code: def test_update_parameters():
      parameter_cell_source = """
  # Integer
  TOP_K = 10
  # Float
  LEARNING_RATE = 0.001
  # String
  MOVIELENS_DATA_SIZE = "100k"
  # List
  RANKING_METRICS = [ evaluator.ndcg_at_k.__name__, evaluator.precision_at_k.__name__ ]
  # Boolean
  EVALUATE_WHILE_TRAINING = True
  """
  
      new_parameters = {
          "MOVIELENS_DATA_SIZE": "1m",
          "TOP_K": 1,
          "EVALUATE_WHILE_TRAINING": False,
          "RANKING_METRICS": ["ndcg_at_k", "precision_at_k"],
          "LEARNING_RATE": 0.1,
      }
  
      new_cell_source = _update_parameters(
          parameter_cell_source, new_parameters
      )
      assert (
          new_cell_source
          == """
  # Integer
  TOP_K = 1
  # Float
  LEARNING_RATE = 0.1
  # String
  MOVIELENS_DATA_SIZE = "1m"
  # List
  RANKING_METRICS = ['ndcg_at_k', 'precision_at_k']
  # Boolean
  EVALUATE_WHILE_TRAINING = False
  """
      )
  
file_path: recommenders/tests/unit/recommenders/utils/test_notebook_utils.py
imports: import pytest
  import nbclient
  from pathlib import Path
  from recommenders.utils.notebook_utils import is_jupyter, is_databricks, execute_notebook, read_notebook, _update_parameters
label_desc: Use image node_id 5 for calling a global function with example usage: test_update_parameters() without return types