code: def __init__(self, *args, **kwargs):
      data = {
          "column1": [1, 2, 3, 4, 5],
          "column2": ["a", "b", "c", "d", "e"],
          "column3": [1.1, 3.3, 2.2, 4.4, 5.5],
          "column4": [True, False, True, False, False],
          "column5": pd.date_range("2023-01-01", periods=5),
      }
  
      df = pd.DataFrame(data)
      self.df = df
  
      dataframe_x = df[["column1", "column3"]].copy()
      y_target = pd.DataFrame(
          data=np.array([0, 0, 0, 1, 1]), columns=["pred"]
      )
      model = DecisionTreeClassifier().fit(dataframe_x, y_target)
      features_dict = {"column3": "Useless col"}
      additional_data = df[["column2", "column4", "column5"]].copy()
      additional_features_dict = {"column2": "Additional col"}
      self.xpl = SmartExplainer(
          model=model, features_dict=features_dict
      )
      self.xpl.compile(
          x=dataframe_x,
          y_pred=y_target,
          y_target=y_target,
          additional_data=additional_data,
          additional_features_dict=additional_features_dict,
      )
      self.smart_app = SmartApp(self.xpl)
  
      self.click_data = {
          "points": [
              {
                  "curveNumber": 0,
                  "pointNumber": 3,
                  "pointIndex": 3,
                  "x": 0.4649,
                  "y": "Sex",
                  "label": "Sex",
                  "value": 0.4649,
                  "customdata": "Sex",
                  "marker.color": "rgba(244, 192, 0, 1.0)",
                  "bbox": {
                      "x0": 717.3,
                      "x1": 717.3,
                      "y0": 82.97,
                      "y1": 130.78,
                  },
              }
          ]
      }
      self.special_cols = ["_index_", "_predict_", "_target_"]
  
      super(TestCallbacks, self).__init__(*args, **kwargs)
  
imports: import unittest
  import copy
  import numpy
  import pandas
  from sklearn.tree import DecisionTreeClassifier
  from dash import dcc
  from shapash import SmartExplainer
  from shapash.webapp.smart_app import SmartApp
  from shapash.webapp.utils.callbacks import select_data_from_prediction_picking, select_data_from_str_filters, select_data_from_bool_filters, select_data_from_numeric_filters, select_data_from_date_filters, get_feature_from_clicked_data, get_feature_from_features_groups, get_group_name, get_indexes_from_datatable, update_click_data_on_subset_changes, get_figure_zoom, get_feature_contributions_sign_to_show, update_features_to_display, get_id_card_features, get_id_card_contrib, create_id_card_data, create_id_card_layout, get_feature_filter_options, create_filter_modalities_selection
label_desc: Use image node_id 1 to create a new TestCallbacks object from inherited base classes: unittest with example: obj = TestCallbacks()