b56afe66a2
Instead of creating TaskAction for each task we create single TaskAction in engine, that knows how to run tasks for it. We also got rid of engine dependency of TaskAction, passing storage and notifier to it instead. References blueprint task-executor Co-authored-by: Ivan A. Melnikov <imelnikov@griddynamics.com> Change-Id: Ie52eba3bba5c730cee091ee24e995e0ba21f9486
230 lines
8.3 KiB
Python
230 lines
8.3 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 concurrent import futures
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from taskflow.engines.action_engine import graph_action
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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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from taskflow.utils import threading_utils
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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 = None
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_task_action_cls = task_action.TaskAction
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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._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_action = self._task_action_cls(self.storage,
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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(self)
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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._root.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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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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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(self)
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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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assert self._graph_action_cls is not None, (
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'Graph action class must be specified')
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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._root = self._graph_action_cls(task_graph)
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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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@property
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def is_running(self):
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return self.storage.get_flow_state() == states.RUNNING
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@property
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def is_reverting(self):
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return self.storage.get_flow_state() == states.REVERTING
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class SingleThreadedActionEngine(ActionEngine):
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# NOTE(harlowja): This one attempts to run in a serial manner.
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_graph_action_cls = graph_action.SequentialGraphAction
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_storage_cls = t_storage.Storage
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class MultiThreadedActionEngine(ActionEngine):
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# NOTE(harlowja): This one attempts to run in a parallel manner.
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_graph_action_cls = graph_action.ParallelGraphAction
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_storage_cls = t_storage.ThreadSafeStorage
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def __init__(self, flow, flow_detail, backend, conf):
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super(MultiThreadedActionEngine, self).__init__(
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flow, flow_detail, backend, conf)
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self._executor = conf.get('executor', None)
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@lock_utils.locked
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def run(self):
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if self._executor is None:
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# NOTE(harlowja): since no executor was provided we have to create
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# one, and also ensure that we shutdown the one we create to
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# ensure that we don't leak threads.
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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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owns_executor = True
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else:
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owns_executor = False
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try:
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ActionEngine.run(self)
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finally:
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# Don't forget to shutdown the executor!!
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if owns_executor:
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try:
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self._executor.shutdown(wait=True)
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finally:
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self._executor = None
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@property
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def executor(self):
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"""Returns the current executor, if no executor is provided on
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construction then this executor will change each time the engine
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is ran.
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"""
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return self._executor
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