Sass is the most widely used, feature rich, and stable CSS extension language available. It has become an essential tool in modern web development because of its ability to reduce complexity and increase composability when styling a website. For a basic example, suppose you want to use the same color for multiple styling rules in your website (e.g., hyperlinks and buttons). With CSS, you’d have to repeat that color every time it is used in styling rule, so in a large project, changing at a later point can be tedious and error-prone.
With Sass, you could store this color in a Sass variable and use it in the styling rules to produce the same CSS, resulting in a single entry point for the color’s value. This simple Sass tool can make CSS styling a lot easier to reason about, making styles a lot easier to customize and maintain.
Sass variables are not the only Sass tool useful for reducing complexity. For Sass and sass newcomers, this vignette first covers how to use basic Sass tools like variables, mixins, and functions in the sass R package. After the basics, you’ll also learn how to write composable sass that allows users to easily override your styling defaults and developers to include your Sass in their styling projects. You’ll also learn how to control the CSS output (e.g., compress and cache it), and how to use it in shiny & rmarkdown.
By mastering these concepts, you’ll not only be able to leverage the
advantages of using Sass over CSS, but you’ll also have the basis needed
to develop R interfaces to Sass projects that allow users to easily
customize your styling templates without any knowledge of
Sass/CSS. For an example, see the bslib R
package, which provides a interface to Bootstrap
Sass through easy-to-use functions like
bs_theme_add_variables()
.
Sass variables are
a great mechanism for simplifying and exposing CSS logic to users. To
create a variable, assign a value (likely a CSS property
value) to a name, then refer to it by name in downstream Sass code.
In this minimal example, we create a body-bg
variable then
use it to generate a single style rule,
but as we’ll see later, variables can also be used inside of other
arbitrary Sass code (e.g., functions, mixins, etc).
library(sass)
variable <- "$body-bg: red;"
rule <- "body { background-color: $body-bg; }"
sass(input = list(variable, rule))
A more convenient and readable way to create Sass variables in R is
to use a named list()
. Also, it’s a good idea to add the
!default
flag after the value since it provides users of
your Sass an opportunity to set their own value. We’ll learn more about
defaults in layering, but for now, just note
that the !default
flag says use this value only if that
variable isn’t already defined:
Sass comes with a variety of built-in
functions (i.e., you don’t have to import
anything to start using them) which are useful for working with CSS
values (colors, numbers, strings,
etc). These built-in functions are primarily useful modifying or
combining CSS values in such a way that isn’t possible with CSS. Here we
use the rgba()
to add alpha blending to black
and assign the result to a variable.1
Sass also provides the ability to define your own functions through
the @function
at-rule. Like functions in most languages, there are four main
components to a function definition: (1) the function name
,
(2) the function argument/inputs (e.g., arg1
,
arg2
), (3) the function body which contains statements
(i.e., statement1
, statement2
, etc.), and
finally (4) a return value
.
For an example of where creating your function becomes useful,
consider this color-contrast()
function, inspired by this
SO answer to a common problem that arises when allowing users
control over background color of something (e.g., the document body).
We’d like to strive for styling rules that are smart enough to overlay
white text on a dark colored background and black text on a light
colored background. color-contrast()
helps us achieve this
since, given a dark color, it returns white; and given a light color, it
returns black.
@function color-contrast($color) {
@return if(
red($color) * 0.299 + green($color) * 0.587 + blue($color) * 0.114 > 186,
black, white
);
}
By saving this function to a file named
color-contrast.scss
, it can then be imported and used in the following way. For a live
example of this in action, consider this Shiny app which
allows the user to interactively choose a background color and the
title’s font color automatically updates to an appropriate color
contrast. See here for more on allowing
shiny users to influence styling on the page using
sass.
sass(
list(
variable,
sass_file("color-contrast.scss"),
"body {
background-color: $body-bg;
color: color-contrast($body-bg);
}"
)
)
NOTE: bslib::bs_theme()
provides it’s
own, more sophisticated, version of color-contrast()
that
you can use like so:
sass::sass_partial("body{color: color-contrast($body-bg)}", bs_theme())
In practice, you’ll want to write your Sass code in
.scss
(or
.sass
) files (instead of inside R strings). That way
you can leverage things like syntax highlighting in RStudio (or your
favorite IDE) and make it easier for others to import your Sass into
their workflow. For example, if I have .scss
file in my
working directory, say my-style.scss
, I can compile it this
way:
This works because sass_file()
uses
sass_import()
to generate an @import
at-rule.
If you visit the docs for
@import
, you’ll notice there’s more you can do that
import local .scss
, like import local or remote
.css
files, import font files, and more. Note also that
{sass}
also provides tools that make importing of local
font files easier – see font_google()
to learn more.
Importing font file(s) directly in Sass/CSS/HTML can be a headache to
implement. This is especially true if you want to serve font files so
that a custom font renders on any client machine, even if the client is
without an internet connection. To make this easier, {sass}
provides a font_google()
which can be used to download,
cache, import, and serve the relevant font files all at once.
library(htmltools)
my_font <- list("my-font" = font_google("Pacifico"))
css <- sass(
list(
my_font,
list("body {font-family: $my-font}")
)
)
shinyApp(
fluidPage(
"Hello",
tags$style(css)
),
function(...) {}
)
To import non-Google fonts, use either font_link()
or
font_face()
. The former is for importing fonts via a remote
URL whereas the former could be use to import any font locally (or
remotely).
Similar to how functions are useful for encapsulating
computation in a reusable unit, mixins
are useful for doing the same with styling rules (i.e.,
packaging them into a reusable unit). Technically speaking, mixins are
similar to functions in that they require a name
, may have
arguments, as well as any number of statements. However, they differ in
that they require the return value to be a style rule,
and when called, need to be @include
d in a larger style
rule in order to generate any CSS.
For some examples, please see the Sass mixin documentation.
This vignette intentionally doesn’t try to re-invent the existing and wonderful Sass documentation. There you’ll find many more useful things as you start to write more Sass, such as control flow, lists, maps, interpolation, and more.
To make Sass code more composable with other Sass code (e.g.,
allowing others to change your variable defaults or import a function or
mixin you’ve defined), consider partitioning your Sass code into a
sass::sass_layer()
. The main idea is to split your Sass
into 4 parts: functions
,
defaults
(i.e. variable defaults),
mixins
, and rules
(i.e.,
styling rules).
layer1 <- sass_layer(
functions = sass_file("color-contrast.scss"),
defaults = list("body-bg" = "black !default"),
rules = "body{background-color: $body-bg; color: color-contrast($body-bg)}"
)
as_sass(layer1)
This allows downstream sass_layer()
s to be
sass_bundle()
d into a single layer, where
defaults
in downstream layers are granted higher priority.
More specifically, this means:
defaults
for layer2
are placed
before defaults
for layer1
.
rules
for layer2
are placed after
rules
for layer1
.
layer2 <- sass_layer(
defaults = list("body-bg" = "white !default")
)
sass(sass_bundle(layer1, layer2))
Another problem that sass_layer()
helps solve is that
sometimes your Sass code might want to import a
local file using a relative path that you know how to resolve,
but not necessarily the person who eventually compiles your Sass. To
solve this issue, provide a named character vector to
file_attachments
, pointing the relevant relative path(s) to
the appropriate absolute path(s). Here’s a contrived example of how that
might look (here’s
a more real example of using it in an R package).
Another problem that sass_layer()
helps solve is that
sometimes you want to attach other HTML dependencies to your Sass/CSS
(e.g., JavaScript, other CSS, etc). For this reason,
sass_layer()
has a html_deps
argument to which
you can provide htmltools::htmlDependency()
objects.
sass()
preserves these, as well as any other HTML
dependencies attached to it’s input, by including them in the return
value. This ensures that, when you include sass()
in rmarkdown or shiny those dependencies come
along for the ride.
DISCLAIMER: If you want to use this feature
and include CSS as a file in shiny,
you’ll need to call htmltools::htmlDependencies()
on the
return value of sass()
to get the dependencies, then
include them in your user interface definition.
The sass()
function provides a few arguments for
controlling the CSS output it generates, including output
,
options
, and cache_options
. The following
covers some of the most important options available.
If the CSS generated from sass()
can be useful in more
than one place, consider writing it to a file (instead of returning it
as a string). To write CSS to a file, give a suitable file path to
sass()
’s output
argument.
