🇷🇺 Русская версия

Sorting Algorithm Visualizer

Interactive sorting algorithm visualizer with real-time animations

Description • Features • Installation • Usage • Algorithms

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Description

An educational Python project that demonstrates how various sorting algorithms work through real-time interactive animations. The visualizer helps build intuition for algorithmic behavior by showing each comparison, swap, and merge step as it happens.

Features

• Bubble Sort — simple algorithm with clear visualization of comparisons and swaps
• Quick Sort — efficient divide-and-conquer algorithm with partition visualization
• Merge Sort — stable algorithm showing the split-and-merge process
• Interactive animation — step-by-step visualization of every algorithm operation
• Color coding — active elements are highlighted during sorting
• Configurable parameters — adjustable array size and animation speed

Installation

Prerequisites

• Python 3.7+
• pip

Setup

1. Clone the repository:

git clone https://github.com/CHUKEPC/sorting_visualizer.git
cd sorting_visualizer

2. Install dependencies:

pip install -r requirements.txt

Usage

Basic usage

Run the program and select an algorithm from the menu:

python sorting_visualizer.py

Programmatic usage

from sorting_visualizer import SortingVisualizer

# Create a visualizer with an array of 30 elements
visualizer = SortingVisualizer(size=30)

# Visualize Bubble Sort
visualizer.visualize(algorithm='bubble', speed=100)

# Visualize Quick Sort
visualizer.visualize(algorithm='quick', speed=100)

# Visualize Merge Sort
visualizer.visualize(algorithm='merge', speed=100)

Examples

Custom data

custom_data = [64, 34, 25, 12, 22, 11, 90, 5, 77, 88]
visualizer = SortingVisualizer(data=custom_data)
visualizer.visualize(algorithm='quick')

Adjusting animation speed

visualizer = SortingVisualizer(size=20)

# Fast animation (10 ms between frames)
visualizer.visualize(algorithm='bubble', speed=10)

# Slow animation (500 ms between frames)
visualizer.visualize(algorithm='bubble', speed=500)

Visualization Guide

• Red bars — elements being compared or moved in the current step
• Blue bars — remaining array elements
• Green bars — final sorted state
• Step counter — displays the current step number and total steps

Tech Stack

• Python 3.7+
• Matplotlib — chart rendering and animation
• NumPy — array operations (optional)

Project Structure

sorting_visualizer/
├── sorting_visualizer.py   # Main module with classes and algorithms
├── requirements.txt        # Project dependencies
├── README.md               # Documentation (English)
├── README_RU.md            # Documentation (Russian)
├── .gitignore              # Git ignore rules
└── LICENSE                 # MIT License

API Reference

Class SortingVisualizer

Parameter	Type	Description	Default
data	List[int]	Initial data array	None
size	int	Array size (if data is not provided)	30

Method visualize()

Parameter	Type	Description	Default
algorithm	str	Algorithm: 'bubble', 'quick', 'merge'	'bubble'
speed	int	Animation speed (ms between frames)	50

Sorting Algorithms

Bubble Sort

• Time complexity: O(n²)
• Stable: Yes
• Notes: Simple to understand but slow for large arrays

Quick Sort

• Time complexity: O(n log n) average, O(n²) worst case
• Stable: No
• Notes: One of the most efficient general-purpose sorting algorithms

Merge Sort

• Time complexity: O(n log n)
• Stable: Yes
• Notes: Guaranteed O(n log n) performance, requires additional memory

Contributing

Contributions are welcome! To contribute:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License. See the LICENSE file for details.

Author

CHUKEPC

• GitHub: @CHUKEPC
• Telegram: @ArtyomRoyal