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MAINT: Don't store data portal everywhere

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Removed lots of data portal references that participated in ref cycles
and prevented deterministic cleanup of dbs.
This commit is contained in:
Richard Frank
2016-04-12 19:33:22 -04:00
parent 8b610a2ab7
commit 70befd490b
8 changed files with 107 additions and 154 deletions
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tests/test_finance.py
+1 -1
View File
@@ -286,7 +286,7 @@ class FinanceTestCase(TestCase):
else:
alternator = 1
tracker = PerformanceTracker(sim_params, self.env, data_portal)
tracker = PerformanceTracker(sim_params, self.env)
# replicate what tradesim does by going through every minute or day
# of the simulation and processing open orders each time
tests/test_perf_tracking.py
+49 -81
View File
@@ -50,7 +50,7 @@ from zipline.utils.serialization_utils import (
loads_with_persistent_ids, dumps_with_persistent_ids
)
from zipline.testing.core import create_data_portal_from_trade_history, \
create_empty_splits_mergers_frame, FakeDataPortal
create_empty_splits_mergers_frame
logger = logging.getLogger('Test Perf Tracking')
@@ -167,7 +167,7 @@ def calculate_results(sim_params,
splits = splits or {}
commissions = commissions or {}
perf_tracker = perf.PerformanceTracker(sim_params, env, data_portal)
perf_tracker = perf.PerformanceTracker(sim_params, env)
results = []
@@ -189,8 +189,10 @@ def calculate_results(sim_params,
except KeyError:
pass
msg = perf_tracker.handle_market_close_daily(date)
perf_tracker.position_tracker.sync_last_sale_prices(date, False)
msg = perf_tracker.handle_market_close_daily(date, data_portal)
perf_tracker.position_tracker.sync_last_sale_prices(
date, False, data_portal,
)
msg['account'] = perf_tracker.get_account(True)
results.append(copy.deepcopy(msg))
return results
@@ -265,9 +267,7 @@ class TestSplitPerformance(unittest.TestCase):
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, FakeDataPortal()
)
perf_tracker = perf.PerformanceTracker(self.sim_params, self.env)
asset1 = self.env.asset_finder.retrieve_asset(1)
asset2 = self.env.asset_finder.retrieve_asset(2)
@@ -1240,11 +1240,10 @@ class TestPositionPerformance(unittest.TestCase):
txn1 = create_txn(self.asset1, trades_1[0].dt, 10.0, 100)
txn2 = create_txn(self.asset2, trades_1[0].dt, 10.0, -100)
pt = perf.PositionTracker(self.env.asset_finder, data_portal,
pt = perf.PositionTracker(self.env.asset_finder,
self.sim_params.data_frequency)
pp = perf.PerformancePeriod(1000.0, self.env.asset_finder,
self.sim_params.data_frequency,
data_portal)
self.sim_params.data_frequency)
pp.position_tracker = pt
pt.execute_transaction(txn1)
pp.handle_execution(txn1)
@@ -1252,7 +1251,7 @@ class TestPositionPerformance(unittest.TestCase):
pp.handle_execution(txn2)
dt = trades_1[-2].dt
pt.sync_last_sale_prices(dt, False)
pt.sync_last_sale_prices(dt, False, data_portal)
pp.calculate_performance()
@@ -1280,7 +1279,7 @@ class TestPositionPerformance(unittest.TestCase):
net_liquidation=1000.0)
dt = trades_1[-1].dt
pt.sync_last_sale_prices(dt, False)
pt.sync_last_sale_prices(dt, False, data_portal)
pp.calculate_performance()
@@ -1333,11 +1332,10 @@ class TestPositionPerformance(unittest.TestCase):
self.sim_params,
{1: trades})
txn = create_txn(self.asset1, trades[1].dt, 10.0, 1000)
pt = perf.PositionTracker(self.env.asset_finder, data_portal,
pt = perf.PositionTracker(self.env.asset_finder,
self.sim_params.data_frequency)
pp = perf.PerformancePeriod(1000.0, self.env.asset_finder,
self.sim_params.data_frequency,
data_portal)
self.sim_params.data_frequency)
pp.position_tracker = pt
pt.execute_transaction(txn)
@@ -1355,7 +1353,7 @@ class TestPositionPerformance(unittest.TestCase):
shorts_count=0)
