code: def test_run_recipe_step_maintains_execution_status_correctly(
      pandas_df, tmp_path
  ):
      dataset_path = tmp_path / "df.parquet"
      pandas_df.to_parquet(dataset_path)
  
      ingest_step_good = IngestStep.from_recipe_config(
          recipe_config={
              "target_col": "C",
              "steps": {
                  "ingest": {
                      "using": "parquet",
                      "location": str(dataset_path),
                  }
              },
          },
          recipe_root=os.getcwd(),
      )
  
      assert (
          get_test_recipe_step_execution_state(ingest_step_good).status
          == StepStatus.UNKNOWN
      )
      assert (
          get_test_recipe_step_execution_state(
              ingest_step_good
          ).last_updated_timestamp
          == 0
      )
      assert (
          get_test_recipe_step_execution_state(
              ingest_step_good
          ).stack_trace
          is None
      )
      curr_time = time.time()
      run_test_recipe_step([ingest_step_good], ingest_step_good)
      assert (
          get_test_recipe_step_execution_state(ingest_step_good).status
          == StepStatus.SUCCEEDED
      )
      assert (
          get_test_recipe_step_execution_state(
              ingest_step_good
          ).last_updated_timestamp
          >= curr_time
      )
      assert (
          get_test_recipe_step_execution_state(
              ingest_step_good
          ).stack_trace
          is None
      )
  
      ingest_step_bad = IngestStep.from_recipe_config(
          recipe_config={
              "target_col": "C",
              "steps": {
                  "ingest": {
                      "using": "parquet",
                      "location": "badlocation",
                  }
              },
          },
          recipe_root=os.getcwd(),
      )
      curr_time = time.time()
      run_test_recipe_step([ingest_step_bad], ingest_step_bad)
      assert (
          get_test_recipe_step_execution_state(ingest_step_bad).status
          == StepStatus.FAILED
      )
      assert (
          get_test_recipe_step_execution_state(
              ingest_step_bad
          ).last_updated_timestamp
          >= curr_time
      )
      assert (
          "Traceback"
          in get_test_recipe_step_execution_state(
              ingest_step_bad
          ).stack_trace
      )
  
imports: import os
  import pathlib
  import shutil
  import time
  from unittest import mock
  import pandas
  import pytest
  from mlflow.environment_variables import MLFLOW_RECIPES_EXECUTION_TARGET_STEP_NAME
  from mlflow.recipes import Recipe
  from mlflow.recipes.step import StepStatus
  from mlflow.recipes.steps.ingest import IngestStep
  from mlflow.recipes.steps.split import SplitStep
  from mlflow.recipes.steps.transform import TransformStep
  from mlflow.recipes.utils.execution import _ExecutionPlan, _get_or_create_execution_directory, get_step_output_path, run_recipe_step
  from tests.recipes.helper_functions import BaseStepImplemented
label_desc: Use image node_id 11 for calling a global function with example usage: test_run_recipe_step_maintains_execution_status_correctly(pandas_df, tmp_path) without return types