X-Git-Url: https://gerrit.fd.io/r/gitweb?p=csit.git;a=blobdiff_plain;f=resources%2Ftools%2Fpresentation%2Fgenerator_tables.py;h=449b2357a8aa7e5165030d228b5bc79e7685b5a6;hp=d66a8fc3cfe6e7ec0ace951ddd09f3c63643d013;hb=1da19da813655f643bc3c6e4d03bed987f076f07;hpb=36048e330c53b0325fb120da0f7661ad2dd44611 diff --git a/resources/tools/presentation/generator_tables.py b/resources/tools/presentation/generator_tables.py index d66a8fc3cf..449b2357a8 100644 --- a/resources/tools/presentation/generator_tables.py +++ b/resources/tools/presentation/generator_tables.py @@ -24,6 +24,7 @@ from xml.etree import ElementTree as ET from datetime import datetime as dt from datetime import timedelta from copy import deepcopy +from json import loads import plotly.graph_objects as go import plotly.offline as ploff @@ -93,7 +94,7 @@ def table_oper_data_html(table, input_data): ) data = input_data.filter_data( table, - params=[u"name", u"parent", u"show-run", u"type"], + params=[u"name", u"parent", u"telemetry-show-run", u"type"], continue_on_error=True ) if data.empty: @@ -146,7 +147,8 @@ def table_oper_data_html(table, input_data): ) thead.text = u"\t" - if tst_data.get(u"show-run", u"No Data") == u"No Data": + if tst_data.get(u"telemetry-show-run", None) is None or \ + isinstance(tst_data[u"telemetry-show-run"], str): trow = ET.SubElement( tbl, u"tr", attrib=dict(bgcolor=colors[u"header"]) ) @@ -176,7 +178,7 @@ def table_oper_data_html(table, input_data): u"Average Vector Size" ) - for dut_data in tst_data[u"show-run"].values(): + for dut_data in tst_data[u"telemetry-show-run"].values(): trow = ET.SubElement( tbl, u"tr", attrib=dict(bgcolor=colors[u"header"]) ) @@ -187,37 +189,41 @@ def table_oper_data_html(table, input_data): tcol.text = u"No Data" continue - try: - threads_nr = len(dut_data[u"runtime"][0][u"clocks"]) - except (IndexError, KeyError): - tcol.text = u"No Data" - continue - - threads = OrderedDict({idx: list() for idx in range(threads_nr)}) - for item in dut_data[u"runtime"]: - for idx in range(threads_nr): - if item[u"vectors"][idx] > 0: - clocks = item[u"clocks"][idx] / item[u"vectors"][idx] - elif item[u"calls"][idx] > 0: - clocks = item[u"clocks"][idx] / item[u"calls"][idx] - elif item[u"suspends"][idx] > 0: - clocks = item[u"clocks"][idx] / item[u"suspends"][idx] + runtime = dict() + for item in dut_data[u"runtime"].get(u"data", tuple()): + tid = int(item[u"labels"][u"thread_id"]) + if runtime.get(tid, None) is None: + runtime[tid] = dict() + gnode = item[u"labels"][u"graph_node"] + if runtime[tid].get(gnode, None) is None: + runtime[tid][gnode] = dict() + try: + runtime[tid][gnode][item[u"name"]] = float(item[u"value"]) + except ValueError: + runtime[tid][gnode][item[u"name"]] = item[u"value"] + + threads = dict({idx: list() for idx in range(len(runtime))}) + for idx, run_data in runtime.items(): + for gnode, gdata in run_data.items(): + if gdata[u"vectors"] > 0: + clocks = gdata[u"clocks"] / gdata[u"vectors"] + elif gdata[u"calls"] > 0: + clocks = gdata[u"clocks"] / gdata[u"calls"] + elif gdata[u"suspends"] > 0: + clocks = gdata[u"clocks"] / gdata[u"suspends"] else: clocks = 0.0 - - if item[u"calls"][idx] > 0: - vectors_call = item[u"vectors"][idx] / item[u"calls"][ - idx] + if gdata[u"calls"] > 0: + vectors_call = gdata[u"vectors"] / gdata[u"calls"] else: vectors_call = 0.0 - - if int(item[u"calls"][idx]) + int(item[u"vectors"][idx]) + \ - int(item[u"suspends"][idx]): + if int(gdata[u"calls"]) + int(gdata[u"vectors"]) + \ + int(gdata[u"suspends"]): threads[idx].append([ - item[u"name"], - item[u"calls"][idx], - item[u"vectors"][idx], - item[u"suspends"][idx], + gnode, + int(gdata[u"calls"]), + int(gdata[u"vectors"]), + int(gdata[u"suspends"]), clocks, vectors_call ]) @@ -384,14 +390,13 @@ def table_merged_details(table, input_data): # Temporary solution: remove NDR results from message: if bool(table.get(u'remove-ndr', False)): try: - col_data = col_data.split(u" |br| ", 1)[1] + col_data = col_data.split(u"\n", 1)[1] except IndexError: pass col_data = col_data.replace(u'\n', u' |br| ').\ replace(u'\r', u'').replace(u'"', u"'") col_data = f" |prein| {col_data} |preout| " - elif column[u"data"].split(u" ")[1] in \ - (u"conf-history", u"show-run"): + elif column[u"data"].split(u" ")[1] in (u"conf-history", ): col_data = col_data.replace(u'\n', u' |br| ') col_data = f" |prein| {col_data[:-5]} |preout| " row_lst.append(f'"{col_data}"') @@ -912,7 +917,11 @@ def table_perf_trending_dash(table, input_data): if len(data_t) < 2: continue - classification_lst, avgs, _ = classify_anomalies(data_t) + try: + classification_lst, avgs, _ = classify_anomalies(data_t) + except ValueError as err: + logging.info(f"{err} Skipping") + return win_size = min(len(data_t), table[u"window"]) long_win_size = min(len(data_t), table[u"long-trend-window"]) @@ -1225,6 +1234,9 @@ def table_perf_trending_dash_html(table, input_data): try: with open(table[u"input-file"], u'rt') as csv_file: csv_lst = list(csv.reader(csv_file, delimiter=u',', quotechar=u'"')) + except FileNotFoundError as err: + logging.warning(f"{err}") + return except KeyError: logging.warning(u"The input file is not defined.") return @@ -1336,6 +1348,8 @@ def table_last_failed_tests(table, input_data): build = str(build) try: version = input_data.metadata(job, build).get(u"version", u"") + duration = \ + input_data.metadata(job, build).get(u"elapsedtime", u"") except KeyError: logging.error(f"Data for {job}: {build} is not present.") return @@ -1354,15 +1368,16 @@ def table_last_failed_tests(table, input_data): continue nic = groups.group(0) failed_tests.append(f"{nic}-{tst_data[u'name']}") - tbl_list.append(str(passed)) - tbl_list.append(str(failed)) + tbl_list.append(passed) + tbl_list.append(failed) + tbl_list.append(duration) tbl_list.extend(failed_tests) file_name = f"{table[u'output-file']}{table[u'output-file-ext']}" logging.info(f" Writing file: {file_name}") with open(file_name, u"wt") as file_handler: for test in tbl_list: - file_handler.write(test + u'\n') + file_handler.write(f"{test}\n") def table_failed_tests(table, input_data):