Curated List of Popular Python Learning Resources and Tools

This article compiles a comprehensive, curated collection of popular Python resources—including frameworks, libraries, applications, books, tutorials, interview questions, data‑structure and algorithm guides, and learning tools—suitable for developers at any skill level seeking to deepen their Python knowledge.

Python Code Repositories

Awesome Python: a curated list of Python frameworks, libraries, software, and resources. https://github.com/vinta/awesome-python

A Chinese version of the list, previously recommended: https://github.com/jobbole/awesome-python-cn

Awesome Python 2: a carefully selected collection of Python frameworks, libraries, software, and resources. https://github.com/trananhkma/fucking-awesome-python

Awesome Python Applications: nearly 400 open‑source Python apps organized by topic, with links to codebases and documentation generated from structured data. https://github.com/mahmoud/awesome-python-applications

Awesome PyTorch: a list of libraries related to PyTorch, the popular tensor and dynamic neural‑network machine‑learning framework. https://github.com/bharathgs/Awesome-pytorch-list

Awesome Asyncio: a curated list of Python asynchronous frameworks, libraries, software, and resources. https://github.com/timofurrer/awesome-asyncio

Awesome Jupyter: an impressive list of Jupyter projects, libraries, and resources for creating and sharing Python notebooks with live code, equations, visualizations, and text. https://github.com/markusschanta/awesome-jupyter

Awesome Python Books: a curated list of the best books on Python. https://github.com/Junnplus/awesome-python-books

Books and Documentation

Python Guide: best‑practice manual for installing, configuring, and using Python, covering pip, numpy, virtualenv, etc. https://github.com/realpython/python-guide

Python Chinese Guide: a beginner‑friendly tutorial with abundant code examples. https://github.com/iswbm/python-guide

Byte of Python: a concise tutorial for beginners, requiring only the ability to save a text file. https://github.com/swaroopch/byte-of-python

Cosmic Python: free O'Reilly book on application‑architecture patterns in Python. https://github.com/cosmicpython/book

PyCharm Chinese Guide: a guide for Python developers with over 100 GIF‑illustrated tips to boost productivity. https://github.com/iswbm/pycharm-guide

Python Black Magic Handbook: documentation on advanced Python tricks. https://github.com/iswbm/magic-python

Python Machine Learning: repository of classic machine‑learning tutorial notebooks. https://github.com/rasbt/python-machine-learning-book-3rd-edition

Interview Questions

CTCI Python: classic Python programming interview questions. https://github.com/StBogdan/CTCI_python

Interactive Coding Challenges: over 120 continuously updated, interactive, test‑driven coding interview problems. https://github.com/donnemartin/interactive-coding-challenges

Python Interview Questions: common interview questions. https://github.com/sigmavirus24/python-interview-questions

Python Interview Questions 2: an additional 300+ interview questions. https://github.com/learning-zone/python-interview-questions

Data Structures and Algorithms

Algorithms: Python 3 data structures and algorithms with simple, clean implementations (18k stars). https://github.com/keon/algorithms

Udemy Algorithms, Data Structures, and Interviews: notebooks from Udemy courses to help interview preparation. https://github.com/jmportilla/Python-for-Algorithms--Data-Structures--and-Interviews

Algorithms by prakhar1989: implementations of algorithms and data structures for joyful learning. https://github.com/prakhar1989/Algorithms

Python Resources

GitHub Trending Python: popular Python repositories on GitHub. https://github.com/trending/python

pep8: a tool to check Python code against PEP 8 style guidelines. https://github.com/treyhunner/pep8

Google Style Guide: Python style guide recommended by Google. https://github.com/google/styleguide

Python Enhancement Proposals (PEPs): official index of Python enhancements. https://github.com/python/peps

Learning Python

Python Koans: an interactive tutorial for learning Python via tests (TDD intro). https://github.com/gregmalcolm/python_koans

Project‑based Learning: list of project‑oriented tutorials, e.g., web scrapers, bots. https://github.com/tuvtran/project-based-learning#python

Learn Python 3 with Jupyter Notebook: series of interactive notebooks. https://github.com/jerry-git/learn-python3

For a more detailed Python self‑study roadmap, see this detailed Python self‑learning map .