X-Git-Url: https://gerrit.fd.io/r/gitweb?p=csit.git;a=blobdiff_plain;f=resources%2Ftools%2Fpresentation%2Fgenerator_cpta.py;h=4063764eb11e28929f4bc2b521249d18ffff94f2;hp=0320b9eec13259c2e81e8ed92b2d94f1f53eda89;hb=HEAD;hpb=a505b3d02cb3dcba44096859287ee2df4ce878ab
diff --git a/resources/tools/presentation/generator_cpta.py b/resources/tools/presentation/generator_cpta.py
deleted file mode 100644
index 0320b9eec1..0000000000
--- a/resources/tools/presentation/generator_cpta.py
+++ /dev/null
@@ -1,863 +0,0 @@
-# Copyright (c) 2021 Cisco and/or its affiliates.
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at:
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-"""Generation of Continuous Performance Trending and Analysis.
-"""
-
-import re
-import logging
-import csv
-
-from collections import OrderedDict
-from datetime import datetime
-from copy import deepcopy
-
-import prettytable
-import plotly.offline as ploff
-import plotly.graph_objs as plgo
-import plotly.exceptions as plerr
-
-from pal_utils import archive_input_data, execute_command, classify_anomalies
-
-
-# Command to build the html format of the report
-HTML_BUILDER = u'sphinx-build -v -c sphinx_conf/trending -a ' \
- u'-b html -E ' \
- u'-t html ' \
- u'-D version="{date}" ' \
- u'{working_dir} ' \
- u'{build_dir}/'
-
-# .css file for the html format of the report
-THEME_OVERRIDES = u"""/* override table width restrictions */
-.wy-nav-content {
- max-width: 1200px !important;
-}
-.rst-content blockquote {
- margin-left: 0px;
- line-height: 18px;
- margin-bottom: 0px;
-}
-.wy-menu-vertical a {
- display: inline-block;
- line-height: 18px;
- padding: 0 2em;
- display: block;
- position: relative;
- font-size: 90%;
- color: #d9d9d9
-}
-.wy-menu-vertical li.current a {
- color: gray;
- border-right: solid 1px #c9c9c9;
- padding: 0 3em;
-}
-.wy-menu-vertical li.toctree-l2.current > a {
- background: #c9c9c9;
- padding: 0 3em;
-}
-.wy-menu-vertical li.toctree-l2.current li.toctree-l3 > a {
- display: block;
- background: #c9c9c9;
- padding: 0 4em;
-}
-.wy-menu-vertical li.toctree-l3.current li.toctree-l4 > a {
- display: block;
- background: #bdbdbd;
- padding: 0 5em;
-}
-.wy-menu-vertical li.on a, .wy-menu-vertical li.current > a {
- color: #404040;
- padding: 0 2em;
- font-weight: bold;
- position: relative;
- background: #fcfcfc;
- border: none;
- border-top-width: medium;
- border-bottom-width: medium;
- border-top-style: none;
- border-bottom-style: none;
- border-top-color: currentcolor;
- border-bottom-color: currentcolor;
- padding-left: 2em -4px;
-}
-"""
-
-COLORS = (
- u"#1A1110",
- u"#DA2647",
- u"#214FC6",
- u"#01786F",
- u"#BD8260",
- u"#FFD12A",
- u"#A6E7FF",
- u"#738276",
- u"#C95A49",
- u"#FC5A8D",
- u"#CEC8EF",
- u"#391285",
- u"#6F2DA8",
- u"#FF878D",
- u"#45A27D",
- u"#FFD0B9",
- u"#FD5240",
- u"#DB91EF",
- u"#44D7A8",
- u"#4F86F7",
- u"#84DE02",
- u"#FFCFF1",
- u"#614051"
-)
-
-
-def generate_cpta(spec, data):
- """Generate all formats and versions of the Continuous Performance Trending
- and Analysis.
-
- :param spec: Specification read from the specification file.
- :param data: Full data set.
- :type spec: Specification
- :type data: InputData
- """
-
- logging.info(u"Generating the Continuous Performance Trending and Analysis "
- u"...")
