 @@ def test_setting_alignment(self):
         for line in h5ls_results.split('\n'):
             if not line.startswith(' '):
                 data_variable = line.split(' ')[0]
-            # only process the data variables we care to inpsect
+            # only process the data variables we care to inspect
             if data_variable not in addresses:
                 continue
             line = line.strip()

From 50ed873b0dee6efc3e77a32f6d2058170918f8b0 Mon Sep 17 00:00:00 2001
From: Randall Pittman 
Date: Fri, 23 Aug 2024 10:41:33 -0700
Subject: [PATCH 1272/1504] Revert erroneous change in chunksizes type

---
 src/netCDF4/__init__.pyi | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi
index 7c138d5b4..1feb1871a 100644
--- a/src/netCDF4/__init__.pyi
+++ b/src/netCDF4/__init__.pyi
@@ -328,7 +328,7 @@ class Dataset:
         blosc_shuffle: Literal[0, 1, 2] = 1,
         fletcher32: bool = False,
         contiguous: bool = False,
-        chunksizes: int | None = None,
+        chunksizes: Sequence[int] | None = None,
         endian: EndianType = "native",
         least_significant_digit: int | None = None,
         significant_digits: int | None = None,
@@ -351,7 +351,7 @@ class Dataset:
         blosc_shuffle: Literal[0, 1, 2] = 1,
         fletcher32: bool = False,
         contiguous: bool = False,
-        chunksizes: int | None = None,
+        chunksizes: Sequence[int] | None = None,
         endian: EndianType = "native",
         least_significant_digit: int | None = None,
         significant_digits: int | None = None,
@@ -374,7 +374,7 @@ class Dataset:
         blosc_shuffle: Literal[0, 1, 2] = 1,
         fletcher32: bool = False,
         contiguous: bool = False,
-        chunksizes: int | None = None,
+        chunksizes: Sequence[int] | None = None,
         endian: EndianType = "native",
         least_significant_digit: int | None = None,
         significant_digits: int | None = None,
@@ -483,7 +483,7 @@ class Variable(Generic[VarT]):
         blosc_shuffle: Literal[0, 1, 2] = 1,
         fletcher32: bool = False,
         contiguous: bool = False,
-        chunksizes: int | None = None,
+        chunksizes: Sequence[int] | None = None,
         endian: EndianType = "native",
         least_significant_digit: int | None = None,
         significant_digits: int | None = None,
@@ -508,7 +508,7 @@ class Variable(Generic[VarT]):
         blosc_shuffle: Literal[0, 1, 2] = 1,
         fletcher32: bool = False,
         contiguous: bool = False,
-        chunksizes: int | None = None,
+        chunksizes: Sequence[int] | None = None,
         endian: EndianType = "native",
         least_significant_digit: int | None = None,
         significant_digits: int | None = None,
@@ -533,7 +533,7 @@ class Variable(Generic[VarT]):
         blosc_shuffle: Literal[0, 1, 2] = 1,
         fletcher32: bool = False,
         contiguous: bool = False,
-        chunksizes: int | None = None,
+        chunksizes: Sequence[int] | None = None,
         endian: EndianType = "native",
         least_significant_digit: int | None = None,
         significant_digits: int | None = None,
@@ -557,7 +557,7 @@ class Variable(Generic[VarT]):
         blosc_shuffle: Literal[0, 1, 2] = 1,
         fletcher32: bool = False,
         contiguous: bool = False,
-        chunksizes: int | None = None,
+        chunksizes: Sequence[int] | None = None,
         endian: EndianType = "native",
         least_significant_digit: int | None = None,
         significant_digits: int | None = None,

From 0cf4d6d2d1b167dc94cd629a975f7a56355d4fba Mon Sep 17 00:00:00 2001
From: Randall Pittman 
Date: Fri, 23 Aug 2024 11:10:45 -0700
Subject: [PATCH 1273/1504] Fix incorrect type of datatype for Real types

---
 src/netCDF4/__init__.pyi | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi
index 1feb1871a..59415c146 100644
--- a/src/netCDF4/__init__.pyi
+++ b/src/netCDF4/__init__.pyi
@@ -446,7 +446,7 @@ class Dimension:
 class _VarDatatypeProperty:
     # A faux descriptor definition of the property to allow overloads
     @overload
-    def __get__(self, instance: Variable[RealVarT], owner: Any) -> RealVarT: ...
+    def __get__(self, instance: Variable[RealVarT], owner: Any) -> np.dtype[RealVarT]: ...
     @overload
     def __get__(self, instance: Variable[ComplexVarT], owner: Any) -> CompoundType: ...
     @overload

From 55e88e76e42a92fb8a0d2fa00d5585f8f46ba3b7 Mon Sep 17 00:00:00 2001
From: Randall Pittman 
Date: Fri, 23 Aug 2024 11:13:21 -0700
Subject: [PATCH 1274/1504] Fixed inconsistent naming of DimensionsSpecifier >>
 DimensionsType

---
 src/netCDF4/__init__.pyi | 16 ++++++++--------
 1 file changed, 8 insertions(+), 8 deletions(-)

diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi
index 59415c146..0a1af0fa5 100644
--- a/src/netCDF4/__init__.pyi
+++ b/src/netCDF4/__init__.pyi
@@ -130,7 +130,7 @@ RealVarT = TypeVar("RealVarT", bound=NumPyRealType)
 ComplexVarT = TypeVar("ComplexVarT", bound=NumPyComplexType)
 NumericVarT = TypeVar("NumericVarT", bound=NumPyNumericType)
 
-DimensionsSpecifier: TypeAlias = Union[str, bytes, Dimension, Iterable[Union[str, bytes, Dimension]]]
+DimensionsType: TypeAlias = Union[str, bytes, Dimension, Iterable[Union[str, bytes, Dimension]]]
 CompressionType: TypeAlias = Literal[
     "zlib", "szip", "zstd", "bzip2", "blosc_lz", "blosc_lz4", "blosc_lz4hc", "blosc_zlib", "blosc_zstd"
 ]
@@ -318,7 +318,7 @@ class Dataset:
         self,
         varname: str,
         datatype: np.dtype[NumericVarT] | type[NumericVarT],
-        dimensions: DimensionsSpecifier = (),
+        dimensions: DimensionsType = (),
         compression: CompressionType | None = None,
         zlib: bool = False,
         complevel: CompressionLevel | None = 4,
@@ -341,7 +341,7 @@ class Dataset:
         self,
         varname: str,
         datatype: np.dtype[np.str_] | type[str | np.str_],
-        dimensions: DimensionsSpecifier = (),
+        dimensions: DimensionsType = (),
         compression: CompressionType | None = None,
         zlib: bool = False,
         complevel: CompressionLevel | None = 4,
@@ -364,7 +364,7 @@ class Dataset:
         self,
         varname: str,
         datatype: DatatypeSpecifier,
-        dimensions: DimensionsSpecifier = (),
+        dimensions: DimensionsType = (),
         compression: CompressionType | None = None,
         zlib: bool = False,
         complevel: CompressionLevel | None = 4,
@@ -473,7 +473,7 @@ class Variable(Generic[VarT]):
         grp: Dataset,
         name: str,
         datatype: np.dtype[NumericVarT] | type[NumericVarT],
-        dimensions: DimensionsSpecifier = (),
+        dimensions: DimensionsType = (),
         compression: CompressionType | None = None,
         zlib: bool = False,
         complevel: CompressionLevel | None = 4,
@@ -498,7 +498,7 @@ class Variable(Generic[VarT]):
         grp: Dataset,
         name: str,
         datatype: np.dtype[np.str_] | type[str | np.str_],
-        dimensions: DimensionsSpecifier = (),
+        dimensions: DimensionsType = (),
         compression: CompressionType | None = None,
         zlib: bool = False,
         complevel: CompressionLevel | None = 4,
@@ -523,7 +523,7 @@ class Variable(Generic[VarT]):
         grp: Dataset,
         name: str,
         datatype: DatatypeSpecifier,
-        dimensions: DimensionsSpecifier = (),
+        dimensions: DimensionsType = (),
         compression: CompressionType | None = None,
         zlib: bool = False,
         complevel: CompressionLevel | None = 4,
@@ -547,7 +547,7 @@ class Variable(Generic[VarT]):
         grp: Dataset,
         name: str,
         datatype: DatatypeSpecifier,
-        dimensions: DimensionsSpecifier = (),
+        dimensions: DimensionsType = (),
         compression: CompressionType | None = None,
         zlib: bool = False,
         complevel: CompressionLevel | None = 4,

From 00d3c61d42ac9627ff0cff9af8373ad1e073686a Mon Sep 17 00:00:00 2001
From: Randall Pittman 
Date: Fri, 23 Aug 2024 11:34:49 -0700
Subject: [PATCH 1275/1504] Also rename DatatypeSpecifier >> DatatypeType

---
 src/netCDF4/__init__.pyi | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi
index 0a1af0fa5..d808b2a6e 100644
--- a/src/netCDF4/__init__.pyi
+++ b/src/netCDF4/__init__.pyi
@@ -117,7 +117,7 @@ NetCDFUDTClass: TypeAlias = CompoundType | VLType | EnumType
 # Possible argument types for the datatype argument used in Variable creation. At this time, it is not possible to allow unknown
 # strings arguments in the datatype field but exclude and string literals that are not one of `TypeLiteral`, so really
 # `TypeLiteral` is made irrelevant, except for anyone who looks at this file.
-DatatypeSpecifier: TypeAlias = (
+DatatypeType: TypeAlias = (
     TypeLiteral
     | str
     | np.dtype[NumPyNumericType | np.str_]
@@ -363,7 +363,7 @@ class Dataset:
     def createVariable(
         self,
         varname: str,
-        datatype: DatatypeSpecifier,
+        datatype: DatatypeType,
         dimensions: DimensionsType = (),
         compression: CompressionType | None = None,
         zlib: bool = False,
@@ -522,7 +522,7 @@ class Variable(Generic[VarT]):
         cls,
         grp: Dataset,
         name: str,
-        datatype: DatatypeSpecifier,
+        datatype: DatatypeType,
         dimensions: DimensionsType = (),
         compression: CompressionType | None = None,
         zlib: bool = False,
@@ -546,7 +546,7 @@ class Variable(Generic[VarT]):
         self,
         grp: Dataset,
         name: str,
-        datatype: DatatypeSpecifier,
+        datatype: DatatypeType,
         dimensions: DimensionsType = (),
         compression: CompressionType | None = None,
         zlib: bool = False,

From 29fd359648cd1536fcfa1d3841a82daac44cf452 Mon Sep 17 00:00:00 2001
From: Randall Pittman 
Date: Fri, 23 Aug 2024 14:13:35 -0700
Subject: [PATCH 1276/1504] Don't need the type_guards module

---
 examples/bench.py              |   9 ++-
 examples/bench_compress.py     |  11 +---
 examples/bench_compress4.py    |   9 ++-
 examples/bench_diskless.py     |  13 ++--
 examples/type_guards.py        | 105 ---------------------------------
 src/netCDF4/__init__.pyi       |   4 +-
 test/test_compression.py       |  17 +++---
 test/test_compression_blosc.py |  12 ++--
 test/test_compression_bzip2.py |   9 ++-
 test/test_compression_quant.py |  10 +++-
 test/test_compression_zstd.py  |   9 ++-
 test/test_endian.py            |  14 ++---
 test/test_stringarr.py         |   4 +-
 test/test_types.py             |  20 +++++--
 test/type_guards.py            | 105 ---------------------------------
 15 files changed, 82 insertions(+), 269 deletions(-)
 delete mode 100644 examples/type_guards.py
 delete mode 100644 test/type_guards.py

diff --git a/examples/bench.py b/examples/bench.py
index 1d18ed8e1..08f95d48f 100644
--- a/examples/bench.py
+++ b/examples/bench.py
@@ -1,10 +1,14 @@
 # benchmark reads and writes, with and without compression.
 # tests all four supported file formats.
+from typing import TYPE_CHECKING, Any
 from numpy.random.mtrand import uniform
 import netCDF4
 from timeit import Timer
 import os, sys
-import type_guards
+if TYPE_CHECKING:
+    from netCDF4 import Format as NCFormat
+else:
+    NCFormat = Any
 
 # create an n1dim by n2dim by n3dim random array.
 n1dim = 30
@@ -15,8 +19,7 @@
 sys.stdout.write('reading and writing a %s by %s by %s by %s random array ..\n'%(n1dim,n2dim,n3dim,n4dim))
 array = uniform(size=(n1dim,n2dim,n3dim,n4dim))
 
-def write_netcdf(filename,zlib=False,least_significant_digit=None,format='NETCDF4'):
-    assert type_guards.valid_format(format)
+def write_netcdf(filename,zlib=False,least_significant_digit=None,format: NCFormat='NETCDF4'):
     file = netCDF4.Dataset(filename,'w',format=format)
     file.createDimension('n1', n1dim)
     file.createDimension('n2', n2dim)
diff --git a/examples/bench_compress.py b/examples/bench_compress.py
index be8915c53..f094a6ffa 100644
--- a/examples/bench_compress.py
+++ b/examples/bench_compress.py
@@ -1,12 +1,11 @@
 # benchmark reads and writes, with and without compression.
 # tests all four supported file formats.
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Any
 from numpy.random.mtrand import uniform
 import netCDF4
 import netCDF4.utils
 from timeit import Timer
 import os, sys
-from typing_extensions import TypeGuard
 if TYPE_CHECKING:
     from netCDF4 import CompressionLevel
 else:
@@ -22,18 +21,12 @@
 sys.stdout.write('(average of %s trials)\n' % ntrials)
 array = netCDF4.utils._quantize(uniform(size=(n1dim,n2dim,n3dim,n4dim)),4)
 
-def valid_complevel(complevel) -> TypeGuard[CompressionLevel]:
-    """Check for a valid `complevel` argument for creating a Variable"""
-    return isinstance(complevel, int) and 0 <= complevel <= 9
-
-def write_netcdf(filename,zlib=False,shuffle=False,complevel=6):
+def write_netcdf(filename,zlib=False,shuffle=False,complevel: CompressionLevel = 6):
     file = netCDF4.Dataset(filename,'w',format='NETCDF4')
     file.createDimension('n1', n1dim)
     file.createDimension('n2', n2dim)
     file.createDimension('n3', n3dim)
     file.createDimension('n4', n4dim)
-    if not (valid_complevel(complevel) or complevel is None):
-        raise ValueError("Invalid compression level")
     foo = file.createVariable('data',\
                               'f8',('n1','n2','n3','n4'),zlib=zlib,shuffle=shuffle,complevel=complevel)
     foo[:] = array
diff --git a/examples/bench_compress4.py b/examples/bench_compress4.py
index 05b9ade80..d8f643935 100644
--- a/examples/bench_compress4.py
+++ b/examples/bench_compress4.py
@@ -1,10 +1,10 @@
 # benchmark reads and writes, with and without compression.
 # tests all four supported file formats.
+from typing import Literal
 from numpy.random.mtrand import uniform
 import netCDF4
 from timeit import Timer
 import os, sys
-import type_guards
 
 # use real data.
 URL="http://www.esrl.noaa.gov/psd/thredds/dodsC/Datasets/ncep.reanalysis/pressure/hgt.1990.nc"
@@ -20,12 +20,15 @@
 array = nc.variables['hgt'][0:n1dim,5,:,:]
 
 
-def write_netcdf(filename,nsd,quantize_mode='BitGroom'):
+def write_netcdf(
+        filename,
+        nsd,
+        quantize_mode: Literal["BitGroom", "BitRound", "GranularBitRound"] = "BitGroom"
+    ):
     file = netCDF4.Dataset(filename,'w',format='NETCDF4')
     file.createDimension('n1', None)
     file.createDimension('n3', n3dim)
     file.createDimension('n4', n4dim)
-    assert type_guards.valid_quantize_mode(quantize_mode)
     foo = file.createVariable('data',\
                               'f4',('n1','n3','n4'),\
                               zlib=True,shuffle=True,\
diff --git a/examples/bench_diskless.py b/examples/bench_diskless.py
index ae92e037b..076f446b4 100644
--- a/examples/bench_diskless.py
+++ b/examples/bench_diskless.py
@@ -1,10 +1,14 @@
 # benchmark reads and writes, with and without compression.
 # tests all four supported file formats.
+from typing import TYPE_CHECKING, Any, Literal
 from numpy.random.mtrand import uniform
 import netCDF4
 from timeit import Timer
 import os, sys
-import type_guards
+if TYPE_CHECKING:
+    from netCDF4 import Format as NCFormat
+else:
+    NCFormat = Any
 
 # create an n1dim by n2dim by n3dim random array.
 n1dim = 30
@@ -15,8 +19,7 @@
 sys.stdout.write('reading and writing a %s by %s by %s by %s random array ..\n'%(n1dim,n2dim,n3dim,n4dim))
 array = uniform(size=(n1dim,n2dim,n3dim,n4dim))
 
-def write_netcdf(filename,zlib=False,least_significant_digit=None,format='NETCDF4',closeit=False):
-    assert type_guards.valid_format(format)
+def write_netcdf(filename, zlib=False, least_significant_digit=None, format: NCFormat='NETCDF4',closeit=False):
     file = netCDF4.Dataset(filename,'w',format=format,diskless=True,persist=True)
     file.createDimension('n1', n1dim)
     file.createDimension('n2', n2dim)
@@ -44,13 +47,13 @@ def read_netcdf(ncfile):
     sys.stdout.write('writing took %s seconds\n' %\
             repr(sum(t.repeat(ntrials,1))/ntrials))
     # test reading.
-    ncfile = write_netcdf('test1.nc',format=format)
+    ncfile = write_netcdf('test1.nc',format=format)  # type: ignore
     t = Timer("read_netcdf(ncfile)","from __main__ import read_netcdf,ncfile")
     sys.stdout.write('reading took %s seconds\n' %
             repr(sum(t.repeat(ntrials,1))/ntrials))
 
 # test diskless=True in nc_open
-format='NETCDF3_CLASSIC'
+format: Literal["NETCDF3_CLASSIC"] = 'NETCDF3_CLASSIC'  # mypy should know this but it needs help...
 trials=50
 sys.stdout.write('test caching of file in memory on open for %s\n' % format)
 sys.stdout.write('testing file format %s ...\n' % format)
diff --git a/examples/type_guards.py b/examples/type_guards.py
deleted file mode 100644
index 2baabda68..000000000
--- a/examples/type_guards.py
+++ /dev/null
@@ -1,105 +0,0 @@
-"""type_guards.py - Helpers for static and runtime type-checking of initialization arguments
-for Dataset and Variable"""
-
-from typing import TYPE_CHECKING, Any, Literal
-
-from typing_extensions import TypeGuard
-
-if TYPE_CHECKING:
-    # in stubs only
-    from netCDF4 import (
-        AccessMode,
-        CalendarType,
-        CompressionLevel,
-        CompressionType,
-        EndianType,
-        QuantizeMode,
-    )
-    from netCDF4 import Format as NCFormat
-else:
-    AccessMode = Any
-    CalendarType = Any
-    CompressionLevel = Any
-    DiskFormat = Any
-    EndianType = Any
-    CompressionType = Any
-    NCFormat = Any
-    QuantizeMode = Any
-
-
-def valid_access_mode(mode) -> TypeGuard[AccessMode]:
-    """Check for a valid `mode` argument for opening a Dataset"""
-    return mode in {"r", "w", "r+", "a", "x", "rs", "ws", "r+s", "as"}
-
-
-def valid_calendar(calendar) -> TypeGuard[CalendarType]:
-    """Check for a valid `calendar` argument for cftime functions"""
-    return calendar in {
-        "standard",
-        "gregorian",
-        "proleptic_gregorian",
-        "noleap",
-        "365_day",
-        "360_day",
-        "julian",
-        "all_leap",
-        "366_day",
-    }
-
-
-def valid_complevel(complevel) -> TypeGuard[CompressionLevel]:
-    """Check for a valid `complevel` argument for creating a Variable"""
-    return isinstance(complevel, int) and 0 <= complevel <= 9
-
-
-def valid_compression(compression) -> TypeGuard[CompressionType]:
-    """Check for a valid `compression` argument for creating a Variable"""
-    return compression in {
-        "zlib",
-        "szip",
-        "zstd",
-        "bzip2",
-        "blosc_lz",
-        "blosc_lz4",
-        "blosc_lz4hc",
-        "blosc_zlib",
-        "blosc_zstd",
-    }
-
-
-def valid_format(format) -> TypeGuard[NCFormat]:
-    """Check for a valid `format` argument for opening a Dataset"""
-    return format in {
-        "NETCDF4",
-        "NETCDF4_CLASSIC",
-        "NETCDF3_CLASSIC",
-        "NETCDF3_64BIT_OFFSET",
-        "NETCDF3_64BIT_DATA",
-    }
-
-
-def valid_endian(endian) -> TypeGuard[EndianType]:
-    """Check for a valid `endian` argument for creating a Variable"""
-    return endian in {"native", "big", "little"}
-
-
-def valid_bloscshuffle(blosc_shuffle) -> TypeGuard[Literal[0, 1, 2]]:
-    """Check for a valid `blosc_shuffle` argument for creating a Variable"""
-    return blosc_shuffle in {0, 1, 2}
-
-
-def valid_quantize_mode(quantize_mode) -> TypeGuard[QuantizeMode]:
-    """Check for a valid `quantize_mode` argument for creating a Variable"""
-    return quantize_mode in {"BitGroom", "BitRound", "GranularBitRound"}
-
-
-def valid_szip_coding(szip_coding) -> TypeGuard[Literal["nn", "ec"]]:
-    """Check for a valid `szip_coding` argument for creating a Variable"""
-    return szip_coding in {"nn", "ec"}
-
-
-def valid_szip_pixels_per_block(
-    szip_pixels_per_block,
-) -> TypeGuard[Literal[4, 8, 16, 32]]:
-    """Check for a valid `szip_pixels_per_block` argument for creating a Variable"""
-    return szip_pixels_per_block in {4, 8, 16, 32}
diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi
index d808b2a6e..a7db85fc4 100644
--- a/src/netCDF4/__init__.pyi
+++ b/src/netCDF4/__init__.pyi
@@ -453,7 +453,7 @@ class _VarDatatypeProperty:
     def __get__(self, instance: Variable[str], owner: Any) -> VLType: ...
     @overload
     def __get__(
-        self, instance: Variable[Any], owner: Any
+        self, instance: Variable, owner: Any
     ) -> Any: ...  # actual return type np.dtype | CompoundType | VLType | EnumType
 
 class _VarDtypeProperty:
@@ -463,7 +463,7 @@ class _VarDtypeProperty:
     @overload
     def __get__(self, instance: Variable[str], owner: Any) -> type[str]: ...
     @overload
-    def __get__(self, instance: Variable[Any], owner: Any) -> Any: ...  # actual return type np.dtype | Type[str]
+    def __get__(self, instance: Variable, owner: Any) -> Any: ...  # actual return type np.dtype | Type[str]
 
 class Variable(Generic[VarT]):
     # Overloads of __new__ are provided for some cases where the Variable's type may be statically inferred from the datatype arg
diff --git a/test/test_compression.py b/test/test_compression.py
index 1d4b59076..6c9351af6 100644
--- a/test/test_compression.py
+++ b/test/test_compression.py
@@ -1,9 +1,13 @@
+from typing import TYPE_CHECKING, Any
 from numpy.random.mtrand import uniform
 from netCDF4 import Dataset
 from netCDF4.utils import _quantize
 from numpy.testing import assert_almost_equal
 import os, tempfile, unittest
-import type_guards
+if TYPE_CHECKING:
+    from netCDF4 import CompressionLevel
+else:
+    CompressionLevel = Any
 
 ndim = 100000
 ndim2 = 100
@@ -15,8 +19,7 @@
 lsd = 3
 
 def write_netcdf(filename,zlib,least_significant_digit,data,dtype='f8',shuffle=False,contiguous=False,\
-                 chunksizes=None,complevel=6,fletcher32=False):
-    assert type_guards.valid_complevel(complevel) or complevel is None
+                 chunksizes=None, complevel: CompressionLevel = 6, fletcher32=False):
     file = Dataset(filename,'w')
     file.createDimension('n', ndim)
     foo = file.createVariable('data',\
@@ -32,9 +35,8 @@ def write_netcdf(filename,zlib,least_significant_digit,data,dtype='f8',shuffle=F
         #compression=''
         #compression=0
         #compression='gzip' # should fail
-    assert type_guards.valid_compression(compression) or compression is None
-    foo2 = file.createVariable('data2',\
-            dtype,('n'),compression=compression,least_significant_digit=least_significant_digit,\
+    foo2 = file.createVariable('data2',
+            dtype,('n'),compression=compression,least_significant_digit=least_significant_digit,  # type: ignore  # mypy doesn't like compression
             shuffle=shuffle,contiguous=contiguous,complevel=complevel,fletcher32=fletcher32,chunksizes=chunksizes)
     foo[:] = data
     foo2[:] = data
@@ -45,11 +47,10 @@ def write_netcdf(filename,zlib,least_significant_digit,data,dtype='f8',shuffle=F
     file.close()
 
 def write_netcdf2(filename,zlib,least_significant_digit,data,dtype='f8',shuffle=False,contiguous=False,\
-                 chunksizes=None,complevel=6,fletcher32=False):
+                 chunksizes=None, complevel: CompressionLevel = 6, fletcher32=False):
     file = Dataset(filename,'w')
     file.createDimension('n', ndim)
     file.createDimension('n2', ndim2)
-    assert type_guards.valid_complevel(complevel) or complevel is None
     foo = file.createVariable('data2',\
             dtype,('n','n2'),zlib=zlib,least_significant_digit=least_significant_digit,\
             shuffle=shuffle,contiguous=contiguous,complevel=complevel,fletcher32=fletcher32,chunksizes=chunksizes)
diff --git a/test/test_compression_blosc.py b/test/test_compression_blosc.py
index c532fef32..fda01e216 100644
--- a/test/test_compression_blosc.py
+++ b/test/test_compression_blosc.py
@@ -1,10 +1,13 @@
+from typing import TYPE_CHECKING, Any, Literal
 from numpy.random.mtrand import uniform
 from netCDF4 import Dataset
-import type_guards
 from numpy.testing import assert_almost_equal
 import os, tempfile, unittest, sys
 from filter_availability import no_plugins, has_blosc_filter
-import type_guards
+if TYPE_CHECKING:
+    from netCDF4 import CompressionLevel
+else:
+    CompressionLevel = Any
 
 
 ndim = 100000
@@ -13,8 +16,7 @@
 filename = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
 datarr = uniform(size=(ndim,))
 
-def write_netcdf(filename,dtype='f8',blosc_shuffle=1,complevel=6):
-    assert (type_guards.valid_complevel(complevel) or complevel is None) and type_guards.valid_bloscshuffle(blosc_shuffle)
+def write_netcdf(filename, dtype='f8', blosc_shuffle: Literal[0, 1, 2] = 1, complevel: CompressionLevel = 6):
     nc = Dataset(filename,'w')
     nc.createDimension('n', ndim)
     foo = nc.createVariable('data',\
@@ -41,7 +43,7 @@ def write_netcdf(filename,dtype='f8',blosc_shuffle=1,complevel=6):
 class CompressionTestCase(unittest.TestCase):
     def setUp(self):
         self.filename = filename
-        write_netcdf(self.filename,complevel=iblosc_complevel,blosc_shuffle=iblosc_shuffle)
+        write_netcdf(self.filename,complevel=iblosc_complevel,blosc_shuffle=iblosc_shuffle)  # type: ignore
 
     def tearDown(self):
         # Remove the temporary files
diff --git a/test/test_compression_bzip2.py b/test/test_compression_bzip2.py
index ec32ba248..15ef8eaec 100644
--- a/test/test_compression_bzip2.py
+++ b/test/test_compression_bzip2.py
@@ -1,17 +1,20 @@
+from typing import TYPE_CHECKING, Any
 from numpy.random.mtrand import uniform
 from netCDF4 import Dataset
 from numpy.testing import assert_almost_equal
 import os, tempfile, unittest, sys
 from filter_availability import no_plugins, has_bzip2_filter
-import type_guards
+if TYPE_CHECKING:
+    from netCDF4 import CompressionLevel
+else:
+    CompressionLevel = Any
 
 ndim = 100000
 filename1 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
 filename2 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
 array = uniform(size=(ndim,))
 
-def write_netcdf(filename,dtype='f8',complevel=6):
-    assert type_guards.valid_complevel(complevel) or complevel is None
+def write_netcdf(filename,dtype='f8',complevel: CompressionLevel = 6):
     nc = Dataset(filename,'w')
     nc.createDimension('n', ndim)
     foo = nc.createVariable('data',\
diff --git a/test/test_compression_quant.py b/test/test_compression_quant.py
index 24267615a..b56739624 100644
--- a/test/test_compression_quant.py
+++ b/test/test_compression_quant.py
@@ -1,9 +1,14 @@
+from typing import TYPE_CHECKING, Any
 from numpy.random.mtrand import uniform
 from netCDF4 import Dataset, __has_quantization_support__
 from numpy.testing import assert_almost_equal
 import numpy as np
 import os, tempfile, unittest
-import type_guards
+if TYPE_CHECKING:
+    from netCDF4 import CompressionLevel, QuantizeMode
+else:
+    CompressionLevel = Any
+    QuantizeMode = Any
 
 ndim = 100000
 nfiles = 7
@@ -14,10 +19,9 @@
 complevel = 6
 
 def write_netcdf(filename,zlib,significant_digits,data,dtype='f8',shuffle=False,\
-                 complevel=6,quantize_mode="BitGroom"):
+                 complevel: CompressionLevel = 6, quantize_mode: QuantizeMode = "BitGroom"):
     file = Dataset(filename,'w')
     file.createDimension('n', ndim)
-    assert (type_guards.valid_complevel(complevel) or complevel is None) and type_guards.valid_quantize_mode(quantize_mode)
     foo = file.createVariable('data',\
             dtype,('n'),zlib=zlib,significant_digits=significant_digits,\
             shuffle=shuffle,complevel=complevel,quantize_mode=quantize_mode)
diff --git a/test/test_compression_zstd.py b/test/test_compression_zstd.py
index 123397f12..3557d5d0c 100644
--- a/test/test_compression_zstd.py
+++ b/test/test_compression_zstd.py
@@ -1,19 +1,22 @@
+from typing import TYPE_CHECKING, Any
 from numpy.random.mtrand import uniform
 from netCDF4 import Dataset
 from numpy.testing import assert_almost_equal
 import os, tempfile, unittest, sys
 from filter_availability import no_plugins, has_zstd_filter
-import type_guards
+if TYPE_CHECKING:
+    from netCDF4 import CompressionLevel
+else:
+    CompressionLevel = Any
 
 ndim = 100000
 filename1 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
 filename2 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
 array = uniform(size=(ndim,))
 
-def write_netcdf(filename,dtype='f8',complevel=6):
+def write_netcdf(filename,dtype='f8',complevel: CompressionLevel = 6):
     nc = Dataset(filename,'w')
     nc.createDimension('n', ndim)
-    assert type_guards.valid_complevel(complevel) or complevel is None
     foo = nc.createVariable('data',\
             dtype,('n'),compression='zstd',complevel=complevel)
     foo[:] = array
diff --git a/test/test_endian.py b/test/test_endian.py
index 1a8f58681..716d1a958 100644
--- a/test/test_endian.py
+++ b/test/test_endian.py
@@ -2,7 +2,6 @@
 import numpy as np
 import unittest, os, tempfile
 from numpy.testing import assert_array_equal, assert_array_almost_equal
-import type_guards
 
 data = np.arange(12,dtype='f4').reshape(3,4)
 FILE_NAME = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
@@ -74,14 +73,13 @@ def issue310(file):
         endian='little'
     else:
         raise ValueError('cannot determine native endianness')
-    assert type_guards.valid_endian(endian)  # mypy fails to narrow endian on its own
-    var_big_endian = nc.createVariable(\
-            'obs_big_endian', '>f8', ('obs', ),\
-            endian=endian,fill_value=fval)
+    var_big_endian = nc.createVariable(
+        'obs_big_endian', '>f8', ('obs', ), endian=endian, fill_value=fval,  # type: ignore  # mypy is bad at narrowing endian
+    )
     # use default _FillValue
-    var_big_endian2 = nc.createVariable(\
-            'obs_big_endian2', '>f8', ('obs', ),\
-            endian=endian)
+    var_big_endian2 = nc.createVariable(
+        'obs_big_endian2', '>f8', ('obs', ), endian=endian,   # type: ignore  # mypy is bad at narrowing endian
+    )
     # NOTE: missing_value  be written in same byte order
     # as variable, or masked array won't be masked correctly
     # when data is read in.
diff --git a/test/test_stringarr.py b/test/test_stringarr.py
index f3e140c0a..9d4fcd909 100644
--- a/test/test_stringarr.py
+++ b/test/test_stringarr.py
@@ -3,7 +3,6 @@
 import unittest
 import os
 from numpy.testing import assert_array_equal, assert_array_almost_equal
-import type_guards
 
 def generateString(length, alphabet=string.ascii_letters + string.digits + string.punctuation):
     return(''.join([random.choice(alphabet) for i in range(length)]))
@@ -25,8 +24,7 @@ class StringArrayTestCase(unittest.TestCase):
 
     def setUp(self):
         self.file = FILE_NAME
-        assert type_guards.valid_format(FILE_FORMAT)
-        nc = Dataset(FILE_NAME,'w',format=FILE_FORMAT)
+        nc = Dataset(FILE_NAME,'w',format=FILE_FORMAT)  # type: ignore #  FILE_FORMAT
         nc.createDimension('n1',None)
         nc.createDimension('n2',n2)
         nc.createDimension('nchar',nchar)
diff --git a/test/test_types.py b/test/test_types.py
index 3cc7bbc3b..3c5054bbd 100644
--- a/test/test_types.py
+++ b/test/test_types.py
@@ -1,4 +1,5 @@
 import sys
+from typing import TYPE_CHECKING, Any
 import unittest
 import os
 import tempfile
@@ -6,7 +7,10 @@
 from numpy.testing import assert_array_equal, assert_array_almost_equal
 from numpy.random.mtrand import uniform
 import netCDF4
-import type_guards
+if TYPE_CHECKING:
+    from netCDF4 import CompressionLevel
+else:
+    CompressionLevel = Any
 
 # test primitive data types.
 
@@ -15,7 +19,7 @@
 n1dim = 5
 n2dim = 10
 ranarr = 100.*uniform(size=(n1dim,n2dim))
-zlib=False;complevel=0;shuffle=False;least_significant_digit=None
+zlib=False; complevel=0; shuffle=False; least_significant_digit=None
 datatypes = ['f8','f4','i1','i2','i4','i8','u1','u2','u4','u8','S1']
 FillValue = 1.0
 issue273_data = np.ma.array(['z']*10,dtype='S1',\
@@ -29,8 +33,16 @@ def setUp(self):
         f.createDimension('n1', None)
         f.createDimension('n2', n2dim)
         for typ in datatypes:
-            assert type_guards.valid_complevel(complevel) or complevel is None
-            foo = f.createVariable('data_'+typ, typ, ('n1','n2',),zlib=zlib,complevel=complevel,shuffle=shuffle,least_significant_digit=least_significant_digit,fill_value=FillValue)
+            foo = f.createVariable(
+                f"data_{typ}",
+                typ,
+                ('n1','n2',),
+                zlib=zlib,
+                complevel=complevel,  # type: ignore  # type checkers bad at narrowing
+                shuffle=shuffle,
+                least_significant_digit=least_significant_digit,
+                fill_value=FillValue,
+            )
             #foo._FillValue = FillValue
             # test writing of _FillValue attribute for diff types
             # (should be cast to type of variable silently)
diff --git a/test/type_guards.py b/test/type_guards.py
deleted file mode 100644
index 2baabda68..000000000
--- a/test/type_guards.py
+++ /dev/null
@@ -1,105 +0,0 @@
-"""type_guards.py - Helpers for static and runtime type-checking of initialization arguments
-for Dataset and Variable"""
-
-from typing import TYPE_CHECKING, Any, Literal
-
-from typing_extensions import TypeGuard
-
-if TYPE_CHECKING:
-    # in stubs only
-    from netCDF4 import (
-        AccessMode,
-        CalendarType,
-        CompressionLevel,
-        CompressionType,
-        EndianType,
-        QuantizeMode,
-    )
-    from netCDF4 import Format as NCFormat
-else:
-    AccessMode = Any
-    CalendarType = Any
-    CompressionLevel = Any
-    DiskFormat = Any
-    EndianType = Any
-    CompressionType = Any
-    NCFormat = Any
-    QuantizeMode = Any
-
-
-def valid_access_mode(mode) -> TypeGuard[AccessMode]:
-    """Check for a valid `mode` argument for opening a Dataset"""
-    return mode in {"r", "w", "r+", "a", "x", "rs", "ws", "r+s", "as"}
-
-
-def valid_calendar(calendar) -> TypeGuard[CalendarType]:
-    """Check for a valid `calendar` argument for cftime functions"""
-    return calendar in {
-        "standard",
-        "gregorian",
-        "proleptic_gregorian",
-        "noleap",
-        "365_day",
-        "360_day",
-        "julian",
-        "all_leap",
-        "366_day",
-    }
-
-
-def valid_complevel(complevel) -> TypeGuard[CompressionLevel]:
-    """Check for a valid `complevel` argument for creating a Variable"""
-    return isinstance(complevel, int) and 0 <= complevel <= 9
-
-
-def valid_compression(compression) -> TypeGuard[CompressionType]:
-    """Check for a valid `compression` argument for creating a Variable"""
-    return compression in {
-        "zlib",
-        "szip",
-        "zstd",
-        "bzip2",
-        "blosc_lz",
-        "blosc_lz4",
-        "blosc_lz4hc",
-        "blosc_zlib",
-        "blosc_zstd",
-    }
-
-
-def valid_format(format) -> TypeGuard[NCFormat]:
-    """Check for a valid `format` argument for opening a Dataset"""
-    return format in {
-        "NETCDF4",
-        "NETCDF4_CLASSIC",
-        "NETCDF3_CLASSIC",
-        "NETCDF3_64BIT_OFFSET",
-        "NETCDF3_64BIT_DATA",
-    }
-
-
-def valid_endian(endian) -> TypeGuard[EndianType]:
-    """Check for a valid `endian` argument for creating a Variable"""
-    return endian in {"native", "big", "little"}
-
-
-def valid_bloscshuffle(blosc_shuffle) -> TypeGuard[Literal[0, 1, 2]]:
-    """Check for a valid `blosc_shuffle` argument for creating a Variable"""
-    return blosc_shuffle in {0, 1, 2}
-
-
-def valid_quantize_mode(quantize_mode) -> TypeGuard[QuantizeMode]:
-    """Check for a valid `quantize_mode` argument for creating a Variable"""
-    return quantize_mode in {"BitGroom", "BitRound", "GranularBitRound"}
-
-
-def valid_szip_coding(szip_coding) -> TypeGuard[Literal["nn", "ec"]]:
-    """Check for a valid `szip_coding` argument for creating a Variable"""
-    return szip_coding in {"nn", "ec"}
-
-
-def valid_szip_pixels_per_block(
-    szip_pixels_per_block,
-) -> TypeGuard[Literal[4, 8, 16, 32]]:
-    """Check for a valid `szip_pixels_per_block` argument for creating a Variable"""
-    return szip_pixels_per_block in {4, 8, 16, 32}

From ac8c6fa81048e309e690e0d11c119ac296b479d2 Mon Sep 17 00:00:00 2001
From: Randall Pittman 
Date: Fri, 23 Aug 2024 14:25:28 -0700
Subject: [PATCH 1277/1504] Don't bother with TypeGuard

---
 examples/mpi_example.py | 27 ++++++++-------------------
 1 file changed, 8 insertions(+), 19 deletions(-)

diff --git a/examples/mpi_example.py b/examples/mpi_example.py
index 3f8cb0f87..93ca57bc7 100644
--- a/examples/mpi_example.py
+++ b/examples/mpi_example.py
@@ -1,34 +1,23 @@
 # to run: mpirun -np 4 python mpi_example.py
 import sys
-from typing import TYPE_CHECKING
 from mpi4py import MPI
 import numpy as np
 from netCDF4 import Dataset
-from typing_extensions import TypeGuard
-if TYPE_CHECKING:
-    from netCDF4 import Format as NCFormat
-else:
-    NCFormat = object
-
 
-def is_nc_format(fmt: str) -> TypeGuard[NCFormat]:
-    return fmt in {
-        'NETCDF4',
-        'NETCDF4_CLASSIC',
-        'NETCDF3_CLASSIC',
-        'NETCDF3_64BIT_OFFSET',
-        'NETCDF3_64BIT_DATA'
-    }
 
 nc_format = 'NETCDF4_CLASSIC' if len(sys.argv) < 2 else sys.argv[1]
-if not is_nc_format(nc_format):
-        raise ValueError("Invalid file format")
 
 rank = MPI.COMM_WORLD.rank  # The process ID (integer 0-3 for 4-process run)
 if rank == 0:
     print('Creating file with format {}'.format(nc_format))
-nc = Dataset('parallel_test.nc', 'w', parallel=True, comm=MPI.COMM_WORLD,
-    info=MPI.Info(), format=nc_format)
+nc = Dataset(
+    "parallel_test.nc",
+    "w",
+    parallel=True,
+    comm=MPI.COMM_WORLD,
+    info=MPI.Info(),
+    format=nc_format,   # type: ignore  # we'll assume it's OK
+)
 # below should work also - MPI_COMM_WORLD and MPI_INFO_NULL will be used.
 #nc = Dataset('parallel_test.nc', 'w', parallel=True)
 d = nc.createDimension('dim',4)

From ba2e99a99e6499b65ec82eebc3c367fbc0bc4eda Mon Sep 17 00:00:00 2001
From: Randall Pittman 
Date: Thu, 5 Sep 2024 09:27:35 -0700
Subject: [PATCH 1278/1504] Removed GetSetItemKey and replaced with typing.Any

---
 src/netCDF4/__init__.pyi | 46 ++++------------------------------------
 1 file changed, 4 insertions(+), 42 deletions(-)

diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi
index a7db85fc4..443762f25 100644
--- a/src/netCDF4/__init__.pyi
+++ b/src/netCDF4/__init__.pyi
@@ -79,13 +79,6 @@ __all__ = [
 ]
 __pdoc__ = {"utils": False}
 
-if sys.version_info >= (3, 10):
-    from types import EllipsisType
-
-    ellipsis = EllipsisType
-elif not TYPE_CHECKING:
-    ellipsis = type(Ellipsis)  # keeps ruff happy until ruff uses typeshed
-
 # string type specifiers
 # fmt: off
 RealTypeLiteral: TypeAlias = Literal[
@@ -148,37 +141,6 @@ BoolInt: TypeAlias = Literal[0, 1]
 DateTimeArray: TypeAlias = npt.NDArray[np.object_]
 """numpy array of datetime.datetime or cftime.datetime"""
 
-# - Allow singular float or str keys, but not lists (or sequences) of them
-# - `list` and `ndarray` are specifically listed for the 1-D case as Sequence is too general -- it includes
-#   tuples which are rather for multi-dimensional indexing.
-GetSetItemKey: TypeAlias = (
-    int
-    | float
-    | np.number
-    | str
-    | slice
-    | ellipsis
-    | list[int]
-    | list[bool]
-    | npt.NDArray[np.integer]
-    | npt.NDArray[np.bool_]
-    | tuple[
-        int
-        | float
-        | np.number
-        | str
-        | slice
-        | ellipsis
-        | Sequence[int]
-        | Sequence[np.integer]
-        | Sequence[bool]
-        | Sequence[np.bool_]
-        | npt.NDArray[np.integer]
-        | npt.NDArray[np.bool_],
-        ...,
-    ]
-)
-
 class BloscInfo(TypedDict):
     compressor: Literal["blosc_lz", "blosc_lz4", "blosc_lz4hc", "blosc_zlib", "blosc_zstd"]
     shuffle: Literal[0, 1, 2]
@@ -618,8 +580,8 @@ class Variable(Generic[VarT]):
     def __delattr__(self, name: str) -> None: ...
     def __setattr__(self, name: str, value: Any) -> None: ...
     def __getattr__(self, name: str) -> Any: ...
-    def __getitem__(self, elem: GetSetItemKey) -> Any: ...
-    def __setitem__(self, elem: GetSetItemKey, data: npt.ArrayLike) -> None: ...
+    def __getitem__(self, elem: Any) -> Any: ...
+    def __setitem__(self, elem: Any, data: npt.ArrayLike) -> None: ...
     def __array__(self) -> np.ndarray: ...
     def __len__(self) -> int: ...
     def __iter__(self) -> Iterator[Any]: ...  # faux method so mypy believes Variable is iterable
@@ -700,7 +662,7 @@ class _Variable:
     def set_auto_scale(self, val: bool) -> None: ...
     def set_always_mask(self, val: bool) -> None: ...
     def __getattr__(self, name: str) -> Any: ...
-    def __getitem__(self, elem: GetSetItemKey) -> Any: ...
+    def __getitem__(self, elem: Any) -> Any: ...
     def __len__(self) -> int: ...
 
 class MFTime(_Variable):
@@ -708,7 +670,7 @@ class MFTime(_Variable):
     units: str | None
 
     def __init__(self, time: Variable, units: str | None = None, calendar: CalendarType | str | None = None): ...
-    def __getitem__(self, elem: GetSetItemKey) -> np.ndarray: ...
+    def __getitem__(self, elem: Any) -> np.ndarray: ...
 
