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Go Concurrency Patterns Series: ← Request/Response | Series Overview | Mutex Patterns → What is the Worker Pool Pattern? The Worker Pool pattern manages a fixed number of worker goroutines that process jobs from a shared queue. This pattern is essential for controlling resource usage, preventing system overload, and ensuring predictable performance under varying loads. Key Components: Job Queue: Channel containing work to be processed Worker Pool: Fixed number of worker goroutines Result Channel: Optional channel for collecting results Dispatcher: Coordinates job distribution to workers Real-World Use Cases Image Processing: Resize/compress images with limited CPU cores Database Operations: Limit concurrent database connections API Rate Limiting: Control outbound API call rates File Processing: Process files with bounded I/O operations Web Scraping: Limit concurrent HTTP requests Background Jobs: Process queued tasks with resource limits Basic Worker Pool Implementation package main import ( "fmt" "math/rand" "sync" "time" ) // Job represents work to be processed type Job struct { ID int Data interface{} } // Result represents the outcome of processing a job type Result struct { JobID int Output interface{} Error error } // WorkerPool manages a pool of workers type WorkerPool struct { workerCount int jobQueue chan Job resultQueue chan Result quit chan bool wg sync.WaitGroup } // NewWorkerPool creates a new worker pool func NewWorkerPool(workerCount, jobQueueSize int) *WorkerPool { return &WorkerPool{ workerCount: workerCount, jobQueue: make(chan Job, jobQueueSize), resultQueue: make(chan Result, jobQueueSize), quit: make(chan bool), } } // Start initializes and starts all workers func (wp *WorkerPool) Start() { for i := 0; i < wp.workerCount; i++ { wp.wg.Add(1) go wp.worker(i) } } // worker processes jobs from the job queue func (wp *WorkerPool) worker(id int) { defer wp.wg.Done() for { select { case job := <-wp.jobQueue: fmt.Printf("Worker %d processing job %d\n", id, job.ID) result := wp.processJob(job) wp.resultQueue <- result case <-wp.quit: fmt.Printf("Worker %d stopping\n", id) return } } } // processJob simulates job processing func (wp *WorkerPool) processJob(job Job) Result { // Simulate work time.Sleep(time.Duration(rand.Intn(100)) * time.Millisecond) // Process the job (example: square the number) if num, ok := job.Data.(int); ok { return Result{ JobID: job.ID, Output: num * num, } } return Result{ JobID: job.ID, Error: fmt.Errorf("invalid job data"), } } // Submit adds a job to the queue func (wp *WorkerPool) Submit(job Job) { wp.jobQueue <- job } // Results returns the result channel func (wp *WorkerPool) Results() <-chan Result { return wp.resultQueue } // Stop gracefully shuts down the worker pool func (wp *WorkerPool) Stop() { close(wp.quit) wp.wg.Wait() close(wp.jobQueue) close(wp.resultQueue) } func main() { // Create worker pool with 3 workers pool := NewWorkerPool(3, 10) pool.Start() defer pool.Stop() // Submit jobs go func() { for i := 1; i <= 10; i++ { job := Job{ ID: i, Data: i * 10, } pool.Submit(job) } }() // Collect results for i := 0; i < 10; i++ { result := <-pool.Results() if result.Error != nil { fmt.Printf("Job %d failed: %v\n", result.JobID, result.Error) } else { fmt.Printf("Job %d result: %v\n", result.JobID, result.Output) } } } Advanced Worker Pool with Context package main import ( "context" "fmt" "sync" "time" ) // ContextJob includes context for cancellation type ContextJob struct { ID string Data interface{} Context context.Context } // ContextResult includes timing and context information type ContextResult struct { JobID string Output interface{} Error error Duration time.Duration WorkerID int } // AdvancedWorkerPool supports context cancellation and monitoring type AdvancedWorkerPool struct { workerCount int jobQueue chan ContextJob resultQueue chan ContextResult ctx context.Context cancel context.CancelFunc wg sync.WaitGroup metrics *PoolMetrics } // PoolMetrics tracks worker pool performance type PoolMetrics struct { mu sync.RWMutex jobsProcessed int64 jobsFailed int64 totalDuration time.Duration activeWorkers int } func (pm *PoolMetrics) RecordJob(duration time.Duration, success bool) { pm.mu.Lock() defer pm.mu.Unlock() if success { pm.jobsProcessed++ } else { pm.jobsFailed++ } pm.totalDuration += duration } func (pm *PoolMetrics) SetActiveWorkers(count int) { pm.mu.Lock() defer pm.mu.Unlock() pm.activeWorkers = count } func (pm *PoolMetrics) GetStats() (processed, failed int64, avgDuration time.Duration, active int) { pm.mu.RLock() defer pm.mu.RUnlock() processed = pm.jobsProcessed failed = pm.jobsFailed active = pm.activeWorkers if pm.jobsProcessed > 0 { avgDuration = pm.totalDuration / time.Duration(pm.jobsProcessed) } return } // NewAdvancedWorkerPool creates a new advanced worker pool func NewAdvancedWorkerPool(ctx context.Context, workerCount, queueSize int) *AdvancedWorkerPool { poolCtx, cancel := context.WithCancel(ctx) return &AdvancedWorkerPool{ workerCount: workerCount, jobQueue: make(chan ContextJob, queueSize), resultQueue: make(chan ContextResult, queueSize), ctx: poolCtx, cancel: cancel, metrics: &PoolMetrics{}, } } // Start begins processing with all workers func (awp *AdvancedWorkerPool) Start() { awp.metrics.SetActiveWorkers(awp.workerCount) for i := 0; i < awp.workerCount; i++ { awp.wg.Add(1) go awp.worker(i) } // Start metrics reporter go awp.reportMetrics() } // worker processes jobs with context support func (awp *AdvancedWorkerPool) worker(id int) { defer awp.wg.Done() for { select { case job := <-awp.jobQueue: start := time.Now() result := awp.processContextJob(job, id) duration := time.Since(start) awp.metrics.RecordJob(duration, result.Error == nil) select { case awp.resultQueue <- result: case <-awp.ctx.Done(): return } case <-awp.ctx.Done(): fmt.Printf("Worker %d shutting down\n", id) return } } } // processContextJob handles job processing with context func (awp *AdvancedWorkerPool) processContextJob(job ContextJob, workerID int) ContextResult { start := time.Now() // Check if job context is already cancelled select { case <-job.Context.Done(): return ContextResult{ JobID: job.ID, Error: job.Context.Err(), Duration: time.Since(start), WorkerID: workerID, } default: } // Simulate work that respects context cancellation workDone := make(chan interface{}, 1) workErr := make(chan error, 1) go func() { // Simulate processing time time.Sleep(time.Duration(50+rand.Intn(100)) * time.Millisecond) if num, ok := job.Data.(int); ok { workDone <- num * num } else { workErr <- fmt.Errorf("invalid data type") } }() select { case result := <-workDone: return ContextResult{ JobID: job.ID, Output: result, Duration: time.Since(start), WorkerID: workerID, } case err := <-workErr: return ContextResult{ JobID: job.ID, Error: err, Duration: time.Since(start), WorkerID: workerID, } case <-job.Context.Done(): return ContextResult{ JobID: job.ID, Error: job.Context.Err(), Duration: time.Since(start), WorkerID: workerID, } case <-awp.ctx.Done(): return ContextResult{ JobID: job.ID, Error: awp.ctx.Err(), Duration: time.Since(start), WorkerID: workerID, } } } // Submit adds a job to the queue func (awp *AdvancedWorkerPool) Submit(job ContextJob) error { select { case awp.jobQueue <- job: return nil case <-awp.ctx.Done(): return awp.ctx.Err() } } // Results returns the result channel func (awp *AdvancedWorkerPool) Results() <-chan ContextResult { return awp.resultQueue } // reportMetrics periodically reports pool statistics func (awp *AdvancedWorkerPool) reportMetrics() { ticker := time.NewTicker(2 * time.Second) defer ticker.Stop() for { select { case <-ticker.C: processed, failed, avgDuration, active := awp.metrics.GetStats() fmt.Printf("Pool Stats - Processed: %d, Failed: %d, Avg Duration: %v, Active Workers: %d\n", processed, failed, avgDuration, active) case <-awp.ctx.Done(): return } } } // Stop gracefully shuts down the worker pool func (awp *AdvancedWorkerPool) Stop() { awp.cancel() awp.wg.Wait() close(awp.jobQueue) close(awp.resultQueue) } func main() { ctx, cancel := context.WithTimeout(context.Background(), 10*time.Second) defer cancel() pool := NewAdvancedWorkerPool(ctx, 4, 20) pool.Start() defer pool.Stop() // Submit jobs with individual timeouts go func() { for i := 1; i <= 15; i++ { jobCtx, jobCancel := context.WithTimeout(ctx, 200*time.Millisecond) job := ContextJob{ ID: fmt.Sprintf("job-%d", i), Data: i * 5, Context: jobCtx, } if err := pool.Submit(job); err != nil { fmt.Printf("Failed to submit job %d: %v\n", i, err) jobCancel() break } // Cancel some jobs early to demonstrate cancellation if i%5 == 0 { go func() { time.Sleep(50 * time.Millisecond) jobCancel() }() } else { defer jobCancel() } } }() // Collect results resultCount := 0 for result := range pool.Results() { resultCount++ if result.Error != nil { fmt.Printf("Job %s failed (worker %d): %v (took %v)\n", result.JobID, result.WorkerID, result.Error, result.Duration) } else { fmt.Printf("Job %s completed (worker %d): %v (took %v)\n", result.JobID, result.WorkerID, result.Output, result.Duration) } if resultCount >= 15 { break } } } Dynamic Worker Pool package main import ( "context" "fmt" "sync" "sync/atomic" "time" ) // DynamicWorkerPool can scale workers up and down based on load type DynamicWorkerPool struct { minWorkers int maxWorkers int currentWorkers int64 jobQueue chan Job resultQueue chan Result ctx context.Context cancel context.CancelFunc wg sync.WaitGroup workerControl chan int // +1 to add worker, -1 to remove worker metrics *DynamicMetrics } // DynamicMetrics tracks load and performance for scaling decisions type DynamicMetrics struct { mu sync.RWMutex queueLength int64 avgProcessingTime time.Duration lastScaleTime time.Time scaleUpThreshold int scaleDownThreshold int } func (dm *DynamicMetrics) UpdateQueueLength(length int) { atomic.StoreInt64(&dm.queueLength, int64(length)) } func (dm *DynamicMetrics) GetQueueLength() int { return int(atomic.LoadInt64(&dm.queueLength)) } func (dm *DynamicMetrics) ShouldScaleUp(currentWorkers int, maxWorkers int) bool { dm.mu.RLock() defer dm.mu.RUnlock() return currentWorkers < maxWorkers && dm.GetQueueLength() > dm.scaleUpThreshold && time.Since(dm.lastScaleTime) > 5*time.Second } func (dm *DynamicMetrics) ShouldScaleDown(currentWorkers int, minWorkers int) bool { dm.mu.RLock() defer dm.mu.RUnlock() return currentWorkers > minWorkers && dm.GetQueueLength() < dm.scaleDownThreshold && time.Since(dm.lastScaleTime) > 10*time.Second } func (dm *DynamicMetrics) RecordScale() { dm.mu.Lock() defer dm.mu.Unlock() dm.lastScaleTime = time.Now() } // NewDynamicWorkerPool creates a new dynamic worker pool func NewDynamicWorkerPool(ctx context.Context, minWorkers, maxWorkers, queueSize int) *DynamicWorkerPool { poolCtx, cancel := context.WithCancel(ctx) return &DynamicWorkerPool{ minWorkers: minWorkers, maxWorkers: maxWorkers, currentWorkers: 0, jobQueue: make(chan Job, queueSize), resultQueue: make(chan Result, queueSize), ctx: poolCtx, cancel: cancel, workerControl: make(chan int, maxWorkers), metrics: &DynamicMetrics{ scaleUpThreshold: queueSize / 2, scaleDownThreshold: queueSize / 4, }, } } // Start initializes the pool with minimum workers func (dwp *DynamicWorkerPool) Start() { // Start with minimum workers for i := 0; i < dwp.minWorkers; i++ { dwp.addWorker() } // Start the scaler go dwp.scaler() // Start queue monitor go dwp.queueMonitor() } // addWorker creates and starts a new worker func (dwp *DynamicWorkerPool) addWorker() { workerID := atomic.AddInt64(&dwp.currentWorkers, 1) dwp.wg.Add(1) go func(id int64) { defer dwp.wg.Done() defer atomic.AddInt64(&dwp.currentWorkers, -1) fmt.Printf("Worker %d started\n", id) for { select { case job := <-dwp.jobQueue: start := time.Now() result := dwp.processJob(job) duration := time.Since(start) fmt.Printf("Worker %d processed job %d in %v\n", id, job.ID, duration) select { case dwp.resultQueue <- result: case <-dwp.ctx.Done(): return } case <-dwp.ctx.Done(): fmt.Printf("Worker %d stopping\n", id) return } } }(workerID) } // processJob simulates job processing func (dwp *DynamicWorkerPool) processJob(job Job) Result { // Simulate variable processing time time.Sleep(time.Duration(50+rand.Intn(200)) * time.Millisecond) if num, ok := job.Data.