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 ...

Python's support for multithreaded programs has improved considerably over the last few years with the advent of the "free-threaded" version of the language. But testing multithreaded programs is ...

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 ...

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 processing ...

Learn how to use Python’s async functions, threads, and multiprocessing capabilities to juggle tasks and improve the responsiveness of your applications. If you program in Python, you have most likely ...

One of the biggest changes to come to the Python world is the addition of the free-threading interpreter, which eliminates the global interpreter lock (GIL) that kept the interpreter thread-safe, but ...

Formal plans for a Python that supports true parallelism are finally on the table. Here’s how a GIL-free Python will finally come together. After much debate, the Python Steering Council intends to ...