(This crossed with Martin Ondrus's reply).
In the past few years CRAN screeners have gotten more strict about
\dontrun{}; a first-round screening often comes back requesting that
\dontrun{}, and commented-out examples, not be used.
https://stat.ethz.ch/pipermail/r-package-devel/2018q3/003084.html
https://stat.ethz.ch/pipermail/r-package-devel/2018q2/002811.html
Guido, perhaps the screening is being applied differently in your case?
Another strategy, albeit one that is a little bit annoying/requires
some more machinery, is to store pre-computed objects in
inst/example-data, then do something like
fitted_model <- readRDS(system.file("example-data", "fit1.rds", package
= "my_pkg"))
the object (which takes too long to fit as part of a testing flow)
then becomes available for showing how methods apply to it.
cheers
Ben
On 11/16/21 2:56 PM, Guido Schwarzer wrote:
Am 16.11.21 um 20:16 schrieb Martin Ondrus:
Hi Duncan,
That's a fair point, and I think making the examples run quicker probably
makes the most sense. I have bad experiences with using dontrun - my
package always gets flagged. Although not ideal, it's probably better to
include some very fast running examples rather than none at all.
Appreciate
your advice/help!
I have been using dontrun for a long time (and I am still using it)
without any real issues. Initially, I used it to get rid of runtime
notes impeding submission to CRAN. Now I am also using it for additional
features, e.g., to describe some additional analyses / figure layouts.
I always check my packages under R-devel on
https://win-builder.r-project.org/ before submission to CRAN. If this
does not trigger any notes, the package is good to go.
Best, Guido
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Dr. Benjamin Bolker
Professor, Mathematics & Statistics and Biology, McMaster University
Director, School of Computational Science and Engineering
(Acting) Graduate chair, Mathematics & Statistics
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