import sys
import os
sys.stdout.reconfigure(line_buffering=True, encoding="utf-8")
sys.stderr.reconfigure(line_buffering=True, encoding="utf-8")
os.environ["PYTHONUNBUFFERED"] = "1"
os.environ["PYTHONIOENCODING"] = "utf-8"

import time
import requests
from dotenv import load_dotenv
load_dotenv()
import pandas as pd
import numpy as np
from datetime import datetime, timezone, timedelta
import threading
import streamlit as st
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import ta
import urllib3
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)


# ──────────────────────────────────────────────
# 페이지 설정 (반드시 최상단)
# ──────────────────────────────────────────────
st.set_page_config(
    page_title="중고모아 트레이딩 대시보드",
    layout="wide",
    initial_sidebar_state="expanded"
)

# 라이트모드 강제 + 한글 폰트
st.markdown("""
<link href="https://fonts.googleapis.com/css2?family=Noto+Sans+KR:wght@300;400;500;600;700&display=swap" rel="stylesheet">
<style>
    html, body, [class*="css"], [data-testid="stAppViewContainer"], [data-testid="stHeader"], [data-testid="stSidebar"] {
        font-family: 'Noto Sans KR', 'Apple SD Gothic Neo', 'Malgun Gothic', system-ui, -apple-system, sans-serif !important;
    }
    html, body, [data-testid="stAppViewContainer"], [data-testid="stHeader"] {
        background-color: #ffffff !important;
        color: #131722 !important;
    }
    [data-testid="stSidebar"] { background-color: #f0f3fa !important; }
    .stSelectbox > div > div { background-color: #ffffff !important; color: #131722 !important; }
    .stButton > button { background-color: #238636 !important; color: #ffffff !important; border: none !important; }
    header { background-color: #f0f0f0 !important; }
</style>
""", unsafe_allow_html=True)

# ──────────────────────────────────────────────
# 설정 — 모든 운영 파라미터는 DB (settings_db.py) 에서 동적으로 조회.
# .env 값은 최초 기동 시에만 DB 기본값으로 복사된다.
# ──────────────────────────────────────────────
import settings_db
import trades_db
import exchange_keys
import exchange_adapters
import users_db
settings_db.init_db_with_env_defaults()
trades_db.init_db()
exchange_keys.init_db()
users_db.init_db()


# ──────────────────────────────────────────────
# 로고 (SVG) — assets/logo.svg 가 있으면 그걸, 없으면 inline fallback
# ──────────────────────────────────────────────
def load_logo_svg(scale: float = 1.0) -> str:
    try:
        with open("assets/logo.svg", "r", encoding="utf-8") as f:
            return f.read()
    except Exception:
        return ""

def TELEGRAM_TOKEN():    return settings_db.get("telegram_token", "")
def TELEGRAM_CHAT_ID():  return settings_db.get("telegram_chat_id", "")
def ALERT_COOLDOWN():    return settings_db.get_int("alert_cooldown_sec", 600)
def STOP_LOSS_PCT_v():   return settings_db.get_float("stop_loss_pct", 0.0075)

BASE = "https://fapi.binance.com"
KST  = timedelta(hours=9)

# 호환용 상수 — 일부 함수에서 직접 참조. DB 값으로 매번 갱신.
STOP_LOSS_PCT = 0.0075  # runtime 에서 STOP_LOSS_PCT_v() 사용 권장
LONG_SIGNALS  = {"strong_long_signal", "long_signal", "vol_long_signal", "reversal_long_signal"}
SHORT_SIGNALS = {"strong_short_signal", "short_signal", "vol_short_signal", "reversal_short_signal"}
TF_LABEL_MAP = {
    "1m": "1분봉", "3m": "3분봉", "5m": "5분봉",
    "15m": "15분봉", "30m": "30분봉",
    "1h": "1시간봉", "4h": "4시간봉", "12h": "12시간봉",
    "1d": "1일봉", "3d": "3일봉", "1M": "1개월봉",
}

# Streamlit 은 매 rerun 마다 메인 스크립트를 새 namespace 에서 재실행해
# globals() 가드도 우회된다. 알림 mutable 상태는 별도 모듈에 두어 sys.modules
# 캐싱으로 process lifetime 보존되도록 한다 (alert_state.py 참조).
import alert_state

# ──────────────────────────────────────────────
# 텔레그램
# ──────────────────────────────────────────────
def send_telegram(message: str):
    token = TELEGRAM_TOKEN()
    chat_id = TELEGRAM_CHAT_ID()
    if not token or not chat_id:
        print("[텔레그램] 토큰/chat_id 미설정 — 메시지 skip")
        return
    try:
        url = f"https://api.telegram.org/bot{token}/sendMessage"
        requests.post(url, data={"chat_id": chat_id, "text": message}, timeout=10)
    except Exception as e:
        print(f"[텔레그램 오류] {e}")

SIG_DEFS = [
    ("strong_long_signal",   "strong_long",  "🟢 강한 롱",  "long"),
    ("strong_short_signal",  "strong_short", "🔴 강한 숏",  "short"),
    ("long_signal",          "long",         "🔼 일반 롱",  "long"),
    ("short_signal",         "short",        "🔽 일반 숏",  "short"),
    ("vol_long_signal",      "vol_long",     "🔼 볼륨 롱",  "long"),
    ("vol_short_signal",     "vol_short",    "🔽 볼륨 숏",  "short"),
    ("reversal_long_signal", "rev_long",     "🔄 롱 추세 꺾임 감지",  "long"),
    ("reversal_short_signal","rev_short",    "🔄 숏 추세 꺾임 감지",  "short"),
    ("short_caution_signal", "short_caution","⚠️ 숏 주의", "caution"),
]

def check_and_alert(df, symbol, interval):
    now = time.time()
    if df is None or df.empty:
        return
    forming_ct = df.iloc[-1]["open_time"]

    # 재시작 후 첫 polling — 역사적 신호 burst 차단을 위해 dedup 만 silent sync
    if interval not in alert_state.synced_intervals:
        for sig, key, _, _ in SIG_DEFS:
            if sig not in df.columns:
                continue
            triggered = df[df[sig].fillna(False)]
            if not triggered.empty:
                alert_state.last_fired_candle[(interval, key)] = triggered.iloc[-1]["open_time"]
        alert_state.synced_intervals.add(interval)
        print(f"[알림스레드] {interval} 초기 sync 완료 — 이후 polling 부터 새 신호만 발사")
        return

    # Phase 1 — pending_groups 검증. forming candle 이라도 매 polling 마다 신호
    # 상태 확인. 사라지면 즉시 [취소 알림] (캔들 마감까지 기다리지 않음).
    new_pending = []
    for p in alert_state.pending_groups:
        if p["interval"] != interval:
            new_pending.append(p)
            continue
        ct = p["candle_time"]
        row_match = df[df["open_time"] == ct]
        if row_match.empty:
            continue  # 캔들이 df 윈도우 밖 — 검증 포기, drop
        row = row_match.iloc[0]
        any_still_true = any(bool(row.get(s, False)) for s in p["sig_cols"])
        if any_still_true:
            if ct == forming_ct:
                # forming 중 + 신호 살아있음 → 계속 감시
                new_pending.append(p)
            # closed + 신호 살아있음 → 확정, pending 에서 제거
        else:
            # 신호 사라짐 (forming/closed 무관) → 즉시 취소 알림
            send_telegram(f"[취소 알림]\n{p['msg']}")
            le = alert_state.long_entry.get(interval)
            se = alert_state.short_entry.get(interval)
            if p["direction"] == "long" and le is not None and le.get("open_time") == ct:
                trades_db.record_exit(symbol, interval, "long", ct,
                                       float(row["close"]), "cancelled")
                alert_state.long_entry[interval] = None
            elif p["direction"] == "short" and se is not None and se.get("open_time") == ct:
                trades_db.record_exit(symbol, interval, "short", ct,
                                        float(row["close"]), "cancelled")
                alert_state.short_entry[interval] = None
    alert_state.pending_groups = new_pending

    # Phase 2 — 신호 검사 + 알림 발사 (모든 TF forming candle 포함).
    # 30초 polling 으로 매 사이클마다 forming candle 의 신호 상태 재검증 →
    # 신호 사라지면 즉시 [취소 알림] 발사 (Phase 1 로직). 5m=2.5m, 15m=7.5m,
    # 30m=15m, 1h=30m 의 절반 시간보다 훨씬 빠른 검증 주기.
    recent = df.tail(3)

    eligible = []
    for sig, key, sub_label, direction in SIG_DEFS:
        if sig not in recent.columns:
            continue
        triggered = recent[recent[sig].fillna(False)]
        seen_key = (interval, sig)
        prev_seen = alert_state.signal_seen_count.get(seen_key)
        if triggered.empty:
            # 신호 사라짐 → 카운터 리셋 (다음 True 시점부터 다시 1회 카운트)
            if prev_seen:
                alert_state.signal_seen_count[seen_key] = {"candle_time": prev_seen["candle_time"], "count": 0}
            continue
        candle_time = triggered.iloc[-1]["open_time"]
        state_key = (interval, key)
        if candle_time == alert_state.last_fired_candle.get(state_key):
            continue
        if now - alert_state.last_alert.get(state_key, 0) <= ALERT_COOLDOWN():
            continue
        # 연속 True polling 카운트 갱신
        if prev_seen is None or prev_seen["candle_time"] != candle_time:
            alert_state.signal_seen_count[seen_key] = {"candle_time": candle_time, "count": 1}
        else:
            alert_state.signal_seen_count[seen_key] = {"candle_time": candle_time, "count": prev_seen["count"] + 1}
        count = alert_state.signal_seen_count[seen_key]["count"]
        # forming candle 만 안정성 (N polls) 요구. 닫힌 캔들은 즉시 발사 (data 확정).
        stable_min = settings_db.get_int("forming_stable_polls", 2)
        if candle_time == forming_ct and count < stable_min:
            continue
        eligible.append({
            "sig": sig, "key": key, "sub_label": sub_label,
            "direction": direction, "candle_time": candle_time, "row": triggered.iloc[-1],
        })

    if not eligible:
        groups = {}
    else:
        groups = {"long": [], "short": [], "caution": []}
        for e in eligible:
            groups[e["direction"]].append(e)

    tf_label = TF_LABEL_MAP.get(interval, interval)

    def _send_group(group):
        if not group:
            return
        candle_time = group[0]["candle_time"]
        candle_time_str = pd.Timestamp(candle_time).strftime("%Y-%m-%d %H:%M")
        sub_labels = " + ".join(e["sub_label"] for e in group)
        direction = group[0]["direction"]
        trades_db.log_signal_events(symbol, interval, group)
        if direction == "caution":
            msg = (
                f"{sub_labels} 신호\n{symbol} {tf_label}\n"
                f"시간: {candle_time_str}"
            )
            send_telegram(msg)
        else:
            entry_price = float(group[0]["row"]["open"])
            sl_pct = STOP_LOSS_PCT_v()
            if direction == "long":
                stop_price = entry_price * (1 - sl_pct)
            else:
                stop_price = entry_price * (1 + sl_pct)
            msg = (
                f"{sub_labels} 진입 신호\n{symbol} {tf_label}\n"
                f"시간: {candle_time_str}\n"
                f"진입가: {entry_price:,.2f}\n"
                f"손절가: {stop_price:,.2f}"
            )
            entry_record = {"price": entry_price, "stop": stop_price, "open_time": candle_time, "entry_msg": msg}
            # 청산 권고는 30m / 1h 의 새 진입 신호만 트리거 (5m / 15m opposite
            # 은 노이즈가 많아 청산권고로 부적합 — 변동성 큰 날 폭주 방지).
            if interval in ("30m", "1h"):
                opposite_dict = alert_state.short_entry if direction == "long" else alert_state.long_entry
                opposite_label = "숏" if direction == "long" else "롱"
                opposite_direction = "short" if direction == "long" else "long"
                for opp_interval, opp_rec in list(opposite_dict.items()):
                    if opp_rec is None:
                        continue
                    send_telegram(
                        f"[반대 신호 감지 - {opposite_label} 청산 권장]\n"
                        f"--- 기존 진입 ---\n{opp_rec['entry_msg']}\n"
                        f"--- 반대 신호 ---\n{msg}"
                    )
                    trades_db.record_exit(symbol, opp_interval, opposite_direction,
                                            opp_rec.get("open_time"), entry_price, "reversal")
                    opposite_dict[opp_interval] = None
            if direction == "long":
                alert_state.long_entry[interval] = entry_record
            else:
                alert_state.short_entry[interval] = entry_record
            trades_db.record_entry(symbol, interval, direction,
                                    [e["sig"] for e in group],
                                    candle_time, entry_price, stop_price)
            send_telegram(msg)
        for e in group:
            alert_state.last_alert[(interval, e["key"])] = now
            alert_state.last_fired_candle[(interval, e["key"])] = e["candle_time"]
        if candle_time == forming_ct:
            alert_state.pending_groups.append({
                "interval": interval,
                "direction": direction,
                "candle_time": candle_time,
                "msg": msg,
                "sig_cols": [e["sig"] for e in group],
            })

