labscheduler.sila_server.generated.schedulingservice package

Submodules

• labscheduler.sila_server.generated.schedulingservice.schedulingservice_base module
  • SchedulingServiceBase
    • SchedulingServiceBase.ComputeSchedule()
    • SchedulingServiceBase.ComputeSchedule_default_lifetime_of_execution
    • SchedulingServiceBase.SelectAlgorithm()
    • SchedulingServiceBase.__is_running
    • SchedulingServiceBase.__periodic_funcs
    • SchedulingServiceBase.__started
    • SchedulingServiceBase._abc_impl
    • SchedulingServiceBase.get_AvailableAlgorithms()
    • SchedulingServiceBase.get_CurrentAlgorithm()
    • SchedulingServiceBase.parent_server
• labscheduler.sila_server.generated.schedulingservice.schedulingservice_client module
  • SchedulingServiceClient
    • SchedulingServiceClient.AvailableAlgorithms
    • SchedulingServiceClient.ComputeSchedule()
    • SchedulingServiceClient.CurrentAlgorithm
    • SchedulingServiceClient.SelectAlgorithm()
• labscheduler.sila_server.generated.schedulingservice.schedulingservice_errors module
  • ComputationError
    • ComputationError._abc_impl
    • ComputationError.fully_qualified_identifier
    • ComputationError.identifier
    • ComputationError.message
  • MissingAlgorithmError
    • MissingAlgorithmError._abc_impl
    • MissingAlgorithmError.fully_qualified_identifier
    • MissingAlgorithmError.identifier
    • MissingAlgorithmError.message
• labscheduler.sila_server.generated.schedulingservice.schedulingservice_feature module
• labscheduler.sila_server.generated.schedulingservice.schedulingservice_types module
  • ComputeSchedule_Responses
    • ComputeSchedule_Responses.Result
    • ComputeSchedule_Responses._asdict()
    • ComputeSchedule_Responses._field_defaults
    • ComputeSchedule_Responses._fields
    • ComputeSchedule_Responses._make()
    • ComputeSchedule_Responses._replace()
  • SelectAlgorithm_Responses
    • SelectAlgorithm_Responses._asdict()
    • SelectAlgorithm_Responses._field_defaults
    • SelectAlgorithm_Responses._fields
    • SelectAlgorithm_Responses._make()
    • SelectAlgorithm_Responses._replace()

Module contents

labscheduler.sila_server.generated.schedulingservice.AlgorithmMetaData

alias of Any

exception labscheduler.sila_server.generated.schedulingservice.ComputationError(message: str | None = None)

Bases: DefinedExecutionError

_abc_impl = <_abc._abc_data object>

class labscheduler.sila_server.generated.schedulingservice.ComputeSchedule_Responses(Result)

Bases: NamedTuple

Result: Any

Returns the computed schedule together with a string whether the schedule is optimal, feasible or infeasible.

_asdict()

Return a new dict which maps field names to their values.

_field_defaults = {}

_fields = ('Result',)

classmethod _make(iterable)

Make a new ComputeSchedule_Responses object from a sequence or iterable

_replace(**kwds)

Return a new ComputeSchedule_Responses object replacing specified fields with new values

labscheduler.sila_server.generated.schedulingservice.Edge

alias of Any

exception labscheduler.sila_server.generated.schedulingservice.MissingAlgorithmError(message: str | None = None)

Bases: DefinedExecutionError

_abc_impl = <_abc._abc_data object>

labscheduler.sila_server.generated.schedulingservice.Node

alias of Any

labscheduler.sila_server.generated.schedulingservice.RequiredResource

alias of Any

class labscheduler.sila_server.generated.schedulingservice.SchedulingServiceBase(parent_server: Server)

Bases: FeatureImplementationBase, ABC

abstractmethod ComputeSchedule(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.

Parameters:

• WorkflowGraph – The workflow graph of an experiment in the required SiLA structure.

• MaxComputationTime – Maximum computation time in seconds

• metadata – The SiLA Client Metadata attached to the call

• instance – The command instance, enabling sending status updates to subscribed clients

Returns:

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

ComputeSchedule_default_lifetime_of_execution: timedelta | None

abstractmethod SelectAlgorithm(AlgorithmName: str, *, metadata: MetadataDict) → SelectAlgorithm_Responses

Selects the algorithm to be used in the ComputeSchedule command

Parameters:

• AlgorithmName – Name of the Algorithm

• metadata – The SiLA Client Metadata attached to the call

_abc_impl = <_abc._abc_data object>

abstractmethod get_AvailableAlgorithms(*, metadata: MetadataDict) → list[AlgorithmMetaData]

List of algorithm info for all available algorithms

Parameters:

metadata – The SiLA Client Metadata attached to the call

Returns:

List of algorithm info for all available algorithms

abstractmethod get_CurrentAlgorithm(*, metadata: MetadataDict) → AlgorithmMetaData

The currently selected algorithm

Parameters:

metadata – The SiLA Client Metadata attached to the call

Returns:

The currently selected algorithm

parent_server: Server

SiLA Server serving this feature implementation

class labscheduler.sila_server.generated.schedulingservice.SchedulingServiceClient

Bases: object

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.

AvailableAlgorithms: ClientUnobservableProperty[list[AlgorithmMetaData]]

List of algorithm info for all available algorithms

ComputeSchedule(WorkflowGraph: WorkflowGraph, MaxComputationTime: float, *, metadata: Iterable[ClientMetadataInstance] | None = None) → ClientObservableCommandInstance[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.

CurrentAlgorithm: ClientUnobservableProperty[AlgorithmMetaData]

The currently selected algorithm

SelectAlgorithm(AlgorithmName: str, *, metadata: Iterable[ClientMetadataInstance] | None = None) → SelectAlgorithm_Responses

Selects the algorithm to be used in the ComputeSchedule command

class labscheduler.sila_server.generated.schedulingservice.SelectAlgorithm_Responses

Bases: NamedTuple

_asdict()

Return a new dict which maps field names to their values.

_field_defaults = {}

_fields = ()

classmethod _make(iterable)

Make a new SelectAlgorithm_Responses object from a sequence or iterable

_replace(**kwds)

Return a new SelectAlgorithm_Responses object replacing specified fields with new values

labscheduler.sila_server.generated.schedulingservice.WorkflowGraph

alias of Any