You are currently browsing the monthly archive for November 2013.
We’re very pleased to announce the release of devtools 1.4. This version brings many improvements to package installation, including automated vignette building, and a better way of referring to repos on github,
install_github("hadley/devtools"). There are also many other bug fixes and minor improvements; to see them all, please read the release notes file on github.
We’re very pleased to announce Shiny 0.8.0 (which actually went up on CRAN about two weeks ago). This release features a vastly better way to display tabular data, and new debugging tools that make it much easier to fix errors in your app.
We now support much more attractive and powerful displays of tabular data using the popular DataTables library. Our DataTables integration features pagination, searching/filtering, sorting, and more. Check out this demo to see it in action, and learn more about how to use it in your own apps by visiting the tutorial’s chapter on DataTables.
In version 0.8.0 of the Shiny package, we’ve greatly improved the set of debugging tools you can use with your Shiny apps. It’s now much easier to figure out what’s happening when things go wrong, thanks to two new features:
- Integration with the new visual debugger that’s available with RStudio v0.98. You can set breakpoints and step through your code much more easily than before.
- A new option ‘shiny.error’ which can take a function as an error handler. It is called when an error occurs in a reactive observer (e.g. when running an output rendering function). You can use options(shiny.error=traceback) to simply print a traceback, options(shiny.error=recover) for debugging from a regular R console, or options(shiny.error=browser) to jump into the RStudio visual debugger.
There have also been a few smaller tweaks and bug fixes. For the full list, you can take a look at our NEWS file.
Welcome, Yihui Xie!
If you’re reading this, there’s a good chance you have heard of Yihui Xie or have used his software; during his time as a PhD student at Iowa State University, he created the knitr, cranvas, and animation packages, among others.
We’re thrilled to announce that Yihui has joined the RStudio team! He will be one of the primary maintainers of the Shiny package and has already contributed some great improvements in the short time he has been with us.
We’re excited to announce Packrat, a new tool for managing the packages your R project depends on.
If you’ve ever been frustrated by package dependencies, whether juggling the packages needed by your own projects or getting someone else’s project to work, Packrat is for you. Similar in spirit to Bundler, Packrat understands package dependencies and manages them inside a private, project-specific library.
Packrat makes your project more isolated, portable, and reproducible. Because your project’s package dependencies travel with it, you control the environment in which your code runs. Your results are easy to duplicate on other machines, whether your own or your collaborators’.
We built Packrat to help us create self-sufficient R projects for deployment, but we think it has many other use cases. Lots more information, including installation instructions, can be found at the Packrat project page:
If you try it, we’d love to get your feedback. Leave a comment here or post in the packrat-discuss Google group.
When OS X Mavericks was released last month we were very disappointed to discover a compatibility issue between Qt (our cross-platform user interface toolkit) and OS X Mavericks that resulted in extremely poor graphics performance.
We now have an updated preview version of RStudio for OS X (v0.98.475) that not only overcomes these issues, but also improves editor, scrolling, and layout performance across the board on OS X (more details below if you are curious):
We were initially optimistic that we could patch Qt to overcome the problems but even with some help from Digia (the organization behind Qt) we never got acceptable performance. Running out of viable options based on Qt, we decided to bypass Qt entirely by implementing the RStudio desktop frame as a native Cocoa application.
OS X Mavericks issues aside, we are thrilled with the result of using Cocoa rather than a cross-platform toolkit. RStudio desktop uses WebKit to render its user-interface, and the Cocoa WebKit Framework is substantially faster than the one in Qt.
Please try out the updated preview and let us know if you encounter any issues or problems on our support forum. For those that prefer to wait for the final release of v0.98 we expect that to happen sometime during the next couple of weeks.