
Rstudio
Persistent config and data for R packages - R-hub blog
Does your R package work best with some configuration? You probably want it to be easily found by your package. Does your R package download huge datasets that don’t change much on the provider side? Maybe you want to save the corresponding data somewhere persistent so that things will go faster during the next R session. In this blog post we shall explain how an R package developer can go about using and setting persistent configuration and data on the user’s machine.
Package Manager 1.1.0 - No Interruptions | RStudio Blog
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.
Scaling and Performance - Tuning Applications in Shiny Server Pro – RStudio Support
Shiny Server Pro allows you to scale Shiny applications to support multiple simultaneous users. The scaling is accomplished by setting 3 arguments in the configuration file (/etc/shiny-server/shiny...