Comprehensive Python Cheatsheet

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ToC = {
    '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, Match_Stmt, Logging, Introspection, Coroutines],
    '7. Libraries':   [Progress_Bar, Plot, Table, Console_App, GUI, Scraping, Web, Profile],
    '8. Multimedia':  [NumPy, Image, Animation, Audio, Synthesizer, Pygame, Pandas, Plotly]
}

#Main

if __name__ == '__main__':      # Skips next line if file was imported.
    main()                      # Runs `def main(): ...` function.

#List

<list> = [<el_1>, <el_2>, ...]  # Creates new list. Also list(<collection>).

#Dictionary

<dict> = {key_1: val_1, key_2: val_2, ...}      # Use `<dict>[key]` to get or set the value.

Counter

>>> from collections import Counter
>>> counter = Counter(['blue', 'blue', 'blue', 'red', 'red'])
>>> counter['yellow'] += 1
>>> print(counter.most_common())
[('blue', 3), ('red', 2), ('yellow', 1)]

#Set

<set> = {<el_1>, <el_2>, ...}                   # Use `set()` for empty set.

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>)

#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); p
Point(x=1, y=2)
>>> p[0]
1
>>> p.x
1
>>> getattr(p, 'y')
2

#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)

#Enumerate

for i, el in enumerate(<coll>, start=0):   # Returns next element and its index on each pass.
    ...

#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

#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

#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>)

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

#String

Immutable sequence of characters.

<str>  = <str>.strip()                       # Strips all whitespace characters from both ends.
<str>  = <str>.strip('<chars>')              # Strips passed characters. Also lstrip/rstrip().

Property Methods

<bool> = <str>.isdecimal()                   # Checks for [0-9]. Also [०-९] and [٠-٩].
<bool> = <str>.isdigit()                     # Checks for [²³¹…] and isdecimal().
<bool> = <str>.isnumeric()                   # Checks for [¼½¾…], [零〇一…] and isdigit().
<bool> = <str>.isalnum()                     # Checks for [a-zA-Z…] and isnumeric().
<bool> = <str>.isprintable()                 # Checks for [ !#$%…] and isalnum().
<bool> = <str>.isspace()                     # Checks for [ \t\n\r\f\v\x1c-\x1f\x85\xa0…].

#Regex

Functions for regular expression matching.

import re
<str>   = re.sub(r'<regex>', new, text, count=0)  # Substitutes all occurrences with 'new'.
<list>  = re.findall(r'<regex>', text)            # Returns all occurrences as strings.
<list>  = re.split(r'<regex>', text, maxsplit=0)  # Add brackets around regex to keep matches.
<Match> = re.search(r'<regex>', text)             # First occurrence of the pattern or None.
<Match> = re.match(r'<regex>', text)              # Searches only at the beginning of the text.
<iter>  = re.finditer(r'<regex>', text)           # Returns all occurrences as Match objects.

Match Object

<str>   = <Match>.group()                         # Returns the whole match. Also group(0).
<str>   = <Match>.group(1)                        # Returns part inside the first brackets.
<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]'                                   # Also [०-९…]. Matches a decimal character.
'\w' == '[a-zA-Z0-9_]'                            # Also [ª²³…]. Matches an alphanumeric or _.
'\s' == '[ \t\n\r\f\v]'                           # Also [\x1c-\x1f…]. Matches a whitespace.

#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.

Example

>>> Person = collections.namedtuple('Person', 'name height')
>>> person = Person('Jean-Luc', 187)
>>> f'{person.name} is {person.height / 100} meters tall.'
'Jean-Luc is 1.87 meters tall.'

General Options

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

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%'   ┃
┗━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━━┛

Ints

{90:c}                                   # 'Z'. Unicode character with value 90.
{90:b}                                   # '1011010'. Number 90 in binary.
{90:X}                                   # '5A'. Number 90 in uppercase hexadecimal.

#Numbers

<int>      = int(<float/str/bool>)                # Or: math.floor(<float>)
<float>    = float(<int/str/bool>)                # Or: <int/float>e±<int>
<complex>  = complex(real=0, imag=0)              # Or: <int/float> ± <int/float>j
<Fraction> = fractions.Fraction(0, 1)             # Or: Fraction(numerator=0, denominator=1)
<Decimal>  = decimal.Decimal(<str/int>)           # Or: Decimal((sign, digits, exponent))

Basic Functions

<num> = pow(<num>, <num>)                         # Or: <number> ** <number>
<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>'. Also hex().

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.

#Combinatorics

import itertools as it

#Datetime

Provides 'date', 'time', 'datetime' and 'timedelta' classes. All are immutable and hashable.

# $ pip3 install python-dateutil
from datetime import date, time, datetime, timedelta, timezone
import zoneinfo, dateutil.tz

Now

<D/DTn> = D/DT.today()                      # Current local date or naive DT. Also DT.now().
<DTa>   = DT.now(<tzinfo>)                  # Aware DT from current time in passed timezone.

Timezone

<tzinfo> = timezone.utc                     # London without daylight saving time (DST).
<tzinfo> = timezone(<timedelta>)            # Timezone with fixed offset from UTC.
<tzinfo> = dateutil.tz.tzlocal()            # Local timezone with dynamic offset from UTC.
<tzinfo> = zoneinfo.ZoneInfo('<iana_key>')  # 'Continent/City_Name' zone with dynamic offset.
<DTa>    = <DT>.astimezone([<tzinfo>])      # Converts DT to the passed or local fixed zone.
<Ta/DTa> = <T/DT>.replace(tzinfo=<tzinfo>)  # Changes object's timezone without conversion.

Encode

<D/T/DT> = D/T/DT.fromisoformat(<str>)      # Object from ISO string. Raises ValueError.
<DT>     = DT.strptime(<str>, '<format>')   # Datetime from str, according to format.
<D/DTn>  = D/DT.fromordinal(<int>)          # D/DT from days since the Gregorian NYE 1.
<DTn>    = DT.fromtimestamp(<float>)        # Local naive DT from seconds since the Epoch.
<DTa>    = DT.fromtimestamp(<float>, <tz>)  # Aware datetime from seconds since the Epoch.

Decode

<str>    = <D/T/DT>.isoformat(sep='T')      # Also `timespec='auto/hours/minutes/seconds/…'`.
<str>    = <D/T/DT>.strftime('<format>')    # Custom string representation of the object.
<int>    = <D/DT>.toordinal()               # Days since Gregorian NYE 1, ignoring time and tz.
<float>  = <DTn>.timestamp()                # Seconds since the Epoch, from local naive DT.
<float>  = <DTa>.timestamp()                # Seconds since the Epoch, from aware datetime.

Format

>>> dt = datetime.strptime('2025-08-14 23:39:00.00 +0200', '%Y-%m-%d %H:%M:%S.%f %z')
>>> dt.strftime("%dth of %B '%y (%a), %I:%M %p %Z")
"14th of August '25 (Thu), 11:39 PM UTC+02:00"

Arithmetics

<bool>   = <D/T/DTn> > <D/T/DTn>            # Ignores time jumps (fold attribute). Also ==.
<bool>   = <DTa>     > <DTa>                # Ignores jumps if they share tz object. Broken ==.
<TD>     = <D/DTn>   - <D/DTn>              # Ignores jumps. Convert to UTC for actual delta.
<TD>     = <DTa>     - <DTa>                # Ignores jumps if they share tzinfo object.
<D/DT>   = <D/DT>    ± <TD>                 # Returned datetime can fall into missing hour.
<TD>     = <TD>      * <float>              # Also: <TD> = abs(<TD>) and <TD> = <TD> ±% <TD>.
<float>  = <TD>      / <TD>                 # E.g. how many hours are in TD. Also //, divmod().

#Arguments

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): ...

