Shiny Baseball

R - Shiny
Themeable HTML components — bs_dependency
Themeable HTML components use Sass to generate CSS rules from Bootstrap Sass
variables, functions, and/or mixins (i.e., stuff inside of theme).
bs_dependencies() makes it a bit easier to create themeable components by
compiling sass::sass() (input) together with Bootstrap Sass inside of a
theme, and packaging up the result into an htmltools::htmlDependency().
Themable components can also be dynamically themed inside of Shiny (i.e.,
they may be themed in 'real-time' via bs_themer(), and more generally,
update their styles in response to shiny::session's setCurrentTheme()
method). Dynamically themeable components provide a "recipe" (i.e., a
function) to bs_dependency_defer(), describing how to generate new CSS
stylesheet(s) from a new theme. This function is called when the HTML page
is first rendered, and may be invoked again with a new theme whenever
shiny::session's setCurrentTheme() is called.
Audit Shiny apps in few steps
Audit your Shiny apps at each commit.
Multiple levels of testings are offered: startup and crash tests,
performance tests (load test and global code profiling), reactivity audit as well as output tests.
All results are gathered in an HTML report uploaded and available to everyone
on any CI/CD plaform or RStudio Connect.
Master Shiny Apps: Complete R Web Development Guide
Master Shiny development with our comprehensive learning path covering fundamentals, UI design, server logic, advanced concepts, and production deployment. Transform from R user to professional web app developer through hands-on tutorials and real-world projects.
Shiny Reactive Programming: Master Advanced Reactive Patterns
Master Shiny’s reactive programming model with comprehensive coverage of reactive expressions, observers, event handling, and advanced patterns. Learn to build efficient, dynamic applications with proper reactive design.
Enterprise UI Design: Professional Bootstrap 5 for Shiny Apps
Master enterprise-grade UI/UX design for Shiny applications using Bootstrap 5, bslib theming, and professional design systems. Learn to create accessible, responsive interfaces that meet corporate standards for biostatistics and clinical research applications.
feddelegrand7/bubblyr: ☁️ ☁️ ☁️ Beautiful Bubbles in Shiny and RMarkdown Backgrounds
☁️ ☁️ ☁️ Beautiful Bubbles in Shiny and RMarkdown Backgrounds - feddelegrand7/bubblyr
Architecture for Non-Trivial R Shiny Applications
This article shows how to use battery R framework to create architecture for big shiny applications
Build Elegant R shiny Apps with New ‘Card’ Features Using {card.pro}
Build Robust R shiny Apps with Elegant and Highly Customizabel ‘Card’ Features Using card.pro R package
Chapter 16 Cookies | JavaScript for R
Invite JavaScript into your Data Science workflow.
How to Develop Robust and Maintainable JavaScript Code Within a Shiny Application
Take your R/Shiny apps to the next level with JavaScript. Learn best practices for typing, documentation, and integrating React with Rhino.
R in the backend not Shiny
1 Using R in the back-end .. but not with R-Shiny LIBData Portal
Shiny
Shiny is a package that makes it easy to create interactive web apps using R and Python.
What is Shiny (in R)? | Domino Data Science Dictionary
Shiny is an R package that enables building interactive web applications that can execute R code on the backend.
Shiny
Shiny is a package that makes it easy to create interactive web apps using R and Python.
Opinionated Backend and Reusability Focused Considerations for Shiny
Purposefully simple helper functions, tools, and a framework for creating reusable applications fit for production in clinical systems.
ShinyUiEditor
Landing page for the ShinyUiEditor: A drag and drop interface for building Shiny apps.
keycloakAuthR/R/shiny.R at master · andyquinterom/keycloakAuthR
Keycloak Authentication for R/Shiny.
Shiny Source Code Explained: Launching the Server - Hypebright
Find out how the server-side of a Shiny application works by exploring the Shiny source code and understanding WebSockets and HTTP requests.
Posit
The 4th Shiny Contest is now in full swing! This community event celebrates learning, sharing, and recognizing outstanding work within the Shiny developer community.
background-jobs/shiny-job at main · sol-eng/background-jobs
Resources for demoing local and Launcher jobs with RStudio - sol-eng/background-jobs
Shiny
Shiny is a package that makes it easy to create interactive web apps using R and Python.
R on Kubernetes - serverless Shiny, R APIs and scheduled scripts
Some examples of running R applications on Google Kubernetes Engine
nanxstats/awesome-shiny-extensions: 🐝 Awesome R packages that offer extended UI or server components for the R web framework Shiny
🐝 Awesome R packages that offer extended UI or server components for the R web framework Shiny - nanxstats/awesome-shiny-extensions
DivadNojnarg/outstanding-shiny-ui-code: Standalone code for the "Outstanding Shiny UI" Book
Standalone code for the "Outstanding Shiny UI" Book - DivadNojnarg/outstanding-shiny-ui-code
dreamRs/shinyapps: Some Shiny applications
Some Shiny applications. Contribute to dreamRs/shinyapps development by creating an account on GitHub.
shiny-loadbalancer/shiny-monitor.R at master · aephidayatuloh/shiny-loadbalancer
Shiny App for Load Balancing. Contribute to aephidayatuloh/shiny-loadbalancer development by creating an account on GitHub.
Alternative Approaches to Scaling Shiny with RStudio Connect, ShinyProxy, or Custom Architecture - Appsilon | End to End Data Science Solutions
Article compares different technologies to scale R Shiny Apps, technologies used: ShinyProxy, Shiny Server Open Source & Pro and solution based Docker and Load Balancer.
shiny-loadblancer-internal.R
shiny-loadblancer-internal.R · GitHub
4 Tips to Make Your Shiny Dashboard Faster
Yes, Shiny apps can be fast and scalable. But only if you build them in the right way and use the proper tools.