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if __name__ == '__main__':
main()<list> = <list>[from_inclusive : to_exclusive : step_size]<list>.append(<el>)
<list>.extend(<collection>)
<list> += [<el>]
<list> += <collection><list>.sort()
<list>.reverse()
<list> = sorted(<collection>)
<iter> = reversed(<list>)sum_of_elements = sum(<collection>)
elementwise_sum = [sum(pair) for pair in zip(list_a, list_b)]
sorted_by_second = sorted(<collection>, key=lambda el: el[1])
sorted_by_both = sorted(<collection>, key=lambda el: (el[1], el[0]))
flatter_list = list(itertools.chain.from_iterable(<list>))
product_of_elems = functools.reduce(lambda out, x: out * x, <collection>)
list_of_chars = list(<str>)index = <list>.index(<el>) # Returns first index of item.
<list>.insert(index, <el>) # Inserts item at index and moves the rest to the right.
<el> = <list>.pop([index]) # Removes and returns item at index or from the end.
<list>.remove(<el>) # Removes first occurrence of item or raises ValueError.
<list>.clear() # Removes all items. <view> = <dict>.keys()
<view> = <dict>.values()
<view> = <dict>.items()value = <dict>.get(key, default=None) # Returns default if key does not exist.
value = <dict>.setdefault(key, default=None) # Same, but also adds default to dict.
<dict> = collections.defaultdict(<type>) # Creates a dict with default value of type.
<dict> = collections.defaultdict(lambda: 1) # Creates a dict with default value 1.<dict>.update(<dict>) # Or: dict_a = {**dict_a, **dict_b}.
<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.value = <dict>.pop(key) # Removes item from dictionary.
{k: v for k, v in <dict>.items() if k in keys} # Filters dictionary by keys.>>> from collections import Counter
>>> colors = ['red', 'blue', 'yellow', 'blue', 'red', 'blue']
>>> counter = Counter(colors)
Counter({'blue': 3, 'red': 2, 'yellow': 1})
>>> counter.most_common()[0]
('blue', 3)<set> = set()<set>.add(<el>)
<set>.update(<collection>)
<set> |= {<el>}
<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><set>.remove(<el>) # Throws error.
<set>.discard(<el>) # Doesn't throw error.<frozenset> = frozenset(<collection>)<range> = range(to_exclusive)
<range> = range(from_inclusive, to_exclusive)
<range> = range(from_inclusive, to_exclusive, ±step_size)from_inclusive = <range>.start
to_exclusive = <range>.stopfor i, el in enumerate(<collection> [, i_start]):
...- Tuple is an immutable and hashable list.
- Named tuple is its subclass with named elements.
>>> from collections import namedtuple
>>> Point = namedtuple('Point', 'x y')
>>> p = Point(1, y=2)
Point(x=1, y=2)
>>> p[0]
1
>>> p.x
1
>>> getattr(p, 'y')
2
>>> p._fields # Or: Point._fields
('x', 'y')In this cheatsheet '<collection>' can also mean an iterator.
from itertools import count, repeat, cycle, chain, islice<iter> = iter(<collection>)
<iter> = iter(<function>, to_exclusive) # Sequence of return values until 'to_exclusive'.
<el> = next(<iter> [, default]) # Raises StopIteration or returns 'default' on end.<iter> = count(start=0, step=1) # Returns incremented value endlessly.
<iter> = repeat(<el> [, times]) # Returns element endlessly or 'times' times.
<iter> = cycle(<collection>) # Repeats the sequence indefinitely.<iter> = chain(<collection>, <collection>) # Empties collections in order.
<iter> = chain.from_iterable(<collection>) # Empties collections inside a collection in order.<iter> = islice(<collection>, to_exclusive)
<iter> = islice(<collection>, from_inclusive, to_exclusive)
<iter> = islice(<collection>, from_inclusive, to_exclusive, step_size)Convenient way to implement the iterator protocol.
def count(start, step):
while True:
yield start
start += step>>> counter = count(10, 2)
>>> next(counter), next(counter), next(counter)
(10, 12, 14)<type> = type(<el>) # <class 'int'> / <class 'str'> / ...from numbers import Integral, Rational, Real, Complex, Number
<bool> = isinstance(<el>, Number)<bool> = callable(<el>)<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 any whitespace character.
<list> = <str>.split(sep=None, maxsplit=-1) # Splits on 'sep' str at most 'maxsplit' times.
<str> = <str>.join(<list>) # Joins elements using string as separator.<str> = <str>.replace(old, new [, count]) # Replaces 'old' with 'new' at most 'count' times.
<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>.index(<sub_str>) # Returns start index of first match.<bool> = <str>.isnumeric() # True if str contains only numeric characters.
