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feat: refactored docs structure
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+52
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---
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title: '1004. Max Consecutive Ones III'
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description: Given a binary array nums and an integer k, return the maximum number of consecutive 1's in the array if you can flip at most k 0's
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icon: dot
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topics:
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- { name: "Array", slug: "array" }
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- { name: "Binary Search", slug: "binary-search" }
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- { name: "Sliding Window", slug: "sliding-window" }
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- { name: "Prefix Sum", slug: "prefix-sum" }
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issue: "https://github.com/prdlk/leetcode/issues/56"
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sidebar:
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label: 'Max Consecutive Ones III'
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badge: 'Medium'
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---
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### Example 1:
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- Input: `nums = [1,1,1,0,0,0,1,1,1,1,0], k = 2`
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- Output: `6`
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- Explanation: `[1,1,1,0,0,1,1,1,1,1,1]` Bolded numbers were flipped from `0` to `1`. The longest subarray is underlined.
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### Example 2:
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- Input: `nums = [0,0,1,1,0,0,1,1,1,0,1,1,0,0,0,1,1,1,1], k = 3`
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- Output: `10`
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- Explanation: `[0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1]` Bolded numbers were flipped from `0` to `1`. The longest subarray is underlined.
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### Constraints:
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- `1 <= nums.length <= 10^5`
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- `nums[i]` is either 0 or 1.
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- `0 <= k <= nums.length`
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## Solution
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```py
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class Solution:
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def longestOnes(self, nums: list[int], k: int) -> int:
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left = 0
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cur = 0
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ans = 0
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for right in range(len(nums)):
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if nums[right] == 0:
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cur += 1
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while cur > k:
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if nums[left] == 0:
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cur -= 1
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left += 1
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ans = max(ans, right - left + 1)
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return ans
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```
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+60
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---
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title: '121. Best Time to Buy and Sell Stock'
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description: You are given an array prices where prices[i] is the price of a given stock on the i^th day
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icon: dot
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topics:
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- { name: "Array", slug: "array" }
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- { name: "Dynamic Programming", slug: "dynamic-programming" }
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video: "1pkOgXD63yU"
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issue: "https://github.com/prdlk/leetcode/issues/50"
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sidebar:
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label: 'Best Time to Buy and Sell Stock'
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badge: 'Easy'
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---
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### Example 1:
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- Input: `prices = [7,1,5,3,6,4]`
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- Output: `5`
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- Explanation: Buy on day `2` (price = `1`) and sell on day `5` (price = `6`), profit = `6-1 = 5`. Note that buying on day `2` and selling on day `1` is not allowed because you must buy before you sell.
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### Example 2:
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- Input: `prices = [7,6,4,3,1]`
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- Output: `0`
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- Explanation: In this case, no transactions are done and the max profit = `0`.
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### Constraints:
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- `1 <= prices.length <= 10^5`
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- `0 <= prices[i] <= 10^4`
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## Approach
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::::warning
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The diagram traces the code below literally. That code does not run: `curr` and `ans` are never initialised, so the first `curr > left` test raises `NameError`, and `left` holds a price rather than an index, so `prices[left]` indexes by value.
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::::
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```mermaid
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flowchart TD
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S(["maxProfit(prices)"]) --> I["left = min(prices)"]
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I --> F{"more right in range(len(prices))?"}
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F -- no --> E(["return ans"])
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F -- yes --> W{"curr > left?"}
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W -- yes --> P["curr -= prices[left]; left += 1"]
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P --> W
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W -- no --> M["ans = max(ans, curr)"]
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M --> F
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```
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## Solution
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```py
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class Solution:
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def maxProfit(self, prices: List[int]) -> int:
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left = min(prices)
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for right in range(len(prices)):
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while curr > left:
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curr -= prices[left]
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left += 1
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ans = max(ans, curr)
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return ans
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```
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---
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title: '209. Minimum Size Subarray Sum'
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description: Given an array of positive integers nums and a positive integer target, return the minimal length of a subarray whose sum is greater than or equal to target. If there is no such subarray, return 0 instead
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icon: dot
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topics:
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- { name: "Array", slug: "array" }
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- { name: "Binary Search", slug: "binary-search" }
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- { name: "Sliding Window", slug: "sliding-window" }
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- { name: "Prefix Sum", slug: "prefix-sum" }
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issue: "https://github.com/prdlk/leetcode/issues/54"
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sidebar:
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label: 'Minimum Size Subarray Sum'
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badge: 'Medium'
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---
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::::warning
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If you have figured out the O(n) solution, try coding another solution of which the time complexity is O(n log(n)).
