def get_measures_or_abort(metrics_and_aggregations, operations, start, stop,
granularity, needed_overlap, fill, ref_identifier):
try:
return processor.get_measures(pecan.request.storage,
metrics_and_aggregations,
operations,
start,
stop,
granularity,
needed_overlap,
fill,
ref_identifier=ref_identifier)
except exceptions.UnAggregableTimeseries as e:
api.abort(400, e)
# TODO(sileht): We currently got only one metric for these exceptions but
# we can improve processor to returns all missing metrics at once, so we
# returns a list for the future
except storage.MetricDoesNotExist as e:
api.abort(404, {
"cause": "Unknown metrics",
"detail": [str(e.metric.id)]
})
except storage.AggregationDoesNotExist as e:
api.abort(
404, {
"cause": "Metrics with unknown aggregation",
"detail": [(str(e.metric.id), e.method)]
})
def get_measures_or_abort(references, operations, start,
stop, granularity, needed_overlap, fill):
try:
return processor.get_measures(
pecan.request.storage,
references,
operations,
start, stop,
granularity, needed_overlap, fill)
except exceptions.UnAggregableTimeseries as e:
api.abort(400, e)
# TODO(sileht): We currently got only one metric for these exceptions but
# we can improve processor to returns all missing metrics at once, so we
# returns a list for the future
except storage.MetricDoesNotExist as e:
api.abort(404, {"cause": "Unknown metrics",
"detail": [str(e.metric.id)]})
except storage.AggregationDoesNotExist as e:
api.abort(404, {"cause": "Metrics with unknown aggregation",
"detail": [(str(e.metric.id), e.method)]})