How are Golang functions used for concurrent programming?

The Go language implements concurrent programming through Goroutine, which allows lightweight threads to be executed simultaneously. Goroutines can be created using the go keyword and communicate through pipes (chan type). In the actual case, we search for strings in parallel and create a pipeline to receive the results of each Goroutine search, thereby improving the search speed.

Using Go functions for concurrent programming

The Go language provides a lightweight thread called Goroutine, which can for concurrent programming. Goroutines can execute concurrently, improving the performance and responsiveness of your application.

To create a Goroutine, you use the go keyword, followed by the function to be executed:

go func() {
    fmt.Println("这是一个 Goroutine！")
}

Goroutines can also receive and send values. Use the chan type to create a pipeline, which allows communication between Goroutines:

// 创建管道
ch := make(chan string)

// Goroutine 发送值
go func() {
    ch <- "消息 1"
    ch <- "消息 2"
}

// 主程序接收值
for msg := range ch {
    fmt.Println(msg)
}

Practical case: Parallel search for strings

Suppose we have a List of files from which we need to find a string. We can use Goroutine to do this in parallel, making the lookup faster:

// 文件列表
files := []string{"file1.txt", "file2.txt", "file3.txt"}

// 创建管道
result := make(chan string)

// Goroutine 并行查找字符串
for _, file := range files {
    go func(file string) {
        data, err := ioutil.ReadFile(file)
        if err != nil {
            result <- file + ": " + err.Error()
            return
        }

        result <- file + ": " + strconv.Itoa(strings.Count(string(data), "foo"))
    }(file)
}

// 主程序打印结果
for result := range result {
    fmt.Println(result)
}

Using this example, we can find the number of occurrences of the string "foo" in each file in parallel, making it faster than a single-threaded lookup. performance.

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