def _create_scatter_elements(cls, properties, context):
columns, data_rows = cls._get_data(properties,
context) # type: ignore[call-arg]
elements = []
metric_name = get_metric_info(properties["metric"], 0)[0]["title"]
for row in data_rows:
d_row = dict(zip(columns, row))
series = merge_multicol(d_row, columns, properties)
site, host = row[:2]
for ts, elem in series.time_data_pairs():
if elem:
elements.append({
"timestamp":
ts,
"value":
round(elem, 3),
"tag":
"scatter",
"label":
host,
"url":
cls._create_url_to_service_view(
site, host, metric_name),
"tooltip":
"%s on %s: %.2f" % (host, date_and_time(ts), elem),
})
return elements
def create_data_for_single_metric(cls, properties, context):
columns, data_rows = cls._get_data(properties, context)
data = []
used_metrics = []
for idx, row in enumerate(data_rows):
d_row = dict(zip(columns, row))
translated_metrics = translate_perf_data(
d_row["service_perf_data"], d_row["service_check_command"])
metric = translated_metrics.get(properties['metric'])
if metric is None:
continue
series = merge_multicol(d_row, columns, properties)
site = d_row['site']
host = d_row["host_name"]
svc_url = makeuri(
request,
[("view_name", "service"), ("site", site), ("host", host),
("service", d_row['service_description'])],
filename="view.py",
)
row_id = "row_%d" % idx
# Historic values
for ts, elem in series.time_data_pairs():
if elem:
data.append({
"tag": row_id,
"timestamp": ts,
"value": elem,
"label": host,
})
# Live value
data.append({
"tag":
row_id,
"timestamp":
int(time.time()),
"value":
metric['value'],
"formatted_value":
metric['unit']['render'](metric['value']),
"url":
svc_url,
"label":
host,
})
used_metrics.append((row_id, metric, d_row))
return data, used_metrics
def create_data_for_single_metric(
properties,
context: VisualContext,
column_generator: Callable[[Any, VisualContext], List[str]],
) -> Tuple[List[Dict[str, Any]], List[Tuple[str, TranslatedMetric, Dict[str, LivestatusColumn]]]]:
# TODO: should return live value and historic values as two different elements, for better typing support.
columns, data_rows = service_table_query(properties, context, column_generator)
data = []
used_metrics = []
for idx, row in enumerate(data_rows):
d_row = dict(zip(columns, row))
translated_metrics = translate_perf_data(
d_row["service_perf_data"], d_row["service_check_command"]
)
metric = translated_metrics.get(properties["metric"])
if metric is None:
continue
series = merge_multicol(d_row, columns, properties)
host = d_row["host_name"]
row_id = "row_%d" % idx
# Historic values
for ts, elem in series.time_data_pairs():
if elem:
data.append(
{
"tag": row_id,
"timestamp": ts,
"value": elem,
"label": host,
}
)
# Live value
data.append(
{
"tag": row_id,
"last_value": True,
"timestamp": int(time.time()),
"value": metric["value"],
"label": host,
"url": create_service_view_url(d_row),
}
)
used_metrics.append((row_id, metric, d_row))
return data, used_metrics
def create_data_for_single_metric(properties, context, column_generator):
columns, data_rows = service_table_query(properties, context,
column_generator)
data = []
used_metrics = []
for idx, row in enumerate(data_rows):
d_row = dict(zip(columns, row))
translated_metrics = translate_perf_data(
d_row["service_perf_data"], d_row["service_check_command"])
metric = translated_metrics.get(properties['metric'])
if metric is None:
continue
series = merge_multicol(d_row, columns, properties)
host = d_row["host_name"]
row_id = "row_%d" % idx
# Historic values
for ts, elem in series.time_data_pairs():
if elem:
data.append({
"tag": row_id,
"timestamp": ts,
"value": elem,
"label": host,
})
# Live value
data.append({
"tag": row_id,
"last_value": True,
"timestamp": int(time.time()),
"value": metric['value'],
"label": host,
"url": create_service_view_url(d_row),
})
used_metrics.append((row_id, metric, d_row))
return data, used_metrics
