minlz

A high-performance Rust implementation of the S2 compression format, providing binary compatibility with the Go implementation at github.com/klauspost/compress/s2.

Features

• Binary Compatible: Produces output 100% compatible with the Go S2 implementation
• High Performance: 1.6-47x faster decoding than Go depending on data pattern
• Multiple Compression Levels: Standard, Better, and Best modes
• Stream Format: Full Reader/Writer support with CRC32 validation
• Block Format: Simple block-based compression for known-size data
• Command-Line Tools: Full-featured s2c and s2d tools compatible with Go implementation
• Dictionary Compression: Full support for dictionary-based compression
• Concurrent Compression: Optional parallel compression with Rayon
• Index Support: Seeking within compressed streams
• Pure Rust: Written entirely in safe Rust with no unsafe code
• Well Tested: 108 tests, fuzz testing, and property-based testing

S2 Format

S2 is an extension of the Snappy compression format that provides:

• Better compression ratios than Snappy
• Faster decompression than Snappy
• Extended copy operations for better compression
• Repeat offset optimization (S2 extension)
• Compatible with Snappy-compressed data (for decompression)

Note: S2-compressed data cannot be decompressed by Snappy decoders.

More Information: S2 Design & Improvements - Overview of S2's design and improvements

Installation

Add this to your Cargo.toml:

[dependencies]
minlz = "0.1"

Optional Features

Enable concurrent compression for improved performance on multi-core systems:

[dependencies]
minlz = { version = "0.1", features = ["concurrent"] }

Usage

Block Format (Simple Compression)

use minlz::{encode, decode};

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let data = b"Hello, World! This is a test.";

    // Compress
    let compressed = encode(data);
    println!("Compressed {} bytes to {} bytes", data.len(), compressed.len());

    // Decompress
    let decompressed = decode(&compressed)?;
    assert_eq!(data, &decompressed[..]);

    Ok(())
}

Stream Format (With CRC Validation)

use minlz::{Writer, Reader};
use std::io::{Write, Read};

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let data = b"Streaming compression with CRC validation!";

    // Compress using stream format
    let mut compressed = Vec::new();
    {
        let mut writer = Writer::new(&mut compressed);
        writer.write_all(data)?;
        writer.flush()?;
    }

    // Decompress using stream format
    let mut reader = Reader::new(&compressed[..]);
    let mut decompressed = Vec::new();
    reader.read_to_end(&mut decompressed)?;

    assert_eq!(data, &decompressed[..]);
    Ok(())
}

Multiple Compression Levels

use minlz::{encode, encode_better, encode_best};

let data = b"Some data to compress...";

// Fast compression (default)
let compressed = encode(data);

// Better compression (slower)
let compressed_better = encode_better(data);

// Best compression (slowest)
let compressed_best = encode_best(data);

Concurrent Compression (Optional Feature)

Enable the concurrent feature for parallel compression on multi-core systems:

use minlz::ConcurrentWriter;
use std::io::Write;

let mut compressed = Vec::new();
{
    // Compress with 4 concurrent workers
    let mut writer = ConcurrentWriter::new(&mut compressed, 4);
    writer.write_all(&large_data)?;
    writer.flush()?;
}

Dictionary Compression

Dictionaries can improve compression of similar data by pre-seeding the compressor with common patterns:

use minlz::{make_dict, encode_with_dict, decode_with_dict};

// Create a dictionary from sample data
let samples = b"Common patterns that appear frequently in your data...";
let dict = make_dict(samples, Some(b"Common")).unwrap();

// Encode with dictionary
let data = b"Data to compress...";
let compressed = encode_with_dict(data, &dict);

// Decode with dictionary
let decompressed = decode_with_dict(&compressed, &dict)?;
assert_eq!(data, &decompressed[..]);

// Serialize dictionary for storage/transmission
let dict_bytes = dict.to_bytes();

Command-Line Tools

The minlz-tools package provides s2c (compression) and s2d (decompression) command-line tools that are fully compatible with the Go s2 tools.

