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1. Collections: List, Dictionary, Set, Tuple, Range, Enumerate, Iterator, Generator.
2. Types: Type, String, Regular_Exp, Format, Numbers, Combinatorics, Datetime.
3. Syntax: Args, Inline, Closure, Decorator, Class, Duck_Type, Enum, Exception.
4. System: Exit, Print, Input, Command_Line_Arguments, Open, Path, OS_Commands.
5. Data: JSON, Pickle, CSV, SQLite, Bytes, Struct, Array, Memory_View, Deque.
6. Advanced: Threading, Operator, Introspection, Metaprograming, Eval, Coroutines.
7. Libraries: Progress_Bar, Plot, Table, Curses, Logging, Scraping, Web, Profile,
NumPy, Image, Audio, Games, Data, GUI.
if __name__ == '__main__': # Runs main() if file wasn't imported.
main()<list> = <list>[from_inclusive : to_exclusive : ±step_size]<list>.append(<el>) # Or: <list> += [<el>]
<list>.extend(<collection>) # Or: <list> += <collection><list>.sort()
<list>.reverse()
<list> = sorted(<collection>)
<iter> = reversed(<list>)sum_of_elements = sum(<collection>)
elementwise_sum = [sum(pair) for pair in zip(list_a, list_b)]
sorted_by_second = sorted(<collection>, key=lambda el: el[1])
sorted_by_both = sorted(<collection>, key=lambda el: (el[1], el[0]))
flatter_list = list(itertools.chain.from_iterable(<list>))
product_of_elems = functools.reduce(lambda out, el: out * el, <collection>)
list_of_chars = list(<str>)- Module operator provides functions itemgetter() and mul() that offer the same functionality as lambda expressions above.
<int> = <list>.count(<el>) # Returns number of occurrences. Also works on strings.
index = <list>.index(<el>) # Returns index of first occurrence or raises ValueError.
<list>.insert(index, <el>) # Inserts item at index and moves the rest to the right.
<el> = <list>.pop([index]) # Removes and returns item at index or from the end.
<list>.remove(<el>) # Removes first occurrence of item or raises ValueError.
<list>.clear() # Removes all items. Also works on dictionary and set.<view> = <dict>.keys() # Coll. of keys that reflects changes.
<view> = <dict>.values() # Coll. of values that reflects changes.
<view> = <dict>.items() # Coll. of key-value tuples that reflects chgs.value = <dict>.get(key, default=None) # Returns default if key is missing.
value = <dict>.setdefault(key, default=None) # Returns and writes default if key is missing.
<dict> = collections.defaultdict(<type>) # Creates a dict with default value of type.
<dict> = collections.defaultdict(lambda: 1) # Creates a dict with default value 1.<dict> = dict(<collection>) # Creates a dict from coll. of key-value pairs.
<dict> = dict(zip(keys, values)) # Creates a dict from two collections.
<dict> = dict.fromkeys(keys [, value]) # Creates a dict from collection of keys.<dict>.update(<dict>) # Adds items. Replaces ones with matching keys.
value = <dict>.pop(key) # Removes item or raises KeyError.
{k for k, v in <dict>.items() if v == value} # Returns set of keys that point to the value.
{k: v for k, v in <dict>.items() if k in keys} # Returns a dictionary, filtered by keys.>>> from collections import Counter
>>> colors = ['blue', 'blue', 'blue', 'red', 'red']
>>> counter = Counter(colors)
>>> counter['yellow'] += 1
Counter({'blue': 3, 'red': 2, 'yellow': 1})
>>> counter.most_common()[0]
('blue', 3)<set> = set()<set>.add(<el>) # Or: <set> |= {<el>}
<set>.update(<col
C020
lection> [, ...]) # Or: <set> |= <set><set> = <set>.union(<coll.>) # Or: <set> | <set>
<set> = <set>.intersection(<coll.>) # Or: <set> & <set>
<set> = <set>.difference(<coll.>) # Or: <set> - <set>
<set> = <set>.symmetric_difference(<coll.>) # Or: <set> ^ <set>
<bool> = <set>.issubset(<coll.>) # Or: <set> <= <set>
<bool> = <set>.issuperset(<coll.>) # Or: <set> >= <set><el> = <set>.pop() # Raises KeyError if empty.
<set>.remove(<el>) # Raises KeyError if missing.
<set>.discard(<el>) # Doesn't raise an error.- Is immutable and hashable.
- That means it can be used as a key in a dictionary or as an element in a set.
<frozenset> = frozenset(<collection>)Tuple is an immutable and hashable list.
<tuple> = ()
<tuple> = (<el>, )
<tuple> = (<el_1>, <el_2> [, ...])Tuple's subclass with named elements.
>>> from collections import namedtuple
>>> Point = namedtuple('Point', 'x y')
>>> p = Point(1, y=2)
Point(x=1, y=2)
>>> p[0]
1
>>> p.x
1
>>> getattr(p, 'y')
2
>>> p._fields # Or: Point._fields
('x', 'y')<range> = range(to_exclusive)
<range> = range(from_inclusive, to_exclusive)
<range> = range(from_inclusive, to_exclusive, ±step_size)from_inclusive = <range>.start
to_exclusive = <range>.stopfor i, el in enumerate(<collection> [, i_start]):
...<iter> = iter(<collection>) # `iter(<iter>)` returns unmodified iterator.
<iter> = iter(<function>, to_exclusive) # A sequence of return values until 'to_exclusive'.
<el> = next(<iter> [, default]) # Raises StopIteration or returns 'default' on end.
<list> = list(<iter>) # Returns a list of iterator's remaining elements.from itertools import count, repeat, cycle, chain, islice<iter> = count(start=0, step=1) # Returns updated value endlessly. Accepts floats.
<iter> = repeat(<el> [, times]) # Returns element endlessly or 'times' times.
<iter> = cycle(<collection>) # Repeats the sequence endlessly.<iter> = chain(<coll_1>, <coll_2> [, ...]) # Empties collections in order.
<iter> = chain.from_iterable(<collection>) # Empties collections inside a collection in order.<iter> = islice(<coll>, to_exclusive) # Only returns first 'to_exclusive' elements.
<iter> = islice(<coll>, from_inclusive, …) # `to_exclusive, step_size`.- Any function that contains a yield statement returns a generator.
- Generators and iterators are interchangeable.
def count(start, step):
while True:
yield start
start += step>>> counter = count(10, 2)
>>> next(counter), next(counter), next(counter)
(10, 12, 14)- Everything is an object.
- Every object has a type.
- Type and class are synonymous.
