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Python ZTM Cheatsheet

Python ZTM Cheatsheet πŸ’»πŸš€

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
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# 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
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# 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
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# Converting Strings to Numbers
age = input("How old are you?")
age = int(age)
pi = input("What is the value of pi?")
pi = float(pi)
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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 # **********
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# 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

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# 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
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# Palindrome check
word = 'reviver'
p = bool(word.find(word[::-1]) + 1)
print(p) # True
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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.
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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 ]
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# 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.
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# Copy a List
basket = ['apples', 'pears', 'oranges']
new_basket = basket.copy()
new_basket2 = basket[:]
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# 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] # 
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# 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
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# 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
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# 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
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# 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)]

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# 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]
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# 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}]
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# Read line of a file into a list
with open("myfile.txt") as f:
  lines = [line.strip() for line in f]
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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)
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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.
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# 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
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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'
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# Immutability
my_tuple[1] = 'donuts'  # TypeError
my_tuple.append('candy')# AttributeError
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# Methods
my_tuple.index('grapes') # 1
my_tuple.count('grapes') # 2
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# Zip
list(zip([1,2,3], [4,5,6])) # [(1, 4), (2, 5), (3, 6)]
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# unzip
z = [(1, 2), (3, 4), (5, 6), (7, 8)] # Some output of zip() function
unzip = lambda z: list(zip(*z))
unzip(z)
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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!
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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}
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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.

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# Frozenset
# hashable --> it can be used as a key in a dictionary or as an element in a set.
<frozenset> = frozenset(<collection>)
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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
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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
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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
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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
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# waiting until user quits
msg = ''
while msg != 'quit':
    msg = input("What should I do?")
    print(msg)
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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]
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Enumerate

for i, el in enumerate('helloo'):
  print(f'{i}, {el}')
# 0, h
# 1, e
# 2, l
# 3, l
# 4, o
# 5, o
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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)
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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')
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from collections import namedtuple
Person = namedtuple('Person', 'name height')
person = Person('Jean-Luc', 187)
f'{person.height}'           # '187'
'{p.height}'.format(p=person)# '187'
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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)

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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)
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* 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
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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)
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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}
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head, *body, tail = [1,2,3,4,5]
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Lambda

# lambda: <return_value>
# lambda <argument1>, <argument2>: <return_value>
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# Factorial
from functools import reduce

n = 3
factorial = reduce(lambda x, y: x*y, range(1, n+1))
print(factorial) #6
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# Fibonacci
fib = lambda n : n if n <= 1 else fib(n-1) + fib(n-2)
result = fib(10)
print(result) #55
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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}
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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)
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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]
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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
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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
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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
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>>> multiply_by_3 = get_multiplier(3)
>>> multiply_by_3(10)
30
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  • 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
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>>> counter = get_counter()
>>> counter(), counter(), counter()
(1, 2, 3)
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Modules

if __name__ == '__main__': # Runs main() if file wasn't imported.
    main()
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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 *
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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.
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Generators

Convenient way to implement the iterator protocol.

def count(start, step):
    while True:
        yield start
        start += step
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>>> counter = count(10, 2)
>>> next(counter), next(counter), next(counter)
(10, 12, 14)
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Decorators

A decorator takes a function, adds some functionality and returns it.

@decorator_name
def function_that_gets_passed_to_decorator():
    ...
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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
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  • 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__
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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
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Multiple Inheritance

class A: pass
class B: pass
class C(A, B): pass
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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'>]
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Exceptions

try:
  5/0
except ZeroDivisionError:
  print("No division by zero!")
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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
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Raising Exception

raise ValueError('some error message')
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Finally

try:
  raise KeyboardInterrupt
except:
  print('oops')
finally:
  print('All done!')

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Command Line Arguments

import sys
script_name = sys.argv[0]
arguments   = sys.argv[1:]
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File IO

Opens a file and returns a corresponding file object.

<file> = open('<path>', mode='r', encoding=None)
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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.
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<str/bytes> = <file>.readline()     # Returns a line.
<list>      = <file>.readlines()    # Returns a list of lines.
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<file>.write(<str/bytes>)           # Writes a string or bytes object.
<file>.writelines(<list>)           # Writes a list of strings or bytes objects.
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  • 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)
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Write Text to File

def write_to_file(filename, text):
    with open(filename, 'w', encoding='utf-8') as file:
        file.write(text)
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Append Text to File

def append_to_file(filename, text):
    with open(filename, 'a', encoding='utf-8') as file:
        file.write(text)
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Useful Libraries

CSV

import csv
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Read Rows from CSV File

def read_csv_file(filename):
    with open(filename, encoding='utf-8') as file:
        return csv.reader(file, delimiter=';')
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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)
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JSON

import json
<str>    = json.dumps(<object>, ensure_ascii=True, indent=None)
<object> = json.loads(<str>)
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Read Object from JSON File

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

import pickle
<bytes>  = pickle.dumps(<object>)
<object> = pickle.loads(<bytes>)
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Read Object from File

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

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

Basic

from time import time
start_time = time()  # Seconds since
...
duration = time() - start_time
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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
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Statistics

from statistics import mean, median, variance, pvariance, pstdev
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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
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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
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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)
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  • 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.
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Timezone

<tz>     = UTC                              # UTC timezone.
<tz>     = tzlocal()                        # Local timezone.
<tz>     = gettz('<Cont.>/<City>')          # Timezone from 'Continent/City_Name' str.
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<DTa>    = <DT>.astimezone(<tz>)            # Datetime, converted to passed timezone.
<Ta/DTa> = <T/DT>.replace(tzinfo=<tz>)      # Unconverted object with new timezone.
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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.
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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.
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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
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Credits

Inspired by: https://zerotomastery.io/cheatsheets/python-cheat-sheet

Connect with me:

AmnaAbd's Discord Amna Abdallah | Twitter AmnaAbd's LinkedIN Amna's Spotify amnaabd amnaabd amnaabd

Top comments (1)

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mccurcio profile image
Matt Curcio

Wow, I learned something new after reading your article.
Good Job!