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The rich ecosystem of Python modules lets you get to work quickly and integrate your systems effectively. With the CData Python Connector for SAP Ariba Source and the SQLAlchemy toolkit, you can build SAP Ariba Source-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to SAP Ariba Source data to query, update, delete, and insert SAP Ariba Source data.
With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live SAP Ariba Source data in Python. When you issue complex SQL queries from SAP Ariba Source, the CData Connector pushes supported SQL operations, like filters and aggregations, directly to SAP Ariba Source and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to SAP Ariba Source 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.
In order to connect with SAP Ariba Source, set the following:
If you are connecting to the Supplier Data API or the Contract API, additionally set the following:
If you're connecting to the Supplier API, set ProjectId to the Id of the sourcing project you want to retrieve data from.
After setting connection properties, you need to configure OAuth connectivity to authenticate.
For more information on creating an OAuth application, refer to the Help documentation.
After setting the following, you are ready to connect:
When you connect, the provider automatically completes the OAuth process:
Follow the procedure below to install SQLAlchemy and start accessing SAP Ariba Source through Python objects.
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
You can now connect with a connection string. Use the create_engine function to create an Engine for working with SAP Ariba Source 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("saparibasource:///?API=SupplierDataAPIWithPagination-V4&APIKey=wWVLn7WTAXrIRMAzZ6VnuEj7Ekot5jnU&Environment=SANDBOX&Realm=testRealm&AuthScheme=OAuthClient&InitiateOAuth=GETANDREFRESH")
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 Vendors 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 Vendors(base): __tablename__ = "Vendors" SMVendorID = Column(String,primary_key=True) Category = Column(String) ...
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.
engine = create_engine("saparibasource:///?API=SupplierDataAPIWithPagination-V4&APIKey=wWVLn7WTAXrIRMAzZ6VnuEj7Ekot5jnU&Environment=SANDBOX&Realm=testRealm&AuthScheme=OAuthClient&InitiateOAuth=GETANDREFRESH")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(Vendors).filter_by(Region="USA"):
print("SMVendorID: ", instance.SMVendorID)
print("Category: ", instance.Category)
print("---------")
Alternatively, you can use the execute method with the appropriate table object. The code below works with an active session.
Vendors_table = Vendors.metadata.tables["Vendors"]
for instance in session.execute(Vendors_table.select().where(Vendors_table.c.Region == "USA")):
print("SMVendorID: ", instance.SMVendorID)
print("Category: ", instance.Category)
print("---------")
For examples of more complex querying, including JOINs, aggregations, limits, and more, refer to the Help documentation for the extension.
To insert SAP Ariba Source 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 SAP Ariba Source.
new_rec = Vendors(SMVendorID="placeholder", Region="USA") session.add(new_rec) session.commit()
To update SAP Ariba Source 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 SAP Ariba Source.
updated_rec = session.query(Vendors).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first() updated_rec.Region = "USA" session.commit()
To delete SAP Ariba Source 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).
deleted_rec = session.query(Vendors).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first() session.delete(deleted_rec) session.commit()
Download a free, 30-day trial of the CData Python Connector for SAP Ariba Source to start building Python apps and scripts with connectivity to SAP Ariba Source data. Reach out to our Support Team if you have any questions.
Download a Community License of the SAP Ariba Source Connector to get started:
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