https://github.com/arslan3x5/leetcode
🔥LeetCode solutions | A Record of My Problem Solving Journey.
https://github.com/arslan3x5/leetcode
Last synced: 22 days ago
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🔥LeetCode solutions | A Record of My Problem Solving Journey.
- Host: GitHub
- URL: https://github.com/arslan3x5/leetcode
- Owner: Arslan3x5
- Created: 2024-08-23T03:51:11.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2024-08-29T09:03:06.000Z (9 months ago)
- Last Synced: 2025-03-23T15:42:06.240Z (3 months ago)
- Language: Python
- Size: 169 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🔥 LeetCode Solutions 🔥
Welcome to my **LeetCode Solutions** repository! 🚀 This repo is a comprehensive record of my journey solving LeetCode problems using Python. Here, you'll find well-documented solutions, along with my thought process and the strategies I've employed to crack these challenges.
## đź“š Table of Contents
- [About the Project](#about-the-project)
- [Problem Solving Approach](#problem-solving-approach)
- [How to Use](#how-to-use)
- [Topics Covered](#topics-covered)
- [Contributing](#contributing)
- [License](#license)
- [Connect with Me](#connect-with-me)
## đź“ť About the Project
This repository serves as a **record of my problem-solving journey** on LeetCode. I’ve tackled problems ranging from easy to hard, all using Python. Each solution is thoroughly explained, and I’ve added comments in the code to make the approach easier to understand.
### Why Python?
Python is one of the most popular languages for coding interviews and algorithmic challenges due to its simplicity, readability, and extensive library support. In this repository, I leverage Python's power to solve problems efficiently.
## đź› Problem Solving Approach
For each problem, I follow a structured approach:
1. **Understanding the Problem:** Carefully read the problem statement, constraints, and examples.
2. **Breaking Down the Solution:** Break down the problem into smaller, manageable steps.
3. **Choosing the Right Data Structures:** Select the most appropriate data structures (e.g., lists, dictionaries, sets) to optimize performance.
4. **Writing the Code:** Implement the solution in Python, ensuring clarity and efficiency.
5. **Testing the Solution:** Run the solution against various test cases to ensure accuracy and performance.
### Example:
```python
# Problem: Two Sum
# Given an array of integers nums and an integer target, return indices of the two numbers such that they add up to target.
def two_sum(nums, target):
hashmap = {}
for i, num in enumerate(nums):
diff = target - num
if diff in hashmap:
return [hashmap[diff], i]
hashmap[num] = i