
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, 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
# macOS -> dist/MyApp.app and dist/MyApp-1.0.0.dmg
# Linux -> dist/MyApp-1.0.0/ and dist/MyApp-1.0.0.tar.gzWindows can produce an installer, macOS can produce an .app bundle and optional .dmg, and Linux produces a portable bundle plus .tar.gz. 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?
| Feature | Shiny | RInno (archived) | Electron + R | RDesk |
|---|---|---|---|---|
| Network ports required | Yes | Yes | Yes | No |
| Works fully offline | No | Partial | Partial | Yes |
| Native file dialogs and menus | No | No | Via JS | Yes |
| Distribution format | Server URL | Installer | Installer | Bundle or installer |
| Bundle size | Server-side | 350 MB+ | 350-500 MB | ~200 MB |
| Skills required | R | R + Electron | R + Node.js | R only |
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
miraiandcallrwith 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.
| Guide | What it covers |
|---|---|
| Getting Started | From install.packages() to your first native app |
| Coming from Shiny | Side-by-side mapping of common Shiny patterns to RDesk |
| Async Guide | Background tasks, progress overlays, cancellation |
| Cookbook | Practical desktop-app recipes |
| Why RDesk? | Project background and architecture |
