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A simple and interactive tool for visualizing the Linear Search algorithm. This project helps users understand how Linear Search works by visually demonstrating each step of the algorithm as it searches for a target value in an array.

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πŸŽ₯ LinearSearch-Visualizer

Welcome to the LinearSearch-Visualizer! This tool helps you visualize the Linear Search algorithm step-by-step. It's an interactive project built with Tkinter, allowing you to observe how the algorithm searches through an array for a target value. πŸ§‘β€πŸ’»


🎬 Watch the Demo

Check out the demo video below to see the Linear Search in action: Watch the Demo


βš™οΈ Features

  • 🟒 Real-time Visualization: Watch the algorithm compare elements in real-time.
  • πŸ“ Custom Input: Customize the array and target value to explore different cases.
  • ⏸️ Step-by-Step Execution: Pause the search and move through each step manually.

πŸ’» Technologies Used

  • Python 🐍 (with Tkinter for GUI)
  • Tkinter provides a simple graphical interface for interaction.

πŸš€ How to Use

  1. Clone the repository:
    git clone https://github.com/codeprnv/LinearSearch-Visualizer.git
  2. Navigate to the project directory and run the script:
    python main.py
  3. Interact with the visualizer to observe the Linear Search process!

🀝 Contributing

We welcome contributions! Follow these steps to contribute:

  1. Fork the repository by clicking on the "Fork" button at the top right of the repo page.
  2. Clone your fork to your local machine using:
    git clone https://github.com/codeprnv/LinearSearch-Visualizer.git
  3. Create a new branch for your changes:
    git checkout -b your-branch-name
  4. Make your changes, then commit:
    git commit -m "Description of your changes"
  5. Push your changes to your fork:
    git push origin your-branch-name
  6. Create a pull request to the original repository.

Feel free to suggest improvements or add new features! πŸ™Œ


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A simple and interactive tool for visualizing the Linear Search algorithm. This project helps users understand how Linear Search works by visually demonstrating each step of the algorithm as it searches for a target value in an array.

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