Metadata-Version: 2.1
Name: BentoML
Version: 0.2.2
Summary: An open framework for building, shipping and running machine learning services
Home-page: https://github.com/bentoml/BentoML
Author: atalaya.io
Author-email: contact@atalaya.io
License: UNKNOWN
Project-URL: Bug Reports, https://github.com/bentoml/BentoML/issues
Project-URL: Source Code, https://github.com/bentoml/BentoML
Project-URL: Gitter Chat Room, https://gitter.im/bentoml/BentoML
Description: [![pypi status](https://img.shields.io/pypi/v/bentoml.svg)](https://pypi.org/project/BentoML)
        [![python versions](https://img.shields.io/pypi/pyversions/bentoml.svg)](https://travis-ci.org/bentoml/BentoML)
        [![Downloads](https://pepy.tech/badge/bentoml)](https://pepy.tech/project/bentoml)
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        [![Documentation Status](https://readthedocs.org/projects/bentoml/badge/?version=latest)](https://bentoml.readthedocs.io/en/latest/?badge=latest)
        [![join BentoML Slack](https://badgen.net/badge/Join/BentoML%20Slack/cyan?icon=slack)](http://bit.ly/2N5IpbB)
        
        > From a model in jupyter notebook to production API service in 5 minutes
        
        # BentoML
        
        [Installation](https://github.com/bentoml/BentoML#installation) | [Getting Started](https://github.com/bentoml/BentoML#getting-started) | [Documentation](http://bentoml.readthedocs.io) | [Examples](https://github.com/bentoml/BentoML#examples) | [Contributing](https://github.com/bentoml/BentoML#contributing) | [License](https://github.com/bentoml/BentoML#license)
        
        
        BentoML is a python framework for building, shipping and running machine learning
        services. It provides high-level APIs for defining an ML service and packaging
        its artifacts, source code, dependencies, and configurations into a
        production-system-friendly format that is ready for deployment.
        
        Use BentoML if you need to:
        
        * Turn your ML model into REST API server, Serverless endpoint, PyPI package, or CLI tool
        
        * Manage the workflow of creating and deploying a ML service
        
        ---
        
        
        ## Installation
        
        ![pypi status](https://img.shields.io/pypi/v/bentoml.svg)
        
        ```python
        pip install bentoml
        ```
        
        
        ## Getting Started
        
        Defining a machine learning service with BentoML is as simple as a few lines of code:
        
        ```python
        @artifacts([PickleArtifact('model')])
        @env(conda_pip_dependencies=["scikit-learn"])
        class IrisClassifier(BentoService):
        
            @api(DataframeHandler)
            def predict(self, df):
                return self.artifacts.model.predict(df)
        ```
        
        
        [![Google Colab Badge](https://colab.research.google.com/assets/colab-badge.svg)](http://bit.ly/2ID50XP) - Try out
        this 5-mins getting started guide, using BentoML to productionize a scikit-learn model and deploy it to AWS Lambda.
        
        
        ## Feature Highlights
        
        * __Multiple Distribution Format__ - Easily package your Machine Learning models
          and preprocessing code into a format that works best with your inference scenario:
          * Docker Image - deploy as containers running REST API Server
          * PyPI Package - integrate into your python applications seamlessly
          * CLI tool - put your model into Airflow DAG or CI/CD pipeline
          * Spark UDF - run batch serving on a large dataset with Spark
          * Serverless Function - host your model on serverless platforms such as AWS Lambda
        
        * __Multiple Framework Support__ - BentoML supports a wide range of ML frameworks
          out-of-the-box including [Tensorflow](https://github.com/tensorflow/tensorflow/),
          [PyTorch](https://github.com/pytorch/pytorch),
          [Scikit-Learn](https://github.com/scikit-learn/scikit-learn),
          [xgboost](https://github.com/dmlc/xgboost),
          [H2O](https://github.com/h2oai/h2o-3),
          [FastAI](https://github.com/fastai/fastai) and can be easily extended to work
          with new or custom frameworks.
        
        * __Deploy Anywhere__ - BentoML bundled ML service can be easily deployed with
          platforms such as [Docker](https://www.docker.com/),
          [Kubernetes](https://kubernetes.io/),
          [Serverless](https://github.com/serverless/serverless),
          [Airflow](https://airflow.apache.org) and [Clipper](http://clipper.ai),
          on cloud platforms including AWS, Google Cloud, and Azure.
        
        * __Custom Runtime Backend__ - Easily integrate your python pre-processing code with
          high-performance deep learning runtime backend, such as
          [tensorflow-serving](https://github.com/tensorflow/serving).
        
        
        ## Documentation
        
        Full documentation and API references can be found at [bentoml.readthedocs.io](http://bentoml.readthedocs.io)
        
        
        ## Examples
        
        All examples can be found under the
        [BentoML/examples](https://github.com/bentoml/BentoML/tree/master/examples)
        directory. More tutorials and examples coming soon!
        
