197 lines
6.1 KiB
Python
197 lines
6.1 KiB
Python
# -*- coding: utf-8 -*-
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# vim: tabstop=4 shiftwidth=4 softtabstop=4
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# Copyright (C) 2012-2013 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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import os
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import random
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import sys
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import time
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import uuid
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logging.basicConfig(level=logging.ERROR)
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top_dir = os.path.abspath(os.path.join(os.path.dirname(__file__),
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os.pardir,
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os.pardir))
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sys.path.insert(0, top_dir)
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import taskflow.engines
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from taskflow.patterns import graph_flow as gf
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from taskflow import task
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# Simulates some type of persistance.
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MY_DB = {
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'space': {
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'cpus': 2,
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'memory': 8192,
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'disk': 1024,
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},
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'vms': {},
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'places': ['127.0.0.1', '127.0.0.2', '127.0.0.3'],
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}
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# This prints out the transitions a flow is going through.
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def flow_notify(state, details):
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print("'%s' entered state: %s" % (details.get('flow_name'), state))
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# This prints out the transitions a flows tasks are going through.
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def task_notify(state, details):
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print("'%s' entered state: %s" % (details.get('task_name'), state))
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# Simulates what nova/glance/keystone... calls a context
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class Context(object):
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def __init__(self, **items):
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self.__dict__.update(items)
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def __str__(self):
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return "Context: %s" % (self.__dict__)
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# Simulates translating an api request into a validated format (aka a vm-spec)
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# that will later be acted upon.
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class ValidateAPIInputs(task.Task):
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def __init__(self):
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super(ValidateAPIInputs, self).__init__('validates-api-inputs',
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provides='vm_spec')
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def execute(self, context):
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print "Validating api inputs for %s" % (context)
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return {'cpus': 1,
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'memory': 512,
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'disk': 100,
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}
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# Simulates reserving the space for a vm and associating the vm to be with
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# a unique identifier.
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class PerformReservation(task.Task):
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def __init__(self):
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super(PerformReservation, self).__init__('reserve-vm',
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provides='vm_reservation_'
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'spec')
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def revert(self, context, vm_spec, result):
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reserved_spec = result
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print("Undoing reservation of %s" % (reserved_spec['uuid']))
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vm_spec = MY_DB['vms'].pop(reserved_spec['uuid'])
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print 'Space before: %s' % (MY_DB['space'])
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# Unreserve 'atomically'
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for (k, v) in vm_spec.items():
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if k in ['scheduled']:
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continue
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MY_DB['space'][k] += v
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print 'Space after: %s' % (MY_DB['space'])
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def execute(self, context, vm_spec):
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print 'Reserving %s for %s' % (vm_spec, context)
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# Reserve 'atomically'
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print 'Space before: %s' % (MY_DB['space'])
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for (k, v) in vm_spec.items():
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if MY_DB['space'][k] < v:
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raise RuntimeError("Not enough %s available" % (k))
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MY_DB['space'][k] -= vm_spec[k]
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print 'Space after: %s' % (MY_DB['space'])
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# Create a fake 'db' entry for the vm
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vm_uuid = str(uuid.uuid4())
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MY_DB['vms'][vm_uuid] = vm_spec
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MY_DB['vms'][vm_uuid]['scheduled'] = False
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return {'uuid': vm_uuid,
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'reserved_on': time.time(),
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'vm_spec': vm_spec,
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}
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# Simulates scheudling a vm to some location
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class ScheduleVM(task.Task):
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def __init__(self):
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super(ScheduleVM, self).__init__('find-hole-for-vm',
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provides=['vm_hole', 'vm_uuid'])
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def revert(self, context, vm_reservation_spec, result):
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vm_uuid = result[1]
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vm_place = result[0]
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print "Marking %s as not having a home at %s anymore" % (vm_uuid,
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vm_place)
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MY_DB['vms'][vm_uuid]['scheduled'] = False
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MY_DB['places'].append(vm_place)
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def execute(self, context, vm_reservation_spec):
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print "Finding a place to put %s" % (vm_reservation_spec)
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vm_uuid = vm_reservation_spec['uuid']
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MY_DB['vms'][vm_uuid]['scheduled'] = True
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# Reserve the place 'atomically'
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vm_place = random.choice(MY_DB['places'])
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print 'Placing %s at %s' % (vm_uuid, vm_place)
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MY_DB['places'].remove(vm_place)
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return vm_place, vm_uuid
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# Fail booting a vm to see what happens.
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class BootVM(task.Task):
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def __init__(self):
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super(BootVM, self).__init__('boot-vm', provides='vm_booted')
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def execute(self, context, vm_reservation_spec, vm_hole):
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raise RuntimeError("Failed booting")
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# Lets try booting a vm (not really) and see how the reversions work.
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flow = gf.Flow("Boot-Fake-Vm").add(
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ValidateAPIInputs(),
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PerformReservation(),
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ScheduleVM(),
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BootVM())
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# Simulates what nova/glance/keystone... calls a context
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context = {
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'user_id': 'xyz',
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'project_id': 'abc',
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'is_admin': True,
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}
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context = Context(**context)
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# Load the flow
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engine = taskflow.engines.load(flow, store={'context': context})
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# Get notified of the state changes the flow is going through.
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engine.notifier.register('*', flow_notify)
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# Get notified of the state changes the flows tasks/runners are going through.
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engine.task_notifier.register('*', task_notify)
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print '-' * 7
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print 'Running'
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print '-' * 7
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try:
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engine.run()
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except Exception as e:
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print 'Flow failed: %r' % e
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print '-' * 11
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print 'All results'
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print '-' * 11
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result = engine.storage.fetch_all()
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for tid in sorted(result):
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print '%s => %s' % (tid, result[tid])
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