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Folksy experiment management for Machine Learning.

Project description

PyPI-Status PyPI-Versions Build-Status Codecov LICENCE

Folksy experiment management for Machine Learning.

# TBD

1   Installation

pip install folk

2   Basic Use

folk is divided into several sub-modules by functionality:

3   Contributing

Package author and current maintainer is Shay Palachy (shay.palachy@gmail.com); You are more than welcome to approach him for help. Contributions are very welcomed.

3.1   Installing for development

Clone:

git clone git@github.com:shaypal5/folk.git

Install in development mode:

cd folk
pip install -e .

3.2   Running the tests

To run the tests use:

pip install pytest pytest-cov coverage
cd folk
pytest

3.3   Adding documentation

The project is documented using the numpy docstring conventions, which were chosen as they are perhaps the most widely-spread conventions that are both supported by common tools such as Sphinx and result in human-readable docstrings. When documenting code you add to this project, follow these conventions.

Additionally, if you update this README.rst file, use python setup.py checkdocs (or pipenv run the same command) to validate it compiles.

4   Credits

Created by Shay Palachy (shay.palachy@gmail.com).

Project details


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Filename, size & hash SHA256 hash help File type Python version Upload date
folk-0.0.9-py2.py3-none-any.whl (11.9 kB) Copy SHA256 hash SHA256 Wheel py2.py3 May 9, 2018

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