import abc from traits.api import ABCHasStrictTraits, Instance from .i_kpi_calculator_factory import IKPICalculatorFactory class BaseKPICalculator(ABCHasStrictTraits): """Base class for the KPICalculators. Inherit this class for your KPI calculator. """ #: A reference to the factory factory = Instance(IKPICalculatorFactory) def __init__(self, factory, *args, **kwargs): self.factory = factory super(BaseKPICalculator, self).__init__(*args, **kwargs) @abc.abstractmethod def run(self, model, data_values): """ Executes the KPI evaluation and returns the results it computes. Reimplement this method in your specific KPI calculator. Parameters ---------- model: BaseKPICalculatorModel The model of the KPI Calculator, instantiated through create_model() data_values: a list of DataValue instances containing data from the MCO and DataSources. Returns ------- List[DataValue]: The result of this KPI evaluation, as a list of DataValues. """ @abc.abstractmethod def slots(self, model): """Returns the input (and output) slots of the KPI Calculator. Slots are the entities that are needed (and produced) by this KPI Calculator. The slots may depend on the configuration options, and thus the model. This allows, for example, to change the slots depending if an option is enabled or not. Parameters ---------- model: BaseKPICalculatorModel The model of the KPICalculator, instantiated through create_model() Returns ------- (input_slots, output_slots): tuple[tuple, tuple] A tuple containing two tuples. The first element is the input slots, the second element is the output slots. Each slot must be an instance of the Slot class. It is possible for each of the two inside tuples to be empty. The case of an empty input slot is common: the KPICalculator does not need any information from the MCO to operate. The case of an empty output slot is uncommon, but supported: the KPICalculator does not produce any output and is therefore useless. """