Guide FastAPI API development with Pydantic models and dependency injection.
npx skills add https://github.com/91zgaoge/memoh-X --skill fastapi-91zgaoge
Please help me install this Agent Skill. Skill: fastapi Source: https://github.com/91zgaoge/memoh-X/tree/main/openviking-packages/fastapi/.agents/skills/fastapi Command: npx skills add https://github.com/91zgaoge/memoh-X --skill fastapi-91zgaoge
This Skill helps developers write clean, efficient, and up-to-date FastAPI code by enforcing best practices and leveraging the latest features.
Annotated, proper dependency injection, and response models.fastapi CLI for development and production.Annotated for path parameters and include a response_model for better documentation and security.Use the fastapi skill to refactor the provided code to use Annotated for path parameters and include a response model.
High-intent search queries and answers about installing and using this skill.
To refactor FastAPI code, use the `Annotated` type hint for path parameters and include an explicit `response_model` in your endpoint definition to ensure robust API design and better documentation.
FastAPI dependency injection best practices involve using the `Annotated` keyword for parameters and defining explicit response models to enforce clean, efficient, and up-to-date code structure.
Integrate Pydantic models in FastAPI by defining them as explicit `response_model` arguments in your endpoints, ensuring data validation, serialization, and robust API design.
Yes, the FastAPI CLI can be used for both development and production environments, providing a standardized way to run and manage your API applications efficiently.
Explicit response models in FastAPI endpoints improve API documentation and security by strictly defining the output data structure, filtering out unnecessary fields from the response.
Optimize FastAPI performance by adhering to current standards, utilizing modern Python features like `Annotated`, and applying efficient code structure patterns for API development.
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