Handling Memory Leaks in a Python 3.9 CLI Tool Using asyncio and aiohttp
Quick question that's been bugging me - I'm currently developing a command-line interface (CLI) tool using Python 3.9 that fetches data from a REST API using `aiohttp` and `asyncio`. However, I'm encountering memory leaks that cause the application to consume an increasing amount of memory over time. I've used `asyncio.gather()` to run multiple requests concurrently, but I suspect that I'm not closing the sessions properly, leading to resource leaks. Here's a simplified version of the code Iām using: ```python import aiohttp import asyncio async def fetch(session, url): async with session.get(url) as response: return await response.json() async def main(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://jsonplaceholder.typicode.com/posts/1", "https://jsonplaceholder.typicode.com/posts/2"] asyncio.run(main(urls)) ``` Upon running the tool with a larger list of URLs, I notice that the memory usage keeps increasing, eventually leading to an `MemoryError`. I've tried using `gc.collect()` to force garbage collection, but it hasn't made a significant difference. Also, I'm aware that aiohttp sessions should be reused and closed properly, but I'm not sure if I'm handling it correctly in my `main` function. What are the best practices for managing memory in an `asyncio` context with aiohttp? Are there any specific patterns I should follow or tools I can use to identify and resolve memory leaks in this scenario? I'm working in a macOS environment. Any advice would be much appreciated.