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Leetcode with dani

Leetcode with dani

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Join us and let's tackle leet code questions together: improve your problem-solving skills Preparing for coding interviews learning new algorithms and data structures connect with other coding enthusiasts

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it looks like this
it looks like this

How to Set Up and Use Competitive Programming Tools for Codeforces Many of you have asked how to use Codeforces efficiently for running and submitting code. It can be difficult to debug submissions when errors occur on random test cases without showing the input and output. Below is the method I use to make the process easier. ### Step-by-Step Guide 1. Install Required Extensions - Open Google Chrome and install the Competitive Companion extension. - Install CPH Submit from the Chrome Web Store. 2. Set Up VS Code - Open VS Code and install the Competitive Programming Helper extension. 3. Organizing Your Workspace - Open VS Code and create a new folder, e.g., Competitive Programming. - You only need to create this folder once; after that, you can use it for all your problems without needing to create new folders repeatedly. 4. Using Competitive Companion - Go to a Codeforces problem. - Click the Competitive Companion extension in your browser. - This will automatically send the problem statement and test cases to your VS Code environment. 5. Running and Submitting Code - Write your solution in VS Code. - Use the Competitive Programming Helper to run test cases locally. - Submit the solution using the CPH Submit extension. This setup makes running and debugging Codeforces problems much easier, especially when dealing with hidden test cases. I hope this helps!

t = int(input())
while t>0:
    t-=1
    lenght = int(input())
    arr1 = list(map(int,input().split()))
    arr2 = list(map(int,input().split()))
    hash1 = set()
    hash2 = set()
    for i in range(len(arr1)):
        hash1.add(arr1[i])
        hash2.add(arr2[i])
    if (len(hash2)<=1 and len(hash1) <=2 )or (len(hash1)<=1 and len(hash2) <=2 ):
        print("NO")
    else:
        print("YES")

▎Problem A: Milya and Two Arrays Contest: Codeforces Round #2059 Time Limit: 1 second per test Memory Limit: 256 megabytes ▎Problem Description An array is called good if every element x that appears in the array appears at least twice. For example, the arrays: • [1, 2, 1, 1, 2] • [3, 3] • [1, 2, 4, 1, 2, 4] are good, while the arrays: • [1] • [1, 2, 1] • [2, 3, 4, 4] are not good. Milya has two good arrays a and b of length n . She can rearrange the elements in array a in any way she wants. After that, she obtains an array c of length n , where:
cᵢ = aᵢ + bᵢ   (1 ≤ i ≤ n)
Your task is to determine whether Milya can rearrange the elements in array a such that there are at least 3 distinct elements in array c . ▎Input Format • The first line contains an integer t ( 1 ≤ t ≤ 1000 ) — the number of test cases. • For each test case: • The first line contains an integer n ( 3 ≤ n ≤ 50 ) — the length of arrays a and b . • The second line contains n integers a₁, a₂, ..., aₙ ( 1 ≤ aᵢ ≤ 10⁹ ) — the elements of array a . • The third line contains n integers b₁, b₂, ..., bₙ ( 1 ≤ bᵢ ≤ 10⁹ ) — the elements of array b . ▎Output Format For each test case, output "YES" if it is possible to obtain at least 3 distinct elements in array c by rearranging array a ; otherwise, output "NO". You can output each letter in any case (for example, "YES", "Yes", "yes", etc.). ▎Example Input
5
4
1 2 1 2
1 2 1 2
6
1 2 3 3 2 1
1 1 1 1 1 1
3
1 1 1
1 1 1
6
1 52 52 3 1 3
59 4 3 59 3 4
4
100 1 100 1
2 2 2 2
Example Output
YES
YES
NO
YES
NO

i dont know how it ranked div-2 it is pretty easy question https://codeforces.com/contest/2059/problem/A

