---
id: sas7bdat
version: "2.2.3"
license: MIT
license_treatment: permissive
maintenance: abandoned
---

# sas7bdat — A sas7bdat file reader for Python

License: permissive · Maintenance: abandoned · Downloads: 157.3K/mo

## What it is and what it does

sas7bdat is a pure-Python reader for SAS7BDAT files, the binary data format used by SAS statistical software. It parses these files without requiring SAS to be installed, returning rows as lists of typed values (strings, floats, dates, times) and optionally converting to pandas DataFrames. The package also includes a command-line tool, `sas7bdat_to_csv`, for batch conversion and metadata inspection.

The library was originally ported from an R implementation but has been substantially rewritten. While the author reports successful testing on sample files, the project has been abandoned since 2019 with no active maintenance. This means new SAS file format features, compression methods, or Python version incompatibilities will not be addressed.

Use it for:

- Import SAS data files into Python workflows without installing SAS software or licensing costs.
- Batch convert legacy SAS7BDAT files to CSV format for archival, migration, or sharing with non-SAS users.
- Load SAS statistical datasets into pandas for analysis in Jupyter notebooks or data science pipelines.
- Extract metadata and column attributes from SAS files for data documentation or schema inspection.
- Automate data pipelines that consume SAS output files from external statistical analyses.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Reads SAS7BDAT files (SAS statistical software data format) using pure Python, with no SAS software required, and optionally converts them to CSV or pandas DataFrames.

Yes, but with caution: install if you need to read SAS7BDAT files and have no alternative, and if your files match the formats already tested. The permissive MIT license and zero runtime dependencies make it low-risk to try. However, do not rely on it for production systems or new SAS file formats—the abandonment since 2019 means bugs in modern Python versions or recent SAS formats will not be fixed. Test thoroughly with your actual data before committing to it.

## Install

pip install sas7bdat
uv add sas7bdat
poetry add sas7bdat

## Installing sas7bdat

Before you install: High install friction: the package is abandoned (last release 2019-07-15, no recent commits), with no runtime dependencies but marked as production-stable despite years without maintenance. Installation itself is straightforward, but the lack of active support means bugs in newer Python versions or SAS file formats will not be fixed.

License in practice: MIT license is permissive, allowing commercial and private use with minimal restrictions. You may use, modify, and distribute this code freely as long as you include the original license notice.

Quickstart:

pip install sas7bdat

from sas7bdat import SAS7BDAT
with SAS7BDAT('foo.sas7bdat', skip_header=True) as reader:
    for row in reader:
        print(row)

df = reader.to_data_frame()

Verify before relying:

- Whether the package works reliably with modern Python versions (3.9+) given the abandonment status and last release in 2019.
- Compatibility with recent SAS file format variations or compression methods introduced after 2019.
- Whether the approximately three hundred sample files tested represent comprehensive coverage or edge cases remain untested.

## Package facts

- License: MIT (permissive)
- Python support: unspecified
- Install friction: high
- Maintenance: abandoned
- Downloads: 157.3K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

read sas7bdat files python, sas data format reader, sas7bdat to csv converter, sas statistical data import, parse sas data files, sas file parser library, data-format-parser, sas-interop, abandoned-but-stable

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