def _complete_task(task_ex, task_spec, state):
# Ignore if task already completed.
if states.is_completed(task_ex.state):
return []
_set_task_state(task_ex, state)
data_flow.publish_variables(task_ex, task_spec)
if not task_spec.get_keep_result():
data_flow.destroy_task_result(task_ex)
def complete(self, state, state_info=None):
"""Complete task and set specified state.
Method sets specified task state and runs all necessary post
completion logic such as publishing workflow variables and
scheduling new workflow commands.
:param state: New task state.
:param state_info: New state information (i.e. error message).
"""
assert self.task_ex
# Ignore if task already completed.
if self.is_completed():
return
# If we were unable to change the task state it means that it was
# already changed by a concurrent process. In this case we need to
# skip all regular completion logic like scheduling new tasks,
# running engine commands and publishing.
if not self.set_state(state, state_info):
return
data_flow.publish_variables(self.task_ex, self.task_spec)
if not self.task_spec.get_keep_result():
# Destroy task result.
for ex in self.task_ex.action_executions:
if hasattr(ex, 'output'):
ex.output = {}
self._after_task_complete()
# Ignore DELAYED state.
if self.task_ex.state == states.RUNNING_DELAYED:
return
# If workflow is paused we shouldn't schedule new commands
# and mark task as processed.
if states.is_paused(self.wf_ex.state):
return
wf_ctrl = wf_base.get_controller(self.wf_ex, self.wf_spec)
# Calculate commands to process next.
cmds = wf_ctrl.continue_workflow(task_ex=self.task_ex)
# Mark task as processed after all decisions have been made
# upon its completion.
self.task_ex.processed = True
dispatcher.dispatch_workflow_commands(self.wf_ex, cmds)
def _complete_task(task_ex, task_spec, state):
# Ignore if task already completed.
if states.is_completed(task_ex.state):
return []
_set_task_state(task_ex, state)
data_flow.publish_variables(
task_ex,
task_spec
)
if not task_spec.get_keep_result():
data_flow.destroy_task_result(task_ex)
def complete(self, state, state_info=None):
"""Complete task and set specified state.
Method sets specified task state and runs all necessary post
completion logic such as publishing workflow variables and
scheduling new workflow commands.
:param state: New task state.
:param state_info: New state information (i.e. error message).
"""
assert self.task_ex
# Ignore if task already completed.
if states.is_completed(self.task_ex.state):
return
self.set_state(state, state_info)
data_flow.publish_variables(self.task_ex, self.task_spec)
if not self.task_spec.get_keep_result():
# Destroy task result.
for ex in self.task_ex.action_executions:
if hasattr(ex, 'output'):
ex.output = {}
self._after_task_complete()
# Ignore DELAYED state.
if self.task_ex.state == states.RUNNING_DELAYED:
return
# If workflow is paused we shouldn't schedule new commands
# and mark task as processed.
if states.is_paused(self.wf_ex.state):
return
wf_ctrl = wf_base.get_controller(self.wf_ex, self.wf_spec)
# Calculate commands to process next.
cmds = wf_ctrl.continue_workflow()
# Mark task as processed after all decisions have been made
# upon its completion.
self.task_ex.processed = True
dispatcher.dispatch_workflow_commands(self.wf_ex, cmds)
def _complete_task(task_ex, task_spec, state):
# Ignore if task already completed.
if states.is_completed(task_ex.state):
return []
_set_task_state(task_ex, state)
try:
data_flow.publish_variables(
task_ex,
task_spec
)
except Exception as e:
_set_task_state(task_ex, states.ERROR, state_info=str(e))
if not task_spec.get_keep_result():
data_flow.destroy_task_result(task_ex)
def _complete_task(task_ex, task_spec, state, state_info=None):
# Ignore if task already completed.
if states.is_completed(task_ex.state):
return []
set_task_state(task_ex, state, state_info)
try:
data_flow.publish_variables(
task_ex,
task_spec
)
except Exception as e:
set_task_state(task_ex, states.ERROR, str(e))
if not task_spec.get_keep_result():
data_flow.destroy_task_result(task_ex)
def _complete_task(task_ex, task_spec, state, state_info=None):
# Ignore if task already completed.
if states.is_completed(task_ex.state):
return []
set_task_state(task_ex, state, state_info)
try:
data_flow.publish_variables(task_ex, task_spec)
except exc.MistralException as e:
LOG.error(
'An error while publishing task variables'
' [task_execution_id=%s]: %s', task_ex.id, str(e))
set_task_state(task_ex, states.ERROR, str(e))
if not task_spec.get_keep_result():
data_flow.destroy_task_result(task_ex)
def _complete_task(task_ex, task_spec, state, state_info=None):
# Ignore if task already completed.
if states.is_completed(task_ex.state):
return []
set_task_state(task_ex, state, state_info)
try:
data_flow.publish_variables(task_ex, task_spec)
except exc.MistralException as e:
LOG.error(
'An error while publishing task variables'
' [task_execution_id=%s]: %s',
task_ex.id, str(e)
)
set_task_state(task_ex, states.ERROR, str(e))
if not task_spec.get_keep_result():
data_flow.destroy_task_result(task_ex)
def complete(self, state, state_info=None):
"""Complete task and set specified state.
Method sets specified task state and runs all necessary post
completion logic such as publishing workflow variables and
scheduling new workflow commands.
:param state: New task state.
:param state_info: New state information (i.e. error message).
