Is it really impossible to implement parallel thread execution in Python?

There is indeed a limitation in Python related to the Global Interpreter Lock (GIL), which prevents multiple threads from executing Python bytecode simultaneously within a single process. This means that multithreading in Python does not provide true parallelism at the CPU level for compute-intensive tasks.

However:

• Threads in Python can run in parallel when performing I/O operations (e.g., network requests, file reading), where the thread releases the GIL during waiting.
• For compute-intensive tasks, the multiprocessing module can be used, which creates separate processes with their own interpreter and memory, providing true parallelism.

Thus, parallel execution of threads in Python is possible but limited by the GIL. For CPU-bound tasks, it is better to use processes.

Example of using threads for I/O:

import threading
import time

def io_task():
    time.sleep(2)  # simulate an I/O operation
    print("Task completed")

threads = [threading.Thread(target=io_task) for _ in range(5)]
for t in threads:
    t.start()
for t in threads:
    t.join()

Here, threads will work in parallel because sleep releases the GIL.