Longest Substring with At Most K Distinct Characters - Python Solution

 Given a string, find the length of the longest substring T that contains at most k distinct characters.

Example 1:

Input: s = "eceba", k = 2
Output: 3
Explanation: T is "ece" which its length is 3.

Example 2:

Input: s = "aa", k = 1
Output: 2
Explanation: T is "aa" which its length is 2.

class Solution:
    def lengthOfLongestSubstringKDistinct(self, s: str, k: int) -> int:
        n = len(s)
        if n <= k:
            return n
        left,right = 0,0
        max_len = k
        hashmap = collections.defaultdict()
        while right < n:
            # inserting the last index of the distinct elements
            if len(hashmap) <= k:
                hashmap[s[right]] = right
                right+=1
            
            # when we have more than k distinct elements
            #we need to move the left pointer 
            if len(hashmap) == k+1:
                del_idx = min(hashmap.values())
                del hashmap[s[del_idx]]
                left = del_idx+1
            max_len = max(max_len,right-left)
        return max_len   

TC: O(n) SC: O(n)

Longest Substring with At Most Two Distinct Characters - Python Solution

 Given a string s , find the length of the longest substring t  that contains at most 2 distinct characters.

Example 1:

Input: "eceba"
Output: 3
Explanation: t is "ece" which its length is 3.

Example 2:

Input: "ccaabbb"
Output: 5
Explanation: t is "aabbb" which its length is 5.

class Solution:
    def lengthOfLongestSubstringTwoDistinct(self, s: str) -> int:
        k = 3
        n = len(s)
        if n < k:
            return n
        left,right = 0,0
        max_len = 2
        hashmap = collections.defaultdict()
        while right < n:
            # inserting the last index of the distinct elements
            if len(hashmap) < k:
                hashmap[s[right]] = right
                right+=1
            
            # when we have more than k-1 or 2 distinct elements
            #we need to move the left pointer 
            if len(hashmap) == k:
                del_idx = min(hashmap.values())
                del hashmap[s[del_idx]]
                left = del_idx+1
            max_len = max(max_len,right-left)
        return max_len   
                

TC: O(n) SC: O(n)

Shortest Path in a Grid with Obstacles Elimination - Python Solution

 Given a m * n grid, where each cell is either 0 (empty) or 1 (obstacle). In one step, you can move up, down, left or right from and to an empty cell.

Return the minimum number of steps to walk from the upper left corner (0, 0) to the lower right corner (m-1, n-1) given that you can eliminate at most k obstacles. If it is not possible to find such walk return -1.

 

Example 1:

Input: 
grid = 
[[0,0,0],
 [1,1,0],
 [0,0,0],
 [0,1,1],
 [0,0,0]], 
k = 1
Output: 6
Explanation: 
The shortest path without eliminating any obstacle is 10. 
The shortest path with one obstacle elimination at position (3,2) is 6. Such path is (0,0) -> (0,1) -> (0,2) -> (1,2) -> (2,2) -> (3,2) -> (4,2).

 

Example 2:

Input: 
grid = 
[[0,1,1],
 [1,1,1],
 [1,0,0]], 
k = 1
Output: -1
Explanation: 
We need to eliminate at least two obstacles to find such a walk.

class Solution:
    def shortestPath(self, grid: List[List[int]], k: int) -> int: 
        if len(grid) == 1 and len(grid[0]) == 1:
            return 0

        queue = deque([(0,0,k,0)]) // 
        visited = set([(0,0,k)])

        if k > (len(grid)-1 + len(grid[0])-1):
            return len(grid)-1 + len(grid[0])-1

        while queue:
            row, col, eliminate, steps = queue.popleft()
            for new_row, new_col in [(row-1,col), (row,col+1), (row+1, col), (row, col-1)]:
                if (new_row >= 0 and
                    new_row < len(grid) and
                    new_col >= 0 and
                    new_col < len(grid[0])):
                    if grid[new_row][new_col] == 1 and eliminate > 0 and (new_row, new_col, eliminate-1) not in visited:
                        visited.add((new_row, new_col, eliminate-1))
                        queue.append((new_row, new_col, eliminate-1, steps+1))
                    if grid[new_row][new_col] == 0 and (new_row, new_col, eliminate) not in visited:
                        if new_row == len(grid)-1 and new_col == len(grid[0])-1:
                            return steps+1
                        visited.add((new_row, new_col, eliminate))
                        queue.append((new_row, new_col, eliminate, steps+1))

        return -1
            
        

Implement Trie (Prefix Tree) - Python Solution

 Implement a trie with insert, search, and startsWith methods.

Example:

Trie trie = new Trie();

trie.insert("apple");
trie.search("apple");   // returns true
trie.search("app");     // returns false
trie.startsWith("app"); // returns true
trie.insert("app");   
trie.search("app");     // returns true

class TrieNode:
    def __init__(self):
        self.word = False
        self.children = {}
class Trie:

    def __init__(self):
        """
        Initialize your data structure here.
        """
        self.root = TrieNode()
        

    def insert(self, word: str) -> None:
        """
        Inserts a word into the trie.
        """
        node = self.root
        for w in word:
            if w not in node.children:
                node.children[w] = TrieNode()
            node = node.children[w]
        node.word = True
        

    def search(self, word: str) -> bool:
        """
        Returns if the word is in the trie.
        """
        node = self.root
        for w in word:
            if w not in node.children:
                return False
            node = node.children[w]
        return node.word

    def startsWith(self, prefix: str) -> bool:
        """
        Returns if there is any word in the trie that starts with the given prefix.
        """
        node = self.root
        for p in prefix:
            if p not in node.children:
                return False
            node = node.children[p]
        return True
        


# Your Trie object will be instantiated and called as such:
# obj = Trie()
# obj.insert(word)
# param_2 = obj.search(word)
# param_3 = obj.startsWith(prefix)

Count of Smaller Numbers After Self Python Leetcode

 You are given an integer array nums and you have to return a new counts array. The counts array has the property where counts[i] is the number of smaller elements to the right of nums[i].

 

Example 1:

Input: nums = [5,2,6,1]
Output: [2,1,1,0]
Explanation:
To the right of 5 there are 2 smaller elements (2 and 1).
To the right of 2 there is only 1 smaller element (1).
To the right of 6 there is 1 smaller element (1).
To the right of 1 there is 0 smaller element.

class Solution:
    def countSmaller(self, nums):
        def sort(enum):
            half = len(enum) // 2
            if half:
                left, right = sort(enum[:half]), sort(enum[half:])
                for i in range(len(enum)-1,-1,-1):
                    if not right or left and left[-1][1] > right[-1][1]:
                        smaller[left[-1][0]] += len(right)
                        enum[i] = left.pop()
                    else:
                        enum[i] = right.pop()
            return enum
        smaller = [0] * len(nums)
        sort(list(enumerate(nums)))
        return smaller

TN: O(NlogN) SC: O(N)

Read N Characters Given Read4 II - Call multiple times - Python Solution

 Given a file and assume that you can only read the file using a given method read4, implement a method read to read n characters. Your method read may be called multiple times.

 

Method read4:

The API read4 reads 4 consecutive characters from the file, then writes those characters into the buffer array buf.

The return value is the number of actual characters read.

Note that read4() has its own file pointer, much like FILE *fp in C.

Definition of read4:

    Parameter:  char[] buf4
    Returns:    int

Note: buf4[] is destination not source, the results from read4 will be copied to buf4[]

Below is a high level example of how read4 works:

File file("abcde"); // File is "abcde", initially file pointer (fp) points to 'a'
char[] buf = new char[4]; // Create buffer with enough space to store characters
read4(buf4); // read4 returns 4. Now buf = "abcd", fp points to 'e'
read4(buf4); // read4 returns 1. Now buf = "e", fp points to end of file
read4(buf4); // read4 returns 0. Now buf = "", fp points to end of file

 

Method read:

By using the read4 method, implement the method read that reads n characters from the file and store it in the buffer array buf. Consider that you cannot manipulate the file directly.

The return value is the number of actual characters read.

Definition of read:

    Parameters:	char[] buf, int n
    Returns:	int

Note: buf[] is destination not source, you will need to write the results to buf[]

 

Example 1:

File file("abc");
Solution sol;
// Assume buf is allocated and guaranteed to have enough space for storing all characters from the file.
sol.read(buf, 1); // After calling your read method, buf should contain "a". We read a total of 1 character from the file, so return 1.
sol.read(buf, 2); // Now buf should contain "bc". We read a total of 2 characters from the file, so return 2.
sol.read(buf, 1); // We have reached the end of file, no more characters can be read. So return 0.

Example 2:

File file("abc");
Solution sol;
sol.read(buf, 4); // After calling your read method, buf should contain "abc". We read a total of 3 characters from the file, so return 3.
sol.read(buf, 1); // We have reached the end of file, no more characters can be read. So return 0.

 

Note:

• Consider that you cannot manipulate the file directly, the file is only accesible for read4 but not for read.
• The read function may be called multiple times.
• Please remember to RESET your class variables declared in Solution, as static/class variables are persisted across multiple test cases. Please see here for more details.
• You may assume the destination buffer array, buf, is guaranteed to have enough space for storing n characters.
• It is guaranteed that in a given test case the same buffer buf is called by read.

# The read4 API is already defined for you.

# def read4(buf4: List[str]) -> int:

class Solution(object):

    def __init__(self):

        self.tmp = [None] * 4

        self.tmppoint = 0

        self.tmpcount = 0

    def read(self, buf: List[str], n: int) -> int:

        total = 0

        while total < n:

            if self.tmppoint == 0:

                self.tmpcount = read4(self.tmp)

            if self.tmpcount == 0: break

            while self.tmppoint < self.tmpcount and total < n:

                buf[total] = self.tmp[self.tmppoint]

                total+=1

                self.tmppoint+=1

            

            if self.tmppoint == self.tmpcount: self.tmppoint = 0

            if self.tmpcount < 4: break

        return total

TC:O(n)

SC:O(n) buffer space 

Longest String Chain Python Solution

 Given a list of words, each word consists of English lowercase letters.

Let's say word1 is a predecessor of word2 if and only if we can add exactly one letter anywhere in word1 to make it equal to word2.  For example, "abc" is a predecessor of "abac".

A word chain is a sequence of words [word_1, word_2, ..., word_k] with k >= 1, where word_1 is a predecessor of word_2, word_2 is a predecessor of word_3, and so on.

Return the longest possible length of a word chain with words chosen from the given list of words.

 

Example 1:

Input: ["a","b","ba","bca","bda","bdca"]
Output: 4
Explanation: one of the longest word chain is "a","ba","bda","bdca".

class Solution:
    def longestStrChain(self, words: List[str]) -> int:
        if not words:
            return 1
        words.sort(key=len)
        cache = {}
        res = 0
        for word in words:
            longest = 0
            for i in range(len(word)):
                child = word[0:i]+word[i+1:]
                longest = max(longest,cache.get(child,0)+1)
            cache[word] = longest
            res = max(res,longest)
        return res

TC:O(N log n) or O(N * max(len(word))) SC: O(N)