# Install from source
cargo install --path minlz-tools

# Compress a file
s2c input.txt              # Creates input.txt.s2
s2c --slower input.txt     # Best compression
s2c --faster input.txt     # Fast compression

# Decompress a file
s2d input.txt.s2           # Creates input.txt
s2d --verify input.txt.s2  # Verify integrity

The tools are cross-compatible with Go's s2c/s2d and offer 12-98x faster performance depending on the operation.

See minlz-tools/README.md for complete documentation.

Performance

This Rust implementation delivers exceptional performance, often exceeding the Go reference implementation.

Benchmark Results (Intel i9-14900K)

Encoding Performance

Decoding Performance

Key Takeaways:

• Decode-heavy workloads: Rust is 17-98x faster (random/text data)
• Best compression mode: Binary compatible with Go's s2.EncodeBest, 12-16x faster
• Standard encoding: Faster than Go across all patterns, 1.5-1.7x on larger data
• Better mode: Go currently faster (area for future optimization)

See BENCHMARKS.md for detailed performance analysis.

Binary Compatibility

This implementation is binary compatible with the Go version. You can compress data with this Rust library and decompress it with the Go library, and vice versa.

Example: Interoperability with Go

Rust side:

use minlz::encode;
use std::fs::File;
use std::io::Write;

let data = b"Hello from Rust!";
let compressed = encode(data);

let mut file = File::create("data.s2")?;
file.write_all(&compressed)?;

Go side:

package main

import (
    "os"
    "github.com/klauspost/compress/s2"
)

func main() {
    compressed, _ := os.ReadFile("data.s2")
    decompressed, _ := s2.Decode(nil, compressed)
    println(string(decompressed)) // "Hello from Rust!"
}

Examples

Run the included examples:

# Basic compression example
cargo run --example basic

# Debug/testing example
cargo run --example debug

Block vs Stream Format

This library implements both formats:

Block Format

Suitable for:

• Data of known size
• In-memory compression
• Simple use cases
• Maximum compression speed

Stream Format

Includes:

• ✓ CRC32 validation (Castagnoli polynomial)
• ✓ Chunk framing with magic headers
• ✓ Full streaming support via Reader/Writer
• ✓ Incremental reading/writing
• ✓ Compatible with Go s2.Reader/Writer

Use stream format for file I/O, network streaming, or when you need data integrity validation.

Testing

This implementation includes comprehensive testing infrastructure:

Run Tests

# Unit and integration tests (48 tests)
cargo test

# Property-based tests (proptest)
cargo test --test proptest

# Benchmarks
cargo bench

# Fuzz testing
cargo install cargo-fuzz
cargo fuzz run fuzz_roundtrip
cargo fuzz run fuzz_decode
cargo fuzz run fuzz_stream

Test Coverage

• 81 Unit/Integration Tests: Core functionality and edge cases
• 10 Concurrent Tests: Parallel compression validation
• 10 Property-Based Tests: Using proptest for randomized testing
  • Roundtrip verification for all compression levels
  • Stream format validation
  • Compression ratio verification
  • Decoder robustness (never panics on invalid input)
  • Edge cases (empty data, small data, all-same-byte)
  • Compression level compatibility
• 3 Fuzz Targets: Continuous fuzzing with libfuzzer
  • Roundtrip fuzzing for all compression levels
  • Decode fuzzing (arbitrary input)
  • Stream format fuzzing
• 4 Compatibility Tests: Cross-validation with Go implementation
• Benchmark Suite: Performance comparison with Go implementation

Total: 108 tests

License

BSD-3-Clause

References

• S2 Design & Improvements - Overview of S2's design and improvements over Snappy
• Go S2 Implementation - Reference implementation
• Snappy Format Specification - Base Snappy format

Contributing

Contributions are welcome! Please ensure:

1. All tests pass (cargo test)
2. Code is formatted (cargo fmt)
3. No clippy warnings (cargo clippy)
4. Binary compatibility with Go implementation is maintained

The current implementation passes all 108 tests, is formatted with rustfmt, and has zero clippy warnings.