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

Create Python applications and scripts that use SQLAlchemy Object-Relational Mappings of SAP SuccessFactors 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 SuccessFactors and the SQLAlchemy toolkit, you can build SAP SuccessFactors-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to SAP SuccessFactors data to query, update, delete, and insert SAP SuccessFactors data.

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

Connecting to SAP SuccessFactors Data

Connecting to SAP SuccessFactors 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 authenticate to SAP Success Factors using Basic authentication or OAuth with SAML assertion.

Basic Authentication

You must provide values for the following properties to successfully authenticate to SAP Success Factors. Note that the provider will reuse the session opened by SAP Success Factors using cookies. Which means that your credentials will be used only on the first request to open the session. After that, cookies returned from SAP Success Factors will be used for authentication.

Url: set this to the URL of the server hosting Success Factors. Some of the servers are listed in the SAP support documentation (external link).
User: set this to the username of your account.
Password: set this to the password of your account.
CompanyId: set this to the unique identifier of your company.

OAuth Authentication

You must provide values for the following properties, which will be used to get the access token.

Url: set this to the URL of the server hosting Success Factors. Some of the servers are listed in the SAP support documentation (external link).
User: set this to the username of your account.
CompanyId: set this to the unique identifier of your company.
OAuthClientId: set this to the API Key that was generated in API Center.
OAuthClientSecret: the X.509 private key used to sign SAML assertion. The private key can be found in the certificate you downloaded in Registering your OAuth Client Application.
InitiateOAuth: set this to GETANDREFRESH.

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

You can now connect with a connection string. Use the create_engine function to create an Engine for working with SAP SuccessFactors 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("sapsuccessfactors:///?User=username&Password=password&CompanyId=CompanyId&Url=https://api4.successfactors.com")

Declare a Mapping Class for SAP SuccessFactors 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 ExtAddressInfo 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 ExtAddressInfo(base):
	__tablename__ = "ExtAddressInfo"
	address1 = Column(String,primary_key=True)
	zipCode = Column(String)
	...

Query SAP SuccessFactors 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("sapsuccessfactors:///?User=username&Password=password&CompanyId=CompanyId&Url=https://api4.successfactors.com")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(ExtAddressInfo).filter_by(city="Springfield"):
	print("address1: ", instance.address1)
	print("zipCode: ", instance.zipCode)
	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


ExtAddressInfo_table = ExtAddressInfo.metadata.tables["ExtAddressInfo"]
for instance in session.execute(ExtAddressInfo_table.select().where(ExtAddressInfo_table.c.city == "Springfield")):
	print("address1: ", instance.address1)
	print("zipCode: ", instance.zipCode)
	print("---------")

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

Insert SAP SuccessFactors Data

To insert SAP SuccessFactors 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 SuccessFactors.


new_rec = ExtAddressInfo(address1="placeholder", city="Springfield")
session.add(new_rec)
session.commit()

Update SAP SuccessFactors Data

To update SAP SuccessFactors 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 SuccessFactors.


updated_rec = session.query(ExtAddressInfo).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first()
updated_rec.city = "Springfield"
session.commit()

Delete SAP SuccessFactors Data

To delete SAP SuccessFactors 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(ExtAddressInfo).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first()
session.delete(deleted_rec)
session.commit()

Free Trial & More Information

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

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