# # Copyright 2014 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 os from nose_parameterized import parameterized from unittest import TestCase from testfixtures import TempDirectory import pandas as pd import zipline.utils.factory as factory from zipline.finance import trading from zipline.finance.blotter import Blotter from zipline.finance.order import ORDER_STATUS from zipline.finance.execution import ( LimitOrder, MarketOrder, StopLimitOrder, StopOrder, ) from zipline.testing import( setup_logger, teardown_logger, ) from zipline.gens.sim_engine import DAY_END, BAR from zipline.finance.cancel_policy import EODCancel, NeverCancel from zipline.finance.slippage import DEFAULT_VOLUME_SLIPPAGE_BAR_LIMIT, \ FixedSlippage from .utils.daily_bar_writer import DailyBarWriterFromDataFrames from zipline.data.us_equity_pricing import BcolzDailyBarReader from zipline.data.data_portal import DataPortal from zipline.protocol import BarData class BlotterTestCase(TestCase): @classmethod def setUpClass(cls): setup_logger(cls) cls.env = trading.TradingEnvironment() cls.sim_params = factory.create_simulation_parameters( start=pd.Timestamp("2006-01-05", tz='UTC'), end=pd.Timestamp("2006-01-06", tz='UTC') ) cls.env.write_data(equities_data={ 24: { 'start_date': cls.sim_params.trading_days[0], 'end_date': cls.env.next_trading_day( cls.sim_params.trading_days[-1] ) }, 25: { 'start_date': cls.sim_params.trading_days[0], 'end_date': cls.env.next_trading_day( cls.sim_params.trading_days[-1] ) } }) cls.tempdir = TempDirectory() assets = { 24: pd.DataFrame({ "open": [50, 50], "high": [50, 50], "low": [50, 50], "close": [50, 50], "volume": [100, 400], "day": [day.value for day in cls.sim_params.trading_days] }), 25: pd.DataFrame({ "open": [50, 50], "high": [50, 50], "low": [50, 50], "close": [50, 50], "volume": [100, 400], "day": [day.value for day in cls.sim_params.trading_days] }) } path = os.path.join(cls.tempdir.path, "tempdata.bcolz") DailyBarWriterFromDataFrames(assets).write( path, cls.sim_params.trading_days, assets ) equity_daily_reader = BcolzDailyBarReader(path) cls.data_portal = DataPortal( cls.env, equity_daily_reader=equity_daily_reader, ) @classmethod def tearDownClass(cls): del cls.env cls.tempdir.cleanup() teardown_logger(cls) @parameterized.expand([(MarketOrder(), None, None), (LimitOrder(10), 10, None), (StopOrder(10), None, 10), (StopLimitOrder(10, 20), 10, 20)]) def test_blotter_order_types(self, style_obj, expected_lmt, expected_stp): blotter = Blotter('daily', self.env.asset_finder) asset_24 = blotter.asset_finder.retrieve_asset(24) blotter.order(asset_24, 100, style_obj) result = blotter.open_orders[asset_24][0] self.assertEqual(result.limit, expected_lmt) self.assertEqual(result.stop, expected_stp) def test_cancel(self): blotter = Blotter('daily', self.env.asset_finder) asset_24 = blotter.asset_finder.retrieve_asset(24) asset_25 = blotter.asset_finder.retrieve_asset(25) oid_1 = blotter.order(asset_24, 100, MarketOrder()) oid_2 = blotter.order(asset_24, 200, MarketOrder()) oid_3 = blotter.order(asset_24, 300, MarketOrder()) # Create an order for another asset to verify that we don't remove it # when we do cancel_all on 24. blotter.order(asset_25, 150, MarketOrder()) self.assertEqual(len(blotter.open_orders), 2) self.assertEqual(len(blotter.open_orders[asset_24]), 3) self.assertEqual( [o.amount for o in blotter.open_orders[asset_24]], [100, 200, 300], ) blotter.cancel(oid_2) self.assertEqual(len(blotter.open_orders), 2) self.assertEqual(len(blotter.open_orders[asset_24]), 2) self.assertEqual( [o.amount for o in blotter.open_orders[asset_24]], [100, 300], ) self.assertEqual( [o.id for o in blotter.open_orders[asset_24]], [oid_1, oid_3], ) blotter.cancel_all_orders_for_asset(asset_24) self.assertEqual(len(blotter.open_orders), 1) self.assertEqual(list(blotter.open_orders), [asset_25]) def test_blotter_eod_cancellation(self): blotter = Blotter('minute', self.env.asset_finder, cancel_policy=EODCancel()) asset_24 = blotter.asset_finder.retrieve_asset(24) # Make two orders for the same sid, so we can test that we are not # mutating the orders list as we are cancelling orders blotter.order(asset_24, 100, MarketOrder()) blotter.order(asset_24, -100, MarketOrder()) self.assertEqual(len(blotter.new_orders), 2) order_ids = [order.id for order in blotter.open_orders[asset_24]] self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN) self.assertEqual(blotter.new_orders[1].status, ORDER_STATUS.OPEN) blotter.execute_cancel_policy(BAR) self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN) self.assertEqual(blotter.new_orders[1].status, ORDER_STATUS.OPEN) blotter.execute_cancel_policy(DAY_END) for order_id in order_ids: order = blotter.orders[order_id] self.assertEqual(order.status, ORDER_STATUS.CANCELLED) def test_blotter_never_cancel(self): blotter = Blotter('minute', self.env.asset_finder, cancel_policy=NeverCancel()) blotter.order(blotter.asset_finder.retrieve_asset(24), 100, MarketOrder()) self.assertEqual(len(blotter.new_orders), 1) self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN) blotter.execute_cancel_policy(BAR) self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN) blotter.execute_cancel_policy(DAY_END) self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN) def