How to Build an ETL App for SAP Ariba Source Data in Python with CData Connect AI

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Connect AI Python SDK and the petl framework, you can build SAP Ariba Source-connected applications and pipelines for extracting, transforming, and loading SAP Ariba Source data. This article shows how to connect to Connect AI and use petl to extract, transform, and load SAP Ariba Source data.

The Connect AI Python SDK (cdata-connect-ai) is a DB-API 2.0 (PEP 249) compliant client, so petl can read directly from the SDK connection with etl.fromdb. There is no driver to install per source: connect with a Personal Access Token and build your pipeline.

Connect to SAP Ariba Source 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 Ariba Source" from the Add Connection panel

3. Enter the necessary authentication properties to connect to SAP Ariba Source.

   In order to connect with SAP Ariba Source, set the following:

   • API: Specify which API you would like the provider to retrieve SAP Ariba data from. Select the Supplier, Sourcing Project Management, or Contract API based on your business role (possible values are SupplierDataAPIWithPaginationV4, SourcingProjectManagementAPIV2, or ContractAPIV1).
   • DataCenter: The data center where your account's data is hosted.
   • Realm: The name of the site you want to access.
   • Environment: Indicate whether you are connecting to a test or production environment (possible values are TEST or PRODUCTION).

   If you are connecting to the Supplier Data API or the Contract API, additionally set the following:

   • User: Id of the user on whose behalf API calls are invoked.
   • PasswordAdapter: The password associated with the authenticating User.

   If you're connecting to the Supplier API, set ProjectId to the Id of the sourcing project you want to retrieve data from.

   Authenticating with OAuth

   After setting connection properties, you need to configure OAuth connectivity to authenticate.

   • Set AuthScheme to OAuthClient.
   • Register an application with the service to obtain the APIKey, OAuthClientId and OAuthClientSecret.

     For more information on creating an OAuth application, refer to the Help documentation.

   Automatic OAuth

   After setting the following, you are ready to connect:

   APIKey: The Application key in your app settings. OAuthClientId: The OAuth Client Id in your app settings. OAuthClientSecret: The OAuth Secret in your app settings.

   When you connect, the provider automatically completes the OAuth process:

   1. The provider obtains an access token from SAP Ariba and uses it to request data.
   2. The provider refreshes the access token automatically when it expires.
   3. The OAuth values are saved in memory relative to the location specified in OAuthSettingsLocation.
   
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 Required Modules

Install the SDK and the petl framework using the pip utility:

pip install cdata-connect-ai
pip install petl

Build an ETL App for SAP Ariba Source Data in Python

Once the required modules are installed, you are ready to build the ETL app. Code snippets follow, but the full source code is available at the end of the article.

First, import the modules and connect to Connect AI with your account email and PAT:

import petl as etl
import cdata_connect_ai

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

Create a SQL Statement to Query SAP Ariba Source

Use SQL to create a statement for querying SAP Ariba Source. In this article, we read data from the Vendors entity. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, SAPAribaSource1).

sql = (
    "SELECT SMVendorID, Category "
    "FROM [SAPAribaSource1].[SAPAribaSource].[Vendors] "
    "WHERE Region = 'USA'"
)

Extract, Transform, and Load the SAP Ariba Source Data

With a connection and query in hand, use petl to extract, transform, and load the SAP Ariba Source data. In this example, we extract SAP Ariba Source data, sort the data by the Category column, and load the data into a CSV file.

table1 = etl.fromdb(conn, sql)

table2 = etl.sort(table1, 'Category')

etl.tocsv(table2, 'vendors_data.csv')

Load New Rows Back into SAP Ariba Source

When SAP Ariba Source supports writes, load rows back with a batch INSERT. The SDK's executemany takes @name placeholders and a list of parameter dictionaries, one per row.

cur = conn.cursor()
cur.executemany(
    "INSERT INTO [SAPAribaSource1].[SAPAribaSource].[Vendors] (SMVendorID, Category) "
    "VALUES (@val1, @val2)",
    [
        {"@val1": "New value 1", "@val2": "New value 1"},
        {"@val1": "New value 2", "@val2": "New value 2"},
    ],
)
print(f"Rows inserted: {cur.rowcount}")

conn.close()

Note: Even for writable sources, a read-only PAT or connection permission will reject write operations.

With the CData Connect AI Python SDK, you can work with SAP Ariba Source data just like you would with any database, including direct access to data in ETL packages like petl.

More Information and Free Trial

Now you can pipe live SAP Ariba Source data through petl using the CData Connect AI Python SDK. For more information on connecting to SAP Ariba Source (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start building data pipelines for live SAP Ariba Source data in Python.

Full Source Code

import petl as etl
import cdata_connect_ai

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

sql = (
    "SELECT SMVendorID, Category "
    "FROM [SAPAribaSource1].[SAPAribaSource].[Vendors] "
    "WHERE Region = 'USA'"
)

table1 = etl.fromdb(conn, sql)

table2 = etl.sort(table1, 'Category')

etl.tocsv(table2, 'vendors_data.csv')

cur = conn.cursor()
cur.executemany(
    "INSERT INTO [SAPAribaSource1].[SAPAribaSource].[Vendors] (SMVendorID, Category) "
    "VALUES (@val1, @val2)",
    [
        {"@val1": "New value 1", "@val2": "New value 1"},
        {"@val1": "New value 2", "@val2": "New value 2"},
    ],
)
print(f"Rows inserted: {cur.rowcount}")
conn.close()