A repository containing implementations of common data structures and algorithms in various programming languages. Each data structure and algorithm has its own folder with the implementation and explanations.
This repository aims to provide a comprehensive collection of data structures and algorithms implemented in various programming languages. It is intended for educational purposes and to serve as a reference for anyone learning or revising these fundamental concepts.
The repository is structured as follows:
Data-Structures-and-Algorithms/
├── Arrays/
│ ├── array_example.py
│ └── README.md
├── LinkedLists/
│ ├── linked_list_example.py
│ └── README.md
├── Trees/
│ ├── binary_tree_example.py
│ └── README.md
├── Sorting/
│ ├── quicksort.py
│ ├── mergesort.py
│ └── README.md
├── Graphs/
│ ├── graph_example.py
│ └── README.md
└── README.md
Each folder contains implementations and explanations related to a specific data structure or algorithm.
- Arrays: Basic operations on arrays, including traversal, insertion, and deletion.
- LinkedLists: Implementations of singly linked lists, doubly linked lists, and circular linked lists.
- Trees: Binary trees, binary search trees, AVL trees, and more.
- Graphs: Representations and traversals (DFS, BFS) of graphs.
- Sorting: Implementations of sorting algorithms like quicksort, mergesort, bubblesort, etc.
- Search: Binary search, linear search, and other search algorithms.
- Navigate to the folder of the desired data structure or algorithm.
- Open the
README.mdfile for an explanation of the concept. - Review the implementation file (e.g.,
array_example.py) for the code. - Run the code using your preferred Python interpreter or IDE.
If you would like to contribute to this repository, please fork the repository, create a new branch, make your changes, and submit a pull request. Contributions are welcome and appreciated! Make sure to follow the coding style and include comments and documentation where necessary.