Unexpected Behavior with multiprocessing.Queue in Python 3.10 when using large data sets
Hey everyone, I'm running into an issue that's driving me crazy. I've looked through the documentation and I'm still confused about I'm relatively new to this, so bear with me. I'm experiencing unexpected behavior when using `multiprocessing.Queue` in Python 3.10 while trying to process large datasets concurrently. My goal is to distribute a large list of dictionaries across multiple worker processes, but I'm encountering some issues with data integrity and performance. Here's the core of my implementation: ```python import multiprocessing import time def worker(queue): while True: item = queue.get() if item is None: break # Simulate processing time time.sleep(0.1) print(f'Processed: {item}') if __name__ == '__main__': data = [{'id': i, 'value': i * 2} for i in range(10000)] queue = multiprocessing.Queue(maxsize=10) processes = [multiprocessing.Process(target=worker, args=(queue,)) for _ in range(4)] for p in processes: p.start() for item in data: queue.put(item) # Stop workers for _ in processes: queue.put(None) for p in processes: p.join() ``` The issue I'm facing is that sometimes the output from the workers displays a 'Processed: None' message, which is unexpected. Moreover, the performance seems to degrade significantly when the data size increases, leading to longer processing times than anticipated. I've tried adjusting the `maxsize` of the queue, but it doesn't seem to help. Another thing I noticed is that when I run the workers with smaller datasets, everything works fine, but as soon as I push the size beyond a certain threshold, those issues appear. I'm not sure if this is a limitation of the queue size or if there’s another bottleneck in the multiprocessing module. Has anyone else faced similar issues, or can you suggest any best practices or optimizations for handling large datasets with `multiprocessing.Queue`? Any insights or alternative approaches would be greatly appreciated! Has anyone else encountered this? Thanks for any help you can provide! This is happening in both development and production on Windows 11. Any advice would be much appreciated.