code: def shapValuesTestCase(problemType, model, data):
      import catboost_spark
  
      shapModes = [
          catboost_spark.EPreCalcShapValues.Auto,
          catboost_spark.EPreCalcShapValues.UsePreCalc,
          catboost_spark.EPreCalcShapValues.NoPreCalc,
      ]
      calcTypes = [
          catboost_spark.ECalcTypeShapValues.Regular,
          catboost_spark.ECalcTypeShapValues.Approximate,
          catboost_spark.ECalcTypeShapValues.Exact,
      ]
  
      for shapMode in shapModes:
          for calcType in calcTypes:
              print(
                  "problem_type={},shap_mode={},shap_calc_type={}".format(
                      problemType, shapMode, calcType
                  )
              )
              shapValuesDf = model.getFeatureImportanceShapValues(
                  data=data, preCalcMode=shapMode, calcType=calcType
              )
              shapValuesDf.show(truncate=False)
  
file_path: catboost/catboost/spark/catboost4j-spark/core/src/test/python/feature_importance_test.py
imports: import os
  import tempfile
  import config
  import test_helpers
label_desc: Use image node_id 4 for calling a global function with example usage: shapValuesTestCase(problemType, model, data) without return types