[Bioc-devel] BiocParallel: Best standards for passing locally assigned variables/functions, e.g. a bpExport()?

[Martin Morgan]

On 11/04/2013 11:34 AM, Michael Lawrence wrote:
> The dynamic nature of R limits the extent of these checks. But as Ryan has
> noted, a simple sanity check goes a long way. If what he has done could be
> extended to the rest of the search path (people always forget to attach
> packages), I think we've hit the 80% with 20%. Got a 404 on that URL btw.

I added three issues to BiocParallel on github.

1. bpexport

2. a function to check for non-local use. I think this should use codetools (to 
avoid adding additional dependencies) but I'm a little flexible. Contributions 
welcome on github, especially as a pull request with code formatted 
consistently, a man page, and especially unit tests to provide a clear 
understanding of circumstances covered or not. Michel Lang's Recall and the 
implementation in foreach also sound releavant here.

3. integration of (2) into bplapply etc.

Please feel free to address these further on github.

Martin

>
> Michael
>
>
> On Mon, Nov 4, 2013 at 11:05 AM, Gabriel Becker <gmbecker at ucdavis.edu>wrote:
>
>> Hey guys,
>>
>> Here is code that I have written which resolves library names into a full
>> list of symbols:
>>
>> https://github.com/duncantl/CodeDepends/blob/forCRAN_0.3.5/R/librarySymbols.RNote
>> this does not require that the packages actually be loaded at the time
>> of the check, and does not load them (or rather, it loads them but does not
>> attach them, so no searchpath muddying occurs). You do need a list of
>> packages to check though (it adds the base ones automatically). It handles
>> dependency and could be easily extended to handle suggests as well I think.
>>
>> When CodeDepends gets pushed to cran (not my call and not high on my
>> priority list to push for currently) it will actually do exactly what you
>> want. (the forCRAN_0.3.5 branch already does and I believe it is
>> documented, so you could use devtools to install it now).
>>
>> As a side note, I'm not sure that existence of a symbol is sufficient (it
>> certainly is necessary). What about situations where the symbol exists but
>> is stale compared to the value in the parent? Are we sure that can never
>> happen?
>>
>> ~G
>>
>>
>> On Mon, Nov 4, 2013 at 7:29 AM, Michel Lang <michellang at gmail.com> wrote:
>>
>>> You might want to consider using Recall() for recursion which should
>> solve
>>> this. Determining the required variables using heuristics as codetools
>> will
>>> probably lead to some confusion when using functions which include calls
>>> to, e.g., with():
>>>
>>> f = function() {
>>>    with(iris, Sepal.Length + Sepal.Width)
>>> }
>>> codetools:::findGlobals(f)
>>>
>>> I would suggest to write up some documentation on what the function's
>>> environment contains and how to to define variables accordingly - or why
>> it
>>> can generally be considered a good idea to pass everything essential as
>> an
>>> argument. Nevertheless a "bpExport" function would be a good addition for
>>> some rare corner cases in my opinion.
>>>
>>> Michel
>>>
>>>
>>> 2013/11/3 Henrik Bengtsson <hb at biostat.ucsf.edu>
>>>
>>>> Hi,
>>>>
>>>> in BiocParallel, is there a suggested (or planned) best standards for
>>>> making *locally* assigned variables (e.g. functions) available to the
>>>> applied function when it runs in a separate R process (which will be
>>>> the most common use case)?  I understand that avoid local variables
>>>> should be avoided and it's preferred to put as mush as possible in
>>>> packages, but that's not always possible or very convenient.
>>>>
>>>> EXAMPLE:
>>>>
>>>> library('BiocParallel')
