I explore the ways you can use threads in Python and the limitations the language puts upon you when doing so. The basic idea behind threading is a simple one: just as the computer can run more than ...

Each Python instance receives the code and data needed to run the task in question. Listing 3 presents our web-reading script rewritten to use multiprocessing. With threading and coroutines ...

We’ll walk through the difference between threads and processes in a Python context, before reviewing some of the different approaches you can take and what they’re best suited for.

Here’s a slightly simpler version of this script: import asyncio ... how those things are implemented in Python. Async is about concurrency, while threads and multiprocessing are about parallelism.

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 ...

In the main thread, I occasionally need to ask the user to take some action. Which means I need to suppress the logger from actually printing until the user has a chance to make a decision.

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 ...