html - How to Style navigable page sidebar in Shiny using bslib - Stack Overflow
Add LDAP Authentication to a Shiny app
Step-by-step guide showing how to protect a Shiny app using LDAP
Making Tables Shiny: DT, formattable, and reactable
Demo of popular packages for generating interactive tables suitable for Shiny apps
formattable
Another nice table-making package is formattable.
The cute heatmap-style colour formatting and the easy-to-use formatter functions make formattable very appealing.
color_tile() fills the cells with a colour gradient corresponding to the values
color_bar() adds a colour bar to each cell, where the length is proportional to the value
The true_false_formatter() defined below demonstrates how to define your own formatting function, in this case formatting TRUE, FALSE and NA as green, red and black.
If you want the features of both DT and formattable, you can combine them by converting the formattable() output to as.datatable(), and much of the formattable features will be preserved.
However, one problem I had was that when using DT::datatable, missing values (NA) are left blank in the display (which I prefer), but in the converted from formattable() version, NA’s are printed. Also, color_bar columns seem to be converted to character, which can no longer be sorted numerically.
reactable
Next I tried reactable, a package based on the React Table library.
Columns are customised via the columns argument, which takes a named list of column definitions defined using colDef(). These include format definitions created using colFormat.
In the end, I used DT::datatable() in my Shiny app, because I found it the easiest, fastest, and most comprehensive. I’ve been able to achieve most of the features I wanted using just DT.
Heatmap-like fill effect:
apply the formatStyle() function to the output of datatable() to set the backgroundColor for selected columns:
Abbreviate long cells
Sometimes some cells have a large amount of text that would mess up the table layout if I showed it all. In these cases, I like to abbreviate long values and show the full text in a tooltip.
To do this, you can use JavaScript to format the column to show a substring with “…” and the full string in a tooltip (<span title="Long string">Substring...</span) when values are longer than N characters (in this case 10 characters). You can do this using columnDefs and pass JavaScript with the JS() function:
Really plain table
Sometimes I don’t need any of the faff. Here’s how to get rid of it all:
headerCallbackRemoveHeaderFooter <- c( "function(thead, data, start, end, display){", " $('th', thead).css('display', 'none');", "}" )
datatable( my_pic_villagers, options = list( dom = "t", ordering = FALSE, paging = FALSE, searching = FALSE, headerCallback = JS(headerCallbackRemoveHeaderFooter) ), selection = 'none', callback = JS( "$('table.dataTable.no-footer').css('border-bottom', 'none');" ), class = 'row-border', escape = FALSE, rownames = FALSE, filter = "none", width = 500 )
rstudio/shiny: Easy interactive web applications with R
Easy interactive web applications with R.
Compared to event-based programming, reactivity allows Shiny to do the minimum amount of work when input(s) change, and allows humans to more easily reason about complex MVC logic.
An attractive default look based on Bootstrap which can also be easily customized with the bslib package or avoided entirely with more direct R bindings to HTML/CSS/JavaScript.
Tools for improving and monitoring performance, including native support for async programming, caching, load testing, and more.
Shiny - Stop-Trigger-Delay
Shiny is a package that makes it easy to create interactive web apps using R and Python.
observeEvent() is used to perform an action in response to an event
eventReactive() is used to create a calculated value that only updates in response to an event
observe() and reactive() functions automatically trigger on whatever they access
observeEvent() and eventReactive() functions need to be explicitly told what triggers them
And where does isolate fit in all this?
isolate() is used to stop a reaction
observeEvent() is used to perform an action in response to an event
eventReactive() is used to create a calculated value that only updates in response to an event
Overview – Next Generation Shiny Apps with {bslib}
Welcome and Getting Started – Next Generation Shiny Apps with {bslib}
Welcome to the workshop and hello, bslib!
Getting started with shinytest2
How to enhance your R shiny application with httpOnly Cookies
httpOnly Cookies are crucial for security, protecting against cross-site scripting attacks in R Shiny apps. Read more about them here.
Draft for adding OAuth support to shiny by thohan88 · Pull Request #518 · r-lib/httr2
Info: This is a draft for discussion purposes. It's not a polished PR and currently includes minimal error handling and documentation. It may be big enough to warrant a separate package, bu...
