Ray provides a simple, universal API for building distributed applications.

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for andrew-anyscale from gravatar.com andrew-anyscale Avatar for artur1993 from gravatar.com artur1993 Avatar for aslonnie from gravatar.com aslonnie Avatar for bveeramani from gravatar.com bveeramani Avatar for ekl from gravatar.com ekl Avatar for elba from gravatar.com elba Avatar for eoakes from gravatar.com eoakes Avatar for matthewdeng from gravatar.com matthewdeng Avatar for pcmoritz from gravatar.com pcmoritz Avatar for richardliaw from gravatar.com richardliaw Avatar for rkn from gravatar.com rkn Avatar for swang from gravatar.com swang

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: Apache 2.0
  • Author: Ray Team
  • Tags ray , distributed , parallel , machine-learning , hyperparameter-tuningreinforcement-learning , deep-learning , serving , python
  • Requires: Python >=3.10
  • Provides-Extra: cgraph , client , data , default , observability , serve , tune , adag , serve-grpc , serve-async-inference , cpp , rllib , train , air , all , all-cpp , llm
Classifiers
Report project as malware

Project description

https://github.com/ray-project/ray/raw/master/doc/source/images/ray_header_logo.png https://readthedocs.org/projects/ray/badge/?version=master https://img.shields.io/badge/Ray-Join%20Slack-blue https://img.shields.io/badge/Discuss-Ask%20Questions-blue https://img.shields.io/twitter/follow/raydistributed.svg?style=social&logo=twitter https://img.shields.io/badge/Get_started_for_free-3C8AE9?logo=data%3Aimage%2Fpng%3Bbase64%2CiVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8%2F9hAAAAAXNSR0IArs4c6QAAAERlWElmTU0AKgAAAAgAAYdpAAQAAAABAAAAGgAAAAAAA6ABAAMAAAABAAEAAKACAAQAAAABAAAAEKADAAQAAAABAAAAEAAAAAA0VXHyAAABKElEQVQ4Ea2TvWoCQRRGnWCVWChIIlikC9hpJdikSbGgaONbpAoY8gKBdAGfwkfwKQypLQ1sEGyMYhN1Pd%2B6A8PqwBZeOHt%2FvsvMnd3ZXBRFPQjBZ9K6OY8ZxF%2B0IYw9PW3qz8aY6lk92bZ%2BVqSI3oC9T7%2FyCVnrF1ngj93us%2B540sf5BrCDfw9b6jJ5lx%2FyjtGKBBXc3cnqx0INN4ImbI%2Bl%2BPnI8zWfFEr4chLLrWHCp9OO9j19Kbc91HX0zzzBO8EbLK2Iv4ZvNO3is3h6jb%2BCwO0iL8AaWqB7ILPTxq3kDypqvBuYuwswqo6wgYJbT8XxBPZ8KS1TepkFdC79TAHHce%2F7LbVioi3wEfTpmeKtPRGEeoldSP%2FOeoEftpP4BRbgXrYZefsAI%2BP9JU7ImyEAAAAASUVORK5CYII%3D

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI libraries for simplifying ML compute:

https://github.com/ray-project/ray/raw/master/doc/source/images/what-is-ray-padded.svg

Learn more about Ray AI Libraries:

  • Data: Scalable Datasets for ML

  • Train: Distributed Training

  • Tune: Scalable Hyperparameter Tuning

  • RLlib: Scalable Reinforcement Learning

  • Serve: Scalable and Programmable Serving

Or more about Ray Core and its key abstractions:

  • Tasks: Stateless functions executed in the cluster.

  • Actors: Stateful worker processes created in the cluster.

  • Objects: Immutable values accessible across the cluster.

Learn more about Monitoring and Debugging:

Ray runs on any machine, cluster, cloud provider, and Kubernetes, and features a growing ecosystem of community integrations.

Install Ray with: pip install ray. For nightly wheels, see the Installation page.

Why Ray?

