code: def test_divmod():
      df1 = pd.Series(np.random.rand(10))
      df2 = pd.Series(np.random.rand(10))
  
      ddf1 = dd.from_pandas(df1, npartitions=3)
      ddf2 = dd.from_pandas(df2, npartitions=3)
  
      result = divmod(ddf1, 2.0)
      expected = divmod(df1, 2.0)
      assert_eq(result[0], expected[0])
      assert_eq(result[1], expected[1])
  
      result = divmod(ddf1, ddf2)
      expected = divmod(df1, df2)
      assert_eq(result[0], expected[0])
      assert_eq(result[1], expected[1])
  
imports: from __future__ import annotations
  import contextlib
  import warnings
  from datetime import datetime
  import numpy
  import pandas
  import pytest
  from pandas.api.types import is_scalar
  import dask.dataframe
  from dask.array.numpy_compat import _numpy_125
  from dask.dataframe._compat import PANDAS_GE_140, PANDAS_GE_150, PANDAS_GE_200, PANDAS_VERSION, check_numeric_only_deprecation
  from dask.dataframe.utils import assert_dask_graph, assert_eq, make_meta, pyarrow_strings_enabled
label_desc: Use image node_id 26 for calling a global function with example usage: test_divmod() without return types