    _send_group(groups.get("long", []))
    _send_group(groups.get("short", []))
    _send_group(groups.get("caution", []))

    current_price = float(df.iloc[-1]["close"])
    le = alert_state.long_entry.get(interval)
    se = alert_state.short_entry.get(interval)
    if le is not None and current_price <= le["stop"]:
        send_telegram(
            f"[손절가알림]\n{le['entry_msg']}\n"
            f"현재가: {current_price:,.2f}"
        )
        trades_db.record_exit(symbol, interval, "long", le.get("open_time"),
                                current_price, "stop_loss")
        alert_state.long_entry[interval] = None
    if se is not None and current_price >= se["stop"]:
        send_telegram(
            f"[손절가알림]\n{se['entry_msg']}\n"
            f"현재가: {current_price:,.2f}"
        )
        trades_db.record_exit(symbol, interval, "short", se.get("open_time"),
                                current_price, "stop_loss")
        alert_state.short_entry[interval] = None

# ──────────────────────────────────────────────
# 데이터 수집
# ──────────────────────────────────────────────
def get_klines(symbol="BTCUSDT", interval="5m", limit=375):
    url = f"{BASE}/fapi/v1/klines"
    r = requests.get(url, params={"symbol": symbol, "interval": interval, "limit": limit}, timeout=10, verify=False)
    df = pd.DataFrame(r.json(), columns=[
        "open_time","open","high","low","close","volume",
        "close_time","quote_vol","trades","taker_buy_vol","taker_sell_vol","ignore"
    ])
    for c in ["open","high","low","close","volume","taker_buy_vol","taker_sell_vol"]:
        df[c] = df[c].astype(float)
    df["taker_sell_vol"] = df["volume"] - df["taker_buy_vol"]
    df["open_time"] = pd.to_datetime(df["open_time"], unit="ms") + KST
    return df

def get_funding_rate(symbol="BTCUSDT", limit=100):
    url = f"{BASE}/fapi/v1/fundingRate"
    r = requests.get(url, params={"symbol": symbol, "limit": limit}, timeout=10, verify=False)
    df = pd.DataFrame(r.json())
    df["fundingRate"] = df["fundingRate"].astype(float) * 100
    df["fundingTime"] = pd.to_datetime(df["fundingTime"], unit="ms") + KST
    return df

def get_open_interest_history(symbol="BTCUSDT", period="5m", limit=100):
    url = f"{BASE}/futures/data/openInterestHist"
    r = requests.get(url, params={"symbol": symbol, "period": period, "limit": limit}, timeout=10, verify=False)
    df = pd.DataFrame(r.json())
    df["sumOpenInterest"] = df["sumOpenInterest"].astype(float)
    df["timestamp"] = pd.to_datetime(df["timestamp"], unit="ms") + KST
    return df

def get_long_short_ratio(symbol="BTCUSDT", period="5m", limit=500):
    url = f"{BASE}/futures/data/topLongShortPositionRatio"
    r = requests.get(url, params={"symbol": symbol, "period": period, "limit": limit}, timeout=10, verify=False)
    df = pd.DataFrame(r.json())
    df["longShortRatio"] = df["longShortRatio"].astype(float)
    df["timestamp"] = pd.to_datetime(df["timestamp"], unit="ms") + KST
    return df

def get_taker_buy_sell_ratio(symbol="BTCUSDT", period="5m", limit=100):
    url = f"{BASE}/futures/data/takerlongshortRatio"
    r = requests.get(url, params={"symbol": symbol, "period": period, "limit": limit}, timeout=10, verify=False)
    df = pd.DataFrame(r.json())
    df["buySellRatio"] = df["buySellRatio"].astype(float)
    df["timestamp"] = pd.to_datetime(df["timestamp"], unit="ms") + KST
    return df

# ──────────────────────────────────────────────
# 지표 계산
# ──────────────────────────────────────────────
def compute_indicators(df, interval="5m"):
    c = df["close"]
    df["MA7"]   = c.rolling(7).mean()
    df["MA25"]  = c.rolling(25).mean()
    df["MA99"]  = c.rolling(99).mean()
    df["MA200"] = c.rolling(200).mean()
    df["BB_mid"]   = c.rolling(20).mean()
    df["BB_std"]   = c.rolling(20).std()
    df["BB_upper"] = df["BB_mid"] + 2 * df["BB_std"]
    df["BB_lower"] = df["BB_mid"] - 2 * df["BB_std"]
    df["RSI"]  = ta.momentum.RSIIndicator(c, window=14).rsi()
    macd = ta.trend.MACD(c, window_slow=26, window_fast=12, window_sign=9)
    df["MACD"] = macd.macd()
    df["MACD_signal"] = macd.macd_signal()
    df["MACD_hist"]   = macd.macd_diff()
    stoch = ta.momentum.StochRSIIndicator(c, window=14, smooth1=3, smooth2=3)
    df["StochRSI_k"] = stoch.stochrsi_k() * 100
    df["StochRSI_d"] = stoch.stochrsi_d() * 100
    df["ATR"] = ta.volatility.AverageTrueRange(df["high"], df["low"], df["close"], window=14).average_true_range()
    df = compute_signals(df, interval)
    return df

def compute_signals(df, interval="5m"):
    # 임계값들은 settings_db 에서 1회 조회 (rerun 마다 N개 변수 호출 비용 작음)
    LONG_RSI_MAX     = settings_db.get_float("long_rsi_max", 75.0)
    SHORT_RSI_MIN    = settings_db.get_float("short_rsi_min", 25.0)
    SLONG_RSI_MAX    = settings_db.get_float("strong_long_rsi_max", 65.0)
    SSHORT_RSI_MIN   = settings_db.get_float("strong_short_rsi_min", 35.0)
    BODY_PCT_MIN     = settings_db.get_float("body_pct_min", 0.002)
    REV_BODY_PCT     = settings_db.get_float("reversal_body_pct", 0.003)
    REV_VOL_MULT     = settings_db.get_float("reversal_vol_mult", 1.3)
    VOL_EXH_MULT     = settings_db.get_float("vol_exhaustion_mult", 3.0)
    VOL_NET_MULT     = settings_db.get_float("vol_net_mult", 2.0)
    OI_ACTIVE_PCT    = settings_db.get_float("oi_active_pct", 0.001)
    FR_SHORT_EXTREME = settings_db.get_float("fr_short_extreme", -0.007)

    # close 가 MA7, MA25 양쪽 위/아래에 있는 것 만 요구. MA끼리 정렬 (MA7>MA25)은
    # 추세 반전 직후엔 늦게 형성되어 양봉/음봉 신호를 차단하는 부작용 있어 제거.
    df["bull_ma_2"] = (
        (df["close"] > df["MA7"]) & (df["close"] > df["MA25"])
    )
    df["bear_ma_2"] = (
        (df["close"] < df["MA7"]) & (df["close"] < df["MA25"])
    )
    df["bull_ma"] = (
        (df["close"] > df["MA7"]) & (df["MA7"] > df["MA25"])
    )
    df["bear_ma"] = (
        (df["close"] < df["MA7"]) & (df["MA7"] < df["MA25"])
    )
    bb_range = (df["BB_upper"] - df["BB_lower"]).replace(0, float("nan"))
    df["bb_pos"] = (df["close"] - df["BB_lower"]) / bb_range
    body_pct = (df["close"] - df["open"]) / df["open"].replace(0, float("nan"))
    df["long_signal"]  = df["bull_ma_2"] & (df["RSI"] < LONG_RSI_MAX)  & (df["MACD_hist"] > df["MACD_hist"].shift(1)) & (df["close"] > df["BB_mid"]) & (body_pct >= BODY_PCT_MIN)
    df["short_signal"] = df["bear_ma_2"] & (df["RSI"] > SHORT_RSI_MIN) & (df["MACD_hist"] < df["MACD_hist"].shift(1)) & (df["close"] < df["BB_mid"]) & (body_pct <= -BODY_PCT_MIN)
    df["long_signal"]  = df["long_signal"]  & (df["long_signal"].rolling(5,  min_periods=1).sum().shift(1).fillna(0) == 0)
    df["short_signal"] = df["short_signal"] & (df["short_signal"].rolling(5, min_periods=1).sum().shift(1).fillna(0) == 0)

    if "sumOpenInterest" in df.columns and df["sumOpenInterest"].notna().sum() > 5:
        oi_series = df["sumOpenInterest"].ffill()
    else:
        oi_series = df["close"] * df["volume"]
    df["oi_up"]    = oi_series > oi_series.shift(1)
    df["oi_down"]  = oi_series < oi_series.shift(1)
    df["oi_up_2"]   = df["oi_up"]  & df["oi_up"].shift(1).fillna(False)
    df["oi_down_2"] = df["oi_down"] & df["oi_down"].shift(1).fillna(False)
    df["oi_active"] = oi_series.pct_change().abs() > OI_ACTIVE_PCT

    df["taker_buy_dom"]  = df["taker_buy_vol"]  > df["taker_sell_vol"]
    df["taker_sell_dom"] = df["taker_sell_vol"] > df["taker_buy_vol"]
    df["taker_buy_2"]  = df["taker_buy_dom"]  & df["taker_buy_dom"].shift(1).fillna(False)
    df["taker_sell_2"] = df["taker_sell_dom"] & df["taker_sell_dom"].shift(1).fillna(False)

    df["fr_long_favor"]  = df["taker_buy_vol"].rolling(3).mean()  > df["taker_sell_vol"].rolling(3).mean()
    df["fr_short_favor"] = df["taker_sell_vol"].rolling(3).mean() > df["taker_buy_vol"].rolling(3).mean()

    df["strong_long_signal"]  = df["bull_ma_2"] & (df["RSI"] < SLONG_RSI_MAX)  & (df["MACD_hist"] > df["MACD_hist"].shift(1)) & df["oi_up_2"]   & df["taker_buy_2"]  & df["fr_long_favor"]  & (df["close"] > df["open"])
    df["strong_short_signal"] = df["bear_ma_2"] & (df["RSI"] > SSHORT_RSI_MIN) & (df["MACD_hist"] < df["MACD_hist"].shift(1)) & df["oi_down_2"] & df["taker_sell_2"] & df["fr_short_favor"] & (df["close"] < df["open"])
    df["strong_long_signal"]  = df["strong_long_signal"]  & (df["strong_long_signal"].rolling(10,  min_periods=1).sum().shift(1).fillna(0) == 0)
    df["strong_short_signal"] = df["strong_short_signal"] & (df["strong_short_signal"].rolling(10, min_periods=1).sum().shift(1).fillna(0) == 0)

    vol_avg    = df["volume"].rolling(10).mean()
    spike      = df["volume"] > vol_avg * VOL_EXH_MULT
    buy_spike  = spike & (df["taker_buy_vol"]  > df["taker_sell_vol"])
    sell_spike = spike & (df["taker_sell_vol"] > df["taker_buy_vol"])
    df["exhaustion_short"] = buy_spike.shift(1).fillna(False)
    df["exhaustion_long"]  = sell_spike.shift(1).fillna(False)

    _vol_min_map = {"1m": 33, "3m": 100, "5m": 100, "15m": 300, "30m": 600, "1h": 1200, "2h": 2400, "4h": 4800, "12h": 14400, "1d": 28800, "3d": 86400, "1M": 864000}
    _vol_min = _vol_min_map.get(interval, 100)

    df["sell_net"] = df["taker_sell_vol"] - df["taker_buy_vol"]
    sell_net_avg = df["sell_net"].rolling(10).mean()
    sell_spike_strong = (
        (df["sell_net"] > sell_net_avg * VOL_NET_MULT) &
        (df["sell_net"] > 0) &
        (df["taker_sell_vol"] > _vol_min) &
        df["oi_active"]
    )
    cooldown_vol_short = sell_spike_strong.rolling(10, min_periods=1).sum().shift(1).fillna(0) == 0
    df["vol_short_signal"] = sell_spike_strong & cooldown_vol_short

    df["buy_net"] = df["taker_buy_vol"] - df["taker_sell_vol"]
    buy_net_avg = df["buy_net"].rolling(10).mean()
    buy_spike_strong = (
        (df["buy_net"] > buy_net_avg * VOL_NET_MULT) &
        (df["buy_net"] > 0) &
        (df["taker_buy_vol"] > _vol_min) &
        df["oi_active"]
    )
    cooldown_vol_long = buy_spike_strong.rolling(10, min_periods=1).sum().shift(1).fillna(0) == 0
    df["vol_long_signal"] = buy_spike_strong & cooldown_vol_long

    if "fundingRate" in df.columns and "sumOpenInterest" in df.columns:
        fr_extreme = df["fundingRate"] <= FR_SHORT_EXTREME
        raw_signal = df["oi_down_2"] & fr_extreme
        cooldown_mask = raw_signal.rolling(5, min_periods=1).sum().shift(1).fillna(0) == 0
        df["short_caution_signal"] = raw_signal & cooldown_mask
    else:
        df["short_caution_signal"] = False

