[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-3730":3},{"id":4,"name":5,"fullName":6,"owner":5,"repo":5,"description":7,"homepage":8,"htmlUrl":9,"language":10,"languages":9,"totalLinesOfCode":9,"stars":11,"forks":12,"watchers":13,"openIssues":14,"contributorsCount":15,"subscribersCount":15,"size":15,"stars1d":16,"stars7d":17,"stars30d":18,"stars90d":15,"forks30d":15,"starsTrendScore":19,"compositeScore":20,"rankGlobal":9,"rankLanguage":9,"license":21,"archived":22,"fork":22,"defaultBranch":23,"hasWiki":24,"hasPages":22,"topics":25,"createdAt":9,"pushedAt":9,"updatedAt":37,"readmeContent":38,"aiSummary":39,"trendingCount":15,"starSnapshotCount":15,"syncStatus":40,"lastSyncTime":41,"discoverSource":42},3730,"bokeh","bokeh\u002Fbokeh","Interactive Data Visualization in the browser, from  Python","https:\u002F\u002Fbokeh.org",null,"TypeScript",20401,4259,423,835,0,1,9,33,4,79.8,"BSD 3-Clause \"New\" or \"Revised\" License",false,"branch-3.10",true,[5,26,27,28,29,30,31,32,33,34,35,36],"data-visualisation","interactive-plots","javascript","jupyter","notebooks","numfocus","plots","plotting","python","visualisation","visualization","2026-06-12 04:00:19","\u003Cpicture>\n  \u003Csource media=\"(prefers-color-scheme: light)\" srcset=\"https:\u002F\u002Fraw.githubusercontent.com\u002Fbokeh\u002Fpm\u002Fmain\u002Fassets\u002Flogos\u002FSVG\u002Fbokeh-logo-white-text-no-padding.svg\">\n  \u003Cimg src=\"https:\u002F\u002Fraw.githubusercontent.com\u002Fbokeh\u002Fpm\u002Fmain\u002Fassets\u002Flogos\u002FSVG\u002Fbokeh-logo-black-text-no-padding.svg\" alt=\"Bokeh logo -- text is white in dark theme and black in light theme\" height=60\u002F>\n\u003C\u002Fpicture>\n\n----\n\n[Bokeh](https:\u002F\u002Fbokeh.org) is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics and affords high-performance interactivity across large or streaming datasets. Bokeh can help anyone who wants to create interactive plots, dashboards, and data applications quickly and easily.\n\n\u003Ctable>\n\n\u003Ctr>\n\n  \u003Ctd>Package\u003C\u002Ftd>\n\n  \u003Ctd>\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fv\u002Fbokeh?label=Version&color=ECD078&style=for-the-badge\"\n         alt=\"Latest package version\" \u002F>\n  \u003C\u002Ftd>\n\n  \u003Ctd>\n    \u003Ca href=\"https:\u002F\u002Fdocs.bokeh.org\u002Fen\u002Flatest\u002Fdocs\u002Ffirst_steps\u002Finstallation.html\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fpyversions\u002Fbokeh?color=ECD078&style=for-the-badge\"\n         alt=\"Supported Python versions\" \u002F>\n    \u003C\u002Fa>\n  \u003C\u002Ftd>\n\n  \u003Ctd>\n    \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fbokeh\u002Fbokeh\u002Fblob\u002F-\u002FLICENSE.txt\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Flicense\u002Fbokeh\u002Fbokeh.svg?color=ECD078&style=for-the-badge\"\n         alt=\"Bokeh license (BSD 3-clause)\" \u002F>\n    \u003C\u002Fa>\n  \u003C\u002Ftd>\n\n\u003C\u002Ftr>\n\n\u003Ctr>\n\n  \u003Ctd>Project\u003C\u002Ftd>\n\n  \u003Ctd>\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fcontributors-anon\u002Fbokeh\u002Fbokeh?color=ECD078&style=for-the-badge\"\n         alt=\"Github contributors\" \u002F>\n  \u003C\u002Ftd>\n\n  \u003Ctd>\n    \u003Ca href=\"https:\u002F\u002Fnumfocus.org\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fsponsor-numfocus-ECD078?style=for-the-badge\"\n         alt=\"Link to NumFOCUS\" \u002F>\n    \u003C\u002Fa>\n  \u003C\u002Ftd>\n\n  \u003Ctd>\n    \u003Ca href=\"https:\u002F\u002Fdocs.bokeh.org\u002Fen\u002Flatest\u002F\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fdocumentation-latest-ECD078?style=for-the-badge\"\n         alt=\"Link to documentation\" \u002F>\n    \u003C\u002Fa>\n  \u003C\u002Ftd>\n\n\u003C\u002Ftr>\n\n\u003Ctr>\n\n  \u003Ctd>Downloads\u003C\u002Ftd>\n\n  \u003Ctd>\n    \u003Ca href=\"https:\u002F\u002Fdocs.bokeh.org\u002Fen\u002Flatest\u002Fdocs\u002Ffirst_steps\u002Finstallation.html\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fdm\u002Fbokeh?color=D98B43&label=pypi&logo=python&logoColor=yellow&style=for-the-badge\"\n         alt=\"PyPI downloads per month\" \u002F>\n    \u003C\u002Fa>\n  \u003C\u002Ftd>\n\n  \u003Ctd>\n    \u003Ca href=\"https:\u002F\u002Fdocs.bokeh.org\u002Fen\u002Flatest\u002Fdocs\u002Ffirst_steps\u002Finstallation.html\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fconda\u002Fd\u002Fconda-forge\u002Fbokeh?style=for-the-badge&logo=python&color=D98B43&logoColor=yellow\"\n         alt=\"Conda downloads per month\" \u002F>\n    \u003C\u002Fa>\n  \u003C\u002Ftd>\n\n  \u003Ctd>\n    \u003Ca href=\"https:\u002F\u002Fwww.npmjs.com\u002Fpackage\u002F@bokeh\u002Fbokehjs\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fnpm\u002Fdm\u002F%40bokeh\u002Fbokehjs?style=for-the-badge&logo=npm&label=NPM&color=D98B43\"\n         alt=\"NPM downloads per month\" \u002F>\n    \u003C\u002Fa>\n  \u003C\u002Ftd>\n\n\u003C\u002Ftr>\n\n\u003Ctr>\n\n  \u003Ctd>Build\u003C\u002Ftd>\n\n  \u003Ctd>\n    \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fbokeh\u002Fbokeh\u002Factions\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Factions\u002Fworkflow\u002Fstatus\u002Fbokeh\u002Fbokeh\u002Fbokeh-ci.yml?label=Bokeh-CI&logo=github&style=for-the-badge\"\n         alt=\"Current Bokeh-CI github actions build status\" \u002F>\n    \u003C\u002Fa>\n  \u003C\u002Ftd>\n\n  \u003Ctd>\n    \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fbokeh\u002Fbokeh\u002Factions\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Factions\u002Fworkflow\u002Fstatus\u002Fbokeh\u002Fbokeh\u002Fbokehjs-ci.yml?label=BokehJS-CI&logo=github&style=for-the-badge\"\n         alt=\"Current BokehJS-CI github actions build status\" \u002F>\n    \u003C\u002Fa>\n  \u003C\u002Ftd>\n\n  \u003Ctd>\n    \u003Ca href=\"https:\u002F\u002Fcodecov.io\u002Fgh\u002Fbokeh\u002Fbokeh\" >\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fcodecov\u002Fc\u002Fgithub\u002Fbokeh\u002Fbokeh?logo=codecov&style=for-the-badge&token=bhEzGkDUaw\"\n         alt=\"Codecov coverage percentage\" \u002F>\n    \u003C\u002Fa>\n  \u003C\u002Ftd>\n\n\u003C\u002Ftr>\n\n\u003Ctr>\n\n  \u003Ctd>Community\u003C\u002Ftd>\n\n  \u003Ctd>\n    \u003Ca href=\"https:\u002F\u002Fdiscourse.bokeh.org\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fdiscourse\u002Fhttps\u002Fdiscourse.bokeh.org\u002Fposts.svg?color=blue&logo=discourse&style=for-the-badge\"\n         