jikime-lang-python

To set up a FastAPI project with async SQLAlchemy 2.0, use uv to initialize the environment, install FastAPI, uvicorn, and pydantic, then implement asynchronous database operations using async/await patterns for I/O-bound tasks.

The best way to validate data in Python APIs is using Pydantic v2, which ensures data integrity through type hinting and validation models, seamlessly integrating with FastAPI to structure and enforce API request schemas.

You write tests for asynchronous Python functions using pytest by applying modern testing best practices tailored for async/await patterns, ensuring robust test coverage for I/O-bound operations and web application endpoints.

Yes, the Python development guide covers both frameworks. It provides code examples and instructions for building APIs with FastAPI and developing full-stack web applications using Django for Python 3.13+.

You manage environment variables and type hinting by following included best practices for Python 3.13+ development, ensuring data integrity and configuration security across FastAPI applications and data pipelines.

Yes, you can use this skill for building data science pipelines in Python. It covers data science libraries, data validation with Pydantic, and asynchronous patterns to process I/O-bound data workflows efficiently.