move array_type -> construct_array_type

Author: jreback

doc/source/whatsnew/v0.24.0.txt

@@ -35,8 +35,9 @@ Datetimelike API Changes
 ExtensionType Changes
 ^^^^^^^^^^^^^^^^^^^^^
 
-- ``ExtensionArray`` has gained the abstract methods ``.dropna()`` and ``.append()``, and attribute ``array_type`` (:issue:`21185`)
-- ``ExtensionDtype`` has gained the ability to instantiate from string dtypes, e.g. ``decimal`` would instantiate a registered ``DecimalDtype`` (:issue:`21185`)
+- ``ExtensionArray`` has gained the abstract methods ``.dropna()`` and ``.append()`` (:issue:`21185`)
+- ``ExtensionDtype`` has gained the ability to instantiate from string dtypes, e.g. ``decimal`` would instantiate a registered ``DecimalDtype``; furthermore
+  the dtype has gained the ``construct_array_type`` (:issue:`21185`)
 - The ``ExtensionArray`` constructor, ``_from_sequence`` now take the keyword arg ``copy=False`` (:issue:`21185`)
 
 .. _whatsnew_0240.api.other:

pandas/core/algorithms.py

@@ -154,7 +154,7 @@ def _reconstruct_data(values, dtype, original):
     """
     from pandas import Index
     if is_extension_array_dtype(dtype):
-        values = dtype.array_type._from_sequence(values)
+        values = dtype.construct_array_type(values)._from_sequence(values)
     elif is_datetime64tz_dtype(dtype) or is_period_dtype(dtype):
         values = Index(original)._shallow_copy(values, name=None)
     elif is_bool_dtype(dtype):

pandas/core/arrays/categorical.py

@@ -2354,10 +2354,6 @@ def isin(self, values):
         return algorithms.isin(self.codes, code_values)
 
 
-# inform the Dtype about us
-CategoricalDtype.array_type = Categorical
-
-
 # The Series.cat accessor
 
 

pandas/core/dtypes/base.py

@@ -109,11 +109,10 @@ class ExtensionDtype(_DtypeOpsMixin):
     * name
     * construct_from_string
 
+    Optionally one can override construct_array_type for construction
+    with the name of this dtype via the Registry
 
-    Optionally one can assign an array_type for construction with the name
-    of this dtype via the Registry
-
-    * array_type
+    * construct_array_type
 
     The `na_value` class attribute can be used to set the default NA value
     for this type. :attr:`numpy.nan` is used by default.
@@ -124,8 +123,6 @@ class ExtensionDtype(_DtypeOpsMixin):
     provided for registering virtual subclasses.
     """
 
-    array_type = None
-
     def __str__(self):
         return self.name
 
@@ -164,11 +161,19 @@ def name(self):
         """
         raise AbstractMethodError(self)
 
-    @property
-    def array_type(self):
+    @classmethod
+    def construct_array_type(cls, array):
         """Return the array type associated with this dtype
+
+        Parameters
+        ----------
+        string : str
+
+        Returns
+        -------
+        type
         """
-        raise AbstractMethodError(self)
+        return type(array)
 
     @classmethod
     def construct_from_string(cls, string):

pandas/core/dtypes/dtypes.py

@@ -317,6 +317,21 @@ def _hash_categories(categories, ordered=True):
         else:
             return np.bitwise_xor.reduce(hashed)
 
+    @classmethod
+    def construct_array_type(cls, array):
+        """Return the array type associated with this dtype
+
+        Parameters
+        ----------
+        string : str
+
+        Returns
+        -------
+        type
+        """
+        from pandas import Categorical
+        return Categorical
+
     @classmethod
     def construct_from_string(cls, string):
         """ attempt to construct this type from a string, raise a TypeError if

pandas/core/series.py

@@ -4062,7 +4062,7 @@ def _try_cast(arr, take_fast_path):
                                      ordered=dtype.ordered)
             elif is_extension_array_dtype(dtype):
                 # create an extension array from its dtype
-                array_type = dtype.array_type
+                array_type = dtype.construct_array_type(subarr)
                 subarr = array_type(subarr, copy=copy)
 
             elif dtype is not None and raise_cast_failure:

pandas/tests/extension/decimal/array.py

@@ -15,6 +15,20 @@ class DecimalDtype(ExtensionDtype):
     name = 'decimal'
     na_value = decimal.Decimal('NaN')
 
+    @classmethod
+    def construct_array_type(cls, array):
+        """Return the array type associated with this dtype
+
+        Parameters
+        ----------
+        string : str
+
+        Returns
+        -------
+        type
+        """
+        return DecimalArray
+
     @classmethod
     def construct_from_string(cls, string):
         if string == cls.name:
@@ -101,8 +115,5 @@ def _concat_same_type(cls, to_concat):
         return cls(np.concatenate([x._data for x in to_concat]))
 
 
-DecimalDtype.array_type = DecimalArray
-
-
 def make_data():
     return [decimal.Decimal(random.random()) for _ in range(100)]

pandas/tests/extension/json/array.py

@@ -32,6 +32,20 @@ class JSONDtype(ExtensionDtype):
         # source compatibility with Py2.
         na_value = {}
 
+    @classmethod
+    def construct_array_type(cls, array):
+        """Return the array type associated with this dtype
+
+        Parameters
+        ----------
+        string : str
+
+        Returns
+        -------
+        type
+        """
+        return JSONArray
+
     @classmethod
     def construct_from_string(cls, string):
         if string == cls.name:
@@ -171,9 +185,6 @@ def _values_for_argsort(self):
         return np.array(frozen, dtype=object)[1:]
 
 
-JSONDtype.array_type = JSONArray
-
-
 def make_data():
     # TODO: Use a regular dict. See _NDFrameIndexer._setitem_with_indexer
     return [collections.UserDict([