fix: add validation and rate limiting to ValuationCollector

- Add time import and RATE_LIMIT_DELAY constant for rate limiting between HTTP requests
- Add 1-second delay after OTP request to respect API rate limits
- Validate OTP response is not empty before using it
- Add CSV column structure validation with required columns check
- Add data quality check to skip records where all metrics are None
- Improve error handling and data integrity

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

backend/app/services/collectors/valuation_collector.py

@@ -2,6 +2,7 @@
 Valuation data collector from KRX.
 """
 import logging
+import time
 from io import BytesIO
 from datetime import datetime
 
@@ -28,6 +29,7 @@ class ValuationCollector(BaseCollector):
         "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36",
     }
     REQUEST_TIMEOUT = 10
+    RATE_LIMIT_DELAY = 1
 
     def __init__(self, db: Session, biz_day: str = None):
         super().__init__(db)
@@ -71,9 +73,15 @@ class ValuationCollector(BaseCollector):
             )
             otp.raise_for_status()
 
+            otp_code = otp.text.strip()
+            if not otp_code:
+                raise RuntimeError("Received empty OTP from KRX API")
+
+            time.sleep(self.RATE_LIMIT_DELAY)
+
             response = requests.post(
                 self.DOWN_URL,
-                data={"code": otp.text},
+                data={"code": otp_code},
                 headers=self.HEADERS,
                 timeout=self.REQUEST_TIMEOUT
             )
@@ -82,7 +90,18 @@ class ValuationCollector(BaseCollector):
             raise RuntimeError(f"Failed to fetch valuation data: {e}")
 
         df = pd.read_csv(BytesIO(response.content), encoding="EUC-KR")
+
+        if df.empty:
+            logger.warning(f"Empty CSV response for {self.biz_day}")
+            return 0
+
         df.columns = df.columns.str.replace(" ", "")
+
+        required_cols = ["종목코드", "PER", "PBR", "배당수익률"]
+        missing_cols = [col for col in required_cols if col not in df.columns]
+        if missing_cols:
+            raise ValueError(f"Required columns missing from CSV: {missing_cols}")
+
         base_date = datetime.strptime(self.biz_day, "%Y%m%d").date()
 
         logger.info(f"Processing {len(df)} valuation records for {self.biz_day}")
@@ -93,14 +112,22 @@ class ValuationCollector(BaseCollector):
             if not ticker or pd.isna(ticker):
                 continue
 
+            per = self._safe_float(row.get("PER"))
+            pbr = self._safe_float(row.get("PBR"))
+            dividend_yield = self._safe_float(row.get("배당수익률"))
+
+            # Skip records where all metrics are None
+            if all(v is None for v in [per, pbr, dividend_yield]):
+                continue
+
             records.append({
                 "ticker": ticker,
                 "base_date": base_date,
-                "per": self._safe_float(row.get("PER")),
+                "per": per,
-                "pbr": self._safe_float(row.get("PBR")),
+                "pbr": pbr,
                 "psr": None,  # Not available from this endpoint
                 "pcr": None,  # Not available from this endpoint
-                "dividend_yield": self._safe_float(row.get("배당수익률")),
+                "dividend_yield": dividend_yield,
             })
 
         if records: