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 new():
subj = KPISet(perc_levels=(100.0,))
subj[KPISet.RESP_TIMES].add(0.1)
subj[KPISet.RESP_TIMES].add(0.01)
subj[KPISet.RESP_TIMES].add(0.001)
subj.recalculate()
return subj
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 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 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 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
point[DataPoint.CURRENT][item['name']] = kpiset
overall.merge_kpis(kpiset)
point[DataPoint.CURRENT][''] = overall
point.recalculate()
return point
def __get_kpi_errors(self, errors):
result = []
for msg in errors:
kpi_error = KPISet.error_item_skel(
error=msg,
ret_c=errors[msg]['rc'],
cnt=errors[msg]['count'],
errtype=KPISet.ERRTYPE_ERROR, # TODO: what about asserts?
urls=Counter(), tag=None)
result.append(kpi_error)
return result
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 test_kpiset_merge_many_rtimes(self):
vals = {
round(random() * 20 + 0.1,
int(random() * 3) + 2): int(random() * 3 + 1)
for _ in range(1000)
}
src = KPISet()
src[KPISet.RESP_TIMES].update(vals)
dst = KPISet()
dst.rtimes_len = 100
for _ in range(100):
dst.merge_kpis(src)
dst.compact_times()
self.assertEqual(100, len(dst[KPISet.RESP_TIMES]))
def __get_kpiset(self, aggr, kpi, label):
kpiset = KPISet()
kpiset[KPISet.FAILURES] = kpi['ec']
kpiset[KPISet.CONCURRENCY] = kpi['na']
kpiset[KPISet.SAMPLE_COUNT] = kpi['n']
assert kpi['n'] > 0 and kpi['n'] >= kpi['ec']
kpiset[KPISet.SUCCESSES] = kpi['n'] - kpi['ec']
kpiset.sum_rt += kpi['t_avg'] * kpi['n'] / 1000.0
kpiset.sum_lt += kpi['lt_avg'] * kpi['n'] / 1000.0
perc_map = {'90line': 90.0, "95line": 95.0, "99line": 99.0}
for field, level in iteritems(perc_map):
kpiset[KPISet.PERCENTILES][str(level)] = aggr[label][field] / 1000.0
return kpiset
def __add_err_diff(self, point, err_diff):
for label in err_diff:
point_label = '' if label == 'ALL' else label
if point_label not in point[DataPoint.CURRENT]:
self.log.warning("Got inconsistent kpi/error data for label: %s", point_label)
kpiset = KPISet()
point[DataPoint.CURRENT][point_label] = kpiset
kpiset[KPISet.SAMPLE_COUNT] = sum([item['count'] for item in err_diff[label].values()])
else:
kpiset = point[DataPoint.CURRENT][point_label]
kpiset[KPISet.ERRORS] = self.__get_kpi_errors(err_diff[label])
kpiset[KPISet.FAILURES] = sum([x['cnt'] for x in kpiset[KPISet.ERRORS]])
kpiset[KPISet.SAMPLE_COUNT] = kpiset[KPISet.SUCCESSES] + kpiset[KPISet.FAILURES]
assert kpiset[KPISet.SAMPLE_COUNT] > 0, point_label
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 add_data(self, data):
"""
Append data
:type data: bzt.modules.aggregator.DataPoint
"""
while len(self.body):
self.body.pop(0)
self.body.append(Text(("stat-hdr", " Percentiles: "), align=RIGHT))
overall = data.get(self.key).get('', KPISet())
for key in sorted(overall.get(KPISet.PERCENTILES).keys(), key=float):
dat = (float(key), overall[KPISet.PERCENTILES][key])
self.body.append(
Text(("stat-txt", "%.1f%%: %.3f" % dat), align=RIGHT))
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 _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 __extend_reported_data(dp_list):
for dp in dp_list:
for data in dp['cumulative'], dp['current']:
del data['']
for key in list(
data.keys()
): # list() is important due to changing dictionary size in the cycle
sep = key.rindex('-')
original_label, state_idx = key[:sep], int(key[sep + 1:])
kpi_set = data.pop(key)
if original_label not in data:
data[original_label] = {}
data[original_label][state_idx] = kpi_set
if '' not in data:
data[''] = dict()
if state_idx not in data['']:
data[''][state_idx] = KPISet()
data[''][state_idx].merge_kpis(kpi_set)
def add_data(self, data):
"""
Append data point
:type data: bzt.modules.aggregator.DataPoint
"""
