👀 Views: 88 💬 Answers: 1 📅 Created: 2025-08-22

fastapi asyncio memory-leak Python

I'm working with a memory leak scenario in my FastAPI application when using background tasks with async functions. The application processes a important amount of data, and I've implemented a background task that runs an async function to handle data processing. However, over time, the application consumes more and more memory, leading to performance degradation. Here's a simplified version of the code I'm using: ```python from fastapi import FastAPI, BackgroundTasks import asyncio app = FastAPI() async def process_data(data): await asyncio.sleep(5) # Simulate a long-running task # Process the data here @app.post("/start-task/") async def start_task(data: str, background_tasks: BackgroundTasks): background_tasks.add_task(process_data, data) return {"message": "Task started"} ``` I have tried using `gc.collect()` to force garbage collection after each task, but it hasn't made a noticeable difference. I also monitored memory usage with the `memory_profiler` package, but it only shows the increasing memory consumption without giving insights into the objects causing the leak. Additionally, I've ensured that no references are held unintentionally by checking global variables and avoiding circular references. However, my application still consumes more memory with each request. I am running Python 3.10 and FastAPI 0.68.0. Does anyone have any suggestions or debugging strategies to help identify the root cause of this memory leak? Any ideas what could be causing this?