Merge pull request #10 from TexasCoding:refactoring_14

feat(orderbook): fix volume accumulation and enhance market structure analytics

Author: TexasCoding

CHANGELOG.md

@@ -13,6 +13,50 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Old implementations are removed when improved
 - Clean, modern code architecture is prioritized
 
+## [1.1.4] - 2025-01-30
+
+### Fixed
+- **📊 OrderBook Volume Accumulation**: Fixed critical bug where market depth updates were accumulating volumes instead of replacing them
+  - Market depth updates now correctly replace volume at price levels rather than adding to them
+  - Resolved extremely high volume readings that were incorrect
+  - Fixed handling of DomType 3/4 (BestBid/BestAsk) vs regular bid/ask updates
+
+- **📈 OHLCV Volume Interpretation**: Fixed misinterpretation of GatewayQuote volume field
+  - GatewayQuote volume represents daily total, not individual trade volume
+  - OHLCV bars now correctly show volume=0 for quote-based updates
+  - Prevents unrealistic volume spikes (e.g., 29,000+ per 5-second bar)
+
+- **🔍 Trade Classification**: Improved trade side classification accuracy
+  - Now captures bid/ask prices BEFORE orderbook update for correct classification
+  - Uses historical spread data to properly classify trades as buy/sell
+  - Added null handling for edge cases
+
+### Enhanced
+- **🧊 Iceberg Detection**: Added price level refresh history tracking
+  - OrderBook now maintains history of volume updates at each price level
+  - Tracks up to 50 updates per price level over 30-minute windows
+  - Enhanced `detect_iceberg_orders` to use historical refresh patterns
+  - Added `get_price_level_history()` method for analysis
+
+- **📊 Market Structure Analysis**: Refactored key methods to use price level history
+  - `get_support_resistance_levels`: Now identifies persistent levels based on order refresh patterns
+  - `detect_order_clusters`: Finds price zones with concentrated historical activity
+  - `get_liquidity_levels`: Detects "sticky" liquidity that reappears after consumption
+  - All methods now provide institutional-grade analytics based on temporal patterns
+
+### Added
+- **🔧 Debug Scripts**: New diagnostic tools for market data analysis
+  - `working_market_depth_debug.py`: Comprehensive DOM type analysis
+  - `test_trade_classification.py`: Verify trade side classification
+  - `test_enhanced_iceberg.py`: Test iceberg detection with history
+  - `test_refactored_methods.py`: Verify all refactored analytics
+
+### Technical Details
+- Price level history stored as `dict[tuple[float, str], list[dict]]` with timestamp and volume
+- Support/resistance now uses composite strength score (40% refresh count, 30% volume, 20% rate, 10% consistency)
+- Order clusters detect "magnetic" price levels with persistent order placement
+- Liquidity detection finds market maker zones with high refresh rates
+
 ## [1.1.3] - 2025-01-29
 
 ### Fixed

README.md

@@ -24,14 +24,17 @@ This Python SDK acts as a bridge between your trading strategies and the Project
 
 **IMPORTANT**: This project is under active development. New updates may introduce breaking changes without backward compatibility. During this development phase, we prioritize clean, modern code architecture over maintaining legacy implementations.
 
-**Current Version**: v1.1.3 (Contract Selection & Interactive Demo)
+**Current Version**: v1.1.4 (Contract Selection & Interactive Demo)
 
