catalyst/zipline/testing/fixtures.py

import sqlite3
from unittest import TestCase

from contextlib2 import ExitStack
from logbook import NullHandler, Logger
from six import with_metaclass, iteritems
from toolz import flip
import pandas as pd
import responses

from .core import (
    create_daily_bar_data,
    create_minute_bar_data,
    tmp_dir,
)
from ..data.data_portal import DataPortal
from ..data.resample import minute_to_session
from ..data.us_equity_pricing import (
    SQLiteAdjustmentReader,
    SQLiteAdjustmentWriter,
)
from ..data.us_equity_pricing import (
    BcolzDailyBarReader,
    BcolzDailyBarWriter,
)
from ..data.minute_bars import (
    BcolzMinuteBarReader,
    BcolzMinuteBarWriter,
    US_EQUITIES_MINUTES_PER_DAY,
    FUTURES_MINUTES_PER_DAY,
)

from ..finance.trading import TradingEnvironment
from ..utils import factory
from ..utils.classproperty import classproperty
from ..utils.final import FinalMeta, final
from .core import tmp_asset_finder, make_simple_equity_info
from zipline.assets import Equity
from zipline.pipeline import SimplePipelineEngine
from zipline.pipeline.loaders.testing import make_seeded_random_loader
from zipline.utils.calendars import (
    get_calendar,
    register_calendar)


class ZiplineTestCase(with_metaclass(FinalMeta, TestCase)):
    """
    Shared extensions to core unittest.TestCase.

    Overrides the default unittest setUp/tearDown functions with versions that
    use ExitStack to correctly clean up resources, even in the face of
    exceptions that occur during setUp/setUpClass.

    Subclasses **should not override setUp or setUpClass**!

    Instead, they should implement `init_instance_fixtures` for per-test-method
    resources, and `init_class_fixtures` for per-class resources.

    Resources that need to be cleaned up should be registered using
    either `enter_{class,instance}_context` or `add_{class,instance}_callback}.
    """
    _in_setup = False

    @final
    @classmethod
    def setUpClass(cls):
        # Hold a set of all the "static" attributes on the class. These are
        # things that are not populated after the class was created like
        # methods or other class level attributes.
        cls._static_class_attributes = set(vars(cls))
        cls._class_teardown_stack = ExitStack()
        try:
            cls._base_init_fixtures_was_called = False
            cls.init_class_fixtures()
            assert cls._base_init_fixtures_was_called, (
                "ZiplineTestCase.init_class_fixtures() was not called.\n"
                "This probably means that you overrode init_class_fixtures"
                " without calling super()."
            )
        except:
            cls.tearDownClass()
            raise

    @classmethod
    def init_class_fixtures(cls):
        """
        Override and implement this classmethod to register resources that
        should be created and/or torn down on a per-class basis.

        Subclass implementations of this should always invoke this with super()
        to ensure that fixture mixins work properly.
        """
        if cls._in_setup:
            raise ValueError(
                'Called init_class_fixtures from init_instance_fixtures.'
                'Did you write super(..., self).init_class_fixtures() instead'
                ' of super(..., self).init_instance_fixtures()?',
            )
        cls._base_init_fixtures_was_called = True

    @final
    @classmethod
    def tearDownClass(cls):
        # We need to get this before it's deleted by the loop.
        stack = cls._class_teardown_stack
        for name in set(vars(cls)) - cls._static_class_attributes:
            # Remove all of the attributes that were added after the class was
            # constructed. This cleans up any large test data that is class
            # scoped while still allowing subclasses to access class level
            # attributes.
            delattr(cls, name)
        stack.close()

    @final
    @classmethod
    def enter_class_context(cls, context_manager):
        """
        Enter a context manager to be exited during the tearDownClass
        """
        if cls._in_setup:
            raise ValueError(
                'Attempted to enter a class context in init_instance_fixtures.'
                '\nDid you mean to call enter_instance_context?',
            )
        return cls._class_teardown_stack.enter_context(context_manager)

    @final
    @classmethod
    def add_class_callback(cls, callback):
        """
        Register a callback to be executed during tearDownClass.

        Parameters
        ----------
        callback : callable
            The callback to invoke at the end of the test suite.
        """
        if cls._in_setup:
            raise ValueError(
                'Attempted to add a class callback in init_instance_fixtures.'
                '\nDid you mean to call add_instance_callback?',
            )
        return cls._class_teardown_stack.callback(callback)

    @final
    def setUp(self):
        type(self)._in_setup = True
        self._pre_setup_attrs = set(vars(self))
        self._instance_teardown_stack = ExitStack()
        try:
            self._init_instance_fixtures_was_called = False
            self.init_instance_fixtures()
            assert self._init_instance_fixtures_was_called, (
                "ZiplineTestCase.init_instance_fixtures() was not"
                " called.\n"
                "This probably means that you overrode"
                " init_instance_fixtures without calling super()."
            )
        except:
            self.tearDown()
            raise
        finally:
            type(self)._in_setup = False

    def init_instance_fixtures(self):
        self._init_instance_fixtures_was_called = True

    @final
    def tearDown(self):
        # We need to get this before it's deleted by the loop.
        stack = self._instance_teardown_stack
        for attr in set(vars(self)) - self._pre_setup_attrs:
            delattr(self, attr)
        stack.close()

    @final
    def enter_instance_context(self, context_manager):
        """
        Enter a context manager that should be exited during tearDown.
        """
        return self._instance_teardown_stack.enter_context(context_manager)

    @final
    def add_instance_callback(self, callback):
        """
        Register a callback to be executed during tearDown.

        Parameters
        ----------
        callback : callable
            The callback to invoke at the end of each test.
        """
        return self._instance_teardown_stack.callback(callback)


def alias(attr_name):
    """Make a fixture attribute an alias of another fixture's attribute by
    default.

    Parameters
    ----------
    attr_name : str
        The name of the attribute to alias.

    Returns
    -------
    p : classproperty
        A class property that does the property aliasing.