    # 추세 꺾임 감지: 직전 3봉의 추세 방향과 현재 캔들 방향이 반대 + 강한 폭 + 거래량 동반.
    # - 추세 판단: close[t-1] vs close[t-3] (현재 캔들 제외, 직전까지의 흐름)
    # - 현재 캔들 강도: |close-open|/open >= 0.3% (작은 캔들 노이즈 차단)
    # - 거래량: 직전 3봉 평균의 1.3배 이상 (확신)
    # - 쿨다운: 3봉
    prior_close = df["close"].shift(1)
    prior_close_3 = df["close"].shift(3)
    was_up = prior_close > prior_close_3
    was_down = prior_close < prior_close_3
    candle_body_pct = (df["close"] - df["open"]) / df["open"].replace(0, float("nan"))
    vol_avg3 = df["volume"].rolling(3).mean().shift(1)
    vol_strong = df["volume"] > vol_avg3 * REV_VOL_MULT
    rev_short_raw = was_up & (candle_body_pct < -REV_BODY_PCT) & vol_strong
    rev_long_raw  = was_down & (candle_body_pct > REV_BODY_PCT) & vol_strong
    df["reversal_short_signal"] = rev_short_raw & (rev_short_raw.rolling(3, min_periods=1).sum().shift(1).fillna(0) == 0)
    df["reversal_long_signal"]  = rev_long_raw  & (rev_long_raw.rolling(3,  min_periods=1).sum().shift(1).fillna(0) == 0)

    return df

# ──────────────────────────────────────────────
# 차트 빌드
# ──────────────────────────────────────────────
COLORS = {
    "bg":    "#ffffff",
    "grid":  "#e0e3eb",
    "text":  "#131722",
    "green": "#26a69a",
    "red":   "#ef5350",
    "yellow":"#f5ce05",
    "blue":  "#2962ff",
    "purple":"#9c27b0",
    "orange":"#ff9800",
    "MA7":   "#f5ce05",
    "MA25":  "#ef5350",
    "MA99":  "#9c27b0",
    "MA200": "#2962ff",
    "BB":    "rgba(41,98,255,0.1)",
}

def _to_floor_freq(period):
    return {"1m":"1min","3m":"3min","5m":"5min","15m":"15min","30m":"30min","1h":"1h","4h":"4h","12h":"12h","1d":"1D","3d":"3D","1M":"1ME"}.get(period, period)

def build_chart(symbol, interval, candle_limit=200):
    # 지표 계산은 충분한 history 필요 (MA99=99, MACD=26, BB=20, RSI=14 등).
    # candle_limit 가 작아도 fetch 는 최소 200 으로 — 차트 표시 시점에만 candle_limit 로 잘라서 보여준다.
    fetch_limit = max(candle_limit, 200)
    df = get_klines(symbol, interval, fetch_limit)
    oi_period = interval if interval in ["5m","15m","30m","1h","4h","12h","1d","3d","1M"] else "5m"

    try:
        oi = get_open_interest_history(symbol, oi_period, 200)
        if not oi.empty:
            oi_m = oi[["timestamp","sumOpenInterest"]].rename(columns={"timestamp":"open_time"})
            df["open_time_r"] = df["open_time"].dt.floor(_to_floor_freq(oi_period))
            oi_m["open_time"] = oi_m["open_time"].dt.floor(_to_floor_freq(oi_period))
            df = df.merge(oi_m, left_on="open_time_r", right_on="open_time", how="left", suffixes=("","_oi"))
            df = df.drop(columns=["open_time_r","open_time_oi"], errors="ignore")
            df["sumOpenInterest"] = df["sumOpenInterest"].ffill()
    except: pass

    try:
        fr = get_funding_rate(symbol, 200)
        if not fr.empty:
            fr_m = fr[["fundingTime","fundingRate"]].rename(columns={"fundingTime":"open_time"})
            fr_m["open_time"] = fr_m["open_time"].dt.floor(_to_floor_freq("1h"))
            df["open_time_r2"] = df["open_time"].dt.floor(_to_floor_freq("1h"))
            df = df.merge(fr_m, left_on="open_time_r2", right_on="open_time", how="left", suffixes=("","_fr"))
            df = df.drop(columns=["open_time_r2","open_time_fr"], errors="ignore")
            df["fundingRate"] = df["fundingRate"].ffill().fillna(0)
    except: pass

    try:
        ls = get_long_short_ratio(symbol, oi_period, 200)
        if not ls.empty:
            ls_m = ls[["timestamp","longShortRatio"]].rename(columns={"timestamp":"open_time"})
            df["open_time_r3"] = df["open_time"].dt.floor(_to_floor_freq(oi_period))
            ls_m["open_time"] = ls_m["open_time"].dt.floor(_to_floor_freq(oi_period))
            df = df.merge(ls_m, left_on="open_time_r3", right_on="open_time", how="left", suffixes=("","_ls"))
            df = df.drop(columns=["open_time_r3","open_time_ls"], errors="ignore")
            df["longShortRatio"] = df["longShortRatio"].ffill()
    except: pass

    df = compute_indicators(df, interval)

    try:
        if interval != "1h":
            df_1h = get_klines(symbol, "1h", 150)
            df_1h["MA7"]   = df_1h["close"].rolling(7).mean()
            df_1h["MA25"]  = df_1h["close"].rolling(25).mean()
            df_1h["MA99"]  = df_1h["close"].rolling(99).mean()
            df_1h["MA200"] = df_1h["close"].rolling(200).mean()
            df_1h["h1_bull_2"] = (
                (df_1h["close"] > df_1h["MA7"]) & (df_1h["MA7"] > df_1h["MA25"])
            )
            df_1h["h1_bear_2"] = (
                (df_1h["close"] < df_1h["MA7"]) & (df_1h["MA7"] < df_1h["MA25"])
            )
            df_1h["h1_bull"] = (
                (df_1h["close"] > df_1h["MA7"]) &
                (df_1h["MA7"]   > df_1h["MA25"]) &
                (df_1h["MA25"]  > df_1h["MA99"])
            )
            df_1h["h1_bear"] = (
                (df_1h["close"] < df_1h["MA7"]) &
                (df_1h["MA7"]   < df_1h["MA25"]) &
                (df_1h["MA25"]  < df_1h["MA99"])
            )
            df_1h_m = df_1h[["open_time","h1_bull","h1_bear","h1_bull_2","h1_bear_2"]].copy()
            df["open_time_1h"] = df["open_time"].dt.floor("1h")
            df_1h_m["open_time"] = df_1h_m["open_time"].dt.floor("1h")
            df = df.merge(df_1h_m, left_on="open_time_1h", right_on="open_time",
                         how="left", suffixes=("","_1h"))
            df = df.drop(columns=["open_time_1h","open_time_1h_x","open_time_1h_y"], errors="ignore")
            df["_date"] = df["open_time"].dt.date
            for col in ["h1_bull","h1_bear","h1_bull_2","h1_bear_2"]:
                df[col] = df.groupby("_date")[col].transform(lambda x: x.ffill())
            df.drop(columns=["_date"], inplace=True)
            df["h1_bull"]   = df["h1_bull"].fillna(False)
            df["h1_bear"]   = df["h1_bear"].fillna(False)
            df["h1_bull_2"] = df["h1_bull_2"].fillna(False)
            df["h1_bear_2"] = df["h1_bear_2"].fillna(False)
        else:
            df["h1_bull"]   = df["bull_ma"]
            df["h1_bear"]   = df["bear_ma"]
            df["h1_bull_2"] = df["bull_ma_2"]
            df["h1_bear_2"] = df["bear_ma_2"]
    except:
        df["h1_bull"] = False
        df["h1_bear"] = False

    df["long_signal"]         = df["long_signal"]        & df["taker_buy_dom"]
    df["short_signal"]        = df["short_signal"]       & df["taker_sell_dom"]
    df["strong_long_signal"]  = df["strong_long_signal"]
    df["strong_short_signal"] = df["strong_short_signal"]
    df["short_caution_signal"]= df["short_caution_signal"]
    df["long_exhaustion_warn"] = False

    # 지표 계산은 충분한 history 로 했고, 차트 표시는 사용자가 지정한 candle_limit 만큼만.
    if len(df) > candle_limit:
        df = df.tail(candle_limit).reset_index(drop=True)
    t = df["open_time"]

    fig = make_subplots(
        rows=7, cols=1,
        shared_xaxes=True,
        row_heights=[0.38, 0.10, 0.10, 0.10, 0.10, 0.11, 0.11],
        vertical_spacing=0.01,
        subplot_titles=["", "Taker Buy/Sell Volume", "Open Interest",
                        "Funding Rate (%)", "Long/Short Ratio (탑트레이더)",
                        "RSI / StochRSI", "MACD"]
    )

    fig.add_trace(go.Candlestick(
        x=t, open=df["open"], high=df["high"], low=df["low"], close=df["close"],
        increasing_line_color=COLORS["green"], decreasing_line_color=COLORS["red"],
        increasing_fillcolor=COLORS["green"], decreasing_fillcolor=COLORS["red"],
        name="캔들", line=dict(width=1)
    ), row=1, col=1)

    fig.add_trace(go.Scatter(x=t, y=df["BB_upper"], line=dict(color=COLORS["BB"].replace("0.1","0.6"), width=0.8), name="BB상단", showlegend=False), row=1, col=1)
    fig.add_trace(go.Scatter(x=t, y=df["BB_lower"], line=dict(color=COLORS["BB"].replace("0.1","0.6"), width=0.8), fill="tonexty", fillcolor=COLORS["BB"], name="BB하단", showlegend=False), row=1, col=1)

    for ma, col in [("MA200", COLORS["MA200"]), ("MA99", COLORS["MA99"]), ("MA25", COLORS["MA25"]), ("MA7", COLORS["MA7"])]:
        fig.add_trace(go.Scatter(x=t, y=df[ma], line=dict(color=col, width=1.2), name=ma), row=1, col=1)

    if "longShortRatio" in df.columns:
        fig.add_trace(go.Scatter(x=t, y=df["longShortRatio"], line=dict(color=COLORS["orange"], width=1), name="탑트레이더 L/S"), row=1, col=1)

    if "fundingRate" in df.columns:
        fig.add_trace(go.Scatter(x=t, y=df["fundingRate"], line=dict(color=COLORS["purple"], width=1), name="Funding Rate"), row=1, col=1)

    if "sumOpenInterest" in df.columns:
        fig.add_trace(go.Scatter(x=t, y=df["sumOpenInterest"], line=dict(color=COLORS["blue"], width=1), name="OI"), row=1, col=1)

    fig.add_trace(go.Scatter(x=t, y=df["taker_sell_vol"], mode="markers", marker=dict(color=COLORS["red"], size=3), name="Taker Sell"), row=1, col=1)
    fig.add_trace(go.Scatter(x=t, y=df["taker_buy_vol"],  mode="markers", marker=dict(color=COLORS["green"], size=3), name="Taker Buy"), row=1, col=1)

