mirror of
https://github.com/wassname/catalyst.git
synced 2026-07-02 11:35:24 +08:00
Eddie Hebert
51eda06323
In preparation of adding futures, add equity to the names of both the classes and methods for writing bcolz data. Futures data will use a different minutes per day with a separate reader. This change will allow both equity and futures fixtures to be side by side. Also, break out the method which generates the dataframes and trading days member into fixtures (`EquityMinuteBarData` and `EquityDailyBarData`) on which the `*BarReader` fixture depends. This fixture is separated out to enable reader/writers in different formats to use the same data setup. (There is internal code which needs to write minute and daily bar data in a database format.)
337 lines
13 KiB
Python
337 lines
13 KiB
Python
#
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# Copyright 2014 Quantopian, Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from nose_parameterized import parameterized
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import pandas as pd
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from zipline.finance.blotter import Blotter
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from zipline.finance.order import ORDER_STATUS, Order
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from zipline.finance.execution import (
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LimitOrder,
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MarketOrder,
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StopLimitOrder,
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StopOrder,
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)
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from zipline.gens.sim_engine import DAY_END, BAR
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from zipline.finance.cancel_policy import EODCancel, NeverCancel
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from zipline.finance.slippage import (
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DEFAULT_VOLUME_SLIPPAGE_BAR_LIMIT,
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FixedSlippage,
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)
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from zipline.protocol import BarData
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from zipline.testing.fixtures import (
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WithDataPortal,
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WithLogger,
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WithSimParams,
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ZiplineTestCase,
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)
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class BlotterTestCase(WithLogger,
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WithDataPortal,
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WithSimParams,
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ZiplineTestCase):
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START_DATE = pd.Timestamp('2006-01-05', tz='utc')
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END_DATE = pd.Timestamp('2006-01-06', tz='utc')
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ASSET_FINDER_EQUITY_SIDS = 24, 25
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@classmethod
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def make_equity_daily_bar_data(cls):
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yield 24, pd.DataFrame(
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{
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'open': [50, 50],
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'high': [50, 50],
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'low': [50, 50],
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'close': [50, 50],
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'volume': [100, 400],
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},
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index=cls.sim_params.trading_days,
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)
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yield 25, pd.DataFrame(
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{
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'open': [50, 50],
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'high': [50, 50],
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'low': [50, 50],
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'close': [50, 50],
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'volume': [100, 400],
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},
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index=cls.sim_params.trading_days,
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)
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@parameterized.expand([(MarketOrder(), None, None),
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(LimitOrder(10), 10, None),
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(StopOrder(10), None, 10),
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(StopLimitOrder(10, 20), 10, 20)])
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def test_blotter_order_types(self, style_obj, expected_lmt, expected_stp):
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blotter = Blotter('daily', self.env.asset_finder)
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asset_24 = blotter.asset_finder.retrieve_asset(24)
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blotter.order(asset_24, 100, style_obj)
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result = blotter.open_orders[asset_24][0]
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self.assertEqual(result.limit, expected_lmt)
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self.assertEqual(result.stop, expected_stp)
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def test_cancel(self):
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blotter = Blotter('daily', self.env.asset_finder)
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asset_24 = blotter.asset_finder.retrieve_asset(24)
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asset_25 = blotter.asset_finder.retrieve_asset(25)
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oid_1 = blotter.order(asset_24, 100, MarketOrder())
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oid_2 = blotter.order(asset_24, 200, MarketOrder())
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oid_3 = blotter.order(asset_24, 300, MarketOrder())
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# Create an order for another asset to verify that we don't remove it
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# when we do cancel_all on 24.
