Files
catalyst/zipline/sources/test_source.py
T
Jean Bredeche 6fb4923cc7 Re-implemented the Calendar API.
Instead of having separate ExchangeCalendar and TradingSchedule objects, we
now just have TradingCalendar.  The TradingCalendar keeps track of each
session (defined as a contiguous set of minutes between an open and a close).
It's also responsible for handling the grouping logic of any given minute
to its containing session, or the next/previous session if it's not a market
minute for the given calendar.
2016-07-12 13:13:50 -04:00

249 lines
7.9 KiB
Python

#
# Copyright 2013 Quantopian, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# 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.
"""
A source to be used in testing.
"""
import pytz
from six.moves import filter
from datetime import datetime, timedelta
import itertools
from six.moves import range
from zipline.protocol import (
Event,
DATASOURCE_TYPE
)
from zipline.gens.utils import hash_args
def create_trade(sid, price, amount, datetime, source_id="test_factory"):
trade = Event()
trade.source_id = source_id
trade.type = DATASOURCE_TYPE.TRADE
trade.sid = sid
trade.dt = datetime
trade.price = price
trade.close_price = price
trade.open_price = price
trade.low = price * .95
trade.high = price * 1.05
trade.volume = amount
return trade
def date_gen(start,
end,
trading_calendar,
delta=timedelta(minutes=1),
repeats=None):
"""
Utility to generate a stream of dates.
"""
daily_delta = not (delta.total_seconds()
% timedelta(days=1).total_seconds())
cur = start
if daily_delta:
# if we are producing daily timestamps, we
# use midnight
cur = cur.replace(hour=0, minute=0, second=0,
microsecond=0)
def advance_current(cur):
"""
Advances the current dt skipping non market days and minutes.
"""
cur = cur + delta
currently_executing = \
(daily_delta and (cur in trading_calendar.all_sessions)) or \
(trading_calendar.is_open_on_minute(cur))
if currently_executing:
return cur
else:
if daily_delta:
return trading_calendar.minute_to_session_label(cur)
else:
return trading_calendar.open_and_close_for_session(
trading_calendar.minute_to_session_label(cur)
)[0]
# yield count trade events, all on trading days, and
# during trading hours.
while cur < end:
if repeats:
for j in range(repeats):
yield cur
else:
yield cur
cur = advance_current(cur)
class SpecificEquityTrades(object):
"""
Yields all events in event_list that match the given sid_filter.
If no event_list is specified, generates an internal stream of events
to filter. Returns all events if filter is None.
Configuration options:
count : integer representing number of trades
sids : list of values representing simulated internal sids
start : start date
delta : timedelta between internal events
filter : filter to remove the sids
"""
def __init__(self, env, trading_calendar, *args, **kwargs):
# We shouldn't get any positional arguments.
assert len(args) == 0
self.env = env
self.trading_calendar = trading_calendar
# Default to None for event_list and filter.
self.event_list = kwargs.get('event_list')
self.filter = kwargs.get('filter')
if self.event_list is not None:
# If event_list is provided, extract parameters from there
# This isn't really clean and ultimately I think this
# class should serve a single purpose (either take an
# event_list or autocreate events).
self.count = kwargs.get('count', len(self.event_list))
self.start = kwargs.get('start', self.event_list[0].dt)
self.end = kwargs.get('end', self.event_list[-1].dt)
self.delta = delta = kwargs.get('delta')
if delta is None:
self.delta = self.event_list[1].dt - self.event_list[0].dt
self.concurrent = kwargs.get('concurrent', False)
self.identifiers = kwargs.get(
'sids',
set(event.sid for event in self.event_list)
)
assets_by_identifier = {}
for identifier in self.identifiers:
assets_by_identifier[identifier] = env.asset_finder.\
lookup_generic(identifier, datetime.now())[0]
self.sids = [asset.sid for asset in assets_by_identifier.values()]
for event in self.event_list:
event.sid = assets_by_identifier[event.sid].sid
else:
# Unpack config dictionary with default values.
self.count = kwargs.get('count', 500)
self.start = kwargs.get(
'start',
datetime(2008, 6, 6, 15, tzinfo=pytz.utc))
self.end = kwargs.get(
'end',
datetime(2008, 6, 6, 15, tzinfo=pytz.utc))
self.delta = kwargs.get(
'delta',
timedelta(minutes=1))
self.concurrent = kwargs.get('concurrent', False)
self.identifiers = kwargs.get('sids', [1, 2])
assets_by_identifier = {}
for identifier in self.identifiers:
assets_by_identifier[identifier] = env.asset_finder.\
lookup_generic(identifier, datetime.now())[0]
self.sids = [asset.sid for asset in assets_by_identifier.values()]
# Hash_value for downstream sorting.
self.arg_string = hash_args(*args, **kwargs)
self.generator = self.create_fresh_generator()
def __iter__(self):
return self
def next(self):
return self.generator.next()
def __next__(self):
return next(self.generator)
def rewind(self):
self.generator = self.create_fresh_generator()
def get_hash(self):
return self.__class__.__name__ + "-" + self.arg_string
def update_source_id(self, gen):
for event in gen:
event.source_id = self.get_hash()
yield event
def create_fresh_generator(self):
if self.event_list:
event_gen = (event for event in self.event_list)
unfiltered = self.update_source_id(event_gen)
# Set up iterators for each expected field.
else:
if self.concurrent:
# in this context the count is the number of
# trades per sid, not the total.
date_generator = date_gen(
start=self.start,
end=self.end,
delta=self.delta,
repeats=len(self.sids),
trading_calendar=self.trading_calendar,
)
else:
date_generator = date_gen(
start=self.start,
end=self.end,
delta=self.delta,
trading_calendar=self.trading_calendar,
)
source_id = self.get_hash()
unfiltered = (
create_trade(
sid=sid,
price=float(i % 10) + 1.0,
amount=(i * 50) % 900 + 100,
datetime=date,
source_id=source_id,
) for (i, date), sid in itertools.product(
enumerate(date_generator), self.sids
)
)
# If we specified a sid filter, filter out elements that don't
# match the filter.
if self.filter:
filtered = filter(
lambda event: event.sid in self.filter, unfiltered)
# Otherwise just use all events.
else:
filtered = unfiltered
# Return the filtered event stream.
return filtered