Python Pro

Modern Python Skill

Write clean, typed, idiomatic Python. Prefer Python 3.12+ when the runtime allows.

When to Use

• Writing or modernizing Python modules
• Setting up a Python project (uv, ruff, pyright, pyproject.toml)
• Production libraries, APIs, or tooling implementation

When Not to Use

• Choosing FastAPI vs Django vs layout (python-patterns)
• Choosing asyncio vs threads vs processes (python-concurrency)
• Profiling latency/CPU/memory (python-performance)
• Reviewing a diff (code-review)
• Non-Python stacks
• Basic syntax-only questions

Related Skills

• Use python-patterns when architecture (framework/layout/ADR) is still open.
• Use python-testing to protect behavior.
• Before merge: code-review.

Version Handling

Confirm the target Python version first.

Python 3.12+ (Preferred)

Use modern syntax: type aliases (PEP 695), native generics, enhanced f-strings, @override (from typing import override).

Python 3.10–3.11 (Constrained)

Stay compatible with the runtime. Use typing_extensions where the project already allows it (Protocol, ParamSpec, TypeGuard). Avoid 3.12-only syntax. Note upgrade benefits when relevant.

Python ≤3.9

Unsupported for new work unless the repo MSRV is already pinned there. State the constraint and keep changes minimal.

Core Principles

• Prefer the newest features the target version allows.
• Functions and data over gratuitous OOP. Prefer dataclass(slots=True) or Pydantic at boundaries.
• Structural subtyping: typing.Protocol over deep abc.ABC trees.
• Explicit public surface: __all__; _name for internals.
• Rule of Three before shared abstractions.
• End-to-end type hints targeting strict pyright or mypy.
• Tests: DAMP over aggressive DRY (python-testing).
• Tooling: uv, ruff, pyright/mypy, pyproject.toml.
• Stdlib first; justify new dependencies.
• Zero import-time I/O or heavy compute.

Recommended Defaults (adapt to version)

• Package & environment: uv (or the repo's existing venv)
• Lint + format: ruff
• Types: pyright (strict where viable) or mypy
• Tests: pytest
• Config: pyproject.toml
• Models: dataclasses + slots=True internally; Pydantic v2 at I/O boundaries
• HTTP: FastAPI only if python-patterns already chose it
• CLI: typer or click

Working Approach

1. Confirm Python version, runtime, and project constraints.
2. Define module boundaries, __all__, and data contracts.
3. Implement with types, no import-time side effects, explicit errors.
4. Add isolated tests (python-testing).
5. Run ruff and pyright/mypy.
6. Profile only when there is a measured hotspot (python-performance).

Output Expectations

• Code compatible with the confirmed Python version
• Type hints on signatures and data definitions
• Minimal public surface
• Protocols for swappable dependencies
• Justified third-party deps

Final Checklist

• Target Python version confirmed
• Functions/dataclasses where classes are unnecessary
• Public vs private surface explicit
• Dependencies abstracted via Protocol or injection
• No import-time I/O
• Types complete for the target version
• No bare except:
• Older-runtime limitations noted when applicable