code: def test_python_rmse(rating_true, rating_pred):
      assert (
          rmse(
              rating_true=rating_true,
              rating_pred=rating_true,
              col_prediction=DEFAULT_RATING_COL,
          )
          == 0
      )
      assert rmse(rating_true, rating_pred) == pytest.approx(
          7.254309, TOL
      )
  
imports: import numpy
  import pandas
  import pytest
  from unittest.mock import Mock
  from sklearn.preprocessing import minmax_scale
  from pandas.testing import assert_frame_equal
  from recommenders.utils.constants import DEFAULT_USER_COL, DEFAULT_ITEM_COL, DEFAULT_RATING_COL, DEFAULT_PREDICTION_COL
  from recommenders.evaluation.python_evaluation import _check_column_dtypes, merge_rating_true_pred, merge_ranking_true_pred, rmse, mae, rsquared, exp_var, get_top_k_items, precision_at_k, recall_at_k, ndcg_at_k, map_at_k, map, auc, logloss, user_diversity, diversity, historical_item_novelty, novelty, user_item_serendipity, user_serendipity, serendipity, catalog_coverage, distributional_coverage, ColumnMismatchError, ColumnTypeMismatchError
label_desc: Use image node_id 6 for calling a global function with example usage: test_python_rmse(rating_true, rating_pred) without return types