SAS2PY is the fastest and most accurate SAS code migration platform, converting SAS to Python, PySpark, SQL, Snowflake, Databricks, Redshift, Fabric and more with AI-driven validation.

SAS-to-Python Migration Automated Conversion: Quickly convert SAS code including macros, PROCs, and data steps into clean Python (or PySpark) scripts.

Our revolutionary tool streamlines your data transformation journey by effortlessly converting up to 95% of your legacy SAS code to modern PySpark, empowering you to leverage the robust capabilities of the Python ecosystem.

Switching from SAS to Python can be overwhelming for data analysts accustomed to SAS’s structured environment. This beginner’s guide will walk you through the basics of SAS-to-Python conversion, helping you build confidence and skills in Python.

SAS2PY is the fastest and most accurate SAS code migration platform, converting SAS to Python, PySpark, SQL, Snowflake, Databricks, Redshift, Fabric and more with AI-driven validation.

SAS2PY automates ETL migrations to Pandas by converting workflows into Pandas-based data transformation pipelines. It supports push (direct deployment to Pandas-based processing environments) and pull (API-driven extraction from storage like S3 or databases) models.

Convert SAS code to Python & SQL (Databricks, Snowpark, Redshift, Snowflake, Bigquery, Synapse) with 95% automation out-of-the-box! Start Converting to Python Work Smarter!

Syntax Conversion: Parse SAS, SQL, or ETL workflows and convert them into Snowflake SQL or Snowpark-compatible Python scripts. Schema Translation: Adapt legacy database schemas to Snowflake's multi-cluster, shared data architecture.

SAS2PY automates ETL migrations to Databricks by converting workflows into PySpark pipelines optimized for Delta Lake. It supports both push (direct deployment to Databricks) and pull (API-driven conversion from storage like S3) models.

Syntax Conversion: Parse SAS, SQL, or ETL workflows and convert them into SQL or Snowpark-compatible Python scripts. Schema Translation: Adapt legacy database schemas to naitive multi-cluster, shared data architecture.