Recovering R Packages Automagically

In the process of working on a new R package, one of the TODO’s on my list was testing it on a new version of R. However, upgrading R is a somewhat dreaded process, as this involves (re)installing all your old packages. While solutions like packrat deal with R package dependencies, this doesn’t seem to work for R upgrades. Another solution involves simply copying the R package library into the new R version’s package library, but this introduces the issue of potential breakage.

After some searching, I found multiple solutions that involve transferring installed packages, all doing the same basic process:

• check what packages you have currently; save the list
• upgrade R
• reinstall packages, and compare to find what’s missing

Unfortunately, all the code that does this task is messier than I’d like, so I took some time (read: procrastinated) to put together a neat little R script that writes your package list file for you, recovers it, and then installs your missing packages automagically.

## How to recover R packages version to version
##
## This script eases the transition pains of upgrading R
## by saving `.rda` files that list out your installed packages
## to compare across different versions of R, and install
## missing packages programmatically.
##
## This works with CRAN packages and Bioconductor packages,
## but unfortunately manual installation is required of Github
## packages. 
## ---------------------------------------------------------------
## 0. Functions of note

.current_pkgs <- function() {
    tmp <- installed.packages()
    current_pkgs <- as.vector(tmp[is.na(tmp[, "Priority"]), 1])
    return(current_pkgs)
}

.compare_pkgs <- function(previous_pkgs) {
    missing_pkgs <- setdiff(previous_pkgs, .current_pkgs())
    return(missing_pkgs)
}

## ----------------------------------------------------------------
## 1. Save current R version's set of packages
path <- paste0("pkgs_", gsub(" ", "_", R.Version()$version.string))
path <- gsub("\\(|\\)", "", path)
path <- gsub("-", "", path)

## Write package list for current R version as rda  
assign(path, .current_pkgs())
save(list = path, file = paste0(path, ".rda"))

## ----------------------------------------------------------------
## 2. Upgrade R

## ----------------------------------------------------------------
## 3. Reinstall packages

## Load in list of previous R version's packages
l <- list.files(pattern = "pkgs")
path <- l[length(l)] # grab the latest version's
load(file = path)
previous_pkgs <- eval(as.name(gsub(".rda", "", path)))

## Calculate and install missing packages
missing_pkgs <- .compare_pkgs(previous_pkgs)
install.packages(missing_pkgs)
update.packages()

## Bioconductor packages reinstall - post CRAN
source("https://bioconductor.org/biocLite.R")
biocLite()

missing_pkgs <- .compare_pkgs(previous_pkgs)
for (i in 1:length(missing)) { biocLite(missing_pkgs[i]) }

## Check `warnings()` to see any failures in installation