Source code for taskflow.engines.action_engine.completer

# -*- coding: utf-8 -*-

#    Copyright (C) 2014 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 abc
import weakref

from oslo_utils import reflection
import six

from taskflow.engines.action_engine import executor as ex
from taskflow import logging
from taskflow import retry as retry_atom
from taskflow import states as st
from taskflow import task as task_atom
from taskflow.types import failure

LOG = logging.getLogger(__name__)


@six.add_metaclass(abc.ABCMeta)
[docs]class Strategy(object): """Failure resolution strategy base class.""" strategy = None def __init__(self, runtime): self._runtime = runtime @abc.abstractmethod
[docs] def apply(self): """Applies some algorithm to resolve some detected failure."""
def __str__(self): base = reflection.get_class_name(self, fully_qualified=False) if self.strategy is not None: strategy_name = self.strategy.name else: strategy_name = "???" return base + "(strategy=%s)" % (strategy_name)
[docs]class RevertAndRetry(Strategy): """Sets the *associated* subflow for revert to be later retried.""" strategy = retry_atom.RETRY def __init__(self, runtime, retry): super(RevertAndRetry, self).__init__(runtime) self._retry = retry def apply(self): tweaked = self._runtime.reset_nodes([self._retry], state=None, intention=st.RETRY) tweaked.extend(self._runtime.reset_subgraph(self._retry, state=None, intention=st.REVERT)) return tweaked
[docs]class RevertAll(Strategy): """Sets *all* nodes/atoms to the ``REVERT`` intention.""" strategy = retry_atom.REVERT_ALL def __init__(self, runtime): super(RevertAll, self).__init__(runtime) self._analyzer = runtime.analyzer def apply(self): return self._runtime.reset_nodes(self._analyzer.iterate_all_nodes(), state=None, intention=st.REVERT)
[docs]class Revert(Strategy): """Sets atom and *associated* nodes to the ``REVERT`` intention.""" strategy = retry_atom.REVERT def __init__(self, runtime, atom): super(Revert, self).__init__(runtime) self._atom = atom def apply(self): tweaked = self._runtime.reset_nodes([self._atom], state=None, intention=st.REVERT) tweaked.extend(self._runtime.reset_subgraph(self._atom, state=None, intention=st.REVERT)) return tweaked
[docs]class Completer(object): """Completes atoms using actions to complete them.""" def __init__(self, runtime): self._runtime = weakref.proxy(runtime) self._analyzer = runtime.analyzer self._storage = runtime.storage self._task_action = runtime.task_action self._retry_action = runtime.retry_action self._undefined_resolver = RevertAll(self._runtime) def _complete_task(self, task, event, result): """Completes the given task, processes task failure.""" if event == ex.EXECUTED: self._task_action.complete_execution(task, result) else: self._task_action.complete_reversion(task, result) def _complete_retry(self, retry, event, result): """Completes the given retry, processes retry failure.""" if event == ex.EXECUTED: self._retry_action.complete_execution(retry, result) else: self._retry_action.complete_reversion(retry, result)
[docs] def resume(self): """Resumes nodes in the contained graph. This is done to allow any previously completed or failed nodes to be analyzed, there results processed and any potential nodes affected to be adjusted as needed. This should return a set of nodes which should be the initial set of nodes that were previously not finished (due to a RUNNING or REVERTING attempt not previously finishing). """ for node in self._analyzer.iterate_all_nodes(): if self._analyzer.get_state(node) == st.FAILURE: self._process_atom_failure(node, self._storage.get(node.name)) for retry in self._analyzer.iterate_retries(st.RETRYING): self._runtime.retry_subflow(retry) unfinished_nodes = set() for node in self._analyzer.iterate_all_nodes(): if self._analyzer.get_state(node) in (st.RUNNING, st.REVERTING): unfinished_nodes.add(node) return unfinished_nodes
[docs] def complete(self, node, event, result): """Performs post-execution completion of a node. Returns whether the result should be saved into an accumulator of failures or whether this should not be done. """ if isinstance(node, task_atom.BaseTask): self._complete_task(node, event, result) else: self._complete_retry(node, event, result) if isinstance(result, failure.Failure): if event == ex.EXECUTED: self._process_atom_failure(node, result) else: # Reverting failed, always retain the failure... return True return False
def _determine_resolution(self, atom, failure): """Determines which resolution strategy to activate/apply.""" retry = self._analyzer.find_atom_retry(atom) if retry is not None: # Ask retry controller what to do in case of failure. strategy = self._retry_action.on_failure(retry, atom, failure) if strategy == retry_atom.RETRY: return RevertAndRetry(self._runtime, retry) elif strategy == retry_atom.REVERT: # Ask parent retry and figure out what to do... parent_resolver = self._determine_resolution(retry, failure) # Ok if the parent resolver says something not REVERT, and # it isn't just using the undefined resolver, assume the # parent knows best. if parent_resolver is not self._undefined_resolver: if parent_resolver.strategy != retry_atom.REVERT: return parent_resolver return Revert(self._runtime, retry) elif strategy == retry_atom.REVERT_ALL: return RevertAll(self._runtime) else: raise ValueError("Unknown atom failure resolution" " action/strategy '%s'" % strategy) else: return self._undefined_resolver def _process_atom_failure(self, atom, failure): """Processes atom failure & applies resolution strategies. On atom failure this will find the atoms associated retry controller and ask that controller for the strategy to perform to resolve that failure. After getting a resolution strategy decision this method will then adjust the needed other atoms intentions, and states, ... so that the failure can be worked around. """ resolver = self._determine_resolution(atom, failure) LOG.debug("Applying resolver '%s' to resolve failure '%s'" " of atom '%s'", resolver, failure, atom) tweaked = resolver.apply() # Only show the tweaked node list when blather is on, otherwise # just show the amount/count of nodes tweaks... if LOG.isEnabledFor(logging.BLATHER): LOG.blather("Modified/tweaked %s nodes while applying" " resolver '%s'", tweaked, resolver) else: LOG.debug("Modified/tweaked %s nodes while applying" " resolver '%s'", len(tweaked), resolver)