On Thu, 20 Oct 2011, Rainer M Krug wrote:
On Wed, Oct 19, 2011 at 8:05 PM, G?bor Cs?rdi <csa...@rmki.kfki.hu> wrote:
Dear R developers,
I am seeking advice on some $subject matter.
If this is intended to be a CRAN update, then really you need to ask
the CRAN crew about the possible implications (and I've sent a private
reply to Gábor and them).
My package will have an update soon, that is not backward compatible
with the current version. It will likely break much of the existing
code. Many (~50) packages depend on 'igraph' and they, too, will most
probably break with the new version.
Don't forget the indirect dependencies - might be many more.
Why would they need to change? There are indeed current 50 CRAN/BioC
packages which directly depend on igraph according to
tools::dependsOnPkgs(). However, there are another 12 which
'Suggests: igraph', and those might need to change.
One approach used by e.g. ggplot and roxygen, is to call the new package
ggplot2 or roxygen2. This would not break old packages.
My intended solution is, that I create a snapshot of the current
package, under another name (igraph0), and ask package maintainers to
depend on that version. Then, after a short time, I'll update the
current igraph version.
I would rather give the new one a a new name by appending the 2
Do you see any drawbacks of this solution? Is there some existing
practice for situations like this? Suggestions are greatly
appreciated.
Well - they require immediate action by the package maintainers. Yo could
put a warning in the original iplot package, that the package is not updated
any more and that a switch to iplot 2 is suggested. So no immediate action
by the package maintainers is required.
Cheers,
Rainer
Btw. an alternative would be to ask them to depend on the exact
current version of the package. This is an easier solution, but it
won't give people the opportunity to load both versions of the package
at the same time, if they want to run their old code.
Thank You, Best Regards,
Gabor
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Gabor Csardi <csardi.ga...@gmail.com> Dept. Statistics, Harvard University
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