We can leverage small parts of the R’s C API in order to infer the type of objects directly at the run-time of a function call, and use this information to dynamically wrap objects as needed. We’ll also present an example of recursing through a list.

To get a basic familiarity with the main functions exported from R API, I recommend reading Hadley’s guide to R’s C internals guide here first, as we will be using some of these functions for navigating native R SEXPs. (Reading it will also give you an appreciation for just how much work Rcpp does in insulating us from the ugliness of the R API.)

From the R API, we’ll be using the TYPEOF macro, as well as referencing the internal R types:

• REALSXP for numeric vectors,
• INTSXP for integer vectors,
• VECSXP for lists

We’ll start with a simple example: an Rcpp function that takes a list, loops through it, and:

• if we encounter a numeric vector, double each element in it;
• if we encounter an integer vector, add 1 to each element in it

#include <Rcpp.h>
using namespace Rcpp;
 
// [[Rcpp::export]]
List do_stuff( List x_ ) {
    List x = clone(x_);
    for( List::iterator it = x.begin(); it != x.end(); ++it ) {
        switch( TYPEOF(*it) ) {
            case REALSXP: {
                NumericVector tmp = as<NumericVector>(*it);
          	tmp = tmp * 2;
		break;    
            }
      	    case INTSXP: {
                if( Rf_isFactor(*it) ) break; // factors have internal type INTSXP too
        	IntegerVector tmp = as<IntegerVector>(*it);
		tmp = tmp + 1;
                break;
      	    }
      	    default: {
                stop("incompatible SEXP encountered; only accepts lists with REALSXPs and INTSXPs");
      	    }
       }
  }  
  return x;
}

A quick test:

dat <- list( 
    1:5, ## integer
    as.numeric(1:5) ## numeric
)
tmp <- do_stuff(dat)
print(tmp)


[[1]]
[1] 2 3 4 5 6

[[2]]
[1]  2  4  6  8 10

Some notes on the above:

1. We clone the list passed through to ensure we work with a copy, rather than the original list passed in,
2. We switch over the internal R type using TYPEOF, and do something for the case of numeric vectors (REALSXP), and integer vectors (INTSXP),
3. After we’ve figured out what kind of object we have, we can use Rcpp::as to wrap the R object with the appropriate container,
4. Because Rcpp’s wrappers point to the internal R structures, any changes made to them are reflected in the R object wrapped,
5. We use Rcpp sugar to easily add and multiply each element in a vector,
6. We throw an error if a non-numeric / non-integer object is encountered. One could leave the default: switch just to do nothing or fall through, or handle other SEXPs as needed as well.

We also check that we fail gracefully when we encounter a non-accepted SEXP:

do_stuff( list(new.env()) )


Error: incompatible SEXP encountered; only accepts lists with REALSXPs and
INTSXPs

However, this only operates on top-level objects within the list. What if your list contains other lists, and you want to recurse through those lists as well?

It’s actually quite simple: if the internal R type of the object encountered is a VECSXP, then we just call our recursive function on that element itself!

#include <Rcpp.h>
using namespace Rcpp;
 
// [[Rcpp::export]]
List recurse(List x_) {
    List x = clone(x_);
    for( List::iterator it = x.begin(); it != x.end(); ++it ) {
        switch( TYPEOF(*it) ) {
            case VECSXP: {
                *it = recurse(*it);
        	break;
            }
            case REALSXP: {
                NumericVector tmp = as<NumericVector>(*it);
        	tmp = tmp * 2;
            	break;
      	    }
      	    case INTSXP: {
            	if( Rf_isFactor(*it) ) break; // factors have internal type INTSXP too
        	IntegerVector tmp = as<IntegerVector>(*it);
        	tmp = tmp + 1;
        	break;
      	    }
      	    default: {
                stop("incompatible SEXP encountered; only accepts lists containing lists, REALSXPs, and INTSXPs");
      	    }
        }
    }
    return x;
}

A test case:

dat <- list( 
    x=1:5, ## integer
    y=as.numeric(1:5), ## numeric
    z=list( ## another list to recurse into
        zx=10L, ## integer
        zy=20 ## numeric
    )
)
out <- recurse(dat)
print(out)


$x
[1] 2 3 4 5 6

$y
[1]  2  4  6  8 10

$z
$z$zx
[1] 11

$z$zy
[1] 40

Note that all we had to do was add a VECSXP case in our switch statement. If we see a list, we call the same recurse function on that list, and then re-assign the result of that recursive call. Neat!

Hence, by using TYPEOF to query the internal R type of objects pre-wrap, we can wrap objects as needed into an appropriate container, and then use Rcpp / C++ code as necessary to modify them.