s-zip 0.4.0

High-performance streaming ZIP library with async/await support - Read/write ZIP files with minimal memory footprint. Supports arbitrary writers and Tokio runtime.
Documentation

s-zip

Crates.io Documentation License: MIT

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s-zip is a streaming ZIP reader and writer designed for backend systems that need to process large archives with minimal memory usage.

The focus is not on end-user tooling, but on providing a reliable ZIP building block for servers, batch jobs, and data pipelines.

Why s-zip?

Most ZIP libraries assume small files or in-memory buffers. s-zip is built around streaming from day one.

  • Constant memory usage
  • Suitable for very large files
  • Works well in containers and memory-constrained environments
  • Designed for backend and data-processing workloads

Key Features

  • Streaming ZIP writer (no full buffering)
  • Async/await support ⚡ NEW in v0.4.0! Compatible with Tokio runtime
  • Arbitrary writer support (File, Vec, network streams, etc.)
  • Streaming ZIP reader with minimal memory footprint
  • ZIP64 support for files >4GB
  • Multiple compression methods: DEFLATE, Zstd (optional)
  • Predictable memory usage: ~2-5 MB constant with 1MB buffer threshold
  • High performance: Zstd 3x faster than DEFLATE with 11-27x better compression
  • Concurrent operations: Create multiple ZIPs simultaneously with async
  • Rust safety guarantees
  • Backend-friendly API

Non-goals

  • Not a CLI replacement for zip/unzip
  • Not focused on desktop or interactive usage
  • Not optimized for small files convenience

Typical Use Cases

  • Web applications (Axum, Actix, Rocket) - Generate ZIPs on-demand
  • Cloud services - Stream ZIPs to S3, GCS without local storage
  • Generating large ZIP exports on the server
  • Packaging reports or datasets
  • Data pipelines and batch jobs
  • Infrastructure tools that require ZIP as an intermediate format
  • Real-time streaming - WebSocket, SSE, HTTP uploads

Performance Highlights

Based on comprehensive benchmarks (see BENCHMARK_RESULTS.md):

Metric DEFLATE level 6 Zstd level 3 Improvement
Speed (1MB) 610 MiB/s 2.0 GiB/s 3.3x faster
File Size (1MB compressible) 3.16 KB 281 bytes 11x smaller 🗜️
File Size (10MB compressible) 29.97 KB 1.12 KB 27x smaller 🗜️
Memory Usage 2-5 MB constant 2-5 MB constant Same ✓
CPU Usage Moderate Low-Moderate Better ✓

Key Benefits:

  • ✅ No temp files - Direct streaming saves disk I/O
  • ✅ ZIP64 support for files >4GB
  • ✅ Zstd compression: faster + smaller than DEFLATE
  • ✅ Constant memory usage regardless of archive size

Quick Start

Add this to your Cargo.toml:

[dependencies]
s-zip = "0.4"

# With async support (Tokio runtime)
s-zip = { version = "0.4", features = ["async"] }

# With async + Zstd compression
s-zip = { version = "0.4", features = ["async", "async-zstd"] }

Optional Features

Feature Description Dependencies
async Enables async/await support with Tokio runtime tokio, async-compression
async-zstd Async + Zstd compression support async, zstd-support
zstd-support Zstd compression for sync API zstd

Note: async-zstd includes both async and zstd-support features.

Reading a ZIP file

use s_zip::StreamingZipReader;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let mut reader = StreamingZipReader::open("archive.zip")?;

    // List all entries
    for entry in reader.entries() {
        println!("{}: {} bytes", entry.name, entry.uncompressed_size);
    }

    // Read a specific file
    let data = reader.read_entry_by_name("file.txt")?;
    println!("Content: {}", String::from_utf8_lossy(&data));

    // Or use streaming for large files
    let mut stream = reader.read_entry_streaming_by_name("large_file.bin")?;
    std::io::copy(&mut stream, &mut std::io::stdout())?;

    Ok(())
}

Writing a ZIP file

use s_zip::StreamingZipWriter;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let mut writer = StreamingZipWriter::new("output.zip")?;

