Do not allow fitted recipes

[topepo]

Another thing that I've seen is that people prep a recipe then use add_recipe(). Can we error when that happens and add something to the man file for add_recipe()?

library(tidymodels)

training <- mtcars[1:20, ]
testing <- mtcars[21:32, ]

model <- linear_reg() %>%
  set_engine("lm")

workflow <- workflow() %>%
  add_model(model)

recipe <- recipe(mpg ~ cyl + disp, training) %>%
  step_log(disp) %>% 
  prep()

map_lgl(recipe$steps, is_trained)
#> [1] TRUE

workflow <- add_recipe(workflow, recipe)

fit_workflow <- fit(workflow, training)

^{Created on 2022-09-21 by the reprex package (v2.0.1)}

[DavisVaughan]

Maybe recipes::is_trained() should do all(map_lgl(x$steps, is_trained)) if given a recipe. Then workflows can do

if (recipes::is_trained(recipe)) {
  abort("Can't add a trained recipe to a workflow.")
}

I wouldn't worry too much about partially trained recipes

[simonpcouch]

Unfortunately the all(map_lgl(rec$steps, is_trained)) approach wouldn't do the trick either, as in the no-steps case:

library(recipes)

rec <- recipe(mpg ~ cyl, mtcars)
rec_trained <- recipe(mpg ~ cyl, mtcars) %>% prep()
  
all(purrr::map_lgl(rec$steps, is_trained))
#> [1] TRUE
all(purrr::map_lgl(rec_trained$steps, is_trained))
#> [1] TRUE

From the print.recipe() method, though, it looks like "tr_info" %in% names(x) is a flag we could look to:

"tr_info" %in% names(rec)
#> [1] FALSE
"tr_info" %in% names(rec_trained)
#> [1] TRUE

@EmilHvitfeldt, would you game for a PR that transitions is_trained() to a method with a recipe and default method?

^{Created on 2023-05-05 with reprex v2.0.2}

[EmilHvitfeldt]

Are you looking for fully_trained()?

library(recipes)

rec <- recipe(mpg ~ cyl, mtcars)
rec_trained <- recipe(mpg ~ cyl, mtcars) %>% prep()

fully_trained(rec)
#> [1] FALSE

fully_trained(rec_trained)
#> [1] TRUE

[simonpcouch]

Perfect, thanks so much @EmilHvitfeldt!

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