Today’s ML workloads are increasingly compute-intensive. As convenient as they are, single-node development environments such as your laptop cannot scale to meet these demands.

Ray is a unified way to scale Python and AI applications from a laptop to a cluster.

With Ray, you can seamlessly scale the same code from a laptop to a cluster. Ray is designed to be general-purpose, meaning that it can performantly run any kind of workload. If your application is written in Python, you can scale it with Ray, no other infrastructure required.

More Information

Older documents:

Getting Involved

Platform

Purpose

Estimated Response Time

Support Level

Discourse Forum

For discussions about development and questions about usage.

< 1 day

Community

GitHub Issues

For reporting bugs and filing feature requests.

< 2 days

Ray OSS Team

Slack

For collaborating with other Ray users.

< 2 days

Community

StackOverflow

For asking questions about how to use Ray.

3-5 days

Community

Meetup Group

For learning about Ray projects and best practices.

Monthly

Ray DevRel

Twitter

For staying up-to-date on new features.

Daily

Ray DevRel

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for andrew-anyscale from gravatar.com andrew-anyscale Avatar for artur1993 from gravatar.com artur1993 Avatar for aslonnie from gravatar.com aslonnie Avatar for bveeramani from gravatar.com bveeramani Avatar for ekl from gravatar.com ekl Avatar for elba from gravatar.com elba Avatar for eoakes from gravatar.com eoakes Avatar for matthewdeng from gravatar.com matthewdeng Avatar for pcmoritz from gravatar.com pcmoritz Avatar for richardliaw from gravatar.com richardliaw Avatar for rkn from gravatar.com rkn Avatar for swang from gravatar.com swang

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: Apache 2.0
  • Author: Ray Team
  • Tags ray , distributed , parallel , machine-learning , hyperparameter-tuningreinforcement-learning , deep-learning , serving , python
  • Requires: Python >=3.10
  • Provides-Extra: cgraph , client , data , default , observability , serve , tune , adag , serve-grpc , serve-async-inference , cpp , rllib , train , air , all , all-cpp , llm
Classifiers

Release history Release notifications | RSS feed

This version

2.56.0

2.55.1

2.55.0

2.54.1

2.54.0

2.53.0

2.52.1

2.52.0

2.51.2

2.51.1

2.51.0

2.50.1

2.50.0

2.49.2

2.49.1

2.49.0

2.48.0

2.47.1

2.47.0

2.46.0

2.45.0

2.44.1

2.44.0

2.43.0

2.42.1

2.42.0

2.41.0

2.40.0

2.39.0

2.38.0

2.37.0

2.36.1

2.36.0

2.35.0

2.34.0

2.33.0

2.32.0

2.32.0rc0 pre-release

2.31.0

2.30.0

2.24.0

2.23.0

2.22.0

2.21.0

2.20.0

2.12.0

2.11.0

2.10.0

2.9.3

2.9.2

2.9.1

2.9.0

2.8.1

2.8.0

2.7.2

2.7.1

2.7.0

2.7.0rc0 pre-release

2.6.3

2.6.2

2.6.1

2.6.0

2.5.1

2.5.0

2.4.0

2.3.1

2.3.0

2.3.0rc0 pre-release

2.2.0

2.1.0

2.0.1

2.0.0

1.13.0

1.12.1

1.12.0

1.11.1

1.11.0

1.10.0

1.9.2

1.9.1

1.9.0

1.8.0

1.7.1 yanked

Reason this release was yanked:

https://github.com/ray-project/ray/issues/19813

1.7.0

1.6.0

1.5.2

1.5.1

1.5.0

1.4.1

1.4.0

1.3.0

1.2.0

1.1.0

1.0.1

1.0.0

0.8.7

0.8.6

0.8.5

0.8.4

0.8.3

0.8.2

0.8.1

0.8.0

0.7.7

0.7.6

0.7.5

0.7.4

0.7.3

0.7.2

0.7.1

0.7.0

0.6.6

0.6.5

0.6.4

0.6.3

0.6.2

0.6.1

0.6.0

0.5.3

0.5.2

0.5.0

0.4.0

0.3.1

0.3.0

0.2.2

0.2.1

0.2.0

0.1.2

0.1.1

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

ray-2.56.0-cp314-cp314-manylinux2014_x86_64.whl (74.1 MB view details)