    // Add first file
    writer.start_entry("file1.txt")?;
    writer.write_data(b"Hello, World!")?;

    // Add second file
    writer.start_entry("folder/file2.txt")?;
    writer.write_data(b"Another file in a folder")?;

    // Finish and write central directory
    writer.finish()?;

    Ok(())
}

Custom compression level

use s_zip::StreamingZipWriter;

let mut writer = StreamingZipWriter::with_compression("output.zip", 9)?; // Max compression
// ... add files ...
writer.finish()?;

Using Zstd compression (requires zstd-support feature)

use s_zip::{StreamingZipWriter, CompressionMethod};

fn main() -> Result<(), Box<dyn std::error::Error>> {
    // Create writer with Zstd compression (level 3, range 1-21)
    let mut writer = StreamingZipWriter::with_zstd("output.zip", 3)?;
    
    // Or use the generic method API
    let mut writer = StreamingZipWriter::with_method(
        "output.zip",
        CompressionMethod::Zstd,
        3  // compression level
    )?;

    writer.start_entry("compressed.bin")?;
    writer.write_data(b"Data compressed with Zstd")?;
    writer.finish()?;

    // Reader automatically detects and decompresses Zstd entries
    let mut reader = StreamingZipReader::open("output.zip")?;
    let data = reader.read_entry_by_name("compressed.bin")?;
    
    Ok(())
}

Note: Zstd compression provides better compression ratios than DEFLATE but may have slower decompression on some systems. The reader will automatically detect and decompress Zstd-compressed entries when the zstd-support feature is enabled.

Async/Await Support (NEW in v0.4.0!)

s-zip now supports async/await with Tokio runtime, enabling non-blocking I/O for web servers and cloud applications.

When to Use Async?

✅ Use Async for:

  • Web frameworks (Axum, Actix, Rocket)
  • Cloud storage uploads (S3, GCS, Azure)
  • Network streams (HTTP, WebSocket)
  • Concurrent operations (multiple ZIPs simultaneously)
  • Real-time applications

✅ Use Sync for:

  • CLI tools and scripts
  • Batch processing (single-threaded)
  • Maximum throughput (CPU-bound tasks)

Async Writer Example

use s_zip::AsyncStreamingZipWriter;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let mut writer = AsyncStreamingZipWriter::new("output.zip").await?;

    writer.start_entry("hello.txt").await?;
    writer.write_data(b"Hello, async world!").await?;

    writer.start_entry("data.txt").await?;
    writer.write_data(b"Streaming with async/await").await?;

    writer.finish().await?;
    Ok(())
}

Async with In-Memory (Cloud Upload)

Perfect for HTTP responses or cloud storage:

use s_zip::AsyncStreamingZipWriter;
use std::io::Cursor;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    // Create ZIP in memory
    let buffer = Vec::new();
    let cursor = Cursor::new(buffer);

    let mut writer = AsyncStreamingZipWriter::from_writer(cursor);

    writer.start_entry("data.json").await?;
    writer.write_data(br#"{"status": "ok"}"#).await?;

    // Get ZIP bytes for upload
    let cursor = writer.finish().await?;
    let zip_bytes = cursor.into_inner();

    // Upload to S3, send as HTTP response, etc.
    println!("Created {} bytes", zip_bytes.len());

    Ok(())
}

Streaming from Async Sources

Stream files directly without blocking:

use s_zip::AsyncStreamingZipWriter;
use tokio::fs::File;
use tokio::io::AsyncReadExt;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let mut writer = AsyncStreamingZipWriter::new("archive.zip").await?;

    // Stream large file without loading into memory
    writer.start_entry("large_file.bin").await?;

    let mut file = File::open("source.bin").await?;
    let mut buffer = vec![0u8; 8192];

    loop {
        let n = file.read(&mut buffer).await?;
        if n == 0 { break; }
        writer.write_data(&buffer[..n]).await?;
    }

    writer.finish().await?;
    Ok(())
}

Concurrent ZIP Creation

Create multiple ZIPs simultaneously (5x faster than sequential):

use s_zip::AsyncStreamingZipWriter;
use tokio::task::JoinSet;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let mut tasks = JoinSet::new();

