Real-Time Orderbook Visualization

Live market data heatmap with whale order tracking and temporal depth analysis.

Features

• Real-time orderbook heatmap with PyQtGraph visualization
• Large order tracking - whale detection and lifecycle monitoring
• Temporal visualization - time-based depth analysis
• Interactive controls - configurable whale thresholds
• Live data streaming from Databento professional market data

Sample Output

Real-time orderbook depth heatmap with bid/ask visualization

Technical Architecture

Databento Live API → In-Memory OrderBook → PyQtGraph Heatmap

Core Technologies:

• PySide6 - Desktop GUI framework
• PyQtGraph - Real-time plotting and visualization
• Databento - Professional market data API
• NumPy - Numerical array operations
• Custom OrderBook Engine - In-memory order tracking
• Whale Tracker - Large order lifecycle monitoring

Key Features:

• Real-time data streaming with QThread
• Interactive heatmap visualization
• Large order detection and tracking
• Configurable whale size thresholds
• Temporal depth analysis

Data Processing

OrderBook Engine

• In-memory order tracking - Fast access to current market state
• Price-time priority - Standard order book organization
• Real-time updates - Add/Modify/Cancel order processing
• Efficient data structures - Custom price level management

Real-time Heatmap Visualization

• Temporal depth analysis - Time flows left-to-right across heatmap
• Price-level granularity - 0.25 tick precision for ES futures
• Bid/Ask color mapping - Blue (bids at bottom) vs Red (asks at top)
• Dynamic price range - Auto-adjusts around best bid/offer
• Matrix transpose optimization - Proper PyQtGraph orientation

Whale Order Tracking

• Large order detection - Configurable size thresholds
• Order lifecycle monitoring - Add/Modify/Cancel tracking
• Visual overlays - Colored rectangles showing whale positions
• Historical preservation - Completed order tracking
• Order ID mapping - Full lifecycle from placement to completion

Live Data Processing

• Databento MBO streaming - Market-by-order level 3 data
• Snapshot initialization - Full orderbook state on startup
• Real-time order processing - Sub-second update cycles
• Thread-safe operations - QThread-based data streaming

Implementation Details

Application Architecture

• Main Window - PySide6 QMainWindow with control buttons
• Data Thread - QThread for live Databento streaming
• Heatmap Widget - PyQtGraph-based visualization component
• Whale Tracker - Large order detection and lifecycle management

Technical Implementation

• Matrix transpose optimization - Proper PyQtGraph ImageItem orientation
• Dynamic price ranging - Auto-adjustment around best bid/offer
• Thread-safe operations - Signal/slot communication between threads
• Memory management - Efficient NumPy array operations

Skills Demonstrated

Desktop Application Development:

• PySide6 GUI application architecture
• Multi-threaded application design
• Real-time data visualization
• Interactive user interface controls

Financial Data Processing:

• Market data API integration (Databento)
• Order book reconstruction and management
• Large order detection and tracking
• Real-time market depth analysis

Data Visualization:

• PyQtGraph real-time plotting
• Heatmap visualization techniques
• Custom colormap and axis formatting
• Matrix orientation and data mapping

Software Engineering:

• Modular code organization
• Thread-safe communication patterns
• Configuration management
• Error handling and logging

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Note: This project demonstrates real-time financial data visualization with professional market data integration and interactive analysis tools.