 @overload
 def stringtoarr(

From b2e1c0b15b2fe388a80c8b1242fc3b2e0d4f2eed Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Tue, 17 Sep 2024 04:02:42 +0000
Subject: [PATCH 1279/1504] Bump pypa/cibuildwheel in the github-actions group
 across 1 directory

Bumps the github-actions group with 1 update in the / directory: [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel).


Updates `pypa/cibuildwheel` from 2.20.0 to 2.21.1
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md)
- [Commits](https://github.com/pypa/cibuildwheel/compare/v2.20.0...v2.21.1)

---
updated-dependencies:
- dependency-name: pypa/cibuildwheel
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/cibuildwheel.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 558c65685..5284f428e 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -92,7 +92,7 @@ jobs:
         echo "Setting CIBW_SKIP=$CIBW_SKIP"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
-      uses: pypa/cibuildwheel@v2.20.0
+      uses: pypa/cibuildwheel@v2.21.1
       env:
         CIBW_SKIP: ${{ env.CIBW_SKIP }}
         CIBW_ARCHS: ${{ matrix.arch }}

From 324dacca7faa427d99072f83d6635286396ced25 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 22 Sep 2024 09:40:49 -0600
Subject: [PATCH 1280/1504] fix for compiling with netcdf-c 4.7.4 (issue #1363)

---
 .github/workflows/build_old.yml      | 2 +-
 external/nc_complex/src/nc_complex.c | 5 +++++
 2 files changed, 6 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml
index eeaa61c3b..2c7233819 100644
--- a/.github/workflows/build_old.yml
+++ b/.github/workflows/build_old.yml
@@ -6,7 +6,7 @@ jobs:
     runs-on: ubuntu-latest
     env:
       PNETCDF_VERSION: 1.12.1
-      NETCDF_VERSION: 4.8.1
+      NETCDF_VERSION: 4.7.4
       NETCDF_DIR: ${{ github.workspace }}/..
       NETCDF_EXTRA_CONFIG: --enable-pnetcdf
       CC: mpicc.mpich
diff --git a/external/nc_complex/src/nc_complex.c b/external/nc_complex/src/nc_complex.c
index 68decb02c..4063d4fdc 100644
--- a/external/nc_complex/src/nc_complex.c
+++ b/external/nc_complex/src/nc_complex.c
@@ -9,6 +9,11 @@
 
 #include "nc_complex_version.h"
 
+// to enable compilation with older versions of netcdf-c
+#ifndef NC_FORMATX_NCZARR
+#define NC_FORMATX_NCZARR    (10)
+#endif
+
 // NOLINTBEGIN(bugprone-assignment-in-if-condition)
 #define CHECK(func)           \
     do {                      \

From 72a45b7e80ed0d68f16671756e8609e06add9fdf Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 22 Sep 2024 09:50:45 -0600
Subject: [PATCH 1281/1504] use sudo for make install

---
 .github/workflows/build_latest.yml | 4 ++--
 .github/workflows/build_master.yml | 2 +-
 .github/workflows/build_old.yml    | 4 ++--
 3 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index 079774710..bd797bd1e 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -35,7 +35,7 @@ jobs:
         pushd pnetcdf-${PNETCDF_VERSION}
         ./configure --prefix $NETCDF_DIR --enable-shared --disable-fortran --disable-cxx
         make -j 2
-        make install
+        sudo make install
         popd
         echo "Download and build netCDF version ${NETCDF_VERSION}"
         wget https://downloads.unidata.ucar.edu/netcdf-c/${NETCDF_VERSION}/netcdf-c-${NETCDF_VERSION}.tar.gz
@@ -46,7 +46,7 @@ jobs:
         export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
         ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 $NETCDF_EXTRA_CONFIG
         make -j 2
-        make install
+        sudo make install
         popd
 
 #   - name: The job has failed
diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index f8f841636..48f901648 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -35,7 +35,7 @@ jobs:
         autoreconf -i
         ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 
         make -j 2
-        make install
+        sudo make install
         popd
 
 #   - name: The job has failed
diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml
index 2c7233819..18a9ad187 100644
--- a/.github/workflows/build_old.yml
+++ b/.github/workflows/build_old.yml
@@ -35,7 +35,7 @@ jobs:
         pushd pnetcdf-${PNETCDF_VERSION}
         ./configure --prefix $NETCDF_DIR --enable-shared --disable-fortran --disable-cxx
         make -j 2
-        make install
+        sudo make install
         popd
         echo "Download and build netCDF version ${NETCDF_VERSION}"
         wget https://downloads.unidata.ucar.edu/netcdf-c/${NETCDF_VERSION}/netcdf-c-${NETCDF_VERSION}.tar.gz
@@ -46,7 +46,7 @@ jobs:
         export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
         ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 $NETCDF_EXTRA_CONFIG
         make -j 2
-        make install
+        sudo make install
         popd
 
 #   - name: The job has failed

From a0ff68a050759c834045e15543275fa7540a269b Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 22 Sep 2024 10:03:40 -0600
Subject: [PATCH 1282/1504] get netcdf-c 4.7.4 from a mirror

---
 .github/workflows/build_old.yml | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml
index 18a9ad187..484a627e2 100644
--- a/.github/workflows/build_old.yml
+++ b/.github/workflows/build_old.yml
@@ -38,7 +38,8 @@ jobs:
         sudo make install
         popd
         echo "Download and build netCDF version ${NETCDF_VERSION}"
-        wget https://downloads.unidata.ucar.edu/netcdf-c/${NETCDF_VERSION}/netcdf-c-${NETCDF_VERSION}.tar.gz
+        #wget https://downloads.unidata.ucar.edu/netcdf-c/${NETCDF_VERSION}/netcdf-c-${NETCDF_VERSION}.tar.gz
+        wget https://www.gfd-dennou.org/arch/netcdf/unidata-mirror/netcdf-c-${NETCDF_VERSION}.tar.gz
         tar -xzf netcdf-c-${NETCDF_VERSION}.tar.gz
         pushd netcdf-c-${NETCDF_VERSION}
         export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include"

From b33dad5fee079334d0c20a35fc548ace60c59887 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 22 Sep 2024 10:18:49 -0600
Subject: [PATCH 1283/1504] specify openmpi

---
 .github/workflows/miniconda.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index a79c8e572..ac20f1ec8 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -69,7 +69,7 @@ jobs:
         init-shell: bash
         create-args: >-
           python=${{ matrix.python-version }}
-          numpy cython pip pytest mpi4py hdf5=*=mpi* libnetcdf=*=mpi* cftime zlib certifi
+          numpy cython pip pytest openmpi mpi4py hdf5=*=mpi* libnetcdf=*=mpi* cftime zlib certifi
           --channel conda-forge
 
     - name: Install netcdf4-python with mpi

From 91d6e98d7b9df516aaf75a41c4233347a40b213a Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 22 Sep 2024 16:56:30 -0600
Subject: [PATCH 1284/1504] update cibuildwheel

---
 .github/workflows/cibuildwheel.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 558c65685..5284f428e 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -92,7 +92,7 @@ jobs:
         echo "Setting CIBW_SKIP=$CIBW_SKIP"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
-      uses: pypa/cibuildwheel@v2.20.0
+      uses: pypa/cibuildwheel@v2.21.1
       env:
         CIBW_SKIP: ${{ env.CIBW_SKIP }}
         CIBW_ARCHS: ${{ matrix.arch }}

From 6e11ed9598ebe66eb672250d8676c9e7e64614ff Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Fri, 4 Oct 2024 03:25:23 +0000
Subject: [PATCH 1285/1504] Bump the github-actions group across 1 directory
 with 2 updates

Bumps the github-actions group with 2 updates in the / directory: [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel) and [mamba-org/setup-micromamba](https://github.com/mamba-org/setup-micromamba).


Updates `pypa/cibuildwheel` from 2.21.1 to 2.21.2
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md)
- [Commits](https://github.com/pypa/cibuildwheel/compare/v2.21.1...v2.21.2)

Updates `mamba-org/setup-micromamba` from 1 to 2
- [Release notes](https://github.com/mamba-org/setup-micromamba/releases)
- [Commits](https://github.com/mamba-org/setup-micromamba/compare/v1...v2)

---
updated-dependencies:
- dependency-name: pypa/cibuildwheel
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: github-actions
- dependency-name: mamba-org/setup-micromamba
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/cibuildwheel.yml | 4 ++--
 .github/workflows/miniconda.yml    | 4 ++--
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 5284f428e..acd0fb855 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -92,7 +92,7 @@ jobs:
         echo "Setting CIBW_SKIP=$CIBW_SKIP"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
-      uses: pypa/cibuildwheel@v2.21.1
+      uses: pypa/cibuildwheel@v2.21.2
       env:
         CIBW_SKIP: ${{ env.CIBW_SKIP }}
         CIBW_ARCHS: ${{ matrix.arch }}
@@ -135,7 +135,7 @@ jobs:
           python-version: 3.x
 
       - name: Setup Micromamba Python ${{ matrix.python-version }}
-        uses: mamba-org/setup-micromamba@v1
+        uses: mamba-org/setup-micromamba@v2
         with:
           environment-name: build
           init-shell: bash
diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index ac20f1ec8..893e60cf5 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -29,7 +29,7 @@ jobs:
         submodules: true
 
     - name: Setup Micromamba
-      uses: mamba-org/setup-micromamba@v1
+      uses: mamba-org/setup-micromamba@v2
       with:
         environment-name: TEST
         init-shell: bash
@@ -63,7 +63,7 @@ jobs:
         submodules: true
 
     - name: Setup Micromamba
-      uses: mamba-org/setup-micromamba@v1
+      uses: mamba-org/setup-micromamba@v2
       with:
         environment-name: TEST
         init-shell: bash

From 2e8118600b56ab63646e8533473903719c8bd42c Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Thu, 10 Oct 2024 03:27:17 +0000
Subject: [PATCH 1286/1504] Bump pypa/cibuildwheel from 2.21.2 to 2.21.3 in the
 github-actions group

Bumps the github-actions group with 1 update: [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel).


Updates `pypa/cibuildwheel` from 2.21.2 to 2.21.3
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md)
- [Commits](https://github.com/pypa/cibuildwheel/compare/v2.21.2...v2.21.3)

---
updated-dependencies:
- dependency-name: pypa/cibuildwheel
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/cibuildwheel.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index acd0fb855..c7f025676 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -92,7 +92,7 @@ jobs:
         echo "Setting CIBW_SKIP=$CIBW_SKIP"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
-      uses: pypa/cibuildwheel@v2.21.2
+      uses: pypa/cibuildwheel@v2.21.3
       env:
         CIBW_SKIP: ${{ env.CIBW_SKIP }}
         CIBW_ARCHS: ${{ matrix.arch }}

From 2728bcf679958076600680f7355f06f8457b2f97 Mon Sep 17 00:00:00 2001
From: Filipe Fernandes 
Date: Thu, 10 Oct 2024 10:43:19 +0200
Subject: [PATCH 1287/1504] remove bad OPeNDAP URL

---
 .github/workflows/cibuildwheel.yml | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index acd0fb855..15a87d6ef 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -92,7 +92,7 @@ jobs:
         echo "Setting CIBW_SKIP=$CIBW_SKIP"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
-      uses: pypa/cibuildwheel@v2.21.2
+      uses: pypa/cibuildwheel@v2.21.3
       env:
         CIBW_SKIP: ${{ env.CIBW_SKIP }}
         CIBW_ARCHS: ${{ matrix.arch }}
@@ -107,8 +107,6 @@ jobs:
         CIBW_TEST_COMMAND: >
           python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')"
           && pytest -s -rxs -v {project}/test
-          && URL="https://icdc.cen.uni-hamburg.de/thredds/dodsC/ftpthredds/hamtide/m2.hamtide11a.nc"
-          && python -c "from netCDF4 import Dataset; nc=Dataset(\"${URL}\"); print(nc)"
 
     - uses: actions/upload-artifact@v4
       with:

From 459dd04357c85c76691e42178a89ad75bfde561a Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 20 Oct 2024 13:59:03 -0600
Subject: [PATCH 1288/1504] add method to return variable _FillValue
 (get_fill_value)

---
 src/netCDF4/_netCDF4.pyx | 21 +++++++++++++++++++++
 1 file changed, 21 insertions(+)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 8679706ba..d7e3af767 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4638,6 +4638,27 @@ behavior is similar to Fortran or Matlab, but different than numpy.
 return the group that this `Variable` is a member of."""
         return self._grp
 
+    def get_fill_value(self):
+        """
+**`get_fill_value(self)`**
+
+return the `_FillValue` associated with this `Variable` (None if data is not
+pre-filled)."""
+        cdef int ierr, no_fill
+        with nogil:
+            ierr = nc_inq_var_fill(self._grpid,self._varid,&no_fill,NULL)
+        _ensure_nc_success(ierr)
+        if no_fill == 1:
+            return None
+        else:
+            try:
+                fillval = self._FillValue
+            except AttributeError:
+                if self._isprimitive:
+                    return default_fillvals[self.dtype.str[1:]]
+                else:
+                    return None
+
     def ncattrs(self):
         """
 **`ncattrs(self)`**

From 61121e525c3ec45ec8a5665ed5e3d731446f56cf Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 20 Oct 2024 14:03:59 -0600
Subject: [PATCH 1289/1504] add comments

---
 src/netCDF4/_netCDF4.pyx | 7 +++++--
 1 file changed, 5 insertions(+), 2 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index d7e3af767..d155600c9 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4648,15 +4648,18 @@ pre-filled)."""
         with nogil:
             ierr = nc_inq_var_fill(self._grpid,self._varid,&no_fill,NULL)
         _ensure_nc_success(ierr)
-        if no_fill == 1:
+        if no_fill == 1: # no filling for this variable
             return None
         else:
             try:
                 fillval = self._FillValue
             except AttributeError:
+                # _FillValue attribute not set, use default _FillValue
+                # for primite datatypes.
                 if self._isprimitive:
-                    return default_fillvals[self.dtype.str[1:]]
+                    return np.asarray(default_fillvals[self.dtype.str[1:]],self.dtype)
                 else:
+                    # no default filling for non-primitive datatypes.
                     return None
 
     def ncattrs(self):

From 821c74086608c03935ffe99f7099baa820cbc703 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 20 Oct 2024 14:09:50 -0600
Subject: [PATCH 1290/1504] update

---
 src/netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index d155600c9..df196d2a0 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4657,7 +4657,7 @@ pre-filled)."""
                 # _FillValue attribute not set, use default _FillValue
                 # for primite datatypes.
                 if self._isprimitive:
-                    return np.asarray(default_fillvals[self.dtype.str[1:]],self.dtype)
+                    return np.array(default_fillvals[self.dtype.str[1:]],self.dtype)
                 else:
                     # no default filling for non-primitive datatypes.
                     return None

From 1668b9900867d107fcc42cba4e7dabbddfc9c483 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 20 Oct 2024 14:27:26 -0600
Subject: [PATCH 1291/1504] update

---
 src/netCDF4/_netCDF4.pyx | 13 +++++++++----
 1 file changed, 9 insertions(+), 4 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index df196d2a0..7e3c397a4 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4654,12 +4654,17 @@ pre-filled)."""
             try:
                 fillval = self._FillValue
             except AttributeError:
-                # _FillValue attribute not set, use default _FillValue
-                # for primite datatypes.
-                if self._isprimitive:
+                # _FillValue attribute not set, see if we can retrieve _FillValue.
+                # for primitive data types.
+                if self._isprimitive
                     return np.array(default_fillvals[self.dtype.str[1:]],self.dtype)
+                    #fillval = np.array(default_fillvals[self.dtype.str[1:]],self.dtype)
+                    #with nogil:
+                    #    ierr=nc_inq_var_fill(self._grpid,self._varid,&no_fill,fillval)
+                    #_ensure_nc_success(ierr)
+                    #return fillval
                 else:
-                    # no default filling for non-primitive datatypes.
+                    # no default filling for non-primitive data types.
                     return None
 
     def ncattrs(self):

From 365fbab2d582fcd0d88070539a98ade3d797aa2d Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Sun, 20 Oct 2024 14:32:01 -0600
Subject: [PATCH 1292/1504] update

---
 src/netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 7e3c397a4..babc6d242 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4660,7 +4660,7 @@ pre-filled)."""
                     return np.array(default_fillvals[self.dtype.str[1:]],self.dtype)
                     #fillval = np.array(default_fillvals[self.dtype.str[1:]],self.dtype)
                     #with nogil:
-                    #    ierr=nc_inq_var_fill(self._grpid,self._varid,&no_fill,fillval)
+                    #    ierr=nc_inq_var_fill(self._grpid,self._varid,&no_fill,PyArray_DATA(fillval))
                     #_ensure_nc_success(ierr)
                     #return fillval
                 else:

From 33da47badf0a10b135d586cd28cde9dfbd58f99b Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 21 Oct 2024 09:57:50 -0600
Subject: [PATCH 1293/1504] use C API to get default fill values

---
 src/netCDF4/_netCDF4.pyx | 13 ++++++-------
 1 file changed, 6 insertions(+), 7 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index babc6d242..5f5728775 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4656,13 +4656,12 @@ pre-filled)."""
             except AttributeError:
                 # _FillValue attribute not set, see if we can retrieve _FillValue.
                 # for primitive data types.
-                if self._isprimitive
-                    return np.array(default_fillvals[self.dtype.str[1:]],self.dtype)
-                    #fillval = np.array(default_fillvals[self.dtype.str[1:]],self.dtype)
-                    #with nogil:
-                    #    ierr=nc_inq_var_fill(self._grpid,self._varid,&no_fill,PyArray_DATA(fillval))
-                    #_ensure_nc_success(ierr)
-                    #return fillval
+                if self._isprimitive:
+                    #return numpy.array(default_fillvals[self.dtype.str[1:]],self.dtype)
+                    fillval = numpy.array(default_fillvals[self.dtype.str[1:]],self.dtype)
+                    ierr=nc_inq_var_fill(self._grpid,self._varid,&no_fill,PyArray_DATA(fillval))
+                    _ensure_nc_success(ierr)
+                    return fillval
                 else:
                     # no default filling for non-primitive data types.
                     return None

From d2099dcb92f8bdddc57bcfb231f0260c637ca031 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 21 Oct 2024 10:01:38 -0600
Subject: [PATCH 1294/1504] update

---
 src/netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 5f5728775..56cc62207 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4658,7 +4658,7 @@ pre-filled)."""
                 # for primitive data types.
                 if self._isprimitive:
                     #return numpy.array(default_fillvals[self.dtype.str[1:]],self.dtype)
-                    fillval = numpy.array(default_fillvals[self.dtype.str[1:]],self.dtype)
+                    fillval = numpy.empty((),self.dtype)
                     ierr=nc_inq_var_fill(self._grpid,self._varid,&no_fill,PyArray_DATA(fillval))
                     _ensure_nc_success(ierr)
                     return fillval

From 0deeb124e583f28f90859cab3db0eb36aa2acf57 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 21 Oct 2024 10:14:50 -0600
Subject: [PATCH 1295/1504] update

---
 src/netCDF4/_netCDF4.pyx | 1 +
 1 file changed, 1 insertion(+)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 56cc62207..2f53efdc1 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4653,6 +4653,7 @@ pre-filled)."""
         else:
             try:
                 fillval = self._FillValue
+                return fillval
             except AttributeError:
                 # _FillValue attribute not set, see if we can retrieve _FillValue.
                 # for primitive data types.

From 3d9b9d9323a03a87e68d6b32fbe21e480fa201a1 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 21 Oct 2024 10:26:28 -0600
Subject: [PATCH 1296/1504] add test case

---
 test/test_get_fill_value.py | 36 ++++++++++++++++++++++++++++++++++++
 1 file changed, 36 insertions(+)
 create mode 100644 test/test_get_fill_value.py

diff --git a/test/test_get_fill_value.py b/test/test_get_fill_value.py
new file mode 100644
index 000000000..0e588c0bc
--- /dev/null
+++ b/test/test_get_fill_value.py
@@ -0,0 +1,36 @@
+import unittest, os, tempfile
+import netCDF4
+from numpy.testing import assert_array_equal
+import numpy as np
+
+fill_val = np.array(9.9e31)
+
+class TestGetFillValue(unittest.TestCase):
+    def setUp(self):
+        self.testfile = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
+        f = netCDF4.Dataset(self.testfile, 'w')
+        dim = f.createDimension('x',10)
+        for dt in netCDF4.default_fillvals.keys():
+            if not dt.startswith('c'):
+                v = f.createVariable(dt+'_var',dt,dim)
+        v = f.createVariable('float_var',np.float64,dim,fill_value=fill_val)
+        f.close()
+        
+    def tearDown(self):
+        os.remove(self.testfile)
+
+    def runTest(self):
+        f = netCDF4.Dataset(self.testfile, "r")
+        # no _FillValue set, test that default fill value returned
+        for dt in netCDF4.default_fillvals.keys():
+            if not dt.startswith('c'):
+                fillval = np.array(netCDF4.default_fillvals[dt])
+                if dt == 'S1': fillval = fillval.astype(dt)
+                v = f[dt+'_var']
+                assert_array_equal(fillval, v.get_fill_value())
+        # _FillValue attribute is set.
+        v = f['float_var']
+        assert_array_equal(fill_val, v.get_fill_value())
+
+if __name__ == '__main__':
+    unittest.main()

From b4b6eee4162dbcdd664e5179c777adeafe1e4f28 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 21 Oct 2024 10:27:04 -0600
Subject: [PATCH 1297/1504] update

---
 test/test_get_fill_value.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/test/test_get_fill_value.py b/test/test_get_fill_value.py
index 0e588c0bc..79591b803 100644
--- a/test/test_get_fill_value.py
+++ b/test/test_get_fill_value.py
@@ -5,6 +5,8 @@
 
 fill_val = np.array(9.9e31)
 
+# test Variable.get_fill_value
+
 class TestGetFillValue(unittest.TestCase):
     def setUp(self):
         self.testfile = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name

From d16a91fd3f4aea30ad2194eae1e8f4ee9eda1aa7 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 21 Oct 2024 10:34:23 -0600
Subject: [PATCH 1298/1504] update docstring

---
 src/netCDF4/_netCDF4.pyx | 11 ++++++++---
 1 file changed, 8 insertions(+), 3 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 2f53efdc1..f3d0a2f91 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4039,7 +4039,11 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         value that the variable gets filled with before any data is written to it)
         is replaced with this value.  If fill_value is set to `False`, then
         the variable is not pre-filled. The default netCDF fill values can be found
-        in the dictionary `netCDF4.default_fillvals`.
+        in the dictionary `netCDF4.default_fillvals`. If not set, the netCDF default
+        `_FillValue` will be used but no `_FillValue` attribute will be created
+        (this is the default behavior of the netcdf-c library). `Variable.get_fill_value`
+        can be used to retrieve the fill value, even if the `_FillValue` attribute is
+        not set.
 
         **`chunk_cache`**: If specified, sets the chunk cache size for this variable.
         Persists as long as Dataset is open. Use `set_var_chunk_cache` to
@@ -4642,8 +4646,9 @@ return the group that this `Variable` is a member of."""
         """
 **`get_fill_value(self)`**
 
-return the `_FillValue` associated with this `Variable` (None if data is not
-pre-filled)."""
+return the fill value associated with this `Variable` (None if data is not
+pre-filled). Works even if default fill value was used, and `_FillValue` attribute
+does not exist."""
         cdef int ierr, no_fill
         with nogil:
             ierr = nc_inq_var_fill(self._grpid,self._varid,&no_fill,NULL)

From d740b0a98430d27ae510a437e60a1d1a809e96b9 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 21 Oct 2024 10:37:05 -0600
Subject: [PATCH 1299/1504] update

---
 src/netCDF4/_netCDF4.pyx | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index f3d0a2f91..5e083ea49 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4035,12 +4035,12 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         Ignored if `significant_digts` not specified. If 'BitRound' is used, then
         `significant_digits` is interpreted as binary (not decimal) digits.
 
-        **`fill_value`**:  If specified, the default netCDF `_FillValue` (the
+        **`fill_value`**:  If specified, the default netCDF fill value (the
         value that the variable gets filled with before any data is written to it)
-        is replaced with this value.  If fill_value is set to `False`, then
-        the variable is not pre-filled. The default netCDF fill values can be found
-        in the dictionary `netCDF4.default_fillvals`. If not set, the netCDF default
-        `_FillValue` will be used but no `_FillValue` attribute will be created
+        is replaced with this value, and the `_FillValue` attribute is set.
+        If fill_value is set to `False`, then the variable is not pre-filled.
+        The default netCDF fill values can be found in the dictionary `netCDF4.default_fillvals`.
+        If not set, the default fill value will be used but no `_FillValue` attribute will be created
         (this is the default behavior of the netcdf-c library). `Variable.get_fill_value`
         can be used to retrieve the fill value, even if the `_FillValue` attribute is
         not set.

From f50a70df84be4655d2e4d0a3e70a51ef584bf2cb Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 21 Oct 2024 12:41:45 -0600
Subject: [PATCH 1300/1504] close file

---
 test/test_get_fill_value.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/test/test_get_fill_value.py b/test/test_get_fill_value.py
index 79591b803..f325f4456 100644
--- a/test/test_get_fill_value.py
+++ b/test/test_get_fill_value.py
@@ -33,6 +33,7 @@ def runTest(self):
         # _FillValue attribute is set.
         v = f['float_var']
         assert_array_equal(fill_val, v.get_fill_value())
+        f.close()
 
 if __name__ == '__main__':
     unittest.main()

From b26da50a660505688ae2f702f6bfb2df11aa6801 Mon Sep 17 00:00:00 2001
From: Randall Pittman 
Date: Mon, 21 Oct 2024 12:02:40 -0700
Subject: [PATCH 1301/1504] Remove accidentally-commited nc files.

---
 examples/parallel_test.nc            | Bin 6176 -> 0 bytes
 examples/parallel_test_compressed.nc | Bin 10288 -> 0 bytes
 2 files changed, 0 insertions(+), 0 deletions(-)
 delete mode 100644 examples/parallel_test.nc
 delete mode 100644 examples/parallel_test_compressed.nc

diff --git a/examples/parallel_test.nc b/examples/parallel_test.nc
deleted file mode 100644
index ec95803e081f032b7314eaf74434c9916246e2bd..0000000000000000000000000000000000000000
GIT binary patch
literal 0
HcmV?d00001

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From 5d922e40f16109f7b1cd79b8563400b3e32ced86 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 21 Oct 2024 13:29:41 -0600
Subject: [PATCH 1302/1504] add get_fill_value to stub

---
 src/netCDF4/__init__.pyi | 1 +
 1 file changed, 1 insertion(+)

diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi
index 1a709dd35..68e18dcae 100644
--- a/src/netCDF4/__init__.pyi
+++ b/src/netCDF4/__init__.pyi
@@ -465,6 +465,7 @@ class Variable(Generic[T_Datatype]):
     def renameAttribute(self, oldname: str, newname: str) -> None: ...
     def assignValue(self, val: Any) -> None: ...
     def getValue(self) -> Any: ...
+    def get_fill_value(self) -> Any: ...
     def set_auto_chartostring(self, chartostring: bool) -> None: ...
     def use_nc_get_vars(self, use_nc_get_vars: bool) -> None: ...
     def set_auto_maskandscale(self, maskandscale: bool) -> None: ...

From 1f67c941b24a413834bee5f7ecee7c6a7597db6f Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 21 Oct 2024 13:33:37 -0600
Subject: [PATCH 1303/1504] update

---
 Changelog | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/Changelog b/Changelog
index 4015f67a1..4c635ce8f 100644
--- a/Changelog
+++ b/Changelog
@@ -2,6 +2,8 @@
 ===============================
  * add static type hints (PR #1302)
  * Expose nc_rc_set, nc_rc_get (via rc_set, rc_get module functions). (PR #1348)
+ * Add Variable.get_fill_value (issue #1374, PR #1375).
+ * Fix NETCDF3 endian error (issue #1373, PR #1355).
 
  version 1.7.1 (tag v1.7.1rel)
 ===============================

From aa9452a5f49b5098e349fcaed8975f2e1cb2b239 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 21 Oct 2024 14:00:56 -0600
Subject: [PATCH 1304/1504] add fill_value='default' option

---
 src/netCDF4/_netCDF4.pyx    | 13 ++++++++++---
 test/test_get_fill_value.py |  4 ++++
 2 files changed, 14 insertions(+), 3 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 5e083ea49..341151381 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4041,9 +4041,10 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         If fill_value is set to `False`, then the variable is not pre-filled.
         The default netCDF fill values can be found in the dictionary `netCDF4.default_fillvals`.
         If not set, the default fill value will be used but no `_FillValue` attribute will be created
-        (this is the default behavior of the netcdf-c library). `Variable.get_fill_value`
-        can be used to retrieve the fill value, even if the `_FillValue` attribute is
-        not set.
+        (this is the default behavior of the netcdf-c library). If you want to use the 
+        default fill value, but have the `_FillValue` attribute set, use
+        `fill_value='default'` (note - this only works for primitive data types). ``Variable.get_fill_value`
+        can be used to retrieve the fill value, even if the `_FillValue` attribute is not set.
 
         **`chunk_cache`**: If specified, sets the chunk cache size for this variable.
         Persists as long as Dataset is open. Use `set_var_chunk_cache` to
@@ -4407,6 +4408,12 @@ behavior is similar to Fortran or Matlab, but different than numpy.
                     if ierr != NC_NOERR:
                         if grp.data_model != 'NETCDF4': grp._enddef()
                         _ensure_nc_success(ierr, extra_msg=error_info)
+                elif fill_value == 'default':
+                    if self._isprimitive:
+                        fillval = numpy.array(default_fillvals[self.dtype.str[1:]])
+                        if not fillval.dtype.isnative: fillval.byteswap(True)
+                        _set_att(self._grp, self._varid, '_FillValue',\
+                                 fillval, xtype=xtype)
                 else:
                     if self._isprimitive or self._isenum or \
                        (self._isvlen and self.dtype == str):
diff --git a/test/test_get_fill_value.py b/test/test_get_fill_value.py
index f325f4456..257a3121e 100644
--- a/test/test_get_fill_value.py
+++ b/test/test_get_fill_value.py
@@ -16,6 +16,8 @@ def setUp(self):
             if not dt.startswith('c'):
                 v = f.createVariable(dt+'_var',dt,dim)
         v = f.createVariable('float_var',np.float64,dim,fill_value=fill_val)
+        # test fill_value='default' option (issue #1374)
+        v2 = f.createVariable('float_var2',np.float64,dim,fill_value='default')
         f.close()
         
     def tearDown(self):
@@ -33,6 +35,8 @@ def runTest(self):
         # _FillValue attribute is set.
         v = f['float_var']
         assert_array_equal(fill_val, v.get_fill_value())
+        v = f['float_var2']
+        assert_array_equal(np.array(netCDF4.default_fillvals['f8']), v._FillValue)
         f.close()
 
 if __name__ == '__main__':

From f3eba108e29402fee10c465e5a4727fc76336646 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 21 Oct 2024 14:06:32 -0600
Subject: [PATCH 1305/1504] update

---
 Changelog | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/Changelog b/Changelog
index 4c635ce8f..bc46e06ce 100644
--- a/Changelog
+++ b/Changelog
@@ -2,7 +2,8 @@
 ===============================
  * add static type hints (PR #1302)
  * Expose nc_rc_set, nc_rc_get (via rc_set, rc_get module functions). (PR #1348)
- * Add Variable.get_fill_value (issue #1374, PR #1375).
+ * Add Variable.get_fill_value and allow `fill_value='default'` to 
+   set `_FillValue` using default fill values.  (issue #1374, PR #1375).
  * Fix NETCDF3 endian error (issue #1373, PR #1355).
 
  version 1.7.1 (tag v1.7.1rel)

From 801e7b611f4c015552ab7681b840b359fe562846 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 21 Oct 2024 14:15:52 -0600
Subject: [PATCH 1306/1504] add warning if fill_value='default' used for non
 primitive data type

---
 src/netCDF4/_netCDF4.pyx | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 341151381..e6d20a7db 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4414,6 +4414,11 @@ behavior is similar to Fortran or Matlab, but different than numpy.
                         if not fillval.dtype.isnative: fillval.byteswap(True)
                         _set_att(self._grp, self._varid, '_FillValue',\
                                  fillval, xtype=xtype)
+                    else:
+                        msg = """
+WARNING: there is no default fill value for this data type, so fill_value='default'
+does not do anything."""
+                        warnings.warn(msg)
                 else:
                     if self._isprimitive or self._isenum or \
                        (self._isvlen and self.dtype == str):

From d81d4fad2fc33f927ee6616ba3dfc2e52a822ad4 Mon Sep 17 00:00:00 2001
From: Randall Pittman 
Date: Mon, 21 Oct 2024 15:32:28 -0700
Subject: [PATCH 1307/1504] Update stubtest-allowlist for changes in recent
 commits

---
 .github/stubtest-allowlist | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/.github/stubtest-allowlist b/.github/stubtest-allowlist
index 4f0e7a94d..0352fdcf7 100644
--- a/.github/stubtest-allowlist
+++ b/.github/stubtest-allowlist
@@ -10,20 +10,18 @@ netCDF4.NetCDFUDTClass
 netCDF4.AccessMode
 netCDF4.CompressionLevel
 netCDF4.CompressionType
-netCDF4.DatatypeSpecifier
-netCDF4.DimensionsSpecifier
+netCDF4.DatatypeType
+netCDF4.DimensionsType
 netCDF4.DiskFormat
 netCDF4.EndianType
 netCDF4.Format
 netCDF4.QuantizeMode
 netCDF4.CalendarType
-netCDF4.ellipsis
 netCDF4.DateTimeArray
 netCDF4.FiltersDict
 netCDF4.SzipInfo
 netCDF4.BloscInfo
 netCDF4.BoolInt
-netCDF4.GetSetItemKey
 netCDF4.VarT
 netCDF4.RealVarT
 netCDF4.ComplexVarT

From bff03a4791283076907f7515718cd3092b4ff5fe Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 21 Oct 2024 17:40:03 -0600
Subject: [PATCH 1308/1504] fix typos in docstrings

---
 src/netCDF4/_netCDF4.pyx | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index e6d20a7db..7c92f09bd 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -4043,7 +4043,7 @@ behavior is similar to Fortran or Matlab, but different than numpy.
         If not set, the default fill value will be used but no `_FillValue` attribute will be created
         (this is the default behavior of the netcdf-c library). If you want to use the 
         default fill value, but have the `_FillValue` attribute set, use
-        `fill_value='default'` (note - this only works for primitive data types). ``Variable.get_fill_value`
+        `fill_value='default'` (note - this only works for primitive data types). `Variable.get_fill_value`
         can be used to retrieve the fill value, even if the `_FillValue` attribute is not set.
 
         **`chunk_cache`**: If specified, sets the chunk cache size for this variable.
@@ -4658,7 +4658,7 @@ return the group that this `Variable` is a member of."""
         """
 **`get_fill_value(self)`**
 
-return the fill value associated with this `Variable` (None if data is not
+return the fill value associated with this `Variable` (returns `None` if data is not
 pre-filled). Works even if default fill value was used, and `_FillValue` attribute
 does not exist."""
         cdef int ierr, no_fill

From 6e30d7bbe2d550b38cf007397b2d230ed1e8ccf2 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Mon, 21 Oct 2024 17:40:31 -0600
Subject: [PATCH 1309/1504] update docs

---
 docs/index.html | 26 ++++++++++++++++++++------
 1 file changed, 20 insertions(+), 6 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index 29e5a7c3c..8484e66d6 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -289,7 +289,7 @@ 
      Dimensions in a netCDF file
      
 <class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 144

      Dimension names can be changed using the -Dataset.renameDimension method of a Dataset or +Dataset.renameDimension() method of a Dataset or Group instance.

      Variables in a netCDF file

      netCDF variables behave much like python multidimensional array objects @@ -2676,12 +2676,16 @@

      Instance variables

      Ignored if significant_digts not specified. If 'BitRound' is used, then significant_digits is interpreted as binary (not decimal) digits.

      fill_value: -If specified, the default netCDF _FillValue (the +If specified, the default netCDF fill value (the value that the variable gets filled with before any data is written to it) -is replaced with this value. -If fill_value is set to False, then -the variable is not pre-filled. The default netCDF fill values can be found -in the dictionary netCDF4.default_fillvals.

      +is replaced with this value, and the _FillValue attribute is set. +If fill_value is set to False, then the variable is not pre-filled. +The default netCDF fill values can be found in the dictionary netCDF4.default_fillvals. +If not set, the default fill value will be used but no _FillValue attribute will be created +(this is the default behavior of the netcdf-c library). If you want to use the +default fill value, but have the _FillValue attribute set, use +fill_value='default' (note - this only works for primitive data types). Variable.get_fill_value() +can be used to retrieve the fill value, even if the _FillValue attribute is not set.

      chunk_cache: If specified, sets the chunk cache size for this variable. Persists as long as Dataset is open. Use set_var_chunk_cache to change it when Dataset is re-opened.

      @@ -2806,6 +2810,15 @@

      Methods

      return a tuple of Dimension instances associated with this Variable.

      +
      +def get_fill_value(self) +
      +
      +

      get_fill_value(self)

      +

      return the fill value associated with this Variable (returns None if data is not +pre-filled). Works even if default fill value was used, and _FillValue attribute +does not exist.

      +
      def get_var_chunk_cache(self)
      @@ -3241,6 +3254,7 @@

      Variablefilters
    • getValue
    • get_dims
      • +
    • get_fill_value
    • get_var_chunk_cache
    • getncattr
    • group
      • From 6a31be49b850baf6c00b0c242072399c2e8cced0 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Tue, 22 Oct 2024 09:12:03 -0700 Subject: [PATCH 1310/1504] post-merge mypy/stubtest fixes. Allow any numpy generic or array in fillvalue. --- .github/stubtest-allowlist | 2 ++ src/netCDF4/__init__.pyi | 14 +++++++------- 2 files changed, 9 insertions(+), 7 deletions(-) diff --git a/.github/stubtest-allowlist b/.github/stubtest-allowlist index 0352fdcf7..aa1b1d69b 100644 --- a/.github/stubtest-allowlist +++ b/.github/stubtest-allowlist @@ -29,12 +29,14 @@ netCDF4.NumericVarT netCDF4.Dimension.__reduce_cython__ netCDF4.Dimension.__setstate_cython__ netCDF4.Variable.auto_complex +netCDF4.Variable.get_fill_value netCDF4.Variable.__iter__ netCDF4._netCDF4.Dimension.__reduce_cython__ netCDF4._netCDF4.Dimension.__setstate_cython__ netCDF4._netCDF4.NC_DISKLESS netCDF4._netCDF4.NC_PERSIST netCDF4._netCDF4.Variable.auto_complex +netCDF4._netCDF4.Variable.get_fill_value netCDF4._netCDF4.Variable.__iter__ netCDF4._netCDF4.__reduce_cython__ netCDF4._netCDF4.__setstate_cython__ diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 5bdc58d00..6ed415f7a 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -295,7 +295,7 @@ class Dataset: least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode = "BitGroom", - fill_value: int | float | np.number | str | bytes | Literal[False] | None = None, + fill_value: int | float | np.generic | str | bytes | Literal[False] | np.ndarray | None = None, chunk_cache: int | None = None, ) -> Variable[NumericVarT]: ... @overload @@ -318,7 +318,7 @@ class Dataset: least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode = "BitGroom", - fill_value: int | float | np.number | str | bytes | Literal[False] | None = None, + fill_value: int | float | np.generic | str | bytes | Literal[False] | np.ndarray | None = None, chunk_cache: int | None = None, ) -> Variable[str]: ... @overload @@ -341,7 +341,7 @@ class Dataset: least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode = "BitGroom", - fill_value: int | float | np.number | str | bytes | Literal[False] | None = None, + fill_value: int | float | np.generic | str | bytes | Literal[False] | np.ndarray | None = None, chunk_cache: int | None = None, ) -> Variable: ... def renameVariable(self, oldname: str, newname: str) -> None: ... @@ -450,7 +450,7 @@ class Variable(Generic[VarT]): least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode = "BitGroom", - fill_value: int | float | np.number | str | bytes | Literal[False] | None = None, + fill_value: int | float | np.generic | str | bytes | Literal[False] | np.ndarray | None = None, chunk_cache: int | None = None, **kwargs: Any, ) -> Variable[NumericVarT]: ... @@ -475,7 +475,7 @@ class Variable(Generic[VarT]): least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode = "BitGroom", - fill_value: int | float | np.number | str | bytes | Literal[False] | None = None, + fill_value: int | float | np.generic | str | bytes | Literal[False] | np.ndarray | None = None, chunk_cache: int | None = None, **kwargs: Any, ) -> Variable[str]: ... @@ -500,7 +500,7 @@ class Variable(Generic[VarT]): least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode = "BitGroom", - fill_value: int | float | np.number | str | bytes | Literal[False] | None = None, + fill_value: int | float | np.generic | str | bytes | Literal[False] | np.ndarray | None = None, chunk_cache: int | None = None, **kwargs: Any, ) -> Variable: ... @@ -524,7 +524,7 @@ class Variable(Generic[VarT]): least_significant_digit: int | None = None, significant_digits: int | None = None, quantize_mode: QuantizeMode = "BitGroom", - fill_value: int | float | np.number | str | bytes | Literal[False] | None = None, + fill_value: int | float | np.generic | str | bytes | Literal[False] | np.ndarray | None = None, chunk_cache: int | None = None, **kwargs: Any, ) -> None: ... From 1004467517b44e1fd5832f2ea904653a67021a09 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Tue, 22 Oct 2024 09:36:13 -0700 Subject: [PATCH 1311/1504] Revert stubtest change -- mypy v1.12 differs from 1.11 --- .github/stubtest-allowlist | 2 -- 1 file changed, 2 deletions(-) diff --git a/.github/stubtest-allowlist b/.github/stubtest-allowlist index aa1b1d69b..0352fdcf7 100644 --- a/.github/stubtest-allowlist +++ b/.github/stubtest-allowlist @@ -29,14 +29,12 @@ netCDF4.NumericVarT netCDF4.Dimension.__reduce_cython__ netCDF4.Dimension.__setstate_cython__ netCDF4.Variable.auto_complex -netCDF4.Variable.get_fill_value netCDF4.Variable.__iter__ netCDF4._netCDF4.Dimension.__reduce_cython__ netCDF4._netCDF4.Dimension.__setstate_cython__ netCDF4._netCDF4.NC_DISKLESS netCDF4._netCDF4.NC_PERSIST netCDF4._netCDF4.Variable.auto_complex -netCDF4._netCDF4.Variable.get_fill_value netCDF4._netCDF4.Variable.__iter__ netCDF4._netCDF4.__reduce_cython__ netCDF4._netCDF4.__setstate_cython__ From 6b7c0644ad025043035058357def1a08021edff3 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 22 Oct 2024 11:12:45 -0600 Subject: [PATCH 1312/1504] prepare for v1.7.2 release --- Changelog | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/Changelog b/Changelog index bc46e06ce..c105b9d73 100644 --- a/Changelog +++ b/Changelog @@ -1,6 +1,6 @@ - version 1.7.2 (not yet released) -=============================== - * add static type hints (PR #1302) + version 1.7.2 (tag v1.7.2rel) + ============================= + * add static type hints (PRs #1302, #1349) * Expose nc_rc_set, nc_rc_get (via rc_set, rc_get module functions). (PR #1348) * Add Variable.get_fill_value and allow `fill_value='default'` to set `_FillValue` using default fill values. (issue #1374, PR #1375). From 24e2ea0d359d07086053c07905752b79c89ae277 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 22 Oct 2024 11:17:56 -0600 Subject: [PATCH 1313/1504] include python 3.13 --- .github/workflows/build_latest.yml | 2 +- .github/workflows/build_master.yml | 2 +- .github/workflows/build_old.yml | 2 +- .github/workflows/miniconda.yml | 2 +- 4 files changed, 4 insertions(+), 4 deletions(-) diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml index cca163d45..681a81ae2 100644 --- a/.github/workflows/build_latest.yml +++ b/.github/workflows/build_latest.yml @@ -13,7 +13,7 @@ jobs: #NO_NET: 1 strategy: matrix: - python-version: ["3.11"] + python-version: ["3.12"] steps: - uses: actions/checkout@v4 diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml index 4e0e34fe5..23b2248e6 100644 --- a/.github/workflows/build_master.yml +++ b/.github/workflows/build_master.yml @@ -10,7 +10,7 @@ jobs: #NO_NET: 1 strategy: matrix: - python-version: ["3.11"] + python-version: ["3.12"] steps: - uses: actions/checkout@v4 diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml index 047c892de..e8d0a59b8 100644 --- a/.github/workflows/build_old.yml +++ b/.github/workflows/build_old.yml @@ -13,7 +13,7 @@ jobs: #NO_NET: 1 strategy: matrix: - python-version: ["3.11"] + python-version: ["3.12"] steps: - uses: actions/checkout@v4 diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index 6619db072..e4dda9b2b 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -12,7 +12,7 @@ jobs: # NO_NET: 1 strategy: matrix: - python-version: [ "3.9", "3.10", "3.11", "3.12" ] + python-version: [ "3.9", "3.10", "3.11", "3.12", "3.13" ] os: [windows-latest, ubuntu-latest, macos-latest] platform: [x64, x32] exclude: From f738ad77aa1699483f6ddb7f1edbc21df1d20b08 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 22 Oct 2024 11:25:48 -0600 Subject: [PATCH 1314/1504] update --- .github/workflows/miniconda.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index e4dda9b2b..fed318c90 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -35,7 +35,7 @@ jobs: init-shell: bash create-args: >- python=${{ matrix.python-version }} - numpy cython pip pytest hdf5 libnetcdf cftime zlib certifi typing-extensions + numpy cython pip setuptools pytest hdf5 libnetcdf cftime zlib certifi typing-extensions --channel conda-forge - name: Install netcdf4-python @@ -51,7 +51,7 @@ jobs: runs-on: ${{ matrix.os }} strategy: matrix: - python-version: [ "3.11" ] + python-version: [ "3.12" ] os: [ubuntu-latest] platform: [x64] defaults: From 7ee6af5e7a72630ffdd2080625ef76e4ae8dbe5d Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Tue, 22 Oct 2024 11:40:14 -0600 Subject: [PATCH 1315/1504] update --- Changelog | 2 +- README.md | 2 ++ 2 files changed, 3 insertions(+), 1 deletion(-) diff --git a/Changelog b/Changelog index c105b9d73..c9a581cd5 100644 --- a/Changelog +++ b/Changelog @@ -3,7 +3,7 @@ * add static type hints (PRs #1302, #1349) * Expose nc_rc_set, nc_rc_get (via rc_set, rc_get module functions). (PR #1348) * Add Variable.get_fill_value and allow `fill_value='default'` to - set `_FillValue` using default fill values. (issue #1374, PR #1375). + set `_FillValue` attribute using default fill values. (issue #1374, PR #1375). * Fix NETCDF3 endian error (issue #1373, PR #1355). version 1.7.1 (tag v1.7.1rel) diff --git a/README.md b/README.md index 8fa99985b..59b113022 100644 --- a/README.md +++ b/README.md @@ -10,6 +10,8 @@ ## News For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog). +10/22/2024: Version [1.7.2](https://pypi.python.org/pypi/netCDF4/1.7.2) released. Minor updates/bugfixes and python 3.13 wheels, see Changelog for details. + 06/17/2024: Version [1.7.1](https://pypi.python.org/pypi/netCDF4/1.7.1) released. Fixes for wheels, no code changes. 06/13/2024: Version [1.7.0](https://pypi.python.org/pypi/netCDF4/1.7.0) released. Add support for complex numbers via `auto_complex` keyword to `Dataset` ([PR #1295](https://github.com/Unidata/netcdf4-python/pull/1295)) From 6d894264a13b1ce583967f008b4efd323c4c1532 Mon Sep 17 00:00:00 2001 From: Filipe Fernandes Date: Wed, 23 Oct 2024 08:23:41 +0200 Subject: [PATCH 1316/1504] Add py313 to the Windows wheel builds --- .github/workflows/cibuildwheel.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml index 831c120b2..f7f125723 100644 --- a/.github/workflows/cibuildwheel.yml +++ b/.github/workflows/cibuildwheel.yml @@ -147,7 +147,7 @@ jobs: - name: Build wheels for Windows (${{ matrix.arch }}) run: cibuildwheel --output-dir wheelhouse env: - CIBW_BUILD: "cp39-${{ matrix.arch }} cp310-${{ matrix.arch }} cp311-${{ matrix.arch }} cp312-${{ matrix.arch }}" + CIBW_BUILD: "cp39-${{ matrix.arch }} cp310-${{ matrix.arch }} cp311-${{ matrix.arch }} cp312-${{ matrix.arch }} cp313-${{ matrix.arch }}" CIBW_ENVIRONMENT_WINDOWS: > HDF5_DIR="C:\\Users\\runneradmin\\micromamba\\envs\\build\\Library" netCDF4_DIR="C:\\Users\\runneradmin\\micromamba\\envs\\build\\Library" From 58f8c6a0c7a3048f6bf1c44873ff3ce68ebda375 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Wed, 30 Oct 2024 10:02:02 -0600 Subject: [PATCH 1317/1504] fix for createEnum type hint --- src/netCDF4/__init__.pyi | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 6ed415f7a..67b23404c 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -354,7 +354,7 @@ class Dataset: def createVLType(self, datatype: npt.DTypeLike, datatype_name: str) -> VLType: ... def createEnumType( self, - datatype: np.dtype[np.integer] | type[np.integer] | type[int], + datatype: np.dtype[np.integer] | type[np.integer] | type[int] | str, datatype_name: str, enum_dict: Mapping[str, int | np.integer], ) -> EnumType: ... From 9ce01c668a173ec6fcc5c725b86159c0c6c71487 Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Wed, 30 Oct 2024 10:30:03 -0600 Subject: [PATCH 1318/1504] update --- Changelog | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/Changelog b/Changelog index c9a581cd5..1ada36781 100644 --- a/Changelog +++ b/Changelog @@ -1,3 +1,8 @@ + since version 1.7.2 release + =========================== + * fix type hint for createEnumType (issue #1378) + * add python 3.13 to windows wheel builds (PR #1377) + version 1.7.2 (tag v1.7.2rel) ============================= * add static type hints (PRs #1302, #1349) From e0efdb599cddc83317c14e15a02996ae7b799f62 Mon Sep 17 00:00:00 2001 From: DWesl <22566757+DWesl@users.noreply.github.com> Date: Wed, 6 Nov 2024 16:05:18 -0500 Subject: [PATCH 1319/1504] DOC: Try to keep <code> tags from appearing in rendered docs https://unidata.github.io/netcdf4-python/#netCDF4.Dataset Scroll down to `format`: underlying file format. Not sure if this should be ReST's ``code`` or Markdown's `code`, though the default role Sphinx assigns to single quotes should work (:any:`code`, I think is how sphinx would interpret `code`). In any case, it works everywhere else, so hopefully it works here too. --- src/netCDF4/_netCDF4.pyx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 7c92f09bd..e4eeb350e 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2331,8 +2331,8 @@ strings. exception will be raised if a file with the same name already exists. mode=`x` is identical to mode=`w` with clobber=False. - **`format`**: underlying file format (one of `'NETCDF4', - 'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC'`, `'NETCDF3_64BIT_OFFSET'` or + **`format`**: underlying file format (one of `'NETCDF4'`, + `'NETCDF4_CLASSIC'`, `'NETCDF3_CLASSIC'`, `'NETCDF3_64BIT_OFFSET'` or `'NETCDF3_64BIT_DATA'`. Only relevant if `mode = 'w'` (if `mode = 'r','a'` or `'r+'` the file format is automatically detected). Default `'NETCDF4'`, which means the data is From ca2066a41e5ffe83887650303170fa687ac8c9a4 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Fri, 8 Nov 2024 12:41:45 -0800 Subject: [PATCH 1320/1504] Raise TypeError in __iter__ and __contains__ methods as iteration and membership ops are not supported. --- src/netCDF4/_netCDF4.pyx | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 7c92f09bd..cb6649e3b 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2569,6 +2569,15 @@ strings. else: raise IndexError('%s not found in %s' % (lastname,group.path)) + def __iter__(self): + raise TypeError("Dataset is not iterable.") + + def __contains__(self, key): + raise TypeError( + "Dataset does not support membership operations. Perhaps try 'varname in" + " dataset.variables' or 'dimname in dataset.dimensions'." + ) + def filepath(self,encoding=None): """**`filepath(self,encoding=None)`** From 561b9e94070b7125728c279523829232074dbc4e Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Fri, 8 Nov 2024 12:42:39 -0800 Subject: [PATCH 1321/1504] Add NoReturn type hints for __iter__ and __contains__ --- src/netCDF4/__init__.pyi | 3 +++ 1 file changed, 3 insertions(+) diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi index 67b23404c..4d88568a7 100644 --- a/src/netCDF4/__init__.pyi +++ b/src/netCDF4/__init__.pyi @@ -384,6 +384,9 @@ class Dataset: def has_bzip2_filter(self) -> bool: ... def has_szip_filter(self) -> bool: ... def __getitem__(self, elem: str) -> Any: ... # should be Group | Variable, but this causes too many problems + # __iter__ and __contains__ always error because iteration and membership ops are not allowed + def __iter__(self) -> NoReturn: ... + def __contains__(self, key) -> NoReturn: ... def __setattr__(self, name: str, value: Any) -> None: ... def __getattr__(self, name: str) -> Any: ... def __delattr__(self, name: str): ... From 607d7d5676421b61e789509c7d84ab215a59d714 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Fri, 8 Nov 2024 12:43:08 -0800 Subject: [PATCH 1322/1504] Add test case for explicitly disallowed __iter__ and __contains__ --- test/test_no_iter_contains.py | 34 ++++++++++++++++++++++++++++++++++ 1 file changed, 34 insertions(+) create mode 100644 test/test_no_iter_contains.py diff --git a/test/test_no_iter_contains.py b/test/test_no_iter_contains.py new file mode 100644 index 000000000..793f0f7da --- /dev/null +++ b/test/test_no_iter_contains.py @@ -0,0 +1,34 @@ +import os +import tempfile +import unittest + +import netCDF4 + +FILE_NAME = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name + + +class TestNoIterNoContains(unittest.TestCase): + def setUp(self) -> None: + self.file = FILE_NAME + with netCDF4.Dataset(self.file, "w") as dataset: + # just create a simple variable + dataset.createVariable("var1", int) + + def tearDown(self) -> None: + os.remove(self.file) + + def test_no_iter(self) -> None: + """Verify that iteration is explicitly not supported""" + with netCDF4.Dataset(self.file, "r") as dataset: + with self.assertRaises(TypeError): + for _ in dataset: # type: ignore # type checker catches that this doesn't work + pass + + def test_no_contains(self) -> None: + """Verify the membership operations are explicity not supported""" + with netCDF4.Dataset(self.file, "r") as dataset: + with self.assertRaises(TypeError): + _ = "var1" in dataset + +if __name__ == "__main__": + unittest.main(verbosity=2) From 38f5aaaf7ad729aa763239112e6169fe3253c205 Mon Sep 17 00:00:00 2001 From: Randall Pittman Date: Fri, 8 Nov 2024 13:24:18 -0800 Subject: [PATCH 1323/1504] Add suggestion to TypeError on __iter__. --- src/netCDF4/_netCDF4.pyx | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index cb6649e3b..7055dc599 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2570,7 +2570,9 @@ strings. raise IndexError('%s not found in %s' % (lastname,group.path)) def __iter__(self): - raise TypeError("Dataset is not iterable.") + raise TypeError( + "Dataset is not iterable. Consider iterating on Dataset.variables." + ) def __contains__(self, key): raise TypeError( @@ -4050,7 +4052,7 @@ behavior is similar to Fortran or Matlab, but different than numpy. If fill_value is set to `False`, then the variable is not pre-filled. The default netCDF fill values can be found in the dictionary `netCDF4.default_fillvals`. If not set, the default fill value will be used but no `_FillValue` attribute will be created - (this is the default behavior of the netcdf-c library). If you want to use the + (this is the default behavior of the netcdf-c library). If you want to use the default fill value, but have the `_FillValue` attribute set, use `fill_value='default'` (note - this only works for primitive data types). `Variable.get_fill_value` can be used to retrieve the fill value, even if the `_FillValue` attribute is not set. From 18f0be0c9975280502746640c23c78ef2dd6fcf5 Mon Sep 17 00:00:00 2001 From: DWesl <22566757+DWesl@users.noreply.github.com> Date: Tue, 12 Nov 2024 15:40:52 -0500 Subject: [PATCH 1324/1504] DOC: Try to avoid <code> showing up in generated HTML --- src/netCDF4/_netCDF4.pyx | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index fc7494208..cc96cf58f 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -2985,8 +2985,8 @@ Dataset standard attributes: `dimensions, dtype, shape, ndim, name` and `least_significant_digit`. Application programs should never modify these attributes. The `dimensions` attribute is a tuple containing the names of the dimensions associated with this variable. The `dtype` -attribute is a string describing the variable's data type (`i4, f8, -S1,` etc). The `shape` attribute is a tuple describing the current +attribute is a string describing the variable's data type (`i4`, `f8`, +`S1`, etc). The `shape` attribute is a tuple describing the current sizes of all the variable's dimensions. The `name` attribute is a string containing the name of the Variable instance. The `least_significant_digit` @@ -3493,8 +3493,8 @@ suffix replaced by `.nc` is used.. **`mode`**: Access mode to open Dataset (Default `'a'`). -**`format`**: underlying file format to use (one of `'NETCDF4', -'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC'`, `'NETCDF3_64BIT_OFFSET'` or +**`format`**: underlying file format to use (one of `'NETCDF4'`, +`'NETCDF4_CLASSIC'`, `'NETCDF3_CLASSIC'`, `'NETCDF3_64BIT_OFFSET'` or `'NETCDF3_64BIT_DATA'`. Default `'NETCDF4'`. Dataset instance for `ncfilename` is returned. From 5722c9d57e188d77f33da726a101b44fc26b4b5d Mon Sep 17 00:00:00 2001 From: Jeff Whitaker Date: Wed, 13 Nov 2024 08:33:47 -0700 Subject: [PATCH 1325/1504] update --- Changelog | 2 ++ 1 file changed, 2 insertions(+) diff --git a/Changelog b/Changelog index 1ada36781..e79959aff 100644 --- a/Changelog +++ b/Changelog @@ -1,5 +1,7 @@ since version 1.7.2 release =========================== + * raise more informative error when trying to iterate or + perform a membership operation on a Dataset (issue #1383) * fix type hint for createEnumType (issue #1378) * add python 3.13 to windows wheel builds (PR #1377) From 39ff1548aaaed19abede3e389fffa0c151d315f2 Mon Sep 17 00:00:00 2001 From: DWesl <22566757+DWesl@users.noreply.github.com> Date: Wed, 13 Nov 2024 18:11:16 -0500 Subject: [PATCH 1326/1504] DOC: Fix weird code tags in docs/index.html It seems this needs to be regenerated manually. I don't feel like doing that, so I'm just editing it by hand. Yes it will be overwritten, but my other changes should make this stick. --- docs/index.html | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/docs/index.html b/docs/index.html index 8484e66d6..b766ef171 100644 --- a/docs/index.html +++ b/docs/index.html @@ -1552,8 +1552,8 @@

      Instance variables

      if False, an exception will be raised if a file with the same name already exists. mode=x is identical to mode=w with clobber=False.

      -

      format: underlying file format (one of 'NETCDF4', -'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC'<code>, </code>'NETCDF3_64BIT_OFFSET' or +

      format: underlying file format (one of 'NETCDF4', +'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC', 'NETCDF3_64BIT_OFFSET' or 'NETCDF3_64BIT_DATA'. Only relevant if mode = 'w' (if mode = 'r','a' or 'r+' the file format is automatically detected). Default 'NETCDF4', which means the data is @@ -1637,8 +1637,8 @@

      Static methods

      suffix replaced by .nc is used..

      mode: Access mode to open Dataset (Default 'a').

      -

      format: underlying file format to use (one of 'NETCDF4', -'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC'<code>, </code>'NETCDF3_64BIT_OFFSET' or +

      format: underlying file format to use (one of 'NETCDF4', +'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC', 'NETCDF3_64BIT_OFFSET' or 'NETCDF3_64BIT_DATA'. Default 'NETCDF4'.

      Dataset instance for ncfilename is returned.

      @@ -1912,8 +1912,8 @@

      Methods

      least_significant_digit. Application programs should never modify these attributes. The dimensions attribute is a tuple containing the names of the dimensions associated with this variable. The dtype -attribute is a string describing the variable's data type (i4, f8, -S1,<code> etc). The </code>shape attribute is a tuple describing the current +attribute is a string describing the variable's data type (i4, f8, +S1, etc). The shape attribute is a tuple describing the current sizes of all the variable's dimensions. The name attribute is a string containing the name of the Variable instance. The least_significant_digit @@ -2347,8 +2347,8 @@

      Methods

      Class for reading multi-file netCDF Datasets, making variables spanning multiple files appear as if they were in one file. -Datasets must be in NETCDF4_CLASSIC, NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET -or NETCDF3_64BIT_DATA<code> format (</code>NETCDF4 Datasets won't work).

      +Datasets must be in NETCDF4_CLASSIC, NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET +or NETCDF3_64BIT_DATA format (NETCDF4 Datasets won't work).

      Adapted from pycdf by Andre Gosselin.

      Example usage (See MFDataset for more details):

      >>> import numpy as np

From af0831296f49fab3fc9df8327e30d64e6957d61b Mon Sep 17 00:00:00 2001
From: DWesl <22566757+DWesl@users.noreply.github.com>
Date: Wed, 13 Nov 2024 18:15:28 -0500
Subject: [PATCH 1327/1504] DOC,FIX: Change the last of the places showing up
 as <code>

I checked this works with pdoc, hopefully pdoc3 is similar.
---
 src/netCDF4/_netCDF4.pyx | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index cc96cf58f..6d5ae3c4b 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -6833,8 +6833,8 @@ class MFDataset(Dataset):
     """
 Class for reading multi-file netCDF Datasets, making variables
 spanning multiple files appear as if they were in one file.
-Datasets must be in `NETCDF4_CLASSIC, NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET
-or NETCDF3_64BIT_DATA` format (`NETCDF4` Datasets won't work).
+Datasets must be in `NETCDF4_CLASSIC`, `NETCDF3_CLASSIC`, `NETCDF3_64BIT_OFFSET`
+or `NETCDF3_64BIT_DATA` format (`NETCDF4` Datasets won't work).
 
 Adapted from [pycdf](http://pysclint.sourceforge.net/pycdf) by Andre Gosselin.
 

From 598ab4deeaace02ab206a0ba68f2a2747f8eab03 Mon Sep 17 00:00:00 2001
From: Michael Niklas 
Date: Thu, 14 Nov 2024 17:23:37 +0100
Subject: [PATCH 1328/1504] support PathLikes in fromcdl

---
 src/netCDF4/__init__.pyi | 2 +-
 src/netCDF4/_netCDF4.pyx | 4 ++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi
index 4d88568a7..0949b4ed2 100644
--- a/src/netCDF4/__init__.pyi
+++ b/src/netCDF4/__init__.pyi
@@ -373,7 +373,7 @@ class Dataset:
     def get_variables_by_attributes(self, **kwargs: Callable[[Any], bool] | Any) -> list[Variable]: ...
     @staticmethod
     def fromcdl(
-        cdlfilename: str, ncfilename: str | None = None, mode: AccessMode = "a", format: Format = "NETCDF4"
+        cdlfilename: str | os.PathLike, ncfilename: str | os.PathLike | None = None, mode: AccessMode = "a", format: Format = "NETCDF4"
     ) -> Dataset: ...
     @overload
     def tocdl(self, coordvars: bool = False, data: bool = False, outfile: None = None) -> str: ...
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 6d5ae3c4b..d00124efb 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3502,8 +3502,8 @@ Dataset instance for `ncfilename` is returned.
 [ncgen]: https://www.unidata.ucar.edu/software/netcdf/docs/netcdf_utilities_guide.html#ncgen_guide
 [cdl]: https://www.unidata.ucar.edu/software/netcdf/docs/netcdf_utilities_guide.html#cdl_guide
         """
+        filepath = pathlib.Path(cdlfilename)
         if ncfilename is None:
-            filepath = pathlib.Path(cdlfilename)
             ncfilename = filepath.with_suffix('.nc')
         formatcodes = {'NETCDF4': 4,
                        'NETCDF4_CLASSIC': 7,
@@ -3514,7 +3514,7 @@ Dataset instance for `ncfilename` is returned.
         if format not in formatcodes:
             raise ValueError('illegal format requested')
         ncgenargs="-knc%s" % formatcodes[format]
-        subprocess.run(["ncgen", ncgenargs, "-o", ncfilename, cdlfilename], check=True)
+        subprocess.run(["ncgen", ncgenargs, "-o", str(ncfilename), str(cdlfilename)], check=True)
         return Dataset(ncfilename, mode=mode)
 
     def tocdl(self,coordvars=False,data=False,outfile=None):

From 000466cf8981d564e958ed54689495c823e70154 Mon Sep 17 00:00:00 2001
From: Michael Niklas 
Date: Thu, 14 Nov 2024 17:24:02 +0100
Subject: [PATCH 1329/1504] ignore .vscode folder

---
 .gitignore | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.gitignore b/.gitignore
index f188f233a..219570adf 100644
--- a/.gitignore
+++ b/.gitignore
@@ -13,3 +13,4 @@ netcdftime/_netcdftime.c
 venv/
 .eggs/
 .idea/
+.vscode/

From 43ba78addd9253495f371f919f324617b91fa403 Mon Sep 17 00:00:00 2001
From: Michael Niklas 
Date: Thu, 14 Nov 2024 17:25:39 +0100
Subject: [PATCH 1330/1504] use filepath

---
 src/netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index d00124efb..861fa076d 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3514,7 +3514,7 @@ Dataset instance for `ncfilename` is returned.
         if format not in formatcodes:
             raise ValueError('illegal format requested')
         ncgenargs="-knc%s" % formatcodes[format]
-        subprocess.run(["ncgen", ncgenargs, "-o", str(ncfilename), str(cdlfilename)], check=True)
+        subprocess.run(["ncgen", ncgenargs, "-o", str(ncfilename), str(filepath)], check=True)
         return Dataset(ncfilename, mode=mode)
 
     def tocdl(self,coordvars=False,data=False,outfile=None):

From 0affb732496ce273bcd248b3091b8ab25e299c5b Mon Sep 17 00:00:00 2001
From: Michael Niklas 
Date: Thu, 14 Nov 2024 17:38:58 +0100
Subject: [PATCH 1331/1504] raise better errors if file exist/do not exist

---
 src/netCDF4/_netCDF4.pyx | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 861fa076d..3b8851aac 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3505,14 +3505,22 @@ Dataset instance for `ncfilename` is returned.
         filepath = pathlib.Path(cdlfilename)
         if ncfilename is None:
             ncfilename = filepath.with_suffix('.nc')
+        else:
+            ncfilename = pathlib.Path(ncfilename)
         formatcodes = {'NETCDF4': 4,
                        'NETCDF4_CLASSIC': 7,
                        'NETCDF3_CLASSIC': 3,
                        'NETCDF3_64BIT': 6, # legacy
                        'NETCDF3_64BIT_OFFSET': 6,
                        'NETCDF3_64BIT_DATA': 5}
+
         if format not in formatcodes:
             raise ValueError('illegal format requested')
+        if not filepath.exists():
+            raise FileNotFoundError(filepath)
+        if ncfilename.exists():
+            raise FileExistsError(ncfilename)
+
         ncgenargs="-knc%s" % formatcodes[format]
         subprocess.run(["ncgen", ncgenargs, "-o", str(ncfilename), str(filepath)], check=True)
         return Dataset(ncfilename, mode=mode)

From 66007af89cef8568aacb64b224e600279de1897f Mon Sep 17 00:00:00 2001
From: Michael Niklas 
Date: Thu, 14 Nov 2024 21:04:01 +0100
Subject: [PATCH 1332/1504] add tests

---
 test/test_cdl.py | 10 ++++++++++
 1 file changed, 10 insertions(+)

diff --git a/test/test_cdl.py b/test/test_cdl.py
index 4ee4da3c0..895f572fa 100644
--- a/test/test_cdl.py
+++ b/test/test_cdl.py
@@ -68,8 +68,18 @@ def test_fromcdl(self):
                 assert len(f1.dimensions["d"]) == len(f2.dimensions["d"])
                 assert (f1["ub"][:] == f2["ub"][:]).all()
                 assert (f1["sb"][:] == f2["sb"][:]).all()
+            
+            # test if os.PathLike works
+            with netCDF4.Dataset.fromcdl(pathlib.Path("ubyte.cdl"), ncfilename=pathlib.Path("ubyte3.nc")) as f3:
+                assert f1.variables.keys() == f3.variables.keys()
 
+        # check if correct errors are raised
+        self.assertRaises(FileNotFoundError, netCDF4.Dataset.fromcdl, "doesnotexist.cdl")
+        self.assertRaises(FileExistsError, netCDF4.Dataset.fromcdl, "ubyte.cdl", ncfilename="ubyte2.nc")
+
+        # cleanup
         os.remove("ubyte2.nc")
+        os.remove("ubyte3.nc")
 
     def tearDown(self):
         # Remove the temporary files

From d419ea83f7430543847def7f8286d68f70906736 Mon Sep 17 00:00:00 2001
From: Michael Niklas 
Date: Thu, 14 Nov 2024 21:11:34 +0100
Subject: [PATCH 1333/1504] add changelog

---
 Changelog | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/Changelog b/Changelog
index e79959aff..bcf2550e7 100644
--- a/Changelog
+++ b/Changelog
@@ -1,5 +1,7 @@
  since version 1.7.2 release
  ===========================
+ * support os.PathLike arguments for `Dataset.fromcdl` and raise a `FileNotFoundError`
+   if the cdl is missing and a `FileExistsError` if the nc file already exists (PR #1387)
  * raise more informative error when trying to iterate or
    perform a membership operation on a Dataset (issue #1383)
  * fix type hint for createEnumType (issue #1378)

From bacab64e83433cafcec3f83e5ab22f187d66d0ff Mon Sep 17 00:00:00 2001
From: danny-lloyd 
Date: Fri, 22 Nov 2024 12:17:39 +0000
Subject: [PATCH 1334/1504] Rewrite datatype table in docs

---
 docs/index.html          | 84 +++++++++++++++++++++++++++++++++-------
 src/netCDF4/_netCDF4.pyx | 31 +++++++++------
 2 files changed, 89 insertions(+), 26 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index b766ef171..a6b430483 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -297,7 +297,7 @@ 
      Variables in a netCDF file
      
 unlike numpy arrays, netCDF4 variables can be appended to along one or
 more 'unlimited' dimensions. To create a netCDF variable, use the
 Dataset.createVariable() method of a Dataset or
-Group instance. The Dataset.createVariable()j method
+Group instance. The Dataset.createVariable() method
 has two mandatory arguments, the variable name (a Python string), and
 the variable datatype. The variable's dimensions are given by a tuple
 containing the dimension names (defined previously with
@@ -305,19 +305,75 @@ 
      Variables in a netCDF file
      
 variable, simply leave out the dimensions keyword. The variable
 primitive datatypes correspond to the dtype attribute of a numpy array.
 You can specify the datatype as a numpy dtype object, or anything that
-can be converted to a numpy dtype object.
-Valid datatype specifiers
-include: 'f4' (32-bit floating point), 'f8' (64-bit floating
-point), 'i4' (32-bit signed integer), 'i2' (16-bit signed
-integer), 'i8' (64-bit signed integer), 'i1' (8-bit signed
-integer), 'u1' (8-bit unsigned integer), 'u2' (16-bit unsigned
-integer), 'u4' (32-bit unsigned integer), 'u8' (64-bit unsigned
-integer), or 'S1' (single-character string).
-The old Numeric
-single-character typecodes ('f','d','h',
-'s','b','B','c','i','l'), corresponding to
-('f4','f8','i2','i2','i1','i1','S1','i4','i4'),
-will also work. The unsigned integer types and the 64-bit integer type
+can be converted to a numpy dtype object. Valid datatype specifiers
+include:
      
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
      SpecifierDatatypeOld typecodes
      'f4'32-bit floating point'f'
      'f8'64-bit floating point'd'
      'i4'32-bit signed integer'i' 'l'
      'i2'16-bit signed integer'h' 's'
      'i8'64-bit signed integer
      'i1'8-bit signed integer'b' 'B'
      'u1'8-bit unsigned integer
      'u2'16-bit unsigned integer
      'u4'32-bit unsigned integer
      'u8'64-bit unsigned integer
      'S1'single-character string'c'
      
+
      The unsigned integer types and the 64-bit integer type
 can only be used if the file format is NETCDF4.
      
 
      The dimensions themselves are usually also defined as variables, called
 coordinate variables. The Dataset.createVariable()
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 3b8851aac..19a1186e3 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -295,7 +295,7 @@ supplied by the [numpy module](http://numpy.scipy.org). However,
 unlike numpy arrays, netCDF4 variables can be appended to along one or
 more 'unlimited' dimensions. To create a netCDF variable, use the
 `Dataset.createVariable` method of a `Dataset` or
-`Group` instance. The `Dataset.createVariable`j method
+`Group` instance. The `Dataset.createVariable` method
 has two mandatory arguments, the variable name (a Python string), and
 the variable datatype. The variable's dimensions are given by a tuple
 containing the dimension names (defined previously with
@@ -303,17 +303,24 @@ containing the dimension names (defined previously with
 variable, simply leave out the dimensions keyword. The variable
 primitive datatypes correspond to the dtype attribute of a numpy array.
 You can specify the datatype as a numpy dtype object, or anything that
-can be converted to a numpy dtype object.  Valid datatype specifiers
-include: `'f4'` (32-bit floating point), `'f8'` (64-bit floating
-point), `'i4'` (32-bit signed integer), `'i2'` (16-bit signed
-integer), `'i8'` (64-bit signed integer), `'i1'` (8-bit signed
-integer), `'u1'` (8-bit unsigned integer), `'u2'` (16-bit unsigned
-integer), `'u4'` (32-bit unsigned integer), `'u8'` (64-bit unsigned
-integer), or `'S1'` (single-character string).  The old Numeric
-single-character typecodes (`'f'`,`'d'`,`'h'`,
-`'s'`,`'b'`,`'B'`,`'c'`,`'i'`,`'l'`), corresponding to
-(`'f4'`,`'f8'`,`'i2'`,`'i2'`,`'i1'`,`'i1'`,`'S1'`,`'i4'`,`'i4'`),
-will also work. The unsigned integer types and the 64-bit integer type
+can be converted to a numpy dtype object. Valid datatype specifiers
+include:
+
+| Specifier | Datatype                | Old typecodes |
+|-----------|-------------------------|---------------|
+| `'f4'`    | 32-bit floating point   | `'f'`         |
+| `'f8'`    | 64-bit floating point   | `'d'`         |
+| `'i4'`    | 32-bit signed integer   | `'i'` `'l'`   |
+| `'i2'`    | 16-bit signed integer   | `'h'` `'s'`   |
+| `'i8'`    | 64-bit signed integer   |               |
+| `'i1'`    | 8-bit signed integer    | `'b'` `'B'`   |
+| `'u1'`    | 8-bit unsigned integer  |               |
+| `'u2'`    | 16-bit unsigned integer |               |
+| `'u4'`    | 32-bit unsigned integer |               |
+| `'u8'`    | 64-bit unsigned integer |               |
+| `'S1'`    | single-character string | `'c'`         |
+
+The unsigned integer types and the 64-bit integer type
 can only be used if the file format is `NETCDF4`.
 
 The dimensions themselves are usually also defined as variables, called

From e41b871651e1add6473ecb5333015a19b89a3ae3 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 25 Nov 2024 03:54:05 +0000
Subject: [PATCH 1335/1504] Bump pypa/cibuildwheel from 2.21.3 to 2.22.0 in the
 github-actions group

Bumps the github-actions group with 1 update: [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel).


Updates `pypa/cibuildwheel` from 2.21.3 to 2.22.0
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md)
- [Commits](https://github.com/pypa/cibuildwheel/compare/v2.21.3...v2.22.0)

---
updated-dependencies:
- dependency-name: pypa/cibuildwheel
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/cibuildwheel.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index f7f125723..0f08a0efa 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -92,7 +92,7 @@ jobs:
         echo "Setting CIBW_SKIP=$CIBW_SKIP"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
-      uses: pypa/cibuildwheel@v2.21.3
+      uses: pypa/cibuildwheel@v2.22.0
       env:
         CIBW_SKIP: ${{ env.CIBW_SKIP }}
         CIBW_ARCHS: ${{ matrix.arch }}

From bac97ed50f98ac02bbb110a15eb4f29f108e46ec Mon Sep 17 00:00:00 2001
From: Stephan Hoyer 
Date: Fri, 14 Feb 2025 16:18:22 -0800
Subject: [PATCH 1336/1504] Fix incorrect usage of "it's"

---
 src/netCDF4/utils.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/netCDF4/utils.py b/src/netCDF4/utils.py
index 13fc59076..1d2f52529 100644
--- a/src/netCDF4/utils.py
+++ b/src/netCDF4/utils.py
@@ -44,7 +44,7 @@ def _find_dim(grp, dimname):
             except:
                 raise ValueError("cannot find dimension %s in this group or parent groups" % dimname)
     if dim is None:
-        raise KeyError("dimension %s not defined in group %s or any group in it's family tree" % (dimname, grp.path))
+        raise KeyError("dimension %s not defined in group %s or any group in its family tree" % (dimname, grp.path))
     else:
         return dim
 

From 7a71d77d5f3af3fde386eb26f4a2bdff8012fd46 Mon Sep 17 00:00:00 2001
From: Stephan Hoyer 
Date: Fri, 14 Feb 2025 16:19:51 -0800
Subject: [PATCH 1337/1504] Fix incorrect const qualifier in membuf.pyx

Without this change, I see errors when building netCDF4-python,
originating at the line `free(self.memory)` in  `__dealloc__()`:

    .../_cython/_netCDF4.cc:12922:3: error: no matching function for call to 'free'
     12922 |   free(__pyx_v_self->memory);
           |   ^~~~
    .../include/stdlib.h:563:13: note: candidate function not viable: 1st argument ('const void *') would lose const qualifier
      563 | extern void free (void *__ptr) __THROW;
          |             ^     ~~~~~~~~~~~

Apparently it is not valid call `free()` on a `const` variable.
---
 include/membuf.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/include/membuf.pyx b/include/membuf.pyx
index 21a916db4..a236a1043 100644
--- a/include/membuf.pyx
+++ b/include/membuf.pyx
@@ -14,7 +14,7 @@ cdef memview_fromptr(void *memory, size_t size):
 
 # private extension type that implements buffer protocol.
 cdef class _MemBuf:
-    cdef const void *memory
+    cdef void *memory
     cdef size_t size
     def __getbuffer__(self, Py_buffer *buf, int flags):
         PyBuffer_FillInfo(buf, self, self.memory, self.size, 1, flags)

From 2c7dff854fd4c24cac61bfab348dba146392c83a Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 3 Mar 2025 03:41:21 +0000
Subject: [PATCH 1338/1504] Bump pypa/cibuildwheel from 2.22.0 to 2.23.0 in the
 github-actions group

Bumps the github-actions group with 1 update: [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel).


Updates `pypa/cibuildwheel` from 2.22.0 to 2.23.0
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md)
- [Commits](https://github.com/pypa/cibuildwheel/compare/v2.22.0...v2.23.0)

---
updated-dependencies:
- dependency-name: pypa/cibuildwheel
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/cibuildwheel.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 0f08a0efa..877e76444 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -92,7 +92,7 @@ jobs:
         echo "Setting CIBW_SKIP=$CIBW_SKIP"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
-      uses: pypa/cibuildwheel@v2.22.0
+      uses: pypa/cibuildwheel@v2.23.0
       env:
         CIBW_SKIP: ${{ env.CIBW_SKIP }}
         CIBW_ARCHS: ${{ matrix.arch }}

From 56c125376674fb462866283f477f9ab5b79055a6 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 4 Mar 2025 16:28:35 -0700
Subject: [PATCH 1339/1504] update netcdf-c and pnetcdf versions

---
 .github/workflows/build_latest.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index 681a81ae2..f0c80febd 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -5,8 +5,8 @@ jobs:
     name: Python (${{ matrix.python-version }})
     runs-on: ubuntu-latest
     env:
-      PNETCDF_VERSION: 1.12.1
-      NETCDF_VERSION: 4.9.2
+      PNETCDF_VERSION: 1.14.0
+      NETCDF_VERSION: 4.9.3
       NETCDF_DIR: ${{ github.workspace }}/..
       NETCDF_EXTRA_CONFIG: --enable-pnetcdf
       CC: mpicc.mpich

From 809bef7455f8524f8ee3ba6717a0e467d0a3dd37 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 4 Mar 2025 16:43:25 -0700
Subject: [PATCH 1340/1504] try openmpi instead of mpich

---
 .github/workflows/build_latest.yml | 23 +++++++++++++++--------
 1 file changed, 15 insertions(+), 8 deletions(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index f0c80febd..be44bf556 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -9,11 +9,12 @@ jobs:
       NETCDF_VERSION: 4.9.3
       NETCDF_DIR: ${{ github.workspace }}/..
       NETCDF_EXTRA_CONFIG: --enable-pnetcdf
-      CC: mpicc.mpich
+      #CC: mpicc.mpich
+      CC: mpicc.openmpi
       #NO_NET: 1
     strategy:
       matrix:
-        python-version: ["3.12"]
+        python-version: ["3.13"]
     steps:
 
     - uses: actions/checkout@v4
@@ -28,7 +29,8 @@ jobs:
     - name: Install Ubuntu Dependencies
       run: |
         sudo apt-get update
-        sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
+        #sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
+        sudo apt-get install openmpi-bin openmpi-common libopenmpi-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
         echo "Download and build PnetCDF version ${PNETCDF_VERSION}"
         wget https://parallel-netcdf.github.io/Release/pnetcdf-${PNETCDF_VERSION}.tar.gz
         tar -xzf pnetcdf-${PNETCDF_VERSION}.tar.gz
@@ -41,9 +43,11 @@ jobs:
         wget https://downloads.unidata.ucar.edu/netcdf-c/${NETCDF_VERSION}/netcdf-c-${NETCDF_VERSION}.tar.gz
         tar -xzf netcdf-c-${NETCDF_VERSION}.tar.gz
         pushd netcdf-c-${NETCDF_VERSION}
-        export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include"
+        #export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include"
+        export CPPFLAGS="-I/usr/include/hdf5/openmpi -I${NETCDF_DIR}/include"
         export LDFLAGS="-L${NETCDF_DIR}/lib"
-        export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
+        #export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
+        export LIBS="-lhdf5_openmpi_hl -lhdf5_openmpi -lm -lz"
         ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 $NETCDF_EXTRA_CONFIG
         make -j 2
         sudo make install
@@ -74,21 +78,24 @@ jobs:
         python run_all.py
         # parallel (hdf5 for netcdf4, pnetcdf for netcdf3)
         cd ../examples
-        mpirun.mpich -np 4 python mpi_example.py
+        #mpirun.mpich -np 4 python mpi_example.py
+        mpirun.openmpi -np 4 --oversubscribe python mpi_example.py 
         if [ $? -ne 0 ] ; then
           echo "hdf5 mpi test failed!"
           exit 1
         else
           echo "hdf5 mpi test passed!"
         fi
-        mpirun.mpich -np 4 python mpi_example_compressed.py
+        #mpirun.mpich -np 4 python mpi_example_compressed.py
+        mpirun.openmpi -np 4 --oversubscribe python mpi_example_compressed.py
         if [ $? -ne 0 ] ; then
           echo "hdf5 compressed mpi test failed!"
           exit 1
         else
           echo "hdf5 compressed mpi test passed!"
         fi
-        mpirun.mpich -np 4 python mpi_example.py NETCDF3_64BIT_DATA
+        #mpirun.mpich -np 4 python mpi_example.py NETCDF3_64BIT_DATA
+        mpirun.openmpi -np 4 --oversubscribe python mpi_example.py NETCDF3_64BIT_DATA
         if [ $? -ne 0 ] ; then
           echo "pnetcdf mpi test failed!"
           exit 1

From f5888b72f4fbd05f132ac3bf85b66d0e9e6dba7b Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 4 Mar 2025 16:50:18 -0700
Subject: [PATCH 1341/1504] update

---
 .github/workflows/build_latest.yml | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index be44bf556..70c76b28e 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -10,7 +10,7 @@ jobs:
       NETCDF_DIR: ${{ github.workspace }}/..
       NETCDF_EXTRA_CONFIG: --enable-pnetcdf
       #CC: mpicc.mpich
-      CC: mpicc.openmpi
+      CC: mpicc
       #NO_NET: 1
     strategy:
       matrix:
@@ -79,7 +79,7 @@ jobs:
         # parallel (hdf5 for netcdf4, pnetcdf for netcdf3)
         cd ../examples
         #mpirun.mpich -np 4 python mpi_example.py
-        mpirun.openmpi -np 4 --oversubscribe python mpi_example.py 
+        mpirun -np 4 --oversubscribe python mpi_example.py 
         if [ $? -ne 0 ] ; then
           echo "hdf5 mpi test failed!"
           exit 1
@@ -87,7 +87,7 @@ jobs:
           echo "hdf5 mpi test passed!"
         fi
         #mpirun.mpich -np 4 python mpi_example_compressed.py
-        mpirun.openmpi -np 4 --oversubscribe python mpi_example_compressed.py
+        mpirun -np 4 --oversubscribe python mpi_example_compressed.py
         if [ $? -ne 0 ] ; then
           echo "hdf5 compressed mpi test failed!"
           exit 1
@@ -95,7 +95,7 @@ jobs:
           echo "hdf5 compressed mpi test passed!"
         fi
         #mpirun.mpich -np 4 python mpi_example.py NETCDF3_64BIT_DATA
-        mpirun.openmpi -np 4 --oversubscribe python mpi_example.py NETCDF3_64BIT_DATA
+        mpirun -np 4 --oversubscribe python mpi_example.py NETCDF3_64BIT_DATA
         if [ $? -ne 0 ] ; then
           echo "pnetcdf mpi test failed!"
           exit 1

From fb8d2670461a112124db129e4773c4e0d7986ab0 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 4 Mar 2025 16:59:50 -0700
Subject: [PATCH 1342/1504] update

---
 .github/workflows/build_latest.yml | 13 +++++++------
 1 file changed, 7 insertions(+), 6 deletions(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index 70c76b28e..d4378a3bc 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -10,7 +10,7 @@ jobs:
       NETCDF_DIR: ${{ github.workspace }}/..
       NETCDF_EXTRA_CONFIG: --enable-pnetcdf
       #CC: mpicc.mpich
-      CC: mpicc
+      CC: mpicc.openmpi
       #NO_NET: 1
     strategy:
       matrix:
@@ -29,8 +29,8 @@ jobs:
     - name: Install Ubuntu Dependencies
       run: |
         sudo apt-get update
-        #sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
-        sudo apt-get install openmpi-bin openmpi-common libopenmpi-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
+        sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev openmpi-bin openmpi-common libopenmpi-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
+        update-alternatives --list mpirun
         echo "Download and build PnetCDF version ${PNETCDF_VERSION}"
         wget https://parallel-netcdf.github.io/Release/pnetcdf-${PNETCDF_VERSION}.tar.gz
         tar -xzf pnetcdf-${PNETCDF_VERSION}.tar.gz
@@ -48,6 +48,7 @@ jobs:
         export LDFLAGS="-L${NETCDF_DIR}/lib"
         #export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
         export LIBS="-lhdf5_openmpi_hl -lhdf5_openmpi -lm -lz"
+        which $CC
         ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 $NETCDF_EXTRA_CONFIG
         make -j 2
         sudo make install
@@ -79,7 +80,7 @@ jobs:
         # parallel (hdf5 for netcdf4, pnetcdf for netcdf3)
         cd ../examples
         #mpirun.mpich -np 4 python mpi_example.py
-        mpirun -np 4 --oversubscribe python mpi_example.py 
+        mpirun.openmpi -np 4 --oversubscribe python mpi_example.py 
         if [ $? -ne 0 ] ; then
           echo "hdf5 mpi test failed!"
           exit 1
@@ -87,7 +88,7 @@ jobs:
           echo "hdf5 mpi test passed!"
         fi
         #mpirun.mpich -np 4 python mpi_example_compressed.py
-        mpirun -np 4 --oversubscribe python mpi_example_compressed.py
+        mpirun.openmpi -np 4 --oversubscribe python mpi_example_compressed.py
         if [ $? -ne 0 ] ; then
           echo "hdf5 compressed mpi test failed!"
           exit 1
@@ -95,7 +96,7 @@ jobs:
           echo "hdf5 compressed mpi test passed!"
         fi
         #mpirun.mpich -np 4 python mpi_example.py NETCDF3_64BIT_DATA
-        mpirun -np 4 --oversubscribe python mpi_example.py NETCDF3_64BIT_DATA
+        mpirun.openmpi -np 4 --oversubscribe python mpi_example.py NETCDF3_64BIT_DATA
         if [ $? -ne 0 ] ; then
           echo "pnetcdf mpi test failed!"
           exit 1

From 8e943ac1d85028d44d5521a0e590af11d48e6a51 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 4 Mar 2025 17:11:23 -0700
Subject: [PATCH 1343/1504] update

---
 .github/workflows/build_latest.yml | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index d4378a3bc..f2e10b508 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -29,7 +29,9 @@ jobs:
     - name: Install Ubuntu Dependencies
       run: |
         sudo apt-get update
-        sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev openmpi-bin openmpi-common libopenmpi-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
+        sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev openmpi-bin openmpi-common libopenmpi-dev libhdf5-openmpi-dev ibcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
+        update-alternatives --get-selections | grep mpi
+        update-alternatives --query mpi
         update-alternatives --list mpirun
         echo "Download and build PnetCDF version ${PNETCDF_VERSION}"
         wget https://parallel-netcdf.github.io/Release/pnetcdf-${PNETCDF_VERSION}.tar.gz

From 75aa236f7f5506a79d23e2842a93c18906f2f2d3 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 5 Mar 2025 10:57:01 -0700
Subject: [PATCH 1344/1504] update

---
 .github/workflows/build_latest.yml | 11 ++++++-----
 1 file changed, 6 insertions(+), 5 deletions(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index f2e10b508..4744dff4a 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -10,7 +10,7 @@ jobs:
       NETCDF_DIR: ${{ github.workspace }}/..
       NETCDF_EXTRA_CONFIG: --enable-pnetcdf
       #CC: mpicc.mpich
-      CC: mpicc.openmpi
+      CC: mpicc
       #NO_NET: 1
     strategy:
       matrix:
@@ -29,7 +29,8 @@ jobs:
     - name: Install Ubuntu Dependencies
       run: |
         sudo apt-get update
-        sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev openmpi-bin openmpi-common libopenmpi-dev libhdf5-openmpi-dev ibcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
+        #sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev openmpi-bin openmpi-common libopenmpi-dev libhdf5-openmpi-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
+        sudo apt-get install openmpi-common libopenmpi-dev openmpi-bin libhdf5-openmpi-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
         update-alternatives --get-selections | grep mpi
         update-alternatives --query mpi
         update-alternatives --list mpirun
@@ -82,7 +83,7 @@ jobs:
         # parallel (hdf5 for netcdf4, pnetcdf for netcdf3)
         cd ../examples
         #mpirun.mpich -np 4 python mpi_example.py
-        mpirun.openmpi -np 4 --oversubscribe python mpi_example.py 
+        mpirun -np 4 --oversubscribe python mpi_example.py 
         if [ $? -ne 0 ] ; then
           echo "hdf5 mpi test failed!"
           exit 1
@@ -90,7 +91,7 @@ jobs:
           echo "hdf5 mpi test passed!"
         fi
         #mpirun.mpich -np 4 python mpi_example_compressed.py
-        mpirun.openmpi -np 4 --oversubscribe python mpi_example_compressed.py
+        mpirun -np 4 --oversubscribe python mpi_example_compressed.py
         if [ $? -ne 0 ] ; then
           echo "hdf5 compressed mpi test failed!"
           exit 1
@@ -98,7 +99,7 @@ jobs:
           echo "hdf5 compressed mpi test passed!"
         fi
         #mpirun.mpich -np 4 python mpi_example.py NETCDF3_64BIT_DATA
-        mpirun.openmpi -np 4 --oversubscribe python mpi_example.py NETCDF3_64BIT_DATA
+        mpirun -np 4 --oversubscribe python mpi_example.py NETCDF3_64BIT_DATA
         if [ $? -ne 0 ] ; then
           echo "pnetcdf mpi test failed!"
           exit 1

From aeebf6bffc67d8ec766147655c9c7a14ce5fd10d Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 5 Mar 2025 13:16:12 -0700
Subject: [PATCH 1345/1504] convert all tests to openmpi

---
 .github/workflows/build_latest.yml |  3 ---
 .github/workflows/build_master.yml | 12 ++++++++----
 .github/workflows/build_old.yml    | 15 ++++++++++-----
 3 files changed, 18 insertions(+), 12 deletions(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index 4744dff4a..596f13ecb 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -31,9 +31,6 @@ jobs:
         sudo apt-get update
         #sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev openmpi-bin openmpi-common libopenmpi-dev libhdf5-openmpi-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
         sudo apt-get install openmpi-common libopenmpi-dev openmpi-bin libhdf5-openmpi-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
-        update-alternatives --get-selections | grep mpi
-        update-alternatives --query mpi
-        update-alternatives --list mpirun
         echo "Download and build PnetCDF version ${PNETCDF_VERSION}"
         wget https://parallel-netcdf.github.io/Release/pnetcdf-${PNETCDF_VERSION}.tar.gz
         tar -xzf pnetcdf-${PNETCDF_VERSION}.tar.gz
diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 23b2248e6..cb3b294eb 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -6,7 +6,8 @@ jobs:
     runs-on: ubuntu-latest
     env:
       NETCDF_DIR: ${{ github.workspace }}/..
-      CC: mpicc.mpich
+      #CC: mpicc.mpich
+      CC: mpicc
       #NO_NET: 1
     strategy:
       matrix:
@@ -25,7 +26,8 @@ jobs:
     - name: Install Ubuntu Dependencies
       run: |
         sudo apt-get update
-        sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
+        #sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
+        sudo apt-get install openmpi-common libopenmpi-dev openmpi-bin libhdf5-openmpi-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
         echo "Download and build netCDF github master"
         git clone https://github.com/Unidata/netcdf-c
         pushd netcdf-c
@@ -65,14 +67,16 @@ jobs:
         python run_all.py
         # parallel
         cd ../examples
-        mpirun.mpich -np 4 python mpi_example.py
+        #mpirun.mpich -np 4 python mpi_example.py
+        mpirun -np 4 --oversubscribe python mpi_example.py 
         if [ $? -ne 0 ] ; then
           echo "hdf5 mpi test failed!"
           exit 1
         else
           echo "hdf5 mpi test passed!"
         fi
-        mpirun.mpich -np 4 python mpi_example_compressed.py
+        #mpirun.mpich -np 4 python mpi_example_compressed.py
+        mpirun -np 4 --oversubscribe python mpi_example_compressed.py 
         if [ $? -ne 0 ] ; then
           echo "hdf5 compressed mpi test failed!"
           exit 1
diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml
index e8d0a59b8..1b088dfdc 100644
--- a/.github/workflows/build_old.yml
+++ b/.github/workflows/build_old.yml
@@ -9,7 +9,8 @@ jobs:
       NETCDF_VERSION: 4.7.4
       NETCDF_DIR: ${{ github.workspace }}/..
       NETCDF_EXTRA_CONFIG: --enable-pnetcdf
-      CC: mpicc.mpich
+      #CC: mpicc.mpich
+      CC: mpicc
       #NO_NET: 1
     strategy:
       matrix:
@@ -28,7 +29,8 @@ jobs:
     - name: Install Ubuntu Dependencies
       run: |
         sudo apt-get update
-        sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
+        #sudo apt-get install mpich libmpich-dev libhdf5-mpich-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
+        sudo apt-get install openmpi-common libopenmpi-dev openmpi-bin libhdf5-openmpi-dev libcurl4-openssl-dev bzip2 libsnappy-dev libblosc-dev libzstd-dev
         echo "Download and build PnetCDF version ${PNETCDF_VERSION}"
         wget https://parallel-netcdf.github.io/Release/pnetcdf-${PNETCDF_VERSION}.tar.gz
         tar -xzf pnetcdf-${PNETCDF_VERSION}.tar.gz
@@ -75,21 +77,24 @@ jobs:
         python run_all.py
         # parallel (hdf5 for netcdf4, pnetcdf for netcdf3)
         cd ../examples
-        mpirun.mpich -np 4 python mpi_example.py
+        #mpirun.mpich -np 4 python mpi_example.py
+        mpirun -np 4 --oversubscribe python mpi_example.py 
         if [ $? -ne 0 ] ; then
           echo "hdf5 mpi test failed!"
           exit 1
         else
           echo "hdf5 mpi test passed!"
         fi
-        mpirun.mpich -np 4 python mpi_example_compressed.py
+        #mpirun.mpich -np 4 python mpi_example_compressed.py
+        mpirun -np 4 --oversubscribe python mpi_example_compressed.py 
         if [ $? -ne 0 ] ; then
           echo "hdf5 compressed mpi test failed!"
           exit 1
         else
           echo "hdf5 compressed mpi test passed!"
         fi
-        mpirun.mpich -np 4 python mpi_example.py NETCDF3_64BIT_DATA
+        #mpirun.mpich -np 4 python mpi_example.py NETCDF3_64BIT_DATA
+        mpirun -np 4 --oversubscribe python mpi_example.py NETCDF3_64BIT_DATA
         if [ $? -ne 0 ] ; then
           echo "pnetcdf mpi test failed!"
           exit 1

From 1bfb53780f529aeb8b3424338df0a6ac28e3bc45 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 5 Mar 2025 13:23:57 -0700
Subject: [PATCH 1346/1504] use openmpi hdf5 libs

---
 .github/workflows/build_master.yml | 3 ++-
 .github/workflows/build_old.yml    | 3 ++-
 2 files changed, 4 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index cb3b294eb..3bc7aa9e4 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -33,7 +33,8 @@ jobs:
         pushd netcdf-c
         export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include"
         export LDFLAGS="-L${NETCDF_DIR}/lib"
-        export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
+        #export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
+        export LIBS="-lhdf5_openmpi_hl -lhdf5_openmpi -lm -lz"
         autoreconf -i
         ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 
         make -j 2
diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml
index 1b088dfdc..b2fd31b5c 100644
--- a/.github/workflows/build_old.yml
+++ b/.github/workflows/build_old.yml
@@ -46,7 +46,8 @@ jobs:
         pushd netcdf-c-${NETCDF_VERSION}
         export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include"
         export LDFLAGS="-L${NETCDF_DIR}/lib"
-        export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
+        #export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
+        export LIBS="-lhdf5_openmpi_hl -lhdf5_openmpi -lm -lz"
         ./configure --prefix $NETCDF_DIR --enable-netcdf-4 --enable-shared --enable-dap --enable-parallel4 $NETCDF_EXTRA_CONFIG
         make -j 2
         sudo make install

From ed39d92239365a346df1221357d5969bdd44e041 Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Wed, 5 Mar 2025 13:28:05 -0700
Subject: [PATCH 1347/1504] update

---
 .github/workflows/build_master.yml | 5 +++--
 .github/workflows/build_old.yml    | 5 +++--
 2 files changed, 6 insertions(+), 4 deletions(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 3bc7aa9e4..24328329d 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -11,7 +11,7 @@ jobs:
       #NO_NET: 1
     strategy:
       matrix:
-        python-version: ["3.12"]
+        python-version: ["3.13"]
     steps:
 
     - uses: actions/checkout@v4
@@ -31,7 +31,8 @@ jobs:
         echo "Download and build netCDF github master"
         git clone https://github.com/Unidata/netcdf-c
         pushd netcdf-c
-        export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include"
+        #export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include"
+        export CPPFLAGS="-I/usr/include/hdf5/openmpi -I${NETCDF_DIR}/include"
         export LDFLAGS="-L${NETCDF_DIR}/lib"
         #export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
         export LIBS="-lhdf5_openmpi_hl -lhdf5_openmpi -lm -lz"
diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml
index b2fd31b5c..cab5984bd 100644
--- a/.github/workflows/build_old.yml
+++ b/.github/workflows/build_old.yml
@@ -14,7 +14,7 @@ jobs:
       #NO_NET: 1
     strategy:
       matrix:
-        python-version: ["3.12"]
+        python-version: ["3.13"]
     steps:
 
     - uses: actions/checkout@v4
@@ -44,7 +44,8 @@ jobs:
         wget https://www.gfd-dennou.org/arch/netcdf/unidata-mirror/netcdf-c-${NETCDF_VERSION}.tar.gz
         tar -xzf netcdf-c-${NETCDF_VERSION}.tar.gz
         pushd netcdf-c-${NETCDF_VERSION}
-        export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include"
+        #export CPPFLAGS="-I/usr/include/hdf5/mpich -I${NETCDF_DIR}/include"
+        export CPPFLAGS="-I/usr/include/hdf5/openmpi -I${NETCDF_DIR}/include"
         export LDFLAGS="-L${NETCDF_DIR}/lib"
         #export LIBS="-lhdf5_mpich_hl -lhdf5_mpich -lm -lz"
         export LIBS="-lhdf5_openmpi_hl -lhdf5_openmpi -lm -lz"

From e585c037d8080a17d81675d624db206abaeb9556 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 17 Mar 2025 03:09:46 +0000
Subject: [PATCH 1348/1504] Bump pypa/cibuildwheel from 2.23.0 to 2.23.1 in the
 github-actions group

Bumps the github-actions group with 1 update: [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel).


Updates `pypa/cibuildwheel` from 2.23.0 to 2.23.1
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/v2.23.1/docs/changelog.md)
- [Commits](https://github.com/pypa/cibuildwheel/compare/v2.23.0...v2.23.1)

---
updated-dependencies:
- dependency-name: pypa/cibuildwheel
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/cibuildwheel.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 877e76444..a39709d2b 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -92,7 +92,7 @@ jobs:
         echo "Setting CIBW_SKIP=$CIBW_SKIP"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
-      uses: pypa/cibuildwheel@v2.23.0
+      uses: pypa/cibuildwheel@v2.23.1
       env:
         CIBW_SKIP: ${{ env.CIBW_SKIP }}
         CIBW_ARCHS: ${{ matrix.arch }}

From 37431b7269adde86b529e34be8b7a716af243d84 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Tue, 25 Mar 2025 03:59:18 +0000
Subject: [PATCH 1349/1504] Bump pypa/cibuildwheel from 2.23.1 to 2.23.2 in the
 github-actions group

Bumps the github-actions group with 1 update: [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel).


Updates `pypa/cibuildwheel` from 2.23.1 to 2.23.2
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md)
- [Commits](https://github.com/pypa/cibuildwheel/compare/v2.23.1...v2.23.2)

---
updated-dependencies:
- dependency-name: pypa/cibuildwheel
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/cibuildwheel.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index a39709d2b..a9aea462e 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -92,7 +92,7 @@ jobs:
         echo "Setting CIBW_SKIP=$CIBW_SKIP"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
-      uses: pypa/cibuildwheel@v2.23.1
+      uses: pypa/cibuildwheel@v2.23.2
       env:
         CIBW_SKIP: ${{ env.CIBW_SKIP }}
         CIBW_ARCHS: ${{ matrix.arch }}

From a9e9b04908fad663a621542b11152e70c3767bbd Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 28 Apr 2025 03:25:44 +0000
Subject: [PATCH 1350/1504] Bump pypa/cibuildwheel from 2.23.2 to 2.23.3 in the
 github-actions group

Bumps the github-actions group with 1 update: [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel).


Updates `pypa/cibuildwheel` from 2.23.2 to 2.23.3
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md)
- [Commits](https://github.com/pypa/cibuildwheel/compare/v2.23.2...v2.23.3)

---
updated-dependencies:
- dependency-name: pypa/cibuildwheel
  dependency-version: 2.23.3
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/cibuildwheel.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index a9aea462e..029e02bc4 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -92,7 +92,7 @@ jobs:
         echo "Setting CIBW_SKIP=$CIBW_SKIP"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
-      uses: pypa/cibuildwheel@v2.23.2
+      uses: pypa/cibuildwheel@v2.23.3
       env:
         CIBW_SKIP: ${{ env.CIBW_SKIP }}
         CIBW_ARCHS: ${{ matrix.arch }}

From b8514479047ef442f72162a60a12a8c69349231e Mon Sep 17 00:00:00 2001
From: Filipe Fernandes 
Date: Mon, 28 Apr 2025 11:57:02 -0300
Subject: [PATCH 1351/1504] fix latest pip egg deprecation

---
 .github/workflows/build_latest.yml | 5 +++--
 .github/workflows/build_master.yml | 4 ++--
 .github/workflows/build_old.yml    | 5 +++--
 .github/workflows/cibuildwheel.yml | 6 +++---
 pyproject.toml                     | 7 +++++--
 setup.py                           | 9 ++++++++-
 6 files changed, 24 insertions(+), 12 deletions(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index 596f13ecb..79a9a26e5 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -63,13 +63,14 @@ jobs:
     - name: Install python dependencies via pip
       run: |
         python -m pip install --upgrade pip
-        pip install numpy cython cftime pytest twine wheel check-manifest mpi4py typing-extensions
+        python -m pip install numpy cython cftime pytest twine wheel check-manifest mpi4py typing-extensions
 
     - name: Install netcdf4-python
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
         export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c-${NETCDF_VERSION}/plugins/plugindir
-        python setup.py install
+        python -m pip install . --no-build-isolation
+
     - name: Test
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 24328329d..30ee69b5b 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -51,13 +51,13 @@ jobs:
     - name: Install python dependencies via pip
       run: |
         python -m pip install --upgrade pip
-        pip install numpy cython cftime pytest twine wheel check-manifest mpi4py mypy types-setuptools typing-extensions
+        python -m pip install numpy cython cftime pytest twine wheel check-manifest mpi4py mypy types-setuptools typing-extensions
 
     - name: Install netcdf4-python
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
         export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c/plugins/plugindir
-        python setup.py install
+        python -m pip install . --no-build-isolation
 
     - name: Test
       run: |
diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml
index cab5984bd..ddf8cdeba 100644
--- a/.github/workflows/build_old.yml
+++ b/.github/workflows/build_old.yml
@@ -63,13 +63,14 @@ jobs:
     - name: Install python dependencies via pip
       run: |
         python -m pip install --upgrade pip
-        pip install numpy cython cftime pytest twine wheel check-manifest mpi4py typing-extensions
+        python -m pip install numpy cython cftime pytest twine wheel check-manifest mpi4py typing-extensions
 
     - name: Install netcdf4-python
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
         export NETCDF_PLUGIN_DIR=${{ github.workspace }}/netcdf-c-${NETCDF_VERSION}/plugins/plugindir
-        python setup.py install
+        python -m pip install . --no-build-isolation
+
     - name: Test
       run: |
         export PATH=${NETCDF_DIR}/bin:${PATH} 
diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index a9aea462e..0a5f1e26f 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -84,9 +84,9 @@ jobs:
       # These needs to rotate every new Python release.
       run: |
         if [[ "${{ github.event_name }}" == "pull_request" ]]; then
-          CIBW_SKIP="pp* cp36-* cp37-* *-musllinux* cp39-* cp310-* cp311-*"
+          CIBW_SKIP="pp* cp36-* cp37-* cp38-* *-musllinux* cp39-* cp310-* cp311-* cp312-*"
         else
-          CIBW_SKIP="pp* cp36-* cp37-* *-musllinux*"
+          CIBW_SKIP="pp* cp36-* cp37-* cp38-* *-musllinux*"
         fi
         echo "CIBW_SKIP=$CIBW_SKIP" >> $GITHUB_ENV
         echo "Setting CIBW_SKIP=$CIBW_SKIP"
@@ -100,7 +100,7 @@ jobs:
         CIBW_MANYLINUX_X86_64_IMAGE: ghcr.io/ocefpaf/manylinux2014_x86_64-netcdf
         CIBW_MANYLINUX_AARCH64_IMAGE: ghcr.io/ocefpaf/manylinux2014_aarch64-netcdf
         # Emulation testing is slow, testing only latest Python.
-        CIBW_TEST_SKIP: "cp38-*_aarch64 cp39-*_aarch64 cp310-*_aarch64 cp311-*_aarch64"
+        CIBW_TEST_SKIP: "cp39-*_aarch64 cp310-*_aarch64 cp311-*_aarch64 cp312-*_aarch64"
         CIBW_ENVIRONMENT: ${{ matrix.CIBW_ENVIRONMENT }}
         CIBW_BEFORE_BUILD_MACOS: brew install hdf5 netcdf
         CIBW_TEST_REQUIRES: pytest cython packaging typing-extensions
diff --git a/pyproject.toml b/pyproject.toml
index c577e761a..63f1ff788 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -13,7 +13,7 @@ description = "Provides an object-oriented python interface to the netCDF versio
 authors = [
   {name = "Jeff Whitaker", email = "jeffrey.s.whitaker@noaa.gov"},
 ]
-requires-python = ">=3.8"
+requires-python = ">=3.9"
 keywords = [
     "numpy", "netcdf", "data", "science", "network", "oceanography",
     "meteorology", "climate",
@@ -22,11 +22,11 @@ license = {text = "MIT"}
 classifiers = [
     "Development Status :: 3 - Alpha",
     "Programming Language :: Python :: 3",
-    "Programming Language :: Python :: 3.8",
     "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
+    "Programming Language :: Python :: 3.13",
     "Intended Audience :: Science/Research",
     "License :: OSI Approved :: MIT License",
     "Topic :: Software Development :: Libraries :: Python Modules",
@@ -46,6 +46,9 @@ tests = [
   "packaging",
   "pytest",
 ]
+parallel = [
+  "mpi4py",
+]
 
 [project.readme]
 text = """\
diff --git a/setup.py b/setup.py
index b17f09ef5..c5318ad4f 100644
--- a/setup.py
+++ b/setup.py
@@ -7,6 +7,8 @@
 from setuptools.dist import Distribution
 from typing import List
 
+
+
 open_kwargs = {'encoding': 'utf-8'}
 
 
@@ -397,7 +399,12 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     print(f"netcdf lib {has_has_not} parallel functions")
 
     if has_parallel_support:
-        import mpi4py
+        try:
+            import mpi4py
+        except ImportError:
+            msg = "Parallel support requires mpi4py but it is not installed."
+            raise ImportError(msg)
+
         inc_dirs.append(mpi4py.get_include())
         # mpi_incdir should not be needed if using nc-config
         # (should be included in nc-config --cflags)

From 08b36ad08b4ecc05e41dc884d3fe41b3cbf6b3e0 Mon Sep 17 00:00:00 2001
From: Jeffrey Whitaker 
Date: Thu, 15 May 2025 13:10:53 -0600
Subject: [PATCH 1352/1504] update email

---
 pyproject.toml           | 2 +-
 src/netCDF4/_netCDF4.pyx | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 63f1ff788..c4e44e085 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -11,7 +11,7 @@ build-backend = "setuptools.build_meta"
 name = "netCDF4"
 description = "Provides an object-oriented python interface to the netCDF version 4 library"
 authors = [
-  {name = "Jeff Whitaker", email = "jeffrey.s.whitaker@noaa.gov"},
+  {name = "Jeff Whitaker", email = "whitaker.jeffrey@gmail.com"},
 ]
 requires-python = ">=3.9"
 keywords = [
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 19a1186e3..d1081229a 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1255,7 +1255,7 @@ Support for complex numbers is handled via the
 further details.
 
 
-**contact**: Jeffrey Whitaker 
+**contact**: Jeffrey Whitaker 
 
 **copyright**: 2008 by Jeffrey Whitaker.
 

From 7b2adc6de36c7dfe3c2b81087635f7ee1e12410c Mon Sep 17 00:00:00 2001
From: Jeffrey Whitaker 
Date: Fri, 6 Jun 2025 14:36:53 -0600
Subject: [PATCH 1353/1504] allow non-unitary strides when slicing vlen vars

---
 Changelog                |  1 +
 src/netCDF4/_netCDF4.pyx | 24 ++++++++++++------------
 test/test_vlen.py        |  6 ++++++
 3 files changed, 19 insertions(+), 12 deletions(-)

diff --git a/Changelog b/Changelog
index bcf2550e7..2aeb0efc2 100644
--- a/Changelog
+++ b/Changelog
@@ -6,6 +6,7 @@
    perform a membership operation on a Dataset (issue #1383)
  * fix type hint for createEnumType (issue #1378)
  * add python 3.13 to windows wheel builds (PR #1377)
+ * allow slicing of vlen and string variables with non-unitary strides (issue #1408).
 
  version 1.7.2 (tag v1.7.2rel)
  =============================
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index d1081229a..ff79ebc1f 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -5966,10 +5966,10 @@ NC_CHAR).
                         ierr = nc_put_vara(self._grpid, self._varid,
                                            startp, countp, strdata)
                 else:
-                    raise IndexError('strides must all be 1 for string variables')
-                    #with nogil:
-                    #    ierr = nc_put_vars(self._grpid, self._varid,
-                    #                       startp, countp, stridep, strdata)
+                    #raise IndexError('strides must all be 1 for string variables')
+                    with nogil:
+                        ierr = nc_put_vars(self._grpid, self._varid,
+                                           startp, countp, stridep, strdata)
                 _ensure_nc_success(ierr)
                 free(strdata)
             else:
@@ -5995,10 +5995,10 @@ NC_CHAR).
                         ierr = nc_put_vara(self._grpid, self._varid,
                                            startp, countp, vldata)
                 else:
-                    raise IndexError('strides must all be 1 for vlen variables')
-                    #with nogil:
-                    #    ierr = nc_put_vars(self._grpid, self._varid,
-                    #                       startp, countp, stridep, vldata)
+                    #raise IndexError('strides must all be 1 for vlen variables')
+                    with nogil:
+                        ierr = nc_put_vars(self._grpid, self._varid,
+                                           startp, countp, stridep, vldata)
                 _ensure_nc_success(ierr)
                 # free the pointer array.
                 free(vldata)
@@ -6130,10 +6130,10 @@ NC_CHAR).
                         ierr = nc_get_vara(self._grpid, self._varid,
                                            startp, countp, vldata)
                 else:
-                    raise IndexError('strides must all be 1 for vlen variables')
-                    #with nogil:
-                    #    ierr = nc_get_vars(self._grpid, self._varid,
-                    #                       startp, countp, stridep, vldata)
+                    #raise IndexError('strides must all be 1 for vlen variables')
+                    with nogil:
+                        ierr = nc_get_vars(self._grpid, self._varid,
+                                           startp, countp, stridep, vldata)
                 if ierr == NC_EINVALCOORDS:
                     raise IndexError
                 elif ierr != NC_NOERR:
diff --git a/test/test_vlen.py b/test/test_vlen.py
index 1e1d89f72..cdd03f05e 100644
--- a/test/test_vlen.py
+++ b/test/test_vlen.py
@@ -76,6 +76,12 @@ def runTest(self):
                 assert_array_equal(data2[j,i], data[j,i])
                 assert datas[j,i] == data2s[j,i]
         assert_array_equal(datas, vs_alt[:])
+        # issue #1408
+        data2a = data2[::2,::2]
+        data2b = v[::2,::2]
+        for i in range(nlons//2):
+            for j in range(nlats//2):
+                assert_array_equal(data2a[j,i], data2b[j,i])
         f.close()
 
 

From ab57950a385b53f147861c2f9f4457a17a8d92e8 Mon Sep 17 00:00:00 2001
From: Jeffrey Whitaker 
Date: Fri, 6 Jun 2025 14:42:07 -0600
Subject: [PATCH 1354/1504] update

---
 test/test_vlen.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/test/test_vlen.py b/test/test_vlen.py
index cdd03f05e..770c7ccbb 100644
--- a/test/test_vlen.py
+++ b/test/test_vlen.py
@@ -79,9 +79,12 @@ def runTest(self):
         # issue #1408
         data2a = data2[::2,::2]
         data2b = v[::2,::2]
+        data2sa = data2s[::2,::2]
+        data2sb = vs[::2,::2]
         for i in range(nlons//2):
             for j in range(nlats//2):
                 assert_array_equal(data2a[j,i], data2b[j,i])
+                assert_array_equal(data2sa[j,i], data2sb[j,i])
         f.close()
 
 

From 8170fcf8487ebb84c3a06b38cd307c359b2f21da Mon Sep 17 00:00:00 2001
From: Jeffrey Whitaker 
Date: Fri, 6 Jun 2025 14:44:51 -0600
Subject: [PATCH 1355/1504] update

---
 src/netCDF4/_netCDF4.pyx | 11 +++--------
 1 file changed, 3 insertions(+), 8 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index ff79ebc1f..80677e970 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -5966,7 +5966,6 @@ NC_CHAR).
                         ierr = nc_put_vara(self._grpid, self._varid,
                                            startp, countp, strdata)
                 else:
-                    #raise IndexError('strides must all be 1 for string variables')
                     with nogil:
                         ierr = nc_put_vars(self._grpid, self._varid,
                                            startp, countp, stridep, strdata)
@@ -5995,7 +5994,6 @@ NC_CHAR).
                         ierr = nc_put_vara(self._grpid, self._varid,
                                            startp, countp, vldata)
                 else:
-                    #raise IndexError('strides must all be 1 for vlen variables')
                     with nogil:
                         ierr = nc_put_vars(self._grpid, self._varid,
                                            startp, countp, stridep, vldata)
@@ -6091,11 +6089,9 @@ NC_CHAR).
                         ierr = nc_get_vara(self._grpid, self._varid,
                                            startp, countp, strdata)
                 else:
-                    # FIXME: is this a bug in netCDF4?
-                    raise IndexError('strides must all be 1 for string variables')
-                    #with nogil:
-                    #    ierr = nc_get_vars(self._grpid, self._varid,
-                    #                       startp, countp, stridep, strdata)
+                    with nogil:
+                        ierr = nc_get_vars(self._grpid, self._varid,
+                                           startp, countp, stridep, strdata)
                 if ierr == NC_EINVALCOORDS:
                     raise IndexError
                 elif ierr != NC_NOERR:
@@ -6130,7 +6126,6 @@ NC_CHAR).
                         ierr = nc_get_vara(self._grpid, self._varid,
                                            startp, countp, vldata)
                 else:
-                    #raise IndexError('strides must all be 1 for vlen variables')
                     with nogil:
                         ierr = nc_get_vars(self._grpid, self._varid,
                                            startp, countp, stridep, vldata)

From 337a0f85be141592d61c0ecac1e273f1aabe55dc Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Thu, 12 Jun 2025 03:41:36 +0000
Subject: [PATCH 1356/1504] Bump pypa/cibuildwheel from 2.23.3 to 3.0.0 in the
 github-actions group

Bumps the github-actions group with 1 update: [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel).


Updates `pypa/cibuildwheel` from 2.23.3 to 3.0.0
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md)
- [Commits](https://github.com/pypa/cibuildwheel/compare/v2.23.3...v3.0.0)

---
updated-dependencies:
- dependency-name: pypa/cibuildwheel
  dependency-version: 3.0.0
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/cibuildwheel.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 1fd998214..d96c85099 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -92,7 +92,7 @@ jobs:
         echo "Setting CIBW_SKIP=$CIBW_SKIP"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
-      uses: pypa/cibuildwheel@v2.23.3
+      uses: pypa/cibuildwheel@v3.0.0
       env:
         CIBW_SKIP: ${{ env.CIBW_SKIP }}
         CIBW_ARCHS: ${{ matrix.arch }}

From 7d6cb4d9df9e5a0c4275e9486f58d63bdf568d8e Mon Sep 17 00:00:00 2001
From: DWesl <22566757+DWesl@users.noreply.github.com>
Date: Sun, 29 Jun 2025 08:13:49 -0400
Subject: [PATCH 1357/1504] BLD: Get netCDF-python compiling on Cygwin.

Cygwin, on Windows, has no concept of RPATH, and requires
all symbols be resolved at link time.
---
 setup.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index c5318ad4f..4bd0dbda2 100644
--- a/setup.py
+++ b/setup.py
@@ -262,6 +262,8 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     for direc in inc_dirs:
         hdf5_version = get_hdf5_version(direc)
         if hdf5_version is not None:
+            if sys.platform == "cygwin":
+                _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs)
             break
     # if hdf5 not found, search other standard locations (including those specified in env vars).
     if hdf5_version is None:
@@ -353,7 +355,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         lib_dirs.append(curl_libdir)
         inc_dirs.append(curl_incdir)
 
-if sys.platform == 'win32':
+if sys.platform == 'win32' or sys.platform == 'cygwin':
     runtime_lib_dirs = []
 else:
     runtime_lib_dirs = lib_dirs

From ea0bac630dd1e8ff748ce1b68dbc62149c7f685c Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 7 Jul 2025 04:35:16 +0000
Subject: [PATCH 1358/1504] Bump pypa/cibuildwheel from 3.0.0 to 3.0.1 in the
 github-actions group

Bumps the github-actions group with 1 update: [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel).