(int); ok { return Result{ JobID: job.ID, Output: num * 2, } } return Result{ JobID: job.ID, Error: fmt.Errorf("invalid job data"), } } // scaler monitors load and adjusts worker count func (dwp *DynamicWorkerPool) scaler() { ticker := time.NewTicker(3 * time.Second) defer ticker.Stop() for { select { case <-ticker.C: currentWorkers := int(atomic.LoadInt64(&dwp.currentWorkers)) queueLength := dwp.metrics.GetQueueLength() fmt.Printf("Scaler check - Workers: %d, Queue: %d\n", currentWorkers, queueLength) if dwp.metrics.ShouldScaleUp(currentWorkers, dwp.maxWorkers) { fmt.Printf("Scaling up: adding worker (current: %d)\n", currentWorkers) dwp.addWorker() dwp.metrics.RecordScale() } else if dwp.metrics.ShouldScaleDown(currentWorkers, dwp.minWorkers) { fmt.Printf("Scaling down: removing worker (current: %d)\n", currentWorkers) // Signal one worker to stop by closing context // In a real implementation, you might use a more sophisticated approach dwp.metrics.RecordScale() } case <-dwp.ctx.Done(): return } } } // queueMonitor tracks queue length for scaling decisions func (dwp *DynamicWorkerPool) queueMonitor() { ticker := time.NewTicker(1 * time.Second) defer ticker.Stop() for { select { case <-ticker.C: queueLength := len(dwp.jobQueue) dwp.metrics.UpdateQueueLength(queueLength) case <-dwp.ctx.Done(): return } } } // Submit adds a job to the queue func (dwp *DynamicWorkerPool) Submit(job Job) error { select { case dwp.jobQueue <- job: return nil case <-dwp.ctx.Done(): return dwp.ctx.Err() } } // Results returns the result channel func (dwp *DynamicWorkerPool) Results() <-chan Result { return dwp.resultQueue } // Stop gracefully shuts down the pool func (dwp *DynamicWorkerPool) Stop() { dwp.cancel() dwp.wg.Wait() close(dwp.jobQueue) close(dwp.resultQueue) } func main() { ctx, cancel := context.WithTimeout(context.Background(), 30*time.Second) defer cancel() pool := NewDynamicWorkerPool(ctx, 2, 6, 20) pool.Start() defer pool.Stop() // Submit jobs in bursts to trigger scaling go func() { // Initial burst for i := 1; i <= 10; i++ { job := Job{ID: i, Data: i * 10} if err := pool.Submit(job); err != nil { fmt.Printf("Failed to submit job %d: %v\n", i, err) break } } time.Sleep(8 * time.Second) // Second burst for i := 11; i <= 25; i++ { job := Job{ID: i, Data: i * 10} if err := pool.Submit(job); err != nil { fmt.Printf("Failed to submit job %d: %v\n", i, err) break } } time.Sleep(5 * time.Second) // Final smaller batch for i := 26; i <= 30; i++ { job := Job{ID: i, Data: i * 10} if err := pool.Submit(job); err != nil { fmt.Printf("Failed to submit job %d: %v\n", i, err) break } } }() // Collect results resultCount := 0 for result := range pool.Results() { resultCount++ if result.Error != nil { fmt.Printf("Job %d failed: %v\n", result.JobID, result.Error) } else { fmt.Printf("Job %d completed: %v\n", result.JobID, result.Output) } if resultCount >= 30 { break } } } Best Practices Right-Size the Pool: Match worker count to available resources Monitor Performance: Track queue length, processing times, and throughput Handle Backpressure: Implement proper queue management Graceful Shutdown: Ensure all workers complete current jobs Error Handling: Isolate worker failures from the pool Resource Cleanup: Properly close channels and cancel contexts Load Balancing: Distribute work evenly across workers Common Pitfalls Too Many Workers: Creating more workers than CPU cores for CPU-bound tasks Unbounded Queues: Memory issues with unlimited job queues Worker Leaks: Not properly shutting down workers Blocking Operations: Long-running jobs blocking other work No Backpressure: Not handling queue overflow situations Testing Worker Pools package main import ( "context" "testing" "time" ) func TestWorkerPool(t *testing.T) { ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second) defer cancel() pool := NewAdvancedWorkerPool(ctx, 2, 5) pool.Start() defer pool.Stop() // Submit test jobs jobCount := 5 for i := 1; i <= jobCount; i++ { job := ContextJob{ ID: fmt.Sprintf("test-%d", i), Data: i, Context: ctx, } if err := pool.Submit(job); err != nil { t.Fatalf("Failed to submit job: %v", err) } } // Collect results results := make(map[string]ContextResult) for i := 0; i < jobCount; i++ { select { case result := <-pool.Results(): results[result.JobID] = result case <-time.After(2 * time.Second): t.Fatal("Timeout waiting for results") } } // Verify all jobs completed if len(results) != jobCount { t.Errorf("Expected %d results, got %d", jobCount, len(results)) } // Verify results are correct for i := 1; i <= jobCount; i++ { jobID := fmt.Sprintf("test-%d", i) result, exists := results[jobID] if !exists { t.Errorf("Missing result for job %s", jobID) continue } if result.Error != nil { t.Errorf("Job %s failed: %v", jobID, result.Error) continue } expected := i * i if result.Output != expected { t.Errorf("Job %s: expected %d, got %v", jobID, expected, result.Output) } } } The Worker Pool pattern is essential for building scalable, resource-efficient concurrent applications in Go. It provides controlled concurrency, predictable resource usage, and excellent performance characteristics for both CPU-bound and I/O-bound workloads. ...

Go Concurrency Patterns Series: ← Mutex Patterns | Series Overview | Once Pattern → What is the WaitGroup Pattern? The WaitGroup pattern uses sync.WaitGroup to coordinate the completion of multiple goroutines. It acts as a counter that blocks until all registered goroutines have finished executing, making it perfect for implementing barriers and waiting for parallel tasks to complete. Key Operations: Add(n): Increment the counter by n Done(): Decrement the counter by 1 (usually called with defer) Wait(): Block until counter reaches zero Real-World Use Cases Parallel Processing: Wait for all workers to complete Batch Operations: Process multiple items concurrently Service Initialization: Wait for all services to start Data Collection: Gather results from multiple sources Cleanup Operations: Ensure all cleanup tasks finish Testing: Coordinate test goroutines Basic WaitGroup Usage package main import ( "fmt" "math/rand" "sync" "time" ) // Task represents work to be done type Task struct { ID int Name string } // processTask simulates processing a task func processTask(task Task, wg *sync.WaitGroup) { defer wg.Done() // Always call Done when goroutine finishes fmt.Printf("Starting task %d: %s\n", task.ID, task.Name) // Simulate work duration := time.Duration(rand.Intn(1000)) * time.Millisecond time.Sleep(duration) fmt.Printf("Completed task %d: %s (took %v)\n", task.ID, task.Name, duration) } func main() { tasks := []Task{ {1, "Process images"}, {2, "Send emails"}, {3, "Update database"}, {4, "Generate reports"}, {5, "Backup files"}, } var wg sync.WaitGroup fmt.Println("Starting parallel task processing...") // Start all tasks for _, task := range tasks { wg.Add(1) // Increment counter for each goroutine go processTask(task, &wg) } // Wait for all tasks to complete wg.Wait() fmt.Println("All tasks completed!") } WaitGroup with Error Handling package main import ( "fmt" "math/rand" "sync" "time" ) // Result represents the outcome of a task type Result struct { TaskID int Data interface{} Error error } // TaskProcessor handles tasks with error collection type TaskProcessor struct { wg sync.WaitGroup results chan Result errors []error mu sync.Mutex } // NewTaskProcessor creates a new task processor func NewTaskProcessor(bufferSize int) *TaskProcessor { return &TaskProcessor{ results: make(chan Result, bufferSize), } } // processTaskWithError simulates task processing that might fail func (tp *TaskProcessor) processTaskWithError(taskID int, data interface{}) { defer tp.wg.Done() fmt.Printf("Processing task %d\n", taskID) // Simulate work time.Sleep(time.Duration(rand.Intn(500)) * time.Millisecond) // Simulate random failures if rand.Float32() < 0.3 { err := fmt.Errorf("task %d failed", taskID) tp.results <- Result{TaskID: taskID, Error: err} // Collect error tp.mu.Lock() tp.errors = append(tp.errors, err) tp.mu.Unlock() fmt.Printf("Task %d failed\n", taskID) return } // Success result := fmt.Sprintf("Result from task %d", taskID) tp.results <- Result{TaskID: taskID, Data: result} fmt.Printf("Task %d completed successfully\n", taskID) } // ProcessTasks processes multiple tasks and collects results func (tp *TaskProcessor) ProcessTasks(taskCount int) ([]Result, []error) { // Start all tasks for i := 1; i <= taskCount; i++ { tp.wg.Add(1) go tp.processTaskWithError(i, fmt.Sprintf("data-%d", i)) } // Close results channel when all tasks complete go func() { tp.wg.Wait() close(tp.results) }() // Collect results var results []Result for result := range tp.results { results = append(results, result) } tp.mu.Lock() errors := make([]error, len(tp.errors)) copy(errors, tp.errors) tp.mu.Unlock() return results, errors } func main() { processor := NewTaskProcessor(10) fmt.Println("Starting task processing with error handling...") results, errors := processor.ProcessTasks(8) fmt.Printf("\nProcessing complete!\n") fmt.Printf("Successful tasks: %d\n", len(results)-len(errors)) fmt.Printf("Failed tasks: %d\n", len(errors)) if len(errors) > 0 { fmt.Println("\nErrors:") for _, err := range errors { fmt.Printf(" - %v\n", err) } } fmt.Println("\nResults:") for _, result := range results { if result.Error == nil { fmt.Printf(" Task %d: %v\n", result.TaskID, result.Data) } } } Nested WaitGroups for Hierarchical Tasks package main import ( "fmt" "sync" "time" ) // Department represents a department with multiple teams type Department struct { Name string Teams []Team } // Team represents a team with multiple workers type Team struct { Name string Workers []string } // processDepartment processes all teams in a department func processDepartment(dept Department, wg *sync.WaitGroup) { defer wg.Done() fmt.Printf("Department %s starting work\n", dept.Name) var teamWG sync.WaitGroup // Process all teams in parallel for _, team := range dept.Teams { teamWG.Add(1) go processTeam(team, &teamWG) } // Wait for all teams to complete teamWG.Wait() fmt.Printf("Department %s completed all work\n", dept.Name) } // processTeam processes all workers in a team func processTeam(team Team, wg *sync.WaitGroup) { defer wg.Done() fmt.Printf(" Team %s starting work\n", team.Name) var workerWG sync.WaitGroup // Process all workers in parallel for _, worker := range team.Workers { workerWG.Add(1) go processWorker(worker, &workerWG) } // Wait for all workers to complete workerWG.Wait() fmt.Printf(" Team %s completed all work\n", team.Name) } // processWorker simulates worker processing func processWorker(worker string, wg *sync.WaitGroup) { defer wg.Done() fmt.Printf(" Worker %s working...\n", worker) time.Sleep(time.Duration(100+rand.Intn(200)) * time.Millisecond) fmt.Printf(" Worker %s finished\n", worker) } func main() { departments := []Department{ { Name: "Engineering", Teams: []Team{ { Name: "Backend", Workers: []string{"Alice", "Bob", "Charlie"}, }, { Name: "Frontend", Workers: []string{"Diana", "Eve"}, }, }, }, { Name: "Marketing", Teams: []Team{ { Name: "Digital", Workers: []string{"Frank", "Grace"}, }, { Name: "Content", Workers: []string{"Henry", "Ivy", "Jack"}, }, }, }, } var deptWG sync.WaitGroup fmt.Println("Starting company-wide project...") // Process all departments in parallel for _, dept := range departments { deptWG.Add(1) go processDepartment(dept, &deptWG) } // Wait for all departments to complete deptWG.Wait() fmt.Println("Company-wide project completed!") } WaitGroup with Timeout package main import ( "context" "fmt" "sync" "time" ) // TimedTaskRunner runs tasks with timeout support type TimedTaskRunner struct { timeout time.Duration } // NewTimedTaskRunner creates a new timed task runner func NewTimedTaskRunner(timeout time.Duration) *TimedTaskRunner { return &TimedTaskRunner{timeout: timeout} } // RunWithTimeout runs tasks with a timeout func (ttr *TimedTaskRunner) RunWithTimeout(tasks []func()) error { ctx, cancel := context.WithTimeout(context.Background(), ttr.timeout) defer cancel() var wg sync.WaitGroup done := make(chan struct{}) // Start all tasks for i, task := range tasks { wg.Add(1) go func(taskID int, taskFunc func()) { defer wg.Done() fmt.Printf("Starting task %d\n", taskID) taskFunc() fmt.Printf("Completed task %d\n", taskID) }(i+1, task) } // Wait for completion in separate goroutine go func() { wg.Wait() close(done) }() // Wait for either completion or timeout select { case <-done: fmt.Println("All tasks completed successfully") return nil case <-ctx.Done(): fmt.Println("Tasks timed out") return ctx.Err() } } // simulateTask creates a task that takes a specific duration func simulateTask(duration time.Duration, name string) func() { return func() { fmt.Printf(" %s working for %v\n", name, duration) time.Sleep(duration) fmt.Printf(" %s finished\n", name) } } func main() { runner := NewTimedTaskRunner(2 * time.Second) // Test with tasks that complete within timeout fmt.Println("Test 1: Tasks that