code: def test_ts_predictor_fix_order_by_modification(self, mock_handler):
      # set integration data
  
      df = pd.DataFrame(
          [
              {
                  "a": 1,
                  "t": dt.datetime(2020, 1, 1, 10, 0, 0),
                  "g": "x",
              },
              {
                  "a": 2,
                  "t": dt.datetime(2020, 1, 1, 10, 1, 0),
                  "g": "x",
              },
              {
                  "a": 3,
                  "t": dt.datetime(2020, 1, 1, 10, 2, 0),
                  "g": "x",
              },
          ]
      )
      self.set_handler(mock_handler, name="pg", tables={"tasks": df})
  
      # --- use TS predictor ---
  
      predictor = {
          "name": "task_model",
          "predict": "a",
          "problem_definition": {
              "timeseries_settings": {
                  "is_timeseries": True,
                  "window": 2,
                  "order_by": "t",
                  "horizon": 3,
              }
          },
          "dtypes": {
              "a": dtype.integer,
              "t": dtype.date,
              "g": dtype.categorical,
          },
          "predicted_value": "",
      }
      self.set_predictor(predictor)
  
      # set predictor output
      predict_result = [
          # window
          {
              "a": 2,
              "t": dt.datetime(2020, 1, 1, 10, 1, 0),
              "g": "x",
              "__mindsdb_row_id": 2,
          },
          {
              "a": 3,
              "t": dt.datetime(2020, 1, 1, 10, 2, 0),
              "g": "x",
              "__mindsdb_row_id": 3,
          },
          # horizon
          {
              "a": 1,
              "t": dt.datetime(2020, 1, 1, 10, 3, 0),
              "g": "x",
              "__mindsdb_row_id": None,
          },
          {
              "a": 1,
              "t": dt.datetime(2020, 1, 1, 10, 4, 0),
              "g": "x",
              "__mindsdb_row_id": None,
          },
          {
              "a": 1,
              "t": dt.datetime(2020, 1, 1, 10, 5, 0),
              "g": "x",
              "__mindsdb_row_id": None,
          },
      ]
      predict_result = pd.DataFrame(predict_result)
      self.mock_predict.side_effect = lambda *a, **b: predict_result
  
      # > latest ______________________
      ret = self.execute(
          """
              select t.t as t0, p.* from pg.tasks t
              join mindsdb.task_model p
              where t.t > latest
          """
      )
  
      ret_df = self.ret_to_df(ret)
      assert ret_df.shape[0] == 3
      assert ret_df.t.min() == dt.datetime(2020, 1, 1, 10, 3, 0)
      # table shouldn't join
      assert ret_df.t0[0] is None
  
imports: from unittest.mock import patch
  import datetime
  import tempfile
  import pytest
  import pandas
  import numpy
  from mindsdb_sql.render.sqlalchemy_render import SqlalchemyRender
  from mindsdb.api.executor.utilities.sql import query_df
  from mindsdb.api.mysql.mysql_proxy.utilities.lightwood_dtype import dtype
  from .executor_test_base import BaseExecutorMockPredictor
label_desc: Use image node_id 8 for calling the Test obj's underlying member method code with example usage: obj.test_ts_predictor_fix_order_by_modification(mock_handler) without return types