A curated list of Python books (print + legit free online editions), inspired by GoBooks.
Last updated: 2026-01-25
- Beginner
- Core Python & Level Up
- Clean Code, Design & Architecture
- Testing
- Packaging, Tooling & Project Setup
- Web Development
- Data Analysis & Visualization
- Machine Learning & AI
- Automation & Scripting
- DevOps, Systems & Cloud
- Concurrency & Performance
- Free & Official “Books” (Docs / Open Editions)
- Contributing
- License
- (2025) Automate the Boring Stuff with Python (3rd Edition) — Al Sweigart. Practical beginner-friendly projects to automate everyday tasks (files, spreadsheets, web, PDFs, and more).
- (2023) Python Crash Course (3rd Edition) — Eric Matthes. A fast, project-based intro that gets you building real apps quickly.
- (2024) Think Python (3rd Edition) — Allen Downey. Concept-first learning with clear explanations, exercises, and notebook-friendly examples. Free online edition.
- (2019) Introducing Python (2nd Edition) — Bill Lubanovic. A broad, approachable tour of Python fundamentals plus common libraries and tasks.
- (2018) Serious Python — Julien Danjou. “Black-belt” tips on writing and shipping Python more like a pro.
- (2024) Effective Python (3rd Edition) — Brett Slatkin. 125 concrete best practices that sharpen your Python style and avoid subtle gotchas.
- (2022) Fluent Python (2nd Edition) — Luciano Ramalho. Deep dive into idiomatic Python, data models, protocols, and modern features.
- (2021) Python Distilled — David Beazley. A concise “what matters most” guide to core Python concepts with crisp examples.
- (2017) Python Tricks — Dan Bader. Bite-sized patterns and language features that make your code more Pythonic.
- (2013) Python Cookbook (3rd Edition) — David Beazley, Brian K. Jones. Recipe-style solutions to common problems, from text to iterators to concurrency.
- (2025) Clean Architecture with Python — Packt (Sam Keen). Applies clean architecture principles to Python apps with maintainability and scaling in mind.
- (2021) Robust Python — Patrick Viafore. Uses typing, boundaries, and disciplined design to make Python code safer and easier to change.
- (2020) Architecture Patterns with Python — Harry Percival, Bob Gregory. Practical patterns (DDD-ish boundaries, message buses, etc.) for bigger Python systems. Free to read online.
- (2022) Python Testing with pytest (2nd Edition) — Brian Okken. Modern pytest workflows: fixtures, parametrization, plugins, and maintainable test suites.
- (2020) Practices of the Python Pro — Dane Hillard. Teaches professional habits: modularity, readability, refactoring, and process—not just syntax.
- (2017) Test-Driven Development with Python (2nd Edition) — Harry J.W. Percival. Build a web app end-to-end using TDD with Django + Selenium. Free to read online (with purchase options).
- (2024) Hypermodern Python Tooling — Claudio Jolowicz. Modern project setup: packaging, deps, linting, types, tests, CI, and automation.
- (2017) The Hitchhiker’s Guide to Python — Community. Opinionated best practices for structuring projects, tooling, and “doing Python” well. Free online.
- (2024) Django for Beginners (5th Edition) — William S. Vincent. Beginner-friendly Django projects that walk you from zero to deployed apps.
- (2024) Django 5 By Example (5th Edition) — Antonio Mele. Learn Django by building multiple real-world apps step by step.
- (2023) FastAPI: Modern Python Web Development — Bill Lubanovic. Practical FastAPI patterns: validation, auth, databases, performance, and deployment.
- (2018) Flask Web Development (2nd Edition) — Miguel Grinberg. Classic Flask guide: blueprints, forms, auth, testing, and production basics.
- (2020) Two Scoops of Django 3.x — Daniel & Audrey Feldroy. Opinionated best practices for Django project structure and conventions (great, but dated vs Django 5/6).
- (2022) Python for Data Analysis (3rd Edition) — Wes McKinney. The definitive pandas-first guide to wrangling, cleaning, and analyzing data. Free open-access edition.
- (2017) Python Data Science Handbook — Jake VanderPlas. Practical tour of NumPy, pandas, Matplotlib, and scikit-learn basics. Free online edition.
- (2022) Hands-On Machine Learning (3rd Edition) — Aurélien Géron. A hands-on ML path from classic models to deep learning with real code and intuition.
- (2022) Natural Language Processing with Transformers (Revised Edition) — Tunstall, von Werra, Wolf. Hugging Face–centric NLP: fine-tuning, evaluation, and shipping transformer models.
- (2021) Deep Learning with Python (2nd Edition) — François Chollet. Keras-first deep learning with practical recipes and the “why” behind them.
- (2025) Automate the Boring Stuff with Python (3rd Edition) — Al Sweigart. The same book’s official online version for learning by doing. Free online edition.
- (2017) Python for Everybody — Charles Severance. A gentle intro focused on practical programming and problem solving. Free online edition.
- (2020) Python for DevOps — Noah Gift, Kennedy Behrman, Alfredo Deza, Grig Gheorghiu. Automate infra tasks and build reliable DevOps workflows with Python.
- (2022) Python Concurrency with asyncio — Matthew Fowler. Learn async/await deeply by building real concurrent programs and services.
- (2020) High Performance Python (2nd Edition) — Micha Gorelick, Ian Ozsvald. Profiling-first performance work: data structures, parallelism, and speeding up hot paths.
- The Python Tutorial (Official Docs) — The canonical “start here” tutorial from the Python core team. Free.
- Python HOWTOs (Official Docs) — Focused guides on specific topics (logging, Unicode, sorting, etc.). Free.
- Python Packaging User Guide — Official packaging guide (build, publish, dependencies, best practices). Free.
- Django Documentation — The source of truth for Django features and APIs. Free.
- FastAPI Documentation — Excellent docs with examples and explanations. Free.
- Use legal links (publisher / author site / official free edition).
- Prefer the latest edition when it exists.
- One entry per bullet:
- (YEAR) [Title](link) — Author. One-sentence description.
- Keep descriptions short (one sentence).
- If something is free to read online, add
*Free online edition.*at the end of the bullet.
- Suggested: CC0 1.0 (public domain dedication) for the list itself.