How to Build an ETL App for SAP ByDesign Data in Python with CData

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 ByDesign and the petl framework, you can build SAP ByDesign-connected applications and pipelines for extracting, transforming, and loading SAP ByDesign data. This article shows how to connect to SAP ByDesign with the CData Python Connector and use petl and pandas to extract, transform, and load SAP ByDesign data.

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

Connecting to SAP ByDesign Data

Connecting to SAP ByDesign 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.

Set the following connection properties to connect to SAP ByDesign.

• Url: Set this to the Url of your SAP ByDesign site. For example, https://test.sapbydesign.com
• User: Set this to the username of your account.
• Password: Set this to the password of your account.
• CustomService or AnalyticsService: Only one of these must be specified. If you have a custom service you want to retrieve data from, specify CustomService. If you want to retrieve the reports of a analytical service, specify AnalyticsService.
  If neither is specified, 'cc_home_analytics.svc' will used as a default for the AnalyticsService property. If you are not sure what service to specify, you can always query the Services view to list available services.

After installing the CData SAP ByDesign Connector, follow the procedure below to install the other required modules and start accessing SAP ByDesign 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 ByDesign 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.sapbydesign as mod

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

cnxn = mod.connect("URL=https://my999999.sapbydesign.com;User=username;Password=password;CustomService=servicename;")

Create a SQL Statement to Query SAP ByDesign

Use SQL to create a statement for querying SAP ByDesign. In this article, we read data from the [Inventory Balance] entity.

sql = "SELECT ID, ProductCategoryID FROM [Inventory Balance] WHERE ProductCategoryID = '1234567'"

Extract, Transform, and Load the SAP ByDesign Data

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

Loading SAP ByDesign Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

etl.tocsv(table2,'[inventory balance]_data.csv')

With the CData Python Connector for SAP ByDesign, you can work with SAP ByDesign 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 CData Python Connector for SAP ByDesign to start building Python apps and scripts with connectivity to SAP ByDesign 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.sapbydesign as mod

cnxn = mod.connect("URL=https://my999999.sapbydesign.com;User=username;Password=password;CustomService=servicename;")

sql = "SELECT ID, ProductCategoryID FROM [Inventory Balance] WHERE ProductCategoryID = '1234567'"

table1 = etl.fromdb(cnxn,sql)

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

etl.tocsv(table2,'[inventory balance]_data.csv')