Mastodawn

{testthat} is great for automatic testing. Here are some tricks for the heavy user: https://blog.r-hub.io/2020/11/18/testthat-utility-belt/ #rstats #testing #unittest #testthat

Helper code and files for your testthat tests - R-hub blog

If your package uses testthat for unit testing, as many packages on CRAN, you might have wondered at least once about where to put “things” you wished to use in several tests: a function generating a random string, an example image, etc. In this blog post, we shall offer a round-up of how to use such code and files when testing your package. Code called in your tests Remember our post about internal functions in R packages? What about internal functions in unit tests of R packages? And code that needs to be run for tests?

Data Science Jan 16

Its good to have many tests in your R package, but it can be a pain to debug some failing tests when it happens. {lazytest} for the rescue: only rerun the failing tests, until they pass: https://lazytest.cynkra.com/ #RStats #testthat #lazy

Runs Only Failed Tests

A companion package to the testthat package that saves development time by helping you rerun only the tests that have failed during the last run.

Simon Nov 28

Wrote about using #googlejules to migrate an #RStats test suite to #testthat

https://www.linkedin.com/posts/mirai-solutions-gmbh_from-runit-to-testthat-with-coding-agent-activity-7399043585066655744-yRX6

#aiagents

From RUnit to testthat with Coding Agent Support | Mirai Solutions GmbH

We present an interesting case study: we migrated the test suite of our R package 𝗫𝗟𝗖𝗼𝗻𝗻𝗲𝗰𝘁 from 𝗥𝗨𝗻𝗶𝘁 to 𝘁𝗲𝘀𝘁𝘁𝗵𝗮𝘁 using 𝗔𝗜-𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗰𝗼𝗱𝗶𝗻𝗴 𝗮𝗴𝗲𝗻𝘁𝘀s. We used 𝗚𝗼𝗼𝗴𝗹𝗲 𝗝𝘂𝗹𝗲𝘀, an asynchronous coding agent, to handle the repetitive, multi-file refactoring work. The process wasn't just about automation, it required careful context preparation, environment setup, and iterative prompt engineering. Key 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆𝘀: • AI agents excel at tedious, semantics-aware tasks (like fixing 𝘦𝘹𝘱𝘦𝘤𝘵_𝘦𝘲𝘶𝘢𝘭 argument order across dozens of files) • Managed VM environments reduce risks while maintaining utility • Combining different AI tools (Jules + Aider) provided robust validation through "third-party" code review This results in a faithfully migrated test suite with equivalent coverage and behavior, achieved faster and with more confidence. Read about our process, challenges, and solutions in our news post. https://lnkd.in/d-QUGDJ4 #rstats #SoftwareDevelopment #AIEngineering #TestAutomation #OpenSource

Data Science Nov 17

Discover the power of property-based testing in R with the #quickcheck package! Seamlessly integrates with #testthat and offers a variety of generators for atomic vectors, lists, and tibbles. Perfect for ensuring your code's reliability. Check it out: https://github.com/armcn/quickcheck #rstats #rprogramming #testing

GitHub - armcn/quickcheck: Property Based Testing in R

Property Based Testing in R. Contribute to armcn/quickcheck development by creating an account on GitHub.

GitHub

Data Science Oct 14

{testthat} is great for automatic testing. Here are some tricks for the heavy user: https://blog.r-hub.io/2020/11/18/testthat-utility-belt/ #rstats #testing #unittest #testthat

Helper code and files for your testthat tests - R-hub blog

If your package uses testthat for unit testing, as many packages on CRAN, you might have wondered at least once about where to put “things” you wished to use in several tests: a function generating a random string, an example image, etc. In this blog post, we shall offer a round-up of how to use such code and files when testing your package. Code called in your tests Remember our post about internal functions in R packages? What about internal functions in unit tests of R packages? And code that needs to be run for tests?

Data Science Sep 23

Its good to have many tests in your R package, but it can be a pain to debug some failing tests when it happens. {lazytest} for the rescue: only rerun the failing tests, until they pass: https://lazytest.cynkra.com/ #RStats #testthat #lazy

Runs Only Failed Tests

A companion package to the testthat package that saves development time by helping you rerun only the tests that have failed during the last run.

Data Science Jul 25, 2025

Discover the power of property-based testing in R with the #quickcheck package! Seamlessly integrates with #testthat and offers a variety of generators for atomic vectors, lists, and tibbles. Perfect for ensuring your code's reliability. Check it out: https://github.com/armcn/quickcheck #rstats #rprogramming #testing

GitHub - armcn/quickcheck: Property Based Testing in R

Property Based Testing in R. Contribute to armcn/quickcheck development by creating an account on GitHub.

GitHub

Data Science Jun 21, 2025

{testthat} is great for automatic testing. Here are some tricks for the heavy user: https://blog.r-hub.io/2020/11/18/testthat-utility-belt/ #rstats #testing #unittest #testthat

Helper code and files for your testthat tests - R-hub blog

If your package uses testthat for unit testing, as many packages on CRAN, you might have wondered at least once about where to put “things” you wished to use in several tests: a function generating a random string, an example image, etc. In this blog post, we shall offer a round-up of how to use such code and files when testing your package. Code called in your tests Remember our post about internal functions in R packages? What about internal functions in unit tests of R packages? And code that needs to be run for tests?

Data Science May 30, 2025

Its good to have many tests in your R package, but it can be a pain to debug some failing tests when it happens. {lazytest} for the rescue: only rerun the failing tests, until they pass: https://lazytest.cynkra.com/ #RStats #testthat #lazy

Runs Only Failed Tests

A companion package to the testthat package that saves development time by helping you rerun only the tests that have failed during the last run.

Data Science Mar 31, 2025

Discover the power of property-based testing in R with the #quickcheck package! Seamlessly integrates with #testthat and offers a variety of generators for atomic vectors, lists, and tibbles. Perfect for ensuring your code's reliability. Check it out: https://github.com/armcn/quickcheck #rstats #rprogramming #testing

GitHub - armcn/quickcheck: Property Based Testing in R

Property Based Testing in R. Contribute to armcn/quickcheck development by creating an account on GitHub.

GitHub