In my company we are currently two data scientists that work with R, and we are looking at integrating R more and more into our development and production environment.
One of the problems I am facing is this. Let's say that I am working on exploring an hypothesis which requires long computations. What I would usually do if i were working on my own is: save the partial results of these computations on a local .Rds file so that I don't have to re-run them every time, but can load them from disk.
However, this poses a problem when working in a team.
Let's say that I try out an hypothesis in an R notebook and save partial computations to disk as above. Then I commit my changes to the repository and create a pull request for my teammate to review my work. Now, he would have to run the whole time-consuming code to be able to inspect the results, because the file I saved is only available on my local machine. This often leads to us just looking at each other code and not run it, because that would take time, but this is not ideal. Has any of you encountered this problem or know a solution/package/way to approach this problem of sharing partial results?
In other words: is there a good system to share (and possibly version) data and partial results in a team, and not just code?