Download Python Cheat Sheet PDF for Quick Reference [2024]

Python is a high-level programming language used extensively in data research and software development. With dozens of modules and libraries to choose from, Python’s both a lucrative and easy-to-use language. Ever worked on a Python project and craved a Python commands cheat sheet to help you out? You’ve come to the right place.

Guido Van Rossum developed Python in 1991 when he released Python 0.9.0. Currently, the latest version of Python is Python 3.9.

If you’re a beginner, Python might feel intimidating. But with a little support, we’ll show you that it’s actually a rewarding and simple language. Today, we’ll present a Python cheat sheet, which will help you use Python with ease. By the end, you’ll be a pro at using everything about this programming language, including Python syntax.

If you have a basic understanding of Python and want an easy reference while developing Python applications, this Python 3 cheat sheet is for you.

Read on as we walk you through various Python commands or functions, operators, data types, data structures, and much more.

Let’s get started with our Python basics cheat sheet!

The Zen of Python

Before we get into our Python syntax cheat sheet, check out this poetic description of Python principles by Tim Peters:

>>> import this
The Zen of Python, by Tim Peters
Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!

Python Basics Cheat Sheet

Click here to download the Python Cheat Sheet PDF.

1. Math Operators

You can perform math operations like addition, subtraction, multiplication, and division using arithmetic operators in Python. You can also access several libraries that can help you with more advanced arithmetic problems. Here’s a quick list of some operators and their functions:

1. Find exponents

2. Find the remainder.

3. Perform Integer division.

4. Perform Division operations.

5. Perform Multiplication operations.

6. Perform Subtraction operations.

7. Perform Addition operations.

Examples

>>> 3 * 8 + 6 + 0
30
>>> (2 + 3) * 6
30
>>> 5 ** 6
15625

Complete Python Bootcamp From Zero to Hero in Python

2. Data Types

A data type is a mechanism to inform the compiler which data (integer, character, float, etc.) should be stored and how much memory to allocate as a result.

Here are Python’s data types:

Numbers (float, complex or floating-point)
Sequence (strings, list, tuples, etc.)
Boolean (True or False)
Set
Dictionary

>>> a = 5.5 # float datatype
>>> a
5.5
>>> a = 5 # int datatype
>>> a
5
>>> a = [1, 2, 3, 4, 5, 6] # list datatype
>>> a
[1, 2, 3, 4, 5, 6]
>>> a = 'hello' # string datatype
>>> a
'hello'
>>> a = {1, 2, 3} # set datatype
>>> a
{1, 2, 3}
>>> a = True # boolean datatype
>>> a
True
>>> a = {1: 2} # dictionary datatype
>>> a
{1: 2}

3. Variables

A variable is a memory area where data is kept in any programming language. This area is usually present inside the RAM at a given address. Variables may hold any value, including numbers, text, and true/false values. As a result, if you wish to use that value at any point in the program, you may simply use the variable that has that value.

It's worth noting that because Python isn't a highly typed language, you don't have to specify the type of variable based on the value it holds. The type of data stored in a variable will be decoded implicitly at run time in Python, and determined by the type of data stored in that variable.

>>> a = 'This is a string variable'
>>> a
'This is a string variable'

>>> a = 5
>>> a
5

4. Comments

A good programming practice is to leave comments for yourself and others, regardless of the programming language. While python is simpler to understand than Java, c++, and other languages, it’s only polite to leave comments to offer clarification on the file’s purpose.

Inline Comment

# This is an inline comment

Multiline Comment

"""
This is a
multiline comment
"""

5. Printing Output

The print() method sends a message to the screen or another standard output device. The message can be a string or another object, which will be converted to a string before being displayed on the screen.

>>> print('How are you?')
How are you?
>>> x = 10
>>> print('Hello world!', x)
Hello world! 10

6. input()

When the input() function is called, the program execution is halted until the user provides an input.

