version 1.0.2

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: dplyr
 Title: A Grammar of Data Manipulation
-Version: 1.0.1
+Version: 1.0.2
 Authors@R: 
     c(person(given = "Hadley",
              family = "Wickham",
@@ -13,7 +13,8 @@ Authors@R:
              role = "aut",
              comment = c(ORCID = "0000-0002-2444-4226")),
       person(given = "Lionel",
-             family = "Henry",
+             family = "
+             Henry",
              role = "aut"),
       person(given = "Kirill",
              family = "Müller",
@@ -38,12 +39,12 @@ Encoding: UTF-8
 LazyData: yes
 RoxygenNote: 7.1.1
 NeedsCompilation: yes
-Packaged: 2020-07-22 12:06:49 UTC; romainfrancois
+Packaged: 2020-08-12 15:16:36 UTC; romainfrancois
 Author: Hadley Wickham [aut, cre] (<https://orcid.org/0000-0003-4757-117X>),
   Romain François [aut] (<https://orcid.org/0000-0002-2444-4226>),
   Lionel Henry [aut],
   Kirill Müller [aut] (<https://orcid.org/0000-0002-1416-3412>),
   RStudio [cph, fnd]
 Maintainer: Hadley Wickham <hadley@rstudio.com>
 Repository: CRAN
-Date/Publication: 2020-07-31 07:00:05 UTC
+Date/Publication: 2020-08-18 12:30:02 UTC

NAMESPACE

@@ -459,7 +459,7 @@ export(with_groups)
 export(with_order)
 export(wrap_dbplyr_obj)
 import(rlang)
-import(vctrs)
+import(vctrs, except = data_frame)
 importFrom(R6,R6Class)
 importFrom(generics,intersect)
 importFrom(generics,setdiff)

NEWS.md

@@ -1,3 +1,13 @@
+# dplyr 1.0.2
+
+* Fixed `across()` issue where data frame columns would mask objects referred to
+  from `all_of()` (#5460).
+
+* `bind_cols()` gains a `.name_repair` argument, passed to `vctrs::vec_cbind()` (#5451)
+
+* `summarise(.groups = "rowwise")` makes a rowwise data frame even if the input data 
+  is not grouped (#5422). 
+
 # dplyr 1.0.1
 
 * New function `cur_data_all()` similar to `cur_data()` but includes the grouping variables (#5342). 
@@ -61,7 +71,7 @@
 * `lead()` and `lag()` are stricter about their inputs. 
 
 * Extending data frames requires that the extra class or classes are added first, not last. 
-  Having the extact class at the end causes some vctrs operations to fail with a message like:
+  Having the extra class at the end causes some vctrs operations to fail with a message like:
 
