It’s possible to customize algorithms in so many ways (for anything ranging from performance, or domain correctness, or flexibility) — if you understand how it

It’s possible to customize algorithms in so many ways (for anything ranging from performance, or domain correctness, or flexibility) — if you understand how it works under the hood, and can bend it to what you want. Doesn’t make sense for some generic library to build an interface for all that, or even try to be all things for all people. Very rarely are you likely to find the best solution for your needs off-the-shelf, unless you have the exact same needs of the library authors (assuming also that they have access to more competence than you). IME, not often the case. And it’s turned out to be nicer (from the long term perspective — experimentation flexibility, maintainability, etc) to roll my own. Of course, one tries to pick a layer of the stack to build on top of (Eg: Numpy/Jax, or Julia, or whatever) instead of boiling the ocean.