Backend Python Expert

Structure FastAPI backends by implementing repository patterns for database access and service layers for business logic. This architecture ensures scalable APIs, separates concerns, and maintains code quality across teams.

Optimize async Python performance through profiling, tuning, caching, and scalable architectures. Analyze bottlenecks in production-like environments to improve throughput and reduce latency in asynchronous services.

Implement dependency injection in FastAPI using type safety and Pydantic-based validation. This ensures robust API endpoints, comprehensive error handling, and maintainable code structures across teams.

Refactor existing services to asynchronous patterns by applying async programming techniques. This transition improves performance and scalability while maintaining code integrity.

Testing strategies for FastAPI backends include comprehensive error handling and validation tests. These strategies ensure robust APIs and maintainable code quality across teams.

Implement Pydantic-based validation when building FastAPI backends requiring type safety. This ensures robust APIs, comprehensive error handling, and maintainable code structures.