[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"similar-elyra-ai--elyra":3,"tool-elyra-ai--elyra":61},[4,18,26,36,44,52],{"id":5,"name":6,"github_repo":7,"description_zh":8,"stars":9,"difficulty_score":10,"last_commit_at":11,"category_tags":12,"status":17},4358,"openclaw","openclaw\u002Fopenclaw","OpenClaw 是一款专为个人打造的本地化 AI 助手，旨在让你在自己的设备上拥有完全可控的智能伙伴。它打破了传统 AI 助手局限于特定网页或应用的束缚，能够直接接入你日常使用的各类通讯渠道，包括微信、WhatsApp、Telegram、Discord、iMessage 等数十种平台。无论你在哪个聊天软件中发送消息，OpenClaw 都能即时响应，甚至支持在 macOS、iOS 和 Android 设备上进行语音交互，并提供实时的画布渲染功能供你操控。\n\n这款工具主要解决了用户对数据隐私、响应速度以及“始终在线”体验的需求。通过将 AI 部署在本地，用户无需依赖云端服务即可享受快速、私密的智能辅助，真正实现了“你的数据，你做主”。其独特的技术亮点在于强大的网关架构，将控制平面与核心助手分离，确保跨平台通信的流畅性与扩展性。\n\nOpenClaw 非常适合希望构建个性化工作流的技术爱好者、开发者，以及注重隐私保护且不愿被单一生态绑定的普通用户。只要具备基础的终端操作能力（支持 macOS、Linux 及 Windows WSL2），即可通过简单的命令行引导完成部署。如果你渴望拥有一个懂你",349277,3,"2026-04-06T06:32:30",[13,14,15,16],"Agent","开发框架","图像","数据工具","ready",{"id":19,"name":20,"github_repo":21,"description_zh":22,"stars":23,"difficulty_score":10,"last_commit_at":24,"category_tags":25,"status":17},3808,"stable-diffusion-webui","AUTOMATIC1111\u002Fstable-diffusion-webui","stable-diffusion-webui 是一个基于 Gradio 构建的网页版操作界面，旨在让用户能够轻松地在本地运行和使用强大的 Stable Diffusion 图像生成模型。它解决了原始模型依赖命令行、操作门槛高且功能分散的痛点，将复杂的 AI 绘图流程整合进一个直观易用的图形化平台。\n\n无论是希望快速上手的普通创作者、需要精细控制画面细节的设计师，还是想要深入探索模型潜力的开发者与研究人员，都能从中获益。其核心亮点在于极高的功能丰富度：不仅支持文生图、图生图、局部重绘（Inpainting）和外绘（Outpainting）等基础模式，还独创了注意力机制调整、提示词矩阵、负向提示词以及“高清修复”等高级功能。此外，它内置了 GFPGAN 和 CodeFormer 等人脸修复工具，支持多种神经网络放大算法，并允许用户通过插件系统无限扩展能力。即使是显存有限的设备，stable-diffusion-webui 也提供了相应的优化选项，让高质量的 AI 艺术创作变得触手可及。",162132,"2026-04-05T11:01:52",[14,15,13],{"id":27,"name":28,"github_repo":29,"description_zh":30,"stars":31,"difficulty_score":32,"last_commit_at":33,"category_tags":34,"status":17},1381,"everything-claude-code","affaan-m\u002Feverything-claude-code","everything-claude-code 是一套专为 AI 编程助手（如 Claude Code、Codex、Cursor 等）打造的高性能优化系统。它不仅仅是一组配置文件，而是一个经过长期实战打磨的完整框架，旨在解决 AI 代理在实际开发中面临的效率低下、记忆丢失、安全隐患及缺乏持续学习能力等核心痛点。\n\n通过引入技能模块化、直觉增强、记忆持久化机制以及内置的安全扫描功能，everything-claude-code 能显著提升 AI 在复杂任务中的表现，帮助开发者构建更稳定、更智能的生产级 AI 代理。其独特的“研究优先”开发理念和针对 Token 消耗的优化策略，使得模型响应更快、成本更低，同时有效防御潜在的攻击向量。\n\n这套工具特别适合软件开发者、AI 研究人员以及希望深度定制 AI 工作流的技术团队使用。无论您是在构建大型代码库，还是需要 AI 协助进行安全审计与自动化测试，everything-claude-code 都能提供强大的底层支持。作为一个曾荣获 Anthropic 黑客大奖的开源项目，它融合了多语言支持与丰富的实战钩子（hooks），让 AI 真正成长为懂上",141543,2,"2026-04-06T11:32:54",[14,13,35],"语言模型",{"id":37,"name":38,"github_repo":39,"description_zh":40,"stars":41,"difficulty_score":32,"last_commit_at":42,"category_tags":43,"status":17},2271,"ComfyUI","Comfy-Org\u002FComfyUI","ComfyUI 是一款功能强大且高度模块化的视觉 AI 引擎，专为设计和执行复杂的 Stable Diffusion 图像生成流程而打造。它摒弃了传统的代码编写模式，采用直观的节点式流程图界面，让用户通过连接不同的功能模块即可构建个性化的生成管线。\n\n这一设计巧妙解决了高级 AI 绘图工作流配置复杂、灵活性不足的痛点。用户无需具备编程背景，也能自由组合模型、调整参数并实时预览效果，轻松实现从基础文生图到多步骤高清修复等各类复杂任务。ComfyUI 拥有极佳的兼容性，不仅支持 Windows、macOS 和 Linux 全平台，还广泛适配 NVIDIA、AMD、Intel 及苹果 Silicon 等多种硬件架构，并率先支持 SDXL、Flux、SD3 等前沿模型。\n\n无论是希望深入探索算法潜力的研究人员和开发者，还是追求极致创作自由度的设计师与资深 AI 绘画爱好者，ComfyUI 都能提供强大的支持。其独特的模块化架构允许社区不断扩展新功能，使其成为当前最灵活、生态最丰富的开源扩散模型工具之一，帮助用户将创意高效转化为现实。",107888,"2026-04-06T11:32:50",[14,15,13],{"id":45,"name":46,"github_repo":47,"description_zh":48,"stars":49,"difficulty_score":10,"last_commit_at":50,"category_tags":51,"status":17},4487,"LLMs-from-scratch","rasbt\u002FLLMs-from-scratch","LLMs-from-scratch 是一个基于 PyTorch 的开源教育项目，旨在引导用户从零开始一步步构建一个类似 ChatGPT 的大型语言模型（LLM）。它不仅是同名技术著作的官方代码库，更提供了一套完整的实践方案，涵盖模型开发、预训练及微调的全过程。\n\n该项目主要解决了大模型领域“黑盒化”的学习痛点。许多开发者虽能调用现成模型，却难以深入理解其内部架构与训练机制。通过亲手编写每一行核心代码，用户能够透彻掌握 Transformer 架构、注意力机制等关键原理，从而真正理解大模型是如何“思考”的。此外，项目还包含了加载大型预训练权重进行微调的代码，帮助用户将理论知识延伸至实际应用。\n\nLLMs-from-scratch 特别适合希望深入底层原理的 AI 开发者、研究人员以及计算机专业的学生。对于不满足于仅使用 API，而是渴望探究模型构建细节的技术人员而言，这是极佳的学习资源。其独特的技术亮点在于“循序渐进”的教学设计：将复杂的系统工程拆解为清晰的步骤，配合详细的图表与示例，让构建一个虽小但功能完备的大模型变得触手可及。无论你是想夯实理论基础，还是为未来研发更大规模的模型做准备",90106,"2026-04-06T11:19:32",[35,15,13,14],{"id":53,"name":54,"github_repo":55,"description_zh":56,"stars":57,"difficulty_score":10,"last_commit_at":58,"category_tags":59,"status":17},4292,"Deep-Live-Cam","hacksider\u002FDeep-Live-Cam","Deep-Live-Cam 是一款专注于实时换脸与视频生成的开源工具，用户仅需一张静态照片，即可通过“一键操作”实现摄像头画面的即时变脸或制作深度伪造视频。它有效解决了传统换脸技术流程繁琐、对硬件配置要求极高以及难以实时预览的痛点，让高质量的数字内容创作变得触手可及。\n\n这款工具不仅适合开发者和技术研究人员探索算法边界，更因其极简的操作逻辑（仅需三步：选脸、选摄像头、启动），广泛适用于普通用户、内容创作者、设计师及直播主播。无论是为了动画角色定制、服装展示模特替换，还是制作趣味短视频和直播互动，Deep-Live-Cam 都能提供流畅的支持。\n\n其核心技术亮点在于强大的实时处理能力，支持口型遮罩（Mouth Mask）以保留使用者原始的嘴部动作，确保表情自然精准；同时具备“人脸映射”功能，可同时对画面中的多个主体应用不同面孔。此外，项目内置了严格的内容安全过滤机制，自动拦截涉及裸露、暴力等不当素材，并倡导用户在获得授权及明确标注的前提下合规使用，体现了技术发展与伦理责任的平衡。",88924,"2026-04-06T03:28:53",[14,15,13,60],"视频",{"id":62,"github_repo":63,"name":64,"description_en":65,"description_zh":66,"ai_summary_zh":66,"readme_en":67,"readme_zh":68,"quickstart_zh":69,"use_case_zh":70,"hero_image_url":71,"owner_login":72,"owner_name":73,"owner_avatar_url":74,"owner_bio":75,"owner_company":76,"owner_location":76,"owner_email":76,"owner_twitter":76,"owner_website":76,"owner_url":77,"languages":78,"stars":118,"forks":119,"last_commit_at":120,"license":121,"difficulty_score":10,"env_os":122,"env_gpu":123,"env_ram":123,"env_deps":124,"category_tags":132,"github_topics":134,"view_count":32,"oss_zip_url":76,"oss_zip_packed_at":76,"status":17,"created_at":154,"updated_at":155,"faqs":156,"releases":186},4533,"elyra-ai\u002Felyra","elyra","Elyra extends JupyterLab with an AI centric approach.","Elyra 是一款专为人工智能工作流设计的 JupyterLab 扩展工具，旨在将原本侧重于交互式探索的笔记本环境，升级为支持生产级 AI 管道开发的综合平台。它主要解决了数据科学家在从原型设计过渡到实际部署时面临的痛点，例如难以将分散的代码片段整合为可重复执行的批量任务，或缺乏可视化的流程编排能力。\n\n这款软件非常适合 AI 研究人员、数据科学家以及机器学习工程师使用。通过 Elyra，用户无需离开熟悉的 Jupyter 界面，即可利用直观的可视化编辑器拖拽构建复杂的 AI 流水线，并直接将 Notebook、Python 或 R 脚本作为批量作业提交到本地或远程混合环境中运行。其独特的技术亮点包括对混合运行时的原生支持、可复用的代码片段管理、集成化的 Git 版本控制，以及实验性的 Python 脚本调试功能。此外，Elyra 还能结合 AI 助手提供智能代码建议，并自动生成目录以优化大型脚本的导航体验。对于希望在不切换工具链的前提下，提升模型开发效率并实现流程标准化的团队而言，Elyra 是一个实用且强大的选择。","\u003C!--\n{% comment %}\nCopyright 2018-2026 Elyra Authors\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n\nhttp:\u002F\u002Fwww.apache.org\u002Flicenses\u002FLICENSE-2.0\n\nUnless required by applicable law or agreed to in writing, software\ndistributed under the License is distributed on an \"AS IS\" BASIS,\nWITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\nSee the License for the specific language governing permissions and\nlimitations under the License.\n{% endcomment %}\n-->\n\n\n[![PyPI version](https:\u002F\u002Fbadge.fury.io\u002Fpy\u002Felyra.svg)](https:\u002F\u002Fbadge.fury.io\u002Fpy\u002Felyra)\n[![Anaconda-Server Badge](https:\u002F\u002Fanaconda.org\u002Fconda-forge\u002Felyra\u002Fbadges\u002Fversion.svg)](https:\u002F\u002Fanaconda.org\u002Fconda-forge\u002Felyra)\n[![Downloads](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Felyra-ai_elyra_readme_150dfe653354.png)](https:\u002F\u002Fpepy.tech\u002Fproject\u002Felyra)\n[![Documentation Status](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Felyra-ai_elyra_readme_13d664e1afd7.png)](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002F?badge=latest)\n[![GitHub](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fissue_tracking-github-blue.svg)](https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fissues)\n[![OpenSSF Best Practices](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Felyra-ai_elyra_readme_50ccde67b228.png)](https:\u002F\u002Fbestpractices.coreinfrastructure.org\u002Fprojects\u002F5761)\n[![Gitter](https:\u002F\u002Fbadges.gitter.im\u002Felyra-ai\u002Fcommunity.svg)](https:\u002F\u002Fgitter.im\u002Felyra-ai\u002Fcommunity?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)\n\n# Elyra\n\nElyra is a set of AI-centric extensions to JupyterLab Notebooks.\n\nElyra currently includes the following functionality:\n\n- [Visual Pipeline Editor](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html#ai-pipelines-visual-editor)\n- [Ability to run a notebook, Python or R script as a batch job](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html#ability-to-run-a-notebook-python-or-r-script-as-a-batch-job)\n- [Reusable Code Snippets](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html#reusable-code-snippets)\n- [AI Assistant integration](https:\u002F\u002Fgithub.com\u002Fjupyterlab\u002Fmagic-wand) for AI-powered code assistance in notebook cells. See the [AI Assistant setup guide](docs\u002Fsource\u002Fuser_guide\u002Fai-assistant-setup.md) for configuration details.\n- [Hybrid runtime support](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html#hybrid-runtime-support) based on [Jupyter Enterprise Gateway](https:\u002F\u002Fgithub.com\u002Fjupyter\u002Fenterprise_gateway)\n- [Python and R script editors with local\u002Fremote execution capabilities](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html#python-and-r-scripts-execution-support)\n- [Python script navigation using auto-generated Table of Contents](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html##python-and-r-scripts-execution-support)\n- [Python script integrated debugger (Experimental)](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html##python-and-r-scripts-execution-support)\n- [Notebook navigation using auto-generated outlines using Table of Contents](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html#notebook-navigation-using-auto-generated-table-of-contents)\n- [Language Server Protocol integration](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html#language-server-protocol-integration)\n- [Version control using Git integration](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html#version-control-using-git-integration)\n\n![Elyra](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Felyra-ai_elyra_readme_7e6236a0672e.png)\n\nThe [Elyra Getting Started Guide](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html) includes more details on these features. A version-specific summary of new features is located on the [releases page](https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Freleases).\n\n## Try Elyra\n\n#### Using container images\n\nYou can also try Elyra by running one of the container images from [Docker Hub](https:\u002F\u002Fhub.docker.com\u002Fr\u002Felyra\u002Felyra\u002Ftags) or [quay.io](https:\u002F\u002Fquay.io\u002Frepository\u002Felyra\u002Felyra?tab=tags):\n- `elyra\u002Felyra:latest` has the latest released version installed.\n- `elyra\u002Felyra:x.y.z` has a specific version installed.\n\nNote: You can also [build a container image from the `main` branch (\"dev build\")](https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Ftree\u002Fmain\u002Fetc\u002Fdocker\u002Felyra) to try out features that have not been released yet.\n\nTo run one of the container images, issue the following command, specifying a tag of your choice.