QuartoLive

QuartoLive allows to run interactive R and Python code in static quarto documents using WebR. QuartoLive supports interactive exercises and rich output. QuartoLive is documented here.

1 Installation

Install webr extension for quarto by running:

quarto add r-wasm/quarto-live

then add to yaml:

format: live-html
engine: knitr

For knitr, the following line must be added after yaml, for now:

{{< include ./_extensions/r-wasm/live/_knitr.qmd >}}

2 Interactive editor

webR-enabled code cells are established by using {webr} or {pyodide} in a Quarto HTML document.

```{webr}
for (x in 1:5) {
  print(x ** 2)
}
```

```{pyodide}
for x in range(1, 6):
  print(10 + x)
```

Default table style can be set under yaml:

webr:
  render-df: paged-table

Other options are kable, paged-table, gt, gt-interactive, DT and reactable.

Additional yaml chunk options are

• edit: true: Allow code chunk to be edited?
• autorun: true: Should code chunk be automatically executed?
• runbutton: true: Show run button?
• caption: bla: Chunk title
• completion: true: Allow code completion?
• startover: true: Allow initial code to be reset?
• persist: true: Locally save user entered content?
• timelimit: Set upper bound for execution time. Default is 30 seconds
• min-lines,max-lines: Fix editor height
• fig-height,fig-width: Figure height and width

3 Installing packages

3.1 On setup

To install packages on launch, add to yaml.

webr:
  packages:
    - dplyr
    - ggplot2

3.2 In chunks

```{webr}
install.packages("dplyr", quiet = TRUE)
library(dplyr)
```

4 Resources

Resources can be defined which are made available to webr.

---
format: live-html
resources:
  - data
  - https://raw.githubusercontent.com/mwaskom/seaborn-data/master/flights.csv
---

```{webr}
list.files("data")
mt <- read.csv("data/mtcars.csv")
mod <- glm(mpg ~ cyl, data = mt)
summary(mod)
```

```{webr}
flights <- read.csv("flights.csv")
with(flights, plot(year, passengers))
```