https://github.com/kubeflow/pipelines
Machine Learning Pipelines for Kubeflow
Science Score: 36.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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✓Committers with academic emails
8 of 466 committers (1.7%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (14.0%) to scientific vocabulary
Keywords
Keywords from Contributors
Repository
Machine Learning Pipelines for Kubeflow
Basic Info
- Host: GitHub
- Owner: kubeflow
- License: apache-2.0
- Language: Python
- Default Branch: master
- Homepage: https://www.kubeflow.org/docs/components/pipelines/
- Size: 331 MB
Statistics
- Stars: 3,922
- Watchers: 102
- Forks: 1,778
- Open Issues: 294
- Releases: 171
Topics
Metadata Files
README.md
Kubeflow Pipelines
Overview of the Kubeflow pipelines service
Kubeflow is a machine learning (ML) toolkit that is dedicated to making deployments of ML workflows on Kubernetes simple, portable, and scalable.
Kubeflow pipelines are reusable end-to-end ML workflows built using the Kubeflow Pipelines SDK.
The Kubeflow pipelines service has the following goals:
- End to end orchestration: enabling and simplifying the orchestration of end to end machine learning pipelines
- Easy experimentation: making it easy for you to try numerous ideas and techniques, and manage your various trials/experiments.
- Easy re-use: enabling you to re-use components and pipelines to quickly cobble together end to end solutions, without having to re-build each time.
Installation
Kubeflow Pipelines can be installed as part of the Kubeflow Platform. Alternatively you can deploy Kubeflow Pipelines as a standalone service.
The Docker container runtime has been deprecated on Kubernetes 1.20+. Kubeflow Pipelines has switched to use Emissary Executor by default from Kubeflow Pipelines 1.8. Emissary executor is Container runtime agnostic, meaning you are able to run Kubeflow Pipelines on Kubernetes cluster with any Container runtimes.
Dependencies Compatibility Matrix
| Dependency | Versions | | -------------- | ---------- | | Argo Workflows | v3.5, v3.6 | | MySQL | v8 |
Documentation
Get started with your first pipeline and read further information in the Kubeflow Pipelines overview.
See the various ways you can use the Kubeflow Pipelines SDK.
See the Kubeflow Pipelines API doc for API specification.
Consult the Python SDK reference docs when writing pipelines using the Python SDK.
Deep Wiki
Check out our AI Powered repo documentation on DeepWiki.
:warning: Please note, this is AI generated and may not have completely accurate information.
Contributing to Kubeflow Pipelines
Before you start contributing to Kubeflow Pipelines, read the guidelines in How to Contribute. To learn how to build and deploy Kubeflow Pipelines from source code, read the developer guide.
Kubeflow Pipelines Community
Community Meeting
The Kubeflow Pipelines Community Meeting occurs every other Wed 10-11AM (PST).
Slack
We also have a slack channel (#kubeflow-pipelines) on the Cloud Native Computing Foundation Slack workspace. You can find more details at https://www.kubeflow.org/docs/about/community/#kubeflow-slack-channels
Architecture
Details about the KFP Architecture can be found at Architecture.md
Blog posts
- From Raw Data to Model Serving: A Blueprint for the AI/ML Lifecycle with Kubeflow (By Helber Belmiro)
- Getting started with Kubeflow Pipelines (By Amy Unruh)
- How to create and deploy a Kubeflow Machine Learning Pipeline (By Lak Lakshmanan)
Acknowledgments
Kubeflow pipelines uses Argo Workflows by default under the hood to orchestrate Kubernetes resources. The Argo community has been very supportive and we are very grateful.
