backend-python

Build a Python backend using TDD by writing failing tests first with pytest, then implementing API endpoints and service layers to pass them. This approach enforces clean architecture boundaries, strict typing, and Pydantic model usage for reliable services.

The best way to structure SQLAlchemy data migrations is using Alembic with disciplined migration hygiene. This Skill provides patterns and rules for maintainable migrations, ensuring database schema changes align with domain models and clean architecture boundaries.

Yes, you can and should use Pydantic models for API input validation. This Skill requires strict Pydantic model usage to define API inputs, enforcing strict typing and ensuring reliable data handling before requests reach your service layers.

Test-driven development for Python API endpoints works by defining a strict Pydantic model for your API input and writing a failing test with pytest first, then implementing the endpoint logic to pass the test.

You need pytest for TDD workflows and Alembic for database migration hygiene to fully apply clean architecture in Python. These tools enforce testing discipline and structured data migrations across service layers and repository boundaries.

You should use a service layer pattern in backend Python applications to separate business logic from API endpoints and repository boundaries. This clean architecture approach prevents brittle APIs and ensures maintainable, strictly typed code.