I think Duncan's point is that R-core are (reasonably) very, very,
very conservative about adding things to base R. It would be useful to
the community, and would indeed further the discussion, to make a tiny
package containing just that function. (Even just copying it from some
other package might require some work to disentangle it from
dependencies: for example, a quick glance at dplyr::if_else shows that
it uses functions from rlang, vctrs, ...)
I'd be happy to accept a pull request in `gtools`, which is a
zero-dependency (except base R) package for small utility functions ...
cheers
Ben Bolker
On 7/8/25 07:36, Antoine Fabri wrote:
It's not about asking others to do it really, that was a harsh assumption.
I'd be happy to propose a version if it helps, I'd be also very happy if it
were just a copy of if_else or fifelse (both MIT FWIW).
It's a low level building block and it's broken, IMO it's way better to
have it available and documented in base R and incite everyone to use it,
so not only we don't suffer from it in the code we write, but also in the
code we use or inherit from.
Le mar. 8 juil. 2025 à 13:25, Duncan Murdoch <murdoch.dun...@gmail.com> a
écrit :
Rather than asking others to do this, why don't you create a tiny
package containing nothing other than an ifelse() replacement? I
wouldn't want to depend on dplyr or data.table just to get their
versions, but depending on your tiny package wouldn't be an issue.
Duncan Murdoch
On 2025-07-08 6:12 a.m., Antoine Fabri wrote:
Dear r-devel,
`ifelse()` has a lot of issues, and for these reasons it has been redone
in
`dplyr::if_else()` and `data.table::fifelse()`, which are both great. Yet
it's an important base R function, it's really hard to program in base R
without it and scores probably as high as it gets in the most_used *
most_problematic metric.
Obviously we can't change it without breaking a ton of code, but with all
the experience we now have with it and the dplyr and data.table
alternative
maybe it might not be absurd to have a good alternative, say `if.else` in
base R, that we can document on the same page and recommend for future
use.
It would require a common type in yes/no, not return logical() for all
zero
length input, work with dates, datetimes and factors, handle a na
condition
etc. The test suites of dplyr and data.table probably tell us everything
about the edge cases we want to look at. Maybe the old ifelse could even
warn when called from the top level, to incite us to work with the new
one.
It feels wrong to me to be stuck with ifelse() forever just because it
has
been like this for a long time. I'm sure some of you learnt your way
around
it but I work with R every day and after 10+ years of R it still bites me
all the time, I'm probably not alone, at least chatGPT called it a
"footgun", and we don't want that :).
Thanks,
Antoine
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Dr. Benjamin Bolker
Professor, Mathematics & Statistics and Biology, McMaster University
Director, School of Computational Science and Engineering
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