From c8304e86013b641e7291e9e4b4195fed09db9079 Mon Sep 17 00:00:00 2001 From: jfkirk Date: Wed, 6 Apr 2016 14:08:06 -0400 Subject: [PATCH] ENH: Adds ExchangeCalendar, TradingSchedule, and implementations Conflicts: tests/data/test_minute_bars.py tests/data/test_us_equity_pricing.py tests/finance/test_slippage.py tests/pipeline/test_engine.py tests/pipeline/test_us_equity_pricing_loader.py tests/serialization_cases.py tests/test_algorithm.py tests/test_assets.py tests/test_bar_data.py tests/test_benchmark.py tests/test_exception_handling.py tests/test_fetcher.py tests/test_finance.py tests/test_history.py tests/test_perf_tracking.py tests/test_security_list.py tests/utils/test_events.py zipline/algorithm.py zipline/data/data_portal.py zipline/data/us_equity_loader.py zipline/errors.py zipline/finance/trading.py zipline/testing/core.py zipline/utils/events.py --- tests/data/test_minute_bars.py | 33 +- tests/data/test_us_equity_pricing.py | 9 +- tests/finance/test_slippage.py | 7 +- tests/pipeline/test_engine.py | 9 +- tests/pipeline/test_pipeline_algo.py | 5 +- tests/resources/calendars/nyse.csv | 6619 +++++++++++++++++ tests/risk/test_risk_cumulative.py | 8 +- tests/risk/test_risk_period.py | 54 +- tests/test_algorithm.py | 59 +- tests/test_assets.py | 3 +- tests/test_bar_data.py | 46 +- tests/test_benchmark.py | 11 +- tests/test_exchange_calendar.py | 301 + tests/test_fetcher.py | 7 +- tests/test_finance.py | 58 +- tests/test_history.py | 59 +- tests/test_perf_tracking.py | 109 +- tests/test_security_list.py | 16 +- tests/test_trading_schedule.py | 58 + tests/test_tradingcalendar.py | 265 - tests/utils/test_events.py | 73 +- zipline/_protocol.pyx | 3 +- zipline/algorithm.py | 31 +- zipline/data/data_portal.py | 40 +- zipline/data/us_equity_loader.py | 6 +- zipline/errors.py | 19 + zipline/finance/performance/tracker.py | 53 +- zipline/finance/risk/cumulative.py | 15 +- zipline/finance/risk/period.py | 33 +- zipline/finance/risk/report.py | 11 +- zipline/finance/risk/risk.py | 14 +- zipline/finance/trading.py | 370 +- zipline/sources/benchmark_source.py | 6 +- zipline/sources/simulated.py | 19 +- zipline/sources/test_source.py | 17 +- zipline/testing/core.py | 61 +- zipline/testing/fixtures.py | 8 +- zipline/utils/calendars/__init__.py | 26 + zipline/utils/calendars/calendar_helpers.py | 199 + zipline/utils/calendars/exchange_calendar.py | 497 ++ .../utils/calendars/nyse_exchange_calendar.py | 522 ++ zipline/utils/calendars/trading_schedule.py | 367 + zipline/utils/cme_exchange_calendar.py | 454 ++ zipline/utils/events.py | 117 +- zipline/utils/factory.py | 140 +- zipline/utils/simfactory.py | 9 + 46 files changed, 9709 insertions(+), 1137 deletions(-) create mode 100644 tests/resources/calendars/nyse.csv create mode 100644 tests/test_exchange_calendar.py create mode 100644 tests/test_trading_schedule.py delete mode 100644 tests/test_tradingcalendar.py create mode 100644 zipline/utils/calendars/__init__.py create mode 100644 zipline/utils/calendars/calendar_helpers.py create mode 100644 zipline/utils/calendars/exchange_calendar.py create mode 100644 zipline/utils/calendars/nyse_exchange_calendar.py create mode 100644 zipline/utils/calendars/trading_schedule.py create mode 100644 zipline/utils/cme_exchange_calendar.py diff --git a/tests/data/test_minute_bars.py b/tests/data/test_minute_bars.py index 8d304e6a..4cf89a50 100644 --- a/tests/data/test_minute_bars.py +++ b/tests/data/test_minute_bars.py @@ -45,8 +45,7 @@ from zipline.data.minute_bars import ( US_EQUITIES_MINUTES_PER_DAY, BcolzMinuteWriterColumnMismatch ) -from zipline.finance.trading import TradingEnvironment - +from zipline.utils.calendars import get_calendar, default_nyse_schedule # Calendar is set to cover several half days, to check a case where half # days would be read out of order in cases of windows which spanned over @@ -59,15 +58,11 @@ class BcolzMinuteBarTestCase(TestCase): @classmethod def setUpClass(cls): - cls.env = TradingEnvironment() - all_market_opens = cls.env.open_and_closes.market_open - all_market_closes = cls.env.open_and_closes.market_close - indexer = all_market_opens.index.slice_indexer( - start=TEST_CALENDAR_START, - end=TEST_CALENDAR_STOP + trading_days = get_calendar('NYSE').trading_days( + TEST_CALENDAR_START, TEST_CALENDAR_STOP ) - cls.market_opens = all_market_opens[indexer] - cls.market_closes = all_market_closes[indexer] + cls.market_opens = trading_days.market_open + cls.market_closes = trading_days.market_close cls.test_calendar_start = cls.market_opens.index[0] cls.test_calendar_stop = cls.market_opens.index[-1] @@ -802,10 +797,12 @@ class BcolzMinuteBarTestCase(TestCase): data = {sids[0]: data_1, sids[1]: data_2} - start_minute_loc = self.env.market_minutes.get_loc(minutes[0]) - minute_locs = [self.env.market_minutes.get_loc(minute) - - start_minute_loc - for minute in minutes] + start_minute_loc = \ + default_nyse_schedule.all_execution_minutes.get_loc(minutes[0]) + minute_locs = [ + default_nyse_schedule.all_execution_minutes.get_loc(minute) \ + - start_minute_loc + for minute in minutes] for i, col in enumerate(columns): for j, sid in enumerate(sids): @@ -824,7 +821,9 @@ class BcolzMinuteBarTestCase(TestCase): 'close': arange(1, 781), 'volume': arange(1, 781) } - dts = array(self.env.minutes_for_days_in_range(start_day, end_day)) + dts = array(default_nyse_schedule.execution_minutes_for_days_in_range( + start_day, end_day + )) self.writer.write_cols(sid, dts, cols) self.assertEqual( @@ -866,7 +865,9 @@ class BcolzMinuteBarTestCase(TestCase): 'close': arange(1, 601), 'volume': arange(1, 601) } - dts = array(self.env.minutes_for_days_in_range(start_day, end_day)) + dts = array(default_nyse_schedule.execution_minutes_for_days_in_range( + start_day, end_day + )) self.writer.write_cols(sid, dts, cols) self.assertEqual( diff --git a/tests/data/test_us_equity_pricing.py b/tests/data/test_us_equity_pricing.py index f3db013f..15e73a78 100644 --- a/tests/data/test_us_equity_pricing.py +++ b/tests/data/test_us_equity_pricing.py @@ -46,6 +46,7 @@ from zipline.testing.fixtures import ( WithBcolzDailyBarReader, ZiplineTestCase, ) +from zipline.utils.calendars import get_calendar TEST_CALENDAR_START = Timestamp('2015-06-01', tz='UTC') TEST_CALENDAR_STOP = Timestamp('2015-06-30', tz='UTC') @@ -96,11 +97,9 @@ class BcolzDailyBarTestCase(WithBcolzDailyBarReader, ZiplineTestCase): @classmethod def init_class_fixtures(cls): super(BcolzDailyBarTestCase, cls).init_class_fixtures() - all_trading_days = cls.env.trading_days - cls.trading_days = all_trading_days[ - all_trading_days.get_loc(TEST_CALENDAR_START): - all_trading_days.get_loc(TEST_CALENDAR_STOP) + 1 - ] + cls.trading_days = get_calendar('NYSE').trading_days( + TEST_CALENDAR_START, TEST_CALENDAR_STOP + ).index @property def assets(self): diff --git a/tests/finance/test_slippage.py b/tests/finance/test_slippage.py index 50029dc0..4c7778ea 100644 --- a/tests/finance/test_slippage.py +++ b/tests/finance/test_slippage.py @@ -38,6 +38,7 @@ from zipline.testing.fixtures import ( WithSimParams, ZiplineTestCase, ) +from zipline.utils.calendars import default_nyse_schedule class SlippageTestCase(WithSimParams, WithDataPortal, ZiplineTestCase): @@ -93,7 +94,7 @@ class SlippageTestCase(WithSimParams, WithDataPortal, ZiplineTestCase): ) with tmp_bcolz_minute_bar_reader(self.env, days, assets) as reader: data_portal = DataPortal( - self.env, + self.env, default_nyse_schedule, first_trading_day=reader.first_trading_day, equity_minute_reader=reader, ) @@ -482,8 +483,12 @@ class SlippageTestCase(WithSimParams, WithDataPortal, ZiplineTestCase): ) with tmp_bcolz_minute_bar_reader(self.env, days, assets) as reader: data_portal = DataPortal( +<<<<<<< HEAD self.env, first_trading_day=reader.first_trading_day, +======= + self.env, default_nyse_schedule, +>>>>>>> ENH: Adds ExchangeCalendar, TradingSchedule, and implementations equity_minute_reader=reader, ) diff --git a/tests/pipeline/test_engine.py b/tests/pipeline/test_engine.py index 7f748650..cd89387a 100644 --- a/tests/pipeline/test_engine.py +++ b/tests/pipeline/test_engine.py @@ -85,6 +85,7 @@ from zipline.testing.fixtures import ( ZiplineTestCase, ) from zipline.utils.memoize import lazyval +from zipline.utils.calendars import default_nyse_schedule class RollingSumDifference(CustomFactor): @@ -826,7 +827,7 @@ class FrameInputTestCase(WithTradingEnvironment, ZiplineTestCase): cls.dates = date_range( cls.start, cls.end, - freq=cls.env.trading_day, + freq=default_nyse_schedule.day, tz='UTC', ) cls.assets = cls.asset_finder.retrieve_all(cls.asset_ids) @@ -985,7 +986,7 @@ class SyntheticBcolzTestCase(WithAdjustmentReader, def test_SMA(self): engine = SimplePipelineEngine( lambda column: self.pipeline_loader, - self.env.trading_days, + default_nyse_schedule.all_execution_days, self.asset_finder, ) window_length = 5 @@ -1039,7 +1040,7 @@ class SyntheticBcolzTestCase(WithAdjustmentReader, # valuable. engine = SimplePipelineEngine( lambda column: self.pipeline_loader, - self.env.trading_days, + default_nyse_schedule.all_execution_days, self.asset_finder, ) window_length = 5 @@ -1083,7 +1084,7 @@ class ParameterizedFactorTestCase(WithTradingEnvironment, ZiplineTestCase): @classmethod def init_class_fixtures(cls): super(ParameterizedFactorTestCase, cls).init_class_fixtures() - day = cls.env.trading_day + day = default_nyse_schedule.day cls.dates = dates = date_range( '2015-02-01', diff --git a/tests/pipeline/test_pipeline_algo.py b/tests/pipeline/test_pipeline_algo.py index c0b5de80..15aac672 100644 --- a/tests/pipeline/test_pipeline_algo.py +++ b/tests/pipeline/test_pipeline_algo.py @@ -60,7 +60,7 @@ from zipline.testing.fixtures import ( WithDataPortal, ZiplineTestCase, ) -from zipline.utils.tradingcalendar import trading_day +from zipline.utils.calendars import default_nyse_schedule TEST_RESOURCE_PATH = join( @@ -70,6 +70,9 @@ TEST_RESOURCE_PATH = join( ) +trading_day = default_nyse_schedule.day + + def rolling_vwap(df, length): "Simple rolling vwap implementation for testing" closes = df['close'].values diff --git a/tests/resources/calendars/nyse.csv b/tests/resources/calendars/nyse.csv new file mode 100644 index 00000000..dce0c3a8 --- /dev/null +++ b/tests/resources/calendars/nyse.csv @@ -0,0 +1,6619 @@ +,market_open,market_close +1990-01-02 00:00:00+00:00,1990-01-02 14:31:00+00:00,1990-01-02 21:00:00+00:00 +1990-01-03 00:00:00+00:00,1990-01-03 14:31:00+00:00,1990-01-03 21:00:00+00:00 +1990-01-04 00:00:00+00:00,1990-01-04 14:31:00+00:00,1990-01-04 21:00:00+00:00 +1990-01-05 00:00:00+00:00,1990-01-05 14:31:00+00:00,1990-01-05 21:00:00+00:00 +1990-01-08 00:00:00+00:00,1990-01-08 14:31:00+00:00,1990-01-08 21:00:00+00:00 +1990-01-09 00:00:00+00:00,1990-01-09 14:31:00+00:00,1990-01-09 21:00:00+00:00 +1990-01-10 00:00:00+00:00,1990-01-10 14:31:00+00:00,1990-01-10 21:00:00+00:00 +1990-01-11 00:00:00+00:00,1990-01-11 14:31:00+00:00,1990-01-11 21:00:00+00:00 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a/tests/risk/test_risk_cumulative.py +++ b/tests/risk/test_risk_cumulative.py @@ -22,7 +22,7 @@ import zipline.finance.risk as risk from zipline.utils import factory from zipline.finance.trading import SimulationParameters, TradingEnvironment - +from zipline.utils.calendars import default_nyse_schedule from . import answer_key ANSWER_KEY = answer_key.ANSWER_KEY @@ -51,7 +51,7 @@ class TestRisk(unittest.TestCase): self.sim_params = SimulationParameters( period_start=start_date, period_end=end_date, - env=self.env, + trading_schedule=default_nyse_schedule, ) self.algo_returns_06 = factory.create_returns_from_list( @@ -60,7 +60,9 @@ class TestRisk(unittest.TestCase): ) self.cumulative_metrics_06 = risk.RiskMetricsCumulative( - self.sim_params, env=self.env + self.sim_params, + treasury_curves=self.env.treasury_curves, + trading_schedule=default_nyse_schedule, ) for dt, returns in answer_key.RETURNS_DATA.iterrows(): diff --git a/tests/risk/test_risk_period.py b/tests/risk/test_risk_period.py index 37fcdce4..62881b94 100644 --- a/tests/risk/test_risk_period.py +++ b/tests/risk/test_risk_period.py @@ -26,7 +26,7 @@ import zipline.finance.risk as risk from zipline.utils import factory from zipline.finance.trading import SimulationParameters, TradingEnvironment - +from zipline.utils.calendars import default_nyse_schedule from . import answer_key from . answer_key import AnswerKey @@ -60,7 +60,7 @@ class TestRisk(unittest.TestCase): self.sim_params = SimulationParameters( period_start=start_date, period_end=end_date, - env=self.env, + trading_schedule=default_nyse_schedule, ) self.algo_returns_06 = factory.create_returns_from_list( @@ -75,7 +75,8 @@ class TestRisk(unittest.TestCase): self.algo_returns_06, self.sim_params, benchmark_returns=self.benchmark_returns_06, - env=self.env, + trading_schedule=default_nyse_schedule, + treasury_curves=self.env.treasury_curves, ) start_08 = datetime.datetime( @@ -95,7 +96,7 @@ class TestRisk(unittest.TestCase): self.sim_params08 = SimulationParameters( period_start=start_08, period_end=end_08, - env=self.env, + trading_schedule=default_nyse_schedule, ) def tearDown(self): @@ -116,8 +117,9 @@ class TestRisk(unittest.TestCase): returns.index[0], returns.index[-1], returns, - env=self.env, + trading_schedule=default_nyse_schedule, benchmark_returns=self.env.benchmark_returns, + treasury_curves=self.env.treasury_curves, ) self.assertEqual(metrics.max_drawdown, 0.505) @@ -142,7 +144,10 @@ class TestRisk(unittest.TestCase): def test_trading_days_06(self): returns = factory.create_returns_from_range(self.sim_params) - metrics = risk.RiskReport(returns, self.sim_params, env=self.env) + metrics = risk.RiskReport(returns, self.sim_params, + trading_schedule=default_nyse_schedule, + treasury_curves=self.env.treasury_curves, + benchmark_returns=self.env.benchmark_returns) self.assertEqual([x.num_trading_days for x in metrics.year_periods], [251]) self.assertEqual([x.num_trading_days for x in metrics.month_periods], @@ -366,7 +371,10 @@ class TestRisk(unittest.TestCase): def test_benchmark_returns_08(self): returns = factory.create_returns_from_range(self.sim_params08) - metrics = risk.RiskReport(returns, self.sim_params08, env=self.env) + metrics = risk.RiskReport(returns, self.sim_params08, + trading_schedule=default_nyse_schedule, + treasury_curves=self.env.treasury_curves, + benchmark_returns=self.env.benchmark_returns) self.assertEqual([round(x.benchmark_period_returns, 3) for x in metrics.month_periods], @@ -412,7 +420,10 @@ class TestRisk(unittest.TestCase): def test_trading_days_08(self): returns = factory.create_returns_from_range(self.sim_params08) - metrics = risk.RiskReport(returns, self.sim_params08, env=self.env) + metrics = risk.RiskReport(returns, self.sim_params08, + trading_schedule=default_nyse_schedule, + treasury_curves=self.env.treasury_curves, + benchmark_returns=self.env.benchmark_returns) self.assertEqual([x.num_trading_days for x in metrics.year_periods], [253]) @@ -421,7 +432,10 @@ class TestRisk(unittest.TestCase): def test_benchmark_volatility_08(self): returns = factory.create_returns_from_range(self.sim_params08) - metrics = risk.RiskReport(returns, self.sim_params08, env=self.env) + metrics = risk.RiskReport(returns, self.sim_params08, + trading_schedule=default_nyse_schedule, + treasury_curves=self.env.treasury_curves, + benchmark_returns=self.env.benchmark_returns) self.assertEqual([round(x.benchmark_volatility, 3) for x in metrics.month_periods], @@ -469,7 +483,10 @@ class TestRisk(unittest.TestCase): def test_treasury_returns_06(self): returns = factory.create_returns_from_range(self.sim_params) - metrics = risk.RiskReport(returns, self.sim_params, env=self.env) + metrics = risk.RiskReport(returns, self.sim_params, + trading_schedule=default_nyse_schedule, + treasury_curves=self.env.treasury_curves, + benchmark_returns=self.env.benchmark_returns) self.assertEqual([round(x.treasury_period_return, 4) for x in metrics.month_periods], [0.0037, @@ -533,12 +550,15 @@ class TestRisk(unittest.TestCase): sim_params90s = SimulationParameters( period_start=start, period_end=end, - env=self.env, + trading_schedule=default_nyse_schedule, ) returns = factory.create_returns_from_range(sim_params90s) returns = returns[:-10] # truncate the returns series to end mid-month - metrics = risk.RiskReport(returns, sim_params90s, env=self.env) + metrics = risk.RiskReport(returns, sim_params90s, + trading_schedule=default_nyse_schedule, + treasury_curves=self.env.treasury_curves, + benchmark_returns=self.env.benchmark_returns) total_months = 60 self.check_metrics(metrics, total_months, start) @@ -546,10 +566,13 @@ class TestRisk(unittest.TestCase): sim_params = SimulationParameters( period_start=start_date, period_end=start_date.replace(year=(start_date.year + years)), - env=self.env, + trading_schedule=default_nyse_schedule, ) returns = factory.create_returns_from_range(sim_params) - metrics = risk.RiskReport(returns, self.sim_params, env=self.env) + metrics = risk.RiskReport(returns, self.sim_params, + trading_schedule=default_nyse_schedule, + treasury_curves=self.env.treasury_curves, + benchmark_returns=self.env.benchmark_returns) total_months = years * 12 self.check_metrics(metrics, total_months, start_date) @@ -636,7 +659,8 @@ class TestRisk(unittest.TestCase): self.algo_returns_06, self.sim_params, benchmark_returns=benchmark_returns, - env=self.env, + trading_schedule=default_nyse_schedule, + treasury_curves=self.env.treasury_curves, ) for risk_period in chain.from_iterable(itervalues(report.to_dict())): self.assertIsNone(risk_period['beta']) diff --git a/tests/test_algorithm.py b/tests/test_algorithm.py index 73d4308c..12bb2da6 100644 --- a/tests/test_algorithm.py +++ b/tests/test_algorithm.py @@ -166,7 +166,7 @@ from zipline.utils.control_flow import nullctx import zipline.utils.events from zipline.utils.events import date_rules, time_rules, Always import zipline.utils.factory as factory -from zipline.utils.tradingcalendar import trading_day, trading_days +from zipline.utils.calendars import default_nyse_schedule # Because test cases appear to reuse some resources. @@ -826,7 +826,7 @@ def before_trading_start(context, data): self.sim_params.data_frequency = 'daily' sim_params = factory.create_simulation_parameters( - num_days=4, env=self.env, data_frequency='daily') + num_days=4, data_frequency='daily') algo = TestRegisterTransformAlgorithm( sim_params=sim_params, @@ -835,7 +835,7 @@ def before_trading_start(context, data): self.assertEqual(algo.sim_params.data_frequency, 'daily') sim_params = factory.create_simulation_parameters( - num_days=4, env=self.env, data_frequency='minute') + num_days=4, data_frequency='minute') algo = TestRegisterTransformAlgorithm( sim_params=sim_params, @@ -953,7 +953,7 @@ def before_trading_start(context, data): period_end=period_end, capital_base=float("1.0e5"), data_frequency='minute', - env=env + trading_schedule=default_nyse_schedule, ) data_portal = create_data_portal( @@ -961,6 +961,7 @@ def before_trading_start(context, data): tempdir, sim_params, equities.index, + default_nyse_schedule, ) algo = algo_class(sim_params=sim_params, env=env) algo.run(data_portal) @@ -1551,9 +1552,10 @@ def handle_data(context, data): env=self.env, ) trades = factory.create_daily_trade_source( - [0], self.sim_params, self.env) + [0], self.sim_params, self.env, default_nyse_schedule) data_portal = create_data_portal_from_trade_history( - self.env, tempdir, self.sim_params, {0: trades}) + self.env, default_nyse_schedule, tempdir, self.sim_params, + {0: trades}) results = test_algo.run(data_portal) all_txns = [ @@ -1640,7 +1642,7 @@ def handle_data(context, data): params = SimulationParameters( period_start=pd.Timestamp("2007-01-03", tz='UTC'), period_end=pd.Timestamp("2007-01-05", tz='UTC'), - env=self.env + trading_schedule=default_nyse_schedule, ) # order method shouldn't blow up @@ -2719,7 +2721,6 @@ class TestTradingControls(WithSimParams, WithDataPortal, ZiplineTestCase): sim_params = factory.create_simulation_parameters( start=start, num_days=4, - env=env, data_frequency='minute', ) @@ -2727,7 +2728,8 @@ class TestTradingControls(WithSimParams, WithDataPortal, ZiplineTestCase): env, tempdir, sim_params, - [1] + [1], + default_nyse_schedule, ) def handle_data(algo, data): @@ -2848,7 +2850,8 @@ class TestTradingControls(WithSimParams, WithDataPortal, ZiplineTestCase): env, tempdir, self.sim_params, - [0] + [0], + default_nyse_schedule, ) algo.run(data_portal) @@ -2862,7 +2865,8 @@ class TestTradingControls(WithSimParams, WithDataPortal, ZiplineTestCase): env, tempdir, self.sim_params, - [0] + [0], + default_nyse_schedule, ) algo = SetAssetDateBoundsAlgorithm( sim_params=self.sim_params, @@ -2881,7 +2885,8 @@ class TestTradingControls(WithSimParams, WithDataPortal, ZiplineTestCase): env, tempdir, self.sim_params, - [0] + [0], + default_nyse_schedule, ) algo = SetAssetDateBoundsAlgorithm( sim_params=self.sim_params, @@ -2907,7 +2912,7 @@ class TestAccountControls(WithDataPortal, WithSimParams, ZiplineTestCase): [100, 100, 100, 300], timedelta(days=1), cls.sim_params, - cls.env, + default_nyse_schedule, ), }, index=cls.sim_params.trading_days, @@ -3054,7 +3059,7 @@ class TestFutureFlip(WithSimParams, WithDataPortal, ZiplineTestCase): [1e9, 1e9, 1e9], timedelta(days=1), cls.sim_params, - cls.env + default_nyse_schedule, ), }, index=cls.sim_params.trading_days, @@ -3064,7 +3069,7 @@ class TestFutureFlip(WithSimParams, WithDataPortal, ZiplineTestCase): def test_flip_algo(self): metadata = {1: {'symbol': 'TEST', 'start_date': self.sim_params.trading_days[0], - 'end_date': self.env.next_trading_day( + 'end_date': default_nyse_schedule.next_execution_day( self.sim_params.trading_days[-1]), 'multiplier': 5}} @@ -3206,7 +3211,7 @@ class TestOrderCancelation(WithDataPortal, sim_params=SimulationParameters( period_start=self.sim_params.period_start, period_end=self.sim_params.period_end, - env=self.env, + trading_schedule=self.env, data_frequency=data_frequency, emission_rate='minute' if minute_emission else 'daily' ) @@ -3419,8 +3424,12 @@ class TestEquityAutoClose(WithTmpDir, ZiplineTestCase): sids = asset_info.index env = self.enter_instance_context(tmp_trading_env(equities=asset_info)) - market_opens = env.open_and_closes.market_open.loc[self.test_days] - market_closes = env.open_and_closes.market_close.loc[self.test_days] + market_opens = default_nyse_schedule.schedule.market_open.loc[ + self.test_days + ] + market_closes = default_nyse_schedule.schedule.market_close.loc[ + self.test_days + ] if frequency == 'daily': dates = self.test_days @@ -3441,12 +3450,12 @@ class TestEquityAutoClose(WithTmpDir, ZiplineTestCase): ) reader = BcolzDailyBarReader(path) data_portal = DataPortal( - env, + env, default_nyse_schedule, first_trading_day=reader.first_trading_day, equity_daily_reader=reader, ) elif frequency == 'minute': - dates = env.minutes_for_days_in_range( + dates = default_nyse_schedule.execution_minutes_for_days_in_range( self.test_days[0], self.test_days[-1], ) @@ -3471,7 +3480,7 @@ class TestEquityAutoClose(WithTmpDir, ZiplineTestCase): ) reader = BcolzMinuteBarReader(self.tmpdir.path) data_portal = DataPortal( - env, + env, default_nyse_schedule, first_trading_day=reader.first_trading_day, equity_minute_reader=reader, ) @@ -3485,7 +3494,6 @@ class TestEquityAutoClose(WithTmpDir, ZiplineTestCase): end=self.test_days[-1], data_frequency=frequency, emission_rate=frequency, - env=env, capital_base=capital_base, ) @@ -3498,7 +3506,7 @@ class TestEquityAutoClose(WithTmpDir, ZiplineTestCase): else: final_prices = { asset.sid: trade_data_by_sid[asset.sid].loc[ - env.get_open_and_close(asset.end_date)[1] + default_nyse_schedule.start_and_end(asset.end_date)[1] ].close for asset in assets } @@ -3852,6 +3860,9 @@ class TestEquityAutoClose(WithTmpDir, ZiplineTestCase): expected_cash.extend([after_second_auto_close] * (390 + 390)) expected_position_counts.extend([1] * (390 + 390)) + # Check list lengths first to avoid expensive comparison + self.assertEqual(len(algo.cash), len(expected_cash)) + # TODO find more efficient way to compare these lists self.assertEqual(algo.cash, expected_cash) self.assertEqual( list(output['ending_cash']), @@ -3987,7 +3998,7 @@ class TestOrderAfterDelist(WithTradingEnvironment, ZiplineTestCase): sim_params=SimulationParameters( period_start=pd.Timestamp("2016-01-06", tz='UTC'), period_end=pd.Timestamp("2016-01-07", tz='UTC'), - env=self.env, + trading_schedule=default_nyse_schedule, data_frequency="minute" ) ) diff --git a/tests/test_assets.py b/tests/test_assets.py index 70be6ab7..de1409c1 100644 --- a/tests/test_assets.py +++ b/tests/test_assets.py @@ -83,7 +83,7 @@ from zipline.testing.fixtures import ( WithAssetFinder, ZiplineTestCase, ) -from zipline.utils.tradingcalendar import trading_day +from zipline.utils.calendars import default_nyse_schedule @contextmanager @@ -776,6 +776,7 @@ class AssetFinderTestCase(ZiplineTestCase): def test_compute_lifetimes(self): num_assets = 4 + trading_day = default_nyse_schedule.day first_start = pd.Timestamp('2015-04-01', tz='UTC') frame = make_rotating_equity_info( diff --git a/tests/test_bar_data.py b/tests/test_bar_data.py index 761530ff..a97da758 100644 --- a/tests/test_bar_data.py +++ b/tests/test_bar_data.py @@ -28,6 +28,7 @@ from zipline.testing.fixtures import ( WithDataPortal, ZiplineTestCase, ) +from zipline.utils.calendars import default_nyse_schedule OHLC = ["open", "high", "low", "close"] OHLCP = OHLC + ["price"] @@ -165,8 +166,10 @@ class TestMinuteBarData(WithBarDataChecks, def test_minute_before_assets_trading(self): # grab minutes that include the day before the asset start - minutes = self.env.market_minutes_for_day( - self.env.previous_trading_day(self.bcolz_minute_bar_days[0]) + minutes = self.trading_schedule.execution_minutes_for_day( + self.trading_schedule.previous_execution_day( + self.bcolz_minute_bar_days[0] + ) ) # this entire day is before either asset has started trading @@ -192,8 +195,8 @@ class TestMinuteBarData(WithBarDataChecks, self.assertTrue(asset_value is pd.NaT) def test_regular_minute(self): - minutes = self.env.market_minutes_for_day( - self.bcolz_minute_bar_days[0], + minutes = self.trading_schedule.execution_minutes_for_day( + self.bcolz_minute_bar_days[0] ) for idx, minute in enumerate(minutes): @@ -284,7 +287,7 @@ class TestMinuteBarData(WithBarDataChecks, asset2_value) def test_minute_of_last_day(self): - minutes = self.env.market_minutes_for_day( + minutes = self.trading_schedule.execution_minutes_for_day( self.bcolz_daily_bar_days[-1], ) @@ -296,12 +299,15 @@ class TestMinuteBarData(WithBarDataChecks, self.assertTrue(bar_data.can_trade(self.ASSET2)) def test_minute_after_assets_stopped(self): - minutes = self.env.market_minutes_for_day( - self.env.next_trading_day(self.bcolz_minute_bar_days[-1]) + minutes = self.trading_schedule.execution_minutes_for_day( + self.trading_schedule.next_execution_day( + self.bcolz_minute_bar_days[-1] + ) ) - last_trading_minute = \ - self.env.market_minutes_for_day(self.bcolz_minute_bar_days[-1])[-1] + last_trading_minute = self.trading_schedule.execution_minutes_for_day( + self.bcolz_minute_bar_days[-1] + )[-1] # this entire day is after both assets have stopped trading for idx, minute in enumerate(minutes): @@ -341,9 +347,9 @@ class TestMinuteBarData(WithBarDataChecks, ) # ... but that's it's not applied when using spot value - minutes = self.env.minutes_for_days_in_range( + minutes = self.trading_schedule.execution_minutes_for_days_in_range( start=self.bcolz_minute_bar_days[0], - end=self.bcolz_minute_bar_days[1], + end=self.bcolz_minute_bar_days[1] ) for idx, minute in enumerate(minutes): @@ -356,11 +362,11 @@ class TestMinuteBarData(WithBarDataChecks, def test_spot_price_is_adjusted_if_needed(self): # on cls.days[1], the first 9 minutes of ILLIQUID_SPLIT_ASSET are # missing. let's get them. - day0_minutes = self.env.market_minutes_for_day( - self.bcolz_minute_bar_days[0], + day0_minutes = self.trading_schedule.execution_minutes_for_day( + self.bcolz_minute_bar_days[0] ) - day1_minutes = self.env.market_minutes_for_day( - self.bcolz_minute_bar_days[1], + day1_minutes = self.trading_schedule.execution_minutes_for_day( + self.bcolz_minute_bar_days[1] ) for idx, minute in enumerate(day0_minutes[-10:-1]): @@ -604,7 +610,7 @@ class TestDailyBarData(WithBarDataChecks, def make_daily_bar_data(cls): for sid in cls.sids: yield sid, create_daily_df_for_asset( - cls.env, + default_nyse_schedule, cls.bcolz_daily_bar_days[0], cls.bcolz_daily_bar_days[-1], interval=2 - sid % 2 @@ -638,7 +644,9 @@ class TestDailyBarData(WithBarDataChecks, def test_day_before_assets_trading(self): # use the day before self.bcolz_daily_bar_days[0] - day = self.env.previous_trading_day(self.bcolz_daily_bar_days[0]) + day = self.trading_schedule.previous_execution_day( + self.bcolz_daily_bar_days[0] + ) bar_data = BarData(self.data_portal, lambda: day, "daily") self.check_internal_consistency(bar_data) @@ -741,7 +749,9 @@ class TestDailyBarData(WithBarDataChecks, def test_after_assets_dead(self): # both assets end on self.day[-1], so let's try the next day - next_day = self.env.next_trading_day(self.bcolz_daily_bar_days[-1]) + next_day = self.trading_schedule.next_execution_day( + self.bcolz_daily_bar_days[-1] + ) bar_data = BarData(self.data_portal, lambda: next_day, "daily") self.check_internal_consistency(bar_data) diff --git a/tests/test_benchmark.py b/tests/test_benchmark.py index 11b611e6..e39e2535 100644 --- a/tests/test_benchmark.py +++ b/tests/test_benchmark.py @@ -32,6 +32,7 @@ from zipline.testing.fixtures import ( WithSimParams, ZiplineTestCase, ) +from zipline.utils.calendars import default_nyse_schedule class TestBenchmark(WithDataPortal, WithSimParams, ZiplineTestCase): @@ -85,7 +86,7 @@ class TestBenchmark(WithDataPortal, WithSimParams, ZiplineTestCase): days_to_use = self.sim_params.trading_days[1:] source = BenchmarkSource( - 1, self.env, days_to_use, self.data_portal + 1, self.env, default_nyse_schedule, days_to_use, self.data_portal ) # should be the equivalent of getting the price history, then doing @@ -111,6 +112,7 @@ class TestBenchmark(WithDataPortal, WithSimParams, ZiplineTestCase): BenchmarkSource( 3, self.env, + default_nyse_schedule, self.sim_params.trading_days[1:], self.data_portal ) @@ -125,6 +127,7 @@ class TestBenchmark(WithDataPortal, WithSimParams, ZiplineTestCase): BenchmarkSource( 3, self.env, + default_nyse_schedule, self.sim_params.trading_days[120:], self.data_portal ) @@ -138,7 +141,7 @@ class TestBenchmark(WithDataPortal, WithSimParams, ZiplineTestCase): def test_asset_IPOed_same_day(self): # gotta get some minute data up in here. # add sid 4 for a couple of days - minutes = self.env.minutes_for_days_in_range( + minutes = default_nyse_schedule.execution_minutes_for_days_in_range( self.sim_params.trading_days[0], self.sim_params.trading_days[5] ) @@ -160,6 +163,7 @@ class TestBenchmark(WithDataPortal, WithSimParams, ZiplineTestCase): source = BenchmarkSource( 2, self.env, + default_nyse_schedule, self.sim_params.trading_days, data_portal ) @@ -188,7 +192,8 @@ class TestBenchmark(WithDataPortal, WithSimParams, ZiplineTestCase): with self.assertRaises(InvalidBenchmarkAsset) as exc: BenchmarkSource( - 4, self.env, self.sim_params.trading_days, self.data_portal + 4, self.env, default_nyse_schedule, + self.sim_params.trading_days, self.data_portal ) self.assertEqual("4 cannot be used as the benchmark because it has a " diff --git a/tests/test_exchange_calendar.py b/tests/test_exchange_calendar.py new file mode 100644 index 00000000..80521beb --- /dev/null +++ b/tests/test_exchange_calendar.py @@ -0,0 +1,301 @@ +# +# Copyright 2016 Quantopian, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from os.path import ( + abspath, + dirname, + join, +) +from unittest import TestCase + +import pandas as pd +import pytz +from pandas import ( + read_csv, + datetime, + Timestamp, + Timedelta, + date_range, +) +from pandas.util.testing import assert_frame_equal + +from zipline.utils.calendars.nyse_exchange_calendar import NYSEExchangeCalendar + + +class ExchangeCalendarTestBase(object): + + # Override in subclasses. + answer_key_filename = None + calendar_class = None + + @staticmethod + def load_answer_key(filename): + """ + Load a CSV from tests/resources/calendars/{filename}.csv + """ + fullpath = join( + dirname(abspath(__file__)), + 'resources', + 'calendars', + filename + '.csv', + ) + return read_csv( + fullpath, + index_col=0, + # NOTE: Merely passing parse_dates=True doesn't cause pandas to set + # the dtype correctly, and passing all reasonable inputs to the + # dtype kwarg cause read_csv to barf. + parse_dates=[0, 1, 2], + ).tz_localize('UTC') + + @classmethod + def setupClass(cls): + cls.answers = cls.load_answer_key(cls.answer_key_filename) + cls.start_date = cls.answers.index[0] + cls.end_date = cls.answers.index[-1] + cls.calendar = cls.calendar_class(cls.start_date, cls.end_date) + + def test_calculated_against_csv(self): + assert_frame_equal(self.calendar.schedule, self.answers) + + def test_is_open_on_minute(self): + for market_minute in self.answers.market_open: + market_minute_utc = market_minute.tz_localize('UTC') + # The exchange should be classified as open on its first minute + self.assertTrue( + self.calendar.is_open_on_minute(market_minute_utc) + ) + # Decrement minute by one, to minute where the market was not open + pre_market = market_minute_utc - pd.Timedelta(minutes=1) + self.assertFalse( + self.calendar.is_open_on_minute(pre_market) + ) + + def test_open_and_close(self): + for index, row in self.answers.iterrows(): + o_and_c = self.calendar.open_and_close(index) + self.assertEqual(o_and_c[0], + row['market_open'].tz_localize('UTC')) + self.assertEqual(o_and_c[1], + row['market_close'].tz_localize('UTC')) + + def test_no_nones_from_open_and_close(self): + """ + Ensures that, for all minutes in a week, the open_and_close method + never returns a tuple of Nones. + """ + start_week = Timestamp('11/18/2012 12:00AM', tz='EST') + end_week = start_week + Timedelta(days=7) + minutes_in_week = date_range(start_week, end_week, freq='Min') + + for dt in minutes_in_week: + open, close = self.calendar.open_and_close(dt) + self.assertIsNotNone(open, "Open value is None") + self.assertIsNotNone(close, "Close value is None") + + # def test_minutes_for_date(self): + # for date in self.answers.index: + # mins_for_date = self.calendar.minutes_for_date(date) + + def test_minute_window(self): + for open in self.answers.market_open: + open_tz = open.tz_localize('UTC') + window = self.calendar.minute_window(open_tz, 390, 1) + self.assertEqual(len(window), 390) + + +class NYSECalendarTestCase(ExchangeCalendarTestBase, TestCase): + + answer_key_filename = 'nyse' + calendar_class = NYSEExchangeCalendar + + def test_newyears(self): + """ + Check whether tradingcalendar contains certain dates. + """ + # January 2012 + # Su Mo Tu We Th Fr Sa + # 1 2 3 4 5 6 7 + # 8 9 10 11 12 13 14 + # 15 16 17 18 19 20 21 + # 22 23 24 25 26 27 28 + # 29 30 31 + + start_dt = Timestamp('1/1/12', tz='UTC') + end_dt = Timestamp('12/31/13', tz='UTC') + trading_days = self.calendar.trading_days(start=start_dt, + end=end_dt) + + day_after_new_years_sunday = datetime( + 2012, 1, 2, tzinfo=pytz.utc) + + self.assertNotIn(day_after_new_years_sunday, + trading_days.index, + """ + If NYE falls on a weekend, {0} the Monday after is a holiday. + """.strip().format(day_after_new_years_sunday) + ) + + first_trading_day_after_new_years_sunday = datetime( + 2012, 1, 3, tzinfo=pytz.utc) + + self.assertIn(first_trading_day_after_new_years_sunday, + trading_days.index, + """ + If NYE falls on a weekend, {0} the Tuesday after is the first trading day. + """.strip().format(first_trading_day_after_new_years_sunday) + ) + + # January 2013 + # Su Mo Tu We Th Fr Sa + # 1 2 3 4 5 + # 6 7 8 9 10 11 12 + # 13 14 15 16 17 18 19 + # 20 21 22 23 24 25 26 + # 27 28 29 30 31 + + new_years_day = datetime( + 2013, 1, 1, tzinfo=pytz.utc) + + self.assertNotIn(new_years_day, + trading_days.index, + """ + If NYE falls during the week, e.g. {0}, it is a holiday. + """.strip().format(new_years_day) + ) + + first_trading_day_after_new_years = datetime( + 2013, 1, 2, tzinfo=pytz.utc) + + self.assertIn(first_trading_day_after_new_years, + trading_days.index, + """ + If the day after NYE falls during the week, {0} \ + is the first trading day. + """.strip().format(first_trading_day_after_new_years) + ) + + def test_thanksgiving(self): + """ + Check tradingcalendar Thanksgiving dates. + """ + # November 2005 + # Su Mo Tu We Th Fr Sa + # 1 2 3 4 5 + # 6 7 8 9 10 11 12 + # 13 14 15 16 17 18 19 + # 20 21 22 23 24 25 26 + # 27 28 29 30 + + start_dt = Timestamp('1/1/05', tz='UTC') + end_dt = Timestamp('12/31/12', tz='UTC') + trading_days = self.calendar.trading_days(start=start_dt, + end=end_dt) + + thanksgiving_with_four_weeks = datetime( + 2005, 11, 24, tzinfo=pytz.utc) + + self.assertNotIn(thanksgiving_with_four_weeks, + trading_days.index, + """ + If Nov has 4 Thursdays, {0} Thanksgiving is the last Thursady. + """.strip().format(thanksgiving_with_four_weeks) + ) + + # November 2006 + # Su Mo Tu We Th Fr Sa + # 1 2 3 4 + # 5 6 7 8 9 10 11 + # 12 13 14 15 16 17 18 + # 19 20 21 22 23 24 25 + # 26 27 28 29 30 + thanksgiving_with_five_weeks = datetime( + 2006, 11, 23, tzinfo=pytz.utc) + + self.assertNotIn(thanksgiving_with_five_weeks, + trading_days.index, + """ + If Nov has 5 Thursdays, {0} Thanksgiving is not the last week. + """.strip().format(thanksgiving_with_five_weeks) + ) + + first_trading_day_after_new_years_sunday = datetime( + 2012, 1, 3, tzinfo=pytz.utc) + + self.assertIn(first_trading_day_after_new_years_sunday, + trading_days.index, + """ + If NYE falls on a weekend, {0} the Tuesday after is the first trading day. + """.strip().format(first_trading_day_after_new_years_sunday) + ) + + def test_day_after_thanksgiving(self): + # November 2012 + # Su Mo Tu We Th Fr Sa + # 1 2 3 + # 4 5 6 7 8 9 10 + # 11 12 13 14 15 16 17 + # 18 19 20 21 22 23 24 + # 25 26 27 28 29 30 + fourth_friday_open = Timestamp('11/23/2012 11:00AM', tz='EST') + fourth_friday = Timestamp('11/23/2012 3:00PM', tz='EST') + self.assertTrue(self.calendar.is_open_on_minute(fourth_friday_open)) + self.assertFalse(self.calendar.is_open_on_minute(fourth_friday)) + + # November 2013 + # Su Mo Tu We Th Fr Sa + # 1 2 + # 3 4 5 6 7 8 9 + # 10 11 12 13 14 15 16 + # 17 18 19 20 21 22 23 + # 24 25 26 27 28 29 30 + fifth_friday_open = Timestamp('11/29/2013 11:00AM', tz='EST') + fifth_friday = Timestamp('11/29/2013 3:00PM', tz='EST') + self.assertTrue(self.calendar.is_open_on_minute(fifth_friday_open)) + self.assertFalse(self.calendar.is_open_on_minute(fifth_friday)) + + def test_early_close_independence_day_thursday(self): + """ + Until 2013, the market closed early the Friday after an + Independence Day on Thursday. Since then, the early close is on + Wednesday. + """ + # July 2002 + # Su Mo Tu We Th Fr Sa + # 1 2 3 4 5 6 + # 7 8 9 10 11 12 13 + # 14 15 16 17 18 19 20 + # 21 22 23 24 25 26 27 + # 28 29 30 31 + wednesday_before = Timestamp('7/3/2002 3:00PM', tz='EST') + friday_after_open = Timestamp('7/5/2002 11:00AM', tz='EST') + friday_after = Timestamp('7/5/2002 3:00PM', tz='EST') + self.assertTrue(self.calendar.is_open_on_minute(wednesday_before)) + self.assertTrue(self.calendar.is_open_on_minute(friday_after_open)) + self.assertFalse(self.calendar.is_open_on_minute(friday_after)) + + # July 2013 + # Su Mo Tu We Th Fr Sa + # 1 2 3 4 5 6 + # 7 8 9 10 11 12 13 + # 14 15 16 17 18 19 20 + # 21 22 23 24 25 26 27 + # 28 29 30 31 + wednesday_before = Timestamp('7/3/2013 3:00PM', tz='EST') + friday_after_open = Timestamp('7/5/2013 11:00AM', tz='EST') + friday_after = Timestamp('7/5/2013 3:00PM', tz='EST') + self.assertFalse(self.calendar.is_open_on_minute(wednesday_before)) + self.assertTrue(self.calendar.is_open_on_minute(friday_after_open)) + self.assertTrue(self.calendar.is_open_on_minute(friday_after)) diff --git a/tests/test_fetcher.py b/tests/test_fetcher.py index 0425aee3..f760b21e 100644 --- a/tests/test_fetcher.py +++ b/tests/test_fetcher.py @@ -28,6 +28,7 @@ from zipline.testing.fixtures import ( WithSimParams, ZiplineTestCase, ) +from zipline.utils.calendars import default_nyse_schedule from .resources.fetcher_inputs.fetcher_test_data import ( AAPL_CSV_DATA, AAPL_IBM_CSV_DATA, @@ -108,7 +109,8 @@ class FetcherTestCase(WithResponses, data_frequency=data_frequency ) - results = test_algo.run(FetcherDataPortal(self.env)) + results = test_algo.run(FetcherDataPortal(self.env, + default_nyse_schedule)) return results @@ -141,7 +143,8 @@ def handle_data(context, data): # manually setting data portal and getting generator because we need # the minutely emission packets here. TradingAlgorithm.run() only # returns daily packets. - test_algo.data_portal = FetcherDataPortal(self.env) + test_algo.data_portal = FetcherDataPortal(self.env, + default_nyse_schedule) gen = test_algo.get_generator() perf_packets = list(gen) diff --git a/tests/test_finance.py b/tests/test_finance.py index 1d7eef48..7df84b48 100644 --- a/tests/test_finance.py +++ b/tests/test_finance.py @@ -50,6 +50,10 @@ from zipline.testing.fixtures import ( ) import zipline.utils.factory as factory +from zipline.utils.calendars import ( + default_nyse_schedule, + get_calendar, +) DEFAULT_TIMEOUT = 15 # seconds EXTENDED_TIMEOUT = 90 @@ -199,7 +203,7 @@ class FinanceTestCase(WithLogger, data_frequency="minute" ) - minutes = env.market_minute_window( + minutes = default_nyse_schedule.minute_window( sim_params.first_open, int((trade_interval.total_seconds() / 60) * trade_count) + 100) @@ -217,8 +221,9 @@ class FinanceTestCase(WithLogger, } write_bcolz_minute_data( - env, - env.days_in_range(minutes[0], minutes[-1]), + default_nyse_schedule, + default_nyse_schedule.execution_days_in_range(minutes[0], + minutes[-1]), tempdir.path, iteritems(assets), ) @@ -226,7 +231,7 @@ class FinanceTestCase(WithLogger, equity_minute_reader = BcolzMinuteBarReader(tempdir.path) data_portal = DataPortal( - env, + env, default_nyse_schedule, first_trading_day=equity_minute_reader.first_trading_day, equity_minute_reader=equity_minute_reader, ) @@ -254,7 +259,7 @@ class FinanceTestCase(WithLogger, equity_daily_reader = BcolzDailyBarReader(path) data_portal = DataPortal( - env, + env, default_nyse_schedule, first_trading_day=equity_daily_reader.first_trading_day, equity_daily_reader=equity_daily_reader, ) @@ -417,25 +422,25 @@ class TradingEnvironmentTestCase(WithLogger, ] for holiday in holidays: - self.assertTrue(not self.env.is_trading_day(holiday)) + self.assertTrue(not self.cal.is_open_on_day(holiday)) first_trading_day = datetime(2008, 1, 2, tzinfo=pytz.utc) last_trading_day = datetime(2008, 12, 31, tzinfo=pytz.utc) workdays = [first_trading_day, last_trading_day] for workday in workdays: - self.assertTrue(self.env.is_trading_day(workday)) + self.assertTrue(self.cal.is_open_on_day(workday)) def test_simulation_parameters(self): - env = SimulationParameters( + sp = SimulationParameters( period_start=datetime(2008, 1, 1, tzinfo=pytz.utc), period_end=datetime(2008, 12, 31, tzinfo=pytz.utc), capital_base=100000, - env=self.env, + trading_schedule=default_nyse_schedule, ) - self.assertTrue(env.last_close.month == 12) - self.assertTrue(env.last_close.day == 31) + self.assertTrue(sp.last_close.month == 12) + self.assertTrue(sp.last_close.day == 31) @timed(DEFAULT_TIMEOUT) def test_sim_params_days_in_period(self): @@ -452,7 +457,7 @@ class TradingEnvironmentTestCase(WithLogger, period_start=datetime(2007, 12, 31, tzinfo=pytz.utc), period_end=datetime(2008, 1, 7, tzinfo=pytz.utc), capital_base=100000, - env=self.env, + trading_schedule=default_nyse_schedule, ) expected_trading_days = ( @@ -473,7 +478,7 @@ class TradingEnvironmentTestCase(WithLogger, params.trading_days.tolist()) @timed(DEFAULT_TIMEOUT) - def test_market_minute_window(self): + def test_minute_window(self): # January 2008 # Su Mo Tu We Th Fr Sa @@ -488,10 +493,10 @@ class TradingEnvironmentTestCase(WithLogger, # 10:01 AM Eastern on January 7th.. start = us_east.localize(datetime(2008, 1, 7, 10, 1)) - utc_start = start.astimezone(utc) + utc_start = pd.Timestamp(start.astimezone(utc)) # Get the next 10 minutes - minutes = self.env.market_minute_window( + minutes = self.cal.minute_window( utc_start, 10, ) self.assertEqual(len(minutes), 10) @@ -499,7 +504,7 @@ class TradingEnvironmentTestCase(WithLogger, self.assertEqual(minutes[i], utc_start + timedelta(minutes=i)) # Get the previous 10 minutes. - minutes = self.env.market_minute_window( + minutes = self.cal.minute_window( utc_start, 10, step=-1, ) self.assertEqual(len(minutes), 10) @@ -512,14 +517,14 @@ class TradingEnvironmentTestCase(WithLogger, # Today: 10:01 AM -> 4:00 PM (360 minutes) # Tomorrow: 9:31 AM -> 4:00 PM (390 minutes, 750 total) # Last Day: 9:31 AM -> 12:00 PM (150 minutes, 900 total) - minutes = self.env.market_minute_window( - utc_start, 900, + minutes = self.cal.minute_window( + start, 900, ) - today = self.env.market_minutes_for_day(start)[30:] - tomorrow = self.env.market_minutes_for_day( + today = self.cal.minutes_for_date(utc_start)[30:] + tomorrow = self.cal.minutes_for_date( start + timedelta(days=1) ) - last_day = self.env.market_minutes_for_day( + last_day = self.cal.minutes_for_date( start + timedelta(days=2))[:150] self.assertEqual(len(minutes), 900) @@ -534,17 +539,17 @@ class TradingEnvironmentTestCase(WithLogger, # Today: 10:01 AM -> 9:31 AM (31 minutes) # Friday: 4:00 PM -> 9:31 AM (390 minutes, 421 total) # Thursday: 4:00 PM -> 9:41 AM (380 minutes, 801 total) - minutes = self.env.market_minute_window( - utc_start, 801, step=-1, + minutes = self.cal.minute_window( + start, 801, step=-1, ) - today = self.env.market_minutes_for_day(start)[30::-1] + today = self.cal.minutes_for_date(utc_start)[30::-1] # minus an extra two days from each of these to account for the two # weekend days we skipped - friday = self.env.market_minutes_for_day( + friday = self.cal.minutes_for_date( start + timedelta(days=-3), )[::-1] - thursday = self.env.market_minutes_for_day( + thursday = self.cal.minutes_for_date( start + timedelta(days=-4), )[:9:-1] @@ -566,6 +571,5 @@ class TradingEnvironmentTestCase(WithLogger, max_date = pd.Timestamp('2008-08-01', tz='UTC') env = TradingEnvironment(max_date=max_date) - self.assertLessEqual(env.last_trading_day, max_date) self.assertLessEqual(env.treasury_curves.index[-1], max_date) diff --git a/tests/test_history.py b/tests/test_history.py index 26519444..c3ea73da 100644 --- a/tests/test_history.py +++ b/tests/test_history.py @@ -24,6 +24,7 @@ from zipline.testing import ( str_to_seconds, MockDailyBarReader, ) +from zipline.utils.calendars import default_nyse_schedule from zipline.testing.fixtures import ( WithBcolzMinuteBarReader, WithDataPortal, @@ -78,7 +79,7 @@ class WithHistory(WithDataPortal): @classmethod def init_class_fixtures(cls): super(WithHistory, cls).init_class_fixtures() - cls.trading_days = cls.env.days_in_range( + cls.trading_days = default_nyse_schedule.execution_days_in_range( start=cls.TRADING_START_DT, end=cls.TRADING_END_DT ) @@ -455,14 +456,14 @@ class MinuteEquityHistoryTestCase(WithHistory, ZiplineTestCase): for sid in sids: asset = cls.asset_finder.retrieve_asset(sid) data[sid] = create_minute_df_for_asset( - cls.env, + default_nyse_schedule, asset.start_date, asset.end_date, start_val=2, ) data[1] = create_minute_df_for_asset( - cls.env, + default_nyse_schedule, pd.Timestamp('2014-01-03', tz='utc'), pd.Timestamp('2016-01-30', tz='utc'), start_val=2, @@ -509,7 +510,7 @@ class MinuteEquityHistoryTestCase(WithHistory, ZiplineTestCase): )) asset3 = cls.asset_finder.retrieve_asset(3) data[3] = create_minute_df_for_asset( - cls.env, + default_nyse_schedule, asset3.start_date, asset3.end_date, start_val=2, @@ -539,7 +540,7 @@ class MinuteEquityHistoryTestCase(WithHistory, ZiplineTestCase): capital_base=float('1.0e5'), data_frequency='minute', emission_rate='daily', - env=self.env, + trading_schedule=default_nyse_schedule, ) test_algo = TradingAlgorithm( @@ -678,8 +679,10 @@ class MinuteEquityHistoryTestCase(WithHistory, ZiplineTestCase): def test_minute_before_assets_trading(self): # since asset2 and asset3 both started trading on 1/5/2015, let's do # some history windows that are completely before that - minutes = self.env.market_minutes_for_day( - self.env.previous_trading_day(pd.Timestamp('2015-01-05', tz='UTC')) + minutes = default_nyse_schedule.execution_minutes_for_day( + default_nyse_schedule.previous_execution_day( + pd.Timestamp('2015-01-05', tz='UTC') + ) )[0:60] for idx, minute in enumerate(minutes): @@ -726,7 +729,7 @@ class MinuteEquityHistoryTestCase(WithHistory, ZiplineTestCase): # 10 minutes asset = self.env.asset_finder.retrieve_asset(sid) - minutes = self.env.market_minutes_for_day( + minutes = default_nyse_schedule.execution_minutes_for_day( pd.Timestamp('2015-01-05', tz='UTC') )[0:60] @@ -737,7 +740,9 @@ class MinuteEquityHistoryTestCase(WithHistory, ZiplineTestCase): def test_minute_midnight(self): midnight = pd.Timestamp('2015-01-06', tz='UTC') - last_minute = self.env.previous_open_and_close(midnight)[1] + last_minute = default_nyse_schedule.start_and_end( + default_nyse_schedule.previous_execution_day(midnight) + )[1] midnight_bar_data = \ BarData(self.data_portal, lambda: midnight, 'minute') @@ -755,7 +760,7 @@ class MinuteEquityHistoryTestCase(WithHistory, ZiplineTestCase): def test_minute_after_asset_stopped(self): # SHORT_ASSET's last day was 2015-01-06 # get some history windows that straddle the end - minutes = self.env.market_minutes_for_day( + minutes = default_nyse_schedule.execution_minutes_for_day( pd.Timestamp('2015-01-07', tz='UTC') )[0:60] @@ -850,7 +855,7 @@ class MinuteEquityHistoryTestCase(WithHistory, ZiplineTestCase): # before any of the adjustments, last 10 minutes of jan 5 window1 = self.data_portal.get_history_window( [asset], - self.env.get_open_and_close(jan5)[1], + default_nyse_schedule.start_and_end(jan5)[1], 10, '1m', 'close' @@ -1099,20 +1104,21 @@ class MinuteEquityHistoryTestCase(WithHistory, ZiplineTestCase): def test_minute_different_lifetimes(self): # at trading start, only asset1 existed - day = self.env.next_trading_day(self.TRADING_START_DT) + day = default_nyse_schedule.next_execution_day(self.TRADING_START_DT) - asset1_minutes = self.env.minutes_for_days_in_range( + asset1_minutes = \ + default_nyse_schedule.execution_minutes_for_days_in_range( start=self.ASSET1.start_date, end=self.ASSET1.end_date ) asset1_idx = asset1_minutes.searchsorted( - self.env.get_open_and_close(day)[0] + default_nyse_schedule.start_and_end(day)[0] ) window = self.data_portal.get_history_window( [self.ASSET1, self.ASSET2], - self.env.get_open_and_close(day)[0], + default_nyse_schedule.start_and_end(day)[0], 100, '1m', 'close' @@ -1130,7 +1136,7 @@ class MinuteEquityHistoryTestCase(WithHistory, ZiplineTestCase): def test_history_window_before_first_trading_day(self): # trading_start is 2/3/2014 # get a history window that starts before that, and ends after that - first_day_minutes = self.env.market_minutes_for_day( + first_day_minutes = default_nyse_schedule.execution_minutes_for_day( self.TRADING_START_DT ) exp_msg = ( @@ -1150,7 +1156,7 @@ class MinuteEquityHistoryTestCase(WithHistory, ZiplineTestCase): # January 2015 has both daily and minute data for ASSET2 day = pd.Timestamp('2015-01-07', tz='UTC') - minutes = self.env.market_minutes_for_day(day) + minutes = default_nyse_schedule.execution_minutes_for_day(day) # minute data, baseline: # Jan 5: 2 to 391 @@ -1214,7 +1220,7 @@ class MinuteEquityHistoryTestCase(WithHistory, ZiplineTestCase): # January 2015 has both daily and minute data for ASSET2 day = pd.Timestamp('2015-01-08', tz='UTC') - minutes = self.env.market_minutes_for_day(day) + minutes = default_nyse_schedule.execution_minutes_for_day(day) # minute data, baseline: # Jan 5: 2 to 391 @@ -1333,7 +1339,8 @@ class DailyEquityHistoryTestCase(WithHistory, ZiplineTestCase): @classmethod def create_df_for_asset(cls, start_day, end_day, interval=1, force_zeroes=False): - days = cls.env.days_in_range(start_day, end_day) + days = default_nyse_schedule.execution_days_in_range(start_day, + end_day) days_count = len(days) # default to 2 because the low array subtracts 1, and we don't @@ -1362,7 +1369,7 @@ class DailyEquityHistoryTestCase(WithHistory, ZiplineTestCase): def test_daily_before_assets_trading(self): # asset2 and asset3 both started trading in 2015 - days = self.env.days_in_range( + days = default_nyse_schedule.execution_days_in_range( start=pd.Timestamp('2014-12-15', tz='UTC'), end=pd.Timestamp('2014-12-18', tz='UTC'), ) @@ -1400,9 +1407,9 @@ class DailyEquityHistoryTestCase(WithHistory, ZiplineTestCase): # get the first 30 days of 2015 jan5 = pd.Timestamp('2015-01-04') - days = self.env.days_in_range( + days = default_nyse_schedule.execution_days_in_range( start=jan5, - end=self.env.add_trading_days(30, jan5) + end=default_nyse_schedule.add_execution_days(30, jan5) ) for idx, day in enumerate(days): @@ -1445,7 +1452,7 @@ class DailyEquityHistoryTestCase(WithHistory, ZiplineTestCase): def test_daily_after_asset_stopped(self): # SHORT_ASSET trades on 1/5, 1/6, that's it. - days = self.env.days_in_range( + days = default_nyse_schedule.execution_days_in_range( start=pd.Timestamp('2015-01-07', tz='UTC'), end=pd.Timestamp('2015-01-08', tz='UTC') ) @@ -1637,7 +1644,7 @@ class DailyEquityHistoryTestCase(WithHistory, ZiplineTestCase): # trading_start is 2/3/2014 # get a history window that starts before that, and ends after that - second_day = self.env.next_trading_day(self.TRADING_START_DT) + second_day = default_nyse_schedule.next_execution_day(self.TRADING_START_DT) exp_msg = ( 'History window extends before 2014-01-03. To use this history ' @@ -1663,7 +1670,7 @@ class DailyEquityHistoryTestCase(WithHistory, ZiplineTestCase): )[self.ASSET1] # Use a minute to force minute mode. - first_minute = self.env.open_and_closes.market_open[ + first_minute = default_nyse_schedule.open_and_closes.market_open[ self.TRADING_START_DT] with self.assertRaisesRegexp(HistoryWindowStartsBeforeData, exp_msg): @@ -1794,7 +1801,7 @@ class MinuteToDailyAggregationTestCase(WithBcolzMinuteBarReader, # Set up a fresh data portal for each test, since order of calling # needs to be tested. self.equity_daily_aggregator = DailyHistoryAggregator( - self.env.open_and_closes.market_open, + default_nyse_schedule.schedule.market_open, self.bcolz_minute_bar_reader, ) diff --git a/tests/test_perf_tracking.py b/tests/test_perf_tracking.py index c8550c89..f36515ba 100644 --- a/tests/test_perf_tracking.py +++ b/tests/test_perf_tracking.py @@ -59,6 +59,7 @@ from zipline.testing.fixtures import ( WithTradingEnvironment, ZiplineTestCase, ) +from zipline.utils.calendars import default_nyse_schedule logger = logging.getLogger('Test Perf Tracking') @@ -175,7 +176,9 @@ def calculate_results(sim_params, splits = splits or {} commissions = commissions or {} - perf_tracker = perf.PerformanceTracker(sim_params, env) + perf_tracker = perf.PerformanceTracker(sim_params, + default_nyse_schedule, + env) results = [] @@ -240,7 +243,9 @@ def setup_env_data(env, sim_params, sids, futures_sids=[]): for sid in sids: data[sid] = { "start_date": sim_params.trading_days[0], - "end_date": env.next_trading_day(sim_params.trading_days[-1]) + "end_date": default_nyse_schedule.next_execution_day( + sim_params.trading_days[-1] + ) } env.write_data(equities_data=data) @@ -249,7 +254,9 @@ def setup_env_data(env, sim_params, sids, futures_sids=[]): for future_sid in futures_sids: futures_data[future_sid] = { "start_date": sim_params.trading_days[0], - "end_date": env.next_trading_day(sim_params.trading_days[-1]), + "end_date": default_nyse_schedule.next_execution_day( + sim_params.trading_days[-1] + ), "multiplier": 100 } @@ -271,7 +278,9 @@ class TestSplitPerformance(WithSimParams, WithTmpDir, ZiplineTestCase): def test_multiple_splits(self): # if multiple positions all have splits at the same time, verify that # the total leftover cash is correct - perf_tracker = perf.PerformanceTracker(self.sim_params, self.env) + perf_tracker = perf.PerformanceTracker(self.sim_params, + default_nyse_schedule, + self.env) asset1 = self.asset_finder.retrieve_asset(1) asset2 = self.asset_finder.retrieve_asset(2) @@ -300,13 +309,14 @@ class TestSplitPerformance(WithSimParams, WithTmpDir, ZiplineTestCase): [100, 100], oneday, self.sim_params, - env=self.env + trading_schedule=default_nyse_schedule, ) # set up a long position in sid 1 # 100 shares at $20 apiece = $2000 position data_portal = create_data_portal_from_trade_history( self.env, + default_nyse_schedule, self.tmpdir, self.sim_params, {1: events}, @@ -411,7 +421,7 @@ class TestDividendPerformance(WithSimParams, after = factory.get_next_trading_dt( before, timedelta(days=1), - self.env, + default_nyse_schedule, ) self.assertEqual(after.hour, 13) @@ -423,7 +433,7 @@ class TestDividendPerformance(WithSimParams, [100, 100, 100, 100, 100, 100], oneday, self.sim_params, - env=self.env + trading_schedule=default_nyse_schedule, ) dbpath = self.instance_tmpdir.getpath('adjustments.sqlite') @@ -431,7 +441,7 @@ class TestDividendPerformance(WithSimParams, writer = SQLiteAdjustmentWriter( dbpath, MockDailyBarReader(), - self.env.trading_days, + default_nyse_schedule.all_execution_days, ) splits = mergers = create_empty_splits_mergers_frame() dividends = pd.DataFrame({ @@ -446,6 +456,7 @@ class TestDividendPerformance(WithSimParams, adjustment_reader = SQLiteAdjustmentReader(dbpath) data_portal = create_data_portal_from_trade_history( self.env, + default_nyse_schedule, self.instance_tmpdir, self.sim_params, {1: events}, @@ -488,7 +499,7 @@ class TestDividendPerformance(WithSimParams, [100, 100, 100, 100, 100, 100], oneday, self.sim_params, - env=self.env + trading_schedule=default_nyse_schedule, ) dbpath = self.instance_tmpdir.getpath('adjustments.sqlite') @@ -496,7 +507,7 @@ class TestDividendPerformance(WithSimParams, writer = SQLiteAdjustmentWriter( dbpath, MockDailyBarReader(), - self.env.trading_days, + default_nyse_schedule.all_execution_days, ) splits = mergers = create_empty_splits_mergers_frame() dividends = pd.DataFrame({ @@ -522,6 +533,7 @@ class TestDividendPerformance(WithSimParams, data_portal = create_data_portal_from_trade_history( self.env, + default_nyse_schedule, self.instance_tmpdir, self.sim_params, events, @@ -562,7 +574,7 @@ class TestDividendPerformance(WithSimParams, [100, 100, 100, 100, 100, 100], oneday, self.sim_params, - env=self.env + trading_schedule=default_nyse_schedule, ) dbpath = self.instance_tmpdir.getpath('adjustments.sqlite') @@ -570,7 +582,7 @@ class TestDividendPerformance(WithSimParams, writer = SQLiteAdjustmentWriter( dbpath, MockDailyBarReader(), - self.env.trading_days, + default_nyse_schedule.all_execution_days, ) splits = mergers = create_empty_splits_mergers_frame() dividends = pd.DataFrame({ @@ -586,6 +598,7 @@ class TestDividendPerformance(WithSimParams, data_portal = create_data_portal_from_trade_history( self.env, + default_nyse_schedule, self.instance_tmpdir, self.sim_params, {1: events}, @@ -623,7 +636,7 @@ class TestDividendPerformance(WithSimParams, [100, 100, 100, 100, 100, 100], oneday, self.sim_params, - env=self.env + trading_schedule=default_nyse_schedule, ) dbpath = self.instance_tmpdir.getpath('adjustments.sqlite') @@ -631,7 +644,7 @@ class TestDividendPerformance(WithSimParams, writer = SQLiteAdjustmentWriter( dbpath, MockDailyBarReader(), - self.env.trading_days, + default_nyse_schedule.all_execution_days, ) splits = mergers = create_empty_splits_mergers_frame() dividends = pd.DataFrame({ @@ -647,6 +660,7 @@ class TestDividendPerformance(WithSimParams, data_portal = create_data_portal_from_trade_history( self.env, + default_nyse_schedule, self.instance_tmpdir, self.sim_params, {1: events}, @@ -685,14 +699,14 @@ class TestDividendPerformance(WithSimParams, [100, 100, 100, 100, 100, 100], oneday, self.sim_params, - env=self.env + trading_schedule=default_nyse_schedule, ) dbpath = self.instance_tmpdir.getpath('adjustments.sqlite') writer = SQLiteAdjustmentWriter( dbpath, MockDailyBarReader(), - self.env.trading_days, + default_nyse_schedule.all_execution_days, ) splits = mergers = create_empty_splits_mergers_frame() @@ -709,6 +723,7 @@ class TestDividendPerformance(WithSimParams, data_portal = create_data_portal_from_trade_history( self.env, + default_nyse_schedule, self.instance_tmpdir, self.sim_params, {1: events}, @@ -745,20 +760,21 @@ class TestDividendPerformance(WithSimParams, [100, 100, 100, 100, 100, 100], oneday, self.sim_params, - env=self.env + trading_schedule=default_nyse_schedule, ) pay_date = self.sim_params.first_open # find pay date that is much later. for i in range(30): - pay_date = factory.get_next_trading_dt(pay_date, oneday, self.env) + pay_date = factory.get_next_trading_dt(pay_date, oneday, + default_nyse_schedule) dbpath = self.instance_tmpdir.getpath('adjustments.sqlite') writer = SQLiteAdjustmentWriter( dbpath, MockDailyBarReader(), - self.env.trading_days, + default_nyse_schedule.all_execution_days, ) splits = mergers = create_empty_splits_mergers_frame() dividends = pd.DataFrame({ @@ -774,6 +790,7 @@ class TestDividendPerformance(WithSimParams, data_portal = create_data_portal_from_trade_history( self.env, + default_nyse_schedule, self.instance_tmpdir, self.sim_params, {1: events}, @@ -811,7 +828,7 @@ class TestDividendPerformance(WithSimParams, [100, 100, 100, 100, 100, 100], oneday, self.sim_params, - env=self.env + trading_schedule=default_nyse_schedule, ) dbpath = self.instance_tmpdir.getpath('adjustments.sqlite') @@ -819,7 +836,7 @@ class TestDividendPerformance(WithSimParams, writer = SQLiteAdjustmentWriter( dbpath, MockDailyBarReader(), - self.env.trading_days, + default_nyse_schedule.all_execution_days, ) splits = mergers = create_empty_splits_mergers_frame() dividends = pd.DataFrame({ @@ -835,6 +852,7 @@ class TestDividendPerformance(WithSimParams, data_portal = create_data_portal_from_trade_history( self.env, + default_nyse_schedule, self.instance_tmpdir, self.sim_params, {1: events}, @@ -869,7 +887,7 @@ class TestDividendPerformance(WithSimParams, [100, 100, 100, 100, 100, 100], oneday, self.sim_params, - env=self.env + trading_schedule=default_nyse_schedule, ) dbpath = self.instance_tmpdir.getpath('adjustments.sqlite') @@ -877,7 +895,7 @@ class TestDividendPerformance(WithSimParams, writer = SQLiteAdjustmentWriter( dbpath, MockDailyBarReader(), - self.env.trading_days, + default_nyse_schedule.all_execution_days, ) splits = mergers = create_empty_splits_mergers_frame() dividends = pd.DataFrame({ @@ -893,6 +911,7 @@ class TestDividendPerformance(WithSimParams, data_portal = create_data_portal_from_trade_history( self.env, + default_nyse_schedule, self.instance_tmpdir, self.sim_params, {1: events}, @@ -925,7 +944,7 @@ class TestDividendPerformance(WithSimParams, [100, 100, 100, 100, 100], oneday, self.sim_params, - env=self.env + trading_schedule=default_nyse_schedule, ) dbpath = self.instance_tmpdir.getpath('adjustments.sqlite') @@ -933,7 +952,7 @@ class TestDividendPerformance(WithSimParams, writer = SQLiteAdjustmentWriter( dbpath, MockDailyBarReader(), - self.env.trading_days, + default_nyse_schedule.all_execution_days, ) splits = mergers = create_empty_splits_mergers_frame() dividends = pd.DataFrame({ @@ -942,8 +961,9 @@ class TestDividendPerformance(WithSimParams, 'declared_date': np.array([events[-3].dt], dtype='datetime64[ns]'), 'ex_date': np.array([events[-2].dt], dtype='datetime64[ns]'), 'record_date': np.array([events[0].dt], dtype='datetime64[ns]'), - 'pay_date': np.array([self.env.next_trading_day(events[-1].dt)], - dtype='datetime64[ns]'), + 'pay_date': np.array( + [default_nyse_schedule.next_execution_day(events[-1].dt)], + dtype='datetime64[ns]'), }) writer.write(splits, mergers, dividends) adjustment_reader = SQLiteAdjustmentReader(dbpath) @@ -957,10 +977,11 @@ class TestDividendPerformance(WithSimParams, ) sim_params.period_end = events[-1].dt - sim_params.update_internal_from_env(self.env) + sim_params.update_internal_from_trading_schedule(default_nyse_schedule) data_portal = create_data_portal_from_trade_history( self.env, + default_nyse_schedule, self.instance_tmpdir, sim_params, {1: events}, @@ -1049,7 +1070,7 @@ class TestPositionPerformance(WithInstanceTmpDir, ZiplineTestCase): [100, 100, 100, 100], oneday, self.sim_params, - env=self.env + trading_schedule=default_nyse_schedule, ) trades_2 = factory.create_trade_history( @@ -1058,11 +1079,12 @@ class TestPositionPerformance(WithInstanceTmpDir, ZiplineTestCase): [100, 100, 100, 100], oneday, self.sim_params, - env=self.env + trading_schedule=default_nyse_schedule, ) data_portal = create_data_portal_from_trade_history( self.env, + default_nyse_schedule, self.instance_tmpdir, self.sim_params, {1: trades_1, 2: trades_2} @@ -1154,11 +1176,12 @@ class TestPositionPerformance(WithInstanceTmpDir, ZiplineTestCase): [100, 100, 100, 100], oneday, self.sim_params, - env=self.env + trading_schedule=default_nyse_schedule, ) data_portal = create_data_portal_from_trade_history( self.env, + default_nyse_schedule, self.instance_tmpdir, self.sim_params, {1: trades}) @@ -1245,11 +1268,12 @@ class TestPositionPerformance(WithInstanceTmpDir, ZiplineTestCase): [100, 100, 100, 100], oneday, self.sim_params, - env=self.env + trading_schedule=default_nyse_schedule, ) data_portal = create_data_portal_from_trade_history( self.env, + default_nyse_schedule, self.instance_tmpdir, self.sim_params, {1: trades}) @@ -1360,13 +1384,14 @@ single short-sale transaction""" [100, 100, 100, 100, 100, 100], oneday, self.sim_params, - env=self.env + trading_schedule=default_nyse_schedule, ) trades_1 = trades[:-2] data_portal = create_data_portal_from_trade_history( self.env, + default_nyse_schedule, self.instance_tmpdir, self.sim_params, {1: trades}) @@ -1593,11 +1618,12 @@ cost of sole txn in test" [100, 100, 100, 100], oneday, sim_params, - env=self.env + trading_schedule=default_nyse_schedule, ) data_portal = create_data_portal_from_trade_history( self.env, + default_nyse_schedule, self.instance_tmpdir, self.sim_params, {3: trades} @@ -1712,11 +1738,12 @@ single short-sale transaction""" [100, 100, 100, 100, 100, 100], oneday, self.sim_params, - env=self.env + trading_schedule=default_nyse_schedule, ) data_portal = create_data_portal_from_trade_history( self.env, + default_nyse_schedule, self.instance_tmpdir, self.sim_params, {3: trades} @@ -1956,11 +1983,12 @@ trade after cover""" [100, 100, 100, 100, 100, 100, 100, 100, 100, 100], oneday, self.sim_params, - env=self.env + trading_schedule=default_nyse_schedule, ) data_portal = create_data_portal_from_trade_history( self.env, + default_nyse_schedule, self.instance_tmpdir, self.sim_params, {1: trades}) @@ -2042,13 +2070,14 @@ shares in position" [100, 100, 100, 100, 100], oneday, self.sim_params, - self.env + default_nyse_schedule, ) trades = factory.create_trade_history(*history_args) transactions = factory.create_txn_history(*history_args)[:4] data_portal = create_data_portal_from_trade_history( self.env, + default_nyse_schedule, self.instance_tmpdir, self.sim_params, {1: trades}) @@ -2167,7 +2196,7 @@ shares in position" [200, -100, -100, 100, -300, 100, 500, 400], oneday, self.sim_params, - self.env + default_nyse_schedule, ) cost_bases = [10, 10, 0, 8, 9, 9, 13, 13.5] @@ -2318,9 +2347,7 @@ class TestPositionTracker(WithTradingEnvironment, Originally this bug was due to np.dot([], []) returning np.bool_(False) """ - sim_params = factory.create_simulation_parameters( - num_days=4, env=self.env - ) + sim_params = factory.create_simulation_parameters(num_days=4) pt = perf.PositionTracker(self.env.asset_finder, sim_params.data_frequency) diff --git a/tests/test_security_list.py b/tests/test_security_list.py index 2b0223b1..cd0dfa72 100644 --- a/tests/test_security_list.py +++ b/tests/test_security_list.py @@ -18,6 +18,7 @@ from zipline.utils.security_list import ( SecurityListSet, load_from_directory, ) +from zipline.utils.calendars import default_nyse_schedule LEVERAGED_ETFS = load_from_directory('leveraged_etf_list') @@ -87,7 +88,7 @@ class SecurityListTestCase(WithLogger, ZiplineTestCase): cls.sim_params = factory.create_simulation_parameters( start=start, num_days=4, - env=cls.env + trading_schedule=default_nyse_schedule ) cls.sim_params2 = sp2 = factory.create_simulation_parameters( @@ -110,13 +111,15 @@ class SecurityListTestCase(WithLogger, ZiplineTestCase): tempdir=cls.tempdir, sim_params=cls.sim_params, sids=range(0, 5), + trading_schedule=default_nyse_schedule, ) cls.data_portal2 = create_data_portal( env=cls.env2, tempdir=cls.tempdir2, sim_params=cls.sim_params2, - sids=range(0, 5) + sids=range(0, 5), + trading_schedule=default_nyse_schedule, ) def test_iterate_over_restricted_list(self): @@ -212,14 +215,14 @@ class SecurityListTestCase(WithLogger, ZiplineTestCase): def test_algo_with_rl_violation_after_knowledge_date(self): sim_params = factory.create_simulation_parameters( start=list( - LEVERAGED_ETFS.keys())[0] + timedelta(days=7), num_days=5, - env=self.env) + LEVERAGED_ETFS.keys())[0] + timedelta(days=7), num_days=5) data_portal = create_data_portal( self.env, self.tempdir, sim_params=sim_params, - sids=range(0, 5) + sids=range(0, 5), + trading_schedule=default_nyse_schedule, ) algo = RestrictedAlgoWithoutCheck(symbol='BZQ', @@ -270,7 +273,8 @@ class SecurityListTestCase(WithLogger, ZiplineTestCase): env, new_tempdir, sim_params, - range(0, 5) + range(0, 5), + trading_schedule=default_nyse_schedule, ) algo = RestrictedAlgoWithoutCheck( diff --git a/tests/test_trading_schedule.py b/tests/test_trading_schedule.py new file mode 100644 index 00000000..cba11678 --- /dev/null +++ b/tests/test_trading_schedule.py @@ -0,0 +1,58 @@ +from unittest import TestCase + +from pandas import ( + Timestamp, + date_range, +) + +from zipline.utils.calendars import ( + get_calendar, + ExchangeTradingSchedule, + normalize_date, +) + + +class TestExchangeTradingSchedule(TestCase): + + @classmethod + def setUpClass(cls): + cls.nyse_cal = get_calendar('NYSE') + cls.nyse_exchange_schedule = ExchangeTradingSchedule(cal=cls.nyse_cal) + + def test_nyse_data_availability_time(self): + """ + Ensure that the NYSE schedule's data availability time is the market + open. + """ + # This is a time on the day after Thanksgiving when the market was open + test_dt = Timestamp('11/23/2012 11:00AM', tz='EST') + test_date = normalize_date(test_dt) + desired_data_time = Timestamp('11/23/2012 9:31AM', tz='EST') + + # Get the data availability time from the NYSE schedule + data_time = self.nyse_exchange_schedule.data_availability_time( + date=test_date + ) + + # Check the schedule answer against the hard-coded answer + self.assertEqual(data_time, desired_data_time, + "Data availability time is not the market open") + + def test_nyse_execution_time(self): + """ + Runs a series of times through both the NYSE calendar and NYSE + schedule, ensuring that the schedule and calendar agree. + """ + # Get all of the minutes in a 24-hour day + start_range = Timestamp('11/23/2012 12:00AM', tz='EST') + end_range = Timestamp('11/23/2012 11:59PM', tz='EST') + time_range = date_range(start_range, end_range, freq='Min') + + for dt in time_range: + cal_open = self.nyse_cal.is_open_on_minute(dt) + sched_exec = self.nyse_exchange_schedule.is_executing_on_minute(dt) + self.assertEqual( + cal_open, sched_exec, + "Mismatch between schedule: %s and calendar: %s at time %s" + % (cal_open, sched_exec, dt) + ) diff --git a/tests/test_tradingcalendar.py b/tests/test_tradingcalendar.py deleted file mode 100644 index 4719e148..00000000 --- a/tests/test_tradingcalendar.py +++ /dev/null @@ -1,265 +0,0 @@ -# -# Copyright 2013 Quantopian, Inc. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from unittest import TestCase -from zipline.utils import tradingcalendar -from zipline.utils import tradingcalendar_lse -from zipline.utils import tradingcalendar_tse -from zipline.utils import tradingcalendar_bmf -import pytz -import datetime -from zipline.finance.trading import TradingEnvironment -from nose.tools import nottest - - -class TestTradingCalendar(TestCase): - - def test_calendar_vs_environment(self): - """ - test_calendar_vs_environment checks whether the - historical data from yahoo matches our rule based system. - handy, if not canonical, reference: - http://www.chronos-st.org/NYSE_Observed_Holidays-1885-Present.html - """ - - env = TradingEnvironment() - bench_days = env.benchmark_returns[tradingcalendar.start:].index - bounds = env.trading_days.slice_locs(start=tradingcalendar.start, - end=bench_days[-1]) - env_days = env.trading_days[bounds[0]:bounds[1]] - self.check_days(env_days, bench_days) - - @nottest - def test_lse_calendar_vs_environment(self): - env = TradingEnvironment( - bm_symbol='^FTSE', - exchange_tz='Europe/London' - ) - - env_start_index = \ - env.trading_days.searchsorted(tradingcalendar_lse.start) - env_days = env.trading_days[env_start_index:] - cal_days = tradingcalendar_lse.trading_days - self.check_days(env_days, cal_days) - - @nottest - def test_tse_calendar_vs_environment(self): - env = TradingEnvironment( - bm_symbol='^GSPTSE', - exchange_tz='US/Eastern' - ) - - env_start_index = \ - env.trading_days.searchsorted(tradingcalendar_tse.start) - env_days = env.trading_days[env_start_index:] - cal_days = tradingcalendar_tse.trading_days - self.check_days(env_days, cal_days) - - @nottest - def test_bmf_calendar_vs_environment(self): - env = TradingEnvironment( - bm_symbol='^BVSP', - exchange_tz='America/Sao_Paulo' - ) - - env_start_index = \ - env.trading_days.searchsorted(tradingcalendar_bmf.start) - env_days = env.trading_days[env_start_index:] - cal_days = tradingcalendar_bmf.trading_days - self.check_days(env_days, cal_days) - - def check_days(self, env_days, cal_days): - diff = env_days.difference(cal_days) - self.assertEqual( - len(diff), - 0, - "{diff} should be empty".format(diff=diff) - ) - - diff2 = cal_days.difference(env_days) - self.assertEqual( - len(diff2), - 0, - "{diff} should be empty".format(diff=diff2) - ) - - def test_newyears(self): - """ - Check whether tradingcalendar contains certain dates. - """ - # January 2012 - # Su Mo Tu We Th Fr Sa - # 1 2 3 4 5 6 7 - # 8 9 10 11 12 13 14 - # 15 16 17 18 19 20 21 - # 22 23 24 25 26 27 28 - # 29 30 31 - - day_after_new_years_sunday = datetime.datetime( - 2012, 1, 2, tzinfo=pytz.utc) - - self.assertNotIn(day_after_new_years_sunday, - tradingcalendar.trading_days, - """ -If NYE falls on a weekend, {0} the Monday after is a holiday. -""".strip().format(day_after_new_years_sunday) - ) - - first_trading_day_after_new_years_sunday = datetime.datetime( - 2012, 1, 3, tzinfo=pytz.utc) - - self.assertIn(first_trading_day_after_new_years_sunday, - tradingcalendar.trading_days, - """ -If NYE falls on a weekend, {0} the Tuesday after is the first trading day. -""".strip().format(first_trading_day_after_new_years_sunday) - ) - - # January 2013 - # Su Mo Tu We Th Fr Sa - # 1 2 3 4 5 - # 6 7 8 9 10 11 12 - # 13 14 15 16 17 18 19 - # 20 21 22 23 24 25 26 - # 27 28 29 30 31 - - new_years_day = datetime.datetime( - 2013, 1, 1, tzinfo=pytz.utc) - - self.assertNotIn(new_years_day, - tradingcalendar.trading_days, - """ -If NYE falls during the week, e.g. {0}, it is a holiday. -""".strip().format(new_years_day) - ) - - first_trading_day_after_new_years = datetime.datetime( - 2013, 1, 2, tzinfo=pytz.utc) - - self.assertIn(first_trading_day_after_new_years, - tradingcalendar.trading_days, - """ -If the day after NYE falls during the week, {0} \ -is the first trading day. -""".strip().format(first_trading_day_after_new_years) - ) - - def test_thanksgiving(self): - """ - Check tradingcalendar Thanksgiving dates. - """ - # November 2005 - # Su Mo Tu We Th Fr Sa - # 1 2 3 4 5 - # 6 7 8 9 10 11 12 - # 13 14 15 16 17 18 19 - # 20 21 22 23 24 25 26 - # 27 28 29 30 - thanksgiving_with_four_weeks = datetime.datetime( - 2005, 11, 24, tzinfo=pytz.utc) - - self.assertNotIn(thanksgiving_with_four_weeks, - tradingcalendar.trading_days, - """ -If Nov has 4 Thursdays, {0} Thanksgiving is the last Thursady. -""".strip().format(thanksgiving_with_four_weeks) - ) - - # November 2006 - # Su Mo Tu We Th Fr Sa - # 1 2 3 4 - # 5 6 7 8 9 10 11 - # 12 13 14 15 16 17 18 - # 19 20 21 22 23 24 25 - # 26 27 28 29 30 - thanksgiving_with_five_weeks = datetime.datetime( - 2006, 11, 23, tzinfo=pytz.utc) - - self.assertNotIn(thanksgiving_with_five_weeks, - tradingcalendar.trading_days, - """ -If Nov has 5 Thursdays, {0} Thanksgiving is not the last week. -""".strip().format(thanksgiving_with_five_weeks) - ) - - first_trading_day_after_new_years_sunday = datetime.datetime( - 2012, 1, 3, tzinfo=pytz.utc) - - self.assertIn(first_trading_day_after_new_years_sunday, - tradingcalendar.trading_days, - """ -If NYE falls on a weekend, {0} the Tuesday after is the first trading day. -""".strip().format(first_trading_day_after_new_years_sunday) - ) - - def test_day_after_thanksgiving(self): - early_closes = tradingcalendar.get_early_closes( - tradingcalendar.start, - tradingcalendar.end.replace(year=tradingcalendar.end.year + 1) - ) - - # November 2012 - # Su Mo Tu We Th Fr Sa - # 1 2 3 - # 4 5 6 7 8 9 10 - # 11 12 13 14 15 16 17 - # 18 19 20 21 22 23 24 - # 25 26 27 28 29 30 - fourth_friday = datetime.datetime(2012, 11, 23, tzinfo=pytz.utc) - self.assertIn(fourth_friday, early_closes) - - # November 2013 - # Su Mo Tu We Th Fr Sa - # 1 2 - # 3 4 5 6 7 8 9 - # 10 11 12 13 14 15 16 - # 17 18 19 20 21 22 23 - # 24 25 26 27 28 29 30 - fifth_friday = datetime.datetime(2013, 11, 29, tzinfo=pytz.utc) - self.assertIn(fifth_friday, early_closes) - - def test_early_close_independence_day_thursday(self): - """ - Until 2013, the market closed early the Friday after an - Independence Day on Thursday. Since then, the early close is on - Wednesday. - """ - early_closes = tradingcalendar.get_early_closes( - tradingcalendar.start, - tradingcalendar.end.replace(year=tradingcalendar.end.year + 1) - ) - # July 2002 - # Su Mo Tu We Th Fr Sa - # 1 2 3 4 5 6 - # 7 8 9 10 11 12 13 - # 14 15 16 17 18 19 20 - # 21 22 23 24 25 