Skip to content

Use your business objects

You can use business objects (the instances of the classes from your business model) directly with the rule engine, without converting them to dictionaries.

Arta processes mappings in the rules and actions to inject data into functions, as you saw in the simple example of this documentation.

The problem with dict serialisation

Let’s consider the following example, representing a Car with its Engine which itself has attributes.

1
2
3
4
5
6
class Engine:
    power: int
    consumption: int  

class Car:
    engine: Engine

When following the regular usage of Arta, one would convert an instance of a Car to a dictionary with a sort of serializer. A candidate code for this might be:

1
2
3
4
5
6
7
8
9
from typing import Any

def serialize_car_to_dict(car: Car) -> dict[str, Any]:
    return {
        "engine": {
            "power": car.engine.power,
            "consumption": car.engine.consumption
        }
    }

When using Pydantic

If you use Pydantic, you might directly use the model_dump function in order to represent your object as a dictionnary object.

This way, you can write you conditions as follows:

1
2
3
4
5
6
7
conditions:
  HAS_LOWER_CONSUMPTION:
    description: "Whether an engine as a low consumption".
    validation_function: is_value_below_threshold
    condition_parameters:
      value: input.engine.power
      threshold: 10

This is where the mapping is important: to go through the engine data and access the power attribute. We serialised the object in a custom code but there might be a better solution with less code…

Transform any business object to a mapping

The solution to this issue is to use any business object as a mapping. In Python, any object may behave as such by subclassing Mapping and implementing the abstract methods.

As an example, we provide the following mixin:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
from collections.abc import Mapping, Iterator
from typing import Any

class ObjectToMappingMixin(Mapping):
    def __iter__(self) -> Iterator[Any]:
        return iter(vars(self))

    def __len__(self) -> int:
        return len(vars(self))

    def __getitem__(self, key: str, /) -> Any:
        return getattr(self, key)

Now, we can make our business objects subclass this mixin:

1
2
3
4
5
6
class Engine(ObjectToMappingMixin):
    power: int
    consumption: int  

class Car(ObjectToMappingMixin):
    engine: Engine

Engine and Car now behave as mapping and it’s possible to access the attributes of Engine from car using the dict’s getitem strategy, such as:

1
2
3
4
5
engine = Engine(power=1, consumption= 12)
car = Car(engine=engine)

assert car["engine"]["power"] == 1
assert car["engine"]["consumption"] == 12

Finaly, when using the RulesEngine.apply_rules method, there is not longer need to convert your business objects to dictionaries, you can directly use them like:

1
2
3
4
from arta import RulesEngine

eng = RulesEngine(config_path="/to/my/config/dir") 
result = eng.apply_rules(input_data={"car": car})