Observables in Shiny: Understanding the Issue with `observeEvents` and How to Work Around It

Introduction

Shiny is a popular R package for building interactive web applications. One of its key features is the ability to create reactive user interfaces that respond to user input. In this article, we will explore the issue with storing and reloading observeEvent callbacks in Shiny and provide a solution using a different approach.

What are Observables?

In Shiny, observables are functions that react to changes in user input or other observable values. They are used to create reactive user interfaces where the UI updates automatically when the underlying data changes. Observables are created using the observeEvent function, which takes two arguments: a Shiny input object (such as an actionButton) and a closure that defines the behavior.

The Issue with Storing Observables

In the provided example code, we create observables dynamically during the life of the application. We then store these observables in an RDS file using the saveRDS function from the RDS package. However, when we load the stored observables back into the application using the readRDS function, they do not seem to work as expected.

The Problem with `observeEvent`

The issue lies in how Shiny handles observables that are created dynamically. When you create an observable using observeEvent, it is stored in the Shiny session object. However, when you store and reload the observables, the Shiny session object is not persisted. This means that the new observables do not have access to the old ones, which leads to unexpected behavior.

Workaround: Using a Custom Session

One way to work around this issue is to create a custom Shiny session that stores the observables in a data frame. We can then load and reuse this data frame when we want to reload the observables.

library(shiny)

# Create a custom session that stores observables in a data frame
customSession <- function() {
  # Create a new Shiny session object
  session <- shiny::app_session()
  
  # Initialize an empty data frame to store observables
  observableList <- data.frame()
  
  # Define the server function for this session
  server <- function(input, output, session) {
    # Define a reactive expression that returns the observable list
    observable_list_reactive <- reactivity(session, {
      observableList
    })
    
    # Return the observable list as an output
    output$observableList <- renderText({
      table2text(observable_list_reactive())
    })
  }
  
  # Return the custom session object
  return(list(session = session, observableList = observableList))
}

# Create a new Shiny app using the custom session
ui <- fluidPage(
  actionButton("btn1","Btn1"),
  actionButton("btn2","Btn2"),
  actionButton("btn3","Btn3"),
  actionButton("btn4","Btn4"),
  actionButton("btn5","Btn5"),
  actionButton("btn6","Btn6"),
  actionButton("btn7","Btn7"),
  hr(),
  actionButton("makeCallbacks","Make Callbacks"),
  actionButton("saveCallbacks", "Save Callbacks"),
  actionButton("loadCallbacks", "Load callbacks"),
)

server <- function(input, output, session) {
  # Get the custom session object
  data <- customSession()
  
  # Create a reactive expression that generates the observable list
  observeEvent(input$makeCallbacks, {
    # Create a new row in the observable list data frame
    new_row <- rbind(data$observableList, 
                     lapply(1:7, function(i){
                       observeEvent(input[[paste0("btn",i)]],{
                         print(i)
                       },
                       label = paste0("Event for Button ", i))
                     })
    )
    
    # Update the observable list data frame
    data$observableList <- new_row
  })
  
  # Create a reactive expression that loads and displays the observable list
  observeEvent(input$loadCallbacks, {
    # Load the observable list from the RDS file
    observable_list <- readRDS("observerList.RDS")
    
    # Update the observable list data frame with the loaded values
    data$observableList <- observable_list
    
    # Display the updated observable list
    output$observableList <- renderText({
      table2text(data$observableList)
    })
  })
}

# Run the Shiny app
shinyApp(ui, server, options = list("launch.browser"=TRUE))

Conclusion

Storing and reloading observables in Shiny can be challenging. However, by creating a custom session object that stores observables in a data frame, we can work around this issue and load and reuse our observables as needed.

Note that the above code is an example of how to create a custom session object using the customSession function. In practice, you may need to modify this function to suit your specific use case.

Also note that the above code uses the reactivity package to define reactive expressions for generating and updating the observable list. This package provides a powerful way to work with reactive data in Shiny.

In conclusion, by understanding how observables work in Shiny and using creative solutions like custom sessions, we can build more robust and maintainable applications.

Last modified on 2025-01-27

Observables in Shiny: Understanding the Issue with observeEvents and How to Work Around It