fastapi-expert
jeffallan/claude-skills
Deep expertise in async Python, Pydantic V2, and production-grade API development with FastAPI.
What is fastapi-expert?
Use when building high-performance async Python APIs with FastAPI and Pydantic V2. This skill helps you create REST endpoints, define Pydantic models, implement authentication flows, set up async SQLAlchemy database operations, add JWT authentication, build WebSocket endpoints, and generate OpenAPI documentation.
- Create REST endpoints with FastAPI routers and proper HTTP status codes
- Define and validate data models using Pydantic V2 schemas with field validators
- Implement async database operations with SQLAlchemy and CRUD patterns
- Add JWT authentication and OAuth2 security flows
- Build WebSocket endpoints for real-time communication
- Generate and document OpenAPI/Swagger specifications automatically
How to install fastapi-expert
npx skills add https://github.com/jeffallan/claude-skills --skill fastapi-expert- Python 3.10+
- FastAPI and Pydantic V2 installed
- SQLAlchemy with async support (optional, for database operations)
- Knowledge of async/await patterns in Python
How to use fastapi-expert
- 1.Analyze your API requirements and identify endpoints, data models, and authentication needs
- 2.Design Pydantic V2 schemas for request/response validation using field_validator and model_config
- 3.Implement async endpoints using APIRouter with proper dependency injection via Annotated
- 4.Add JWT authentication using OAuth2PasswordBearer and token creation/verification
- 5.Write async tests with pytest-asyncio and httpx, verifying endpoints and OpenAPI docs at /docs
- 6.Deploy with proper environment variable configuration for secrets
Use cases
- Building a user authentication system with JWT tokens and password hashing
- Creating a REST API with async database queries and Pydantic validation
- Implementing role-based access control with dependency injection
- Setting up WebSocket endpoints for real-time data streaming
- Migrating from Django REST Framework to FastAPI with async operations
- Backend developers building Python APIs
- Full-stack engineers implementing async services
- Teams migrating from Django/DRF to FastAPI
- Developers needing production-grade authentication and validation
fastapi-expert FAQ
Always use Pydantic V2 syntax: field_validator, model_validator, and model_config instead of the deprecated @validator and class Config patterns.
Use SQLAlchemy's AsyncSession with async/await, execute queries with await db.execute(), and commit with await db.commit(). Never use synchronous database calls.
Use OAuth2PasswordBearer with JWT tokens. Create access tokens with an expiration time, verify them in a get_current_user dependency, and use Annotated to inject the current user into endpoints.
FastAPI generates OpenAPI docs automatically at /docs (Swagger UI) and /redoc (ReDoc). Ensure endpoints have proper response_model definitions and docstrings for full documentation.
Avoid mixing sync and async code. Use async/await for all I/O operations (database, HTTP calls). If you must call sync code, use run_in_threadpool from FastAPI.
Full instructions (SKILL.md)
Source of truth, from jeffallan/claude-skills.
name: fastapi-expert description: "Use when building high-performance async Python APIs with FastAPI and Pydantic V2. Invoke to create REST endpoints, define Pydantic models, implement authentication flows, set up async SQLAlchemy database operations, add JWT authentication, build WebSocket endpoints, or generate OpenAPI documentation. Trigger terms: FastAPI, Pydantic, async Python, Python API, REST API Python, SQLAlchemy async, JWT authentication, OpenAPI, Swagger Python." license: MIT metadata: author: https://github.com/Jeffallan version: "1.1.0" domain: backend triggers: FastAPI, Pydantic, async Python, Python API, REST API Python, SQLAlchemy async, JWT authentication, OpenAPI, Swagger Python role: specialist scope: implementation output-format: code related-skills: fullstack-guardian, django-expert, test-master
FastAPI Expert
Deep expertise in async Python, Pydantic V2, and production-grade API development with FastAPI.
When to Use This Skill
- Building REST APIs with FastAPI
- Implementing Pydantic V2 validation schemas
- Setting up async database operations
- Implementing JWT authentication/authorization
- Creating WebSocket endpoints
- Optimizing API performance
Core Workflow
- Analyze requirements — Identify endpoints, data models, auth needs
- Design schemas — Create Pydantic V2 models for validation
- Implement — Write async endpoints with proper dependency injection
- Secure — Add authentication, authorization, rate limiting
- Test — Write async tests with pytest and httpx; run
pytestafter each endpoint group and verify OpenAPI docs at/docs
Checkpoint after each step: confirm schemas validate correctly, endpoints return expected HTTP status codes, and
/docsreflects the intended API surface before proceeding.
Minimal Complete Example
Schema + endpoint + dependency injection in one cohesive unit:
# schemas.py
from pydantic import BaseModel, EmailStr, field_validator, model_config
class UserCreate(BaseModel):
model_config = model_config(str_strip_whitespace=True)
email: EmailStr
password: str
name: str | None = None
@field_validator("password")
@classmethod
def password_strength(cls, v: str) -> str:
if len(v) < 8:
raise ValueError("Password must be at least 8 characters")
return v
class UserResponse(BaseModel):
model_config = model_config(from_attributes=True)
id: int
email: EmailStr
name: str | None = None
# routers/users.py
from fastapi import APIRouter, Depends, HTTPException, status
from sqlalchemy.ext.asyncio import AsyncSession
from typing import Annotated
from app.database import get_db
from app.schemas import UserCreate, UserResponse
from app import crud
router = APIRouter(prefix="/users", tags=["users"])
DbDep = Annotated[AsyncSession, Depends(get_db)]
@router.post("/", response_model=UserResponse, status_code=status.HTTP_201_CREATED)
async def create_user(payload: UserCreate, db: DbDep) -> UserResponse:
existing = await crud.get_user_by_email(db, payload.email)
if existing:
raise HTTPException(status_code=status.HTTP_409_CONFLICT, detail="Email already registered")
return await crud.create_user(db, payload)
# crud.py
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from app.models import User
from app.schemas import UserCreate
from app.security import hash_password
async def get_user_by_email(db: AsyncSession, email: str) -> User | None:
result = await db.execute(select(User).where(User.email == email))
return result.scalar_one_or_none()
async def create_user(db: AsyncSession, payload: UserCreate) -> User:
user = User(email=payload.email, hashed_password=hash_password(payload.password), name=payload.name)
db.add(user)
await db.commit()
await db.refresh(user)
return user
JWT Authentication Snippet
# security.py
from datetime import datetime, timedelta, timezone
from jose import JWTError, jwt
from fastapi import Depends, HTTPException, status
from fastapi.security import OAuth2PasswordBearer
from typing import Annotated
SECRET_KEY = "read-from-env" # use os.environ / settings
ALGORITHM = "HS256"
oauth2_scheme = OAuth2PasswordBearer(tokenUrl="/auth/token")
def create_access_token(subject: str, expires_delta: timedelta = timedelta(minutes=30)) -> str:
payload = {"sub": subject, "exp": datetime.now(timezone.utc) + expires_delta}
return jwt.encode(payload, SECRET_KEY, algorithm=ALGORITHM)
async def get_current_user(token: Annotated[str, Depends(oauth2_scheme)]) -> str:
try:
data = jwt.decode(token, SECRET_KEY, algorithms=[ALGORITHM])
subject: str | None = data.get("sub")
if subject is None:
raise ValueError
return subject
except (JWTError, ValueError):
raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="Invalid credentials")
CurrentUser = Annotated[str, Depends(get_current_user)]
Reference Guide
Load detailed guidance based on context:
| Topic | Reference | Load When |
|---|---|---|
| Pydantic V2 | references/pydantic-v2.md | Creating schemas, validation, model_config |
| SQLAlchemy | references/async-sqlalchemy.md | Async database, models, CRUD operations |
| Endpoints | references/endpoints-routing.md | APIRouter, dependencies, routing |
| Authentication | references/authentication.md | JWT, OAuth2, get_current_user |
| Testing | references/testing-async.md | pytest-asyncio, httpx, fixtures |
| Django Migration | references/migration-from-django.md | Migrating from Django/DRF to FastAPI |
Constraints
MUST DO
- Use type hints everywhere (FastAPI requires them)
- Use Pydantic V2 syntax (
field_validator,model_validator,model_config) - Use
Annotatedpattern for dependency injection - Use async/await for all I/O operations
- Use
X | Noneinstead ofOptional[X] - Return proper HTTP status codes
- Document endpoints (auto-generated OpenAPI)
MUST NOT DO
- Use synchronous database operations
- Skip Pydantic validation
- Store passwords in plain text
- Expose sensitive data in responses
- Use Pydantic V1 syntax (
@validator,class Config) - Mix sync and async code improperly
- Hardcode configuration values
Output Templates
When implementing FastAPI features, provide:
- Schema file (Pydantic models)
- Endpoint file (router with endpoints)
- CRUD operations if database involved
- Brief explanation of key decisions
Knowledge Reference
FastAPI, Pydantic V2, async SQLAlchemy, Alembic migrations, JWT/OAuth2, pytest-asyncio, httpx, BackgroundTasks, WebSockets, dependency injection, OpenAPI/Swagger
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