Text Compression for Beginners: Building Huffman Coding from Scratch in Swift
Ever wondered how file compression actually works? This weekend, curiosity got the better of me, so I decided to dive deep and implement Huffman coding from scratch.
What you’ll learn:
- 🌳 How Huffman trees work (with visual examples)
- 📊 Why Huffman is perfect for text/code compression
- 🔍 Step-by-step walkthrough of the „Mississippi“ example
- ⚡ How to achieve ~50% compression on typical text files
Why Huffman?
Unlike Run Length Encoding (great for images), Huffman coding shines with the kind of files we work with daily – source code, JSON, XML, plain text. It assigns shorter bit sequences to frequent characters and longer ones to rare characters.
The best part? It’s lossless – your original file is perfectly restored after decompression.
What we’ll build:
A complete compression/decompression system including:
- Frequency analysis
- Huffman tree construction
- Bit-level file operations
- Compact tree serialization
Ready to see how „Mississippi“ becomes just 3 bytes? Let’s dive in! 👇
P.S. The CLI tool is called „Kompressor“ after my vacuum-packed cat plushie that never fully „decompressed“ 😸