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go-concurrency-patternsGo 并发模式

Agent Skill

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。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

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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
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openclaw skills install go-concurrency-patterns
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简介

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。

SKILL.md

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

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