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… ...

Learn how to use Python’s async functions, threads, and multiprocessing capabilities to juggle tasks and improve the responsiveness of your applications.

Find out what makes Python a versatile powerhouse for modern software development—from data science to machine learning, systems automation, web and API development, and more.

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.

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 ...

Python vs Java If you’re a Python dev who can’t wait until 2026 for strong typing and multicore threading support, there are other options. One of Python’s strengths is its ability to invoke code ...

I have worker thread(s) that use the logger. 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 ...

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, ...

Overall, the choice between VBA and Python for Excel automation depends on your specific needs. Even though it's outdated, ...

The guide describes how threads are created, how they travel along within the GPU and work together with other threads, how memory can be managed both on the CPU and GPU, creating CUDA kernels ...