    Examples
    --------
    >>> class C(object):
    ...     attr = 1
    ...
    >>> class D(C):
    ...     attr_alias = alias('attr')
    ...
    >>> D.attr
    1
    >>> D.attr_alias
    1
    >>> class E(D):
    ...     attr_alias = 2
    ...
    >>> E.attr
    1
    >>> E.attr_alias
    2
    """
    return classproperty(flip(getattr, attr_name))


class WithDefaultDateBounds(object):
    """
    ZiplineTestCase mixin which makes it possible to synchronize date bounds
    across fixtures.

    This fixture should always be the last fixture in bases of any fixture or
    test case that uses it.

    Attributes
    ----------
    START_DATE : datetime
    END_DATE : datetime
        The date bounds to be used for fixtures that want to have consistent
        dates.
    """
    START_DATE = pd.Timestamp('2006-01-03', tz='utc')
    END_DATE = pd.Timestamp('2006-12-29', tz='utc')


class WithLogger(object):
    """
    ZiplineTestCase mixin providing cls.log_handler as an instance-level
    fixture.

    After init_instance_fixtures has been called `self.log_handler` will be a
    new ``logbook.NullHandler``.

    Methods
    -------
    make_log_handler() -> logbook.LogHandler
        A class method which constructs the new log handler object. By default
        this will construct a ``NullHandler``.
    """
    make_log_handler = NullHandler

    @classmethod
    def init_class_fixtures(cls):
        super(WithLogger, cls).init_class_fixtures()
        cls.log = Logger()
        cls.log_handler = cls.enter_class_context(
            cls.make_log_handler().applicationbound(),
        )


class WithAssetFinder(WithDefaultDateBounds):
    """
    ZiplineTestCase mixin providing cls.asset_finder as a class-level fixture.

    After init_class_fixtures has been called, `cls.asset_finder` is populated
    with an AssetFinder.

    Attributes
    ----------
    ASSET_FINDER_EQUITY_SIDS : iterable[int]
        The default sids to construct equity data for.
    ASSET_FINDER_EQUITY_SYMBOLS : iterable[str]
        The default symbols to use for the equities.
    ASSET_FINDER_EQUITY_START_DATE : datetime
        The default start date to create equity data for. This defaults to
        ``START_DATE``.
    ASSET_FINDER_EQUITY_END_DATE : datetime
        The default end date to create equity data for. This defaults to
        ``END_DATE``.

    Methods
    -------
    make_equity_info() -> pd.DataFrame
        A class method which constructs the dataframe of equity info to write
        to the class's asset db. By default this is empty.
    make_futures_info() -> pd.DataFrame
        A class method which constructs the dataframe of futures contract info
        to write to the class's asset db. By default this is empty.
    make_exchanges_info() -> pd.DataFrame
        A class method which constructs the dataframe of exchange information
        to write to the class's assets db. By default this is empty.
    make_root_symbols_info() -> pd.DataFrame
        A class method which constructs the dataframe of root symbols
        information to write to the class's assets db. By default this is
        empty.
    make_asset_finder_db_url() -> string
        A class method which returns the URL at which to create the SQLAlchemy
        engine. By default provides a URL for an in-memory database.
    make_asset_finder() -> pd.DataFrame
        A class method which constructs the actual asset finder object to use
        for the class. If this method is overridden then the ``make_*_info``
        methods may not be respected.

    See Also
    --------
    zipline.testing.make_simple_equity_info
    zipline.testing.make_jagged_equity_info
    zipline.testing.make_rotating_equity_info
    zipline.testing.make_future_info
    zipline.testing.make_commodity_future_info
    """
    ASSET_FINDER_EQUITY_SIDS = ord('A'), ord('B'), ord('C')
    ASSET_FINDER_EQUITY_SYMBOLS = None
    ASSET_FINDER_EQUITY_START_DATE = alias('START_DATE')
    ASSET_FINDER_EQUITY_END_DATE = alias('END_DATE')

    @classmethod
    def _make_info(cls):
        return None

    make_futures_info = _make_info
    make_exchanges_info = _make_info
    make_root_symbols_info = _make_info

    del _make_info

    @classmethod
    def make_equity_info(cls):
        register_calendar("TEST", get_calendar("NYSE"), force=True)

        return make_simple_equity_info(
            cls.ASSET_FINDER_EQUITY_SIDS,
            cls.ASSET_FINDER_EQUITY_START_DATE,
            cls.ASSET_FINDER_EQUITY_END_DATE,
            cls.ASSET_FINDER_EQUITY_SYMBOLS,
        )

    @classmethod
    def make_asset_finder_db_url(cls):
        return 'sqlite:///:memory:'

    @classmethod
    def make_asset_finder(cls):
        return cls.enter_class_context(tmp_asset_finder(
            url=cls.make_asset_finder_db_url(),
            equities=cls.make_equity_info(),
            futures=cls.make_futures_info(),
            exchanges=cls.make_exchanges_info(),
            root_symbols=cls.make_root_symbols_info(),
        ))

    @classmethod
    def init_class_fixtures(cls):
        super(WithAssetFinder, cls).init_class_fixtures()
        cls.asset_finder = cls.make_asset_finder()


class WithTradingCalendars(object):
    """
    ZiplineTestCase mixin providing cls.trading_calendar,
    cls.all_trading_calendars, cls.trading_calendar_for_asset_type as a
    class-level fixture.

    After ``init_class_fixtures`` has been called:
    - `cls.trading_calendar` is populated with a default of the nyse trading
    calendar for compatibility with existing tests
    - `cls.all_trading_calendars` is populated with the trading calendars
    keyed by name,
    - `cls.trading_calendar_for_asset_type` is populated with the trading
    calendars keyed by the asset type which uses the respective calendar.