<type> = type(<el>) # Or: <el>.__class__
<bool> = isinstance(<el>, <type>) # Or: issubclass(type(<el>), <type>)>>> type('a'), 'a'.__class__, str
(<class 'str'>, <class 'str'>, <class 'str'>)from types import FunctionType, MethodType, LambdaType, GeneratorTypeEach abstract base class specifies a set of virtual subclasses. These classes are then recognized by isinstance() and issubclass() as subclasses of the ABC, although they are really not. ABC can also manually decide whether or not a specific class is its virtual subclass, usually based on which methods the class has implemented (Collection, Iterable).
>>> from collections.abc import Sequence, Collection, Iterable
>>> isinstance([1, 2, 3], Iterable)
True+------------------+------------+------------+------------+
| | Sequence | Collection | Iterable |
+------------------+------------+------------+------------+
| list, range, str | yes | yes | yes |
| dict, set | | yes | yes |
| iter | | | yes |
+------------------+------------+------------+------------+
>>> from numbers import Integral, Rational, Real, Complex, Number
>>> isinstance(123, Number)
True+--------------------+----------+----------+----------+----------+----------+
| | Integral | Rational | Real | Complex | Number |
+--------------------+----------+----------+----------+----------+----------+
| int | yes | yes | yes | yes | yes |
| fractions.Fraction | | yes | yes | yes | yes |
| float | | | yes | yes | yes |
| complex | | | | yes | yes |
| decimal.Decimal | | | | | yes |
+--------------------+----------+----------+----------+----------+----------+
<str> = <str>.strip() # Strips all whitespace characters from both ends.
<str> = <str>.strip('<chars>') # Strips all passed characters from both ends.<list> = <str>.split() # Splits on one or more whitespace characters.
<list> = <str>.split(sep=None, maxsplit=-1) # Splits on 'sep' str at most 'maxsplit' times.
<list> = <str>.splitlines(keepends=False) # Splits on \n,\r,\r\n. Keeps them if 'keepends'.
<str> = <str>.join(<coll_of_strings>) # Joins elements using string as separator.<bool> = <sub_str> in <str> # Checks if string contains a substring.
<bool> = <str>.startswith(<sub_str>) # Pass tuple of strings for multiple options.
<bool> = <str>.endswith(<sub_str>) # Pass tuple of strings for multiple options.
<int> = <str>.find(<sub_str>) # Returns start index of first match or -1.
<int> = <str>.index(<sub_str>) # Same but raises ValueError if missing.<str> = <str>.replace(old, new [, count]) # Replaces 'old' with 'new' at most 'count' times.
<str> = <str>.translate(<table>) # Use `str.maketrans(<dict>)` to generate table.<str> = chr(<int>) # Converts int to Unicode char.
<int> = ord(<str>) # Converts Unicode char to int.- Also:
'lstrip()','rstrip()'. - Also:
'lower()','upper()','capitalize()'and'title()'.
+---------------+----------+----------+----------+----------+----------+
| | [ !#$%…] | [a-zA-Z] | [¼½¾] | [²³¹] | [0-9] |
+---------------+----------+----------+----------+----------+----------+
| isprintable() | yes | yes | yes | yes | yes |
| isalnum() | | yes | yes | yes | yes |
| isnumeric() | | | yes | yes | yes |
| isdigit() | | | | yes | yes |
| isdecimal() | | | | | yes |
+---------------+----------+----------+----------+----------+----------+
- Also:
'isspace()'checks for'[ \t\n\r\f\v…]'.
import re
<str> = re.sub(<regex>, new, text, count=0) # Substitutes all occurrences with 'new'.
<list> = re.findall(<regex>, text) # Returns all occurrences as strings.
<list> = re.split(<regex>, text, maxsplit=0) # Use brackets in regex to include the matches.
<Match> = re.search(<regex>, text) # Searches for first occurrence of the pattern.
<Match> = re.match(<regex>, text) # Searches only at the beginning of the text.
<iter> = re.finditer(<regex>, text) # Returns all occurrences as match objects.- Search() and match() return None if they can't find a match.
- Argument
'flags=re.IGNORECASE'can be used with all functions. - Argument
'flags=re.MULTILINE'makes'^'and'$'match the start/end of each line. - Argument
'flags=re.DOTALL'makes dot also accept the'\n'. - Use
r'\1'or'\\1'for backreference. - Add
'?'after an operator to make it non-greedy.
<str> = <Match>.group() # Returns the whole match. Also group(0).
<str> = <Match>.group(1) # Returns part in the first bracket.
<tuple> = <Match>.groups() # Returns all bracketed parts.
<int> = <Match>.start() # Returns start index of the match.
<int> = <Match>.end() # Returns exclusive end index of the match.- By default digits, alphanumerics and whitespaces from all alphabets are matched, unless
'flags=re.ASCII'argument is used. - Use a capital letter for negation.
'\d' == '[0-9]' # Matches any digit.
'\w' == '[a-zA-Z0-9_]' # Matches any alphanumeric.
'\s' == '[ \t\n\r\f\v]' # Matches any whitespace.<str> = f'{<el_1>}, {<el_2>}'
<str> = '{}, {}'.format(<el_1>, <el_2>)>>> from collections import namedtuple
>>> Person = namedtuple('Person', 'name height')
>>> person = Person('Jean-Luc', 187)
>>> f'{person.height}'
'187'
>>> '{p.height}'.format(p=person)
'187'{<el>:<10} # '<el> '
{<el>:^10} # ' <el> '
{<el>:>10} # ' <el>'
{<el>:.<10} # '<el>......'
{<el>:0} # '<el>''!r' calls object's repr() method, instead of str(), to get a string.
