main cleanup

core/data_provider.py

@@ -1,6 +1,12 @@
 """
 Multi-Timeframe, Multi-Symbol Data Provider
 
+CRITICAL POLICY: NO SYNTHETIC DATA ALLOWED
+This module MUST ONLY use real market data from exchanges.
+NEVER use np.random.*, mock/fake/synthetic data, or placeholder values.
+If data is unavailable: return None/0/empty, log errors, raise exceptions.
+See: reports/REAL_MARKET_DATA_POLICY.md
+
 This module consolidates all data functionality including:
 - Historical data fetching from Binance API
 - Real-time data streaming via WebSocket
@@ -227,6 +233,40 @@ class DataProvider:
             logger.warning(f"Error ensuring datetime index: {e}")
             return df
     
+    def get_price_range_over_period(self, symbol: str, start_time: datetime,
+                                  end_time: datetime, timeframe: str = '1m') -> Optional[Dict[str, float]]:
+        """Get min/max price and other statistics over a specific time period"""
+        try:
+            # Get historical data for the period
+            data = self.get_historical_data(symbol, timeframe, limit=50000, refresh=False)
+            if data is None:
+                return None
+
+            # Filter data for the time range
+            data = data[(data.index >= start_time) & (data.index <= end_time)]
+
+            if len(data) == 0:
+                return None
+
+            # Calculate statistics
+            price_range = {
+                'min_price': float(data['low'].min()),
+                'max_price': float(data['high'].max()),
+                'open_price': float(data.iloc[0]['open']),
+                'close_price': float(data.iloc[-1]['close']),
+                'avg_price': float(data['close'].mean()),
+                'price_volatility': float(data['close'].std()),
+                'total_volume': float(data['volume'].sum()),
+                'data_points': len(data),
+                'time_range_seconds': (end_time - start_time).total_seconds()
+            }
+
+            return price_range
+
+        except Exception as e:
+            logger.error(f"Error getting price range for {symbol}: {e}")
+            return None
+
     def get_historical_data(self, symbol: str, timeframe: str, limit: int = 1000, refresh: bool = False) -> Optional[pd.DataFrame]:
         """Get historical OHLCV data for a symbol and timeframe"""
         try:
@@ -985,6 +1025,33 @@ class DataProvider:
             support_levels = sorted(list(set(support_levels)))
             resistance_levels = sorted(list(set(resistance_levels)))
             
+            # Extract trend context from pivot levels
+            pivot_context = {
+                'nested_levels': len(pivot_levels),
+                'level_details': {}
+            }
+
+            # Get trend info from primary level (level_0)
+            if 'level_0' in pivot_levels and pivot_levels['level_0']:
+                level_0 = pivot_levels['level_0']
+                pivot_context['trend_direction'] = getattr(level_0, 'trend_direction', 'UNKNOWN')
+                pivot_context['trend_strength'] = getattr(level_0, 'trend_strength', 0.0)
+            else:
+                pivot_context['trend_direction'] = 'UNKNOWN'
+                pivot_context['trend_strength'] = 0.0
+
+            # Add details for each level
+            for level_key, level_data in pivot_levels.items():
+                if level_data:
+                    level_info = {
+                        'swing_points_count': len(getattr(level_data, 'swing_points', [])),
+                        'support_levels_count': len(getattr(level_data, 'support_levels', [])),
+                        'resistance_levels_count': len(getattr(level_data, 'resistance_levels', [])),
+                        'trend_direction': getattr(level_data, 'trend_direction', 'UNKNOWN'),
+                        'trend_strength': getattr(level_data, 'trend_strength', 0.0)
+                    }
+                    pivot_context['level_details'][level_key] = level_info
+
             # Create PivotBounds object
             bounds = PivotBounds(
                 symbol=symbol,
@@ -994,7 +1061,7 @@ class DataProvider:
                 volume_min=float(volume_min),
                 pivot_support_levels=support_levels,
                 pivot_resistance_levels=resistance_levels,
-                pivot_context=pivot_levels,
+                pivot_context=pivot_context,
                 created_timestamp=datetime.now(),
                 data_period_start=monthly_data['timestamp'].min(),
                 data_period_end=monthly_data['timestamp'].max(),