ray-project/ray
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Star History
Momentum
+1.1K
STARS · LAST 30 DAYS
37
PER DAY
#56
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +259 | +1.1K | +3.3K |
| Per day | 37 | 37 | 37 |
| Forks gained | +40 | +162 | +405 |
ray gained 1.1K stars in the last 30 days, about 37 a day, and now has 43.9K. It is about 10 years old and has averaged roughly 4.4K stars a year. It ranks #56 among Python repositories and #237 across all languages on GitHubRepo.
Trending Record
6
DAYS ON TRENDING
#201
BEST RANK
Sep 23, 2026
FIRST APPEARANCE
Active
STATUS TODAY
ray has maintained a continuous presence across global trending indexes, peaking at #201. Below is the 30-day activity profile:
💡 Overview
ray is an open-source project written in Python: Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Engineered for speed, consistency, and developer ease, it solves common hurdles in data-science, deep-learning, deployment. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install ray⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
ray coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with ray.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
🚀 Getting Started
Install ray using your package manager: `pip install ray`
Initialize your project workspace or configuration file for ray.
Import ray into your codebase or invoke it directly from your terminal.
Execute your test suite or run `ray --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
ray-project/ray is currently ranked #237 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #232 | sharkdp/fd | Rust | ★ 44.6K | Compare ↗ |
| #233 | juanfont/headscale | Go | ★ 44.2K | Compare ↗ |
| #234 | danielmiessler/Fabric | Go | ★ 44.1K | Compare ↗ |
| #235 | apache/spark | Scala | ★ 44.1K | Compare ↗ |
| #236 | colinhacks/zod | TypeScript | ★ 44K | Compare ↗ |
| #237 | ray-project/ray This Project | Python | ★ 43.9K | |
| #238 | astaxie/build-web-application-with-golang | Go | ★ 43.9K | Compare ↗ |
| #239 | HeyPuter/puter | TypeScript | ★ 43.6K | Compare ↗ |
| #240 | reactive-resume/reactive-resume | TypeScript | ★ 43.5K | Compare ↗ |
| #241 | vercel-labs/agent-browser | Rust | ★ 43.3K | Compare ↗ |
| #242 | FuelLabs/fuels-rs | Rust | ★ 43K | Compare ↗ |
Frequently Asked Questions
What does ray do? +
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
What language is ray written in? +
The primary language is Python. Topics include: data-science, deep-learning, deployment, distributed, hyperparameter-optimization.
Is ray actively maintained? +
Yes, the last recorded push was on Sep 27, 2026 with 3,569 open issues being tracked.
How many stars does ray have? +
ray has 43,938 stars and 8,090 forks on GitHub.
How does ray rank among GitHub repositories? +
With 43,938 stars, ray-project/ray is ranked #237 globally across all repositories tracked on GitHubRepo and #56 among Python projects.
What license is ray distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