-
- ret_code = _generate_all_charts(spec, data)
-
- cmd = HTML_BUILDER.format(
- date=datetime.utcnow().strftime(u'%Y-%m-%d %H:%M UTC'),
- working_dir=spec.environment[u'paths'][u'DIR[WORKING,SRC]'],
- build_dir=spec.environment[u'paths'][u'DIR[BUILD,HTML]'])
- execute_command(cmd)
-
- with open(spec.environment[u'paths'][u'DIR[CSS_PATCH_FILE]'], u'w') as \
- css_file:
- css_file.write(THEME_OVERRIDES)
-
- with open(spec.environment[u'paths'][u'DIR[CSS_PATCH_FILE2]'], u'w') as \
- css_file:
- css_file.write(THEME_OVERRIDES)
-
- if spec.environment.get(u"archive-inputs", False):
- archive_input_data(spec)
-
- logging.info(u"Done.")
-
- return ret_code
-
-
-def _generate_trending_traces(in_data, job_name, build_info,
- name=u"", color=u"", incl_tests=u"mrr"):
- """Generate the trending traces:
- - samples,
- - outliers, regress, progress
- - average of normal samples (trending line)
-
- :param in_data: Full data set.
- :param job_name: The name of job which generated the data.
- :param build_info: Information about the builds.
- :param name: Name of the plot
- :param color: Name of the color for the plot.
- :param incl_tests: Included tests, accepted values: mrr, ndr, pdr
- :type in_data: OrderedDict
- :type job_name: str
- :type build_info: dict
- :type name: str
- :type color: str
- :type incl_tests: str
- :returns: Generated traces (list) and the evaluated result.
- :rtype: tuple(traces, result)
- """
-
- if incl_tests not in (u"mrr", u"ndr", u"pdr", u"pdr-lat"):
- return list(), None
-
- data_x = list(in_data.keys())
- data_y_pps = list()
- data_y_mpps = list()
- data_y_stdev = list()
- if incl_tests == u"pdr-lat":
- for item in in_data.values():
- data_y_pps.append(float(item.get(u"lat_1", u"nan")) / 1e6)
- data_y_stdev.append(float(u"nan"))
- data_y_mpps.append(float(item.get(u"lat_1", u"nan")) / 1e6)
- multi = 1.0
- else:
- for item in in_data.values():
- data_y_pps.append(float(item[u"receive-rate"]))
- data_y_stdev.append(float(item[u"receive-stdev"]) / 1e6)
- data_y_mpps.append(float(item[u"receive-rate"]) / 1e6)
- multi = 1e6
- hover_text = list()
- xaxis = list()
- for index, key in enumerate(data_x):
- str_key = str(key)
- date = build_info[job_name][str_key][0]
- hover_str = (u"date: {date}
"
- u"{property} [Mpps]:
"
- u""
- u"{sut}-ref: {build}
"
- u"csit-ref: {test}-{period}-build-{build_nr}
"
- u"testbed: {testbed}")
- if incl_tests == u"mrr":
- hover_str = hover_str.replace(
- u"", f"stdev [Mpps]: {data_y_stdev[index]:.3f}
"
- )
- else:
- hover_str = hover_str.replace(u"", u"")
- if incl_tests == u"pdr-lat":
- hover_str = hover_str.replace(u"", u"{value:.1e}")
- else:
- hover_str = hover_str.replace(u"", u"{value:.3f}")
- if u"-cps" in name:
- hover_str = hover_str.replace(u"[Mpps]", u"[Mcps]").\
- replace(u"throughput", u"connection rate")
- if u"vpp" in job_name:
- hover_str = hover_str.format(
- date=date,
- property=u"average" if incl_tests == u"mrr" else u"throughput",
- value=data_y_mpps[index],
- sut=u"vpp",
- build=build_info[job_name][str_key][1].rsplit(u'~', 1)[0],
- test=incl_tests,
- period=u"daily" if incl_tests == u"mrr" else u"weekly",
- build_nr=str_key,
- testbed=build_info[job_name][str_key][2])
- elif u"dpdk" in job_name:
- hover_str = hover_str.format(
- date=date,
- property=u"average" if incl_tests == u"mrr" else u"throughput",
