Question

I am developing a framework for reproducible computing with R. One problem that I am struggling with is that some R code might run perfectly in version X.Y-Z of a package, but then why you try to reproduce it 3 years later, the packages have updated, some functions are changed, and the code doesn’t run anymore. This problem affects also for example Sweave documents that use packages.

The only way to confidently reproduce the results is by installing the R version and version of the packages that were used by the original author. If this was a single case, one could pull stuff from the CRAN archives and install appropriate versions. But for my framework this is impractical, and I need to have the package versions preinstalled.

Assume for now that I restrict myself to a single version of R, e.g. 2.14. What would be a practical way to install many versions of R packages, so that I can load them on the fly? I suppose I can do something like creating separate library directories for every version of every package and then using custom lib.loc arguments while loading them. This is going to be messy though. Any tips or previous attempts to do something similar?

My framework runs on Ubuntu server.

Answer 1

You could install packages with versions (e.g. rename to foo_1.0 directory instead of foo) and softlink the versions you want to re-create a given R + packages snapshot into one library. Obviously, the packages could actually live in a separate tree, so you could have library.projectX/foo -> library.all/foo/1.0.