<list> = textwrap.wrap(<str>, width) # Nicely breaks string into lines.<str> = chr(<int>) # Converts int to unicode char.
<int> = ord(<str>) # Converts unicode char to int.>>> ord('0'), ord('9')
(48, 57)
>>> ord('A'), ord('Z')
(65, 90)
>>> ord('a'), ord('z')
(97, 122)import re
<str> = re.sub(<regex>, new, text, count=0) # Substitutes all occurrences.
<list> = re.findall(<regex>, text) # Returns all occurrences.
<list> = re.split(<regex>, text, maxsplit=0) # Use brackets in regex to keep the matches.
<Match> = re.search(<regex>, text) # Searches for first occurrence of 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.- Parameter
'flags=re.IGNORECASE'can be used with all functions. - Parameter
'flags=re.DOTALL'makes dot also accept newline. - Use
r'\1'or'\\\\1'for backreference. - Use
'?'to make operator non-greedy.
<str> = <Match>.group() # Whole match.
<str> = <Match>.group(1) # Part in first bracket.
<tuple> = <Match>.groups() # All bracketed parts.
<int> = <Match>.start() # Start index of a match.
<int> = <Match>.end() # Exclusive end index of a match.Expressions below hold true for strings that contain only ASCII characters. Use capital letter for negation.
'\d' == '[0-9]' # Digit
'\s' == '[ \t\n\r\f\v]' # Whitespace
'\w' == '[a-zA-Z0-9_]' # Alphanumeric<str> = f'{<el_1>}, {<el_2>}'
<str> = '{}, {}'.format(<el_1>, <el_2>)>>> Person = collections.namedtuple('Person', 'name height')
>>> person = Person('Jean-Luc', 187)
>>> f'{person.height}'
'187'
>>> '{p.height}'.format(p=person)
'187'{<el>:<10} # '<el> '
{<el>:>10} # ' <el>'
{<el>:^10} # ' <el> '
{<el>:->10} # '------<el>'
{<el>:>0} # '<el>''!r' calls object's repr() method, instead of format(), to get a string.
{'abcde'!r:<10} # "'abcde' "{'abcde':.3} # 'abc'
{'abcde':10.3} # 'abc '{1.23456:.3f} # '1.235'
{1.23456:10.3f} # ' 1.235'{ 123456:10,} # ' 123,456'
{ 123456:10_} # ' 123_456'
{ 123456:+10} # ' +123456'
{-123456:=10} # '- 123456'
{ 123456: } # ' 123456'
{-123456: } # '-123456'{65:c} # 'A'
{3:08b} # '00000011' -> Binary with leading zeros.
{3:0<8b} # '11000000' -> Binary with trailing zeros.'f'- Fixed point:.<precision>f'%'- Percent:.<precision>%'e'- Exponent
'c'- character'b'- binary'x'- hex'X'- HEX
<num> = pow(<num>, <num>) # Or: <num> ** <num>
<real> = abs(<num>)
<int> = round(<real>)
<real> = round(<real>, ±ndigits)from math import e, pi
from math import cos, acos, sin, asin, tan, atan, degrees, radians
from math import log, log10, log2
from math import inf, nan, isinf, isnanfrom statistics import mean, median, variance, pvariance, pstdevfrom random import random, randint, choice, shuffle
<float> = random()
<int> = randint(from_inclusive, to_inclusive)
<el> = choice(<list>)
shuffle(<list>)- Every function returns an iterator.
- If you want to print the iterator, you need to pass it to the list() function!
from itertools import product, combinations, combinations_with_replacement, permutations>>> product([0, 1], repeat=3)
[(0, 0, 0), (0, 0, 1), (0, 1, 0), (0, 1, 1),
(1, 0, 0), (1, 0, 1), (1, 1, 0), (1, 1, 1)]>>> product('ab', '12')
[('a', '1'), ('a', '2'),
('b', '1'), ('b', '2')]>>> combinations('abc', 2)
[('a', 'b'), ('a', 'c'), ('b', 'c')]>>> combinations_with_replacement('abc', 2)
[('a', 'a'), ('a', 'b'), ('a', 'c'),
('b', 'b'), ('b', 'c'),
('c', 'c')]>>> permutations('abc', 2)
[('a', 'b'), ('a', 'c'),
('b', 'a'), ('b', 'c'),
('c', 'a'), ('c', 'b')]from datetime import datetime
now = datetime.now()
now.month # 3
now.strftime('%Y%m%d') # '20180315'
now.strftime('%Y%m%d%H%M%S') # '20180315002834'
<datetime> = datetime.strptime('2015-05-12 00:39', '%Y-%m-%d %H:%M')<function>(<positional_args>) # f(0, 0)
<function>(<keyword_args>) # f(x=0, y=0)
<function>(<positional_args>, <keyword_args>) # f(0, y=0)def f(<nondefault_args>): # def f(x, y)
def f(<default_args>): # def f(x=0, y=0)
def f(<nondefault_args>, <default_args>): # def f(x, y=0)Splat expands collection into positional arguments, while splatty-splat expands dictionary into keyword arguments.
