Performance Degradation in FastAPI with Large JSON Responses
This might be a silly question, but I recently switched to I'm facing significant performance issues when returning large JSON responses in my FastAPI application... My application is designed to serve a data-heavy API, and while it works fine for small datasets, I'm noticing a considerable increase in response time when the data size exceeds a few megabytes. For example, when I return a JSON response that is about 8MB, the response time spikes to over 2 seconds, which is unacceptable for my use case. I've tried several optimizations, such as using the `JSONResponse` directly instead of the default response, but it didn't seem to help. Here's a snippet of how I'm currently returning the data: ```python from fastapi import FastAPI from fastapi.responses import JSONResponse app = FastAPI() @app.get("/data") async def get_data(): data = generate_large_data_set() # This generates a list of dictionaries return JSONResponse(content=data) ``` I've also considered using `asyncio` to handle the data generation, but I don't see a noticeable performance improvement. Furthermore, I checked the server's CPU and memory usage during these requests, and they aren't maxing out, which makes me think that the bottleneck might be somewhere else. I've also enabled GZip compression, but it seems to complicate the JSON serialization process and doesn't yield the expected results either. When I enable GZip, the response time still exceeds 1.5 seconds even for JSON payloads that are only 4MB. Is there a best practice for optimizing FastAPI to handle large JSON responses better? Should I consider paginating the data instead? Any insights on how to improve the performance would be greatly appreciated! I've been using Python for about a year now. Any ideas how to fix this? This issue appeared after updating to Python LTS. Could this be a known issue?