The input() Function
>>> print('How are you?')
>>> myStatus = input()
>>> print('Nice to meet you, {}'.format(myStatus))
How are you?
Al
Nice to meet you, Al

7. Len() Function

The len() function returns the number of elements in a sequential or a random data structure like list, string, set.

>>> len('Computer')
8

8. Typecasting Functions

Here’s how to convert integers to float or string:

>>> str(14)
'14'
>>> print('He is {} years old'.format(str(14)))
He is 14 years old.
>>> str(-4.89)
'-4.89'

Here’s how to convert float to integer:

>>> int(6.7)
6
>>> int(6.6) + 1
7

Flow Control

1. Comparison Operators

Equal to

Not equal to

Less than

Greater Than

Less than or Equal to

Greater than or Equal to

>>> 71 == 70
False
>>> 40 == 34
False
>>> 'man' == 'man'
True
>>> 'man' == 'Man'
False
>>> 'bat' != 'butterfly'
True
>>> 50 == 50.0
True
>>> 1 == '1'
False

2. Boolean Evaluation

>>> True == True
True
>>> True != False
True
>>> True is True
True
>>> True is not False
True
>>> if a is True:
>>> pass
>>> if a is not False:
>>> pass
>>> if a:
>>> pass
>>> if a is False:
>>> pass
>>> if a is not True:
>>> pass
>>> if not a:
>>> pass

3. Boolean Operators

There are three Boolean operators: and, or, and not.

Here’s the truth table for the “and” operator:

True and True True

True and False False

False and True False

False and False False

Here’s the truth table for the “not” operator

not True False

not False True

Finally, here’s the truth table for “or” operator

True or True True

True or False True

False or True True

False or False False

4. Mixing Boolean and Comparison Operators

>>> (43< 57) and (3 < 9)
True
>>> (14 < 15) and (92< 61)
False
>>> (1 == 3) or (4 == 4)
True

In addition to the comparison operators, you can use several Boolean operators in an expression:

>>> 2 + 2 == 4 and not 2 + 2 == 6 and 2 * 2 == 2 + 2
True

5. If-Else Statements

name = 'Peter'
if name == 'Peter':
 print('Hello, Peter')

Output

Hello, Peter

name = 'Mike'
if name == 'Peter':
 print('Hello, Peter.')
else:
 print('Hello, anonymous')

Output

Hello, anonymous

6. Combining If and Else (elif statement)

name = 'Mike'
age = 5
if name == 'Peter':
 print('Hi, Peter.')
elif age < 10:
 print('Your age is less than 10')
name = 'Mike'
age = 30
if name == 'Peter':
 print('Hello, Peter.')
elif age < 10:
 print('Your age is less than 12')
else:
 print('Your age is more than 10')

Output

Your age is less than 10

Your age is more than 10

7. While Loop Statements

While loop statements are used to run a block of code for a specified number of times:

var = 0
while var < 10:
 print('Hello, world.')
 var = var + 1

Output

Hello, world.

8. Break Statement

If the execution reaches a break statement, the iteration is stopped and the control exits from the loop.

var = 1
while True:
 print('This block of code is running...')
 if var == 10:
 break
 var += 1
print('Loop exited')

Output

This block of code is running...

Loop exited

9. Continue Statement

The control restarts from the beginning of the loop once the program encounters the continue statement.

var = 0
while var <= 10:
 var += 1
 if var == 5:
 continue
 print('This block of code is running for number... ', var)
print('Loop exited')

Output

This block of code is running for number... 1

This block of code is running for number... 2

This block of code is running for number... 3

This block of code is running for number... 4

This block of code is running for number... 6

This block of code is running for number... 7

This block of code is running for number... 8

This block of code is running for number... 9

This block of code is running for number... 10

This block of code is running for number... 11

Loop exited

10. For Loop

A for loop is controlled by a sequence, such as an iterator, a list, or another collection type. The body of the loop is run for each item in the series, and the loop finishes when the sequence is exhausted.

for var in range(1, 10):
 print("Loop running...")
print('Loop exited')

Output

Loop running...

