Initial commit: cc-cursor 全链路量化研究平台

7 Sprints 全部完成:
  Sprint 0: 基础设施 (DataManager + MariaDB)
  Sprint 1: 因子引擎 (34因子/12分类)
  Sprint 2: VectorBT 回测 (5策略+截面)
  Sprint 3: Optuna 优化 (+Walk-Forward)
  Sprint 4: ML 模型 (LightGBM+CatBoost)
  Sprint 5: Qwen 情绪因子 (三源新闻+日期对齐)
  Sprint 6: Agent 系统 (4Agent+日报.md/.html)

生产加固 (15项): Tushare双源fallback, SSH自动恢复, pool_pre_ping,
  save_daily先删后插, load_dotenv绝对路径, 日报5d/20d修复,
  RiskAgent改上证指数, 昨日对比+数据截止, mac_report utf8mb4,
  CLAUDE-*.md 9条已知Bug, demo全参数化, djapi数据源归一化,
  indexDatas API修正

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

finance/cli/demo_sentiment.py

@@ -0,0 +1,103 @@
+"""
+Sprint 5 验证脚本 — 情绪因子快速验证。
+
+用法:
+    python cli/demo_sentiment.py
+    python cli/demo_sentiment.py --ts_code 600519.SH
+    python cli/demo_sentiment.py --ts_code 000001.SZ --no-qwen
+"""
+
+import sys, os, argparse
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+import pandas as pd
+from data.data_manager import DataManager
+from factors.sentiment.news_source import NewsSource, align_news_to_trading_days
+from factors.sentiment.qwen_client import QwenClient
+from factors.sentiment.sentiment_engine import SentimentEngine
+
+
+def main():
+    p = argparse.ArgumentParser(description="Sprint 5 — 情绪因子快速验证")
+    p.add_argument("--ts_code", default="000001.SZ", help="测试股票代码")
+    p.add_argument("--no-qwen", action="store_true", help="跳过 Qwen 情绪分析")
+    args = p.parse_args()
+
+    print("=" * 60)
+    print("Sprint 5 — Qwen 情绪因子验证")
+    print("=" * 60)
+
+    dm = DataManager(); dm.init_db()
+
+    print("\n[1/5] 新闻数据源测试...")
+    news_src = NewsSource(use_mcp=False)
+    news_df = news_src.fetch(args.ts_code, max_news=10)
+    if not news_df.empty:
+        print("  获取 {} 条新闻".format(len(news_df)))
+        for _, row in news_df.head(3).iterrows():
+            print("  [{}] {}... (source={})".format(row["date"], str(row["title"])[:80], row["source"]))
+    else:
+        print("  (无新闻数据)")
+    print("[OK]")
+
+    print("\n[2/5] 日期对齐测试...")
+    from data.data_manager import DataManager as DM
+    price = dm.get_daily(args.ts_code) if dm.get_daily(args.ts_code) is not None else dm.get_daily("000001.SZ")
+    if price is not None and not price.empty:
+        price = price.set_index("trade_date").sort_index()
+        daily_idx = pd.to_datetime(price.index, format="%Y%m%d", errors="coerce")
+        test_news = pd.DataFrame({"date": ["20240601", "20240602", "20240603"],
+                                  "title": ["周六新闻", "周日新闻", "周一新闻"],
+                                  "content": [""] * 3, "source": ["test"] * 3, "url": [""] * 3})
+        aligned = align_news_to_trading_days(test_news, daily_idx)
+        for _, row in aligned.iterrows():
+            print("  {}: {}".format(row["title"], row["date"]))
+    print("[OK]")
+
+    print("\n[3/5] Qwen 客户端状态...")
+    client = QwenClient()
+    has_api = bool(client.api_key) or bool(client.local_base_url)
+    if has_api and not args.no_qwen:
+        mode = "本地Ollama/{}".format(client.local_model) if client.local_base_url else "DashScope/{}".format(client.model)
+        print("  模式: {}".format(mode))
+    else:
+        print("  模式: 未配置或跳过")
+    print("[OK]")
+
+    print("\n[4/5] SentimentEngine 全链路 (max_news=10)...")
+    try:
+        sent_engine = SentimentEngine(dm, qwen_client=client, news_source=news_src)
+        sent_df = sent_engine.compute(args.ts_code, max_news=10)
+        if sent_df is not None and not sent_df.empty:
+            valid = sent_df.dropna(how="all")
+            print("  情绪因子: {}".format(list(sent_df.columns)))
+            print("  有效行: {}/{}".format(len(valid), len(sent_df)))
+            if not valid.empty:
+                print(valid.tail(5).round(4).to_string())
+    except Exception as e:
+        print("  [WARN] {}".format(e))
+    print("[OK]")
+
+    print("\n[5/5] 分析范围解析...")
+    scope = sent_engine.get_scope_stocks()
+    print("  成分股数量: {}".format(len(scope)))
+    if scope:
+        print("  示例: {}".format(", ".join(scope[:5])))
+    print("[OK]")
+
+    try:
+        from reports.storage import save_report
+        save_report("## 情绪因子验证 — {}\n\n- 新闻源: OK\n- 日期对齐: OK\n- Qwen: {}".format(
+            args.ts_code, "就绪" if has_api else "未配置"),
+            "情绪因子验证", subject_type="stock", subject_code=args.ts_code)
+        print("  报告已存入 DB")
+    except Exception:
+        pass
+
+    print("\n" + "=" * 60)
+    print("Sprint 5 验证完成")
+    print("=" * 60)
+
+
+if __name__ == "__main__":
+    main()