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by jbay808
1990 days ago
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> As soon as a professional has been paid to fight open source integration for 1-2 days, it would have been better if the employer had simply bought matlab. I'm a licensed professional, and in my experience it takes 1-2 hours to set up a conda virtualenv with all the packages I need. Whereas if I want Matlab, it takes about a week to talk through the budgeting and licensing options with my employer, find the right number of seats to purchase (other departments might decide to get in on the purchase, so we need to consult broadly), choose which toolboxes we'll pay for, go back and forth on the quotes and POs, and make sure all the licensing really works. But your mileage may vary. |
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Yes, there are problems where Python is an easy solution. And many where it is not. And some where it cannot solve the problem without extreme effort.
Having been in dev a long time, this is the simplest, naive works best case path. If this were how setting up Python worked for everyone, there would not be an incredible amount of forum posts, github issues, setup help and problems, easily found on the internet. If you've not had to change underlying code in some python package or even worse recompile underlying C libraries, then you have not faced the kids of problems many (me included) have.
Ever solve a problem like the one I listed? That is not a simple conda install (and I use conda stuff vastly more than matlab/mathematica, so I'm pretty aware of it's use and features). Many problems I can solve in Mathematica (my preferred tool for certain work) cannot be approached by Python at all (or any open source tools I am aware of, and I have tried pretty much all of the things listed as MMA replacements).
>find the right number of seats to purchase (other departments might decide to get in on the purchase
So you're no longer making an apples to apples comparison - you just solved a bigger problem with the Matlab side.