MoFin 初始提交

完整数据采集+分析管道： - market_watch.py：90行业板块采集（同花顺/东方财富） - 市场精选推荐 cron：全市场分析+候选池+星级推荐 - price_monitor.py：持仓/自选高频价格监控 - refresh_mtf_cache.py：多周期K线缓存 - 策略评估/知识萃取管道文档：docs/ 含完整需求+架构设计注意：尚未配置 git remote，笑笑接手后自行配置
2026-06-20 12:04:21 +08:00
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+#!/usr/bin/env python3
+"""market_screener.py — 小果本地LLM全市场筛选（分步少吃多餐版）"""
+
+import json, os, re, time, urllib.request, urllib.error
+from datetime import datetime
+from pathlib import Path
+
+WEB_DASHBOARD_DIR = Path(__file__).resolve().parent.parent.parent / "web-dashboard" if "hermes" in str(Path(__file__).resolve()) else Path(__file__).parent
+DATA_DIR = WEB_DASHBOARD_DIR / "data"
+MARKET_JSON = DATA_DIR / "market.json"
+POOL_JSON = DATA_DIR / "candidate_pool.json"
+XIAOGUO_API = "http://192.168.1.122:18003/v1/chat/completions"
+XIAOGUO_MODEL = "Qwen3.6-27B-OptiQ-4bit"
+API_TIMEOUT = 60
+MAX_SECTORS = 5
+MAX_CANDIDATES_POOL = 60
+TENCENT_URL = "http://qt.gtimg.cn/q="
+
+
+def load_json(path):
+    try:
+        with open(path, "r", encoding="utf-8") as f:
+            return json.load(f)
+    except (FileNotFoundError, json.JSONDecodeError):
+        return None
+
+
+def save_json(path, data):
+    path.parent.mkdir(parents=True, exist_ok=True)
+    with open(path, "w", encoding="utf-8") as f:
+        json.dump(data, f, ensure_ascii=False, indent=2)
+
+
+def call_xiaoguo(messages, timeout=API_TIMEOUT):
+    """调用主模型（走Hermes gateway），小果本地LLM太缩水扛不住全市场分析"""
+    payload = json.dumps({"model": "hermes-agent", "messages": messages,
+                          "temperature": 0.1, "max_tokens": 2048}).encode()
+    req = urllib.request.Request("http://localhost:8643/v1/chat/completions", data=payload,
+                                 headers={"Content-Type": "application/json",
+                                          "Authorization": "Bearer hermes123"}, method="POST")
+    try:
+        resp = urllib.request.build_opener(urllib.request.ProxyHandler({})).open(req, timeout=timeout)
+        return json.loads(resp.read())["choices"][0]["message"]["content"]
+    except Exception as e:
+        print(f"API失败: {e}", flush=True)
+        return None
+
+
+def extract_json(text):
+    """从回复中提取第一个完整JSON，跳过思考过程"""
+    # 优先找代码块
+    m = re.search(r"```(?:json)?\s*(\{[\s\S]*?\})\s*```", text)
+    if m:
+        try:
+            return json.loads(m.group(1))
+        except json.JSONDecodeError:
+            pass
+    # 跳过思考过程行（Here's a thinking process / 数字列表项）
+    clean_lines = []
+    for line in text.split("\n"):
+        s = line.strip()
+        if re.match(r"^\d+\.\s+\*\*", s) or "Here's a thinking" in s or "**Analyze" in s:
+            continue
+        if s.startswith("```"):
+            clean_lines.append(s)
+            continue
+        clean_lines.append(line)
+    clean = "\n".join(clean_lines)
+    # 找第一个完整JSON
+    start = clean.find("{")
+    if start < 0:
+        return None
+    for mode in ["直接", "跳过头部"]:
+        for pos in [start, clean.find("\n{", start), clean.find("{", start + 1)]:
+            if pos < 0:
+                continue
+            depth = 0
+            for i in range(pos, len(clean)):
+                if clean[i] == "{": depth += 1
+                elif clean[i] == "}":
+                    depth -= 1
+                    if depth == 0:
+                        try:
+                            return json.loads(clean[pos:i+1])
+                        except json.JSONDecodeError:
+                            break
+    return None
+
+
+def tencent_quote(code):
+    try:
+        opener = urllib.request.build_opener(urllib.request.ProxyHandler({}))
+        tc = f"sh{code}" if code.startswith("6") or code.startswith("5") else f"sz{code}"
+        resp = opener.open(TENCENT_URL + tc, timeout=5)
