The multiprocessing API was originally designed to mimic the thread API. However, it has evolved and in recent versions of Python 3, it supports more features more robustly. The multiprocessing library is designed when CPU-intensive jobs need to happen in parallel and multiple cores are available (given that a four core Raspberry Pi can currently be purchased for $35, there are usually multiple cores available). Multiprocessing is not useful when the processes spend a majority of their time waiting on I/O (for example, network, disk, database, or keyboard), but they are the way to go for parallel computation.
The multiprocessing module spins up new operating system processes to do the work. On Windows machines, this is a relatively expensive operation; on Linux, processes are implemented in the kernel the same way threads are, so the overhead is limited to the cost of running separate Python interpreters in each process.
Let's try to parallelize a compute-heavy operation using...
