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We are happy to announce the availability of v1.1 of RStudio Shiny Server Pro, our commercial server for deploying Shiny applications. In this release we took your feedback and made it easier for you to integrate Shiny Server Pro into your production environments. With Shiny Server Pro v1.1 you now can:
- Control access to your applications with Google Authentication (OAuth2).
- Create sessions and authenticate with PAM (auth_pam and pam_sessions_profile).
- Set the version of R that is used per application and/or per user
- Customize page templates for directory listings and error pages.
- Monitor service health and get additional metrics with a new health check endpoint.
- Provide custom environment variables to a Shiny process using Bash profiles
- Configure apps to run using the authenticated user’s account with custom environment variables from Bash or PAM
- Launch Shiny apps with a prefix command such as ‘nice’ allowing you to prioritize compute resources per application or per user
If you haven’t tried Shiny Server Pro yet, download a copy here.
We’ve redesigned our training pages to make it even easier for you to learn R or Shiny. Visit our new training web page, www.rstudio.com/training, to see:
- A curated list of free materials for learning R. We think that these are some of the most helpful resources on the web. They would make an effective starting place if you want to improve your R skills.
- Announcements for upcoming RStudio public workshops, like the Introduction to R course that we’re holding on April 28 & 29 in San Francisco.
- A database of well known R instructors, who can provide on-site — as well as online — R training.
- Links to the new Shiny Dev Center, which includes articles, examples, and a tutorial, all designed to help you master Shiny.
- Links to the preview sites for R Markdown, an easy option for writing reproducible reports with R, and ggvis, an R package that creates interactive plots with the grammar of graphics.
- Links to books that we have written (or are writing) about R and its tools.
Why are we so excited about training? We think that learning R and Shiny is the best investment that a data user can make. These two free tools can streamline how you analyze data and deliver results. Browse through the links at www.rstudio.com/training and see for yourself.
devtools 1.5 is now available on CRAN. It includes four new functions to make it easier to add useful infrastructure to packages:
add_test_infrastructure()will create testthat infrastructure when needed.
add_rstudio_project()adds an Rstudio project file to your package.
add_travis()adds a basic template for travis-ci.
add_build_ignore()makes it easy to add files to
escaping special characters as needed.
We’ve also bumped two dependencies: devtools now requires R 3.0.2 and roxygen2 3.0.0. We’ve also included many minor improvements and bug fixes, particularly for package installation. For example
install_github() now prefers the safer github personal access token, and does a better job of installing the dependencies that you actually need. We also provide versions of
system.file() that work with all packages, regardless of how they’re loaded. See a complete list of changes in the full release notes.
Please join us for our popular Introduction to R course for data scientists and data analysts in San Francisco on April 28 and 29. This is a two-day workshop, designed to provide a comprehensive introduction to R that will have you analyzing and modeling data with R in no time. We will cover practical skills for visualizing, transforming, and modeling data in R. You will learn how to explore and understand data as well as how to build linear and non-linear models in R.
The course will be led by RStudio Master Instructor and author Dr. Garrett Grolemund.
We offer introductory R training only a few times a year. The Boston course in January sold out quickly. Space is limited. We encourage you to register (rstudio-sfbay.eventbrite.com) as soon as you can.
“The instructor was amazing. He knew so much and could answer any questions. His expertise was obvious and he was also very clear about how to explain it to a varied audience.” – Workshop Student, January 2014
“Very well organized and at a good pace. The example datasets were very helpful. Excellent teachers!” – Workshop Student, January 2014