+        d = resp.read().decode("gbk").split('="')[1].split('"')[0].split("~")
+        if len(d) > 32:
+            return {"name": d[1], "price": float(d[3]) if d[3] else 0,
+                    "change_pct": float(d[32]) if d[32] else 0}
+    except:
+        pass
+    return None
+
+
+def load_pool():
+    pool = load_json(POOL_JSON)
+    return pool if pool else {"last_updated": "", "total_candidates": 0, "candidates": []}
+
+
+def save_pool(pool):
+    pool["last_updated"] = datetime.now().strftime("%Y-%m-%d %H:%M")
+    pool["total_candidates"] = len([c for c in pool.get("candidates", []) if not c.get("dropped")])
+    save_json(POOL_JSON, pool)
+
+
+def add_or_update(pool, code, name, sector, score, reason, entry_range, stop_loss, target, vprice, vchg):
+    now = datetime.now().strftime("%Y-%m-%d %H:%M")
+    for c in pool.setdefault("candidates", []):
+        if c["code"] == code and not c.get("dropped"):
+            c.update({"last_updated": now, "num_observations": c.get("num_observations", 1) + 1,
+                      "xiaoguo_score": score, "xiaoguo_reason": reason,
+                      "xiaoguo_strategy": {"entry_range": entry_range, "stop_loss": stop_loss, "target": target},
+                      "verified_price": vprice, "verified_change": vchg})
+            c.setdefault("score_history", []).append({"date": now, "score": score})
+            hist = c["score_history"]
+            if len(hist) >= 3:
+                recent = [h["score"] for h in hist[-3:]]
+                c["trend_warning"] = all(recent[i] > recent[i+1] for i in range(2))
+            return False
+    pool["candidates"].append({"code": code, "name": name, "sector": sector,
+        "xiaoguo_score": score, "xiaoguo_reason": reason,
+        "xiaoguo_strategy": {"entry_range": entry_range, "stop_loss": stop_loss, "target": target},
+        "verified_price": vprice, "verified_change": vchg,
+        "added_at": now, "last_updated": now, "num_observations": 1,
+        "score_history": [{"date": now, "score": score}],
+        "zhiwei_star": None, "zhiwei_reviewed": False, "zhiwei_reviewed_at": None,
+        "promoted": False, "promoted_at": None, "dropped": False, "drop_reason": None,
+        "trend_warning": False, "trend_note": ""})
+    return True
+
+
+def cleanup(pool):
+    now = datetime.now()
+    for c in pool.get("candidates", []):
+        if c.get("dropped"): continue
+        hist = c.get("score_history", [])
+        if len(hist) >= 3 and sum(h["score"] for h in hist[-3:]) / 3 < 5:
+            c.update({"dropped": True, "drop_reason": "平均评分<5"}); continue
+        if len(hist) >= 3:
+            recent = [h["score"] for h in hist[-3:]]
+            if all(recent[i] > recent[i+1] for i in range(2)):
+                if c.get("trend_warning"): c.update({"dropped": True, "drop_reason": "连续下降2轮"})
+                else: c["trend_warning"] = True
+        if c.get("last_updated"):
+            try:
+                if (now - datetime.strptime(c["last_updated"], "%Y-%m-%d %H:%M")).days >= 7:
+                    c.update({"dropped": True, "drop_reason": "超7天未更新"})
+            except: pass
+
+
+# ── 第1步：大盘分析 ──
+def step1(sectors, source):
+    normalized = []
+    for s in sectors:
+        cp = (s.get("change", 0) / 100) if source == "eastmoney" else s.get("change", 0)
+        parts = [f"{s['name']}({cp:+.2f}%)"]
+        if s.get("lead_stock"): parts.append(f"领涨:{s['lead_stock']}")
+        if s.get("net_inflow"): parts.append(f"资金:{s['net_inflow']}亿")
+        normalized.append((" | ".join(parts), cp))
+    gainers = [x[0] for x in sorted(normalized, key=lambda x: x[1], reverse=True) if x[1] > 0][:10]
+    losers = [x[0] for x in sorted(normalized, key=lambda x: x[1]) if x[1] <= 0][:5]
+    text = "领涨板块：\n" + "\n".join(gainers)
+    if losers: text += "\n领跌板块：\n" + "\n".join(losers)
