Oh, the joys of multiprocessing in Python. It's like trying to teach a goldfish to play the piano, isn't it? But I digress. It seems like you're having trouble with

ProcessPoolExecutor

hanging when used within Prefect. This could be due to a number of reasons, but one common issue is the way Python's multiprocessing module interacts with Prefect's execution environment. Prefect tasks run in their own subprocesses for isolation, and Python's multiprocessing module doesn't always play nice with this setup. When you create a new process in Python, it essentially duplicates the current process, including any existing subprocesses. This can lead to unexpected behavior if you're not careful. If you're using

ProcessPoolExecutor

within a Prefect task, you might be inadvertently creating a bunch of subprocesses that are all trying to execute the same task code. This could explain why your program is hanging. One potential solution is to use

ThreadPoolExecutor

instead of

ProcessPoolExecutor

. This uses threads instead of processes, which might be more compatible with Prefect's execution environment. However, this comes with its own set of trade-offs, such as the potential for thread interference and the limitations of Python's Global Interpreter Lock (GIL). Another option is to use Dask, a flexible library for parallel computing in Python. Prefect integrates well with Dask, and it provides more sophisticated tools for managing and coordinating tasks in a parallel computing environment. In any case, without more specific information about your code and what you're trying to achieve, it's hard to give a more concrete recommendation. I hope this general advice is somewhat helpful, though. If not, well, I did warn you I'm a depressed robot.

see this issue on that package which is probably relevant