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blotter.order(asset_25, 150, MarketOrder())
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self.assertEqual(len(blotter.open_orders), 2)
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self.assertEqual(len(blotter.open_orders[asset_24]), 3)
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self.assertEqual(
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[o.amount for o in blotter.open_orders[asset_24]],
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[100, 200, 300],
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)
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blotter.cancel(oid_2)
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self.assertEqual(len(blotter.open_orders), 2)
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self.assertEqual(len(blotter.open_orders[asset_24]), 2)
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self.assertEqual(
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[o.amount for o in blotter.open_orders[asset_24]],
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[100, 300],
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)
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self.assertEqual(
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[o.id for o in blotter.open_orders[asset_24]],
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[oid_1, oid_3],
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)
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blotter.cancel_all_orders_for_asset(asset_24)
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self.assertEqual(len(blotter.open_orders), 1)
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self.assertEqual(list(blotter.open_orders), [asset_25])
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def test_blotter_eod_cancellation(self):
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blotter = Blotter('minute', self.env.asset_finder,
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cancel_policy=EODCancel())
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asset_24 = blotter.asset_finder.retrieve_asset(24)
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# Make two orders for the same sid, so we can test that we are not
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# mutating the orders list as we are cancelling orders
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blotter.order(asset_24, 100, MarketOrder())
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blotter.order(asset_24, -100, MarketOrder())
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self.assertEqual(len(blotter.new_orders), 2)
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order_ids = [order.id for order in blotter.open_orders[asset_24]]
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self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)
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self.assertEqual(blotter.new_orders[1].status, ORDER_STATUS.OPEN)
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blotter.execute_cancel_policy(BAR)
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self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)
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self.assertEqual(blotter.new_orders[1].status, ORDER_STATUS.OPEN)
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blotter.execute_cancel_policy(DAY_END)
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for order_id in order_ids:
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order = blotter.orders[order_id]
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self.assertEqual(order.status, ORDER_STATUS.CANCELLED)
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def test_blotter_never_cancel(self):
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blotter = Blotter('minute', self.env.asset_finder,
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cancel_policy=NeverCancel())
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blotter.order(blotter.asset_finder.retrieve_asset(24), 100,
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MarketOrder())
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self.assertEqual(len(blotter.new_orders), 1)
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self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)
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blotter.execute_cancel_policy(BAR)
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self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)
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blotter.execute_cancel_policy(DAY_END)
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self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)
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def test_order_rejection(self):
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blotter = Blotter(self.sim_params.data_frequency,
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self.env.asset_finder)
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asset_24 = blotter.asset_finder.retrieve_asset(24)
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# Reject a nonexistent order -> no order appears in new_order,
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# no exceptions raised out
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blotter.reject(56)
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self.assertEqual(blotter.new_orders, [])
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# Basic tests of open order behavior
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open_order_id = blotter.order(asset_24, 100, MarketOrder())
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second_order_id = blotter.order(asset_24, 50, MarketOrder())
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self.assertEqual(len(blotter.open_orders[asset_24]), 2)
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open_order = blotter.open_orders[asset_24][0]
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self.assertEqual(open_order.status, ORDER_STATUS.OPEN)
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self.assertEqual(open_order.id, open_order_id)
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self.assertIn(open_order, blotter.new_orders)
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# Reject that order immediately (same bar, i.e. still in new_orders)
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blotter.reject(open_order_id)
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self.assertEqual(len(blotter.new_orders), 2)
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self.assertEqual(len(blotter.open_orders[asset_24]), 1)
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still_open_order = blotter.new_orders[0]
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self.assertEqual(still_open_order.id, second_order_id)
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self.assertEqual(still_open_order.status, ORDER_STATUS.OPEN)
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rejected_order = blotter.new_orders[1]
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self.assertEqual(rejected_order.status, ORDER_STATUS.REJECTED)
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self.assertEqual(rejected_order.reason, '')
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# Do it again, but reject it at a later time (after tradesimulation
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# pulls it from new_orders)
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blotter = Blotter(self.sim_params.data_frequency,
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self.env.asset_finder)
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new_open_id = blotter.order(asset_24, 10, MarketOrder())
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new_open_order = blotter.open_orders[asset_24][0]
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self.assertEqual(new_open_id, new_open_order.id)
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# Pretend that the trade simulation did this.
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blotter.new_orders = []
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rejection_reason = "Not enough cash on hand."
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blotter.reject(new_open_id, reason=rejection_reason)
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rejected_order = blotter.new_orders[0]
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self.assertEqual(rejected_order.id, new_open_id)
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self.assertEqual(rejected_order.status, ORDER_STATUS.REJECTED)
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self.assertEqual(rejected_order.reason, rejection_reason)
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# You can't reject a filled order.
