什么是指针
一个指针变量指向了一个值的内存地址。(也就是我们声明了一个指针之后,可以像变量赋值一样,把一个值的内存地址放入到指针当中。)
类似于变量和常量,在使用指针前你需要声明指针。指针声明格式如下:
var-type 为指针类型,var_name 为指针变量名,* 号用于指定变量是作为一个指针。以下是有效的指针声明:
var ip *int /* 指向整型*/
var fp *float32 /* 指向浮点型 */
本例中这是一个指向 int 和 float32 的指针。
package main
import "fmt"
func main() {
var a int= 20 /* 声明实际变量 */
var ip *int /* 声明指针变量 */
ip = &a /* 指针变量的存储地址 */
fmt.Printf("a 变量的地址是: %x\n", &a )
/* 指针变量的存储地址 */
fmt.Printf("ip 变量储存的指针地址: %x\n", ip )
/* 使用指针访问值 */
fmt.Printf("*ip 变量的值: %d\n", *ip )
}
指向数组的指针:
定义方式:
var ptr [MAX]*int;
这样的话,就等于新建了数组那么多的指针,然后等待放入相关的内存地址。
//例子:
package main
import "fmt"
const MAX int = 3
func main() {
a := []int{10,100,200}
var i int
var ptr [MAX]*int;
fmt.Println(ptr) //这个打印出来是[<nil> <nil> <nil>]
for i = 0; i < MAX; i++ {
ptr[i] = &a[i] /* 整数地址赋值给指针数组 */
}
for i = 0; i < MAX; i++ {
fmt.Printf("a[%d] = %d\n", i,*ptr[i] ) //*ptr[i]就是打印出相关指针的值了。
}
}
上面的例子当中,都是用指针直接指向一个值的内存地址。下面再来看看指向指针的指针。
指向指针的指针
如果一个指针变量存放的又是另一个指针变量的地址,则称这个指针变量为指向指针的指针变量。
当定义一个指向指针的指针变量时,第一个指针存放第二个指针的地址,第二个指针存放变量的地址:
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" alt="" width="622" />
定义方式:
package main
import "fmt"
func main() {
var a int
var ptr *int
var pptr **int
a = 3000
/* 指针 ptr 地址 */
ptr = &a
/* 指向指针 ptr 地址 */
pptr = &ptr
/* 获取 pptr 的值 */
fmt.Printf("变量 a = %d\n", a)
fmt.Printf("指针变量 *ptr = %d\n", *ptr)
fmt.Printf("指向指针的指针变量 **pptr = %d\n", **pptr)
fmt.Println("==================================")
fmt.Printf("变量的内存地址 a = %d\n", ptr) //ptr这个值是指向a的内存地址的。
fmt.Printf("第一个指针变量的内存地址 *ptr = %d\n", pptr) //pptr这个值,是指向指针ptr在内存中的地址的。
}
//打印结果
变量 a = 3000
指针变量 *ptr = 3000
指向指针的指针变量 **pptr = 3000
==================================
变量的内存地址 a = 824633761976
第一个指针变量的内存地址 *ptr = 824633745448
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