pyRerve is a library for connecting Python to an R process (an excellent statistic package) running Rserve as a RPC connection gateway. Through such a connection variables can be get and set in R from Python, and also R-functions can be called remotely. In contrast to rpy or rpy2 the R process does not have to run on the same machine, it can run on a remote machine and all variable access and function calls will be delegated there through the network.
Furthermore - and this makes everything feel very pythonic - all data structures will automatically be converted from native R to native Python and numpy types and back.
The question behind that usually is: Can pyRserve already be used for real work?
Well, pyRserve has been used at various companies in production mode for over three years now. So it is pretty stable and many things work as they should. However it is not complete yet - there are a few loose ends which should still be improved.
V 0.2 (2010-03-19) Fixed rendering of TaggedArrays
V 0.1 (2010-01-10) Initial version
It has been tested run with Python 2.6, 2.7.x, 3.2, and 3.3.
The latest development has been tested with R 3.0.1 and Rserve 1.8.0, but it also should work with R 2.13.1 and newer in that series. Rserve is suppported from version 0.6.6 on.
pyRserve has been written by Ralph Heinkel (www.ralph-heinkel.com) and is released under MIT license.
Make sure that Numpy is installed (version 1.4.x or higher).
Then from your unix/windows command line run:
pip pyRserve
For manual installation download the tar.gz or zip package. After unpacking, cd into the pyRserve directory and run python setup.py install from the command line.
Actually pip pyRserve should install numpy if it is missing.
pyRserve is now hosted on GitHub at https://github.com/ralhei/pyRserve.
Documentation can be found at http://packages.python.org/pyRserve/.
For discussion of pyRserve issues and getting help please use the Google newsgroup available at http://groups.google.com/group/pyrserve.