feat: market_watch调度链挂S2扫描器(策略家族S1+S2并列运行)
This commit is contained in:
xxm
@@ -1,257 +1,278 @@
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#!/usr/bin/env python3
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"""market_watch.py — 行業熱點數據採集，寫入 dashboard data/market.json
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數據源優先級：
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後端A：東方財富 push2 API（首選，有板塊代碼+實時指數）
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後端B：同花順 THS / akshare（降級，有漲跌家數+資金流向）
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注意：當前服務器無法連通東方財富API（已被封禁/域名不可達），
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實際運行時自動降級到同花順 THS 後端。THS 提供90+行業板塊的
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實時漲跌、上漲/下跌家數、淨流入資金等數據，足以滿足需求。
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輸出：data/market.json → MoFin Dashboard 市場數據展示
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"""
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import json
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from datetime import datetime
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from pathlib import Path
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from mofin_db import get_conn, init_all_tables, write_market_snapshot
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DATA_DIR = Path(__file__).parent.parent / "data"
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# ── 後端A：東方財富 push2 API（首選，有板塊代碼+實時指數） ──
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def _fetch_em(url):
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"""通用 EM API 請求"""
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import urllib.request
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req = urllib.request.Request(
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url,
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headers={"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"}
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)
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resp = urllib.request.urlopen(req, timeout=10)
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return json.loads(resp.read().decode("utf-8"))
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def fetch_sector_em():
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"""東方財富行業板塊"""
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try:
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data = _fetch_em(
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"https://push2.eastmoney.com/api/qt/clist/get?"
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"pn=1&pz=60&po=1&np=1&fields=f2,f3,f4,f12,f14&fs=m:90+t:2"
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)
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return [{
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"name": i["f14"],
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"code": i["f12"],
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"price": i.get("f2", 0),
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"change": i.get("f3", 0),
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} for i in data.get("data", {}).get("diff", [])]
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except Exception:
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return None
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def fetch_concept_em():
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"""東方財富概念板塊"""
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try:
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data = _fetch_em(
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"https://push2.eastmoney.com/api/qt/clist/get?"
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"pn=1&pz=30&po=1&np=1&fields=f2,f3,f4,f12,f14&fs=m:90+t:3"
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)
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return [{
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"name": i["f14"],
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"code": i["f12"],
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"change": i.get("f3", 0),
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} for i in data.get("data", {}).get("diff", [])]
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except Exception:
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return None
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# ── 後端B：同花順 THS / akshare（降級） ──
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def fetch_sector_ths():
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"""THS 行業板塊（含漲跌家數、資金流向、領漲股）"""
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try:
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import akshare as ak
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df = ak.stock_board_industry_summary_ths()
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return [{
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"name": r["板块"],
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"code": "",
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"price": 0,
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"change": float(r.get("涨跌幅", 0)),
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"volume": float(r.get("总成交量", 0)),
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"turnover": float(r.get("总成交额", 0)),
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"net_inflow": float(r.get("净流入", 0)),
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"up_count": int(r.get("上涨家数", 0)),
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"down_count": int(r.get("下跌家数", 0)),
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"avg_price": float(r.get("均价", 0)),
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"lead_stock": r.get("领涨股", ""),
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"lead_stock_change": float(r.get("领涨股-涨跌幅", 0)),
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} for _, r in df.iterrows()]
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except Exception as e:
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print(f"THS行業失敗: {e}", flush=True)
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return []
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def fetch_concept_ths():
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"""THS 概念板塊（僅名稱，無實時漲跌）"""
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try:
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import akshare as ak
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df = ak.stock_board_concept_name_ths()
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return [{
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"name": r["name"],
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"code": str(r.get("code", "")),
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"change": 0,
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} for _, r in df.iterrows()]
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except Exception as e:
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print(f"THS概念失敗: {e}", flush=True)
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return []
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# ── 輔助函數 ──
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def get_market_mood(sectors):
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if not sectors:
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return "unknown"
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ratio = sum(1 for s in sectors if s.get("change", 0) > 0) / len(sectors)
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return "bullish" if ratio > 0.7 else "neutral" if ratio > 0.4 else "bearish"
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def get_market_verdict(up_ratio, mood, sectors):
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"""Return (verdict, reason) based on sector data."""
