code: def test_get_recipe_tracking_config_returns_expected_config_on_databricks(
      tracking_uri,
      artifact_location,
      experiment_name,
      experiment_id,
      run_name_prefix,
  ):
      with mock.patch(
          "mlflow.recipes.utils.tracking.is_in_databricks_runtime",
          return_value=True,
      ):
          default_tracking_uri = "databricks"
          default_experiment_name = (
              "sklearn_regression"  # equivalent to recipe name
          )
  
          profile_contents = {
              "experiment": {},
              "INGEST_CONFIG": None,
              "INGEST_SCORING_CONFIG": None,
              "PREDICT_OUTPUT_CONFIG": None,
          }
          if tracking_uri is not None:
              profile_contents["experiment"][
                  "tracking_uri"
              ] = tracking_uri
          if artifact_location is not None:
              profile_contents["experiment"][
                  "artifact_location"
              ] = artifact_location
          if experiment_name is not None:
              profile_contents["experiment"]["name"] = experiment_name
          if experiment_id is not None:
              profile_contents["experiment"]["id"] = experiment_id
          if run_name_prefix is not None:
              profile_contents["experiment"][
                  "run_name_prefix"
              ] = run_name_prefix
  
          profile_path = (
              pathlib.Path.cwd() / "profiles" / "testprofile.yaml"
          )
          with open(profile_path, "w") as f:
              yaml.safe_dump(profile_contents, f)
  
          recipe_config = get_recipe_config(
              recipe_root_path=os.getcwd(), profile="testprofile"
          )
          recipe_tracking_config = get_recipe_tracking_config(
              recipe_root_path=os.getcwd(), recipe_config=recipe_config
          )
          assert recipe_tracking_config.tracking_uri == (
              tracking_uri or default_tracking_uri
          )
          assert (
              recipe_tracking_config.artifact_location
              == artifact_location
          )
          if run_name_prefix is None:
              assert recipe_tracking_config.run_name is None
          else:
              assert run_name_prefix in recipe_tracking_config.run_name
          if experiment_name is not None:
              assert (
                  recipe_tracking_config.experiment_name
                  == experiment_name
              )
          elif experiment_id is not None:
              assert (
                  recipe_tracking_config.experiment_id == experiment_id
              )
          elif experiment_id is None and experiment_name is None:
              assert (
                  recipe_tracking_config.experiment_name
                  == default_experiment_name
              )
  
file_path: mlflow/tests/recipes/test_tracking_utils.py
imports: import os
  import pathlib
  from unittest import mock
  import pytest
  import yaml
  import mlflow
  from mlflow.recipes.utils import get_recipe_config
  from mlflow.recipes.utils.tracking import get_recipe_tracking_config, log_code_snapshot
  from mlflow.utils.file_utils import path_to_local_file_uri, path_to_local_sqlite_uri
  from tests.recipes.helper_functions import list_all_artifacts
label_desc: Use image node_id 2 for calling a global function with example usage: test_get_recipe_tracking_config_returns_expected_config_on_databricks(tracking_uri, artifact_location, experiment_name, experiment_id, run_name_prefix) without return types