ExpertOptionAPI-pro

The latest version of ExpertOptionAPI created with alot of help of the Chipa Comunity

ExpertOptionAPI Usage Guide

This README provides a full example of how to use the ExpertOptionAPI Python library along with the AlligatorIndicator and RSIIndicator.

Features

• Connect to ExpertOption using WebSocket
• Fetch account balance and active trading assets
• Dynamically select high-profit assets
• Subscribe to live candle data
• Place and monitor trade orders
• Fetch historical candles
• Analyze market trends with indicators
• Get traders' choice sentiment

Requirements

• Python 3.7+
• asyncio
• Logging
• ExpertOptionAPI and indicators module

Installation

Make sure to install the necessary modules and have the Expert.api and Expert.indicators properly configured in your environment.

Example

import asyncio
import logging
from Expert.api import ExpertOptionAPI
from Expert.indicators import AlligatorIndicator, RSIIndicator

# Configure logging
logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')

async def main():
    token = ""  # Replace with your token
    api = ExpertOptionAPI(token=token, demo=True, server_region="wss://fr24g1us.expertoption.finance/ws/v40")
    
    try:
        await api.connect()
        
        # Balance and asset info
        balance = api.get_balance()
        print(f"Account balance: {balance}")
        print(f"Active assets: {len(api.active_assets)}")
        
        # Select the most profitable asset
        selected_asset_id = 240
        available_assets = [
            (asset_id, asset["profit"]) 
            for asset_id, asset in api.active_assets.items() 
            if asset.get("is_active") == 1 and asset.get("type") == 1 and "profit" in asset
        ]
        if available_assets:
            selected_asset_id = max(available_assets, key=lambda x: x[1])[0]
            print(f"Selected: {api.active_assets[selected_asset_id]['name']} (ID: {selected_asset_id})")

        # Subscribe to candles
        await api.get_candles(selected_asset_id, timeframes=[0, 5])
        candle_data = api.candle_cache.get(selected_asset_id)
        print(f"Candles: {candle_data}")
        
        # Place an order
        order_id = await api.place_order(selected_asset_id, amount=1.0, direction="call")
        print(f"Order ID: {order_id}")
        order = await api.check_order_status(order_id)
        print(f"Order Status: {order.status}, Profit: {order.profit}")

        # Historical data and indicators
        periods = [[1744822016, 1744822726]]
        historical = await api.get_historical_candles(selected_asset_id, periods)

        alligator = AlligatorIndicator(historical)
        print(f"Alligator: {await alligator.evaluate_market_trend(api, selected_asset_id)}")

        rsi = RSIIndicator(historical)
        print(f"RSI: {rsi.evaluate_market_condition()}")

        # Traders choice
        choice = await api.get_traders_choice(selected_asset_id)
        print(f"Traders' Choice: {choice}")

    except Exception as e:
        print(f"Error: {e}")
        api.logger.error("Main execution failed", exc_info=True)
    finally:
        await api.disconnect()

if __name__ == "__main__":
    asyncio.run(main())

Notes

• Replace the token with a valid one from your ExpertOption account.
• The AlligatorIndicator and RSIIndicator rely on proper historical candle data.

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Happy coding and profitable trading!