30 KiB
Comprehensive Python Cheatsheet
Download text file or Fork me on GitHub.
Main
if __name__ == '__main__':
main()
List
<list> = <list>[from_inclusive : to_exclusive : step_size]
<list>.append(<el>)
<list>.extend(<list>)
<list> += [<el>]
<list> += <list>
<list>.sort()
<list>.reverse()
<list> = sorted(<list>)
<iter> = reversed(<list>)
sum_of_elements = sum(<list>)
elementwise_sum = [sum(pair) for pair in zip(list_a, list_b)]
sorted_by_second = sorted(<list>, key=lambda el: el[1])
sorted_by_both = sorted(<list>, key=lambda el: (el[1], el[0]))
flattened_list = list(itertools.chain.from_iterable(<list>))
list_of_chars = list(<str>)
product_of_elems = functools.reduce(lambda out, x: out * x, <list>)
no_duplicates = list(dict.fromkeys(<list>))
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.
<list>.clear() # Removes all items.
Dictionary
<view> = <dict>.keys()
<view> = <dict>.values()
<view> = <dict>.items()
value = <dict>.get(key, default) # Returns default if key does not exist.
value = <dict>.setdefault(key, default) # Same, but also adds default to dict.
<dict> = collections.defaultdict(<type>) # Creates a dictionary with default value of type.
<dict> = collections.defaultdict(lambda: 1) # Creates a dictionary with default value 1.
<dict>.update(<dict>)
<dict> = dict(<list>) # Initiates a dict from list of key-value pairs.
<dict> = dict(zip(keys, values)) # Initiates a dict from two lists.
<dict> = dict.fromkeys(keys [, value]) # Initiates a dict from list of keys.
{k: v for k, v in <dict>.items() if k in keys} # Filters a dict by keys.
Counter
>>> from collections import Counter
>>> colors = ['blue', 'red', 'blue', 'yellow', 'blue', 'red']
>>> Counter(colors)
Counter({'blue': 3, 'red': 2, 'yellow': 1})
>>> <counter>.most_common()[0][0]
'blue'
Set
<set> = set()
<set>.add(<el>)
<set>.update(<set>)
<set>.clear()
<set> = <set>.union(<set>) # Or: <set> | <set>
<set> = <set>.intersection(<set>) # Or: <set> & <set>
<set> = <set>.difference(<set>) # Or: <set> - <set>
<set> = <set>.symmetric_difference(<set>) # Or: <set> ^ <set>
<bool> = <set>.issubset(<set>) # Or: <set> < <set>
<bool> = <set>.issuperset(<set>) # Or: <set> > <set>
Frozenset
Is hashable and can be used as a key in dictionary.
<frozenset> = frozenset(<collection>)
Range
range(to_exclusive)
range(from_inclusive, to_exclusive)
range(from_inclusive, to_exclusive, step_size)
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
>>> Point = collections.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
Skips first element:
next(<iter>)
for element in <iter>:
...
Reads input until it reaches an empty line:
for line in iter(input, ''):
...
Same, but prints a message every time:
from functools import partial
for line in iter(partial(input, 'Please enter value: '), ''):
...
Generator
Convenient way to implement the iterator protocol.
def step(start, step):
while True:
yield start
start += step
>>> stepper = step(10, 2)
>>> next(stepper), next(stepper), next(stepper)
(10, 12, 14)
Type
<type> = type(<el>) # <class 'int'> / <class 'str'> / ...
from numbers import Number, Integral, Real, Rational, Complex
is_number = isinstance(<el>, Number)
is_function = callable(<el>)
String
<str> = <str>.strip() # Strips all whitespace characters.
<str> = <str>.strip('<chars>') # Strips all passed characters.
<list> = <str>.split() # Splits on any whitespace character.
<list> = <str>.split(sep=None, maxsplit=-1) # Splits on 'sep' at most 'maxsplit' times.
<str> = <str>.join(<list>) # Joins elements using string as separator.
<str> = <str>.replace(old_str, new_str)
<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 first index of a substring.
<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)
print(<el_1> [, <el_2>, end='', sep='', file=<file>]) # Use 'file=sys.stderr' for errors.
>>> from pprint import pprint
>>> pprint(locals())
{'__doc__': None,
'__name__': '__main__',
'__package__': None, ...}
Regex
import re
<str> = re.sub(<regex>, new, text, count=0) # Substitutes all occurrences.
<list> = re.findall(<regex>, text)
<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.
<Match_iter> = re.finditer(<regex>, text) # Searches for all occurrences of pattern.
- 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 operators non-greedy.
Match Object
<str> = <Match>.group() # Whole match.
<str> = <Match>.group(1) # Part in first bracket.
<int> = <Match>.start() # Start index of a match.
<int> = <Match>.end() # Exclusive end index of a match.
Special Sequences
Use capital letter 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 = namedtuple('Person', 'name height')
>>> person = Person('Jean-Luc', 187)
>>> f'{person.height:10}'
' 187'
>>> '{p.height:10}'.format(p=person)
' 187'
General Options
{<el>:<10} # '<el> '
{<el>:>10} # ' <el>'
{<el>:^10} # ' <el> '
{<el>:->10} # '------<el>'
{<el>:>0} # '<el>'
String Options
"!r" uses object's repr() method, instead of format(), to get a string:
{'abcde'!r} # "'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
pow(x, y) # Or: x ** y
abs(<num>)
round(<num> [, ndigits])
Constants
from math import e, pi
Trigonometry
from math import cos, acos, sin, asin, tan, atan, degrees, radians
Logarithm
from math import log, log10, log2
log(x [, base]) # Base e, if not specified.
log10(x) # Base 10.
log2(x) # Base 2.
Infinity, nan
from math import inf, nan, isinf, isnan
Or:
float('inf'), float('nan')
Random
from random import random, randint, choice, shuffle
<float> = random()
<int> = randint(from_inclusive, to_inclusive)
<el> = choice(<list>)
shuffle(<list>)
Datetime
from datetime import datetime, strptime
now = datetime.now()
now.month # 3
now.strftime('%Y%m%d') # '20180315'
now.strftime('%Y%m%d%H%M%S') # '20180315002834'
<datetime> = strptime('2015-05-12 00:39', '%Y-%m-%d %H:%M')
Arguments
"*" is the splat operator, that takes a list as input, and expands it into actual positional arguments in the function call.
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)
Splat operator can also be used in function declarations:
def add(*a):
return sum(a)
>>> add(1, 2, 3)
6
And in few other places:
>>> a = (1, 2, 3)
>>> [*a]
[1, 2, 3]
>>> head, *body, tail = [1, 2, 3, 4]
>>> body
[2, 3]
Inline
Lambda
lambda: <return_value>
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, ..., 9}
<dict> = {i: i*2 for i in range(10)} # {0: 0, 1: 2, ..., 9: 18}
<iter> = (x+5 for x in range(10)) # (5, 6, ..., 14)
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, ..., 9)
<any_type> = reduce(lambda out, x: out + x, range(10)) # 45
Any, All
<bool> = any(el[1] for el in <collection>)
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')
from enum import Enum
Direction = Enum('Direction', 'n e s w')
Cutlery = Enum('Cutlery', {'knife': 1, 'fork': 2, 'spoon': 3})
# Warning: Objects will share the objects that are initialized in the dictionary!
Creature = type('Creature', (), {'position': Point(0, 0), 'direction': Direction.n})
creature = Creature()
Closure
def get_multiplier(a):
def out(b):
return a * b
return out
>>> multiply_by_3 = get_multiplier(3)
>>> multiply_by_3(10)
30
Or:
from functools import partial
<function> = partial(<function>, <argument_1> [, <argument_2>, ...])
