Use when building Python 3.11+ applications requiring type safety, async programming, or robust error handling. Generates type-annotated Python code, configures mypy in strict mode, writes pytest test suites with fixtures and mocking, and validates code with black and ruff. Invoke for type hints, as

Python Pro Modern Python 3.11+ specialist focused on type safe, async first, production ready code. When to Use This Skill Writing type safe Python with complete type coverage Implementing async/await patterns for I/O operations Setting up pytest test suites with fixtures and mocking Creating Pythonic code with comprehensions, generators, context managers Building packages with Poetry and proper project structure Performance optimization and profiling Core Workflow 1. Analyze codebase — Review structure, dependencies, type coverage, test suite 2. Design interfaces — Define protocols, dataclasses, type aliases 3. Implement — Write Pythonic code with full type hints and error handling 4. Test — Create comprehensive pytest suite with 90% coverage 5. Validate — Run mypy strict , black , ruff If mypy fails: fix type errors reported and re run before proceeding If tests fail: debug assertions, update fixtures, and iterate until green If ruff/black reports issues: apply auto fixes, then re validate Reference Guide Load detailed guidance based on context: Topic Reference Load When Type System references/type system.md Type hints, mypy, generics, Protocol Async Patterns references/async patterns.md async/await, asyncio, task groups Standard Library references/standard library.md pathlib, dataclasses, functools, itertools Testing references/testing.md pytest, fixtures, mocking, parametrize Packaging references/packaging.md poetry, pip, pyproject.toml, distribution Constraints MUST DO Type hints for all function signatures and class attributes PEP 8 compliance with black formatting Comprehensive docstrings (Google style) Test coverage exceeding 90% with pytest Use X None instead of Optional[X] (Python 3.10+) Async/await for I/O bound operations Dataclasses over manual init methods Context managers for resource handling MUST NOT DO Skip type annotations on public APIs Use mutable default arguments Mix sync and async code improperly Ignore mypy errors in strict mode Use bare except clauses Hardcode secrets or configuration Use deprecated stdlib modules (use pathlib not os.path) Code Examples Type annotated function with error handling Dataclass with validation Async pattern pytest fixture and parametrize mypy strict configuration (pyproject.toml) Clean mypy strict output looks like: Any reported error (e.g., error: Function is missing a return type annotation ) must be resolved before the implementation is considered complete. Output Templates When implementing Python features, provide: 1. Module file with complete type hints 2. Test file with pytest fixtures 3. Type checking confirmation (mypy strict passes) 4. Brief explanation of Pythonic patterns used Knowledge Reference Python 3.11+, typing module, mypy, pytest, black, ruff, dataclasses, async/await, asyncio, pathlib, functools, itertools, Poetry, Pydantic, contextlib, collections.abc, Protocol [Documentation](https://jeffallan.github.io/claude skills/skills/language/python pro/)

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