# Pipelines in shiny apps

Pipelines can be used as part of Shiny widgets or apps. In the following example, we define a simple pipeline which generates a chart, and use that to power a shiny widget.

In this example, we emulate streaming dataset using the shiny::reactivePoll function and randomly sampling from an existing sample dataset in the package.

  data("iris")
shinyPipeline <- AnalysisPipeline()
shinyPipeline %>>% setLoggerDetails(target = "none")
shinyPipeline %>>% univarCatDistPlots(uniCol = "Species", priColor = "blue", optionalPlots = 0, storeOutput = T) ->   shinyPipeline

We then use the pipeline within the shiny::renderPlot function, and set the sampled data to execute the pipeline, and generate the chart. Since the data keeps changing due to our reactive poll, the expression within the shiny::renderPlot function keeps getting called in the reactive context.

  sampled_data <- shiny::reactivePoll(intervalMillis = 2000,
session = NULL,
checkFunc = function() return(base::sample(1:100, 1)),
valueFunc = function() return(iris[sample(1:nrow(iris), 100),]))
  shiny::renderPlot(height = 400, {
sampled_data <- sampled_data()
shinyPipeline %>>% setInput(input = sampled_data) -> shinyPipeline
shinyPipeline %>>% generateOutput %>>% getOutputById("1")
})