readstat

Rust library for parsing SAS binary files (.sas7bdat) into Apache Arrow RecordBatch format. Parsing is performed via FFI bindings to the ReadStat C library; the resulting data is exposed through a safe, idiomatic Rust API.

Note: The ReadStat C library supports SAS, SPSS, and Stata file formats. The readstat-sys crate exposes the full ReadStat API — all 125 functions across all formats. However, this crate only implements parsing and conversion for SAS .sas7bdat files. SPSS and Stata support is a possible future addition, but is not planned at this time — if you need those formats today, the readstat-sys bindings already expose the complete SPSS (.sav, .zsav, .por) and Stata (.dta) C API to build on.

Minimum Supported Rust Version (MSRV): 1.88 (Rust edition 2024).

Quick Start

Configure a reader from a path (or use from_bytes / from_mmap) and read an entire file into one Arrow RecordBatch:

fn main() -> Result<(), readstat::ReadStatError> {
    let reader = readstat::ReadStatReader::from_path("data.sas7bdat")?
        .rows(0, None)
        .columns(["Make", "Model"])
        .chunk_rows(10_000);
    let batch = reader.read()?;
    println!("{} rows x {} columns", batch.num_rows(), batch.num_columns());
    Ok(())
}

Or read just the file/variable metadata, without loading any rows:

fn main() -> Result<(), readstat::ReadStatError> {
    let reader = readstat::ReadStatReader::from_path("data.sas7bdat")?;
    let md = reader.metadata()?;
    println!("{:?} rows x {} columns", md.row_count, md.var_count);
    Ok(())
}

Use chunks() to collect chunks or visit() for bounded-memory processing. To write, construct a WriteConfig with new(format) or extension-inferred from_output(path), create ReadStatWriter::new(config, schema), call write(&batch) for each batch, then consume it with finish() to atomically publish the output and obtain the written row count. See the crate documentation for complete examples.

Features

Output format writers are feature-gated (all enabled by default):

• csv — CSV output via arrow-csv
• parquet — Parquet output (Snappy, Zstd, Brotli, Gzip, Lz4 compression)
• feather — Arrow IPC / Feather format
• ndjson — Newline-delimited JSON
• sql — DataFusion SQL query support (enabled by default), with synchronous and asynchronous APIs

Key Types

• ReadStatReader — Primary path, owned-bytes, and mmap reader; supports row/column selection, metadata, whole reads, chunks, and visitors
• ReadStatMetadata — File-level metadata (row/var counts, encoding, compression, schema)
• ReadStatWriter — Writes Arrow batches to the requested output format
• WriteConfig — Output configuration (path, format, compression)

Buffered SQL inputs may be executed repeatedly. Use record_batch_channel with synchronous APIs and async_record_batch_channel with async APIs for bounded, error-aware streaming input. Only channel-backed SQL input is single-execution because its receiver is consumed by the first scan; async output encoding runs off the executor with bounded backpressure.

For the full architecture overview, see docs/ARCHITECTURE.md.