python-pro

# 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 ```python from pathlib import Path def read_config(path: Path) -> dict[str, str]: """Read configuration from a file. Args: path: Path to the configuration file. Returns: Parsed key-value configuration entries. Raises: FileNotFoundError: If the config file does not exist. ValueError: If a line cannot be parsed. """ config: dict[str, str] = {} with path.open() as f: for line in f: key, _, value = line.partition("=") if not key.strip(): raise ValueError(f"Invalid config line: {line!r}") config[key.strip()] = value.strip() return config ``` ### Dataclass with validation ```python from dataclasses import dataclass, field @dataclass class AppConfig: host: str port: int debug: bool = False allowed_origins: list[str] = field(default_factory=list) def __post_init__(self) -> None: if not (1 <= self.port <= 65535): raise ValueError(f"Invalid port: {self.port}") ``` ### Async pattern ```python import asyncio import httpx async def fetch_all(urls: list[str]) -> list[bytes]: """Fetch multiple URLs concurrently.""" async with httpx.AsyncClient() as client: tasks = [client.get(url) for url in urls] responses = await asyncio.gather(*tasks) return [r.content for r in responses] ``` ### pytest fixture and parametrize ```python import pytest from pathlib import Path @pytest.fixture def config_file(tmp_path: Path) -> Path: cfg = tmp_path / "config.txt" cfg.write_text("host=localhost\nport=8080\n") return cfg @pytest.mark.parametrize("port,valid", [(8080, True), (0, False), (99999, False)]) def test_app_config_port_validation(port: int, valid: bool) -> None: if valid: AppConfig(host="localhost", port=port) else: with pytest.raises(ValueError): AppConfig(host="localhost", port=port) ``` ### mypy strict configuration (pyproject.toml) ```toml [tool.mypy] python_version = "3.11" strict = true warn_return_any = true warn_unused_configs = true disallow_untyped_defs = true ``` Clean `mypy --strict` output looks like: ``` Success: no issues found in 12 source files ``` 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/)