by Hong Ooi This article is a lightly-edited version of the "Microsoft365R and Shiny" vignette in the latest Microsoft365R release. We describe how to incorporate Microsoft365R and interactive authentication with Azure Active Directory (AAD) into a Shiny web app. There are a few steps involved: Register your app with AAD Use the app ID to authenticate and get an OAuth token Pass the token to the Microsoft365R functions App registration The default Microsoft365R app registration only works when the package is used on a local machine; it does not support running in a remote server. Because of this, when you...

You mastered R, Shiny, Python, and Dash. Your app is production-ready. Now learn about hosting options and pick one that best suits your needs!

Use Docker Compose to simplify Shiny app deployment and reach dev/prod parity. Part 1 looks at local development.

Build better Shiny apps with Appsilon's proven methods for effective user tests. Follow along to discover how you

Docker Compose Example with Shiny Apps. Contribute to analythium/docker-compose-shiny-example development by creating an account on GitHub.

This post provides a guide to effectively and securely scale your ShinyProxy deployment of shiny apps in production with Docker Swarm and Traefik

This document is full of supplemental resources and content from the Shiny in Production Workshop delievered at rstudio::conf 2019.

Collection of notifications, confirm dialogs and alerts for 'Shiny' applications - dreamRs/shinypop

The Hosting Data Apps website is dedicated to help you learn about your hosting options. As outlined in the opening post, data app development related content is kept to a minimum. In this post we list resources that provide accessible introduction to Shiny app development.

I have deployed shiny server with several shiny apps. Each app is used as online dashboard which should be refreshed periodically (e.g. every 2 hours or at 10pm every day) according to my plan. N...

Links and resources for Shiny, JavaScript, HTML, and CSS.

We are creating a database and integrate persistent data storage in an R Shiny application with a remote MySQL database for free.

When using shiny in production, often you will want to have some sort of database interactions for storing and accessing data. The DBI package provides an easy way to do the database interactions with a variety of SQL database flavors. In this example, I’m going to use a SQLite ...

[Disclaimer] The package presented in this blog post is stillexperimental at the time of writing these lines (2021-02-28), so itmight face some API changes in the future.Yesterday Jacqueline’s tweeted about her need to add POST requests toa {shiny} application.I'm astounded that it doesn't seem like a Shiny app is able to acceptPOST requests. I have data I wanna pass to my server :/— Dr. Jacqueline Nolis (@skyetetra)February27, 2021This is actually one of the things I had in mind when building{brochure}: more flexibility with the HTTP requests and how they arehandled.So here is a working ex...

When using shiny in production, often you will want to have some sort of database interactions for storing and accessing data. The DBI package provides an easy way to do the database interactions with a variety of SQL database flavors. In this example, I’m going to use a SQLite in memory database for reproducibility. In practice, you will just switch to the code to use a persistent database. Let’s start by creating a table to right to.

In this guide you’ll find both original content and curated resources to: + Build R shiny apps from scratch + Select the optimal dashboard framework for your R shiny app dashboard + R packages to build interactive, professional quality data visualization + Improve the user experience and dashboard speed tricks + All the ways you can deploy and share R shiny app dashboards + Lessons from a dashboard veteran for better R shiny app dashboards

Véritables outils de visualisation des données, les tables interactives permettent de trier, colorer, éditer, rechercher, paginer les données

In this guide you’ll find both original content and curated resources to: + Build R shiny apps from scratch + Select the optimal dashboard framework for your R shiny app dashboard + R packages to build interactive, professional quality data visualization + Improve the user experience and dashboard speed tricks + All the ways you can deploy and share R shiny app dashboards + Lessons from a dashboard veteran for better R shiny app dashboards

This is a tutorial post about building a webapp with user form and leaflet map visualization using R Shiny. The webapp I built aims to collect crowdsourced data of how sustainable are the eateries …

Quickly and conveniently create interactive visualisations of spatial data with or without background maps. Attributes of displayed features are fully queryable via pop-up windows. Additional functionality includes methods to visualise true- and false-color raster images and bounding boxes.

Shiny's 1.6 has a new function, bindCache(), which makes it easy to dramatically speed up reactive expressions and output rendering functions.

Together with Clara Bicalho (UC Berkeley) and Sisi Huang (WZB), I recently developed a web application that acts as a convenient interface to the DeclareDesign R package and its repository of resea…

In this article we look at how to build a shiny app with clear code, reusable and automatically tested modules. For that, we first go into the package structure and testing a shiny app before we focus on the actual modules.

In this post we’d like to introduce you to our new R package shinyMatrix. It provides you with an editable matrix input field for shiny apps.

Pedro Coutinho Silva is a software engineer at Appsilon Data Science. It is not always possible to create a dashboard that fully meets your expectations or requirements using only existing libraries. Maybe you want a specific function that needs to be custom built, or maybe you want to add your own style or company branding. Whatever the case, a moment might come when you need to expand and organize your code base, and dive into creating a custom solution for your project; but where to start?