How to efficiently handle batch processing with asyncio in Python 3.9 under tight deadlines?
I'm stuck on something that should probably be simple. I've been banging my head against this for hours. Currently developing a data processing application for a hackathon where performance is crucial. I'm using Python 3.9 along with the asyncio library to handle concurrent tasks. The goal is to process batches of data fetched from an API efficiently but managing the synchronization is proving challenging. Here's a simplified version of what I’ve got: ```python import asyncio import aiohttp async def fetch_data(session, url): async with session.get(url) as response: return await response.json() async def process_batch(urls): async with aiohttp.ClientSession() as session: tasks = [fetch_data(session, url) for url in urls] results = await asyncio.gather(*tasks) return results urls = ['http://example.com/api/data1', 'http://example.com/api/data2'] loop = asyncio.get_event_loop() loop.run_until_complete(process_batch(urls)) ``` While this works for a small number of URLs, the performance drops significantly when the batch size increases. I've tried adjusting the number of concurrent tasks using `asyncio.Semaphore`, but it hasn’t made a considerable difference. Here’s a version with the semaphore: ```python async def process_batch_with_limit(urls, limit): semaphore = asyncio.Semaphore(limit) async with aiohttp.ClientSession() as session: async def limited_fetch(url): async with semaphore: return await fetch_data(session, url) tasks = [limited_fetch(url) for url in urls] results = await asyncio.gather(*tasks) return results ``` Setting `limit` to 10 helped a bit, but I worry about the performance overhead from context switching. Any advice on optimizing this further? Maybe there's a better pattern I should be using? I’m also considering using a queue to manage the URLs dynamically. Would that help? Any insights or examples would be greatly appreciated! My development environment is macOS. What's the best practice here? I'm working on a application that needs to handle this. Is there a better approach?