This article covers several aspects of creating widgets that are not required by all widgets, but are an essential part of getting bindings to certain types of JavaScript libraries to work properly. Topics covered include:
Transforming JSON representations of R objects into representations required by JavaScript libraries (e.g. an R data frame to a d3 dataset).
Tracking instance-specific widget data within JavaScript bindings.
Passing JavaScript functions from R to JavaScript (e.g. a user provided formatting or drawing function)
Generating custom HTML to enclose a widget (the default is a <div> but some libraries require a different element e.g. a <span>).
R objects passed as part of the x parameter to the createWidget() function are transformed to JSON using the internal function htmlwidgets:::toJSON()1, which is basically a wrapper function of jsonlite::toJSON() by default. However, sometimes this representation is not what is required by the JavaScript library you are interfacing with. There are two JavaScript functions that you can use to transform the JSON data.
R data frames are represented in “long” form (an array of named vectors) whereas d3 typically requires “wide” form (an array of objects each of which includes all names and values). Since the R representation is smaller in size and much faster to transmit over the network, we create the long-form representation of R data, and then transform the data in JavaScript using the dataframeToD3() helper function.
Here is an example of the long-form representation of an R data frame:
{
"Sepal.Length": [5.1, 4.9, 4.7],
"Sepal.Width": [3.5, 3, 3.2],
"Petal.Length": [1.4, 1.4, 1.3],
"Petal.Width": [0.2, 0.2, 0.2],
"Species": ["setosa", "setosa", "setosa"]
} After we apply HTMLWidgets.dataframeToD3(), it will become:
[
{
"Sepal.Length": 5.1,
"Sepal.Width": 3.5,
"Petal.Length": 1.4,
"Petal.Width": 0.2,
"Species": "setosa"
},
{
"Sepal.Length": 4.9,
"Sepal.Width": 3,
"Petal.Length": 1.4,
"Petal.Width": 0.2,
"Species": "setosa"
},
{
"Sepal.Length": 4.7,
"Sepal.Width": 3.2,
"Petal.Length": 1.3,
"Petal.Width": 0.2,
"Species": "setosa"
}
] As a real example, the simpleNetwork widget accepts a data frame containing network links on the R side, then transforms it to a d3 representation within the JavaScript renderValue function:
renderValue: function(el, x, instance) {
// convert links data frame to d3 friendly format
var links = HTMLWidgets.dataframeToD3(x.links);
// ... use the links, etc ...
}Sometimes a 2-dimensional array requires a similar transposition. For this the transposeArray2D() function is provided. Here is an example array:
[
[5.1, 4.9, 4.7, 4.6, 5, 5.4, 4.6, 5],
[3.5, 3, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4],
[1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5],
[0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2],
["setosa", "setosa", "setosa", "setosa", "setosa", "setosa", "setosa", "setosa"]
] HTMLWidgets.transposeArray2D() can transpose it to:
[
[5.1, 3.5, 1.4, 0.2, "setosa"],
[4.9, 3, 1.4, 0.2, "setosa"],
[4.7, 3.2, 1.3, 0.2, "setosa"],
[4.6, 3.1, 1.5, 0.2, "setosa"],
[5, 3.6, 1.4, 0.2, "setosa"],
[5.4, 3.9, 1.7, 0.4, "setosa"],
[4.6, 3.4, 1.4, 0.3, "setosa"],
[5, 3.4, 1.5, 0.2, "setosa"]
] As a real example, the dygraphs widget uses this function to transpose the “file” (data) argument it gets from the R side before passing it on to the dygraphs library:
renderValue: function(el, x, instance) {
// ... code excluded ...
// transpose array
attrs.file = HTMLWidgets.transposeArray2D(attrs.file);
// ... more code excluded ...
}You may find it necessary to customize the JSON serialization of widget data when the default serializer in htmlwidgets does not work in the way you have expected. For widget package authors, there are two levels of customization for the JSON serialization: you can either customize the default values of arguments for jsonlite::toJSON(), or just customize the whole function.
jsonlite::toJSON() has a lot of arguments, and we have already changed some of its default values. Below is the JSON serializer we use in htmlwidgets at the moment:
function (x, ..., dataframe = "columns", null = "null", na = "null",
auto_unbox = TRUE, digits = getOption("shiny.json.digits",
16), use_signif = TRUE, force = TRUE, POSIXt = "ISO8601",
UTC = TRUE, rownames = FALSE, keep_vec_names = TRUE)
{
jsonlite::toJSON(I(x), dataframe = dataframe, null = null,
na = na, auto_unbox = auto_unbox, digits = digits, use_signif = use_signif,
force = force, POSIXt = POSIXt, UTC = UTC, rownames = rownames,
keep_vec_names = keep_vec_names, json_verbatim = TRUE,
...)