    Attributes
    ----------
    TRADING_CALENDAR_STRS : iterable
        iterable of identifiers of the calendars to use.
    TRADING_CALENDAR_FOR_ASSET_TYPE : dict
        A dictionay which maps asset type names to the calendar associated
        with that asset type.
    """
    TRADING_CALENDAR_STRS = ('NYSE',)
    TRADING_CALENDAR_FOR_ASSET_TYPE = {Equity: 'NYSE'}
    TRADING_CALENDAR_FOR_EXCHANGE = {}
    # For backwards compatibility, exisitng tests and fixtures refer to
    # `trading_calendar` with the assumption that the value is the NYSE
    # calendar.
    TRADING_CALENDAR_PRIMARY_CAL = 'NYSE'

    @classmethod
    def init_class_fixtures(cls):
        super(WithTradingCalendars, cls).init_class_fixtures()

        cls.trading_calendars = {}

        for cal_str in cls.TRADING_CALENDAR_STRS:
            # Set name to allow aliasing.
            calendar = get_calendar(cal_str)
            setattr(cls,
                    '{0}_calendar'.format(cal_str.lower()), calendar)
            cls.trading_calendars[cal_str] = calendar
        for asset_type, cal_str in iteritems(
                cls.TRADING_CALENDAR_FOR_ASSET_TYPE):
            calendar = get_calendar(cal_str)
            cls.trading_calendars[asset_type] = calendar
        for exchange, cal_str in iteritems(cls.TRADING_CALENDAR_FOR_EXCHANGE):
            register_calendar(exchange, get_calendar(cal_str))
            cls.trading_calendars[exchange] = get_calendar(cal_str)
        cls.trading_calendar = cls.trading_calendars[
            cls.TRADING_CALENDAR_PRIMARY_CAL]


class WithTradingEnvironment(WithAssetFinder,
                             WithTradingCalendars,
                             WithDefaultDateBounds):
    """
    ZiplineTestCase mixin providing cls.env as a class-level fixture.

    After ``init_class_fixtures`` has been called, `cls.env` is populated
    with a trading environment whose `asset_finder` is the result of
    `cls.make_asset_finder`.

    Attributes
    ----------
    TRADING_ENV_MIN_DATE : datetime
        The min_date to forward to the constructed TradingEnvironment.
    TRADING_ENV_MAX_DATE : datetime
        The max date to forward to the constructed TradingEnvironment.
    TRADING_ENV_TRADING_CALENDAR : pd.DatetimeIndex
        The trading calendar to use for the class's TradingEnvironment.

    Methods
    -------
    make_load_function() -> callable
        A class method that returns the ``load`` argument to pass to the
        constructor of ``TradingEnvironment`` for this class.
        The signature for the callable returned is:
        ``(datetime, pd.DatetimeIndex, str) -> (pd.Series, pd.DataFrame)``
    make_trading_environment() -> TradingEnvironment
        A class method that constructs the trading environment for the class.
        If this is overridden then ``make_load_function`` or the class
        attributes may not be respected.

    See Also
    --------
    :class:`zipline.finance.trading.TradingEnvironment`
    """

    @classmethod
    def make_load_function(cls):
        return None

    @classmethod
    def make_trading_environment(cls):
        return TradingEnvironment(
            load=cls.make_load_function(),
            asset_db_path=cls.asset_finder.engine,
            trading_calendar=cls.trading_calendar,
        )

    @classmethod
    def init_class_fixtures(cls):
        super(WithTradingEnvironment, cls).init_class_fixtures()
        cls.env = cls.make_trading_environment()


class WithSimParams(WithTradingEnvironment):
    """
    ZiplineTestCase mixin providing cls.sim_params as a class level fixture.

    The arguments used to construct the trading environment may be overridded
    by putting ``SIM_PARAMS_{argname}`` in the class dict except for the
    trading environment which is overridden with the mechanisms provided by
    ``WithTradingEnvironment``.

    Attributes
    ----------
    SIM_PARAMS_YEAR : int
    SIM_PARAMS_CAPITAL_BASE : float
    SIM_PARAMS_NUM_DAYS : int
    SIM_PARAMS_DATA_FREQUENCY : {'daily', 'minute'}
    SIM_PARAMS_EMISSION_RATE : {'daily', 'minute'}
        Forwarded to ``factory.create_simulation_parameters``.

    SIM_PARAMS_START : datetime
    SIM_PARAMS_END : datetime
        Forwarded to ``factory.create_simulation_parameters``. If not
        explicitly overridden these will be ``START_DATE`` and ``END_DATE``

    See Also
    --------
    zipline.utils.factory.create_simulation_parameters
    """
    SIM_PARAMS_YEAR = None
    SIM_PARAMS_CAPITAL_BASE = 1.0e5
    SIM_PARAMS_NUM_DAYS = None
    SIM_PARAMS_DATA_FREQUENCY = 'daily'
    SIM_PARAMS_EMISSION_RATE = 'daily'

    SIM_PARAMS_START = alias('START_DATE')
    SIM_PARAMS_END = alias('END_DATE')

    @classmethod
    def make_simparams(cls):
        return factory.create_simulation_parameters(
            year=cls.SIM_PARAMS_YEAR,
            start=cls.SIM_PARAMS_START,
            end=cls.SIM_PARAMS_END,
            num_days=cls.SIM_PARAMS_NUM_DAYS,
            capital_base=cls.SIM_PARAMS_CAPITAL_BASE,
            data_frequency=cls.SIM_PARAMS_DATA_FREQUENCY,
            emission_rate=cls.SIM_PARAMS_EMISSION_RATE,
            trading_calendar=cls.trading_calendar,
        )

    @classmethod
    def init_class_fixtures(cls):
        super(WithSimParams, cls).init_class_fixtures()
        cls.sim_params = cls.make_simparams()


class WithTradingSessions(WithTradingCalendars, WithDefaultDateBounds):
    """
    ZiplineTestCase mixin providing cls.trading_days, cls.all_trading_sessions
    as a class-level fixture.

    After init_class_fixtures has been called, `cls.all_trading_sessions`
    is populated with a dictionary of calendar name to the DatetimeIndex
    containing the calendar trading days ranging from:

    (DATA_MAX_DAY - (cls.TRADING_DAY_COUNT) -> DATA_MAX_DAY)

    `cls.trading_days`, for compatibility with existing tests which make the
    assumption that trading days are equity only, defaults to the nyse trading
    sessions.

