Python ZTM Cheatsheet 💻🚀
We created this Python 3 Cheat Sheet initially for students of Complete Python Developer in 2020: Zero to Mastery but we're now sharing it with any Python beginners to help them learn and remember common Python syntax and with intermediate and advanced Python developers as a handy reference. If you'd like to download a PDF version of this Python Cheat Sheet, you can get it here!
Contents
Python Types: Numbers,Strings,Boolean,Lists,Dictionaries, Tuples,Sets,None
Python Basics: Comparison Operators,Logical Operators,Loops,Range,Enumerate,Counter,Named Tuple,OrderedDict
Functions: Functions,Lambda,Comprehensions,Map,Filter,Reduce,Ternary,Any,All,Closures,Scope
Advanced Python: Modules,Iterators,Generators,Decorators,Class,Exceptions,Command Line Arguments,File IO,Useful Libraries
Numbers
python's 2 main types for Numbers is int and float (or integers and floating point numbers)
type(1) # int
type(-10) # int
type(0) # int
type(0.0) # float
type(2.2) # float
type(4E2) # float - 4*10 to the power of 2
# Arithmetic
10 + 3 # 13
10 - 3 # 7
10 * 3 # 30
10 ** 3 # 1000
10 / 3 # 3.3333333333333335
10 // 3 # 3 --> floor division - no decimals and returns an int
10 % 3 # 1 --> modulo operator - return the reminder. Good for deciding if number is even or odd
# Basic Functions
pow(5, 2) # 25 --> like doing 5**2
abs(-50) # 50
round(5.46) # 5
round(5.468, 2)# 5.47 --> round to nth digit
bin(512) # '0b1000000000' --> binary format
hex(512) # '0x200' --> hexadecimal format
# Converting Strings to Numbers
age = input("How old are you?")
age = int(age)
pi = input("What is the value of pi?")
pi = float(pi)
Strings
strings in python as stored as sequences of letters in memory
type('Hellloooooo') # str
'I\'m thirsty'
"I'm thirsty"
"\n" # new line
"\t" # adds a tab
'Hey you!'[4] # y
name = 'Andrei Neagoie'
name[4] # e
name[:] # Andrei Neagoie
name[1:] # ndrei Neagoie
name[:1] # A
name[-1] # e
name[::1] # Andrei Neagoie
name[::-1] # eiogaeN ierdnA
name[0:10:2]# Ade e
# : is called slicing and has the format [ start : end : step ]
'Hi there ' + 'Timmy' # 'Hi there Timmy' --> This is called string concatenation
'*'*10 # **********
# Basic Functions
len('turtle') # 6
# Basic Methods
' I am alone '.strip() # 'I am alone' --> Strips all whitespace characters from both ends.
'On an island'.strip('d') # 'On an islan' --> # Strips all passed characters from both ends.
'but life is good!'.split() # ['but', 'life', 'is', 'good!']
'Help me'.replace('me', 'you') # 'Help you' --> Replaces first with second param
'Need to make fire'.startswith('Need')# True
'and cook rice'.endswith('rice') # True
'bye bye'.index('e') # 2
'still there?'.upper() # STILL THERE?
'HELLO?!'.lower() # hello?!
'ok, I am done.'.capitalize() # 'Ok, I am done.'
'oh hi there'.find('i') # 4 --> returns the starting index position of the first occurrence
'oh hi there'.count('e') # 2
# String Formatting
name1 = 'Andrei'
name2 = 'Sunny'
print(f'Hello there {name1} and {name2}') # Hello there Andrei and Sunny - Newer way to do things as of python 3.6
print('Hello there {}, {}'.format(name1, name2))# Hello there Andrei and Sunny
print('Hello there %s and %s' %(name1, name2)) # Hello there Andrei and Sunny --> you can also use %d, %f, %r for integers, floats, string representations of objects respectively
# Palindrome check
word = 'reviver'
p = bool(word.find(word[::-1]) + 1)
print(p) # True
Boolean
True or False. Used in a lot of comparison and logical operations in Python
bool(True)
bool(False)
# all of the below evaluate to False. Everything else will evaluate to True in Python.
print(bool(None))
print(bool(False))
print(bool(0))
print(bool(0.0))
print(bool([]))
print(bool({}))
print(bool(()))
print(bool(''))
print(bool(range(0)))
print(bool(set()))
# See Logical Operators and Comparison Operators section for more on booleans.
Lists
Unlike strings, lists are mutable sequences in python
my_list = [1, 2, '3', True]# We assume this list won't mutate for each example below
len(my_list) # 4
my_list.index('3') # 2
my_list.count(2) # 1 --> count how many times 2 appears
my_list[3] # True
my_list[1:] # [2, '3', True]
my_list[:1] # [1]
my_list[-1] # True
my_list[::1] # [1, 2, '3', True]
my_list[::-1] # [True, '3', 2, 1]
my_list[0:3:2] # [1, '3']
# : is called slicing and has the format [ start : end : step ]
# Add to List
my_list * 2 # [1, 2, '3', True, 1, 2, '3', True]
my_list + [100] # [1, 2, '3', True, 100] --> doesn't mutate original list, creates new one
my_list.append(100) # None --> Mutates original list to [1, 2, '3', True, 100] # Or: <list> += [<el>]
my_list.extend([100, 200]) # None --> Mutates original list to [1, 2, '3', True, 100, 200]
my_list.insert(2, '!!!') # None --> [1, 2, '!!!', '3', True] - Inserts item at index and moves the rest to the right.
' '.join(['Hello','There'])# 'Hello There' --> Joins elements using string as separator.
# Copy a List
basket = ['apples', 'pears', 'oranges']
new_basket = basket.copy()
new_basket2 = basket[:]
# Remove from List
[1,2,3].pop() # 3 --> mutates original list, default index in the pop method is -1 (the last item)
[1,2,3].pop(1) # 2 --> mutates original list
[1,2,3].remove(2)# None --> [1,3] Removes first occurrence of item or raises ValueError.
[1,2,3].clear() # None --> mutates original list and removes all items: []
del [1,2,3][0] #
# Ordering
[1,2,5,3].sort() # None --> Mutates list to [1, 2, 3, 5]
[1,2,5,3].sort(reverse=True) # None --> Mutates list to [5, 3, 2, 1]
[1,2,5,3].reverse() # None --> Mutates list to [3, 5, 2, 1]
sorted([1,2,5,3]) # [1, 2, 3, 5] --> new list created
list(reversed([1,2,5,3]))# [3, 5, 2, 1] --> reversed() returns an iterator
# Useful operations
1 in [1,2,5,3] # True
min([1,2,3,4,5])# 1
max([1,2,3,4,5])# 5
sum([1,2,3,4,5])# 15
# Get First and Last element of a list
mList = [63, 21, 30, 14, 35, 26, 77, 18, 49, 10]
first, *x, last = mList
print(first) #63
print(last) #10
# Matrix
matrix = [[1,2,3], [4,5,6], [7,8,9]]
matrix[2][0] # 7 --> Grab first first of the third item in the matrix object
# Looping through a matrix by rows:
mx = [[1,2,3],[4,5,6]]
for row in range(len(mx)):
for col in range(len(mx[0])):
print(mx[row][col]) # 1 2 3 4 5 6
# Transform into a list:
[mx[row][col] for row in range(len(mx)) for col in range(len(mx[0]))] # [1,2,3,4,5,6]
# Combine columns with zip and *:
[x for x in zip(*mx)] # [(1, 3), (2, 4)]
# List Comprehensions
# new_list[<action> for <item> in <iterator> if <some condition>]
a = [i for i in 'hello'] # ['h', 'e', 'l', 'l', '0']
b = [i*2 for i in [1,2,3]] # [2, 4, 6]
c = [i for i in range(0,10) if i % 2 == 0]# [0, 2, 4, 6, 8]
# Advanced Functions
list_of_chars = list('Helloooo') # ['H', 'e', 'l', 'l', 'o', 'o', 'o', 'o']
sum_of_elements = sum([1,2,3,4,5]) # 15
element_sum = [sum(pair) for pair in zip([1,2,3],[4,5,6])] # [5, 7, 9]
sorted_by_second = sorted(['hi','you','man'], key=lambda el: el[1])# ['man', 'hi', 'you']
sorted_by_key = sorted([
{'name': 'Bina', 'age': 30},
{'name':'Andy', 'age': 18},
{'name': 'Zoey', 'age': 55}],
key=lambda el: (el['name']))# [{'name': 'Andy', 'age': 18}, {'name': 'Bina', 'age': 30}, {'name': 'Zoey', 'age': 55}]
# Read line of a file into a list
with open("myfile.txt") as f:
lines = [line.strip() for line in f]
Dictionaries
Also known as mappings or hash tables. They are key value pairs that are guaranteed to retain order of insertion starting from Python 3.7
my_dict = {'name': 'Andrei Neagoie', 'age': 30, 'magic_power': False}
my_dict['name'] # Andrei Neagoie
len(my_dict) # 3
list(my_dict.keys()) # ['name', 'age', 'magic_power']
list(my_dict.values()) # ['Andrei Neagoie', 30, False]
list(my_dict.items()) # [('name', 'Andrei Neagoie'), ('age', 30), ('magic_power', False)]
my_dict['favourite_snack'] = 'Grapes'# {'name': 'Andrei Neagoie', 'age': 30, 'magic_power': False, 'favourite_snack': 'Grapes'}
my_dict.get('age') # 30 --> Returns None if key does not exist.
