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

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



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

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

Connecting to Workday Data

Connecting to Workday 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, there are three pieces of information required: Authentication, API URL, and WSDL URL.

Authentication

To authenticate, specify your User and Password. Note that you must append your Tenant to your User separated by an '@' character. For instance, if you normally log in with 'geraldg' and your Tenant is 'mycompany_mc1', then your User should be specified as 'geraldg@mycompany_mc1'.

API URL

The API URL may be specified either directly via APIURL, or it may be constructed from the Tenant, Service, and Host. The APIURL is constructed in the following format: <Host>/ccx/service/<Tenant>/<Service>.

WSDL URL

The WSDLURL may be specified in its entirety, or may be constructed from the Service and WSDLVersion connection properties. The WSDLURL is constructed in the following format: https://community.workday.com/sites/default/files/file-hosting/productionapi/<Service>/<WSDLVersion>/<Service>.wsdl

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

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

cnxn = mod.connect("User=myuser;Password=mypassword;Tenant=mycompany_gm1;Host=https://wd3-impl-services1.workday.com")

Create a SQL Statement to Query Workday

Use SQL to create a statement for querying Workday. In this article, we read data from the Workers entity.

sql = "SELECT Worker_Reference_WID, Legal_Name_Last_Name FROM Workers WHERE Legal_Name_Last_Name = 'Morgan'"

Extract, Transform, and Load the Workday Data

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

Loading Workday Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

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

cnxn = mod.connect("User=myuser;Password=mypassword;Tenant=mycompany_gm1;Host=https://wd3-impl-services1.workday.com")

sql = "SELECT Worker_Reference_WID, Legal_Name_Last_Name FROM Workers WHERE Legal_Name_Last_Name = 'Morgan'"

table1 = etl.fromdb(cnxn,sql)

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

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