>>> multiply_by_3 = partial(operator.mul, 3)
>>> multiply_by_3(10)
30
Decorator
@closure_name
def function_that_gets_passed_to_closure():
...
Debugger example:
from functools import wraps
def debug(func):
@wraps(func) # Needed for metadata copying (func name, ...).
def out(*args, **kwargs):
print(func.__name__)
return func(*args, **kwargs)
return out
@debug
def add(x, y):
return x + y
Class
class <name>:
def __init__(self, a):
self.a = a
def __str__(self):
return str(self.a)
def __repr__(self):
return str({'a': self.a}) # Or: return f'{self.__dict__}'
@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
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() # Can be used for automatic indexing.
...
@classmethod
def get_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', ['knife', 'fork', 'spoon'])
Cutlery = Enum('Cutlery', 'knife fork spoon')
Cutlery = Enum('Cutlery', {'knife': 1, 'fork': 2, 'spoon': 3})
# Functions can not be values, so they must be enclosed in tuple:
LogicOp = Enum('LogicOp', {'AND': (lambda l, r: l and r, ),
'OR' : (lambda l, r: l or r, )})
# But 'list(<enum>)' will only work if there is another value in the tuple:
LogicOp = Enum('LogicOp', {'AND': (auto(), lambda l, r: l and r),
'OR' : (auto(), lambda l, r: l or r)})
System
Arguments
import sys
script_name = sys.argv[0]
arguments = sys.argv[1:]
Read File
def read_file(filename):
with open(filename, encoding='utf-8') as file:
return file.readlines()
Write 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']
Execute Command
import os
<str> = os.popen(<command>).read()
Or:
>>> import subprocess
>>> a = subprocess.run(['ls', '-a'], stdout=subprocess.PIPE)
>>> a.stdout
b'.\n..\nfile1.txt\nfile2.txt\n'
>>> a.returncode
0
Input
filename = input('Enter a file name: ')
Prints lines until EOF:
while True:
try:
print(input())
except EOFError:
break
Recursion Limit
>>> sys.getrecursionlimit()
1000
>>> sys.setrecursionlimit(10000)
JSON
import json
Serialization
<str> = json.dumps(<object>, ensure_ascii=True, indent=None)
<dict> = json.loads(<str>)
To preserve order:
from collections import OrderedDict
<dict> = json.loads(<str>, object_pairs_hook=OrderedDict)
Read File
def read_json_file(filename):
with open(filename, encoding='utf-8') as file:
return json.load(file)
Write to 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)
SQLite
import sqlite3
db = sqlite3.connect(<filename>)
Read
cursor = db.execute(<query>)
if cursor:
<tuple> = cursor.fetchone() # First row.
<list> = cursor.fetchall() # Remaining rows.
db.close()
Write
db.execute(<query>)
db.commit()
Pickle
>>> import pickle
>>> favorite_color = {'lion': 'yellow', 'kitty': 'red'}
>>> pickle.dump(favorite_color, open('data.p', 'wb'))
>>> pickle.load(open('data.p', 'rb'))
{'lion': 'yellow', 'kitty': 'red'}
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
Bytes
Bytes objects are immutable sequences of single bytes.
Encode
<Bytes> = b'<str>'
<Bytes> = <str>.encode(encoding='utf-8')
<Bytes> = <int>.to_bytes(<length>, byteorder='big|little', signed=False)
<Bytes> = bytes.fromhex(<hex>)
Decode
<str> = <Bytes>.decode('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):
with open(filename, 'wb') as file:
file.write(bytes)
<Bytes> = b''.join(<list_of_Bytes>)
Struct
This module performs conversions between Python values and C struct represented as Python Bytes object.
from struct import pack, unpack
<Bytes> = pack('<format>', <value_1> [, <value_2>, ...])
<tuple> = 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
Use capital leters for unsigned type.