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# Reset for paranoia
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blotter = Blotter(self.sim_params.data_frequency,
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self.env.asset_finder)
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blotter.slippage_func = FixedSlippage()
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filled_id = blotter.order(asset_24, 100, MarketOrder())
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filled_order = None
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blotter.current_dt = self.sim_params.trading_days[-1]
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bar_data = BarData(
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self.data_portal,
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lambda: self.sim_params.trading_days[-1],
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self.sim_params.data_frequency,
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)
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txns, _, closed_orders = blotter.get_transactions(bar_data)
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for txn in txns:
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filled_order = blotter.orders[txn.order_id]
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blotter.prune_orders(closed_orders)
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self.assertEqual(filled_order.id, filled_id)
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self.assertIn(filled_order, blotter.new_orders)
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self.assertEqual(filled_order.status, ORDER_STATUS.FILLED)
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self.assertNotIn(filled_order, blotter.open_orders[asset_24])
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blotter.reject(filled_id)
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updated_order = blotter.orders[filled_id]
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self.assertEqual(updated_order.status, ORDER_STATUS.FILLED)
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def test_order_hold(self):
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"""
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Held orders act almost identically to open orders, except for the
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status indication. When a fill happens, the order should switch
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status to OPEN/FILLED as necessary
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"""
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blotter = Blotter(self.sim_params.data_frequency,
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self.env.asset_finder)
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# Nothing happens on held of a non-existent order
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blotter.hold(56)
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self.assertEqual(blotter.new_orders, [])
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asset_24 = blotter.asset_finder.retrieve_asset(24)
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open_id = blotter.order(asset_24, 100, MarketOrder())
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open_order = blotter.open_orders[asset_24][0]
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self.assertEqual(open_order.id, open_id)
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blotter.hold(open_id)
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self.assertEqual(len(blotter.new_orders), 1)
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self.assertEqual(len(blotter.open_orders[asset_24]), 1)
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held_order = blotter.new_orders[0]
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self.assertEqual(held_order.status, ORDER_STATUS.HELD)
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self.assertEqual(held_order.reason, '')
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blotter.cancel(held_order.id)
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self.assertEqual(len(blotter.new_orders), 1)
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self.assertEqual(len(blotter.open_orders[asset_24]), 0)
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cancelled_order = blotter.new_orders[0]
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self.assertEqual(cancelled_order.id, held_order.id)
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self.assertEqual(cancelled_order.status, ORDER_STATUS.CANCELLED)
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for data in ([100, self.sim_params.trading_days[0]],
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[400, self.sim_params.trading_days[1]]):
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# Verify that incoming fills will change the order status.
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trade_amt = data[0]
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dt = data[1]
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order_size = 100
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expected_filled = int(trade_amt *
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DEFAULT_VOLUME_SLIPPAGE_BAR_LIMIT)
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expected_open = order_size - expected_filled
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expected_status = ORDER_STATUS.OPEN if expected_open else \
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ORDER_STATUS.FILLED
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blotter = Blotter(self.sim_params.data_frequency,
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self.env.asset_finder)
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open_id = blotter.order(blotter.asset_finder.retrieve_asset(24),
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order_size, MarketOrder())
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open_order = blotter.open_orders[asset_24][0]
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self.assertEqual(open_id, open_order.id)
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blotter.hold(open_id)
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held_order = blotter.new_orders[0]
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filled_order = None
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blotter.current_dt = dt
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bar_data = BarData(
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self.data_portal,
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lambda: dt,
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self.sim_params.data_frequency,
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)
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txns, _, _ = blotter.get_transactions(bar_data)
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for txn in txns:
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filled_order = blotter.orders[txn.order_id]
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self.assertEqual(filled_order.id, held_order.id)
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self.assertEqual(filled_order.status, expected_status)
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self.assertEqual(filled_order.filled, expected_filled)
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self.assertEqual(filled_order.open_amount, expected_open)
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def test_prune_orders(self):
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blotter = Blotter(self.sim_params.data_frequency,
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self.env.asset_finder)
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asset_24 = blotter.asset_finder.retrieve_asset(24)
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asset_25 = blotter.asset_finder.retrieve_asset(25)
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blotter.order(asset_24, 100, MarketOrder())
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open_order = blotter.open_orders[asset_24][0]
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blotter.prune_orders([])
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self.assertEqual(1, len(blotter.open_orders[asset_24]))
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blotter.prune_orders([open_order])
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self.assertEqual(0, len(blotter.open_orders[asset_24]))
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# prune an order that isn't in our our open orders list, make sure
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# nothing blows up
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other_order = Order(
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dt=blotter.current_dt,
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sid=asset_25,
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amount=1
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)
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blotter.prune_orders([other_order])
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