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testthat 0.11.0

Hadley Wickham Headshot
Written by Hadley Wickham
2015-10-15

testthat 0.11.0 is now available on CRAN. Testthat makes it easy to turn your existing informal tests into formal automated tests that you can rerun quickly and easily. Learn more at http://r-pkgs.had.co.nz/tests.html. Install the latest version with:

install.packages("testthat")

In this version:

  • New expect_silent() ensures that code produces no output, messages, or warnings. expect_output(), expect_message(), expect_warning(), and expect_error() now accept NA as the second argument to indicate that there shouldn’t be any output, messages, warnings, or errors (i.e. they should be missing)
f <- function() {
  print(1)
  message(2)
  warning(3)
}
expect_silent(f())
#> Error: f() produced output, warnings, messages

expect_warning(log(-1), NA)
#> Error: log(-1) expected no warnings:
#> *  NaNs produced
  • Praise gets more diverse thanks to Gabor Csardi’s praise package, and you now also get random encouragment if your tests don’t pass.

  • testthat no longer muffles warning messages. This was a bug in the previous version, as warning messages are usually important and should be dealt with explicitly, either by resolving the problem or explicitly capturing them with expect_warning().

  • Two new skip functions make it easier to skip tests that don’t work in certain environments: skip_on_os() skips tests on the specified operating system, and skip_on_appveyor() skips tests on Appveyor.

There were a number of other minor improvements and bug fixes. See the release notes for a complete list.

A big thanks goes out to all the contributors who made this release happen. There’s no way I could be as productive without the fantastic commmunity of R developers who come up with thoughtful new features, and who discover and fix my bugs!

Hadley Wickham Headshot

Hadley Wickham

Chief Scientist, Posit
Hadley is Chief Scientist at Posit PBC, winner of the 2019 COPSS award, and a member of the R Foundation. He builds tools (both computational and cognitive) to make data science easier, faster, and more fun. His work includes packages for data science (like the tidyverse, which includes ggplot2, dplyr, and tidyr)and principled software development (e.g. roxygen2, testthat, and pkgdown). He is also a writer, educator, and speaker promoting the use of R for data science.