    Attributes
    ----------
    DATA_MAX_DAY : datetime
        The most recent trading day in the calendar.
    TRADING_DAY_COUNT : int
        The number of days to put in the calendar. The default value of
        ``TRADING_DAY_COUNT`` is 126 (half a trading-year). Inheritors can
        override TRADING_DAY_COUNT to request more or less data.
    """
    DATA_MIN_DAY = alias('START_DATE')
    DATA_MAX_DAY = alias('END_DATE')

    # For backwards compatibility, exisitng tests and fixtures refer to
    # `trading_days` with the assumption that the value is days of the NYSE
    # calendar.
    trading_days = alias('nyse_sessions')

    @classmethod
    def init_class_fixtures(cls):
        super(WithTradingSessions, cls).init_class_fixtures()

        cls.trading_sessions = {}

        for cal_str in cls.TRADING_CALENDAR_STRS:
            trading_calendar = cls.trading_calendars[cal_str]
            sessions = trading_calendar.sessions_in_range(
                cls.DATA_MIN_DAY, cls.DATA_MAX_DAY)
            # Set name for aliasing.
            setattr(cls,
                    '{0}_sessions'.format(cal_str.lower()), sessions)
            cls.trading_sessions[cal_str] = sessions
        for exchange, cal_str in iteritems(cls.TRADING_CALENDAR_FOR_EXCHANGE):
            trading_calendar = cls.trading_calendars[cal_str]
            sessions = trading_calendar.sessions_in_range(
                cls.DATA_MIN_DAY, cls.DATA_MAX_DAY)
            cls.trading_sessions[exchange] = sessions


class WithTmpDir(object):
    """
    ZiplineTestCase mixing providing cls.tmpdir as a class-level fixture.

    After init_class_fixtures has been called, `cls.tmpdir` is populated with
    a `testfixtures.TempDirectory` object whose path is `cls.TMP_DIR_PATH`.

    Attributes
    ----------
    TMP_DIR_PATH : str
        The path to the new directory to create. By default this is None
        which will create a unique directory in /tmp.
    """
    TMP_DIR_PATH = None

    @classmethod
    def init_class_fixtures(cls):
        super(WithTmpDir, cls).init_class_fixtures()
        cls.tmpdir = cls.enter_class_context(
            tmp_dir(path=cls.TMP_DIR_PATH),
        )


class WithInstanceTmpDir(object):
    """
    ZiplineTestCase mixing providing self.tmpdir as an instance-level fixture.

    After init_instance_fixtures has been called, `self.tmpdir` is populated
    with a `testfixtures.TempDirectory` object whose path is
    `cls.TMP_DIR_PATH`.

    Attributes
    ----------
    INSTANCE_TMP_DIR_PATH : str
        The path to the new directory to create. By default this is None
        which will create a unique directory in /tmp.
    """
    INSTANCE_TMP_DIR_PATH = None

    def init_instance_fixtures(self):
        super(WithInstanceTmpDir, self).init_instance_fixtures()
        self.instance_tmpdir = self.enter_instance_context(
            tmp_dir(path=self.INSTANCE_TMP_DIR_PATH),
        )


class WithEquityDailyBarData(WithTradingEnvironment):
    """
    ZiplineTestCase mixin providing cls.make_equity_daily_bar_data.

    Attributes
    ----------
    EQUITY_DAILY_BAR_START_DATE : Timestamp
        The date at to which to start creating data. This defaults to
        ``START_DATE``.
    EQUITY_DAILY_BAR_END_DATE = Timestamp
        The end date up to which to create data. This defaults to ``END_DATE``.
    EQUITY_DAILY_BAR_SOURCE_FROM_MINUTE : bool
        If this flag is set, `make_equity_daily_bar_data` will read data from
        the minute bars defined by `WithEquityMinuteBarData`.
        The current default is `False`, but could be `True` in the future.

    Methods
    -------
    make_equity_daily_bar_data() -> iterable[(int, pd.DataFrame)]
        A class method that returns an iterator of (sid, dataframe) pairs
        which will be written to the bcolz files that the class's
        ``BcolzDailyBarReader`` will read from. By default this creates
        some simple sythetic data with
        :func:`~zipline.testing.create_daily_bar_data`

    See Also
    --------
    WithEquityMinuteBarData
    zipline.testing.create_daily_bar_data
    """
    EQUITY_DAILY_BAR_LOOKBACK_DAYS = 0

    EQUITY_DAILY_BAR_USE_FULL_CALENDAR = False
    EQUITY_DAILY_BAR_START_DATE = alias('START_DATE')
    EQUITY_DAILY_BAR_END_DATE = alias('END_DATE')
    EQUITY_DAILY_BAR_SOURCE_FROM_MINUTE = None

    @classmethod
    def _make_equity_daily_bar_from_minute(cls):
        assets = cls.asset_finder.retrieve_all(cls.asset_finder.equities_sids)
        minute_data = dict(cls.make_equity_minute_bar_data())
        for asset in assets:
            yield asset.sid, minute_to_session(minute_data[asset.sid],
                                               cls.trading_calendar)

    @classmethod
    def make_equity_daily_bar_data(cls):
        # Requires a WithEquityMinuteBarData to come before in the MRO.
        # Resample that data so that daily and minute bar data are aligned.
        if cls.EQUITY_DAILY_BAR_SOURCE_FROM_MINUTE:
            return cls._make_equity_daily_bar_from_minute()
        else:
            return create_daily_bar_data(
                cls.equity_daily_bar_days,
                cls.asset_finder.sids,
            )

    @classmethod
    def init_class_fixtures(cls):
        super(WithEquityDailyBarData, cls).init_class_fixtures()
        if cls.EQUITY_DAILY_BAR_USE_FULL_CALENDAR:
            days = cls.trading_calendar.all_sessions
        else:
            if cls.trading_calendar.is_session(
                    cls.EQUITY_DAILY_BAR_START_DATE
            ):
                first_session = cls.EQUITY_DAILY_BAR_START_DATE
            else:
                first_session = cls.trading_calendar.minute_to_session_label(
                    pd.Timestamp(cls.EQUITY_DAILY_BAR_START_DATE)
                )

            if cls.EQUITY_DAILY_BAR_LOOKBACK_DAYS > 0:
                first_session = cls.trading_calendar.sessions_window(
                    first_session,
                    -1 * cls.EQUITY_DAILY_BAR_LOOKBACK_DAYS
                )[0]

            days = cls.trading_calendar.sessions_in_range(
                first_session,
                cls.EQUITY_DAILY_BAR_END_DATE,
            )

        cls.equity_daily_bar_days = days


class WithBcolzEquityDailyBarReader(WithEquityDailyBarData, WithTmpDir):
    """
    ZiplineTestCase mixin providing cls.bcolz_daily_bar_path,
    cls.bcolz_daily_bar_ctable, and cls.bcolz_equity_daily_bar_reader
    class level fixtures.

