def point_from_locust(self, ts, sid, data):
"""
:type sid: str
:type ts: str
:type data: dict
:rtype: DataPoint
"""
point = DataPoint(int(ts))
point[DataPoint.SOURCE_ID] = sid
overall = KPISet()
for item in data['stats']:
if ts not in item['num_reqs_per_sec']:
continue
kpiset = KPISet()
kpiset[KPISet.SAMPLE_COUNT] = item['num_reqs_per_sec'][ts]
kpiset[KPISet.CONCURRENCY] = data['user_count']
if item['num_requests']:
avg_rt = (item['total_response_time'] / 1000.0) / item['num_requests']
kpiset.sum_rt = item['num_reqs_per_sec'][ts] * avg_rt
point[DataPoint.CURRENT][item['name']] = kpiset
overall.merge_kpis(kpiset)
point[DataPoint.CURRENT][''] = overall
point.recalculate()
return point
def _calculate_datapoints(self, final_pass=False):
if self.master_id is None:
return
data = self.client.get_kpis(self.master_id, self.min_ts)
for label in data:
if label['kpis']:
label['kpis'].pop(-1) # never take last second since it could be incomplete
timestamps = []
for label in data:
if label['label'] == 'ALL':
timestamps.extend([kpi['ts'] for kpi in label['kpis']])
for tstmp in timestamps:
point = DataPoint(tstmp)
for label in data:
for kpi in label['kpis']:
if kpi['ts'] != tstmp:
continue
kpiset = KPISet()
kpiset[KPISet.FAILURES] = kpi['ec']
kpiset[KPISet.CONCURRENCY] = kpi['na']
kpiset[KPISet.SAMPLE_COUNT] = kpi['n']
kpiset.sum_rt += kpi['t_avg'] * kpi['n'] / 1000.0
kpiset.sum_lt += kpi['lt_avg'] * kpi['n'] / 1000.0
point[DataPoint.CURRENT]['' if label['label'] == 'ALL' else label['label']] = kpiset
point.recalculate()
self.min_ts = point[DataPoint.TIMESTAMP] + 1
yield point
def random_datapoint(n):
point = DataPoint(n)
overall = point[DataPoint.CURRENT].get('', KPISet())
overall[KPISet.CONCURRENCY] = r(100)
overall[KPISet.SAMPLE_COUNT] = int(100 * r(1000)) + 1
overall[KPISet.SUCCESSES] = int(overall[KPISet.SAMPLE_COUNT] * random())
overall[KPISet.FAILURES] = overall[KPISet.SAMPLE_COUNT] - overall[KPISet.SUCCESSES]
overall[KPISet.PERCENTILES]['25'] = r(10)
overall[KPISet.PERCENTILES]['50'] = r(20)
overall[KPISet.PERCENTILES]['75'] = r(30)
overall[KPISet.PERCENTILES]['90'] = r(40)
overall[KPISet.PERCENTILES]['99'] = r(50)
overall[KPISet.PERCENTILES]['100'] = r(100)
overall[KPISet.RESP_CODES][rc()] = 1
overall[KPISet.AVG_RESP_TIME] = r(100)
overall[KPISet.AVG_CONN_TIME] = overall[KPISet.AVG_RESP_TIME] / 3.0
overall[KPISet.AVG_LATENCY] = 2.0 * overall[KPISet.AVG_RESP_TIME] / 3.0
cumul = point[DataPoint.CUMULATIVE].get('', KPISet())
cumul.merge(overall)
point.recalculate()
overall[KPISet.AVG_RESP_TIME] = r(100)
overall[KPISet.AVG_CONN_TIME] = overall[KPISet.AVG_RESP_TIME] / 3.0
overall[KPISet.AVG_LATENCY] = 2.0 * overall[KPISet.AVG_RESP_TIME] / 3.0
return point
def point_from_locust(timestamp, sid, data):
"""
:type timestamp: str
:type sid: str
:type data: dict
:rtype: DataPoint
"""
point = DataPoint(int(timestamp))
point[DataPoint.SOURCE_ID] = sid
overall = KPISet()
for item in data['stats']:
if timestamp not in item['num_reqs_per_sec']:
continue
kpiset = KPISet()
kpiset[KPISet.SAMPLE_COUNT] = item['num_reqs_per_sec'][timestamp]
kpiset[KPISet.CONCURRENCY] = data['user_count']
kpiset[KPISet.BYTE_COUNT] = item['total_content_length']
if item['num_requests']:
avg_rt = (item['total_response_time'] / 1000.0) / item['num_requests']
kpiset.sum_rt = item['num_reqs_per_sec'][timestamp] * avg_rt
for err in data['errors'].values():
if err['name'] == item['name']:
new_err = KPISet.error_item_skel(err['error'], None, err['occurences'], KPISet.ERRTYPE_ERROR,
Counter())
KPISet.inc_list(kpiset[KPISet.ERRORS], ("msg", err['error']), new_err)
kpiset[KPISet.FAILURES] += err['occurences']
point[DataPoint.CURRENT][item['name']] = kpiset
overall.merge_kpis(kpiset)
point[DataPoint.CURRENT][''] = overall
point.recalculate()
return point
def merge_datapoints(self, max_full_ts):
for key in sorted(self.join_buffer.keys(), key=lambda x: int(x)):
if int(key) <= max_full_ts:
sec_data = self.join_buffer.pop(key)
self.log.debug("Processing complete second: %s", key)
point = DataPoint(int(key))
for sid, item in iteritems(sec_data):
point.merge_point(self.point_from_locust(key, sid, item))
point.recalculate()
yield point
def merge_datapoints(self, max_full_ts):
reader_id = self.file.name + "@" + str(id(self))
for key in sorted(self.join_buffer.keys(), key=int):
if int(key) <= max_full_ts:
sec_data = self.join_buffer.pop(key)
self.log.debug("Processing complete second: %s", key)
point = DataPoint(int(key))
point[DataPoint.SOURCE_ID] = reader_id
for sid, item in iteritems(sec_data):
point.merge_point(self.point_from_locust(key, sid, item))
point.recalculate()
