What methods and tools are available for implementing concurrency in Python?

In Python, several methods and tools are available for implementing concurrency:

1. Threads (threading) — the threading module allows creating threads that run in parallel. However, due to GIL (Global Interpreter Lock) in CPython, threads do not provide true parallelism in computations, but are useful for I/O operations.

2. Multiprocessing — the multiprocessing module creates separate processes that do not share memory, bypassing the GIL limitation and allowing the use of multiple CPU cores.

3. Asynchronous programming (asyncio) — the asyncio library enables writing asynchronous code using coroutines, which is efficient for a large number of I/O operations without creating threads or processes.

4. Concurrent Futures — the concurrent.futures module provides a convenient interface for running tasks in threads (ThreadPoolExecutor) or processes (ProcessPoolExecutor).

Example of using threading:

import threading

def worker():
    print("Work in thread")

thread = threading.Thread(target=worker)
thread.start()
thread.join()

For CPU-intensive tasks, it is better to use multiprocessing.