args = (1, 2)
kwargs = {'x': 3, 'y': 4, 'z': 5}
func(*args, **kwargs) func(1, 2, x=3, y=4, z=5)Splat combines zero or more positional arguments into tuple, while splatty-splat combines zero or more keyword arguments into dictionary.
def add(*a):
return sum(a)>>> add(1, 2, 3)
6def f(*args): # f(1, 2, 3)
def f(x, *args): # f(1, 2, 3)
def f(*args, z): # f(1, 2, z=3)
def f(x, *args, z): # f(1, 2, z=3)def f(**kwargs): # f(x=1, y=2, z=3)
def f(x, **kwargs): # f(x=1, y=2, z=3) | f(1, y=2, z=3)def f(*args, **kwargs): # f(x=1, y=2, z=3) | f(1, y=2, z=3) | f(1, 2, z=3) | f(1, 2, 3)
def f(x, *args, **kwargs): # f(x=1, y=2, z=3) | f(1, y=2, z=3) | f(1, 2, z=3) | f(1, 2, 3)
def f(*args, y, **kwargs): # f(x=1, y=2, z=3) | f(1, y=2, z=3)
def f(x, *args, z, **kwargs): # f(x=1, y=2, z=3) | f(1, y=2, z=3) | f(1, 2, z=3)<list> = [*<collection> [, ...]]
<set> = {*<collection> [, ...]}
<tuple> = (*<collection>, [...])
<dict> = {**<dict> [, ...]}head, *body, tail = <collection><function> = lambda: <return_value>
<function> = lambda <argument_1>, <argument_2>: <return_value><list> = [i+1 for i in range(10)] # [1, 2, ..., 10]
<set> = {i for i in range(10) if i > 5} # {6, 7, 8, 9}
<iter> = (i+5 for i in range(10)) # (5, 6, ..., 14)
<dict> = {i: i*2 for i in range(10)} # {0: 0, 1: 2, ..., 9: 18}out = [i+j for i in range(10) for j in range(10)]out = []
for i in range(10):
for j in range(10):
out.append(i+j)from functools import reduce
<iter> = map(lambda x: x + 1, range(10)) # (1, 2, ..., 10)
<iter> = filter(lambda x: x > 5, range(10)) # (6, 7, 8, 9)
<int> = reduce(lambda out, x: out + x, range(10)) # 45<bool> = any(<collection>) # False if empty.
<bool> = all(el[1] for el in <collection>) # True if empty.<expression_if_true> if <condition> else <expression_if_false>>>> [a if a else 'zero' for a in (0, 1, 0, 3)]
['zero', 1, 'zero', 3]from collections import namedtuple
Point = namedtuple('Point', 'x y')
point = Point(0, 0)from enum import Enum
Direction = Enum('Direction', 'n e s w')
Cutlery = Enum('Cutlery', {'fork': 1, 'knife': 2, 'spoon': 3})# Warning: Objects will share the objects that are initialized in the dictionary!
Creature = type('Creature', (), {'p': Point(0, 0), 'd': Direction.n})
creature = Creature()We have a closure in Python when:
- A nested function references a value of its enclosing function and then
- the enclosing function returns the nested function.
def get_multiplier(a):
def out(b):
return a * b
return out>>> multiply_by_3 = get_multiplier(3)
>>> multiply_by_3(10)
30- If multiple nested functions within enclosing function reference the same value, that value gets shared.
- To dynamically access function's first free variable use
'<function>.__closure__[0].cell_contents'.
from functools import partial
<function> = partial(<function> [, <arg_1>, <arg_2>, ...])>>> multiply_by_3 = partial(operator.mul, 3)
>>> multiply_by_3(10)
30If variable is being assigned to anywhere in the scope, it is regarded as a local variable, unless it is declared as a 'global' or 'nonlocal'.
def get_counter():
i = 0
def out():
nonlocal i
i += 1
return i
return out>>> counter = get_counter()
>>> counter(), counter(), counter()
(1, 2, 3)A decorator takes a function, adds some functionality and returns it.
@decorator_name
def function_that_gets_passed_to_decorator():
...Decorator that prints function's name every time it gets called.
from functools import wraps
def debug(func):
@wraps(func)
def out(*args, **kwargs):
print(func.__name__)
return func(*args, **kwargs)
return out
@debug
def add(x, y):
return x + y- Wraps is a helper decorator that copies metadata of function add() to function out().
