Python Blotter.process_trade方法代码示例

# 需要导入模块: from zipline.finance.blotter import Blotter [as 别名]
# 或者: from zipline.finance.blotter.Blotter import process_trade [as 别名]
    def test_order_rejection(self):
        blotter = Blotter()
        # Reject a nonexistent order -> no order appears in new_order,
        # no exceptions raised out
        blotter.reject(56)
        self.assertEqual(blotter.new_orders, [])

        # Basic tests of open order behavior
        open_order_id = blotter.order(24, 100, MarketOrder())
        second_order_id = blotter.order(24, 50, MarketOrder())
        self.assertEqual(len(blotter.open_orders[24]), 2)
        open_order = blotter.open_orders[24][0]
        self.assertEqual(open_order.status, ORDER_STATUS.OPEN)
        self.assertEqual(open_order.id, open_order_id)
        self.assertIn(open_order, blotter.new_orders)

        # Reject that order immediately (same bar, i.e. still in new_orders)
        blotter.reject(open_order_id)
        self.assertEqual(len(blotter.new_orders), 2)
        self.assertEqual(len(blotter.open_orders[24]), 1)
        still_open_order = blotter.new_orders[0]
        self.assertEqual(still_open_order.id, second_order_id)
        self.assertEqual(still_open_order.status, ORDER_STATUS.OPEN)
        rejected_order = blotter.new_orders[1]
        self.assertEqual(rejected_order.status, ORDER_STATUS.REJECTED)
        self.assertEqual(rejected_order.reason, '')

        # Do it again, but reject it at a later time (after tradesimulation
        # pulls it from new_orders)
        blotter = Blotter()
        new_open_id = blotter.order(24, 10, MarketOrder())
        new_open_order = blotter.open_orders[24][0]
        self.assertEqual(new_open_id, new_open_order.id)
        # Pretend that the trade simulation did this.
        blotter.new_orders = []

        rejection_reason = "Not enough cash on hand."
        blotter.reject(new_open_id, reason=rejection_reason)
        rejected_order = blotter.new_orders[0]
        self.assertEqual(rejected_order.id, new_open_id)
        self.assertEqual(rejected_order.status, ORDER_STATUS.REJECTED)
        self.assertEqual(rejected_order.reason, rejection_reason)

        # You can't reject a filled order.
        blotter = Blotter()   # Reset for paranoia
        blotter.current_dt = datetime.datetime.now()
        filled_id = blotter.order(24, 100, MarketOrder())
        aapl_trade = create_trade(24, 50.0, 400, datetime.datetime.now())
        filled_order = None
        for txn, updated_order in blotter.process_trade(aapl_trade):
            filled_order = updated_order

        self.assertEqual(filled_order.id, filled_id)
        self.assertIn(filled_order, blotter.new_orders)
        self.assertEqual(filled_order.status, ORDER_STATUS.FILLED)
        self.assertNotIn(filled_order, blotter.open_orders[24])

        blotter.reject(filled_id)
        updated_order = blotter.orders[filled_id]
        self.assertEqual(updated_order.status, ORDER_STATUS.FILLED)

# 需要导入模块: from zipline.finance.blotter import Blotter [as 别名]
# 或者: from zipline.finance.blotter.Blotter import process_trade [as 别名]
    def test_order_hold(self):
        """
        Held orders act almost identically to open orders, except for the
        status indication. When a fill happens, the order should switch
        status to OPEN/FILLED as necessary
        """
        blotter = Blotter()
        # Nothing happens on held of a non-existent order
        blotter.hold(56)
        self.assertEqual(blotter.new_orders, [])

        open_id = blotter.order(24, 100, MarketOrder())
        open_order = blotter.open_orders[24][0]
        self.assertEqual(open_order.id, open_id)

        blotter.hold(open_id)
        self.assertEqual(len(blotter.new_orders), 1)
        self.assertEqual(len(blotter.open_orders[24]), 1)
        held_order = blotter.new_orders[0]
        self.assertEqual(held_order.status, ORDER_STATUS.HELD)
        self.assertEqual(held_order.reason, '')

        blotter.cancel(held_order.id)
        self.assertEqual(len(blotter.new_orders), 1)
        self.assertEqual(len(blotter.open_orders[24]), 0)
        cancelled_order = blotter.new_orders[0]
        self.assertEqual(cancelled_order.id, held_order.id)
        self.assertEqual(cancelled_order.status, ORDER_STATUS.CANCELLED)