alt=\"Community support on discourse.bokeh.org\" \u002F>\n    \u003C\u002Fa>\n  \u003C\u002Ftd>\n\n  \u003Ctd>\n    \u003Ca href=\"https:\u002F\u002Fstackoverflow.com\u002Fquestions\u002Ftagged\u002Fbokeh\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fstackexchange\u002Fstackoverflow\u002Ft\u002F%5Bbokeh%5D?style=for-the-badge&logo=stackoverflow&label=stackoverflow&color=blue\"\n         alt=\"Bokeh-tagged questions on Stack Overflow\" \u002F>\n     \u003C\u002Fa>\n  \u003C\u002Ftd>\n\n\u003C\u002Ftr>\n\n\n\u003C\u002Ftable>\n\n*Consider [making a donation](https:\u002F\u002Fopencollective.com\u002Fbokeh) if you enjoy using Bokeh and want to support its development.*\n\n![4x9 image grid of Bokeh plots](https:\u002F\u002Fuser-images.githubusercontent.com\u002F1078448\u002F190840954-dc243c99-9295-44de-88e9-fafd0f4f7f8a.jpg)\n\n## Installation\n\nTo install Bokeh and its required dependencies using `pip`, enter the following command at a Bash or Windows command prompt:\n```\npip install bokeh\n```\n\nTo install using `conda`, enter the following command at a Bash or Windows command prompt:\n\n```\nconda install bokeh\n```\n\nRefer to the [installation documentation](https:\u002F\u002Fdocs.bokeh.org\u002Fen\u002Flatest\u002Fdocs\u002Ffirst_steps\u002Finstallation.html) for more details.\n\n## Resources\n\nOnce Bokeh is installed, check out the [first steps guides](https:\u002F\u002Fdocs.bokeh.org\u002Fen\u002Flatest\u002Fdocs\u002Ffirst_steps.html#first-steps-guides).\n\nVisit the [full documentation site](https:\u002F\u002Fdocs.bokeh.org) to view the [User's Guide](https:\u002F\u002Fdocs.bokeh.org\u002Fen\u002Flatest\u002Fdocs\u002Fuser_guide.html) or [checkout the Bokeh tutorial repository](https:\u002F\u002Fgithub.com\u002Fbokeh\u002Ftutorial\u002F) to learn about Bokeh in live Jupyter Notebooks.\n\nCommunity support is available on the [Project Discourse](https:\u002F\u002Fdiscourse.bokeh.org).\n\nIf you would like to contribute to Bokeh, please review the [Contributor Guide](https:\u002F\u002Fdocs.bokeh.org\u002Fen\u002Flatest\u002Fdocs\u002Fdev_guide.html) and [request an invitation to the Bokeh Dev Slack workspace](https:\u002F\u002Fslack-invite.bokeh.org\u002F).\n\n*Note: Everyone who engages in the Bokeh project's discussion forums, codebases, and issue trackers is expected to follow the [Code of Conduct](https:\u002F\u002Fgithub.com\u002Fbokeh\u002Fbokeh\u002Fblob\u002FHEAD\u002Fdocs\u002FCODE_OF_CONDUCT.md).*\n\n## Support\n\n### Fiscal Support\n\nThe Bokeh project is grateful for [individual contributions](https:\u002F\u002Fopencollective.com\u002Fbokeh), as well as for present and past monetary support from the organizations and companies listed below:\n\n\u003Ctable align=\"center\">\n\u003Ctr>\n\n  \u003Ctd>\n    \u003Ca href=\"https:\u002F\u002Fwww.numfocus.org\u002F\">\n    \u003Cimg src=\"https:\u002F\u002Fstatic.bokeh.org\u002Fsponsor\u002Fnumfocus.svg\"\n         alt=\"NumFocus Logo\" width=\"200\"\u002F>\n    \u003C\u002Fa>\n  \u003C\u002Ftd>\n\n  \u003Ctd>\n    \u003Ca href=\"https:\u002F\u002Fchanzuckerberg.com\u002F\">\n    \u003Cimg