Function signature design principles for Golang function performance optimization

Go function performance optimization principle: use value receivers first: avoid pointer receivers to improve concurrency performance. Avoid named return values: Use return tuples or Errors when possible to handle errors and multiple return values. Optimize slice and map passes: Use pointer references to avoid unnecessary copies. Consider concurrency safety: Use mutexes or read-write locks to protect shared data. Optimize string concatenation: use strings.Builder instead of operator. Optimize array search: Use map instead of linear array search to improve search speed.

Go language function performance optimization: function signature design principles

In the Go language, function signatures will have a significant impact on the performance of the function. A well-designed function signature can simplify calls, improve readability, and optimize performance.

Prefer using value receivers

Using composite types such as structures or slices as value receivers (passing a copy) instead of pointer receivers (passing a reference) can avoid unnecessary memory allocation and Improve concurrency performance.

Example:

// 值接收器
func UpdateUser(user User) {
    // 对 user 副本进行修改
}

// 指针接收器
func UpdateUserPtr(user *User) {
    // 对 user 原对象进行修改
}

Avoid using named return values

Although named return values ​​are convenient to use, they will increase the size of the stack frame and increase the call overhead have negative impacts. Prefer using the return tuple or Errors technique to handle errors and multiple return values.

Example:

// 避免命名返回值
func GetUserInfo(id int) (name string, age int, err error) {
    // ...
}

// 使用返回元组
func GetUserInfoTuple(id int) (string, int, error) {
    // ...
}

Optimize passing of slices and maps

Using slices and maps as value receivers or return values ​​creates copies, thus reducing performance. To avoid unnecessary copies, pointer references can be used.

Example:

// 值接收器
func SortSlice(slice []int) {
    // 对 slice 副本进行排序
}

// 指针引用
func SortSlicePtr(slice *[]int) {
    // 对 slice 原对象进行排序
}

Consider concurrency safety

If a function is called in a concurrent environment, concurrency safety must be ensured. Shared data should be protected using a mutex (Mutex) or a read-write lock (RWMutex).

Example:

import "sync"

var mutex = &sync.Mutex{}

// 并发安全的函数
func GetConcurrentData() (data string) {
    mutex.Lock()
    defer mutex.Unlock()
    // ...
    return data
}

Practical case

Optimizing string splicing

String splicing is a For common operations, performance can be optimized by using strings.Builder instead of the operator.

// 使用 + 运算符
func ConcatenateStrings(a, b string) string {
    return a + b
}

// 使用 strings.Builder
func ConcatenateStringsBuilder(a, b string) string {
    var builder strings.Builder
    builder.WriteString(a)
    builder.WriteString(b)
    return builder.String()
}

Optimize array search

Using map instead of linear array search can greatly improve the search speed, especially when the amount of data is large .

// 线性数组查找
func FindInArray(array []string, element string) int {
    for i := 0; i < len(array); i++ {
        if array[i] == element {
            return i
        }
    }
    return -1
}

// map 查找
func FindInMap(m map[string]bool, element string) bool {
    return m[element]
}

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