What is your practical experience with multithreading and thread management in applications?

In my practical experience with multithreading in Python, I have used the threading and concurrent.futures modules for parallel execution of tasks that do not heavily load the CPU, such as network requests or input/output operations.

I am also familiar with the Global Interpreter Lock (GIL), which limits the concurrent execution of Python bytecode in multiple threads. Therefore, for CPU-intensive tasks, I prefer to use multiprocessing via the multiprocessing module.

An example of using threading to run multiple threads:

import threading
import time

def worker(num):
    print(f'Thread {num} started')
    time.sleep(2)
    print(f'Thread {num} finished')

threads = []
for i in range(3):
    t = threading.Thread(target=worker, args=(i,))
    threads.append(t)
    t.start()

for t in threads:
    t.join()

Thus, I know how to create and manage threads, synchronize their work, and consider Python's limitations when designing multithreaded applications.