[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tool-xorbitsai--xorbits":3,"similar-xorbitsai--xorbits":217},{"id":4,"github_repo":5,"name":6,"description_en":7,"description_zh":8,"ai_summary_zh":8,"readme_en":9,"readme_zh":10,"quickstart_zh":11,"use_case_zh":12,"hero_image_url":13,"owner_login":14,"owner_name":15,"owner_avatar_url":16,"owner_bio":17,"owner_company":18,"owner_location":18,"owner_email":18,"owner_twitter":19,"owner_website":20,"owner_url":21,"languages":22,"stars":53,"forks":54,"last_commit_at":55,"license":56,"difficulty_score":57,"env_os":58,"env_gpu":59,"env_ram":58,"env_deps":60,"category_tags":67,"github_topics":71,"view_count":81,"oss_zip_url":18,"oss_zip_packed_at":18,"status":82,"created_at":83,"updated_at":84,"faqs":85,"releases":116},867,"xorbitsai\u002Fxorbits","xorbits","Scalable Python DS & ML, in an API compatible & lightning fast way.","Xorbits 是一款专为数据科学和机器学习设计的开源计算框架，致力于解决 Python 生态中数据处理与模型训练难以扩展的痛点。当数据集超出单机内存限制，或需要更高算力时，传统的 pandas 等库往往力不从心。Xorbits 允许用户在不改变现有代码逻辑的前提下，轻松将工作流从个人笔记本扩展到数千台机器的集群。\n\n它特别适合数据科学家、机器学习工程师以及使用 Python 进行数据分析的开发者。Xorbits 的核心优势在于其高度兼容的 API，支持 pandas、NumPy、PyTorch 和 XGBoost 等主流库。用户仅需修改一行代码，即可利用多核 CPU 或 GPU 加速计算，显著提升处理效率。无论是预处理、调参还是模型服务，Xorbits 都能提供无缝的弹性伸缩能力，让团队无需深入钻研底层基础设施，就能高效应对海量数据挑战。","\u003Cdiv align=\"center\">\n  \u003Cimg width=\"77%\" alt=\"\" src=\"https:\u002F\u002Fxorbits.readthedocs.io\u002Fen\u002Flatest\u002F_static\u002Fxorbits.svg\">\u003Cbr>\n\u003C\u002Fdiv>\n\n[![PyPI Latest Release](https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fv\u002Fxorbits.svg?style=for-the-badge)](https:\u002F\u002Fpypi.org\u002Fproject\u002Fxorbits\u002F)\n[![License](https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fl\u002Fxorbits.svg?style=for-the-badge)](https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fblob\u002Fmain\u002FLICENSE)\n[![Coverage](https:\u002F\u002Fimg.shields.io\u002Fcodecov\u002Fc\u002Fgithub\u002Fxorbitsai\u002Fxorbits?style=for-the-badge)](https:\u002F\u002Fcodecov.io\u002Fgh\u002Fxorbitsai\u002Fxorbits)\n[![Build Status](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Factions\u002Fworkflow\u002Fstatus\u002Fxorbitsai\u002Fxorbits\u002Fpython.yaml?branch=main&style=for-the-badge&label=GITHUB%20ACTIONS&logo=github)](https:\u002F\u002Factions-badge.atrox.dev\u002Fxorbitsai\u002Fxorbits\u002Fgoto?ref=main)\n[![Doc](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fxorbitsai_xorbits_readme_51d302063c11.png)](https:\u002F\u002Fxorbits.readthedocs.io\u002F)\n[![Slack](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fjoin_Slack-781FF5.svg?logo=slack&style=for-the-badge)](https:\u002F\u002Fjoin.slack.com\u002Ft\u002Fxorbitsio\u002Fshared_invite\u002Fzt-1o3z9ucdh-RbfhbPVpx7prOVdM1CAuxg)\n[![Twitter](https:\u002F\u002Fimg.shields.io\u002Ftwitter\u002Ffollow\u002Fxorbitsio?logo=twitter&style=for-the-badge)](https:\u002F\u002Ftwitter.com\u002Fxorbitsio)\n\n## What is Xorbits?\n\nXorbits is an open-source computing framework that makes it easy to scale data science and machine learning workloads —\nfrom data preprocessing to tuning, training, and model serving. Xorbits can leverage multi-cores or GPUs to accelerate\ncomputation on a single machine or scale out up to thousands of machines to support processing terabytes of data and training or serving large models.\n\nXorbits provides a suite of best-in-class [libraries](https:\u002F\u002Fxorbits.readthedocs.io\u002Fen\u002Flatest\u002Flibraries\u002Findex.html) for data\nscientists and machine learning practitioners. Xorbits provides the capability to scale tasks without the necessity for\nextensive knowledge of infrastructure.\n\nXorbits features a familiar Python API that supports a variety of libraries, including pandas, NumPy, PyTorch,\nXGBoost, etc. With a simple modification of just one line of code, your pandas workflow can be seamlessly scaled\nusing Xorbits:\n\n\u003Cdiv align=\"center\">\n  \u003Cimg width=\"70%\" alt=\"\" src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fxorbitsai_xorbits_readme_a85ff8fab545.gif\">\u003Cbr>\n\u003C\u002Fdiv>\n\n## Why Xorbits?\n\nAs ML and AI workloads continue to grow in complexity, the computational demands soar high. Even though single-node development\nenvironments like your laptop provide convenience, but they fall short when it comes to accommodating these scaling demands. \n\n### Seamlessly scale your workflow from laptop to cluster\n\nTo use Xorbits, you do not need to specify how to distribute the data or even know how many cores your system has.\nYou can keep using your existing notebooks and still enjoy a significant speed boost from Xorbits, even on your laptop.\n\n### Process large datasets that pandas can't\n\nXorbits can [leverage all of your computational cores](https:\u002F\u002Fxorbits.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Fwhy_xorbits\u002Fpandas.html#boosting-performance-and-scalability-with-xorbits). \nIt is especially beneficial for handling [larger datasets](https:\u002F\u002Fxorbits.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Fwhy_xorbits\u002Fpandas.html#overcoming-memory-limitations-in-large-datasets-with-xorbits),\nwhere pandas may slow down or run out of memory.\n\n### Lightning-fast speed\n\nAccording to our benchmark tests, Xorbits surpasses other popular pandas API frameworks in speed and scalability. \nSee our [performance comparison](https:\u002F\u002Fxorbits.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Fwhy_xorbits\u002Fcomparisons.html#performance-comparison)\n, [explanation](https:\u002F\u002Fxorbits.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Fwhy_xorbits\u002Ffast.html) and [research paper](https:\u002F\u002Farxiv.org\u002Fabs\u002F2401.00865).\n\n### Leverage the Python ecosystem with native integrations\n\nXorbits aims to take full advantage of the entire ML ecosystem, offering native integration with pandas and other libraries.\n\n## Where to get it?\nThe source code is currently hosted on GitHub at: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\n\nBinary installers for the latest released version are available at the [Python\nPackage Index (PyPI)](https:\u002F\u002Fpypi.org\u002Fproject\u002Fxorbits).