diff options
Diffstat (limited to 'resources/tools/presentation/generator_CPTA.py')
| -rw-r--r-- | resources/tools/presentation/generator_CPTA.py | 147 |
1 files changed, 83 insertions, 64 deletions
diff --git a/resources/tools/presentation/generator_CPTA.py b/resources/tools/presentation/generator_CPTA.py index 2c62e11a97..c996aca0bd 100644 --- a/resources/tools/presentation/generator_CPTA.py +++ b/resources/tools/presentation/generator_CPTA.py @@ -87,7 +87,7 @@ def generate_cpta(spec, data): return ret_code -def _generate_trending_traces(in_data, build_info, moving_win_size=10, +def _generate_trending_traces(in_data, job_name, build_info, moving_win_size=10, show_trend_line=True, name="", color=""): """Generate the trending traces: - samples, @@ -95,12 +95,14 @@ def _generate_trending_traces(in_data, build_info, moving_win_size=10, - outliers, regress, progress :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 moving_win_size: Window size. :param show_trend_line: Show moving median (trending plot). :param name: Name of the plot :param color: Name of the color for the plot. :type in_data: OrderedDict + :type job_name: str :type build_info: dict :type moving_win_size: int :type show_trend_line: bool @@ -116,10 +118,15 @@ def _generate_trending_traces(in_data, build_info, moving_win_size=10, hover_text = list() xaxis = list() for idx in data_x: - hover_text.append("vpp-ref: {0}<br>csit-ref: mrr-daily-build-{1}". - format(build_info[str(idx)][1].rsplit('~', 1)[0], - idx)) - date = build_info[str(idx)][0] + if "dpdk" in job_name: + hover_text.append("dpdk-ref: {0}<br>csit-ref: mrr-weekly-build-{1}". + format(build_info[job_name][str(idx)][1]. + rsplit('~', 1)[0], idx)) + elif "vpp" in job_name: + hover_text.append("vpp-ref: {0}<br>csit-ref: mrr-daily-build-{1}". + format(build_info[job_name][str(idx)][1]. + rsplit('~', 1)[0], idx)) + date = build_info[job_name][str(idx)][0] xaxis.append(datetime(int(date[0:4]), int(date[4:6]), int(date[6:8]), int(date[9:11]), int(date[12:]))) @@ -229,7 +236,10 @@ def _generate_trending_traces(in_data, build_info, moving_win_size=10, ) traces.append(trace_trend) - return traces, anomaly_classification[-1] + if anomaly_classification: + return traces, anomaly_classification[-1] + else: + return traces, None def _generate_all_charts(spec, input_data): @@ -252,7 +262,7 @@ def _generate_all_charts(spec, input_data): logs.append(("INFO", " Generating the chart '{0}' ...". format(graph.get("title", "")))) - job_name = spec.cpta["data"].keys()[0] + job_name = graph["data"].keys()[0] csv_tbl = list() res = list() @@ -266,8 +276,10 @@ def _generate_all_charts(spec, input_data): return chart_data = dict() - for job in data: - for index, bld in job.items(): + for job, job_data in data.iteritems(): + 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() @@ -280,7 +292,7 @@ def _generate_all_charts(spec, input_data): # Add items to the csv table: for tst_name, tst_data in chart_data.items(): tst_lst = list() - for bld in builds_lst: + for bld in builds_dict[job_name]: itm = tst_data.get(int(bld), '') tst_lst.append(str(itm)) csv_tbl.append("{0},".format(tst_name) + ",".join(tst_lst) + '\n') @@ -296,6 +308,7 @@ def _generate_all_charts(spec, input_data): test_name = test_name.split('.')