On Fri, Aug 21, 2009 at 6:03 AM, Barry Rowlingson
<b.rowling...@lancaster.ac.uk> wrote:
> I'm often wanting to develop functions whilst manipulating data. But I
> don't want to end up with a .RData full of functions and data. It
> might be that I have functions that are re-usable but not worth
> sticking in a package.
>
> So I've tried to come up with a paradigm for function development
> that more closely follows the way Matlab and Python do it (partly
> inspired by a confused Matlab convert over on R-help).
>
> My requirements were thus:
>
> * .R files as the master source for R functions
> * Don't see the functions in ls()
> * After editing R, make it easy to update the definitions visible to
> R (unlike rebuilding and reloading a package).
>
> So I wrote these two in a few mins:
>
> loadDir <- function(dir){
> e = attach(NULL,name=dir)
> assign("__path__",dir,envir=e)
> reloadDir(e)
> e
> }
>
> reloadDir <- function(e){
> path = get("__path__",e)
> files =
> list.files(path,".R$",full.names=TRUE,recursive=TRUE,ignore.case=TRUE)
> for(f in files){
> sys.source(f,envir=e)
> }
> }
Rather than using __path__, why not just use chdir = TRUE in
sys.source() and rely on the usual R working directory semantics?
> Sourcing everything on any change seems a bit wasteful, but until R
> objects have timestamps I can't think of a better way. Hmm, maybe my
> environment could keep a __timestamp__ object... Okay, this is getting
> less simple now...
That's what I do for all of my packages during development. You
really need a huge amount of code before it starts to take a
noticeable amount of time.
Hadley
--
http://had.co.nz/
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