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BigBodyCobain
50 lines
1.4 KiB
Python
50 lines
1.4 KiB
Python
"""Lightweight metrics for mesh protocol health signals."""
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from __future__ import annotations
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import threading
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import time
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_lock = threading.Lock()
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_metrics: dict[str, int] = {}
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_timers: dict[str, dict[str, float]] = {}
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_last_updated: float = 0.0
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def increment(name: str, count: int = 1) -> None:
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global _last_updated
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with _lock:
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_metrics[name] = _metrics.get(name, 0) + count
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_last_updated = time.time()
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def observe_ms(name: str, duration_ms: float) -> None:
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global _last_updated
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sample = max(0.0, float(duration_ms or 0.0))
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with _lock:
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bucket = dict(_timers.get(name) or {})
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bucket["count"] = float(bucket.get("count", 0.0)) + 1.0
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bucket["total_ms"] = float(bucket.get("total_ms", 0.0)) + sample
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bucket["max_ms"] = max(float(bucket.get("max_ms", 0.0)), sample)
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bucket["last_ms"] = sample
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bucket["avg_ms"] = bucket["total_ms"] / max(bucket["count"], 1.0)
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_timers[name] = bucket
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_last_updated = time.time()
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def reset() -> None:
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global _last_updated
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with _lock:
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_metrics.clear()
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_timers.clear()
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_last_updated = 0.0
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def snapshot() -> dict:
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with _lock:
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return {
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"updated_at": _last_updated,
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"counters": dict(_metrics),
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"timers": {name: dict(bucket) for name, bucket in _timers.items()},
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}
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