go-concurrency

Go Concurrency Skill

This skill provides expert guidance on Go's concurrency primitives and patterns, covering goroutines, channels, synchronization, and best practices for building concurrent systems.

When to Use

Activate this skill when:

• Implementing concurrent/parallel processing
• Working with goroutines and channels
• Using synchronization primitives (mutexes, wait groups, etc.)
• Debugging race conditions
• Optimizing concurrent performance
• Implementing worker pools or pipelines
• Handling context cancellation

Goroutine Fundamentals

Basic Goroutines

// Simple goroutine
go func() {
    fmt.Println("Hello from goroutine")
}()

// Goroutine with parameters
go func(msg string) {
    fmt.Println(msg)
}("Hello")

// Goroutine with closure
message := "Hello"
go func() {
    fmt.Println(message) // Captures message
}()

Common Pitfalls

// ❌ BAD: Loop variable capture
for i := 0; i < 5; i++ {
    go func() {
        fmt.Println(i) // All goroutines may print 5
    }()
}

// ✅ GOOD: Pass as parameter
for i := 0; i < 5; i++ {
    go func(n int) {
        fmt.Println(n) // Each prints correct value
    }(i)
}

// ✅ GOOD: Create local copy
for i := 0; i < 5; i++ {
    i := i // Create new variable
    go func() {
        fmt.Println(i)
    }()
}

Channel Patterns

Channel Types

// Unbuffered channel (synchronous)
ch := make(chan int)

// Buffered channel (asynchronous up to buffer size)
ch := make(chan int, 10)

// Send-only channel
func send(ch chan<- int) {
    ch <- 42
}

// Receive-only channel
func receive(ch <-chan int) {
    value := <-ch
}

// Bidirectional channel
ch := make(chan int)

Channel Operations

// Send
ch <- value

// Receive
value := <-ch

// Receive with ok check
value, ok := <-ch
if !ok {
    // Channel closed
}

// Close channel
close(ch)

// Range over channel
for value := range ch {
    fmt.Println(value)
}

Select Statement

// Wait for first available operation
select {
case msg1 := <-ch1:
    fmt.Println("Received from ch1:", msg1)
case msg2 := <-ch2:
    fmt.Println("Received from ch2:", msg2)
case ch3 <- value:
    fmt.Println("Sent to ch3")
default:
    fmt.Println("No channels ready")
}

// Timeout pattern
select {
case result := <-ch:
    return result, nil
case <-time.After(5 * time.Second):
    return nil, errors.New("timeout")
}

// Context cancellation
select {
case result := <-ch:
    return result, nil
case <-ctx.Done():
    return nil, ctx.Err()
}

Synchronization Primitives

Mutex

type SafeCounter struct {
    mu    sync.Mutex
    count int
}

func (c *SafeCounter) Increment() {
    c.mu.Lock()
    defer c.mu.Unlock()
    c.count++
}

func (c *SafeCounter) Value() int {
    c.mu.Lock()
    defer c.mu.Unlock()
    return c.count
}

RWMutex

type Cache struct {
    mu    sync.RWMutex
    items map[string]interface{}
}

func (c *Cache) Get(key string) (interface{}, bool) {
    c.mu.RLock() // Multiple readers allowed
    defer c.mu.RUnlock()
    value, ok := c.items[key]
    return value, ok
}

func (c *Cache) Set(key string, value interface{}) {
    c.mu.Lock() // Exclusive write access
    defer c.mu.Unlock()
    c.items[key] = value
}

WaitGroup

func processItems(items []Item) {
    var wg sync.WaitGroup

    for _, item := range items {
        wg.Add(1)
        go func(item Item) {
            defer wg.Done()
            process(item)
        }(item)
    }

    wg.Wait() // Wait for all goroutines
}

Once

type Database struct {
    instance *sql.DB
    once     sync.Once
}

func (d *Database) GetConnection() *sql.DB {
    d.once.Do(func() {
        d.instance, _ = sql.Open("postgres", "connection-string")
    })
    return d.instance
}