    // Create 10 ZIPs concurrently
    for i in 0..10 {
        tasks.spawn(async move {
            let path = format!("output_{}.zip", i);
            let mut writer = AsyncStreamingZipWriter::new(&path).await?;
            writer.start_entry("data.txt").await?;
            writer.write_data(b"Concurrent creation!").await?;
            writer.finish().await?;
            Ok::<_, s_zip::SZipError>(())
        });
    }

    // Wait for all to complete
    while let Some(result) = tasks.join_next().await {
        result.unwrap()?;
    }

    println!("Created 10 ZIPs concurrently!");
    Ok(())
}

Performance: Async vs Sync

Scenario Sync Async Advantage
Local disk (5MB) 6.7ms 7.1ms ≈ Same (~6% overhead)
In-memory (100KB) 146µs 136µs Async 7% faster
Network upload (5×50KB) 1053ms 211ms Async 5x faster 🚀
10 concurrent operations 70ms 10-15ms Async 4-7x faster 🚀

See PERFORMANCE.md for detailed benchmarks.

Using Arbitrary Writers (Advanced)

NEW in v0.3.0: s-zip now supports writing to any type that implements Write + Seek, not just files. This enables:

  • In-memory ZIP creation (Vec, Cursor)
  • Network streaming (TCP streams with buffering)
  • Custom storage backends (S3, databases, etc.)
use s_zip::StreamingZipWriter;
use std::io::Cursor;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    // Write ZIP to in-memory buffer
    let buffer = Vec::new();
    let cursor = Cursor::new(buffer);

    let mut writer = StreamingZipWriter::from_writer(cursor)?;

    writer.start_entry("data.txt")?;
    writer.write_data(b"In-memory ZIP content")?;

    // finish() returns the writer, allowing you to extract the data
    let cursor = writer.finish()?;
    let zip_bytes = cursor.into_inner();

    // Now you can save to file, send over network, etc.
    std::fs::write("output.zip", &zip_bytes)?;
    println!("Created ZIP with {} bytes", zip_bytes.len());

    Ok(())
}

⚠️ IMPORTANT - Memory Usage by Writer Type:

Writer Type Memory Usage Best For
File (StreamingZipWriter::new(path)) ✅ ~2-5 MB constant Large files, production use
Network streams (TCP, pipes) ✅ ~2-5 MB constant Streaming over network
Vec/Cursor (from_writer()) ⚠️ ENTIRE ZIP IN RAM Small archives only (<100MB)

⚠️ Critical Warning for Vec/Cursor: When using Vec<u8> or Cursor<Vec<u8>> as the writer, the entire compressed ZIP file will be stored in memory. While the compressor still uses only ~2-5MB for its internal buffer, the final output accumulates in the Vec. Only use this for small archives or when you have sufficient RAM.

Recommended approach for large files:

  • Use StreamingZipWriter::new(path) to write to disk (constant ~2-5MB memory)
  • Use network streams for real-time transmission
  • Reserve Vec<u8>/Cursor for small temporary ZIPs (<100MB)

The implementation uses a 1MB buffer threshold to periodically flush compressed data to the writer, keeping compression memory low (~2-5MB) for all writer types. However, in-memory writers like Vec<u8> will still accumulate the full output.

See examples/arbitrary_writer.rs for more examples.

Supported Compression Methods

Method Description Default Feature Flag Best For
DEFLATE (8) Standard ZIP compression Always available Text, source code, JSON, XML, CSV, XLSX
Stored (0) No compression - Always available Already compressed files (JPG, PNG, MP4, PDF)
Zstd (93) Modern compression algorithm - zstd-support All text/data files, logs, databases

Compression Method Selection Guide

Use DEFLATE (default) when:

  • ✅ Maximum compatibility required (all ZIP tools support it)
  • ✅ Working with: text files, source code, JSON, XML, CSV, HTML, XLSX
  • ✅ Standard ZIP format compliance needed

Use Zstd when:

  • Best performance: 3.3x faster compression, 11-27x better compression ratio
  • ✅ Working with: server logs, database dumps, repetitive data, large text files
  • ✅ Backend/internal systems (don't need old tool compatibility)
  • ✅ Processing large volumes of data

