Open-SAS VS Code Extension

Features

• Syntax Highlighting: Full SAS-style statistical analysis syntax highlighting for .osas and .sas files
• Code Snippets: Common statistical analysis patterns and procedures
• File Execution: Run SAS-style Open-SAS files directly from VS Code
• Notebook Support: Interactive statistical notebooks (both .ipynb with osas kernel and .osasnb files)
• IntelliSense: Code completion and syntax checking
• Integrated Terminal: View results in VS Code's integrated terminal

Installation

1. Install the extension from the VS Code Marketplace
2. Install the Open-SAS Python package:

   pip install open-sas
   

3. Install the Jupyter kernel (optional, for notebook support):

   python -m open_sas.kernel install
   

Usage

Basic SAS-Style Files (.osas)

1. Create a new file with .osas extension
2. Write your SAS-style code
3. Use Ctrl+Shift+P → "Open-SAS: Run File" to execute
4. View results in the integrated terminal

Interactive Notebooks

Option 1: Standard Jupyter Notebooks (.ipynb)

1. Install the Open-SAS kernel: python -m open_sas.kernel install
2. Create a new Jupyter notebook (.ipynb)
3. Select "osas" as the kernel
4. Write SAS-style code in cells and execute

Option 2: Open-SAS Notebooks (.osasnb)

1. Create a new file with .osasnb extension
2. Write SAS-style code in cells
3. Execute cells individually or run all
4. View formatted output and datasets

Code Snippets

Type common statistical analysis patterns and press Tab to expand:

• data → DATA step template
• proc → Statistical procedure template
• means → PROC MEANS template
• freq → PROC FREQ template
• reg → PROC REG template
• sql → PROC SQL template
• macro → Macro definition template

Supported Features

• DATA Steps: Variable creation, conditional logic, DATALINES
• PROC MEANS: Descriptive statistics with CLASS variables and OUTPUT statements
• PROC FREQ: Frequency tables and cross-tabulations with options
• PROC SORT: Data sorting with ascending/descending order
• PROC PRINT: Data display and formatting
• PROC REG: Linear regression analysis with MODEL, OUTPUT, and SCORE statements
• PROC SURVEYSELECT: Random sampling with SRS method, SAMPRATE/N options, and OUTALL flag
• PROC UNIVARIATE: Detailed univariate analysis with distribution diagnostics
• PROC CORR: Correlation analysis (Pearson, Spearman)
• PROC FACTOR: Principal component analysis and factor analysis
• PROC CLUSTER: Clustering methods (k-means, hierarchical)
• PROC NPAR1WAY: Nonparametric tests (Mann-Whitney, Kruskal-Wallis)
• PROC TTEST: T-tests (independent and paired)
• PROC LOGIT: Logistic regression modeling
• PROC TIMESERIES: Time series analysis and seasonal decomposition
• PROC TREE/FOREST/BOOST: Machine learning (decision trees, random forests, gradient boosting)
• PROC SQL: SQL query processing with DuckDB backend
• PROC LANGUAGE: Built-in LLM integration for text generation and analysis
• SAS Macro System: %MACRO/%MEND, %LET, & substitution, %PUT, %IF/%THEN/%ELSE, %DO/%END
• SAS Format System: Built-in date/time, numeric, and currency formats with metadata persistence
• Macro Variables: %LET, %PUT statements
• Libraries: LIBNAME functionality
• TITLE Statements: Title support for output formatting

Configuration

The extension can be configured through VS Code settings:

• open-sas.pythonPath: Path to Python executable
• open-sas.openSASPath: Path to Open-SAS runner script
• open-sas.showOutputOnRun: Show output channel when running code

Requirements

• Python 3.8 or higher
• Open-SAS Python package
• VS Code 1.60.0 or higher

Demo

Check out the comprehensive demo in examples/osas_walkthrough.ipynb to see all features in action.

Contributing

Contributions are welcome! Please see the main project repository for contribution guidelines.

License

MIT License - see LICENSE for details.

Support

• 📖 Documentation
• 🐛 Issue Tracker
• 💬 Discussions

⚖️ Legal Disclaimer

SAS® is a registered trademark of SAS Institute Inc. Open-SAS is not affiliated with, endorsed by, or sponsored by SAS Institute Inc.

This extension uses original, independently developed code to implement statistical functionality using SAS-like syntax for educational and analytical use. It is not a clone, derivative, or replacement for SAS software and does not use any proprietary code from SAS Institute.

Open-SAS is provided as-is, under an open-source license, for research and community contribution purposes.