Home

🧠 Data Structures & Algorithms in Python

A hands-on, open-source collection of Data Structures & Algorithms implementations in Python — built for learning, practice, experimentation, and coding interviews.

Learn → Think → Implement → Optimize → Repeat

---

🚀 About This Repository

This repository contains a growing collection of Data Structures & Algorithms problems and implementations in Python.

The goal is simple:

Don't just memorize solutions. Understand the patterns behind them.

The repository is organized around both data structures and problem-solving techniques, making it useful for beginners, interview candidates, competitive programmers, and developers.

---

🎯 What You'll Find

• 🧱 Data Structures
• ⚡ Algorithms
• 🧩 Problem-Solving Patterns
• 🧠 LeetCode Problems
• 🏆 Contest Problems
• 🔄 Recursion & Backtracking
• 🌳 Trees & Binary Search Trees
• 🕸️ Graph Algorithms
• 🔗 Linked Lists
• 📚 Stacks & Queues
• ⛰️ Heaps
• 🔢 Bit Manipulation
• 🗺️ Hash Maps
• 🪟 Sliding Window
• ➕ Prefix Sum
• 🔍 Binary Search
• 🎯 Interview-focused problems

---

🗺️ Where Should I Start?

🌱 Beginner

Start with:

1. Bit Manipulation
2. Hash Maps
3. Stack & Queue
4. Linked Lists
5. Two Pointers

Then move towards:

6. Sliding Window
7. Prefix Sum
8. Recursion

---

🚀 Intermediate

After becoming comfortable with the basics:

1. Binary Trees
2. BST
3. Heaps
4. Backtracking
5. Graphs
6. Shortest Path Algorithms

---

🔥 Interview Preparation

For interview preparation, focus on patterns rather than individual problems.

Recommended order:

Arrays
   ↓
Hash Maps
   ↓
Two Pointers
   ↓
Sliding Window
   ↓
Prefix Sum
   ↓
Binary Search
   ↓
Stack / Queue
   ↓
Linked List
   ↓
Trees
   ↓
Heap
   ↓
Graphs
   ↓
Backtracking
   ↓
Dynamic Programming