When running on a server with 8 or 16 cores, what allows faster task execution – a thread or a goroutine?

The standard library modules in Python for parallel code execution include:

• threading — for creating and managing threads. Suitable for I/O-bound tasks.
• multiprocessing — for running multiple processes, which can bypass the GIL and utilize multiple CPU cores effectively.
• concurrent.futures — a high-level interface for working with thread pools (ThreadPoolExecutor) and process pools (ProcessPoolExecutor).

Example using concurrent.futures for parallel execution:

import concurrent.futures

def task(n):
    return n * n

with concurrent.futures.ThreadPoolExecutor() as executor:
    results = list(executor.map(task, range(5)))

print(results)  # [0, 1, 4, 9, 16]