本文整理汇总了Python中bzt.modules.aggregator.KPISet.from_dict方法的典型用法代码示例。如果您正苦于以下问题:Python KPISet.from_dict方法的具体用法?Python KPISet.from_dict怎么用?Python KPISet.from_dict使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类bzt.modules.aggregator.KPISet
的用法示例。
在下文中一共展示了KPISet.from_dict方法的5个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_prepare_no_filename_in_settings
# 需要导入模块: from bzt.modules.aggregator import KPISet [as 别名]
# 或者: from bzt.modules.aggregator.KPISet import from_dict [as 别名]
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))
示例2: test_log_messages_samples_count
# 需要导入模块: from bzt.modules.aggregator import KPISet [as 别名]
# 或者: from bzt.modules.aggregator.KPISet import from_dict [as 别名]
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())
示例3: __get_datapoint
# 需要导入模块: from bzt.modules.aggregator import KPISet [as 别名]
# 或者: from bzt.modules.aggregator.KPISet import from_dict [as 别名]
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
示例4: test_xml_format_sample_labels
# 需要导入模块: from bzt.modules.aggregator import KPISet [as 别名]
# 或者: from bzt.modules.aggregator.KPISet import from_dict [as 别名]
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}),
#.........这里部分代码省略.........
示例5: test_log_messages_failed_labels
# 需要导入模块: from bzt.modules.aggregator import KPISet [as 别名]
# 或者: from bzt.modules.aggregator.KPISet import from_dict [as 别名]
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}),
#.........这里部分代码省略.........