"""预警服务（5 类预警阈值评估 + 去重位图 + 事件发布）.

对齐 02-architecture-design.md §11 预警体系：
  - LOW_MASTERY：掌握度 < 0.4
  - CRITICAL_LOW：掌握度 < 0.2
  - SCORE_DROP：成绩环比下降 ≥ 20%
  - ABSENT_FREQUENT：缺勤 ≥ 3 次/周
  - TREND_DECLINE：连续 3 次成绩下降

去重策略：
  Redis bitmap key = data_ana:warning:{target_id}:{type}:{date}
  TTL = 25h（跨天容忍，避免边界重复触发）

事件发布：
  warning.triggered 复用 edu.insight.mastery.updated topic（总裁裁决 §2.11）
  Outbox 豁免（总裁裁决 §2.10）
"""

from datetime import UTC, datetime
from typing import Any

import structlog

from .config import settings
from .repository import clickhouse_repository, kafka_producer, redis_client

logger = structlog.get_logger(__name__)


# 预警类型常量
class WarningType:
    """预警类型."""

    LOW_MASTERY = "LOW_MASTERY"
    CRITICAL_LOW = "CRITICAL_LOW"
    SCORE_DROP = "SCORE_DROP"
    ABSENT_FREQUENT = "ABSENT_FREQUENT"
    TREND_DECLINE = "TREND_DECLINE"


class Severity:
    """预警严重程度."""

    INFO = "INFO"
    WARN = "WARN"
    CRITICAL = "CRITICAL"


# 预警类型 → 严重程度映射
_SEVERITY_MAP: dict[str, str] = {
    WarningType.LOW_MASTERY: Severity.WARN,
    WarningType.CRITICAL_LOW: Severity.CRITICAL,
    WarningType.SCORE_DROP: Severity.WARN,
    WarningType.ABSENT_FREQUENT: Severity.WARN,
    WarningType.TREND_DECLINE: Severity.WARN,
}


def _warning_dedup_key(target_id: str, warning_type: str) -> str:
    """预警去重位图 key（25h TTL，避免边界重复触发）."""
    today = datetime.now(UTC).strftime("%Y%m%d")
    return f"data_ana:warning:{target_id}:{warning_type}:{today}"


async def _check_and_dedup(target_id: str, warning_type: str) -> bool:
    """检查去重（首次返回 True，已触发过返回 False）."""
    key = _warning_dedup_key(target_id, warning_type)
    is_first = await redis_client.setnx_dedup(key, ttl_s=25 * 3600)
    if not is_first:
        logger.info(
            "warning_dedup_skipped",
            target_id=target_id,
            warning_type=warning_type,
        )
    return is_first


async def _trigger_warning(
    target_id: str,
    warning_type: str,
    threshold: float,
    current_value: float,
    student_id: str = "",
    knowledge_point_id: str = "",
    metadata: dict[str, str] | None = None,
) -> dict[str, Any]:
    """触发预警（去重 + 事件发布）."""
    severity = _SEVERITY_MAP.get(warning_type, Severity.WARN)

    # 1. 去重检查
    should_trigger = await _check_and_dedup(target_id, warning_type)
    if not should_trigger:
        return {
            "target_id": target_id,
            "warning_type": warning_type,
            "triggered": False,
            "deduplicated": True,
            "threshold": threshold,
            "current_value": current_value,
        }

    # 2. 发布 warning.triggered 事件（Outbox 豁免，复用 mastery topic）
    published = await kafka_producer.publish_warning_triggered(
        target_id=target_id,
        warning_type=warning_type,
        threshold=threshold,
        current_value=current_value,
        severity=severity,
        student_id=student_id,
        knowledge_point_id=knowledge_point_id,
        metadata=metadata,
    )

    logger.warning(
        "warning_triggered",
        target_id=target_id,
        warning_type=warning_type,
        severity=severity,
        threshold=threshold,
        current_value=current_value,
        published=published,
    )
    return {
        "target_id": target_id,
        "warning_type": warning_type,
        "severity": severity,
        "triggered": True,
        "deduplicated": False,
        "threshold": threshold,
        "current_value": current_value,
        "event_published": published,
    }


async def evaluate_mastery_warning(
    student_id: str,
    knowledge_point_id: str,
    mastery_level: float,
) -> list[dict[str, Any]]:
    """评估掌握度预警（LOW_MASTERY / CRITICAL_LOW）.

