How to handle multiple async requests in FastAPI with shared resources without race conditions?
I'm having trouble with I'm currently building an API using FastAPI (v0.68.0) where I need to handle multiple async requests that access and modify shared resources represented by a global dictionary. When I run concurrent requests, I encounter race conditions that cause data corruption. Specifically, I'm seeing instances where the values in the shared dictionary get overwritten unexpectedly. Here's a simplified version of my code: ```python from fastapi import FastAPI, HTTPException import asyncio app = FastAPI() shared_data = {} @app.post('/update/{key}') async def update_data(key: str, value: str): if key in shared_data: raise HTTPException(status_code=400, detail="Key already exists") await asyncio.sleep(0.1) # Simulate some async operation shared_data[key] = value return {"message": "Data updated successfully"} @app.get('/data/{key}') async def read_data(key: str): return {"key": key, "value": shared_data.get(key, "Not found")} ``` I've tried using locks with `asyncio.Lock`, but I'm not sure how to implement it correctly to prevent race conditions while still maintaining performance. Here’s what I attempted: ```python lock = asyncio.Lock() @app.post('/update/{key}') async def update_data(key: str, value: str): async with lock: if key in shared_data: raise HTTPException(status_code=400, detail="Key already exists") await asyncio.sleep(0.1) # Simulate some async operation shared_data[key] = value return {"message": "Data updated successfully"} ``` However, I'm still encountering issues where simultaneous requests seem to interfere with each other, especially when I increase the load. Can anyone suggest the best practices for managing shared state in FastAPI with async operations without facing these race conditions? I'm also concerned about the performance implications of using locks when handling high traffic. Am I missing something obvious?