Adding `extendr_api` library as a dependency

Run this command in a terminal, in your project's directory:

cargo add extendr-api

To add it manually, edit your project's Cargo.toml file and add to the [dependencies] section:

extendr-api = "0.9.0"

The extendr_api library will be automatically available globally. Read the extendr_api library documentation.

Back to the crate overview.

Readme

`extendr-api`

extendr-api is an opinionated, ergonomic, and safe interface to R API.

Installation

Simply add this line to the [dependencies] section of your Cargo.toml. You will then be able to call R code from Rust.

[dependencies]
extendr-api = "0.8.0"

About

On the extendr homepage there is a comprehensive user-guide.

The API documentation on doc.rs, and for development API documentation.

Overview

See Robj for much of the content of this crate. Robj provides a safe wrapper for the R object type.

Use attributes and macros to export to R.

For a module named mymodule (typically in a file named mymodule.rs)

use extendr_api::prelude::*;
// Export a function or impl to R.
#[extendr]
fn fred(a: i32) -> i32 {
    a + 1
}

// define exports using extendr_module
extendr_module! {
   mod mymodule;
   fn fred;
}

In R:

result <- fred(1)

Robj is a wrapper for R objects. The r!() and R!() macros let you build R objects using Rust and R syntax respectively.

use extendr_api::prelude::*;
test! {
    // An R object with a single string "hello"
    let character = r!("hello");
    let character = r!(["hello", "goodbye"]);

    // An R integer object with a single number 1L.
    // Note that in Rust, 1 is an integer and 1.0 is a real.
    let integer = r!(1);

    // An R real object with a single number 1.
    // Note that in R, 1 is a real and 1L is an integer.
    let real = r!(1.0);

    // An R real vector.
    let real_vector = r!([1.0, 2.0]);
    let real_vector = &[1.0, 2.0].iter().collect_robj();
    let real_vector = r!(vec![1.0, 2.0]);

    // An R function object.
    let function = R!("function(x, y) { x + y }")?;

    // A named list using the list! macro.
    let list = list!(a = 1, b = 2);

    // An unnamed list (of R objects) using the List wrapper.
    let list = r!(List::from_values(vec![1, 2, 3]));
    let list = r!(List::from_values(vec!["a", "b", "c"]));
    let list = r!(List::from_values(&[r!("a"), r!(1), r!(2.0)]));

    // A symbol
    let sym = sym!(wombat);

    // A R vector using collect_robj()
    let vector = (0..3).map(|x| x * 10).collect_robj();
}

In Rust, we prefer to use iterators rather than loops.

use extendr_api::prelude::*;
test! {
    // 1 ..= 100 is the same as 1:100
    let res = r!(1 ..= 100);
    assert_eq!(res, R!("1:100")?);

    // Rust arrays are zero-indexed so it is more common to use 0 .. 100.
    let res = r!(0 .. 100);
    assert_eq!(res.len(), 100);

    // Using map is a super fast way to generate vectors.
    let iter = (0..3).map(|i| format!("fred{}", i));
    let character = iter.collect_robj();
    assert_eq!(character, r!(["fred0", "fred1", "fred2"]));
}

To index a vector, first convert it to a slice and then remember to use 0-based indexing. In Rust, going out of bounds will cause and error (a panic) unlike C++ which may crash.

use extendr_api::prelude::*;
test! {
    let vals = r!([1.0, 2.0]);
    let slice = vals.as_real_slice().ok_or("expected slice")?;
    let one = slice[0];
    let two = slice[1];
    // let error = slice[2];
    assert_eq!(one, 1.0);
    assert_eq!(two, 2.0);
}

Much slower, but more general are these methods:

use extendr_api::prelude::*;
test! {
    let vals = r!([1.0, 2.0, 3.0]);

    // one-based indexing [[i]], returns an object.
    assert_eq!(vals.index(1)?, r!(1.0));

    // one-based slicing [x], returns an object.
    assert_eq!(vals.slice(1..=2)?, r!([1.0, 2.0]));

    // $ operator, returns an object
    let list = list!(a = 1.0, b = "xyz");
    assert_eq!(list.dollar("a")?, r!(1.0));
}

The R! macro lets you embed R code in Rust and takes Rust expressions in {{ }} pairs.

