Python — The Complete Field Guide (Beginner → Expert)

Contents

84 chapters, one page each. Prefer one long page? Read the whole book on one page.

1. How to use this guide2 min
2. Table of contents3 min
3. Part 0 — Start here
4. 0.1 Setup: Python, uv, ruff, a type checker, and an editor2 min
5. 0.2 The series: OS → networking → security → AI, in Python4 min
6. 0.3 The Go ↔ Rust ↔ Python phrasebook2 min
7. 0.4 The Python labs: what you build for each guide in the series1 min
8. 0.5 Why Python runs AI, and where it does not belong2 min
9. Part I — Foundations: the Python way
10. 1. What Python is: CPython, bytecode, and the REPL2 min
11. 2. Names, objects, and references: the model behind every Python bug5 min
12. 3. Numbers, text, and bytes3 min
13. 4. Control flow and pattern matching2 min
14. 5. Functions: arguments, scope, and closures2 min
15. 6. Collections: list , tuple , dict , set , and comprehensions3 min
16. 7. Errors and exceptions2 min
17. 8. Files, paths, and context managers2 min
18. 9. Modules, packages, and imports2 min
19. 10. 🔎 Checkpoint: names, objects, and collections1 min
20. 11. Terminal project: a word-frequency counter1 min
21. 12. Terminal project: a web access-log analyzer3 min
22. Part II — Intermediate: idiomatic Python
23. 13. Iterators and generators: lazy pipelines3 min
24. 14. Decorators2 min
25. 15. Classes, properties, and dataclasses2 min
26. 16. The data model: making your objects feel built in2 min
27. 17. Inheritance, composition, ABCs, and protocols2 min
28. 18. Type hints that pay for themselves2 min
29. 19. The standard library you will use every week2 min
30. 20. Testing with pytest and Hypothesis2 min
31. 21. Projects and packaging: pyproject.toml , uv , lockfiles2 min
32. 22. 🔎 Checkpoint: generators, classes, and types1 min
33. 23. Terminal project: pygrep , a tested grep clone2 min
34. 24. Terminal project: an LRU cache with TTL, two ways3 min
35. Part III — Advanced: internals, concurrency, performance
36. 25. How CPython runs your code: bytecode, frames, and the specializing interpreter2 min
37. 26. Memory: reference counting, the cycle collector, and __slots__3 min
38. 27. The GIL, threads, and free-threaded Python3 min
39. 28. Processes: multiprocessing and concurrent.futures2 min
40. 29. asyncio: the event loop, tasks, timeouts, and cancellation3 min
41. 30. Descriptors, __init_subclass__ , and metaclasses: how frameworks work2 min
42. 31. Performance: measure first, then vectorize, cache, or go native2 min
43. 32. Project: a parallel file hasher, four ways2 min
44. Part IV — Systems Python: the OS guide in Python
45. 33. Syscalls from Python: what open() really does2 min
46. 34. Processes: subprocess done right, exit codes, and signals3 min
47. 35. Files that survive crashes: fsync and atomic replacement1 min
48. 36. Reading /proc : build your own ps2 min
49. 37. mmap , shared memory, and pipes2 min
50. 38. Python as a better shell: automation and a systemd service1 min
51. 39. A container in 80 lines: namespaces with os.unshare2 min
52. Part V — Network Python: the networking and HTTPS guides in Python
53. 40. Sockets four ways: blocking, threads, selectors , asyncio3 min
54. 41. A DNS client from raw bytes with struct3 min
55. 42. HTTP/1.1 from a bare socket2 min
56. 43. HTTP clients done right: timeouts, retries, pooling, and an SSRF guard4 min
57. 44. A production API with FastAPI: validation, limits, and shutdown3 min
58. 45. TLS and mutual TLS with the ssl module2 min
59. 46. Project: an async service health checker2 min
60. Part VI — Security-focused Python
61. 47. Python's own attack surface4 min
62. 48. Cryptography done right: secrets , hmac , AEAD, password hashing3 min
63. 49. Web security in Python: injection, templates, and uploads2 min
64. 50. Supply chain: lockfiles, hashes, audits, and trusted publishing2 min
65. 51. Project: an auth service with Argon2 and JWTs2 min
66. 52. Project: a log-based intrusion detector2 min
67. Part VII — Python for data science and AI/ML
68. 53. NumPy: arrays, broadcasting, and why vectorized code is fast3 min
69. 54. pandas and Polars: tables, groupby, joins, and time series2 min
70. 55. Plotting just enough: matplotlib1 min
71. 56. scikit-learn: the fit/predict contract, pipelines, and leakage2 min
72. 57. Autograd from scratch: the engine inside PyTorch in 120 lines4 min
73. 58. PyTorch: tensors, nn.Module , and the training loop2 min
74. 59. Hugging Face: tokenizers, models, and datasets1 min
75. 60. Data pipelines for training: extraction, cleaning, dedup, JSONL2 min
76. 61. LLM apps in Python: structured output, RAG, a tool-calling agent, an MCP server6 min
77. 62. Experiment hygiene: seeds, configs, notebooks, and reproducibility2 min
78. Part VIII — Open source walkthrough: inside requests
79. 63. How to read a real codebase2 min
80. 64. The call path: requests.get() to the socket9 min
81. 65. The design lessons in requests3 min
82. 66. Running the tests and making a change2 min
83. Part IX — Expert and professional Python
84. 67. Library and API design: making code other people can use3 min
85. 68. Logging and observability1 min
86. 69. Debugging: pdb , faulthandler , py-spy , and remote attach2 min
87. 70. Shipping Python: containers, wheels, and GPU images2 min
88. 71. How not to write Python: an anti-pattern catalog2 min
89. 72. Capstone: one request, every layer, every guide, in Python7 min
90. Appendices
91. Appendix A — Traceback decoder: the 15 exceptions you will actually see2 min
92. Appendix B — Tooling cheat sheet1 min
93. Appendix C — Glossary2 min
94. Appendix D — A 90-day plan1 min
95. Appendix E — The guides, books, and codebases this guide draws on2 min