How to use SQLAlchemy ORM to access Suadeo Data in Python

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

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

Connecting to Suadeo Data

Connecting to Suadeo 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.

The driver uses the OAuth 2.0 Resource Owner Password Credentials (ROPC) grant to authenticate to Suadeo. Authentication occurs directly using your credentials; there is no browser-based authorization flow or refresh token.

Set the following connection properties:

• URL: The base URL of your Suadeo instance.
• User: Your Suadeo username.
• Password: Your Suadeo password.
• AuthenticationName: The name identifier for the authentication configuration in your Suadeo instance. Different authentication names can be configured for different environments or use cases.

When you connect, the driver sends your credentials to the Suadeo OAuth token endpoint, receives an access token, and uses it for all subsequent requests. A new access token is obtained automatically when needed during the session.

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

You can now connect with a connection string. Use the create_engine function to create an Engine for working with Suadeo 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("suadeo:///?URL=https://mysuadeoinstance&User=username&Password=password&AuthenticationName=your_auth_name")

Declare a Mapping Class for Suadeo 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 Customers 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 Customers(base):
	__tablename__ = "Customers"
	Id = Column(String,primary_key=True)
	Name = Column(String)
	...

Query Suadeo 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("suadeo:///?URL=https://mysuadeoinstance&User=username&Password=password&AuthenticationName=your_auth_name")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(Customers).filter_by(Status="Active"):
	print("Id: ", instance.Id)
	print("Name: ", instance.Name)
	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

Customers_table = Customers.metadata.tables["Customers"]
for instance in session.execute(Customers_table.select().where(Customers_table.c.Status == "Active")):
	print("Id: ", instance.Id)
	print("Name: ", instance.Name)
	print("---------")

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

Free Trial & More Information

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