rocker VS paws

I am, strictly speaking, not a big R user, so take my opinion with a grain of salt, but if I were using R extensively, I would absolutely use the Rocker project containers to manage different R versions and different sets of dependencies for different projects: https://rocker-project.org/

Perhaps the main difference is r package are not available as binaries from rstudio (posit) repo but their is a cran2copr repo that works really well or you can still install from source in your home. For more info on cran2copr see: https://cran.rstudio.com/bin/linux/fedora/ . Personally I am slowly moving to container based workflow with podman (and not toolbox as you end up having your r package install directly in home but that can be worked out by specifying the ribs path). I use docker image from the rocker project: https://rocker-project.org/

If you have such specific requirements it’s often easier to use a container like the one from rocker (runs in der docker) instead. Btw wouldn’t be surprised if you’d get the latest version running in there as well.

Check out the Rocker Project, comprising of Docker containers for R, and can be used with RStudio. Also, virtual environments e.g., renv package can also help solve the package versioning issue, aside from containerization, and is transferable to a new machine via the renv::restore() function.

https://hub.docker.com/u/rocker has a lot of R-related images and they look pretty legit (look at "Tags" to find different versions). Don't use weird looking images. There's a lot of malware out there. Here's a guide on nice docker files: https://docs.docker.com/develop/develop-images/dockerfile\_best-practices/

Other people have mentioned renv and packrat already (hasn't renv basically superseded packrat at this point?), but what is also nearly ready-made to deal with this is rocker's R images. They have a bunch of images preconfigured for typical TidyVerse stuff, Shiny, etc.

The Apple M1 is ARM. As far as my knowledge, ARM isn't supported. Looks like the rocker project is aware of it. Considering how popular these chips are, i'm confident a lot of smart people are working on it. :)

But, with docker, there are many prebuilt images provided by the RStudio team directly, and other great repositories from rocker. These are basically images for your full SDLC with R, from development to deployments.

I just want to give a shout-out to the paws package (https://github.com/paws-r/paws) too. I use it often and want make others aware of it as well