[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-9717":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":10,"rankLanguage":10,"license":22,"archived":23,"fork":23,"defaultBranch":24,"hasWiki":23,"hasPages":25,"topics":26,"createdAt":10,"pushedAt":10,"updatedAt":36,"readmeContent":37,"aiSummary":38,"trendingCount":16,"starSnapshotCount":16,"syncStatus":39,"lastSyncTime":40,"discoverSource":41},9717,"PySyft","OpenMined\u002FPySyft","OpenMined","Perform data science on data that remains in someone else's server","https:\u002F\u002Fwww.openmined.org\u002F",null,"Python",9903,1999,195,16,0,1,3,22,4,40.9,"Apache License 2.0",false,"dev",true,[27,28,29,30,31,32,33,34,35],"cryptography","deep-learning","federated-learning","hacktoberfest","privacy","python","pytorch","secure-computation","syft","2026-06-12 02:02:11","\u003Cdiv align=\"left\"> \u003Ca href=\"https:\u002F\u002Fpypi.org\u002Fproject\u002Fsyft\u002F\">\u003Cimg src=\"https:\u002F\u002Fstatic.pepy.tech\u002Fbadge\u002Fpysyft\" \u002F>\u003C\u002Fa> \u003Ca href=\"https:\u002F\u002Fpypi.org\u002Fproject\u002Fsyft\u002F\">\u003Cimg src=\"https:\u002F\u002Fbadge.fury.io\u002Fpy\u002Fsyft.svg\" \u002F>\u003C\u002Fa> \u003Ca href=\"https:\u002F\u002Fhub.docker.com\u002Fu\u002Fopenmined\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fdocker-images-blue?logo=docker\" \u002F>\u003C\u002Fa> \u003Ca href=\"https:\u002F\u002Fgithub.com\u002FOpenMined\u002FPySyft\u002Factions\u002Fworkflows\u002Fnightlies.yml\">\u003Cimg src=\"https:\u002F\u002Fgithub.com\u002FOpenMined\u002FPySyft\u002Factions\u002Fworkflows\u002Fnightlies.yml\u002Fbadge.svg?branch=dev\" \u002F>\u003C\u002Fa> \u003Ca href=\"https:\u002F\u002Fjoin.slack.com\u002Ft\u002Fopenmined\u002Fshared_invite\u002Fzt-2hxwk07i9-HO7u5C7XOgou4Z62VU78zA\u002F\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fchat-on%20slack-purple?logo=slack\" \u002F>\u003C\u002Fa> \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Findex.html\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fread-docs-yellow?logo=mdbook\" \u002F>\u003C\u002Fa>\n\u003Cbr \u002F>\u003Cbr \u002F>\u003C\u002Fdiv>\n\n\u003Cpicture>\n  \u003Csource media=\"(prefers-color-scheme: dark)\" srcset=\"docs\u002Fimg\u002FSyft-Logo-Light.svg\">\n  \u003Cimg alt=\"Syft Logo\" src=\"docs\u002Fimg\u002FSyft-Logo.svg\" width=\"200px\" \u002F>\n\u003C\u002Fpicture>\n\n\u003Ch3> Data Science on data you are not allowed to see\u003C\u002Fh3>\n\nPySyft enables a new way to do data science, where you can use non-public information, without seeing nor obtaining a copy of the data itself. All you need is to connect to a \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fcomponents\u002Fdatasite-server.html\">Datasite\u003C\u002Fa>!\n\nDatasites are like websites, but for data. Designed with the principles of \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fabs\u002F2012.08347\">structured transparency\u003C\u002Fa>, they enable data owners to control how their data is protected and data scientists to use data without obtaining a copy.\n\nPySyft supports any statistical analysis or machine learning, offering support for directly running Python code - even using third-party Python libraries.\n\n\u003Ch4> Supported on:\u003C\u002Fh4>\n\n✅ Linux\n✅ macOS\n✅ Windows\n✅ Docker\n✅ Kubernetes\n\n# Quickstart\n\nTry out your \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Findex.html\">first query against a live demo Datasite! \u003C\u002Fa>\n\n## Install Client\n\n```bash\npip install -U \"syft[data_science]\"\n```\n\nMore instructions are available \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fquick-install.html\">here\u003C\u002Fa>.