MUO on MSN

I put my computer’s internet traffic on a map, and I didn’t expect what I found

I expected neat lines pointing to websites, but TapMap showed me the infrastructure my laptop was really talking to ...

How AI helped build hreflang XML sitemaps at scale

Learn how iterative prompting, Python, and Google Colab helped turn a multilingual hreflang mapping project into a scalable workflow.
GitHub

Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine.

Also supports saving captions for url+caption datasets. If you believe in making reusable tools to make data easy to use for ML and you would like to contribute, please join the DataToML chat. For all ...
GitHub

better multiprocessing and multithreading in Python

objects to be transferred between processes using pipes or multi-producer/multi-consumer queues objects to be shared between processes using a server process or (for ...
InfoWorld

Python threading and subprocesses explained

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. By default, ...
InfoWorld

Python concurrency and parallelism explained

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 ...
Hackaday

Thread Carefully: An Introduction To Concurrent Python

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 ...