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 ...

The ability to execute code in parallel is crucial in a wide variety of scenarios. Concurrent programming is a key asset for web servers, producer/consumer models, batch number-crunching and pretty ...

Your Python cache can run the same work twice, even with the GIL. See the check-then-act race, the lru_cache gotcha, and how ...

Python already has several ways to run programs concurrently — including asynchronous functions, threads, subinterpreters, and multiprocessing — but all of those options have drawbacks of one kind or ...

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. The single biggest new feature in Python ...

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 adds ...

Parallelism comes down to the ability to segment a task into pieces that can be worked on at the same time, he said, but not all tasks can be. If it takes him an hour to solve a Rubik's Cube, he asked ...