R package for accessing .NET

Accessing the Common Language Runtime (.NET or Mono) from the R statistical software, in-process.

You can find windows binaries of the latest version at https://rclr.codeplex.com.

Installing on Linux is always installing from source anyway, be it from a tarball, cloning the repo, or using devtools.

You may find source package tarball of the latest version at https://rclr.codeplex.com.

rClr is not your average R package and requires a few more tools than is typical for most R packages.

On Windows you will need a C# and C and/or Visual C++ compiler. Using the Visual Studio 2013 toolchain is recommended. Read the current build instructions. As of December 2014 Mono is optional on Windows.

A Linux distribution with R, g++ and the Mono toolchain (including xbuild) should work. Note that while a range of Mono versions in the 3.X series may work, I recommend you use versions 3.8 or above. This may require you to look for adequate versions (for instance Debian is lagging behind currently). You may want to have a look at the instructions at the mono download page for Linux and use the Xamarin packages.

You should be able to install the package using the install_github function of the package devtools. The following commands have been tested successfully on Windows with VS2013 and Linux with Mono 3.10, on 2014-12-19.

# Optionally you may remove a prior package
remove.packages('rClr')
library(devtools)
install_github("jmp75/rClr", build_vignettes=TRUE)

The package contains documentation, code sample and a vignette to get started.

library(rClr)
?rClr
# There is an HTML vignette:
browseVignettes('rClr')

You will otherwise find some documentation at https://r2clr.codeplex.com/documentation

While this package is sometimes used for the author's paid day job, this is largely a personal endeavour. Support is appreciated in many forms.

• Citations: As of December 2014, A presentation given at the R user conference 2013. A journal paper will, hmm, "soon" follow.
• Documentation: reporting issues, feature requests or discussion threads as such can be very valuable material if done well.
• Consulting or contract work is an option that may be arranged.

A few packages using rClr are publicly accessible, and may be of interest if you want to build your own package with dependencies on rClr.

• If you are interested in environmental modelling: RtoTIME is a package that depends on rClr
• rsqlserver is an Sql Server driver database interface (DBI) driver for R
• A package to access optimization tools on .NET