Annoucing the Rcpp Gallery

January 8, 2013

(This article was first published on Thinking inside the box , and kindly contributed to R-bloggers)

Earlier this morning, JJ announced what we had been working on for the last
few weeks: the Rcpp Gallery.

Now, as our luck will have it, the Rcpp-devel list received
his message
but did not transmit it for an apparent mail system outage at WU Vienna: no sign at the
Gmane archive of rcpp-devel
or in the personal mailboxen of myself or anybody I spoke to. Hence, so far,
and preceding this blog announcement, the only way word got out was via this
earlier tweet of mine
from about 12 hours ago.

The Rcpp Gallery is really the brainchild of JJ. It builds on what he
contributed over the last few months in not one but two implementations: Rcpp
Attributes. These are described in a
vignette of their own.
They provide very powerful new functions like sourceCpp
which allow the easiest-yet way to get compiled code into R—see for example these
posts from my blog about
simulating pi
in essentially five lines of R or five lines of C++, or this post about using
the GSL with ease
from R. The Rcpp Gallery also builds on Yihui’s excellent
knitr package which
gained the ability to process C++ code just like R code, as well as some
Ruby /
Jekyll magic to build a website on the github
infrastructure. I helped a little on the side by (at long last) learning how
to do prettier websites thanks to Boostrap and its theming extensions.

So what does it do, and what is it for? Have a look around the Rcpp Gallery site.
Each post is based on a single C++ (or Markdown) file which gets digested by
knitr and Rcpp, with the actual output shown alongside the marked up code and
explanatory text. Raw sources are available, just pass them into the
sourceCpp() function from a current Rcpp release and you should have the
same output.

Our idea is to have this as a repository for useful code: from simple and
introductory to fancy and featureful. We already seeded it with several dozen posts
covered anything from lesser known but powerful STL idioms, to Rcpp sugar, to tieing
in Armadillo or GSL, random number generation and of course benchmarking—as
we do love performance.

The entire content is in this github repository,
and our page on
how to contribute
details how you can get involved.

We are looking forward to what is to come. In many ways, we are only just getting started.

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