---
title: "Report Previewer"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Report Previewer}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

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.

1. Create a `tabsetPanel` within main app with the previewer.
2. Integrate the UI components of the modules into the app's UI.
3. Initialize reporter instance.
4. 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.*
5. 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:

```{r message = FALSE}
library(shiny)
library(teal.reporter)
library(ggplot2)
library(rtables)
library(DT)
library(bslib)
```

A basic `shiny` app with the previewer module:

```{r}
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)
```
