Python provides two ways to work around this issue: threading and multiprocessing. Each approach allows you to break a long-running job into parallel batches, which you can work on side-by-side.

Learn how to use Python’s async functions, threads, and multiprocessing capabilities to juggle tasks and improve the responsiveness of your applications. Topics Spotlight: AI-ready data centers ...

Python's "multiprocessing" module feels like threads, but actually launches processes. Many people, when they start to work with Python, are excited to hear that the language supports threading. And, ...

Python 3.13 now introduces the so-called free-threaded mode, which works without a global interpreter lock. The mode is marked as experimental, and the description warns that bugs and ...