24172082a9
This change introduces new entity in the ActionEngine internals, TaskExecutor. It's responsibilities are simple: take task and it's arguments and execute it or revert it when engine says so. Implements blueprint task-executor Change-Id: I81c63bf4f43342a630f5aa9872fb14776e481176
155 lines
4.7 KiB
Python
155 lines
4.7 KiB
Python
# -*- coding: utf-8 -*-
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# vim: tabstop=4 shiftwidth=4 softtabstop=4
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# Copyright (C) 2013 Yahoo! Inc. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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import abc
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import contextlib
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import six
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from concurrent import futures
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from taskflow.utils import misc
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from taskflow.utils import threading_utils
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@contextlib.contextmanager
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def _autobind(task, bind_name, bind_func, **kwargs):
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try:
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task.bind(bind_name, bind_func, **kwargs)
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yield task
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finally:
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task.unbind(bind_name, bind_func)
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def _noop(*args, **kwargs):
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pass
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def _execute_task(task, arguments, progress_callback):
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with _autobind(task, 'update_progress', progress_callback):
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try:
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result = task.execute(**arguments)
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except Exception:
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# NOTE(imelnikov): wrap current exception with Failure
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# object and return it
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result = misc.Failure()
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return task, 'executed', result
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def _revert_task(task, arguments, result, failures, progress_callback):
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kwargs = arguments.copy()
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kwargs['result'] = result
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kwargs['flow_failures'] = failures
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with _autobind(task, 'update_progress', progress_callback):
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try:
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result = task.revert(**kwargs)
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except Exception:
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# NOTE(imelnikov): wrap current exception with Failure
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# object and return it
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result = misc.Failure()
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return task, 'reverted', result
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@six.add_metaclass(abc.ABCMeta)
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class TaskExecutorBase(object):
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"""Executes and reverts tasks.
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This class takes task and its arguments and executes or reverts it.
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It encapsulates knowledge on how task should be executed or reverted:
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right now, on separate thread, on another machine, etc.
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"""
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@abc.abstractmethod
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def execute_task(self, task, arguments, progress_callback=_noop):
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"""Schedules task execution."""
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@abc.abstractmethod
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def revert_task(self, task, arguments, result, failures,
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progress_callback=_noop):
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"""Schedules task reversion"""
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@abc.abstractmethod
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def wait_for_any(self, fs):
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"""Wait for futures returned by this executor to complete"""
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def start(self):
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"""Prepare to execute tasks"""
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pass
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def stop(self):
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"""Finalize task executor"""
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pass
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class SerialTaskExecutor(TaskExecutorBase):
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"""Execute task one after another."""
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@staticmethod
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def _completed_future(result):
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future = futures.Future()
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future.set_result(result)
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return future
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def execute_task(self, task, arguments, progress_callback=_noop):
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return self._completed_future(
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_execute_task(task, arguments, progress_callback))
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def revert_task(self, task, arguments, result, failures,
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progress_callback=_noop):
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return self._completed_future(
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_revert_task(task, arguments, result,
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failures, progress_callback))
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def wait_for_any(self, fs):
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# NOTE(imelnikov): this executor returns only done futures
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return fs, []
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class ParallelTaskExecutor(TaskExecutorBase):
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"""Executes tasks in parallel.
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Submits tasks to executor which should provide interface similar
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to concurrent.Futures.Executor.
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"""
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def __init__(self, executor=None):
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self._executor = executor
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self._own_executor = executor is None
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def execute_task(self, task, arguments, progress_callback=_noop):
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return self._executor.submit(
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_execute_task, task, arguments, progress_callback)
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def revert_task(self, task, arguments, result, failures,
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progress_callback=_noop):
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return self._executor.submit(
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_revert_task, task,
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arguments, result, failures, progress_callback)
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def wait_for_any(self, fs):
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return futures.wait(fs, return_when=futures.FIRST_COMPLETED)
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def start(self):
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if self._own_executor:
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thread_count = threading_utils.get_optimal_thread_count()
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self._executor = futures.ThreadPoolExecutor(thread_count)
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def stop(self):
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if self._own_executor:
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self._executor.shutdown(wait=True)
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self._executor = None
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