in reply to RFC -- Evolving Perl: a Decision Theory Approach to the Challenges of Perl 7

Thank you, nice write up thechartist. I agree with the fully rational approach. Regarding data science, I am sure you are aware of PDL and BioPerl. You could probably throw together a blag post or even meta module on CPAN that ties in Perl interfaces to the littany of Apache projects and others that seem to always get mentioned with Data Science. An effort like that would always identify what is missing and create a hit list. I've often thought about doing the same thing with machine learning and computer vision (e.g., OpenCV support on parity with Python), even though it's only something I reach for very rarely I know that it needs someone to be the driver. One day maybe I will have time and need for that.

That said, Python has likely consolidated enough of this information to create a nice target list of things to support. The trick is finding others in our community that would contribute to creating the critical mass to create a Data Science "community". Sounds like you definitely have the energy to blaze a trail in that regard.

But to make a reference to the confusion on why Roku was not as big of a hit as it was, my only comment is that it's not language features that get a use domain excited about a language; it's the availability and maturity of the tooling they need. So if there is a domain that someone wishes to see Perl or Roku being used as the primary medium for tools, then a substantial effort needs to be made to create the tooling. Sometimes this happens organically (most things in Perl, in particular PDL). Some things are astroturfed into a community by the full weight of the US Government (e.g., SciPy and friends - and most modern things tbh).

  • Comment on Re: RFC -- Evolving Perl: a Decision Theory Approach to the Challenges of Perl 7

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Re^2: RFC -- Evolving Perl: a Decision Theory Approach to the Challenges of Perl 7
by thechartist (Monk) on Jul 12, 2020 at 15:54 UTC

    Hi Perlfan,

    I've been going through a number of 'Meditations' here on Perl Monks, some of Larry Wall's historical statements on the motivation of Perl, watched Sawyer X's discussion on Perl 7, and had a number of discussions on the Perl Programmers Facebook group on a "wishlist" for Perl 7. Synthesizing these things deserves a separate Meditation on its own.

    FYI -- there have been a number of discussions in other forums RE: Making Perl more competitive for 'data science' applications. I think PDL is a great option currently, but the documentation and tutorials need development. I'm looking into what has been done previously with Jupyter; I'd like to have Perl PDL integrated with Jupyter notebooks to draw some attention to the current capabilities of Perl. I know there is a CPAN Jupyter Kernel, but I haven't tested it yet.

[reply]
      This thread was TL;DR and I'm probably missing the point ... but regarding

      > Jupyter notebooks

      Johann Rolschewski gave a lightning talk on integrating Perl in Jupyter on the German Perl Workshop 2020 (the biggest real Perl Workshop 2020 ;-)

      His slides are available in English

      http://jorol.de/talks/2020-GPW-Jupyter/#10

      I think there must be a video too on YT, tho in German.

      Cheers Rolf
      (addicted to the Perl Programming Language :)
      Wikisyntax for the Monastery

[reply]
      For Perl in Jupyter, see Devel::IPerl.

      If people have specific thoughts about individual points (even lots of them, or only a few) in the docs and tutorials that could be better, then please reply on here, or open an issue on https://github.com/PDLPorters/pdl/issues!

[reply]

In Section Meditations