- value=data_y_mpps[index],
- sut=u"dpdk",
- build=build_info[job_name][str_key][1].rsplit(u'~', 1)[0],
- test=incl_tests,
- period=u"weekly",
- build_nr=str_key,
- testbed=build_info[job_name][str_key][2])
- elif u"trex" in job_name:
- hover_str = hover_str.format(
- date=date,
- property=u"average" if incl_tests == u"mrr" else u"throughput",
- value=data_y_mpps[index],
- sut=u"trex",
- build=u"",
- test=incl_tests,
- period=u"daily" if incl_tests == u"mrr" else u"weekly",
- build_nr=str_key,
- testbed=build_info[job_name][str_key][2])
- if incl_tests == u"pdr-lat":
- hover_str = hover_str.replace(
- u"throughput [Mpps]", u"latency [s]"
- )
- hover_text.append(hover_str)
- xaxis.append(datetime(int(date[0:4]), int(date[4:6]), int(date[6:8]),
- int(date[9:11]), int(date[12:])))
-
- data_pd = OrderedDict()
- for key, value in zip(xaxis, data_y_pps):
- data_pd[key] = value
-
- try:
- anomaly_classification, avgs_pps, stdevs_pps = \
- classify_anomalies(data_pd)
- except ValueError as err:
- logging.info(f"{err} Skipping")
- return list(), None
- avgs_mpps = [avg_pps / multi for avg_pps in avgs_pps]
- stdevs_mpps = [stdev_pps / multi for stdev_pps in stdevs_pps]
-
- anomalies = OrderedDict()
- anomalies_colors = list()
- anomalies_avgs = list()
- anomaly_color = {
- u"regression": 0.0,
- u"normal": 0.5,
- u"progression": 1.0
- }
- if anomaly_classification:
- for index, (key, value) in enumerate(data_pd.items()):
- if anomaly_classification[index] in (u"regression", u"progression"):
- anomalies[key] = value / multi
- anomalies_colors.append(
- anomaly_color[anomaly_classification[index]])
- anomalies_avgs.append(avgs_mpps[index])
- anomalies_colors.extend([0.0, 0.5, 1.0])
-
- # Create traces
-
- trace_samples = plgo.Scatter(
- x=xaxis,
- y=data_y_mpps,
- mode=u"markers",
- line={
- u"width": 1
- },
- showlegend=True,
- legendgroup=name,
- name=f"{name}",
- marker={
- u"size": 5,
- u"color": color,
- u"symbol": u"circle",
- },
- text=hover_text,
- hoverinfo=u"text+name"
- )
- traces = [trace_samples, ]
-
- trend_hover_text = list()
- for idx in range(len(data_x)):
- if incl_tests == u"pdr-lat":
- trend_hover_str = (
- f"trend [s]: {avgs_mpps[idx]:.1e}
"
- )
- else:
- trend_hover_str = (
- f"trend [Mpps]: {avgs_mpps[idx]:.3f}
"
- f"stdev [Mpps]: {stdevs_mpps[idx]:.3f}"
- )
- trend_hover_text.append(trend_hover_str)
-
- trace_trend = plgo.Scatter(
- x=xaxis,
- y=avgs_mpps,
- mode=u"lines",
- line={
- u"shape": u"linear",
- u"width": 1,
- u"color": color,
- },
- showlegend=False,
- legendgroup=name,
- name=f"{name}",
- text=trend_hover_text,
- hoverinfo=u"text+name"
- )
- traces.append(trace_trend)
-
- if incl_tests == u"pdr-lat":
- colorscale = [
- [0.00, u"green"],
- [0.33, u"green"],
- [0.33, u"white"],
- [0.66, u"white"],
- [0.66, u"red"],
- [1.00, u"red"]
- ]
- ticktext = [u"Progression", u"Normal", u"Regression"]
- else:
- colorscale = [
- [0.00, u"red"],
- [0.33, u"red"],
- [0.33, u"white"],
- [0.66, u"white"],
- [0.66, u"green"],
- [1.00, u"green"]
- ]
- ticktext = [u"Regression", u"Normal", u"Progression"]
- trace_anomalies = plgo.Scatter(
- x=list(anomalies.keys()),
- y=anomalies_avgs,
- mode=u"markers",
- hoverinfo=u"none",
- showlegend=False,
- legendgroup=name,
- name=f"{name}-anomalies",
- marker={
- u"size": 15,
