AlgoVisualAlyzer

A Python-based tool to visualize and understand sorting algorithms!

This project showcases the functionality of popular sorting algorithms, including:

• Bubble Sort
• Quick Sort
• Insertion Sort
• Selection Sort
• Heap Sort

Include a demo GIF/screenshot here!

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Features

• Intuitive Visualizations: See how each sorting algorithm processes data step-by-step.
• Educational Focus: Designed to help learners grasp sorting algorithms through interactive demos.
• Modular Design: Each algorithm is implemented in a clean, modular format for easy understanding and reuse.
• Customizable Speed: Adjust the visualization speed to observe steps in detail.
• Randomized Data: Generates random arrays to visualize sorting dynamically.
• Interactive Controls: Use keyboard shortcuts to reset, start, or switch between algorithms.

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Sorting Algorithms Implemented

1. Bubble Sort

• Compares adjacent elements and swaps them if they are in the wrong order.
• Time Complexity:
  • Best Case: O(n)
  • Worst Case: O(n²)
• Space Complexity: O(1)

2. Quick Sort

• A divide-and-conquer algorithm that partitions the array and sorts the partitions recursively.
• Time Complexity:
  • Best Case: O(n log n)
  • Worst Case: O(n²) (when the pivot selection is poor)
• Space Complexity: O(log n) (due to recursion)

3. Insertion Sort

• Builds the sorted array one item at a time by inserting elements in their correct positions.
• Time Complexity:
  • Best Case: O(n)
  • Worst Case: O(n²)
• Space Complexity: O(1)

4. Selection Sort

• Selects the smallest element from the unsorted portion and swaps it with the first unsorted element.
• Time Complexity:
  • Best Case: O(n²)
  • Worst Case: O(n²)
• Space Complexity: O(1)

5. Heap Sort

• Uses a binary heap data structure to sort elements by repeatedly extracting the maximum (or minimum) element.
• Time Complexity:
  • Best Case: O(n log n)
  • Worst Case: O(n log n)
• Space Complexity: O(1) (in-place sorting)

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Installation

1. Clone the Repository:

   git clone https://github.com/pi3t4/AlgoVisualAlyzer.git
   cd AlgoVisualAlyzer
   pip install -r requirements.txt
   python Algovisual.py

   Usage Instructions Controls : R: Reset the list and generate a new random dataset. SPACE: Start the selected sorting algorithm. A: Switch to ascending order. D: Switch to descending order. I: Select Insertion Sort. B: Select Bubble Sort. S: Select Selection Sort. M: Select Merge Sort. Q: Select Quick Sort. H: Select Heap Sort. Visualization : The bars represent the values in the list. As the algorithm progresses, the bars change color to indicate which elements are being compared or swapped.