Infer large_string type as pyarrow_numpy strings

pandas/core/arrays/string_arrow.py

@@ -448,6 +448,15 @@ def _str_rstrip(self, to_strip=None):
 class ArrowStringArrayNumpySemantics(ArrowStringArray):
     _storage = "pyarrow_numpy"
 
+    def __init__(self, values) -> None:
+        _chk_pyarrow_available()
+
+        if isinstance(values, (pa.Array, pa.ChunkedArray)) and pa.types.is_large_string(
+            values.type
+        ):
+            values = pc.cast(values, pa.string())
+        super().__init__(values)
+
     @classmethod
     def _result_converter(cls, values, na=None):
         if not isna(na):

pandas/io/_util.py

@@ -28,4 +28,7 @@ def _arrow_dtype_mapping() -> dict:
 def arrow_string_types_mapper() -> Callable:
     pa = import_optional_dependency("pyarrow")
 
-    return {pa.string(): pd.StringDtype(storage="pyarrow_numpy")}.get
+    return {
+        pa.string(): pd.StringDtype(storage="pyarrow_numpy"),
+        pa.large_string(): pd.StringDtype(storage="pyarrow_numpy"),
+    }.get

pandas/tests/arrays/string_/test_string_arrow.py

@@ -12,7 +12,10 @@
     StringArray,
     StringDtype,
 )
-from pandas.core.arrays.string_arrow import ArrowStringArray
+from pandas.core.arrays.string_arrow import (
+    ArrowStringArray,
+    ArrowStringArrayNumpySemantics,
+)
 
 skip_if_no_pyarrow = pytest.mark.skipif(
     pa_version_under7p0,
@@ -166,6 +169,9 @@ def test_pyarrow_not_installed_raises():
     with pytest.raises(ImportError, match=msg):
         ArrowStringArray([])
 
+    with pytest.raises(ImportError, match=msg):
+        ArrowStringArrayNumpySemantics([])
+
     with pytest.raises(ImportError, match=msg):
         ArrowStringArray._from_sequence(["a", None, "b"])
 

pandas/tests/io/test_parquet.py

@@ -1139,6 +1139,25 @@ def test_roundtrip_decimal(self, tmp_path, pa):
         expected = pd.DataFrame({"a": ["123"]}, dtype="string[python]")
         tm.assert_frame_equal(result, expected)
 
+    def test_infer_string_large_string_type(self, tmp_path, pa):
+        # GH#54798
+        import pyarrow as pa
+        import pyarrow.parquet as pq
+
+        path = tmp_path / "large_string.p"
+
+        table = pa.table({"a": pa.array([None, "b", "c"], pa.large_string())})
+        pq.write_table(table, path)
+
+        with pd.option_context("future.infer_string", True):
+            result = read_parquet(path)
+        expected = pd.DataFrame(
+            data={"a": [None, "b", "c"]},
+            dtype="string[pyarrow_numpy]",
+            columns=pd.Index(["a"], dtype="string[pyarrow_numpy]"),
+        )
+        tm.assert_frame_equal(result, expected)
+
 
 class TestParquetFastParquet(Base):
     def test_basic(self, fp, df_full):