Time to revisit ifelse ?

On Tue, Jul 8, 2025 at 10:55?AM Josiah Parry <josiah.parry at gmail.com> wrote:

I think the point is not that there needs to be a smaller package for yet
another if-else (https://xkcd.com/927/). It is that if the R-language, as a
whole, had a performant if-else in the base of the language would benefit
**everyone** such that a data.table or dplyr or gtools etc. alternative
would not be necessary.

While that may be true, Josiah, R Core's time is very limited.
Following Duncan's idea, if a small, simple package were created and
was proven to dominate the performance of standard ifelse without
causing any issues with the ten thousand plus packages in the R
environment, that would make R Core's decision much simpler, whether
or not to use the existing, proved performant code.

Asking R Core to
do the research and testing for something which currently _works_,
albeit not in the most efficient way possible, is pretty much a
non-starter. Do as much work as possible for R Core to have even a
possibility of consideration. For something similar, albeit much less
core (pun intended) to R's code, see this discussion [1] from June
2012 on Kendall's tau, where the code already existed but was deemed
unimportant enough to add to base R.

[1] https://stat.ethz.ch/pipermail/r-devel/2012-June/064351.html

Thanks,

Avi

On Tue, Jul 8, 2025 at 5:09?AM Ben Bolker <bbolker at gmail.com> wrote:

   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 ? 13:25, Duncan Murdoch <murdoch.duncan at gmail.com>

a

?crit :

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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