Metadata-Version: 2.1
Name: fets
Version: 0.5.3
Summary: Feature Engineering Transformer Set
Home-page: https://gitlab.com/redsharpbyte/fets
Author: Red Boumghar
License: BSD
Keywords: data,feature-engineering,feature-extraction,machine-learning,transformer,transformation,pipeline
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: BSD License
Requires-Python: >=3
Provides-Extra: test
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: pandas
Requires-Dist: scikit-learn
Requires-Dist: joblib
Provides-Extra: test
Requires-Dist: pytest; extra == 'test'

FETS
=====

[![pipeline status](https://gitlab.com/redsharpbyte/fets/badges/master/pipeline.svg)](https://gitlab.com/redsharpbyte/fets/commits/master)
[![coverage report](https://gitlab.com/redsharpbyte/fets/badges/master/coverage.svg)](https://gitlab.com/redsharpbyte/fets/commits/master)



Set of ready-to-use transformers for your feature engineering pipelines in scikit-learn.

Inspired by the number of times I had to rewrite transformers and by the number 
of times we all did exactly the same.


How-To
======

TODO



Installation
============

```
red@spaceport# pip install fets
```

Testing
=======

```
red@spaceport# cd fets/
red@spaceport# pytest -v tests
```