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if not sectors:
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return "unknown", "数据不足"
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if up_ratio < 25:
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return "弱势", f"仅{up_ratio}%板块上涨，{mood}"
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elif up_ratio < 40:
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return "偏弱", f"{up_ratio}%板块上涨，结构分化"
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elif up_ratio < 60:
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return "均衡", f"{up_ratio}%板块上涨，涨跌均衡"
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else:
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return "强势", f"{up_ratio}%板块上涨，整体走强"
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def get_hot_sectors(sectors, top_n=3):
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"""Return sectors with highest positive change as hot sectors."""
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hot = [s for s in sectors if s.get("change", 0) > 1.0]
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hot.sort(key=lambda s: s.get("change", 0), reverse=True)
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return [{
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"name": s["name"],
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"change": s.get("change", 0),
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"reason": f"板块涨{s.get('change',0):.1f}%"
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} for s in hot[:top_n]]
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def get_danger_sectors(sectors, top_n=3):
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"""Return sectors with lowest (negative) change as danger sectors."""
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danger = [s for s in sectors if s.get("change", 0) < -1.0]
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danger.sort(key=lambda s: s.get("change", 0))
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return [{
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"name": s["name"],
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"change": s.get("change", 0),
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"reason": f"板块跌{s.get('change',0):.1f}%"
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} for s in danger[:top_n]]
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# ── 主流程 ──
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def main():
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# 行業板塊：EM → THS → 兜底
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sectors = fetch_sector_em()
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source = "eastmoney"
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if sectors is None:
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sectors = fetch_sector_ths()
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source = "ths"
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# 概念板塊：EM → THS → 空
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concepts = fetch_concept_em()
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concept_source = "eastmoney"
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if concepts is None:
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concepts = fetch_concept_ths()
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concept_source = "ths"
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if not concepts:
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concepts = []
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concept_source = "unavailable"
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# 排序
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sorted_sectors = sorted(sectors, key=lambda s: s.get("change", 0), reverse=True)
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top_gainers = [s for s in sorted_sectors if s.get("change", 0) > 0][:5]
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top_losers = [s for s in reversed(sorted_sectors) if s.get("change", 0) < 0][:3]
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# 计算大盘数据
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up_ratio = round(
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sum(1 for s in sectors if s.get("change", 0) > 0) / max(len(sectors), 1) * 100, 1
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)
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mood = get_market_mood(sectors)
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verdict, verdict_reason = get_market_verdict(up_ratio, mood, sectors)
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market_data = {
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"timestamp": datetime.now().strftime("%Y-%m-%d %H:%M"),
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"source": source,
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"concept_source": concept_source,
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"total_sectors": len(sectors),
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"up_ratio": up_ratio,
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"mood": mood,
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"market_verdict": verdict,
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"verdict_reason": verdict_reason,
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"hot_sectors": get_hot_sectors(sectors),
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"danger_sectors": get_danger_sectors(sectors),
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"top_gainers": top_gainers,
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"top_losers": top_losers,
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"sectors": sectors,
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"concepts": concepts,
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}
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DATA_DIR.mkdir(parents=True, exist_ok=True)
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# ── SQLite 写入（替代 market.json）──
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conn = get_conn()
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init_all_tables(conn)
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ok, msg, sid = write_market_snapshot(conn, market_data)
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if ok:
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print(f"[DB] {msg}", flush=True)
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else:
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print(f"[DB] 写入失败（JSON 不受影响）: {msg}", flush=True)
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conn.close()
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# ── 大盘市场阶段（market_regime）：与回测 _load_index_ctx 同算法 ──
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# 回测用 above_ma20 + adx 做市场过滤（v_next4 要求趋势市才出手），
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# 实盘此前只有当日涨跌幅 mood，缺 MA20+ADX 的市场阶段判断 —— 此处补齐。
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try:
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import market_regime as _mr
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_regime = _mr.compute_regime()
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if _regime:
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_mr.save_regime(_regime)
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print(f"[regime] {_regime['date']} → {_regime['regime']} "
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f"(above_ma20={_regime['above_ma20']} adx={_regime['adx']})", flush=True)
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else:
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print("[regime] sh000001 数据不足，跳过", flush=True)
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except Exception as _e:
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print(f"[regime] 计算失败: {_e}", flush=True)
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# ── v_mr 均值回复扫描（每天最多一次，regime 门控内置）──
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# trend_down/choppy 时扫描深超跌小盘票，写 candidates(sector='v_mr')
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# mr_scanner 自带幂等保护：当天已有 v_mr 候选则跳过，避免重复全扫描
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try:
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import subprocess as _sp
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import sys as _sys
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_script = Path(__file__).parent / "mr_scanner.py"
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if _script.exists():
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_r = _sp.run(
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[_sys.executable, str(_script), "--top", "15"],
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capture_output=True, text=True, timeout=1500)