{'abcde'!r:10} # "'abcde' "
{'abcde':10.3} # 'abc '
{'abcde':.3} # 'abc'{ 123456:10,} # ' 123,456'
{ 123456:10_} # ' 123_456'
{ 123456:+10} # ' +123456'
{-123456:=10} # '- 123456'
{ 123456: } # ' 123456'
{-123456: } # '-123456'{1.23456:10.3} # ' 1.23'
{1.23456:10.3f} # ' 1.235'
{1.23456:10.3e} # ' 1.235e+00'
{1.23456:10.3%} # ' 123.456%'+---------------+-----------------+-----------------+-----------------+-----------------+
| | {<float>} | {<float>:f} | {<float>:e} | {<float>:%} |
+---------------+-----------------+-----------------+-----------------+-----------------+
| 0.000056789 | '5.6789e-05' | '0.000057' | '5.678900e-05' | '0.005679%' |
| 0.00056789 | '0.00056789' | '0.000568' | '5.678900e-04' | '0.056789%' |
| 0.0056789 | '0.0056789' | '0.005679' | '5.678900e-03' | '0.567890%' |
| 0.056789 | '0.056789' | '0.056789' | '5.678900e-02' | '5.678900%' |
| 0.56789 | '0.56789' | '0.567890' | '5.678900e-01' | '56.789000%' |
| 5.6789 | '5.6789' | '5.678900' | '5.678900e+00' | '567.890000%' |
| 56.789 | '56.789' | '56.789000' | '5.678900e+01' | '5678.900000%' |
| 567.89 | '567.89' | '567.890000' | '5.678900e+02' | '56789.000000%' |
+---------------+-----------------+-----------------+-----------------+-----------------+
+---------------+-----------------+-----------------+-----------------+-----------------+
| | {<float>:.2} | {<float>:.2f} | {<float>:.2e} | {<float>:.2%} |
+---------------+-----------------+-----------------+-----------------+-----------------+
| 0.000056789 | '5.7e-05' | '0.00' | '5.68e-05' | '0.01%' |
| 0.00056789 | '0.00057' | '0.00' | '5.68e-04' | '0.06%' |
| 0.0056789 | '0.0057' | '0.01' | '5.68e-03' | '0.57%' |
| 0.056789 | '0.057' | '0.06' | '5.68e-02' | '5.68%' |
| 0.56789 | '0.57' | '0.57' | '5.68e-01' | '56.79%' |
| 5.6789 | '5.7' | '5.68' | '5.68e+00' | '567.89%' |
| 56.789 | '5.7e+01' | '56.79' | '5.68e+01' | '5678.90%' |
| 567.89 | '5.7e+02' | '567.89' | '5.68e+02' | '56789.00%' |
+---------------+-----------------+-----------------+-----------------+-----------------+
{90:c} # 'Z'
{90:b} # '1011010'
{90:X} # '5A'<int> = int(<float/str/bool>) # Or: math.floor(<float>)
<float> = float(<int/str/bool>) # Or: <real>e±<int>
<complex> = complex(real=0, imag=0) # Or: <real> ± <real>j
<Fraction> = fractions.Fraction(0, 1) # Or: Fraction(numerator=0, denominator=1)
<Decimal> = decimal.Decimal(<str/int>) # Or: Decimal((sign, digits, exponent))'int(<str>)'and'float(<str>)'raise ValueError on malformed strings.- Decimal numbers can be represented exactly, unlike floats where
'1.1 + 2.2 != 3.3'. - Precision of decimal operations is set with:
'decimal.getcontext().prec = <int>'.
<num> = pow(<num>, <num>) # Or: <num> ** <num>
<num> = abs(<num>) # <float> = abs(<complex>)
<num> = round(<num> [, ±ndigits]) # `round(126, -1) == 130`from math import e, pi, inf, nan, isinf, isnan
from math import cos, acos, sin, asin, tan, atan, degrees, radians
from math import log, log10, log2from statistics import mean, median, variance, stdev, pvariance, pstdevfrom random import random, randint, choice, shuffle
<float> = random()
<int> = randint(from_inclusive, to_inclusive)
<el> = choice(<list>)
shuffle(<list>)<int> = ±0b<bin> # Or: ±0x<hex>
<int> = int('±<bin>', 2) # Or: int('±<hex>', 16)
<int> = int('±0b<bin>', 0) # Or: int('±0x<hex>', 0)
<str> = bin(<int>) # Returns '[-]0b<bin>'.<int> = <int> & <int> # And
<int> = <int> | <int> # Or
<int> = <int> ^ <int> # Xor (0 if both bits equal)
<int> = <int> << n_bits # Shift left (>> for right)
<int> = ~<int> # Not (also: -<int> - 1)- Every function returns an iterator.
- If you want to print the iterator, you need to pass it to the list() function first!
from itertools import product, combinations, combinations_with_replacement, permutations>>> product([0, 1], repeat=3)
[(0, 0, 0), (0, 0, 1), (0, 1, 0), (0, 1, 1), ..., (1, 1, 1)]>>> product('abc', 'abc') # a b c
[('a', 'a'), ('a', 'b'), ('a', 'c'), # a x x x
('b', 'a'), ('b', 'b'), ('b', 'c'), # b x x x
('c', 'a'), ('c', 'b'), ('c', 'c')] # c x x x>>> combinations('abc', 2) # a b c
[('a', 'b'), ('a', 'c'), # a . x x
('b', 'c')] # b . . x>>> combinations_with_replacement('abc', 2) # a b c
[('a', 'a'), ('a', 'b'), ('a', 'c'), # a x x x
('b', 'b'), ('b', 'c'), # b . x x
('c', 'c')] # c . . x>>> permutations('abc', 2) # a b c
[('a', 'b'), ('a', 'c'), # a . x x
('b', 'a'), ('b', 'c'), # b x . x
('c', 'a'), ('c', 'b')] # c x x .- Module 'datetime' provides 'date'
<D>, 'time'<T>, 'datetime'<DT>and 'timedelta'<TD>classes. All are immutable and hashable. - Time and datetime objects can be 'aware'
<a>, meaning they have defined timezone, or 'naive'<n>, meaning they don't. - If object is naive, it is presumed to be in the system's timezone.
from datetime import date, time, datetime, timedelta
from dateutil.tz import UTC, tzlocal, gettz, resolve_imaginary<D> = date(year, month, day)
<T> = time(hour=0, minute=0, second=0, microsecond=0, tzinfo=None, fold=0)
<DT> = datetime(year, month, day, hour=0, minute=0, second=0, ...)
<TD> = timedelta(days=0, seconds=0, microseconds=0, milliseconds=0,
minutes=0, hours=0, weeks=0)- Use
'<D/DT>.weekday()'to get the day of the week (Mon == 0). 'fold=1'means the second pass in case of time jumping back for one hour.'<DTa> = resolve_imaginary(<DTa>)'fixes DTs that fall into the missing hour.
<D/DTn> = D/DT.today() # Current local date or naive datetime.
<DTn> = DT.utcnow() # Naive datetime from current UTC time.
<DTa> = DT.now(<tzinfo>) # Aware datetime from current tz time.- To extract time use
'<DTn>.time()','<DTa>.time()'or'<DTa>.timetz()'.
<tzinfo> = UTC # UTC timezone. London without DST.
<tzinfo> = tzlocal() # Local timezone. Also gettz().
<tzinfo> = gettz('<Continent>/<City>') # 'Continent/City_Name' timezone or None.
<DTa> = <DT>.astimezone(<tzinfo>) # Datetime, converted to passed timezone.
