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README.rst

Ray

https://travis-ci.com/ray-project/ray.svg?branch=master https://readthedocs.org/projects/ray/badge/?version=latest

Ray is a flexible, high-performance distributed execution framework.

Ray is easy to install: pip install ray

Example Use

Basic Python Distributed with Ray
# Execute f serially.


def f():
    time.sleep(1)
    return 1



results = [f() for i in range(4)]
# Execute f in parallel.

@ray.remote
def f():
    time.sleep(1)
    return 1


ray.init()
results = ray.get([f.remote() for i in range(4)])

Ray comes with libraries that accelerate deep learning and reinforcement learning development:

  • Ray Tune: Hyperparameter Optimization Framework
  • Ray RLlib: Scalable Reinforcement Learning

Installation

Ray can be installed on Linux and Mac with pip install ray.

To build Ray from source or to install the nightly versions, see the installation documentation.

More Information

Getting Involved