fix TA warning

core/data_provider.py

@@ -1334,10 +1334,10 @@ class DataProvider:
             df['psar'] = psar.psar()
             
             # === MOMENTUM INDICATORS ===
-            # RSI (multiple periods)
-            df['rsi_14'] = ta.momentum.rsi(df['close'], window=14)
-            df['rsi_7'] = ta.momentum.rsi(df['close'], window=7)
-            df['rsi_21'] = ta.momentum.rsi(df['close'], window=21)
+            # RSI (multiple periods) - using our own implementation to avoid ta library deprecation warnings
+            df['rsi_14'] = self._calculate_rsi(df['close'], period=14)
+            df['rsi_7'] = self._calculate_rsi(df['close'], period=7)
+            df['rsi_21'] = self._calculate_rsi(df['close'], period=21)
             
             # Stochastic Oscillator
             stoch = ta.momentum.StochasticOscillator(df['high'], df['low'], df['close'])
@@ -2191,9 +2191,9 @@ class DataProvider:
                 df['sma_20'] = ta.trend.sma_indicator(df['close'], window=20)
                 df['ema_12'] = ta.trend.ema_indicator(df['close'], window=12)
             
-            # Basic RSI
+            # Basic RSI - using our own implementation to avoid ta library deprecation warnings
             if len(df) >= 14:
-                df['rsi_14'] = ta.momentum.rsi(df['close'], window=14)
+                df['rsi_14'] = self._calculate_rsi(df['close'], period=14)
             
             # Basic volume indicators
             if len(df) >= 10:
@@ -2212,6 +2212,31 @@ class DataProvider:
             logger.error(f"Error adding basic indicators: {e}")
             return df
     
+    def _calculate_rsi(self, prices: pd.Series, period: int = 14) -> float:
+        """Calculate RSI (Relative Strength Index) - custom implementation to avoid ta library deprecation warnings"""
+        try:
+            if len(prices) < period + 1:
+                return 50.0  # Default neutral value
+            
+            # Calculate price changes
+            delta = prices.diff()
+            
+            # Separate gains and losses
+            gain = (delta.where(delta > 0, 0)).rolling(window=period).mean()
+            loss = (-delta.where(delta < 0, 0)).rolling(window=period).mean()
+            
+            # Calculate RS and RSI
+            rs = gain / loss
+            rsi = 100 - (100 / (1 + rs))
+            
+            # Return the last value, or 50 if NaN
+            last_rsi = rsi.iloc[-1]
+            return float(last_rsi) if not pd.isna(last_rsi) else 50.0
+            
+        except Exception as e:
+            logger.debug(f"Error calculating RSI: {e}")
+            return 50.0  # Default neutral value
+    
     def _load_from_cache(self, symbol: str, timeframe: str) -> Optional[pd.DataFrame]:
         """Load data from cache"""
         try: