`rvee`

Recreational V programming for R / WIP

Early work! (not ready for production)

Create R extension packages with the V programming language. V is a simple, safe and fast programming language with the speed of C.

R has good interfaces for many programming languages such as C , fortran , cpp (e.g. Rcpp) , python (e.g. reticulate) and rust (e.g. r-rust). R Package rvee intends to provide an easy toolkist for creating R packages with the v programming language.

Status

Translation to C and compilation 🎉!

Interfacing:

Generating all interfacing code from v file with rvee::rv_export_c()
wraps simple input and return types: f64, int, bool, string
wraps numeric, logical, integer, character, factor and list input and return types.
compiling and working :-)
wraps data.frame input and return types.
wraps array input and return types: []f64, []int, []bool, []string
CRAN checks

r module (in v):

Numeric, direct access as a []f64
Integer, direct access as a []int
Character, indirect access as a []string. string values of R are reused, but newly created string (not managed by R) are copied.
Logical, indirect access as a []bool. automatically converts between []bool and logical.
Factor
List
DataFrame
Environment
Function

Installation

The unstable development version from GitHub with:

# install.packages("devtools")
devtools::install_github("edwindj/rvee")

Overview

Possible routes for creating an R extension with v code are:

Transpiling V code to C code and use it as a normal C extension.
Using the v compiler to build a shared library linked to the R shared library.

Both options have their benefits and draw backs:

Allows for easy distribution and installation, but requires tweaking the compilation flags to pass CRAN checks etc. and removing/stripping code that is not needed by R.
Allows for an optimized shared library, but requires v to be installed by the installer (e.g. CRAN).

Example

Transpiling to C works.

Put your v files in the "<pkg>/src/v" directory and decorate each function to be exported with the [rv_export] attribute (see example below).

After that

rvee::rv_export_c generates the necessary interfacing code:

"./R/rv_export.R": R functions calling the v functions declared in "./src/v/rv_export.v"
"./src/v/rv_export.v": v wrapper functions translating input and output to the original v functions.
"./src/init.c": registration code for the shared library
"./src/<pkg>.c": the c code generated by v from the source files in the "<pkg>/src/v" directory.

After that devtools::load_all (or R CMD SHLIB) work: they will compile "init.c" and "<pkg>.c" into "<pkg>.so"/"<pkg>.dll".

Suppose we have the following file “/src/example.v”

import r {Numeric}

[rv_export]
pub fn scalar_numeric(x f64) f64{
   return x + 1.
}

[rv_export]
pub fn scalar_integer(x int) int{
   return x + 1
}


[rv_export]
fn negate(x bool) bool {
  return !x
}

[rv_export]
fn my_numeric(mut x Numeric) Numeric{
  //This changes the values in place!
  for mut val in x.data {
    val += 1.
  }
  return x
}

With:

rvee::rv_export_c("<pkg>", prefix="my_pkg") # <pkg> is root dir of the source of your package...

The interfacing code is generated:

"<pkg>/src/v/rv_export.v":

/* Automatically generated with R package: `rvee`
* rvee version: 0.1.0.9000
*/
import r

[manualfree]
fn my_pkg_scalar_numeric(x C.SEXP) C.SEXP {
  defer {r.protected.flush()} // clear any protected r objects

  // wrap input x
  i_x_v := r.as_f64(x)
  res := scalar_numeric(i_x_v)

  //wrap output
  return r.from_f64(res)

}

[manualfree]
fn my_pkg_scalar_integer(x C.SEXP) C.SEXP {
  defer {r.protected.flush()} // clear any protected r objects

  // wrap input x
  i_x_v := r.as_int(x)
  res := scalar_integer(i_x_v)

  //wrap output
  return r.from_int(res)

}

[manualfree]
fn my_pkg_negate(x C.SEXP) C.SEXP {
  defer {r.protected.flush()} // clear any protected r objects

  // wrap input x
  i_x_v := r.as_bool(x)
  res := negate(i_x_v)

  //wrap output
  return r.from_bool(res)

}

[manualfree]
fn my_pkg_my_numeric(x C.SEXP) C.SEXP {
  defer {r.protected.flush()} // clear any protected r objects

  // wrap input x
  mut i_x_v := r.as_numeric(x)
  res := my_numeric(mut i_x_v)

  //wrap output
  return r.from_numeric(res)

}

and

"<pkg>/R/rv_export.R":

## Automatically generated with R package: `rvee`
#  rvee version: 0.1.0.9000
#
#' @useDynLib my_pkg, .registration=TRUE
NULL

#' my_pkg_scalar_numeric
#'
#' my_pkg_scalar_numeric calls the v function 'scalar_numeric'
#' ('example/example.v:4').
#' @param x numeric
#' @return numeric
#' @keywords internal
my_pkg_scalar_numeric <- function(x){
  x <- as.numeric(x)
  .Call('_my_pkg_scalar_numeric', x)
}

#' my_pkg_scalar_integer
#'
#' my_pkg_scalar_integer calls the v function 'scalar_integer'
#' ('example/example.v:9').
#' @param x integer
#' @return integer
#' @keywords internal
my_pkg_scalar_integer <- function(x){
  x <- as.integer(x)
  .Call('_my_pkg_scalar_integer', x)
}

#' my_pkg_negate
#'
#' my_pkg_negate calls the v function 'negate'
#' ('example/example.v:15').
#' @param x logical
#' @return logical
#' @keywords internal
my_pkg_negate <- function(x){
  x <- as.logical(x)
  .Call('_my_pkg_negate', x)
}

#' my_pkg_my_numeric
#'
#' my_pkg_my_numeric calls the v function 'my_numeric'
#' ('example/example.v:20').
#' @param x numeric
#' @return numeric
#' @keywords internal
my_pkg_my_numeric <- function(x){
  x <- as.numeric(x)
  .Call('_my_pkg_my_numeric', x)
}

And create the shared library with a call to devtools

devtools::load_all("<pkg>")

edwindj / rvee