    for mask, sym, color, sig_name in [
        (df["exhaustion_short"],   "star",           COLORS["red"],    "매수소진(숏)"),
        (df["exhaustion_long"],    "star",           COLORS["green"],  "매도소진(롱)"),
        (df.get("long_exhaustion_warn", pd.Series([False]*len(df), index=df.index)), "x", COLORS["orange"], "롱소진경고(숏전환)"),
        (df["strong_short_signal"],"triangle-down",  COLORS["red"],    "강한 숏 진입 신호"),
        (df.get("vol_short_signal", pd.Series([False]*len(df), index=df.index)), "triangle-down", COLORS["orange"], "볼륨급등 숏 신호"),
        (df.get("vol_long_signal", pd.Series([False]*len(df), index=df.index)), "triangle-up", "#00bfff", "볼륨급등 롱 신호"),
        (df["strong_long_signal"], "triangle-up",    COLORS["green"],  "강한 롱 진입 신호"),
        (df["short_signal"],       "triangle-down",  COLORS["orange"], "숏 진입 신호"),
        (df["long_signal"],        "triangle-up",    COLORS["blue"],   "롱 진입 신호"),
        (df.get("short_caution_signal", pd.Series([False]*len(df), index=df.index)), "diamond", "#ff00ff", "숏 진입(주의)"),
    ]:
        d = df[mask]
        if not d.empty:
            cd = list(zip(d["open_time"].dt.strftime("%m/%d %H:%M").tolist(), d["open"].tolist()))
            _long_sigs = ["강한 롱 진입 신호", "볼륨급등 롱 신호", "롱 진입 신호", "매도소진(롱)"]
            _short_sigs = ["강한 숏 진입 신호", "볼륨급등 숏 신호", "숏 진입 신호", "매수소진(숏)", "롱소진경고(숏전환)", "숏 진입(주의)"]
            if sig_name in _long_sigs:
                y_val = d["low"] * 0.9998
            elif sig_name in _short_sigs:
                y_val = d["high"] * 1.0002
            else:
                y_val = d["close"]
            fig.add_trace(go.Scatter(
                x=d["open_time"], y=y_val,
                mode="markers", marker=dict(symbol=sym, color=color, size=10),
                name=sig_name,
                customdata=cd,
                hovertemplate="<b>" + sig_name + "</b><br>신호: %{customdata[0]}<br>가격: %{customdata[1]:,.1f}<extra></extra>",
                showlegend=True,
            ), row=1, col=1)
        else:
            fig.add_trace(go.Scatter(
                x=[None], y=[None],
                mode="markers", marker=dict(symbol=sym, color=color, size=10),
                name=sig_name,
                showlegend=True,
            ), row=1, col=1)

    buy_vol  = df["taker_buy_vol"] - df["taker_sell_vol"]
    colors_v = [COLORS["green"] if v >= 0 else COLORS["red"] for v in buy_vol]
    fig.add_trace(go.Bar(x=t, y=buy_vol, marker_color=colors_v, name="Taker Net"), row=2, col=1)
    if "sumOpenInterest" not in df.columns:
        df["spike_avg"] = df["volume"].rolling(10).mean()
        fig.add_trace(go.Scatter(x=t, y=df["spike_avg"] * 3, line=dict(color=COLORS["yellow"], width=0.8, dash="dot"), name="스파이크 기준(3x)"), row=2, col=1)

    if "sumOpenInterest" in df.columns:
        fig.add_trace(go.Scatter(x=t, y=df["sumOpenInterest"], line=dict(color=COLORS["purple"], width=1.5), fill="tozeroy", fillcolor="rgba(156,39,176,0.15)", name="OI"), row=3, col=1)

    if "fundingRate" in df.columns:
        fr_colors = [COLORS["red"] if v < 0 else COLORS["green"] for v in df["fundingRate"]]
        fig.add_trace(go.Bar(x=t, y=df["fundingRate"], marker_color=fr_colors, name="FR"), row=4, col=1)
        fig.add_hline(y=0.005,  line=dict(color=COLORS["orange"], width=1, dash="dash"), row=4, col=1)
        fig.add_hline(y=-0.005, line=dict(color=COLORS["orange"], width=1, dash="dash"), row=4, col=1)
        fig.add_hline(y=-0.007, line=dict(color=COLORS["red"],    width=1, dash="dash"), row=4, col=1)

    if "longShortRatio" in df.columns:
        fig.add_trace(go.Scatter(x=t, y=df["longShortRatio"], line=dict(color=COLORS["orange"], width=1.5), name="탑트레이더 L/S"), row=5, col=1)
        fig.add_hline(y=1.0, line=dict(color=COLORS["grid"], width=0.8, dash="dash"), row=5, col=1)

    fig.add_trace(go.Scatter(x=t, y=df["RSI"],       line=dict(color=COLORS["blue"],   width=1.5), name="RSI(14)"), row=6, col=1)
    fig.add_trace(go.Scatter(x=t, y=df["StochRSI_k"],line=dict(color=COLORS["red"], width=1.5), name="StochRSI K"), row=6, col=1)
    fig.add_trace(go.Scatter(x=t, y=df["StochRSI_d"],line=dict(color=COLORS["orange"], width=1.0, dash="dot"), name="StochRSI D"), row=6, col=1)
    for lvl in [20, 50, 80]:
        fig.add_hline(y=lvl, line=dict(color=COLORS["grid"], width=0.6, dash="dash"), row=6, col=1)

    hist_colors = [COLORS["green"] if v >= 0 else COLORS["red"] for v in df["MACD_hist"].fillna(0)]
    fig.add_trace(go.Bar(x=t, y=df["MACD_hist"], marker_color=hist_colors, name="MACD Hist"), row=7, col=1)
    fig.add_trace(go.Scatter(x=t, y=df["MACD"],        line=dict(color=COLORS["blue"],   width=1.2), name="MACD"), row=7, col=1)
    fig.add_trace(go.Scatter(x=t, y=df["MACD_signal"], line=dict(color=COLORS["orange"], width=1.2), name="Signal"), row=7, col=1)
    fig.add_hline(y=0, line=dict(color=COLORS["grid"], width=0.5), row=7, col=1)

    last_price = df["close"].iloc[-1]
    fig.add_hline(y=last_price, line=dict(color=COLORS["yellow"], width=1, dash="dash"), row=1, col=1)
    fig.add_annotation(
        x=df["open_time"].iloc[-1], y=last_price,
        text=f"▶ {last_price:,.1f}",
        showarrow=False,
        font=dict(color=COLORS["yellow"], size=12),
        xanchor="left", yanchor="middle",
        bgcolor="rgba(245,206,5,0.15)",
        bordercolor=COLORS["yellow"], borderwidth=1,
        row=1, col=1
    )

    fig.update_layout(
        height=1600,
        paper_bgcolor="#ffffff",
        plot_bgcolor="#ffffff",
        font=dict(color=COLORS["text"], size=11,
                  family="'Noto Sans KR', 'Apple SD Gothic Neo', 'Malgun Gothic', sans-serif"),
        legend=dict(bgcolor="rgba(255,255,255,0.95)", bordercolor=COLORS["grid"], borderwidth=1,
                    orientation="h", x=0, y=1.02, yanchor="bottom", font=dict(size=10)),
        xaxis_rangeslider_visible=False,
        margin=dict(l=60, r=100, t=60, b=20),
        hovermode="x unified",
        dragmode="pan",
        showlegend=False,
    )

    for i in range(1, 8):
        fig.update_xaxes(showgrid=True, gridcolor=COLORS["grid"], zeroline=False, row=i, col=1,
                         showline=True, linecolor=COLORS["grid"])
        fig.update_yaxes(showgrid=True, gridcolor=COLORS["grid"], zeroline=False, row=i, col=1,
                         showline=True, linecolor=COLORS["grid"])

    def tight(series, pad=0.03):
        s = series.dropna()
        if s.empty: return None, None
        lo, hi = s.min(), s.max()
        margin = (hi - lo) * pad if (hi - lo) > 0 else abs(lo) * pad + 1
        return lo - margin, hi + margin

    lo, hi = tight(pd.concat([df["low"], df["high"]]), pad=0.02)
    if lo: fig.update_yaxes(range=[lo, hi], row=1, col=1)

    buy_vol = df["taker_buy_vol"] - df["taker_sell_vol"]
    abs_max = buy_vol.abs().quantile(0.98) * 1.5
    if abs_max > 0: fig.update_yaxes(range=[-abs_max, abs_max], row=2, col=1)

    if "sumOpenInterest" in df.columns:
        lo, hi = tight(df["sumOpenInterest"], pad=0.05)
        if lo: fig.update_yaxes(range=[lo, hi], row=3, col=1)

    if "fundingRate" in df.columns:
        lo, hi = tight(df["fundingRate"], pad=0.2)
        if lo: fig.update_yaxes(range=[lo, hi], row=4, col=1)

    if "longShortRatio" in df.columns:
        lo, hi = tight(df["longShortRatio"], pad=0.05)
        if lo: fig.update_yaxes(range=[lo, hi], row=5, col=1)

    fig.update_yaxes(range=[0, 100], row=6, col=1)

    macd_all = pd.concat([df["MACD"], df["MACD_signal"], df["MACD_hist"]]).dropna()
    lo, hi = tight(macd_all, pad=0.1)
    if lo: fig.update_yaxes(range=[lo, hi], row=7, col=1)

    return fig, df

# ──────────────────────────────────────────────
# 알림 스레드
# ──────────────────────────────────────────────
# 알림 스레드용 mutable state 는 alert_state 모듈에 보관 (위 import 참조).

def _build_signal_df(symbol, interval, klines_limit=200):
    df = get_klines(symbol, interval, klines_limit)
    oi_period = interval if interval in ["5m","15m","30m","1h","4h","12h","1d","3d","1M"] else "5m"
    try:
        oi = get_open_interest_history(symbol, oi_period, min(klines_limit, 500))
        if not oi.empty:
            oi_m = oi[["timestamp","sumOpenInterest"]].rename(columns={"timestamp":"open_time"})
            df["open_time_r"] = df["open_time"].dt.floor(_to_floor_freq(oi_period))
            oi_m["open_time"] = oi_m["open_time"].dt.floor(_to_floor_freq(oi_period))
            df = df.merge(oi_m, left_on="open_time_r", right_on="open_time", how="left", suffixes=("","_oi"))
            df = df.drop(columns=["open_time_r","open_time_oi"], errors="ignore")
            df["sumOpenInterest"] = df["sumOpenInterest"].ffill()
    except: pass
    try:
        fr = get_funding_rate(symbol, 200)
        if not fr.empty:
            fr_m = fr[["fundingTime","fundingRate"]].rename(columns={"fundingTime":"open_time"})
            fr_m["open_time"] = fr_m["open_time"].dt.floor(_to_floor_freq("1h"))
            df["open_time_r2"] = df["open_time"].dt.floor(_to_floor_freq("1h"))
            df = df.merge(fr_m, left_on="open_time_r2", right_on="open_time", how="left", suffixes=("","_fr"))
            df = df.drop(columns=["open_time_r2","open_time_fr"], errors="ignore")
            df["fundingRate"] = df["fundingRate"].ffill().fillna(0)
    except: pass
    df = compute_indicators(df, interval)
    return df

def _alert_timeframes():
    return settings_db.get_list("alert_timeframes", default=["5m", "15m", "30m", "1h"])

def _alert_loop():
    while True:
        poll = max(10, settings_db.get_int("polling_interval_sec", 30))
        if not settings_db.get_bool("alert_enabled", True):
            time.sleep(poll)
            continue
        with alert_state.alert_lock:
            symbol = alert_state.alert_symbol
        for interval in _alert_timeframes():
            try:
                df = _build_signal_df(symbol, interval, 200)
                check_and_alert(df, symbol, interval)
            except Exception as e:
                print(f"[알림스레드 오류] {interval}: {e}")
        time.sleep(poll)

