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Added diagnostics printout at the end of the test suite....
Added diagnostics printout at the end of the test suite. This will make it easier for us to understand problem reports from users.

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taskclient.py
180 lines | 5.8 KiB | text/x-python | PythonLexer
# encoding: utf-8
# -*- test-case-name: IPython.kernel.tests.test_taskcontrollerxmlrpc -*-
"""
A blocking version of the task client.
"""
__docformat__ = "restructuredtext en"
#-------------------------------------------------------------------------------
# Copyright (C) 2008 The IPython Development Team
#
# Distributed under the terms of the BSD License. The full license is in
# the file COPYING, distributed as part of this software.
#-------------------------------------------------------------------------------
#-------------------------------------------------------------------------------
# Imports
#-------------------------------------------------------------------------------
from zope.interface import Interface, implements
from twisted.python import components, log
from IPython.kernel.twistedutil import blockingCallFromThread
from IPython.kernel import task, error
from IPython.kernel.mapper import (
SynchronousTaskMapper,
ITaskMapperFactory,
IMapper
)
from IPython.kernel.parallelfunction import (
ParallelFunction,
ITaskParallelDecorator
)
#-------------------------------------------------------------------------------
# The task client
#-------------------------------------------------------------------------------
class IBlockingTaskClient(Interface):
"""
A vague interface of the blocking task client
"""
pass
class BlockingTaskClient(object):
"""
A blocking task client that adapts a non-blocking one.
"""
implements(
IBlockingTaskClient,
ITaskMapperFactory,
IMapper,
ITaskParallelDecorator
)
def __init__(self, task_controller):
self.task_controller = task_controller
self.block = True
def run(self, task, block=False):
"""Run a task on the `TaskController`.
See the documentation of the `MapTask` and `StringTask` classes for
details on how to build a task of different types.
:Parameters:
task : an `ITask` implementer
:Returns: The int taskid of the submitted task. Pass this to
`get_task_result` to get the `TaskResult` object.
"""
tid = blockingCallFromThread(self.task_controller.run, task)
if block:
return self.get_task_result(tid, block=True)
else:
return tid
def get_task_result(self, taskid, block=False):
"""
Get a task result by taskid.
:Parameters:
taskid : int
The taskid of the task to be retrieved.
block : boolean
Should I block until the task is done?
:Returns: A `TaskResult` object that encapsulates the task result.
"""
return blockingCallFromThread(self.task_controller.get_task_result,
taskid, block)
def abort(self, taskid):
"""
Abort a task by taskid.
:Parameters:
taskid : int
The taskid of the task to be aborted.
"""
return blockingCallFromThread(self.task_controller.abort, taskid)
def barrier(self, taskids):
"""Block until a set of tasks are completed.
:Parameters:
taskids : list, tuple
A sequence of taskids to block on.
"""
return blockingCallFromThread(self.task_controller.barrier, taskids)
def spin(self):
"""
Touch the scheduler, to resume scheduling without submitting a task.
This method only needs to be called in unusual situations where the
scheduler is idle for some reason.
"""
return blockingCallFromThread(self.task_controller.spin)
def queue_status(self, verbose=False):
"""
Get a dictionary with the current state of the task queue.
:Parameters:
verbose : boolean
If True, return a list of taskids. If False, simply give
the number of tasks with each status.
:Returns:
A dict with the queue status.
"""
return blockingCallFromThread(self.task_controller.queue_status, verbose)
def clear(self):
"""
Clear all previously run tasks from the task controller.
This is needed because the task controller keep all task results
in memory. This can be a problem is there are many completed
tasks. Users should call this periodically to clean out these
cached task results.
"""
return blockingCallFromThread(self.task_controller.clear)
def map(self, func, *sequences):
"""
Apply func to *sequences elementwise. Like Python's builtin map.
This version is load balanced.
"""
return self.mapper().map(func, *sequences)
def mapper(self, clear_before=False, clear_after=False, retries=0,
recovery_task=None, depend=None, block=True):
"""
Create an `IMapper` implementer with a given set of arguments.
The `IMapper` created using a task controller is load balanced.
See the documentation for `IPython.kernel.task.BaseTask` for
documentation on the arguments to this method.
"""
return SynchronousTaskMapper(self, clear_before=clear_before,
clear_after=clear_after, retries=retries,
recovery_task=recovery_task, depend=depend, block=block)
def parallel(self, clear_before=False, clear_after=False, retries=0,
recovery_task=None, depend=None, block=True):
mapper = self.mapper(clear_before, clear_after, retries,
recovery_task, depend, block)
pf = ParallelFunction(mapper)
return pf
components.registerAdapter(BlockingTaskClient,
task.ITaskController, IBlockingTaskClient)