I used packrat (v 0.4.8.-1) to to create a snapshot and bundle of the R package dependencies that go along with the corresponding R code. I want to provide the R code and packrat bundle to others to make the work I am doing (including the R environment) fully reproducible.

I tested unbundling using a different computer from the one I used to write R code and create the bundle. I opened an R code file in R studio, and called library(packrat) to load packrat (also v 0.4.8-1). I then called packrat::unbundle(bundle = "directory", where = "directory"), which unbundled successfully. But subsequently calling packrat::restore() gave me the error "This project has not yet been packified. Run 'packrat::init()' to init packrat". It seems like init() should not be necessary because I am not trying to create a new snapshot, but rather utilize the one in the bundle. The packrat page (https://rstudio.github.io/packrat/) and CRAN provide very little documentation about unbundling to help troubleshoot this, or that I could point users of my code to for instructions (who likely will be familiar with R, but may not have used packrat).

So, can someone please provide clear step-by-step instructions for how users of a bundled snapshot should unbundle, and then use that saved snapshot to run a R code file?

After some experimenting, I found an approach that seems to have worked so far.

I have provided users with three files:

-tar.gz (packrat bundle file)
-unbundle.R (R code file that includes a library statement to load 
 the packrat library, and the unbundle command for the tar.gz file)
-unbundle_readme.txt  

The readme file includes instructions similar to those below, and so far users have been able to run R code using the package dependencies. The readme file tells users about requirements (R, R studio, packrat, R package development prerequisites (Rtools for Windows, XCode for Mac)), and includes output of sessionInfo() to document R package versions that the R code should use after instructions are followed. In the example below 'code_folder' refers to a folder within the tar.gz file that contains R. code and associated input files.

Example unbundle instructions:

Step 1

Save, but do not expand/unzip, the tar file to a directory. Problems with accessing the saved package dependencies are more likely when a program other than R or R studio is used to unbundle the tar file.

If the tar file has already been expanded, re-save the tar file to a new directory, which should not be a the same directory as the expanded tar file, or a subdirectory of the expanded tar file.

Step 2

Save unbundle.R in the same directory as the tar file

Step 3

Open unbundle.R using R studio

Step 4

Execute unbundle.R (This will create a subfolder ‘code_folder’. Please note that this step may take 5-15 minutes to run.)

Step 5

Close R studio

Step 6

Navigate to the subfolder ‘cold_folder’

Step 7

Open a R script using R studio (The package library should correspond to that listed below. This will indicate R studio is accessing the saved package dependencies.)

Step 8

Execute the R code, which will utilize the project package library. After the package library has been loaded using the above steps, it is not necessary to re-load the package library for each script. R studio will continue to access the package dependencies for each script you open within the R studio session. If you subsequently close R-studio, and then open scripts from within the unbundle directory, R studio should still access the dependencies without requiring re-loading of the saved package snapshot.