Getting Started with the CData Connect AI Python SDK for SAP SuccessFactors

The CData Connect AI Python SDK (cdata-connect-ai) is a DB-API 2.0 (PEP 249) compliant client that lets you fetch and act on live SAP SuccessFactors data with standard Python database code. Because Connect AI provides the connectivity: you install one package, authenticate with a Personal Access Token, and query SAP SuccessFactors (and every other source connected in Connect AI) using the same familiar connect() / cursor() / fetchall() pattern you already know from libraries like sqlite3 and psycopg2.

This guide walks through connecting SAP SuccessFactors in Connect AI, generating a Personal Access Token, installing the SDK, and reading (and, where supported, writing) live SAP SuccessFactors data.

Prerequisites

• An account in CData Connect AI
• Python 3.8 or higher
• An active SAP SuccessFactors account with valid credentials

Connect to SAP SuccessFactors in Connect AI

CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select "SAP SuccessFactors" from the Add Connection panel

3. Enter the necessary authentication properties to connect to SAP SuccessFactors.

   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.
   
4. Click Save & Test
5. Navigate to the Permissions tab and update the user-based permissions.

Generate a Personal Access Token (PAT)

The Python SDK authenticates to Connect AI with your account email and a Personal Access Token (PAT). It is best practice to create a separate PAT for each application to maintain granularity of access.

1. Click the Gear icon () at the top right of the Connect AI app to open the Settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create.
4. The PAT is only visible at creation, so copy it and store it securely.

Install the SDK

Install the SDK from PyPI with pip:

pip install cdata-connect-ai

Connect and Run Your First Query

Connect with your account email and PAT, then query sys_tables to discover every table available across your connected sources. Identifiers in Connect AI are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, SAPSuccessFactors1).

import cdata_connect_ai

conn = cdata_connect_ai.connect(
    username="[email protected]",
    password="<your_pat>",
)
cur = conn.cursor()

# Discover what's available across your connected sources
cur.execute("SELECT CatalogName, SchemaName, TableName FROM sys_tables LIMIT 25")

for row in cur.fetchall():
    print(row)

Pick any table from the results and query it directly:

cur.execute(
    "SELECT address1, zipCode "
    "FROM [SAPSuccessFactors1].[SAPSuccessFactors].[ExtAddressInfo] "
    "LIMIT 10"
)

for row in cur.fetchall():
    print(row)

Write Back to SAP SuccessFactors

When the data source and your connection permissions allow it, the same cursor runs INSERT, UPDATE, and DELETE statements. Bind values with pyformat (%(name)s) parameters, exactly as you would for a filtered read, and check cursor.rowcount for the number of affected rows.

# Insert a new record
cur.execute(
    "INSERT INTO [SAPSuccessFactors1].[SAPSuccessFactors].[ExtAddressInfo] (address1) "
    "VALUES (%(newvalue)s)",
    {"newvalue": "Example value"},
)
print(f"Rows inserted: {cur.rowcount}")

# Update existing records
cur.execute(
    "UPDATE [SAPSuccessFactors1].[SAPSuccessFactors].[ExtAddressInfo] "
    "SET zipCode = %(newvalue)s "
    "WHERE city = 'Springfield'",
    {"newvalue": "Updated value"},
)
print(f"Rows updated: {cur.rowcount}")

conn.close()

Note: Even for writable sources, a read-only PAT or connection permission will reject write operations. The same parameterized pattern also covers DELETE statements and stored procedures through cursor.callproc().

That is the entire workflow: one package, a PAT, and standard DB-API calls. Because the SDK returns a normal DB-API connection, it drops straight into the rest of the Python data ecosystem. From here you can load SAP SuccessFactors data into pandas, build ETL pipelines with petl, or power a Dash web app, all using this same connection.

More Information and Free Trial

Now you can query live SAP SuccessFactors data from Python through the CData Connect AI Python SDK. For more information on connecting to SAP SuccessFactors (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start working with live SAP SuccessFactors data in Python.