def before_trading_start(context, data):
    # Pipeline_output returns the constructed dataframe.
    output = pipeline_output('example')

    # Select and update your universe.
    context.my_universe = output.sort('sma_short', ascending=False).iloc[:200]
    update_universe(context.my_universe.index)

def before_trading_start(context, data):
    context.output = pipeline_output('example')

    context.short_list = context.output.sort(['sma_rank'], ascending=True).iloc[:200]
    context.long_list = context.output.sort(['sma_rank'], ascending=True).iloc[-200:]

    update_universe(context.long_list.index.union(context.short_list.index))

 def handle_data(context, data):
     closes = pipeline_output('test_close')
     volumes = pipeline_output('test_volume')
     date = get_datetime().normalize()
     for asset in self.assets:
         # Assets should appear iff they exist today and yesterday.
         exists_today = self.exists(date, asset)
         existed_yesterday = self.exists(date - self.trading_day, asset)
         if exists_today and existed_yesterday:
             self.assertEqual(
                 closes.loc[asset, 'close'],
                 self.expected_close(date, asset)
             )
             self.assertEqual(
                 volumes.loc[asset, 'volume'],
                 self.expected_volume(date, asset)
             )
         else:
             self.assertNotIn(asset, closes.index)
             self.assertNotIn(asset, volumes.index)

 def handle_data(context, data):
     results = pipeline_output("test")
     date = get_datetime().normalize()
     for asset in self.assets:
         # Assets should appear iff they exist today and yesterday.
         exists_today = self.exists(date, asset)
         existed_yesterday = self.exists(date - self.trading_day, asset)
         if exists_today and existed_yesterday:
             latest = results.loc[asset, "close"]
             self.assertEqual(latest, self.expected_close(date, asset))
         else:
             self.assertNotIn(asset, results.index)

 def before_trading_start(context, data):
     context.results = pipeline_output("test")
     self.assertTrue(context.results.empty)
     count[0] += 1

 def initialize(context):
     attach_pipeline(Pipeline(), "test")
     pipeline_output("test")
     raise AssertionError("Shouldn't make it past pipeline_output()")

def before_trading_start(context, data):
    context.pipeline_data = pipeline_output('my_pipeline')

 def before_trading_start(context, data):
     trace.append("BTS call")
     pipeline_output('my_pipeline')