Sage 300 Python Connector

Connecting to Sage 300 with Python

CData Python Connectors leverage the Database API (DB-API) interface to make it easy to work with Sage 300 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 Sage 300
• Query Sage 300 to retrieve or update data
• Connect your Sage 300 data with Python data tools.

Connecting to Sage 300 in Python

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

import cdata.sage 300 as mod
conn = mod.connect("User=user@domain.com; Password=password;")

#Create cursor and iterate over results
cur = conn.cursor()
cur.execute("SELECT * FROM Invoices")
 
rs = cur.fetchall()
 
for row in rs:
print(row)

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.

Visualize Sage 300 Data with pandas

The data-centric interfaces of the Sage 300 Python Connector make it easy to integrate with popular tools like pandas and SQLAlchemy to visualize data in real-time.

engine = create_engine("sage 300///Password=password&User=user")

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

df.plot()
plt.show()

More Than Read-Only: Full Update/CRUD Support

Sage 300 Connector goes beyond read-only functionality to deliver full support for Create, Read Update, and Delete operations (CRUD). Your end-users can interact with the data presented by the Sage 300 Connector as easily as interacting with a database table.