Design FastAPI applications with Service Layer pattern and Pydantic v2 validation.
npx skills add https://github.com/ulf1/trading-regime --skill 303-fastapi
Please help me install this Agent Skill. Skill: 303-fastapi Source: https://github.com/ulf1/trading-regime/tree/main/.agent/skills/303-fastapi Command: npx skills add https://github.com/ulf1/trading-regime --skill 303-fastapi
It solves the challenge of building production-grade FastAPI backends reliably by enforcing a clean Service Layer architecture, correct async/sync concurrency behavior, and consistent error handling that keeps business logic independent from HTTP concerns.
TestClient, dependency_overrides, and fixture-based cleanup to prevent cross-test leakage.Ask the AI to scaffold a FastAPI app using the Service Layer pattern, add Pydantic v2 request/response models, implement global exception mapping for service errors, and generate unit tests using TestClient with dependency overrides.
High-intent search queries and answers about installing and using this skill.
Use the Service Layer pattern in FastAPI to separate Transport (routers/controllers) from Business Logic (services). This keeps your rules stable and testable, independent from HTTP concerns. It enforces strict Transport-to-Service separation for reliable backends.
Test FastAPI services using TestClient and pytest-asyncio with dependency_overrides. This approach ensures deterministic unit tests and uses fixture-based cleanup to prevent cross-test leakage, keeping your service layer testable and stable.
Handle async/sync concurrency in FastAPI by using async I/O for non-blocking operations, routing sync I/O through FastAPI's threadpool, and offloading CPU-bound work to processes. This matrix ensures reliable behavior under high-concurrency traffic.
The best way to map service exceptions to HTTP responses in FastAPI is by implementing global exception handling at the perimeter. This keeps business logic independent from HTTP concerns while ensuring consistent error responses across your RESTful API.
Yes, using Pydantic v2 for request and response validation in FastAPI enforces explicit schema rigor. This reduces runtime contract drift and ensures your API endpoints validate input correctly before delegating logic to the service layer.
Yes, you can build high-concurrency trading data APIs with FastAPI using the Service Layer pattern. It supports Pydantic v2 validation, correct async/sync concurrency, and deterministic unit tests for production-grade behavior.
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