R - Shiny

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 · GitHub

Yes, Shiny apps can be fast and scalable. But only if you build them in the right way and use the proper tools.

This post provides a guide to use ShinyProxy, an open-source tool with enterprise features, to deploy R Shiny apps.

Demonstration of user management and authentication system in R Shiny - yanirmor/shiny-user-management

Take screenshots in Shiny apps. Contribute to dreamRs/capture development by creating an account on GitHub.

Simple ZeroClipboard Clipboard Functionality for Shiny/R Applications - smbache/zeroclipr

Article posted by Andy Merlino, on Friday, July 17nd, 2020

🎨 A colour picker tool for Shiny and for selecting colours in plots (in R) - daattali/colourpicker

Broadly speaking, there are two strategies for connecting a shiny application to a database using secure authentication. The first is running the application as a service account. The second is run...

The unicode character U+1F4C1 (📁) is named "File Folder" and belongs to the Miscellaneous Symbols and Pictographs block. It is HTML encoded as 📁.

Adding acceptance tests first makes refactoring safer.

Learn how to manage state in Shiny modules using a React-inspired approach with event handlers for better control and flexibility.

Shiny is a package that makes it easy to create interactive web apps using R and Python.

Shiny is a package that makes it easy to create interactive web apps using R and Python.

Shiny is a package that makes it easy to create interactive web apps using R and Python.

Shiny is a package that makes it easy to create interactive web apps using R and Python.

This is a book that covers the standard shiny app workflow.

Seamless SSO for R applications

Learn how to implement strong authentication and SSO in Shiny apps with Descope. This guide integrates both OIDC and SAML with Posit Connect for seamless login.

Provides tools for implementing Retrieval-Augmented Generation (RAG) workflows with Large Language Models (LLMs). Includes functions for document processing, text chunking, embedding generation, storage management, and content retrieval. Supports various document types and embedding providers (Ollama, OpenAI), with DuckDB as the default storage backend. Integrates with the ellmer package to equip chat objects with retrieval capabilities. Designed to offer both sensible defaults and customization options with transparent access to intermediate outputs.

Awesome notifications for shiny. Contribute to JohnCoene/awn development by creating an account on GitHub.

Minimal busy indicator for Shiny apps. Contribute to dreamRs/shinybusy development by creating an account on GitHub.

Hierarchical tree input for Shiny apps. Contribute to dreamRs/shinytreeview development by creating an account on GitHub.

Transform your R Shiny applications into standalone desktop apps with nhyris. This minimal framework leverages Electron to simplify packaging and distribution, ensuring your Shiny apps are cross-platform and easy to deploy. Learn how to get started, customize your project, and build your first Electron application with nhyris.

You can set global options to control Shiny's behaviour. The developer mode automatically enables Shiny options for you. How? Find out here!

Step-by-step guide showing how to protect a Shiny app using LDAP