Why is it better to use multiprocessing instead of multithreading in Python for performing computational tasks?

In Python, multithreading is limited by the Global Interpreter Lock (GIL), which prevents multiple threads from executing Python bytecode simultaneously. This means that for compute-intensive tasks, threads cannot effectively utilize multiple CPU cores. Multiprocessing, on the other hand, creates separate processes with their own interpreter and memory, allowing parallel execution of computations on different cores. Therefore, for CPU-bound tasks in Python, it is preferable to use multiprocessing to achieve real parallelism and speed up computations.