from datetime import date, datetime
from decimal import Decimal

import pytest

from app.core.contracts import RequestContext
from app.model.fund import (
    FundCapitalFlow,
    FundCustomerProfile,
    FundProduct,
    FundRiskAlert,
    FundTransaction,
)
from app.model.risk import RiskLoginRecord, RiskUser, RiskWorkOrder
from app.service.risk_scan_service import (
    RiskRuleEngine,
    RiskScanService,
    _new_alert_id,
)


class ScalarRows:
    def __init__(self, rows):
        self.rows = rows

    def all(self):
        return list(self.rows)


class FakeSession:
    def __init__(self, *, scalar_values=None, rows=None, get_values=None):
        self.scalar_values = list(scalar_values or [])
        self.rows = list(rows or [])
        self.get_values = list(get_values or [])
        self.statements = []
        self.committed = False
        self.rolled_back = False

    async def scalar(self, statement):
        self.statements.append(statement)
        return self.scalar_values.pop(0) if self.scalar_values else None

    async def scalars(self, statement):
        self.statements.append(statement)
        return ScalarRows(self.rows)

    async def get(self, _model, _identifier):
        return self.get_values.pop(0) if self.get_values else None

    def add(self, _value):
        return None

    async def flush(self):
        return None

    async def commit(self):
        self.committed = True

    async def rollback(self):
        self.rolled_back = True

    def begin_nested(self):
        return _NestedTransaction()


class _NestedTransaction:
    async def __aenter__(self):
        return self

    async def __aexit__(self, _exc_type, _exc, _traceback):
        return False


def transaction() -> FundTransaction:
    return FundTransaction(
        id=100,
        transaction_no="TX-100",
        order_id=200,
        work_order_id=300,
        customer_id=1,
        account_id=2,
        product_id=3,
        order_side="sell",
        transaction_type="赎回",
        executed_price=Decimal("1.000000"),
        nav=Decimal("1.000000"),
        executed_quantity=Decimal("750000.0000"),
        shares=Decimal("750000.0000"),
        gross_amount=Decimal("750000.00"),
        amount=Decimal("750000.00"),
        fee_rate_snapshot=Decimal("0.000000"),
        fee_amount=Decimal("0.00"),
        net_amount=Decimal("750000.00"),
        quote_at=datetime(2026, 9, 10, 8, 0),
        quote_source="test",
        executed_at=datetime(2026, 9, 10, 8, 0),
        confirmed_at=datetime(2026, 9, 10, 8, 0),
        auto_confirmed=0,
        created_at=datetime(2026, 9, 10, 8, 0),
    )


def capital_flow() -> FundCapitalFlow:
    return FundCapitalFlow(
        id=400,
        flow_no="FLOW-400",
        customer_id=1,
        flow_type="入金",
        amount=Decimal("800000.00"),
        status="成功",
        settled_at=datetime(2026, 9, 8, 8, 0),
        occurred_at=datetime(2026, 9, 8, 8, 0),
        source_type="银行转入",
        match_status="已匹配",
        created_at=datetime(2026, 9, 8, 8, 0),
        updated_at=datetime(2026, 9, 8, 8, 0),
    )


def risk_user(investor_type: str = "C2") -> RiskUser:
    return RiskUser(
        id=1,
        user_no="CUST-001",
        username="customer001",
        user_type="CUSTOMER",
        investor_type=investor_type,
        is_professional_investor=0,
        professional_investor_status="未申请",
        fund_account_status="已开户",
        status="正常",
        created_at=datetime(2026, 1, 1),
        updated_at=datetime(2026, 9, 10),
    )


def product(
    risk_level: str = "R5",
    *,
    disclosure: int = 1,
    confirmation: int = 1,
    recording: int = 1,
) -> FundProduct:
    return FundProduct(
        id=3,
        product_code="P-001",
        product_name="测试产品",
        exchange_code="159999",
        product_category="股票型",
        risk_level=risk_level,
        currency="CNY",
        lot_size=Decimal("100.0000"),
        price_tick=Decimal("0.000100"),
        min_amount=Decimal("100.00"),
        single_investor_max_holding_ratio=Decimal("100.0000"),
        risk_disclosure_required=disclosure,
        second_confirmation_required=confirmation,
        recording_required=recording,
        status="在售",
        created_at=datetime(2026, 1, 1),
        updated_at=datetime(2026, 9, 10),
    )


