How to organize large Shiny apps?

Question

What are the best practices to organize larger Shiny applications?
I think best R practices are also applicable to Shiny.
Best R practices are discussed here: How to organize large R programs
Link to Google's R Style Guide: Style Guide

But what are the unique tips and tricks in Shiny context which I can adopt to make my Shiny code look better (and more readable)? I am thinking of things like:

• Exploiting object oriented programming in Shiny
• In server.R which parts should be sourced?
• File hierarchy of project containing markdown documents, pictures, xml and source files

For example if I am using navbarPage and tabsetPanel in every tabPanel my code is starting to look quite messy after addition of several UI elements.

Example code:

server <- function(input, output) {   #Here functions and outputs..  }  ui <- shinyUI(navbarPage("My Application",   tabPanel("Component 1",              sidebarLayout(                 sidebarPanel(                     # UI elements..                 ),                 mainPanel(                     tabsetPanel(                         tabPanel("Plot", plotOutput("plot")                                  # More UI elements..                                  ),                          tabPanel("Summary", verbatimTextOutput("summary")                                  # And some more...                                  ),                          tabPanel("Table", tableOutput("table")                                  # And...                                  )                     )                 )     )              ),   tabPanel("Component 2"),   tabPanel("Component 3") ))  shinyApp(ui = ui, server = server) 

For organizing ui.R code I found quite nice solution from GitHub: radiant code
Solution is to use renderUI to render every tabPanel and in server.R tabs are sourced to different files.

server <- function(input, output) {    # This part can be in different source file for example component1.R   ###################################   output$component1 <- renderUI({         sidebarLayout(                 sidebarPanel(                 ),                 mainPanel(                     tabsetPanel(                         tabPanel("Plot", plotOutput("plot")),                          tabPanel("Summary", verbatimTextOutput("summary")),                          tabPanel("Table", tableOutput("table"))                     )                 )     )   })  #####################################    } ui <- shinyUI(navbarPage("My Application",   tabPanel("Component 1", uiOutput("component1")),   tabPanel("Component 2"),   tabPanel("Component 3") ))  shinyApp(ui = ui, server = server) 

Answer 1

After addition of modules to R shiny. Managing of complex structures in shiny applications has become a lot easier.

Detailed description of shiny modules:Here

Advantages of using modules:

• Once created, they are easily reused
• ID collisions is easier to avoid
• Code organization based on inputs and output of modules

In tab based shiny app, one tab can be considered as one module which has inputs and outputs. Outputs of tabs can be then passed to other tabs as inputs.

Single-file app for tab-based structure which exploits modular thinking. App can be tested by using cars dataset. Parts of the code where copied from the Joe Cheng(first link). All comments are welcome.

# Tab module # This module creates new tab which renders dataTable  dataTabUI <- function(id, input, output) {   # Create a namespace function using the provided id   ns <- NS(id)    tagList(sidebarLayout(sidebarPanel(input),                          mainPanel(dataTableOutput(output))))  }  # Tab module # This module creates new tab which renders plot plotTabUI <- function(id, input, output) {   # Create a namespace function using the provided id   ns <- NS(id)    tagList(sidebarLayout(sidebarPanel(input),                          mainPanel(plotOutput(output))))  }  dataTab <- function(input, output, session) {   # do nothing...   # Should there be some logic?   }  # File input module # This module takes as input csv file and outputs dataframe # Module UI function csvFileInput <- function(id, label = "CSV file") {   # Create a namespace function using the provided id   ns <- NS(id)    tagList(     fileInput(ns("file"), label),     checkboxInput(ns("heading"), "Has heading"),     selectInput(       ns("quote"),       "Quote",       c(         "None" = "",         "Double quote" = "\"",         "Single quote" = "'"       )     )   ) }  # Module server function csvFile <- function(input, output, session, stringsAsFactors) {   # The selected file, if any   userFile <- reactive({     # If no file is selected, don't do anything     validate(need(input$file, message = FALSE))     input$file   })    # The user's data, parsed into a data frame   dataframe <- reactive({     read.csv(       userFile()$datapath,       header = input$heading,       quote = input$quote,       stringsAsFactors = stringsAsFactors     )   })    # We can run observers in here if we want to   observe({     msg <- sprintf("File %s was uploaded", userFile()$name)     cat(msg, "\n")   })    # Return the reactive that yields the data frame   return(dataframe) } basicPlotUI <- function(id) {   ns <- NS(id)   uiOutput(ns("controls"))  } # Functionality for dataselection for plot # SelectInput is rendered dynamically based on data  basicPlot <- function(input, output, session, data) {   output$controls <- renderUI({     ns <- session$ns     selectInput(ns("col"), "Columns", names(data), multiple = TRUE)   })   return(reactive({     validate(need(input$col, FALSE))     data[, input$col]   })) }  ################################################################################## # Here starts main program. Lines above can be sourced: source("path-to-module.R") ##################################################################################  library(shiny)   ui <- shinyUI(navbarPage(   "My Application",   tabPanel("File upload", dataTabUI(     "tab1",     csvFileInput("datafile", "User data (.csv format)"),     "table"   )),   tabPanel("Plot", plotTabUI(     "tab2", basicPlotUI("plot1"), "plotOutput"   ))  ))   server <- function(input, output, session) {   datafile <- callModule(csvFile, "datafile",                          stringsAsFactors = FALSE)    output$table <- renderDataTable({     datafile()   })    plotData <- callModule(basicPlot, "plot1", datafile())    output$plotOutput <- renderPlot({     plot(plotData())   }) }   shinyApp(ui, server)