---
id: saspy
version: "5.108.6"
license: unclear
license_treatment: permissive
maintenance: active
---

# saspy — A Python interface to SAS

License: permissive · Maintenance: active · Downloads: 311.5K/mo

## What it is and what it does

SASPy is a bridge between Python and SAS that lets you write Python code to submit SAS programs to local or remote SAS systems and retrieve results back into Python. It converts between SAS datasets and Pandas DataFrames, supports multiple deployment types (Linux, Windows, MVS), and works in notebooks, IDEs, and batch scripts. The package generates SAS code from Python objects and methods, or accepts explicit SAS code you write, then returns analytics results as text, HTML5 documents, or structured data.

The package is designed for teams that need to combine SAS and Python capabilities in a single workflow—for instance, preprocessing data in Python, running SAS analytics, and post-processing results back in Python. It has no runtime dependencies beyond Python itself, though it requires an active SAS installation to connect to. The project is actively maintained and has been in development since 2016.

Use it for:

- Submit SAS procedures from Python and retrieve results as Pandas DataFrames for further analysis.
- Convert SAS datasets to Pandas for Python-based machine learning, then push results back to SAS.
- Run SAS analytics in Jupyter or Databricks notebooks while controlling workflow logic from Python.
- Automate SAS batch jobs from Python scripts, capturing output and graphics programmatically.
- Build mixed-language data pipelines that leverage both SAS and Python strengths in a single process.

## Worth the install?

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

SASPy connects Python to SAS deployments (local or remote) to run SAS code and return results as text, HTML, or Pandas DataFrames, enabling mixed Python/SAS workflows.

Yes, if you need to integrate SAS with Python workflows. The package is actively maintained, has no external dependencies, uses a permissive license, and is designed for exactly this use case. Install only if you have access to a SAS 9.4+ or SAS Viya 3+ deployment and need bidirectional Python-SAS integration.

## Install

pip install saspy
uv add saspy
poetry add saspy

## Installing saspy

Before you install: Low install friction with no runtime dependencies. The package is actively maintained, with a recent release 22 days ago and ongoing repository activity. Suitable for straightforward installation.

License in practice: Licensed under Apache License 2.0 (permissive), allowing use in commercial and open-source projects with minimal restrictions beyond attribution and liability disclaimers.

Quickstart:

pip install saspy

import saspy
sas = saspy.SASsession()
result = sas.submit('proc print data=sashelp.class; run;')
print(result)

Requires a SAS 9.4+ or SAS Viya 3+ deployment to connect to; Python alone cannot run SAS code without an accessible SAS instance.

Verify before relying:

- Whether the package works with Python versions beyond 3.5 despite the old classifiers listed (3.4, 3.5).
- Specific configuration steps required for each SAS deployment type (Linux, Windows, MVS, Jupyter, Databricks, Zeppelin).
- Performance characteristics and latency when connecting to remote SAS instances.

## Package facts

- License: not declared (permissive)
- Python support: unspecified
- Install friction: low
- Maintenance: active
- Downloads: 311.5K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

python sas interface, run sas code from python, sas pandas integration, python sas connector, sas analytics python, sas data frame conversion, python sas deployment, sas-integration, data-interchange, analytics-bridge

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