The answer is somewhere in the middle. The Python standard library comes with "multiprocessing", a module that gives the feeling of working with threads, but that actually works with processes. So in ...

But for long-running processes that benefit from parallelism across cores, the multiprocessing library is useful. As an aside, Python modules and packages that use C libraries (such as NumPy or ...

Multiprocessing is the most powerful ... Also, as shown in Listing 1, Python’s standard library comes with high-level conveniences for running operations in threads. You don’t need to know ...

I'm running some simulations using the joblib library. For that ... Post the results for each row to a multiprocessing.Queue, and spawn a single process that gets from the queue and writes ...