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.

In this article, I focus on one of those forms that has a reputation for being particularly frustrating for many developers: threading. I explore the ways you can use threads in Python and the ...

a version of Python that allows full concurrency, or multi-threading, by removing the Global Interpreter Lock. Whether you call it “free-threaded” or “no-GIL” Python, the result is the ...

Ruby and Python's standard implementations make use of a Global Interpreter Lock. Justin James explains the major advantages and downsides of the GIL mechanism. Multithreading and parallel ...

Guided by this logic, Python inventor Guido van Rossum architected all of Python’s multithreading capabilities around the fatally flawed assumption that computers of the future would have only a ...