Go Concurrency Tutorial

Concurrency is a fundamental strength of Go, designed into the language from the beginning. Go's concurrency model is based on goroutines and channels, providing an elegant way to write concurrent programs that can efficiently utilize multi-core processors.

1. Goroutines Basics

1.1 What are Goroutines?

Goroutines are lightweight threads managed by the Go runtime. They are much more efficient than OS threads and enable you to run thousands or even millions of concurrent operations.

// Starting a goroutine
func sayHello() {
    fmt.Println("Hello from goroutine!")
}

func main() {
    // Start a new goroutine
    go sayHello()
    
    // Give goroutine time to complete
    time.Sleep(100 * time.Millisecond)
}

1.2 Goroutines vs Threads

Key differences between goroutines and traditional threads:

  • Memory usage: Goroutines start with small stack (2KB) that grows as needed
  • Creation cost: Much cheaper than OS threads
  • Scheduling: Managed by Go runtime, not OS kernel
  • Communication: Designed to use channels for safe communication

1.3 Multiple Goroutines

You can easily start many goroutines:

func worker(id int) {
    fmt.Printf("Worker %d starting\n", id)
    time.Sleep(time.Second)
    fmt.Printf("Worker %d done\n", id)
}

func main() {
    for i := 1; i <= 5; i++ {
        go worker(i)
    }
    time.Sleep(2 * time.Second)
}

2. Channels

2.1 Channel Basics

Channels are typed conduits for communication between goroutines. They provide synchronization and safe data exchange.

// Creating and using channels
func main() {
    // Create a channel of strings
    messages := make(chan string)
    
    // Send a message in a goroutine
    go func() { messages <- "ping" }()
    
    // Receive the message
    msg := <-messages
    fmt.Println(msg) // "ping"
}

2.2 Channel Buffering

Channels can be buffered to allow sending without immediate receivers:

func main() {
    // Buffered channel with capacity of 2
    messages := make(chan string, 2)
    
    // Send without blocking
    messages <- "buffered"
    messages <- "channel"
    
    // Receive later
    fmt.Println(<-messages) // "buffered"
    fmt.Println(<-messages) // "channel"
}

2.3 Channel Directions

You can specify channel direction in function parameters for type safety:

// Only accepts a channel for sending
func ping(pings chan<- string, msg string) {
    pings <- msg
}

// Accepts one channel for receiving and another for sending
func pong(pings <-chan string, pongs chan<- string) {
    msg := <-pings
    pongs <- msg
}

3. Synchronization

3.1 WaitGroups

sync.WaitGroup waits for a collection of goroutines to finish:

func worker(id int, wg *sync.WaitGroup) {
    defer wg.Done() // Notify WaitGroup when done
    
    fmt.Printf("Worker %d starting\n", id)
    time.Sleep(time.Second)
    fmt.Printf("Worker %d done\n", id)
}

func main() {
    var wg sync.WaitGroup
    
    for i := 1; i <= 5; i++ {
        wg.Add(1) // Increment WaitGroup counter
        go worker(i, &wg)
    }
    
    wg.Wait() // Block until all workers complete
}

3.2 Mutexes

Mutexes protect shared state from concurrent access:

type SafeCounter struct {
    mu    sync.Mutex
    count int
}

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

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

3.3 Once

sync.Once ensures code runs exactly once:

var (
    once     sync.Once
    instance *Singleton
)

func getInstance() *Singleton {
    once.Do(func() {
        instance = &Singleton{}
    })
    return instance
}

4. Concurrency Patterns

4.1 Worker Pools

A pool of goroutines processing work from a channel:

func worker(id int, jobs <-chan int, results chan<- int) {
    for j := range jobs {
        fmt.Printf("worker %d started job %d\n", id, j)
        time.Sleep(time.Second)
        fmt.Printf("worker %d finished job %d\n", id, j)
        results <- j * 2
    }
}

func main() {
    jobs := make(chan int, 100)
    results := make(chan int, 100)
    
    // Start 3 workers
    for w := 1; w <= 3; w++ {
        go worker(w, jobs, results)
    }
    
    // Send 5 jobs
    for j := 1; j <= 5; j++ {
        jobs <- j
    }
    close(jobs)
    
    // Collect results
    for a := 1; a <= 5; a++ {
       <-results
    }
}

4.2 Fan-out/Fan-in

Distribute work to multiple goroutines (fan-out) and combine results (fan-in):

func producer(nums ...int) <-chan int {
    out := make(chan int)
    go func() {
        for _, n := range nums {
            out <- n
        }
        close(out)
    }()
    return out
}

func square(in <-chan int) <-chan int {
    out := make(chan int)
    go func() {
        for n := range in {
            out <- n * n
        }
        close(out)
    }()
    return out
}

func main() {
    // Set up the pipeline
    c := producer(1, 2, 3, 4)
    out := square(c)
    
