Testing in R

testing
R
Last reviewed

April 3, 2025

Last modified

May 13, 2025

R offers several testing frameworks, but the most widely used is the testthat package. It provides a straightforward way to write unit tests for your R code. The package is designed to be easy to use, even for those who are new to testing.

Setting up testthat

To get started with testthat, you need to install the package and set up a testing structure in your R project. You need to have a tests directory in your project root. Inside this directory, you need a subdirectory called testthat. You can create this with:

# Install packages if not already installed, and load them
install.packages(c("devtools", "testthat", "usethis", "covr"))
# and then run
usethis::use_testthat()

It will set up the tests/testthat directory and a testthat.R file. This file will contain the setup code for your tests. It will also add the testthat package to your package’s DESCRIPTION file under the ‘Suggests’ field.

Tip

Please visit our Project structure guide for a recommendation on how to structure your R project.

Writing tests with testthat

Your files in the tests/testthat directory should be named test-*.R, where * is a descriptive name for the test. The testthat.R file will source all the test files in the tests/testthat directory, so you do not need to load them manually. They must match the same structure as the functions under your /R directory. For example, if you have a function my_function() in R/my_function.R, you should create a test file tests/testthat/test-my_function.R to test it.

So let’s say we have a trivial function count_tu_delft_faculties() in your project that counts the number of faculties at TU Delft. TU Delft has 8 faculties, so the function should return 8. You would create a file R/count_tu_delft_faculties.R with the following content:

#' Count the number of faculties at TU Delft
#'
#' @return The number of faculties at TU Delft
#' @export
count_tu_delft_faculties <- function() {
    # This is a placeholder function
    return(8)
}

This function is a simple placeholder that returns the number of faculties at TU Delft. In a real-world scenario, this function would contain logic to count the faculties dynamically, perhaps by querying a database or an API.

Then, you would create a test file tests/testthat/test-count_tu_delft_faculties.R to test this function. The test file should contain tests that check if the function returns the expected value (8 in this case).

test_that("description of the test", {
  # Call the function
  result <- count_tu_delft_faculties()
  
  # Test that it returns the expected value
  expect_identical(result, 8)
  
  # We could add more expectations
  expect_type(result, "double")
  # etc.
})

You can use various expect_* functions to check the results of your code.

Running tests

You should run your tests regularly to ensure that your code is working as expected. You can run all the tests in your package using:

devtools::test()

This will run all the tests in the tests/testthat directory and report any failures or errors. You can also run individual test files by specifying the file name:

devtools::test_file("tests/testthat/test-count_tu_delft_faculties.R")

This will run only the tests in the specified file.

Test coverage

To check the test coverage of your package, you can use devtools::test_coverage(). This will generate a report showing which part of your code is covered by tests and which are not.

You can also use the covr package to have a more detailed control over coverage reporting. To check the coverage of your package:

covr::package_coverage()

You can also use covr::report() to generate an HTML report of the coverage.

Learn more