rds2rust

A pure Rust library for reading and writing R's RDS (R Data Serialization) files without requiring an R runtime. Inspired by rds2cpp, which provides similar functionality with a C++ implementation.

Features

• Pure Rust implementation - No R runtime required
• Complete RDS format support - Reads and writes all R object types
• Memory efficient - Optimized with string interning, compact attributes, and object deduplication
• Automatic compression - Transparent gzip compression/decompression
• Type safe - Strong Rust types for all R objects
• Zero-copy where possible - Efficient parsing and serialization

Supported R Types

• Primitive types: NULL, integers, doubles, logicals, characters, raw bytes, complex numbers
• Collections: vectors, lists, pairlists, expression vectors
• Data structures: data frames, matrices, factors (ordered and unordered)
• Object-oriented: S3 objects, S4 objects with slots
• Language objects: formulas, unevaluated expressions, function calls
• Functions: closures, environments, promises, special/builtin functions
• Advanced: reference tracking (REFSXP), ALTREP compact sequences

Installation

Add this to your Cargo.toml:

[dependencies]
rds2rust = "0.1"

Quick Start

Reading an RDS file

use rds2rust::{read_rds, RObject};
use std::fs;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    // Read RDS file (automatically decompresses if gzipped)
    let data = fs::read("data.rds")?;
    let obj = read_rds(&data)?;

    // Pattern match on R object type
    match obj {
        RObject::DataFrame(df) => {
            println!("Data frame with {} columns", df.columns.len());

            // Access a specific column
            if let Some(RObject::Real(values)) = df.columns.get("temperature") {
                println!("Temperature values: {:?}", values);
            }
        }
        RObject::Integer(vec) => {
            println!("Integer vector: {:?}", vec);
        }
        _ => println!("Other R object type"),
    }

    Ok(())
}

Writing an RDS file

use rds2rust::{write_rds, RObject};
use std::fs;
use std::sync::Arc;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    // Create an R object (e.g., a character vector)
    let obj = RObject::Character(vec![
        Arc::from("hello"),
        Arc::from("world"),
    ]);

    // Serialize to RDS format (automatically gzip compressed)
    let rds_data = write_rds(&obj)?;

    // Write to file
    fs::write("output.rds", rds_data)?;

    Ok(())
}

Working with Data Frames

use rds2rust::{read_rds, RObject};
use std::sync::Arc;

// Read a data frame
let data = std::fs::read("iris.rds")?;
let obj = read_rds(&data)?;

if let RObject::DataFrame(df) = obj {
    // Access columns by name
    let sepal_length = df.columns.get(&Arc::from("Sepal.Length"));
    let species = df.columns.get(&Arc::from("Species"));

    // Access row names
    println!("First row name: {}", df.row_names[0]);

    // Iterate over columns
    for (name, values) in &df.columns {
        println!("Column: {}", name);
    }
}

Working with Factors

use rds2rust::{read_rds, RObject};

let data = std::fs::read("factor.rds")?;
let obj = read_rds(&data)?;

if let RObject::Factor(factor) = obj {
    // Check if it's an ordered factor
    if factor.ordered {
        println!("Ordered factor with {} levels", factor.levels.len());
    }

    // Get level labels
    for level in &factor.levels {
        println!("Level: {}", level);
    }

    // Get values (1-based indices into levels)
    for &index in &factor.values {
        if index > 0 && index <= factor.levels.len() as i32 {
            let level = &factor.levels[(index - 1) as usize];
            println!("Value: {}", level);
        }
    }
}

Working with S3/S4 Objects

use rds2rust::{read_rds, RObject};
use std::sync::Arc;

let data = std::fs::read("model.rds")?;
let obj = read_rds(&data)?;

// S3 objects
if let RObject::S3Object(s3) = obj {
    println!("S3 class: {:?}", s3.class);

    // Access base object
    match s3.base.as_ref() {
        RObject::List(elements) => {
            println!("S3 object is a list with {} elements", elements.len());
        }
        _ => {}
    }

    // Access additional attributes
    if let Some(desc) = s3.attributes.get("description") {
        println!("Description: {:?}", desc);
    }
}

