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

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How to use SQLAlchemy ORM to access SAP ByDesign Data in Python


Create Python applications and scripts that use SQLAlchemy Object-Relational Mappings of SAP ByDesign data.

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

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

Connecting to SAP ByDesign Data

Connecting to SAP ByDesign 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.

Set the following connection properties to connect to SAP ByDesign.

  • Url: Set this to the Url of your SAP ByDesign site. For example, https://test.sapbydesign.com
  • User: Set this to the username of your account.
  • Password: Set this to the password of your account.
  • CustomService or AnalyticsService: Only one of these must be specified. If you have a custom service you want to retrieve data from, specify CustomService. If you want to retrieve the reports of a analytical service, specify AnalyticsService.
    If neither is specified, 'cc_home_analytics.svc' will used as a default for the AnalyticsService property. If you are not sure what service to specify, you can always query the Services view to list available services.

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

You can now connect with a connection string. Use the create_engine function to create an Engine for working with SAP ByDesign 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("sapbydesign:///?URL=https://my999999.sapbydesign.com&User=username&Password=password&CustomService=servicename")

Declare a Mapping Class for SAP ByDesign 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 [Inventory Balance] 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 [Inventory Balance](base): __tablename__ = "[Inventory Balance]" ID = Column(String,primary_key=True) ProductCategoryID = Column(String) ...

Query SAP ByDesign 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("sapbydesign:///?URL=https://my999999.sapbydesign.com&User=username&Password=password&CustomService=servicename") factory = sessionmaker(bind=engine) session = factory() for instance in session.query([Inventory Balance]).filter_by(ProductCategoryID="1234567"): print("ID: ", instance.ID) print("ProductCategoryID: ", instance.ProductCategoryID) 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

[Inventory Balance]_table = [Inventory Balance].metadata.tables["[Inventory Balance]"] for instance in session.execute([Inventory Balance]_table.select().where([Inventory Balance]_table.c.ProductCategoryID == "1234567")): print("ID: ", instance.ID) print("ProductCategoryID: ", instance.ProductCategoryID) 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 SAP ByDesign to start building Python apps and scripts with connectivity to SAP ByDesign data. Reach out to our Support Team if you have any questions.