Linking R and Julia?

Question

Julia looks very promising for fast and syntax-sane computation (e.g. here), but I suspect it will not be anywhere near R in terms of overall statistics workflow for some ti

Answer 1

A quick update. Since this question was asked, there has been the beginnings of a Julia package that allows one to call R programs from within Julia.

More here: https://github.com/lgautier/Rif.jl

Answer 2

I too have been looking at Julia ever since Doug Bates sent me a heads-up in January. But like @gsk3, I measure this on an "Rcpp scale" as I would like to pass rich R objects to Julia. And that does not seem to be supported at all right now.

Julia has a nice and simple C interface. So that gets us something like .C(). But as recently discussed on r-devel, you really do not want .C(), in most cases you rather want .Call() in order to pass actual SEXP variables representing real R objects. So right now I see little scope for Julia from R because of this limitation.

Maybe an indirect interface using tcp/ip to Rserve could be a first start before Julia matures a little and we get a proper C++ interface. Or we use something based on Rcpp to get from from R to C++ before we enter an intermediate layer [which someone would have to write] from which we data feed to Julia, just like the actual R API only offers a C layer. Dunno.

And the end of the day, some patience may be needed. I started to look at R around 1996 or 1997 when Fritz Leisch made the first announcements on the comp.os.linux.announce newsgroup. And R had rather limited facilities then (but the full promise of the S language, of course, si we knew we had a winner). And a few years later I was ready to make it my primary modeling language. At that time CRAN had still way less than 100 packages...

Julia may well get there. But for now I suspect many of us will get work done in R, and have just a few curious glimpses at Julia.