There are many community projects out there that provide binary R packages for various distributions. You may know Michael Rutter’s legendary c2d4u.team/c2d4u4.0+ PPA, but this situation has been greatly improved more recently with Detlef Steuer’s autoCRAN OBS repo for OpenSUSE, my iucar/cran Copr repo for Fedora, and Dirk Eddelbuettel’s r2u repo, again, for Ubuntu. These have obvious advantages that come with the system package management layer, such as lightning-fast installations and updates, with automatic dependency management, reversibility, and multitenancy (several users sharing the same set of packages), among others (see this paper for further details). Moreover, the {bspm} package adds the integration layer that we were lacking for all these years, enabling a bridge to the system package manager that doesn’t require admin rights or for you to leave your beloved R console (i.e. the Windows experience on Linux).
However, it may be noticed that CentOS/RHEL was the great forgotten here, but there are quite a lot of users out there tied to this distro for different reasons. Moreover, such reasons usually imply that they don’t have access to admin rights at all, not even for the setup.
So here I announce that I created the {rspm} package, which, as its name indicates, enables easy access to RStudio Public Package Manager (i.e., it does the repo setup for you), but also monitors and scans every installation to automatically detect, download, install and configure any missing system requirements. Most importantly, this is done in full user-mode (i.e., system requirements are installed into the user home) in a dynamic way (no need to restart, no need to manage environment variables). It is definitely not as fast as the other projects, but it is complementary in the sense that this may be compatible with {renv}/{pak}-based workflows (I didn’t try yet, but it would require minor adjustments if not none at all).
I made this primarily targeted at CentOS Stream 8, but for nearly the same price I added support for Ubuntu (bionic, focal, jammy) too (although note that this requires the installation of the apt-file utility). Please give it a spin if you feel like it, and let me know how it goes. Here’s a demo of the installation of {sf}, which, as you may know, has quite a number of system requirements:
Finally, I would like to thank RStudio for their investment in providing this extremely useful resource for the Linux R community.
Thanks for this post. It’s really usefull!
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