ENH: ExtensionArray.fillna

pandas/core/arrays/base.py

@@ -216,11 +216,6 @@ def isna(self):
         """
         raise AbstractMethodError(self)
 
-    def tolist(self):
-        # type: () -> list
-        """Convert the array to a list of scalars."""
-        return list(self)
-
     def fillna(self, value=None, method=None, limit=None):
         """ Fill NA/NaN values using the specified method.
 

pandas/core/base.py

@@ -8,11 +8,11 @@
 
 from pandas.core.dtypes.missing import isna
 from pandas.core.dtypes.generic import ABCDataFrame, ABCSeries, ABCIndexClass
+from pandas.core.dtypes.cast import tolist
 from pandas.core.dtypes.common import (
     is_object_dtype,
     is_list_like,
     is_scalar,
-    is_datetimelike,
     is_extension_type,
     is_extension_array_dtype)
 
@@ -826,11 +826,7 @@ def tolist(self):
         --------
         numpy.ndarray.tolist
         """
-
-        if is_datetimelike(self):
-            return [com._maybe_box_datetimelike(x) for x in self._values]
-        else:
-            return self._values.tolist()
+        return tolist(self._values)
 
     def __iter__(self):
         """

pandas/core/dtypes/cast.py

@@ -11,7 +11,8 @@
 from .common import (_ensure_object, is_bool, is_integer, is_float,
                      is_complex, is_datetimetz, is_categorical_dtype,
                      is_datetimelike,
-                     is_extension_type, is_object_dtype,
+                     is_extension_type, is_extension_array_dtype,
+                     is_object_dtype,
                      is_datetime64tz_dtype, is_datetime64_dtype,
                      is_datetime64_ns_dtype,
                      is_timedelta64_dtype, is_timedelta64_ns_dtype,
@@ -1222,3 +1223,32 @@ def construct_1d_object_array_from_listlike(values):
     result = np.empty(len(values), dtype='object')
     result[:] = values
     return result
+
+
+def tolist(values):
+    """Convert an array-like to a list of scalar types.
+
+    Parameters
+    ----------
+    values : ndarray or ExtensionArray
+
+    Returns
+    -------
+    list
+        Each element of the list is a Python scalar (stor, int float)
+        or a pandas scalar (Timestamp / Timedelta / Interval / Period) or
+        the scalar type for 3rd party Extension Arrays.
+
+    See Also
+    --------
+    Series.tolist
+    numpy.ndarray.tolist
+    """
+    from pandas.core.common import _maybe_box_datetimelike
+
+    if is_datetimelike(values):
+        return [_maybe_box_datetimelike(x) for x in values]
+    elif is_extension_array_dtype(values):
+        return list(values)
+    else:
+        return values.tolist()

pandas/tests/dtypes/test_cast.py

@@ -23,7 +23,8 @@
     maybe_convert_scalar,
     find_common_type,
     construct_1d_object_array_from_listlike,
-    construct_1d_arraylike_from_scalar)
+    construct_1d_arraylike_from_scalar,
+    tolist)
 from pandas.core.dtypes.dtypes import (
     CategoricalDtype,
     DatetimeTZDtype,
@@ -324,6 +325,18 @@ def test_maybe_convert_objects_copy(self):
         out = maybe_convert_objects(values, copy=True)
         assert values is not out
 
+    @pytest.mark.parametrize('values, expected', [
+        (pd.date_range('2017', periods=1), [pd.Timestamp('2017')]),
+        (pd.period_range('2017', periods=1, freq='D'),
+         [pd.Period('2017', freq='D')]),
+        (pd.timedelta_range(0, periods=1), [pd.Timedelta('0')]),
+        (pd.interval_range(0, periods=1), [pd.Interval(0, 1)]),
+        (np.array([0, 1]), [0, 1]),
+    ])
+    def test_tolist(self, values, expected):
+        result = tolist(values)
+        assert result == expected
+
 
 class TestCommonTypes(object):
 

pandas/tests/extension/base/interface.py

@@ -2,6 +2,7 @@
 
 import pandas as pd
 from pandas.compat import StringIO
+from pandas.core.dtypes.cast import tolist
 from pandas.core.dtypes.common import is_extension_array_dtype
 from pandas.core.dtypes.dtypes import ExtensionDtype
 
@@ -53,3 +54,8 @@ def test_is_extension_array_dtype(self, data):
         assert is_extension_array_dtype(data.dtype)
         assert is_extension_array_dtype(pd.Series(data))
         assert isinstance(data.dtype, ExtensionDtype)
+
+    def test_tolist(self, data):
+        result = tolist(data)
+        expected = list(data)
+        assert result == expected