my_dict.get('ages', 0 ) # 0 --> Returns default (2nd param) if key is not found
#Remove key
del my_dict['name']
my_dict.pop('name', None)
my_dict.update({'cool': True}) # {'name': 'Andrei Neagoie', 'age': 30, 'magic_power': False, 'favourite_snack': 'Grapes', 'cool': True}
{**my_dict, **{'cool': True} } # {'name': 'Andrei Neagoie', 'age': 30, 'magic_power': False, 'favourite_snack': 'Grapes', 'cool': True}
new_dict = dict([['name','Andrei'],['age',32],['magic_power',False]]) # Creates a dict from collection of key-value pairs.
new_dict = dict(zip(['name','age','magic_power'],['Andrei',32, False]))# Creates a dict from two collections.
new_dict = my_dict.pop('favourite_snack') # Removes item from dictionary.
# Dictionary Comprehension
{key: value for key, value in new_dict.items() if key == 'age' or key == 'name'} # {'name': 'Andrei', 'age': 32} --> Filter dict by keys
Tuples
Like lists, but they are used for immutable thing (that don't change)
my_tuple = ('apple','grapes','mango', 'grapes')
apple, grapes, mango, grapes = my_tuple# Tuple unpacking
len(my_tuple) # 4
my_tuple[2] # mango
my_tuple[-1] # 'grapes'
# Immutability
my_tuple[1] = 'donuts' # TypeError
my_tuple.append('candy')# AttributeError
# Methods
my_tuple.index('grapes') # 1
my_tuple.count('grapes') # 2
# Zip
list(zip([1,2,3], [4,5,6])) # [(1, 4), (2, 5), (3, 6)]
# unzip
z = [(1, 2), (3, 4), (5, 6), (7, 8)] # Some output of zip() function
unzip = lambda z: list(zip(*z))
unzip(z)
Sets
Unorderd collection of unique elements.
my_set = set()
my_set.add(1) # {1}
my_set.add(100)# {1, 100}
my_set.add(100)# {1, 100} --> no duplicates!
new_list = [1,2,3,3,3,4,4,5,6,1]
set(new_list) # {1, 2, 3, 4, 5, 6}
my_set.remove(100) # {1} --> Raises KeyError if element not found
my_set.discard(100) # {1} --> Doesn't raise an error if element not found
my_set.clear() # {}
new_set = {1,2,3}.copy()# {1,2,3}
set1 = {1,2,3}
set2 = {3,4,5}
set3 = set1.union(set2) # {1,2,3,4,5}
set4 = set1.intersection(set2) # {3}
set5 = set1.difference(set2) # {1, 2}
set6 = set1.symmetric_difference(set2)# {1, 2, 4, 5}
set1.issubset(set2) # False
set1.issuperset(set2) # False
set1.isdisjoint(set2) # False --> return True if two sets have a null intersection.
