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#!/usr/bin/env python
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# encoding: utf-8
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"""
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A new example showing how to use `TaskRejectError` to handle dependencies
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in the IPython task system.
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To run this example, do::
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$ ipcluster local -n 4
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Then, in another terminal start up IPython and do::
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In [0]: %run taskreject.py
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In [1]: mec.execute('run=True', targets=[0,1])
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After the first command, the scheduler will keep rescheduling the tasks, as
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they will fail with `TaskRejectError`. But after the second command, there
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are two engines that the tasks can run on. The tasks are quickly funneled
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to these engines.
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If you want to see how the controller is scheduling and retrying the tasks
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do a `tail -f` on the controller's log file in ~/.ipython/log.
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"""
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#-----------------------------------------------------------------------------
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# Copyright (C) 2008-2009 The IPython Development Team
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#
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# Distributed under the terms of the BSD License. The full license is in
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# the file COPYING, distributed as part of this software.
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#-----------------------------------------------------------------------------
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from IPython.kernel import client
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from IPython.kernel import TaskRejectError
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mec = client.MultiEngineClient()
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tc = client.TaskClient()
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mec.execute('from IPython.kernel import TaskRejectError')
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mec.execute('run = False')
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def map_task():
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if not run:
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raise TaskRejectError('task dependency not met')
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return 3.0e8
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task_ids = []
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for i in range(10):
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task = client.MapTask(map_task, retries=20)
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task_ids.append(tc.run(task, block=False))
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