On Sun, Aug 16, 2020 at 11:20 PM Stephen J. Turnbull <turnbull.stephen.fw@u.tsukuba.ac.jp> wrote:
It's getting the fiddly stuff right (numerical stability and accuracy,
catching edge cases in algorithms) so that you can use it with
confidence for work that has consequences if you get it wrong that (to
me, anyway) would justify inclusion in the stdlib.

And for that, you want a robust, well supported library, like, say LAPACK, or EIGEN, or ...., you know like what scipy uses ;-)

The python standard library really isn't the place for that kind of code.

However, a pure python implementation could, optionally, reach out to an external lib for specific functionality like that though.


Christopher Barker, PhD

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