// S4 objects
if let RObject::S4Object(s4) = obj {
    println!("S4 class: {:?}", s4.class);

    // Access slots
    if let Some(slot_value) = s4.slots.get(&Arc::from("data")) {
        println!("Data slot: {:?}", slot_value);
    }
}

Roundtrip: Read and Write

use rds2rust::{read_rds, write_rds};
use std::fs;

// Read an RDS file
let input_data = fs::read("input.rds")?;
let obj = read_rds(&input_data)?;

// Process the data...
// (modify the object as needed)

// Write back to RDS format
let output_data = write_rds(&obj)?;
fs::write("output.rds", output_data)?;

// Verify roundtrip
let obj2 = read_rds(&output_data)?;
assert_eq!(obj, obj2);

Type System

The RObject enum represents all possible R object types:

pub enum RObject {
    Null,
    Integer(Vec<i32>),
    Real(Vec<f64>),
    Logical(Vec<Logical>),
    Character(Vec<Arc<str>>),
    Raw(Vec<u8>),
    Complex(Vec<Complex>),
    List(Vec<RObject>),
    Pairlist(Vec<PairlistElement>),
    Language(Vec<RObject>),
    Expression(Vec<RObject>),
    Closure { formals: Box<RObject>, body: Box<RObject>, environment: Box<RObject> },
    Environment { enclosing: Box<RObject>, frame: Box<RObject>, hashtab: Box<RObject> },
    Promise { value: Box<RObject>, expression: Box<RObject>, environment: Box<RObject> },
    Special { name: Arc<str> },
    Builtin { name: Arc<str> },
    DataFrame(Box<DataFrameData>),
    Factor(Box<FactorData>),
    S3Object(Box<S3ObjectData>),
    S4Object(Box<S4ObjectData>),
    WithAttributes { object: Box<RObject>, attributes: Attributes },
}

Special Values

R's special values are represented as:

• NA (integers): RObject::NA_INTEGER constant (i32::MIN)
• NA (logicals): Logical::Na enum variant
• NA (real): Check with f64::is_nan()
• Inf/-Inf: f64::INFINITY and f64::NEG_INFINITY
• NaN: f64::NAN

Memory Optimizations

rds2rust includes several memory optimizations for efficient data processing:

1. String Interning - All strings use Arc<str> for automatic deduplication
2. Boxed Large Variants - Large enum variants are boxed to reduce memory overhead
3. Compact Attributes - SmallVec stores 0-2 attributes inline without heap allocation
4. Object Deduplication - Identical objects are automatically shared during parsing

These optimizations provide 20-50% memory reduction for typical RDS files while maintaining zero API overhead.

Performance Tips

Reading Large Files

use rds2rust::read_rds;
use std::fs::File;
use std::io::Read;

// For very large files, read in chunks if needed
let mut file = File::open("large.rds")?;
let mut buffer = Vec::new();
file.read_to_end(&mut buffer)?;

let obj = read_rds(&buffer)?;

Reusing Parsed Objects

use std::sync::Arc;
use rds2rust::RObject;

// Wrap in Arc for cheap cloning
let obj = Arc::new(read_rds(&data)?);

// Clone is cheap (just increments reference count)
let obj2 = Arc::clone(&obj);

Limitations

• Write support: All R types can be written except for some complex environment configurations
• Compression formats: Currently supports gzip; bzip2/xz support planned
• ALTREP: Reads ALTREP objects but writes them as regular vectors
• External pointers: Not supported (rarely used in serialized data)

Development Status

Current version: 0.1.0

Test coverage: 137 passing tests covering all R object types

Completed phases:

• ✅ All basic R types (NULL, vectors, matrices, data frames)
• ✅ All object-oriented types (S3, S4, factors)
• ✅ All language types (expressions, formulas, closures, environments)
• ✅ All special types (promises, special functions, builtin functions)
• ✅ Reference tracking and ALTREP optimization
• ✅ Complete read/write roundtrip support
• ✅ Memory optimizations (string interning, compact attributes, deduplication)

License

Licensed under:

• MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)

Resources

• RDS Format Documentation
• Project Plan
• Test Generation Guide
• R Internals Manual