def work_order(
    *,
    disclosure_at: datetime | None = None,
    confirmation_at: datetime | None = None,
    recording_reference: str | None = None,
    channel: str | None = "手机应用",
) -> RiskWorkOrder:
    return RiskWorkOrder(
        id=300,
        work_order_no="WO-300",
        customer_id=1,
        product_id=3,
        channel=channel,
        risk_disclosure_ack_at=disclosure_at,
        second_confirmation_at=confirmation_at,
        recording_reference=recording_reference,
        status="已提交",
        created_at=datetime(2026, 9, 1),
        updated_at=datetime(2026, 9, 10),
    )


def customer_profile(birth_date: date = date(1954, 1, 1)) -> FundCustomerProfile:
    return FundCustomerProfile(
        customer_id=1,
        trade_account="ACC-001",
        real_name="张三",
        birth_date=birth_date,
        investor_type="C2",
        total_asset=Decimal("1000000.00"),
        behavior_score=20,
        updated_at=datetime(2026, 9, 10),
    )


@pytest.mark.asyncio
async def test_fast_in_fast_out_builds_fact_based_alert() -> None:
    session = FakeSession(
        rows=[transaction()],
        scalar_values=[capital_flow(), None],
    )

    alerts = await RiskRuleEngine(session)._fast_in_fast_out()

    assert len(alerts) == 1
    assert alerts[0].trigger_rule_codes == ["RW-003"]
    assert alerts[0].alert_level == "高"
    assert "800000" in alerts[0].evidence_summary
    assert alerts[0].evidence_snapshot["ratio"] == "0.9375"


@pytest.mark.asyncio
async def test_duplicate_rule_hit_is_suppressed() -> None:
    session = FakeSession(
        rows=[transaction()],
        scalar_values=[capital_flow(), 1],
    )

    alerts = await RiskRuleEngine(session)._fast_in_fast_out()

    assert alerts == []


def test_same_transaction_alerts_are_merged() -> None:
    first = FundRiskAlert(
        id=1,
        alert_no="AL-1",
        customer_id=1,
        related_transaction_id=100,
        alert_type="大额快进快出",
        alert_level="高",
        trigger_rule_codes=["RW-003"],
        evidence_summary="摘要一",
        evidence_snapshot={"product_id": 3},
        priority_score=98,
        event_status="正在发生",
        status="待处理",
        ack_status="未确认",
        is_escalated=0,
        created_at=datetime(2026, 9, 10),
        updated_at=datetime(2026, 9, 10),
    )
    second = FundRiskAlert(
        id=2,
        alert_no="AL-2",
        customer_id=1,
        related_transaction_id=100,
        alert_type="老年客户异常大额赎回",
        alert_level="中",
        trigger_rule_codes=["RW-012"],
        evidence_summary="摘要二",
        evidence_snapshot={"age": 72},
        priority_score=96,
        event_status="正在发生",
        status="待处理",
        ack_status="未确认",
        is_escalated=0,
        created_at=datetime(2026, 9, 10),
        updated_at=datetime(2026, 9, 10),
    )

    merged = RiskRuleEngine._merge_same_transaction_alerts([first, second])

    assert len(merged) == 1
    assert merged[0].trigger_rule_codes == ["RW-003", "RW-012"]
    assert merged[0].alert_level == "高"
    assert merged[0].evidence_summary == "摘要一；摘要二"
    assert len(merged[0].evidence_snapshot["merged_alerts"]) == 2


