e1ef04492e
Instead of having a ad-hoc state-machine being used to perform the various runtime actions (performed when a engine is ran) we can gain a much more explict execution model by translating that ad-hoc state machine to an explicit one instead... This commit does just that, it adds a new fsm type that can be used to create, define and run state-machines that respond to various events (internal or external) and uses it in the runner action engine module to run the previously ad-hc/implicit state-machine. Implements blueprint runner-state-machine Change-Id: Id35633a9de707f3ffb1a4b7e9619af1be009317f
240 lines
9.5 KiB
Python
240 lines
9.5 KiB
Python
# -*- coding: utf-8 -*-
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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 logging
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from taskflow import states as st
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from taskflow.types import fsm
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from taskflow.utils import misc
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# Waiting state timeout (in seconds).
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_WAITING_TIMEOUT = 60
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# Meta states the state machine uses.
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_UNDEFINED = 'UNDEFINED'
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_GAME_OVER = 'GAME_OVER'
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_META_STATES = (_GAME_OVER, _UNDEFINED)
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LOG = logging.getLogger(__name__)
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class _MachineMemory(object):
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"""State machine memory."""
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def __init__(self):
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self.next_nodes = set()
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self.not_done = set()
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self.failures = []
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self.done = set()
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class _MachineBuilder(object):
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"""State machine *builder* that the runner uses.
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NOTE(harlowja): the machine states that this build will for are::
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+--------------+-----------+------------+----------+---------+
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| Start | Event | End | On Enter | On Exit |
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+--------------+-----------+------------+----------+---------+
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| ANALYZING | finished | GAME_OVER | on_enter | on_exit |
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| ANALYZING | schedule | SCHEDULING | on_enter | on_exit |
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| ANALYZING | wait | WAITING | on_enter | on_exit |
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| FAILURE[$] | | | | |
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| GAME_OVER | failed | FAILURE | on_enter | on_exit |
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| GAME_OVER | reverted | REVERTED | on_enter | on_exit |
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| GAME_OVER | success | SUCCESS | on_enter | on_exit |
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| GAME_OVER | suspended | SUSPENDED | on_enter | on_exit |
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| RESUMING | schedule | SCHEDULING | on_enter | on_exit |
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| REVERTED[$] | | | | |
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| SCHEDULING | wait | WAITING | on_enter | on_exit |
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| SUCCESS[$] | | | | |
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| SUSPENDED[$] | | | | |
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| UNDEFINED[^] | start | RESUMING | on_enter | on_exit |
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| WAITING | analyze | ANALYZING | on_enter | on_exit |
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+--------------+-----------+------------+----------+---------+
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Between any of these yielded states (minus ``GAME_OVER`` and ``UNDEFINED``)
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if the engine has been suspended or the engine has failed (due to a
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non-resolveable task failure or scheduling failure) the machine will stop
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executing new tasks (currently running tasks will be allowed to complete)
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and this machines run loop will be broken.
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"""
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def __init__(self, runtime, waiter):
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self._analyzer = runtime.analyzer
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self._completer = runtime.completer
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self._scheduler = runtime.scheduler
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self._storage = runtime.storage
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self._waiter = waiter
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def runnable(self):
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return self._storage.get_flow_state() == st.RUNNING
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def build(self, timeout=None):
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memory = _MachineMemory()
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if timeout is None:
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timeout = _WAITING_TIMEOUT
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def resume(old_state, new_state, event):
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memory.next_nodes.update(self._completer.resume())
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memory.next_nodes.update(self._analyzer.get_next_nodes())
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return 'schedule'
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def game_over(old_state, new_state, event):
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if memory.failures:
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return 'failed'
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if self._analyzer.get_next_nodes():
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return 'suspended'
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elif self._analyzer.is_success():
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return 'success'
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else:
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return 'reverted'
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def schedule(old_state, new_state, event):
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if self.runnable() and memory.next_nodes:
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not_done, failures = self._scheduler.schedule(
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memory.next_nodes)
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if not_done:
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memory.not_done.update(not_done)
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if failures:
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memory.failures.extend(failures)
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memory.next_nodes.clear()
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return 'wait'
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def wait(old_state, new_state, event):
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# TODO(harlowja): maybe we should start doing 'yield from' this
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# call sometime in the future, or equivalent that will work in
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# py2 and py3.
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if memory.not_done:
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done, not_done = self._waiter.wait_for_any(memory.not_done,
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timeout)
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memory.done.update(done)
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memory.not_done = not_done
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return 'analyze'
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def analyze(old_state, new_state, event):
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next_nodes = set()
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while memory.done:
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fut = memory.done.pop()
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try:
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node, event, result = fut.result()
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retain = self._completer.complete(node, event, result)
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if retain and isinstance(result, misc.Failure):
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memory.failures.append(result)
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except Exception:
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memory.failures.append(misc.Failure())
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else:
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try:
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more_nodes = self._analyzer.get_next_nodes(node)
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except Exception:
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memory.failures.append(misc.Failure())
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else:
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next_nodes.update(more_nodes)
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if self.runnable() and next_nodes and not memory.failures:
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memory.next_nodes.update(next_nodes)
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return 'schedule'
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elif memory.not_done:
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return 'wait'
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else:
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return 'finished'
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def on_exit(old_state, event):
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LOG.debug("Exiting old state '%s' in response to event '%s'",
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old_state, event)
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def on_enter(new_state, event):
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LOG.debug("Entering new state '%s' in response to event '%s'",
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new_state, event)
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# NOTE(harlowja): when ran in debugging mode it is quite useful
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# to track the various state transitions as they happen...
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watchers = {}
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if LOG.isEnabledFor(logging.DEBUG):
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watchers['on_exit'] = on_exit
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watchers['on_enter'] = on_enter
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m = fsm.FSM(_UNDEFINED)
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m.add_state(_GAME_OVER, **watchers)
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m.add_state(_UNDEFINED, **watchers)
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m.add_state(st.ANALYZING, **watchers)
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m.add_state(st.RESUMING, **watchers)
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m.add_state(st.REVERTED, terminal=True, **watchers)
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m.add_state(st.SCHEDULING, **watchers)
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m.add_state(st.SUCCESS, terminal=True, **watchers)
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m.add_state(st.SUSPENDED, terminal=True, **watchers)
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m.add_state(st.WAITING, **watchers)
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m.add_state(st.FAILURE, terminal=True, **watchers)
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m.add_transition(_GAME_OVER, st.REVERTED, 'reverted')
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m.add_transition(_GAME_OVER, st.SUCCESS, 'success')
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m.add_transition(_GAME_OVER, st.SUSPENDED, 'suspended')
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m.add_transition(_GAME_OVER, st.FAILURE, 'failed')
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m.add_transition(_UNDEFINED, st.RESUMING, 'start')
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m.add_transition(st.ANALYZING, _GAME_OVER, 'finished')
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m.add_transition(st.ANALYZING, st.SCHEDULING, 'schedule')
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m.add_transition(st.ANALYZING, st.WAITING, 'wait')
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m.add_transition(st.RESUMING, st.SCHEDULING, 'schedule')
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m.add_transition(st.SCHEDULING, st.WAITING, 'wait')
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m.add_transition(st.WAITING, st.ANALYZING, 'analyze')
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m.add_reaction(_GAME_OVER, 'finished', game_over)
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m.add_reaction(st.ANALYZING, 'analyze', analyze)
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m.add_reaction(st.RESUMING, 'start', resume)
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m.add_reaction(st.SCHEDULING, 'schedule', schedule)
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m.add_reaction(st.WAITING, 'wait', wait)
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return (m, memory)
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class Runner(object):
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"""Runner that iterates while executing nodes using the given runtime.
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This runner acts as the action engine run loop/state-machine, it resumes
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the workflow, schedules all task it can for execution using the runtimes
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scheduler and analyzer components, and than waits on returned futures and
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then activates the runtimes completion component to finish up those tasks
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and so on...
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NOTE(harlowja): If the runtimes scheduler component is able to schedule
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tasks in parallel, this enables parallel running and/or reversion.
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"""
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# Informational states this action yields while running, not useful to
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# have the engine record but useful to provide to end-users when doing
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# execution iterations.
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ignorable_states = (st.SCHEDULING, st.WAITING, st.RESUMING, st.ANALYZING)
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def __init__(self, runtime, waiter):
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self._builder = _MachineBuilder(runtime, waiter)
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@property
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def builder(self):
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return self._builder
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def runnable(self):
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return self._builder.runnable()
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def run_iter(self, timeout=None):
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"""Runs the nodes using a built state machine."""
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machine, memory = self.builder.build(timeout=timeout)
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for (_prior_state, new_state) in machine.run_iter('start'):
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# NOTE(harlowja): skip over meta-states.
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if new_state not in _META_STATES:
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if new_state == st.FAILURE:
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yield (new_state, memory.failures)
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else:
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yield (new_state, [])
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