Report Previewer • teal.reporter

The Report previewer is an advanced shiny module designed for visualization, editing, and downloading of report cards. It extended the base modules introduced in the simpleReporter vignette, enhancing interactivity and user engagement with report content.

The five essential steps for implementing the report previewer include integrating it within a shiny application. Key code segments are highlighted in ### REPORTER code blocks.

Create a tabsetPanel within main app with the previewer.
Integrate the UI components of the modules into the app’s UI.
Initialize reporter instance.
Create the report card function with two optional arguments: card and comment. This function must return a ReportCard object. The ReportCard object should be built step by step, assuming that it is empty at the beginning.
- If the comment argument is provided, it should be added to the card. If not, it should be added automatically at the end of the card.
- If the card argument is provided, the ReportCard instance should be automatically created for the user. If not, the function should create the card itself. Please note that the document page’s design is up to the developer’s imagination.
Invoke the servers with the Reporter instance and the function to create the ReportCard instance.

The code added to introduce the reporter is wrapped in the ### REPORTER code blocks.

First, load the required packages:

library(shiny)
library(teal.reporter)
library(ggplot2)
library(rtables)
library(DT)
library(bslib)

A basic shiny app with the previewer module:

ui <- fluidPage(
  # please, specify specific bootstrap version and theme
  theme = bs_theme(version = "4"),
  titlePanel(""),
  tabsetPanel(
    tabPanel(
      "main App",
      tags$br(),
      sidebarLayout(
        sidebarPanel(
          uiOutput("encoding")
        ),
        mainPanel(
          tabsetPanel(
            id = "tabs",
            tabPanel("Plot", plotOutput("dist_plot")),
            tabPanel("Table", verbatimTextOutput("table")),
            tabPanel("Table DataFrame", verbatimTextOutput("table2")),
            tabPanel("Table DataTable", dataTableOutput("table3"))
          )
        )
      )
    ),
    ### REPORTER
    tabPanel(
      "Previewer",
      reporter_previewer_ui("prev")
    )
    ###
  )
)
server <- function(input, output, session) {
  output$encoding <- renderUI({
    tagList(
      ### REPORTER
      simple_reporter_ui("simple_reporter"),
      ###
      if (input$tabs == "Plot") {
        sliderInput(
          "binwidth",
          "binwidth",
          min = 2,
          max = 10,
          value = 8
        )
      } else if (input$tabs %in% c("Table", "Table DataFrame", "Table DataTable")) {
        selectInput(
          "stat",
          label = "Statistic",
          choices = c("mean", "median", "sd"),
          "mean"
        )
      } else {
        NULL
      }
    )
  })
  plot <- reactive({
    req(input$binwidth)
    x <- mtcars$mpg
    ggplot(data = mtcars, aes(x = mpg)) +
      geom_histogram(binwidth = input$binwidth)
  })
  output$dist_plot <- renderPlot(plot())

  table <- reactive({
    req(input$stat)
    lyt <- basic_table() %>%
      split_rows_by("Month", label_pos = "visible") %>%
      analyze("Ozone", afun = eval(str2expression(input$stat)))
    build_table(lyt, airquality)
  })
  output$table <- renderPrint(table())

  table2 <- reactive({
    req(input$stat)
    data <- aggregate(
      airquality[, c("Ozone"), drop = FALSE], list(Month = airquality$Month), get(input$stat),
      na.rm = TRUE
    )
    colnames(data) <- c("Month", input$stat)
    data
  })
  output$table2 <- renderPrint(print.data.frame(table2()))
  output$table3 <- renderDataTable(table2())

  ### REPORTER
  reporter <- Reporter$new()
  card_fun <- function(card = ReportCard$new(), comment) {
    if (input$tabs == "Plot") {
      card$set_name("Plot Module")
      card$append_text("My plot", "header2")
      card$append_plot(plot())
      card$append_rcode(
        paste(
          c(
            "x <- mtcars$mpg",
            "ggplot2::ggplot(data = mtcars, ggplot2::aes(x = mpg)) +",
            paste0("ggplot2::geom_histogram(binwidth = ", input$binwidth, ")")
          ),
          collapse = "\n"
        ),
        echo = TRUE,
        eval = FALSE
      )
    } else if (input$tabs == "Table") {
      card$set_name("Table Module rtables")
      card$append_text("My rtables", "header2")
      card$append_table(table())
      card$append_rcode(
        paste(
          c(
            "lyt <- rtables::basic_table() %>%",
            'rtables::split_rows_by("Month", label_pos = "visible") %>%',
            paste0('rtables::analyze("Ozone", afun = ', input$stat, ")"),
            "rtables::build_table(lyt, airquality)"
          ),
          collapse = "\n"
        ),
        echo = TRUE,
        eval = FALSE
      )
    } else if (input$tabs %in% c("Table DataFrame", "Table DataTable")) {
      card$set_name("Table Module DF")
      card$append_text("My Table DF", "header2")
      card$append_table(table2())
      # Here r code added as a regular verbatim text
      card$append_text(
        paste0(
          c(
            'data <- aggregate(airquality[, c("Ozone"), drop = FALSE], list(Month = airquality$Month), ',
            input$stat,
            ", na.rm = TRUE)\n",
            'colnames(data) <- c("Month", ', paste0('"', input$stat, '"'), ")\n",
            "data"
          ),
          collapse = ""
        ), "verbatim"
      )
    }
    if (!comment == "") {
      card$append_text("Comment", "header3")
      card$append_text(comment)
    }
    card
  }
  simple_reporter_srv("simple_reporter", reporter = reporter, card_fun = card_fun)
  reporter_previewer_srv("prev", reporter)
  ###
}

if (interactive()) shinyApp(ui = ui, server = server)