Shiny App-Packages

Getting your app into an R package

Welcome!

Develop your Shiny application as an R package.

Shiny combines the power of R’s statistical capabilities with the interactivity of a web-based application.

R packages are collections of pre-built, self-contained code, data, and documentation designed to perform operations or accomplish tasks beyond the capabilities of the R language.

What’s in the book

This book is a resource to help ‘connect the dots’ between building scalable Shiny applications and writing R packages. Adopting R package development practices in the early stages of your Shiny app will improve the reusability, maintainability, and shareability of all your hard work.

The code and data originate from the excellent Building Web Applications with Shiny (BWAS) course. If you’re new to Shiny development this course is a great place to start. The four learning modules will provide a solid understanding for many of the topics covered in this book.

LLM Disclaimer: who wrote this?

Given the current landscape of online resources and the impressive capabilities of large language models (LLMs), I feel it’s important to clarify the authorship of this book.

Only the code included in this book was created with the assistance of LLMs, and this applies only to specific chapters that are explicitly noted. I have fully authored the narrative, commentary, and explanations. Hopefully, the typos and/or grammatical errors serve as a signature of authenticity.

Recent Updates!

This resource is being revised to include recent changes in the Shiny development landscape (Positron, LLM tools and packages, etc.). While most of the information in the Introduction and App-packages sections will remain unchanged, I will continue to update the other sections as Shiny app (and R package) development evolves and changes. Expand the callout boxes below to view the new sections and updates.

New Sections/Chapters

Debugging

• The previous debugging chapter has been expanded into a Debugging section:
  • 10  Debuggers
    
  • 11  Print debugging
    
  • 12  Debugging apps
    
  • 13  Logging

Shiny LLM Tools

• I’ve added a new Shiny LLM Tools section:
  • 26  Shiny Assistant
    
  • 27  ellmer
    
  • 28  chores
    
  • 29  gander (in development)

Special Topics

• The special topics section now covers:
  • 30  🏗️ Shiny UI Editor (in development)
    
  • 31  Code style
    
  • 32  🏗️ App data (in development)
    
  • 33  🏗️ Dependency hell (in development)

Updates

Shiny

• New diagrams:
  • 2.5.1 Modules
    
  • 2.5.2 Standalone app function

Packages

• New section:
  • 3.1.3 Positron’s workspaces

Development

• 4.4 Install
  • Now covers the differences between RStudio and Positron

Dependencies

• New diagrams:
  • 6.1 Package exports
    
  • 6.2 Package imports (also includes a new section on managing dependencies with renv)

Documentation

• New diagrams
  • 5.1 roxygen2 basics
    
  • 5.2 Documenting app functions

Testing

• New sections
  • 16.1 Unit tests & LLMs
    
  • 16.3 Test logging

Deployment

• Updated examples
  • 21.2 Shiny app deployment
    
  • 21.3 Actions, Shiny & Docker
    
• Expanded example
  • 22  pkgdown

Frameworks

• 23  golem
  • app rebuilt using version 0.5.1
    
• 24  leprechaun
  • app built using version 1.0.0.9001
    
• 25  rhino
  • app built using version 1.10

What’s not in the book

This book isn’t a replacement for Mastering Shiny or R Packages, 2ed (or Writing R Extensions). I highly suggest bookmarking these resources to return and read when you’d like to learn more about R package and Shiny development.

I also won’t be recommending a particular Shiny framework or package, but I’ll cover a few popular choices, show what they’re doing ‘under the hood,’ and let you decide if you’d like to adopt their practices.

What I assume about you

If you’re reading this, I assume you’re comfortable with R, RStudio, Shiny, and the tidyverse. Maybe you haven’t built a ton of applications, but you understand reactivity, and you’re comfortable with the core Shiny concepts (i.e., the UI, server, *_Input(), *_Output(), and render_* functions, etc.).

Code examples

The code files for each chapter are stored in GitHub repository. Major code changes are stored in branches. Whenever a new branch is used, you’ll see the Git Branch icon with a link to the repo/branch in the margin.

See the <branch> branch of sap.

In an effort to make the code and examples more accessible and easy to use, I’ve also created the shinypak package. This package can be used to launch or download the applications in each branch.¹

Example:

# install.packages('pak')
pak::pak('mjfrigaard/shinypak')
shinypak::launch('02.3_proj-app')

---

1. shinypak uses the .Rproj files to launch apps, so a an installation of RStudio is required. However, the applications in each branch still be downloaded with shinypak::get().