Use SQLAlchemy ORMs to Access Azure Management Data in Python

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Azure Management Python Connector

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

The CData Python Connector for Azure Management enables you to create Python applications and scripts that use SQLAlchemy Object-Relational Mappings of Azure Management data.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems effectively. With the CData Python Connector for Azure Management and the SQLAlchemy toolkit, you can build Azure Management-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to Azure Management data to query, update, delete, and insert 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 CData Connector 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.

Follow the procedure below to install SQLAlchemy and start accessing Azure Management through Python objects.

Install Required Modules

Use the pip utility to install the SQLAlchemy toolkit:

pip install sqlalchemy

Be sure to import the module with the following:

import sqlalchemy

Model Azure Management Data in Python

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

engine = create_engine("azuredatamanagement:///?InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Declare a Mapping Class for Azure Management Data

After establishing the connection, declare a mapping class for the table you wish to model in the ORM (in this article, we will model the Subscriptions table). Use the sqlalchemy.ext.declarative.declarative_base function and create a new class with some or all of the fields (columns) defined.

base = declarative_base()
class Subscriptions(base):
	__tablename__ = "Subscriptions"
	DisplayName = Column(String,primary_key=True)
	AuthorizationSource = Column(String)

Query Azure Management Data

With the mapping class prepared, you can use a session object to query the data source. After binding the Engine to the session, provide the mapping class to the session query method.

Using the query Method

engine = create_engine("azuredatamanagement:///?InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(Subscriptions).filter_by(SubscriptionId="fadc4-4cdaf-fadc4-4cdaf"):
	print("DisplayName: ", instance.DisplayName)
	print("AuthorizationSource: ", instance.AuthorizationSource)

Alternatively, you can use the execute method with the appropriate table object. The code below works with an active session.

Using the execute Method

Subscriptions_table = Subscriptions.metadata.tables["Subscriptions"]
for instance in session.execute( == "fadc4-4cdaf-fadc4-4cdaf")):
	print("DisplayName: ", instance.DisplayName)
	print("AuthorizationSource: ", instance.AuthorizationSource)

For examples of more complex querying, including JOINs, aggregations, limits, and more, refer to the Help documentation for the extension.

Insert Azure Management Data

To insert Azure Management data, define an instance of the mapped class and add it to the active session. Call the commit function on the session to push all added instances to Azure Management.

new_rec = Subscriptions(DisplayName="placeholder", SubscriptionId="fadc4-4cdaf-fadc4-4cdaf")

Update Azure Management Data

To update Azure Management data, fetch the desired record(s) with a filter query. Then, modify the values of the fields and call the commit function on the session to push the modified record to Azure Management.

updated_rec = session.query(Subscriptions).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first()
updated_rec.SubscriptionId = "fadc4-4cdaf-fadc4-4cdaf"

Delete Azure Management Data

To delete Azure Management data, fetch the desired record(s) with a filter query. Then delete the record with the active session and call the commit function on the session to perform the delete operation on the provided records (rows).

deleted_rec = session.query(Subscriptions).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first()

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.