[Bioc-devel] Methods to speed up R CMD Check

3 ways to do this, one that doesn't work, and two that work ;-)


1. Simple way that doesn't work:

   ## Just a place holder. Will be initialized at run-time the first
   ## time it's needed.
   .some_internal_global_variable <- NULL

   toto <- function()
   {
     if (is.null(.some_global_variable))
         .some_internal_global_variable <<- 55L
   }

   However, if you put this in your package, you'll get the following
   error the first time toto() is called:

     cannot change value of locked binding for
'.some_internal_global_variable'

2. Simple way that works: initialize the global variable in the
    .onLoad() hook. This works because the .onLoad() hook is executed
    right before the package namespace gets locked.

   ## Just a place holder. Will be initialized at load-time.
   .some_internal_global_variable <- NULL

   .onLoad <- function(libname, pkgname)
   {
     .some_internal_global_variable <<- 55L
   }

   However, I don't really like using this approach when initialization
   of the global variable requires access to the internet. It means that
   in case of connectivity issue your users won't be able to load the
   package and troubleshooting can become really tricky when you can't
   even load a package. So in that case I prefer the solution below.

3. Define the internal global variable in an environment:

   .my_internal_global_variables <- new.env(parent=emptyenv())

   .get_eh <- function() get("eh", envir=.my_internal_global_variables)
   .set_eh <- function(value) assign("eh", value,
envir=.my_internal_global_variables)

   toto <- function()
   {
     eh <- try(.get_eh(), silent=TRUE)
     if (inherits(eh, "try-error")) {
       eh <- ExperimentHub()
       .set_eh(eh)
     }
     eh
   }

Hope this helps,

H.




On 3/23/21 10:05 AM, Murphy, Alan E wrote:
> Hey Herv?,
>
> I get the idea now thanks for clarifying. Where do I place the call to
> ExperimentHub in the package?:
>
> eh <- ExperimentHub()  # the only call to ExperimentHub() in
>                            # the entire R session
>
> The package contains calls to the datasets in internal functions,
> examples, tests and the vignette so eh it would need to be available to
> all. Sorry I don't have much experience using experiment datasets.
>
> Kind regards,
> Alan.
>
> ------------------------------------------------------------------------
> *From:* Herv? Pag?s <hpages.on.github at gmail.com>
> *Sent:* 23 March 2021 16:46
> *To:* Murphy, Alan E <a.murphy at imperial.ac.uk>; Martin Morgan
> <mtmorgan.bioc at gmail.com>; Kern, Lori <Lori.Shepherd at RoswellPark.org>;
> bioc-devel at r-project.org <bioc-devel at r-project.org>
> *Subject:* Re: [Bioc-devel] Methods to speed up R CMD Check
>
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> On 3/23/21 4:11 AM, Murphy, Alan E wrote:
>> Hi,
>>
>> Thank you very much Martin and Herv? for your suggestions. I have reverted my zzz.R on load function to that advised by ExperimentHub and had used the ID look up (system.time(tt_alzh <- eh[["EH5373"]])) on internal functions and unit tests. However, the check  is still taking ~18 minutes so I need to do a bit more work. Even with
> my new on load function, calling datasets by name still takes
> substantially longer, see below for the example Herv? gave on my new code:
>>
>> a<-function(){
>>    eh <- query(ExperimentHub(), "ewceData")
>
> The above line is not needed. Creating an ExperimentHub instance can be
> quite expensive and with the current approach 'R CMD check' will do it
> dozens of times. My suggestion was to create an ExperimentHub instance
> once for all the first time you need it, and reuse it in all your data
> access functions:
>
>     eh <- ExperimentHub()  # the only call to ExperimentHub() in
>                            # the entire R session
>
> Also there's no need to query(). Just use the EHb ID directly on the
> ExperimentHub instance to load your data:
>
>     eh[["EH5373"]]
>
> This should reduce 'R CMD check' by a few more minutes.
>
> H.
>
> --
> Herv? Pag?s
>
> Bioconductor Core Team
> hpages.on.github at gmail.com

--
Herv? Pag?s

Bioconductor Core Team
hpages.on.github at gmail.com