COBY : specs + task 1

COBY/interfaces/aggregation_engine.py

@@ -0,0 +1,139 @@
+"""
+Interface for data aggregation and heatmap generation.
+"""
+
+from abc import ABC, abstractmethod
+from typing import Dict, List
+from ..models.core import (
+    OrderBookSnapshot, PriceBuckets, HeatmapData, 
+    ImbalanceMetrics, ConsolidatedOrderBook
+)
+
+
+class AggregationEngine(ABC):
+    """Aggregates data into price buckets and heatmaps"""
+    
+    @abstractmethod
+    def create_price_buckets(self, orderbook: OrderBookSnapshot, 
+                           bucket_size: float) -> PriceBuckets:
+        """
+        Convert order book data to price buckets.
+        
+        Args:
+            orderbook: Order book snapshot
+            bucket_size: Size of each price bucket
+            
+        Returns:
+            PriceBuckets: Aggregated price bucket data
+        """
+        pass
+    
+    @abstractmethod
+    def update_heatmap(self, symbol: str, buckets: PriceBuckets) -> HeatmapData:
+        """
+        Update heatmap data with new price buckets.
+        
+        Args:
+            symbol: Trading symbol
+            buckets: Price bucket data
+            
+        Returns:
+            HeatmapData: Updated heatmap visualization data
+        """
+        pass
+    
+    @abstractmethod
+    def calculate_imbalances(self, orderbook: OrderBookSnapshot) -> ImbalanceMetrics:
+        """
+        Calculate order book imbalance metrics.
+        
+        Args:
+            orderbook: Order book snapshot
+            
+        Returns:
+            ImbalanceMetrics: Calculated imbalance metrics
+        """
+        pass
+    
+    @abstractmethod
+    def aggregate_across_exchanges(self, symbol: str, 
+                                 orderbooks: List[OrderBookSnapshot]) -> ConsolidatedOrderBook:
+        """
+        Aggregate order book data from multiple exchanges.
+        
+        Args:
+            symbol: Trading symbol
+            orderbooks: List of order book snapshots from different exchanges
+            
+        Returns:
+            ConsolidatedOrderBook: Consolidated order book data
+        """
+        pass
+    
+    @abstractmethod
+    def calculate_volume_weighted_price(self, orderbooks: List[OrderBookSnapshot]) -> float:
+        """
+        Calculate volume-weighted average price across exchanges.
+        
+        Args:
+            orderbooks: List of order book snapshots
+            
+        Returns:
+            float: Volume-weighted average price
+        """
+        pass
+    
+    @abstractmethod
+    def get_market_depth(self, orderbook: OrderBookSnapshot, 
+                        depth_levels: List[float]) -> Dict[float, Dict[str, float]]:
+        """
+        Calculate market depth at different price levels.
+        
+        Args:
+            orderbook: Order book snapshot
+            depth_levels: List of depth percentages (e.g., [0.1, 0.5, 1.0])
+            
+        Returns:
+            Dict: Market depth data {level: {'bid_volume': x, 'ask_volume': y}}
+        """
+        pass
+    
+    @abstractmethod
+    def smooth_heatmap(self, heatmap: HeatmapData, smoothing_factor: float) -> HeatmapData:
+        """
+        Apply smoothing to heatmap data to reduce noise.
+        
+        Args:
+            heatmap: Raw heatmap data
+            smoothing_factor: Smoothing factor (0.0 to 1.0)
+            
+        Returns:
+            HeatmapData: Smoothed heatmap data
+        """
+        pass
+    
+    @abstractmethod
+    def calculate_liquidity_score(self, orderbook: OrderBookSnapshot) -> float:
+        """
+        Calculate liquidity score for an order book.
+        
+        Args:
+            orderbook: Order book snapshot
+            
+        Returns:
+            float: Liquidity score (0.0 to 1.0)
+        """
+        pass
+    
+    @abstractmethod
+    def detect_support_resistance(self, heatmap: HeatmapData) -> Dict[str, List[float]]:
+        """
+        Detect support and resistance levels from heatmap data.
+        
+        Args:
+            heatmap: Heatmap data
+            
+        Returns:
+            Dict: {'support': [prices], 'resistance': [prices]}
+        """
+        pass