A comprehensive collection of implementations and explanations of common data structures and algorithms in Python. This repository is designed for beginners through advanced programmers who want to understand how data structures and algorithms work and how to use them effectively in Python.
This repository showcases core concepts in computer science using Python. Each data structure and algorithm includes clean code and, where possible, explanations and example usage. The goal is to help users learn by example and to provide a reference for interviews, studies, and practical programming.
- Implementation of fundamental data structures (lists, stacks, queues, trees, graphs, etc.)
- Common algorithms (sorting, searching, recursion, graph traversals, etc.)
- Step-by-step explanations and comments in the code
- Well-organized Python files for easy understanding and use
- Clone the repository:
git clone https://github.com/guillainbisimwa/Data-Structures-Algorithms-in-Python.git
- Navigate to the folder:
cd Data-Structures-Algorithms-in-Python - Open any Python file to explore implementations.
- Array & List Algorithms
- Stack & Queue Implementations
- Linked Lists (Singly/Doubly)
- Trees (Binary, BST, AVL, Heaps)
- Graphs (Representations, DFS, BFS)
- Sorting Algorithms (Bubble, Merge, Quick, etc.)
- Searching Algorithms (Linear, Binary, etc.)
- Other Algorithms (Recursion, Dynamic Programming)
- Use these files as references for learning or interview prep.
- Run the Python files directly to test implementations.
- Explore examples and adapt the code as needed for your own projects.
Contributions, bug reports, and suggestions are welcome! Feel free to open issues or submit pull requests to improve or expand on the data structures and algorithms in this repository.
This project is licensed under the MIT License. See the LICENSE file for details.
Happy Coding & Learning!