advanced patterns with asyncio and aiohttp when Handling Concurrent Requests in Python 3.11
I'm not sure how to approach I'm not sure how to approach I'm working with an scenario with using `asyncio` and `aiohttp` to handle multiple concurrent requests in my Python 3.11 application... I have a function that makes several HTTP GET requests to an external API, and I expect the responses to be processed concurrently. However, I'm experiencing unexpected delays and sometimes getting a `TimeoutError` even though the API is up and running. Here's a simplified version of my code: ```python import asyncio import aiohttp async def fetch(session, url): async with session.get(url) as response: return await response.json() async def fetch_all(urls): async with aiohttp.ClientSession() as session: tasks = [fetch(session, url) for url in urls] return await asyncio.gather(*tasks) if __name__ == '__main__': urls = [ 'https://api.example.com/data1', 'https://api.example.com/data2', 'https://api.example.com/data3' ] asyncio.run(fetch_all(urls)) ``` When I run this code, it sometimes takes longer than expected to complete all requests, and I've seen `TimeoutError: ClientTimeout` messages in the output. I've tried increasing the timeout settings in my session like this: ```python async with aiohttp.ClientSession(timeout=aiohttp.ClientTimeout(total=60)) as session: ``` But this hasn't resolved the scenario. I also checked if the external API was under heavy load, but it seems responsive. Is there something I'm missing in my implementation, or could there be an scenario with how I manage the event loop? Any insights would be greatly appreciated! Could someone point me to the right documentation?