# Working with R and JS Types

    library(QuickJSR)

## Mappings and Conversions Between R and JS Types

`QuickJSR` uses the respective `C` APIs of `R` and `QuickJS` in order to pass values between the two. This allows for increased efficiency in passing and returning values (as no serialisation or de-serialisation is required) and also allows for greater flexibility in working with R closures, functions, and environments in JS code.

`QuickJSR` aims to broadly follow the conventions of `jsonlite` in terms of how R types are converted to JS types and vice-versa.

### Primitive & Scalar Types

The following table outlines the basic mappings of primitive types between R and JS types:

R Type | JS Type
--- | ---
NULL | null
logical | boolean
integer | number
double | number
character | string
date | date
POSIXct | date
factor | string

Note that the handling of `Date`/`POSIXct` types differs from `jsonlite`, where they are converted to strings. In `QuickJSR`, they are treated directly as `Date` objects in JS.

### Container Types

The following table outlines the basic mappings of container types between R and JS types:

R Type | JS Type
--- | ---
named list | object
unnamed list | array
vector | array
array | array
matrix | 2D number array
data.frame | array of objects

Examples of the `matrix` and `data.frame` conversions are shown below:

    m <- matrix(1:6, nrow = 2)
    cat(to_json(m))
    #> [[1,3,5],[2,4,6]]

    df <- data.frame(a = 1:3, b = c("x", "y", "z"))
    cat(to_json(df))
    #> [{"a":1,"b":"x"},{"a":2,"b":"y"},{"a":3,"b":"z"}]

Note that the `to_json()` function operates by converting R objects to their JS equivalents, and then calling `JSON.stringify()` on the result. This allows you to explore how different types are being converted to JS.

### Functions and Closures

Functions and closures can be passed between R and JS code. In JS, functions are represented as `Function` objects, and can be called directly from JS code.

    ctx <- JSContext$new()
    ctx$source(code = "function callRFunction(f, x, y) { return f(x, y); }")

    ctx$call("callRFunction", function(x, y) x + y, 1, 2)
    #> [1] 3
    ctx$call("callRFunction", function(x, y) paste0(x, ",", y), "a", "b")
    #> [1] "a,b"

## Working with R Environments

R environments are represented in JS as a custom class: `REnv`. The `REnv` class simply wraps the pointer to the R environment, and provides methods for getting and setting values - this means that there is only a ‘cost’ for conversion when values or accessed or updated.

Environment values can be accessed using either `env.value` or `env["value"]` syntax:

    ctx$source(code = 'function env_test(env) { return env.a + env["b"]; }')
    env <- new.env()
    env$a <- 1
    env$b <- 2
    ctx$call("env_test", env)
    #> [1] 3

Values in the environment can also be updated from JS code:

    ctx$source(code = "function env_update(env) { env.a = 10; env.b = 20; }")
    ctx$call("env_update", env)
    #> NULL
    env$a
    #> [1] 10
    env$b
    #> [1] 20

## Accessing Package Namespaces & Functions

`QuickJSR` automatically adds a global object `R` to each context, which can be used to access the namespaces of installed packages - and subsequently extract and use functions and objects from them.

    qjs_eval('R.package("base").getwd()')
    #> [1] "/tmp/RtmpFpozrw/Rbuild1a660031db1a58/QuickJSR/vignettes"