\n\n```\ndocker run -it -p 8888:8888 elyra\u002Felyra:dev jupyter lab --debug\n```\n\nTo make a local directory containing your Notebooks (e.g. ${HOME}\u002Fopensource\u002Fjupyter-notebooks\u002F) available in your\ndocker container, you can use a mount command similar to the following:\n\n```\ndocker run -it -p 8888:8888 -v ${HOME}\u002Fopensource\u002Fjupyter-notebooks\u002F:\u002Fhome\u002Fjovyan\u002Fwork -w \u002Fhome\u002Fjovyan\u002Fwork elyra\u002Felyra:dev jupyter lab --debug\n```\n\nThese should produce output similar to that below, where you can then find the URL to be used to access Elyra in your local browser.\n\n```\n    To access the notebook, open this file in a browser:\n        file:\u002F\u002F\u002Fhome\u002Fjovyan\u002F.local\u002Fshare\u002Fjupyter\u002Fruntime\u002Fnbserver-6-open.html\n    Or copy and paste one of these URLs:\n        http:\u002F\u002F4d17829ecd4c:8888\u002F?token=d690bde267ec75d6f88c64a39825f8b05b919dd084451f82\n     or http:\u002F\u002F127.0.0.1:8888\u002F?token=d690bde267ec75d6f88c64a39825f8b05b919dd084451f82\n```\n\nRefer to the [installation documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fstable\u002Fgetting_started\u002Finstallation.html#docker) for details.\n\n## Installation\n\nFor detailed information refer to the [installation documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fstable\u002Fgetting_started\u002Finstallation.html).\n\n### Prerequisites :\n* [Node.js 22](https:\u002F\u002Fnodejs.org\u002Fen\u002F)\n* [Python 3.10+](https:\u002F\u002Fwww.python.org\u002Fdownloads\u002F)\n* [Miniconda](https:\u002F\u002Fdocs.conda.io\u002Fen\u002Flatest\u002Fminiconda.html) \u002F [Micromamba](https:\u002F\u002Fmamba.readthedocs.io\u002Fen\u002Flatest\u002Finstallation\u002Fmicromamba-installation.html) (optional)\n\n### Install current release (for JupyterLab 4.x)\n\nThe current release version is displayed at the top of this page.\n\n  - Install from PyPI\n\n    ```bash\n    pip3 install --upgrade \"elyra[all]\"\n    ```\n\n  - Install from conda-forge\n\n    ```bash\n    conda install -c conda-forge \"elyra[all]\"\n    ```\n\n### Install older release\n\nInstallation instructions and JupyterLab support vary by release. Note that a JupyterLab build is required. Installation instructions are located in the [release-specific documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fstable\u002F), which can be accessed by selecting a specific version.\n\n\u003Cdetails>\n  \u003Csummary>Elyra 4.x (JupyterLab 4.2.5+)\u003C\u002Fsummary>\n\n  - Install from PyPI\n\n    ```bash\n    pip3 install --upgrade \"elyra[all]\"\n    ```\n\n  - Install from conda-forge\n\n    ```bash\n    conda install -c conda-forge \"elyra[all]\"\n    ```\n\u003C\u002Fdetails>\n\n\u003Cdetails>\n  \u003Csummary>Elyra 3.7 \u003C 4.0 (JupyterLab 3.x)\u003C\u002Fsummary>\n\n  - Install from PyPI\n\n    ```bash\n    pip3 install --upgrade \"elyra[all]\u003C4.0.0\"\n    ```\n\n  - Install from conda-forge\n\n    ```bash\n    conda install -c conda-forge \"elyra[all]\u003C4.0.0\"\n    ```\n\u003C\u002Fdetails>\n\n\u003Cdetails>\n  \u003Csummary>Elyra 3.1 \u003C 3.7 (JupyterLab 3.x)\u003C\u002Fsummary>\n\n  - Install from PyPI\n\n    ```bash\n    pip3 install --upgrade \"elyra[all]>=3.1.0\" && jupyter lab build\n    ```\n\n  - Install from conda-forge\n\n    ```bash\n    conda install -c conda-forge \"elyra[all]>=3.1.0\" && jupyter lab build\n    ```\n\u003C\u002Fdetails>\n\n\u003Cdetails>\n  \u003Csummary>Elyra 2.0 \u003C 3.1 (JupyterLab 3.x)\u003C\u002Fsummary>\n\n  - Install from PyPI\n\n    ```bash\n    pip3 install --upgrade \"elyra>=2.0.1\" && jupyter lab build\n    ```\n\n  - Install from conda-forge\n\n    ```bash\n    conda install -c conda-forge \"elyra>=2.0.1\" && jupyter lab build\n    ```\n\u003C\u002Fdetails>\n\n### Verify Installation\n\nRun the following commands to verify the installation. Note that in the example output below the `[version]` placeholder is displayed instead of an actual version identifier, which might change with every release.\n\n```bash\njupyter server extension list\n```\nShould output:\n```\nConfig dir: \u002F...\u002F.jupyter\n\nConfig dir: \u002F...\u002Fetc\u002Fjupyter\n    elyra enabled\n    - Validating elyra...\n      elyra  OK\n    jupyter_lsp enabled\n    - Validating jupyter_lsp...\n      jupyter_lsp [version] OK\n    jupyter_resource_usage enabled\n    - Validating jupyter_resource_usage...\n      jupyter_resource_usage [version] OK\n    jupyter_server_mathjax enabled\n    - Validating jupyter_server_mathjax...\n      jupyter_server_mathjax  OK\n    jupyterlab enabled\n    - Validating jupyterlab...\n      jupyterlab [version] OK\n    jupyterlab_git enabled\n    - Validating jupyterlab_git...\n      jupyterlab_git [version] OK\n    nbclassic enabled\n    - Validating nbclassic...\n      nbclassic  OK\n    nbdime enabled\n    - Validating nbdime...\n      nbdime [version] OK\n\nConfig dir: \u002F...\u002Fetc\u002Fjupyter\n```\n\nNOTE: If you don't see the Elyra server extension enabled, you may need to explicitly enable\nit with `jupyter server extension enable elyra`\n\n```bash\njupyter labextension list\n```\nShould output:\n```\nJupyterLab [version]\n\u002F...\u002Fshare\u002Fjupyter\u002Flabextensions\n        nbdime-jupyterlab [version] enabled OK\n        @jupyter-server\u002Fresource-usage [version] enabled OK (python, jupyter-resource-usage)\n        @krassowski\u002Fjupyterlab-lsp [version] enabled OK (python, jupyterlab_lsp)\n        @elyra\u002Fcode-snippet-extension [version] enabled OK\n        @elyra\u002Fmetadata-extension [version] enabled OK\n        @elyra\u002Fpipeline-editor-extension [version] enabled OK\n        @elyra\u002Fpython-editor-extension [version] enabled OK\n        @elyra\u002Fscala-editor-extension [version] enabled OK\n        @elyra\u002Fr-editor-extension [version] enabled OK\n        @elyra\u002Ftheme-extension [version] enabled OK\n        @jupyterlab\u002Fgit [version] enabled OK (python, jupyterlab-git)\n\nOther labextensions (built into JupyterLab)\n   app dir: \u002F...\u002Fshare\u002Fjupyter\u002Flab\n```\n\n## Starting Elyra\nAfter verifying Elyra has been installed, start Elyra with:\n```bash\njupyter lab\n```\n\n## Getting Help\n\nWe welcome your questions, ideas, and feedback. Check the [`Getting Help` section in the `Getting Started guide`](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Fgetting-help.html) to learn more about the channels you can use to get in touch with us.\n\n## Contributing to Elyra\nIf you are interested in helping make Elyra better, we encourage you to take a look at our\n[Contributing](CONTRIBUTING.md) page,\n[Development Workflow](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fdeveloper_guide\u002Fdevelopment-workflow.html)\ndocumentation, and invite you to attend our weekly dev community meetings.\n\n## Meetup with Us!\nOur daily and weekly community meeting schedule can be found [here](https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Fcommunity#daily-dev-meetings).\n","\u003C!--\n{% comment %}\n版权所有 © 2018–2026 Elyra 作者\n\n根据 Apache License, Version 2.0（“许可证”）授权；除非符合许可证的规定，否则不得使用本文件。\n您可以在以下网址获得许可证副本：\n\nhttp:\u002F\u002Fwww.apache.org\u002Flicenses\u002FLICENSE-2.0\n\n除非适用法律要求或书面同意，否则软件按“原样”分发，不提供任何形式的保证或条件。\n有关权限和限制的具体语言，请参阅许可证。\n\n{% endcomment %}\n-->\n\n\n[![PyPI版本](https:\u002F\u002Fbadge.fury.io\u002Fpy\u002Felyra.svg)](https:\u002F\u002Fbadge.fury.io\u002Fpy\u002Felyra)\n[![Anaconda-Server徽章](https:\u002F\u002Fanaconda.org\u002Fconda-forge\u002Felyra\u002Fbadges\u002Fversion.svg)](https:\u002F\u002Fanaconda.org\u002Fconda-forge\u002Felyra)\n[![下载量](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Felyra-ai_elyra_readme_150dfe653354.png)](https:\u002F\u002Fpepy.tech\u002Fproject\u002Felyra)\n[![文档状态](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Felyra-ai_elyra_readme_13d664e1afd7.png)](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002F?badge=latest)\n[![GitHub](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fissue_tracking-github-blue.svg)](https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fissues)\n[![OpenSSF最佳实践](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Felyra-ai_elyra_readme_50ccde67b228.png)](https:\u002F\u002Fbestpractices.coreinfrastructure.org\u002Fprojects\u002F5761)\n[![Gitter](https:\u002F\u002Fbadges.gitter.im\u002Felyra-ai\u002Fcommunity.svg)](https:\u002F\u002Fgitter.im\u002Felyra-ai\u002Fcommunity?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)\n\n# Elyra\n\nElyra 是一组以 AI 为中心的 JupyterLab Notebook 扩展。\n\nElyra 目前包含以下功能：\n\n- [可视化工作流编辑器](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html#ai-pipelines-visual-editor)\n- [将 Notebook、Python 或 R 脚本作为批处理作业运行的能力](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html#ability-to-run-a-notebook-python-or-r-script-as-a-batch-job)\n- [可重用代码片段](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html#reusable-code-snippets)\n- [AI 助手集成](https:\u002F\u002Fgithub.com\u002Fjupyterlab\u002Fmagic-wand)，用于在 Notebook 单元格中提供 AI 驱动的代码辅助。配置详情请参阅 [AI 助手设置指南](docs\u002Fsource\u002Fuser_guide\u002Fai-assistant-setup.md)。\n- [混合运行时支持](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html#hybrid-runtime-support)，基于 [Jupyter Enterprise Gateway](https:\u002F\u002Fgithub.com\u002Fjupyter\u002Fenterprise_gateway)\n- [具有本地\u002F远程执行能力的 Python 和 R 脚本编辑器](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html#python-and-r-scripts-execution-support)\n- [使用自动生成目录的 Python 脚本导航](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html##python-and-r-scripts-execution-support)\n- [Python 脚本集成调试器（实验性）](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html##python-and-r-scripts-execution-support)\n- [使用自动生成目录的 Notebook 导航](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html#notebook-navigation-using-auto-generated-table-of-contents)\n- [语言服务器协议集成](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html#language-server-protocol-integration)\n- [使用 Git 集成进行版本控制](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html#version-control-using-git-integration)\n\n![Elyra](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Felyra-ai_elyra_readme_7e6236a0672e.png)\n\n[Elyra 入门指南](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Foverview.html) 包含更多关于这些功能的详细信息。特定版本的新特性摘要位于 [发布页面](https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Freleases)。\n\n## 试用 Elyra\n\n#### 使用容器镜像\n\n您也可以通过运行来自 [Docker Hub](https:\u002F\u002Fhub.docker.com\u002Fr\u002Felyra\u002Felyra\u002Ftags) 或 [quay.io](https:\u002F\u002Fquay.io\u002Frepository\u002Felyra\u002Felyra?tab=tags) 的容器镜像来试用 Elyra：\n- `elyra\u002Felyra:latest` 安装了最新发布的版本。\n- `elyra\u002Felyra:x.y.z` 安装了特定版本。\n\n注意：您还可以从 `main` 分支构建容器镜像（“开发版”），以试用尚未发布的功能。\n\n要运行其中一个容器镜像，您可以发出以下命令，并指定您选择的标签。\n\n```\ndocker run -it -p 8888:8888 elyra\u002Felyra:dev jupyter lab --debug\n```\n\n要使包含您的 Notebooks 的本地目录（例如 ${HOME}\u002Fopensource\u002Fjupyter-notebooks\u002F）在 Docker 容器中可用，可以使用类似如下的挂载命令：\n\n```\ndocker run -it -p 8888:8888 -v ${HOME}\u002Fopensource\u002Fjupyter-notebooks\u002F:\u002Fhome\u002Fjovyan\u002Fwork -w \u002Fhome\u002Fjovyan\u002Fwork elyra\u002Felyra:dev jupyter lab --debug\n```\n\n这些命令应产生类似于下面的输出，您可以在其中找到用于在本地浏览器中访问 Elyra 的 URL。