Output

class lsst.pipe.base.connectionTypes.Output(name: str, storageClass: str, doc: str = '', multiple: bool = False, _deprecation_context: str = '', dimensions: Iterable[str] = (), isCalibration: bool = False, *, deprecated: str | None = None)

Bases: DimensionedConnection

Connection for output dataset.

Attributes Summary

deprecated	A description of why this connection is deprecated, including the version after which it may be removed.
dimensions	The keys of the butler data coordinates for this dataset type.
doc	Documentation for this connection.
isCalibration	True if this dataset type may be included in CALIBRATION collections to associate it with a validity range, False (default) otherwise.
multiple	Indicates if this connection should expect to contain multiple objects of the given dataset type.

Attributes Documentation

deprecated: str | None = None

A description of why this connection is deprecated, including the version after which it may be removed.

If not None, the string is appended to the docstring for this connection and the corresponding config Field.

dimensions: Iterable[str] = ()

The keys of the butler data coordinates for this dataset type.

doc: str = ''

Documentation for this connection.

isCalibration: bool = False

True if this dataset type may be included in CALIBRATION collections to associate it with a validity range, False (default) otherwise.

multiple: bool = False

Indicates if this connection should expect to contain multiple objects of the given dataset type.

Tasks with more than one connection with multiple=True with the same dimensions may want to implement PipelineTaskConnections.adjustQuantum to ensure those datasets are consistent (i.e. zip-iterable) in PipelineTask.runQuantum() and notify the execution system as early as possible of outputs that will not be produced because the corresponding input is missing.