src=\"https:\u002F\u002Fstatic.bokeh.org\u002Fsponsor\u002Fczi.svg\"\n         alt=\"CZI Logo\" width=\"200\"\u002F>\n    \u003C\u002Fa>\n  \u003C\u002Ftd>\n\n  \u003Ctd colspan=\"2\">\n    \u003Ca href=\"https:\u002F\u002Fwww.blackstone.com\u002Fthe-firm\u002F\">\n    \u003Cimg src=\"https:\u002F\u002Fstatic.bokeh.org\u002Fsponsor\u002Fblackstone.png\"\n         alt=\"Blackstone Logo\" width=\"400\"\u002F>\n    \u003C\u002Fa>\n  \u003C\u002Ftd>\n\n \u003C\u002Ftr>\n \u003Ctr>\n\n  \u003Ctd>\n    \u003Ca href=\"https:\u002F\u002Ftidelift.com\u002F\">\n    \u003Cimg src=\"https:\u002F\u002Fstatic.bokeh.org\u002Fsponsor\u002Ftidelift.svg\"\n         alt=\"TideLift Logo\" width=\"200\"\u002F>\n    \u003C\u002Fa>\n  \u003C\u002Ftd>\n\n  \u003Ctd>\n    \u003Ca href=\"https:\u002F\u002Fwww.anaconda.com\u002F\">\n    \u003Cimg src=\"https:\u002F\u002Fstatic.bokeh.org\u002Fsponsor\u002Fanaconda.png\"\n         alt=\"Anaconda Logo\" width=\"200\"\u002F>\n    \u003C\u002Fa>\n  \u003C\u002Ftd>\n\n  \u003Ctd>\n    \u003Ca href=\"https:\u002F\u002Fwww.nvidia.com\">\n    \u003Cimg src=\"https:\u002F\u002Fstatic.bokeh.org\u002Fsponsor\u002Fnvidia.png\"\n         alt=\"NVidia Logo\" width=\"200\"\u002F>\n    \u003C\u002Fa>\n  \u003C\u002Ftd>\n\n  \u003Ctd>\n    \u003Ca href=\"https:\u002F\u002Fdeveloper.nvidia.com\u002Frapids\">\n    \u003Cimg src=\"https:\u002F\u002Fstatic.bokeh.org\u002Fsponsor\u002Frapids.png\"\n         alt=\"Rapids Logo\" width=\"200\"\u002F>\n    \u003C\u002Fa>\n  \u003C\u002Ftd>\n\n\u003C\u002Ftr>\n\u003C\u002Ftable>\n\nIf your company uses Bokeh and is able to sponsor the project, please contact \u003Ca href=\"info@bokeh.org\">info@bokeh.org\u003C\u002Fa>\n\n*Bokeh is a Sponsored Project of NumFOCUS, a 501(c)(3) nonprofit charity in the United States. NumFOCUS provides Bokeh with fiscal, legal, and administrative support to help ensure the health and sustainability of the project. Visit [numfocus.org](https:\u002F\u002Fnumfocus.org) for more information.*\n\n*Donations to Bokeh are managed by NumFOCUS. For donors in the United States, your gift is tax-deductible to the extent provided by law. As with any donation, you should consult with your tax adviser about your particular tax situation.*\n\n### In-kind Support\n\nNon-monetary support can help with development, collaboration, infrastructure, security, and vulnerability management. The Bokeh project is grateful to the following companies for their donation of services:\n\n* [Amazon Web Services](https:\u002F\u002Faws.amazon.com\u002F)\n* [GitGuardian](https:\u002F\u002Fgitguardian.com\u002F)\n* [GitHub](https:\u002F\u002Fgithub.com\u002F)\n* [makepath](https:\u002F\u002Fmakepath.com\u002F)\n* [Pingdom](https:\u002F\u002Fwww.pingdom.com\u002Fwebsite-monitoring)\n* [Slack](https:\u002F\u002Fslack.com)\n* [QuestionScout](https:\u002F\u002Fwww.questionscout.com\u002F)\n* [1Password](https:\u002F\u002F1password.com\u002F)\n* [Digital Ocean](https:\u002F\u002Fwww.digitalocean.com)\n","Bokeh 是一个用于现代网页浏览器的交互式数据可视化库。它支持从 Python 生成美观且简洁的图形，并能高效处理大规模或流式数据集的交互操作。其核心功能包括创建可交互的图表、仪表板和数据应用，同时具备高性能的数据渲染能力。Bokeh 适合需要快速开发具有高度互动性的数据分析与展示项目的场景，如科研、教育及商业分析等领域。",2,"2026-06-11 02:55:51","top_language"]