auto-stock/backend/app/services/mdd_manager.py

"""
MDD(Maximum Drawdown) 관리 - CLAUDE.md 섹션 6.3

- 포트폴리오 최고점 대비 하락률 추적
- -10% 돌파 시: 신규 진입 중단 + 기존 포지션 30% 축소
- -20% 돌파 시: 전체 포지션 50% 강제 축소 (레버리지/인버스 우선)
"""
import asyncio
import json
import logging
from typing import Dict, Optional

from app.core.json_helpers import _dumps

logger = logging.getLogger(__name__)

_MDD_REDIS_KEY = "mdd:state"


class MDDManager:
    """포트폴리오 MDD 관리자 (싱글톤으로 사용)"""

    def __init__(self):
        self.peak_balance: float = 0.0
        self.is_paused: bool = False
        self.is_short_term_strategy_paused: bool = False  # MDD -10% 시 단기 전략 중단
        self.reduction_applied: Optional[str] = None  # None, "10pct", "20pct"
        self._reduction_executed_10pct: bool = False  # 중복 축소 실행 방지
        self._reduction_executed_20pct: bool = False
        self._lock = asyncio.Lock()  # 스케줄러-sync 동시 접근 방지

    async def save_to_redis(self) -> None:
        """MDD 상태를 Redis에 영속화 — 앱 재시작 시 복원용."""
        try:
            from app.core.redis import get_redis
            r = get_redis()
            if r:
                state = {
                    "peak_balance": self.peak_balance,
                    "is_paused": self.is_paused,
                    "is_short_term_strategy_paused": self.is_short_term_strategy_paused,
                    "reduction_applied": self.reduction_applied,
                    "_reduction_executed_10pct": self._reduction_executed_10pct,
                    "_reduction_executed_20pct": self._reduction_executed_20pct,
                }
                await r.set(_MDD_REDIS_KEY, _dumps(state))
        except Exception as e:
            logger.warning(f"[MDD] Redis 저장 실패: {e}")

    async def load_from_redis(self) -> bool:
        """Redis에서 MDD 상태 복원. 복원 성공 시 True 반환."""
        try:
            from app.core.redis import get_redis
            r = get_redis()
            if r:
                raw = await r.get(_MDD_REDIS_KEY)
                if raw:
                    state = json.loads(raw)
                    self.peak_balance = float(state.get("peak_balance", 0.0))
                    self.is_paused = bool(state.get("is_paused", False))
                    self.is_short_term_strategy_paused = bool(state.get("is_short_term_strategy_paused", False))
                    self.reduction_applied = state.get("reduction_applied")
                    self._reduction_executed_10pct = bool(state.get("_reduction_executed_10pct", False))
                    self._reduction_executed_20pct = bool(state.get("_reduction_executed_20pct", False))
                    logger.info(
                        f"[MDD] Redis에서 복원: peak={self.peak_balance:,.0f}, "
                        f"paused={self.is_paused}, reduction={self.reduction_applied}"
                    )
                    return True
        except Exception as e:
            logger.warning(f"[MDD] Redis 복원 실패: {e}")
        return False

    async def update(self, current_balance: float) -> Dict:
        """MDD 업데이트 및 필요한 조치 반환 (thread-safe)

        Returns:
            {"action": "NONE"/"REDUCE_AND_PAUSE"/"FORCE_REDUCE",
             "drawdown": float, ...}
        """
        async with self._lock:
            if current_balance > self.peak_balance:
                self.peak_balance = current_balance
                self.is_paused = False
                self.is_short_term_strategy_paused = False
                self.reduction_applied = None
                self._reduction_executed_10pct = False
                self._reduction_executed_20pct = False

            if self.peak_balance <= 0:
                return {"action": "NONE", "drawdown": 0.0}

            drawdown_pct = ((current_balance - self.peak_balance) / self.peak_balance) * 100

            # -20% 돌파: 50% 강제 축소
            if drawdown_pct <= -20 and self.reduction_applied != "20pct":
                self.is_paused = True
                self.is_short_term_strategy_paused = True  # 단번에 -20% 도달 시에도 단기전략 차단
                self.reduction_applied = "20pct"
                logger.warning(f"MDD {drawdown_pct:.1f}% - 50% 강제 축소 + 신규진입 중단")
                await self.save_to_redis()
                # Telegram MDD 경고
                try:
                    from app.services.telegram_notifier import telegram_notifier
                    asyncio.ensure_future(telegram_notifier.notify_mdd_warning(
                        action="FORCE_REDUCE", drawdown=drawdown_pct, reduce_pct=0.50,
                    ))
                except Exception:
                    pass
                return {
                    "action": "FORCE_REDUCE",
                    "drawdown": drawdown_pct,
                    "reduce_pct": 0.50,
                    "prioritize_leverage": True,
                }

