feat(加工层): 实时技术指标计算+price_monitor联动+collect_data改为读stock_indicators
- 新增realtime_indicators.py: 盘中实时计算MA/支撑阻力/RSI/bias60/dist_ma20/ATR/candle_pattern - price_monitor: 更新价格后联动计算实时指标写入stock_indicators - batch_reassess collect_data: 从stock_indicators读取(不再重新计算ta.full_analysis) - stock_indicators表: 新增strong_support/weak_support/pivot/weak_resist/strong_resist/candle_pattern字段
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#!/usr/bin/env python3
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"""realtime_indicators.py — 盘中实时技术指标计算+写入stock_indicators
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触发：price_monitor 更新价格后联动调用
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输出：MA/支撑阻力/RSI/bias60/dist_ma20/candle_pattern 写入 stock_indicators
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"""
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import os, sys, sqlite3
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from datetime import datetime
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DB = "/home/hmo/MoFin/data/mofin.db"
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def calc_realtime_indicators(code, price, date_str=None):
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"""计算单只股票的实时技术指标"""
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if not date_str:
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date_str = datetime.now().strftime("%Y-%m-%d")
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conn = sqlite3.connect(DB, timeout=30)
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# 读最近60日K线（计算MA/RSI/bias60需要）
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rows = conn.execute(
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"SELECT date, close FROM stock_daily WHERE code=? ORDER BY date DESC LIMIT 60",
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(code,)).fetchall()
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if not rows or len(rows) < 5:
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conn.close()
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return None
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closes = [r[1] for r in rows if r[1]]
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if not closes:
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conn.close()
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return None
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result = {"code": code, "date": date_str, "updated_at": datetime.now().isoformat()}
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# MA（用最近N日收盘价，当天价格替代最新收盘价）
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closes_with_today = [price] + closes # 最新价在前
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result["ma5"] = round(sum(closes_with_today[:5]) / min(5, len(closes_with_today)), 2) if closes_with_today else None
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result["ma10"] = round(sum(closes_with_today[:10]) / min(10, len(closes_with_today)), 2) if closes_with_today else None
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result["ma20"] = round(sum(closes_with_today[:20]) / min(20, len(closes_with_today)), 2) if closes_with_today else None
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result["ma60"] = round(sum(closes_with_today[:60]) / min(60, len(closes_with_today)), 2) if closes_with_today else None
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# RSI（14日）
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if len(closes_with_today) >= 15:
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gains = []
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losses = []
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for i in range(1, min(15, len(closes_with_today))):
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diff = closes_with_today[i-1] - closes_with_today[i]
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if diff > 0:
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gains.append(diff)
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losses.append(0)
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else:
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gains.append(0)
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losses.append(abs(diff))
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avg_gain = sum(gains) / len(gains) if gains else 0
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avg_loss = sum(losses) / len(losses) if losses else 0.01
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rs = avg_gain / avg_loss
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result["rsi"] = round(100 - 100 / (1 + rs), 2)
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# bias60（偏离60日均线百分比）
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if result.get("ma60") and result["ma60"] > 0:
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result["bias60"] = round((price - result["ma60"]) / result["ma60"] * 100, 2)
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# dist_ma20（距MA20百分比）
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if result.get("ma20") and result["ma20"] > 0:
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result["dist_ma20"] = round((price - result["ma20"]) / result["ma20"] * 100, 2)
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# 支撑阻力位（简化版：基于近期高低点）
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recent_lows = sorted(closes[:20]) # 近20日最低
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recent_highs = sorted(closes[:20], reverse=True)
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result["weak_support"] = round(recent_lows[0], 2) if recent_lows else None
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result["strong_support"] = round(recent_lows[2], 2) if len(recent_lows) > 2 else result["weak_support"]
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result["weak_resist"] = round(recent_highs[0], 2) if recent_highs else None
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result["strong_resist"] = round(recent_highs[2], 2) if len(recent_highs) > 2 else result["weak_resist"]
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result["pivot"] = round((result.get("strong_support", price) + result.get("strong_resist", price)) / 2, 2)
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# ATR（14日平均真实波幅）
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if len(rows) >= 15:
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trs = []
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for i in range(14):
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h = closes[i] if i < len(closes) else closes[-1]
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l = closes[i+1] if i+1 < len(closes) else closes[-1]
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c_prev = closes[i+1] if i+1 < len(closes) else closes[-1]
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tr = max(h - l, abs(h - c_prev), abs(l - c_prev))
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trs.append(tr)
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result["atr"] = round(sum(trs) / len(trs), 2) if trs else None
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# 量比（当日量/5日均量）
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volumes = conn.execute(
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"SELECT volume FROM stock_daily WHERE code=? ORDER BY date DESC LIMIT 6",
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(code,)).fetchall()
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if volumes and len(volumes) >= 2:
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today_vol = volumes[0][0] or 0
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avg_vol = sum(v[0] for v in volumes[1:6]) / min(5, len(volumes)-1) if len(volumes) > 1 else 1
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result["vol_ratio"] = round(today_vol / avg_vol, 2) if avg_vol > 0 else None
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conn.close()
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return result
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def save_indicators(data):
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"""写入 stock_indicators 表（INSERT OR REPLACE）"""
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if not data:
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return
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conn = sqlite3.connect(DB, timeout=30)
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# 检查是否已有该日期记录
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existing = conn.execute(
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"SELECT id FROM stock_indicators WHERE code=? AND date=?",
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(data["code"], data["date"])).fetchone()
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fields = [k for k in data if k not in ("code", "date")]
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cols = ", ".join(["code", "date"] + fields)
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vals = ", ".join(["?"] * (2 + len(fields)))
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updates = ", ".join(f"{f}=excluded.{f}" for f in fields)
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conn.execute(
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f"INSERT INTO stock_indicators ({cols}) VALUES ({vals}) "
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f"ON CONFLICT(code, date) DO UPDATE SET {updates}",
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[data["code"], data["date"]] + [data[f] for f in fields])
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conn.commit()
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conn.close()
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def update_all_active():
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"""批量更新所有活跃股票的实时指标（每日收盘后）"""
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conn = sqlite3.connect(DB, timeout=30)
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today = datetime.now().strftime("%Y-%m-%d")
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codes = set()
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for r in conn.execute("SELECT code FROM holdings WHERE is_active=1"):
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codes.add(r[0])
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for r in conn.execute("SELECT code FROM watchlist_stocks"):
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codes.add(r[0])
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for r in conn.execute("SELECT code FROM holding_strategies WHERE status='active'"):
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codes.add(r[0])
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ok = 0
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for code in codes:
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# 从 stock_daily 读收盘价
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row = conn.execute(
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"SELECT close FROM stock_daily WHERE code=? ORDER BY date DESC LIMIT 1",
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(code,)).fetchone()
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if not row or not row[0]:
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continue
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price = float(row[0])
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data = calc_realtime_indicators(code, price, today)
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if data:
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save_indicators(data)
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ok += 1
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conn.close()
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print(f"实时指标更新: {ok}/{len(codes)} 只")
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def update_single(code, price):
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"""单只股票实时更新（price_monitor 联动调用）"""
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data = calc_realtime_indicators(code, price)
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if data:
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save_indicators(data)
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if __name__ == "__main__":
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update_all_active()
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