saslite 0.1.1

Lightweight local SAS language interpreter

SASLite

SASLite is a lightweight local interpreter for a practical subset of the SAS language, implemented in Python on top of pandas. It is intended for local data checks, small automation workflows, SAS-like examples, and migration/testing work where a full SAS runtime is not available.

SASLite is an independent project. It is not affiliated with, endorsed by, or supported by SAS Institute Inc.

Status

This project is currently alpha software. It supports a useful subset of SAS syntax, but it is not a complete SAS replacement. Validate results carefully before using them for regulated, clinical, financial, or other high-stakes work.

Installation

pip install saslite

Optional extras:

pip install "saslite[excel]"
pip install "saslite[gui]"

For local development from a checkout:

pip install -e ".[excel,gui]"

Command Line

Run a SAS program:

saslite path/to/program.sas

Run one statement:

saslite -e "data demo; x = 1; output; run;"

Start the interactive prompt:

saslite --interactive

Use a persistent working directory for local datasets:

saslite --workdir ./work path/to/program.sas

GUI

Install the GUI extra:

pip install "saslite[gui]"

Start the browser-based GUI:

saslite-gui

This starts a local Flask server at http://127.0.0.1:5000 and opens it in the default browser. To keep it from opening a browser tab automatically:

saslite-gui --no-browser

Start the desktop wrapper, powered by pywebview:

saslite-desktop

On Windows, the desktop wrapper may require Microsoft Edge WebView2 Runtime. The browser-based saslite-gui command is the simpler fallback.

Python API

from saslite import SasInterpreter

sas = SasInterpreter()

result = sas.execute(
    """
    data work.employees;
        input name $ age salary;
        datalines;
    Alice 30 50000
    Bob 25 40000
    ;
    run;

    proc print data=work.employees;
    run;
    """
)

print(result.success)
df = sas.get_dataset("WORK", "EMPLOYEES")
print(df)

Create a SASLite dataset from pandas:

import pandas as pd
from saslite import SasInterpreter

sas = SasInterpreter()
source = pd.DataFrame({"id": [1, 2, 3], "value": [10, 20, 30]})
sas.create_dataset("source", source)

sas.execute(
    """
    data work.result;
        set work.source;
        doubled = value * 2;
    run;
    """
)

result = sas.get_dataset("WORK", "RESULT")

Supported Features

SASLite includes support for:

• DATA step basics: DATA, SET, INPUT, DATALINES, INFILE, OUTPUT, KEEP, DROP, RENAME, WHERE, IF, DO, BY, FIRST. and LAST.
• PROC SQL basics: SELECT, CREATE TABLE, joins, grouping, ordering, calculated columns, CASE, LIKE, BETWEEN, IN, IS NULL, and common aggregate functions.
• PROC steps including PRINT, SORT, CONTENTS, MEANS, SUMMARY, FREQ, IMPORT, EXPORT, APPEND, and DATASETS.
• LIBNAME references for local work areas.
• A lightweight macro expander for common macro-variable workflows.
• Common SAS-style character, numeric, date/time, missing-value, and utility functions.
• CSV import/export through the Python API and PROC IMPORT/EXPORT.

See DOCS.md and the examples/ directory in the source repository for more complete usage notes.

Examples

data work.sales;
    input region $ product $ amount;
    datalines;
East Widget 100
West Gadget 200
East Widget 150
;
run;

proc sql;
    create table work.summary as
    select region, sum(amount) as total_sales
    from work.sales
    group by region
    order by total_sales desc;
quit;

Run it with:

saslite examples/basic_sql.sas

Known Limits

SASLite intentionally implements a subset of SAS. Some advanced or environment specific SAS features are not supported, including the full macro language, remote libraries, SAS server integration, complete format/informat coverage, ODS, graphics, and every PROC available in commercial SAS.

When SASLite cannot parse or execute a program exactly, simplify the program to the supported subset or use the Python API to prepare input datasets directly.

Development

Install development dependencies:

pip install -e ".[excel,gui]"
pip install pytest build twine

Run tests:

python -m pytest -q

Build distribution artifacts:

python -m build

Check package metadata:

python -m twine check dist/*

Publishing

Test the package on TestPyPI before publishing to PyPI:

python -m build
python -m twine upload --repository testpypi dist/*

After verifying installation from TestPyPI, publish the same version to PyPI:

python -m twine upload dist/*

License

SASLite is distributed under the MIT License. See LICENSE for details.