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Re: Perl in data science: could a grant from Perl foundation be useful?

by Anonymous Monk
on Feb 21, 2020 at 23:17 UTC ( #11113324=note: print w/replies, xml ) Need Help??


in reply to Perl in data science: could a grant from Perl foundation be useful?

No, I do not see anything here that would benefit from "throwing money at it." To accomplish their science objectives, data scientists have many options, of which "Perl is only one of now-many." The scientist's obvious (and only) goal is to get to their finish-line of an accepted publication, not per se "to use Perl" to get there. Anyone who needs to know about PDL already does, and if they elect to use it they will do so without (financial) provocation. The Foundation should keep its money in its pocket.
  • Comment on Re: Perl in data science: could a grant from Perl foundation be useful?

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Re^2: Perl in data science: could a grant from Perl foundation be useful?
by zubenel0 (Sexton) on Feb 22, 2020 at 06:37 UTC
    That's a fair point and I have doubts if financial support would have a desired effect too. However, I think that in most cases the scientist is not forced to use one particular programming language as Python, R, SAS, MATLAB, Julia, Perl or something else. The problem is not that some particular tool is necessary or not. The problem is that PDL and other Perl modules are not known well enough as options and are not attractive enough for people that could use them. For example I only recently discovered that such thing as PDL exists and did not know this option before.

    To summarize, I think that the need for usage of a particular programming language in data science is much more limited than its actual usage. The goal might be to make Perl a more attractive option not only for those who need it and cannot avoid it but also for those who do not need any particular option and are considering which of these to choose in order to achieve their goals.

      Agree that researchers are not forced to use one particular language. The choice of programming language and tools is almost free when working alone. However, when working in groups that share code it is more difficult to freely choose. Nowadays, it can be almost impossible be the only one using Perl while all others code in Python or R, unless the particular workflow and local culture allows it. For example if only exchanging data chunks in some standard format, instead of code. I believe that the major barrier to widespread use of Perl is that it has largely been displaced by Python and R in the general culture of scientific circles. Technical details or idiosyncrasies are weak arguments often used in discussions, but I believe the real thing is just cultural.
        I believe that the major barrier to widespread use of Perl is that it has largely been displaced

        There is only one book left on the shelf...

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