Python lets you parallelize workloads using threads, subprocesses, or both. Here's what you need to know about Python's thread and process pools and Python threads after Python 3.13.

This is an example of when the threading module’s multitude of options could be useful: we can mark the updater thread as a daemon thread, which means that Python will exit when only daemon ...

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 ...

An experimental ‘no-GIL’ build mode in Python 3.13 disables the Global Interpreter Lock to enable true parallel execution in Python. Here’s where to start.

Because multiple threads within a process share data, they can work with one another more closely and easily. For example, let's say you want to retrieve all of the data from a variety of websites. My ...

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, ...