# Quantum¶

class lsst.daf.butler.Quantum(*, taskName: Optional[str] = None, taskClass: Optional[Type[CT_co]] = None, dataId: Optional[lsst.daf.butler.core.dimensions._coordinate.DataCoordinate] = None, initInputs: Union[Mapping[lsst.daf.butler.core.datasets.type.DatasetType, lsst.daf.butler.core.datasets.ref.DatasetRef], Iterable[lsst.daf.butler.core.datasets.ref.DatasetRef], None] = None, inputs: Optional[Mapping[lsst.daf.butler.core.datasets.type.DatasetType, List[lsst.daf.butler.core.datasets.ref.DatasetRef]]] = None, outputs: Optional[Mapping[lsst.daf.butler.core.datasets.type.DatasetType, List[lsst.daf.butler.core.datasets.ref.DatasetRef]]] = None)

Bases: object

Class representing a discrete unit of work.

A Quantum may depend on one or more datasets and produce one or more datasets.

Most Quanta will be executions of a particular PipelineTask’s runQuantum method, but they can also be used to represent discrete units of work performed manually by human operators or other software agents.

Parameters: taskName : str, optional Fully-qualified name of the Task class that executed or will execute this Quantum. If not provided, taskClass must be. taskClass : type, optional The Task class that executed or will execute this Quantum. If not provided, taskName must be. Overrides taskName if both are provided. dataId : DataId, optional The dimension values that identify this Quantum. initInputs : collection of DatasetRef, optional Datasets that are needed to construct an instance of the Task. May be a flat iterable of DatasetRef instances or a mapping from DatasetType to DatasetRef. inputs : Mapping, optional Inputs identified prior to execution, organized as a mapping from DatasetType to a list of DatasetRef. outputs : Mapping, optional Outputs from executing this quantum of work, organized as a mapping from DatasetType to a list of DatasetRef.

Attributes Summary

 dataId Return dimension values of the unit of processing (DataId). initInputs Return mapping of datasets used to construct the Task. inputs Return mapping of input datasets that were expected to be used. outputs Return mapping of output datasets (to be) generated by this quantum. taskClass Task class associated with this Quantum (type). taskName Return Fully-qualified name of the task associated with Quantum.

Attributes Documentation

dataId

Return dimension values of the unit of processing (DataId).

initInputs

Return mapping of datasets used to construct the Task.

Has DatasetType instances as keys (names can also be used for lookups) and DatasetRef instances as values.

inputs

Return mapping of input datasets that were expected to be used.

Has DatasetType instances as keys (names can also be used for lookups) and a list of DatasetRef instances as values.

Notes

We cannot use set instead of list for the nested container because DatasetRef instances cannot be compared reliably when some have integers IDs and others do not.

outputs

Return mapping of output datasets (to be) generated by this quantum.

Has the same form as predictedInputs.

Notes

We cannot use set instead of list for the nested container because DatasetRef instances cannot be compared reliably when some have integers IDs and others do not.

taskClass

Task class associated with this Quantum (type).

taskName

Return Fully-qualified name of the task associated with Quantum.