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::::
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### Example 1:
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- Input: `target = 7, nums = [2,3,1,2,4,3]`
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- Output: `2`
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- Explanation: The subarray `[4,3]` has the minimal length under the problem constraint.
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### Example 2:
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- Input: `target = 4, nums = [1,4,4]`
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- Output: `1`
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### Example 3:
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- Input: `target = 11, nums = [1,1,1,1,1,1,1,1]`
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- Output: `0`
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### Constraints:
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- `1 <= target <= 10^9`
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- `1 <= nums.length <= 10^5`
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- `1 <= nums[i] <= 10^4`
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## Solution
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```py
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class Solution:
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def minSubArrayLen(self, target: int, nums: list[int]) -> int:
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window_sum = 0
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length = len(nums) + 1
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left = 0
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for right in range(len(nums)):
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window_sum += nums[right]
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while window_sum >= target:
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length = min(length, right - left + 1)
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window_sum -= nums[left]
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left += 1
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if length > len(nums):
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return 0
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return length
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```
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+67
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---
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title: '3. Longest Substring Without Repeating Characters'
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description: Given a string s, find the length of the longest substring without duplicate characters
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icon: dot
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topics:
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- { name: "Hash Table", slug: "hash-table" }
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- { name: "String", slug: "string" }
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- { name: "Sliding Window", slug: "sliding-window" }
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video: "wiGpQwVHdE0"
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issue: "https://github.com/prdlk/leetcode/issues/51"
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sidebar:
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label: 'Longest Substring Without Repeating Characters'
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badge: 'Medium'
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---
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### Example 1:
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- Input: `s = "abcabcbb"`
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- Output: `3`
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- Explanation: The answer is "abc", with the length of `3`. Note that "bca" and "cab" are also correct answers.
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### Example 2:
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- Input: `s = "bbbbb"`
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- Output: `1`
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- Explanation: The answer is "b", with the length of `1`.
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### Example 3:
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- Input: `s = "pwwkew"`
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- Output: `3`
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- 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.
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### Constraints:
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- `0 <= s.length <= 10^5`
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- `s` consists of English letters, digits, symbols and spaces.
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## Approach
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```mermaid
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flowchart TD
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S(["lengthOfLongestSubstring(s)"]) --> I["left = 0, ans = 0, window = set()"]
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I --> L{"more (right, c) in s?"}
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L -- no --> E(["return ans"])
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L -- yes --> W{"c already in window?"}
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W -- yes --> P["window.remove(s[left]); left += 1 — shrink until c is free"]
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P --> W
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W -- no --> A["window.add(c)"]
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A --> M["ans = max(ans, right - left + 1)"]
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M --> L
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```
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## Solution
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```py
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class Solution:
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def lengthOfLongestSubstring(self, s: str) -> int:
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left = 0
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ans = 0
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window = set()
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for right, c in enumerate(s):
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while c in window:
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window.remove(s[left])
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left += 1
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window.add(c)
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ans = max(ans, right - left + 1)
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return ans
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```
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---
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title: '424. Longest Repeating Character Replacement'
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description: You are given a string s and an integer k. You can choose any character of the string and change it to any other uppercase English character. You can perform this operation at most k times
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icon: dot
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topics:
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- { name: "Hash Table", slug: "hash-table" }
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- { name: "String", slug: "string" }
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- { name: "Sliding Window", slug: "sliding-window" }
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video: "gqXU1UyA8pk"
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issue: "https://github.com/prdlk/leetcode/issues/52"
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sidebar:
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label: 'Longest Repeating Character Replacement'
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badge: 'Medium'
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---
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### Example 1:
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- Input: `s = "ABAB", k = 2`
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- Output: `4`
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- Explanation: Replace the two 'A's with two 'B's or vice versa.
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### Example 2:
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- Input: `s = "AABABBA", k = 1`
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- Output: `4`
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- Explanation: Replace the one 'A' in the middle with 'B' and form "AABBBBA". The substring "BBBB" has the longest repeating letters, which is `4`. There may exists other ways to achieve this answer too.
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### Constraints:
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- `1 <= s.length <= 10^5`
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- `s` consists of only uppercase English letters.
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- `0 <= k <= s.length`
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## Approach
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```mermaid
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flowchart TD
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S(["characterReplacement(s, k)"]) --> I["count = {}, res = 0, l = 0, maxF = 0"]
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I --> L{"more (r, c) in s?"}
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L -- no --> E(["return res"])
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L -- yes --> A["count[c] += 1; maxF = max(maxF, count[c])"]
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A --> W{"(r - l + 1) - maxF > k? — too many chars to replace"}
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W -- yes --> P["count[s[l]] -= 1; l += 1 — shrink from the left"]
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P --> W
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W -- no --> M["res = max(res, r - l + 1)"]
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M --> L
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```
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## Solution
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```py
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class Solution:
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def characterReplacement(self, s: str, k: int) -> int:
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count = {}
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res = 0
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l = 0
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maxF = 0
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for r, c in enumerate(s):
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count[c] = 1 + count.get(c, 0)
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maxF = max(maxF, count[c])
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while (r - l + 1) - maxF > k:
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count[s[l]] -= 1
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l += 1
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res = max(res, r - l + 1)
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return res
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```
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---
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title: '567. Permutation in String'
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description: Given two strings s1 and s2, return true if s2 contains a permutation of s1, or false otherwise
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icon: dot
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topics:
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- { name: "Hash Table", slug: "hash-table" }
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- { name: "Two Pointers", slug: "two-pointers" }
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- { name: "String", slug: "string" }
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- { name: "Sliding Window", slug: "sliding-window" }
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video: "UbyhOgBN834"
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issue: "https://github.com/prdlk/leetcode/issues/53"
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sidebar:
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label: 'Permutation in String'
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badge: 'Medium'
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---
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### Example 1:
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- Input: `s1 = "ab", s2 = "eidbaooo"`
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- Output: `true`
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- Explanation: `s2` contains one permutation of `s1` ("ba").
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### Example 2:
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- Input: `s1 = "ab", s2 = "eidboaoo"`
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- Output: `false`
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### Constraints:
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- `1 <= s1.length, s2.length <= 10^4`
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- `s1` and `s2` consist of lowercase English letters.
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## Approach
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```mermaid
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flowchart TD
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S(["checkInclusion(s1, s2)"]) --> G{"k = len(s1) > len(s2)?"}
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G -- yes --> X(["return False"])
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G -- no --> I["need = Counter(s1), window = Counter()"]
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I --> L{"more (right, c) in s2?"}
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L -- no --> E(["return False"])
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L -- yes --> A["window[c] += 1"]
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A --> B{"right >= k? — window is now longer than k"}
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B -- yes --> C["drop s2[right - k] from window, deleting the key at 0"]
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B -- no --> Q
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C --> Q{"window == need?"}
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Q -- yes --> R(["return True"])
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Q -- no --> L
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```
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## Solution
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```py
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from collections import Counter
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class Solution:
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def checkInclusion(self, s1: str, s2: str) -> bool:
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k = len(s1)
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if k > len(s2):
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return False
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need = Counter(s1)
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window = Counter()
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for right, c in enumerate(s2):
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window[c] += 1
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if right >= k:
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left_char = s2[right - k]
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window[left_char] -= 1
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if window[left_char] == 0:
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del window[left_char]
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if window == need:
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return True
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return False
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```
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+46
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---
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title: '643. Maximum Average Subarray I'
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description: You are given an integer array nums consisting of n elements, and an integer k
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icon: dot
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topics:
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- { name: "Array", slug: "array" }
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- { name: "Sliding Window", slug: "sliding-window" }
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issue: "https://github.com/prdlk/leetcode/issues/55"
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sidebar:
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label: 'Maximum Average Subarray I'
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badge: 'Easy'
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---
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### Example 1:
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- Input: `nums = [1,12,-5,-6,50,3], k = 4`
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- Output: `12.75000`
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- Explanation: Maximum average is `(12 - 5 - 6 + 50`) / `4 = 51 / 4 = 12.75`
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### Example 2:
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- Input: `nums = [5], k = 1`
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- Output: `5.00000`
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### Constraints:
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- `n == nums.length`
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- `1 <= k <= n <= 10^5`
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- `-10^4 <= nums[i] <= 10^4`
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## Solution
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```py
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class Solution:
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def findMaxAverage(self, nums: list[int], k: int) -> float:
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window_sum = 0
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for i in range(k):
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window_sum += nums[i]
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largest = window_sum
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for right in range(k, len(nums)):
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left = right - k
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window_sum -= nums[left]
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window_sum += nums[right]
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largest = max(largest, window_sum)
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return largest / k
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```
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