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BUG: Use context in lieu of "use_environment" decorator
The "use_environment" decorator is too side-effectful (e.g., connecting to Yahoo! Finance or another data source) to be used as a decorator to a function that gets evaluated during module load. This causes problems, e.g., if Zipline is being used in a gevent environment, when the trading environment created by the decorator argument tries to use greenlets when gevent hasn't been fully initialized. Since the decorator is nothing more than a context-manager wrapper, this commit removes the decorator and replaces its use with contexts, i.e., "with" statements.
This commit is contained in:
Jonathan Kamens
+119
-115
@@ -107,49 +107,51 @@ class TestDividendPerformance(unittest.TestCase):
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)
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self.assertEqual(after.hour, 13)
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@trading.use_environment(trading.TradingEnvironment())
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def test_long_position_receives_dividend(self):
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#post some trades in the market
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events = factory.create_trade_history(
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1,
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[10, 10, 10, 10, 10],
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[100, 100, 100, 100, 100],
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oneday,
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self.sim_params
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)
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with trading.TradingEnvironment():
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#post some trades in the market
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events = factory.create_trade_history(
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1,
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[10, 10, 10, 10, 10],
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[100, 100, 100, 100, 100],
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oneday,
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self.sim_params
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)
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dividend = factory.create_dividend(
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1,
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10.00,
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# declared date, when the algorithm finds out about
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# the dividend
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events[1].dt,
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# ex_date, when the algorithm is credited with the
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# dividend
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events[1].dt,
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# pay date, when the algorithm receives the dividend.
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events[2].dt
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)
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dividend = factory.create_dividend(
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1,
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10.00,
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# declared date, when the algorithm finds out about
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# the dividend
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events[1].dt,
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# ex_date, when the algorithm is credited with the
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# dividend
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events[1].dt,
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# pay date, when the algorithm receives the dividend.
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events[2].dt
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)
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txn = create_txn(events[0], 10.0, 100)
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events.insert(0, txn)
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events.insert(1, dividend)
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results = calculate_results(self, events)
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txn = create_txn(events[0], 10.0, 100)
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events.insert(0, txn)
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events.insert(1, dividend)
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results = calculate_results(self, events)
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self.assertEqual(len(results), 5)
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cumulative_returns = \
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[event['cumulative_perf']['returns'] for event in results]
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self.assertEqual(cumulative_returns, [0.0, 0.0, 0.1, 0.1, 0.1])
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daily_returns = [event['daily_perf']['returns'] for event in results]
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self.assertEqual(daily_returns, [0.0, 0.0, 0.10, 0.0, 0.0])
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cash_flows = [event['daily_perf']['capital_used'] for event in results]
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self.assertEqual(cash_flows, [-1000, 0, 1000, 0, 0])
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cumulative_cash_flows = \
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[event['cumulative_perf']['capital_used'] for event in results]
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self.assertEqual(cumulative_cash_flows, [-1000, -1000, 0, 0, 0])
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cash_pos = \
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[event['cumulative_perf']['ending_cash'] for event in results]
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self.assertEqual(cash_pos, [9000, 9000, 10000, 10000, 10000])
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self.assertEqual(len(results), 5)
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cumulative_returns = \
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[event['cumulative_perf']['returns'] for event in results]
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self.assertEqual(cumulative_returns, [0.0, 0.0, 0.1, 0.1, 0.1])
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daily_returns = [event['daily_perf']['returns']
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for event in results]
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self.assertEqual(daily_returns, [0.0, 0.0, 0.10, 0.0, 0.0])
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cash_flows = [event['daily_perf']['capital_used']
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for event in results]
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self.assertEqual(cash_flows, [-1000, 0, 1000, 0, 0])
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cumulative_cash_flows = \
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[event['cumulative_perf']['capital_used'] for event in results]
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self.assertEqual(cumulative_cash_flows, [-1000, -1000, 0, 0, 0])
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cash_pos = \
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[event['cumulative_perf']['ending_cash'] for event in results]
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self.assertEqual(cash_pos, [9000, 9000, 10000, 10000, 10000])
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def test_post_ex_long_position_receives_no_dividend(self):
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#post some trades in the market
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@@ -1026,92 +1028,94 @@ class TestPerformanceTracker(unittest.TestCase):
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else:
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yield event
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@trading.use_environment(trading.TradingEnvironment())
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def test_minute_tracker(self):
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""" Tests minute performance tracking."""
