fastapi-patterns

FastAPI dependency injection patterns standardize how shared logic and database sessions are provided to async endpoints. This skill provides blueprints for organizing dependencies hierarchically to ensure consistency across large projects and simplify testing scaffolds.

Pydantic v2 schemas using from_attributes allow direct conversion from ORM objects to response models in FastAPI. This skill provides standardized patterns for defining validation schemas, ensuring consistent request parsing and response serialization across your API endpoints.

FastAPI async middleware intercepts requests for processing like authentication or logging, while background tasks handle post-response operations. This skill applies standardized patterns for implementing both, ensuring non-blocking operations are correctly structured within your application architecture.

Yes, Pydantic v2 is required alongside FastAPI in your Python environment to implement these standardized patterns. The schemas and validation approaches specifically leverage Pydantic v2 features like from_attributes, making both packages prerequisites for applying the blueprints.

FastAPI testing scaffolds require structured test client setups and fixture management for async endpoints. This skill provides error handling templates and testing patterns that standardize how API responses are validated and how exceptions are consistently managed across projects.