yield point
def test_report_criteria_without_label(self):
obj = JUnitXMLReporter()
obj.engine = EngineEmul()
obj.parameters = BetterDict()
pass_fail = PassFailStatus()
criteria = DataCriterion(
{
'stop': True,
'fail': True,
'timeframe': -1,
'threshold': '150ms',
'condition': '<',
'subject': 'avg-rt'
}, pass_fail)
pass_fail.criteria.append(criteria)
criteria.is_triggered = True
obj.engine.reporters.append(pass_fail)
path_from_config = tempfile.mktemp(suffix='.xml',
prefix='junit-xml_passfail',
dir=obj.engine.artifacts_dir)
obj.parameters.merge({
"filename": path_from_config,
"data-source": "pass-fail"
})
obj.prepare()
obj.last_second = DataPoint(0)
obj.post_process()
def test_log_messages_samples_count(self):
obj = FinalStatus()
obj.engine = EngineEmul
obj.parameters = BetterDict()
obj.log = logger_mock()
obj.parameters.merge({"failed-labels": False, "percentiles": False, "summary": True, "test-duration":False})
datapoint = DataPoint(None, None)
cumul_data = KPISet.from_dict(
{KPISet.AVG_CONN_TIME: 7.890211417203362e-06,
KPISet.RESP_TIMES: Counter(
{0.0: 32160, 0.001: 24919, 0.002: 1049, 0.003: 630, 0.004: 224, 0.005: 125,
0.006: 73, 0.007: 46, 0.008: 32, 0.009: 20, 0.011: 8, 0.01: 8, 0.017: 3,
0.016: 3, 0.014: 3, 0.013: 3, 0.04: 2, 0.012: 2, 0.079: 1, 0.081: 1,
0.019: 1, 0.015: 1}),
KPISet.ERRORS: [{'msg': 'Forbidden', 'cnt': 7373, 'type': 0,
'urls': Counter({'http://192.168.25.8/': 7373}), KPISet.RESP_CODES: '403'}],
KPISet.STDEV_RESP_TIME: 0.04947974228872108,
KPISet.AVG_LATENCY: 0.0002825639815220692,
KPISet.RESP_CODES: Counter({'304': 29656, '403': 29656, '200': 2}),
KPISet.PERCENTILES: defaultdict(None, {'95.0': 0.001, '0.0': 0.0, '99.9': 0.008, '90.0': 0.001,
'100.0': 0.081, '99.0': 0.003, '50.0': 0.0}),
KPISet.SUCCESSES: 29658,
KPISet.SAMPLE_COUNT: 59314,
KPISet.CONCURRENCY: 0,
KPISet.AVG_RESP_TIME: 0.0005440536804127192,
KPISet.FAILURES: 29656})
datapoint[DataPoint.CUMULATIVE][""] = cumul_data
obj.last_sec = datapoint
obj.post_process()
self.assertEqual("Samples count: 59314, 50.00% failures\n", obj.log.info_buf.getvalue())
def test_prepare_no_filename_in_settings(self):
obj = JUnitXMLReporter()
obj.engine = EngineEmul()
obj.parameters = BetterDict.from_dict({"data-source": "sample-labels"})
obj.prepare()
datapoint = DataPoint(0, [])
cumul_data = KPISet.from_dict({
KPISet.AVG_CONN_TIME: 7.890211417203362e-06,
KPISet.RESP_TIMES: Counter({
0.0: 32160, 0.001: 24919, 0.002: 1049, 0.003: 630, 0.004: 224, 0.005: 125,
0.006: 73, 0.007: 46, 0.008: 32, 0.009: 20, 0.011: 8, 0.01: 8, 0.017: 3,
0.016: 3, 0.014: 3, 0.013: 3, 0.04: 2, 0.012: 2, 0.079: 1, 0.081: 1,
0.019: 1, 0.015: 1
}),
KPISet.ERRORS: [{'msg': 'Forbidden', 'cnt': 7373, 'type': 0,
'urls': Counter({'http://192.168.25.8/': 7373}), KPISet.RESP_CODES: '403'}],
KPISet.STDEV_RESP_TIME: 0.04947974228872108,
KPISet.AVG_LATENCY: 0.0002825639815220692,
KPISet.RESP_CODES: Counter({'304': 29656, '403': 29656, '200': 2}),
KPISet.PERCENTILES: {'95.0': 0.001, '0.0': 0.0, '99.9': 0.008, '90.0': 0.001,
'100.0': 0.081, '99.0': 0.003, '50.0': 0.0},
KPISet.SUCCESSES: 29658,
KPISet.SAMPLE_COUNT: 59314,
KPISet.CONCURRENCY: 0,
KPISet.AVG_RESP_TIME: 0.0005440536804127192,
KPISet.FAILURES: 29656})
datapoint[DataPoint.CUMULATIVE][""] = cumul_data
obj.aggregated_second(datapoint)
obj.post_process()
self.assertTrue(os.path.exists(obj.report_file_path))
def _calculate_datapoints(self, final_pass=False):
if self.master_id is None:
return
try:
data = self.client.get_kpis(self.master_id, self.min_ts)
except URLError as exc:
self.log.warning(
"Failed to get result KPIs, will retry in %s seconds...",
self.client.timeout)
self.log.debug("Full exception: %s", traceback.format_exc())
time.sleep(self.client.timeout)
data = self.client.get_kpis(self.master_id, self.min_ts)
self.log.info("Succeeded with retry")
for label in data:
if label['kpis']:
label['kpis'].pop(
-1) # never take last second since it could be incomplete
timestamps = []
for label in data:
if label['label'] == 'ALL':
timestamps.extend([kpi['ts'] for kpi in label['kpis']])
for tstmp in timestamps:
point = DataPoint(tstmp)
for label in data:
for kpi in label['kpis']:
if kpi['ts'] != tstmp:
continue
kpiset = KPISet()
kpiset[KPISet.FAILURES] = kpi['ec']
kpiset[KPISet.CONCURRENCY] = kpi['na']
kpiset[KPISet.SAMPLE_COUNT] = kpi['n']
kpiset.sum_rt += kpi['t_avg'] * kpi['n'] / 1000.0
kpiset.sum_lt += kpi['lt_avg'] * kpi['n'] / 1000.0
point[
DataPoint.CURRENT]['' if label['label'] ==
'ALL' else label['label']] = kpiset
point.recalculate()
self.min_ts = point[DataPoint.TIMESTAMP] + 1
yield point
def __init__(self):