 ✅ **Production Ready SDK Components**:
 - Complete ProjectX Gateway API integration with connection pooling
 - Historical and real-time market data APIs with intelligent caching
 - 55+ technical indicators with computation caching (Full TA-Lib compatibility)
-- Institutional-grade orderbook analysis tools with memory management and dynamic tick size detection
+- Institutional-grade orderbook analysis with price level history tracking
 - Portfolio and risk management APIs
+- **NEW v1.1.4**: Fixed orderbook volume accumulation and OHLCV interpretation
+- **NEW v1.1.4**: Enhanced iceberg detection with refresh pattern analysis
+- **NEW v1.1.4**: Market structure analytics based on temporal patterns
 - **NEW**: 50-70% performance improvements through optimization
 - **NEW**: 60% memory usage reduction with sliding windows
 - **NEW**: Sub-second response times for cached operations
@@ -310,9 +313,15 @@ orderbook = create_orderbook("MGC", project_x=client)  # Uses real instrument me
 depth_snapshot = orderbook.get_orderbook_snapshot()
 best_prices = orderbook.get_best_bid_ask()
 
-# Advanced analysis
-iceberg_orders = orderbook.detect_iceberg_orders()
-imbalance = orderbook.calculate_order_imbalance()
+# Advanced analysis with price level history
+iceberg_orders = orderbook.detect_iceberg_orders()  # Now uses refresh patterns
+support_resistance = orderbook.get_support_resistance_levels()  # Persistent levels
+order_clusters = orderbook.detect_order_clusters()  # Historical activity zones
+liquidity_levels = orderbook.get_liquidity_levels(min_volume=5)  # Sticky liquidity
+
+# Price level history tracking
+history_stats = orderbook.get_price_level_history()
+print(f"Tracked levels: {history_stats['total_tracked_levels']}")
 
 # Monitor memory usage
 memory_stats = orderbook.get_memory_stats()
@@ -611,7 +620,7 @@ We welcome contributions! Please follow these guidelines:
 
 ## 📝 Changelog
 
-### Version 1.1.3 (Latest) - 2025-01-29
+### Version 1.1.4 (Latest) - 2025-01-29
 **🔧 Contract Selection & Interactive Tools**
 
 **Breaking Changes:**

docs/api/orderbook.rst

@@ -6,7 +6,9 @@ Advanced Level 2 orderbook management and market microstructure analysis.
 Overview
 --------
 
-The OrderBook class provides institutional-grade orderbook analytics for real-time market depth analysis. It includes advanced features like iceberg order detection, market imbalance analysis, volume profiling, and dynamic support/resistance identification.
+The OrderBook class provides institutional-grade orderbook analytics for real-time market depth analysis. It includes advanced features like iceberg order detection with price level history tracking, market imbalance analysis, volume profiling, and dynamic support/resistance identification based on temporal patterns.
+
+**New in v1.1.4**: Enhanced analytics using price level refresh history for detecting persistent levels, iceberg orders, and market maker activity zones.
 
 .. currentmodule:: project_x_py
 

docs/conf.py

@@ -23,8 +23,8 @@
 project = "project-x-py"
 copyright = "2025, Jeff West"
 author = "Jeff West"
-release = "1.1.3"
-version = "1.1.3"
+release = "1.1.4"
+version = "1.1.4"
 
 # -- General configuration ---------------------------------------------------
 

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "project-x-py"
-version = "1.1.3"
+version = "1.1.4"
 description = "High-performance Python SDK for futures trading with real-time WebSocket data, technical indicators, order management, and market depth analysis"
 readme = "README.md"
 license = { text = "MIT" }
@@ -34,6 +34,7 @@ dependencies = [
     "polars>=1.31.0", # TODO: Update to 1.31.0
     "pytz>=2025.2",
     "requests>=2.32.4",
+    "rich>=14.1.0",
     "signalrcore>=0.9.5",
     "websocket-client>=1.0.0",
 ]

src/project_x_py/__init__.py

@@ -23,7 +23,7 @@
 
 from typing import Any, Optional
 
-__version__ = "1.1.3"
+__version__ = "1.1.4"
 __author__ = "TexasCoding"
 
 # Core client classes

src/project_x_py/indicators/__init__.py

@@ -134,7 +134,7 @@
 )
 
 # Version info
-__version__ = "1.1.3"
+__version__ = "1.1.4"
 __author__ = "TexasCoding"