    - mastery < 0.2 → CRITICAL_LOW（最严重，先评估）
    - 0.2 ≤ mastery < 0.4 → LOW_MASTERY
    """
    triggered: list[dict[str, Any]] = []

    if mastery_level < settings.warning_critical_mastery_threshold:
        result = await _trigger_warning(
            target_id=student_id,
            warning_type=WarningType.CRITICAL_LOW,
            threshold=settings.warning_critical_mastery_threshold,
            current_value=mastery_level,
            student_id=student_id,
            knowledge_point_id=knowledge_point_id,
        )
        if result["triggered"]:
            triggered.append(result)
        return triggered  # CRITICAL_LOW 已触发，不再触发 LOW_MASTERY

    if mastery_level < settings.warning_low_mastery_threshold:
        result = await _trigger_warning(
            target_id=student_id,
            warning_type=WarningType.LOW_MASTERY,
            threshold=settings.warning_low_mastery_threshold,
            current_value=mastery_level,
            student_id=student_id,
            knowledge_point_id=knowledge_point_id,
        )
        if result["triggered"]:
            triggered.append(result)

    return triggered


async def evaluate_score_drop(
    student_id: str,
    current_score: float,
    previous_score: float,
    exam_id: str = "",
) -> dict[str, Any] | None:
    """评估成绩下降预警（SCORE_DROP）.

    成绩环比下降 ≥ warning_score_drop_percent（默认 20%）触发.
    """
    if previous_score <= 0:
        return None

    drop_ratio = (previous_score - current_score) / previous_score
    if drop_ratio < settings.warning_score_drop_percent:
        return None

    return await _trigger_warning(
        target_id=student_id,
        warning_type=WarningType.SCORE_DROP,
        threshold=settings.warning_score_drop_percent,
        current_value=round(drop_ratio, 4),
        student_id=student_id,
        metadata={
            "exam_id": exam_id,
            "previous_score": str(previous_score),
            "current_score": str(current_score),
        },
    )


async def evaluate_absent_frequent(
    student_id: str,
    absent_count_week: int,
) -> dict[str, Any] | None:
    """评估缺勤频繁预警（ABSENT_FREQUENT）.

    一周内缺勤 ≥ warning_absent_per_week（默认 3 次）触发.
    """
    if absent_count_week < settings.warning_absent_per_week:
        return None

    return await _trigger_warning(
        target_id=student_id,
        warning_type=WarningType.ABSENT_FREQUENT,
        threshold=float(settings.warning_absent_per_week),
        current_value=float(absent_count_week),
        student_id=student_id,
    )


async def evaluate_trend_decline(
    student_id: str,
    recent_scores: list[float],
) -> dict[str, Any] | None:
    """评估趋势下降预警（TREND_DECLINE）.

    连续 3 次成绩下降触发（recent_scores 按时间正序，最早在前）.
    """
    if len(recent_scores) < 3:
        return None

    # 检查最近 3 次是否连续下降
    last_three = recent_scores[-3:]
    is_declining = all(last_three[i] > last_three[i + 1] for i in range(len(last_three) - 1))
    if not is_declining:
        return None

    drop = last_three[-2] - last_three[-1]
    return await _trigger_warning(
        target_id=student_id,
        warning_type=WarningType.TREND_DECLINE,
        threshold=0.0,  # 下降幅度阈值（0 表示只要下降就触发）
        current_value=round(drop, 4),
        student_id=student_id,
    )


async def evaluate_all_warnings(
    student_id: str,
    knowledge_point_id: str = "",
    mastery_level: float | None = None,
) -> list[dict[str, Any]]:
    """综合评估学生所有预警类型（GetWarnings RPC 调用）.

