Make `if_any()` and `if_all()` consistent in all contexts #7747

DavisVaughan · 2025-10-28T17:53:21Z

Closes #7746
Closes #7077

It turns out that our application of if_any() and if_all() was fairly inconsistent. This is due to the fact that they are tricky to get right, we have 2 different implementations of them. One for the expansion case and one for the evaluation case. I've now tried to unify these to use the same underlying implementation, dplyr_list_pany() or dplyr_list_pall() depending on the scenario. I'll probably look into reviving these r-lib/vctrs#1675 because I think they would be useful for this.

In addition to greater consistency across the board, you'll also note that in errors the In argument: label also now reports the original expression pre-expansion in the filter() cases, which is a much better error

In the examples below, for filter(), note that adding () around the if_any() or if_all() calls triggers the evaluation case rather than the expansion case.

library(dplyr)

# With zero inputs, if_any

# Before
df <- tibble(x = 1:2)
filter(df, if_any(c(), identity))
#> # A tibble: 0 × 1
#> # ℹ 1 variable: x <int>
filter(df, (if_any(c(), identity)))
#> # A tibble: 2 × 1
#>       x
#>   <int>
#> 1     1
#> 2     2
filter(df, any())
#> # A tibble: 0 × 1
#> # ℹ 1 variable: x <int>

# After
df <- tibble(x = 1:2)
filter(df, if_any(c(), identity))
#> # A tibble: 0 × 1
#> # ℹ 1 variable: x <int>
filter(df, (if_any(c(), identity)))
#> # A tibble: 0 × 1
#> # ℹ 1 variable: x <int>
filter(df, any())
#> # A tibble: 0 × 1
#> # ℹ 1 variable: x <int>

# With one non-logical input

# Before
df <- tibble(x = 1:2)
filter(df, if_any(x, identity))
#> Error in `filter()`:
#> ℹ In argument: `(function (x) ...`.
#> Caused by error:
#> ! `..1` must be a logical vector, not an integer vector.
filter(df, (if_any(x, identity)))
#> Error in `filter()`:
#> ℹ In argument: `(if_any(x, identity))`.
#> Caused by error:
#> ! `..1` must be a logical vector, not an integer vector.
mutate(df, a = if_any(x, identity))
#> # A tibble: 2 × 2
#>       x     a
#>   <int> <int>
#> 1     1     1
#> 2     2     2

# After
df <- tibble(x = 1:2)
filter(df, if_any(x, identity))
#> Error in `filter()`:
#> ℹ In argument: `if_any(x, identity)`.
#> Caused by error in `if_any()`:
#> ! `x` must be a logical vector, not an integer vector.
filter(df, (if_any(x, identity)))
#> Error in `filter()`:
#> ℹ In argument: `(if_any(x, identity))`.
#> Caused by error in `if_any()`:
#> ! `x` must be a logical vector, not an integer vector.
mutate(df, a = if_any(x, identity))
#> Error in `mutate()`:
#> ℹ In argument: `a = if_any(x, identity)`.
#> Caused by error in `if_any()`:
#> ! `x` must be a logical vector, not an integer vector.

# In general, with non-logical types resulting from applying `.fns` we now error
# more appropriately

# Before
df <- tibble(x = c(TRUE, FALSE), y = c("a", "b"))
filter(df, if_any(c(x, y), identity))
#> Error in `filter()`:
#> ℹ In argument: `|...`.
#> Caused by error in `<function(x) x>(x) | <function(x) x>(y)`:
#> ! operations are possible only for numeric, logical or complex types
filter(df, (if_any(c(x, y), identity)))
#> Error in `filter()`:
#> ℹ In argument: `(if_any(c(x, y), identity))`.
#> Caused by error in `op()`:
#> ! operations are possible only for numeric, logical or complex types

# After
df <- tibble(x = c(TRUE, FALSE), y = c("a", "b"))
filter(df, if_any(c(x, y), identity))
#> Error in `filter()`:
#> ℹ In argument: `if_any(c(x, y), identity)`.
#> Caused by error in `if_any()`:
#> ! `y` must be a logical vector, not a character vector.
filter(df, (if_any(c(x, y), identity)))
#> Error in `filter()`:
#> ℹ In argument: `(if_any(c(x, y), identity))`.
#> Caused by error in `if_any()`:
#> ! `y` must be a logical vector, not a character vector.

DavisVaughan · 2025-10-29T19:55:59Z

CLAUDE.md

@@ -0,0 +1,76 @@
+# CLAUDE.md


Plucked from ellmer, with modifications. I'm just trying it out.

DavisVaughan · 2025-10-29T19:57:10Z

NEWS.md

+
+  * When called with one input, both now return logical vectors rather than the original column.
+
+  * The result of applying `.fns` now must be a logical vector.


This is a breaking change, but hopefully not a common issue? We really do want the result of .fns to be logical vectors, particularly for #7746 to work right.

The vctrs functions for pany/pall will probably also be pretty strict about requiring logical inputs.

