PERF: improve perf of index iteration (GH7683)

doc/source/v0.15.0.txt

@@ -150,6 +150,7 @@ Enhancements
 Performance
 ~~~~~~~~~~~
 
+- Performance improvements in ``DatetimeIndex.__iter__`` to allow faster iteration (:issue:`7683`)
 
 
 

pandas/core/base.py

@@ -390,6 +390,9 @@ def _ops_compat(self, name, op_accessor):
     is_year_start = _field_accessor('is_year_start', "Logical indicating if first day of year (defined by frequency)")
     is_year_end = _field_accessor('is_year_end', "Logical indicating if last day of year (defined by frequency)")
 
+    def __iter__(self):
+        return (self._box_func(v) for v in self.asi8)
+
     @property
     def _box_func(self):
         """

pandas/tseries/index.py

@@ -1093,6 +1093,27 @@ def __array_finalize__(self, obj):
         self.name = getattr(obj, 'name', None)
         self._reset_identity()
 
+    def __iter__(self):
+        """
+        Return an iterator over the boxed values
+
+        Returns
+        -------
+        Timestamps : ndarray
+        """
+
+        # convert in chunks of 10k for efficiency
+        data = self.asi8
+        l = len(self)
+        chunksize = 10000
+        chunks = int(l / chunksize) + 1
+        for i in range(chunks):
+            start_i = i*chunksize
+            end_i = min((i+1)*chunksize,l)
+            converted = tslib.ints_to_pydatetime(data[start_i:end_i], tz=self.tz, offset=self.offset, box=True)
+            for v in converted:
+                yield v
+
     def _wrap_union_result(self, other, result):
         name = self.name if self.name == other.name else None
         if self.tz != other.tz:
@@ -1476,9 +1497,6 @@ def normalize(self):
         return DatetimeIndex(new_values, freq='infer', name=self.name,
                              tz=self.tz)
 
-    def __iter__(self):
-        return iter(self.asobject)
-
     def searchsorted(self, key, side='left'):
         if isinstance(key, np.ndarray):
             key = np.array(key, dtype=_NS_DTYPE, copy=False)

pandas/tseries/period.py

@@ -738,10 +738,6 @@ def astype(self, dtype):
             return Index(self.values, dtype)
         raise ValueError('Cannot cast PeriodIndex to dtype %s' % dtype)
 
-    def __iter__(self):
-        for val in self.values:
-            yield Period(ordinal=val, freq=self.freq)
-
     def searchsorted(self, key, side='left'):
         if isinstance(key, compat.string_types):
             key = Period(key, freq=self.freq).ordinal

pandas/tseries/tests/test_timezones.py

@@ -1027,7 +1027,6 @@ def test_intersection(self):
 
     def test_timestamp_equality_different_timezones(self):
         utc_range = date_range('1/1/2000', periods=20, tz='UTC')
-
         eastern_range = utc_range.tz_convert('US/Eastern')
         berlin_range = utc_range.tz_convert('Europe/Berlin')
 

pandas/tslib.pyx

@@ -74,61 +74,90 @@ try:
 except NameError: # py3
     basestring = str
 
-def ints_to_pydatetime(ndarray[int64_t] arr, tz=None):
+cdef inline object create_timestamp_from_ts(int64_t value, pandas_datetimestruct dts, object tz, object offset):
+    cdef _Timestamp ts_base
+    ts_base = _Timestamp.__new__(Timestamp, dts.year, dts.month,
+                                 dts.day, dts.hour, dts.min,
+                                 dts.sec, dts.us, tz)
+
+    ts_base.value = value
+    ts_base.offset = offset
+    ts_base.nanosecond = dts.ps / 1000
+
+    return ts_base
+
+cdef inline object create_datetime_from_ts(int64_t value, pandas_datetimestruct dts, object tz, object offset):
+    return datetime(dts.year, dts.month, dts.day, dts.hour,
+                    dts.min, dts.sec, dts.us, tz)
+
+def ints_to_pydatetime(ndarray[int64_t] arr, tz=None, offset=None, box=False):
+    # convert an i8 repr to an ndarray of datetimes or Timestamp (if box == True)
+
     cdef:
         Py_ssize_t i, n = len(arr)
         pandas_datetimestruct dts
+        object dt
+        int64_t value
         ndarray[object] result = np.empty(n, dtype=object)
+        object (*func_create)(int64_t, pandas_datetimestruct, object, object)
+
+    if box and util.is_string_object(offset):
+        from pandas.tseries.frequencies import to_offset
+        offset = to_offset(offset)
+
+    if box:
+      func_create = create_timestamp_from_ts
+    else:
+      func_create = create_datetime_from_ts
 
     if tz is not None:
         if _is_utc(tz):
             for i in range(n):
-                if arr[i] == iNaT:
-                    result[i] = np.nan
