Develop Python/FastAPI backend APIs with Pydantic validation and SQLAlchemy 2.0 async patterns.
npx skills add https://github.com/Donnadieu/continuum --skill backend-donnadieu
Please help me install this Agent Skill. Skill: backend Source: https://github.com/Donnadieu/continuum/tree/main/.claude/skills/backend Command: npx skills add https://github.com/Donnadieu/continuum --skill backend-donnadieu
This Skill provides a comprehensive set of patterns and best practices for developing the Python/FastAPI backend of the Continuum platform, ensuring consistency, maintainability, and adherence to core principles.
Use the backend skill to implement a new API endpoint for managing user profiles.
High-intent search queries and answers about installing and using this skill.
The best way to structure an async FastAPI backend is using a service layer architecture with SQLAlchemy 2.0 async patterns, separating business logic from API routes through repositories. This ensures maintainability and adherence to async-first principles.
To validate API request data in FastAPI, use Pydantic schema design for route definitions and data models. Pydantic enforces type hinting and validation principles, ensuring payloads conform to expected formats before reaching your service layer.
Yes, this FastAPI backend pattern supports Neo4j graph operations alongside standard PostgreSQL interactions. It provides specific guidelines for integrating graph database queries within your service layer architecture while maintaining provenance tracking.
To test FastAPI endpoints with pytest, implement robust unit and integration testing strategies that validate API routes, Pydantic schemas, and service layer logic. This ensures comprehensive coverage across repository patterns and database interactions.
Yes, you can implement background worker tasks within a Python FastAPI backend. This skill provides specific patterns for structuring asynchronous background jobs while maintaining user isolation and provenance tracking principles.
Use the repository pattern in SQLAlchemy 2.0 async applications to abstract database operations from business logic. This separation enforces service layer architecture, ensuring consistent data access flows and maintainable async database interactions.
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