Helpers to save flow factory in metadata

This change adds new helpers that, taken together, allow to resume
the flows having nothing but flow detail at hands. First one,
load_from_factory, gets flow factory function as a parameter and
saves its fully qualified name and arguments to flow metadata. Others
can be used to re-create the flow using that metadata, and load
it into engine.

Change-Id: Ia3cd989b3b0388ec0a9f09fe527f768eec5cc904
This commit is contained in:
Ivan A. Melnikov 2013-10-14 18:08:00 +04:00
parent c866318b3e
commit 961d91ff7a
6 changed files with 221 additions and 18 deletions

View File

@ -18,5 +18,8 @@
# promote helpers to this module namespace
from taskflow.engines.helpers import flow_from_detail # noqa
from taskflow.engines.helpers import load # noqa
from taskflow.engines.helpers import load_from_detail # noqa
from taskflow.engines.helpers import load_from_factory # noqa
from taskflow.engines.helpers import run # noqa

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@ -19,8 +19,10 @@
import six
import stevedore.driver
from taskflow.openstack.common import importutils
from taskflow.persistence import backends as p_backends
from taskflow.utils import persistence_utils as p_utils
from taskflow.utils import reflection
# NOTE(imelnikov): this is the entrypoint namespace, not the module namespace.
@ -98,7 +100,7 @@ def run(flow, store=None, engine_conf=None, backend=None):
can be backend itself, or a dictionary that is passed to
taskflow.persistence.backends.fetch to obtain backend.
:param flow: flow to load
:param flow: flow to run
:param store: dict -- data to put to storage to satisfy flow requirements
:param engine_conf: engine type and configuration configuration
:param backend: storage backend to use or configuration
@ -107,3 +109,91 @@ def run(flow, store=None, engine_conf=None, backend=None):
engine = load(flow, store=store, engine_conf=engine_conf, backend=backend)
engine.run()
return engine.storage.fetch_all()
def load_from_factory(flow_factory, factory_args=None, factory_kwargs=None,
store=None, book=None, engine_conf=None, backend=None):
"""Load flow from factory function into engine
Gets flow factory function (or name of it) and creates flow with
it. Then, flow is loaded into engine with load(), and factory
function fully qualified name is saved to flow metadata so that
it can be later resumed with resume.
:param flow_factory: function or string: function that creates the flow
:param factory_args: list or tuple of factory positional arguments
:param factory_kwargs: dict of factory keyword arguments
:param store: dict -- data to put to storage to satisfy flow requirements
:param book: LogBook to create flow detail in
:param engine_conf: engine type and configuration configuration
:param backend: storage backend to use or configuration
:returns: engine
"""
if isinstance(flow_factory, six.string_types):
factory_fun = importutils.import_class(flow_factory)
factory_name = flow_factory
else:
factory_fun = flow_factory
factory_name = reflection.get_callable_name(flow_factory)
try:
reimported = importutils.import_class(factory_name)
assert reimported == factory_fun
except (ImportError, AssertionError):
raise ValueError('Flow factory %r is not reimportable by name %s'
% (factory_fun, factory_name))
args = factory_args or []
kwargs = factory_kwargs or {}
flow = factory_fun(*args, **kwargs)
factory_data = dict(name=factory_name, args=args, kwargs=kwargs)
if isinstance(backend, dict):
backend = p_backends.fetch(backend)
flow_detail = p_utils.create_flow_detail(flow, book=book, backend=backend,
meta={'factory': factory_data})
return load(flow=flow, flow_detail=flow_detail,
store=store, book=book,
engine_conf=engine_conf, backend=backend)
def flow_from_detail(flow_detail):
"""Recreate flow previously loaded with load_form_factory
Gets flow factory name from metadata, calls it to recreate the flow
:param flow_detail: FlowDetail that holds state of the flow to load
"""
try:
factory_data = flow_detail.meta['factory']
except (KeyError, AttributeError, TypeError):
raise ValueError('Cannot reconstruct flow %s %s: '
'no factory information saved.'
% (flow_detail.name, flow_detail.uuid))
try:
factory_fun = importutils.import_class(factory_data['name'])
except (KeyError, ImportError):
raise ImportError('Could not import factory for flow %s %s'
% (flow_detail.name, flow_detail.uuid))
args = factory_data.get('args', ())
kwargs = factory_data.get('kwargs', {})
return factory_fun(*args, **kwargs)
def load_from_detail(flow_detail, store=None, engine_conf=None, backend=None):
"""Reload flow previously loaded with load_form_factory
Gets flow factory name from metadata, calls it to recreate the flow
and loads flow into engine with load().
:param flow_detail: FlowDetail that holds state of the flow to load
:param store: dict -- data to put to storage to satisfy flow requirements
:param engine_conf: engine type and configuration configuration
:param backend: storage backend to use or configuration
:returns: engine
"""
flow = flow_from_detail(flow_detail)
return load(flow, flow_detail=flow_detail,
store=store, engine_conf=engine_conf, backend=backend)

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@ -34,7 +34,6 @@ import taskflow.engines
from taskflow import states
import my_flows # noqa
import my_utils # noqa
@ -43,8 +42,7 @@ FINISHED_STATES = (states.SUCCESS, states.FAILURE, states.REVERTED)
def resume(flowdetail, backend):
print('Resuming flow %s %s' % (flowdetail.name, flowdetail.uuid))
engine = taskflow.engines.load(my_flows.flow_factory(),
flow_detail=flowdetail,
engine = taskflow.engines.load_from_detail(flow_detail=flowdetail,
backend=backend)
engine.run()

