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Ever dreamed of launching your own automated trading bot that reacts to live market moves in milliseconds—without getting stuck on unreliable data or messy setup? 👀

This is exactly what developers are doing today with real-time stock, forex, and crypto APIs.

In this quick post, I’ll show you how to get your first trading bot prototype running in just 30 minutes. Perfect for anyone who wants to test ideas fast and see real data in action.

✅ Step 1: Get Your API Key

Head over to Finage and sign up for an account. You’ll receive your API key in just a few minutes—no long forms, no fuss.

✅ Step 2: Connect to the WebSocket

We’ll use Python and the websocket library to connect to real-time US stock data.

Here’s a simple example:

import websocket
import json

SOCKET_URL = "wss://abcd1234.finage.ws:7000/?token=YOUR_SOCKET_KEY"

def on_message(ws, message):
    print(f"Received: {message}")

def on_open(ws):
    subscribe_message = {
        "action": "subscribe",
        "symbols": "AMZN,TSLA"
    }
    ws.send(json.dumps(subscribe_message))

ws = websocket.WebSocketApp(SOCKET_URL, on_message=on_message)
ws.on_open = on_open
ws.run_forever()

✅ What this does:

  • Connects to Finage’s real-time data WebSocket.
  • Subscribes to live updates for Amazon (AMZN) and Tesla (TSLA).
  • Prints out every price update you receive.

✅ Step 3: Add Basic Trading Logic

This is the fun part! Once you’re getting live data, you can start adding simple if-else logic to simulate trades. For example:

def on_message(ws, message):
    data = json.loads(message)
    price = float(data['price'])  # example structure

    if price > 1500:
        print("Sell signal triggered 🚨")
    else:
        print("Buy signal triggered ✅")

Of course, real bots need more complex strategies, risk management, and error handling—but this gets you off the ground.

✅ Step 4: Avoid This #1 Mistake

Many devs start out using free or unreliable data… which is great for testing but a disaster when you try to scale.

Why? Because:

  • Delayed data = missed opportunities.
  • Unstable APIs = broken bots.
  • Incomplete data = bad decisions.

👉 Pro tip: Always use real-time, production-ready data even for your prototypes, especially if you want to build confidence that your bot will scale.

🚀 What You’ve Built

By following these simple steps, you now have:
✅ A live connection to Wall Street-level data.
✅ A trading bot prototype that reacts in real time.
✅ The confidence to move toward a production-ready solution.

This 30-minute flow is the first step—but the hardest part is starting, and you’ve done that 💪.

Let me know if you try this out or if you have any questions! 👇

🔗 Check out Finage’s APIs to keep building 🚀