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Given an integer array nums
, return the length of the longest strictly increasing subsequence.
Example 1:
Input: nums = [10,9,2,5,3,7,101,18] Output: 4 Explanation: The longest increasing subsequence is [2,3,7,101], therefore the length is 4.
Example 2:
Input: nums = [0,1,0,3,2,3] Output: 4
Example 3:
Input: nums = [7,7,7,7,7,7,7] Output: 1
Constraints:
1 <= nums.length <= 2500
-10 4 <= nums[i] <= 10 4
Follow up: Can you come up with an algorithm that runs in O(n log(n))
time complexity?
Python
# time complexity: O(n^2) # space complexity: O(1) from typing import List class Solution: def lengthOfLIS(self, nums: List[int]) -> int: countList = [1] * len(nums ) for i in range(1, len(nums)): for j in range(i): if nums[i] > nums[j]: countList[i] = max(countList[i], countList[j] + 1) return max(countList) nums = [0, 1, 0, 3, 2, 3] print(Solution().lengthOfLIS(nums))