# ──────────────────────────────────────────────
# 일일 리포트 (자정 KST)
# ──────────────────────────────────────────────
DAILY_REPORT_TIMEFRAMES = ["5m", "15m", "30m", "1h", "4h"]
DAILY_REPORT_KLINES_LIMIT = {"5m": 500, "15m": 250, "30m": 200, "1h": 200, "4h": 200}
DAILY_REPORT_PAIRS = [
    ("strong_long_signal",  "strong_short_signal"),
    ("long_signal",         "short_signal"),
    ("vol_long_signal",     "vol_short_signal"),
]
DAILY_REPORT_SIGNAL_LABELS = [
    ("strong_long_signal",  "강한 롱"),
    ("strong_short_signal", "강한 숏"),
    ("long_signal",         "일반 롱"),
    ("short_signal",        "일반 숏"),
    ("vol_long_signal",     "볼륨 롱"),
    ("vol_short_signal",    "볼륨 숏"),
]

def _count_daily_signals_per_type(df, cutoff_kst, offset=1):
    result = {sig: [0, 0] for sig, _ in DAILY_REPORT_SIGNAL_LABELS}
    if df is None or df.empty or "open_time" not in df.columns:
        return result
    recent = df[df["open_time"] >= cutoff_kst].reset_index(drop=True)
    if len(recent) <= offset:
        return result
    for long_sig, short_sig in DAILY_REPORT_PAIRS:
        if long_sig not in recent.columns or short_sig not in recent.columns:
            continue
        for i in range(len(recent) - offset):
            row = recent.iloc[i]
            future = recent.iloc[i + offset]
            if bool(row.get(long_sig, False)):
                result[long_sig][0] += 1
                if bool(future.get(short_sig, False)):
                    result[long_sig][1] += 1
            if bool(row.get(short_sig, False)):
                result[short_sig][0] += 1
                if bool(future.get(long_sig, False)):
                    result[short_sig][1] += 1
    return result

def _build_daily_report_lines(dfs, cutoff_kst, now_kst, symbol, offset, header_suffix):
    lines = [
        f"📊 24시간 신호 통계 ({symbol}) - {header_suffix}",
        f"기준: {now_kst.strftime('%Y-%m-%d %H:%M')} KST",
    ]
    for tf in DAILY_REPORT_TIMEFRAMES:
        df = dfs.get(tf)
        counts = _count_daily_signals_per_type(df, cutoff_kst, offset=offset)
        lines.append("")
        lines.append(f"[{TF_LABEL_MAP.get(tf, tf)}]")
        total_all = 0
        failed_all = 0
        for sig, sig_label in DAILY_REPORT_SIGNAL_LABELS:
            t, f = counts.get(sig, [0, 0])
            passed = t - f
            lines.append(f"{sig_label}: {passed}T {f}F")
            total_all += t
            failed_all += f
        passed_all = total_all - failed_all
        rate = (passed_all / total_all * 100) if total_all > 0 else 0.0
        lines.append(f"합계: {passed_all}T {failed_all}F (승률 {rate:.2f}%)")
    return "\n".join(lines)

def _count_stop_touches_per_type(df, cutoff_kst, lookahead=3):
    """
    각 진입 신호 캔들 (1번째 캔들) 기준으로 그 후 lookahead 개 캔들 동안
    (즉 1번째 캔들 시작가 ~ (lookahead+1) 번째 캔들 시작가 구간) 손절가를
    터치했는지 카운트. 롱은 low <= stop, 숏은 high >= stop.

    반환: {signal_name: [touch_count, total_count]}
    """
    result = {sig: [0, 0] for sig, _ in DAILY_REPORT_SIGNAL_LABELS}
    if df is None or df.empty or "open_time" not in df.columns:
        return result
    recent = df[df["open_time"] >= cutoff_kst].reset_index(drop=True)
    if len(recent) <= lookahead:
        return result
    for sig, _ in DAILY_REPORT_SIGNAL_LABELS:
        if sig not in recent.columns:
            continue
        if sig in LONG_SIGNALS:
            direction = "long"
        elif sig in SHORT_SIGNALS:
            direction = "short"
        else:
            continue  # short_caution_signal — 진입 신호 아님, 손절가 추적 X
        for i in range(len(recent) - lookahead):
            row = recent.iloc[i]
            if not bool(row.get(sig, False)):
                continue
            entry = float(row["open"])
            window = recent.iloc[i:i + lookahead]
            result[sig][1] += 1
            if direction == "long":
                stop = entry * (1 - STOP_LOSS_PCT)
                if float(window["low"].min()) <= stop:
                    result[sig][0] += 1
            else:
                stop = entry * (1 + STOP_LOSS_PCT)
                if float(window["high"].max()) >= stop:
                    result[sig][0] += 1
    return result

def _build_stop_touch_lines(dfs, cutoff_kst, now_kst, symbol):
    lines = [
        f"[손절가 터치 횟수 알림(시간봉 *3배기준)] ({symbol})",
        f"기준: {now_kst.strftime('%Y-%m-%d %H:%M')} KST",
        f"손절 비율: ±{STOP_LOSS_PCT*100:.2f}% (10x 레버리지 기준 ROI ±{STOP_LOSS_PCT*100*10:.1f}%)",
    ]
    for tf in DAILY_REPORT_TIMEFRAMES:
        df = dfs.get(tf)
        counts = _count_stop_touches_per_type(df, cutoff_kst, lookahead=3)
        lines.append("")
        lines.append(f"[{TF_LABEL_MAP.get(tf, tf)}]")
        touch_all = 0
        total_all = 0
        for sig, sig_label in DAILY_REPORT_SIGNAL_LABELS:
            if sig == "short_caution_signal":
                continue
            touch, total = counts.get(sig, [0, 0])
            lines.append(f"{sig_label}: {touch}/{total}")
            touch_all += touch
            total_all += total
        rate = (touch_all / total_all * 100) if total_all > 0 else 0.0
        lines.append(f"합계: {touch_all}/{total_all} (터치율 {rate:.2f}%)")
    return "\n".join(lines)

def _count_reversal_outcomes(df, cutoff_kst, lookahead=3):
    """추세 꺾임 신호의 lookahead 봉 후 방향 일치 카운트.
    - reversal_long: close[i+lookahead] > close[i] -> T (상승 지속)
    - reversal_short: close[i+lookahead] < close[i] -> T (하락 지속)
    반환: {sig_name: [total, failed]}
    """
    result = {"reversal_long_signal": [0, 0], "reversal_short_signal": [0, 0]}
    if df is None or df.empty or "open_time" not in df.columns:
        return result
    recent = df[df["open_time"] >= cutoff_kst].reset_index(drop=True)
    if len(recent) <= lookahead:
        return result
    for sig in ("reversal_long_signal", "reversal_short_signal"):
        if sig not in recent.columns:
            continue
        for i in range(len(recent) - lookahead):
            row = recent.iloc[i]
            if not bool(row.get(sig, False)):
                continue
            future = recent.iloc[i + lookahead]
            entry_close = float(row["close"])
            future_close = float(future["close"])
            confirmed = (sig == "reversal_long_signal" and future_close > entry_close) or \
                        (sig == "reversal_short_signal" and future_close < entry_close)
            result[sig][0] += 1
            if not confirmed:
                result[sig][1] += 1
    return result

def _build_reversal_lines(dfs, cutoff_kst, now_kst, symbol):
    lines = [
        f"📊 추세 꺾임 감지 통계 ({symbol})",
        f"기준: {now_kst.strftime('%Y-%m-%d %H:%M')} KST  (3봉 후 방향 일치)",
    ]
    for tf in DAILY_REPORT_TIMEFRAMES:
        df = dfs.get(tf)
        counts = _count_reversal_outcomes(df, cutoff_kst, lookahead=3)
        lines.append("")
        lines.append(f"[{TF_LABEL_MAP.get(tf, tf)}]")
        total_all = 0
        failed_all = 0
        for sig, lbl in [("reversal_long_signal", "🔄 롱 추세 꺾임 감지"),
                         ("reversal_short_signal", "🔄 숏 추세 꺾임 감지")]:
            t, f = counts[sig]
            passed = t - f
            lines.append(f"{lbl}: {passed}T {f}F")
            total_all += t
            failed_all += f
        passed_all = total_all - failed_all
        rate = (passed_all / total_all * 100) if total_all > 0 else 0.0
        lines.append(f"합계: {passed_all}T {failed_all}F (승률 {rate:.2f}%)")
    return "\n".join(lines)

def send_daily_report(symbol="BTCUSDT"):
    now_kst = (datetime.now(timezone.utc) + KST).replace(tzinfo=None)
    cutoff_kst = now_kst - timedelta(hours=24)
    dfs = {}
    for tf in DAILY_REPORT_TIMEFRAMES:
        try:
            dfs[tf] = _build_signal_df(symbol, tf, DAILY_REPORT_KLINES_LIMIT[tf])
        except Exception as e:
            print(f"[일일리포트 {tf} 데이터 오류] {e}")
            dfs[tf] = None
    msg_1x = _build_daily_report_lines(dfs, cutoff_kst, now_kst, symbol, offset=1, header_suffix="1배 시간 (다음 봉 검증)")
    send_telegram(msg_1x)
    msg_2x = _build_daily_report_lines(dfs, cutoff_kst, now_kst, symbol, offset=2, header_suffix="2배 시간 (2번째 봉 검증)")
    send_telegram(msg_2x)
    msg_touch = _build_stop_touch_lines(dfs, cutoff_kst, now_kst, symbol)
    send_telegram(msg_touch)
    msg_rev = _build_reversal_lines(dfs, cutoff_kst, now_kst, symbol)
    send_telegram(msg_rev)

def _daily_report_loop():
    while True:
        try:
            if not settings_db.get_bool("daily_report_enabled", True):
                time.sleep(60)
                continue
            now_kst = (datetime.now(timezone.utc) + KST).replace(tzinfo=None)
            today_str = now_kst.strftime("%Y-%m-%d")
            if alert_state.last_report_date is None:
                alert_state.last_report_date = today_str
                print(f"[일일리포트] 스레드 기동 -- 다음 자정({today_str} 24:00 KST) 까지 대기")
            elif alert_state.last_report_date != today_str:
                print(f"[일일리포트] 자정 통과 감지 -> 발송 ({today_str})")
                with alert_state.alert_lock:
                    symbol = alert_state.alert_symbol
                send_daily_report(symbol)
                alert_state.last_report_date = today_str
        except Exception as e:
            print(f"[일일리포트 스레드 오류] {e}")
        time.sleep(60)

# ──────────────────────────────────────────────
# 메인 UI
# ──────────────────────────────────────────────
def render_login_page():
    """로그인 화면 — 중앙 정렬 카드 (fito 스타일)."""
    st.markdown("""
    <style>
        [data-testid="stSidebar"] { display: none !important; }
        [data-testid="stSidebarCollapseButton"],
        [data-testid="stSidebarCollapsed"] { display: none !important; }
        [data-testid="stAppViewContainer"] {
            background: linear-gradient(135deg, #0f172a 0%, #1e293b 50%, #334155 100%) !important;
        }
        [data-testid="stAppViewContainer"] section.main {
            margin-left: 0 !important;
            display: flex; align-items: center; justify-content: center;
            min-height: 100vh;
        }
        .login-card {
            background: #ffffff;
            border-radius: 14px;
            padding: 40px 36px 30px 36px;
            box-shadow: 0 20px 50px rgba(0,0,0,0.3);
            width: 380px;
            margin: 0 auto;
        }
        .login-card .logo-wrap {
            display: flex; justify-content: center; margin-bottom: 24px;
        }
        .login-card h1 {
            font-size: 18px; font-weight: 700; color: #111827;
            text-align: center; margin: 0 0 4px 0;
        }
        .login-card .subtitle {
            font-size: 12px; color: #6b7280;
            text-align: center; margin-bottom: 24px;
        }
    </style>
    """, unsafe_allow_html=True)

    col1, col2, col3 = st.columns([1, 2, 1])
    with col2:
        st.markdown('<div class="login-card">', unsafe_allow_html=True)
        st.markdown(f'<div class="logo-wrap">{load_logo_svg()}</div>', unsafe_allow_html=True)
        st.markdown('<h1>업무관리 시스템</h1>', unsafe_allow_html=True)
        st.markdown('<div class="subtitle">로그인하여 시작하세요</div>', unsafe_allow_html=True)

        with st.form("login_form", clear_on_submit=False):
            username = st.text_input("아이디", placeholder="username", key="login_user")
            password = st.text_input("비밀번호", type="password", placeholder="password", key="login_pw")
            submitted = st.form_submit_button("로그인", use_container_width=True, type="primary")
            if submitted:
                user = users_db.authenticate(username.strip(), password)
                if user:
                    st.session_state.user = user
                    st.rerun()
                else:
                    st.error("아이디 또는 비밀번호가 올바르지 않습니다.")
        st.markdown('</div>', unsafe_allow_html=True)


def render_my_info_page():
    st.markdown(
        '<div style="display:flex; align-items:flex-end; justify-content:space-between; '
        'padding:0 0 8px 0; border-bottom:1px solid #e5e7eb; margin-bottom:14px;">'
        '<div style="font-size:20px; font-weight:800; color:#111827;">👤 개인정보 수정</div>'
        '<div style="font-size:11px; color:#6b7280;">비밀번호 변경</div>'
        '</div>',
        unsafe_allow_html=True,
    )

    user = st.session_state.get("user", {})
    col_l, col_r = st.columns([2, 1], gap="medium")

    with col_l:
        with st.container(border=True):
            st.markdown("###### 계정 정보")
            cc1, cc2 = st.columns(2)
            with cc1:
                st.text_input("아이디", value=user.get("username", ""), disabled=True)
            with cc2:
                st.text_input("권한", value=user.get("role", ""), disabled=True)
            st.caption(f"가입: {user.get('created_at', '-')} · 마지막 로그인: {user.get('last_login_at', '-')}")

        with st.container(border=True):
            st.markdown("###### 비밀번호 변경")
            with st.form("change_pw_form", clear_on_submit=True):
                old_pw = st.text_input("현재 비밀번호", type="password")
                new_pw = st.text_input("새 비밀번호 (6자 이상)", type="password")
                new_pw2 = st.text_input("새 비밀번호 확인", type="password")
                submitted = st.form_submit_button("비밀번호 변경", type="primary",
                                                    use_container_width=True)
                if submitted:
                    if new_pw != new_pw2:
                        st.error("새 비밀번호가 일치하지 않습니다.")
                    elif len(new_pw) < 6:
                        st.error("새 비밀번호는 6자 이상이어야 합니다.")
                    elif users_db.change_password(user.get("username", ""), old_pw, new_pw):
                        st.success("✅ 비밀번호 변경 완료. 다음 로그인부터 새 비밀번호 사용.")
                    else:
                        st.error("현재 비밀번호가 올바르지 않습니다.")

