434 lines
19 KiB
Python
434 lines
19 KiB
Python
"""
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山寨币爆发监控系统 v11.7.9 — 价格跟踪+三级分级跟踪止盈+趋势反转（纯前瞻版）
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趋势反转检测：1H连续阴动K、量价背离、空头加速（替代MACD/RSI）
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v1.7.9: 跟踪止盈按盈利分三级 — 防震(3×ATR) → 锁利(2×ATR) → 紧贴(1.2×ATR)
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止盈止损跟踪、动态买入/卖出指引
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"""
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import sys, os, shutil
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# ⚠️ 安全机制：启动时强制清__pycache__，防止旧版字节码残留
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for cache_dir in [
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os.path.join(os.path.dirname(__file__), "__pycache__"),
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os.path.join(os.path.dirname(__file__), "..", "__pycache__"),
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]:
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if os.path.exists(cache_dir):
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shutil.rmtree(cache_dir, ignore_errors=True)
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import ccxt
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import pandas as pd
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import json
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import sys
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import os
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from datetime import datetime
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sys.path.insert(0, os.path.dirname(__file__))
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from altcoin_db import (
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init_db, get_active_recommendations, update_recommendation_tracking,
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expire_old_recommendations, get_stats, update_recommendation_action_status,
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should_push, log_push, apply_recommendation_state_transition, log_cron_run,
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update_latest_price_cache,
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)
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from pa_engine import (
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calc_atr, full_pa_analysis, detect_trend_exhaustion,
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analyze_entry_point,
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)
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from feishu_push import push_altcoin_tp_sl_alert
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from config_loader import load_rules
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from opportunity_lifecycle import apply_entry_quality_gate
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exchange = ccxt.binance({"enableRateLimit": True})
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def fetch_klines(symbol, timeframe, limit=200):
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try:
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ohlcv = exchange.fetch_ohlcv(symbol, timeframe, limit=limit)
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df = pd.DataFrame(ohlcv, columns=["timestamp", "open", "high", "low", "close", "volume"])
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df["timestamp"] = pd.to_datetime(df["timestamp"], unit="ms")
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return df
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except Exception:
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return None
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def analyze_tracking_signals(symbol, rec, current_price):
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"""
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对active推荐做动态跟踪分析
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返回: {"action_status": str, "sell_signals": [...], "buy_signals": [...],
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"exhaustion": {...}, "entry_update": {...}}
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"""
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sell_signals = []
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buy_signals = []
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action_status = "持有" # 默认状态
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entry_price = rec["entry_price"]
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stop_loss = rec.get("stop_loss", entry_price * 0.95)
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tp1 = rec.get("tp1", entry_price * 1.03)
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tp2 = rec.get("tp2", entry_price * 1.05)
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entry_plan = rec.get("entry_plan") or {}
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# ---- 拉取1H数据做趋势分析 ----
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h1_df = fetch_klines(symbol, "1h", limit=100)
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m15_df = fetch_klines(symbol, "15m", limit=100)
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h4_df = fetch_klines(symbol, "4h", limit=100)
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atr_1h = calc_atr(h1_df, 14) if h1_df is not None else 0
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# ---- 趋势衰减检测 ----
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exhaustion = {}
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if h1_df is not None and atr_1h > 0:
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exhaustion = detect_trend_exhaustion(h1_df, atr_1h)
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if exhaustion.get("exhausted"):
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for es in exhaustion.get("signals", []):
