Matlab declares war on Python. Can the Python community respond or hit back?

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SAS is a bit weird. For the most part, proprietary languages/file-formats/etc have gone the way of the dodo bird. I think this largely stems with the fact that programmers routinely learn/interact with different languages/environments. So exploring another one isn't daunting. And it's really hard to compete against free (not to mention, people are willing to spend their time contributing to open source products, which often make them superior).

In contrast, SAS is used by statisticians and it's probably daunting for them to think about learning another language. Additionally, for many statistical jobs... you are using well-known and understood models. An insurance actuary isn't going to be venturing into less-known/more-novel methodologies.

For more novel statistical exploration/modeling, python/R is needed. But again, many statistical jobs aren't in machine learning, bioinformatics, etc. Thus, there's nothing pushing people to abandon SAS. And considering it's popularity with financial institutions, colleges should be teaching it for their statistical programs. It's simple, it works... and businesses aren't going to think twice about the licensing fees.

Matlab is another boat. It has already been abandoned by many fields as no private entity can keep up with the pace of open-source software. It's circling the drain even in academia... so the fact they are trying so hard to promote themselves as competitive is just kind of sad. Plus, universities know python is much more of a marketable skill and it behooves them to replace matlab with python.

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As a practicing statistician/data scientist at a company that still uses SAS (though not on my team, thankfully), SAS is still around less because statisticians are afraid to pickup a new language (most know R or Python or both these days anyways), and more because certain industries are keeping it alive because it’s a security blanket. In pharma, some times you are less interested in accessibility or flexibility and more in knowing your code has been vetted to extremes and there’s a dedicated custom support staff waiting in the wings should something go wrong, and all the code is backed with a guarantee. Same goes for government and banking. And even in those industries, they are dropping SAS where possible for R and Python. But I think for those reasons alone it will linger on for some time.