Extract, Transform, and Load 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 ETL applications and pipelines for Google Campaign Manager data in Python with petl.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Google Campaign Manager and the petl framework, you can build Google Campaign Manager-connected applications and pipelines for extracting, transforming, and loading Google Campaign Manager data. This article shows how to connect to Google Campaign Manager with the CData Python Connector and use petl and pandas to extract, transform, and load 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 driver 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.

After installing the CData Google Campaign Manager Connector, follow the procedure below to install the other required modules and start accessing Google Campaign Manager through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install petl
pip install pandas

Build an ETL App for Google Campaign Manager Data in Python

Once the required modules and frameworks are installed, we are ready to build our ETL app. Code snippets follow, but the full source code is available at the end of the article.

First, be sure to import the modules (including the CData Connector) with the following:

import petl as etl
import pandas as pd
import cdata.googlecm as mod

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

cnxn = mod.connect("UserProfileID=MyUserProfileID;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Create a SQL Statement to Query Google Campaign Manager

Use SQL to create a statement for querying Google Campaign Manager. In this article, we read data from the CampaignPerformance entity.

sql = "SELECT Clicks, Device FROM CampaignPerformance WHERE Device = 'Mobile devices with full browsers'"

Extract, Transform, and Load the Google Campaign Manager Data

With the query results stored in a DataFrame, we can use petl to extract, transform, and load the Google Campaign Manager data. In this example, we extract Google Campaign Manager data, sort the data by the Device column, and load the data into a CSV file.

Loading Google Campaign Manager Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'Device')

etl.tocsv(table2,'campaignperformance_data.csv')

In the following example, we add new rows to the CampaignPerformance table.

Adding New Rows to Google Campaign Manager

table1 = [ ['Clicks','Device'], ['NewClicks1','NewDevice1'], ['NewClicks2','NewDevice2'], ['NewClicks3','NewDevice3'] ]

etl.appenddb(table1, cnxn, 'CampaignPerformance')

With the CData Python Connector for Google Campaign Manager, you can work with Google Campaign Manager data just like you would with any database, including direct access to data in ETL packages like petl.

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.



Full Source Code


import petl as etl
import pandas as pd
import cdata.googlecm as mod

cnxn = mod.connect("UserProfileID=MyUserProfileID;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

sql = "SELECT Clicks, Device FROM CampaignPerformance WHERE Device = 'Mobile devices with full browsers'"

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'Device')

etl.tocsv(table2,'campaignperformance_data.csv')

table3 = [ ['Clicks','Device'], ['NewClicks1','NewDevice1'], ['NewClicks2','NewDevice2'], ['NewClicks3','NewDevice3'] ]

etl.appenddb(table3, cnxn, 'CampaignPerformance')