Reactivity 101

Case Studies: Building Web Applications with Shiny in R

Dean Attali

Shiny Consultant

Reactivity basics

Shiny uses reactive programming
Outputs react to changes in input
When value of variable x changes, anything that relies on x is re-evaluated
Contrast with regular R:
```
x <- 5
y <- x + 1
x <- 10
```
What is the value of y? 6 or 11?

Reactive variables

All inputs are reactive
input$<inputId> inside render function will cause output to re-render
```
output$my_plot <- renderPlot({
    plot(rnorm( input$num ))
})
```
output$my_plot depends on input$num
- input$num changes ⇒
  
  output$my_plot reacts

Reactive contexts

Reactive values can only be used inside reactive contexts
Any render*() function is a reactive context
Accessing reactive value outside of reactive context ⇒ error

server <- function(input, output) { 
    print(input$num)
}

ERROR: Operation not allowed without an active reactive context.

Observe a reactive variable

observe({ ... }) to access reactive variable

server <- function(input, output) { 
    observe({ 
        print( input$num )  
    }) 
}

Useful for debugging, track reactive variable
Each reactive variable creates a dependency

observe({ 
    print( input$num1 ) 
    print( input$num2 )
})

Create a reactive variable

reactive({ ... }) to create reactive variable

Wrong:

server <- function(input, output) {
    x <- input$num + 1
}

ERROR: Operation not allowed without an active reactive context.

Correct:

server <- function(input, output) { 
  x <- reactive({ 
      input$num + 1 
  })
}

Reactive variables

Access custom reactive variable like a function:
- add parentheses ()

server <- function(input, output){
    x <- reactive({
        input$num + 1
    }) 
    observe({ 
        print( input$num )
        print( x() ) 
    })
}

Let's practice!

Case Studies: Building Web Applications with Shiny in R