Testing is crucial

Writing tests to ensure code correctness is a crucial part of developing robust software. This is especially true for dynamic languages such as R, which lack some of the tools that ensure correctness in statically checked programming languages.

‘box’ does not dictate a specific style of testing, and different kinds of testing are appropriate in different situations. However, the following article suggests a structure for the test accompanying a module which I have found to work well.

Following the suggested structure causes the implementation and the tests of each module to be located in paths next to each other. This structure is found in several other conventions across programming languages; but it differs somewhat from the convention of R packages (where all implementation code is in a separate directory from all testing code), and differs drastically from the convention found for instance in Java. That said, it should be possible to make a Java-like test project work with ‘box’, too.

Support for existing testing frameworks

‘box’ is agnostic regarding the testing framework. The following example employs the widely used ‘testthat’ unit testing package, but other frameworks exist, and should also work.

This example uses the bio/seq module from the Getting started vignette. To enable unit testing, this module contains the following code at the very end:

if (is.null(box::name())) {

This allows us to run the tests by running the module source code from the command line, e.g. via

Rscript bio/seq.r

… or inside an IDE such as RStudio by choosing the menu item “Tools” › “Jobs” › “Start Local Job…” [1]. This works because box::name returns the name of the module from which this function is called. But if the function is invoked from code that wasn’t loaded via box::use (as is the case here), its value is NULL. In other words, is.null(box::name()) is a way of testing whether the code currently being run is loaded as a module, or executed directly.

The code inside the if imports the __tests__ submodule: that’s where we put the unit tests. The name __tests__ is a convention. You’re free to choose a different name, but I recommend sticking with this convention. Note that __tests__ is not a valid R variable name; that’s why it needs to be written in backticks, i.e. the qualified local module name is ./`__tests__`.

In this case, the __tests__ submodule consists of a directory with the following contents:

The __init__.r file corresponds closely to the file tests/testthat.R in a standard R package structure. It loads ‘testthat’ and launches the tests:


.on_load = function (ns) {


This first loads and attaches the ‘testthat’ package. Although attaching is not strictly necessary, ‘testthat’ code is a lot more readable without cluttering the code with explicit name qualifications.

Next it invokes test_dir and passes the tests’ directory via box::file inside the module’s .on_load hook — remember that only declarations should be at file level inside a module! All code execution should happen inside functions.

The helper-module.r file is a ‘testthat’ helper; these are sourced automatically by ‘testthat’ in the environment where the tests are run. We use this mechanism to load our module in the test environment:


And, again, attaching isn’t strictly necessary here. Note also that, depending on how the tests are run, this helper file might not be needed, since executing the module script file itself already loads the module contents into the global namespace; however, not all ways of loading the tests do this; for instance, RStudio’s “Start Local Job” doesn’t. So having this helper is sometimes necessary, and never hurts.

With this set-up, the actual unit test files look exactly like regular ‘testthat’ test files. For instance, here’s __tests__/test-seq.r:

test_that('valid sequences can be created', {
    expect_error((s = seq('GATTACA')), NA)

    expect_error(seq('cattaga'), NA)

test_that('invalid sequences cannot be created', {

A note on RStudio and other IDEs

Most IDEs have an option to “Source” a local file. When doing this it may seem as if the tests are correctly run, but this isn’t actually the case! This is because box::use doesn’t reload code that has already been loaded previously; instead, it uses an already loaded, cached version. This means that running the tests via the “Source” button risks running an outdated version of the tests, or the module, or both, after modifying their code.

To avoid this, always execute the test module in a new R session. In RStudio, the easiest way of doing this is by running it as a job, via the menu “Tools” › “Jobs” › “Start Local Job…” (or using the option “Source as Local Job…” in the “Source” drop-down).

Test interfaces, not implementation details

One big difference between testing module code and testing package code is that, with the testing structure laid out above, the testing code only sees the module’s public interface, it does not get access to the internal module implementation.[2]

This is by design: the idea is that we want to test the observable behaviour rather than the (purely incidental) current implementation, which might be changed. This is the way unit testing works in many other environments, and how it is often recommended.

But I realise that this may not always be appropriate. Sometimes we need to test implementation details. There are essentially two workarounds for this. For the moment, I have not yet developed a strong preference for either of these methods.

  1. Put the tests into the module files themselves.

    # mymod.r
    this_works = function () TRUE
    if (is.null(box::name())) {
        # Define tests
        test_that('implementation detail X works', {
        # Invoke tests
  2. Get access to the private module namespace for testing. When loading a module with box::use, the module object has an attribute namespace that holds the private module namespace. It generally shouldn’t be accessed by client code, but access by the testing code for a module is entirely legitimate:

    # __tests__/test-something.r
    impl = attr(mymod, 'namespace')
    test_that('implementation detail X works', {

[1] It may be tempting to instead use the “Source” button but doing so is problematic; see the section “A note on RStudio and other IDEs”!

[2] Depending on how it’s invoked; but we shouldn’t make assumptions. In particular, when invoked as a job in RStudio, the test module is loaded via the test helper, and thus the module internals are not visible.