def test_datapoint_to_json(self): obj = ConsolidatingAggregator() obj.track_percentiles = [0.0, 50.0, 95.0, 99.0, 100.0] obj.prepare() obj.add_underling(self.get_success_reader()) for point in obj.datapoints(): obj.log.info(to_json(point))
def test_negative_response_time_scaling_crash(self): obj = ConsolidatingAggregator() obj.track_percentiles = [0.0, 50.0, 95.0, 99.0, 100.0] obj.prepare() self.sniff_log(obj.log) mock = MockReader() mock.data.append((1, "first", 1, -r(), r(), r(), 200, 'FAILx3', '', 0)) mock.data.append((2, "first", 1, -r(), r(), r(), 200, 'FAILx1', '', 0)) mock.data.append((5, "first", 1, -r(), r(), r(), 200, None, '', 0)) mock.data.append( (7, "second", 1, -r(), r(), r(), 200, 'FAILx3', '', 0)) mock.data.append((3, "first", 1, -r(), r(), r(), 200, 'FAILx3', '', 0)) mock.data.append( (6, "second", 1, -r(), r(), r(), 200, 'unique FAIL', '', 0)) obj.add_underling(mock) obj.check() for point in obj.datapoints(): obj.log.info(to_json(point)) self.assertIn("Negative response time reported", self.log_recorder.warn_buff.getvalue())
def test_set_rtimes_len(self): obj = ConsolidatingAggregator() obj.settings['rtimes-len'] = 42 obj.prepare() reader = self.get_fail_reader() obj.add_underling(reader) listener = MockListener() obj.add_listener(listener) obj.check() for dp in listener.results: for kpiset in dp['cumulative'].values(): self.assertEqual(42, kpiset.rtimes_len) for kpiset in dp['current'].values(): self.assertNotEqual(42, kpiset.rtimes_len)
def test_errors_cumulative(self): aggregator = ConsolidatingAggregator() aggregator.track_percentiles = [50] aggregator.prepare() reader = self.get_fail_reader() aggregator.add_underling(reader) aggregator.shutdown() aggregator.post_process() cum_dict = aggregator.underlings[0].cumulative first_err_ids = [id(err) for err in cum_dict['first']['errors']] second_err_ids = [id(err) for err in cum_dict['second']['errors']] total_err_ids = [id(err) for err in cum_dict['']['errors']] all_ids = first_err_ids + second_err_ids + total_err_ids self.assertEqual(len(all_ids), len(set(all_ids))) for label in cum_dict: data = cum_dict[label] total_errors_count = sum(err['cnt'] for err in data['errors']) self.assertEqual(data['fail'], total_errors_count)
def test_two_executions(self): # check consolidator obj = ConsolidatingAggregator() obj.prepare() obj.track_percentiles = [0, 50, 100] underling1 = self.get_reader() underling2 = self.get_reader() obj.add_underling(underling1) obj.add_underling(underling2) cnt = 0 for _ in range(1, 10): for point in obj.datapoints(): overall = point[DataPoint.CURRENT][''] self.assertEquals(2, overall[KPISet.CONCURRENCY]) self.assertGreater(overall[KPISet.PERCENTILES]["100.0"], 0) self.assertGreater(overall[KPISet.AVG_RESP_TIME], 0) cnt += 1 self.assertEquals(2, cnt)
class TestConsolidatingAggregator(BZTestCase): def setUp(self): super(TestConsolidatingAggregator, self).setUp() self.obj = ConsolidatingAggregator() self.obj.engine=EngineEmul() def test_two_executions(self): self.obj.track_percentiles = [0, 50, 100] self.obj.prepare() underling1 = get_success_reader() underling2 = get_success_reader() self.obj.add_underling(underling1) self.obj.add_underling(underling2) cnt = 0 for _ in range(1, 10): for point in self.obj.datapoints(): self.assertEqual(2, len(point[DataPoint.SUBRESULTS])) overall = point[DataPoint.CURRENT][''] self.assertEquals(2, overall[KPISet.CONCURRENCY]) self.assertGreater(overall[KPISet.PERCENTILES]["100.0"], 0) self.assertGreater(overall[KPISet.AVG_RESP_TIME], 0) cnt += 1 self.assertEquals(2, cnt) def test_errors_cumulative(self): self.obj.track_percentiles = [50] self.obj.prepare() reader = get_fail_reader() self.obj.add_underling(reader) self.obj.shutdown() self.obj.post_process() cum_dict = self.obj.underlings[0].cumulative first_err_ids = [id(err) for err in