← All open source projects

Shiny

rstudio/shiny

Shiny is an R framework for interactive web applications with a reactive model.

Forks 1,892
Author rstudio
Language R
License NOASSERTION
Synced 2026-06-27

In Short

Shiny turns R code into an interactive web application: charts, tables, sliders, and filters update automatically when inputs change.

What It Is

Shiny is a framework for building interactive web applications in R. Its strong idea is that an analyst can build a live app without hand-writing HTML, CSS, and JavaScript.

What Is Inside

The project provides a reactive model, widgets, R Markdown integration, and Bootstrap-based styling. Outputs recalculate when connected inputs change, not after every user action.

How People Use It

Shiny is used for analytical dashboards, research prototypes, internal reports, and small data products. It is especially useful for teams where R is the main analysis language.

Example

Minimal Shiny Idea

R syntax is shown as plain text: an input slider controls a value, and the output reacts to changes.

Language: Plain text
ui <- fluidPage(
  sliderInput("n", "Rows", 1, 100, 20),
  tableOutput("data")
)

server <- function(input, output) {
  output$data <- renderTable(head(mtcars, input$n))
}

Strengths

Shiny’s strength is the short path from analysis to application. Code that used to live in a notebook or script can become an interface for colleagues.

Limits

The limitation is the boundary of the R ecosystem. Complex public interfaces, high-traffic products, and fine client-side behavior may need a separate web architecture.

Project Context

Shiny is maintained in the rstudio/shiny repository; its public history starts on 2012-06-20. The primary metadata language is R, and the license is NOASSERTION. The project also has a dedicated site: https://shiny.posit.co/.

This context keeps the page grounded in a specific repository: the project has an owner, technical base, license, change history, and real constraints of its ecosystem.

Shiny should be evaluated through a concrete scenario: who will maintain it, where it fits in the existing stack, which updates must be tracked, and what happens if it fails. That view is more useful than installing a project just because it is popular, because open source helps only when its role in the system is clear to the team.