Install and contribution


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.


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 file. Use the following commands to get a copy from GitHub and install all dependencies:

git clone
cd seglearn
pip install .

Or install using pip and GitHub:

pip install -U git+


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



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.