feat: 所有页面接入 Google Analytics (G-LVVXH3TL04)

- onchain_metrics.py: 独立模块，CoinMetrics/CoinGecko/Farside 免费数据源
- main.py: 集成后台线程 + REST API (/api/onchain/metrics, /latest, /available)
- requirements.txt: 添加 requests 依赖
- 5分钟自动刷新，CSV 落盘到 data/onchain/

ChanMacro/chan_integration.py

@@ -0,0 +1,224 @@
+"""
+chan_integration.py — 缠论引擎集成：检测 BSP 信号并写入 signal_features。
+
+复用 bsp_monitor/engine.py 的 ChanEngine 管线，对历史日线数据批量跑缠论，
+提取 B1/B2/B3/S1/S2/S3 信号，通过 SignalTracker 记录到 signal_features。
+"""
+
+import sys
+import os
+from datetime import date as Date, timedelta
+from typing import List, Optional
+import logging
+
+# 确保 Chan 引擎在路径上（与 bsp_monitor/engine.py 相同的路径设置）
+_PARENT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+if _PARENT not in sys.path:
+    sys.path.insert(0, _PARENT)
+
+import pandas as pd
+
+from ChanEnum import Chan_BSP_TYPE, Chan_BSP_DIR
+from ChanBSP import ChanBSP
+
+logger = logging.getLogger(__name__)
+
+
+class ChanSignalDetector:
+    """
+    对历史日线数据运行缠论管线，提取所有 BSP 信号。
+
+    Usage:
+        detector = ChanSignalDetector()
+        signals = detector.detect_from_db("2026-01-01", "2026-06-24")
+        # → [{"date": Date, "signal_type": "B3", "entry_price": 96500, ...}, ...]
+    """
+
+    def __init__(self):
+        from TF_DF import TF_DF as _TF_DF_Class
+        self._TF_DF_Class = _TF_DF_Class
+
+    def detect_from_db(self, start_date: str, end_date: str) -> list[dict]:
+        """从数据库加载日线数据，跑缠论管线，提取信号。"""
+        from database import get_connection
+        conn = get_connection()
+        df = pd.read_sql_query(
+            "SELECT date, open, high, low, close, volume "
+            "FROM ohlcv_daily WHERE symbol='BTC/USDT:USDT' "
+            "AND date BETWEEN ? AND ? ORDER BY date",
+            conn, params=(start_date, end_date)
+        )
+        conn.close()
+
+        if df.empty or len(df) < 50:
+            logger.warning(f"日线数据不足: {len(df)} 根")
+            return []
+
+        return self.detect_from_df(df)
+
+    def detect_from_df(self, df: pd.DataFrame) -> list[dict]:
+        """从 DataFrame 运行缠论管线，提取 BSP 信号。"""
+        # 需要 datetime 列才能跑 TF_DF
+        df = df.copy()
+        df["timestamp"] = pd.to_datetime(df["date"])
+        df["date"] = df["timestamp"]
+
+        try:
+            engine = self._build_engine(df)
+        except Exception as e:
+            logger.error(f"缠论管线失败: {e}")
+            return []
+
+        return self._extract_signals(engine)
+
+    def _build_engine(self, df: pd.DataFrame):
+        """构建缠论管线（对齐 bsp_monitor/engine.py 的 ChanEngine）。"""
+        from TF_DF import TF_DF as _TF_DF_Class
+
+        if df.empty or len(df) < 50:
+            raise ValueError(f"数据不足: {len(df)} 根 K 线")
+
+        if "date" not in df.columns and "timestamp" in df.columns:
+            df["date"] = df["timestamp"]
+
+        # 使用 __new__ 避免触发 TF_DF.__init__
+        engine = type('ChanEngine', (), {})()  # 简单容器
+        tf = _TF_DF_Class.__new__(_TF_DF_Class)
+
+        df_with_indicators = tf.add_indicators(df.copy())
+        engine.klu_list = tf.get_klu_list(df_with_indicators)
+        engine.klc_list = tf.get_klc_list(engine.klu_list)
+        engine.bi_list = tf.cal_bi_list(engine.klc_list)
+        engine.seg_list = tf.get_seg_list(engine.bi_list)
+        engine.bi_zs_list = tf.cal_bi_zs(engine.seg_list)
+        engine.bsp_list = tf.find_all_bsp(engine.bi_list, engine.bi_zs_list)
+
+        return engine
+
+    def _extract_signals(self, engine) -> list[dict]:
+        """从 ChanEngine 输出中提取所有 BSP 信号。"""
+        signals = []
+        for bsp in engine.bsp_list:
+            if bsp.type == Chan_BSP_TYPE.NONE:
+                continue
+            if bsp.klc is None:
+                continue
+
+            signal_type = self._bsp_type_str(bsp.type)
+            entry_price = bsp.klc.close
+            signal_date = self._klc_date(bsp.klc)
+
+            if signal_date is None:
+                continue
+
+            # 信号质量：根据分型强度判断
+            strength = self._calc_strength(bsp)
+            grade = "A" if strength >= 70 else "B" if strength >= 50 else "C"
+
+            signals.append({
+                "date": signal_date,
+                "signal_type": signal_type,
+                "entry_price": float(entry_price),
+                "signal_grade": grade,
+                "signal_strength": float(strength),
+            })
+
+        details = ", ".join(f"{s['signal_type']}({s['date']})" for s in signals)
+        logger.info(f"检测到 {len(signals)} 个信号: {details}")
+        return signals
+
+    def populate_signal_features(self, start_date: str = "2024-01-01",
+                                  end_date: Optional[str] = None) -> int:
+        """
+        完整流程：检测信号 → 计算市场状态 → 写入 signal_features。
+
+        Returns: 写入的信号数量。
+        """
+        if end_date is None:
+            end_date = Date.today().isoformat()
+
+        logger.info(f"开始信号检测: {start_date} → {end_date}")
+
+        # Step 1: 检测缠论信号
+        signals = self.detect_from_db(start_date, end_date)
+        if not signals:
+            logger.warning("未检测到任何 BSP 信号")
+            return 0
+
+        # Step 2: 去重 — 跳过已存在的信号
+        from database import get_connection
+        conn = get_connection()
+        existing = set()
+        for row in conn.execute(
+            "SELECT date, signal_type FROM signal_features"
+        ).fetchall():
+            existing.add((row[0], row[1]))
+        conn.close()
+
+        new_signals = [s for s in signals
+                       if (str(s["date"]), s["signal_type"]) not in existing]
+        if not new_signals:
+            logger.info("所有信号已存在，跳过")
+            return 0
+
+        # Step 3: 写入 signal_features
+        from expectancy.tracker import SignalTracker
+        tracker = SignalTracker()
+        count = tracker.backfill_signals(new_signals)
+
+        logger.info(f"信号入库完成: {count}/{len(signals)}")
+        return count
+
+    @staticmethod
+    def _bsp_type_str(t: Chan_BSP_TYPE) -> str:
+        mapping = {
+            Chan_BSP_TYPE.B1: "B1", Chan_BSP_TYPE.B2: "B2", Chan_BSP_TYPE.B3: "B3",
+            Chan_BSP_TYPE.S1: "S1", Chan_BSP_TYPE.S2: "S2", Chan_BSP_TYPE.S3: "S3",
+        }
+        return mapping.get(t, "UNKNOWN")
+
+    @staticmethod
+    def _klc_date(klc) -> Optional[Date]:
+        """从 KLC 提取信号确认日期。"""
+        end_time = getattr(klc, "end_time", None)
+        if end_time is None:
+            start_time = getattr(klc, "start_time", None)
+            if start_time is None:
+                return None
+            end_time = start_time
+        if hasattr(end_time, "date"):
+            return end_time.date()
+        if isinstance(end_time, str):
+            return Date.fromisoformat(end_time[:10])
+        return None
+
+    @staticmethod
+    def _calc_strength(bsp: ChanBSP) -> float:
+        """根据 BSP 特征计算信号强度 0-100。"""
+        score = 50.0
+        klc = bsp.klc
+        if klc is None:
+            return score
+
+        # 分型强度
+        from ChanEnum import Chan_KLC_FX
+        fx = getattr(klc, "klc_fx_type", None)
+        if fx is not None:
+            strong_fxs = {Chan_KLC_FX.TOP2, Chan_KLC_FX.TOP3, Chan_KLC_FX.BOTTOM2, Chan_KLC_FX.BOTTOM3}
+            medium_fxs = {Chan_KLC_FX.TOP1, Chan_KLC_FX.BOTTOM1, Chan_KLC_FX.TOP4, Chan_KLC_FX.BOTTOM4}
+            if fx in strong_fxs:
+                score += 25
+            elif fx in medium_fxs:
+                score += 10
+
+        # BSP 类型
+        if bsp.type in (Chan_BSP_TYPE.B1, Chan_BSP_TYPE.S1):
+            score += 10  # 一类买卖点: 背驰确认, 额外加分
+
+        # 笔特征
+        bi = getattr(bsp, "bi", None)
+        if bi and hasattr(bi, "height") and hasattr(bi, "width"):
+            if bi.width > 3 and abs(bi.height) > 100:
+                score += 10
+
+        return min(score, 100.0)

ChanMacro/cli.py

@@ -5,6 +5,7 @@ cli.py — Command-line interface for ChanMacro.
 import argparse
 import json
 import logging
+import time
 from datetime import date as Date, datetime, timedelta
 
 logging.basicConfig(
@@ -49,6 +50,24 @@ def _build_market_state(target: Date) -> tuple:
         oi_matrix_score=oi, volatility_regime_score=vol,
     )
     state.market_state_hash = state.compute_hash()
+
+    # Persist regime to DB so subsequent calls have correct state
+    from database import get_connection
+    conn = get_connection()
+    conn.execute("""
+        INSERT OR REPLACE INTO regime_history
+        (date, regime, confidence, regime_version, maturity_score, all_scores_json,
+         prior_regime, confirmation_days)
+        VALUES (?, ?, ?, ?, ?, ?, ?, ?)
+    """, (
+        str(target), r.regime.value, r.confidence, r.regime_version,
+        r.maturity_score, json.dumps(r.all_scores),
+        r.prior_regime.value if r.prior_regime else None,
+        r.confirmation_days,
+    ))
+    conn.commit()
+    conn.close()
+
     return state, r
 
 
@@ -93,13 +112,13 @@ def cmd_fetch(args):
 
 def cmd_score(args):
     """Compute all factor scores and regime for a date."""
-    from database import init_db, get_connection
+    from database import init_db
 
     target = parse_date(args.date) if args.date else Date.today()
     init_db()
     logger.info(f"Computing scores for {target}...")
 
-    state, regime_result = _build_market_state(target)
+    state, _ = _build_market_state(target)
 
     # Output
     ps = state.price_structure_score
@@ -128,26 +147,6 @@ def cmd_score(args):
     print(f"  Market State Hash:  {state.market_state_hash}")
     print()
 
-    # Store regime to DB
-    conn = get_connection()
-    conn.execute("""
-        INSERT OR REPLACE INTO regime_history
-        (date, regime, confidence, regime_version, maturity_score, all_scores_json,
-         prior_regime, confirmation_days)
-        VALUES (?, ?, ?, ?, ?, ?, ?, ?)
-    """, (
-        str(target),
-        state.regime.value,
-        state.regime_confidence,
-        state.regime_version,
-        state.regime_maturity_score,
-        json.dumps(regime_result.all_scores),
-        regime_result.prior_regime.value if regime_result.prior_regime else None,
-        regime_result.confirmation_days,
-    ))
-    conn.commit()
-    conn.close()
-
     return state
 
 
@@ -193,23 +192,104 @@ def cmd_track(args):
 
 
 def cmd_backfill(args):
-    """Backfill historical scores and/or signals."""
+    """Backfill historical breadth + regime scores."""
     from datetime import date as Date, timedelta
     from database import init_db, get_connection
     from fetchers.ohlcv import OHLCVFetcher
+    from fetchers.breadth import BreadthFetcher
+    from config import config
+    import pandas as pd
+    import requests
 
     start = parse_date(args.from_date)
     end = parse_date(args.to_date) if args.to_date else Date.today()
     init_db()
 
-    # First, backfill OHLCV data
-    logger.info(f"Backfilling OHLCV from {start} to {end}...")
-    fetcher = OHLCVFetcher()
-    df = fetcher.fetch()
-    if not df.empty:
-        fetcher.store_df(df)
+    # Step 1: Ensure OHLCV data exists for the range
+    logger.info(f"Step 1/3: Fetching BTC OHLCV...")
+    OHLCVFetcher().store_df(OHLCVFetcher().fetch())
 
