code: def test_check_result_repr(iris_dataset):
      # Arrange
      check = MixedNulls()
      check_res = check.run(iris_dataset)
  
      # Assert
      assert_that(check.__repr__(), is_("MixedNulls"))
      assert_that(
          check_res.__repr__(),
          equal_to(
              "Mixed Nulls: {'n_samples': 150, 'columns': {'sepal length (cm)': {}, 'sepal width (cm)': {},"
              " 'petal length (cm)': {}, 'petal width (cm)': {}, 'target': {}}, 'feature_importance': sepal length (cm)"
              "    NaN\nsepal width (cm)     NaN\npetal length (cm)    NaN\npetal width (cm)     NaN\ntarget            "
              "   NaN\ndtype: object}"
          ),
      )
  
imports: import contextlib
  import io
  import pathlib
  import typing
  from unittest.mock import Mock, patch
  import jsonpickle
  import pandas
  import plotly.express
  import plotly.io
  from hamcrest import all_of, any_of, assert_that, calling, equal_to, greater_than, has_entries, has_length, instance_of, is_, matches_regexp, only_contains, raises
  from ipywidgets import VBox, Widget
  from deepchecks.core.check_result import CheckFailure, CheckResult
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.tabular.checks import ColumnsInfo, MixedNulls
  from deepchecks.utils.json_utils import from_json
  from tests.common import DummyCheck, create_check_result, create_suite_result, instance_of_ipython_formatter
label_desc: Use image node_id 5 for calling a global function with example usage: test_check_result_repr(iris_dataset) without return types