Use SQLAlchemy ORMs to Access SAP Data in Python

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SAP ERP Python Connector

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

The CData Python Connector for SAP enables you to create Python applications and scripts that use SQLAlchemy Object-Relational Mappings of SAP 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 and the SQLAlchemy toolkit, you can build SAP-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to SAP data to query SAP data.

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

Connecting to SAP Data

Connecting to SAP 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.

You can connect to SAP systems using either librfc32.dll, librfc32u.dll, NetWeaver, or Web Services (SOAP). Set the ConnectionType connection property to CLASSIC (librfc32.dll), CLASSIC_UNICODE (librfc32u.dll), NETWEAVER, or SOAP.

If you are using the SOAP interface, set the Client, RFCUrl, SystemNumber, User, and Password properties, under the Authentication section.

Otherwise, set Host, User, Password, Client, and SystemNumber.

Note: We do not distribute the librfc32.dll or other SAP assemblies. You must find them from your SAP installation and install them on your machine.

For more information, see this guide on obtaining the connection properties needed to connect to any SAP system.

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

You can now connect with a connection string. Use the create_engine function to create an Engine for working with SAP 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("saperp:///? Number=09&ConnectionType=Classic&Location=C:/mysapschemafolder")

Declare a Mapping Class for SAP 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 MARA 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 MARA(base): __tablename__ = "MARA" MANDT = Column(String,primary_key=True) MBRSH = Column(String) ...

Query SAP 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("saperp:///? Number=09&ConnectionType=Classic&Location=C:/mysapschemafolder") factory = sessionmaker(bind=engine) session = factory() for instance in session.query(MARA).filter_by(ERNAM="BEHRMANN"): print("MANDT: ", instance.MANDT) print("MBRSH: ", instance.MBRSH) 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

MARA_table = MARA.metadata.tables["MARA"] for instance in session.execute( == "BEHRMANN")): print("MANDT: ", instance.MANDT) print("MBRSH: ", instance.MBRSH) 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 SAP Python Connector to start building Python apps and scripts with connectivity to SAP data. Reach out to our Support Team if you have any questions.