-    # Then compute scores for each date
+    # Step 2: Backfill breadth — fetch TOP50 daily data and compute per date
+    logger.info(f"Step 2/3: Backfilling breadth {start} → {end}...")
+    provider_url = config.provider_url
+    all_symbol_data = {}
+
+    for sym in config.top50_symbols:
+        try:
+            df = pd.DataFrame(requests.get(
+                f"{provider_url}/api/candles",
+                params={"symbol": sym, "tf": "1d", "limit": 400},
+                timeout=30
+            ).json())
+            if not df.empty and "timestamp" in df.columns:
+                df["date"] = pd.to_datetime(df["timestamp"], unit="ms").dt.date
+                df["close"] = df["close"].astype(float)
+                df["high"] = df["high"].astype(float)
+                df["ema20"] = df["close"].ewm(20).mean()
+                all_symbol_data[sym] = df
+        except Exception as e:
+            logger.debug(f"  Skip {sym}: {e}")
+
+    logger.info(f"  Fetched {len(all_symbol_data)}/{len(config.top50_symbols)} symbols")
+
+    # Compute breadth for each date
+    conn = get_connection()
+    current = start
+    breadth_count = 0
+    while current <= end:
+        target_str = str(current)
+        try:
+            advances_50 = declines_50 = above_ema20_50 = new_highs_50 = 0
+            advances_30 = advances_20 = above_ema20_30 = above_ema20_20 = 0
+            new_highs_30 = new_highs_20 = 0
+
+            for rank, (sym, df) in enumerate(all_symbol_data.items()):
+                rows = df[df["date"] == current]
+                if rows.empty:
+                    continue
+                row = rows.iloc[0]
+                prev_rows = df[df["date"] < current]
+                if prev_rows.empty:
+                    continue
+                prev = prev_rows.iloc[-1]
+
+                if row["close"] > prev["close"]:
+                    if rank < 50: advances_50 += 1
+                    if rank < 30: advances_30 += 1
+                    if rank < 20: advances_20 += 1
+                elif row["close"] < prev["close"]:
+                    if rank < 50: declines_50 += 1
+
+                if not pd.isna(row.get("ema20")) and row["close"] > row["ema20"]:
+                    if rank < 50: above_ema20_50 += 1
+                    if rank < 30: above_ema20_30 += 1
+                    if rank < 20: above_ema20_20 += 1
+
+                recent_highs = df[(df["date"] < current) & (df["date"] >= current - timedelta(days=20))]
+                if not recent_highs.empty and row["high"] > recent_highs["high"].max():
+                    if rank < 50: new_highs_50 += 1
+                    if rank < 30: new_highs_30 += 1
+                    if rank < 20: new_highs_20 += 1
+
+            conn.execute("""INSERT OR REPLACE INTO breadth_daily
+                (date, total_tracked, advance_top50, decline_top50, above_ema20_top50,
+                 new_highs_20d_top50, advance_top30, advance_top20,
+                 above_ema20_top30, above_ema20_top20, new_highs_20d_top30, new_highs_20d_top20)
+                VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)""",
+                (target_str, len(all_symbol_data),
+                 advances_50, declines_50, above_ema20_50, new_highs_50,
+                 advances_30, advances_20, above_ema20_30, above_ema20_20,
+                 new_highs_30, new_highs_20))
+            breadth_count += 1
+        except Exception as e:
+            logger.debug(f"  Breadth skip {current}: {e}")
+        current += timedelta(days=1)
+
+    conn.commit()
+    logger.info(f"  Breadth backfill: {breadth_count} days")
+
+    # Step 3: Compute regime scores for each date
+    logger.info(f"Step 3/3: Computing regime scores {start} → {end}...")
     from scoring.price_structure import PriceStructureScorer
     from scoring.breadth_scorer import BreadthScorer
     from scoring.oi_matrix import OIMatrixScorer
@@ -217,10 +297,8 @@ def cmd_backfill(args):
     from regime_detector import RegimeDetector
 
     detector = RegimeDetector()
-    conn = get_connection()
-
     current = start
-    count = 0
+    score_count = 0
     while current <= end:
         try:
             ps = PriceStructureScorer().compute(current)
@@ -228,33 +306,27 @@ def cmd_backfill(args):
             if br.score == 50.0 and br.label == "No Data":
                 current += timedelta(days=1)
                 continue
-
             oi = OIMatrixScorer().compute(current)
             vol = VolatilityRegimeScorer().compute(current)
-            r = detector.detect(ps.score, br.breadth_top50,
-                                vol.vol_regime.value, current)
+            r = detector.detect(ps.score, br.breadth_top50, vol.vol_regime.value, current)
 
-            conn.execute("""
-                INSERT OR REPLACE INTO regime_history
+            conn.execute("""INSERT OR REPLACE INTO regime_history
                 (date, regime, confidence, regime_version, maturity_score,
                  all_scores_json, confirmation_days)
-                VALUES (?, ?, ?, ?, ?, ?, ?)
-            """, (
-                str(current), r.regime.value, r.confidence,
-                r.regime_version, r.maturity_score,
-                json.dumps(r.all_scores), r.confirmation_days,
-            ))
-            count += 1
-            if count % 30 == 0:
+                VALUES (?, ?, ?, ?, ?, ?, ?)""",
+                (str(current), r.regime.value, r.confidence, r.regime_version,
+                 r.maturity_score, json.dumps(r.all_scores), r.confirmation_days))
+            score_count += 1
+            if score_count % 30 == 0:
                 conn.commit()
-                logger.info(f"  Backfilled {count} days... ({current})")
+                logger.info(f"  Scored {score_count} days... ({current})")
         except Exception as e:
-            logger.debug(f"  Skip {current}: {e}")
+            logger.debug(f"  Score skip {current}: {e}")
         current += timedelta(days=1)
 
     conn.commit()
     conn.close()
-    logger.info(f"Backfill complete: {count} days scored")
+    logger.info(f"Backfill complete: {breadth_count} breadth + {score_count} regime days")
 
 
 def cmd_expectancy(args):
@@ -333,6 +405,12 @@ def main():
     # validate
     p_validate = sub.add_parser("validate", help="Run validation framework")
 
+    # cron
+    p_cron = sub.add_parser("cron", help="Run scheduled fetch+score loop")
+    # detect (Chan BSP signals)
+    p_detect = sub.add_parser("detect", help="Detect Chan BSP signals and populate signal_features")
+    p_detect.add_argument("--from", dest="from_date", default="2024-01-01")
+    p_detect.add_argument("--to", dest="to_date")
     # serve
     p_serve = sub.add_parser("serve", help="Start web dashboard")
 
@@ -354,8 +432,30 @@ def main():
         from validation.reporter import ValidationReporter
         report = ValidationReporter().run_all()
         print(report)
+    elif args.command == "detect":
+        from chan_integration import ChanSignalDetector
+        start = args.from_date
+        end = args.to_date or Date.today().isoformat()
+        detector = ChanSignalDetector()
+        count = detector.populate_signal_features(start, end)
+        logger.info(f"写入 {count} 条信号记录")
     elif args.command == "serve":
-        logger.info("Web dashboard not yet implemented (Phase 7)")
+        from scheduler import get_scheduler
+        get_scheduler().start()
+        logger.info("启动 Web Dashboard: http://127.0.0.1:8124")
+        from web.app import app
+        app.run(host="0.0.0.0", port=8124, debug=False)
+    elif args.command == "cron":
+        from scheduler import get_scheduler
+        logger.info("启动后台调度器 (Ctrl+C 停止)")
+        s = get_scheduler()
+        s.start()
+        try:
+            while True:
+                time.sleep(60)
+        except KeyboardInterrupt:
+            s.stop()
+            logger.info("调度器已停止")
     else:
         parser.print_help()
 

ChanMacro/scheduler.py

@@ -0,0 +1,153 @@
+"""
+scheduler.py — 后台自动调度：定时拉取数据 + 计算因子 + 制度判定。
+
+Python main.py cron         → 前台阻塞运行，每 N 分钟一个 tick
+Web app 启动时自动启动调度器  → 后台线程，不阻塞 Web 请求
+"""
+
+import threading
+import logging
+import time
+from datetime import datetime, timezone, timedelta
+from typing import Optional
+
+logger = logging.getLogger("chanmacro.scheduler")
+
+
+class MacroScheduler:
+    """后台调度器：定时 fetch + score。"""
+
+    def __init__(self, interval_minutes: int = 60):
+        self.interval = interval_minutes
+        self._thread: Optional[threading.Thread] = None
+        self._stop = threading.Event()
+        self._last_run: Optional[datetime] = None
+        self._running = False
+
+    def start(self) -> None:
+        """启动后台线程。"""
+        if self._running:
+            return
+        self._stop.clear()
+        self._thread = threading.Thread(target=self._loop, name="macro-scheduler", daemon=True)
+        self._thread.start()
+        self._running = True
+        logger.info(f"调度器已启动, 每 {self.interval} 分钟执行一次")
+
+    def stop(self) -> None:
+        """停止后台线程。"""
+        self._stop.set()
+        self._running = False
+        logger.info("调度器已停止")
+
+    @property
+    def last_run(self) -> Optional[datetime]:
+        return self._last_run
+
+    def _loop(self) -> None:
+        """后台循环。"""
+        # 首次启动立即跑一次
+        self._tick()
+
+        while not self._stop.wait(self.interval * 60):
+            self._tick()
+
+    def _tick(self) -> None:
+        """执行一次：fetch → score。"""
+        try:
+            from fetchers.ohlcv import OHLCVFetcher
+            from fetchers.breadth import BreadthFetcher
+            from fetchers.derivatives import DerivativesFetcher
+            from database import init_db
+            from datetime import date as Date
+
+            init_db()
+            today = Date.today()
+
+            # Fetch
+            ohlcv = OHLCVFetcher()
+            df = ohlcv.fetch()
+            if not df.empty:
+                ohlcv.store_df(df)
+
+            breadth = BreadthFetcher()
+            record = breadth.fetch()
+            if record:
+                breadth.store(record=record)
+
+            deriv = DerivativesFetcher()
+            records = deriv.fetch(today)
+            if records:
+                deriv.store(records=records)
+
+            # Score + Regime (also persisted inside _build_state)
+            from scoring.price_structure import PriceStructureScorer
+            from scoring.breadth_scorer import BreadthScorer
+            from scoring.oi_matrix import OIMatrixScorer
+            from scoring.volatility_regime import VolatilityRegimeScorer
+            from regime_detector import RegimeDetector
+            from models import MarketStateVector
+            from config import config
+            import json
+            from database import get_connection
+
+            ps = PriceStructureScorer().compute(today)
+            br = BreadthScorer().compute(today)
+            oi = OIMatrixScorer().compute(today)
+            vol = VolatilityRegimeScorer().compute(today)
+
+            detector = RegimeDetector()
+            detector.load_state(config.db_path)
+            r = detector.detect(ps.score, br.breadth_top50, vol.vol_regime.value, today)
+
+            conn = get_connection()
+            conn.execute("""
+                INSERT OR REPLACE INTO regime_history
+                (date, regime, confidence, regime_version, maturity_score,
+                 all_scores_json, prior_regime, confirmation_days)
+                VALUES (?, ?, ?, ?, ?, ?, ?, ?)
+            """, (
+                str(today), r.regime.value, r.confidence, r.regime_version,
+                r.maturity_score, json.dumps(r.all_scores),
+                r.prior_regime.value if r.prior_regime else None,
+                r.confirmation_days,
+            ))
+            conn.commit()
+            conn.close()
+
+            # 检测新信号（每天运行一次，UTC 0 点后首次触发）
+            now = datetime.now(timezone.utc)
+            if self._last_run is None or now.date() > self._last_run.date():
+                try:
+                    from chan_integration import ChanSignalDetector
+                    detector = ChanSignalDetector()
+                    # 检测最近 90 天的 4h 信号
+                    count = detector.populate_signal_features(
+                        start_date=(today - __import__('datetime').timedelta(days=90)).isoformat(),
+                        end_date=today.isoformat(),
+                    )
+                    if count > 0:
+                        logger.info(f"新增 {count} 条信号记录")
+                except Exception as e:
+                    logger.debug(f"信号检测跳过: {e}")
+
+            self._last_run = now
+            logger.info(
+                f"Tick 完成: regime={r.regime.value} conf={r.confidence:.2f} "
+                f"breadth={br.score:.0f}({br.breadth_bucket.value}) "
+                f"price={ps.score:.0f} oi={oi.oi_state.value} vol={vol.vol_regime.value}"
+            )
+
+        except Exception as e:
+            logger.error(f"Tick 失败: {e}", exc_info=True)
+
+
+# 单例
+_scheduler: Optional[MacroScheduler] = None
+
+
+def get_scheduler() -> MacroScheduler:
+    global _scheduler
+    if _scheduler is None:
+        _scheduler = MacroScheduler(interval_minutes=60)
+    return _scheduler

ChanMacro/web/app.py

@@ -6,7 +6,8 @@ import sys
 import os
 sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
-from datetime import date as Date, timedelta
+import json
+from datetime import date as Date
 from flask import Flask, render_template, jsonify, request
 
 from database import get_connection
@@ -23,7 +24,7 @@ app = Flask(__name__)
 
 
 def _build_state(target: Date):
-    """Shared: build MarketStateVector for a date."""
+    """Build MarketStateVector and persist regime to DB."""
     ps = PriceStructureScorer().compute(target)
     br = BreadthScorer().compute(target)
     oi = OIMatrixScorer().compute(target)
@@ -44,6 +45,23 @@ def _build_state(target: Date):
         oi_matrix_score=oi, volatility_regime_score=vol,
     )
     state.market_state_hash = state.compute_hash()
+
+    # Persist regime to DB so load_state() works across requests
+    conn = get_connection()
+    conn.execute("""
+        INSERT OR REPLACE INTO regime_history
+        (date, regime, confidence, regime_version, maturity_score, all_scores_json,
+         prior_regime, confirmation_days)
+        VALUES (?, ?, ?, ?, ?, ?, ?, ?)
+    """, (
+        str(target), r.regime.value, r.confidence, r.regime_version,
+        r.maturity_score, json.dumps(r.all_scores),
+        r.prior_regime.value if r.prior_regime else None,
+        r.confirmation_days,
+    ))
+    conn.commit()
+    conn.close()
+
     return state
 
 
@@ -155,4 +173,6 @@ def api_expectancy():
 
 
 if __name__ == "__main__":
+    from scheduler import get_scheduler
+    get_scheduler().start()
     app.run(host="0.0.0.0", port=8124, debug=True)

ChanMacro/web/static/js/dashboard.js

@@ -1,60 +1,75 @@
-// dashboard.js — ChanMacro dashboard
+// dashboard.js — ChanMacro
 
+const C = { TREND: "#3fb950", RANGE: "#d29922", PANIC: "#f85149" };
 let regimeChart = null, breadthChart = null;
 
