Understanding the `expect_silent()` Function from Testthat

The expect_silent() function is a powerful tool provided by the testthat package for unit testing in R. It allows developers to test their code’s behavior without expecting any output, which is particularly useful when dealing with functions that may throw errors or produce warnings.

However, there have been instances where users have encountered unexpected behavior of the expect_silent() function, particularly when it comes to detecting errors produced by other packages like ggplot2. In this article, we will delve into the details of how expect_silent() works and explore why it may not always detect errors as expected.

Understanding the Purpose of Expect Silent

The primary purpose of expect_silent() is to test whether a piece of code produces any output when executed. This can be useful in a variety of scenarios, such as testing the robustness of functions that may throw exceptions or producing warnings.

library(testthat)

test_that("expect_silent works as expected", {
  expect_silent({
    stop()
  })
})

In this example, we use expect_silent() to test whether the stop() function produces any output. Since stop() throws an error, we would expect the test to fail.

The Default Behavior of Expect Silent

By default, expect_silent() is set to detect errors and warnings produced by the code being tested. If the code being tested produces any output that matches this criterion, the test will fail.

However, there have been instances where expect_silent() appears to ignore errors or warnings produced by other packages, such as ggplot2. In these cases, we need to dig deeper into how expect_silent() works and why it may not always detect errors as expected.

Capturing Output from GGPlot2

One possible solution to this problem is to capture the output from ggplot2 and then test whether it can be printed. This approach requires us to create a working plot and a broken plot, and then use expect_silent() to test whether printing these plots produces any errors.

library(ggplot2)
library(testthat)

# First test should succeed (no output)
test_that("silent when ggplot2 succeeds", {
  working.plot <- ggplot(diamonds, aes(x = carat, y = price)) + geom_point()
  expect_silent(print(working.plot))
})

# Second test should fail
test_that("fails when ggplot2 throws an error", {
  broken.plot <- ggplot(diamonds, aes(x = carrot, y = price)) + geom_point()
  expect_silent(print(broken.plot))
})

In this example, we create a working plot using ggplot() and a broken plot with a misspelled column name. We then use expect_silent() to test whether printing these plots produces any errors.

The Role of Print() in R

The behavior of print() is an interesting one. In the default R session, print() is used to print objects to the console, such as charts or tables.

However, when we run code in a testing environment, such as with testthat, the output is not always printed to the console. This is because testing environments are designed to be non-interactive, meaning they do not rely on user input.

One possible reason why printing may be necessary with expect_silent() is that it relies on the assumption that most commands in R are run through the print() function. When we use print() to print an object to STDOUT, the interactive mode of the console assumes that this command is part of a larger workflow.

In testing environments, however, this assumption no longer holds. We can test whether printing is necessary by using the interactive() function from base R.

library(testthat)

test_that("print() is necessary", {
  expect_true(interactive())
})

test_that("print() is not necessary in test environment", {
  expect_false(interactive())
})

Conclusion

The expect_silent() function from testthat provides a powerful tool for unit testing in R. However, its behavior can be unpredictable when dealing with errors produced by other packages like ggplot2.

By capturing output from ggplot2 and then testing whether it can be printed, we can work around this issue and ensure that our tests produce accurate results.

We also need to understand the role of print() in R and how it behaves in different environments. By recognizing when printing may or may not be necessary, we can write more effective tests that rely on the correct behavior of expect_silent().

In summary, while expect_silent() is a powerful tool for unit testing, its behavior can be unpredictable at times. By understanding its role and how it interacts with other packages like ggplot2, we can use it to our advantage and write more effective tests.

Last modified on 2025-04-25

Understanding the expect_silent() Function from Testthat