    After init_class_fixtures has been called:
    - `cls.bcolz_daily_bar_path` is populated with
      `cls.tmpdir.getpath(cls.BCOLZ_DAILY_BAR_PATH)`.
    - `cls.bcolz_daily_bar_ctable` is populated with data returned from
      `cls.make_equity_daily_bar_data`. By default this calls
      :func:`zipline.pipeline.loaders.synthetic.make_equity_daily_bar_data`.
    - `cls.bcolz_equity_daily_bar_reader` is a daily bar reader
       pointing to the directory that was just written to.

    Attributes
    ----------
    BCOLZ_DAILY_BAR_PATH : str
        The path inside the tmpdir where this will be written.
    EQUITY_DAILY_BAR_LOOKBACK_DAYS : int
        The number of days of data to add before the first day. This is used
        when a test needs to use history, in which case this should be set to
        the largest history window that will be
        requested.
    EQUITY_DAILY_BAR_USE_FULL_CALENDAR : bool
        If this flag is set the ``equity_daily_bar_days`` will be the full
        set of trading days from the trading environment. This flag overrides
        ``EQUITY_DAILY_BAR_LOOKBACK_DAYS``.
    BCOLZ_DAILY_BAR_READ_ALL_THRESHOLD : int
        If this flag is set, use the value as the `read_all_threshold`
        parameter to BcolzDailyBarReader, otherwise use the default
        value.
    EQUITY_DAILY_BAR_SOURCE_FROM_MINUTE : bool
        If this flag is set, `make_equity_daily_bar_data` will read data from
        the minute bar reader defined by a `WithBcolzEquityMinuteBarReader`.

    Methods
    -------
    make_bcolz_daily_bar_rootdir_path() -> string
        A class method that returns the path for the rootdir of the daily
        bars ctable. By default this is a subdirectory BCOLZ_DAILY_BAR_PATH in
        the shared temp directory.

    See Also
    --------
    WithBcolzEquityMinuteBarReader
    WithDataPortal
    zipline.testing.create_daily_bar_data
    """
    BCOLZ_DAILY_BAR_PATH = 'daily_equity_pricing.bcolz'
    BCOLZ_DAILY_BAR_READ_ALL_THRESHOLD = None
    EQUITY_DAILY_BAR_SOURCE_FROM_MINUTE = False
    # allows WithBcolzEquityDailyBarReaderFromCSVs to call the
    # `write_csvs`method without needing to reimplement `init_class_fixtures`
    _write_method_name = 'write'

    @classmethod
    def make_bcolz_daily_bar_rootdir_path(cls):
        return cls.tmpdir.makedir(cls.BCOLZ_DAILY_BAR_PATH)

    @classmethod
    def init_class_fixtures(cls):
        super(WithBcolzEquityDailyBarReader, cls).init_class_fixtures()
        cls.bcolz_daily_bar_path = p = cls.make_bcolz_daily_bar_rootdir_path()
        days = cls.equity_daily_bar_days

        cls.bcolz_daily_bar_ctable = t = getattr(
            BcolzDailyBarWriter(p, cls.trading_calendar, days[0], days[-1]),
            cls._write_method_name,
        )(cls.make_equity_daily_bar_data())

        if cls.BCOLZ_DAILY_BAR_READ_ALL_THRESHOLD is not None:
            cls.bcolz_equity_daily_bar_reader = BcolzDailyBarReader(
                t, cls.BCOLZ_DAILY_BAR_READ_ALL_THRESHOLD)
        else:
            cls.bcolz_equity_daily_bar_reader = BcolzDailyBarReader(t)


class WithBcolzEquityDailyBarReaderFromCSVs(WithBcolzEquityDailyBarReader):
    """
    ZiplineTestCase mixin that provides
    cls.bcolz_equity_daily_bar_reader from a mapping of sids to CSV
    file paths.
    """
    _write_method_name = 'write_csvs'


def _trading_days_for_minute_bars(calendar,
                                  start_date,
                                  end_date,
                                  lookback_days):
    first_session = calendar.minute_to_session_label(start_date)

    if lookback_days > 0:
        first_session = calendar.sessions_window(
            first_session,
            -1 * lookback_days
        )[0]

    return calendar.sessions_in_range(first_session, end_date)


class _WithMinuteBarDataBase(WithTradingEnvironment):
    MINUTE_BAR_LOOKBACK_DAYS = 0
    MINUTE_BAR_START_DATE = alias('START_DATE')
    MINUTE_BAR_END_DATE = alias('END_DATE')


class WithEquityMinuteBarData(_WithMinuteBarDataBase):
    """
    ZiplineTestCase mixin providing cls.equity_minute_bar_days.

    After init_class_fixtures has been called:
    - `cls.equity_minute_bar_days` has the range over which data has been
       generated.

    Attributes
    ----------
    EQUITY_MINUTE_BAR_LOOKBACK_DAYS : int
        The number of days of data to add before the first day.
        This is used when a test needs to use history, in which case this
        should be set to the largest history window that will be requested.
    EQUITY_MINUTE_BAR_START_DATE : Timestamp
        The date at to which to start creating data. This defaults to
        ``START_DATE``.
    EQUITY_MINUTE_BAR_END_DATE = Timestamp
        The end date up to which to create data. This defaults to ``END_DATE``.

