ENH: implement DatetimeLikeArray

pandas/core/indexes/datetimelike.py

@@ -121,8 +121,149 @@ def ceil(self, freq):
         return self._round(freq, np.ceil)
 
 
-class DatetimeIndexOpsMixin(object):
+class DatetimeLikeArray(object):
+    """
+    Shared Base/Mixin class for DatetimeArray, TimedeltaArray, PeriodArray
+
+    Assumes that __new__/__init__ defines:
+        _data
+        freq
+    """
+
+    @property
+    def _box_func(self):
+        """
+        box function to get object from internal representation
+        """
+        raise com.AbstractMethodError(self)
+
+    def __iter__(self):
+        return (self._box_func(v) for v in self.asi8)
+
+    @property
+    def values(self):
+        """ return the underlying data as an ndarray """
+        return self._data.view(np.ndarray)
+
+    @property
+    def asi8(self):
+        # do not cache or you'll create a memory leak
+        return self.values.view('i8')
+
+    # ------------------------------------------------------------------
+    # Null Handling
+
+    @property  # NB: override with cache_readonly in immutable subclasses
+    def _isnan(self):
+        """ return if each value is nan"""
+        return (self.asi8 == iNaT)
+
+    @property  # NB: override with cache_readonly in immutable subclasses
+    def hasnans(self):
+        """ return if I have any nans; enables various perf speedups """
+        return self._isnan.any()
+
+    def _maybe_mask_results(self, result, fill_value=None, convert=None):
+        """
+        Parameters
+        ----------
+        result : a ndarray
+        convert : string/dtype or None
+
+        Returns
+        -------
+        result : ndarray with values replace by the fill_value
+
+        mask the result if needed, convert to the provided dtype if its not
+        None
+
+        This is an internal routine
+        """
+
+        if self.hasnans:
+            if convert:
+                result = result.astype(convert)
+            if fill_value is None:
+                fill_value = np.nan
+            result[self._isnan] = fill_value
+        return result
+
+    # ------------------------------------------------------------------
+
+    @property
+    def freqstr(self):
+        """
+        Return the frequency object as a string if its set, otherwise None
+        """
+        if self.freq is None:
+            return None
+        return self.freq.freqstr
+
+    @property  # NB: override with cache_readonly in immutable subclasses
+    def inferred_freq(self):
+        """
+        Tryies to return a string representing a frequency guess,
+        generated by infer_freq.  Returns None if it can't autodetect the
+        frequency.
+        """
+        try:
+            return frequencies.infer_freq(self)
+        except ValueError:
+            return None
+
+    # ------------------------------------------------------------------
+    # Arithmetic Methods
+
+    def _add_datelike(self, other):
+        raise TypeError("cannot add {cls} and {typ}"
+                        .format(cls=type(self).__name__,
+                                typ=type(other).__name__))
+
+    def _sub_datelike(self, other):
+        raise com.AbstractMethodError(self)
+
+    def _sub_period(self, other):
+        return NotImplemented
+
+    def _add_delta(self, other):
+        return NotImplemented
+
+    def _add_delta_td(self, other):
+        """
+        Add a delta of a timedeltalike
+        return the i8 result view
+        """
+        inc = delta_to_nanoseconds(other)
+        new_values = checked_add_with_arr(self.asi8, inc,
+                                          arr_mask=self._isnan).view('i8')
+        if self.hasnans:
+            new_values[self._isnan] = iNaT
+        return new_values.view('i8')
+
+    def _add_delta_tdi(self, other):
+        """
+        Add a delta of a TimedeltaIndex
+        return the i8 result view
+        """
+        if not len(self) == len(other):
+            raise ValueError("cannot add indices of unequal length")
+
+        self_i8 = self.asi8
+        other_i8 = other.asi8
+        new_values = checked_add_with_arr(self_i8, other_i8,
+                                          arr_mask=self._isnan,
+                                          b_mask=other._isnan)
+        if self.hasnans or other.hasnans:
+            mask = (self._isnan) | (other._isnan)
+            new_values[mask] = iNaT
+        return new_values.view('i8')
+
+
+class DatetimeIndexOpsMixin(DatetimeLikeArray):
     """ common ops mixin to support a unified interface datetimelike Index """
+    inferred_freq = cache_readonly(DatetimeLikeArray.inferred_freq.fget)
+    _isnan = cache_readonly(DatetimeLikeArray._isnan.fget)
+    hasnans = cache_readonly(DatetimeLikeArray.hasnans.fget)
 
     def equals(self, other):
         """
@@ -152,9 +293,6 @@ def equals(self, other):
 
         return np.array_equal(self.asi8, other.asi8)
 