<Ta/DTa> = <T/DT>.replace(tzinfo=<tzinfo>) # Unconverted object with new timezone.<D/T/DT> = D/T/DT.fromisoformat('<iso>') # Object from ISO string. Raises ValueError.
<DT> = DT.strptime(<str>, '<format>') # Datetime from str, according to format.
<D/DTn> = D/DT.fromordinal(<int>) # D/DTn from days since Christ, at midnight.
<DTn> = DT.fromtimestamp(<real>) # Local time DTn from seconds since Epoch.
<DTa> = DT.fromtimestamp(<real>, <tz.>) # Aware datetime from seconds since Epoch.- ISO strings come in following forms:
'YYYY-MM-DD','HH:MM:SS.ffffff[±<offset>]', or both separated by an arbitrary character. Offset is formatted as:'HH:MM'. - Epoch on Unix systems is:
'1970-01-01 00:00 UTC','1970-01-01 01:00 CET', ...
<str> = <D/T/DT>.isoformat(sep='T') # Also timespec='auto/hours/minutes/seconds'.
<str> = <D/T/DT>.strftime('<format>') # Custom string representation.
<int> = <D/DT>.toordinal() # Days since Christ, ignoring time and tz.
<float> = <DTn>.timestamp() # Seconds since Epoch, from DTn in local tz.
<float> = <DTa>.timestamp() # Seconds since Epoch, from DTa.>>> from datetime import datetime
>>> dt = datetime.strptime('2015-05-14 23:39:00.00 +0200', '%Y-%m-%d %H:%M:%S.%f %z')
>>> dt.strftime("%A, %dth of %B '%y, %I:%M%p %Z")
"Thursday, 14th of May '15, 11:39PM UTC+02:00"- When parsing,
'%z'also accepts'±HH:MM'. - For abbreviated weekday and month use
'%a'and'%b'.
<D/DT> = <D/DT> ± <TD> # Returned datetime can fall into missing hour.
<TD> = <D/DTn> - <D/DTn> # Returns the difference, ignoring time jumps.
<TD> = <DTa> - <DTa> # Ignores time jumps if they share tzinfo object.
<TD> = <DT_UTC> - <DT_UTC> # Convert DTs to UTC to get the actual delta.<function>(<positional_args>) # f(0, 0)
<function>(<keyword_args>) # f(x=0, y=0)
<function>(<positional_args>, <keyword_args>) # f(0, y=0)def f(<nondefault_args>): # def f(x, y):
def f(<default_args>): # def f(x=0, y=0):
def f(<nondefault_args>, <default_args>): # def f(x, y=0):Splat expands a collection into positional arguments, while splatty-splat expands a dictionary into keyword arguments.
args = (1, 2)
kwargs = {'x': 3, 'y': 4, 'z': 5}
func(*args, **kwargs)func(1, 2, x=3, y=4, z=5)Splat combines zero or more positional arguments into a tuple, while splatty-splat combines zero or more keyword arguments into a dictionary.
def add(*a):
return sum(a)>>> add(1, 2, 3)
6def f(x, y, z): # f(x=1, y=2, z=3) | f(1, y=2, z=3) | f(1, 2, z=3) | f(1, 2, 3)
def f(*, x, y, z): # f(x=1, y=2, z=3)
def f(x, *, y, z): # f(x=1, y=2, z=3) | f(1, y=2, z=3)
def f(x, y, *, z): # f(x=1, y=2, z=3) | f(1, y=2, z=3) | f(1, 2, z=3)def f(*args): # f(1, 2, 3)
def f(x, *args): # f(1, 2, 3)
def f(*args, z): # f(1, 2, z=3)
def f(x, *args, z): # f(1, 2, z=3)def f(**kwargs): # f(x=1, y=2, z=3)
def f(x, **kwargs): # f(x=1, y=2, z=3) | f(1, y=2, z=3)
def f(*, x, **kwargs): # f(x=1, y=2, z=3)def f(*args, **kwargs): # f(x=1, y=2, z=3) | f(1, y=2, z=3) | f(1, 2, z=3) | f(1, 2, 3)
def f(x, *args, **kwargs): # f(x=1, y=2, z=3) | f(1, y=2, z=3) | f(1, 2, z=3) | f(1, 2, 3)
def f(*args, y, **kwargs): # f(x=1, y=2, z=3) | f(1, y=2, z=3)
def f(x, *args, z, **kwargs): # f(x=1, y=2, z=3) | f(1, y=2, z=3) | f(1, 2, z=3)<list> = [*<collection> [, ...]]
<set> = {*<collection> [, ...]}
<tuple> = (*<collection>, [...])
<dict> = {**<dict> [, ...]}head, *body, tail = <collection><function> = lambda: <return_value>
<function> = lambda <argument_1>, <argument_2>: <return_value><list> = [i+1 for i in range(10)] # [1, 2, ..., 10]
<set> = {i for i in range(10) if i > 5} # {6, 7, 8, 9}
<iter> = (i+5 for i in range(10)) # (5, 6, ..., 14)
<dict> = {i: i*2 for i in range(10)} # {0: 0, 1: 2, ..., 9: 18}out = [i+j for i in range(10) for j in range(10)]out = []
for i in range(10):
for j in range(10):
out.append(i+j)from functools import reduce
<iter> = map(lambda x: x + 1, range(10)) # (1, 2, ..., 10)
<iter> = filter(lambda x: x > 5, range(10)) # (6, 7, 8, 9)
<obj> = reduce(lambda out, x: out + x, range(10)) # 45<bool> = any(<collection>) # False if empty.
<bool> = all(el[1] for el in <collection>) # True if empty.<obj> = <expression_if_true> if <condition> else <expression_if_false>>>> [a if a else 'zero' for a in (0, 1, 2, 3)]
['zero', 1, 2, 3]from collections import namedtuple
Point = namedtuple('Point', 'x y')
point = Point(0, 0)from enum import Enum
Direction = Enum('Direction', 'n e s w')
direction = Direction.nfrom dataclasses import make_dataclass
Creature = make_dataclass('Creature', ['location', 'direction'])
creature = Creature(Point(0, 0), Direction.n)We have a closure in Python when:
- A nested function references a value of its enclosing function and then
- the enclosing function returns the nested function.
def get_multiplier(a):
def out(b):
return a * b
return out>>> multiply_by_3 = get_multiplier(3)
>>> multiply_by_3(10)
30- If multiple nested functions within enclosing function reference the same value, that value gets shared.
- To dynamically access function's first free variable use
'<function>.__closure__[0].cell_contents'.
from functools import partial
<function> = partial(<function> [, <arg_1>, <arg_2>, ...])>>> import operator as op
>>> multiply_by_3 = partial(op.mul, 3)
>>> multiply_by_3(10)
30- Partial is also useful in cases when function needs to be passed as an argument, because it enables us to set its arguments beforehand.
- A few examples being:
'defaultdict(<function>)','iter(<function>, to_exclusive)'and dataclass's'field(default_factory=<function>)'.
If variable is being assigned to anywhere in the scope, it is regarded as a local variable, unless it is declared as a 'global' or a 'nonlocal'.
def get_counter():
i = 0
def out():
nonlocal i
i += 1
return i
return out>>> counter = get_counter()
>>> counter(), counter(), counter()
(1, 2, 3)A decorator takes a function, adds some functionality and returns it.
@decorator_name
def function_that_gets_passed_to_decorator():
...Decorator that prints function's name every time it gets called.
from functools import wraps
def debug(func):
@wraps(func)
def out(*args, **kwargs):
print(func.__name__)
return func(*args, **kwargs)
return out
@debug
def add(x, y):
return x + y- Wraps is a helper decorator that copies the metadata of the passed function (func) to the function it is wrapping (out).
- Without it
'add.__name__'would return'out'.
Decorator that caches function's return values. All function's arguments must be hashable.
from functools import lru_cache
@lru_cache(maxsize=None)
def fib(n):
return n if n < 2 else fib(n-2) + fib(n-1)- CPython interpreter limits recursion depth to 1000 by default. To increase it use
'sys.setrecursionlimit(<depth>)'.
A decorator that accepts arguments and returns a normal decorator that accepts a function.
from functools import wraps
def debug(print_result=False):
def decorator(func):
@wraps(func)
def out(*args, **kwargs):
result = func(*args, **kwargs)
print(func.__name__, result if print_result else '')
return result
return out
return decorator
@debug(print_result=True)
def add(x, y):
return x + yclass <name>:
def __init__(self, a):
self.a = a
def __repr__(self):
class_name = self.__class__.__name__
return f'{class_name}({self.a!r})'
def __str__(self):
return str(self.a)
@classmethod
def get_class_name(cls):
return cls.__name__- Return value of repr() should be unambiguous and of str() readable.
- If only repr() is defined, it will also be used for str().
print(<el>)
print(f'{<el>}')
raise Exception(<el>)
loguru.logger.debug(<el>)
csv.writer(<file>).writerow([<el>])print([<el>])
print(f'{<el>!r}')
>>> <el>
loguru.logger.exception()
Z = dataclasses.make_dataclass('Z', ['a']); print(Z(<el>))class <name>:
def __init__(self, a=None):
self.a = aclass Person:
def __init__(self, name, age):
self.name = name
self.age = age
class Employee(Person):
def __init__(self, name, age, staff_num):
super().__init__(name, age)
self.staff_num = staff_numclass A: pass
class B: pass
class C(A, B): passMRO determines the order in which parent classes are traversed when searching for a method:
>>> C.mro()
[<class 'C'>, <class 'A'>, <class 'B'>, <class 'object'>]Pythonic way of implementing getters and setters.
class MyClass:
@property
def a(self):
return self._a
@a.setter
def a(self, value):
self._a = value>>> el = MyClass()
>>> el.a = 123
>>> el.a
123Decorator that automatically generates init(), repr() and eq() special methods.
from dataclasses import dataclass, field
@dataclass(order=False, frozen=False)
class <class_name>:
<attr_name_1>: <type>
<attr_name_2>: <type> = <default_value>
<attr_name_3>: list/dict/set = field(default_factory=list/dict/set)- Objects can be made sortable with
'order=True'and immutable with'frozen=True'. - For object to be hashable, all attributes must be hashable and frozen must be True.
- Function field() is needed because
'<attr_name>: list = []'would make a list that is shared among all instances. - Default_factory can be any callable.
from dataclasses import make_dataclass
<class> = make_dataclass('<class_name>', <coll_of_attribute_names>)
<class> = make_dataclass('<class_name>', <coll_of_tuples>)
<tuple> = ('<attr_name>', <type> [, <default_value>])Mechanism that restricts objects to attributes listed in 'slots' and significantly reduces their memory footprint.
class MyClassWithSlots:
__slots__ = ['a']
def __init__(self):
self.a = 1from copy import copy, deepcopy
<object> = copy(<object>)
<object> = deepcopy(<object>)A duck type is an implicit type that prescribes a set of special methods. Any object that has those methods defined is considered a member of that duck type.
- If eq() method is not overridden, it returns
'id(self) == id(other)', which is the same as'self is other'. - That means all objects compare not equal by default.
- Only the left side object has eq() method called, unless it returns NotImplemented, in which case the right object is consulted.
class MyComparable:
def __init__(self, a):
self.a = a
def __eq__(self, other):
if isinstance(other, type(self)):
return self.a == other.a
return NotImplemented- Hashable object needs both hash() and eq() methods and its hash value should never change.
- Hashable objects that compare equal must have the same hash value, meaning default hash() that returns
'id(self)'will not do. - That is why Python automatically makes classes unhashable if you only implement eq().
class MyHashable:
def __init__(self, a):
self._a = a
@property
def a(self):
return self._a
def __eq__(self, other):
if isinstance(other, type(self)):
return self.a == other.a
return NotImplemented
def __hash__(self):
return hash(self.a)- With total_ordering decorator, you only need to provide eq() and one of lt(), gt(), le() or ge() special methods.
from functools import total_ordering
@total_ordering
class MySortable:
def __init__(self, a):
self.a = a
def __eq__(self, other):
if isinstance(other, type(self)):
return self.a == other.a
return NotImplemented
def __lt__(self, other):
if isinstance(other, type(self)):
return self.a < other.a
return NotImplemented- Any object that has methods next() and iter() is an iterator.
- Next() should return next item or raise StopIteration.
- Iter() should return 'self'.
class Counter:
def __init__(self):
self.i = 0
def __next__(self):
self.i += 1
return self.i
def __iter__(self):
return self>>> counter = Counter()
>>> next(counter), next(counter), next(counter)
(1, 2, 3)- Iterators returned by the iter() function, such as list_iterator and set_iterator.
- Objects returned by the itertools module, such as count, repeat and cycle.
- Generators returned by the generator functions and generator expressions.
- File objects returned by the open() function, etc.
- All functions and classes have a call() method, hence are callable.
- When this cheatsheet uses
'<function>'as an argument, it actually means'<callable>'.
class Counter:
def __init__(self):
self.i = 0
def __call__(self):
self.i += 1
return self.i>>> counter = Counter()
>>> counter(), counter(), counter()
(1, 2, 3)- Enter() should lock the resources and optionally return an object.
