359cc490bd
To make it easily possible to change the retry atom execution from being in the engine thread this creates a retry executor (which is similar to the task executor) and provide that a serial executor (which it will use to execute with). This makes the retry and task actions closer to being the same and makes the surrounding code that much similar (which makes understanding it easier). Change-Id: I993e938280df3bd97f8076293183ef21989e2dba
101 lines
3.7 KiB
Python
101 lines
3.7 KiB
Python
# -*- coding: utf-8 -*-
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# Copyright (C) 2014 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 weakref
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from taskflow import exceptions as excp
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from taskflow import states as st
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from taskflow.types import failure
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class RetryScheduler(object):
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"""Schedules retry atoms."""
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def __init__(self, runtime):
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self._runtime = weakref.proxy(runtime)
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self._retry_action = runtime.retry_action
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self._storage = runtime.storage
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def schedule(self, retry):
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"""Schedules the given retry atom for *future* completion.
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Depending on the atoms stored intention this may schedule the retry
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atom for reversion or execution.
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"""
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intention = self._storage.get_atom_intention(retry.name)
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if intention == st.EXECUTE:
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return self._retry_action.schedule_execution(retry)
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elif intention == st.REVERT:
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return self._retry_action.schedule_reversion(retry)
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elif intention == st.RETRY:
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self._retry_action.change_state(retry, st.RETRYING)
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self._runtime.retry_subflow(retry)
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return self._retry_action.schedule_execution(retry)
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else:
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raise excp.ExecutionFailure("Unknown how to schedule retry with"
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" intention: %s" % intention)
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class TaskScheduler(object):
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"""Schedules task atoms."""
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def __init__(self, runtime):
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self._storage = runtime.storage
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self._task_action = runtime.task_action
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def schedule(self, task):
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"""Schedules the given task atom for *future* completion.
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Depending on the atoms stored intention this may schedule the task
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atom for reversion or execution.
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"""
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intention = self._storage.get_atom_intention(task.name)
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if intention == st.EXECUTE:
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return self._task_action.schedule_execution(task)
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elif intention == st.REVERT:
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return self._task_action.schedule_reversion(task)
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else:
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raise excp.ExecutionFailure("Unknown how to schedule task with"
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" intention: %s" % intention)
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class Scheduler(object):
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"""Safely schedules atoms using a runtime ``fetch_scheduler`` routine."""
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def __init__(self, runtime):
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self._fetch_scheduler = runtime.fetch_scheduler
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def schedule(self, atoms):
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"""Schedules the provided atoms for *future* completion.
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This method should schedule a future for each atom provided and return
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a set of those futures to be waited on (or used for other similar
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purposes). It should also return any failure objects that represented
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scheduling failures that may have occurred during this scheduling
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process.
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"""
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futures = set()
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for atom in atoms:
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scheduler = self._fetch_scheduler(atom)
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try:
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futures.add(scheduler.schedule(atom))
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except Exception:
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# Immediately stop scheduling future work so that we can
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# exit execution early (rather than later) if a single atom
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# fails to schedule correctly.
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return (futures, [failure.Failure()])
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return (futures, [])
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