code: def test_serendipity(spark_diversity_data):
      train_df, reco_df, _ = spark_diversity_data
      evaluator = SparkDiversityEvaluation(
          train_df=train_df,
          reco_df=reco_df,
          col_user="UserId",
          col_item="ItemId",
          col_relevance="Relevance",
      )
      assert evaluator.serendipity() == pytest.approx(0.43408, TOL)
  
imports: import pytest
  import numpy
  import pandas
  from pandas.util.testing import assert_frame_equal
  from recommenders.evaluation.python_evaluation import precision_at_k, recall_at_k, ndcg_at_k, map_at_k, map
label_desc: Use image node_id 23 for calling a global function with example usage: test_serendipity(spark_diversity_data) without return types