0e7be02a48
Add optional env kwarg to resume_workflow and rerun_workflow in default engine. Add database API to update env in the params and context of the existing workflow execution. The updated env will be merged into existing __env of workflow context. For existing task, the env will be merged into __env of in_context. Partially implements: blueprint mistral-rerun-update-env Change-Id: Id378762d90ca5fc62d14e22134f18f9bce71a123
198 lines
6.3 KiB
Python
198 lines
6.3 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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#
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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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import copy
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from oslo_log import log as logging
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from mistral import exceptions as exc
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from mistral import utils as u
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from mistral.workbook import parser as spec_parser
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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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from mistral.workflow import utils as wf_utils
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LOG = logging.getLogger(__name__)
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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):
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"""Creates a new workflow controller.
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:param wf_ex: Workflow execution.
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"""
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self.wf_ex = wf_ex
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self.wf_spec = spec_parser.get_workflow_spec(wf_ex.spec)
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def _update_task_ex_env(self, task_ex, env):
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if not env:
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return task_ex
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task_ex.in_context['__env'] = u.merge_dicts(
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task_ex.in_context['__env'],
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env
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)
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return task_ex
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def continue_workflow(self, task_ex=None, reset=True, env=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 to rerun.
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:param: reset: If true, then purge action executions for the tasks.
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:param env: A set of environment variables to overwrite.
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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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if task_ex:
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return self._get_rerun_commands([task_ex], reset, env=env)
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return self._find_next_commands(env=env)
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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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: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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@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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upstream_task_execs = self._get_upstream_task_executions(task_spec)
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upstream_ctx = data_flow.evaluate_upstream_context(upstream_task_execs)
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ctx = u.merge_dicts(
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copy.deepcopy(self.wf_ex.context),
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upstream_ctx
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)
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if self.wf_ex.context:
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ctx['__env'] = u.merge_dicts(
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copy.deepcopy(upstream_ctx.get('__env', {})),
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copy.deepcopy(self.wf_ex.context.get('__env', {}))
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)
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return ctx
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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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@abc.abstractmethod
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def _find_next_commands(self, env=None):
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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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:param env: A set of environment variables to overwrite.
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:return: List of workflow commands.
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"""
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# Add all tasks in IDLE state.
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idle_tasks = wf_utils.find_task_executions_with_state(
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self.wf_ex,
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states.IDLE
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)
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for task_ex in idle_tasks:
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self._update_task_ex_env(task_ex, env)
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return [commands.RunExistingTask(t) for t in idle_tasks]
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def _get_rerun_commands(self, task_exs, reset=True, env=None):
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"""Get commands to rerun existing task executions.
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:param task_exs: List of task executions.
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:param reset: If true, then purge action executions for the tasks.
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:param env: A set of environment variables to overwrite.
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:return: List of workflow commands.
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"""
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for task_ex in task_exs:
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self._update_task_ex_env(task_ex, env)
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cmds = [commands.RunExistingTask(t_e, reset) for t_e in task_exs]
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LOG.debug("Found commands: %s" % cmds)
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return cmds
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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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@staticmethod
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def _get_class(wf_type):
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"""Gets a workflow controller class by given workflow type.
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:param wf_type: Workflow type.
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:returns: Workflow controller class.
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"""
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for wf_ctrl_cls in u.iter_subclasses(WorkflowController):
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if wf_type == wf_ctrl_cls.__workflow_type__:
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return wf_ctrl_cls
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raise exc.NotFoundException(
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'Failed to find a workflow controller [type=%s]' % wf_type
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)
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@staticmethod
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def get_controller(wf_ex, wf_spec=None):
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if not wf_spec:
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wf_spec = spec_parser.get_workflow_spec(wf_ex['spec'])
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return WorkflowController._get_class(wf_spec.get_type())(wf_ex)
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