How to Build an ETL App for Oracle Eloqua Reporting Data in Python with CData

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

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

Connecting to Oracle Eloqua Reporting Data

Connecting to Oracle Eloqua Reporting 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.

Oracle Eloqua Reporting supports the following authentication methods:

• Basic authentication (User and Password)
• OAuth 2.0 code grant flow
• OAuth 2.0 password grant flow

Basic Authentication (User and Password)

To perform authentication with a user and password, specify these properties:

• AuthScheme: Basic.
• Company: The company name associated with your Oracle Eloqua Reporting account.
• User: Your login account name.
• Password: Your login password.

OAuth Authentication (Code Grant Flow)

To authenticate with the OAuth code grant flow, you must set AuthScheme to OAuth and create a custom OAuth application. For information about how to create a custom OAuth application, see the Help documentation.

Then set the following properties:

• InitiateOAuth: GETANDREFRESH. Used to automatically get and refresh the OAuthAccessToken.
• OAuthClientId: The client Id assigned when you registered your application.
• OAuthClientSecret: The client secret that was assigned when you registered your application.
• CallbackURL: The redirect URI that was defined when you registered your application.

When you connect, the driver opens Oracle Eloqua Reporting's OAuth endpoint in your default browser. Log in and grant permissions to the application. When the access token expires, the driver refreshes it automatically.

OAuth Authentication (Password Grant Flow)

With the OAuth password grant flow, you can use your OAuth application's credentials alongside your user credentials to authenticate without the need to grant permission manually via a browser prompt. You must create an OAuth app (see the Help documentation) to use this authentication method.

Set the following properties:

• AuthScheme: OAuthPassword
• Company: The company's unique identifier.
• User: Your login account name.
• Password: Your login password.
• OAuthClientId: The client Id assigned when you registered your custom OAuth application.
• OAuthClientSecret: The client secret assigned when you registered your custom OAuth application.

After installing the CData Oracle Eloqua Reporting Connector, follow the procedure below to install the other required modules and start accessing Oracle Eloqua Reporting 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 Oracle Eloqua Reporting 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.oracleeloquareporting as mod

You can now connect with a connection string. Use the connect function for the CData Oracle Eloqua Reporting Connector to create a connection for working with Oracle Eloqua Reporting data.

cnxn = mod.connect("AuthScheme=Basic;User=user;Password=password;Company=MyCompany;")

Create a SQL Statement to Query Oracle Eloqua Reporting

Use SQL to create a statement for querying Oracle Eloqua Reporting. In this article, we read data from the entity.

sql = "SELECT ,  FROM  WHERE  = ''"

Extract, Transform, and Load the Oracle Eloqua Reporting Data

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

Loading Oracle Eloqua Reporting Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

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

With the CData Python Connector for Oracle Eloqua Reporting, you can work with Oracle Eloqua Reporting 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 CData Python Connector for Oracle Eloqua Reporting to start building Python apps and scripts with connectivity to Oracle Eloqua Reporting 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.oracleeloquareporting as mod

cnxn = mod.connect("AuthScheme=Basic;User=user;Password=password;Company=MyCompany;")

sql = "SELECT ,  FROM  WHERE  = ''"

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

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