            # -10% 돌파: 30% 축소 + 신규진입 중단 + 단기전략 중단
            if drawdown_pct <= -10 and self.reduction_applied is None:
                self.is_paused = True
                self.is_short_term_strategy_paused = True  # CLAUDE.md 5.3: 단기 매매 전략 중단
                self.reduction_applied = "10pct"
                logger.warning(f"MDD {drawdown_pct:.1f}% - 30% 축소 + 신규진입 중단 + 단기전략 중단")
                await self.save_to_redis()
                # Telegram MDD 경고
                try:
                    from app.services.telegram_notifier import telegram_notifier
                    asyncio.ensure_future(telegram_notifier.notify_mdd_warning(
                        action="REDUCE_AND_PAUSE", drawdown=drawdown_pct, reduce_pct=0.30,
                    ))
                except Exception:
                    pass
                return {
                    "action": "REDUCE_AND_PAUSE",
                    "drawdown": drawdown_pct,
                    "reduce_pct": 0.30,
                    "short_term_strategy_paused": True,
                }

            # Redis 영속화 (상태 변경 시)
            await self.save_to_redis()
            return {"action": "NONE", "drawdown": drawdown_pct}

    async def save_to_redis_v2(self, user_id: int) -> None:
        """[v2] 사용자 스코프 MDD 상태를 `mdd:state:{user_id}` 키로 영속화.

        save_to_redis()와 동일 직렬화 포맷 재사용, 키 네임스페이스만 사용자별로 분리.
        레거시 save_to_redis()는 불변(전역 "mdd:state" 키 그대로).
        """
        try:
            from app.core.redis import get_redis
            r = get_redis()
            if r:
                state = {
                    "peak_balance": self.peak_balance,
                    "is_paused": self.is_paused,
                    "is_short_term_strategy_paused": self.is_short_term_strategy_paused,
                    "reduction_applied": self.reduction_applied,
                    "_reduction_executed_10pct": self._reduction_executed_10pct,
                    "_reduction_executed_20pct": self._reduction_executed_20pct,
                }
                await r.set(f"{_MDD_REDIS_KEY}:{user_id}", _dumps(state))
        except Exception as e:
            logger.warning(f"[MDD v2] Redis 저장 실패 (user={user_id}): {e}")

    async def load_from_redis_v2(self, user_id: int) -> bool:
        """[v2] `mdd:state:{user_id}` 키에서 사용자 스코프 MDD 상태 복원."""
        try:
            from app.core.redis import get_redis
            r = get_redis()
            if r:
                raw = await r.get(f"{_MDD_REDIS_KEY}:{user_id}")
                if raw:
                    state = json.loads(raw)
                    self.peak_balance = float(state.get("peak_balance", 0.0))
                    self.is_paused = bool(state.get("is_paused", False))
                    self.is_short_term_strategy_paused = bool(state.get("is_short_term_strategy_paused", False))
                    self.reduction_applied = state.get("reduction_applied")
                    self._reduction_executed_10pct = bool(state.get("_reduction_executed_10pct", False))
                    self._reduction_executed_20pct = bool(state.get("_reduction_executed_20pct", False))
                    logger.info(
                        f"[MDD v2] Redis에서 복원: user={user_id} peak={self.peak_balance:,.0f}, "
                        f"paused={self.is_paused}, reduction={self.reduction_applied}"
                    )
                    return True
        except Exception as e:
            logger.warning(f"[MDD v2] Redis 복원 실패 (user={user_id}): {e}")
        return False

    async def can_open_new_position(self) -> bool:
        """신규 포지션 진입 가능 여부 (thread-safe)"""
        async with self._lock:
            return not self.is_paused

    async def is_short_term_strategy_enabled(self) -> bool:
        """단기 전략 활성화 여부 (thread-safe) — MDD -10% 이상일 때만 활성화"""
        async with self._lock:
            return not self.is_short_term_strategy_paused

    async def reset(self):
        """MDD 상태 리셋 (수동 복구 시) — async + Lock으로 동시성 안전 보장"""
        async with self._lock:
            self.is_paused = False
            self.is_short_term_strategy_paused = False
            self.reduction_applied = None
            self._reduction_executed_10pct = False
            self._reduction_executed_20pct = False
            logger.info("MDD 관리자 리셋")
            await self.save_to_redis()


    async def execute_reduction(self, mdd_action: dict) -> list[dict]:
        """MDD 액션에 따라 포지션 축소 매도 실행.

