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 two 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. Until then I still consider it beta-status.
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.x, 2.7.x and Python 3.2.
The latest development has been tested with R 2.13.1 and Rserve 0.6.6.
pyRserve has been written by Ralph Heinkel (www.ralph-heinkel.com) and is released under MIT license.
Make sure that Numpy is installed. Actually easy_install pyRserve should install numpy if it is missing.
Then from your unix/windows command line run:
easy_install pyRserve
or download the tar.gz or zip package. After unpacking run python setup.py install from your command line.
Actually easy_install pyRserve should install numpy if it is missing. If it fails please use pip instead.
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.