\n\n```\n    要访问 Notebook，请在浏览器中打开此文件：\n        file:\u002F\u002F\u002Fhome\u002Fjovyan\u002F.local\u002Fshare\u002Fjupyter\u002Fruntime\u002Fnbserver-6-open.html\n    或复制并粘贴以下任一 URL：\n        http:\u002F\u002F4d17829ecd4c:8888\u002F?token=d690bde267ec75d6f88c64a39825f8b05b919dd084451f82\n     或 http:\u002F\u002F127.0.0.1:8888\u002F?token=d690bde267ec75d6f88c64a39825f8b05b919dd084451f82\n```\n\n有关详细信息，请参阅 [安装文档](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fstable\u002Fgetting_started\u002Finstallation.html#docker)。\n\n## 安装\n\n有关详细信息，请参阅 [安装文档](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fstable\u002Fgetting_started\u002Finstallation.html)。\n\n### 先决条件：\n* [Node.js 22](https:\u002F\u002Fnodejs.org\u002Fen\u002F)\n* [Python 3.10+](https:\u002F\u002Fwww.python.org\u002Fdownloads\u002F)\n* [Miniconda](https:\u002F\u002Fdocs.conda.io\u002Fen\u002Flatest\u002Fminiconda.html) \u002F [Micromamba](https:\u002F\u002Fmamba.readthedocs.io\u002Fen\u002Flatest\u002Finstallation\u002Fmicromamba-installation.html)（可选）\n\n### 安装当前版本（适用于 JupyterLab 4.x）\n\n当前版本显示在本页顶部。\n\n  - 从 PyPI 安装\n\n    ```bash\n    pip3 install --upgrade \"elyra[all]\"\n    ```\n\n  - 从 conda-forge 安装\n\n    ```bash\n    conda install -c conda-forge \"elyra[all]\"\n    ```\n\n### 安装旧版本\n\n不同版本的安装说明和 JupyterLab 支持有所不同。请注意，需要构建 JupyterLab 才能使用。安装说明位于[特定版本的文档](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fstable\u002F)中，可通过选择特定版本进行访问。\n\n\u003Cdetails>\n  \u003Csummary>Elyra 4.x（JupyterLab 4.2.5+）\u003C\u002Fsummary>\n\n  - 从 PyPI 安装\n\n    ```bash\n    pip3 install --upgrade \"elyra[all]\"\n    ```\n\n  - 从 conda-forge 安装\n\n    ```bash\n    conda install -c conda-forge \"elyra[all]\"\n    ```\n\u003C\u002Fdetails>\n\n\u003Cdetails>\n  \u003Csummary>Elyra 3.7 \u003C 4.0（JupyterLab 3.x）\u003C\u002Fsummary>\n\n  - 从 PyPI 安装\n\n    ```bash\n    pip3 install --upgrade \"elyra[all]\u003C4.0.0\"\n    ```\n\n  - 从 conda-forge 安装\n\n    ```bash\n    conda install -c conda-forge \"elyra[all]\u003C4.0.0\"\n    ```\n\u003C\u002Fdetails>\n\n\u003Cdetails>\n  \u003Csummary>Elyra 3.1 \u003C 3.7（JupyterLab 3.x）\u003C\u002Fsummary>\n\n  - 从 PyPI 安装\n\n    ```bash\n    pip3 install --upgrade \"elyra[all]>=3.1.0\" && jupyter lab build\n    ```\n\n  - 从 conda-forge 安装\n\n    ```bash\n    conda install -c conda-forge \"elyra[all]>=3.1.0\" && jupyter lab build\n    ```\n\u003C\u002Fdetails>\n\n\u003Cdetails>\n  \u003Csummary>Elyra 2.0 \u003C 3.1（JupyterLab 3.x）\u003C\u002Fsummary>\n\n  - 从 PyPI 安装\n\n    ```bash\n    pip3 install --upgrade \"elyra>=2.0.1\" && jupyter lab build\n    ```\n\n  - 从 conda-forge 安装\n\n    ```bash\n    conda install -c conda-forge \"elyra>=2.0.1\" && jupyter lab build\n    ```\n\u003C\u002Fdetails>\n\n### 验证安装\n\n运行以下命令以验证安装。请注意，在下面的示例输出中，`[version]` 占位符代替了实际的版本标识符，该标识符可能会随每次发布而变化。\n\n```bash\njupyter server extension list\n```\n应输出：\n```\n配置目录：\u002F...\u002F.jupyter\n\n配置目录：\u002F...\u002Fetc\u002Fjupyter\n    elyra 已启用\n    - 正在验证 elyra...\n      elyra 已通过\n    jupyter_lsp 已启用\n    - 正在验证 jupyter_lsp...\n      jupyter_lsp [version] 已通过\n    jupyter_resource_usage 已启用\n    - 正在验证 jupyter_resource_usage...\n      jupyter_resource_usage [version] 已通过\n    jupyter_server_mathjax 已启用\n    - 正在验证 jupyter_server_mathjax...\n      jupyter_server_mathjax 已通过\n    jupyterlab 已启用\n    - 正在验证 jupyterlab...\n      jupyterlab [version] 已通过\n    jupyterlab_git 已启用\n    - 正在验证 jupyterlab_git...\n      jupyterlab_git [version] 已通过\n    nbclassic 已启用\n    - 正在验证 nbclassic...\n      nbclassic 已通过\n    nbdime 已启用\n    - 正在验证 nbdime...\n      nbdime [version] 已通过\n\n配置目录：\u002F...\u002Fetc\u002Fjupyter\n```\n\n注意：如果您没有看到 Elyra 服务器扩展已启用，可能需要使用 `jupyter server extension enable elyra` 命令显式启用它。\n\n```bash\njupyter labextension list\n```\n应输出：\n```\nJupyterLab [version]\n\u002F...\u002Fshare\u002Fjupyter\u002Flabextensions\n        nbdime-jupyterlab [version] 已启用且正常\n        @jupyter-server\u002Fresource-usage [version] 已启用且正常（Python，jupyter-resource-usage）\n        @krassowski\u002Fjupyterlab-lsp [version] 已启用且正常（Python，jupyterlab_lsp）\n        @elyra\u002Fcode-snippet-extension [version] 已启用且正常\n        @elyra\u002Fmetadata-extension [version] 已启用且正常\n        @elyra\u002Fpipeline-editor-extension [version] 已启用且正常\n        @elyra\u002Fpython-editor-extension [version] 已启用且正常\n        @elyra\u002Fscala-editor-extension [version] 已启用且正常\n        @elyra\u002Fr-editor-extension [version] 已启用且正常\n        @elyra\u002Ftheme-extension [version] 已启用且正常\n        @jupyterlab\u002Fgit [version] 已启用且正常（Python，jupyterlab-git）\n\n其他内置在 JupyterLab 中的 Lab 扩展\n   应用程序目录：\u002F...\u002Fshare\u002Fjupyter\u002Flab\n```\n\n## 启动 Elyra\n在确认 Elyra 已成功安装后，可以通过以下命令启动 Elyra：\n```bash\njupyter lab\n```\n\n## 获取帮助\n\n我们欢迎您的问题、想法和反馈。请查看《入门指南》中的[`获取帮助`部分](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Fgetting-help.html)，了解您可以用来与我们联系的各种渠道。\n\n## 参与 Elyra 贡献\n如果您有兴趣帮助改进 Elyra，我们鼓励您查看我们的[贡献](CONTRIBUTING.md)页面、[开发工作流程](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fdeveloper_guide\u002Fdevelopment-workflow.html)文档，并邀请您参加我们每周的开发者社区会议。\n\n## 与我们见面！\n我们的每日和每周社区会议日程安排可在[此处](https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Fcommunity#daily-dev-meetings)找到。","# Elyra 快速上手指南\n\nElyra 是一套面向 AI 开发的 JupyterLab 扩展工具集，支持可视化流水线编辑、脚本批量执行、代码片段复用及 AI 助手集成等功能，旨在简化机器学习工作流的构建与运行。\n\n## 环境准备\n\n在开始之前，请确保您的系统满足以下前置依赖要求：\n\n*   **Node.js**: 版本 22\n*   **Python**: 版本 3.10 或更高\n*   **包管理器** (可选但推荐): Miniconda 或 Micromamba\n*   **JupyterLab**: 需安装 JupyterLab 4.x (当前最新版本)\n\n> **注意**：国内用户若遇到网络问题，建议在安装 Python 包时配置清华或阿里云镜像源。\n\n## 安装步骤\n\n您可以选择通过 `pip` 或 `conda` 进行安装。以下命令将安装包含所有功能的完整版本。\n\n### 方式一：使用 pip 安装\n\n```bash\n# 推荐使用国内镜像源加速下载\npip3 install --upgrade \"elyra[all]\" -i https:\u002F\u002Fpypi.tuna.tsinghua.edu.cn\u002Fsimple\n```\n\n### 方式二：使用 conda 安装\n\n```bash\nconda install -c conda-forge \"elyra[all]\"\n# 若 conda-forge 下载缓慢，可尝试配置国内镜像源后执行上述命令\n```\n\n### 验证安装\n\n安装完成后，运行以下命令检查服务器扩展和前端插件是否启用成功：\n\n```bash\njupyter server extension list\n```\n输出中应包含 `elyra enabled` 且状态为 `OK`。\n\n```bash\njupyter labextension list\n```\n输出中应包含 `@elyra\u002Fpipeline-editor-extension` 等相关插件且状态为 `enabled OK`。\n\n> 如果未看到 Elyra 服务器扩展启用，请手动执行：`jupyter server extension enable elyra`\n\n## 基本使用\n\n### 1. 启动 Elyra\n\n安装验证无误后，直接启动 JupyterLab 即可进入 Elyra 环境：\n\n```bash\njupyter lab\n```\n\n浏览器会自动打开 JupyterLab 界面，此时您已可以使用 Elyra 的各项功能。\n\n### 2. 创建可视化 AI 流水线 (Visual Pipeline)\n\n1.  在 JupyterLab 左侧文件浏览器中，右键点击空白处。\n2.  选择 **New** > **Pipeline**。\n3.  将现有的 `.ipynb` (Notebook)、`.py` (Python 脚本) 或 `.r` (R 脚本) 文件拖拽至画布中作为节点。\n4.  连接节点以定义执行顺序。\n5.  点击工具栏的 **Run** 按钮，即可将流水线作为批处理作业提交执行（支持本地或远程集群）。\n\n### 3. 使用 AI 助手与代码片段\n\n*   **AI 助手**：在 Notebook 单元格中，可通过集成的 AI Assistant (需额外配置) 获取代码建议。\n*   **代码片段**：点击左侧边栏的代码片段图标，可直接拖拽预定义的常用代码块到编辑器中，提高开发效率。\n\n### 替代方案：使用 Docker 快速体验\n\n如果您不想配置本地环境，可以直接使用 Docker 容器运行最新版 Elyra：\n\n```bash\ndocker run -it -p 8888:8888 -v ${HOME}\u002Fjupyter-notebooks\u002F:\u002Fhome\u002Fjovyan\u002Fwork -w \u002Fhome\u002Fjovyan\u002Fwork elyra\u002Felyra:latest jupyter lab --debug\n```\n\n运行成功后，复制终端输出的带有 token 的 URL (例如 `http:\u002F\u002F127.0.0.1:8888\u002F?token=...`) 到浏览器访问即可。","某金融数据团队需要在每周固定时间自动运行包含数据清洗、特征工程和模型训练的多个 Jupyter Notebook，并将结果归档。\n\n### 没有 elyra 时\n- 工程师必须手动按顺序逐个打开并执行五个独立的 Notebook，一旦中间步骤报错，整个流程中断且难以快速定位重跑。\n- 缺乏可视化的流程视图，新加入的团队成员很难理解各个脚本之间的数据依赖关系和整体执行逻辑。\n- 将本地开发好的 Notebook 部署到生产环境时，需要额外编写复杂的 Shell 脚本或 Airflow DAG 文件来调度批处理任务，维护成本极高。\n- 代码复用困难，常用的数据预处理逻辑散落在不同文件中，每次新项目都需要重复复制粘贴，容易引入版本不一致的错误。\n\n### 使用 elyra 后\n- 利用可视化管道编辑器（Visual Pipeline Editor），通过拖拽即可将多个 Notebook 和 Python 脚本串联成有向无环图，支持一键提交为批量作业自动运行。\n- 管道图清晰展示了节点间的输入输出依赖，任何环节失败均可独立重试，大幅降低了运维排查难度。\n- 原生支持将 Notebook 直接作为批处理任务在本地或远程集群（如 Kubernetes）上调度，无需编写额外的胶水代码即可实现从开发到生产的无缝衔接。\n- 内置可重用代码片段库，团队可将通用的特征提取函数标准化存储，直接在各个节点中调用，确保了逻辑的一致性和开发效率。\n\nelyra 通过将分散的 Notebook 转化为可编排、可自动化的视觉化 AI 管道，彻底解决了机器学习工作流从实验探索到生产部署的“最后一公里”难题。","https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Felyra-ai_elyra_7e6236a0.png","elyra-ai","Elyra AI Toolkit","https:\u002F\u002Foss.gittoolsai.com\u002Favatars\u002Felyra-ai_01ab9dd6.png","Elyra is an open source set of AI-centric extensions to JupyterLab Notebooks. The project is hosted in incubation in the LF AI & Data Foundation.",null,"https:\u002F\u002Fgithub.com\u002Felyra-ai",[79,83,87,91,95,99,103,107,111,114],{"name":80,"color":81,"percentage":82},"Python","#3572A5",71.8,{"name":84,"color":85,"percentage":86},"TypeScript","#3178c6",21.3,{"name":88,"color":89,"percentage":90},"CSS","#663399",2.3,{"name":92,"color":93,"percentage":94},"Jinja","#a52a22",1.7,{"name":96,"color":97,"percentage":98},"Jupyter Notebook","#DA5B0B",1.4,{"name":100,"color":101,"percentage":102},"Makefile","#427819",0.7,{"name":104,"color":105,"percentage":106},"Shell","#89e051",0.3,{"name":108,"color":109,"percentage":110},"Dockerfile","#384d54",0.2,{"name":112,"color":113,"percentage":110},"JavaScript","#f1e05a",{"name":115,"color":116,"percentage":117},"R","#198CE7",0.1,1991,367,"2026-04-06T12:05:24","Apache-2.0","未说明 (通常支持 Linux, macOS, Windows，只要满足 Node.js 和 Python 环境)","未说明",{"notes":125,"python":126,"dependencies":127},"Elyra 是 JupyterLab 的扩展工具，主要用于可视化管道编辑和脚本执行。安装前必须预先安装 Node.js 22 和 Python 3.10+。不同版本的 Elyra 对应不同版本的 JupyterLab（如 Elyra 4.x 需要 JupyterLab 4.2.5+），旧版本安装后可能需要手动运行 'jupyter lab build'。推荐使用 Docker 容器快速体验，或通过 pip\u002Fconda 安装。","3.10+",[128,129,130,131],"Node.js 22","JupyterLab 4.x (当前版本)","jupyter_server","Miniconda\u002FMicromamba (可选)",[16,15,13,133,14],"插件",[135,136,137,138,139,140,141,142,143,64,144,145,146,147,148,149,150,151,152,153],"notebooks","notebook-jupyter","jupyterlab","jupyterlab-extensions","ai","machine-learning","pipelines","kubeflow-pipelines","python","binder","jupyterlab-notebooks","kubeflow","hacktoberfest","jupyterlab-extension","anaconda","pypi","docker","apache-airflow","airflow","2026-03-27T02:49:30.150509","2026-04-07T02:08:24.388741",[157,162,167,172,177,182],{"id":158,"question_zh":159,"answer_zh":160,"source_url":161},20643,"如何在 Elyra 中添加自定义 Docker 镜像（例如包含 CellProfiler）作为执行环境？","Elyra 支持添加自定义 Docker 镜像作为执行环境。对于希望使用特定工具（如 CellProfiler）的用户，只需确保镜像配置正确即可。在 Elyra 1.3 版本及以后，系统已修复了相关兼容性问题，现在默认使用 'python3' 别名而非 'python'，因此大多数包含 Python 库的镜像可以直接使用，无需额外修改。如果遇到问题，请检查镜像是否基于受支持的架构并包含必要的依赖项。","https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fissues\u002F901",{"id":163,"question_zh":164,"answer_zh":165,"source_url":166},20644,"如何在 Kubeflow Pipelines (KFP) 的自定义组件之间传递数据？","Elyra 支持在运行时原生组件（如 KFP 组件到 KFP 组件）之间交换数据。用户可以将父节点的任何兼容输出选择为后续节点的输入。在配置参数时，需遵循特定的 JSON Schema 规范：'parameters' 部分必须包含 'id' 以及 'type' 或 'enum'；'uihints' 需符合相应 schema；而 'current_parameters' 较为灵活。如果在 UI 中看到类似 \"parent name: output name\" 的扁平化下拉选项，这是为了简化输入输出的选择过程。确保组件定义文件（component.yaml）正确注册，并在管道编辑器中正确连接输入输出端口。","https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fissues\u002F1761",{"id":168,"question_zh":169,"answer_zh":170,"source_url":171},20645,"在 JupyterHub 或 Open Data Hub 中启动 Elyra 时，为什么看不到运行时镜像（runtime-images）和运行时（runtimes）的输入参数？","此问题通常是由于使用的 Elyra 镜像版本过旧导致的。例如，s2i-lab-elyra:v0.0.6 版本存在扩展包版本不匹配的问题。解决方案是升级到 v0.0.7 或更高版本的镜像（可在 Quay.io 或 ODH manifest repository v1.0.9+ 中找到）。新版本已修复了前端扩展打包问题，用户无需手动安装 node 包。如果暂时无法升级，可以使用 Elyra CLI 命令手动添加运行时和运行时镜像作为临时变通方案。","https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fissues\u002F1473",{"id":173,"question_zh":174,"answer_zh":175,"source_url":176},20646,"在 Windows 上运行 Elyra 本地管道演示时出现 'subprocess.CalledProcessError' 或 'exit status 9009' 错误怎么办？","在 Windows 上运行本地管道时，常因系统找不到 'python3' 命令而报错（错误代码 9009）。这是因为 Windows 默认的命令通常是 'python' 而不是 'python3'。解决方法包括：1. 确保已安装 Python 并将其添加到系统 PATH 中；2. 尝试移除冲突的 python3.exe（如果存在）；3. 升级 Elyra 到 3.1.0 或更高版本，该版本专门改进了对 Windows 的支持，修复了相关的命令调用逻辑。升级后重新运行示例管道通常能解决问题。","https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fissues\u002F2073",{"id":178,"question_zh":179,"answer_zh":180,"source_url":181},20647,"在本地可以运行 Elyra 示例，但提交到 Kubeflow Pipeline 时报错，可能是什么原因？","这种情况通常与环境配置或凭证设置有关。虽然本地运行正常，但提交到 Kubeflow 时需要确保：1. 已正确安装并配置 Kubeflow 和 MinIO；2. Elyra 中的 Kubeflow 运行时配置（如 API 端点、凭证、命名空间）准确无误；3. 容器镜像能够访问所需的数据存储（如 MinIO bucket）。建议检查 Elyra 的运行时配置界面，确认所有连接测试通过。如果问题依旧，可以参考社区中类似的跟进问题（如 issue #1692）获取更具体的排查步骤，或查看服务器端的详细日志以定位具体失败环节。","https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fissues\u002F1198",{"id":183,"question_zh":184,"answer_zh":185,"source_url":166},20648,"Elyra 管道编辑器中如何定义组件的参数结构以支持数据交换？","为了支持组件间的数据交换，组件的参数定义必须符合 Elyra 的 JSON Schema 规范。具体来说，'parameters' 数组中的每个对象必须包含 'id' 字段，并且至少包含 'type' 或 'enum' 其中之一。例如，定义一个笔记本输入参数可能需要：{\"id\": \"elyra_notebook\", \"type\": \"string\"}。对于输出数据，可以使用类似的 ID（如 \"elyra_output_data\"），并在 'current_parameters' 中初始化空值。UI 提示（uihints）可用于控制参数在界面上的显示方式。确保这些定义与 pipeline-schemas 仓库中的 v3 版本 schema 保持一致，以避免验证错误。",[187,192,197,202,207,212,217,222,227,232,237,242,247,252,257,262,267,272,277],{"id":188,"version":189,"summary_zh":190,"released_at":191},126610,"v4.0.0","## 快速链接\n- [完整变更日志](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv4.0.0\u002Fgetting_started\u002Fchangelog.html)\n- [发布文档](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv4.0.0\u002F)\n- [安装文档](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv4.0.0\u002Fgetting_started\u002Finstallation.html)\n- [获取帮助](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv4.0.0\u002Fgetting_started\u002Fgetting-help.html)\n\n## 新特性亮点\n\n- 添加对 JupyterLab 4.x 的支持 - [#3201](https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3201)\n- 更新 JupyterLab 版本兼容性至 4.3.x - [#3293](https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3293)\n- 从 elyra-code-viewer 切换到 jupyterlab-code-viewer - [#3265](https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3265)\n- 将 jupyterlab-git 更新至 0.51.2 以修复漏洞 - [#3319](https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3319)\n- 启用运行时及其依赖项的条件式安装（例如：KFP、Airflow）- [#3248](https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3248)\n- 为通用流水线和通用组件添加 Airflow 2.x 支持 - [#3167](https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3167)\n- 添加对 Python 3.12 和 3.13 的支持 - [#3311](https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3311)\n- 移除对已停止维护的 Python 3.8 的支持 - [#3277](https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3277)\n- 多项依赖库更新，并包含安全修复\n\n**完整变更日志**: https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fcompare\u002Fv3.15.0...v4.0.0\n\n## 新贡献者\n* @harshad16 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3188 中做出了首次贡献\n* @savemuri 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3204 中做出了首次贡献\n* @paloma-rebuelta 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3202 中做出了首次贡献\n* @rkpattnaik780 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3197 中做出了首次贡献\n* @varunpatel07 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3213 中做出了首次贡献\n* @konono 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3226 中做出了首次贡献\n* @shalberd 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3240 中做出了首次贡献\n* @caponetto 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3257 中做出了首次贡献\n* @jiridanek 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3260 中做出了首次贡献\n* @frrivero 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3293 中做出了首次贡献\n\n**完整变更日志**: https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fcompare\u002Fv3.15.0...v4.0.0","2025-08-16T21:46:26",{"id":193,"version":194,"summary_zh":195,"released_at":196},126611,"v3.15.0","## 快速链接\n- [完整变更日志](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.15.0\u002Fgetting_started\u002Fchangelog.html)\n- [发布文档](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.15.0\u002F)\n- [安装文档](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.15.0\u002Fgetting_started\u002Finstallation.html)\n- [获取帮助](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.15.0\u002Fgetting_started\u002Fgetting-help.html)\n\n## 新特性亮点\n\n### 流水线编辑器：启用特定运行时\n\n默认情况下，Elyra 安装已预配置为支持在本地环境（通过 JupyterLab）和远程环境（Kubeflow Pipelines 和 Apache Airflow）中执行流水线。从本版本开始，您可以自定义 Elyra，仅显示您计划使用的运行时。\n\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F223213156-ad3f4c0e-3acd-4e6a-a016-caf3ba9c3898.png)\n\n有关详细信息，请参阅新的[_配置流水线编辑器_用户指南主题](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.15.0\u002Fuser_guide\u002Fpipeline-editor-configuration.html)。\n\n### Kubeflow Pipelines 流水线编辑器：支持令牌认证\n\n[Kubeflow Pipelines 运行时配置](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.15.0\u002Fuser_guide\u002Fruntime-conf.html)现在支持使用静态承载令牌进行认证。要利用此认证机制，请选择[`EXISTING_BEARER_TOKEN`并指定令牌值](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.15.0\u002Fuser_guide\u002Fruntime-conf.html#kubeflow-authentication-type-auth-type)。Elyra 会将指定的令牌原样传递给 Kubeflow Pipelines。\n\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F225053385-a5b3bc71-4506-4186-b888-63afe7846c45.png)\n \n\n## 变更内容\n### 新特性\n* 根据配置设置筛选可用运行时，由 @kevin-bates 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3114 中实现\n* 添加对 KFP 静态承载令牌认证的支持，由 @ptitzler 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3124 中实现\n### 错误修复\n* 修复测试工件输出位置的错误，由 @ptitzler 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3117 中修复\n* 隐藏 Binder 链接和引用，由 @ptitzler 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3119 中实现\n* 在笔记本执行之前确定使用哪个内核，由 @ptitzler 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3135 中实现\n### 其他\n* 为准备 Node.js 16 版本的生命周期结束，要求使用 Node.js 18 或更高版本，由 @ptitzler 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3118 中提出\n* 更新社区资源，由 @ptitzler 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3123 中完成\n* 降低 kfp-tekton 依赖的最低版本，由 @ptitzler 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3125 中实现\n\n\n**完整变更日志**：https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fcompare\u002Fv3.14.3...v3.15.0","2023-03-29T14:23:28",{"id":198,"version":199,"summary_zh":200,"released_at":201},126612,"v3.14.3","\u003C!-- 发布说明由 .github\u002Frelease.yml 中的配置在 v3.14.3 版本生成 -->\n\n## 变更内容\n### Bug 修复\n* @ptitzler 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3094 中更新了 Kubeflow 版本信息\n* @ptitzler 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3093 中修复了流水线参数的 KFP 代码生成问题\n* @cjackal 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3106 中跳过 `bootstrapper.py` 中不兼容版本字符串的版本检查\n\n### 其他\n* @akchinSTC 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3095 中更新 GitHub 工作流以使用 v3\u002Fv4 操作\n* @akchinSTC 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3097 中更新函数格式，使其符合 black v23 的代码风格检查\n* @ptitzler 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3098 中从 CI 测试中移除 Python 3.7\n* @ptitzler 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3101 中移除对 Python 3.7 的引用\n* @kevin-bates 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3103 中确保当 papermill 引擎未提供种子值时，env 段落为空字典\n* @ptitzler 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3112 中从文档中移除对 JupyterLab 1.x 和 2.x 的引用\n* @ptitzler 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3113 中将 kfp-tekton 升级至 1.6.2，以引入 kfp 1.8.19\n\n## 新贡献者\n* @cjackal 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3106 中完成了首次贡献\n\n**完整变更日志**: https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fcompare\u002Fv3.14.2...v3.14.3","2023-02-21T22:35:14",{"id":203,"version":204,"summary_zh":205,"released_at":206},126613,"v3.14.2","\u003C!-- 使用 .github\u002Frelease.yml 中的配置在 v3.14.2 版本生成的发布说明 -->\n\n## 变更内容\n### 新特性\n* 更新工厂镜像标签，使用 SHA256 哈希值，由 @akchinSTC 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3075 中实现。\n### Bug 修复\n* 修复处理程序中的 write_error 函数实现，由 @akchinSTC 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3080 中完成。\n* 修复负数参数的行为，由 @marthacryan 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3062 中完成。\n* 修复默认为零的整数参数处理问题，由 @marthacryan 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3090 中完成。\n### 其他\n* 在文档中添加参数博客文章的链接，由 @kiersten-stokes 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3064 中完成。\n* 移除与 KFP 相关软件包依赖中的大写字母，由 @kevin-bates 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3076 中完成。\n* 由于 CI 环境中设置不一致，禁用相关测试，由 @akchinSTC 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3073 中完成。\n* 降低 jupyter_core 的最低版本要求，并为 Python 3.7 设置 nbclient 的最高版本限制，由 @kevin-bates 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3071 中完成。\n* 更新软件包，包含所有可选依赖的子包，由 @akchinSTC 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3067 中完成。\n* 将数据文件重新打包到 elyra-server 发行版中，由 @akchinSTC 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3081 中完成。\n* 支持将 Podman 用作容器运行时，由 @akchinSTC 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3082 中完成。\n* 修复 oneOf 文件选择问题，由 @marthacryan 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3065 中完成。\n* 更新适用于 Linux 环境的发布脚本，由 @akchinSTC 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3086 中完成。\n\n\n**完整变更日志**: https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fcompare\u002Fv3.14.1...v3.14.2","2023-01-26T22:22:50",{"id":208,"version":209,"summary_zh":210,"released_at":211},126614,"v3.14.1","\u003C!-- 发布说明由 .github\u002Frelease.yml 中的配置在 v3.14.1 版本生成 -->\r\n\r\n## 变更内容\r\n### Bug 修复\r\n* 移除 jupyter-server-terminal 的限制，并由 @akchinSTC 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3057 中修复发布脚本。\r\n\r\n\r\n**完整变更日志**: https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fcompare\u002Fv3.14.0...v3.14.1","2022-12-14T22:53:32",{"id":213,"version":214,"summary_zh":215,"released_at":216},126615,"v3.14.0","## 快速链接\n- [完整变更日志](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.14.0\u002Fgetting_started\u002Fchangelog.html)\n- [发布文档](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.14.0\u002F)\n- [安装文档](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.14.0\u002Fgetting_started\u002Finstallation.html)\n- [获取帮助](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.14.0\u002Fgetting_started\u002Fgetting-help.html)\n\n## 新特性亮点\n\n### 流水线编辑器：为 Kubeflow 流水线配置流水线参数\n\n[流水线参数](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.14.0\u002Fuser_guide\u002Fpipelines.html#defining-pipeline-parameters) 允许在不修改流水线本身的情况下，自定义流水线的运行和导出。流水线参数是一种类型化的变量，可以应用于通用节点或自定义节点。