Adds a trading day index to tradingcalander.

The trading day index is all business days in range minus the
non trading days we are already calculating.

Also, uses trading calendar indexes for batch transform, since the
batch transform was the only use of non_trading_days.

Instead of constantly adding and removing holidays to do market
day delta math, uses pandas DatetimeIndex to get the index of the dates
and uses the index difference to calculate market days.

zipline/transforms/utils.py

@@ -29,7 +29,7 @@ from numbers import Integral
 import pandas as pd
 
 from zipline.protocol import Event
-from zipline.utils.tradingcalendar import non_trading_days
+from zipline.utils import tradingcalendar
 from zipline.gens.utils import assert_sort_unframe_protocol, hash_args
 
 log = logbook.Logger('Transform')
@@ -209,9 +209,6 @@ class EventWindow(object):
         if self.market_aware:
             assert self.window_length and self.delta is None, \
                 "Market-aware mode only works with full-day windows."
-            self.all_holidays = deque(non_trading_days)
-            self.cur_holidays = deque()
-
         # Non-market-aware mode requires a timedelta.
         else:
             assert self.delta and not self.window_length, \
@@ -244,9 +241,6 @@ class EventWindow(object):
         # adding new ticks.
         self.handle_add(event)
 
-        if self.market_aware:
-            self.add_new_holidays(event.dt)
-
         # Clear out any expired events. drop_condition changes depending
         # on whether or not we are running in market_aware mode.
         #
@@ -262,25 +256,11 @@ class EventWindow(object):
             # behavior for removing ticks.
             self.handle_remove(popped)
 
-    def add_new_holidays(self, newest):
-        # Add to our tracked window any untracked holidays that are
-        # older than our newest event. (newest should always be
-        # self.ticks[-1])
-        while len(self.all_holidays) > 0 and self.all_holidays[0] <= newest:
-            self.cur_holidays.append(self.all_holidays.popleft())
-
-    def drop_old_holidays(self, oldest):
-        # Drop from our tracked window any holidays that are older
-        # than our oldest tracked event. (oldest should always
-        # be self.ticks[0])
-        while len(self.cur_holidays) > 0 and self.cur_holidays[0] < oldest:
-            self.cur_holidays.popleft()
-
     def out_of_market_window(self, oldest, newest):
-        self.drop_old_holidays(oldest)
-        calendar_dates_between = (newest.date() - oldest.date()).days
-        holidays_between = len(self.cur_holidays)
-        trading_days_between = calendar_dates_between - holidays_between
+        oldest_index = tradingcalendar.trading_days.searchsorted(oldest)
+        newest_index = tradingcalendar.trading_days.searchsorted(newest)
+
+        trading_days_between = newest_index - oldest_index
 
         # "Put back" a day if oldest is earlier in its day than newest,
         # reflecting the fact that we haven't yet completed the last

zipline/utils/tradingcalendar.py

@@ -14,6 +14,7 @@
 # limitations under the License.
 
 
+import pandas as pd
 import pytz
 
 from datetime import datetime
@@ -176,6 +177,15 @@ def get_non_trading_days(start, end):
     # - President Gerald R. Ford - Jan 2, 2007
     non_trading_days.append(datetime(2007, 1, 2, tzinfo=pytz.utc))
 
-    return sorted(non_trading_days)
+    return pd.DatetimeIndex(sorted(non_trading_days))
 
-non_trading_days = get_non_trading_days(start, end)
+
+def get_trading_days(start, end):
+    business_days = pd.DatetimeIndex(start=start, end=end,
+                                     freq=pd.datetools.BDay())
+
+    non_trading_days = get_non_trading_days(start, end)
+
+    return business_days - non_trading_days
+
+trading_days = get_trading_days(start, end)