Install and contribution

Dependencies

Seglearn is tested to work under Python 3.5. The dependency requirements are based on the last scikit-learn release:

  • scipy(>=0.17.0)

  • numpy(>=1.11.0)

  • scikit-learn(>=0.21.3)

Additionally, to run the examples, you need:

  • matplotlib(>=2.0.0)

  • keras (>=2.1.4) for the neural network examples

  • pandas

In order to run the test cases, you need:

  • pytest

The neural network examples were tested on keras using the tensorflow-gpu backend, which is recommended.

Installation

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

pip install -U seglearn

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/dmbee/seglearn.git
cd seglearn
pip install .

Or install using pip and GitHub:

pip install -U git+https://github.com/dmbee/seglearn.git

Testing

After installation, you can use pytest to run the test suite from seglearn’s root directory:

pytest

Contribute

You can contribute to this code through Pull Request on GitHub. Please, make sure that your code is coming with unit tests to ensure full coverage and continuous integration in the API.