Loop exited

11. Range Function

Programmers use Python's range() to run an iteration for a specified number of times. It takes the following arguments:

Start: the number that the sequence of integers should begin with.

Stop: the integer before which the integer sequence should be returned. Stop – 1 is the end of the integer range. Stop – 1 is the end of the integer range.

Step: the integer value that determines the increase between each integer in the sequence.

for var in range(1, 20, 2):
 print("Loop running with step size of 2...")
print('Loop exited')

Output

Loop running with step size of 2...

Loop exited

For-If- Else Statements Combined

For-if-else statements allow you to provide conditional statements inside the loops including the if, else and elif.

for var in range(1, 11):
 if(var%2==0):
 print("This is even integer")
 else:
 print("This is odd integer")
print('Loop exited')

Output

This is odd integer

This is even integer

This is odd integer

This is even integer

This is odd integer

This is even integer

This is odd integer

This is even integer

This is odd integer

This is even integer

Loop exited

Modules in Python

We can import other python module codes by importing file/function from other python modules using the import statement of Python. The import statement is the most frequent method of triggering the import mechanism, but it isn’t the only means for import.

import random
for i in range(5):
 print("Random integer is", random.randint(1, 30))

Output

Random integer is 8

Random integer is 10

Random integer is 11

Random integer is 3

Random integer is 8

We can also use the from statement to import a specified method of the module

from collections import Counter
List = [1, 2, 3, 4, 5, 5, 1]
Cnt = Counter(List)
print(Cnt)

Output

Counter({1: 2, 5: 2, 2: 1, 3: 1, 4: 1})

Function

A function is a reusable, ordered block of code that performs a single, connected activity. Functions provide your program more modularity and allow you to reuse a lot of code. Python also includes several built-in functions such as print(), but you may also construct your own.

def checkParity(num):
 if(num % 2 == 0):
 print("Number is even")
 else:
 print("Number is odd")
num = 5
checkParity(num)

Output

Number is odd

Here’s a function that returns something:

def checkParity(num):
 if(num % 2 == 0):
 return "Number is even"
 else:
 return "Number is odd"
num = 4
parity = checkParity(num)
print(parity)

Output

Number is even

Exception Handling

In programming languages, exceptions are circumstances in which an error occurs that prevents the code from continuing. If you divide anything by zero, for example, a runtime exception will occur, and the program will crash. However, you may write what to do in the program if such a case arises, which is known as exception handling. In Python, the main code is written inside the try block. The exceptions are handled inside the except block. The finally block is always executed regardless of an exception occurring.

def divideBy(num):
 try:
 print(10 / num)
 except:
 print("Cannot divide by 0")
 finally:
 print("Division finished")
num = 0
divideBy(num)

Output

Cannot divide by 0

Division finished

Lists in Python

A list is a sequence of heterogeneous elements in Python. It's similar to an array, except it may hold data from several sources. The values of a changeable list can be changed. We can use indexing to parse each value of the list or to access a list element.

>>> list = ['truck', 'car', 'submarine', 'jet']
>>> list
['truck', 'car', 'submarine', 'jet']
>>> list = ['truck', 'car', 'submarine', 'jet']
>>> list[0]
'truck'
>>> list[1]
'car'
>>> list[2]
'submarine'
>>> list[3]
'jet'

We can also use negative indexes with lists:

>>> list = ['truck', 'car', 'submarine', 'jet']
>>> list[-2]
'submarine'
>>> list[-3]
'car'
>>> 'The {} is larger than a {}.'.format(list[-2], list[-3])
'The submarine is larger than a car.'

