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abandonware empires
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this post was submitted on 09 Nov 2023
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If you rely on free packages in Python for processing, those are as likely to become obsolete as anything else (if not more likely). I also really dislike the compatibility issues with different versions of different packages, the whole environment aspect. Buying new computer with different version of windows? Who knows what will work there.
In this sense for scientific computation I prefer something like MATLAB. Code written 40 years ago, most likely would still work. New computer? No problem, no configuration, just install Matlab, and it runs! Yes, it costs money, but you get what you paid for. Mathematica is another option, but I mean ugh!
I mostly use pandas that I don't think is going anywhere, we're also going to start tests with a library called 'chainladder' that is used for some actuarial reserves calculations, from everything else I'm programming custom functions because as far as I know, there's not a lot of actuarial mathematics libraries on Python (R have much more support for that, but I prefer the flexibility of Python, like a good portion of my job is scrapping our regulatory body website for information and not sure how good R work on that).
If you really don't want to spend money, there's always GNU Octave. Sure, it doesn't have the thousands of matlab toolboxes, but if you're running code from 40 years ago it shouldn't need those anyway. I wrote a couple of scripts recently and then rewrote them slightly so that they would be compatible with octave.
Matlab is ugly because it's so backwards compatible. And it only is backwards compatible until someone decides to use it to interface with external hardware that you need a specific version of some library for.