Comment by bsenftner
4 years ago
Third'ing: the current crop of new developers have no freaking idea how much power they have at their finger tips. Us greybeard old game developers look at today's hardware and literally cream our jeans in comparison to the crap we put up with in the previous decades. People have no idea, playing with their crappy interpenetrated languages, just how much raw power we have if one is willing to learn the low level languages to access them. (Granted, Numpy and BLAS to a wonderful job for JIT languages.)
I'd say it is almost the other way around. We have so much wonderful CPU power that we can spare some for the amazing flexibility of Python etc.
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.
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.