How to Build an ETL App for Adobe Experience Manager 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 Adobe Experience Manager and the petl framework, you can build Adobe Experience Manager-connected applications and pipelines for extracting, transforming, and loading Adobe Experience Manager data. This article shows how to connect to Adobe Experience Manager with the CData Python Connector and use petl and pandas to extract, transform, and load Adobe Experience Manager data.

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

Connecting to Adobe Experience Manager Data

Connecting to Adobe Experience 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.

The driver connects to Adobe Experience Manager (AEM) instances that expose the JCR repository over WebDAV. It supports both on-premises AEM and AEM as a Cloud Service deployments.

To establish a connection, set the following properties:

• URL: The WebDAV-enabled JCR server URL.
  • AEM as a Cloud Service: https://author-pXXXXX-eXXXXX.adobeaemcloud.com/crx/server
  • Local development: http://localhost:4502/crx/server
• User: Your AEM username.
• Password: Your AEM password.

Note: Tables are dynamically generated based on the JCR repository structure. Ensure that the configured user has sufficient permissions to access the required content paths in the AEM repository.

After installing the CData Adobe Experience Manager Connector, follow the procedure below to install the other required modules and start accessing Adobe Experience 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 Adobe Experience 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.adobeexperiencemanager as mod

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

cnxn = mod.connect("URL=https://author-p12345-e67890.adobeaemcloud.com/crx/server;User=admin;Password=admin;")

Create a SQL Statement to Query Adobe Experience Manager

Use SQL to create a statement for querying Adobe Experience Manager. In this article, we read data from the Content entity.

sql = "SELECT Id, Name FROM Content WHERE Name = 'example'"

Extract, Transform, and Load the Adobe Experience Manager Data

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

Loading Adobe Experience Manager Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

With the CData Python Connector for Adobe Experience Manager, you can work with Adobe Experience 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 CData Python Connector for Adobe Experience Manager to start building Python apps and scripts with connectivity to Adobe Experience 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.adobeexperiencemanager as mod

cnxn = mod.connect("URL=https://author-p12345-e67890.adobeaemcloud.com/crx/server;User=admin;Password=admin;")

sql = "SELECT Id, Name FROM Content WHERE Name = 'example'"

table1 = etl.fromdb(cnxn,sql)

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

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