- Without it
'add.__name__'would return'out'.
Decorator that caches function's return values. All function's arguments must be hashable.
from functools import lru_cache
@lru_cache(maxsize=None)
def fib(n):
return n if n < 2 else fib(n-2) + fib(n-1)- Recursion depth is limited to 1000 by default. To increase it use
'sys.setrecursionlimit(<depth>)'.
from functools import wraps
def debug(print_result=False):
def decorator(func):
@wraps(func)
def out(*args, **kwargs):
result = func(*args, **kwargs)
print(func.__name__, result if print_result else '')
return result
return out
return decorator
@debug(print_result=True)
def add(x, y):
return x + yclass <name>:
def __init__(self, a):
self.a = a
def __repr__(self):
class_name = self.__class__.__name__
return f'{class_name}({self.a!r})'
def __str__(self):
return str(self.a)
@classmethod
def get_class_name(cls):
return cls.__name__class <name>:
def __init__(self, a=None):
self.a = aclass Person:
def __init__(self, name, age):
self.name = name
self.age = age
class Employee(Person):
def __init__(self, name, age, staff_num):
super().__init__(name, age)
self.staff_num = staff_num- 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.
class MyComparable:
def __init__(self, a):
self.a = a
def __eq__(self, other):
if isinstance(other, type(self)):
return self.a == other.a
return False - Hashable object needs both hash() and eq() methods and it's 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 = copy.deepcopy(a)
@property
def a(self):
return self.__a
def __eq__(self, other):
if isinstance(other, type(self)):
return self.a == other.a
return False
def __hash__(self):
return hash(self.a)- Methods do not depend on each other, so they can be skipped if not needed.
- Any object with defined getitem() is considered iterable, even if it lacks iter().
class MySequence:
def __init__(self, a):
self.a = a
def __len__(self):
return len(self.a)
def __getitem__(self, i):
return self.a[i]
def __iter__(self):
for el in self.a:
yield elclass Counter:
def __init__(self):
self.i = 0
def __call__(self):
self.i += 1
return self.i>>> counter = Counter()
>>> counter(), counter(), counter()
(1, 2, 3)class MyOpen():
def __init__(self, filename):
self.filename = filename
def __enter__(self):
self.file = open(self.filename)
return self.file
def __exit__(self, *args):
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!from copy import copy, deepcopy
<object> = copy(<object>)
<object> = deepcopy(<object>)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()
@classmethod
def get_member_names(cls):
return [a.name for a in cls.__members__.values()]<member> = <enum>.<member_name>
<member> = <enum>['<member_name>']
<member> = <enum>(<value>)
name = <member>.name
value = <member>.valuelist_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>))Cutlery = Enum('Cutlery', ['fork', 'knife', 'spoon'])
Cutlery = Enum('Cutlery', 'fork knife spoon')
Cutlery = Enum('Cutlery', {'fork': 1, 'knife': 2, 'spoon': 3})from functools import partial
LogicOp = Enum('LogicOp', {'AND': partial(lambda l, r: l and r),
'OR' : partial(lambda l, r: l or r)})while True:
try:
x = int(input('Please enter a number: '))
except ValueError:
print('Oops! That was no valid number. Try again...')
else:
print('Thank you.')
breakraise ValueError('A very specific message!')>>> try:
... raise KeyboardInterrupt
... finally:
... print('Goodbye, world!')
Goodbye, world!
Traceback (most recent call last):
File "<stdin>", line 2, in <module>
KeyboardInterruptprint(<el_1>, ..., sep=' ', end='\n', file=sys.stdout, flush=False)- Use
'file=sys.stderr'for errors.
>>> from pprint import pprint
>>> pprint(dir())
['__annotations__',
'__builtins__',
'__doc__', ...]- Reads a line from user input or pipe if present.
- Trailing newline gets stripped.
- Prompt string is printed to the standard output before reading input.
<str> = input(prompt=None)while True:
try:
print(input())
except EOFError:
breakimport sys
script_name = sys.argv[0]
arguments = sys.argv[1:]from argparse import ArgumentParser, FileType
p = ArgumentParser(description=<str>)
p.add_argument('-<short_name>', '--<name>', action='store_true') # Flag
p.add_argument('-<short_name>', '--<name>', type=<type>) # Option
p.add_argument('<name>', type=<type>, nargs=1) # Argument
p.add_argument('<name>', type=<type>, nargs='+') # Arguments
args = p.parse_args()
value = args.<name>- Use
'help=<str>'for argument description. - Use
'type=FileType(<mode>)'for files.
Opens file and returns a corresponding file object.
<file> = open('<path>', mode='r', encoding=None)'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.
<file>.seek(0) # Move to the start of the file.
<file>.seek(offset) # Move 'offset' chars/bytes from the start.
<file>.seek(offset, <anchor>) # Anchor: 0 start, 1 current pos., 2 end.def read_file(filename):
with open(filename, encoding='utf-8') as file:
return file.readlines()def write_to_file(filename, text):
with open(filename, 'w', encoding='utf-8') as file:
file.write(text)from os import path, listdir
<bool> = path.exists('<path>')
<bool> = path.isfile('<path>')
<bool> = path.isdir('<path>')
<list> = listdir('<path>')>>> from glob import glob
>>> glob('../*.gif')
['1.gif', 'card.gif']from pathlib import Path
cwd = Path()
<Path> = Path('<path>' [, '<path>', <Path>, ...])
<Path> = <Path> / '<dir>' / '<file>'<bool> = <Path>.exists()
<bool> = <Path>.is_file()
<bool> = <Path>.is_dir()
<iter> = <Path>.iterdir()
<iter> = <Path>.glob('<pattern>')<str> = str(<Path>) # Returns path as string.
<tup.> = <Path>.parts # Returns all components as strings.
<Path> = <Path>.resolve() # Returns absolute path without symlinks.<str> = <Path>.name # Final component.
<str> = <Path>.stem # Final component without extension.
<str> = <Path>.suffix # Final component's extension.
<Path> = <Path>.parent # Path without final component.import os
<str> = os.popen(<command>).read()>>> import subprocess
>>> a = subprocess.run(['ls', '-a'], stdout=subprocess.PIPE)
>>> a.stdout
b'.\n..\nfile1.txt\nfile2.txt\n'
>>> a.returncode
0import csvdef read_csv_file(filename):
with open(filename, encoding='utf-8') as file:
return csv.reader(file, delimiter=';')def write_to_csv_file(filename, rows):
with open(filename, 'w', encoding='utf-8') as file:
writer = csv.writer(file, delimiter=';')
writer.writerows(rows)import json
<str> = json.dumps(<object>, ensure_ascii=True, indent=None)
<object> = json.loads(<str>)def read_json_file(filename):
with open(filename, encoding='utf-8') as file:
return json.load(file)def write_to_json_file(filename, an_object):
with open(filename, 'w', encoding='utf-8') as file:
json.dump(an_object, file, ensure_ascii=False, indent=2)import pickle
<bytes> = pickle.dumps(<object>)
<object> = pickle.loads(<bytes>)def read_pickle_file(filename):
with open(filename, 'rb') as file:
return pickle.load(file)def write_to_pickle_file(filename, an_object):
with open(filename, 'wb') as file:
pickle.dump(an_object, file)import sqlite3
db = sqlite3.connect('<path>')
...
db.close()cursor = db.execute('<query>')
if cursor:
<tuple> = cursor.fetchone() # First row.
<list> = cursor.fetchall() # Remaining rows.db.execute('<query>')
db.commit()Bytes object is immutable sequence of single bytes. Mutable version is called 'bytearray'.
<bytes> = b'<str>'
<int> = <bytes>[<index>]
<bytes> = <bytes>[<slice>]
<ints> = list(<bytes>)
<bytes> = b''.join(<coll_of_bytes>)<bytes> = <str>.encode(encoding='utf-8')
<bytes> = <int>.to_bytes(<length>, byteorder='big|little', signed=False)
<bytes> = bytes.fromhex('<hex>')<str> = <bytes>.decode(encoding='utf-8')
<int> = int.from_bytes(<bytes>, byteorder='big|little', signed=False)
<hex> = <bytes>.hex()def read_bytes(filename):
with open(filename, 'rb') as file:
return file.read()def write_bytes(filename, bytes_obj):
with open(filename, 'wb') as file:
file.write(bytes_obj)- Module that performs conversions between Python values and a C struct, represented as a Python bytes object.
- Machine’s native type sizes and byte order are used by default.
from struct import pack, unpack, iter_unpack, calcsize
<bytes> = pack('<format>', <value_1> [, <value_2>, ...])
<tuple> = unpack('<format>', <bytes>)
<tuples> = iter_unpack('<format>', <bytes>)>>> pack('>hhl', 1, 2, 3)
b'\x00\x01\x00\x02\x00\x00\x00\x03'
>>> unpack('>hhl', b'\x00\x01\x00\x02\x00\x00\x00\x03')
(1, 2, 3)
>>> calcsize('>hhl')
8'='- native byte order'<'- little-endian'>'- big-endian
'x'- pad byte'c'- char (1)'h'- short (2)'i'- int (4)'l'- long (4)'q'- long long (8)'f'- float (4)'d'- double (8)
List that can hold only elements of predefined type. Available types are listed above.
from array import array
<array> = array('<typecode>' [, <collection>])Used for accessing the internal data of an object that supports the buffer protocol.
