️ Golang: Thwarting Race Conditions with Deliberate Design
Tags: go, racecondition, beginners
Published: 2023-05-29 11:02:19

---
title: ️ Golang: Thwarting Race Conditions with Deliberate Design
published: true
date: 2023-05-29 10:53:56 UTC
tags: python,golang,racecondition,beginner
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---

![](https://cdn-images-1.medium.com/max/1024/1*XFOJ0zuEFztjzOdEL57VtQ.png)

“Concurrency is not the same as parallelism.” — Rob Pike, one of the Go language’s developers. Race conditions have become increasingly evident and challenging for developers as concurrent and parallel programming paradigms have grown in popularity. They are elusive, difficult to recreate, and induce nondeterministic mistakes, which are a programmer’s worst nightmare.

🧐 Let’s dive deep into how the designers of Go, often referred to as Golang, battled race conditions from the ground up, striving to shield developers from this phantom menace.

### What is a Race Condition? 🏃‍♀️🏃‍♂️

Let’s imagine a restaurant where two waiters take orders for the same dish from two different tables. They run to the kitchen to cook the dish, but there are only enough ingredients to make one. The waiter who arrives at the kitchen first prepares and serves the dish. The second waiter is now stuck with an order he can’t complete — a classic illustration of a race condition.

A race problem happens in programming when two or more threads access common data and attempt to alter it concurrently. Because the thread scheduling algorithm governs the execution order, the outcome is uncertain because it is determined by the order in which the threads are scheduled.

### Golang’s Protective Shield Against Race Conditions 🛡️

### 1. The Elegance of Goroutines 🕺

To understand Golang’s defense against race circumstances, we must first look at Goroutines, which are Golang’s concurrent units of execution. Consider Goroutines to be restaurant waitstaff. In the real world, a busy restaurant does not recruit a new waiter for each new diner. Instead, they use their existing employees to efficiently serve many tables. Goroutines are lightweight threads that are more efficient than standard OS threads. The Go runtime can manage thousands of Goroutines at the same time.

Goroutines do not prevent race problems, but they facilitate the concurrent programming model, encouraging safer behaviors.

```
func serveDish(i int) {
    fmt.Println("Serving dish", i)
}

func main() {
    for i := 0; i < 10; i++ {
        go serveDish(i)
    }

    time.Sleep(time.Second)
}
```

In this snippet, we spawn 10 Goroutines to “serve dishes.” Here, each Goroutine is serving a dish independently — no shared mutable state, no risk of a race condition.

### 2. Channels: The Conveyor Belts of Golang 🚧

While Goroutines are similar to restaurant waitstaff, channels are similar to sushi restaurant conveyor belts. Channels provide communication between Goroutines in the same way that dishes are conveyed from the kitchen to the dining area.

Channels, by default, block sends and receives until the other side is ready. This trait allows channels to synchronize Goroutines, which is critical for avoiding race problems.

```
func serveDish(c chan int) {
    dish := <-c
    fmt.Println("Serving dish", dish)
}

func main() {
    c := make(chan int)

    for i := 0; i < 10; i++ {
        go serveDish(c)
        c <- i
    }

    time.Sleep(time.Second)
}
```

In this case, we’re using a channel to send the dish number to each Goroutine. Again, no race conditions since there’s no shared mutable state.

### 3. Mutexes: The Bouncers of Golang 🔐

In reality, we must occasionally share mutable state between Goroutines. Imagine a restaurant’s storage area with limited access; not everyone can enter at the same time. Similarly, the `sync` package in Go includes synchronization primitives such as Mutexes (Mutual Exclusion).

```
var dishesServed = 0
var lock sync.Mutex

func serveDish() {
    lock.Lock()
    defer lock.Unlock()
    dishesServed++
    fmt.Println("Dishes served: ", dishesServed)
}

func main() {
    for i := 0; i < 10; i++ {
        go serveDish()
    }

    time.Sleep(time.Second)
}
```

Here, we’re using a mutex to ensure only one Goroutine has access to dishesServed at a time, thus avoiding a potential race condition.

### 4. The Go Race Detector: The Referee 🏁

Even with these robust built-in measures, race situations might occur if developers are not cautious. Go’s designers anticipated this and included a race detector. Consider this as a diligent race official, watching each runner’s (Goroutine’s) actions and indicating any foul play (race condition).

To aid the detection of these elusive race conditions, developers can activate the race detector during tests (go test -race) or while running the program (go run -race).

Although not flawless, the race detector is a useful tool in ensuring the integrity of concurrent Go applications. It may not detect every race condition, and it may occasionally report false positives. However, the value it adds far transcends these little drawbacks.

### Final Word 🖋️

Golang has emerged as a star chef in the restaurant of concurrent programming, addressing the classic challenges connected with concurrency and parallelism, particularly race situations. It gives developers with a full set of tools to cook up efficient, concurrent, and safe applications while limiting the risks of producing undesirable race circumstances via Goroutines, channels, Mutexes, and the race detector.