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use dt.normalize() in pd>=0.20

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wassname
2018-03-31 09:51:15 +08:00
parent 06399caa2b
commit 4a2d5678ad
14 changed files with 28 additions and 40 deletions
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catalyst/_protocol.pyx
+1 -2
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@@ -16,7 +16,6 @@ import warnings
from contextlib import contextmanager
from functools import wraps
from pandas.tslib import normalize_date
import pandas as pd
import numpy as np
@@ -564,7 +563,7 @@ cdef class BarData:
})
cdef bool _is_stale_for_asset(self, asset, dt, adjusted_dt, data_portal):
session_label = normalize_date(dt) # FIXME
session_label = dt.normalize_date() # FIXME
if not asset.is_alive_for_session(session_label):
return False
catalyst/algorithm.py
+3 -4
View File
@@ -21,7 +21,6 @@ import logbook
import pytz
import pandas as pd
from contextlib2 import ExitStack
from pandas.tseries.tools import normalize_date
import numpy as np
from itertools import chain, repeat
@@ -1345,7 +1344,7 @@ class TradingAlgorithm(object):
# Make sure the asset exists, and that there is a last price for it.
# FIXME: we should use BarData's can_trade logic here, but I haven't
# yet found a good way to do that.
normalized_date = normalize_date(self.datetime)
normalized_date = self.datetime.normalize()
if normalized_date < asset.start_date:
raise CannotOrderDelistedAsset(
@@ -1392,7 +1391,7 @@ class TradingAlgorithm(object):
)
if asset.auto_close_date:
day = normalize_date(self.get_datetime())
day = self.get_datetime().normalize()
if day > min(asset.end_date, asset.auto_close_date):
# If we are after the asset's end date or auto close date, warn
@@ -2475,7 +2474,7 @@ class TradingAlgorithm(object):
"""
Internal implementation of `pipeline_output`.
"""
today = normalize_date(self.get_datetime())
today = self.get_datetime().normalize()
data = NO_DATA = object()
try:
data = self._pipeline_cache.unwrap(today)
catalyst/data/data_portal.py
+4 -5
View File
@@ -20,7 +20,6 @@ import numpy as np
from numpy import float64, int64, nan
import pandas as pd
from pandas import isnull
from pandas.tslib import normalize_date
from six import iteritems
from six.moves import reduce
@@ -439,7 +438,7 @@ class DataPortal(object):
(isinstance(asset, (Asset, ContinuousFuture))))
def _get_fetcher_value(self, asset, field, dt):
day = normalize_date(dt)
day = dt.normalize()
try:
return \
@@ -1130,7 +1129,7 @@ class DataPortal(object):
if self._asset_start_dates[sid] > dt:
raise NoTradeDataAvailableTooEarly(
sid=sid,
dt=normalize_date(dt),
dt=dt.normalize(),
start_dt=start_date
)
@@ -1138,7 +1137,7 @@ class DataPortal(object):
if self._asset_end_dates[sid] < dt:
raise NoTradeDataAvailableTooLate(
sid=sid,
dt=normalize_date(dt),
dt=dt.normalize(),
end_dt=end_date
)
@@ -1262,7 +1261,7 @@ class DataPortal(object):
if self._extra_source_df is None:
return []
day = normalize_date(dt)
day = dt.normalize()
if day in self._extra_source_df.index:
assets = self._extra_source_df.loc[day]['sid']
catalyst/data/history_loader.py
+2 -3
View File
@@ -21,7 +21,6 @@ from abc import (
from numpy import concatenate
from lru import LRU
from pandas import isnull
from pandas.tslib import normalize_date
from toolz import sliding_window
from six import with_metaclass
@@ -93,8 +92,8 @@ class HistoryCompatibleUSEquityAdjustmentReader(object):
The adjustments as a dict of loc -> Float64Multiply
"""
sid = int(asset)
start = normalize_date(dts[0])
end = normalize_date(dts[-1])
start = dts[0].normalize()
end = dts[-1].normalize()
adjs = {}
if field != 'volume':
mergers = self._adjustments_reader.get_adjustments_for_sid(
catalyst/data/us_equity_pricing.py
+1 -2
View File
@@ -49,7 +49,6 @@ from pandas import (
to_datetime,
Timestamp,
)
from pandas.tslib import iNaT
from six import (
iteritems,
string_types,
@@ -422,7 +421,7 @@ class BcolzDailyBarWriter(object):
)
full_table.attrs['first_trading_day'] = (
earliest_date if earliest_date is not None else iNaT
earliest_date if earliest_date is not None else NaT
)
full_table.attrs['first_row'] = first_row
catalyst/finance/performance/tracker.py
+1 -2
View File
@@ -62,7 +62,6 @@ from __future__ import division
import logbook
import pandas as pd
from pandas.tseries.tools import normalize_date
from catalyst.finance.performance.period import PerformancePeriod
from catalyst.errors import NoFurtherDataError
@@ -344,7 +343,7 @@ class PerformanceTracker(object):
"""
self.position_tracker.sync_last_sale_prices(dt, False, data_portal)
self.update_performance()
todays_date = normalize_date(dt)
todays_date = dt.normalize()
account = self.get_account(False)
bench_returns = self.all_benchmark_returns.loc[todays_date:dt]
catalyst/finance/risk/cumulative.py
+1 -2
View File
@@ -18,7 +18,6 @@ import logbook
import numpy as np
import pandas as pd
from pandas.tseries.tools import normalize_date
from six import iteritems
@@ -80,7 +79,7 @@ class RiskMetricsCumulative(object):
