For this vignette, we’ll use the Gaussian Processes example notebook provided in the package:
notebook <- reactor_example("gaussian_processes.Rmd")
If you’d like to start from scratch with a new notebook, you can run:
Now that we have a notebook, we need to export it as a Shiny application. The
export_shiny function takes a notebook and creates two files in a given directory:
notebook.Rmd, which contains the Reactor notebook, and
app.R, which launches the notebook as a Shiny application. Create a folder, here we call it
app, and then run:
The newly created file
./app/app.R contains the following:
# shinyApp library(shiny) library(reactor) notebook <- ReactorNotebook$load('notebook.Rmd') start_reactor_as_shiny(notebook)
If you open
app.R in RStudio, it will recognize it as a Shiny application and the
Run App button will appear above the editor. You can deploy the application to
shinyapps.io using the built-in tools from RStudio.
Alternatively, you can deploy the application directly from R using the
rsconnect package. The package’s “Getting Started” vignette describes how to do so in detail; we summarize the steps in this vignette as well.
First, load the
rsconnect package and set the account name, token, and secret, which can be found on the Profile / Tokens page of your shinyapps.io account.
Next, deploy the application using the
deployApp function, supplying an application name:
deployApp(appDir = "app", appName = "gaussian_processes")
Once the deployment is complete, the notebook will be available as an online Shiny application. The example notebook used here can be found at https://hsusmann.shinyapps.io/gaussian_processes/.