\n\n```shell\n# PyPI\npip install xorbits\n```\n\n## Other resources\n* [Documentation](https:\u002F\u002Fxorbits.readthedocs.io)\n* [Performance Benchmarks](https:\u002F\u002Fxorbits.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Fwhy_xorbits\u002Fcomparisons.html#performance-comparison)\n* [Development Guide](https:\u002F\u002Fxorbits.readthedocs.io\u002Fen\u002Flatest\u002Fdevelopment\u002Findex.html)\n* [Research Paper on Xorbits' Internals](https:\u002F\u002Farxiv.org\u002Fabs\u002F2401.00865)\n\n## License\n[Apache 2](LICENSE)\n\n## Roadmaps\nThe main goals we want to achieve in the future include the following:\n\n* Transitioning from pandas native to arrow native for data storage  \n  will reduce the memory cost substantially and is more friendly for compute engine.\n* Introducing native engines that leverage technologies like vectorization and codegen \n  to accelerate computations.\n* Scale as many libraries and algorithms as possible!\n\nMore detailed roadmaps will be revealed soon. Stay tuned!\n\n## Relationship with Mars\nThe creators of Xorbits are mainly those of Mars, and we currently built Xorbits on Mars \nto reduce duplicated work, but the vision of Xorbits suggests that it's not \nappropriate to put everything on Mars. Instead, we need a new project \nto support the roadmaps better. In the future, we will replace some core internal components \nwith other upcoming ones we will propose. Stay tuned!\n\n## Getting involved\n\n| Platform                                                                                      | Purpose                                            |\n|-----------------------------------------------------------------------------------------------|----------------------------------------------------|\n| [Github Issues](https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fissues)                                  | Reporting bugs and filing feature requests.        |\n| [StackOverflow](https:\u002F\u002Fstackoverflow.com\u002Fquestions\u002Ftagged\u002Fxorbits)                           | Asking questions about how to use Xorbits.         |\n| [Slack](https:\u002F\u002Fjoin.slack.com\u002Ft\u002Fxorbitsio\u002Fshared_invite\u002Fzt-1o3z9ucdh-RbfhbPVpx7prOVdM1CAuxg) | Collaborating with other Xorbits users.            |\n\n## Citing Xorbits\n\nIf Xorbits could help you, please cite our paper using the following metadata:\n\n```\n@inproceedings{lu2024Xorbits,\n  title = {Xorbits: Automating Operator Tiling for Distributed Data Science},\n  shorttitle = {Xorbits},\n  booktitle = {2024 {{IEEE}} 40th {{International Conference}} on {{Data Engineering}} ({{ICDE}})},\n  author = {Lu, Weizheng and He, Kaisheng and Qin, Xuye and Li, Chengjie and Wang, Zhong and Yuan, Tao and Liao, Xia and Zhang, Feng and Chen, Yueguo and Du, Xiaoyong},\n  year = {2024},\n  month = may,\n  pages = {5211--5223},\n  issn = {2375-026X},\n  doi = {10.1109\u002FICDE60146.2024.00392},\n}\n```","\u003Cdiv align=\"center\">\n  \u003Cimg width=\"77%\" alt=\"\" src=\"https:\u002F\u002Fxorbits.readthedocs.io\u002Fen\u002Flatest\u002F_static\u002Fxorbits.svg\">\u003Cbr>\n\u003C\u002Fdiv>\n\n[![PyPI Latest Release](https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fv\u002Fxorbits.svg?style=for-the-badge)](https:\u002F\u002Fpypi.org\u002Fproject\u002Fxorbits\u002F)\n[![License](https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fl\u002Fxorbits.svg?style=for-the-badge)](https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fblob\u002Fmain\u002FLICENSE)\n[![Coverage](https:\u002F\u002Fimg.shields.io\u002Fcodecov\u002Fc\u002Fgithub\u002Fxorbitsai\u002Fxorbits?style=for-the-badge)](https:\u002F\u002Fcodecov.io\u002Fgh\u002Fxorbitsai\u002Fxorbits)\n[![Build Status](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Factions\u002Fworkflow\u002Fstatus\u002Fxorbitsai\u002Fxorbits\u002Fpython.yaml?branch=main&style=for-the-badge&label=GITHUB%20ACTIONS&logo=github)](https:\u002F\u002Factions-badge.atrox.dev\u002Fxorbitsai\u002Fxorbits\u002Fgoto?ref=main)\n[![Doc](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fxorbitsai_xorbits_readme_51d302063c11.png)](https:\u002F\u002Fxorbits.readthedocs.io\u002F)\n[![Slack](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fjoin_Slack-781FF5.svg?logo=slack&style=for-the-badge)](https:\u002F\u002Fjoin.slack.com\u002Ft\u002Fxorbitsio\u002Fshared_invite\u002Fzt-1o3z9ucdh-RbfhbPVpx7prOVdM1CAuxg)\n[![Twitter](https:\u002F\u002Fimg.shields.io\u002Ftwitter\u002Ffollow\u002Fxorbitsio?logo=twitter&style=for-the-badge)](https:\u002F\u002Ftwitter.com\u002Fxorbitsio)\n\n## Xorbits 是什么？\n\nXorbits 是一个开源计算框架，旨在轻松扩展数据科学和机器学习工作负载（Workloads）——\n从数据预处理到调优、训练和模型服务。Xorbits 可以利用多核或 GPU（图形处理器）来加速\n单机上的计算，或者扩展到数千台机器以支持处理 TB 级数据以及训练或服务大型模型。\n\nXorbits 为数据科学家和机器学习从业者提供了一套一流的 [库（Libraries）](https:\u002F\u002Fxorbits.readthedocs.io\u002Fen\u002Flatest\u002Flibraries\u002Findex.html)。Xorbits 提供了扩展任务的能力，而无需\n深入了解基础设施（Infrastructure）。\n\nXorbits 具有熟悉的 Python API（应用程序接口），支持多种库，包括 pandas、NumPy、PyTorch、\nXGBoost 等。只需简单修改一行代码，您的 pandas 工作流就可以使用 Xorbits 无缝扩展：\n\n\u003Cdiv align=\"center\">\n  \u003Cimg width=\"70%\" alt=\"\" src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fxorbitsai_xorbits_readme_a85ff8fab545.gif\">\u003Cbr>\n\u003C\u002Fdiv>\n\n## 为什么选择 Xorbits？\n\n随着 ML（机器学习）和 AI（人工智能）工作负载的复杂性不断增加，计算需求急剧上升。尽管像您的笔记本电脑这样的单节点（Single-Node）开发环境\n提供了便利，但在满足这些扩展需求方面却显得力不从心。 \n\n### 将工作流从笔记本电脑无缝扩展到集群（Cluster）\n\n要使用 Xorbits，您不需要指定如何分发数据，甚至不需要知道系统有多少个核心。\n您可以继续使用现有的 Notebooks（笔记本），即使是在笔记本电脑上，也能享受 Xorbits 带来的显著速度提升。\n\n### 处理 pandas 无法处理的大型数据集\n\nXorbits 可以 [利用您所有的计算核心](https:\u002F\u002Fxorbits.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Fwhy_xorbits\u002Fpandas.html#boosting-performance-and-scalability-with-xorbits)。 \n这对于处理 [更大的数据集](https:\u002F\u002Fxorbits.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Fwhy_xorbits\u002Fpandas.html#overcoming-memory-limitations-in-large-datasets-with-xorbits) 尤其有益，\n在这些情况下，pandas 可能会变慢或耗尽内存。\n\n### 闪电般的速度\n\n根据我们的基准测试（Benchmark Tests），Xorbits 在速度和可扩展性方面超越了其他流行的 pandas API 框架。 \n查看我们的 [性能对比](https:\u002F\u002Fxorbits.