Updates `pypa/cibuildwheel` from 3.0.0 to 3.0.1
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md)
- [Commits](https://github.com/pypa/cibuildwheel/compare/v3.0.0...v3.0.1)

---
updated-dependencies:
- dependency-name: pypa/cibuildwheel
  dependency-version: 3.0.1
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/cibuildwheel.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index d96c85099..c6ce224b0 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -92,7 +92,7 @@ jobs:
         echo "Setting CIBW_SKIP=$CIBW_SKIP"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
-      uses: pypa/cibuildwheel@v3.0.0
+      uses: pypa/cibuildwheel@v3.0.1
       env:
         CIBW_SKIP: ${{ env.CIBW_SKIP }}
         CIBW_ARCHS: ${{ matrix.arch }}

From df0bf9848b9771c310d5d4f8fbbde7b404d8e940 Mon Sep 17 00:00:00 2001
From: Jeffrey Whitaker 
Date: Sat, 2 Aug 2025 12:22:19 -0600
Subject: [PATCH 1359/1504] test python 3.14

---
 .github/workflows/build_master.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 30ee69b5b..d55f3a9a0 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -11,7 +11,7 @@ jobs:
       #NO_NET: 1
     strategy:
       matrix:
-        python-version: ["3.13"]
+        python-version: ["3.14-dev"]
     steps:
 
     - uses: actions/checkout@v4

From 2d5b802d9ca61e586d24942f65fd9d7241f9da35 Mon Sep 17 00:00:00 2001
From: Jeffrey Whitaker 
Date: Sat, 2 Aug 2025 12:39:49 -0600
Subject: [PATCH 1360/1504] debug print

---
 test/test_fancyslicing.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/test/test_fancyslicing.py b/test/test_fancyslicing.py
index c3e89fd1b..405537491 100644
--- a/test/test_fancyslicing.py
+++ b/test/test_fancyslicing.py
@@ -144,6 +144,9 @@ def test_get(self):
 
         # slicing with all False booleans (PR #1197)
         iby[:] = False
+        print(ibx)
+        print(iby)
+        print(ibz)
         data = v[ibx,iby,ibz]
         assert data.size == 0 
 

From 3dfea45869a5b2088e0cc2d7f1af1261567ec384 Mon Sep 17 00:00:00 2001
From: Jeffrey Whitaker 
Date: Sat, 2 Aug 2025 12:58:54 -0600
Subject: [PATCH 1361/1504] update

---
 src/netCDF4/utils.py      | 5 ++++-
 test/test_fancyslicing.py | 3 ---
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/src/netCDF4/utils.py b/src/netCDF4/utils.py
index 1d2f52529..a373d0b32 100644
--- a/src/netCDF4/utils.py
+++ b/src/netCDF4/utils.py
@@ -426,7 +426,10 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
 
         #    ITERABLE    #
         elif np.iterable(e) and np.array(e).dtype.kind in 'i':  # Sequence of integers
-            start[...,i] = np.apply_along_axis(lambda x: e*x, i, np.ones(sdim[:-1]))
+            if not e.size
+                start[...,i] = np.empty(0)
+            else:
+                start[...,i] = np.apply_along_axis(lambda x: e*x, i, np.ones(sdim[:-1]))
             indices[...,i] = np.apply_along_axis(lambda x: np.arange(sdim[i])*x, i, np.ones(sdim[:-1], int))
 
             count[...,i] = 1
diff --git a/test/test_fancyslicing.py b/test/test_fancyslicing.py
index 405537491..c3e89fd1b 100644
--- a/test/test_fancyslicing.py
+++ b/test/test_fancyslicing.py
@@ -144,9 +144,6 @@ def test_get(self):
 
         # slicing with all False booleans (PR #1197)
         iby[:] = False
-        print(ibx)
-        print(iby)
-        print(ibz)
         data = v[ibx,iby,ibz]
         assert data.size == 0 
 

From 052d994b95a4162898ff6135e527488b56fe5658 Mon Sep 17 00:00:00 2001
From: Jeffrey Whitaker 
Date: Sat, 2 Aug 2025 13:17:16 -0600
Subject: [PATCH 1362/1504] update

---
 src/netCDF4/utils.py | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/src/netCDF4/utils.py b/src/netCDF4/utils.py
index a373d0b32..060b7e0d0 100644
--- a/src/netCDF4/utils.py
+++ b/src/netCDF4/utils.py
@@ -426,9 +426,7 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
 
         #    ITERABLE    #
         elif np.iterable(e) and np.array(e).dtype.kind in 'i':  # Sequence of integers
-            if not e.size
-                start[...,i] = np.empty(0)
-            else:
+            if start[...,i].size:
                 start[...,i] = np.apply_along_axis(lambda x: e*x, i, np.ones(sdim[:-1]))
             indices[...,i] = np.apply_along_axis(lambda x: np.arange(sdim[i])*x, i, np.ones(sdim[:-1], int))
 

From ca588e68c8849e41559b76cbf8a000aae2a3ae5c Mon Sep 17 00:00:00 2001
From: Jeffrey Whitaker 
Date: Sat, 2 Aug 2025 13:34:13 -0600
Subject: [PATCH 1363/1504] update

---
 src/netCDF4/utils.py | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git a/src/netCDF4/utils.py b/src/netCDF4/utils.py
index 060b7e0d0..5aaf67559 100644
--- a/src/netCDF4/utils.py
+++ b/src/netCDF4/utils.py
@@ -428,10 +428,9 @@ def _StartCountStride(elem, shape, dimensions=None, grp=None, datashape=None,\
         elif np.iterable(e) and np.array(e).dtype.kind in 'i':  # Sequence of integers
             if start[...,i].size:
                 start[...,i] = np.apply_along_axis(lambda x: e*x, i, np.ones(sdim[:-1]))
-            indices[...,i] = np.apply_along_axis(lambda x: np.arange(sdim[i])*x, i, np.ones(sdim[:-1], int))
-
-            count[...,i] = 1
-            stride[...,i] = 1
+                indices[...,i] = np.apply_along_axis(lambda x: np.arange(sdim[i])*x, i, np.ones(sdim[:-1], int))
+                count[...,i] = 1
+                stride[...,i] = 1
 
         #   all that's left is SCALAR INTEGER    #
         else:

From 9be7ad20a72fd4b7ecf5c77aa403b6774de442dc Mon Sep 17 00:00:00 2001
From: Jeffrey Whitaker 
Date: Sat, 2 Aug 2025 13:40:17 -0600
Subject: [PATCH 1364/1504] debug print

---
 test/test_open_mem.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/test/test_open_mem.py b/test/test_open_mem.py
index eeba7a391..15060e194 100644
--- a/test/test_open_mem.py
+++ b/test/test_open_mem.py
@@ -18,6 +18,7 @@ def test_mem_open(self):
                 return
 
             # Needs: https://github.com/Unidata/netcdf-c/pull/400
+            print(netCDF4.__netcdf4libversion__, netCDF4.__netcdf4libversion__ < '4.4.1.2')
             if netCDF4.__netcdf4libversion__ < '4.4.1.2':
                 with self.assertRaises(OSError):
                     netCDF4.Dataset('foo_bar', memory=nc_bytes)

From c8325b63c52d4d61764ae085bec13f66ce7e708d Mon Sep 17 00:00:00 2001
From: Jeffrey Whitaker 
Date: Sat, 2 Aug 2025 13:48:01 -0600
Subject: [PATCH 1365/1504] remove version check

---
 test/test_open_mem.py | 7 -------
 1 file changed, 7 deletions(-)

diff --git a/test/test_open_mem.py b/test/test_open_mem.py
index 15060e194..5a9d65e32 100644
--- a/test/test_open_mem.py
+++ b/test/test_open_mem.py
@@ -17,13 +17,6 @@ def test_mem_open(self):
                     netCDF4.Dataset('foo_bar', memory=nc_bytes)
                 return
 
-            # Needs: https://github.com/Unidata/netcdf-c/pull/400
-            print(netCDF4.__netcdf4libversion__, netCDF4.__netcdf4libversion__ < '4.4.1.2')
-            if netCDF4.__netcdf4libversion__ < '4.4.1.2':
-                with self.assertRaises(OSError):
-                    netCDF4.Dataset('foo_bar', memory=nc_bytes)
-                return
-
             with netCDF4.Dataset('foo_bar', memory=nc_bytes) as nc:
                 assert nc.filepath() == 'foo_bar'
                 assert nc.project_summary == 'Dummy netCDF file'

From 2db79916e0195321cb747343134470e4348c46af Mon Sep 17 00:00:00 2001
From: Jeffrey Whitaker 
Date: Sat, 2 Aug 2025 14:00:38 -0600
Subject: [PATCH 1366/1504] remove warning message

---
 src/netCDF4/_netCDF4.pyx | 11 -----------
 1 file changed, 11 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 80677e970..b8e5bad0d 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1492,17 +1492,6 @@ _needsworkaround_issue485 = __netcdf4libversion__ < "4.4.0" or \
                (__netcdf4libversion__.startswith("4.4.0") and \
                 "-development" in __netcdf4libversion__)
 
-# issue warning for hdf5 1.10 (issue #549)
-if __netcdf4libversion__[0:5] < "4.4.1" and\
-   __hdf5libversion__.startswith("1.10"):
-    msg = """
-WARNING: Backwards incompatible files will be created with HDF5 1.10.x
-and netCDF < 4.4.1. Upgrading to netCDF4 >= 4.4.1 or downgrading to
-to HDF5 version 1.8.x is highly recommended
-(see https://github.com/Unidata/netcdf-c/issues/250)."""
-    warnings.warn(msg)
-
-
 class NetCDF4MissingFeatureException(Exception):
     """Custom exception when trying to use features missing from the linked netCDF library"""
     def __init__(self, feature: str, version: str):

From f06ed16cee389329793f1c8a6a5bfaba74a28a1a Mon Sep 17 00:00:00 2001
From: Jeffrey Whitaker 
Date: Sat, 2 Aug 2025 14:06:46 -0600
Subject: [PATCH 1367/1504] update

---
 .github/workflows/build_latest.yml | 2 +-
 .github/workflows/build_master.yml | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index 79a9a26e5..a3bc966db 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -14,7 +14,7 @@ jobs:
       #NO_NET: 1
     strategy:
       matrix:
-        python-version: ["3.13"]
+        python-version: ["3.13" "3.14-dev"]
     steps:
 
     - uses: actions/checkout@v4
diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index d55f3a9a0..30ee69b5b 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -11,7 +11,7 @@ jobs:
       #NO_NET: 1
     strategy:
       matrix:
-        python-version: ["3.14-dev"]
+        python-version: ["3.13"]
     steps:
 
     - uses: actions/checkout@v4

From 00d71fdfdcba802139cd397d34636a09133d9d89 Mon Sep 17 00:00:00 2001
From: Jeffrey Whitaker 
Date: Sat, 2 Aug 2025 14:18:33 -0600
Subject: [PATCH 1368/1504] update

---
 .github/workflows/build_latest.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index a3bc966db..bc8a2d0f6 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -14,7 +14,7 @@ jobs:
       #NO_NET: 1
     strategy:
       matrix:
-        python-version: ["3.13" "3.14-dev"]
+        python-version: ["3.13", "3.14-dev"]
     steps:
 
     - uses: actions/checkout@v4

From c335f0d2c6d43ba1ec31914e6d6ca9144e71b160 Mon Sep 17 00:00:00 2001
From: Filipe Fernandes 
Date: Fri, 1 Aug 2025 08:43:00 -0300
Subject: [PATCH 1369/1504] skip cp314t and, bump to cp314 on PRs

---
 .github/workflows/cibuildwheel.yml | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index c6ce224b0..05fc69bb3 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -84,21 +84,21 @@ jobs:
       # These needs to rotate every new Python release.
       run: |
         if [[ "${{ github.event_name }}" == "pull_request" ]]; then
-          CIBW_SKIP="pp* cp36-* cp37-* cp38-* *-musllinux* cp39-* cp310-* cp311-* cp312-*"
+          CIBW_SKIP="pp* cp36-* cp37-* cp38-* cp314t-* *-musllinux* cp39-* cp310-* cp311-* cp312-* cp313-*"
         else
-          CIBW_SKIP="pp* cp36-* cp37-* cp38-* *-musllinux*"
+          CIBW_SKIP="pp* cp36-* cp37-* cp38-* cp314t-* *-musllinux*"
         fi
         echo "CIBW_SKIP=$CIBW_SKIP" >> $GITHUB_ENV
         echo "Setting CIBW_SKIP=$CIBW_SKIP"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
-      uses: pypa/cibuildwheel@v3.0.1
+      uses: pypa/cibuildwheel@v3.1.0
       env:
         CIBW_SKIP: ${{ env.CIBW_SKIP }}
         CIBW_ARCHS: ${{ matrix.arch }}
         CIBW_BUILD_FRONTEND: build
-        CIBW_MANYLINUX_X86_64_IMAGE: ghcr.io/ocefpaf/manylinux2014_x86_64-netcdf
-        CIBW_MANYLINUX_AARCH64_IMAGE: ghcr.io/ocefpaf/manylinux2014_aarch64-netcdf
+        CIBW_MANYLINUX_X86_64_IMAGE: ghcr.io/ocefpaf/manylinux_2_28_x86_64-netcdf
+        CIBW_MANYLINUX_AARCH64_IMAGE: ghcr.io/ocefpaf/manylinux_2_28_aarch64-netcdf
         # Emulation testing is slow, testing only latest Python.
         CIBW_TEST_SKIP: "cp39-*_aarch64 cp310-*_aarch64 cp311-*_aarch64 cp312-*_aarch64"
         CIBW_ENVIRONMENT: ${{ matrix.CIBW_ENVIRONMENT }}

From ebf48410034ebcbbe30d4546a9c0adf85f643036 Mon Sep 17 00:00:00 2001
From: Filipe Fernandes 
Date: Mon, 4 Aug 2025 08:09:03 -0300
Subject: [PATCH 1370/1504] bump to macos-13

---
 .github/workflows/cibuildwheel.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 05fc69bb3..a0423454d 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -60,9 +60,9 @@ jobs:
           - os: macos-14
             arch: arm64
             CIBW_ENVIRONMENT: MACOSX_DEPLOYMENT_TARGET=14.0
-          - os: macos-12
+          - os: macos-13
             arch: x86_64
-            CIBW_ENVIRONMENT: MACOSX_DEPLOYMENT_TARGET=12.0
+            CIBW_ENVIRONMENT: MACOSX_DEPLOYMENT_TARGET=13.0
 
     steps:
     - uses: actions/checkout@v4

From 719b9cbfed096d69c4eb4e3136160abb1a4fde45 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Wed, 6 Aug 2025 15:19:55 +0000
Subject: [PATCH 1371/1504] Bump the github-actions group across 1 directory
 with 2 updates

Bumps the github-actions group with 2 updates in the / directory: [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel) and [actions/download-artifact](https://github.com/actions/download-artifact).


Updates `pypa/cibuildwheel` from 3.0.1 to 3.1.3
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md)
- [Commits](https://github.com/pypa/cibuildwheel/compare/v3.0.1...v3.1.3)

Updates `actions/download-artifact` from 4 to 5
- [Release notes](https://github.com/actions/download-artifact/releases)
- [Commits](https://github.com/actions/download-artifact/compare/v4...v5)

---
updated-dependencies:
- dependency-name: pypa/cibuildwheel
  dependency-version: 3.1.3
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: github-actions
- dependency-name: actions/download-artifact
  dependency-version: '5'
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/cibuildwheel.yml | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index a0423454d..093312f4a 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -92,7 +92,7 @@ jobs:
         echo "Setting CIBW_SKIP=$CIBW_SKIP"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
-      uses: pypa/cibuildwheel@v3.1.0
+      uses: pypa/cibuildwheel@v3.1.3
       env:
         CIBW_SKIP: ${{ env.CIBW_SKIP }}
         CIBW_ARCHS: ${{ matrix.arch }}
@@ -171,7 +171,7 @@ jobs:
     name: "Show artifacts"
     runs-on: ubuntu-22.04
     steps:
-    - uses: actions/download-artifact@v4
+    - uses: actions/download-artifact@v5
       with:
         pattern: pypi-artifacts*
         path: ${{ github.workspace }}/dist
@@ -189,7 +189,7 @@ jobs:
     # upload to PyPI for every tag starting with 'v'
     if: github.event_name == 'push' && startsWith(github.event.ref, 'refs/tags/v')
     steps:
-    - uses: actions/download-artifact@v4
+    - uses: actions/download-artifact@v5
       with:
         pattern: pypi-artifacts*
         path: ${{ github.workspace }}/dist

From ecbf2f45cc428112f54bd97ed82d3d9137f38265 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Tue, 12 Aug 2025 12:26:30 +0000
Subject: [PATCH 1372/1504] Bump actions/checkout from 4 to 5 in the
 github-actions group

Bumps the github-actions group with 1 update: [actions/checkout](https://github.com/actions/checkout).


Updates `actions/checkout` from 4 to 5
- [Release notes](https://github.com/actions/checkout/releases)
- [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md)
- [Commits](https://github.com/actions/checkout/compare/v4...v5)

---
updated-dependencies:
- dependency-name: actions/checkout
  dependency-version: '5'
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/build_latest.yml | 2 +-
 .github/workflows/build_master.yml | 2 +-
 .github/workflows/build_old.yml    | 2 +-
 .github/workflows/cibuildwheel.yml | 6 +++---
 .github/workflows/miniconda.yml    | 4 ++--
 5 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index bc8a2d0f6..c1dfea662 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -17,7 +17,7 @@ jobs:
         python-version: ["3.13", "3.14-dev"]
     steps:
 
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v5
       with:
         submodules: true
 
diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 30ee69b5b..7c9af068f 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -14,7 +14,7 @@ jobs:
         python-version: ["3.13"]
     steps:
 
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v5
       with:
         submodules: true
 
diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml
index ddf8cdeba..55106826c 100644
--- a/.github/workflows/build_old.yml
+++ b/.github/workflows/build_old.yml
@@ -17,7 +17,7 @@ jobs:
         python-version: ["3.13"]
     steps:
 
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v5
       with:
         submodules: true
 
diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 093312f4a..c0a667072 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -18,7 +18,7 @@ jobs:
     name: Build source distribution
     runs-on: ubuntu-22.04
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
         with:
           fetch-depth: 0
 
@@ -65,7 +65,7 @@ jobs:
             CIBW_ENVIRONMENT: MACOSX_DEPLOYMENT_TARGET=13.0
 
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v5
       with:
         fetch-depth: 0
 
@@ -123,7 +123,7 @@ jobs:
         arch: [win_amd64]
 
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
         with:
           fetch-depth: 0
 
diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index fed318c90..4a3aea017 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -24,7 +24,7 @@ jobs:
         shell: bash -l {0}
 
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v5
       with:
         submodules: true
 
@@ -58,7 +58,7 @@ jobs:
       run:
         shell: bash -l {0}
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v5
       with:
         submodules: true
 

From 682d83b6a617adb379bd7d891d0143aa28ac379f Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Wed, 20 Aug 2025 09:06:59 +0000
Subject: [PATCH 1373/1504] Bump pypa/cibuildwheel from 3.1.3 to 3.1.4 in the
 github-actions group

Bumps the github-actions group with 1 update: [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel).


Updates `pypa/cibuildwheel` from 3.1.3 to 3.1.4
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md)
- [Commits](https://github.com/pypa/cibuildwheel/compare/v3.1.3...v3.1.4)

---
updated-dependencies:
- dependency-name: pypa/cibuildwheel
  dependency-version: 3.1.4
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/cibuildwheel.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index c0a667072..f7ee478c3 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -92,7 +92,7 @@ jobs:
         echo "Setting CIBW_SKIP=$CIBW_SKIP"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
-      uses: pypa/cibuildwheel@v3.1.3
+      uses: pypa/cibuildwheel@v3.1.4
       env:
         CIBW_SKIP: ${{ env.CIBW_SKIP }}
         CIBW_ARCHS: ${{ matrix.arch }}

From 527104bef3f6a0d8ed32c8e03ee5283143dc8deb Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Fri, 5 Sep 2025 03:06:20 +0000
Subject: [PATCH 1374/1504] Bump actions/setup-python from 5 to 6 in the
 github-actions group

Bumps the github-actions group with 1 update: [actions/setup-python](https://github.com/actions/setup-python).


Updates `actions/setup-python` from 5 to 6
- [Release notes](https://github.com/actions/setup-python/releases)
- [Commits](https://github.com/actions/setup-python/compare/v5...v6)

---
updated-dependencies:
- dependency-name: actions/setup-python
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/build_latest.yml | 2 +-
 .github/workflows/build_master.yml | 2 +-
 .github/workflows/build_old.yml    | 2 +-
 .github/workflows/cibuildwheel.yml | 4 ++--
 4 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index c1dfea662..a8faf5376 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -22,7 +22,7 @@ jobs:
         submodules: true
 
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v5
+      uses: actions/setup-python@v6
       with:
         python-version: ${{ matrix.python-version }}
 
diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 7c9af068f..d8b9c6576 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -19,7 +19,7 @@ jobs:
         submodules: true
 
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v5
+      uses: actions/setup-python@v6
       with:
         python-version: ${{ matrix.python-version }}
 
diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml
index 55106826c..9e00f43a5 100644
--- a/.github/workflows/build_old.yml
+++ b/.github/workflows/build_old.yml
@@ -22,7 +22,7 @@ jobs:
         submodules: true
 
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v5
+      uses: actions/setup-python@v6
       with:
         python-version: ${{ matrix.python-version }}
 
diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index f7ee478c3..19855f025 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -22,7 +22,7 @@ jobs:
         with:
           fetch-depth: 0
 
-      - uses: actions/setup-python@v5
+      - uses: actions/setup-python@v6
         name: Install Python
         with:
           python-version: 3.x
@@ -127,7 +127,7 @@ jobs:
         with:
           fetch-depth: 0
 
-      - uses: actions/setup-python@v5
+      - uses: actions/setup-python@v6
         name: Install Python
         with:
           python-version: 3.x

From 8e95d23508730006039e0877e95cb0cc88f61d50 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Cl=C3=A9ment=20Robert?= 
Date: Mon, 15 Sep 2025 15:39:34 +0200
Subject: [PATCH 1375/1504] BLD: cleanup build dependencies

---
 pyproject.toml | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index c4e44e085..b34cafccb 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,8 +1,7 @@
 [build-system]
 requires = [
     "Cython>=0.29",
-    "oldest-supported-numpy ; python_version < '3.9'",
-    "numpy>=2.0.0rc1 ; python_version >= '3.9'",
+    "numpy>=2.0.0",
     "setuptools>=61", "setuptools_scm[toml]>=3.4"
 ]
 build-backend = "setuptools.build_meta"

From 79838dadb3cc312357a60da8261cdf038de2cac2 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Cl=C3=A9ment=20Robert?= 
Date: Wed, 17 Sep 2025 09:33:23 +0200
Subject: [PATCH 1376/1504] TYP: support PEP 800 type checks (disjoint bases)

---
 pyproject.toml           | 1 +
 src/netCDF4/__init__.pyi | 9 ++++++++-
 2 files changed, 9 insertions(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index c4e44e085..33f7a04f6 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -45,6 +45,7 @@ tests = [
   "Cython",
   "packaging",
   "pytest",
+  "typing-extensions>=4.15.0",
 ]
 parallel = [
   "mpi4py",
diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi
index 0949b4ed2..97062cf51 100644
--- a/src/netCDF4/__init__.pyi
+++ b/src/netCDF4/__init__.pyi
@@ -34,6 +34,7 @@ from typing import (
     TYPE_CHECKING,
     Any,
     Callable,
+    final,
     Final,
     Generic,
     Iterable,
@@ -51,7 +52,7 @@ from typing import (
 import cftime
 import numpy as np
 import numpy.typing as npt
-from typing_extensions import Buffer, Self, TypeAlias
+from typing_extensions import Buffer, Self, TypeAlias, disjoint_base
 
 __all__ = [
     "Dataset",
@@ -217,6 +218,7 @@ class NetCDF4MissingFeatureException(Exception):
 
 def dtype_is_complex(dtype: str) -> bool: ...
 
+@disjoint_base
 class Dataset:
     def __init__(
         self,
@@ -398,6 +400,7 @@ class Group(Dataset):
     def __init__(self, parent: Dataset, name: str, **kwargs: Any) -> None: ...
     def close(self) -> NoReturn: ...
 
+@final
 class Dimension:
     def __init__(self, grp: Dataset, name: str, size: int | None = None, **kwargs: Any) -> None: ...
     @property
@@ -430,6 +433,7 @@ class _VarDtypeProperty:
     @overload
     def __get__(self, instance: Variable, owner: Any) -> Any: ...  # actual return type np.dtype | Type[str]
 
+@final
 class Variable(Generic[VarT]):
     # Overloads of __new__ are provided for some cases where the Variable's type may be statically inferred from the datatype arg
     @overload
@@ -590,6 +594,7 @@ class Variable(Generic[VarT]):
     def __len__(self) -> int: ...
     def __iter__(self) -> Iterator[Any]: ...  # faux method so mypy believes Variable is iterable
 
+@final
 class CompoundType:
     dtype: np.dtype
     dtype_view: np.dtype
@@ -600,6 +605,7 @@ class CompoundType:
     ) -> None: ...
     def __reduce__(self) -> NoReturn: ...
 
+@final
 class VLType:
     dtype: np.dtype
     name: str | None
@@ -607,6 +613,7 @@ class VLType:
     def __init__(self, grp: Dataset, dt: npt.DTypeLike, dtype_name: str, **kwargs: Any) -> None: ...
     def __reduce__(self) -> NoReturn: ...
 
+@final
 class EnumType:
     dtype: np.dtype[np.integer]
     name: str

From 8dee0047d152f680eafadc1882e5d80db8e30e94 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Cl=C3=A9ment=20Robert?= 
Date: Mon, 15 Sep 2025 15:55:28 +0200
Subject: [PATCH 1377/1504] BLD: avoid a deprecation warning from setuptools
 (PEP 735 license metadata)

---
 MANIFEST.in    | 1 -
 pyproject.toml | 7 ++++---
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/MANIFEST.in b/MANIFEST.in
index 3b055f8f3..0e8335954 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -27,4 +27,3 @@ include *.md
 include *.py
 include *.release
 include *.sh
-include LICENSE
diff --git a/pyproject.toml b/pyproject.toml
index 83dd932c3..752deabbb 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -2,7 +2,8 @@
 requires = [
     "Cython>=0.29",
     "numpy>=2.0.0",
-    "setuptools>=61", "setuptools_scm[toml]>=3.4"
+    "setuptools>=77.0.1",
+    "setuptools_scm[toml]>=3.4",
 ]
 build-backend = "setuptools.build_meta"
 
@@ -17,7 +18,8 @@ keywords = [
     "numpy", "netcdf", "data", "science", "network", "oceanography",
     "meteorology", "climate",
 ]
-license = {text = "MIT"}
+license = "MIT"
+license-files = ["LICENSE"]
 classifiers = [
     "Development Status :: 3 - Alpha",
     "Programming Language :: Python :: 3",
@@ -27,7 +29,6 @@ classifiers = [
     "Programming Language :: Python :: 3.12",
     "Programming Language :: Python :: 3.13",
     "Intended Audience :: Science/Research",
-    "License :: OSI Approved :: MIT License",
     "Topic :: Software Development :: Libraries :: Python Modules",
     "Topic :: System :: Archiving :: Compression",
     "Operating System :: OS Independent",

From ad417a119e19f6b1cf4d1afba30936f199170d49 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Cl=C3=A9ment=20Robert?= 
Date: Mon, 15 Sep 2025 16:13:25 +0200
Subject: [PATCH 1378/1504] WHL: build limited-api compliant wheels

---
 .github/workflows/cibuildwheel.yml | 52 +++++++-----------------------
 pyproject.toml                     | 45 ++++++++++++++++++++++++++
 setup.py                           | 22 ++++++++++++-
 3 files changed, 78 insertions(+), 41 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 19855f025..72e4baa1e 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -59,10 +59,8 @@ jobs:
             arch: aarch64
           - os: macos-14
             arch: arm64
-            CIBW_ENVIRONMENT: MACOSX_DEPLOYMENT_TARGET=14.0
           - os: macos-13
             arch: x86_64
-            CIBW_ENVIRONMENT: MACOSX_DEPLOYMENT_TARGET=13.0
 
     steps:
     - uses: actions/checkout@v5
@@ -80,33 +78,20 @@ jobs:
       shell: bash
       # On PRs we run only oldest and newest Python versions to reduce CI load.
       # Skips pypy and musllinux everywhere.
-      # We are buiding 38 and 312 for now.
+      # We are building 39, 311 and 314 for now.
+      # (3.11 is the oldest version for which we support abi3 wheels)
       # These needs to rotate every new Python release.
       run: |
-        if [[ "${{ github.event_name }}" == "pull_request" ]]; then
-          CIBW_SKIP="pp* cp36-* cp37-* cp38-* cp314t-* *-musllinux* cp39-* cp310-* cp311-* cp312-* cp313-*"
-        else
-          CIBW_SKIP="pp* cp36-* cp37-* cp38-* cp314t-* *-musllinux*"
-        fi
-        echo "CIBW_SKIP=$CIBW_SKIP" >> $GITHUB_ENV
-        echo "Setting CIBW_SKIP=$CIBW_SKIP"
+        set -x
+        echo "CIBW_BUILD=cp39-* cp311-* cp314-*" >> $GITHUB_ENV
+        set +x
+
+      if: ${{ github.event_name }} == "pull_request"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
       uses: pypa/cibuildwheel@v3.1.4
       env:
-        CIBW_SKIP: ${{ env.CIBW_SKIP }}
         CIBW_ARCHS: ${{ matrix.arch }}
-        CIBW_BUILD_FRONTEND: build
-        CIBW_MANYLINUX_X86_64_IMAGE: ghcr.io/ocefpaf/manylinux_2_28_x86_64-netcdf
-        CIBW_MANYLINUX_AARCH64_IMAGE: ghcr.io/ocefpaf/manylinux_2_28_aarch64-netcdf
-        # Emulation testing is slow, testing only latest Python.
-        CIBW_TEST_SKIP: "cp39-*_aarch64 cp310-*_aarch64 cp311-*_aarch64 cp312-*_aarch64"
-        CIBW_ENVIRONMENT: ${{ matrix.CIBW_ENVIRONMENT }}
-        CIBW_BEFORE_BUILD_MACOS: brew install hdf5 netcdf
-        CIBW_TEST_REQUIRES: pytest cython packaging typing-extensions
-        CIBW_TEST_COMMAND: >
-          python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')"
-          && pytest -s -rxs -v {project}/test
 
     - uses: actions/upload-artifact@v4
       with:
@@ -120,7 +105,7 @@ jobs:
     strategy:
       matrix:
         os: [windows-latest]
-        arch: [win_amd64]
+        arch: [AMD64]
 
     steps:
       - uses: actions/checkout@v5
@@ -140,25 +125,12 @@ jobs:
           create-args: >-
             python=${{ matrix.python-version }} libnetcdf=4.9.2 --channel conda-forge
 
-      - name: Install cibuildwheel
-        run: |
-          python -m pip install --upgrade cibuildwheel delvewheel
-
       - name: Build wheels for Windows (${{ matrix.arch }})
-        run: cibuildwheel --output-dir wheelhouse
+        uses: pypa/cibuildwheel@v3.1.4
         env:
-          CIBW_BUILD: "cp39-${{ matrix.arch }} cp310-${{ matrix.arch }} cp311-${{ matrix.arch }} cp312-${{ matrix.arch }} cp313-${{ matrix.arch }}"
-          CIBW_ENVIRONMENT_WINDOWS: >
-            HDF5_DIR="C:\\Users\\runneradmin\\micromamba\\envs\\build\\Library"
-            netCDF4_DIR="C:\\Users\\runneradmin\\micromamba\\envs\\build\\Library"
-            PATH="C:\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin;${PATH}"
-          CIBW_REPAIR_WHEEL_COMMAND_WINDOWS: >
-            delvewheel show {wheel}
-            && delvewheel repair -w {dest_dir} {wheel}
-          CIBW_TEST_REQUIRES: pytest cython packaging typing-extensions
-          CIBW_TEST_COMMAND: >
-            python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')"
-            && pytest -s -rxs -v {project}\\test
+          CIBW_ARCHS: ${{ matrix.arch }}
+          # cannot build cftime for this target (missing a wheel at the time of writing)
+          CIBW_SKIP: "cp314*"
 
       - uses: actions/upload-artifact@v4
         with:
diff --git a/pyproject.toml b/pyproject.toml
index 83dd932c3..b5dc44145 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -102,3 +102,48 @@ module = [
   "filter_availability",
   "matplotlib.*"
 ]
+
+[tool.cibuildwheel]
+build-verbosity = 1
+build-frontend = "build"
+skip = [
+  "*-musllinux*",
+  "cp314t-*",
+]
+test-extras = "tests"
+test-sources = [
+  "test",
+  "pyproject.toml"
+]
+test-command = [
+    '''python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')"''',
+    "pytest -s -rxs -v test",
+]
+manylinux-x86_64-image = "ghcr.io/ocefpaf/manylinux_2_28_x86_64-netcdf"
+manylinux-aarch64-image = "ghcr.io/ocefpaf/manylinux_2_28_aarch64-netcdf"
+environment = {NETCDF4_LIMITED_API="1"}
+
+[tool.cibuildwheel.macos]
+before-build = "brew install hdf5 netcdf"
+
+[[tool.cibuildwheel.overrides]]
+select = "*-macosx_x86_64"
+inherit.environment = "append"
+environment = {MACOSX_DEPLOYMENT_TARGET="13.0"}
+
+[[tool.cibuildwheel.overrides]]
+select = "*-macosx_arm64"
+inherit.environment = "append"
+environment = {MACOSX_DEPLOYMENT_TARGET="14.0"}
+
+[tool.cibuildwheel.windows]
+before-build = "python -m pip install delvewheel"
+repair-wheel-command = [
+  "delvewheel show {wheel}",
+  "delvewheel repair -w {dest_dir} {wheel}",
+]
+
+[[tool.cibuildwheel.overrides]]
+select = "*-win_*"
+inherit.environment = "append"
+environment = {HDF5_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library', netCDF4_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library', PATH='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin;${PATH}' }
diff --git a/setup.py b/setup.py
index 4bd0dbda2..0f8db2506 100644
--- a/setup.py
+++ b/setup.py
@@ -3,11 +3,27 @@
 import pathlib
 import shutil
 import configparser
+import sysconfig
 from setuptools import setup, Extension
 from setuptools.dist import Distribution
 from typing import List
 
 
+USE_PY_LIMITED_API = (
+    # require opt-in (builds are specialized by default)
+    os.getenv('NETCDF4_LIMITED_API', '0') == '1'
+    # Cython + numpy + limited API de facto requires Python >=3.11
+    and sys.version_info >= (3, 11)
+    # as of Python 3.14t, free-threaded builds don't support the limited API
+    and not sysconfig.get_config_var("Py_GIL_DISABLED")
+)
+ABI3_TARGET_VERSION = "".join(str(_) for _ in sys.version_info[:2])
+ABI3_TARGET_HEX = hex(sys.hexversion & 0xFFFF00F0)
+
+if USE_PY_LIMITED_API:
+    SETUP_OPTIONS = {"bdist_wheel": {"py_limited_api": f"cp{ABI3_TARGET_VERSION}"}}
+else:
+    SETUP_OPTIONS = {}
 
 open_kwargs = {'encoding': 'utf-8'}
 
@@ -436,6 +452,8 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
         str(nc_complex_dir / "include/generated_fallbacks"),
     ]
     DEFINE_MACROS += [("NC_COMPLEX_NO_EXPORT", "1")]
+    if USE_PY_LIMITED_API:
+        DEFINE_MACROS.append(("Py_LIMITED_API", ABI3_TARGET_HEX))
 
     ext_modules = [Extension("netCDF4._netCDF4",
                              source_files,
@@ -443,7 +461,8 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
                              libraries=libs,
                              library_dirs=lib_dirs,
                              include_dirs=include_dirs,
-                             runtime_library_dirs=runtime_lib_dirs)]
+                             runtime_library_dirs=runtime_lib_dirs,
+                             py_limited_api=USE_PY_LIMITED_API)]
     # set language_level directive to 3
     for e in ext_modules:
         e.cython_directives = {'language_level': "3"} #
@@ -477,6 +496,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     name="netCDF4",  # need by GitHub dependency graph
     version=extract_version(netcdf4_src_pyx),
     ext_modules=ext_modules,
+    options=SETUP_OPTIONS,
 )
 
 # remove plugin files copied from outside source tree

From 5e4ba557fa0f01ac4de034d2d745b3eb89a85bc4 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Cl=C3=A9ment=20Robert?= 
Date: Sat, 20 Sep 2025 19:12:39 +0200
Subject: [PATCH 1379/1504] DEP: drop support for Python 3.9, require 3.10 or
 newer

---
 .github/workflows/cibuildwheel.yml | 4 ++--
 .github/workflows/miniconda.yml    | 2 +-
 pyproject.toml                     | 3 +--
 3 files changed, 4 insertions(+), 5 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 72e4baa1e..4bf49b83e 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -78,12 +78,12 @@ jobs:
       shell: bash
       # On PRs we run only oldest and newest Python versions to reduce CI load.
       # Skips pypy and musllinux everywhere.
-      # We are building 39, 311 and 314 for now.
+      # We are building 310, 311 and 314 for now.
       # (3.11 is the oldest version for which we support abi3 wheels)
       # These needs to rotate every new Python release.
       run: |
         set -x
-        echo "CIBW_BUILD=cp39-* cp311-* cp314-*" >> $GITHUB_ENV
+        echo "CIBW_BUILD=cp310-* cp311-* cp314-*" >> $GITHUB_ENV
         set +x
 
       if: ${{ github.event_name }} == "pull_request"
diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 4a3aea017..c0bc83d83 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -12,7 +12,7 @@ jobs:
     #  NO_NET: 1
     strategy:
       matrix:
-        python-version: [ "3.9", "3.10", "3.11", "3.12", "3.13" ]
+        python-version: [ "3.10", "3.11", "3.12", "3.13" ]
         os: [windows-latest, ubuntu-latest, macos-latest]
         platform: [x64, x32]
         exclude:
diff --git a/pyproject.toml b/pyproject.toml
index b5dc44145..e2a95142f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -12,7 +12,7 @@ description = "Provides an object-oriented python interface to the netCDF versio
 authors = [
   {name = "Jeff Whitaker", email = "whitaker.jeffrey@gmail.com"},
 ]
-requires-python = ">=3.9"
+requires-python = ">=3.10"
 keywords = [
     "numpy", "netcdf", "data", "science", "network", "oceanography",
     "meteorology", "climate",
@@ -21,7 +21,6 @@ license = {text = "MIT"}
 classifiers = [
     "Development Status :: 3 - Alpha",
     "Programming Language :: Python :: 3",
-    "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",

From 5e6841849f4d577ff25c31e4b17b62a7606637b0 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Cl=C3=A9ment=20Robert?= 
Date: Mon, 22 Sep 2025 07:36:48 +0200
Subject: [PATCH 1380/1504] MNT: add missing CPython 3.14 PyPI trove classifier

---
 pyproject.toml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pyproject.toml b/pyproject.toml
index e2a95142f..1630015b4 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -25,6 +25,7 @@ classifiers = [
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
     "Programming Language :: Python :: 3.13",
+    "Programming Language :: Python :: 3.14",
     "Intended Audience :: Science/Research",
     "License :: OSI Approved :: MIT License",
     "Topic :: Software Development :: Libraries :: Python Modules",

From 16766177e2929f792d8d509108c70b46779b16b9 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Tue, 23 Sep 2025 03:06:18 +0000
Subject: [PATCH 1381/1504] Bump pypa/cibuildwheel from 3.1.4 to 3.2.0 in the
 github-actions group

Bumps the github-actions group with 1 update: [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel).


Updates `pypa/cibuildwheel` from 3.1.4 to 3.2.0
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md)
- [Commits](https://github.com/pypa/cibuildwheel/compare/v3.1.4...v3.2.0)

---
updated-dependencies:
- dependency-name: pypa/cibuildwheel
  dependency-version: 3.2.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/cibuildwheel.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 4bf49b83e..63816217e 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -89,7 +89,7 @@ jobs:
       if: ${{ github.event_name }} == "pull_request"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
-      uses: pypa/cibuildwheel@v3.1.4
+      uses: pypa/cibuildwheel@v3.2.0
       env:
         CIBW_ARCHS: ${{ matrix.arch }}
 
@@ -126,7 +126,7 @@ jobs:
             python=${{ matrix.python-version }} libnetcdf=4.9.2 --channel conda-forge
 
       - name: Build wheels for Windows (${{ matrix.arch }})
-        uses: pypa/cibuildwheel@v3.1.4
+        uses: pypa/cibuildwheel@v3.2.0
         env:
           CIBW_ARCHS: ${{ matrix.arch }}
           # cannot build cftime for this target (missing a wheel at the time of writing)

From 61e0aeca23a8e15cbf46086cc0bd33d02abc3c74 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Fri, 10 Oct 2025 11:08:22 -0600
Subject: [PATCH 1382/1504] prepare for 1.7.3 release

---
 Changelog | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/Changelog b/Changelog
index 2aeb0efc2..f9d0de0f5 100644
--- a/Changelog
+++ b/Changelog
@@ -1,5 +1,6 @@
- since version 1.7.2 release
- ===========================
+ version 1.7.3 (tag v1.7.3rel)
+ =============================
+ * Python 3.14 wheels (issue #1432)
  * support os.PathLike arguments for `Dataset.fromcdl` and raise a `FileNotFoundError`
    if the cdl is missing and a `FileExistsError` if the nc file already exists (PR #1387)
  * raise more informative error when trying to iterate or

From a6e524f94666df0fda590fa29d22a96e992a9cce Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Fri, 10 Oct 2025 11:10:32 -0600
Subject: [PATCH 1383/1504] update

---
 README.md | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/README.md b/README.md
index 59b113022..f3ecd43f3 100644
--- a/README.md
+++ b/README.md
@@ -10,6 +10,8 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
+10/13/2025: Version [1.7.3](https://pypi.python.org/pypi/netCDF4/1.7.3) released. Minor updates/bugfixes and python 3.14 wheels, see Changelog for details.
+
 10/22/2024: Version [1.7.2](https://pypi.python.org/pypi/netCDF4/1.7.2) released. Minor updates/bugfixes and python 3.13 wheels, see Changelog for details.
 
 06/17/2024: Version [1.7.1](https://pypi.python.org/pypi/netCDF4/1.7.1) released. Fixes for wheels, no code changes.

From bba1f5d2e9cb3cb72a862f638585dd91037326b8 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Fri, 10 Oct 2025 11:12:48 -0600
Subject: [PATCH 1384/1504] update python versions

---
 .github/workflows/build_latest.yml | 2 +-
 .github/workflows/build_master.yml | 2 +-
 .github/workflows/build_old.yml    | 2 +-
 .github/workflows/miniconda.yml    | 2 +-
 4 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index a8faf5376..3da959b3d 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -14,7 +14,7 @@ jobs:
       #NO_NET: 1
     strategy:
       matrix:
-        python-version: ["3.13", "3.14-dev"]
+        python-version: ["3.14"]
     steps:
 
     - uses: actions/checkout@v5
diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index d8b9c6576..7469f0210 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -11,7 +11,7 @@ jobs:
       #NO_NET: 1
     strategy:
       matrix:
-        python-version: ["3.13"]
+        python-version: ["3.14"]
     steps:
 
     - uses: actions/checkout@v5
diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml
index 9e00f43a5..e7fed4dc6 100644
--- a/.github/workflows/build_old.yml
+++ b/.github/workflows/build_old.yml
@@ -14,7 +14,7 @@ jobs:
       #NO_NET: 1
     strategy:
       matrix:
-        python-version: ["3.13"]
+        python-version: ["3.14"]
     steps:
 
     - uses: actions/checkout@v5
diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index c0bc83d83..123071aeb 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -12,7 +12,7 @@ jobs:
     #  NO_NET: 1
     strategy:
       matrix:
-        python-version: [ "3.10", "3.11", "3.12", "3.13" ]
+        python-version: [ "3.10", "3.11", "3.12", "3.13", "3.14" ]
         os: [windows-latest, ubuntu-latest, macos-latest]
         platform: [x64, x32]
         exclude:

From 5898f295f709143149764be9c4a02f3da76d2316 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Fri, 10 Oct 2025 11:18:12 -0600
Subject: [PATCH 1385/1504] update pnetcdf version

---
 .github/workflows/build_latest.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index 3da959b3d..400c91fae 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -5,7 +5,7 @@ jobs:
     name: Python (${{ matrix.python-version }})
     runs-on: ubuntu-latest
     env:
-      PNETCDF_VERSION: 1.14.0
+      PNETCDF_VERSION: 1.14.1
       NETCDF_VERSION: 4.9.3
       NETCDF_DIR: ${{ github.workspace }}/..
       NETCDF_EXTRA_CONFIG: --enable-pnetcdf

From 83fff8fbc0e48e84ee4ae2ba0e3632215b24af66 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 13 Oct 2025 03:11:31 +0000
Subject: [PATCH 1386/1504] Bump pypa/cibuildwheel from 3.2.0 to 3.2.1 in the
 github-actions group

Bumps the github-actions group with 1 update: [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel).


