Why is multithreading important in Python development?

Multithreading in Python is important for improving performance and responsiveness of applications, especially when multiple tasks need to be executed simultaneously, such as user input processing, network requests, or background computations.

Although due to GIL (Global Interpreter Lock) in the standard CPython implementation, multithreading is limited in terms of parallel execution of Python bytecode, it is useful for I/O-bound operations where threads can wait for completion without blocking the main thread.

For CPU-intensive tasks, multiprocessing (using the multiprocessing module) is often used, but threading remains an important tool for asynchronous and concurrent programming.

Example of using threading for network requests:

import threading
import requests

def fetch_url(url):
    response = requests.get(url)
    print(f"{url}: {len(response.content)} bytes")

threads = []
urls = ["https://example.com", "https://python.org"]
for url in urls:
    thread = threading.Thread(target=fetch_url, args=(url,))
    thread.start()
    threads.append(thread)

for thread in threads:
    thread.join()