   ```
   Input must be a vector, not a `<data.frame/...>` object
@@ -267,7 +277,7 @@
 
 * `src_mysql()`, `src_postgres()`, and `src_sqlite()` has been deprecated. 
   We've recommended against them for some time. Instead please use the approach 
-  described at <http://dbplyr.tidyverse.org/>.
+  described at <https://dbplyr.tidyverse.org/>.
 
 * `select_vars()`, `rename_vars()`, `select_var()`, `current_vars()` are now
   deprecated (@perezp44, #4432)
@@ -1022,7 +1032,7 @@
 This version of dplyr includes some major changes to how database connections work. By and large, you should be able to continue using your existing dplyr database code without modification, but there are two big changes that you should be aware of:
 
 * Almost all database related code has been moved out of dplyr and into a
-  new package, [dbplyr](http://github.com/hadley/dbplyr/). This makes dplyr
+  new package, [dbplyr](https://github.com/tidyverse/dbplyr/). This makes dplyr
   simpler, and will make it easier to release fixes for bugs that only affect
   databases. `src_mysql()`, `src_postgres()`, and `src_sqlite()` will still
   live dplyr so your existing code continues to work.
@@ -1048,7 +1058,7 @@ mtcars2
 
 This is particularly useful if you want to perform non-SELECT queries as you can do whatever you want with `DBI::dbGetQuery()` and `DBI::dbExecute()`.
 
-If you've implemented a database backend for dplyr, please read the [backend news](https://github.com/hadley/dbplyr/blob/master/NEWS.md#backends) to see what's changed from your perspective (not much). If you want to ensure your package works with both the current and previous version of dplyr, see `wrap_dbplyr_obj()` for helpers.
+If you've implemented a database backend for dplyr, please read the [backend news](https://github.com/tidyverse/dbplyr/blob/master/NEWS.md#backends) to see what's changed from your perspective (not much). If you want to ensure your package works with both the current and previous version of dplyr, see `wrap_dbplyr_obj()` for helpers.
 
 ## UTF-8
 
@@ -1387,7 +1397,7 @@ and so these functions have been deprecated (but remain around for backward comp
 * Outdated benchmarking demos have been removed (#1487).
 
 * Code related to starting and signalling clusters has been moved out to
-  [multidplyr](http://github.com/hadley/multidplyr).
+  [multidplyr](https://github.com/tidyverse/multidplyr).
 
 ## New functions
 

R/across.R

@@ -31,10 +31,10 @@
 #'   to access the current column and grouping keys respectively.
 #' @param ... Additional arguments for the function calls in `.fns`.
 #' @param .names A glue specification that describes how to name the output
-#'   columns. This can use `{col}` to stand for the selected column name, and
-#'   `{fn}` to stand for the name of the function being applied. The default
-#'   (`NULL`) is equivalent to `"{col}"` for the single function case and
-#'   `"{col}_{fn}"` for the case where a list is used for `.fns`.
+#'   columns. This can use `{.col}` to stand for the selected column name, and
+#'   `{.fn}` to stand for the name of the function being applied. The default
+#'   (`NULL`) is equivalent to `"{.col}"` for the single function case and
+#'   `"{.col}_{.fn}"` for the case where a list is used for `.fns`.
 #'
 #' @returns
 #' A tibble with one column for each column in `.cols` and each function in `.fns`.
@@ -60,13 +60,13 @@
 #' # Use the .names argument to control the output names
 #' iris %>%
 #'   group_by(Species) %>%
-#'   summarise(across(starts_with("Sepal"), mean, .names = "mean_{col}"))
+#'   summarise(across(starts_with("Sepal"), mean, .names = "mean_{.col}"))
 #' iris %>%
 #'   group_by(Species) %>%
-#'   summarise(across(starts_with("Sepal"), list(mean = mean, sd = sd), .names = "{col}.{fn}"))
+#'   summarise(across(starts_with("Sepal"), list(mean = mean, sd = sd), .names = "{.col}.{.fn}"))
 #' iris %>%
 #'   group_by(Species) %>%
-#'   summarise(across(starts_with("Sepal"), list(mean, sd), .names = "{col}.fn{fn}"))
