Everything you ever wanted to know about SciPy


If you're not familiar,

SciPy provides fundamental algorithms for scientific computing.

It's one of the most widely-used packages in the Python data science ecosystem, right up there with pandas, numpy, and scikit-learn. As of this writing,

...over 110,000 GitHub repositories and 6,500 packages depend on SciPy.

This is a fascinating journal article, not quite like anything I've ever seen before. It's a review of the history, the architecture, the structure, and more of the community and the package itself. I enjoyed it because I personally enjoy knowing the history and the stories behind the technology that shapes our current environment. So often, the quirks of the way things are today are related to path-dependence and can only be well understood in full view of their historical contexts. For example, I didn't know that scikits (like scikit-learn) were evolutions out of core scipy, separated out in an effort to keep scope manageable.

Long, skimmable, unique.


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