This release adds new management, service, and configuration options to RStudio Package Manager. Highlights include a more versatile repository calendar, more flexibility in serving multiple binary package versions, and more options for configuring git sources. Read more →

Successful package management strategies are usually a three-part plan with clearly delineated responsibilities between admins and data scientists. Read more →

Data science teams are often frustrated by poorly-designed or nonexistent approaches to R and Python package management. In this post, you’ll learn specifically how that pain shows up for data scientists and how to identify your organization’s requirements for a better package management plan. Read more →

Data Scientists and the IT Admins or DevOps engineers who support these platforms often face “package management” problems. Understanding and following the package management prime directive can drastically ease your organization’s headaches. Read more →

Packages are the heart of open source data science, but we know they aren’t always easy. Data scientists need access to ever-evolving tools to do their best work, and IT needs to understand the risk of new software while providing a stable environment for reproducible work. RStudio Package Manager helps teams work together to accomplish these goals. Today we are excited to announce a greatly expanded focus, enabling teams to realize these benefits across languages and ecosystems by adding support for Bioconductor, beta support for Python packages from PyPI, and new options for managing historical CRAN snapshots. Read more →

RStudio analyzes how the California Department of Public Health built a COVID-19 dashboard in R and Shiny that now serves millions of California citizens. Read more →

Today we are excited to release version 1.1.6 of RStudio Package Manager and announce https://packagemanager.rstudio.com. This service builds on top of the work done by CRAN, to offer the R community: Access to pre-compiled packages on Linux via install.packages resulting in significantly faster package install times on Linux systems including cloud servers, CI/CD systems, and Docker containers. Historical checkpoints for CRAN enabling reproducible work, and even time travel, by freezing package dependencies with a one-line repository option. Read more →

RStudio Package Manager 1.1.2 introduces beta support for Windows package binaries. These binaries make it easier and faster to install R packages on Windows Desktop. With this release, all the benefits of Package Manager are available to desktop users including versioned repositories, curated subsets of CRAN, centralized access to CRAN, Git, local packages, and usage tracking. Now data scientists on Windows can easily share work, collaborate, and spend more time doing analysis instead of debugging packages. Read more →

Earlier this month we announced RStudio Package Manager version 1.1.0, a major update to RStudio Package Manager that added support for: Faster package installs on Linux with pre-compiled binaries Easier installs through the display of system requirements A calendar of repository checkpoints to make it easier to reproduce work This patch release updates the 1.1.0 version without introducing any new features. The 1.1.0.1 patch fixes a bug in the prior release that impacts performance when serving binary packages from historical checkpoints. Read more →

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 →