How to handle large JSON responses efficiently in Python 3.9 using aiohttp?
I recently switched to I need help solving I've been struggling with this for a few days now and could really use some help... I'm working on a project where I need to fetch and process large JSON data from an external API using `aiohttp`. The API response can be up to 20MB in size, and I'm working with performance optimization when trying to load the entire response into memory. I want to parse the JSON incrementally to keep memory usage low. I started with the following code: ```python import aiohttp import asyncio async def fetch_large_json(url): async with aiohttp.ClientSession() as session: async with session.get(url) as response: if response.status == 200: data = await response.json() # This is where I hit performance optimization return data else: print(f'behavior: {response.status}') url = 'https://api.example.com/large-json' loop = asyncio.get_event_loop() result = loop.run_until_complete(fetch_large_json(url)) print(result) ``` When I run this, it works, but the latency is high, and it consumes too much memory. I'm also receiving a `JSONDecodeError` sometimes due to malformed JSON when the response is large. I've tried using streaming with `response.content.iter_any()` but couldn't figure out how to properly decode the chunks into a valid JSON object. Here’s an attempt I made: ```python async with session.get(url) as response: if response.status == 200: async for line in response.content: # Attempt to handle each line as JSON try: json_line = json.loads(line.decode('utf-8')) # Process json_line here except json.JSONDecodeError: print('Failed to decode JSON line') ``` This gives me an behavior because the JSON is not split by lines but is a single large object. Could anyone suggest an efficient way to handle such large JSON responses with `aiohttp`? Any best practices for streaming or parsing would be appreciated! This is part of a larger CLI tool I'm building. Am I missing something obvious? I'm working in a Ubuntu 20.04 environment. How would you solve this? What's the best practice here? I'm coming from a different tech stack and learning Python. Any pointers in the right direction?