Github user ran-z commented on a diff in the pull request:
https://github.com/apache/incubator-ariatosca/pull/97#discussion_r111380601
--- Diff: aria/orchestrator/workflow_runner.py ---
@@ -0,0 +1,166 @@
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You 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.
+
+"""
+Workflow runner
+"""
+
+import os
+import sys
+from datetime import datetime
+
+from . import exceptions
+from .context.workflow import WorkflowContext
+from .workflows.builtin import BUILTIN_WORKFLOWS,
BUILTIN_WORKFLOWS_PATH_PREFIX
+from .workflows.core.engine import Engine
+from .workflows.executor.process import ProcessExecutor
+from ..modeling import models
+from ..modeling import utils as modeling_utils
+from ..utils.imports import import_fullname
+
+
+DEFAULT_TASK_MAX_ATTEMPTS = 1
+DEFAULT_TASK_RETRY_INTERVAL = 1
+# TODO move this constant somewhere in the DSL parser?
+WORKFLOW_POLICY_INTERNAL_PROPERTIES = ('implementation', 'dependencies')
+
+
+class WorkflowRunner(object):
+
+ def __init__(self, workflow_name, service_id, inputs,
+ model_storage, resource_storage, plugin_manager,
+ executor=None,
task_max_attempts=DEFAULT_TASK_MAX_ATTEMPTS,
+ task_retry_interval=DEFAULT_TASK_RETRY_INTERVAL):
+ """
+ Manages a single workflow execution on a given service
+ :param workflow_name: Workflow name
+ :param service_id: Service id
+ :param inputs: A key-value dict of inputs for the execution
+ :param model_storage: Model storage
+ :param resource_storage: Resource storage
+ :param plugin_manager: Plugin manager
+ :param executor: Executor for tasks. Defaults to a ProcessExecutor
instance.
+ :param task_max_attempts: Maximum attempts of repeating each
failing task
+ :param task_retry_interval: Retry interval in between retry
attempts of a failing task
+ """
+
+ self._model_storage = model_storage
+ self._resource_storage = resource_storage
+ self._workflow_name = workflow_name
+
+ # the IDs are stored rather than the models themselves, so this
module could be used
+ # by several threads without raising errors on model objects
shared between threads
+ self._service_id = service_id
+
+ self._validate_workflow_exists_for_service()
+
+ workflow_fn = self._get_workflow_fn()
+
+ execution = self._create_execution_model(inputs)
+ self._execution_id = execution.id
+
+ workflow_context = WorkflowContext(
+ name=self.__class__.__name__,
+ model_storage=self._model_storage,
+ resource_storage=resource_storage,
+ service_id=service_id,
+ execution_id=execution.id,
+ workflow_name=workflow_name,
+ task_max_attempts=task_max_attempts,
+ task_retry_interval=task_retry_interval)
+
+ # transforming the execution inputs to dict, to pass them to the
workflow function
+ execution_inputs_dict =
models.Parameter.unwrap_dict(self.execution.inputs)
+ self._tasks_graph = workflow_fn(ctx=workflow_context,
**execution_inputs_dict)
+
+ executor = executor or
ProcessExecutor(plugin_manager=plugin_manager)
+ self._engine = Engine(
+ executor=executor,
+ workflow_context=workflow_context,
+ tasks_graph=self._tasks_graph)
+
+ @property
+ def execution(self):
+ return self._model_storage.execution.get(self._execution_id)
+
+ @property
+ def service(self):
+ return self._model_storage.service.get(self._service_id)
+
+ def execute(self):
+ self._engine.execute()
+
+ def cancel(self):
+ self._engine.cancel_execution()
+
+ def _create_execution_model(self, inputs):
+ execution = models.Execution(
+ created_at=datetime.utcnow(),
+ service=self.service,
+ workflow_name=self._workflow_name,
+ inputs={})
+
+ if self._workflow_name in BUILTIN_WORKFLOWS:
+ workflow_inputs = dict() # built-in workflows don't have any
inputs
+ else:
+ workflow_inputs = dict((k, v) for k, v in
+
self.service.workflows[self._workflow_name].inputs.iteritems()
+ if k not in
WORKFLOW_POLICY_INTERNAL_PROPERTIES)
+
+ execution.inputs = modeling_utils.create_inputs(inputs,
workflow_inputs)
+ # TODO: these two following calls should execute atomically
+ self._validate_no_active_executions(execution)
+ self._model_storage.execution.put(execution)
+ return execution
+
+ def _validate_workflow_exists_for_service(self):
+ if self._workflow_name not in self.service.workflows and \
+ self._workflow_name not in BUILTIN_WORKFLOWS:
+ raise exceptions.UndeclaredWorkflowError(
+ 'No workflow policy {0} declared in service {1}'
+ .format(self._workflow_name, self.service.name))
+
+ def _validate_no_active_executions(self, execution):
+ active_executions = [e for e in self.service.executions
+ if e.id != execution.id and e.is_active()]
--- End diff --
making pending not active
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