Kubeflow 流水线编辑器新增了一个 `PIPELINE PARAMETERS` 选项卡，用户可以在其中定义流水线参数。\n\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F206323483-5cf627e2-de33-4c55-b435-a9565cba4098.png)\n\n要使某个参数值对通用节点可用，只需从“流水线参数”列表中选择该参数：\n\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F206324018-7be972cc-ee0c-4802-b154-73820423a2af.png)\n\nJupyter 笔记本和脚本可以通过环境变量访问所选参数及其关联值。\n\n要将参数值传递给自定义节点，需选择“参数”作为输入，并从列表中选取所需的参数：\n\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F206782028-d3d0e653-4efa-4178-8866-6acf0cc72fbb.png)\n\n请注意，对于自定义节点，参数列表仅包含类型兼容的参数。\n\n您可以在提交流水线或导出流水线时，在流水线编辑器中自定义参数值：\n\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F206781446-b06862c9-8898-4536-9e09-44f0a7ee23dd.png)\n\n此外，您还可以在 Kubeflow 中央仪表板的流水线界面中自定义参数值。\n\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F206325856-498530de-1cae-483a-a421-0b33b7e5133c.png)\n\n\n### 流水线编辑器：自定义 GPU 供应商（仅限 Kubeflow 流水线）\n\n对于通用组件，现在可以[指定自定义 GPU 供应商](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fuser_guide\u002Fpipelines.html#resources-cpu-gpu-and-ram)。请注意，必须在 Kubernetes 中安装相应的设备插件，否则节点执行将会失败。默认供应商仍为 `nvidia.com\u002Fgpu`。\n\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F206545309-7653cd22-fedd-48d6-8efc-ccfd03fea9c2.png)\n\n### 流水线编辑器：指定自定义流水线导出文件名\n\n现在，导出流水线时可以自定义文件名。使用自定义文件名有助于更轻松地保留同一流水线的多个版本。\n\n\u003Cimg width=\"391\" alt=\"Screenshot 2022-11-28 at 17 15 15\" src=\"https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F204414406-a0a2b5ff-01b","2022-12-14T21:09:38",{"id":218,"version":219,"summary_zh":220,"released_at":221},126616,"v3.13.0","## 快速链接\n- [完整变更日志](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.13.0\u002Fgetting_started\u002Fchangelog.html)\n- [发布文档](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.13.0\u002F)\n- [安装文档](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.13.0\u002Fgetting_started\u002Finstallation.html)\n- [获取帮助](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.13.0\u002Fgetting_started\u002Fgetting-help.html)\n\n## 新特性亮点\n\n### 流水线编辑器：自定义共享内存大小\n\n现在可以为单个节点或使用流水线默认设置的所有节点[自定义 Kubernetes 为执行流水线节点的 Pod 提供的共享内存量](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.13.0\u002Fuser_guide\u002Fpipelines.html#shared-memory-size)。\n\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F194907961-2cfc6a5a-0c81-478b-9f73-e448455f20d1.png)\n\n### 流水线编辑器：增强对卷挂载的支持\n\n[数据卷节点属性](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.13.0\u002Fuser_guide\u002Fpipelines.html#data-volumes)现在可以选择以只读模式挂载卷（防止意外覆盖），并且可以在指定的卷中挂载子路径。利用这些新的属性，可以对不应拥有对挂载数据卷无限制访问权限的节点实施更严格的访问控制。\n\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F195152918-9c39f1fd-d8ed-4862-bb08-a594d51fff5e.png)\n\n### 流水线编辑器：导出 Kubeflow Pipelines 的 Python DSL\n\n[Elyra 流水线编辑器和 `elyra-pipeline export` CLI 命令](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fuser_guide\u002Fpipelines.html#exporting-pipelines)现在除了已支持的 YAML 格式外，还可以导出 Kubeflow Pipelines 的 [Python DSL](https:\u002F\u002Fwww.kubeflow.org\u002Fdocs\u002Fcomponents\u002Fpipelines\u002Fv1\u002Fsdk\u002Fsdk-overview\u002F)。\n\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F200143763-24c1a9f5-f4f1-42ff-8467-e1a6cce4d290.png)\n\n## 变更内容\n### 新特性\n* 流水线编辑器：扩展数据卷节点属性，由 @ptitzler 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2961 中实现\n* 流水线编辑器：允许配置共享内存大小，由 @ptitzler 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2942 中实现\n* 文档说明如何刷新组件目录条目，由 @ptitzler 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2997 中实现\n* 重写 KFP 代码生成，由 @ptitzler 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2993 中实现\n### Bug 修复\n* 容忍名为“local”的运行时配置实例，由 @kevin-bates 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2968 中实现\n* 修复 `cos_object_prefix` 流水线属性的处理问题，由 @kiersten-stokes 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2972 中实现\n* 在后续尝试中跳过 DisableNodeCaching 实例转换，由 @kiersten-stokes 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2981 中实现\n* 修复节点缓存属性传播的 bug，由 @kiersten-stokes 在 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F3012 中实现\n### 其他\n* 添加“最新 Elyra 流水线回顾”","2022-11-14T19:45:15",{"id":223,"version":224,"summary_zh":225,"released_at":226},126617,"v3.12.0","此版本需要进行[流水线迁移](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.12.0\u002Fuser_guide\u002Fpipelines.html#migrating-pipelines)。\n\n## 快速链接\n- [完整变更日志](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.12.0\u002Fgetting_started\u002Fchangelog.html)\n- [发布文档](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.12.0\u002F)\n- [安装文档](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.12.0\u002Fgetting_started\u002Finstallation.html)\n- [获取帮助](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.12.0\u002Fgetting_started\u002Fgetting-help.html)\n\n## 新特性亮点\n\n### 流水线编辑器：为节点添加 Kubernetes 标签\n\n[Kubernetes 标签](https:\u002F\u002Fkubernetes.io\u002Fdocs\u002Fconcepts\u002Foverview\u002Fworking-with-objects\u002Flabels\u002F)现在可以作为流水线默认值定义，也可以分配给单个节点。具体请参阅 [Elyra 文档](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.12.0\u002Fuser_guide\u002Fpipelines.html#kubernetes-pod-labels)。\n\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F192849052-6667b073-6c7e-4bfe-945c-765f0062b1d5.png)\n\n使用标签为执行该节点的 Kubernetes Pod 分配标识性元数据。\n\n### 流水线编辑器：禁用节点缓存\n\n某些运行时环境支持节点输出缓存，从而减少重复执行节点的需求，这可以提升性能并降低资源消耗。对于 Kubeflow Pipelines 运行时，现在您可以为以非确定性方式生成输出的[自定义节点](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.12.0\u002Fuser_guide\u002Fpipeline-components.html#custom-components) [禁用节点缓存](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.12.0\u002Fuser_guide\u002Fpipelines.html#disable-node-caching)。您可以通过指定流水线默认值或针对单个节点来禁用所有节点的缓存。\n\n由于[Elyra 的限制](https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fissues\u002F2717)，[通用节点](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.12.0\u002Fuser_guide\u002Fpipeline-components.html#generic-components)目前始终不会被缓存。\n\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F191901329-0397ac47-f2da-4370-871e-2c892e15cf1a.png)\n\n### 流水线编辑器：更友好的属性输入\n\n[流水线默认属性](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.12.0\u002Fuser_guide\u002Fpipelines.html#default-node-properties)和[节点属性](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.12.0\u002Fuser_guide\u002Fpipelines.html#configuring-common-node-properties)现在可以使用自定义小部件进行配置：\n  ![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F191919273-d1067898-41bc-4965-82fd-97d7ecfa835b.png)\n\n有关小部件的说明，请参阅相关文档：\n- [禁用节点缓存](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.12.0\u002Fuser_guide\u002Fpipelines.html#disable-node-caching)\n- [环境变量](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.12.0\u002Fuser_guide\u002Fpipelines.html#environment-variables)\n- [数据卷挂载](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.12.0\u002Fuser_guide\u002Fpipelines.html#data-volumes)\n- [Kubernetes Pod 标签](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.12.0\u002Fuser_guide\u002Fpipelines.html#kubernetes-pod-labels)\n- [Kuber","2022-10-04T22:43:16",{"id":228,"version":229,"summary_zh":230,"released_at":231},126618,"v3.11.1","## 快速链接\n- [完整变更日志](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.11.1\u002Fgetting_started\u002Fchangelog.html)\n- [发布文档](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.11.1\u002F)\n- [安装文档](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.11.1\u002Fgetting_started\u002Finstallation.html)\n- [获取帮助](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.11.1\u002Fgetting_started\u002Fgetting-help.html)\n\n## 变更内容\n### 错误修复\n\n- 考虑画布如何处理图标大小 - https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2914\n- 更新通用节点以使用静态图标 API - https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2908\n- 在内核切换时启用调试器 - https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2903\n\n\u003C!-- 发行说明基于 .github\u002Frelease.yml 配置生成，版本为 v3.11.1 -->\n\n\n\n**完整变更日志**: https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fcompare\u002Fv3.11.0...v3.11.1","2022-09-01T21:55:17",{"id":233,"version":234,"summary_zh":235,"released_at":236},126619,"v3.11.0","## 快速链接\n- [完整变更日志](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.11.0\u002Fgetting_started\u002Fchangelog.html)\n- [发布文档](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.11.0\u002F)\n- [安装文档](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.11.0\u002Fgetting_started\u002Finstallation.html)\n- [获取帮助](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.11.0\u002Fgetting_started\u002Fgetting-help.html)\n\n## 新特性亮点\n\n### JupyterLab 启动器：了解 Elyra 的最新动态\n\nJupyterLab 启动器现在在 _Elyra_ 类别中新增了一个“新功能”磁贴，该磁贴会链接到您当前使用的版本的发布摘要，例如，对于 Elyra 3.11 版本，链接为 https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Freleases\u002Ftag\u002Fv3.11.0。发布摘要会突出显示新功能，并提供指向特定于该版本资源的链接。\n\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F187368482-6f84739e-674a-460b-99b2-0c9a15588495.png)\n\n\n### Python 代码编辑器：改进的调试器集成\n\n**此功能目前处于实验阶段。** [Elyra Python 编辑器](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.11.0\u002Fuser_guide\u002Fenhanced-script-support.html#python-script-execution-support) 已经得到扩展，使得使用 [JupyterLab 调试器](https:\u002F\u002Fjupyterlab.readthedocs.io\u002Fen\u002Flatest\u002Fuser\u002Fdebugger.html) 变得更加便捷。更多信息请参阅[用户指南](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.11.0\u002Fuser_guide\u002Fenhanced-script-support.html#python-script-debugging-support-experimental)。\n\n  ![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F184614413-5bd6bab0-3571-43a5-b15c-d9366260f6f5.png)\n\n### 新的 Scala 代码编辑器\n\n**此功能目前处于实验阶段。** Elyra 面向 JupyterLab 的编辑器系列现在新增了 [Scala 代码编辑器](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.11.0\u002Fuser_guide\u002Fenhanced-script-support.html#scala-script-execution-support-experimental)。该编辑器也可以作为独立扩展从 [PyPI](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.11.0\u002Fgetting_started\u002Finstallation.html#pip) 安装。\n\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F184099736-6a3dc7da-ea74-41f5-a8ae-18950585b6fb.png)\n\n请注意，Scala 文件不支持视觉化流水线编辑器。\n\n### 流水线编辑器：支持 Kubernetes 容忍度\n\n视觉化流水线编辑器现在允许可选地输入 [Kubernetes Pod 容忍度](https:\u002F\u002Fkubernetes.io\u002Fdocs\u002Fconcepts\u002Fscheduling-eviction\u002Ftaint-and-toleration\u002F)。容忍度可以定义为[适用于所有节点的流水线默认设置]以及针对单个节点的设置，并且同时支持 Kubeflow Pipelines 和 Apache Airflow。