A peer-to-peer cluster actor system implementation for Swift.
NOTE: This project provides a cluster runtime implementation for the distributed actors language feature.
Important: This library is currently released as beta preview software. While we anticipate very few changes, please be mindful that until a stable 1.0 version is announced, this library does not guarantee source compatibility.
We anticipate to release a number of 1.0.0-beta-n
releases during the beta phase of Swift 5.7, before releasing a source stable 1.0 soon after.
Most APIs and runtime are rather stable, and have proven itself for a long time already. Most of the remaining work is around making sure all APIs work nicely with the latest revision of the distributed actor
language feature.
Important: Please ignore and do not use any functionality that is prefixed with an
_
(such as types and methods), as they are intended to be removed as we reach the stable 1.0 release.
Distributed actors are an extension of the "local only" actor model offered by Swift with its actor
keyword.
Distributed actors are declared using the distributed actor
keywords (and importing the Distributed
module),
and enable the declaring of distributed func
methods inside such actor. Such methods may then be invoked remotely,
from other peers in a distributed actor system.
The distributed actor language feature does not include any specific runtime, and only defines the language and semantic rules surrounding distributed actors. This library provides a feature-rich clustering server-side focused implementation of such runtime (i.e. a DistributedActorSystem
implementation) for distributed actors.
To learn more about both the language feature and library, please refer to the reference documentation of this project.
The primary purpose of open sourcing this library early is proving the ability to implement a feature complete, compelling clustering solution using the distributed actor
language feature, and co-evolving the two in tandem.
You can refer to the Samples/
directory to view a number of more realistic sample apps which showcase how distributed actors can be used in a cluster.
The most "classical" example of distributed actors is the SampleDiningPhilosophers
.
You can run it all in a single node (run --package-path Samples/ SampleDiningPhilosophers
), or in 3 cluster nodes hosted on the same physical machine: run --package-path Samples/ SampleDiningPhilosophers distributed
. Notice how one does not need to change implementation of the distributed actors to run them in either "local" or "distributed" mode.
Please refer to the rendered docc reference documentation to learn about distributed actors and how to use this library and its various features.
Note: Documentation is still work in progress, please feel free to submit issues or patches about missing or unclear documentation.
This library requires beta releases of Swift (5.7+) and Xcode to function property as the distributed actor
feature is part of that Swift release.
When developing on macOS, please also make sure to update to the latest beta of macOS, as some parts of the Swift runtime necessary for distributed actors to work are part of the Swift runtime library which is shipped with the OS.
Distributed actors are not back-deployed and require the latest versions of iOS, macOS, watchOS etc.
When developing on Linux systems, you can download the latest Swift 5.7 toolchains from swift.org/downloads, and use it to try out or run the library like this:
$ export TOOLCHAIN=/path/to/toolchain
$ $TOOLCHAIN/usr/bin/swift test
$ $TOOLCHAIN/usr/bin/swift run --package-path Samples/ SampleDiningPhilosophers dist
Latest (beta) Xcode releases include complete support for the distributed
language syntax (distributed actor
, distributed func
), so please use the latest Beta Xcode available to edit the project and any projects using distributed actors.
It is possible to open and edit this project in other IDEs, however most IDEs have not yet caught up with the latest language syntax (i.e. distributed actor
) and therefore may have trouble understanding the new syntax.
VSCode
You can use the Swift Server Work Group maintained VSCode plugin to edit this project from VSCode.
You can install the VSCode extension from here.
The extension uses sourcekit-lsp and thus should be able to highlight and edit distributed actor using sources just fine. If it does not, please report issues!
CLion
The project is possible to open in CLion as a SwiftPM package project, however CLion and AppCode do not yet support the new distributed
syntax, so they might have issues formatting the code until this is implemented.
See also the following guides by community members about using CLion for Swift development:
The project currently is emitting many warnings about Sendable
, this is expected and we are slowly working towards removing them.
Much of the project's internals use advanced synchronization patterns not recognized by sendable checks, so many of the warnings are incorrect but the compiler has no way of knowing this. We will be removing much of these internals as we move them to use the Swift actor runtime instead.
Documentation for this project is using the Doc Compiler, via the SwiftPM DocC plugin.
If you are not familiar with DocC syntax and general style, please refer to its documentation: https://developer.apple.com/documentation/docc
The project includes two helper scripts, to build and preview documentation.
