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):
"""
Point of entry. Process an event frame.
"""
# extract dates
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 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 = {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)
