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())