Model Context Protocol (MCP) finally gives AI models a way to access the business data needed to make them really useful at work. CData MCP Servers have the depth and performance to make sure AI has access to all of the answers.
Try them now for free →
Using the CData ODBC Driver for SAS Data Sets in PyCharm
Connect to SAS Data Sets as an ODBC data source in PyCharm using the CData ODBC Driver for SAS Data Sets.
The CData ODBC Drivers can be used in any environment that supports loading an ODBC Driver. In this tutorial we will explore using the CData ODBC Driver for SAS Data Sets from within PyCharm. Included are steps for adding the CData ODBC Driver as a data source, as well as basic PyCharm code to query the data source and display results.
To begin, this tutorial will assume that you have already installed the CData ODBC Driver for SAS Data Sets as well as PyCharm.
Add Pyodbc to the Project
Follow the steps below to add the pyodbc module to your project.
- Click File -> Settings to open the project settings window.
- Click Project Interpreter from the Project: YourProjectName menu.
- To add pyodbc, click the + button and enter pyodbc.
- Click Install Package to install pyodbc.
Connect to SAS Data Sets
You can now connect with an ODBC connection string or a DSN. See the Getting Started section in the CData driver documentation for a guide to creating a DSN on your OS.
Set the following connection properties to connect to your SAS DataSet files:
Connecting to Local Files
- Set the Connection Type to "Local." Local files support SELECT, INSERT, and DELETE commands.
- Set the URI to a folder containing SAS files, e.g. C:\PATH\TO\FOLDER\.
Connecting to Cloud-Hosted SAS DataSet Files
While the driver is capable of pulling data from SAS DataSet files hosted on a variety of cloud data stores, INSERT, UPDATE, and DELETE are not supported outside of local files in this driver.
Set the Connection Type to the service hosting your SAS DataSet files. A unique prefix at the beginning of the URI connection property is used to identify the cloud data store and the remainder of the path is a relative path to the desired folder (one table per file) or single file (a single table). For more information, refer to the Getting Started section of the Help documentation.
Below is the syntax for a DSN:
[CData SASDataSets Source]
Driver = CData ODBC Driver for SAS Data Sets
Description = My Description
URI = C:/myfolder
Execute SQL to SAS Data Sets
Instantiate a Cursor and use the execute method of the Cursor class to execute any SQL statement.
import pyodbc
cnxn = pyodbc.connect('DRIVER={CData ODBC Driver for SASDataSets};URI = C:/myfolder;')
cursor = cnxn.cursor()
cursor.execute("SELECT name, borough FROM restaurants WHERE cuisine = 'American'")
rows = cursor.fetchall()
for row in rows:
print(row.name, row.borough)
After connecting to SAS Data Sets in PyCharm using the CData ODBC Driver, you will be able to build Python apps with access to SAS Data Sets data as if it were a standard database. If you have any questions, comments, or feedback regarding this tutorial, please contact us at support@cdata.com.
Ready to get started?
Download a free trial of the SAS Data Sets ODBC Driver to get started:
Download NowLearn more:
SAS Data Sets ODBC Driver
The SAS Data Sets ODBC Driver is a powerful tool that allows you to connect with live data from SAS Data Sets, directly from any applications that support ODBC connectivity.
Access SAS Data Sets data like you would a database - read, write, and update through a standard ODBC Driver interface.
