code: def test_without_shuffle_and_with_one_chunk(
      setup, func_name, func_opts
  ):
      if func_opts.func_name in ["__and__", "__or__", "__xor__"]:
          # FIXME bitwise logical operators behave differently with pandas when index is not aligned.
          return
  
      # only 1 axis is monotonic
      # data1 with index split into [0...4], [5...9],
      data1 = pd.DataFrame(
          np.random.rand(10, 10),
          index=np.arange(10),
          columns=[4, 1, 3, 2, 10, 5, 9, 8, 6, 7],
      )
      data1 = to_boolean_if_needed(func_opts.func_name, data1)
      df1 = from_pandas(data1, chunk_size=(5, 10))
      # data2 with index split into [6...11], [2, 5],
      data2 = pd.DataFrame(
          np.random.rand(10, 10),
          index=np.arange(11, 1, -1),
          columns=[5, 9, 12, 3, 11, 10, 6, 4, 1, 2],
      )
      data2 = to_boolean_if_needed(func_opts.func_name, data2)
      df2 = from_pandas(data2, chunk_size=(6, 10))
  
      df3 = func_opts.func(df1, df2)
  
      expected = func_opts.func(data1, data2)
      result = df3.execute().fetch()
  
      pd.testing.assert_frame_equal(
          sort_dataframe(expected), sort_dataframe(result)
      )
  
      # only 1 axis is monotonic
      # data1 with columns split into [0...4], [5...9],
      data1 = pd.DataFrame(
          np.random.rand(10, 10),
          index=[4, 1, 3, 2, 10, 5, 9, 8, 6, 7],
          columns=np.arange(10),
      )
      data1 = to_boolean_if_needed(func_opts.func_name, data1)
      df1 = from_pandas(data1, chunk_size=(10, 5))
      # data2 with columns split into [6...11], [2, 5],
      data2 = pd.DataFrame(
          np.random.rand(10, 10),
          index=[5, 9, 12, 3, 11, 10, 6, 4, 1, 2],
          columns=np.arange(11, 1, -1),
      )
      data2 = to_boolean_if_needed(func_opts.func_name, data2)
      df2 = from_pandas(data2, chunk_size=(10, 6))
  
      df3 = func_opts.func(df1, df2)
  
      expected = func_opts.func(data1, data2)
      result = df3.execute().fetch()
  
      pd.testing.assert_frame_equal(
          sort_dataframe(expected), sort_dataframe(result)
      )
  
imports: import operator
  from dataclasses import dataclass
  from functools import partial
  from typing import Callable, Union
  import numpy
  import pandas
  import pytest
  from ....None import tensor
  from ....tensor.datasource import array
  from ....utils import dataslots
  from ...None import to_datetime
  from ...datasource.dataframe import from_pandas
  from ...datasource.series import from_pandas
  from ..tests.test_arithmetic import comp_func
label_desc: Use image node_id 7 for calling a global function with example usage: test_without_shuffle_and_with_one_chunk(setup, func_name, func_opts) without return types