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 GIL is controversial because it only allows one thread at a time to access the Python interpreter. This means that it’s often not possible for threads to take advantage of multi-core systems.

For parallelism, Python offers multiprocessing, which launches multiple instances of the Python interpreter, each one running independently on its own hardware thread.. All three of these ...

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, ...