f1058af707
Task action is an internal to the action engine init and runtime and shouldn't become part of the public api of the action engine type. Change-Id: I68a10a83718f70cc037e7aaa9259c7bfdc9b93a4
204 lines
7.7 KiB
Python
204 lines
7.7 KiB
Python
# -*- coding: utf-8 -*-
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# vim: tabstop=4 shiftwidth=4 softtabstop=4
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# Copyright (C) 2012 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 threading
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from taskflow.engines.action_engine import executor
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from taskflow.engines.action_engine import graph_action
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from taskflow.engines.action_engine import graph_analyzer
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from taskflow.engines.action_engine import task_action
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from taskflow.engines import base
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from taskflow import exceptions as exc
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from taskflow.openstack.common import excutils
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from taskflow import states
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from taskflow import storage as t_storage
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from taskflow.utils import flow_utils
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from taskflow.utils import lock_utils
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from taskflow.utils import misc
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from taskflow.utils import reflection
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class ActionEngine(base.EngineBase):
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"""Generic action-based engine.
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This engine flattens the flow (and any subflows) into a execution graph
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which contains the full runtime definition to be executed and then uses
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this graph in combination with the action classes & storage to attempt to
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run your flow (and any subflows & contained tasks) to completion.
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During this process it is permissible and valid to have a task or multiple
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tasks in the execution graph fail, which will cause the process of
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reversion to commence. See the valid states in the states module to learn
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more about what other states the tasks & flow being ran can go through.
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"""
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_graph_action_cls = graph_action.FutureGraphAction
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_graph_analyzer_cls = graph_analyzer.GraphAnalyzer
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_task_action_cls = task_action.TaskAction
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_task_executor_cls = executor.SerialTaskExecutor
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def __init__(self, flow, flow_detail, backend, conf):
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super(ActionEngine, self).__init__(flow, flow_detail, backend, conf)
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self._analyzer = None
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self._root = None
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self._lock = threading.RLock()
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self._state_lock = threading.RLock()
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self.notifier = misc.TransitionNotifier()
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self.task_notifier = misc.TransitionNotifier()
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self._task_executor = self._task_executor_cls()
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self._task_action = self._task_action_cls(self.storage,
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self._task_executor,
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self.task_notifier)
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def _revert(self, current_failure=None):
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self._change_state(states.REVERTING)
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try:
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state = self._root.revert()
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except Exception:
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with excutils.save_and_reraise_exception():
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self._change_state(states.FAILURE)
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self._change_state(state)
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if state == states.SUSPENDED:
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return
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failures = self.storage.get_failures()
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misc.Failure.reraise_if_any(failures.values())
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if current_failure:
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current_failure.reraise()
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def __str__(self):
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return "%s: %s" % (reflection.get_class_name(self), id(self))
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def suspend(self):
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"""Attempts to suspend the engine.
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If the engine is currently running tasks then this will attempt to
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suspend future work from being started (currently active tasks can
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not currently be preempted) and move the engine into a suspend state
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which can then later be resumed from.
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"""
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self._change_state(states.SUSPENDING)
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@property
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def execution_graph(self):
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self.compile()
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return self._analyzer.execution_graph
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@lock_utils.locked
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def run(self):
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"""Runs the flow in the engine to completion."""
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if self.storage.get_flow_state() == states.REVERTED:
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self._reset()
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self.compile()
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external_provides = set(self.storage.fetch_all().keys())
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missing = self._flow.requires - external_provides
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if missing:
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raise exc.MissingDependencies(self._flow, sorted(missing))
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self._task_executor.start()
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try:
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if self.storage.has_failures():
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self._revert()
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else:
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self._run()
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finally:
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self._task_executor.stop()
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def _run(self):
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self._change_state(states.RUNNING)
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try:
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state = self._root.execute()
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except Exception:
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self._change_state(states.FAILURE)
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self._revert(misc.Failure())
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else:
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self._change_state(state)
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@lock_utils.locked(lock='_state_lock')
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def _change_state(self, state):
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old_state = self.storage.get_flow_state()
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if not states.check_flow_transition(old_state, state):
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return
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self.storage.set_flow_state(state)
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try:
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flow_uuid = self._flow.uuid
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except AttributeError:
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# NOTE(harlowja): if the flow was just a single task, then it will
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# not itself have a uuid, but the constructed flow_detail will.
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if self._flow_detail is not None:
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flow_uuid = self._flow_detail.uuid
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else:
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flow_uuid = None
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details = dict(engine=self,
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flow_name=self._flow.name,
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flow_uuid=flow_uuid,
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old_state=old_state)
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self.notifier.notify(state, details)
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def _reset(self):
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for name, uuid in self.storage.reset_tasks():
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details = dict(engine=self,
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task_name=name,
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task_uuid=uuid,
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result=None)
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self.task_notifier.notify(states.PENDING, details)
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self._change_state(states.PENDING)
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@lock_utils.locked
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def compile(self):
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"""Compiles the contained flow into a structure which the engine can
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use to run or if this can not be done then an exception is thrown
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indicating why this compilation could not be achieved.
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"""
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if self._root is not None:
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return
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self._change_state(states.RESUMING) # does nothing in PENDING state
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task_graph = flow_utils.flatten(self._flow)
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if task_graph.number_of_nodes() == 0:
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raise exc.EmptyFlow("Flow %s is empty." % self._flow.name)
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self._analyzer = self._graph_analyzer_cls(task_graph,
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self.storage)
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self._root = self._graph_action_cls(self._analyzer,
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self.storage,
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self._task_action)
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for task in task_graph.nodes_iter():
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task_version = misc.get_version_string(task)
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self.storage.ensure_task(task.name, task_version, task.save_as)
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self._change_state(states.SUSPENDED) # does nothing in PENDING state
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class SingleThreadedActionEngine(ActionEngine):
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"""Engine that runs tasks in serial manner"""
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_storage_cls = t_storage.Storage
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class MultiThreadedActionEngine(ActionEngine):
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"""Engine that runs tasks in parallel manner"""
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_storage_cls = t_storage.ThreadSafeStorage
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def _task_executor_cls(self):
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return executor.ParallelTaskExecutor(self._executor)
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def __init__(self, flow, flow_detail, backend, conf):
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self._executor = conf.get('executor', None)
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super(MultiThreadedActionEngine, self).__init__(
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flow, flow_detail, backend, conf)
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