No interruptions. That was our team’s goal for RStudio Package Manager 1.1.0 - we set out to make R package installation fast enough that it wouldn’t interrupt your work. More and more data scientists use Linux environments, whether to access extra horsepower during development or to run production code in containers. Unfortunately, the rise in Linux environments has seen a corresponding increase in package installation pain. For Windows and Mac OS, CRAN provides pre-compiled binary packages that install almost instantly, but the same binaries are not available on Linux. Read more →

We’re excited to announce that renv is now available on CRAN! You can install renv with: install.packages("renv") renv is an R dependency manager. Use renv to make your projects more: Isolated: Each project gets its own library of R packages, so you can feel free to upgrade and change package versions in one project without worrying about breaking your other projects. Portable: Because renv captures the state of your R packages within a lockfile, you can more easily share and collaborate on projects with others, and ensure that everyone is working from a common base. Read more →

Access to data is crucial for data science. Unfortunately, servers that run RStudio are often disconnected from databases, especially in organizations that are new to R. In order to help data scientists access their databases, RStudio offers ODBC data connectors that are supported, easy to install, and designed to work everywhere you use RStudio professional products. The 1.6.0 release of RStudio Professional Drivers includes a few important updates. New data sources Read more →

Shiny 1.4.0 has been released! This release mostly focuses on under-the-hood fixes, but there are a few user-facing changes as well. If you’ve written a Shiny app before, you’ve probably encountered errors like this: div("Hello", "world!", ) #> Error in tag("div", list(...)) : argument is missing, with no default This is due to a trailing comma in div(). It’s very easy to accidentally add trailing commas when you’re writing and debugging a Shiny application. Read more →

We’re hosting a free, half-day event with one of our Full Service Certified Partners, ProCogia, in Seattle on Wednesday October 9th. This event is for data science and IT teams that want to learn more about: helpful new RStudio R packages like pins what RStudio professional products can do for your data science team if you have both Jupyter and RStudio users using Kubernetes or Slurm to scale your work If you’re interested in learning more, be sure to register on the ProCogia event page: RStudio & ProCogia Roadshow: R in Enterprise. Read more →

Join RStudio at one of our Fall and Winter workshops! We’ll be hosting a few different workshops in a variety of cities across the US and UK. Topics range from building tidy tools, to teaching data science, to mastering machine learning. See below for more details on each workshop and how to register. Building Tidy Tools with Hadley Wickham When: October 14 & 15, 2019 Where: Loudermilk Conference Center in Atlanta, GA Read more →

This release adds new workflows for data scientists and improved production settings for administrators. For data scientists, it used to be hard to use the same data or R objects in different content, and even harder to update those resources regularly. This release enables you to pin objects in Connect to solve these challenges. For administrators, we’ve reduced the most common sources of publishing failures and significantly improved error handling. Read more →

Join us Wednesday, October 23rd, in Austin, Texas as RStudio teams up with Yotabites, to host a free half-day event on using open source data science languages and RStudio in production. Yotabites is an RStudio Full Service Certified Partner that provides consulting and professional services for RStudio products. This event is for RStudio and Jupyter users and their IT colleagues who enable them. We will show how RStudio products can be incorporated into robust business processes and how Yotabites can help simplify the process. Read more →

Today, we’re announcing an important update to RStudio Server Pro 1.2 that introduces two new capabilities. Slurm Jobs Slurm is a open-source workload management system, capable of running distributed jobs across a cluster. It’s a popular tool for data science teams to run big, resource-intensive jobs on dedicated hardware. In this update, we’re introducing a new Slurm back end for RStudio Server Pro’s new Job Launcher (itself introduced in the initial release of RStudio Server Pro 1. Read more →

Today we are excited to announce the pins package is available on CRAN! pins allows you to pin, discover and share remote resources, locally or in remote storage. If you find yourself using download.file() or asking others to download files before running your R code, use pin() to achieve fast, simple and reliable reproducible research over remote resources. Pins You can use the pins package to: Pin remote resources locally to work offline and cache results with ease, pin() stores resources in boards which you can then retrieve with pin_get(). Read more →