V8 is Google’s open source, high performance JavaScript engine. It is written in C++ and implements ECMAScript as specified in ECMA-262, 5th edition. The V8 R package builds on the C++ library to provide a completely standalone JavaScript engine within R:
# Create a new context
ct <- v8()
# Evaluate some code
ct$eval("var foo = 123")
ct$eval("var bar = 456")
ct$eval("foo + bar")
[1] "579"
A major advantage over the other foreign language interfaces is that V8 requires no compilers, external executables or other run-time dependencies. The entire engine is contained within a 6MB package (2MB zipped) and works on all major platforms.
{"x":0.6072914263572589}
[1] "124"
However note that V8 by itself is just the naked JavaScript engine. Currently, there is no DOM (i.e. no window object), no network or disk IO, not even an event loop. Which is fine because we already have all of those in R. In this sense V8 resembles other foreign language interfaces such as Rcpp or rJava, but then for JavaScript.
The ct$source
method is a convenience function for
loading JavaScript libraries from a file or url.
[1] "true"
[1] "true"
By default all data interchange between R and JavaScript happens via JSON using the bidirectional mapping implemented in the jsonlite package.
mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
Alternatively use JS()
to assign the value of a
JavaScript expression (without converting to JSON):
[1] 81
The ct$call
method calls a JavaScript function,
automatically converting objects (arguments and return value) between R
and JavaScript:
mpg cyl disp hp drat wt qsec vs am gear carb
Duster 360 14.3 8 360 245 3.21 3.570 15.84 0 0 3 4
Cadillac Fleetwood 10.4 8 472 205 2.93 5.250 17.98 0 0 3 4
Lincoln Continental 10.4 8 460 215 3.00 5.424 17.82 0 0 3 4
Chrysler Imperial 14.7 8 440 230 3.23 5.345 17.42 0 0 3 4
Camaro Z28 13.3 8 350 245 3.73 3.840 15.41 0 0 3 4
It looks a bit like .Call
but then for JavaScript
instead of C.
If a call to ct$eval()
, ct$get()
, or
ct$call()
returns a JavaScript promise, you can set
await = TRUE
to wait for the promise to be resolved. It
will then return the result of the promise, or an error in case the
promise is rejected.
js = 'function test_number(x){
var promise = new Promise(function(resolve, reject) {
if(x == 42)
resolve(true)
else
reject("This is wrong")
})
return promise;
}'
# Call will just show a promise
ctx <- V8::v8()
ctx$eval(js)
# A promise does not return anything in itself:
ctx$call("test_number", 42)
named list()
[1] TRUE
Error: This is wrong
A fun way to learn JavaScript or debug a session is by entering the interactive console:
From here you can interactively work in JavaScript without typing
ct$eval
every time:
var cf = crossfilter(diamonds)
var price = cf.dimension(function(x){return x.price})
var depth = cf.dimension(function(x){return x.depth})
price.filter([2000, 3000])
output = depth.top(10)
To exit the console, either press ESC
or type
exit
. Afterwards you can retrieve the objects back into
R:
Evaluating invalid JavaScript code results in a SyntaxError:
Error: SyntaxError: Unexpected token '<'
JavaScript runtime exceptions are automatically propagated into R errors:
Error: ReferenceError: doesnotexit is not defined
Within JavaScript we can also call back to the R console manually
using console.log
, console.warn
and
console.error
. This allows for explicitly generating
output, warnings or errors from within a JavaScript application.
this is a message
Warning: Heads up!
Error: Oh no! An error!
A example of using console.error
is to verify that
external resources were loaded:
Unlike what you might be used to from Node or your browser, the
global namespace for a new context is very minimal. By default it
contains only a few objects: global
(a reference to
itself), console
(for console.log
and friends)
and print
(an alias of console.log needed by some
JavaScript libraries)
[1] "print" "console" "global"
A context always has a global scope, even when no name is set. When a
context is initiated with global = NULL
, it can still be
reached by evaluating the this
keyword within the global
scope:
[1] 1
ct2$assign("cars", cars)
ct2$eval("var foo = 123")
ct2$eval("function test(x){x+1}")
ct2$get(JS("Object.keys(this).length"))
[1] 4
[1] "print" "cars" "foo" "test"
To create your own global you could use something like:
ct2$eval("var __global__ = this")
ct2$eval("(function(){var bar = [1,2,3,4]; __global__.bar = bar; })()")
ct2$get("bar")
[1] 1 2 3 4
V8 also allows for validating JavaScript syntax, without actually evaluating it.
[1] TRUE
[1] TRUE
This might be useful for all those R libraries that generate browser graphics via templated JavaScript. Note that JavaScript does not allow for defining anonymous functions in the global scope:
[1] FALSE
To check if an anonymous function is syntactically valid, prefix it
with !
or wrap in ()
. These are OK:
[1] TRUE
[1] TRUE
A recently added feature is to interact with R from within JavaScript
using the console.r
API`. This is most easily demonstrated
via the interactive console.
From JavaScript we can read/write R objects via
console.r.get
and console.r.assign
. The final
argument is an optional list specifying arguments passed to
toJSON
or fromJSON
.
// read the iris object into JS
var iris = console.r.get("iris")
var iris_col = console.r.get("iris", {dataframe : "col"})
//write an object back to the R session
console.r.assign("iris2", iris)
console.r.assign("iris3", iris, {simplifyVector : false})
To call R functions use console.r.call
. The first
argument should be a string which evaluates to a function. The second
argument contains a list of arguments passed to the function, similar to
do.call
in R. Both named and unnamed lists are supported.
The return object is returned to JavaScript via JSON.
//calls rnorm(n=2, mean=10, sd=5)
var out = console.r.call('rnorm', {n: 2,mean:10, sd:5})
var out = console.r.call('rnorm', [2, 20, 5])
//anonymous function
var out = console.r.call('function(x){x^2}', {x:12})
There is also an console.r.eval
function, which
evaluates some code. It takes only a single argument (the string to
evaluate) and does not return anything. Output is printed to the
console.
Besides automatically converting objects, V8 also propagates exceptions between R, C++ and JavaScript up and down the stack. Hence you can catch R errors as JavaScript exceptions when calling an R function from JavaScript or vice versa. If nothing gets caught, exceptions bubble all the way up as R errors in your top-level R session.