Re:It takes a PhD to develop that
by TheOtherHobbes on Monday October 04, 2021 @09:52AM
(#28746690)
Python has nice optimised libs for that, so it's not completely a surprise for that kind of application.
If you're doing generic symbol shuffling with a bit of math, Python is fast-ish to code and horribly slow to run. You can easily waste a lot of performance - and possibly cash - trying to use it for production.
Whether or not you'll save budget by writing your own optimised fast libs in some other lang is a different issue, and very application dependent.
Also it's not that simple. One place I worked at (scientific computation-kind of place), we'd prototype everything in Python, and production would be carefully rewritten C++. Standards were very high for prod, and we struggled to hire "good enough", modern C++, endless debates about "ooh template meta-programming or struct or bare metal pointers" kind of stuff.
3 times out of 4, the Python prototype was faster than the subsequent C++. It was because it had to be, the prototype was ran and re-ran and tweaked many times in the course of development. C++ was written once, deployed, and churned daily, without anyone caring for its speed.