#Splat Operator

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)

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)

Other Uses

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

#Inline

<func> = lambda: <return_value>                     # A single statement function.
<func> = lambda <arg_1>, <arg_2>: <return_value>    # Also allows 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}

Map, Filter, Reduce

from functools import reduce

Any, All

<bool> = any(<collection>)                          # Is `bool(<el>)` True for any el?
<bool> = all(<collection>)                          # True for all? Also True if empty.

Conditional Expression

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

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.

#Imports

Mechanism that makes code in one file available to another file.

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'.

#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

Partial

from functools import partial
<function> = partial(<function> [, <arg_1> [, ...]])

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

#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

Cache

Decorator that caches function's return values. All function's arguments must be hashable.

from functools import cache

@cache
def fib(n):
    return n if n < 2 else fib(n-2) + fib(n-1)

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

#Class

A template for creating user-defined objects.

class MyClass:
    def __init__(self, a):
        self.a = a
    def __str__(self):
        return str(self.a)
    def __repr__(self):
        class_name = self.__class__.__name__
        return f'{class_name}({self.a!r})'

    @classmethod
    def get_class_name(cls):
        return cls.__name__

Expressions that call the str() method:

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

Expressions that call the repr() method:

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

Inheritance

class Person:
    def __init__(self, name):
        self.name = name

class Employee(Person):
    def __init__(self, name, staff_num):
        super().__init__(name)
        self.staff_num = staff_num

Multiple inheritance:

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

Type Annotations

• They add type hints to variables, arguments and functions ('def f() -> <type>:').
• Hints are used by type checkers like mypy, data validation libraries such as Pydantic and lately also by Cython compiler. However, they are not enforced by CPython interpreter.

from collections import abc

<name>: <type> [| ...] [= <obj>]                              # `|` since 3.10.
<name>: list/set/abc.Iterable/abc.Sequence[<type>] [= <obj>]  # Since 3.9.
<name>: dict/tuple[<type>, ...] [= <obj>]                     # Since 3.9.

Dataclass

Decorator that uses class variables to generate init(), repr() and eq() special methods.

from dataclasses import dataclass, field, make_dataclass

@dataclass(order=False, frozen=False)
class <class_name>:
    <attr_name>: <type>
    <attr_name>: <type> = <default_value>
    <attr_name>: list/dict/set = field(default_factory=list/dict/set)

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()

Slots

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

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

Copy

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

#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.

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.
• To sort collection of strings in proper alphabetical order pass 'key=locale.strxfrm' to sorted() after running 'locale.setlocale(locale.LC_COLLATE, "en_US.UTF-8")'.

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 exception.
• 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

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.

class Counter:
    def __init__(self):
        self.i = 0
    def __call__(self):
        self.i += 1
        return self.i

Context Manager

• With statements only work on objects that have enter() and exit() special methods.
• 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.
• The exit() method can suppress the exception by returning 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()

#Iterable Duck Types

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

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 main drawback of this decision is that the 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 getitem() and len().
• 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 getitem() and len() defined. It returns reversed iterator of object's items.

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 on Python's website 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, array, memoryview and deque, since 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()     │     !      │     !      │     ✓      │      ✓       ┃
┃ contains() │     ✓      │     ✓      │     ✓      │      ✓       ┃
┃ len()      │            │     !      │     !      │      !       ┃
┃ getitem()  │            │            │     !      │      !       ┃
┃ reversed() │            │            │     ✓      │      ✓       ┃
┃ index()    │            │            │            │      ✓       ┃
┃ count()    │            │            │            │      ✓       ┃
┗━━━━━━━━━━━━┷━━━━━━━━━━━━┷━━━━━━━━━━━━┷━━━━━━━━━━━━┷━━━━━━━━━━━━━━┛

#Enum

Class of named constants called members.

from enum import Enum, auto

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)})

#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>

Catching Exceptions

except <exception>: ...
except <exception> as <name>: ...
except (<exception>, [...]): ...
except (<exception>, [...]) as <name>: ...

Raising Exceptions

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

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)
trace_str = ''.join(traceback.format_tb(<name>.__traceback__))
error_msg = ''.join(traceback.format_exception(type(<name>), <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 such as ZeroDivisionError.
      ├── AssertionError          # Raised by `assert <exp>` if expression returns false value.
      ├── AttributeError          # Raised when object doesn't have requested attribute/method.
      ├── EOFError                # Raised by input() when it hits an end-of-file condition.
      ├── LookupError             # Base class for errors when a collection can't find an item.
      │    ├── 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. May be too late to start deleting variables.
      ├── NameError               # Raised when nonexistent name (variable/func/class) is used.
      │    └── UnboundLocalError  # Raised when local name is used before it's being defined.
      ├── OSError                 # Errors such as FileExistsError/TimeoutError (see #Open).
      │    └── ConnectionError    # Errors such as BrokenPipeError/ConnectionAbortedError.
      ├── RuntimeError            # Raised by errors that don't fall into other categories.
      │    ├── NotImplementedEr…  # Can be raised by abstract methods or by unfinished code.
      │    └── RecursionError     # Raised when the maximum recursion depth is exceeded.
      ├── StopIteration           # Raised when an empty iterator is passed to next().
      ├── TypeError               # When an argument of the wrong type is passed to function.
      └── ValueError              # When argument has the right type but inappropriate value.

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 the wrong type!')
raise ValueError('Argument has the right type but an inappropriate value!')
raise RuntimeError('I am too lazy to define my own exception!')

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(<int>)                   # Exits with the passed exit code.
sys.exit(<obj>)                   # Prints to stderr and exits with 1.

#Print

print(<el_1>, ..., sep=' ', end='\n', file=sys.stdout, flush=False)

Pretty Print

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

#Input

<str> = input(prompt=None)

#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>)                             # Returns a parser.
p.add_argument('-<short_name>', '--<name>', action='store_true')  # Flag (defaults to False).
p.add_argument('-<short_name>', '--<name>', type=<type>)          # Option (defaults to None).
p.add_argument('<name>', type=<type>, nargs=1)                    # Mandatory first argument.
p.add_argument('<name>', type=<type>, nargs='+')                  # Mandatory remaining args.
p.add_argument('<name>', type=<type>, nargs='?/*')                # Optional argument/s.
args  = p.parse_args()                                            # Exits on parsing error.
<obj> = args.<name>                                               # Returns `<type>(<arg>)`.

#Open

Opens the file and returns a corresponding file object.

<file> = open(<path>, mode='r', encoding=None, newline=None)

Modes

• 'r' - Read. Used by default.
• 'w' - Write. Deletes existing contents.
• 'x' - Write or fail if the file already exists.
• 'a' - Append. Creates new file if it doesn't exist.
• 'w+' - Read and write. Deletes existing contents.
• 'r+' - Read and write from the start.
• 'a+' - Read and write from the end.
• 'b' - Binary mode ('rb', 'wb', 'xb', …)

<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, origin)    # Origin: 0 start, 1 current position, 2 end.

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

import os, glob
from pathlib import Path

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> = os.scandir(path='.')       # Returns DirEntry objects located at the path.
<str>  = <DirEntry>.path            # Returns the 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

<Path> = Path(<path> [, ...])       # Accepts strings, Paths, and DirEntry objects.
<Path> = <path> / <path> [/ ...]    # First or second path must be a Path object.
<Path> = <Path>.resolve()           # Returns absolute path with resolved symlinks.

#OS Commands

import os, shutil, subprocess

Shell Commands

<pipe> = os.popen('<command>')      # Executes command in sh/cmd. Returns its stdout pipe.
<str>  = <pipe>.read(size=-1)       # Reads 'size' chars or until EOF. Also readline/s().
<int>  = <pipe>.close()             # Closes the pipe. Returns None on success (returncode 0).

Sends '1 + 1' to the basic calculator and captures its output:

>>> subprocess.run('bc', input='1 + 1\n', capture_output=True, text=True)
CompletedProcess(args='bc', returncode=0, stdout='2\n', stderr='')

Sends test.in to the basic calculator running in standard mode and saves its output to test.out:

>>> from shlex import split
>>> os.popen('echo 1 + 1 > test.in')
>>> subprocess.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'

#JSON

Text file format for storing collections of strings and numbers.

import json
<str>    = json.dumps(<object>)     # Converts object to JSON string.
<object> = json.loads(<str>)        # Converts JSON string to object.

Read Object from JSON File

def read_json_file(filename):
    with open(filename, encoding='utf-8') as file:
        return json.load(file)

Write Object to JSON 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)

#Pickle

Binary file format for storing Python objects.

import pickle
<bytes>  = pickle.dumps(<object>)   # Converts object to bytes object.
<object> = pickle.loads(<bytes>)    # Converts bytes object to object.

Read Object from File

def read_pickle_file(filename):
    with open(filename, 'rb') as file:
        return pickle.load(file)

Write Object to File

def write_to_pickle_file(filename, an_object):
    with open(filename, 'wb') as file:
        pickle.dump(an_object, file)

#CSV

Text file format for storing spreadsheets.

import csv

Read

<reader> = csv.reader(<file>)       # Also: `dialect='excel', delimiter=','`.
<list>   = next(<reader>)           # Returns next row as a list of strings.
<list>   = list(<reader>)           # Returns a list of remaining rows.

Write

<writer> = csv.writer(<file>)       # Also: `dialect='excel', delimiter=','`.
<writer>.writerow(<collection>)     # Encodes objects using `str(<el>)`.
<writer>.writerows(<coll_of_coll>)  # Appends multiple rows.

Parameters

• 'dialect' - Master parameter that sets the default values. String or a 'csv.Dialect' object.
• 'delimiter' - A one-character string used to separate fields.
• 'lineterminator' - How writer terminates rows. Reader is hardcoded to '\n', '\r', '\r\n'.
• 'quotechar' - Character for quoting fields that contain special characters.
• 'escapechar' - Character for escaping quotechars.
• 'doublequote' - Whether quotechars inside fields are/get doubled or escaped.
• 'quoting' - 0: As necessary, 1: All, 2: All but numbers which are read as floats, 3: None.
• 'skipinitialspace' - Is space character at the start of the field stripped by the reader.

┏━━━━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━┓
┃                  │     excel    │   excel-tab  │     unix     ┃
┠──────────────────┼──────────────┼──────────────┼──────────────┨
┃ delimiter        │       ','    │      '\t'    │       ','    ┃
┃ lineterminator   │    '\r\n'    │    '\r\n'    │      '\n'    ┃
┃ quotechar        │       '"'    │       '"'    │       '"'    ┃
┃ escapechar       │      None    │      None    │      None    ┃
┃ doublequote      │      True    │      True    │      True    ┃
┃ quoting          │         0    │         0    │         1    ┃
┃ skipinitialspace │     False    │     False    │     False    ┃
┗━━━━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━┛

Read Rows from CSV File

def read_csv_file(filename, **csv_params):
    with open(filename, encoding='utf-8', newline='') as file:
        return list(csv.reader(file, **csv_params))

Write Rows to CSV File

def write_to_csv_file(filename, rows, mode='w', **csv_params):
    with open(filename, mode, encoding='utf-8', newline='') as file:
        writer = csv.writer(file, **csv_params)
        writer.writerows(rows)

#SQLite

A server-less database engine that stores each database into a separate file.

import sqlite3
<conn> = sqlite3.connect(<path>)                # Opens existing or new file. Also ':memory:'.
<conn>.close()                                  # Closes connection. Discards uncommitted data.

Read

<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>).

Write

<conn>.execute('<query>')                       # Can raise a subclass of sqlite3.Error.
<conn>.commit()                                 # Saves all changes since the last commit.
<conn>.rollback()                               # Discards all changes since the last commit.

Or:

with <conn>:                                    # Exits the block with commit() or rollback(),
    <conn>.execute('<query>')                   # depending on whether any exception occurred.

Placeholders

<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.

Example

Values are not actually saved in this example 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)]

SQLAlchemy

Library for interacting with various DB systems via SQL, method chaining, or ORM.

# $ pip3 install sqlalchemy
from sqlalchemy import create_engine, text
<engine> = create_engine('<url>')               # Url: 'dialect://user:password@host/dbname'.
<conn>   = <engine>.connect()                   # Creates a connection. Also <conn>.close().
<cursor> = <conn>.execute(text('<query>'), …)   # Replaces ':<key>'s with keyword arguments.
with <conn>.begin(): ...                        # Exits the block with commit or rollback.

#Bytes

A 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 an 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 as a separator.

Encode

<bytes> = bytes(<coll_of_ints>)          # Ints must be in range from 0 to 255.
<bytes> = bytes(<str>, 'utf-8')          # Encodes the string. Also <str>.encode().
<bytes> = bytes.fromhex('<hex>')         # Hex pairs can be separated by whitespaces.
<bytes> = <int>.to_bytes(n_bytes, …)     # `byteorder='big/little', signed=False`.

Decode

<list>  = list(<bytes>)                  # Returns ints in range from 0 to 255.
<str>   = str(<bytes>, 'utf-8')          # Returns a string. Also <bytes>.decode().
<str>   = <bytes>.hex()                  # Returns hex pairs. Accepts `sep=<str>`.
<int>   = int.from_bytes(<bytes>, …)     # `byteorder='big/little', signed=False`.

Read Bytes from File

def read_bytes(filename):
    with open(filename, 'rb') as file:
        return file.read()

Write Bytes to File

def write_bytes(filename, bytes_obj):
    with open(filename, 'wb') as file:
        file.write(bytes_obj)

#Struct

• Module that performs conversions between a sequence of numbers and a bytes object.
• System’s type sizes, byte order, and alignment rules are used by default.

from struct import pack, unpack

<bytes> = pack('<format>', <el_1> [, ...])  # Packs objects according to format string.
<tuple> = unpack('<format>', <bytes>)       # Use iter_unpack() to get iterator of tuples.

For standard type sizes and manual alignment (padding) start format string with:

• '=' - System's byte order (usually little-endian).
• '<' - Little-endian (i.e. least significant byte first).
• '>' - Big-endian (also '!').

#Array

List that can only hold numbers of a predefined type. Available types and their minimum sizes in bytes are listed above. Type sizes and byte order are always determined by the system, however bytes of each element can be reversed with byteswap() method.

from array import array

#Memory View

A sequence object that points to the memory of another bytes-like object. Each element can reference a single or multiple consecutive bytes, depending on format. Order and number of elements can be changed with slicing.

<mview> = memoryview(<bytes/bytearray/array>)  # Immutable if bytes is passed, else mutable.
<obj>   = <mview>[index]                       # Returns int or float. Bytes if format is 'c'.
<mview> = <mview>[<slice>]                     # Returns memoryview with rearranged elements.
<mview> = <mview>.cast('<typecode>')           # Only works between B/b/c and other types.
<mview>.release()                              # Releases memory buffer of the base object.

#Deque

A thread-safe list with efficient appends and pops from either side. Pronounced "deck".

from collections import deque

#Threading

CPython interpreter can only run a single thread at a time. Using multiple threads won't result in a faster execution, unless at least one of the threads contains an I/O operation.

from threading import Thread, Lock, RLock, Semaphore, Event, Barrier
from concurrent.futures import ThreadPoolExecutor, as_completed

Thread

<Thread> = Thread(target=<function>)           # Use `args=<collection>` to set the arguments.
<Thread>.start()                               # Starts the thread. Also <Thread>.is_alive().
<Thread>.join()                                # Waits for the thread to finish.

Lock

<lock> = Lock/RLock()                          # RLock can only be released by acquirer.
<lock>.acquire()                               # Waits for the lock to be available.
<lock>.release()                               # Makes the lock available again.

Or:

with <lock>:                                   # Enters the block by calling acquire() and
    ...                                        # exits it with release(), even on error.

Semaphore, Event, Barrier

<Semaphore> = Semaphore(value=1)               # Lock that can be acquired by 'value' threads.
<Event>     = Event()                          # Method wait() blocks until set() is called.
<Barrier>   = Barrier(n_times)                 # Wait() blocks until it's called n_times.

Queue

<Queue> = queue.Queue(maxsize=0)               # A thread-safe first-in-first-out queue.
<Queue>.put(<el>)                              # Blocks until queue stops being full.
<Queue>.put_nowait(<el>)                       # Raises queue.Full exception if full.
<el> = <Queue>.get()                           # Blocks until queue stops being empty.
<el> = <Queue>.get_nowait()                    # Raises queue.Empty exception if empty.

Thread Pool Executor

<Exec> = ThreadPoolExecutor(max_workers=None)  # Or: `with ThreadPoolExecutor() as <name>: ...`
<iter> = <Exec>.map(<func>, <args_1>, ...)     # Multithreaded and non-lazy map(). Keeps order.
<Futr> = <Exec>.submit(<func>, <arg_1>, ...)   # Creates a thread and returns its Future obj.
<Exec>.shutdown()                              # Blocks until all threads finish executing.

#Operator

Module of functions that provide the functionality of operators. Functions are ordered by operator precedence, starting with least binding.

import operator as op

#Match Statement

Executes the first block with matching pattern. Added in Python 3.10.

match <object/expression>:
    case <pattern> [if <condition>]:
        <code>
    ...

Patterns

<value_pattern> = 1/'abc'/True/None/math.pi        # Matches the literal or a dotted name.
<class_pattern> = <type>()                         # Matches any object of that type (or ABC).
<wildcard_patt> = _                                # Matches any object. Useful in last case.
<capture_patt>  = <name>                           # Matches any object and binds it to name.
<as_pattern>    = <pattern> as <name>              # Binds match to name. Also <type>(<name>).
<or_pattern>    = <pattern> | <pattern> [| ...]    # Matches any of the patterns.
<sequence_patt> = [<pattern>, ...]                 # Matches sequence with matching items.
<mapping_patt>  = {<value_pattern>: <patt>, ...}   # Matches dictionary with matching items.
<class_pattern> = <type>(<attr_name>=<patt>, ...)  # Matches object with matching attributes.

Example

>>> from pathlib import Path
>>> match Path('/home/gto/python-cheatsheet/README.md'):
...     case Path(
...         parts=['/', 'home', user, *_]
...     ) as p if p.name.lower().startswith('readme') and p.is_file():
...         print(f'{p.name} is a readme file that belongs to user {user}.')
'README.md is a readme file that belongs to user gto.'

#Logging

import logging as log

Setup

log.basicConfig(
    filename=None,                                # Logs to stderr or appends to file.
    format='%(levelname)s:%(name)s:%(message)s',  # Add '%(asctime)s' for local datetime.
    level=log.WARNING,                            # Drops messages with lower priority.
    handlers=[log.StreamHandler(sys.stderr)]      # Uses FileHandler if filename is set.
)

Creates a logger that writes all messages to a file and sends them to the root's handler that prints warnings or higher:

>>> logger = log.getLogger('my_module')
>>> handler = log.FileHandler('test.log', encoding='utf-8')
>>> handler.setFormatter(log.Formatter('%(asctime)s %(levelname)s:%(name)s:%(message)s'))
>>> logger.addHandler(handler)
>>> logger.setLevel('DEBUG')
>>> log.basicConfig()
>>> log.root.handlers[0].setLevel('WARNING')
>>> logger.critical('Running out of disk space.')
CRITICAL:my_module:Running out of disk space.
>>> print(open('test.log').read())
2023-02-07 23:21:01,430 CRITICAL:my_module:Running out of disk space.

#Introspection

<list> = dir()                      # List of of local names (including functions and classes).
<dict> = vars()                     # Dict of local names and their objects. Also locals().
<dict> = globals()                  # Dict of global names (for instance '__builtin__' module).

#Coroutines

• Coroutines have a lot in common with threads, but unlike threads, they only give up control when they call another coroutine and they don’t use as much memory.
• Coroutine definition starts with 'async' and its call with 'await'.
• Use 'asyncio.run(<coroutine>)' to start the first/main coroutine.

import asyncio as aio

Runs a terminal game where you control an asterisk that must avoid numbers:

import asyncio, collections, curses, curses.textpad, enum, random

P = collections.namedtuple('P', 'x y')    # Position
D = enum.Enum('D', 'n e s w')             # Direction
W, H = 15, 7                              # Width, Height

def main(screen):
    curses.curs_set(0)                    # Makes cursor invisible.
    screen.nodelay(True)                  # Makes getch() non-blocking.
    asyncio.run(main_coroutine(screen))   # Starts running asyncio code.

async def main_coroutine(screen):
    moves = asyncio.Queue()
    state = {'*': P(0, 0)} | {id_: P(W//2, H//2) for id_ in range(10)}
    ai    = [random_controller(id_, moves) for id_ in range(10)]
    mvc   = [human_controller(screen, moves), model(moves, state), view(state, screen)]
    tasks = [asyncio.create_task(coro) for coro in ai + mvc]
    await asyncio.wait(tasks, return_when=asyncio.FIRST_COMPLETED)

async def random_controller(id_, moves):
    while True:
        d = random.choice(list(D))
        moves.put_nowait((id_, d))
        await asyncio.sleep(random.triangular(0.01, 0.65))

async def human_controller(screen, moves):
    while True:
        key_mappings = {258: D.s, 259: D.n, 260: D.w, 261: D.e}
        if d := key_mappings.get(screen.getch()):
            moves.put_nowait(('*', d))
        await asyncio.sleep(0.005)

async def model(moves, state):
    while state['*'] not in (state[id_] for id_ in range(10)):
        id_, d = await moves.get()
        deltas = {D.n: P(0, -1), D.e: P(1, 0), D.s: P(0, 1), D.w: P(-1, 0)}
        state[id_] = P((state[id_].x + deltas[d].x) % W, (state[id_].y + deltas[d].y) % H)

async def view(state, screen):
    offset = P(curses.COLS//2 - W//2, curses.LINES//2 - H//2)
    while True:
        screen.erase()
        curses.textpad.rectangle(screen, offset.y-1, offset.x-1, offset.y+H, offset.x+W)
        for id_, p in state.items():
            screen.addstr(offset.y + (p.y - state['*'].y + H//2) % H,
                          offset.x + (p.x - state['*'].x + W//2) % W, str(id_))
        screen.refresh()
        await asyncio.sleep(0.005)

if __name__ == '__main__':
    curses.wrapper(main)

Libraries

# $ pip3 install tqdm
>>> import tqdm, time
>>> for el in tqdm.tqdm([1, 2, 3], desc='Processing'):
...     time.sleep(1)
Processing: 100%|████████████████████| 3/3 [00:03<00:00,  1.00s/it]

#Plot

# $ pip3 install matplotlib
import matplotlib.pyplot as plt

plt.plot/bar/scatter(x_data, y_data [, label=<str>])  # Also plt.plot(y_data).
plt.legend()                                          # Adds a legend.
plt.title/xlabel/ylabel(<str>)                        # Adds a title or label.
plt.savefig(<path>)                                   # Saves the figure.
plt.show()                                            # Displays the figure.
plt.clf()                                             # Clears the figure.