26 27 - # 28 29 30 31 - wednesday_before = datetime.datetime(2002, 7, 3, tzinfo=pytz.utc) - friday_after = datetime.datetime(2002, 7, 5, tzinfo=pytz.utc) - self.assertNotIn(wednesday_before, early_closes) - self.assertIn(friday_after, early_closes) - - # July 2013 - # Su Mo Tu We Th Fr Sa - # 1 2 3 4 5 6 - # 7 8 9 10 11 12 13 - # 14 15 16 17 18 19 20 - # 21 22 23 24 25 26 27 - # 28 29 30 31 - wednesday_before = datetime.datetime(2013, 7, 3, tzinfo=pytz.utc) - friday_after = datetime.datetime(2013, 7, 5, tzinfo=pytz.utc) - self.assertIn(wednesday_before, early_closes) - self.assertNotIn(friday_after, early_closes) diff --git a/tests/utils/test_events.py b/tests/utils/test_events.py index 90e2ebc0..2a2c03c0 100644 --- a/tests/utils/test_events.py +++ b/tests/utils/test_events.py @@ -28,6 +28,7 @@ from six.moves import range, map from zipline.finance.trading import TradingEnvironment from zipline.testing import subtest, parameter_space import zipline.utils.events +from zipline.utils.calendars import get_calendar from zipline.utils.events import ( EventRule, StatelessRule, @@ -165,7 +166,7 @@ class TestEventManager(TestCase): class CountingRule(Always): count = 0 - def should_trigger(self, dt, env): + def should_trigger(self, dt): CountingRule.count += 1 return True @@ -174,9 +175,7 @@ class TestEventManager(TestCase): Event(r(), lambda context, data: None) ) - mock_algo_class = namedtuple('FakeAlgo', ['trading_environment']) - mock_algo = mock_algo_class(trading_environment="fake_env") - self.em.handle_data(mock_algo, None, datetime.datetime.now()) + self.em.handle_data(None, None, datetime.datetime.now()) self.assertEqual(CountingRule.count, 5) @@ -188,7 +187,7 @@ class TestEventRule(TestCase): def test_not_implemented(self): with self.assertRaises(NotImplementedError): - super(Always, Always()).should_trigger('a', env=None) + super(Always, Always()).should_trigger('a') def minutes_for_days(ordered_days=False): @@ -207,7 +206,7 @@ def minutes_for_days(ordered_days=False): Iterating over this yields a single day, iterating over the day yields the minutes for that day. """ - env = TradingEnvironment() + cal = get_calendar('NYSE') random.seed('deterministic') if ordered_days: # Get a list of 500 trading days, in order. As a performance @@ -223,16 +222,15 @@ def minutes_for_days(ordered_days=False): # Other than AfterOpen and BeforeClose, we don't rely on the the nature # of the clock, so we don't care. def day_picker(day): - return random.choice(env.trading_days[:-1]) + return random.choice(cal.all_trading_days[:-1]) - return ((env.market_minutes_for_day(day_picker(cnt)),) + return ((cal.trading_minutes_for_day(day_picker(cnt)),) for cnt in range(500)) class RuleTestCase(TestCase): @classmethod def setUpClass(cls): - cls.env = TradingEnvironment() # On the AfterOpen and BeforeClose tests, we want ensure that the # functions are pure, and that running them with the same input will # provide the same output, regardless of whether the function is run 1 @@ -244,9 +242,6 @@ class RuleTestCase(TestCase): cls.after_open = AfterOpen(hours=1, minutes=5) cls.class_ = None # Mark that this is the base class. - @classmethod - def tearDownClass(cls): - del cls.env def test_completeness(self): """ @@ -280,32 +275,31 @@ class TestStatelessRules(RuleTestCase): cls.class_ = StatelessRule - cls.sept_days = cls.env.days_in_range( + cls.nyse_cal = get_calendar('NYSE') + + cls.sept_days = cls.nyse_cal.trading_days_in_range( pd.Timestamp('2014-09-01'), pd.Timestamp('2014-09-30'), ) - cls.sept_week = cls.env.minutes_for_days_in_range( + cls.sept_week = cls.nyse_cal.trading_minutes_for_days_in_range( datetime.date(year=2014, month=9, day=21), datetime.date(year=2014, month=9, day=26), ) @subtest(minutes_for_days(), 'ms') def test_Always(self, ms): - should_trigger = partial(Always().should_trigger, env=self.env) + should_trigger = Always().should_trigger self.assertTrue(all(map(should_trigger, ms))) @subtest(minutes_for_days(), 'ms') def test_Never(self, ms): - should_trigger = partial(Never().should_trigger, env=self.env) + should_trigger = Never().should_trigger self.assertFalse(any(map(should_trigger, ms))) @subtest(minutes_for_days(ordered_days=True), 'ms') def test_AfterOpen(self, ms): - should_trigger = partial( - self.after_open.should_trigger, - env=self.env, - ) + should_trigger = self.after_open.should_trigger for i, m in enumerate(ms): # Should only trigger at the 64th minute if i != 64: @@ -316,10 +310,7 @@ class TestStatelessRules(RuleTestCase): @subtest(minutes_for_days(ordered_days=True), 'ms') def test_BeforeClose(self, ms): ms = list(ms) - should_trigger = partial( - self.before_close.should_trigger, - env=self.env - ) + should_trigger = self.before_close.should_trigger for m in ms: # Should only trigger at the 65th-to-last minute if m != ms[-66]: @@ -329,7 +320,7 @@ class TestStatelessRules(RuleTestCase): @subtest(minutes_for_days(), 'ms') def test_NotHalfDay(self, ms): - should_trigger = partial(NotHalfDay().should_trigger, env=self.env) + should_trigger = NotHalfDay().should_trigger self.assertTrue(should_trigger(FULL_DAY)) self.assertFalse(should_trigger(HALF_DAY)) @@ -340,14 +331,13 @@ class TestStatelessRules(RuleTestCase): """ self.assertTrue( NthTradingDayOfWeek(0).should_trigger( - self.env.trading_days[0], self.env + self.nyse_cal.all_trading_days[0] ) ) @subtest(param_range(MAX_WEEK_RANGE), 'n') def test_NthTradingDayOfWeek(self, n): - should_trigger = partial(NthTradingDayOfWeek(n).should_trigger, - env=self.env) + should_trigger = NthTradingDayOfWeek(n).should_trigger prev_day = self.sept_week[0].date() n_tdays = 0 for m in self.sept_week: @@ -362,17 +352,15 @@ class TestStatelessRules(RuleTestCase): @subtest(param_range(MAX_WEEK_RANGE), 'n') def test_NDaysBeforeLastTradingDayOfWeek(self, n): - should_trigger = partial( - NDaysBeforeLastTradingDayOfWeek(n).should_trigger, env=self.env - ) + should_trigger = NDaysBeforeLastTradingDayOfWeek(n).should_trigger for m in self.sept_week: if should_trigger(m): n_tdays = 0 date = m.to_datetime().date() - next_date = self.env.next_trading_day(date) + next_date = self.nyse_cal.next_trading_day(date) while next_date.weekday() > date.weekday(): date = next_date - next_date = self.env.next_trading_day(date) + next_date = self.nyse_cal.next_trading_day(date) n_tdays += 1 self.assertEqual(n_tdays, n) @@ -486,10 +474,9 @@ class TestStatelessRules(RuleTestCase): @subtest(param_range(MAX_MONTH_RANGE), 'n') def test_NthTradingDayOfMonth(self, n): - should_trigger = partial(NthTradingDayOfMonth(n).should_trigger, - env=self.env) + should_trigger = NthTradingDayOfMonth(n).should_trigger for n_tdays, d in enumerate(self.sept_days): - for m in self.env.market_minutes_for_day(d): + for m in self.nyse_cal.trading_minutes_for_day(d): if should_trigger(m): self.assertEqual(n_tdays, n) else: @@ -497,11 +484,9 @@ class TestStatelessRules(RuleTestCase): @subtest(param_range(MAX_MONTH_RANGE), 'n') def test_NDaysBeforeLastTradingDayOfMonth(self, n): - should_trigger = partial( - NDaysBeforeLastTradingDayOfMonth(n).should_trigger, env=self.env - ) + should_trigger = NDaysBeforeLastTradingDayOfMonth(n).should_trigger for n_days_before, d in enumerate(reversed(self.sept_days)): - for m in self.env.market_minutes_for_day(d): + for m in self.nyse_cal.trading_minutes_for_day(d): if should_trigger(m): self.assertEqual(n_days_before, n) else: @@ -513,7 +498,7 @@ class TestStatelessRules(RuleTestCase): rule2 = Never() composed = rule1 & rule2 - should_trigger = partial(composed.should_trigger, env=self.env) + should_trigger = composed.should_trigger self.assertIsInstance(composed, ComposedRule) self.assertIs(composed.first, rule1) self.assertIs(composed.second, rule2) @@ -536,14 +521,14 @@ class TestStatefulRules(RuleTestCase): """ count = 0 - def should_trigger(self, dt, env): - st = self.rule.should_trigger(dt, env) + def should_trigger(self, dt): + st = self.rule.should_trigger(dt) if st: self.count += 1 return st rule = RuleCounter(OncePerDay()) for m in ms: - rule.should_trigger(m, env=self.env) + rule.should_trigger(m) self.assertEqual(rule.count, 1) diff --git a/zipline/_protocol.pyx b/zipline/_protocol.pyx index d8e2c86d..7b471331 100644 --- a/zipline/_protocol.pyx +++ b/zipline/_protocol.pyx @@ -223,7 +223,8 @@ cdef class BarData: dt = self.simulation_dt_func() if self._adjust_minutes: - dt = self.data_portal.env.previous_market_minute(dt) + dt = \ + self.data_portal.trading_schedule.previous_execution_minute(dt) return dt diff --git a/zipline/algorithm.py b/zipline/algorithm.py index 24bce19f..e2132437 100644 --- a/zipline/algorithm.py +++ b/zipline/algorithm.py @@ -94,6 +94,7 @@ from zipline.utils.api_support import ( from zipline.utils.input_validation import ensure_upper_case, error_keywords from zipline.utils.cache import CachedObject, Expired +from zipline.utils.calendars import default_nyse_schedule import zipline.utils.events from zipline.utils.events import ( EventManager, @@ -273,6 +274,12 @@ class TradingAlgorithm(object): futures=kwargs.pop('futures_metadata', None), ) + # If a schedule has been provided, pop it. Otherwise, use NYSE. + self.trading_schedule = kwargs.pop( + 'trading_schedule', + default_nyse_schedule, + ) + # set the capital base self.capital_base = kwargs.pop('capital_base', DEFAULT_CAPITAL_BASE) self.sim_params = kwargs.pop('sim_params', None) @@ -281,10 +288,12 @@ class TradingAlgorithm(object): capital_base=self.capital_base, start=kwargs.pop('start', None), end=kwargs.pop('end', None), - env=self.trading_environment, + trading_schedule=self.trading_schedule, ) else: - self.sim_params.update_internal_from_env(self.trading_environment) + self.sim_params.update_internal_from_trading_schedule( + self.trading_schedule + ) self.perf_tracker = None # Pull in the environment's new AssetFinder for quick reference @@ -411,7 +420,7 @@ class TradingAlgorithm(object): if get_loader is not None: self.engine = SimplePipelineEngine( get_loader, - self.trading_environment.trading_days, + self.trading_schedule.schedule.index, self.asset_finder, ) else: @@ -484,8 +493,7 @@ class TradingAlgorithm(object): If the clock property is not set, then create one based on frequency. """ if self.sim_params.data_frequency == 'minute': - env = self.trading_environment - trading_o_and_c = env.open_and_closes.ix[ + trading_o_and_c = self.trading_schedule.schedule.ix[ self.sim_params.trading_days] market_opens = trading_o_and_c['market_open'].values.astype( 'datetime64[ns]').astype(np.int64) @@ -506,10 +514,11 @@ class TradingAlgorithm(object): def _create_benchmark_source(self): return BenchmarkSource( - self.benchmark_sid, - self.trading_environment, - self.sim_params.trading_days, - self.data_portal, + benchmark_sid=self.benchmark_sid, + env=self.trading_environment, + trading_schedule=self.trading_schedule, + trading_days=self.sim_params.trading_days, + data_portal=self.data_portal, emission_rate=self.sim_params.emission_rate, ) @@ -522,6 +531,7 @@ class TradingAlgorithm(object): # None so that it will be overwritten here. self.perf_tracker = PerformanceTracker( sim_params=self.sim_params, + trading_schedule=self.trading_schedule, env=self.trading_environment, ) @@ -625,6 +635,7 @@ class TradingAlgorithm(object): ) self.data_portal = DataPortal( self.trading_environment, + self.trading_schedule, first_trading_day=equity_daily_reader.first_trading_day, equity_daily_reader=equity_daily_reader, ) @@ -2210,7 +2221,7 @@ class TradingAlgorithm(object): -------- PipelineEngine.run_pipeline """ - days = self.trading_environment.trading_days + days = self.trading_schedule.all_execution_days # Load data starting from the previous trading day... start_date_loc = days.get_loc(start_date) diff --git a/zipline/data/data_portal.py b/zipline/data/data_portal.py index d5ec13ad..0e9b478f 100644 --- a/zipline/data/data_portal.py +++ b/zipline/data/data_portal.py @@ -116,6 +116,7 @@ class DailyHistoryAggregator(object): cache = self._caches[field] = (dt.date(), market_open, {}) _, market_open, entries = cache + market_open = market_open.tz_localize('UTC') if dt != market_open: prev_dt = dt_value - self._one_min else: @@ -496,6 +497,7 @@ class DataPortal(object): """ def __init__(self, env, + trading_schedule, first_trading_day, equity_daily_reader=None, equity_minute_reader=None, @@ -503,6 +505,7 @@ class DataPortal(object): future_minute_reader=None, adjustment_reader=None): self.env = env + self.trading_schedule = trading_schedule self.views = {} @@ -535,7 +538,7 @@ class DataPortal(object): self._equity_daily_reader = equity_daily_reader if self._equity_daily_reader is not None: self._equity_history_loader = USEquityDailyHistoryLoader( - self.env, + self.trading_schedule, self._equity_daily_reader, self._adjustment_reader ) @@ -547,10 +550,10 @@ class DataPortal(object): if self._equity_minute_reader is not None: self._equity_daily_aggregator = DailyHistoryAggregator( - self.env.open_and_closes.market_open, + self.trading_schedule.schedule.market_open, self._equity_minute_reader) self._equity_minute_history_loader = USEquityMinuteHistoryLoader( - self.env, + self.trading_schedule, self._equity_minute_reader, self._adjustment_reader ) @@ -591,7 +594,7 @@ class DataPortal(object): # asset -> df. In other words, # self.augmented_sources_map['days_to_cover']['AAPL'] gives us the df # holding that data. - source_date_index = self.env.days_in_range( + source_date_index = self.trading_schedule.execution_days_in_range( start=sim_params.period_start, end=sim_params.period_end ) @@ -1012,12 +1015,13 @@ class DataPortal(object): @remember_last def _get_days_for_window(self, end_date, bar_count): - tds = self.env.trading_days - end_loc = self.env.trading_days.get_loc(end_date) + tds = self.trading_schedule.all_execution_days + end_loc = tds.get_loc(end_date) start_loc = end_loc - bar_count + 1 - if start_loc < 0: + start_dt = tds[start_loc] + if start_dt < self._first_trading_day: raise HistoryWindowStartsBeforeData( - first_trading_day=self.env.first_trading_day.date(), + first_trading_day=self._first_trading_day.date(), bar_count=bar_count, suggested_start_day=tds[bar_count].date(), ) @@ -1069,7 +1073,7 @@ class DataPortal(object): # get all the minutes for the days NOT including today for day in days_for_window[:-1]: - minutes = self.env.market_minutes_for_day(day) + minutes = self.trading_schedule.execution_minutes_for_day(day) values_for_day = np.zeros(len(minutes), dtype=np.float64) @@ -1084,7 +1088,7 @@ class DataPortal(object): # get the minutes for today last_day_minutes = pd.date_range( - start=self.env.get_open_and_close(end_dt)[0], + start=self.trading_schedule.start_and_end(end_dt)[0], end=end_dt, freq="T" ) @@ -1168,13 +1172,15 @@ class DataPortal(object): of minute frequency for the given sids. """ # get all the minutes for this window - mm = self.env.market_minutes + mm = self.trading_schedule.all_execution_minutes end_loc = mm.get_loc(end_dt) start_loc = end_loc - bar_count + 1 if start_loc < 0: - suggested_start_day = (mm[bar_count] + self.env.trading_day).date() + suggested_start_day = \ + (mm[bar_count] + self.trading_schedule.day).date() raise HistoryWindowStartsBeforeData( - first_trading_day=self.env.first_trading_day.date(), + first_trading_day=\ + self.trading_schedule.first_execution_day.date(), bar_count=bar_count, suggested_start_day=suggested_start_day, ) @@ -1690,9 +1696,11 @@ class DataPortal(object): # we get all the minutes for the last (bars - 1) days, then add # all the minutes so far today. the +2 is to account for ignoring # today, and the previous day, in doing the math. - previous_day = self.env.previous_trading_day(ending_minute) - days = self.env.days_in_range( - self.env.add_trading_days(-days_count + 2, previous_day), + previous_day = \ + self.trading_schedule.previous_execution_day(ending_minute) + days = self.trading_schedule.execution_days_in_range( + self.trading_schedule.add_execution_days(-days_count + 2, + previous_day), previous_day, ) diff --git a/zipline/data/us_equity_loader.py b/zipline/data/us_equity_loader.py index 2d107d4b..63e7d32b 100644 --- a/zipline/data/us_equity_loader.py +++ b/zipline/data/us_equity_loader.py @@ -82,8 +82,8 @@ class USEquityHistoryLoader(with_metaclass(ABCMeta)): """ FIELDS = ('open', 'high', 'low', 'close', 'volume') - def __init__(self, env, reader, adjustment_reader, sid_cache_size=1000): - self.env = env + def __init__(self, trading_schedule, reader, adjustment_reader, sid_cache_size=1000): + self.trading_schedule = trading_schedule self._reader = reader self._adjustments_reader = adjustment_reader self._window_blocks = { @@ -403,7 +403,7 @@ class USEquityMinuteHistoryLoader(USEquityHistoryLoader): @lazyval def _calendar(self): - mm = self.env.market_minutes + mm = self.trading_schedule.all_execution_minutes return mm[mm.slice_indexer(start=self._reader.first_trading_day, end=self._reader.last_available_dt)] diff --git a/zipline/errors.py b/zipline/errors.py index e17e4af5..85440414 100644 --- a/zipline/errors.py +++ b/zipline/errors.py @@ -635,3 +635,22 @@ class NonExistentAssetInTimeFrame(ZiplineError): "The target asset '{asset}' does not exist for the entire timeframe " "between {start_date} and {end_date}." ) + + +class InvalidCalendarName(ZiplineError): + """ + Raised when a calendar with an invalid name is requested. + """ + msg = ( + "The requested ExchangeCalendar, {calendar_name}, does not exist." + ) + + +class CalendarNameCollision(ZiplineError): + """ + Raised when the static calendar registry already has a calendar with a + given name. + """ + msg = ( + "A calendar with the name {calendar_name} is already registered." + ) diff --git a/zipline/finance/performance/tracker.py b/zipline/finance/performance/tracker.py index 1ca6148c..038445e3 100644 --- a/zipline/finance/performance/tracker.py +++ b/zipline/finance/performance/tracker.py @@ -78,28 +78,28 @@ class PerformanceTracker(object): """ Tracks the performance of the algorithm. """ - def __init__(self, sim_params, env): + def __init__(self, sim_params, trading_schedule, env): self.sim_params = sim_params - self.env = env + self.trading_schedule = trading_schedule + self.asset_finder = env.asset_finder + self.treasury_curves = env.treasury_curves self.period_start = self.sim_params.period_start self.period_end = self.sim_params.period_end self.last_close = self.sim_params.last_close - first_open = self.sim_params.first_open.tz_convert( - self.env.exchange_tz - ) + first_open = self.sim_params.first_open.tz_convert(trading_schedule.tz) self.day = pd.Timestamp(datetime(first_open.year, first_open.month, first_open.day), tz='UTC') - self.market_open, self.market_close = env.get_open_and_close(self.day) + self.market_open, self.market_close = trading_schedule.start_and_end( + self.day + ) self.total_days = self.sim_params.days_in_period self.capital_base = self.sim_params.capital_base self.emission_rate = sim_params.emission_rate - all_trading_days = env.trading_days - mask = ((all_trading_days >= normalize_date(self.period_start)) & - (all_trading_days <= normalize_date(self.period_end))) - - self.trading_days = all_trading_days[mask] + self.trading_days = trading_schedule.trading_dates( + self.period_start, self.period_end + ) self.position_tracker = PositionTracker( asset_finder=env.asset_finder, @@ -109,15 +109,23 @@ class PerformanceTracker(object): self.all_benchmark_returns = pd.Series( index=self.trading_days) self.cumulative_risk_metrics = \ - risk.RiskMetricsCumulative(self.sim_params, self.env) + risk.RiskMetricsCumulative( + self.sim_params, + self.treasury_curves, + self.trading_schedule + ) elif self.emission_rate == 'minute': self.all_benchmark_returns = pd.Series(index=pd.date_range( self.sim_params.first_open, self.sim_params.last_close, freq='Min')) self.cumulative_risk_metrics = \ - risk.RiskMetricsCumulative(self.sim_params, self.env, - create_first_day_stats=True) + risk.RiskMetricsCumulative( + self.sim_params, + self.treasury_curves, + self.trading_schedule, + create_first_day_stats=True + ) # this performance period will span the entire simulation from # inception. @@ -134,7 +142,7 @@ class PerformanceTracker(object): keep_orders=False, # don't serialize positions for cumulative period serialize_positions=False, - asset_finder=self.env.asset_finder, + asset_finder=self.asset_finder, name="Cumulative" ) self.cumulative_performance.position_tracker = self.position_tracker @@ -150,7 +158,7 @@ class PerformanceTracker(object): keep_transactions=True, keep_orders=True, serialize_positions=True, - asset_finder=self.env.asset_finder, + asset_finder=self.asset_finder, name="Daily" ) self.todays_performance.position_tracker = self.position_tracker @@ -380,7 +388,9 @@ class PerformanceTracker(object): # Get the next trading day and, if it is past the bounds of this # simulation, return the daily perf packet - next_trading_day = self.env.next_trading_day(completed_date) + next_trading_day = self.trading_schedule.next_execution_day( + completed_date + ) # Take a snapshot of our current performance to return to the # browser. @@ -393,9 +403,10 @@ class PerformanceTracker(object): return daily_update # move the market day markers forward + # TODO Is this redundant with next_trading_day above? + self.day = self.trading_schedule.next_execution_day(self.day) self.market_open, self.market_close = \ - self.env.next_open_and_close(self.day) - self.day = self.env.next_trading_day(self.day) + self.trading_schedule.start_and_end(self.day) # Roll over positions to current day. self.todays_performance.rollover() @@ -439,7 +450,9 @@ class PerformanceTracker(object): self.sim_params, benchmark_returns=bms, algorithm_leverages=acl, - env=self.env) + trading_schedule=self.trading_schedule, + treasury_curves=self.treasury_curves, + ) risk_dict = self.risk_report.to_dict() return risk_dict diff --git a/zipline/finance/risk/cumulative.py b/zipline/finance/risk/cumulative.py index bf56213e..3a0baf7c 100644 --- a/zipline/finance/risk/cumulative.py +++ b/zipline/finance/risk/cumulative.py @@ -86,8 +86,10 @@ class RiskMetricsCumulative(object): 'information', ) - def __init__(self, sim_params, env, create_first_day_stats=False): - self.treasury_curves = env.treasury_curves + def __init__(self, sim_params, treasury_curves, trading_schedule, + create_first_day_stats=False): + self.treasury_curves = treasury_curves + self.trading_schedule = trading_schedule self.start_date = sim_params.period_start.replace( hour=0, minute=0, second=0, microsecond=0 ) @@ -95,12 +97,14 @@ class RiskMetricsCumulative(object): hour=0, minute=0, second=0, microsecond=0 ) - self.trading_days = env.days_in_range(self.start_date, self.end_date) + self.trading_days = trading_schedule.trading_dates( + self.start_date, self.end_date + ) # Hold on to the trading day before the start, # used for index of the zero return value when forcing returns # on the first day. - self.day_before_start = self.start_date - env.trading_days.freq + self.day_before_start = self.start_date - self.trading_days.freq last_day = normalize_date(sim_params.period_end) if last_day not in self.trading_days: @@ -110,7 +114,6 @@ class RiskMetricsCumulative(object): self.trading_days = self.trading_days.append(last_day) self.sim_params = sim_params - self.env = env self.create_first_day_stats = create_first_day_stats @@ -268,7 +271,7 @@ algorithm_returns ({algo_count}) in range {start} : {end} on {dt}" self.treasury_curves, self.start_date, treasury_end, - self.env, + self.trading_schedule, ) self.daily_treasury[treasury_end] = treasury_period_return self.treasury_period_return = self.daily_treasury[treasury_end] diff --git a/zipline/finance/risk/period.py b/zipline/finance/risk/period.py index b4af1288..ec3c1428 100644 --- a/zipline/finance/risk/period.py +++ b/zipline/finance/risk/period.py @@ -41,11 +41,9 @@ choose_treasury = functools.partial(risk.choose_treasury, class RiskMetricsPeriod(object): - def __init__(self, start_date, end_date, returns, env, - benchmark_returns=None, algorithm_leverages=None): + def __init__(self, start_date, end_date, returns, trading_schedule, + treasury_curves, benchmark_returns, algorithm_leverages=None): - self.env = env - treasury_curves = env.treasury_curves if treasury_curves.index[-1] >= start_date: mask = ((treasury_curves.index >= start_date) & (treasury_curves.index <= end_date)) @@ -58,16 +56,20 @@ class RiskMetricsPeriod(object): self.start_date = start_date self.end_date = end_date + self.trading_schedule = trading_schedule - if benchmark_returns is None: - br = env.benchmark_returns - benchmark_returns = br[(br.index >= returns.index[0]) & - (br.index <= returns.index[-1])] - + trading_dates = trading_schedule.trading_dates( + start=self.start_date, + end=self.end_date, + ) self.algorithm_returns = self.mask_returns_to_period(returns, - env) - self.benchmark_returns = self.mask_returns_to_period(benchmark_returns, - env) + trading_dates) + + # Benchmark needs to be masked to the same dates as the algo returns + self.benchmark_returns = self.mask_returns_to_period( + benchmark_returns, + self.algorithm_returns.index + ) self.algorithm_leverages = algorithm_leverages self.calculate_metrics() @@ -108,7 +110,7 @@ class RiskMetricsPeriod(object): self.treasury_curves, self.start_date, self.end_date, - self.env, + self.trading_schedule, ) self.sharpe = self.calculate_sharpe() # The consumer currently expects a 0.0 value for sharpe in period, @@ -187,15 +189,14 @@ class RiskMetricsPeriod(object): return '\n'.join(statements) - def mask_returns_to_period(self, daily_returns, env): + def mask_returns_to_period(self, daily_returns, trading_days): if isinstance(daily_returns, list): returns = pd.Series([x.returns for x in daily_returns], index=[x.date for x in daily_returns]) else: # otherwise we're receiving an index already returns = daily_returns - trade_days = env.trading_days - trade_day_mask = returns.index.normalize().isin(trade_days) + trade_day_mask = returns.index.normalize().isin(trading_days) mask = ((returns.index >= self.start_date) & (returns.index <= self.end_date) & trade_day_mask) diff --git a/zipline/finance/risk/report.py b/zipline/finance/risk/report.py index 4ef72f98..a54aff15 100644 --- a/zipline/finance/risk/report.py +++ b/zipline/finance/risk/report.py @@ -67,8 +67,9 @@ log = logbook.Logger('Risk Report') class RiskReport(object): - def __init__(self, algorithm_returns, sim_params, env, - benchmark_returns=None, algorithm_leverages=None): + def __init__(self, algorithm_returns, sim_params, trading_schedule, + treasury_curves, benchmark_returns, + algorithm_leverages=None): """ algorithm_returns needs to be a list of daily_return objects sorted in date ascending order @@ -79,7 +80,8 @@ class RiskReport(object): self.algorithm_returns = algorithm_returns self.sim_params = sim_params - self.env = env + self.trading_schedule = trading_schedule + self.treasury_curves = treasury_curves self.benchmark_returns = benchmark_returns self.algorithm_leverages = algorithm_leverages @@ -140,7 +142,8 @@ class RiskReport(object): end_date=cur_end, returns=self.algorithm_returns, benchmark_returns=self.benchmark_returns, - env=self.env, + trading_schedule=self.trading_schedule, + treasury_curves=self.treasury_curves, algorithm_leverages=self.algorithm_leverages, ) diff --git a/zipline/finance/risk/risk.py b/zipline/finance/risk/risk.py index a3f99ac3..19117df7 100644 --- a/zipline/finance/risk/risk.py +++ b/zipline/finance/risk/risk.py @@ -202,14 +202,6 @@ def get_treasury_rate(treasury_curves, treasury_duration, day): return rate -def search_day_distance(end_date, dt, env): - tdd = env.trading_day_distance(dt, end_date) - if tdd is None: - return None - assert tdd >= 0 - return tdd - - def select_treasury_duration(start_date, end_date): td = end_date - start_date if td.days <= 31: @@ -237,7 +229,7 @@ def select_treasury_duration(start_date, end_date): def choose_treasury(select_treasury, treasury_curves, start_date, end_date, - env, compound=True): + trading_schedule, compound=True): """ Find the latest known interest rate for a given duration within a date range. @@ -269,7 +261,9 @@ def choose_treasury(select_treasury, treasury_curves, start_date, end_date, prev_day) if rate is not None: search_day = prev_day - search_dist = search_day_distance(end_date, prev_day, env) + search_dist = trading_schedule.execution_day_distance( + end_date, prev_day + ) break if search_day: diff --git a/zipline/finance/trading.py b/zipline/finance/trading.py index 10fb1828..ed234982 100644 --- a/zipline/finance/trading.py +++ b/zipline/finance/trading.py @@ -13,22 +13,15 @@ # See the License for the specific language governing permissions and # limitations under the License. -import bisect import logbook import datetime -import pandas as pd -import numpy as np from six import string_types from sqlalchemy import create_engine from zipline.assets import AssetDBWriter, AssetFinder from zipline.data.loader import load_market_data -from zipline.utils import tradingcalendar -from zipline.errors import ( - NoFurtherDataError -) -from zipline.utils.memoize import remember_last, lazyval +from zipline.utils.calendars import default_nyse_schedule log = logbook.Logger('Trading') @@ -80,36 +73,26 @@ class TradingEnvironment(object): # reference to a TradingEnvironment PERSISTENT_TOKEN = "" - def __init__(self, - load=None, - bm_symbol='^GSPC', - exchange_tz="US/Eastern", - min_date=None, - max_date=None, - env_trading_calendar=tradingcalendar, - asset_db_path=':memory:'): - self.trading_day = env_trading_calendar.trading_day.copy() - - # `tc_td` is short for "trading calendar trading days" - tc_td = env_trading_calendar.trading_days - - self.trading_days = tc_td[tc_td.slice_indexer(min_date, max_date)] - - self.first_trading_day = self.trading_days[0] - self.last_trading_day = self.trading_days[-1] - - self.early_closes = env_trading_calendar.get_early_closes( - self.first_trading_day, self.last_trading_day) - - self.open_and_closes = env_trading_calendar.open_and_closes.loc[ - self.trading_days] + def __init__( + self, + load=None, + bm_symbol='^GSPC', + exchange_tz="US/Eastern", + min_date=None, + max_date=None, + trading_schedule=default_nyse_schedule, + asset_db_path=':memory:' + ): self.bm_symbol = bm_symbol if not load: load = load_market_data - self.benchmark_returns, self.treasury_curves = \ - load(self.trading_day, self.trading_days, self.bm_symbol) + self.benchmark_returns, self.treasury_curves = load( + trading_schedule.day, + trading_schedule.schedule.index, + self.bm_symbol, + ) if max_date: tr_c = self.treasury_curves @@ -133,10 +116,6 @@ class TradingEnvironment(object): else: self.asset_finder = None - @lazyval - def market_minutes(self): - return self.minutes_for_days_in_range(self.first_trading_day, - self.last_trading_day) def write_data(self, **kwargs): """Write data into the asset_db. @@ -148,284 +127,13 @@ class TradingEnvironment(object): """ AssetDBWriter(self.engine).write(**kwargs) - def normalize_date(self, test_date): - test_date = pd.Timestamp(test_date, tz='UTC') - return pd.tseries.tools.normalize_date(test_date) - - def utc_dt_in_exchange(self, dt): - return pd.Timestamp(dt).tz_convert(self.exchange_tz) - - def exchange_dt_in_utc(self, dt): - return pd.Timestamp(dt, tz=self.exchange_tz).tz_convert('UTC') - - def is_market_hours(self, test_date): - if not self.is_trading_day(test_date): - return False - - mkt_open, mkt_close = self.get_open_and_close(test_date) - return test_date >= mkt_open and test_date <= mkt_close - - def is_trading_day(self, test_date): - dt = self.normalize_date(test_date) - return (dt in self.trading_days) - - def next_trading_day(self, test_date): - dt = self.normalize_date(test_date) - delta = datetime.timedelta(days=1) - - while dt <= self.last_trading_day: - dt += delta - if dt in self.trading_days: - return dt - - return None - - def previous_trading_day(self, test_date): - dt = self.normalize_date(test_date) - delta = datetime.timedelta(days=-1) - - while self.first_trading_day < dt: - dt += delta - if dt in self.trading_days: - return dt - - return None - - def add_trading_days(self, n, date): - """ - Adds n trading days to date. If this would fall outside of the - trading calendar, a NoFurtherDataError is raised. - - :Arguments: - n : int - The number of days to add to date, this can be positive or - negative. - date : datetime - The date to add to. - - :Returns: - new_date : datetime - n trading days added to date. - """ - if n == 1: - return self.next_trading_day(date) - if n == -1: - return self.previous_trading_day(date) - - idx = self.get_index(date) + n - if idx < 0 or idx >= len(self.trading_days): - raise NoFurtherDataError( - msg='Cannot add %d days to %s' % (n, date) - ) - - return self.trading_days[idx] - - def days_in_range(self, start, end): - start_date = self.normalize_date(start) - end_date = self.normalize_date(end) - - mask = ((self.trading_days >= start_date) & - (self.trading_days <= end_date)) - return self.trading_days[mask] - - def opens_in_range(self, start, end): - return self.open_and_closes.market_open.loc[start:end] - - def closes_in_range(self, start, end): - return self.open_and_closes.market_close.loc[start:end] - - def minutes_for_days_in_range(self, start, end): - """ - Get all market minutes for the days between start and end, inclusive. - """ - start_date = self.normalize_date(start) - end_date = self.normalize_date(end) - - o_and_c = self.open_and_closes[ - self.open_and_closes.index.slice_indexer(start_date, end_date)] - - opens = o_and_c.market_open - closes = o_and_c.market_close - - one_min = pd.Timedelta(1, unit='m') - - all_minutes = [] - for i in range(0, len(o_and_c.index)): - market_open = opens[i] - market_close = closes[i] - day_minutes = np.arange(market_open, market_close + one_min, - dtype='datetime64[m]') - all_minutes.append(day_minutes) - - # Concatenate all minutes and truncate minutes before start/after end. - return pd.DatetimeIndex( - np.concatenate(all_minutes), copy=False, tz='UTC', - ) - - def next_open_and_close(self, start_date): - """ - Given the start_date, returns the next open and close of - the market. - """ - next_open = self.next_trading_day(start_date) - - if next_open is None: - raise NoFurtherDataError( - msg=("Attempt to backtest beyond available history. " - "Last known date: %s" % self.last_trading_day) - ) - - return self.get_open_and_close(next_open) - - def previous_open_and_close(self, start_date): - """ - Given the start_date, returns the previous open and close of the - market. - """ - previous = self.previous_trading_day(start_date) - - if previous is None: - raise NoFurtherDataError( - msg=("Attempt to backtest beyond available history. " - "First known date: %s" % self.first_trading_day) - ) - return self.get_open_and_close(previous) - - def next_market_minute(self, start): - """ - Get the next market minute after @start. This is either the immediate - next minute, the open of the same day if @start is before the market - open on a trading day, or the open of the next market day after @start. - """ - if self.is_trading_day(start): - market_open, market_close = self.get_open_and_close(start) - # If start before market open on a trading day, return market open. - if start < market_open: - return market_open - # If start is during trading hours, then get the next minute. - elif start < market_close: - return start + datetime.timedelta(minutes=1) - # If start is not in a trading day, or is after the market close - # then return the open of the *next* trading day. - return self.next_open_and_close(start)[0] - - @remember_last - def previous_market_minute(self, start): - """ - Get the next market minute before @start. This is either the immediate - previous minute, the close of the same day if @start is after the close - on a trading day, or the close of the market day before @start. - """ - if self.is_trading_day(start): - market_open, market_close = self.get_open_and_close(start) - # If start after the market close, return market close. - if start > market_close: - return market_close - # If start is during trading hours, then get previous minute. - if start > market_open: - return start - datetime.timedelta(minutes=1) - # If start is not a trading day, or is before the market open - # then return the close of the *previous* trading day. - return self.previous_open_and_close(start)[1] - - def get_open_and_close(self, day): - index = self.open_and_closes.index.get_loc(day.date()) - todays_minutes = self.open_and_closes.iloc[index] - return todays_minutes[0], todays_minutes[1] - - def market_minutes_for_day(self, stamp): - market_open, market_close = self.get_open_and_close(stamp) - return pd.date_range(market_open, market_close, freq='T') - - def open_close_window(self, start, count, offset=0, step=1): - """ - Return a DataFrame containing `count` market opens and closes, - beginning with `start` + `offset` days and continuing `step` minutes at - a time. - """ - # TODO: Correctly handle end of data. - start_idx = self.get_index(start) + offset - stop_idx = start_idx + (count * step) - - index = np.arange(start_idx, stop_idx, step) - - return self.open_and_closes.iloc[index] - - def market_minute_window(self, start, count, step=1): - """ - Return a DatetimeIndex containing `count` market minutes, starting with - `start` and continuing `step` minutes at a time. - """ - if not self.is_market_hours(start): - raise ValueError("market_minute_window starting at " - "non-market time {minute}".format(minute=start)) - - all_minutes = [] - - current_day_minutes = self.market_minutes_for_day(start) - first_minute_idx = current_day_minutes.searchsorted(start) - minutes_in_range = current_day_minutes[first_minute_idx::step] - - # Build up list of lists of days' market minutes until we have count - # minutes stored altogether. - while True: - - if len(minutes_in_range) >= count: - # Truncate off extra minutes - minutes_in_range = minutes_in_range[:count] - - all_minutes.append(minutes_in_range) - count -= len(minutes_in_range) - if count <= 0: - break - - if step > 0: - start, _ = self.next_open_and_close(start) - current_day_minutes = self.market_minutes_for_day(start) - else: - _, start = self.previous_open_and_close(start) - current_day_minutes = self.market_minutes_for_day(start) - - minutes_in_range = current_day_minutes[::step] - - # Concatenate all the accumulated minutes. - return pd.DatetimeIndex( - np.concatenate(all_minutes), copy=False, tz='UTC', - ) - - def trading_day_distance(self, first_date, second_date): - first_date = self.normalize_date(first_date) - second_date = self.normalize_date(second_date) - - # TODO: May be able to replace the following with searchsorted. - # Find leftmost item greater than or equal to day - i = bisect.bisect_left(self.trading_days, first_date) - if i == len(self.trading_days): # nothing found - return None - j = bisect.bisect_left(self.trading_days, second_date) - if j == len(self.trading_days): - return None - - return j - i - - def get_index(self, dt): - """ - Return the index of the given @dt, or the index of the preceding - trading day if the given dt is not in the trading calendar. - """ - ndt = self.normalize_date(dt) - if ndt in self.trading_days: - return self.trading_days.searchsorted(ndt) - else: - return self.trading_days.searchsorted(ndt) - 1 - class SimulationParameters(object): def __init__(self, period_start, period_end, capital_base=10e3, emission_rate='daily', data_frequency='daily', - env=None, + trading_schedule=None, arena='backtest'): self.period_start = period_start @@ -438,60 +146,56 @@ class SimulationParameters(object): # copied to algorithm's environment for runtime access self.arena = arena - if env is not None: - self.update_internal_from_env(env=env) + if trading_schedule is not None: + self.update_internal_from_trading_schedule( + trading_schedule=trading_schedule + ) - def update_internal_from_env(self, env): + def update_internal_from_trading_schedule(self, trading_schedule): assert self.period_start <= self.period_end, \ "Period start falls after period end." - assert self.period_start <= env.last_trading_day, \ + assert self.period_start <= trading_schedule.last_execution_day, \ "Period start falls after the last known trading day." - assert self.period_end >= env.first_trading_day, \ + assert self.period_end >= trading_schedule.first_execution_day, \ "Period end falls before the first known trading day." - self.first_open = self._calculate_first_open(env) - self.last_close = self._calculate_last_close(env) + self.first_open = self._calculate_first_open(trading_schedule) + self.last_close = self._calculate_last_close(trading_schedule) - start_index = env.get_index(self.first_open) - end_index = env.get_index(self.last_close) + # Take the length of an inclusive slice of trading dates + self.trading_days = trading_schedule.trading_dates( + self.first_open, self.last_close + ) + self.days_in_period = len(self.trading_days) - # take an inclusive slice of the environment's - # trading_days. - self.trading_days = env.trading_days[start_index:end_index + 1] - - def _calculate_first_open(self, env): + def _calculate_first_open(self, trading_schedule): """ Finds the first trading day on or after self.period_start. """ first_open = self.period_start one_day = datetime.timedelta(days=1) - while not env.is_trading_day(first_open): + while not trading_schedule.is_executing_on_day(first_open): first_open = first_open + one_day - mkt_open, _ = env.get_open_and_close(first_open) + mkt_open, _ = trading_schedule.start_and_end(first_open) return mkt_open - def _calculate_last_close(self, env): + def _calculate_last_close(self, trading_schedule): """ Finds the last trading day on or before self.period_end """ last_close = self.period_end one_day = datetime.timedelta(days=1) - while not env.is_trading_day(last_close): + while not trading_schedule.is_executing_on_day(last_close): last_close = last_close - one_day - _, mkt_close = env.get_open_and_close(last_close) + _, mkt_close = trading_schedule.start_and_end(last_close) return mkt_close - @property - def days_in_period(self): - """return the number of trading days within the period [start, end)""" - return len(self.trading_days) - def __repr__(self): return """ {class_name}( diff --git a/zipline/sources/benchmark_source.py b/zipline/sources/benchmark_source.py index 82f23f93..70241bd7 100644 --- a/zipline/sources/benchmark_source.py +++ b/zipline/sources/benchmark_source.py @@ -23,8 +23,8 @@ from zipline.errors import ( class BenchmarkSource(object): - def __init__(self, benchmark_sid, env, trading_days, data_portal, - emission_rate="daily"): + def __init__(self, benchmark_sid, env, trading_schedule, trading_days, + data_portal, emission_rate="daily"): self.benchmark_sid = benchmark_sid self.env = env self.trading_days = trading_days @@ -55,7 +55,7 @@ class BenchmarkSource(object): if self.emission_rate == "minute": # we need to take the env's benchmark returns, which are daily, # and resample them to minute - minutes = env.minutes_for_days_in_range( + minutes = trading_schedule.execution_minutes_for_days_in_range( start=trading_days[0], end=trading_days[-1] ) diff --git a/zipline/sources/simulated.py b/zipline/sources/simulated.py index 8fd65806..272f5c78 100644 --- a/zipline/sources/simulated.py +++ b/zipline/sources/simulated.py @@ -21,8 +21,8 @@ from datetime import timedelta import pandas as pd from zipline.sources.data_source import DataSource -from zipline.utils import tradingcalendar as calendar_nyse from zipline.gens.utils import hash_args +from zipline.utils.calendars import default_nyse_schedule class RandomWalkSource(DataSource): @@ -35,7 +35,8 @@ class RandomWalkSource(DataSource): VALID_FREQS = frozenset(('daily', 'minute')) def __init__(self, start_prices=None, freq='minute', start=None, - end=None, drift=0.1, sd=0.1, calendar=calendar_nyse): + end=None, drift=0.1, sd=0.1, + trading_schedule=default_nyse_schedule): """ :Arguments: start_prices : dict @@ -52,8 +53,8 @@ class RandomWalkSource(DataSource): Constant drift of the price series. sd: float Standard deviation of the price series. - calendar : calendar object - Calendar to use. + trading_schedule : TradingSchedule object + TradingSchedule to use. See zipline.utils for different choices. :Example: @@ -66,7 +67,7 @@ class RandomWalkSource(DataSource): """ # Hash_value for downstream sorting. self.arg_string = hash_args(start_prices, freq, start, end, - calendar.__name__) + trading_schedule.__name__) if freq not in self.VALID_FREQS: raise ValueError('%s not in %s' % (freq, self.VALID_FREQS)) @@ -78,13 +79,13 @@ class RandomWalkSource(DataSource): else: self.start_prices = start_prices - self.calendar = calendar + self.trading_schedule = trading_schedule if start is None: - self.start = calendar.start + self.start = trading_schedule.first_execution_day else: self.start = start if end is None: - self.end = calendar.end_base + self.end = trading_schedule.last_execution_day else: self.end = end @@ -94,7 +95,7 @@ class RandomWalkSource(DataSource): self.sids = self.start_prices.keys() self.open_and_closes = \ - calendar.open_and_closes[self.start:self.end] + trading_schedule.schedule[self.start:self.end] self._raw_data = None diff --git a/zipline/sources/test_source.py b/zipline/sources/test_source.py index d870ab6a..cbbe5494 100644 --- a/zipline/sources/test_source.py +++ b/zipline/sources/test_source.py @@ -52,7 +52,7 @@ def create_trade(sid, price, amount, datetime, source_id="test_factory"): def date_gen(start, end, - env, + trading_schedule, delta=timedelta(minutes=1), repeats=None): """ @@ -73,13 +73,13 @@ def date_gen(start, """ cur = cur + delta - if not (env.is_trading_day + if not (trading_schedule.is_executing_on_day if daily_delta - else env.is_market_hours)(cur): + else trading_schedule.is_executing_on_minute)(cur): if daily_delta: - return env.next_trading_day(cur) + return trading_schedule.next_execution_day(cur) else: - return env.next_open_and_close(cur)[0] + return trading_schedule.next_start_and_end(cur)[0] else: return cur @@ -109,11 +109,12 @@ class SpecificEquityTrades(object): delta : timedelta between internal events filter : filter to remove the sids """ - def __init__(self, env, *args, **kwargs): + def __init__(self, env, trading_schedule, *args, **kwargs): # We shouldn't get any positional arguments. assert len(args) == 0 self.env = env + self.trading_schedule = trading_schedule # Default to None for event_list and filter. self.event_list = kwargs.get('event_list') @@ -205,14 +206,14 @@ class SpecificEquityTrades(object): end=self.end, delta=self.delta, repeats=len(self.sids), - env=self.env, + trading_schedule=self.trading_schedule, ) else: date_generator = date_gen( start=self.start, end=self.end, delta=self.delta, - env=self.env, + trading_schedule=self.trading_schedule, ) source_id = self.get_hash() diff --git a/zipline/testing/core.py b/zipline/testing/core.py index 4e997975..4b462412 100644 --- a/zipline/testing/core.py +++ b/zipline/testing/core.py @@ -47,6 +47,7 @@ from zipline.utils import security_list from zipline.utils.input_validation import expect_dimensions from zipline.utils.sentinel import sentinel from zipline.utils.tradingcalendar import trading_days +from zipline.utils.calendars import default_nyse_schedule import numpy as np from numpy import float64 @@ -425,10 +426,10 @@ class ExplodingObject(object): raise UnexpectedAttributeAccess(name) -def write_minute_data(env, tempdir, minutes, sids): +def write_minute_data(trading_schedule, tempdir, minutes, sids): write_bcolz_minute_data( - env, - env.days_in_range(minutes[0], minutes[-1]), + trading_schedule, + trading_schedule.execution_days_in_range(minutes[0], minutes[-1]), tempdir.path, create_minute_bar_data(minutes, sids), ) @@ -475,39 +476,41 @@ def write_daily_data(tempdir, sim_params, sids): return path -def create_data_portal(env, tempdir, sim_params, sids, adjustment_reader=None): +def create_data_portal(env, tempdir, sim_params, sids, trading_schedule, + adjustment_reader=None): if sim_params.data_frequency == "daily": daily_path = write_daily_data(tempdir, sim_params, sids) equity_daily_reader = BcolzDailyBarReader(daily_path) return DataPortal( - env, + env, trading_schedule, first_trading_day=equity_daily_reader.first_trading_day, equity_daily_reader=equity_daily_reader, adjustment_reader=adjustment_reader ) else: - minutes = env.minutes_for_days_in_range( + minutes = trading_schedule.execution_minutes_for_days_in_range( sim_params.first_open, sim_params.last_close ) - minute_path = write_minute_data(env, tempdir, minutes, sids) + minute_path = write_minute_data(trading_schedule, tempdir, minutes, + sids) equity_minute_reader = BcolzMinuteBarReader(minute_path) return DataPortal( - env, + env, trading_schedule, first_trading_day=equity_minute_reader.first_trading_day, equity_minute_reader=equity_minute_reader, adjustment_reader=adjustment_reader ) -def write_bcolz_minute_data(env, days, path, data): - market_opens = env.open_and_closes.market_open.loc[days] - market_closes = env.open_and_closes.market_close.loc[days] +def write_bcolz_minute_data(trading_schedule, days, path, data): + market_opens = trading_schedule.schedule.loc[days].market_open + market_closes = trading_schedule.schedule.loc[days].market_close BcolzMinuteBarWriter( days[0], @@ -518,14 +521,16 @@ def write_bcolz_minute_data(env, days, path, data): ).write(data) -def create_minute_df_for_asset(env, +def create_minute_df_for_asset(trading_schedule, start_dt, end_dt, interval=1, start_val=1, minute_blacklist=None): - asset_minutes = env.minutes_for_days_in_range(start_dt, end_dt) + asset_minutes = trading_schedule.execution_minutes_for_days_in_range( + start_dt, end_dt + ) minutes_count = len(asset_minutes) minutes_arr = np.array(range(start_val, start_val + minutes_count)) @@ -553,8 +558,9 @@ def create_minute_df_for_asset(env, return df -def create_daily_df_for_asset(env, start_day, end_day, interval=1): - days = env.days_in_range(start_day, end_day) +def create_daily_df_for_asset(trading_schedule, start_day, end_day, + interval=1): + days = trading_schedule.execution_days_in_range(start_day, end_day) days_count = len(days) days_arr = np.arange(days_count) + 2 @@ -608,8 +614,8 @@ def trades_by_sid_to_dfs(trades_by_sid, index): ) -def create_data_portal_from_trade_history(env, tempdir, sim_params, - trades_by_sid): +def create_data_portal_from_trade_history(env, trading_schedule, tempdir, + sim_params, trades_by_sid): if sim_params.data_frequency == "daily": path = os.path.join(tempdir.path, "testdaily.bcolz") BcolzDailyBarWriter(path, sim_params.trading_days).write( @@ -619,12 +625,12 @@ def create_data_portal_from_trade_history(env, tempdir, sim_params, equity_daily_reader = BcolzDailyBarReader(path) return DataPortal( - env, + env, trading_schedule, first_trading_day=equity_daily_reader.first_trading_day, equity_daily_reader=equity_daily_reader, ) else: - minutes = env.minutes_for_days_in_range( + minutes = trading_schedule.execution_minutes_for_days_in_range( sim_params.first_open, sim_params.last_close ) @@ -659,8 +665,8 @@ def create_data_portal_from_trade_history(env, tempdir, sim_params, }).set_index("dt") write_bcolz_minute_data( - env, - env.days_in_range( + trading_schedule, + trading_schedule.execution_days_in_range( sim_params.first_open, sim_params.last_close ), @@ -671,7 +677,7 @@ def create_data_portal_from_trade_history(env, tempdir, sim_params, equity_minute_reader = BcolzMinuteBarReader(tempdir.path) return DataPortal( - env, + env, trading_schedule, first_trading_day=equity_minute_reader.first_trading_day, equity_minute_reader=equity_minute_reader, ) @@ -679,11 +685,13 @@ def create_data_portal_from_trade_history(env, tempdir, sim_params, class FakeDataPortal(DataPortal): - def __init__(self, env=None, first_trading_day=None): + def __init__(self, env=None, trading_schedule=default_nyse_schedule, + first_trading_day=None): if env is None: env = TradingEnvironment() - super(FakeDataPortal, self).__init__(env, first_trading_day) + super(FakeDataPortal, self).