<memoryview> = memoryview(<bytes> / <bytearray> / <array>)
<memoryview>.release()Thread-safe list with efficient appends and pops from either side. Pronounced "deck".
from collections import deque
<deque> = deque(<collection>, maxlen=None)<deque>.appendleft(<el>)
<el> = <deque>.popleft()<deque>.extendleft(<collection>) # Collection gets reversed.
<deque>.rotate(n=1) # Rotates elements to the right.from threading import Thread, RLockthread = Thread(target=<function>, args=(<first_arg>, ))
thread.start()
...
thread.join()lock = RLock()
lock.acquire()
...
lock.release()Inspecting code at runtime.
<list> = dir() # Names of in-scope variables.
<dict> = locals() # Dict of local variables. Also vars().
<dict> = globals() # Dict of global variables.<dict> = vars(<object>)
<bool> = hasattr(<object>, '<attr_name>')
value = getattr(<object>, '<attr_name>')
setattr(<object>, '<attr_name>', value)from inspect import signature
sig = signature(<function>)
no_of_params = len(sig.parameters)
param_names = list(sig.parameters.keys())Code that generates code.
Type is the root class. If only passed the object it returns it's type (class). Otherwise it creates a new class.
<class> = type(<class_name>, <parents_tuple>, <attributes_dict>)>>> Z = type('Z', (), {'a': 'abcde', 'b': 12345})
>>> z = Z()Class that creates class.
def my_meta_class(name, parents, attrs):
attrs['a'] = 'abcde'
return type(name, parents, attrs)class MyMetaClass(type):
def __new__(cls, name, parents, attrs):
attrs['a'] = 'abcde'
return type.__new__(cls, name, parents, attrs)When class is created it checks if it has metaclass defined. If not, it recursively checks if any of his parents has it defined and eventually comes to type.
class MyClass(metaclass=MyMetaClass):
b = 12345>>> MyClass.a, MyClass.b
('abcde', 12345)from operator import add, sub, mul, truediv, floordiv, mod, pow, neg, abs
from operator import eq, ne, lt, le, gt, ge
from operator import not_, and_, or_
from operator import itemgetter, attrgetter, methodcallerimport operator as op
product_of_elems = functools.reduce(op.mul, <collection>)
sorted_by_second = sorted(<collection>, key=op.itemgetter(1))
sorted_by_both = sorted(<collection>, key=op.itemgetter(1, 0))
LogicOp = enum.Enum('LogicOp', {'AND': op.and_, 'OR' : op.or_})
last_el = op.methodcaller('pop')(<list>)>>> from ast import literal_eval
>>> literal_eval('1 + 2')
3
>>> literal_eval('[1, 2, 3]')
[1, 2, 3]
>>> literal_eval('abs(1)')
ValueError: malformed node or stringimport ast
from ast import Num, BinOp, UnaryOp
import operator as op
LEGAL_OPERATORS = {ast.Add: op.add, # <el> + <el>
ast.Sub: op.sub, # <el> - <el>
ast.Mult: op.mul, # <el> * <el>
ast.Div: op.truediv, # <el> / <el>
ast.Pow: op.pow, # <el> ** <el>
ast.BitXor: op.xor, # <el> ^ <el>
ast.USub: op.neg} # - <el>
def evaluate(expression):
root = ast.parse(expression, mode='eval')
return eval_node(root.body)
def eval_node(node):
node_type = type(node)
if node_type == Num:
return node.n
if node_type not in [BinOp, UnaryOp]:
raise TypeError(node)
operator_type = type(node.op)
if operator_type not in LEGAL_OPERATORS:
raise TypeError(f'Illegal operator {node.op}')
operator = LEGAL_OPERATORS[operator_type]
if node_type == BinOp:
left, right = eval_node(node.left), eval_node(node.right)
return operator(left, right)
elif node_type == UnaryOp:
operand = eval_node(node.operand)
return operator(operand)>>> evaluate('2 ^ 6')
4
>>> evaluate('2 ** 6')
64
>>> evaluate('1 + 2 * 3 ** (4 ^ 5) / (6 + -7)')
-5.0- Similar to generator, but generator pulls data through the pipe with iteration, while coroutine pushes data into the pipeline with send().
- Coroutines provide more powerful data routing possibilities than iterators.
- If you built a collection of simple data processing components, you can glue them together into complex arrangements of pipes, branches, merging, etc.
- All coroutines must be "primed" by first calling next().
- Remembering to call next() is easy to forget.
- Solved by wrapping coroutines with a decorator:
def coroutine(func):
def out(*args, **kwargs):
cr = func(*args, **kwargs)
next(cr)
return cr
return outdef reader(target):
for i in range(10):
target.send(i)
target.close()
@coroutine
def adder(target):
while True:
item = (yield)
target.send(item + 100)
@coroutine
def printer():
while True:
item = (yield)
print(item)
reader(adder(printer())) # 100, 101, ..., 109# $ pip3 install tqdm
from tqdm import tqdm
from time import sleep
for i in tqdm([1, 2, 3]):
sleep(0.2)
for i in tqdm(range(100)):
sleep(0.02)# $ pip3 install matplotlib
from matplotlib import pyplot
pyplot.plot(<data_1> [, <data_2>, ...])
pyplot.savefig(<filename>, transparent=True)
pyplot.show()# $ pip3 install tabulate
from tabulate import tabulate
import csv
with open(<filename>, encoding='utf-8') as file:
lines = csv.reader(file, delimiter=';')
headers = [header.title() for header in next(lines)]
table = tabulate(lines, headers)
print(table)# $ pip3 install curses
from curses import wrapper
def main():
wrapper(draw)
def draw(screen):
screen.clear()
screen.addstr(0, 0, 'Press ESC to quit.')
while screen.getch() != 27:
pass
def get_border(screen):
from collections import namedtuple
P = namedtuple('P', 'x y')
height, width = screen.getmaxyx()
return P(width-1, height-1)# $ pip3 install requests beautifulsoup4
>>> import requests
>>> from bs4 import BeautifulSoup
>>> url = 'https://en.wikipedia.org/wiki/Python_(programming_language)'
>>> page = requests.get(url)
>>> doc = BeautifulSoup(page.text, 'html.parser')
>>> table = doc.find('table', class_='infobox vevent')
>>> rows = table.find_all('tr')
>>> link = rows[11].find('a')['href']
>>> ver = rows[6].find('div').text.split()[0]
>>> link, ver
('https://www.python.org/', '3.7.2')# $ pip3 install bottle
from bottle import run, route, post, template, request, response
import jsonrun(host='localhost', port=8080)
run(host='0.0.0.0', port=80, server='cherrypy')@route('/img/<image>')
def send_image(image):
return static_file(image, 'images/', mimetype='image/png')@route('/<sport>')
def send_page(sport):
return template('<h1>{{title}}</h1>', title=sport)@post('/odds/<sport>')
def odds_handler(sport):
team = request.forms.get('team')
home_odds, away_odds = 2.44, 3.29
response.headers['Content-Type'] = 'application/json'
response.headers['Cache-Control'] = 'no-cache'
return json.dumps([team, home_odds, away_odds])# $ pip3 install requests
>>> import requests
>>> url = 'http://localhost:8080/odds/football'
>>> data = {'team': 'arsenal f.c.'}
>>> response = requests.post(url, data=data)
>>> response.json()
['arsenal f.c.', 2.44, 3.29]from time import time
start_time = time() # Seconds since Epoch.
...
duration = time() - start_timefrom time import perf_counter as pc
start_time = pc() # Seconds since restart.
...
duration = pc() - start_timefrom timeit import timeit
timeit('"-".join(str(a) for a in range(100))',
number=10000, globals=globals(), setup='pass')# $ pip3 install line_profiler
@profile
def main():
a = [*range(10000)]
b = {*range(10000)}
main()$ kernprof -lv test.py
Line # Hits Time Per Hit % Time Line Contents
==============================================================
1 @profile
2 def main():
3 1 1128.0 1128.0 27.4 a = [*range(10000)]
4 1 2994.0 2994.0 72.6 b = {*range(10000)}
# $ pip3 install pycallgraph
from pycallgraph import output, PyCallGraph
from datetime import datetime
time_str = datetime.now().strftime('%Y%m%d%H%M%S')
filename = f'profile-{time_str}.png'
drawer = output.GraphvizOutput(output_file=filename)
with PyCallGraph(output=drawer):
<code_to_be_profiled>Array manipulation mini language. Can run up to one hundred times faster than equivalent Python code.
# $ pip3 install numpy
import numpy as np<array> = np.array(<list>)
<array> = np.arange(from_inclusive, to_exclusive, step_size)
<array> = np.ones(<shape>)
<array> = np.random.randint(from_inclusive, to_exclusive, <shape>)<array>.shape = <shape>
<view> = <array>.reshape(<shape>)
<view> = np.broadcast_to(<array>, <shape>)<array> = <array>.sum(axis)
indexes = <array>.argmin(axis)- Shape is a tuple of dimension sizes.
