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Python Connector Libraries for SAP ByDesign Data Connectivity. Integrate SAP ByDesign with popular Python tools like Pandas, SQLAlchemy, Dash & petl.

Use pandas to Visualize SAP ByDesign Data in Python



The CData Python Connector for SAP ByDesign enables you use pandas and other modules to analyze and visualize live SAP ByDesign data in Python.

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, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build SAP ByDesign-connected Python applications and scripts for visualizing SAP ByDesign data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to SAP ByDesign data, execute queries, and visualize the results.

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.

Follow the procedure below to install the required modules and start accessing SAP ByDesign through Python objects.

Install Required Modules

Use the pip utility to install the pandas & Matplotlib modules and the SQLAlchemy toolkit:

pip install pandas
pip install matplotlib
pip install sqlalchemy

Be sure to import the module with the following:

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engine

Visualize SAP ByDesign Data in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with SAP ByDesign data.

engine = create_engine("sapbydesign:///?URL=https://my999999.sapbydesign.com&User=username&Password=password&CustomService=servicename")

Execute SQL to SAP ByDesign

Use the read_sql function from pandas to execute any SQL statement and store the resultset in a DataFrame.

df = pandas.read_sql("SELECT ID, ProductCategoryID FROM [Inventory Balance] WHERE ProductCategoryID = '1234567'", engine)

Visualize SAP ByDesign Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the SAP ByDesign data. The show method displays the chart in a new window.

df.plot(kind="bar", x="ID", y="ProductCategoryID")
plt.show()

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 pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin

engine = create_engine("sapbydesign:///?URL=https://my999999.sapbydesign.com&User=username&Password=password&CustomService=servicename")
df = pandas.read_sql("SELECT ID, ProductCategoryID FROM [Inventory Balance] WHERE ProductCategoryID = '1234567'", engine)

df.plot(kind="bar", x="ID", y="ProductCategoryID")
plt.show()