code: def test_classifier(self, mock_handler):
      df = pd.DataFrame(
          {
              "sepal_length": [
                  5.1,
                  4.9,
                  4.7,
                  4.6,
                  6.4,
                  6.9,
                  5.5,
                  6.5,
                  7.7,
                  6.3,
                  6.7,
                  7.2,
              ],
              "sepal_width": [
                  3.5,
                  3.0,
                  3.2,
                  3.1,
                  3.2,
                  3.1,
                  2.3,
                  2.8,
                  2.8,
                  2.7,
                  3.3,
                  3.2,
              ],
              "petal_length": [
                  1.4,
                  4.0,
                  1.3,
                  1.5,
                  4.5,
                  4.9,
                  4.0,
                  4.6,
                  6.7,
                  4.9,
                  5.7,
                  6.0,
              ],
              "petal_width": [
                  0.2,
                  0.2,
                  0.2,
                  0.2,
                  1.5,
                  1.5,
                  1.3,
                  1.5,
                  2.0,
                  1.8,
                  2.1,
                  1.8,
              ],
              "species": [
                  "Iris-setosa",
                  "Iris-setosa",
                  "Iris-setosa",
                  "Iris-setosa",
                  "Iris-versicolor",
                  "Iris-versicolor",
                  "Iris-versicolor",
                  "Iris-versicolor",
                  "Iris-virginica",
                  "Iris-virginica",
                  "Iris-virginica",
                  "Iris-virginica",
              ],
          }
      )
      self.set_handler(mock_handler, name="pg", tables={"iris": df})
  
      # create project
      self.run_sql("create database proj;")
  
      # create predictor
      self.run_sql(
          """
              CREATE MODEL proj.my_pycaret_class_model
              FROM pg
                  (SELECT sepal_length, sepal_width, petal_length, petal_width, species FROM iris)
              PREDICT species
              USING
                engine = 'pycaret',
                model_type = 'classification',
                model_name = 'xgboost',
                setup_session_id = 123,
                setup_fold = 2;
          """
      )
      self.wait_predictor("proj", "my_pycaret_class_model")
  
      # run predict
      ret = self.run_sql(
          """
              SELECT prediction_label
              FROM pg.iris as t
              JOIN proj.my_pycaret_class_model AS m;
          """
      )
  
      assert ret["prediction_label"].iloc[0] == "Iris-setosa"
  
file_path: mindsdb/mindsdb/integrations/handlers/pycaret_handler/test/test_pycaret.py
imports: import importlib
  import time
  from unittest.mock import patch
  import pandas
  import pytest
  from mindsdb_sql import parse_sql
  from tests.unit.executor_test_base import BaseExecutorTest
label_desc: Use image node_id 3 for calling the TestPyCaret obj's underlying member method code with example usage: obj.test_classifier(mock_handler) without return types