Build FastAPI REST APIs with Pydantic models, OAuth2/JWT security, and OpenAPI documentation.
npx skills add https://github.com/itechmeat/llm-code --skill fastapi-itechmeat
Please help me install this Agent Skill. Skill: fastapi Source: https://github.com/itechmeat/llm-code/tree/main/skills/fastapi Command: npx skills add https://github.com/itechmeat/llm-code --skill fastapi-itechmeat
This Skill provides comprehensive guidance for building high-performance REST APIs using the FastAPI framework, helping teams design robust backends with clear validation, security, and documentation patterns.
Create a minimal FastAPI app with at least one endpoint and OpenAPI docs, then run it locally to explore docs and validation.
High-intent search queries and answers about installing and using this skill.
To build a REST API with FastAPI, define Pydantic models for automatic data validation and use modular routers for endpoints. This approach ensures robust input validation and structured API design across small to large projects.
Implement OAuth2 and JWT security in FastAPI by defining dedicated security dependencies. This pattern enforces consistent authentication across endpoints, protecting routes with token-based validation for production-grade APIs.
FastAPI generates OpenAPI documentation automatically based on your route definitions and Pydantic models. This provides interactive API docs pages without manual schema writing, reflecting endpoint validation and security patterns.
Yes, FastAPI is suitable for large production microservices. By structuring projects with modular routers, dependency injection, and Pydantic models, teams can scale endpoints, validation, and security patterns effectively.
Structure a FastAPI project by organizing endpoints into modular routers and using dependency injection for shared logic like database sessions or security. This pattern keeps code maintainable and separates validation concerns cleanly.
Testing a FastAPI web API involves using Python testing tools to validate endpoint responses, input validation logic, and security enforcement. This ensures your routing patterns and Pydantic models behave correctly under various conditions.
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