8000 ENH: Implement ndarray.__format__ for 0d arrays by eric-wieser · Pull Request #9883 · numpy/numpy · GitHub
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ENH: Implement ndarray.__format__ for 0d arrays #9883

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Merged
merged 2 commits into from
Oct 18, 2017
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ENH: Implement ndarray.__format__ for 0d arrays #9883

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ENH: Implement ndarray.__format__ for 0d arrays
eric-wieser Oct 18, 2017
86a7ac6
STY: Add blank line after variable declarations.
charris Oct 18, 2017
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5 changes: 5 additions & 0 deletions numpy/core/src/multiarray/methods.c
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Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,7 @@
#include "item_selection.h"
#include "conversion_utils.h"
#include "shape.h"
#include "strfuncs.h"

#include "methods.h"
#include "alloc.h"
Expand Down Expand Up @@ -2533,6 +2534,10 @@ NPY_NO_EXPORT PyMethodDef array_methods[] = {
(PyCFunction) array_complex,
METH_VARARGS, NULL},

{"__format__",
(PyCFunction) array_format,
METH_VARARGS, NULL},

#ifndef NPY_PY3K
/*
* While we could put these in `tp_sequence`, its' easier to define them
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28 changes: 28 additions & 0 deletions numpy/core/src/multiarray/strfuncs.c
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Expand Up @@ -197,3 +197,31 @@ array_str(PyArrayObject *self)
}
return s;
}

NPY_NO_EXPORT PyObject *
array_format(PyArrayObject *self, PyObject *args)
{
PyObject *format;
if (!PyArg_ParseTuple(args, "O:__format__", &format))
return NULL;

/* 0d arrays - forward to the scalar type */
if (PyArray_NDIM(self) == 0) {
PyObject *item = PyArray_ToScalar(PyArray_DATA(self), self);
PyObject *res;

if (item == NULL) {
return NULL;
}
res = PyObject_Format(item, format);
Py_DECREF(item);
return res;
}
/* Everything else - use the builtin */
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What does the builtin do here?

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@eric-wieser eric-wieser Oct 18, 2017 •
edited
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It keeps the arbitrary and python-dependent behavior that we had before this patch.

Most importantly it handles '{}'.format in the typical way. On python 3, it throws an exception if a format string is given, while on python 2 it evaluates format(str(arr), 'theformatspec').

else {
return PyObject_CallMethod(
(PyObject *)&PyBaseObject_Type, "__format__", "OO",
(PyObject *)self, format
);
}
}
3 changes: 3 additions & 0 deletions numpy/core/src/multiarray/strfuncs.h
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Expand Up @@ -10,4 +10,7 @@ array_repr(PyArrayObject *self);
NPY_NO_EXPORT PyObject *
array_str(PyArrayObject *self);

NPY_NO_EXPORT PyObject *
array_format(PyArrayObject *self, PyObject *args);

#endif
31 changes: 31 additions & 0 deletions numpy/core/tests/test_multiarray.py
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Expand Up @@ -7013,6 +7013,37 @@ def test_null_inside_ustring_array_is_truthy(self):
assert_(a)


class TestFormat(object):

def test_0d(self):
a = np.array(np.pi)
assert_equal('{:0.3g}'.format(a), '3.14')
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Is assert_equal the best way to compare strings? Maybe just assert_(str1 == str2) would be a bit cleaner.

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Yes, because then it shows the two values if they differ.

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OK.

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In pytest you can just assert str1 == str2 and you will get values if there is a failure.


def test_failure():
    a = 'apple'
    b = 'banana'
    assert a == b

Output is

================================== FAILURES ===================================
________________________________ test_failure _________________________________

    def test_failure():
        a = 'apple'
        b = 'banana'
>       assert a == b
E       AssertionError: assert 'apple' == 'banana'
E         - apple
E         + banana

test_util.py:20: AssertionError
========================== 1 failed in 0.24 seconds ===========================

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For consistency, we should probably use the same form we use in most of the test suite, which gives:

>>> np.testing.assert_equal('a', 'b')
AssertionError: 
Items are not equal:
 ACTUAL: 'a'
 DESIRED: 'b'

AFAIK, the switch to pytest was recent, and we were previously using nose

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We are still using nose, the pytest conversion is still in progress and I don't think I will get back to it until 1.15.

assert_equal('{:0.3g}'.format(a[()]), '3.14')

def test_1d_no_format(self):
a = np.array([np.pi])
assert_equal('{}'.format(a), str(a))

def test_1d_format(self):
# until gh-5543, ensure that the behaviour matches what it used to be
a = np.array([np.pi])

def ret_and_exc(f, *args, **kwargs):
try:
return f(*args, **kwargs), None
except Exception as e:
# exceptions don't compare equal, so return type and args
# which do
return None, (type(e), e.args)

# Could switch on python version here, but all we care about is
# that the behaviour hasn't changed
assert_equal(
ret_and_exc(object.__format__, a, '30'),
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I suppose we should silence warnings in ret_and_exc, or return a third tuple item which is the warning

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Maybe just figure out what the result should be and use that? Eventually object.__format__ is going to fail with non-empty argument.

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Right, and I think that ndarray.__format__ should start failing at the same time. Maybe we should just make ndarray.__format__ fail with an empty argument right now...

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Looks like it went away in Python 3.4.

* :meth:`object.__format__` no longer accepts non-empty format strings, it now
  raises a :exc:`TypeError` instead.  Using a non-empty string has been
  deprecated since Python 3.2.  This change has been made to prevent a
  situation where previously working (but incorrect) code would start failing
  if an object gained a __format__ method, which means that your code may now
  raise a :exc:`TypeError` if you are using an ``'s'`` format code with objects
  that do not have a __format__ method that handles it.  See :issue:`7994` for
  background.

Should ours work if an empty string is passed?

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I fixed this by making the test Python version dependent.

ret_and_exc('{:30}'.format, a)
)


class TestCTypes(object):

def test_ctypes_is_available(self):
Expand Down
0