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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():
    return 1

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

def f():
    return 1

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

View the codebase on GitHub.

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

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

Pandas on Ray