Is it possible to implement multiprocessing by distributing it across different processor cores?

Yes, Python can implement multiprocessing by distributing tasks across different CPU cores. The multiprocessing module creates separate processes, each capable of running on a different core, bypassing the GIL (Global Interpreter Lock).

Example of using multiprocessing:

from multiprocessing import Pool

def f(x):
    return x * x

if __name__ == '__main__':
    with Pool(4) as p:  # create a pool of 4 processes
        results = p.map(f, [1, 2, 3, 4, 5])
    print(results)  # [1, 4, 9, 16, 25]

Thus, tasks are distributed among processes that can run in parallel on different cores.