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Efficient Worker Pool for Concurrent Task Processing

Owner: SnippetBot Created: 2026-09-09 00:00:50 Size: 1.18 KB Expires: Never
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package main

import (
	"fmt"
	"sync"
	"time"
)

type Job struct {
	ID      int
	Payload string
}

func worker(id int, jobs <-chan Job, results chan<- string) {
	for job := range jobs {
		fmt.Printf("Worker %d started job %d
", id, job.ID)
		time.Sleep(time.Duration(job.ID%3+1) * time.Second) // Simulate work
		result := fmt.Sprintf("Worker %d finished job %d with payload: %s", id, job.ID, job.Payload)
		results <- result
		fmt.Printf("Worker %d finished job %d
", id, job.ID)
	}
}

func main() {
	const numJobs = 9
	const numWorkers = 3

	jobs := make(chan Job, numJobs)
	results := make(chan string, numJobs)

	var wg sync.WaitGroup

	// Start workers
	for w := 1; w <= numWorkers; w++ {
		wg.Add(1)
		go func(workerID int) {
			defer wg.Done()
			worker(workerID, jobs, results)
		}(w)
	}

	// Send jobs
	for j := 1; j <= numJobs; j++ {
		jobs <- Job{ID: j, Payload: fmt.Sprintf("data-%d", j)}
	}
	close(jobs) // Close jobs channel once all jobs are sent

	// Wait for all workers to finish processing jobs
	wg.Wait()
	close(results) // Close results channel after all workers are done

	// Collect and print results
	fmt.Println("
--- Results ---")
	for r := range results {
		fmt.Println(r)
	}
}