ENH (string dtype): convert string_view columns to future string dtype instead of object dtype in Parquet/Feather IO (#60235)

* ENH (string dtype): convert string_view columns to future string dtype instead of object dtype in Parquet IO

* move test to feather

* fixup

Author: jorisvandenbossche

pandas/io/_util.py

@@ -4,6 +4,7 @@
 
 import numpy as np
 
+from pandas.compat import pa_version_under18p0
 from pandas.compat._optional import import_optional_dependency
 
 import pandas as pd
@@ -35,7 +36,11 @@ def _arrow_dtype_mapping() -> dict:
 def arrow_string_types_mapper() -> Callable:
     pa = import_optional_dependency("pyarrow")
 
-    return {
+    mapping = {
         pa.string(): pd.StringDtype(na_value=np.nan),
         pa.large_string(): pd.StringDtype(na_value=np.nan),
-    }.get
+    }
+    if not pa_version_under18p0:
+        mapping[pa.string_view()] = pd.StringDtype(na_value=np.nan)
+
+    return mapping.get

pandas/tests/io/test_feather.py

@@ -6,6 +6,8 @@
 import numpy as np
 import pytest
 
+from pandas.compat.pyarrow import pa_version_under18p0
+
 import pandas as pd
 import pandas._testing as tm
 
@@ -249,6 +251,24 @@ def test_string_inference(self, tmp_path):
         )
         tm.assert_frame_equal(result, expected)
 
+    @pytest.mark.skipif(pa_version_under18p0, reason="not supported before 18.0")
+    def test_string_inference_string_view_type(self, tmp_path):
+        # GH#54798
+        import pyarrow as pa
+        from pyarrow import feather
+
+        path = tmp_path / "string_view.parquet"
+        table = pa.table({"a": pa.array([None, "b", "c"], pa.string_view())})
+        feather.write_feather(table, path)
+
+        with pd.option_context("future.infer_string", True):
+            result = read_feather(path)
+
+            expected = pd.DataFrame(
+                data={"a": [None, "b", "c"]}, dtype=pd.StringDtype(na_value=np.nan)
+            )
+        tm.assert_frame_equal(result, expected)
+
     def test_out_of_bounds_datetime_to_feather(self):
         # GH#47832
         df = pd.DataFrame(