Adds ml_utils() tests

tests/testthat/_snaps/ml-utils.md

@@ -0,0 +1,21 @@
+# ml_formula() works
+
+    Code
+      ml_formula(am ~ mpg, mtcars)
+    Output
+      $label
+      [1] "am"
+      
+      $features
+      [1] "mpg"
+      
+
+# ml_installed() works on simulated interactive session
+
+    Code
+      ml_installed()
+    Message
+      ! Required Python libraries to run ML functions are missing
+        Could not find: torch, torcheval, and scikit-learn
+        Do you wish to install? (This will be a one time operation)
+

tests/testthat/helper-utils.R

@@ -112,3 +112,14 @@ test_databricks_cluster_version <- function() {
   }
   .test_env$dbr
 }
+
+test_databricks_stump_env <- function() {
+  env_name <- use_envname(
+    version = test_databricks_cluster_version(),
+    backend = "databricks"
+  )
+  if (names(env_name) != "exact") {
+    py_install("numpy", env_name, pip = TRUE, python = Sys.which("python"))
+  }
+  path(reticulate::virtualenv_python(env_name))
+}

tests/testthat/test-deploy.R

@@ -1,20 +1,9 @@
 skip_if_not_databricks()
 
-test_databricks_deploy_env_path <- function() {
-  env_name <- use_envname(
-    version = test_databricks_cluster_version(),
-    backend = "databricks"
-  )
-  if (names(env_name) != "exact") {
-    py_install("numpy", env_name, pip = TRUE, python = Sys.which("python"))
-  }
-  path(reticulate::virtualenv_python(env_name))
-}
-
 test_databricks_deploy_output <- function() {
   list(
     appDir = path(getwd()),
-    python = test_databricks_deploy_env_path(),
+    python = test_databricks_stump_env(),
     envVars = c("DATABRICKS_HOST", "DATABRICKS_TOKEN"),
     server = "my_server",
     account = "my_account",
@@ -44,7 +33,7 @@ test_that("Basic use, passing DBR version works", {
         accounts = function(...) accounts_df()
       )
       # Initializes environment
-      invisible(test_databricks_deploy_env_path())
+      invisible(test_databricks_stump_env())
 
       expect_equal(
         deploy_databricks(version = test_databricks_cluster_version()),
@@ -209,7 +198,7 @@ test_that("Rare cases for finding environments works", {
   withr::with_envvar(
     new = c("WORKON_HOME" = use_test_env()),
     {
-      env_path <- test_databricks_deploy_env_path()
+      env_path <- test_databricks_stump_env()
       local_mocked_bindings(
         py_exe = function(...) {
           return(NULL)

tests/testthat/test-ml-utils.R

@@ -0,0 +1,59 @@
+test_that("ml_formula() works", {
+  expect_snapshot(ml_formula(am ~ mpg, mtcars))
+  expect_error(
+    ml_formula(am ~ mpg * cyl, mtcars),
+    "Formula resulted in an invalid parameter set"
+  )
+})
+
+test_that("snake_to_camel() works", {
+  expect_equal(
+    snake_to_camel("var_one"),
+    "varOne"
+  )
+})
+
+test_that("ml_connect_not_supported() works", {
+  expect_silent(
+    ml_connect_not_supported(
+      args = list(),
+      not_supported = c(
+        "elastic_net_param", "reg_param", "threshold",
+        "aggregation_depth", "fit_intercept",
+        "raw_prediction_col", "uid", "weight_col"
+      )
+    )
+  )
+
+  expect_error(
+    ml_connect_not_supported(
+      args = list(reg_param = 1),
+      not_supported = c(
+        "elastic_net_param", "reg_param", "threshold",
+        "aggregation_depth", "fit_intercept",
+        "raw_prediction_col", "uid", "weight_col"
+      ),
+      "The following argument(s) are not supported by Spark Connect:"
+    )
+  )
+})
+
+test_that("ml_installed() works on simulated interactive session", {
+  test_databricks_stump_env()
+  withr::with_envvar(
+    new = c("WORKON_HOME" = use_new_test_env()),
+    {
+      local_mocked_bindings(
+        check_interactive = function(...) TRUE,
+        check_rstudio = function(...) TRUE,
+        menu = function(...) {
+          return(1)
+        },
+        py_install = function(...) invisible()
+      )
+      expect_snapshot(
+        ml_installed()
+      )
+    }
+  )
+})