def get(self, name):
LOG.debug("Fetch workbook [name=%s]" % name)
values = db_api.workbook_get(name)
if not values:
abort(404)
else:
return Workbook.from_dict(values)
def get(self, name):
LOG.debug("Fetch workbook [name=%s]" % name)
values = db_api.workbook_get(name)
if not values:
abort(404)
else:
return Workbook.from_dict(values)
def scheduler_triggers(self, ctx):
LOG.debug('Processing next Scheduler triggers.')
for trigger in sched.get_next_triggers():
wb = db_api.workbook_get(trigger['workbook_name'])
context.set_ctx(trusts.create_context(wb))
try:
task = parser.get_workbook(
wb['definition']).get_trigger_task_name(trigger['name'])
self.engine.start_workflow_execution(wb['name'], task)
finally:
sched.set_next_execution_time(trigger)
context.set_ctx(None)
def scheduler_triggers(self, ctx):
LOG.debug('Processing next Scheduler triggers.')
for trigger in sched.get_next_triggers():
wb = db_api.workbook_get(trigger['workbook_name'])
context.set_ctx(trusts.create_context(wb))
try:
task = parser.get_workbook(
wb['definition']).get_trigger_task_name(trigger['name'])
self.engine.start_workflow_execution(wb['name'], task)
finally:
sched.set_next_execution_time(trigger)
context.set_ctx(None)
def post(self, workbook_name, execution):
"""Create a new Execution."""
LOG.debug("Create execution [workbook_name=%s, execution=%s]" %
(workbook_name, execution))
if (db_api.workbook_get(workbook_name)
and db_api.workbook_definition_get(workbook_name)):
context = None
if execution.context:
context = json.loads(execution.context)
engine = pecan.request.context['engine']
values = engine.start_workflow_execution(execution.workbook_name,
execution.task,
context)
return Execution.from_dict(values)
def _get_workbook(cls, workbook_name):
wb = db_api.workbook_get(workbook_name)
return parser.get_workbook(wb["definition"])
def _add_variables_to_data_flow_context(cls, df_ctx, execution):
db_workbook = db_api.workbook_get(execution['workbook_name'])
data_flow.add_openstack_data_to_context(df_ctx, db_workbook)
data_flow.add_execution_to_context(df_ctx, execution)
def get(self, name):
"""Return the named workbook."""
LOG.debug("Fetch workbook [name=%s]" % name)
values = db_api.workbook_get(name)
return Workbook.from_dict(values)
def _add_variables_to_data_flow_context(cls, context, execution):
db_workbook = db_api.workbook_get(execution['workbook_name'])
data_flow.add_token_to_context(context, db_workbook)
data_flow.add_execution_to_context(context, execution)
def get_all(self, workbook_name):
"""Return all Executions."""
LOG.debug("Fetch executions [workbook_name=%s]" % workbook_name)
if db_api.workbook_get(workbook_name):
return self._get_all(workbook_name=workbook_name)
def _get_workbook(cls, workbook_name):
wb = db_api.workbook_get(workbook_name)
return parser.get_workbook(wb["definition"])
def _add_variables_to_data_flow_context(cls, context, execution):
db_workbook = db_api.workbook_get(execution['workbook_name'])
data_flow.add_token_to_context(context, db_workbook)
data_flow.add_execution_to_context(context, execution)