cum_dict['first']['errors']] second_err_ids = [id(err) for err in cum_dict['second']['errors']] total_err_ids = [id(err) for err in cum_dict['']['errors']] all_ids = first_err_ids + second_err_ids + total_err_ids self.assertEqual(len(all_ids), len(set(all_ids))) for label in cum_dict: data = cum_dict[label] total_errors_count = sum(err['cnt'] for err in data['errors']) self.assertEqual(data['fail'], total_errors_count) def test_labels_variety(self): self.obj.track_percentiles = [50] self.obj.prepare() reader1 = get_success_reader() reader2 = get_success_reader_alot() self.obj.log.info(len(reader1.data) + len(reader2.data)) self.obj.generalize_labels = 25 self.obj.add_underling(reader1) self.obj.add_underling(reader2) self.obj.shutdown() self.obj.post_process() cum_dict = self.obj.cumulative len_limit = (self.obj.generalize_labels + 1) # due to randomness, it it can go a bit higher than limit labels = list(cum_dict.keys()) self.assertGreaterEqual(len(labels), self.obj.generalize_labels / 2) # assert that it's at least half full self.assertLessEqual(len(labels), len_limit + 1) # allow +1 label because '' is cumulative def test_labels_constant_part(self): self.obj.track_percentiles = [50] self.obj.prepare() reader = get_success_reader_alot(prefix='http://blazedemo.com/?r=') self.obj.log.info(len(reader.data)) self.obj.generalize_labels = 25 self.obj.add_underling(reader) self.obj.shutdown() self.obj.post_process() cum_dict = self.obj.cumulative labels = list(cum_dict.keys()) self.assertGreaterEqual(len(labels), self.obj.generalize_labels / 2) # assert that it's at least half full self.assertLessEqual(len(labels), self.obj.generalize_labels + 1) # allow +1 label because '' is cumulative def test_labels_aggressive_folding(self): self.obj.track_percentiles = [50] self.obj.prepare() reader = get_success_reader_selected_labels() self.obj.log.info(len(reader.data)) self.obj.generalize_labels = 25 self.obj.add_underling(reader) self.obj.shutdown() self.obj.post_process() cum_dict = self.obj.cumulative labels = list(cum_dict.keys()) self.assertEqual(len(labels), 6) def test_labels_aggressive_folding_2(self): self.obj.track_percentiles = [50] self.obj.prepare() label_count = 50 reader = get_success_reader_shrinking_labels(max_label_size=int(label_count * 2), count=label_count) self.obj.log.info(len(reader.data)) self.obj.generalize_labels = label_count self.obj.add_underling(reader) last = None for point in self.obj.datapoints(True): last = point cum_dict = self.obj.cumulative labels = list(cum_dict.keys()) labels_count = len(labels) self.assertLessEqual(labels_count, label_count + 1) # didn't overflow self.assertGreaterEqual(labels_count, label_count * 0.25) # at least a quarter-filled self.assertEqual(1, len(last[DataPoint.SUBRESULTS])) self.assertEqual(last, last[DataPoint.SUBRESULTS][0]) def test_errors_variety(self): self.obj.track_percentiles = [50] self.obj.prepare() reader1 = get_fail_reader() reader2 = get_fail_reader_alot() self.obj.max_error_count = 50 self.obj.add_underling(reader1) self.obj.add_underling(reader2) self.obj.shutdown() self.obj.post_process() expected = self.obj.max_error_count # due to randomness, it it can go a bit higher than limit self.assertLessEqual(len(self.obj.known_errors), expected) self.assertGreaterEqual(len(self.obj.known_errors), self.obj.max_error_count / 2) # assert that it's at least half full def test_uniq_errors(self): self.obj.track_percentiles = [50] self.obj.prepare() reader = get_fail_reader() self.obj.max_error_count = 9 self.obj.add_underling(reader) self.obj.shutdown() self.obj.post_process() cum_dict = self.obj.cumulative self.assertEqual(len(cum_dict['']['errors']), 3) def test_set_rtimes_len(self): self.obj.settings['histogram-initial'] = 10.0 self.obj.prepare() reader = get_fail_reader() self.obj.add_underling(reader) listener = MockListener() self.obj.add_listener(listener) self.obj.check() for dp in listener.results: for kpiset in dp['cumulative'].values(): self.assertEqual(10000, kpiset[KPISet.RESP_TIMES].high) for kpiset in dp['current'].values(): self.assertEqual(10000, kpiset[KPISet.RESP_TIMES].high) def test_inf_values(self): self.obj.settings['max-buffer-len'] = "inf" self.obj.prepare() self.assertEqual(self.obj.max_buffer_len, float("inf")) def test_datapoint_to_json(self): self.obj.track_percentiles = [0.0, 50.0, 95.0, 99.0, 100.0] self.obj.prepare() self.obj.add_underling(get_success_reader()) for point in self.obj.datapoints(): if point[DataPoint.SUBRESULTS] == [point]: del point[DataPoint.SUBRESULTS] self.obj.log.info(to_json(point)) def test_negative_response_time_scaling_crash(self): self.obj.track_percentiles = [0.0, 50.0, 95.0, 99.0, 100.0] self.obj.prepare() self.sniff_log(self.obj.log) mock = MockReader() mock.data.append((1, "first", 1, -r(), r(), r(), 200, 'FAILx3', '', 0)) mock.data.append((2, "first", 1, -r(), r(), r(), 200, 'FAILx1', '', 0)) mock.data.append((5, "first", 1, -r(), r(), r(), 200, None, '', 0)) mock.data.append((7, "second", 1, -r(), r(), r(), 200, 'FAILx3', '', 0)) mock.data.append((3, "first", 1, -r(), r(), r(), 200, 'FAILx3', '', 0)) mock.data.append((6, "second", 1, -r(), r(), r(), 200, 'unique FAIL', '', 0)) self.obj.add_underling(mock) self.obj.check() for point in self.obj.datapoints(): self.obj.log.info(to_json(point)) self.assertIn("Negative response time reported", self.log_recorder.warn_buff.getvalue())
class TestConsolidatingAggregator(BZTestCase): def setUp(self): super(TestConsolidatingAggregator, self).setUp() self.obj = ConsolidatingAggregator() def test_two_executions(self): self.obj.track_percentiles = [0, 50, 100] self.obj.prepare() underling1 = get_success_reader() underling2 = get_success_reader() self.obj.add_underling(underling1) self.obj.add_underling(underling2) cnt = 0 for _ in range(1, 10): for point in self.obj.datapoints(): overall = point[DataPoint.CURRENT][''] self.assertEquals(2, overall[KPISet.CONCURRENCY]) self.assertGreater(overall[KPISet.PERCENTILES]["100.0"], 0) self.assertGreater(overall[KPISet.AVG_RESP_TIME], 0) cnt += 1 self.assertEquals(2, cnt) def test_errors_cumulative(self): self.obj.track_percentiles = [50] self.obj.prepare() reader = get_fail_reader() self.obj.add_underling(reader) self.obj.shutdown() self.obj.post_process() cum_dict = self.obj.underlings[0].cumulative first_err_ids = [id(err) for err in cum_dict['first']['errors']] second_err_ids = [id(err) for err in cum_dict['second']['errors']] total_err_ids = [id(err) for err in cum_dict['']['errors']] all_ids = first_err_ids + second_err_ids + total_err_ids self.assertEqual(len(all_ids), len(set(all_ids))) for label in cum_dict: data = cum_dict[label] total_errors_count = sum(err['cnt'] for err in data['errors']) self.assertEqual(data['fail'], total_errors_count) def test_labels_variety(self): self.obj.track_percentiles = [50] self.obj.prepare() reader1 = get_success_reader() reader2 = get_success_reader_alot() self.obj.log.info(len(reader1.data) + len(reader2.data)) self.obj.generalize_labels = 25 self.obj.add_underling(reader1) self.obj.add_underling(reader2) self.obj.shutdown() self.obj.post_process() cum_dict = self.obj.cumulative len_limit = (self.obj.generalize_labels + 1) # due to randomness, it it can go a bit higher than limit labels = list(cum_dict.keys()) self.assertGreaterEqual(len(labels), self.obj.generalize_labels / 2) # assert that it's at least half full self.assertLessEqual(len(labels), len_limit + 1) # allow +1 label because '' is cumulative def test_labels_constant_part(self): self.obj.track_percentiles = [50] self.obj.prepare() reader = get_success_reader_alot(prefix='http://blazedemo.com/?r=') self.obj.log.info(len(reader.data)) self.obj.generalize_labels = 25 self.obj.add_underling(reader) self.obj.shutdown() self.obj.post_process() cum_dict = self.obj.cumulative labels = list(cum_dict.keys()) self.assertGreaterEqual(len(labels), self.obj.generalize_labels / 2) # assert that it's at least half full self.assertLessEqual(len(labels), self.obj.generalize_labels + 1) # allow +1 label because '' is cumulative def test_labels_aggressive_folding(self): self.obj.track_percentiles = [50] self.obj.prepare() reader = get_success_reader_selected_labels() self.obj.log.info(len(reader.data)) self.obj.generalize_labels = 25 self.obj.add_underling(reader) self.obj.shutdown() self.obj.post_process() cum_dict = self.obj.cumulative labels = list(cum_dict.keys()) self.assertEqual(len(labels), 6) def test_labels_aggressive_folding_2(self): self.obj.track_percentiles = [50] self.obj.prepare() LABEL_COUNT = 50 reader = get_success_reader_shrinking_labels(max_label_size=int(LABEL_COUNT * 2), count=LABEL_COUNT) self.obj.log.info(len(reader.data)) self.obj.generalize_labels = LABEL_COUNT self.obj.add_underling(reader) for point in self.obj.datapoints(): last = point cum_dict = self.obj.cumulative labels = list(cum_dict.keys()) labels_count = len(labels) self.assertLessEqual(labels_count, LABEL_COUNT + 1) # didn't overflow self.assertGreaterEqual(labels_count, LABEL_COUNT * 0.25) # at least a quorter-filled def test_errors_variety(self): self.obj.track_percentiles = [50] self.obj.prepare() reader1 = get_fail_reader() reader2 = get_fail_reader_alot() self.obj.max_error_count = 50 self.obj.add_underling(reader1) self.obj.add_underling(reader2) self.obj.shutdown() self.obj.post_process() expected = self.obj.max_error_count # due to randomness, it it can go a bit higher than limit self.assertLessEqual(len(self.obj.known_errors), expected) self.assertGreaterEqual(len(self.obj.known_errors), self.obj.max_error_count / 2) # assert that it's at least half full def test_uniq_errors(self): self.obj.track_percentiles = [50] self.obj.prepare() reader = get_fail_reader() self.obj.max_error_count = 9 self.obj.add_underling(reader) self.obj.shutdown() self.obj.post_process() cum_dict = self.obj.cumulative self.assertEqual(len(cum_dict['']['errors']), 3) def test_set_rtimes_len(self): self.obj.settings['histogram-initial'] = 10.0 self.obj.prepare() reader = get_fail_reader() self.obj.add_underling(reader) listener = MockListener() self.obj.add_listener(listener) self.obj.check() for dp in listener.results: for kpiset in dp['cumulative'].values(): self.assertEqual(10000, kpiset[KPISet.RESP_TIMES].high) for kpiset in dp['current'].values(): self.assertEqual(10000, kpiset[KPISet.RESP_TIMES].high) def test_inf_values(self): self.obj.settings['max-buffer-len'] = "inf" self.obj.prepare() self.assertEqual(self.obj.max_buffer_len, float("inf")) def test_datapoint_to_json(self): self.obj.track_percentiles = [0.0, 50.0, 95.0, 99.0, 100.0] self.obj.prepare() self.obj.add_underling(get_success_reader()) for point in self.obj.datapoints(): self.obj.log.info(to_json(point)) def test_negative_response_time_scaling_crash(self): self.obj.track_percentiles = [0.0, 50.0, 95.0, 99.0, 100.0] self.obj.prepare() self.sniff_log(self.obj.log) mock = MockReader() mock.data.append((1, "first", 1, -r(), r(), r(), 200, 'FAILx3', '', 0)) mock.data.append((2, "first", 1, -r(), r(), r(), 200, 'FAILx1', '', 0)) mock.data.append((5, "first", 1, -r(), r(), r(), 200, None, '', 0)) mock.data.append((7, "second", 1, -r(), r(), r(), 200, 'FAILx3', '', 0)) mock.data.append((3, "first", 1, -r(), r(), r(), 200, 'FAILx3', '', 0)) mock.data.append((6, "second", 1, -r(), r(), r(), 200, 'unique FAIL', '', 0)) self.obj.add_underling(mock) self.obj.check() for point in self.obj.datapoints(): self.obj.log.info(to_json(point)) self.assertIn("Negative response time reported", self.log_recorder.warn_buff.getvalue())