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start_dt = trading.environment.exchange_dt_in_utc(
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datetime.datetime(2013, 3, 1, 9, 31))
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end_dt = trading.environment.exchange_dt_in_utc(
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datetime.datetime(2013, 3, 1, 16, 0))
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with trading.TradingEnvironment():
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start_dt = trading.environment.exchange_dt_in_utc(
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datetime.datetime(2013, 3, 1, 9, 31))
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end_dt = trading.environment.exchange_dt_in_utc(
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datetime.datetime(2013, 3, 1, 16, 0))
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sim_params = SimulationParameters(
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period_start=start_dt,
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period_end=end_dt,
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emission_rate='minute'
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)
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tracker = perf.PerformanceTracker(sim_params)
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sim_params = SimulationParameters(
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period_start=start_dt,
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period_end=end_dt,
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emission_rate='minute'
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)
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tracker = perf.PerformanceTracker(sim_params)
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foo_event_1 = factory.create_trade('foo', 10.0, 20, start_dt)
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order_event_1 = Order(**{
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'sid': foo_event_1.sid,
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'amount': -25,
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'dt': foo_event_1.dt
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})
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bar_event_1 = factory.create_trade('bar', 100.0, 200, start_dt)
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txn_event_1 = Transaction(sid=foo_event_1.sid,
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amount=-25,
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dt=foo_event_1.dt,
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price=10.0,
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commission=0.50)
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benchmark_event_1 = Event({
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'dt': start_dt,
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'returns': 1.0,
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'type': DATASOURCE_TYPE.BENCHMARK
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})
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foo_event_1 = factory.create_trade('foo', 10.0, 20, start_dt)
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order_event_1 = Order(**{
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'sid': foo_event_1.sid,
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'amount': -25,
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'dt': foo_event_1.dt
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})
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bar_event_1 = factory.create_trade('bar', 100.0, 200, start_dt)
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txn_event_1 = Transaction(sid=foo_event_1.sid,
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amount=-25,
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dt=foo_event_1.dt,
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price=10.0,
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commission=0.50)
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benchmark_event_1 = Event({
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'dt': start_dt,
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'returns': 1.0,
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'type': DATASOURCE_TYPE.BENCHMARK
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})
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foo_event_2 = factory.create_trade(
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'foo', 11.0, 20, start_dt + datetime.timedelta(minutes=1))
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bar_event_2 = factory.create_trade(
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'bar', 11.0, 20, start_dt + datetime.timedelta(minutes=1))
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benchmark_event_2 = Event({
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'dt': start_dt + datetime.timedelta(minutes=1),
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'returns': 2.0,
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'type': DATASOURCE_TYPE.BENCHMARK
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})
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foo_event_2 = factory.create_trade(
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'foo', 11.0, 20, start_dt + datetime.timedelta(minutes=1))
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bar_event_2 = factory.create_trade(
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'bar', 11.0, 20, start_dt + datetime.timedelta(minutes=1))
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benchmark_event_2 = Event({
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'dt': start_dt + datetime.timedelta(minutes=1),
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'returns': 2.0,
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'type': DATASOURCE_TYPE.BENCHMARK
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})
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events = [
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foo_event_1,
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order_event_1,
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benchmark_event_1,
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txn_event_1,
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bar_event_1,
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foo_event_2,
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benchmark_event_2,
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bar_event_2,
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]
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events = [
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foo_event_1,
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order_event_1,
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benchmark_event_1,
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txn_event_1,
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bar_event_1,
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foo_event_2,
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benchmark_event_2,
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bar_event_2,
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]
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grouped_events = itertools.groupby(
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events, operator.attrgetter('dt'))
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grouped_events = itertools.groupby(
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events, operator.attrgetter('dt'))
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messages = {}
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for date, group in grouped_events:
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tracker.set_date(date)
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for event in group:
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tracker.process_event(event)
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tracker.handle_minute_close(date)
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msg = tracker.to_dict()
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messages[date] = msg
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messages = {}
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for date, group in grouped_events:
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tracker.set_date(date)
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for event in group:
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tracker.process_event(event)
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tracker.handle_minute_close(date)
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msg = tracker.to_dict()
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messages[date] = msg
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self.assertEquals(2, len(messages))
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self.assertEquals(2, len(messages))
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msg_1 = messages[foo_event_1.dt]
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msg_2 = messages[foo_event_2.dt]
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msg_1 = messages[foo_event_1.dt]
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msg_2 = messages[foo_event_2.dt]
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self.assertEquals(1, len(msg_1['minute_perf']['transactions']),
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"The first message should contain one transaction.")
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# Check that transactions aren't emitted for previous events.
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self.assertEquals(0, len(msg_2['minute_perf']['transactions']),
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"The second message should have no transactions.")
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self.assertEquals(1, len(msg_1['minute_perf']['transactions']),
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"The first message should contain one "
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"transaction.")
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# Check that transactions aren't emitted for previous events.
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self.assertEquals(0, len(msg_2['minute_perf']['transactions']),
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"The second message should have no "
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"transactions.")
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self.assertEquals(1, len(msg_1['minute_perf']['orders']),
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"The first message should contain one orders.")
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# Check that orders aren't emitted for previous events.
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self.assertEquals(0, len(msg_2['minute_perf']['orders']),
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"The second message should have no orders.")
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self.assertEquals(1, len(msg_1['minute_perf']['orders']),
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"The first message should contain one orders.")
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# Check that orders aren't emitted for previous events.
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self.assertEquals(0, len(msg_2['minute_perf']['orders']),
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"The second message should have no orders.")
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# Ensure that period_close moves through time.
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# Also, ensure that the period_closes are the expected dts.
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self.assertEquals(foo_event_1.dt,
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msg_1['minute_perf']['period_close'])
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self.assertEquals(foo_event_2.dt,
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msg_2['minute_perf']['period_close'])
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# Ensure that period_close moves through time.
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# Also, ensure that the period_closes are the expected dts.
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self.assertEquals(foo_event_1.dt,
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msg_1['minute_perf']['period_close'])
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self.assertEquals(foo_event_2.dt,
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msg_2['minute_perf']['period_close'])
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