How to Visualize Adobe Experience Manager Data in Python with pandas

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, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Adobe Experience Manager-connected Python applications and scripts for visualizing Adobe Experience Manager data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Adobe Experience Manager data, execute queries, and visualize the results.

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.

Follow the procedure below to install the required modules and start accessing Adobe Experience Manager through Python objects.

Install Required Modules

Use the pip utility to install the pandas & Matplotlib modules and the SQLAlchemy toolkit:

pip install pandas
pip install matplotlib
pip install sqlalchemy

Be sure to import the module with the following:

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engine

Visualize Adobe Experience Manager Data in Python

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

engine = create_engine("adobeexperiencemanager:///?URL=https://author-p12345-e67890.adobeaemcloud.com/crx/server&User=admin&Password=admin")

Execute SQL to Adobe Experience Manager

Use the read_sql function from pandas to execute any SQL statement and store the resultset in a DataFrame.

df = pandas.read_sql("SELECT Id, Name FROM Content WHERE Name = 'example'", engine)

Visualize Adobe Experience Manager Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the Adobe Experience Manager data. The show method displays the chart in a new window.

df.plot(kind="bar", x="Id", y="Name")
plt.show()

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 pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin

engine = create_engine("adobeexperiencemanager:///?URL=https://author-p12345-e67890.adobeaemcloud.com/crx/server&User=admin&Password=admin")
df = pandas.read_sql("SELECT Id, Name FROM Content WHERE Name = 'example'", engine)

df.plot(kind="bar", x="Id", y="Name")
plt.show()