Make tibble a soft rather than hard dependency

DESCRIPTION

@@ -11,9 +11,8 @@ LazyData: true
 URL: https://github.com/r-lib/rematch2#readme
 BugReports: https://github.com/r-lib/rematch2/issues
 RoxygenNote: 7.1.0
-Imports:
-    tibble
 Suggests:
     covr,
-    testthat
+    testthat,
+    tibble
 Encoding: UTF-8

NAMESPACE

@@ -10,5 +10,3 @@ export(re_exec)
 export(re_exec_all)
 export(re_match)
 export(re_match_all)
-importFrom(tibble,new_tibble)
-importFrom(tibble,tibble)

R/all.R

@@ -69,12 +69,13 @@ re_match_all <- function(text, pattern, perl=TRUE, ...) {
     res,
     names = c(attr(match[[1]], "capture.names"), ".match"),
     row.names = seq_along(text),
-    class = c("tbl_df", "tbl", "data.frame")
+    class = "data.frame"
   )
 
   res$.text <- text
   nc <- ncol(res)
-  res[, c(seq_len(nc - 2), nc, nc - 1)]
+  res <- res[, c(seq_len(nc - 2), nc, nc - 1)]
+  as_tibble(res)
 }
 
 match1 <- function(text1, match1) {

R/bind_re_match.R

@@ -2,7 +2,8 @@
 #'
 #' Taking a data frame and a column name as input, this function will run
 #' \code{\link{re_match}} and bind the results as new columns to the original
-#' table., returning a \code{\link[tibble]{tibble}}. This makes it friendly for
+#' table., returning a \code{\link[tibble]{tibble}} if the tibble package is
+#' installed, a \code{data.frame} otherwise. This makes it friendly for
 #' pipe-oriented programming with \link[magrittr]{magrittr}.
 #'
 #' @note If named capture groups will result in multiple columns with the same
@@ -23,7 +24,8 @@
 #'   suitable for programming.
 #'
 #' @examples
-#' match_cars <- tibble::rownames_to_column(mtcars)
+#' match_cars <- mtcars
+#' match_cars$rowname <- rownames(mtcars)
 #' bind_re_match(match_cars, rowname, "^(?<make>\\w+) ?(?<model>.+)?$")
 #'
 #' @export
@@ -36,7 +38,9 @@ bind_re_match <- function(df, from, ..., keep_match = FALSE) {
 bind_re_match_ <- function(df, from, ..., keep_match = FALSE) {
 
   stopifnot(is.data.frame(df))
-  if (!tibble::has_name(df, from))
+  stopifnot(is_installed("tibble"))
+
+  if (!from %in% names(df))
     stop(from, " is not present in the data frame.")
 
   res <- re_match(text = df[[from]], ...)

R/exec.R

@@ -81,10 +81,11 @@ re_exec <- function(text, pattern, perl=TRUE, ...) {
     })
   )
 
-  res <- new_tibble(
+  res <- structure(
     list(text, matchlist),
     names = c(".text", ".match"),
-    nrow = length(text)
+    row.names = seq_along(text),
+    class = "data.frame"
   )
 
   if (!is.null(attr(match, "capture.start"))) {
@@ -113,10 +114,11 @@ re_exec <- function(text, pattern, perl=TRUE, ...) {
       }
     )
 
-    res <- new_tibble(
+    res <- structure(
       c(grouplists, res),
       names = c(attr(match, "capture.names"), ".text", ".match"),
-      nrow = length(res[[1]])
+      row.names = seq_along(text),
+      class = "data.frame"
     )
   }
 

R/package.R

@@ -5,7 +5,6 @@
 #' groups from the match of a regular expression to a character vector.
 #' See \code{\link{re_match}}.
 #'
-#' @importFrom tibble tibble new_tibble
 "_PACKAGE"
 
 #' Extract Regular Expression Matches Into a Data Frame
@@ -78,6 +77,6 @@ re_match <- function(text, pattern, perl = TRUE, ...) {
   }
 
   names(res) <- c(attr(match, "capture.names"), ".text", ".match")
-  class(res) <- c("tbl_df", "tbl", class(res))
-  res
+
+  as_tibble(res)
 }

R/utils.R

@@ -0,0 +1,11 @@
+as_tibble <- function(x) {
+  if (is_installed("tibble")) {
+    tibble::new_tibble(x, nrow = NROW(x))
+  } else {
+    x
+  }
+}
+
+is_installed <- function(pkg) {
+  isTRUE(requireNamespace(pkg, quietly = TRUE))
+}