Go Concurrency Patterns

# go-concurrency-patterns — detailed patterns and worked examples

## Patterns

### Pattern 1: Worker Pool

```go
package main

import (
    "context"
    "fmt"
    "sync"
)

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, len(jobs))

    var wg sync.WaitGroup
    for i := 0; i < numWorkers; i++ {
        wg.Add(1)
        go func(workerID int) {
            defer wg.Done()
            for job := range jobs {
                select {
                case <-ctx.Done():
                    return
                default:
                    result := processJob(job)
                    results <- result
                }
            }
        }(i)
    }

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

    return results
}

func processJob(job Job) Result {
    // Simulate work
    return Result{
        JobID:  job.ID,
        Output: fmt.Sprintf("Processed: %s", job.Data),
    }
}

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

    jobs := make(chan Job, 100)

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

    // Process with 5 workers
    results := WorkerPool(ctx, 5, jobs)

    for result := range results {
        fmt.Printf("Result: %+v\n", result)
    }
}
```

### Pattern 2: Fan-Out/Fan-In Pipeline

```go
package main

import (
    "context"
    "sync"
)

// Stage 1: Generate numbers
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: Square numbers (can run multiple instances)
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, cs ...<-chan int) <-chan int {
    var wg sync.WaitGroup
    out := make(chan int)

    // Start output goroutine for each input channel
    output := func(c <-chan int) {
        defer wg.Done()
        for n := range c {
            select {
            case <-ctx.Done():
                return
            case out <- n:
            }
        }
    }

    wg.Add(len(cs))
    for _, c := range cs {
        go output(c)
    }

    // Close out after all inputs are done
    go func() {
        wg.Wait()
        close(out)
    }()

    return out
}

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

    // Generate input
    in := generate(ctx, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10)

    // Fan out to multiple squarers
    c1 := square(ctx, in)
    c2 := square(ctx, in)
    c3 := square(ctx, in)

    // Fan in results
    for result := range merge(ctx, c1, c2, c3) {
        fmt.Println(result)
    }
}
```

### Pattern 3: Bounded Concurrency with Semaphore

```go
package main

import (
    "context"
    "fmt"
    "golang.org/x/sync/semaphore"
    "sync"
)

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 {