R package build, reason for "object 'xxx' not found"

Question

I'm attempting to build an R package from code that works outside a package. My first try and it is rather complex, nested functions that end up doing parallel processing using doMPI and foreach. Also using RStudio 1.01.43 on Ubuntu 16.04. I build the package and works ok. Then when I try to run the top level function which calls the next it throws an error:

Error in { : task 6 failed - "object 'RunOys' not found" 

I'm setting the boolean variable RunOys=TRUE manually before calling the top level function, when it gets down to the one where this variable is called for an ifelse statement it fails. Before I call the top level function I check the globalenv() and

> RunOys
[1] TRUE

In the foreach parallel code I have this statement, which works find until compiled into an R package:

FinalCalcs <- function (...) {
    results <- data.frame ( foreach::`%dopar%`(
             foreach::`%:%`(foreach::foreach(j = 1:NumSim, .combine = acomb,
                                             .options.mpi=opts1),
                            foreach::foreach (i = 1:PopSize, .combine=rbind,
                                    .options.mpi=opts2,
                                    .export = c(ls(globalenv())),
                                    .packages = c("zoo", "msm", "FAdist", "qmra"))),
                            {

which should export all of the objects in globalenv() to each slave.

I can't understand why some variables seem to get passed and not other. Do I need to specify it explicitly as a @param in the file for the function where it is called?

Answer 1

With foreach, the better is to have all the needed variables present in the same environment where foreach is called. So basically, I always use foreach inside a function and pass all the variables that are needed in the foreach to this function.

Do as if foreach couldn't see past its calling function. You won't need to export anything. For functions, use package::function (like in packages so that you don't need to @import packages).