    with col_r:
        with st.container(border=True):
            st.markdown("###### 등록된 사용자")
            users = users_db.list_users()
            if users:
                df_u = pd.DataFrame(users)[["username", "role", "last_login_at"]]
                st.dataframe(df_u, use_container_width=True, hide_index=True)
            else:
                st.info("사용자 목록을 불러오지 못함.")


def render_sidebar() -> str:
    """fito 스타일 다크 사이드바.
    - full 모드: 240px, 헤더 + 아이콘+텍스트 메뉴 + 푸터
    - mini 모드: 60px, 햄버거 + 정사각형 아이콘 버튼 (텍스트 없음, hover tooltip)
    - Streamlit 기본 collapse 버튼은 숨김 (혼란 방지)
    """
    try:
        from streamlit_option_menu import option_menu
        HAS_OPTION_MENU = True
    except ImportError:
        HAS_OPTION_MENU = False

    if "sidebar_mini" not in st.session_state:
        st.session_state.sidebar_mini = False
    if "current_page" not in st.session_state:
        st.session_state.current_page = "dashboard"

    mini = st.session_state.sidebar_mini
    sidebar_width = "64px" if mini else "260px"

    st.markdown(f"""
    <style>
        /* Streamlit 1.57 sidebar collapse 토글 완전 무력화 — 우리 햄버거만 사용 */
        [data-testid="stSidebarCollapseButton"],
        [data-testid="stSidebarCollapsed"],
        [data-testid="collapsedControl"],
        button[kind="header"],
        button[data-testid="baseButton-header"] {{ display: none !important; }}

        /* 사이드바 — 모든 viewport 강제 표시 + 너비 고정 (mini/full) */
        [data-testid="stSidebar"] {{
            background-color: #1f2937 !important;
            width: {sidebar_width} !important;
            min-width: {sidebar_width} !important;
            max-width: {sidebar_width} !important;
            transform: none !important;
            visibility: visible !important;
            margin-left: 0 !important;
            transition: width 0.2s ease;
            position: relative !important;
        }}
        [data-testid="stSidebarContent"],
        [data-testid="stSidebar"] > div:first-child {{
            background-color: #1f2937 !important;
            padding: 0 !important;
            width: {sidebar_width} !important;
        }}
        [data-testid="stSidebar"] section {{ padding-top: 0 !important; }}
        [data-testid="stSidebar"] * {{ color: #e5e7eb !important; }}

        @media (max-width: 767px) {{
            [data-testid="stAppViewContainer"] > section.main {{ margin-left: 0 !important; }}
        }}

        /* 헤더 영역 — full mode */
        .sb-header-full {{
            display: flex; align-items: center; justify-content: space-between;
            padding: 14px 12px 12px 16px;
            border-bottom: 1px solid #374151;
        }}
        .sb-header-full .brand {{
            color: #60a5fa !important; font-weight: 800; font-size: 18px; letter-spacing: 1px;
            line-height: 1.1;
        }}
        .sb-header-full .subtitle {{
            color: #9ca3af !important; font-size: 11px; margin-top: 2px;
        }}
        /* 헤더 — mini mode (햄버거만) */
        .sb-header-mini {{
            display: flex; justify-content: center; align-items: center;
            padding: 14px 0 12px 0;
            border-bottom: 1px solid #374151;
        }}

        /* 토글 버튼 — 사이드바 안 stButton 스타일 */
        [data-testid="stSidebar"] .stButton > button {{
            background: transparent !important;
            border: none !important;
            color: #9ca3af !important;
            font-size: 18px !important;
            padding: 6px !important;
            min-height: 36px !important;
            border-radius: 6px !important;
        }}
        [data-testid="stSidebar"] .stButton > button:hover {{
            background: #374151 !important;
            color: #ffffff !important;
        }}

        /* mini mode 아이콘 버튼 정사각형 */
        [data-testid="stSidebar"] .stButton > button p {{
            font-size: 22px !important; line-height: 1 !important; margin: 0 !important;
        }}
        .mini-active > div > button {{
            background: #2563eb !important;
            color: #ffffff !important;
        }}
        .mini-active > div > button p {{
            color: #ffffff !important;
        }}

        /* 푸터 */
        .sb-footer {{
            padding: 10px 16px; border-top: 1px solid #374151;
            font-size: 11px; color: #6b7280 !important; margin-top: 14px;
        }}
    </style>
    """, unsafe_allow_html=True)

    labels = ["대시보드", "트레이드 이력", "거래소 API", "자동매매", "시스템 설정", "내 정보"]
    keys = ["dashboard", "trades", "exchange_keys", "automation", "settings", "my_info"]
    bs_icons = ["bar-chart-line", "graph-up-arrow", "key", "robot", "gear", "person-circle"]
    emoji_icons = ["📊", "📈", "🔑", "🤖", "⚙️", "👤"]

    with st.sidebar:
        if mini:
            # ── mini 헤더: 햄버거 토글만 (가운데) ──
            st.markdown('<div class="sb-header-mini"></div>', unsafe_allow_html=True)
            if st.button("☰", key="sidebar_toggle_mini",
                          use_container_width=True, help="메뉴 펼치기"):
                st.session_state.sidebar_mini = False
                st.rerun()

            # ── mini 메뉴: 정사각형 아이콘 버튼 (텍스트 없음, hover tooltip) ──
            for label, key, emoji in zip(labels, keys, emoji_icons):
                active = (st.session_state.current_page == key)
                if active:
                    st.markdown('<div class="mini-active">', unsafe_allow_html=True)
                if st.button(emoji, key=f"mini_{key}",
                              use_container_width=True, help=label):
                    st.session_state.current_page = key
                    st.rerun()
                if active:
                    st.markdown('</div>', unsafe_allow_html=True)

        else:
            # ── full 헤더: SVG 로고 (좌) + 햄버거 (우) ──
            head_col1, head_col2 = st.columns([5, 1], gap="small")
            with head_col1:
                logo_svg = load_logo_svg()
                if logo_svg:
                    st.markdown(
                        f'<div style="padding:8px 0 0 6px;">{logo_svg}</div>',
                        unsafe_allow_html=True,
                    )
                else:
                    st.markdown(
                        '<div style="padding:8px 0 0 6px;">'
                        '<div style="color:#60a5fa; font-weight:800; font-size:18px;">JUNGGOMOA</div>'
                        '<div style="color:#9ca3af; font-size:11px;">트레이딩 시스템</div>'
                        '</div>',
                        unsafe_allow_html=True,
                    )
            with head_col2:
                st.markdown('<div style="padding-top:8px;"></div>', unsafe_allow_html=True)
                if st.button("☰", key="sidebar_toggle_full", help="메뉴 접기"):
                    st.session_state.sidebar_mini = True
                    st.rerun()
            st.markdown('<hr style="border:none; border-top:1px solid #374151; margin:6px 0 4px 0;"/>',
                          unsafe_allow_html=True)

            # ── full 메뉴 ──
            if HAS_OPTION_MENU:
                try:
                    default_idx = keys.index(st.session_state.current_page)
                except ValueError:
                    default_idx = 0
                choice = option_menu(
                    menu_title=None,
                    options=labels,
                    icons=bs_icons,
                    default_index=default_idx,
                    key="full_menu",
                    styles={
                        "container": {"padding": "0", "background-color": "#1f2937"},
                        "icon": {"color": "#60a5fa", "font-size": "16px"},
                        "nav-link": {
                            "color": "#e5e7eb",
                            "font-size": "14px",
                            "text-align": "left",
                            "margin": "2px 6px",
                            "padding": "10px 12px",
                            "border-radius": "6px",
                            "--hover-color": "#374151",
                            "font-family": "'Noto Sans KR', sans-serif",
                        },
                        "nav-link-selected": {
                            "background-color": "#2563eb",
                            "color": "#ffffff",
                            "font-weight": "600",
                        },
                    },
                )
                st.session_state.current_page = keys[labels.index(choice)] if choice in labels else "dashboard"
            else:
                try:
                    idx = keys.index(st.session_state.current_page)
                except ValueError:
                    idx = 0
                choice = st.radio("menu", labels, index=idx, label_visibility="collapsed")
                st.session_state.current_page = keys[labels.index(choice)]

            # ── 푸터: 아바타 + username + 로그아웃 ──
            user = st.session_state.get("user", {})
            uname = user.get("username", "guest")
            initial = uname[0].upper() if uname else "?"
            st.markdown(
                f'<div style="margin-top:18px; padding:12px 14px; border-top:1px solid #374151; '
                f'display:flex; align-items:center; gap:10px;">'
                f'  <div style="width:30px; height:30px; border-radius:50%; '
                f'              background:linear-gradient(135deg, #3b82f6, #60a5fa); '
                f'              display:flex; align-items:center; justify-content:center; '
                f'              color:white; font-weight:700; font-size:13px;">{initial}</div>'
                f'  <div style="flex:1; min-width:0;">'
                f'    <div style="font-size:12px; color:#e5e7eb; font-weight:600; '
                f'                white-space:nowrap; overflow:hidden; text-overflow:ellipsis;">{uname}</div>'
                f'    <div style="font-size:10px; color:#9ca3af;">{user.get("role", "user")}</div>'
                f'  </div>'
                f'</div>',
                unsafe_allow_html=True,
            )
            if st.button("로그아웃", key="sidebar_logout", use_container_width=True):
                st.session_state.pop("user", None)
                st.session_state.current_page = "dashboard"
                st.rerun()

    return st.session_state.current_page


def render_trades_page():
    st.markdown("## 📈 트레이드 이력")
    st.caption("DB 에 기록된 진입 → 청산 lifecycle. 손절(stop_loss) / 반대신호(reversal) / 취소(cancelled) 별로 분석.")

    if not trades_db._enabled():
        st.warning("DATABASE_URL 미설정. PostgreSQL 컨테이너가 떠있어야 트레이드 이력이 기록됩니다.")
        st.code("docker compose up -d postgres", language="bash")
        return

    rows = trades_db.fetch_trades(limit=500)
    if not rows:
        st.info("아직 기록된 트레이드 없음. 진입 신호가 발사되면 자동으로 누적됩니다.")
        return

    df = pd.DataFrame(rows)
    # 정렬 / 표시 컬럼 정리
    display_cols = ["entry_time", "symbol", "interval", "direction", "signal_types",
                    "entry_price", "stop_price", "status", "exit_time", "exit_price",
                    "exit_reason", "pnl_pct"]
    display_cols = [c for c in display_cols if c in df.columns]
    df_disp = df[display_cols].copy()

    # ── 요약 메트릭 ──
    closed = df[df["status"].isin(["stop_loss", "reversal", "cancelled"])]
    open_count = int((df["status"] == "open").sum())
    total = len(df)
    if len(closed) > 0:
        wins = int((closed["pnl_pct"] > 0).sum())
        losses = int((closed["pnl_pct"] <= 0).sum())
        win_rate = wins / len(closed) * 100
        avg_pnl = float(closed["pnl_pct"].mean())
        cum_pnl = float(closed["pnl_pct"].sum())
    else:
        wins = losses = 0
        win_rate = avg_pnl = cum_pnl = 0.0

    m1, m2, m3, m4, m5, m6 = st.columns(6)
    m1.metric("총 트레이드", total)
    m2.metric("진행 중", open_count)
    m3.metric("종료", len(closed))
    m4.metric("승률", f"{win_rate:.1f}%", f"{wins}W / {losses}L")
    m5.metric("평균 PnL%", f"{avg_pnl:+.2f}%")
    m6.metric("누적 PnL%", f"{cum_pnl:+.2f}%")

    st.markdown("---")