Cloud Run Websocket support now allows you to deploy a R Shiny Server as a serverless app to GCP Cloud Run
Cloud Run Websocket support now allows you to deploy a R Shiny Server - a dashboard hosting tool to host R Shiny dashhboards - as a serverless app to GCP Cloud Run
Fastest Growing R Shiny App Store
Showcase your R shiny application and grow your user base. Real time usage stats and reviews for all your apps. Contribute today.
Why you should learn Javascript to master R Shiny. And how to get started - datahabits.io
Although the concealment of Javascript is by design and makes Shiny in the first instance easy to use, in the long run when you want to build serious and more visual appealing apps, you most likely need to utilize javascript to make most of the web framework
Pimping your shiny app with a JavaScript library : an example using sweetalert2 - Rtask
The R task Force - R experts for all your needs
Best Practice: Development of Robust Shiny Dashboards as R Packages
This article describes best practice approaches for developing shiny dashboards. The creation of the dashboard in package form, as well as the use of unit tests should enable the development of robust solutions and guarantee high quality.
What are some useful css/SASS, HTML, and javascript/typescript tools,...
Integrating CSS/SASS, HTML, and JavaScript/TypeScript into R Shiny applications can significantly enhance the user interface and interactivity of your apps....
Create a table of shiny inputs
Create an interactive table of Shiny inputs by providing data and a table definition.
Shiny
Shiny is a package that makes it easy to create interactive web apps using R and Python.
Shiny was designed with an emphasis on distinct input and output components in the UI. Inputs send values from the client to the server, and when the server has values for the client to display, they are received and rendered by outputs.
You want the server to trigger logic on the client that doesn’t naturally relate to any single output.
You want the server to update a specific (custom) output on the client, but not by totally invalidating the output and replacing the value, just making a targeted modification.
You have some client JavaScript that isn’t related to any particular input, yet wants to trigger some behavior in R. For example, binding keyboard shortcuts on the web page to R functions on the server, or alerting R when the size of the browser window has changed.
R Shiny Security: How to Make Your Shiny Apps Secured – R-Craft
Securing your Shiny application is not just an added feature; it’s a fundamental necessity. Often, functionality and design are prioritized in development, but ensuring the security of your app is equally important, if not more so. Shiny security involves more than just adhering to general programming best practices like utilizing environment variables instead of hardcoding […] The post appeared first on appsilon.com/blog/.
Pimping your shiny app with a JavaScript library : an example using sweetalert2 – R-Craft
You can read the original post in its original format on Rtask website by ThinkR here: Pimping your shiny app with a JavaScript library : an example using sweetalert2 You think that some of the components of {shiny} are not very functional or downright austere? Are you looking to implement some feature in your app but it is not available in the {shiny} toolbox? Take a look at JavaScript! JavaScript is a very popular programming language that is often used to add features to web pages. With HTML and This post is better presented on its original ThinkR website here: Pimping your shiny app with a JavaScript library : an example using sweetalert2
How to Make Your Shiny App Beautiful
Master the art of Shiny app design: Boost aesthetics, improve UX, and refine code efficiency with our comprehensive guide.
Shiny App-Packages
Getting your app into an R package
Foreword | Outstanding User Interfaces with Shiny
A book about deeply customizing Shiny app for production.
Michal Lauer - How to deploy an R Shiny application to Google Cloud Platform (GCP) using Docker and Github Actions
Learn how to effortlessly deploy R Shiny apps on Google Cloud Platform using Docker and GitHub Actions for seamless integration and efficient application management.
Mastering Asynchronous Programming in R Shiny: A Comprehensive Guide - Hypebright
Learn how to supercharge your R Shiny applications with asynchronous programming. Explore top packages and best practices!
Introduction
Shiny Server @CNR-IBBA. Contribute to cnr-ibba/shiny-server development by creating an account on GitHub.
Nicholas Actuarial Solutions on LinkedIn: Developing Actuarial Applications using R Shiny
Our founder Nicholas Yeo and Actuarial Analysts Debbie Min Jyeh Ooi and Nadia Suharto presented "Developing Actuarial Applications using R Shiny" at the event…
Mastering file download in shiny - Rtask
The R task Force - R experts for all your needs
Supplement to Shiny in Production
This document is full of supplemental resources and content from the Shiny in Production Workshop delievered at rstudio::conf 2019.
Saturn Elephant - Tooltips for a dropdown list in Shiny