-const REGIME_COLORS = { TREND: "#3fb950", RANGE: "#d29922", PANIC: "#f85149" };
-const BUCKET_CLASS = { EXTREME: "bucket-EXTREME", STRONG: "bucket-STRONG",
-    NORMAL: "bucket-NORMAL", WEAK: "bucket-WEAK", PANIC: "bucket-PANIC" };
-
 async function loadState() {
   try {
     const r = await fetch("/api/state");
     const d = await r.json();
-    if (d.error) { document.getElementById("db-status").textContent = d.error; return; }
+    if (d.error) { document.getElementById("update-time").textContent = d.error; return; }
 
-    document.getElementById("db-status").textContent = "✓ " + d.date;
-    document.getElementById("update-time").textContent = "更新于 " + new Date().toLocaleTimeString();
+    document.getElementById("update-time").textContent = d.date;
 
     // Hero
     const regime = d.regime;
-    document.getElementById("hero-regime").textContent = regime === "TREND" ? "趋势" : regime === "RANGE" ? "震荡" : "恐慌";
-    document.getElementById("hero-regime").className = "hero-regime regime-" + regime;
+    const names = { TREND: "TREND", RANGE: "RANGE", PANIC: "PANIC" };
+    document.getElementById("hero-regime").textContent = names[regime] || regime;
+    document.getElementById("hero-regime").className = "regime-name " + regime.toLowerCase();
     document.getElementById("hero-badge").textContent = regime;
-    document.getElementById("hero-badge").className = "badge-regime badge-" + regime;
+    document.getElementById("hero-badge").className = "regime-badge " + regime.toLowerCase();
     document.getElementById("hero-conf").textContent = (d.regime_confidence * 100).toFixed(0) + "%";
-    document.getElementById("hero-maturity").textContent = d.regime_maturity.toFixed(0) + "/100";
-
-    // Factors
-    document.getElementById("f-price").textContent = d.price_structure.score.toFixed(0);
-    document.getElementById("f-price").style.color =
+    document.getElementById("hero-maturity").textContent = d.regime_maturity.toFixed(0);
+    document.getElementById("hero-ps").textContent = d.price_structure.score.toFixed(0);
+    document.getElementById("hero-ps").style.color =
       d.price_structure.score >= 60 ? "#3fb950" : d.price_structure.score >= 40 ? "#d29922" : "#f85149";
-    document.getElementById("f-price-sub").textContent = d.price_structure.label;
-    document.getElementById("f-price-narr").textContent = d.price_structure.narrative;
+    document.getElementById("hero-br").textContent = d.breadth.score.toFixed(0);
+    document.getElementById("hero-br").style.color =
+      d.breadth.bucket === "EXTREME" || d.breadth.bucket === "STRONG" ? "#3fb950" :
+      d.breadth.bucket === "WEAK" || d.breadth.bucket === "PANIC" ? "#f85149" : "#d29922";
 
-    const b = d.breadth;
-    document.getElementById("f-breadth").textContent = b.score.toFixed(0);
-    document.getElementById("f-breadth").setAttribute("style",
-      "color: " + (b.bucket === "EXTREME" || b.bucket === "STRONG" ? "#3fb950" :
-                   b.bucket === "WEAK" || b.bucket === "PANIC" ? "#f85149" :
-                   b.bucket === "NORMAL" ? "#d29922" : "#e6edf3"));
+    // Factor cards
+    const ps = d.price_structure;
+    document.getElementById("f-price").textContent = ps.score.toFixed(0);
+    document.getElementById("f-price").style.color =
+      ps.score >= 60 ? "#3fb950" : ps.score >= 40 ? "#d29922" : "#f85149";
+    document.getElementById("f-price-sub").textContent =
+      `趋势 ${ps.trend.toFixed(0)} · 波动 ${ps.vol_comp.toFixed(0)} · 动量 ${ps.momentum.toFixed(0)}`;
+    document.getElementById("bar-price").style.width = ps.score + "%";
+    document.getElementById("bar-price").style.background =
+      ps.score >= 60 ? "#3fb950" : ps.score >= 40 ? "#d29922" : "#f85149";
+
+    const br = d.breadth;
+    document.getElementById("f-breadth").textContent = br.score.toFixed(0);
+    document.getElementById("f-breadth").style.color =
+      br.bucket === "EXTREME" || br.bucket === "STRONG" ? "#3fb950" :
+      br.bucket === "WEAK" || br.bucket === "PANIC" ? "#f85149" : "#d29922";
     document.getElementById("f-breadth-sub").textContent =
-      `${b.bucket} · T20=${b.top20.toFixed(0)} T50=${b.top50.toFixed(0)} div=${b.divergence > 0 ? "+" : ""}${b.divergence.toFixed(0)}`;
-    document.getElementById("f-breadth-narr").textContent = b.narrative;
+      `${br.bucket} · T20=${br.top20.toFixed(0)} T50=${br.top50.toFixed(0)}`;
+    document.getElementById("bar-breadth").style.width = br.score + "%";
+    document.getElementById("bar-breadth").style.background =
+      br.bucket === "EXTREME" || br.bucket === "STRONG" ? "#3fb950" :
+      br.bucket === "WEAK" || br.bucket === "PANIC" ? "#f85149" : "#d29922";
 
-    document.getElementById("f-oi").textContent = d.oi_state;
+    document.getElementById("f-oi").textContent = d.oi_state.toUpperCase().replace(" ", "\n");
     document.getElementById("f-oi").style.color =
-      d.oi_state === "New Longs" ? "#3fb950" : d.oi_state === "New Shorts" ? "#f85149" :
-      d.oi_state === "Short Covering" ? "#d29922" : d.oi_state === "Long Exit" ? "#f85149" : "#e6edf3";
-    document.getElementById("f-oi-sub").textContent = `分数: ${d.oi_score.toFixed(0)}`;
-    document.getElementById("f-oi-narr").textContent = d.oi_narrative;
+      d.oi_state === "New Longs" ? "#3fb950" : d.oi_state.includes("Short") || d.oi_state === "Long Exit" ? "#f85149" : "#8b949e";
+    document.getElementById("f-oi-sub").textContent = d.oi_narrative;
 
-    document.getElementById("f-vol").textContent = d.volatility;
+    const vm = { LOW_VOL: "低波动", NORMAL_VOL: "正常", HIGH_VOL: "高波动", EXPLOSIVE_VOL: "极端" };
+    document.getElementById("f-vol").textContent = vm[d.volatility] || d.volatility;
     document.getElementById("f-vol").style.color =
-      d.volatility === "LOW_VOL" ? "#58a6ff" : d.volatility === "NORMAL_VOL" ? "#e6edf3" :
+      d.volatility === "LOW_VOL" ? "#58a6ff" : d.volatility === "NORMAL_VOL" ? "#8b949e" :
       d.volatility === "HIGH_VOL" ? "#d29922" : "#f85149";
-    document.getElementById("f-vol-sub").textContent = `分数: ${d.price_structure.score.toFixed(0)}`;
+    document.getElementById("f-vol-sub").textContent = d.volatility;
+    document.getElementById("bar-vol").style.width =
+      (d.volatility === "EXPLOSIVE_VOL" ? 95 : d.volatility === "HIGH_VOL" ? 70 :
+       d.volatility === "NORMAL_VOL" ? 40 : 20) + "%";
+    document.getElementById("bar-vol").style.background =
+      d.volatility === "EXPLOSIVE_VOL" ? "#f85149" : d.volatility === "HIGH_VOL" ? "#d29922" :
+      d.volatility === "NORMAL_VOL" ? "#8b949e" : "#58a6ff";
   } catch (e) {
-    document.getElementById("db-status").textContent = "连接失败";
+    document.getElementById("update-time").textContent = "连接失败";
   }
 }
 
@@ -63,72 +78,50 @@ async function loadHistory() {
     const r = await fetch("/api/history?days=60");
     const d = await r.json();
 
-    // Regime chart
     const dates = d.regimes.map(x => x.date);
-    const regimes = d.regimes.map(x => x.regime);
-    const colors = regimes.map(r => REGIME_COLORS[r] || "#8b949e");
+    const colors = d.regimes.map(x => C[x.regime] || "#5c6675");
 
     if (regimeChart) regimeChart.destroy();
-    const ctx1 = document.getElementById("chart-regime").getContext("2d");
-    regimeChart = new Chart(ctx1, {
+    regimeChart = new Chart(document.getElementById("chart-regime").getContext("2d"), {
       type: "bar",
-      data: {
-        labels: dates,
-        datasets: [{
-          label: "置信度",
-          data: d.regimes.map(x => x.confidence * 100),
-          backgroundColor: colors,
-          borderWidth: 0,
-          borderRadius: 2,
-        }]
-      },
+      data: { labels: dates, datasets: [{ data: d.regimes.map(x => x.confidence * 100),
+        backgroundColor: colors, borderWidth: 0, borderRadius: 2 }] },
       options: {
-        responsive: true,
-        maintainAspectRatio: false,
-        plugins: {
-          legend: { display: false },
-          tooltip: {
-            callbacks: {
-              label: ctx => `${d.regimes[ctx.dataIndex].regime} · ${ctx.raw.toFixed(0)}%`
-            }
-          }
-        },
+        responsive: true, maintainAspectRatio: false,
+        plugins: { legend: { display: false } },
         scales: {
-          x: { ticks: { color: "#8b949e", maxTicksLimit: 15, maxRotation: 45 } },
-          y: { max: 100, ticks: { color: "#8b949e" } }
+          x: { ticks: { color: "#5c6675", maxTicksLimit: 15, maxRotation: 45, font: { size: 10 } },
+               grid: { color: "#151a23" } },
+          y: { max: 100, ticks: { color: "#5c6675", font: { size: 10 } }, grid: { color: "#151a23" } }
         }
       }
     });
 
-    // Breadth chart
     if (breadthChart) breadthChart.destroy();
-    const ctx2 = document.getElementById("chart-breadth").getContext("2d");
-    breadthChart = new Chart(ctx2, {
+    breadthChart = new Chart(document.getElementById("chart-breadth").getContext("2d"), {
       type: "line",
       data: {
         labels: d.breadth.map(x => x.date),
         datasets: [
           { label: "上涨", data: d.breadth.map(x => x.advance), borderColor: "#3fb950",
-            backgroundColor: "rgba(63,185,80,0.1)", fill: true, tension: 0.3, pointRadius: 0 },
+            backgroundColor: "rgba(63,185,80,0.08)", fill: true, tension: 0.3, pointRadius: 0 },
           { label: "下跌", data: d.breadth.map(x => x.decline), borderColor: "#f85149",
-            backgroundColor: "rgba(248,81,73,0.1)", fill: true, tension: 0.3, pointRadius: 0 },
+            backgroundColor: "rgba(248,81,73,0.06)", fill: true, tension: 0.3, pointRadius: 0 },
           { label: ">EMA20", data: d.breadth.map(x => x.above_ema20), borderColor: "#58a6ff",
-            borderDash: [4, 2], tension: 0.3, pointRadius: 0 },
+            borderDash: [3, 3], tension: 0.3, pointRadius: 0 },
         ]
       },
       options: {
-        responsive: true,
-        maintainAspectRatio: false,
-        plugins: { legend: { labels: { color: "#8b949e", usePointStyle: true, boxWidth: 8 } } },
+        responsive: true, maintainAspectRatio: false,
+        plugins: { legend: { labels: { color: "#5c6675", usePointStyle: true, boxWidth: 6, font: { size: 10 } } } },
         scales: {
-          x: { ticks: { color: "#8b949e", maxTicksLimit: 15, maxRotation: 45 } },
-          y: { max: 50, ticks: { color: "#8b949e" } }
+          x: { ticks: { color: "#5c6675", maxTicksLimit: 15, maxRotation: 45, font: { size: 10 } },
+               grid: { color: "#151a23" } },
+          y: { ticks: { color: "#5c6675", font: { size: 10 } }, grid: { color: "#151a23" } }
         }
       }
     });
-  } catch (e) {
-    console.error("History load failed:", e);
-  }
+  } catch (e) { console.error(e); }
 }
 
 async function loadExpectancy() {
@@ -136,36 +129,32 @@ async function loadExpectancy() {
   try {
     const r = await fetch(`/api/expectancy?signal=${signal}`);
     const d = await r.json();
-    if (d.error) { document.getElementById("exp-layers").innerHTML = `<tr><td colspan="6">${d.error}</td></tr>`; return; }
+    if (d.error) { document.getElementById("exp-layers").innerHTML =
+      `<tr><td colspan="6" style="color:#f85149">${d.error}</td></tr>`; return; }
 
-    document.getElementById("exp-sufficiency").textContent = d.sufficiency;
-    document.getElementById("exp-sufficiency").className =
-      "badge " + (d.sufficiency === "HIGH" ? "bg-success" : d.sufficiency === "MEDIUM" ? "bg-warning" :
-                  d.sufficiency === "LOW" ? "bg-danger" : "bg-secondary");
+    const el = document.getElementById("exp-sufficiency");
+    el.textContent = d.sufficiency;
+    el.className = "suff suff-" + d.sufficiency;
 
     let html = "";
     for (const l of d.layers) {
       html += `<tr>
-        <td>${l.name}</td>
-        <td>${l.samples}</td>
-        <td>${l.effective_samples.toFixed(0)}</td>
+        <td>${l.name}</td><td>${l.samples}</td><td>${l.effective_samples.toFixed(0)}</td>
         <td>${l.raw_winrate ? (l.raw_winrate * 100).toFixed(1) + "%" : "—"}</td>
         <td><strong>${(l.posterior_winrate * 100).toFixed(1)}%</strong></td>
-        <td>${l.avg_return ? (l.avg_return > 0 ? "+" : "") + l.avg_return.toFixed(1) + "%" : "—"}</td>
+        <td style="color:${l.avg_return > 0 ? '#3fb950' : l.avg_return < 0 ? '#f85149' : '#8b949e'}">${l.avg_return ? (l.avg_return > 0 ? "+" : "") + l.avg_return.toFixed(2) + "%" : "—"}</td>
       </tr>`;
     }
     document.getElementById("exp-layers").innerHTML = html;
 
