Python Cheatsheet for Developers

Content Outlines

    1. Collections: List, Dictionary, Set, Tuple, Range, Enumerate, Iterator, Generator.
    2. Types:            Type, String, Regular_Exp, Format, Numbers, Combinatorics, Datetime.
    3. Syntax:           Args, Inline, Import, Decorator, Class, Duck_Types, 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.

Main

if __name__ == '__main__':     # Runs main() if file wasn't imported.
    main()

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List

<list> = <list>[<slice>]       # Or: <list>[from_inclusive : to_exclusive : ±step]

<list>.append(<el>)            # Or: <list> += [<el>] | adds a new element to the end of the list
<list>.extend(<collection>)    # Or: <list> += <collection> | adds all elements of a collection(list,tuples,etc) to the end of the list

<list>.sort()                  # Sorts in ascending order.
<list>.reverse()               # Reverses the list in-place.
<list> = sorted(<collection>)  # Returns a new sorted list.
<iter> = reversed(<list>)      # Returns reversed iterator.

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>)

For details about sorted(), min() and max() see sortable.
Module operator provides functions itemgetter() and mul() that offer the same functionality as lambda expressions above.

<list>.insert(<int>, <el>)     # Inserts item at index and moves the rest to the right.
<el>  = <list>.pop([<int>])    # Removes and returns item at index or from the end.
<int> = <list>.count(<el>)     # Returns number of occurrences. Also works on strings.
<int> = <list>.index(<el>)     # Returns index of the first occurrence or raises ValueError.
<list>.remove(<el>)            # Removes first occurrence of the item or raises ValueError.
<list>.clear()                 # Removes all items. Also works on dictionary and set.

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Dictionary

<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>)        # Returns a dict with default value of type.
<dict> = collections.defaultdict(lambda: 1)     # Returns 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.

Counter

>>> 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)

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Set

<set> = set()                                   # `{}` returns a dictionary.

<set>.add(<el>)                                 # Or: <set> |= {<el>}
<set>.update(<collection> [, ...])              # 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.

Frozen Set

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>)

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Tuple

Tuple is an immutable and hashable list.

<tuple> = ()                                # Empty tuple.
<tuple> = (<el>,)                           # Or: <el>,
<tuple> = (<el_1>, <el_2> [, ...])          # Or: <el_1>, <el_2> [, ...]

Named Tuple

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

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Range

Immutable and hashable sequence of integers.

<range> = range(stop)                       # range(to_exclusive)
<range> = range(start, stop)                # range(from_inclusive, to_exclusive)
<range> = range(start, stop, ±step)         # range(from_inclusive, to_exclusive, ±step_size)

>>> [i for i in range(3)]
[0, 1, 2]

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Enumerate

for i, el in enumerate(<collection> [, i_start]):
    ...

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Iterator

<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.

Itertools

import itertools as it

<iter> = it.count(start=0, step=1)          # Returns updated value endlessly. Accepts floats.
<iter> = it.repeat(<el> [, times])          # Returns element endlessly or 'times' times.
<iter> = it.cycle(<collection>)             # Repeats the sequence endlessly.

<iter> = it.chain(<coll>, <coll> [, ...])   # Empties collections in order (figuratively).
<iter> = it.chain.from_iterable(<coll>)     # Empties collections inside a collection in order.

<iter> = it.islice(<coll>, to_exclusive)    # Only returns first 'to_exclusive' elements.
<iter> = it.islice(<coll>, from_inc, …)     # `to_exclusive, +step_size`. Indices can be None.

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Generator

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)

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Type

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'>)

Some types do not have built-in names, so they must be imported:

from types import FunctionType, MethodType, LambdaType, GeneratorType, ModuleType

Abstract Base Classes

Each 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. For instance, Iterable ABC looks for method iter(), while Collection ABC looks for iter(), contains() and len().

