python-pro

Create Python 3.11+ modules with strict typing, async APIs, and pytest suites.

Updated Feb 11, 2026

Search Tags:#linting #pytest #python #mypy #asyncio #dataclasses #typing

Ready to run

npx skills add https://github.com/lamb92009/claude-skills --skill python-pro-lamb92009

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: python-pro
Source: https://github.com/lamb92009/claude-skills/tree/main/python-pro
Command: npx skills add https://github.com/lamb92009/claude-skills --skill python-pro-lamb92009

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Python development for robust, type-safe, asynchronous applications. It helps teams enforce strong typing, modern async patterns, and production-grade practices in Python 3.11+.

Core Features & Use Cases

Type safety and correctness: embraces complete type hints, dataclasses, and runtime checks to prevent common errors.
Async/await patterns: designed for I/O-bound workloads with proper async structure and testing.
Testing and quality: supports pytest, fixtures, and mocking to ensure reliable code; includes mypy configuration and linting guidance.
Project hygiene: promotes clean packaging with Poetry, code formatting with Black, and static analysis with Ruff.

Quick Start

Create a small production-grade Python module with complete type hints, an async API, and a pytest-based test suite.

Frequently Asked Questions about python-pro

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I enforce strict typing and async patterns in Python 3.11+?▼

You enforce strict typing and async patterns in Python 3.11+ by applying complete type hints, using dataclasses, and structuring I/O-bound workloads with async/await. This approach prevents common errors and ensures maintainable production codebases.

What's the best way to configure mypy and pytest for a production Python codebase?▼

The best way to configure mypy and pytest involves establishing strict type-checking rules and utilizing pytest fixtures with mocking. This combination ensures reliable code testing and consistent static analysis across your team's Python projects.

Can I use dataclasses and asyncio together for I/O-bound Python workloads?▼

Yes, you can use dataclasses and asyncio together for I/O-bound Python workloads. Combining them allows you to define structured, type-safe state while leveraging asynchronous programming for fast, non-blocking I/O operations.

Do I need Poetry and Ruff to maintain type-safe Python projects?▼

You need Poetry and Ruff to maintain type-safe Python projects because they provide clean packaging and static analysis. Integrating these tools with Black formatting ensures consistent, high-quality code hygiene across your team.

Why does mypy strict mode fail on missing type hints for public APIs?▼

Mypy strict mode fails on missing type hints because enforcing type hints on public APIs is required for type safety. Adding complete type annotations to your functions prevents runtime errors and satisfies static analysis checks.

How do I test asynchronous Python functions with pytest?▼

You test asynchronous Python functions with pytest by utilizing specialized async test fixtures and mocking. This ensures your async/await patterns are properly validated and reliable under I/O-bound workload conditions.