'x'
- pad byte'c'
- char'h'
- short'i'
- int'l'
- long'q'
- long long'f'
- float'd'
- double
Hashlib
>>> hashlib.md5(<str>.encode()).hexdigest()
'33d0eba106da4d3ebca17fcd3f4c3d77'
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()
Itertools
Every function returns an iterator and can accept any collection and/or iterator. If you want to print the iterator, you need to pass it to the list() function.
from itertools import *
Combinatoric iterators
>>> 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')]
>>> product('ab', [1, 2])
[('a', 1), ('a', 2),
('b', 1), ('b', 2)]
>>> 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)]
Infinite iterators
>>> i = count(5, 2)
>>> next(i), next(i), next(i)
(5, 7, 9)
>>> a = cycle('abc')
>>> [next(a) for _ in range(10)]
['a', 'b', 'c', 'a', 'b', 'c', 'a', 'b', 'c', 'a']
>>> repeat(10, 3)
[10, 10, 10]
Iterators
>>> chain([1, 2], range(3, 5))
[1, 2, 3, 4]
>>> compress('abc', [True, 0, 1])
['a', 'c']
>>> islice([1, 2, 3], 1, None) # islice(<seq>, from_inclusive, to_exclusive)
[2, 3]
>>> people = [{'id': 1, 'name': 'bob'},
{'id': 2, 'name': 'bob'},
{'id': 3, 'name': 'peter'}]
>>> {name: list(ppp) for name, ppp in groupby(people, key=lambda p: p['name'])}
{'bob': [{'id': 1, 'name': 'bob'},
{'id': 2, 'name': 'bob'}],
'peter': [{'id': 3, 'name': 'peter'}]}
Introspection and Metaprograming
Inspecting code at runtime and code that generates code. You can:
- Look at the attributes
- Set new attributes
- Create functions dynamically
- Traverse the parent classes
- Change values in the class
Variables
<list> = dir() # In-scope variables.
<dict> = locals() # Local variables.
<dict> = globals() # Global variables.
Attributes
>>> class Z:
... def __init__(self):
... self.a = 'abcde'
... self.b = 12345
>>> z = Z()
>>> vars(z)
{'a': 'abcde', 'b': 12345}
>>> getattr(z, 'a')
'abcde'
>>> hasattr(z, 'c')
False
>>> setattr(z, 'c', 10)
Parameters
Getting the number of parameters of a function:
from inspect import signature
sig = signature(<function>)
no_of_params = len(sig.parameters)
Type
Type is the root class. If only passed the object it returns it's type. Otherwise it creates a new class (and not the instance!):
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):
...
return type(name, parents, attrs)
Or:
class MyMetaClass(type):
def __new__(klass, name, parents, attrs):
...
return type.__new__(klass, 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 BlaBla:
__metaclass__ = Bla
Operator
from operator import add, sub, mul, truediv, floordiv, mod, pow, neg, abs, \
eq, ne, lt, le, gt, ge, \
not_, and_, or_, \
itemgetter
product_of_elems = functools.reduce(mul, <list>)
sorted_by_second = sorted(<list>, key=itemgetter(1))
sorted_by_both = sorted(<list>, key=itemgetter(0, 1))
Eval
Basic
>>> from ast import literal_eval
>>> literal_eval('1 + 2')
3
>>> literal_eval('[1, 2, 3]')
[1, 2, 3]
Using Abstract Syntax Trees
import ast
from ast import Num, BinOp, UnaryOp
import operator as op
legal_operators = {ast.Add: op.add,
ast.Sub: op.sub,
ast.Mult: op.mul,
ast.Div: op.truediv,
ast.Pow: op.pow,
ast.BitXor: op.xor,
ast.USub: op.neg}
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()))
Libraries
Plot
# $ pip3 install matplotlib
from matplotlib import pyplot
pyplot.plot(<data_1> [, <data_2>, ...])
