Multitasking with processes

Like the threading module, the multiprocessing module is also used to provide multitasking capabilities. The threading module is actually a bit deceptive: its implementation in Python is not actually for parallel processing, but instead for processing on a single core with time-sharing. The default Python implementation CPython, at interpreter level, is not thread safe. Whenever threads are used, there is a global interpreter lock (GIL) that is placed over the objects that are accessed within Python threads. This lock executes the threads in time-sharing manner, giving a small quantity of time to every thread, and thus there is no performance gain in our program. The multiprocessing module was developed, therefore, to provide parallel processing to the Python ecosystem. This decreases the execution time by spawning the load across multiple processor...