    # ── 누적 PnL 차트 ──
    if len(closed) > 0:
        c2 = closed.sort_values("exit_time").copy()
        c2["cum_pnl"] = c2["pnl_pct"].cumsum()
        fig = go.Figure()
        fig.add_trace(go.Scatter(x=c2["exit_time"], y=c2["cum_pnl"],
                                  mode="lines+markers",
                                  line=dict(color="#2962ff", width=2),
                                  marker=dict(
                                      color=["#26a69a" if v > 0 else "#ef5350" for v in c2["pnl_pct"]],
                                      size=6),
                                  name="누적 PnL%"))
        fig.add_hline(y=0, line=dict(color="#888", width=0.6, dash="dash"))
        fig.update_layout(
            height=320,
            paper_bgcolor="#ffffff", plot_bgcolor="#ffffff",
            font=dict(color="#131722", size=11,
                      family="'Noto Sans KR', 'Apple SD Gothic Neo', 'Malgun Gothic', sans-serif"),
            margin=dict(l=40, r=20, t=30, b=30),
            xaxis_title="청산 시각", yaxis_title="누적 PnL %",
        )
        st.plotly_chart(fig, use_container_width=True)

        # ── 시간축 / 신호별 승률 ──
        c3, c4 = st.columns(2)
        with c3:
            st.markdown("##### 시간축별 승률")
            by_iv = closed.groupby("interval").agg(
                n=("pnl_pct", "size"),
                wins=("pnl_pct", lambda s: int((s > 0).sum())),
                avg_pnl=("pnl_pct", "mean"),
                sum_pnl=("pnl_pct", "sum"),
            ).reset_index()
            by_iv["win_rate%"] = (by_iv["wins"] / by_iv["n"] * 100).round(1)
            st.dataframe(by_iv, use_container_width=True, hide_index=True)
        with c4:
            st.markdown("##### 청산 사유별 분포")
            by_reason = closed.groupby("exit_reason").agg(
                n=("pnl_pct", "size"),
                avg_pnl=("pnl_pct", "mean"),
                sum_pnl=("pnl_pct", "sum"),
            ).reset_index()
            st.dataframe(by_reason, use_container_width=True, hide_index=True)

        # ── 시간축별 PnL 막대 ──
        st.markdown("##### 시간축 × 방향별 누적 PnL%")
        bar = closed.groupby(["interval", "direction"])["pnl_pct"].sum().reset_index()
        fig2 = go.Figure()
        for d, color in [("long", "#26a69a"), ("short", "#ef5350")]:
            sub = bar[bar["direction"] == d]
            fig2.add_trace(go.Bar(x=sub["interval"], y=sub["pnl_pct"],
                                    name=d, marker_color=color))
        fig2.update_layout(
            barmode="group", height=300,
            paper_bgcolor="#ffffff", plot_bgcolor="#ffffff",
            font=dict(color="#131722", size=11,
                      family="'Noto Sans KR', 'Apple SD Gothic Neo', 'Malgun Gothic', sans-serif"),
            margin=dict(l=40, r=20, t=10, b=30),
            yaxis_title="누적 PnL %",
        )
        st.plotly_chart(fig2, use_container_width=True)

    st.markdown("---")
    st.markdown("### 🧾 최근 트레이드 (최대 500건)")
    st.dataframe(df_disp, use_container_width=True, hide_index=True)


def _section_header(emoji: str, title: str, subtitle: str = ""):
    sub = f' <span style="color:#9ca3af; font-size:12px; font-weight:400; margin-left:6px;">{subtitle}</span>' if subtitle else ""
    st.markdown(
        f'<div style="display:flex; align-items:center; margin:-4px 0 10px 0;">'
        f'<div style="font-size:15px; font-weight:700; color:#1f2937;">{emoji} {title}</div>'
        f'{sub}'
        f'</div>',
        unsafe_allow_html=True,
    )


def render_settings_page():
    # 페이지 헤더 — 컴팩트 (한 줄)
    st.markdown(
        '<div style="display:flex; align-items:flex-end; justify-content:space-between; '
        'padding:0 0 8px 0; border-bottom:1px solid #e5e7eb; margin-bottom:10px;">'
        '<div style="font-size:20px; font-weight:800; color:#111827;">⚙️ 시스템 설정</div>'
        '<div style="font-size:11px; color:#6b7280;">DB 영속 저장 · 저장 즉시 반영</div>'
        '</div>',
        unsafe_allow_html=True,
    )

    cur = settings_db.all_settings()

    with st.form("settings_form", clear_on_submit=False):
        # 5개 탭으로 분리 — 한 번에 한 섹션만 보여 한 화면(1080) fit
        tab_tg, tab_alert, tab_signal, tab_vol, tab_chart = st.tabs(
            ["📨 텔레그램", "🔔 알림 / 모니터링", "🎯 신호 임계값", "💧 거래량 / 펀딩비", "📊 차트"]
        )

        # ── 텔레그램 ──
        with tab_tg:
            st.markdown("###### Telegram Bot 설정")
            col_a, col_b = st.columns(2)
            with col_a:
                # type=password 제거 — 사용자 요청대로 plain text 로 보이게
                token = st.text_input("Bot Token", value=cur.get("telegram_token", ""),
                                        placeholder="예: 1234567890:ABCDEF...")
            with col_b:
                chat_id = st.text_input("Chat ID", value=cur.get("telegram_chat_id", ""),
                                          placeholder="예: -1001234567890 또는 본인 user id")
            st.caption("⚠️ Token 은 plain text 로 표시됩니다 (DB 저장 후엔 다시 보임). 노출 주의.")

        # ── 알림 / 모니터링 ──
        with tab_alert:
            col_c, col_d = st.columns(2)
            with col_c:
                symbol_default = cur.get("alert_symbol", "BTCUSDT")
                symbol_options = ["BTCUSDT", "ETHUSDT", "SOLUSDT", "BNBUSDT"]
                if symbol_default not in symbol_options:
                    symbol_options.insert(0, symbol_default)
                symbol = st.selectbox("모니터링 심볼", symbol_options,
                                        index=symbol_options.index(symbol_default))
            with col_d:
                tf_options = ["1m", "3m", "5m", "15m", "30m", "1h", "4h"]
                tf_current = [t for t in cur.get("alert_timeframes", "5m,15m,30m,1h").split(",") if t.strip()]
                tf_selected = st.multiselect("알림 시간축", tf_options, default=tf_current)
            col_e, col_f, col_g, col_j = st.columns(4)
            with col_e:
                cooldown = st.number_input("쿨다운(초)", 30, 3600,
                                            int(cur.get("alert_cooldown_sec", "600") or 600))
            with col_f:
                sl_pct_pct = st.number_input("손절(%)", 0.05, 5.0,
                                              float(cur.get("stop_loss_pct", "0.0075") or 0.0075) * 100, step=0.05)
            with col_g:
                poll_sec = st.number_input("폴링(초)", 10, 300,
                                            int(cur.get("polling_interval_sec", "30") or 30))
            with col_j:
                forming_polls = st.number_input("forming polls", 1, 10,
                                                  int(cur.get("forming_stable_polls", "2") or 2))
            col_h, col_i = st.columns(2)
            with col_h:
                alert_enabled = st.checkbox("✅ 알림 활성화", value=cur.get("alert_enabled", "1") == "1")
            with col_i:
                daily_enabled = st.checkbox("📅 일일 리포트 활성화", value=cur.get("daily_report_enabled", "1") == "1")

        # ── 신호 임계값 ──
        with tab_signal:
            st.markdown("###### RSI 임계값")
            c1, c2, c3, c4 = st.columns(4)
            with c1:
                long_rsi_max = st.number_input("일반 롱 RSI ≤", 30.0, 100.0,
                                                 float(cur.get("long_rsi_max", "75")))
            with c2:
                short_rsi_min = st.number_input("일반 숏 RSI ≥", 0.0, 70.0,
                                                  float(cur.get("short_rsi_min", "25")))
            with c3:
                slong_rsi_max = st.number_input("강한 롱 RSI ≤", 30.0, 100.0,
                                                  float(cur.get("strong_long_rsi_max", "65")))
            with c4:
                sshort_rsi_min = st.number_input("강한 숏 RSI ≥", 0.0, 70.0,
                                                   float(cur.get("strong_short_rsi_min", "35")))
            st.markdown("###### 캔들 body / 추세 꺾임")
            c5, c6, c7 = st.columns(3)
            with c5:
                body_pct_min = st.number_input("body 최소(%)", 0.0, 5.0,
                                                 float(cur.get("body_pct_min", "0.002")) * 100,
                                                 step=0.05) / 100
            with c6:
                rev_body_pct = st.number_input("추세 꺾임 body(%)", 0.0, 5.0,
                                                 float(cur.get("reversal_body_pct", "0.003")) * 100,
                                                 step=0.05) / 100
            with c7:
                rev_vol_mult = st.number_input("추세 꺾임 vol 배수", 1.0, 10.0,
                                                 float(cur.get("reversal_vol_mult", "1.3")), step=0.1)

        # ── 거래량 / 펀딩비 ──
        with tab_vol:
            st.markdown("###### 거래량 배수")
            c1, c2, c3 = st.columns(3)
            with c1:
                vol_exh = st.number_input("Exhaustion 배수", 1.5, 20.0,
                                            float(cur.get("vol_exhaustion_mult", "3.0")), step=0.5)
            with c2:
                vol_net = st.number_input("vol Net 배수", 1.0, 10.0,
                                            float(cur.get("vol_net_mult", "2.0")), step=0.1)
            with c3:
                oi_active = st.number_input("OI 활성도(%)", 0.0, 5.0,
                                              float(cur.get("oi_active_pct", "0.001")) * 100,
                                              step=0.05) / 100
            st.markdown("###### 펀딩비 임계 (단위: %)")
            c4, c5, c6 = st.columns(3)
            with c4:
                fr_overheat = st.number_input("롱 과열 FR (≥)", 0.0, 1.0,
                                                float(cur.get("fr_long_overheat", "0.005")),
                                                step=0.001, format="%.4f")
            with c5:
                fr_caution = st.number_input("숏 경보 FR (≤)", -1.0, 0.0,
                                               float(cur.get("fr_short_caution", "-0.005")),
                                               step=0.001, format="%.4f")
            with c6:
                fr_extreme = st.number_input("숏 주의 FR (≤)", -1.0, 0.0,
                                               float(cur.get("fr_short_extreme", "-0.007")),
                                               step=0.001, format="%.4f")

        # ── 차트 ──
        with tab_chart:
            st.markdown("###### 한 화면 캔들 수")
            c1, c2 = st.columns(2)
            with c1:
                cl_desktop = st.number_input("데스크톱", 10, 500,
                                               int(cur.get("candle_limit_desktop", "53")))
            with c2:
                cl_mobile = st.number_input("모바일", 5, 200,
                                              int(cur.get("candle_limit_mobile", "14")))

        # ── 저장 / 테스트 버튼 (탭 밖 하단) ──
        st.markdown('<div style="margin-top:14px;"></div>', unsafe_allow_html=True)
        bcol1, bcol2, _ = st.columns([2, 1, 3])
        with bcol1:
            submitted = st.form_submit_button("💾 전체 설정 저장",
                                                use_container_width=True, type="primary")
        with bcol2:
            test_msg = st.form_submit_button("🧪 텔레그램 테스트", use_container_width=True)

        if submitted or test_msg:
            saves = {
                "telegram_token":       token.strip(),
                "telegram_chat_id":     chat_id.strip(),
                "alert_symbol":         symbol,
                "alert_timeframes":     ",".join(tf_selected) if tf_selected else "5m,15m,30m,1h",
                "alert_cooldown_sec":   int(cooldown),
                "stop_loss_pct":        f"{sl_pct_pct/100:.6f}",
                "polling_interval_sec": int(poll_sec),
                "alert_enabled":        "1" if alert_enabled else "0",
                "daily_report_enabled": "1" if daily_enabled else "0",
                "forming_stable_polls": int(forming_polls),
                "long_rsi_max":         long_rsi_max,
                "short_rsi_min":        short_rsi_min,
                "strong_long_rsi_max":  slong_rsi_max,
                "strong_short_rsi_min": sshort_rsi_min,
                "body_pct_min":         f"{body_pct_min:.6f}",
                "reversal_body_pct":    f"{rev_body_pct:.6f}",
                "reversal_vol_mult":    rev_vol_mult,
                "vol_exhaustion_mult":  vol_exh,
                "vol_net_mult":         vol_net,
                "oi_active_pct":        f"{oi_active:.6f}",
                "fr_long_overheat":     f"{fr_overheat:.6f}",
                "fr_short_caution":     f"{fr_caution:.6f}",
                "fr_short_extreme":     f"{fr_extreme:.6f}",
                "candle_limit_desktop": int(cl_desktop),
                "candle_limit_mobile":  int(cl_mobile),
            }
            for k, v in saves.items():
                settings_db.set_value(k, v)
            with alert_state.alert_lock:
                alert_state.alert_symbol = symbol
            if test_msg:
                send_telegram("✅ junggomoa.com 대시보드 — 설정 저장 + 테스트 메시지")
                st.toast("텔레그램 테스트 발송 + 설정 저장", icon="📨")
            else:
                st.toast(f"{len(saves)}개 항목 저장됨", icon="✅")


def render_exchange_keys_page():
    st.markdown("## 🔑 거래소 API 키")
    st.caption("거래소별 API Key / Secret 을 Fernet 으로 암호화하여 PostgreSQL 에 영속 저장. 자동매매 시 활성 키로 주문 발사.")

