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Off every active line (PATHFINDER-2026-10-13/03-unified-proposal.md, cuts). Deleted: src/openultrasast/regress/ and the deep-mode REGRESS branch (deep now records a regress_retired degradation and equals standard; proof is the search-with-proof arm's job), the sandbox docker runner and probe that only regress used, --fail-on worth-fixing, RegressConfig, the two ledger helpers only regress called; skills.py and index.py with the hunter pool's skill routing; model/audit.py; cpg/queries/vocabulary.sc with benchmarks/push/ontology_gap.py. Docs and the scan skill describe the retirement. Net: 3,895 lines deleted, 86 added. Targeted tests: 180 passed, 28 skipped; 3,331 tests collect. Co-Authored-By: Claude Fable 5.1 <[email protected]>
129 lines
3.9 KiB
Python
129 lines
3.9 KiB
Python
"""Loop-owned complexity ledger: overlay hotspot scores without hiding sev-5 inventory."""
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from __future__ import annotations
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import json
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from collections.abc import Mapping, Sequence
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from dataclasses import asdict, dataclass, replace
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from pathlib import Path
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from typing import TYPE_CHECKING
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if TYPE_CHECKING:
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from .map import Hotspot
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TRIGGERABLE_DELTA = 1.5
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NOT_TRIGGERABLE_DELTA = -1.5
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VERDICT_DELTAS = {
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"triggerable": TRIGGERABLE_DELTA,
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"not_triggerable": NOT_TRIGGERABLE_DELTA,
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}
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@dataclass(frozen=True)
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class LedgerEntry:
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score_delta: float
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last_verdict: str
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round: int = 0
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def hotspot_key(path: str, function_name: str | None) -> str:
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return f"{path}:{function_name or ''}"
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def load_ledger(path: Path | None) -> dict[str, LedgerEntry]:
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if path is None or not path.exists():
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return {}
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payload = json.loads(path.read_text())
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entries: dict[str, LedgerEntry] = {}
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for key, value in payload.items():
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entry = _coerce_entry(value)
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if entry is not None:
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entries[str(key)] = entry
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return entries
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def write_ledger(path: Path, ledger: Mapping[str, LedgerEntry | Mapping[str, object]]) -> None:
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payload: dict[str, dict[str, object]] = {}
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for key, value in ledger.items():
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entry = _coerce_entry(value)
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if entry is None:
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continue
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payload[str(key)] = asdict(entry)
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path.parent.mkdir(parents=True, exist_ok=True)
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path.write_text(json.dumps(payload, indent=2, sort_keys=True) + "\n")
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def record_verdict(
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ledger: Mapping[str, LedgerEntry | Mapping[str, object]],
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*,
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path: str,
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function_name: str | None,
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verdict: str,
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) -> dict[str, LedgerEntry]:
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updated: dict[str, LedgerEntry] = {}
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for key, value in ledger.items():
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entry = _coerce_entry(value)
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if entry is not None:
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updated[str(key)] = entry
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key = hotspot_key(path, function_name)
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previous = updated.get(key)
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updated[key] = LedgerEntry(
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score_delta=round((previous.score_delta if previous else 0.0) + VERDICT_DELTAS.get(verdict, 0.0), 4),
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last_verdict=verdict,
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round=(previous.round if previous else 0) + 1,
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)
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return updated
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def apply_overlay(
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hotspots: Sequence[Hotspot],
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ledger: Mapping[str, LedgerEntry | Mapping[str, object]],
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) -> tuple[Hotspot, ...]:
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if not ledger:
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return tuple(hotspots)
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adjusted: list[Hotspot] = []
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for hotspot in hotspots:
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entry = _coerce_entry(ledger.get(hotspot_key(hotspot.path, hotspot.function_name)))
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if entry is None or entry.score_delta == 0.0:
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adjusted.append(hotspot)
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continue
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score = round(hotspot.score + entry.score_delta, 4)
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signals = dict(hotspot.signals)
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signals["ledger_delta"] = entry.score_delta
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adjusted.append(
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replace(
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hotspot,
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score=score,
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band=_band_for(score),
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signals=signals,
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rationale=(
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f"{hotspot.rationale} ledger overlay last_verdict={entry.last_verdict} "
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f"score_delta={entry.score_delta} (inventory retained)."
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),
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)
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)
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return tuple(sorted(adjusted, key=lambda item: (-item.score, item.path, item.function_name or "")))
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def _coerce_entry(value: object) -> LedgerEntry | None:
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if isinstance(value, LedgerEntry):
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return value
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if not isinstance(value, Mapping):
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return None
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raw_delta = value.get("score_delta")
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if isinstance(raw_delta, bool) or not isinstance(raw_delta, int | float):
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return None
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raw_round = value.get("round", 0)
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round_n = raw_round if isinstance(raw_round, int) and not isinstance(raw_round, bool) else 0
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return LedgerEntry(
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score_delta=float(raw_delta),
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last_verdict=str(value.get("last_verdict", "")),
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round=round_n,
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)
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def _band_for(score: float) -> str:
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from .map import _band
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return _band(score)
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