LegacyTaskRunner¶
- class lsst.pipe.base.LegacyTaskRunner(TaskClass, parsedCmd, doReturnResults=False)¶
Bases:
TaskRunner
A
TaskRunner
forCmdLineTask
s which calls theTask
‘srun
method on adataRef
rather than therunDataRef
method.Attributes Summary
Default timeout (seconds) for multiprocessing.
Methods Summary
__call__
(args)Run the Task on a single target.
getTargetList
(parsedCmd, **kwargs)Get a list of (dataRef, kwargs) for
TaskRunner.__call__
.makeTask
([parsedCmd, args])Create a Task instance.
precall
(parsedCmd)Hook for code that should run exactly once, before multiprocessing.
Prepare this instance for multiprocessing
run
(parsedCmd)Run the task on all targets.
runTask
(task, dataRef, kwargs)Call
run
for this task instead ofrunDataRef
.Attributes Documentation
- TIMEOUT = 2592000¶
Default timeout (seconds) for multiprocessing.
Methods Documentation
- __call__(args)¶
Run the Task on a single target.
- Parameters:
- args
Arguments for Task.runDataRef()
- Returns:
- struct
lsst.pipe.base.Struct
Contains these fields if
doReturnResults
isTrue
:dataRef
: the provided data reference.metadata
: task metadata after execution of run.result
: result returned by task run, orNone
if the task fails.exitStatus
: 0 if the task completed successfully, 1 otherwise.
If
doReturnResults
isFalse
the struct contains:exitStatus
: 0 if the task completed successfully, 1 otherwise.
- struct
Notes
This default implementation assumes that the
args
is a tuple containing a data reference and a dict of keyword arguments.Warning
If you override this method and wish to return something when
doReturnResults
isFalse
, then it must be picklable to support multiprocessing and it should be small enough that pickling and unpickling do not add excessive overhead.
- static getTargetList(parsedCmd, **kwargs)¶
Get a list of (dataRef, kwargs) for
TaskRunner.__call__
.- Parameters:
- parsedCmd
argparse.Namespace
The parsed command object returned by
lsst.pipe.base.ArgumentParser.parse_args
.- kwargs
Any additional keyword arguments. In the default
TaskRunner
this is an empty dict, but having it simplifies overridingTaskRunner
for tasks whose runDataRef method takes additional arguments (see case (1) below).
- parsedCmd
Notes
The default implementation of
TaskRunner.getTargetList
andTaskRunner.__call__
works for any command-line task whoserunDataRef
method takes exactly one argument: a data reference. Otherwise you must provide a variant of TaskRunner that overridesTaskRunner.getTargetList
and possiblyTaskRunner.__call__
. There are two cases.Case 1
If your command-line task has a
runDataRef
method that takes one data reference followed by additional arguments, then you need only overrideTaskRunner.getTargetList
to return the additional arguments as an argument dict. To make this easier, your overridden version ofgetTargetList
may callTaskRunner.getTargetList
with the extra arguments as keyword arguments. For example, the following adds an argument dict containing a single key: “calExpList”, whose value is the list of data IDs for the calexp ID argument:def getTargetList(parsedCmd): return TaskRunner.getTargetList( parsedCmd, calExpList=parsedCmd.calexp.idList )
It is equivalent to this slightly longer version:
@staticmethod def getTargetList(parsedCmd): argDict = dict(calExpList=parsedCmd.calexp.idList) return [(dataId, argDict) for dataId in parsedCmd.id.idList]
Case 2
If your task does not meet condition (1) then you must override both TaskRunner.getTargetList and
TaskRunner.__call__
. You may do this however you see fit, so long asTaskRunner.getTargetList
returns a list, each of whose elements is sent toTaskRunner.__call__
, which runs your task.
- makeTask(parsedCmd=None, args=None)¶
Create a Task instance.
- Parameters:
- parsedCmd
Parsed command-line options (used for extra task args by some task runners).
- args
Args tuple passed to
TaskRunner.__call__
(used for extra task arguments by some task runners).
Notes
makeTask
can be called with either theparsedCmd
argument orargs
argument set to None, but it must construct identical Task instances in either case.Subclasses may ignore this method entirely if they reimplement both
TaskRunner.precall
andTaskRunner.__call__
.
- precall(parsedCmd)¶
Hook for code that should run exactly once, before multiprocessing.
Notes
Must return True if
TaskRunner.__call__
should subsequently be called.Warning
Implementations must take care to ensure that no unpicklable attributes are added to the TaskRunner itself, for compatibility with multiprocessing.
The default implementation writes package versions, schemas and configs, or compares them to existing files on disk if present.
- prepareForMultiProcessing()¶
Prepare this instance for multiprocessing
Optional non-picklable elements are removed.
This is only called if the task is run under multiprocessing.
- run(parsedCmd)¶
Run the task on all targets.
- Parameters:
- parsedCmd
argparse.Namespace
Parsed command
argparse.Namespace
.
- parsedCmd
- Returns:
- resultList
list
A list of results returned by
TaskRunner.__call__
, or an empty list ifTaskRunner.__call__
is not called (e.g. ifTaskRunner.precall
returnsFalse
). SeeTaskRunner.__call__
for details.
- resultList
Notes
The task is run under multiprocessing if
TaskRunner.numProcesses
is more than 1; otherwise processing is serial.
- runTask(task, dataRef, kwargs)¶
Call
run
for this task instead ofrunDataRef
. SeeTaskRunner.runTask
above for details.