Develop async FastAPI APIs with SQLAlchemy 2.0 and Pydantic V2.
npx skills add https://github.com/BoraPerusic/agents --skill fastapi-pro-boraperusic
Please help me install this Agent Skill. Skill: fastapi-pro Source: https://github.com/BoraPerusic/agents/tree/main/skills/to%20try/fastapi-pro Command: npx skills add https://github.com/BoraPerusic/agents --skill fastapi-pro-boraperusic
Build high-performance async APIs with FastAPI, SQLAlchemy 2.0, and Pydantic V2 to enable scalable, production-ready web services.
Clarify goals, constraints, and required inputs, then design scalable FastAPI endpoints using async patterns and Pydantic models for production-grade APIs.
High-intent search queries and answers about installing and using this skill.
Build async APIs with FastAPI by enforcing asynchronous request handling, modern dependency injection, and secure data validation through Pydantic V2. This approach generates production-ready microservices with robust serialization and automatic OpenAPI documentation.
Yes, SQLAlchemy 2.0+ async support is integrated directly into this FastAPI workflow. It enables high-concurrency database operations alongside asynchronous request handling, with database migrations managed using Alembic to ensure scalable data access.
FastAPI includes native WebSocket support for real-time communication services. This allows you to build modern Python async workflows that maintain persistent connections for instant data pushing alongside standard REST API endpoints.
The best way to handle authentication in FastAPI microservices is by implementing OAuth2 with JWT or API keys. These patterns secure data validation and route access using modern dependency injection and Annotated types.
Offload work in a FastAPI application by utilizing built-in background tasks and task queues. This prevents blocking asynchronous request handling, ensuring high-performance API responses while heavier processing completes concurrently.
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