View File

@ -30,20 +30,14 @@ sys.path.insert(0, top_dir)
sys.path.insert(0, self_dir)
import taskflow.engines
from taskflow.utils import persistence_utils as p_utils
import my_flows # noqa
import my_utils # noqa
backend = my_utils.get_backend()
logbook = p_utils.temporary_log_book(backend)
flow = my_flows.flow_factory()
flowdetail = p_utils.create_flow_detail(flow, logbook, backend)
engine = taskflow.engines.load(flow, flow_detail=flowdetail,
engine = taskflow.engines.load_from_factory(my_flows.flow_factory,
backend=backend)
print('Running flow %s %s' % (flowdetail.name, flowdetail.uuid))
print('Running flow %s %s' % (engine.storage.flow_name,
engine.storage.flow_uuid))
engine.run()

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@ -0,0 +1,113 @@
# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
# Copyright (C) 2013 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 mock
from taskflow import test
from taskflow.tests import utils as test_utils
from taskflow.utils import persistence_utils as p_utils
import taskflow.engines
class FlowFromDetailTestCase(test.TestCase):
def test_no_meta(self):
_lb, flow_detail = p_utils.temporary_flow_detail()
self.assertIs(flow_detail.meta, None)
expected_msg = '^Cannot .* no factory information saved.$'
with self.assertRaisesRegexp(ValueError, expected_msg):
taskflow.engines.flow_from_detail(flow_detail)
def test_no_factory_in_meta(self):
_lb, flow_detail = p_utils.temporary_flow_detail()
flow_detail.meta = {}
expected_msg = '^Cannot .* no factory information saved.$'
with self.assertRaisesRegexp(ValueError, expected_msg):
taskflow.engines.flow_from_detail(flow_detail)
def test_no_importable_function(self):
_lb, flow_detail = p_utils.temporary_flow_detail()
flow_detail.meta = dict(factory=dict(
name='you can not import me, i contain spaces'
))
expected_msg = '^Could not import factory'
with self.assertRaisesRegexp(ImportError, expected_msg):
taskflow.engines.flow_from_detail(flow_detail)
def test_no_arg_factory(self):
name = 'some.test.factory'
_lb, flow_detail = p_utils.temporary_flow_detail()
flow_detail.meta = dict(factory=dict(name=name))
with mock.patch('taskflow.openstack.common.importutils.import_class',
return_value=lambda: 'RESULT') as mock_import:
result = taskflow.engines.flow_from_detail(flow_detail)
mock_import.assert_called_onec_with(name)
self.assertEquals(result, 'RESULT')
def test_factory_with_arg(self):
name = 'some.test.factory'
_lb, flow_detail = p_utils.temporary_flow_detail()
flow_detail.meta = dict(factory=dict(name=name, args=['foo']))
with mock.patch('taskflow.openstack.common.importutils.import_class',
return_value=lambda x: 'RESULT %s' % x) as mock_import:
result = taskflow.engines.flow_from_detail(flow_detail)
mock_import.assert_called_onec_with(name)
self.assertEquals(result, 'RESULT foo')
def my_flow_factory(task_name):
return test_utils.DummyTask(name=task_name)
class LoadFromFactoryTestCase(test.TestCase):
def test_non_reimportable(self):
def factory():
pass
with self.assertRaisesRegexp(ValueError,
'Flow factory .* is not reimportable'):
taskflow.engines.load_from_factory(factory)
def test_it_works(self):
engine = taskflow.engines.load_from_factory(
my_flow_factory, factory_kwargs={'task_name': 'test1'})
self.assertIsInstance(engine._flow, test_utils.DummyTask)
fd = engine.storage._flowdetail
self.assertEquals(fd.name, 'test1')
self.assertEquals(fd.meta.get('factory'), {
'name': '%s.my_flow_factory' % __name__,
'args': [],
'kwargs': {'task_name': 'test1'},
})
def test_it_works_by_name(self):
factory_name = '%s.my_flow_factory' % __name__
engine = taskflow.engines.load_from_factory(
factory_name, factory_kwargs={'task_name': 'test1'})
self.assertIsInstance(engine._flow, test_utils.DummyTask)
fd = engine.storage._flowdetail
self.assertEquals(fd.name, 'test1')
self.assertEquals(fd.meta.get('factory'), {
'name': factory_name,
'args': [],
'kwargs': {'task_name': 'test1'},
})

View File

@ -58,7 +58,7 @@ def temporary_flow_detail(backend=None):
return book, book.find(flow_id)
def create_flow_detail(flow, book=None, backend=None):
def create_flow_detail(flow, book=None, backend=None, meta=None):
"""Creates a flow detail for the given flow and adds it to the provided
logbook (if provided) and then uses the given backend (if provided) to
save the logbook then returns the created flow detail.
@ -73,7 +73,12 @@ def create_flow_detail(flow, book=None, backend=None):
except AttributeError:
LOG.warn("Flow %s does not have a uuid attribute, creating one.", flow)
flow_id = uuidutils.generate_uuid()
flow_detail = logbook.FlowDetail(name=flow_name, uuid=flow_id)
if meta is not None:
if flow_detail.meta is None:
flow_detail.meta = {}
flow_detail.meta.update(meta)
if backend is not None and book is None:
LOG.warn("No logbook provided for flow %s, creating one.", flow)