Parameterized Unit Testing.
Introducing patrick
This package is an extension to testthat
that enables parameterized unit testing in R.
Installing
The release version of patrick
is available on CRAN. Install it in the usual manner:
install.packages("patrick")
The development version of patrick
is currently only available on GitHub. Install it using devtools
.
devtools::install_github("google/patrick")
To use patrick
as a testing tool within your package, add it to your list of Suggests
and Remotes
within your package's DESCRIPTION
.
Suggests:
patrick
Use
Many packages within R employ the following pattern when writing tests:
test_that("Data is a successfully converted: numeric", {
input <- convert(numeric_data)
expect_type(input, "double")
})
test_that("Data is a successfully converted: character", {
input <- convert(character_data)
expect_type(input, "character")
})
While explicit, recycling a test pattern like this is prone to user error and other issues, as it is a violation of the classic DNRY rule (do not repeat yourself). patrick
eliminates this problem by creating test parameters.
with_parameters_test_that("Data is successfully converted:", {
input <- convert(test_data)
expect_type(input, type)
},
test_data = list(numeric_data, character_data),
type = c("double", "character"),
.test_name = type
)
Parameterized tests behave exactly the same as standard testthat
tests. Per usual, you call all of your tests with devtools::test
, and they'll also run during package checks. Each executes independently and then your test report will produce a single report. A complete name for each test will be formed using the initial test description and the strings in the .test_name
parameter.
Small sets of cases can be reasonably passed as parameters to with_parameters_test_that
. This becomes less readable when the number of cases increases. To help mitigate this issue, patrick
provides a case generator helper function.
with_parameters_test_that("Data is successfully converted:", {
input <- convert(test_data)
expect_type(input, type)
},
cases(
double = list(test_data = numeric_data, type = "double"),
character = list(test_data = character_data, type = "character")
)
)
More complicated testing cases can be constructed using data frames. This is usually best handled within a helper function and in a helper-<test>.R
file.
make_cases <- function() {
tibble::tribble(
~ .test_name, ~ expr, ~ numeric_value,
"sin", sin(pi / 4), 1 / sqrt(2),
"cos", cos(pi / 4), 1 / sqrt(2),
"tan", tan(pi / 4), 1
)
}
with_parameters_test_that(
"trigonometric functions match identities",
{
testthat::expect_equal(expr, numeric_value)
},
.cases = make_cases()
)
If you don't provide test names when generating cases, patrick
will generate them automatically from the test data.
Inspiration
This package is inspired by parameterized testing packages in other languages, notably the parameterized
library in Python.
Contributing
Please read the CONTRIBUTING.md
for details on how to contribute to this project.
Disclaimer
This is not an officially supported Google product.