Web Reference: 1 day ago · If you want your application to make better use of the computational resources of multi-core machines, you are advised to use multiprocessing or concurrent.futures.ProcessPoolExecutor. However, threading is still an appropriate model if you want to run multiple I/O-bound tasks simultaneously. In Python 3.2+, stdlib concurrent.futures module provides a higher level API to threading, including passing return values or exceptions from a worker thread back to the main thread. Oct 3, 2025 · Multithreading in Python allows multiple threads (smaller units of a process) to run concurrently, enabling efficient multitasking. It is especially useful for I/O-bound tasks like file handling, network requests, or user interactions.
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