Python protocol.Event类代码示例

    def handle_data(self, data, *args, **kwargs):
        """
        Point of entry. Process an event frame.
        """
        # extract dates
        dts = [event.dt for event in itervalues(data._data)]
        # we have to provide the event with a dt. This is only for
        # checking if the event is outside the window or not so a
        # couple of seconds shouldn't matter. We don't add it to
        # the data parameter, because it would mix dt with the
        # sid keys.
        event = Event()
        event.dt = max(dts)
        event.data = {k: v.__dict__ for k, v in iteritems(data._data)
                      # Need to check if data has a 'length' to filter
                      # out sids without trade data available.
                      # TODO: expose more of 'no trade available'
                      # functionality to zipline
                      if len(v)}

        # only modify the trailing window if this is
        # a new event. This is intended to make handle_data
        # idempotent.
        if self.last_dt < event.dt:
            self.updated = True
            self._append_to_window(event)
        else:
            self.updated = False

        # return newly computed or cached value
        return self.get_transform_value(*args, **kwargs)

    def handle_data(self, data, *args, **kwargs):
        """
        New method to handle a data frame as sent to the algorithm's
        handle_data method.
        """
        # extract dates
        # dts = [data[sid].datetime for sid in self.sids]
        dts = [event.datetime for event in data.itervalues()]
        # we have to provide the event with a dt. This is only for
        # checking if the event is outside the window or not so a
        # couple of seconds shouldn't matter. We don't add it to
        # the data parameter, because it would mix dt with the
        # sid keys.
        event = Event()
        event.dt = max(dts)
        event.data = {
            k: v.__dict__
            for k, v in data.iteritems()
            # Need to check if data has a 'length' to filter
            # out sids without trade data available.
            # TODO: expose more of 'no trade available'
            # functionality to zipline
            if len(v)
        }

        # append data frame to window. update() will call handle_add() and
        # handle_remove() appropriately
        self.update(event)

        # return newly computed or cached value
        return self.get_transform_value(*args, **kwargs)

    def handle_data(self, data, *args, **kwargs):
        """
        New method to handle a data frame as sent to the algorithm's
        handle_data method.
        """
        # extract dates
        #dts = [data[sid].datetime for sid in self.sids]
        dts = [event.datetime for event in data.itervalues()]
        # we have to provide the event with a dt. This is only for
        # checking if the event is outside the window or not so a
        # couple of seconds shouldn't matter. We don't add it to
        # the data parameter, because it would mix dt with the
        # sid keys.
        event = Event()
        event.dt = max(dts)
        event.data = {k: v.__dict__ for k, v in data.iteritems()
                      # Need to check if data has a 'length' to filter
                      # out sids without trade data available.
                      # TODO: expose more of 'no trade available'
                      # functionality to zipline
                      if len(v)}

        # only modify the trailing window if this is
        # a new event. This is intended to make handle_data
        # idempotent.
        if event not in self.ticks:
            # append data frame to window. update() will call handle_add() and
            # handle_remove() appropriately, and self.updated
            # will be modified based on the refresh_period
            self.update(event)
        else:
            # we are recalculating based on an old event, so
            # there is no change in the contents of the trailing
            # window
            self.updated = False

        # return newly computed or cached value
        return self.get_transform_value(*args, **kwargs)

    def handle_data(self, data, *args, **kwargs):
        """
        New method to handle a data frame as sent to the algorithm's
        handle_data method.
        """
        # extract dates
        #dts = [data[sid].datetime for sid in self.sids]
        dts = [event.datetime for event in data.itervalues()]
        # we have to provide the event with a dt. This is only for
        # checking if the event is outside the window or not so a
        # couple of seconds shouldn't matter. We don't add it to
        # the data parameter, because it would mix dt with the
        # sid keys.
        event = Event()
        event.dt = max(dts)
        event.data = data

        # append data frame to window. update() will call handle_add() and
        # handle_remove() appropriately
        self.update(event)

        # return newly computed or cached value
        return self.get_transform_value(*args, **kwargs)

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