How to Build an ETL App for Azure Active Directory Data in Python with CData



Create ETL applications and real-time data pipelines for Azure Active Directory 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 Azure Active Directory and the petl framework, you can build Azure Active Directory-connected applications and pipelines for extracting, transforming, and loading Azure Active Directory data. This article shows how to connect to Azure Active Directory with the CData Python Connector and use petl and pandas to extract, transform, and load Azure Active Directory data.

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

Connecting to Azure Active Directory Data

Connecting to Azure Active Directory 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.

Azure Active Directory uses the OAuth authentication standard. To authenticate using OAuth, you will need to create an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties. See the OAuth section in the Help documentation for an authentication guide.

After installing the CData Azure Active Directory Connector, follow the procedure below to install the other required modules and start accessing Azure Active Directory 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 Azure Active Directory 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.azuread as mod

You can now connect with a connection string. Use the connect function for the CData Azure Active Directory Connector to create a connection for working with Azure Active Directory data.

cnxn = mod.connect("OAuthClientId=MyApplicationId;OAuthClientSecret=MySecretKey;CallbackURL=http://localhost:33333;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Create a SQL Statement to Query Azure Active Directory

Use SQL to create a statement for querying Azure Active Directory. In this article, we read data from the Domains entity.

sql = "SELECT id, availabilityStatus FROM Domains WHERE isVerified = 'TRUE'"

Extract, Transform, and Load the Azure Active Directory Data

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

Loading Azure Active Directory Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

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

Adding New Rows to Azure Active Directory

table1 = [ ['id','availabilityStatus'], ['Newid1','NewavailabilityStatus1'], ['Newid2','NewavailabilityStatus2'], ['Newid3','NewavailabilityStatus3'] ]

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

With the CData Python Connector for Azure Active Directory, you can work with Azure Active Directory 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 Azure Active Directory to start building Python apps and scripts with connectivity to Azure Active Directory 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.azuread as mod

cnxn = mod.connect("OAuthClientId=MyApplicationId;OAuthClientSecret=MySecretKey;CallbackURL=http://localhost:33333;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

sql = "SELECT id, availabilityStatus FROM Domains WHERE isVerified = 'TRUE'"

table1 = etl.fromdb(cnxn,sql)

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

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

table3 = [ ['id','availabilityStatus'], ['Newid1','NewavailabilityStatus1'], ['Newid2','NewavailabilityStatus2'], ['Newid3','NewavailabilityStatus3'] ]

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

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Python Connector Libraries for Azure Active Directory Data Connectivity. Integrate Azure Active Directory with popular Python tools like Pandas, SQLAlchemy, Dash & petl.