        CLAUDE.md 5.3:
        - REDUCE_AND_PAUSE (-10%): 기존 포지션 30% 축소
        - FORCE_REDUCE (-20%): 50% 강제 축소, 레버리지/인버스 ETF 우선

        중복 실행 방지: 동일 reduction_applied 레벨에서 1회만 실행.
        """
        action = mdd_action.get("action", "NONE")
        if action == "NONE":
            return []

        reduce_pct = mdd_action.get("reduce_pct", 0.0)
        prioritize_leverage = mdd_action.get("prioritize_leverage", False)

        if reduce_pct <= 0:
            return []

        # [BUG FIX] executed_key를 Lock 밖(finally)에서도 참조하므로
        # Lock 진입 전에 None으로 초기화
        executed_key: Optional[str] = None

        # 중복 실행 방지: 이미 해당 레벨의 축소가 실행된 경우 스킵
        async with self._lock:
            # [이슈2 수정] reduction_applied가 None이면 executed_key가
            # "_reduction_executed_None" 속성을 생성해 중복 실행 방지가 무력화됨.
            # None 상태는 MDD 미달(정상)이므로 early return.
            if self.reduction_applied is None:
                logger.debug(f"[MDD] reduction_applied=None — 축소 불필요, 스킵")
                return []
            executed_key = f"_reduction_executed_{self.reduction_applied}"
            if getattr(self, executed_key, False):
                logger.debug(f"[MDD] {action} 축소 이미 실행됨 — 스킵")
                return []
            setattr(self, executed_key, True)

        try:
            from app.services.korea_investment_api import korea_investment_api
            from app.services.db_worker import enqueue_trade_history

            # 현재 보유 종목 조회
            balance = await korea_investment_api.get_balance()
            holdings = balance.get("output1", [])
            if not holdings:
                logger.info(f"[MDD] {action} — 보유 종목 없음, 축소 불필요")
                return []

            # 레버리지/인버스 ETF 우선 정렬 (FORCE_REDUCE 시)
            LEVERAGE_KEYWORDS = {"레버리지", "2X", "3X", "인버스", "TIGER 200선물", "KODEX 인버스", "곱버스"}
            if prioritize_leverage:
                def _is_leverage(h):
                    name = h.get("prdt_name", "")
                    return any(kw in name for kw in LEVERAGE_KEYWORDS)
                holdings = sorted(holdings, key=lambda h: (not _is_leverage(h),))

            results = []
            skipped = 0
            for h in holdings:
                stock_code = h.get("pdno", "")
                stock_name = h.get("prdt_name", stock_code)
                quantity = int(h.get("hldg_qty", 0) or 0)
                current_price = float(h.get("prpr", 0) or 0)

                if quantity <= 0 or current_price <= 0:
                    skipped += 1
                    continue

                sell_qty = max(int(quantity * reduce_pct), 1)
                sell_qty = min(sell_qty, quantity)

                try:
                    from app.services.trade_executor import safe_place_order
                    order_resp = await safe_place_order(
                        stock_code=stock_code,
                        order_type="SELL",
                        quantity=sell_qty,
                        price=None,  # 시장가
                    )
                    if order_resp and order_resp.get("rt_cd") == "0":
                        order_id = order_resp.get("output", {}).get("ODNO", "")
                        avg_price = float(h.get("pchs_avg_pric", current_price))
                        profit_loss = (current_price - avg_price) * sell_qty
                        profit_loss_rate = ((current_price - avg_price) / avg_price * 100) if avg_price > 0 else 0.0

                        # MDD 강제매도는 시스템적(systemic) 리스크 축소이며,
                        # 개별 종목의 전략 실패가 아니므로 loss_tracker에 기록하지 않음.
                        # 기록 시 양호한 종목이 MDD 축소로 인해 false ban될 수 있음.

                        await enqueue_trade_history({
                            "stock_code": stock_code,
                            "stock_name": stock_name,
                            "order_type": "SELL",
                            "order_price": current_price,
                            "order_quantity": sell_qty,
                            "executed_price": current_price,
                            "executed_quantity": sell_qty,
                            "total_amount": current_price * sell_qty,
                            "status": "COMPLETED",
                            "order_id": order_id,
                            "exit_reason": f"MDD {action} ({reduce_pct*100:.0f}% 축소)",
                            "net_profit_loss": profit_loss,
                            "strategy_type": "mdd_reduction",
                        })

                        # [FIX] 전량 매도 시 ActiveTrade 닫기
                        remaining_qty = quantity - sell_qty
                        if remaining_qty <= 0:
                            from app.services.db_worker import enqueue_close_active_trade
                            await enqueue_close_active_trade(stock_code)
                        else:
                            # 부분 매도: remaining_pct 갱신
                            # 기존 ActiveTrade의 remaining_pct에 매도 비율을 곱해야 함
                            # (예: 기존 0.5 * 남은비율 0.7 = 0.35)
                            # db_worker가 직접 setattr하므로, reduce_ratio를 전달하여
                            # 워커가 기존 값에 곱하도록 처리
                            from app.services.db_worker import enqueue_active_trade_upsert
                            sell_ratio = remaining_qty / quantity  # 남은 비율 (0.7 or 0.5)
                            await enqueue_active_trade_upsert({
                                "stock_code": stock_code,
                                "remaining_pct_multiply": sell_ratio,
                            })

                        results.append({
                            "stock_code": stock_code,
                            "stock_name": stock_name,
                            "sell_quantity": sell_qty,
                            "reason": action,
                        })
                        logger.warning(
                            f"[MDD] {action} 매도: {stock_code} {stock_name} "
                            f"{sell_qty}주 (총 {quantity}주 중 {reduce_pct*100:.0f}%)"
                        )

                    await asyncio.sleep(0.3)  # KIS API 레이트 리밋

                except Exception as e:
                    logger.error(f"[MDD] 축소 매도 실패 ({stock_code}): {e}")

            failed_count = len(holdings) - len(results) - skipped
            if failed_count > 0 and executed_key is not None:
                # 매도 실패 종목이 있으면 플래그 리셋 → 다음 주기에 재시도
                async with self._lock:
                    setattr(self, executed_key, False)
                logger.warning(
                    f"[MDD] {action} 부분 완료: {len(results)}종목 성공, "
                    f"{failed_count}종목 실패 → 다음 주기 재시도 예정"
                )
            else:
                logger.warning(f"[MDD] {action} 완료: {len(results)}종목 축소 매도")
            return results

        except Exception as e:
            logger.error(f"[MDD] execute_reduction 실패: {e}", exc_info=True)
            # 전체 실패 시 플래그 리셋 → 재시도 가능
            if executed_key is not None:
                async with self._lock:
                    setattr(self, executed_key, False)
            return []

    async def execute_reduction_v2(self, mdd_action: dict, kis, user_id: int) -> list[dict]:
        """[v2] 사용자 스코프 포지션 축소 매도 실행.

        execute_reduction()과 동일 로직이나 전역 korea_investment_api 대신 주입된
        kis(사용자 인스턴스)를 사용하고, trade_history/active_trade 큐 payload에
        user_id를 포함해 db_worker가 해당 사용자 레코드만 갱신하도록 한다.
        기존 execute_reduction()은 완전히 불변.
        """
        action = mdd_action.get("action", "NONE")
        if action == "NONE":
            return []

        reduce_pct = mdd_action.get("reduce_pct", 0.0)
        prioritize_leverage = mdd_action.get("prioritize_leverage", False)

        if reduce_pct <= 0:
            return []

        executed_key: Optional[str] = None

        async with self._lock:
            if self.reduction_applied is None:
                logger.debug(f"[MDD v2] user={user_id} reduction_applied=None — 축소 불필요, 스킵")
                return []
            executed_key = f"_reduction_executed_{self.reduction_applied}"
            if getattr(self, executed_key, False):
                logger.debug(f"[MDD v2] user={user_id} {action} 축소 이미 실행됨 — 스킵")
                return []
            setattr(self, executed_key, True)

        try:
            from app.services.db_worker import (
                enqueue_trade_history,
                enqueue_close_active_trade_v2,
                enqueue_active_trade_upsert,
            )

            balance = await kis.get_balance()
            holdings = balance.get("output1", [])
            if not holdings:
                logger.info(f"[MDD v2] user={user_id} {action} — 보유 종목 없음, 축소 불필요")
                return []