__init__(env, trading_schedule, + first_trading_day) def get_spot_value(self, asset, field, dt, data_frequency): if field == "volume": @@ -712,8 +720,9 @@ class FetcherDataPortal(DataPortal): Mock dataportal that returns fake data for history and non-fetcher spot value. """ - def __init__(self, env, first_trading_day=None): - super(FetcherDataPortal, self).__init__(env, first_trading_day) + def __init__(self, env, trading_schedule, first_trading_day=None): + super(FetcherDataPortal, self).__init__(env, trading_schedule, + first_trading_day) def get_spot_value(self, asset, field, dt, data_frequency): # if this is a fetcher field, exercise the regular code path diff --git a/zipline/testing/fixtures.py b/zipline/testing/fixtures.py index b5129f0a..eac58d26 100644 --- a/zipline/testing/fixtures.py +++ b/zipline/testing/fixtures.py @@ -33,7 +33,7 @@ from ..data.minute_bars import ( ) from ..finance.trading import TradingEnvironment -from ..utils import tradingcalendar, factory +from ..utils import factory from ..utils.classproperty import classproperty from ..utils.final import FinalMeta, final from ..utils.metautils import with_metaclasses @@ -47,6 +47,7 @@ from zipline.pipeline.loaders.utils import ( get_values_for_date_ranges, zip_with_dates ) +from zipline.utils.calendars import default_nyse_schedule class ZiplineTestCase(with_metaclass(FinalMeta, TestCase)): @@ -399,7 +400,7 @@ class WithTradingEnvironment(WithAssetFinder): """ TRADING_ENV_MIN_DATE = None TRADING_ENV_MAX_DATE = None - TRADING_ENV_TRADING_CALENDAR = tradingcalendar + TRADING_ENV_TRADING_SCHEDULE = default_nyse_schedule @classmethod def make_load_function(cls): @@ -412,7 +413,7 @@ class WithTradingEnvironment(WithAssetFinder): asset_db_path=cls.asset_finder.engine, min_date=cls.TRADING_ENV_MIN_DATE, max_date=cls.TRADING_ENV_MAX_DATE, - env_trading_calendar=cls.TRADING_ENV_TRADING_CALENDAR, + trading_schedule=cls.TRADING_ENV_TRADING_SCHEDULE, ) @classmethod @@ -611,6 +612,7 @@ class WithBcolzDailyBarReader(WithTradingEnvironment, WithTmpDir): BCOLZ_DAILY_BAR_END_DATE = alias('END_DATE') BCOLZ_DAILY_BAR_READ_ALL_THRESHOLD = None BCOLZ_DAILY_BAR_SOURCE_FROM_MINUTE = False + BCOLZ_TRADING_SCHEDULE = default_nyse_schedule # allows WithBcolzDailyBarReaderFromCSVs to call the `write_csvs` method # without needing to reimplement `init_class_fixtures` _write_method_name = 'write' diff --git a/zipline/utils/calendars/__init__.py b/zipline/utils/calendars/__init__.py new file mode 100644 index 00000000..c4d74f24 --- /dev/null +++ b/zipline/utils/calendars/__init__.py @@ -0,0 +1,26 @@ +# +# Copyright 2016 Quantopian, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from .exchange_calendar import ( + ExchangeCalendar, get_calendar +) +from .trading_schedule import ( + TradingSchedule, ExchangeTradingSchedule, default_nyse_schedule +) +from .calendar_helpers import normalize_date + +__all__ = ['get_calendar', 'ExchangeCalendar', 'TradingSchedule', + 'ExchangeTradingSchedule', 'default_nyse_schedule', + 'normalize_date'] diff --git a/zipline/utils/calendars/calendar_helpers.py b/zipline/utils/calendars/calendar_helpers.py new file mode 100644 index 00000000..afdcaff4 --- /dev/null +++ b/zipline/utils/calendars/calendar_helpers.py @@ -0,0 +1,199 @@ +# +# Copyright 2016 Quantopian, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import pandas as pd +import numpy as np +import bisect + +from zipline.errors import NoFurtherDataError + + +def normalize_date(date): + date = pd.Timestamp(date, tz='UTC') + return pd.tseries.tools.normalize_date(date) + +def delta_from_time(t): + """ + Convert a datetime.time into a timedelta. + """ + return pd.Timedelta( + hours=t.hour, + minutes=t.minute, + seconds=t.second, + ) + +def _get_index(dt, all_trading_days): + """ + Return the index of the given @dt, or the index of the preceding + trading day if the given dt is not in the trading calendar. + """ + ndt = normalize_date(dt) + if ndt in all_trading_days: + return all_trading_days.searchsorted(ndt) + else: + return all_trading_days.searchsorted(ndt) - 1 + +# The following methods are intended to be inserted in both the +# ExchangeCalendar and TradingSchedule classes with partial hooks to those +# class' methods. These methods live in the helpers module to avoid code +# duplication. + +def next_scheduled_day(date, last_trading_day, is_scheduled_day_hook): + dt = normalize_date(date) + delta = pd.Timedelta(days=1) + + while dt <= last_trading_day: + dt += delta + if is_scheduled_day_hook(dt): + return dt + return None + +def previous_scheduled_day(date, first_trading_day, is_scheduled_day_hook): + dt = normalize_date(date) + delta = pd.Timedelta(days=-1) + + while first_trading_day < dt: + dt += delta + if is_scheduled_day_hook(dt): + return dt + return None + +def next_open_and_close(date, open_and_close_hook, + next_scheduled_day_hook): + return open_and_close_hook(next_scheduled_day_hook(date)) + +def previous_open_and_close(date, open_and_close_hook, + previous_scheduled_day_hook): + return open_and_close_hook(previous_scheduled_day_hook(date)) + +def scheduled_day_distance(first_date, second_date, all_days): + first_date = normalize_date(first_date) + second_date = normalize_date(second_date) + + i = bisect.bisect_left(all_days, first_date) + if i == len(all_days): # nothing found + return None + j = bisect.bisect_left(all_days, second_date) + if j == len(all_days): + return None + distance = j - 1 + assert distance >= 0 + return distance + +def minutes_for_day(day, open_and_close_hook): + start, end = open_and_close_hook(day) + return pd.date_range(start, end, freq='T') + +def days_in_range(start, end, all_days): + """ + Get all execution days between start and end, + inclusive. + """ + start_date = normalize_date(start) + end_date = normalize_date(end) + + mask = ((all_days >= start_date) & (all_days <= end_date)) + return all_days[mask] + +def minutes_for_days_in_range(start, end, days_in_range_hook, + minutes_for_day_hook): + """ + Get all execution minutes for the days between start and end, + inclusive. + """ + start_date = normalize_date(start) + end_date = normalize_date(end) + + all_minutes = [] + for day in days_in_range_hook(start_date, end_date): + day_minutes = minutes_for_day_hook(day) + all_minutes.append(day_minutes) + + # Concatenate all minutes and truncate minutes before start/after end. + return pd.DatetimeIndex(np.concatenate(all_minutes), copy=False, tz='UTC') + +def add_scheduled_days(n, date, next_scheduled_day_hook, + previous_scheduled_day_hook, all_trading_days): + """ + Adds n trading days to date. If this would fall outside of the + trading calendar, a NoFurtherDataError is raised. + + :Arguments: + n : int + The number of days to add to date, this can be positive or + negative. + date : datetime + The date to add to. + + :Returns: + new_date : datetime + n trading days added to date. + """ + if n == 1: + return next_scheduled_day_hook(date) + if n == -1: + return previous_scheduled_day_hook(date) + + idx = _get_index(date, all_trading_days) + n + if idx < 0 or idx >= len(all_trading_days): + raise NoFurtherDataError( + msg='Cannot add %d days to %s' % (n, date) + ) + + return all_trading_days[idx] + +def all_scheduled_minutes(all_days, minutes_for_days_in_range_hook): + first_day = all_days[0] + last_day = all_days[-1] + return minutes_for_days_in_range_hook(first_day, last_day) + +def next_scheduled_minute(start, is_scheduled_day_hook, open_and_close_hook, + next_open_and_close_hook): + """ + Get the next market minute after @start. This is either the immediate + next minute, the open of the same day if @start is before the market + open on a trading day, or the open of the next market day after @start. + """ + if is_scheduled_day_hook(start): + market_open, market_close = open_and_close_hook(start) + # If start before market open on a trading day, return market open. + if start < market_open: + return market_open + # If start is during trading hours, then get the next minute. + elif start < market_close: + return start + pd.Timedelta(minutes=1) + # If start is not in a trading day, or is after the market close + # then return the open of the *next* trading day. + return next_open_and_close_hook(start)[0] + +def previous_scheduled_minute(start, is_scheduled_day_hook, + open_and_close_hook, + previous_open_and_close_hook): + """ + Get the next market minute before @start. This is either the immediate + previous minute, the close of the same day if @start is after the close + on a trading day, or the close of the market day before @start. + """ + if is_scheduled_day_hook(start): + market_open, market_close = open_and_close_hook(start) + # If start after the market close, return market close. + if start > market_close: + return market_close + # If start is during trading hours, then get previous minute. + if start > market_open: + return start - pd.Timedelta(minutes=1) + # If start is not a trading day, or is before the market open + # then return the close of the *previous* trading day. + return previous_open_and_close_hook(start)[1] diff --git a/zipline/utils/calendars/exchange_calendar.py b/zipline/utils/calendars/exchange_calendar.py new file mode 100644 index 00000000..547aee39 --- /dev/null +++ b/zipline/utils/calendars/exchange_calendar.py @@ -0,0 +1,497 @@ +# +# Copyright 2016 Quantopian, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from abc import ( + ABCMeta, + abstractproperty, + abstractmethod, +) +from functools import partial + +import pandas as pd +from pandas import ( + DataFrame, + date_range, + DateOffset, + DatetimeIndex, +) +from pandas.tseries.offsets import CustomBusinessDay +from six import with_metaclass + +from zipline.errors import ( + InvalidCalendarName, + CalendarNameCollision, +) +from zipline.utils.memoize import remember_last + +from .calendar_helpers import ( + next_scheduled_day, + previous_scheduled_day, + next_open_and_close, + previous_open_and_close, + scheduled_day_distance, + minutes_for_day, + days_in_range, + minutes_for_days_in_range, + add_scheduled_days, + all_scheduled_minutes, + next_scheduled_minute, + previous_scheduled_minute, +) + +start_default = pd.Timestamp('1990-01-01', tz='UTC') +end_base = pd.Timestamp('today', tz='UTC') +# Give an aggressive buffer for logic that needs to use the next trading +# day or minute. +end_default = end_base + pd.Timedelta(days=365) + + +def days_at_time(days, t, tz, day_offset=0): + """ + Shift an index of days to time t, interpreted in tz. + + Overwrites any existing tz info on the input. + + Parameters + ---------- + days : DatetimeIndex + The "base" time which we want to change. + t : datetime.time + The time we want to offset @days by + tz : pytz.timezone + The timezone which these times represent + day_offset : int + The number of days we want to offset @days by + """ + days = DatetimeIndex(days).tz_localize(None).tz_localize(tz) + days_offset = days + DateOffset(day_offset) + return days_offset.shift( + 1, freq=DateOffset(hour=t.hour, minute=t.minute, second=t.second) + ).tz_convert('UTC') + + +def holidays_at_time(calendar, start, end, time, tz): + return days_at_time( + calendar.holidays( + # Workaround for https://github.com/pydata/pandas/issues/9825. + start.tz_localize(None), + end.tz_localize(None), + ), + time, + tz=tz, + ) + + +def _overwrite_special_dates(midnight_utcs, + opens_or_closes, + special_opens_or_closes): + """ + Overwrite dates in open_or_closes with corresponding dates in + special_opens_or_closes, using midnight_utcs for alignment. + """ + # Short circuit when nothing to apply. + if not len(special_opens_or_closes): + return + + len_m, len_oc = len(midnight_utcs), len(opens_or_closes) + if len_m != len_oc: + raise ValueError( + "Found misaligned dates while building calendar.\n" + "Expected midnight_utcs to be the same length as open_or_closes,\n" + "but len(midnight_utcs)=%d, len(open_or_closes)=%d" % len_m, len_oc + ) + + # Find the array indices corresponding to each special date. + indexer = midnight_utcs.get_indexer(special_opens_or_closes.normalize()) + + # -1 indicates that no corresponding entry was found. If any -1s are + # present, then we have special dates that doesn't correspond to any + # trading day. + if -1 in indexer: + bad_dates = list(special_opens_or_closes[indexer == -1]) + raise ValueError("Special dates %s are not trading days." % bad_dates) + + # NOTE: This is a slightly dirty hack. We're in-place overwriting the + # internal data of an Index, which is conceptually immutable. Since we're + # maintaining sorting, this should be ok, but this is a good place to + # sanity check if things start going haywire with calendar computations. + opens_or_closes.values[indexer] = special_opens_or_closes.values + + +class ExchangeCalendar(with_metaclass(ABCMeta)): + """ + An ExchangeCalendar represents the timing information of a single market + exchange. + + Properties + ---------- + name : str + The name of this exchange calendar. + e.g.: 'NYSE', 'LSE', 'CME Energy' + tz : timezone + The native timezone of the exchange. + """ + + def __init__(self, start=start_default, end=end_default): + tz = self.tz + open_offset = self.open_offset + close_offset = self.close_offset + + # Define those days on which the exchange is usually open. + self.day = CustomBusinessDay( + holidays=self.holidays_adhoc, + calendar=self.holidays_calendar, + ) + + # Midnight in UTC for each trading day. + _all_days = date_range(start, end, freq=self.day, tz='UTC') + + # `DatetimeIndex`s of standard opens/closes for each day. + _opens = days_at_time(_all_days, self.open_time, tz, open_offset) + _closes = days_at_time(_all_days, self.close_time, tz, close_offset) + + # `DatetimeIndex`s of nonstandard opens/closes + _special_opens = self._special_opens(start, end) + _special_closes = self._special_closes(start, end) + + # Overwrite the special opens and closes on top of the standard ones. + _overwrite_special_dates(_all_days, _opens, _special_opens) + _overwrite_special_dates(_all_days, _closes, _special_closes) + + # In pandas 0.16.1 _opens and _closes will lose their timezone + # information. This looks like it has been resolved in 0.17.1. + # http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#datetime-with-tz # noqa + self.schedule = DataFrame( + index=_all_days, + columns=['market_open', 'market_close'], + data={ + 'market_open': _opens, + 'market_close': _closes, + }, + dtype='datetime64[ns]', + ) + + self.first_trading_day = _all_days[0] + self.last_trading_day = _all_days[-1] + self.early_closes = _special_closes.map(self.session_date) + + # Assign the partial calendar helpers + self.next_trading_day = partial( + next_scheduled_day, + last_trading_day=self.last_trading_day, + is_scheduled_day_hook=self.is_open_on_day, + ) + self.previous_trading_day = partial( + previous_scheduled_day, + first_trading_day=self.first_trading_day, + is_scheduled_day_hook=self.is_open_on_day, + ) + self.next_open_and_close = partial( + next_open_and_close, + open_and_close_hook=self.open_and_close, + next_scheduled_day_hook=self.next_trading_day, + ) + self.previous_open_and_close = partial( + previous_open_and_close, + open_and_close_hook=self.open_and_close, + previous_scheduled_day_hook=self.previous_trading_day, + ) + self.trading_day_distance = partial( + scheduled_day_distance, + all_days=self.all_trading_days, + ) + self.trading_minutes_for_day = partial( + minutes_for_day, + open_and_close_hook=self.open_and_close, + ) + self.trading_days_in_range = partial( + days_in_range, + all_days=self.all_trading_days, + ) + self.trading_minutes_for_days_in_range = partial( + minutes_for_days_in_range, + days_in_range_hook=self.trading_days_in_range, + minutes_for_day_hook=self.trading_minutes_for_day, + ) + self.add_trading_days = partial( + add_scheduled_days, + next_scheduled_day_hook=self.next_trading_day, + previous_scheduled_day_hook=self.previous_trading_day, + all_trading_days=self.all_trading_days, + ) + self.next_market_minute = partial( + next_scheduled_minute, + is_scheduled_day_hook=self.is_open_on_day, + open_and_close_hook=self.open_and_close, + next_open_and_close_hook=self.next_open_and_close, + ) + self.previous_market_minute = partial( + previous_scheduled_minute, + is_scheduled_day_hook=self.is_open_on_day, + open_and_close_hook=self.open_and_close, + previous_open_and_close_hook=self.previous_open_and_close, + ) + + def _special_dates(self, calendars, ad_hoc_dates, start_date, end_date): + """ + Union an iterable of pairs of the form + + (time, calendar) + + and an iterable of pairs of the form + + (time, [dates]) + + (This is shared logic for computing special opens and special closes.) + """ + tz = self.native_timezone + _dates = DatetimeIndex([], tz='UTC').union_many( + [ + holidays_at_time(calendar, start_date, end_date, time_, tz) + for time_, calendar in calendars + ] + [ + days_at_time(datetimes, time_, tz) + for time_, datetimes in ad_hoc_dates + ] + ) + return _dates[(_dates >= start_date) & (_dates <= end_date)] + + def _special_opens(self, start, end): + return self._special_dates( + self.special_opens_calendars, + self.special_opens_adhoc, + start, + end, + ) + + def _special_closes(self, start, end): + return self._special_dates( + self.special_closes_calendars, + self.special_closes_adhoc, + start, + end, + ) + + @abstractproperty + def name(self): + """ + The name of this exchange calendar. + E.g.: 'NYSE', 'LSE', 'CME Energy' + """ + raise NotImplementedError() + + @abstractproperty + def tz(self): + """ + The native timezone of the exchange. + + SD: Not clear that this needs to be exposed. + """ + raise NotImplementedError() + + @abstractmethod + def is_open_on_minute(self, dt): + """ + Is the exchange open at minute @dt. + + Parameters + ---------- + dt : Timestamp + + Returns + ------- + bool + True if exchange is open at the given dt, otherwise False. + """ + raise NotImplementedError() + + @abstractmethod + def is_open_on_day(self, dt): + """ + Is the exchange open anytime during @dt. + + SD: Need to decide whether this method answers the question: + - Is exchange open at any time during the calendar day containing dt + or + - Is exchange open at any time during the trading session containg dt. + Semantically it seems that the first makes more sense. + + Parameters + ---------- + dt : Timestamp + The UTC-canonicalized date. + + Returns + ------- + bool + True if exchange is open at any time during @dt. + """ + raise NotImplementedError() + + @abstractmethod + def trading_days(self, start, end): + """ + Calculates all of the exchange sessions between the given + start and end. + + SD: Presumably @start and @end are UTC-canonicalized, as our exchange + sessions are. If not, then it's not clear how this method should behave + if @start and @end are both in the middle of the day. + + Parameters + ---------- + start : Timestamp + end : Timestamp + + Returns + ------- + DatetimeIndex + A DatetimeIndex populated with all of the trading days between + the given start and end. + """ + raise NotImplementedError() + + @property + def all_trading_days(self): + return self.schedule.index + + @property + @remember_last + def all_trading_minutes(self): + return all_scheduled_minutes(self.all_trading_days, + self.trading_minutes_for_days_in_range) + + @abstractmethod + def open_and_close(self, date): + """ + Given a UTC-canonicalized date, returns a tuple of timestamps of the + open and close of the exchange session on that date. + + SD: Can @date be an arbitrary datetime, or should we first map it to + and exchange session using session_date. Need to check what the + consumers expect. + + Parameters + ---------- + date : Timestamp + The UTC-canonicalized date whose open and close are needed. + + Returns + ------- + (Timestamp, Timestamp) + The open and close for the given date. + """ + raise NotImplementedError() + + @abstractmethod + def session_date(self, dt): + """ + Given a time, returns the UTC-canonicalized date of the exchange + session in which the time belongs. If the time is not in an exchange + session (while the market is closed), returns the date of the next + exchange session after the time. + + Parameters + ---------- + dt : Timestamp + + Returns + ------- + Timestamp + The date of the exchange session in which dt belongs. + """ + raise NotImplementedError() + + @abstractmethod + def minutes_for_date(self, date): + """ + Given a UTC-canonicalized date, returns a DatetimeIndex of all trading + minutes in the exchange session for that date. + + SD: Sounds like @date can be an arbitrary datetime, and that we should + first map to an exchange session by calling self.session_date. Need to + check what the consumers expect. + + Parameters + ---------- + date : Timestamp + The UTC-canonicalized date whose minutes are needed. + + Returns + ------- + DatetimeIndex + A DatetimeIndex populated with all of the minutes in the + given date. + """ + raise NotImplementedError() + + @abstractmethod + def minute_window(self, start, count, step=1): + """ + Return a DatetimeIndex containing `count` market minutes, starting with + `start` and continuing `step` minutes at a time. + + Parameters + ---------- + start : Timestamp + The start of the window. + count : int + The number of minutes needed. + step : int + The step size by which to increment. + + Returns + ------- + DatetimeIndex + A window with @count minutes, starting with @start a returning + every @step minute. + """ + raise NotImplementedError() + + + +_static_calendars = {} + +_lazy_calendar_names = ['NYSE'] + +def get_calendar(name): + """ + Retrieves an instance of an ExchangeCalendar whose name is given. + + Parameters + ---------- + name : str + The name of the ExchangeCalendar to be retrieved. + """ + # First, check if the calendar is already registered + if name not in _static_calendars: + # The calendar is not registered, so check if it is a lazy calendar + if name not in _lazy_calendar_names: + # It's not a lazy calendar, so raise an exception + raise InvalidCalendarName(calendar_name=name) + + if name is 'NYSE': + from zipline.utils.calendars.nyse_exchange_calendar \ + import NYSEExchangeCalendar + nyse_cal = NYSEExchangeCalendar() + register_calendar(nyse_cal) + + return _static_calendars[name] + + +def register_calendar(calendar): + # Check if we are already holding a calendar with the same name + if calendar.name in _static_calendars: + raise CalendarNameCollision(calendar_name=calendar.name) + _static_calendars[calendar.name] = calendar diff --git a/zipline/utils/calendars/nyse_exchange_calendar.py b/zipline/utils/calendars/nyse_exchange_calendar.py new file mode 100644 index 00000000..59f08ece --- /dev/null +++ b/zipline/utils/calendars/nyse_exchange_calendar.py @@ -0,0 +1,522 @@ +# +# Copyright 2016 Quantopian, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from datetime import time +from itertools import chain + +import numpy as np +import pandas as pd +from dateutil.relativedelta import ( + MO, + TH, +) +from pandas import ( + date_range, + DateOffset, + Timestamp, + Timedelta, +) +from pandas.tseries.holiday import( + AbstractHolidayCalendar, + GoodFriday, + Holiday, + nearest_workday, + sunday_to_monday, + USLaborDay, + USPresidentsDay, + USThanksgivingDay, +) +from pandas.tseries.offsets import Day +from pytz import timezone + +from .exchange_calendar import ExchangeCalendar +from .calendar_helpers import normalize_date + +# Useful resources for making changes to this file: +# http://www.nyse.com/pdfs/closings.pdf +# http://www.stevemorse.org/jcal/whendid.html + +MONDAY, TUESDAY, WEDNESDAY, THURSDAY, FRIDAY, SATURDAY, SUNDAY = range(7) + +US_EASTERN = timezone('US/Eastern') +NYSE_OPEN = time(9, 31) +NYSE_CLOSE = time(16) +NYSE_STANDARD_EARLY_CLOSE = time(13) +# Does the market open or close on a different calendar day, compared to the +# calendar day assigned by the exchang to this session? +NYSE_OPEN_OFFSET = 0 +NYSE_CLOSE_OFFSET = 0 + +# Closings +USNewYearsDay = Holiday( + 'New Years Day', + month=1, + day=1, + # When Jan 1 is a Sunday, NYSE observes the subsequent Monday. When Jan 1 + # Saturday (as in 2005 and 2011), no holiday is observed. + observance=sunday_to_monday +) +USMemorialDay = Holiday( + # NOTE: The definition for Memorial Day is incorrect as of pandas 0.16.0. + # See https://github.com/pydata/pandas/issues/9760. + 'Memorial Day', + month=5, + day=25, + offset=DateOffset(weekday=MO(1)), +) +USMartinLutherKingJrAfter1998 = Holiday( + 'Dr. Martin Luther King Jr. Day', + month=1, + day=1, + # The NYSE didn't observe MLK day as a holiday until 1998. + start_date=Timestamp('1998-01-01'), + offset=DateOffset(weekday=MO(3)), +) +USIndependenceDay = Holiday( + 'July 4th', + month=7, + day=4, + observance=nearest_workday, +) +Christmas = Holiday( + 'Christmas', + month=12, + day=25, + observance=nearest_workday, +) + +# Half Days +MonTuesThursBeforeIndependenceDay = Holiday( + # When July 4th is a Tuesday, Wednesday, or Friday, the previous day is a + # half day. + 'Mondays, Tuesdays, and Thursdays Before Independence Day', + month=7, + day=3, + days_of_week=(MONDAY, TUESDAY, THURSDAY), + start_date=Timestamp("1995-01-01"), +) +FridayAfterIndependenceDayExcept2013 = Holiday( + # When July 4th is a Thursday, the next day is a half day (except in 2013, + # when, for no explicable reason, Wednesday was a half day instead). + "Fridays after Independence Day that aren't in 2013", + month=7, + day=5, + days_of_week=(FRIDAY,), + observance=lambda dt: None if dt.year == 2013 else dt, + start_date=Timestamp("1995-01-01"), +) +USBlackFridayBefore1993 = Holiday( + 'Black Friday', + month=11, + day=1, + # Black Friday was not observed until 1992. + start_date=Timestamp('1992-01-01'), + end_date=Timestamp('1993-01-01'), + offset=[DateOffset(weekday=TH(4)), Day(1)], +) +USBlackFridayInOrAfter1993 = Holiday( + 'Black Friday', + month=11, + day=1, + start_date=Timestamp('1993-01-01'), + offset=[DateOffset(weekday=TH(4)), Day(1)], +) +# These have the same definition, but are used in different places because the +# NYSE closed at 2:00 PM on Christmas Eve until 1993. +ChristmasEveBefore1993 = Holiday( + 