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Python Connector Libraries for Sage 200 Data Connectivity. Integrate Sage 200 with popular Python tools like Pandas, SQLAlchemy, Dash & petl.

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How to use SQLAlchemy ORM to access Sage 200 Data in Python


Create Python applications and scripts that use SQLAlchemy Object-Relational Mappings of Sage 200 data.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems effectively. With the CData Python Connector for Sage 200 and the SQLAlchemy toolkit, you can build Sage 200-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to Sage 200 data to query Sage 200 data.

With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Sage 200 data in Python. When you issue complex SQL queries from Sage 200, the CData Connector pushes supported SQL operations, like filters and aggregations, directly to Sage 200 and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Sage 200 Data

Connecting to Sage 200 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.

  • Schema: Determines which Sage 200 edition you are connecting to. Specify either StandardUK or ProfessionalUK.
  • Subscription Key: Provides access to the APIs that are used to establish a connection. You will first need to log into the Sage 200 API website and subscribe to the API edition that matches your account. You can do so here: https://developer.columbus.sage.com/docs/services/api/uk. Afterwards, the subscription key may be found in your profile after logging into Sage 200.

Follow the procedure below to install SQLAlchemy and start accessing Sage 200 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 Sage 200 Data in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with Sage 200 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("sage200:///?SubscriptionKey=12345&Schema=StandardUK&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Declare a Mapping Class for Sage 200 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 Banks 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 Banks(base): __tablename__ = "Banks" Id = Column(String,primary_key=True) Code = Column(String) ...

Query Sage 200 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("sage200:///?SubscriptionKey=12345&Schema=StandardUK&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt") factory = sessionmaker(bind=engine) session = factory() for instance in session.query(Banks).filter_by(Code="12345"): print("Id: ", instance.Id) print("Code: ", instance.Code) 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

Banks_table = Banks.metadata.tables["Banks"] for instance in session.execute(Banks_table.select().where(Banks_table.c.Code == "12345")): print("Id: ", instance.Id) print("Code: ", instance.Code) 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 Sage 200 to start building Python apps and scripts with connectivity to Sage 200 data. Reach out to our Support Team if you have any questions.