- Exit() should release the resources.
- Any exception that happens inside the with block is passed to the exit() method.
- If it wishes to suppress the exception it must return a true value.
class MyOpen:
def __init__(self, filename):
self.filename = filename
def __enter__(self):
self.file = open(self.filename)
return self.file
def __exit__(self, exc_type, exception, traceback):
self.file.close()>>> with open('test.txt', 'w') as file:
... file.write('Hello World!')
>>> with MyOpen('test.txt') as file:
... print(file.read())
Hello World!- Only required method is iter(). It should return an iterator of object's items.
- Contains() automatically works on any object that has iter() defined.
class MyIterable:
def __init__(self, a):
self.a = a
def __iter__(self):
return iter(self.a)
def __contains__(self, el):
return el in self.a>>> obj = MyIterable([1, 2, 3])
>>> [el for el in obj]
[1, 2, 3]
>>> 1 in obj
True- Only required methods are iter() and len().
- This cheatsheet actually means
'<iterable>'when it uses'<collection>'. - I chose not to use the name 'iterable' because it sounds scarier and more vague than 'collection'.
class MyCollection:
def __init__(self, a):
self.a = a
def __iter__(self):
return iter(self.a)
def __contains__(self, el):
return el in self.a
def __len__(self):
return len(self.a)- Only required methods are len() and getitem().
- Getitem() should return an item at index or raise IndexError.
- Iter() and contains() automatically work on any object that has getitem() defined.
- Reversed() automatically works on any object that has len() and getitem() defined.
class MySequence:
def __init__(self, a):
self.a = a
def __iter__(self):
return iter(self.a)
def __contains__(self, el):
return el in self.a
def __len__(self):
return len(self.a)
def __getitem__(self, i):
return self.a[i]
def __reversed__(self):
return reversed(self.a)- It's a richer interface than the basic sequence.
- Extending it generates iter(), contains(), reversed(), index() and count().
- Unlike
'abc.Iterable'and'abc.Collection', it is not a duck type. That is why'issubclass(MySequence, abc.Sequence)'would return False even if MySequence had all the methods defined.
from collections import abc
class MyAbcSequence(abc.Sequence):
def __init__(self, a):
self.a = a
def __len__(self):
return len(self.a)
def __getitem__(self, i):
return self.a[i]+------------+------------+------------+------------+--------------+
| | Iterable | Collection | Sequence | abc.Sequence |
+------------+------------+------------+------------+--------------+
| iter() | REQ | REQ | Yes | Yes |
| contains() | Yes | Yes | Yes | Yes |
| len() | | REQ | REQ | REQ |
| getitem() | | | REQ | REQ |
| reversed() | | | Yes | Yes |
| index() | | | | Yes |
| count() | | | | Yes |
+------------+------------+------------+------------+--------------+
- Other ABCs that generate missing methods are: MutableSequence, Set, MutableSet, Mapping and MutableMapping.
- Names of their required methods are stored in
'<abc>.__abstractmethods__'.
from enum import Enum, auto
class <enum_name>(Enum):
<member_name_1> = <value_1>
<member_name_2> = <value_2_a>, <value_2_b>
<member_name_3> = auto()- If there are no numeric values before auto(), it returns 1.
- Otherwise it returns an increment of the last numeric value.
<member> = <enum>.<member_name> # Returns a member.
<member> = <enum>['<member_name>'] # Returns a member or raises KeyError.
<member> = <enum>(<value>) # Returns a member or raises ValueError.
<str> = <member>.name # Returns member's name.
<obj> = <member>.value # Returns member's value.list_of_members = list(<enum>)
member_names = [a.name for a in <enum>]
member_values = [a.value for a in <enum>]
random_member = random.choice(list(<enum>))def get_next_member(member):
members = list(member.__class__)
index = (members.index(member) + 1) % len(members)
return members[index]Cutlery = Enum('Cutlery', 'fork knife spoon')
Cutlery = Enum('Cutlery', ['fork', 'knife', 'spoon'])
Cutlery = Enum('Cutlery', {'fork': 1, 'knife': 2, 'spoon': 3})from functools import partial
LogicOp = Enum('LogicOp', {'AND': partial(lambda l, r: l and r),
'OR' : partial(lambda l, r: l or r)})- Another solution in this particular case is to use built-in functions and_() and or_() from the module operator.
try:
<code>
except <exception>:
<code>try:
<code_1>
except <exception_a>:
<code_2_a>
except <exception_b>:
<code_2_b>
else:
<code_2_c>
finally:
<code_3>- Code inside the
'else'block will only be executed if'try'block had no exception. - Code inside the
'finally'block will always be executed.
except <exception>:
except <exception> as <name>:
except (<exception>, [...]):
except (<exception>, [...]) as <name>:- Also catches subclasses of the exception.
- Use
'traceback.print_exc()'to print the error message to stderr. - Use
'print(<name>)'to print just the cause of the exception (its arguments).
raise <exception>
raise <exception>()
raise <exception>(<el> [, ...])except <exception> as <name>:
...
raisearguments = <name>.args
exc_type = <name>.__class__
filename = <name>.__traceback__.tb_frame.f_code.co_filename
func_name = <name>.__traceback__.tb_frame.f_code.co_name
line = linecache.getline(filename, <name>.__traceback__.tb_lineno)
error_msg = ''.join(traceback.format_exception(exc_type, <name>, <name>.__traceback__))BaseException
+-- SystemExit # Raised by the sys.exit() function.
+-- KeyboardInterrupt # Raised when the user hits the interrupt key (ctrl-c).
+-- Exception # User-defined exceptions should be derived from this class.
+-- ArithmeticError # Base class for arithmetic errors.
| +-- ZeroDivisionError # Raised when dividing by zero.
+-- AttributeError # Raised when an attribute is missing.
+-- EOFError # Raised by input() when it hits end-of-file condition.
+-- LookupError # Raised when a look-up on a collection fails.
| +-- IndexError # Raised when a sequence index is out of range.
| +-- KeyError # Raised when a dictionary key or set element is not found.
+-- NameError # Raised when a variable name is not found.
+-- OSError # Errors such as “file not found” or “disk full” (see Open).
| +-- FileNotFoundError # When a file or directory is requested but doesn't exist.
+-- RuntimeError # Raised by errors that don't fall into other categories.
| +-- RecursionError # Raised when the maximum recursion depth is exceeded.
+-- StopIteration # Raised by next() when run on an empty iterator.
+-- TypeError # Raised when an argument is of wrong type.
+-- ValueError # When an argument is of right type but inappropriate value.
+-- UnicodeError # Raised when encoding/decoding strings to/from bytes fails.