'Christmas Eve', + month=12, + day=24, + end_date=Timestamp('1993-01-01'), + # When Christmas is a Saturday, the 24th is a full holiday. + days_of_week=(MONDAY, TUESDAY, WEDNESDAY, THURSDAY), +) +ChristmasEveInOrAfter1993 = Holiday( + 'Christmas Eve', + month=12, + day=24, + start_date=Timestamp('1993-01-01'), + # When Christmas is a Saturday, the 24th is a full holiday. + days_of_week=(MONDAY, TUESDAY, WEDNESDAY, THURSDAY), +) + + +# http://en.wikipedia.org/wiki/Aftermath_of_the_September_11_attacks +September11Closings = date_range('2001-09-11', '2001-09-16', tz='UTC') + +# http://en.wikipedia.org/wiki/Hurricane_sandy +HurricaneSandyClosings = date_range( + '2012-10-29', + '2012-10-30', + tz='UTC' +) + +# National Days of Mourning +# - President Richard Nixon - April 27, 1994 +# - President Ronald W. Reagan - June 11, 2004 +# - President Gerald R. Ford - Jan 2, 2007 +USNationalDaysofMourning = [ + Timestamp('1994-04-27', tz='UTC'), + Timestamp('2004-06-11', tz='UTC'), + Timestamp('2007-01-02', tz='UTC'), +] + + +class NYSEHolidayCalendar(AbstractHolidayCalendar): + """ + Non-trading days for the NYSE. + + See NYSEExchangeCalendar for full description. + """ + rules = [ + USNewYearsDay, + USMartinLutherKingJrAfter1998, + USPresidentsDay, + GoodFriday, + USMemorialDay, + USIndependenceDay, + USLaborDay, + USThanksgivingDay, + USIndependenceDay, + Christmas, + ] + + +class NYSE2PMCloseCalendar(AbstractHolidayCalendar): + """ + Holiday Calendar for 2PM closes for NYSE + """ + rules = [ + ChristmasEveBefore1993, + USBlackFridayBefore1993, + ] + + +class NYSEEarlyCloseCalendar(AbstractHolidayCalendar): + """ + Regular early close calendar for NYSE + """ + rules = [ + MonTuesThursBeforeIndependenceDay, + FridayAfterIndependenceDayExcept2013, + USBlackFridayInOrAfter1993, + ChristmasEveInOrAfter1993, + ] + + +class NYSEExchangeCalendar(ExchangeCalendar): + """ + Exchange calendar for NYSE + + Open Time: 9:31 AM, US/Eastern + Close Time: 4:00 PM, US/Eastern + + Regularly-Observed Holidays: + - New Years Day (observed on monday when Jan 1 is a Sunday) + - Martin Luther King Jr. Day (3rd Monday in January, only after 1998) + - Washington's Birthday (aka President's Day, 3rd Monday in February) + - Good Friday (two days before Easter Sunday) + - Memorial Day (last Monday in May) + - Independence Day (observed on the nearest weekday to July 4th) + - Labor Day (first Monday in September) + - Thanksgiving (fourth Thursday in November) + - Christmas (observed on nearest weekday to December 25) + + NOTE: The NYSE does not observe the following US Federal Holidays: + - Columbus Day + - Veterans Day + + Regularly-Observed Early Closes: + - July 3rd (Mondays, Tuesdays, and Thursdays, 1995 onward) + - July 5th (Fridays, 1995 onward, except 2013) + - Christmas Eve (except on Fridays, when the exchange is closed entirely) + - Day After Thanksgiving (aka Black Friday, observed from 1992 onward) + + NOTE: Until 1993, the standard early close time for the NYSE was 2:00 PM. + From 1993 onward, it has been 1:00 PM. + + Additional Irregularities: + - Closed from 9/11/2001 to 9/16/2001 due to terrorist attacks in NYC. + - Closed on 10/29/2012 and 10/30/2012 due to Hurricane Sandy. + - Closed on 4/27/1994 due to Richard Nixon's death. + - Closed on 6/11/2004 due to Ronald Reagan's death. + - Closed on 1/2/2007 due to Gerald Ford's death. + - Closed at 1:00 PM on Wednesday, July 3rd, 2013 + - Closed at 1:00 PM on Friday, December 31, 1999 + - Closed at 1:00 PM on Friday, December 26, 1997 + - Closed at 1:00 PM on Friday, December 26, 2003 + + NOTE: The exchange was **not** closed early on Friday December 26, 2008, + nor was it closed on Friday December 26, 2014. The next Thursday Christmas + will be in 2025. If someone is still maintaining this code in 2025, then + we've done alright...and we should check if it's a half day. + """ + + exchange_name = 'NYSE' + native_timezone = US_EASTERN + open_time = NYSE_OPEN + close_time = NYSE_CLOSE + open_offset = NYSE_OPEN_OFFSET + close_offset = NYSE_CLOSE_OFFSET + + holidays_calendar = NYSEHolidayCalendar() + special_opens_calendars = () + special_closes_calendars = [ + (NYSE_STANDARD_EARLY_CLOSE, NYSEEarlyCloseCalendar()), + (time(14), NYSE2PMCloseCalendar()), + ] + + holidays_adhoc = list(chain( + September11Closings, + HurricaneSandyClosings, + USNationalDaysofMourning, + )) + + special_opens_adhoc = () + special_closes_adhoc = [ + (NYSE_STANDARD_EARLY_CLOSE, ('1997-12-26', + '1999-12-31', + '2003-12-26', + '2013-07-03')), + ] + + @property + def name(self): + """ + The name of this exchange calendar. + E.g.: 'NYSE', 'LSE', 'CME Energy' + """ + return self.exchange_name + + @property + def tz(self): + """ + The native timezone of the exchange. + """ + return self.native_timezone + + def is_open_on_minute(self, dt): + """ + Is the exchange open (accepting orders) at @dt. + + Parameters + ---------- + dt : Timestamp + + Returns + ------- + bool + True if exchange is open at the given dt, otherwise False. + """ + # Retrieve the exchange session relevant for this datetime + session = self.session_date(dt) + # Retrieve the open and close for this exchange session + open, close = self.open_and_close(session) + # Is @dt within the trading hours for this exchange session + return open <= dt and dt <= close + + def is_open_on_day(self, dt): + """ + Is the exchange open (accepting orders) anytime during the calendar day + containing @dt. + + Parameters + ---------- + dt : Timestamp + + Returns + ------- + bool + True if exchange is open at any time during the day containing @dt + """ + dt_normalized = normalize_date(dt) + return dt_normalized in self.schedule.index + + def trading_days(self, start, end): + """ + Calculates all of the exchange sessions between the given + start and end, inclusive. + + SD: Should @start and @end are UTC-canonicalized, as our exchange + sessions are. If not, then it's not clear how this method should behave + if @start and @end are both in the middle of the day. Here, I assume we + need to map @start and @end to session. + + Parameters + ---------- + start : Timestamp + end : Timestamp + + Returns + ------- + DatetimeIndex + A DatetimeIndex populated with all of the trading days between + the given start and end. + """ + start_session = self.session_date(start) + end_session = self.session_date(end) + # Increment end_session by one day, beucase .loc[s:e] return all values + # in the DataFrame up to but not including `e`. + # end_session += Timedelta(days=1) + return self.schedule.loc[start_session:end_session] + + def open_and_close(self, dt): + """ + Given a datetime, returns a tuple of timestamps of the + open and close of the exchange session containing the datetime. + + SD: Should we accept an arbitrary datetime, or should we first map it + to and exchange session using session_date. Need to check what the + consumers expect. Here, I assume we need to map it to a session. + + Parameters + ---------- + dt : Timestamp + A dt in a session whose open and close are needed. + + Returns + ------- + (Timestamp, Timestamp) + The open and close for the given dt. + """ + session = self.session_date(dt) + return self._get_open_and_close(session) + + def _get_open_and_close(self, session_date): + """ + Retrieves the open and close for a given session. + + Parameters + ---------- + session_date : Timestamp + The canonicalized session_date whose open and close are needed. + + Returns + ------- + (Timestamp, Timestamp) or (None, None) + The open and close for the given dt, or Nones if the given date is + not a session. + """ + # Return a tuple of nones if the given date is not a session. + if session_date not in self.schedule.index: + return (None, None) + + o_and_c = self.schedule.loc[session_date] + # `market_open` and `market_close` should be timezone aware, but pandas + # 0.16.1 does not appear to support this: + # http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#datetime-with-tz # noqa + return (o_and_c['market_open'].tz_localize('UTC'), + o_and_c['market_close'].tz_localize('UTC')) + + def session_date(self, dt): + """ + Given a datetime, returns the UTC-canonicalized date of the exchange + session in which the time belongs. If the time is not in an exchange + session (while the market is closed), returns the date of the next + exchange session after the time. + + Parameters + ---------- + dt : Timestamp + A timezone-aware Timestamp. + + Returns + ------- + Timestamp + The date of the exchange session in which dt belongs. + """ + while not self.is_open_on_day(dt): + dt += Timedelta(days=1) + return normalize_date(dt) + + def minutes_for_date(self, dt): + """ + Given a datetime, returns a DatetimeIndex of all trading + minutes in the exchange session for that datetime. + + SD: Should @dt be an arbitrary datetime, so that we should + first map to an exchange session by calling self.session_date. Need to + check what the consumers expect. Here, I assume we need to map it to a + session. + + Parameters + ---------- + dt : Timestamp + The datetime whose exchange session minutes are needed. + + Returns + ------- + DatetimeIndex + A DatetimeIndex populated with all of the minutes in the + given dt. + """ + session = self.session_date(dt) + open, close = self.open_and_close(session) + return date_range(open, close, freq='min', tz='UTC') + + def minute_window(self, start, count, step=1): + """ + Returns a DatetimeIndex containing `count` market minutes, starting + with `start` and continuing `step` minutes at a time. + + Parameters + ---------- + start : Timestamp + The start of the window. + count : int + The number of minutes needed. + step : int + The step size by which to increment. + + Returns + ------- + DatetimeIndex + A window with @count minutes, start with @start. + """ + if not self.is_open_on_minute(start): + raise ValueError("minute_window starting at non-market time " + "{minute}".format(minute=start)) + + start_utc = start.astimezone(timezone('UTC')) + + session = self.session_date(start) + session_idx = self.schedule.index.get_loc(session) + + mins_in_session = self.minutes_for_date(session) + start_idx = mins_in_session.searchsorted(start_utc) + + # Use a list instead of a pandas DatetimeIndex, as using .append() + # with DatetimeIndex can become expensive if used several times, since + # it makes a full copy of the data. list.extend() will not typically + # copy the data unless there is not enough memory to extend into, which + # is usually not problem. + all_minutes = list(mins_in_session[start_idx::np.sign(step)]) + + while True: + + step_minutes = all_minutes[0::np.absolute(step)] + + if len(step_minutes) >= count: + step_minutes = step_minutes[:count] + return pd.DatetimeIndex(step_minutes, copy=False) + + # Iterate session forward or backward + session_idx += np.sign(step) + # Get the minutes in the next exchange session + session = self.schedule.index[session_idx] + session_minutes = self.minutes_for_date(session)[::np.sign(step)] + + # A these new session_minutes to the `all_minutes` candidate list + all_minutes.extend(list(session_minutes)) diff --git a/zipline/utils/calendars/trading_schedule.py b/zipline/utils/calendars/trading_schedule.py new file mode 100644 index 00000000..f0964107 --- /dev/null +++ b/zipline/utils/calendars/trading_schedule.py @@ -0,0 +1,367 @@ +# +# Copyright 2016 Quantopian, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from abc import ( + ABCMeta, + abstractmethod, + abstractproperty, +) +from functools import partial + +from zipline.utils.memoize import remember_last + +from .exchange_calendar import get_calendar +from .calendar_helpers import ( + next_scheduled_day, + previous_scheduled_day, + next_open_and_close, + previous_open_and_close, + scheduled_day_distance, + minutes_for_day, + days_in_range, + minutes_for_days_in_range, + add_scheduled_days, + all_scheduled_minutes, + next_scheduled_minute, + previous_scheduled_minute, +) + + +class TradingSchedule(object): + """ + A TradingSchedule defines the execution timing of a TradingAlgorithm. + """ + __metaclass__ = ABCMeta + + def __init__(self): + # Assign the partial calendar helpers + self.next_execution_day = partial( + next_scheduled_day, + last_trading_day=self.last_execution_day, + is_scheduled_day_hook=self.is_executing_on_day, + ) + self.previous_execution_day = partial( + previous_scheduled_day, + first_trading_day=self.first_execution_day, + is_scheduled_day_hook=self.is_executing_on_day, + ) + self.next_start_and_end = partial( + next_open_and_close, + open_and_close_hook=self.start_and_end, + next_scheduled_day_hook=self.next_execution_day, + ) + self.previous_start_and_end = partial( + previous_open_and_close, + open_and_close_hook=self.start_and_end, + previous_scheduled_day_hook=self.previous_execution_day, + ) + self.execution_day_distance = partial( + scheduled_day_distance, + all_days=self.all_execution_days, + ) + self.execution_minutes_for_day = partial( + minutes_for_day, + open_and_close_hook=self.start_and_end, + ) + self.execution_days_in_range = partial( + days_in_range, + all_days=self.all_execution_days, + ) + self.execution_minutes_for_days_in_range = partial( + minutes_for_days_in_range, + days_in_range_hook=self.execution_days_in_range, + minutes_for_day_hook=self.execution_minutes_for_day, + ) + self.add_execution_days = partial( + add_scheduled_days, + next_scheduled_day_hook=self.next_execution_day, + previous_scheduled_day_hook=self.previous_execution_day, + all_trading_days=self.all_execution_days, + ) + self.next_execution_minute = partial( + next_scheduled_minute, + is_scheduled_day_hook=self.is_executing_on_day, + open_and_close_hook=self.start_and_end, + next_open_and_close_hook=self.next_start_and_end, + ) + self.previous_execution_minute = partial( + previous_scheduled_minute, + is_scheduled_day_hook=self.is_executing_on_day, + open_and_close_hook=self.start_and_end, + previous_open_and_close_hook=self.previous_start_and_end, + ) + + @abstractproperty + def day(self): + """ + A CustomBusinessDay defining those days on which the algorithm is + usually trading. + """ + raise NotImplementedError() + + @abstractproperty + def tz(self): + """ + The native timezone for this TradingSchedule. + """ + raise NotImplementedError() + + @abstractproperty + def first_execution_day(self): + """ + The first possible day of trading in this TradingSchedule. + """ + raise NotImplementedError() + + @abstractproperty + def last_execution_day(self): + """ + The last possible day of trading in this TradingSchedule. + """ + raise NotImplementedError() + + @abstractmethod + def trading_sessions(self, start, end): + """ + Calculates all of the trading sessions between the given + start and end. + + Parameters + ---------- + start : Timestamp + end : Timestamp + + Returns + ------- + DataFrame + A DataFrame, with a DatetimeIndex of trading dates, containing + columns of trading starts and ends in this TradingSchedule. + """ + raise NotImplementedError() + + @property + @remember_last + def all_execution_days(self): + return self.schedule.index + + @property + @remember_last + def all_execution_minutes(self): + return all_scheduled_minutes(self.all_execution_days, + self.execution_minutes_for_days_in_range) + + def trading_dates(self, start, end): + """ + Calculates the dates of all of the trading sessions between the given + start and end. + + Parameters + ---------- + start : Timestamp + end : Timestamp + + Returns + ------- + DatetimeIndex + A DatetimeIndex containing the dates of the desired trading + sessions. + """ + return self.trading_sessions(start, end).index + + @abstractmethod + def data_availability_time(self, date): + """ + Given a UTC-canonicalized date, returns a time by-which all data from + the previous date is available to the algorithm. + + Parameters + ---------- + date : Timestamp + The UTC-canonicalized calendar date whose data availability time + is needed. + + Returns + ------- + Timestamp or None + The data availability time on the given date, or None if there is + no data availability time for that date. + """ + raise NotImplementedError() + + @abstractmethod + def start_and_end(self, date): + """ + Given a UTC-canonicalized date, returns a tuple of timestamps of the + start and end of the algorithm trading session for that date. + + Parameters + ---------- + date : Timestamp + The UTC-canonicalized algorithm trading session date whose start + and end are needed. + + Returns + ------- + (Timestamp, Timestamp) + The start and end for the given date. + """ + raise NotImplementedError() + + @abstractmethod + def is_executing_on_minute(self, dt): + """ + Calculates if a TradingAlgorithm using this TradingSchedule should be + executed at time dt. + + Parameters + ---------- + dt : Timestamp + The time being queried. + + Returns + ------- + bool + True if the TradingAlgorithm should be executed at dt, + otherwise False. + """ + raise NotImplementedError() + + @abstractmethod + def is_executing_on_day(self, dt): + """ + Calculates if a TradingAlgorithm using this TradingSchedule would + execute on the day of dt. + + Parameters + ---------- + dt : Timestamp + The time being queried. + + Returns + ------- + bool + True if the TradingAlgorithm should be executed at dt, + otherwise False. + """ + raise NotImplementedError() + + @abstractmethod + def minute_window(self, start, count, step=1): + """ + Return a DatetimeIndex containing `count` market minutes, starting with + `start` and continuing `step` minutes at a time. + + Parameters + ---------- + start : Timestamp + The start of the window. + count : int + The number of minutes needed. + step : int + The step size by which to increment. + + Returns + ------- + DatetimeIndex + A window with @count minutes, starting with @start a returning + every @step minute. + """ + raise NotImplementedError() + + +class ExchangeTradingSchedule(TradingSchedule): + """ + A TradingSchedule that functions as a wrapper around an ExchangeCalendar. + """ + + def __init__(self, cal): + """ + Docstring goes here, Jimmy + + Parameters + ---------- + cal : ExchangeCalendar + The ExchangeCalendar to be represented by this + ExchangeTradingSchedule. + """ + self._exchange_calendar = cal + super(ExchangeTradingSchedule, self).__init__() + + @property + def day(self): + return self._exchange_calendar.day + + @property + def tz(self): + return self._exchange_calendar.tz + + @property + def schedule(self): + return self._exchange_calendar.schedule + + @property + def first_execution_day(self): + return self._exchange_calendar.first_trading_day + + @property + def last_execution_day(self): + return self._exchange_calendar.last_trading_day + + def trading_sessions(self, start, end): + """ + See TradingSchedule definition. + """ + return self._exchange_calendar.trading_days(start, end) + + def data_availability_time(self, date): + """ + See TradingSchedule definition. + """ + calendar_open, _ = self._exchange_calendar.open_and_close(date) + return calendar_open + + def start_and_end(self, date): + """ + See TradingSchedule definition. + """ + return self._exchange_calendar.open_and_close(date) + + def is_executing_on_minute(self, dt): + """ + See TradingSchedule definition. + """ + return self._exchange_calendar.is_open_on_minute(dt) + + def is_executing_on_day(self, dt): + """ + See TradingSchedule definition. + """ + return self._exchange_calendar.is_open_on_day(dt) + + def minute_window(self, start, count, step=1): + return self._exchange_calendar.minute_window(start=start, + count=count, + step=step) + + +class NYSETradingSchedule(ExchangeTradingSchedule): + """ + An ExchangeTradingSchedule for NYSE. Provided for convenience. + """ + def __init__(self): + super(NYSETradingSchedule, self).__init__(cal=get_calendar('NYSE')) + + +default_nyse_schedule = NYSETradingSchedule() diff --git a/zipline/utils/cme_exchange_calendar.py b/zipline/utils/cme_exchange_calendar.py new file mode 100644 index 00000000..9aeb9ad2 --- /dev/null +++ b/zipline/utils/cme_exchange_calendar.py @@ -0,0 +1,454 @@ +# +# Copyright 2016 Quantopian, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from datetime import time +from itertools import chain + +import numpy as np +import pandas as pd +from dateutil.relativedelta import ( + MO, + TH, +) +from pandas import ( + date_range, + DateOffset, + Timestamp, +) +from pandas.tseries.holiday import( + AbstractHolidayCalendar, + GoodFriday, + Holiday, + nearest_workday, + sunday_to_monday, + USLaborDay, + USPresidentsDay, + USThanksgivingDay, +) +from pandas.tseries.offsets import Day +from pytz import timezone + +from zipline.utils.calendars import ExchangeCalendar + +# Useful resources for making changes to this file: +# http://www.nyse.com/pdfs/closings.pdf +# http://www.stevemorse.org/jcal/whendid.html + +MONDAY, TUESDAY, WEDNESDAY, THURSDAY, FRIDAY, SATURDAY, SUNDAY = range(7) + +US_CENTRAL = timezone('Americas/Chicago') +CME_OPEN = time(17) +CME_CLOSE = time(16) +# CME_STANDARD_EARLY_CLOSE = time(13) +# Does the market open or close on a different calendar day, compared to the +# calendar day assigned by the exchang to this session? +CME_OPEN_OFFSET = -1 +CME_CLOSE_OFFSET = 0 + +# Closings +USNewYearsDay = Holiday( + 'New Years Day', + month=1, + day=1, + # When Jan 1 is a Sunday, NYSE observes the subsequent Monday. When Jan 1 + # Saturday (as in 2005 and 2011), no holiday is observed. + observance=sunday_to_monday +) +USMemorialDay = Holiday( + # NOTE: The definition for Memorial Day is incorrect as of pandas 0.16.0. + # See https://github.com/pydata/pandas/issues/9760. + 'Memorial Day', + month=5, + day=25, + offset=DateOffset(weekday=MO(1)), +) +USMartinLutherKingJrAfter1998 = Holiday( + 'Dr. Martin Luther King Jr. Day', + month=1, + day=1, + # The NYSE didn't observe MLK day as a holiday until 1998. + start_date=Timestamp('1998-01-01'), + offset=DateOffset(weekday=MO(3)), +) +USIndependenceDay = Holiday( + 'July 4th', + month=7, + day=4, + observance=nearest_workday, +) +Christmas = Holiday( + 'Christmas', + month=12, + day=25, + observance=nearest_workday, +) + +# Half Days +MonTuesThursBeforeIndependenceDay = Holiday( + # When July 4th is a Tuesday, Wednesday, or Friday, the previous day is a + # half day. + 'Mondays, Tuesdays, and Thursdays Before Independence Day', + month=7, + day=3, + days_of_week=(MONDAY, TUESDAY, THURSDAY), + start_date=Timestamp("1995-01-01"), +) +FridayAfterIndependenceDayExcept2013 = Holiday( + # When July 4th is a Thursday, the next day is a half day (except in 2013, + # when, for no explicable reason, Wednesday was a half day instead). + "Fridays after Independence Day that aren't in 2013", + month=7, + day=5, + days_of_week=(FRIDAY,), + observance=lambda dt: None if dt.year == 2013 else dt, + start_date=Timestamp("1995-01-01"), +) +USBlackFridayBefore1993 = Holiday( + 'Black Friday', + month=11, + day=1, + # Black Friday was not observed until 1992. + start_date=Timestamp('1992-01-01'), + end_date=Timestamp('1993-01-01'), + offset=[DateOffset(weekday=TH(4)), Day(1)], +) +USBlackFridayInOrAfter1993 = Holiday( + 'Black Friday', + month=11, + day=1, + start_date=Timestamp('1993-01-01'), + offset=[DateOffset(weekday=TH(4)), Day(1)], +) +# These have the same definition, but are used in different places because the +# NYSE closed at 2:00 PM on Christmas Eve until 1993. +ChristmasEveBefore1993 = Holiday( + 'Christmas Eve', + month=12, + day=24, + end_date=Timestamp('1993-01-01'), + # When Christmas is a Saturday, the 24th is a full holiday. + days_of_week=(MONDAY, TUESDAY, WEDNESDAY, THURSDAY), +) +ChristmasEveInOrAfter1993 = Holiday( + 'Christmas Eve', + month=12, + day=24, + start_date=Timestamp('1993-01-01'), + # When Christmas is a Saturday, the 24th is a full holiday. + days_of_week=(MONDAY, TUESDAY, WEDNESDAY, THURSDAY), +) + + +# http://en.wikipedia.org/wiki/Aftermath_of_the_September_11_attacks +September11Closings = date_range('2001-09-11', '2001-09-16', tz='UTC') + +# http://en.wikipedia.org/wiki/Hurricane_sandy +HurricaneSandyClosings = date_range( + '2012-10-29', + '2012-10-30', + tz='UTC' +) + +# National Days of Mourning +# - President Richard Nixon - April 27, 1994 +# - President Ronald W. Reagan - June 11, 2004 +# - President Gerald R. Ford - Jan 2, 2007 +USNationalDaysofMourning = [ + Timestamp('1994-04-27', tz='UTC'), + Timestamp('2004-06-11', tz='UTC'), + Timestamp('2007-01-02', tz='UTC'), +] + + +class CMEHolidayCalendar(AbstractHolidayCalendar): + """ + Non-trading days for the CME. + + See CMEExchangeCalendar for full description. + """ + rules = [ + USNewYearsDay, + USMartinLutherKingJrAfter1998, + USPresidentsDay, + GoodFriday, + USMemorialDay, + USIndependenceDay, + USLaborDay, + USThanksgivingDay, + USIndependenceDay, + Christmas, + ] + + +class CMEEarlyCloseCalendar(AbstractHolidayCalendar): + """ + Regular early close calendar for NYSE + """ + rules = [ + MonTuesThursBeforeIndependenceDay, + FridayAfterIndependenceDayExcept2013, + USBlackFridayInOrAfter1993, + ChristmasEveInOrAfter1993, + ] + + +class CMEExchangeCalendar(ExchangeCalendar): + """ + Exchange calendar for CME + + Open Time: 5:00 AM, Americas/Chicago + Close Time: 5:00 PM, Americas/Chicago + + Regularly-Observed Holidays: + - New Years Day (observed on monday when Jan 1 is a Sunday) + - Martin Luther King Jr. Day (3rd Monday in January, only after 1998) + - Washington's Birthday (aka President's Day, 3rd Monday in February) + - Good Friday (two days before Easter Sunday) + - Memorial Day (last Monday in May) + - Independence Day (observed on the nearest weekday to July 4th) + - Labor Day (first Monday in September) + - Thanksgiving (fourth Thursday in November) + - Christmas (observed on nearest weekday to December 25) + + NOTE: The CME does not observe the following US Federal Holidays: + - Columbus Day + - Veterans Day + + Regularly-Observed Early Closes: + - July 3rd (Mondays, Tuesdays, and Thursdays, 1995 onward) + - July 5th (Fridays, 1995 onward, except 2013) + - Christmas Eve (except on Fridays, when the exchange is closed entirely) + - Day After Thanksgiving (aka Black Friday, observed from 1992 onward) + + NOTE: Until 1993, the standard early close time for the NYSE was 2:00 PM. + From 1993 onward, it has been 1:00 PM. + + Additional Irregularities: + - Closed from 9/11/2001 to 9/16/2001 due to terrorist attacks in NYC. + - Closed on 10/29/2012 and 10/30/2012 due to Hurricane Sandy. + - Closed on 4/27/1994 due to Richard Nixon's death. + - Closed on 6/11/2004 due to Ronald Reagan's death. + - Closed on 1/2/2007 due to Gerald Ford's death. + - Closed at 1:00 PM on Wednesday, July 3rd, 2013 + - Closed at 1:00 PM on Friday, December 31, 1999 + - Closed at 1:00 PM on Friday, December 26, 1997 + - Closed at 1:00 PM on Friday, December 26, 2003 + + NOTE: The exchange was **not** closed early on Friday December 26, 2008, + nor was it closed on Friday December 26, 2014. The next Thursday Christmas + will be in 2025. If someone is still maintaining this code in 2025, then + we've done alright...and we should check if it's a half day. + """ + + native_timezone = US_CENTRAL + open_time = CME_OPEN + close_time = CME_CLOSE + open_offset = CME_OPEN_OFFSET + close_offset = CME_CLOSE_OFFSET + + holidays_calendar = CMEHolidayCalendar() + special_opens_calendars = () + special_closes_calendars = [] + + holidays_adhoc = chain( + September11Closings, + HurricaneSandyClosings, + USNationalDaysofMourning, + ) + + special_opens_adhoc = () + special_closes_adhoc = [] + + @property + def name(self): + """ + The name of this exchange calendar. + E.g.: 'NYSE', 'LSE', 'CME Energy' + """ + return 'CME' + + @property + def tz(self): + """ + The native timezone of the exchange. + + SD: Not clear that this needs to be exposed. + """ + return self.native_timezone + + def is_open(self, dt): + """ + Parameters + ---------- + dt : Timestamp + + Returns + ------- + bool + True if exchange is open at the given dt, otherwise False. + """ + # Retrieve the exchange session relevant for this datetime + session = self.session_date(dt) + # Retrieve the opens and closes for this exchange session + o_and_c_df = self.open_and_close(session) + # Is @dt within the trading hours for this exchange session + for index, row in o_and_c_df.iterrows(): + if row['market_open'] <= dt and dt <= row['market_close']: + return True + return False + + def trading_days(self, start, end): + """ + Calculates all of the exchange sessions between the given + start and end. + + SD: Presumably @start and @end are UTC-canonicalized, as our exchange + sessions are. If not, then it's not clear how this method should behave + if @start and @end are both in the middle of the day. + + Parameters + ---------- + start : Timestamp + end : Timestamp + + Returns + ------- + DatetimeIndex + A DatetimeIndex populated with all of the trading days between + the given start and end. + """ + return self.schedule.index[start:end] + + def open_and_close(self, session): + """ + Given a UTC-canonicalized date, returns a tuple of timestamps of the + open and close of the exchange session on that date. + + SD: Can @date be an arbitrary datetime, or should we first map it to + and exchange session using session_date. Need to check what the + consumers expect. Here, I assume we need to map it to a session. + + Parameters + ---------- + session : Timestamp + The UTC-canonicalized session whose open and close are needed. + + Returns + ------- + (Timestamp, Timestamp) + The open and close for the given date. + """ + # Generalised logic for the case of trading pauses. + # Note: this logic is ~3-4 times slower than that used for the NYSE + # (pass a list, to ensure we get a DataFrame returned) + return self.schedule.loc[[session]] + + def session_date(self, dt): + """ + Given a time, returns the UTC-canonicalized date of the exchange + session in which the time belongs. If the time is not in an exchange + session (while the market is closed), returns the date of the next + exchange session after the time. + + Parameters + ---------- + dt : Timestamp + A timezone-aware Timestamp. + + Returns + ------- + Timestamp + The date of the exchange session in which dt belongs. + """ + dt_utc = dt.tz_convert('UTC').tz_convert(None) + return dt_utc.replace(hour=0, minute=0, second=0) + + def minutes_for_date(self, date): + """ + Given a UTC-canonicalized date, returns a DatetimeIndex of all trading + minutes in the exchange session for that date. + + SD: Sounds like @date can be an arbitrary datetime, and that we should + first map to an exchange session by calling self.session_date. Need to + check what the consumers expect. + + Parameters + ---------- + date : Timestamp + The UTC-canonicalized date whose minutes are needed. + + Returns + ------- + DatetimeIndex + A DatetimeIndex populated with all of the minutes in the + given date. + """ + open, close = self.open_and_close(date) + return date_range(open, close, freq='min', tz='UTC') + + def minute_window(self, start, count, step=1): + """ + Return a DatetimeIndex containing `count` market minutes, starting with + `start` and continuing `step` minutes at a time. + + Parameters + ---------- + start : Timestamp + The start of the window. + count : int + The number of minutes needed. + step : int + The step size by which to increment. + + Returns + ------- + DatetimeIndex + A window with @count minutes, start with @start. + """ + if not self.is_open(start): + raise ValueError("minute_window starting at non-market time " + "{minute}".format(minute=start)) + + start_utc = start.tz_convert('UTC') + + session = self.session_date(start) + session_idx = self.schedule.index.get_loc(session) + + mins_in_session = self.minutes_for_date(session) + start_idx = mins_in_session.searchsorted(start_utc) + + # Use a list instead of a pandas DatetimeIndex, as using .append() + # with DatetimeIndex can become expensive if used several times, since + # it makes a full copy of the data. list.extend() will not typically + # copy the data unless there is not enough memory to extend into, which + # is usually not problem. + all_minutes = list(mins_in_session[start_idx::np.sign(step)]) + + while True: + + step_minutes = all_minutes[0::step] + + if len(step_minutes) >= count: + step_minutes = step_minutes[:count] + return pd.DatetimeIndex(step_minutes, copy=False) + + # Iterate session forward or backward + session_idx += np.sign(step) + # Get the minutes in the next exchange session + session = self.schedule.index[session_idx] + session_minutes = self.minutes_for_date(session) + + # A these new session_minutes to the `all_minutes` candidate list + all_minutes.extend(list(session_minutes)) diff --git a/zipline/utils/events.py b/zipline/utils/events.py index 4a9627fc..444dd1dd 100644 --- a/zipline/utils/events.py +++ b/zipline/utils/events.py @@ -22,6 +22,10 @@ import pytz from .context_tricks import nop_context +from zipline.utils.calendars import ( + get_calendar, + normalize_date, +) __all__ = [ 'EventManager', @@ -52,6 +56,9 @@ MAX_MONTH_RANGE = 26 MAX_WEEK_RANGE = 5 +_static_nyse_cal = get_calendar('NYSE') + + def naive_to_utc(ts): """ Converts a UTC tz-naive timestamp to a tz-aware timestamp. @@ -204,7 +211,6 @@ class EventManager(object): context, data, dt, - context.trading_environment, ) @@ -218,17 +224,17 @@ class Event(namedtuple('Event', ['rule', 'callback'])): callback = callback or (lambda *args, **kwargs: None) return super(cls, cls).__new__(cls, rule=rule, callback=callback) - def handle_data(self, context, data, dt, env): + def handle_data(self, context, data, dt): """ Calls the callable only when the rule is triggered. """ - if self.rule.should_trigger(dt, env): + if self.rule.should_trigger(dt): self.callback(context, data) class EventRule(six.with_metaclass(ABCMeta)): @abstractmethod - def should_trigger(self, dt, env): + def should_trigger(self, dt): """ Checks if the rule should trigger with its current state. This method should be pure and NOT mutate any state on the object. @@ -274,24 +280,23 @@ class ComposedRule(StatelessRule): self.second = second self.composer = composer - def should_trigger(self, dt, env): + def should_trigger(self, dt): """ Composes the two rules with a lazy composer. """ return self.composer( self.first.should_trigger, self.second.should_trigger, - dt, - env + dt ) @staticmethod - def lazy_and(first_should_trigger, second_should_trigger, dt, env): + def lazy_and(first_should_trigger, second_should_trigger, dt): """ Lazily ands the two rules. This will NOT call the should_trigger of the second rule if the first one returns False. """ - return first_should_trigger(dt, env) and second_should_trigger(dt, env) + return first_should_trigger(dt) and second_should_trigger(dt) class Always(StatelessRule): @@ -299,7 +304,7 @@ class Always(StatelessRule): A rule that always triggers. """ @staticmethod - def always_trigger(dt, env): + def always_trigger(dt): """ A should_trigger implementation that will always trigger. """ @@ -312,7 +317,7 @@ class Never(StatelessRule): A rule that never triggers. """ @staticmethod - def never_trigger(dt, env): + def never_trigger(dt): """ A should_trigger implementation that will never trigger. """ @@ -340,13 +345,14 @@ class AfterOpen(StatelessRule): self._one_minute = datetime.timedelta(minutes=1) - def calculate_dates(self, dt, env): + def calculate_dates(self, dt): # given a dt, find that day's open and period end (open + offset) - self._period_start, self._period_close = env.get_open_and_close(dt) + self._period_start, self._period_close = \ + _static_nyse_cal.get_open_and_close(dt) self._period_end = \ self._period_start + self.offset - self._one_minute - def should_trigger(self, dt, env): + def should_trigger(self, dt): # There are two reasons why we might want to recalculate the dates. # One is the first time we ever call should_trigger, when # self._period_start is none. The second is when we're on a new day, @@ -360,7 +366,7 @@ class AfterOpen(StatelessRule): self._period_start is None or self._period_close <= dt ): - self.calculate_dates(dt, env) + self.calculate_dates(dt) return dt == self._period_end @@ -384,14 +390,14 @@ class BeforeClose(StatelessRule): self._one_minute = datetime.timedelta(minutes=1) - def calculate_dates(self, dt, env): + def calculate_dates(self, dt): # given a dt, find that day's close and period start (close - offset) - self._period_end = env.get_open_and_close(dt)[1] + self._period_end = _static_nyse_cal.get_open_and_close(dt)[1] self._period_start = \ self._period_end - self.offset self._period_close = self._period_end - def should_trigger(self, dt, env): + def should_trigger(self, dt): # There are two reasons why we might want to recalculate the dates. # One is the first time we ever call should_trigger, when # self._period_start is none. The second is when we're on a new day, @@ -405,7 +411,7 @@ class BeforeClose(StatelessRule): self._period_start is None or self._period_close <= dt ): - self.calculate_dates(dt, env) + self.calculate_dates(dt) return self._period_start == dt @@ -414,8 +420,8 @@ class NotHalfDay(StatelessRule): """ A rule that only triggers when it is not a half day. """ - def should_trigger(self, dt, env): - return dt.date() not in env.early_closes + def should_trigger(self, dt): + return normalize_date(dt) not in _static_nyse_cal.early_closes class TradingDayOfWeekRule(six.with_metaclass(ABCMeta, StatelessRule)): @@ -430,14 +436,14 @@ class TradingDayOfWeekRule(six.with_metaclass(ABCMeta, StatelessRule)): self.next_midnight_timestamp = None @abstractmethod - def date_func(self, dt, env): + def date_func(self, dt): raise NotImplementedError - def calculate_start_and_end(self, dt, env): + def calculate_start_and_end(self, dt): next_trading_day = _coerce_datetime( - env.add_trading_days( + _static_nyse_cal.add_trading_days( self.td_delta, - self.date_func(dt, env), + self.date_func(dt), ) ) @@ -452,23 +458,24 @@ class TradingDayOfWeekRule(six.with_metaclass(ABCMeta, StatelessRule)): ) ) - next_open, next_close = env.get_open_and_close(next_trading_day) + next_open, next_close = _static_nyse_cal.open_and_close( + next_trading_day + ) self.next_date_start = next_open self.next_date_end = next_close self.next_midnight_timestamp = next_trading_day - def should_trigger(self, dt, env): + def should_trigger(self, dt): if self.next_date_start is None: # First time this method has been called. Calculate the midnight, # open, and close for the first trigger, which occurs on the week # of the simulation start - self.calculate_start_and_end(dt, env) + self.calculate_start_and_end(dt) # If we've passed the trigger, calculate the next one if dt > self.next_date_end: self.calculate_start_and_end(self.next_date_end + - datetime.timedelta(days=7), - env) + datetime.timedelta(days=7)) # if the given dt is within the next matching day, return true. if self.next_date_start <= dt <= self.next_date_end or \ @@ -484,9 +491,9 @@ class NthTradingDayOfWeek(TradingDayOfWeekRule): This is zero-indexed, n=0 is the first trading day of the week. """ @staticmethod - def get_first_trading_day_of_week(dt, env): + def get_first_trading_day_of_week(dt): prev = dt - dt = env.previous_trading_day(dt) + dt = _static_nyse_cal.previous_trading_day(dt) # If we're on the first trading day of the TradingEnvironment, # calling previous_trading_day on it will return None, which # will blow up when we try and call .date() on it. The first @@ -497,7 +504,7 @@ class NthTradingDayOfWeek(TradingDayOfWeekRule): return prev while dt.date().weekday() < prev.date().weekday(): prev = dt - dt = env.previous_trading_day(dt) + dt = _static_nyse_cal.previous_trading_day(dt) if dt is None: return prev @@ -517,14 +524,14 @@ class NDaysBeforeLastTradingDayOfWeek(TradingDayOfWeekRule): super(NDaysBeforeLastTradingDayOfWeek, self).__init__(-n) @staticmethod - def get_last_trading_day_of_week(dt, env): + def get_last_trading_day_of_week(dt): prev = dt - dt = env.next_trading_day(dt) + dt = _static_nyse_cal.next_trading_day(dt) # Traverse forward until we hit a week border, then jump back to the # previous trading day. while dt.date().weekday() > prev.date().weekday(): prev = dt - dt = env.next_trading_day(dt) + dt = _static_nyse_cal.next_trading_day(dt) if env.is_trading_day(prev): return prev.date() @@ -546,30 +553,30 @@ class NthTradingDayOfMonth(StatelessRule): self.month = None self.day = None - def should_trigger(self, dt, env): - return self.get_nth_trading_day_of_month(dt, env) == dt.date() + def should_trigger(self, dt): + return self.get_nth_trading_day_of_month(dt) == dt.date() - def get_nth_trading_day_of_month(self, dt, env): + def get_nth_trading_day_of_month(self, dt): if self.month == dt.month: # We already computed the day for this month. return self.day if not self.td_delta: - self.day = self.get_first_trading_day_of_month(dt, env) + self.day = self.get_first_trading_day_of_month(dt) else: - self.day = env.add_trading_days( + self.day = _static_nyse_cal.add_trading_days( self.td_delta, - self.get_first_trading_day_of_month(dt, env), + self.get_first_trading_day_of_month(dt), ).date() return self.day - def get_first_trading_day_of_month(self, dt, env): + def get_first_trading_day_of_month(self, dt): self.month = dt.month dt = dt.replace(day=1) - self.first_day = (dt if env.is_trading_day(dt) - else env.next_trading_day(dt)).date() + self.first_day = (dt if _static_nyse_cal.is_open_on_day(dt) + else _static_nyse_cal.next_trading_day(dt)).date() return self.first_day @@ -584,25 +591,25 @@ class NDaysBeforeLastTradingDayOfMonth(StatelessRule): self.month = None self.day = None - def should_trigger(self, dt, env): - return self.get_nth_to_last_trading_day_of_month(dt, env) == dt.date() + def should_trigger(self, dt): + return self.get_nth_to_last_trading_day_of_month(dt) == dt.date() - def get_nth_to_last_trading_day_of_month(self, dt, env): + def get_nth_to_last_trading_day_of_month(self, dt): if self.month == dt.month: # We already computed the last day for this month. return self.day if not self.td_delta: - self.day = self.get_last_trading_day_of_month(dt, env) + self.day = self.get_last_trading_day_of_month(dt) else: - self.day = env.add_trading_days( + self.day = _static_nyse_cal.add_trading_days( self.td_delta, - self.get_last_trading_day_of_month(dt, env), + self.get_last_trading_day_of_month(dt), ).date() return self.day - def get_last_trading_day_of_month(self, dt, env): + def get_last_trading_day_of_month(self, dt): self.month = dt.month if dt.month == 12: @@ -614,7 +621,7 @@ class NDaysBeforeLastTradingDayOfMonth(StatelessRule): year = dt.year month = dt.month + 1 - self.last_day = env.previous_trading_day( + self.last_day = _static_nyse_cal.previous_trading_day( dt.replace(year=year, month=month, day=1) ).date() return self.last_day @@ -649,7 +656,7 @@ class OncePerDay(StatefulRule): super(OncePerDay, self).__init__(rule) - def should_trigger(self, dt, env): + def should_trigger(self, dt): if self.date is None or dt >= self.next_date: # initialize or reset for new date self.triggered = False @@ -659,7 +666,7 @@ class OncePerDay(StatefulRule): # to know if we've moved to the next day self.next_date = dt + pd.Timedelta(1, unit="d") - if not self.triggered and self.rule.should_trigger(dt, env): + if not self.triggered and self.rule.should_trigger(dt): self.triggered = True return True diff --git a/zipline/utils/factory.py b/zipline/utils/factory.py index 9adb4dcb..a05d228a 100644 --- a/zipline/utils/factory.py +++ b/zipline/utils/factory.py @@ -35,6 +35,7 @@ from zipline.data.loader import ( # For backwards compatibility load_from_yahoo, load_bars_from_yahoo, ) +from zipline.utils.calendars import default_nyse_schedule __all__ = ['load_from_yahoo', 'load_bars_from_yahoo'] @@ -45,16 +46,16 @@ def create_simulation_parameters(year=2006, start=None, end=None, num_days=None, data_frequency='daily', emission_rate='daily', - env=None): - if env is None: - # Construct a complete environment with reasonable defaults - env = TradingEnvironment(load=noop_load) + trading_schedule=default_nyse_schedule): if start is None: start = pd.Timestamp("{0}-01-01".format(year), tz='UTC') if end is None: if num_days: - start_index = env.trading_days.searchsorted(start) - end = env.trading_days[start_index + num_days - 1] + start_index = trading_schedule.all_execution_days\ + .searchsorted(start) + end = trading_schedule.all_execution_days[ + start_index + num_days - 1 + ] else: end = pd.Timestamp("{0}-12-31".format(year), tz='UTC') sim_params = SimulationParameters( @@ -63,31 +64,31 @@ def create_simulation_parameters(year=2006, start=None, end=None, capital_base=capital_base, data_frequency=data_frequency, emission_rate=emission_rate, - env=env, + trading_schedule=trading_schedule, ) return sim_params -def get_next_trading_dt(current, interval, env): - next_dt = pd.Timestamp(current).tz_convert(env.exchange_tz) +def get_next_trading_dt(current, interval, trading_schedule): + next_dt = pd.Timestamp(current).tz_convert(trading_schedule.tz) while True: # Convert timestamp to naive before adding day, otherwise the when # stepping over EDT an hour is added. next_dt = pd.Timestamp(next_dt.replace(tzinfo=None)) next_dt = next_dt + interval - next_dt = pd.Timestamp(next_dt, tz=env.exchange_tz) + next_dt = pd.Timestamp(next_dt, tz=trading_schedule.tz) next_dt_utc = next_dt.tz_convert('UTC') - if env.is_market_hours(next_dt_utc): + if trading_schedule.is_executing_on_minute(next_dt_utc): break - next_dt = next_dt_utc.tz_convert(env.exchange_tz) + next_dt = next_dt_utc.tz_convert(trading_schedule.tz) return next_dt_utc -def create_trade_history(sid, prices, amounts, interval, sim_params, env, - source_id="test_factory"): +def create_trade_history(sid, prices, amounts, interval, sim_params, + trading_schedule, source_id="test_factory"): trades = [] current = sim_params.first_open @@ -100,7 +101,7 @@ def create_trade_history(sid, prices, amounts, interval, sim_params, env, trade_dt = current trade = create_trade(sid, price, amount, trade_dt, source_id) trades.append(trade) - current = get_next_trading_dt(current, interval, env) + current = get_next_trading_dt(current, interval, trading_schedule) assert len(trades) == len(prices) return trades @@ -171,12 +172,13 @@ def create_commission(sid, value, datetime): return txn -def create_txn_history(sid, priceList, amtList, interval, sim_params, env): +def create_txn_history(sid, priceList, amtList, interval, sim_params, + trading_schedule): txns = [] current = sim_params.first_open for price, amount in zip(priceList, amtList): - current = get_next_trading_dt(current, interval, env) + current = get_next_trading_dt(current, interval, trading_schedule) txns.append(create_txn(sid, price, amount, current)) current = current + interval @@ -193,7 +195,8 @@ def create_returns_from_list(returns, sim_params): data=returns) -def create_daily_trade_source(sids, sim_params, env, concurrent=False): +def create_daily_trade_source(sids, sim_params, env, trading_schedule, + concurrent=False): """ creates trade_count trades for each sid in sids list. first trade will be on sim_params.period_start, and daily @@ -205,11 +208,13 @@ def create_daily_trade_source(sids, sim_params, env, concurrent=False): timedelta(days=1), sim_params, env=env, + trading_schedule=trading_schedule, concurrent=concurrent, ) -def create_minutely_trade_source(sids, sim_params, env, concurrent=False): +def create_minutely_trade_source(sids, sim_params, env, trading_schedule, + concurrent=False): """ creates trade_count trades for each sid in sids list. first trade will be on sim_params.period_start, and every minute @@ -221,16 +226,17 @@ def create_minutely_trade_source(sids, sim_params, env, concurrent=False): timedelta(minutes=1), sim_params, env=env, + trading_schedule=trading_schedule, concurrent=concurrent, ) def create_trade_source(sids, trade_time_increment, sim_params, env, - concurrent=False): + trading_schedule, concurrent=False): # If the sim_params define an end that is during market hours, that will be # used as the end of the data source - if env.is_market_hours(sim_params.period_end): + if trading_schedule.is_executing_on_minute(sim_params.period_end): end = sim_params.period_end # Otherwise, the last_close after the period_end is used as the end of the # data source @@ -246,98 +252,8 @@ def create_trade_source(sids, trade_time_increment, sim_params, env, 'filter': sids, 'concurrent': concurrent, 'env': env, + 'trading_schedule': trading_schedule, } source = SpecificEquityTrades(*args, **kwargs) return source - - -def create_test_df_source(sim_params=None, env=None, bars='daily'): - if bars == 'daily': - freq = pd.datetools.BDay() - elif bars == 'minute': - freq = pd.datetools.Minute() - else: - raise ValueError('%s bars not understood.' % bars) - - if sim_params and bars == 'daily': - index = sim_params.trading_days - else: - if env is None: - env = TradingEnvironment(load=noop_load) - - start = pd.datetime(1990, 1, 3, 0, 0, 0, 0, pytz.utc) - end = pd.datetime(1990, 1, 8, 0, 0, 0, 0, pytz.utc) - - days = env.days_in_range(start, end) - - if bars == 'daily': - index = days - if bars == 'minute': - index = pd.DatetimeIndex([], freq=freq) - - for day in days: - day_index = env.market_minutes_for_day(day) - index = index.append(day_index) - - x = np.arange(1, len(index) + 1) - - df = pd.DataFrame(x, index=index, columns=[0]) - - return DataFrameSource(df), df - - -def create_test_panel_source(sim_params=None, env=None, source_type=None): - start = sim_params.first_open \ - if sim_params else pd.datetime(1990, 1, 3, 0, 0, 0, 0, pytz.utc) - - end = sim_params.last_close \ - if sim_params else pd.datetime(1990, 1, 8, 0, 0, 0, 0, pytz.utc) - - if env is None: - env = TradingEnvironment(load=noop_load) - - index = env.days_in_range(start, end) - - price = np.arange(0, len(index)) - volume = np.ones(len(index)) * 1000 - - arbitrary = np.ones(len(index)) - - df = pd.DataFrame({'price': price, - 'volume': volume, - 'arbitrary': arbitrary}, - index=index) - if source_type: - df['type'] = source_type - - panel = pd.Panel.from_dict({0: df}) - - return DataPanelSource(panel), panel - - -def create_test_panel_ohlc_source(sim_params, env): - start = sim_params.first_open \ - if sim_params else pd.datetime(1990, 1, 3, 0, 0, 0, 0, pytz.utc) - - end = sim_params.last_close \ - if sim_params else pd.datetime(1990, 1, 8, 0, 0, 0, 0, pytz.utc) - - index = env.days_in_range(start, end) - price = np.arange(0, len(index)) + 100 - high = price * 1.05 - low = price * 0.95 - open_ = price + .1 * (price % 2 - .5) - volume = np.ones(len(index)) * 1000 - arbitrary = np.ones(len(index)) - - df = pd.DataFrame({'price': price, - 'high': high, - 'low': low, - 'open': open_, - 'volume': volume, - 'arbitrary': arbitrary}, - index=index) - panel = pd.Panel.from_dict({0: df}) - - return DataPanelSource(panel), panel diff --git a/zipline/utils/simfactory.py b/zipline/utils/simfactory.py index cb882a31..4388f9d1 100644 --- a/zipline/utils/simfactory.py +++ b/zipline/utils/simfactory.py @@ -2,6 +2,7 @@ import zipline.utils.factory as factory from zipline.testing.core import create_data_portal_from_trade_history from zipline.test_algorithms import TestAlgorithm +from zipline.utils.calendars import default_nyse_schedule def create_test_zipline(**config): @@ -48,6 +49,11 @@ def create_test_zipline(**config): else: order_amount = 100 + if 'trading_schedule' in config: + trading_schedule = config['trading_schedule'] + else: + trading_schedule = default_nyse_schedule + # ------------------- # Create the Algo # ------------------- @@ -60,6 +66,7 @@ def create_test_zipline(**config): order_count, sim_params=config.get('sim_params', factory.create_simulation_parameters()), + trading_schedule=trading_schedule, slippage=config.get('slippage'), identifiers=sid_list ) @@ -75,6 +82,7 @@ def create_test_zipline(**config): sid_list, test_algo.sim_params, test_algo.trading_environment, + trading_schedule, concurrent=concurrent_trades, ) @@ -87,6 +95,7 @@ def create_test_zipline(**config): data_portal = create_data_portal_from_trade_history( config['env'], + trading_schedule, config['tempdir'], config['sim_params'], trades_by_sid