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Swift Concurrency 6 2

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xu-xiang
swift-concurrency-6-2

Swift 6.2 可接近的并发性 — 默认单线程,@concurrent 用于显式后台卸载,隔离一致性用于主 actor 类型。

Overview

Publisherxu-xiang
Repositoryeverything-claude-code-zh
Skill nameswift-concurrency-6-2
Stars
2K
Forks
325
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by xu-xiang on GitHub. Read the source before you install it.

Installation

Install the Swift Concurrency 6 2 AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/xu-xiang/everything-claude-code-zh/tree/main/docs/zh-CN/skills/swift-concurrency-6-2
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/xu-xiang/everything-claude-code-zh.git /tmp/everything-claude-code-zh
mkdir -p .claude/skills
cp -r /tmp/everything-claude-code-zh/docs/zh-CN/skills/swift-concurrency-6-2 .claude/skills/swift-concurrency-6-2
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Swift Concurrency 6 2 in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Swift Concurrency 6 2 on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Swift Concurrency 6 2 is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Swift 6.2 可接近的并发

采用 Swift 6.2 并发模型的模式,其中代码默认在单线程上运行,并发是显式引入的。在无需牺牲性能的情况下消除常见的数据竞争错误。

何时启用

  • 将 Swift 5.x 或 6.0/6.1 项目迁移到 Swift 6.2
  • 解决数据竞争安全编译器错误
  • 设计基于 MainActor 的应用架构
  • 将 CPU 密集型工作卸载到后台线程
  • 在 MainActor 隔离的类型上实现协议一致性
  • 在 Xcode 26 中启用“可接近的并发”构建设置

核心问题:隐式的后台卸载

在 Swift 6.1 及更早版本中,异步函数可能会被隐式卸载到后台线程,即使在看似安全的代码中也会导致数据竞争错误:

swift
// Swift 6.1: ERROR
@MainActor
final class StickerModel {
    let photoProcessor = PhotoProcessor()

    func extractSticker(_ item: PhotosPickerItem) async throws -> Sticker? {
        guard let data = try await item.loadTransferable(type: Data.self) else { return nil }

        // Error: Sending 'self.photoProcessor' risks causing data races
        return await photoProcessor.extractSticker(data: data, with: item.itemIdentifier)
    }
}

Swift 6.2 修复了这个问题:异步函数默认保持在调用者所在的 actor 上。

swift
// Swift 6.2: OK — async stays on MainActor, no data race
@MainActor
final class StickerModel {
    let photoProcessor = PhotoProcessor()

    func extractSticker(_ item: PhotosPickerItem) async throws -> Sticker? {
        guard let data = try await item.loadTransferable(type: Data.self) else { return nil }
        return await photoProcessor.extractSticker(data: data, with: item.itemIdentifier)
    }
}

核心模式 — 隔离的一致性

MainActor 类型现在可以安全地符合非隔离协议:

swift
protocol Exportable {
    func export()
}

// Swift 6.1: ERROR — crosses into main actor-isolated code
// Swift 6.2: OK with isolated conformance
extension StickerModel: @MainActor Exportable {
    func export() {
        photoProcessor.exportAsPNG()
    }
}

编译器确保该一致性仅在主 actor 上使用:

swift
// OK — ImageExporter is also @MainActor
@MainActor
struct ImageExporter {
    var items: [any Exportable]

    mutating func add(_ item: StickerModel) {
        items.append(item)  // Safe: same actor isolation
    }
}

// ERROR — nonisolated context can't use MainActor conformance
nonisolated struct ImageExporter {
    var items: [any Exportable]

    mutating func add(_ item: StickerModel) {
        items.append(item)  // Error: Main actor-isolated conformance cannot be used here
    }
}

核心模式 — 全局和静态变量

使用 MainActor 保护全局/静态状态:

swift
// Swift 6.1: ERROR — non-Sendable type may have shared mutable state
final class StickerLibrary {
    static let shared: StickerLibrary = .init()  // Error
}

// Fix: Annotate with @MainActor
@MainActor
final class StickerLibrary {
    static let shared: StickerLibrary = .init()  // OK
}

MainActor 默认推断模式

Swift 6.2 引入了一种模式,默认推断 MainActor — 无需手动标注:

swift
// With MainActor default inference enabled:
final class StickerLibrary {
    static let shared: StickerLibrary = .init()  // Implicitly @MainActor
}

final class StickerModel {
    let photoProcessor: PhotoProcessor
    var selection: [PhotosPickerItem]  // Implicitly @MainActor
}

extension StickerModel: Exportable {  // Implicitly @MainActor conformance
    func export() {
        photoProcessor.exportAsPNG()
    }
}

