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15481966
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2013-03-18T16:30:36.560
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2014-12-03T17:57:01.780
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2014-12-03T17:57:01.780
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As a stop-gap, I've written a new <a href="http://cran.r-project.org/web/packages/rbundler/index.html" rel="nofollow">rbundler</a> package. It installs project dependencies into a project-specific subdirectory (e.g. <code><PROJECT>/.Rbundle</code>), allowing the user to avoid using global libraries. <ul> <li><a href="https://github.com/opower/rbundler" rel="nofollow">rbundler</a> on Github</li> <li><a href="http://cran.r-project.org/web/packages/rbundler/index.html" rel="nofollow">rbundler</a> on CRAN</li> </ul> We've been using <code>rbundler</code> at Opower for a few months now and have seen a huge improvement in developer workflow, testability, and maintainability of internal packages. Combined with our internal package repository, we have been able to stabilize development of a dozen or so packages for use in production applications. A common workflow: <ul> <li>Check out a project from github</li> <li>cd into the project directory</li> <li>Fire up R</li> <li>From the R console: <blockquote> library(rbundler) bundle('.') </blockquote></li> </ul> All dependencies will be installed into <code>./.Rbundle</code>, and an <code>.Renviron</code> file will be created with the following contents: <pre><code>R_LIBS_USER='.Rbundle' </code></pre> Any R operations run from within this project directory will adhere to the project-speciic library and package dependencies. Note that, while this method uses the package DESCRIPTION to define dependencies, it needn't have an actual package structure. Thus, <code>rbundler</code> becomes a general tool for managing an R project, whether it be a simple script or a full-blown package.
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