Building a Real-Time Futures Market Dashboard with Python and WebSockets

Real-time market data is essential for futures traders. In this guide, we'll build a dashboard that streams live futures data using Python and WebSockets. Why Real-Time Data Matters For futures day traders, especially those trading with prop firms, having access to real-time data can make the difference between a winning and losing trade. Modern platforms like NinjaTrader and Tradovate provide WebSocket APIs for streaming market data. Architecture Overview Our dashboard will consist of: A WebSocket client connecting to market data feeds A Python backend processing incoming ticks A simple web frontend displaying price charts and order book data Implementation import websockets import asyncio import json async def stream_futures_data ( symbol = " ES " ): uri = f " wss://data.example.com/stream/ { symbol } " async with websockets . connect ( uri ) as ws : async for message in ws : data = json . loads ( message ) process_tick ( data ) def process_tick ( data ): # Update OHLCV candles # Cal