In the realm of Python software development, two common approaches for managing concurrent operations are threading and asynchronous (async) programming. Both methods allow you to perform multiple ...

Threads can provide concurrency, even if they're not truly parallel. In my last article, I took a short tour through the ways you can add concurrency to your programs. In this article, I focus on one ...

A Python project demonstrating the performance differences between threading and multiprocessing in CPU-bound tasks. It includes a script that measures execution time for both approaches, highlighting ...

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.

There’s more than one way to thread (or not to thread) a Python program. We point you to several threading resources, a fast new static type checker from Astral, a monkey patch for Pandas that ...

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 ...