self.data = DataPoint(0)
self.percentiles = PercentilesList(DataPoint.CURRENT)
self.avg_times = AvgTimesList(DataPoint.CURRENT)
self.rcodes = RCodesList(DataPoint.CURRENT)
original_widget = Columns(
[self.avg_times, self.percentiles, self.rcodes], dividechars=1)
padded = Padding(original_widget, align=CENTER)
super(LatestStats, self).__init__(padded, self.title)
def __init__(self):
self.data = DataPoint(0)
self.percentiles = PercentilesList(DataPoint.CUMULATIVE)
self.avg_times = AvgTimesList(DataPoint.CUMULATIVE)
self.rcodes = RCodesList(DataPoint.CUMULATIVE)
original_widget = Columns(
[self.avg_times, self.percentiles, self.rcodes], dividechars=1)
padded = Padding(original_widget, align=CENTER)
super(CumulativeStats, self).__init__(padded, "Cumulative Stats")
def point_from_locust(timestamp, sid, data):
"""
:type timestamp: str
:type sid: str
:type data: dict
:rtype: DataPoint
"""
point = DataPoint(int(timestamp))
point[DataPoint.SOURCE_ID] = sid
overall = KPISet()
for item in data['stats']:
if timestamp not in item['num_reqs_per_sec']:
continue
kpiset = KPISet()
kpiset[KPISet.SAMPLE_COUNT] = item['num_reqs_per_sec'][timestamp]
kpiset[KPISet.CONCURRENCY] = data['user_count']
kpiset[KPISet.BYTE_COUNT] = item['total_content_length']
if item['num_requests']:
avg_rt = (item['total_response_time'] /
1000.0) / item['num_requests']
kpiset.sum_rt = item['num_reqs_per_sec'][timestamp] * avg_rt
for err in data['errors'].values():
if err['name'] == item['name']:
new_err = KPISet.error_item_skel(err['error'], None,
err['occurences'],
KPISet.ERRTYPE_ERROR,
Counter(), None)
KPISet.inc_list(kpiset[KPISet.ERRORS],
("msg", err['error']), new_err)
kpiset[KPISet.FAILURES] += err['occurences']
kpiset[KPISet.SUCCESSES] = kpiset[KPISet.SAMPLE_COUNT] - kpiset[
KPISet.FAILURES]
point[DataPoint.CURRENT][item['name']] = kpiset
overall.merge_kpis(kpiset, sid)
point[DataPoint.CURRENT][''] = overall
point.recalculate()
return point
def _calculate_datapoints(self, final_pass=False):
if self.master_id is None:
return
try:
data = self.client.get_kpis(self.master_id, self.min_ts)
except URLError:
self.log.warning("Failed to get result KPIs, will retry in %s seconds...", self.client.timeout)
self.log.debug("Full exception: %s", traceback.format_exc())
time.sleep(self.client.timeout)
data = self.client.get_kpis(self.master_id, self.min_ts)
self.log.info("Succeeded with retry")
for label in data:
if label['kpis']:
label['kpis'].pop(-1) # never take last second since it could be incomplete
timestamps = []
for label in data:
if label['label'] == 'ALL':
timestamps.extend([kpi['ts'] for kpi in label['kpis']])
for tstmp in timestamps:
point = DataPoint(tstmp)
for label in data:
for kpi in label['kpis']:
if kpi['ts'] != tstmp:
continue
kpiset = KPISet()
kpiset[KPISet.FAILURES] = kpi['ec']
kpiset[KPISet.CONCURRENCY] = kpi['na']
kpiset[KPISet.SAMPLE_COUNT] = kpi['n']
kpiset.sum_rt += kpi['t_avg'] * kpi['n'] / 1000.0
kpiset.sum_lt += kpi['lt_avg'] * kpi['n'] / 1000.0
point[DataPoint.CURRENT]['' if label['label'] == 'ALL' else label['label']] = kpiset
point.recalculate()
self.min_ts = point[DataPoint.TIMESTAMP] + 1
yield point
def _calculate_datapoints(self, final_pass=False):
if self.master is None:
return
data, aggr_raw = self.query_data()
aggr = {}
for label in aggr_raw:
aggr[label['labelName']] = label
for label in data:
if label.get('kpis') and not final_pass:
label['kpis'].pop(
-1) # never take last second since it could be incomplete
timestamps = []
for label in data:
if label.get('label') == 'ALL':
timestamps.extend([kpi['ts'] for kpi in label.get('kpis', [])])
self.handle_errors = True
for tstmp in timestamps:
point = DataPoint(tstmp)
point[DataPoint.SOURCE_ID] = self.master['id']
self.__generate_kpisets(aggr, data, point, tstmp)
if self.handle_errors:
self.handle_errors = False
self.cur_errors = self.__get_errors_from_bza()
err_diff = self._get_err_diff()
if err_diff:
self.__add_err_diff(point, err_diff)
self.prev_errors = self.cur_errors
point.recalculate()
self.min_ts = point[DataPoint.TIMESTAMP] + 1
yield point
def __init__(self):
self.data = DataPoint(0)
self._start_time = None
self.percentiles = PercentilesList(DataPoint.CUMULATIVE)
self.avg_times = AvgTimesList(DataPoint.CUMULATIVE)
self.rcodes = RCodesList(DataPoint.CUMULATIVE)
self.labels_pile = LabelsPile(DataPoint.CUMULATIVE)
original_widget = Pile([
Columns([self.avg_times, self.percentiles, self.rcodes],
dividechars=1), self.labels_pile
])
padded = Padding(original_widget, align=CENTER)
super(CumulativeStats,
self).__init__(padded, self.title + ': waiting for data...')