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if _r.stdout:
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for _line in _r.stdout.strip().splitlines():
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print(f"[mr_scanner] {_line}", flush=True)
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if _r.returncode != 0 and _r.stderr:
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print(f"[mr_scanner] stderr: {_r.stderr[:500]}", flush=True)
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else:
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print("[mr_scanner] 脚本不存在，跳过", flush=True)
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except Exception as _e:
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print(f"[mr_scanner] 调用失败: {_e}", flush=True)
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# 靜默：只寫文件，不輸出到stdout，避免cron推送
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if __name__ == "__main__":
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main()
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#!/usr/bin/env python3
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"""market_watch.py — 行業熱點數據採集，寫入 dashboard data/market.json
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數據源優先級：
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後端A：東方財富 push2 API（首選，有板塊代碼+實時指數）
|
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後端B：同花順 THS / akshare（降級，有漲跌家數+資金流向）
|
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|
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注意：當前服務器無法連通東方財富API（已被封禁/域名不可達），
|
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實際運行時自動降級到同花順 THS 後端。THS 提供90+行業板塊的
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實時漲跌、上漲/下跌家數、淨流入資金等數據，足以滿足需求。
|
||||
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輸出：data/market.json → MoFin Dashboard 市場數據展示
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"""
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import json
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from datetime import datetime
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from pathlib import Path
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from mofin_db import get_conn, init_all_tables, write_market_snapshot
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DATA_DIR = Path(__file__).parent.parent / "data"
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# ── 後端A：東方財富 push2 API（首選，有板塊代碼+實時指數） ──
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def _fetch_em(url):
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"""通用 EM API 請求"""
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import urllib.request
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req = urllib.request.Request(
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url,
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headers={"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"}
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)
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resp = urllib.request.urlopen(req, timeout=10)
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return json.loads(resp.read().decode("utf-8"))
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def fetch_sector_em():
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"""東方財富行業板塊"""
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try:
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data = _fetch_em(
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"https://push2.eastmoney.com/api/qt/clist/get?"
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"pn=1&pz=60&po=1&np=1&fields=f2,f3,f4,f12,f14&fs=m:90+t:2"
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)
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return [{
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"name": i["f14"],
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"code": i["f12"],
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"price": i.get("f2", 0),
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"change": i.get("f3", 0),
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} for i in data.get("data", {}).get("diff", [])]
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except Exception:
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return None
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def fetch_concept_em():
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"""東方財富概念板塊"""
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try:
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data = _fetch_em(
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"https://push2.eastmoney.com/api/qt/clist/get?"
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"pn=1&pz=30&po=1&np=1&fields=f2,f3,f4,f12,f14&fs=m:90+t:3"
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)
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return [{
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"name": i["f14"],
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"code": i["f12"],
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"change": i.get("f3", 0),
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} for i in data.get("data", {}).get("diff", [])]
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except Exception:
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return None
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# ── 後端B：同花順 THS / akshare（降級） ──
|
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def fetch_sector_ths():
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"""THS 行業板塊（含漲跌家數、資金流向、領漲股）"""
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try:
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import akshare as ak
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df = ak.stock_board_industry_summary_ths()
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return [{
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"name": r["板块"],
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"code": "",
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"price": 0,
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"change": float(r.get("涨跌幅", 0)),
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"volume": float(r.get("总成交量", 0)),
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"turnover": float(r.get("总成交额", 0)),
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"net_inflow": float(r.get("净流入", 0)),
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"up_count": int(r.get("上涨家数", 0)),
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"down_count": int(r.get("下跌家数", 0)),
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"avg_price": float(r.get("均价", 0)),
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"lead_stock": r.get("领涨股", ""),
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"lead_stock_change": float(r.get("领涨股-涨跌幅", 0)),
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} for _, r in df.iterrows()]
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except Exception as e:
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print(f"THS行業失敗: {e}", flush=True)
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return []
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def fetch_concept_ths():
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"""THS 概念板塊（僅名稱，無實時漲跌）"""
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try:
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import akshare as ak
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df = ak.stock_board_concept_name_ths()
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return [{
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"name": r["name"],
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"code": str(r.get("code", "")),
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"change": 0,
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} for _, r in df.iterrows()]
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except Exception as e:
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print(f"THS概念失敗: {e}", flush=True)
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return []
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# ── 輔助函數 ──
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def get_market_mood(sectors):
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if not sectors:
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return "unknown"
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ratio = sum(1 for s in sectors if s.get("change", 0) > 0) / len(sectors)
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return "bullish" if ratio > 0.7 else "neutral" if ratio > 0.4 else "bearish"
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def get_market_verdict(up_ratio, mood, sectors):
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"""Return (verdict, reason) based on sector data."""
