266 lines
8.6 KiB
Python
266 lines
8.6 KiB
Python
# Copyright 2014 - Mirantis, Inc.
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# Copyright 2015 - StackStorm, Inc.
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# Copyright 2015 - Huawei Technologies Co. Ltd
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# Copyright 2016 - Brocade Communications Systems, Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain 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,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import abc
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from oslo_log import log as logging
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from osprofiler import profiler
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from mistral.db.v2 import api as db_api
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from mistral import exceptions as exc
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from mistral.lang import parser as spec_parser
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from mistral import utils as u
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from mistral.workflow import commands
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from mistral.workflow import data_flow
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from mistral.workflow import states
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LOG = logging.getLogger(__name__)
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@profiler.trace('wf-controller-get-controller', hide_args=True)
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def get_controller(wf_ex, wf_spec=None):
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"""Gets a workflow controller instance by given workflow execution object.
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:param wf_ex: Workflow execution object.
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:param wf_spec: Workflow specification object. If passed, the method works
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faster.
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:returns: Workflow controller class.
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"""
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if not wf_spec:
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wf_spec = spec_parser.get_workflow_spec_by_execution_id(wf_ex.id)
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wf_type = wf_spec.get_type()
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ctrl_cls = None
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for cls in u.iter_subclasses(WorkflowController):
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if cls.__workflow_type__ == wf_type:
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ctrl_cls = cls
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break
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if not ctrl_cls:
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raise exc.MistralError(
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'Failed to find a workflow controller [type=%s]' % wf_type
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)
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return ctrl_cls(wf_ex, wf_spec)
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class TaskLogicalState(object):
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"""Task logical state.
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This data structure describes what state a task should have according
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to the logic of the workflow type and state of other tasks.
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"""
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def __init__(self, state, state_info=None, cardinality=0,
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triggered_by=None):
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self.state = state
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self.state_info = state_info
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self.cardinality = cardinality
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self.triggered_by = triggered_by or []
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def get_state(self):
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return self.state
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def get_state_info(self):
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return self.state_info
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def get_cardinality(self):
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return self.cardinality
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def get_triggered_by(self):
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return self.get_triggered_by
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class WorkflowController(object):
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"""Workflow Controller base class.
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Different workflow controllers implement different workflow algorithms.
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In practice it may actually mean that there may be multiple ways of
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describing workflow models (and even languages) that will be supported
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by Mistral.
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"""
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def __init__(self, wf_ex, wf_spec=None):
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"""Creates a new workflow controller.
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:param wf_ex: Workflow execution.
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:param wf_spec: Workflow specification.
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"""
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self.wf_ex = wf_ex
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if wf_spec is None:
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wf_spec = spec_parser.get_workflow_spec_by_execution_id(wf_ex.id)
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self.wf_spec = wf_spec
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@profiler.trace('workflow-controller-continue-workflow', hide_args=True)
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def continue_workflow(self, task_ex=None):
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"""Calculates a list of commands to continue the workflow.
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Given a workflow specification this method makes required analysis
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according to this workflow type rules and identifies a list of
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commands needed to continue the workflow.
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:param task_ex: Task execution that caused workflow continuation.
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Optional. If not specified, it means that no certain task caused
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this operation (e.g. workflow has been just started or resumed
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manually).
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:return: List of workflow commands (instances of
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mistral.workflow.commands.WorkflowCommand).
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"""
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if self._is_paused_or_completed():
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return []
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return self._find_next_commands(task_ex)
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def rerun_tasks(self, task_execs, reset=True):
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"""Gets commands to rerun existing task executions.
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:param task_execs: List of task executions.
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:param reset: If true, then purge action executions for the tasks.
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:return: List of workflow commands.
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"""
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if self._is_paused_or_completed():
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return []
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cmds = [
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commands.RunExistingTask(self.wf_ex, self.wf_spec, t_e, reset,
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rerun=True)
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for t_e in task_execs
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]
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LOG.debug("Commands to rerun workflow tasks: %s", cmds)
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return cmds
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@abc.abstractmethod
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def get_logical_task_state(self, task_ex):
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"""Determines a logical state of the given task.
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:param task_ex: Task execution.
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:return: Tuple (state, state_info, cardinality) where 'state' and
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'state_info' are the corresponding values which the given
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task should have according to workflow rules and current
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states of other tasks. 'cardinality' gives the estimation on
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the number of preconditions that are not yet met in case if
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state is WAITING. This number can be used to estimate how
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frequently we can refresh the state of this task.
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"""
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raise NotImplementedError
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@abc.abstractmethod
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def find_indirectly_affected_task_executions(self, task_name):
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"""Get a set of task executions indirectly affected by the given.
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:param task_name: Task name.
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:return: Task executions that can be indirectly affected by a task
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identified by the given name.
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"""
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raise NotImplementedError
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@abc.abstractmethod
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def is_error_handled_for(self, task_ex):
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"""Determines if error is handled for specific task.
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:param task_ex: Task execution.
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:return: True if either there is no error at all or
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error is considered handled.
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"""
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raise NotImplementedError
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@abc.abstractmethod
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def all_errors_handled(self):
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"""Determines if all errors (if any) are handled.
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:return: True if either there aren't errors at all or all
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errors are considered handled.
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"""
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raise NotImplementedError
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def any_cancels(self):
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"""Determines if there are any task cancellations.
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:return: True if there is one or more tasks in cancelled state.
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"""
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return len(self._get_task_executions(state=states.CANCELLED)) > 0
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@abc.abstractmethod
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def evaluate_workflow_final_context(self):
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"""Evaluates final workflow context assuming that workflow has finished.
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:return: Final workflow context.
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"""
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raise NotImplementedError
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def get_task_inbound_context(self, task_spec):
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# TODO(rakhmerov): This method should also be able to work with task_ex
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# to cover 'split' (aka 'merge') use case.
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upstream_task_execs = self._get_upstream_task_executions(task_spec)
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return data_flow.evaluate_upstream_context(upstream_task_execs)
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@abc.abstractmethod
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def _get_upstream_task_executions(self, task_spec):
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"""Gets workflow upstream tasks for the given task.
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:param task_spec: Task specification.
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:return: List of upstream task executions for the given task spec.
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"""
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raise NotImplementedError
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def may_complete_workflow(self, task_ex):
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"""Determines if the task execution may lead to workflow completion."""
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return states.is_completed(task_ex.state)
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@abc.abstractmethod
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def _find_next_commands(self, task_ex):
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"""Finds commands that should run next.
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A concrete algorithm of finding such tasks depends on a concrete
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workflow controller.
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:return: List of workflow commands.
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"""
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# If task execution was passed then we should make all calculations
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# only based on it.
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if task_ex:
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return []
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# Add all tasks in IDLE state.
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return [
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commands.RunExistingTask(self.wf_ex, self.wf_spec, t)
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for t in self._get_task_executions(state=states.IDLE)
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]
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def _is_paused_or_completed(self):
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return states.is_paused_or_completed(self.wf_ex.state)
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def _get_task_executions(self, **kwargs):
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return db_api.get_task_executions(
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workflow_execution_id=self.wf_ex.id,
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sort_keys=[], # disable sorting
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**kwargs
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)
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