[R] eval and evironments: call local function in a global function

[Renaud Gaujoux]

Ah! It looks interesting and seems more conservative than changing the 
actual environment. I could do the restore within an on.exit to deal 
with the error eventuality.
Do you think could define a dummy setVar function in my package 
namespace, and change its behaviour on runtime?

This way, as soon as he has loaded the package, the user will be able to 
call setVar anywhere in his functions. What setVar does would be set by 
my main code that runs before calling the user's function.

Gabor Grothendieck wrote:
> Another possibility is that you could inject setVar into
> fun.global's environment.
>
> First save any existing setVar in fun.global's environment to tmp
> and then assign our own setVar there.  We then run fun.global()
> and reverse the changes we made in fun.global's environment
> setting everything back to what it was before.
>
> If setVar is called from fun.global2 instead of fun.global then
> its up to the user to ensure that fun.global2 can access
> fun.global's environment.
>
> fun.global <- function() { message('fun.global'); fun.global2() }
> fun.global2 <- function() { message("fun.global2"); setVar(2) }
>
> main <- function() {
>   l.var <- 0
>   e <- environment(fun.global)
>
>   tmp <- if (exists("setVar", e)) get("setVar", e) ##
>   assign("setVar", function(value) { message("setVar"); l.var <<- value }, e)
>   fun.global()
>   if (is.null(tmp)) rm(setVar, envir = e) else assign("setVar", tmp, e)
>
>   print(l.var)
> }
> main()
>
>
> Yet another possibility is to simply mandate that the user call setVar
> directly from fun.global and ask them to do it like this:
>
> fun.global <- function() parent.frame()$setVar(4)
> main <- function() {
>        l.var <- 0
>        setVar <- function(value) { message("set Var"); l.var <<- value }
>        environment(fun.global) <- environment()
>        fun.global()
>        print(l.var)
> }
> main()
>
>
>
>
> On Fri, Aug 21, 2009 at 6:33 AM, Renaud
> Gaujoux<renaud at mancala.cbio.uct.ac.za> wrote:
>   
>> Thanks Duncan, I agree that touching the environments is risky and not
>> robust. I rather go for another solution.
>> But the function solution still require to pass an extra object to the
>> user's function. I'd like the user to simply be able to call function setVar
>> as if it was a standard R function (visible from any of his -- possibly
>> nested -- functions), but this function would act on a variable local to the
>> main call, that I can setup on runtime. This variable should be protected
>> from direct access as much as possible (my idea with the local layer was
>> something to implement kind of a private variable). Maybe it's just
>> impossible ?
>> -- Sorry to insist :) --
>>
>> Renaud
>>
>> Duncan Murdoch wrote:
>>     
>>> On 8/20/2009 4:27 AM, Renaud Gaujoux wrote:
>>>       
>>>> Hi,
>>>>
>>>> in my project I want the user to be able to write hook functions that are
>>>> in turn called in my main code. I'd like the user's hooks to be able to call
>>>> some function that set a variable outside their running environment.
>>>>         
>>> The trick is that this variable is not global, but defined
>>>       
>>>> on runtime before calling the hooks, and I don't want to leave any trace
>>>> (i.e. global variables) after the main code has finished.
>>>>         
>>> The best way to do this is to pass the function (setVar below) as an
>>> argument to the user's function.  If it's the user's function, you have no
>>> business messing with it by changing its environment.  How do you know the
>>> user didn't spend hours working out some crazy scheme of creating a nested
>>> function with a carefully crafted environment, and evaluation of his
>>> function depends on you leaving it alone?
>>>
>>>
>>>       
>>>> I thought that the following would work but it doesn't. I guess I got too
>>>> messy with environment and enclosures:
>>>>
>>>> # global function defined by the user
>>>> fun.global <- function(){
>>>>    message('fun.global')
>>>>    setVar(5) #
>>>> }
>>>>         
>>> Pass setVar as an arg:
>>>
>>> fun.global <- function(setVar) {
>>>    message('fun.global')
>>>    setVar(5)
>>> }
>>>
>>>       
>>>> # my main code
>>>> main <- function(){
>>>>    message('main')
>>>>      # define a function to set some local variable
>>>>    setVar <- local({
>>>>    l.var <- 0
>>>>    function(value){
>>>>        message('setVar')
>>>>       l.var <<- value
>>>>    }
>>>>    })
>>>>    .workspace <- environment(setVar)
>>>>    environment(setVar) <- new.env()
>>>>      eval(fun.global(), enclos=environment(setVar))
>>>>    print(get('l.var', envir=.workspace, inherits=FALSE))
>>>> }
>>>>         
>>> I wouldn't bother with the extra layer of local(), just put l.var in
>>> main's evalution frame.  (Since you're the one writing setVar, you can avoid
>>> any name clashes.)  That is:
>>>
>>> main <- function() {
>>>    message('main')
>>>    l.var <- 0
>>>    setVar <- function(value) {
>>>    message('setVar')
>>>    l.var <<- value
>>>    }
>>>    fun.global(setVar)
>>>    print(l.var)
>>> }
>>>
>>> Duncan Murdoch
>>>
>>>       
>>>> main()
>>>>
>>>> I get the following output:
>>>>  > main
>>>>  > fun.global
>>>>  > Error in fun.global() : could not find function "setVar"
>>>>
>>>> There is definitely a problem of lookup somewhere. I first tried without
>>>> eval, as I thought that function setVar would then be defined in a parent
>>>> environment of the call to fun.global, but it does not work either.
>>>> Can anybody tell me what's the problem and how I should do my stuff?
>>>>
>>>> Thanks,
>>>> Renaud
>>>>
>>>> ______________________________________________
>>>> R-help at r-project.org mailing list
>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>> PLEASE do read the posting guide
>>>> http://www.R-project.org/posting-guide.html
>>>> and provide commented, minimal, self-contained, reproducible code.
>>>>         
>> ______________________________________________
>> R-help at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>>