code: def test_arrow_load_from_zero_chunks(
      dtype, string_storage2, request, using_infer_string
  ):
      # GH-41040
      pa = pytest.importorskip("pyarrow")
  
      if using_infer_string and string_storage2 != "pyarrow_numpy":
          request.applymarker(
              pytest.mark.xfail(
                  reason="infer_string takes precedence over string storage"
              )
          )
  
      data = pd.array([], dtype=dtype)
      df = pd.DataFrame({"a": data})
      table = pa.table(df)
      if dtype.storage == "python":
          assert table.field("a").type == "string"
      else:
          assert table.field("a").type == "large_string"
      # Instantiate the same table with no chunks at all
      table = pa.table(
          [pa.chunked_array([], type=pa.string())], schema=table.schema
      )
      with pd.option_context("string_storage", string_storage2):
          result = table.to_pandas()
      assert isinstance(result["a"].dtype, pd.StringDtype)
      expected = df.astype(f"string[{string_storage2}]")
      tm.assert_frame_equal(result, expected)
  
imports: import operator
  import numpy
  import pytest
  from pandas.compat.pyarrow import pa_version_under12p0
  from pandas.core.dtypes.common import is_dtype_equal
  import pandas
  import pandas._testing
  from pandas.core.arrays.string_arrow import ArrowStringArray, ArrowStringArrayNumpySemantics
label_desc: Use image node_id 33 for calling a global function with example usage: test_arrow_load_from_zero_chunks(dtype, string_storage2, request, using_infer_string) without return types