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python-backend

python-backend

github.com/jiatasticDevelopment102.2k installsUpdated 40w ago
Repository

About python-backend

python-backend is a reference skill for developers building Python backends with FastAPI, SQLAlchemy, and Upstash. It provides patterns for API structure, async data access, validation, authentication, caching, and rate limiting.

Key features

  1. 01FastAPI project and API patterns
  2. 02Async SQLAlchemy database access
  3. 03Pydantic validation and dependency injection
  4. 04JWT and OAuth2 security patterns
  5. 05Upstash caching and rate limiting

Use cases

  1. 01Structuring a FastAPI REST API
  2. 02Adding async database access
  3. 03Implementing authentication and input validation
  4. 04Setting up caching or rate limiting

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/jiatastic/open-python-skills --skill python-backend

After installing, type/python-backendin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
database_patterns.md
fastapi_patterns.md
security_patterns.md
upstash_patterns.md

Details

From the project README

python-backend

Production-ready Python backend patterns for FastAPI, SQLAlchemy, and Upstash.

When to Use This Skill

  • Building REST APIs with FastAPI
  • Implementing JWT/OAuth2 authentication
  • Setting up SQLAlchemy async databases
  • Integrating Redis/Upstash caching and rate limiting
  • Refactoring AI-generated Python code
  • Designing API patterns and project structure

Core Principles

  1. Async-first - Use async/await for I/O operations
  2. Type everything - Pydantic models for validation
  3. Dependency injection - Use FastAPI's Depends()
  4. Fail fast - Validate early, use HTTPException
  5. Security by default - Never trust user input

Quick Patterns

Project Structure
src/
├── auth/
│   ├── router.py      # endpoints
│   ├── schemas.py     # pydantic models
│   ├── models.py      # db models
│   ├── service.py     # business logic
│   └── dependencies.py
├── posts/
│   └── ...
├── config.py
├── database.py
└── main.py
Async Routes
# BAD - blocks event loop
@router.get("/")
async def bad():
    time.sleep(10)  # Blocking!

# GOOD - runs in threadpool
@router.get("/")
def good():
    time.sleep(10)  # OK in sync function

# BEST - non-blocking
@router.get("/")
async def best():
    await asyncio.sleep(10)  # Non-blocking
Pydantic Validation
from pydantic import BaseModel, EmailStr, Field

class UserCreate(BaseModel):
    email: EmailStr
    username: str = Field(min_length=3, max_length=50, pattern="^[a-zA-Z0-9_]+$")
    age: int = Field(ge=18)
Dependency Injection
async def get_current_user(token: str = Depends(oauth2_scheme)) -> User:
    payload = decode_token(token)
    user = await get_user(payload["sub"])
    if not user:
        raise HTTPException(401, "User not found")
    return user

@router.get("/me")
async def get_me(user: User = Depends(get_current_user)):
    return user
SQLAlchemy Async
from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker, create_async_engine

engine = create_async_engine(DATABASE_URL, pool_pre_ping=True)
SessionLocal = async_sessionmaker(engine, expire_on_commit=False)

async def get_session() -> AsyncGenerator[AsyncSession, None]:
    async with SessionLocal() as session:
        yield session
Redis Caching
from upstash_redis import Redis

redis = Redis.from_env()

@app.get("/data/{id}")
def get_data(id: str):
    cached = redis.get(f"data:{id}")
    if cached:
        return cached
    data = fetch_from_db(id)
    redis.setex(f"data:{id}", 600, data)
    return data
Rate Limiting
from upstash_ratelimit import Ratelimit, SlidingWindow

ratelimit = Ratelimit(
    redis=Redis.from_env(),
    limiter=SlidingWindow(max_requests=10, window=60),
)

@app.get("/api/resource")
def protected(request: Request):
    result = ratelimit.limit(request.client.host)
    if not result.allowed:
        raise HTTPException(429, "Rate limit exceeded")
    return {"data": "..."}

Reference Documents

For detailed patterns, see:

DocumentContent
references/fastapi_patterns.mdProject structure, async, Pydantic, dependencies, testing
references/security_patterns.mdJWT, OAuth2, password hashing, CORS, API keys
references/database_patterns.mdSQLAlchemy async, transactions, eager loading, migrations
references/upstash_patterns.mdRedis, rate limiting, QStash background jobs

Resources

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