throw better errors when method doesn't exists

R/parsnip.R

@@ -1,6 +1,23 @@
 #' @export
 orbital.model_fit <- function(x, ...) {
-  res <- c(".pred" = deparse1(tidypredict::tidypredict_fit(x)))
+  res <- tryCatch(
+    tidypredict::tidypredict_fit(x),
+    error = function(cnd) {
+      if (grepl("no applicable method for", cnd$message)) {
+        cls <- class(x)
+        cls <- setdiff(cls, "model_fit")
+        cls <- gsub("^_", "", cls)
+
+        cli::cli_abort(
+          "A model of class {.cls {cls}} is not supported.",
+          call = rlang::call2("orbital")
+        )
+      }
+      stop(cnd)
+    }
+  )
+
+  res <- c(".pred" = deparse1(res))
 
   new_orbital_class(res)
 }

R/recipes.R

@@ -19,7 +19,21 @@ orbital.recipe <- function(x, eqs = NULL, ...) {
 
   out <- c(.pred = unname(eqs))
   for (i in rev(seq_len(n_steps))) {
-    res <- orbital(x$steps[[i]], all_vars)
+    res <- tryCatch(
+      orbital(x$steps[[i]], all_vars),
+      error = function(cnd) {
+        if (grepl("not implemented", cnd$message)) {
+          cls <- class(x$steps[[i]])
+          cls <- setdiff(cls, "step")
+
+          cli::cli_abort(
+            "The recipe step {.fun {cls}} is not supported.",
+            call = rlang::call2("orbital")
+          )
+        }
+        stop(cnd)
+      }
+    )
 
     out <- c(res, out)
 

tests/testthat/_snaps/parsnip.md

@@ -0,0 +1,8 @@
+# multiplication works
+
+    Code
+      orbital(wf_fit)
+    Condition
+      Error in `orbital()`:
+      ! A model of class <train.kknn> is not supported.
+

tests/testthat/_snaps/recipes.md

@@ -0,0 +1,8 @@
+# multiplication works
+
+    Code
+      orbital(wf_fit)
+    Condition
+      Error in `orbital()`:
+      ! The recipe step `step_impute_knn()` is not supported.
+

tests/testthat/test-parsnip.R

@@ -0,0 +1,20 @@
+test_that("multiplication works", {
+  skip_if_not_installed("recipes")
+  skip_if_not_installed("parsnip")
+  skip_if_not_installed("workflows")
+  skip_if_not_installed("tidypredict")
+
+  rec_spec <- recipes::recipe(mpg ~ ., data = mtcars) %>%
+    recipes::step_normalize(recipes::all_numeric_predictors())
+
+  lm_spec <- parsnip::nearest_neighbor(mode = "regression")
+
+  wf_spec <- workflows::workflow(rec_spec, lm_spec)
+
+  wf_fit <- parsnip::fit(wf_spec, mtcars)
+
+  expect_snapshot(
+    error = TRUE,
+    orbital(wf_fit)
+  )
+})

tests/testthat/test-recipes.R

@@ -0,0 +1,20 @@
+test_that("multiplication works", {
+  skip_if_not_installed("recipes")
+  skip_if_not_installed("parsnip")
+  skip_if_not_installed("workflows")
+  skip_if_not_installed("tidypredict")
+
+  rec_spec <- recipes::recipe(mpg ~ ., data = mtcars) %>%
+    recipes::step_impute_knn(recipes::all_numeric_predictors())
+
+  lm_spec <- parsnip::linear_reg()
+
+  wf_spec <- workflows::workflow(rec_spec, lm_spec)
+
+  wf_fit <- parsnip::fit(wf_spec, mtcars)
+
+  expect_snapshot(
+    error = TRUE,
+    orbital(wf_fit)
+  )
+})