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if not sectors:
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return "unknown", "数据不足"
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if up_ratio < 25:
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return "弱势", f"仅{up_ratio}%板块上涨，{mood}"
|
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elif up_ratio < 40:
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return "偏弱", f"{up_ratio}%板块上涨，结构分化"
|
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elif up_ratio < 60:
|
||||
return "均衡", f"{up_ratio}%板块上涨，涨跌均衡"
|
||||
else:
|
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return "强势", f"{up_ratio}%板块上涨，整体走强"
|
||||
|
||||
|
||||
def get_hot_sectors(sectors, top_n=3):
|
||||
"""Return sectors with highest positive change as hot sectors."""
|
||||
hot = [s for s in sectors if s.get("change", 0) > 1.0]
|
||||
hot.sort(key=lambda s: s.get("change", 0), reverse=True)
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||||
return [{
|
||||
"name": s["name"],
|
||||
"change": s.get("change", 0),
|
||||
"reason": f"板块涨{s.get('change',0):.1f}%"
|
||||
} for s in hot[:top_n]]
|
||||
|
||||
|
||||
def get_danger_sectors(sectors, top_n=3):
|
||||
"""Return sectors with lowest (negative) change as danger sectors."""
|
||||
danger = [s for s in sectors if s.get("change", 0) < -1.0]
|
||||
danger.sort(key=lambda s: s.get("change", 0))
|
||||
return [{
|
||||
"name": s["name"],
|
||||
"change": s.get("change", 0),
|
||||
"reason": f"板块跌{s.get('change',0):.1f}%"
|
||||
} for s in danger[:top_n]]
|
||||
|
||||
|
||||
# ── 主流程 ──
|
||||
|
||||
def main():
|
||||
# 行業板塊：EM → THS → 兜底
|
||||
sectors = fetch_sector_em()
|
||||
source = "eastmoney"
|
||||
if sectors is None:
|
||||
sectors = fetch_sector_ths()
|
||||
source = "ths"
|
||||
|
||||
# 概念板塊：EM → THS → 空
|
||||
concepts = fetch_concept_em()
|
||||
concept_source = "eastmoney"
|
||||
if concepts is None:
|
||||
concepts = fetch_concept_ths()
|
||||
concept_source = "ths"
|
||||
if not concepts:
|
||||
concepts = []
|
||||
concept_source = "unavailable"
|
||||
|
||||
# 排序
|
||||
sorted_sectors = sorted(sectors, key=lambda s: s.get("change", 0), reverse=True)
|
||||
top_gainers = [s for s in sorted_sectors if s.get("change", 0) > 0][:5]
|
||||
top_losers = [s for s in reversed(sorted_sectors) if s.get("change", 0) < 0][:3]
|
||||
|
||||
# 计算大盘数据
|
||||
up_ratio = round(
|
||||
sum(1 for s in sectors if s.get("change", 0) > 0) / max(len(sectors), 1) * 100, 1
|
||||
)
|
||||
mood = get_market_mood(sectors)
|
||||
verdict, verdict_reason = get_market_verdict(up_ratio, mood, sectors)
|
||||
|
||||
market_data = {
|
||||
"timestamp": datetime.now().strftime("%Y-%m-%d %H:%M"),
|
||||
"source": source,
|
||||
"concept_source": concept_source,
|
||||
"total_sectors": len(sectors),
|
||||
"up_ratio": up_ratio,
|
||||
"mood": mood,
|
||||
"market_verdict": verdict,
|
||||
"verdict_reason": verdict_reason,
|
||||