    Methods
    -------
    make_equity_minute_bar_data() -> iterable[(int, pd.DataFrame)]
        A class method that returns a dict mapping sid to dataframe
        which will be written to into the the format of the inherited
        class which writes the minute bar data for use by a reader.
        By default this creates some simple sythetic data with
        :func:`~zipline.testing.create_minute_bar_data`

    See Also
    --------
    WithEquityDailyBarData
    zipline.testing.create_minute_bar_data
    """
    EQUITY_MINUTE_BAR_LOOKBACK_DAYS = alias('MINUTE_BAR_LOOKBACK_DAYS')
    EQUITY_MINUTE_BAR_START_DATE = alias('MINUTE_BAR_START_DATE')
    EQUITY_MINUTE_BAR_END_DATE = alias('MINUTE_BAR_END_DATE')

    @classmethod
    def make_equity_minute_bar_data(cls):
        trading_calendar = cls.trading_calendars[Equity]
        return create_minute_bar_data(
            trading_calendar.minutes_for_sessions_in_range(
                cls.equity_minute_bar_days[0],
                cls.equity_minute_bar_days[-1],
            ),
            cls.asset_finder.equities_sids,
        )

    @classmethod
    def init_class_fixtures(cls):
        super(WithEquityMinuteBarData, cls).init_class_fixtures()
        trading_calendar = cls.trading_calendars[Equity]
        cls.equity_minute_bar_days = _trading_days_for_minute_bars(
            trading_calendar,
            pd.Timestamp(cls.EQUITY_MINUTE_BAR_START_DATE),
            pd.Timestamp(cls.EQUITY_MINUTE_BAR_END_DATE),
            cls.EQUITY_MINUTE_BAR_LOOKBACK_DAYS
        )


class WithFutureMinuteBarData(_WithMinuteBarDataBase):
    """
    ZiplineTestCase mixin providing cls.future_minute_bar_days.

    After init_class_fixtures has been called:
    - `cls.future_minute_bar_days` has the range over which data has been
       generated.

    Attributes
    ----------
    FUTURE_MINUTE_BAR_LOOKBACK_DAYS : int
        The number of days of data to add before the first day.
        This is used when a test needs to use history, in which case this
        should be set to the largest history window that will be requested.
    FUTURE_MINUTE_BAR_START_DATE : Timestamp
        The date at to which to start creating data. This defaults to
        ``START_DATE``.
    FUTURE_MINUTE_BAR_END_DATE = Timestamp
        The end date up to which to create data. This defaults to ``END_DATE``.

    Methods
    -------
    make_future_minute_bar_data() -> iterable[(int, pd.DataFrame)]
        A class method that returns a dict mapping sid to dataframe
        which will be written to into the the format of the inherited
        class which writes the minute bar data for use by a reader.
        By default this creates some simple sythetic data with
        :func:`~zipline.testing.create_minute_bar_data`

    See Also
    --------
    zipline.testing.create_minute_bar_data
    """
    FUTURE_MINUTE_BAR_LOOKBACK_DAYS = alias('MINUTE_BAR_LOOKBACK_DAYS')
    FUTURE_MINUTE_BAR_START_DATE = alias('MINUTE_BAR_START_DATE')
    FUTURE_MINUTE_BAR_END_DATE = alias('MINUTE_BAR_END_DATE')

    @classmethod
    def make_future_minute_bar_data(cls):
        trading_calendar = get_calendar('CME')
        return create_minute_bar_data(
            trading_calendar.minutes_for_sessions_in_range(
                cls.future_minute_bar_days[0],
                cls.future_minute_bar_days[-1],
            ),
            cls.asset_finder.futures_sids,
        )

    @classmethod
    def init_class_fixtures(cls):
        super(WithFutureMinuteBarData, cls).init_class_fixtures()
        # To be replaced by quanto calendar.
        trading_calendar = get_calendar('CME')
        cls.future_minute_bar_days = _trading_days_for_minute_bars(
            trading_calendar,
            pd.Timestamp(cls.FUTURE_MINUTE_BAR_START_DATE),
            pd.Timestamp(cls.FUTURE_MINUTE_BAR_END_DATE),
            cls.FUTURE_MINUTE_BAR_LOOKBACK_DAYS
        )


class WithBcolzEquityMinuteBarReader(WithEquityMinuteBarData, WithTmpDir):
    """
    ZiplineTestCase mixin providing cls.bcolz_minute_bar_path,
    cls.bcolz_minute_bar_ctable, and cls.bcolz_equity_minute_bar_reader
    class level fixtures.

    After init_class_fixtures has been called:
    - `cls.bcolz_minute_bar_path` is populated with
      `cls.tmpdir.getpath(cls.BCOLZ_MINUTE_BAR_PATH)`.
    - `cls.bcolz_minute_bar_ctable` is populated with data returned from
      `cls.make_equity_minute_bar_data`. By default this calls
      :func:`zipline.pipeline.loaders.synthetic.make_equity_minute_bar_data`.
    - `cls.bcolz_equity_minute_bar_reader` is a minute bar reader
       pointing to the directory that was just written to.

    Attributes
    ----------
    BCOLZ_MINUTE_BAR_PATH : str
        The path inside the tmpdir where this will be written.

    Methods
    -------
    make_bcolz_minute_bar_rootdir_path() -> string
        A class method that returns the path for the directory that contains
        the minute bar ctables. By default this is a subdirectory
        BCOLZ_MINUTE_BAR_PATH in the shared temp directory.

