comments | difficulty | edit_url | tags | ||
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true |
Easy |
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Given a sorted array of distinct integers and a target value, return the index if the target is found. If not, return the index where it would be if it were inserted in order.
You must write an algorithm with O(log n)
runtime complexity.
Example 1:
Input: nums = [1,3,5,6], target = 5 Output: 2
Example 2:
Input: nums = [1,3,5,6], target = 2 Output: 1
Example 3:
Input: nums = [1,3,5,6], target = 7 Output: 4
Constraints:
1 <= nums.length <= 104
-104 <= nums[i] <= 104
nums
contains distinct values sorted in ascending order.-104 <= target <= 104
Since the array
The time complexity is
class Solution:
def searchInsert(self, nums: List[int], target: int) -> int:
left, right = 0, len(nums)
while left < right:
mid = (left + right) >> 1
if nums[mid] >= target:
right = mid
else:
left = mid + 1
return left
class Solution {
public int searchInsert(int[] nums, int target) {
int left = 0, right = nums.length;
while (left < right) {
int mid = (left + right) >>> 1;
if (nums[mid] >= target) {
right = mid;
} else {
left = mid + 1;
}
}
return left;
}
}
class Solution {
public:
int searchInsert(vector<int>& nums, int target) {
int left = 0, right = nums.size();
while (left < right) {
int mid = left + right >> 1;
if (nums[mid] >= target)
right = mid;
else
left = mid + 1;
}
return left;
}
};
func searchInsert(nums []int, target int) int {
left, right := 0, len(nums)
for left < right {
mid := (left + right) >> 1
if nums[mid] >= target {
right = mid
} else {
left = mid + 1
}
}
return left
}
use std::cmp::Ordering;
impl Solution {
pub fn search_insert(nums: Vec<i32>, target: i32) -> i32 {
let mut left = 0;
let mut right = nums.len();
while left < right {
let mid = left + (right - left) / 2;
match nums[mid].cmp(&target) {
Ordering::Less => {
left = mid + 1;
}
Ordering::Greater => {
right = mid;
}
Ordering::Equal => {
return mid as i32;
}
}
}
left as i32
}
}
/**
* @param {number[]} nums
* @param {number} target
* @return {number}
*/
var searchInsert = function (nums, target) {
let left = 0;
let right = nums.length;
while (left < right) {
const mid = (left + right) >> 1;
if (nums[mid] >= target) {
right = mid;
} else {
left = mid + 1;
}
}
return left;
};
We can also directly use the built-in function for binary search.
The time complexity is
class Solution:
def searchInsert(self, nums: List[int], target: int) -> int:
return bisect_left(nums, target)
class Solution {
public int searchInsert(int[] nums, int target) {
int i = Arrays.binarySearch(nums, target);
return i < 0 ? -i - 1 : i;
}
}
class Solution {
public:
int searchInsert(vector<int>& nums, int target) {
return lower_bound(nums.begin(), nums.end(), target) - nums.begin();
}
};
func searchInsert(nums []int, target int) int {
return sort.SearchInts(nums, target)
}
class Solution {
/**
* @param integer[] $nums
* @param integer $target
* @return integer
*/
function searchInsert($nums, $target) {
$key = array_search($target, $nums);
if ($key !== false) {
return $key;
}
$nums[] = $target;
sort($nums);
return array_search($target, $nums);
}
}