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Extract, Transform, and Load Azure Management Data in Python

The CData Python Connector for Azure Management enables you to create ETL applications and pipelines for Azure Management 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 Management and the petl framework, you can build Azure Management-connected applications and pipelines for extracting, transforming, and loading Azure Management data. This article shows how to connect to Azure Management with the CData Python Connector and use petl and pandas to extract, transform, and load Azure Management data.

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

Connecting to Azure Management Data

Connecting to Azure Management 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 Data Management uses the OAuth 2 authentication standard. See the Getting Started section of the CData driver documentation for a guide.

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

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

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

Create a SQL Statement to Query Azure Management

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

sql = "SELECT DisplayName, AuthorizationSource FROM Subscriptions WHERE SubscriptionId = 'fadc4-4cdaf-fadc4-4cdaf'"

Extract, Transform, and Load the Azure Management Data

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

Loading Azure Management Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

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

Adding New Rows to Azure Management

table1 = [ ['DisplayName','AuthorizationSource'], ['NewDisplayName1','NewAuthorizationSource1'], ['NewDisplayName2','NewAuthorizationSource2'], ['NewDisplayName3','NewAuthorizationSource3'] ]

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

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

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

sql = "SELECT DisplayName, AuthorizationSource FROM Subscriptions WHERE SubscriptionId = 'fadc4-4cdaf-fadc4-4cdaf'"

table1 = etl.fromdb(cnxn,sql)

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

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

table3 = [ ['DisplayName','AuthorizationSource'], ['NewDisplayName1','NewAuthorizationSource1'], ['NewDisplayName2','NewAuthorizationSource2'], ['NewDisplayName3','NewAuthorizationSource3'] ]

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