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/fastapi

Use when building APIs with FastAPI. Covers dependency injection, Pydantic v2 validation, async database access, authentication, background tasks, and testing.

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$ npx -y skills add nimadorostkar/Claude-Skills-collection --skill fastapi --agent claude-code

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  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
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Use when building APIs with FastAPI. Covers dependency injection, Pydantic v2 validation, async database access, authentication, background tasks, and testing.

SKILL.md

fastapi.SKILL.md
name: fastapi
description: Use when building APIs with FastAPI. Covers dependency injection, Pydantic v2 validation, async database access, authentication, background tasks, and testing.
metadata:
  category: backend
  version: 1.0.0
  tags: [fastapi, python, pydantic, async, api]

FastAPI

Purpose

Build FastAPI services that use the framework's strengths — declarative validation and dependency injection — without falling into its two standard traps: blocking calls inside `async def`, and business logic in the route handler.

When to Use

  • Building or reviewing a FastAPI application.
  • Structuring dependencies, authentication, and database sessions.
  • Diagnosing latency that appears only under concurrency.
  • Writing tests for FastAPI endpoints.

Capabilities

  • Route and router organization.
  • Pydantic v2 models for request, response, and settings.
  • Dependency injection with scoped lifecycles.
  • Async SQLAlchemy sessions, correctly scoped per request.
  • Authentication and authorization dependencies.
  • Testing with `httpx.AsyncClient` and dependency overrides.

Inputs

  • The API contract and the data layer.
  • Whether the workload is I/O-bound (nearly always) or CPU-bound.

Outputs

  • Thin route handlers delegating to service functions.
  • Response models that control exactly what is serialized.
  • A test suite that overrides dependencies rather than mocking internals.

Workflow

1. **Define the schemas** — Separate request, response, and internal models. Never return an ORM object directly; a `response_model` is your defense against leaking a password hash. 2. **Build the dependencies** — Database session, current user, feature flags. These are the injection points that make the app testable. 3. **Keep handlers thin** — Parse, authorize, delegate, return. Business logic lives in a service module that knows nothing about HTTP. 4. **Get async right** — In an `async def` handler, every I/O call must be awaited. A blocking call there stalls the entire event loop, not just that request. 5. **Test through the app** — `httpx.AsyncClient` with `app.dependency_overrides` gives you real routing, real validation, and a fake database.

Best Practices

  • A blocking call inside `async def` (a sync DB driver, `requests`, `time.sleep`) blocks every concurrent request on that worker. If a handler must call blocking code, define it as `def` — FastAPI runs it in a thread pool.
  • Always set `response_model`. Without it, whatever your service returns is what the client sees, including fields you added last week.
  • Use `Annotated[Session, Depends(get_session)]` — it keeps signatures readable and reusable.
  • Validate settings with `pydantic-settings` at startup. Fail to boot on a bad config rather than at 3am on the first request that touches it.
  • `BackgroundTasks` runs in the same process and dies with it. For anything that must not be lost, use a real queue.
  • Mount routers by domain, not by HTTP verb.

Examples

**Dependency-injected handler and an overridable test:**

from typing import Annotated
from fastapi import APIRouter, Depends, HTTPException, status

router = APIRouter(prefix="/orders", tags=["orders"])

SessionDep = Annotated[AsyncSession, Depends(get_session)]
CurrentUser = Annotated[User, Depends(get_current_user)]


@router.post("", response_model=OrderRead, status_code=status.HTTP_201_CREATED)
async def create_order(
    payload: OrderCreate,
    session: SessionDep,
    user: CurrentUser,
) -> Order:
    try:
        return await orders.place(session, customer_id=user.id, items=payload.items)
    except InsufficientInventory as e:
        raise HTTPException(status.HTTP_409_CONFLICT, detail=str(e)) from e
@pytest.fixture
async def client(session: AsyncSession) -> AsyncIterator[AsyncClient]:
    app.dependency_overrides[get_session] = lambda: session
    app.dependency_overrides[get_current_user] = lambda: User(id="usr_test")
    transport = ASGITransport(app=app)
    async with AsyncClient(transport=transport, base_url="http://test") as c:
        yield c
    app.dependency_overrides.clear()

Notes

  • Pydantic v2 is roughly an order of magnitude faster than v1 on validation, but `Config` classes, validators, and `.dict()` all changed. Do not mix idioms.
  • `@lru_cache` on a settings factory is the standard way to make configuration a singleton dependency.
  • FastAPI's generated OpenAPI schema is only as good as your response models and status codes. Treat the generated docs as a review artifact.
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