/python-pro

name: python-pro
description: 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, async/await patterns, dataclasses, dependency injection, logging configuration, and structured error handling.
license: MIT
metadata:
  author: https://github.com/Jeffallan
  version: "1.1.0"
  domain: language
  triggers: Python development, type hints, async Python, pytest, mypy, dataclasses, Python best practices, Pythonic code
  role: specialist
  scope: implementation
  output-format: code
  related-skills: fastapi-expert, devops-engineer

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

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

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

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

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)

[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

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