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moai-lang-python

Develop Python 3.13+ applications with FastAPI, Django, and pytest.

Updated Mar 14, 2026
Search Tags:#pytest#fastapi#python#data science#programming#async#django
One-click install
npx skills add https://github.com/jinwoonghong/MESAsim --skill moai-lang-python-jinwoonghong
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: moai-lang-python
Source: https://github.com/jinwoonghong/MESAsim/tree/main/.claude/skills/moai-lang-python
Command: npx skills add https://github.com/jinwoonghong/MESAsim --skill moai-lang-python-jinwoonghong

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python:3.13+, pytest, ruff, mypy, fastapi, pydantic, sqlalchemy, poetry, uv, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines Python development by providing expert guidance and code examples for modern Python features, web frameworks, testing, and data science.

Core Features & Use Cases

  • Modern Python: Leverage the latest features of Python 3.13+, including JIT compilation and pattern matching.
  • Web Development: Build robust APIs and web applications with FastAPI and Django.
  • Data Science & Testing: Implement data pipelines and ensure code quality with pytest and data libraries.
  • Use Case: Develop a new FastAPI microservice, ensuring it uses async patterns, Pydantic for validation, and is fully testable with pytest.

Quick Start

Use the moai-lang-python skill to create a basic FastAPI endpoint that accepts a POST request with a JSON body containing a 'name' field and returns a JSON response with a 'message' field.

Frequently Asked Questions about moai-lang-python

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

FAQPage Schema
How do I build a FastAPI microservice with async patterns and pytest testing?▼

Build FastAPI microservices by applying async patterns, Pydantic validation, and pytest testing to ensure reliable API performance. This approach guarantees structured code and robust application performance.

What's the best way to structure a Python data pipeline using modern features?▼

Structure Python data pipelines by leveraging Python 3.13+ features like pattern matching alongside data science libraries. This ensures efficient data handling and robust application performance for processing tasks.

Do I need Python 3.13+ to use modern async patterns with SQLAlchemy?▼

Python 3.13+ is required to leverage modern features like JIT compilation and pattern matching. Using it with SQLAlchemy and FastAPI ensures efficient, modern, and robust application performance.

How does pytest work with FastAPI and Pydantic for API validation?▼

Pytest works with FastAPI by testing API endpoints and validating JSON responses against Pydantic models. This ensures structured code, automated testing coverage, and reliable application performance.

Can I use Django and FastAPI together in the same Python application?▼

Django and FastAPI can be used together within Python 3.13+ development. This Skill provides comprehensive support for both web frameworks, addressing the need for efficient API creation and robust web application development.

What are the limitations of using Python 3.13+ JIT compilation for web development?▼

Python 3.13+ JIT compilation limitations depend on framework compatibility and async patterns. While it enhances performance, ensure your FastAPI or Django web frameworks fully support these modern features for reliable application performance.

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