Python FastAPI Stack

Structure a FastAPI project by organizing code into modular routers, Pydantic schemas, services, and dependencies. This enforces clean separation of concerns, type-safety, and lifecycle management for scalable, testable backends.

The best way to separate concerns in FastAPI is using a conventional architecture pattern that isolates routers for endpoints, schemas for validation, and services for business logic, reducing onboarding time and improving reliability.

Yes, you can use Pydantic v2 and SQLAlchemy with this FastAPI architecture. The structure leverages Pydantic v2 for strong typing and data validation, while SQLAlchemy handles database interactions within the service layers.

Manage application lifespan and error handling in FastAPI by applying the provided lifespan pattern and robust error handling mechanisms. This lifecycle management improves backend reliability and maintains clear interfaces.

No external Skill dependencies are required to scaffold a FastAPI application this way. The architecture blueprint applies conventional patterns directly to projects building RESTful services using FastAPI, Pydantic, and SQLAlchemy.