Python blotter.Blotter类代码示例

    def test_blotter_processes_splits(self):
        blotter = Blotter('daily',  equity_slippage=FixedSlippage())

        # set up two open limit orders with very low limit prices,
        # one for sid 1 and one for sid 2
        asset1 = self.asset_finder.retrieve_asset(1)
        asset2 = self.asset_finder.retrieve_asset(2)
        asset133 = self.asset_finder.retrieve_asset(133)

        blotter.order(asset1, 100, LimitOrder(10))
        blotter.order(asset2, 100, LimitOrder(10))

        # send in splits for assets 133 and 2.  We have no open orders for
        # asset 133 so it should be ignored.
        blotter.process_splits([(asset133, 0.5), (asset2, 0.3333)])

        for asset in [asset1, asset2]:
            order_lists = blotter.open_orders[asset]
            self.assertIsNotNone(order_lists)
            self.assertEqual(1, len(order_lists))

        asset1_order = blotter.open_orders[1][0]
        asset2_order = blotter.open_orders[2][0]

        # make sure the asset1 order didn't change
        self.assertEqual(100, asset1_order.amount)
        self.assertEqual(10, asset1_order.limit)
        self.assertEqual(1, asset1_order.asset)

        # make sure the asset2 order did change
        # to 300 shares at 3.33
        self.assertEqual(300, asset2_order.amount)
        self.assertEqual(3.33, asset2_order.limit)
        self.assertEqual(2, asset2_order.asset)

    def test_batch_order_matches_multiple_orders(self):
        """
        Ensure the effect of order_batch is the same as multiple calls to
        order.
        """
        blotter1 = Blotter(self.sim_params.data_frequency,
                           self.asset_finder)
        blotter2 = Blotter(self.sim_params.data_frequency,
                           self.asset_finder)
        for i in range(1, 4):
            order_arg_lists = [
                (self.asset_24, i * 100, MarketOrder()),
                (self.asset_25, i * 100, LimitOrder(i * 100 + 1)),
            ]

            order_batch_ids = blotter1.batch_order(order_arg_lists)
            order_ids = []
            for order_args in order_arg_lists:
                order_ids.append(blotter2.order(*order_args))
            self.assertEqual(len(order_batch_ids), len(order_ids))

            self.assertEqual(len(blotter1.open_orders),
                             len(blotter2.open_orders))

            for (asset, _, _), order_batch_id, order_id in zip(
                    order_arg_lists, order_batch_ids, order_ids
            ):
                self.assertEqual(len(blotter1.open_orders[asset]),
                                 len(blotter2.open_orders[asset]))
                self.assertEqual(order_batch_id,
                                 blotter1.open_orders[asset][i-1].id)
                self.assertEqual(order_id,
                                 blotter2.open_orders[asset][i-1].id)

    def test_blotter_processes_splits(self):
        blotter = Blotter("daily", self.env.asset_finder, slippage_func=FixedSlippage())

        # set up two open limit orders with very low limit prices,
        # one for sid 1 and one for sid 2
        blotter.order(blotter.asset_finder.retrieve_asset(1), 100, LimitOrder(10))
        blotter.order(blotter.asset_finder.retrieve_asset(2), 100, LimitOrder(10))

        # send in a split for sid 2
        blotter.process_splits([(2, 0.3333)])

        for sid in [1, 2]:
            order_lists = blotter.open_orders[sid]
            self.assertIsNotNone(order_lists)
            self.assertEqual(1, len(order_lists))

        aapl_order = blotter.open_orders[1][0].to_dict()
        fls_order = blotter.open_orders[2][0].to_dict()

        # make sure the aapl order didn't change
        self.assertEqual(100, aapl_order["amount"])
        self.assertEqual(10, aapl_order["limit"])
        self.assertEqual(1, aapl_order["sid"])

        # make sure the fls order did change
        # to 300 shares at 3.33
        self.assertEqual(300, fls_order["amount"])
        self.assertEqual(3.33, fls_order["limit"])
        self.assertEqual(2, fls_order["sid"])

    def test_blotter_order_types(self, style_obj, expected_lmt, expected_stp):

        blotter = Blotter()

        blotter.order(24, 100, style_obj)
        result = blotter.open_orders[24][0]

        self.assertEqual(result.limit, expected_lmt)
        self.assertEqual(result.stop, expected_stp)

    def test_blotter_order_types(self, style_obj, expected_lmt, expected_stp):

        blotter = Blotter('daily', self.env.asset_finder)

        asset_24 = blotter.asset_finder.retrieve_asset(24)
        blotter.order(asset_24, 100, style_obj)
        result = blotter.open_orders[asset_24][0]

        self.assertEqual(result.limit, expected_lmt)
        self.assertEqual(result.stop, expected_stp)

    def test_cancel(self):
        blotter = Blotter('daily', self.asset_finder)

        oid_1 = blotter.order(self.asset_24, 100, MarketOrder())
        oid_2 = blotter.order(self.asset_24, 200, MarketOrder())
        oid_3 = blotter.order(self.asset_24, 300, MarketOrder())

