Python Cheatsheet
The following gives an overview of the most basic concepts found in python. It serves as a quick reminder when not having coded in python for a while.
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Main
if __name__ == '__main__':
main()
List
<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.
Dictionary
<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.
Counter
>>> 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()
<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
Is hashable, meaning it can be used as a key in dictionary or as an element in set.
<frozenset> = frozenset(<collection>)
Range
<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>.stop
Enumerate
for i, el in enumerate(<collection> [, i_start]):
...
Named Tuple
- 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')
Iterator
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)
Generator
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> = type(<el>) # <class 'int'> / <class 'str'> / ...
from numbers import Integral, Rational, Real, Complex, Number
<bool> = isinstance(<el>, Number)
<bool> = callable(<el>)
String
<str> = <str>.strip() # Strips all whitespace characters from both ends.
<str> = <str>.strip('<chars>') # Strips all passed characters from both ends.
<list> = <str>.split() # Splits on any whitespace character.
<list> = <str>.split(sep=None, maxsplit=-1) # Splits on 'sep' str at most 'maxsplit' times.
<str> = <str>.join(<collection>) # 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.
Char
<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)
Regex
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.
Match Object
<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.
Special Sequences
Expressions below hold true for strings that contain only ASCII characters. Use capital letters for negation.
'\d' == '[0-9]' # Digit
'\s' == '[ \t\n\r\f\v]' # Whitespace
'\w' == '[a-zA-Z0-9_]' # Alphanumeric
Format
<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'
General Options
{<el>:<10} # '<el> '
{<el>:>10} # ' <el>'
{<el>:^10} # ' <el> '
{<el>:->10} # '------<el>'
{<el>:>0} # '<el>'
String Options
'!r'
calls object’s repr() method, instead of format(), to get a string.
{'abcde'!r:<10} # "'abcde' "
{'abcde':.3} # 'abc'
{'abcde':10.3} # 'abc '
Number Options
{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.
Float presentation types:
* 'f'
- Fixed point: .<precision>f
* '%'
- Percent: .<precision>%
* 'e'
- Exponent
Integer presentation types:
* 'c'
- character
* 'b'
- binary
* 'x'
- hex
* 'X'
- HEX
Numbers
Basic Functions
<num> = pow(<num>, <num>) # Or: <num> ** <num>
<real> = abs(<num>)
<int> = round(<real>)
<real> = round(<real>, ±ndigits)
Math
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, isnan
Statistics
from statistics import mean, median, variance, pvariance, pstdev
Random
from random import random, randint, choice, shuffle
<float> = random()
<int> = randint(from_inclusive, to_inclusive)
<el> = choice(<list>)
shuffle(<list>)
Combinatorics
- 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')]
Datetime
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')
Arguments
Inside Function Call
<function>(<positional_args>) # f(0, 0)
<function>(<keyword_args>) # f(x=0, y=0)
<function>(<positional_args>, <keyword_args>) # f(0, y=0)
Inside Function Definition
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 Operator
Inside Function Call
Splat expands a collection into positional arguments, while splatty-splat expands a dictionary into keyword arguments.
args = (1, 2)
kwargs = {'x': 3, 'y': 4, 'z': 5}
func(*args, **kwargs)
Is the same as:
func(1, 2, x=3, y=4, z=5)
Inside Function Definition
Splat combines zero or more positional arguments into a tuple, while splatty-splat combines zero or more keyword arguments into a dictionary.
def add(*a):
return sum(a)
>>> add(1, 2, 3)
6
Legal argument combinations:
def f(*args): # f(1, 2, 3)
def f(x, *args): # f(1, 2, 3)
def f(*args, z): # f(1, 2, z=3)
def f(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)
Other Uses
<list> = [*<collection> [, ...]]
<set> = {*<collection> [, ...]}
<tuple> = (*<collection>, [...])
<dict> = {**<dict> [, ...]}
head, *body, tail = <collection>
Inline
Lambda
<function> = lambda: <return_value>
<function> = lambda <argument_1>, <argument_2>: <return_value>
Comprehension
<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)]
Is the same as:
out = []
for i in range(10):
for j in range(10):
out.append(i+j)
Map, Filter, Reduce
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
Any, All
<bool> = any(<collection>) # False if empty.
<bool> = all(el[1] for el in <collection>) # True if empty.
If - Else
<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]
Namedtuple, Enum, Class
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()
Closure
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'
.
Partial
from functools import partial
<function> = partial(<function> [, <arg_1>, <arg_2>, ...])
>>> multiply_by_3 = partial(operator.mul, 3)
>>> multiply_by_3(10)
30
Nonlocal
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 ‘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)
Decorator
A decorator takes a function, adds some functionality and returns it.
