Dave Rosenman
Dave Rosenman

Reputation: 1467

Synchronizing Dependent selectInputs in Shiny for Accurate Data Table Display

I have a Shiny app with two dependent selectInputs: input$name (corresponding to the Name field in the data) and input$date (corresponding to the Contract_Start_Date field in the data). The input$date options are dynamically updated based on the selected input$name, and I need the data table output to always reflect the correct data based on synchronized selections from both selectInputs. The challenge is ensuring the data table isn’t generated based on an outdated input$date before it is updated after input$name changes.

To ensure synchronization between input$name and input$date, I used the following approach:

Is this a correct approach to solve the synchronization problem? Is there a better way to do this?

I've tried several approaches to this and they all seem to work fine (one involving invalidateLater, one involving freezeReactiveValue, and several over approaches). No noticeable issues when actually using the app... And this is even with approaches I know are wrong that could lead to data synchronization issues and input$date being used to generate the data table output before being invalidated once input$name changes. On potential issue with my approach below is potential overlaps in date options. What if you change the value of input$name and the new name has dates that overlap with the previous name?

Anyways thanks in advance for any help on this.

library(shiny)
library(dplyr)
library(lubridate)

data <- structure(list(Name = c("A", "A", "A", "A", "A", "A", "A", "A", 
                                "A", "B", "B", "B", "B", "B", "B", "B", "B", "B"), 
                       Contract_Start_Date = structure(c(18993, 18993, 18993, 19754, 
                                                         19754, 19754, 20089, 20089, 20089, 18993, 
                                                         18993, 18993, 19358, 19358, 19358, 20544, 20544, 20544), 
                                                       class = "Date"), 
                       Line_of_Business = c("L1", "L2", "L3", "L1", "L2", 
                                            "L3", "L1", "L2", "L3", "L1", "L2", "L3", 
                                            "L1", "L2", "L3", "L1", "L2", "L3"), 
                       Members = c(589L, 342L, 235L, 100L, 212L, 
                                   235L, 335L, 456L, 567L, 687L, 982L, 123L, 145L, 167L, 231L, 
                                   234L, 1234L, 999L)), row.names = c(NA, -18L), 
                  class = c("tbl_df", "tbl", "data.frame"))
lookup <- structure(list(Name = c("A", "A", "A", "B", "B", "B"), Contract_Start_Date = structure(c(18993, 
                                                                                                   19754, 20089, 18993, 19358, 20544), class = "Date"), Salesforce_ID = c("A1", 
                                                                                                                                                                          "A2", "A3", "B1", "B2", "B3")), class = c("tbl_df", "tbl", "data.frame"
                                                                                                                                                                          ), row.names = c(NA, -6L))                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             


ui <- fluidPage(
  titlePanel("Example App"),
  sidebarLayout(
    sidebarPanel(
      selectInput("name", "Select Name:", choices = sort(unique(lookup$Name))),
      selectInput("date", "Select Contract Start Date:", choices = NULL)
    ),
    mainPanel(
      dataTableOutput("dataOutput")
    )
  )
)

server <- function(input, output, session) {
  # Reactive values to store synchronized inputs and state
  rv <- reactiveValues(name = NULL, date = NULL)
  
  # Reactive expression for date choices based on selected Name
  date_choices <- reactive({
    req(input$name)
    lookup %>%
      filter(Name == input$name) %>%
      pull(Contract_Start_Date)
  })
  
  # Update date based on reactive expression for dates
  observeEvent(input$name, {
    dates <- date_choices()
    updateSelectInput(session, "date", choices = dates, selected = dates[1])  # Update input$date with new valid choices
  })
  
  # Observe and update reactive values
  observe({
    req(input$name, input$date)
    
    valid_dates <- date_choices()
    if (as.character(input$date) %in% as.character(valid_dates)) {
      rv$name <- input$name
      rv$date <- input$date
    }
  })
  
  # Reactive expression to filter the data based on synchronized inputs
  filtered_data <- reactive({
    req(rv$name, rv$date)
    cat("ran\n") # should just print 'ran' once each time name or date is updated by user
    data %>%
      filter(Name == rv$name, Contract_Start_Date == as.Date(rv$date))
  })
  
  # Render the filtered data as a table
  output$dataOutput <- renderDataTable({
    req(filtered_data())  # Ensure filtered_data is valid before rendering
    filtered_data()
  })
}

shinyApp(ui = ui, server = server)

Upvotes: 0

Views: 58

Answers (1)

Bryce Chamberlain
Bryce Chamberlain

Reputation: 535

Here is how I would approach this:

  • Set up some default options so the first reactivity loop doesn't trigger, and the table loads initially with data.
  • Use some CSS to hide the DT spinner/loader, it creates screen flashing.
  • Update the table data instead of creating a whole new table.
  • I don't think the reactiveValues are necessary, I think shiny will keep things synced just using inputs.
  • Add some code to only update the selection if the current selection is no longer valuable. This way we minimize the reactivity triggered by date.

Hopefully it'll work for you!

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

data <- structure(list(Name = c("A", "A", "A", "A", "A", "A", "A", "A", 
                                "A", "B", "B", "B", "B", "B", "B", "B", "B", "B"), 
                       Contract_Start_Date = structure(c(18993, 18993, 18993, 19754, 
                                                         19754, 19754, 20089, 20089, 20089, 18993, 
                                                         18993, 18993, 19358, 19358, 19358, 20544, 20544, 20544), 
                                                       class = "Date"), 
                       Line_of_Business = c("L1", "L2", "L3", "L1", "L2", 
                                            "L3", "L1", "L2", "L3", "L1", "L2", "L3", 
                                            "L1", "L2", "L3", "L1", "L2", "L3"), 
                       Members = c(589L, 342L, 235L, 100L, 212L, 
                                   235L, 335L, 456L, 567L, 687L, 982L, 123L, 145L, 167L, 231L, 
                                   234L, 1234L, 999L)), row.names = c(NA, -18L), 
                  class = c("tbl_df", "tbl", "data.frame"))
lookup <- structure(list(Name = c("A", "A", "A", "B", "B", "B"), Contract_Start_Date = structure(c(18993, 
                                                                                                   19754, 20089, 18993, 19358, 20544), class = "Date"), Salesforce_ID = c("A1", 
                                                                                                                                                                          "A2", "A3", "B1", "B2", "B3")), class = c("tbl_df", "tbl", "data.frame"
                                                                                                                                                                          ), row.names = c(NA, -6L))                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             


# set initial options.
options = list(name = sort(unique(lookup$Name)))
options$date = lookup %>%
  filter(Name == options$name[1]) %>%
  pull(Contract_Start_Date)

ui <- fluidPage(
  titlePanel("Example App"),
  # hide spinner which causes screen flashing. 
  tags$style(HTML("
        .dataTables_processing {
          visibility: hidden !important;
        }
  ")),
  sidebarLayout(
    sidebarPanel(
      selectInput(
        "name", 
        "Select Name:", 
        choices = options$name
      ),
      selectInput(
        "date", 
        "Select Contract Start Date:", 
        choices = options$date
      )
    ),
    mainPanel(
      dataTableOutput("dataOutput")
    )
  )
)

server <- function(input, output, session) {
  
  # observer to manage date options.
  observe({
    
    # get new options.
    new_options = lookup %>%
      filter(Name == input$name) %>%
      pull(Contract_Start_Date)
    
    # if the options have changed, update the input.
    if(length(new_options) != length(options$date) || any(new_options != options$date)){
      # if the current selection is no longer an option, we'll select a new choice.
      # otherwise, just update the options. 
      if(!(isolate(input$date) %in% new_options)){
        # this will trigger reactivity (a table update).
        updateSelectizeInput('data', choices = new_options, selected = new_options[1])
      } else {
        # this should not trigger reactivity, because the selection did not change. 
        updateSelectizeInput(session = session, inputId = 'data', choices = new_options)
      }
      options$date <<- new_options # update global options object. 
    }
    
  })
  
  # Reactive expression to filter the data based on synchronized inputs
  filtered_data <- reactive({
    req(input$name, input$date)
    cat("ran\n") # should just print 'ran' once each time name or date is updated by user
    data %>%
      filter(Name == input$name, Contract_Start_Date == as.Date(input$date))
  })
  
  # Render the filtered data as a table
  output$dataOutput <- DT::renderDT({
    req(isolate(filtered_data()))  # Ensure filtered_data is valid before rendering
    isolate(filtered_data()) # we'll update data using the observer below for a smoother UX.
  })
  
  # Update the data table as data changes.
  observeEvent(filtered_data(), {
    DT::replaceData(dataTableProxy('dataOutput'), filtered_data())
  })
  
}

shinyApp(ui = ui, server = server)

Upvotes: 0

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