[-1] trace, rslt = _generate_trending_traces( test_data, + job_name=job_name, build_info=build_info, moving_win_size=win_size, name='-'.join(test_name.split('-')[3:-1]), @@ -322,30 +335,32 @@ def _generate_all_charts(spec, input_data): logs.append(("WARNING", "No data for the plot. Skipped.")) data_out = { + "job_name": job_name, "csv_table": csv_tbl, "results": res, "logs": logs } data_q.put(data_out) - job_name = spec.cpta["data"].keys()[0] - - builds_lst = list() - for build in spec.input["builds"][job_name]: - status = build["status"] - if status != "failed" and status != "not found": - builds_lst.append(str(build["build"])) - - # Get "build ID": "date" dict: - build_info = OrderedDict() - for build in builds_lst: - try: - build_info[build] = ( - input_data.metadata(job_name, build)["generated"][:14], - input_data.metadata(job_name, build)["version"] + builds_dict = dict() + for job in spec.input["builds"].keys(): + if builds_dict.get(job, None) is None: + builds_dict[job] = list() + for build in spec.input["builds"][job]: + status = build["status"] + if status != "failed" and status != "not found": + builds_dict[job].append(str(build["build"])) + + # Create "build ID": "date" dict: + build_info = dict() + 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: + build_info[job_name][build] = ( + input_data.metadata(job_name, build).get("generated", ""), + input_data.metadata(job_name, build).get("version", "") ) - except KeyError: - build_info[build] = ("", "") work_queue = multiprocessing.JoinableQueue() manager = multiprocessing.Manager() @@ -370,21 +385,24 @@ def _generate_all_charts(spec, input_data): anomaly_classifications = list() # Create the header: - csv_table = list() - header = "Build Number:," + ",".join(builds_lst) + '\n' - csv_table.append(header) - build_dates = [x[0] for x in build_info.values()] - header = "Build Date:," + ",".join(build_dates) + '\n' - csv_table.append(header) - vpp_versions = [x[1] for x in build_info.values()] - header = "VPP Version:," + ",".join(vpp_versions) + '\n' - csv_table.append(header) + csv_tables = dict() + for job_name in builds_dict.keys(): + if csv_tables.get(job_name, None) is None: + csv_tables[job_name] = list() + header = "Build Number:," + ",".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 = "Build Date:," + ",".join(build_dates) + '\n' + csv_tables[job_name].append(header) + versions = [x[1] for x in build_info[job_name].values()] + header = "Version:," + ",".join(versions) + '\n' + csv_tables[job_name].append(header) while not data_queue.empty(): result = data_queue.get() anomaly_classifications.extend(result["results"]) - csv_table.extend(result["csv_table"]) + csv_tables[result["job_name"]].extend(result["csv_table"]) for item in result["logs"]: if item[0] == "INFO": @@ -406,33 +424,34 @@ def _generate_all_charts(spec, input_data): worker.join() # Write the tables: - file_name = spec.cpta["output-file"] + "-trending" - with open("{0}.csv".format(file_name), 'w') as file_handler: - file_handler.writelines(csv_table) - - txt_table = None - with open("{0}.csv".format(file_name), 'rb') as csv_file: - csv_content = csv.reader(csv_file, delimiter=',', quotechar='"') - 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) - except Exception as err: - logging.warning("Error occurred while generating TXT table:" - "\n{0}".format(err)) - line_nr += 1 - txt_table.align["Build Number:"] = "l" - with open("{0}.txt".format(file_name), "w") as txt_file: - txt_file.write(str(txt_table)) + for job_name, csv_table in csv_tables.items(): + file_name = spec.cpta["output-file"] + "-" + job_name + "-trending" + with open("{0}.csv".format(file_name), 'w') as file_handler: + file_handler.writelines(csv_table) + + txt_table = None + with open("{0}.csv".format(file_name), 'rb') as csv_file: + csv_content = csv.reader(csv_file, delimiter=',', quotechar='"') + 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) + except Exception as err: + logging.warning("Error occurred while generating TXT " + "table:\n{0}".format(err)) + line_nr += 1 + txt_table.align["Build Number:"] = "l" + with open("{0}.txt".format(file_name), "w") as txt_file: + txt_file.write(str(txt_table)) # Evaluate result: if anomaly_classifications: |