>>> from collections.abc import Iterable, Collection, Sequence
>>> isinstance([1, 2, 3], Iterable)
True

+------------------+------------+------------+------------+
|                  |  Iterable  | Collection |  Sequence  |
+------------------+------------+------------+------------+
| list, range, str |    yes     |    yes     |    yes     |
| dict, set        |    yes     |    yes     |            |
| iter             |    yes     |            |            |
+------------------+------------+------------+------------+

>>> from numbers import Number, Complex, Real, Rational, Integral
>>> isinstance(123, Number)
True

+--------------------+----------+----------+----------+----------+----------+
|                    |  Number  |  Complex |   Real   | Rational | Integral |
+--------------------+----------+----------+----------+----------+----------+
| int                |   yes    |   yes    |   yes    |   yes    |   yes    |
| fractions.Fraction |   yes    |   yes    |   yes    |   yes    |          |
| float              |   yes    |   yes    |   yes    |          |          |
| complex            |   yes    |   yes    |          |          |          |
| decimal.Decimal    |   yes    |          |          |          |          |
+--------------------+----------+----------+----------+----------+----------+

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String

<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)    # On [\n\r\f\v\x1c-\x1e\x85\u2028\u2029] and \r\n.
<str>  = <str>.join(<coll_of_strings>)       # Joins elements using string as a 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 the 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 character.
<int>  = ord(<str>)                          # Converts Unicode character to int.

Also: 'lstrip()', 'rstrip()' and 'rsplit()'.
Also: 'lower()', 'upper()', 'capitalize()' and 'title()'.

Property Methods

+---------------+----------+----------+----------+----------+----------+
|               | [ !#$%…] | [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\x1c-\x1f\x85\u2000…]'.

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Regex

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.

Argument 'new' can be a function that accepts a Match object and returns a string.
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 ('\1' returns a character with octal code 1).
Add '?' after '*' and '+' to make them non-greedy.

Match Object

<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.

Special Sequences

'\d' == '[0-9]'                                # Matches decimal characters.
'\w' == '[a-zA-Z0-9_]'                         # Matches alphanumerics and underscore.
'\s' == '[ \t\n\r\f\v]'                        # Matches whitespaces.

By default, decimal characters, alphanumerics and whitespaces from all alphabets are matched unless 'flags=re.ASCII' argument is used.
As shown above, it restricts all special sequence matches to the first 128 characters and prevents '\s' from accepting '[\x1c-\x1f]' (the so-called separator characters).
Use a capital letter for negation (all non-ASCII characters will be matched when used in combination with ASCII flag).

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Format

<str> = f'{<el_1>}, {<el_2>}'            # Curly brackets can also contain expressions.
<str> = '{}, {}'.format(<el_1>, <el_2>)  # Or: '{0}, {a}'.format(<el_1>, a=<el_2>)
<str> = '%s, %s' % (<el_1>, <el_2>)      # Redundant and inferior C style formatting.

Attributes

>>> Person = collections.namedtuple('Person', 'name height')
>>> person = Person('Jean-Luc', 187)
>>> f'{person.height}'
'187'
>>> '{p.height}'.format(p=person)
'187'

General Options

{<el>:<10}                               # '<el>      '
{<el>:^10}                               # '   <el>   '
{<el>:>10}                               # '      <el>'
{<el>:.<10}                              # '<el>......'
{<el>:0}                                 # '<el>'

Options can be generated dynamically: f'{<el>:{<str/int>}[…]}'.
Adding '!r' before the colon converts object to string by calling its repr() method.

Strings

{'abcde':10}                             # 'abcde     '
{'abcde':10.3}                           # 'abc       '
{'abcde':.3}                             # 'abc'
{'abcde'!r:10}                           # "'abcde'   "

Numbers

{123456:10}                              # '    123456'
{123456:10,}                             # '   123,456'
{123456:10_}                             # '   123_456'
{123456:+10}                             # '   +123456'
{123456:=+10}                            # '+   123456'
{123456: }                               # ' 123456'
{-123456: }                              # '-123456'

Floats

{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%'

Comparison of presentation types:

+--------------+----------------+----------------+----------------+----------------+
|              |    {<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%' |
+--------------+----------------+----------------+----------------+----------------+

+--------------+----------------+----------------+----------------+----------------+
|              |  {<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%'   |
+--------------+----------------+----------------+----------------+----------------+

When both rounding up and rounding down are possible, the one that returns result with even last digit is chosen. That makes '{6.5:.0f}' a '6' and '{7.5:.0f}' an '8'.
This rule only effects numbers that can be represented exactly by a float (.5, .25, …).

Ints

{90:c}                                   # 'Z'
{90:b}                                   # '1011010'
{90:X}                                   # '5A'

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Numbers

<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 are stored exactly, unlike most floats where '1.1 + 2.2 != 3.3'.
Floats can be compared with: 'math.isclose(<float>, <float>)'.
Precision of decimal operations is set with: 'decimal.getcontext().prec = <int>'.

Basic Functions

<num> = pow(<num>, <num>)                         # Or: <num> ** <num>
<num> = abs(<num>)                                # <float> = abs(<complex>)
<num> = round(<num> [, ±ndigits])                 # `round(126, -1) == 130`

Math

from math import e, pi, inf, nan, isinf, isnan    # `<el> == nan` is always False.
from math import sin, cos, tan, asin, acos, atan  # Also: degrees, radians.
from math import log, log10, log2                 # Log can accept base as second arg.

Statistics

from statistics import mean, median, variance     # Also: stdev, quantiles, groupby.

Random

from random import random, randint, choice        # Also shuffle, gauss, triangular, seed.
<float> = random()                                # A float inside [0, 1).
<int>   = randint(from_inc, to_inc)               # An int inside [from_inc, to_inc].
<el>    = choice(<sequence>)                      # Keeps the sequence intact.

Bin, Hex

<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>'.

Bitwise Operators

<int> = <int> & <int>                             # And (0b1100 & 0b1010 == 0b1000).
<int> = <int> | <int>                             # Or  (0b1100 | 0b1010 == 0b1110).
<int> = <int> ^ <int>                             # Xor (0b1100 ^ 0b1010 == 0b0110).
<int> = <int> << n_bits                           # Left shift. Use >> for right.
<int> = ~<int>                                    # Not. Also -<int> - 1.

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Combinatorics

Every function returns an iterator.
If you want to print the iterator, you need to pass it to the list() function first!

import itertools as it

>>> it.product([0, 1], repeat=3)
[(0, 0, 0), (0, 0, 1), (0, 1, 0), (0, 1, 1),
 (1, 0, 0), (1, 0, 1), (1, 1, 0), (1, 1, 1)]

>>> it.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

>>> it.combinations('abc', 2)                     #   a  b  c
[('a', 'b'), ('a', 'c'),                          # a .  x  x
 ('b', 'c')]                                      # b .  .  x

>>> it.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

>>> it.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  .

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Datetime

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, datetime_exists, resolve_imaginary

Constructors

<D>  = date(year, month, day)               # Only accepts valid dates from 1 to 9999 AD.
<T>  = time(hour=0, minute=0, second=0)     # Also: `microsecond=0, tzinfo=None, fold=0`.
<DT> = datetime(year, month, day, hour=0)   # Also: `minute=0, second=0, microsecond=0, …`.
<TD> = timedelta(weeks=0, days=0, hours=0)  # Also: `minutes=0, seconds=0, microsecond=0`.

Use '<D/DT>.weekday()' to get the day of the week as an int, with Monday being 0.
'fold=1' means the second pass in case of time jumping back for one hour.
Timedelta normalizes arguments to ±days, seconds (< 86 400) and microseconds (< 1M).

Now

<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()'.

Timezone

<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 the passed timezone.
<Ta/DTa> = <T/DT>.replace(tzinfo=<tzinfo>)  # Unconverted object with a new timezone.

Encode

<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 the Gregorian NYE 1.
<DTn>    = DT.fromtimestamp(<real>)         # Local time DTn from seconds since the Epoch.
<DTa>    = DT.fromtimestamp(<real>, <tz.>)  # Aware datetime from seconds since the Epoch.

ISO strings come in following forms: 'YYYY-MM-DD', 'HH:MM:SS.mmmuuu[±HH:MM]', or both separated by an arbitrary character. All parts following hours are optional.
Python uses the Unix Epoch: '1970-01-01 00:00 UTC', '1970-01-01 01:00 CET', ...

Decode

<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 Gregorian NYE 1, ignoring time and tz.
<float>  = <DTn>.timestamp()                # Seconds since the Epoch, from DTn in local tz.
<float>  = <DTa>.timestamp()                # Seconds since the Epoch, from aware datetime.

Format

>>> dt = datetime.strptime('2015-05-14 23:39:00.00 +2000', '%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"

'%Z' only accepts 'UTC/GMT' and local timezone's code. '%z' also accepts '±HH:MM'.
For abbreviated weekday and month use '%a' and '%b'.

Arithmetics

<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>     = <TD>    * <real>                 # Also: <TD> = abs(<TD>) and <TD> = <TD> ±% <TD>.
<float>  = <TD>    / <TD>                   # How many weeks/years there are in TD. Also //.

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Arguments

Inside Function Call

func(<positional_args>)                           # func(0, 0)
func(<keyword_args>)                              # func(x=0, y=0)
func(<positional_args>, <keyword_args>)           # func(0, y=0)

Inside Function Definition

def func(<nondefault_args>): ...                  # def func(x, y): ...
def func(<default_args>): ...                     # def func(x=0, y=0): ...
def func(<nondefault_args>, <default_args>): ...  # def func(x, y=0): ...

Default values are evaluated when function is first encountered in the scope.
Any mutation of a mutable default value will persist between invocations.

Splat Operator

Inside Function Call

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)

Is the same as:

func(1, 2, x=3, y=4, z=5)

Inside Function Definition

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)
6

Legal argument combinations:

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(**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(*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, 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)

Other Uses

<list>  = [*<coll.> [, ...]]    # Or: list(<collection>) [+ ...]
<tuple> = (*<coll.>, [...])     # Or: tuple(<collection>) [+ ...]
<set>   = {*<coll.> [, ...]}    # Or: set(<collection>) [| ...]
<dict>  = {**<dict> [, ...]}    # Or: dict(**<dict> [, ...])

head, *body, tail = <coll.>     # Head or tail can be omitted.

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Inline

Lambda

<func> = lambda: <return_value>                     # A single statement function.
<func> = lambda <arg_1>, <arg_2>: <return_value>    # Also accepts default arguments.

Comprehensions

<list> = [i+1 for i in range(10)]                   # Or: [1, 2, ..., 10]
<iter> = (i for i in range(10) if i > 5)            # Or: iter([6, 7, 8, 9])
<set>  = {i+5 for i in range(10)}                   # Or: {5, 6, ..., 14}
<dict> = {i: i*2 for i in range(10)}                # Or: {0: 0, 1: 2, ..., 9: 18}

>>> [l+r for l in 'abc' for r in 'abc']
['aa', 'ab', 'ac', ..., 'cc']

Map, Filter, Reduce

<iter> = map(lambda x: x + 1, range(10))            # Or: iter([1, 2, ..., 10])
<iter> = filter(lambda x: x > 5, range(10))         # Or: iter([6, 7, 8, 9])
<obj>  = reduce(lambda out, x: out + x, range(10))  # Or: 45

Reduce must be imported from the functools module.

Any, All

<bool> = any(<collection>)                          # Is `bool(el)` True for any element.
<bool> = all(<collection>)                          # Is True for all elements or empty.

Conditional Expression

<obj> = <exp> if <condition> else <exp>             # Only one expression gets evaluated.

>>> [a if a else 'zero' for a in (0, 1, 2, 3)]
['zero', 1, 2, 3]

Named Tuple, Enum, Dataclass

from collections import namedtuple
Point = namedtuple('Point', 'x y')                  # Creates a tuple's subclass.
point = Point(0, 0)                                 # Returns its instance.

from enum import Enum
Direction = Enum('Direction', 'n e s w')            # Creates an enum.
direction = Direction.n                             # Returns its member.

from dataclasses import make_dataclass
Player = make_dataclass('Player', ['loc', 'dir'])   # Creates a class.
player = Player(point, direction)                   # Returns its instance.

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Imports

import <module>            # Imports a built-in or '<module>.py'.
import <package>           # Imports a built-in or '<package>/__init__.py'.
import <package>.<module>  # Imports a built-in or '<package>/<module>.py'.

Package is a collection of modules, but it can also define its own objects.
On a filesystem this corresponds to a directory of Python files with an optional init script.
Running 'import <package>' does not automatically provide access to the package's modules unless they are explicitly imported in its init script.

Closure

We have/get 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'.

Partial

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>)'.

Non-Local

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)

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Decorator

A decorator takes a function, adds some functionality and returns it.
It can be any callable, but is usually implemented as a function that returns a closure.

@decorator_name
def function_that_gets_passed_to_decorator():
    ...

Debugger Example

Decorator that prints function's name every time the function is 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'.

LRU Cache

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)

Default size of the cache is 128 values. Passing 'maxsize=None' makes it unbounded.
CPython interpreter limits recursion depth to 1000 by default. To increase it use 'sys.setrecursionlimit(<depth>)'.

Parametrized Decorator

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 + y

Using only '@debug' to decorate the add() function would not work here, because debug would then receive the add() function as a 'print_result' argument. Decorators can however manually check if the argument they received is a function and act accordingly.

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Class

class <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().
Methods decorated with '@staticmethod' do not receive 'self' nor 'cls' as their first arg.