\n\n## Launch Server\n\nLaunch \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fdeployment\u002Fdeployment-doc-1-2-intro-req.html\">a development server \u003C\u002Fa> directly in your Jupyter Notebook:\n\n```python\nimport syft as sy\n\nsy.requires(\">=0.9.5,\u003C0.9.6\")\n\nserver = sy.orchestra.launch(\n    name=\"my-datasite\",\n    port=8080,\n    create_producer=True,\n    n_consumers=1,\n    dev_mode=False,\n    reset=True, # resets database\n)\n```\n\nor from the command line:\n\n```bash\n$ syft launch --name=my-datasite --port=8080 --reset=True\n\nStarting syft-datasite server on 0.0.0.0:8080\n```\n\nDatasite servers can be deployed as a single container using Docker or directly in Kubernetes. Check out our \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fdeployment\u002Fdeployment-doc-1-2-intro-req.html\">deployment guide.\u003C\u002Fa>\n\n## Launch Client\n\nMain way to use a Datasite is via our Syft client, in a Jupyter Notebook. Check out our \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fcomponents\u002Fsyft-client.html\"> PySyft client guide\u003C\u002Fa>:\n\n```python\nimport syft as sy\n\nsy.requires(\">=0.9.5,\u003C0.9.6\")\n\ndatasite_client = sy.login(\n    port=8080,\n    email=\"info@openmined.org\",\n    password=\"changethis\"\n)\n```\n\n## PySyft - Getting started 📝\n\nLearn about PySyft via our getting started guide:\n\n- \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fgetting-started\u002Fintroduction.html\">PySyft from the ground up\u003C\u002Fa>\n- \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fgetting-started\u002Fpart1-dataset-and-assets.html\"> Part 1: Datasets & Assets\u003C\u002Fa>\n- \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fgetting-started\u002Fpart2-datasite-access.html\"> Part 2: Client and Datasite Access\u003C\u002Fa>\n- \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fgetting-started\u002Fpart3-research-study.html\"> Part 3: Propose the research study\u003C\u002Fa>\n- \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fgetting-started\u002Fpart4-review-code-request.html\"> Part 4: Review Code Requests\u003C\u002Fa>\n- \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fgetting-started\u002Fpart5-retrieving-results.html\"> Part 5: Retrieving Results\u003C\u002Fa>\n\n# PySyft In-depth\n\n📚 Check out \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Findex.html\">our docs website\u003C\u002Fa>.\n\nQuick PySyft components links:\n\n- \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fcomponents\u002Fdatasite-server.html\">DataSite Server\u003C\u002Fa>\n\n- \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002F\u002Fcomponents\u002Fsyft-client.html\">Syft Client\u003C\u002Fa>\n\n- \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fcomponents\u002Fdatasets.html\">Datasets API (`.datasets`)\u003C\u002Fa>\n\n- \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fcomponents\u002Fusers-api.html\">Users API (`.users`)\u003C\u002Fa>\n\n\u003C!-- - \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fcomponents\u002Fprojects-api.html\">Projects API (`.projects`)\u003C\u002Fa> -->\n\n- \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fcomponents\u002Frequests-api.html\">Request API (`.requests`)\u003C\u002Fa>\n\n- \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fcomponents\u002Fcode-api.html\">Code API (`.code`)\u003C\u002Fa>\n\n- \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fcomponents\u002Fsyft-policies.html\">Syft Policies API (`.policy`)\u003C\u002Fa>\n\n- \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fcomponents\u002Fsettings-api.html\">Settings API (`.settings`)\u003C\u002Fa>\n\n- \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fcomponents\u002Fnotifications.html\">Notifications API (`.notifications`)\u003C\u002Fa>\n\n- \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Fcomponents\u002Fsyncing-api.html\">Sync API (`.sync`)\u003C\u002Fa>\n\n## Why use PySyft?