\n\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F183430312-8051e79c-db1b-4f5f-bcdb-3f02c8819d34.png)\n\n### 流水线编辑器：支持 Kubernetes Pod 注解\n\n视觉化流水线编辑器现在允许可选地输入 [Kubernetes [Pod] 注解](https:\u002F\u002Fkubernetes.io\u002Fdocs\u002Fconcepts\u002Foverview\u002Fworki","2022-08-23T17:15:42",{"id":238,"version":239,"summary_zh":240,"released_at":241},126620,"v3.10.1","## Quick links\r\n- [Complete changelog](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.10.1\u002Fgetting_started\u002Fchangelog.html)\r\n- [Release documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.10.1\u002F)\r\n- [Installation documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.10.1\u002Fgetting_started\u002Finstallation.html)\r\n- [Getting help](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.10.1\u002Fgetting_started\u002Fgetting-help.html)\r\n\r\n## What's Changed\r\n### Bug Fixes\r\n* Cap markdown to fix documentation builds by @kiersten-stokes in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2836\r\n### Other\r\n* Update typing extensions dependency version cap by @akchinSTC in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2831\r\n\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fcompare\u002Fv3.10.0...v3.10.1","2022-07-18T16:35:45",{"id":243,"version":244,"summary_zh":245,"released_at":246},126621,"v3.10.0","## Quick links\r\n- [Complete changelog](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.10.0\u002Fgetting_started\u002Fchangelog.html)\r\n- [Release documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.10.0\u002F)\r\n- [Installation documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.10.0\u002Fgetting_started\u002Finstallation.html)\r\n- [Getting help](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.10.0\u002Fgetting_started\u002Fgetting-help.html)\r\n\r\n## New feature highlights\r\n\r\n\r\n### Pipeline editor: mount shared volumes in custom pipeline nodes\r\n\r\nPipeline nodes that are implemented using [custom components ](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.10.0\u002Fuser_guide\u002Fpipeline-components.html#custom-components) or generic components can now be configured to utilize data volume mounts. Take advantage of volume mounts if two or more pipeline nodes need to efficiently share data. Data volume mounts can be [configured as pipeline defaults (applying to all generic and custom nodes) or for individual nodes](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.10.0\u002Fuser_guide\u002Fpipelines.html#defining-pipeline-properties). \r\nVolume mounts are only supported by the Kubeflow Pipelines and Apache Airflow runtimes.\r\n\r\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F177649287-5cc7783c-8360-45ec-adbe-bb038b126122.png)\r\n\r\n### URL and Airflow catalog connectors: support user credentials\r\n\r\nElyra uses [catalog connectors](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.10.0\u002Fuser_guide\u002Fpipeline-components.html#component-catalogs) to make [custom components](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.10.0\u002Fuser_guide\u002Fpipeline-components.html#custom-components) available to the Visual Pipeline Editor. The catalog connectors for the [URL component catalog](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.10.0\u002Fuser_guide\u002Fpipeline-components.html#url-component-catalog), the [Apache Airflow package catalog](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.10.0\u002Fuser_guide\u002Fpipeline-components.html#apache-airflow-package-catalog), and the [Apache Airflow provider package catalog](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.10.0\u002Fuser_guide\u002Fpipeline-components.html#apache-airflow-provider-package-catalog) were extended to allow for input of user credentials to support access to secured resources.\r\n\r\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F177649566-ef0c01f9-840b-434c-90c2-fd676afeda78.png)\r\n\r\n\r\n## What's Changed\r\n### New Features\r\n* Add authentication support to Airflow connectors by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2791\r\n* Add authentication support to URL catalog connector by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2804\r\n* Customize rendering of component catalog list by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2813\r\n* Support data exchange between custom & generic components via volumes by @kiersten-stokes in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2799\r\n### Bug Fixes\r\n* Fix for Script Editor console does not properly highlight error messages by @VNA818-RPI in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2800\r\n* Update docs to reflect proper generic op output file usage by @akchinSTC in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2798\r\n* Fix invalid repository URLs in 'Elyra in an air gapped environment' topic by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2810\r\n* Fix Airflow operation processing for number data types by @kiersten-stokes in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2815\r\n* Remove final instance of `BashOperator` from tests by @kiersten-stokes in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2817\r\n* Optionally search for operators in airflow.contrib.operators package by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2819\r\n* Fix version issue in release script by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2824\r\n### Other\r\n* Add errors to tag editor by @marthacryan in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2769\r\n* Add  elapsed time information to identify long running pytests by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2776\r\n* CI: fetch packages info if server tests fail by @tal66 in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2783\r\n* Install jupyterlab during normal builds by @ajbozarth in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2790\r\n* Add GitHub release notes instructions to developer guide by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2806\r\n* Update developer guide with CI test analysis information by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2807\r\n* Update prerequisite details in documentation  by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2809\r\n* [DEV-ONLY] Remove dependency on path location in pipeline tests by @kevin-bates in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2811\r\n\r\n## New Contributors\r\n* @tal66 made their first contribution in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2783\r\n* @VNA818-RPI made their first contribution in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2800\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fcompare\u002Fv3.9.1...v3.10.0","2022-07-07T22:40:12",{"id":248,"version":249,"summary_zh":250,"released_at":251},126622,"v3.9.1","## Quick links\r\n- [Complete changelog](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.9.1\u002Fgetting_started\u002Fchangelog.html)\r\n- [Release documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.9.1\u002F)\r\n- [Installation documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.9.1\u002Fgetting_started\u002Finstallation.html)\r\n- [Getting help](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.9.1\u002Fgetting_started\u002Fgetting-help.html)\r\n\r\n## What's Changed\r\n### Bug Fixes\r\n* Clear all singleton instances during shutdown by @kiersten-stokes in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2781\r\n### Other\r\n* Update master branch references to main by @akchinSTC in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2771\r\n* Do not persist the jupyter baseUrl in pipelines by @ajbozarth in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2775\r\n\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fcompare\u002Fv3.9.0...v3.9.1","2022-06-15T13:43:15",{"id":253,"version":254,"summary_zh":255,"released_at":256},126623,"v3.9.0","## Quick links\r\n- [Complete changelog](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.9.0\u002Fgetting_started\u002Fchangelog.html)\r\n- [Release documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.9.0\u002F)\r\n- [Installation documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.9.0\u002Fgetting_started\u002Finstallation.html)\r\n- [Getting help](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.9.0\u002Fgetting_started\u002Fgetting-help.html)\r\n\r\n## New feature highlights\r\n\r\n### Access sensitive information in generic pipeline nodes\r\n\r\nJupyter notebooks, Python scripts or R scripts might require access to resources that are protected using sensitive information, such as an API key or a user id and password. If you are running pipelines on Kubeflow Pipelines or Apache Airflow you can take advantage of [Kubernetes secrets](https:\u002F\u002Fkubernetes.io\u002Fdocs\u002Fconcepts\u002Fconfiguration\u002Fsecret\u002F) that are defined in your cluster. Starting with version 3.9 you can [configure pipelines to expose these secrets as environment variables](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.9.0\u002Fuser_guide\u002Fbest-practices-file-based-nodes.html#handling-sensitive-information), which notebooks or scripts can access. \r\n\r\n![Using secrets](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F170140291-fbcaf5f4-1658-49e6-ad4e-5f47372c41f9.gif)\r\n\r\n\r\n### Pipeline CLI: identify pipeline dependencies\r\n\r\nThe [`elyra-pipeline describe`](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.9.0\u002Fuser_guide\u002Fpipelines.html#describing-a-pipeline-from-the-command-line-interface) CLI command output now includes information about the following dependencies for nodes that utilize [generic components](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.9.0\u002Fuser_guide\u002Fpipeline-components.html#generic-components): container images, data volumes, and Kubernetes secrets. The machine readable output (produced when the `--json` option is specified) is most commonly used to automate processes, such as impact analysis and dependency checking. In the example below the output of the command is piped to the [`jq` command-line processor](https:\u002F\u002Fstedolan.github.io\u002Fjq\u002F), which extracts information about the container images that the pipeline's notebooks or script are executed in:\r\n\r\n```\r\n$ elyra-pipeline describe --json my.pipeline | jq '.dependencies.container_images[]'\r\n\"tensorflow\u002Ftensorflow:2.8.0\"\r\n```\r\n\r\nThis information could be used to identify pipelines that use a specific container image version or to verify that the container images are available in a specific container registry. \r\n\r\n### Create code snippets from notebook cells\r\n\r\nCreate a code snippet by [selecting one or more cells in a Jupyter notebook](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.9.0\u002Fuser_guide\u002Fcode-snippets.html#creating-a-code-snippet). \r\n\r\n![2022-05-23_15-19-29 (1)](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F169914420-9dbaed09-abc4-4350-a5ee-87110dbcfe3b.gif)\r\n\r\n\r\n### Documentation: Running Elyra in an air gapped environment\r\n\r\nThe new [documentation topic](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.9.0\u002Frecipes\u002Frunning-elyra-in-air-gapped-environment.html) covers considerations for running Elyra in an air gapped environment.\r\n\r\n\u003C!