# SPDX-License-Identifier: AGPL-3.0-or-later
"""R0049-R0053 — canary fingerprint cohort.

CanaryFingerprintLifter (E.3.11) parses the fingerprint payload
(navigator/webdriver flag, canvas/audio/WebGL hashes, WebRTC IPs,
TZ/language/geo composite) and emits per Appendix A.9. The v0
:class:`RuleEngine` cannot navigate a structured fingerprint blob —
these rules are inert under the regex matcher.
"""
from __future__ import annotations

from collections.abc import Callable
from pathlib import Path

import pytest

from decnet.ttp.impl.rule_engine import RuleEngine
from decnet.ttp.store.base import RuleState
from decnet.ttp.store.impl.filesystem import _parse_and_compile
from tests.ttp.rule_precision.conftest import CorpusRow, make_event

CohortLoader = Callable[[str], list[CorpusRow]]

_RULE_IDS = [f"R{n:04d}" for n in range(49, 54)]


@pytest.mark.parametrize("rule_id", _RULE_IDS)
def test_rule_yaml_present(rule_id: str) -> None:
    path = Path("rules/ttp") / f"{rule_id}.yaml"
    assert path.exists(), f"missing YAML: {path}"
    compiled = _parse_and_compile(path, RuleState())
    assert compiled.rule_id == rule_id


@pytest.mark.parametrize("rule_id", _RULE_IDS)
async def test_lifter_bound_inert_in_v0(
    rule_id: str,
    precision_engine: RuleEngine,
    corpus_loader: CohortLoader,
) -> None:
    fired: set[str] = set()
    for row in corpus_loader("canary"):
        tags = await precision_engine.evaluate(make_event(row))
        fired.update(tag.rule_id for tag in tags)
    assert rule_id not in fired


def _build_lifter() -> "CanaryFingerprintLifter":
    from decnet.ttp.impl.canary_fingerprint_lifter import (
        CanaryFingerprintLifter,
    )
    from tests.ttp._stub_store import StubRuleStore

    rules = [
        _parse_and_compile(Path("rules/ttp") / f"{rid}.yaml", RuleState())
        for rid in _RULE_IDS
    ]
    lifter = CanaryFingerprintLifter(StubRuleStore(compiled=rules))
    for rule in rules:
        lifter._index.install(rule)
    return lifter


@pytest.mark.parametrize("rule_id", _RULE_IDS)
def test_canary_rule_precision(
    rule_id: str,
    corpus_loader: CohortLoader,
) -> None:
    """E.3.11 — drive CanaryFingerprintLifter over the labelled corpus
    and assert per-rule precision (H-band rules → ≥95%, M-band → ≥80%).
    R0052 is M-band (0.7 confidence); the rest are H-band.
    """
    import asyncio

    from tests.ttp.rule_precision.conftest import precision_for

    rows = corpus_loader("canary")
    if not rows:
        pytest.skip("no canary corpus available")
    lifter = _build_lifter()
    fired: dict[str, list[str]] = {}
    for row in rows:
        tags = asyncio.run(lifter.tag(make_event(row)))
        fired[row.label] = [tag.rule_id for tag in tags]
    precision, _tp, _fp = precision_for(rule_id, rows, fired)
    threshold = 0.80 if rule_id == "R0052" else 0.95
    assert precision >= threshold, (
        f"{rule_id} precision {precision:.2f} < {threshold} on canary corpus"
    )