REF: Stop mixing DTA/TDA into DTI/TDI

pandas/core/arrays/datetimes.py

@@ -131,7 +131,13 @@ def wrapper(self, other):
                 return ops.invalid_comparison(self, other, op)
 
             if is_object_dtype(other):
-                result = op(self.astype('O'), np.array(other))
+                # We have to use _comp_method_OBJECT_ARRAY instead of numpy
+                #  comparison otherwise it would fail to raise when
+                #  comparing tz-aware and tz-naive
+                with np.errstate(all='ignore'):
+                    result = ops._comp_method_OBJECT_ARRAY(op,
+                                                           self.astype(object),
+                                                           other)
                 o_mask = isna(other)
             elif not (is_datetime64_dtype(other) or
                       is_datetime64tz_dtype(other)):
@@ -430,28 +436,6 @@ def _timezone(self):
         """
         return timezones.get_timezone(self.tzinfo)
 
-    @property
-    def offset(self):
-        """
-        get/set the frequency of the instance
-        """
-        msg = ('{cls}.offset has been deprecated and will be removed '
-               'in a future version; use {cls}.freq instead.'
-               .format(cls=type(self).__name__))
-        warnings.warn(msg, FutureWarning, stacklevel=2)
-        return self.freq
-
-    @offset.setter
-    def offset(self, value):
-        """
-        get/set the frequency of the instance
-        """
-        msg = ('{cls}.offset has been deprecated and will be removed '
-               'in a future version; use {cls}.freq instead.'
-               .format(cls=type(self).__name__))
-        warnings.warn(msg, FutureWarning, stacklevel=2)
-        self.freq = value
-
     @property  # NB: override with cache_readonly in immutable subclasses
     def is_normalized(self):
         """

pandas/core/indexes/datetimelike.py

@@ -10,7 +10,7 @@
 from pandas._libs import NaT, iNaT, lib
 from pandas.compat.numpy import function as nv
 from pandas.errors import AbstractMethodError
-from pandas.util._decorators import Appender, cache_readonly
+from pandas.util._decorators import Appender, cache_readonly, deprecate_kwarg
 
 from pandas.core.dtypes.common import (
     ensure_int64, is_bool_dtype, is_dtype_equal, is_float, is_integer,
@@ -19,6 +19,7 @@
 
 from pandas.core import algorithms, ops
 from pandas.core.accessor import PandasDelegate
+from pandas.core.arrays import ExtensionOpsMixin
 from pandas.core.arrays.datetimelike import (
     DatetimeLikeArrayMixin, _ensure_datetimelike_to_i8)
 import pandas.core.indexes.base as ibase
@@ -30,15 +31,30 @@
 _index_doc_kwargs = dict(ibase._index_doc_kwargs)
 
 
-class DatetimeIndexOpsMixin(DatetimeLikeArrayMixin):
+def ea_passthrough(name):
     """
-    common ops mixin to support a unified interface datetimelike Index
+    Make an alias for a method of the underlying ExtensionArray.
+
+    Parameters
+    ----------
+    name : str
+
+    Returns
+    -------
+    method
     """
+    def method(self, *args, **kwargs):
+        return getattr(self._eadata, name)(*args, **kwargs)
+
+    method.__name__ = name
+    # TODO: docstrings
+    return method
+
 
-    # override DatetimeLikeArrayMixin method
-    copy = Index.copy
-    view = Index.view
-    __setitem__ = Index.__setitem__
+class DatetimeIndexOpsMixin(ExtensionOpsMixin):
+    """
+    common ops mixin to support a unified interface datetimelike Index
+    """
 
     # DatetimeLikeArrayMixin assumes subclasses are mutable, so these are
     # properties there.  They can be made into cache_readonly for Index
@@ -50,6 +66,14 @@ class DatetimeIndexOpsMixin(DatetimeLikeArrayMixin):
     _resolution = cache_readonly(DatetimeLikeArrayMixin._resolution.fget)
     resolution = cache_readonly(DatetimeLikeArrayMixin.resolution.fget)
 
+    _box_values = ea_passthrough("_box_values")
+    _maybe_mask_results = ea_passthrough("_maybe_mask_results")
+    __iter__ = ea_passthrough("__iter__")
+
+    @property
+    def freqstr(self):
+        return self._eadata.freqstr
+
     def unique(self, level=None):
         if level is not None:
             self._validate_index_level(level)
@@ -74,9 +98,6 @@ def wrapper(self, other):
         wrapper.__name__ = '__{}__'.format(op.__name__)
         return wrapper
 
-    # A few methods that are shared
-    _maybe_mask_results = DatetimeLikeArrayMixin._maybe_mask_results
-
     # ------------------------------------------------------------------------
 
     def equals(self, other):
@@ -549,7 +570,7 @@ def _concat_same_dtype(self, to_concat, name):
             # - remove the .asi8 here
             # - remove the _maybe_box_as_values
             # - combine with the `else` block
-            new_data = self._concat_same_type(to_concat).asi8
+            new_data = self._eadata._concat_same_type(to_concat).asi8
         else:
             new_data = type(self._values)._concat_same_type(to_concat)
 
@@ -581,6 +602,12 @@ def _time_shift(self, periods, freq=None):
         result = self._eadata._time_shift(periods, freq=freq)
         return type(self)(result, name=self.name)
 
+    @deprecate_kwarg(old_arg_name='n', new_arg_name='periods')
+    @Appender(DatetimeLikeArrayMixin.shift.__doc__)
+    def shift(self, periods, freq=None):
+        result = self._eadata.shift(periods, freq=freq)
+        return type(self)(result, name=self.name)
+
 
 def wrap_arithmetic_op(self, other, result):
     if result is NotImplemented:

pandas/core/indexes/datetimes.py

@@ -26,7 +26,7 @@
 import pandas.core.common as com
 from pandas.core.indexes.base import Index
 from pandas.core.indexes.datetimelike import (
-    DatetimeIndexOpsMixin, DatetimelikeDelegateMixin)
+    DatetimeIndexOpsMixin, DatetimelikeDelegateMixin, ea_passthrough)
 from pandas.core.indexes.numeric import Int64Index
 from pandas.core.ops import get_op_result_name
 import pandas.core.tools.datetimes as tools
@@ -96,19 +96,13 @@ class DatetimeDelegateMixin(DatetimelikeDelegateMixin):
     _delegate_class = DatetimeArray
 
 
-@delegate_names(DatetimeArray, ["to_period", "tz_localize", "tz_convert",
-                                "day_name", "month_name"],
-                typ="method", overwrite=True)
-@delegate_names(DatetimeArray,
-                DatetimeArray._field_ops, typ="property", overwrite=True)
 @delegate_names(DatetimeArray,
                 DatetimeDelegateMixin._delegated_properties,
                 typ="property")
 @delegate_names(DatetimeArray,
                 DatetimeDelegateMixin._delegated_methods,
                 typ="method", overwrite=False)
-class DatetimeIndex(DatetimeArray, DatetimeIndexOpsMixin, Int64Index,
-                    DatetimeDelegateMixin):
+class DatetimeIndex(DatetimeIndexOpsMixin, Int64Index, DatetimeDelegateMixin):
     """
     Immutable ndarray of datetime64 data, represented internally as int64, and
     which can be boxed to Timestamp objects that are subclasses of datetime and
@@ -268,6 +262,7 @@ def _join_i8_wrapper(joinf, **kwargs):
     _object_ops = DatetimeArray._object_ops
     _field_ops = DatetimeArray._field_ops
     _datetimelike_ops = DatetimeArray._datetimelike_ops
+    _datetimelike_methods = DatetimeArray._datetimelike_methods
 
     # --------------------------------------------------------------------
     # Constructors
@@ -294,8 +289,8 @@ def __new__(cls, data=None,
                           "endpoints is deprecated.  Use "
                           "`pandas.date_range` instead.",
                           FutureWarning, stacklevel=2)
-
-            return cls(dtarr, name=name)
+            return cls._simple_new(
+                dtarr._data, freq=dtarr.freq, tz=dtarr.tz, name=name)
 
         if is_scalar(data):
             raise TypeError("{cls}() must be called with a "
@@ -331,7 +326,11 @@ def _simple_new(cls, values, name=None, freq=None, tz=None, dtype=None):
         # DatetimeArray._simple_new will accept either i8 or M8[ns] dtypes
         assert isinstance(values, np.ndarray), type(values)
 