+-----------+------------+------------+------------+
| | list | dict | set |
+-----------+------------+------------+------------+
| getitem() | IndexError | KeyError | |
| pop() | IndexError | KeyError | KeyError |
| remove() | ValueError | | KeyError |
| index() | ValueError | | |
+-----------+------------+------------+------------+
raise TypeError('Argument is of wrong type!')
raise ValueError('Argument is of right type but inappropriate value!')
raise RuntimeError('None of above!')class MyError(Exception):
pass
class MyInputError(MyError):
passExits the interpreter by raising SystemExit exception.
import sys
sys.exit() # Exits with exit code 0 (success).
sys.exit(<el>) # Prints to stderr and exits with 1.
sys.exit(<int>) # Exits with passed exit code.print(<el_1>, ..., sep=' ', end='\n', file=sys.stdout, flush=False)- Use
'file=sys.stderr'for messages about errors. - Use
'flush=True'to forcibly flush the stream.
from pprint import pprint
pprint(<collection>, width=80, depth=None, compact=False, sort_dicts=True)- Levels deeper than 'depth' get replaced by '...'.
Reads a line from user input or pipe if present.
<str> = input(prompt=None)- Trailing newline gets stripped.
- Prompt string is printed to the standard output before reading input.
- Raises EOFError when user hits EOF (ctrl-d/z) or input stream gets exhausted.
import sys
script_name = sys.argv[0]
arguments = sys.argv[1:]from argparse import ArgumentParser, FileType
p = ArgumentParser(description=<str>)
p.add_argument('-<short_name>', '--<name>', action='store_true') # Flag
p.add_argument('-<short_name>', '--<name>', type=<type>) # Option
p.add_argument('<name>', type=<type>, nargs=1) # First argument
p.add_argument('<name>', type=<type>, nargs='+') # Remaining arguments
p.add_argument('<name>', type=<type>, nargs='*') # Optional arguments
args = p.parse_args() # Exits on error.
value = args.<name>- Use
'help=<str>'to set argument description. - Use
'default=<el>'to set the default value. - Use
'type=FileType(<mode>)'for files.
Opens the file and returns a corresponding file object.
<file> = open(<path>, mode='r', encoding=None, newline=None)'encoding=None'means that the default encoding is used, which is platform dependent. Best practice is to use'encoding="utf-8"'whenever possible.'newline=None'means all different end of line combinations are converted to '\n' on read, while on write all '\n' characters are converted to system's default line separator.'newline=""'means no conversions take place, but input is still broken into chunks by readline() and readlines() on either '\n', '\r' or '\r\n'.
'r'- Read (default).'w'- Write (truncate).'x'- Write or fail if the file already exists.'a'- Append.'w+'- Read and write (truncate).'r+'- Read and write from the start.'a+'- Read and write from the end.'t'- Text mode (default).'b'- Binary mode.
'FileNotFoundError'can be raised when reading with'r'or'r+'.'FileExistsError'can be raised when writing with'x'.'IsADirectoryError'and'PermissionError'can be raised by any.'OSError'is the parent class of all listed exceptions.
<file>.seek(0) # Moves to the start of the file.
<file>.seek(offset) # Moves 'offset' chars/bytes from the start.
<file>.seek(0, 2) # Moves to the end of the file.
<bin_file>.seek(±offset, <anchor>) # Anchor: 0 start, 1 current position, 2 end.<str/bytes> = <file>.read(size=-1) # Reads 'size' chars/bytes or until EOF.
<str/bytes> = <file>.readline() # Returns a line or empty string/bytes on EOF.
<list> = <file>.readlines() # Returns a list of remaining lines.
<str/bytes> = next(<file>) # Returns a line using buffer. Do not mix.<file>.write(<str/bytes>) # Writes a string or bytes object.
<file>.writelines(<collection>) # Writes a coll. of strings or bytes objects.
<file>.flush() # Flushes write buffer.- Methods do not add or strip trailing newlines, even writelines().
def read_file(filename):
with open(filename, encoding='utf-8') as file:
return file.readlines()def write_to_file(filename, text):
with open(filename, 'w', encoding='utf-8') as file:
file.write(text)from os import getcwd, path, listdir
from glob import glob<str> = getcwd() # Returns the current working directory.
<str> = path.join(<path>, ...) # Joins two or more pathname components.
<str> = path.abspath(<path>) # Returns absolute path.<str> = path.basename(<path>) # Returns final component of the path.
<str> = path.dirname(<path>) # Returns path without the final component.
<tup.> = path.splitext(<path>) # Splits on last period of the final component.<list> = listdir(path='.') # Returns filenames located at path.
<list> = glob('<pattern>') # Returns paths matching the wildcard pattern.<bool> = path.exists(<path>) # Or: <Path>.exists()
<bool> = path.isfile(<path>) # Or: <DirEntry/Path>.is_file()
<bool> = path.isdir(<path>) # Or: <DirEntry/Path>.is_dir()Using scandir() instead of listdir() can significantly increase the performance of code that also needs file type information.
from os import scandir<iter> = scandir(path='.') # Returns DirEntry objects located at path.
<str> = <DirEntry>.path # Returns whole path as a string.
<s
244F
tr> = <DirEntry>.name # Returns final component as a string.
<file> = open(<DirEntry>) # Opens the file and returns file object.from pathlib import Path<Path> = Path(<path> [, ...]) # Accepts strings, Paths and DirEntry objects.
<Path> = <path> / <path> [/ ...] # One of the paths must be a Path object.<Path> = Path() # Returns relative cwd. Also Path('.').
<Path> = Path.cwd() # Returns absolute cwd. Also Path().resolve().
<Path> = Path.home() # Returns user's home directory.
<Path> = Path(__file__).resolve() # Returns script's path if cwd wasn't changed.<Path> = <Path>.parent # Returns Path without final component.
<str> = <Path>.name # Returns final component as a string.
<str> = <Path>.stem # Returns final component without extension.
<str> = <Path>.suffix # Returns final component's extension.
<tup.> = <Path>.parts # Returns all components as strings.<iter> = <Path>.iterdir() # Returns dir contents as Path objects.
<iter> = <Path>.glob('<pattern>') # Returns Paths matching the wildcard pattern.<str> = str(<Path>) # Returns path as a string.
<file> = open(<Path>) # Opens the file and returns file object.- Paths can be either strings, Paths or DirEntry objects.