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sell_signals.append(es)
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if exhaustion["severity"] == "high":
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action_status = "衰减"
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elif exhaustion["severity"] == "medium":
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# 中度衰减，还持有但需关注
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sell_signals.append("趋势中度衰减，关注止盈")
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# ---- 止盈信号检测 ----
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pnl_pct = ((current_price / entry_price) - 1) * 100 if entry_price > 0 else 0
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# 到达TP1（v1.7.8：TP1保留作为提醒目标）
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if tp1 > 0 and current_price >= tp1:
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sell_signals.append(f"✅ 到达TP1(${tp1:.4f}), 建议止盈50%仓位")
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action_status = "止盈1" # 无条件：TP1到了就是止盈，无论之前什么状态
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# === v1.7.8 跟踪止盈全面升级 ===
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# 核心改动:
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# ① 激活门槛 5%→3% (抓更多利润)
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# ② ATR乘数 2.0→1.5 (更紧贴行情)
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# ③ 每次tracker运行都重新计算并只升不降 (动态跟随行情逐步抬高)
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# ④ 跟踪止盈触发时无条件覆盖所有状态 (利润保护优先级最高)
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# ⑤ TP2已废除(历史0命中),跟踪止盈是唯一动态止盈方式
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rules = load_rules()
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trail_cfg = rules.get("tracker", {}).get("trailing_stop", {})
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trailing_stop_level = entry_plan.get("trailing_stop_level", 0)
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if trail_cfg.get("enabled", True) and atr_1h > 0 and entry_price > 0:
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activate_pct = trail_cfg.get("activate_pnl_pct", 3)
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# === v1.7.9 三级分级乘数: 按盈利切换 ===
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tiers = trail_cfg.get("tiers", [])
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trail_atr_mult = 1.5 # 兜底
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tier_label = ""
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if tiers:
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for t in sorted(tiers, key=lambda x: x.get("min_pnl_pct", 0), reverse=True):
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if pnl_pct >= t.get("min_pnl_pct", 0):
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trail_atr_mult = t.get("atr_mult", 1.5)
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tier_label = t.get("label", "")
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break
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# === 动态跟随：每次运行都重新计算跟踪止盈位 ===
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# 算法: trailing_stop = current_price - atr_mult × ATR_1h
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# 规则: 只升不降 (max(old_level, new_level))
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# 激活条件: pnl_pct ≥ activate_pct (3%)
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if pnl_pct >= activate_pct:
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new_trail = current_price - trail_atr_mult * atr_1h
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if trailing_stop_level > 0:
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# 已有跟踪位 → 只上移不下移
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trailing_stop_level = max(trailing_stop_level, new_trail)
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else:
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# 首次激活
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trailing_stop_level = new_trail
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tier_info = f" [{tier_label}·{trail_atr_mult}×ATR]" if tier_label else ""
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sell_signals.append(f"🎯 跟踪止盈激活(盈+{pnl_pct:.1f}%≥{activate_pct}%{tier_info}, 回撤{trail_atr_mult}×ATR触发)")
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# === 触发检查：当前价跌破跟踪止盈位 → 止盈 ===
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# 🔴 v1.7.8: 跟踪止盈触发时无条件覆盖(利润保护优先级最高)
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if trailing_stop_level > 0 and current_price <= trailing_stop_level:
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drop_from_trail = trailing_stop_level - current_price
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sell_signals.append(f"🎯 跟踪止盈触发! 从高位回撤${drop_from_trail:.4f}({drop_from_trail/trailing_stop_level*100:.1f}%)")
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action_status = "跟踪止盈"
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# 定期报告（即使没触发也显示跟踪位）
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if trailing_stop_level > 0 and current_price > trailing_stop_level and pnl_pct >= activate_pct * 2:
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cushion = (current_price - trailing_stop_level) / current_price * 100
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sell_signals.append(f"📊 跟踪止盈中: 止盈位${trailing_stop_level:.4f}(距现价{cushion:.1f}%)")
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elif pnl_pct >= 1 and trailing_stop_level > 0 and current_price <= trailing_stop_level:
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# 利润回落到1%以内但跟踪位已激活且被击穿 → 保本出
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sell_signals.append(f"🔒 保本止盈: 利润缩至{pnl_pct:.1f}%,跟踪位击穿")
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action_status = "跟踪止盈"
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# ---- 无TP保护的推荐，涨超15%自动止盈（孤儿推荐保护）----
