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Merge pull request #1793 from quantopian/tests-without-yahoo

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TST: Don't require downloading of data for tests
This commit is contained in:
Richard Frank
2017-05-18 13:27:08 -04:00
committed by GitHub
parent ca26208569 8734224701
commit be8ea7c54c
12 changed files with 145 additions and 75 deletions
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tests/pipeline/test_pipeline_algo.py
+3 -3
View File
@@ -566,7 +566,7 @@ class PipelineAlgorithmTestCase(WithBcolzEquityDailyBarReaderFromCSVs,
)
algo.run(
FakeDataPortal(),
FakeDataPortal(self.env),
# Yes, I really do want to use the start and end dates I passed to
# TradingAlgorithm.
overwrite_sim_params=False,
@@ -606,7 +606,7 @@ class PipelineAlgorithmTestCase(WithBcolzEquityDailyBarReaderFromCSVs,
)
algo.run(
FakeDataPortal(),
FakeDataPortal(self.env),
overwrite_sim_params=False,
)
@@ -654,7 +654,7 @@ class PipelineAlgorithmTestCase(WithBcolzEquityDailyBarReaderFromCSVs,
)
algo.run(
FakeDataPortal(),
FakeDataPortal(self.env),
overwrite_sim_params=False,
)
tests/test_algorithm.py
+65 -38
View File
@@ -88,11 +88,11 @@ from zipline.finance.asset_restrictions import (
)
from zipline.testing import (
FakeDataPortal,
copy_market_data,
create_daily_df_for_asset,
create_data_portal,
create_data_portal_from_trade_history,
create_minute_df_for_asset,
empty_trading_env,
make_test_handler,
make_trade_data_for_asset_info,
parameter_space,
@@ -100,6 +100,7 @@ from zipline.testing import (
tmp_trading_env,
to_utc,
trades_by_sid_to_dfs,
tmp_dir,
)
from zipline.testing import RecordBatchBlotter
from zipline.testing.fixtures import (
@@ -108,7 +109,6 @@ from zipline.testing.fixtures import (
WithSimParams,
WithTradingEnvironment,
WithTmpDir,
WithTradingCalendars,
ZiplineTestCase,
)
from zipline.test_algorithms import (
@@ -314,6 +314,7 @@ def handle_data(algo, data):
initialize=lambda context: None,
handle_data=lambda context, data: None,
sim_params=self.sim_params,
env=self.env,
)
# Verify that api methods get resolved dynamically by patching them out
@@ -785,7 +786,8 @@ def log_nyse_close(context, data):
for i, date in enumerate(dates)
]
)
with tmp_trading_env(equities=metadata) as env:
with tmp_trading_env(equities=metadata,
load=self.make_load_function()) as env:
algo = TradingAlgorithm(env=env)
# Set the period end to a date after the period end
@@ -852,7 +854,8 @@ class TestTransformAlgorithm(WithLogger,
def init_class_fixtures(cls):
super(TestTransformAlgorithm, cls).init_class_fixtures()
cls.futures_env = cls.enter_class_context(
tmp_trading_env(futures=cls.make_futures_info()),
tmp_trading_env(futures=cls.make_futures_info(),
load=cls.make_load_function()),
)
def test_invalid_order_parameters(self):
@@ -892,7 +895,8 @@ def before_trading_start(context, data):
def test_run_twice(self):
algo1 = TestRegisterTransformAlgorithm(
sim_params=self.sim_params,
sids=[0, 1]
sids=[0, 1],
env=self.env,
)
res1 = algo1.run(self.data_portal)
@@ -901,7 +905,8 @@ def before_trading_start(context, data):
