Cleanup for separate() and spread()

NEWS.md

@@ -52,6 +52,8 @@
 
 * `unite()` now removes old columns before adding new (#89, @krlmlr).
 
+* `separate()` now warns if defunct ... argument is used (#151, @krlmlr).
+
 # tidyr 0.3.1
 
 * Fixed bug where attributes of non-gather columns were lost (#104)

R/separate.R

@@ -71,8 +71,7 @@ separate <- function(data, col, into, sep = "[^[:alnum:]]+", remove = TRUE,
 #' @param convert If \code{TRUE}, will run \code{\link{type.convert}} with
 #'   \code{as.is = TRUE} on new columns. This is useful if the component
 #'   columns are integer, numeric or logical.
-#' @param ... Other arguments passed on to \code{\link{strsplit}} to control
-#'   how the regular expression is processed.
+#' @param ... Defunct, will be removed in the next version of the package.
 #' @keywords internal
 #' @export
 separate_ <- function(data, col, into, sep = "[^[:alnum:]]+", remove = TRUE,
@@ -87,6 +86,10 @@ separate_.data.frame <- function(data, col, into, sep = "[^[:alnum:]]+",
   stopifnot(is.character(col), length(col) == 1)
   value <- as.character(data[[col]])
 
+  if (length(list(...)) != 0) {
+    warning("Using ... for passing arguments to strsplit is defunct.")
+  }
+
   if (is.numeric(sep)) {
     l <- strsep(value, sep)
   } else if (is.character(sep)) {
@@ -116,9 +119,9 @@ separate_.tbl_df <- function(data, col, into, sep = "[^[:alnum:]]+",
 }
 
 #' @export
-separate_.tbl_df <- function(data, col, into, sep = "[^[:alnum:]]+",
-                             remove = TRUE, convert = FALSE,
-                             extra = "warn", fill = "warn", ...) {
+separate_.grouped_df <- function(data, col, into, sep = "[^[:alnum:]]+",
+                                 remove = TRUE, convert = FALSE,
+                                 extra = "warn", fill = "warn", ...) {
   dplyr::grouped_df(NextMethod(), dplyr::groups(data))
 }
 

R/spread.R

@@ -137,8 +137,8 @@ spread_.tbl_df <- function(data, key_col, value_col, fill = NA,
 }
 
 #' @export
-spread_.tbl_df <- function(data, key_col, value_col, fill = NA,
-                           convert = FALSE, drop = TRUE) {
+spread_.grouped_df <- function(data, key_col, value_col, fill = NA,
+                               convert = FALSE, drop = TRUE) {
   regroup(data, NextMethod(), except = c(key_col, value_col))
 }