Hello,
are you trying to pase SAS code (or lightly modified SAS code) and run it in R?
Then you are right: the hard part is parsing the code. I don't believe that's
possible without a custom parser, and even then it's really hard to parse all
the SAS "sub languages" right: data step, macro code and macro variables, IML,
SAS Procedures etc.
On Tuesday 13 July 2010 02:39:22 pm Roger Deangelis wrote:
> Thanks Richard and Erik,
>
> I hate to buy the book and not find the solution to the following:
>
> proc.means <- function(....) {
> deparse(match.call()[-1])
> }
>
> proc.means(this is a sentence)
>
> unexpected symbol in "proc means(this is)
>
> One possible solution would be to 'peek' into the memory buffer that holds
> the
> function arguments.
>
> It is easy to replicate the 'dataset' output for many SAS procs(ie
> transpose, freq, summary, means...)
> I am not interested in 'report writing in R'.
>
> The hard part is parsing the SAS syntax, I wish R had a drop down to PERL.
>
> per1 on;
>
> some perl code
>
> perl off;
>
> also
>
> sas on;
>
> some SAS code
>
> sas off;
>
> The purpose of parmbuff is to turn off of Rs scanning and resolution of
> function arguments
> and just provide the bare text between '(' and ')' in the function call.
>
> This is a very powerful construct.
>
> A function would provide something like
>
> sas.on(
>
>
> )
>
--
----
Friedrich Schuster
Dompfaffenweg 6
69123 Heidelberg
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