Summary Installing a package that has just been released to CRAN is painful for many users on Mac and Windows because often the difference between a ‘binary’ and a ‘source’ version is not immediately clear and they end up trying to install the source version, which leads to errors and heartbreak.When I was designing The Carpentries Workbench, I needed to make sure that people could reliably install R packages at any time

TL;DR In 6 months (end of November 2022) the CRAN Checks API https://cranchecks.info/ will be gone You can still get badges at https://badges.cranchecks.info You can use the new badges like: [](https://cran.r-project.org/web/checks/check_results_dplyr.html) Find more details at https://github.com/sckott/cchecksbadges Sunsetting the CRAN Checks API If you contribute an R package to

A new R package, cffr, has beendeveloped,peer-reviewed byrOpenSci and accepted by CRAN. Thispackage has a single purpose: to create a valid CITATION.cff file using themetadata of any R package. CITATION.cff files and why they matter A Citation File Format (CFF) is aplain text file with human- and machine-readable citation information forsoftware (and datasets) ¹ . Under the hood, a CFF file is a YAML file.

terrainr version 0.4.0 is now on CRAN! This version is a relatively minor updatethat shouldn’t impact most workflows, but makes some changes to improve thelogic and consistency of the package. The rest of this post runs through thechanges you can expect if you update.packages any time soon! What’s a terrainr? terrainr is an R package for theretrieval and visualization of spatial data.

In March we held a Community Call discussing the maintenance of R packages.This call included a starting presentation by Julia Silge followed by a discussion featuring panelists with a wide variety of backgrounds: Elin Waring, Erin Grand, Leonardo Collado-Torres and Scott Chamberlain.

If you have an R package on CRAN, you probably know about CRAN checks. Each package on CRAN, that is not archived on CRAN ¹ , has a checks page, like this one for ropenaq:https://cloud.r-project.org/web/checks/check_results_ropenaq.html The table above is results of running R CMD CHECK on the package on a combination of different operating systems, R versions and compilers.

Importance of Hydrology Given that liquid water is essential to life on Earth, water research cuts across numerous disciplines including hydrology, meteorology, geography, climate science, engineering, ecology, and more. Numerous R packages have emerged from this diversity of approaches, and we recently gathered many of them into a new rOpenSci task view which we broadly titled ‘Hydrology’ and published to CRAN.

Most of us who work in R just want to Get Stuff Done™. We want a minimum amount of friction between ourselves and the data we need to wrangle, analyze, and visualize. We’re focused on solving a problem or gaining insights into a new area of research. We rely on a rich, community-driven ecosystem of packages to help get our work done and likely make an unconscious assumption that there is a safety net out there, protecting us from harm.

The new magick package is an ambitious effort to modernize and simplify high-quality image processing in R. It wraps the ImageMagick STL which is perhaps the most comprehensive open-source image processing library available today. The ImageMagick library has an overwhelming amount of functionality. The current version of Magick exposes a decent chunk of it, but being a first release, documentation is still sparse.

Travis is a continuous integration service which allows for running automated testing code everytime you push to GitHub. Hadley’s book about R packages explains how and why R package authors should take advantage of this in their development process.