pyplot.show()
pyplot.savefig(<filename>, transparent=True)
Progress Bar
# $ pip3 install tqdm
from tqdm import tqdm
from time import sleep
for i in tqdm(range(100)):
sleep(0.02)
for i in tqdm([1, 2, 3]):
sleep(0.2)
Table
Prints CSV file as ASCII table:
# $ pip3 install tabulate
from csv import reader
from tabulate import tabulate
with open(<filename>, newline='') as csv_file:
reader = reader(csv_file, delimiter=';')
headers = [a.title() for a in next(reader)]
print(tabulate(reader, headers))
Curses
# $ 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)
Image
Creates PNG image of greyscale gradient:
# $ pip3 install pillow
from PIL import Image
width, height = 100, 100
img = Image.new('L', (width, height), 'white')
img.putdata([255*a/(width*height) for a in range(width*height)])
img.save('out.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
Saves a list of floats with values between 0 and 1 to a WAV file:
import wave, struct
frames = [struct.pack('h', int((a-0.5)*60000)) for a in <list>]
wf = wave.open(<filename>, 'wb')
wf.setnchannels(1)
wf.setsampwidth(4)
wf.setframerate(44100)
wf.writeframes(b''.join(frames))
wf.close()
Url
from urllib.parse import quote, quote_plus, unquote, unquote_plus
Encode
>>> quote("Can't be in URL!")
'Can%27t%20be%20in%20URL%21'
>>> quote_plus("Can't be in URL!")
'Can%27t+be+in+URL%21'
Decode
>>> unquote('Can%27t+be+in+URL%21')
"Can't+be+in+URL!"'
>>> unquote_plus('Can%27t+be+in+URL%21')
"Can't be in URL!"
Scraping
# $ pip3 install requests beautifulsoup4
>>> import requests
>>> from bs4 import BeautifulSoup
>>> page = requests.get('https://en.wikipedia.org/wiki/Python_(programming_language)')
>>> document = BeautifulSoup(page.text, 'html.parser')
>>> table = document.find('table', class_='infobox vevent')
>>> rows = table.find_all('tr')
>>> website = rows[11].find('a')['href']
'https://www.python.org/'
>>> latest_v = rows[6].find('div').text.split()[0]
'3.7.2'
Web
# $ pip3 install bottle
import bottle
from urllib.parse import unquote
Run
bottle.run(host='localhost', port=8080)
bottle.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):
sport = unquote(sport).lower()
page = read_file(sport)
return template(page)
REST Request
@post('/odds/<sport>')
def odds_handler(sport):
team = bottle.request.forms.get('team')
team = unquote(team).lower()
db = sqlite3.connect(<db_path>)
home_odds, away_odds = get_odds(db, sport, team)
db.close()
response.headers['Content-Type'] = 'application/json'
response.headers['Cache-Control'] = 'no-cache'
return json.dumps([home_odds, away_odds])
Profile
Basic
from time import time
start_time = time()
...
duration = time() - start_time
Timing a Snippet
from timeit import timeit
timeit('"-".join(str(a) for a in range(100))',
number=10000, globals=globals())
Line Profiler
# $ pip3 install line_profiler
@profile
def main():
a = [(i%3 + 1) * 3 for i in range(10000)]
b = [i ** (i/10000) for i in range(10000)]
main()
$ kernprof -lv test.py
Line # Hits Time Per Hit % Time Line Contents
==============================================================
1 @profile
2 def main():
3 1 6196.0 6196.0 53.2 a = [(i%3 + 1) * 3 for i in range(10000)]
4 1 5455.0 5455.0 46.8 b = [i ** (i/10000) for i in range(10000)]
Call Graph
Generates a PNG image of call graph with highlighted bottlenecks.
# $ pip3 install pycallgraph
from pycallgraph import output, PyCallGraph
from datetime import datetime
graph = output.GraphvizOutput()
time_str = datetime.now().strftime('%Y%m%d%H%M%S')
graph.output_file = f'profile-{time_str}.png'
with PyCallGraph(output=graph):
<code_to_be_profiled>
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()