    参数：
      - student_id：学生 ID
      - knowledge_point_id：知识点 ID（可选，指定则只评估该知识点）
      - mastery_level：预计算的掌握度（可选，未提供则查询）

    返回：触发的预警列表
    """
    triggered: list[dict[str, Any]] = []

    # 1. 掌握度预警
    if mastery_level is None:
        snapshot = await clickhouse_repository.query_mastery_snapshot(
            student_id=student_id,
        )
        if snapshot is not None:
            knowledge_points = snapshot.get("knowledgePoints", [])
            if knowledge_point_id:
                # 仅评估指定知识点
                knowledge_points = [
                    kp
                    for kp in knowledge_points
                    if kp.get("knowledge_point_id") == knowledge_point_id
                ]
            for kp in knowledge_points:
                level = kp.get("mastery_level", 0.0)
                warnings = await evaluate_mastery_warning(
                    student_id=student_id,
                    knowledge_point_id=kp.get("knowledge_point_id", ""),
                    mastery_level=level,
                )
                triggered.extend(warnings)
    else:
        warnings = await evaluate_mastery_warning(
            student_id=student_id,
            knowledge_point_id=knowledge_point_id,
            mastery_level=mastery_level,
        )
        triggered.extend(warnings)

    # 2. 缺勤预警
    attendance = await clickhouse_repository.query_attendance(student_id=student_id)
    if attendance is not None:
        # 简化：统计总缺勤数（P6 改为按周统计）
        absent_count = attendance.get("absentCount", 0)
        if absent_count >= settings.warning_absent_per_week:
            warning = await evaluate_absent_frequent(
                student_id=student_id,
                absent_count_week=absent_count,
            )
            if warning is not None and warning.get("triggered"):
                triggered.append(warning)

    # 3. 成绩下降预警（需要查询最近两次成绩）
    trend = await clickhouse_repository.query_learning_trend(student_id=student_id)
    if trend is not None:
        points = trend.get("points", [])
        if len(points) >= 2:
            current = points[-1].get("score", 0.0)
            previous = points[-2].get("score", 0.0)
            drop_warning = await evaluate_score_drop(
                student_id=student_id,
                current_score=current,
                previous_score=previous,
            )
            if drop_warning is not None and drop_warning.get("triggered"):
                triggered.append(drop_warning)

        # 4. 趋势下降预警
        scores = [p.get("score", 0.0) for p in points]
        trend_warning = await evaluate_trend_decline(
            student_id=student_id,
            recent_scores=scores,
        )
        if trend_warning is not None and trend_warning.get("triggered"):
            triggered.append(trend_warning)

    return triggered


async def get_warnings(
    student_id: str,
    warning_type: str = "",
) -> list[dict[str, Any]]:
    """查询预警列表（GetWarnings RPC 实现）.

    参数：
      - student_id：学生 ID
      - warning_type：预警类型过滤（空表示全部）

    返回：预警列表（每条含 target_id / warning_type / severity / threshold /
    current_value / triggered_at）
    """
    # 当前实现：实时评估返回触发结果
    # P6 演进：将预警历史持久化到 ClickHouse 供查询
    triggered = await evaluate_all_warnings(student_id=student_id)
    if warning_type:
        triggered = [w for w in triggered if w.get("warning_type") == warning_type]
    return triggered


async def trigger_warning_manual(
    target_id: str,
    warning_type: str,
    threshold: float,
    current_value: float,
    student_id: str = "",
    knowledge_point_id: str = "",
    severity: str = "",
    metadata: dict[str, str] | None = None,
) -> dict[str, Any]:
    """手动触发预警（TriggerWarning RPC 实现，管理员/API 用）."""
    # 覆盖默认 severity
    if severity:
        _SEVERITY_MAP[warning_type] = severity

    return await _trigger_warning(
        target_id=target_id,
        warning_type=warning_type,
        threshold=threshold,
        current_value=current_value,
        student_id=student_id,
        knowledge_point_id=knowledge_point_id,
        metadata=metadata,
    )