How can I avoid resource strain and potential crashes when making concurrent HTTP calls in a FastAPI endpoint?

Asynchronous Calls with HTTPX in FastAPI Endpoints

Concerns About Using ThreadPoolExecutor in FastAPI

You expressed concerns about the impact of using concurrent.futures.ThreadPoolExecutor in a FastAPI endpoint, particularly regarding thread creation, host starvation, and application crashes. These concerns are valid since excessive thread creation can strain resources and potentially lead to performance issues.

Recommendation: HTTPX Async API

To avoid these potential pitfalls, it's recommended to utilize the async capabilities of the HTTPX library instead of concurrent.futures.ThreadPoolExecutor. HTTPX provides an efficient asynchronous API that allows you to make HTTP requests without the need for explicit thread management. This approach offers several advantages:

• Controlled Connection Pooling: HTTPX enables you to control the size of the connection pool, ensuring that a reasonable number of connections are maintained for optimal performance without overwhelming the host.
• Asynchronous Requests: Asynchronous requests don't block the event loop, freeing up resources for other operations, thus preventing performance bottlenecks.
• Graceful Shutdown: HTTPX allows you to explicitly close the AsyncClient instance, ensuring proper cleanup and preventing resource leaks.

Working Example

The following code snippet demonstrates how to implement asynchronous HTTP requests with HTTPX in a FastAPI endpoint:

from fastapi import FastAPI, Request
from contextlib import asynccontextmanager
import httpx
import asyncio

URLS = ['https://www.foxnews.com/',
        'https://edition.cnn.com/',
        'https://www.nbcnews.com/',
        'https://www.bbc.co.uk/',
        'https://www.reuters.com/']

@asynccontextmanager
async def lifespan(app: FastAPI):
    # customise settings
    limits = httpx.Limits(max_keepalive_connections=5, max_connections=10)
    timeout = httpx.Timeout(5.0, read=15.0)  # 15s timeout on read. 5s timeout elsewhere.

    # Initialise the Client on startup and add it to the state
    async with httpx.AsyncClient(limits=limits, timeout=timeout) as client:
        yield {'client': client}
        # The Client closes on shutdown 

app = FastAPI(lifespan=lifespan)

async def send(url, client):
    return await client.get(url)

@app.get('/')
async def main(request: Request):
    client = request.state.client
    tasks = [send(url, client) for url in URLS]
    responses = await asyncio.gather(*tasks)
    return [r.text[:50] for r in responses]  # for demo purposes, only return the first 50 chars of each response

Alternative: Streaming Responses to Avoid RAM Usage

If reading the entire response bodies into RAM is a concern, consider utilizing HTTPX's Streaming responses along with FastAPI's StreamingResponse:

... # (same as previous code snippet)

async def iter_content(responses):
     for r in responses:
        async for chunk in r.aiter_text():
            yield chunk[:50]  # for demo purposes, return only the first 50 chars of each response and then break the loop
            yield '\n\n'
            break
        await r.aclose()

@app.get('/')
async def main(request: Request):
    client = request.state.client
    tasks = [send(url, client) for url in URLS]
    responses = await asyncio.gather(*tasks)
    return StreamingResponse(iter_content(responses), media_type='text/event-stream')

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