Uploaded CPython 3.14

ray-2.56.0-cp314-cp314-manylinux2014_aarch64.whl (73.2 MB view details)

Uploaded CPython 3.14

ray-2.56.0-cp314-cp314-macosx_12_0_arm64.whl (66.3 MB view details)

Uploaded CPython 3.14macOS 12.0+ ARM64

ray-2.56.0-cp313-cp313-manylinux2014_x86_64.whl (74.1 MB view details)

Uploaded CPython 3.13

ray-2.56.0-cp313-cp313-manylinux2014_aarch64.whl (73.3 MB view details)

Uploaded CPython 3.13

ray-2.56.0-cp313-cp313-macosx_12_0_arm64.whl (66.3 MB view details)

Uploaded CPython 3.13macOS 12.0+ ARM64

ray-2.56.0-cp312-cp312-win_amd64.whl (28.4 MB view details)

Uploaded CPython 3.12Windows x86-64

ray-2.56.0-cp312-cp312-manylinux2014_x86_64.whl (74.2 MB view details)

Uploaded CPython 3.12

ray-2.56.0-cp312-cp312-manylinux2014_aarch64.whl (73.3 MB view details)

Uploaded CPython 3.12

ray-2.56.0-cp312-cp312-macosx_12_0_arm64.whl (66.3 MB view details)

Uploaded CPython 3.12macOS 12.0+ ARM64

ray-2.56.0-cp311-cp311-win_amd64.whl (28.4 MB view details)

Uploaded CPython 3.11Windows x86-64

ray-2.56.0-cp311-cp311-manylinux2014_x86_64.whl (74.1 MB view details)

Uploaded CPython 3.11

ray-2.56.0-cp311-cp311-manylinux2014_aarch64.whl (73.3 MB view details)

Uploaded CPython 3.11

ray-2.56.0-cp311-cp311-macosx_12_0_arm64.whl (66.4 MB view details)

Uploaded CPython 3.11macOS 12.0+ ARM64

ray-2.56.0-cp310-cp310-win_amd64.whl (28.4 MB view details)

Uploaded CPython 3.10Windows x86-64

ray-2.56.0-cp310-cp310-manylinux2014_x86_64.whl (74.1 MB view details)

Uploaded CPython 3.10

ray-2.56.0-cp310-cp310-manylinux2014_aarch64.whl (73.2 MB view details)

Uploaded CPython 3.10

ray-2.56.0-cp310-cp310-macosx_12_0_arm64.whl (66.4 MB view details)

Uploaded CPython 3.10macOS 12.0+ ARM64

File details

Details for the file ray-2.56.0-cp314-cp314-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for ray-2.56.0-cp314-cp314-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 73edb6fb5fd05481b1f358ac2e8a4c7f6a031d89f9b823d25a587ddb7529070f
MD5 bd120cf68cd622855485f78680686022
BLAKE2b-256 d55b33ac5616706d1bc0bd40e22baf12acccd687b505f85d107f549355379d6f

See more details on using hashes here.

File details

Details for the file ray-2.56.0-cp314-cp314-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for ray-2.56.0-cp314-cp314-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 c3a16d43d75283a3d64fa1d904a3adaf3f526f3f508f447505b8bb8dc70bad6c
MD5 af1f15e874dfd2cf480d68a7508412c2
BLAKE2b-256 303c2819cc8b40bf4034ff871c18d04a0422b7b0a51b32260c6f03a06460aaa5

See more details on using hashes here.

File details

Details for the file ray-2.56.0-cp314-cp314-macosx_12_0_arm64.whl.

