def run(self, node_args):
"""To be transparently called by Selinon.
Selinon transparently calls run(), which takes care of task audit and
some additional checks and calls execute().
"""
# SQS guarantees 'deliver at least once', so there could be multiple
# messages of a type, give up immediately
if self.storage and isinstance(self.storage,
(BayesianPostgres, PackagePostgres)):
if self.storage.get_worker_id_count(self.task_id) > 0:
raise TaskAlreadyExistsError("Task with ID '%s'"
" was already processed" %
self.task_id)
start = datetime.utcnow()
try:
result = self.execute(node_args)
finally:
# remove all files that were downloaded for this task
ObjectCache.wipe()
end = datetime.utcnow()
if result:
# Ensure result complies with the defined schema (if any) before saving
self.validate_result(result)
if result is None:
# Keep track of None results and add _audit and _release keys
result = {}
if self.add_audit_info:
# `_audit` key is added to every analysis info submitted
result['_audit'] = {
'started_at': json_serial(start),
'ended_at': json_serial(end),
'version': 'v1'
}
ecosystem_name = node_args.get('ecosystem')
result['_release'] = '{}:{}:{}'.format(ecosystem_name,
node_args.get('name'),
node_args.get('version'))
return result
def run(self, node_args):
"""To be transparently called by Selinon.
Selinon transparently calls run(), which takes care of task audit and
some additional checks and calls execute().
"""
# SQS guarantees 'deliver at least once', so there could be multiple
# messages of a type, give up immediately
if self.storage and isinstance(self.storage, (BayesianPostgres, PackagePostgres)):
if self.storage.get_worker_id_count(self.task_id) > 0:
raise TaskAlreadyExistsError("Task with ID '%s'"
" was already processed" % self.task_id)
start = datetime.utcnow()
try:
result = self.execute(node_args)
except Exception as exc:
if self.add_audit_info:
# `_audit` key is added to every analysis info submitted
end = datetime.utcnow()
result = dict()
self._add_audit_info(
task_result=result,
task_start=start,
task_end=end,
node_args=node_args,
)
# write the audit info to the storage
self.storage.store_error(
node_args=node_args,
flow_name=self.flow_name,
task_name=self.task_name,
task_id=self.task_id,
exc_info=sys.exc_info(),
result=result
)
raise exc
finally:
# remove all files that were downloaded for this task
ObjectCache.wipe()
end = datetime.utcnow()
if result:
# Ensure result complies with the defined schema (if any) before saving
self.validate_result(result)
if result is None:
# Keep track of None results and add _audit and _release keys
result = {}
if self.add_audit_info:
# `_audit` key is added to every analysis info submitted
self._add_audit_info(
task_result=result,
task_start=start,
task_end=end,
node_args=node_args,
)
return result