#Table

# $ pip3 install tabulate
import csv, tabulate
with open('test.csv', encoding='utf-8', newline='') as file:
    rows = list(csv.reader(file))
print(tabulate.tabulate(rows, headers='firstrow'))

#Console App

# $ pip3 install windows-curses
import curses, os
from curses import A_REVERSE, KEY_DOWN, KEY_UP, KEY_LEFT, KEY_RIGHT, KEY_ENTER

def main(screen):
    ch, first, selected, paths = 0, 0, 0, os.listdir()
    while ch != ord('q'):
        height, width = screen.getmaxyx()
        screen.erase()
        for y, filename in enumerate(paths[first : first+height]):
            color = A_REVERSE if filename == paths[selected] else 0
            screen.addnstr(y, 0, filename, width-1, color)
        ch = screen.getch()
        selected += (ch == KEY_DOWN) - (ch == KEY_UP)
        selected = max(0, min(len(paths)-1, selected))
        first += (selected >= first + height) - (selected < first)
        if ch in [KEY_LEFT, KEY_RIGHT, KEY_ENTER, ord('\n'), ord('\r')]:
            new_dir = '..' if ch == KEY_LEFT else paths[selected]
            if os.path.isdir(new_dir):
                os.chdir(new_dir)
                first, selected, paths = 0, 0, os.listdir()

if __name__ == '__main__':
    curses.wrapper(main)

#GUI App

# $ pip3 install PySimpleGUI
import PySimpleGUI as sg

text_box = sg.Input(default_text='100', enable_events=True, key='-QUANTITY-')
dropdown = sg.InputCombo(['g', 'kg', 't'], 'kg', readonly=True, enable_events=True, k='-UNIT-')
label    = sg.Text('100 kg is 220.462 lbs.', key='-OUTPUT-')
button   = sg.Button('Close')
window   = sg.Window('Weight Converter', [[text_box, dropdown], [label], [button]])

while True:
    event, values = window.read()
    if event in [sg.WIN_CLOSED, 'Close']:
        break
    try:
        quantity = float(values['-QUANTITY-'])
    except ValueError:
        continue
    unit = values['-UNIT-']
    factors = {'g': 0.001, 'kg': 1, 't': 1000}
    lbs = quantity * factors[unit] / 0.45359237
    window['-OUTPUT-'].update(value=f'{quantity} {unit} is {lbs:g} lbs.')
window.close()

#Scraping

# $ pip3 install requests beautifulsoup4
import requests, bs4, os

response   = requests.get('https://en.wikipedia.org/wiki/Python_(programming_language)')
document   = bs4.BeautifulSoup(response.text, 'html.parser')
table      = document.find('table', class_='infobox vevent')
python_url = table.find('th', text='Website').next_sibling.a['href']
logo_url   = table.find('img')['src']
logo       = requests.get(f'https:{logo_url}').content
filename   = os.path.basename(logo_url)
with open(filename, 'wb') as file:
    file.write(logo)
print(f'{python_url}, file://{os.path.abspath(filename)}')

Selenium

Library for scraping websites with dynamic content.

# $ pip3 install selenium
from selenium import webdriver

<WebDrv> = webdriver.Chrome/Firefox/Safari/Edge()     # Opens a browser. Also <WebDrv>.quit().
<WebDrv>.get('<url>')                                 # Also <WebDrv>.implicitly_wait(seconds).
<El>   = <WebDrv/El>.find_element('css selector', …)  # '<tag>#<id>.<class>[<attr>="<val>"]…'.
<list> = <WebDrv/El>.find_elements('xpath', …)        # '//<tag>[@<attr>="<val>"]…'. See XPath.
<str>  = <El>.get_attribute(<str>)                    # Property if exists. Also <El>.text.
<El>.click/clear()                                    # Also <El>.send_keys(<str>).

XPath — also available in lxml, Scrapy, and browser's console via '$x("<xpath>")':

<xpath>     = //<element>[/ or // <element>]          # /<child>, //<descendant>, /../<sibling>
<xpath>     = //<element>/following::<element>        # Next element. Also preceding/parent/…
<element>   = <tag><conditions><index>                # `<tag> = */a/…`, `<index> = [1/2/…]`.
<condition> = [<sub_cond> [and/or <sub_cond>]]        # For negation use `not(<sub_cond>)`.
<sub_cond>  = @<attr>[="<val>"]                       # `text()=`, `.=` match (complete) text.
<sub_cond>  = contains(@<attr>, "<val>")              # Is <val> a substring of attr's value?
<sub_cond>  = [//]<element>                           # Has matching child? Descendant if //.

#Web App

Flask is a micro web framework/server. If you just want to open a html file in a web browser use 'webbrowser.open(<path>)' instead.

# $ pip3 install flask
import flask as fl

Static Request

@app.route('/img/<path:filename>')
def serve_file(filename):
    return fl.send_from_directory('dirname/', filename)

Dynamic Request

@app.route('/<sport>')
def serve_html(sport):
    return fl.render_template_string('<h1>{{title}}</h1>', title=sport)

REST Request

@app.post('/<sport>/odds')
def serve_json(sport):
    team = fl.request.form['team']
    return {'team': team, 'odds': [2.09, 3.74, 3.68]}

Starts the app in its own thread and queries its REST API:

# $ pip3 install requests
>>> import threading, requests
>>> threading.Thread(target=app.run, daemon=True).start()
>>> url = 'http://localhost:5000/football/odds'
>>> response = requests.post(url, data={'team': 'arsenal f.c.'})
>>> response.json()
{'team': 'arsenal f.c.', 'odds': [2.09, 3.74, 3.68]}

#Profiling

from time import perf_counter
start_time = perf_counter()
...
duration_in_seconds = perf_counter() - start_time

Timing a Snippet

>>> from timeit import timeit
>>> timeit('list(range(10000))', number=1000, globals=globals(), setup='pass')
0.19373

Profiling by Line

$ pip3 install line_profiler
$ echo '@profile
def main():
    a = list(range(10000))
    b = set(range(10000))
main()' > test.py
$ kernprof -lv test.py
Line #      Hits         Time  Per Hit   % Time  Line Contents
==============================================================
     1                                           @profile
     2                                           def main():
     3         1        253.4    253.4     32.2      a = list(range(10000))
     4         1        534.1    534.1     67.8      b = set(range(10000))

Call and Flame Graphs

$ apt/brew install graphviz && pip3 install gprof2dot snakeviz  # Or download installer.
$ tail --lines=+2 test.py > test.py                             # Removes first line.
$ python3 -m cProfile -o test.prof test.py                      # Runs built-in profiler.
$ gprof2dot --format=pstats test.prof | dot -T png -o test.png  # Generates call graph.
$ xdg-open/open test.png                                        # Displays call graph.
$ snakeviz test.prof                                            # Displays flame graph.

Sampling and Memory Profilers

┏━━━━━━━━━━━━━━┯━━━━━━━━━━━━┯━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┯━━━━━━━┯━━━━━━┓
┃ pip3 install │   Target   │          How to run           │ Lines │ Live ┃
┠──────────────┼────────────┼───────────────────────────────┼───────┼──────┨
┃ pyinstrument │    CPU     │ pyinstrument test.py          │   ×   │  ×   ┃
┃ py-spy       │    CPU     │ py-spy top -- python3 test.py │   ×   │  ✓   ┃
┃ scalene      │ CPU+Memory │ scalene test.py               │   ✓   │  ×   ┃
┃ memray       │   Memory   │ memray run --live test.py     │   ✓   │  ✓   ┃
┗━━━━━━━━━━━━━━┷━━━━━━━━━━━━┷━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┷━━━━━━━┷━━━━━━┛

#NumPy

Array manipulation mini-language. It can run up to one hundred times faster than the equivalent Python code. An even faster alternative that runs on a GPU is called CuPy.

