FEAT-modin-project#6808: Implement '__arrow_array__' for Series (modi…

…n-project#7200)

Signed-off-by: Anatoly Myachev <anatoly.myachev@intel.com>

modin/pandas/series.py

@@ -517,6 +517,14 @@ def values(self):  # noqa: RT01, D200
             data = pd.Categorical(data, dtype=self.dtype)
         return data
 
+    def __arrow_array__(self, type=None):  # noqa: GL08
+        # Although pandas.Series does not implement this method (true for version 2.2.*),
+        # however, pyarrow has support for it. This method emulates this behavior and
+        # allows pyarrow to work with modin.pandas.Series.
+        import pyarrow
+
+        return pyarrow.array(self._to_pandas(), type=type)
+
     def add(
         self, other, level=None, fill_value=None, axis=0
     ) -> Series:  # noqa: PR01, RT01, D200

modin/tests/pandas/test_series.py

@@ -1387,6 +1387,30 @@ def test_constructor_arrow_extension_array():
     df_equals(md_ser.dtypes, pd_ser.dtypes)
 
 
+def test_pyarrow_array_retrieve():
+    pa = pytest.importorskip("pyarrow")
+    modin_series, pandas_series = create_test_series(
+        [1, 2, None], dtype="uint8[pyarrow]"
+    )
+    eval_general(
+        modin_series,
+        pandas_series,
+        lambda ser: pa.array(ser),
+    )
+
+
+def test___arrow_array__():
+    # https://github.com/modin-project/modin/issues/6808
+    pa = pytest.importorskip("pyarrow")
+    mpd_df_1 = pd.DataFrame({"a": ["1", "2", "3"], "b": ["4", "5", "6"]})
+    mpd_df_2 = pd.DataFrame({"a": ["7", "8", "9"], "b": ["10", "11", "12"]})
+    test_df = pd.concat([mpd_df_1, mpd_df_2])
+
+    res_from_md = pa.Table.from_pandas(df=test_df)
+    res_from_pd = pa.Table.from_pandas(df=test_df._to_pandas())
+    assert res_from_md.equals(res_from_pd)
+
+
 @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
 def test_copy(data):
     modin_series, pandas_series = create_test_series(data)