Use SQLAlchemy ORMs to Access Magento Data in Python

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Magento Python Connector

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



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

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

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

Connecting to Magento Data

Connecting to Magento 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.

Magento uses the OAuth 1 authentication standard. To connect to the Magento REST API, you will need to obtain values for the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties by registering an app with your Magento system. See the "Getting Started" section in the help documentation for a guide to obtaining the OAuth values and connecting.

You will also need to provide the URL to your Magento system. The URL depends on whether you are using the Magento REST API as a customer or administrator.

  • Customer: To use Magento as a customer, make sure you have created a customer account in the Magento homepage. To do so, click Account -> Register. You can then set the URL connection property to the endpoint of your Magento system.

  • Administrator: To access Magento as an administrator, set CustomAdminPath instead. This value can be obtained in the Advanced settings in the Admin menu, which can be accessed by selecting System -> Configuration -> Advanced -> Admin -> Admin Base URL.

    If the Use Custom Admin Path setting on this page is set to YES, the value is inside the Custom Admin Path text box; otherwise, set the CustomAdminPath connection property to the default value, which is "admin".

Follow the procedure below to install SQLAlchemy and start accessing Magento 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 Magento Data in Python

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

engine = create_engine("magento:///?OAuthClientId=MyConsumerKey&OAuthClientSecret=MyConsumerSecret&CallbackURL=http://127.0.0.1:33333&Url=https://mymagentohost.com&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Declare a Mapping Class for Magento 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 Products 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 Products(base):
	__tablename__ = "Products"
	Name = Column(String,primary_key=True)
	Price = Column(String)
	...

Query Magento 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("magento:///?OAuthClientId=MyConsumerKey&OAuthClientSecret=MyConsumerSecret&CallbackURL=http://127.0.0.1:33333&Url=https://mymagentohost.com&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(Products).filter_by(Style="High Tech"):
	print("Name: ", instance.Name)
	print("Price: ", instance.Price)
	print("---------")

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

Using the execute Method

Products_table = Products.metadata.tables["Products"]
for instance in session.execute(Products_table.select().where(Products_table.c.Style == "High Tech")):
	print("Name: ", instance.Name)
	print("Price: ", instance.Price)
	print("---------")

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

Insert Magento Data

To insert Magento 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 Magento.

new_rec = Products(Name="placeholder", Style="High Tech")
session.add(new_rec)
session.commit()

Update Magento Data

To update Magento 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 Magento.

updated_rec = session.query(Products).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first()
updated_rec.Style = "High Tech"
session.commit()

Delete Magento Data

To delete Magento 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(Products).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first()
session.delete(deleted_rec)
session.commit()

Free Trial & More Information

Download a free, 30-day trial of the Magento Python Connector to start building Python apps and scripts with connectivity to Magento data. Reach out to our Support Team if you have any questions.