Python References

Use this page as your deep-dive map after you finish the core roadmap. It points to the primary references that working Python engineers use repeatedly.

Official Docs

Packaging and Distribution

Code Quality

Environment and Tooling

Specialization Paths

  • Backend APIs: FastAPI, Flask, Django, async networking, deployment, observability.
  • Automation: scripting, CLI tools, file processing, schedulers, infrastructure glue.
  • Data and AI: NumPy, pandas, notebooks, model pipelines, experiment reproducibility.
  • Testing and quality: unit tests, property tests, linting, typing, CI.

Deep-Dive Path

  1. Read the Python tutorial and language reference side by side.
  2. Build one package and publish it to a private or public package registry.
  3. Add `pytest`, Ruff, and type checking to a real project.
  4. Pick one specialization and ship a small production-style project.