By default, sass()
outputs 'expanded'
CSS
meaning there are lots of white-space and line-breaks included to make
it more readable by humans. Computers don’t need all those unnecessary
characters, so to speed up your page load time when you go to include
the CSS in shiny or rmarkdown, consider removing them
altogether with output_style = "compressed"
:
When compressing the CSS output, it can be useful to include a source map so that it’s
easier to inspect the CSS from the website. The easiest way to include a
source map is to set source_map_embed = TRUE
:
Sometimes calling sass()
can be computationally
expensive, in which case, it can be useful to leverage its caching
capability. Caching is enabled by default, unless Shiny’s Developer Mode
(shiny::devmode()
) is enabled. To explicitly enable
(disable), set options(sass.cache = )
to TRUE
(or FALSE
):
You can also configure the location, size, and age of file caching
via sass_file_cache()
, which can be passed directly to a
sass()
call:
Or used with sass_cache_set_dir()
to configure the file
cache globally:
Note that the location of the file cache defaults to
sass_cache_context_dir()
, which depends on the context in
which it’s running. When inside a Shiny app, the cache location is
relative to the app’s directory so the cache can persist and be shared
across R processes. Otherwise, the context directory is a OS and package
specific caching directory.
There are two basic approaches to including the CSS that
sass()
returns as HTML in your shiny app.
If you’re curious, the official shiny article on
CSS has more details with a couple different approaches. Regardless
of the approach, consider leveraging compressing and caching
the CSS output to make your app faster to load.
The character string that sass()
returns is already
marked as HTML()
2, so to include it in your
shiny app, wrap it in a <style>
tag.
It’s not necessary to place this tag in the <head>
of
the document, but it’s good practice:
To write CSS to a file, give a suitable file path to
sass()
’s output
argument. Here we write to a
specially named www/
subdirectory so that
shiny will automatically make those file(s) available
to the web app.
Sometimes it’s useful to allow users of your shiny
app to be able to influence your app’s styling via
shiny input(s). One way this can be done is via dynamic
UI, where you use renderUI()
/uiOutput()
to
dynamically insert CSS as an HTML string
whenever a relevant input changes. Be aware, however, that whenever you
allow dynamic user input to generate HTML()
, you’re leaving
yourself open to security vulnerabilites; so try to avoid it, and
never allow clients to enter free form textInput()
without any sort of sanitation of the user input.
Consider this basic example of using a colourInput()
widget (from the colourpicker package) to choose the
body’s background color, which triggers a call to
sass()
:
library(shiny)
ui <- fluidPage(
headerPanel("Sass Color Example"),
colourpicker::colourInput("color", "Background Color", value = "#6498d2", showColour = "text"),
uiOutput("sass")
)
server <- function(input, output) {
output$sass <- renderUI({
tags$head(tags$style(css()))
})
css <- reactive({
sass::sass(list(
list(color = input$color),
"body { background-color: $color; }"
))
})
}
shinyApp(ui, server)
Below are a few more sophisticated examples of dynamic input:
shiny::runApp(system.file("sass-font", package = "sass"))
shiny::runApp(system.file("sass-size", package = "sass"))
shiny::runApp(system.file("sass-theme", package = "sass"))
knitr recently gained a
Sass engine powered by the sass package. This means you
can write Sass code directly into a code sass
chunk and the
resulting CSS will be included in the resulting document (The
echo = FALSE
prevents the Sass code from being shown in the
resulting document).
```{sass, echo = FALSE}
$body-bg: red;
body{
background-color: $body-bg;
}
```
If you like to write R sass code instead, you can do
that as well, and by default it works similarly to the sass
engine (except that the sass-specific code chunk options will be
ignored, but you can specify those options via
sass::sass()
instead).
```{r, echo = FALSE}
sass(sass_file("my-style.scss"))
```
If syntax highlighting is enabled in your output document , it’s also
possible to display the generated CSS (instead of embedding it as HTML)
with syntax highlighting by setting the code chunk options
class.output='css'
and comment=''
.
Unfortunately, for some output formats, like
rmarkdown::html_vignette()
, syntax hightlighting isn’t
supported, but for output formats like
rmarkdown::html_document()
, you can enable syntax
highlighting by setting the highlight
parameter to a
non-default value (e.g., tango
).
```{r, class.output='css', comment=''}
sass(sass_file("my-style.scss"))
```
Oh, by the way, the value of a variable may be an expression.↩︎
Including dynamic user
input directly as HTML()
, especially with free form
inputs like textInput()
, is a security vulnerability. Avoid
it if you can.↩︎