refactor: Modify view_stock_details to show detailed query and raw results

src/screener/t_sunnyband.py

@@ -169,20 +169,80 @@ def view_stock_details(ticker: str, interval: str, start_date: datetime, end_dat
     print(f"Date Range: {start_date.date()} to {end_date.date()}")
     
     try:
-        # Get price data
-        df = get_stock_data(ticker, start_date, end_date, interval)
+        # Construct query
+        client = create_client()
+        today = datetime.now().date()
+        start_date = today - timedelta(days=60)
         
-        if df.empty:
-            print("No data found for this stock")
+        if interval == "daily":
+            table = "stock_prices_daily"
+            date_col = "date"
+            query = f"""
+                SELECT 
+                    {date_col} as date,
+                    open,
+                    high,
+                    low,
+                    close,
+                    volume
+                FROM stock_db.{table}
+                WHERE ticker = '{ticker}'
+                AND {date_col} BETWEEN '{start_date}' AND '{today}'
+                ORDER BY date ASC
+            """
+        else:
+            table = "stock_prices"
+            date_col = "window_start"
+            minutes_map = {
+                "5min": 5,
+                "15min": 15,
+                "30min": 30,
+                "1hour": 60
+            }
+            minutes = minutes_map[interval]
+            
+            query = f"""
+                SELECT 
+                    fromUnixTimestamp(intDiv({date_col}, 300) * 300) as interval_start,
+                    min(open) as open,
+                    max(high) as high,
+                    min(low) as low,
+                    argMax(close, {date_col}) as close,
+                    sum(volume) as volume
+                FROM stock_db.{table}
+                WHERE ticker = '{ticker}'
+                AND {date_col} BETWEEN toUnixTimestamp('{start_date}') AND toUnixTimestamp('{today}')
+                GROUP BY interval_start
+                ORDER BY interval_start ASC
+            """
+        
+        # Print the actual query being executed
+        print("\nExecuting Query:")
+        print(query)
+        
+        # Execute query and get results
+        result = client.query(query)
+        
+        if not result.result_rows:
+            print("\nNo data found for this stock")
             return
             
-        print("\nData Sample:")
-        print("First 5 rows:")
-        print(df.head().to_string())
-        print("\nLast 5 rows:")
-        print(df.tail().to_string())
+        # Convert to DataFrame
+        df = pd.DataFrame(
+            result.result_rows,
+            columns=['date', 'open', 'high', 'low', 'close', 'volume']
+        )
         
-        print(f"\nTotal rows: {len(df)}")
+        # Print raw query results
+        print("\nRaw Query Results:")
+        print(f"Number of rows returned: {len(result.result_rows)}")
+        print("\nFirst 5 rows of raw data:")
+        for i, row in enumerate(result.result_rows[:5]):
+            print(f"Row {i + 1}: {row}")
+        
+        print("\nLast 5 rows of raw data:")
+        for i, row in enumerate(result.result_rows[-5:]):
+            print(f"Row {len(result.result_rows) - 4 + i}: {row}")
         
         # Calculate SunnyBands
         sunny = SunnyBands()