    See Also
    --------
    WithBcolzEquityDailyBarReader
    WithDataPortal
    zipline.testing.create_minute_bar_data
    """
    BCOLZ_EQUITY_MINUTE_BAR_PATH = 'minute_equity_pricing'

    @classmethod
    def make_bcolz_equity_minute_bar_rootdir_path(cls):
        return cls.tmpdir.makedir(cls.BCOLZ_EQUITY_MINUTE_BAR_PATH)

    @classmethod
    def init_class_fixtures(cls):
        super(WithBcolzEquityMinuteBarReader, cls).init_class_fixtures()
        cls.bcolz_equity_minute_bar_path = p = \
            cls.make_bcolz_equity_minute_bar_rootdir_path()
        days = cls.equity_minute_bar_days

        writer = BcolzMinuteBarWriter(
            p,
            cls.trading_calendar,
            days[0],
            days[-1],
            US_EQUITIES_MINUTES_PER_DAY
        )
        writer.write(cls.make_equity_minute_bar_data())

        cls.bcolz_equity_minute_bar_reader = \
            BcolzMinuteBarReader(p)


class WithBcolzFutureMinuteBarReader(WithFutureMinuteBarData, WithTmpDir):
    """
    ZiplineTestCase mixin providing cls.bcolz_minute_bar_path,
    cls.bcolz_minute_bar_ctable, and cls.bcolz_equity_minute_bar_reader
    class level fixtures.

    After init_class_fixtures has been called:
    - `cls.bcolz_minute_bar_path` is populated with
      `cls.tmpdir.getpath(cls.BCOLZ_MINUTE_BAR_PATH)`.
    - `cls.bcolz_minute_bar_ctable` is populated with data returned from
      `cls.make_equity_minute_bar_data`. By default this calls
      :func:`zipline.pipeline.loaders.synthetic.make_equity_minute_bar_data`.
    - `cls.bcolz_equity_minute_bar_reader` is a minute bar reader
       pointing to the directory that was just written to.

    Attributes
    ----------
    BCOLZ_FUTURE_MINUTE_BAR_PATH : str
        The path inside the tmpdir where this will be written.

    Methods
    -------
    make_bcolz_minute_bar_rootdir_path() -> string
        A class method that returns the path for the directory that contains
        the minute bar ctables. By default this is a subdirectory
        BCOLZ_MINUTE_BAR_PATH in the shared temp directory.

    See Also
    --------
    WithBcolzEquityDailyBarReader
    WithDataPortal
    zipline.testing.create_minute_bar_data
    """
    BCOLZ_FUTURE_MINUTE_BAR_PATH = 'minute_future_pricing'

    @classmethod
    def make_bcolz_future_minute_bar_rootdir_path(cls):
        return cls.tmpdir.makedir(cls.BCOLZ_FUTURE_MINUTE_BAR_PATH)

    @classmethod
    def init_class_fixtures(cls):
        super(WithBcolzFutureMinuteBarReader, cls).init_class_fixtures()
        trading_calendar = get_calendar('CME')
        cls.bcolz_future_minute_bar_path = p = \
            cls.make_bcolz_future_minute_bar_rootdir_path()
        days = cls.future_minute_bar_days

        writer = BcolzMinuteBarWriter(
            p,
            trading_calendar,
            days[0],
            days[-1],
            FUTURES_MINUTES_PER_DAY,
        )
        writer.write(cls.make_future_minute_bar_data())

        cls.bcolz_future_minute_bar_reader = \
            BcolzMinuteBarReader(p)


class WithAdjustmentReader(WithBcolzEquityDailyBarReader):
    """
    ZiplineTestCase mixin providing cls.adjustment_reader as a class level
    fixture.

    After init_class_fixtures has been called, `cls.adjustment_reader` will be
    populated with a new SQLiteAdjustmentReader object. The data that will be
    written can be passed by overriding `make_{field}_data` where field may
    be `splits`, `mergers` `dividends`, or `stock_dividends`.
    The daily bar reader used for this adjustment reader may be customized
    by overriding `make_adjustment_writer_equity_daily_bar_reader`.
    This is useful to providing a `MockDailyBarReader`.

    Methods
    -------
    make_splits_data() -> pd.DataFrame
        A class method that returns a dataframe of splits data to write to the
        class's adjustment db. By default this is empty.
    make_mergers_data() -> pd.DataFrame
        A class method that returns a dataframe of mergers data to write to the
        class's adjustment db. By default this is empty.
    make_dividends_data() -> pd.DataFrame
        A class method that returns a dataframe of dividends data to write to
        the class's adjustment db. By default this is empty.
    make_stock_dividends_data() -> pd.DataFrame
        A class method that returns a dataframe of stock dividends data to
        write to the class's adjustment db. By default this is empty.
    make_adjustment_db_conn_str() -> string
        A class method that returns the sqlite3 connection string for the
        database in to which the adjustments will be written. By default this
        is an in-memory database.
    make_adjustment_writer_equity_daily_bar_reader() -> pd.DataFrame
        A class method that returns the daily bar reader to use for the class's
        adjustment writer. By default this is the class's actual
        ``bcolz_equity_daily_bar_reader`` as inherited from
        ``WithBcolzEquityDailyBarReader``. This should probably not be
          overridden; however, some tests used a ``MockDailyBarReader``
         for this.
    make_adjustment_writer(conn: sqlite3.Connection) -> AdjustmentWriter
        A class method that constructs the adjustment which will be used
        to write the data into the connection to be used by the class's
        adjustment reader.

    See Also
    --------
    zipline.testing.MockDailyBarReader
    """
    @classmethod
    def _make_data(cls):
        return None

    make_splits_data = _make_data
    make_mergers_data = _make_data
    make_dividends_data = _make_data
    make_stock_dividends_data = _make_data

    del _make_data

    @classmethod
    def make_adjustment_writer(cls, conn):
        return SQLiteAdjustmentWriter(
            conn,
            cls.make_adjustment_writer_equity_daily_bar_reader(),
            cls.equity_daily_bar_days,
        )

    @classmethod
    def make_adjustment_writer_equity_daily_bar_reader(cls):
        return cls.bcolz_equity_daily_bar_reader

    @classmethod
    def make_adjustment_db_conn_str(cls):
        return ':memory:'

    @classmethod
    def init_class_fixtures(cls):
        super(WithAdjustmentReader, cls).init_class_fixtures()
        conn = sqlite3.connect(cls.make_adjustment_db_conn_str())
        cls.make_adjustment_writer(conn).write(
            splits=cls.make_splits_data(),
            mergers=cls.make_mergers_data(),
            dividends=cls.make_dividends_data(),
            stock_dividends=cls.make_stock_dividends_data(),
        )
        cls.adjustment_reader = SQLiteAdjustmentReader(conn)


class WithSeededRandomPipelineEngine(WithTradingSessions, WithAssetFinder):
    """
    ZiplineTestCase mixin providing class-level fixtures for running pipelines
    against deterministically-generated random data.