# Frozenset
# hashable --> it can be used as a key in a dictionary or as an element in a set.
<frozenset> = frozenset(<collection>)
None
None is used for absence of a value and can be used to show nothing has been assigned to an object
type(None) # NoneType
a = None
Comparison Operators
== # equal values
!= # not equal
> # left operand is greater than right operand
< # left operand is less than right operand
>= # left operand is greater than or equal to right operand
<= # left operand is less than or equal to right operand
<element> is <element> # check if two operands refer to same object in memory
Logical Operators
1 < 2 and 4 > 1 # True
1 > 3 or 4 > 1 # True
1 is not 4 # True
not True # False
1 not in [2,3,4]# True
if <condition that evaluates to boolean>:
# perform action1
elif <condition that evaluates to boolean>:
# perform action2
else:
# perform action3
Loops
my_list = [1,2,3]
my_tuple = (1,2,3)
my_list2 = [(1,2), (3,4), (5,6)]
my_dict = {'a': 1, 'b': 2. 'c': 3}
for num in my_list:
print(num) # 1, 2, 3
for num in my_tuple:
print(num) # 1, 2, 3
for num in my_list2:
print(num) # (1,2), (3,4), (5,6)
for num in '123':
print(num) # 1, 2, 3
for k,v in my_dict.items(): # Dictionary Unpacking
print(k) # 'a', 'b', 'c'
print(v) # 1, 2, 3
while <condition that evaluates to boolean>:
# action
if <condition that evaluates to boolean>:
break # break out of while loop
if <condition that evaluates to boolean>:
continue # continue to the next line in the block
# waiting until user quits
msg = ''
while msg != 'quit':
msg = input("What should I do?")
print(msg)
Range
range(10) # range(0, 10) --> 0 to 9
range(1,10) # range(1, 10)
list(range(0,10,2))# [0, 2, 4, 6, 8]
Enumerate
for i, el in enumerate('helloo'):
print(f'{i}, {el}')
# 0, h
# 1, e
# 2, l
# 3, l
# 4, o
# 5, o
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)
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')
from collections import namedtuple
Person = namedtuple('Person', 'name height')
person = Person('Jean-Luc', 187)
f'{person.height}' # '187'
'{p.height}'.format(p=person)# '187'
OrderedDict
- Maintains order of insertion
from collections import OrderedDict
# Store each person's languages, keeping # track of who responded first.
programmers = OrderedDict()
programmers['Tim'] = ['python', 'javascript']
programmers['Sarah'] = ['C++']
programmers['Bia'] = ['Ruby', 'Python', 'Go']
for name, langs in programmers.items():
print(name + '-->')
for lang in langs:
print('\t' + lang)
Functions
*args and **kwargs
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}
some_func(*args, **kwargs) # same as some_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
Ordering of parameters:
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 of *
[*[1,2,3], *[4]] # [1, 2, 3, 4]
{*[1,2,3], *[4]} # {1, 2, 3, 4}
(*[1,2,3], *[4]) # (1, 2, 3, 4)
{**{'a': 1, 'b': 2}, **{'c': 3}}# {'a': 1, 'b': 2, 'c': 3}
head, *body, tail = [1,2,3,4,5]
Lambda
# lambda: <return_value>
# lambda <argument1>, <argument2>: <return_value>
# Factorial
from functools import reduce
n = 3
factorial = reduce(lambda x, y: x*y, range(1, n+1))
print(factorial) #6
# Fibonacci
fib = lambda n : n if n <= 1 else fib(n-1) + fib(n-2)
result = fib(10)
print(result) #55
Comprehensions
<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}
output = [i+j for i in range(3) for j in range(3)] # [0, 1, 2, 1, 2, 3, 2, 3, 4]
# Is the same as:
output = []
for i in range(3):
for j in range(3):
output.append(i+j)
Ternary Condition
# <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]
Map Filter Reduce
from functools import reduce
list(map(lambda x: x + 1, range(10))) # [1, 2, 3, 4, 5, 6, 7, 8, 9,10]
list(filter(lambda x: x > 5, range(10))) # (6, 7, 8, 9)
reduce(lambda acc, x: acc + x, range(10)) # 45
Any All
any([False, True, False])# True if at least one item in collection is truthy, False if empty.
all([True,1,3,True]) # True if all items in collection are true
Closures
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'.
Scope
If variable is being assigned to anywhere in the scope, it is regarded as a local variable, unless it is declared as a 'global' or a 'nonlocal'.
def get_counter():
i = 0
def out():
nonlocal i
i += 1
return i
return out
>>> counter = get_counter()
>>> counter(), counter(), counter()
(1, 2, 3)
Modules
if __name__ == '__main__': # Runs main() if file wasn't imported.
main()
import <module_name>
from <module_name> import <function_name>
import <module_name> as m
from <module_name> import <function_name> as m_function
from <module_name> import *
Iterators
In this cheatsheet '<collection>' can also mean an iterator.