-    let summary = `最终估计: <strong>${(d.final_estimate * 100).toFixed(1)}%</strong>`;
-    if (d.avg_return_7d) summary += ` · 平均收益: <strong>${d.avg_return_7d > 0 ? "+" : ""}${d.avg_return_7d.toFixed(1)}%</strong>`;
-    if (d.profit_factor) summary += ` · 盈亏比: <strong>${d.profit_factor}</strong>`;
-    document.getElementById("exp-summary").innerHTML = summary;
-  } catch (e) {
-    console.error("Expectancy load failed:", e);
-  }
+    let s = `后验胜率 <strong style="color:#58a6ff">${(d.final_estimate * 100).toFixed(1)}%</strong>`;
+    if (d.avg_return_7d) s += ` · 平均收益 <strong>${d.avg_return_7d > 0 ? "+" : ""}${d.avg_return_7d.toFixed(2)}%</strong>`;
+    if (d.profit_factor) s += ` · 盈亏比 <strong>${d.profit_factor}</strong>`;
+    if (d.max_adverse) s += ` · MAE <strong>${d.max_adverse.toFixed(1)}%</strong>`;
+    document.getElementById("exp-summary").innerHTML = s;
+  } catch (e) { console.error(e); }
 }
 
-// Init
 loadState();
 loadHistory();
 loadExpectancy();

ChanMacro/web/templates/index.html

@@ -4,138 +4,157 @@
 <meta charset="UTF-8">
 <meta name="viewport" content="width=device-width, initial-scale=1.0">
 <title>ChanMacro — 市场状态</title>
-<link href="https://cdn.jsdelivr.net/npm/bootstrap@5.3.0/dist/css/bootstrap.min.css" rel="stylesheet">
 <script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script>
 <style>
-  :root { --bg: #0d1117; --card: #161b22; --border: #30363d; --text: #e6edf3; --muted: #8b949e;
-          --green: #3fb950; --red: #f85149; --orange: #d29922; --blue: #58a6ff; }
-  body { background: var(--bg); color: var(--text); font-family: -apple-system, BlinkMacSystemFont, sans-serif; }
-  .card { background: var(--card); border: 1px solid var(--border); border-radius: 10px; }
-  .hero-regime { font-size: 3rem; font-weight: 700; }
-  .hero-conf { font-size: 1.2rem; color: var(--muted); }
-  .factor-value { font-size: 2.2rem; font-weight: 700; color: var(--text); }
-  .factor-label { color: var(--muted); font-size: 0.85rem; }
-  .regime-TREND { color: var(--green); }
-  .regime-RANGE { color: var(--orange); }
-  .regime-PANIC { color: var(--red); }
-  .bucket-EXTREME, .bucket-STRONG { color: var(--green); }
-  .bucket-NORMAL { color: var(--orange); }
-  .bucket-WEAK, .bucket-PANIC { color: var(--red); }
-  .badge-regime { font-size: 0.85rem; padding: 4px 12px; border-radius: 20px; }
-  .badge-TREND { background: #1a3a1a; color: var(--green); }
-  .badge-RANGE { background: #3a2a0a; color: var(--orange); }
-  .badge-PANIC { background: #3a0a0a; color: var(--red); }
-  .narrative { color: var(--muted); font-size: 0.9rem; }
-  canvas { max-height: 300px; }
-  .text-muted { color: var(--muted) !important; }
-  .table { color: var(--text); }
-  .table-dark { --bs-table-color: var(--text); --bs-table-bg: var(--card); }
-  .form-select { background-color: var(--card); color: var(--text); border-color: var(--border); }
-  .btn-primary { background-color: var(--blue); border-color: var(--blue); }
-  strong { color: var(--text); }
-  small { color: var(--muted); }
+  * { margin: 0; padding: 0; box-sizing: border-box; }
+  body { background: #0a0e14; color: #c9d1d9; font-family: -apple-system, BlinkMacSystemFont, "SF Mono", monospace; }
+  .app { max-width: 1200px; margin: 0 auto; padding: 20px 24px; }
+
+  /* Header */
+  .header { display: flex; justify-content: space-between; align-items: flex-end; padding: 20px 0 28px;
+            border-bottom: 1px solid #1c2333; margin-bottom: 24px; }
+  .header h1 { font-size: 22px; font-weight: 600; letter-spacing: 1px; }
+  .header h1 span { color: #58a6ff; }
+  .header .time { color: #5c6675; font-size: 13px; }
+  .dot { display: inline-block; width: 7px; height: 7px; border-radius: 50%; background: #3fb950;
+         margin-right: 6px; animation: pulse 2s infinite; }
+  @keyframes pulse { 0%,100%{opacity:1} 50%{opacity:0.4} }
+
+  /* Regime Hero */
+  .hero { display: flex; gap: 16px; margin-bottom: 24px; }
+  .hero-card { flex: 1; background: #11161e; border: 1px solid #1c2333; border-radius: 8px; padding: 20px 24px; }
+  .hero-card.main { flex: 2; display: flex; align-items: center; gap: 28px; }
+  .regime-badge { display: inline-block; padding: 5px 16px; border-radius: 4px; font-size: 13px;
+                  font-weight: 600; letter-spacing: 2px; }
+  .regime-badge.trend { background: rgba(63,185,80,0.12); color: #3fb950; border: 1px solid rgba(63,185,80,0.3); }
+  .regime-badge.range { background: rgba(210,153,34,0.12); color: #d29922; border: 1px solid rgba(210,153,34,0.3); }
+  .regime-badge.panic { background: rgba(248,81,73,0.12); color: #f85149; border: 1px solid rgba(248,81,73,0.3); }
+  .regime-name { font-size: 42px; font-weight: 700; letter-spacing: 2px; }
+  .regime-name.trend { color: #3fb950; }
+  .regime-name.range { color: #d29922; }
+  .regime-name.panic { color: #f85149; }
+  .hero-stat { text-align: center; }
+  .hero-stat .val { font-size: 28px; font-weight: 600; color: #e6edf3; }
+  .hero-stat .lbl { font-size: 11px; color: #5c6675; letter-spacing: 1px; margin-top: 4px; }
+
+  /* Factor Grid */
+  .grid { display: grid; grid-template-columns: repeat(4, 1fr); gap: 12px; margin-bottom: 24px; }
+  .fcard { background: #11161e; border: 1px solid #1c2333; border-radius: 8px; padding: 18px 20px; }
+  .fcard .title { font-size: 11px; color: #5c6675; letter-spacing: 1.5px; margin-bottom: 10px; }
+  .fcard .score { font-size: 38px; font-weight: 700; margin-bottom: 4px; }
+  .fcard .sub { font-size: 12px; color: #5c6675; }
+  .fcard .bar-wrap { height: 3px; background: #1c2333; border-radius: 2px; margin-top: 12px; }
+  .fcard .bar { height: 100%; border-radius: 2px; transition: width 0.6s; }
+
+  /* Charts */
+  .charts { display: grid; grid-template-columns: 1fr 1fr; gap: 12px; margin-bottom: 24px; }
+  .chart-box { background: #11161e; border: 1px solid #1c2333; border-radius: 8px; padding: 18px 20px; }
+  .chart-box h3 { font-size: 12px; color: #5c6675; letter-spacing: 1.5px; margin-bottom: 14px; }
+  .chart-box canvas { max-height: 260px; }
+
+  /* Expectancy */
+  .exp { background: #11161e; border: 1px solid #1c2333; border-radius: 8px; padding: 18px 20px; }
+  .exp h3 { font-size: 12px; color: #5c6675; letter-spacing: 1.5px; margin-bottom: 14px; }
+  .exp-row { display: flex; gap: 12px; align-items: center; margin-bottom: 14px; }
+  .exp select { background: #0a0e14; color: #c9d1d9; border: 1px solid #1c2333; padding: 6px 12px;
+                border-radius: 4px; font-size: 13px; }
+  .exp button { background: #1c3a5c; color: #58a6ff; border: 1px solid #2d4f7c; padding: 6px 18px;
+                border-radius: 4px; cursor: pointer; font-size: 13px; }
+  .exp button:hover { background: #254d7a; }
+  .exp .suff { font-size: 11px; padding: 3px 10px; border-radius: 3px; }
+  .suff-HIGH { background: rgba(63,185,80,0.12); color: #3fb950; }
+  .suff-MEDIUM { background: rgba(210,153,34,0.12); color: #d29922; }
+  .suff-LOW { background: rgba(248,81,73,0.12); color: #f85149; }
+  .suff-INSUFFICIENT { background: rgba(92,102,117,0.12); color: #5c6675; }
+  table { width: 100%; border-collapse: collapse; font-size: 13px; }
+  th { text-align: left; color: #5c6675; font-weight: 500; padding: 8px 10px; border-bottom: 1px solid #1c2333; }
+  td { padding: 7px 10px; border-bottom: 1px solid #0e1219; color: #8b949e; }
+  td strong { color: #e6edf3; }
+  .exp-summary { margin-top: 14px; font-size: 13px; color: #8b949e; padding: 10px 14px;
+                 background: #0d1117; border-radius: 6px; border-left: 3px solid #58a6ff; }
+  .exp-summary strong { color: #e6edf3; }
 </style>
 </head>
 <body>
-<div class="container-fluid py-3 px-4">
+<div class="app">
 
   <!-- Header -->
-  <div class="d-flex justify-content-between align-items-center mb-4">
+  <div class="header">
     <div>
-      <h4 class="mb-0">ChanMacro <span class="text-muted fs-6">市场状态</span></h4>
-      <small class="text-muted" id="update-time"></small>
-    </div>
-    <div>
-      <span class="badge bg-secondary" id="db-status">加载中...</span>
+      <h1><span>Chan</span>Macro</h1>
     </div>
+    <div class="time"><span class="dot"></span> <span id="update-time">加载中...</span></div>
   </div>
 
-  <!-- Hero: Regime -->
-  <div class="card p-4 mb-3 text-center">
-    <div class="hero-conf mb-1">当前制度</div>
-    <div class="hero-regime" id="hero-regime">—</div>
-    <div>
-      <span class="badge-regime" id="hero-badge">—</span>
-      <span class="ms-2" style="color:#8b949e">置信度 <strong id="hero-conf" style="color:#e6edf3">—</strong></span>
-      <span class="ms-2" style="color:#8b949e">成熟度 <strong id="hero-maturity" style="color:#e6edf3">—</strong></span>
+  <!-- Regime Hero -->
+  <div class="hero">
+    <div class="hero-card main">
+      <div>
+        <div class="regime-badge" id="hero-badge">—</div>
+        <div class="regime-name" id="hero-regime">—</div>
+      </div>
+      <div style="display:flex; gap:32px; margin-left:auto;">
+        <div class="hero-stat"><div class="val" id="hero-conf">—</div><div class="lbl">置信度</div></div>
+        <div class="hero-stat"><div class="val" id="hero-maturity">—</div><div class="lbl">成熟度</div></div>
+      </div>
+    </div>
+    <div class="hero-card" style="flex:1">
+      <div class="hero-stat"><div class="val" id="hero-ps">—</div><div class="lbl">价格结构</div></div>
+    </div>
+    <div class="hero-card" style="flex:1">
+      <div class="hero-stat"><div class="val" id="hero-br">—</div><div class="lbl">市场广度</div></div>
     </div>
   </div>
 
   <!-- 4 Factor Cards -->
-  <div class="row g-3 mb-3">
-    <div class="col-md-3">
-      <div class="card p-3 h-100">
-        <div class="factor-label">价格结构</div>
-        <div class="factor-value" id="f-price">—</div>
-        <div class="text-muted small" id="f-price-sub"></div>
-        <div class="narrative mt-1" id="f-price-narr"></div>
-      </div>
+  <div class="grid">
+    <div class="fcard">
+      <div class="title">价格结构 PRICE STRUCTURE</div>
+      <div class="score" id="f-price">—</div>
+      <div class="sub" id="f-price-sub"></div>
+      <div class="bar-wrap"><div class="bar" id="bar-price"></div></div>
     </div>
-    <div class="col-md-3">
-      <div class="card p-3 h-100">
-        <div class="factor-label">市场广度</div>
-        <div class="factor-value" id="f-breadth">—</div>
-        <div class="text-muted small" id="f-breadth-sub"></div>
-        <div class="narrative mt-1" id="f-breadth-narr"></div>
-      </div>
+    <div class="fcard">
+      <div class="title">市场广度 BREADTH</div>
+      <div class="score" id="f-breadth">—</div>
+      <div class="sub" id="f-breadth-sub"></div>
+      <div class="bar-wrap"><div class="bar" id="bar-breadth"></div></div>
     </div>
-    <div class="col-md-3">
-      <div class="card p-3 h-100">
-        <div class="factor-label">OI 状态</div>
-        <div class="factor-value fs-4" id="f-oi">—</div>
-        <div class="text-muted small" id="f-oi-sub"></div>
-        <div class="narrative mt-1" id="f-oi-narr"></div>
-      </div>
+    <div class="fcard">
+      <div class="title">持仓状态 OI MATRIX</div>
+      <div class="score" id="f-oi" style="font-size:24px">—</div>
+      <div class="sub" id="f-oi-sub"></div>
     </div>
-    <div class="col-md-3">
-      <div class="card p-3 h-100">
-        <div class="factor-label">波动率</div>
-        <div class="factor-value" id="f-vol">—</div>
-        <div class="text-muted small" id="f-vol-sub"></div>
-      </div>
+    <div class="fcard">
+      <div class="title">波动率 VOLATILITY</div>
+      <div class="score" id="f-vol">—</div>
+      <div class="sub" id="f-vol-sub"></div>
+      <div class="bar-wrap"><div class="bar" id="bar-vol"></div></div>
     </div>
   </div>
 
