fastapi-expert
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.
Works with
---
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
---
# 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
1. **Analyze requirements** — Identify endpoints, data models, auth needs
2. **Design schemas** — Create Pydantic V2 models for validation
3. **Implement** — Write async endpoints with proper dependency injection
4. **Secure** — Add authentication, authorization, rate limiting
5. **Test** — Write async tests with pytest and httpx; run `pytest` after each endpoint group and verify OpenAPI docs at `/docs`
> **Checkpoint after each step:** confirm schemas validate correctly, endpoints return expected HTTP status codes, and `/docs` reflects the intended API surface before proceeding.
## Minimal Complete Example
Schema + endpoint + dependency injection in one cohesive unit:
```python
# 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
```
```python
# 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)
```
```python
# 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
```python
# 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 `Annotated` pattern for dependency injection
- Use async/await for all I/O operations
- Use `X | None` instead of `Optional[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:
1. Schema file (Pydantic models)
2. Endpoint file (router with endpoints)
3. CRUD operations if database involved
4. 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
[Documentation](https://jeffallan.github.io/claude-skills/skills/backend/fastapi-expert/)More API Design skills
lark-event
larksuite/cli
Lark/Feishu real-time event listening / subscribing / consuming: stream events as NDJSON via `lark-cli event consume <EventKey>` (covers IM messages/reactions/chat changes, Approval status changes, Task updates, VC meeting started/joined/ended, Minutes generated, Whiteboard updated, etc.). Use for Lark bots, real-time message processing, long-running subscribers, streaming webhook/push handlers. Supports `--max-events` / `--timeout` bounded runs and a stderr ready-marker contract — designed for AI agents running as subprocesses.
lark-contact
larksuite/cli
飞书 / Lark 通讯录:按姓名 / 邮箱解析成 open_id,或按 open_id 反查姓名 / 部门 / 邮箱 / 联系方式 / 个人状态 / 签名,以及按关键词搜索当前用户可见的机器人 / 智能体(agent)。当用户提到一个名字要下一步发消息 / 排日程,或拿到 open_id 想查具体信息时使用。不负责部门树遍历、按部门列员工、组织架构图,这类需求走原生 OpenAPI。
lark-openapi-explorer
larksuite/cli
飞书/Lark 原生 OpenAPI 探索:从官方文档库中挖掘未经 CLI 封装的原生 OpenAPI 接口。当用户的需求无法被现有 lark-* skill 或 lark-cli 已注册命令满足,需要查找并调用原生飞书 OpenAPI 时使用。