# $ pip3 install numpy
import numpy as np

Indexing

<el>       = <2d>[row_index, col_index]                 # Or: <3d>[<int>, <int>, <int>]
<1d_view>  = <2d>[row_index]                            # Or: <3d>[<int>, <int>, <slice>]
<1d_view>  = <2d>[:, col_index]                         # Or: <3d>[<int>, <slice>, <int>]
<2d_view>  = <2d>[from:to_row_i, from:to_col_i]         # Or: <3d>[<int>, <slice>, <slice>]

Broadcasting

A set of rules by which NumPy functions operate on arrays of different shapes.

left  = [ 0.1 ,  0.6 ,  0.8 ]                           # Shape: (3,)
right = [[0.1], [0.6], [0.8]]                           # Shape: (3, 1)

1. If array shapes differ in length, left-pad the shorter shape with ones:

left  = [[0.1 ,  0.6 ,  0.8]]                           # Shape: (1, 3) <- !
right = [[0.1], [0.6], [0.8]]                           # Shape: (3, 1)

2. If any dimensions differ in size, expand the ones that have size 1 by duplicating their elements:

left  = [[0.1,  0.6,  0.8],                             # Shape: (3, 3) <- !
         [0.1,  0.6,  0.8],
         [0.1,  0.6,  0.8]]

right = [[0.1,  0.1,  0.1],                             # Shape: (3, 3) <- !
         [0.6,  0.6,  0.6],
         [0.8,  0.8,  0.8]]

Example

>>> points = np.array([0.1, 0.6, 0.8])
[ 0.1,  0.6,  0.8 ]
>>> wrapped_points = points.reshape(3, 1)
[[0.1], [0.6], [0.8]]
>>> distances = points - wrapped_points
[[ 0. ,  0.5,  0.7],
 [-0.5,  0. ,  0.2],
 [-0.7, -0.2,  0. ]]
>>> distances = np.abs(distances)
[[ 0. ,  0.5,  0.7],
 [ 0.5,  0. ,  0.2],
 [ 0.7,  0.2,  0. ]]
>>> distances[range(3), range(3)] = np.inf
[[ inf,  0.5,  0.7],
 [ 0.5,  inf,  0.2],
 [ 0.7,  0.2,  inf]]
>>> distances.argmin(1)
[1, 2, 1]

#Image

# $ pip3 install pillow
from PIL import Image

Modes

• 'L' - Lightness (greyscale image). Each pixel is an int between 0 and 255.
• 'RGB' - Red, green, blue (true color image). Each pixel is a tuple of three ints.
• 'RGBA' - RGB with alpha. Low alpha (i.e. forth int) makes pixels more transparent.
• 'HSV' - Hue, saturation, value. Three ints representing color in HSV color space.

WIDTH, HEIGHT = 100, 100
n_pixels = WIDTH * HEIGHT
hues = (255 * i/n_pixels for i in range(n_pixels))
img = Image.new('HSV', (WIDTH, HEIGHT))
img.putdata([(int(h), 255, 255) for h in hues])
img.convert('RGB').save('test.png')

Adds noise to the PNG image and displays it:

from random import randint
add_noise = lambda value: max(0, min(255, value + randint(-20, 20)))
img = Image.open('test.png').convert('HSV')
img.putdata([(add_noise(h), s, v) for h, s, v in img.getdata()])
img.show()

Image Draw

from PIL import ImageDraw
<Draw> = ImageDraw.Draw(<Image>)                # Object for adding 2D graphics to the image.
<Draw>.point((x, y))                            # Draws a point. Truncates floats into ints.
<Draw>.line((x1, y1, x2, y2 [, ...]))           # To get anti-aliasing use Image's resize().
<Draw>.arc((x1, y1, x2, y2), deg1, deg2)        # Draws in clockwise dir. Also pieslice().
<Draw>.rectangle((x1, y1, x2, y2))              # To rotate use Image's rotate() and paste().
<Draw>.polygon((x1, y1, x2, y2, ...))           # Last point gets connected to the first.
<Draw>.ellipse((x1, y1, x2, y2))                # Also rounded_rectangle(), regular_polygon().
<Draw>.text((x, y), <str>, font=<Font>)         # `<Font> = ImageFont.truetype(<path>, size)`

#Animation

# $ pip3 install imageio
from PIL import Image, ImageDraw
import imageio

WIDTH, HEIGHT, R = 126, 126, 10
frames = []
for velocity in range(1, 16):
    y = sum(range(velocity))
    frame = Image.new('L', (WIDTH, HEIGHT))
    draw = ImageDraw.Draw(frame)
    draw.ellipse((WIDTH/2-R, y, WIDTH/2+R, y+R*2), fill='white')
    frames.append(frame)
frames += reversed(frames[1:-1])
imageio.mimsave('test.gif', frames, duration=0.03)

#Audio

import wave

Sample Values

┏━━━━━━━━━━━┯━━━━━━━━━━━┯━━━━━━┯━━━━━━━━━━━┓
┃ sampwidth │    min    │ zero │    max    ┃
┠───────────┼───────────┼──────┼───────────┨
┃     1     │         0 │  128 │       255 ┃
┃     2     │    -32768 │    0 │     32767 ┃
┃     3     │  -8388608 │    0 │   8388607 ┃
┗━━━━━━━━━━━┷━━━━━━━━━━━┷━━━━━━┷━━━━━━━━━━━┛

Read Float Samples from WAV File

def read_wav_file(filename):
    def get_int(bytes_obj):
        an_int = int.from_bytes(bytes_obj, 'little', signed=(p.sampwidth != 1))
        return an_int - 128 * (p.sampwidth == 1)
    with wave.open(filename) as file:
        p = file.getparams()
        frames = file.readframes(-1)
    bytes_samples = (frames[i : i + p.sampwidth] for i in range(0, len(frames), p.sampwidth))
    return [get_int(b) / pow(2, p.sampwidth * 8 - 1) for b in bytes_samples], p

Write Float Samples to WAV File

def write_to_wav_file(filename, samples_f, p=None, nchannels=1, sampwidth=2, framerate=44100):
    def get_bytes(a_float):
        a_float = max(-1, min(1 - 2e-16, a_float))
        a_float += p.sampwidth == 1
        a_float *= pow(2, p.sampwidth * 8 - 1)
        return int(a_float).to_bytes(p.sampwidth, 'little', signed=(p.sampwidth != 1))
    if p is None:
        p = wave._wave_params(nchannels, sampwidth, framerate, 0, 'NONE', 'not compressed')
    with wave.open(filename, 'wb') as file:
        file.setparams(p)
        file.writeframes(b''.join(get_bytes(f) for f in samples_f))

Examples

from math import pi, sin
samples_f = (sin(i * 2 * pi * 440 / 44100) for i in range(100_000))
write_to_wav_file('test.wav', samples_f)

Adds noise to the WAV file:

from random import uniform
samples_f, params = read_wav_file('test.wav')
samples_f = (f + uniform(-0.05, 0.05) for f in samples_f)
write_to_wav_file('test.wav', samples_f, params)

Plays the WAV file:

# $ pip3 install simpleaudio
from simpleaudio import play_buffer
with wave.open('test.wav') as file:
    p = file.getparams()
    frames = file.readframes(-1)
    play_buffer(frames, p.nchannels, p.sampwidth, p.framerate).wait_done()

Text to Speech

# $ pip3 install pyttsx3
import pyttsx3
engine = pyttsx3.init()
engine.say('Sally sells seashells by the seashore.')
engine.runAndWait()

