Setting R Environment Variable from a Shiny Module Using Sys.setenv()

Introduction

In this post, we will explore how to set environment variables in R using the Sys.setenv() function and integrate it with a Shiny application. We’ll break down the process step-by-step, providing explanations, examples, and code snippets along the way.

Understanding Environment Variables in R

Before diving into setting environment variables from a Shiny module, let’s quickly cover what environment variables are and how they work in R.

Environment variables are used to store data that can be accessed by multiple programs or scripts. In R, you can set environment variables using the Sys.setenv() function, which allows you to modify the system-wide environment variables or local variables within a script or program.

Setting Environment Variables from a Shiny Module

To set environment variables from a Shiny module, we’ll need to create a new module that uses the Sys.setenv() function. Let’s start by creating a new R file for our module and call it setEnvModule.R.

## setEnvModule.R

credentialsInput <- function(id) {
  ns <- NS(id)

  tagList(
    textInput(ns("username"), "Username", value = get_username()),
    passwordInput(ns("password"), "Password", value = get_password()),
    actionButton(ns("credentialSubmitButton"), "Submit" ))
}

setEnv <- function(input, output, session) {
  observeEvent(input$credentialSubmitButton, {
    set_username(input$username)
    set_password(input$password)

    print(paste(get_username(), get_password()))
  })

  # Set environment variable
  Sys.setenv("MY_VAR", "my_value")
}

In this code snippet, we’ve created a new module called setEnv that uses the Sys.setenv() function to set an environment variable named “MY_VAR” with the value “my_value”. We’ll discuss how to integrate this module with our Shiny application in the next section.

Integrating the Module with the Shiny Application

To use the new module, we need to modify our original Shiny application code to call the setEnv function instead of the old setCredentials function. Let’s update our app.R file as follows:

## app.R

library(shiny)

# Define UI
ui <- fluidPage(
  titlePanel("Set credentials"),
  credentialsInput("credentials")
)

# Define server
server <- function(input, output) {
  # Call new module
  callModule(setEnv, "credentials")

  # Display environment variable value
  output$myVar <- renderText({
    paste0(get("MY_VAR"))
  })
}

# Run shiny app
shinyApp(ui = ui, server = server)

In this code snippet, we’ve updated the server function to call the setEnv module instead of the old setCredentials function. We’ve also added a new text output called “myVar” that displays the value of the environment variable “MY_VAR”.

Running the Shiny Application

Now that we have our code snippets, let’s run the shiny application using RStudio Server.

# Run shiny app
runApp("app")

This will launch a new web interface where you can interact with the Shiny application. Try submitting the form and verifying that the environment variable value is displayed correctly on the webpage.

Troubleshooting

One common issue when setting environment variables from a Shiny module is that the changes are not reflected immediately. This might be due to the way R handles environment variables or caching issues within the Shiny application.

To troubleshoot this issue, try the following:

Restart RStudio Server after making any changes to your code.
Verify that the Sys.setenv() function is being called correctly by adding some debug print statements to your code snippet.
Try setting environment variables directly from the command line or in your system’s preferences to rule out issues related to environment variable persistence.

Conclusion

In this post, we explored how to set environment variables in R using the Sys.setenv() function and integrate it with a Shiny application. We broke down the process step-by-step, providing explanations, examples, and code snippets along the way. With this knowledge, you should be able to create your own custom Shiny modules that interact with environment variables to achieve specific use cases.

Additional Resources

For further learning on R environment variables or Shiny applications, check out the following resources:

Feel free to ask if you have any further questions or need additional clarification.

Last modified on 2023-11-02