Modifying a Value of an Element in a List

>>> list = ['truck', 'car', 'submarine', 'jet']
>>> list[1] = 'bike'
>>> list
['cat', 'bike', 'rat', 'elephant']
>>> list[2] = list[1]
>>> list
['cat', 'bike', 'bike', 'elephant']
>>> list[-1] = 54321
>>> list
['cat', 'bike', 'bike', 54321]

List Concatenation and List Replication

>>> [4, 5, 6] + ['P', 'Q', 'R']
[4, 5, 6, 'P', 'Q', 'R']
>>> ['A', 'B', 'C'] * 4
['A', 'B', 'C', 'A', 'B', 'C', 'A', 'B', 'C', 'A', 'B', 'C']
>>> list = [1, 2, 3]
>>> list = list + ['X', 'Y', 'Z']
>>> list
[1, 2, 3, 'X', 'Y', 'Z']

Removing Values from Lists

>>> list = ['truck', 'car', 'submarine', 'jet']
>>> del list[2]
>>> list
['truck', 'car', 'jet']
>>> del list[2]
>>> list
['truck', 'car']

Using for Loops with Lists for Traversal

>>> products = ['bag', 'rubber', 'knife', 'cooker']
>>> for i, product in enumerate(products):
>>> print('Index {} in products is: {}'.format(str(i), product))
Index 0 in products is: bag
Index 1 in products is: rubber
Index 2 in products is: knife
Index 3 in products is: cooker

Iterating through Multiple Lists with Zip()

>>> name = ['David', 'Mike', 'Tommy']
>>> age = [10, 31, 54]
>>> for n, a in zip(name, age):
>>> print('{} is {} years old'.format(n, a))
David is 10 years old
Mike is 31 years old
Tommy is 54 years old

The In and Not in Operators

>>> 'pen' in ['cap', 'owl', 'pen', 'rubber']
True
>>> list = ['cap', 'owl', 'pen', 'rubber']
>>> 'truck' in list
False
>>> 'pen' not in list
False
>>> 'train' not in list
True

Finding a Value in a List with the Index() Method

>>> list = ['notebook', 'pen', 'eraser', 'sharpener']
>>> list.index('pen')
1

Adding Values to Lists with the Append() and Insert() Methods

append()

>>> list = ['car', 'truck', 'bike']
>>> list.append('bicycle')
>>> list
['car', 'truck', 'bike', 'bicycle']

insert()

>>> list = ['car', 'truck', 'bike']
>>> list.insert(1, 'bicycle')
>>> list
['car', 'bicycle', 'truck', 'bike']

Removing Values from Lists with Remove()

>>> list = ['car', 'bike', 'submarine', 'jet']
>>> list.remove('bike')
>>> list
['car', 'submarine', 'jet']

If a value appears multiple times in the list, only the first instance of the value will be removed.

Sorting the Values in a List with the Sort() Method

>>> list = [2, 3, 1]
>>> list.sort()
>>> list
[1, 2, 3]

Dictionaries and Structuring Data

A Python dictionary is a collection of elements that are not in any particular order. A dictionary has a key: value pair, whereas other compound data types simply have value as an element.

The Keys(), Values(), and Items() Methods

Traversing the values:

>>> book = {'color': 'red', 'price': 160}
>>> for v in book.values():
>>> print(v)
red
160

Traversing the keys:

>>> for k in book.keys():
>>> print(k)
color
price

Traversing keys and values:

>>> for i in book.items():
>>> print(i)
('color', 'red')
('price', 160)

A for loop can iterate through the keys, values, or key-value pairs in a dictionary using the keys(), values(), and items() methods, respectively.

The Get() Method

Get() accepts two parameters: a key and a default value if the key isn't found.

>>> items = {'chairs': 5, 'tables': 2}
>>> 'There are {} tables.'.format(str(items.get('tables', 0)))
'There are 2 tables.'
>>> 'There are {} computers.'.format(str(items.get('computers', 0)))
'There are 0 computers.'

Check Key’s Presence in Dictionary

>>> 'color' in book
True

Sets

A set is an unordered collection of unique elements. Python sets are similar to mathematics sets, and allow all set related operations including union, intersection, and difference.