# Validate that the account attributes were updated.
pt.sync_last_sale_prices(trades[-2].dt, False)
pt.sync_last_sale_prices(trades[-2].dt, False, data_portal)
# Validate that the account attributes were updated.
account = pp.as_account()
@@ -1373,7 +1371,7 @@ class TestPositionPerformance(unittest.TestCase):
net_liquidation=1000.0)
# now simulate a price jump to $11
pt.sync_last_sale_prices(trades[-1].dt, False)
pt.sync_last_sale_prices(trades[-1].dt, False, data_portal)
pp.calculate_performance()
@@ -1425,11 +1423,10 @@ class TestPositionPerformance(unittest.TestCase):
self.sim_params,
{1: trades})
txn = create_txn(self.asset1, trades[1].dt, 10.0, 100)
pt = perf.PositionTracker(self.env.asset_finder, data_portal,
pt = perf.PositionTracker(self.env.asset_finder,
self.sim_params.data_frequency)
pp = perf.PerformancePeriod(1000.0, self.env.asset_finder,
self.sim_params.data_frequency,
data_portal,
period_open=self.sim_params.period_start,
period_close=self.sim_params.period_end)
pp.position_tracker = pt
@@ -1444,7 +1441,7 @@ class TestPositionPerformance(unittest.TestCase):
# stocks with a last sale price of 0.
self.assertEqual(pp.positions[1].last_sale_price, 10.0)
pt.sync_last_sale_prices(trades[-1].dt, False)
pt.sync_last_sale_prices(trades[-1].dt, False, data_portal)
pp.calculate_performance()
@@ -1544,18 +1541,17 @@ single short-sale transaction"""
{1: trades})
txn = create_txn(self.asset1, trades[1].dt, 10.0, -100)
pt = perf.PositionTracker(self.env.asset_finder, data_portal,
pt = perf.PositionTracker(self.env.asset_finder,
self.sim_params.data_frequency)
pp = perf.PerformancePeriod(
1000.0, self.env.asset_finder,
self.sim_params.data_frequency,
data_portal)
self.sim_params.data_frequency)
pp.position_tracker = pt
pt.execute_transaction(txn)
pp.handle_execution(txn)
pt.sync_last_sale_prices(trades_1[-1].dt, False)
pt.sync_last_sale_prices(trades_1[-1].dt, False, data_portal)
pp.calculate_performance()
@@ -1611,7 +1607,7 @@ single short-sale transaction"""
# simulate a rollover to a new period
pp.rollover()
pt.sync_last_sale_prices(trades[-1].dt, False)
pt.sync_last_sale_prices(trades[-1].dt, False, data_portal)
pp.calculate_performance()
@@ -1665,17 +1661,16 @@ single short-sale transaction"""
)
# now run a performance period encompassing the entire trade sample.
ptTotal = perf.PositionTracker(self.env.asset_finder, data_portal,
ptTotal = perf.PositionTracker(self.env.asset_finder,
self.sim_params.data_frequency)
ppTotal = perf.PerformancePeriod(1000.0, self.env.asset_finder,
self.sim_params.data_frequency,
data_portal)
self.sim_params.data_frequency)
ppTotal.position_tracker = pt
ptTotal.execute_transaction(txn)
ppTotal.handle_execution(txn)
ptTotal.sync_last_sale_prices(trades[-1].dt, False)
ptTotal.sync_last_sale_prices(trades[-1].dt, False, data_portal)
ppTotal.calculate_performance()
@@ -1778,11 +1773,10 @@ cost of sole txn in test"
)
txn = create_txn(self.asset3, trades[1].dt, 10.0, 1)
pt = perf.PositionTracker(self.env.asset_finder, data_portal,
pt = perf.PositionTracker(self.env.asset_finder,
self.sim_params.data_frequency)
pp = perf.PerformancePeriod(1000.0, self.env.asset_finder,
self.sim_params.data_frequency,
data_portal)
self.sim_params.data_frequency)
pp.position_tracker = pt
pt.execute_transaction(txn)
@@ -1795,7 +1789,7 @@ cost of sole txn in test"