@pytest.mark.asyncio
async def test_scan_service_uses_transaction_boundary() -> None:
    class FakeRuleEngine:
        async def refresh_alerts(self):
            return [
                FundRiskAlert(
                    id=1,
                    alert_no="AL-1",
                    customer_id=1,
                    alert_type="大额快进快出",
                    alert_level="高",
                    trigger_rule_codes=["RW-003"],
                    evidence_summary="摘要",
                    evidence_snapshot={},
                    priority_score=98,
                    event_status="正在发生",
                    status="待处理",
                    ack_status="未确认",
                    is_escalated=0,
                    created_at=datetime(2026, 9, 10),
                    updated_at=datetime(2026, 9, 10),
                )
            ]

    session = FakeSession()
    context = RequestContext(
        user_id="990000002",
        trace_id="scan-trace",
        permissions=("risk:alert:scan",),
        data_scope="all",
    )

    result = await RiskScanService(
        session,
        rule_engine=FakeRuleEngine(),
        notification_enabled=False,
    ).scan(context)

    assert result == {
        "message": "规则扫描完成",
        "created_count": 1,
        "high_risk_count": 1,
        "notification_count": 0,
    }
    assert session.committed is True
    assert session.rolled_back is False


def test_alert_id_is_nonzero_positive() -> None:
    alert_id = _new_alert_id()

    assert 0 < alert_id < 2**63


@pytest.mark.asyncio
async def test_scan_creates_high_risk_notifications_in_savepoint() -> None:
    class FakeRuleEngine:
        async def refresh_alerts(self):
            return [
                FundRiskAlert(
                    id=1,
                    alert_no="AL-1",
                    customer_id=1,
                    alert_type="大额快进快出",
                    alert_level="高",
                    trigger_rule_codes=["RW-003"],
                    evidence_summary="摘要",
                    evidence_snapshot={},
                    priority_score=98,
                    event_status="正在发生",
                    status="待处理",
                    ack_status="未确认",
                    handler_id=990000002,
                    is_escalated=0,
                    created_at=datetime(2026, 9, 10),
                    updated_at=datetime(2026, 9, 10),
                )
            ]

    class FakeNotificationService:
        def __init__(self):
            self.calls = []

        def create_in_app(self, alert, **kwargs):
            self.calls.append(("in_app", alert.alert_no, kwargs))

        def create_mail_record(self, alert, **kwargs):
            self.calls.append(("mail", alert.alert_no, kwargs))

    notifier = FakeNotificationService()
    context_value = RequestContext(
        user_id="990000002",
        trace_id="scan-trace",
        permissions=("risk:alert:scan",),
        data_scope="all",
    )

    result = await RiskScanService(
        FakeSession(),
        rule_engine=FakeRuleEngine(),
        notification_service=notifier,
        notification_email="risk@example.com",
    ).scan(context_value)

    assert result["notification_count"] == 2
    assert [call[0] for call in notifier.calls] == ["in_app", "mail"]


@pytest.mark.asyncio
async def test_notification_failure_does_not_rollback_scan() -> None:
    class FakeRuleEngine:
        async def refresh_alerts(self):
            return [
                FundRiskAlert(
                    id=1,
                    alert_no="AL-1",
                    customer_id=1,
                    alert_type="大额快进快出",
                    alert_level="高",
                    trigger_rule_codes=["RW-003"],
                    evidence_summary="摘要",
                    evidence_snapshot={},
                    priority_score=98,
                    event_status="正在发生",
                    status="待处理",
                    ack_status="未确认",
                    is_escalated=0,
                    created_at=datetime(2026, 9, 10),
                    updated_at=datetime(2026, 9, 10),
                )
            ]

    class FailingNotificationService:
        def create_in_app(self, *_args, **_kwargs):
            raise RuntimeError("notification failed")

    session = FakeSession()
    context_value = RequestContext(
        user_id="990000002",
        trace_id="scan-trace",
        permissions=("risk:alert:scan",),
        data_scope="all",
    )

    result = await RiskScanService(
        session,
        rule_engine=FakeRuleEngine(),
        notification_service=FailingNotificationService(),
    ).scan(context_value)

    assert result["created_count"] == 1
    assert result["notification_count"] == 0
    assert session.committed is True
    assert session.rolled_back is False


@pytest.mark.asyncio
async def test_suitability_mismatch_high_and_medium_boundaries() -> None:
    session = FakeSession(
        rows=[transaction()],
        get_values=[risk_user("C2"), product("R5"), work_order()],
        scalar_values=[None],
    )
    alerts = await RiskRuleEngine(session)._suitability_mismatch()
    assert len(alerts) == 1
    assert alerts[0].alert_level == "高"

    session = FakeSession(
        rows=[transaction()],
        get_values=[risk_user("C4"), product("R5"), work_order()],
        scalar_values=[None],
    )
    alerts = await RiskRuleEngine(session)._suitability_mismatch()
    assert len(alerts) == 1
    assert alerts[0].alert_level == "中"