Solution 4: Digit-by-Digit Using a Dictionary This method converts the number to a string and processes each digit individually. It uses a dictionary to map base values and computes the appropriate power of ten for each digit. The solution handles subtractive cases (i.e., when a digit is 4 or 9) separately.
class Solution:
    def intToRoman(self, num: int) -> str:
        roman = {1: "I", 5: "V", 10: "X", 50: "L", 100: "C", 500: "D", 1000: "M"}
        s = ""
        st = str(num)
        length = len(st)
        
        for ch in st:
            i = int(ch)
            # Calculate the current power of ten (e.g., 1000, 100, 10, 1)
            place = 10 ** (length - 1)
            if i == 4 or i == 9:
                # For subtractive cases, e.g., 4 -> "IV" and 9 -> "IX"
                s += roman[place] + roman[place * (i + 1)]
            else:
                if i >= 5:
                    s += roman[place * 5]
                    s += roman[place] * (i - 5)
                else:
                    s += roman[place] * i
            length -= 1
        return s

# Example usage:
if __name__ == '__main__':
    sol = Solution()
    print(sol.intToRoman(3749))  # Output: "MMMDCCXLIX"

Approach 1: Greedy Algorithm
class Solution:
    def intToRoman(self, num: int) -> str:
        # Define the mapping of integers to Roman numerals
        val = [
            1000, 900, 500, 400,
            100, 90, 50, 40,
            10, 9, 5, 4,
            1
        ]
        syms = [
            "M", "CM", "D", "CD",
            "C", "XC", "L", "XL",
            "X", "IX", "V", "IV",
            "I"
        ]
        
        roman_num = ''
        i = 0
        while num > 0:
            for _ in range(num // val[i]):
                roman_num += syms[i]
                num -= val[i]
            i += 1
        return roman_num

# Example usage:
sol = Solution()
print(sol.intToRoman(1994))  # Output: "MCMXCIV"
Approach 2: Using a Dictionary
class Solution:
    def intToRoman(self, num: int) -> str:
        # Mapping of integer values to Roman numerals
        roman_map = {
            1000: 'M',
            900: 'CM',
            500: 'D',
            400: 'CD',
            100: 'C',
            90: 'XC',
            50: 'L',
            40: 'XL',
            10: 'X',
            9: 'IX',
            5: 'V',
            4: 'IV',
            1: 'I'
        }
        
        roman_numeral = ''
        
        for value in roman_map.keys():
            while num >= value:
                roman_numeral += roman_map[value]
                num -= value
        
        return roman_numeral

# Example usage:
sol = Solution()
print(sol.intToRoman(58))  # Output: "LVIII"
Approach 3: Recursive Method
class Solution:
    def intToRoman(self, num: int) -> str:
        # Define the mapping of integers to Roman numerals
        roman_map = [
            (1000, 'M'),
            (900, 'CM'),
            (500, 'D'),
            (400, 'CD'),
            (100, 'C'),
            (90, 'XC'),
            (50, 'L'),
            (40, 'XL'),
            (10, 'X'),
            (9, 'IX'),
            (5, 'V'),
            (4, 'IV'),
            (1, 'I')
        ]
        
        def convert(n):
            if n == 0:
                return ""
            for value, symbol in roman_map:
                if n >= value:
                    return symbol + convert(n - value)
        
        return convert(num)

# Example usage:
sol = Solution()
print(sol.intToRoman(3))  # Output: "III"
Summary of Approaches 1. Greedy Algorithm: This approach involves repeatedly subtracting the largest possible Roman numeral value from the integer until the number is reduced to zero. 2. Using a Dictionary: Similar to the greedy approach but utilizes a dictionary to map values to their Roman numeral representations for clarity. 3. Recursive Method: This approach uses recursion to build the Roman numeral string by checking against the mapping and reducing the number accordingly.