test_order_rejection(self): blotter = Blotter(self.sim_params.data_frequency, self.env.asset_finder) asset_24 = blotter.asset_finder.retrieve_asset(24) # Reject a nonexistent order -> no order appears in new_order, # no exceptions raised out blotter.reject(56) self.assertEqual(blotter.new_orders, []) # Basic tests of open order behavior open_order_id = blotter.order(asset_24, 100, MarketOrder()) second_order_id = blotter.order(asset_24, 50, MarketOrder()) self.assertEqual(len(blotter.open_orders[asset_24]), 2) open_order = blotter.open_orders[asset_24][0] self.assertEqual(open_order.status, ORDER_STATUS.OPEN) self.assertEqual(open_order.id, open_order_id) self.assertIn(open_order, blotter.new_orders) # Reject that order immediately (same bar, i.e. still in new_orders) blotter.reject(open_order_id) self.assertEqual(len(blotter.new_orders), 2) self.assertEqual(len(blotter.open_orders[asset_24]), 1) still_open_order = blotter.new_orders[0] self.assertEqual(still_open_order.id, second_order_id) self.assertEqual(still_open_order.status, ORDER_STATUS.OPEN) rejected_order = blotter.new_orders[1] self.assertEqual(rejected_order.status, ORDER_STATUS.REJECTED) self.assertEqual(rejected_order.reason, '') # Do it again, but reject it at a later time (after tradesimulation # pulls it from new_orders) blotter = Blotter(self.sim_params.data_frequency, self.env.asset_finder) new_open_id = blotter.order(asset_24, 10, MarketOrder()) new_open_order = blotter.open_orders[asset_24][0] self.assertEqual(new_open_id, new_open_order.id) # Pretend that the trade simulation did this. blotter.new_orders = [] rejection_reason = "Not enough cash on hand." blotter.reject(new_open_id, reason=rejection_reason) rejected_order = blotter.new_orders[0] self.assertEqual(rejected_order.id, new_open_id) self.assertEqual(rejected_order.status, ORDER_STATUS.REJECTED) self.assertEqual(rejected_order.reason, rejection_reason) # You can't reject a filled order. # Reset for paranoia blotter = Blotter(self.sim_params.data_frequency, self.env.asset_finder) blotter.slippage_func = FixedSlippage() filled_id = blotter.order(asset_24, 100, MarketOrder()) filled_order = None blotter.current_dt = self.sim_params.trading_days[-1] bar_data = BarData( self.data_portal, lambda: self.sim_params.trading_days[-1], self.sim_params.data_frequency, ) txns, _ = blotter.get_transactions(bar_data) for txn in txns: filled_order = blotter.orders[txn.order_id] self.assertEqual(filled_order.id, filled_id) self.assertIn(filled_order, blotter.new_orders) self.assertEqual(filled_order.status, ORDER_STATUS.FILLED) self.assertNotIn(filled_order, blotter.open_orders[asset_24]) blotter.reject(filled_id) updated_order = blotter.orders[filled_id] self.assertEqual(updated_order.status, ORDER_STATUS.FILLED) def test_order_hold(self): """ Held orders act almost identically to open orders, except for the status indication. When a fill happens, the order should switch status to OPEN/FILLED as necessary """ blotter = Blotter(self.sim_params.data_frequency, self.env.asset_finder) # Nothing happens on held of a non-existent order blotter.hold(56) self.assertEqual(blotter.new_orders, []) asset_24 = blotter.asset_finder.retrieve_asset(24) open_id = blotter.order(asset_24, 100, MarketOrder()) open_order = blotter.open_orders[asset_24][0] self.assertEqual(open_order.id, open_id) blotter.hold(open_id) self.assertEqual(len(blotter.new_orders), 1) self.assertEqual(len(blotter.open_orders[asset_24]), 1) held_order = blotter.new_orders[0] self.assertEqual(held_order.status, ORDER_STATUS.HELD) self.assertEqual(held_order.reason, '') blotter.cancel(held_order.id) self.assertEqual(len(blotter.new_orders), 1) self.assertEqual(len(blotter.open_orders[asset_24]), 0) cancelled_order = blotter.new_orders[0] self.assertEqual(cancelled_order.id, held_order.id) self.assertEqual(cancelled_order.status, ORDER_STATUS.CANCELLED) for data in ([100, self.sim_params.trading_days[0]], [400, self.sim_params.trading_days[1]]): # Verify that incoming fills will change the order status. trade_amt = data[0] dt = data[1] order_size = 100 expected_filled = int(trade_amt * DEFAULT_VOLUME_SLIPPAGE_BAR_LIMIT) expected_open = order_size - expected_filled expected_status = ORDER_STATUS.OPEN if expected_open else \ ORDER_STATUS.FILLED blotter = Blotter(self.sim_params.data_frequency, self.env.asset_finder) open_id = blotter.order(blotter.asset_finder.retrieve_asset(24), order_size, MarketOrder()) open_order = blotter.open_orders[asset_24][0] self.assertEqual(open_id, open_order.id) blotter.hold(open_id) held_order = blotter.new_orders[0] filled_order = None blotter.current_dt = dt bar_data = BarData( self.data_portal, lambda: dt, self.sim_params.data_frequency, ) txns, _ = blotter.get_transactions(bar_data) for txn in txns: filled_order = blotter.orders[txn.order_id] self.assertEqual(filled_order.id, held_order.id) self.assertEqual(filled_order.status, expected_status) self.assertEqual(filled_order.filled, expected_filled) self.assertEqual(filled_order.open_amount, expected_open)