@pytest.mark.asyncio
async def test_suitability_mismatch_rejects_complete_trace_and_matching_level() -> None:
    session = FakeSession(
        rows=[transaction()],
        get_values=[
            risk_user("C2"),
            product("R5"),
            work_order(
                disclosure_at=datetime(2026, 9, 1),
                confirmation_at=datetime(2026, 9, 1),
                recording_reference="REC-1",
            ),
        ],
        scalar_values=[None],
    )
    assert await RiskRuleEngine(session)._suitability_mismatch() == []

    session = FakeSession(
        rows=[transaction()],
        get_values=[risk_user("C5"), product("R5"), work_order()],
        scalar_values=[None],
    )
    assert await RiskRuleEngine(session)._suitability_mismatch() == []


def _complete_trace() -> RiskWorkOrder:
    return work_order(
        disclosure_at=datetime(2026, 9, 1),
        confirmation_at=datetime(2026, 9, 1),
        recording_reference="REC-1",
    )


@pytest.mark.asyncio
async def test_suitability_exemption_limit_breach_raises_alert() -> None:
    """C3→R4 属第十五条允许的越级购买，但单只持仓超过总资产 20% 仍要预警。

    原先扫描侧只看"留痕是否齐全"：签了揭示书、留痕齐全就直接不报 —— 于是"签了字
    但买超额度"这种明确违规反而没有预警。
    """
    session = FakeSession(
        rows=[transaction()],
        get_values=[risk_user("C3"), product("R4"), _complete_trace()],
        scalar_values=[None, Decimal("100000.00"), Decimal("30000.00")],
    )

    alerts = await RiskRuleEngine(session)._suitability_mismatch()

    assert len(alerts) == 1
    assert alerts[0].alert_level == "中"
    assert "20%" in alerts[0].evidence_summary
    assert alerts[0].evidence_snapshot["exemption_ratio"] == "0.3"
    assert alerts[0].evidence_snapshot["exemption_limit"] == "0.20"


@pytest.mark.asyncio
async def test_suitability_exemption_within_limit_is_not_an_alert() -> None:
    """留痕齐全且占比未超额度 → 豁免成立，不该产生预警。"""
    session = FakeSession(
        rows=[transaction()],
        get_values=[risk_user("C3"), product("R4"), _complete_trace()],
        scalar_values=[None, Decimal("100000.00"), Decimal("10000.00")],
    )

    assert await RiskRuleEngine(session)._suitability_mismatch() == []


@pytest.mark.asyncio
async def test_suitability_exemption_missing_asset_data_does_not_create_alerts() -> None:
    """总资产为 0（上游未落地）时不能算成"超限"。

    本项目的画像与持仓由本项目之外的流程写入，拿 0 去算会让每一笔 C3→R4 都变成
    违规 —— 豁免规则就成了新的误报源。缺失只如实记录，交给研判侧提示人工确认。
    """
    session = FakeSession(
        rows=[transaction()],
        get_values=[risk_user("C3"), product("R4"), _complete_trace()],
        scalar_values=[None, Decimal("0"), Decimal("10000.00")],
    )

    assert await RiskRuleEngine(session)._suitability_mismatch() == []


@pytest.mark.asyncio
async def test_suitability_missing_trace_still_alerts_without_exemption_data() -> None:
    """留痕不完整这条老语义不能被新增的额度逻辑冲掉。"""
    session = FakeSession(
        rows=[transaction()],
        get_values=[risk_user("C3"), product("R4"), work_order()],
        scalar_values=[None, Decimal("0"), None],
    )

    alerts = await RiskRuleEngine(session)._suitability_mismatch()

    assert len(alerts) == 1
    assert "交易留痕不完整" in alerts[0].evidence_summary
    assert alerts[0].evidence_snapshot["exemption_data_missing"] is True