        for trade_amt in (100, 400):
            # Verify that incoming fills will change the order status.
            order_size = 100
            expected_filled = trade_amt * 0.25
            expected_open = order_size - expected_filled
            expected_status = ORDER_STATUS.OPEN if expected_open else \
                ORDER_STATUS.FILLED

            blotter = Blotter()
            blotter.current_dt = datetime.datetime.now()
            open_id = blotter.order(24, order_size, MarketOrder())
            open_order = blotter.open_orders[24][0]
            self.assertEqual(open_id, open_order.id)
            blotter.hold(open_id)
            held_order = blotter.new_orders[0]

            aapl_trade = create_trade(24, 50.0, trade_amt,
                                      datetime.datetime.now())
            filled_order = None
            for txn, updated_order in blotter.process_trade(aapl_trade):
                filled_order = updated_order
            self.assertEqual(filled_order.id, held_order.id)
            self.assertEqual(filled_order.status, expected_status)
            self.assertEqual(filled_order.filled, expected_filled)
            self.assertEqual(filled_order.open_amount, expected_open)

# 需要导入模块: from zipline.finance.blotter import Blotter [as 别名]
# 或者: from zipline.finance.blotter.Blotter import process_trade [as 别名]
    def transaction_sim(self, **params):
        """ This is a utility method that asserts expected
        results for conversion of orders to transactions given a
        trade history"""

        trade_count = params['trade_count']
        trade_interval = params['trade_interval']
        order_count = params['order_count']
        order_amount = params['order_amount']
        order_interval = params['order_interval']
        expected_txn_count = params['expected_txn_count']
        expected_txn_volume = params['expected_txn_volume']
        # optional parameters
        # ---------------------
        # if present, alternate between long and short sales
        alternate = params.get('alternate')
        # if present, expect transaction amounts to match orders exactly.
        complete_fill = params.get('complete_fill')

        sid = 1
        sim_params = factory.create_simulation_parameters()
        blotter = Blotter()
        price = [10.1] * trade_count
        volume = [100] * trade_count
        start_date = sim_params.first_open

        generated_trades = factory.create_trade_history(
            sid,
            price,
            volume,
            trade_interval,
            sim_params,
            env=self.env,
        )

        if alternate:
            alternator = -1
        else:
            alternator = 1

        order_date = start_date
        for i in range(order_count):

            blotter.set_date(order_date)
            blotter.order(sid, order_amount * alternator ** i, MarketOrder())

            order_date = order_date + order_interval
            # move after market orders to just after market next
            # market open.
            if order_date.hour >= 21:
                if order_date.minute >= 00:
                    order_date = order_date + timedelta(days=1)
                    order_date = order_date.replace(hour=14, minute=30)

        # there should now be one open order list stored under the sid
        oo = blotter.open_orders
        self.assertEqual(len(oo), 1)
        self.assertTrue(sid in oo)
        order_list = oo[sid][:]  # make copy
        self.assertEqual(order_count, len(order_list))

        for i in range(order_count):
            order = order_list[i]
            self.assertEqual(order.sid, sid)
            self.assertEqual(order.amount, order_amount * alternator ** i)

        tracker = PerformanceTracker(sim_params, env=self.env)

        benchmark_returns = [
            Event({'dt': dt,
                   'returns': ret,
                   'type':
                   zipline.protocol.DATASOURCE_TYPE.BENCHMARK,
                   'source_id': 'benchmarks'})
            for dt, ret in self.env.benchmark_returns.iteritems()
            if dt.date() >= sim_params.period_start.date() and
            dt.date() <= sim_params.period_end.date()
        ]

        generated_events = date_sorted_sources(generated_trades,
                                               benchmark_returns)

        # this approximates the loop inside TradingSimulationClient
        transactions = []
        for dt, events in itertools.groupby(generated_events,
                                            operator.attrgetter('dt')):
            for event in events:
                if event.type == DATASOURCE_TYPE.TRADE:

                    for txn, order in blotter.process_trade(event):
                        transactions.append(txn)
                        tracker.process_transaction(txn)
                elif event.type == DATASOURCE_TYPE.BENCHMARK:
                    tracker.process_benchmark(event)
                elif event.type == DATASOURCE_TYPE.TRADE:
                    tracker.process_trade(event)

        if complete_fill:
            self.assertEqual(len(transactions), len(order_list))

#.........这里部分代码省略.........