<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.
Generators
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)
Decorators
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
- Wraps is a helper decorator that copies metadata of function add() to function out().
- Without it
'add.__name__'would return'out'.
Class
User defined objects are created using the class keyword
class <name>:
age = 80 # Class Object Attribute
def __init__(self, a):
self.a = a # Object Attribute
@classmethod
def get_class_name(cls):
return cls.__name__
Inheritance
class Person:
def __init__(self, name, age):
self.name = name
self.age = age
class Employee(Person):
def __init__(self, name, age, staff_num):
super().__init__(name, age)
self.staff_num = staff_num
Multiple Inheritance
class A: pass
class B: pass
class C(A, B): pass
MRO determines the order in which parent classes are traversed when searching for a method:
>>> C.mro()
[<class 'C'>, <class 'A'>, <class 'B'>, <class 'object'>]
Exceptions
try:
5/0
except ZeroDivisionError:
print("No division by zero!")
while True:
try:
x = int(input('Enter your age: '))
except ValueError:
print('Oops! That was no valid number. Try again...')
else: # code that depends on the try block running successfully should be placed in the else block.
print('Carry on!')
break
Raising Exception
raise ValueError('some error message')
Finally
try:
raise KeyboardInterrupt
except:
print('oops')
finally:
print('All done!')
Command Line Arguments
import sys
script_name = sys.argv[0]
arguments = sys.argv[1:]
File IO
Opens a 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.
File
<file>.seek(0) # Moves to the start of the file.
<str/bytes> = <file>.readline() # Returns a line.
<list> = <file>.readlines() # Returns a list of lines.
<file>.write(<str/bytes>) # Writes a string or bytes object.
<file>.writelines(<list>) # Writes a list of strings or bytes objects.
- Methods do not add or strip trailing newlines.
Read Text from File
def read_file(filename):
with open(filename, encoding='utf-8') as file:
return file.readlines() # or read()
for line in read_file(filename):
print(line)
Write Text to File
def write_to_file(filename, text):
with open(filename, 'w', encoding='utf-8') as file:
file.write(text)
Append Text to File
def append_to_file(filename, text):
with open(filename, 'a', encoding='utf-8') as file:
file.write(text)
Useful Libraries
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)
Profile
Basic
from time import time
start_time = time() # Seconds since
...
duration = time() - start_time
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
random() # random float between 0 and 1
randint(0, 100) # random integer between 0 and 100
random_el = choice([1,2,3,4]) # select a random element from list
shuffle([1,2,3,4]) # shuffles a list
Datetime
- Module 'datetime' provides 'date'
<D>, 'time'<T>, 'datetime'<DT>and 'timedelta'<TD>classes. All are immutable and hashable. - Time and datetime can be 'aware'
<a>, meaning they have defined timezone, or 'naive'<n>, meaning they don't. - If object is naive it is presumed to be in system's timezone.
from datetime import date, time, datetime, timedelta
from dateutil.tz import UTC, tzlocal, gettz
Constructors
<D> = date(year, month, day)
<T> = time(hour=0, minute=0, second=0, microsecond=0, tzinfo=None, fold=0)
<DT> = datetime(year, month, day, hour=0, minute=0, second=0, ...)
<TD> = timedelta(days=0, seconds=0, microseconds=0, milliseconds=0,
minutes=0, hours=0, weeks=0)
- Use
'<D/DT>.weekday()'to get the day of the week (Mon == 0). 'fold=1'means second pass in case of time jumping back for one hour.
Now
<D/DTn> = D/DT.today() # Current local date or naive datetime.
<DTn> = DT.utcnow() # Naive datetime from current UTC time.
<DTa> = DT.now(<tz>) # Aware datetime from current tz time.
Timezone
<tz> = UTC # UTC timezone.
<tz> = tzlocal() # Local timezone.
<tz> = gettz('<Cont.>/<City>') # Timezone from 'Continent/City_Name' str.
<DTa> = <DT>.astimezone(<tz>) # Datetime, converted to passed timezone.
<Ta/DTa> = <T/DT>.replace(tzinfo=<tz>) # Unconverted object with new timezone.
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.
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
Credits
Inspired by: https://zerotomastery.io/cheatsheets/python-cheat-sheet
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Top comments (1)
Wow, I learned something new after reading your article.
Good Job!