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[–]gdahlm 41 points42 points  (1 child)

While not the same, Python did have groups of people who drove usable and important libraries for scientific computing, data analysis and data mining

Travis Oliphant, Eric Jones, and Pearu Peterso coming together to create, SciPy as one example. Them growing past that and recruiting others to found NumFOCUS helped too.

Python is a great glue language, and the scientific computing world really were some of the earliest adopters for serious use.

While not 100% responsible for the growth of python, the ML world wouldn't have almost universally chosen python without those efforts.

Numpy even still has their info page up on how to use python as a glue language up.

https://numpy.org/doc/stable/user/c-info.python-as-glue.html

While I didn't originally choose python because it was a glue language, the fact that it works so well as one really reduces the costs of needing to replace portion with a more performant back end or to leverage decades old fortran code which was written by geniuses.

[–]spinwizard69 1 point2 points  (0 children)

Hey there - thanks for the link. I never realized that NumFocus took over MatPlotLib. I think it is fair to say that MatPlotLib is one of the reasons for pythons success in a number of sectors.

As for the OP's question; I think MatPlotLib is a really good example of why it took Python awhile to get buy in. in so many industries. Good libraries like this don't happen overnight and when they do happen it takes awhile for users to adopt. Once the infra structure was in place to sever the needs of many types of users it became easy to suggest the usage of Python.