FastAPI worker timing out

[ArijitSinghEDA]

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Example Code

from fastapi import FastAPI
from pydantic import BaseModel
import asyncio
import uvicorn

app = FastAPI()

class Item(BaseModel):
    sql: str

@app.post("/out")
async def func(item: Item):
    from functionality import main
    asyncio.ensure_future(main(query=item.sql))
    return 1

if __name__=="__main__":
    uvicorn.run(app, host="127.0.0.1", port=8888)

Description

I am running the code using gunicorn inside my virtual environment with the command
python -m gunicorn main:app --bind 127.0.0.1:8888 --workers 4 --worker-class uvicorn.workers.UvicornWorker --timeout 86400 --graceful-timeout 86400

Inside my main function, I am reading an sql query and converting it into a pandas dataframe. When the query has 5M rows, there's no issue, but when the number of rows increase to 10M, the workers are sent a SIGKILL signal, even after setting both timeout and graceful-timeout. Is there any internal timeout set by fastAPI? I searched all over the internet but couldn't find anything suggesting that fastAPI can behave like this.

Operating System

Linux

Operating System Details

I am using wsl on my Windows system.

FastAPI Version

0.104.1

Pydantic Version

2.4.2

Python Version

3.10.12

Additional Context

I am running this from inside a virtual environment.

[theobouwman]

Maybe you dont have enough memory?

[jgould22]

Mentioned in the docs here https://docs.gunicorn.org/en/stable/faq.html?highlight=SIGKILL#why-are-workers-silently-killed

[ArijitSinghEDA]

I made the same dataset and loaded on my local system without any problem, and a pandas dataframe also gets loaded into the memory. So does it mean fastAPI/gunicorn is taking excessive memory?

[ArijitSinghEDA]

And I checked my memory consumption. It maximum to 94%, but the worker restarts after consumption was 86% (other necessary processes are also running in the background, so this memory consumption percentage is for the whole system)