ENH: add ExtensionArray._explode method; adjust pyarrow extension for use of new interface

doc/source/reference/extensions.rst

@@ -34,6 +34,7 @@ objects.
 
       api.extensions.ExtensionArray._accumulate
       api.extensions.ExtensionArray._concat_same_type
+      api.extensions.ExtensionArray._explode
       api.extensions.ExtensionArray._formatter
       api.extensions.ExtensionArray._from_factorized
       api.extensions.ExtensionArray._from_sequence

doc/source/whatsnew/v2.2.0.rst

@@ -73,6 +73,7 @@ enhancement2
 
 Other enhancements
 ^^^^^^^^^^^^^^^^^^
+- :meth:`ExtensionArray._explode` interface method added to allow extension type implementations of the ``explode`` method (:issue:`54833`)
 - DataFrame.apply now allows the usage of numba (via ``engine="numba"``) to JIT compile the passed function, allowing for potential speedups (:issue:`54666`)
 -
 

pandas/core/arrays/arrow/array.py

@@ -1609,6 +1609,10 @@ def _explode(self):
         """
         See Series.explode.__doc__.
         """
+        # child class explode method supports only list types; return
+        # default implementation for non list types.
+        if not pa.types.is_list(self.dtype.pyarrow_dtype):
+            return super()._explode()
         values = self
         counts = pa.compute.list_value_length(values._pa_array)
         counts = counts.fill_null(1).to_numpy()

pandas/core/arrays/base.py

@@ -142,6 +142,7 @@ class ExtensionArray:
     view
     _accumulate
     _concat_same_type
+    _explode
     _formatter
     _from_factorized
     _from_sequence
@@ -1924,6 +1925,41 @@ def _hash_pandas_object(
             values, encoding=encoding, hash_key=hash_key, categorize=categorize
         )
 
+    def _explode(self) -> tuple[Self, npt.NDArray[np.uint64]]:
+        """
+        Transform each element of list-like to a row.
+
+        For arrays that do not contain list-like elements the default
+        implementation of this method just returns a copy and an array
+        of ones (unchanged index).
+
+        Returns
+        -------
+        ExtensionArray
+            Array with the exploded values.
+        np.ndarray[uint64]
+            The original lengths of each list-like for determining the
+            resulting index.
+
+        See Also
+        --------
+        Series.explode : The method on the ``Series`` object that this
+            extension array method is meant to support.
+
+        Examples
+        --------
+        >>> import pyarrow as pa
+        >>> a = pd.array([[1, 2, 3], [4], [5, 6]],
+        ...              dtype=pd.ArrowDtype(pa.list_(pa.int64())))
+        >>> a._explode()
+        (<ArrowExtensionArray>
+        [1, 2, 3, 4, 5, 6]
+        Length: 6, dtype: int64[pyarrow], array([3, 1, 2], dtype=int32))
+        """
+        values = self.copy()
+        counts = np.ones(shape=(len(self),), dtype=np.uint64)
+        return values, counts
+
     def tolist(self) -> list:
         """
         Return a list of the values.

pandas/core/series.py

@@ -76,10 +76,7 @@
     pandas_dtype,
     validate_all_hashable,
 )
-from pandas.core.dtypes.dtypes import (
-    ArrowDtype,
-    ExtensionDtype,
-)
+from pandas.core.dtypes.dtypes import ExtensionDtype
 from pandas.core.dtypes.generic import ABCDataFrame
 from pandas.core.dtypes.inference import is_hashable
 from pandas.core.dtypes.missing import (
@@ -4390,7 +4387,7 @@ def explode(self, ignore_index: bool = False) -> Series:
         3      4
         dtype: object
         """
-        if isinstance(self.dtype, ArrowDtype) and self.dtype.type == list:
+        if isinstance(self.dtype, ExtensionDtype):
             values, counts = self._values._explode()
         elif len(self) and is_object_dtype(self.dtype):
             values, counts = reshape.explode(np.asarray(self._values))

pandas/tests/series/methods/test_explode.py

@@ -163,3 +163,13 @@ def test_explode_pyarrow_list_type(ignore_index):
         dtype=pd.ArrowDtype(pa.int64()),
     )
     tm.assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize("ignore_index", [True, False])
+def test_explode_pyarrow_non_list_type(ignore_index):
+    pa = pytest.importorskip("pyarrow")
+    data = [1, 2, 3]
+    ser = pd.Series(data, dtype=pd.ArrowDtype(pa.int64()))
+    result = ser.explode(ignore_index=ignore_index)
+    expected = pd.Series([1, 2, 3], dtype="int64[pyarrow]", index=[0, 1, 2])
+    tm.assert_series_equal(result, expected)