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Python

IBM DB2 Python Connector

Read, write, and update DB2 with Python

Easily connect Python-based data access, visualization, ORM, ETL, AI/ML, and custom apps with IBM DB2!

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CData Drivers now work with AI Coding tools

Python Connector Libraries for DB2 Data Connectivity. Integrate DB2 with popular Python tools like Pandas, SQLAlchemy, Dash & petl. Easy-to-use Python Database API (DB-API) Modules connect DB2 data with Python and any Python-based applications.

Features

Support for LUW and AS/400 instances of DB2. For interest in z/OS support, please contact our support team at [email protected].
Connect to live IBM DB2 data, for real-time data access with the IBM DB2 Python Connectors
Full support for data aggregation and complex JOINs in SQL queries
Seamless integration with leading BI, reporting, and ETL tools and with custom applications via the DB2 Connector.

Specifications

Python Database API (DB-API) Modules for DB2 with bi-directional access.
Write SQL, get IBM DB2 data. Access DB2 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 IBM DB2

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


Connecting to DB2 with Python

CData Python Connectors leverage the Database API (DB-API) interface to make it easy to work with DB2 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 DB2
  • Query DB2 to retrieve or update data
  • Connect your DB2 data with Python data tools.


Connecting to DB2 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.db2 as mod
conn = mod.connect("[email protected]; Password=password;")

#Create cursor and iterate over results
cur = conn.cursor()
cur.execute("SELECT * FROM DB2Table")
	
rs = cur.fetchall()
	
for row in rs:
print(row)
		
engine = create_engine("db2///Password=password&User=user")

df = pandas.read_sql("SELECT * FROM DB2Table", engine)

df.plot()
plt.show()

Visualize DB2 Data with pandas

The data-centric interfaces of the DB2 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

DB2 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 DB2 Connector as easily as interacting with a database table.

AI-assisted development with CData CLI

Build DB2 integrations faster with AI that understands your schema

Schema-aware AI

CData CLI gives AI coding tools access to your DB2 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 DB2.

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