Use SQLAlchemy ORMs to Access DB2 Data in Python

Ready to get started?

Download for a free trial:

Download Now

Learn more:

IBM DB2 Python Connector

Python Connector Libraries for IBM DB2 Data Connectivity. Integrate IBM DB2 with popular Python tools like Pandas, SQLAlchemy, Dash & petl.

The CData Python Connector for DB2 enables you to create Python applications and scripts that use SQLAlchemy Object-Relational Mappings of DB2 data.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems effectively. With the CData Python Connector for DB2 and the SQLAlchemy toolkit, you can build DB2-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to DB2 data to query, update, delete, and insert DB2 data.

With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live DB2 data in Python. When you issue complex SQL queries from DB2, the CData Connector pushes supported SQL operations, like filters and aggregations, directly to DB2 and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to DB2 Data

Connecting to DB2 data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

Follow the procedure below to install SQLAlchemy and start accessing DB2 through Python objects.

Install Required Modules

Use the pip utility to install the SQLAlchemy toolkit:

pip install sqlalchemy

Be sure to import the module with the following:

import sqlalchemy

Model DB2 Data in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with DB2 data.

engine = create_engine("db2:///?Server=")

Declare a Mapping Class for DB2 Data

After establishing the connection, declare a mapping class for the table you wish to model in the ORM (in this article, we will model the Orders table). Use the sqlalchemy.ext.declarative.declarative_base function and create a new class with some or all of the fields (columns) defined.

base = declarative_base()
class Orders(base):
	__tablename__ = "Orders"
	OrderName = Column(String,primary_key=True)
	Freight = Column(String)

Query DB2 Data

With the mapping class prepared, you can use a session object to query the data source. After binding the Engine to the session, provide the mapping class to the session query method.

Using the query Method

engine = create_engine("db2:///?Server=")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(Orders).filter_by(ShipCity="New York"):
	print("OrderName: ", instance.OrderName)
	print("Freight: ", instance.Freight)

Alternatively, you can use the execute method with the appropriate table object. The code below works with an active session.

Using the execute Method

Orders_table = Orders.metadata.tables["Orders"]
for instance in session.execute( == "New York")):
	print("OrderName: ", instance.OrderName)
	print("Freight: ", instance.Freight)

For examples of more complex querying, including JOINs, aggregations, limits, and more, refer to the Help documentation for the extension.

Insert DB2 Data

To insert DB2 data, define an instance of the mapped class and add it to the active session. Call the commit function on the session to push all added instances to DB2.

new_rec = Orders(OrderName="placeholder", ShipCity="New York")

Update DB2 Data

To update DB2 data, fetch the desired record(s) with a filter query. Then, modify the values of the fields and call the commit function on the session to push the modified record to DB2.

updated_rec = session.query(Orders).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first()
updated_rec.ShipCity = "New York"

Delete DB2 Data

To delete DB2 data, fetch the desired record(s) with a filter query. Then delete the record with the active session and call the commit function on the session to perform the delete operation on the provided records (rows).

deleted_rec = session.query(Orders).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first()

Free Trial & More Information

Download a free, 30-day trial of the DB2 Python Connector to start building Python apps and scripts with connectivity to DB2 data. Reach out to our Support Team if you have any questions.