Problem Statement Write a function int_to_roman(num: int) -> str that converts an integer (1 to 3999) to its Roman numeral representation. The Roman numeral system uses the following symbols: • I = 1 • V = 5 • X = 10 • L = 50 • C = 100 • D = 500 • M = 1000 ▎Example Test Cases 1. Input: int_to_roman(1994) Output: "MCMXCIV" Explanation: 1994 = 1000 (M) + 900 (CM) + 90 (XC) + 4 (IV). 2. Input: int_to_roman(58) Output: "LVIII" Explanation: 58 = 50 (L) + 5 (V) + 3 (III). 3. Input: int_to_roman(4) Output: "IV" Explanation: 4 is represented as IV. 4. Input: int_to_roman(9) Output: "IX" Explanation: 9 is represented as IX. 5. Input: int_to_roman(3999) Output: "MMMCMXCIX" Explanation: 3999 = 3000 (MMM) + 900 (CM) + 90 (XC) + 9 (IX). ▎Constraints • Input integer num will be in the range [1, 3999].

give me array of this 2 4 6 8 10

Codeforces (Div. 3) ▎A. Candies Time limit per test: 1 second Memory limit per test: 256 megabytes ▎Problem Statement Recently, Vova found n candy wrappers. He remembers that he bought x candies during the first day, 2x candies during the second day, 4x candies during the third day, and so on. On the k -th day, he bought 2⁽ᵏ⁻¹⁾ ⋅ x candies. However, Vova doesn't remember x or k , but he is sure that: • x and k are positive integers • k > 1 Vova will be satisfied if you find any positive integer x such that there exists some integer k > 1 where:
x + 2x + 4x + … + 2ᵏ⁻¹x = n
It is guaranteed that at least one solution exists. ▎Input The first line contains one integer t (1 ≤ t ≤ 10⁴) — the number of test cases. Each of the next t lines contains one integer n (3 ≤ n ≤ 10⁹) — the number of candy wrappers Vova found. ▎Output For each test case, print one integer — any valid x such that there exists an integer k > 1 satisfying the given equation. ▎ExamplesInput
7
3
6
7
21
28
999999999
999999984
Output
1
2
1
7
4
333333333
333333328
Explanation • For n = 3 , one possible solution is x = 1, k = 2 since 1 ⋅ 1 + 2 ⋅ 1 = 3 . • For n = 6 , one possible solution is x = 2, k = 2 since 1 ⋅ 2 + 2 ⋅ 2 = 6 . • For n = 7 , one possible solution is x = 1, k = 3 since 1 ⋅ 1 + 2 ⋅ 1 + 4 ⋅ 1 = 7 . --- ▎Solution Code
t = int(input())
while t > 0:
    num = int(input())
    k = 3
    n = 4
    while num % k:
        k += n
        n *= 2
    print(num // k)
🔗 Problem link: Codeforces 1343A - Candies

Repost from N/a
fullstack-node-js.pdf6.50 MB

i added new book resources check it

🌟 Day 10 Challenge: Walking Robot Simulation 🤖 🔗 Problem Link: 874. Walking Robot Simulation Hey everyone! 👋 Today, we’re solving an interesting robot movement problem where the robot moves on an infinite grid while avoiding obstacles! 🚀 --- ▎📝 Problem Statement: A robot starts at (0,0) facing north and follows a series of commands: • -2: Turn left 90° • -1: Turn right 90° • 1 ≤ k ≤ 9: Move forward k units • If the robot hits an obstacle, it stops moving in that direction but continues executing the next command. 🛑 Goal: Find the maximum squared Euclidean distance the robot reaches from the origin (0,0). 💡 Key Notes: • North → +Y • East → +X • South → -Y • West → -X --- ▎🔍 Understanding with Examples 📌 Example 1: Input: commands = [4,-1,3], obstacles = [] Output: 25 ✅ The robot moves to (3,4), and the max squared distance is 3² + 4² = 25. 📌 Example 2 (With Obstacles): Input: commands = [4,-1,4,-2,4], obstacles = [[2,4]] Output: 65 ✅ The robot gets blocked at (2,4), then continues moving north to (1,8), reaching a max squared distance of 1² + 8² = 65. --- ▎🏗 Approach to Solve the Problem 1️⃣ Track directions efficiently: • Use dx, dy arrays to manage the direction changes when turning left or right. 2️⃣ Use a set for obstacles for quick lookup (O(1) checks). 3️⃣ Loop through commands and update position accordingly: • If moving forward → Check if the next step is an obstacle. • If turning → Update direction accordingly. --- ▎💻 Code (Python)
from typing import List

