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119 lines
4.1 KiB
Markdown
119 lines
4.1 KiB
Markdown
## Isolation: avoiding dependency
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Sometimes it's useful for an observer/endpoint to access a reactive value or expression, but not to take a dependency on it. For example, if the observer performs a long calculation or downloads large data set, you might want it to execute only when a button is clicked.
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For this, we'll use `actionButton` from the `shinyIncubator` package. If you want try this code yourself, you'll have to install the package from Github, using devtools:
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{% highlight r %}
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install.packages('devtools')
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devtools::install_github('shiny-incubator', 'rstudio')
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{% endhighlight %}
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We'll define a `ui.R` that is a slight modification of the one from 01_hello -- the only difference is that it has an actionButton labeled "Go!". You can see it in action at [http://glimmer.rstudio.com/winston/actionbutton/](http://glimmer.rstudio.com/winston/actionbutton/).
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The actionButton includes some JavaScript code that sends numbers to the server. When the web browser first connects, it sends a value of 0, and on each click, it sends an incremented value: 1, 2, 3, and so on.
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{% highlight r %}
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library(shinyIncubator)
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shinyUI(pageWithSidebar(
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headerPanel("Click the button"),
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sidebarPanel(
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sliderInput("obs", "Number of observations:",
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min = 0, max = 1000, value = 500),
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actionButton("goButton", "Go!")
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),
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mainPanel(
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plotOutput("distPlot")
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)
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))
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{% endhighlight %}
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In our `server.R`, there are two changes to note. First, `output$distPlot` will take a dependency on `input$goButton`, simply by accessing it. When the button is clicked, the value of `input$goButton` increases, and so `output$distPlot` re-executes.
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The second change is that the access to `input$obs` is wrapped with `isolate()`. This function takes an R expression, and it tells Shiny that the calling observer or reactive expression should not take a dependency on any reactive objects inside the expression.
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{% highlight r %}
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shinyServer(function(input, output) {
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output$distPlot <- renderPlot({
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# Take a dependency on input$goButton
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input$goButton
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# Use isolate() to avoid dependency on input$obs
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dist <- isolate(rnorm(input$obs))
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hist(dist)
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})
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})
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{% endhighlight %}
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The resulting graph looks like this:
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And here's a walkthrough of the process when `input$obs` is set to 1000, and then the Go button is clicked:
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In the `actionButton` example, you might want to prevent it from returning a plot the first time, before the button has been clicked. Since the starting value of an `actionButton` is zero, this can be accomplished with the following:
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{% highlight r %}
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output$distPlot <- renderPlot({
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if (input$goButton == 0)
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return()
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# plot-making code here
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})
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{% endhighlight %}
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Reactive values are not the only things that can be isolated; reactive expressions can also be put inside an `isolate()`. Building off the Fibonacci example from above, this would calculate the _n_th value only when the button is clicked:
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{% highlight r %}
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output$nthValue <- renderText({
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if (input$goButton == 0)
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return()
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isolate({ fib(as.numeric(input$n)) })
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})
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{% endhighlight %}
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It's also possible to put multiple lines of code in `isolate()`. For example here are some blocks of code that have equivalent effect:
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{% highlight r %}
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# Separate calls to isolate -------------------------------
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x <- isolate({ input$xSlider }) + 100
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y <- isolate({ input$ySlider }) * 2
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z <- x/y
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# Single call to isolate ----------------------------------
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isolate({
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x <- input$xSlider + 100
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y <- input$ySlider * 2
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z <- x/y
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})
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# Single call to isolate, use return value ----------------
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z <- isolate({
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x <- input$xSlider + 100
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y <- input$ySlider * 2
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x/y
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})
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{% endhighlight %}
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In all of these cases, the calling function won't take a reactive dependency on either of the `input` variables.
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