Properties

Kraken tasks have properties which are described as class annotations as Property types. They function as a lazy transport mechanism for data between tasks and allows Kraken to automatically establish dependencies between tasks whose properties are connected.

from kraken.core import Property, Task

class SayHello(Task):
    name: Property[str]

    def execute(self) -> None:
        print("Hello,", self.name.get())

class GetName(Task):
    name: Property[str] = Property.output()

    def execute(self) -> None:
        self.name = "World"

Properties as descriptors

When accessing a property on a task, you get the Property object back. When setting a value, you can use it's set() method, or directly assign to the property. This is because properties are descriptors and implement __get__() and __set__() accordingly.

say_hello = project.task("say_hello", GetName)
say_hello.name.set("World")
say_hello.name = "World"

Output properties

Not much differentiates output properties from normal properties, except that they raise a Property.Deferred exception instead of Property.Empty when their .get() method is called and they have not been populated with a value.

In addition, output properties are taken into account when finding task outputs by type using {@pylink kraken.core.system.task.TaskSet.select}.

Preferred property types

You should prefer to use a Property[Sequence[X]] over a Property[List[X]]. This prevents accidental mutation of the underlying list. The same goes for Property[Mapping[K, V]] over Property[Dict[K, V]]. It also improves usability of the property API because you no longer have to cast or convert everything to the explicit type.

A property value can still be mutated by using {@pylink kraken.core.system.property.Property.setmap}. It is a utility function, combining map() and set().

prop: Property[Sequence[str]] = ...
prop.setmap(lambda v: [*v, "new value"])