- Axis is an index of dimension that gets collapsed. Leftmost dimension has index 0.
<el> = <2d_array>[0, 0] # First element.
<1d_view> = <2d_array>[0] # First row.
<1d_view> = <2d_array>[:, 0] # First column. Also [..., 0].
<3d_view> = <2d_array>[None, :, :] # Expanded by dimension of size 1.<1d_array> = <2d_array>[<1d_row_indexes>, <1d_column_indexes>]
<2d_array> = <2d_array>[<2d_row_indexes>, <2d_column_indexes>]<2d_bools> = <2d_array> > 0
<1d_array> = <2d_array>[<2d_bools>]- If row and column indexes differ in shape, they are combined with broadcasting.
Broadcasting is a set of rules by which NumPy functions operate on arrays of different sizes and/or dimensions.
left = [[0.1], [0.6], [0.8]] # Shape: (3, 1)
right = [ 0.1 , 0.6 , 0.8 ] # Shape: (3)left = [[0.1], [0.6], [0.8]] # Shape: (3, 1)
right = [[0.1 , 0.6 , 0.8]] # Shape: (1, 3) <- !2. If any dimensions differ in size, expand the ones that have size 1 by duplicating their elements:
left = [[0.1, 0.1, 0.1], [0.6, 0.6, 0.6], [0.8, 0.8, 0.8]] # Shape: (3, 3) <- !
right = [[0.1, 0.6, 0.8], [0.1, 0.6, 0.8], [0.1, 0.6, 0.8]] # Shape: (3, 3) <- !>>> 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 = wrapped_points - 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. ]]
>>> i = np.arange(3)
[0, 1, 2]
>>> distances[i, i] = np.inf
[[ inf, 0.5, 0.7],
[ 0.5, inf, 0.2],
[ 0.7, 0.2, inf]]
>>> distances.argmin(1)
[1, 2, 1]# $ pip3 install pillow
from PIL import Imagewidth = 100
height = 100
size = width * height
pixels = [255 * i/size for i in range(size)]
img = Image.new('HSV', (width, height))
img.putdata([(int(a), 255, 255) for a in pixels])
img.convert(mode='RGB').save('test.png')from random import randint
add_noise = lambda value: max(0, min(255, value + randint(-20, 20)))
img = Image.open('test.png').convert(mode='HSV')
img.putdata([(add_noise(h), s, v) for h, s, v in img.getdata()])
img.convert(mode='RGB').save('test.png')'1'- 1-bit pixels, black and white, stored with one pixel per byte.'L'- 8-bit pixels, greyscale.'RGB'- 3x8-bit pixels, true color.'RGBA'- 4x8-bit pixels, true color with transparency mask.'HSV'- 3x8-bit pixels, Hue, Saturation, Value color space.
import wave
from struct import pack, iter_unpackdef read_wav_file(filename):
with wave.open(filename, 'rb') as wf:
frames = wf.readframes(wf.getnframes())
return [a[0] for a in iter_unpack('<h', frames)]def write_to_wav_file(filename, frames_int, mono=True):
frames_short = (pack('<h', a) for a in frames_int)
with wave.open(filename, 'wb') as wf:
wf.setnchannels(1 if mono else 2)
wf.setsampwidth(2)
wf.setframerate(44100)
wf.writeframes(b''.join(frames_short))from math import pi, sin
frames_f = (sin(i * 2 * pi * 440 / 44100) for i in range(100000))
frames_i = (int(a * 30000) for a in frames_f)
write_to_wav_file('test.wav', frames_i)from random import randint
add_noise = lambda value: max(-32768, min(32767, value + randint(-500, 500)))
frames_i = (add_noise(a) for a in read_wav_file('test.wav'))
write_to_wav_file('test.wav', frames_i)# $ pip3 install simpleaudio
import simpleaudio, math, struct
from itertools import chain, repeat
F = 44100
P1 = '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: 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 key: 8.176 * 2 ** (int(key) / 12)
parse_n = lambda note: (get_hz(note[:2]), 0.25 if '♪' in note else 0.125)
get_note = lambda note: get_wave(*parse_n(note)) if note else get_pause(0.125)
frames_i = chain.from_iterable(get_note(n) for n in f'{P1}{P1}{P2}'.split(','))
frames_b = b''.join(struct.pack('<h', int(a * 30000)) for a in frames_i)
simpleaudio.play_buffer(frames_b, 1, 2, F)#!/usr/bin/env python3
#
# Usage: .py
#
from collections import namedtuple
from enum import Enum
import re
import sys
def main():
pass
###
## UTIL
#
def read_file(filename):
with open(filename, encoding='utf-8') as file:
return file.readlines()
if __name__ == '__main__':
main()