[pypy-dev] Motivation for re-implementing R (GNU S) in PyPy (perhaps?)

[Maurice Ling]

Well, R is free and open sourced. It is based on S and Splus, which the 
developers decided to close-source after a while (after achieving 
success). R is also known as GNU S for that matter.

IMHO, R itself is a simple language and a relatively simple platform. It 
is a language that manipulates data but philosophically, it is not a 
statistical or mathematical language. The R core team seems to adhere to 
the view that R is a programming language where (by chance and intent) a 
lot of statistical tools are built on. Hence, most of the statistical 
libraries for R are written in R. I believe that the entire Bioconductor 
is written in R.

Hence, the motivation for considering implementing or re-implementing R 
in PyPy is "natively" to bring in the strength of R (huge amounts of 
statistical libraries and data sets) into Python.

I have to admit that my skills in this area (langauage 
interpreters/compilers) is rather limited to undergraduate level but I'm 
willing to learn more. So I'm currently reading codes on language 
interpreters for esoteric languages like BrainFuck simply because they 
are tiny but provides the relevant concepts.

So, anyone like to support the idea of (re-)implementing R on PyPy? I'll 
need some "emotional" strength to go on this route. Also willing to hear 
other radical options...

Another thing of interest to me is implementing modeling/simulation 
languages in PyPy as it will help in my future career route but my 
knowledge of even the simulation languages are rather limited.

Please advice and comment.

Cheers
maurice