Implement a bounded worker pool pattern in Go.

A worker pool limits the number of goroutines working concurrently, preventing resource exhaustion (file handles, DB connections, memory) when processing a large number of tasks. It is one of the most commonly asked Go patterns in technical interviews.

type Job    struct { ID int; Payload string }
type Result struct { JobID int; Output string; Err error }

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

    for w := 0; w < numWorkers; w++ {
        go func() {
            defer wg.Done()
            for {
                select {
                case <-ctx.Done():
                    return
                case job, ok := <-jobs:
                    if !ok { return } // channel closed — all work done
                    out, err := processJob(job)
                    select {
                    case results <- Result{job.ID, out, err}:
                    case <-ctx.Done(): return
                    }
                }
            }
        }()
    }

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

// Usage
ctx, cancel := context.WithTimeout(context.Background(), 60*time.Second)
defer cancel()

jobs := make(chan Job, 100)
go func() {
    defer close(jobs)
    for i, item := range workItems {
        select {
        case jobs <- Job{ID: i, Payload: item}:
        case <-ctx.Done(): return
        }
    }
}()

for r := range workerPool(ctx, jobs, runtime.NumCPU()) {
    if r.Err != nil { log.Printf("job %d failed: %v", r.JobID, r.Err) }
}

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