}For example, we convert data frames to JSON by columns instead of rows (the latter is jsonlite::toJSON’s default). If you want to change the default values of any arguments, you can attach an attribute TOJSON_ARGS to the widget data to be passed to createWidget(), e.g.
fooWidget <- function(data, name, ...) {
# ... process the data ...
params <- list(foo = data, bar = TRUE)
# customize toJSON() argument values
attr(params, 'TOJSON_ARGS') <- list(digits = 7, na = 'string')
htmlwidgets::createWidget(name, x = params, ...)
}We changed the default value of digits from 16 to 7, and na from null to string in the above example. It is up to you, the package author, whether you want to expose such customization to users. For example, you can leave an extra argument in your widget function so that users can customize the behavior of the JSON serializer:
fooWidget <- function(data, name, ..., JSONArgs = list(digits = 7)) {
# ... process the data ...
params <- list(foo = data, bar = TRUE)
# customize toJSON() argument values
attr(params, 'TOJSON_ARGS') <- JSONArgs
htmlwidgets::createWidget(name, x = params, ...)
}You can also use a global option htmlwidgets.TOJSON_ARGS to customize the JSON serializer arguments for all widgets in the current R session, e.g.
options(htmlwidgets.TOJSON_ARGS = list(digits = 7, pretty = TRUE))If you do not want to use jsonlite, you can completely override the serializer function by attaching an attribute TOJSON_FUNC to the widget data, e.g.
fooWidget <- function(data, name, ...) {
# ... process the data ...
params <- list(foo = data, bar = TRUE)
# customize the JSON serializer
attr(params, 'TOJSON_FUNC') <- MY_OWN_JSON_FUNCTION
htmlwidgets::createWidget(name, x = params, ...)
}Here MY_OWN_JSON_FUNCTION can be an arbitrary R function that converts R objects to JSON. If you have also specified the TOJSON_ARGS attribute, it will be passed to your custom JSON function as well.
Note these features about custom JSON serializers require the shiny version to be greater than 0.11.1 if you render the widgets in Shiny apps.
You may have noticed that the JavaScript binding for a widget consists of a set of JavaScript functions rather than a class which has its own instance data. Many widgets do not require instance data, but if yours does (e.g. you need to save a JS library provided object, reference to a DOM element, or any other computed data) there is a mechanism available to do so.
Here is how it works: return an object from the initialize method and that object will subsequently be passed to the renderValue and resize methods. For example:
HTMLWidgets.widget({
name: "demo",
type: "output",
initialize: function(el, width, height) {
// object we'll use for instance data
return {};
},
renderValue: function(el, x, instance) {
// access instance as necessary
},
resize: function(el, width, height, instance) {
// access instance as necessary
}
});A real-life example of using instance data is in the dygraphs widget, which uses the instance to store the actual Dygraph object for later manipulation. You can see the code for the dygraphs JavaScript binding that takes advantage of instance data.
As you would expect, character vectors passed from R to JavaScript are converted to JavaScript strings. However, what if you want to allow users to provide custom JavaScript functions for formatting, drawing, or event handling? For this case, the htmlwidgets package includes a JS() function that allows you to request that a character value is evaluated as JavaScript when it is received on the client.
For example, the dygraphs widget includes a dyCallbacks function that allows the user to provide callback functions for a variety of contexts. These callbacks are “marked” as containing JavaScript so that they can be converted to actual JavaScript functions on the client:
callbacks <- list(
clickCallback = JS(clickCallback)
drawCallback = JS(drawCallback)
highlightCallback = JS(highlightCallback)
pointClickCallback = JS(pointClickCallback)
underlayCallback = JS(underlayCallback)
)Another example is in the DT (DataTables) widget, where users can specify an initCallback with JavaScript to execute after the table is loaded and initialized:
datatable(head(iris, 20), options = list(
initComplete = JS(
"function(settings, json) {",
"$(this.api().table().header()).css({'background-color': '#000', 'color': '#fff'});",
"}")
))If multiple arguments are passed to JS() (as in the above example), they will be concatenated into a single string separated by \n.
Typically the HTML “housing” for a widget is just a <div> element, and this is correspondingly the default behavior for new widgets that don’t specify otherwise. However, sometimes you need a different element type. For example, the sparkline widget requires a <span> element so implements the following custom HTML generation function:
sparkline_html <- function(id, style, class, ...){
tags$span(id = id, class = class)
}Note that this function is looked up within the package implementing the widget by the convention widgetname_html so it need not be formally exported from your package or otherwise registered with htmlwidgets.
Most widgets won’t need a custom HTML function but if you need to generate custom HTML for your widget (e.g. you need an <input> or a <span> rather than a <div>) then you should use the htmltools package (as demonstrated by the code above).
N.B. It is not exported from htmlwidgets, so you are not supposed to call this function directly.↩