Contents

robin-stocks 3.4.0

0

A Python wrapper around the Robinhood API

A Python wrapper around the Robinhood API

Stars: 2009, Watchers: 2009, Forks: 537, Open Issues: 315

The jmfernandes/robin_stocks repo was created 7 years ago and the last code push was 1 weeks ago.
The project is very popular with an impressive 2009 github stars!

How to Install robin_stocks

You can install robin_stocks using pip

pip install robin_stocks

or add it to a project with poetry

poetry add robin_stocks

Package Details

Author
Josh Fernandes
License
MIT
Homepage
https://github.com/jmfernandes/robin_stocks
PyPi:
https://pypi.org/project/robin-stocks/
GitHub Repo:
https://github.com/jmfernandes/robin_stocks
No  robin_stocks  pypi packages just yet.

Errors

A list of common robin_stocks errors.

Code Examples

Here are some robin_stocks code examples and snippets.

GitHub Issues

The robin_stocks package has 315 open issues on GitHub

  • Robinhood Banking & IRA
  • Add comprehensive futures trading support to robin_stocks
  • Robinhood Programmatic Login Unavailable
  • Add recurring investments API support
  • Authentication , no notifications in Robinhood App
  • robinhood futures support ?

See more issues on GitHub

Related Packages & Articles

pandas-ta 0.4.71b0

A Comprehensive Python 3 Technical Analysis Library with Pandas Dataframe Extension for Quantitative Researchers, Traders, and Investors.

finta 1.3

Common financial technical indicators implemented in Pandas.

tensortrade 1.0.4

TensorTrade: A reinforcement learning library for training, evaluating, and deploying robust trading agents.

pyfolio 0.9.2

pyfolio is a Python library for performance and risk analysis of financial portfolios

PyAlgoTrade 0.20

PyAlgoTrade is an event driven algorithmic trading Python library.

ta 0.11.0

ta is a Python module that provides a technical analysis library, designed to enable feature engineering from financial time series datasets. It is built on the pandas and numpy libraries and offers a wide range of indicators such as volume, volatility, trend, and momentum indicators. ta is designed for Python developers working in the financial sector, making it a valuable asset in the field of Financial Software and Fintech Solutions, particularly for those developing trading algorithms or investment strategies.