    // Consume the output
    for n := range out {
        fmt.Println(n) // 1, 4, 9, 16
    }
}

4.3 Context

context package manages deadlines, cancellations across API boundaries:

func worker(ctx context.Context, wg *sync.WaitGroup) {
    defer wg.Done()
    
    for {
        select {
        case <-ctx.Done():
            fmt.Println("Worker cancelled")
            return
        default:
            // Do work
            fmt.Println("Working...")
            time.Sleep(500 * time.Millisecond)
        }
    }
}

func main() {
    ctx, cancel := context.WithTimeout(context.Background(), 2*time.Second)
    defer cancel()
    
    var wg sync.WaitGroup
    wg.Add(1)
    go worker(ctx, &wg)
    
    wg.Wait()
}

5. Advanced Topics

5.1 Select Statement

select lets a goroutine wait on multiple communication operations:

func main() {
    c1 := make(chan string)
    c2 := make(chan string)
    
    go func() {
        time.Sleep(1 * time.Second)
        c1 <- "one"
    }()
    
    go func() {
        time.Sleep(2 * time.Second)
        c2 <- "two"
    }()
    
    for i := 0; i < 2; i++ {
        select {
        case msg1 := <-c1:
            fmt.Println("received", msg1)
        case msg2 := <-c2:
            fmt.Println("received", msg2)
        }
    }
}

5.2 Timer and Ticker

Timers and tickers help with delayed or periodic execution:

func main() {
    // Timer fires once after duration
    timer := time.NewTimer(2 * time.Second)
    <-timer.C
    fmt.Println("Timer fired")
    
    // Ticker fires repeatedly
    ticker := time.NewTicker(500 * time.Millisecond)
    done := make(chan bool)
    
    go func() {
        for {
            select {
            case <-done:
                return
            case t := <-ticker.C:
                fmt.Println("Tick at", t)
            }
        }
    }()
    
    time.Sleep(1600 * time.Millisecond)
    ticker.Stop()
    done <- true
}

5.3 Atomic Operations

sync/atomic provides low-level atomic memory operations:

type AtomicCounter struct {
    count int64
}

func (c *AtomicCounter) Inc() {
    atomic.AddInt64(&c.count, 1)
}

func (c *AtomicCounter) Value() int64 {
    return atomic.LoadInt64(&c.count)
}

6. Common Pitfalls

6.1 Goroutine Leaks

Goroutines can leak if they're blocked indefinitely:

// Leaking goroutine example
func leak() {
    ch := make(chan int)
    go func() {
        val := <-ch // Blocked forever
        fmt.Println(val)
    }()
    return // Channel never gets sent to
}

// Fixed version
func noLeak() {
    ch := make(chan int)
    done := make(chan bool)
    
    go func() {
        val := <-ch
        fmt.Println(val)
        done <- true
    }()
    
    ch <- 42 // Send value
    <-done   // Wait for completion
}

6.2 Race Conditions

Data races occur when goroutines access shared data without synchronization:

// Race condition example
var counter int

func increment() {
    counter++
}

func main() {
    for i := 0; i < 1000; i++ {
        go increment()
    }
    time.Sleep(1 * time.Second)
    fmt.Println(counter) // May not be 1000
}

// Fixed with mutex
var (
    counter int
    mu      sync.Mutex
)

func safeIncrement() {
    mu.Lock()
    defer mu.Unlock()
    counter++
}

6.3 Deadlocks

Deadlocks occur when goroutines wait for each other indefinitely:

// Deadlock example
func main() {
    ch := make(chan int)
    ch <- 42      // Send blocks until someone receives
    val := <-ch   // But we never get here
    fmt.Println(val)
}

// Fixed by using buffered channel or separate goroutines
func noDeadlock() {
    ch := make(chan int, 1) // Buffered channel
    ch <- 42
    val := <-ch
    fmt.Println(val)
}

7. Best Practices

7.1 Principles of Go Concurrency

Key principles for effective concurrent programming in Go:

  • Don't communicate by sharing memory; share memory by communicating
  • Keep goroutines focused on a single task
  • Use channels to coordinate goroutines
  • Prefer small, independent goroutines

7.2 When to Use What

Choosing the right concurrency tool:

Scenario Solution
Independent tasks Goroutines
Communication between goroutines Channels
Shared state access Mutexes
Wait for completion WaitGroup
Deadlines/cancellations Context

7.3 Debugging Concurrent Programs

Tools and techniques for debugging:

  • Use go run -race to detect race conditions
  • Add logging with timestamps
  • Use pprof for performance analysis
  • Keep goroutines simple and testable
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