此模式是选择启用的,推荐用于应用、脚本和其他可执行目标。

核心模式 — 使用 @concurrent 进行后台工作

当需要真正的并行性时,使用 @concurrent 显式卸载:

重要: 此示例需要启用“可接近的并发”构建设置 — SE-0466 (MainActor 默认隔离) 和 SE-0461 (默认非隔离非发送)。启用这些设置后,extractSticker 会保持在调用者所在的 actor 上,使得可变状态的访问变得安全。如果没有这些设置,此代码存在数据竞争 — 编译器会标记它。

swift
nonisolated final class PhotoProcessor {
    private var cachedStickers: [String: Sticker] = [:]

    func extractSticker(data: Data, with id: String) async -> Sticker {
        if let sticker = cachedStickers[id] {
            return sticker
        }

        let sticker = await Self.extractSubject(from: data)
        cachedStickers[id] = sticker
        return sticker
    }

    // Offload expensive work to concurrent thread pool
    @concurrent
    static func extractSubject(from data: Data) async -> Sticker { /* ... */ }
}

// Callers must await
let processor = PhotoProcessor()
processedPhotos[item.id] = await processor.extractSticker(data: data, with: item.id)

要使用 @concurrent:

  1. 将包含类型标记为 nonisolated
  2. 向函数添加 @concurrent
  3. 如果函数还不是异步的,则添加 async
  4. 在调用点添加 await

关键设计决策

决策原理
默认单线程最自然的代码是无数据竞争的;并发是选择启用的
异步函数保持在调用者所在的 actor 上消除了导致数据竞争错误的隐式卸载
隔离的一致性MainActor 类型可以符合协议,而无需不安全的变通方法
@concurrent 显式选择启用后台执行是一种有意的性能选择,而非偶然
MainActor 默认推断减少了应用目标中样板化的 @MainActor 标注
选择启用采用非破坏性的迁移路径 — 逐步启用功能

迁移步骤

  1. 在 Xcode 中启用:构建设置中的 Swift Compiler > Concurrency 部分
  2. 在 SPM 中启用:在包清单中使用 SwiftSettings API
  3. 使用迁移工具:通过 swift.org/migration 进行自动代码更改
  4. 从 MainActor 默认值开始:为应用目标启用推断模式
  5. 在需要的地方添加 @concurrent:先进行性能分析,然后卸载热点路径
  6. 彻底测试:数据竞争问题会变成编译时错误

最佳实践

  • 从 MainActor 开始 — 先编写单线程代码,稍后再优化
  • 仅对 CPU 密集型工作使用 @concurrent — 图像处理、压缩、复杂计算
  • 为主要是单线程的应用目标启用 MainActor 推断模式
  • 在卸载前进行性能分析 — 使用 Instruments 查找实际的瓶颈
  • 使用 MainActor 保护全局变量 — 全局/静态可变状态需要 actor 隔离
  • 使用隔离的一致性,而不是 nonisolated 变通方法或 @Sendable 包装器
  • 增量迁移 — 在构建设置中一次启用一个功能

应避免的反模式

  • 对每个异步函数都应用 @concurrent(大多数不需要后台执行)
  • 在不理解隔离的情况下使用 nonisolated 来抑制编译器错误
  • 当 actor 提供相同安全性时,仍保留遗留的 DispatchQueue 模式
  • 在并发相关的 Foundation Models 代码中跳过 model.availability 检查
  • 与编译器对抗 — 如果它报告数据竞争,代码就存在真正的并发问题
  • 假设所有异步代码都在后台运行(Swift 6.2 默认:保持在调用者所在的 actor 上)

何时使用

  • 所有新的 Swift 6.2+ 项目(“可接近的并发”是推荐的默认设置)
  • 将现有应用从 Swift 5.x 或 6.0/6.1 并发迁移过来
  • 在采用 Xcode 26 期间解决数据竞争安全编译器错误
  • 构建以 MainActor 为中心的应用架构(大多数 UI 应用)
  • 性能优化 — 将特定的繁重计算卸载到后台

Frequently asked questions

What does the Swift Concurrency 6 2 AI skill do?

Swift 6.2 可接近的并发性 — 默认单线程,@concurrent 用于显式后台卸载,隔离一致性用于主 actor 类型。

Why use Swift Concurrency 6 2 on TypingMind?

Because you install it once and use it with any model. Swift Concurrency 6 2 is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Swift Concurrency 6 2 in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/xu-xiang/everything-claude-code-zh/tree/main/docs/zh-CN/skills/swift-concurrency-6-2. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Swift Concurrency 6 2?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Swift Concurrency 6 2?

As many as you like. As long as a model supports skills, you can use Swift Concurrency 6 2 with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Swift Concurrency 6 2 AI skill free?

Yes. It is published on GitHub by xu-xiang under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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