Creating a Set

You can generate sets by using curly braces {} and the built-in function set ():

>>> s = {2, 4, 6}
>>> s = set([2, 4, 6])

If you use curly braces {} to create an empty set, you'll get the data structure as a dictionary instead.

>>> s = {}
>>> type(s)
<class 'dict'>

All duplicate values are automatically removed by a set:

>>> s = {1, 2, 3, 2, 3, 4, 4, 5}
>>> s
{1, 2, 3, 4, 5}

Adding to the Set

>>> a = {1, 2, 3, 4, 5}
>>> a.add(6)
>>> a
{1, 2, 3, 4, 5, 6}
>>> set = {0, 1, 2, 3, 4}
>>> set.update([2, 3, 4, 5, 6])
>>> set
{0, 1, 2, 3, 4, 5, 6}

Removing from a Set

The remove() and discard() methods remove an element from the set; however remove() will throw a key error if the value isn't present.

>>> set = {1, 2, 3, 4}
>>> set.remove(4)
>>> set
{1, 2, 3}
>>> set.remove(3)
Traceback (most recent call last):
 File "<stdin>", line 1, in <module>
KeyError: 3

You can also use discard():

>>> s = {1, 2, 3, 4}
>>> s.discard(4)
>>> s
{1, 2, 3}
>>> s.discard(4)

Union of Multiple Sets

>>> s1 = {1, 2, 3, 4}
>>> s2 = {3, 4, 5, 6}
>>> s1.union(s2)
{1, 2, 3, 4, 5, 6}

Intersection of Multiple Sets

>>> s1 = {1, 2, 3, 4}
>>> s2 = {2, 3, 4}
>>> s3 = {3, 4, 5}
>>> s1.intersection(s2, s3)
{3, 4}

Difference of Two Sets

>>> s1 = {1, 2, 3}
>>> s2 = {2, 3, 4}
>>> s1.difference(s2)
{1}
>>> s2.difference(s1)
{4}

Symmetric Difference of Two Sets

>>> s1 = {1, 2, 3}
>>> s2 = {2, 3, 4}
>>> s1.symmetric_difference(s2)
{1, 4}

itertools Module

When dealing with iterators, the itertools module offers a set of quick and memory-efficient tools (like lists or dictionaries).

Accumulate()

Using accumulate() returns the results of a function as an iterator:

import itertools
import operator
data = [1, 2, 3, 4, 5]
result = itertools.accumulate(data, operator.mul)
for each in result:
 print(each)

Output

120

The operator.mul() takes two numbers and multiplies them:

operator.mul(3, 5)
15
operator.mul(4, 3)
12
operator.mul(6, 3)
18
operator.mul(2, 5)
10

We can also use the method without any iterator:

import itertools
data = [1, 2, 3, 4, 5, 6, 7]
result = itertools.accumulate(data)
for each in result:
 print(each)

Output

Combinations()

import itertools
shapes = [1, 2, 3, 4, 5]
combinations = itertools.combinations(shapes, 2)
for combination in combinations:
 print(combination)

Output

(1, 2)
(1, 3)
(1, 4)
(1, 5)
(2, 3)
(2, 4)
(2, 5)
(3, 4)
(3, 5)
(4, 5)

(1, 2)

(1, 3)

(1, 4)

(1, 5)

(2, 3)

(2, 4)

(2, 5)

(3, 4)

(3, 5)

(4, 5)

Combinations_with_Replacement()

import itertools
shapes = [1, 2, 3, 4, 5]
combinations = itertools.combinations_with_replacement(shapes, 2)
for combination in combinations:
 print(combination)

Output

(1, 1)
(1, 2)
(1, 3)
(1, 4)
(1, 5)
(2, 2)
(2, 3)
(2, 4)
(2, 5)
(3, 3)
(3, 4)
(3, 5)
(4, 4)
(4, 5)
(5, 5)

(1, 1)

(1, 2)

(1, 3)

(1, 4)

(1, 5)

(2, 2)

(2, 3)

(2, 4)

