Go language functions implement concurrent programming by creating coroutines and utilizing channels. Coroutines are lightweight threads created with the go keyword. A channel is a pipe for transferring data between coroutines. The producer coroutine uses the operator to receive data. The following example demonstrates a practical case for parallel processing of data, where the worker function squares the input value and implements inter-coroutine communication through the worker channel and the result channel.
In the Go language, functions provide powerful tools for implementing concurrent programming. By creating and managing concurrent functions, we can easily write efficient, scalable applications.
The coroutine in the Go language is a lightweight thread that shares the memory space of the main program. The cost of switching between coroutines is low, making them ideal for executing parallel tasks.
To create a coroutine, you can use the go
keyword:
go func() { // 并发执行的代码 }
Each coroutine will execute in parallel and will not be affected by the main program or other coroutines.
Channel is a pipe that transfers data between coroutines. Data is declared through the chan
keyword, for example:
ch := make(chan int)
The producer coroutine can use the <-
operator to send data from the channel:
ch <- 1
Consumer coroutines can use the ->
operator to receive data from the channel:
val := <-ch
The following example shows how to use The function processes the data in parallel:
package main import ( "fmt" "sync" ) // 工作函数 func worker(in <-chan int, out chan<- int, wg *sync.WaitGroup) { defer wg.Done() for v := range in { v *= v out <- v } } func main() { // 创建工作通道和结果通道 in := make(chan int) out := make(chan int) // 创建工作池 var wg sync.WaitGroup for i := 0; i < 4; i++ { wg.Add(1) go worker(in, out, &wg) } // 向工作通道中发送数据 for i := 0; i < 1000; i++ { in <- i } // 关闭工作通道 close(in) // 从结果通道中接收数据 for v := range out { fmt.Printf("%d ", v) } // 等待所有工作完成 wg.Wait() }
In this case, the worker
function processes the data, squaring each input value. We create a worker pool containing four coroutines. The main program sends data to the working channel, while the coroutine receives data from the channel and processes tasks in parallel. Finally, the main program receives the processed data from the result channel.
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