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Expose aggregated metrics #204

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Merged
flora-hofmann-frequenz merged 1 commit into from
Jul 9, 2025
Merged

Expose aggregated metrics #204

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2 changes: 1 addition & 1 deletion RELEASE_NOTES.md
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@

## New Features

<!-- Here goes the main new features and examples or instructions on how to use them -->
* Expose aggregated metrics if available.

## Bug Fixes

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33 changes: 24 additions & 9 deletions src/frequenz/client/reporting/_types.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,6 @@

"""Types for the Reporting API client."""

import math
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
from datetime import datetime, timezone
Expand Down Expand Up @@ -70,11 +69,13 @@ def is_empty(self) -> bool:
return True
return False

# pylint: disable=too-many-locals
# pylint: disable=too-many-branches
def __iter__(self) -> Iterator[MetricSample]:
"""Get generator that iterates over all values in the batch.

Note: So far only `SimpleMetricSample` in the `MetricSampleVariant`
message is supported.
`SimpleMetricSample` and `AggregatedMetricSample` in the
`MetricSampleVariant` message is supported.


Yields:
Expand All @@ -93,12 +94,26 @@ def __iter__(self) -> Iterator[MetricSample]:
for sample in getattr(item, "metric_samples", []):
ts = sample.sampled_at.ToDatetime().replace(tzinfo=timezone.utc)
met = Metric.from_proto(sample.metric).name
value = (
sample.value.simple_metric.value
if sample.value.HasField("simple_metric")
else math.nan
)
yield MetricSample(ts, mid, cid, met, value)

# Handle simple_metric
if sample.value.HasField("simple_metric"):
value = sample.value.simple_metric.value
yield MetricSample(ts, mid, cid, met, value)

# Handle aggregated_metric
if sample.value.HasField("aggregated_metric"):
agg = sample.value.aggregated_metric
# Average value
yield MetricSample(ts, mid, cid, f"{met}_avg", agg.avg_value)
# Min value if present
if agg.HasField("min_value"):
yield MetricSample(ts, mid, cid, f"{met}_min", agg.min_value)
# Max value if present
if agg.HasField("max_value"):
yield MetricSample(ts, mid, cid, f"{met}_max", agg.max_value)
# Optionally yield individual raw values
for i, raw in enumerate(agg.raw_values):
yield MetricSample(ts, mid, cid, f"{met}_raw_{i}", raw)

if self.has_bounds:
for i, bound in enumerate(sample.bounds):
Expand Down
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