[R] Best way to study internals of R ( mix of C, C++, Fortran, and R itself)?

[Juan Telleria]

The R Community made a call for one person to be in charge of R Contributed
Documentation, and I have done a request for being in charge of such duty.

If assigned, my plan is to implement Atlassian's Confluence along the R
Community (Accessed though R Project.org), in order to generate a Wiki and
Document Store for R, at all levels (R Internals, User Tutorials, etc.)

In a similar way the Apache Software Foundation does:
https://cwiki.apache.org/confluence/dashboard.action

So contribution and user guide for internals could be documented in such
platform for future users.


El 21/11/2017 10:26 p. m., "Jeff Newmiller" <jdnewmil at dcn.davis.ca.us>
escribió:

> 1) What is easy for one person may be very hard for another, so your
> question is really unanswerable. You do need to know C and Fortran to get
> through the source code. Get started soon reading the R Internals document
> if it sounds interesting to you... you are bound to learn something even if
> you don't stick with it. If you have questions about the internals though,
> you should read the Posting Guide to find out where to ask them (hint: not
> here).
>
> 2) There are lots of blogs and surveys out there about how R's popularity
> has increased over time, though Python seems to have higher billing in job
> descriptions I have seen. Generally if you know multiple tools and the
> underlying theory you are working with then you are more likely to succeed,
> so don't limit yourself by dismissing R for reasons of comparative
> popularity.
> --
> Sent from my phone. Please excuse my brevity.
>
> On November 21, 2017 11:14:45 AM PST, Robert Wilkins <
> iwritecode2 at gmail.com> wrote:
> >How difficult is it to get a good feel for the internals of R, if you
> >want
> >to learn the general code base, but also the CPU intensive stuff ( much
> >of
> >it in C or Fortran?) and the ways in which the general code and the CPU
> >intensive stuff is connected together?
> >
> >R has a very large audience, but my understanding is that only a small
> >group have a good understanding of the internals (and some of those
> >will
> >eventually move on to something else in their career, or retire
> >altogether).
> >
> >While I'm at it, a second question: 15 years ago, nobody would ever
> >offer a
> >job based on R skills ( SAS, yes, SPSS, maybe, but R skills, year after
> >year, did not imply job offers). How much has that changed, both for R
> >and
> >for NumPy/Pandas/SciPy ?
> >
> >thanks in advance
> >
> >Robert
> >
> >       [[alternative HTML version deleted]]
> >
> >______________________________________________
> >R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> >https://stat.ethz.ch/mailman/listinfo/r-help
> >PLEASE do read the posting guide
> >http://www.R-project.org/posting-guide.html
> >and provide commented, minimal, self-contained, reproducible code.
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/
> posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

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