python-pro

Implements strict typing, asyncio patterns, and pytest tests for Python 3.11+ projects.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/kamushadenes/nix --skill python-pro-kamushadenes
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: python-pro
Source: https://github.com/kamushadenes/nix/tree/main/home/common/ai/resources/claude-code/skills/python-pro
Command: npx skills add https://github.com/kamushadenes/nix --skill python-pro-kamushadenes

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps developers deliver production-grade Python 3.11+ code with thorough typing, robust asynchronous patterns, and maintainable structure.

Core Features & Use Cases

  • Full type annotations on all public APIs
  • Async/await patterns with asyncio
  • pytest-based tests and high coverage
  • Modern Python syntax and production-ready patterns
  • Use Case: Refactor a legacy codebase to adopt strict typing and asynchronous I/O.

Quick Start

Start by providing a small Python module and a testing plan to graduate it to type-safe, async-ready code.

Frequently Asked Questions about python-pro

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

FAQPage Schema
How do I add strict typing and async/await patterns to a legacy Python codebase?

You can refactor legacy code by applying full type annotations on all public APIs and converting I/O operations to async/await patterns using asyncio, ensuring production-grade maintainability.

What is the best way to structure pytest tests for a production Python service?

The best way to structure pytest tests for a production Python service is to implement test-driven development with high coverage, ensuring robust validation across APIs, libraries, and services before deployment.

Does this approach to production-grade Python require a specific minimum version?

Yes, this approach to production-grade Python requires targeting Python 3.11+ to leverage modern syntax, strict typing on public APIs, and robust asynchronous patterns effectively.

Can I use mypy for type checking across APIs, libraries, and services?

Yes, you can use mypy for type checking by applying full type annotations on all public APIs, ensuring type safety and code quality across your libraries and services.

Why does modernizing a Python project for production require asyncio and high test coverage?

Modernizing a Python project requires asyncio and high test coverage to deliver robust asynchronous I/O patterns and maintainable structure, ensuring the code meets production-grade reliability standards.

What are the limitations of refactoring legacy code to use strict typing in Python?

A limitation of refactoring legacy code to strict typing in Python is the requirement to target version 3.11+ for modern syntax compatibility, which may necessitate upgrading older runtime environments.