To build documentation:
./scripts/docs/generate_docc.sh
And to preview and browse the documentation as a web-page, run:
./scripts/docs/preview_docc.sh
Which will result in an output similar to this:
========================================
Starting Local Preview Server
http://localhost:8000/documentation/distributecluster
Integration tests include running actual multiple nodes of a cluster and e.g. killing them off to test the recovery mechanisms of the cluster.
Requirements:
brew install coreutils
to install stdbuf
This project requires Swift 5.7+.
字节跳动发布的AI编程神器IDE
Trae是一种自适应的集成开发环境(IDE),通过自动化和多元协作改变开发流程。利用Trae,团队能够更快速、精确地编写和部署代码,从而提高编程效率和项目交付速度。Trae具备上下文感知和代码自动完成功能,是提升开发效率的理想工具。
AI小说写作助手,一站式润色、改写、扩写
蛙蛙写作—国内先进的AI写作平台,涵盖小说、学术、社交媒体等多场景。提供续写、改写、润色等功能,助力创作者高效优化写作流程。界面简洁,功能全面,适合各类写作者提升内容品质和工作效率。
全能AI智能助手,随时解答生活与工作的多样问题
问小白,由元石科技研发的AI智能助手,快速准确地解答各种生活和工作问题,包括但不限于搜 索、规划和社交互动,帮助用户在日常生活中提高效率,轻松管理个人事务。
实时语音翻译/同声传译工具
Transly是一个多场景的AI大语言模型驱动的同声传译、专业翻译助手,它拥有超精准的音频识别翻译能力,几乎零延迟的使用体验和支持多国语言可以让你带它走遍全球,无论你是留学生、商务人士、韩剧美剧爱好者,还是出国游玩、多 国会议、跨国追星等等,都可以满足你所有需要同传的场景需求,线上线下通用,扫除语言障碍,让全世界的语言交流不再有国界。
一键生成PPT和Word,让学习生活更轻松
讯飞智文是一个利用 AI 技术的项目,能够帮助用户生成 PPT 以及各类文档。无论是商业领域的市场分析报告、年度目标制定,还是学生群体的职业生涯规划、实习避坑指南,亦或是活动策划、旅游攻略等内容,它都能提供支持,帮助用户精准表达,轻松呈现各种信息。
深度推理能力全新升级,全面对标OpenAI o1
科大讯飞的星火大模型,支持语言理解、知识问答和文本创作等多功能,适用于多种文件和业务场景,提升办公和日常生活的效率。讯飞星火是一个提供丰富智能服务的平台,涵盖科技 资讯、图像创作、写作辅助、编程解答、科研文献解读等功能,能为不同需求的用户提供便捷高效的帮助,助力用户轻松获取信息、解决问题,满足多样化使用场景。
一种基于大语言模型的高效单流解耦语音令牌文本到语音合成模型
Spark-TTS 是一个基于 PyTorch 的开源文本到语音合成项目,由多个知名机构联合参与。该项目提供了高效的 LLM(大语言模型)驱动的语音合成方案,支持语音克隆和语音创建功能,可通过命令行界面(CLI)和 Web UI 两种方式使用。用户可以根据需求调整语音的性别、音高、速度等参数,生成高质量的语音。该项目适用于多种场景,如有声读物制作、智能语音助手开发等。
AI助力,做PPT更简单!
咔片是一款轻量化在线演示设计工具,借助 AI 技术,实现从内容生成到智能设计的 一站式 PPT 制作服务。支持多种文档格式导入生成 PPT,提供海量模板、智能美化、素材替换等功能,适用于销售、教师、学生等各类人群,能高效制作出高品质 PPT,满足不同场景演示需求。
选题、配图、成文,一站式创作,让内容运营更高效
讯飞绘文,一个AI集成平台,支持写作、选题、配图、排版和发布。高效生成适用于各类媒体的定制内容,加速品牌传播,提升内容营销效果。
专业的AI公文写作平台,公文写作神器
AI 材料星,专业的 AI 公文写作辅助平台,为体制内工作人员提供高效的公文写作解决方案。拥有海量公文文库、9 大核心 AI 功能,支持 30 + 文稿类型生成,助力快速完成领导讲话、工作总结、述职报告等材料,提升办公效率,是体制打工人的得力写作神器。
最新AI工具、AI资讯
独家AI资源、AI项目落地
微信扫一扫关注公众号