- u"symbol": u"circle-open",
- u"color": anomalies_colors,
- u"colorscale": colorscale,
- u"showscale": True,
- u"line": {
- u"width": 2
- },
- u"colorbar": {
- u"y": 0.5,
- u"len": 0.8,
- u"title": u"Circles Marking Data Classification",
- u"titleside": u"right",
- u"titlefont": {
- u"size": 14
- },
- u"tickmode": u"array",
- u"tickvals": [0.167, 0.500, 0.833],
- u"ticktext": ticktext,
- u"ticks": u"",
- u"ticklen": 0,
- u"tickangle": -90,
- u"thickness": 10
- }
- }
- )
- traces.append(trace_anomalies)
-
- if anomaly_classification:
- return traces, anomaly_classification[-1]
-
- return traces, None
-
-
-def _generate_all_charts(spec, input_data):
- """Generate all charts specified in the specification file.
-
- :param spec: Specification.
- :param input_data: Full data set.
- :type spec: Specification
- :type input_data: InputData
- """
-
- def _generate_chart(graph):
- """Generates the chart.
-
- :param graph: The graph to be generated
- :type graph: dict
- :returns: Dictionary with the job name, csv table with results and
- list of tests classification results.
- :rtype: dict
- """
-
- logging.info(f" Generating the chart {graph.get(u'title', u'')} ...")
-
- job_name = list(graph[u"data"].keys())[0]
-
- # Transform the data
- logging.info(
- f" Creating the data set for the {graph.get(u'type', u'')} "
- f"{graph.get(u'title', u'')}."
- )
-
- data = input_data.filter_tests_by_name(
- graph,
- params=[u"type", u"result", u"throughput", u"latency", u"tags"],
- continue_on_error=True
- )
-
- if data is None or data.empty:
- logging.error(u"No data.")
- return dict()
-
- return_lst = list()
-
- for ttype in graph.get(u"test-type", (u"mrr", )):
- for core in graph.get(u"core", tuple()):
- csv_tbl = list()
- csv_tbl_lat_1 = list()
- csv_tbl_lat_2 = list()
- res = dict()
- chart_data = dict()
- chart_tags = dict()
- for item in graph.get(u"include", tuple()):
- reg_ex = re.compile(str(item.format(core=core)).lower())
- for job, job_data in data.items():
- if job != job_name:
- continue
- for index, bld in job_data.items():
- for test_id, test in bld.items():
- if not re.match(reg_ex, str(test_id).lower()):
- continue
- if chart_data.get(test_id, None) is None:
- chart_data[test_id] = OrderedDict()
- try:
- lat_1 = u""
- lat_2 = u""
- if ttype == u"mrr":
- rate = test[u"result"][u"receive-rate"]
- stdev = \
- test[u"result"][u"receive-stdev"]
- elif ttype == u"ndr":
- rate = \
- test["throughput"][u"NDR"][u"LOWER"]
- stdev = float(u"nan")
- elif ttype == u"pdr":
- rate = \
- test["throughput"][u"PDR"][u"LOWER"]
- stdev = float(u"nan")
- lat_1 = test[u"latency"][u"PDR50"]\
- [u"direction1"][u"avg"]
- lat_2 = test[u"latency"][u"PDR50"]\
- [u"direction2"][u"avg"]
- else:
- continue
- chart_data[test_id][int(index)] = {
- u"receive-rate": rate,
- u"receive-stdev": stdev
- }
- if ttype == u"pdr":
- chart_data[test_id][int(index)].update(
- {
- u"lat_1": lat_1,
- u"lat_2": lat_2
- }
- )
- chart_tags[test_id] = \
- test.get(u"tags", None)
- except (KeyError, TypeError):
- pass
-
- # Add items to the csv table:
- for tst_name, tst_data in chart_data.items():
- tst_lst = list()
- tst_lst_lat_1 = list()
- tst_lst_lat_2 = list()
- for bld in builds_dict[job_name]:
- itm = tst_data.get(int(bld), dict())
- # CSIT-1180: Itm will be list, compute stats.
