classes-instead-of-dicts

Using pydantic models instead of dicts enforces typed schema contracts, preventing runtime errors by validating data at boundaries and improving API reliability, testing, and maintainability.

Refactor legacy dict-based payloads by replacing them with pydantic.BaseModel classes for input/output validation and SQLAlchemy models for persistence, updating API handlers to accept typed inputs.

Typed classes for data exchange are needed when adding or modifying classes, planning storage logic, or designing API interfaces across Python projects using pydantic and SQLAlchemy to ensure reliable validation.

Yes, this approach works with pydantic and SQLAlchemy by using pydantic.BaseModel for input/output validation and SQLAlchemy models for persistence, ensuring clear separation between transfer objects and persistence schemas.

The best way to enforce validation at API boundaries is preferring explicit typed classes like pydantic.BaseModel over freeform dicts, ensuring data exchange is validated and API contracts are strictly typed.