The Rraw! macro will not expand the {{ }} pairs.

use extendr_api::prelude::*;
test! {
    // The text "1 + 1" is parsed as R source code.
    // The result is 1.0 + 1.0 in Rust.
    assert_eq!(R!("1 + 1")?, r!(2.0));

    let a = 1.0;
    assert_eq!(R!("1 + {{a}}")?, r!(2.0));

    assert_eq!(R!(r"
        x <- {{ a }}
        x + 1
    ")?, r!(2.0));

    assert_eq!(R!(r#"
        x <- "hello"
        x
    "#)?, r!("hello"));

    // Use the R meaning of {{ }} and do not expand.
    assert_eq!(Rraw!(r"
        x <- {{ 1 }}
        x + 1
    ")?, r!(2.0));
}

The r! macro converts a rust object to an R object and takes parameters.

use extendr_api::prelude::*;
test! {
    // The text "1.0+1.0" is parsed as Rust source code.
    let one = 1.0;
    assert_eq!(r!(one+1.0), r!(2.0));
}

You can call R functions and primitives using the call! macro.

use extendr_api::prelude::*;
test! {

    // As one R! macro call
    let confint1 = R!("confint(lm(weight ~ group - 1, PlantGrowth))")?;

    // As many parameterized calls.
    let formula = call!("~", sym!(weight), lang!("-", sym!(group), 1))?;
    let plant_growth = global!(PlantGrowth)?;
    let model = call!("lm", formula, plant_growth)?;
    let confint2 = call!("confint", model)?;

    assert_eq!(confint1.as_real_vector(), confint2.as_real_vector());
}

Rust has a concept of "Owned" and "Borrowed" objects.

Owned objects, such as Vec and String allocate memory which is released when the object lifetime ends.

Borrowed objects such as &[i32] and &str are fat pointers to another object's memory and can't live longer than the object they reference.

Borrowed objects are much faster than owned objects and use less memory but are used only for temporary access.

When we take a slice of an R vector, for example, we need the original R object to be alive or the data will be corrupted.

use extendr_api::prelude::*;
test! {
    // robj is an "Owned" object that controls the memory allocated.
    let robj = r!([1, 2, 3]);

    // Here slice is a "borrowed" reference to the bytes in robj.
    // and cannot live longer than robj.
    let slice = robj.as_integer_slice().ok_or("expected slice")?;
    assert_eq!(slice.len(), 3);
}

Feature gates

extendr-api has some optional features behind these feature gates:

ndarray: provides the conversion between R's matrices and ndarray.
num-complex: provides the conversion between R's complex numbers and num-complex.
serde: provides the serde support.
graphics: provides the functionality to control or implement graphics devices.
either: provides implementation of type conversion traits for Either<L, R> from either if L and R both implement those traits.
faer: provides conversion between R's matrices and faer.

extendr-api has different encodings (conversions) of a Result<T,E> into an Robj. In below x_ok represents an R variable on R side which was returned from rust via T::into_robj() or similar. Likewise x_err was returned to R side from rust via E::into_robj() or similar. extendr-api

result_list' Ok(T) is encoded as list(ok = x_ok, err = NULL) and Err as list(ok = NULL, err = e_err)
result_condition' Ok(T) is encoded as x_ok and Err(E) as condition(msg="extendr_error", value = x_err, class=c("extendr_error", "error", "condition"))
Multiple of above result feature gates. Only one result feature gate will take effect, the precedence is currently [result_list, result_condition, ... ].

Finally, there are parts of R's API that are deemed non-API, in that R packages on CRAN are recommended not to have these available in packages. If you want to have access to them, you may use the non-api feature to expose them.

License

MIT

Adding extendr_api library as a dependency

Adding `extendr_api` library as a dependency