Folksy experiment management for Machine Learning.
# TBD
Contents
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).