CI: Fix pyarrow nightly build

.github/actions/build_pandas/action.yml

@@ -12,6 +12,7 @@ runs:
       run: |
         micromamba info
         micromamba list
+        pip list --pre
       shell: bash -el {0}
 
     - name: Uninstall existing Pandas installation

pandas/compat/__init__.py

@@ -28,6 +28,7 @@
     pa_version_under8p0,
     pa_version_under9p0,
     pa_version_under11p0,
+    pa_version_under13p0,
 )
 
 if TYPE_CHECKING:
@@ -183,6 +184,7 @@ def get_bz2_file() -> type[pandas.compat.compressors.BZ2File]:
     "pa_version_under8p0",
     "pa_version_under9p0",
     "pa_version_under11p0",
+    "pa_version_under13p0",
     "IS64",
     "ISMUSL",
     "PY310",

pandas/compat/pyarrow.py

@@ -7,16 +7,17 @@
 try:
     import pyarrow as pa
 
-    _pa_version = pa.__version__
-    _palv = Version(_pa_version)
+    _palv = Version(Version(pa.__version__).base_version)
     pa_version_under7p0 = _palv < Version("7.0.0")
     pa_version_under8p0 = _palv < Version("8.0.0")
     pa_version_under9p0 = _palv < Version("9.0.0")
     pa_version_under10p0 = _palv < Version("10.0.0")
     pa_version_under11p0 = _palv < Version("11.0.0")
+    pa_version_under13p0 = _palv < Version("13.0.0")
 except ImportError:
     pa_version_under7p0 = True
     pa_version_under8p0 = True
     pa_version_under9p0 = True
     pa_version_under10p0 = True
     pa_version_under11p0 = True
+    pa_version_under13p0 = True

pandas/core/arrays/arrow/array.py

@@ -24,6 +24,7 @@
     pa_version_under8p0,
     pa_version_under9p0,
     pa_version_under11p0,
+    pa_version_under13p0,
 )
 from pandas.util._decorators import doc
 from pandas.util._validators import validate_fillna_kwargs
@@ -1218,7 +1219,7 @@ def to_numpy(
             else:
                 result = result.to_numpy(dtype=dtype)
             return result
-        elif pa.types.is_time(pa_type):
+        elif pa.types.is_time(pa_type) or pa.types.is_date(pa_type):
             # convert to list of python datetime.time objects before
             # wrapping in ndarray
             result = np.array(list(self), dtype=dtype)
@@ -1416,6 +1417,8 @@ def _reduce_pyarrow(self, name: str, *, skipna: bool = True, **kwargs) -> pa.Sca
 
         data_to_reduce = self._pa_array
 
+        cast_kwargs = {} if pa_version_under13p0 else {"safe": False}
+
         if name in ["any", "all"] and (
             pa.types.is_integer(pa_type)
             or pa.types.is_floating(pa_type)
@@ -1491,9 +1494,15 @@ def pyarrow_meth(data, skip_nulls, **kwargs):
         if name in ["min", "max", "sum"] and pa.types.is_duration(pa_type):
             result = result.cast(pa_type)
         if name in ["median", "mean"] and pa.types.is_temporal(pa_type):
+            if not pa_version_under13p0:
+                nbits = pa_type.bit_width
+                if nbits == 32:
+                    result = result.cast(pa.int32(), **cast_kwargs)
+                else:
+                    result = result.cast(pa.int64(), **cast_kwargs)
             result = result.cast(pa_type)
         if name in ["std", "sem"] and pa.types.is_temporal(pa_type):
-            result = result.cast(pa.int64())
+            result = result.cast(pa.int64(), **cast_kwargs)
             if pa.types.is_duration(pa_type):
                 result = result.cast(pa_type)
             elif pa.types.is_time(pa_type):

pandas/tests/extension/test_arrow.py

@@ -1706,7 +1706,11 @@ def test_to_numpy_with_defaults(data):
     result = data.to_numpy()
 
     pa_type = data._pa_array.type
-    if pa.types.is_duration(pa_type) or pa.types.is_timestamp(pa_type):
+    if (
+        pa.types.is_duration(pa_type)
+        or pa.types.is_timestamp(pa_type)
+        or pa.types.is_date(pa_type)
+    ):
         expected = np.array(list(data))
     else:
         expected = np.array(data._pa_array)
@@ -2969,7 +2973,7 @@ def test_date32_repr():
     # GH48238
     arrow_dt = pa.array([date.fromisoformat("2020-01-01")], type=pa.date32())
     ser = pd.Series(arrow_dt, dtype=ArrowDtype(arrow_dt.type))
-    assert repr(ser) == "0   2020-01-01\ndtype: date32[day][pyarrow]"
+    assert repr(ser) == "0    2020-01-01\ndtype: date32[day][pyarrow]"
 
 
 @pytest.mark.xfail(

pandas/tests/io/test_parquet.py

@@ -17,6 +17,7 @@
 from pandas.compat.pyarrow import (
     pa_version_under7p0,
     pa_version_under8p0,
+    pa_version_under13p0,
 )
 import pandas.util._test_decorators as td
 
@@ -1006,14 +1007,15 @@ def test_read_dtype_backend_pyarrow_config(self, pa, df_full):
 
         pa_table = pyarrow.Table.from_pandas(df)
         expected = pa_table.to_pandas(types_mapper=pd.ArrowDtype)
-        # pyarrow infers datetimes as us instead of ns
-        expected["datetime"] = expected["datetime"].astype("timestamp[us][pyarrow]")
-        expected["datetime_with_nat"] = expected["datetime_with_nat"].astype(
-            "timestamp[us][pyarrow]"
-        )
-        expected["datetime_tz"] = expected["datetime_tz"].astype(
-            pd.ArrowDtype(pyarrow.timestamp(unit="us", tz="Europe/Brussels"))
-        )
+        if pa_version_under13p0:
+            # pyarrow infers datetimes as us instead of ns
+            expected["datetime"] = expected["datetime"].astype("timestamp[us][pyarrow]")
+            expected["datetime_with_nat"] = expected["datetime_with_nat"].astype(
+                "timestamp[us][pyarrow]"
+            )
+            expected["datetime_tz"] = expected["datetime_tz"].astype(
+                pd.ArrowDtype(pyarrow.timestamp(unit="us", tz="Europe/Brussels"))
+            )
 
         check_round_trip(
             df,