\n\nIn a variety of domains across society, data owners have **valid concerns about the risks associated with sharing their data**, such as legal risks, privacy invasion (_misuing the data_), or intellectual property (_copying and redistributing it_).\n\nDatasites enable data scientists to **answer questions** without even seeing or acquiring a copy of the data, **within the data owners's definition of acceptable use**. We call this process \u003Cb> Remote Data Science\u003C\u002Fb>.\n\nThis means that the **current risks** of sharing information with someone will **no longer prevent** the vast benefits such as innovation, insights and scientific discovery. With each Datasite, data owners are able to enable `1000x more accesible data` in each scientific field and lead, together with data scientists, breakthrough innovation.\n\nLearn more about our work on \u003Ca href=\"https:\u002F\u002Fopenmined.org\u002F\">our website\u003C\u002Fa>.\n\n## Support\n\nFor questions about PySyft, reach out via `#support` on \u003Ca href=\"https:\u002F\u002Fslack.openmined.org\u002F\">Slack\u003C\u002Fa>.\n\n## Syft Versions\n\n:exclamation: PySyft and Syft Server must use the same `version`.\n\n**Latest Stable**\n\n- `0.9.5` (Stable) - \u003Ca href=\"https:\u002F\u002Fdocs.openmined.org\u002Fen\u002Flatest\u002Findex.html\">Docs\u003C\u002Fa>\n- Install PySyft (Stable): `pip install -U syft`\n\n\nFind more about previous \u003Ca href=\".\u002Freleases.md\">releases here\u003C\u002Fa>.\n\n# Community\n\nSupported by the OpenMined Foundation, the OpenMined Community is an online network of over 17,000 technologists, researchers, and industry professionals keen to _unlock 1000x more data in every scientific field and industry_.\n\n\u003Ca href=\"https:\u002F\u002Fjoin.slack.com\u002Ft\u002Fopenmined\u002Fshared_invite\u002Fzt-2hxwk07i9-HO7u5C7XOgou4Z62VU78zA\">\u003Cimg width=150px src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FJoin_us-%20slack-purple?logo=slack\" \u002F>\u003C\u002Fa>\n\n# Courses\n\n\u003Ctable border=\"5\" bordercolor=\"grey\">\n\u003Ctr>\n\u003Cth align=\"center\">\n\u003Cimg width=\"200\" height=\"1\">\n\u003Cdiv align=\"center\">\n\u003Ca href=\"https:\u002F\u002Fcourses.openmined.org\u002Fcourses\u002Four-privacy-opportunity\">\u003Cimg src=\"docs\u002Fimg\u002Fcourse_privacy.png\" alt=\"\" width=\"100%\" align=\"center\" \u002F>\u003C\u002Fa>\n\u003C\u002Fth>\n\u003Cth align=\"center\">\n\u003Cimg width=\"200\" height=\"1\">\n\u003Cdiv align=\"center\">\n\u003Ca href=\"https:\u002F\u002Fcourses.openmined.org\u002Fcourses\u002Ffoundations-of-private-computation\">\u003Cimg src=\"docs\u002Fimg\u002Fcourse_foundations.png\" alt=\"\" width=\"100%\" align=\"center\" \u002F>\u003C\u002Fa>\n\u003C\u002Fdiv>\n\u003C\u002Fth>\n\u003Cth align=\"center\">\n\u003Cimg width=\"200\" height=\"1\">\n\u003Cdiv align=\"center\">\n\u003Ca href=\"https:\u002F\u002Fcourses.openmined.org\u002Fcourses\u002Fintroduction-to-remote-data-science\">\u003Cimg src=\"docs\u002Fimg\u002Fcourse_introduction.png\" alt=\"\" width=\"100%\" align=\"center\">\u003C\u002Fa>\n\u003C\u002Fdiv>\n\u003C\u002Fth>\n\u003C\u002Ftr>\n\u003C\u002Ftable>\n\n# Contributors\n\nOpenMined and Syft appreciates all contributors, if you would like to fix a bug or suggest a new feature, please reach out via \u003Ca href=\"https:\u002F\u002Fgithub.com\u002FOpenMined\u002FPySyft\u002Fissues\">Github\u003C\u002Fa> or \u003Ca href=\"https:\u002F\u002Fjoin.slack.com\u002Ft\u002Fopenmined\u002Fshared_invite\u002Fzt-2hxwk07i9-HO7u5C7XOgou4Z62VU78zA\u002F\">Slack\u003C\u002Fa>!