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Fwhy_xorbits\u002Fcomparisons.html#performance-comparison)\n，[解释](https:\u002F\u002Fxorbits.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Fwhy_xorbits\u002Ffast.html) 和 [研究论文](https:\u002F\u002Farxiv.org\u002Fabs\u002F2401.00865)。\n\n### 通过原生集成利用 Python 生态系统（Ecosystem）\n\nXorbits 旨在充分利用整个 ML 生态系统，提供与 pandas 和其他库的原生集成。\n\n## 哪里获取？\n源代码当前托管在 GitHub 上：https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\n\n最新版本的二进制安装程序可在 [Python\n包索引（PyPI）](https:\u002F\u002Fpypi.org\u002Fproject\u002Fxorbits) 获取。\n\n```shell\n# PyPI\npip install xorbits\n```\n\n## 其他资源\n* [文档](https:\u002F\u002Fxorbits.readthedocs.io)\n* [性能基准测试](https:\u002F\u002Fxorbits.readthedocs.io\u002Fen\u002Flatest\u002Fgetting_started\u002Fwhy_xorbits\u002Fcomparisons.html#performance-comparison)\n* [开发指南](https:\u002F\u002Fxorbits.readthedocs.io\u002Fen\u002Flatest\u002Fdevelopment\u002Findex.html)\n* [关于 Xorbits 内部机制的研究论文](https:\u002F\u002Farxiv.org\u002Fabs\u002F2401.00865)\n\n## 许可证\n[Apache 2](LICENSE)\n\n## 路线图（Roadmaps）\n我们未来希望实现的主要目标包括以下内容：\n\n* 从 pandas 原生过渡到 Arrow 原生进行数据存储  \n  这将大幅降低内存成本，并且对计算引擎（Compute Engine）更友好。\n* 引入利用向量化（Vectorization）和代码生成（Codegen）等技术来加速计算的原生引擎。\n* 尽可能多地扩展库和算法！\n\n更详细的路线图将很快公布。敬请期待！\n\n## 与 Mars 的关系\nXorbits 的创建者主要是 Mars 的创建者，我们目前基于 Mars 构建 Xorbits \n以减少重复工作，但 Xorbits 的愿景表明将所有内容放在 Mars 上并不\n合适。相反，我们需要一个新项目 \n来更好地支持路线图。在未来，我们将用我们即将提出的其他组件替换一些核心内部组件。\n敬请期待！\n\n## 参与进来\n\n| 平台                                                                                      | 目的                                            |\n|-----------------------------------------------------------------------------------------------|----------------------------------------------------|\n| [Github Issues](https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fissues)                                  | 报告错误和提交功能请求。        |\n| [StackOverflow](https:\u002F\u002Fstackoverflow.com\u002Fquestions\u002Ftagged\u002Fxorbits)                           | 询问如何使用 Xorbits 的问题。         |\n| [Slack](https:\u002F\u002Fjoin.slack.com\u002Ft\u002Fxorbitsio\u002Fshared_invite\u002Fzt-1o3z9ucdh-RbfhbPVpx7prOVdM1CAuxg) | 与其他 Xorbits 用户协作。            |\n\n## 引用 Xorbits\n\n如果 Xorbits 对您有帮助，请使用以下元数据引用我们的论文：\n\n```\n@inproceedings{lu2024Xorbits,\n  title = {Xorbits: Automating Operator Tiling for Distributed Data Science},\n  shorttitle = {Xorbits},\n  booktitle = {2024 {{IEEE}} 40th {{International Conference}} on {{Data Engineering}} ({{ICDE}})},\n  author = {Lu, Weizheng and He, Kaisheng and Qin, Xuye and Li, Chengjie and Wang, Zhong and Yuan, Tao and Liao, Xia and Zhang, Feng and Chen, Yueguo and Du, Xiaoyong},\n  year = {2024},\n  month = may,\n  pages = {5211--5223},\n  issn = {2375-026X},\n  doi = {10.1109\u002FICDE60146.2024.00392},\n}\n```","# Xorbits 快速上手指南\n\n## 环境准备\n*   **系统要求**：支持 Linux、macOS 及 Windows 系统\n*   **前置依赖**：已安装 Python 环境及 pip 包管理工具\n\n## 安装步骤\n推荐使用 pip 从 PyPI 安装最新版本的 Xorbits：\n\n```shell\npip install xorbits\n```\n\n## 基本使用\nXorbits 提供了与原生 pandas 高度一致的 API，旨在让用户无需深入了解基础设施即可扩展任务。只需修改一行代码，即可将现有的 pandas 工作流无缝迁移至 Xorbits 以获得性能提升。\n\n1.  **替换导入语句**\n    将原有的 `import pandas as pd` 修改为：\n    ```python\n    import xorbits.pandas as pd\n    ```\n\n2.  **执行现有代码**\n    保持后续数据处理逻辑不变。Xorbits 将自动利用所有计算核心加速运算，并有效处理超出单机内存限制的大型数据集。\n\n3.  **生态兼容性**\n    除了 pandas，该框架还支持 NumPy、PyTorch、XGBoost 等主流机器学习库的分布式扩展。\n\n> 更多资源：[官方文档](https:\u002F\u002Fxorbits.readthedocs.io) | [GitHub 源码](https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits)","某电商公司数据团队急需清洗并分析过去三年的全量用户点击流日志（约 50GB），以训练新的商品推荐模型。\n\n### 没有 xorbits 时\n- 受限于单点机器内存，尝试用原生 Pandas 一次性读入全量数据常因内存溢出（OOM）导致进程被杀。\n- 为应对大数据量，团队被迫暂停业务开发，转而去学习和适配 Spark 或 Dask 等重型分布式栈。\n- 即使数据能跑通，传统方案难以充分利用现代 CPU 的多核优势，导致单条 SQL 聚合查询耗时极长。\n\n### 使用 xorbits 后\n- 仅将 `import pandas as pd` 改为 `from xorbits.pandas import *`，库内部自动优化存储，完美绕过单机内存墙。\n- 业务代码几乎零改造，既保留了 Pandas 的开发效率，又获得了接近原生的分布式执行速度。\n- 智能利用空闲计算资源，将原本需要数小时的特征工程流水线压缩至分钟级响应。\n\n核心价值：让数据科学家在不牺牲开发体验的前提下，获得从个人笔记本到千机集群的线性扩展能力。","https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fxorbitsai_xorbits_91745e4c.png","xorbitsai","Xorbits","https:\u002F\u002Foss.gittoolsai.com\u002Favatars\u002Fxorbitsai_a7fc1829.png","Xorbits builds production-ready infrastructure for Model Inference and AI Agents.",null,"Xorbitsio","xinference.io","https:\u002F\u002Fgithub.com\u002Fxorbitsai",[23,27,31,35,39,43,47,50],{"name":24,"color":25,"percentage":26},"Python","#3572A5",97.7,{"name":28,"color":29,"percentage":30},"JavaScript","#f1e05a",1.1,{"name":32,"color":33,"percentage":34},"Cython","#fedf5b",0.8,{"name":36,"color":37,"percentage":38},"C++","#f34b7d",0.2,{"name":40,"color":41,"percentage":42},"Shell","#89e051",0.1,{"name":44,"color":45,"percentage":46},"HTML","#e34c26",0,{"name":48,"color":49,"percentage":46},"C","#555555",{"name":51,"color":52,"percentage":46},"Dockerfile","#384d54",1202,70,"2026-03-15T14:00:12","Apache-2.0",1,"未说明","非必需，支持利用多核或 GPU 加速，具体显卡型号、显存大小及 CUDA 版本未说明",{"notes":61,"python":58,"dependencies":62},"基于 Mars 构建；通过 pip 安装；旨在无缝扩展从笔记本到集群的工作流；支持多种数据科学和机器学习库；未来计划过渡到 Arrow 原生数据存储。",[63,64,65,66],"pandas","NumPy","PyTorch","XGBoost",[68,69,70],"其他","开发框架","数据工具",[72,73,74,63,75,76,77,78,79,80],"data-science","distributed-systems","numpy","python","scalable","lightgbm","machine-learning","ml","xgboost",3,"ready","2026-03-27T02:49:30.150509","2026-04-06T08:17:42.699092",[86,91,96,101,106,111],{"id":87,"question_zh":88,"answer_zh":89,"source_url":90},3723,"在分布式集群模式下如何读取本地 CSV 文件？","Xorbits 分布式计算不支持直接读取客户端本地的文件路径（如 F:\\dataset）。必须将文件存储在集群可访问的对象存储中（例如 HDFS、OSS 等），确保所有工作节点都能看到该文件，然后使用相对路径或存储路径读取。","https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fissues\u002F763",{"id":92,"question_zh":93,"answer_zh":94,"source_url":95},3724,"如何在部署 Xorbits 时进行自定义配置？","用户可以通过 `-f` 选项在部署时指定自定义配置文件。对于 Kubernetes、云或集群用户，可以根据需求覆盖默认参数。建议参考官方文档中的自定义配置文件示例进行设置。","https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fissues\u002F454",{"id":97,"question_zh":98,"answer_zh":99,"source_url":100},3725,"使用 `np.array(df)` 转换 DataFrame 时报 AttributeError 如何解决？","如果在较旧版本中遇到 `'series' object has no attribute '__array__'` 错误，这是因为与 NumPy 的兼容性问题。该问题已在主分支修复，请升级 Xorbits 至 v0.3.0 或更高版本即可解决。","https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fissues\u002F248",{"id":102,"question_zh":103,"answer_zh":104,"source_url":105},3726,"`read_csv` 的 `skiprows` 参数不起作用是什么原因？","早期版本的 `xorbits.pandas.read_csv()` 可能会忽略 `skiprows` 关键字参数。该功能已在 v0.2.0 版本中修复并正式支持 `int skiprows`，请检查当前版本是否为 v0.2.0 及以上。","https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fissues\u002F193",{"id":107,"question_zh":108,"answer_zh":109,"source_url":110},3727,"`df.values[0]` 获取不到标量值而是 DataRef 对象怎么办？","这是一个已知 Bug，导致 `df.values[0]` 返回 `DataRef` 对象而非实际数值，进而引发 `TypeError`。该问题计划在 v0.3.0 版本中修复，建议升级版本或暂时避免直接使用 `.values[0]` 进行标量运算。","https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fissues\u002F319",{"id":112,"question_zh":113,"answer_zh":114,"source_url":115},3728,"DataFrame 计算后自动丢弃未使用的列是否正常？","这不是预期行为，而是由优化模块引起的 Bug。维护者已确认复现该问题（即计算后未参与计算的列被丢弃），并计划尽快修复。建议关注后续版本更新以恢复正常的列保留行为。","https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fissues\u002F672",[117,122,127,132,137,142,147,152,157,162,167,172,177,182,187,192,197,202,207,212],{"id":118,"version":119,"summary_zh":120,"released_at":121},112964,"v0.8.2","# What's new in 0.8.2 (2024-12-26)\nThese are the changes in xorbits v0.8.2.\n## Enhancements\n* ENH: update web ui deps & remove deprecated numpy.compat by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F835\n* ENH: upgrade CI tests to python>=3.10 by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F837\n## Bug fixes\n* BUG: Fix isolation exit by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F834\n* BUG: set column name when using `xorbits.pandas.Index` by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F836\n## Documentation\n* DOC: operator fusion by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F838\n\n\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fcompare\u002Fv0.8.1...v0.8.2\n","2024-12-26T02:16:22",{"id":123,"version":124,"summary_zh":125,"released_at":126},112965,"v0.8.1","# What's new in 0.8.1 (2024-12-05)\nThese are the changes in xorbits v0.8.1.\n## Enhancements\n* ENH: Fix cuda storage transfer deadlock on multiple GPUs by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F788\n* BLD: Dockerfile for cpu and cuda by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F831\n* BLD: build wheel CI upgrade macos-12 to macos-13 by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F833\n## Bug fixes\n* BUG:  fix xoscar.errors.NoIdleSlot when using new_cluster by @hucorz in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F827\n* BUG: Fix no build_categorical_column error of GPU read_parquet by @hucorz in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F832\n\n\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fcompare\u002Fv0.8.0...v0.8.1\n","2024-12-05T13:00:03",{"id":128,"version":129,"summary_zh":130,"released_at":131},112966,"v0.8.0","# What's new in 0.8.0 (2024-11-05)\nThese are the changes in xorbits v0.8.0.\n## Enhancements\n* ENH: Compatible with NumPy 2.x by @Dawnfz-Lenfeng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F817\n* BLD: Support python 3.12 by @hucorz in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F825\n* BLD: Compat with numpy 2.x  by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F826\n## Documentation\n* DOC: URLs link to original lightgbm and xgboost docs by @Dawnfz-Lenfeng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F822\n* DOC: URLs link to original numpy and pandas docs  by @Dawnfz-Lenfeng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F824\n\n\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fcompare\u002Fv0.7.4...v0.8.0\n","2024-11-05T09:35:19",{"id":133,"version":134,"summary_zh":135,"released_at":136},112967,"v0.7.4","# What's new in 0.7.4 (2024-10-06)\nThese are the changes in xorbits v0.7.4.\n## Enhancements\n* ENH: distributed xgboost.init with rabit deprecated, move to collective by @hucorz in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F805\n* ENH: Fix some warning caused by deprecation by @hucorz in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F804\n* ENH: update web packages version by @hucorz in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F815\n* ENH: Fix config for xorbits and xorbits.pandas by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F818\n* BLD: Fix upload PyPI by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F820\n## Tests\n* TST: Fix cudf & hadoop failed tests cases by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F806\n## Documentation\n* DOC: update doc content && update sphinx to latest version by @hucorz in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F809\n* DOC: update CI environment dependencies for doc build by @Dawnfz-Lenfeng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F814\n* DOC: Add storage backend, fix broken links, update API reference by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F816\n* DOC: installation and compatible packages by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F819\n\n\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fcompare\u002Fv0.7.3...v0.7.4\n","2024-10-06T10:14:47",{"id":138,"version":139,"summary_zh":140,"released_at":141},112968,"v0.7.3","# What's new in 0.7.3 (2024-08-22)\nThese are the changes in xorbits v0.7.3.\n## Enhancements\n* ENH: fix test CI dependency of hadoop, lightgbm and web ui by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F772\n* ENH: Remove `sum_over_features` parameter from `manhattan_distances` with sklearn > 1.4 by @Dawnfz-Lenfeng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F779\n* ENH: Fix import error if np>=2.0 by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F787\n* ENH: Fix tests hang in CI by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F794\n* ENH: support cudf Buffer BufferOwner structure by @hucorz in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F798\n* ENH: Fix DataFrame._data deprecated warnings by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F793\n* ENH: Fix gpu cudf `to_csv` by @hucorz in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F799\n* ENH: Fix vineyard compatibility issue by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F783\n* ENH: fix cudf comp issue by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F803\n* BLD: Pin numpy\u003C2.0 as xorbits is not fully prepared for it  by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F782\n* BLD: Fix macos and windows build CI by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F784\n* BLD: Fix CI of uploading pypi  by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F785\n* BLD: Fix macos build wheel CI by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F789\n* BLD: Fix Docker CI\u002FCD workflow by @Dawnfz-Lenfeng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F796\n* BLD: Fix slurm CI\u002FCD workflow by @Dawnfz-Lenfeng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F801\n* BLD: update CI test workflow yaml by @hucorz in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F802\n* BLD: Fix asv workflow by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F792\n* REF: Delede code on pd \u003C 1.2.2 by @hucorz in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F797\n## Bug fixes\n* BUG: fix compatibility issue of df.sort_index() and df.groupby(sort=True) by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F776\n* BUG: fix CI of pypi & dockerhub  by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F777\n## Tests\n* TST: compatible libs with pandas 1.5.3 by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F775\n\n## New Contributors\n* @Dawnfz-Lenfeng made their first contribution in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F779\n* @hucorz made their first contribution in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F798\n\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fcompare\u002Fv0.7.2...v0.7.3\n","2024-08-22T03:24:41",{"id":143,"version":144,"summary_zh":145,"released_at":146},112969,"v0.7.2","# What's new in 0.7.2 (2024-01-05)\nThese are the changes in xorbits v0.7.2.\n## Enhancements\n* ENH: Modify `JAX` fusion optimization by @JiaYaobo in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F755\n## Bug fixes\n* BUG: fix read s3 parquet by @Hank0626 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F764\n## Documentation\n* DOC: add citation on README.md by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F766\n## Others\n* Bump @babel\u002Ftraverse from 7.22.8 to 7.23.2 in \u002Fpython\u002Fxorbits\u002Fweb\u002Fui by @dependabot in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F749\n* CHORE: drop CI support for  python 3.8 by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F765\n\n\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fcompare\u002Fv0.7.1...v0.7.2\n","2024-01-05T08:55:43",{"id":148,"version":149,"summary_zh":150,"released_at":151},112970,"v0.7.1","# What's new in 0.7.1 (2023-11-21)\nThese are the changes in xorbits v0.7.1.\n## New features\n* FEAT: Slurm Deployment For Xorbits by @fengsxy in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F719\n## Bug fixes\n* BUG: Fix pd.read_csv cannot read pathlib.Path by @traderbxy in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F757\n## Documentation\n* DOC: add user guide on lightgbm by @traderbxy in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F753\n* DOC: add user guide on xgboost by @traderbxy in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F754\n\n## New Contributors\n* @traderbxy made their first contribution in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F753\n* @fengsxy made their first contribution in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F719\n\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fcompare\u002Fv0.7.0...v0.7.1\n","2023-11-21T11:51:42",{"id":153,"version":154,"summary_zh":155,"released_at":156},112971,"v0.7.0","# What's new in 0.7.0 (2023-10-20)\nThese are the changes in xorbits v0.7.0.\n## New features\n* FEAT: Add `Dataframe.Groupby.nth` by @JiaYaobo in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F684\n* FEAT: Support `read_csv` via `http` by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F704\n* FEAT: Add `xorbits.sklearn` module by @JiaYaobo in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F716\n## Enhancements\n* ENH: groupby.nunique supports by series by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F726\n## Bug fixes\n* BUG: df.groupby.agg error when func is nunique with tuple kwargs by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F722\n* BUG: read parquet from s3 error: No Such Bucket by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F732\n* BUG: Fix read_csv with index_col by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F736\n* BUG: `merge` performance issue caused by `DataFrameAutoMergeMixin` by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F740\n* BUG: column pruning causes missing columns on `DataFrameIndex` op by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F743\n## Tests\n* TST: Fix xorbits.sklearn windows CI by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F748\n## Others\n* Fix reduction agg with UDF by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F737\n* Fix reduction agg with numpy udf by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F742\n\n## New Contributors\n* @JiaYaobo made their first contribution in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F684\n\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fcompare\u002Fv0.6.3...v0.7.0\n","2023-10-20T08:20:14",{"id":158,"version":159,"summary_zh":160,"released_at":161},112972,"v0.6.3","# What's new in 0.6.3 (2023-09-23)\nThese are the changes in xorbits v0.6.3.\n## Enhancements\n* ENH: Add a check whether scheduling is stuck by @Flying-Tom in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F695\n* ENH: Compatible with scikit-learn 1.3.1 by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F715\n## Bug fixes\n* BUG: fix df deep copy by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F709\n## Others\n* CHORE: Deprecate `downcast` in `fillna` by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F705\n\n\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fcompare\u002Fv0.6.2...v0.6.3\n","2023-09-23T05:09:46",{"id":163,"version":164,"summary_zh":165,"released_at":166},112973,"v0.6.2","# What's new in 0.6.2 (2023-09-20)\nThese are the changes in xorbits v0.6.2.\n## Enhancements\n* ENH: added auto merge for cartesian_chunk by @qinxuye in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F699\n## Bug fixes\n* BUG: `df.agg` with kwargs by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F707\n* BUG: Column pruning failed when `groupby` by multi series by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F708\n## Others\n* CHORE: Fix hadoop CI by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F706\n\n\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fcompare\u002Fv0.6.1...v0.6.2\n","2023-09-20T09:50:04",{"id":168,"version":169,"summary_zh":170,"released_at":171},112974,"v0.6.1","# What's new in 0.6.1 (2023-09-15)\nThese are the changes in xorbits v0.6.1.\n## New features\n* FEAT: Impl series __setitem__ by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F694\n## Enhancements\n* ENH: Add a status monitor to trace the running stage of subtask by @Flying-Tom in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F677\n* ENH: impl array protocol for series and index by @UranusSeven in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F531\n* BLD: ADLFS import error and docker build failed by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F698\n## Bug fixes\n* BUG: Tensor map chunk error when func is `tolist` by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F697\n## Others\n* CHORE: Deprecate ``use_inf_as_na`` option by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F689\n* CHORE: Fix asv CI by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F654\n\n\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fcompare\u002Fv0.6.0...v0.6.1\n","2023-09-15T10:34:56",{"id":173,"version":174,"summary_zh":175,"released_at":176},112975,"v0.6.0","# What's new in 0.6.0 (2023-09-08)\nThese are the changes in xorbits v0.6.0.\n## New features\n* FEAT: support loading zip file for read_parquet by @YibinLiu666 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F662\n## Enhancements\n* ENH: Use memoryview to open reader in MMAP storage backend by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F675\n* ENH: Compatible with Pandas 2.1.0 by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F679\n* ENH: Improve use_arrow_dtype for pandas 2.0+ by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F580\n* ENH: Default enable arrow dtype for read_parquet if pandas>=2.1 by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F685\n## Bug fixes\n* BUG: ipython data missing columns due to column pruning by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F681\n## Documentation\n* DOC: Readme for tpch benchmark script by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F676\n## Others\n* Add support to import xorbits.numpy.special functions by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F683\n* CHORE: Fix Pandas \u003C= 2.0.3 for now by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F678\n* CHORE: fsspec as dependency by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F686\n\n\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fcompare\u002Fv0.5.2...v0.6.0\n","2023-09-08T16:43:46",{"id":178,"version":179,"summary_zh":180,"released_at":181},112976,"v0.5.2","# What's new in 0.5.2 (2023-08-30)\nThese are the changes in xorbits v0.5.2.\n## New features\n* FEAT: MMAP storage backend by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F674\n## Enhancements\n* ENH: Use arrow table to transfer dataset meta by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F663\n## Bug fixes\n* BUG: Fix dtypes of `pd.pivot_table` by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F668\n* BUG: Fix tpch by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F670\n## Tests\n* TST: Add test_put_get_arrow by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F656\n## Others\n* CHORE: Modify required reviews by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F665\n* CHORE: disable infer_datetime_format option to reduce warnings by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F673\n\n\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fcompare\u002Fv0.5.1...v0.5.2\n","2023-08-30T03:50:56",{"id":183,"version":184,"summary_zh":185,"released_at":186},112977,"v0.5.1","# What's new in 0.5.1 (2023-08-14)\nThese are the changes in xorbits v0.5.1.\n## New features\n* FEAT: Export dataset by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F639\n* FEAT: Iterable dataset by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F643\n## Enhancements\n* ENH: Compatible with scikit-learn 1.3.0 by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F648\n* BLD: fix docker build on python 3.11 by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F642\n* BLD: add datasets dependency in docker base image  by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F644\n* BLD: git reset to fix dirty tag by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F655\n* BLD: Fix source building by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F657\n* BLD: Fix uploading wheel when it exists by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F658\n## Bug fixes\n* BUG: Fix Huggingface dataset loader filelock conflict by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F633\n* BUG: Fix pre-commit arg and CI node version by @Flying-Tom in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F622\n* BUG: Fix missing ArrowDtype by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F641\n* BUG: Fix `_generate_value` when building mock dataframe by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F645\n* BUG: Fix issues when connecting to a real yarn cluster by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F647\n## Tests\n* TST: K8s with juicefs CI may leads to pv conflict by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F646\n## Others\n* Fix copyright by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F651\n* CHORE: Remove win32 support by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F652\n\n\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fcompare\u002Fv0.5.0...v0.5.1\n","2023-08-14T14:07:17",{"id":188,"version":189,"summary_zh":190,"released_at":191},112978,"v0.5.0","# What's new in 0.5.0 (2023-07-28)\nThese are the changes in xorbits v0.5.0.\n## New features\n* FEAT: Basic datasets feature by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F600\n* FEAT: Raise clearer errors when encountering OOM by @Flying-Tom in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F621\n* Feat: Basic datasets getitem by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F628\n## Enhancements\n* ENH: add dedup method by @Hank0626 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F617\n## Bug fixes\n* BUG: Fix `pd.read_csv` with encoding parameter by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F614\n* BUG: fix from_tensor by @Hank0626 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F625\n* BUG: fix drop_duplicates no dtypes by @Hank0626 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F627\n## Tests\n* TST: Fix asv benchmark by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F624\n## Documentation\n* DOC: Add best practice for loading data by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F620\n* Doc: Datasets doc by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F619\n## Others\n* CHORE: add msbuild to CI by @YibinLiu666 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F631\n\n## New Contributors\n* @Flying-Tom made their first contribution in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F621\n\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fcompare\u002Fv0.4.4...v0.5.0\n","2023-07-28T11:24:32",{"id":193,"version":194,"summary_zh":195,"released_at":196},112979,"v0.4.4","# What's new in 0.4.4 (2023-07-21)\nThese are the changes in xorbits v0.4.4.\n## New features\n* FEAT: add xorbits experimental by @Hank0626 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F611\n## Enhancements\n* ENH: Optimize graph fusion by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F609\n## Bug fixes\n* BUG: fix s3 glob by @Hank0626 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F612\n\n\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fcompare\u002Fv0.4.3...v0.4.4\n","2023-07-21T11:22:09",{"id":198,"version":199,"summary_zh":200,"released_at":201},112980,"v0.4.3","# What's new in 0.4.3 (2023-07-20)\nThese are the changes in xorbits v0.4.3.\n## New features\n* FEAT: support text dedup by @Hank0626 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F576\n## Enhancements\n* ENH: Support xoscar copy_to by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F582\n## Bug fixes\n* BUG: Fix Read Parquet by @Hank0626 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F590\n* BUG: Fix LGBM CI by @Hank0626 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F599\n* BUG: Fetch to local when print object data by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F598\n* BUG: Fix compatibility with the newest lightgbm by @yifeis7 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F601\n## Others\n* Bump semver from 5.7.1 to 5.7.2 in \u002Fpython\u002Fxorbits\u002Fweb\u002Fui by @dependabot in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F594\n* Bump word-wrap from 1.2.3 to 1.2.4 in \u002Fpython\u002Fxorbits\u002Fweb\u002Fui by @dependabot in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F606\n\n\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fcompare\u002Fv0.4.2...v0.4.3\n","2023-07-20T04:02:08",{"id":203,"version":204,"summary_zh":205,"released_at":206},112981,"v0.4.2","# What's new in 0.4.2 (2023-07-10)\r\nThese are the changes in xorbits v0.4.2. v0.4.2 is a hotfix version to address a few crucial issues.\r\n## Bug fixes\r\n* BUG: Fix StringAccessor __getitem__ error by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F588\r\n* BUG: Fix RuntimeError: cannot schedule new futures after shutdown by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F589\r\n\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fcompare\u002Fv0.4.1...v0.4.2\r\n","2023-07-10T11:22:46",{"id":208,"version":209,"summary_zh":210,"released_at":211},112982,"v0.4.1","# What's new in 0.4.1 (2023-07-07)\nThese are the changes in xorbits v0.4.1.\n## New features\n* FEAT: Support base `Index.str` accessor by @RayJi01 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F511\n* FEAT: External Storage JuiceFS on K8S by @Zhou1213CN in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F497\n* FEAT: Support pandas option by @Hank0626 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F535\n* FEAT: Support nlargest and nsmallest op by @ZJU3190105746 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F530\n* FEAT: Support read parquet from http urls by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F573\n## Enhancements\n* ENH: Re-impl DataFrameNunique op by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F577\n* BLD: Fix scipy version in pyproject.toml by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F585\n* CLN: Fix github urls by @qinxuye in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F568\n## Bug fixes\n* BUG: Fix password lost when calling `pd.read_sql` by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F545\n* BUG: Fix error for unsupported input type of `read_sql` by @yifeis7 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F547\n* BUG: fix sparse divide CI by @Hank0626 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F550\n* BUG: fix joblib CI by @Hank0626 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F554\n* BUG: Fix build error on macos by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F565\n* BUG: Fix dataframe shape property by @yifeis7 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F566\n* BUG: Match more error  message by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F575\n* BUG: Fix importing learn.contrib is slow by @codingl2k1 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F569\n## Tests\n* TST: Fix version of sklearn by @qinxuye in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F559\n## Documentation\n* DOC: Documentation for JuiceFS on Kubernetes by @Zhou1213CN in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F538\n* DOC: Add Chinese doc for external storage JuiceFS on K8S by @Zhou1213CN in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F551\n* DOC: update why xorbits by @onesuper in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F556\n* DOC: update readme by @onesuper in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F557\n* DOC: make the slurm docs more concise by @luweizheng in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F561\n## Others\n* Bump scipy from 1.9.2 to 1.10.0 in \u002FCI by @dependabot in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F584\n* CHORE: Restrict fork repositories from using public ci resources by @ChengjieLi28 in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F574\n\n## New Contributors\n* @qinxuye made their first contribution in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F559\n* @onesuper made their first contribution in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F556\n* @codingl2k1 made their first contribution in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F565\n* @ZJU3190105746 made their first contribution in https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fpull\u002F530\n\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxorbitsai\u002Fxorbits\u002Fcompare\u002Fv0.4.0...v0.4.1\n","2023-07-07T15:51:20",{"id":213,"version":214,"summary_zh":215,"released_at":216},112983,"v0.4.0","# What's new in 0.4.0 (2023-06-21)\nThese are the changes in xorbits v0.4.0.\n## New features\n* FEAT: Support xgboost wrapper by @Hank0626 in https:\u002F\u002Fgithub.com\u002Fxprobe-inc\u002Fxorbits\u002Fpull\u002F502\n* FEAT: Add lightGBM wrapper by @yifeis7 in https:\u002F\u002Fgithub.com\u002Fxprobe-inc\u002Fxorbits\u002Fpull\u002F507\n## Enhancements\n* ENH: Fix the incompatibility with the latest version of SQLAlchemy. by @yifeis7 in https:\u002F\u002Fgithub.com\u002Fxprobe-inc\u002Fxorbits\u002Fpull\u002F520\n## Bug fixes\n* BUG: fix `sort_index` bug of multi-level indexed Dataframe with multi-chunk by @pangyoki in https:\u002F\u002Fgithub.com\u002Fxprobe-inc\u002Fxorbits\u002Fpull\u002F506\n* BUG: fix dataframe sample by @Hank0626 in https:\u002F\u002Fgithub.com\u002Fxprobe-inc\u002Fxorbits\u002Fpull\u002F532\n* Bug: Fix numpy CI by @Hank0626 in https:\u002F\u002Fgithub.com\u002Fxprobe-inc\u002Fxorbits\u002Fpull\u002F537\n* BUG: fix lightgbm by @Hank0626 in https:\u002F\u002Fgithub.com\u002Fxprobe-inc\u002Fxorbits\u002Fpull\u002F541\n* BUG: Suppress scipy warnings by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxprobe-inc\u002Fxorbits\u002Fpull\u002F543\n## Documentation\n* DOC: Init Xgboost Doc by @Hank0626 in https:\u002F\u002Fgithub.com\u002Fxprobe-inc\u002Fxorbits\u002Fpull\u002F525\n* DOC: Updated doc for python support version by @shark-21 in https:\u002F\u002Fgithub.com\u002Fxprobe-inc\u002Fxorbits\u002Fpull\u002F518\n* DOC: Install xgboost for doc building by @aresnow1 in https:\u002F\u002Fgithub.com\u002Fxprobe-inc\u002Fxorbits\u002Fpull\u002F539\n* DOC: Add lightgbm doc by @yifeis7 in https:\u002F\u002Fgithub.com\u002Fxprobe-inc\u002Fxorbits\u002Fpull\u002F540\n\n\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Fxprobe-inc\u002Fxorbits\u002Fcompare\u002Fv0.3.2...v0.4.0\n","2023-06-21T14:34:11",[218,228,238,246,254,265],{"id":219,"name":220,"github_repo":221,"description_zh":222,"stars":223,"difficulty_score":81,"last_commit_at":224,"category_tags":225,"status":82},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",[69,226,227],"图像","Agent",{"id":229,"name":230,"github_repo":231,"description_zh":232,"stars":233,"difficulty_score":234,"last_commit_at":235,"category_tags":236,"status":82},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",140436,2,"2026-04-05T23:32:43",[69,227,237],"语言模型",{"id":239,"name":240,"github_repo":241,"description_zh":242,"stars":243,"difficulty_score":234,"last_commit_at":244,"category_tags":245,"status":82},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。",107662,"2026-04-03T11:11:01",[69,226,227],{"id":247,"name":248,"github_repo":249,"description_zh":250,"stars":251,"difficulty_score":234,"last_commit_at":252,"category_tags":253,"status":82},3704,"NextChat","ChatGPTNextWeb\u002FNextChat","NextChat 是一款轻量且极速的 AI 助手，旨在为用户提供流畅、跨平台的大模型交互体验。它完美解决了用户在多设备间切换时难以保持对话连续性，以及面对众多 AI 模型不知如何统一管理的痛点。无论是日常办公、学习辅助还是创意激发，NextChat 都能让用户随时随地通过网页、iOS、Android、Windows、MacOS 或 Linux 端无缝接入智能服务。\n\n这款工具非常适合普通用户、学生、职场人士以及需要私有化部署的企业团队使用。对于开发者而言，它也提供了便捷的自托管方案，支持一键部署到 Vercel 或 Zeabur 等平台。\n\nNextChat 的核心亮点在于其广泛的模型兼容性，原生支持 Claude、DeepSeek、GPT-4 及 Gemini Pro 等主流大模型，让用户在一个界面即可自由切换不同 AI 能力。此外，它还率先支持 MCP（Model Context Protocol）协议，增强了上下文处理能力。针对企业用户，NextChat 提供专业版解决方案，具备品牌定制、细粒度权限控制、内部知识库整合及安全审计等功能，满足公司对数据隐私和个性化管理的高标准要求。",87618,"2026-04-05T07:20:52",[69,237],{"id":255,"name":256,"github_repo":257,"description_zh":258,"stars":259,"difficulty_score":234,"last_commit_at":260,"category_tags":261,"status":82},2268,"ML-For-Beginners","microsoft\u002FML-For-Beginners","ML-For-Beginners 是由微软推出的一套系统化机器学习入门课程，旨在帮助零基础用户轻松掌握经典机器学习知识。这套课程将学习路径规划为 12 周，包含 26 节精炼课程和 52 道配套测验，内容涵盖从基础概念到实际应用的完整流程，有效解决了初学者面对庞大知识体系时无从下手、缺乏结构化指导的痛点。\n\n无论是希望转型的开发者、需要补充算法背景的研究人员，还是对人工智能充满好奇的普通爱好者，都能从中受益。课程不仅提供了清晰的理论讲解，还强调动手实践，让用户在循序渐进中建立扎实的技能基础。其独特的亮点在于强大的多语言支持，通过自动化机制提供了包括简体中文在内的 50 多种语言版本，极大地降低了全球不同背景用户的学习门槛。此外，项目采用开源协作模式，社区活跃且内容持续更新，确保学习者能获取前沿且准确的技术资讯。如果你正寻找一条清晰、友好且专业的机器学习入门之路，ML-For-Beginners 将是理想的起点。",84991,"2026-04-05T10:45:23",[226,70,262,263,227,68,237,69,264],"视频","插件","音频",{"id":266,"name":267,"github_repo":268,"description_zh":269,"stars":270,"difficulty_score":81,"last_commit_at":271,"category_tags":272,"status":82},3128,"ragflow","infiniflow\u002Fragflow","RAGFlow 是一款领先的开源检索增强生成（RAG）引擎，旨在为大语言模型构建更精准、可靠的上下文层。它巧妙地将前沿的 RAG 技术与智能体（Agent）能力相结合，不仅支持从各类文档中高效提取知识，还能让模型基于这些知识进行逻辑推理和任务执行。\n\n在大模型应用中，幻觉问题和知识滞后是常见痛点。RAGFlow 通过深度解析复杂文档结构（如表格、图表及混合排版），显著提升了信息检索的准确度，从而有效减少模型“胡编乱造”的现象，确保回答既有据可依又具备时效性。其内置的智能体机制更进一步，使系统不仅能回答问题，还能自主规划步骤解决复杂问题。\n\n这款工具特别适合开发者、企业技术团队以及 AI 研究人员使用。无论是希望快速搭建私有知识库问答系统，还是致力于探索大模型在垂直领域落地的创新者，都能从中受益。RAGFlow 提供了可视化的工作流编排界面和灵活的 API 接口，既降低了非算法背景用户的上手门槛，也满足了专业开发者对系统深度定制的需求。作为基于 Apache 2.0 协议开源的项目，它正成为连接通用大模型与行业专有知识之间的重要桥梁。",77062,"2026-04-04T04:44:48",[227,226,69,237,68]]