+#'   summarise(across(starts_with("Sepal"), list(mean, sd), .names = "{.col}.fn{.fn}"))
 #'
 #' # c_across() ---------------------------------------------------------------
 #' df <- tibble(id = 1:4, w = runif(4), x = runif(4), y = runif(4), z = runif(4))
@@ -79,7 +79,7 @@
 #' @export
 across <- function(.cols = everything(), .fns = NULL, ..., .names = NULL) {
   key <- key_deparse(sys.call())
-  setup <- across_setup({{ .cols }}, fns = .fns, names = .names, key = key)
+  setup <- across_setup({{ .cols }}, fns = .fns, names = .names, key = key, .caller_env = caller_env())
 
   vars <- setup$vars
   if (length(vars) == 0L) {
@@ -148,28 +148,39 @@ c_across <- function(cols = everything()) {
   vec_c(!!!cols, .name_spec = zap())
 }
 
+across_glue_mask <- function(.col, .fn, .caller_env) {
+  glue_mask <- env(.caller_env, .col = .col, .fn = .fn)
+  # TODO: we can make these bindings louder later
+  env_bind_active(
+    glue_mask, col = function() glue_mask$.col, fn = function() glue_mask$.fn
+  )
+  glue_mask
+}
+
 # TODO: The usage of a cache in `across_setup()` and `c_across_setup()` is a stopgap solution, and
 # this idea should not be used anywhere else. This should be replaced by the
 # next version of hybrid evaluation, which should offer a way for any function
 # to do any required "set up" work (like the `eval_select()` call) a single
 # time per top-level call, rather than once per group.
-across_setup <- function(cols, fns, names, key) {
+across_setup <- function(cols, fns, names, key, .caller_env) {
   mask <- peek_mask("across()")
-
   value <- mask$across_cache_get(key)
   if (!is.null(value)) {
     return(value)
   }
 
+  # `across()` is evaluated in a data mask so we need to remove the
+  # mask layer from the quosure environment (#5460)
   cols <- enquo(cols)
-  across_cols <- mask$across_cols()
+  cols <- quo_set_env(cols, data_mask_top(quo_get_env(cols), recursive = TRUE, inherit = TRUE))
 
-  vars <- tidyselect::eval_select(expr(!!cols), across_cols)
+  vars <- tidyselect::eval_select(cols, data = mask$across_cols())
   vars <- names(vars)
 
   if (is.null(fns)) {
     if (!is.null(names)) {
-      names <- vec_as_names(glue(names, col = vars, fn = "1"), repair = "check_unique")
+      glue_mask <- across_glue_mask(.caller_env, .col = vars, .fn = "1")
+      names <- vec_as_names(glue(names, .envir = glue_mask), repair = "check_unique")
     }
 
     value <- list(vars = vars, fns = fns, names = names)
@@ -180,10 +191,10 @@ across_setup <- function(cols, fns, names, key) {
 
   # apply `.names` smart default
   if (is.function(fns) || is_formula(fns)) {
-    names <- names %||% "{col}"
+    names <- names %||% "{.col}"
     fns <- list("1" = fns)
   } else {
-    names <- names %||% "{col}_{fn}"
+    names <- names %||% "{.col}_{.fn}"
   }
 
   if (!is.list(fns)) {
@@ -206,17 +217,30 @@ across_setup <- function(cols, fns, names, key) {
     }
   }
 
-  names <- vec_as_names(glue(names,
-    col = rep(vars, each = length(fns)),
-    fn  = rep(names_fns, length(vars))
-  ), repair = "check_unique")
+  glue_mask <- glue_mask <- across_glue_mask(.caller_env,
+    .col = rep(vars, each = length(fns)),
+    .fn  = rep(names_fns, length(vars))
+  )
+  names <- vec_as_names(glue(names, .envir = glue_mask), repair = "check_unique")
 
   value <- list(vars = vars, fns = fns, names = names)
   mask$across_cache_add(key, value)
 
   value
 }
 
+# FIXME: This pattern should be encapsulated by rlang
+data_mask_top <- function(env, recursive = FALSE, inherit = FALSE) {
+  while (env_has(env, ".__tidyeval_data_mask__.", inherit = inherit)) {
+    env <- env_parent(env_get(env, ".top_env", inherit = inherit))
+    if (!recursive) {
+      return(env)
+    }
+  }
+
+  env
+}
+
 c_across_setup <- function(cols, key) {
   mask <- peek_mask("c_across()")
 

R/arrange.R

@@ -5,7 +5,7 @@
 #' columns.
 #'
 #' Unlike other dplyr verbs, `arrange()` largely ignores grouping; you
-#' need to explicitly mention grouping variables (or use  `by_group = TRUE`)
+#' need to explicitly mention grouping variables (or use  `.by_group = TRUE`)
 #' in order to group by them, and functions of variables are evaluated
 #' once per data frame, not once per group.
 #'
@@ -116,7 +116,24 @@ arrange_rows <- function(.data, dots) {
   data <- withCallingHandlers({
     transmute(new_data_frame(.data), !!!quosures)
   }, error = function(cnd) {
-    stop_arrange_transmute(cnd)
+    if (inherits(cnd, "dplyr:::mutate_error")) {
+      error_name <- cnd$error_name
+      index <- sub("^.*_", "", error_name)
+      error_expression <- cnd$error_expression
+
+      bullets <- c(
+        x = glue("Could not create a temporary column for `..{index}`."),
+        i = glue("`..{index}` is `{error_expression}`.")
+      )
+    } else {
+      bullets <- c(x = conditionMessage(cnd))
+    }
+
+    abort(c(
+      "arrange() failed at implicit mutate() step. ",
+      bullets
+    ), class = "dplyr_error")
+
   })
 
   # we can't just use vec_compare_proxy(data) because we need to apply
@@ -140,19 +157,3 @@ arrange_rows <- function(.data, dots) {
 
   exec("order", !!!unname(proxies), decreasing = FALSE, na.last = TRUE)
 }
-
-# FIXME: Temporary util until the API change from
-# https://github.com/r-lib/vctrs/pull/1155 is on CRAN and we can
-# depend on it
-delayedAssign(
-  "dplyr_proxy_order",
-  if (env_has(ns_env("vctrs"), "vec_proxy_order")) {
-    vec_proxy_order
-  } else {
-    function(x, ...) vec_proxy_compare(x, ..., relax = TRUE)
-  }
-)
-
-# Hack to pass CRAN check with older vctrs versions where
-# `vec_proxy_order()` doesn't exist
-utils::globalVariables("vec_proxy_order")

R/bind.r

@@ -26,6 +26,9 @@
 #'   list of data frames is supplied, the labels are taken from the
 #'   names of the list. If no names are found a numeric sequence is
 #'   used instead.
+#' @param .name_repair One of `"unique"`, `"universal"`, or
+#'   `"check_unique"`. See [vctrs::vec_as_names()] for the meaning of these
+#'   options.
 #' @return `bind_rows()` and `bind_cols()` return the same type as
 #'   the first input, either a data frame, `tbl_df`, or `grouped_df`.
 #' @examples
@@ -146,7 +149,7 @@ bind_rows <- function(..., .id = NULL) {
 
 #' @export
 #' @rdname bind
-bind_cols <- function(...) {
+bind_cols <- function(..., .name_repair = c("unique", "universal", "check_unique", "minimal")) {
   dots <- list2(...)
 
   dots <- squash_if(dots, vec_is_list)
@@ -156,7 +159,7 @@ bind_cols <- function(...) {
   is_data_frame <- map_lgl(dots, is.data.frame)
   names(dots)[is_data_frame] <- ""
 
-  out <- vec_cbind(!!!dots)
+  out <- vec_cbind(!!!dots, .name_repair = .name_repair)
   if (!any(map_lgl(dots, is.data.frame))) {
     out <- as_tibble(out)
   }

R/compat-purrr.R

@@ -1,4 +1,4 @@
-# nocov start - compat-purrr (last updated: rlang 0.3.0.9000)
+# nocov start - compat-purrr (last updated: rlang 0.3.2.9000)
 
 # This file serves as a reference for compatibility functions for
 # purrr. They are not drop-in replacements but allow a similar style
@@ -30,6 +30,11 @@ map_cpl <- function(.x, .f, ...) {
   map_mold(.x, .f, complex(1), ...)
 }
 
+walk <- function(.x, .f, ...) {
+  map(.x, .f, ...)
+  invisible(.x)
+}
+
 pluck <- function(.x, .f) {
   map(.x, `[[`, .f)
 }
@@ -72,15 +77,12 @@ map2_chr <- function(.x, .y, .f, ...) {
 map2_cpl <- function(.x, .y, .f, ...) {
   as.vector(map2(.x, .y, .f, ...), "complex")
 }
-walk2 <- function(.x, .y, .f, ...) {
-  map2(.x, .y, .f, ...)
-  invisible(.x)
-}
+
 args_recycle <- function(args) {
-  lengths <- lengths(args)
+  lengths <- map_int(args, length)
   n <- max(lengths)
 
-  abort_if_not(all(lengths == 1L | lengths == n))
+  stopifnot(all(lengths == 1L | lengths == n))
   to_recycle <- lengths == 1L
   args[to_recycle] <- map(args[to_recycle], function(x) rep.int(x, n))
 
@@ -97,7 +99,7 @@ pmap <- function(.l, .f, ...) {
 
 probe <- function(.x, .p, ...) {
   if (is_logical(.p)) {
-    abort_if_not(length(.p) == length(.x))
+    stopifnot(length(.p) == length(.x))
     .p
   } else {
     map_lgl(.x, .p, ...)