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Skills/jiatastic/open-python-skills/python-backend
python-backend logo

python-backend

jiatastic/open-python-skills
2K installs4 stars
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Installation

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

Summary

>

SKILL.md

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

  • FastAPI Documentation
  • SQLAlchemy 2.0 Documentation
  • Upstash Documentation
  • Pydantic Documentation

Score

0–100
55/ 100

Grade

C

Popularity15/30

1,649 installs — growing adoption.

Completeness19/30

Documented: full SKILL.md body, one-line install. Missing: description, category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Python Backend skill score badge previewScore badge

Markdown

[![Python Backend skill](https://www.remoteopenclaw.com/skills/jiatastic/open-python-skills/python-backend/badges/score.svg)](https://www.remoteopenclaw.com/skills/jiatastic/open-python-skills/python-backend)

HTML

<a href="https://www.remoteopenclaw.com/skills/jiatastic/open-python-skills/python-backend"><img src="https://www.remoteopenclaw.com/skills/jiatastic/open-python-skills/python-backend/badges/score.svg" alt="Python Backend skill"/></a>

Python Backend FAQ

How do I install the Python Backend skill?

Run “npx skills add https://github.com/jiatastic/open-python-skills --skill python-backend” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Python Backend skill do?

> The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Python Backend skill free?

Yes. Python Backend is a free, open-source skill published from jiatastic/open-python-skills. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Python Backend work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Python Backend works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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