This project implements a simple Huffman coding algorithm for compressing and decompressing text files. Huffman coding is a popular method for lossless data compression, where frequently occurring characters are represented by shorter binary codes, thus reducing the overall file size.
- Compress text files into a binary format (
.bin) - Decompress binary files back to their original text format
- Error handling for empty input files
- Python 3.x
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Clone this repository:
git clone https://github.com/Nikson2003/huffman-coding.git
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Navigate into the project directory:
cd huffman-coding -
Ensure you have Python installed. You can check your Python version with:
python --version
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Place the text file you want to compress in the project directory and update the path variable in main.py to point to your text file.
path = "testing.txt" -
Run the main.py script:
python main.py
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After running, the compressed file will be created in the same directory with a .bin extension. The decompressed text file will have _decompressed appended to the original filename.
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Frequency Dictionary: The algorithm first calculates the frequency of each character in the input text.
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Heap Creation: A min-heap is created based on the frequencies of the characters.
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Huffman Tree Construction: Nodes are merged to create a binary tree, where each leaf node represents a character.
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Code Generation: Binary codes are generated for each character based on their position in the tree.
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Encoding: The input text is encoded into a binary string, padded to ensure its length is a multiple of 8 bits.
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Compression: The padded binary string is converted into a byte array and written to a binary file.
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Decompression: The binary file is read, decoded, and the original text is restored.