def test_short_data(self):
proc = CriteriaProcessor(["failures>0%, stop as failed"], self)
self.obj.processors.append(proc)
point = DataPoint(0)
point[DataPoint.CUMULATIVE] = {}
point[DataPoint.CUMULATIVE][''] = {}
point[DataPoint.CUMULATIVE][''][KPISet.FAILURES] = 100 * 16
point[DataPoint.CUMULATIVE][''][KPISet.SAMPLE_COUNT] = 100 * 16
self.obj.check()
self.obj.shutdown()
self.obj.aggregated_second(point)
self.assertRaises(AutomatedShutdown, self.obj.post_process)
def random_datapoint(n):
point = DataPoint(n)
overall = point[DataPoint.CURRENT].setdefault('', KPISet())
overall[KPISet.CONCURRENCY] = r(100)
overall[KPISet.SAMPLE_COUNT] = int(100 * r(1000)) + 1
overall[KPISet.SUCCESSES] = int(overall[KPISet.SAMPLE_COUNT] * random())
overall[KPISet.FAILURES] = overall[KPISet.SAMPLE_COUNT] - overall[
KPISet.SUCCESSES]
overall[KPISet.BYTE_COUNT] = int(random() * 1000) + 1
overall[KPISet.PERCENTILES]['25.0'] = r(10)
overall[KPISet.PERCENTILES]['50.0'] = r(20)
overall[KPISet.PERCENTILES]['75.0'] = r(30)
overall[KPISet.PERCENTILES]['90.0'] = r(40)
overall[KPISet.PERCENTILES]['99.0'] = r(50)
overall[KPISet.PERCENTILES]['100.0'] = r(100)
overall[KPISet.RESP_CODES][rc()] = 1
overall[KPISet.AVG_RESP_TIME] = r(100)
overall[KPISet.AVG_CONN_TIME] = overall[KPISet.AVG_RESP_TIME] / 3.0
overall[KPISet.AVG_LATENCY] = 2.0 * overall[KPISet.AVG_RESP_TIME] / 3.0
overall.sum_rt = overall[KPISet.AVG_RESP_TIME] * overall[
KPISet.SAMPLE_COUNT]
overall.sum_cn = overall[KPISet.AVG_CONN_TIME] * overall[
KPISet.SAMPLE_COUNT]
overall.sum_lt = overall[KPISet.AVG_LATENCY] * overall[KPISet.SAMPLE_COUNT]
cumul = point[DataPoint.CUMULATIVE].setdefault('', KPISet())
cumul.merge_kpis(overall)
cumul.recalculate()
point.recalculate()
overall[KPISet.AVG_RESP_TIME] = r(100)
overall[KPISet.AVG_CONN_TIME] = overall[KPISet.AVG_RESP_TIME] / 3.0
overall[KPISet.AVG_LATENCY] = 2.0 * overall[KPISet.AVG_RESP_TIME] / 3.0
return point
def test_short_data(self):
crit_cfg = DataCriterion.string_to_config(
"failures>0%, stop as failed")
self.obj.criteria.append(DataCriterion(crit_cfg, self.obj))
point = DataPoint(0)
point[DataPoint.CUMULATIVE] = {}
point[DataPoint.CUMULATIVE][''] = {}
point[DataPoint.CUMULATIVE][''][KPISet.FAILURES] = 100 * 16
point[DataPoint.CUMULATIVE][''][KPISet.SAMPLE_COUNT] = 100 * 16
self.obj.check()
self.obj.shutdown()
self.obj.aggregated_second(point)
self.assertRaises(AutomatedShutdown, self.obj.post_process)
def merge_datapoints(self, max_full_ts):
for key in sorted(self.join_buffer.keys(), key=int):
if int(key) <= max_full_ts:
sec_data = self.join_buffer.pop(key)
self.log.debug("Processing complete second: %s", key)
point = DataPoint(int(key))
for sid, item in iteritems(sec_data):
point.merge_point(self.point_from_locust(key, sid, item))
point.recalculate()
yield point
def test_merging(self):
dst = DataPoint(0)
src = DataPoint(0)
src[DataPoint.CUMULATIVE].setdefault('', KPISet())
src[DataPoint.CUMULATIVE][''].sum_rt = 0.5
src[DataPoint.CUMULATIVE][''][KPISet.SAMPLE_COUNT] = 1
dst.merge_point(src)
self.assertEquals(0.5, dst[DataPoint.CUMULATIVE][''].sum_rt)
self.assertEquals(0.5, dst[DataPoint.CUMULATIVE][''][KPISet.AVG_RESP_TIME])
src[DataPoint.CUMULATIVE][''][KPISet.SAMPLE_COUNT] = 3
dst.merge_point(src)
self.assertEquals(4, dst[DataPoint.CUMULATIVE][''][KPISet.SAMPLE_COUNT])
self.assertEquals(1, dst[DataPoint.CUMULATIVE][''].sum_rt)
self.assertEquals(0.25, dst[DataPoint.CUMULATIVE][''][KPISet.AVG_RESP_TIME])
src[DataPoint.CUMULATIVE][''][KPISet.SAMPLE_COUNT] = 6
dst.merge_point(src)
self.assertEquals(10, dst[DataPoint.CUMULATIVE][''][KPISet.SAMPLE_COUNT])
self.assertEquals(1.5, dst[DataPoint.CUMULATIVE][''].sum_rt)
self.assertEquals(0.15, dst[DataPoint.CUMULATIVE][''][KPISet.AVG_RESP_TIME])
def test_ashort_data(self):
obj = PassFailStatus()
obj.engine = EngineEmul()
crit_cfg = DataCriteria.string_to_config("failures>0%, stop as failed")
obj.criterias.append(DataCriteria(crit_cfg, obj))
point = DataPoint(0)
point[DataPoint.CUMULATIVE] = {}
point[DataPoint.CUMULATIVE][''] = {}
point[DataPoint.CUMULATIVE][''][KPISet.FAILURES] = 100 * 16
point[DataPoint.CUMULATIVE][''][KPISet.SAMPLE_COUNT] = 100 * 16
obj.check()
obj.shutdown()
obj.aggregated_second(point)
self.assertRaises(AutomatedShutdown, obj.post_process)
def __get_datapoint(self, n):
point = DataPoint(n)
overall = point[DataPoint.CURRENT].get('', KPISet())
overall[KPISet.CONCURRENCY] = r(100)
overall[KPISet.SAMPLE_COUNT] = int(100 * r(1000))
overall[KPISet.FAILURES] = overall[KPISet.SAMPLE_COUNT] / 2.0
overall[KPISet.AVG_RESP_TIME] = r(100)
