─ Session info ───────────────────────────────────────────────────────────────
setting value
version R version 4.3.1 (2023-06-16)
os macOS Monterey 12.6.9
system x86_64, darwin20
ui X11
language (EN)
collate en_US.UTF-8
ctype en_US.UTF-8
tz America/New_York
date 2023-09-26
pandoc 3.1.1 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/ (via rmarkdown)
─ Packages ───────────────────────────────────────────────────────────────────
package * version date (UTC) lib source
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colorspace 2.1-0 2023-01-23 [1] CRAN (R 4.3.0)
digest 0.6.33 2023-07-07 [1] CRAN (R 4.3.0)
dplyr 1.1.2 2023-04-20 [1] CRAN (R 4.3.0)
evaluate 0.21 2023-05-05 [1] CRAN (R 4.3.0)
fansi 1.0.4 2023-01-22 [1] CRAN (R 4.3.0)
fastmap 1.1.1 2023-02-24 [1] CRAN (R 4.3.0)
generics 0.1.3 2022-07-05 [1] CRAN (R 4.3.0)
ggplot2 * 3.4.3 2023-08-14 [1] CRAN (R 4.3.0)
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gtable 0.3.3 2023-03-21 [1] CRAN (R 4.3.0)
htmltools 0.5.5 2023-03-23 [1] CRAN (R 4.3.0)
htmlwidgets 1.6.2 2023-03-17 [1] CRAN (R 4.3.0)
jsonlite 1.8.7 2023-06-29 [1] CRAN (R 4.3.0)
knitr 1.43 2023-05-25 [1] CRAN (R 4.3.0)
lifecycle 1.0.3 2022-10-07 [1] CRAN (R 4.3.0)
lubridate * 1.9.2 2023-02-10 [1] CRAN (R 4.3.0)
magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.3.0)
munsell 0.5.0 2018-06-12 [1] CRAN (R 4.3.0)
pillar 1.9.0 2023-03-22 [1] CRAN (R 4.3.0)
pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.3.0)
R6 2.5.1 2021-08-19 [1] CRAN (R 4.3.0)
rlang 1.1.1 2023-04-28 [1] CRAN (R 4.3.0)
rmarkdown 2.23 2023-07-01 [1] CRAN (R 4.3.0)
rstudioapi 0.15.0 2023-07-07 [1] CRAN (R 4.3.0)
scales 1.2.1 2022-08-20 [1] CRAN (R 4.3.0)
sessioninfo * 1.2.2 2021-12-06 [1] CRAN (R 4.3.0)
shinylive * 0.1.0 2023-09-25 [1] Github (posit-dev/r-shinylive@77c775a)
tibble 3.2.1 2023-03-20 [1] CRAN (R 4.3.0)
tidyselect 1.2.0 2022-10-10 [1] CRAN (R 4.3.0)
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utf8 1.2.3 2023-01-31 [1] CRAN (R 4.3.0)
vctrs 0.6.3 2023-06-14 [1] CRAN (R 4.3.0)
withr 2.5.0 2022-03-03 [1] CRAN (R 4.3.0)
xfun 0.39 2023-04-20 [1] CRAN (R 4.3.0)
yaml 2.3.7 2023-01-23 [1] CRAN (R 4.3.0)
[1] /Users/max/Library/R/x86_64/4.3/library
[2] /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/library
──────────────────────────────────────────────────────────────────────────────shinylive-in-book-test
Preface
For writing online books (with Quarto), I’d like to be able to demonstrate concepts and results dynamically. To some extent, we can do this with gganimate, but it is very limiting.
We’d like to use shiny. At the 2023 posit conference, Joe Cheng unveiled shinylive-r, a tool to embed R and shiny into a webpage using WebAssembly (aka Wasm) using webR.
This repo is a work in progress since we (Posit) have not fully worked out all of the details (as of today: 2023-09-26). Also, initial testing will allow developers to make APIs to make things more easy to use.
The example use case that I’ll use to test is to show how natural splines can affect the classification boundaries produced via logistic regression. Using a simulated data set, we want to show the resulting class boundary curve for a given number of degrees of freedom for the splines. The user should be able to modify these and see the results.
The next “chapter” has code to pre-compute the results instead of doing them in shiny (which might be too time-consuming). You can skip that if you are not interested; we generate a validation set of data points (sim_val) to plot and a data frame of predictions that are used to compute the class boundaries using a contour plot (predicted_values). These are the main inputs in the shiny app.
The third chapter is about the shiny app.
Software
I used a recent version of R (R version 4.3.1 (2023-06-16)), the latest daily release of the RStudio IDE, and the latest quarto (version 1.4.376).
I installed the shinylive Quarto extension:
shell> quarto add quarto-ext/shinyliveand also the corresponding R package (I suggest using R’s pak package):
R> pak::pak("posit-dev/r-shinylive")Versions:
Thanks
Thanks to George Stagg, Joe Cheng, Winston Chang, and everyone else who made webR and shinylive happen.