"hot_sectors": get_hot_sectors(sectors),
|
||||
"danger_sectors": get_danger_sectors(sectors),
|
||||
"top_gainers": top_gainers,
|
||||
"top_losers": top_losers,
|
||||
"sectors": sectors,
|
||||
"concepts": concepts,
|
||||
}
|
||||
|
||||
DATA_DIR.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
# ── SQLite 写入（替代 market.json）──
|
||||
conn = get_conn()
|
||||
init_all_tables(conn)
|
||||
ok, msg, sid = write_market_snapshot(conn, market_data)
|
||||
if ok:
|
||||
print(f"[DB] {msg}", flush=True)
|
||||
else:
|
||||
print(f"[DB] 写入失败（JSON 不受影响）: {msg}", flush=True)
|
||||
conn.close()
|
||||
|
||||
# ── 大盘市场阶段（market_regime）：与回测 _load_index_ctx 同算法 ──
|
||||
# 回测用 above_ma20 + adx 做市场过滤（v_next4 要求趋势市才出手），
|
||||
# 实盘此前只有当日涨跌幅 mood，缺 MA20+ADX 的市场阶段判断 —— 此处补齐。
|
||||
try:
|
||||
import market_regime as _mr
|
||||
_regime = _mr.compute_regime()
|
||||
if _regime:
|
||||
_mr.save_regime(_regime)
|
||||
print(f"[regime] {_regime['date']} → {_regime['regime']} "
|
||||
f"(above_ma20={_regime['above_ma20']} adx={_regime['adx']})", flush=True)
|
||||
else:
|
||||
print("[regime] sh000001 数据不足，跳过", flush=True)
|
||||
except Exception as _e:
|
||||
print(f"[regime] 计算失败: {_e}", flush=True)
|
||||
|
||||
# ── v_mr 均值回复扫描（每天最多一次，regime 门控内置）──
|
||||
# trend_down/choppy 时扫描深超跌小盘票，写 candidates(sector='v_mr')
|
||||
# mr_scanner 自带幂等保护：当天已有 v_mr 候选则跳过，避免重复全扫描
|
||||
try:
|
||||
import subprocess as _sp
|
||||
import sys as _sys
|
||||
_script = Path(__file__).parent / "mr_scanner.py"
|
||||
if _script.exists():
|
||||
_r = _sp.run(
|
||||
[_sys.executable, str(_script), "--top", "15"],
|
||||
capture_output=True, text=True, timeout=1500)
|
||||
if _r.stdout:
|
||||
for _line in _r.stdout.strip().splitlines():
|
||||
print(f"[mr_scanner] {_line}", flush=True)
|
||||
if _r.returncode != 0 and _r.stderr:
|
||||
print(f"[mr_scanner] stderr: {_r.stderr[:500]}", flush=True)
|
||||
else:
|
||||
print("[mr_scanner] 脚本不存在，跳过", flush=True)
|
||||
except Exception as _e:
|
||||
print(f"[mr_scanner] 调用失败: {_e}", flush=True)
|
||||
|
||||
# ── S2 恐慌买超跌扫描（每天最多一次，大盘RSI<25门控内置）──
|
||||
# 策略家族(§39): S1(v_weak甜区)+S2(恐慌买)同时运行零重叠
|
||||
# s2_scanner 自带幂等：当天已有 s2_panic 候选则跳过
|
||||
try:
|
||||
import subprocess as _sp2
|
||||
import sys as _sys2
|
||||
_script2 = Path(__file__).parent / "s2_scanner.py"
|
||||
if _script2.exists():
|
||||
_r2 = _sp2.run(
|
||||
[_sys2.executable, str(_script2), "--top", "15"],
|
||||
capture_output=True, text=True, timeout=1500)
|
||||
if _r2.stdout:
|
||||
for _line in _r2.stdout.strip().splitlines():
|
||||
print(f"[s2_scanner] {_line}", flush=True)
|
||||
if _r2.returncode != 0 and _r2.stderr:
|
||||
print(f"[s2_scanner] stderr: {_r2.stderr[:500]}", flush=True)
|
||||
else:
|
||||
print("[s2_scanner] 脚本不存在，跳过", flush=True)
|
||||
except Exception as _e2:
|
||||
print(f"[s2_scanner] 调用失败: {_e2}", flush=True)
|
||||
|
||||
# 靜默：只寫文件，不輸出到stdout，避免cron推送
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
|
||||
Reference in New Issue
Block a user