class TestConsolidatingAggregator(BZTestCase): def setUp(self): super(TestConsolidatingAggregator, self).setUp() self.obj = ConsolidatingAggregator() self.obj.engine = EngineEmul() def test_two_executions(self): self.obj.track_percentiles = [0, 50, 100] self.obj.prepare() underling1 = get_success_reader() underling2 = get_success_reader() self.obj.add_underling(underling1) self.obj.add_underling(underling2) cnt = 0 for _ in range(1, 10): for point in self.obj.datapoints(): self.assertEqual(2, len(point[DataPoint.SUBRESULTS])) overall = point[DataPoint.CURRENT][''] self.assertEquals(2, overall[KPISet.CONCURRENCY]) self.assertGreater(overall[KPISet.PERCENTILES]["100.0"], 0) self.assertGreater(overall[KPISet.AVG_RESP_TIME], 0) cnt += 1 self.assertEquals(2, cnt) def test_new_aggregator(self): # aggregator's config self.obj.extend_aggregation = True reader = MockReader() watcher = MockReader() # executor/reporter prepare level self.obj.add_underling(reader) self.obj.add_listener(watcher) # send rules to underlings self.obj.startup() reader.buffer_scale_idx = '100.0' # data format: t_stamp, label, conc, r_time, con_time, latency, r_code, error, trname, byte_count reader.data.append((1, "a", 1, 1, 1, 1, 200, None, '', 0)) reader.data.append((2, "b", 1, 2, 2, 2, 200, 'OK', '', 0)) reader.data.append((2, "b", 1, 3, 3, 3, 404, "Not Found", '', 0)) reader.data.append((2, "c", 1, 4, 4, 4, 200, None, '', 0)) reader.data.append((3, "d", 1, 5, 5, 5, 200, None, '', 0)) reader.data.append((4, "b", 1, 6, 6, 6, 200, None, '', 0)) # let's collect data to seconds and send something aggregated to watcher self.obj.shutdown() self.obj.post_process() data_points = watcher.results[-1][DataPoint.CUMULATIVE] self.assertEquals(7, len(data_points)) sample_labels = {'a-0', 'b-0', 'b-1', 'b-2', 'c-0', 'd-0', ''} self.assertEquals(sample_labels, set(data_points.keys())) def test_errors_cumulative(self): self.obj.track_percentiles = [50] self.obj.prepare() reader = get_fail_reader() self.obj.add_underling(reader) self.obj.shutdown() self.obj.post_process() cum_dict = self.obj.underlings[0].cumulative first_err_ids = [id(err) for err in cum_dict['first']['errors']] second_err_ids = [id(err) for err in cum_dict['second']['errors']] total_err_ids = [id(err) for err in cum_dict['']['errors']] all_ids = first_err_ids + second_err_ids + total_err_ids self.assertEqual(len(all_ids), len(set(all_ids))) for label in cum_dict: data = cum_dict[label] total_errors_count = sum(err['cnt'] for err in data['errors']) self.assertEqual(data['fail'], total_errors_count) def test_labels_variety(self): self.obj.track_percentiles = [50] self.obj.prepare() reader1 = get_success_reader() reader2 = get_success_reader_alot() self.obj.log.info(len(reader1.data) + len(reader2.data)) self.obj.generalize_labels = 25 self.obj.add_underling(reader1) self.obj.add_underling(reader2) self.obj.shutdown() self.obj.post_process() cum_dict = self.obj.cumulative len_limit = (self.obj.generalize_labels + 1) # due to randomness, it it can go a bit higher than limit labels = list(cum_dict.keys()) self.assertGreaterEqual(len(labels), self.obj.generalize_labels / 2) # assert that it's at least half full self.assertLessEqual(len(labels), len_limit + 1) # allow +1 label because '' is cumulative def test_labels_constant_part(self): self.obj.track_percentiles = [50] self.obj.prepare() reader = get_success_reader_alot(prefix='http://blazedemo.com/?r=') self.obj.log.info(len(reader.data)) self.obj.generalize_labels = 25 self.obj.add_underling(reader) self.obj.shutdown() self.obj.post_process() cum_dict = self.obj.cumulative labels = list(cum_dict.keys()) self.assertGreaterEqual(len(labels), self.obj.generalize_labels / 2) # assert that it's at least half full