Serverless Shiny Inspired by Max Kuhn's presentation at R/Pharma today I tried out embedding shiny a app within a Quarto website and hosting it on GitHub pages. The app itself is a chemistry quiz built to help my son who had a school test coming up. By running it within a Quarto website it's available for him to use on …

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Shiny textInput label This is just a short post highlighing how you can move a textInput label so that it is within the textbox textInput box itself. This is a style that can be used when you have multiple textInputs and wish to preserve screen height. First we define a css class to reduce the size of the label text …

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SelectizeInput SelectizeInput is a powerful shiny widget built on the selectize.js library. The behavior of selectize.js can be extended using plugins, which are available in the shiny::selectizeInput() functon. One particularly useful plugin is "drag_drop" which allows a user to re-order the items selected …

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Why package a plumber API? There are many advantages to building R-based code as a package. You can use the DESCRIPTION file to store metadata related to the API, separate functions from endpoints in the R/ folder, include documentation and run tests. In this example we'll build a simple plumber API as a package. The …

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An earlier post demonstrated how the jupyter SAS kernel could be used to run SAS from within a Quarto document. This post demonstrates the saspy library and how SAS can be incorporated into Quarto, ultimately passing data to an interactive observable visualization. Setup and Configure saspy needs to be installed and …

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Quarto is a powerful web publishing system based on Pandoc. Working with jupyter kernels expands the number of languages that Quarto can work with. In this example we'll add SAS capability to Quarto. Setup First install the saspy and the SAS kernel packages. 1pip install saspy 2pip install sas_kernel Once installed the …

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Metadata can be included in the yaml header of an RMarkdown document. The yaml can store metadata in the params parameter or as individual yaml parameters. For example, the RMarkdown file below adds some metadata parameters to the header: short_title, reference and meta_list. The rmarkdown function rmarkdown::metadata …

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This post describes three ways to tag functions with metadata. Attributes Using attributes is a simple way to add metadata to any object in R. Data frames and other objects already use attributes to hold metadata which are accessible via the attributes function. 1df <- data.frame(a = 1:5, b = letters[1:5]) 2 3## …

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Quarto is the new publishing system from RStudio based on Pandoc. It's a powerful tool for publising from R, Python and Julia, working in a very similar fashion to RMarkdown. There are several great blog posts already highlighting features of Quarto and thoughts on changing from RMarkdown to Quarto. Recently, I've been …

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This post expands upon the post on {distill} Comments. It includes a method to reply to comments and store comments and replies in an hierarchical manner. In the previous post I covered how we could use RStudio Connect to manage commenting on a static blog. Here we extend it, adding a way to reply to comments and store …

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