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Agent Skill · 开发

go-concurrency-patterns(Go 并发模式)

go-concurrency-patterns 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

go-concurrency-patterns 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 1,675。

总安装 25,368周安装 1,057GitHub Stars 公开资料未说明下载 8,456核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:go-concurrency-patterns(Go 并发模式)
来源仓库:https://github.com/wpank/go-concurrency-patterns
安装命令:
openclaw skills install go-concurrency-patterns
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install go-concurrency-patterns

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

生产 Go 并发模式 — goroutine、通道、同步原语、上下文、工作池、管道和正常关闭。在构建并发 Go 应用程序或调试竞争条件时使用。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install go-concurrency-patterns;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

go-concurrency-patterns 怎么安装?

在终端执行 openclaw skills install go-concurrency-patterns。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

go-concurrency-patterns 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

go-concurrency-patterns 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

go-concurrency-patterns 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

go-concurrency-patterns 用的人多吗?

公开数据是累计安装 25,368 次,近一周安装 1,057 次,下载 8,456 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

go-concurrency-patterns 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
go-concurrency-patterns

Go 并发模式 · 本页

25,368—需要联网MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
go-concurrency
model
standard
description
Production Go concurrency patterns — goroutines, channels, sync primitives, context, worker pools, pipelines, and graceful shutdown. Use when building concurrent Go applications or debugging race conditions.

Go Concurrency Patterns

Production patterns for Go concurrency including goroutines, channels, synchronization primitives, and context management.

When to Use

  • Building concurrent Go applications
  • Implementing worker pools and pipelines
  • Managing goroutine lifecycles and cancellation
  • Debugging race conditions
  • Implementing graceful shutdown

Concurrency Primitives

PrimitivePurposeWhen to Use
goroutineLightweight concurrent executionAny concurrent work
channelCommunication between goroutinesPassing data, signaling
selectMultiplex channel operationsWaiting on multiple channels
sync.MutexMutual exclusionProtecting shared state
sync.WaitGroupWait for goroutines to completeCoordinating goroutine completion
context.ContextCancellation and deadlinesRequest-scoped lifecycle management
errgroup.GroupConcurrent tasks with errorsParallel work that can fail

Go Concurrency Mantra: Don't communicate by sharing memory; share memory by communicating.

Quick Start

func main() {
    ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second)
    defer cancel()

    results := make(chan string, 10)
    var wg sync.WaitGroup

    for i := 0; i < 3; i++ {
        wg.Add(1)
        go func(id int) {
            defer wg.Done()
            select {
            case <-ctx.Done():
                return
            case results <- fmt.Sprintf("Worker %d done", id):
            }
        }(i)
    }

    go func() { wg.Wait(); close(results) }()

    for result := range results {
        fmt.Println(result)
    }
}

Pattern 1: Worker Pool

type Job struct {
    ID   int
    Data string
}

type Result struct {
    JobID  int
    Output string
    Err    error
}

func WorkerPool(ctx context.Context, numWorkers int, jobs <-chan Job) <-chan Result {
    results := make(chan Result)
    var wg sync.WaitGroup

    for i := 0; i < numWorkers; i++ {
        wg.Add(1)
        go func() {
            defer wg.Done()
            for job := range jobs {
                select {
                case <-ctx.Done():
                    return
                default:
                    results <- Result{
                        JobID:  job.ID,
                        Output: fmt.Sprintf("Processed: %s", job.Data),
                    }
                }
            }
        }()
    }

    go func() { wg.Wait(); close(results) }()
    return results
}

// Usage
func main() {
    ctx, cancel := context.WithCancel(context.Background())
    defer cancel()

    jobs := make(chan Job, 100)
    go func() {
        for i := 0; i < 50; i++ {
            jobs <- Job{ID: i, Data: fmt.Sprintf("job-%d", i)}
        }
        close(jobs)
    }()

    for result := range WorkerPool(ctx, 5, jobs) {
        fmt.Printf("Result: %+v\
", result)
    }
}

Pattern 2: Fan-Out / Fan-In Pipeline

// Stage 1: Generate values
func generate(ctx context.Context, nums ...int) <-chan int {
    out := make(chan int)
    go func() {
        defer close(out)
        for _, n := range nums {
            select {
            case <-ctx.Done(): return
            case out <- n:
            }
        }
    }()
    return out
}