self.assertLessEqual(len(labels), self.obj.generalize_labels + 1) # allow +1 label because '' is cumulative def test_labels_aggressive_folding(self): self.obj.track_percentiles = [50] self.obj.prepare() reader = get_success_reader_selected_labels() self.obj.log.info(len(reader.data)) self.obj.generalize_labels = 25 self.obj.add_underling(reader) self.obj.shutdown() self.obj.post_process() cum_dict = self.obj.cumulative labels = list(cum_dict.keys()) self.assertEqual(len(labels), 6) def test_labels_aggressive_folding_2(self): self.obj.track_percentiles = [50] self.obj.prepare() label_count = 50 reader = get_success_reader_shrinking_labels(max_label_size=int(label_count * 2), count=label_count) self.obj.log.info(len(reader.data)) self.obj.generalize_labels = label_count self.obj.add_underling(reader) last = None for point in self.obj.datapoints(True): last = point cum_dict = self.obj.cumulative labels = list(cum_dict.keys()) labels_count = len(labels) self.assertLessEqual(labels_count, label_count + 1) # didn't overflow self.assertGreaterEqual(labels_count, label_count * 0.25) # at least a quarter-filled self.assertEqual(1, len(last[DataPoint.SUBRESULTS])) self.assertEqual(last, last[DataPoint.SUBRESULTS][0]) def test_errors_variety(self): self.obj.track_percentiles = [50] self.obj.prepare() reader1 = get_fail_reader() reader2 = get_fail_reader_alot() self.obj.max_error_count = 50 self.obj.add_underling(reader1) self.obj.add_underling(reader2) self.obj.shutdown() self.obj.post_process() expected = self.obj.max_error_count # due to randomness, it it can go a bit higher than limit self.assertLessEqual(len(self.obj.known_errors), expected) self.assertGreaterEqual(len(self.obj.known_errors), self.obj.max_error_count / 2) # assert that it's at least half full def test_uniq_errors(self): self.obj.track_percentiles = [50] self.obj.prepare() reader = get_fail_reader() self.obj.max_error_count = 9 self.obj.add_underling(reader) self.obj.shutdown() self.obj.post_process() cum_dict = self.obj.cumulative self.assertEqual(len(cum_dict['']['errors']), 3) def test_set_rtimes_len(self): self.obj.settings['histogram-initial'] = 10.0 self.obj.prepare() reader = get_fail_reader() self.obj.add_underling(reader) listener = MockListener() self.obj.add_listener(listener) self.obj.check() for dp in listener.results: for kpiset in dp['cumulative'].values(): self.assertEqual(10000, kpiset[KPISet.RESP_TIMES].high) for kpiset in dp['current'].values(): self.assertEqual(10000, kpiset[KPISet.RESP_TIMES].high) def test_inf_values(self): self.obj.settings['max-buffer-len'] = "inf" self.obj.prepare() self.assertEqual(self.obj.max_buffer_len, float("inf")) def test_datapoint_to_json(self): self.obj.track_percentiles = [0.0, 50.0, 95.0, 99.0, 100.0] self.obj.prepare() self.obj.add_underling(get_success_reader()) for point in self.obj.datapoints(): if point[DataPoint.SUBRESULTS] == [point]: del point[DataPoint.SUBRESULTS] self.obj.log.info(to_json(point)) def test_negative_response_time_scaling_crash(self): self.obj.track_percentiles = [0.0, 50.0, 95.0, 99.0, 100.0] self.obj.prepare() self.sniff_log(self.obj.log) mock = MockReader() mock.data.append((1, "first", 1, -r(), r(), r(), 200, 'FAILx3', '', 0)) mock.data.append((2, "first", 1, -r(), r(), r(), 200, 'FAILx1', '', 0)) mock.data.append((5, "first", 1, -r(), r(), r(), 200, None, '', 0)) mock.data.append((7, "second", 1, -r(), r(), r(), 200, 'FAILx3', '', 0)) mock.data.append((3, "first", 1, -r(), r(), r(), 200, 'FAILx3', '', 0)) mock.data.append((6, "second", 1, -r(), r(), r(), 200, 'unique FAIL', '', 0)) self.obj.add_underling(mock) self.obj.check() for point in self.obj.datapoints(): self.obj.log.info(to_json(point)) self.assertIn("Negative response time reported", self.log_recorder.warn_buff.getvalue()) def test_ramp_up_exclude(self): self.obj.track_percentiles = [50] self.obj.prepare() self.obj.engine.config['settings']['ramp-up-exclude'] = True self.obj.engine.config['execution'] = [ {'scenario': 'first', 'ramp-up': 50}, {'scenario': 'second', 'ramp-up': '1s'}, {'scenario': 'third'} ] self.obj.engine.config['scenarios'] = BetterDict.from_dict({ 'first': {'requests': [{'url': 'first'}]}, 'second': {'requests': [{'url': 'second'}]}, 'third': {'requests': [{'url': 'third'}]}}) reader = get_success_reader() self.obj.add_underling(reader) self.obj.shutdown() self.obj.post_process() self.assertEquals(self.obj.cumulative, {})
def test_extend_datapoints(self): # check reported data format conversion for test state filtering on BM side def get_mock(origin_func, store): # generate replacement for BlazemeterUploader._dpoint_serializer.get_kpi_body def mock_get_kpi_body(data, isfinal): store.append(data) # save received data for verifying return origin_func( data, isfinal) # call original get_kpi_body as well return mock_get_kpi_body mock = BZMock() mock.mock_get.update({ '1': { "result": [] }, 'https://a.blazemeter.com/api/v4/tests?projectId=1&name=Taurus+Test': { "result": [] }, '3': { "result": [] }, }) mock.mock_post.update({ 'https://a.blazemeter.com/api/v4/projects': { "result": { "id": 1 } }, 'https://a.blazemeter.com/api/v4/tests': { "result": { 'id': 1 } }, 'https://a.blazemeter.com/api/v4/tests/1/start-external': { "result": { 'session': { 'id': 1, 'userId': 1, 'testId': 1 }, 'master': { 'id': 1, 'userId': 1 }, 'signature': 'sign' } }, 'https://data.blazemeter.com/submit.php?session_id=1&signature=sign&test_id=1&user_id=1&pq=0&target=labels_bulk&update=1': [ {}, { "result": { 'session': { "statusCode": 140, 'status': 'ENDED' } } }, {}, ], 'https://data.blazemeter.com/api/v4/image/1/files?signature=sign': [ IOError("monitoring push expected fail"), { "result": True }, { "result": True }, { "result": True }, { "result": True }, { "result": True }, { "result": True }, { "result": True }, { "result": True }, ], 'https://a.blazemeter.com/api/v4/sessions/1/stop': {}, 'https://data.blazemeter.com/submit.php?session_id=1&signature=sign&test_id=1&user_id=1&pq=0&target=engine_health&update=1': { "result": { 'session': {} } } }) obj = BlazeMeterUploader() sent_data_points = [] obj._dpoint_serializer.get_kpi_body = get_mock( obj._dpoint_serializer.get_kpi_body, sent_data_points) obj.parameters['project'] = 'Proj name' obj.settings['token'] = '123' obj.settings['browser-open'] = 'none' obj.engine = EngineEmul() aggregator = ConsolidatingAggregator() aggregator.engine = obj.engine aggregator.settings['extend-aggregation'] = True reader = MockReader() watcher = MockReader() reader.buffer_scale_idx = '100.0' # data format: t_stamp, label, conc, r_time, con_time, latency, r_code, error, trname, byte_count reader.data.append((1, "a", 1, 1, 1, 1, 200, None, '', 1)) reader.data.append((2, "b", 1, 2, 2, 2, 200, 'OK', '', 2)) reader.data.append((2, "b", 1, 3, 3, 3, 404, "Not Found", '', 3)) reader.data.append((2, "c", 1, 4, 4, 4, 200, None, '', 4)) reader.data.append((3, "d", 1, 5, 5, 5, 200, None, '', 5)) reader.data.append((5, "b", 1, 6, 6, 6, 200, None, '', 6)) reader.data.append((5, "c", 1, 7, 7, 7, 200, None, '', 7)) original_labels = list(d[1] for d in reader.data) aggregator.add_underling(reader) aggregator.add_listener(watcher) obj.engine.aggregator = aggregator mock.apply(obj._user) obj._user.timeout = 0.001 obj.engine.aggregator.prepare() obj.prepare() obj.engine.aggregator.startup() obj.startup() obj.engine.aggregator.check() obj.check() obj.engine.aggregator.shutdown() obj.shutdown() obj.engine.aggregator.post_process() obj.post_process() sent_data_points = sent_data_points[0] + sent_data_points[1] state_labels = [0, 1, 2] for dp in sent_data_points: for data in dp['cumulative'], dp['current']: for label in data: self.assertIn(label, original_labels + ['']) self.assertIsInstance(data[label], dict) for key in data[label]: self.assertIn(key, state_labels)