            LEVERAGE_KEYWORDS = {"레버리지", "2X", "3X", "인버스", "TIGER 200선물", "KODEX 인버스", "곱버스"}
            if prioritize_leverage:
                def _is_leverage(h):
                    name = h.get("prdt_name", "")
                    return any(kw in name for kw in LEVERAGE_KEYWORDS)
                holdings = sorted(holdings, key=lambda h: (not _is_leverage(h),))

            results = []
            skipped = 0
            for h in holdings:
                stock_code = h.get("pdno", "")
                stock_name = h.get("prdt_name", stock_code)
                quantity = int(h.get("hldg_qty", 0) or 0)
                current_price = float(h.get("prpr", 0) or 0)

                if quantity <= 0 or current_price <= 0:
                    skipped += 1
                    continue

                sell_qty = max(int(quantity * reduce_pct), 1)
                sell_qty = min(sell_qty, quantity)

                try:
                    # UserContext 조립 완료(트레이딩팀) — 종목별 동시 주문 락
                    # (_order_semaphores/Redis 분산락)을 거치도록 safe_place_order_v2 사용.
                    # SL/사이징 로직은 그대로, 주문 호출 경로만 교체.
                    from app.services.tenant.context import UserContext
                    from app.services.trade_executor import safe_place_order_v2

                    from app.core.config import settings as _settings

                    reduction_ctx = UserContext(
                        user_id=user_id,
                        username="",
                        mode=getattr(kis, "mode", _settings.KIS_MODE),
                        kis=kis,
                        mdd=self,
                        loss_tracker=None,
                    )
                    order_resp = await safe_place_order_v2(
                        reduction_ctx,
                        stock_code=stock_code,
                        order_type="SELL",
                        quantity=sell_qty,
                        price=None,  # 시장가
                    )
                    if order_resp and order_resp.get("rt_cd") == "0":
                        order_id = order_resp.get("output", {}).get("ODNO", "")
                        avg_price = float(h.get("pchs_avg_pric", current_price))
                        profit_loss = (current_price - avg_price) * sell_qty
                        profit_loss_rate = ((current_price - avg_price) / avg_price * 100) if avg_price > 0 else 0.0

                        # MDD 강제매도는 시스템적 리스크 축소 — loss_tracker 미기록 (execute_reduction과 동일 정책)
                        await enqueue_trade_history({
                            "user_id": user_id,
                            "stock_code": stock_code,
                            "stock_name": stock_name,
                            "order_type": "SELL",
                            "order_price": current_price,
                            "order_quantity": sell_qty,
                            "executed_price": current_price,
                            "executed_quantity": sell_qty,
                            "total_amount": current_price * sell_qty,
                            "status": "COMPLETED",
                            "order_id": order_id,
                            "exit_reason": f"MDD {action} ({reduce_pct*100:.0f}% 축소)",
                            "net_profit_loss": profit_loss,
                            "strategy_type": "mdd_reduction",
                        })

                        remaining_qty = quantity - sell_qty
                        if remaining_qty <= 0:
                            await enqueue_close_active_trade_v2(user_id, stock_code, strategy_name=None)
                        else:
                            sell_ratio = remaining_qty / quantity
                            await enqueue_active_trade_upsert({
                                "user_id": user_id,
                                "stock_code": stock_code,
                                "remaining_pct_multiply": sell_ratio,
                            })

                        results.append({
                            "stock_code": stock_code,
                            "stock_name": stock_name,
                            "sell_quantity": sell_qty,
                            "reason": action,
                        })
                        logger.warning(
                            f"[MDD v2] user={user_id} {action} 매도: {stock_code} {stock_name} "
                            f"{sell_qty}주 (총 {quantity}주 중 {reduce_pct*100:.0f}%)"
                        )

                    await asyncio.sleep(0.3)  # KIS API 레이트 리밋

                except Exception as e:
                    logger.error(f"[MDD v2] user={user_id} 축소 매도 실패 ({stock_code}): {e}")

            failed_count = len(holdings) - len(results) - skipped
            if failed_count > 0 and executed_key is not None:
                async with self._lock:
                    setattr(self, executed_key, False)
                logger.warning(
                    f"[MDD v2] user={user_id} {action} 부분 완료: {len(results)}종목 성공, "
                    f"{failed_count}종목 실패 → 다음 주기 재시도 예정"
                )
            else:
                logger.warning(f"[MDD v2] user={user_id} {action} 완료: {len(results)}종목 축소 매도")
            return results

        except Exception as e:
            logger.error(f"[MDD v2] user={user_id} execute_reduction_v2 실패: {e}", exc_info=True)
            if executed_key is not None:
                async with self._lock:
                    setattr(self, executed_key, False)
            return []


# 싱글톤 인스턴스
mdd_manager = MDDManager()