while len(self.body):
self.body.pop(0)
overall = data.get(self.key).get('', KPISet())
self.body.append(Text(("stat-hdr", " Response Codes: "), align=RIGHT))
for key in sorted(overall.get(KPISet.RESP_CODES).keys()):
if overall[KPISet.SAMPLE_COUNT]:
part = 100 * float(overall[KPISet.RESP_CODES][key]) / overall[
KPISet.SAMPLE_COUNT]
else:
part = 0
dat = (
key,
part,
overall[KPISet.RESP_CODES][key],
)
if not len(key):
style = "stat-nonhttp"
elif key[0] == '2':
style = 'stat-2xx'
elif key[0] == '3':
style = 'stat-3xx'
elif key[0] == '4':
style = 'stat-4xx'
elif key[0] == '5':
style = 'stat-5xx'
else:
style = "stat-nonhttp"
self.body.append(
Text((style, "%s: %.2f%% (%s)" % dat), align=RIGHT))
dat = (100, overall[KPISet.SAMPLE_COUNT])
self.body.append(
Text(('stat-txt', "All: %.2f%% (%s)" % dat), align=RIGHT))
def test_log_messages_percentiles(self):
obj = FinalStatus()
obj.engine = EngineEmul
obj.parameters = BetterDict()
obj.log = logger_mock()
obj.parameters.merge({"failed-labels": False, "percentiles": True, "summary": False, "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()
target_output = ("Average times: total 0.001, latency 0.000, connect 0.000\n"
"Percentile 0.0%: 0.000\n"
"Percentile 50.0%: 0.000\n"
"Percentile 90.0%: 0.001\n"
"Percentile 95.0%: 0.001\n"
"Percentile 99.0%: 0.003\n"
"Percentile 99.9%: 0.008\n"
"Percentile 100.0%: 0.081\n"
)
self.assertEqual(target_output, obj.log.info_buf.getvalue())
def add_data(self, data):
"""
Append data
:type data: bzt.modules.aggregator.DataPoint
"""
while len(self.body):
self.body.pop(0)
self.body.append(Text(("stat-hdr", " Average Times: "), align=RIGHT))
overall = data.get(self.key).get('', KPISet())
self.body.append(
Text(("stat-txt", "Elapsed: %.3f" % overall[KPISet.AVG_RESP_TIME]),
align=RIGHT))
self.body.append(
Text(("stat-txt", "Connect: %.3f" % overall[KPISet.AVG_CONN_TIME]),
align=RIGHT))
self.body.append(
Text(("stat-txt", "Latency: %.3f" % overall[KPISet.AVG_LATENCY]),
align=RIGHT))
def test_prepare_filename_in_settings(self):
# test path parameter from config
obj = JUnitXMLReporter()
obj.engine = EngineEmul()
obj.parameters = BetterDict()
path_from_config = tempfile.mktemp(suffix='.xml', prefix='junit-xml-path-in-settings',
dir=obj.engine.artifacts_dir)
obj.parameters.merge({"filename": path_from_config, "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 add_data(self, data):
"""
New datapoint notification
:type data: bzt.modules.aggregator.DataPoint
"""
overall = data[DataPoint.CURRENT].get('', KPISet())
# self.log.debug("Got data for second: %s", to_json(data))
active = int(math.floor(overall[KPISet.SAMPLE_COUNT] * overall[
KPISet.AVG_RESP_TIME]))
self.graphs.append(overall[KPISet.CONCURRENCY],
min(overall[KPISet.CONCURRENCY], active),
overall[KPISet.SAMPLE_COUNT],
overall[KPISet.FAILURES],
overall[KPISet.AVG_RESP_TIME],
overall[KPISet.AVG_CONN_TIME],
overall[KPISet.AVG_LATENCY], )
self.latest_stats.add_data(data)
self.cumulative_stats.add_data(data)
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_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, "test-duration": 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_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 __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
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 __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
def test_xml_format_sample_labels(self):
# generate xml, compare hash
obj = JUnitXMLReporter()
obj.engine = EngineEmul()
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(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.aggregated_second(datapoint)
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()[1].getchildren()[0].tag)
self.assertListEqual(['29656', 'taurus_sample-labels', '0', '59314'], xml_tree.values())