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ec2534422bca09410dc0b3cb294564cdb214065f
* Perform ray.register_class under the hood. * Fix bug. * Release worker lock when waiting for imports to arrive in get. * Remove calls to register_class from examples and tests. * Clear serialization state between tests. * Fix bug and add test for multiple custom classes with same name. * Fix failure test. * Fix linting and cleanups to python code. * Fixes to documentation. * Implement recursion depth for recursively registering classes. * Fix linting. * Push warning to user if waiting for class for too long. * Fix typos. * Don't export FunctionToRun if pickling the function fails. * Don't broadcast class definition when pickling class.
Revert "Suppress warning in start_ray.sh about leaving child processes running when parent exits. (#429)" (#437)
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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