# use the newly instantiated environment.
algo2 = TestRegisterTransformAlgorithm(
sim_params=self.sim_params,
sids=[0, 1]
sids=[0, 1],
env=self.env,
)
res2 = algo2.run(self.data_portal)
@@ -1062,7 +1067,8 @@ def before_trading_start(context, data):
}] * 2)
equities['symbol'] = ['A', 'B']
with TempDirectory() as tempdir, \
tmp_trading_env(equities=equities) as env:
tmp_trading_env(equities=equities,
load=self.make_load_function()) as env:
sim_params = SimulationParameters(
start_session=start_session,
end_session=period_end,
@@ -1569,15 +1575,16 @@ class TestAlgoScript(WithLogger,
def test_noop(self):
algo = TradingAlgorithm(initialize=initialize_noop,
handle_data=handle_data_noop)
handle_data=handle_data_noop,
env=self.env)
algo.run(self.data_portal)
def test_noop_string(self):
algo = TradingAlgorithm(script=noop_algo)
algo = TradingAlgorithm(script=noop_algo, env=self.env)
algo.run(self.data_portal)
def test_no_handle_data(self):
algo = TradingAlgorithm(script=no_handle_data)
algo = TradingAlgorithm(script=no_handle_data, env=self.env)
algo.run(self.data_portal)
def test_api_calls(self):
@@ -1593,7 +1600,8 @@ class TestAlgoScript(WithLogger,
def test_api_get_environment(self):
platform = 'zipline'
algo = TradingAlgorithm(script=api_get_environment_algo,
platform=platform)
platform=platform,
env=self.env)
algo.run(self.data_portal)
self.assertEqual(algo.environment, platform)
@@ -1779,6 +1787,7 @@ def handle_data(context, data):
test_algo = TradingAlgorithm(
script=record_variables,
sim_params=self.sim_params,
env=self.env,
)
set_algo_instance(test_algo)
@@ -3169,7 +3178,8 @@ class TestTradingControls(WithSimParams, WithDataPortal, ZiplineTestCase):
orient='index',
)
with TempDirectory() as tempdir, \
tmp_trading_env(equities=metadata) as env:
tmp_trading_env(equities=metadata,
load=self.make_load_function()) as env:
sim_params = factory.create_simulation_parameters(
start=start,
num_days=4,
@@ -3296,7 +3306,8 @@ class TestTradingControls(WithSimParams, WithDataPortal, ZiplineTestCase):
'sid': 999,
}])
with TempDirectory() as tempdir, \
tmp_trading_env(equities=metadata) as env:
tmp_trading_env(equities=metadata,
load=self.make_load_function()) as env:
algo = SetAssetDateBoundsAlgorithm(
sim_params=self.sim_params,
env=env,
@@ -3318,7 +3329,8 @@ class TestTradingControls(WithSimParams, WithDataPortal, ZiplineTestCase):
'sid': 999,
}])
with TempDirectory() as tempdir, \
tmp_trading_env(equities=metadata) as env:
tmp_trading_env(equities=metadata,
load=self.make_load_function()) as env:
data_portal = create_data_portal(
env.asset_finder,
tempdir,
@@ -3341,7 +3353,8 @@ class TestTradingControls(WithSimParams, WithDataPortal, ZiplineTestCase):
'sid': 999,
}])
with TempDirectory() as tempdir, \
tmp_trading_env(equities=metadata) as env:
tmp_trading_env(equities=metadata,
load=self.make_load_function()) as env:
data_portal = create_data_portal(
env.asset_finder,
tempdir,
@@ -3768,7 +3781,7 @@ class TestFuturesAlgo(WithDataPortal, WithSimParams, ZiplineTestCase):
self.assertEqual(txn['price'], expected_price)
class TestTradingAlgorithm(ZiplineTestCase):
class TestTradingAlgorithm(WithTradingEnvironment, ZiplineTestCase):
def test_analyze_called(self):
self.perf_ref = None
@@ -3785,11 +3798,11 @@ class TestTradingAlgorithm(ZiplineTestCase):
initialize=initialize,
handle_data=handle_data,
analyze=analyze,
env=self.env,
)
with empty_trading_env() as env:
data_portal = FakeDataPortal(env)
results = algo.run(data_portal)
data_portal = FakeDataPortal(self.env)
results = algo.run(data_portal)
self.assertIs(results, self.perf_ref)
@@ -3989,7 +4002,7 @@ class TestOrderCancelation(WithDataPortal,
self.assertFalse(log_catcher.has_warnings)
class TestEquityAutoClose(WithTmpDir, WithTradingCalendars, ZiplineTestCase):
class TestEquityAutoClose(WithTradingEnvironment, WithTmpDir, ZiplineTestCase):
"""
Tests if delisted equities are properly removed from a portfolio holding
positions in said equities.
@@ -4020,7 +4033,10 @@ class TestEquityAutoClose(WithTmpDir, WithTradingCalendars, ZiplineTestCase):
sids = asset_info.index
env = self.enter_instance_context(tmp_trading_env(equities=asset_info))
env = self.enter_instance_context(
tmp_trading_env(equities=asset_info,
load=self.make_load_function())
)
if frequency == 'daily':
dates = self.test_days
@@ -4642,7 +4658,7 @@ class TestOrderAfterDelist(WithTradingEnvironment, ZiplineTestCase):
self.assertEqual(expected_message, w.message)
class AlgoInputValidationTestCase(ZiplineTestCase):
class AlgoInputValidationTestCase(WithTradingEnvironment, ZiplineTestCase):
def test_reject_passing_both_api_methods_and_script(self):
script = dedent(
@@ -4668,11 +4684,12 @@ class AlgoInputValidationTestCase(ZiplineTestCase):
with self.assertRaises(ValueError):
TradingAlgorithm(
script=script,
env=self.env,
**{method: lambda *args, **kwargs: None}
)
class TestPanelData(ZiplineTestCase):
class TestPanelData(WithTradingEnvironment, ZiplineTestCase):
@parameterized.expand([
('daily',
@@ -4694,6 +4711,9 @@ class TestPanelData(ZiplineTestCase):
def dt_transform(dt):
return dt
else:
raise AssertionError('Unexpected data_frequency: %s' %
data_frequency)
sids = range(1, 3)
dfs = {}
@@ -4734,19 +4754,26 @@ class TestPanelData(ZiplineTestCase):
'prev_close']].values.astype('float64')
)
trading_algo = TradingAlgorithm(initialize=initialize,
handle_data=handle_data)
trading_algo.run(data=panel)
check_panels()
price_record.loc[:] = np.nan
with tmp_trading_env(load=self.make_load_function()) as env:
trading_algo = TradingAlgorithm(initialize=initialize,
handle_data=handle_data,
env=env)
trading_algo.run(data=panel)
check_panels()
price_record.loc[:] = np.nan
run_algorithm(
start=start_dt,
end=end_dt,
capital_base=1,
initialize=initialize,
handle_data=handle_data,
data_frequency=data_frequency,
data=panel
)
check_panels()
with tmp_dir() as tmpdir:
root = tmpdir.getpath('example_data/root')
copy_market_data(self.MARKET_DATA_DIR, root)
run_algorithm(
start=start_dt,
end=end_dt,
capital_base=1,
initialize=initialize,
handle_data=handle_data,
data_frequency=data_frequency,
data=panel,
environ={'ZIPLINE_ROOT': root},
)
check_panels()
tests/test_examples.py
+6 -2
View File
@@ -21,8 +21,9 @@ import pandas as pd
from zipline import examples
from zipline.data.bundles import register, unregister
from zipline.testing import test_resource_path
from zipline.testing.fixtures import WithTmpDir, ZiplineTestCase
from zipline.testing import test_resource_path, copy_market_data
from zipline.testing.fixtures import WithTmpDir, ZiplineTestCase, \
WithTradingEnvironment
from zipline.testing.predicates import assert_equal
from zipline.utils.cache import dataframe_cache
@@ -53,6 +54,9 @@ class ExamplesTests(WithTmpDir, ZiplineTestCase):
serialization='pickle',
)
copy_market_data(WithTradingEnvironment.MARKET_DATA_DIR,
cls.tmpdir.getpath('example_data/root'))
@parameterized.expand(examples.EXAMPLE_MODULES)
def test_example(self, example_name):
actual_perf = examples.run_example(
tests/test_finance.py
+2 -1
View File
@@ -190,7 +190,8 @@ class FinanceTestCase(WithLogger,
asset1 = self.asset_finder.retrieve_asset(1)
metadata = make_simple_equity_info([asset1.sid], self.start, self.end)
with TempDirectory() as tempdir, \
tmp_trading_env(equities=metadata) as env:
tmp_trading_env(equities=metadata,
load=self.make_load_function()) as env:
if trade_interval < timedelta(days=1):
sim_params = factory.create_simulation_parameters(
tests/test_perf_tracking.py
+3 -2
View File
@@ -57,7 +57,6 @@ from zipline.testing.fixtures import (
WithSimParams,
WithTmpDir,
WithTradingEnvironment,
WithTradingCalendars,
ZiplineTestCase,
)
from zipline.utils.calendars import get_calendar
@@ -1029,7 +1028,8 @@ class TestDividendPerformanceHolidayStyle(TestDividendPerformance):
END_DATE = pd.Timestamp('2003-12-08', tz='utc')
class TestPositionPerformance(WithInstanceTmpDir, WithTradingCalendars,
class TestPositionPerformance(WithInstanceTmpDir,
WithTradingEnvironment,
ZiplineTestCase):