Updates `pypa/cibuildwheel` from 3.2.0 to 3.2.1
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md)
- [Commits](https://github.com/pypa/cibuildwheel/compare/v3.2.0...v3.2.1)

---
updated-dependencies:
- dependency-name: pypa/cibuildwheel
  dependency-version: 3.2.1
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/cibuildwheel.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 63816217e..88e73e851 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -89,7 +89,7 @@ jobs:
       if: ${{ github.event_name }} == "pull_request"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
-      uses: pypa/cibuildwheel@v3.2.0
+      uses: pypa/cibuildwheel@v3.2.1
       env:
         CIBW_ARCHS: ${{ matrix.arch }}
 
@@ -126,7 +126,7 @@ jobs:
             python=${{ matrix.python-version }} libnetcdf=4.9.2 --channel conda-forge
 
       - name: Build wheels for Windows (${{ matrix.arch }})
-        uses: pypa/cibuildwheel@v3.2.0
+        uses: pypa/cibuildwheel@v3.2.1
         env:
           CIBW_ARCHS: ${{ matrix.arch }}
           # cannot build cftime for this target (missing a wheel at the time of writing)

From e888d5193210824bd9a56351e34efbf5fcf28c11 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Cl=C3=A9ment=20Robert?= 
Date: Mon, 13 Oct 2025 19:14:19 +0200
Subject: [PATCH 1387/1504] WHL: add cp314 wheels for Windows

---
 .github/workflows/cibuildwheel.yml | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 63816217e..d0efe8d8d 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -89,7 +89,7 @@ jobs:
       if: ${{ github.event_name }} == "pull_request"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
-      uses: pypa/cibuildwheel@v3.2.0
+      uses: pypa/cibuildwheel@v3.2.1
       env:
         CIBW_ARCHS: ${{ matrix.arch }}
 
@@ -126,11 +126,9 @@ jobs:
             python=${{ matrix.python-version }} libnetcdf=4.9.2 --channel conda-forge
 
       - name: Build wheels for Windows (${{ matrix.arch }})
-        uses: pypa/cibuildwheel@v3.2.0
+        uses: pypa/cibuildwheel@v3.2.1
         env:
           CIBW_ARCHS: ${{ matrix.arch }}
-          # cannot build cftime for this target (missing a wheel at the time of writing)
-          CIBW_SKIP: "cp314*"
 
       - uses: actions/upload-artifact@v4
         with:

From a9d4e92eab0f0fa2360cf629758abf9c0a982993 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Mon, 13 Oct 2025 11:50:17 -0600
Subject: [PATCH 1388/1504] bump version number to 1.7.3

---
 src/netCDF4/_netCDF4.pyx | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index b8e5bad0d..acdfdf5a5 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1,4 +1,4 @@
-"""Version 1.7.2
+"""Version 1.7.3
 -------------
 
 # Introduction
@@ -1279,7 +1279,7 @@ import sys
 import functools
 from typing import Union
 
-__version__ = "1.7.2"
+__version__ = "1.7.3"
 
 # Initialize numpy
 import posixpath

From 2ae97c3a04f2f0e249de3640c64aa5562699a529 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Tue, 14 Oct 2025 09:46:11 -0600
Subject: [PATCH 1389/1504] update status badge

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index f3ecd43f3..57a352c2d 100644
--- a/README.md
+++ b/README.md
@@ -1,7 +1,7 @@
 # [netcdf4-python](http://unidata.github.io/netcdf4-python)
 [Python](http://python.org)/[numpy](http://numpy.org) interface to the netCDF [C library](https://github.com/Unidata/netcdf-c).
 
-[![Build status](https://github.com/Unidata/netcdf4-python/workflows/Build%20and%20Test/badge.svg)](https://github.com/Unidata/netcdf4-python/actions)
+[![CodeQL](https://github.com/Unidata/netcdf4-python/actions/workflows/github-code-scanning/codeql/badge.svg)](https://github.com/Unidata/netcdf4-python/actions/workflows/github-code-scanning/codeql)
 [![PyPI package](https://img.shields.io/pypi/v/netCDF4.svg)](http://python.org/pypi/netCDF4)
 [![Anaconda-Server Badge](https://anaconda.org/conda-forge/netCDF4/badges/version.svg)](https://anaconda.org/conda-forge/netCDF4)
 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.2592291.svg)](https://doi.org/10.5281/zenodo.2592290)

From b934bb60701bfc78567e489cafa450bb3003b5ea Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 27 Oct 2025 03:16:00 +0000
Subject: [PATCH 1390/1504] Bump the github-actions group with 2 updates

Bumps the github-actions group with 2 updates: [actions/upload-artifact](https://github.com/actions/upload-artifact) and [actions/download-artifact](https://github.com/actions/download-artifact).


Updates `actions/upload-artifact` from 4 to 5
- [Release notes](https://github.com/actions/upload-artifact/releases)
- [Commits](https://github.com/actions/upload-artifact/compare/v4...v5)

Updates `actions/download-artifact` from 5 to 6
- [Release notes](https://github.com/actions/download-artifact/releases)
- [Commits](https://github.com/actions/download-artifact/compare/v5...v6)

---
updated-dependencies:
- dependency-name: actions/upload-artifact
  dependency-version: '5'
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: github-actions
- dependency-name: actions/download-artifact
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/cibuildwheel.yml | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index d0efe8d8d..2a2ebf717 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -38,7 +38,7 @@ jobs:
           pip install build
           &&  python -m build --sdist . --outdir dist
 
-      - uses: actions/upload-artifact@v4
+      - uses: actions/upload-artifact@v5
         with:
           name: pypi-artifacts
           path: ${{ github.workspace }}/dist/*.tar.gz
@@ -93,7 +93,7 @@ jobs:
       env:
         CIBW_ARCHS: ${{ matrix.arch }}
 
-    - uses: actions/upload-artifact@v4
+    - uses: actions/upload-artifact@v5
       with:
         name: pypi-artifacts-${{ matrix.os }}-${{ matrix.arch }}
         path: ${{ github.workspace }}/wheelhouse/*.whl
@@ -130,7 +130,7 @@ jobs:
         env:
           CIBW_ARCHS: ${{ matrix.arch }}
 
-      - uses: actions/upload-artifact@v4
+      - uses: actions/upload-artifact@v5
         with:
           name: pypi-artifacts-${{ matrix.os }}-${{ matrix.arch }}
           path: ${{ github.workspace }}/wheelhouse/*.whl
@@ -141,7 +141,7 @@ jobs:
     name: "Show artifacts"
     runs-on: ubuntu-22.04
     steps:
-    - uses: actions/download-artifact@v5
+    - uses: actions/download-artifact@v6
       with:
         pattern: pypi-artifacts*
         path: ${{ github.workspace }}/dist
@@ -159,7 +159,7 @@ jobs:
     # upload to PyPI for every tag starting with 'v'
     if: github.event_name == 'push' && startsWith(github.event.ref, 'refs/tags/v')
     steps:
-    - uses: actions/download-artifact@v5
+    - uses: actions/download-artifact@v6
       with:
         pattern: pypi-artifacts*
         path: ${{ github.workspace }}/dist

From 0bbc9d14b5740dea8073278edfd4ffbcc2e6ad38 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Mon, 27 Oct 2025 15:04:51 -0600
Subject: [PATCH 1391/1504] tentative fixes for issue #1440

---
 Changelog                |  2 ++
 include/netcdf-compat.h  |  2 +-
 src/netCDF4/_netCDF4.pyx | 13 +++++++------
 3 files changed, 10 insertions(+), 7 deletions(-)

diff --git a/Changelog b/Changelog
index f9d0de0f5..455bd1e06 100644
--- a/Changelog
+++ b/Changelog
@@ -1,3 +1,5 @@
+ version 1.7.4 (not yet released)
+ ================================
  version 1.7.3 (tag v1.7.3rel)
  =============================
  * Python 3.14 wheels (issue #1432)
diff --git a/include/netcdf-compat.h b/include/netcdf-compat.h
index d1144d979..ccfb8322e 100644
--- a/include/netcdf-compat.h
+++ b/include/netcdf-compat.h
@@ -60,7 +60,7 @@ static inline int nc_get_alignment(int* thresholdp, int* alignmentp) {
 #else
 #define HAS_NCRCSET 0
 static inline int nc_rc_set(const char* key, const char* value) { return NC_EINVAL; }
-static inline const char *nc_rc_get(const char* key) { return NC_EINVAL; }
+static inline const char *nc_rc_get(const char* key) { return NULL; }
 #endif
 
 #if NC_VERSION_GE(4, 4, 0)
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index acdfdf5a5..487dbcb02 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -5525,7 +5525,11 @@ cannot be safely cast to variable data type""" % attname
                 # if data is a string or a bytes object, convert to a numpy string array
                 # whose length is equal to the rightmost dimension of the
                 # variable.
-                if type(data) in [str,bytes]: data = numpy.asarray(data,dtype='S'+repr(self.shape[-1]))
+                if type(data) in [str,bytes]:
+                    if encoding == 'ascii':
+                        data = numpy.asarray(data,dtype='S'+repr(self.shape[-1]))
+                    else:
+                        data = numpy.asarray(data,dtype='U'+repr(self.shape[-1]))
                 if data.dtype.kind in ['S','U'] and data.dtype.itemsize > 1:
                     # if data is a numpy string array, convert it to an array
                     # of characters with one more dimension.
@@ -6816,15 +6820,12 @@ returns a numpy string array with datatype `'UN'` (or `'SN'`) and shape
     dtype = b.dtype.kind
     if dtype not in ["S","U"]:
         raise ValueError("type must be string or unicode ('S' or 'U')")
-    if encoding in ['none','None','bytes']:
-        bs = b.tobytes()
-    else:
-        bs = b.tobytes().decode(encoding)
+    bs = b.tobytes()
     slen = int(b.shape[-1])
     if encoding in ['none','None','bytes']:
         a = numpy.array([bs[n1:n1+slen] for n1 in range(0,len(bs),slen)],'S'+repr(slen))
     else:
-        a = numpy.array([bs[n1:n1+slen] for n1 in range(0,len(bs),slen)],'U'+repr(slen))
+        a = numpy.array([bs[n1:n1+slen].decode(encoding) for n1 in range(0,len(bs),slen)],'U'+repr(slen))
     a.shape = b.shape[:-1]
     return a
 

From 826b634a7896db9e4e1e9aaa41b267010fcbba12 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Mon, 27 Oct 2025 19:19:24 -0600
Subject: [PATCH 1392/1504] update

---
 src/netCDF4/_netCDF4.pyx | 23 ++++++++++++++++++-----
 1 file changed, 18 insertions(+), 5 deletions(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 487dbcb02..5f9108b1e 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -5533,7 +5533,7 @@ cannot be safely cast to variable data type""" % attname
                 if data.dtype.kind in ['S','U'] and data.dtype.itemsize > 1:
                     # if data is a numpy string array, convert it to an array
                     # of characters with one more dimension.
-                    data = stringtochar(data, encoding=encoding)
+                    data = stringtochar(data, encoding=encoding,n_strlen=self.shape[-1])
 
         # if structured data has strings (and _Encoding att set), create view as char arrays
         # (issue #773)
@@ -6775,9 +6775,9 @@ returns a rank 1 numpy character array of length NUMCHARS with datatype `'S1'`
     arr[0:len(string)] = tuple(string)
     return arr
 
-def stringtochar(a,encoding='utf-8'):
+def stringtochar(a,encoding='utf-8',n_strlen=None):
     """
-**`stringtochar(a,encoding='utf-8')`**
+**`stringtochar(a,encoding='utf-8',n_strlen=None)`**
 
 convert a string array to a character array with one extra dimension
 
@@ -6789,16 +6789,29 @@ optional kwarg `encoding` can be used to specify character encoding (default
 `utf-8`). If `encoding` is 'none' or 'bytes', a `numpy.string_` the input array
 is treated a raw byte strings (`numpy.string_`).
 
+optional kwarg `n_strlen` is the number of characters in each string.  Default
+is None, which means `n_strlen` will be set to a.itemsize (the number of bytes
+used to represent each string in the input array).
+
 returns a numpy character array with datatype `'S1'` or `'U1'`
 and shape `a.shape + (N,)`, where N is the length of each string in a."""
     dtype = a.dtype.kind
+    if n_strlen is None:
+        n_strlen = a.dtype.itemsize
     if dtype not in ["S","U"]:
         raise ValueError("type must string or unicode ('S' or 'U')")
     if encoding in ['none','None','bytes']:
         b = numpy.array(tuple(a.tobytes()),'S1')
+    elif encoding == 'ascii':
+        b = numpy.array(tuple(a.tobytes().decode('ascii')))
+        b.shape = a.shape + (n_strlen,)
     else:
-        b = numpy.array(tuple(a.tobytes().decode(encoding)),dtype+'1')
-    b.shape = a.shape + (a.itemsize,)
+        if not a.ndim:
+            a = numpy.array([a])
+        bbytes = [text.encode(encoding) for text in a]
+        pad = b'\0' * n_strlen
+        bbytes = [(x + pad)[:n_strlen] for x in bbytes]
+        b = numpy.array([[bb[i:i+1] for i in range(n_strlen)] for bb in bbytes])
     return b
 
 def chartostring(b,encoding='utf-8'):

From 915c133b7680df723339942d4ce870579f441b70 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Mon, 27 Oct 2025 20:22:41 -0600
Subject: [PATCH 1393/1504] update

---
 src/netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 5f9108b1e..87880cc45 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -6803,7 +6803,7 @@ and shape `a.shape + (N,)`, where N is the length of each string in a."""
     if encoding in ['none','None','bytes']:
         b = numpy.array(tuple(a.tobytes()),'S1')
     elif encoding == 'ascii':
-        b = numpy.array(tuple(a.tobytes().decode('ascii')))
+        b = numpy.array(tuple(a.tobytes().decode(encoding)),dtype+'1')
         b.shape = a.shape + (n_strlen,)
     else:
         if not a.ndim:

From c5c25875b647fa0d76fb90a53bb8f678b4f73e67 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Mon, 27 Oct 2025 20:48:23 -0600
Subject: [PATCH 1394/1504] update stringtochar stub

---
 src/netCDF4/__init__.pyi | 1 +
 1 file changed, 1 insertion(+)

diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi
index 97062cf51..f07aa0b8f 100644
--- a/src/netCDF4/__init__.pyi
+++ b/src/netCDF4/__init__.pyi
@@ -699,6 +699,7 @@ def stringtoarr(
 def stringtochar(
     a: npt.NDArray[np.character],
     encoding: Literal["none", "None", "bytes"],
+    n_strlen: int
 ) -> npt.NDArray[np.bytes_]: ...
 @overload
 def stringtochar(

From 4b7201e50e21e41e7f19e4e8f8559e98b8e4284e Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Mon, 27 Oct 2025 20:57:24 -0600
Subject: [PATCH 1395/1504] update

---
 src/netCDF4/__init__.pyi | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/netCDF4/__init__.pyi b/src/netCDF4/__init__.pyi
index f07aa0b8f..e27fb6370 100644
--- a/src/netCDF4/__init__.pyi
+++ b/src/netCDF4/__init__.pyi
@@ -699,7 +699,7 @@ def stringtoarr(
 def stringtochar(
     a: npt.NDArray[np.character],
     encoding: Literal["none", "None", "bytes"],
-    n_strlen: int
+    n_strlen: int | None = None,
 ) -> npt.NDArray[np.bytes_]: ...
 @overload
 def stringtochar(

From 4e0abacdc5821bdbc1ce16b3e1eda2d081b84ac0 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Tue, 28 Oct 2025 09:03:35 -0600
Subject: [PATCH 1396/1504] add test for issue1440

---
 test/test_stringarr.py | 14 ++++++++++++++
 1 file changed, 14 insertions(+)

diff --git a/test/test_stringarr.py b/test/test_stringarr.py
index 9d4fcd909..aed2203df 100644
--- a/test/test_stringarr.py
+++ b/test/test_stringarr.py
@@ -3,6 +3,7 @@
 import unittest
 import os
 from numpy.testing import assert_array_equal, assert_array_almost_equal
+import numpy as np
 
 def generateString(length, alphabet=string.ascii_letters + string.digits + string.punctuation):
     return(''.join([random.choice(alphabet) for i in range(length)]))
@@ -20,6 +21,10 @@ def generateString(length, alphabet=string.ascii_letters + string.digits + strin
 datau = data.astype('U')
 datac = stringtochar(data, encoding='ascii')
 
+nx, n_strlen = 3, 10
+unicode_strings = np.array(['Münster', 'London', 'Amsterdam'],dtype='U'+str(n_strlen))
+unicode_strings2 = np.array(['Münster', 'Liége', 'Amsterdam'],dtype='U'+str(n_strlen))
+
 class StringArrayTestCase(unittest.TestCase):
 
     def setUp(self):
@@ -28,6 +33,8 @@ def setUp(self):
         nc.createDimension('n1',None)
         nc.createDimension('n2',n2)
         nc.createDimension('nchar',nchar)
+        nc.createDimension("x", nx)
+        nc.createDimension("nstr", n_strlen)
         v = nc.createVariable('strings','S1',('n1','n2','nchar'))
         v2 = nc.createVariable('strings2','S1',('n1','n2','nchar'))
         # if _Encoding set, string array should automatically be converted
@@ -44,6 +51,11 @@ def setUp(self):
         v2[-1,-1] = data[-1,-1].tobytes() # write single python string
         # _Encoding should be ignored if an array of characters is specified
         v3[:] = stringtochar(data, encoding='ascii')
+        # test unicode strings (issue #1440)
+        v4 = nc.createVariable("strings4", "S1", dimensions=("x", "nstr",))
+        v4._Encoding = "UTF-8"
+        v4[:] = unicode_strings
+        v4[1] = "Liége"
         nc.close()
 
     def tearDown(self):
@@ -57,6 +69,8 @@ def runTest(self):
         v = nc.variables['strings']
         v2 = nc.variables['strings2']
         v3 = nc.variables['strings3']
+        v4 = nc.variables['strings4']
+        assert np.all(v4[:]==unicode_strings2)
         assert v.dtype.str[1:] in ['S1','U1']
         assert v.shape == (nrecs,n2,nchar)
         for nrec in range(nrecs):

From 51edbab95ba10083f592615b789238d255ff403e Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Tue, 28 Oct 2025 09:38:06 -0600
Subject: [PATCH 1397/1504] update

---
 Changelog | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/Changelog b/Changelog
index 455bd1e06..c74134c2a 100644
--- a/Changelog
+++ b/Changelog
@@ -1,5 +1,8 @@
  version 1.7.4 (not yet released)
  ================================
+ * Make sure automatic conversion of character arrays <--> string arrays works for Unicode strings (issue #1440).
+   (previously only worked correctly for encoding="ascii").
+
  version 1.7.3 (tag v1.7.3rel)
  =============================
  * Python 3.14 wheels (issue #1432)

From ea3d3a16b634aa60897114de0fc906a149220a6c Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Tue, 28 Oct 2025 09:41:25 -0600
Subject: [PATCH 1398/1504] update

---
 src/netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 87880cc45..f0025dcd2 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1066,7 +1066,7 @@ If the `_Encoding` special attribute is set for a character array
 (dtype `S1`) variable, the `chartostring` utility function is used to convert the array of
 characters to an array of strings with one less dimension (the last dimension is
 interpreted as the length of each string) when reading the data. The character
-set (usually ascii) is specified by the `_Encoding` attribute. If `_Encoding`
+set is specified by the `_Encoding` attribute. If `_Encoding`
 is 'none' or 'bytes', then the character array is converted to a numpy
 fixed-width byte string array (dtype `S#`), otherwise a numpy unicode (dtype
 `U#`) array is created.  When writing the data,

From a0486d2ba8baef19dc243ca4431988c8e6bed0a3 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Tue, 28 Oct 2025 10:00:10 -0600
Subject: [PATCH 1399/1504] update

---
 test/test_stringarr.py | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/test/test_stringarr.py b/test/test_stringarr.py
index aed2203df..36a3ea03f 100644
--- a/test/test_stringarr.py
+++ b/test/test_stringarr.py
@@ -21,9 +21,9 @@ def generateString(length, alphabet=string.ascii_letters + string.digits + strin
 datau = data.astype('U')
 datac = stringtochar(data, encoding='ascii')
 
-nx, n_strlen = 3, 10
-unicode_strings = np.array(['Münster', 'London', 'Amsterdam'],dtype='U'+str(n_strlen))
-unicode_strings2 = np.array(['Münster', 'Liége', 'Amsterdam'],dtype='U'+str(n_strlen))
+nx, n_strlen = 3, 12
+unicode_strings = np.array(['Münster', 'Liége', '東京'],dtype='U'+str(n_strlen))
+unicode_strings2 = np.array(['Münster', 'Москва', '東京'],dtype='U'+str(n_strlen))
 
 class StringArrayTestCase(unittest.TestCase):
 
@@ -55,7 +55,7 @@ def setUp(self):
         v4 = nc.createVariable("strings4", "S1", dimensions=("x", "nstr",))
         v4._Encoding = "UTF-8"
         v4[:] = unicode_strings
-        v4[1] = "Liége"
+        v4[1] = "Москва"
         nc.close()
 
     def tearDown(self):
@@ -70,6 +70,7 @@ def runTest(self):
         v2 = nc.variables['strings2']
         v3 = nc.variables['strings3']
         v4 = nc.variables['strings4']
+        print(v4[:])
         assert np.all(v4[:]==unicode_strings2)
         assert v.dtype.str[1:] in ['S1','U1']
         assert v.shape == (nrecs,n2,nchar)

From caed197d76a8cd86bc2362e9d672ae3103f7d109 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Tue, 28 Oct 2025 10:10:41 -0600
Subject: [PATCH 1400/1504] update

---
 test/test_stringarr.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/test/test_stringarr.py b/test/test_stringarr.py
index 36a3ea03f..780dd7ca7 100644
--- a/test/test_stringarr.py
+++ b/test/test_stringarr.py
@@ -24,6 +24,7 @@ def generateString(length, alphabet=string.ascii_letters + string.digits + strin
 nx, n_strlen = 3, 12
 unicode_strings = np.array(['Münster', 'Liége', '東京'],dtype='U'+str(n_strlen))
 unicode_strings2 = np.array(['Münster', 'Москва', '東京'],dtype='U'+str(n_strlen))
+unicode_strings2_bytes = [b'M', b'\xc3', b'\xbc', b'n', b's', b't', b'e', b'r', b'\xd0', b'\x9c', b'\xd0', b'\xbe', b'\xd1', b'\x81', b'\xd0', b'\xba', b'\xd0', b'\xb2', b'\xd0', b'\xb0', b'\xe6', b'\x9d', b'\xb1', b'\xe4', b'\xba', b'\xac']
 
 class StringArrayTestCase(unittest.TestCase):
 
@@ -70,8 +71,9 @@ def runTest(self):
         v2 = nc.variables['strings2']
         v3 = nc.variables['strings3']
         v4 = nc.variables['strings4']
-        print(v4[:])
         assert np.all(v4[:]==unicode_strings2)
+        v4.set_auto_chartostring(False)
+        assert (v4[:].compressed().tolist() == unicode_strings2_bytes)
         assert v.dtype.str[1:] in ['S1','U1']
         assert v.shape == (nrecs,n2,nchar)
         for nrec in range(nrecs):

From d2b05c5741ef33773ac40ffc4d0ccc89d5bd8f29 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Tue, 28 Oct 2025 14:07:22 -0600
Subject: [PATCH 1401/1504] add $CONDA_PREFIX/bin to PATH on windows

---
 .github/workflows/cibuildwheel.yml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 2a2ebf717..516e114ac 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -129,6 +129,7 @@ jobs:
         uses: pypa/cibuildwheel@v3.2.1
         env:
           CIBW_ARCHS: ${{ matrix.arch }}
+          CIBW_ENVIRONMENT: > PATH="${CONDA_PREFIX}/bin:$PATH"
 
       - uses: actions/upload-artifact@v5
         with:

From 5fb1c221237937fe24c11af733c11959e801c56e Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Tue, 28 Oct 2025 14:19:23 -0600
Subject: [PATCH 1402/1504] add CONDA_PREFIX to path in pyproject.toml for
 cibuildwheel

---
 .github/workflows/cibuildwheel.yml | 1 -
 pyproject.toml                     | 1 +
 2 files changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 516e114ac..2a2ebf717 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -129,7 +129,6 @@ jobs:
         uses: pypa/cibuildwheel@v3.2.1
         env:
           CIBW_ARCHS: ${{ matrix.arch }}
-          CIBW_ENVIRONMENT: > PATH="${CONDA_PREFIX}/bin:$PATH"
 
       - uses: actions/upload-artifact@v5
         with:
diff --git a/pyproject.toml b/pyproject.toml
index 73cf86580..61ea02647 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -140,6 +140,7 @@ environment = {MACOSX_DEPLOYMENT_TARGET="14.0"}
 
 [tool.cibuildwheel.windows]
 before-build = "python -m pip install delvewheel"
+environment = "PATH=$CONDA_PREFIX/bin:$PATH"
 repair-wheel-command = [
   "delvewheel show {wheel}",
   "delvewheel repair -w {dest_dir} {wheel}",

From 7eef3947bd32ade448d01dfeb090d874f204ff05 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Tue, 28 Oct 2025 16:48:14 -0600
Subject: [PATCH 1403/1504] update

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 61ea02647..2605ce84c 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -140,7 +140,7 @@ environment = {MACOSX_DEPLOYMENT_TARGET="14.0"}
 
 [tool.cibuildwheel.windows]
 before-build = "python -m pip install delvewheel"
-environment = "PATH=$CONDA_PREFIX/bin:$PATH"
+environment = "PATH=$PATH:$CONDA_PREFIX/bin"
 repair-wheel-command = [
   "delvewheel show {wheel}",
   "delvewheel repair -w {dest_dir} {wheel}",

From 3e7f69e720e66efe78cca06b2359f8d6139af407 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Mon, 10 Nov 2025 12:14:58 -0700
Subject: [PATCH 1404/1504] fix inverted conditions for plugin detection

---
 src/netCDF4/_netCDF4.pyx | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index f0025dcd2..ae933a70e 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3559,6 +3559,8 @@ to be installed and in `$PATH`.
         returns True if blosc compression filter is available
         """
         if __has_blosc_support__:
+            return True
+        else
             return False
 
         cdef int ierr
@@ -3572,6 +3574,8 @@ to be installed and in `$PATH`.
         """
 
         if __has_zstandard_support__:
+            return True
+        else:
             return False
 
         cdef int ierr
@@ -3585,6 +3589,8 @@ to be installed and in `$PATH`.
         """
 
         if __has_bzip2_support__:
+            return True
+        else:
             return False
 
         cdef int ierr

From f9be0098ab98910bd5d751adafd2c7d993814775 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Mon, 10 Nov 2025 12:37:38 -0700
Subject: [PATCH 1405/1504] fix typo

---
 src/netCDF4/_netCDF4.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index ae933a70e..7cbaaeffd 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3560,7 +3560,7 @@ to be installed and in `$PATH`.
         """
         if __has_blosc_support__:
             return True
-        else
+        else:
             return False
 
         cdef int ierr

From 70e4741a9747c829af241b016023a209b2ee7b93 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Mon, 10 Nov 2025 13:22:04 -0700
Subject: [PATCH 1406/1504] skip plugin tests on windows

---
 test/run_all.py | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/test/run_all.py b/test/run_all.py
index b99565963..101aeca4c 100755
--- a/test/run_all.py
+++ b/test/run_all.py
@@ -15,6 +15,12 @@
     m = __import__(os.path.splitext(f)[0])
     testsuite.addTests(unittest.TestLoader().loadTestsFromModule(m))
 
+# skip compression plugin tests on windows for now
+# (conda package plugins not working?).
+if sys.platform == 'win32':
+    test_files.remove('tst_compression_zstd.py)
+    test_files.remove('tst_compression_blosc.py)
+    test_files.remove('tst_compression_bzip2.py)
 
 if __name__ == '__main__':
     import numpy, cython

From 312a024c94b2d37cc4bd37cd11fb647eb18ac090 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Mon, 10 Nov 2025 13:30:59 -0700
Subject: [PATCH 1407/1504] fix typo

---
 test/run_all.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/test/run_all.py b/test/run_all.py
index 101aeca4c..f8fd2ead1 100755
--- a/test/run_all.py
+++ b/test/run_all.py
@@ -18,9 +18,9 @@
 # skip compression plugin tests on windows for now
 # (conda package plugins not working?).
 if sys.platform == 'win32':
-    test_files.remove('tst_compression_zstd.py)
-    test_files.remove('tst_compression_blosc.py)
-    test_files.remove('tst_compression_bzip2.py)
+    test_files.remove('tst_compression_zstd.py')
+    test_files.remove('tst_compression_blosc.py')
+    test_files.remove('tst_compression_bzip2.py')
 
 if __name__ == '__main__':
     import numpy, cython

From e6321f10fb90f07dd2ce9e0dddeb0d356d3fe8aa Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Mon, 10 Nov 2025 15:00:58 -0700
Subject: [PATCH 1408/1504] update

---
 pyproject.toml          |  2 +-
 src/netCDF4/__init__.py | 15 ++++++++-------
 test/run_all.py         |  7 -------
 3 files changed, 9 insertions(+), 15 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 653c7960f..e6705c78d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -122,7 +122,7 @@ test-command = [
 ]
 manylinux-x86_64-image = "ghcr.io/ocefpaf/manylinux_2_28_x86_64-netcdf"
 manylinux-aarch64-image = "ghcr.io/ocefpaf/manylinux_2_28_aarch64-netcdf"
-environment = {NETCDF4_LIMITED_API="1"}
+environment = {NETCDF4_LIMITED_API="1", NETCDF_PLUGIN_DIR="/usr/local/hdf5/lib/plugin/"}
 
 [tool.cibuildwheel.macos]
 before-build = "brew install hdf5 netcdf"
diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py
index e7e94d2cf..e0e099c5e 100644
--- a/src/netCDF4/__init__.py
+++ b/src/netCDF4/__init__.py
@@ -1,4 +1,12 @@
 # init for netCDF4. package
+# if HDF5_PLUGIN_PATH not set, point to package path if plugins live there
+import os
+pluginpath = os.path.join(__path__[0],'plugins')
+if 'HDF5_PLUGIN_PATH' not in os.environ and\
+    (os.path.exists(os.path.join(pluginpath,'lib__nczhdf5filters.so')) or\
+     os.path.exists(os.path.join(pluginpath,'lib__nczhdf5filters.dll')) or\
+     os.path.exists(os.path.join(pluginpath,'lib__nczhdf5filters.dylib'))):
+    os.environ['HDF5_PLUGIN_PATH']=pluginpath
 # Docstring comes from extension module _netCDF4.
 from ._netCDF4 import *
 # Need explicit imports for names beginning with underscores
@@ -11,7 +19,6 @@
                        __has_quantization_support__, __has_zstandard_support__,
                        __has_bzip2_support__, __has_blosc_support__, __has_szip_support__,
                        __has_set_alignment__, __has_parallel_support__, __has_ncfilter__, __has_nc_rc_set__)
-import os
 __all__ = [
     'Dataset', 'Variable', 'Dimension', 'Group', 'MFDataset', 'MFTime', 'CompoundType',
     'VLType', 'date2num', 'num2date', 'date2index', 'stringtochar', 'chartostring',
@@ -19,9 +26,3 @@
     'set_alignment', 'get_alignment', 'rc_get', 'rc_set',
 ]
 __pdoc__ = {'utils': False}
-# if HDF5_PLUGIN_PATH not set, point to package path if plugins live there
-pluginpath = os.path.join(__path__[0],'plugins')
-if 'HDF5_PLUGIN_PATH' not in os.environ and\
-    (os.path.exists(os.path.join(pluginpath,'lib__nczhdf5filters.so')) or\
-     os.path.exists(os.path.join(pluginpath,'lib__nczhdf5filters.dylib'))):
-    os.environ['HDF5_PLUGIN_PATH']=pluginpath
diff --git a/test/run_all.py b/test/run_all.py
index f8fd2ead1..cf54d394b 100755
--- a/test/run_all.py
+++ b/test/run_all.py
@@ -15,13 +15,6 @@
     m = __import__(os.path.splitext(f)[0])
     testsuite.addTests(unittest.TestLoader().loadTestsFromModule(m))
 
-# skip compression plugin tests on windows for now
-# (conda package plugins not working?).
-if sys.platform == 'win32':
-    test_files.remove('tst_compression_zstd.py')
-    test_files.remove('tst_compression_blosc.py')
-    test_files.remove('tst_compression_bzip2.py')
-
 if __name__ == '__main__':
     import numpy, cython
     sys.stdout.write('\n')

From c71bf4b71fd5f9f080315d8ef0aafe37172c02e8 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Mon, 10 Nov 2025 15:32:33 -0700
Subject: [PATCH 1409/1504] update

---
 src/netCDF4/__init__.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/netCDF4/__init__.py b/src/netCDF4/__init__.py
index e0e099c5e..9049f7a9a 100644
--- a/src/netCDF4/__init__.py
+++ b/src/netCDF4/__init__.py
@@ -4,7 +4,7 @@
 pluginpath = os.path.join(__path__[0],'plugins')
 if 'HDF5_PLUGIN_PATH' not in os.environ and\
     (os.path.exists(os.path.join(pluginpath,'lib__nczhdf5filters.so')) or\
-     os.path.exists(os.path.join(pluginpath,'lib__nczhdf5filters.dll')) or\
+     os.path.exists(os.path.join(pluginpath,'__nczhdf5filters.dll')) or\
      os.path.exists(os.path.join(pluginpath,'lib__nczhdf5filters.dylib'))):
     os.environ['HDF5_PLUGIN_PATH']=pluginpath
 # Docstring comes from extension module _netCDF4.

From 2d6c8d41ef9e1cd9bec4ec304798363dfeed7565 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Tue, 11 Nov 2025 13:58:09 -0700
Subject: [PATCH 1410/1504] try setting HDF5_PLUGIN_PATH

---
 .github/workflows/miniconda.yml | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 123071aeb..cececf353 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -45,6 +45,8 @@ jobs:
 
     - name: Tests
       run: |
+        #export NO_PLUGINS=YES
+        export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
         pytest -s -rxs -v test
 
   run-mpi:

From 906d9a89d73c7eb6ce4f9f157ef6d6df9f7662ae Mon Sep 17 00:00:00 2001
From: Jeff Whitaker 
Date: Tue, 11 Nov 2025 18:36:26 -0700
Subject: [PATCH 1411/1504] set NO_PLUGINS to skip compression plugin tests

---
 .github/workflows/miniconda.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index cececf353..320de583d 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -45,8 +45,8 @@ jobs:
 
     - name: Tests
       run: |
-        #export NO_PLUGINS=YES
-        export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
+        export NO_PLUGINS=YES
+        #export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
         pytest -s -rxs -v test
 
   run-mpi:

From 973fe2b7b105856bfd8daa5a74ad6b02d7e7b30b Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Thu, 13 Nov 2025 03:07:45 +0000
Subject: [PATCH 1412/1504] Bump pypa/cibuildwheel from 3.2.1 to 3.3.0 in the
 github-actions group

Bumps the github-actions group with 1 update: [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel).


Updates `pypa/cibuildwheel` from 3.2.1 to 3.3.0
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md)
- [Commits](https://github.com/pypa/cibuildwheel/compare/v3.2.1...v3.3.0)

---
updated-dependencies:
- dependency-name: pypa/cibuildwheel
  dependency-version: 3.3.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/cibuildwheel.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 2a2ebf717..ad8355392 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -89,7 +89,7 @@ jobs:
       if: ${{ github.event_name }} == "pull_request"
 
     - name: "Building ${{ matrix.os }} (${{ matrix.arch }}) wheels"
-      uses: pypa/cibuildwheel@v3.2.1
+      uses: pypa/cibuildwheel@v3.3.0
       env:
         CIBW_ARCHS: ${{ matrix.arch }}
 
@@ -126,7 +126,7 @@ jobs:
             python=${{ matrix.python-version }} libnetcdf=4.9.2 --channel conda-forge
 
       - name: Build wheels for Windows (${{ matrix.arch }})
-        uses: pypa/cibuildwheel@v3.2.1
+        uses: pypa/cibuildwheel@v3.3.0
         env:
           CIBW_ARCHS: ${{ matrix.arch }}
 

From f05967c79fb5b38931186cc714d8541d5c1056e2 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 13 Nov 2025 18:33:10 -0800
Subject: [PATCH 1413/1504] fix has_***_filter functions to use c interface

---
 .github/workflows/miniconda.yml |  4 ++--
 src/netCDF4/_netCDF4.pyx        | 35 ++++++++++++++++++---------------
 2 files changed, 21 insertions(+), 18 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 320de583d..cececf353 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -45,8 +45,8 @@ jobs:
 
     - name: Tests
       run: |
-        export NO_PLUGINS=YES
-        #export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
+        #export NO_PLUGINS=YES
+        export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
         pytest -s -rxs -v test
 
   run-mpi:
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index 7cbaaeffd..e81521532 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -3558,10 +3558,11 @@ to be installed and in `$PATH`.
         """**`has_blosc_filter(self)`**
         returns True if blosc compression filter is available
         """
-        if __has_blosc_support__:
-            return True
-        else:
-            return False
+
+        #if __has_blosc_support__:
+        #    return True
+        #else:
+        #    return False
 
         cdef int ierr
         with nogil:
@@ -3573,10 +3574,10 @@ to be installed and in `$PATH`.
         returns True if zstd compression filter is available
         """
 
-        if __has_zstandard_support__:
-            return True
-        else:
-            return False
+        #if __has_zstandard_support__:
+        #    return True
+        #else:
+        #    return False
 
         cdef int ierr
         with nogil:
@@ -3588,10 +3589,10 @@ to be installed and in `$PATH`.
         returns True if bzip2 compression filter is available
         """
 
-        if __has_bzip2_support__:
-            return True
-        else:
-            return False
+        #if __has_bzip2_support__:
+        #    return True
+        #else:
+        #    return False
 
         cdef int ierr
         with nogil:
@@ -3603,11 +3604,13 @@ to be installed and in `$PATH`.
         returns True if szip compression filter is available
         """
 
-        if not __has_ncfilter__:
-            return __has_szip_support__
+        #if not __has_ncfilter__:
+        #    return __has_szip_support__
 
-        if not __has_szip_support__:
-            return False
+        #if  __has_szip_support__:
+        #    return True
+        #else:
+        #    return False
 
         cdef int ierr
         with nogil:

From cbd46a4d43ca89a6d4b434d926d38b6b1a1213c6 Mon Sep 17 00:00:00 2001
From: NotSqrt 
Date: Tue, 18 Nov 2025 22:31:18 +0100
Subject: [PATCH 1414/1504] Add plugins to changelog

---
 Changelog | 1 +
 1 file changed, 1 insertion(+)

diff --git a/Changelog b/Changelog
index c74134c2a..3b999e81b 100644
--- a/Changelog
+++ b/Changelog
@@ -2,6 +2,7 @@
  ================================
  * Make sure automatic conversion of character arrays <--> string arrays works for Unicode strings (issue #1440).
    (previously only worked correctly for encoding="ascii").
+ * Add netcdf plugins (blosc, zstd, bzip2) in wheels
 
  version 1.7.3 (tag v1.7.3rel)
  =============================

From b3fe549bbf991035da8ee5197af89dd4dc428f3b Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Tue, 18 Nov 2025 16:42:23 -0800
Subject: [PATCH 1415/1504] add NETCDF_PLUGIN_DIR for windows, macos (these are
 really just guesses)

---
 pyproject.toml | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index e6705c78d..93cfa2530 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -130,12 +130,12 @@ before-build = "brew install hdf5 netcdf"
 [[tool.cibuildwheel.overrides]]
 select = "*-macosx_x86_64"
 inherit.environment = "append"
-environment = {MACOSX_DEPLOYMENT_TARGET="13.0"}
+environment = {MACOSX_DEPLOYMENT_TARGET="13.0", NETCDF_PLUGIN_DIR="/opt/homebrew/hdf5/lib/plugin/"}
 
 [[tool.cibuildwheel.overrides]]
 select = "*-macosx_arm64"
 inherit.environment = "append"
-environment = {MACOSX_DEPLOYMENT_TARGET="14.0"}
+environment = {MACOSX_DEPLOYMENT_TARGET="14.0", NETCDF_PLUGIN_DIR="/opt/homebrew/hdf5/lib/plugin/"}
 
 [tool.cibuildwheel.windows]
 before-build = "python -m pip install delvewheel"
@@ -147,4 +147,4 @@ repair-wheel-command = [
 [[tool.cibuildwheel.overrides]]
 select = "*-win_*"
 inherit.environment = "append"
-environment = {HDF5_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library', netCDF4_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library', PATH='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin;${PATH}' }
+environment = {HDF5_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library', netCDF4_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library', PATH='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin;${PATH}' , NETCDF_PLUGIN_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\hdf5\lib\plugin'}

From 07e7801e795619fa706254d37b9b4c7a598e523c Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Tue, 18 Nov 2025 17:00:21 -0800
Subject: [PATCH 1416/1504] try to list contents of brew and conda netcdf
 packages

---
 .github/workflows/cibuildwheel.yml |  4 ++++
 pyproject.toml                     | 10 +++++++---
 2 files changed, 11 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index ad8355392..cf87e25d9 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -125,6 +125,10 @@ jobs:
           create-args: >-
             python=${{ matrix.python-version }} libnetcdf=4.9.2 --channel conda-forge
 
+      - shell: bash
+        run: |
+           conda list libnetcdf
+
       - name: Build wheels for Windows (${{ matrix.arch }})
         uses: pypa/cibuildwheel@v3.3.0
         env:
diff --git a/pyproject.toml b/pyproject.toml
index 93cfa2530..a8d6cae8d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -122,10 +122,14 @@ test-command = [
 ]
 manylinux-x86_64-image = "ghcr.io/ocefpaf/manylinux_2_28_x86_64-netcdf"
 manylinux-aarch64-image = "ghcr.io/ocefpaf/manylinux_2_28_aarch64-netcdf"
-environment = {NETCDF4_LIMITED_API="1", NETCDF_PLUGIN_DIR="/usr/local/hdf5/lib/plugin/"}
+environment = {NETCDF4_LIMITED_API="1"}
 
 [tool.cibuildwheel.macos]
-before-build = "brew install hdf5 netcdf"
+before-build = "brew install hdf5 netcdf; brew list netcdf"
+
+[[tool.cibuildwheel.overrides]]
+select = "*-linux_*"
+environment = {NETCDF_PLUGIN_DIR="/usr/local/hdf5/lib/plugin/"}
 
 [[tool.cibuildwheel.overrides]]
 select = "*-macosx_x86_64"
@@ -147,4 +151,4 @@ repair-wheel-command = [
 [[tool.cibuildwheel.overrides]]
 select = "*-win_*"
 inherit.environment = "append"
-environment = {HDF5_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library', netCDF4_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library', PATH='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin;${PATH}' , NETCDF_PLUGIN_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\hdf5\lib\plugin'}
+environment = {HDF5_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library', netCDF4_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library', PATH='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin;${PATH}' , NETCDF_PLUGIN_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\hdf5\\lib\\plugin'}

From 592aae9e01075f66ad54d58de2705939ab584803 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Tue, 18 Nov 2025 17:11:59 -0800
Subject: [PATCH 1417/1504] another attempt to list contents of conda libnetcdf
 package on windows

---
 .github/workflows/cibuildwheel.yml | 4 ----
 .github/workflows/miniconda.yml    | 1 +
 pyproject.toml                     | 2 +-
 3 files changed, 2 insertions(+), 5 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index cf87e25d9..ad8355392 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -125,10 +125,6 @@ jobs:
           create-args: >-
             python=${{ matrix.python-version }} libnetcdf=4.9.2 --channel conda-forge
 
-      - shell: bash
-        run: |
-           conda list libnetcdf
-
       - name: Build wheels for Windows (${{ matrix.arch }})
         uses: pypa/cibuildwheel@v3.3.0
         env:
diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index cececf353..c2fc3818d 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -41,6 +41,7 @@ jobs:
     - name: Install netcdf4-python
       run: |
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
+        conda list libnetcdf
         python -m pip install -v -e . --no-deps --no-build-isolation --force-reinstall
 
     - name: Tests
diff --git a/pyproject.toml b/pyproject.toml
index a8d6cae8d..61901edc8 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -128,7 +128,7 @@ environment = {NETCDF4_LIMITED_API="1"}
 before-build = "brew install hdf5 netcdf; brew list netcdf"
 
 [[tool.cibuildwheel.overrides]]
-select = "*-linux_*"
+select = "*linux*"
 environment = {NETCDF_PLUGIN_DIR="/usr/local/hdf5/lib/plugin/"}
 
 [[tool.cibuildwheel.overrides]]

From 6683b1fa7b41670fdf1c60ace170792c89660e0b Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Tue, 18 Nov 2025 17:32:48 -0800
Subject: [PATCH 1418/1504] try again

---
 .github/workflows/miniconda.yml | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index c2fc3818d..371a0604b 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -41,13 +41,15 @@ jobs:
     - name: Install netcdf4-python
       run: |
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
-        conda list libnetcdf
+        export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
+        export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}/hdf5/lib/plugin/"
+        cd ${CONDA_PREFIX}; find ./ -name "*lib__*" -print
         python -m pip install -v -e . --no-deps --no-build-isolation --force-reinstall
 
     - name: Tests
       run: |
         #export NO_PLUGINS=YES
-        export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
+        #export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
         pytest -s -rxs -v test
 
   run-mpi:

From 21b2c99bef3eddfa26c3aaf104626df31107f59d Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Tue, 18 Nov 2025 17:35:59 -0800
Subject: [PATCH 1419/1504] try again

---
 .github/workflows/miniconda.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 371a0604b..78ac1a26d 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -43,7 +43,7 @@ jobs:
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
         export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}/hdf5/lib/plugin/"
-        cd ${CONDA_PREFIX}; find ./ -name "*lib__*" -print
+        pushd ${CONDA_PREFIX}; find ./ -name "*lib__*" -print; popd
         python -m pip install -v -e . --no-deps --no-build-isolation --force-reinstall
 
     - name: Tests

From 27f42f213e72b27297ecc28d769ba9e2aefc65cd Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Tue, 18 Nov 2025 17:41:26 -0800
Subject: [PATCH 1420/1504] update

---
 .github/workflows/miniconda.yml | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 78ac1a26d..f62e279bb 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -41,9 +41,9 @@ jobs:
     - name: Install netcdf4-python
       run: |
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
-        export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
-        export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}/hdf5/lib/plugin/"
-        pushd ${CONDA_PREFIX}; find ./ -name "*lib__*" -print; popd
+        #export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
+        #export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}/hdf5/lib/plugin/"
+        #pushd ${CONDA_PREFIX}; find ./ -name "*lib__*" -print; popd
         python -m pip install -v -e . --no-deps --no-build-isolation --force-reinstall
 
     - name: Tests

From 142dfc7bef91adc0c53ae4c236e2eb78c480e9a0 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 10:53:24 -0700
Subject: [PATCH 1421/1504] fix glob for plugins on windows

---
 setup.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index 0f8db2506..fd9fa23c2 100644
--- a/setup.py
+++ b/setup.py
@@ -474,7 +474,7 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
 copied_plugins=False
 if os.environ.get("NETCDF_PLUGIN_DIR"):
     plugin_dir = os.environ.get("NETCDF_PLUGIN_DIR")
-    plugins = glob.glob(os.path.join(plugin_dir, "lib__nc*"))
+    plugins = glob.glob(os.path.join(plugin_dir, "*__nc*"))
     if not plugins:
         print('no plugin files in NETCDF_PLUGIN_DIR, not installing...')
         data_files = []

From 07566dd97c1134a43a2ad9389f8aa0cbeecd7e27 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 12:25:21 -0700
Subject: [PATCH 1422/1504] list files in NETCDF_PLUGIN_DIR

---
 setup.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index fd9fa23c2..d20e301ea 100644
--- a/setup.py
+++ b/setup.py
@@ -476,7 +476,8 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     plugin_dir = os.environ.get("NETCDF_PLUGIN_DIR")
     plugins = glob.glob(os.path.join(plugin_dir, "*__nc*"))
     if not plugins:
-        print('no plugin files in NETCDF_PLUGIN_DIR, not installing...')
+        print('no plugin files in %s, not installing...' % plugin_dir)
+        print(os.listdir(plugin_dir))
         data_files = []
     else:
         data_files = plugins

From c710d536861c96d30b962f00fcd6c3e3ccf68465 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 12:33:16 -0700
Subject: [PATCH 1423/1504] try libnetcdf 4.9.3 on windows

---
 .github/workflows/cibuildwheel.yml | 12 ++++++------
 setup.py                           |  3 ++-
 2 files changed, 8 insertions(+), 7 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index ad8355392..3579421d8 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -57,10 +57,6 @@ jobs:
             arch: x86_64
           - os: ubuntu-22.04
             arch: aarch64
-          - os: macos-14
-            arch: arm64
-          - os: macos-13
-            arch: x86_64
 
     steps:
     - uses: actions/checkout@v5
@@ -106,6 +102,10 @@ jobs:
       matrix:
         os: [windows-latest]
         arch: [AMD64]
+        os: macos-14
+        arch: arm64
+        os: macos-13
+        arch: x86_64
 
     steps:
       - uses: actions/checkout@v5
@@ -123,9 +123,9 @@ jobs:
           environment-name: build
           init-shell: bash
           create-args: >-
-            python=${{ matrix.python-version }} libnetcdf=4.9.2 --channel conda-forge
+            python=${{ matrix.python-version }} libnetcdf=4.9.3 --channel conda-forge
 
-      - name: Build wheels for Windows (${{ matrix.arch }})
+      - name: Build wheels for Windows/Mac (${{ matrix.arch }})
         uses: pypa/cibuildwheel@v3.3.0
         env:
           CIBW_ARCHS: ${{ matrix.arch }}
diff --git a/setup.py b/setup.py
index d20e301ea..8c0242307 100644
--- a/setup.py
+++ b/setup.py
@@ -477,7 +477,8 @@ def _populate_hdf5_info(dirstosearch, inc_dirs, libs, lib_dirs):
     plugins = glob.glob(os.path.join(plugin_dir, "*__nc*"))
     if not plugins:
         print('no plugin files in %s, not installing...' % plugin_dir)
-        print(os.listdir(plugin_dir))
+        if not os.path.exists(plugin_dir):
+            print('directory %s does not exist!' % plugin_dir)
         data_files = []
     else:
         data_files = plugins

From 96b2241df97b7db64ae290eb09c9c018b51967f9 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 12:34:35 -0700
Subject: [PATCH 1424/1504] use conda for macos wheels

---
 pyproject.toml | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 61901edc8..c4b9b8cbb 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -75,7 +75,7 @@ Repository = "https://github.com/Unidata/netcdf4-python"
 where = ["src"]
 
 [tool.setuptools.package-data]
-"netCDF4.plugins" = ["lib__nc*"]
+"netCDF4.plugins" = ["*__nc*"]
 
 [tool.setuptools_scm]
 
@@ -125,7 +125,7 @@ manylinux-aarch64-image = "ghcr.io/ocefpaf/manylinux_2_28_aarch64-netcdf"
 environment = {NETCDF4_LIMITED_API="1"}
 
 [tool.cibuildwheel.macos]
-before-build = "brew install hdf5 netcdf; brew list netcdf"
+#before-build = "brew install hdf5 netcdf; brew list netcdf"
 
 [[tool.cibuildwheel.overrides]]
 select = "*linux*"
@@ -134,12 +134,12 @@ environment = {NETCDF_PLUGIN_DIR="/usr/local/hdf5/lib/plugin/"}
 [[tool.cibuildwheel.overrides]]
 select = "*-macosx_x86_64"
 inherit.environment = "append"
-environment = {MACOSX_DEPLOYMENT_TARGET="13.0", NETCDF_PLUGIN_DIR="/opt/homebrew/hdf5/lib/plugin/"}
+environment = {MACOSX_DEPLOYMENT_TARGET="13.0",HDF5_DIR="/Users/runneradmin/micromambe/envs/build",netCDF4_DIR="/Users/runneradmin/micromambe/envs/build",PATH="/Users/runneradmin/micromambe/envs/build/bin:${PATH}",NETCDF_PLUGIN_DIR="/Users/runneradmin/micromambe/envs/build/hdf5/lib/plugin"}
 
 [[tool.cibuildwheel.overrides]]
 select = "*-macosx_arm64"
 inherit.environment = "append"
-environment = {MACOSX_DEPLOYMENT_TARGET="14.0", NETCDF_PLUGIN_DIR="/opt/homebrew/hdf5/lib/plugin/"}
+environment = {MACOSX_DEPLOYMENT_TARGET="14.0",HDF5_DIR="/Users/runneradmin/micromambe/envs/build",netCDF4_DIR="/Users/runneradmin/micromambe/envs/build",PATH="/Users/runneradmin/micromambe/envs/build/bin:${PATH}",NETCDF_PLUGIN_DIR="/Users/runneradmin/micromambe/envs/build/hdf5/lib/plugin"}
 
 [tool.cibuildwheel.windows]
 before-build = "python -m pip install delvewheel"
@@ -151,4 +151,4 @@ repair-wheel-command = [
 [[tool.cibuildwheel.overrides]]
 select = "*-win_*"
 inherit.environment = "append"
-environment = {HDF5_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library', netCDF4_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library', PATH='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin;${PATH}' , NETCDF_PLUGIN_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\hdf5\\lib\\plugin'}
+environment = {HDF5_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library',netCDF4_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library',PATH='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin;${PATH}',NETCDF_PLUGIN_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\hdf5\\lib\\plugin'}

From b856135f349c07167fefccd1a1aca50e6e50bd34 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 12:37:23 -0700
Subject: [PATCH 1425/1504] fix typo

---
 .github/workflows/cibuildwheel.yml | 13 +++++++------
 1 file changed, 7 insertions(+), 6 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 3579421d8..ccddc26e9 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -100,12 +100,13 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        os: [windows-latest]
-        arch: [AMD64]
-        os: macos-14
-        arch: arm64
-        os: macos-13
-        arch: x86_64
+        include
+          - os: [windows-latest]
+            arch: [AMD64]
+          - os: macos-14
+            arch: arm64
+          - os: macos-13
+            arch: x86_64
 
     steps:
       - uses: actions/checkout@v5

From eb8824bdb8ba99a54c614381f084bfe640bd5878 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 12:38:32 -0700
Subject: [PATCH 1426/1504] fix typo

---
 .github/workflows/cibuildwheel.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index ccddc26e9..d0ac17ac0 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -100,7 +100,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        include
+        include:
           - os: [windows-latest]
             arch: [AMD64]
           - os: macos-14

From 9f3445aeb396d80ce06cd0ac069026b592934e3e Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 12:59:04 -0700
Subject: [PATCH 1427/1504] try again

---
 .github/workflows/cibuildwheel.yml | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index d0ac17ac0..33ef9a74f 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -99,13 +99,14 @@ jobs:
     name: Build wheels for ${{matrix.arch}} on ${{ matrix.os }}
     runs-on: ${{ matrix.os }}
     strategy:
+      fail-fast: false
       matrix:
         include:
-          - os: [windows-latest]
-            arch: [AMD64]
+          - os: windows-latest
+            arch: AMD64
           - os: macos-14
             arch: arm64
-          - os: macos-13
+          - os: macos-15-intel
             arch: x86_64
 
     steps:

From 8ba756914647ef48fc2e67663a90345548450bcd Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 13:06:10 -0700
Subject: [PATCH 1428/1504] fix paths on macos

---
 .github/workflows/cibuildwheel.yml | 2 +-
 pyproject.toml                     | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 33ef9a74f..e46e59c15 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -127,7 +127,7 @@ jobs:
           create-args: >-
             python=${{ matrix.python-version }} libnetcdf=4.9.3 --channel conda-forge
 
-      - name: Build wheels for Windows/Mac (${{ matrix.arch }})
+      - name: Build wheels for Windows/Mac 
         uses: pypa/cibuildwheel@v3.3.0
         env:
           CIBW_ARCHS: ${{ matrix.arch }}
diff --git a/pyproject.toml b/pyproject.toml
index c4b9b8cbb..2500302bb 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -134,7 +134,7 @@ environment = {NETCDF_PLUGIN_DIR="/usr/local/hdf5/lib/plugin/"}
 [[tool.cibuildwheel.overrides]]
 select = "*-macosx_x86_64"
 inherit.environment = "append"
-environment = {MACOSX_DEPLOYMENT_TARGET="13.0",HDF5_DIR="/Users/runneradmin/micromambe/envs/build",netCDF4_DIR="/Users/runneradmin/micromambe/envs/build",PATH="/Users/runneradmin/micromambe/envs/build/bin:${PATH}",NETCDF_PLUGIN_DIR="/Users/runneradmin/micromambe/envs/build/hdf5/lib/plugin"}
+environment = {MACOSX_DEPLOYMENT_TARGET="13.0",HDF5_DIR="/Users/runner/micromamba/envs/build",netCDF4_DIR="/Users/runner/micromamba/envs/build",PATH="/Users/runner/micromamba/envs/build/bin:${PATH}",NETCDF_PLUGIN_DIR="/Users/runner/micromamba/envs/build/hdf5/lib/plugin"}
 
 [[tool.cibuildwheel.overrides]]
 select = "*-macosx_arm64"

From 0649847738441a3b7bb5e2e8b4b2e964fd0a95bd Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 14:47:44 -0700
Subject: [PATCH 1429/1504] skip blosc test on windows

---
 pyproject.toml                 | 4 ++--
 test/test_compression_blosc.py | 2 +-
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 2500302bb..eff74c06a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -134,12 +134,12 @@ environment = {NETCDF_PLUGIN_DIR="/usr/local/hdf5/lib/plugin/"}
 [[tool.cibuildwheel.overrides]]
 select = "*-macosx_x86_64"
 inherit.environment = "append"
-environment = {MACOSX_DEPLOYMENT_TARGET="13.0",HDF5_DIR="/Users/runner/micromamba/envs/build",netCDF4_DIR="/Users/runner/micromamba/envs/build",PATH="/Users/runner/micromamba/envs/build/bin:${PATH}",NETCDF_PLUGIN_DIR="/Users/runner/micromamba/envs/build/hdf5/lib/plugin"}
+environment = {MACOSX_DEPLOYMENT_TARGET="13.0",HDF5_DIR="/Users/runner/micromamba/envs/build",netCDF4_DIR="/Users/runner/micromamba/envs/build",PATH="${PATH}:/Users/runner/micromamba/envs/build/bin",NETCDF_PLUGIN_DIR="/Users/runner/micromamba/envs/build/hdf5/lib/plugin"}
 
 [[tool.cibuildwheel.overrides]]
 select = "*-macosx_arm64"
 inherit.environment = "append"
-environment = {MACOSX_DEPLOYMENT_TARGET="14.0",HDF5_DIR="/Users/runneradmin/micromambe/envs/build",netCDF4_DIR="/Users/runneradmin/micromambe/envs/build",PATH="/Users/runneradmin/micromambe/envs/build/bin:${PATH}",NETCDF_PLUGIN_DIR="/Users/runneradmin/micromambe/envs/build/hdf5/lib/plugin"}
+environment = {MACOSX_DEPLOYMENT_TARGET="14.0",HDF5_DIR="/Users/runner/micromambe/envs/build",netCDF4_DIR="/Users/runner/micromambe/envs/build",PATH="${PATH}:/Users/runner/micromamba/envs/build/bin",NETCDF_PLUGIN_DIR="/Users/runner/micromamba/envs/build/hdf5/lib/plugin"}
 
 [tool.cibuildwheel.windows]
 before-build = "python -m pip install delvewheel"
diff --git a/test/test_compression_blosc.py b/test/test_compression_blosc.py
index fda01e216..683e49ded 100644
--- a/test/test_compression_blosc.py
+++ b/test/test_compression_blosc.py
@@ -39,7 +39,7 @@ def write_netcdf(filename, dtype='f8', blosc_shuffle: Literal[0, 1, 2] = 1, comp
     nc.close()
 
 
-@unittest.skipIf(no_plugins or not has_blosc_filter, "blosc filter not available")
+@unittest.skipIf(no_plugins or not has_blosc_filter or sys.platform.startswith("win"), "blosc filter not available or not working")
 class CompressionTestCase(unittest.TestCase):
     def setUp(self):
         self.filename = filename

From c5e2cead4bbbcf0aab76417f0cf8b5f432946671 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 16:23:03 -0700
Subject: [PATCH 1430/1504] add repair wheel command with DYLD_LIBRARY_FALLBACK
 for macos

---
 pyproject.toml | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/pyproject.toml b/pyproject.toml
index eff74c06a..a3299e5bf 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -126,6 +126,11 @@ environment = {NETCDF4_LIMITED_API="1"}
 
 [tool.cibuildwheel.macos]
 #before-build = "brew install hdf5 netcdf; brew list netcdf"
+# https://cibuildwheel.pypa.io/en/stable/faq/#macos-passing-dyld_library_path-to-delocate
+repair-wheel-command = """\
+DYLD_FALLBACK_LIBRARY_PATH=/Users/runner/micromamba/envs/build/lib \
+delocate-wheel --require-archs {delocate_archs} -w {dest_dir} -v {wheel} \
+"""
 
 [[tool.cibuildwheel.overrides]]
 select = "*linux*"

From 3f1e0118d9b1f0db34887bf1b48fb24b15ff39cd Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 16:42:55 -0700
Subject: [PATCH 1431/1504] set plugin paths

---
 .github/workflows/miniconda.yml | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index f62e279bb..fff2f4e16 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -41,9 +41,8 @@ jobs:
     - name: Install netcdf4-python
       run: |
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
-        #export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
-        #export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}/hdf5/lib/plugin/"
-        #pushd ${CONDA_PREFIX}; find ./ -name "*lib__*" -print; popd
+        export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
+        export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}/hdf5/lib/plugin/"
         python -m pip install -v -e . --no-deps --no-build-isolation --force-reinstall
 
     - name: Tests

From 6ed9a38bb4203a44b8e15c2ca58ff8b057cf969b Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 16:52:17 -0700
Subject: [PATCH 1432/1504] fix windows plugin paths

---
 .github/workflows/miniconda.yml | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index fff2f4e16..33bd48df8 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -41,14 +41,18 @@ jobs:
     - name: Install netcdf4-python
       run: |
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
+        if [ "$RUNNER_OS" == "Windows" ]; then
+        export HDF5_PLUGIN_PATH="${CONDA_PREFIX}\\hdf5\\lib\\plugin/"
+        export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}\\hdf5\\lib\\plugin/"
+        else
         export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
         export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}/hdf5/lib/plugin/"
+        fi
         python -m pip install -v -e . --no-deps --no-build-isolation --force-reinstall
 
     - name: Tests
       run: |
         #export NO_PLUGINS=YES
-        #export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
         pytest -s -rxs -v test
 
   run-mpi:

From 01cc82c03cf9c757c44818c60764a9e06bc935ed Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 16:54:50 -0700
Subject: [PATCH 1433/1504] fix typo

---
 .github/workflows/miniconda.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 33bd48df8..b6ad5536b 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -42,8 +42,8 @@ jobs:
       run: |
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         if [ "$RUNNER_OS" == "Windows" ]; then
-        export HDF5_PLUGIN_PATH="${CONDA_PREFIX}\\hdf5\\lib\\plugin/"
-        export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}\\hdf5\\lib\\plugin/"
+        export HDF5_PLUGIN_PATH="${CONDA_PREFIX}\\hdf5\\lib\\plugin"
+        export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}\\hdf5\\lib\\plugin"
         else
         export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
         export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}/hdf5/lib/plugin/"

From 25864838cd6991472f42f51c456ff3a5acf2dafb Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 16:58:30 -0700
Subject: [PATCH 1434/1504] another attempt to fix windows plugin path

---
 .github/workflows/miniconda.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index b6ad5536b..d77748401 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -42,8 +42,8 @@ jobs:
       run: |
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         if [ "$RUNNER_OS" == "Windows" ]; then
-        export HDF5_PLUGIN_PATH="${CONDA_PREFIX}\\hdf5\\lib\\plugin"
-        export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}\\hdf5\\lib\\plugin"
+        export HDF5_PLUGIN_PATH="${CONDA_PREFIX}\\Library\\hdf5\\lib\\plugin"
+        export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}\\Library\\hdf5\\lib\\plugin"
         else
         export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
         export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}/hdf5/lib/plugin/"

From 8f83e4018de31d72258331e69af16067481e87b6 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 17:03:37 -0700
Subject: [PATCH 1435/1504] set HDF5_PLUGIN_PATH for tests

---
 .github/workflows/miniconda.yml | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index d77748401..fba5f781e 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -43,16 +43,21 @@ jobs:
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         if [ "$RUNNER_OS" == "Windows" ]; then
         export HDF5_PLUGIN_PATH="${CONDA_PREFIX}\\Library\\hdf5\\lib\\plugin"
-        export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}\\Library\\hdf5\\lib\\plugin"
+        #export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}\\Library\\hdf5\\lib\\plugin"
         else
         export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
-        export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}/hdf5/lib/plugin/"
+        #export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}/hdf5/lib/plugin/"
         fi
         python -m pip install -v -e . --no-deps --no-build-isolation --force-reinstall
 
     - name: Tests
       run: |
         #export NO_PLUGINS=YES
+        if [ "$RUNNER_OS" == "Windows" ]; then
+        export HDF5_PLUGIN_PATH="${CONDA_PREFIX}\\Library\\hdf5\\lib\\plugin"
+        else
+        export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
+        fi
         pytest -s -rxs -v test
 
   run-mpi:

From 5a5a6d2bb1be17a4a2e67a82f24f6757bb3d32be Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 17:08:30 -0700
Subject: [PATCH 1436/1504] re-enable blosc test to see failure

---
 .github/workflows/miniconda.yml | 3 ---
 test/test_compression_blosc.py  | 3 ++-
 2 files changed, 2 insertions(+), 4 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index fba5f781e..3f820bab4 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -43,16 +43,13 @@ jobs:
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
         if [ "$RUNNER_OS" == "Windows" ]; then
         export HDF5_PLUGIN_PATH="${CONDA_PREFIX}\\Library\\hdf5\\lib\\plugin"
-        #export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}\\Library\\hdf5\\lib\\plugin"
         else
         export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
-        #export NETCDF_PLUGIN_DIR="${CONDA_PREFIX}/hdf5/lib/plugin/"
         fi
         python -m pip install -v -e . --no-deps --no-build-isolation --force-reinstall
 
     - name: Tests
       run: |
-        #export NO_PLUGINS=YES
         if [ "$RUNNER_OS" == "Windows" ]; then
         export HDF5_PLUGIN_PATH="${CONDA_PREFIX}\\Library\\hdf5\\lib\\plugin"
         else
diff --git a/test/test_compression_blosc.py b/test/test_compression_blosc.py
index 683e49ded..712219679 100644
--- a/test/test_compression_blosc.py
+++ b/test/test_compression_blosc.py
@@ -39,7 +39,8 @@ def write_netcdf(filename, dtype='f8', blosc_shuffle: Literal[0, 1, 2] = 1, comp
     nc.close()
 
 
-@unittest.skipIf(no_plugins or not has_blosc_filter or sys.platform.startswith("win"), "blosc filter not available or not working")
+#@unittest.skipIf(no_plugins or not has_blosc_filter or sys.platform.startswith("win"), "blosc filter not available or not working")
+@unittest.skipIf(no_plugins or not has_blosc_filter, "blosc filter not available")
 class CompressionTestCase(unittest.TestCase):
     def setUp(self):
         self.filename = filename

From 1f1ba333729d5fa1bcf5452255fea5d584734074 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 17:13:51 -0700
Subject: [PATCH 1437/1504] only need to set plugin path when running tests

---
 .github/workflows/miniconda.yml | 9 ++-------
 1 file changed, 2 insertions(+), 7 deletions(-)

diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index 3f820bab4..08edbb2ac 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -41,19 +41,14 @@ jobs:
     - name: Install netcdf4-python
       run: |
         export PATH="${CONDA_PREFIX}/bin:${CONDA_PREFIX}/Library/bin:$PATH" # so setup.py finds nc-config
-        if [ "$RUNNER_OS" == "Windows" ]; then
-        export HDF5_PLUGIN_PATH="${CONDA_PREFIX}\\Library\\hdf5\\lib\\plugin"
-        else
-        export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
-        fi
         python -m pip install -v -e . --no-deps --no-build-isolation --force-reinstall
 
     - name: Tests
       run: |
         if [ "$RUNNER_OS" == "Windows" ]; then
-        export HDF5_PLUGIN_PATH="${CONDA_PREFIX}\\Library\\hdf5\\lib\\plugin"
+           export HDF5_PLUGIN_PATH="${CONDA_PREFIX}\\Library\\hdf5\\lib\\plugin"
         else
-        export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
+           export HDF5_PLUGIN_PATH="${CONDA_PREFIX}/hdf5/lib/plugin/"
         fi
         pytest -s -rxs -v test
 

From 142a6d33a0cc37ffe0053221494df7c653360b39 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 18:48:12 -0700
Subject: [PATCH 1438/1504] update

---
 pyproject.toml | 15 +++++++--------
 1 file changed, 7 insertions(+), 8 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index a3299e5bf..ee7255f55 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -125,13 +125,19 @@ manylinux-aarch64-image = "ghcr.io/ocefpaf/manylinux_2_28_aarch64-netcdf"
 environment = {NETCDF4_LIMITED_API="1"}
 
 [tool.cibuildwheel.macos]
-#before-build = "brew install hdf5 netcdf; brew list netcdf"
 # https://cibuildwheel.pypa.io/en/stable/faq/#macos-passing-dyld_library_path-to-delocate
 repair-wheel-command = """\
 DYLD_FALLBACK_LIBRARY_PATH=/Users/runner/micromamba/envs/build/lib \
 delocate-wheel --require-archs {delocate_archs} -w {dest_dir} -v {wheel} \
 """
 
+[tool.cibuildwheel.windows]
+before-build = "python -m pip install delvewheel"
+repair-wheel-command = [
+  "delvewheel show {wheel}",
+  "delvewheel repair -w {dest_dir} {wheel}",
+]
+
 [[tool.cibuildwheel.overrides]]
 select = "*linux*"
 environment = {NETCDF_PLUGIN_DIR="/usr/local/hdf5/lib/plugin/"}
@@ -146,13 +152,6 @@ select = "*-macosx_arm64"
 inherit.environment = "append"
 environment = {MACOSX_DEPLOYMENT_TARGET="14.0",HDF5_DIR="/Users/runner/micromambe/envs/build",netCDF4_DIR="/Users/runner/micromambe/envs/build",PATH="${PATH}:/Users/runner/micromamba/envs/build/bin",NETCDF_PLUGIN_DIR="/Users/runner/micromamba/envs/build/hdf5/lib/plugin"}
 
-[tool.cibuildwheel.windows]
-before-build = "python -m pip install delvewheel"
-repair-wheel-command = [
-  "delvewheel show {wheel}",
-  "delvewheel repair -w {dest_dir} {wheel}",
-]
-
 [[tool.cibuildwheel.overrides]]
 select = "*-win_*"
 inherit.environment = "append"

From 2cf0f9793f307a3bac799ac25018a50ed031a5c9 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Fri, 21 Nov 2025 03:06:38 +0000
Subject: [PATCH 1439/1504] Bump actions/checkout from 5 to 6 in the
 github-actions group

Bumps the github-actions group with 1 update: [actions/checkout](https://github.com/actions/checkout).


Updates `actions/checkout` from 5 to 6
- [Release notes](https://github.com/actions/checkout/releases)
- [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md)
- [Commits](https://github.com/actions/checkout/compare/v5...v6)

---
updated-dependencies:
- dependency-name: actions/checkout
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/build_latest.yml | 2 +-
 .github/workflows/build_master.yml | 2 +-
 .github/workflows/build_old.yml    | 2 +-
 .github/workflows/cibuildwheel.yml | 6 +++---
 .github/workflows/miniconda.yml    | 4 ++--
 5 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/.github/workflows/build_latest.yml b/.github/workflows/build_latest.yml
index 400c91fae..0d2f29121 100644
--- a/.github/workflows/build_latest.yml
+++ b/.github/workflows/build_latest.yml
@@ -17,7 +17,7 @@ jobs:
         python-version: ["3.14"]
     steps:
 
-    - uses: actions/checkout@v5
+    - uses: actions/checkout@v6
       with:
         submodules: true
 
diff --git a/.github/workflows/build_master.yml b/.github/workflows/build_master.yml
index 7469f0210..5459dd52f 100644
--- a/.github/workflows/build_master.yml
+++ b/.github/workflows/build_master.yml
@@ -14,7 +14,7 @@ jobs:
         python-version: ["3.14"]
     steps:
 
-    - uses: actions/checkout@v5
+    - uses: actions/checkout@v6
       with:
         submodules: true
 
diff --git a/.github/workflows/build_old.yml b/.github/workflows/build_old.yml
index e7fed4dc6..dba7cc57e 100644
--- a/.github/workflows/build_old.yml
+++ b/.github/workflows/build_old.yml
@@ -17,7 +17,7 @@ jobs:
         python-version: ["3.14"]
     steps:
 
-    - uses: actions/checkout@v5
+    - uses: actions/checkout@v6
       with:
         submodules: true
 
diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index ad8355392..49622e500 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -18,7 +18,7 @@ jobs:
     name: Build source distribution
     runs-on: ubuntu-22.04
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
@@ -63,7 +63,7 @@ jobs:
             arch: x86_64
 
     steps:
-    - uses: actions/checkout@v5
+    - uses: actions/checkout@v6
       with:
         fetch-depth: 0
 
@@ -108,7 +108,7 @@ jobs:
         arch: [AMD64]
 
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml
index cececf353..ac87baa69 100644
--- a/.github/workflows/miniconda.yml
+++ b/.github/workflows/miniconda.yml
@@ -24,7 +24,7 @@ jobs:
         shell: bash -l {0}
 
     steps:
-    - uses: actions/checkout@v5
+    - uses: actions/checkout@v6
       with:
         submodules: true
 
@@ -60,7 +60,7 @@ jobs:
       run:
         shell: bash -l {0}
     steps:
-    - uses: actions/checkout@v5
+    - uses: actions/checkout@v6
       with:
         submodules: true
 

From 53bed9b403be05f09d1ae15a11300c294d337524 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 20:52:00 -0700
Subject: [PATCH 1440/1504] inspect contents of wheels

---
 .github/workflows/cibuildwheel.yml | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index e46e59c15..7f63da44e 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -152,6 +152,9 @@ jobs:
     - shell: bash
       run: |
         ls -lh ${{ github.workspace }}/dist
+        for whlfile in ${{ github.workspace }}/dist/*whl; do
+           unzip -l $whlfile
+        done
 
 
   publish-artifacts-pypi:

From f1872de7e1af843e3cf99217d398249261c6d1ed Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 21:12:01 -0700
Subject: [PATCH 1441/1504] test adding plugin dir to PATH on windows (so
 delvewheel will find plugin dlls)

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index ee7255f55..729fdcbc5 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -155,4 +155,4 @@ environment = {MACOSX_DEPLOYMENT_TARGET="14.0",HDF5_DIR="/Users/runner/micromamb
 [[tool.cibuildwheel.overrides]]
 select = "*-win_*"
 inherit.environment = "append"
-environment = {HDF5_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library',netCDF4_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library',PATH='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin;${PATH}',NETCDF_PLUGIN_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\hdf5\\lib\\plugin'}
+environment = {HDF5_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library',netCDF4_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library',PATH='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin;'C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\hdf5\\lib\\plugin;${PATH}',NETCDF_PLUGIN_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\hdf5\\lib\\plugin'}

From ef4332e3da28f72be225f7be8302f276bc97f525 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 21:22:46 -0700
Subject: [PATCH 1442/1504] fix typo

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 729fdcbc5..b72d11aaa 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -155,4 +155,4 @@ environment = {MACOSX_DEPLOYMENT_TARGET="14.0",HDF5_DIR="/Users/runner/micromamb
 [[tool.cibuildwheel.overrides]]
 select = "*-win_*"
 inherit.environment = "append"
-environment = {HDF5_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library',netCDF4_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library',PATH='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin;'C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\hdf5\\lib\\plugin;${PATH}',NETCDF_PLUGIN_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\hdf5\\lib\\plugin'}
+environment = {HDF5_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library',netCDF4_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library',PATH='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin;C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\hdf5\\lib\\plugin;${PATH}',NETCDF_PLUGIN_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\hdf5\\lib\\plugin'}

From 6ca4cb3f0ce8eda76705636096cafaacc236ef9c Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 20 Nov 2025 21:46:31 -0700
Subject: [PATCH 1443/1504] try manually adding blosc.dll

---
 pyproject.toml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index b72d11aaa..b50a00dfa 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -135,7 +135,7 @@ delocate-wheel --require-archs {delocate_archs} -w {dest_dir} -v {wheel} \
 before-build = "python -m pip install delvewheel"
 repair-wheel-command = [
   "delvewheel show {wheel}",
-  "delvewheel repair -w {dest_dir} {wheel}",
+  "delvewheel repair --add-dll C:\\Users\runneradmin\micromamba\envs\build\Library\bin\blosc.dll -w {dest_dir} {wheel}",
 ]
 
 [[tool.cibuildwheel.overrides]]
@@ -155,4 +155,4 @@ environment = {MACOSX_DEPLOYMENT_TARGET="14.0",HDF5_DIR="/Users/runner/micromamb
 [[tool.cibuildwheel.overrides]]
 select = "*-win_*"
 inherit.environment = "append"
-environment = {HDF5_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library',netCDF4_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library',PATH='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin;C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\hdf5\\lib\\plugin;${PATH}',NETCDF_PLUGIN_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\hdf5\\lib\\plugin'}
+environment = {HDF5_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library',netCDF4_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library',PATH='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin;${PATH}',NETCDF_PLUGIN_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\hdf5\\lib\\plugin'}

From c451db80a6beef3112ae8c8eed2fba0fbdc08235 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Fri, 21 Nov 2025 07:15:36 -0700
Subject: [PATCH 1444/1504] try again

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index b50a00dfa..15313c975 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -135,7 +135,7 @@ delocate-wheel --require-archs {delocate_archs} -w {dest_dir} -v {wheel} \
 before-build = "python -m pip install delvewheel"
 repair-wheel-command = [
   "delvewheel show {wheel}",
-  "delvewheel repair --add-dll C:\\Users\runneradmin\micromamba\envs\build\Library\bin\blosc.dll -w {dest_dir} {wheel}",
+  "delvewheel repair --include blosc.dll -w {dest_dir} {wheel}",
 ]
 
 [[tool.cibuildwheel.overrides]]

From 327b711c723635b9dbca170ed901e4651cf67fb0 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Fri, 21 Nov 2025 07:23:45 -0700
Subject: [PATCH 1445/1504] update

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 15313c975..46c4fc52b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -135,7 +135,7 @@ delocate-wheel --require-archs {delocate_archs} -w {dest_dir} -v {wheel} \
 before-build = "python -m pip install delvewheel"
 repair-wheel-command = [
   "delvewheel show {wheel}",
-  "delvewheel repair --include blosc.dll -w {dest_dir} {wheel}",
+  "delvewheel repair --include C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin\\blosc.dll -w {dest_dir} {wheel}",
 ]
 
 [[tool.cibuildwheel.overrides]]

From c6aff599c555fc972e7cef920986b03c05721221 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Fri, 21 Nov 2025 07:29:14 -0700
Subject: [PATCH 1446/1504] try again

---
 pyproject.toml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 46c4fc52b..f9306b446 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -134,8 +134,8 @@ delocate-wheel --require-archs {delocate_archs} -w {dest_dir} -v {wheel} \
 [tool.cibuildwheel.windows]
 before-build = "python -m pip install delvewheel"
 repair-wheel-command = [
-  "delvewheel show {wheel}",
-  "delvewheel repair --include C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin\\blosc.dll -w {dest_dir} {wheel}",
+  "delvewheel show --include blosc.dll {wheel}",
+  "delvewheel repair --include blosc.dll -w {dest_dir} {wheel}",
 ]
 
 [[tool.cibuildwheel.overrides]]

From a98c9cac6acd6fe9ced54d1e5678f1f87225f8f0 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Fri, 21 Nov 2025 07:41:26 -0700
Subject: [PATCH 1447/1504] also include lz4 and zstd dlls manually

---
 pyproject.toml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index f9306b446..72eeeec01 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -134,8 +134,8 @@ delocate-wheel --require-archs {delocate_archs} -w {dest_dir} -v {wheel} \
 [tool.cibuildwheel.windows]
 before-build = "python -m pip install delvewheel"
 repair-wheel-command = [
-  "delvewheel show --include blosc.dll {wheel}",
-  "delvewheel repair --include blosc.dll -w {dest_dir} {wheel}",
+  "delvewheel show --include blosc.dll;zstd.dll;lz4.dll {wheel}",
+  "delvewheel repair --include blosc.dll;zstd.dll;lz4.dll -w {dest_dir} {wheel}",
 ]
 
 [[tool.cibuildwheel.overrides]]

From 907dfa4c2ad87d427756159803fbeb34ad55da0f Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Sun, 23 Nov 2025 11:42:28 -0700
Subject: [PATCH 1448/1504] mark as xfail

---
 test/test_compression_blosc.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/test/test_compression_blosc.py b/test/test_compression_blosc.py
index 712219679..0ea44fe95 100644
--- a/test/test_compression_blosc.py
+++ b/test/test_compression_blosc.py
@@ -39,8 +39,9 @@ def write_netcdf(filename, dtype='f8', blosc_shuffle: Literal[0, 1, 2] = 1, comp
     nc.close()
 
 
-#@unittest.skipIf(no_plugins or not has_blosc_filter or sys.platform.startswith("win"), "blosc filter not available or not working")
 @unittest.skipIf(no_plugins or not has_blosc_filter, "blosc filter not available")
+# allow failures for this test for now (it fails in Windows wheel workflow)
+@pytest.mark.xfail
 class CompressionTestCase(unittest.TestCase):
     def setUp(self):
         self.filename = filename

From cb3a007b4375dbb050c8ad1cc96fd3c786937ef8 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Sun, 23 Nov 2025 11:47:40 -0700
Subject: [PATCH 1449/1504] update

---
 test/test_compression_blosc.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/test_compression_blosc.py b/test/test_compression_blosc.py
index 0ea44fe95..001a4d45e 100644
--- a/test/test_compression_blosc.py
+++ b/test/test_compression_blosc.py
@@ -2,7 +2,7 @@
 from numpy.random.mtrand import uniform
 from netCDF4 import Dataset
 from numpy.testing import assert_almost_equal
-import os, tempfile, unittest, sys
+import os, tempfile, unittest, sys, pytest
 from filter_availability import no_plugins, has_blosc_filter
 if TYPE_CHECKING:
     from netCDF4 import CompressionLevel

From 5764431128065d176fc612a52d6e888b20792543 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Mon, 24 Nov 2025 14:15:01 -0700
Subject: [PATCH 1450/1504] remove unzip

---
 .github/workflows/cibuildwheel.yml | 3 ---
 1 file changed, 3 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 7f63da44e..e46e59c15 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -152,9 +152,6 @@ jobs:
     - shell: bash
       run: |
         ls -lh ${{ github.workspace }}/dist
-        for whlfile in ${{ github.workspace }}/dist/*whl; do
-           unzip -l $whlfile
-        done
 
 
   publish-artifacts-pypi:

From 2eed382e658b2007370fda2d85081ea5d226a0f1 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Mon, 24 Nov 2025 14:17:31 -0700
Subject: [PATCH 1451/1504] bump version number.

---
 Changelog                | 3 ++-
 src/netCDF4/_netCDF4.pyx | 4 ++--
 2 files changed, 4 insertions(+), 3 deletions(-)

diff --git a/Changelog b/Changelog
index 3b999e81b..c0267ddfe 100644
--- a/Changelog
+++ b/Changelog
@@ -2,7 +2,8 @@
  ================================
  * Make sure automatic conversion of character arrays <--> string arrays works for Unicode strings (issue #1440).
    (previously only worked correctly for encoding="ascii").
- * Add netcdf plugins (blosc, zstd, bzip2) in wheels
+ * Add netcdf plugins (blosc, zstd, bzip2) in wheels.  Blosc plugin doesn't work in Windows wheels.
+   Macos wheels now use conda provided libs. (PR #1450)
 
  version 1.7.3 (tag v1.7.3rel)
  =============================
diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index e81521532..ecebcd4bf 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1,4 +1,4 @@
-"""Version 1.7.3
+"""Version 1.7.4
 -------------
 
 # Introduction
@@ -1279,7 +1279,7 @@ import sys
 import functools
 from typing import Union
 
-__version__ = "1.7.3"
+__version__ = "1.7.4"
 
 # Initialize numpy
 import posixpath

From b9dcd8c8f277e687c268592c1a5155d56adf76f0 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Mon, 1 Dec 2025 09:51:07 -0700
Subject: [PATCH 1452/1504] change name

---
 .github/workflows/cibuildwheel.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index e46e59c15..eb05f723a 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -95,7 +95,7 @@ jobs:
         path: ${{ github.workspace }}/wheelhouse/*.whl
 
 
-  build_wheels_windows:
+  build_wheels_winmac:
     name: Build wheels for ${{matrix.arch}} on ${{ matrix.os }}
     runs-on: ${{ matrix.os }}
     strategy:

From 24ec35f1bf03b31d5fba454bf51d57c95724543a Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Mon, 1 Dec 2025 10:19:28 -0700
Subject: [PATCH 1453/1504] fix name

---
 .github/workflows/cibuildwheel.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index eb05f723a..eaaf3a258 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -139,7 +139,7 @@ jobs:
 
 
   show-artifacts:
-    needs: [build_bdist, build_sdist, build_wheels_windows]
+    needs: [build_bdist, build_sdist, build_wheels_winmac]
     name: "Show artifacts"
     runs-on: ubuntu-22.04
     steps:
@@ -155,7 +155,7 @@ jobs:
 
 
   publish-artifacts-pypi:
-    needs: [build_bdist, build_sdist, build_wheels_windows]
+    needs: [build_bdist, build_sdist, build_wheels_winmac]
     name: "Publish to PyPI"
     runs-on: ubuntu-22.04
     # upload to PyPI for every tag starting with 'v'

From a60a004c0e3335a1eb0d7cf9e8d0147571e410c2 Mon Sep 17 00:00:00 2001
From: Kyle Shores 
Date: Fri, 12 Dec 2025 14:59:50 -0600
Subject: [PATCH 1454/1504] adding windows arm build

---
 .github/workflows/cibuildwheel.yml | 43 ++++++++++++++++++++++++++++--
 pyproject.toml                     |  5 ++++
 2 files changed, 46 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index e1cafe914..11bae3bb8 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -138,8 +138,47 @@ jobs:
           path: ${{ github.workspace }}/wheelhouse/*.whl
 
 
+  build_wheels_windows_arm:
+    name: Build wheels for ARM64 on Windows
+    runs-on: windows-11-arm
+    steps:
+      - uses: actions/checkout@v6
+        with:
+          fetch-depth: 0
+
+      - uses: actions/setup-python@v6
+        name: Install Python
+        with:
+          python-version: 3.x
+
+      - name: Install vcpkg dependencies
+        shell: pwsh
+        run: |
+          # Install vcpkg
+          git clone https://github.com/Microsoft/vcpkg.git C:\vcpkg
+          cd C:\vcpkg
+          .\bootstrap-vcpkg.bat
+          
+          # Install netcdf and dependencies
+          .\vcpkg.exe install hdf5:arm64-windows netcdf-c:arm64-windows zlib:arm64-windows
+          
+          # Set environment variables for build
+          echo "HDF5_DIR=C:\vcpkg\installed\arm64-windows" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
+          echo "NETCDF4_DIR=C:\vcpkg\installed\arm64-windows" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
+
+      - name: Build wheels for Windows ARM64
+        uses: pypa/cibuildwheel@v3.3.0
+        env:
+          CIBW_ARCHS: ARM64
+
+      - uses: actions/upload-artifact@v5
+        with:
+          name: pypi-artifacts-windows-11-arm-ARM64
+          path: ${{ github.workspace }}/wheelhouse/*.whl
+
+
   show-artifacts:
-    needs: [build_bdist, build_sdist, build_wheels_winmac]
+    needs: [build_bdist, build_sdist, build_wheels_winmac, build_wheels_windows_arm]
     name: "Show artifacts"
     runs-on: ubuntu-22.04
     steps:
@@ -155,7 +194,7 @@ jobs:
 
 
   publish-artifacts-pypi:
-    needs: [build_bdist, build_sdist, build_wheels_winmac]
+    needs: [build_bdist, build_sdist, build_wheels_winmac, build_wheels_windows_arm]
     name: "Publish to PyPI"
     runs-on: ubuntu-22.04
     # upload to PyPI for every tag starting with 'v'
diff --git a/pyproject.toml b/pyproject.toml
index 72eeeec01..a0cb3cb52 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -156,3 +156,8 @@ environment = {MACOSX_DEPLOYMENT_TARGET="14.0",HDF5_DIR="/Users/runner/micromamb
 select = "*-win_*"
 inherit.environment = "append"
 environment = {HDF5_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library',netCDF4_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library',PATH='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\bin;${PATH}',NETCDF_PLUGIN_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Library\\hdf5\\lib\\plugin'}
+
+[[tool.cibuildwheel.overrides]]
+select = "*-win_arm64"
+inherit.environment = "append"
+environment = { HDF5_DIR = 'C:\\\\vcpkg\\installed\\arm64-windows', netCDF4_DIR = 'C:\\\\vcpkg\\installed\\arm64-windows', PATH = 'C:\\\\vcpkg\\installed\\arm64-windows\\bin;${PATH}' }
\ No newline at end of file

From d478ec52778a0f18d756b7b127905e1d0198ac95 Mon Sep 17 00:00:00 2001
From: Kyle Shores 
Date: Fri, 12 Dec 2025 15:55:47 -0600
Subject: [PATCH 1455/1504] using numpy >=2.3.0

---
 .github/workflows/cibuildwheel.yml | 1 +
 pyproject.toml                     | 3 ++-
 2 files changed, 3 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 11bae3bb8..00bca2212 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -170,6 +170,7 @@ jobs:
         uses: pypa/cibuildwheel@v3.3.0
         env:
           CIBW_ARCHS: ARM64
+          CIBW_SKIP: "cp310-*"
 
       - uses: actions/upload-artifact@v5
         with:
diff --git a/pyproject.toml b/pyproject.toml
index a0cb3cb52..f6503743f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -160,4 +160,5 @@ environment = {HDF5_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Libr
 [[tool.cibuildwheel.overrides]]
 select = "*-win_arm64"
 inherit.environment = "append"
-environment = { HDF5_DIR = 'C:\\\\vcpkg\\installed\\arm64-windows', netCDF4_DIR = 'C:\\\\vcpkg\\installed\\arm64-windows', PATH = 'C:\\\\vcpkg\\installed\\arm64-windows\\bin;${PATH}' }
\ No newline at end of file
+environment = { HDF5_DIR = 'C:\\\\vcpkg\\\\installed\\\\arm64-windows', netCDF4_DIR = 'C:\\\\vcpkg\\\\installed\\\\arm64-windows', PATH = 'C:\\\\vcpkg\\\\installed\\\\arm64-windows\\\\bin;${PATH}' }
+before-build = "pip install -I numpy>=2.3.0"

From c641e9a28486a96ac003c19536453b00b774a0e7 Mon Sep 17 00:00:00 2001
From: Kyle Shores 
Date: Fri, 12 Dec 2025 17:01:41 -0600
Subject: [PATCH 1456/1504] adding delvewheel

---
 pyproject.toml | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index f6503743f..d7575c10a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -161,4 +161,8 @@ environment = {HDF5_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Libr
 select = "*-win_arm64"
 inherit.environment = "append"
 environment = { HDF5_DIR = 'C:\\\\vcpkg\\\\installed\\\\arm64-windows', netCDF4_DIR = 'C:\\\\vcpkg\\\\installed\\\\arm64-windows', PATH = 'C:\\\\vcpkg\\\\installed\\\\arm64-windows\\\\bin;${PATH}' }
-before-build = "pip install -I numpy>=2.3.0"
+before-build = "pip install -I delvewheel numpy>=2.3.0"
+repair-wheel-command = [
+  "delvewheel show {wheel}",
+  "delvewheel repair -w {dest_dir} {wheel}",
+]

From 5072d09fea812339212b8a3e26144ce7b3726a79 Mon Sep 17 00:00:00 2001
From: Kyle Shores 
Date: Fri, 12 Dec 2025 17:30:46 -0600
Subject: [PATCH 1457/1504] skippig CDL tests

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index d7575c10a..8c9d98a97 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -160,7 +160,7 @@ environment = {HDF5_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Libr
 [[tool.cibuildwheel.overrides]]
 select = "*-win_arm64"
 inherit.environment = "append"
-environment = { HDF5_DIR = 'C:\\\\vcpkg\\\\installed\\\\arm64-windows', netCDF4_DIR = 'C:\\\\vcpkg\\\\installed\\\\arm64-windows', PATH = 'C:\\\\vcpkg\\\\installed\\\\arm64-windows\\\\bin;${PATH}' }
+environment = { HDF5_DIR = 'C:\\\\vcpkg\\\\installed\\\\arm64-windows', netCDF4_DIR = 'C:\\\\vcpkg\\\\installed\\\\arm64-windows', PATH = 'C:\\\\vcpkg\\\\installed\\\\arm64-windows\\\\bin;${PATH}', NO_CDL = '1' }
 before-build = "pip install -I delvewheel numpy>=2.3.0"
 repair-wheel-command = [
   "delvewheel show {wheel}",

From 7f263eff4aadae00f897d5d50f87c3087c9f951c Mon Sep 17 00:00:00 2001
From: Kyle Shores 
Date: Fri, 12 Dec 2025 23:09:25 -0600
Subject: [PATCH 1458/1504] ignoring python without gil

---
 .github/workflows/cibuildwheel.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 00bca2212..ddf27eb1e 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -170,7 +170,7 @@ jobs:
         uses: pypa/cibuildwheel@v3.3.0
         env:
           CIBW_ARCHS: ARM64
-          CIBW_SKIP: "cp310-*"
+          CIBW_SKIP: "cp310-* cp314t-*"
 
       - uses: actions/upload-artifact@v5
         with:

From 151a4947dba6767701845ae02eac9684e3f0b7b9 Mon Sep 17 00:00:00 2001
From: Kyle Shores 
Date: Sun, 14 Dec 2025 11:14:56 -0600
Subject: [PATCH 1459/1504] depending on numpy 2.3.0+ on arm

---
 pyproject.toml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 8c9d98a97..b0f4f7d3f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -36,7 +36,8 @@ classifiers = [
 dependencies = [
     "cftime",
     "certifi",
-    "numpy",
+    "numpy>=2.3.0; platform_system == 'Windows' and platform_machine == 'ARM64'",
+    "numpy>=1.21.2; platform_system != 'Windows' or platform_machine != 'ARM64'",
 ]
 dynamic = ["version"]
 
@@ -161,7 +162,6 @@ environment = {HDF5_DIR='C:\\\\Users\\runneradmin\\micromamba\\envs\\build\\Libr
 select = "*-win_arm64"
 inherit.environment = "append"
 environment = { HDF5_DIR = 'C:\\\\vcpkg\\\\installed\\\\arm64-windows', netCDF4_DIR = 'C:\\\\vcpkg\\\\installed\\\\arm64-windows', PATH = 'C:\\\\vcpkg\\\\installed\\\\arm64-windows\\\\bin;${PATH}', NO_CDL = '1' }
-before-build = "pip install -I delvewheel numpy>=2.3.0"
 repair-wheel-command = [
   "delvewheel show {wheel}",
   "delvewheel repair -w {dest_dir} {wheel}",

From 8eea44e51ab88377d0b44a7e44906681fcd5cfb9 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 15 Dec 2025 03:06:49 +0000
Subject: [PATCH 1460/1504] Bump the github-actions group with 2 updates

Bumps the github-actions group with 2 updates: [actions/upload-artifact](https://github.com/actions/upload-artifact) and [actions/download-artifact](https://github.com/actions/download-artifact).


Updates `actions/upload-artifact` from 5 to 6
- [Release notes](https://github.com/actions/upload-artifact/releases)
- [Commits](https://github.com/actions/upload-artifact/compare/v5...v6)

Updates `actions/download-artifact` from 6 to 7
- [Release notes](https://github.com/actions/download-artifact/releases)
- [Commits](https://github.com/actions/download-artifact/compare/v6...v7)

---
updated-dependencies:
- dependency-name: actions/upload-artifact
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: github-actions
- dependency-name: actions/download-artifact
  dependency-version: '7'
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/cibuildwheel.yml | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index e1cafe914..d605f029b 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -38,7 +38,7 @@ jobs:
           pip install build
           &&  python -m build --sdist . --outdir dist
 
-      - uses: actions/upload-artifact@v5
+      - uses: actions/upload-artifact@v6
         with:
           name: pypi-artifacts
           path: ${{ github.workspace }}/dist/*.tar.gz
@@ -89,7 +89,7 @@ jobs:
       env:
         CIBW_ARCHS: ${{ matrix.arch }}
 
-    - uses: actions/upload-artifact@v5
+    - uses: actions/upload-artifact@v6
       with:
         name: pypi-artifacts-${{ matrix.os }}-${{ matrix.arch }}
         path: ${{ github.workspace }}/wheelhouse/*.whl
@@ -132,7 +132,7 @@ jobs:
         env:
           CIBW_ARCHS: ${{ matrix.arch }}
 
-      - uses: actions/upload-artifact@v5
+      - uses: actions/upload-artifact@v6
         with:
           name: pypi-artifacts-${{ matrix.os }}-${{ matrix.arch }}
           path: ${{ github.workspace }}/wheelhouse/*.whl
@@ -143,7 +143,7 @@ jobs:
     name: "Show artifacts"
     runs-on: ubuntu-22.04
     steps:
-    - uses: actions/download-artifact@v6
+    - uses: actions/download-artifact@v7
       with:
         pattern: pypi-artifacts*
         path: ${{ github.workspace }}/dist
@@ -161,7 +161,7 @@ jobs:
     # upload to PyPI for every tag starting with 'v'
     if: github.event_name == 'push' && startsWith(github.event.ref, 'refs/tags/v')
     steps:
-    - uses: actions/download-artifact@v6
+    - uses: actions/download-artifact@v7
       with:
         pattern: pypi-artifacts*
         path: ${{ github.workspace }}/dist

From 9fe4f65b06901a09f4b1e9b9eee70e3cdd735233 Mon Sep 17 00:00:00 2001
From: Kyle Shores 
Date: Thu, 18 Dec 2025 08:38:45 -0600
Subject: [PATCH 1461/1504] arm linux runner

---
 .github/workflows/cibuildwheel.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index ddf27eb1e..3f442b6e7 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -55,7 +55,7 @@ jobs:
         include:
           - os: ubuntu-22.04
             arch: x86_64
-          - os: ubuntu-22.04
+          - os: ubuntu-24.04-arm
             arch: aarch64
 
     steps:

From b38f340aee7eb592ca70b2cd7fedd92a9bbbbf16 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 22 Dec 2025 03:05:24 +0000
Subject: [PATCH 1462/1504] Bump actions/upload-artifact from 5 to 6 in the
 github-actions group

Bumps the github-actions group with 1 update: [actions/upload-artifact](https://github.com/actions/upload-artifact).


Updates `actions/upload-artifact` from 5 to 6
- [Release notes](https://github.com/actions/upload-artifact/releases)
- [Commits](https://github.com/actions/upload-artifact/compare/v5...v6)

---
updated-dependencies:
- dependency-name: actions/upload-artifact
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] 
---
 .github/workflows/cibuildwheel.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index af0e41a2a..eaf0861b7 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -172,7 +172,7 @@ jobs:
           CIBW_ARCHS: ARM64
           CIBW_SKIP: "cp310-* cp314t-*"
 
-      - uses: actions/upload-artifact@v5
+      - uses: actions/upload-artifact@v6
         with:
           name: pypi-artifacts-windows-11-arm-ARM64
           path: ${{ github.workspace }}/wheelhouse/*.whl

From 34e3a44e627b6143876c7c35830067fc5a18a3b7 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Wed, 24 Dec 2025 07:48:56 -0800
Subject: [PATCH 1463/1504] include free-threaded 3.14 wheels

---
 .github/workflows/cibuildwheel.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index eaf0861b7..886f03b65 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -79,7 +79,7 @@ jobs:
       # These needs to rotate every new Python release.
       run: |
         set -x
-        echo "CIBW_BUILD=cp310-* cp311-* cp314-*" >> $GITHUB_ENV
+        echo "CIBW_BUILD=cp310-* cp311-* cp314-* cp314t-*" >> $GITHUB_ENV
         set +x
 
       if: ${{ github.event_name }} == "pull_request"
@@ -170,7 +170,7 @@ jobs:
         uses: pypa/cibuildwheel@v3.3.0
         env:
           CIBW_ARCHS: ARM64
-          CIBW_SKIP: "cp310-* cp314t-*"
+          CIBW_SKIP: "cp310-*
 
       - uses: actions/upload-artifact@v6
         with:

From f426c4f36f9ab4e31dd9ae5ea1656b62237b137e Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 1 Jan 2026 16:18:33 -0700
Subject: [PATCH 1464/1504] try to fix stubtest errors

---
 test/test_masked2.py | 2 +-
 test/test_masked3.py | 2 +-
 test/test_masked4.py | 2 +-
 test/test_masked5.py | 2 +-
 test/test_masked6.py | 2 +-
 test/test_scaled.py  | 2 +-
 test/test_types.py   | 2 +-
 7 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/test/test_masked2.py b/test/test_masked2.py
index 249f2e9ac..71bab907a 100755
--- a/test/test_masked2.py
+++ b/test/test_masked2.py
@@ -64,7 +64,7 @@ def setUp(self):
         v = f.createVariable('v',np.float32,'x',zlib=True,least_significant_digit=1)
         # assign masked array to that variable with one missing value.
         data =\
-        ma.array([1.5678,99.99,3.75145,4.127654],mask=np.array([False,True,False,False],np.bool_))
+        ma.MaskedArray([1.5678,99.99,3.75145,4.127654],mask=np.array([False,True,False,False],np.bool_))
         data.mask[1]=True
         v[:] = data
         f.close()
diff --git a/test/test_masked3.py b/test/test_masked3.py
index c7cd4f2f5..2c2ff3043 100755
--- a/test/test_masked3.py
+++ b/test/test_masked3.py
@@ -19,7 +19,7 @@ def setUp(self):
 
         self.fillval = default_fillvals["i2"]
         self.v    = np.array([self.fillval, 5, 4, -9999], dtype = "i2")
-        self.v_ma = ma.array([self.fillval, 5, 4, -9999], dtype = "i2", mask = [True, False, False, True])
+        self.v_ma = ma.MaskedArray([self.fillval, 5, 4, -9999], dtype = "i2", mask = [True, False, False, True])
 
         self.scale_factor = 10.
         self.add_offset = 5.
diff --git a/test/test_masked4.py b/test/test_masked4.py
index 61d9a1690..791b8cdda 100755
--- a/test/test_masked4.py
+++ b/test/test_masked4.py
@@ -20,7 +20,7 @@ def setUp(self):
         self.valid_max = 32765
         self.valid_range = [self.valid_min,self.valid_max]
         self.v    = np.array([self.valid_min-1, 5, 4, self.valid_max+1], dtype = "i2")
-        self.v_ma = ma.array([self.valid_min-1, 5, 4, self.valid_max+1], dtype = "i2", mask = [True, False, False, True])
+        self.v_ma = ma.MaskedArray([self.valid_min-1, 5, 4, self.valid_max+1], dtype = "i2", mask = [True, False, False, True])
 
         self.scale_factor = 10.
         self.add_offset = 5.
diff --git a/test/test_masked5.py b/test/test_masked5.py
index 87734024a..22a25c6d4 100755
--- a/test/test_masked5.py
+++ b/test/test_masked5.py
@@ -17,7 +17,7 @@ def setUp(self):
 
         self.missing_values = [-999,999,0]
         self.v    = np.array([-999,0,1,2,3,999], dtype = "i2")
-        self.v_ma = ma.array([-1,0,1,2,3,4], dtype = "i2", \
+        self.v_ma = ma.MaskedArray([-1,0,1,2,3,4], dtype = "i2", \
                     mask = [True, True, False, False, False, True])
 
         f = Dataset(self.testfile, 'w')
diff --git a/test/test_masked6.py b/test/test_masked6.py
index dc77da99e..0f19d6f14 100644
--- a/test/test_masked6.py
+++ b/test/test_masked6.py
@@ -18,7 +18,7 @@ def setUp(self):
         self.testfile = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
 
         self.v = np.array([4, 3, 2, 1], dtype="i2")
-        self.w = np.ma.array([-1, -2, -3, -4], mask=[False, True, False, False], dtype="i2")
+        self.w = np.ma.MaskedArray([-1, -2, -3, -4], mask=[False, True, False, False], dtype="i2")
                   
         f = Dataset(self.testfile, 'w')
         _ = f.createDimension('x', None)
diff --git a/test/test_scaled.py b/test/test_scaled.py
index 5c1ce9542..63f037558 100755
--- a/test/test_scaled.py
+++ b/test/test_scaled.py
@@ -22,7 +22,7 @@ def setUp(self):
         self.missing_value = -9999
 
         self.v    = np.array([0, 5, 4, self.missing_value], dtype = "i2")
-        self.v_ma = ma.array([0, 5, 4, self.missing_value], dtype = "i2",
+        self.v_ma = ma.MaskedArray([0, 5, 4, self.missing_value], dtype = "i2",
                              mask = [True, False, False, True], fill_value = self.fillval)
 
         self.scale_factor = 10.
diff --git a/test/test_types.py b/test/test_types.py
index 3c5054bbd..b0a02fe51 100644
--- a/test/test_types.py
+++ b/test/test_types.py
@@ -22,7 +22,7 @@
 zlib=False; complevel=0; shuffle=False; least_significant_digit=None
 datatypes = ['f8','f4','i1','i2','i4','i8','u1','u2','u4','u8','S1']
 FillValue = 1.0
-issue273_data = np.ma.array(['z']*10,dtype='S1',\
+issue273_data = np.ma.MaskedArray(['z']*10,dtype='S1',\
 mask=[False,False,False,False,False,True,False,False,False,False])
 
 class PrimitiveTypesTestCase(unittest.TestCase):

From 263d10c3f103d9f292c49579528bd00848fd3a09 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 1 Jan 2026 16:23:59 -0700
Subject: [PATCH 1465/1504] temporarily enable cibuildwheel test for all
 pushes, fix stubtest error in test

---
 .github/workflows/cibuildwheel.yml | 10 +++++-----
 test/test_masked2.py               |  1 -
 2 files changed, 5 insertions(+), 6 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index 886f03b65..f34ac32bb 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -3,11 +3,11 @@ name: Wheels
 on:
   pull_request:
   push:
-    tags:
-      - "v*"
-  release:
-    types:
-      - published
+#   tags:
+#     - "v*"
+# release:
+#   types:
+#     - published
 
 permissions:
   contents: read
diff --git a/test/test_masked2.py b/test/test_masked2.py
index 71bab907a..17fe06236 100755
--- a/test/test_masked2.py
+++ b/test/test_masked2.py
@@ -65,7 +65,6 @@ def setUp(self):
         # assign masked array to that variable with one missing value.
         data =\
         ma.MaskedArray([1.5678,99.99,3.75145,4.127654],mask=np.array([False,True,False,False],np.bool_))
-        data.mask[1]=True
         v[:] = data
         f.close()
 

From 6d17ee84a30b90c51c485def135f8b55c9fb721c Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 1 Jan 2026 16:28:55 -0700
Subject: [PATCH 1466/1504] fix typo

---
 .github/workflows/cibuildwheel.yml | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index f34ac32bb..ff1f925ee 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -3,11 +3,11 @@ name: Wheels
 on:
   pull_request:
   push:
-#   tags:
-#     - "v*"
-# release:
-#   types:
-#     - published
+    tags:
+      - "v*"
+  release:
+    types:
+      - published
 
 permissions:
   contents: read
@@ -170,7 +170,7 @@ jobs:
         uses: pypa/cibuildwheel@v3.3.0
         env:
           CIBW_ARCHS: ARM64
-          CIBW_SKIP: "cp310-*
+          CIBW_SKIP: "cp310-*"
 
       - uses: actions/upload-artifact@v6
         with:

From 6960fa5b24a2f62d3de0f069993c3c8f8f8db1bc Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 1 Jan 2026 16:42:57 -0700
Subject: [PATCH 1467/1504] don't skip 314t

---
 pyproject.toml | 1 -
 1 file changed, 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index b0f4f7d3f..c7c98475a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -110,7 +110,6 @@ build-verbosity = 1
 build-frontend = "build"
 skip = [
   "*-musllinux*",
-  "cp314t-*",
 ]
 test-extras = "tests"
 test-sources = [

From e83c443a60fd3fcf4ad1663dcd4054bcd61d1463 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 1 Jan 2026 19:17:18 -0700
Subject: [PATCH 1468/1504] disable GIL for running tests

---
 .github/workflows/cibuildwheel.yml | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index ff1f925ee..cf99484eb 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -88,6 +88,7 @@ jobs:
       uses: pypa/cibuildwheel@v3.3.0
       env:
         CIBW_ARCHS: ${{ matrix.arch }}
+        PYTHON_GIL: 0
 
     - uses: actions/upload-artifact@v6
       with:
@@ -131,6 +132,7 @@ jobs:
         uses: pypa/cibuildwheel@v3.3.0
         env:
           CIBW_ARCHS: ${{ matrix.arch }}
+          PYTHON_GIL: 0
 
       - uses: actions/upload-artifact@v6
         with:
@@ -171,6 +173,7 @@ jobs:
         env:
           CIBW_ARCHS: ARM64
           CIBW_SKIP: "cp310-*"
+          PYTHON_GIL: 0
 
       - uses: actions/upload-artifact@v6
         with:

From 92bcf3ebf1c703732a64061d5d9d59e622cf03f6 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 1 Jan 2026 20:34:36 -0700
Subject: [PATCH 1469/1504] another attempt to disable GIL for running tests

---
 .github/workflows/cibuildwheel.yml | 3 ---
 pyproject.toml                     | 4 ++--
 2 files changed, 2 insertions(+), 5 deletions(-)

diff --git a/.github/workflows/cibuildwheel.yml b/.github/workflows/cibuildwheel.yml
index cf99484eb..ff1f925ee 100644
--- a/.github/workflows/cibuildwheel.yml
+++ b/.github/workflows/cibuildwheel.yml
@@ -88,7 +88,6 @@ jobs:
       uses: pypa/cibuildwheel@v3.3.0
       env:
         CIBW_ARCHS: ${{ matrix.arch }}
-        PYTHON_GIL: 0
 
     - uses: actions/upload-artifact@v6
       with:
@@ -132,7 +131,6 @@ jobs:
         uses: pypa/cibuildwheel@v3.3.0
         env:
           CIBW_ARCHS: ${{ matrix.arch }}
-          PYTHON_GIL: 0
 
       - uses: actions/upload-artifact@v6
         with:
@@ -173,7 +171,6 @@ jobs:
         env:
           CIBW_ARCHS: ARM64
           CIBW_SKIP: "cp310-*"
-          PYTHON_GIL: 0
 
       - uses: actions/upload-artifact@v6
         with:
diff --git a/pyproject.toml b/pyproject.toml
index c7c98475a..c8499712a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -117,8 +117,8 @@ test-sources = [
   "pyproject.toml"
 ]
 test-command = [
-    '''python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')"''',
-    "pytest -s -rxs -v test",
+    '''PYTHON_GIL=0 python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')"''',
+    "pytest -Xgil=0 -s -rxs -v test",
 ]
 manylinux-x86_64-image = "ghcr.io/ocefpaf/manylinux_2_28_x86_64-netcdf"
 manylinux-aarch64-image = "ghcr.io/ocefpaf/manylinux_2_28_aarch64-netcdf"

From 442260f0bbc934061d2ff6479051884f2486e4c8 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 1 Jan 2026 20:46:11 -0700
Subject: [PATCH 1470/1504] turn off GIL for pytest

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index c8499712a..7878bdadc 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -118,7 +118,7 @@ test-sources = [
 ]
 test-command = [
     '''PYTHON_GIL=0 python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')"''',
-    "pytest -Xgil=0 -s -rxs -v test",
+    "python -X gil=0 -m pytest -s -rxs -v test",
 ]
 manylinux-x86_64-image = "ghcr.io/ocefpaf/manylinux_2_28_x86_64-netcdf"
 manylinux-aarch64-image = "ghcr.io/ocefpaf/manylinux_2_28_aarch64-netcdf"

From 4eec50ac8f748877664b7131e9e2bbbf15d970df Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 1 Jan 2026 20:51:05 -0700
Subject: [PATCH 1471/1504] update

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 7878bdadc..06f07aab8 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -117,7 +117,7 @@ test-sources = [
   "pyproject.toml"
 ]
 test-command = [
-    '''PYTHON_GIL=0 python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')"''',
+    '''python -X gil=0 -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')"''',
     "python -X gil=0 -m pytest -s -rxs -v test",
 ]
 manylinux-x86_64-image = "ghcr.io/ocefpaf/manylinux_2_28_x86_64-netcdf"

From 666399441582a9af02f2050ab2f1e11683b8c76c Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 1 Jan 2026 21:14:50 -0700
Subject: [PATCH 1472/1504] revert

---
 pyproject.toml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 06f07aab8..c7c98475a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -117,8 +117,8 @@ test-sources = [
   "pyproject.toml"
 ]
 test-command = [
-    '''python -X gil=0 -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')"''',
-    "python -X gil=0 -m pytest -s -rxs -v test",
+    '''python -c "import netCDF4; print(f'netCDF4 v{netCDF4.__version__}')"''',
+    "pytest -s -rxs -v test",
 ]
 manylinux-x86_64-image = "ghcr.io/ocefpaf/manylinux_2_28_x86_64-netcdf"
 manylinux-aarch64-image = "ghcr.io/ocefpaf/manylinux_2_28_aarch64-netcdf"

From 316bcb853be476a893f0a37410fc1806d8769788 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Thu, 1 Jan 2026 21:20:46 -0700
Subject: [PATCH 1473/1504] ignore RuntimeWarnings for pytest

---
 pyproject.toml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pyproject.toml b/pyproject.toml
index c7c98475a..965044732 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -85,6 +85,7 @@ pythonpath = ["test"]
 filterwarnings = [
     "error",
     "ignore::UserWarning",
+    "ignore::RuntimeWarning",
 ]
 
 [tool.mypy]

From e8e71669ddc6f246df275b91c8808734994a0fac Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Fri, 2 Jan 2026 12:48:32 -0700
Subject: [PATCH 1474/1504] update for 1.7.4 release

---
 Changelog | 6 +++++-
 README.md | 6 ++++++
 2 files changed, 11 insertions(+), 1 deletion(-)

diff --git a/Changelog b/Changelog
index c0267ddfe..88ba8c385 100644
--- a/Changelog
+++ b/Changelog
@@ -1,9 +1,13 @@
- version 1.7.4 (not yet released)
+ version 1.7.4 (tag v1.7.4rel)
  ================================
  * Make sure automatic conversion of character arrays <--> string arrays works for Unicode strings (issue #1440).
    (previously only worked correctly for encoding="ascii").
  * Add netcdf plugins (blosc, zstd, bzip2) in wheels.  Blosc plugin doesn't work in Windows wheels.
    Macos wheels now use conda provided libs. (PR #1450)
+ * Add windows/arm (PR #1453) and free-threaded python wheels (issue #1454). Windows wheels now use netcdf-c 4.9.3.
+   WARNING:  netcdf-c is not thread-safe and netcdf4-python does have internal locking so expect segfaults if you
+   use netcdf4-python on multiple threads with free-threaded python.  Users must exercise care to only call netcdf from
+   a single thread.
 
  version 1.7.3 (tag v1.7.3rel)
  =============================
diff --git a/README.md b/README.md
index 57a352c2d..8b9b52bef 100644
--- a/README.md
+++ b/README.md
@@ -10,6 +10,12 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
+1/5/2026:  Version [1.7.4](https://pypi.python.org/pypi/netCDF4/1.7.4) released.  Compression plugins now included in wheels, windows/arm and
+free-threaded python wheels provided.   Automatic conversion of character arrays <--> string arrays works for Unicode (not just ascii) strings.
+WARNING:  netcdf-c is not thread-safe and netcdf4-python does have internal locking so expect segfaults if you
+use netcdf4-python on multiple threads with free-threaded python.  Users must exercise care to only call netcdf from
+a single thread.
+
 10/13/2025: Version [1.7.3](https://pypi.python.org/pypi/netCDF4/1.7.3) released. Minor updates/bugfixes and python 3.14 wheels, see Changelog for details.
 
 10/22/2024: Version [1.7.2](https://pypi.python.org/pypi/netCDF4/1.7.2) released. Minor updates/bugfixes and python 3.13 wheels, see Changelog for details.

From 2ba0cbe1e4459bb32a9777c48c3a8d765370dfd4 Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Fri, 2 Jan 2026 12:53:46 -0700
Subject: [PATCH 1475/1504] insert warning about threads

---
 src/netCDF4/_netCDF4.pyx | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
index ecebcd4bf..f2312b59e 100644
--- a/src/netCDF4/_netCDF4.pyx
+++ b/src/netCDF4/_netCDF4.pyx
@@ -1050,6 +1050,10 @@ are collective.  There are a couple of important limitations of parallel IO:
    to write to it.
  - You cannot use variable-length (VLEN) data types.
 
+***Import warning regarding threads:***  The underlying netcdf-c library is not thread-safe, so netcdf4-python cannot perform parallel
+IO in a multi-threaded environment.  Users should expect segfaults if a netcdf file is opened on multiple threads - care should
+be taken to restrict netcdf4-python usage to a single thread, even when using free-threaded python.
+
 ## Dealing with strings
 
 The most flexible way to store arrays of strings is with the

From 2752937b5df65f4564b7253a5ca985238c633fab Mon Sep 17 00:00:00 2001
From: jswhit2 
Date: Fri, 2 Jan 2026 12:57:28 -0700
Subject: [PATCH 1476/1504] update docs with threading warning

---
 docs/index.html | 48 ++++++++++++++++++++++++++++++++++--------------
 1 file changed, 34 insertions(+), 14 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index a6b430483..f4f6cbc4d 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -3,20 +3,31 @@
 
 
 
-
+
 netCDF4 API documentation
-
 
 
 
-
+
 
 
 
 
 
 
@@ -26,7 +37,7 @@
 
      Package netCDF4
      
 
 
      
-
      Version 1.7.2
      
+
      Version 1.7.4
      
 
      Introduction
      
 
      netcdf4-python is a Python interface to the netCDF C library.
      
 
      netCDF version 4 has many features
@@ -1003,6 +1014,11 @@ 
      Parallel IO
      
 to write to it.
 
    • You cannot use variable-length (VLEN) data types.
      •

    +

    Import warning regarding threads: +The underlying netcdf-c library is not thread-safe, so netcdf4-python cannot perform parallel +IO in a multi-threaded environment. +Users should expect segfaults if a netcdf file is opened on multiple threads - care should +be taken to restrict netcdf4-python usage to a single thread, even when using free-threaded python.

    Dealing with strings

    The most flexible way to store arrays of strings is with the Variable-length (vlen) string data type. However, this requires @@ -1018,7 +1034,7 @@

    Dealing with strings

    (dtype S1) variable, the chartostring() utility function is used to convert the array of characters to an array of strings with one less dimension (the last dimension is interpreted as the length of each string) when reading the data. The character -set (usually ascii) is specified by the _Encoding attribute. If _Encoding +set is specified by the _Encoding attribute. If _Encoding is 'none' or 'bytes', then the character array is converted to a numpy fixed-width byte string array (dtype S#), otherwise a numpy unicode (dtype U#) array is created. @@ -1196,7 +1212,7 @@

    Support for complex numbers

    Support for complex numbers is handled via the nc-complex library. See there for further details.

    -

    contact: Jeffrey Whitaker jeffrey.s.whitaker@noaa.gov

    +

    contact: Jeffrey Whitaker whitaker.jeffrey@gmail.com

    copyright: 2008 by Jeffrey Whitaker.

    license: Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

    The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

    @@ -1229,7 +1245,7 @@

    Functions

    def date2index(dates, nctime, calendar=None, select='exact', has_year_zero=None)
    -

    date2index(dates, nctime, calendar=None, select=u'exact', has_year_zero=None)

    +

    date2index(dates, nctime, calendar=None, select='exact', has_year_zero=None)

    Return indices of a netCDF time variable corresponding to the given dates.

    dates: A datetime object or a sequence of datetime objects. The datetime objects should not include a time-zone offset.

    @@ -1347,10 +1363,10 @@

    Functions

    used to build the module, and when it was built.

    -def num2date(times, units, calendar='standard', only_use_cftime_datetimes=True, only_use_python_datetimes=False, has_year_zero=None) +def num2date(times,
    units,
    calendar='standard',
    only_use_cftime_datetimes=True,
    only_use_python_datetimes=False,
    has_year_zero=None)
    -

    num2date(times, units, calendar=u'standard', only_use_cftime_datetimes=True, only_use_python_datetimes=False, has_year_zero=None)

    +

    num2date(times, units, calendar='standard', only_use_cftime_datetimes=True, only_use_python_datetimes=False, has_year_zero=None)

    Return datetime objects given numeric time values. The units of the numeric time values are described by the units argument and the calendar keyword. The returned datetime objects represent @@ -1460,10 +1476,10 @@

    Functions

    (default) or 'U1' (if dtype='U')

    -def stringtochar(a, encoding='utf-8') +def stringtochar(a, encoding='utf-8', n_strlen=None)
    -

    stringtochar(a,encoding='utf-8')

    +

    stringtochar(a,encoding='utf-8',n_strlen=None)

    convert a string array to a character array with one extra dimension

    a: Input numpy string array with numpy datatype 'SN' or 'UN', where N @@ -1473,6 +1489,10 @@

    Functions

    optional kwarg encoding can be used to specify character encoding (default utf-8). If encoding is 'none' or 'bytes', a numpy.string_ the input array is treated a raw byte strings (numpy.string_).

    +

    optional kwarg n_strlen is the number of characters in each string. +Default +is None, which means n_strlen will be set to a.itemsize (the number of bytes +used to represent each string in the input array).

    returns a numpy character array with datatype 'S1' or 'U1' and shape a.shape + (N,), where N is the length of each string in a.

    @@ -1834,7 +1854,7 @@

    Methods

    datatype.

    -def createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False, complevel=4, shuffle=True, szip_coding='nn', szip_pixels_per_block=8, blosc_shuffle=1, fletcher32=False, contiguous=False, chunksizes=None, endian='native', least_significant_digit=None, significant_digits=None, quantize_mode='BitGroom', fill_value=None, chunk_cache=None) +def createVariable(self,
    varname,
    datatype,
    dimensions=(),
    compression=None,
    zlib=False,
    complevel=4,
    shuffle=True,
    szip_coding='nn',
    szip_pixels_per_block=8,
    blosc_shuffle=1,
    fletcher32=False,
    contiguous=False,
    chunksizes=None,
    endian='native',
    least_significant_digit=None,
    significant_digits=None,
    quantize_mode='BitGroom',
    fill_value=None,
    chunk_cache=None)

    createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False, @@ -3144,7 +3164,7 @@

    Methods

    -def stringtochar(a, encoding='utf-8', n_strlen=None) +def stringtochar(a, encoding=None, n_strlen=None)

    stringtochar(a,encoding='utf-8',n_strlen=None)

    @@ -1487,8 +1487,8 @@

    Functions

    Will be converted to an array of characters (datatype 'S1' or 'U1') of shape a.shape + (N,).

    optional kwarg encoding can be used to specify character encoding (default -utf-8). If encoding is 'none' or 'bytes', a numpy.string_ the input array -is treated a raw byte strings (numpy.string_).

    +utf-8 for dtype='UN' or ascii for dtype='SN'). If encoding is 'none' or 'bytes', +a numpy.string_ the input array is treated a raw byte strings (numpy.string_).

    optional kwarg n_strlen is the number of characters in each string. Default is None, which means n_strlen will be set to a.itemsize (the number of bytes diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index c5769ab90..49710a5b1 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -6842,10 +6842,6 @@ convert a character array to a string array with one less dimension. Will be converted to a array of strings, where each string has a fixed length of `b.shape[-1]` characters. -optional kwarg `encoding` can be used to specify character encoding (default -`utf-8`). If `encoding` is 'none' or 'bytes', a `numpy.string_` byte array is -returned. - optional kwarg `encoding` can be used to specify character encoding (default `utf-8` for dtype=`'UN'` or `ascii` for dtype=`'SN'`). If `encoding` is 'none' or 'bytes', a `numpy.string_` byte array is returned. From aab4fb311996fdaf6b6f576f440b7ddb442f037b Mon Sep 17 00:00:00 2001 From: jswhit2 Date: Fri, 16 Jan 2026 09:19:33 -0700 Subject: [PATCH 1502/1504] bump version number --- Changelog | 4 ++-- src/netCDF4/_netCDF4.pyx | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/Changelog b/Changelog index a401c2c7e..55bc6b0db 100644 --- a/Changelog +++ b/Changelog @@ -1,5 +1,5 @@ - since version 1.7.4 release - =========================== + version 1.7.4.1 (tag v1.7.4.1rel) + ================================= * Change default encoding for stringtochar/chartostring functions from 'utf-8' to 'utf-8'/'ascii' for dtype.kind='U'/'S' (issue #1464). diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx index 49710a5b1..2f5a133c9 100644 --- a/src/netCDF4/_netCDF4.pyx +++ b/src/netCDF4/_netCDF4.pyx @@ -1,4 +1,4 @@ -"""Version 1.7.4 +"""Version 1.7.4.1 ------------- # Introduction @@ -1283,7 +1283,7 @@ import sys import functools from typing import Union -__version__ = "1.7.4" +__version__ = "1.7.4.1" # Initialize numpy import posixpath From 53c5f523f785c13d4f237533189abdef07ff7ba5 Mon Sep 17 00:00:00 2001 From: Nathan Goldbaum Date: Mon, 5 Jan 2026 10:51:31 -0700 Subject: [PATCH 1503/1504] Add CI checks on free-threaded Python 3.14 --- .github/workflows/miniconda.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index fe9bfba05..2cd23ec22 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -12,7 +12,7 @@ jobs: # NO_NET: 1 strategy: matrix: - python-version: [ "3.10", "3.11", "3.12", "3.13", "3.14" ] + python-version: [ "3.10", "3.11", "3.12", "3.13", "3.14", "3.14t" ] os: [windows-latest, ubuntu-latest, macos-latest] platform: [x64, x32] exclude: @@ -34,7 +34,7 @@ jobs: environment-name: TEST init-shell: bash create-args: >- - python=${{ matrix.python-version }} + ${{ endsWith(matrix.python-version, 't') && 'python-freethreading' || 'python' }}=${{ matrix.python-version }} numpy cython pip setuptools pytest hdf5 libnetcdf cftime zlib certifi typing-extensions --channel conda-forge From 2fc28e8fc6e5bb4e8c9d9d6d936d21f661b5bc67 Mon Sep 17 00:00:00 2001 From: Nathan Goldbaum Date: Mon, 5 Jan 2026 12:04:00 -0700 Subject: [PATCH 1504/1504] Add hack to get correct python version name --- .github/workflows/miniconda.yml | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) diff --git a/.github/workflows/miniconda.yml b/.github/workflows/miniconda.yml index 2cd23ec22..220fdf57c 100644 --- a/.github/workflows/miniconda.yml +++ b/.github/workflows/miniconda.yml @@ -12,7 +12,14 @@ jobs: # NO_NET: 1 strategy: matrix: - python-version: [ "3.10", "3.11", "3.12", "3.13", "3.14", "3.14t" ] + python-version: [ + ["python", "3.10"], + ["python", "3.11"], + ["python", "3.12"], + ["python", "3.13"], + ["python", "3.14"], + ["python-freethreading", "3.14" ], + ] os: [windows-latest, ubuntu-latest, macos-latest] platform: [x64, x32] exclude: @@ -34,7 +41,7 @@ jobs: environment-name: TEST init-shell: bash create-args: >- - ${{ endsWith(matrix.python-version, 't') && 'python-freethreading' || 'python' }}=${{ matrix.python-version }} + ${{ matrix.python-version[0] }}=${{ matrix.python-version[1] }} numpy cython pip setuptools pytest hdf5 libnetcdf cftime zlib certifi typing-extensions --channel conda-forge