code: def test_lazyframe_slice(ldf: pl.LazyFrame) -> None:
      py_data = ldf.collect().rows()
  
      for start, stop, step, _ in py_data:
          s = slice(start, stop, step)
          sliced_py_data = py_data[s]
          try:
              sliced_df_data = ldf[s].collect().rows()
              assert (
                  sliced_py_data == sliced_df_data
              ), f"slice [{start}:{stop}:{step}] failed on lazy df w/len={len(py_data)}"
  
          except ValueError as exc:
              # test params will trigger some known
              # unsupported cases; filter them here.
              if "not supported" not in str(exc):
                  raise
  
imports: from hypothesis import given
  from hypothesis.strategies import integers
  import polars
  from polars.testing.parametric import column, dataframes
label_desc: Use image node_id 1 for calling a global function with example usage: test_lazyframe_slice(ldf) without return types