complete within timeout") tasks1 := []func(){ simulateTask(300*time.Millisecond, "Quick task 1"), simulateTask(500*time.Millisecond, "Quick task 2"), simulateTask(400*time.Millisecond, "Quick task 3"), } if err := runner.RunWithTimeout(tasks1); err != nil { fmt.Printf("Error: %v\n", err) } fmt.Println("\nTest 2: Tasks that exceed timeout") tasks2 := []func(){ simulateTask(800*time.Millisecond, "Slow task 1"), simulateTask(1500*time.Millisecond, "Slow task 2"), simulateTask(2000*time.Millisecond, "Very slow task"), } if err := runner.RunWithTimeout(tasks2); err != nil { fmt.Printf("Error: %v\n", err) } } Dynamic WaitGroup Management package main import ( "fmt" "sync" "time" ) // DynamicTaskManager manages tasks that can spawn other tasks type DynamicTaskManager struct { wg sync.WaitGroup taskChan chan func() quit chan struct{} active sync.WaitGroup } // NewDynamicTaskManager creates a new dynamic task manager func NewDynamicTaskManager() *DynamicTaskManager { return &DynamicTaskManager{ taskChan: make(chan func(), 100), quit: make(chan struct{}), } } // Start begins processing tasks func (dtm *DynamicTaskManager) Start() { go dtm.taskProcessor() } // taskProcessor processes tasks from the channel func (dtm *DynamicTaskManager) taskProcessor() { for { select { case task := <-dtm.taskChan: dtm.active.Add(1) go func() { defer dtm.active.Done() task() }() case <-dtm.quit: return } } } // AddTask adds a task to be processed func (dtm *DynamicTaskManager) AddTask(task func()) { select { case dtm.taskChan <- task: case <-dtm.quit: } } // Wait waits for all active tasks to complete func (dtm *DynamicTaskManager) Wait() { dtm.active.Wait() } // Stop stops the task manager func (dtm *DynamicTaskManager) Stop() { close(dtm.quit) dtm.Wait() } // recursiveTask demonstrates a task that spawns other tasks func recursiveTask(manager *DynamicTaskManager, depth int, maxDepth int, id string) func() { return func() { fmt.Printf("Task %s (depth %d) starting\n", id, depth) time.Sleep(100 * time.Millisecond) if depth < maxDepth { // Spawn child tasks for i := 0; i < 2; i++ { childID := fmt.Sprintf("%s.%d", id, i+1) manager.AddTask(recursiveTask(manager, depth+1, maxDepth, childID)) } } fmt.Printf("Task %s (depth %d) completed\n", id, depth) } } func main() { manager := NewDynamicTaskManager() manager.Start() defer manager.Stop() fmt.Println("Starting dynamic task processing...") // Add initial tasks that will spawn more tasks for i := 0; i < 3; i++ { taskID := fmt.Sprintf("root-%d", i+1) manager.AddTask(recursiveTask(manager, 0, 2, taskID)) } // Wait for all tasks (including dynamically created ones) to complete manager.Wait() fmt.Println("All tasks completed!") } Best Practices Always Use defer: Call Done() with defer to ensure it’s called even if panic occurs Add Before Starting: Call Add() before starting goroutines to avoid race conditions Don’t Reuse WaitGroups: Create new WaitGroup for each batch of operations Handle Panics: Use recover in goroutines to prevent panic from affecting WaitGroup Avoid Negative Counters: Don’t call Done() more times than Add() Use Timeouts: Combine with context for timeout handling Consider Alternatives: Use channels for complex coordination scenarios Common Pitfalls 1. Race Condition with Add/Done // Bad: Race condition func badExample() { var wg sync.WaitGroup for i := 0; i < 5; i++ { go func() { wg.Add(1) // Race: might be called after Wait() defer wg.Done() // do work }() } wg.Wait() // Might not wait for all goroutines } // Good: Add before starting goroutines func goodExample() { var wg sync.WaitGroup for i := 0; i < 5; i++ { wg.Add(1) // Add before starting goroutine go func() { defer wg.Done() // do work }() } wg.Wait() } 2. Forgetting to Call Done // Bad: Missing Done() call func badTask(wg *sync.WaitGroup) { // do work if someCondition { return // Forgot to call Done()! } wg.Done() } // Good: Always use defer func goodTask(wg *sync.WaitGroup) { defer wg.Done() // Always called // do work if someCondition { return // Done() still called } } Testing WaitGroup Patterns package main import ( "sync" "testing" "time" ) func TestWaitGroupCompletion(t *testing.T) { var wg sync.WaitGroup completed := make([]bool, 5) for i := 0; i < 5; i++ { wg.Add(1) go func(index int) { defer wg.Done() time.Sleep(10 * time.Millisecond) completed[index] = true }(i) } wg.Wait() // Verify all tasks completed for i, done := range completed { if !done { t.Errorf("Task %d did not complete", i) } } } func TestWaitGroupWithTimeout(t *testing.T) { var wg sync.WaitGroup done := make(chan struct{}) wg.Add(1) go func() { defer wg.Done() time.Sleep(50 * time.Millisecond) }() go func() { wg.Wait() close(done) }() select { case <-done: // Success case <-time.After(100 * time.Millisecond): t.Error("WaitGroup did not complete within timeout") } } The WaitGroup pattern is essential for coordinating goroutines in Go. It provides a simple yet powerful way to wait for multiple concurrent operations to complete, making it perfect for parallel processing, batch operations, and synchronization barriers. ...

Go Concurrency Patterns Series: ← Rate Limiter | Series Overview | Actor Model → What is the Semaphore Pattern? A semaphore is a synchronization primitive that maintains a count of available resources and controls access to them. It allows a specified number of goroutines to access a resource concurrently while blocking others until resources become available. Types: Binary Semaphore: Acts like a mutex (0 or 1) Counting Semaphore: Allows N concurrent accesses Weighted Semaphore: Resources have different weights/costs Real-World Use Cases Connection Pools: Limit database/HTTP connections Resource Management: Control access to limited resources Download Managers: Limit concurrent downloads API Rate Limiting: Control concurrent API calls Worker Pools: Limit concurrent workers Memory Management: Control memory-intensive operations Basic Semaphore Implementation package main import ( "context" "fmt" "sync" "time" ) // Semaphore implements a counting semaphore type Semaphore struct { ch chan struct{} } // NewSemaphore creates a new semaphore with given capacity func NewSemaphore(capacity int) *Semaphore { return &Semaphore{ ch: make(chan struct{}, capacity), } } // Acquire acquires a resource from the semaphore func (s *Semaphore) Acquire() { s.ch <- struct{}{} } // TryAcquire tries to acquire a resource without blocking func (s *Semaphore) TryAcquire() bool { select { case s.ch <- struct{}{}: return true default: return false } } // AcquireWithContext acquires a resource with context cancellation func (s *Semaphore) AcquireWithContext(ctx context.Context) error { select { case s.ch <- struct{}{}: return nil case <-ctx.Done(): return ctx.Err() } } // Release releases a resource back to the semaphore func (s *Semaphore) Release() { <-s.ch } // Available returns the number of available resources func (s *Semaphore) Available() int { return cap(s.ch) - len(s.ch) } // Used returns the number of used resources func (s *Semaphore) Used() int { return len(s.ch) } // Capacity returns the total capacity func (s *Semaphore) Capacity() int { return cap(s.ch) } // simulateWork simulates work that requires a resource func simulateWork(id int, duration time.Duration, sem *Semaphore) { fmt.Printf("Worker %d: Requesting resource...\n", id) sem.Acquire() fmt.Printf("Worker %d: Acquired resource (available: %d/%d)\n", id, sem.Available(), sem.Capacity()) // Simulate work time.Sleep(duration) sem.Release() fmt.Printf("Worker %d: Released resource (available: %d/%d)\n", id, sem.Available(), sem.Capacity()) } func main() { // Create semaphore with capacity of 3 sem := NewSemaphore(3) fmt.Println("=== Basic Semaphore Demo ===") fmt.Printf("Semaphore capacity: %d\n\n", sem.Capacity()) var wg sync.WaitGroup // Start 6 workers, but only 3 can work concurrently for i := 1; i <= 6; i++ { wg.Add(1) go func(id int) { defer wg.Done() simulateWork(id, time.Duration(1+id%3)*time.Second, sem) }(i) time.Sleep(200 * time.Millisecond) // Stagger starts } wg.Wait() fmt.Printf("\nFinal state - Available: %d/%d\n", sem.Available(), sem.Capacity()) } Advanced Semaphore with Timeout and Context package main import ( "context" "fmt" "sync" "sync/atomic" "time" ) // AdvancedSemaphore provides additional features like metrics and timeouts type AdvancedSemaphore struct { ch chan struct{} capacity int // Metrics totalAcquires int64 totalReleases int64 timeouts int64 cancellations int64 // Monitoring mu sync.RWMutex waitingGoroutines int } // NewAdvancedSemaphore creates a new advanced semaphore func NewAdvancedSemaphore(capacity int) *AdvancedSemaphore { return &AdvancedSemaphore{ ch: make(chan struct{}, capacity), capacity: capacity, } } // Acquire acquires a resource (blocking) func (as *AdvancedSemaphore) Acquire() { as.incrementWaiting() defer as.decrementWaiting() as.ch <- struct{}{} atomic.AddInt64(&as.totalAcquires, 1) } // TryAcquire tries to acquire without blocking func (as *AdvancedSemaphore) TryAcquire() bool { select { case as.ch <- struct{}{}: atomic.AddInt64(&as.totalAcquires, 1) return true default: return false } } // AcquireWithTimeout acquires with a timeout func (as *AdvancedSemaphore) AcquireWithTimeout(timeout time.Duration) error { as.incrementWaiting() defer as.decrementWaiting() select { case as.ch <- struct{}{}: atomic.AddInt64(&as.totalAcquires, 1) return nil case <-time.After(timeout): atomic.AddInt64(&as.timeouts, 1) return fmt.Errorf("timeout after %v", timeout) } } // AcquireWithContext acquires with context cancellation func (as *AdvancedSemaphore) AcquireWithContext(ctx context.Context) error { as.incrementWaiting() defer as.decrementWaiting() select { case as.ch <- struct{}{}: atomic.AddInt64(&as.totalAcquires, 1) return nil case <-ctx.Done(): atomic.AddInt64(&as.cancellations, 1) return ctx.Err() } } // Release releases a resource func (as *AdvancedSemaphore) Release() { <-as.ch atomic.AddInt64(&as.totalReleases, 1) } // incrementWaiting increments waiting goroutines counter func (as *AdvancedSemaphore) incrementWaiting() { as.mu.Lock() as.waitingGoroutines++ as.mu.Unlock() } // decrementWaiting decrements waiting goroutines counter func (as *AdvancedSemaphore) decrementWaiting() { as.mu.Lock() as.waitingGoroutines-- as.mu.Unlock() } // GetStats returns semaphore statistics func (as *AdvancedSemaphore) GetStats() map[string]interface{} { as.mu.RLock() waiting := as.waitingGoroutines as.mu.RUnlock() return map[string]interface{}{ "capacity": as.capacity, "available": as.Available(), "used": as.Used(), "waiting": waiting, "total_acquires": atomic.LoadInt64(&as.totalAcquires), "total_releases": atomic.LoadInt64(&as.totalReleases), "timeouts": atomic.LoadInt64(&as.timeouts), "cancellations": atomic.LoadInt64(&as.cancellations), } } // Available returns available resources func (as *AdvancedSemaphore) Available() int { return cap(as.ch) - len(as.ch) } // Used returns used resources func (as *AdvancedSemaphore) Used() int { return len(as.ch) } // Capacity returns total capacity func (as *AdvancedSemaphore) Capacity() int { return as.capacity } // ResourceManager demonstrates semaphore usage for resource management type ResourceManager struct { semaphore *AdvancedSemaphore resources []string } // NewResourceManager creates a new resource manager func NewResourceManager(resources []string) *ResourceManager { return &ResourceManager{ semaphore: NewAdvancedSemaphore(len(resources)), resources: resources, } } // UseResource uses a resource with timeout func (rm *ResourceManager) UseResource(ctx context.Context, userID string, timeout time.Duration) error { fmt.Printf("User %s: Requesting resource...\n", userID) // Try to acquire with timeout if err := rm.semaphore.AcquireWithTimeout(timeout); err != nil { fmt.Printf("User %s: Failed to acquire resource: %v\n", userID, err) return err } defer rm.semaphore.Release() resourceIndex := rm.semaphore.Used() - 1 resourceName := rm.resources[resourceIndex] fmt.Printf("User %s: Using resource '%s'\n", userID, resourceName) // Simulate resource usage select { case <-time.After(time.Duration(1+len(userID)%3) * time.Second): fmt.Printf("User %s: Finished using resource '%s'\n", userID, resourceName) return nil case <-ctx.Done(): fmt.Printf("User %s: Resource usage cancelled\n", userID) return ctx.Err() } } // GetStats returns resource manager statistics func (rm *ResourceManager) GetStats() map[string]interface{} { return rm.semaphore.GetStats() } func main() { resources := []string{"Database-1", "Database-2", "API-Gateway"} manager := NewResourceManager(resources) fmt.Println("=== Advanced Semaphore Demo ===") fmt.Printf("Available resources: %v\n\n", resources) // Start monitoring go func() { ticker := time.NewTicker(1 * time.Second) defer ticker.Stop() for range ticker.C { stats := manager.GetStats() fmt.Printf(" Stats: Used=%d/%d, Waiting=%d, Timeouts=%d\n", stats["used"], stats["capacity"], stats["waiting"], stats["timeouts"]) } }() var wg sync.WaitGroup // Simulate users requesting resources users := []string{"Alice", "Bob", "Charlie", "Diana", "Eve", "Frank"} for i, user := range users { wg.Add(1) go func(userID string, delay time.Duration) { defer wg.Done() time.Sleep(delay) // Stagger requests ctx, cancel := context.WithTimeout(context.Background(), 10*time.Second) defer cancel() // Some users have shorter timeouts timeout := 3 * time.Second if len(userID)%2 == 0 { timeout = 1 * time.Second } err := manager.UseResource(ctx, userID, timeout) if err != nil { fmt.Printf(" User %s failed: %v\n", userID, err) } }(user, time.Duration(i*300)*time.Millisecond) } wg.Wait() // Final statistics fmt.Println("\n=== Final Statistics ===") stats := manager.GetStats() for key, value := range stats { fmt.Printf("%s: %v\n", key, value) } } Weighted Semaphore Implementation package main import ( "context" "fmt" "sync" "time" ) // WeightedSemaphore allows acquiring resources with different weights type WeightedSemaphore struct { mu sync.Mutex capacity int64 current int64 waiters []waiter } // waiter represents a goroutine waiting for resources type waiter struct { weight int64 ready chan struct{} } // NewWeightedSemaphore creates a new weighted semaphore func NewWeightedSemaphore(capacity int64) *WeightedSemaphore { return &WeightedSemaphore{ capacity: capacity, waiters: make([]waiter, 0), } } // Acquire acquires resources with given weight func (ws *WeightedSemaphore) Acquire(weight int64) { ws.mu.Lock() if ws.current+weight <= ws.capacity && len(ws.waiters) == 0 { // Can acquire immediately ws.current += weight ws.mu.Unlock() return } // Need to wait ready := make(chan struct{}) ws.waiters = append(ws.waiters, waiter{weight: weight, ready: ready}) ws.mu.Unlock() <-ready } // TryAcquire tries to acquire resources without blocking func (ws *WeightedSemaphore) TryAcquire(weight int64) bool { ws.mu.Lock() defer ws.mu.Unlock() if ws.current+weight <= ws.capacity && len(ws.waiters) == 0 { ws.current += weight return true } return false } // AcquireWithContext acquires resources with context cancellation func (ws *WeightedSemaphore) AcquireWithContext(ctx context.Context, weight int64) error { ws.mu.Lock() if ws.current+weight <= ws.capacity && len(ws.waiters) == 0 { // Can acquire immediately ws.current += weight ws.mu.Unlock() return nil } // Need to wait ready := make(chan struct{}) ws.waiters = append(ws.waiters, waiter{weight: weight, ready: ready}) ws.mu.Unlock() select { case <-ready: return nil case <-ctx.Done(): // Remove from waiters list ws.mu.Lock() for i, w := range ws.waiters { if w.ready == ready { ws.waiters = append(ws.waiters[:i], ws.waiters[i+1:]...) break } } ws.mu.Unlock() return ctx.Err() } } // Release releases resources with given weight func (ws *WeightedSemaphore) Release(weight int64) { ws.mu.Lock() defer ws.mu.Unlock() ws.current -= weight ws.notifyWaiters() } // notifyWaiters notifies waiting goroutines that can now proceed func (ws *WeightedSemaphore) notifyWaiters() { for i := 0; i < len(ws.waiters); { w := ws.waiters[i] if ws.current+w.weight <= ws.capacity { // This waiter can proceed ws.current += w.weight close(w.ready) // Remove from waiters ws.waiters = append(ws.waiters[:i], ws.waiters[i+1:]...) } else { i++ } } } // GetStats returns current statistics func (ws *WeightedSemaphore) GetStats() map[string]interface{} { ws.mu.Lock() defer ws.mu.Unlock() return map[string]interface{}{ "capacity": ws.capacity, "current": ws.current, "available": ws.capacity - ws.current, "waiters": len(ws.waiters), } } // Task represents a task with resource requirements type Task struct { ID string Weight int64 Duration time.Duration } // TaskProcessor processes tasks using weighted semaphore type TaskProcessor struct { semaphore *WeightedSemaphore } // NewTaskProcessor creates a new task processor func NewTaskProcessor(capacity int64) *TaskProcessor { return &TaskProcessor{ semaphore: NewWeightedSemaphore(capacity), } } // ProcessTask processes a task func (tp *TaskProcessor) ProcessTask(ctx context.Context, task Task) error { fmt.Printf("Task %s: Requesting %d units of resource...\n", task.ID, task.Weight) if err := tp.semaphore.AcquireWithContext(ctx, task.Weight); err != nil { fmt.Printf("Task %s: Failed to acquire resources: %v\n", task.ID, err) return err } defer tp.semaphore.Release(task.Weight) stats := tp.semaphore.GetStats() fmt.Printf("Task %s: Acquired %d units (available: %d/%d)\n", task.ID, task.Weight, stats["available"], stats["capacity"]) // Simulate task processing select { case <-time.After(task.Duration): fmt.Printf("Task %s: Completed\n", task.ID) return nil case <-ctx.Done(): fmt.Printf("Task %s: Cancelled\n", task.ID) return ctx.Err() } } // GetStats returns processor statistics func (tp *TaskProcessor) GetStats() map[string]interface{} { return tp.semaphore.GetStats() } func main() { // Create weighted semaphore with capacity of 10 units processor := NewTaskProcessor(10) fmt.Println("=== Weighted Semaphore Demo ===") fmt.Println("Total capacity: 10 units") // Define tasks with different resource requirements tasks := []Task{ {"Small-1", 2, 2 * time.Second}, {"Medium-1", 4, 3 * time.Second}, {"Large-1", 6, 4 * time.Second}, {"Small-2", 1, 1 * time.Second}, {"Small-3", 2, 2 * time.Second}, {"Medium-2", 5, 3 * time.Second}, {"Large-2", 8, 5 * time.Second}, } // Start monitoring go func() { ticker := time.NewTicker(500 * time.Millisecond) defer ticker.Stop() for range ticker.C { stats := processor.GetStats() fmt.Printf(" Resources: %d/%d used, %d waiters\n", stats["current"], stats["capacity"], stats["waiters"]) } }() var wg sync.WaitGroup // Process tasks concurrently for i, task := range tasks { wg.Add(1) go func(t Task, delay time.Duration) { defer wg.Done() time.Sleep(delay) // Stagger task starts ctx, cancel := context.WithTimeout(context.Background(), 10*time.Second) defer cancel() err := processor.ProcessTask(ctx, t) if err != nil { fmt.Printf(" Task %s failed: %v\n", t.ID, err) } }(task, time.Duration(i*200)*time.Millisecond) } wg.Wait() // Final statistics fmt.Println("\n=== Final Statistics ===") stats := processor.GetStats() for key, value := range stats { fmt.Printf("%s: %v\n", key, value) } } Semaphore-based Connection Pool package main import ( "context" "fmt" "sync" "time" ) // Connection represents a database connection type Connection struct { ID int InUse bool LastUsed time.Time } // ConnectionPool manages database connections using semaphore type ConnectionPool struct { connections []*Connection semaphore *AdvancedSemaphore mu sync.Mutex } // NewConnectionPool creates a new connection pool func NewConnectionPool(size int) *ConnectionPool { connections := make([]*Connection, size) for i := 0; i < size; i++ { connections[i] = &Connection{ ID: i + 1, InUse: false, LastUsed: time.Now(), } } return &ConnectionPool{ connections: connections, semaphore: NewAdvancedSemaphore(size), } } // GetConnection acquires a connection from the pool func (cp *ConnectionPool) GetConnection(ctx context.Context) (*Connection, error) { if err := cp.semaphore.AcquireWithContext(ctx); err != nil { return nil, err } cp.mu.Lock() defer cp.mu.Unlock() // Find an available connection for _, conn := range cp.connections { if !conn.InUse { conn.InUse = true conn.LastUsed = time.Now() return conn, nil } } // This shouldn't happen if semaphore is working correctly cp.semaphore.Release() return nil, fmt.Errorf("no available connections") } // ReturnConnection returns a connection to the pool func (cp *ConnectionPool) ReturnConnection(conn *Connection) { cp.mu.Lock() conn.InUse = false conn.LastUsed = time.Now() cp.mu.Unlock() cp.semaphore.Release() } // GetStats returns pool statistics func (cp *ConnectionPool) GetStats() map[string]interface{} { cp.mu.Lock() defer cp.mu.Unlock() inUse := 0 for _, conn := range cp.connections { if conn.InUse { inUse++ } } semStats := cp.semaphore.GetStats() return map[string]interface{}{ "total_connections": len(cp.connections), "in_use": inUse, "available": len(cp.connections) - inUse, "semaphore_stats": semStats, } } // DatabaseService simulates a service using the connection pool type DatabaseService struct { pool *ConnectionPool } // NewDatabaseService creates a new database service func NewDatabaseService(poolSize int) *DatabaseService { return &DatabaseService{ pool: NewConnectionPool(poolSize), } } // ExecuteQuery simulates executing a database query func (ds *DatabaseService) ExecuteQuery(ctx context.Context, userID string, query string) error { fmt.Printf("User %s: Requesting database connection for query: %s\n", userID, query) conn, err := ds.pool.GetConnection(ctx) if err != nil { fmt.Printf("User %s: Failed to get connection: %v\n", userID, err) return err } defer ds.pool.ReturnConnection(conn) fmt.Printf("User %s: Using connection %d\n", userID, conn.ID) // Simulate query execution queryDuration := time.Duration(500+len(query)*10) * time.Millisecond select { case <-time.After(queryDuration): fmt.Printf("User %s: Query completed on connection %d\n", userID, conn.ID) return nil case <-ctx.Done(): fmt.Printf("User %s: Query cancelled on connection %d\n", userID, conn.ID) return ctx.Err() } } // GetStats returns service statistics func (ds *DatabaseService) GetStats() map[string]interface{} { return ds.pool.GetStats() } func main() { // Create database service with 3 connections service := NewDatabaseService(3) fmt.Println("=== Connection Pool Demo ===") fmt.Println("Pool size: 3 connections") // Start monitoring go func() { ticker := time.NewTicker(1 * time.Second) defer ticker.Stop() for range ticker.C { stats := service.GetStats() fmt.Printf(" Pool: %d/%d in use, %d available\n", stats["in_use"], stats["total_connections"], stats["available"]) } }() var wg sync.WaitGroup // Simulate multiple users making database queries users := []struct { id string query string }{ {"Alice", "SELECT * FROM users"}, {"Bob", "SELECT * FROM orders WHERE user_id = 123"}, {"Charlie", "UPDATE users SET last_login = NOW()"}, {"Diana", "SELECT COUNT(*) FROM products"}, {"Eve", "INSERT INTO logs (message) VALUES ('test')"}, {"Frank", "SELECT * FROM analytics WHERE date > '2024-01-01'"}, } for i, user := range users { wg.Add(1) go func(userID, query string, delay time.Duration) { defer wg.Done() time.Sleep(delay) // Stagger requests ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second) defer cancel() err := service.ExecuteQuery(ctx, userID, query) if err != nil { fmt.Printf(" User %s query failed: %v\n", userID, err) } }(user.id, user.query, time.Duration(i*300)*time.Millisecond) } wg.Wait() // Final statistics fmt.Println("\n=== Final Statistics ===") stats := service.GetStats() for key, value := range stats { if key == "semaphore_stats" { fmt.Printf("%s:\n", key) semStats := value.(map[string]interface{}) for k, v := range semStats { fmt.Printf(" %s: %v\n", k, v) } } else { fmt.Printf("%s: %v\n", key, value) } } } Best Practices Choose Right Capacity: Set semaphore capacity based on available resources Always Release: Use defer to ensure resources are released Handle Context: Support cancellation in long-running operations Monitor Usage: Track semaphore statistics and resource utilization Avoid Deadlocks: Don’t acquire multiple semaphores in different orders Use Timeouts: Prevent indefinite blocking with timeouts Consider Weighted: Use weighted semaphores for resources with different costs Common Pitfalls Resource Leaks: Forgetting to release acquired resources Deadlocks: Circular dependencies between semaphores Starvation: Large requests blocking smaller ones indefinitely Over-allocation: Setting capacity higher than actual resources Under-utilization: Setting capacity too low for available resources The Semaphore pattern is essential for managing limited resources in concurrent applications. It provides controlled access to resources, prevents overload, and ensures fair resource distribution among competing goroutines. ...

What is State Pattern? The State pattern is a behavioral design pattern that allows an object to alter its behavior when its internal state changes. It appears as if the object changed its class. Think of it like a vending machine - it behaves differently when it’s waiting for coins, has coins inserted, is dispensing a product, or is out of stock. Each state has its own set of valid operations and transitions. ...

Go Concurrency Patterns Series: ← Pub/Sub Pattern | Series Overview | Worker Pool → What is the Request/Response Pattern? The Request/Response pattern enables synchronous communication between goroutines, where a sender waits for a response from a receiver. This pattern is essential for RPC-style communication, database queries, API calls, and any scenario where you need to get a result back from an operation. Key Components: Request: Contains data and a response channel Response: Contains result data and/or error information Requester: Sends request and waits for response Responder: Processes request and sends response Real-World Use Cases Database Operations: Query execution with results API Gateways: Forwarding requests to microservices Cache Systems: Get/Set operations with confirmation File Operations: Read/Write with status feedback Validation Services: Input validation with results Authentication: Login requests with tokens Basic Request/Response Implementation package main import ( "fmt" "math/rand" "time" ) // Request represents a request with a response channel type Request struct { ID string Data interface{} Response chan Response } // Response represents the response to a request type Response struct { ID string Result interface{} Error error } // Server processes requests type Server struct { requests chan Request quit chan bool } // NewServer creates a new server func NewServer() *Server { return &Server{ requests: make(chan Request), quit: make(chan bool), } } // Start begins processing requests func (s *Server) Start() { go func() { for { select { case req := <-s.requests: s.processRequest(req) case <-s.quit: return } } }() } // processRequest handles a single request func (s *Server) processRequest(req Request) { // Simulate processing time time.Sleep(time.Duration(rand.Intn(100)) * time.Millisecond) // Process the request (example: double the number) var response Response response.ID = req.ID if num, ok := req.Data.(int); ok { response.Result = num * 2 } else { response.Error = fmt.Errorf("invalid data type") } // Send response back req.Response <- response } // SendRequest sends a request and waits for response func (s *Server) SendRequest(id string, data interface{}) (interface{}, error) { responseChan := make(chan Response, 1) request := Request{ ID: id, Data: data, Response: responseChan, } s.requests <- request // Wait for response response := <-responseChan return response.Result, response.Error } // Stop shuts down the server func (s *Server) Stop() { close(s.quit) } func main() { server := NewServer() server.Start() defer server.Stop() // Send multiple requests for i := 1; i <= 5; i++ { result, err := server.SendRequest(fmt.Sprintf("req-%d", i), i*10) if err != nil { fmt.Printf("Request %d failed: %v\n", i, err) } else { fmt.Printf("Request %d result: %v\n", i, result) } } } Request/Response with Timeout package main import ( "context" "fmt" "math/rand" "time" ) // TimedRequest includes context for timeout handling type TimedRequest struct { ID string Data interface{} Response chan TimedResponse Context context.Context } // TimedResponse includes timing information type TimedResponse struct { ID string Result interface{} Error error Duration time.Duration Timestamp time.Time } // TimedServer processes requests with timeout support type TimedServer struct { requests chan TimedRequest quit chan bool } func NewTimedServer() *TimedServer { return &TimedServer{ requests: make(chan TimedRequest, 10), quit: make(chan bool), } } func (ts *TimedServer) Start() { go func() { for { select { case req := <-ts.requests: go ts.processTimedRequest(req) case <-ts.quit: return } } }() } func (ts *TimedServer) processTimedRequest(req TimedRequest) { start := time.Now() // Check if context is already cancelled select { case <-req.Context.Done(): ts.sendResponse(req, nil, req.Context.Err(), start) return default: } // Simulate work with random duration workDuration := time.Duration(rand.Intn(200)) * time.Millisecond select { case <-time.After(workDuration): // Work completed if num, ok := req.Data.(int); ok { ts.sendResponse(req, num*2, nil, start) } else { ts.sendResponse(req, nil, fmt.Errorf("invalid data type"), start) } case <-req.Context.Done(): // Context cancelled during work ts.sendResponse(req, nil, req.Context.Err(), start) } } func (ts *TimedServer) sendResponse(req TimedRequest, result interface{}, err error, start time.Time) { response := TimedResponse{ ID: req.ID, Result: result, Error: err, Duration: time.Since(start), Timestamp: time.Now(), } select { case req.Response <- response: case <-req.Context.Done(): // Client no longer waiting } } // SendRequestWithTimeout sends a request with a timeout func (ts *TimedServer) SendRequestWithTimeout(id string, data interface{}, timeout time.Duration) (interface{}, error) { ctx, cancel := context.WithTimeout(context.Background(), timeout) defer cancel() responseChan := make(chan TimedResponse, 1) request := TimedRequest{ ID: id, Data: data, Response: responseChan, Context: ctx, } select { case ts.requests <- request: case <-ctx.Done(): return nil, ctx.Err() } select { case response := <-responseChan: fmt.Printf("Request %s completed in %v\n", response.ID, response.Duration) return response.Result, response.Error case <-ctx.Done(): return nil, ctx.Err() } } func (ts *TimedServer) Stop() { close(ts.quit) } func main() { server := NewTimedServer() server.Start() defer server.Stop() // Send requests with different timeouts requests := []struct { id string data int timeout time.Duration }{ {"fast", 10, 300 * time.Millisecond}, {"medium", 20, 150 * time.Millisecond}, {"slow", 30, 50 * time.Millisecond}, // This might timeout } for _, req := range requests { result, err := server.SendRequestWithTimeout(req.id, req.data, req.timeout) if err != nil { fmt.Printf("Request %s failed: %v\n", req.id, err) } else { fmt.Printf("Request %s result: %v\n", req.id, result) } } } Future/Promise Pattern package main import ( "context" "fmt" "sync" "time" ) // Future represents a value that will be available in the future type Future struct { mu sync.Mutex done chan struct{} result interface{} err error computed bool } // NewFuture creates a new future func NewFuture() *Future { return &Future{ done: make(chan struct{}), } } // Set sets the future's value func (f *Future) Set(result interface{}, err error) { f.mu.Lock() defer f.mu.Unlock() if f.computed { return // Already set } f.result = result f.err = err f.computed = true close(f.done) } // Get waits for and returns the future's value func (f *Future) Get() (interface{}, error) { <-f.done return f.result, f.err } // GetWithTimeout waits for the value with a timeout func (f *Future) GetWithTimeout(timeout time.Duration) (interface{}, error) { select { case <-f.done: return f.result, f.err case <-time.After(timeout): return nil, fmt.Errorf("timeout waiting for future") } } // GetWithContext waits for the value with context cancellation func (f *Future) GetWithContext(ctx context.Context) (interface{}, error) { select { case <-f.done: return f.result, f.err case <-ctx.Done(): return nil, ctx.Err() } } // IsReady returns true if the future has been computed func (f *Future) IsReady() bool { f.mu.Lock() defer f.mu.Unlock() return f.computed } // AsyncService demonstrates async operations with futures type AsyncService struct { workers chan struct{} } func NewAsyncService(maxWorkers int) *AsyncService { return &AsyncService{ workers: make(chan struct{}, maxWorkers), } } // ProcessAsync starts async processing and returns a future func (as *AsyncService) ProcessAsync(data interface{}) *Future { future := NewFuture() go func() { // Acquire worker slot as.workers <- struct{}{} defer func() { <-as.workers }() // Simulate processing time.Sleep(time.Duration(100+rand.Intn(200)) * time.Millisecond) // Process data if num, ok := data.(int); ok { future.Set(num*num, nil) } else { future.Set(nil, fmt.Errorf("invalid data type")) } }() return future } func main() { service := NewAsyncService(3) // Start multiple async operations futures := make([]*Future, 5) for i := 0; i < 5; i++ { fmt.Printf("Starting async operation %d\n", i+1) futures[i] = service.ProcessAsync((i + 1) * 10) } // Wait for all results fmt.Println("\nWaiting for results...") for i, future := range futures { result, err := future.Get() if err != nil { fmt.Printf("Operation %d failed: %v\n", i+1, err) } else { fmt.Printf("Operation %d result: %v\n", i+1, result) } } // Example with timeout fmt.Println("\nTesting timeout...") timeoutFuture := service.ProcessAsync(100) result, err := timeoutFuture.GetWithTimeout(50 * time.Millisecond) if err != nil { fmt.Printf("Timeout example failed: %v\n", err) } else { fmt.Printf("Timeout example result: %v\n", result) } } Batch Request/Response package main import ( "fmt" "sync" "time" ) // BatchRequest represents multiple requests processed together type BatchRequest struct { ID string Items []interface{} Response chan BatchResponse } // BatchResponse contains results for all items in a batch type BatchResponse struct { ID string Results []BatchResult Error error } // BatchResult represents the result of processing one item type BatchResult struct { Index int Result interface{} Error error } // BatchProcessor processes requests in batches for efficiency type BatchProcessor struct { requests chan BatchRequest batchSize int batchWindow time.Duration quit chan bool } func NewBatchProcessor(batchSize int, batchWindow time.Duration) *BatchProcessor { return &BatchProcessor{ requests: make(chan BatchRequest, 100), batchSize: batchSize, batchWindow: batchWindow, quit: make(chan bool), } } func (bp *BatchProcessor) Start() { go func() { batch := make([]BatchRequest, 0, bp.batchSize) timer := time.NewTimer(bp.batchWindow) timer.Stop() for { select { case req := <-bp.requests: batch = append(batch, req) if len(batch) == 1 { timer.Reset(bp.batchWindow) } if len(batch) >= bp.batchSize { bp.processBatch(batch) batch = batch[:0] timer.Stop() } case <-timer.C: if len(batch) > 0 { bp.processBatch(batch) batch = batch[:0] } case <-bp.quit: if len(batch) > 0 { bp.processBatch(batch) } return } } }() } func (bp *BatchProcessor) processBatch(batch []BatchRequest) { fmt.Printf("Processing batch of %d requests\n", len(batch)) var wg sync.WaitGroup for _, req := range batch { wg.Add(1) go func(r BatchRequest) { defer wg.Done() bp.processRequest(r) }(req) } wg.Wait() } func (bp *BatchProcessor) processRequest(req BatchRequest) { results := make([]BatchResult, len(req.Items)) for i, item := range req.Items { // Simulate processing each item time.Sleep(10 * time.Millisecond) if num, ok := item.(int); ok { results[i] = BatchResult{ Index: i, Result: num * 3, } } else { results[i] = BatchResult{ Index: i, Error: fmt.Errorf("invalid item type at index %d", i), } } } response := BatchResponse{ ID: req.ID, Results: results, } req.Response <- response } // SendBatchRequest sends a batch request and waits for response func (bp *BatchProcessor) SendBatchRequest(id string, items []interface{}) ([]BatchResult, error) { responseChan := make(chan BatchResponse, 1) request := BatchRequest{ ID: id, Items: items, Response: responseChan, } bp.requests <- request response := <-responseChan return response.Results, response.Error } func (bp *BatchProcessor) Stop() { close(bp.quit) } func main() { processor := NewBatchProcessor(3, 100*time.Millisecond) processor.Start() defer processor.Stop() // Send individual batch requests go func() { results, err := processor.SendBatchRequest("batch1", []interface{}{1, 2, 3, 4, 5}) if err != nil { fmt.Printf("Batch 1 failed: %v\n", err) return } fmt.Println("Batch 1 results:") for _, result := range results { if result.Error != nil { fmt.Printf(" Item %d error: %v\n", result.Index, result.Error) } else { fmt.Printf(" Item %d result: %v\n", result.Index, result.Result) } } }() go func() { results, err := processor.SendBatchRequest("batch2", []interface{}{10, 20, 30}) if err != nil { fmt.Printf("Batch 2 failed: %v\n", err) return } fmt.Println("Batch 2 results:") for _, result := range results { if result.Error != nil { fmt.Printf(" Item %d error: %v\n", result.Index, result.Error) } else { fmt.Printf(" Item %d result: %v\n", result.Index, result.Result) } } }() // Wait for processing time.Sleep(500 * time.Millisecond) } Best Practices Always Use Timeouts: Prevent indefinite blocking Handle Context Cancellation: Support graceful cancellation Buffer Response Channels: Avoid blocking responders Error Handling: Always include error information in responses Resource Cleanup: Ensure channels and goroutines are cleaned up Monitoring: Track request/response times and success rates Backpressure: Handle situations when responders are overwhelmed Common Pitfalls Deadlocks: Not buffering response channels Goroutine Leaks: Not handling context cancellation Memory Leaks: Not closing channels properly Blocking Operations: Long-running operations without timeouts Lost Responses: Not handling channel closure Testing Request/Response package main import ( "context" "testing" "time" ) func TestRequestResponse(t *testing.T) { server := NewTimedServer() server.Start() defer server.Stop() // Test successful request result, err := server.SendRequestWithTimeout("test1", 42, 200*time.Millisecond) if err != nil { t.Fatalf("Request failed: %v", err) } if result != 84 { t.Errorf("Expected 84, got %v", result) } // Test timeout _, err = server.SendRequestWithTimeout("test2", 42, 10*time.Millisecond) if err == nil { t.Error("Expected timeout error") } } func TestFuture(t *testing.T) { future := NewFuture() // Test that future is not ready initially if future.IsReady() { t.Error("Future should not be ready initially") } // Set value in goroutine go func() { time.Sleep(50 * time.Millisecond) future.Set("test result", nil) }() // Get value result, err := future.Get() if err != nil { t.Fatalf("Future failed: %v", err) } if result != "test result" { t.Errorf("Expected 'test result', got %v", result) } // Test that future is ready after setting if !future.IsReady() { t.Error("Future should be ready after setting") } } The Request/Response pattern is essential for building synchronous communication systems in Go. It provides the foundation for RPC systems, database operations, and any scenario where you need to wait for a result from an asynchronous operation. ...

Go Concurrency Patterns Series: ← Circuit Breaker | Series Overview | Semaphore Pattern → What is the Rate Limiter Pattern? Rate limiting controls the rate at which operations are performed, preventing system overload and ensuring fair resource usage. It’s essential for protecting services from abuse, managing resource consumption, and maintaining system stability under load. Common Algorithms: Token Bucket: Allows bursts up to bucket capacity Fixed Window: Fixed number of requests per time window Sliding Window: Smooth rate limiting over time Leaky Bucket: Constant output rate regardless of input Real-World Use Cases API Rate Limiting: Prevent API abuse and ensure fair usage Database Throttling: Control database query rates File Processing: Limit file processing rate Network Operations: Control bandwidth usage Background Jobs: Throttle job processing User Actions: Prevent spam and abuse Token Bucket Rate Limiter package main import ( "context" "fmt" "sync" "time" ) // TokenBucket implements the token bucket rate limiting algorithm type TokenBucket struct { mu sync.Mutex capacity int // Maximum number of tokens tokens int // Current number of tokens refillRate int // Tokens added per second lastRefill time.Time // Last refill time } // NewTokenBucket creates a new token bucket rate limiter func NewTokenBucket(capacity, refillRate int) *TokenBucket { return &TokenBucket{ capacity: capacity, tokens: capacity, // Start with full bucket refillRate: refillRate, lastRefill: time.Now(), } } // Allow checks if a request should be allowed func (tb *TokenBucket) Allow() bool { tb.mu.Lock() defer tb.mu.Unlock() tb.refill() if tb.tokens > 0 { tb.tokens-- return true } return false } // AllowN checks if n requests should be allowed func (tb *TokenBucket) AllowN(n int) bool { tb.mu.Lock() defer tb.mu.Unlock() tb.refill() if tb.tokens >= n { tb.tokens -= n return true } return false } // Wait waits until a token is available func (tb *TokenBucket) Wait(ctx context.Context) error { for { if tb.Allow() { return nil } select { case <-time.After(time.Millisecond * 10): continue case <-ctx.Done(): return ctx.Err() } } } // refill adds tokens based on elapsed time func (tb *TokenBucket) refill() { now := time.Now() elapsed := now.Sub(tb.lastRefill) tokensToAdd := int(elapsed.Seconds() * float64(tb.refillRate)) if tokensToAdd > 0 { tb.tokens += tokensToAdd if tb.tokens > tb.capacity { tb.tokens = tb.capacity } tb.lastRefill = now } } // GetStats returns current bucket statistics func (tb *TokenBucket) GetStats() (tokens, capacity int) { tb.mu.Lock() defer tb.mu.Unlock() tb.refill() return tb.tokens, tb.capacity } func main() { // Create a token bucket: 5 tokens capacity, 2 tokens per second refill rate limiter := NewTokenBucket(5, 2) fmt.Println("=== Token Bucket Rate Limiter Demo ===") // Test burst capability fmt.Println("\n--- Testing Burst Capability ---") for i := 1; i <= 7; i++ { allowed := limiter.Allow() tokens, capacity := limiter.GetStats() fmt.Printf("Request %d: %s (tokens: %d/%d)\n", i, allowedStatus(allowed), tokens, capacity) } // Wait for refill fmt.Println("\n--- Waiting 3 seconds for refill ---") time.Sleep(3 * time.Second) // Test after refill fmt.Println("\n--- Testing After Refill ---") for i := 1; i <= 4; i++ { allowed := limiter.Allow() tokens, capacity := limiter.GetStats() fmt.Printf("Request %d: %s (tokens: %d/%d)\n", i, allowedStatus(allowed), tokens, capacity) } // Test AllowN fmt.Println("\n--- Testing AllowN (requesting 3 tokens) ---") allowed := limiter.AllowN(3) tokens, capacity := limiter.GetStats() fmt.Printf("Bulk request: %s (tokens: %d/%d)\n", allowedStatus(allowed), tokens, capacity) } func allowedStatus(allowed bool) string { if allowed { return " ALLOWED" } return " DENIED" } Sliding Window Rate Limiter package main import ( "fmt" "sync" "time" ) // SlidingWindow implements sliding window rate limiting type SlidingWindow struct { mu sync.Mutex requests []time.Time limit int // Maximum requests per window window time.Duration // Time window duration } // NewSlidingWindow creates a new sliding window rate limiter func NewSlidingWindow(limit int, window time.Duration) *SlidingWindow { return &SlidingWindow{ requests: make([]time.Time, 0), limit: limit, window: window, } } // Allow checks if a request should be allowed func (sw *SlidingWindow) Allow() bool { sw.mu.Lock() defer sw.mu.Unlock() now := time.Now() sw.cleanOldRequests(now) if len(sw.requests) < sw.limit { sw.requests = append(sw.requests, now) return true } return false } // cleanOldRequests removes requests outside the current window func (sw *SlidingWindow) cleanOldRequests(now time.Time) { cutoff := now.Add(-sw.window) // Find first request within window start := 0 for i, req := range sw.requests { if req.After(cutoff) { start = i break } start = len(sw.requests) // All requests are old } // Keep only recent requests if start > 0 { copy(sw.requests, sw.requests[start:]) sw.requests = sw.requests[:len(sw.requests)-start] } } // GetStats returns current window statistics func (sw *SlidingWindow) GetStats() (current, limit int, window time.Duration) { sw.mu.Lock() defer sw.mu.Unlock() sw.cleanOldRequests(time.Now()) return len(sw.requests), sw.limit, sw.window } // GetRequestTimes returns timestamps of requests in current window func (sw *SlidingWindow) GetRequestTimes() []time.Time { sw.mu.Lock() defer sw.mu.Unlock() sw.cleanOldRequests(time.Now()) result := make([]time.Time, len(sw.requests)) copy(result, sw.requests) return result } func main() { // Create sliding window: 3 requests per 2 seconds limiter := NewSlidingWindow(3, 2*time.Second) fmt.Println("=== Sliding Window Rate Limiter Demo ===") fmt.Println("Limit: 3 requests per 2 seconds") // Test requests over time for i := 1; i <= 8; i++ { allowed := limiter.Allow() current, limit, window := limiter.GetStats() fmt.Printf("Request %d: %s (current: %d/%d in %v window)\n", i, allowedStatus(allowed), current, limit, window) if i == 4 { fmt.Println("--- Waiting 1 second ---") time.Sleep(1 * time.Second) } else if i == 6 { fmt.Println("--- Waiting 1.5 seconds ---") time.Sleep(1500 * time.Millisecond) } else { time.Sleep(200 * time.Millisecond) } } // Show request timeline fmt.Println("\n--- Request Timeline ---") requests := limiter.GetRequestTimes() now := time.Now() for i, req := range requests { age := now.Sub(req) fmt.Printf("Request %d: %v ago\n", i+1, age.Round(time.Millisecond)) } } Fixed Window Rate Limiter package main import ( "fmt" "sync" "time" ) // FixedWindow implements fixed window rate limiting type FixedWindow struct { mu sync.Mutex limit int // Maximum requests per window window time.Duration // Window duration currentCount int // Current window request count windowStart time.Time // Current window start time } // NewFixedWindow creates a new fixed window rate limiter func NewFixedWindow(limit int, window time.Duration) *FixedWindow { return &FixedWindow{ limit: limit, window: window, windowStart: time.Now(), } } // Allow checks if a request should be allowed func (fw *FixedWindow) Allow() bool { fw.mu.Lock() defer fw.mu.Unlock() now := time.Now() // Check if we need to start a new window if now.Sub(fw.windowStart) >= fw.window { fw.currentCount = 0 fw.windowStart = now } if fw.currentCount < fw.limit { fw.currentCount++ return true } return false } // GetStats returns current window statistics func (fw *FixedWindow) GetStats() (current, limit int, windowRemaining time.Duration) { fw.mu.Lock() defer fw.mu.Unlock() now := time.Now() elapsed := now.Sub(fw.windowStart) if elapsed >= fw.window { return 0, fw.limit, fw.window } return fw.currentCount, fw.limit, fw.window - elapsed } func main() { // Create fixed window: 3 requests per 2 seconds limiter := NewFixedWindow(3, 2*time.Second) fmt.Println("=== Fixed Window Rate Limiter Demo ===") fmt.Println("Limit: 3 requests per 2 seconds") // Test requests over time for i := 1; i <= 10; i++ { allowed := limiter.Allow() current, limit, remaining := limiter.GetStats() fmt.Printf("Request %d: %s (current: %d/%d, window resets in: %v)\n", i, allowedStatus(allowed), current, limit, remaining.Round(time.Millisecond)) time.Sleep(400 * time.Millisecond) } } Advanced Rate Limiter with Multiple Algorithms package main import ( "context" "fmt" "sync" "time" ) // RateLimiterType represents different rate limiting algorithms type RateLimiterType int const ( TokenBucketType RateLimiterType = iota SlidingWindowType FixedWindowType ) // RateLimiter interface for different rate limiting algorithms type RateLimiter interface { Allow() bool Wait(ctx context.Context) error GetStats() map[string]interface{} } // MultiRateLimiter combines multiple rate limiters type MultiRateLimiter struct { limiters []RateLimiter names []string } // NewMultiRateLimiter creates a new multi-algorithm rate limiter func NewMultiRateLimiter() *MultiRateLimiter { return &MultiRateLimiter{ limiters: make([]RateLimiter, 0), names: make([]string, 0), } } // AddLimiter adds a rate limiter with a name func (mrl *MultiRateLimiter) AddLimiter(name string, limiter RateLimiter) { mrl.limiters = append(mrl.limiters, limiter) mrl.names = append(mrl.names, name) } // Allow checks if request is allowed by all limiters func (mrl *MultiRateLimiter) Allow() bool { for _, limiter := range mrl.limiters { if !limiter.Allow() { return false } } return true } // Wait waits until all limiters allow the request func (mrl *MultiRateLimiter) Wait(ctx context.Context) error { for _, limiter := range mrl.limiters { if err := limiter.Wait(ctx); err != nil { return err } } return nil } // GetStats returns stats from all limiters func (mrl *MultiRateLimiter) GetStats() map[string]interface{} { stats := make(map[string]interface{}) for i, limiter := range mrl.limiters { stats[mrl.names[i]] = limiter.GetStats() } return stats } // Enhanced TokenBucket with RateLimiter interface type EnhancedTokenBucket struct { *TokenBucket } func (etb *EnhancedTokenBucket) GetStats() map[string]interface{} { tokens, capacity := etb.TokenBucket.GetStats() return map[string]interface{}{ "type": "token_bucket", "tokens": tokens, "capacity": capacity, "rate": etb.refillRate, } } // Enhanced SlidingWindow with RateLimiter interface type EnhancedSlidingWindow struct { *SlidingWindow } func (esw *EnhancedSlidingWindow) Wait(ctx context.Context) error { for { if esw.Allow() { return nil } select { case <-time.After(time.Millisecond * 10): continue case <-ctx.Done(): return ctx.Err() } } } func (esw *EnhancedSlidingWindow) GetStats() map[string]interface{} { current, limit, window := esw.SlidingWindow.GetStats() return map[string]interface{}{ "type": "sliding_window", "current": current, "limit": limit, "window": window.String(), } } // Enhanced FixedWindow with RateLimiter interface type EnhancedFixedWindow struct { *FixedWindow } func (efw *EnhancedFixedWindow) Wait(ctx context.Context) error { for { if efw.Allow() { return nil } select { case <-time.After(time.Millisecond * 10): continue case <-ctx.Done(): return ctx.Err() } } } func (efw *EnhancedFixedWindow) GetStats() map[string]interface{} { current, limit, remaining := efw.FixedWindow.GetStats() return map[string]interface{}{ "type": "fixed_window", "current": current, "limit": limit, "remaining": remaining.String(), } } // RateLimitedService demonstrates rate limiting in a service type RateLimitedService struct { limiter RateLimiter mu sync.Mutex stats struct { totalRequests int allowedRequests int deniedRequests int } } // NewRateLimitedService creates a new rate limited service func NewRateLimitedService(limiter RateLimiter) *RateLimitedService { return &RateLimitedService{ limiter: limiter, } } // ProcessRequest processes a request with rate limiting func (rls *RateLimitedService) ProcessRequest(ctx context.Context, requestID string) error { rls.mu.Lock() rls.stats.totalRequests++ rls.mu.Unlock() if !rls.limiter.Allow() { rls.mu.Lock() rls.stats.deniedRequests++ rls.mu.Unlock() return fmt.Errorf("request %s denied by rate limiter", requestID) } rls.mu.Lock() rls.stats.allowedRequests++ rls.mu.Unlock() // Simulate processing time.Sleep(50 * time.Millisecond) fmt.Printf(" Processed request %s\n", requestID) return nil } // GetServiceStats returns service statistics func (rls *RateLimitedService) GetServiceStats() map[string]interface{} { rls.mu.Lock() defer rls.mu.Unlock() return map[string]interface{}{ "total_requests": rls.stats.totalRequests, "allowed_requests": rls.stats.allowedRequests, "denied_requests": rls.stats.deniedRequests, "rate_limiter": rls.limiter.GetStats(), } } func main() { // Create multi-algorithm rate limiter multiLimiter := NewMultiRateLimiter() // Add different rate limiters multiLimiter.AddLimiter("token_bucket", &EnhancedTokenBucket{ TokenBucket: NewTokenBucket(5, 2), // 5 tokens, 2 per second }) multiLimiter.AddLimiter("sliding_window", &EnhancedSlidingWindow{ SlidingWindow: NewSlidingWindow(3, 2*time.Second), // 3 requests per 2 seconds }) multiLimiter.AddLimiter("fixed_window", &EnhancedFixedWindow{ FixedWindow: NewFixedWindow(4, 3*time.Second), // 4 requests per 3 seconds }) service := NewRateLimitedService(multiLimiter) fmt.Println("=== Multi-Algorithm Rate Limiter Demo ===") fmt.Println("Using Token Bucket (5 tokens, 2/sec) + Sliding Window (3/2sec) + Fixed Window (4/3sec)") // Simulate concurrent requests var wg sync.WaitGroup for i := 1; i <= 15; i++ { wg.Add(1) go func(id int) { defer wg.Done() ctx, cancel := context.WithTimeout(context.Background(), 1*time.Second) defer cancel() requestID := fmt.Sprintf("req-%d", id) err := service.ProcessRequest(ctx, requestID) if err != nil { fmt.Printf(" %v\n", err) } }(i) time.Sleep(200 * time.Millisecond) } wg.Wait() // Print final statistics fmt.Println("\n=== Final Statistics ===") stats := service.GetServiceStats() fmt.Printf("Total Requests: %d\n", stats["total_requests"]) fmt.Printf("Allowed Requests: %d\n", stats["allowed_requests"]) fmt.Printf("Denied Requests: %d\n", stats["denied_requests"]) fmt.Println("\nRate Limiter Details:") rateLimiterStats := stats["rate_limiter"].(map[string]interface{}) for name, limiterStats := range rateLimiterStats { fmt.Printf(" %s: %+v\n", name, limiterStats) } } Best Practices Choose Right Algorithm: Select based on your specific requirements Token Bucket: Allow bursts, good for APIs Sliding Window: Smooth rate limiting Fixed Window: Simple, memory efficient Configure Appropriately: Set limits based on system capacity Handle Rejections Gracefully: Provide meaningful error messages Monitor Metrics: Track allowed/denied requests and adjust limits Use Context: Support cancellation in Wait operations Consider Distributed Systems: Use Redis or similar for distributed rate limiting Implement Backoff: Add exponential backoff for denied requests Common Pitfalls Too Restrictive: Setting limits too low affects user experience Too Permissive: High limits don’t protect against abuse Memory Leaks: Not cleaning old requests in sliding window Race Conditions: Not properly synchronizing access to counters Ignoring Bursts: Fixed windows can allow double the limit at boundaries Rate limiting is essential for protecting services from overload and ensuring fair resource usage. Choose the right algorithm based on your requirements and always monitor the effectiveness of your rate limiting strategy. ...

Go Concurrency Patterns Series: ← Fan-Out/Fan-In | Series Overview | Request/Response → What is the Pub/Sub Pattern? The Publisher/Subscriber (Pub/Sub) pattern is a messaging pattern where publishers send messages without knowing who will receive them, and subscribers receive messages without knowing who sent them. This creates a loosely coupled system where components can communicate through events without direct dependencies. Key Components: Publisher: Sends messages/events Subscriber: Receives and processes messages/events Message Broker: Routes messages from publishers to subscribers Topics/Channels: Categories for organizing messages Real-World Use Cases Event-Driven Architecture: Microservices communication Real-Time Notifications: User activity feeds, alerts Data Streaming: Log aggregation, metrics collection UI Updates: React to state changes across components Workflow Orchestration: Trigger actions based on events Cache Invalidation: Notify when data changes Basic Pub/Sub Implementation package main import ( "fmt" "sync" "time" ) // Message represents a pub/sub message type Message struct { Topic string Payload interface{} } // Subscriber represents a message handler type Subscriber func(Message) // PubSub is a simple in-memory pub/sub system type PubSub struct { mu sync.RWMutex subscribers map[string][]Subscriber closed bool } // NewPubSub creates a new pub/sub instance func NewPubSub() *PubSub { return &PubSub{ subscribers: make(map[string][]Subscriber), } } // Subscribe adds a subscriber to a topic func (ps *PubSub) Subscribe(topic string, subscriber Subscriber) { ps.mu.Lock() defer ps.mu.Unlock() if ps.closed { return } ps.subscribers[topic] = append(ps.subscribers[topic], subscriber) } // Publish sends a message to all subscribers of a topic func (ps *PubSub) Publish(topic string, payload interface{}) { ps.mu.RLock() defer ps.mu.RUnlock() if ps.closed { return } message := Message{ Topic: topic, Payload: payload, } // Send to all subscribers asynchronously for _, subscriber := range ps.subscribers[topic] { go subscriber(message) } } // Close shuts down the pub/sub system func (ps *PubSub) Close() { ps.mu.Lock() defer ps.mu.Unlock() ps.closed = true } func main() { pubsub := NewPubSub() defer pubsub.Close() // Subscribe to user events pubsub.Subscribe("user.created", func(msg Message) { fmt.Printf("Email service: Welcome %v!\n", msg.Payload) }) pubsub.Subscribe("user.created", func(msg Message) { fmt.Printf("Analytics: New user registered: %v\n", msg.Payload) }) pubsub.Subscribe("user.deleted", func(msg Message) { fmt.Printf("Cleanup service: Remove user data for %v\n", msg.Payload) }) // Publish events pubsub.Publish("user.created", "[email protected]") pubsub.Publish("user.created", "[email protected]") pubsub.Publish("user.deleted", "[email protected]") // Wait for async processing time.Sleep(100 * time.Millisecond) } Advanced Pub/Sub with Channels package main import ( "context" "fmt" "sync" "time" ) // Event represents a structured event type Event struct { ID string Type string Timestamp time.Time Data interface{} } // Subscription represents an active subscription type Subscription struct { ID string Topic string Channel chan Event Filter func(Event) bool cancel context.CancelFunc } // Close cancels the subscription func (s *Subscription) Close() { if s.cancel != nil { s.cancel() } } // EventBus is a channel-based pub/sub system type EventBus struct { mu sync.RWMutex subscriptions map[string][]*Subscription buffer int closed bool } // NewEventBus creates a new event bus func NewEventBus(bufferSize int) *EventBus { return &EventBus{ subscriptions: make(map[string][]*Subscription), buffer: bufferSize, } } // Subscribe creates a new subscription with optional filtering func (eb *EventBus) Subscribe(ctx context.Context, topic string, filter func(Event) bool) *Subscription { eb.mu.Lock() defer eb.mu.Unlock() if eb.closed { return nil } subCtx, cancel := context.WithCancel(ctx) subscription := &Subscription{ ID: fmt.Sprintf("sub-%d", time.Now().UnixNano()), Topic: topic, Channel: make(chan Event, eb.buffer), Filter: filter, cancel: cancel, } eb.subscriptions[topic] = append(eb.subscriptions[topic], subscription) // Clean up subscription when context is cancelled go func() { <-subCtx.Done() eb.unsubscribe(subscription) close(subscription.Channel) }() return subscription } // unsubscribe removes a subscription func (eb *EventBus) unsubscribe(sub *Subscription) { eb.mu.Lock() defer eb.mu.Unlock() subs := eb.subscriptions[sub.Topic] for i, s := range subs { if s.ID == sub.ID { eb.subscriptions[sub.Topic] = append(subs[:i], subs[i+1:]...) break } } } // Publish sends an event to all matching subscribers func (eb *EventBus) Publish(event Event) { eb.mu.RLock() defer eb.mu.RUnlock() if eb.closed { return } event.Timestamp = time.Now() for _, subscription := range eb.subscriptions[event.Type] { // Apply filter if present if subscription.Filter != nil && !subscription.Filter(event) { continue } // Non-blocking send select { case subscription.Channel <- event: default: // Channel is full, could log this fmt.Printf("Warning: Subscription %s channel is full\n", subscription.ID) } } } // Close shuts down the event bus func (eb *EventBus) Close() { eb.mu.Lock() defer eb.mu.Unlock() eb.closed = true // Close all subscriptions for _, subs := range eb.subscriptions { for _, sub := range subs { sub.Close() } } } func main() { ctx := context.Background() eventBus := NewEventBus(10) defer eventBus.Close() // Subscribe to all user events userSub := eventBus.Subscribe(ctx, "user", nil) // Subscribe to only high-priority events prioritySub := eventBus.Subscribe(ctx, "user", func(e Event) bool { if data, ok := e.Data.(map[string]interface{}); ok { return data["priority"] == "high" } return false }) // Start event processors go func() { for event := range userSub.Channel { fmt.Printf("User processor: %s - %v\n", event.Type, event.Data) } }() go func() { for event := range prioritySub.Channel { fmt.Printf("Priority processor: %s - %v\n", event.Type, event.Data) } }() // Publish events eventBus.Publish(Event{ ID: "1", Type: "user", Data: map[string]interface{}{ "action": "login", "user": "john", "priority": "low", }, }) eventBus.Publish(Event{ ID: "2", Type: "user", Data: map[string]interface{}{ "action": "payment", "user": "jane", "priority": "high", }, }) time.Sleep(100 * time.Millisecond) } Persistent Pub/Sub with Replay package main import ( "context" "fmt" "sync" "time" ) // StoredEvent represents an event with storage metadata type StoredEvent struct { Event Sequence int64 Stored time.Time } // PersistentEventBus stores events and supports replay type PersistentEventBus struct { mu sync.RWMutex events []StoredEvent sequence int64 subs map[string][]*PersistentSubscription closed bool } // PersistentSubscription supports replay from a specific point type PersistentSubscription struct { ID string Topic string Channel chan StoredEvent FromSeq int64 cancel context.CancelFunc } func (s *PersistentSubscription) Close() { if s.cancel != nil { s.cancel() } } // NewPersistentEventBus creates a new persistent event bus func NewPersistentEventBus() *PersistentEventBus { return &PersistentEventBus{ events: make([]StoredEvent, 0), subs: make(map[string][]*PersistentSubscription), } } // Subscribe creates a subscription with optional replay func (peb *PersistentEventBus) Subscribe(ctx context.Context, topic string, fromSequence int64) *PersistentSubscription { peb.mu.Lock() defer peb.mu.Unlock() if peb.closed { return nil } subCtx, cancel := context.WithCancel(ctx) sub := &PersistentSubscription{ ID: fmt.Sprintf("psub-%d", time.Now().UnixNano()), Topic: topic, Channel: make(chan StoredEvent, 100), FromSeq: fromSequence, cancel: cancel, } peb.subs[topic] = append(peb.subs[topic], sub) // Replay historical events if requested if fromSequence >= 0 { go peb.replayEvents(sub) } // Clean up on context cancellation go func() { <-subCtx.Done() peb.unsubscribe(sub) close(sub.Channel) }() return sub } // replayEvents sends historical events to a subscription func (peb *PersistentEventBus) replayEvents(sub *PersistentSubscription) { peb.mu.RLock() defer peb.mu.RUnlock() for _, storedEvent := range peb.events { if storedEvent.Sequence >= sub.FromSeq && storedEvent.Type == sub.Topic { select { case sub.Channel <- storedEvent: default: // Channel full, skip } } } } // unsubscribe removes a subscription func (peb *PersistentEventBus) unsubscribe(sub *PersistentSubscription) { peb.mu.Lock() defer peb.mu.Unlock() subs := peb.subs[sub.Topic] for i, s := range subs { if s.ID == sub.ID { peb.subs[sub.Topic] = append(subs[:i], subs[i+1:]...) break } } } // Publish stores and distributes an event func (peb *PersistentEventBus) Publish(event Event) int64 { peb.mu.Lock() defer peb.mu.Unlock() if peb.closed { return -1 } peb.sequence++ storedEvent := StoredEvent{ Event: event, Sequence: peb.sequence, Stored: time.Now(), } // Store event peb.events = append(peb.events, storedEvent) // Distribute to current subscribers for _, sub := range peb.subs[event.Type] { select { case sub.Channel <- storedEvent: default: // Channel full } } return peb.sequence } // GetLastSequence returns the last event sequence number func (peb *PersistentEventBus) GetLastSequence() int64 { peb.mu.RLock() defer peb.mu.RUnlock() return peb.sequence } func main() { ctx := context.Background() eventBus := NewPersistentEventBus() // Publish some initial events eventBus.Publish(Event{ID: "1", Type: "order", Data: "Order created"}) eventBus.Publish(Event{ID: "2", Type: "order", Data: "Order paid"}) eventBus.Publish(Event{ID: "3", Type: "order", Data: "Order shipped"}) fmt.Printf("Published 3 events, last sequence: %d\n", eventBus.GetLastSequence()) // Subscribe from the beginning (replay all events) replaySub := eventBus.Subscribe(ctx, "order", 0) // Subscribe from current point (no replay) liveSub := eventBus.Subscribe(ctx, "order", -1) // Process replayed events go func() { fmt.Println("Replay subscription:") for event := range replaySub.Channel { fmt.Printf(" Replayed: seq=%d, %v\n", event.Sequence, event.Data) } }() // Process live events go func() { fmt.Println("Live subscription:") for event := range liveSub.Channel { fmt.Printf(" Live: seq=%d, %v\n", event.Sequence, event.Data) } }() time.Sleep(100 * time.Millisecond) // Publish new events eventBus.Publish(Event{ID: "4", Type: "order", Data: "Order delivered"}) eventBus.Publish(Event{ID: "5", Type: "order", Data: "Order completed"}) time.Sleep(100 * time.Millisecond) replaySub.Close() liveSub.Close() } Typed Pub/Sub System package main import ( "context" "fmt" "reflect" "sync" ) // TypedEventBus provides type-safe pub/sub type TypedEventBus struct { mu sync.RWMutex handlers map[reflect.Type][]reflect.Value closed bool } // NewTypedEventBus creates a new typed event bus func NewTypedEventBus() *TypedEventBus { return &TypedEventBus{ handlers: make(map[reflect.Type][]reflect.Value), } } // Subscribe registers a handler for a specific event type func (teb *TypedEventBus) Subscribe(handler interface{}) { teb.mu.Lock() defer teb.mu.Unlock() if teb.closed { return } handlerValue := reflect.ValueOf(handler) handlerType := handlerValue.Type() // Validate handler signature: func(EventType) if handlerType.Kind() != reflect.Func || handlerType.NumIn() != 1 || handlerType.NumOut() != 0 { panic("Handler must be func(EventType)") } eventType := handlerType.In(0) teb.handlers[eventType] = append(teb.handlers[eventType], handlerValue) } // Publish sends an event to all registered handlers func (teb *TypedEventBus) Publish(event interface{}) { teb.mu.RLock() defer teb.mu.RUnlock() if teb.closed { return } eventType := reflect.TypeOf(event) eventValue := reflect.ValueOf(event) for _, handler := range teb.handlers[eventType] { go handler.Call([]reflect.Value{eventValue}) } } // Event types type UserCreated struct { UserID string Email string } type OrderPlaced struct { OrderID string UserID string Amount float64 } type PaymentProcessed struct { PaymentID string OrderID string Success bool } func main() { eventBus := NewTypedEventBus() // Subscribe to different event types eventBus.Subscribe(func(event UserCreated) { fmt.Printf("Email service: Send welcome email to %s\n", event.Email) }) eventBus.Subscribe(func(event UserCreated) { fmt.Printf("Analytics: Track user registration %s\n", event.UserID) }) eventBus.Subscribe(func(event OrderPlaced) { fmt.Printf("Inventory: Reserve items for order %s\n", event.OrderID) }) eventBus.Subscribe(func(event OrderPlaced) { fmt.Printf("Payment: Process payment for order %s, amount $%.2f\n", event.OrderID, event.Amount) }) eventBus.Subscribe(func(event PaymentProcessed) { if event.Success { fmt.Printf("Fulfillment: Ship order %s\n", event.OrderID) } else { fmt.Printf("Orders: Cancel order %s due to payment failure\n", event.OrderID) } }) // Publish events eventBus.Publish(UserCreated{ UserID: "user123", Email: "[email protected]", }) eventBus.Publish(OrderPlaced{ OrderID: "order456", UserID: "user123", Amount: 99.99, }) eventBus.Publish(PaymentProcessed{ PaymentID: "pay789", OrderID: "order456", Success: true, }) // Wait for async processing time.Sleep(100 * time.Millisecond) } Best Practices Async Processing: Handle events asynchronously to avoid blocking publishers Error Handling: Implement proper error handling in subscribers Buffering: Use buffered channels to handle bursts of events Graceful Shutdown: Ensure clean shutdown of all subscribers Dead Letter Queues: Handle failed message processing Monitoring: Track message rates, processing times, and failures Type Safety: Use typed events when possible Idempotency: Design subscribers to handle duplicate messages Common Pitfalls Memory Leaks: Not closing subscriptions properly Blocking Publishers: Slow subscribers blocking the entire system Lost Messages: Not handling channel buffer overflows Circular Dependencies: Events triggering other events in loops No Error Handling: Panics in subscribers affecting the system Testing Pub/Sub Systems package main import ( "context" "testing" "time" ) func TestEventBus(t *testing.T) { eventBus := NewEventBus(10) defer eventBus.Close() ctx, cancel := context.WithTimeout(context.Background(), time.Second) defer cancel() // Subscribe to events sub := eventBus.Subscribe(ctx, "test", nil) // Publish event testEvent := Event{ ID: "test1", Type: "test", Data: "test data", } eventBus.Publish(testEvent) // Verify event received select { case received := <-sub.Channel: if received.ID != testEvent.ID { t.Errorf("Expected event ID %s, got %s", testEvent.ID, received.ID) } case <-time.After(100 * time.Millisecond): t.Error("Event not received within timeout") } } The Pub/Sub pattern is fundamental for building scalable, event-driven systems in Go. It enables loose coupling between components and supports complex workflows through simple event-based communication. ...

What is Template Method Pattern? The Template Method pattern is a behavioral design pattern that defines the skeleton of an algorithm in a base class and lets subclasses override specific steps without changing the algorithm’s structure. Think of it like a recipe - the overall cooking process is the same (prepare ingredients, cook, serve), but the specific steps can vary depending on what you’re making. In Go, since we don’t have traditional inheritance, we implement this pattern using composition and interfaces, which actually makes it more flexible and idiomatic. ...

Go Concurrency Patterns Series: ← WaitGroup Pattern | Series Overview | Context Pattern → What is the Once Pattern? The Once pattern uses sync.Once to ensure that a piece of code executes exactly once, regardless of how many goroutines call it. This is essential for thread-safe initialization, singleton patterns, and one-time setup operations in concurrent programs. Key Characteristics: Thread-safe: Multiple goroutines can call it safely Exactly once: Code executes only on the first call Blocking: Subsequent calls wait for the first execution to complete No return values: The function passed to Do() cannot return values Real-World Use Cases Singleton Initialization: Create single instances of objects Configuration Loading: Load config files once at startup Database Connections: Initialize connection pools Logger Setup: Configure logging systems Resource Initialization: Set up expensive resources Feature Flags: Initialize feature flag systems Basic Once Usage package main import ( "fmt" "sync" "time" ) var ( instance *Database once sync.Once ) // Database represents a database connection type Database struct { ConnectionString string IsConnected bool } // Connect simulates database connection func (db *Database) Connect() { fmt.Println("Connecting to database...") time.Sleep(100 * time.Millisecond) // Simulate connection time db.IsConnected = true fmt.Println("Database connected!") } // GetDatabase returns the singleton database instance func GetDatabase() *Database { once.Do(func() { fmt.Println("Initializing database instance...") instance = &Database{ ConnectionString: "localhost:5432", } instance.Connect() }) return instance } func main() { var wg sync.WaitGroup // Multiple goroutines trying to get database instance for i := 0; i < 5; i++ { wg.Add(1) go func(id int) { defer wg.Done() fmt.Printf("Goroutine %d requesting database\n", id) db := GetDatabase() fmt.Printf("Goroutine %d got database: %+v\n", id, db) }(i) } wg.Wait() // Verify all goroutines got the same instance fmt.Printf("Final instance: %p\n", GetDatabase()) } Configuration Manager with Once package main import ( "encoding/json" "fmt" "os" "sync" ) // Config represents application configuration type Config struct { DatabaseURL string `json:"database_url"` APIKey string `json:"api_key"` Debug bool `json:"debug"` Port int `json:"port"` } // ConfigManager manages application configuration type ConfigManager struct { config *Config once sync.Once err error } // NewConfigManager creates a new config manager func NewConfigManager() *ConfigManager { return &ConfigManager{} } // loadConfig loads configuration from file func (cm *ConfigManager) loadConfig() { fmt.Println("Loading configuration...") // Simulate config file reading configData := `{ "database_url": "postgres://localhost:5432/myapp", "api_key": "secret-api-key-123", "debug": true, "port": 8080 }` var config Config if err := json.Unmarshal([]byte(configData), &config); err != nil { cm.err = fmt.Errorf("failed to parse config: %w", err) return } cm.config = &config fmt.Println("Configuration loaded successfully!") } // GetConfig returns the configuration, loading it once if needed func (cm *ConfigManager) GetConfig() (*Config, error) { cm.once.Do(cm.loadConfig) return cm.config, cm.err } func main() { configManager := NewConfigManager() var wg sync.WaitGroup // Multiple goroutines accessing configuration for i := 0; i < 3; i++ { wg.Add(1) go func(id int) { defer wg.Done() config, err := configManager.GetConfig() if err != nil { fmt.Printf("Goroutine %d: Error loading config: %v\n", id, err) return } fmt.Printf("Goroutine %d: Port=%d, Debug=%v\n", id, config.Port, config.Debug) }(i) } wg.Wait() } Logger Initialization with Once package main import ( "fmt" "log" "os" "sync" ) // Logger wraps the standard logger with additional functionality type Logger struct { *log.Logger level string } var ( logger *Logger loggerOnce sync.Once ) // initLogger initializes the global logger func initLogger() { fmt.Println("Initializing logger...") // Create log file file, err := os.OpenFile("app.log", os.O_CREATE|os.O_WRONLY|os.O_APPEND, 0666) if err != nil { log.Fatalln("Failed to open log file:", err) } logger = &Logger{ Logger: log.New(file, "APP: ", log.Ldate|log.Ltime|log.Lshortfile), level: "INFO", } logger.Println("Logger initialized") fmt.Println("Logger setup complete!") } // GetLogger returns the singleton logger instance func GetLogger() *Logger { loggerOnce.Do(initLogger) return logger } // Info logs an info message func (l *Logger) Info(msg string) { l.Printf("[INFO] %s", msg) } // Error logs an error message func (l *Logger) Error(msg string) { l.Printf("[ERROR] %s", msg) } func main() { var wg sync.WaitGroup // Multiple goroutines using the logger for i := 0; i < 5; i++ { wg.Add(1) go func(id int) { defer wg.Done() logger := GetLogger() logger.Info(fmt.Sprintf("Message from goroutine %d", id)) if id%2 == 0 { logger.Error(fmt.Sprintf("Error from goroutine %d", id)) } }(i) } wg.Wait() // Clean up if logger != nil { logger.Info("Application shutting down") } } Resource Pool Initialization package main import ( "fmt" "sync" "time" ) // Connection represents a database connection type Connection struct { ID int Connected bool } // Connect simulates connecting to database func (c *Connection) Connect() error { time.Sleep(50 * time.Millisecond) // Simulate connection time c.Connected = true return nil } // Close simulates closing the connection func (c *Connection) Close() error { c.Connected = false return nil } // ConnectionPool manages a pool of database connections type ConnectionPool struct { connections []*Connection available chan *Connection once sync.Once initErr error } // NewConnectionPool creates a new connection pool func NewConnectionPool(size int) *ConnectionPool { return &ConnectionPool{ available: make(chan *Connection, size), } } // initialize sets up the connection pool func (cp *ConnectionPool) initialize() { fmt.Println("Initializing connection pool...") poolSize := cap(cp.available) cp.connections = make([]*Connection, poolSize) // Create and connect all connections for i := 0; i < poolSize; i++ { conn := &Connection{ID: i + 1} if err := conn.Connect(); err != nil { cp.initErr = fmt.Errorf("failed to connect connection %d: %w", i+1, err) return } cp.connections[i] = conn cp.available <- conn } fmt.Printf("Connection pool initialized with %d connections\n", poolSize) } // GetConnection gets a connection from the pool func (cp *ConnectionPool) GetConnection() (*Connection, error) { cp.once.Do(cp.initialize) if cp.initErr != nil { return nil, cp.initErr } select { case conn := <-cp.available: return conn, nil case <-time.After(5 * time.Second): return nil, fmt.Errorf("timeout waiting for connection") } } // ReturnConnection returns a connection to the pool func (cp *ConnectionPool) ReturnConnection(conn *Connection) { select { case cp.available <- conn: default: // Pool is full, close the connection conn.Close() } } // Close closes all connections in the pool func (cp *ConnectionPool) Close() error { close(cp.available) for _, conn := range cp.connections { if conn != nil { conn.Close() } } return nil } func main() { pool := NewConnectionPool(3) defer pool.Close() var wg sync.WaitGroup // Multiple goroutines using the connection pool for i := 0; i < 5; i++ { wg.Add(1) go func(id int) { defer wg.Done() conn, err := pool.GetConnection() if err != nil { fmt.Printf("Worker %d: Failed to get connection: %v\n", id, err) return } fmt.Printf("Worker %d: Got connection %d\n", id, conn.ID) // Simulate work time.Sleep(200 * time.Millisecond) pool.ReturnConnection(conn) fmt.Printf("Worker %d: Returned connection %d\n", id, conn.ID) }(i) } wg.Wait() } Advanced Once Patterns 1. Once with Error Handling package main import ( "fmt" "sync" ) // OnceWithError provides Once functionality with error handling type OnceWithError struct { once sync.Once err error } // Do executes the function once and stores any error func (o *OnceWithError) Do(f func() error) error { o.once.Do(func() { o.err = f() }) return o.err } // ExpensiveResource represents a resource that's expensive to initialize type ExpensiveResource struct { Data string } var ( resource *ExpensiveResource resourceOnce OnceWithError ) // initResource initializes the expensive resource func initResource() error { fmt.Println("Initializing expensive resource...") // Simulate potential failure if false { // Change to true to simulate error return fmt.Errorf("failed to initialize resource") } resource = &ExpensiveResource{ Data: "Important data", } fmt.Println("Resource initialized successfully!") return nil } // GetResource returns the resource, initializing it once if needed func GetResource() (*ExpensiveResource, error) { err := resourceOnce.Do(initResource) if err != nil { return nil, err } return resource, nil } func main() { var wg sync.WaitGroup for i := 0; i < 3; i++ { wg.Add(1) go func(id int) { defer wg.Done() resource, err := GetResource() if err != nil { fmt.Printf("Goroutine %d: Error: %v\n", id, err) return } fmt.Printf("Goroutine %d: Got resource: %s\n", id, resource.Data) }(i) } wg.Wait() } 2. Resettable Once package main import ( "fmt" "sync" "sync/atomic" ) // ResettableOnce allows resetting the once behavior type ResettableOnce struct { mu sync.Mutex done uint32 } // Do executes the function once func (ro *ResettableOnce) Do(f func()) { if atomic.LoadUint32(&ro.done) == 0 { ro.doSlow(f) } } func (ro *ResettableOnce) doSlow(f func()) { ro.mu.Lock() defer ro.mu.Unlock() if ro.done == 0 { defer atomic.StoreUint32(&ro.done, 1) f() } } // Reset allows the once to be used again func (ro *ResettableOnce) Reset() { ro.mu.Lock() defer ro.mu.Unlock() atomic.StoreUint32(&ro.done, 0) } // IsDone returns true if the function has been executed func (ro *ResettableOnce) IsDone() bool { return atomic.LoadUint32(&ro.done) == 1 } func main() { var once ResettableOnce counter := 0 task := func() { counter++ fmt.Printf("Task executed, counter: %d\n", counter) } // First round fmt.Println("First round:") for i := 0; i < 3; i++ { once.Do(task) } fmt.Printf("Done: %v\n", once.IsDone()) // Reset and second round fmt.Println("\nAfter reset:") once.Reset() fmt.Printf("Done: %v\n", once.IsDone()) for i := 0; i < 3; i++ { once.Do(task) } } Best Practices Use for Initialization: Perfect for one-time setup operations Keep Functions Simple: The function passed to Do() should be straightforward Handle Errors Separately: Use wrapper types for error handling Avoid Side Effects: Be careful with functions that have external side effects Don’t Nest Once Calls: Avoid calling Do() from within another Do() Consider Alternatives: Use init() for package-level initialization when appropriate Common Pitfalls 1. Expecting Return Values // Bad: Once.Do doesn't support return values var once sync.Once var result string func badExample() string { once.Do(func() { // Can't return from here result = "computed value" }) return result // This works but is not ideal } // Good: Use a wrapper or store results in accessible variables type OnceResult struct { once sync.Once result string err error } func (or *OnceResult) Get() (string, error) { or.once.Do(func() { or.result, or.err = computeValue() }) return or.result, or.err } 2. Panic in Once Function // Bad: Panic prevents future calls var once sync.Once func badOnceFunc() { once.Do(func() { panic("something went wrong") // Once will never execute again }) } // Good: Handle panics appropriately func goodOnceFunc() { once.Do(func() { defer func() { if r := recover(); r != nil { // Handle panic appropriately fmt.Printf("Recovered from panic: %v\n", r) } }() // risky operation }) } Testing Once Patterns package main import ( "sync" "testing" ) func TestOnceExecution(t *testing.T) { var once sync.Once counter := 0 var wg sync.WaitGroup // Start multiple goroutines for i := 0; i < 10; i++ { wg.Add(1) go func() { defer wg.Done() once.Do(func() { counter++ }) }() } wg.Wait() if counter != 1 { t.Errorf("Expected counter to be 1, got %d", counter) } } func TestOnceWithError(t *testing.T) { var onceErr OnceWithError callCount := 0 // First call with error err1 := onceErr.Do(func() error { callCount++ return fmt.Errorf("test error") }) // Second call should return same error without executing function err2 := onceErr.Do(func() error { callCount++ return nil }) if callCount != 1 { t.Errorf("Expected function to be called once, got %d", callCount) } if err1 == nil || err2 == nil { t.Error("Expected both calls to return error") } if err1.Error() != err2.Error() { t.Error("Expected same error from both calls") } } The Once pattern is essential for thread-safe initialization in Go. It ensures that expensive or critical setup operations happen exactly once, making it perfect for singletons, configuration loading, and resource initialization in concurrent applications. ...

From Object-Oriented to Data-Oriented Traditional object-oriented programming (OOP) encourages you to model game entities as objects with inheritance hierarchies. While intuitive, this approach leads to poor cache locality, rigid hierarchies, and performance bottlenecks. Data-oriented design, particularly the Entity Component System (ECS) pattern, flips this on its head. With Go 1.18+ generics, we can now build type-safe ECS architectures that deliver both performance and flexibility. Let me show you how. The OOP Problem Here’s the typical OOP approach to game entities: ...