-    def __iter__(self):
-        return (self._box_func(v) for v in self.asi8)
-
     @staticmethod
     def _join_i8_wrapper(joinf, dtype, with_indexers=True):
         """ create the join wrapper methods """
@@ -229,13 +367,6 @@ def _ensure_localized(self, result):
             result = result.tz_localize(self.tz)
         return result
 
-    @property
-    def _box_func(self):
-        """
-        box function to get object from internal representation
-        """
-        raise com.AbstractMethodError(self)
-
     def _box_values(self, values):
         """
         apply box func to passed values
@@ -311,27 +442,6 @@ def __getitem__(self, key):
 
             return self._simple_new(result, **attribs)
 
-    @property
-    def freqstr(self):
-        """
-        Return the frequency object as a string if its set, otherwise None
-        """
-        if self.freq is None:
-            return None
-        return self.freq.freqstr
-
-    @cache_readonly
-    def inferred_freq(self):
-        """
-        Tryies to return a string representing a frequency guess,
-        generated by infer_freq.  Returns None if it can't autodetect the
-        frequency.
-        """
-        try:
-            return frequencies.infer_freq(self)
-        except ValueError:
-            return None
-
     def _nat_new(self, box=True):
         """
         Return Index or ndarray filled with NaT which has the same
@@ -424,11 +534,6 @@ def get_duplicates(self):
     _na_value = NaT
     """The expected NA value to use with this index."""
 
-    @cache_readonly
-    def _isnan(self):
-        """ return if each value is nan"""
-        return (self.asi8 == iNaT)
-
     @property
     def asobject(self):
         """Return object Index which contains boxed values.
@@ -449,31 +554,6 @@ def _convert_tolerance(self, tolerance, target):
                              'target index size')
         return tolerance
 
-    def _maybe_mask_results(self, result, fill_value=None, convert=None):
-        """
-        Parameters
-        ----------
-        result : a ndarray
-        convert : string/dtype or None
-
-        Returns
-        -------
-        result : ndarray with values replace by the fill_value
-
-        mask the result if needed, convert to the provided dtype if its not
-        None
-
-        This is an internal routine
-        """
-
-        if self.hasnans:
-            if convert:
-                result = result.astype(convert)
-            if fill_value is None:
-                fill_value = np.nan
-            result[self._isnan] = fill_value
-        return result
-
     def tolist(self):
         """
         return a list of the underlying data
@@ -630,17 +710,6 @@ def _convert_scalar_indexer(self, key, kind=None):
         return (super(DatetimeIndexOpsMixin, self)
                 ._convert_scalar_indexer(key, kind=kind))
 
-    def _add_datelike(self, other):
-        raise TypeError("cannot add {0} and {1}"
-                        .format(type(self).__name__,
-                                type(other).__name__))
-
-    def _sub_datelike(self, other):
-        raise com.AbstractMethodError(self)
-
-    def _sub_period(self, other):
-        return NotImplemented
-
     def _addsub_offset_array(self, other, op):
         """
         Add or subtract array-like of DateOffset objects
@@ -802,42 +871,6 @@ def __isub__(self, other):
             return self.__sub__(other)
         cls.__isub__ = __isub__
 
-    def _add_delta(self, other):
-        return NotImplemented
-
-    def _add_delta_td(self, other):
-        """
-        Add a delta of a timedeltalike
-        return the i8 result view
-        """
-
-        inc = delta_to_nanoseconds(other)
-        new_values = checked_add_with_arr(self.asi8, inc,
-                                          arr_mask=self._isnan).view('i8')
-        if self.hasnans:
-            new_values[self._isnan] = iNaT
-        return new_values.view('i8')
-
-    def _add_delta_tdi(self, other):
-        """
-        Add a delta of a TimedeltaIndex
-        return the i8 result view
-        """
-
-        # delta operation
-        if not len(self) == len(other):
-            raise ValueError("cannot add indices of unequal length")
-
-        self_i8 = self.asi8
-        other_i8 = other.asi8
-        new_values = checked_add_with_arr(self_i8, other_i8,
-                                          arr_mask=self._isnan,
-                                          b_mask=other._isnan)
-        if self.hasnans or other.hasnans:
-            mask = (self._isnan) | (other._isnan)
-            new_values[mask] = iNaT
-        return new_values.view('i8')
-
     def isin(self, values):
         """
         Compute boolean array of whether each index value is found in the