# on the first day.
self.day_before_start = self.start_session - self.sessions.freq
last_day = normalize_date(sim_params.end_session)
last_day = sim_params.end_session.normalize()
if last_day not in self.sessions:
last_day = pd.tseries.index.DatetimeIndex(
[last_day]
catalyst/finance/trading.py
+2 -3
View File
@@ -16,7 +16,6 @@ from functools import partial
import logbook
import pandas as pd
from pandas.tslib import normalize_date
from six import string_types
from sqlalchemy import create_engine
@@ -164,8 +163,8 @@ class SimulationParameters(object):
# chop off any minutes or hours on the given start and end dates,
# as we only support session labels here (and we represent session
# labels as midnight UTC).
self._start_session = normalize_date(start_session)
self._end_session = normalize_date(end_session)
self._start_session = start_session.normalize()
self._end_session = end_session.normalize()
self._capital_base = capital_base
self._emission_rate = emission_rate
catalyst/gens/tradesimulation.py
+1 -2
View File
@@ -14,7 +14,6 @@
# limitations under the License.
from contextlib2 import ExitStack
from logbook import Logger, Processor
from pandas.tslib import normalize_date
from catalyst.protocol import BarData
from catalyst.utils.api_support import ZiplineAPI
from six import viewkeys
@@ -229,7 +228,7 @@ class AlgorithmSimulator(object):
elif action == SESSION_END:
# End of the session.
if emission_rate == 'daily':
handle_benchmark(normalize_date(dt))
handle_benchmark(dt).normalize()
execute_order_cancellation_policy()
yield self._get_daily_message(dt, algo, algo.perf_tracker)
catalyst/utils/factory.py
+6 -6
View File
@@ -117,9 +117,9 @@ def create_dividend(sid, payment, declared_date, ex_date, pay_date):
'net_amount': payment,
'payment_sid': None,
'ratio': None,
'declared_date': pd.tslib.normalize_date(declared_date),
'ex_date': pd.tslib.normalize_date(ex_date),
'pay_date': pd.tslib.normalize_date(pay_date),
'declared_date': pd.tslib.declared_date.normalize(),
'ex_date': pd.tslib.ex_date.normalize(),
'pay_date': pd.tslib.pay_date.normalize(),
'type': DATASOURCE_TYPE.DIVIDEND,
'source_id': 'MockDividendSource'
})
@@ -134,9 +134,9 @@ def create_stock_dividend(sid, payment_sid, ratio, declared_date,
'ratio': ratio,
'net_amount': None,
'gross_amount': None,
'dt': pd.tslib.normalize_date(declared_date),
'ex_date': pd.tslib.normalize_date(ex_date),
'pay_date': pd.tslib.normalize_date(pay_date),
'dt': pd.tslib.declared_date.normalize(),
'ex_date': pd.tslib.ex_date.normalize(),
'pay_date': pd.tslib.pay_date.normalize(),
'type': DATASOURCE_TYPE.DIVIDEND,
'source_id': 'MockDividendSource'
})
catalyst/utils/run_algo.py
+2 -2
View File
@@ -263,8 +263,8 @@ def _run(handle_data,
# We still need to support bundles for other misc data, but we
# can handle this later.
if start != pd.tslib.normalize_date(start) or \
end != pd.tslib.normalize_date(end):
if start != pd.tslib.start.normalize() or \
end != pd.tslib.end.normalize():
# todo: add to Sim_Params the option to start & end at specific times
log.warn(
"Catalyst currently starts and ends on the start and "
tests/finance/test_slippage.py
+2 -3
View File
@@ -21,7 +21,6 @@ import datetime
from math import sqrt
from nose_parameterized import parameterized
from pandas.tslib import normalize_date
import numpy as np
import pandas as pd
import pytz
@@ -1108,8 +1107,8 @@ class OrdersStopTestCase(WithSimParams,
)),
)
days = pd.date_range(
start=normalize_date(self.minutes[0]),
end=normalize_date(self.minutes[-1])
start=self.minutes[0].normalize(),
end=self.minutes[-1].normalize()
)
with tmp_bcolz_equity_minute_bar_reader(
self.trading_calendar, days, assets) as reader:
tests/pipeline/test_pipeline_algo.py
+1 -2
View File
@@ -27,7 +27,6 @@ from pandas import (
Series,
Timestamp,
)
from pandas.tseries.tools import normalize_date
from six import iteritems, itervalues
from catalyst.algorithm import TradingAlgorithm
@@ -530,7 +529,7 @@ class PipelineAlgorithmTestCase(WithBcolzEquityDailyBarReaderFromCSVs,
attach_pipeline(pipeline, 'test')
def handle_data(context, data):
today = normalize_date(get_datetime())
today = get_datetime().normalize()
results = pipeline_output('test')
expect_over_300 = {
AAPL: today < self.AAPL_split_date,
tests/test_fetcher.py
+1 -2
View File
@@ -395,7 +395,6 @@ def handle_data(context, data):
algocode = """
from pandas import Timestamp
from pandas.tseries.tools import normalize_date
from catalyst.api import fetch_csv, record, sid, get_datetime
def initialize(context):
@@ -411,7 +410,7 @@ def initialize(context):
context.bar_count = 0
def handle_data(context, data):
expected = context.expected_sids[normalize_date(get_datetime())]
expected = context.expected_sids[get_datetime().normalize()]
actual = data.fetcher_assets
for stk in expected:
if stk not in actual: