DEV Community

Market Masters
Market Masters

Posted on

Build a Trading Bot with the MarketMasters API in Python

Build a Trading Bot with the MarketMasters API in Python

Trading Bot Dashboard

Learn how to automate your trading decisions with real-time market data and technical indicators.

Why Build a Trading Bot?

Trading is emotional. A bot isn't. By automating your strategy, you:

  • Remove emotion from entries and exits
  • Execute trades instantly when conditions are met
  • Monitor multiple markets 24/7
  • Backtest strategies with historical data

In this guide, we'll build a simple trading bot using the MarketMasters API — which gives you institutional-grade data including klines, chart patterns, Elliott Wave analysis, and more.

Prerequisites 

pip install requests pandas
Enter fullscreen mode Exit fullscreen mode

You'll need a MarketMasters API key from marketmasters.ai/profile/account.

Step 1: Set Up the API Client 

import requests

BASE_URL = "https://api.marketmasters.ai/v1"
API_KEY = "your_api_key_here"

headers = {
    "x-api-key": API_KEY
}

def get_klines(symbol, timeframe="1h", limit=50):
    url = f"{BASE_URL}/klines"
    params = {"symbol": symbol, "timeframe": timeframe, "limit": limit}
    response = requests.get(url, headers=headers, params=params)
    return response.json()
Enter fullscreen mode Exit fullscreen mode

The API returns klines with embedded indicators: RSI(14), ADX(14), DMI+/-, ROC(9), and volume metrics.

Step 2: Analyze the Data 

def analyze_signal(klines):
    latest = klines[-1]
    rsi = latest[8]    # RSI(14)
    adx = latest[9]    # ADX(14)
    dmi_plus = latest[10]
    dmi_minus = latest[11]

    if rsi < 30 and adx > 20 and dmi_plus > dmi_minus:
        return "BUY"
    elif rsi > 70 and adx > 20 and dmi_minus > dmi_plus:
        return "SELL"
    return "HOLD"

btc_data = get_klines("BTCUSDT", "1h", 20)
print(f"Signal: {analyze_signal(btc_data)}")
Enter fullscreen mode Exit fullscreen mode

Step 3: Chart Patterns 

def get_active_patterns(symbols="BTCUSDT,ETHUSDT,SOLUSDT"):
    url = f"{BASE_URL}/chartpatterns"
    params = {"symbols": symbols}
    return requests.get(url, headers=headers, params=params).json()

patterns = get_active_patterns()
for pattern in patterns:
    if pattern.get("score", 0) > 80:
        print(f"{pattern['symbol']}: {pattern['type']}")
Enter fullscreen mode Exit fullscreen mode

Step 4: Elliott Wave 

def get_elliott_wave(symbol, tf="4h"):
    url = f"{BASE_URL}/elliottwave"
    return requests.get(url, headers=headers, params={"symbols": symbol, "timeframe": tf}).json()
Enter fullscreen mode Exit fullscreen mode

Step 5: Trading Loop 

import time

def trading_loop():
    symbols = ["BTCUSDT", "ETHUSDT", "SOLUSDT"]
    while True:
        for symbol in symbols:
            klines = get_klines(symbol, "1h", 20)
            print(f"{symbol}: {analyze_signal(klines)}")
        time.sleep(3600)
Enter fullscreen mode Exit fullscreen mode

API Endpoints

Endpoint Use Case
/klines OHLCV + RSI, ADX
/chartpatterns Auto patterns
/elliottwave Wave analysis
/stocks/klines Stock data
/stocks/analysis Fundamentals

Notes

  1. Free tier = 30 req/min
  2. Backtest before live trading
  3. Use stop losses
  4. Paper trade first

Get your API key at marketmasters.ai

Happy trading!

Top comments (0)