feat(screener): ScreenContext.news_sentiment field + load query

stock-lab/app/screener/engine.py

@@ -17,6 +17,7 @@ class ScreenContext:
     flow:   pd.DataFrame                       # cols: ticker,date,foreign_net,institution_net
     kospi:  pd.Series                          # index=date(str), name="kospi"
     asof:   dt.date
+    news_sentiment: "pd.DataFrame | None" = None
 
     @classmethod
     def load(cls, conn: sqlite3.Connection, asof: dt.date,
@@ -38,6 +39,10 @@ class ScreenContext:
             "FROM krx_flow WHERE date BETWEEN ? AND ? ORDER BY date",
             conn, params=(cutoff, asof_iso),
         )
+        news_sentiment = pd.read_sql_query(
+            "SELECT ticker, score_raw, news_count FROM news_sentiment WHERE date = ?",
+            conn, params=(asof_iso,),
+        )
 
         # KOSPI 지수: MVP에서는 005930(삼성전자) 종가를 시장 대용으로 사용.
         # 후속 슬라이스에서 ^KS11 별도 캐시.
@@ -47,7 +52,8 @@ class ScreenContext:
             kospi = sub.copy()
             kospi.name = "kospi"
 
-        return cls(master=master, prices=prices, flow=flow, kospi=kospi, asof=asof)
+        return cls(master=master, prices=prices, flow=flow, kospi=kospi, asof=asof,
+                   news_sentiment=news_sentiment)
 
     def restrict(self, tickers) -> "ScreenContext":
         tickers = pd.Index(tickers)