Owner
- Name: Kubeflow
- Login: kubeflow
- Kind: organization
- Website: https://kubeflow.org
- Repositories: 41
- Profile: https://github.com/kubeflow
Kubeflow is an open, community driven project to make it easy to deploy and manage an ML stack on Kubernetes
Committers
Last synced: 9 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Alexey Volkov | a****v@a****m | 614 |
| Yuan (Bob) Gong | g****4@g****m | 522 |
| Chen Sun | c****n | 478 |
| Connor McCarthy | m****s@g****m | 465 |
| Googler | n****y@g****m | 366 |
| IronPan | y****a@g****m | 319 |
| Ning | n****o@g****m | 183 |
| Jiaxiao Zheng | j****g@g****m | 177 |
| James Liu | 3****y | 157 |
| sina chavoshi | s****i@g****m | 109 |
| Joe Li | 5****i | 100 |
| dependabot[bot] | 4****] | 99 |
| hongye-sun | 4****n | 98 |
| Riley Bauer | 3****r | 87 |
| jingzhang36 | j****z@g****m | 81 |
| You Quan Chong | y****g@g****m | 81 |
| Ajay Gopinathan | a****n@g****m | 74 |
| Jason Dai | j****i@g****m | 71 |
| gkcalat | 3****t | 59 |
| Humair Khan | H****K | 58 |
| Kevin Naughton | k****n@g****m | 58 |
| Helber Belmiro | h****o@g****m | 55 |
| Yasser Elsayed | y****m | 53 |
| Yaqi Ji | j****2@g****m | 48 |
| Michael Hu | h****l@g****m | 47 |
| Niklas Hansson | n****n@g****m | 47 |
| Lingqing Gan | l****n@g****m | 47 |
| Pascal Vicaire | 2****e | 46 |
| Rui Fang | 3****i | 45 |
| Renmin | r****o | 44 |
| and 436 more... | ||
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 1,435
- Total pull requests: 3,121
- Average time to close issues: over 1 year
- Average time to close pull requests: 4 months
- Total issue authors: 724
- Total pull request authors: 270
- Average comments per issue: 4.78
- Average comments per pull request: 4.56
- Merged pull requests: 1,555
- Bot issues: 7
- Bot pull requests: 1,183
Past Year
- Issues: 282
- Pull requests: 1,104
- Average time to close issues: about 1 month
- Average time to close pull requests: 11 days
- Issue authors: 143
- Pull request authors: 105
- Average comments per issue: 0.89
- Average comments per pull request: 3.65
- Merged pull requests: 666
- Bot issues: 1
- Bot pull requests: 179
Top Authors
Issue Authors
- hbelmiro (77)
- Bobgy (54)
- chensun (36)
- HumairAK (34)
- Ark-kun (19)
- zijianjoy (17)
- axel7083 (15)
- Linchin (15)
- droctothorpe (15)
- rimolive (15)
- DharmitD (14)
- gkcalat (14)
- mprahl (13)
- thesuperzapper (13)
- connor-mccarthy (11)
Pull Request Authors
- copybara-service[bot] (881)
- dependabot[bot] (302)
- HumairAK (161)
- connor-mccarthy (140)
- hbelmiro (122)
- chensun (106)
- mprahl (98)
- Tomcli (52)
- Ark-kun (49)
- VaniHaripriya (45)
- DharmitD (45)
- droctothorpe (44)
- rimolive (42)
- gregsheremeta (32)
- dandawg (32)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 19
-
Total downloads:
- pypi 20,828,246 last-month
- Total docker downloads: 3,863,794
-
Total dependent packages: 85
(may contain duplicates) -
Total dependent repositories: 1,194
(may contain duplicates) - Total versions: 1,017
- Total maintainers: 10
pypi.org: kfp
Kubeflow Pipelines SDK
- Homepage: https://github.com/kubeflow/pipelines
- Documentation: https://kubeflow-pipelines.readthedocs.io/en/stable/
- License: Apache Software License
-
Latest release: 2.14.3
published 6 months ago
Rankings
Maintainers (2)
pypi.org: kfp-server-api
Kubeflow Pipelines API
- Homepage: https://github.com/kubeflow/pipelines
- Documentation: https://kfp-server-api.readthedocs.io/
- License: Apache 2.0
-
Latest release: 2.14.3
published 6 months ago
Rankings
Maintainers (2)
pypi.org: kfp-pipeline-spec
Kubeflow Pipelines pipeline spec
- Homepage: https://github.com/kubeflow/pipelines
- Documentation: https://kfp-pipeline-spec.readthedocs.io/
- License: Apache 2.0
-
Latest release: 2.14.3
published 6 months ago
Rankings
Maintainers (1)
proxy.golang.org: github.com/kubeflow/pipelines/api
- Homepage: https://github.com/kubeflow/pipelines
- Documentation: https://pkg.go.dev/github.com/kubeflow/pipelines/api#section-documentation
- License: Apache-2.0
Rankings
proxy.golang.org: github.com/kubeflow/pipelines/third_party/ml-metadata
- Homepage: https://github.com/kubeflow/pipelines
- Documentation: https://pkg.go.dev/github.com/kubeflow/pipelines/third_party/ml-metadata#section-documentation
- License: Apache-2.0
Rankings
proxy.golang.org: github.com/kubeflow/pipelines
- Homepage: https://github.com/kubeflow/pipelines
- Documentation: https://pkg.go.dev/github.com/kubeflow/pipelines#section-documentation
- License: Apache-2.0
-
Latest release: v1.7.0-alpha.3
published over 4 years ago
Rankings
pypi.org: google-cloud-pipeline-components
This SDK enables a set of First Party (Google owned) pipeline components that allow users to take their experience from Vertex AI SDK and other Google Cloud services and create a corresponding pipeline using KFP or Managed Pipelines.
