ENH: support cumsum with pyarrow durations

pandas/core/arrays/arrow/array.py

@@ -985,7 +985,18 @@ def _accumulate(
         pyarrow_meth = getattr(pc, pyarrow_name, None)
         if pyarrow_meth is None:
             return super()._accumulate(name, skipna=skipna, **kwargs)
-        result = pyarrow_meth(self._data, skip_nulls=skipna, **kwargs)
+
+        data_to_accum = self._data
+
+        pa_dtype = data_to_accum.type
+        if pa.types.is_duration(pa_dtype):
+            data_to_accum = data_to_accum.cast(pa.int64())
+
+        result = pyarrow_meth(data_to_accum, skip_nulls=skipna, **kwargs)
+
+        if pa.types.is_duration(pa_dtype):
+            result = result.cast(pa_dtype)
+
         return type(self)(result)
 
     def _reduce(self, name: str, *, skipna: bool = True, **kwargs):

pandas/tests/extension/test_arrow.py

@@ -372,16 +372,27 @@ def test_getitem_scalar(self, data):
 
 
 class TestBaseAccumulateTests(base.BaseAccumulateTests):
-    def check_accumulate(self, s, op_name, skipna):
-        result = getattr(s, op_name)(skipna=skipna).astype("Float64")
-        expected = getattr(s.astype("Float64"), op_name)(skipna=skipna)
+    def check_accumulate(self, ser, op_name, skipna):
+        result = getattr(ser, op_name)(skipna=skipna)
+
+        if ser.dtype.kind == "m":
+            # Just check that we match the integer behavior.
+            ser = ser.astype("int64[pyarrow]")
+            result = result.astype("int64[pyarrow]")
+
+        result = result.astype("Float64")
+        expected = getattr(ser.astype("Float64"), op_name)(skipna=skipna)
         self.assert_series_equal(result, expected, check_dtype=False)
 
     @pytest.mark.parametrize("skipna", [True, False])
     def test_accumulate_series_raises(self, data, all_numeric_accumulations, skipna):
         pa_type = data.dtype.pyarrow_dtype
         if (
-            (pa.types.is_integer(pa_type) or pa.types.is_floating(pa_type))
+            (
+                pa.types.is_integer(pa_type)
+                or pa.types.is_floating(pa_type)
+                or pa.types.is_duration(pa_type)
+            )
             and all_numeric_accumulations == "cumsum"
             and not pa_version_under9p0
         ):
@@ -423,9 +434,7 @@ def test_accumulate_series(self, data, all_numeric_accumulations, skipna, reques
                     raises=NotImplementedError,
                 )
             )
-        elif all_numeric_accumulations == "cumsum" and (
-            pa.types.is_duration(pa_type) or pa.types.is_boolean(pa_type)
-        ):
+        elif all_numeric_accumulations == "cumsum" and (pa.types.is_boolean(pa_type)):
             request.node.add_marker(
                 pytest.mark.xfail(
                     reason=f"{all_numeric_accumulations} not implemented for {pa_type}",