catalyst/zipline/sources/test_source.py

#
# 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 itertools import cycle
from six.moves import filter, zip
from datetime import datetime, timedelta
import numpy as np

from six.moves import range

from zipline.protocol import (
    Event,
    DATASOURCE_TYPE
)
from zipline.gens.utils import hash_args
from zipline.utils.tradingcalendar import trading_days


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=datetime(2006, 6, 6, 12, tzinfo=pytz.utc),
             delta=timedelta(minutes=1),
             count=100,
             repeats=None):
    """
    Utility to generate a stream of dates.
    """
    one_day = timedelta(days=1)
    cur = start
    if delta == one_day:
        # if we are producing daily timestamps, we
        # use midnight
        cur = cur.replace(hour=0, minute=0, second=0,
                          microsecond=0)

    # yield count trade events, all on trading days, and
    # during trading hours.
    # NB: Being inside of trading hours is currently dependent upon the
    # count parameter being less than the number of trading minutes in a day
    for i in range(count):
        if repeats:
            for j in range(repeats):
                yield cur
        else:
            yield cur

        cur = cur + delta
        cur_midnight = cur.replace(hour=0, minute=0, second=0, microsecond=0)
        # skip over any non-trading days
        while cur_midnight not in trading_days:
            cur = cur + one_day
            cur_midnight = cur.replace(hour=0, minute=0, second=0,
                                       microsecond=0)
            cur = cur.replace(day=cur_midnight.day)


def mock_prices(count):
    """
    Utility to generate a stream of mock prices. By default
    cycles through values from 0.0 to 10.0, n times.
    """
    return (float(i % 10) + 1.0 for i in range(count))


def mock_volumes(count):
    """
    Utility to generate a set of volumes. By default cycles
    through values from 100 to 1000, incrementing by 50.
    """
    return ((i * 50) % 900 + 100 for i in range(count))


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, *args, **kwargs):
        # We shouldn't get any positional arguments.
        assert len(args) == 0

        # 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.sids = kwargs.get(
                'sids',
                np.unique([event.sid for event in self.event_list]).tolist())
            self.start = kwargs.get('start', self.event_list[0].dt)
            self.end = kwargs.get('start', self.event_list[-1].dt)
            self.delta = kwargs.get(
                'delta',
                self.event_list[1].dt - self.event_list[0].dt)
            self.concurrent = kwargs.get('concurrent', False)

        else:
            # Unpack config dictionary with default values.
            self.count = kwargs.get('count', 500)
            self.sids = kwargs.get('sids', [1, 2])
            self.start = kwargs.get(
                'start',
                datetime(2008, 6, 6, 15, tzinfo=pytz.utc))
            self.delta = kwargs.get(
                'delta',
                timedelta(minutes=1))
            self.concurrent = kwargs.get('concurrent', False)

        # 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.
                dates = date_gen(
                    count=self.count,
                    start=self.start,
                    delta=self.delta,
                    repeats=len(self.sids),
                )
            else:
                dates = date_gen(
                    count=self.count,
                    start=self.start,
                    delta=self.delta
                )

            prices = mock_prices(self.count)
            volumes = mock_volumes(self.count)

            sids = cycle(self.sids)

            # Combine the iterators into a single iterator of arguments
            arg_gen = zip(sids, prices, volumes, dates)

            # Convert argument packages into events.
            unfiltered = (create_trade(*args, source_id=self.get_hash())
                          for args in arg_gen)

        # 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