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pandas-datareader, with Interactive Brokers Gateway

I'm using this fork to add Interactive Brokers Gateway to Pandas Datareader.

This package relies on a IB Gateway being active at its default location: https://localhost:5000. You can get the Gateway here. Getting started guide is here for running the service.

Usage

import requests
import pandas_datareader as pdr

session = requests.Session()
session.verify = False #required due to self-signed SSL cert

pdr.ib.time_series.IBTimeSeriesReader(symbols='396336017', period = '1w', bar = '1h', session = session).read()

Future Work

If anyone at Interactive Brokers is watching, please surface options data and an isTruncated flag!

Pandas Datareader readme continues below.

pandas-datareader

Up to date remote data access for pandas, works for multiple versions of pandas.

https://travis-ci.org/pydata/pandas-datareader.svg?branch=master https://coveralls.io/repos/pydata/pandas-datareader/badge.svg?branch=master https://readthedocs.org/projects/pandas-datareader/badge/?version=latest

Installation

Install using pip

pip install pandas-datareader

Usage

import pandas_datareader as pdr
pdr.get_data_fred('GS10')

Documentation

Stable documentation is available on github.io. A second copy of the stable documentation is hosted on read the docs for more details.

Development documentation is available for the latest changes in master.

Requirements

Using pandas datareader requires the following packages:

  • pandas>=0.23
  • lxml
  • requests>=2.19.0

Building the documentation additionally requires:

  • matplotlib
  • ipython
  • requests_cache
  • sphinx
  • pydata_sphinx_theme

Development and testing additionally requires:

  • black
  • coverage
  • codecov
  • coveralls
  • flake8
  • pytest
  • pytest-cov
  • wrapt

Install latest development version

pip install git+https://github.com/pydata/pandas-datareader.git

or

git clone https://github.com/pydata/pandas-datareader.git
cd pandas-datareader
python setup.py install

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Extract data from a wide range of Internet sources into a pandas DataFrame.

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