update tests to no use everything()

tests/testthat/_snaps/class.md

@@ -122,7 +122,7 @@
       predictor: 10
       
       -- Operations 
-      * Checking the class(es) for: everything()
+      * Checking the class(es) for: all_predictors()
 
 ---
 

tests/testthat/_snaps/colcheck.md

@@ -1,7 +1,7 @@
 # check_col works in the bake stage
 
     Code
-      rp1 %>% check_cols(everything()) %>% prep() %>% bake(mtcars[-1])
+      rp1 %>% check_cols(all_predictors()) %>% prep() %>% bake(mtcars[-1])
     Condition
       Error in `bake()`:
       x The following required columns are missing from `new_data`: `mpg`.
@@ -65,7 +65,7 @@
       predictor: 10
       
       -- Operations 
-      * Check if the following columns are present:: everything()
+      * Check if the following columns are present:: all_predictors()
 
 ---
 

tests/testthat/_snaps/cut.md

@@ -11,7 +11,7 @@
 ---
 
     Code
-      recipe(x) %>% step_cut(everything(), breaks = 2) %>% prep()
+      recipe(~., x) %>% step_cut(all_predictors(), breaks = 2) %>% prep()
     Condition
       Error in `step_cut()`:
       Caused by error in `prep()`:

tests/testthat/_snaps/missing.md

@@ -46,7 +46,7 @@
 ---
 
     Code
-      tst(everything())
+      tst(all_predictors())
     Condition
       Error in `check_missing()`:
       Caused by error in `bake()`:

tests/testthat/_snaps/profile.md

@@ -1,7 +1,8 @@
 # bad values
 
     Code
-      sacr_rec %>% step_profile(everything(), profile = vars(sqft)) %>% prep(data = Sacramento)
+      sacr_rec %>% step_profile(all_predictors(), profile = vars(sqft)) %>% prep(
+        data = Sacramento)
     Condition
       Error in `step_profile()`:
       Caused by error in `prep()`:

tests/testthat/_snaps/shuffle.md

@@ -1,7 +1,7 @@
 # bake a single row
 
     Code
-      dat4 <- bake(rec4, dat[1, ], everything())
+      dat4 <- bake(rec4, dat[1, ])
     Condition
       Warning:
       `new_data` contains a single row; unable to shuffle.
@@ -55,7 +55,7 @@
       predictor: 4
       
       -- Operations 
-      * Shuffled: everything()
+      * Shuffled: all_predictors()
 
 ---
 
@@ -74,5 +74,5 @@
       Training data contained 50 data points and no incomplete rows.
       
       -- Operations 
-      * Shuffled: x1, x2, x3, x4, y | Trained
+      * Shuffled: x1, x2, x3, x4 | Trained
 

tests/testthat/test-class.R

@@ -29,8 +29,8 @@ test_that("bake_check_class helper function gives expected output", {
 })
 
 test_that("check_class works when class is learned", {
-  rec1 <- recipe(x) %>%
-    check_class(everything()) %>%
+  rec1 <- recipe(~ ., x) %>%
+    check_class(all_predictors()) %>%
     prep()
 
   expect_error(bake(rec1, x), NA)
@@ -76,7 +76,7 @@ test_that("check_class works when class is provided", {
 # recipes has internal coercion to character >> factor
 test_that("characters are handled correctly", {
   rec5_NULL <- recipe(Sacramento[1:10, ], sqft ~ .) %>%
-    check_class(everything()) %>%
+    check_class(all_predictors()) %>%
     prep(Sacramento[1:10, ], strings_as_factors = FALSE)
 
   expect_error(bake(rec5_NULL, Sacramento[11:20, ]), NA)
@@ -96,7 +96,7 @@ test_that("characters are handled correctly", {
     )
 
   rec6_NULL <- recipe(sacr_fac[1:10, ], sqft ~ .) %>%
-    check_class(everything()) %>%
+    check_class(all_predictors()) %>%
     prep(sacr_fac[1:10, ], strings_as_factors = TRUE)
 
   expect_snapshot(error = TRUE,
@@ -165,7 +165,7 @@ test_that("empty selection tidy method works", {
 
