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python-pro

Generate type-safe async Python 3.11+ code with pytest suites and mypy validation.

Updated Jun 16, 2026
Search Tags:#pytest#python#backend#mypy#asyncio#typing
One-click install
npx skills add https://github.com/Design-System-ET/genexus-dev-opencode --skill python-pro-design-system-et
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: python-pro
Source: https://github.com/Design-System-ET/genexus-dev-opencode/tree/main/skills/python-pro
Command: npx skills add https://github.com/Design-System-ET/genexus-dev-opencode --skill python-pro-design-system-et

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pytest, mypy, black, ruff, httpx, pydantic, and includes references (resource) components.

What problem does it solve?

This Skill addresses the challenges of maintaining large-scale Python codebases by enforcing strict type safety, robust async patterns, and comprehensive testing standards.

Core Features & Use Cases

  • Type-Safe Development: Generates code with full type annotations and strict mypy configuration to catch bugs before runtime.
  • Async-First Architecture: Implements efficient I/O-bound operations using modern async/await patterns and task groups.
  • Production-Grade Testing: Automates the creation of pytest suites with fixtures, mocking, and high coverage requirements.

Quick Start

Invoke the python-pro skill to generate a new module with type hints and a corresponding pytest suite for the current project.

Frequently Asked Questions about python-pro

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

FAQPage Schema
How do I build type-safe asynchronous Python applications with strict mypy validation?▼

To build type-safe asynchronous Python applications, generate code with full type annotations and async/await patterns, then validate it using strict mypy configuration to catch bugs before runtime. This approach ensures robust I/O-bound concurrency.

What is the best way to generate pytest suites with high coverage for Python 3.11+?▼

The best way to generate high-coverage pytest suites for Python 3.11+ is to automate the creation of test cases with fixtures, mocking, and strict validation. This ensures robust testing standards for large-scale codebases.

Can I use asyncio with dependency injection and structured error handling in Python?▼

Yes, you can implement asyncio with dependency injection and structured error handling in Python. This combination targets modern implementation tasks, ensuring efficient I/O-bound operations and robust application architecture.

Does this approach to Python development enforce PEP 8 compliance and strict typing?▼

Yes, this Python development approach enforces strict adherence to PEP 8 and full type annotations. It targets Python 3.11+ applications, ensuring type safety and alignment with modern best practices.

How do I structure Python projects to handle large-scale codebase maintenance?▼

Structure Python projects for large-scale maintenance by enforcing strict type safety, robust async patterns, and comprehensive testing standards. This addresses maintenance challenges through automated validation and production-grade architecture.

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