Async SQLAlchemy Session Handling in FastAPI with PostgreSQL
I'm performance testing and I'm working with an scenario when trying to use SQLAlchemy with async functionality in my FastAPI application. I have a PostgreSQL database, and I'm utilizing the `asyncpg` driver along with `SQLAlchemy 1.4`. The question arises when I try to perform multiple database operations simultaneously, which results in a `RuntimeError: Task '...' got interrupted` behavior. I have set up my database session like this: ```python from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine from sqlalchemy.orm import sessionmaker DATABASE_URL = 'postgresql+asyncpg://user:password@localhost/dbname' engine = create_async_engine(DATABASE_URL, echo=True) session_local = sessionmaker(engine, class_=AsyncSession, expire_on_commit=False) ``` In my FastAPI route, I am trying to fetch and update records like so: ```python from fastapi import FastAPI, Depends from sqlalchemy.ext.asyncio import AsyncSession app = FastAPI() async def get_db() -> AsyncSession: async with session_local() as session: yield session @app.get('/items/{item_id}') async def read_item(item_id: int, db: AsyncSession = Depends(get_db)): result = await db.execute(select(Item).where(Item.id == item_id)) item = result.scalar_one_or_none() return item @app.put('/items/{item_id}') async def update_item(item_id: int, update_data: ItemUpdate, db: AsyncSession = Depends(get_db)): await db.execute(update(Item).where(Item.id == item_id).values(**update_data.dict())) await db.commit() return {'message': 'Item updated'} ``` When I try to hit the update endpoint while the read endpoint is being executed, I get the behavior mentioned above. I also ensured that all database interactions are awaited properly. I've tried wrapping the session management in a try-except block to catch any exceptions, but that hasn’t resolved the scenario. Any suggestions on how to handle concurrent database operations more effectively in FastAPI using async SQLAlchemy? I'm working on a application that needs to handle this. Any help would be greatly appreciated! My team is using Python for this CLI tool. What's the best practice here?