 test_that("printing", {
   rec7 <- recipe(mpg ~ ., mtcars) %>%
-    check_class(everything())
+    check_class(all_predictors())
 
   expect_snapshot(print(rec7))
   expect_snapshot(prep(rec7))

tests/testthat/test-colcheck.R

@@ -5,29 +5,29 @@ rp1 <- recipe(mtcars, cyl ~ .)
 rp2 <- recipe(mtcars, cyl ~ mpg + drat)
 
 test_that("check_col works in the prep stage", {
-  expect_error(rp1 %>% check_cols(everything()) %>% prep(), NA)
-  expect_error(rp2 %>% check_cols(everything()) %>% prep(), NA)
+  expect_error(rp1 %>% check_cols(all_predictors()) %>% prep(), NA)
+  expect_error(rp2 %>% check_cols(all_predictors()) %>% prep(), NA)
   expect_error(rp2 %>% check_cols(cyl, mpg, drat) %>% prep(), NA)
   expect_error(rp2 %>% check_cols(cyl, mpg) %>% prep(), NA)
 })
 
 
 test_that("check_col works in the bake stage", {
 
-  expect_error(rp1 %>% check_cols(everything()) %>% prep() %>% bake(mtcars),
+  expect_error(rp1 %>% check_cols(all_predictors()) %>% prep() %>% bake(mtcars),
                NA)
-  expect_equal(rp1 %>% check_cols(everything()) %>% prep() %>% bake(mtcars),
+  expect_equal(rp1 %>% check_cols(all_predictors()) %>% prep() %>% bake(mtcars),
                tibble(mtcars[ ,c(1, 3:11, 2)]))
   expect_error(rp2 %>% check_cols(cyl, mpg, drat) %>% prep %>% bake(mtcars), NA)
   expect_equal(rp2 %>% check_cols(cyl, mpg, drat) %>% prep %>% bake(mtcars),
                tibble(mtcars[ ,c(1, 5, 2)]))
 
   expect_error(
-    rp1 %>% check_cols(everything()) %>% prep() %>% bake(mtcars),
+    rp1 %>% check_cols(all_predictors()) %>% prep() %>% bake(mtcars),
     NA
   )
   expect_equal(
-    rp1 %>% check_cols(everything()) %>% prep() %>% bake(mtcars),
+    rp1 %>% check_cols(all_predictors()) %>% prep() %>% bake(mtcars),
     tibble(mtcars[, c(1, 3:11, 2)])
   )
   expect_error(rp2 %>% check_cols(cyl, mpg, drat) %>% prep() %>% bake(mtcars), NA)
@@ -36,7 +36,7 @@ test_that("check_col works in the bake stage", {
     tibble(mtcars[, c(1, 5, 2)])
   )
   expect_snapshot(error = TRUE,
-    rp1 %>% check_cols(everything()) %>% prep() %>% bake(mtcars[-1])
+    rp1 %>% check_cols(all_predictors()) %>% prep() %>% bake(mtcars[-1])
   )
   expect_snapshot(error = TRUE,
     rp2 %>% check_cols(cyl, mpg, drat) %>% prep() %>%
@@ -195,7 +195,7 @@ test_that("empty selection tidy method works", {
 
 test_that("printing", {
   rec <- recipe(mpg ~ ., mtcars) %>%
-    check_cols(everything())
+    check_cols(all_predictors())
 
   expect_snapshot(print(rec))
   expect_snapshot(prep(rec))

tests/testthat/test-cut.R

@@ -5,7 +5,7 @@ test_that("step_cut throws error on non-numerics", {
     recipe(x) %>% step_cut(cat_var, breaks = 2) %>% prep()
   )
   expect_snapshot(error = TRUE,
-    recipe(x) %>% step_cut(everything(), breaks = 2) %>% prep()
+    recipe(~., x) %>% step_cut(all_predictors(), breaks = 2) %>% prep()
   )
 })
 

tests/testthat/test-indicate_na.R

@@ -43,7 +43,7 @@ test_that("step_indicate_na populates binaries correctly", {
 
 test_that("step_indicate_na on all columns", {
   baked <- recipe(Ozone ~ ., data = airquality) %>%
-    step_indicate_na(everything()) %>%
+    step_indicate_na(all_predictors()) %>%
     prep(airquality, verbose = FALSE, retain = TRUE) %>%
     bake(new_data = NULL)
 