Concurrency Patterns

Worker Pool

type WorkerPool struct {
    workerCount int
    jobs        chan Job
    results     chan Result
    wg          sync.WaitGroup
}

type Job struct {
    ID   int
    Data interface{}
}

type Result struct {
    JobID int
    Value interface{}
    Error error
}

func NewWorkerPool(workerCount int) *WorkerPool {
    return &WorkerPool{
        workerCount: workerCount,
        jobs:        make(chan Job, 100),
        results:     make(chan Result, 100),
    }
}

func (p *WorkerPool) Start(ctx context.Context) {
    for i := 0; i < p.workerCount; i++ {
        p.wg.Add(1)
        go p.worker(ctx)
    }
}

func (p *WorkerPool) worker(ctx context.Context) {
    defer p.wg.Done()

    for {
        select {
        case job, ok := <-p.jobs:
            if !ok {
                return
            }
            result := processJob(job)
            select {
            case p.results <- result:
            case <-ctx.Done():
                return
            }
        case <-ctx.Done():
            return
        }
    }
}

func (p *WorkerPool) Submit(job Job) {
    p.jobs <- job
}

func (p *WorkerPool) Results() <-chan Result {
    return p.results
}

func (p *WorkerPool) Close() {
    close(p.jobs)
    p.wg.Wait()
    close(p.results)
}

// Usage
ctx := context.Background()
pool := NewWorkerPool(10)
pool.Start(ctx)

for i := 0; i < 100; i++ {
    pool.Submit(Job{ID: i, Data: fmt.Sprintf("job-%d", i)})
}

go func() {
    for result := range pool.Results() {
        if result.Error != nil {
            log.Printf("Job %d failed: %v", result.JobID, result.Error)
        } else {
            log.Printf("Job %d completed: %v", result.JobID, result.Value)
        }
    }
}()

pool.Close()

Pipeline Pattern

// Generator stage
func generator(ctx context.Context, nums ...int) <-chan int {
    out := make(chan int)
    go func() {
        defer close(out)
        for _, n := range nums {
            select {
            case out <- n:
            case <-ctx.Done():
                return
            }
        }
    }()
    return out
}

// Processing stage
func square(ctx context.Context, in <-chan int) <-chan int {
    out := make(chan int)
    go func() {
        defer close(out)
        for n := range in {
            select {
            case out <- n * n:
            case <-ctx.Done():
                return
            }
        }
    }()
    return out
}

// Another processing stage
func double(ctx context.Context, in <-chan int) <-chan int {
    out := make(chan int)
    go func() {
        defer close(out)
        for n := range in {
            select {
            case out <- n * 2:
            case <-ctx.Done():
                return
            }
        }
    }()
    return out
}

// Usage - compose pipeline
ctx := context.Background()
numbers := generator(ctx, 1, 2, 3, 4, 5)
squared := square(ctx, numbers)
doubled := double(ctx, squared)

for result := range doubled {
    fmt.Println(result)
}

Fan-Out/Fan-In

// Fan-out: distribute work to multiple goroutines
func fanOut(ctx context.Context, input <-chan int, workers int) []<-chan int {
    channels := make([]<-chan int, workers)

    for i := 0; i < workers; i++ {
        channels[i] = worker(ctx, input)
    }

    return channels
}

func worker(ctx context.Context, input <-chan int) <-chan int {
    output := make(chan int)
    go func() {
        defer close(output)
        for n := range input {
            select {
            case output <- expensiveOperation(n):
            case <-ctx.Done():
                return
            }
        }
    }()
    return output
}

// Fan-in: merge multiple channels into one
func fanIn(ctx context.Context, channels ...<-chan int) <-chan int {
    var wg sync.WaitGroup
    output := make(chan int)

    multiplex := func(ch <-chan int) {
        defer wg.Done()
        for n := range ch {
            select {
            case output <- n:
            case <-ctx.Done():
                return
            }
        }
    }

    wg.Add(len(channels))
    for _, ch := range channels {
        go multiplex(ch)
    }

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

    return output
}

// Usage
ctx := context.Background()
input := generator(ctx, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10)

// Fan-out to 3 workers
workers := fanOut(ctx, input, 3)

// Fan-in results
results := fanIn(ctx, workers...)

