def to_result(self):
"""
Returns the current state of this signal as a result (i.e. a success or failure)
"""
try:
return result.Success(self.now)
except Exception as e:
return result.Failure(e)
def update(self, new_value, propagator = Propagator.instance()):
"""
Updates the current value of this signal to the new value and propagates
the change through the data-flow graph
"""
if new_value != self.__current:
self.__current = new_value
# Propagate the update
propagator.propagate(self, result.Success(self.__current))
def __recalculate(self):
# Link ourself to our dependencies as we go
tracking.begin(lambda dep: dep.link_child(self))
# If an error occurs during the calculation, we want to store it
r = None
try:
r = result.Success(self.__calc())
except Exception as e:
r = result.Failure(e)
finally:
tracking.end()
return r
def __lshift__(self, value):
"""
Emits the given value at the next opportunity
"""
self.__to_emit = result.Success(value)
return self
def emit(self, value, propagator=Propagator.instance()):
"""
Propagates the given value through the data-flow graph
"""
propagator.propagate(self, result.Success(value))