    if not exchange_keys._enabled():
        st.warning("DATABASE_URL 또는 cryptography 패키지 미설정. 컨테이너 재기동 / 의존성 확인 필요.")
        return

    creds = exchange_keys.list_credentials()

    st.markdown("### ➕ 새 키 등록")
    with st.form("new_cred", clear_on_submit=True):
        c1, c2, c3 = st.columns([1, 1, 1])
        with c1:
            ex = st.selectbox("거래소", exchange_keys.SUPPORTED_EXCHANGES)
        with c2:
            label = st.text_input("Label", placeholder="예: main / sub / strategy_A")
        with c3:
            testnet = st.checkbox("Testnet", value=False)
        c4, c5 = st.columns(2)
        with c4:
            api_key = st.text_input("API Key", type="password")
        with c5:
            api_secret = st.text_input("API Secret", type="password")
        passphrase = st.text_input("Passphrase (OKX/Bitget 만 필요)", type="password",
                                     placeholder="해당 거래소가 아니면 비워두세요")
        submitted = st.form_submit_button("등록", use_container_width=True, type="primary")
        if submitted:
            if not api_key or not api_secret:
                st.error("API Key / Secret 둘 다 입력 필수")
            else:
                cid = exchange_keys.add_credential(ex, label, api_key, api_secret,
                                                     passphrase or None, testnet, True)
                if cid:
                    st.success(f"✅ 등록 완료 (id={cid}). 페이지 새로고침으로 목록에 반영.")
                else:
                    st.error("등록 실패. 컨테이너 로그 확인.")

    st.markdown("---")
    st.markdown(f"### 📒 등록된 키 ({len(creds)})")
    if not creds:
        st.info("아직 등록된 키 없음.")
        return
    for c in creds:
        with st.expander(
            f"`#{c['id']}` **{c['exchange'].upper()}** [{c['label'] or '-'}] "
            f"{'🧪TESTNET' if c['testnet'] else '🟢LIVE'} {'✅' if c['enabled'] else '⏸️'}",
        ):
            cc1, cc2 = st.columns(2)
            with cc1:
                st.code(f"API Key: {c['api_key_masked']}")
            with cc2:
                st.code(f"Secret:  {c['api_secret_masked']}")
            if c.get("passphrase_masked"):
                st.code(f"Passphrase: {c['passphrase_masked']}")
            st.caption(f"등록: {c['created_at']} / 수정: {c['updated_at']}")

            colx, coly, colz = st.columns(3)
            with colx:
                new_enabled = st.checkbox("활성", value=c["enabled"], key=f"en_{c['id']}")
                if new_enabled != c["enabled"]:
                    if exchange_keys.update_credential(c["id"], enabled=new_enabled):
                        st.success("상태 변경 — 새로고침 시 반영")
            with coly:
                new_testnet = st.checkbox("Testnet", value=c["testnet"], key=f"tn_{c['id']}")
                if new_testnet != c["testnet"]:
                    if exchange_keys.update_credential(c["id"], testnet=new_testnet):
                        st.success("Testnet 변경")
            with colz:
                if st.button("🗑️ 삭제", key=f"del_{c['id']}"):
                    if exchange_keys.delete_credential(c["id"]):
                        st.success("삭제 완료. 새로고침으로 목록 반영.")


def render_automation_page():
    st.markdown("## 🤖 자동매매 설정")
    st.caption("⚠️ 현재 어댑터는 **DRY-RUN 더미** (실제 거래소 주문 미연결). 인터페이스 / 설정 / 키 관리만 갖춰진 상태. "
                "실 주문 연결은 추후 거래소별 SDK 어댑터 추가 후 활성화.")

    if not exchange_keys._enabled():
        st.warning("DATABASE_URL 또는 cryptography 미설정.")
        return

    cfg = exchange_keys.automation_all()
    creds = exchange_keys.list_credentials()
    cred_options = {f"#{c['id']} {c['exchange'].upper()} [{c['label'] or '-'}] {'🧪' if c['testnet'] else ''}": str(c["id"])
                    for c in creds if c["enabled"]}
    cred_labels = list(cred_options.keys())

    with st.form("automation_form"):
        c1, c2, c3 = st.columns(3)
        with c1:
            enabled = st.checkbox("자동매매 ON", value=cfg.get("enabled", "0") == "1",
                                   help="글로벌 킬스위치. OFF 면 시그널만 기록.")
        with c2:
            dry_run = st.checkbox("DRY-RUN (실 주문 X)", value=cfg.get("dry_run", "1") == "1",
                                    help="ON 권장. 어댑터가 stdout 으로만 출력.")
        with c3:
            allowed_dirs = st.selectbox("허용 방향",
                                          ["long,short", "long", "short"],
                                          index=["long,short", "long", "short"].index(cfg.get("allowed_directions", "long,short")) if cfg.get("allowed_directions", "long,short") in ["long,short", "long", "short"] else 0)

        st.markdown("##### 활성 키")
        if cred_labels:
            cur_id = cfg.get("active_credential", "")
            cur_label = next((k for k, v in cred_options.items() if v == cur_id), cred_labels[0])
            active_label = st.selectbox("활성 거래소 키", cred_labels, index=cred_labels.index(cur_label))
            active_id = cred_options[active_label]
        else:
            st.info("등록된 활성 키가 없습니다. '🔑 거래소 API' 페이지에서 먼저 등록하세요.")
            active_id = ""

        st.markdown("##### 포지션 / 리스크")
        c4, c5, c6, c7 = st.columns(4)
        with c4:
            leverage = st.number_input("레버리지", 1, 125, int(cfg.get("leverage", "10")))
        with c5:
            pos_pct = st.number_input("포지션 크기 (잔고%)",
                                        0.1, 100.0, float(cfg.get("position_size_pct", "1.0")), step=0.1)
        with c6:
            max_open = st.number_input("동시 진입 최대", 1, 20, int(cfg.get("max_open_trades", "3")))
        with c7:
            min_score = st.number_input("최소 신호 score", 1, 5, int(cfg.get("min_signal_score", "1")),
                                          help="동시 발사된 신호 수가 N 이상일 때만 진입 (예: 2 = 강한+일반 동시)")

        c8, _ = st.columns(2)
        with c8:
            tp_pct = st.number_input("Take Profit (%, 0=OFF)",
                                       0.0, 100.0, float(cfg.get("tp_pct", "0.0")), step=0.1)

        submitted = st.form_submit_button("💾 자동매매 설정 저장", use_container_width=True, type="primary")
        if submitted:
            settings = {
                "enabled":            "1" if enabled else "0",
                "dry_run":            "1" if dry_run else "0",
                "active_credential":  active_id,
                "leverage":           leverage,
                "position_size_pct":  pos_pct,
                "max_open_trades":    max_open,
                "min_signal_score":   min_score,
                "allowed_directions": allowed_dirs,
                "tp_pct":             tp_pct,
            }
            for k, v in settings.items():
                exchange_keys.automation_set(k, v)
            st.success("✅ 저장 완료.")

    st.markdown("---")
    st.markdown("### 🧪 어댑터 테스트 (DRY-RUN)")
    if st.button("get_balance 호출"):
        if not active_id:
            st.error("활성 키 미선택")
        else:
            cred = exchange_keys.get_credential(int(active_id))
            adapter = exchange_adapters.make_adapter(cred, dry_run=True)
            bal = adapter.get_balance("USDT")
            st.code(f"adapter.get_balance('USDT') -> {bal}")

    st.markdown("---")
    st.markdown("### 📋 현재 자동매매 설정")
    st.json(cfg)


def main():
    # ── 로그인 게이트 (st.stop 으로 강제 중단 — 다른 위젯 렌더 차단) ──
    if not st.session_state.get("user"):
        render_login_page()
        st.stop()

    if not alert_state.alert_started:
        t = threading.Thread(target=_alert_loop, daemon=True)
        t.start()
        alert_state.alert_started = True

    if not alert_state.daily_report_started:
        dr = threading.Thread(target=_daily_report_loop, daemon=True)
        dr.start()
        alert_state.daily_report_started = True

    page = render_sidebar()

    if page == "settings":
        render_settings_page()
        return
    if page == "trades":
        render_trades_page()
        return
    if page == "exchange_keys":
        render_exchange_keys_page()
        return
    if page == "automation":
        render_automation_page()
        return
    if page == "my_info":
        render_my_info_page()
        return

    # 대시보드 진입 시 DB 의 alert_symbol 을 기본 심볼로 사용
    if not alert_state.alert_symbol or alert_state.alert_symbol == "BTCUSDT":
        alert_state.alert_symbol = settings_db.get("alert_symbol", "BTCUSDT")

    col1, col2, col3, col4, col5 = st.columns([2, 1, 1, 1, 2])
    with col1:
        st.markdown("### 📊 선물 대시보드")
    with col2:
        symbol = st.selectbox("심볼", ["BTCUSDT","ETHUSDT","SOLUSDT","BNBUSDT"], index=0, label_visibility="collapsed")
    with col3:
        interval = st.selectbox("시간축", ["1m","3m","5m","15m","30m","1h","4h","12h","1d","3d","1M"], index=2, label_visibility="collapsed")
    with col4:
        refresh_sec = st.number_input("갱신(초)", min_value=10, max_value=300, value=30)
    with col5:
        now_kst = datetime.now(timezone.utc) + KST
        st.markdown(f"<div style='text-align:right; font-size:12px; color:#888; margin-bottom:2px;'>🕐 마지막 갱신: {now_kst.strftime('%Y-%m-%d %H:%M:%S')} KST</div>", unsafe_allow_html=True)
        col5a, col5b, col5c, col5d = st.columns(4)
        with col5a:
            refresh_btn = st.button("🔄 새로고침")
        with col5b:
            auto = st.checkbox("자동갱신", value=True)
        with col5c:
            show_legend = st.checkbox("범례", value=False)
        with col5d:
            mobile_mode = st.checkbox("모바일", value=False)

    cl_desktop = settings_db.get_int("candle_limit_desktop", 53)
    cl_mobile  = settings_db.get_int("candle_limit_mobile", 14)
    candle_limit = cl_mobile if mobile_mode else cl_desktop

    with alert_state.alert_lock:
        alert_state.alert_symbol   = symbol
        alert_state.alert_interval = interval

    try:
        with st.spinner("데이터 로딩 중..."):
            fig, df = build_chart(symbol, interval, candle_limit)

        try:
            fr_df = get_funding_rate(symbol, 1)
            if not fr_df.empty:
                rate = fr_df["fundingRate"].iloc[-1]
                fr_extreme  = settings_db.get_float("fr_short_extreme", -0.007)
                fr_caution  = settings_db.get_float("fr_short_caution", -0.005)
                fr_overheat = settings_db.get_float("fr_long_overheat", 0.005)
                if rate <= fr_extreme:
                    st.error(f"🚨 극단적 숏스퀴즈 위험 | FR: {rate:.4f}% | 숏 신규진입 절대 금지")
                elif rate <= fr_caution:
                    st.warning(f"⚠️ 숏스퀴즈 경보 구간 | FR: {rate:.4f}% | 숏 진입 시 청산가 재확인 필수")
                elif rate >= fr_overheat:
                    st.info(f"📈 롱 과열 구간 | FR: {rate:.4f}% | 롱스퀴즈 주의")
                else:
                    st.success(f"✅ FR 정상 | {rate:.4f}%")
        except: pass

        fig.update_layout(showlegend=show_legend)
        st.plotly_chart(fig, use_container_width=True, config={
            "scrollZoom": True,
            "doubleClick": "reset",
            "displayModeBar": True,
            "modeBarButtonsToRemove": ["lasso2d", "select2d"],
        })



    except Exception as e:
        st.error(f"데이터 로드 오류: {e}")
        import traceback
        st.code(traceback.format_exc())

    if auto:
        time.sleep(refresh_sec)
        st.rerun()

if __name__ == "__main__":
    main()