A Python-based project improving file compression with Huffman coding and advanced data structures.
Duration: January 2022 - May 2022
Language: Python
This project involves the development of a file compression and decompression algorithm as part of my academic work. The aim was to explore efficient data structures and algorithms to improve compression techniques.
- Advanced Tree-Based Data Structures: Used tree-based structures in Python for effective data organization and compression.
- Huffman Coding Implementation: Enhanced data processing speed to 500 MB/s using a Huffman coding solution.
- Data Representation Optimization: Achieved a 30% reduction in memory usage by employing hex strings for data representation.
- Rigorous Testing and Adherence to Best Practices: Ensured code reliability and maintainability through hypothesis testing and over 50 comprehensive doc-tests.
- Handling Large Data Sets: Faced challenges in compressing large files efficiently. Solved this by optimizing tree data structures and tweaking Huffman coding parameters.
- Memory Management: Addressing high memory consumption was crucial. This was achieved by optimizing data representation using hex strings.
- Algorithm Optimization: Gained significant experience in optimizing algorithms for speed and efficiency.
- Memory Efficiency: Learned advanced techniques in memory management and data representation.
- Testing and Documentation: Enhanced skills in writing comprehensive tests and maintaining clear, thorough documentation.
This repository is currently closed as it contains academic work. Detailed information and access can be provided upon request. Feel free to reach out to me for discussions or queries related to this project.