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=0884da80eed536eed5af45653ba1028bf9a30137;hb=HEAD;hpb=a6ed764aecf2983a759931cc8d4bef161045d062 diff --git a/resources/tools/presentation/generator_cpta.py b/resources/tools/presentation/generator_cpta.py deleted file mode 100644 index 0884da80ee..0000000000 --- a/resources/tools/presentation/generator_cpta.py +++ /dev/null @@ -1,682 +0,0 @@ -# Copyright (c) 2020 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 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 conf_cpta -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"#45A27D", - u"#391285", - u"#C95A49", - u"#FFD12A", - u"#738276", - u"#BD8260", - u"#FC5A8D", - u"#CEC8EF", - u"#A6E7FF", - u"#6F2DA8", - u"#FF878D", - u"#01786F", - 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.configuration.get(u"archive-inputs", True): - 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"): - return list(), None - - data_x = list(in_data.keys()) - data_y_pps = list() - data_y_mpps = list() - data_y_stdev = list() - 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) - - 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]: {value:.3f}
" - 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 u"dpdk" in job_name: - hover_text.append(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.lower(), - period=u"weekly", - build_nr=str_key, - testbed=build_info[job_name][str_key][2])) - elif u"vpp" in job_name: - hover_text.append(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.lower(), - period=u"daily" if incl_tests == u"MRR" else u"weekly", - build_nr=str_key, - testbed=build_info[job_name][str_key][2])) - - 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 - - anomaly_classification, avgs_pps, stdevs_pps = classify_anomalies(data_pd) - avgs_mpps = [avg_pps / 1e6 for avg_pps in avgs_pps] - stdevs_mpps = [stdev_pps / 1e6 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 / 1e6 - 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)): - 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) - - 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": [ - [0.00, u"red"], - [0.33, u"red"], - [0.33, u"white"], - [0.66, u"white"], - [0.66, u"green"], - [1.00, u"green"] - ], - 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": [u"Regression", u"Normal", u"Progression"], - 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'')} ...") - - incl_tests = graph.get(u"include-tests", u"MRR") - - job_name = list(graph[u"data"].keys())[0] - - csv_tbl = list() - res = dict() - - # Transform the data - logging.info( - f" Creating the data set for the {graph.get(u'type', u'')} " - f"{graph.get(u'title', u'')}." - ) - - if graph.get(u"include", None): - data = input_data.filter_tests_by_name( - graph, - params=[u"type", u"result", u"throughput", u"tags"], - continue_on_error=True - ) - else: - data = input_data.filter_data( - graph, - params=[u"type", u"result", u"throughput", u"tags"], - continue_on_error=True) - - if data is None or data.empty: - logging.error(u"No data.") - return dict() - - chart_data = dict() - chart_tags = dict() - for job, job_data in data.items(): - if job != job_name: - continue - for index, bld in job_data.items(): - for test_name, test in bld.items(): - if chart_data.get(test_name, None) is None: - chart_data[test_name] = OrderedDict() - try: - if incl_tests == u"MRR": - rate = test[u"result"][u"receive-rate"] - stdev = test[u"result"][u"receive-stdev"] - elif incl_tests == u"NDR": - rate = test[u"throughput"][u"NDR"][u"LOWER"] - stdev = float(u"nan") - elif incl_tests == u"PDR": - rate = test[u"throughput"][u"PDR"][u"LOWER"] - stdev = float(u"nan") - else: - continue - chart_data[test_name][int(index)] = { - u"receive-rate": rate, - u"receive-stdev": stdev - } - chart_tags[test_name] = 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() - 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""))) - except AttributeError: - tst_lst.append(u"") - csv_tbl.append(f"{tst_name}," + u",".join(tst_lst) + u'\n') - - # Generate traces: - traces = 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=incl_tests - ) - 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=incl_tests - ) - except IndexError: - logging.error( - f"Out of colors: index: {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']}/{graph[u'output-file-name']}" - f"{spec.cpta[u'output-file-type']}") - - 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.") - - return {u"job_name": job_name, u"csv_table": csv_tbl, u"results": res} - - builds_dict = dict() - for job in spec.input[u"builds"].keys(): - if builds_dict.get(job, None) is None: - builds_dict[job] = list() - for build in spec.input[u"builds"][job]: - status = build[u"status"] - if 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() - for job_name in builds_dict: - if csv_tables.get(job_name, None) is None: - csv_tables[job_name] = list() - header = f"Build Number:,{u','.join(builds_dict[job_name])}\n" - csv_tables[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) - versions = [x[1] for x in build_info[job_name].values()] - header = f"Version:,{u','.join(versions)}\n" - csv_tables[job_name].append(header) - - for chart in spec.cpta[u"plots"]: - result = _generate_chart(chart) - if not result: - continue - - csv_tables[result[u"job_name"]].extend(result[u"csv_table"]) - - 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)) - - # 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