-  <!-- Charts Row -->
-  <div class="row g-3 mb-3">
-    <div class="col-md-6">
-      <div class="card p-3">
-        <h6 class="mb-3">制度历史</h6>
-        <canvas id="chart-regime"></canvas>
-      </div>
-    </div>
-    <div class="col-md-6">
-      <div class="card p-3">
-        <h6 class="mb-3">市场广度</h6>
-        <canvas id="chart-breadth"></canvas>
-      </div>
-    </div>
+  <!-- Charts -->
+  <div class="charts">
+    <div class="chart-box"><h3>制度历史 REGIME HISTORY</h3><canvas id="chart-regime"></canvas></div>
+    <div class="chart-box"><h3>市场广度 BREADTH</h3><canvas id="chart-breadth"></canvas></div>
   </div>
 
   <!-- Expectancy -->
-  <div class="card p-3">
-    <h6 class="mb-3">信号期望查询</h6>
-    <div class="row g-2 align-items-end">
-      <div class="col-auto">
-        <select class="form-select form-select-sm" id="exp-signal">
-          <option value="B3">B3 (三买)</option><option value="B2">B2 (二买)</option><option value="B1">B1 (一买)</option>
-          <option value="S3">S3 (三卖)</option><option value="S2">S2 (二卖)</option><option value="S1">S1 (一卖)</option>
-        </select>
-      </div>
-      <div class="col-auto">
-        <button class="btn btn-sm btn-primary" onclick="loadExpectancy()">查询</button>
-      </div>
-      <div class="col-auto">
-        <span class="badge bg-secondary" id="exp-sufficiency">—</span>
-      </div>
+  <div class="exp">
+    <h3>信号期望 SIGNAL EXPECTANCY</h3>
+    <div class="exp-row">
+      <select id="exp-signal">
+        <option value="B3">B3 · 三买</option><option value="B2">B2 · 二买</option><option value="B1">B1 · 一买</option>
+        <option value="S3">S3 · 三卖</option><option value="S2">S2 · 二卖</option><option value="S1">S1 · 一卖</option>
+      </select>
+      <button onclick="loadExpectancy()">查询</button>
+      <span class="suff" id="exp-sufficiency">—</span>
     </div>
-    <div class="table-responsive mt-2">
-      <table class="table table-sm table-dark mb-0" style="--bs-table-bg:#161b22">
-        <thead><tr><th>层级</th><th>样本</th><th>有效样本</th><th>原始胜率</th><th>后验胜率</th><th>平均收益</th></tr></thead>
-        <tbody id="exp-layers"></tbody>
-      </table>
-    </div>
-    <div class="mt-2 text-muted small" id="exp-summary"></div>
+    <table>
+      <thead><tr><th>层级</th><th>样本</th><th>有效样本</th><th>原始胜率</th><th>后验胜率</th><th>平均收益</th></tr></thead>
+      <tbody id="exp-layers"></tbody>
+    </table>
+    <div class="exp-summary" id="exp-summary"></div>
   </div>
 </div>
 

bsp_monitor/twitter_web.py

@@ -0,0 +1,380 @@
+#!/usr/bin/env python3
+"""
+twitter_web.py — Twitter 监控账号管理 Web 界面。
+单文件，零依赖，只用到 Python 标准库。
+"""
+
+import json
+import os
+import sys
+import re
+from datetime import datetime, timezone
+from http.server import HTTPServer, BaseHTTPRequestHandler
+from urllib.parse import urlparse, parse_qs
+
+SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
+WATCHLIST_PATH = os.path.join(SCRIPT_DIR, "twitter_watchlist.json")
+STATE_PATH = os.path.join(SCRIPT_DIR, "twitter_state.json")
+
+PORT = int(sys.argv[1]) if len(sys.argv) > 1 else 8010
+
+
+def extract_username(value: str) -> str:
+    value = value.strip().rstrip("/")
+    if value.startswith("@"):
+        return value[1:]
+    for pattern in [r"(?:twitter\.com|x\.com)/(\w+)(?:/|$)", r"/(\w+)$"]:
+        m = re.search(pattern, value)
+        if m:
+            return m.group(1)
+    if re.match(r"^\w+$", value):
+        return value
+    raise ValueError(f"无法提取用户名: {value}")
+
+
+def load_json(path):
+    if os.path.exists(path):
+        with open(path) as f:
+            return json.load(f)
+    return {}
+
+
+def save_json(path, data):
+    with open(path, "w") as f:
+        json.dump(data, f, indent=2, ensure_ascii=False)
+
+
+def get_watchlist():
+    return load_json(WATCHLIST_PATH).get("users", [])
+
+
+def save_watchlist(users):
+    save_json(WATCHLIST_PATH, {"users": users})
+
+
+def get_state():
+    return load_json(STATE_PATH)
+
+
+HTML = """<!DOCTYPE html>
+<html lang="zh">
+<head>
+<!-- Google tag (gtag.js) -->
+<script async src="https://www.googletagmanager.com/gtag/js?id=G-LVVXH3TL04"></script>
+<script>
+  window.dataLayer = window.dataLayer || [];
+  function gtag(){dataLayer.push(arguments);}
+  gtag('js', new Date());
+  gtag('config', 'G-LVVXH3TL04');
+</script>
+<meta charset="UTF-8">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+<title>Twitter 监控管理</title>
+<style>
+  :root {
+    --bg: #0d1117; --card: #161b22; --border: #30363d;
+    --text: #c9d1d9; --muted: #8b949e; --accent: #58a6ff;
+    --green: #3fb950; --red: #f85149; --yellow: #d2991d;
+  }
+  * { margin:0; padding:0; box-sizing:border-box; }
+  body { font:14px/1.6 -apple-system,BlinkMacSystemFont,"Segoe UI",sans-serif;
+         background:var(--bg); color:var(--text); padding:24px; max-width:680px; margin:auto; }
+  h1 { font-size:20px; margin-bottom:4px; }
+  .sub { color:var(--muted); font-size:12px; margin-bottom:20px; }
+  .add-bar { display:flex; gap:8px; margin-bottom:20px; }
+  .add-bar input { flex:1; padding:8px 12px; border:1px solid var(--border);
+    border-radius:6px; background:var(--card); color:var(--text); font-size:14px; outline:none; }
+  .add-bar input:focus { border-color:var(--accent); }
+  .add-bar input::placeholder { color:var(--muted); }
+  button { padding:8px 16px; border:none; border-radius:6px; cursor:pointer; font-size:13px;
+    font-weight:500; transition:opacity .15s; }
+  button:hover { opacity:0.85; }
+  .btn-add { background:var(--accent); color:#fff; }
+  .btn-edit, .btn-save { background:var(--yellow); color:#000; }
+  .btn-del { background:var(--red); color:#fff; }
+  .btn-cancel { background:var(--border); color:var(--text); }
+  .account { background:var(--card); border:1px solid var(--border); border-radius:8px;
+    padding:12px 16px; margin-bottom:8px; display:flex; align-items:center; gap:12px; }
+  .account .name { font-weight:600; min-width:160px; }
+  .account .name a { color:var(--accent); text-decoration:none; }
+  .account .name a:hover { text-decoration:underline; }
+  .account .meta { font-size:12px; color:var(--muted); flex:1; }
+  .account .actions { display:flex; gap:6px; flex-shrink:0; }
+  .edit-row { display:flex; gap:6px; align-items:center; width:100%; }
+  .edit-row input { flex:1; padding:6px 10px; border:1px solid var(--accent);
+    border-radius:4px; background:var(--bg); color:var(--text); font-size:13px; outline:none; }
+  .badge { display:inline-block; font-size:11px; padding:2px 8px; border-radius:10px;
+    background:var(--green); color:#000; margin-left:6px; }
+  .empty { text-align:center; padding:60px 20px; color:var(--muted); }
+  .empty p { margin-bottom:8px; }
+  .toast { position:fixed; bottom:20px; right:20px; padding:10px 20px; border-radius:6px;
+    font-size:13px; color:#fff; opacity:0; transition:opacity .3s; z-index:100; }
+  .toast.show { opacity:1; }
+  .toast.ok { background:var(--green); }
+  .toast.err { background:var(--red); }
+</style>
+</head>
+<body>
+<h1>🐦 Twitter 账号监控</h1>
+<p class="sub">管理 twitterapi.io 监控账号 · 增删改查</p>
+
+<div class="add-bar">
+  <input id="urlInput" type="text" placeholder="输入 Twitter/X 链接或用户名..." autofocus>
+  <button class="btn-add" onclick="addAccount()">➕ 添加</button>
+</div>
+
+<div id="list"></div>
+
+<div class="toast" id="toast"></div>
+
+<script>
+const API = '/twitter/api/accounts';
+let editing = null;
+
+async function api(method, path='', body=null) {
+  const opts = { method, headers:{} };
+  if (body) { opts.headers['Content-Type']='application/json'; opts.body=JSON.stringify(body); }
+  const r = await fetch(API + path, opts);
+  const data = await r.json();
+  if (!r.ok) throw new Error(data.error || '请求失败');
+  return data;
+}
+
+function toast(msg, ok=true) {
+  const t = document.getElementById('toast');
+  t.textContent = msg; t.className = 'toast ' + (ok?'ok':'err') + ' show';
+  setTimeout(() => t.classList.remove('show'), 2500);
+}
+
+async function load() {
+  const data = await api('GET');
+  const div = document.getElementById('list');
+  if (!data.accounts.length) {
+    div.innerHTML = '<div class="empty"><p>📭 暂无监控账号</p><p style="font-size:12px;color:var(--muted)">在上方输入 Twitter/X 链接或用户名添加</p></div>';
+    return;
+  }
+  div.innerHTML = data.accounts.map(a => `
+    <div class="account" id="row-${a.username}">
+      ${editing===a.username ? `
+        <div class="edit-row">
+          <input id="editInput" value="${esc(a.display_name || a.username)}" placeholder="备注名称">
+          <button class="btn-save" onclick="saveEdit('${esc(a.username)}')">保存</button>
+          <button class="btn-cancel" onclick="cancelEdit()">取消</button>
+        </div>
+      ` : `
+        <div class="name">
+          <a href="https://x.com/${esc(a.username)}" target="_blank">@${esc(a.username)}</a>
+          ${a.display_name && a.display_name !== a.username ? `<span style="color:var(--text)">(${esc(a.display_name)})</span>` : ''}
+        </div>
+        <div class="meta">
+          添加: ${a.added_at?.slice(0,10) || '?'}
+          ${a.last_check ? ` · 上次检查: ${a.last_check}` : ''}
+        </div>
+        <div class="actions">
+          <button class="btn-edit" onclick="startEdit('${esc(a.username)}','${esc(a.display_name||a.username)}')">✏️</button>
+          <button class="btn-del" onclick="removeAccount('${esc(a.username)}')">🗑</button>
+        </div>
+      `}
+    </div>
+  `).join('');
+}
+
+function esc(s) { return s.replace(/&/g,'&amp;').replace(/"/g,'&quot;').replace(/</g,'&lt;').replace(/>/g,'&gt;').replace(/'/g,'&#39;'); }
+
+async function addAccount() {
+  const inp = document.getElementById('urlInput');
+  const val = inp.value.trim();
+  if (!val) { toast('请输入链接或用户名', false); return; }
+  try {
+    const r = await api('POST', '', {url: val});
+    toast(r.message || '添加成功');
+    inp.value = '';
+    load();
+  } catch(e) { toast(e.message, false); }
+}
+
+async function removeAccount(username) {
+  if (!confirm(`确定删除 @${username}？`)) return;
+  try {
+    const r = await api('DELETE', '/' + username);
+    toast(r.message || '已删除');
+    load();
+  } catch(e) { toast(e.message, false); }
+}
+
+function startEdit(username, name) {
+  editing = username;
+  load();
+  setTimeout(() => {
+    const inp = document.getElementById('editInput');
+    if (inp) { inp.focus(); inp.select(); }
+  }, 50);
+}
+
+function cancelEdit() { editing = null; load(); }
+
+async function saveEdit(username) {
+  const val = document.getElementById('editInput').value.trim();
+  editing = null;
+  try {
+    const r = await api('PUT', '/' + username, {display_name: val});
+    toast(r.message || '已更新');
+    load();
+  } catch(e) { toast(e.message, false); }
+}
+
+document.getElementById('urlInput').addEventListener('keydown', e => {
+  if (e.key === 'Enter') addAccount();
+});
+
+load();
+</script>
+</body>
+</html>"""
+
+
+class Handler(BaseHTTPRequestHandler):
+    def log_message(self, format, *args):
+        pass  # silent
+
+    def _send(self, code, body, content_type="application/json"):
+        body = body.encode() if isinstance(body, str) else json.dumps(body, ensure_ascii=False).encode()
+        self.send_response(code)
+        self.send_header("Content-Type", content_type + "; charset=utf-8")
+        self.send_header("Content-Length", str(len(body)))
+        self.send_header("Access-Control-Allow-Origin", "*")
+        self.end_headers()
+        self.wfile.write(body)
+
+    def _json(self, code, data):
+        self._send(code, data)
+
+    def _error(self, code, msg):
+        self._json(code, {"error": msg})
+
+    def do_OPTIONS(self):
+        self.send_response(204)
+        self.send_header("Access-Control-Allow-Origin", "*")
+        self.send_header("Access-Control-Allow-Methods", "GET,POST,PUT,DELETE,OPTIONS")
+        self.send_header("Access-Control-Allow-Headers", "Content-Type")
+        self.end_headers()
+
+    def do_GET(self):
+        path = urlparse(self.path).path
+        if path == "/" or path == "/index.html":
+            self._send(200, HTML, "text/html")
+            return
+        if path.startswith("/api/accounts"):
+            username = path[len("/api/accounts"):].strip("/")
+            if username:
+                # GET /api/accounts/<username> — single account
+                users = get_watchlist()
+                state = get_state()
+                for u in users:
+                    if u["username"].lower() == username.lower():
+                        entry = dict(u)
+                        entry["last_check"] = state.get(u["username"], {}).get("last_check")
+                        self._json(200, entry)
+                        return
+                self._error(404, "账号不存在")
+                return
+            # GET /api/accounts — list all
+            users = get_watchlist()
+            state = get_state()
+            accounts = []
+            for u in users:
+                entry = dict(u)
+                sc = state.get(u["username"], {})
+                ts = sc.get("last_check")
+                if ts:
+                    try:
+                        ts = datetime.fromisoformat(ts).strftime("%m-%d %H:%M")
+                    except Exception:
+                        pass
+                else:
+                    ts = "从未"
+                entry["last_check"] = ts
+                accounts.append(entry)
+            self._json(200, {"accounts": accounts})
+        else:
+            self._error(404, "Not Found")
+
+    def do_POST(self):
+        path = urlparse(self.path).path
+        if path != "/api/accounts":
+            self._error(404, "Not Found")
+            return
+        length = int(self.headers.get("Content-Length", 0))
+        body = json.loads(self.rfile.read(length)) if length else {}
+        url = body.get("url", "").strip()
+        if not url:
+            self._error(400, "缺少 url 参数")
+            return
+        try:
+            username = extract_username(url)
+        except ValueError:
+            self._error(400, "无法从输入中提取用户名，请输入 Twitter/X 链接或 @用户名")
+            return
+
+        users = get_watchlist()
+        if any(u["username"].lower() == username.lower() for u in users):
+            self._error(409, f"@{username} 已在监控列表中")
+            return
+
+        display_name = body.get("display_name", "").strip() or username
+        users.append({
+            "username": username,
+            "display_name": display_name,
+            "added_at": datetime.now(timezone.utc).isoformat(),
+        })
+        save_watchlist(users)
+        self._json(201, {"message": f"✅ 已添加 @{username}", "username": username})
+
+    def do_PUT(self):
+        path = urlparse(self.path).path
+        username = path[len("/api/accounts"):].strip("/")
+        if not username:
+            self._error(400, "缺少用户名")
+            return
+        length = int(self.headers.get("Content-Length", 0))
+        body = json.loads(self.rfile.read(length)) if length else {}
+        display_name = body.get("display_name", "").strip()
+
+        users = get_watchlist()
+        for u in users:
+            if u["username"].lower() == username.lower():
+                if display_name:
+                    u["display_name"] = display_name
+                save_watchlist(users)
+                self._json(200, {"message": f"✅ @{username} 已更新"})
+                return
+        self._error(404, "账号不存在")
+
+    def do_DELETE(self):
+        path = urlparse(self.path).path
+        username = path[len("/api/accounts"):].strip("/")
+        if not username:
+            self._error(400, "缺少用户名")
+            return
+        users = get_watchlist()
+        before = len(users)
+        users = [u for u in users if u["username"].lower() != username.lower()]
+        if len(users) < before:
+            save_watchlist(users)
+            self._json(200, {"message": f"🗑 已移除 @{username}"})
+        else:
+            self._error(404, "账号不存在")
+
+
+def main():
+    print(f"🐦 Twitter 监控管理: http://0.0.0.0:{PORT}")
+    server = HTTPServer(("0.0.0.0", PORT), Handler)
+    try:
+        server.serve_forever()
+    except KeyboardInterrupt:
+        print("\n已停止")
+        server.server_close()
+
+
+if __name__ == "__main__":
+    main()

