Ready to get started?

Learn more about the CData Python Connector for Excel Services or download a free trial:

Download Now

Extract, Transform, and Load Excel Services Data in Python

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

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

Connecting to Excel Services Data

Connecting to Excel Services 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.

The URL, User, and Password properties, under the Authentication section, must be set to valid credentials for SharePoint Online, SharePoint 2010, or SharePoint 2013. Additionally, the Library property must be set to a valid SharePoint Document Library and the File property must be set to a valid .xlsx file in the indicated Library.

After installing the CData Excel Services Connector, follow the procedure below to install the other required modules and start accessing Excel Services 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 Excel Services 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.excelservices as mod

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

cnxn = mod.connect("URL=https://myorg.sharepoint.com;User=admin@myorg.onmicrosoft.com;Password=password;File=Book1.xlsx;")

Create a SQL Statement to Query Excel Services

Use SQL to create a statement for querying Excel Services. In this article, we read data from the Account entity.

sql = "SELECT Name, AnnualRevenue FROM Account WHERE Industry = 'Floppy Disks'"

Extract, Transform, and Load the Excel Services Data

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

Loading Excel Services Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

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

Adding New Rows to Excel Services

table1 = [ ['Name','AnnualRevenue'], ['NewName1','NewAnnualRevenue1'], ['NewName2','NewAnnualRevenue2'], ['NewName3','NewAnnualRevenue3'] ]

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

With the CData Python Connector for Excel Services, you can work with Excel Services 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 Excel Services Python Connector to start building Python apps and scripts with connectivity to Excel Services 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.excelservices as mod

cnxn = mod.connect("URL=https://myorg.sharepoint.com;User=admin@myorg.onmicrosoft.com;Password=password;File=Book1.xlsx;")

sql = "SELECT Name, AnnualRevenue FROM Account WHERE Industry = 'Floppy Disks'"

table1 = etl.fromdb(cnxn,sql)

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

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

table3 = [ ['Name','AnnualRevenue'], ['NewName1','NewAnnualRevenue1'], ['NewName2','NewAnnualRevenue2'], ['NewName3','NewAnnualRevenue3'] ]

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