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Python

QuickBooks Online Python Connector

Read, write, and update QuickBooks Online with Python

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

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CData Drivers now work with AI Coding tools

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

Features

Powerful metadata querying enables SQL-like access to non-database sources
Push down query optimization pushes SQL operations down to the server whenever possible, increasing performance
Client-side query execution engine, supports SQL-92 operations that are not available server-side
Connect to live QuickBooks Online data, for real-time data access with the QuickBooks Online ADO.NET Provider
Full support for data aggregation and complex JOINs in SQL queries
Secure connectivity through modern cryptography, including TLS 1.2, SHA-256, ECC, etc.
Seamless integration with leading BI, reporting, and ETL tools and with custom applications via the QuickBooks Online Connector.

Specifications

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

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


Connecting to QuickBooks Online with Python

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


Connecting to QuickBooks Online 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.quickbooksonline as mod
conn = mod.connect("[email protected]; Password=password;")

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

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

df.plot()
plt.show()

Visualize QuickBooks Online Data with pandas

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

More than read-only: full update/CRUD support

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

AI-assisted development with CData CLI

Build QuickBooks Online integrations faster with AI that understands your schema

Schema-aware AI

CData CLI gives AI coding tools access to your QuickBooks Online 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 QuickBooks Online.

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