Source code for labscheduler.sila_server.generated.schedulingservice.schedulingservice_base

# Generated by sila2.code_generator; sila2.__version__: 0.12.2
from __future__ import annotations

from abc import ABC, abstractmethod
from typing import TYPE_CHECKING, List, Optional

from sila2.server import FeatureImplementationBase, MetadataDict, ObservableCommandInstance

if TYPE_CHECKING:
    from datetime import timedelta

    from ...server import Server
    from .schedulingservice_types import (
        AlgorithmMetaData,
        ComputeSchedule_Responses,
        SelectAlgorithm_Responses,
        WorkflowGraph,
    )




class SchedulingServiceBase(FeatureImplementationBase, ABC):
    parent_server: Server

    ComputeSchedule_default_lifetime_of_execution: timedelta | None

    def __init__(self, parent_server: Server):
        """
            Provides an interface for the PythonLabOrchestrator or any other lab environment to interact with the
        scheduling module. It provides an observable command to schedule a workflow(exact syntax explained in command).
        You can choose between different algorithms as get their metadata.
        """
        super().__init__(parent_server=parent_server)

        self.ComputeSchedule_default_lifetime_of_execution = None



    @abstractmethod
    def get_AvailableAlgorithms(self, *, metadata: MetadataDict) -> list[AlgorithmMetaData]:
        """
        List of algorithm info for all available algorithms

        :param metadata: The SiLA Client Metadata attached to the call
        :return: List of algorithm info for all available algorithms
        """




    @abstractmethod
    def get_CurrentAlgorithm(self, *, metadata: MetadataDict) -> AlgorithmMetaData:
        """
        The currently selected algorithm

        :param metadata: The SiLA Client Metadata attached to the call
        :return: The currently selected algorithm
        """




    @abstractmethod
    def SelectAlgorithm(self, AlgorithmName: str, *, metadata: MetadataDict) -> SelectAlgorithm_Responses:
        """
        Selects the algorithm to be used in the ComputeSchedule command


        :param AlgorithmName: Name of the Algorithm

        :param metadata: The SiLA Client Metadata attached to the call

        """




    @abstractmethod
    def ComputeSchedule(
        self,
        WorkflowGraph: WorkflowGraph,
        MaxComputationTime: float,
        *,
        metadata: MetadataDict,
        instance: ObservableCommandInstance,
    ) -> ComputeSchedule_Responses:
        """
        Takes a workflow graph (see parameter description) and computes a schedule for the currently configured lab
        environment (LabConfigurationController) with the currently selected algorithm.
        You have to give the maximum computation time.

        :param WorkflowGraph: The workflow graph of an experiment in the required SiLA structure.
        :param MaxComputationTime: Maximum computation time in seconds
        :param metadata: The SiLA Client Metadata attached to the call
        :param instance: The command instance, enabling sending status updates to subscribed clients

        :return: A tuple with:
            - The computed schedule
            - A string indicating whether the schedule is "optimal", "feasible", or "infeasible"
        """