// Stage 2: Transform (run multiple instances for fan-out)
func square(ctx context.Context, in <-chan int) <-chan int {
    out := make(chan int)
    go func() {
        defer close(out)
        for n := range in {
            select {
            case <-ctx.Done(): return
            case out <- n * n:
            }
        }
    }()
    return out
}

// Fan-in: Merge multiple channels into one
func merge(ctx context.Context, channels ...<-chan int) <-chan int {
    var wg sync.WaitGroup
    out := make(chan int)

    wg.Add(len(channels))
    for _, ch := range channels {
        go func(c <-chan int) {
            defer wg.Done()
            for n := range c {
                select {
                case <-ctx.Done(): return
                case out <- n:
                }
            }
        }(ch)
    }

    go func() { wg.Wait(); close(out) }()
    return out
}

// Usage: fan out to 3 squarers, fan in results
func main() {
    ctx, cancel := context.WithCancel(context.Background())
    defer cancel()

    in := generate(ctx, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10)
    c1 := square(ctx, in)
    c2 := square(ctx, in)
    c3 := square(ctx, in)

    for result := range merge(ctx, c1, c2, c3) {
        fmt.Println(result)
    }
}

Pattern 3: errgroup with Cancellation

import "golang.org/x/sync/errgroup"

func fetchAllURLs(ctx context.Context, urls []string) ([]string, error) {
    g, ctx := errgroup.WithContext(ctx)
    results := make([]string, len(urls))

    for i, url := range urls {
        i, url := i, url
        g.Go(func() error {
            req, err := http.NewRequestWithContext(ctx, "GET", url, nil)
            if err != nil {
                return fmt.Errorf("creating request for %s: %w", url, err)
            }
            resp, err := http.DefaultClient.Do(req)
            if err != nil {
                return fmt.Errorf("fetching %s: %w", url, err)
            }
            defer resp.Body.Close()
            results[i] = fmt.Sprintf("%s: %d", url, resp.StatusCode)
            return nil
        })
    }

    if err := g.Wait(); err != nil {
        return nil, err // First error cancels all others via ctx
    }
    return results, nil
}

// With concurrency limit
func fetchWithLimit(ctx context.Context, urls []string) ([]string, error) {
    g, ctx := errgroup.WithContext(ctx)
    g.SetLimit(10) // Max concurrent goroutines
    results := make([]string, len(urls))

    for i, url := range urls {
        i, url := i, url
        g.Go(func() error {
            result, err := fetchURL(ctx, url)
            if err != nil { return err }
            results[i] = result
            return nil
        })
    }

    return results, g.Wait()
}

Pattern 4: Bounded Concurrency (Semaphore)

import "golang.org/x/sync/semaphore"

type RateLimitedWorker struct {
    sem *semaphore.Weighted
}

func NewRateLimitedWorker(maxConcurrent int64) *RateLimitedWorker {
    return &RateLimitedWorker{sem: semaphore.NewWeighted(maxConcurrent)}
}

func (w *RateLimitedWorker) Do(ctx context.Context, tasks []func() error) []error {
    var (
        wg     sync.WaitGroup
        mu     sync.Mutex
        errors []error
    )

    for _, task := range tasks {
        if err := w.sem.Acquire(ctx, 1); err != nil {
            return []error{err}
        }
        wg.Add(1)
        go func(t func() error) {
            defer wg.Done()
            defer w.sem.Release(1)
            if err := t(); err != nil {
                mu.Lock()
                errors = append(errors, err)
                mu.Unlock()
            }
        }(task)
    }

    wg.Wait()
    return errors
}

// Simpler alternative: channel-based semaphore
type Semaphore chan struct{}

func NewSemaphore(n int) Semaphore       { return make(chan struct{}, n) }
func (s Semaphore) Acquire()             { s <- struct{}{} }
func (s Semaphore) Release()             { <-s }

