code: def test_group_by_dynamic_startby_monday_crossing_dst(
      start_by: StartBy,
      expected_time: list[datetime],
      expected_value: list[float],
  ) -> None:
      start_dt = datetime(2021, 11, 7)
      end_dt = datetime(2021, 11, 14)
      date_range = pl.datetime_range(
          start_dt, end_dt, "1d", time_zone="US/Central", eager=True
      )
      df = pl.DataFrame(
          {"time": date_range, "value": range(len(date_range))}
      )
      result = df.group_by_dynamic(
          "time", every="1w", start_by=start_by
      ).agg(pl.col("value").mean())
      expected = pl.DataFrame(
          {"time": expected_time, "value": expected_value},
      )
      expected = expected.with_columns(
          pl.col("time").dt.replace_time_zone("US/Central")
      )
      assert_frame_equal(result, expected)
  
imports: from __future__ import annotations
  import sys
  from datetime import date, datetime, timedelta
  from typing import TYPE_CHECKING, Any
  import numpy
  import pytest
  import polars
  from polars.testing import assert_frame_equal
label_desc: Use image node_id 22 for calling a global function with example usage: test_group_by_dynamic_startby_monday_crossing_dst(start_by, expected_time, expected_value) without return types