def get_test_runs_for_test(test_id):
test_id = parse.unquote(test_id)
start_date = _parse_datetimes(flask.request.args.get('start_date', None))
stop_date = _parse_datetimes(flask.request.args.get('stop_date', None))
datetime_resolution = flask.request.args.get('datetime_resolution', 'min')
if datetime_resolution not in ['sec', 'min', 'hour', 'day']:
message = ('Datetime resolution: %s, is not a valid'
' choice' % datetime_resolution)
status_code = 400
return abort(make_response(message, status_code))
with session_scope() as session:
db_test_runs = api.get_test_runs_by_test_test_id(test_id,
session=session,
start_date=start_date,
stop_date=stop_date)
if not db_test_runs:
# NOTE(mtreinish) if no data is returned from the DB just return an
# empty set response, the test_run_aggregator function assumes data
# is present.
return jsonify({'numeric': {}, 'data': {}})
test_runs =\
test_run_aggregator.convert_test_runs_list_to_time_series_dict(
db_test_runs, datetime_resolution)
return jsonify(test_runs)
def test_get_test_runs_test_test_id(self):
run = api.create_run()
test_a = api.create_test('fake_test')
test_b = api.create_test('less_fake_test')
api.create_test_run(test_a.id, run.id, 'success')
api.create_test_run(test_b.id, run.id, 'success')
res = api.get_test_runs_by_test_test_id('less_fake_test')
self.assertEqual(1, len(res))
self.assertEqual(test_b.id, res[0].test_id)
self.assertEqual(run.id, res[0].run_id)
def test_get_test_runs_test_test_id(self):
run = api.create_run()
test_a = api.create_test('fake_test')
test_b = api.create_test('less_fake_test')
api.create_test_run(test_a.id, run.id, 'success')
api.create_test_run(test_b.id, run.id, 'success')
res = api.get_test_runs_by_test_test_id('less_fake_test')
self.assertEqual(1, len(res))
self.assertEqual(test_b.id, res[0].test_id)
self.assertEqual(run.id, res[0].run_id)
def _get_data(test_id, start_date, stop_date):
with session_scope() as session:
db_test_runs = api.get_test_runs_by_test_test_id(
test_id, session=session, start_date=start_date,
stop_date=stop_date)
if not db_test_runs:
# NOTE(mtreinish) if no data is returned from the DB just
# return an empty set response, the test_run_aggregator
# function assumes data is present.
return {'numeric': {}, 'data': {}, 'failed_runs': {}}
test_runs =\
test_run_aggregator.convert_test_runs_list_to_time_series_dict(
db_test_runs, datetime_resolution)
failed_run_ids = [
x.run_id for x in db_test_runs if x.status == 'fail']
failed_runs = api.get_runs_by_ids(failed_run_ids, session=session)
job_names = {}
providers = {}
failed_uuids = [x.uuid for x in failed_runs]
split_uuids = []
if len(failed_uuids) <= 10:
split_uuids = [[x] for x in failed_uuids]
else:
for i in range(0, len(failed_uuids), 10):
end = i + 10
split_uuids.append(failed_uuids[i:end])
for uuids in split_uuids:
change_dict = {}
for uuid in uuids:
metadata = api.get_run_metadata(uuid, session=session)
short_uuid = None
change_num = None
patch_num = None
for meta in metadata:
if meta.key == 'build_short_uuid':
short_uuid = meta.value
elif meta.key == 'build_change':
change_num = meta.value
elif meta.key == 'build_patchset':
patch_num = meta.value
elif meta.key == 'build_name':
job_names[uuid] = meta.value
elif meta.key == 'node_provider':
providers[uuid] = meta.value
# NOTE(mtreinish): If the required metadata fields
# aren't present skip ES lookup
if not short_uuid or not change_num or not patch_num:
continue
global classifier
if classifier:
change_dict[uuid] = {
'change_num': change_num,
'patch_num': patch_num,
'short_uuid': short_uuid,
}
query_thread = threading.Thread(
target=_populate_bug_dict, args=[change_dict])
query_threads.append(query_thread)
query_thread.start()
output = []
for thread in query_threads:
thread.join()
for run in failed_runs:
temp_run = {}
temp_run['provider'] = providers.get(run.uuid)
temp_run['job_name'] = job_names.get(run.uuid)
temp_run['run_at'] = run.run_at.isoformat()
temp_run['artifacts'] = run.artifacts
temp_run['bugs'] = bug_dict.get(run.uuid, [])
output.append(temp_run)
test_runs['failed_runs'] = output
return test_runs
def _get_data(test_id, start_date, stop_date):
with session_scope() as session:
db_test_runs = api.get_test_runs_by_test_test_id(
test_id,
session=session,
start_date=start_date,
stop_date=stop_date)
if not db_test_runs:
# NOTE(mtreinish) if no data is returned from the DB just
# return an empty set response, the test_run_aggregator
# function assumes data is present.
return {'numeric': {}, 'data': {}, 'failed_runs': {}}
test_runs =\
test_run_aggregator.convert_test_runs_list_to_time_series_dict(
db_test_runs, datetime_resolution)
failed_run_ids = [
x.run_id for x in db_test_runs if x.status == 'fail'
]
failed_runs = api.get_runs_by_ids(failed_run_ids, session=session)
job_names = {}
providers = {}
failed_uuids = [x.uuid for x in failed_runs]
split_uuids = []
if len(failed_uuids) <= 10:
split_uuids = [[x] for x in failed_uuids]
else:
for i in range(0, len(failed_uuids), 10):
end = i + 10
split_uuids.append(failed_uuids[i:end])
for uuids in split_uuids:
change_dict = {}
for uuid in uuids:
metadata = api.get_run_metadata(uuid, session=session)
short_uuid = None
change_num = None
patch_num = None
for meta in metadata:
if meta.key == 'build_short_uuid':
short_uuid = meta.value
elif meta.key == 'build_change':
change_num = meta.value
elif meta.key == 'build_patchset':
patch_num = meta.value
elif meta.key == 'build_name':
job_names[uuid] = meta.value
elif meta.key == 'node_provider':
providers[uuid] = meta.value
# NOTE(mtreinish): If the required metadata fields
# aren't present skip ES lookup
if not short_uuid or not change_num or not patch_num:
continue
global classifier
if classifier:
change_dict[uuid] = {
'change_num': change_num,
'patch_num': patch_num,
'short_uuid': short_uuid,
}
query_thread = threading.Thread(target=_populate_bug_dict,
args=[change_dict])
query_threads.append(query_thread)
query_thread.start()
output = []
for thread in query_threads:
thread.join()
for run in failed_runs:
temp_run = {}
temp_run['provider'] = providers.get(run.uuid)
temp_run['job_name'] = job_names.get(run.uuid)
temp_run['run_at'] = run.run_at.isoformat()
temp_run['artifacts'] = run.artifacts
temp_run['bugs'] = bug_dict.get(run.uuid, [])
output.append(temp_run)
test_runs['failed_runs'] = output
return test_runs
