# -*- coding: utf-8 -*- # 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 threading from taskflow.engines.action_engine import executor from taskflow.engines.action_engine import graph_action from taskflow.engines.action_engine import graph_analyzer from taskflow.engines.action_engine import retry_action from taskflow.engines.action_engine import task_action from taskflow.engines import base from taskflow import exceptions as exc from taskflow.openstack.common import excutils from taskflow import retry from taskflow import states from taskflow import storage as t_storage from taskflow.utils import flow_utils from taskflow.utils import lock_utils from taskflow.utils import misc from taskflow.utils import reflection class ActionEngine(base.EngineBase): """Generic action-based engine. This engine flattens the flow (and any subflows) into a execution graph which contains the full runtime definition to be executed and then uses this graph in combination with the action classes & storage to attempt to run your flow (and any subflows & contained tasks) to completion. During this process it is permissible and valid to have a task or multiple tasks in the execution graph fail, which will cause the process of reversion to commence. See the valid states in the states module to learn more about what other states the tasks & flow being ran can go through. """ _graph_action_factory = graph_action.FutureGraphAction _graph_analyzer_factory = graph_analyzer.GraphAnalyzer _task_action_factory = task_action.TaskAction _task_executor_factory = executor.SerialTaskExecutor _retry_action_factory = retry_action.RetryAction def __init__(self, flow, flow_detail, backend, conf): super(ActionEngine, self).__init__(flow, flow_detail, backend, conf) self._analyzer = None self._root = None self._compiled = False self._lock = threading.RLock() self._state_lock = threading.RLock() self._task_executor = None self._task_action = None self._retry_action = None self._storage_ensured = False def __str__(self): return "%s: %s" % (reflection.get_class_name(self), id(self)) def suspend(self): if not self._compiled: raise exc.InvalidState("Can not suspend an engine" " which has not been compiled") self._change_state(states.SUSPENDING) @property def execution_graph(self): """The graph of nodes to be executed. NOTE(harlowja): Only accessible after compilation has completed. """ g = None if self._compiled and self._analyzer: g = self._analyzer.execution_graph return g @lock_utils.locked def run(self): """Runs the flow in the engine to completion.""" self.compile() self.prepare() self._task_executor.start() try: self._run() finally: self._task_executor.stop() def _run(self): self._change_state(states.RUNNING) try: state = self._root.execute() except Exception: with excutils.save_and_reraise_exception(): self._change_state(states.FAILURE) else: self._change_state(state) if state != states.SUSPENDED and state != states.SUCCESS: failures = self.storage.get_failures() misc.Failure.reraise_if_any(failures.values()) def _change_state(self, state): with self._state_lock: old_state = self.storage.get_flow_state() if not states.check_flow_transition(old_state, state): return self.storage.set_flow_state(state) try: flow_uuid = self._flow.uuid except AttributeError: # NOTE(harlowja): if the flow was just a single task, then it # will not itself have a uuid, but the constructed flow_detail # will. if self._flow_detail is not None: flow_uuid = self._flow_detail.uuid else: flow_uuid = None details = dict(engine=self, flow_name=self._flow.name, flow_uuid=flow_uuid, old_state=old_state) self.notifier.notify(state, details) def _ensure_storage_for(self, execution_graph): # NOTE(harlowja): signal to the tasks that exist that we are about to # resume, if they have a previous state, they will now transition to # a resuming state (and then to suspended). self._change_state(states.RESUMING) # does nothing in PENDING state for node in execution_graph.nodes_iter(): version = misc.get_version_string(node) if isinstance(node, retry.Retry): self.storage.ensure_retry(node.name, version, node.save_as) else: self.storage.ensure_task(node.name, version, node.save_as) self._change_state(states.SUSPENDED) # does nothing in PENDING state @lock_utils.locked def prepare(self): if not self._compiled: raise exc.InvalidState("Can not prepare an engine" " which has not been compiled") if not self._storage_ensured: self._ensure_storage_for(self.execution_graph) self._storage_ensured = True # At this point we can check to ensure all dependencies are either # flow/task provided or storage provided, if there are still missing # dependencies then this flow will fail at runtime (which we can avoid # by failing at preparation time). external_provides = set(self.storage.fetch_all().keys()) missing = self._flow.requires - external_provides if missing: raise exc.MissingDependencies(self._flow, sorted(missing)) # Reset everything back to pending (if we were previously reverted). if self.storage.get_flow_state() == states.REVERTED: self._root.reset_all() self._change_state(states.PENDING) @lock_utils.locked def compile(self): if self._compiled: return execution_graph = flow_utils.flatten(self._flow) if execution_graph.number_of_nodes() == 0: raise exc.Empty("Flow %s is empty." % self._flow.name) self._analyzer = self._graph_analyzer_factory(execution_graph, self.storage) if self._task_executor is None: self._task_executor = self._task_executor_factory() if self._task_action is None: self._task_action = self._task_action_factory(self.storage, self._task_executor, self.task_notifier) if self._retry_action is None: self._retry_action = self._retry_action_factory(self.storage, self.task_notifier) self._root = self._graph_action_factory(self._analyzer, self.storage, self._task_action, self._retry_action) self._compiled = True return class SingleThreadedActionEngine(ActionEngine): """Engine that runs tasks in serial manner.""" _storage_factory = t_storage.SingleThreadedStorage class MultiThreadedActionEngine(ActionEngine): """Engine that runs tasks in parallel manner.""" _storage_factory = t_storage.MultiThreadedStorage def _task_executor_factory(self): return executor.ParallelTaskExecutor(self._executor) def __init__(self, flow, flow_detail, backend, conf, **kwargs): super(MultiThreadedActionEngine, self).__init__( flow, flow_detail, backend, conf) self._executor = kwargs.get('executor')