Str() use cases:

print(<el>)
f'{<el>}'
logging.warning(<el>)
csv.writer(<file>).writerow([<el>])
raise Exception(<el>)

Repr() use cases:

print/str/repr([<el>])
f'{<el>!r}'
Z = dataclasses.make_dataclass('Z', ['a']); print/str/repr(Z(<el>))
>>> <el>

Constructor Overloading

class <name>:
    def __init__(self, a=None):
        self.a = a

Inheritance

class 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_num

Multiple Inheritance

class A: pass
class B: pass
class C(A, B): pass

MRO determines the order in which parent classes are traversed when searching for a method or an attribute:

>>> C.mro()
[<class 'C'>, <class 'A'>, <class 'B'>, <class 'object'>]

Property

Pythonic way of implementing getters and setters.

class Person:
    @property
    def name(self):
        return ' '.join(self._name)

    @name.setter
    def name(self, value):
        self._name = value.split()

>>> person = Person()
>>> person.name = '\t Guido  van Rossum \n'
>>> person.name
'Guido van Rossum'

Dataclass

Decorator 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. Its 'default_factory' argument can be any callable.
For attributes of arbitrary type use 'typing.Any'.

Inline:

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>])

Rest of type annotations (CPython interpreter ignores them all):

def func(<arg_name>: <type> [= <obj>]) -> <type>: ...
<var_name>: typing.List/Set/Iterable/Sequence/Optional[<type>]
<var_name>: typing.Dict/Tuple/Union[<type>, ...]

Slots

Mechanism that restricts objects to attributes listed in 'slots' and significantly reduces their memory footprint.

class MyClassWithSlots:
    __slots__ = ['a']
    def __init__(self):
        self.a = 1

Copy

from copy import copy, deepcopy
<object> = copy(<object>)
<object> = deepcopy(<object>)

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Duck Types

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.

Comparable

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. False is returned if both return NotImplemented.
Ne() automatically works on any object that has eq() defined.

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

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)

Sortable

With 'total_ordering' decorator, you only need to provide eq() and one of lt(), gt(), le() or ge() special methods and the rest will be automatically generated.
Functions sorted() and min() only require lt() method, while max() only requires gt(). However, it is best to define them all so that confusion doesn't arise in other contexts.
When two lists, strings or dataclasses are compared, their values get compared in order until a pair of unequal values is found. The comparison of this two values is then returned. The shorter sequence is considered smaller in case of all values being equal.

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

Iterator

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)

Python has many different iterator objects:

Sequence 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.

Callable

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)

Context Manager

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!

Iterable Duck Types

Iterable

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

Collection

Only required methods are iter() and len(). Len() should return the number of items.
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'. The only drawback of this decision is that a reader could think a certain function doesn't accept iterators when it does, since iterators are the only built-in objects that are iterable but are not collections.

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)

Sequence

Only required methods are len() and getitem().
Getitem() should return an item at the passed 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)

Discrepancies between glossary definitions and abstract base classes:

Glossary defines iterable as any object with iter() or getitem() and sequence as any object with getitem() and len(). It does not define collection.
Passing ABC Iterable to isinstance() or issubclass() checks whether object/class has method iter(), while ABC Collection checks for iter(), contains() and len().

ABC Sequence

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. It however recognizes list, tuple, range, str, bytes, bytearray, memoryview and deque, because they are registered as Sequence's virtual subclasses.

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]

Table of required and automatically available special methods:

+------------+------------+------------+------------+--------------+
|            |  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__'.

Enum

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]

Inline

Cutlery = Enum('Cutlery', 'fork knife spoon')
Cutlery = Enum('Cutlery', ['fork', 'knife', 'spoon'])
Cutlery = Enum('Cutlery', {'fork': 1, 'knife': 2, 'spoon': 3})

User-defined functions cannot be values, so they must be wrapped:

from functools import partial
LogicOp = Enum('LogicOp', {'AND': partial(lambda l, r: l and r),
                           'OR':  partial(lambda l, r: l or r)})

Member names are in all caps because trying to access a member that is named after a reserved keyword raises SyntaxError.

Exceptions

try:
    <code>
except <exception>:
    <code>

Complex Example

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 exceptions.
Code inside the 'finally' block will always be executed (unless a signal is received).

Catching Exceptions

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).
Use 'logging.exception(<message>)' to log the exception.

Raising Exceptions

raise <exception>
raise <exception>()
raise <exception>(<el> [, ...])

Re-raising caught exception:

except <exception> as <name>:
    ...
    raise

Exception Object

arguments = <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)
traceback = ''.join(traceback.format_tb(<name>.__traceback__))
error_msg = ''.join(traceback.format_exception(exc_type, <name>, <name>.__traceback__))

Built-in Exceptions

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.
      +-- AssertionError          # Raised by `assert <exp>` if expression returns false value.
      +-- 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 missing.
      +-- MemoryError             # Out of memory. Could be too late to start deleting vars.
      +-- NameError               # Raised when an object is missing.
      +-- 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.

