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longest-substring-without-repeating-characters_3.py
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longest-substring-without-repeating-characters_3.py
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# Companies
# Given a string s, find the length of the longest
# substring
# without repeating characters.
# Example 1:
# Input: s = "abcabcbb"
# Output: 3
# Explanation: The answer is "abc", with the length of 3.
# Example 2:
# Input: s = "bbbbb"
# Output: 1
# Explanation: The answer is "b", with the length of 1.
# Example 3:
# Input: s = "pwwkew"
# Output: 3
# Explanation: The answer is "wke", with the length of 3.
# Notice that the answer must be a substring, "pwke" is a subsequence and not a substring.
# ---------------------------------------Runtime 188 ms Beats 19.80% Memory 16.3 MB Beats 89.24%---------------------------------------
# My solution
# Time Complexity O(n^2)
class Solution:
def lengthOfLongestSubstring(self, s: str) -> int:
left = right = 0
ans: int = 0
for right in range(1, len(s)):
curr_window: str = s[left:right]
ans = max(ans, len(set(curr_window)))
while (
s[right] in curr_window
and (left <= len(s) - 1)
and (len(curr_window) != 1)
):
left += 1
curr_window = s[left:right]
ans = max(ans, len(set(s[left : right + 1])))
return ans
# Solution @zhanweiting
# Time complexity :O(n).
# Space complexity: O(m)
class Solution:
def lengthOfLongestSubstring(self, s: str) -> int:
seen = {}
l = 0
output = 0
for r in range(len(s)):
"""
If s[r] not in seen, we can keep increasing the window size by moving right pointer
"""
if s[r] not in seen:
output = max(output, r - l + 1)
"""
There are two cases if s[r] in seen:
case1: s[r] is inside the current window, we need to change the window by moving left pointer to seen[s[r]] + 1.
case2: s[r] is not inside the current window, we can keep increase the window
"""
else:
if seen[s[r]] < l:
output = max(output, r - l + 1)
else:
l = seen[s[r]] + 1
seen[s[r]] = r
return output