IBKRTools

A modern, user-friendly Python wrapper for Interactive Brokers TWS API, making it easier to download and manage market data.

Features

• Simple Interface: Intuitive Pythonic interface for interacting with IBKR TWS API
• Real-time Data: Stream real-time market data for stocks, forex, and futures
• Historical Data: Fetch historical market data with flexible timeframes and bar sizes
• Type Hints: Full Python type hints for better IDE support and code clarity
• Thread-Safe: Built with thread safety in mind for concurrent operations
• Comprehensive: Supports multiple asset classes and data types

Installation

pip install ibkrtools

Prerequisites

• Python 3.8+
• Interactive Brokers TWS or IB Gateway installed and running
• Active IBKR account with market data subscriptions

Quick Start

Real-time Data

from ibkrtools import RealTimeData

# Initialize with your symbols
rt = RealTimeData(
    stocks=["AAPL", "MSFT"],
    forex=["EUR/USD"],
    futures=["ES"]
)

# Start streaming data
rt.run()

Historical Data

from ibkrtools import HistoricalData

# Fetch historical data
df = HistoricalData(
    stock_symbols=["AAPL"],
    forex_pairs=["EUR/USD"],
    future_symbols=["ES"],
    what_to_show="TRADES",
    duration="1 D",
    bar_size="1 hour",
    save=True,
    path="historical_data"
)

Documentation

RealTimeData

RealTimeData(
    stocks: List[str] = [],
    forex: List[str] = [],
    futures: List[str] = []
)

Methods

• run(): Start the real-time data streaming
• stop(): Stop the data streaming
• get_latest(symbol: str): Get the latest data for a symbol

HistoricalData

HistoricalData(
    stock_symbols: List[str] = [],
    forex_pairs: List[str] = [],
    future_symbols: List[str] = [],
    what_to_show: str = "TRADES",
    duration: str = "1 D",
    bar_size: str = "1 hour",
    path: str = "Historical_Data",
    save: bool = True,
    verbose: bool = False
) -> pd.DataFrame

Parameters

• what_to_show: Type of market data (e.g., "TRADES", "BID", "ASK", "MIDPOINT")
• duration: Amount of historical data to fetch (e.g., "1 D", "1 M", "1 Y")
• bar_size: Bar size (e.g., "1 min", "5 mins", "1 hour", "1 day")
• path: Directory to save the data
• save: Whether to save the data to disk
• verbose: Enable verbose output

Examples

Real-time Data with Callbacks

def on_data(symbol, data):
    print(f"{symbol}: {data}")

rt = RealTimeData(stocks=["AAPL"])
rt.on_data = on_data
rt.run()

Fetching Historical Data for Multiple Assets

df = HistoricalData(
    stock_symbols=["AAPL", "MSFT"],
    forex_pairs=["EUR/USD", "GBP/USD"],
    duration="1 W",
    bar_size="1 hour"
)
print(df.head())

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

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

Disclaimer

This software is for educational purposes only. Use it at your own risk. The author is not responsible for any financial losses incurred while using this software. Always test with paper trading before using real money.