Python Fundamentals Best Practices
Core habits that keep Python code readable, correct, and maintainable before you reach for frameworks or data tools. Treat this as a onboarding checklist for every new module or repo.
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Core habits that keep Python code readable, correct, and maintainable before you reach for frameworks or data tools. Treat this as a onboarding checklist for every new module or repo.
pyproject.toml and a lockfile (uv.lock). Reproducible CI and clones.requires-python in pyproject.toml.ruff check and ruff format on every PR. Fast style and lint feedback.snake_case functions, PascalCase classes, UPPER constants.% formatting and format() for new code. Clearer and faster.pathlib.Path instead of os.path string juggling. Cross-platform safe joins.def f(x=[])). Use None and assign inside.Decimal for money, not binary float. Avoid 0.1 + 0.2 surprises in billing.encoding="utf-8" on all text file I/O. Prevent platform-default bugs.copy.deepcopy when independence matters. Shallow copies share inner lists.isinstance for type checks, not type(x) is Cls on subclasses. Polymorphism-friendly.append loops when transforming sequences. Readable and often faster.match/case for structural branching on dicts and dataclasses. Cleaner than deep if chains.* in public APIs. Prevents ambiguous call sites.if __name__ == "__main__":. Importable modules without side effects.python -m package.module. Correct relative imports and __package__.from myapp.utils import x). Clearer than relative in large trees.types modules. Fail fast at design time when possible.json.py, types.py). Breaks imports mysteriously.src/ layout for installable packages. Prevents accidental imports from repo root.No - configure ruff and focus on readability. Automate formatting debates away.
Module-level constants and cached read-only config are fine. Mutable globals complicate tests - prefer injection.
Optional for throwaway scripts. Add them when the script grows or becomes a package.
match for structure (dict keys, typed events). if for simple scalar conditions.
This cookbook pins uv 0.6+ as the default fast path. Poetry remains valid for teams already standardized on it.
Start with new modules at strict optional flags; widen gradually. Pydantic models at HTTP boundaries first.
Better for map/filter transforms. Use a for loop when side effects or complex branching dominate.
print is fine for CLI UX. Services should use logging with structured fields - see errors-logging section.
Explicit comparisons (is None, len(x) == 0) when falsy-but-valid values like 0 matter.
Isolated environments with locked dependencies - everything else fails without reproducible installs.
Stack versions: This page was written for Python 3.14.0 (stable 3.14, maintenance 3.13), FastAPI 0.115+, Django 5.2, Flask 3.1, Pydantic 2, PyTorch 2.6+, pandas 2.2+, Polars 1.x, ruff 0.9+, and uv 0.6+.
Reviewed by Chris St. John·Last updated Jul 16, 2026