Files
deb-python-taskflow/taskflow/engines/action_engine/engine.py
Joshua Harlow d736bdbfae Add a flow flattening util
Instead of recursively executing subflows which causes
dead locks when they parent and subflows share the same
executor we can instead flatten the parent and subflows
into a single graph, composed with only tasks and run
this instead, which will not have the issue of subflows
dead locking, since after flattening there is no concept
of a subflow.

Fixes bug: 1225759

Change-Id: I79b9b194cd81e36ce75ba34a673e3e9d3e96c4cd
2013-09-20 12:41:57 +04:00

173 lines
6.1 KiB
Python

# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
# Copyright (C) 2012 Yahoo! Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
import multiprocessing
import threading
from concurrent import futures
from taskflow.engines.action_engine import graph_action
from taskflow.engines.action_engine import task_action
from taskflow.persistence import utils as p_utils
from taskflow import decorators
from taskflow import exceptions as exc
from taskflow import states
from taskflow import storage as t_storage
from taskflow.utils import flow_utils
from taskflow.utils import misc
class ActionEngine(object):
"""Generic action-based engine.
Converts the flow to recursive structure of actions.
"""
def __init__(self, flow, storage):
self._failures = []
self._root = None
self._flow = flow
self._lock = threading.RLock()
self.notifier = misc.TransitionNotifier()
self.task_notifier = misc.TransitionNotifier()
self.storage = storage
def _revert(self, current_failure):
self._change_state(states.REVERTING)
self._root.revert(self)
self._change_state(states.REVERTED)
self._change_state(states.FAILURE)
if self._failures:
if len(self._failures) == 1:
self._failures[0].reraise()
else:
exc_infos = [f.exc_info for f in self._failures]
raise exc.LinkedException.link(exc_infos)
else:
current_failure.reraise()
def _reset(self):
self._failures = []
@decorators.locked
def run(self):
self.compile()
self._reset()
external_provides = set(self.storage.fetch_all().keys())
missing = self._flow.requires - external_provides
if missing:
raise exc.MissingDependencies(self._flow, sorted(missing))
self._change_state(states.RUNNING)
try:
self._root.execute(self)
except Exception:
self._revert(misc.Failure())
else:
self._change_state(states.SUCCESS)
def _change_state(self, state):
self.storage.set_flow_state(state)
details = dict(engine=self)
self.notifier.notify(state, details)
def on_task_state_change(self, task_action, state, result=None):
if isinstance(result, misc.Failure):
self._failures.append(result)
details = dict(engine=self,
task_name=task_action.name,
task_uuid=task_action.uuid,
result=result)
self.task_notifier.notify(state, details)
def _translate_flow_to_action(self):
# Flatten the flow into just 1 graph.
task_graph = flow_utils.flatten(self._flow)
ga = graph_action.SequentialGraphAction(task_graph)
for n in task_graph.nodes_iter():
ga.add(n, task_action.TaskAction(n, self))
return ga
@decorators.locked
def compile(self):
if self._root is None:
self._root = self._translate_flow_to_action()
class SingleThreadedActionEngine(ActionEngine):
def __init__(self, flow, flow_detail=None, book=None, backend=None):
if flow_detail is None:
flow_detail = p_utils.create_flow_detail(flow,
book=book,
backend=backend)
ActionEngine.__init__(self, flow,
storage=t_storage.Storage(flow_detail, backend))
class MultiThreadedActionEngine(ActionEngine):
def __init__(self, flow, flow_detail=None, book=None, backend=None,
executor=None):
if flow_detail is None:
flow_detail = p_utils.create_flow_detail(flow,
book=book,
backend=backend)
ActionEngine.__init__(self, flow,
storage=t_storage.ThreadSafeStorage(flow_detail,
backend))
if executor is not None:
self._executor = executor
self._owns_executor = False
self._thread_count = -1
else:
self._executor = None
self._owns_executor = True
# TODO(harlowja): allow this to be configurable??
try:
self._thread_count = multiprocessing.cpu_count() + 1
except NotImplementedError:
# NOTE(harlowja): apparently may raise so in this case we will
# just setup two threads since its hard to know what else we
# should do in this situation.
self._thread_count = 2
@decorators.locked
def run(self):
if self._owns_executor:
if self._executor is not None:
# The previous shutdown failed, something is very wrong.
raise exc.InvalidStateException("The previous shutdown() of"
" the executor powering this"
" engine failed. Something is"
" very very wrong.")
self._executor = futures.ThreadPoolExecutor(self._thread_count)
try:
ActionEngine.run(self)
finally:
# Don't forget to shutdown the executor!!
if self._owns_executor and self._executor is not None:
self._executor.shutdown(wait=True)
self._executor = None
@property
def executor(self):
return self._executor