code: def test_df_property_has_expected_value(spark_session, tmp_path, df):
      df_spark = spark_session.createDataFrame(df)
      path = str(tmp_path / "temp.parquet")
      df_spark.write.parquet(path)
  
      source = SparkDatasetSource(path=path)
  
      dataset = SparkDataset(
          df=df_spark,
          source=source,
          name="testname",
      )
      assert dataset.df == df_spark
  
imports: import json
  import os
  import pandas
  import pytest
  import mlflow.data
  from mlflow.data.code_dataset_source import CodeDatasetSource
  from mlflow.data.delta_dataset_source import DeltaDatasetSource
  from mlflow.data.spark_dataset import SparkDataset
  from mlflow.data.spark_dataset_source import SparkDatasetSource
  from mlflow.exceptions import MlflowException
  from mlflow.models.evaluation.base import EvaluationDataset
  from mlflow.types.schema import Schema
  from mlflow.types.utils import _infer_schema
label_desc: Use image node_id 8 for calling a global function with example usage: test_df_property_has_expected_value(spark_session, tmp_path, df) without return types