File Compression Web Application

Overview

A powerful web application for file compression using advanced data structures and algorithms, demonstrating key computer science principles.

Data Structures and Algorithms Explored

1. Huffman Coding Algorithm

Key DSA Concepts

• Greedy Algorithm: Huffman coding uses a greedy approach to build an optimal prefix code
• Priority Queue (Min-Heap): Efficiently manages character frequencies during tree construction
• Binary Tree: Represents the Huffman encoding tree
• Hash Map (Dictionary): Stores character frequencies and encoding mappings

Implementation Details

• Time Complexity: O(n log k), where n is data length and k is unique characters
• Space Complexity: O(k), where k is the number of unique characters
• Uses heapq for priority queue operations
• Builds an optimal prefix code for data compression

2. Frequency-Based Compression Techniques

DSA Concepts

• Sorting Algorithms: Used to sort characters by frequency
• Set Data Structure: Efficiently remove less frequent characters
• Statistical Analysis: Calculate character frequency thresholds

3. Compression Strategies

Algorithmic Approaches

• Character frequency filtering
• Prefix coding
• Lossy and lossless compression techniques
• Multi-stage compression algorithm

4. Advanced Data Processing

• Stream Processing: Handle data in chunks
• Encoding Techniques:
  • Base64 encoding
  • zlib compression
• Error Handling: Robust decompression mechanisms

Algorithmic Complexity Analysis

Compression Process

1. Frequency Dictionary Creation: O(n)
2. Huffman Tree Construction: O(k log k)
3. Encoding Generation: O(k)
4. Data Compression: O(n)

Decompression Process

1. Code Reversal: O(k)
2. Bit Stream Decoding: O(n)

Technologies

• Python
• Flask
• Huffman Coding Algorithm
• zlib Compression
• Base64 Encoding

Installation

Prerequisites

• Python 3.8+
• pip

Setup

1. Clone the repository

git clone https://github.com/yourusername/file-compression-webapp.git
cd file-compression-webapp

2. Create a virtual environment

python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install dependencies

pip install -r requirements.txt

4. Run the application

python app.py

Usage

• Upload files for compression
• Adjust compression percentage
• Download compressed or decompressed files

Compression Techniques

• Character frequency filtering
• Huffman coding
• zlib compression
• Base64 encoding

Learning Outcomes

• Advanced compression algorithms
• Efficient data representation
• Algorithmic optimization techniques
• Practical application of theoretical computer science concepts

License

MIT License

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.