@@ -52,7 +52,7 @@ test_that("step_indicate_na on all columns", {
     c(
       "Solar.R", "Wind", "Temp", "Month", "Day", "Ozone",
       "na_ind_Solar.R", "na_ind_Wind", "na_ind_Temp",
-      "na_ind_Month", "na_ind_Day", "na_ind_Ozone"
+      "na_ind_Month", "na_ind_Day"
     )
   )
 })

tests/testthat/test-missing.R

@@ -10,7 +10,7 @@ set_with_na <- tibble(
 
 tst <- function(...) {
   cols <- quos(...)
-  recipe(set_with_na) %>%
+  recipe(~ ., set_with_na) %>%
     check_missing(!!!cols) %>%
     prep() %>%
     bake(set_with_na)
@@ -33,7 +33,7 @@ test_that("check_missing throws error on all types", {
 
 test_that("check_missing works on multiple columns simultaneously", {
   expect_snapshot(error = TRUE, tst(a, e))
-  expect_snapshot(error = TRUE, tst(everything()))
+  expect_snapshot(error = TRUE, tst(all_predictors()))
 })
 
 test_that("check_missing on a new set", {

tests/testthat/test-naomit.R

@@ -2,15 +2,15 @@ library(testthat)
 library(recipes)
 
 test_that("step_naomit on all columns", {
-  baked <- recipe(Ozone ~ ., data = airquality) %>%
-    step_naomit(everything()) %>%
+  baked <- recipe(~ ., data = airquality) %>%
+    step_naomit(all_predictors()) %>%
     prep(airquality, verbose = FALSE) %>%
     bake(new_data = NULL)
 
   na_res <- tibble(na.omit(airquality))
   attributes(na_res)$na.action <- NULL
 
-  expect_equal(baked, na_res[, c(2:6, 1)])
+  expect_equal(baked, na_res)
 })
 
 test_that("step_naomit on subset of columns", {

tests/testthat/test-ordinalscore.R

@@ -65,7 +65,7 @@ test_that("nonlinear scores", {
 
 test_that("bad spec", {
   rec3 <- recipe(~., data = ex_dat) %>%
-    step_ordinalscore(everything())
+    step_ordinalscore(all_predictors())
   expect_snapshot(error = TRUE,
     prep(rec3, training = ex_dat, verbose = FALSE)
   )

tests/testthat/test-profile.R

@@ -72,7 +72,7 @@ test_that("character profile", {
 test_that("bad values", {
   expect_snapshot(error = TRUE,
     sacr_rec %>%
-      step_profile(everything(), profile = vars(sqft)) %>%
+      step_profile(all_predictors(), profile = vars(sqft)) %>%
       prep(data = Sacramento)
   )
   expect_snapshot(error = TRUE,

tests/testthat/test-shuffle.R

@@ -46,7 +46,7 @@ test_that("nominal data", {
 
 test_that("all data", {
   rec3 <- recipe(y ~ ., data = dat) %>%
-    step_shuffle(everything())
+    step_shuffle(all_predictors())
 
   rec3 <- prep(rec3, training = dat, verbose = FALSE)
   set.seed(2516)
@@ -62,10 +62,10 @@ test_that("all data", {
 
 test_that("bake a single row", {
   rec4 <- recipe(y ~ ., data = dat) %>%
-    step_shuffle(everything())
+    step_shuffle(all_predictors())
 
   rec4 <- prep(rec4, training = dat, verbose = FALSE)
-  expect_snapshot(dat4 <- bake(rec4, dat[1, ], everything()))
+  expect_snapshot(dat4 <- bake(rec4, dat[1, ]))
   expect_equal(dat4, tibble(dat[1, ]))
 })
 
@@ -122,7 +122,7 @@ test_that("empty selection tidy method works", {
 
 test_that("printing", {
   rec <- recipe(y ~ ., data = dat) %>%
-    step_shuffle(everything())
+    step_shuffle(all_predictors())
 
   expect_snapshot(print(rec))
   expect_snapshot(prep(rec))