overall[KPISet.AVG_CONN_TIME] = overall[KPISet.AVG_RESP_TIME] / 3.0
overall[KPISet.AVG_LATENCY] = 2.0 * overall[KPISet.AVG_RESP_TIME] / 3.0
overall[KPISet.PERCENTILES]['25'] = r(10)
overall[KPISet.PERCENTILES]['50'] = r(20)
overall[KPISet.PERCENTILES]['75'] = r(30)
overall[KPISet.PERCENTILES]['90'] = r(40)
overall[KPISet.PERCENTILES]['99'] = r(50)
overall[KPISet.PERCENTILES]['100'] = r(100)
overall[KPISet.RESP_CODES][rc()] = 1
return point
def test_merging(self):
dst = DataPoint(0)
src = DataPoint(0)
src[DataPoint.CUMULATIVE].setdefault('', KPISet())
src[DataPoint.CUMULATIVE][''].sum_rt = 0.5
src[DataPoint.CUMULATIVE][''][KPISet.SAMPLE_COUNT] = 1
dst.merge_point(src)
self.assertEquals(0.5, dst[DataPoint.CUMULATIVE][''].sum_rt)
self.assertEquals(0.5, dst[DataPoint.CUMULATIVE][''][KPISet.AVG_RESP_TIME])
src[DataPoint.CUMULATIVE][''][KPISet.SAMPLE_COUNT] = 3
dst.merge_point(src)
self.assertEquals(4, dst[DataPoint.CUMULATIVE][''][KPISet.SAMPLE_COUNT])
self.assertEquals(1, dst[DataPoint.CUMULATIVE][''].sum_rt)
self.assertEquals(0.25, dst[DataPoint.CUMULATIVE][''][KPISet.AVG_RESP_TIME])
src[DataPoint.CUMULATIVE][''][KPISet.SAMPLE_COUNT] = 6
dst.merge_point(src)
self.assertEquals(10, dst[DataPoint.CUMULATIVE][''][KPISet.SAMPLE_COUNT])
self.assertEquals(1.5, dst[DataPoint.CUMULATIVE][''].sum_rt)
self.assertEquals(0.15, dst[DataPoint.CUMULATIVE][''][KPISet.AVG_RESP_TIME])
def test_xml_format_passfail(self):
obj = JUnitXMLReporter()
obj.engine = EngineEmul()
obj.parameters = BetterDict()
obj.engine.provisioning = CloudProvisioning()
obj.engine.provisioning.results_url = "http://test/report/123"
pass_fail1 = PassFailStatus()
fc1_triggered = DataCriterion(
{
'stop': True,
'label': 'Sample 1 Triggered',
'fail': True,
'timeframe': -1,
'threshold': '150ms',
'condition': '<',
'subject': 'avg-rt'
}, pass_fail1)
fc1_not_triggered = DataCriterion(
{
'stop': True,
'label': 'Sample 1 Not Triggered',
'fail': True,
'timeframe': -1,
'threshold': '300ms',
'condition': '>',
'subject': 'avg-rt'
}, pass_fail1)
pass_fail2 = PassFailStatus()
fc2_triggered = DataCriterion(
{
'stop': True,
'label': 'Sample 2 Triggered',
'fail': True,
'timeframe': -1,
'threshold': '150ms',
'condition': '<=',
'subject': 'avg-rt'
}, pass_fail1)
fc2_not_triggered = DataCriterion(
{
'stop': True,
'label': 'Sample 2 Not Triggered',
'fail': True,
'timeframe': -1,
'threshold': '300ms',
'condition': '=',
'subject': 'avg-rt'
}, pass_fail1)
pass_fail1.criteria.append(fc1_triggered)
pass_fail1.criteria.append(fc1_not_triggered)
pass_fail2.criteria.append(fc2_triggered)
pass_fail2.criteria.append(fc2_not_triggered)
fc1_triggered.is_triggered = True
fc2_triggered.is_triggered = True
obj.engine.reporters.append(pass_fail1)
obj.engine.reporters.append(pass_fail2)
obj.engine.reporters.append(BlazeMeterUploader())
path_from_config = tempfile.mktemp(suffix='.xml',
prefix='junit-xml_passfail',
dir=obj.engine.artifacts_dir)
obj.parameters.merge({
"filename": path_from_config,
"data-source": "pass-fail"
})
obj.prepare()
obj.last_second = DataPoint(0)
obj.post_process()
with open(obj.report_file_path, 'rb') as fds:
f_contents = fds.read()
logging.info("File: %s", f_contents)
xml_tree = etree.fromstring(f_contents)
self.assertEqual('testsuites', xml_tree.tag)
suite = xml_tree.getchildren()[0]
self.assertEqual('testsuite', suite.tag)
test_cases = suite.getchildren()
self.assertEqual(4, len(test_cases))
self.assertEqual('testcase', test_cases[0].tag)
self.assertEqual('error', test_cases[0].getchildren()[1].tag)
self.assertEqual('error', test_cases[2].getchildren()[1].tag)
sys_out = test_cases[0].getchildren()[0]
self.assertEqual('system-out', sys_out.tag)
self.assertIn('BlazeMeter report link: http://test/report/123',
sys_out.text)
def test_xml_format_sample_labels(self):
# generate xml, compare hash
obj = JUnitXMLReporter()
obj.engine = EngineEmul()
rep = BlazeMeterUploader()
rep.results_url = "http://report/123"
obj.engine.reporters.append(rep)
obj.parameters = BetterDict()
path_from_config = tempfile.mktemp(suffix='.xml',
prefix='junit-xml-sample-labels',
dir=obj.engine.artifacts_dir)
# data-source: finalstats by default
obj.parameters.merge({"filename": path_from_config})
obj.prepare()
datapoint = DataPoint(0, [])
cumul_data = datapoint[DataPoint.CUMULATIVE]
cumul_data[""] = KPISet.from_dict({
KPISet.AVG_CONN_TIME:
7.890211417203362e-06,
KPISet.RESP_TIMES:
Counter({
0.0: 32160,
0.001: 24919,
0.002: 1049,
0.003: 630,
0.004: 224,
0.005: 125,
0.006: 73,
0.007: 46,
0.008: 32,
0.009: 20,
0.011: 8,
0.01: 8,
0.017: 3,
0.016: 3,
0.014: 3,
0.013: 3,
0.04: 2,
0.012: 2,