@pytest.mark.asyncio
async def test_elderly_redemption_requires_age_amount_average_and_uncommon_device() -> None:
    login = RiskLoginRecord(
        id=500,
        user_id=1,
        login_at=datetime(2026, 9, 9),
        login_result="成功",
        device_id="DEVICE-NEW",
        is_common_device=0,
        created_at=datetime(2026, 9, 9),
    )
    session = FakeSession(
        rows=[transaction()],
        get_values=[customer_profile()],
        scalar_values=[Decimal("100000.00"), login, None],
    )
    alerts = await RiskRuleEngine(session)._elderly_redemption()
    assert len(alerts) == 1
    assert alerts[0].trigger_rule_codes == ["RW-012"]

    session = FakeSession(
        rows=[transaction()],
        get_values=[customer_profile()],
        scalar_values=[Decimal("250000.00"), login, None],
    )
    boundary_alerts = await RiskRuleEngine(session)._elderly_redemption()
    assert len(boundary_alerts) == 1

    session = FakeSession(
        rows=[transaction()],
        get_values=[customer_profile()],
        scalar_values=[Decimal("260000.00")],
    )
    assert await RiskRuleEngine(session)._elderly_redemption() == []


@pytest.mark.asyncio
async def test_elderly_redemption_rejects_common_device() -> None:
    login = RiskLoginRecord(
        id=500,
        user_id=1,
        login_at=datetime(2026, 9, 9),
        login_result="成功",
        device_id="DEVICE-COMMON",
        is_common_device=1,
        created_at=datetime(2026, 9, 9),
    )
    session = FakeSession(
        rows=[transaction()],
        get_values=[customer_profile()],
        scalar_values=[Decimal("100000.00"), login],
    )
    assert await RiskRuleEngine(session)._elderly_redemption() == []


@pytest.mark.asyncio
async def test_night_small_trade_boundaries() -> None:
    # confirmed_at 在库里是 **UTC**（见 app/infrastructure/db.py:15-21），而"凌晨"是
    # **北京时间**概念：北京 00:00–06:00 对应 UTC 的前一日 16:00–22:00。
    # 原先这里直接拿 UTC 小时当北京时间（写 0 点 / 6 点），等于在测"北京 08:00 / 14:00"，
    # 规则修正后这些用例的语义也一并修正（docs/25 P1 #6）。
    night = transaction()
    night.confirmed_at = datetime(2026, 9, 9, 16, 0)  # 北京 09-10 00:00，凌晨起点（含）
    night.amount = Decimal("10000.00")
    session = FakeSession(rows=[night], scalar_values=[None])
    alerts = await RiskRuleEngine(session)._low_risk_night_trade()
    assert len(alerts) == 1

    regular = transaction()
    regular.confirmed_at = datetime(2026, 9, 9, 22, 0)  # 北京 09-10 06:00，凌晨终点（不含）
    session = FakeSession(rows=[regular], scalar_values=[None])
    assert await RiskRuleEngine(session)._low_risk_night_trade() == []

    too_large = transaction()
    too_large.confirmed_at = datetime(2026, 9, 9, 18, 0)  # 北京 09-10 02:00，在凌晨但金额超限
    too_large.amount = Decimal("10000.01")
    session = FakeSession(rows=[too_large], scalar_values=[None])
    assert await RiskRuleEngine(session)._low_risk_night_trade() == []


@pytest.mark.asyncio
async def test_auto_investment_false_positive_uses_valid_work_order() -> None:
    tx = transaction()
    tx.work_order_id = 300
    session = FakeSession(
        rows=[tx],
        get_values=[work_order(channel="自动定投")],
        scalar_values=[None],
    )
    alerts = await RiskRuleEngine(session)._auto_investment_false_positive()
    assert len(alerts) == 1
    assert alerts[0].trigger_rule_codes == ["RW-018"]

    session = FakeSession(
        rows=[tx],
        get_values=[work_order(channel="定投")],
        scalar_values=[None],
    )
    assert len(await RiskRuleEngine(session)._auto_investment_false_positive()) == 1

    session = FakeSession(
        rows=[tx],
        get_values=[work_order(channel="手机应用")],
        scalar_values=[None],
    )
    assert await RiskRuleEngine(session)._auto_investment_false_positive() == []