The latest version of the opencv R package can detect and decode QR codes! # Install latest opencvinstall.packages("opencv", repos = "https://ropensci.r-universe.dev") There are two ways of using this: the ocv_qr_detect function tries to find the QR in an image file.
As part of our multilingual publishing project, and with funding from the R Consortium, we’ve worked on the R package babeldown for translating Markdown-based content using the DeepL API.In this tech note, we’ll show how you can use babeldown to translate a Hugo blog post!
Introducing cran.dev shortlinks! On r-universe you can find package repositories from many different organizations and maintainers. But sometimes you just want to lookup a particular CRAN package, without knowing the developer.The new cran.dev shortlink service lets you navigate or link directly to the r-universe homepage and docs of any established CRAN package.
Downloading repository snapshots The new snapshot API lets you download a full copy of any CRAN-like repository on r-universe. You can use such a snapshot to mirror the entire CRAN-like repository on your own servers, or for example to build a stable, validated release of your package suite. The API endpoint is simply /api/snapshot and has several options to filter content.
A lot of what I do as rOpenSci’s community assistant is related to social media.I check for posts about rOpenSci packages, invite people to share usecases,advertise upcoming events, as well as promotingnew packages which completed software peer review.
I’m thrilled to share that CRediTas has passed peer review and been accepted to rOpenSci as well as to CRAN. I am glad to acknowledge the editor Emily Riedered and the two reviewers Marcelo S. Perlin and João Martins. Their comments and support were really insightful. CRediTas is a tiny package to facilitate the tedious job of creating CRediT authors statements for scientific publications.
I’m thrilled to share that waywiser, my R package focused on providing framework-agnostic (but tidymodels-friendly) methods for assessing models fit to spatial data 1 , has passed peer review and been accepted to rOpenSci.
How packages appear in r-universe Last month we explained how r-universe makes it easy to search and browse through the countless R packages, articles, and datasets to let you discover and learn new things. We are continuously growing this database by adding more R projects, to guide you through everything the R ecosystem has to offer. Currently r-universe is tracking and indexing of over 18.000 R packages.
Finding the right tool for the job The hardest part about effectively using R is finding the best packages for the problem you are trying to solve. I think this is even more important than being fluent in the language itself, which you will pick up along the way as you start using R more frequently. However, building your code on reliable foundations is essential for good results, and difficult to fix later on in a project.
Running your own package registry Tiny update for r-universe users whos run their own package registry: we have changed the preferred git repo name where you host your packages.json registry file. Previously the git repository was simply called universe, i.e. the registry for tiledb-inc.r-universe.dev was in the GitHub repository tiledb-inc/universe.
