Python sync/async framework for Interactive Brokers API
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README.rst

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Introduction

The ib_insync package is build on top of the Python API from Interactive Brokers. The objective is to make it as easy as possible to use the API to its fullest extent.

The main features are:

  • An IB component that automatically keeps in sync;
  • An easy to use linear style of programming (no more callbacks);
  • A fully asynchonous framework based on asyncio for advanced users;
  • Interactive operation with live data in Jupyter notebooks.

Installation

pip3 install -U ib_insync

Requirements:

To install packages needed for the examples and notebooks:

pip3 install -U jupyter numpy pandas

Example

This is a complete script to download historical data:

from ib_insync import *
# util.startLoop()  # uncomment this line when in a notebook

ib = IB()
ib.connect('127.0.0.1', 7497, clientId=1)

contract = Forex('EURUSD')
bars = ib.reqHistoricalData(contract, endDateTime='', durationStr='30 D',
        barSizeSetting='1 hour', whatToShow='MIDPOINT', useRTH=True)

# convert to pandas dataframe:
df = util.df(bars)
print(df[['date', 'open', 'high', 'low', 'close']])

Output:

                   date      open      high       low     close
0   2017-08-13 23:15:00  1.182850  1.183100  1.182100  1.182400
1   2017-08-14 00:00:00  1.182400  1.182450  1.181875  1.182175
2   2017-08-14 01:00:00  1.182175  1.182675  1.181900  1.182525
...
719 2017-09-22 22:00:00  1.194425  1.195425  1.194225  1.195050

Be sure to take a look at the notebooks and the recipes too.

Documentation

API docs

Discussion

The insync user group is the place to discuss IB-insync and anything related to it.

Disclaimer

The software is provided on the conditions of the simplified BSD license.

This project is not affiliated with Interactive Brokers Group, Inc.'s.

Good luck and enjoy,

author:Ewald de Wit <ewald.de.wit@gmail.com>