def get_runs_by_run_metadata_key(run_metadata_key, value):
run_metadata_key = parse.unquote(run_metadata_key)
value = parse.unquote(value)
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', 'day')
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:
runs = (api.get_time_series_runs_by_key_value(run_metadata_key,
value,
start_date,
stop_date,
session))
# Groups runs by metadata
group_by = "build_name"
runs_by_build_name = _group_runs_by_key(runs, group_by)
# Group runs by the chosen data_range.
# That does not apply when you choose 'sec' since runs are already
# grouped by it.
aggregated_runs = \
RunAggregator(runs_by_build_name).aggregate(datetime_resolution)
return jsonify(_aggregate_runs(aggregated_runs))
def test_get_time_series_runs_by_key_value(self):
runs = []
run_at = datetime.datetime.utcnow()
for run_num in moves.range(15):
run = api.create_run(run_num,
run_num + 1,
run_num + 2,
3,
run_at=run_at)
runs.append(run)
run_meta = {'test_key': 'fun', 'non_test': 'value-%s' % run_num}
if run_num >= 3:
run_meta = {
'test_key': 'no-fun',
'non_test': 'value-%s' % run_num
}
api.add_run_metadata(run_meta, run.id)
runs_time_series = api.get_time_series_runs_by_key_value(
'test_key', 'fun')
self.assertEqual(1, len(runs_time_series))
timestamp = list(runs_time_series.keys())[0]
self.assertEqual(3, len(runs_time_series[timestamp]))
for run_num in moves.range(3):
run_dict = {
'skip': run_num,
'fail': run_num + 1,
'pass': run_num + 2,
'id': runs[run_num].uuid,
'run_time': 3.0,
'metadata': {
u'test_key': u'fun',
u'non_test': u'value-%s' % run_num
}
}
self.assertIn(run_dict, runs_time_series[timestamp])
for run_num in moves.range(3, 14):
missing_run_dict = {
'skip': run_num,
'fail': run_num + 1,
'pass': run_num + 2,
'id': runs[run_num].id,
'run_time': 3.0,
'metadata': {
u'test_key': u'fun',
u'non_test': u'value-%s' % run_num
}
}
self.assertNotIn(missing_run_dict, runs_time_series[timestamp])
def get_runs_by_run_metadata_key(run_metadata_key, value):
run_metadata_key = parse.unquote(run_metadata_key)
value = parse.unquote(value)
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', 'day')
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:
runs = (api.get_time_series_runs_by_key_value(run_metadata_key, value,
start_date, stop_date,
session))
# prepare run_times to be consumed for producing 'numeric' data.
run_times = {}
for run_at, run_data in runs.items():
for run in run_data:
if run['fail'] > 0 or run['pass'] == 0:
continue
build_name = run['metadata']['build_name']
if run_at in run_times:
if build_name in run_times[run_at]:
run_times[run_at][build_name].append(run['run_time'])
else:
run_times[run_at][build_name] = [run['run_time']]
else:
run_times[run_at] = {build_name: [run['run_time']]}
# if there is more than one run with the same run_at time
# and build_name just average the results.
for run_at, run_time_data in run_times.items():
for build_name, times in run_time_data.items():
run_times[run_at][build_name] = numpy.mean(times)
numeric = run_aggregator.get_numeric_data(run_times,
datetime_resolution)
# Groups runs by metadata
group_by = "build_name"
runs_by_build_name = _group_runs_by_key(runs, group_by)
# Group runs by the chosen data_range.
# That does not apply when you choose 'sec' since runs are already
# grouped by it.
aggregated_runs = run_aggregator.RunAggregator(
runs_by_build_name).aggregate(datetime_resolution)
data = _aggregate_runs(aggregated_runs)
return jsonify({'numeric': numeric, 'data': data})
def test_get_time_series_runs_by_key_value(self):
runs = []
run_at = datetime.datetime.utcnow()
for run_num in moves.range(15):
run = api.create_run(run_num, run_num + 1, run_num + 2, 3,
run_at=run_at)
runs.append(run)
run_meta = {'test_key': 'fun', 'non_test': 'value-%s' % run_num}
if run_num >= 3:
run_meta = {'test_key': 'no-fun',
'non_test': 'value-%s' % run_num}
api.add_run_metadata(run_meta, run.id)
runs_time_series = api.get_time_series_runs_by_key_value('test_key',
'fun')
self.assertEqual(1, len(runs_time_series))
timestamp = list(runs_time_series.keys())[0]
self.assertEqual(3, len(runs_time_series[timestamp]))
for run_num in moves.range(3):
run_dict = {
'skip': run_num,
'fail': run_num + 1,
'pass': run_num + 2,
'id': runs[run_num].uuid,
'run_time': 3.0,
'metadata': {
u'test_key': u'fun',
u'non_test': u'value-%s' % run_num
}
}
self.assertIn(run_dict, runs_time_series[timestamp])
for run_num in moves.range(3, 14):
missing_run_dict = {
'skip': run_num,
'fail': run_num + 1,
'pass': run_num + 2,
'id': runs[run_num].id,
'run_time': 3.0,
'metadata': {
u'test_key': u'fun',
u'non_test': u'value-%s' % run_num
}
}
self.assertNotIn(missing_run_dict, runs_time_series[timestamp])