class TestConsolidatingAggregator(BZTestCase): def setUp(self): super(TestConsolidatingAggregator, self).setUp() self.obj = ConsolidatingAggregator() def test_two_executions(self): self.obj.track_percentiles = [0, 50, 100] self.obj.prepare() underling1 = get_success_reader() underling2 = get_success_reader() self.obj.add_underling(underling1) self.obj.add_underling(underling2) cnt = 0 for _ in range(1, 10): for point in self.obj.datapoints(): overall = point[DataPoint.CURRENT][''] self.assertEquals(2, overall[KPISet.CONCURRENCY]) self.assertGreater(overall[KPISet.PERCENTILES]["100.0"], 0) self.assertGreater(overall[KPISet.AVG_RESP_TIME], 0) cnt += 1 self.assertEquals(2, cnt) def test_errors_cumulative(self): self.obj.track_percentiles = [50] self.obj.prepare() reader = get_fail_reader() self.obj.add_underling(reader) self.obj.shutdown() self.obj.post_process() cum_dict = self.obj.underlings[0].cumulative first_err_ids = [id(err) for err in cum_dict['first']['errors']] second_err_ids = [id(err) for err in cum_dict['second']['errors']] total_err_ids = [id(err) for err in cum_dict['']['errors']] all_ids = first_err_ids + second_err_ids + total_err_ids self.assertEqual(len(all_ids), len(set(all_ids))) for label in cum_dict: data = cum_dict[label] total_errors_count = sum(err['cnt'] for err in data['errors']) self.assertEqual(data['fail'], total_errors_count) def test_errors_variety(self): self.obj.track_percentiles = [50] self.obj.prepare() reader1 = get_fail_reader() reader2 = get_fail_reader_alot() self.obj.max_error_count = 9 self.obj.add_underling(reader1) self.obj.add_underling(reader2) self.obj.shutdown() self.obj.post_process() cum_dict = self.obj.cumulative self.assertLessEqual(len(cum_dict['']['errors']), self.obj.max_error_count) def test_uniq_errors(self): self.obj.track_percentiles = [50] self.obj.prepare() reader = get_fail_reader() self.obj.max_error_count = 9 self.obj.add_underling(reader) self.obj.shutdown() self.obj.post_process() cum_dict = self.obj.cumulative self.assertEqual(len(cum_dict['']['errors']), 3) def test_set_rtimes_len(self): self.obj.settings['rtimes-len'] = 42 self.obj.prepare() reader = get_fail_reader() self.obj.add_underling(reader) listener = MockListener() self.obj.add_listener(listener) self.obj.check() for dp in listener.results: for kpiset in dp['cumulative'].values(): self.assertEqual(42, kpiset.rtimes_len) for kpiset in dp['current'].values(): self.assertNotEqual(42, kpiset.rtimes_len) def test_inf_values(self): self.obj.settings['max-buffer-len'] = "inf" self.obj.prepare() self.assertEqual(self.obj.max_buffer_len, float("inf")) def test_datapoint_to_json(self): self.obj.track_percentiles = [0.0, 50.0, 95.0, 99.0, 100.0] self.obj.prepare() self.obj.add_underling(get_success_reader()) for point in self.obj.datapoints(): self.obj.log.info(to_json(point)) def test_negative_response_time_scaling_crash(self): self.obj.track_percentiles = [0.0, 50.0, 95.0, 99.0, 100.0] self.obj.prepare() self.sniff_log(self.obj.log) mock = MockReader() mock.data.append((1, "first", 1, -r(), r(), r(), 200, 'FAILx3', '', 0)) mock.data.append((2, "first", 1, -r(), r(), r(), 200, 'FAILx1', '', 0)) mock.data.append((5, "first", 1, -r(), r(), r(), 200, None, '', 0)) mock.data.append((7, "second", 1, -r(), r(), r(), 200, 'FAILx3', '', 0)) mock.data.append((3, "first", 1, -r(), r(), r(), 200, 'FAILx3', '', 0)) mock.data.append((6, "second", 1, -r(), r(), r(), 200, 'unique FAIL', '', 0)) self.obj.add_underling(mock) self.obj.check() for point in self.obj.datapoints(): self.obj.log.info(to_json(point)) self.assertIn("Negative response time reported", self.log_recorder.warn_buff.getvalue())