Stream US stock ticks in real time with Python and WebSocket

The problem with polling market data

If you’ve ever tried to fetch live US stock prices using REST APIs, you know the struggle: rate limits kick in when you need data the most, and the time between requests creates blind spots. For tick-by-tick analysis — like detecting volume spikes or order-flow imbalances — polling just doesn’t cut it.

Real-time push with WebSocket

WebSocket lets the server push every trade directly to you, eliminating polling delays and rate limits. I recently built a real-time tick feed for hot US stocks using Python and a WebSocket API. The data provider I used (AllTick) delivers each trade as a JSON object with symbol, price, and volume — super easy to parse.

Let’s see the code

Here’s the simplest version to get you started:

import websocket
import json

def on_message(ws, message):
    data = json.loads(message)
    # Print price and volume for every trade
    print(f"{data['symbol']} price: {data['price']} volume: {data['volume']}")

def on_open(ws):
    # Subscribe to a few popular tickers
    symbols = ["AAPL", "TSLA", "AMZN"]
    for symbol in symbols:
        ws.send(json.dumps({
            "action": "subscribe",
            "symbol": symbol
        }))

ws = websocket.WebSocketApp("wss://apis.alltick.co/ws/stock-tick",
                            on_message=on_message,
                            on_open=on_open)
ws.run_forever()

Run it, and you’ll see a live stream of every trade for Apple, Tesla, and Amazon. It’s that fast.

What to do with the data

• Store it in Redis for ultra-fast access and real-time dashboards.
• Archive to SQLite or PostgreSQL for backtesting.
• Build a Streamlit dashboard to visualize volume leaders in real time.

Make it production-ready

• Auto-reconnect: Handle on_close and reconnect with backoff.
• Deduplication: Use the trade ID to avoid double-counting.
• Async: Use asyncio or websockets library for non-blocking I/O.
• Heartbeat: Keep the connection alive with ping/pong.

Final thoughts

Streaming real-time stock ticks is easier than most developers think. With a few lines of Python and a reliable WebSocket endpoint, you can turn your local machine into a powerful market monitoring station. I’ve been using this setup daily to feed our quant models, and it hasn’t missed a beat. Give it a try and see what insights you can uncover!