Pipeline

class lsst.pipe.base.Pipeline(description: str)

Bases: object

A Pipeline is a representation of a series of tasks to run, and the configuration for those tasks.

Parameters

descriptionstr

A description of that this pipeline does.

Methods Summary

addConfigFile(label, filename)	Add overrides from a specified file.
addConfigOverride(label, key, value)	Apply single config override.
addConfigPython(label, pythonString)	Add Overrides by running a snippet of python code against a config.
addInstrument(instrument)	Add an instrument to the pipeline, or replace an instrument that is already defined.
addTask(task, label)	Add a new task to the pipeline, or replace a task that is already associated with the supplied label.
fromFile(filename)	Load a pipeline defined in a pipeline yaml file.
fromIR(deserialized_pipeline)	Create a pipeline from an already created PipelineIR object.
fromPipeline(pipeline)	Create a new pipeline by copying an already existing Pipeline.
fromString(pipeline_string)	Create a pipeline from string formatted as a pipeline document.
from_uri(uri)	Load a pipeline defined in a pipeline yaml file at a location specified by a URI.
getInstrument()	Get the instrument from the pipeline.
removeTask(label)	Remove a task from the pipeline.
subsetFromLabels(labelSpecifier)	Subset a pipeline to contain only labels specified in labelSpecifier
toExpandedPipeline()	Returns a generator of TaskDefs which can be used to create quantum graphs.
toFile(filename)
write_to_uri(uri)

Methods Documentation

addConfigFile(label: str, filename: str) → None

Add overrides from a specified file.

Parameters

labelstr

The label used to identify the task associated with config to modify

filenamestr

Path to the override file.

addConfigOverride(label: str, key: str, value: object) → None

Apply single config override.

Parameters

labelstr

Label of the task.

key: `str`

Fully-qualified field name.

valueobject

Value to be given to a field.

addConfigPython(label: str, pythonString: str) → None

Add Overrides by running a snippet of python code against a config.

Parameters

labelstr

The label used to identity the task associated with config to modify.

pythonString: `str`

A string which is valid python code to be executed. This is done with config as the only local accessible value.

addInstrument(instrument: Union[Instrument, str]) → None

Add an instrument to the pipeline, or replace an instrument that is already defined.

Parameters

instrumentInstrument or str

Either a derived class object of a lsst.daf.butler.instrument or a string corresponding to a fully qualified lsst.daf.butler.instrument name.

addTask(task: Union[lsst.pipe.base.PipelineTask, str], label: str) → None

Add a new task to the pipeline, or replace a task that is already associated with the supplied label.

Parameters

task: `PipelineTask` or `str`

Either a derived class object of a PipelineTask or a string corresponding to a fully qualified PipelineTask name.

label: `str`

A label that is used to identify the PipelineTask being added

classmethod fromFile(filename: str) → lsst.pipe.base.Pipeline

Load a pipeline defined in a pipeline yaml file.

Parameters

filename: `str`

A path that points to a pipeline defined in yaml format. This filename may also supply additional labels to be used in subsetting the loaded Pipeline. These labels are separated from the path by a #, and may be specified as a comma separated list, or a range denoted as beginning..end. Beginning or end may be empty, in which case the range will be a half open interval. Unlike python iteration bounds, end bounds are INCLUDED. Note that range based selection is not well defined for pipelines that are not linear in nature, and correct behavior is not guaranteed, or may vary from run to run.

Returns

pipeline: Pipeline

The pipeline loaded from specified location with appropriate (if any) subsetting

Notes

This method attempts to prune any contracts that contain labels which are not in the declared subset of labels. This pruning is done using a string based matching due to the nature of contracts and may prune more than it should.

classmethod fromIR(deserialized_pipeline: lsst.pipe.base.pipelineIR.PipelineIR) → lsst.pipe.base.Pipeline

Create a pipeline from an already created PipelineIR object.

Parameters

deserialized_pipeline: `PipelineIR`

An already created pipeline intermediate representation object

Returns

pipeline: Pipeline

classmethod fromPipeline(pipeline: lsst.pipe.base.pipelineIR.PipelineIR) → lsst.pipe.base.Pipeline

Create a new pipeline by copying an already existing Pipeline.

Parameters

pipeline: `Pipeline`

An already created pipeline intermediate representation object

Returns

pipeline: Pipeline

classmethod fromString(pipeline_string: str) → lsst.pipe.base.Pipeline

Create a pipeline from string formatted as a pipeline document.

Parameters

pipeline_stringstr

A string that is formatted according like a pipeline document

Returns

pipeline: Pipeline

classmethod from_uri(uri: Union[str, lsst.daf.butler.ButlerURI]) → lsst.pipe.base.Pipeline

Load a pipeline defined in a pipeline yaml file at a location specified by a URI.

Parameters

uri: `str` or `ButlerURI`

If a string is supplied this should be a URI path that points to a pipeline defined in yaml format. This uri may also supply additional labels to be used in subsetting the loaded Pipeline. These labels are separated from the path by a #, and may be specified as a comma separated list, or a range denoted as beginning..end. Beginning or end may be empty, in which case the range will be a half open interval. Unlike python iteration bounds, end bounds are INCLUDED. Note that range based selection is not well defined for pipelines that are not linear in nature, and correct behavior is not guaranteed, or may vary from run to run. The same specifiers can be used with a ButlerURI object, by being the sole contents in the fragments attribute.

Returns

pipeline: Pipeline

The pipeline loaded from specified location with appropriate (if any) subsetting

Notes

This method attempts to prune any contracts that contain labels which are not in the declared subset of labels. This pruning is done using a string based matching due to the nature of contracts and may prune more than it should.

getInstrument() → Instrument

Get the instrument from the pipeline.

Returns

instrumentInstrument, str, or None

A derived class object of a lsst.daf.butler.instrument, a string corresponding to a fully qualified lsst.daf.butler.instrument name, or None if the pipeline does not have an instrument.

removeTask(label: str) → None

Remove a task from the pipeline.

Parameters

labelstr

The label used to identify the task that is to be removed

Raises

KeyError

If no task with that label exists in the pipeline

subsetFromLabels(labelSpecifier: lsst.pipe.base.LabelSpecifier) → lsst.pipe.base.Pipeline

Subset a pipeline to contain only labels specified in labelSpecifier

Parameters

labelSpecifierlabelSpecifier

Object containing labels that describes how to subset a pipeline.

Returns

pipelinePipeline

A new pipeline object that is a subset of the old pipeline

Raises

ValueError

Raised if there is an issue with specified labels

Notes

This method attempts to prune any contracts that contain labels which are not in the declared subset of labels. This pruning is done using a string based matching due to the nature of contracts and may prune more than it should.

toExpandedPipeline() → Generator[lsst.pipe.base.TaskDef, None, None]

Returns a generator of TaskDefs which can be used to create quantum graphs.

Returns

generatorgenerator of TaskDef

The generator returned will be the sorted iterator of tasks which are to be used in constructing a quantum graph.

Raises

NotImplementedError

If a dataId is supplied in a config block. This is in place for future use

toFile(filename: str) → None

write_to_uri(uri: Union[str, lsst.daf.butler.ButlerURI]) → None