>>>> library('BatchJobs')
>>>>
>>>> # Here I pick a recursive functions to make the problem a bit harder,
>>> i.e.
>>>> # the function needs to call itself ("itself" = see below)
>>>> fib <- function(n=0) {
>>>>    if (n < 0) stop("Invalid 'n': ", n)
>>>>    if (n == 0 || n == 1) return(1)
>>>>    fib(n-2) + fib(n-1)
>>>> }
>>>>
>>>> # Executing in the current R session
>>>> cluster.functions <- makeClusterFunctionsInteractive()
>>>> bpParams <- BatchJobsParam(cluster.functions=cluster.functions)
>>>> register(bpParams)
>>>> values <- bplapply(0:9, FUN=fib)
>>>> ## SubmitJobs |++++++++++++++++++++++++++++++++++| 100% (00:00:00)
>>>> ## Waiting [S:0 R:0 D:10 E:0] |+++++++++++++++++++| 100% (00:00:00)
>>>>
>>>>
>>>> # Executing in a separate R process, where fib() is not defined
>>>> # (not specific to BiocParallel)
>>>> cluster.functions <- makeClusterFunctionsLocal()
>>>> bpParams <- BatchJobsParam(cluster.functions=cluster.functions)
>>>> register(bpParams)
>>>> values <- bplapply(0:9, FUN=fib)
>>>> ## SubmitJobs |++++++++++++++++++++++++++++++++++| 100% (00:00:00)
>>>> ## Waiting [S:0 R:0 D:10 E:0] |+++++++++++++++++++| 100% (00:00:00)
>>>> Error in LastError$store(results = results, is.error = !ok,
>> throw.error =
>>>> TRUE)
>>>> :
>>>>    Errors occurred during execution. First error message:
>>>> Error in FUN(...): could not find function "fib"
>>>> [...]
>>>>
>>>>
>>>> # The following illustrates that the solution is not always
>>>> straightforward.
>>>> # (not specific to BiocParallel; must have been discussed previously)
>>>> values <- bplapply(0:9, FUN=function(n, fib) {
>>>>    fib(n)
>>>> }, fib=fib)
>>>> Error in LastError$store(results = results, is.error = !ok,
>>>> throw.error = TRUE) :
>>>>    Errors occurred during execution. First error message:
>>>> Error in fib(n): could not find function "fib"
>>>> [...]
>>>>
>>>> # Workaround; make fib() aware of itself
>>>> # (this is something the user need to do, and would be very
>>>> #  hard for BiocParallel et al. to automate.  BTW, should all
>>>> #  recursive functions be implemented this way?).
>>>> fib <- function(n=0) {
>>>>    if (n < 0) stop("Invalid 'n': ", n)
>>>>    if (n == 0 || n == 1) return(1)
>>>>    fib <- sys.function() # Make function aware of itself
>>>>    fib(n-2) + fib(n-1)
>>>> }
>>>> values <- bplapply(0:9, FUN=function(n, fib) {
>>>>    fib(n)
>>>> }, fib=fib)
>>>>
>>>>
>>>> WISHLIST:
>>>> Considering the above recursive issue solved, a slightly more explicit
>>>> and standardized solution is then:
>>>>
>>>> values <- bplapply(0:9, FUN=function(n, BPGLOBALS=NULL) {
>>>>    for (name in names(BPGLOBALS)) assign(name, BPGLOBALS[[name]])
>>>>    fib(n)
>>>> }, BPGLOBALS=list(fib=fib))
>>>>
>>>> Could the above be generalized into something as neat as:
>>>>
>>>> bpExport("fib")
>>>> values <- bplapply(0:9, FUN=function(n) {
>>>>    BiocParallel::bpImport("fib")
>>>>    fib(n)
>>>> })
>>>>
>>>> or ideally just (analogously to parallel::clusterExport()):
>>>>
>>>> bpExport("fib")
>>>> values <- bplapply(0:9, FUN=fib)
>>>>
>>>> /Henrik
>>>>
>>>> _______________________________________________
>>>> Bioc-devel at r-project.org mailing list
>>>> https://stat.ethz.ch/mailman/listinfo/bioc-devel
>>>>
>>>
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>>>
>>> _______________________________________________
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>>>
>>
>>
>>
>> --
>> Gabriel Becker
>> Graduate Student
>> Statistics Department
>> University of California, Davis
>>
>>          [[alternative HTML version deleted]]
>>
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>>
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