Maybe something like this:
> isRecommendedPkg <- utils:::isBasePkg
> body(isRecommendedPkg)[[c(3L, 3L)]] <- "recommended"
> installed <- unique(list.files(.libPaths()))
> installed[vapply(installed, isRecommendedPkg, NA)]
[1] "KernSmooth" "MASS" "Matrix" "boot" "class"
[6] "cluster" "codetools" "foreign" "lattice" "mgcv"
[11] "nlme" "nnet" "rpart" "spatial" "survival"
where in your package you would define isRecommendedPkg "manually".
Another (but quite undocumented and so maybe not "recommended" :-))
possibility is this:
> mk <- file.path(R.home("share"), "make", "vars.mk")
> pp <- sub("^.*= +", "", grep("^R_PKGS_RECOMMENDED", readLines(mk), value
= TRUE))
> sort(strsplit(pp, " ")[[1L]])
[1] "KernSmooth" "MASS" "Matrix" "boot" "class"
[6] "cluster" "codetools" "foreign" "lattice" "mgcv"
[11] "nlme" "nnet" "rpart" "spatial" "survival"
I grepped around and did not find variables in any base namespace containing
the names of these packages. It wouldn't be too hard to define such variables
when R is configured/built, but maybe there are "reasons" to not do that ... ?
Mikael
> It would be much faster (but slightly less reliable) to use
> list.files(.libPaths()) to get the names of all installed packages, and
> then filter them to the known list of base and recommended packages,
> which changes very rarely.
>
> Duncan Murdoch
>
> On 12/10/2023 8:34 a.m., Tony Wilkes wrote:
> > Dear all,
> >
> > In my R package that I'm developing, I use `installed.packages(priority =
"base")` to programmatically get all core/base R packages (i.e. base, stats,
etc.). And similarly, I use installed.packages(priority = "recommended")` to
programmatically get the recommended R packages (i.e. mgcv, lattice, etc.).
> >
> > However, CRAN has requested to not use `installed.packages()`, as it is
slow. I fully get and agree with that assesment. I used installed.packages()`
anyway because I could not find a better, fool-proof alternative.
> >
> > Nonetheless, I was asked to change this code for optimalisation. So I would
like to ask: how do I programmatically get all base/core R packages safely and
efficiently, but without using `installed.packages()`? And the same question for
recommended R packages. I have of course Googled it, and looked at R's
documentation (though R's documentation is large, so it's easy to miss
something); no solution found. So if any of you has a smart idea: I'm all ears.
> >
> > Thank you in advance.
> >
> > Kind regards,
> >
> > Tony.
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