> Are things better elsewhere? Python has excellent libraries. But these are big monoliths that not only do not compose well, but are also hard to understand de

> Are things better elsewhere? Python has excellent libraries. But these are big monoliths that not only do not compose well, but are also hard to understand deeply as they are essentially a thin layer over C, C++, Fortran, etc. I dunno. Things like the use of scipy.spatial.distance metrics[1] by in sklearn clustering[2] seems a great example of composability that is easy to learn and very efficient. And the sklearrn side isn't a "thing layer over C, C++, Fortran" even if scikit is (sort of) this. [1] https://docs.scipy.org/doc/scipy/reference/spatial.distance.html https://docs.scipy.org/doc/scipy/reference/spatial.distance.... [2] https://scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise_distances.html https://scikit-learn.org/stable/modules/generated/sklearn.me...