@decorator_name
def function_that_gets_passed_to_decorator():
...
Debugger Example
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
'add.__name__'
would return 'out'
.
LRU Cache
Decorator that caches function’s return values. All function’s arguments must be hashable.
from functools import lru_cache
@lru_cache(maxsize=None)
def fib(n):
return n if n < 2 else fib(n-2) + fib(n-1)
- Recursion depth is limited to 1000 by default. To increase it use
'sys.setrecursionlimit(<depth>)'
.
Parametrized Decorator
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
class <name>:
def __init__(self, a):
self.a = a
def __repr__(self):
class_name = self.__class__.__name__
return f'{class_name}({self.a!r})'
def __str__(self):
return str(self.a)
@classmethod
def get_class_name(cls):
return cls.__name__
Constructor Overloading
class <name>:
def __init__(self, a=None):
self.a = a
Inheritance
class Person:
def __init__(self, name, age):
self.name = name
self.age = age
class Employee(Person):
def __init__(self, name, age, staff_num):
super().__init__(name, age)
self.staff_num = staff_num
Comparable
- If eq() method is not overridden, it returns
'id(self) == id(other)'
, which is the same as'self is other'
. - That means all objects compare not equal by default.
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
- 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 = 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)
Sequence
- 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 el
Callable
class Counter:
def __init__(self):
self.i = 0
def __call__(self):
self.i += 1
return self.i
>>> counter = Counter()
>>> counter(), counter(), counter()
(1, 2, 3)
Withable
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!
Copy
from copy import copy, deepcopy
<object> = copy(<object>)
<object> = deepcopy(<object>)
Enum
from enum import Enum, auto
class <enum_name>(Enum):
<member_name_1> = <value_1>
<member_name_2> = <value_2_a>, <value_2_b>
<member_name_3> = auto()
@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>.value
list_of_members = list(<enum>)
member_names = [a.name for a in <enum>]
member_values = [a.value for a in <enum>]
random_member = random.choice(list(<enum>))
Inline
Cutlery = Enum('Cutlery', ['fork', 'knife', 'spoon'])
Cutlery = Enum('Cutlery', 'fork knife spoon')
Cutlery = Enum('Cutlery', {'fork': 1, 'knife': 2, 'spoon': 3})
Functions can not 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
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.')
break
Raising Exception
raise ValueError('A very specific message!')
Finally
>>> try:
... raise KeyboardInterrupt
... finally:
... print('Goodbye, world!')
Goodbye, world!
Traceback (most recent call last):
File "<stdin>", line 2, in <module>
KeyboardInterrupt
print(<el_1>, ..., sep=' ', end='\n', file=sys.stdout, flush=False)
- Use
'file=sys.stderr'
for errors.
Pretty Print
>>> from pprint import pprint
>>> pprint(dir())
['__annotations__',
'__builtins__',
'__doc__', ...]
Input
- 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)
Prints lines until EOF:
while True:
try:
print(input())
except EOFError:
break
Command Line Arguments
import sys
script_name = sys.argv[0]
arguments = sys.argv[1:]
Argparse
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.
Open
Opens file and returns a corresponding file object.
<file> = open('<path>', mode='r', encoding=None)
Modes
'r'
- Read (default).'w'
- Write (truncate).'x'
- Write or fail if the file already exists.'a'
- Append.'w+'
- Read and write (truncate).'r+'
- Read and write from the start.'a+'
- Read and write from the end.'t'
- Text mode (default).'b'
- Binary mode.
Seek
<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.
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)
Path
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']
Pathlib
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.
Command Execution
import os
<str> = os.popen(<command>).read()
Subprocess
>>> import subprocess
>>> a = subprocess.run(['ls', '-a'], stdout=subprocess.PIPE)
>>> a.stdout
b'.\n..\nfile1.txt\nfile2.txt\n'
>>> a.returncode
0
CSV
import csv
Read Rows from CSV File
def read_csv_file(filename):
with open(filename, encoding='utf-8') as file:
return csv.reader(file, delimiter=';')
Write Rows to CSV File
def write_to_csv_file(filename, rows):
with open(filename, 'w', encoding='utf-8') as file:
writer = csv.writer(file, delimiter=';')
writer.writerows(rows)
JSON
import json
<str> = json.dumps(<object>, ensure_ascii=True, indent=None)
<object> = json.loads(<str>)
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
import pickle
<bytes> = pickle.dumps(<object>)
<object> = pickle.loads(<bytes>)
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)
SQLite
import sqlite3
db = sqlite3.connect('<path>')
...
db.close()
Read
cursor = db.execute('<query>')
if cursor:
<tuple> = cursor.fetchone() # First row.
<list> = cursor.fetchall() # Remaining rows.