- try:
- tst_lst.append(str(itm.get(u"receive-rate", u"")))
- if ttype == u"pdr":
- tst_lst_lat_1.append(
- str(itm.get(u"lat_1", u""))
- )
- tst_lst_lat_2.append(
- str(itm.get(u"lat_2", u""))
- )
- except AttributeError:
- tst_lst.append(u"")
- if ttype == u"pdr":
- tst_lst_lat_1.append(u"")
- tst_lst_lat_2.append(u"")
- csv_tbl.append(f"{tst_name}," + u",".join(tst_lst) + u'\n')
- csv_tbl_lat_1.append(
- f"{tst_name}," + u",".join(tst_lst_lat_1) + u"\n"
- )
- csv_tbl_lat_2.append(
- f"{tst_name}," + u",".join(tst_lst_lat_2) + u"\n"
- )
-
- # Generate traces:
- traces = list()
- traces_lat = list()
- index = 0
- groups = graph.get(u"groups", None)
- visibility = list()
-
- if groups:
- for group in groups:
- visible = list()
- for tag in group:
- for tst_name, test_data in chart_data.items():
- if not test_data:
- logging.warning(
- f"No data for the test {tst_name}"
- )
- continue
- if tag not in chart_tags[tst_name]:
- continue
- try:
- trace, rslt = _generate_trending_traces(
- test_data,
- job_name=job_name,
- build_info=build_info,
- name=u'-'.join(tst_name.split(u'.')[-1].
- split(u'-')[2:-1]),
- color=COLORS[index],
- incl_tests=ttype
- )
- except IndexError:
- logging.error(f"Out of colors: index: "
- f"{index}, test: {tst_name}")
- index += 1
- continue
- traces.extend(trace)
- visible.extend(
- [True for _ in range(len(trace))]
- )
- res[tst_name] = rslt
- index += 1
- break
- visibility.append(visible)
- else:
- for tst_name, test_data in chart_data.items():
- if not test_data:
- logging.warning(f"No data for the test {tst_name}")
- continue
- try:
- trace, rslt = _generate_trending_traces(
- test_data,
- job_name=job_name,
- build_info=build_info,
- name=u'-'.join(
- tst_name.split(u'.')[-1].split(u'-')[2:-1]),
- color=COLORS[index],
- incl_tests=ttype
- )
- if ttype == u"pdr":
- trace_lat, _ = _generate_trending_traces(
- test_data,
- job_name=job_name,
- build_info=build_info,
- name=u'-'.join(
- tst_name.split(u'.')[-1].split(
- u'-')[2:-1]),
- color=COLORS[index],
- incl_tests=u"pdr-lat"
- )
- traces_lat.extend(trace_lat)
- except IndexError:
- logging.error(
- f"Out of colors: index: "
- f"{index}, test: {tst_name}"
- )
- index += 1
- continue
- traces.extend(trace)
- res[tst_name] = rslt
- index += 1
-
- if traces:
- # Generate the chart:
- try:
- layout = deepcopy(graph[u"layout"])
- except KeyError as err:
- logging.error(u"Finished with error: No layout defined")
- logging.error(repr(err))
- return dict()
- if groups:
- show = list()
- for i in range(len(visibility)):
- visible = list()
- for vis_idx, _ in enumerate(visibility):
- for _ in range(len(visibility[vis_idx])):
- visible.append(i == vis_idx)
- show.append(visible)
-
- buttons = list()
- buttons.append(dict(
- label=u"All",
- method=u"update",
- args=[{u"visible":
- [True for _ in range(len(show[0]))]}, ]
- ))
- for i in range(len(groups)):
- try:
- label = graph[u"group-names"][i]
- except (IndexError, KeyError):
- label = f"Group {i + 1}"
- buttons.append(dict(
- label=label,
- method=u"update",
- args=[{u"visible": show[i]}, ]
- ))
-
- layout[u"updatemenus"] = list([
- dict(
- active=0,
- type=u"dropdown",
- direction=u"down",
- xanchor=u"left",
- yanchor=u"bottom",
- x=-0.12,
- y=1.0,
- buttons=buttons
- )
- ])
-
- name_file = (
- f"{spec.cpta[u'output-file']}/"
- f"{graph[u'output-file-name']}.html"
- )
- name_file = name_file.format(core=core, test_type=ttype)
-
- logging.info(f" Writing the file {name_file}")
- plpl = plgo.Figure(data=traces, layout=layout)
- try:
- ploff.plot(
- plpl,
- show_link=False,
- auto_open=False,
- filename=name_file
- )
- except plerr.PlotlyEmptyDataError:
- logging.warning(u"No data for the plot. Skipped.")
