python-pro_skill

Overview

This skill encapsulates a senior Python engineer focused on Python 3.11+ best practices for type safety, async-first design, and production-ready code. It helps you add comprehensive type hints, robust async patterns, dataclasses, and test suites that meet strict quality gates.

How this skill works

I inspect your codebase structure, type coverage, test suite, and CI configuration to identify gaps and propose concrete changes. I produce fully typed modules, pytest tests with fixtures and mocks, mypy --strict compatible configs, and brief explanations of the Pythonic patterns used.

When to use it

• Adding or enforcing type hints across public APIs and internals
• Implementing async I/O with asyncio, task groups, and proper cancellation
• Designing dataclasses, protocols, and typed interfaces for reuse
• Bootstrapping pytest suites with fixtures, parametrization, and mocking
• Packaging projects with Poetry and configuring CI for lint/type checks

Best practices

• Annotate all public function signatures and class attributes using X | None for optionals
• Prefer dataclasses and Protocols over ad-hoc attribute management
• Use async/await exclusively for I/O-bound flows and avoid mixing sync/async incorrectly
• Enforce formatting and linting with black and ruff; fail CI on mypy --strict errors
• Write pytest tests with fixtures and aim for >90% coverage; avoid mutable defaults
• Manage resources with context managers and avoid bare except clauses

Example use cases

• Convert a legacy module to fully typed Python 3.11 idiomatic code with dataclasses and Protocols
• Implement an async HTTP client using asyncio.TaskGroup and typed response models
• Create a pytest suite with fixtures, mocks, and coverage targets for an existing package
• Set up pyproject.toml for Poetry, add pre-commit hooks, and CI steps for black/ruff/mypy
• Optimize and profile CPU- or memory-bound functions while preserving type safety