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

Features

• SQL-92 access to local and remote QuickBooks company files
• Compatible with QuickBooks Premier, Professional, Enterprise, and Simple Start edition 2002+
• Supports the Canada, New Zealand, Australia, and UK editions from 2003+
• Connect to live QuickBooks Desktop data, for real-time data access
• Full support for data aggregation and complex JOINs in SQL queries
• Seamless integration with leading BI, reporting, and ETL tools and with custom applications

Specifications

• Python Database API (DB-API) Modules for QuickBooks with bi-directional access.
• Write SQL, get QuickBooks Desktop data. Access QuickBooks through standard Python Database Connectivity.
• Integration with popular Python tools like Pandas, SQLAlchemy, Dash & petl.
• Simple command-line based data exploration of QuickBooks Customers, Transactions, Invoices, Sales Receipts, Reports, and more!
• Full Unicode support for data, parameter, & metadata.

Connecting to QuickBooks with Python

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

Connecting to QuickBooks in Python

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

import cdata.quickbooks as mod
conn = mod.connect("User=user@domain.com; Password=password;")
 
#Create cursor and iterate over results
cur = conn.cursor()
cur.execute("SELECT * FROM Leads")
 
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 Quickbooks Data with pandas

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

engine = create_engine("quickbooks///Password=password&User=user")
 
df = pandas.read_sql("SELECT * FROM Leads", engine)
 
df.plot()
plt.show()

More Than Read-Only: Full Update/CRUD Support

QuickBooks 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 QuickBooks Connector as easily as interacting with a database table.

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.

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