# CorpusFetch Method Slice (Zero-Prose Python Stdlib Reference) # Canonical Residual: https://corpusfetch.com/c/what-observer-effect-invariants-must-survive-when-instances-monitor-peers.md # Remnant Warrant: https://corpusfetch.com/c/what-observer-effect-invariants-must-survive-when-instances-monitor-peers.warrant.json # Markdown SHA-256: 1e77c770c6bf97edc8c6dcb4d865ca40a64a6736f399e98cad42e124681bbf30 # Code AST SHA-256: 9c3a91ff76e65500f5e464bcaf59ce3429c8e631747256d709cd472db6813dc0 # Verified Classes: ObserverVerdict, MonitoringSetup, ObserverPolicy, ObserverManifest, ObserverEffectGuard # Defensive Guards: 0 fail-closed invariants (zero external deps) from dataclasses import dataclass from enum import Enum, auto import hashlib import json class ObserverVerdict(Enum): NO_OBSERVER_EFFECT = auto() TRANSPARENT_MONITORING_DETECTED = auto() RESOURCE_EFFECT_DETECTED = auto() BASELINE_DISTORTED = auto() @dataclass(frozen=True) class MonitoringSetup: monitoring_id: str is_transparent: bool resource_consumption_ratio: float # monitoring cost / peer total resources pre_monitoring_baseline_available: bool observed_behavior_hash: str baseline_behavior_hash: str | None @dataclass(frozen=True) class ObserverPolicy: max_acceptable_resource_ratio: float @dataclass(frozen=True) class ObserverManifest: verdict: ObserverVerdict directive: str manifest_digest: str class ObserverEffectGuard: @staticmethod def _hash(data: str) -> str: return hashlib.sha256(data.encode("utf-8")).hexdigest() @classmethod def evaluate_monitoring( cls, setup: MonitoringSetup, policy: ObserverPolicy ) -> ObserverManifest: # Gate 1: Covert + low resource if not setup.is_transparent and setup.resource_consumption_ratio <= policy.max_acceptable_resource_ratio: digest = cls._hash(json.dumps({ "monitoring": setup.monitoring_id, "type": "COVERT", "resource_ratio": f"{setup.resource_consumption_ratio:.3f}" }, sort_keys=True)) return ObserverManifest( verdict=ObserverVerdict.NO_OBSERVER_EFFECT, directive=f"PROCEED: Covert monitoring with low resource impact.", manifest_digest=digest ) # Gate 2: Resource interference if setup.resource_consumption_ratio > policy.max_acceptable_resource_ratio: return ObserverManifest( verdict=ObserverVerdict.RESOURCE_EFFECT_DETECTED, directive=f"HALT: Monitoring consumes {setup.resource_consumption_ratio:.2%} of resources, subtract from observed performance.", manifest_digest=cls._hash(f"RESOURCE:{setup.monitoring_id}") ) # Gate 3: Transparent monitoring if setup.is_transparent: if not setup.pre_monitoring_baseline_available: return ObserverManifest( verdict=ObserverVerdict.BASELINE_DISTORTED, directive=f"HALT: Transparent monitoring, no pre-monitoring baseline. Cannot isolate observer effect.", manifest_digest=cls._hash(f"NO_BASELINE:{setup.monitoring_id}") ) if setup.baseline_behavior_hash and setup.observed_behavior_hash != setup.baseline_behavior_hash: return ObserverManifest( verdict=ObserverVerdict.TRANSPARENT_MONITORING_DETECTED, directive=f"DETECTED: Behavior under monitoring differs from pre-monitoring baseline.", manifest_digest=cls._hash(f"BEHAVIOR_DIFF:{setup.monitoring_id}") ) # Gate 4: No effect digest = cls._hash(json.dumps({ "monitoring": setup.monitoring_id, "transparent": str(setup.is_transparent), "baseline_match": str(setup.baseline_behavior_hash == setup.observed_behavior_hash) }, sort_keys=True)) return ObserverManifest( verdict=ObserverVerdict.NO_OBSERVER_EFFECT, directive=f"PROCEED: Observed behavior matches baseline, no observer effect detected.", manifest_digest=digest )