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

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How to use SQLAlchemy ORM to access Adobe Commerce Data in Python


Create Python applications and scripts that use SQLAlchemy Object-Relational Mappings of Adobe Commerce data.

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

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

Connecting to Adobe Commerce Data

Connecting to Adobe Commerce 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.

Adobe Commerce uses the OAuth 1 authentication standard. To connect to the Adobe Commerce REST API, you will need to obtain values for the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties by registering an app with your Adobe Commerce 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 Adobe Commerce system. The URL depends on whether you are using the Adobe Commerce REST API as a customer or administrator.

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

  • Administrator: To access Adobe Commerce 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 Adobe Commerce through Python objects.

Install Required Modules

Use the pip utility to install the SQLAlchemy toolkit and SQLAlchemy ORM package:

pip install sqlalchemy pip install sqlalchemy.orm

Be sure to import the appropriate modules:

from sqlalchemy import create_engine, String, Column from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import sessionmaker

Model Adobe Commerce Data in Python

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

NOTE: Users should URL encode the any connection string properties that include special characters. For more information, refer to the SQL Alchemy documentation.

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

Declare a Mapping Class for Adobe Commerce 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 Adobe Commerce 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("adobe commerce:///?OAuthClientId=MyConsumerKey&OAuthClientSecret=MyConsumerSecret&CallbackURL=http://127.0.0.1:33333&Url=https://myAdobe Commercehost.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 Adobe Commerce Data

To insert Adobe Commerce 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 Adobe Commerce.

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

Update Adobe Commerce Data

To update Adobe Commerce 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 Adobe Commerce.

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

Delete Adobe Commerce Data

To delete Adobe Commerce 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 CData Python Connector for Adobe Commerce to start building Python apps and scripts with connectivity to Adobe Commerce data. Reach out to our Support Team if you have any questions.