ENH: Limit handle_data to times with market data.

To prevent cases where custom data types had unaligned timestamps,
only call handle_data when market data passes through.

Custom data that comes before market data will still update
the data bar. But the handling of that data will only be done
when there is actionable market data.

tests/test_algorithm_gen.py

@@ -21,6 +21,7 @@ from nose.tools import (
 )
 
 from datetime import datetime
+import pandas as pd
 
 import pytz
 from zipline.finance import trading
@@ -31,6 +32,10 @@ from zipline.utils.test_utils import (
     setup_logger,
     teardown_logger
 )
+from zipline.protocol import (
+    Event,
+    DATASOURCE_TYPE
+)
 
 DEFAULT_TIMEOUT = 15  # seconds
 EXTENDED_TIMEOUT = 90
@@ -59,8 +64,10 @@ class TestAlgo(TradingAlgorithm):
         self.set_slippage(RecordDateSlippage(spread=0.05))
         self.stocks = [8229]
         self.ordered = False
+        self.num_bars = 0
 
     def handle_data(self, data):
+        self.num_bars += 1
         self.latest_date = self.get_datetime()
 
         if not self.ordered:
@@ -138,6 +145,53 @@ class AlgorithmGeneratorTestCase(TestCase):
         self.assertTrue(algo.slippage.latest_date)
         self.assertTrue(algo.latest_date)
 
+    @timed(DEFAULT_TIMEOUT)
+    def test_handle_data_on_market(self):
+        """
+        Ensure that handle_data is only called on market minutes.
+
+        i.e. events that come in at midnight should be processed at market
+        open.
+        """
+        from zipline.finance.trading import SimulationParameters
+        sim_params = SimulationParameters(
+            period_start=datetime(2012, 7, 30, tzinfo=pytz.utc),
+            period_end=datetime(2012, 7, 30, tzinfo=pytz.utc),
+            data_frequency='minute'
+        )
+        algo = TestAlgo(self,
+                        sim_params=sim_params)
+
+        midnight_custom_source = [Event({
+            'custom_field': 42.0,
+            'sid': 'custom_data',
+            'source_id': 'TestMidnightSource',
+            'dt': pd.Timestamp('2012-07-30', tz='UTC'),
+            'type': DATASOURCE_TYPE.CUSTOM
+        })]
+        minute_event_source = [Event({
+            'volume': 100,
+            'price': 200.0,
+            'high': 210.0,
+            'open_price': 190.0,
+            'low': 180.0,
+            'sid': 8229,
+            'source_id': 'TestMinuteEventSource',
+            'dt': pd.Timestamp('2012-07-30 9:31 AM', tz='US/Eastern').
+            tz_convert('UTC'),
+            'type': DATASOURCE_TYPE.TRADE
+        })]
+
+        algo.set_sources([midnight_custom_source, minute_event_source])
+
+        gen = algo.get_generator()
+        # Consume the generator
+        list(gen)
+
+        # Though the events had different time stamps, handle data should
+        # have only been called once, at the market open.
+        self.assertEqual(algo.num_bars, 1)
+
     @timed(DEFAULT_TIMEOUT)
     def test_progress(self):
         """

zipline/gens/tradesimulation.py

@@ -137,7 +137,6 @@ class AlgorithmSimulator(object):
 
                         elif event.type == DATASOURCE_TYPE.CUSTOM:
                             self.update_universe(event)
-                            updated = True
 
                         elif event.type == DATASOURCE_TYPE.SPLIT:
                             self.algo.blotter.process_split(event)