uninformative error without needed parsnip extension

[simonpcouch]

Related to tidymodels/parsnip#793: add_model() is another step where we can be confident a user has "finished" defining their model spec, and we can warn or error then if a user hasn't loaded the needed parsnip extension package.

# note: do not load required parsnip extension
library(parsnip)
library(workflows)

bt_mod <- bag_tree() %>%
  set_engine("rpart") %>%
  set_mode("regression")

bt_wf <- workflow() %>%
  add_model(bt_mod) %>%
  add_formula(mpg ~ .)

fit(bt_wf, data = mtcars)
#> Error in if (nrow(out) != 1L) {: argument is of length zero

# works fine with baguette loaded
library(baguette)

fit(bt_wf, data = mtcars)
#> ══ Workflow [trained] ══════════════════════════════════════════════════════════
#> Preprocessor: Formula
#> Model: bag_tree()
#> 
#> ── Preprocessor ────────────────────────────────────────────────────────────────
#> mpg ~ .
#> 
#> ── Model ───────────────────────────────────────────────────────────────────────
#> Bagged CART (regression with 11 members)
#> 
#> Variable importance scores include:
#> 
#> # A tibble: 10 × 4
#>    term  value std.error  used
#>    <chr> <dbl>     <dbl> <int>
#>  1 wt    849.       95.5    11
#>  2 hp    843.       82.4    11
#>  3 disp  840.       79.4    11
#>  4 drat  480.       90.5    11
#>  5 cyl   459.       56.3    11
#>  6 qsec  220.       46.4    11
#>  7 am     70.1      40.3     9
#>  8 gear   60.7      29.4     7
#>  9 vs     60.0      23.3    10
#> 10 carb   51.6      18.2    11

^{Created on 2022-09-08 by the reprex package (v2.0.1)}

[DavisVaughan]

See #175 (comment)

[github-actions]

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