feat: Scan entire date range for signals in ATR EMA strategy

src/screener/t_atr_ema_v2.py

@@ -7,48 +7,53 @@ from utils.data_utils import get_stock_data, validate_signal_date, print_signal,
 from screener.user_input import get_interval_choice, get_date_range
 from indicators.three_atr_ema import ThreeATREMAIndicator
 
-def check_entry_signal(df: pd.DataFrame) -> tuple:
+def check_entry_signal(df: pd.DataFrame) -> list:
     """
-    Check for entry signal based on Three ATR EMA strategy
+    Check for entry signals based on Three ATR EMA strategy throughout the date range
     
     Args:
         df (pd.DataFrame): DataFrame with price data
         
     Returns:
-        tuple: (bool, datetime, dict) Entry signal, signal date, and signal data
+        list: List of tuples (signal, date, signal_data) for each signal found
     """
     if len(df) < 2:  # Need at least 2 bars for comparison
-        return False, None, None
+        return []
         
     indicator = ThreeATREMAIndicator()
     results = indicator.calculate(df)
     
     if len(results) < 2:
-        return False, None, None
+        return []
+    
+    signals = []
+    
+    # Start from index 1 to compare with previous
+    for i in range(1, len(df)):
+        current = df.iloc[i]
+        previous = df.iloc[i-1]
         
-    # Get latest values
+        # Get indicator values
-    current = df.iloc[-1]
+        ema = results['ema'].iloc[i]
-    previous = df.iloc[-2]
+        lower_band = results['lower_band'].iloc[i]
+        prev_lower_band = results['lower_band'].iloc[i-1]
+        
+        # Entry conditions from Pine script:
+        entry_signal = (
+            current['close'] < ema and
+            previous['close'] <= prev_lower_band and
+            current['close'] > previous['close']
+        )
+        
+        if entry_signal:
+            signal_data = {
+                'price': current['close'],
+                'ema': ema,
+                'lower_band': lower_band
+            }
+            signals.append((True, current['date'], signal_data))
     
-    # Get indicator values
+    return signals
-    ema = results['ema'].iloc[-1]
-    lower_band = results['lower_band'].iloc[-1]
-    prev_lower_band = results['lower_band'].iloc[-2]
-    
-    # Entry conditions from Pine script:
-    entry_signal = (
-        current['close'] < ema and
-        previous['close'] <= prev_lower_band and
-        current['close'] > previous['close']
-    )
-    
-    signal_data = {
-        'price': current['close'],
-        'ema': ema,
-        'lower_band': lower_band
-    } if entry_signal else None
-    
-    return entry_signal, current['date'] if entry_signal else None, signal_data
 
 def run_atr_ema_scanner_v2(min_price: float, max_price: float, min_volume: int, portfolio_size: float = None) -> None:
     """
@@ -122,8 +127,8 @@ def run_atr_ema_scanner_v2(min_price: float, max_price: float, min_volume: int,
                 if df.empty or len(df) < 21:  # Need at least 21 bars for EMA
                     continue
                 
-                signal, signal_date, signal_data = check_entry_signal(df)
+                signals = check_entry_signal(df)
-                if signal:
+                for signal, signal_date, signal_data in signals:
                     entry_data = {
                         'ticker': ticker,
                         'entry_price': signal_data['price'],
@@ -146,8 +151,6 @@ def run_atr_ema_scanner_v2(min_price: float, max_price: float, min_volume: int,
                         })
                     
                     entry_signals.append(entry_data)
-                    
-                    # Print signal information with date
                     print_signal(entry_data)
                     
             except Exception as e: