
In order to move away from the existing flows having their own implementation of running, start moving the existing flows to be patterns that only structure tasks (and impose constraints about how the group of tasks can run) in useful ways. Let the concept of running those patterns be handled by an engine instead of being handled by the flow itself. This will allow for varying engines to be able to run flows in whichever way the engine chooses (as long as the constraints set up by the flow are observed). Currently threaded flow and graph flow are broken by this commit, since they have not been converted to being a structure of tasks + constraints. The existing engine has not yet been modified to run those structures either, work is underway to remediate this. Part of: blueprint patterns-and-engines Followup bugs that must be addressed: Bug: 1221448 Bug: 1221505 Change-Id: I3a8b96179f336d1defe269728ebae0caa3d832d7
188 lines
5.6 KiB
Python
188 lines
5.6 KiB
Python
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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print('GraphFlow is under refactoring now, so this example '
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'is temporarily broken')
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sys.exit(0)
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logging.basicConfig(level=logging.ERROR)
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my_dir_path = os.path.dirname(os.path.abspath(__file__))
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sys.path.insert(0, os.path.join(os.path.join(my_dir_path, os.pardir),
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os.pardir))
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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['flow'], 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['runner'], 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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self.provides.update(['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 {
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'vm_spec': {
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'cpus': 1,
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'memory': 512,
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'disk': 100,
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}
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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 PeformReservation(task.Task):
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def __init__(self):
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super(PeformReservation, self).__init__('reserve-vm')
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self.provides.update(['vm_reservation_spec'])
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self.requires.update(['vm_spec'])
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def revert(self, context, result, cause):
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reserved_spec = result['vm_reservation_spec']
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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] += vm_spec[k]
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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] < vm_spec[k]:
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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 {
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'vm_reservation_spec': {
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'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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}
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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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self.provides.update(['vm_hole'])
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self.requires.update(['vm_reservation_spec'])
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def revert(self, context, result, cause):
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vm_uuid = result['vm_uuid']
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vm_place = result['vm_hole']
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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 {
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'vm_hole': vm_place,
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'vm_uuid': vm_uuid,
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}
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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')
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self.provides.update(['vm_booted'])
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self.requires.update(['vm_reservation_spec', 'vm_hole'])
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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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flo = gf.Flow("Boot-Fake-Vm")
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flo.add(ValidateAPIInputs())
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flo.add(PeformReservation())
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flo.add(ScheduleVM())
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flo.add(BootVM())
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# Get notified of the state changes the flow is going through.
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flo.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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flo.task_notifier.register('*', task_notify)
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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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print '-' * 7
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print 'Running'
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print '-' * 7
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try:
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flo.run(context)
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except Exception as e:
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print 'Flow failed: %r' % e
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print '-- Flow state %s' % (flo.state)
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print '-' * 11
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print 'All results'
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print '-' * 11
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for (tid, v) in sorted(flo.results.items()):
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print '%s => %s' % (tid, v)
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