A drake workflow can have several custom functions stored in its R directory. It would make sense to develop unit tests for the custom functions. There is well-established tooling and structures for running testthat unit tests on an R package in RStudio (or from a command line).
Any pointers to resources or examples would be greatly appreciated. Thanks!
The best practices for unit tests do not change much when drake enters the picture. Here are the main considerations.
drake, you are probably dealing with annoyingly long runtimes in your full pipeline. So one challenge is to construct tests that do not take forever. I recommend invoking your functions on a small dataset, a small number of iterations, or whatever will get the test done in a reasonable amount of time. You can run a lot of basic checks that way. To more thoroughly validate the answers that come from your functions, you can run an additional set of checks on the results of the drake pipeline.testthat, you probably have your functions arranged in a package-like structure, or even a fully-fledged package, and you may even be loading your functions with devtools::load_all() or library(yourPackage). If you load your functions this way instead of individually sourcing your function scripts, be sure to call expose_imports() before make() so drake can analyze the functions for dependencies.