fastapi
Provides comprehensive guidance for FastAPI framework including routing, request validation, dependency injection, async operations, OpenAPI documentation, and database integration. Use when the user asks about FastAPI, needs to create REST APIs, or build high-performance Python web services.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/fastapi/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How fastapi Compares
| Feature / Agent | fastapi | Standard Approach |
|---|---|---|
| Platform Support | multi | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Provides comprehensive guidance for FastAPI framework including routing, request validation, dependency injection, async operations, OpenAPI documentation, and database integration. Use when the user asks about FastAPI, needs to create REST APIs, or build high-performance Python web services.
Which AI agents support this skill?
This skill is compatible with multi.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
## When to use this skill
Use this skill whenever the user wants to:
- Build REST or async APIs with FastAPI and Pydantic models
- Implement dependency injection, authentication, or middleware
- Configure routing, OpenAPI documentation, and deployment
- Integrate with databases using async patterns
## How to use this skill
### Workflow
1. **Create app** — instantiate `FastAPI()` and define route handlers
2. **Define models** — use Pydantic for request/response validation
3. **Add dependencies** — implement DI for auth, DB sessions, etc.
4. **Test and deploy** — run with uvicorn, verify via `/docs`
### Quick Start Example
```python
from fastapi import FastAPI, HTTPException, Depends
from pydantic import BaseModel
from datetime import datetime
app = FastAPI(title="My API", version="1.0.0")
# Request/Response models
class ItemCreate(BaseModel):
name: str
price: float
description: str | None = None
class ItemResponse(ItemCreate):
id: int
created_at: datetime
# Dependency example
async def get_db():
db = SessionLocal()
try:
yield db
finally:
db.close()
# Route handlers
@app.post("/items/", response_model=ItemResponse, status_code=201)
async def create_item(item: ItemCreate, db=Depends(get_db)):
db_item = Item(**item.model_dump())
db.add(db_item)
db.commit()
return db_item
@app.get("/items/{item_id}", response_model=ItemResponse)
async def get_item(item_id: int, db=Depends(get_db)):
item = db.query(Item).get(item_id)
if not item:
raise HTTPException(status_code=404, detail="Item not found")
return item
```
```bash
# Run the server
uvicorn main:app --reload
# Interactive docs available at http://localhost:8000/docs
```
### Authentication Example
```python
from fastapi.security import OAuth2PasswordBearer
oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")
@app.get("/users/me")
async def read_current_user(token: str = Depends(oauth2_scheme)):
user = verify_token(token)
if not user:
raise HTTPException(status_code=401, detail="Invalid token")
return user
```
## Best Practices
- Define explicit request and response schemas with Pydantic; use consistent status codes
- Use async functions and database connection pools for high concurrency
- Configure CORS middleware and security headers for production
- Leverage automatic OpenAPI docs (`/docs`, `/redoc`) for API exploration
- Use `BackgroundTasks` for non-blocking operations like email sending
## Reference
- Official documentation: https://fastapi.tiangolo.com/
## Keywords
fastapi, async API, Pydantic, OpenAPI, dependency injection, Python web, REST API, uvicorn