FastAPI

What This Skill Does

The FastAPI skill empowers OpenClaw to architect and maintain production-grade Python web services. It encapsulates expert knowledge on building high-performance asynchronous APIs, leveraging Pydantic v2 for data validation, and managing complex dependency injection patterns. This skill ensures your API implementation adheres to best practices, such as preventing event-loop blockage, managing lifespan events correctly, and implementing robust error handling across your stack.

Installation

To integrate this skill into your environment, run the following command in your terminal: clawhub install openclaw/skills/skills/ivangdavila/fastapi

Use Cases

• Rapid API Development: Quickly scaffold RESTful endpoints with automatic OpenAPI documentation and strict data typing.
• Async Optimization: Refactor synchronous blocking code to non-blocking asynchronous patterns to handle high concurrent traffic.
• Microservices Orchestration: Manage DB connections, shared state, and lifecycle events within containerized services.
• Data Integrity: Implement complex Pydantic models for request validation to ensure only valid data reaches your business logic.

Example Prompts

1. "Analyze my FastAPI endpoint and identify if I'm accidentally blocking the event loop with synchronous database drivers."
2. "Show me the modern way to handle lifespan events in FastAPI using the async context manager instead of the deprecated startup event."
3. "Refactor this Pydantic model to use Field(default_factory=list) instead of shared mutable list defaults."

Tips & Limitations

This skill is designed for development and architectural guidance. Users must be aware of the 'Async Traps' documented, specifically avoiding time.sleep() and ensuring that CPU-bound tasks are offloaded to executors. Remember that dependencies are cached per request; misuse of stateful dependencies can lead to memory bloat if not carefully managed using lru_cache or app.state. Always use Pydantic v2 methods (model_validate, model_dump) as v1 syntax is deprecated. While the skill provides architectural advice and code snippets, it does not replace the need for unit testing your specific business logic. Finally, avoid returning raw Pydantic models; returning dictionaries is preferred for performance in high-throughput applications.