        - [![Google Colab Badge](https://colab.research.google.com/assets/colab-badge.svg)](http://bit.ly/2ID50XP) - [Quick Start Guide](https://github.com/bentoml/BentoML/blob/master/examples/quick-start/bentoml-quick-start-guide.ipynb)
        - [![Google Colab Badge](https://colab.research.google.com/assets/colab-badge.svg)](http://bit.ly/2KegK6n) - [Scikit-learn Sentiment Analysis](https://github.com/bentoml/BentoML/blob/master/examples/sklearn-sentiment-clf/sklearn-sentiment-clf.ipynb)
        - [![Google Colab Badge](https://colab.research.google.com/assets/colab-badge.svg)](http://bit.ly/2KdwNRN) - [H2O Classification](https://github.com/bentoml/BentoML/blob/master/examples/h2o-classification/h2o-classification.ipynb)
        - [![Google Colab Badge](https://colab.research.google.com/assets/colab-badge.svg)](http://bit.ly/2IbtfNO) - [Keras Text Classification](https://github.com/bentoml/BentoML/blob/master/examples/tf-keras-text-classification/tf-keras-text-classification.ipynb)
        - [![Google Colab Badge](https://colab.research.google.com/assets/colab-badge.svg)](http://bit.ly/2wPh3M3) - [XGBoost Titanic Survival Prediction](https://github.com/bentoml/BentoML/blob/master/examples/xgboost-predict-titanic-survival/XGBoost-titanic-survival-prediction.ipynb)
        - [![Google Colab Badge](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/bentoml/gallery/blob/master/fast-ai/pet-classification/notebook.ipynb) - [FastAI Pet Classification](https://github.com/bentoml/gallery/blob/master/fast-ai/pet-classification/notebook.ipynb)
        - [(WIP) PyTorch Fashion MNIST classification](https://github.com/bentoml/BentoML/blob/master/examples/pytorch-fashion-mnist/pytorch-fashion-mnist.ipynb)
        - [(WIP) Tensorflow Keras Fashion MNIST classification](https://github.com/bentoml/BentoML/blob/master/examples/tf-keras-fashion-mnist/tf-keras-fashion-mnist-classification.ipynb)
        
        
        Deployment guides:
        - [Serverless deployment with AWS Lambda](https://github.com/bentoml/BentoML/blob/master/examples/deploy-with-serverless)
        - [API server deployment with AWS SageMaker](https://github.com/bentoml/BentoML/blob/master/examples/deploy-with-sagemaker)
        - [(WIP) API server deployment on Kubernetes](https://github.com/bentoml/BentoML/tree/master/examples/deploy-with-kubernetes)
        - [(WIP) API server deployment with Clipper](https://github.com/bentoml/BentoML/pull/151)
        
        
        We collect example notebook page views to help us improve this project.
        To opt-out of tracking, delete the `[Impression]` line in the first markdown cell of any example notebook: ~~!\[Impression\]\(http...~~
        
        
        ## Contributing
        
        Have questions or feedback? Post a [new github issue](https://github.com/bentoml/BentoML/issues/new/choose)
        or join our Slack chat room: [![join BentoML Slack](https://badgen.net/badge/Join/BentoML%20Slack/cyan?icon=slack)](http://bit.ly/2N5IpbB)
        
        Want to help build BentoML? Check out our
        [contributing guide](https://github.com/bentoml/BentoML/blob/master/CONTRIBUTING.md) and the
        [development guide](https://github.com/bentoml/BentoML/blob/master/DEVELOPMENT.md).
        
        To make sure you have a pleasant experience, please read the [code of conduct](https://github.com/bentoml/BentoML/blob/master/CODE_OF_CONDUCT.md).
        It outlines core values and beliefs and will make working together a happier experience.
        
        Happy hacking!
        
        ## Releases
        
        BentoML is under active development and is evolving rapidly. **Currently it is a
        Beta release, we may change APIs in future releases**.
        
        Read more about the latest features and changes in BentoML from the [releases page](https://github.com/bentoml/BentoML/releases).
        and follow the [BentoML Community Calendar](http://bit.ly/2XvUiM2).
        
        
        ## License
        
        [Apache License 2.0](https://github.com/bentoml/BentoML/blob/master/LICENSE)
        
        
        [![FOSSA Status](https://app.fossa.io/api/projects/git%2Bgithub.com%2Fbentoml%2FBentoML.svg?type=large)](https://app.fossa.io/projects/git%2Bgithub.com%2Fbentoml%2FBentoML?ref=badge_large)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Requires-Python: >=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*
Description-Content-Type: text/markdown
Provides-Extra: doc_builder
Provides-Extra: h2o
Provides-Extra: all
Provides-Extra: dev
Provides-Extra: api_server
Provides-Extra: xgboost
Provides-Extra: fastai
Provides-Extra: imageio
Provides-Extra: tensorflow
Provides-Extra: pytorch
Provides-Extra: test
