Native Desktop Application Framework

Build native desktop applications for Windows (with future support planned for macOS and Linux) using 'R' and embedded 'webviews'. Provides a robust 'R6'-based event loop, asynchronous background task management via 'mirai' and 'callr', and a native message bridge for seamless 'R'-to-user-interface communication without listening ports or network overhead. Allows 'R' developers to create professional, standalone desktop tools with modern web-based user interfaces while maintaining a pure 'R' backend.

RDesk

Package R analyses into self-contained native desktop applications with zero network port requirements.

RDesk packages your R analysis into a standalone desktop application for Windows (with future support planned for macOS and Linux). Instead of running an HTTP server and opening a browser tab, RDesk uses a native launcher plus an embedded webview so the app runs offline with local IPC only.

Quick Start

# Install from CRAN
install.packages("RDesk")

# Scaffold an interactive app
RDesk::rdesk_create_app("MyApp")

# Run it immediately
source("MyApp/app.R")

When you are ready to ship:

RDesk::build_app(
  app_dir         = "MyApp",
  app_name        = "MyApp",
  build_installer = TRUE
)

# Windows -> dist/MyApp-1.0.0-setup.exe (or dist/MyApp-1.0.0-windows.zip)

Windows produces a standalone installer or portable zip distribution (with macOS and Linux packaging in active development). No separate R installation or browser server is required on the target machine when using the bundled runtime.

Development version

devtools::install_github("Janakiraman-311/RDesk")

Why RDesk?

Core Features

• Zero-port IPC - R and the UI communicate through native stdin/stdout pipes and platform webview bindings, without opening network ports.
• Async by default - Non-blocking background work using mirai and callr with support for progress updates, loading states, and cancellation.
• Version-safe runtime - build_app() bundles a matching R runtime so the shipped app and its packages stay aligned.
• Modern web UI - Build the interface with plain HTML, CSS, and JavaScript while keeping the backend in R.
• Automated scaffolding - rdesk_create_app() generates a working application template with handlers, structure, and theme support.
• Native packaging - Produce platform-specific bundles and installers without adopting a browser-server deployment model.

Who It's For

RDesk is built for R developers who need to package a local statistical or data tool for non-R users.

• Pharma and clinical - distribute review or validation tools for offline execution.
• Consulting - package analytical models into branded tools without exposing source code.
• Internal teams - replace complex spreadsheet macros with structured R applications.
• Restricted environments - ship local tools where listening ports are disallowed or heavily scrutinized.

Example Apps

Two apps ship with RDesk demonstrating different complexity levels.

CarsAnalyser - minimal dashboard

app_dir <- system.file("apps/mtcars_dashboard", package = "RDesk")
source(file.path(app_dir, "app.R"))

Data Intelligence Studio - full-featured data profiling tool

app_dir <- system.file("apps/data_studio", package = "RDesk")
source(file.path(app_dir, "app.R"))

Documentation

Full documentation is available at janakiraman-311.github.io/RDesk.

License

MIT (c) Janakiraman G.