Golang is a modern programming language that has been widely used in many fields through its concurrency capabilities and efficient memory management. In golang, sorting is one of the common operations, and the sorting algorithm is also a relatively basic data structure and algorithm.
Golang provides some built-in sorting functions, such as the common sort.Ints in the sort package, which can sort integer slices. Additionally, we can also use sort.Strings to sort string slices. But in some scenarios, we need to write our own sorting function to meet specific sorting requirements. In this case, we need to understand the sorting algorithm and the sorting method provided by golang.
The sorting functions provided in golang are very convenient. For example, sort.Ints and sort.Strings provided by the sort package are very common. The following is an example of using sort.Ints for sorting:
package main import ( "fmt" "sort" ) func main() { nums := []int{3, 2, 1, 4, 5, 7, 6} sort.Ints(nums) fmt.Println(nums) }
The output result is: [1 2 3 4 5 6 7]
We can also use sort.Strings to sort strings :
package main import ( "fmt" "sort" ) func main() { strs := []string{"a", "c", "b", "d", "f", "e"} sort.Strings(strs) fmt.Println(strs) }
The output result is: [a b c d e f]
Bubble sort is a basic sorting algorithm and a comparison Easy to understand and implement. The basic principle is to compare adjacent elements, and swap positions if the order is wrong. After one round of sorting, the maximum or minimum value will reach the end of the sequence, and this process is repeated until all elements are in order. The following is the bubble sort algorithm implemented using go:
package main import "fmt" func bubbleSort(nums []int) { for i := len(nums)-1; i > 0; i-- { for j := 0; j < i; j++ { if nums[j] > nums[j+1] { nums[j], nums[j+1] = nums[j+1], nums[j] } } } } func main() { nums := []int{3,2,1,4,5,7,6} bubbleSort(nums) fmt.Println(nums) }
The output result is: [1 2 3 4 5 6 7]
Quick sort is another common sorting algorithm. The basic principle is to divide the sequence to be sorted into two parts through one sorting. One part is smaller than the reference element, the other part is larger than the reference element, and then the two parts are quickly processed separately. Sort and finally get an ordered sequence. In the Go language, quick sorting is also relatively easy to implement. The code is as follows:
package main import "fmt" func quickSort(nums []int) []int { if len(nums) <= 1 { return nums } pivot := nums[0] var left, right []int for _, num := range nums[1:] { if num < pivot { left = append(left, num) } else { right = append(right, num) } } left = quickSort(left) right = quickSort(right) return append(append(left, pivot), right...) } func main() { nums := []int{3, 2, 1, 4, 5, 7, 6} nums = quickSort(nums) fmt.Println(nums) }
The output result is: [1 2 3 4 5 6 7]
Merge sort is another relatively fast sorting algorithm. The basic principle is to divide the sequence to be sorted into two sequences, sort them separately and then merge them. Compared with the quick sort algorithm, merge sort does not require element exchange, so it can achieve "stable" sorting results. In golang, we can use recursion to implement the merge sort algorithm. The code is as follows:
package main import "fmt" func mergeSort(nums []int) []int { if len(nums) <= 1 { return nums } mid := len(nums) / 2 left, right := nums[:mid], nums[mid:] left = mergeSort(left) right = mergeSort(right) return merge(left, right) } func merge(left, right []int) []int { merged := make([]int, 0, len(left)+len(right)) for len(left) > 0 && len(right) > 0 { if left[0] <= right[0] { merged = append(merged, left[0]) left = left[1:] } else { merged = append(merged, right[0]) right = right[1:] } } merged = append(merged, left...) merged = append(merged, right...) return merged } func main() { nums := []int{3, 2, 1, 4, 5, 7, 6} nums = mergeSort(nums) fmt.Println(nums) }
The output result is: [1 2 3 4 5 6 7]
Summary:
In golang, we can use the built-in sort function to perform basic sorting operations. For some more complex sorting requirements, we can choose the corresponding sorting algorithm to implement according to the specific situation. Common sorting algorithms include bubble sort, quick sort and merge sort. When implementing, attention should be paid to the complexity and stability of the algorithm.
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