for result := range results {
    fmt.Println(result)
}

Semaphore Pattern

type Semaphore struct {
    sem chan struct{}
}

func NewSemaphore(maxConcurrency int) *Semaphore {
    return &Semaphore{
        sem: make(chan struct{}, maxConcurrency),
    }
}

func (s *Semaphore) Acquire() {
    s.sem <- struct{}{}
}

func (s *Semaphore) Release() {
    <-s.sem
}

// Usage
sem := NewSemaphore(5) // Max 5 concurrent operations

for _, item := range items {
    sem.Acquire()
    go func(item Item) {
        defer sem.Release()
        process(item)
    }(item)
}

Rate Limiting

// Token bucket rate limiter
type RateLimiter struct {
    ticker   *time.Ticker
    tokens   chan struct{}
}

func NewRateLimiter(rate time.Duration, burst int) *RateLimiter {
    rl := &RateLimiter{
        ticker: time.NewTicker(rate),
        tokens: make(chan struct{}, burst),
    }

    // Fill bucket initially
    for i := 0; i < burst; i++ {
        rl.tokens <- struct{}{}
    }

    // Refill tokens
    go func() {
        for range rl.ticker.C {
            select {
            case rl.tokens <- struct{}{}:
            default:
            }
        }
    }()

    return rl
}

func (rl *RateLimiter) Wait(ctx context.Context) error {
    select {
    case <-rl.tokens:
        return nil
    case <-ctx.Done():
        return ctx.Err()
    }
}

func (rl *RateLimiter) Stop() {
    rl.ticker.Stop()
}

// Usage
limiter := NewRateLimiter(time.Second/10, 5) // 10 requests per second, burst of 5
defer limiter.Stop()

for _, request := range requests {
    if err := limiter.Wait(ctx); err != nil {
        log.Printf("Rate limit error: %v", err)
        continue
    }
    processRequest(request)
}

Error Handling in Concurrent Code

errgroup Package

import "golang.org/x/sync/errgroup"

func fetchURLs(ctx context.Context, urls []string) error {
    g, ctx := errgroup.WithContext(ctx)

    for _, url := range urls {
        url := url // Capture for goroutine
        g.Go(func() error {
            return fetchURL(ctx, url)
        })
    }

    // Wait for all goroutines, return first error
    return g.Wait()
}

// With limited concurrency
func fetchURLsLimited(ctx context.Context, urls []string) error {
    g, ctx := errgroup.WithContext(ctx)
    g.SetLimit(10) // Max 10 concurrent

    for _, url := range urls {
        url := url
        g.Go(func() error {
            return fetchURL(ctx, url)
        })
    }

    return g.Wait()
}

Best Practices

1. Always close channels from sender side
2. Use context for cancellation and timeouts
3. Avoid goroutine leaks - ensure they can exit
4. Use buffered channels to avoid blocking
5. Prefer sync.RWMutex for read-heavy workloads
6. Don't use defer in hot loops
7. Test with race detector: go test -race
8. Use errgroup for error propagation
9. Limit concurrent operations with worker pools
10. Profile before optimizing

Race Condition Detection

# Run tests with race detector
go test -race ./...

# Run program with race detector
go run -race main.go

# Build with race detector
go build -race

Common Patterns to Avoid

// ❌ BAD: Unbounded goroutine creation
for _, item := range millionItems {
    go process(item) // May create millions of goroutines
}

// ✅ GOOD: Use worker pool
pool := NewWorkerPool(100)
for _, item := range millionItems {
    pool.Submit(item)
}

// ❌ BAD: Goroutine leak
func leak() <-chan int {
    ch := make(chan int)
    go func() {
        ch <- expensiveComputation() // If receiver never reads, goroutine leaks
    }()
    return ch
}

// ✅ GOOD: Use context for cancellation
func noLeak(ctx context.Context) <-chan int {
    ch := make(chan int)
    go func() {
        defer close(ch)
        result := expensiveComputation()
        select {
        case ch <- result:
        case <-ctx.Done():
        }
    }()
    return ch
}

Resources

Additional examples and patterns are available in:

• assets/examples/ - Complete concurrency examples
• assets/patterns/ - Common concurrency patterns
• references/ - Links to Go concurrency resources and papers