#Synthesizer

# $ pip3 install simpleaudio
import array, itertools as it, math, simpleaudio

F  = 44100
P1 = '71♩,69♪,,71♩,66♪,,62♩,66♪,,59♩,,,71♩,69♪,,71♩,66♪,,62♩,66♪,,59♩,,,'
P2 = '71♩,73♪,,74♩,73♪,,74♪,,71♪,,73♩,71♪,,73♪,,69♪,,71♩,69♪,,71♪,,67♪,,71♩,,,'
get_pause   = lambda seconds: it.repeat(0, int(seconds * F))
sin_f       = lambda i, hz: math.sin(i * 2 * math.pi * hz / F)
get_wave    = lambda hz, seconds: (sin_f(i, hz) for i in range(int(seconds * F)))
get_hz      = lambda note: 440 * 2 ** ((int(note[:2]) - 69) / 12)
get_sec     = lambda note: 1/4 if '♩' in note else 1/8
get_samples = lambda note: get_wave(get_hz(note), get_sec(note)) if note else get_pause(1/8)
samples_f   = it.chain.from_iterable(get_samples(n) for n in (P1+P2).split(','))
samples_i   = array.array('h', (int(f * 30000) for f in samples_f))
simpleaudio.play_buffer(samples_i, 1, 2, F).wait_done()

#Pygame

# $ pip3 install pygame
import pygame as pg

pg.init()
screen = pg.display.set_mode((500, 500))
rect = pg.Rect(240, 240, 20, 20)
while not pg.event.get(pg.QUIT):
    deltas = {pg.K_UP: (0, -20), pg.K_RIGHT: (20, 0), pg.K_DOWN: (0, 20), pg.K_LEFT: (-20, 0)}
    for event in pg.event.get(pg.KEYDOWN):
        dx, dy = deltas.get(event.key, (0, 0))
        rect = rect.move((dx, dy))
    screen.fill(pg.Color('black'))
    pg.draw.rect(screen, pg.Color('white'), rect)
    pg.display.flip()

Rectangle

Object for storing rectangular coordinates.

<Rect> = pg.Rect(x, y, width, height)           # Floats get truncated into ints.
<int>  = <Rect>.x/y/centerx/centery/…           # Top, right, bottom, left. Allows assignments.
<tup.> = <Rect>.topleft/center/…                # Topright, bottomright, bottomleft. Same.
<Rect> = <Rect>.move((delta_x, delta_y))        # Use move_ip() to move in-place.

Surface

Object for representing images.

<Surf> = pg.display.set_mode((width, height))   # Opens new window and returns its surface.
<Surf> = pg.Surface((width, height))            # New RGB surface. RGBA if `flags=pg.SRCALPHA`.
<Surf> = pg.image.load(<path/file>)             # Loads the image. Format depends on source.
<Surf> = pg.surfarray.make_surface(<np_array>)  # Also `<np_arr> = surfarray.pixels3d(<Surf>)`.
<Surf> = <Surf>.subsurface(<Rect>)              # Creates a new surface from the cutout.

Font

<Font> = pg.font.Font(<path/file>, size)        # Loads TTF file. Pass None for default font.
<Surf> = <Font>.render(text, antialias, color)  # Background color can be specified at the end.

Sound

<Sound> = pg.mixer.Sound(<path/file/bytes>)     # WAV file or bytes/array of signed shorts.
<Sound>.play/stop()                             # Also set_volume(<float>), fadeout(msec).

Basic Mario Brothers Example

import collections, dataclasses, enum, io, itertools as it, pygame as pg, urllib.request
from random import randint

P = collections.namedtuple('P', 'x y')          # Position
D = enum.Enum('D', 'n e s w')                   # Direction
W, H, MAX_S = 50, 50, P(5, 10)                  # Width, Height, Max speed

def main():
    def get_screen():
        pg.init()
        return pg.display.set_mode((W*16, H*16))
    def get_images():
        url = 'https://gto76.github.io/python-cheatsheet/web/mario_bros.png'
        img = pg.image.load(io.BytesIO(urllib.request.urlopen(url).read()))
        return [img.subsurface(get_rect(x, 0)) for x in range(img.get_width() // 16)]
    def get_mario():
        Mario = dataclasses.make_dataclass('Mario', 'rect spd facing_left frame_cycle'.split())
        return Mario(get_rect(1, 1), P(0, 0), False, it.cycle(range(3)))
    def get_tiles():
        border = [(x, y) for x in range(W) for y in range(H) if x in [0, W-1] or y in [0, H-1]]
        platforms = [(randint(1, W-2), randint(2, H-2)) for _ in range(W*H // 10)]
        return [get_rect(x, y) for x, y in border + platforms]
    def get_rect(x, y):
        return pg.Rect(x*16, y*16, 16, 16)
    run(get_screen(), get_images(), get_mario(), get_tiles())

def run(screen, images, mario, tiles):
    clock = pg.time.Clock()
    pressed = set()
    while not pg.event.get(pg.QUIT) and clock.tick(28):
        keys = {pg.K_UP: D.n, pg.K_RIGHT: D.e, pg.K_DOWN: D.s, pg.K_LEFT: D.w}
        pressed |= {keys.get(e.key) for e in pg.event.get(pg.KEYDOWN)}
        pressed -= {keys.get(e.key) for e in pg.event.get(pg.KEYUP)}
        update_speed(mario, tiles, pressed)
        update_position(mario, tiles)
        draw(screen, images, mario, tiles)

def update_speed(mario, tiles, pressed):
    x, y = mario.spd
    x += 2 * ((D.e in pressed) - (D.w in pressed))
    x += (x < 0) - (x > 0)
    y += 1 if D.s not in get_boundaries(mario.rect, tiles) else (D.n in pressed) * -10
    mario.spd = P(x=max(-MAX_S.x, min(MAX_S.x, x)), y=max(-MAX_S.y, min(MAX_S.y, y)))

def update_position(mario, tiles):
    x, y = mario.rect.topleft
    n_steps = max(abs(s) for s in mario.spd)
    for _ in range(n_steps):
        mario.spd = stop_on_collision(mario.spd, get_boundaries(mario.rect, tiles))
        x, y = x + (mario.spd.x / n_steps), y + (mario.spd.y / n_steps)
        mario.rect.topleft = x, y

def get_boundaries(rect, tiles):
    deltas = {D.n: P(0, -1), D.e: P(1, 0), D.s: P(0, 1), D.w: P(-1, 0)}
    return {d for d, delta in deltas.items() if rect.move(delta).collidelist(tiles) != -1}

def stop_on_collision(spd, bounds):
    return P(x=0 if (D.w in bounds and spd.x < 0) or (D.e in bounds and spd.x > 0) else spd.x,
             y=0 if (D.n in bounds and spd.y < 0) or (D.s in bounds and spd.y > 0) else spd.y)

def draw(screen, images, mario, tiles):
    screen.fill((85, 168, 255))
    mario.facing_left = mario.spd.x < 0 if mario.spd.x else mario.facing_left
    is_airborne = D.s not in get_boundaries(mario.rect, tiles)
    image_index = 4 if is_airborne else (next(mario.frame_cycle) if mario.spd.x else 6)
    screen.blit(images[image_index + (mario.facing_left * 9)], mario.rect)
    for t in tiles:
        is_border = t.x in [0, (W-1)*16] or t.y in [0, (H-1)*16]
        screen.blit(images[18 if is_border else 19], t)
    pg.display.flip()

if __name__ == '__main__':
    main()

#Pandas

# $ pip3 install pandas matplotlib
import pandas as pd, matplotlib.pyplot as plt

Series

Ordered dictionary with a name.

>>> sr = pd.Series([1, 2], index=['x', 'y'], name='a'); sr
x    1
y    2
Name: a, dtype: int64

Series — Aggregate, Transform, Map:

<el> = <Sr>.sum/max/mean/idxmax/all()          # Or: <Sr>.agg(lambda <Sr>: <el>)
<Sr> = <Sr>.rank/diff/cumsum/ffill/interpo…()  # Or: <Sr>.agg/transform(lambda <Sr>: <Sr>)
<Sr> = <Sr>.fillna(<el>)                       # Or: <Sr>.agg/transform/map(lambda <el>: <el>)

DataFrame

Table with labeled rows and columns.