class Solution:
    def robotSim(self, commands: List[int], obstacles: List[List[int]]) -> int:
        # Step 1: Define movement directions (North, East, South, West)
        directions = [(0,1), (1,0), (0,-1), (-1,0)]  
        x, y, max_dist, d = 0, 0, 0, 0  # Robot starts at (0,0), facing North
        
        # Step 2: Convert obstacles list into a set for quick lookups
        obstacle_set = set(map(tuple, obstacles))  

        # Step 3: Process each command
        for command in commands:
            if command == -2:  # Turn left
                d = (d - 1) % 4
            elif command == -1:  # Turn right
                d = (d + 1) % 4
            else:  # Move forward k steps
                for _ in range(command):
                    next_x, next_y = x + directions[d][0], y + directions[d][1]
                    
                    # Stop moving if an obstacle is hit
                    if (next_x, next_y) in obstacle_set:
                        break  
                    
                    x, y = next_x, next_y  # Update position
                    max_dist = max(max_dist, x*x + y*y)  # Update max distance
        
        return max_dist  # Return max squared Euclidean distance
--- ▎📝 Explanation of the Code: 1. Tracking Directions: • We use an array directions = [(0,1), (1,0), (0,-1), (-1,0)] to handle North, East, South, and West movements. • Turning left (-2) moves us backwards in the array, while turning right (-1) moves us forward. 2. Efficient Obstacle Lookup: • We store obstacles in a set (O(1) lookup) instead of a list to quickly check if a position is blocked. 3. Processing Commands: • For k steps forward, check if the next step is an obstacle: • ✅ If not blocked, update x, y. • ❌ If blocked, stop moving in that direction. • Keep track of the maximum squared Euclidean distance reached. --- ▎✅ Complexity Analysis:Time Complexity: O(N + M), where N = len(commands), M = len(obstacles) • Space Complexity: O(M) (for storing obstacles in a set)

photo content

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https://youtu.be/h6fcK_fRYaI?si=fdF5l_fUWXPiu_kw I really love this video! Please check it out when you have some free time and let me know what you think.

🌟 Day 10 Challenge: Find Pivot Index 🌟 🔗 Problem Link: 724. Find Pivot Index 📝 Problem Statement: Given an array of integers nums, calculate the pivot index of this array. The pivot index is the index where the sum of all the numbers strictly to the left of the index is equal to the sum of all the numbers strictly to the index's right. If the index is on the left edge of the array, then the left sum is 0 because there are no elements to the left. This also applies to the right edge of the array. Return the leftmost pivot index. If no such index exists, return -1. --- ▎🔍 Approach: Prefix Sum We can use a prefix sum technique to efficiently check for the pivot index. ▎Steps to Solve: 1. Compute prefix sums: We maintain a prefix sum array p, where p[i] stores the sum of elements from index 0 to i-1. 2. Iterate through the array: For each index i, check if the left sum (p[i] - nums[i-1]) equals the right sum (p[-1] - p[i]). 3. Return the first valid index: If we find an index where both sums match, return it. 4. Return -1 if no pivot index is found. --- ▎📝 Code Implementation:
class Solution:
    def pivotIndex(self, nums: List[int]) -> int:
        # Step 1: Compute prefix sum
        p = [0]  # Prefix sum array initialized with 0
        for i in range(len(nums)):
            p.append(p[-1] + nums[i])  # Store cumulative sum
        
