feat: Phase 2 - collect obi_depth_10, spot_perp_divergence, tiered_cvd_whale for BTC gate-control

backend/market_data_collector.py

@@ -16,7 +16,9 @@ PG_HOST = os.getenv("PG_HOST", "10.106.0.3")
 PG_PORT = int(os.getenv("PG_PORT", "5432"))
 PG_DB = os.getenv("PG_DB", "arb_engine")
 PG_USER = os.getenv("PG_USER", "arb")
-PG_PASS = os.getenv("PG_PASS", "arb_engine_2026")
+PG_PASS = os.getenv("PG_PASS")
+if not PG_PASS:
+    raise RuntimeError("PG_PASS 未设置，请在 .env 或环境变量中注入数据库密码")
 
 TABLE_SQL = """
 CREATE TABLE IF NOT EXISTS market_indicators (
@@ -158,6 +160,121 @@ class MarketDataCollector:
         }
         self.save_indicator(symbol, "funding_rate", ts, payload)
 
+    async def collect_obi_depth(self, session: aiohttp.ClientSession, symbol: str) -> None:
+        """
+        OBI（订单簿失衡）采集 — Phase 2 BTC gate-control 核心特征
+        计算：(bid_vol - ask_vol) / (bid_vol + ask_vol)，范围[-1,1]
+        正值=买压大，负值=卖压大
+        """
+        endpoint = "https://fapi.binance.com/fapi/v1/depth"
+        data = await self.fetch_json(session, endpoint, {"symbol": symbol, "limit": 10})
+        ts = int(time.time() * 1000)
+
+        bids = data.get("bids", [])
+        asks = data.get("asks", [])
+        bid_vol = sum(float(b[1]) for b in bids)
+        ask_vol = sum(float(a[1]) for a in asks)
+        total_vol = bid_vol + ask_vol
+        obi = (bid_vol - ask_vol) / total_vol if total_vol > 0 else 0.0
+
+        best_bid = float(bids[0][0]) if bids else 0.0
+        best_ask = float(asks[0][0]) if asks else 0.0
+        spread_bps = ((best_ask - best_bid) / best_bid * 10000) if best_bid > 0 else 0.0
+
+        payload = {
+            "symbol": symbol,
+            "obi": round(obi, 6),
+            "bid_vol_10": round(bid_vol, 4),
+            "ask_vol_10": round(ask_vol, 4),
+            "best_bid": best_bid,
+            "best_ask": best_ask,
+            "spread_bps": round(spread_bps, 3),
+        }
+        self.save_indicator(symbol, "obi_depth_10", ts, payload)
+
+    async def collect_spot_perp_divergence(self, session: aiohttp.ClientSession, symbol: str) -> None:
+        """
+        期现背离采集 — Phase 2 BTC gate-control 核心特征
+        divergence = (spot - mark) / mark，正值=现货溢价，负值=现货折价
+        """
+        spot_url = "https://api.binance.com/api/v3/ticker/price"
+        perp_url = "https://fapi.binance.com/fapi/v1/premiumIndex"
+
+        spot_data, perp_data = await asyncio.gather(
+            self.fetch_json(session, spot_url, {"symbol": symbol}),
+            self.fetch_json(session, perp_url, {"symbol": symbol}),
+        )
+        ts = int(time.time() * 1000)
+
+        spot_price = float(spot_data["price"])
+        mark_price = float(perp_data["markPrice"])
+        index_price = float(perp_data.get("indexPrice", mark_price))
+        divergence = (spot_price - mark_price) / mark_price if mark_price > 0 else 0.0
+
+        payload = {
+            "symbol": symbol,
+            "spot_price": spot_price,
+            "mark_price": mark_price,
+            "index_price": index_price,
+            "divergence": round(divergence, 8),
+            "divergence_bps": round(divergence * 10000, 3),
+        }
+        self.save_indicator(symbol, "spot_perp_divergence", ts, payload)
+
+    async def collect_tiered_cvd_whale(self, session: aiohttp.ClientSession, symbol: str) -> None:
+        """
+        巨鲸CVD分层采集 — Phase 2 BTC gate-control 核心特征
+        分层：small(<$10k), medium($10k-$100k), whale(>$100k)
+        net_cvd = buy_usd - sell_usd（正=净买入）
+        """
+        endpoint = "https://fapi.binance.com/fapi/v1/aggTrades"
+        data = await self.fetch_json(session, endpoint, {"symbol": symbol, "limit": 500})
+        ts = int(time.time() * 1000)
+
+        tiers = {
+            "small":  {"buy": 0.0, "sell": 0.0},
+            "medium": {"buy": 0.0, "sell": 0.0},
+            "whale":  {"buy": 0.0, "sell": 0.0},
+        }
+
+        for trade in data:
+            price = float(trade["p"])
+            qty = float(trade["q"])
+            usd_val = price * qty
+            is_sell = trade["m"]  # m=True 表示卖单（taker卖）
+
+            if usd_val < 10_000:
+                tier = "small"
+            elif usd_val < 100_000:
+                tier = "medium"
+            else:
+                tier = "whale"
+
+            if is_sell:
+                tiers[tier]["sell"] += usd_val
+            else:
+                tiers[tier]["buy"] += usd_val
+
+        result = {}
+        for name, t in tiers.items():
+            buy, sell = t["buy"], t["sell"]
+            net = buy - sell
+            total = buy + sell
+            result[name] = {
+                "buy_usd": round(buy, 2),
+                "sell_usd": round(sell, 2),
+                "net_cvd": round(net, 2),
+                "cvd_ratio": round(net / total, 4) if total > 0 else 0.0,
+            }
+
+        payload = {
+            "symbol": symbol,
+            "tiers": result,
+            "whale_net_cvd": result["whale"]["net_cvd"],
+            "whale_cvd_ratio": result["whale"]["cvd_ratio"],
+        }
+        self.save_indicator(symbol, "tiered_cvd_whale", ts, payload)
+
     async def collect_symbol(self, session: aiohttp.ClientSession, symbol: str) -> None:
         tasks = [
             ("long_short_ratio", self.collect_long_short_ratio(session, symbol)),
@@ -165,6 +282,9 @@ class MarketDataCollector:
             ("open_interest_hist", self.collect_open_interest_hist(session, symbol)),
             ("coinbase_premium", self.collect_coinbase_premium(session, symbol)),
             ("funding_rate", self.collect_funding_rate(session, symbol)),
+            ("obi_depth_10", self.collect_obi_depth(session, symbol)),
+            ("spot_perp_divergence", self.collect_spot_perp_divergence(session, symbol)),
+            ("tiered_cvd_whale", self.collect_tiered_cvd_whale(session, symbol)),
         ]
 