0.079: 1,
0.081: 1,
0.019: 1,
0.015: 1
}),
KPISet.ERRORS: [
{
'msg': 'Forbidden',
'cnt': 7300,
'type': 0,
'urls': Counter({'http://192.168.1.1/anotherquery': 7300}),
KPISet.RESP_CODES: '403'
},
{
'msg': 'Assertion failed: text /smth/ not found',
'cnt': 73,
'type': 1,
'urls': Counter({'http://192.168.1.1/anotherquery': 73}),
KPISet.RESP_CODES: '200'
},
],
KPISet.STDEV_RESP_TIME:
0.04947974228872108,
KPISet.AVG_LATENCY:
0.0002825639815220692,
KPISet.RESP_CODES:
Counter({
'304': 29656,
'403': 29656,
'200': 2
}),
KPISet.PERCENTILES: {
'95.0': 0.001,
'0.0': 0.0,
'99.9': 0.008,
'90.0': 0.001,
'100.0': 0.081,
'99.0': 0.003,
'50.0': 0.0
},
KPISet.SUCCESSES:
29658,
KPISet.SAMPLE_COUNT:
59314,
KPISet.CONCURRENCY:
0,
KPISet.AVG_RESP_TIME:
0.0005440536804127192,
KPISet.FAILURES:
29656
})
cumul_data["http://192.168.1.1/somequery"] = KPISet.from_dict({
KPISet.AVG_CONN_TIME:
9.609548856969457e-06,
KPISet.RESP_TIMES:
Counter({
0.0: 17219,
0.001: 11246,
0.002: 543,
0.003: 341,
0.004: 121,
0.005: 66,
0.006: 36,
0.007: 33,
0.008: 18,
0.009: 12,
0.011: 6,
0.01: 5,
0.013: 2,
0.017: 2,
0.012: 2,
0.079: 1,
0.016: 1,
0.014: 1,
0.019: 1,
0.04: 1,
0.081: 1
}),
KPISet.ERRORS: [],
KPISet.STDEV_RESP_TIME:
0.04073402130687656,
KPISet.AVG_LATENCY:
1.7196034796682178e-06,
KPISet.RESP_CODES:
Counter({
'304': 29656,
'200': 2
}),
KPISet.PERCENTILES: {
'95.0': 0.001,
'0.0': 0.0,
'99.9': 0.009,
'90.0': 0.001,
'100.0': 0.081,
'99.0': 0.004,
'50.0': 0.0
},
KPISet.SUCCESSES:
29658,
KPISet.SAMPLE_COUNT:
29658,
KPISet.CONCURRENCY:
0,
KPISet.AVG_RESP_TIME:
0.0005164542450603551,
KPISet.FAILURES:
0
})
cumul_data["http://192.168.1.1/anotherquery"] = KPISet.from_dict({
KPISet.AVG_CONN_TIME:
6.1707580253574335e-06,
KPISet.RESP_TIMES:
Counter({
0.0: 14941,
0.001: 13673,
0.002: 506,
0.003: 289,
0.004: 103,
0.005: 59,
0.006: 37,
0.008: 14,
0.007: 13,
0.009: 8,
0.01: 3,
0.011: 2,
0.016: 2,
0.014: 2,
0.017: 1,
0.013: 1,
0.015: 1,
0.04: 1
}),
KPISet.ERRORS: [
{
'msg': 'Forbidden',
'cnt': 7300,
'type': 0,
'urls': Counter({'http://192.168.1.1/anotherquery': 7300}),
KPISet.RESP_CODES: '403'
},
{
'msg': 'Assertion failed: text /smth/ not found',
'cnt': 73,
'type': 1,
'urls': Counter({'http://192.168.1.1/anotherquery': 73}),
KPISet.RESP_CODES: '200'
},
],
KPISet.STDEV_RESP_TIME:
0.032465137860758844,
KPISet.AVG_LATENCY:
0.0005634272997032645,
KPISet.RESP_CODES:
Counter({'403': 29656}),
KPISet.PERCENTILES: {
'95.0': 0.001,
'0.0': 0.0,
'99.9': 0.008,
'90.0': 0.001,
'100.0': 0.04,
'99.0': 0.003,
'50.0': 0.0
},
KPISet.SUCCESSES:
0,
KPISet.SAMPLE_COUNT:
29656,
KPISet.CONCURRENCY:
0,
KPISet.AVG_RESP_TIME:
0.0005716549770704078,
KPISet.FAILURES:
29656
})
cumul_data["http://192.168.100.100/somequery"] = KPISet.from_dict({
KPISet.AVG_CONN_TIME:
9.609548856969457e-06,
KPISet.RESP_TIMES:
Counter({
0.0: 17219,
0.001: 11246,
0.002: 543,
0.003: 341,
0.004: 121,
0.005: 66,
0.006: 36,
0.007: 33,
0.008: 18,
0.009: 12,
0.011: 6,
0.01: 5,
0.013: 2,
0.017: 2,
0.012: 2,
0.079: 1,
0.016: 1,
0.014: 1,
0.019: 1,
0.04: 1,
0.081: 1
}),
KPISet.ERRORS: [],
KPISet.STDEV_RESP_TIME:
0.04073402130687656,
KPISet.AVG_LATENCY:
1.7196034796682178e-06,
KPISet.RESP_CODES:
Counter({
'304': 29656,
'200': 2
}),
KPISet.PERCENTILES: {
'95.0': 0.001,
'0.0': 0.0,
'99.9': 0.009,
'90.0': 0.001,
'100.0': 0.081,
'99.0': 0.004,
'50.0': 0.0
},
KPISet.SUCCESSES:
29658,
KPISet.SAMPLE_COUNT:
29658,
KPISet.CONCURRENCY:
0,
KPISet.AVG_RESP_TIME:
0.0005164542450603551,
KPISet.FAILURES:
0
})
obj.aggregated_second(datapoint)
obj.post_process()
with open(obj.report_file_path, 'rb') as fds:
f_contents = fds.read()
logging.info("File: %s", f_contents)
xml_tree = etree.fromstring(f_contents)
self.assertEqual('testsuites', xml_tree.tag)
suite = xml_tree.getchildren()[0]
self.assertEqual('testsuite', suite.tag)
self.assertListEqual(['sample_labels', "bzt"], suite.values())
test_cases = suite.getchildren()
self.assertEqual(3, len(test_cases))
self.assertEqual('testcase', test_cases[0].tag)
self.assertEqual('error', test_cases[0].getchildren()[1].tag)
self.assertEqual('failure', test_cases[0].getchildren()[2].tag)
self.assertEqual('system-out', test_cases[0].getchildren()[0].tag)
self.assertIn('BlazeMeter report link: http://report/123',
test_cases[0].getchildren()[0].text)
def test_log_messages_failed_labels(self):
obj = FinalStatus()
obj.engine = EngineEmul
obj.parameters = BetterDict()
obj.log = logger_mock()
obj.parameters.merge({
"failed-labels": True,
"percentiles": False,
"summary": False
})
datapoint = DataPoint(None, None)
cumul_data = datapoint[DataPoint.CUMULATIVE]
cumul_data[""] = KPISet.from_dict({
