Missing reactive dependency in shiny app stopping data from updating with input

[Athomaswood]

I am trying to write a shiny app that will let the user;

1. Load some data in,
2. Select a specific row based off an ID,
3. Edit the data in a datatable, and
4. Export the edited data

As it is, the app does all of these things, but does not allow the user to change the ID and select a new row without restarting the app. The data in the table stays the same and doesn't update the ID input is changed or when the action button is pressed.

I think the issue is that I am missing a reactive dependency somewhere, but I am not sure where it is.

library(shiny)
library(DT)
library(dplyr)

editTableUI <- function(id, width = NULL) {
  ns <- NS(id)
  tagList(fluidRow(DT::dataTableOutput(ns('data_table'), width = width)))
}

editTableServer <-
  function(input, output, session, data) {
    
    output$data_table = DT::renderDataTable(
      data,
      selection = 'none',
      editable = TRUE,
      options = list(dom = 't', pageLength = nrow(data)))
    
    proxy = DT::dataTableProxy('data_table')
    
    observeEvent(input$data_table_cell_edit, {
      info = input$data_table_cell_edit
      str(info)
      i = info$row
      j = info$col
      v = info$value
      
      data[i, j] <<- coerceValue(v, data[i, j])
      replaceData(proxy, data, resetPaging = FALSE)})

    return({reactive(data)})
  }



#  ------------------------------------------------------------------------

ui <- fluidPage(
  uiOutput("id"),
  conditionalPanel(condition = "input.id",
                   actionButton(inputId = "go_id", label = "Load ID Data")),
  editTableUI("table"),
  downloadButton('download_CSV', 'Download CSV'))


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

# Load data ---------------------------------------------------------------

  df <- reactive({iris %>% mutate(id = rownames(iris))})
  
  # create list of IDs
  output$id <- renderUI({
    id_list <- df() %>% pull(id)
    selectInput("id", "Select an ID", choices = id_list, multiple = F)})
  
  # filter total data to data for selected ID
  id_df <- eventReactive(input$go_id, {df() %>% filter(id == input$id)})
  
  # select variables and gather
  display_df <- eventReactive(input$go_id,{
    id_df() %>% 
      select(-Species) %>% 
      tidyr::gather(key = "Variable Label", value = "Original") %>%
      dplyr::mutate(Update = as.numeric(Original))})
  
  editdata <- callModule(editTableServer, "table", data = display_df())
  
  
  output$download_CSV <- downloadHandler(
    filename = function() {paste("dataset-", Sys.Date(), ".csv", sep = "")},
    content = function(file) {write.csv(editdata(), file, row.names = F)})
             
}

shinyApp(ui, server)

[michaelbgarcia]

Hey there, the key is making sure that the reactive you are passing to the module is actually a reactive, not the data frame itself. See the data parameter inside the callModule function. Then, within the module, access that data frame object with the same syntax you would a reactive, i.e. data() and not data. Therefore, making those two small modifications, this app seems to work for me.

library(shiny)
library(DT)
#> 
#> Attaching package: 'DT'
#> The following objects are masked from 'package:shiny':
#> 
#>     dataTableOutput, renderDataTable
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

editTableUI <- function(id, width = NULL) {
  ns <- NS(id)
  tagList(fluidRow(DT::dataTableOutput(ns('data_table'), width = width)))
}

editTableServer <-
  function(input, output, session, data) {
    
    output$data_table = DT::renderDataTable(
      data(),
      selection = 'none',
      editable = TRUE,
      options = list(dom = 't', pageLength = nrow(data())))
    
    proxy = DT::dataTableProxy('data_table')
    
    observeEvent(input$data_table_cell_edit, {
      info = input$data_table_cell_edit
      str(info)
      i = info$row
      j = info$col
      v = info$value
      
      data()[i, j] <<- coerceValue(v, data()[i, j])
      replaceData(proxy, data(), resetPaging = FALSE)})
    
    return({reactive(data())})
  }



#  ------------------------------------------------------------------------

ui <- fluidPage(
  uiOutput("id"),
  conditionalPanel(condition = "input.id",
                   actionButton(inputId = "go_id", label = "Load ID Data")),
  editTableUI("table"),
  downloadButton('download_CSV', 'Download CSV'))


server <- function(input, output, session) {
  
  # Load data ---------------------------------------------------------------
  
  df <- reactive({iris %>% mutate(id = rownames(iris))})
  
  # create list of IDs
  output$id <- renderUI({
    id_list <- df() %>% pull(id)
    selectInput("id", "Select an ID", choices = id_list, multiple = F)})
  
  # filter total data to data for selected ID
  id_df <- eventReactive(input$go_id, {df() %>% filter(id == input$id)})
  
  # select variables and gather
  display_df <- eventReactive(input$go_id,{
    id_df() %>% 
      select(-Species) %>% 
      tidyr::gather(key = "Variable Label", value = "Original") %>%
      dplyr::mutate(Update = as.numeric(Original))})
  
  editdata <- callModule(editTableServer, "table", data = display_df)
  
  
  output$download_CSV <- downloadHandler(
    filename = function() {paste("dataset-", Sys.Date(), ".csv", sep = "")},
    content = function(file) {write.csv(editdata(), file, row.names = F)})
  
}

shinyApp(ui, server)

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^{Created on 2020-10-06 by the reprex package (v0.3.0)}