        # Create an order for another asset to verify that we don't remove it
        # when we do cancel_all on 24.
        blotter.order(self.asset_25, 150, MarketOrder())

        self.assertEqual(len(blotter.open_orders), 2)
        self.assertEqual(len(blotter.open_orders[self.asset_24]), 3)
        self.assertEqual(
            [o.amount for o in blotter.open_orders[self.asset_24]],
            [100, 200, 300],
        )

        blotter.cancel(oid_2)
        self.assertEqual(len(blotter.open_orders), 2)
        self.assertEqual(len(blotter.open_orders[self.asset_24]), 2)
        self.assertEqual(
            [o.amount for o in blotter.open_orders[self.asset_24]],
            [100, 300],
        )
        self.assertEqual(
            [o.id for o in blotter.open_orders[self.asset_24]],
            [oid_1, oid_3],
        )

        blotter.cancel_all_orders_for_asset(self.asset_24)
        self.assertEqual(len(blotter.open_orders), 1)
        self.assertEqual(list(blotter.open_orders), [self.asset_25])

    def test_prune_orders(self):
        blotter = Blotter(self.sim_params.data_frequency,
                          self.env.asset_finder)

        asset_24 = blotter.asset_finder.retrieve_asset(24)
        asset_25 = blotter.asset_finder.retrieve_asset(25)

        blotter.order(asset_24, 100, MarketOrder())
        open_order = blotter.open_orders[asset_24][0]

        blotter.prune_orders([])
        self.assertEqual(1, len(blotter.open_orders[asset_24]))

        blotter.prune_orders([open_order])
        self.assertEqual(0, len(blotter.open_orders[asset_24]))

        # prune an order that isn't in our our open orders list, make sure
        # nothing blows up

        other_order = Order(
            dt=blotter.current_dt,
            sid=asset_25,
            amount=1
        )

        blotter.prune_orders([other_order])

    def test_blotter_processes_splits(self):
        sim_params = factory.create_simulation_parameters()
        blotter = Blotter()
        blotter.set_date(sim_params.period_start)

        # set up two open limit orders with very low limit prices,
        # one for sid 1 and one for sid 2
        blotter.order(1, 100, LimitOrder(10))
        blotter.order(2, 100, LimitOrder(10))

        # send in a split for sid 2
        split_event = factory.create_split(2, 0.33333,
                                           sim_params.period_start +
                                           timedelta(days=1))

        blotter.process_split(split_event)

        for sid in [1, 2]:
            order_lists = blotter.open_orders[sid]
            self.assertIsNotNone(order_lists)
            self.assertEqual(1, len(order_lists))

        aapl_order = blotter.open_orders[1][0].to_dict()
        fls_order = blotter.open_orders[2][0].to_dict()

        # make sure the aapl order didn't change
        self.assertEqual(100, aapl_order['amount'])
        self.assertEqual(10, aapl_order['limit'])
        self.assertEqual(1, aapl_order['sid'])

        # make sure the fls order did change
        # to 300 shares at 3.33
        self.assertEqual(300, fls_order['amount'])
        self.assertEqual(3.33, fls_order['limit'])
        self.assertEqual(2, fls_order['sid'])

    def __init__(self, *args, **kwargs):
        """Initialize sids and other state variables.

        :Arguments:
            data_frequency : str (daily, hourly or minutely)
               The duration of the bars.
            annualizer : int <optional>
               Which constant to use for annualizing risk metrics.
               If not provided, will extract from data_frequency.
            capital_base : float <default: 1.0e5>
               How much capital to start with.
        """
        self._portfolio = None
        self.datetime = None

        self.registered_transforms = {}
        self.transforms = []
        self.sources = []

        self._recorded_vars = {}

        self.logger = None

        self.benchmark_return_source = None

        # default components for transact
        self.slippage = VolumeShareSlippage()
        self.commission = PerShare()

        self.leverage = NullLeverage()

        if 'data_frequency' in kwargs:
            self.set_data_frequency(kwargs.pop('data_frequency'))
        else:
            self.data_frequency = None

        # Override annualizer if set
        if 'annualizer' in kwargs:
            self.annualizer = kwargs['annualizer']

        # set the capital base
        self.capital_base = kwargs.pop('capital_base', DEFAULT_CAPITAL_BASE)

        self.sim_params = kwargs.pop('sim_params', None)
        if self.sim_params:
            self.sim_params.data_frequency = self.data_frequency

        self.blotter = kwargs.pop('blotter', None)
        if not self.blotter:
            self.blotter = Blotter()

        # an algorithm subclass needs to set initialized to True when
        # it is fully initialized.
        self.initialized = False

