Wednesday, July 23, 2025 From rOpenSci (https://ropensci.org/blog/2025/07/23/news-july-2025/). Except where otherwise noted, content on this site is licensed under the CC-BY license.
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!
We’re very excited to introduce the new rOpenSci Champions! This cohort will participate in the program and carry out their work in Spanish, allowing us to continue strengthening the open science and research software development community in this language. We’re excited about the projects they’ll be developing, which tackle real-world challenges across diverse disciplines and regions of Latin America.
Read all about the new Champions and their projects in our blog post.
August 1st, useR! 2025 Virtual with free registration.
August 8th through 10th, 2025 useR! 2025 will take place in Penn Pavilion, Duke University, Durham, North Carolina.
rOpenSci will be there!
Yanina Bellini Saibene will be presenting her keynote “We R Together. How to learn, use and improve a programming language as a community” on Sat, Aug 9, 2025 - 17:00–18:00 (EDT)
Will Landau will be presenting his keynote “Poweful simulation pipelines with {targets}” on Sun, Aug 10, 2025 - 15:00-16:00 (EDT)
Noam Ross will be presenting “Curating a Community of Packages: Lessons from a Decade of rOpenSci Peer Review” on Sat, Aug 9, 2025 - 13:00–14:10 (EDT)
Our Champion Erika Siregar is presenting “rPlaywright: Bringing Playwright’s Power to R for Scalable Web Automation”, Fri, Aug 8, 2025 - 18:15–19:30 (EDT)
Our Champion Andrea Gomez Vargas is presenting “ARcenso: A Package Born from Chaos, Powered by Community” on Sat, Aug 9, 2025 - 13:00–14:10 (EDT)
Luis D. Verde Arregoita is presenting “Bringing the fun of hex stickers to your R session” on Sun, Aug 10, 2025 - 10:30–12:00 (EDT)
We are looking forward to seeing you there!
Read all about coworking!
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!
The following package recently became a part of our software suite:
Discover more packages, read more about Software Peer Review.
The following nine packages have had an update since the last newsletter: commonmark (v2.0.0), emodnet.wfs (v2.1.1), crul (v1.6.0), fellingdater (v1.2.0), lightr (v1.9.0), qpdf (v1.4.0), weathercan (v0.7.4), webchem (v1.3.1), and webmockr (v2.2.0).
There are sixteen recently closed and active submissions and 5 submissions on hold. Issues are at different stages:
One at ‘6/approved’:
Four at ‘4/review(s)-in-awaiting-changes’:
trud, Query the NHS TRUD API. Submitted by Alasdair Warwick.
SSARP, SSARP (Species-/Speciation-Area Relationship Projector). Submitted by kmartinet.
dataset, Create Data Frames that are Easier to Exchange and Reuse. Submitted by Daniel Antal.
pkgmatch, Find R Packages Matching Either Descriptions or Other R Packages. Submitted by mark padgham.
Seven at ‘3/reviewer(s)-assigned’:
openFDA, openFDA API. Submitted by Simon Parker.
reviser, Tools for Studying Revision Properties in Real-Time Time Series Vintages. Submitted by Marc Burri.
rixpress, Build Reproducible Analytical Pipelines With Nix. Submitted by Bruno Rodrigues.
partialling.out, Residuals from partial regressions. Submitted by Marc Bosch. (Stats).
distionary, Create and Evaluate Probability Distributions. Submitted by Vincenzo Coia.
sasquatch, Use SAS, R, and quarto Together. Submitted by Ryan Zomorrodi.
read.abares, Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources. Submitted by Adam H. Sparks.
Two at ‘2/seeking-reviewer(s)’:
mantis, Multiple Time Series Scanner. Submitted by Phuong Quan.
galamm, Generalized Additive Latent and Mixed Models. Submitted by Øystein Sørensen. (Stats).
Two at ‘1/editor-checks’:
SPARQLchunks, Run SPARQL Chunks and Inline Functions to Retrieve Data. Submitted by André Ourednik.
capybara, Fast and Memory Efficient Fitting of Linear Models With High-Dimensional. Submitted by Mauricio “Pachá” Vargas Sepúlveda.
Find out more about Software Peer Review and how to get involved.
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?.
Refer to our help wanted page – before opening a PR, we recommend asking in the issue whether help is still needed.
Some useful tips for R package developers. 👀
Sharing a request by Heather Turner and Lluís Revilla.
There is a new CRAN Task View proposal for “Package Development and Maintenance”. This task view lists and comments on packages useful for package development and maintenance. The authors and the CRAN task View editorial team are looking for feedback. In particular, they’d especially like your feedback if you’re new to package development or find the idea of creating and maintaining a package intimidating (to avoid the “curse of knowledge”).
Regarding this task view, they’d like to know:
Read the proposal. Please submit your feedback directly in the repository or send the feedback through private channels to Lluís Revilla (email, Slack, …)
If you’re writing a wrapper for an API that has no regular caching headers, you might be interested in the cachem package for caching. Thanks to Tan Ho and Pieter Huybrechts for the tip. See its use in comtradr by Paul Bochtler.
Miles McBain shared an interesting debugging tip in his post Dive()ing into the hunt #rstats, using a custom function to implement something like a ‘row-wise data debug’ mode!
The CRAN cookbook by Jasmine Daly and Beni Altmann features a section called “Structuring of Examples” mentioning dontrun and friends and their use cases. Thanks to Hugo Gruson for the find!
Carlos Scheidegger, a developer of Quarto, wrote an interesting Bluesky thread about why it’s not considerate to write “any update on this?” on open bug reports or feature requests.
Carlos suggests that better alternatives are to “add new information to the post about how you want to use it, or other workarounds” which might give developers ideas for different fixes, or to simply upvote the request. But avoid “any updates?”, which is hard on the developer because all they can say is “no”, and they know that will disappoint people.
The chores package by Simon Couch provides LLM helpers for tasks that are hard to automate, like converting your messages to using the cli R package. Its thoughtful documentation includes guidance on creating your own helpers.
Speaking of LLM tooling in R, Luis D. Verde Arregoitia maintains an extensive guide.
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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