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# 加速推荐（粗筛/细筛层）没有 TP/SL，price_tracker 无法判断出场点。
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# 涨超15%仍无结论 → 认怂落袋，避免永续浮盈不兑现。
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if tp1 == 0 and pnl_pct >= 15:
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sell_signals.append(f"✅ 无TP保护自动止盈(涨+{pnl_pct:.1f}%≥15%，落袋为安)")
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action_status = "止盈1"
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# ---- 止损接近警告 ----
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if stop_loss > 0:
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loss_pct = ((current_price / stop_loss) - 1) * 100
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if loss_pct < 3: # 当前价离止损不到3%
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sell_signals.append(f"⚠️ 接近止损！当前${current_price:.4f}离止损${stop_loss:.4f}仅{loss_pct:.1f}%")
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if current_price <= stop_loss:
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sell_signals.append(f"🔴 已触发止损！${current_price:.4f}≤${stop_loss:.4f}")
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action_status = "止损"
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# ---- 趋势反转信号（PA行为检测，替代MACD） ----
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if h1_df is not None and len(h1_df) >= 30 and atr_1h > 0:
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pa_1h = full_pa_analysis(h1_df, "1h")
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pa_1h_candles = pa_1h.get("candles_class", [])
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recent_candles = pa_1h_candles[-6:] if len(pa_1h_candles) >= 6 else pa_1h_candles
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# 1H连续阴动K → 趋势反转
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dy_bear_count = sum(1 for c in recent_candles if c["type"] == "dynamic" and c["direction"] == -1)
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if dy_bear_count >= 3:
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sell_signals.append(f"🔴 1H连续{dy_bear_count}根阴动K(趋势反转)")
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if action_status == "持有":
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action_status = "反转"
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# 1H量价背离：放量但阴线（多头出货）
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avg_vol = float(h1_df["volume"].rolling(20).mean().iloc[-1])
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recent_3 = h1_df.tail(3)
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high_vol_bear = 0
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for _, row in recent_3.iterrows():
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vol_r = row["volume"] / avg_vol if avg_vol > 0 else 0
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if vol_r >= 2 and row["close"] < row["open"]:
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high_vol_bear += 1
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if high_vol_bear >= 2:
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sell_signals.append("🔴 1H放量阴线×2(多头出货)")
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# 1H连续K空头加速
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cont_k = pa_1h.get("continuous_k", [])
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for ck in cont_k:
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if ck["type"] == "bearish_continue" and ck["length"] >= 3:
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sell_signals.append(f"🔴 1H连续{ck['length']}K空头加速")
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if action_status == "持有":
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action_status = "反转"
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# === 时间衰减 (v1.6.9) ===
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# 持仓>24h仍无盈利→降级衰减
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decay_cfg = rules.get("tracker", {}).get("time_decay", {})
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if decay_cfg.get("enabled", True):
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decay_hours = decay_cfg.get("decay_hours", 24)
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rec_time = rec.get("rec_time", "")
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if rec_time:
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try:
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t_rec = datetime.fromisoformat(rec_time)
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hours_held = (datetime.now() - t_rec).total_seconds() / 3600
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if hours_held > decay_hours and pnl_pct <= 0 and action_status == "持有":
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sell_signals.append(f"⏰ 持仓{hours_held:.0f}h无盈利，降级衰减")
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action_status = "衰减"
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except Exception:
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pass
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# ---- 动态买入指引（只允许在未触发任何止盈/止损/退出信号时执行） ----
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entry_update = {}
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current_action = entry_plan.get("entry_action", "")
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# 如果推荐状态是"等回踩"，检查是否到了回踩价位。
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# 注意：一旦本轮 action_status 已经是止盈/止损/跟踪止盈/反转/衰减，就绝不能再覆盖成“可即刻买入”。
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if action_status == "持有" and current_action in ("等回踩", "🟡等回踩") and h4_df is not None and atr_1h > 0:
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pa_4h = full_pa_analysis(h4_df, "4h")
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h4_zones = pa_4h.get("zones", [])
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direction = 1 # 做多方向
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# 重新做15min入场点分析
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if m15_df is not None and len(m15_df) >= 20:
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entry_result = analyze_entry_point(
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h1_df=h1_df, m15_df=m15_df, atr_1h=atr_1h,
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zones_4h=h4_zones, direction=direction,
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)
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new_action = entry_result.get("action", "等回踩")
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if new_action == "即刻买入":
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buy_signals.append(f"🟢 回踩确认完毕！可即刻入场(15min动K确认)")
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action_status = "可即刻买入"
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elif new_action == "等回踩":
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wait_price = entry_result.get("wait_price", 0)
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if wait_price > 0:
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# 检查当前价是否接近回踩目标
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dist_pct = ((current_price / wait_price) - 1) * 100
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if abs(dist_pct) < 2:
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buy_signals.append(f"🟢 当前价接近回踩目标！${current_price:.4f}≈${wait_price:.4f}")
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action_status = "可即刻买入"
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entry_update = {
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"new_action": new_action,
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"reason": entry_result.get("reason", ""),
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"wait_price": entry_result.get("wait_price", 0),
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}
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action_status, gated_plan, gate_reasons = apply_entry_quality_gate(
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action_status=action_status,
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entry_plan=entry_plan,
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signals=rec.get("signals"),
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current_price=current_price,
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market_context=rec.get("market_context") or {},
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derivatives_context=rec.get("derivatives_context") or {},
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sector_context=rec.get("sector_context") or {},
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)
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if gate_reasons:
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buy_signals.append("⚠️ 买点质量闸门: " + "；".join(gate_reasons[:3]))
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entry_plan.update(gated_plan)
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return {
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"action_status": action_status,
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"sell_signals": sell_signals,
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"buy_signals": buy_signals,
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"exhaustion": exhaustion,
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"entry_update": entry_update,
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"pnl_pct": round(pnl_pct, 2),
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"trailing_stop_level": trailing_stop_level,
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}
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def track_prices():
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"""拉取所有active推荐币的实时价格，更新盈亏 + 动态跟踪信号"""
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recs = get_active_recommendations()
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if not recs:
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output = {
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"status": "no_active",
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"message": "无active推荐需要跟踪",
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"stats": get_stats(),
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"track_time": datetime.now().isoformat(),
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}
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print(json.dumps(output, ensure_ascii=False))
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return output
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results = []
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failed_symbols = []
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for rec in recs:
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symbol = rec["symbol"]
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try:
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ticker = exchange.fetch_ticker(symbol)
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current_price = ticker["last"]
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# 最新价格缓存：看板读取小表 latest_price_cache，不再依赖 price_tracking 高频流水表
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update_latest_price_cache(symbol, current_price, source="tracker")
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# 基础盈亏跟踪
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track_result = update_recommendation_tracking(rec["id"], current_price)
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# PA增强：动态跟踪信号分析
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tracking_signals = analyze_tracking_signals(symbol, rec, current_price)
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# === v1.7.8 跟踪止盈DB回写 ===
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# 每次tracker运行都写DB,支持动态跟随行情逐步抬高跟踪位
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trail_level = tracking_signals.get("trailing_stop_level", 0)
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if trail_level > 0:
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entry_plan = rec.get("entry_plan") or {}
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old_trail = entry_plan.get("trailing_stop_level", 0)
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# v1.7.8: 只要跟踪位有变化就写DB(上移时必变;首次激活也写)
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if abs(trail_level - old_trail) > 0.000001:
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entry_plan["trailing_stop_level"] = trail_level
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import sqlite3 as _sq
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_c2 = _sq.connect(os.getenv("ALPHAX_DB_PATH", os.path.join(os.path.dirname(__file__), "data", "altcoin_monitor.db")))
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_c2.execute("UPDATE recommendation SET entry_plan_json=? WHERE id=?",
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(json.dumps(entry_plan, ensure_ascii=False), rec["id"]))
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_c2.commit()
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_c2.close()
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# 主链路状态迁移：tracker 只提交“候选状态 + 当前价”，最终状态由 DB 主链路统一落库。
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# 飞书推送只能消费主链路返回的最终状态，不能再自行判断。
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terminal_action = {
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"hit_tp2": "止盈2",
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"stopped_out": "止损",
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}.get(track_result.get("status"))
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requested_action = terminal_action or tracking_signals["action_status"]
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state_decision = apply_recommendation_state_transition(
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rec["id"],
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requested_action=requested_action,
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current_price=current_price,
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event_time=datetime.now().strftime("%Y-%m-%dT%H:%M:%S"),
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signals=tracking_signals.get("sell_signals", []) + tracking_signals.get("buy_signals", []),
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)
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final_action = state_decision.get("action_status", requested_action)
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if state_decision.get("push_required"):
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if should_push(symbol, "entry", final_action):
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try:
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push_altcoin_tp_sl_alert(
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state_decision["push_symbol"],
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state_decision["push_current_price"],
|
||
state_decision["push_entry_price"],
|
||
state_decision["push_pnl_pct"],
|
||
final_action,
|
||
state_decision.get("push_signals", []),
|
||
state_decision.get("stop_loss", 0),
|
||
state_decision.get("tp1", 0),
|
||
state_decision.get("tp2", 0),
|
||
)
|
||
log_push(symbol, "entry", final_action, rec_id=rec["id"])
|
||
except Exception as e:
|
||
print(f"飞书推送失败({symbol}): {e}")
|
||
else:
|
||
print(f"⏭ 跳过推送({symbol}): entry/{final_action} 12h冷却中")
|
||
|
||
results.append({
|
||
"symbol": symbol,
|
||
"rec_id": rec["id"],
|
||
"entry_price": rec["entry_price"],
|
||
"current_price": current_price,
|
||
"pnl_pct": tracking_signals["pnl_pct"],
|
||
"status": track_result["status"],
|
||
"action_status": tracking_signals["action_status"],
|
||
"sell_signals": tracking_signals["sell_signals"],
|
||
"buy_signals": tracking_signals["buy_signals"],
|
||
"exhaustion_severity": tracking_signals.get("exhaustion", {}).get("severity", "low"),
|
||
})
|
||
print(f" {symbol}: 入场${rec['entry_price']} → 现在${current_price} "
|
||
f"盈亏{tracking_signals['pnl_pct']}% 状态={track_result['status']} "
|
||
f"操作={tracking_signals['action_status']}")
|
||
|
||
except Exception as e:
|
||
failed_symbols.append({"symbol": symbol, "error": str(e)})
|
||
print(f" {symbol}: 获取价格失败 - {e}")
|
||
|
||
# 过期检查
|
||
expire_old_recommendations()
|
||
|
||
output = {
|
||
"status": "tracked",
|
||
"tracked_count": len(results),
|
||
"failed_count": len(failed_symbols),
|
||
"failed_symbols": failed_symbols,
|
||
"results": results,
|
||
"stats": get_stats(),
|
||
"track_time": datetime.now().isoformat(),
|
||
}
|
||
print(json.dumps(output, ensure_ascii=False, indent=2))
|
||
return output
|
||
|
||
|
||
if __name__ == "__main__":
|
||
started_at = datetime.now()
|
||
try:
|
||
init_db()
|
||
output = track_prices()
|
||
except Exception as e:
|
||
finished_at = datetime.now()
|
||
log_cron_run(
|
||
job_name="跟踪",
|
||
script_name="price_tracker.py",
|
||
run_status="error",
|
||
result_status="exception",
|
||
started_at=started_at.isoformat(),
|
||
finished_at=finished_at.isoformat(),
|
||
duration_ms=int((finished_at - started_at).total_seconds() * 1000),
|
||
summary={},
|
||
error_message=str(e),
|
||
)
|
||
raise
|
||
else:
|
||
finished_at = datetime.now()
|
||
summary = {
|
||
"tracked_count": output.get("tracked_count", 0),
|
||
"failed_count": output.get("failed_count", 0),
|
||
"active_count": output.get("stats", {}).get("active_count", 0),
|
||
}
|
||
log_cron_run(
|
||
job_name="跟踪",
|
||
script_name="price_tracker.py",
|
||
run_status="success",
|
||
result_status=output.get("status", "completed"),
|
||
started_at=started_at.isoformat(),
|
||
finished_at=finished_at.isoformat(),
|
||
duration_ms=int((finished_at - started_at).total_seconds() * 1000),
|
||
summary=summary,
|
||
error_message="",
|
||
)
|