This repository documents my learning journey of data structures and algorithms using Python. It contains implementations, explanations, and examples of various data structures and algorithms that I have learned and practiced.
In this repository, I share my progress and understanding of data structures and algorithms through Python. I have explored various concepts, implemented algorithms, and provided detailed explanations along with examples. The goal of this project is to deepen my understanding of these fundamental concepts and provide a useful resource for others who are also interested in learning about data structures and algorithms.
This section contains implementations of various data structures. Each data structure is explained in detail, along with its time and space complexities. The following data structures are covered:
- Linked List
- Stack
- Queue
- Binary Tree
- Binary Search Tree
- Heap
- Hash Table
- and more...
This section covers a wide range of algorithms that are commonly used in computer science and programming. Each algorithm is implemented in Python, explained thoroughly, and accompanied by relevant examples. The following algorithms are included:
- Sorting algorithms (Bubble Sort, Insertion Sort, Merge Sort, Quick Sort, etc.)
- Searching algorithms (Linear Search, Binary Search, etc.)
- Graph algorithms (Breadth-First Search, Depth-First Search, Dijkstra's Algorithm, etc.)
- Dynamic Programming algorithms
- and more...
To use the code in this repository, follow these steps:
- Clone the repository:
git clone https://github.com/EmaLinuxawy/ds-algo-journey.git - Navigate to the project directory:
cd ds-algo-journey
Each data structure and algorithm implementation is contained in its own file. You can explore the repository and navigate to the specific file you are interested in. Each file includes detailed explanations and examples to help you understand and use the code effectively.
Feel free to modify and experiment with the code to deepen your understanding of the concepts. Contributions and improvements to the existing implementations are also welcome.