-- Release notes generated using configuration in .github\u002Frelease.yml at v3.9.0 -->\r\n\r\n## What's Changed\r\n### New Features\r\n* Add backend support for Kubernetes secrets environment variables by @kiersten-stokes in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2715\r\n* Elyra pipeline describe enhancements by @binayakdutta in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2722\r\n* Add 'Running Elyra in an air gapped environment' topic to documentation by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2744\r\n* Update 'elyra-pipeline describe' command by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2742\r\n* Create code snippet from whole cells (#1199) by @xlegs in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2726\r\n### Bug Fixes\r\n* Simplify R and Python icon svgs by @ajbozarth in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2705\r\n* Prepend baseUrl to icon source by @ajbozarth in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2728\r\n* Fix pipeline submit button reload bug by @karlaspuldaro in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2734\r\n* Fix metadata dropdown style in dark mode by @karlaspuldaro in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2743\r\n* Fix incorrect string replacement in release script by @akchinSTC in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2748\r\n* Fix save as code snippet by @marthacryan in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2756\r\n* Fix release script updates to schemas docs and package desc by @akchinSTC in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2752\r\n* Fix tag bug by @marthacryan in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2761\r\n* Fix metadata editor being able to open in multiple tabs by @marthacryan in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2762\r\n* Fix missing placeholder text in metadata editor by @marthacryan in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2764\r\n* Trim whitespace to prevent invalid tags in metadata editor by @marthacryan in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2768\r\n### Other\r\n* Add link to new ","2022-06-03T22:11:10",{"id":258,"version":259,"summary_zh":260,"released_at":261},126624,"v3.8.1","\u003C!-- Release notes generated using configuration in .github\u002Frelease.yml at v3.8.1 -->\r\n## Quick links\r\n- [Complete changelog](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.8.1\u002Fgetting_started\u002Fchangelog.html)\r\n- [Release documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.8.1\u002F)\r\n- [Installation documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.8.1\u002Fgetting_started\u002Finstallation.html)\r\n- [Getting help](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.8.1\u002Fgetting_started\u002Fgetting-help.html)\r\n\r\n## What's Changed\r\n### Other\r\n* Remove unreachable code  by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2695\r\n* Update to JupyterLab 3.4 by @ajbozarth in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2632\r\n* Fix incorrect regex search in release script by @akchinSTC in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2703\r\n\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fcompare\u002Fv3.8.0...v3.8.1","2022-05-25T14:52:31",{"id":263,"version":264,"summary_zh":265,"released_at":266},126625,"v3.8.0","## Quick links\r\n- [Complete changelog](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.8.0\u002Fgetting_started\u002Fchangelog.html)\r\n- [Release documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.8.0\u002F)\r\n- [Installation documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.8.0\u002Fgetting_started\u002Finstallation.html)\r\n- [Getting help](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.8.0\u002Fgetting_started\u002Fgetting-help.html)\r\n\r\n## New feature highlights\r\n\r\n### Pipeline editor: define pipeline defaults for runtime images and environment variables\r\n\r\nPipeline nodes that are implemented using [generic components ](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fuser_guide\u002Fpipeline-components.html#generic-components)(those being used to run Jupyter notebooks, Python scripts, or R scripts) are configured using properties. These properties define, for example, [the container image to be used to run as the execution environment](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fuser_guide\u002Fpipelines.html#creating-pipelines-using-the-visual-pipeline-editor). In previous releases it was required to explicitly associate each pipeline node with a container image.  Elyra 3.8+ allows for selection of [pipeline defaults](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fuser_guide\u002Fpipelines.html#defining-pipeline-properties) that are applied to all applicable nodes. These defaults can be optionally overridden for these nodes. Two such defaults are for the runtime image and environment variables, reducing the number of steps required to configure nodes.\r\n\r\n![2022-04-28_15-26-32 (1)](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F165858100-6f8c9be8-e85c-432f-b759-98f4683ac814.gif)\r\n\r\nTip: Hover over a node in the canvas to view a summary of its properties.\r\n\r\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F165967504-320ab91b-be88-476f-aaf4-8172bea8e3b0.png)\r\n\r\n\r\n\r\n### Pipeline editor: mount shared volumes in generic pipeline nodes\r\n\r\nPipeline nodes that are implemented using [generic components ](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fuser_guide\u002Fpipeline-components.html#generic-components) can now be configured to utilize data volume mounts. Take advantage of volume mounts if two or more pipeline nodes need to efficiently share data. Data volume mounts [be configured as pipeline defaults (applying to all generic nodes) or for individual nodes](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fuser_guide\u002Fpipelines.html#defining-pipeline-properties).  \r\n Volume mounts are only supported by the Kubeflow Pipelines and Apache Airflow runtimes.\r\n\r\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F165859752-1275c057-f119-44b8-8526-736df1f4c325.png)\r\n\r\n### Pipeline editor: organize generic pipeline inputs and outputs on object storage\r\n\r\nPipeline nodes that are implemented using [generic components ](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fuser_guide\u002Fpipeline-components.html#generic-components)(those being used to run Jupyter notebooks, Python scripts, or R scripts) utilize object storage buckets as storage for input artifacts, such as Jupyter notebooks or scripts, and output artifacts, like completed notebooks or data files. The new [object storage path prefix pipeline property](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fuser_guide\u002Fpipelines.html#defining-pipeline-properties) enables you to designate a custom location where those artifacts are stored.\r\n\r\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F165960714-bca288f6-2b8d-49c8-8846-b817ba863260.png)\r\n\r\n\r\n### Kubeflow Pipelines with Argo: support emissary workflow executor\r\n\r\nElyra now supports Kubeflow Pipelines installations that are configured to use the [emissary executor](\r\nhttps:\u002F\u002Fwww.kubeflow.org\u002Fdocs\u002Fcomponents\u002Fpipelines\u002Finstallation\u002Fchoose-executor\u002F#emissary-executor) as Argo workflow executor. There is no need to enable or configure anything in Elyra. Refer to the [updated requirements for custom pipeline components](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fuser_guide\u002Fbest-practices-custom-pipeline-components.html#requirements) for important information. \r\n\r\n### Kubeflow Pipelines runtime configurations: public API endpoint\r\n\r\nKubeflow Pipeline runtime configurations have been extended to allow for the optional configuration of a [public API endpoint](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fuser_guide\u002Fruntime-conf.html#public-kubeflow-pipelines-api-endpoint-public-api-endpoint). You should configure this endpoint if your [Kubeflow Pipelines authentication type](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flatest\u002Fuser_guide\u002Fruntime-conf.html#kubeflow-authentication-type-auth-type) is configured as `KUBERNETES_SERVICE_ACCOUNT_TOKEN`. If configured, Elyra uses this URL (instead of the API URL) to generate links that provide access to the [Kubeflow Central Dashboard](https:\u002F\u002Fwww.kubeflow.org\u002Fdocs\u002Fcomponents\u002Fcentral-dash\u002Foverview\u002F).\r\n\r\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F165858640-5d2c5134-7fea-462c-aaaf-1ac9a2b2687a.png)\r\n\r\n\r\n### Metadata CLI: import metadata \r\n\r\nThe [`elyra-metadata` CLI](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Flate","2022-05-03T14:24:02",{"id":268,"version":269,"summary_zh":270,"released_at":271},126626,"v3.7.0","## Quick links\r\n- [Complete changelog](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.7.0\u002Fgetting_started\u002Fchangelog.html)\r\n- [Release documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.7.0\u002F)\r\n- [Installation documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.7.0\u002Fgetting_started\u002Finstallation.html)\r\n- [Getting help](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.7.0\u002Fgetting_started\u002Fgetting-help.html)\r\n\r\n## New feature highlights\r\n\r\n### JupyterLab 3.3 (including settings editor)\r\n\r\nElyra v3.7 is the first release that takes advantage of [JupyterLab 3.3](https:\u002F\u002Fjupyterlab.readthedocs.io\u002Fen\u002Fstable\u002Fgetting_started\u002Fchangelog.html#v3-3). One of the highlights is the settings editor, which enables you to configure JupyterLab (and installed extensions). To customize the behavior of the Visual Pipeline Editor, click the `settings` link on the canvas or choose 'Settings'  > 'Advanced Settings Editor' from the main menu.\r\n\r\n   ![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F157985314-f49eaa3d-e58d-4523-906f-e02b6820aca3.png)\r\n\r\nSearch for `elyra` to see the complete list of customization options. There's only one in version 3.7, defining what happens when you double click on a pipeline node.\r\n\r\n   ![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F157985733-e4f2eac0-2651-4983-a776-ad3888a7f37e.png)\r\n\r\n### Pipeline editor: view component definitions\r\n\r\nThe pipeline editor now allows for viewing of [custom component definitions](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.7.0\u002Fuser_guide\u002Fpipeline-components.html). Select a node that utilizes a custom component, open the context menu, and select 'Open Component Definition':\r\n\r\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F160431184-dcde1b2e-ebb5-4cfb-8690-0cebb231ba1a.png)\r\n\r\nThe component's source (YAML for Kubeflow Pipelines components, Python source code for Apache Airflow operators) is rendered using the new generic `elyra-code-viewer-extension` extension.\r\n\r\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F160431307-1d2c4041-188c-4987-87f2-b9e1841b3f27.png)\r\n\r\nNote: editing of custom component definitions is not supported.