mirror of
https://github.com/wassname/catalyst.git
synced 2026-06-29 09:21:05 +08:00
Joe Jevnik
bc0b117dc9
Changes BcolzDailyBarWriter to not be an abc, data is passed as an iterator of (sid, dataframe) pairs to the write method. Changes the AssetsDBWriter to be a single class which accepts an engine at construction time and has a `write` method for writing dataframes for the various tables. We no longer support writing the various other data types, callers should coerce their data into a dataframe themselves. See zipline.assets.synthetic for some helpers to do this. Adds many new fixtures and updates some existing fixtures to use the new ones: WithDefaultDateBounds A fixture that provides the suite a START_DATE and END_DATE. This is meant to make it easy for other fixtures to synchronize their date ranges without depending on eachother in strange ways. For example, WithBcolzMinuteBarReader and WithBcolzDailyBarReader by default should both have data for the same dates, so they may use depend on WithDefaultDates without forcing a dependency between them. WithTmpDir, WithInstanceTmpDir Provides the suite or individual test case a temporary directory. WithBcolzDailyBarReader Provides the suite a BcolzDailyBarReader which reads from bcolz data written to a temporary directory. The data will be read from dataframes and then converted to bcolz files with BcolzDailyBarWriter.write WithBcolzDailyBarReaderFromCSVs Provides the suite a BcolzDailyBarReader which reads from bcolz data written to a temporary directory. The data will be read from a collection of CSV files and then converted into the bcolz data through BcolzDailyBarWriter.write_csvs WithBcolzMinuteBarReader Provides the suite a BcolzMinuteBarReader which reads from bcolz data written to a temporary directory. The data will be read from dataframes and then converted to bcolz files with BcolzMinuteBarWriter.write WithAdjustmentReader Provides the suite a SQLiteAdjustmentReader which reads from an in memory sqlite database. The data will be read from dataframes and then converted into sqlite with SQLiteAdjustmentWriter.write WithDataPortal Provides each test case a DataPortal object with data from temporary resources.
309 lines
12 KiB
Python
309 lines
12 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
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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_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, _ = 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, 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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