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Python

SASxpt Python Connector

SQL-based access to SAS xpt from Python

Easily connect Python-based data access, visualization, ORM, ETL, AI/ML, and custom apps with SAS XPORT!

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Python Connector Libraries for SAS xpt Data Connectivity. Integrate SAS xpt with popular Python tools like Pandas, SQLAlchemy, Dash & petl. Easy-to-use Python Database API (DB-API) Modules connect SAS xpt data with Python and any Python-based applications.

Features

Connect to live SAS XPORT data, for real-time data access with the SAS XPORT JDBC Driver
Full support for data aggregation and complex JOINs in SQL queries
Generate table schema automatically based on existing SAS XPORT data or manually for greater control of the content you need
Seamless integration with leading BI, reporting, and ETL tools and with custom applications via the SAS xpt Connector.

Specifications

Python Database API (DB-API) Modules for SAS xpt .
Write SQL, get SAS XPORT data. Access SAS xpt through standard Python Database Connectivity.
Integration with popular Python tools like Pandas, SQLAlchemy, Dash & petl.
Full Unicode support for data, parameter, & metadata.

CData Python connectors in action!

Watch the video overview for a first hand-look at the powerful data integration capabilities included in the CData Python Connectors.

Watch the Python Connector Video Overview

Python connectivity with SAS XPORT

Full-featured and consistent SQL access to any supported data source through Python


Connecting to SAS xpt with Python

CData Python Connectors leverage the Database API (DB-API) interface to make it easy to work with SAS xpt from a wide range of standard Python data tools. Connecting to and working with your data in Python follows a basic pattern, regardless of data source:

  • Configure the connection properties to SAS xpt
  • Query SAS xpt to retrieve or update data
  • Connect your SAS xpt data with Python data tools.


Connecting to SAS xpt in Python

To connect to your data from Python, import the extension and create a connection:

Once you import the extension, you can work with all of your enterprise data using the python modules and toolkits that you already know and love, quickly building apps that help you drive business.

import cdata.sasxpt as mod
conn = mod.connect("[email protected]; Password=password;")

#Create cursor and iterate over results
cur = conn.cursor()
cur.execute("SELECT * FROM SASxptData")
	
rs = cur.fetchall()
	
for row in rs:
print(row)
		
engine = create_engine("sasxpt///Password=password&User=user")

df = pandas.read_sql("SELECT * FROM SASxptData", engine)

df.plot()
plt.show()

Visualize SAS xpt Data with pandas

The data-centric interfaces of the SAS xpt Python Connector make it easy to integrate with popular tools like pandas and SQLAlchemy to visualize data in real-time.

AI-assisted development with CData CLI

Build SAS xpt integrations faster with AI that understands your schema

Schema-aware AI

CData CLI gives AI coding tools access to your SAS xpt schema. No more guessing table names or column types—AI sees the same metadata in your Python Connectors.

Your AI Knows SQL

How to find table names, column names, and how to generate SQL syntax are things that AI knows well from millions of training data. No need for customization, no hallucinations. Your AI acts like a domain specialist to SAS xpt.

More Accurate, More Token-Efficient

With CData CLI's queryable schema detection and highly efficient queries with filters, aggregation, joins with correct pushdown, your AI will achieve more accuracy with less token usage.

Supported AI Coding Tools
Download CData CLI