def run_delayed_task(context):
"""Runs the delayed task. Performs all the steps required to setup
a task to run which are not already done. This is mostly code
copied over from convey_task_result.
:param context Mistral authentication context inherited from a
caller thread.
"""
auth_context.set_ctx(context)
db_api.start_tx()
try:
execution_id = task['execution_id']
execution = db_api.execution_get(execution_id)
# Change state from DELAYED to RUNNING.
WORKFLOW_TRACE.info("Task '%s' [%s -> %s]"
% (task['name'],
task['state'], states.RUNNING))
executables = data_flow.prepare_tasks([task],
outbound_context,
workbook)
db_api.commit_tx()
finally:
db_api.end_tx()
if states.is_stopped_or_finished(execution['state']):
return
for task_id, action_name, action_params in executables:
self._run_task(task_id, action_name, action_params)
def run_delayed_task():
"""
Runs the delayed task. Performs all the steps required to setup
a task to run which are not already done. This is mostly code
copied over from convey_task_result.
"""
db_api.start_tx()
try:
workbook_name = task['workbook_name']
execution_id = task['execution_id']
execution = db_api.execution_get(workbook_name, execution_id)
# Change state from DELAYED to IDLE to unblock processing.
WORKFLOW_TRACE.info("Task '%s' [%s -> %s]"
% (task['name'],
task['state'], states.IDLE))
db_task = db_api.task_update(workbook_name,
execution_id,
task['id'],
{"state": states.IDLE})
task_to_start = [db_task]
data_flow.prepare_tasks(task_to_start, outbound_context)
db_api.commit_tx()
finally:
db_api.end_tx()
if not states.is_stopped_or_finished(execution["state"]):
cls._run_tasks(task_to_start)
def run_delayed_task():
"""
Runs the delayed task. Performs all the steps required to setup
a task to run which are not already done. This is mostly code
copied over from convey_task_result.
"""
db_api.start_tx()
try:
workbook_name = task['workbook_name']
execution_id = task['execution_id']
execution = db_api.execution_get(workbook_name, execution_id)
# Change state from DELAYED to IDLE to unblock processing.
WORKFLOW_TRACE.info("Task '%s' [%s -> %s]" %
(task['name'], task['state'], states.IDLE))
db_task = db_api.task_update(workbook_name, execution_id,
task['id'],
{"state": states.IDLE})
task_to_start = [db_task]
data_flow.prepare_tasks(task_to_start, outbound_context)
db_api.commit_tx()
finally:
db_api.end_tx()
if not states.is_stopped_or_finished(execution["state"]):
cls._run_tasks(task_to_start)
def convey_task_result(cls, workbook_name, execution_id,
task_id, state, result):
db_api.start_tx()
workbook = cls._get_workbook(workbook_name)
try:
#TODO(rakhmerov): validate state transition
task = db_api.task_get(workbook_name, execution_id, task_id)
task_output = data_flow.get_task_output(task, result)
# Update task state.
task = db_api.task_update(workbook_name, execution_id, task_id,
{"state": state, "output": task_output})
execution = db_api.execution_get(workbook_name, execution_id)
# Calculate task outbound context.
outbound_context = data_flow.get_outbound_context(task)
cls._create_next_tasks(task, workbook)
# Determine what tasks need to be started.
tasks = db_api.tasks_get(workbook_name, execution_id)
new_exec_state = cls._determine_execution_state(execution, tasks)
if execution['state'] != new_exec_state:
execution = \
db_api.execution_update(workbook_name, execution_id, {
"state": new_exec_state
})
LOG.info("Changed execution state: %s" % execution)
tasks_to_start = workflow.find_resolved_tasks(tasks)
data_flow.prepare_tasks(tasks_to_start, outbound_context)
db_api.commit_tx()
except Exception as e:
raise exc.EngineException("Failed to create necessary DB objects:"
" %s" % e)
finally:
db_api.end_tx()
if states.is_stopped_or_finished(execution["state"]):
return task
if tasks_to_start:
cls._run_tasks(tasks_to_start)
return task
def convey_task_result(self, cntx, **kwargs):
"""Conveys task result to Mistral Engine.
This method should be used by clients of Mistral Engine to update
state of a task once task action has been performed. One of the
clients of this method is Mistral REST API server that receives
task result from the outside action handlers.
Note: calling this method serves an event notifying Mistral that
it possibly needs to move the workflow on, i.e. run other workflow
tasks for which all dependencies are satisfied.
:param cntx: a request context dict
:type cntx: dict
:param kwargs: a dict of method arguments
:type kwargs: dict
:return: Task.