\n\n\u003Cpicture>\n  \u003Csource media=\"(prefers-color-scheme: dark)\" srcset=\"docs\u002Fimg\u002Fcontributors_dark.jpg\">\n  \u003Cimg src=\"docs\u002Fimg\u002Fcontributors_light.jpg\" alt=\"Contributors\" width=\"100%\" \u002F>\n\u003C\u002Fpicture>\n\n# About OpenMined\n\nOpenMined is a non-profit foundation creating technology infrastructure that helps researchers get answers from data without needing a copy or direct access. Our community of technologists is building Syft.\n\n\u003Ca href=\"https:\u002F\u002Fdonate.stripe.com\u002FfZe03H0aLdAO59e9AA\n\">\u003Cimg width=200px src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FDonate_to-OpenMined-yellow?logo=stripe\" \u002F>\u003C\u002Fa>\n\n# Supporters\n\n\u003Ctable border=\"0\">\n\u003Ctr>\n\u003Cth align=\"center\">\n\u003Ca href=\"https:\u002F\u002Fsloan.org\u002F\">\u003Cimg src=\"docs\u002Fimg\u002Flogo_sloan.png\" \u002F>\u003C\u002Fa>\n\u003C\u002Fth>\n\u003Cth align=\"center\">\n\u003Ca href=\"https:\u002F\u002Fopensource.fb.com\u002F\">\u003Cimg src=\"docs\u002Fimg\u002Flogo_meta.png\" \u002F>\u003C\u002Fa>\n\u003C\u002Fth>\n\u003Cth align=\"center\">\n\u003Ca href=\"https:\u002F\u002Fpytorch.org\u002F\">\u003Cimg src=\"docs\u002Fimg\u002Flogo_torch.png\" \u002F>\u003C\u002Fa>\n\u003C\u002Fth>\n\u003Cth align=\"center\">\n\u003Ca href=\"https:\u002F\u002Fwww.dpmc.govt.nz\u002F\">\n\u003Cpicture>\n  \u003Csource media=\"(prefers-color-scheme: dark)\" srcset=\"docs\u002Fimg\u002Flogo_nz_dark.png\">\n  \u003Cimg src=\"docs\u002Fimg\u002Flogo_nz_light.png\" \u002F>\n\u003C\u002Fpicture>\n\u003C\u002Fa>\n\u003C\u002Fth>\n\u003Cth align=\"center\">\n\u003Ca href=\"https:\u002F\u002Ftwitter.com\u002F\">\u003Cimg src=\"docs\u002Fimg\u002Flogo_twitter.png\" \u002F>\u003C\u002Fa>\n\u003C\u002Fth>\n\u003Cth align=\"center\">\n\u003Ca href=\"https:\u002F\u002Fgoogle.com\u002F\">\u003Cimg src=\"docs\u002Fimg\u002Flogo_google.png\" \u002F>\u003C\u002Fa>\n\u003C\u002Fth>\n\u003Cth align=\"center\">\n\u003Ca href=\"https:\u002F\u002Fmicrosoft.com\u002F\">\u003Cimg src=\"docs\u002Fimg\u002Flogo_microsoft.png\" \u002F>\u003C\u002Fa>\n\u003C\u002Fth>\n\u003Cth align=\"center\">\n\u003Ca href=\"https:\u002F\u002Fomidyar.com\u002F\">\u003Cimg src=\"docs\u002Fimg\u002Flogo_on.png\" \u002F>\u003C\u002Fa>\n\u003C\u002Fth>\n\u003Cth align=\"center\">\n\u003Ca href=\"https:\u002F\u002Fwww.udacity.com\u002F\">\u003Cimg src=\"docs\u002Fimg\u002Flogo_udacity.png\" \u002F>\u003C\u002Fa>\n\u003C\u002Fth>\n\u003Cth align=\"center\">\n\u003Ca href=\"https:\u002F\u002Fwww.centerfordigitalhealthinnovation.org\u002F\">\n\n\u003Cpicture>\n  \u003Csource media=\"(prefers-color-scheme: dark)\" srcset=\"docs\u002Fimg\u002Flogo_cdhi_dark.png\">\n  \u003Cimg src=\"docs\u002Fimg\u002Flogo_cdhi_light.png\" \u002F>\n\u003C\u002Fpicture>\n\n\u003C\u002Fa>\n\u003C\u002Fth>\n\u003Cth align=\"center\">\n\u003Ca href=\"https:\u002F\u002Farkhn.org\u002F\">\n\u003Cpicture>\n  \u003Csource media=\"(prefers-color-scheme: dark)\" srcset=\"docs\u002Fimg\u002Flogo_arkhn.png\">\n  \u003Cimg src=\"docs\u002Fimg\u002Flogo_arkhn_light.png\" \u002F>\n\u003C\u002Fpicture>\n\u003C\u002Fa>\n\u003C\u002Fth>\n\u003C\u002Ftr>\n\u003C\u002Ftable>\n\n# License\n\n[Apache License 2.0](LICENSE)\u003Cbr \u002F>\n\u003Ca href=\"https:\u002F\u002Fwww.flaticon.com\u002Ffree-icons\u002Fperson\" title=\"person icons\">Person icons created by Freepik - Flaticon\u003C\u002Fa>\n\n\u003C!-- 🥇 -->\n","PySyft 是一个允许在不直接访问数据的情况下进行数据分析和机器学习的Python库。其核心功能是通过连接到Datasite（一种专为数据设计的网站）来执行数据科学任务，而无需实际查看或获取数据副本，从而保障了数据隐私与安全。该项目支持包括深度学习在内的多种统计分析和机器学习模型，并且兼容第三方Python库。PySyft特别适用于需要处理敏感信息但又希望利用这些数据进行研究或开发的应用场景，如医疗健康、金融等领域。此外，它还提供了跨平台支持，包括Linux、macOS、Windows以及Docker和Kubernetes等容器化环境。",2,"2026-06-11 03:24:21","top_topic"]