"""Pure-function tests for the v2 Regime Monitor contract."""

from __future__ import annotations

import copy
import json
from datetime import date, timedelta

import pytest
from sqlalchemy import select

from app.models.regime_snapshot import RegimeSnapshot
from app.routers import market as market_router
from app.services import regime_monitor_service as rms
from app.services.regime_monitor_service import (
    DEFAULT_CONFIG,
    HY_OAS_ELEVATED,
    HY_OAS_MILD,
    HY_OAS_STRESSED,
    _compute_index,
    _fundamental_scores_asof,
    _score_pillars,
    band_for,
    breadth_level_score,
    f2_credit_spreads,
    p1_trend_break,
    p2_death_cross,
    p3_drawdown,
    p4_relative_strength,
    p5_volatility,
)


def _dated(values: list[float], end: date = date(2026, 6, 26)) -> list[tuple[date, float]]:
    return [
        (end - timedelta(days=len(values) - 1 - index), value)
        for index, value in enumerate(values)
    ]


def test_band_for_keeps_documented_boundaries():
    assert band_for(10) == "stable"
    assert band_for(30) == "watch"
    assert band_for(60) == "elevated"
    assert band_for(80) == "breaking"


def test_price_sensors_are_stress_only():
    smh_under = [100.0] * 199 + [50.0]
    qqq_above = [100.0] * 200
    assert round(p1_trend_break(smh_under, qqq_above) or 0, 1) == 66.7

    bearish = [300.0 - index for index in range(260)]
    healthy = [100.0 + index * 0.5 for index in range(260)]
    assert (p2_death_cross(bearish, bearish) or 0) > 0
    assert p2_death_cross(healthy, healthy) == 0

    closes = [100.0] * 252 + [80.0]
    assert p3_drawdown(closes, [100.0] * 253) == 100.0


def test_relative_strength_flat_or_better_is_zero():
    flat = [100.0] * 70
    rising = [100.0 + index for index in range(70)]
    falling = [100.0 - index * 0.5 for index in range(70)]
    assert p4_relative_strength(flat, flat) == 0.0
    assert p4_relative_strength(rising, flat) == 0.0
    assert (p4_relative_strength(falling, flat) or 0) > 0


def test_volatility_and_breadth_zero_points():
    assert p5_volatility(15) == 0
    assert p5_volatility(30) == 100
    assert breadth_level_score(60) == 0
    assert breadth_level_score(20) == 100
    assert breadth_level_score(None) is None


def test_credit_uses_named_anchors_and_constant_series_is_not_extreme():
    assert f2_credit_spreads([HY_OAS_MILD] * 100) == 0
    assert f2_credit_spreads([HY_OAS_ELEVATED] * 100) == 35.0
    assert f2_credit_spreads([HY_OAS_STRESSED] * 100) == 70.0
    rising = [3.0 + index * 0.01 for index in range(100)]
    assert (f2_credit_spreads(rising) or 0) > f2_credit_spreads([3.0] * 100)


def test_score_pillars_gates_band_below_75_percent_coverage():
    pillars = [
        {"id": "price", "label": "Price", "score": 80.0, "sensors": []},
        {"id": "breadth", "label": "Breadth", "score": 20.0, "sensors": []},
        {"id": "credit", "label": "Credit", "score": None, "sensors": []},
        {"id": "volatility", "label": "Vol", "score": None, "sensors": []},
    ]
    result = _score_pillars(pillars, {"price": 40, "breadth": 25, "credit": 20, "volatility": 15})
    assert result["coverage"] == 65.0
    assert result["score"] is not None
    assert result["band"] is None


def test_fundamentals_never_replay_before_effective_date_and_expire():
    overrides = {
        "f1_score": 0.0,
        "f3_score": 100.0,
        "fetched_at": "2026-06-01T10:00:00+00:00",
        "effective_date": "2026-06-02",
    }
    config = {**DEFAULT_CONFIG, "fundamental_staleness_days": 80}
    assert _fundamental_scores_asof(overrides, config, date(2026, 6, 1))[:2] == (None, None)
    assert _fundamental_scores_asof(overrides, config, date(2026, 6, 2))[:2] == (0.0, 100.0)
    assert _fundamental_scores_asof(overrides, config, date(2026, 8, 22))[:2] == (None, None)


@pytest.mark.asyncio
async def test_unlock_does_not_redate_a_fundamental_observation(monkeypatch):
    stored = {
        "f1_score": 100.0,
        "f3_score": 0.0,
        "locked": True,
        "source": "manual",
        "fetched_at": "2026-06-01T10:00:00+00:00",
        "effective_date": "2026-06-02",
    }
    saved: dict = {}

    async def fake_get(_db):
        return dict(stored)

    async def fake_update(_db, _key, value):
        saved.update(json.loads(value))

    monkeypatch.setattr(rms, "get_fundamental_overrides", fake_get)
    monkeypatch.setattr(rms, "update_setting", fake_update)

    result = await rms.set_fundamental_overrides(object(), locked=False)

    assert result["locked"] is False
    assert result["fetched_at"] == stored["fetched_at"]
    assert result["effective_date"] == stored["effective_date"]
    assert saved == result


