rOpenSci | rOpenSci News Digest, November 2023

rOpenSci News Digest, November 2023

Dear rOpenSci friends, it’s time for our monthly news roundup!

You can read this post on our blog. Now let’s dive into the activity at and around rOpenSci!

🔗 rOpenSci HQ

🔗 Giving season: consider donating to rOpenSci

This Giving Season consider donating to rOpenSci to support our mission of empowering Open Science.

Sustaining an open project with quality infrastructure freely accessible to the global and diverse community of R software users, research software developers, and engineers requires many different resources. Our organization’s ongoing costs are supported by grants and donations from individuals and organizations which share our vision and mission.

By supporting us, you’re not just donating; you’re contributing to a community that’s breaking down barriers, creating opportunities, and shaping the future of open and reproducible science for everyone.

Join us in this vital mission today! You can donate here:

🔗 R-universe now builds WASM binaries for all R packages!

R-universe now builds WebAssembly binaries for all R packages for use in WebR applications such as shinylive. Read more in our tech note.

🔗 Recording of comm call R in Government

In this community call, our panelists shared their experiences and examples of projects with R at different levels of government and in different countries.

With Luíza Andrade, Karly Harker, Ahmadou Dicko, Pablo Tiscornia.

🔗 Coworking

Read all about coworking in our recent post!

Join us for social coworking & office hours monthly on first Tuesdays! Hosted by Steffi LaZerte and various community hosts. Everyone welcome. No RSVP needed. Consult our Events page to find your local time and how to join.

And remember, you can always cowork independently on work related to R, work on packages that tend to be neglected, or work on what ever you need to get done!

🔗 Software 📦

🔗 New packages

The following package recently became a part of our software suite:

  • fastMatMR, developed by Rohit Goswami: An interface to the fast_matrix_market C++ library, this package offers efficient read and write operations for Matrix Market files in R. It supports both sparse and dense matrix formats. Peer-reviewed at ROpenSci ( It is available on CRAN. It has been reviewed by Øystein Sørensen and Ildikó Czeller.

Discover more packages, read more about Software Peer Review.

🔗 New versions

The following eleven packages have had an update since the last newsletter: assertr (v3.0.1), beastier (v2.5), beautier (v2.6.11), biomartr (v1.0.6), drake (7.13.8), eia (v0.4.1), fastMatMR (v1.2.4), gutenbergr (v0.2.4), opencv (v0.4.0), stats19 (v3.0.2), and waywiser (v0.5.1).

🔗 Software Peer Review

There are eighteen recently closed and active submissions and 3 submissions on hold. Issues are at different stages:

Find out more about Software Peer Review and how to get involved.

🔗 On the blog

  • The rOpenSci Multiverse by Alejandra Bellini and Yanina Bellini Saibene. In this article we summarize the interviews of the series Meeting the stars of the R universe In this article, we bring you five examples of organizations and teams that choose the R Universe to facilitate access and promote community sharing of data and software. Other languages: El multiverso de rOpenSci (es).

  • Empowering Open Science: Donate to Support our Mission by The rOpenSci Team. rOpenSci is a nonprofit organization that is funded entirely by grants and donations. These collaborations enable us to sustain our projects and meet our goals.

🔗 Tech Notes

🔗 Use cases

Three use cases of our packages and resources have been reported since we sent the last newsletter.

Explore other use cases and report your own!

🔗 Call for maintainers

If you’re interested in maintaining any of the R packages below, you might enjoy reading our blog post What Does It Mean to Maintain a Package? (or listening to its discussion on the R Weekly highlights podcast hosted by Eric Nantz and Mike Thomas)!

  • rvertnet, Retrieve, map and summarize data from the archives ( Functions allow searching by many parameters, including taxonomic names, places, and dates. In addition, there is an interface for conducting spatially delimited searches, and another for requesting large datasets via email. Issue for volunteering.

🔗 Call for co-maintainers

Refer to our somewhat recent blog post to identify other packages where help is especially wished for! See also our help wanted page – before opening a PR, we recommend asking in the issue whether help is still needed.

🔗 Package development corner

Some useful tips for R package developers. 👀 For a change, this month’s tips are more about programming than about packaging.

🔗 Classed conditions from rlang functions

If you use rlang (or cli, that will pass arguments to rlang) for messages, warnings, errors, you can add a class to the signal you’re returning. This is handy for conditionally suppressing some warnings, and also for more specific testing, as explained in Mike Mahoney’s short and insightful blog post.

🔗 Static code analysis with lintr

The lintr package helps you write better R code by detecting common mistakes. It is customizable: you can skip the linters you’re not interested in.

A new version of the package was recently released on CRAN. Refer to the changelog for the changes, including a way to exclude the next line for linting, and new linters, for instance length_levels_linter() “for using the specific function nlevels() instead of checking length(levels(x))”.

🔗 How to get good with R

Nick Tierney wrote a wise post on How to get good with R, and the conclusion indicates he’s open to discussion. An important topic not only for package developers.

🔗 Lesser-known reasons to prefer apply() over for loops

Hugo Gruson wrote a very informative blog post on “Lesser-known reasons to prefer apply() over for loops”. The third one will surprise you. 😉 (Yes, this is click bait.)

🔗 Null coalescing operator soon in base R

The %||% operator that you might know from rlang has been added to the development version of base R! Source: a toot of Jenny Bryan’s.

🔗 Evercran: run historical R versions on today’s computers

Gábor Csárdi’s experimental evercran project helps you run historical R versions on today’s computers

🔗 Last words

Thanks for reading! If you want to get involved with rOpenSci, check out our Contributing Guide that can help direct you to the right place, whether you want to make code contributions, non-code contributions, or contribute in other ways like sharing use cases. You can also support our work through donations.

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