KPISet.AVG_CONN_TIME:
7.890211417203362e-06,
KPISet.RESP_TIMES:
Counter({
0.0: 32160,
0.001: 24919,
0.002: 1049,
0.003: 630,
0.004: 224,
0.005: 125,
0.006: 73,
0.007: 46,
0.008: 32,
0.009: 20,
0.011: 8,
0.01: 8,
0.017: 3,
0.016: 3,
0.014: 3,
0.013: 3,
0.04: 2,
0.012: 2,
0.079: 1,
0.081: 1,
0.019: 1,
0.015: 1
}),
KPISet.ERRORS: [{
'msg':
'Forbidden',
'cnt':
7373,
'type':
0,
'urls':
Counter({'http://192.168.1.1/anotherquery': 7373}),
KPISet.RESP_CODES:
'403'
}],
KPISet.STDEV_RESP_TIME:
0.04947974228872108,
KPISet.AVG_LATENCY:
0.0002825639815220692,
KPISet.RESP_CODES:
Counter({
'304': 29656,
'403': 29656,
'200': 2
}),
KPISet.PERCENTILES:
defaultdict(
None, {
'95.0': 0.001,
'0.0': 0.0,
'99.9': 0.008,
'90.0': 0.001,
'100.0': 0.081,
'99.0': 0.003,
'50.0': 0.0
}),
KPISet.SUCCESSES:
29658,
KPISet.SAMPLE_COUNT:
59314,
KPISet.CONCURRENCY:
0,
KPISet.AVG_RESP_TIME:
0.0005440536804127192,
KPISet.FAILURES:
29656
})
cumul_data["http://192.168.1.1/somequery"] = KPISet.from_dict({
KPISet.AVG_CONN_TIME:
9.609548856969457e-06,
KPISet.RESP_TIMES:
Counter({
0.0: 17219,
0.001: 11246,
0.002: 543,
0.003: 341,
0.004: 121,
0.005: 66,
0.006: 36,
0.007: 33,
0.008: 18,
0.009: 12,
0.011: 6,
0.01: 5,
0.013: 2,
0.017: 2,
0.012: 2,
0.079: 1,
0.016: 1,
0.014: 1,
0.019: 1,
0.04: 1,
0.081: 1
}),
KPISet.ERRORS: [],
KPISet.STDEV_RESP_TIME:
0.04073402130687656,
KPISet.AVG_LATENCY:
1.7196034796682178e-06,
KPISet.RESP_CODES:
Counter({
'304': 29656,
'200': 2
}),
KPISet.PERCENTILES:
defaultdict(
None, {
'95.0': 0.001,
'0.0': 0.0,
'99.9': 0.009,
'90.0': 0.001,
'100.0': 0.081,
'99.0': 0.004,
'50.0': 0.0
}),
KPISet.SUCCESSES:
29658,
KPISet.SAMPLE_COUNT:
29658,
KPISet.CONCURRENCY:
0,
KPISet.AVG_RESP_TIME:
0.0005164542450603551,
KPISet.FAILURES:
0
})
cumul_data["http://192.168.1.1/anotherquery"] = KPISet.from_dict({
KPISet.AVG_CONN_TIME:
6.1707580253574335e-06,
KPISet.RESP_TIMES:
Counter({
0.0: 14941,
0.001: 13673,
0.002: 506,
0.003: 289,
0.004: 103,
0.005: 59,
0.006: 37,
0.008: 14,
0.007: 13,
0.009: 8,
0.01: 3,
0.011: 2,
0.016: 2,
0.014: 2,
0.017: 1,
0.013: 1,
0.015: 1,
0.04: 1
}),
KPISet.ERRORS: [{
'msg':
'Forbidden',
'cnt':
7373,
'type':
0,
'urls':
Counter({'http://192.168.1.1/anotherquery': 7373}),
KPISet.RESP_CODES:
'403'
}],
KPISet.STDEV_RESP_TIME:
0.032465137860758844,
KPISet.AVG_LATENCY:
0.0005634272997032645,
KPISet.RESP_CODES:
Counter({'403': 29656}),
KPISet.PERCENTILES:
defaultdict(
None, {
'95.0': 0.001,
'0.0': 0.0,
'99.9': 0.008,
'90.0': 0.001,
'100.0': 0.04,
'99.0': 0.003,
'50.0': 0.0
}),
KPISet.SUCCESSES:
0,
KPISet.SAMPLE_COUNT:
29656,
KPISet.CONCURRENCY:
0,
KPISet.AVG_RESP_TIME:
0.0005716549770704078,
KPISet.FAILURES:
29656
})
cumul_data["http://192.168.100.100/somequery"] = KPISet.from_dict({
KPISet.AVG_CONN_TIME:
9.609548856969457e-06,
KPISet.RESP_TIMES:
Counter({
0.0: 17219,
0.001: 11246,
0.002: 543,
0.003: 341,
0.004: 121,
0.005: 66,
0.006: 36,
0.007: 33,
0.008: 18,
0.009: 12,
0.011: 6,
0.01: 5,
0.013: 2,
0.017: 2,
0.012: 2,
0.079: 1,
0.016: 1,
0.014: 1,
0.019: 1,
0.04: 1,
0.081: 1
}),
KPISet.ERRORS: [],
KPISet.STDEV_RESP_TIME:
0.04073402130687656,
KPISet.AVG_LATENCY:
1.7196034796682178e-06,
KPISet.RESP_CODES:
Counter({
'304': 29656,
'200': 2
}),
KPISet.PERCENTILES:
defaultdict(
None, {
'95.0': 0.001,
'0.0': 0.0,
'99.9': 0.009,
'90.0': 0.001,
'100.0': 0.081,
'99.0': 0.004,
'50.0': 0.0
}),
KPISet.SUCCESSES:
29658,
KPISet.SAMPLE_COUNT:
29658,
KPISet.CONCURRENCY:
0,
KPISet.AVG_RESP_TIME:
0.0005164542450603551,
KPISet.FAILURES:
0
})
obj.last_sec = datapoint
obj.post_process()
self.assertEqual(
"29656 failed samples: http://192.168.1.1/anotherquery\n",
obj.log.info_buf.getvalue())
def test_xml_format_passfail(self):
obj = JUnitXMLReporter()
obj.engine = EngineEmul()
obj.parameters = BetterDict()
pass_fail1 = PassFailStatus()
fc1_triggered = DataCriteria(
{
'stop': True,
'label': 'Sample 1 Triggered',
'fail': True,
'timeframe': -1,
'threshold': '150ms',
'condition': '<',
'subject': 'avg-rt'
}, pass_fail1)
fc1_not_triggered = DataCriteria(
{
'stop': True,
'label': 'Sample 1 Not Triggered',
'fail': True,
'timeframe': -1,
'threshold': '300ms',
'condition': '>',
'subject': 'avg-rt'
}, pass_fail1)
pass_fail2 = PassFailStatus()
fc2_triggered = DataCriteria(
{
'stop': True,
'label': 'Sample 2 Triggered',
'fail': True,
'timeframe': -1,
'threshold': '150ms',
'condition': '<=',
'subject': 'avg-rt'
}, pass_fail1)
fc2_not_triggered = DataCriteria(
{
'stop': True,
'label': 'Sample 2 Not Triggered',
'fail': True,
'timeframe': -1,
'threshold': '300ms',
'condition': '=',
'subject': 'avg-rt'
}, pass_fail1)
