[pypy-dev] Motivation for re-implementing R (GNU S) in PyPy (perhaps?)
mauriceling at gmail.com
Tue Apr 24 05:48:26 CEST 2007
>> 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
>> 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.
> So, if the language is open source, quite simple and the only
> advantage would be to have huge amounts of libraries... Why not just
> make a code conversion from R to Numpy + Python, a full featured
> language, used in a lot more places. Then you can get the libraries
> and also a bigger comunity.
This could be a nice idea - make R codes run on Numpy + Python. My line
of thought is that since there is an implementation of Numpy (I do not
know how complete it is) in PyPy already (pypy/rpython/numpy),
implementing a means to get R codes to run in RPython will be just as
equally good, since RPython are essentially complete Python programs.
Kinda killing 2 birds with a stone, or so.
> Just remember that making an interpreter of R using pypy will not
> bring anything to python, as they would be diferent interpreters that
> just happen to be inplemented on the same platform. It would keep the
> same distance as R as it is today (implemented in C I suppose) and
> Python (also made in C if you consider CPython). So I would probably
> say, do the Numpy work on pypy than make a translator R2Py so you can
> run your favorite R library on top of your optimized Numpy
I think this line of argument can be made against every language
interpreter implemented in PyPy, essentially everything can be
interfaced at C. IMHO, what PyPy offers is the
language-optimization-platform modularization. This may be loafy goal
but sure worth the effort.
I am not sure what making an interpreter of X (where X can be any
anything to Python than implementing X interpreter directly on Python
itself (without using PyPy). Please enlighten me on this.
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