- Homepage: https://github.com/kubeflow/pipelines/tree/master/components/google-cloud
- Documentation: https://google-cloud-pipeline-components.readthedocs.io/
- License: Apache License 2.0
-
Latest release: 2.20.1
published 8 months ago
Rankings
Maintainers (1)
proxy.golang.org: github.com/kubeflow/pipelines/kubernetes_platform
- Homepage: https://github.com/kubeflow/pipelines
- Documentation: https://pkg.go.dev/github.com/kubeflow/pipelines/kubernetes_platform#section-documentation
- License: Apache-2.0
-
Latest release: v0.0.0-20240124215924-b9e08ded48f7
published about 2 years ago
Rankings
proxy.golang.org: github.com/kubeflow/pipelines/v2
- Homepage: https://github.com/kubeflow/pipelines
- Documentation: https://pkg.go.dev/github.com/kubeflow/pipelines/v2#section-documentation
- License: Apache-2.0
Rankings
proxy.golang.org: github.com/kubeflow/pipelines/test/tools/project-cleaner
- Homepage: https://github.com/kubeflow/pipelines
- Documentation: https://pkg.go.dev/github.com/kubeflow/pipelines/test/tools/project-cleaner#section-documentation
- License: Apache-2.0
Rankings
pypi.org: kfp-dsl
A KFP SDK subpackage containing the DSL and runtime code.
- Homepage: https://github.com/kubeflow/pipelines
- Documentation: https://kfp-dsl.readthedocs.io/
- License: Apache 2.0
-
Latest release: 2.1.2
published over 2 years ago
Rankings
Maintainers (4)
pypi.org: kfp-kubernetes
Kubernetes platform configuration library and generated protos.
- Homepage: https://github.com/kubeflow/pipelines
- Documentation: https://kfp-kubernetes.readthedocs.io/
- License: Apache 2.0
-
Latest release: 2.14.0
published 7 months ago
Rankings
Maintainers (1)
conda-forge.org: kfp
Kubeflow is a machine learning (ML) toolkit that is dedicated to making deployments of ML workflows on Kubernetes simple, portable, and scalable. Kubeflow pipelines are reusable end-to-end ML workflows built using the Kubeflow Pipelines SDK.
- Homepage: https://github.com/kubeflow/pipelines
- License: Apache-2.0
-
Latest release: 1.8.14
published over 3 years ago
Rankings
pypi.org: pytorch-kfp-components
PyTorch Kubeflow Pipeline
- Homepage: https://github.com/kubeflow/pipelines/tree/master/components/PyTorch/pytorch-kfp-components/
- Documentation: https://pytorch-kfp-components.readthedocs.io/
- License: Apache License 2.0
-
Latest release: 0.1.0
published over 4 years ago
Rankings
Maintainers (1)
conda-forge.org: kfp-server-api
Generated python client for the KF Pipelines server API
- Homepage: https://github.com/kubeflow/pipelines/tree/master/backend/api/python_http_client
- License: Apache-2.0
-
Latest release: 1.8.4
published over 3 years ago
Rankings
conda-forge.org: kfp-pipeline-spec
- Homepage: https://github.com/kubeflow/pipelines
- License: Apache-2.0
-
Latest release: 0.1.16
published over 3 years ago
Rankings
pypi.org: mongs-kfp
KubeFlow Pipelines SDK
- Homepage: https://github.com/kubeflow/pipelines
- Documentation: https://kubeflow-pipelines.readthedocs.io/en/stable/
- License: Apache Software License
-
Latest release: 2.0.0a2
published almost 4 years ago
Rankings
Maintainers (1)
pypi.org: humair-test-pkg
Kubeflow Pipelines SDK
- Homepage: https://github.com/kubeflow/pipelines
- Documentation: https://humair-test-pkg.readthedocs.io/
- License: apache-2.0
-
Latest release: 0.3
published 10 months ago
Rankings
Maintainers (1)
pypi.org: kfp-leinao
Kubeflow Pipelines SDK
- Homepage: https://github.com/kubeflow/pipelines
- Documentation: https://kubeflow-pipelines.readthedocs.io/en/stable/
- License: Apache Software License
-
Latest release: 2.4.0
published almost 2 years ago
Rankings
Maintainers (1)
Dependencies
- actions/stale v5 composite
- debian stable build
- golang 1.20.4-buster build
- python 3.7 build
- golang 1.15.10 build
- python 3.8 build
- gcr.io/google.com/cloudsdktool/google-cloud-cli alpine build
- python 3.7-slim build
- ubuntu 16.04 build
- ubuntu 16.04 build
- public.ecr.aws/amazonlinux/amazonlinux 2 build
- public.ecr.aws/lts/ubuntu 18.04_stable build
- public.ecr.aws/amazonlinux/amazonlinux 2 build
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- mcr.microsoft.com/azure-cli latest build
- golang 1.10-stretch build
- python 3.7-alpine3.9 build
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- github.com/Masterminds/squirrel v0.0.0-20190107164353-fa735ea14f09
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- 2032 dependencies
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- gcr.io/deeplearning-platform-release/tf2-cpu.2-2 latest build
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- 2487 dependencies
- @google-cloud/storage ^4.1.3 development
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