rstudio/shiny

★ 5,648RAudience · dataComplexity · 2/5Setup · easy

Mindmap

mindmap
  root((Shiny))
    What it does
      R to web app
      Reactive updates
      No web dev needed
    Widgets
      Plots and charts
      Sliders and pickers
      Data tables
    Features
      Modules
      Async processing
      URL sharing
    Audience
      Data analysts
      R developers

mindmap root((Shiny)) What it does R to web app Reactive updates No web dev needed Widgets Plots and charts Sliders and pickers Data tables Features Modules Async processing URL sharing Audience Data analysts R developers

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Things people build with this

USE CASE 1

Turn an R data analysis script into a shareable web dashboard with sliders and charts that update in real time

USE CASE 2

Build an interactive data exploration tool for a team without writing any HTML or JavaScript

USE CASE 3

Create a reproducible report where the exact state can be shared as a URL for presentations or hand-offs

Tech stack

RBootstrapJavaScript

Getting it running

Difficulty · easy Time to first run · 5min

No license information was mentioned in the explanation.

In plain English

Shiny is an R package that lets people who already write R code turn their analysis scripts into interactive web applications without needing to learn HTML, CSS, or JavaScript. You write the logic in R, and Shiny handles the browser side automatically. The core idea is a "reactive" model. When a user moves a slider or changes a dropdown, only the parts of the app that depend on that input recalculate. This is different from older event-driven approaches where you manually wire each button to an action. The result is that apps stay responsive and the code stays readable, even when many inputs feed into many outputs. Shiny ships with a library of ready-made interface widgets: plots, data tables, sliders, date pickers, file uploaders, and more. The default visual style comes from Bootstrap, a well-established web design framework, so apps look clean out of the box. If you want a different look, there are companion packages for customizing the theme, and you can also drop down to raw HTML or CSS if needed. Beyond the basics, Shiny supports modules for breaking large apps into reusable pieces, asynchronous processing so slow calculations do not freeze the interface, built-in caching to avoid repeating expensive work, and load-testing tools to see how an app behaves under many simultaneous users. You can also save and share the exact state of an app via a URL, which is useful for reporting. Installation is a single line in R (install.packages("shiny")), and the package ships with runnable examples you can launch immediately to see how it works. Documentation includes a free online book called Mastering Shiny and an official tutorial, both aimed at R users with no prior web development background.

Copy-paste prompts

Prompt 1

I have an R script that filters a data frame and plots results. Convert it into a Shiny app with a dropdown to pick a category and a chart that updates live.

Prompt 2

How do I add a file upload widget to my Shiny app so users can upload a CSV and see a data table and summary statistics?

Prompt 3

My Shiny app has a slow database query. How do I use async processing so the interface stays responsive while the query runs?

Prompt 4

Show me how to split a large Shiny app into modules so each section of the UI and server logic lives in its own file.

Prompt 5

How do I save and share the current state of my Shiny app as a URL so a colleague can open it with the same inputs already set?

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