manual-spinner {shinybusy}

Manual busy indicator (spinner)

Description

Declare use_busy_spinner in your UI and show/hide server-side with show_spinner/hide_spinner.

Usage

use_busy_spinner(
  spin = "double-bounce",
  color = "#112446",
  position = c("top-right", "top-left", "bottom-right", "bottom-left", "full-page"),
  margins = c(10, 10),
  spin_id = NULL,
  height = "50px",
  width = "50px"
)

show_spinner(spin_id = NULL, session = shiny::getDefaultReactiveDomain())

hide_spinner(spin_id = NULL, session = shiny::getDefaultReactiveDomain())

Arguments

spin

Style of the spinner, see spin_epic or spin_kit for possible choices. Note that for spin_epic, height and width are ignored.

color

Color for the spinner, in a valid CSS format.

position

Where to display the spinner: 'top-right', 'top-left', 'bottom-right', 'bottom-left', 'full-page'.

margins

Distance from margins, a vector of length two, where first element is distance from top/bottom, second element distance from right/left.

spin_id

An explicit id for the spinner, useful if you want to use multiple spinners.

height, width

Height and width of the spinner, default to '50px' for both, must be specified.

session

Shiny session.

Examples

if (interactive()) {
  library(shiny)
  library(shinybusy)

  ui <- fluidPage(

    # Use this function somewhere in UI
    use_busy_spinner(spin = "fading-circle"),

    headerPanel('Iris k-means clustering'),

    sidebarLayout(
      sidebarPanel(
        selectInput('xcol', 'X Variable', names(iris)),
        selectInput('ycol', 'Y Variable', names(iris),
                    selected=names(iris)[[2]]),
        numericInput('clusters', 'Cluster count', 3,
                     min = 1, max = 9),
        actionButton("sleep", "Long calculation")
      ),
      mainPanel(
        plotOutput('plot1')
      )
    )
  )

  server <- function(input, output, session) {

    selectedData <- reactive({
      iris[, c(input$xcol, input$ycol)]
    })

    clusters <- reactive({
      kmeans(selectedData(), input$clusters)
    })

    output$plot1 <- renderPlot({
      palette(c("#E41A1C", "#377EB8", "#4DAF4A", "#984EA3",
                "#FF7F00", "#FFFF33", "#A65628", "#F781BF",
                "#999999"))

      par(mar = c(5.1, 4.1, 0, 1))
      plot(selectedData(),
           col = clusters()$cluster,
           pch = 20, cex = 3)
      points(clusters()$centers, pch = 4, cex = 4, lwd = 4)
    })

    observeEvent(input$sleep, {
      show_spinner()
      Sys.sleep(5)
      hide_spinner()
    })

  }

  shinyApp(ui, server)
}