Skip to main content

Python sports betting toolbox.

Project description

Travis Codecov CircleCI ReadTheDocs PythonVersion Pypi Conda

sports-betting

sports-betting is a collection of tools that makes it easy to create machine learning models for sports betting and evaluate their performance. It is compatible with scikit-learn.

Documentation

Installation documentation, API documentation, and examples can be found on the documentation.

Dependencies

sports-betting is tested to work under Python 3.6+. The dependencies are the following:

  • pandas(>=1.1.0)

  • rich(>=4.28)

Installation

sports-betting is currently available on the PyPi’s repository and you can install it via pip:

pip install -U sports-betting

The package is released also in Anaconda Cloud platform:

conda install -c algowit sports-betting

If you prefer, you can clone it and run the setup.py file. Use the following commands to get a copy from GitHub and install all dependencies:

git clone https://github.com/AlgoWit/sports-betting.git
cd sports-betting
pip install .

Or install using pip and GitHub:

pip install -U git+https://github.com/AlgoWit/sports-betting.git

Testing

After installation, you can use pytest to run the test suite:

make test

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sports-betting-0.1.0.tar.gz (38.9 kB view hashes)

Uploaded Source

Built Distribution

sports_betting-0.1.0-py3-none-any.whl (25.0 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page