+    prompt = f"分析以下A股板块，选出3-5个值得关注的行业（只看趋势，排除一日游）。\n\n{text}\n\n输出JSON：{{\"market_verdict\":\"强势|中性|弱势\",\"hot_sectors\":[{{\"name\":\"板块名\",\"reason\":\"理由\"}}],\"danger_sectors\":[{{\"name\":\"板块名\",\"reason\":\"理由\"}}]}}"
+    print(f"  第1步：大盘分析", flush=True)
+    result = call_xiaoguo([{"role": "user", "content": prompt}])
+    return extract_json(result) if result else None
+
+
+# ── 第2步：个股分析 ──
+def step2(sector, source):
+    name = sector.get("name", "")
+    cp = (sector.get("change", 0) / 100) if source == "eastmoney" else sector.get("change", 0)
+    detail = []
+    if sector.get("up_count"): detail.append(f"上涨{sector['up_count']}/{sector['up_count']+sector.get('down_count',0)}家")
+    if sector.get("net_inflow"): detail.append(f"资金净流入{sector['net_inflow']}亿")
+    if sector.get("lead_stock"): detail.append(f"领涨{sector['lead_stock']}({sector.get('lead_stock_change',0):+.2f}%)")
+    d = " | ".join(detail) if detail else "无详细数据"
+    prompt = f"板块：{name}({cp:+.2f}%) | {d}\n推荐2-3只候选股，评分1-10，附入场区间/止损/目标。JSON：{{\"sector_judgment\":\"\",\"sector_reason\":\"\",\"candidates\":[{{\"code\":\"\",\"name\":\"\",\"score\":0,\"reason\":\"\",\"entry_range\":\"\",\"stop_loss\":\"\",\"target\":\"\"}}]}}"
+    print(f"  分析行业: {name}", flush=True)
+    result = call_xiaoguo([{"role": "user", "content": prompt}])
+    if not result: return None
+    parsed = extract_json(result)
+    if not parsed: return None
+    valid = []
+    for c in parsed.get("candidates", []):
+        q = tencent_quote(c.get("code", ""))
+        if q and q["price"] > 0:
+            c["verified_price"], c["verified_change"] = q["price"], q["change_pct"]
+            valid.append(c)
+    print(f"    候选{len(parsed.get('candidates',[]))}只, 验证通过{len(valid)}只", flush=True)
+    return valid
+
+
+def main():
+    market = load_json(MARKET_JSON)
+    if not market or not market.get("sectors"):
+        print("market.json 无数据", flush=True); return
+    sectors, source = market["sectors"], market.get("source", "ths")
+    print(f"板块: {len(sectors)}, 来源: {source}", flush=True)
+    pool = load_pool()
+    existing = {c["code"] for c in pool.get("candidates", []) if not c.get("dropped")}
+
+    # 第1步
+    view = step1(sectors, source)
+    if not view:
+        print("第1步失败", flush=True); return
+    market["market_verdict"] = view.get("market_verdict", "中性")
+    market["verdict_reason"] = view.get("verdict_reason", "")
+    market["hot_sectors"] = view.get("hot_sectors", [])
+    market["danger_sectors"] = view.get("danger_sectors", [])
+    market["xiaoguo_scan_timestamp"] = datetime.now().strftime("%Y-%m-%d %H:%M")
+    market.setdefault("insights", []).append(f"[小果全市场] {view.get('market_verdict','中性')}")
+    hot_names = [s["name"] for s in view.get("hot_sectors", [])]
+    print(f"热门行业: {hot_names}", flush=True)
+    if not hot_names:
+        save_pool(pool); save_json(MARKET_JSON, market); return
+
+    # 第2步
+    hot_data = [s for s in sectors if s.get("name", "") in hot_names][:MAX_SECTORS]
+    new_count = 0
+    for s in hot_data:
+        cands = step2(s, source)
+        if not cands: continue
+        for c in cands:
+            if add_or_update(pool, c["code"], c.get("name",""), s["name"],
+                           c.get("score",5), c.get("reason",""),
+                           c.get("entry_range",""), c.get("stop_loss",""), c.get("target",""),
+                           c.get("verified_price",0), c.get("verified_change",0)):
+                new_count += 1
+                print(f"  + {c.get('name','')}({c['code']}) {c.get('score',0)}分", flush=True)
+
+    cleanup(pool)
+    save_pool(pool)
+    save_json(MARKET_JSON, market)
+    print(f"完成: 新增{new_count}, 池内{pool['total_candidates']}活跃", flush=True)
+
+if __name__ == "__main__":
+    main()