    Attributes
    ----------
    SEEDED_RANDOM_PIPELINE_SEED : int
        Fixture input. Random seed used to initialize the random state loader.
    seeded_random_loader : SeededRandomLoader
        Fixture output. Loader capable of providing columns for
        zipline.pipeline.data.testing.TestingDataSet.
    seeded_random_engine : SimplePipelineEngine
        Fixture output.  A pipeline engine that will use seeded_random_loader
        as its only data provider.

    Methods
    -------
    run_pipeline(start_date, end_date)
        Run a pipeline with self.seeded_random_engine.

    See Also
    --------
    zipline.pipeline.loaders.synthetic.SeededRandomLoader
    zipline.pipeline.loaders.testing.make_seeded_random_loader
    zipline.pipeline.engine.SimplePipelineEngine
    """
    SEEDED_RANDOM_PIPELINE_SEED = 42

    @classmethod
    def init_class_fixtures(cls):
        super(WithSeededRandomPipelineEngine, cls).init_class_fixtures()
        cls._sids = cls.asset_finder.sids
        cls.seeded_random_loader = loader = make_seeded_random_loader(
            cls.SEEDED_RANDOM_PIPELINE_SEED,
            cls.trading_days,
            cls._sids,
        )
        cls.seeded_random_engine = SimplePipelineEngine(
            get_loader=lambda column: loader,
            calendar=cls.trading_days,
            asset_finder=cls.asset_finder,
        )

    def raw_expected_values(self, column, start_date, end_date):
        """
        Get an array containing the raw values we expect to be produced for the
        given dates between start_date and end_date, inclusive.
        """
        all_values = self.seeded_random_loader.values(
            column.dtype,
            self.trading_days,
            self._sids,
        )
        row_slice = self.trading_days.slice_indexer(start_date, end_date)
        return all_values[row_slice]

    def run_pipeline(self, pipeline, start_date, end_date):
        """
        Run a pipeline with self.seeded_random_engine.
        """
        if start_date not in self.trading_days:
            raise AssertionError("Start date not in calendar: %s" % start_date)
        if end_date not in self.trading_days:
            raise AssertionError("End date not in calendar: %s" % end_date)
        return self.seeded_random_engine.run_pipeline(
            pipeline,
            start_date,
            end_date,
        )


class WithDataPortal(WithAdjustmentReader,
                     # Ordered so that bcolz minute reader is used first.
                     WithBcolzEquityMinuteBarReader,
                     WithBcolzFutureMinuteBarReader):
    """
    ZiplineTestCase mixin providing self.data_portal as an instance level
    fixture.

    After init_instance_fixtures has been called, `self.data_portal` will be
    populated with a new data portal created by passing in the class's
    trading env, `cls.bcolz_equity_minute_bar_reader`,
    `cls.bcolz_equity_daily_bar_reader`, and `cls.adjustment_reader`.

    Attributes
    ----------
    DATA_PORTAL_USE_DAILY_DATA : bool
        Should the daily bar reader be used? Defaults to True.
    DATA_PORTAL_USE_MINUTE_DATA : bool
        Should the minute bar reader be used? Defaults to True.
    DATA_PORTAL_USE_ADJUSTMENTS : bool
        Should the adjustment reader be used? Defaults to True.

    Methods
    -------
    make_data_portal() -> DataPortal
        Method which returns the data portal to be used for each test case.
        If this is overridden, the ``DATA_PORTAL_USE_*`` attributes may not
        be respected.
    """
    DATA_PORTAL_USE_DAILY_DATA = True
    DATA_PORTAL_USE_MINUTE_DATA = True
    DATA_PORTAL_USE_ADJUSTMENTS = True

    DATA_PORTAL_FIRST_TRADING_DAY = None

    def make_data_portal(self):
        if self.DATA_PORTAL_FIRST_TRADING_DAY is None:
            if self.DATA_PORTAL_USE_MINUTE_DATA:
                self.DATA_PORTAL_FIRST_TRADING_DAY = (
                    self.bcolz_equity_minute_bar_reader.
                    first_trading_day)
            elif self.DATA_PORTAL_USE_DAILY_DATA:
                self.DATA_PORTAL_FIRST_TRADING_DAY = (
                    self.bcolz_equity_daily_bar_reader.
                    first_trading_day)

        return DataPortal(
            self.env.asset_finder,
            self.trading_calendar,
            first_trading_day=self.DATA_PORTAL_FIRST_TRADING_DAY,
            equity_daily_reader=(
                self.bcolz_equity_daily_bar_reader
                if self.DATA_PORTAL_USE_DAILY_DATA else
                None
            ),
            equity_minute_reader=(
                self.bcolz_equity_minute_bar_reader
                if self.DATA_PORTAL_USE_MINUTE_DATA else
                None
            ),
            adjustment_reader=(
                self.adjustment_reader
                if self.DATA_PORTAL_USE_ADJUSTMENTS else
                None
            ),
            future_minute_reader=(
                self.bcolz_future_minute_bar_reader
                if self.DATA_PORTAL_USE_MINUTE_DATA else
                None
            ),
        )

    def init_instance_fixtures(self):
        super(WithDataPortal, self).init_instance_fixtures()
        self.data_portal = self.make_data_portal()


class WithResponses(object):
    """
    ZiplineTestCase mixin that provides self.responses as an instance
    fixture.

    After init_instance_fixtures has been called, `self.responses` will be
    a new `responses.RequestsMock` object. Users may add new endpoints to this
    with the `self.responses.add` method.
    """
    def init_instance_fixtures(self):
        super(WithResponses, self).init_instance_fixtures()
        self.responses = self.enter_instance_context(
            responses.RequestsMock(),
        )