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HomeBackend DevelopmentGolangHow to avoid value copying in Golang function parameter passing

In Go, the way to avoid copying function parameter values ​​is to use pointers to pass parameters and add an asterisk (*) before the parameter type. For structs and slices, pass them by reference, structs using a pointer to the structure, and slices using a pointer to the slice data.

How to avoid value copying in Golang function parameter passing

How to avoid value copying in function parameter passing in Go

In Go, function parameters are passed by value by default. This can cause unnecessary copying of values ​​and performance overhead. To avoid this, you can pass parameters using pointers or references.

Passing parameters using pointers

To pass parameters using pointers, add an asterisk (*) before the parameter type:

func myFunc(p *int) {
    // 对指针 p 进行操作
}

Use pointers to pass parameters to modify variable values ​​outside the function:

var x int
myFunc(&x)
fmt.Println(x) // 输出修改后的 x

Use references to pass structures and slices

For structures and slices, you can pass Pass them by reference to avoid value copying:

  • Structure: Use a pointer to a structure (*MyStruct)
  • Slicing: Use a pointer to slice data ([]int)

For example:

type MyStruct struct {
    Value int
}

func myFunc(s *MyStruct) {
    // 对 s 进行操作
}

Actual case:

Suppose we have a function that calculates the sum of two numbers:

func sum(a, b int) int {
    return a + b
}

If we pass the parameter by value, a copy will be created every time this function is called. This is expensive for large numbers or complex data structures.

We can optimize this function by using pointers:

func sum(a, b *int) {
    *a += *b
}

Now, when we call this function, it will directly modify the parameters passed in, thus avoiding unnecessary copying.

Conclusion:

By passing parameters using pointers or references, you can avoid value copying in function parameter passing in Go, thereby improving performance. This is especially important when dealing with big data or complex data structures.

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