        # Step 2: Iterate through the array and check pivot condition
        for i in range(1, len(p)):
            left_sum = p[i] - nums[i - 1]  # Sum of elements to the left of index i-1
            right_sum = p[-1] - p[i]       # Sum of elements to the right of index i-1
            
            if left_sum == right_sum:
                return i - 1  # Return the pivot index
        
        return -1  # If no pivot index is found
--- ▎📝 Explanation of the Code: 1. Building Prefix Sum Array: • We initialize p with [0] to store cumulative sums. • Iterate through nums, appending the cumulative sum to p. 2. Finding Pivot Index: • For each i, compute: • Left sum: p[i] - nums[i-1] (sum of elements before index i-1). • Right sum: p[-1] - p[i] (sum of elements after index i-1). • If both sums are equal, return i-1. 3. Edge Case Handling: • If no such index exists, return -1. --- ▎✅ Complexity Analysis:Time Complexity: O(N) (single pass for prefix sum + single pass for checking pivot index). • Space Complexity: O(N) (extra space for prefix sum array).

🌟 Day 11 Challenge: Find Pivot Index 🌟 🔗 Problem Link: 724. Find Pivot Index 📝 Problem Statement: Given an array of integers nums, calculate the pivot index of this array. The pivot index is the index where the sum of all the numbers strictly to the left of the index is equal to the sum of all the numbers strictly to the index's right. If the index is on the left edge of the array, then the left sum is 0 because there are no elements to the left. This also applies to the right edge of the array. Return the leftmost pivot index. If no such index exists, return -1. --- ▎🔍 Approach: Prefix Sum We can use a prefix sum technique to efficiently check for the pivot index. ▎Steps to Solve: 1. Compute prefix sums: We maintain a prefix sum array p, where p[i] stores the sum of elements from index 0 to i-1. 2. Iterate through the array: For each index i, check if the left sum (p[i] - nums[i-1]) equals the right sum (p[-1] - p[i]). 3. Return the first valid index: If we find an index where both sums match, return it. 4. Return -1 if no pivot index is found. --- ▎📝 Code Implementation:
from typing import List

class Solution:
    def pivotIndex(self, nums: List[int]) -> int:
        # Step 1: Compute prefix sum
        p = [0]  # Prefix sum array initialized with 0
        for i in range(len(nums)):
            p.append(p[-1] + nums[i])  # Store cumulative sum
        
        # Step 2: Iterate through the array and check pivot condition
        for i in range(1, len(p)):
            left_sum = p[i] - nums[i - 1]  # Sum of elements to the left of index i-1
            right_sum = p[-1] - p[i]       # Sum of elements to the right of index i-1
            
            if left_sum == right_sum:
                return i - 1  # Return the pivot index
        
        return -1  # If no pivot index is found
---

▎📝 Explanation of the Code:

1. Building Prefix Sum Array:

   • We initialize p with [0] to store cumulative sums.

   • Iterate through nums, appending the cumulative sum to p.

2. Finding Pivot Index:

   • For each i, compute:

     • Left sum: p[i] - nums[i-1] (sum of elements before index i-1).

     • Right sum: p[-1] - p[i] (sum of elements after index i-1).

   • If both sums are equal, return i-1.

3. Edge Case Handling:

   • If no such index exists, return -1.

---

▎✅ Complexity Analysis:

• Time Complexity: O(N) (single pass for prefix sum + single pass for checking pivot index).

• Space Complexity: O(N) (extra space for prefix sum array).

in Short Yaman is training with a barbell that has plates of varying weights and widths. He needs to distribute these plates between the left and right sides of the barbell. The goal is to maximize the total weight lifted while ensuring that the difference in total widths between the two sides falls within a specified range [L, R]. For each test case, determine the maximum weight Yaman can lift under these conditions. If it's not possible to achieve the desired width balance, the result should be 0.