+ graph["layout"]["title"] = \
+ "<b>{title}</b>".format(title=graph.get("title", ""))
+ name_file = "{0}-{1}{2}".format(spec.cpta["output-file"],
+ graph["output-file-name"],
+ spec.cpta["output-file-type"])
+
+ logs.append(("INFO", " Writing the file '{0}' ...".
+ format(name_file)))
+ plpl = plgo.Figure(data=traces, layout=graph["layout"])
+ try:
+ ploff.plot(plpl, show_link=False, auto_open=False,
+ filename=name_file)
+ except plerr.PlotlyEmptyDataError:
+ 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)
+
+ 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" and \
+ status != "removed":
+ builds_dict[job].append(str(build["build"]))
+
+ # Create "build ID": "date" dict:
+ build_info = dict()
+ tb_tbl = spec.environment.get("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 = ""
+ tb_ip = input_data.metadata(job_name, build).get("testbed", "")
+ if tb_ip and tb_tbl:
+ testbed = tb_tbl.get(tb_ip, "")
+ build_info[job_name][build] = (
+ input_data.metadata(job_name, build).get("generated", ""),
+ input_data.metadata(job_name, build).get("version", ""),
+ testbed
+ )
+
+ work_queue = multiprocessing.JoinableQueue()
+ manager = multiprocessing.Manager()
+ data_queue = manager.Queue()
+ cpus = multiprocessing.cpu_count()
+
+ workers = list()
+ for cpu in range(cpus):
+ worker = Worker(work_queue,
+ data_queue,
+ _generate_chart)
+ worker.daemon = True
+ worker.start()
+ workers.append(worker)
+ os.system("taskset -p -c {0} {1} > /dev/null 2>&1".
+ format(cpu, worker.pid))
+
+ for chart in spec.cpta["plots"]:
+ work_queue.put((chart, ))
+ work_queue.join()
+
+ anomaly_classifications = list()
+
+ # Create the 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_tables[result["job_name"]].extend(result["csv_table"])
+
+ for item in result["logs"]:
+ if item[0] == "INFO":
+ logging.info(item[1])
+ elif item[0] == "ERROR":
+ logging.error(item[1])
+ elif item[0] == "DEBUG":
+ logging.debug(item[1])
+ elif item[0] == "CRITICAL":
+ logging.critical(item[1])
+ elif item[0] == "WARNING":
+ logging.warning(item[1])
+
+ del data_queue
+
+ # Terminate all workers
+ for worker in workers:
+ worker.terminate()
+ worker.join()