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).
