Appendix E — The guides, books, and codebases this guide draws on
Official documentation (the primary source for everything in this guide):
- The Python Tutorial and the Language and Library references.
- The HOWTOs, especially the Descriptor Guide, Logging HOWTO, and Free-threading HOWTO.
- "What's New in Python" for 3.13 and 3.14, and the PEPs cited in each chapter (8, 20, 446, 484, 517/621, 634, 659, 695, 703, 723, 734, 768, 779).
- The Python Packaging User Guide and the uv documentation.
- CPython's developer guide and internals docs.
Books (each one deepens a Part of this guide):
| Book | Deepens |
|---|---|
| Luciano Ramalho, Fluent Python (2nd ed.) | Parts I–III: the data model, iterators, decorators, descriptors, concurrency. The best single book on idiomatic Python. |
| Brett Slatkin, Effective Python (3rd ed.) | Part II and IX: 125 specific, tested recommendations |
| David Beazley & Brian K. Jones, Python Cookbook (3rd ed.) | recipes for Parts II–V |
| Anthony Shaw, CPython Internals | Ch 25–27: the compiler, eval loop, memory, and GIL in C |
| Micha Gorelick & Ian Ozsvald, High Performance Python (2nd ed.) | Ch 31–32, 53: profiling, NumPy, Cython, parallelism |
| Harry Percival & Bob Gregory, Architecture Patterns with Python | Ch 17, 67: composition, dependency injection, testable design |
| Brian Okken, Python Testing with pytest (2nd ed.) | Ch 20 |
| Wes McKinney, Python for Data Analysis (3rd ed., free online) | Ch 53–55, by the creator of pandas |
| Jake VanderPlas, Python Data Science Handbook (free online) | Ch 53–56 |
| Aurélien Géron, Hands-On Machine Learning with Scikit-Learn and PyTorch | Ch 56–58 |
| Sebastian Raschka, Build a Large Language Model (From Scratch) | Ch 58–59 and the AI guide's Part 10 |
Free courses and talks: Andrej Karpathy's Neural Networks: Zero to Hero (micrograd → makemore → GPT; the origin of Ch 57's design); the Real Python tutorials for focused topics; Raymond Hettinger's PyCon talks ("Transforming Code into Beautiful, Idiomatic Python", "Modern Python Dictionaries"); David Beazley's talks on generators and concurrency.
Codebases worth reading, smallest first: micrograd
(Ch 57), requests (Part VIII),
click, httpx,
rich, nanoGPT,
FastAPI,
pydantic, and CPython's own
Lib/ directory, where the standard library is written in readable Python.
In this Wiki: the series this guide plugs into: OS & Linux · OSI · TCP/IP · Security from Zero · Security in Depth · HTTPS Lifecycle · AI from Zero to LLMs · Mathematics · Go · C · Rust · DSA.