DavisVaughan · 2025-10-29T19:59:48Z

R/across.R

+  dplyr_list_pany_pall(x, "any", ..., size = size, error_call = error_call)
+}
+
+dplyr_list_pany_pall <- function(


I'm hoping to just remove this in favor of the vctrs versions soon, but I needed to get the semantics of it right enough to be able to add all the tests here

DavisVaughan · 2025-10-29T20:00:32Z

R/across.R

+  init <- vec_rep(init, times = size)
+
+  reduce(x, op, .init = init)


Having an initial value is an important reason that the 0 and 1 input cases now "just work" correctly. This was NULL before.

DavisVaughan · 2025-10-29T20:04:40Z

R/across.R

+  expr <- expr({
+    ns <- asNamespace("dplyr")

-  combine <- function(x, y) {
-    if (is_null(x)) {
-      y
-    } else {
-      call(op, x, y)
-    }
-  }
-  expr <- reduce(quos, combine, .init = NULL)
+    x <- list(!!!quos)
+
+    # In the evaluation path, `across()` automatically recycles to common size,
+    # so we must here as well for compatibility. `across()` also returns a 0
+    # col, 1 row data frame in the case of no inputs so that it will recycle to
+    # the group size, which we also do here.
+    size <- ns[["dplyr_list_size_common"]](x, absent = 1L, call = call(!!if_fn))
+    x <- ns[["dplyr_list_recycle_common"]](x, size = size, call = call(!!if_fn))
+
+    ns[[!!dplyr_fn]](x, size = size, error_call = call(!!if_fn))
+  })


This is the same kind of trick we use in as_pick_expansion() for the expansion path. I've carefully tried to match it to the evaluation path.

Basically we replace if_any(c(x, y), fn) with something like

x <- list(x = x, y = y) ns <- asNamespace("dplyr") size <- ns[["dplyr_list_size_common"]](x, absent = 1L, call = call(if_any())) x <- ns[["dplyr_list_recycle_common"]](x, size = size, call = call(if_any())) ns[["dplyr_list_pany"]](x, size = size, error_call = call(if_any()))

DavisVaughan · 2025-10-29T20:08:49Z

R/vctrs.R

+# Version of `vec_size_common()` that takes a list.
+# Useful for delaying `!!!` when used within an `expr()` call.
+dplyr_list_size_common <- function(


I'm somewhat convinced that in vctrs we should have exported list_size_common() rather than vec_size_common(), i.e.:

obj_check_vector(x) list_check_all_vectors(xs) vec_size(x) list_size_common(xs) vec_recycle(x) list_recycle_common(xs) vec_cast(x, to) list_cast_common(xs, to)

DavisVaughan · 2025-10-29T20:10:49Z

tests/testthat/test-across.R

  )
 })

+test_that("`across()` recycle `.fns` results to common size", {


Along the way I nearly changed across() to recycle inputs to the group size rather than recycling them to their common size. I think that would have been a mistake so I've added a test to prevent us from ever thinking of doing this.

DavisVaughan · 2025-10-29T20:12:10Z

tests/testthat/test-across.R

+  })
+})
+
+test_that("`if_any()` and `if_all()` have consistent behavior across `filter()` and `mutate()`", {


This is a mega test to make sure things are consistent everywhere.

It's obviously a lot of tests, but I think we really do need them all to be sure we aren't missing an edge case. These are all very hard to reason about since there are so many dimensions that intersect (filter vs mutate, expansion vs evaluation, groups vs no groups, etc)

Let's put it this way, I feel way more confident about this now that we have this test that hits every edge case

And add a battery of tests to ensure we don't regress on this consistency

DavisVaughan changed the title ~~Fix evaluation paths of if_any() and if_all() with zero or one inputs~~ Make if_any() and if_all() consistent in all contexts Oct 29, 2025

DavisVaughan commented Oct 29, 2025

View reviewed changes

DavisVaughan marked this pull request as ready for review October 29, 2025 20:14

DavisVaughan requested a review from lionel- October 29, 2025 20:32

DavisVaughan added 9 commits October 30, 2025 08:46

Add Claude Code files

f391498

More tweaks

c9ff2ed

Accept exactly what Claude Code gave us

16ba69d

Rework Claude's attempt

3aecb7c

Make evaluation and expansion cases more consistent

c22e0f6

And add a battery of tests to ensure we don't regress on this consistency

Remove a TODO and update a snapshot test!

1ed3235

Collect quos first in case the user has a column named ns

a7afead

Update snapshot test

29dab94

Switch to a non snapshot based test

21023cb

DavisVaughan force-pushed the fix/if-across branch from 5ad9c62 to 21023cb Compare October 30, 2025 12:47

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		* When called with one input, both now return logical vectors rather than the original column.

		* The result of applying `.fns` now must be a logical vector.

		init <- vec_rep(init, times = size)

		reduce(x, op, .init = init)

Make if_any() and if_all() consistent in all contexts #7747

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Make `if_any()` and `if_all()` consistent in all contexts #7747

Make `if_any()` and `if_all()` consistent in all contexts #7747

DavisVaughan commented Oct 28, 2025 •

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