Build asynchronous FastAPI APIs with SQLAlchemy 2.0 and Pydantic V2.
npx skills add https://github.com/melikhanmutlu/web_ar --skill fastapi-pro-melikhanmutlu
Please help me install this Agent Skill. Skill: fastapi-pro Source: https://github.com/melikhanmutlu/web_ar/tree/main/skills-extra/fastapi-pro Command: npx skills add https://github.com/melikhanmutlu/web_ar --skill fastapi-pro-melikhanmutlu
This guidance helps developers build high-performance asynchronous APIs quickly by providing proven patterns with FastAPI, SQLAlchemy 2.0, and Pydantic V2.
Create a new FastAPI project following this skill and run with uvicorn to verify asynchronous endpoints.
High-intent search queries and answers about installing and using this skill.
Build async APIs with FastAPI by applying production-grade patterns that integrate SQLAlchemy 2.0 asynchronously and validate data using Pydantic V2. This approach provides type-safe models and OpenAPI documentation for scalable microservices.
Yes, FastAPI WebSockets can stream real-time data to connected clients. You can build a real-time data service that pushes event updates to clients and stores those events in a scalable database using async SQLAlchemy integration.
Yes, this approach supports Pydantic V2 for async data validation. It applies production-grade patterns for microservices that require type-safe models, ensuring robust data validation and OpenAPI documentation generation in FastAPI.
The best way to structure a production-grade FastAPI microservice is using async-first API surfaces, SQLAlchemy 2.0 async integration, and Alembic migrations. This satisfies requirements for WebSockets, type-safe models, and deployment-ready patterns.
To run a new FastAPI project and verify asynchronous endpoints, start the application using uvicorn. This quickly validates your async-first API surface and confirms the production-grade patterns are functioning correctly.
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