Project Title

ray — AI Compute Engine for Scaling Python and ML Applications

Overview

Ray is a unified framework for scaling AI and Python applications, consisting of a core distributed runtime and a set of AI libraries for simplifying ML compute. It enables seamless scaling from a laptop to a cluster, making it a general-purpose solution for any Python application.

Key Features

Scalable Datasets for ML (Data)
Distributed Training (Train)
Scalable Hyperparameter Tuning (Tune)
Scalable Reinforcement Learning (RLlib)
Scalable and Programmable Serving (Serve)
Stateless functions (Tasks), Stateful worker processes (Actors), Immutable values (Objects)

Use Cases

Data Scientists: Scaling ML workloads from single-node to distributed systems
ML Engineers: Developing and deploying distributed training and hyperparameter tuning pipelines
Researchers: Running large-scale reinforcement learning experiments
Enterprises: Deploying scalable machine learning models in production

Advantages

Unified framework for scaling Python and AI applications
General-purpose, can run any kind of Python workload
Seamless scaling from laptop to cluster
Growing ecosystem of community integrations

Limitations / Considerations

Requires Python for application development
May have a learning curve for new users unfamiliar with distributed computing concepts

Dask: A parallel computing library for Python, similar to Ray but with a different focus on dynamic task scheduling.
Apache Spark: A widely-used distributed computing system with a focus on big data processing, offering both batch and stream processing capabilities.
TensorFlow: A popular machine learning framework that also supports distributed training, but is more focused on ML model development rather than general-purpose distributed computing.

Basic Information

GitHub: https://github.com/ray-project/ray
Stars: 38,782
License: Unknown
Last Commit: 2025-09-04

📊 Project Information

Project Name: ray
GitHub URL: https://github.com/ray-project/ray
Programming Language: Python
⭐ Stars: 38,782
🍴 Forks: 6,762
📅 Created: 2016-10-25
🔄 Last Updated: 2025-09-04

🏷️ Project Topics

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