code: def generate_categorized_records(normalized=False, count=2):
      """Generate categorized records by source types"""
      json_data = [
          {"key_{}".format(cnt): "value_{}".format(cnt)}
          for cnt in range(count)
      ]
  
      if normalized:
          for data in json_data:
              data[Normalizer.NORMALIZATION_KEY] = {
                  "normalized_type1": [
                      {"values": ["value1"], "function": None}
                  ],
                  "normalized_type2": [
                      {
                          "values": ["value2", "value3"],
                          "function": None,
                          "send_to_artifacts": True,
                      }
                  ],
                  "normalized_type3": [
                      {
                          "values": ["value2", "value3"],
                          "function": None,
                          "send_to_artifacts": False,
                      }
                  ],
              }
  
      return {"log_type_01_sub_type_01": json_data}
  
file_path: streamalert/tests/unit/streamalert/shared/test_utils.py
imports: import json
  from nose.tools import assert_equal, assert_false
  from streamalert.shared import utils
  from streamalert.shared.normalize import Normalizer
label_desc: Use image node_id 7 for calling a global function with example usage: generate_categorized_records(normalized, count) and returns: dict