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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 BusinessObjects BI, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build SAP BusinessObjects BI-connected Python applications and scripts for visualizing SAP BusinessObjects BI data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to SAP BusinessObjects BI 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 BusinessObjects BI data in Python. When you issue complex SQL queries from SAP BusinessObjects BI, the driver pushes supported SQL operations, like filters and aggregations, directly to SAP BusinessObjects BI and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to SAP BusinessObjects BI 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.
To connect to your SAP Business Objects BI instance, you must set the following connection properties:
Follow the procedure below to install the required modules and start accessing SAP BusinessObjects BI through Python objects.
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
You can now connect with a connection string. Use the create_engine function to create an Engine for working with SAP BusinessObjects BI data.
engine = create_engine("sapbusinessobjectsbi:///?User=username&Password=password&Url=http://myinstance:6405/biprws")
Use the read_sql function from pandas to execute any SQL statement and store the resultset in a DataFrame.
df = pandas.read_sql("SELECT StoreName, TotalRevenue FROM MyCustomReport WHERE State = 'CA'", engine)
With the query results stored in a DataFrame, use the plot function to build a chart to display the SAP BusinessObjects BI data. The show method displays the chart in a new window.
df.plot(kind="bar", x="StoreName", y="TotalRevenue") plt.show()👁 SAP BusinessObjects BI data in a Python plot (Salesforce is shown).
Download a free, 30-day trial of the CData Python Connector for SAP BusinessObjects BI to start building Python apps and scripts with connectivity to SAP BusinessObjects BI data. Reach out to our Support Team if you have any questions.
import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin
engine = create_engine("sapbusinessobjectsbi:///?User=username&Password=password&Url=http://myinstance:6405/biprws")
df = pandas.read_sql("SELECT StoreName, TotalRevenue FROM MyCustomReport WHERE State = 'CA'", engine)
df.plot(kind="bar", x="StoreName", y="TotalRevenue")
plt.show()
Download a Community License of the SAP BusinessObjects BI Connector to get started:
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👁 SAP BusinessObjects BI IconPython Connector Libraries for SAP BusinessObjects BI Data Connectivity. Integrate SAP BusinessObjects BI with popular Python tools like Pandas, SQLAlchemy, Dash & petl.