Agent Skills: Python Backend

Python backend patterns for asyncio, FastAPI, SQLAlchemy 2.0 async, and connection pooling. Use when building async Python services, FastAPI endpoints, database sessions, or connection pool tuning.

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src/skills/python-backend/SKILL.md

Skill Metadata

Name
python-backend
Description
Python backend patterns for asyncio, FastAPI, SQLAlchemy 2.0 async, and connection pooling. Use when building async Python services, FastAPI endpoints, database sessions, or connection pool tuning.

Python Backend

Patterns for building production Python backends with asyncio, FastAPI, SQLAlchemy 2.0, and connection pooling. Each category has individual rule files in rules/ loaded on-demand.

Quick Reference

| Category | Rules | Impact | When to Use | |----------|-------|--------|-------------| | Asyncio | 3 | HIGH | TaskGroup, structured concurrency, cancellation handling | | FastAPI | 3 | HIGH | Dependencies, middleware, background tasks | | SQLAlchemy | 3 | HIGH | Async sessions, relationships, migrations | | Pooling | 3 | MEDIUM | Database pools, HTTP sessions, tuning |

Total: 12 rules across 4 categories

Quick Start

# FastAPI + SQLAlchemy async session
async def get_db() -> AsyncGenerator[AsyncSession, None]:
    async with async_session_factory() as session:
        try:
            yield session
            await session.commit()
        except Exception:
            await session.rollback()
            raise

@router.get("/users/{user_id}")
async def get_user(user_id: UUID, db: AsyncSession = Depends(get_db)):
    result = await db.execute(select(User).where(User.id == user_id))
    return result.scalar_one_or_none()
# Asyncio TaskGroup with timeout
async def fetch_all(urls: list[str]) -> list[dict]:
    async with asyncio.timeout(30):
        async with asyncio.TaskGroup() as tg:
            tasks = [tg.create_task(fetch_url(url)) for url in urls]
    return [t.result() for t in tasks]

Asyncio

Modern Python asyncio patterns using structured concurrency, TaskGroup, and Python 3.11+ features.

Key Patterns

  • TaskGroup replaces gather() with structured concurrency and auto-cancellation
  • asyncio.timeout() context manager for composable timeouts
  • Semaphore for concurrency limiting (rate-limit HTTP requests)
  • except* with ExceptionGroup for handling multiple task failures
  • asyncio.to_thread() for bridging sync code to async

Key Decisions

| Decision | Recommendation | |----------|----------------| | Task spawning | TaskGroup not gather() | | Timeouts | asyncio.timeout() context manager | | Concurrency limit | asyncio.Semaphore | | Sync bridge | asyncio.to_thread() | | Cancellation | Always re-raise CancelledError |

FastAPI

Production-ready FastAPI patterns for lifespan, dependencies, middleware, and settings.

Key Patterns

  • Lifespan with asynccontextmanager for startup/shutdown resource management
  • Dependency injection with class-based services and Depends()
  • Middleware stack: CORS -> RequestID -> Timing -> Logging
  • Pydantic Settings with .env and field validation
  • Exception handlers with RFC 9457 Problem Details

Key Decisions

| Decision | Recommendation | |----------|----------------| | Lifespan | asynccontextmanager (not events) | | Dependencies | Class-based services with DI | | Settings | Pydantic Settings with .env | | Response | ORJSONResponse for performance | | Health | Check all critical dependencies |

SQLAlchemy

Async database patterns with SQLAlchemy 2.0, AsyncSession, and FastAPI integration.

Key Patterns

  • One AsyncSession per request with expire_on_commit=False
  • lazy="raise" on relationships to prevent accidental N+1 queries
  • selectinload for eager loading collections
  • Repository pattern with generic async CRUD
  • Bulk inserts chunked 1000-10000 rows for memory management

Key Decisions

| Decision | Recommendation | |----------|----------------| | Session scope | One AsyncSession per request | | Lazy loading | lazy="raise" + explicit loads | | Eager loading | selectinload for collections | | expire_on_commit | False (prevents lazy load errors) | | Pool | pool_pre_ping=True |

Pooling

Database and HTTP connection pooling for high-performance async Python applications.

Key Patterns

  • SQLAlchemy pool with pool_size, max_overflow, pool_pre_ping
  • Direct asyncpg pool with min_size/max_size and connection lifecycle
  • aiohttp session with TCPConnector limits and DNS caching
  • FastAPI lifespan creating and closing pools at startup/shutdown
  • Pool monitoring with Prometheus metrics

Pool Sizing Formula

pool_size = (concurrent_requests / avg_queries_per_request) * 1.5

Anti-Patterns (FORBIDDEN)

# NEVER use gather() for new code - no structured concurrency
# NEVER swallow CancelledError - breaks TaskGroup and timeout
# NEVER block the event loop with sync calls (time.sleep, requests.get)
# NEVER use global mutable state for db sessions
# NEVER skip dependency injection (create sessions in routes)
# NEVER share AsyncSession across tasks (race condition)
# NEVER use sync Session in async code (blocks event loop)
# NEVER create engine/pool per request
# NEVER forget to close pools on shutdown

Related Skills

  • ork:architecture-patterns - Clean architecture and layer separation
  • ork:async-jobs - Celery/ARQ for background processing
  • streaming-api-patterns - SSE/WebSocket async patterns
  • ork:database-patterns - Database schema design