Python is versatile, flexible, and a simple to debug programming language with extensive libraries and frameworks. Python is easy to learn and ideal for first time programmers.
We’ve compiled a list of the best cheat sheets you can use to learn Python programming to clear doubts and make your Python journey as seamless as possible.
gto76 is a comprehensive Python cheat sheet available on GitHub. The author (Jure Šorn) has included syntax for every Python concept, from basic to advanced. It covers lists, range, enumerates, tuple, dictionaries, generator, and iterator; data types, libraries such as Numpy, Games, Data, Image, Audio, Logging, Scraping, etc., threading, introspection, metaprogramming, and operators.
Mosh Hamedani has some serious street-cred in the programming world, thanks to his free Python tutorials on YouTube. He created this Python cheat sheet to cover core Python concepts like strings, variables, receiving inputs, operators, arithmetic operations, if statements, loops, tuples, functions, exceptions, dictionaries, classes, modules, and inheritance standard libraries, Pypi, and more.
Perso.limsi.fr is a single page cheat sheet explaining Python concepts. It covers Python 3 topics from beginner to intermediate, including basic concepts, modules, conversions, container types, conditionals, and more.
WebsiteSetup covers fundamental and intermediate Python concepts including data types, string creation, math operators, defining functions, lists, tuples, conditional statements, dictionaries, loops, dealing with exceptions, and troubleshooting errors. It is also available in PDF format.
Pythoncheatsheet.org is a comprehensive Python cheat sheet covering various topics, including Python fundamentals, functions, flow control, exception handling, data structures, lists, sets, loops, debugging, YAML, JSON, configuration files, data classes, context manager, virtual environments, and more.
DataCamp is extremely beneficial for Python beginners interested in data science. It covers data types, strings, variables, lists, Python scientific computing packages, Numpy arrays, libraries and more.
Cheatography is a two-page Python cheat sheet for quick reference. It covers Python sys variables, sys.argv, special methods, file methods, list methods, string methods, Python os variables, DateTime methods, and Python indexes and slices.
ehmatthes.github.io covers syntax rules as well as important concepts. The sheet discusses lists, dictionaries, loops, if and while statements, functions, classes, code testing, exceptions, and files, as well as Pygame, Plotly, Django, and Matplotlib.
Python for Data Science
Python for Data Science is a one-page Python cheat sheet to learn the fundamentals of this programming language, especially geared towards data science. It covers data types and conversions, variables and calculations, strings and operations methods, lists and operations and methods, libraries, and Numpy arrays.
Real Python uses syntax and examples to explain basic Python concepts. It covers primitives such as numbers, strings, and Booleans and collections such as lists and dictionaries, control statements, loops, and functions.