\r\n\r\n### Pipeline editor: refresh the component palette on demand\r\n\r\nThe pipeline editor's palette displays components that are stored in local or remote [component catalogs](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.7.0\u002Fuser_guide\u002Fpipeline-components.html#component-catalogs).  Since the content of these catalogs can change at any time, Elyra now includes refresh buttons to allow for complete palette reload (1) or partial palette reload (2) in the ['Component Catalogs' panel](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.7.0\u002Fuser_guide\u002Fpipeline-components.html#managing-custom-components-using-the-jupyterlab-ui). \r\n\r\n![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F160447962-a7dc1863-34ab-424b-bbfc-e03c32f0951b.png)\r\n\r\n\r\n### Metadata CLI: `export` runtimes, runtime images, code snippets, and component catalogs\r\n\r\nElyra stores information about runtimes, runtime images, code snippets, and component catalogs in metadata files. You can export this metadata (e.g. to create a backup) to a local directory using the new `export` command of the `elyra-metadata` CLI. To learn more, run `elyra-metadata export -h` or [take a look at this example](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.7.0\u002Fuser_guide\u002Fruntime-conf.html#exporting-runtime-configurations). \r\n\r\nSupport for metadata import will be added in a future release. (https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fissues\u002F2500)\r\n\r\n### Metadata CLI: `install` command replaced by `create` and `update`\r\n\r\nThe `elyra-metadata` CLI supports two new commands, `elyra-metadata create` (to add a new runtime, code snippet, runtime image, etc) and `elyra-metadata update` (to update an existing runtime, code snippet, runtime image, etc). These commands replace the `elyra-metadata install` command.\r\nIf you are currently using the legacy command in your automation scripts or custom `Dockerfile`s, please migrate by replacing `elyra-metadata install` with `elyra-metadata create` and `elyra-metadata install --replace` with `elyra-metadata update`. The command parameters have not changed. To learn more about the two new commands, run `elyra-metadata create --help` or `elyra-metadata update --help`, respectively.\r\n\r\n**Breaking change in Elyra 4.0:** The `elyra-metadata install` command is no longer supported. (https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fissues\u002F2580)\r\n\r\n### Pipeline CLI: `export` pipelines to runtime-specific format\r\n\r\nElyra uses a proprietary JSON format to store pipeline files, which cannot be used to natively run pipelines on Kubeflow Pipelines or Apache Airflow. Prior to version 3.7 only the pipeline editor supported exporting Elyra pipelines files to Kubeflow Pipelines and Apache Airflow  native formats. The new `elyra-pipeline export` command extends this capability to the CLI. To learn more, run `elyra-pipeline export --help` or [take a look at this example](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.7.0\u002Fuser_guide\u002Fpipelines.html#exporting-","2022-03-31T14:10:08",{"id":273,"version":274,"summary_zh":275,"released_at":276},126627,"v3.6.0","- [Complete changelog](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.6.0\u002Fgetting_started\u002Fchangelog.html)\r\n- [Release documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.6.0\u002F)\r\n\r\n## New feature highlights\r\n\r\n### Duplicate runtime configurations, runtime images, code snippets, and more\r\n\r\nQuickly duplicate existing runtime configurations, runtime images, code snippets, and component catalogs with a single click in the JupyterLab GUI:\r\n\r\n![Duplicate metadata instances in the GUI](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F153243171-3805b93f-9d21-459d-bf41-b237ed5dd5ac.gif)\r\n\r\n### Add Airflow operators from Airflow built distributions  to the pipeline editor\r\n\r\nOut of the box the visual pipeline editor for Apache Airflow pipelines only includes operators that allow for the execution of Jupyter notebooks, Python scripts, and R scripts. Starting with this release of Elyra you can add operators from your Apache Airflow built distribution to the palette:\r\n - Create a catalog connector for Apache Airflow.\r\n - Configure the connector to use the download link for the Apache Airflow built distribution that you have installed in your Airflow cluster.\r\n - Open the pipeline editor and start using the imported operators.\r\n\r\n![Add Apache Airflow built-in operators to the pipeline editor palette](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F153254274-26889b47-99ca-474e-a25a-ccfa5bb494f2.gif)\r\n\r\nResources:\r\n  - [Airflow catalog connector documentation](https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Ftree\u002Fmaster\u002Felyra\u002Fpipeline\u002Fairflow\u002Fpackage_catalog_connector)\r\n\r\n### Add Airflow operators from Airflow provider packages  to the pipeline editor\r\n\r\nStarting with this release of Elyra you can add operators from [provider packages](https:\u002F\u002Fairflow.apache.org\u002Fdocs\u002Fapache-airflow-providers\u002F) to the palette:\r\n - Create a provider package catalog connector for Apache Airflow.\r\n - Configure the connector to use the download link for the Apache Airflow provider package that you have installed in your Airflow cluster.\r\n - Open the pipeline editor and start using the imported operators.\r\n\r\n![Add Apache Airflow provider package operators to the pipeline editor palette](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F153259907-1139278f-07d4-498b-9199-b5cd54225489.gif)\r\n\r\nResources:\r\n  - [Airflow provider package catalog connector documentation](https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Ftree\u002Fmaster\u002Felyra\u002Fpipeline\u002Fairflow\u002Fprovider_package_catalog_connector)\r\n\r\n## What's Changed\r\n* Bump nanoid from 3.1.22 to 3.2.0 by @dependabot in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2411\r\n* Bump ipython from 7.15.0 to 7.16.3 in \u002Fetc\u002Fgeneric by @dependabot in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2408\r\n* Fix typo in RTC documentation topic by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2412\r\n* Fix git branch URL by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2421\r\n* Bump node-fetch from 2.6.1 to 2.6.7 by @dependabot in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2434\r\n* Revert removal of dependency caps by @akchinSTC in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2445\r\n* Restore dependency cap on click and pin black by @akchinSTC in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2446\r\n* Validate numeric fields in submit file dialog by @karlaspuldaro in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2383\r\n* Add GUI support for metadata instance duplication by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2436\r\n* Set 'EnumControl' property values to 'null' in properties JSON  by @kiersten-stokes in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2432\r\n* Add link to Apache Airflow custom components tutorial to 'Getting Started' guide by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2450\r\n* Improve Airflow parser functionality by @kiersten-stokes in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2418\r\n* Add airflow package catalog connector by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2437\r\n* Add test for code snippet cloning by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2451\r\n* Move unit test file to proper test directory by @karlaspuldaro in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2452\r\n* Update pipeline editor node pkg to 1.6.0 by @akchinSTC in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2454\r\n* Add Airflow provider package catalog connector by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2438\r\n* Update built-in connector reference in 'Pipeline Components' documentation by @ptitzler in https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fpull\u002F2457\r\n\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Felyra-ai\u002Felyra\u002Fcompare\u002Fv3.5.0...v3.6.0","2022-02-09T22:40:31",{"id":278,"version":279,"summary_zh":280,"released_at":281},126628,"v3.5.3","- [Changelog](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.5.3\u002Fgetting_started\u002Fchangelog.html)\r\n- [Release documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.5.3\u002F)\r\n\r\n## New feature highlights\r\n\r\n### Support GitLab as DAG repository for Apache Airflow\r\n\r\nElyra now supports GitLab as DAG repository for Apache Airflow runtime configuration. This new feature is only enabled if the [optional gitlab dependency is installed](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.5.3\u002Fgetting_started\u002Finstallation.html#packaging). \r\n\r\n![Configure GitLab as DAG repository](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F153452786-c0e0e0cf-02bf-41f1-bbbd-24462773a15c.gif)\r\n\r\nResources:\r\n - [Runtime configuration documentation](https:\u002F\u002Felyra.readthedocs.io\u002Fen\u002Fv3.5.3\u002Fuser_guide\u002Fruntime-conf.html#git-type-git-type)\r\n\r\n### Attach pipeline node comments to generated pipelines\r\n\r\nComment nodes provide you with the ability to add embedded documentation to pipelines. Starting with this release these comments are passed through to the target runtime environment. \r\n\r\n#### Kubeflow Pipelines\r\n\r\nFor Kubeflow Pipelines node comments are attached to the Kubernetes pods as `elyra\u002Fnode-user-doc` annotations:\r\n\r\n![Pipeline node comments are embedded in the generated](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F153472842-a39c61d7-9771-44d4-8335-a2c34580d80a.png)\r\n\r\n\r\n![Pipeline descriptions are rendered in the Airflow GUI](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F153472299-bba56c2a-bf22-4c06-a46d-26df08f94b06.png)\r\n\r\nTip: If your pipeline includes a description, it is rendered in the Kubeflow Pipelines Dashboard when you open the pipeline:\r\n\r\n![Pipeline descriptions are rendered in the Kubeflow Pipelines GUI](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F153470656-a43c019c-865e-4090-8210-7154ea271fb4.png)\r\n\r\n#### Apache Airflow\r\nFor Apache Airflow node comments are attached to the task instance and can be accessed in the task details view:\r\n\r\n![Pipeline node comments are embedded in the generated DAG](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F153464749-8615084d-3bd8-4b0c-ab3e-793508a5ee4b.gif)\r\n\r\nTip: If your pipeline includes a description, it is rendered in the Apache Airflow GUI when you open the DAG:\r\n\r\n![Pipeline descriptions are rendered in the Airflow GUI](https:\u002F\u002Fuser-images.githubusercontent.com\u002F13068832\u002F153467192-6f10b8d7-6e43-4062-bfdc-0e6cd3e827d5.png)\r\n\r\n","2022-02-14T17:16:10"]