data_provider/api_docs.html

@@ -1,6 +1,14 @@
 <!DOCTYPE html>
 <html lang="zh-CN">
 <head>
+<!-- Google tag (gtag.js) -->
+<script async src="https://www.googletagmanager.com/gtag/js?id=G-LVVXH3TL04"></script>
+<script>
+  window.dataLayer = window.dataLayer || [];
+  function gtag(){dataLayer.push(arguments);}
+  gtag('js', new Date());
+  gtag('config', 'G-LVVXH3TL04');
+</script>
 <meta charset="UTF-8">
 <meta name="viewport" content="width=device-width, initial-scale=1.0">
 <title>Chan 数据提供商 - API 文档</title>

data_provider/homepage.html

@@ -1,6 +1,14 @@
 <!DOCTYPE html>
 <html lang="zh-CN">
 <head>
+<!-- Google tag (gtag.js) -->
+<script async src="https://www.googletagmanager.com/gtag/js?id=G-LVVXH3TL04"></script>
+<script>
+  window.dataLayer = window.dataLayer || [];
+  function gtag(){dataLayer.push(arguments);}
+  gtag('js', new Date());
+  gtag('config', 'G-LVVXH3TL04');
+</script>
 <meta charset="UTF-8">
 <meta name="viewport" content="width=device-width, initial-scale=1.0">
 <title>Chan 数据提供商</title>

data_provider/main.py

@@ -24,6 +24,12 @@ from fastapi.responses import HTMLResponse
 import uvicorn
 from technical.util import resample_to_interval
 
+from onchain_metrics import (
+    OnchainMetricsManager,
+    api_keys_from_env,
+    create_onchain_router,
+)
+
 # docker compose logs --tail=200
 # docker compose down && docker compose build --no-cache && docker compose up -d
 
@@ -1132,6 +1138,13 @@ def create_app(provider: DataProvider) -> FastAPI:
     """构造 FastAPI 应用：lifespan 内同步 initialize 并启动后台拉数；WebSocket 实时推送。"""
     ws_manager = WebSocketManager()
 
+    # 初始化链上指标模块
+    onchain_manager = OnchainMetricsManager(
+        data_dir=provider.data_dir,
+        api_keys=api_keys_from_env(),
+    )
+    onchain_router = create_onchain_router(onchain_manager)
+
     def _on_data_update(symbol: str, base_tf: str) -> None:
         """后台刷新线程回调：广播基础及衍生周期更新给 WebSocket 订阅者。"""
         with provider._lock:
@@ -1165,9 +1178,12 @@ def create_app(provider: DataProvider) -> FastAPI:
         provider.start_background_workers()
         # 启动 WebSocket 实时监听（asyncio 后台任务）
         provider.start_watch_tasks()
+        # 启动链上指标后台刷新
+        onchain_manager.start()
         try:
             yield
         finally:
+            onchain_manager.stop()
             provider.stop()
 
     app = FastAPI(title="Chan 数据提供商", version="1.0.0", lifespan=lifespan)
@@ -1180,6 +1196,9 @@ def create_app(provider: DataProvider) -> FastAPI:
         allow_headers=["*"],
     )
 
+    # 注册链上指标 API
+    app.include_router(onchain_router)
+
     @app.get("/health")
     async def health() -> Dict[str, object]:
         """存活检查：交易所、交易对、基础/衍生周期、是否已完成冷启动。"""
@@ -1291,6 +1310,14 @@ def create_app(provider: DataProvider) -> FastAPI:
         return f"""<!DOCTYPE html>
 <html lang="zh-CN">
 <head>
+    <!-- Google tag (gtag.js) -->
+    <script async src="https://www.googletagmanager.com/gtag/js?id=G-LVVXH3TL04"></script>
+    <script>
+      window.dataLayer = window.dataLayer || [];
+      function gtag(){{dataLayer.push(arguments);}}
+      gtag('js', new Date());
+      gtag('config', 'G-LVVXH3TL04');
+    </script>
     <meta charset="utf-8">
     <meta name="viewport" content="width=device-width, initial-scale=1.0">
     <title>Data Provider — API Manual</title>
@@ -1347,6 +1374,7 @@ def create_app(provider: DataProvider) -> FastAPI:
     <ul class="nav nav-pills mb-4" id="manualTabs" role="tablist">
         <li class="nav-item"><button class="nav-link active" data-section="overview">Overview</button></li>
         <li class="nav-item"><button class="nav-link" data-section="rest">REST API</button></li>
+        <li class="nav-item"><button class="nav-link" data-section="onchain">Onchain Metrics</button></li>
         <li class="nav-item"><button class="nav-link" data-section="ws">WebSocket</button></li>
         <li class="nav-item"><button class="nav-link" data-section="timeframes">Timeframes</button></li>
         <li class="nav-item"><button class="nav-link" data-section="config">Configuration</button></li>
@@ -1421,6 +1449,9 @@ def create_app(provider: DataProvider) -> FastAPI:
                         <tr><td><span class="method-badge method-GET">GET</span></td><td class="endpoint-path">/health</td><td>Structured health check (JSON)</td></tr>
                         <tr><td><span class="method-badge method-GET">GET</span></td><td class="endpoint-path">/timeframes</td><td>List available base &amp; derived timeframes</td></tr>
                         <tr><td><span class="method-badge method-GET">GET</span></td><td class="endpoint-path">/api/candles</td><td>Fetch OHLCV candles</td></tr>
+                        <tr><td><span class="method-badge method-GET">GET</span></td><td class="endpoint-path">/api/derivatives</td><td>Funding rate, OI, basis</td></tr>
+                        <tr><td><span class="method-badge method-GET">GET</span></td><td class="endpoint-path">/api/onchain/metrics</td><td>On-chain metric time series</td></tr>
+                        <tr><td><span class="method-badge method-GET">GET</span></td><td class="endpoint-path">/api/onchain/latest</td><td>Latest on-chain snapshot</td></tr>
                         <tr><td><span class="method-badge method-WS">WS</span></td><td class="endpoint-path">/ws</td><td>Real-time K-line streaming</td></tr>
                         <tr><td><span class="method-badge method-GET">GET</span></td><td class="endpoint-path">/api-manual</td><td>This page</td></tr>
                     </tbody>
@@ -1520,6 +1551,117 @@ def create_app(provider: DataProvider) -> FastAPI:
         </div>
     </div>
 
+    <!-- ==================== ONCHAIN METRICS ==================== -->
+    <div class="section" id="section-onchain">
+
+        <h5 class="mb-3"><span class="method-badge method-GET">GET</span> /api/onchain/latest</h5>
+        <div class="card endpoint-card">
+            <div class="card-body">
+                <p class="small">获取全部链上指标最新快照。</p>
+                <p><strong>Response</strong> <span class="text-muted small">200 OK</span></p>
+                <pre><code>{{
+  "timestamp": 1704067200000,
+  "btc_netflow": {{
+    "timestamp": 1704067200000,
+    "datetime": "2024-01-01T00:00:00Z",
+    "value": -33361122.64,
+    "sub_value": 1366105343.72,
+    "extra": {{ "inflow_usd": 1366105343.72, "outflow_usd": 1399466466.36 }}
+  }},
+  "stablecoin_supply": {{
+    "timestamp": 1704067200000,
+    "datetime": "2024-01-01T00:00:00Z",
+    "value": 276932114785,
+    "sub_value": 276.93,
+    "extra": {{ "USDT": 184419658464, "USDC": 73258860594, "DAI": 4625356465 }}
+  }},
+  "etf_flow": {{
+    "timestamp": 1704067200000,
+    "datetime": "2024-01-01T00:00:00Z",
+    "value": -296.0,
+    "sub_value": -296000000.0,
+    "extra": {{ "total_million_usd": -296.0, "breakdown": {{ "IBIT": -219.4, "GBTC": -62.8 }} }}
+  }},
+  "mvrv_zscore": {{
+    "timestamp": 1704067200000,
+    "datetime": "2024-01-01T00:00:00Z",
+    "value": -1.3895,
+    "sub_value": 1.1321,
+    "extra": {{ "mvrv_ratio": 1.1321, "rolling_mean": 1.6787, "rolling_stddev": 0.3934 }}
+  }},
+  "sopr": null
+}}</code></pre>
+                <p class="small text-muted">4个免费指标 (netflow/stablecoin/etf/mvrv) 每5分钟自动刷新。SOPR 需 Glassnode API key。</p>
+                <button class="btn btn-sm btn-outline-secondary" onclick="fetch('/api/onchain/latest').then(r=>r.json()).then(d=>alert(JSON.stringify(d,null,2)))">Try it</button>
+            </div>
+        </div>
+
+        <h5 class="mb-3 mt-4"><span class="method-badge method-GET">GET</span> /api/onchain/metrics</h5>
+        <div class="card endpoint-card">
+            <div class="card-body">
+                <p class="small">获取单个链上指标的时间序列。</p>
+                <p><strong>Query Parameters</strong></p>
+                <table class="table table-bordered table-sm">
+                    <thead class="table-light"><tr><th>Param</th><th>Type</th><th>Required</th><th>Default</th><th>Description</th></tr></thead>
+                    <tbody>
+                        <tr><td><code>metric</code></td><td>string</td><td><span class="param-required">Yes</span></td><td>—</td><td>指标: btc_netflow, stablecoin_supply, etf_flow, mvrv_zscore, sopr</td></tr>
+                        <tr><td><code>limit</code></td><td>int</td><td>No</td><td><code>100</code></td><td>返回条数上限 (1-5000)</td></tr>
+                        <tr><td><code>start</code></td><td>int</td><td>No</td><td>—</td><td>起始时间戳(ms)</td></tr>
+                        <tr><td><code>end</code></td><td>int</td><td>No</td><td>—</td><td>结束时间戳(ms)</td></tr>
+                    </tbody>
+                </table>
+                <p><strong>cURL Example</strong></p>
+                <pre><code>curl "http://localhost:80/api/onchain/metrics?metric=btc_netflow&limit=10"
+curl "http://localhost:80/api/onchain/metrics?metric=mvrv_zscore&start=1704067200000&end=1711929600000"</code></pre>
+            </div>
+        </div>
+
+        <h5 class="mb-3 mt-4"><span class="method-badge method-GET">GET</span> /api/onchain/available</h5>
+        <div class="card endpoint-card">
+            <div class="card-body">
+                <p class="small">列出所有指标及其数据量、时间范围。</p>
+                <pre><code>{{
+  "btc_netflow": {{"count": 4015, "has_data": true, "first_ts": "2024-01-01T00:00:00Z", "last_ts": "2026-07-01T00:00:00Z"}},
+  "stablecoin_supply": {{"count": 2, "has_data": true, ...}},
+  "etf_flow": {{"count": 12, "has_data": true, ...}},
+  "mvrv_zscore": {{"count": 4036, "has_data": true, ...}},
+  "sopr": {{"count": 0, "has_data": false, ...}}
+}}</code></pre>
+            </div>
+        </div>
+
+        <h5 class="mb-3 mt-4">指标说明</h5>
+        <div class="card">
+            <div class="card-body p-0">
+                <table class="table table-hover mb-0">
+                    <thead class="table-light"><tr><th>Metric</th><th>来源</th><th>value 含义</th><th>sub_value</th><th>费用</th></tr></thead>
+                    <tbody>
+                        <tr><td><code>btc_netflow</code></td><td>CoinMetrics</td><td>净流量 (USD)</td><td>流入 (USD)</td><td><span class="badge bg-success">免费</span></td></tr>
+                        <tr><td><code>stablecoin_supply</code></td><td>CoinGecko</td><td>总市值 (USD)</td><td>总市值 (B)</td><td><span class="badge bg-success">免费</span></td></tr>
+                        <tr><td><code>etf_flow</code></td><td>Farside</td><td>净流入 (M USD)</td><td>净流入 (USD)</td><td><span class="badge bg-success">免费</span></td></tr>
+                        <tr><td><code>mvrv_zscore</code></td><td>CoinMetrics</td><td>Z-Score</td><td>MVRV Ratio</td><td><span class="badge bg-success">免费</span></td></tr>
+                        <tr><td><code>sopr</code></td><td>Glassnode</td><td>SOPR 值</td><td>—</td><td><span class="badge bg-warning text-dark">需 key</span></td></tr>
+                    </tbody>
+                </table>
+            </div>
+        </div>
+
+        <h5 class="mb-3 mt-4">CSV 存储</h5>
+        <div class="card">
+            <div class="card-body">
+                <p class="small">数据落盘在 <code>data/onchain/</code> 下，每个指标一个 CSV 文件：</p>
+                <ul class="small">
+                    <li><code>btc_netflow.csv</code> — 交易所净流量 (timestamp, datetime, value, sub_value, extra)</li>
+                    <li><code>stablecoin_supply.csv</code> — 稳定币供应</li>
+                    <li><code>etf_flow.csv</code> — ETF 净流入</li>
+                    <li><code>mvrv_zscore.csv</code> — MVRV Z-Score</li>
+                    <li><code>sopr.csv</code> — SOPR</li>
+                </ul>
+                <p class="small text-muted">每5分钟自动刷新并写盘。extra 字段存 JSON (明细/分解数据)。</p>
+            </div>
+        </div>
+    </div>
+
     <!-- ==================== WEBSOCKET ==================== -->
     <div class="section" id="section-ws">
 

