Halloween is around the corner so it’s good time to discuss two of R’s scoping mechanisms. R is rich in features, sometimes making it hard to select amoung them. My alarm bells ring loudly when I see manual scope control. After I started writing packages, I realized I wasn’t fully taking advantage of R’s natural beauty to simplify code.

As I searched for good ideas and tips for customizing Rprofile.site and .Rprofile, a common construct I found was:

  r <- getOption("repos")
  r["CRAN"] <- "http://cran.revolutionanalytics.com"
  options("repos" = r)

The use of local() prevents the enclosed code from making any changes to the base environment which is a good thing. Functions also work the same way and it just so happens R provides .First(). We can move the code into .First() and toss local(). Easy peasy.

The next construct I found is

.env <- new.env()
.env$some_function <- function(x) {
    # your code here

.env$different_function <- function(x) {
    # your code here

This creates a hidden namespace, attaches it to the search path, and adds a few utilty functions. Being hidden prevents it from being deleted when you cleanup your environment with rm(). Well, that’s only true if the argument to rm doesn’t include hidden objects.

Defining functions in an initialization file doesn’t help portability, compatibility, or sharability. Where do most functions come from? Packages! If you put all your functions into a package and host it in git repo, you have an easy way to share your code, even if it’s just among your computers. Once you devtools::install_github("my-account/my-package"), you don’t need to attach it to your environment to use any of the functions. Just invoke my-package::my-function(). Now there’s even less clutter in your environment. Sharing could also mean deploying your Shiny app, where the rsconnect package will automatically manage your dependencies.

If you document your functions, the switch to a package format is almost as simple as changing comment delimiters. RStudio will manage all other aspects of building a package. You benefit because now you can access your documentation from R’s help system.

Ah, but you still want your wonderful functions loaded automatically. The simplest code is

.First <- function() {
  library("my-package", quietly = TRUE)

If the library can’t be loaded, then library() will stop execution with an error. I don’t like stopping the initialization process over a missing optional piece. Let’s try library()'s sibling

.First <- function() {
  require("my-package", quietly = TRUE)

That works, but it displays a warning if the package is missing. Needless noise.

.First <- function() {
  suppressWarnings(require("my-package", quietly = TRUE))

The initialization process will complete and won’t display any warning or informational messages. Plus a logical is returned for any additional processing.

.First <- function() {
  if (suppressWarnings(require("my-package", quietly = TRUE)) ) {
      "my-package.option1" = TRUE,
      "my-package.option2" = "my-message"

If you find yourself trying to twist or bend the scoping rules, think if a function or package would accomplish the same result and provide additional benefits of better organization, sharing, documentation and easy Shiny deployment.

See Rprofile.site, dgutils, and wdprompt for my customizations.

Creative Commons License David Gabbé

Generated on: 30-Jul-2018