data-structures-algorithms-python

curated collection of data structures, algorithms, and problem-solving techniques using Python. This repository is part of my learning and preparation journey for coding interviews and competitive programming.

data-structures-algorithms-python/

│ ├── README.md
├── LICENSE
├── .gitignore
│ ├── basics/
│ ├── variables.py
│ ├── loops.py
│ └── functions.py
│ ├── data_structures/
│ ├── arrays.py
│ ├── linked_list.py
│ ├── stack.py
│ ├── queue.py
│ ├── hash_table.py
│ ├── tree.py
│ └── graph.py
│ ├── algorithms/
│ ├── searching/
│ │ ├── linear_search.py
│ │ └── binary_search.py
│ ├── sorting/
│ │ ├── bubble_sort.py
│ │ ├── selection_sort.py
│ │ ├── insertion_sort.py
│ │ ├── merge_sort.py
│ │ └── quick_sort.py
│ └── recursion/
│ ├── factorial.py
│ └── fibonacci.py
│ ├── advanced/
│ ├── dynamic_programming/
│ │ ├── knapsack.py
│ │ ├── lcs.py
│ │ └── fibonacci_memo.py
│ ├── greedy/
│ │ └── activity_selection.py
│ ├── backtracking/
│ │ ├── n_queens.py
│ │ └── sudoku_solver.py
│ └── graph_algorithms/
│ ├── bfs.py
│ ├── dfs.py
│ ├── dijkstra.py
│ └── kruskal.py
│ ├── problems/
│ ├── leetcode/
│ ├── hackerrank/
│ └── codeforces/
│ ├── notebooks/
│ └── DSA-cheatsheet.ipynb
│ └── tests/
└── test_array.py

📚 Contents

• 🔰 Basics
• 🧱 Data Structures
• ⚙️ Algorithms
• 💡 Advanced Topics (DP, Greedy, Graphs)
• 🧪 Unit Tests
• 💻 Practice Problems (LeetCode, HackerRank, etc.)

🧰 Technologies

• Python 3.x
• Jupyter Notebook
• pytest (for testing)

📈 Learning Progress

• Arrays
• Linked List
• Binary Trees
• Graph Algorithms
• Dynamic Programming

🧠 What This Repo Is About

- A structured repository for learning and implementing Data Structures and Algorithms (DSA) in Python.

- Designed to strengthen problem-solving skills for coding interviews and competitive programming.

- Includes Python implementations, practice problems, and visual notebooks.

📌 Why I Built This Repo

- To prepare for technical interviews at top tech companies.

- To apply theoretical knowledge from my MSc in Applied Data Science.

- To showcase my understanding of algorithmic thinking and clean coding.

- To maintain a consistent habit of practicing DSA using Python.

🧱 What’s Covered

- Fundamental Data Structures: Arrays, Linked Lists, Stacks, Queues, Hash Tables, Trees, Graphs

- Core Algorithms: Searching, Sorting, Recursion, Backtracking

- Advanced Topics: Dynamic Programming, Greedy Algorithms, Graph Algorithms

- Practice Problems from LeetCode, HackerRank, Codeforces, etc.

🛠️ Tools & Technologies Used

- Python 3.x

- Jupyter Notebook (for visualizations and explanations)

- pytest for testing

- Git & GitHub for version control

📘 Learning Approach

- Hands-on implementation of each concept

- Code is written with comments and examples

- Covers time and space complexity analysis

- Incrementally adding unit tests and real-world applications

🎯 Goals of This Project

- Build a strong foundation in DSA with Python

- Help others learn DSA through clear, commented code

- Serve as a personal knowledge base for quick review

- Open-source contribution to support learners preparing for interviews

🚀 How to Run

# Clone the repo
git clone https://github.com/MoksedurRahman/data-structures-algorithms-python.git

# Run an example
python data_structures/stack.py