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03f2325780d3c67e1573aafee2b2f1d70c9a4e23
* Rough pass at installing pyarrow along with Ray. * Remove hardcoded path and try to find correct path automatically. * Add print. * Fix linting. * Copy pyarrow files to a location that we manually add to python path in order to avoid interfering with pre-existing pyarrow installations. * Move call to build.sh back into build_ext in setup.py. * Ignore some linting errors. * Fix problem in which pyarrow files to copy were listed before they were built. * Fix tests by importing ray before pyarrow.
Implement object table notification subscriptions and switch to using Redis modules for object table. (#134)
Ray
===
.. image:: https://travis-ci.org/ray-project/ray.svg?branch=master
:target: https://travis-ci.org/ray-project/ray
.. image:: https://readthedocs.org/projects/ray/badge/?version=latest
:target: http://ray.readthedocs.io/en/latest/?badge=latest
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Ray is a flexible, high-performance distributed execution framework.
View the `documentation`_.
.. _`documentation`: http://ray.readthedocs.io/en/latest/index.html
Description
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
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