# stocks with a last sale price of 0.
self.assertEqual(pp.positions[3].last_sale_price, 10.0)
pt.sync_last_sale_prices(trades[-1].dt, False)
pt.sync_last_sale_prices(trades[-1].dt, False, data_portal)
pp.calculate_performance()
self.assertEqual(
@@ -1899,17 +1893,16 @@ single short-sale transaction"""
trades_1 = trades[:-2]
txn = create_txn(self.asset3, trades[0].dt, 10.0, -1)
pt = perf.PositionTracker(self.env.asset_finder, data_portal,
pt = perf.PositionTracker(self.env.asset_finder,
self.sim_params.data_frequency)
pp = perf.PerformancePeriod(1000.0, self.env.asset_finder,
self.sim_params.data_frequency,
data_portal)
self.sim_params.data_frequency)
pp.position_tracker = pt
pt.execute_transaction(txn)
pp.handle_execution(txn)
pt.sync_last_sale_prices(trades[-3].dt, False)
pt.sync_last_sale_prices(trades[-3].dt, False, data_portal)
pp.calculate_performance()
self.assertEqual(
@@ -1969,7 +1962,7 @@ single short-sale transaction"""
# simulate a rollover to a new period
pp.rollover()
pt.sync_last_sale_prices(trades_2[-1].dt, False)
pt.sync_last_sale_prices(trades_2[-1].dt, False, data_portal)
pp.calculate_performance()
self.assertEqual(
@@ -2027,21 +2020,20 @@ single short-sale transaction"""
)
# now run a performance period encompassing the entire trade sample.
ptTotal = perf.PositionTracker(self.env.asset_finder, data_portal,
ptTotal = perf.PositionTracker(self.env.asset_finder,
self.sim_params.data_frequency)
ppTotal = perf.PerformancePeriod(1000.0, self.env.asset_finder,
self.sim_params.data_frequency,
data_portal)
self.sim_params.data_frequency)
ppTotal.position_tracker = ptTotal
for trade in trades_1:
ptTotal.sync_last_sale_prices(trade.dt, False)
ptTotal.sync_last_sale_prices(trade.dt, False, data_portal)
ptTotal.execute_transaction(txn)
ppTotal.handle_execution(txn)
for trade in trades_2:
ptTotal.sync_last_sale_prices(trade.dt, False)
ptTotal.sync_last_sale_prices(trade.dt, False, data_portal)
ppTotal.calculate_performance()
@@ -2144,11 +2136,10 @@ trade after cover"""
short_txn = create_txn(self.asset1, trades[1].dt, 10.0, -100)
cover_txn = create_txn(self.asset1, trades[6].dt, 7.0, 100)
pt = perf.PositionTracker(self.env.asset_finder, data_portal,
pt = perf.PositionTracker(self.env.asset_finder,
self.sim_params.data_frequency)
pp = perf.PerformancePeriod(1000.0, self.env.asset_finder,
self.sim_params.data_frequency,
data_portal)
self.sim_params.data_frequency)
pp.position_tracker = pt
pt.execute_transaction(short_txn)
@@ -2156,7 +2147,7 @@ trade after cover"""
pt.execute_transaction(cover_txn)
pp.handle_execution(cover_txn)
pt.sync_last_sale_prices(trades[-1].dt, False)
pt.sync_last_sale_prices(trades[-1].dt, False, data_portal)
pp.calculate_performance()
@@ -2231,13 +2222,12 @@ shares in position"
self.sim_params,
{1: trades})
pt = perf.PositionTracker(self.env.asset_finder, data_portal,
pt = perf.PositionTracker(self.env.asset_finder,
self.sim_params.data_frequency)
pp = perf.PerformancePeriod(
1000.0,
self.env.asset_finder,
self.sim_params.data_frequency,
data_portal,
period_open=self.sim_params.period_start,
period_close=self.sim_params.trading_days[-1]