-        result = super(DatetimeIndex, cls)._simple_new(values, freq, tz)
+        dtarr = DatetimeArray._simple_new(values, freq=freq, tz=tz)
+        result = object.__new__(cls)
+        result._data = dtarr._data
+        result._freq = dtarr.freq
+        result._tz = dtarr.tz
         result.name = name
         # For groupby perf. See note in indexes/base about _index_data
         result._index_data = result._data
@@ -340,6 +339,10 @@ def _simple_new(cls, values, name=None, freq=None, tz=None, dtype=None):
 
     # --------------------------------------------------------------------
 
+    @property
+    def dtype(self):
+        return self._eadata.dtype
+
     @property
     def _values(self):
         # tz-naive -> ndarray
@@ -360,6 +363,8 @@ def tz(self, value):
         raise AttributeError("Cannot directly set timezone. Use tz_localize() "
                              "or tz_convert() as appropriate")
 
+    tzinfo = tz
+
     @property
     def size(self):
         # TODO: Remove this when we have a DatetimeTZArray
@@ -670,7 +675,7 @@ def intersection(self, other):
     def _get_time_micros(self):
         values = self.asi8
         if self.tz is not None and not timezones.is_utc(self.tz):
-            values = self._local_timestamps()
+            values = self._eadata._local_timestamps()
         return fields.get_time_micros(values)
 
     def to_series(self, keep_tz=None, index=None, name=None):
@@ -1139,12 +1144,64 @@ def _eadata(self):
     _is_monotonic_increasing = Index.is_monotonic_increasing
     _is_monotonic_decreasing = Index.is_monotonic_decreasing
     _is_unique = Index.is_unique
-    astype = DatetimeIndexOpsMixin.astype
 
     _timezone = cache_readonly(DatetimeArray._timezone.fget)
     is_normalized = cache_readonly(DatetimeArray.is_normalized.fget)
     _resolution = cache_readonly(DatetimeArray._resolution.fget)
 
+    strftime = ea_passthrough("strftime")
+    _has_same_tz = ea_passthrough("_has_same_tz")
+    __array__ = ea_passthrough("__array__")
+
+    @property
+    def offset(self):
+        """
+        get/set the frequency of the instance
+        """
+        msg = ('{cls}.offset has been deprecated and will be removed '
+               'in a future version; use {cls}.freq instead.'
+               .format(cls=type(self).__name__))
+        warnings.warn(msg, FutureWarning, stacklevel=2)
+        return self.freq
+
+    @offset.setter
+    def offset(self, value):
+        """
+        get/set the frequency of the instance
+        """
+        msg = ('{cls}.offset has been deprecated and will be removed '
+               'in a future version; use {cls}.freq instead.'
+               .format(cls=type(self).__name__))
+        warnings.warn(msg, FutureWarning, stacklevel=2)
+        self.freq = value
+
+    @property
+    def freq(self):
+        return self._freq
+
+    @freq.setter
+    def freq(self, value):
+        if value is not None:
+            # let DatetimeArray to validation
+            self._eadata.freq = value
+
+        self._freq = to_offset(value)
+
+    def __getitem__(self, key):
+        result = self._eadata.__getitem__(key)
+        if is_scalar(result):
+            return result
+        elif result.ndim > 1:
+            # To support MPL which performs slicing with 2 dim
+            # even though it only has 1 dim by definition
+            assert isinstance(result, np.ndarray), result
+            return result
+        return type(self)(result, name=self.name)
+
+    @property
+    def _box_func(self):
+        return lambda x: Timestamp(x, tz=self.tz)
+
     # --------------------------------------------------------------------
 
     @Substitution(klass='DatetimeIndex')
@@ -1486,9 +1543,8 @@ def date_range(start=None, end=None, periods=None, freq=None, tz=None,
         start=start, end=end, periods=periods,
         freq=freq, tz=tz, normalize=normalize,
         closed=closed, **kwargs)
-
-    result = DatetimeIndex(dtarr, name=name)
-    return result
+    return DatetimeIndex._simple_new(
+        dtarr._data, tz=dtarr.tz, freq=dtarr.freq, name=name)
 
 
 def bdate_range(start=None, end=None, periods=None, freq='B', tz=None,