def create_environment_stuff(self,
@@ -1054,6 +1054,7 @@ class TestPositionPerformance(WithInstanceTmpDir, WithTradingCalendars,
self.env = self.enter_instance_context(tmp_trading_env(
equities=equities,
futures=futures,
load=self.make_load_function(),
))
self.sim_params = create_simulation_parameters(
start=start,
tests/test_security_list.py
+8 -3
View File
@@ -15,7 +15,7 @@ from zipline.testing import (
)
from zipline.testing.fixtures import (
WithLogger,
WithTradingCalendars,
WithTradingEnvironment,
ZiplineTestCase,
)
from zipline.utils import factory
@@ -82,7 +82,9 @@ class IterateRLAlgo(TradingAlgorithm):
self.found = True
class SecurityListTestCase(WithLogger, WithTradingCalendars, ZiplineTestCase):
class SecurityListTestCase(WithLogger,
WithTradingEnvironment,
ZiplineTestCase):
@classmethod
def init_class_fixtures(cls):
@@ -103,6 +105,7 @@ class SecurityListTestCase(WithLogger, WithTradingCalendars, ZiplineTestCase):
'symbol': symbol,
'exchange': "TEST",
} for symbol in symbols]),
load=cls.make_load_function(),
))
cls.sim_params = factory.create_simulation_parameters(
@@ -122,6 +125,7 @@ class SecurityListTestCase(WithLogger, WithTradingCalendars, ZiplineTestCase):
'symbol': symbol,
'exchange': "TEST",
} for symbol in symbols]),
load=cls.make_load_function(),
))
cls.tempdir = cls.enter_class_context(tmp_dir())
@@ -304,7 +308,8 @@ class SecurityListTestCase(WithLogger, WithTradingCalendars, ZiplineTestCase):
}])
with TempDirectory() as new_tempdir, \
security_list_copy(), \
tmp_trading_env(equities=equities) as env:
tmp_trading_env(equities=equities,
load=self.make_load_function()) as env:
# add a delete statement removing bzq
# write a new delete statement file to disk
add_security_data([], ['BZQ'])
tests/test_tradesimulation.py
+11 -8
View File
@@ -19,7 +19,6 @@ from mock import patch
from nose_parameterized import parameterized
from six.moves import range
from unittest import TestCase
from zipline import TradingAlgorithm
from zipline.gens.sim_engine import BEFORE_TRADING_START_BAR
@@ -28,8 +27,12 @@ from zipline.finance.asset_restrictions import NoRestrictions
from zipline.gens.tradesimulation import AlgorithmSimulator
from zipline.sources.benchmark_source import BenchmarkSource
from zipline.test_algorithms import NoopAlgorithm
from zipline.testing.fixtures import WithSimParams, ZiplineTestCase, \
WithDataPortal
from zipline.testing.fixtures import (
WithDataPortal,
WithSimParams,
WithTradingEnvironment,
ZiplineTestCase,
)
from zipline.utils import factory
from zipline.testing.core import FakeDataPortal
from zipline.utils.calendars.trading_calendar import days_at_time
@@ -50,7 +53,7 @@ class BeforeTradingAlgorithm(TradingAlgorithm):
FREQUENCIES = {'daily': 0, 'minute': 1} # daily is less frequent than minute
class TestTradeSimulation(TestCase):
class TestTradeSimulation(WithTradingEnvironment, ZiplineTestCase):
def fake_minutely_benchmark(self, dt):
return 0.01
@@ -61,8 +64,8 @@ class TestTradeSimulation(TestCase):
emission_rate='minute')
with patch.object(BenchmarkSource, "get_value",
self.fake_minutely_benchmark):
algo = NoopAlgorithm(sim_params=params)
algo.run(FakeDataPortal())
algo = NoopAlgorithm(sim_params=params, env=self.env)
algo.run(FakeDataPortal(self.env))
self.assertEqual(len(algo.perf_tracker.sim_params.sessions), 1)
@parameterized.expand([('%s_%s_%s' % (num_sessions, freq, emission_rate),
@@ -82,8 +85,8 @@ class TestTradeSimulation(TestCase):
with patch.object(BenchmarkSource, "get_value",
self.fake_minutely_benchmark):
algo = BeforeTradingAlgorithm(sim_params=params)
algo.run(FakeDataPortal())
algo = BeforeTradingAlgorithm(sim_params=params, env=self.env)
algo.run(FakeDataPortal(self.env))
self.assertEqual(
len(algo.perf_tracker.sim_params.sessions),
zipline/data/loader.py
+18 -11
View File
@@ -53,13 +53,13 @@ def last_modified_time(path):
return pd.Timestamp(os.path.getmtime(path), unit='s', tz='UTC')
def get_data_filepath(name):
def get_data_filepath(name, environ=None):
"""
Returns a handle to data file.