>>> l = pd.DataFrame([[1, 2], [3, 4]], index=['a', 'b'], columns=['x', 'y']); l
   x  y
a  1  2
b  3  4

DataFrame — Merge, Join, Concat:

>>> r = pd.DataFrame([[4, 5], [6, 7]], index=['b', 'c'], columns=['y', 'z']); r
   y  z
b  4  5
c  6  7

DataFrame — Aggregate, Transform, Map:

<Sr> = <DF>.sum/max/mean/idxmax/all()          # Or: <DF>.apply/agg(lambda <Sr>: <el>)
<DF> = <DF>.rank/diff/cumsum/ffill/interpo…()  # Or: <DF>.apply/agg/transfo…(lambda <Sr>: <Sr>)
<DF> = <DF>.fillna(<el>)                       # Or: <DF>.applymap(lambda <el>: <el>)

DataFrame — Encode, Decode:

<DF> = pd.read_json/html('<str/path/url>')     # Run `$ pip3 install beautifulsoup4 lxml`.
<DF> = pd.read_csv('<path/url>')               # `header/index_col/dtype/usecols/…=<obj>`.
<DF> = pd.read_pickle/excel('<path/url>')      # Use `sheet_name=None` to get all Excel sheets.
<DF> = pd.read_sql('<table/query>', <conn.>)   # SQLite3/SQLAlchemy connection (see #SQLite).

GroupBy

Object that groups together rows of a dataframe based on the value of the passed column.

>>> df = pd.DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 6]], list('abc'), list('xyz'))
>>> gb = df.groupby('z'); gb.apply(print)
   x  y  z
a  1  2  3
   x  y  z
b  4  5  6
c  7  8  6

GroupBy — Aggregate, Transform, Map:

<DF> = <GB>.sum/max/mean/idxmax/all()          # Or: <GB>.agg(lambda <Sr>: <el>)
<DF> = <GB>.rank/diff/cumsum/ffill()           # Or: <GB>.transform(lambda <Sr>: <Sr>)
<DF> = <GB>.fillna(<el>)                       # Or: <GB>.transform(lambda <Sr>: <Sr>)

Rolling

Object for rolling window calculations.

<RSr/RDF/RGB> = <Sr/DF/GB>.rolling(win_size)   # Also: `min_periods=None, center=False`.
<RSr/RDF/RGB> = <RDF/RGB>[col_key/s]           # Or: <RDF/RGB>.col_key
<Sr/DF>       = <R>.mean/sum/max()             # Or: <R>.apply/agg(<agg_func/str>)

#Plotly

# $ pip3 install plotly kaleido pandas
import plotly.express as px, pandas as pd

Displays a line chart of total coronavirus deaths per million grouped by continent:

covid = pd.read_csv('https://raw.githubusercontent.com/owid/covid-19-data/8dde8ca49b'
                    '6e648c17dd420b2726ca0779402651/public/data/owid-covid-data.csv',
                    usecols=['iso_code', 'date', 'total_deaths', 'population'])
continents = pd.read_csv('https://gto76.github.io/python-cheatsheet/web/continents.csv',
                         usecols=['Three_Letter_Country_Code', 'Continent_Name'])
df = pd.merge(covid, continents, left_on='iso_code', right_on='Three_Letter_Country_Code')
df = df.groupby(['Continent_Name', 'date']).sum().reset_index()
df['Total Deaths per Million'] = df.total_deaths * 1e6 / df.population
df = df[df.date > '2020-03-14']
df = df.rename({'date': 'Date', 'Continent_Name': 'Continent'}, axis='columns')
px.line(df, x='Date', y='Total Deaths per Million', color='Continent').show()

Displays a multi-axis line chart of total coronavirus cases and changes in prices of Bitcoin, Dow Jones and gold:

import pandas as pd, plotly.graph_objects as go

def main():
    covid, bitcoin, gold, dow = scrape_data()
    df = wrangle_data(covid, bitcoin, gold, dow)
    display_data(df)

def scrape_data():
    def get_covid_cases():
        url = 'https://covid.ourworldindata.org/data/owid-covid-data.csv'
        df = pd.read_csv(url, usecols=['location', 'date', 'total_cases'])
        df = df[df.location == 'World']
        return df.set_index('date').total_cases
    def get_ticker(symbol):
        url = (f'https://query1.finance.yahoo.com/v7/finance/download/{symbol}?'
               'period1=1579651200&period2=9999999999&interval=1d&events=history')
        df = pd.read_csv(url, usecols=['Date', 'Close'])
        return df.set_index('Date').Close
    out = get_covid_cases(), get_ticker('BTC-USD'), get_ticker('GC=F'), get_ticker('^DJI')
    names = ['Total Cases', 'Bitcoin', 'Gold', 'Dow Jones']
    return map(pd.Series.rename, out, names)

def wrangle_data(covid, bitcoin, gold, dow):
    df = pd.concat([bitcoin, gold, dow], axis=1)  # Creates table by joining columns on dates.
    df = df.sort_index().interpolate()            # Sorts table by date and interpolates NaN-s.
    df = df.loc['2020-02-23':]                    # Discards rows before '2020-02-23'.
    df = (df / df.iloc[0]) * 100                  # Calculates percentages relative to day 1.
    df = df.join(covid)                           # Adds column with covid cases.
    return df.sort_values(df.index[-1], axis=1)   # Sorts columns by last day's value.

def display_data(df):
    figure = go.Figure()
    for col_name in reversed(df.columns):
        yaxis = 'y1' if col_name == 'Total Cases' else 'y2'
        trace = go.Scatter(x=df.index, y=df[col_name], name=col_name, yaxis=yaxis)
        figure.add_trace(trace)
    figure.update_layout(
        yaxis1=dict(title='Total Cases', rangemode='tozero'),
        yaxis2=dict(title='%', rangemode='tozero', overlaying='y', side='right'),
        legend=dict(x=1.08),
        width=944,
        height=423
    )
    figure.show()

if __name__ == '__main__':
    main()

#Appendix

# $ pip3 install cython
import pyximport; pyximport.install()
import <cython_script>
<cython_script>.main()

Definitions:

• All 'cdef' definitions are optional, but they contribute to the speed-up.
• Script needs to be saved with a 'pyx' extension.

cdef <ctype> <var_name> = <obj>
cdef <ctype>[n_elements] <var_name> = [<el_1>, <el_2>, ...]
cdef <ctype/void> <func_name>(<ctype> <arg_name>): ...

Virtual Environments

System for installing libraries directly into project's directory.

$ python3 -m venv NAME      # Creates virtual environment in current directory.
$ source NAME/bin/activate  # Activates env. On Windows run `NAME\Scripts\activate`.
$ pip3 install LIBRARY      # Installs the library into active environment.
$ python3 FILE              # Runs the script in active environment. Also `./FILE`.
$ deactivate                # Deactivates the active virtual environment.

Basic Script Template

Run the script with '$ python3 FILE' or '$ chmod u+x FILE; ./FILE'. To automatically start the debugger when uncaught exception occurs run '$ python3 -m pdb -cc FILE'.

#!/usr/bin/env python3
#
# Usage: .py
#

from sys import argv, exit
from collections import defaultdict, namedtuple
from dataclasses import make_dataclass
from enum import Enum
import functools as ft, itertools as it, operator as op, re


def main():
    pass


###
##  UTIL
#

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


if __name__ == '__main__':
    main()

#Index

• Only available in the PDF.
• Ctrl+F / ⌘F is usually sufficient.
• Searching '#<title>' will limit the search to the titles.
• Click on the '#' symbol to get a link to specific section.