In our last article, we explored the S4 OOP system in R. Up until this point, we had only discussed functional OOP systems in R. Today, we are going to...continue reading.

When developing R Shiny apps, making sure they work well and are reliable is important. Rigorous testing isn’t just about finding bugs; it’s about preventing them, saving time, and ensuring...continue reading.

Rhino, the R package development framework created by Appsilon, has recently released two updates – versions 1.8 and 1.9. In this fireside chat, Kamil Żyła (one of the core developers...continue reading.

Understanding how users interact with your application in data analytics is crucial for continuous improvement and user satisfaction. {shiny.telemetry} is a groundbreaking tool that lets you do just that. shiny.telemetry...continue reading.

Are you still conducting runtime benchmarks in R through manual calls to `Sys.time()`? We don’t judge, but there’s a way more powerful and automated way to do the same –...continue reading.

The word “universe” can mean many different things. In modern-day entertainment, we are conditioned to think of it as related movies or media tied together by the tried-and-true formula of...continue reading.

We’re excited to announce the release of Rhino 1.9, bringing with it some powerful new features for developers. This update focuses on enhancing your coding experience with new formatting tools...continue reading.

When it comes to time series forecasting in R, one thing you don’t lack is options. There are dozens of algorithms and their variations you can choose from, and doing...continue reading.

ShinyProxy has emerged as a powerful solution for deploying Shiny applications, empowering organizations to share interactive data visualizations and analyses. With its robust feature set, ShinyProxy has simplified the process...continue reading.