moai-lang-python

You can build async APIs with FastAPI by leveraging Python 3.13+ modern patterns and async capabilities. This skill provides practical guidance for constructing server-side APIs and managing async workloads using standard libraries and tooling.

The best way to structure testable Python code is by combining pytest for execution and Pydantic for data validation. This skill outlines strategies to build robust, testable codebases using these libraries alongside SQLAlchemy.

Yes, you can use Django and SQLAlchemy together within modern data pipelines. This skill guides developers through integrating these common libraries to process data and build robust web applications using Python 3.13+ features.

Python 3.13 introduces features that enhance async workloads for data science workflows. This skill demonstrates how to apply these modern patterns and asynchronous capabilities to build faster, safer data processing pipelines and research workflows.

To start developing Python APIs, you need Python 3.13+ installed along with core libraries like fastapi, django, pydantic, sqlalchemy, and pytest. You can then implement and validate examples using standard tooling.

You should use async patterns in Python web apps when handling concurrent I/O operations or building scalable server-side APIs. This skill provides guidance on applying async patterns effectively across FastAPI, Django, and data pipelines.