backend-patterns

Structure a FastAPI backend using a router-service-model pattern to separate concerns, paired with SQLAlchemy 2.x async data access and Alembic migrations. This enforces consistent API design, modular organization, and reduces boilerplate across modules.

Implement device-scoped queries and soft deletes using a service layer with dependency injection in FastAPI. This separates data access logic from routes, enforcing security-conscious querying and robust error handling across modules.

Set up FastAPI authentication and configuration using Pydantic settings for environment management and a service layer pattern. This approach isolates security logic and configuration validation, ensuring robust and maintainable API design.

Yes, this backend pattern explicitly supports async SQLAlchemy 2.x for data access and Alembic for database migrations. It integrates these tools within a router-service-model architecture to manage schema changes and async queries safely.

Scaffold pytest for a FastAPI project by applying a router-service-model pattern that isolates business logic. This allows targeted unit testing of services and data access layers, ensuring robust error handling and consistent test coverage.

Use a service layer pattern in FastAPI to separate routing logic from data access, enforcing device-scoping and soft deletes. This reduces boilerplate, centralizes error handling, and ensures scalable, maintainable software architecture.