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moai-lang-python

Guide Python 3.13+ development with FastAPI, Django, async patterns, and pytest.

1|Updated Jan 10, 2026
Search Tags:#pytest#fastapi#python#async#django#data-science
One-click install
npx skills add https://github.com/GoosLab/moai-rank --skill moai-lang-python-gooslab
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: moai-lang-python
Source: https://github.com/GoosLab/moai-rank/tree/main/.claude/skills/moai-lang-python
Command: npx skills add https://github.com/GoosLab/moai-rank --skill moai-lang-python-gooslab

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Python 3.13+ development requires modern async frameworks, strong typing, and integrated testing; this Skill provides structured guidance and patterns for API design, data processing, and testing workflows.

Core Features & Use Cases

  • Supports FastAPI and Django APIs with async patterns, typing, and Pydantic v2 validation.
  • Covers SQLAlchemy 2.0 async ORM, data schemas, and repository patterns for scalable backends.
  • Includes testing strategies using pytest, async fixtures, and CI-ready patterns for reliable releases.

Quick Start

Guide me to build a Python 3.13+ project featuring FastAPI, Django, async data processing, and pytest tests.

Frequently Asked Questions about moai-lang-python

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

FAQPage Schema
How do I structure a FastAPI project with async SQLAlchemy 2.0 and Pydantic v2 validation?▼

Build FastAPI services using async SQLAlchemy 2.0 ORM patterns and Pydantic v2 validation to ensure scalable, strongly-typed API backends. This approach uses repository patterns for consistent data schemas and modern asynchronous processing.

How do I write pytest tests with async fixtures for Python 3.13+ asynchronous APIs?▼

Write pytest tests for async APIs by utilizing async fixtures and CI-ready validation patterns. This Python testing strategy ensures reliable releases by validating asynchronous workflows and data processing tasks directly within your continuous integration pipeline.

Does this Python development approach work for both Django and FastAPI async patterns?▼

Yes, this Python approach supports both Django and FastAPI async patterns. It provides structured guidance for API design, applying asynchronous patterns and strong typing across Python 3.13+ frameworks to ensure consistent backend architecture and data workflows.

What's the best way to implement async data processing workflows in Python 3.13+?▼

Implement async data processing in Python 3.13+ by combining SQLAlchemy 2.0 async ORM operations with Pydantic v2 schemas. This pattern handles data science workloads efficiently while maintaining strict type safety and structured data repository integration.

Do I need Python 3.13+ and FastAPI familiarity to use these backend patterns?▼

Yes, you need Python 3.13+ along with familiarity in FastAPI or Django, Pytest, Pydantic, and SQLAlchemy 2.0. These asynchronous programming skills are required to apply the structured guidance for modern API design and data tasks effectively.

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