Have you had experience with multithreading or parallel computing?

Yes, I have experience working with multithreading and parallel computing in Python. For multithreading, the threading module is used, which allows running multiple threads within a single process. However, due to the GIL (Global Interpreter Lock), true parallelism in CPU-bound tasks is limited.

For parallel computations, it is better to use the multiprocessing module, which spawns multiple processes and bypasses GIL limitations.

Example of using threading:

import threading

def worker():
    print("Thread is running")

threads = []
for i in range(5):
    t = threading.Thread(target=worker)
    t.start()
    threads.append(t)

for t in threads:
    t.join()

Example of using multiprocessing:

from multiprocessing import Pool

def f(x):
    return x * x

if __name__ == '__main__':
    with Pool(5) as p:
        print(p.map(f, [1, 2, 3, 4, 5]))

Thus, the choice between threads and processes depends on the task and parallelism requirements.