Creates containing directory, if needed.
"""
dr = data_root()
dr = data_root(environ)
if not os.path.exists(dr):
os.makedirs(dr)
@@ -91,7 +91,8 @@ def has_data_for_dates(series_or_df, first_date, last_date):
return (first <= first_date) and (last >= last_date)
def load_market_data(trading_day=None, trading_days=None, bm_symbol='^GSPC'):
def load_market_data(trading_day=None, trading_days=None, bm_symbol='^GSPC',
environ=None):
"""
Load benchmark returns and treasury yield curves for the given calendar and
benchmark symbol.
@@ -162,19 +163,22 @@ def load_market_data(trading_day=None, trading_days=None, bm_symbol='^GSPC'):
# We need the trading_day to figure out the close prior to the first
# date so that we can compute returns for the first date.
trading_day,
environ,
)
tc = ensure_treasury_data(
bm_symbol,
first_date,
last_date,
now,
environ,
)
benchmark_returns = br[br.index.slice_indexer(first_date, last_date)]
treasury_curves = tc[tc.index.slice_indexer(first_date, last_date)]
return benchmark_returns, treasury_curves
def ensure_benchmark_data(symbol, first_date, last_date, now, trading_day):
def ensure_benchmark_data(symbol, first_date, last_date, now, trading_day,
environ=None):
"""
Ensure we have benchmark data for `symbol` from `first_date` to `last_date`
@@ -204,7 +208,8 @@ def ensure_benchmark_data(symbol, first_date, last_date, now, trading_day):
path.
"""
filename = get_benchmark_filename(symbol)
data = _load_cached_data(filename, first_date, last_date, now, 'benchmark')
data = _load_cached_data(filename, first_date, last_date, now, 'benchmark',
environ)
if data is not None:
return data
@@ -218,7 +223,7 @@ def ensure_benchmark_data(symbol, first_date, last_date, now, trading_day):
first_date - trading_day,
last_date,
)
data.to_csv(get_data_filepath(filename))
data.to_csv(get_data_filepath(filename, environ))
except (OSError, IOError, HTTPError):
logger.exception('failed to cache the new benchmark returns')
raise
@@ -227,7 +232,7 @@ def ensure_benchmark_data(symbol, first_date, last_date, now, trading_day):
return data
def ensure_treasury_data(symbol, first_date, last_date, now):
def ensure_treasury_data(symbol, first_date, last_date, now, environ=None):
"""
Ensure we have treasury data from treasury module associated with
`symbol`.
@@ -259,7 +264,8 @@ def ensure_treasury_data(symbol, first_date, last_date, now):
)
first_date = max(first_date, loader_module.earliest_possible_date())
data = _load_cached_data(filename, first_date, last_date, now, 'treasury')
data = _load_cached_data(filename, first_date, last_date, now, 'treasury',
environ)
if data is not None:
return data
@@ -269,7 +275,7 @@ def ensure_treasury_data(symbol, first_date, last_date, now):
try:
data = loader_module.get_treasury_data(first_date, last_date)
data.to_csv(get_data_filepath(filename))
data.to_csv(get_data_filepath(filename, environ))
except (OSError, IOError, HTTPError):
logger.exception('failed to cache treasury data')
if not has_data_for_dates(data, first_date, last_date):
@@ -277,14 +283,15 @@ def ensure_treasury_data(symbol, first_date, last_date, now):
return data
def _load_cached_data(filename, first_date, last_date, now, resource_name):
def _load_cached_data(filename, first_date, last_date, now, resource_name,
environ=None):
if resource_name == 'benchmark':
from_csv = pd.Series.from_csv
else:
from_csv = pd.DataFrame.from_csv
# Path for the cache.
path = get_data_filepath(filename)
path = get_data_filepath(filename, environ)
# If the path does not exist, it means the first download has not happened
# yet, so don't try to read from 'path'.
zipline/finance/trading.py
+3 -1
View File
@@ -12,6 +12,7 @@
# 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 functools import partial
import logbook
import pandas as pd
@@ -86,11 +87,12 @@ class TradingEnvironment(object):
trading_calendar=None,
asset_db_path=':memory:',
future_chain_predicates=CHAIN_PREDICATES,
environ=None,
):
self.bm_symbol = bm_symbol
if not load:
load = load_market_data
load = partial(load_market_data, environ=environ)
if not trading_calendar:
trading_calendar = get_calendar("NYSE")
zipline/testing/__init__.py
+1
View File
@@ -16,6 +16,7 @@ from .core import ( # noqa
check_allclose,
check_arrays,
chrange,
copy_market_data,
create_daily_df_for_asset,
create_data_portal,
create_data_portal_from_trade_history,
zipline/testing/core.py
+23 -4
View File
@@ -29,6 +29,7 @@ from toolz import concat, curry
from zipline.assets import AssetFinder, AssetDBWriter
from zipline.assets.synthetic import make_simple_equity_info
from zipline.data.data_portal import DataPortal
from zipline.data.loader import get_benchmark_filename, INDEX_MAPPING
from zipline.data.minute_bars import (
BcolzMinuteBarReader,
BcolzMinuteBarWriter,
@@ -52,6 +53,7 @@ from zipline.utils.calendars import get_calendar
from zipline.utils.input_validation import expect_dimensions
from zipline.utils.numpy_utils import as_column, isnat
from zipline.utils.pandas_utils import timedelta_to_integral_seconds
from zipline.utils.paths import ensure_directory
from zipline.utils.sentinel import sentinel
import numpy as np
@@ -695,11 +697,8 @@ def create_data_portal_from_trade_history(asset_finder, trading_calendar,
class FakeDataPortal(DataPortal):
def __init__(self, env=None, trading_calendar=None,
def __init__(self, env, trading_calendar=None,
first_trading_day=None):
if env is None:
env = TradingEnvironment()
if trading_calendar is None:
trading_calendar = get_calendar("NYSE")
@@ -862,6 +861,8 @@ class tmp_trading_env(tmp_asset_finder):
Parameters
----------
load : callable, optional
Function that returns benchmark returns and treasury curves.
finder_cls : type, optional
The type of asset finder to create from the assets db.
**frames
@@ -872,8 +873,13 @@ class tmp_trading_env(tmp_asset_finder):
empty_trading_env
tmp_asset_finder
"""
def __init__(self, load=None, *args, **kwargs):
super(tmp_trading_env, self).__init__(*args, **kwargs)
self._load = load
def __enter__(self):
return TradingEnvironment(
load=self._load,
asset_db_path=super(tmp_trading_env, self).__enter__().engine,
)
@@ -1486,6 +1492,19 @@ def patch_read_csv(url_map, module=pd, strict=False):
yield
def copy_market_data(src_market_data_dir, dest_root_dir):
symbol = '^GSPC'
filenames = (get_benchmark_filename(symbol), INDEX_MAPPING[symbol][1])
ensure_directory(os.path.join(dest_root_dir, 'data'))
for filename in filenames:
shutil.copyfile(
os.path.join(src_market_data_dir, filename),
os.path.join(dest_root_dir, 'data', filename)
)
@curry
def ensure_doctest(f, name=None):
"""Ensure that an object gets doctested. This is useful for instances
zipline/utils/run_algo.py
+2 -2
View File
@@ -129,7 +129,7 @@ def _run(handle_data,
"invalid url %r, must begin with 'sqlite:///'" %
str(bundle_data.asset_finder.engine.url),
)
env = TradingEnvironment(asset_db_path=connstr)
env = TradingEnvironment(asset_db_path=connstr, environ=environ)
first_trading_day =\
bundle_data.equity_minute_bar_reader.first_trading_day
data = DataPortal(
@@ -152,7 +152,7 @@ def _run(handle_data,
"No PipelineLoader registered for column %s." % column
)
else:
env = None
env = TradingEnvironment(environ=environ)
choose_loader = None
perf = TradingAlgorithm(