Write
db.execute('<query>')
db.commit()
Bytes
Bytes object is an 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>)
Encode
<bytes> = <str>.encode(encoding='utf-8')
<bytes> = <int>.to_bytes(<length>, byteorder='big|little', signed=False)
<bytes> = bytes.fromhex('<hex>')
Decode
<str> = <bytes>.decode(encoding='utf-8')
<int> = int.from_bytes(<bytes>, byteorder='big|little', signed=False)
<hex> = <bytes>.hex()
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 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>)
Example
>>> 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
Format
For standard sizes start format string with:
* '='
- native byte order
* '<'
- little-endian
* '>'
- big-endian
Use capital letter for unsigned type. Standard sizes are in brackets:
* '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)
Array
List that can hold only elements of predefined type. Available types are listed above.
from array import array
<array> = array('<typecode>' [, <collection>])
Memory View
Used for accessing the internal data of an object that supports the buffer protocol.
<memoryview> = memoryview(<bytes> / <bytearray> / <array>)
<memoryview>.release()
Deque
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.
Threading
from threading import Thread, RLock
Thread
thread = Thread(target=<function>, args=(<first_arg>, ))
thread.start()
...
thread.join()
Lock
lock = RLock()
lock.acquire()
...
lock.release()
Introspection
Inspecting code at runtime.
Variables
<list> = dir() # Names of in-scope variables.
<dict> = locals() # Dict of local variables. Also vars().
<dict> = globals() # Dict of global variables.
Attributes
<dict> = vars(<object>)
<bool> = hasattr(<object>, '<attr_name>')
value = getattr(<object>, '<attr_name>')
setattr(<object>, '<attr_name>', value)
Parameters
from inspect import signature
sig = signature(<function>)
no_of_params = len(sig.parameters)
param_names = list(sig.parameters.keys())
Metaprograming
Code that generates code.
Type
Type is the root class. If only passed the object it returns its 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()
Meta Class
Class that creates class.
def my_meta_class(name, parents, attrs):
attrs['a'] = 'abcde'
return type(name, parents, attrs)
Or:
class MyMetaClass(type):
def __new__(cls, name, parents, attrs):
attrs['a'] = 'abcde'
return type.__new__(cls, name, parents, attrs)
Metaclass Attribute
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)
Operator
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, methodcaller
import 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>)
Eval
Basic
>>> 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 string
Using Abstract Syntax Trees
import 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
Coroutine
- 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.
Helper Decorator
- 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 out
Pipeline Example
def 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
Libraries
Progress Bar
# $ 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)
Plot
# $ pip3 install matplotlib
from matplotlib import pyplot
pyplot.plot(<data_1> [, <data_2>, ...])
pyplot.savefig(<filename>, transparent=True)
pyplot.show()
Table
Prints CSV file as ASCII table:
# $ 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)
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)
Scraping
# $ 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')
Web
# $ pip3 install bottle
from bottle import run, route, post, template, request, response
import json
Run
run(host='localhost', port=8080)
run(host='0.0.0.0', port=80, server='cherrypy')
Static Request
@route('/img/<image>')
def send_image(image):
return static_file(image, 'images/', mimetype='image/png')
Dynamic Request
@route('/<sport>')
def send_page(sport):
return template('<h1>{{title}}</h1>', title=sport)
REST Request
@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])
Test:
# $ 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]
Profile
Basic
from time import time
start_time = time() # Seconds since Epoch.
...
duration = time() - start_time
High Performance
from time import perf_counter as pc
start_time = pc() # Seconds since restart.
...
duration = pc() - start_time
Timing a Snippet
from timeit import timeit
timeit('"-".join(str(a) for a in range(100))',
number=10000, globals=globals(), setup='pass')
Line Profiler
# $ pip3 install line_profiler
@profile
def main():
a = [*range(10000)]
b = {*range(10000)}
main()
Usage:
$ 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)}
Call Graph
Generates a PNG image of a call graph with highlighted bottlenecks:
# $ 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>
NumPy
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.
Indexing
<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
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)
1. If array shapes differ in length, left-pad the smaller shape with ones:
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) <- !
3. If neither non-matching dimension has size 1, rise an error.
Example
For each point returns index of its nearest point ([0.1, 0.6, 0.8] => [1, 2, 1]
):
>>> 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]
Image
# $ pip3 install pillow
from PIL import Image
Creates PNG image of rainbow gradient:
width = 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')
Adds noise to a PNG image:
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')
Modes
'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.
Audio
import wave
from struct import pack, iter_unpack
Read Frames from WAV File
def 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)]
Write Frames to WAV File
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))
Examples
Saves a sine wave to a mono WAV file:
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)
Adds noise to a mono WAV file:
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)
Plays Popcorn:
# $ 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)
Basic Script Template
#!/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()