code: def test_deterministic_hashing_dataframe():
      # Add duplicate column names in order to use _iLocIndexer._iloc path
      obj = pd.DataFrame(
          [[0, 1, 2, 3], [4, 5, 6, 7]], columns=["a", "b", "c", "c"]
      )
  
      dask_df = dd.from_pandas(obj, npartitions=1)
  
      ddf1 = dask_df.loc[0:1, ["a", "c"]]
      ddf2 = dask_df.loc[0:1, ["a", "c"]]
  
      assert tokenize(ddf1) == tokenize(ddf2)
  
      ddf1 = dask_df.loc[0:1, "c"]
      ddf2 = dask_df.loc[0:1, "c"]
  
      assert tokenize(ddf1) == tokenize(ddf2)
  
      ddf1 = dask_df.iloc[:, [0, 1]]
      ddf2 = dask_df.iloc[:, [0, 1]]
  
      assert tokenize(ddf1) == tokenize(ddf2)
  
      ddf2 = dask_df.iloc[:, [0, 2]]
      assert tokenize(ddf1) != tokenize(ddf2)
  
imports: from __future__ import annotations
  import contextlib
  import numpy
  import pandas
  import pytest
  import dask
  import dask.dataframe
  from dask.base import tokenize
  from dask.dataframe._compat import PANDAS_GE_210, PANDAS_GE_220, IndexingError, tm
  from dask.dataframe.indexing import _coerce_loc_index
  from dask.dataframe.utils import assert_eq, make_meta, pyarrow_strings_enabled
label_desc: Use image node_id 35 for calling a global function with example usage: test_deterministic_hashing_dataframe() without return types