This project will has moved to the address https://rclr.codeplex.com. As of December 2014, newer packages are at the new site

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

Keywords
interfacing R and .NET; R and Mono; R to .NET; CLR hosting; embedding Mono

Installation instructions
Please follow the Installing R packages in the Documentation. A Quick start page documents the first steps to get the library loaded in R.

News

2014-12-18: Release 0.7-2 is available from https://rclr.codeplex.com.

2013-09-21: Release 0.5-2 (beta 5)
  • Fixed memory leaks when passing R vectors to .NET
  • Major improvement to the handling and reporting of CLR exceptions on MS.NET
  • The download page also has a tarball of the sources
  • Support for Mono included in the windows binaries. Date-time handling is the main lagging feature.

Summary
The R Project for Statistical Computing has seen an outstanding adoption in many scientific fields and is a tool of choice for many. Some things are still better done in other languages (C, Fortran, Java, .NET, etc.).
There are ways to link R in-process with most languages, however the interoperability with .NET is lagging.
R.NET offers one way to access R from a Common Language Runtime implementation (CLR).
The project rClr offers the access to a CLR from R in a manner natural to R users.

To give a feel for the capabilities, below is an extract from the tutorials. A hydrology model written in C# and its time series outputs are visualized in R.

001.PNG

rClr aims to be for .NET CLR implementations (.NET framework and Mono) what rJava is for Java.

Last edited Thu at 6:46 AM by jperraud, version 26