-
- if traces_lat:
- try:
- layout = deepcopy(graph[u"layout"])
- layout[u"yaxis"][u"title"] = u"Latency [s]"
- layout[u"yaxis"][u"tickformat"] = u".3s"
- except KeyError as err:
- logging.error(u"Finished with error: No layout defined")
- logging.error(repr(err))
- return dict()
- name_file = (
- f"{spec.cpta[u'output-file']}/"
- f"{graph[u'output-file-name']}-lat.html"
- )
- name_file = name_file.format(core=core, test_type=ttype)
-
- logging.info(f" Writing the file {name_file}")
- plpl = plgo.Figure(data=traces_lat, layout=layout)
- try:
- ploff.plot(
- plpl,
- show_link=False,
- auto_open=False,
- filename=name_file
- )
- except plerr.PlotlyEmptyDataError:
- logging.warning(u"No data for the plot. Skipped.")
-
- return_lst.append(
- {
- u"job_name": job_name,
- u"csv_table": csv_tbl,
- u"csv_lat_1": csv_tbl_lat_1,
- u"csv_lat_2": csv_tbl_lat_2,
- u"results": res
- }
- )
-
- return return_lst
-
- builds_dict = dict()
- for job, builds in spec.input.items():
- if builds_dict.get(job, None) is None:
- builds_dict[job] = list()
- for build in builds:
- if build[u"status"] not in (u"failed", u"not found", u"removed",
- None):
- builds_dict[job].append(str(build[u"build"]))
-
- # Create "build ID": "date" dict:
- build_info = dict()
- tb_tbl = spec.environment.get(u"testbeds", None)
- for job_name, job_data in builds_dict.items():
- if build_info.get(job_name, None) is None:
- build_info[job_name] = OrderedDict()
- for build in job_data:
- testbed = u""
- tb_ip = input_data.metadata(job_name, build).get(u"testbed", u"")
- if tb_ip and tb_tbl:
- testbed = tb_tbl.get(tb_ip, u"")
- build_info[job_name][build] = (
- input_data.metadata(job_name, build).get(u"generated", u""),
- input_data.metadata(job_name, build).get(u"version", u""),
- testbed
- )
-
- anomaly_classifications = dict()
-
- # Create the table header:
- csv_tables = dict()
- csv_tables_l1 = dict()
- csv_tables_l2 = dict()
- for job_name in builds_dict:
- if csv_tables.get(job_name, None) is None:
- csv_tables[job_name] = list()
- if csv_tables_l1.get(job_name, None) is None:
- csv_tables_l1[job_name] = list()
- if csv_tables_l2.get(job_name, None) is None:
- csv_tables_l2[job_name] = list()
- header = f"Build Number:,{u','.join(builds_dict[job_name])}\n"
- csv_tables[job_name].append(header)
- csv_tables_l1[job_name].append(header)
- csv_tables_l2[job_name].append(header)
- build_dates = [x[0] for x in build_info[job_name].values()]
- header = f"Build Date:,{u','.join(build_dates)}\n"
- csv_tables[job_name].append(header)
- csv_tables_l1[job_name].append(header)
- csv_tables_l2[job_name].append(header)
- versions = [x[1] for x in build_info[job_name].values()]
- header = f"Version:,{u','.join(versions)}\n"
- csv_tables[job_name].append(header)
- csv_tables_l1[job_name].append(header)
- csv_tables_l2[job_name].append(header)
- testbed = [x[2] for x in build_info[job_name].values()]
- header = f"Test bed:,{u','.join(testbed)}\n"
- csv_tables[job_name].append(header)
- csv_tables_l1[job_name].append(header)
- csv_tables_l2[job_name].append(header)
-
- for chart in spec.cpta[u"plots"]:
- results = _generate_chart(chart)
- if not results:
- continue
-
- for result in results:
- csv_tables[result[u"job_name"]].extend(result[u"csv_table"])
- csv_tables_l1[result[u"job_name"]].extend(result[u"csv_lat_1"])
- csv_tables_l2[result[u"job_name"]].extend(result[u"csv_lat_2"])
-
- if anomaly_classifications.get(result[u"job_name"], None) is None:
- anomaly_classifications[result[u"job_name"]] = dict()
- anomaly_classifications[result[u"job_name"]].\
- update(result[u"results"])
-
- # Write the tables:
- for job_name, csv_table in csv_tables.items():
- file_name = f"{spec.cpta[u'output-file']}/{job_name}-trending"
- with open(f"{file_name}.csv", u"wt") as file_handler:
- file_handler.writelines(csv_table)
-
- txt_table = None
- with open(f"{file_name}.csv", u"rt") as csv_file:
- csv_content = csv.reader(csv_file, delimiter=u',', quotechar=u'"')
- line_nr = 0
- for row in csv_content:
- if txt_table is None:
- txt_table = prettytable.PrettyTable(row)
- else:
- if line_nr > 1:
- for idx, item in enumerate(row):
- try:
- row[idx] = str(round(float(item) / 1000000, 2))
- except ValueError:
- pass
- try:
- txt_table.add_row(row)
- # PrettyTable raises Exception
- except Exception as err:
- logging.warning(
- f"Error occurred while generating TXT table:\n{err}"
- )
- line_nr += 1
- txt_table.align[u"Build Number:"] = u"l"
- with open(f"{file_name}.txt", u"wt") as txt_file:
- txt_file.write(str(txt_table))
-
- for job_name, csv_table in csv_tables_l1.items():
- file_name = f"{spec.cpta[u'output-file']}/{job_name}-lat-P50-50-d1"
- with open(f"{file_name}.csv", u"wt") as file_handler:
- file_handler.writelines(csv_table)
- for job_name, csv_table in csv_tables_l2.items():
- file_name = f"{spec.cpta[u'output-file']}/{job_name}-lat-P50-50-d2"
- with open(f"{file_name}.csv", u"wt") as file_handler:
- file_handler.writelines(csv_table)
-
- # Evaluate result:
- if anomaly_classifications:
- result = u"PASS"
- for job_name, job_data in anomaly_classifications.items():
- file_name = \
- f"{spec.cpta[u'output-file']}/regressions-{job_name}.txt"
- with open(file_name, u'w') as txt_file:
- for test_name, classification in job_data.items():
- if classification == u"regression":
- txt_file.write(test_name + u'\n')
- if classification in (u"regression", u"outlier"):
- result = u"FAIL"
- file_name = \
- f"{spec.cpta[u'output-file']}/progressions-{job_name}.txt"
- with open(file_name, u'w') as txt_file:
- for test_name, classification in job_data.items():
- if classification == u"progression":
- txt_file.write(test_name + u'\n')
- else:
- result = u"FAIL"
-
- logging.info(f"Partial results: {anomaly_classifications}")
- logging.info(f"Result: {result}")
-
- return result