"""
task_id = kwargs.get('task_id')
state = kwargs.get('state')
result = kwargs.get('result')
db_api.start_tx()
try:
# TODO(rakhmerov): validate state transition
task = db_api.task_get(task_id)
workbook = self._get_workbook(task['workbook_name'])
wf_trace_msg = "Task '%s' [%s -> %s" % \
(task['name'], task['state'], state)
wf_trace_msg += ']' if state == states.ERROR \
else ", result = %s]" % result
WORKFLOW_TRACE.info(wf_trace_msg)
action_name = wb_task.TaskSpec(task['task_spec'])\
.get_full_action_name()
if not a_f.get_action_class(action_name):
action = a_f.resolve_adhoc_action_name(workbook, action_name)
if not action:
msg = 'Unknown action [workbook=%s, action=%s]' % \
(workbook, action_name)
raise exc.ActionException(msg)
result = a_f.convert_adhoc_action_result(workbook,
action_name,
result)
task_output = data_flow.get_task_output(task, result)
# Update task state.
task, context = self._update_task(workbook, task, state,
task_output)
execution = db_api.execution_get(task['execution_id'])
self._create_next_tasks(task, workbook)
# Determine what tasks need to be started.
tasks = db_api.tasks_get(execution_id=task['execution_id'])
new_exec_state = self._determine_execution_state(execution, tasks)
if execution['state'] != new_exec_state:
wf_trace_msg = \
"Execution '%s' [%s -> %s]" % \
(execution['id'], execution['state'], new_exec_state)
WORKFLOW_TRACE.info(wf_trace_msg)
execution = db_api.execution_update(execution['id'], {
"state": new_exec_state
})
LOG.info("Changed execution state: %s" % execution)
# Create a list of tasks that can be executed immediately (have
# their requirements satisfied) along with the list of tasks that
# require some delay before they'll be executed.
tasks_to_start, delayed_tasks = workflow.find_resolved_tasks(tasks)
# Populate context with special variables such as `openstack` and
# `__execution`.
self._add_variables_to_data_flow_context(context, execution)
# Update task with new context and params.
executables = data_flow.prepare_tasks(tasks_to_start,
context,
workbook)
db_api.commit_tx()
except Exception as e:
msg = "Failed to create necessary DB objects: %s" % e
LOG.exception(msg)
raise exc.EngineException(msg)
finally:
db_api.end_tx()
if states.is_stopped_or_finished(execution['state']):
return task
for task in delayed_tasks:
self._schedule_run(workbook, task, context)
for task_id, action_name, action_params in executables:
self._run_task(task_id, action_name, action_params)
return task
def convey_task_result(cls, workbook_name, execution_id,
task_id, state, result):
db_api.start_tx()
try:
workbook = cls._get_workbook(workbook_name)
#TODO(rakhmerov): validate state transition
task = db_api.task_get(workbook_name, execution_id, task_id)
wf_trace_msg = "Task '%s' [%s -> %s" % \
(task['name'], task['state'], state)
wf_trace_msg += ']' if state == states.ERROR \
else ", result = %s]" % result
WORKFLOW_TRACE.info(wf_trace_msg)
task_output = data_flow.get_task_output(task, result)
# Update task state.
task, outbound_context = cls._update_task(workbook, task, state,
task_output)
execution = db_api.execution_get(workbook_name, execution_id)
cls._create_next_tasks(task, workbook)
# Determine what tasks need to be started.
tasks = db_api.tasks_get(workbook_name, execution_id)
new_exec_state = cls._determine_execution_state(execution, tasks)
if execution['state'] != new_exec_state:
wf_trace_msg = \
"Execution '%s' [%s -> %s]" % \
(execution_id, execution['state'], new_exec_state)
WORKFLOW_TRACE.info(wf_trace_msg)
execution = \
db_api.execution_update(workbook_name, execution_id, {
"state": new_exec_state
})
LOG.info("Changed execution state: %s" % execution)
tasks_to_start, delayed_tasks = workflow.find_resolved_tasks(tasks)
cls._add_variables_to_data_flow_context(outbound_context,
execution)
data_flow.prepare_tasks(tasks_to_start, outbound_context)
db_api.commit_tx()
except Exception as e:
LOG.exception("Failed to create necessary DB objects.")
raise exc.EngineException("Failed to create necessary DB objects:"
" %s" % e)
finally:
db_api.end_tx()
if states.is_stopped_or_finished(execution["state"]):
return task
for task in delayed_tasks:
cls._schedule_run(workbook, task, outbound_context)
if tasks_to_start:
cls._run_tasks(tasks_to_start)
return task
def convey_task_result(self, cntx, **kwargs):
"""Conveys task result to Mistral Engine.
