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arrange for numeric_version does not work in dplyr 1.1.0 #6680

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eitsupi opened this issue Feb 2, 2023 · 0 comments · Fixed by r-lib/vctrs#1782 or #6699
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arrange for numeric_version does not work in dplyr 1.1.0 #6680

eitsupi opened this issue Feb 2, 2023 · 0 comments · Fixed by r-lib/vctrs#1782 or #6699
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@eitsupi
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eitsupi commented Feb 2, 2023

The following code seems to have stopped working in dplyr 1.1.0.
Sorting by version number was useful and I hope this will work again.

library(dplyr, warn.conflicts = FALSE)

tibble(a = numeric_version(c("1.2.3", "1.2.2"))) |>
  arrange(a)
#> Error: This type is not supported by `vec_order()`.

Created on 2023-02-02 with reprex v2.0.2

eitsupi added a commit to rocker-org/rocker-versioned2 that referenced this issue Feb 2, 2023
Related to #597

It seems that the wiki update is failing due to a bug caused by two software version upgrades.

- Error parsing docker-bake.json file (docker/buildx#1586)
- `dplyr::arrange` does not work with `numeric_version` vector (tidyverse/dplyr#6680)

This PR change the string that is believed to be causing the false positives in docker-bake.json and avoids the problem by using the old dplyr.
@DavisVaughan DavisVaughan added this to the 1.1.1 milestone Feb 7, 2023
eitsupi added a commit to rocker-org/rocker-versioned2 that referenced this issue Mar 29, 2023
This reverts commit 0cf526e.

dplyr 1.1.1 was released and the issue of `arrange()` was fixed.
(tidyverse/dplyr#6680)
netbsd-srcmastr pushed a commit to NetBSD/pkgsrc that referenced this issue Jun 2, 2023
# vctrs 0.6.2

* Fixed conditional S3 registration to avoid a CRAN check NOTE that appears in
  R >=4.3.0 (#1832).

* Fixed tests to maintain compatibility with the next version of waldo (#1829).

# vctrs 0.6.1

* Fixed a test related to `c.sfc()` changes in sf 1.0-10 (#1817).

# vctrs 0.6.0

* New `vec_run_sizes()` for computing the size of each run within a vector. It
  is identical to the `times` column from `vec_unrep()`, but is faster if you
  don't need the run key (#1210).

* New `sizes` argument to `vec_chop()` which allows you to partition a vector
  using an integer vector describing the size of each expected slice. It is
  particularly useful in combination with `vec_run_sizes()` and `list_sizes()`
  (#1210, #1598).

* New `obj_is_vector()`, `obj_check_vector()`, and `vec_check_size()` validation
  helpers. We believe these are a better approach to vector validation than
  `vec_assert()` and `vec_is()`, which have been marked as questioning because
  the semantics of their `ptype` arguments are hard to define and can often be
  replaced by `vec_cast()` or a type predicate function like
  `rlang::is_logical()` (#1784).

* `vec_is_list()` and `vec_check_list()` have been renamed to `obj_is_list()`
  and `obj_check_list()`, in line with the new `obj_is_vector()` helper. The
  old functions have been silently deprecated, but an official deprecation
  process will start in the next vctrs release (#1803).

* `vec_locate_matches()` gains a new `relationship` argument that holistically
  handles multiple matches between `needles` and `haystack`. In particular,
  `relationship = "many-to-one"` replaces `multiple = "error"` and
  `multiple = "warning"`, which have been removed from the documentation and
  silently soft-deprecated. Official deprecation for those options will start in
  a future release (#1791).

* `vec_locate_matches()` has changed its default `needles_arg` and
  `haystack_arg` values from `""` to `"needles"` and `"haystack"`, respectively.
  This generally generates more informative error messages (#1792).

* `vec_chop()` has gained empty `...` between `x` and the optional `indices`
  argument. For backwards compatibility, supplying `vec_chop(x, indices)`
  without naming `indices` still silently works, but will be deprecated in a
  future release (#1813).

* `vec_slice()` has gained an `error_call` argument (#1785).

* The `numeric_version` type from base R is now better supported in equality,
  comparison, and order based operations (tidyverse/dplyr#6680).

* R >=3.5.0 is now explicitly required. This is in line with the tidyverse
  policy of supporting the [5 most recent versions of
  R](https://www.tidyverse.org/blog/2019/04/r-version-support/).
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