)
@@ -2264,7 +2254,7 @@ shares in position"
"should have a cost basis of 11"
)
pt.sync_last_sale_prices(dt, False)
pt.sync_last_sale_prices(dt, False, data_portal)
pp.calculate_performance()
@@ -2281,7 +2271,7 @@ shares in position"
pp.handle_execution(sale_txn)
dt = down_tick.dt
pt.sync_last_sale_prices(dt, False)
pt.sync_last_sale_prices(dt, False, data_portal)
pp.calculate_performance()
self.assertEqual(
@@ -2299,11 +2289,10 @@ shares in position"
self.assertEqual(pp.pnl, -800, "this period goes from +400 to -400")
pt3 = perf.PositionTracker(self.env.asset_finder, data_portal,
pt3 = perf.PositionTracker(self.env.asset_finder,
self.sim_params.data_frequency)
pp3 = perf.PerformancePeriod(1000.0, self.env.asset_finder,
self.sim_params.data_frequency,
data_portal)
self.sim_params.data_frequency)
pp3.position_tracker = pt3
average_cost = 0
@@ -2317,7 +2306,7 @@ shares in position"
pp3.handle_execution(sale_txn)
trades.append(down_tick)
pt3.sync_last_sale_prices(trades[-1].dt, False)
pt3.sync_last_sale_prices(trades[-1].dt, False, data_portal)
pp3.calculate_performance()
self.assertEqual(
@@ -2351,18 +2340,11 @@ shares in position"
)
cost_bases = [10, 10, 0, 8, 9, 9, 13, 13.5]
trades = factory.create_trade_history(*history_args)
transactions = factory.create_txn_history(*history_args)
data_portal = create_data_portal_from_trade_history(
self.env,
self.tempdir,
self.sim_params,
{1: trades})
pt = perf.PositionTracker(self.env.asset_finder, data_portal,
pt = perf.PositionTracker(self.env.asset_finder,
self.sim_params.data_frequency)
pp = perf.PerformancePeriod(1000.0, self.env.asset_finder, data_portal,
pp = perf.PerformancePeriod(1000.0, self.env.asset_finder,
self.sim_params.data_frequency)
pp.position_tracker = pt
@@ -2413,22 +2395,8 @@ class TestPositionTracker(unittest.TestCase):
sim_params = factory.create_simulation_parameters(
num_days=4, env=self.env
)
trades = factory.create_trade_history(
1,
[10, 10, 10, 11],
[100, 100, 100, 100],
oneday,
sim_params,
env=self.env
)
data_portal = create_data_portal_from_trade_history(
self.env,
self.tempdir,
sim_params,
{1: trades})
pt = perf.PositionTracker(self.env.asset_finder, data_portal,
pt = perf.PositionTracker(self.env.asset_finder,
sim_params.data_frequency)
pos_stats = pt.stats()
@@ -2450,7 +2418,7 @@ class TestPositionTracker(unittest.TestCase):
self.assertNotIsInstance(val, (bool, np.bool_))
def test_position_values_and_exposures(self):
pt = perf.PositionTracker(self.env.asset_finder, None, None)
pt = perf.PositionTracker(self.env.asset_finder, None)
dt = pd.Timestamp("1984/03/06 3:00PM")
pos1 = perf.Position(1, amount=np.float64(10.0),
last_sale_date=dt, last_sale_price=10)
@@ -2482,7 +2450,7 @@ class TestPositionTracker(unittest.TestCase):
self.assertEqual(100 - 200 + 300000 - 400000, pos_stats.net_exposure)
def test_update_positions(self):
pt = perf.PositionTracker(self.env.asset_finder, None, None)
pt = perf.PositionTracker(self.env.asset_finder, None)
dt = pd.Timestamp("2014/01/01 3:00PM")
pos1 = perf.Position(1, amount=np.float64(10.0),
last_sale_date=dt, last_sale_price=10)