R from C -- Simplest Possible Helloworld - c

Question

What is the simplest possible C function for starting the R interpreter, passing in a small expression (eg, 2+2), and getting out the result? I'm trying to compile with MingW on Windows.

Answer 1

You want to call R from C?
Look at section 8.1 in the Writing R Extensions manual. You should also look into the "tests" directory (download the source package extract it and you'll have the tests directory). A similar question was previously asked on R-Help and here was the example:
#include <Rinternals.h>
#include <Rembedded.h>
SEXP hello() {
return mkString("Hello, world!\n");
}
int main(int argc, char **argv) {
SEXP x;
Rf_initEmbeddedR(argc, argv);
x = hello();
return x == NULL; /* i.e. 0 on success */
}
The simple example from the R manual is like so:
#include <Rembedded.h>
int main(int ac, char **av)
{
/* do some setup */
Rf_initEmbeddedR(argc, argv);
/* do some more setup */
/* submit some code to R, which is done interactively via
run_Rmainloop();
A possible substitute for a pseudo-console is
R_ReplDLLinit();
while(R_ReplDLLdo1() > 0) {
add user actions here if desired
}
*/
Rf_endEmbeddedR(0);
/* final tidying up after R is shutdown */
return 0;
}
Incidentally, you might want to consider using Rinside instead: Dirk provides a nice "hello world" example on the project homepage.
In you're interested in calling C from R, here's my original answer:
This isn't exactly "hello world", but here are some good resources:
Jay Emerson recently gave a talk on R package development at the New York useR group, and he provided some very nice examples of using C from within R. Have a look at the paper from this discussion on his website, starting on page 9. All the related source code is here: http://www.stat.yale.edu/~jay/Rmeetup/MyToolkitWithC/.
The course taught at Harvard by Gopi Goswami in 2005: C-C++-R (in Statistics). This includes extensive examples and source code.

Answer 2

Here you go. It's the main function, but you should be able to adapt it to a more general purpose function. This example builds an R expression from C calls and also from a C string. You're on your own for the compiling on windows, but I've provided compile steps on linux:
/* simple.c */
#include <Rinternals.h>
#include <Rembedded.h>
#include <R_ext/Parse.h>
int
main(int argc, char *argv[])
{
char *localArgs[] = {"R", "--no-save","--silent"};
SEXP e, tmp, ret;
ParseStatus status;
int i;
Rf_initEmbeddedR(3, localArgs);
/* EXAMPLE #1 */
/* Create the R expressions "rnorm(10)" with the R API.*/
PROTECT(e = allocVector(LANGSXP, 2));
tmp = findFun(install("rnorm"), R_GlobalEnv);
SETCAR(e, tmp);
SETCADR(e, ScalarInteger(10));
/* Call it, and store the result in ret */
PROTECT(ret = R_tryEval(e, R_GlobalEnv, NULL));
/* Print out ret */
printf("EXAMPLE #1 Output: ");
for (i=0; i<length(ret); i++){
printf("%f ",REAL(ret)[i]);
}
printf("\n");
UNPROTECT(2);
/* EXAMPLE 2*/
/* Parse and eval the R expression "rnorm(10)" from a string */
PROTECT(tmp = mkString("rnorm(10)"));
PROTECT(e = R_ParseVector(tmp, -1, &status, R_NilValue));
PROTECT(ret = R_tryEval(VECTOR_ELT(e,0), R_GlobalEnv, NULL));
/* And print. */
printf("EXAMPLE #2 Output: ");
for (i=0; i<length(ret); i++){
printf("%f ",REAL(ret)[i]);
}
printf("\n");
UNPROTECT(3);
Rf_endEmbeddedR(0);
return(0);
}
Compile steps:
$ gcc -I/usr/share/R/include/ -c -ggdb simple.c
$ gcc -o simple simple.o -L/usr/lib/R/lib -lR
$ LD_LIBRARY_PATH=/usr/lib/R/lib R_HOME=/usr/lib/R ./simple
EXAMPLE #1 Output: 0.164351 -0.052308 -1.102335 -0.924609 -0.649887 0.605908 0.130604 0.243198 -2.489826 1.353731
EXAMPLE #2 Output: -1.532387 -1.126142 -0.330926 0.672688 -1.150783 -0.848974 1.617413 -0.086969 -1.334659 -0.313699

Answer 3

I don't think any of the above has answered the question - which was to evaluate 2 + 2 ;). To use a string expression would be something like:
#include <Rinternals.h>
#include <R_ext/Parse.h>
#include <Rembedded.h>
int main(int argc, char **argv) {
SEXP x;
ParseStatus status;
const char* expr = "2 + 2";
Rf_initEmbeddedR(argc, argv);
x = R_ParseVector(mkString(expr), 1, &status, R_NilValue);
if (TYPEOF(x) == EXPRSXP) { /* parse returns an expr vector, you want the first */
x = eval(VECTOR_ELT(x, 0), R_GlobalEnv);
PrintValue(x);
}
Rf_endEmbeddedR(0);
return 0;
}
This lacks error checking, obviously, but works:
Z:\>gcc -o e.exe e.c -IC:/PROGRA~1/R/R-213~1.0/include -LC:/PROGRA~1/R/R-213~1.0/bin/i386 -lR
Z:\>R CMD e.exe
[1] 4
(To get the proper commands for your R use R CMD SHLIB e.c which gives you the relevant compiler flags)
You can also construct the expression by hand if it's simple enough - e.g., for rnorm(10) you would use
SEXP rnorm = install("rnorm");
SEXP x = eval(lang2(rnorm, ScalarInteger(10)), R_GlobalEnv);

Answer 4

I think you can't do much better than the inline package (which supports C, C++ and Fortran):
library(inline)
fun <- cfunction(signature(x="ANY"),
body='printf("Hello, world\\n"); return R_NilValue;')
res <- fun(NULL)
which will print 'Hello, World' for you. And you don't even know where / how / when the compiler and linker are invoked. [ The R_NilValue is R's NULL version of a SEXP and the .Call() signature used here requires that you return a SEXP -- see the 'Writing R Extensions' manual which you can't really avoid here. ]
You will then take such code and wrap it in a package. We had great success with using
inline for the
Rcpp unit tests (over 200 and counting now) and some of the examples.
Oh, and this inline example will work on any OS. Even Windoze provided you have the R package building tool chain installed, in the PATH etc pp.
Edit: I misread the question. What you want is essentially what the littler front-end does (using pure C) and what the RInside classes factored-out for C++.
Jeff and I never bothered with porting littler to Windoze, but RInside did work there in most-recent release. So you should be able to poke around the build recipes and create a C-only variant of RInside so that you can feed expression to an embedded R process. I suspect that you still want something like Rcpp for the clue as it gets tedious otherwise.
Edit 2: And as Shane mentions, there are indeed a few examples in the R sources in tests/Embedding/ along with a Makefile.win. Maybe that is the simplest start if you're willing to learn about R internals.