def __generate(config_run, title, live_run=True):
run_id = config_run["run_id"]
print("Generate report for config run_id: " + repr(run_id))
metrics = __get_metrics(config_run, title, live_run)
metrics = __enrich_metrics(metrics)
__complete_charts(run_id, metrics, title, config_run)
if live_run:
__update_runtime_timestamp(run_id, report.get_last_timestamp(metrics), "true") # trigger termination runtime report js reload loop
print("Finished run " + repr(run_id))
print("Complete report for test_config run " + repr(run_id) + ":\n" + complete_report_url(run_id))
def __generate(config_run, title, live_run=True):
run_id = config_run["run_id"]
print("Generate report for config run_id: " + repr(run_id))
metrics = __get_metrics(config_run, title, live_run)
metrics = __enrich_metrics(metrics)
__complete_charts(run_id, metrics, title, config_run)
if live_run:
__update_runtime_timestamp(
run_id, report.get_last_timestamp(metrics),
"true") # trigger termination runtime report js reload loop
print("Finished run " + repr(run_id))
print("Complete report for test_config run " + repr(run_id) + ":\n" +
complete_report_url(run_id))
def __get_metrics(config_run, title, live_run=True):
run_id = config_run["run_id"]
__prepare(run_id)
__save_meta(run_id, title, config_run)
metrics = None
if live_run:
print("Current runtime report is " + __report_path(run_id) +
"/runtime/runtime_report.html")
create_runtime_report = True
test_run = liclient.client.get_test(run_id)
stream = test_run.result_stream(__get_result_ids(config_run))
# Wait for test to finish
for data in stream(poll_rate=3):
if (
CLIENTS_ACTIVE_KEY not in data
): # Only treat data which has real metrics, otherwise it is just booting msg etc. (e.g. live feed)
continue
metrics = stream.series
__store_metrics(run_id, metrics)
if create_runtime_report:
# update timestamp to trigger js auto-reload
__update_runtime_timestamp(run_id,
report.get_last_timestamp(metrics))
__runtime_charts(run_id, metrics, config_run)
time.sleep(3)
__store_metrics(run_id, metrics)
metrics = stream.series
else:
metrics = __get_finished_run_results(run_id, config_run)
if (
CLIENTS_ACTIVE_KEY not in metrics
): # Only treat data which has real metrics, otherwise it is just booting msg etc. (e.g. live feed)
print(
"metrics (for config run %s) missing %s, we assume data is incomplete"
% (run_id, CLIENTS_ACTIVE_KEY))
print("submetrics present: " + ", ".join(metrics.keys()))
return
clients_active = metrics[CLIENTS_ACTIVE_KEY]
if not clients_active:
print(
"metrics (for config run %s) missing %s, we assume data is incomplete"
% (run_id, CLIENTS_ACTIVE_KEY))
print("submetrics present: " + ", ".join(metrics.keys()))
return
return metrics
def __get_metrics(config_run, title, live_run=True):
run_id = config_run["run_id"]
__prepare(run_id)
__save_meta(run_id, title, config_run)
metrics = None
if live_run:
print("Current runtime report is " + __report_path(run_id) + "/runtime/runtime_report.html")
create_runtime_report = True
test_run = liclient.client.get_test(run_id)
stream = test_run.result_stream(__get_result_ids(config_run))
# Wait for test to finish
for data in stream(poll_rate=3):
if (CLIENTS_ACTIVE_KEY not in data): # Only treat data which has real metrics, otherwise it is just booting msg etc. (e.g. live feed)
continue
metrics = stream.series
__store_metrics(run_id, metrics)
if create_runtime_report:
# update timestamp to trigger js auto-reload
__update_runtime_timestamp(run_id, report.get_last_timestamp(metrics))
__runtime_charts(run_id, metrics, config_run)
time.sleep(3)
__store_metrics(run_id, metrics)
metrics = stream.series
else:
metrics = __get_finished_run_results(run_id, config_run)
if (CLIENTS_ACTIVE_KEY not in metrics): # Only treat data which has real metrics, otherwise it is just booting msg etc. (e.g. live feed)
print("metrics (for config run %s) missing %s, we assume data is incomplete" % (run_id, CLIENTS_ACTIVE_KEY))
print("submetrics present: " + ", ".join(metrics.keys()))
return
clients_active = metrics[CLIENTS_ACTIVE_KEY]
if not clients_active:
print("metrics (for config run %s) missing %s, we assume data is incomplete" % (run_id, CLIENTS_ACTIVE_KEY))
print("submetrics present: " + ", ".join(metrics.keys()))
return
return metrics