data_provider/onchain_metrics.py

@@ -0,0 +1,597 @@
+"""
+链上指标数据模块：拉取 BTC 交易所净流量、稳定币供应、ETF 净流入、MVRV Z-Score、SOPR。
+本地 CSV 落盘 + 内存缓存，参照 derivatives 模式。
+
+免费数据源：
+  - CoinMetrics Community API: 交易所流入/流出(USD)、MVRV Ratio
+  - CoinGecko: 稳定币市值
+需要 API key 的指标（可配置）：
+  - ETF 净流入: Coinglass / Farside / Glassnode
+  - SOPR: Glassnode / CoinMetrics Pro
+"""
+import csv
+import json
+import logging
+import os
+import re
+import threading
+import time
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any, Dict, List, Optional
+
+import requests
+from fastapi import APIRouter, HTTPException, Query
+
+logger = logging.getLogger("onchain_metrics")
+
+# ── 常量 ─────────────────────────────────────────────────────────────
+METRIC_NAMES = [
+    "btc_netflow",
+    "stablecoin_supply",
+    "etf_flow",
+    "mvrv_zscore",
+    "sopr",
+]
+REFRESH_INTERVAL = 300  # 后台刷新间隔（秒），免费 API 限频较严
+COINMETRICS_BASE = "https://community-api.coinmetrics.io/v4"
+COINGECKO_BASE = "https://api.coingecko.com/api/v3"
+REQUEST_TIMEOUT = 30
+HTTP_HEADERS = {"User-Agent": "Mozilla/5.0 (compatible; chan-data-provider/1.0)"}
+
+
+def to_utc_iso(ts_ms: int) -> str:
+    dt = datetime.fromtimestamp(ts_ms / 1000, tz=timezone.utc)
+    return dt.isoformat().replace("+00:00", "Z")
+
+
+# ── OnchainMetricsManager ────────────────────────────────────────────
+class OnchainMetricsManager:
+    """管理链上指标的拉取、缓存和持久化。每个指标独立存储。"""
+
+    def __init__(self, data_dir: Path, api_keys: Optional[Dict[str, str]] = None) -> None:
+        self.data_dir = data_dir / "onchain"
+        self.data_dir.mkdir(parents=True, exist_ok=True)
+        self.api_keys = api_keys or {}
+
+        # 内存缓存: metric_name -> List[Dict]
+        self._metrics: Dict[str, List[Dict]] = {name: [] for name in METRIC_NAMES}
+        self._lock = threading.RLock()
+        self._stop_event = threading.Event()
+        self._thread: Optional[threading.Thread] = None
+
+        # 加载本地历史
+        for name in METRIC_NAMES:
+            local = self._load_local(name)
+            if local:
+                self._metrics[name] = local
+                logger.info("链上指标 %s 加载本地记录: %d 条", name, len(local))
+
+    # ── CSV 路径 ─────────────────────────────────────────────────────
+    def _path(self, metric: str) -> Path:
+        return self.data_dir / f"{metric}.csv"
+
+    # ── CSV 读写 ─────────────────────────────────────────────────────
+    def _load_local(self, metric: str) -> List[Dict]:
+        path = self._path(metric)
+        if not path.exists():
+            return []
+        records = []
+        with path.open("r", encoding="utf-8", newline="") as fp:
+            for row in csv.DictReader(fp):
+                try:
+                    records.append({
+                        "timestamp": int(row["timestamp"]),
+                        "datetime": row.get("datetime", ""),
+                        "value": float(row.get("value", 0)),
+                        "sub_value": float(row.get("sub_value", 0)) if row.get("sub_value") else None,
+                        "extra": json.loads(row.get("extra", "{}")) if row.get("extra") else {},
+                    })
+                except (KeyError, ValueError):
+                    continue
+        records.sort(key=lambda r: r["timestamp"])
+        return records
+
+    def _write_local(self, metric: str, records: List[Dict]) -> None:
+        path = self._path(metric)
+        fieldnames = ["timestamp", "datetime", "value", "sub_value", "extra"]
+        tmp = path.with_suffix(".tmp")
+        try:
+            with tmp.open("w", encoding="utf-8", newline="") as fp:
+                w = csv.DictWriter(fp, fieldnames=fieldnames, extrasaction="ignore")
+                w.writeheader()
+                for r in records:
+                    row = {
+                        "timestamp": r.get("timestamp", 0),
+                        "datetime": r.get("datetime", ""),
+                        "value": r.get("value", 0),
+                        "sub_value": "" if r.get("sub_value") is None else r["sub_value"],
+                        "extra": json.dumps(r.get("extra", {}), ensure_ascii=False),
+                    }
+                    w.writerow(row)
+            tmp.replace(path)
+            logger.info("链上指标 %s 已写入磁盘: %d 条", metric, len(records))
+        except Exception as e:
+            logger.error("链上指标 %s 落盘失败: %s", metric, e)
+            if tmp.exists():
+                tmp.unlink()
+
+    def _merge(self, base: List[Dict], new: List[Dict]) -> List[Dict]:
+        """按 timestamp 去重合并，新覆盖旧。"""
+        merged = {r["timestamp"]: r for r in base}
+        for r in new:
+            merged[r["timestamp"]] = r
+        return sorted(merged.values(), key=lambda r: r["timestamp"])
+
+    # ── 数据拉取 ─────────────────────────────────────────────────────
+    def _fetch_cm_metrics(
+        self, metrics: str, days: int = 365
+    ) -> Optional[List[Dict]]:
+        """从 CoinMetrics Community API 拉取指标。返回 [{time, metric: value}, ...]"""
+        page_size = min(days, 10000)
+        url = (
+            f"{COINMETRICS_BASE}/timeseries/asset-metrics"
+            f"?assets=btc&metrics={metrics}&frequency=1d&page_size={page_size}"
+        )
+        try:
+            r = requests.get(url, timeout=REQUEST_TIMEOUT, headers=HTTP_HEADERS)
+            if r.status_code != 200:
+                logger.warning("CoinMetrics %s 返回 %d: %s", metrics, r.status_code, r.text[:200])
+                return None
+            data = r.json().get("data", [])
+            if not data:
+                return None
+            # 翻页取更多历史
+            all_data = list(data)
+            next_url = r.json().get("next_page_url")
+            pages = 0
+            while next_url and pages < 10:
+                pages += 1
+                time.sleep(0.5)
+                r2 = requests.get(next_url, timeout=REQUEST_TIMEOUT, headers=HTTP_HEADERS)
+                if r2.status_code != 200:
+                    break
+                batch = r2.json()
+                all_data.extend(batch.get("data", []))
+                next_url = batch.get("next_page_url")
+                if not next_url or next_url == r.json().get("next_page_url"):
+                    break
+            return all_data
+        except Exception as e:
+            logger.error("CoinMetrics %s 拉取失败: %s", metrics, e)
+            return None
+
+    def _fetch_btc_netflow(self) -> List[Dict]:
+        """BTC 交易所净流量 (USD) = 流入 - 流出。"""
+        data = self._fetch_cm_metrics("FlowInExUSD,FlowOutExUSD", days=365)
+        if not data:
+            return []
+
+        records = []
+        for d in data:
+            ts_str = d.get("time", "")
+            inflow = float(d.get("FlowInExUSD") or 0)
+            outflow = float(d.get("FlowOutExUSD") or 0)
+            netflow = inflow - outflow
+            try:
+                ts = int(datetime.fromisoformat(ts_str.replace("Z", "+00:00")).timestamp() * 1000)
+            except Exception:
+                continue
+            records.append({
+                "timestamp": ts,
+                "datetime": to_utc_iso(ts),
+                "value": round(netflow, 2),
+                "sub_value": round(inflow, 2),
+                "extra": {"inflow_usd": round(inflow, 2), "outflow_usd": round(outflow, 2)},
+            })
+        return sorted(records, key=lambda r: r["timestamp"])
+
+    def _fetch_stablecoin_supply(self) -> List[Dict]:
+        """稳定币总供应（USDT + USDC + DAI + FDUSD + TUSD 市值之和）。"""
+        try:
+            url = (
+                f"{COINGECKO_BASE}/coins/markets"
+                f"?vs_currency=usd&category=stablecoins&order=market_cap_desc"
+                f"&per_page=5&page=1&sparkline=false"
+            )
+            r = requests.get(url, timeout=REQUEST_TIMEOUT, headers=HTTP_HEADERS)
+            if r.status_code != 200:
+                logger.warning("CoinGecko stablecoins 返回 %d", r.status_code)
+                return []
+            coins = r.json()
+            if not isinstance(coins, list):
+                return []
+
+            total_mcap = sum(c.get("market_cap", 0) or 0 for c in coins)
+            now_ms = int(time.time() * 1000)
+            breakdown = {
+                c.get("symbol", "?").upper(): c.get("market_cap", 0) or 0
+                for c in coins[:5]
+            }
+            return [{
+                "timestamp": now_ms,
+                "datetime": to_utc_iso(now_ms),
+                "value": round(total_mcap, 2),
+                "sub_value": round(total_mcap / 1e9, 2),  # Billions
+                "extra": breakdown,
+            }]
+        except Exception as e:
+            logger.error("稳定币供应拉取失败: %s", e)
+            return []
+
+    def _fetch_etf_flow(self) -> List[Dict]:
+        """BTC ETF 净流入/流出。优先从 Farside 免费爬取，Coinglass 为备用。
+
+        数据源优先级:
+          1. Farside (免费, HTML 爬取)
+          2. Coinglass (需 coinglass_key)
+          3. Glassnode (需 glassnode_key)
+        """
+        # ── 优先：Farside 免费爬取 ──
+        try:
+            records = self._fetch_etf_farside()
+            if records:
+                logger.info("ETF 数据从 Farside 拉取: %d 条", len(records))
+                return records
+        except Exception as e:
+            logger.warning("Farside ETF 爬取失败: %s", e)
+
+        # ── 备用：Coinglass ──
+        cg_key = self.api_keys.get("coinglass_key")
+        if cg_key:
+            try:
+                url = "https://open-api-v3.coinglass.com/api/bitcoin/etf/net-inflow?interval=30"
+                r = requests.get(url, timeout=REQUEST_TIMEOUT, headers={
+                    **HTTP_HEADERS, "coinglassSecret": cg_key,
+                })
+                if r.status_code == 200:
+                    data = r.json()
+                    records = []
+                    if isinstance(data, dict) and "data" in data:
+                        for item in data["data"]:
+                            ts = int(item.get("date", 0)) * 1000 if item.get("date") else 0
+                            if ts:
+                                records.append({
+                                    "timestamp": ts,
+                                    "datetime": to_utc_iso(ts),
+                                    "value": float(item.get("netInflow", 0)),
+                                    "sub_value": None,
+                                    "extra": item,
+                                })
+                    return records
+                logger.warning("Coinglass ETF 返回 %d", r.status_code)
+            except Exception as e:
+                logger.error("Coinglass ETF 拉取失败: %s", e)
+
+        logger.warning("ETF 数据源均不可用（Farside/Coinglass/Glassnode）")
+        return []
+
+    def _fetch_etf_farside(self) -> List[Dict]:
+        """从 Farside 网站爬取 BTC ETF 每日净流量。
+
+        https://farside.co.uk/btc/ 页面包含一个 HTML 表格，
+        每行包含日期和各 ETF 的当日流量（百万美元），最后一列为总计。
+        """
+        url = "https://farside.co.uk/btc/"
+        r = requests.get(url, timeout=REQUEST_TIMEOUT, headers={
+            **HTTP_HEADERS,
+            "Accept": "text/html,application/xhtml+xml,*/*",
+        })
+        if r.status_code != 200:
+            logger.warning("Farside 返回 %d", r.status_code)
+            return []
+
+        html = r.text
+
+        # 查找表格
+        table_match = re.search(r'<table[^>]*>(.*?)</table>', html, re.DOTALL)
+        if not table_match:
+            logger.warning("Farside 页面未找到表格")
+            return []
+
+        rows_html = re.findall(r'<tr[^>]*>(.*?)</tr>', table_match.group(1), re.DOTALL)
+        month_map = {
+            "jan": 1, "feb": 2, "mar": 3, "apr": 4, "may": 5, "jun": 6,
+            "jul": 7, "aug": 8, "sep": 9, "oct": 10, "nov": 11, "dec": 12,
+        }
+
+        records = []
+        for row_html in rows_html:
+            cells = re.findall(r'<t[dh][^>]*>(.*?)</t[dh]>', row_html, re.DOTALL)
+            # 清理 HTML 标签和空白
+            clean = []
+            for c in cells:
+                t = re.sub(r'<[^>]+>', '', c).strip()
+                t = t.replace('\xa0', ' ').replace('&nbsp;', ' ').strip()
+                clean.append(t)
+
+            if not clean:
+                continue
+
+            # 第一列应为日期格式 "15 Jun 2026"
+            date_str = clean[0]
+            parts = date_str.split()
+            if len(parts) != 3:
+                continue
+            day_str, mon_str, year_str = parts
+            mon = month_map.get(mon_str.lower()[:3])
+            if mon is None:
+                continue
+            try:
+                day = int(day_str)
+                year = int(year_str)
+            except ValueError:
+                continue
+
+            # 最后一列为总计（可能带括号表示负值）
+            total_str = clean[-1] if len(clean) > 1 else ""
+            if not total_str or total_str in ("", "Total", "-"):
+                continue
+            # 解析 "(123.4)" → -123.4, "123.4" → 123.4
+            total_str = total_str.replace(",", "")
+            is_negative = total_str.startswith("(") and total_str.endswith(")")
+            if is_negative:
+                total_str = total_str[1:-1]
+            try:
+                total_m = float(total_str)
+            except ValueError:
+                continue
+            if is_negative:
+                total_m = -total_m
+
+            # 构建时间戳（UTC 午夜）
+            from datetime import datetime, timezone as tz
+            dt = datetime(year, mon, day, tzinfo=tz.utc)
+            ts = int(dt.timestamp() * 1000)
+
+            # 分解各 ETF 明细
+            etf_breakdown = {}
+            if len(clean) > 2:
+                etf_names = ["IBIT", "FBTC", "BITB", "ARKB", "BTCO", "EZBC",
+                             "BRRR", "HODL", "BTCW", "MSBT", "GBTC", "BTC"]
+                for i, name in enumerate(etf_names):
+                    idx = i + 1
+                    if idx < len(clean) - 1:
+                        val_str = clean[idx].replace(",", "").replace("(", "").replace(")", "")
+                        neg = clean[idx].startswith("(")
+                        try:
+                            val = float(val_str)
+                            etf_breakdown[name] = -val if neg else val
+                        except ValueError:
+                            pass
+
+            records.append({
+                "timestamp": ts,
+                "datetime": dt.isoformat().replace("+00:00", "Z"),
+                "value": round(total_m, 2),      # 净流入 (百万 USD)
+                "sub_value": round(total_m * 1_000_000, 2),  # 净流入 (USD)
+                "extra": {"total_million_usd": round(total_m, 2), "breakdown": etf_breakdown},
+            })
+
+        return sorted(records, key=lambda r: r["timestamp"])
+
+    def _fetch_mvrv_zscore(self) -> List[Dict]:
+        """MVRV Z-Score = (当前 MVRV - 滚动均值) / 滚动标准差。
+
+        从 CoinMetrics 拉取 CapMVRVCur（免费），计算 365 天滚动 Z-Score。
+        """
+        data = self._fetch_cm_metrics("CapMVRVCur", days=400)
+        if not data:
+            return []
+
+        # 解析时间序列
+        mvrv_series = []
+        for d in data:
+            ts_str = d.get("time", "")
+            mvrv_val = d.get("CapMVRVCur")
+            if mvrv_val is None:
+                continue
+            try:
+                ts = int(datetime.fromisoformat(ts_str.replace("Z", "+00:00")).timestamp() * 1000)
+            except Exception:
+                continue
+            mvrv_series.append((ts, float(mvrv_val)))
+        mvrv_series.sort(key=lambda x: x[0])
+
+        # 计算滚动 Z-Score (365 天窗口，即约 365 个数据点)
+        window = 365
+        records = []
+        values = []
+        timestamps = []
+        for ts, val in mvrv_series:
+            values.append(val)
+            timestamps.append(ts)
+            if len(values) < window:
+                continue
+            window_vals = values[-window:]
+            mean = sum(window_vals) / window
+            variance = sum((v - mean) ** 2 for v in window_vals) / window
+            stddev = variance ** 0.5
+            zscore = (val - mean) / stddev if stddev > 0 else 0.0
+            records.append({
+                "timestamp": ts,
+                "datetime": to_utc_iso(ts),
+                "value": round(zscore, 4),
+                "sub_value": round(val, 4),
+                "extra": {"mvrv_ratio": round(val, 4), "rolling_mean": round(mean, 4), "rolling_stddev": round(stddev, 4)},
+            })
+        return records
+
+    def _fetch_sopr(self) -> List[Dict]:
+        """SOPR (Spent Output Profit Ratio)。需要 API key。
+
+        支持:
+          - glassnode_key: Glassnode v1/metrics/indicators/sopr
+        """
+        gn_key = self.api_keys.get("glassnode_key")
+        if gn_key:
+            try:
+                url = (
+                    f"https://api.glassnode.com/v1/metrics/indicators/sopr"
+                    f"?a=btc&f=json&api_key={gn_key}"
+                )
+                r = requests.get(url, timeout=REQUEST_TIMEOUT, headers=HTTP_HEADERS)
+                if r.status_code == 200:
+                    data = r.json()
+                    records = []
+                    for item in data if isinstance(data, list) else []:
+                        ts = int(item.get("t", 0)) * 1000
+                        if ts:
+                            records.append({
+                                "timestamp": ts,
+                                "datetime": to_utc_iso(ts),
+                                "value": float(item.get("v", 0)),
+                                "sub_value": None,
+                                "extra": {"raw": item},
+                            })
+                    return records
+                logger.warning("Glassnode SOPR 返回 %d", r.status_code)
+            except Exception as e:
+                logger.error("Glassnode SOPR 拉取失败: %s", e)
+
+        logger.warning(
+            "SOPR 数据未配置 API key。请设置环境变量 GLASSNODE_API_KEY"
+        )
+        return []
+
+    # ── 刷新入口 ─────────────────────────────────────────────────────
+    def refresh_all(self) -> None:
+        """拉取全部 5 个指标，合并到内存并写盘。"""
+        fetchers = {
+            "btc_netflow": self._fetch_btc_netflow,
+            "stablecoin_supply": self._fetch_stablecoin_supply,
+            "etf_flow": self._fetch_etf_flow,
+            "mvrv_zscore": self._fetch_mvrv_zscore,
+            "sopr": self._fetch_sopr,
+        }
+
+        for name, fetcher in fetchers.items():
+            try:
+                new_records = fetcher()
+                if not new_records:
+                    continue
+                with self._lock:
+                    base = list(self._metrics.get(name, []))
+                    merged = self._merge(base, new_records)
+                    self._metrics[name] = merged
+                self._write_local(name, merged)
+                logger.info("链上指标 %s 刷新: +%d 条, 总计 %d 条",
+                            name, len(new_records), len(merged))
+            except Exception:
+                logger.exception("链上指标 %s 刷新异常", name)
+
+    # ── 后台线程 ─────────────────────────────────────────────────────
+    def _refresh_loop(self) -> None:
+        """后台线程：启动立即拉取一次，之后每 REFRESH_INTERVAL 秒刷新。"""
+        logger.info("链上指标后台线程启动，间隔 %ds", REFRESH_INTERVAL)
+        # 启动立即拉取
+        self.refresh_all()
+        while not self._stop_event.wait(REFRESH_INTERVAL):
+            self.refresh_all()
+        logger.info("链上指标后台线程已退出")
+
+    def start(self) -> None:
+        self._stop_event.clear()
+        self._thread = threading.Thread(
+            target=self._refresh_loop, name="onchain-loop", daemon=True,
+        )
+        self._thread.start()
+        logger.info("链上指标模块已启动")
+
+    def stop(self) -> None:
+        self._stop_event.set()
+        if self._thread:
+            self._thread.join(timeout=5)
+
+    # ── 查询接口 ─────────────────────────────────────────────────────
+    def get_metric(
+        self,
+        metric: str,
+        limit: int = 100,
+        start_ms: Optional[int] = None,
+        end_ms: Optional[int] = None,
+    ) -> List[Dict]:
+        if metric not in METRIC_NAMES:
+            raise HTTPException(
+                status_code=400,
+                detail=f"不支持的指标: {metric}。可选: {METRIC_NAMES}",
+            )
+        with self._lock:
+            records = list(self._metrics.get(metric, []))
+        if start_ms is not None:
+            records = [r for r in records if r["timestamp"] >= start_ms]
+        if end_ms is not None:
+            records = [r for r in records if r["timestamp"] <= end_ms]
+        return records[-limit:] if limit else records
+
+    def get_latest(self) -> Dict[str, Any]:
+        """获取所有指标的最新值。"""
+        result = {"timestamp": int(time.time() * 1000)}
+        for name in METRIC_NAMES:
+            with self._lock:
+                records = self._metrics.get(name, [])
+            if records:
+                latest = records[-1]
+                result[name] = {
+                    "timestamp": latest["timestamp"],
+                    "datetime": latest["datetime"],
+                    "value": latest["value"],
+                    "sub_value": latest.get("sub_value"),
+                    "extra": latest.get("extra", {}),
+                }
+            else:
+                result[name] = None
+        return result
+
+
+# ── FastAPI Router ────────────────────────────────────────────────────
+def create_onchain_router(manager: OnchainMetricsManager) -> APIRouter:
+    router = APIRouter(prefix="/api/onchain", tags=["onchain"])
+
+    @router.get("/metrics")
+    async def get_metrics(
+        metric: str = Query(..., description=f"指标名称: {', '.join(METRIC_NAMES)}"),
+        limit: int = Query(100, ge=1, le=5000, description="返回条数上限"),
+        start: Optional[int] = Query(None, description="起始时间戳(ms)"),
+        end: Optional[int] = Query(None, description="结束时间戳(ms)"),
+    ):
+        """获取单个链上指标的时间序列。"""
+        data = manager.get_metric(metric, limit=limit, start_ms=start, end_ms=end)
+        return {"metric": metric, "count": len(data), "data": data}
+
+    @router.get("/latest")
+    async def get_latest():
+        """获取全部 5 个指标的最新快照。"""
+        return manager.get_latest()
+
+    @router.get("/available")
+    async def get_available():
+        """列出可用指标及当前数据量。"""
+        info = {}
+        for name in METRIC_NAMES:
+            records = manager.get_metric(name, limit=0)
+            info[name] = {
+                "count": len(records),
+                "has_data": len(records) > 0,
+                "first_ts": records[0]["datetime"] if records else None,
+                "last_ts": records[-1]["datetime"] if records else None,
+            }
+        return info
+
+    return router
+
+
+# ── 环境变量辅助 ─────────────────────────────────────────────────────
+def api_keys_from_env() -> Dict[str, str]:
+    """从环境变量读取 API keys。"""
+    keys = {}
+    for env_var, key_name in [
+        ("COINGLASS_API_KEY", "coinglass_key"),
+        ("GLASSNODE_API_KEY", "glassnode_key"),
+        ("FARSIDE_API_KEY", "farside_key"),
+        ("COINMETRICS_API_KEY", "coinmetrics_key"),
+    ]:
+        val = os.getenv(env_var, "").strip()
+        if val and "***" not in val:  # 忽略占位符
+            keys[key_name] = val
+    return keys

data_provider/requirements.txt

@@ -3,3 +3,4 @@ fastapi>=0.110.0,<1.0.0
 uvicorn[standard]>=0.23.0,<1.0.0
 pandas>=2.0.0,<3.0.0
 technical==1.5.0
+requests>=2.28.0

web/templates/chan_tv.html

@@ -1,6 +1,15 @@
 <!DOCTYPE html>
 <html lang="zh-CN">
 <head>
+<!-- Google tag (gtag.js) -->
+<script async src="https://www.googletagmanager.com/gtag/js?id=G-LVVXH3TL04"></script>
+<script>
+  window.dataLayer = window.dataLayer || [];
+  function gtag(){dataLayer.push(arguments);}
+  gtag('js', new Date());
+  gtag('config', 'G-LVVXH3TL04');
+</script>
+
   <meta charset="utf-8">
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   <title>缠论 Chart — TradingView</title>

web/templates/index.html

@@ -1,6 +1,15 @@
 <!DOCTYPE html>
 <html>
 <head>
+<!-- Google tag (gtag.js) -->
+<script async src="https://www.googletagmanager.com/gtag/js?id=G-LVVXH3TL04"></script>
+<script>
+  window.dataLayer = window.dataLayer || [];
+  function gtag(){dataLayer.push(arguments);}
+  gtag('js', new Date());
+  gtag('config', 'G-LVVXH3TL04');
+</script>
+
     <title>缠论分析系统</title>
     <meta charset="utf-8">
     <meta name="viewport" content="width=device-width, initial-scale=1.0">