Metadata-Version: 2.1
Name: ebonite
Version: 0.3.2
Summary: Machine Learning Lifecycle Framework
Home-page: https://github.com/zyfra/ebonite
Author: Mikhail Sveshnikov
Author-email: mike0sv@gmail.com
License: Apache-2.0
Project-URL: Changelog, https://github.com/zyfra/ebonite/blob/master/CHANGELOG.rst
Project-URL: Issue Tracker, https://github.com/zyfra/ebonite/issues
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: Unix
Classifier: Operating System :: POSIX
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Utilities
Requires-Python: >=3.6
Requires-Dist: docker (==4.1.0)
Requires-Dist: pyyaml (==5.1.2)
Requires-Dist: requests (==2.22.0)
Requires-Dist: dill (==0.3.1.1)
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Requires-Dist: pyjackson (==0.0.21)
Requires-Dist: everett (==1.0.2)
Requires-Dist: Jinja2 (==2.10.1)
Provides-Extra: testing
Requires-Dist: pandas (==0.25.1) ; extra == 'testing'
Requires-Dist: numpy (==1.17.3) ; extra == 'testing'
Requires-Dist: scikit-learn (==0.21.3) ; extra == 'testing'
Requires-Dist: sqlalchemy (==1.3.10) ; extra == 'testing'
Requires-Dist: tensorflow (==1.14.0) ; extra == 'testing'
Requires-Dist: catboost (==0.19.1) ; extra == 'testing'
Requires-Dist: flasgger (==0.9.3) ; extra == 'testing'
Requires-Dist: boto3 (==1.10.28) ; extra == 'testing'
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.. image:: ebonite.jpg



Ebonite is a machine learning lifecycle framework.
It allows you to persist your models and reproduce them (as services or in general).

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

::

    pip install ebonite

Quickstart
=============

First, create a Ebonite client.

.. code-block:: python

  from ebonite import Ebonite
  ebnt = Ebonite.local()

Second, create a task and push your model object with some sample data.

.. code-block:: python

   task = ebnt.get_or_create_task('my_project', 'my_task')
   model = task.create_and_push_model(clf, test_x, 'my_sklearn_clf')

You are awesome! Now you can load you model from this repo and do other wonderful stuff with it, for
example create a docker image.

Check out examples and documentation to learn more.


Documentation
=============
... is available `here <https://ebonite.readthedocs.io/en/latest/>`_

Supported libraries and repositories
====================================

* Machine Learning

  * scikit-learn

  * TensorFlow < 2

  * XGBoost

  * LightGBM

  * PyTorch

  * CatBoost

* Data

  * NumPy

  * pandas

  * images

* Repositories

  * SQLAlchemy

  * Amazon S3

* Serving

  * Flask



Contributing
============

Read `this <https://github.com/zyfra/ebonite/blob/master/CONTRIBUTING.rst>`_
Changelog
=========

Current release candidate
-------------------------

0.3.2 (2019-12-04)
------------------

* Multi-model interface bug fixes

0.3.1 (2019-12-04)
------------------

* Minor bug fixes

0.3.0 (2019-11-27)
------------------

* Added support for LightGBM models
* Added support for XGBoost models
* Added support for PyTorch models
* Added support for CatBoost models
* Added uwsgi server for flask containers

0.2.1 (2019-11-19)
------------------

* Minor bug fixes

0.2.0 (2019-11-14)
------------------

* First release on PyPI.