@pytest.mark.asyncio
async def test_prior_v2_snapshot_is_immutable_without_explicit_rebuild(db_session):
    snapshot_date = date(2026, 6, 26)
    first = {
        "methodology": "v2",
        "date": snapshot_date.isoformat(),
        "state": {"score": 10.0, "band": "stable"},
        "warning": {"score": 20.0, "band": "stable"},
    }
    changed = copy.deepcopy(first)
    changed["state"] = {"score": 90.0, "band": "breaking"}

    written, _ = await rms._upsert_snapshot(
        db_session, first, rewrite_existing_v2=True
    )
    await db_session.flush()
    rewritten, persisted = await rms._upsert_snapshot(
        db_session, changed, rewrite_existing_v2=False
    )
    row = (
        await db_session.execute(
            select(RegimeSnapshot).where(RegimeSnapshot.date == snapshot_date)
        )
    ).scalar_one()

    assert written is True
    assert rewritten is False
    assert persisted["state"]["score"] == 10.0
    assert row.total_score == 10.0


@pytest.mark.asyncio
async def test_routine_can_refresh_latest_trading_session_after_civil_day_rolls(
    monkeypatch,
):
    latest_date = date(2020, 1, 3)
    config = copy.deepcopy(DEFAULT_CONFIG)
    prices = {
        "SMH": [(latest_date, 100.0)],
        "QQQ": [(latest_date, 100.0)],
        "SPY": [(latest_date, 100.0)],
    }
    rewrites: list[bool] = []

    async def fake_config(_db):
        return config

    async def fake_overrides(_db):
        return {"locked": True, "fetched_at": None, "effective_date": None}

    async def fake_prices(_config, _start, _end):
        return prices

    async def fake_fred(_series_id, _start, _end):
        return None

    async def fake_breadth(_db, _symbols, window, min_tickers):
        return {}, {}

    async def fake_latest(_db):
        return object(), {"methodology": "v2"}

    async def fake_upsert(_db, result, *, rewrite_existing_v2):
        rewrites.append(rewrite_existing_v2)
        return True, result

    class FakeDB:
        async def commit(self):
            return None

    monkeypatch.setattr(rms, "get_regime_config", fake_config)
    monkeypatch.setattr(rms, "get_fundamental_overrides", fake_overrides)
    monkeypatch.setattr(rms, "_fetch_prices", fake_prices)
    monkeypatch.setattr(rms, "_fetch_fred_series", fake_fred)
    monkeypatch.setattr(rms.breadth_service, "compute_breadth_details", fake_breadth)
    monkeypatch.setattr(rms, "_latest_v2_row", fake_latest)
    monkeypatch.setattr(rms, "_upsert_snapshot", fake_upsert)

    result = await rms.update_regime_monitor(FakeDB())

    assert result["date"] == latest_date.isoformat()
    assert rewrites == [True]


@pytest.mark.asyncio
async def test_manual_llm_refresh_recomputes_latest_regime_snapshot(monkeypatch):
    calls: list[str] = []
    refreshed = {"f1_score": 0.0, "f3_score": 100.0}

    async def fake_refresh(_db, force):
        assert force is True
        calls.append("refresh")
        return refreshed

    async def fake_recompute(_db):
        calls.append("recompute")
        return {"available": True}

    monkeypatch.setattr(
        market_router.regime_monitor_service,
        "refresh_fundamental_overrides",
        fake_refresh,
    )
    monkeypatch.setattr(
        market_router.regime_monitor_service,
        "update_regime_monitor",
        fake_recompute,
    )

    response = await market_router.refresh_regime_fundamentals(
        _admin=object(), db=object()
    )

    assert calls == ["refresh", "recompute"]
    assert response.data == refreshed


def test_compute_index_uses_one_max_price_vote_and_has_no_combined_score():
    end = date(2026, 6, 26)
    rising = [100.0 + index * 0.2 for index in range(700)]
    qqq = rising.copy()
    smh = rising[:-1] + [rising[-1] * 0.75]
    prices = {
        "SMH": _dated(smh, end),
        "QQQ": _dated(qqq, end),
        "SPY": _dated(rising, end),
    }
    breadth = [(end, 55.0)]
    divergence = [(end, 20.0)]
    result = _compute_index(
        prices,
        [(end, 20.0)],
        [(end - timedelta(days=index), 4.0) for index in reversed(range(100))],
        {"f1_score": None, "f3_score": None},
        copy.deepcopy(DEFAULT_CONFIG),
        end,
        breadth,
        divergence,
        {end: 25},
    )
    price = next(p for p in result["state"]["pillars"] if p["id"] == "price")
    sensor_scores = [sensor["score"] for sensor in price["sensors"] if sensor["score"] is not None]
    assert price["score"] == max(sensor_scores)
    assert result["methodology"] == "v2"
    assert "combined" not in result
    assert result["basket"]["members_available"] == 25