lsst.pipe.base

The lsst.pipe.base module provides base classes for the task framework. Tasks package the algorithmic units of the LSST Science Pipelines. You can create, configure, and run tasks with their Python APIs. Some tasks, called command-line tasks, are also packaged into data processing pipelines that you can run from the command line.

Contributing

lsst.pipe.base is developed at https://github.com/lsst/pipe_base. You can find Jira issues for this module under the pipe_base component.

Python API reference

lsst.pipe.base Package

Functions

iterConnections(connections, connectionType) Creates an iterator over the selected connections type which yields all the defined connections of that type.
logInfo(obj, prefix[, logLevel]) Log timer information to obj.metadata and obj.log.
timeMethod(func) Decorator to measure duration of a task method.

Classes

ArgumentParser(name[, usage]) Argument parser for command-line tasks that is based on argparse.ArgumentParser.
ButlerInitializedTaskRunner(TaskClass, parsedCmd) A TaskRunner for CmdLineTasks that require a butler keyword argument to be passed to their constructor.
ButlerQuantumContext(butler, quantum) Butler like class specialized for a single quantum
CmdLineTask([config, name, parentTask, log]) Base class for command-line tasks: tasks that may be executed from the command-line.
ConfigDatasetType(name) Dataset type specified by a config parameter.
ConfigFileAction(option_strings, dest[, …]) argparse action to load config overrides from one or more files.
ConfigValueAction(option_strings, dest[, …]) argparse action callback to override config parameters using name=value pairs from the command-line.
DataIdContainer([level]) Container for data IDs and associated data references.
DatasetArgument([name, help, default]) Dataset type specified by a command-line argument.
DeferredDatasetRef Class which denotes that a datasetRef should be treated as deferred when interacting with the butler
GraphBuilder(taskFactory, registry[, …]) GraphBuilder class is responsible for building task execution graph from a Pipeline.
InputOnlyArgumentParser(name[, usage]) ArgumentParser for command-line tasks that don’t write any output.
InputQuantizedConnection(**kwargs)
LegacyTaskRunner(TaskClass, parsedCmd[, …]) A TaskRunner for CmdLineTasks which calls the Task’s run method on a dataRef rather than the runDataRef method.
OutputQuantizedConnection(**kwargs)
Pipeline([iterable]) Pipeline is a sequence of TaskDef objects.
PipelineBuilder(taskFactory[, pipeline]) PipelineBuilder class is responsible for building task pipeline.
PipelineDatasetTypes(initInputs, …) An immutable struct that classifies the dataset types used in a Pipeline.
PipelineTask(*[, config, log, initInputs]) Base class for all pipeline tasks.
PipelineTaskConfig Configuration class for `PipelineTask`s
PipelineTaskConnections alias of lsst.pipe.base.connections.PipelineTaskConnections
QuantumGraph([iterable]) QuantumGraph is a sequence of QuantumGraphTaskNodes objects.
QuantumGraphTaskNodes(taskDef, quanta, …) QuantumGraphTaskNodes represents a bunch of nodes in an quantum graph corresponding to a single task.
QuantumIterData(index, quantum, taskDef, …) Helper class for iterating over quanta in a graph.
ResourceConfig Configuration for resource requirements.
Struct(**keyArgs) A container to which you can add fields as attributes.
Task([config, name, parentTask, log]) Base class for data processing tasks.
TaskDatasetTypes(initInputs, initOutputs, …) An immutable struct that extracts and classifies the dataset types used by a PipelineTask
TaskDef(taskName, config[, taskClass, label]) TaskDef is a collection of information about task needed by Pipeline.
TaskError Use to report errors for which a traceback is not useful.
TaskFactory Abstract base class for task factory.
TaskRunner(TaskClass, parsedCmd[, …]) Run a command-line task, using multiprocessing if requested.

Class Inheritance Diagram