File metadata

File hashes

Hashes for ray-2.56.0-cp314-cp314-macosx_12_0_arm64.whl
Algorithm Hash digest
SHA256 f38e03b77c53e3d94091aedb84b14efe7ee5b581d85b7d13925066bcd48c44a2
MD5 84d3d2113fb56a04bccbc497e5a0fc61
BLAKE2b-256 82a007a00091cf002662946ed2a16fe4b27c80be6fce7fc831e41c7e1471e2f7

See more details on using hashes here.

File details

Details for the file ray-2.56.0-cp313-cp313-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for ray-2.56.0-cp313-cp313-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 54d2725f8b65d9615c933fec5ec62e54a67b8f2e14286026fb014606253670ef
MD5 5abe37d6566d97470a1be9c50a5e149b
BLAKE2b-256 59ba285d409253b332af91884daa4b0a3be3ce799682aa2c1e0f8dbbafaf1da4

See more details on using hashes here.

File details

Details for the file ray-2.56.0-cp313-cp313-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for ray-2.56.0-cp313-cp313-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 a0e9cfe92c88ab74abca23923c15a592f49bc7617ffdda4190daca7785a7c4f6
MD5 e448bc2558458fab3650d28ff341fdae
BLAKE2b-256 59593c4d533a92e99b12b9d2e8690e41d7ace269d77deecb0aef753df7924b9e

See more details on using hashes here.

File details

Details for the file ray-2.56.0-cp313-cp313-macosx_12_0_arm64.whl.

File metadata

File hashes

Hashes for ray-2.56.0-cp313-cp313-macosx_12_0_arm64.whl
Algorithm Hash digest
SHA256 992047f50473b5bfea74c8f528f999968e0b4bc735af23ad476a0f4e04741aea
MD5 9e69058df317a2296600acff510d399a
BLAKE2b-256 658629c9444c9f11f0bf3d4da75d3dc7a27c0fb86f8604beea6513968dc2df26

See more details on using hashes here.

File details

Details for the file ray-2.56.0-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: ray-2.56.0-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 28.4 MB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.4

File hashes

Hashes for ray-2.56.0-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 a8fc809dab6fc07cf05d45ea93a776c852c990512eb1fac0e3d15819fe6df10a
MD5 146b7af824f65c7b601c2903f80d891b
BLAKE2b-256 b99ecac7454325c79eb32f36f233285d9179858c7073bc27ac91afb74854ff12

See more details on using hashes here.

File details

Details for the file ray-2.56.0-cp312-cp312-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for ray-2.56.0-cp312-cp312-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 78ef34a71383c1fcf335e531e0e590867857fce9069f06ed351be6ce7a58fc50
MD5 801451a5b03c3f6e2ca3c8cebd8aeff0
BLAKE2b-256 39d18d442116f41e6bebec418d89f1556c67c77d593b55cf59e716503e7a4a17

See more details on using hashes here.

File details

Details for the file ray-2.56.0-cp312-cp312-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for ray-2.56.0-cp312-cp312-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 e1fd03c6ecc5fe4c31466569e41ce0a4faf26fb930798c9d1f1eb1f405a687c8
MD5 3eaa94c1e0b6f65e03ed72256f4423e3
BLAKE2b-256 6eb2d610ffe2878dae8ab903cfdded883a054c102b0104670bca7b34b662db51

See more details on using hashes here.

File details

Details for the file ray-2.56.0-cp312-cp312-macosx_12_0_arm64.whl.

File metadata

File hashes

Hashes for ray-2.56.0-cp312-cp312-macosx_12_0_arm64.whl
Algorithm Hash digest
SHA256 684a427c50745989e92a332343f0812c93b8506f71c768b95b1eefc113492699
MD5 adaa3201a541ac5350b813350103f804
BLAKE2b-256 05d283777f52c10e04654c162bfa093f4e34cf6decf7a0bb4311e2432bfa8ecb

See more details on using hashes here.

