def requires_emit(self, resolver: Resolver,
queue: QueueScheduler) -> Dict[object, ResultVariable]:
# FIXME: may be done more efficient?
out = {
self.name: resolver.lookup(self.full_name)
} # type : Dict[object, ResultVariable]
return out
def requires_emit_gradual(
self, resolver: Resolver, queue: QueueScheduler, resultcollector: ResultCollector
) -> Dict[object, ResultVariable]:
var = resolver.lookup(self.full_name)
var.listener(resultcollector, self.location)
out = {self.name: var} # type : Dict[object, ResultVariable]
return out
def fetch_variable(
self, requires: Dict[object, ResultVariable], resolver: Resolver, queue_scheduler: QueueScheduler
) -> ResultVariable:
"""
Fetches the referred variable
"""
if self.instance:
# get the Instance
obj = self.instance.execute({k: v.get_value() for k, v in requires.items()}, resolver, queue_scheduler)
if isinstance(obj, list):
raise RuntimeException(self, "can not get a attribute %s, %s is a list" % (self.attribute, obj))
if not isinstance(obj, Instance):
raise RuntimeException(self, "can not get a attribute %s, %s not an entity" % (self.attribute, obj))
# get the attribute result variable
return obj.get_attribute(self.attribute)
else:
return resolver.lookup(self.attribute)
def emit(self, resolver: Resolver, queue: QueueScheduler) -> None:
target = resolver.lookup(self.name)
reqs = self.value.requires_emit(resolver, queue)
ExecutionUnit(queue, resolver, target, reqs, self.value)
def emit(self, resolver: Resolver, queue: QueueScheduler) -> None:
self._add_to_dataflow_graph(resolver.dataflow_graph)
target = resolver.lookup(str(self.name))
assert isinstance(target, ResultVariable)
reqs = self.value.requires_emit(resolver, queue)
ExecutionUnit(queue, resolver, target, reqs, self.value, owner=self)