Show each sensor's longest report gap; stop recording volatile attributes

Choosing room and weather freshness limits required knowing how long
each sensor normally goes without reporting, which HA does not show.
Add max_age_seconds_24h to every source in input_quality: the largest
report age seen at polls over the last 24 hours (hourly buckets, reset
on reload, underestimates by up to one poll interval).

input_quality and weather_comparison change every poll, so the Recorder
stored a new attribute row every five minutes. Mark them unrecorded;
they remain visible on the Status entity. Model coefficients and other
attributes are still recorded.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
This commit is contained in:
buzeraandClaude Opus 5.5 committed 2026-10-26 21:51:35 +02:00
1 parent c0e4de832b
commit 4daba5028b
6 files changed
+64 -3

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@@ -1,6 +1,7 @@
"""Pure timestamp validation for reported sensor snapshots."""
from __future__ import annotations
from collections import deque
from datetime import datetime
from math import isfinite
@@ -16,3 +17,23 @@ def freshness(reported: datetime | None, now: datetime, max_age_seconds: float)
return {"status": "future_timestamp", "age_seconds": round(age, 1)}
return {"status": "stale" if age > max_age_seconds else "valid",
"age_seconds": round(age, 1)}
class ReportAgeHistory:
"""Largest report age seen at polls per entity over the last 24 hours.
Helps choose freshness limits: a limit below a sensor's normal maximum
marks it stale during ordinary operation. Hourly buckets keep memory bounded.
"""
def __init__(self) -> None:
self._buckets: dict[str, deque[list[float]]] = {}
def observe(self, entity_id: str, now: datetime, age_seconds: float) -> float:
hour = now.timestamp() // 3600
buckets = self._buckets.setdefault(entity_id, deque(maxlen=25))
if buckets and buckets[-1][0] == hour:
buckets[-1][1] = max(buckets[-1][1], age_seconds)
else:
buckets.append([hour, age_seconds])
return max(age for start, age in buckets if hour - 24 < start <= hour)