(2, 5)

(3, 3)

(3, 4)

(3, 5)

(4, 4)

(4, 5)

(5, 5)

Count()

A count takes the initial point and step size:

import itertools
for i in itertools.count(1, 3):
 print(i)
 if i >= 15:
 break

Output

Cycle()

Here is an itertools.cycle(iterable):

import itertools
arr = [1, 2, 3, 4, 5]
c = 0
for itr in itertools.cycle(arr):
 if(c > 20):
 break
 print(itr)
 c += 1

Output

Comprehensions

Dictionary Comprehension

>>> dict = {1: 2, 3: 4, 5: 6}
>>> {value: key for key, value in dict.items()}
{2: 1, 4: 3, 6: 5}

List Comprehension

>>> a= [i for i in range(1, 20)]
>>> a
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19]

Set Comprehension

>>> a = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}
>>> a = [i+1 for i in a]
>>> a
[2, 3, 4, 5, 6, 7, 8, 9, 10, 11]

Lambda Functions

Lambda functions are one-liner functions of Python:

>>> add = lambda a, b: a + b
>>> add(1, 2)
3

String Formatting

Using % Operator

>>> a = 4
>>> 'Value is %x' % a
'Value is 4'

.format()

>>> a = 4
>>> 'Value is {}'.format(a)
'Value is 4'

Formatted String Literals (F-Strings)

>>> a = 4
>>> f'Value is {a}'
'Value is 4'

Ternary Conditional Operator

We can write the conditional operators if and else in the single line using the ternary conditional operator:

>>> a = 5
>>> print('Number is even' if a % 2 ==0 else 'Number is odd')
Number is odd
>>>

Conclusion

Think of this Python cheat sheet as your one-stop-shop for quick questions about Python. As you can see, Python has all of the necessary functionalities and data structures to create end-to-end programs and applications.

For easy reference, download our Python Cheat Sheet PDF below:

Cheat Sheet

Ready to take your Python practice to the next level? Check out our list of cool, easy Python projects for beginners.

Happy coding!

Frequently Asked Questions

1. Is there a Python Cheat Sheet?

This Python cheat sheet provides you with everything you need to develop applications in Python. You can also download our Python Cheat Sheet PDF for easy reference.

2. What are Python Commands?

Python commands are functions that perform specific tasks when used. Some examples of Python commands are len, round, string, loop, type, find copy, etc.

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Download Python Cheat Sheet PDF for Quick Reference

The Zen of Python

Python Basics Cheat Sheet

1. Math Operators

Examples

Recommend Python Course

3. Variables

4. Comments

Inline Comment

Multiline Comment

5. Printing Output

6. input()

7. Len() Function

8. Typecasting Functions

Flow Control

1. Comparison Operators

2. Boolean Evaluation

3. Boolean Operators

4. Mixing Boolean and Comparison Operators

5. If-Else Statements

6. Combining If and Else (elif statement)

7. While Loop Statements

8. Break Statement

9. Continue Statement

10. For Loop

11. Range Function

Modules in Python

Function

Exception Handling

Lists in Python

Modifying a Value of an Element in a List

List Concatenation and List Replication

Removing Values from Lists

Using for Loops with Lists for Traversal

Iterating through Multiple Lists with Zip()

The In and Not in Operators

Finding a Value in a List with the Index() Method

Adding Values to Lists with the Append() and Insert() Methods

append()

insert()

Removing Values from Lists with Remove()

Sorting the Values in a List with the Sort() Method

Dictionaries and Structuring Data

The Keys(), Values(), and Items() Methods

The Get() Method

Check Key’s Presence in Dictionary

Sets

Creating a Set

Adding to the Set

Removing from a Set

Union of Multiple Sets

Intersection of Multiple Sets

Difference of Two Sets

Symmetric Difference of Two Sets

itertools Module

Accumulate()

Combinations()

Combinations_with_Replacement()

Count()

Cycle()

Comprehensions

Dictionary Comprehension