Ray

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 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.