Okay, the title may be a little misleading. But it addresses the problem I have.
I’m running many different R projects in production. So they must run in a reproductive way and I can’t afford that the programs break if a package update is installed.
Official Way To Solve This Problem
There are some package manager for R available. But all of them have some drawbacks
- Setting snapshots and going back and forth doesn’t work for me and I was getting a mess.
- Packrat doesn’t work well when you are using locally hosted packages.
- It gets really complicated when you use packages from CRAN which you’ve patched locally.
- Uses only snapshots of CRAN. So you can’t use local packages.
- Uses local copy of CRAN packages.
- I had problems with multi-platform setup: Developing on a Mac and going productive on a Linux server.
I’ve found a way around these package managers. I began using git a safety net.
So my directory
~/Library/R/3.6/library containing all my locally installed
R-packages is a git repository.
When I (accidently) install an update of a package I can go back using all the power of git.
So now I can use a branch for each project. When I need to update a package for project A all other projects aren’t affected.
But do I tell project A to use the correct branch of my repository?
I checkout each branch with the command
git worktree add ~/RLIBS/<project> <BRANCH>
In the project-directory I add an
.Renviron-file with this content
If you’re using RStudio for package development you may have to set the right library-directory in your user’s home-driectory .Renviron file because when you build the new package RStudio runs a new R-session with your home-directory as working directory.
So always check your lib-paths with
The downside of this behaviour is that it isn’t simple to put an update of a project with new libraries into production. I think therefor docker is an interesting alternative.
This article is the result of a lightning-talk I held at Campus useR Group Frankfurt.