Use Stored (no compression) when:

  • ✅ Files are already compressed: JPEG, PNG, GIF, MP4, MOV, PDF, ZIP, GZ
  • ✅ Need fastest possible archive creation
  • ✅ CPU resources are limited

Performance Benchmarks

s-zip includes comprehensive benchmarks to compare compression methods:

# Run all benchmarks with Zstd support
./run_benchmarks.sh

# Or run individual benchmark suites
cargo bench --features zstd-support --bench compression_bench
cargo bench --features zstd-support --bench read_bench

Benchmarks measure:

  • Compression speed: Write throughput for different compression methods and levels
  • Decompression speed: Read throughput for various compressed formats
  • Data patterns: Highly compressible text, random data, and mixed workloads
  • File sizes: From 1KB to 10MB to test scaling characteristics
  • Multiple entries: Performance with 100+ files in a single archive

Results are saved to target/criterion/ with HTML reports showing detailed statistics, comparisons, and performance graphs.

Quick Comparison Results

File Size (1MB Compressible Data)

Method Compressed Size Ratio Speed
DEFLATE level 6 3.16 KB 0.31% ~610 MiB/s
DEFLATE level 9 3.16 KB 0.31% ~494 MiB/s
Zstd level 3 281 bytes 0.03% ~2.0 GiB/s
Zstd level 10 358 bytes 0.03% ~370 MiB/s

Key Insights:

  • Zstd level 3 is 11x smaller and 3.3x faster than DEFLATE on repetitive data
  • For 10MB data: Zstd = 1.12 KB vs DEFLATE = 29.97 KB (27x better!)
  • Random data: All methods ~100% (both handle incompressible data efficiently)
  • Memory: ~2-5 MB constant regardless of file size
  • CPU: Zstd level 3 uses less CPU than DEFLATE level 9

💡 Recommendation: Use Zstd level 3 for best performance and compression. Only use DEFLATE when compatibility with older tools is required.

📊 Full Analysis: See BENCHMARK_RESULTS.md for detailed performance data including:

  • Complete speed benchmarks (1KB to 10MB)
  • Memory profiling
  • CPU usage analysis
  • Multiple compression levels comparison
  • Random vs compressible data patterns

Migration Guide

Upgrading from v0.3.x to v0.4.0

Zero Breaking Changes! The v0.4.0 release is fully backward compatible.

What's New:

  • ✅ Async/await support (opt-in via async feature)
  • ✅ Concurrent ZIP creation
  • ✅ Better performance for network/cloud operations
  • ✅ All existing sync code works unchanged

Migration Options:

Option 1: Keep Using Sync (No Changes)

[dependencies]
s-zip = "0.4"  # No feature flags needed

Your existing code continues to work exactly as before!

Option 2: Add Async Support

[dependencies]
s-zip = { version = "0.4", features = ["async"] }

Now you can use both:

  • StreamingZipWriter (sync, existing code)
  • AsyncStreamingZipWriter (new async API)

Option 3: Async + Zstd

[dependencies]
s-zip = { version = "0.4", features = ["async-zstd"] }

Enables both async and Zstd compression.

API Comparison:

// Sync (v0.3.x and v0.4.0)
let mut writer = StreamingZipWriter::new("output.zip")?;
writer.start_entry("file.txt")?;
writer.write_data(b"data")?;
writer.finish()?;

// Async (NEW in v0.4.0)
let mut writer = AsyncStreamingZipWriter::new("output.zip").await?;
writer.start_entry("file.txt").await?;
writer.write_data(b"data").await?;
writer.finish().await?;

The only differences: AsyncStreamingZipWriter and .await keywords!

Examples

Check out the examples/ directory for complete working examples:

Sync Examples:

Async Examples (NEW!):

Run examples:

# Sync examples
cargo run --example basic
cargo run --example zstd_compression --features zstd-support

# Async examples
cargo run --example async_basic --features async
cargo run --example concurrent_demo --features async
cargo run --example network_simulation --features async

Documentation

License

MIT License - see LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Author

Ton That Vu - @KSD-CO