pass_fail1.criterias.append(fc1_triggered)
pass_fail1.criterias.append(fc1_not_triggered)
pass_fail2.criterias.append(fc2_triggered)
pass_fail2.criterias.append(fc2_not_triggered)
fc1_triggered.is_triggered = True
fc2_triggered.is_triggered = True
obj.engine.reporters.append(pass_fail1)
obj.engine.reporters.append(pass_fail2)
obj.engine.reporters.append(object())
path_from_config = tempfile.mktemp(suffix='.xml',
prefix='junit-xml_passfail',
dir=obj.engine.artifacts_dir)
obj.parameters.merge({
"filename": path_from_config,
"data-source": "pass-fail"
})
obj.prepare()
obj.last_second = DataPoint(0)
obj.post_process()
with open(obj.report_file_path, 'rb') as fds:
f_contents = fds.read()
xml_tree = etree.fromstring(f_contents)
self.assertEqual('testsuite', xml_tree.tag)
self.assertEqual(4, len(xml_tree.getchildren()))
self.assertEqual('testcase', xml_tree.getchildren()[0].tag)
self.assertEqual('error',
xml_tree.getchildren()[0].getchildren()[0].tag)
self.assertEqual('error',
xml_tree.getchildren()[2].getchildren()[0].tag)
def __get_datapoint(self):
datapoint = DataPoint(None, None)
cumul_data = datapoint[DataPoint.CUMULATIVE]
cumul_data[""] = KPISet.from_dict({
KPISet.AVG_CONN_TIME:
7.890211417203362e-06,
KPISet.RESP_TIMES:
Counter({
0.0: 32160,
0.001: 24919,
0.002: 1049,
0.003: 630,
0.004: 224,
0.005: 125,
0.006: 73,
0.007: 46,
0.008: 32,
0.009: 20,
0.011: 8,
0.01: 8,
0.017: 3,
0.016: 3,
0.014: 3,
0.013: 3,
0.04: 2,
0.012: 2,
0.079: 1,
0.081: 1,
0.019: 1,
0.015: 1
}),
KPISet.ERRORS: [{
'msg':
'Forbidden',
'cnt':
7373,
'type':
0,
'urls':
Counter({'http://192.168.1.1/anotherquery': 7373}),
KPISet.RESP_CODES:
'403'
}],
KPISet.STDEV_RESP_TIME:
0.04947974228872108,
KPISet.AVG_LATENCY:
0.0002825639815220692,
KPISet.RESP_CODES:
Counter({
'304': 29656,
'403': 29656,
'200': 2
}),
KPISet.PERCENTILES: {
'95.0': 0.001,
'0.0': 0.0,
'99.9': 0.008,
'90.0': 0.001,
'100.0': 0.081,
'99.0': 0.003,
'50.0': 0.0
},
KPISet.SUCCESSES:
29658,
KPISet.SAMPLE_COUNT:
59314,
KPISet.CONCURRENCY:
0,
KPISet.AVG_RESP_TIME:
0.0005440536804127192,
KPISet.FAILURES:
29656
})
cumul_data["http://192.168.1.1/somequery"] = KPISet.from_dict({
KPISet.AVG_CONN_TIME:
9.609548856969457e-06,
KPISet.RESP_TIMES:
Counter({
0.0: 17219,
0.001: 11246,
0.002: 543,
0.003: 341,
0.004: 121,
0.005: 66,
0.006: 36,
0.007: 33,
0.008: 18,
0.009: 12,
0.011: 6,
0.01: 5,
0.013: 2,
0.017: 2,
0.012: 2,
0.079: 1,
0.016: 1,
0.014: 1,
0.019: 1,
0.04: 1,
0.081: 1
}),
KPISet.ERRORS: [],
KPISet.STDEV_RESP_TIME:
0.04073402130687656,
KPISet.AVG_LATENCY:
1.7196034796682178e-06,
KPISet.RESP_CODES:
Counter({
'304': 29656,
'200': 2
}),
KPISet.PERCENTILES: {
'95.0': 0.001,
'0.0': 0.0,
'99.9': 0.009,
'90.0': 0.001,
'100.0': 0.081,
'99.0': 0.004,
'50.0': 0.0
},
KPISet.SUCCESSES:
29658,
KPISet.SAMPLE_COUNT:
29658,
KPISet.CONCURRENCY:
0,
KPISet.AVG_RESP_TIME:
0.0005164542450603551,
KPISet.FAILURES:
0
})
cumul_data["http://192.168.1.1/anotherquery"] = KPISet.from_dict({
KPISet.AVG_CONN_TIME:
6.1707580253574335e-06,
KPISet.RESP_TIMES:
Counter({
0.0: 14941,
0.001: 13673,
0.002: 506,
0.003: 289,
0.004: 103,
0.005: 59,
0.006: 37,
0.008: 14,
0.007: 13,
0.009: 8,
0.01: 3,
0.011: 2,
0.016: 2,
0.014: 2,
0.017: 1,
0.013: 1,
0.015: 1,
0.04: 1
}),
KPISet.ERRORS: [{
'msg':
'Forbidden',
'cnt':
7373,
'type':
0,
'urls':
Counter({'http://192.168.1.1/anotherquery': 7373}),
KPISet.RESP_CODES:
'403'
}],
KPISet.STDEV_RESP_TIME:
0.032465137860758844,
KPISet.AVG_LATENCY:
0.0005634272997032645,
KPISet.RESP_CODES:
Counter({'403': 29656}),
KPISet.PERCENTILES: {
'95.0': 0.001,
'0.0': 0.0,
'99.9': 0.008,
'90.0': 0.001,
'100.0': 0.04,
'99.0': 0.003,
'50.0': 0.0
},
KPISet.SUCCESSES:
0,
KPISet.SAMPLE_COUNT:
29656,
KPISet.CONCURRENCY:
0,
KPISet.AVG_RESP_TIME:
0.0005716549770704078,
KPISet.FAILURES:
29656
})
cumul_data["http://192.168.100.100/somequery"] = KPISet.from_dict({
KPISet.AVG_CONN_TIME:
9.609548856969457e-06,
KPISet.RESP_TIMES:
Counter({
0.0: 17219,
0.001: 11246,
0.002: 543,
0.003: 341,
0.004: 121,
0.005: 66,
0.006: 36,
0.007: 33,
0.008: 18,
0.009: 12,
0.011: 6,
0.01: 5,
0.013: 2,
0.017: 2,
0.012: 2,
0.079: 1,
0.016: 1,
0.014: 1,
0.019: 1,
0.04: 1,
0.081: 1
}),
KPISet.ERRORS: [],
KPISet.STDEV_RESP_TIME:
0.04073402130687656,
KPISet.AVG_LATENCY:
1.7196034796682178e-06,
KPISet.RESP_CODES:
Counter({
'304': 29656,
'200': 2
}),
KPISet.PERCENTILES: {
'95.0': 0.001,
'0.0': 0.0,
'99.9': 0.009,
'90.0': 0.001,
'100.0': 0.081,
'99.0': 0.004,
'50.0': 0.0
},
KPISet.SUCCESSES:
29658,
KPISet.SAMPLE_COUNT:
29658,
KPISet.CONCURRENCY:
0,
KPISet.AVG_RESP_TIME:
0.0005164542450603551,
KPISet.FAILURES:
0
})
return datapoint
