Why does my Python multiprocessing Pool sometimes raise AttributeError for a class method?
Hey everyone, I'm running into an issue that's driving me crazy. After trying multiple solutions online, I still can't figure this out... I tried several approaches but none seem to work. I'm working on a Python script that uses the `multiprocessing` library to parallelize data processing across multiple CPU cores. The scenario arises when I attempt to use a class method as the target function for `Pool`. Sometimes, I get an `AttributeError` that points to a missing method. My class looks something like this: ```python import multiprocessing class MyProcessor: def __init__(self, data): self.data = data def process_data(self, item): # Simulate processing return item * 2 def run_pool(self): with multiprocessing.Pool(processes=4) as pool: results = pool.map(self.process_data, self.data) return results if __name__ == '__main__': data = [1, 2, 3, 4, 5] processor = MyProcessor(data) print(processor.run_pool()) ``` This setup works as expected most of the time, but occasionally I see this behavior: ``` AttributeError: 'MyProcessor' object has no attribute 'process_data' ``` It seems to happen intermittently, particularly when I use a larger dataset. I've verified that the method is indeed defined within the class. I suspect it might be related to how `Pool` manages objects when they are being pickled, but Iām not sure. Is there a best practice for using class methods with `multiprocessing.Pool`? Should I consider using static methods instead? I've also tried using `functools.partial` but that didn't resolve the scenario. Any insight into this would be greatly appreciated! Am I missing something obvious? I'm working on a CLI tool that needs to handle this. What am I doing wrong? Could this be a known issue?