For what types of tasks in Python are multithreaded solutions suitable?

Multithreaded solutions in Python are suitable for tasks where the main time is spent on input/output (I/O) operations rather than computations. This is due to the GIL (Global Interpreter Lock) restriction, which prevents Python bytecode from executing simultaneously in multiple threads.

Types of tasks suitable for multithreading:

• Network operations (API requests, socket communication).
• Reading and writing files.
• Interacting with databases.
• Handling user events in GUI.

For CPU-intensive tasks, it is better to use multiprocessing (the multiprocessing module) or other approaches.

Example of using threads for network requests:

import threading
import requests

def fetch(url):
    resp = requests.get(url)
    print(f"Received {len(resp.content)} bytes from {url}")

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

for t in threads:
    t.join()