rsample fix for rlang::abort as cli_abort for 506

NEWS.md

@@ -4,6 +4,8 @@
 
 * Started moving error messages to cli (#499, #502).
 
+* Error improvements via cli by @PriKalra (#523).
+
 ## Bug fixes
 
 * `vfold_cv()` now utilizes the `breaks` argument correctly for repeated cross-validation (@ZWael, #471).

R/initial_validation_split.R

@@ -120,26 +120,26 @@ initial_validation_split <- function(data,
 
 check_prop_3 <- function(prop, call = rlang::caller_env()) {
   if (!is.numeric(prop)) {
-    rlang::abort("`prop` needs to be numeric.", call = call)
+    cli_abort("{.arg prop} needs to be numeric.", call = call)
   }
   if (any(is.na(prop))) {
-    rlang::abort("`prop` cannot contain `NA`.", call = call)
+    cli_abort("{.arg prop} cannot contain `NA`.", call = call)
   }
   if (any(is.null(prop))) {
-    rlang::abort("`prop` cannot contain `NULL`.", call = call)
+    cli_abort("{.arg prop} cannot contain `NULL`.", call = call)
   }
   if (length(prop) != 2L) {
-    rlang::abort(
-      "`prop` needs to contain the proportions for training and validation.",
+    cli_abort(
+      "{.arg prop} needs to contain the proportions for training and validation.",
       call = call
     )
   }
   if (any(!(prop > 0)) | any(!(prop < 1))) {
-    rlang::abort("Elements of `prop` need to be in (0, 1).", call = call)
+    cli_abort("Elements of {.arg prop} need to be in (0, 1).", call = call)
   }
   if (!(sum(prop) > 0 ) | !(sum(prop) < 1) ) {
-    rlang::abort(
-      "The sum of the proportions in `prop` needs to be in (0, 1).",
+    cli_abort(
+      "The sum of the proportions in {.arg prop} needs to be in (0, 1).",
       call = call
     )
   }
@@ -303,8 +303,8 @@ validation <- function(x, ...) {
 #' @rdname initial_validation_split
 validation.default <- function(x, ...) {
   cls <- class(x)
-  cli::cli_abort(
-    "No method for objects of class{?es}: {cls}"
+  cli_abort(
+    "No method for objects of class{?es}: {.cls {cls}}"
   )
 }
 
@@ -321,18 +321,18 @@ validation.initial_validation_split <- function(x, ...) {
 #' @export
 #' @keywords internal
 analysis.initial_validation_split <- function(x, ...) {
-  rlang::abort(
-    "The initial validation split does not contain an analysis set.",
-    i = "You can access the training data with `training()`."
+  cli_abort(
+    c("The initial validation split does not contain an analysis set.",
+    "i" = "You can access the training data with {.fun training}.")
   )
 }
 
 #' @export
 #' @keywords internal
 assessment.initial_validation_split <- function(x, ...) {
-  rlang::abort(
-    "The initial validation split does not contain an assessment set.",
-    i = "You can access the testing data with `testing()`."
+  cli_abort(
+    c("The initial validation split does not contain an assessment set.",
+    "i" = "You can access the testing data with {.fun testing}.")
   )
 }
 

R/make_groups.R

@@ -296,8 +296,8 @@ check_prop <- function(prop, replace) {
     ((prop <= 1 && replace) || (prop < 1 && !replace))
   acceptable_prop <- acceptable_prop && prop > 0
   if (!acceptable_prop) {
-    rlang::abort(
-      "`prop` must be a number between 0 and 1.",
+    cli_abort(
+      "{.arg prop} must be a number between 0 and 1.",
       call = rlang::caller_env()
     )
   }
@@ -345,13 +345,13 @@ validate_group <- function(group, data, call = rlang::caller_env()) {
   }
 
   if (is.null(group) || !is.character(group) || length(group) != 1) {
-    rlang::abort(
-      "`group` should be a single character value for the column that will be used for splitting.",
+    cli_abort(
+      "{.arg group} should be a single character value for the column that will be used for splitting.",
       call = call
     )
   }
   if (!any(names(data) == group)) {
-    rlang::abort("`group` should be a column in `data`.", call = call)
+    cli_abort("{.arg group} should be a column in {.arg data}.", call = call)
   }
 
   group

R/mc.R

@@ -104,7 +104,7 @@ mc_complement <- function(ind, n) {
 mc_splits <- function(data, prop = 3 / 4, times = 25,
                       strata = NULL, breaks = 4, pool = 0.1) {
   if (!is.numeric(prop) | prop >= 1 | prop <= 0) {
-    rlang::abort("`prop` must be a number on (0, 1).")
+    cli_abort("{.arg prop} must be a number on (0, 1).")
   }
 
   n <- nrow(data)
@@ -244,7 +244,7 @@ group_mc_splits <- function(data, group, prop = 3 / 4, times = 25, strata = NULL
 
   all_assessable <- purrr::map(split_objs, function(x) nrow(assessment(x)))
   if (any(all_assessable == 0)) {
-    rlang::abort(
+    cli_abort(
       c(
         "Some assessment sets contained zero rows",
         i = "Consider using a non-grouped resampling method"

R/nest.R

@@ -80,9 +80,9 @@ nested_cv <- function(data, outside, inside) {
 
   inner_cl <- cl[["inside"]]
   if (!is_call(inner_cl)) {
-    abort(
-      "`inside` should be a expression such as `vfold()` or ",
-      "bootstraps(times = 10)` instead of an existing object.",
+    cli_abort(
+      "{.arg inside} should be a expression such as {.code vfold()} or
+      {.code bootstraps(times = 10)} instead of an existing object."
     )
   }
   inside <- map(outside$splits, inside_resample, cl = inner_cl, env = env)

tests/testthat/_snaps/initial_validation_split.md

@@ -5,6 +5,7 @@
     Condition
       Error in `analysis()`:
       ! The initial validation split does not contain an analysis set.
+      i You can access the training data with `training()`.
 
 ---
 
@@ -13,6 +14,7 @@
     Condition
       Error in `assessment()`:
       ! The initial validation split does not contain an assessment set.
+      i You can access the testing data with `testing()`.
 
 # basic split stratified
 
@@ -49,6 +51,7 @@
     Condition
       Error in `analysis()`:
       ! The initial validation split does not contain an analysis set.
+      i You can access the training data with `training()`.
 
 ---
 
@@ -57,6 +60,7 @@
     Condition
       Error in `assessment()`:
       ! The initial validation split does not contain an assessment set.
+      i You can access the testing data with `testing()`.
 
 # check_prop_3() works
 

tests/testthat/_snaps/nesting.md

@@ -25,8 +25,8 @@
     Code
       nested_cv(mtcars, outside = vfold_cv(), inside = folds)
     Condition
-      Error in `list2()`:
-      ! Argument 3 can't be empty.
+      Error in `nested_cv()`:
+      ! `inside` should be a expression such as `vfold()` or `bootstraps(times = 10)` instead of an existing object.
 
 # printing