- Functions report OS related errors by raising either OSError or one of its subclasses.
import os, shutilos.chdir(<path>) # Changes the current working directory.
os.mkdir(<path>, mode=0o777) # Creates a directory. Mode is in octal.shutil.copy(from, to) # Copies the file. 'to' can exist or be a dir.
shutil.copytree(from, to) # Copies the directory. 'to' must not exist.os.rename(from, to) # Renames/moves the file or directory.
os.replace(from, to) # Same, but overwrites 'to' if it exists.os.remove(<path>) # Deletes the file.
os.rmdir(<path>) # Deletes the empty directory.
shutil.rmtree(<path>) # Deletes the directory.import os
<str> = os.popen('<shell_command>').read()>>> from subprocess import run
>>> run('bc', input='1 + 1\n', capture_output=True, encoding='utf-8')
CompletedProcess(args='bc', returncode=0, stdout='2\n', stderr='')>>> from shlex import split
>>> os.popen('echo 1 + 1 > test.in')
>>> run(split('bc -s'), stdin=open('test.in'), stdout=open('test.out', 'w'))
CompletedProcess(args=['bc', '-s'], returncode=0)
>>> open('test.out').read()
'2\n'Text file format for storing collections of strings and numbers.
import json
<str> = json.dumps(<object>, ensure_ascii=True, indent=None)
<object> = json.loads(<str>)def read_json_file(filename):
with open(filename, encoding='utf-8') as file:
return json.load(file)def write_to_json_file(filename, an_object):
with open(filename, 'w', encoding='utf-8') as file:
json.dump(an_object, file, ensure_ascii=False, indent=2)Binary file format for storing objects.
import pickle
<bytes> = pickle.dumps(<object>)
<object> = pickle.loads(<bytes>)def read_pickle_file(filename):
with open(filename, 'rb') as file:
return pickle.load(file)def write_to_pickle_file(filename, an_object):
with open(filename, 'wb') as file:
pickle.dump(an_object, file)Text file format for storing spreadsheets.
import csv<reader> = csv.reader(<file>) # Also: `dialect='excel', delimiter=','`.
<list> = next(<reader>) # Returns next row as a list of strings.
<list> = list(<reader>) # Returns list of remaining rows.- File must be opened with
'newline=""'argument, or newlines embedded inside quoted fields will not be interpreted correctly!
<writer> = csv.writer(<file>) # Also: `dialect='excel', delimiter=','`.
<writer>.writerow(<collection>) # Encodes objects using `str(<el>)`.
<writer>.writerows(<coll_of_coll>) # Appends multiple rows.- File must be opened with
'newline=""'argument, or '\r' will be added in front of every '\n' on platforms that use '\r\n' line endings!
'dialect'- Master parameter that sets the default values.'delimiter'- A one-character string used to separate fields.'quotechar'- Character for quoting fields that contain special characters.'doublequote'- Whether quotechars inside fields get doubled or escaped.'skipinitialspace'- Whether whitespace after delimiter gets stripped.'lineterminator'- Specifies how writer terminates rows.'quoting'- Controls the amount of quoting: 0 - as necessary, 1 - all.'escapechar'- Character for escaping 'quotechar' if 'doublequote' is False.
+------------------+--------------+--------------+--------------+
| | excel | excel-tab | unix |
+------------------+--------------+--------------+--------------+
| delimiter | ',' | '\t' | ',' |
| quotechar | '"' | '"' | '"' |
| doublequote | True | True | True |
| skipinitialspace | False | False | False |
| lineterminator | '\r\n' | '\r\n' | '\n' |
| quoting | 0 | 0 | 1 |
| escapechar | None | None | None |
+------------------+--------------+--------------+--------------+
def read_csv_file(filename):
with open(filename, encoding='utf-8', newline='') as file:
return list(csv.reader(file))def write_to_csv_file(filename, rows):
with open(filename, 'w', encoding='utf-8', newline='') as file:
writer = csv.writer(file)
writer.writerows(rows)Server-less database engine that stores each database into a separate file.
Opens a connection to the database file. Creates a new file if path doesn't exist.
import sqlite3
<conn> = sqlite3.connect(<path>) # Also ':memory:'.
<conn>.close() # Closes the connection.Returned values can be of type str, int, float, bytes or None.
<cursor> = <conn>.execute('<query>') # Can raise a subclass of sqlite3.Error.
<tuple> = <cursor>.fetchone() # Returns next row. Also next(<cursor>).
<list> = <cursor>.fetchall() # Returns remaining rows. Also list(<cursor>).<conn>.execute('<query>') # Can raise a subclass of sqlite3.Error.
<conn>.commit() # Commits all transactions since last commit.with <conn>:
<conn>.execute('<query>')- Passed values can be of type str, int, float, bytes, None, bool, datetime.date or datetime.datetme.
- Bools will be stored and returned as ints and dates as ISO formatted strings.
<conn>.execute('<query>', <list/tuple>) # Replaces '?'s in query with values.
<conn>.execute('<query>', <dict/namedtuple>) # Replaces ':<key>'s with values.
<conn>.executemany('<query>', <coll_of_above>) # Runs execute() multiple times.In this example values are not actually saved because 'conn.commit()' is omitted!
>>> conn = sqlite3.connect('test.db')
>>> conn.execute('create table person (person_id integer primary key, name, height)')
>>> conn.execute('insert into person values (null, ?, ?)', ('Jean-Luc', 187)).lastrowid
1
>>> conn.execute('select * from person').fetchall()
[(1, 'Jean-Luc', 187)]Has a very similar interface, with differences listed below.
# $ pip3 install mysql-connector
from mysql import connector
<conn> = connector.connect(host=<str>, …) # `user=<str>, password=<str>, database=<str>`.
<cursor> = <conn>.cursor() # Only cursor has execute method.
<cursor>.execute('<query>') # Can raise a subclass of connector.Error.
<cursor>.execute('<query>', <list/tuple>) # Replaces '%s's in query with values.
<cursor>.execute('<query>', <dict/namedtuple>) # Replaces '%(<key>)s's with values.Bytes object is an immutable sequence of single bytes. Mutable version is called bytearray.
<bytes> = b'<str>' # Only accepts ASCII characters and \x00 - \xff.
<int> = <bytes>[<index>] # Returns int in range from 0 to 255.
<bytes> = <bytes>[<slice>] # Returns bytes even if it has only one element.
<bytes> = <bytes>.join(<coll_of_bytes>) # Joins elements using bytes object as separator.<bytes> = bytes(<coll_of_ints>) # Ints must be in range from 0 to 255.
<bytes> = bytes(<str>, 'utf-8') # Or: <str>.encode('utf-8')
<bytes> = <int>.to_bytes(n_bytes, …) # `byteorder='big/little', signed=False`.
<bytes> = bytes.fromhex('<hex>') # Hex pairs can be separated by spaces.