        # call to user-defined constructor method
        self.initialize(*args, **kwargs)

    def test_slippage_and_commission_dispatching(self):
        blotter = Blotter(
            self.sim_params.data_frequency,
            equity_slippage=FixedSlippage(spread=0.0),
            future_slippage=FixedSlippage(spread=2.0),
            equity_commission=PerTrade(cost=1.0),
            future_commission=PerTrade(cost=2.0),
        )
        blotter.order(self.asset_24, 1, MarketOrder())
        blotter.order(self.future_cl, 1, MarketOrder())

        bar_data = self.create_bardata(
            simulation_dt_func=lambda: self.sim_params.sessions[-1],
        )
        txns, commissions, _ = blotter.get_transactions(bar_data)

        # The equity transaction should have the same price as its current
        # price because the slippage spread is zero. Its commission should be
        # $1.00.
        equity_txn = txns[0]
        self.assertEqual(
            equity_txn.price,
            bar_data.current(equity_txn.asset, 'price'),
        )
        self.assertEqual(commissions[0]['cost'], 1.0)

        # The future transaction price should be 1.0 more than its current
        # price because half of the 'future_slippage' spread is added. Its
        # commission should be $2.00.
        future_txn = txns[1]
        self.assertEqual(
            future_txn.price,
            bar_data.current(future_txn.asset, 'price') + 1.0,
        )
        self.assertEqual(commissions[1]['cost'], 2.0)

    def test_blotter_never_cancel(self):
        blotter = Blotter('minute', cancel_policy=NeverCancel())

        blotter.order(self.asset_24, 100, MarketOrder())

        self.assertEqual(len(blotter.new_orders), 1)
        self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)

        blotter.execute_cancel_policy(BAR)
        self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)

        blotter.execute_cancel_policy(SESSION_END)
        self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)

    def test_blotter_never_cancel(self):
        blotter = Blotter("minute", self.env.asset_finder, cancel_policy=NeverCancel())

        blotter.order(blotter.asset_finder.retrieve_asset(24), 100, MarketOrder())

        self.assertEqual(len(blotter.new_orders), 1)
        self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)

        blotter.execute_cancel_policy(BAR)
        self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)

        blotter.execute_cancel_policy(DAY_END)
        self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)

    def test_prune_orders(self):
        blotter = Blotter(self.sim_params.data_frequency)

        blotter.order(self.asset_24, 100, MarketOrder())
        open_order = blotter.open_orders[self.asset_24][0]

        blotter.prune_orders([])
        self.assertEqual(1, len(blotter.open_orders[self.asset_24]))

        blotter.prune_orders([open_order])
        self.assertEqual(0, len(blotter.open_orders[self.asset_24]))

        # prune an order that isn't in our our open orders list, make sure
        # nothing blows up

        other_order = Order(
            dt=blotter.current_dt,
            asset=self.asset_25,
            amount=1
        )

        blotter.prune_orders([other_order])

    def test_blotter_eod_cancellation(self):
        blotter = Blotter('minute', cancel_policy=EODCancel())

        # Make two orders for the same asset, so we can test that we are not
        # mutating the orders list as we are cancelling orders
        blotter.order(self.asset_24, 100, MarketOrder())
        blotter.order(self.asset_24, -100, MarketOrder())

        self.assertEqual(len(blotter.new_orders), 2)
        order_ids = [order.id for order in blotter.open_orders[self.asset_24]]

        self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)
        self.assertEqual(blotter.new_orders[1].status, ORDER_STATUS.OPEN)

        blotter.execute_cancel_policy(BAR)
        self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)
        self.assertEqual(blotter.new_orders[1].status, ORDER_STATUS.OPEN)

        blotter.execute_cancel_policy(SESSION_END)
        for order_id in order_ids:
            order = blotter.orders[order_id]
            self.assertEqual(order.status, ORDER_STATUS.CANCELLED)

    def test_blotter_eod_cancellation(self):
        blotter = Blotter("minute", self.env.asset_finder, cancel_policy=EODCancel())
        asset_24 = blotter.asset_finder.retrieve_asset(24)

        # Make two orders for the same sid, so we can test that we are not
        # mutating the orders list as we are cancelling orders
        blotter.order(asset_24, 100, MarketOrder())
        blotter.order(asset_24, -100, MarketOrder())

        self.assertEqual(len(blotter.new_orders), 2)
        order_ids = [order.id for order in blotter.open_orders[asset_24]]

        self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)
        self.assertEqual(blotter.new_orders[1].status, ORDER_STATUS.OPEN)

        blotter.execute_cancel_policy(BAR)
        self.assertEqual(blotter.new_orders[0].status, ORDER_STATUS.OPEN)
        self.assertEqual(blotter.new_orders[1].status, ORDER_STATUS.OPEN)

        blotter.execute_cancel_policy(DAY_END)
        for order_id in order_ids:
            order = blotter.orders[order_id]
            self.assertEqual(order.status, ORDER_STATUS.CANCELLED)