unitizer
Differ from testthat
?unitizer
and Packagesunitizer
unitizer
Writes To Your Filesystemall.equal
Stored Reference Valuesunitizer
unitizer
Is Complexunitize
within try
/ tryCatch
Blocksunitizer
Promptunitizer
simplifies creating, reviewing, and debugging unit tests in R. To install:
install.packages('unitizer')
Please keep in mind this is an experimental framework that has been thoroughly tested by one person.
unitizer
bakes in a lot of contextual help so you can get started without reading all the documentation. Try the demo to get an idea:
library(unitizer)
demo(unitizer)
Or check out the screencast to see unitizer
in action.
Are you tired of the deparse
/dput
then copy-paste R objects into test file dance, or do you use testthat::expect_equal_to_reference
a lot?
With unitizer
you review function output at an interactive prompt as you would with informal tests. You then store the value, conditions ( e.g. warnings, etc.), and environment for use as the reference values in formal tests, all with a single keystroke.
Do you wish the nature of a test failure was more immediately obvious?
When tests fail, you are shown a proper diff so you can clearly identify how the test failed:
diff example
Do you wish that you could start debugging your failed tests without additional set-up work?
unitizer
drops you in the test environment so you can debug why the test failed without further ado:
review example
Do you avoid improvements to your functions because that would require painstakingly updating many tests?
The diffs for the failed tests let you immediately confirm only what you intended changed. Then you can update each test with a single keystroke.
unitizer
stores R expressions and the result of evaluating them so that it can detect code regressions. This is akin to saving test output to a .Rout.save
file as documented in Writing R Extensions, except that we’re storing the actual R objects and it is much easier to review them.
To use unitizer
:
unitize("my_file_name.R")
and follow the promptsunitize("my_file_name.R")
; if any tests fail you will be able to review and debug them in an interactive promptunitizer
can run in a non-interactive mode for use with R CMD check
.
help(package="unitizer")
, in particular ?unitize
demo(package="unitizer")
browseVignettes("unitizer")
for a list of vignettes, or skip straight to the Introduction vignetteunitizer
Differ from testthat
?unitizer
requires you to review test outputs and confirm they are as expected. testthat
requires you to assert what the test outputs should be beforehand. There are trade-offs between these strategies that we illustrate here, first with testthat
:
vec <- c(10, -10, 0, .1, Inf, NA)
expect_error(
log10(letters),
"Error in log10\\(letters\\) : non-numeric argument to mathematical function\n"
)
expect_equal(log10(vec), c(1, NaN, -Inf, -1, Inf, NA))
expect_warning(log10(vec), "NaNs produced")
And with unitizer
:
vec <- c(10, -10, 0, .1, Inf, NA)
log10(letters) # input error
log10(vec) # succeed with warnings
These two unit test implementations are functionally equivalent. There are benefits to both approaches. In favor of unitizer
:
In favor of testthat
:
unitizer
you still need to unitize
and review the testsunitizer
is particularly convenient when the tests return complex objects (e.g as lm
does) or produce conditions. There is no need for complicated assertions involving deparsed objects.
testthat
tests to unitizer
If you have a stable set of tests it is probably not worth trying to convert them to unitizer
unless you expect the code those tests cover to change substantially. If you do decide to convert tests you can use the provided testthat_translate*
functions (see ?testthat_translate_file
).
unitizer
and PackagesThe simplest way to use unitizer
as part of your package development process is to create a tests/unitizer
folder for all your unitizer
test scripts. Here is a sample test structure from the demo package:
unitizer.fastlm/ # top level package directory
R/
tests/
run.R # <- calls `unitize` or `unitize_dir`
unitizer/
fastlm.R
cornerCases.R
And this is what the tests/run.R
file would look like
library(unitizer)
unitize("unitizer/fastlm.R")
unitize("unitizer/cornerCases.R")
or equivalently
library(unitizer)
unitize_dir("unitizer")
The path specification for test files should be relative to the tests
directory as that is what R CMD check
uses. When unitize
is run by R CMD check
it will run in a non-interactive mode that will succeed only if all tests pass.
You can use any folder name for your tests, but if you use “tests/unitizer” unitize
will look for files automatically, so the following work assuming your working directory is a folder within the package:
unitize_dir() # same as `unitize_dir("unitizer")`
unitize("fast") # same as `unitize("fastlm.R")`
unitize() # Will prompt for a file to `unitize`
Remember to include unitizer
as a “suggests” package in your DESCRIPTION file.
unitizer
unitizer
Writes To Your FilesystemThe unitize
d tests need to be saved someplace, and the default action is to save to the same directory as the test file. You will always be prompted by unitizer
before it writes to your file system. See storing unitized
tests for implications and alternatives.
all.equal
Stored Reference ValuesOnce you have created your first unitizer
with unitize
, subsequent calls to unitize
will compare the old stored value to the new one using all.equal
. You can change the comparison function by using unitizer_sect
(see tests vignette).
This means you need to be careful with expressions that may deparse differently on different machines. For example, in order to avoid round issues with numerics, it is better to use:
Instead of:
unitizer
can track and manage many aspects of state to make your tests more reproducible. For example, unitizer
can reset your search path to what is is found in a fresh R session prior to running tests to avoid conflicts with whatever libraries you happen to have loaded at the time. Your session state is restored when unitizer
exits. The following aspects of state can be actively tracked and managed:
State management is turned off by default because it requires tracing some base functions which is against CRAN policy. If you wish to enable this feature use unitize(..., state='recommended')
or options(unitizer.state='recommended')
. For more details see ?unitizerState
and the reproducible tests vignette.
unitizer
If you interrupt evaluation with CTRL+C (or with ESC in RStudio), or if you browser
/debug
and quit with ‘Q’, you will exit unitizer
with no opportunity to save any modifications you made during unitizer
review. Make sure you quit by typing ‘Q’ at the unitizer
prompt. If you are in browser
, you will need to let the browsed function finish evaluation to return to the unitizer
prompt, and only then quit.
Tests that modify objects by reference are not perfectly suited for use with unitizer
. The tests will work fine, but unitizer
will only be able to show you the most recent version of the reference object when you review a test, not what it was like when the test was evaluated. This is only an issue with reference objects that are modified (e.g. environments, RC objects, data.table
modified with :=
or set*
).
unitizer
Is ComplexIn order to re-create the feel of the R prompt within unitizer
we resorted to a fair bit of trickery. For the most part this should be transparent to the user, but you should be aware it exists in the event something unexpected happens that exposes it. Here is a non-exhaustive list of some of the tricky things we do:
quit
/q
and ls
(see esoteric topics vignette) at the unitizer
prompttraceback
should work when reviewing tests that produce errors, but only because we capture the trace with sys.calls
and write it to base::.Traceback
during review.Last.value
will not workstdout
and stderr
during test evaluation to capture those streams (see details on tests vignette), though we take care to do so responsiblyunitizer
interactions do not pollute itIn particular, you should avoid evaluating tests that invoke debug
ged functions, or introducing interactivity by using something like options(error=recover)
, or readline
, or some such. Tests will work, but the interaction will be challenging because you will have to do it with stderr
and stdout
captured…
unitize
within try
/ tryCatch
BlocksDoing so will cause unitize
to quit if any test expressions throw conditions. See discussion in error handling.
unitizer
Promptq
and quit
are masked to give the user an opportunity to cancel the quit action in case they meant to quit from unitizer
instead of R. Use Q to quit from unitizer
, as you would from browser
.
ls
is masked with a specialized version for use in unitizer
.
In both cases you can still access the original functions by preceding them with base::