+                value = arr[i]
+                if value == iNaT:
+                    result[i] = NaT
                 else:
-                    pandas_datetime_to_datetimestruct(arr[i], PANDAS_FR_ns, &dts)
-                    result[i] = datetime(dts.year, dts.month, dts.day, dts.hour,
-                                         dts.min, dts.sec, dts.us, tz)
+                    pandas_datetime_to_datetimestruct(value, PANDAS_FR_ns, &dts)
+                    result[i] = func_create(value, dts, tz, offset)
         elif _is_tzlocal(tz) or _is_fixed_offset(tz):
             for i in range(n):
-                if arr[i] == iNaT:
-                    result[i] = np.nan
+                value = arr[i]
+                if value == iNaT:
+                    result[i] = NaT
                 else:
-                    pandas_datetime_to_datetimestruct(arr[i], PANDAS_FR_ns, &dts)
-                    dt = datetime(dts.year, dts.month, dts.day, dts.hour,
-                                  dts.min, dts.sec, dts.us, tz)
+                    pandas_datetime_to_datetimestruct(value, PANDAS_FR_ns, &dts)
+                    dt = func_create(value, dts, tz, offset)
                     result[i] = dt + tz.utcoffset(dt)
         else:
             trans = _get_transitions(tz)
             deltas = _get_deltas(tz)
             for i in range(n):
 
-                if arr[i] == iNaT:
-                    result[i] = np.nan
+                value = arr[i]
+                if value == iNaT:
+                    result[i] = NaT
                 else:
 
                     # Adjust datetime64 timestamp, recompute datetimestruct
-                    pos = trans.searchsorted(arr[i], side='right') - 1
+                    pos = trans.searchsorted(value, side='right') - 1
                     if _treat_tz_as_pytz(tz):
                         # find right representation of dst etc in pytz timezone
                         new_tz = tz._tzinfos[tz._transition_info[pos]]
                     else:
                         # no zone-name change for dateutil tzs - dst etc represented in single object.
                         new_tz = tz
 
-                    pandas_datetime_to_datetimestruct(arr[i] + deltas[pos],
-                                                      PANDAS_FR_ns, &dts)
-                    result[i] = datetime(dts.year, dts.month, dts.day, dts.hour,
-                                         dts.min, dts.sec, dts.us,
-                                         new_tz)
+                    pandas_datetime_to_datetimestruct(value + deltas[pos], PANDAS_FR_ns, &dts)
+                    result[i] = func_create(value, dts, new_tz, offset)
     else:
         for i in range(n):
-            if arr[i] == iNaT:
-                result[i] = np.nan
+
+            value = arr[i]
+            if value == iNaT:
+                result[i] = NaT
             else:
-                pandas_datetime_to_datetimestruct(arr[i], PANDAS_FR_ns, &dts)
-                result[i] = datetime(dts.year, dts.month, dts.day, dts.hour,
-                                     dts.min, dts.sec, dts.us)
+                pandas_datetime_to_datetimestruct(value, PANDAS_FR_ns, &dts)
+                result[i] = func_create(value, dts, None, offset)
 
     return result
 
@@ -183,6 +212,7 @@ class Timestamp(_Timestamp):
     def utcnow(cls):
         return cls.now('UTC')
 
+
     def __new__(cls, object ts_input, object offset=None, tz=None, unit=None):
         cdef _TSObject ts
         cdef _Timestamp ts_base

vb_suite/timeseries.py

@@ -333,3 +333,28 @@ def date_range(start=None, end=None, periods=None, freq=None):
 
 timeseries_is_month_start = Benchmark('rng.is_month_start', setup,
                                   start_date=datetime(2014, 4, 1))
+
+#----------------------------------------------------------------------
+# iterate over DatetimeIndex/PeriodIndex
+setup = common_setup + """
+N = 1000000
+M = 10000
+idx1 = date_range(start='20140101', freq='T', periods=N)
+idx2 = period_range(start='20140101', freq='T', periods=N)
+
+def iter_n(iterable, n=None):
+  i = 0
+  for _ in iterable:
+    i += 1
+    if n is not None and i > n:
+      break
+"""
+
+timeseries_iter_datetimeindex = Benchmark('iter_n(idx1)', setup)
+
+timeseries_iter_periodindex = Benchmark('iter_n(idx2)', setup)
+
+timeseries_iter_datetimeindex_preexit = Benchmark('iter_n(idx1, M)', setup)
+
+timeseries_iter_periodindex_preexit = Benchmark('iter_n(idx2, M)', setup)
+