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.

The multiprocessing module spins up multiple copies of the Python interpreter, each on a separate core, and provides primitives for splitting tasks across cores. But sometimes even the ...

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, ...