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Get the Report →How to use SQLAlchemy ORM to access WooCommerce Data in Python
Create Python applications and scripts that use SQLAlchemy Object-Relational Mappings of WooCommerce data.
The rich ecosystem of Python modules lets you get to work quickly and integrate your systems effectively. With the CData Python Connector for WooCommerce and the SQLAlchemy toolkit, you can build WooCommerce-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to WooCommerce data to query, update, delete, and insert WooCommerce data.
With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live WooCommerce data in Python. When you issue complex SQL queries from WooCommerce, the CData Connector pushes supported SQL operations, like filters and aggregations, directly to WooCommerce and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to WooCommerce Data
Connecting to WooCommerce 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.
WooCommerce supports the following authentication methods: one-legged OAuth1.0 Authentication and standard OAuth2.0 Authentication.
Connecting using one-legged OAuth 1.0 Authentication
Specify the following properties (NOTE: the below credentials are generated from WooCommerce settings page and should not be confused with the credentials generated by using WordPress OAuth2.0 plugin):
- ConsumerKey
- ConsumerSecret
Connecting using WordPress OAuth 2.0 Authentication
After having configured the plugin, you may connect to WooCommerce by providing the following connection properties:
In either case, you will need to set the Url property to the URL of the WooCommerce instance.
Follow the procedure below to install SQLAlchemy and start accessing WooCommerce through Python objects. Use the pip utility to install the SQLAlchemy toolkit and SQLAlchemy ORM package: Be sure to import the appropriate modules: You can now connect with a connection string. Use the create_engine function to create an Engine for working with WooCommerce data.
NOTE: Users should URL encode the any connection string properties that include special characters. For more information, refer to the SQL Alchemy documentation.
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 Orders table). Use the sqlalchemy.ext.declarative.declarative_base function and create a new class with some or all of the fields (columns) defined.
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. Alternatively, you can use the execute method with the appropriate table object. The code below works with an active session.
For examples of more complex querying, including JOINs, aggregations, limits, and more, refer to the Help documentation for the extension. To insert WooCommerce 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 WooCommerce.
To update WooCommerce 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 WooCommerce.
To delete WooCommerce 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).
Download a free, 30-day trial of the CData Python Connector for WooCommerce to start building Python apps and scripts with connectivity to WooCommerce data. Reach out to our Support Team if you have any questions.
Install Required Modules
pip install sqlalchemy
pip install sqlalchemy.orm
from sqlalchemy import create_engine, String, Column
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker
Model WooCommerce Data in Python
engine = create_engine("woocommerce:///?Url=https://example.com/& ConsumerKey=ck_ec52c76185c088ecaa3145287c8acba55a6f59ad& ConsumerSecret=cs_9fde14bf57126156701a7563fc87575713c355e5& InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
Declare a Mapping Class for WooCommerce Data
base = declarative_base()
class Orders(base):
__tablename__ = "Orders"
ParentId = Column(String,primary_key=True)
Total = Column(String)
...
Query WooCommerce Data
Using the query Method
engine = create_engine("woocommerce:///?Url=https://example.com/& ConsumerKey=ck_ec52c76185c088ecaa3145287c8acba55a6f59ad& ConsumerSecret=cs_9fde14bf57126156701a7563fc87575713c355e5& InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(Orders).filter_by(ParentId="3"):
print("ParentId: ", instance.ParentId)
print("Total: ", instance.Total)
print("---------")
Using the execute Method
Orders_table = Orders.metadata.tables["Orders"]
for instance in session.execute(Orders_table.select().where(Orders_table.c.ParentId == "3")):
print("ParentId: ", instance.ParentId)
print("Total: ", instance.Total)
print("---------")
Insert WooCommerce Data
new_rec = Orders(ParentId="placeholder", ParentId="3")
session.add(new_rec)
session.commit()
Update WooCommerce Data
updated_rec = session.query(Orders).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first()
updated_rec.ParentId = "3"
session.commit()
Delete WooCommerce Data
deleted_rec = session.query(Orders).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first()
session.delete(deleted_rec)
session.commit()
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