This method should be used by clients of Mistral Engine to update
state of a task once task action has been performed. One of the
clients of this method is Mistral REST API server that receives
task result from the outside action handlers.
Note: calling this method serves an event notifying Mistral that
it possibly needs to move the workflow on, i.e. run other workflow
tasks for which all dependencies are satisfied.
:param cntx: a request context dict
:type cntx: dict
:param kwargs: a dict of method arguments
:type kwargs: dict
:return: Task.
"""
task_id = kwargs.get('task_id')
state = kwargs.get('state')
result = kwargs.get('result')
db_api.start_tx()
try:
# TODO(rakhmerov): validate state transition
task = db_api.task_get(task_id)
workbook = self._get_workbook(task['workbook_name'])
wf_trace_msg = "Task '%s' [%s -> %s" % \
(task['name'], task['state'], state)
wf_trace_msg += ']' if state == states.ERROR \
else ", result = %s]" % result
WORKFLOW_TRACE.info(wf_trace_msg)
task_output = data_flow.get_task_output(task, result)
# Update task state.
task, outbound_context = self._update_task(workbook, task, state,
task_output)
execution = db_api.execution_get(task['execution_id'])
self._create_next_tasks(task, workbook)
# Determine what tasks need to be started.
tasks = db_api.tasks_get(workbook_name=task['workbook_name'],
execution_id=task['execution_id'])
new_exec_state = self._determine_execution_state(execution, tasks)
if execution['state'] != new_exec_state:
wf_trace_msg = \
"Execution '%s' [%s -> %s]" % \
(execution['id'], execution['state'], new_exec_state)
WORKFLOW_TRACE.info(wf_trace_msg)
execution = \
db_api.execution_update(execution['id'], {
"state": new_exec_state
})
LOG.info("Changed execution state: %s" % execution)
tasks_to_start, delayed_tasks = workflow.find_resolved_tasks(tasks)
self._add_variables_to_data_flow_context(outbound_context,
execution)
data_flow.prepare_tasks(tasks_to_start, outbound_context)
db_api.commit_tx()
except Exception as e:
msg = "Failed to create necessary DB objects: %s" % e
LOG.exception(msg)
raise exc.EngineException(msg)
finally:
db_api.end_tx()
if states.is_stopped_or_finished(execution["state"]):
return task
for task in delayed_tasks:
self._schedule_run(workbook, task, outbound_context)
if tasks_to_start:
self._run_tasks(tasks_to_start)
return task
def convey_task_result(cls, workbook_name, execution_id, task_id, state,
result):
db_api.start_tx()
try:
workbook = cls._get_workbook(workbook_name)
#TODO(rakhmerov): validate state transition
task = db_api.task_get(workbook_name, execution_id, task_id)
wf_trace_msg = "Task '%s' [%s -> %s" % \
(task['name'], task['state'], state)
wf_trace_msg += ']' if state == states.ERROR \
else ", result = %s]" % result
WORKFLOW_TRACE.info(wf_trace_msg)
task_output = data_flow.get_task_output(task, result)
# Update task state.
task, outbound_context = cls._update_task(workbook, task, state,
task_output)
execution = db_api.execution_get(workbook_name, execution_id)
cls._create_next_tasks(task, workbook)
# Determine what tasks need to be started.
tasks = db_api.tasks_get(workbook_name, execution_id)
new_exec_state = cls._determine_execution_state(execution, tasks)
if execution['state'] != new_exec_state:
wf_trace_msg = \
"Execution '%s' [%s -> %s]" % \
(execution_id, execution['state'], new_exec_state)
WORKFLOW_TRACE.info(wf_trace_msg)
execution = \
db_api.execution_update(workbook_name, execution_id, {
"state": new_exec_state
})
LOG.info("Changed execution state: %s" % execution)
tasks_to_start, delayed_tasks = workflow.find_resolved_tasks(tasks)
cls._add_variables_to_data_flow_context(outbound_context,
execution)
data_flow.prepare_tasks(tasks_to_start, outbound_context)
db_api.commit_tx()
except Exception as e:
LOG.exception("Failed to create necessary DB objects.")
raise exc.EngineException("Failed to create necessary DB objects:"
" %s" % e)
finally:
db_api.end_tx()
if states.is_stopped_or_finished(execution["state"]):
return task
for task in delayed_tasks:
cls._schedule_run(workbook, task, outbound_context)
if tasks_to_start:
cls._run_tasks(tasks_to_start)
return task