File details

Details for the file ray-2.56.0-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: ray-2.56.0-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 28.4 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.4

File hashes

Hashes for ray-2.56.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 8e57781685bb4332edf8a7cfb1135ff53d50002b6a0504006e68365bcd26aa7c
MD5 46cd8110dea3ecca7f477388aeb5bcf1
BLAKE2b-256 5a1b0b4c96879ded375d0b35441c6b3633ccbea7c7c5448335589811fe5f275c

See more details on using hashes here.

File details

Details for the file ray-2.56.0-cp311-cp311-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for ray-2.56.0-cp311-cp311-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c5bf1a4384c0e2aa4420c95474b734d064cac354b0f00760be02d886afe96ca4
MD5 91a5bf584181f32c8e411e17897f2720
BLAKE2b-256 18d384df370c773a0b853abdba498a6258106cb928d452ff56eec7f86c2f80b4

See more details on using hashes here.

File details

Details for the file ray-2.56.0-cp311-cp311-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for ray-2.56.0-cp311-cp311-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 aea655831d25084cb343002a8e67a77b6aa552ddb776a65461d49f62884f096a
MD5 cbb36717938aac07be09f9d4cc3b193b
BLAKE2b-256 d66909c8320519aa4d075bd6ecb1694c28d26b5b07a5b46050703d9ac2c5a9b6

See more details on using hashes here.

File details

Details for the file ray-2.56.0-cp311-cp311-macosx_12_0_arm64.whl.

File metadata

File hashes

Hashes for ray-2.56.0-cp311-cp311-macosx_12_0_arm64.whl
Algorithm Hash digest
SHA256 a9ad4e26941eb2f8dbd494ad07f9f2227143164c6114132b26b23ad4f20b1c6f
MD5 13688ba2abd4e627bc81916060b5c7a4
BLAKE2b-256 7bf22cbbbef7a67adc6555b141c7a67557bd7ce21cfb85b85772627c6a582e97

See more details on using hashes here.

File details

Details for the file ray-2.56.0-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: ray-2.56.0-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 28.4 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.4

File hashes

Hashes for ray-2.56.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 b837c5a905647c9b6a4f55061c2782437da24009e4eb4781db1c9c4badc84d0b
MD5 36b7d03143c652cc52cb1c5f150f4c71
BLAKE2b-256 9d0570492aed281a235421ffd116b2eb74f127f387580bb63a7f8ce5c901169e

See more details on using hashes here.

File details

Details for the file ray-2.56.0-cp310-cp310-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for ray-2.56.0-cp310-cp310-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 58be75df2d4a6a85b5e514e4d3261760fe21cc09ba974ce22cc08a8e4e07c449
MD5 b93d3e18989f1e303a2da7cf897e4590
BLAKE2b-256 b0a32d0fbe2d8808ae8837885051f149cefdca3e869eaef4c65618173fa63db5

See more details on using hashes here.

File details

Details for the file ray-2.56.0-cp310-cp310-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for ray-2.56.0-cp310-cp310-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 15ea7ac36bfa3961c1eb2b2a099ed7dcf892f001f462920b6ec379ccafb038b0
MD5 9d8005412abe32de4b5ea2133056e3f1
BLAKE2b-256 f115037f9eac9d3d43079611ca6af58c34b2a4271b9a94d57679356981b7b8e9

See more details on using hashes here.

File details

Details for the file ray-2.56.0-cp310-cp310-macosx_12_0_arm64.whl.

File metadata

File hashes

Hashes for ray-2.56.0-cp310-cp310-macosx_12_0_arm64.whl
Algorithm Hash digest
SHA256 f34b2345a47ad144292c1b34eeba2ed8d556078f7bd118d1adf2090d5199c843
MD5 87862b8c57172cf28ca53d2ecd685273
BLAKE2b-256 9ec0d6ffbe8ae2e2e10ea07aa08ea2dd35597239f0b3faaa29b5d7bbc405ab32

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page