Pattern 5: Graceful Shutdown

func main() {
    ctx, cancel := context.WithCancel(context.Background())

    sigCh := make(chan os.Signal, 1)
    signal.Notify(sigCh, syscall.SIGINT, syscall.SIGTERM)

    server := NewServer()
    server.Start(ctx)

    sig := <-sigCh
    fmt.Printf("Received signal: %v\
", sig)
    cancel() // Cancel context to stop all workers

    server.Shutdown(5 * time.Second)
}

type Server struct {
    wg sync.WaitGroup
}

func (s *Server) Start(ctx context.Context) {
    for i := 0; i < 5; i++ {
        s.wg.Add(1)
        go s.worker(ctx, i)
    }
}

func (s *Server) worker(ctx context.Context, id int) {
    defer s.wg.Done()
    ticker := time.NewTicker(time.Second)
    defer ticker.Stop()

    for {
        select {
        case <-ctx.Done():
            fmt.Printf("Worker %d cleaning up...\
", id)
            return
        case <-ticker.C:
            fmt.Printf("Worker %d working...\
", id)
        }
    }
}

func (s *Server) Shutdown(timeout time.Duration) {
    done := make(chan struct{})
    go func() { s.wg.Wait(); close(done) }()

    select {
    case <-done:
        fmt.Println("Clean shutdown completed")
    case <-time.After(timeout):
        fmt.Println("Shutdown timed out, forcing exit")
    }
}

Pattern 6: Concurrent Map

// sync.Map: optimized for read-heavy workloads with stable keys
type Cache struct {
    m sync.Map
}

func (c *Cache) Get(key string) (any, bool) { return c.m.Load(key) }
func (c *Cache) Set(key string, value any) { c.m.Store(key, value) }
func (c *Cache) GetOrSet(key string, val any) (any, bool) {
    return c.m.LoadOrStore(key, val)
}

// ShardedMap: better for write-heavy workloads
type ShardedMap struct {
    shards    []*shard
    numShards int
}

type shard struct {
    sync.RWMutex
    data map[string]any
}

func NewShardedMap(n int) *ShardedMap {
    m := &ShardedMap{shards: make([]*shard, n), numShards: n}
    for i := range m.shards {
        m.shards[i] = &shard{data: make(map[string]any)}
    }
    return m
}

func (m *ShardedMap) getShard(key string) *shard {
    h := 0
    for _, c := range key {
        h = 31*h + int(c)
    }
    return m.shards[h%m.numShards]
}

func (m *ShardedMap) Get(key string) (any, bool) {
    s := m.getShard(key)
    s.RLock()
    defer s.RUnlock()
    v, ok := s.data[key]
    return v, ok
}

func (m *ShardedMap) Set(key string, value any) {
    s := m.getShard(key)
    s.Lock()
    defer s.Unlock()
    s.data[key] = value
}

When to use which:

  • sync.Map — Few keys, many reads, keys added once and rarely deleted
  • ShardedMap — Many keys, frequent writes, need predictable performance

Select Patterns

// Timeout
select {
case v := <-ch:
    fmt.Println("Received:", v)
case <-time.After(time.Second):
    fmt.Println("Timeout!")
}

// Non-blocking send/receive
select {
case ch <- 42:
    fmt.Println("Sent")
default:
    fmt.Println("Channel full, skipping")
}

// Priority select: check high-priority first
for {
    select {
    case msg := <-highPriority:
        handle(msg)
    default:
        select {
        case msg := <-highPriority:
            handle(msg)
        case msg := <-lowPriority:
            handle(msg)
        }
    }
}

Race Detection

go test -race ./...     # Tests with race detector
go build -race .        # Build with race detector
go run -race main.go    # Run with race detector

Best Practices

Do:

  • Use context.Context for cancellation and deadlines on every goroutine
  • Close channels from the sender side only
  • Use errgroup for concurrent operations that return errors
  • Buffer channels when count is known upfront
  • Prefer channels over mutexes for coordination
  • Always run tests with -race

Don't:

  • Leak goroutines — every goroutine must have an exit path
  • Close a channel from the receiver — causes panic
  • Use time.Sleep for synchronization — use proper primitives
  • Ignore ctx.Done() in long-running goroutines
  • Share memory without synchronization — use channels or mutexes

NEVER Do

  • NEVER close a channel from the receiver — Only the sender should close; receivers panic on closed channels
  • NEVER send on a closed channel — Causes panic; design so sender controls close
  • NEVER use unbounded goroutine spawning — Use worker pools or semaphores for bounded concurrency
  • NEVER ignore the -race flag in testing — Data races are silent bugs that corrupt state
  • NEVER pass pointers to loop variables into goroutines — Capture the value or use index closure pattern
  • NEVER use time.Sleep as synchronization — Use channels, WaitGroups, or context

平台分布

OpenClaw

86.3%
按下载量换算7,298

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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