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The Elegance of Modular Data Processing with Python’s Pipeline Approach

Diving into the intricacies of data processing can often feel like navigating an intricate labyrinth. We build these elaborate processes, only to leave them untouched for fear of breaking them. But what if we could improve it? Here's my perspective on crafting a more maintainable, modular data processing workflow in Python which leans into the "pipe and filter" architectural pattern.

https://github.com/dkraczkowski/dkraczkowski.github.io/tree/main/articles/crafting-data-processing-pipeline
genai-stack

This GenAI application stack will get you started building your own GenAI application in no time. The demo applications can serve as inspiration or as a starting point.

https://github.com/docker/genai-stack
Gsplat: CUDA accelerated rasterization of gaussians with Python bindings

https://docs.gsplat.studio/
Why can't python develop another version of python that is "compiled" instead of interpreted which is similar to c/c++ but the syntax still look like python syntax.

https://www.reddit.com/r/learnpython/comments/1791tnm/why_cant_python_develop_another_version_of_python/