Collections and their exceptions:

+-----------+------------+------------+------------+
|           |    List    |    Set     |    Dict    |
+-----------+------------+------------+------------+
| getitem() | IndexError |            |  KeyError  |
| pop()     | IndexError |  KeyError  |  KeyError  |
| remove()  | ValueError |  KeyError  |            |
| index()   | ValueError |            |            |
+-----------+------------+------------+------------+

Useful built-in exceptions:

raise TypeError('Argument is of wrong type!')
raise ValueError('Argument is of right type but inappropriate value!')
raise RuntimeError('None of above!')

User-defined Exceptions

class MyError(Exception): pass
class MyInputError(MyError): pass

Exit

Exits 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

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.

Pretty Print

from pprint import pprint
pprint(<collection>, width=80, depth=None, compact=False, sort_dicts=True)

Levels deeper than 'depth' get replaced by '...'.

Input

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/ctrl-z⏎) or input stream gets exhausted.

Command Line Arguments

import sys
scripts_path = sys.argv[0]
arguments    = sys.argv[1:]

Argument Parser

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 that will be displayed in help message.
Use 'default=<el>' to set the default value.
Use 'type=FileType(<mode>)' for files. Accepts 'encoding', but 'newline' is None.

Open

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 every '\n', '\r' and '\r\n'.

Modes

'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 ('br', 'bw', 'bx', …).

Exceptions

'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 Object

<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. Runs every 4096/8192 B.

Methods do not add or strip trailing newlines, even writelines().

Read Text from File

def read_file(filename):
    with open(filename, encoding='utf-8') as file:
        return file.readlines()

Write Text to File

def write_to_file(filename, text):
    with open(filename, 'w', encoding='utf-8') as file:
        file.write(text)

Paths

from os import getcwd, path, listdir, scandir
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()

<stat> = os.stat(<path>)            # Or: <DirEntry/Path>.stat()
<real> = <stat>.st_mtime/st_size/…  # Modification time, size in bytes, …

DirEntry

Unlike listdir(), scandir() returns DirEntry objects that cache isfile, isdir and on Windows also stat information, thus significantly increasing the performance of code that requires it.

<iter> = scandir(path='.')          # Returns DirEntry objects located at path.
<str>  = <DirEntry>.path            # Returns whole path as a string.
<str>  = <DirEntry>.name            # Returns final component as a string.
<file> = open(<DirEntry>)           # Opens the file and returns a file object.

Path Object

from pathlib import Path

<Path> = Path(<path> [, ...])       # Accepts strings, Paths and DirEntry objects.
<Path> = <path> / <path> [/ ...]    # First or second path 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 (absolute).
<Path> = Path(__file__).resolve()   # Returns script's path if cwd wasn't changed.

<Path> = <Path>.parent              # Returns Path without the 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 directory 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>)               # Also <Path>.read/write_text/bytes().

OS Commands

import os, shutil, subprocess

os.chdir(<path>)                    # Changes the current working directory.
os.mkdir(<path>, mode=0o777)        # Creates a directory. Permissions are in octal.
os.makedirs(<path>, mode=0o777)     # Creates all path's dirs. Also: `exist_ok=False`.

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.

Files

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Python Cheatsheet for Developers

Content Outlines

Main

List

Dictionary

Counter

Set

Frozen Set

Tuple

Named Tuple

Range

Enumerate

Iterator

Itertools

Generator

Type

Some types do not have built-in names, so they must be imported:

Abstract Base Classes

String

Property Methods

Regex

Match Object

Special Sequences

Format

Attributes

General Options

Strings

Numbers

Floats

Comparison of presentation types:

Ints

Numbers

Basic Functions

Math

Statistics

Random

Bin, Hex

Bitwise Operators

Combinatorics

Datetime

Constructors

Now

Timezone

Encode

Decode

Format

Arithmetics

Arguments

Inside Function Call

Inside Function Definition

Splat Operator

Inside Function Call

Is the same as:

Inside Function Definition

Legal argument combinations:

Other Uses

Inline

Lambda

Comprehensions

Map, Filter, Reduce

Any, All

Conditional Expression

Named Tuple, Enum, Dataclass

Imports

Closure

Partial

Non-Local

Decorator

Debugger Example

LRU Cache

Parametrized Decorator

Class

Str() use cases:

Repr() use cases: