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Extract, Transform, and Load SAP Netweaver Gateway Data in Python

The CData Python Connector for SAP Netweaver Gateway enables you to create ETL applications and pipelines for SAP Netweaver Gateway data in Python with petl.

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

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

Connecting to SAP Netweaver Gateway Data

Connecting to SAP Netweaver Gateway 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.

SAP Gateway allows both basic and OAuth 2.0 authentication. You can use basic authentication to connect to your own account, or you can use OAuth to enable other users to retrieve data from your service with their accounts. In addition to authenticating, set the following connection properties to access SAP Gateway tables.

  • Url: Set this to the URL of your environment, or to the full URL of the service. For example, the full URL might appear as: https://sapes5.sapdevcenter.com/sap/opu/odata/IWBEP/GWSAMPLE_BASIC/. In this example, the environment URL would just be: https://sapes5.sapdevcenter.com.
  • Namespace: Set the appropriate Service Namespace. In the example above, IWBEP is the namespace. It is optional if the full URL to the service is specified.
  • Service: Set this to the service you want to retrieve data from. In the example above, the service is GWSAMPLE_BASIC. It is not required if the full URL is specified.

Authenticate via Basic Authentication

In basic authentication, you use your login credentials to connect. Set the following properties:

  • User: This is the username you use to log in to SAP Gateway.
  • Password: This is the password you use to log in to SAP Gateway.

Authenticate via OAuth Authentication

You can connect to SAP Gateway using the embedded OAuth connectivity (without setting any additional authentication connection properties). When you connect, the OAuth endpoint opens in your browser. Log in and grant permissions to complete the OAuth process. See the OAuth section in the online Help documentation for more information on other OAuth authentication flows.

After installing the CData SAP Netweaver Gateway Connector, follow the procedure below to install the other required modules and start accessing SAP Netweaver Gateway through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install petl
pip install pandas

Build an ETL App for SAP Netweaver Gateway Data in Python

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

First, be sure to import the modules (including the CData Connector) with the following:

import petl as etl
import pandas as pd
import cdata.sapgateway as mod

You can now connect with a connection string. Use the connect function for the CData SAP Netweaver Gateway Connector to create a connection for working with SAP Netweaver Gateway data.

cnxn = mod.connect("User=user;Password=password;URL=https://sapes5.sapdevcenter.com/sap/opu/odata/IWBEP/GWSAMPLE_BASIC/;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Create a SQL Statement to Query SAP Netweaver Gateway

Use SQL to create a statement for querying SAP Netweaver Gateway. In this article, we read data from the SalesOrderLineItems entity.

sql = "SELECT ProductID, Quantity FROM SalesOrderLineItems WHERE Quantity = '15'"

Extract, Transform, and Load the SAP Netweaver Gateway Data

With the query results stored in a DataFrame, we can use petl to extract, transform, and load the SAP Netweaver Gateway data. In this example, we extract SAP Netweaver Gateway data, sort the data by the Quantity column, and load the data into a CSV file.

Loading SAP Netweaver Gateway Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

In the following example, we add new rows to the SalesOrderLineItems table.

Adding New Rows to SAP Netweaver Gateway

table1 = [ ['ProductID','Quantity'], ['NewProductID1','NewQuantity1'], ['NewProductID2','NewQuantity2'], ['NewProductID3','NewQuantity3'] ]

etl.appenddb(table1, cnxn, 'SalesOrderLineItems')

With the CData Python Connector for SAP Netweaver Gateway, you can work with SAP Netweaver Gateway data just like you would with any database, including direct access to data in ETL packages like petl.

Free Trial & More Information

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



Full Source Code


import petl as etl
import pandas as pd
import cdata.sapgateway as mod

cnxn = mod.connect("User=user;Password=password;URL=https://sapes5.sapdevcenter.com/sap/opu/odata/IWBEP/GWSAMPLE_BASIC/;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

sql = "SELECT ProductID, Quantity FROM SalesOrderLineItems WHERE Quantity = '15'"

table1 = etl.fromdb(cnxn,sql)

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

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

table3 = [ ['ProductID','Quantity'], ['NewProductID1','NewQuantity1'], ['NewProductID2','NewQuantity2'], ['NewProductID3','NewQuantity3'] ]

etl.appenddb(table3, cnxn, 'SalesOrderLineItems')