Use SQLAlchemy ORMs to Access Google Campaign Manager Data in Python

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DoubleClick Python Connector

Python Connector Libraries for DoubleClick Campaign Manager Data Connectivity. Integrate DoubleClick Campaign Manager with popular Python tools like Pandas, SQLAlchemy, Dash & petl.

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

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

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

Connecting to Google Campaign Manager Data

Connecting to Google Campaign Manager 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.

Google Campaign Manager uses the OAuth authentication standard. The data provider facilitates OAuth in various ways as described below. The following OAuth flow requires the authenticating user to interact with DoubleClick Campaign Manager, using the browser. You can also use a service account to authenticate.

For authentication guides, see the Getting Started section of the data provider help documentation.

Follow the procedure below to install SQLAlchemy and start accessing Google Campaign Manager 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 Google Campaign Manager Data in Python

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

engine = create_engine("googlecm:///?UserProfileID=MyUserProfileID&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Declare a Mapping Class for Google Campaign Manager 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 CampaignPerformance 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 CampaignPerformance(base):
	__tablename__ = "CampaignPerformance"
	Clicks = Column(String,primary_key=True)
	Device = Column(String)

Query Google Campaign Manager 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("googlecm:///?UserProfileID=MyUserProfileID&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(CampaignPerformance).filter_by(Device="Mobile devices with full browsers"):
	print("Clicks: ", instance.Clicks)
	print("Device: ", instance.Device)

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

Using the execute Method

CampaignPerformance_table = CampaignPerformance.metadata.tables["CampaignPerformance"]
for instance in session.execute( == "Mobile devices with full browsers")):
	print("Clicks: ", instance.Clicks)
	print("Device: ", instance.Device)

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

Insert Google Campaign Manager Data

To insert Google Campaign Manager 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 Google Campaign Manager.

new_rec = CampaignPerformance(Clicks="placeholder", Device="Mobile devices with full browsers")

Update Google Campaign Manager Data

To update Google Campaign Manager 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 Google Campaign Manager.

updated_rec = session.query(CampaignPerformance).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first()
updated_rec.Device = "Mobile devices with full browsers"

Delete Google Campaign Manager Data

To delete Google Campaign Manager 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(CampaignPerformance).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first()

Free Trial & More Information

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