         results = await asyncio.gather(*(t[1] for t in tasks), return_exceptions=True)

backend/signal_engine.py

@@ -126,7 +126,12 @@ def fetch_market_indicators(symbol: str) -> dict:
     with get_sync_conn() as conn:
         with conn.cursor() as cur:
             indicators = {}
-            for ind_type in ["long_short_ratio", "top_trader_position", "open_interest_hist", "coinbase_premium", "funding_rate"]:
+            ind_types = [
+                "long_short_ratio", "top_trader_position", "open_interest_hist",
+                "coinbase_premium", "funding_rate",
+                "obi_depth_10", "spot_perp_divergence", "tiered_cvd_whale",  # Phase 2
+            ]
+            for ind_type in ind_types:
                 cur.execute(
                     "SELECT value FROM market_indicators WHERE symbol=%s AND indicator_type=%s ORDER BY timestamp_ms DESC LIMIT 1",
                     (symbol, ind_type),
@@ -135,7 +140,6 @@ def fetch_market_indicators(symbol: str) -> dict:
                 if not row or row[0] is None:
                     indicators[ind_type] = None
                     continue
-                # value可能是JSON字符串或已解析的dict
                 val = row[0]
                 if isinstance(val, str):
                     try:
@@ -151,10 +155,18 @@ def fetch_market_indicators(symbol: str) -> dict:
                 elif ind_type == "open_interest_hist":
                     indicators[ind_type] = float(val.get("sumOpenInterestValue", 0))
                 elif ind_type == "coinbase_premium":
-                    # premium_pct存的是百分比(如0.05=0.05%)，转成比例(0.0005)
                     indicators[ind_type] = float(val.get("premium_pct", 0)) / 100.0
                 elif ind_type == "funding_rate":
                     indicators[ind_type] = float(val.get("fundingRate", val.get("lastFundingRate", 0)))
+                elif ind_type == "obi_depth_10":
+                    # obi范围[-1,1]，正值=买压，负值=卖压
+                    indicators[ind_type] = float(val.get("obi", 0))
+                elif ind_type == "spot_perp_divergence":
+                    # divergence = (spot - mark) / mark
+                    indicators[ind_type] = float(val.get("divergence", 0))
+                elif ind_type == "tiered_cvd_whale":
+                    # 巨鲸净CVD比率[-1,1]，正值=净买入
+                    indicators[ind_type] = float(val.get("whale_cvd_ratio", 0))
             return indicators