"""
assert self.task_ex
# Record the current task state.
old_task_state = self.task_ex.state
# Ignore if task already completed.
if self.is_completed():
# Publish task event again so subscribers know
# task completed state is being processed again.
self.notify(old_task_state, self.task_ex.state)
return
# If we were unable to change the task state it means that it was
# already changed by a concurrent process. In this case we need to
# skip all regular completion logic like scheduling new tasks,
# running engine commands and publishing.
if not self.set_state(state, state_info):
return
data_flow.publish_variables(self.task_ex, self.task_spec)
if not self.task_spec.get_keep_result():
# Destroy task result.
for ex in self.task_ex.action_executions:
if hasattr(ex, 'output'):
ex.output = {}
self._after_task_complete()
# Ignore DELAYED state.
if self.task_ex.state == states.RUNNING_DELAYED:
return
# If workflow is paused we shouldn't schedule new commands
# and mark task as processed.
if states.is_paused(self.wf_ex.state):
# Publish task event even if the workflow is paused.
self.notify(old_task_state, self.task_ex.state)
return
wf_ctrl = wf_base.get_controller(self.wf_ex, self.wf_spec)
# Calculate commands to process next.
cmds = wf_ctrl.continue_workflow(task_ex=self.task_ex)
# Check whether the task generated any next tasks.
if any([not commands.is_engine_command(c) for c in cmds]):
self.task_ex.has_next_tasks = True
# Check whether the error is handled.
if self.task_ex.state == states.ERROR:
self.task_ex.error_handled = any([c.handles_error for c in cmds])
# Mark task as processed after all decisions have been made
# upon its completion.
self.task_ex.processed = True
self.register_workflow_completion_check()
self.save_finished_time()
# Publish task event.
self.notify(old_task_state, self.task_ex.state)
dispatcher.dispatch_workflow_commands(self.wf_ex, cmds)
def complete(self, state, state_info=None):
"""Complete task and set specified state.
Method sets specified task state and runs all necessary post
completion logic such as publishing workflow variables and
scheduling new workflow commands.
:param state: New task state.
:param state_info: New state information (i.e. error message).
"""
assert self.task_ex
# Ignore if task already completed.
if self.is_completed():
return
# If we were unable to change the task state it means that it was
# already changed by a concurrent process. In this case we need to
# skip all regular completion logic like scheduling new tasks,
# running engine commands and publishing.
if not self.set_state(state, state_info):
return
data_flow.publish_variables(self.task_ex, self.task_spec)
if not self.task_spec.get_keep_result():
# Destroy task result.
for ex in self.task_ex.action_executions:
if hasattr(ex, 'output'):
ex.output = {}
self._after_task_complete()
# Ignore DELAYED state.
if self.task_ex.state == states.RUNNING_DELAYED:
return
wf_ctrl = wf_base.get_controller(self.wf_ex, self.wf_spec)
# Calculate commands to process next.
cmds = wf_ctrl.continue_workflow(task_ex=self.task_ex)
# Save next task names in DB to avoid evaluating them again
# in the future.
self.task_ex.next_tasks = []
for c in cmds:
if commands.is_engine_command(c):
continue
event = c.triggered_by[0]['event'] if c.triggered_by else None
self.task_ex.next_tasks.append((c.task_spec.get_name(), event))
self.task_ex.has_next_tasks = bool(self.task_ex.next_tasks)
# Check whether the error is handled.
if self.task_ex.state == states.ERROR:
self.task_ex.error_handled = any([c.handles_error for c in cmds])
# If workflow is paused we shouldn't schedule new commands
# and mark task as processed.
if states.is_paused(self.wf_ex.state):
return
# Mark task as processed after all decisions have been made
# upon its completion.
self.task_ex.processed = True
self.register_workflow_completion_check()
dispatcher.dispatch_workflow_commands(self.wf_ex, cmds)
def complete(self, state, state_info=None):
"""Complete task and set specified state.
Method sets specified task state and runs all necessary post
completion logic such as publishing workflow variables and
scheduling new workflow commands.
:param state: New task state.
:param state_info: New state information (i.e. error message).
"""
assert self.task_ex
# Record the current task state.
old_task_state = self.task_ex.state
# Ignore if task already completed.
if self.is_completed():
# Publish task event again so subscribers know
# task completed state is being processed again.
self.notify(old_task_state, self.task_ex.state)
return
# If we were unable to change the task state it means that it was
# already changed by a concurrent process. In this case we need to
# skip all regular completion logic like scheduling new tasks,
# running engine commands and publishing.
if not self.set_state(state, state_info):
return
data_flow.publish_variables(self.task_ex, self.task_spec)
if not self.task_spec.get_keep_result():
# Destroy task result.
for ex in self.task_ex.action_executions:
if hasattr(ex, 'output'):
ex.output = {}
self._after_task_complete()
# Ignore DELAYED state.
if self.task_ex.state == states.RUNNING_DELAYED:
return
# If workflow is paused we shouldn't schedule new commands
# and mark task as processed.
if states.is_paused(self.wf_ex.state):
# Publish task event even if the workflow is paused.
self.notify(old_task_state, self.task_ex.state)
return
wf_ctrl = wf_base.get_controller(self.wf_ex, self.wf_spec)
# Calculate commands to process next.
cmds = wf_ctrl.continue_workflow(task_ex=self.task_ex)
# Check whether the task generated any next tasks.
if any([not commands.is_engine_command(c) for c in cmds]):
self.task_ex.has_next_tasks = True
# Check whether the error is handled.
if self.task_ex.state == states.ERROR:
self.task_ex.error_handled = any([c.handles_error for c in cmds])
# Mark task as processed after all decisions have been made
# upon its completion.
self.task_ex.processed = True
self.register_workflow_completion_check()
self.save_finished_time()
# Publish task event.
self.notify(old_task_state, self.task_ex.state)
dispatcher.dispatch_workflow_commands(self.wf_ex, cmds)
