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A comment on Python Programming and Numerical Methods: A Guide for Engineers and Scientists. Parent comment

Re:Python Programming and Numerical Methods: A Guide for Eng... by gautamdivgi on Wednesday February 17, 2021 @11:19AM (#26168099)
Most of your points about language deficiencies are valid. But you still have the same problem of longevity and bitrot. Unless you have teams that are willing to pick up Common Lisp and contribute you will end up being the only maintainer of the code. Case in point my advisor from grad school used C and did all his numerical work from scratch. If I'd not found python, numpy and scipy I'd still be in grad school.

If you're looking for a way out of python because of specific performance issues you face I'm not sure why you did not just go with Julia (unless you really wanted to do Common Lisp).

Try pyinstaller if you need to compile python into a self-contained binary.

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Re:Python Programming and Numerical Methods: A Guide for Eng... by reikonomusha on Wednesday February 17, 2021 @11:25AM (#26168161)
I agree that code needs to be maintained, but I would say that Common Lisp code has a tendency to bitrot a lot slower than other languages because implementations of Common Lisp don’t break code.

So there’s definitely a valid maintenance point of code needs to continue to be extended (though I’ve had no trouble finding or training Common Lisp programmers), but Common Lisp code simply doesn’t stop working on the timespan of years.

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Re:Python Programming and Numerical Methods: A Guide for Eng... by ericbarrett on Wednesday February 17, 2021 @11:38AM (#26168312)
C can bitrot too, especially academic C. A few things I’ve seen are missing headers, builds that only ever worked with what the prof had in /usr/local, conventions that become warnings that become errors (500 invocations of strcpy!), and “beginner” stuff like assuming int’s size or that you can poke hard-coded memory ranges. I do think both languages will be better than Python over decadal time scales.
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