ExpertOptionsToolsV2 ExpertOptionsToolsV2 is a Python library designed to interact with the Expert Option trading platform via its WebSocket API. It provides both asynchronous (ExpertOptionAsync) and synchronous (ExpertOption) clients to perform trading operations, fetch market data, and manage account activities. The library supports demo and real accounts, asset selection, trade placement (call/put), and real-time candle subscriptions. Developed by Ahmed (Telegram: @A11ksa). Features

Asynchronous and Synchronous Clients: Use ExpertOptionAsync for async operations or ExpertOption for synchronous operations. Trading Operations: Place call (buy) and put (sell) trades with customizable expiration times. Market Data: Fetch historical candles, real-time candle subscriptions, and asset payout percentages. Account Management: Retrieve account balance, open/closed deals, and user profile data. Logging: Built-in logging to file and terminal for debugging and monitoring. Validation: Flexible message validation for WebSocket responses. Asset Support: Extensive list of assets (e.g., EURUSD, BTCUSD, AAPL) with IDs and symbols.

Installation Prerequisites

Python 3.8 or higher A valid Expert Option API token (obtain from the Expert Option platform)

Install via pip

Clone the repository or download the project files: git clone https://github.com/A11ksa/Expert-Option-API.git cd Expert-Option-API

Create and activate a virtual environment (recommended): python -m venv venv source venv/bin/activate # Linux/Mac venv\Scripts\activate # Windows

Install the library and its dependencies: pip install .

Dependencies

websockets>=11.0.3 pandas>=1.5.0 rich>=13.0.0 (for colored console output in examples)

Usage Example: Placing a Trade The following example demonstrates how to connect to the Expert Option API, fetch available assets, and place a buy (call) trade using the asynchronous client. import asyncio from ExpertOptionsToolsV2.expertoption import ExpertOptionAsync from ExpertOptionsToolsV2.tracing import LogBuilder

Configure logging

logger = LogBuilder().log_file("trade.log", "INFO").build()

async def main(): # Initialize the API client (replace with your token) token = "Your_ExpertOption_Token" api = ExpertOptionAsync(token=token, demo=True)

try:
    # Connect to the API
    await api.connect()
    print("Connected successfully!")

    # Fetch and print available assets
    await api.print_available_assets()

    # Select an asset with the highest payout
    asset = await api.select_highest_payout_asset()
    if not asset:
        print("No tradable assets available.")
        return

    asset_id = asset["id"]
    symbol = asset["symbol"]
    print(f"Selected asset: {symbol} (ID: {asset_id})")

    # Place a buy trade
    amount = 4.0
    expiration_time = 60  # 60 seconds
    deal_id, result = await api.buy(
        asset_id=asset_id,
        amount=amount,
        expiration_time=expiration_time,
        check_win=True
    )
    print(f"Trade ID: {deal_id}, Result: {result}")

except Exception as e:
    logger.error(f"Error: {e}")
    print(f"Error: {e}")
finally:
    await api.disconnect()

if name == "main": asyncio.run(main())

Example: Fetching Candles Retrieve historical candle data for an asset and display it as a pandas DataFrame. import asyncio from ExpertOptionsToolsV2.expertoption import ExpertOptionAsync

async def main(): token = "Your_ExpertOption_Token" api = ExpertOptionAsync(token=token, demo=True)

try:
    await api.connect()
    candles = await api.get_candles(
        asset_id=142,  # EURUSD
        period=5,      # 5-second timeframe
        offset=0,      # Recent data
        duration=1800  # 30 minutes of data
    )
    print("Candles DataFrame:")
    print(candles)
finally:
    await api.disconnect()

if name == "main": asyncio.run(main())

Key Classes and Modules

ExpertOptionAsync: Asynchronous client for interacting with the Expert Option API. Methods: buy, sell, get_candles, fetch_profile, subscribe_symbol, etc.

ExpertOption: Synchronous wrapper around ExpertOptionAsync for simpler usage. constants.py: Contains asset IDs, symbols, and server configurations. tracing.py: Provides logging utilities (Logger, LogBuilder). validator.py: Offers tools for validating WebSocket messages.

Configuration

API Token: Obtain from the Expert Option platform and pass to the client constructor. Demo Mode: Set demo=True for demo accounts or demo=False for real accounts. Server URL: Defaults to wss://fr24g1eu.expertoption.com/ (Europe). Other regions available in constants.py.

Contributing Contributions are welcome! Please follow these steps:

Fork the repository. Create a new branch (git checkout -b feature/your-feature). Commit your changes (git commit -m "Add your feature"). Push to the branch (git push origin feature/your-feature). Open a Pull Request.

Report issues or suggest features on the GitHub Issues page. Contact For support or inquiries, reach out to the developer:

Telegram: @A11ksa Email: ar123ksa@gmail.com GitHub: A11ksa

License This project is licensed under the MIT License. See the LICENSE file for details.