Let's dive into implementing the decompression function for our custom compression library. Since we're building a combined RLE + Huffman coding system, our decompression logic will need to reverse this process. ### Decompression Logic Overview Our decompression function will need to: 1. Read the compressed byte stream 2. Parse the Huffman tree structure 3. Reconstruct the original data by reversing the RLE encoding ### Implementation Details First, let's create a struct to hold our compressed data format: ```rust use std::collections::HashMap; #[derive(Debug, Serialize, Deserialize)] struct CompressedData { header: Header, data: Vec, } #[derive(Debug, Serialize, Deserialize)] struct Header { original_length: usize, huffman_codes: HashMap>, } ``` The `CompressedData` struct contains: - `header`: Metadata about the original data - `data`: The actual compressed bytes The `Header` struct contains: - `original_length`: Length of the original data before compression - `huffman_codes`: The Huffman codes dictionary ### Decompression Function Here's the implementation of our decompression function: ```rust use std::io; use bincode; pub fn decompress(compressed_bytes: Vec) -> Result, io::Error> { // Deserialize the compressed data structure let compressed_data: CompressedData = bincode::deserialize(&compressed_bytes)?; // Rebuild the Huffman tree from the codes let huffman_tree = huffman_tree_from_codes(&compressed_data.header.huffman_codes)?; // Initialize our output buffer let mut output = Vec::new(); // Initialize our current position in the compressed data let mut current_pos = 0; // Process each byte in the compressed data while current_pos < compressed_data.data.len() { // Find the matching code in the Huffman tree let (code, value) = find_code(&huffman_tree, &compressed_data.data, current_pos)?; // Write the corresponding byte to the output output.write_all(&[value])?; // Move current position forward by the code length current_pos += code.len(); } // Ensure we've properly reconstructed the original data length assert_eq!(output.len(), compressed_data.header.original_length); Ok(output) } // Helper function to rebuild Huffman tree from codes fn huffman_tree_from_codes(codes: &HashMap>) -> Result { // Implementation of rebuilding Huffman tree from codes // (This is a simplified example - actual implementation would need proper tree construction) Ok(HuffmanTree::new()) } // Helper function to find matching code in Huffman tree fn find_code(tree: &HuffmanTree, data: &Vec, start_pos: usize) -> Result<(Vec, u8), io::Error> { // Implementation of code lookup in Huffman tree // (This is a simplified example - actual implementation would need proper code lookup) Ok((Vec::new(), 0)) } ``` ### Explanation 1. **Data Structure**: We start by defining a proper data structure for our compressed data. This includes both the header (metadata) and the actual compressed bytes. 2. **Deserialization**: Using the `bincode` crate, we deserialize the compressed data into our `CompressedData` struct. This gives us access to both the header information and the compressed bytes. 3. **Huffman Tree Reconstruction**: The Huffman tree needs to be reconstructed from the codes stored in the header. This allows us to properly decode the compressed data. 4. **Decompression Logic**: We process each byte of the compressed data, using the Huffman tree to find the corresponding code and write the original byte to the output buffer. 5. **Error Handling**: Proper error handling is implemented using `Result` types to handle potential issues during deserialization and tree reconstruction. ### Next Steps Now that we've implemented the decompression function, the next steps would be: 1. **Implement proper Huffman tree reconstruction**: The current implementation is a placeholder. You'll need to implement proper tree reconstruction from the codes. 2. **Implement proper code lookup**: The `find_code` function currently returns a placeholder value. You'll need to implement proper code lookup in the Huffman tree. 3. **Test the decompression function**: Once the above components are properly implemented, test the decompression function with various sample data to ensure it correctly reconstructs the original data. ### Further Reading For deeper understanding of the concepts involved: - [Huffman Coding](https://en.wikipedia.org/wiki/Huffman_coding) - [Run-Length Encoding (RLE)](https://en.wikipedia.org/wiki/Run-length_encoding) - [Rust Serialization with bincode](https://github.com/TyOverby/bincode) - [Huffman Tree Construction Algorithms](https://en.wikipedia.org/wiki/Huffman_coding#Algorithm)

Custom Compression Library

Learning Outcomes