Hi,
Unless someone is planning to change Stangle to include inline
expressions (which I am *not* advocating), I think that relying on
side-effects within an \Sexpr construction is a bad idea. So, my own
coding style is to restrict my use of \Sexpr to calls of the form
\Sexpr{show.the.value.of.this.variable}. As a result, I more-or-less
believe that having R CMD check use Stangle and report an error is
probably a good thing.
There is a completely separate questions about the relationship between
Sweave/Stangle or knit/purl and literate programming that is linked to
your question about whether to use Stangle on vignettes. The underlying
model(s) in R have drifted away from Knuth's original conception, for
some good reasons.
The original goal of literate programming was to be able to explain the
algorithms and data structures in the code to humans. For that purpose,
it was important to have named code chunks that you could move around,
which would allow you to describe the algorithm starting from a high
level overview and then drilling down into the details. From this
perspective, "tangle" was critical to being able to reconstruct a
program that would compile and run correctly.
The vast majority of applications of Sweave/Stangle or knit/purl in
modern R have a completely different goal: to produce some sort of
document that describes the results of an analysis to a non-programmer
or non-statistician. For this goal, "weave" is much more important
than
"tangle", because the most important aspect is the ability to
integrate
the results (figures, tables, etc) of running the code into the document
that get passed off to the person for whom the analysis was prepared. As
a result, the number of times in my daily work that I need to explicitly
invoke Stangle (or purl) explicitly is many orders of magnitude smaller
than the number of times that I invoke Sweave (or knitr).
-- Kevin
On 5/30/2014 1:04 AM, Yihui Xie wrote:> Hi,
>
> Recently I saw a couple of cases in which the package vignettes were
> somewhat complicated so that Stangle() (or knitr::purl() or other
> tangling functions) can fail to produce the exact R code that is
> executed by the weaving function Sweave() (or knitr::knit(), ...). For
> example, this is a valid document that can pass the weaving process
> but cannot generate a valid R script to be source()d:
>
> \documentclass{article}
> \begin{document}
> Assign 1 to x: \Sexpr{x <- 1}
> <<>>> x + 1
> @
> \end{document}
>
> That is because the inline R code is not written to the R script
> during the tangling process. When an R package vignette contains
> inline R code expressions that have significant side effects, R CMD
> check can fail because the tangled output is not correct. What I
> showed here is only a trivial example, and I have seen two packages
> that have more complicated scenarios than this. Anyway, the key thing
> that I want to discuss here is, since the R code in the vignette has
> been executed once during the weaving process, does it make much sense
> to execute the code generated from the tangle function? In other
> words, if the weaving process has succeeded, is it necessary to
> source() the R script again?
>
> The two options here are:
>
> 1. Do not check the R code from vignettes;
> 2. Or fix the tangle function so that it produces exactly what was
> executed in the weaving process. If this is done, I'm back to my
> previous question: does it make sense to run the code twice?
>
> To push this a little further, personally I do not quite appreciate
> literate programming in R as two separate steps, namely weave and
> tangle. In particular, I do not see the value of tangle, considering
> Sweave() (or knitr::knit()) as the new "source()". Therefore
> eventually I tend to just drop tangle, but perhaps I missed something
> here, and I'd like to hear what other people think about it.
>
> Regards,
> Yihui
> --
> Yihui Xie <xieyihui at gmail.com>
> Web: http://yihui.name
>
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