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

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Connect AI Python SDK 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 Connect AI and use petl to extract, transform, and load Workday data.

The Connect AI Python SDK (cdata-connect-ai) is a DB-API 2.0 (PEP 249) compliant client, so petl can read directly from the SDK connection with etl.fromdb. There is no driver to install per source: connect with a Personal Access Token and build your pipeline.

Getting Started

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Connect to Workday in Connect AI

CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select "Workday" from the Add Connection panel

3. Enter the necessary authentication properties to connect to Workday.

   To connect to Workday, users need to find the Tenant and BaseURL and then select their API type.

   Obtaining the BaseURL and Tenant

   To obtain the BaseURL and Tenant properties, log into Workday and search for "View API Clients." On this screen, you'll find the Workday REST API Endpoint, a URL that includes both the BaseURL and Tenant.

   The format of the REST API Endpoint is: https://domain.com/subdirectories/mycompany, where:

   • https://domain.com/subdirectories/ is the BaseURL.
   • mycompany (the portion of the url after the very last slash) is the Tenant.
   For example, in the REST API endpoint https://wd3-impl-services1.workday.com/ccx/api/v1/mycompany, the BaseURL is https://wd3-impl-services1.workday.com and the Tenant is mycompany.

   Using ConnectionType to Select the API

   The value you use for the ConnectionType property determines which Workday API you use. See our Community Article for more information on Workday connectivity options and best practices.

   API	ConnectionType Value
   WQL	WQL
   Reports as a Service	Reports
   REST	REST
   SOAP	SOAP

   
   

   Authentication

   Your method of authentication depends on which API you are using.

   • WQL, Reports as a Service, REST: Use OAuth authentication.
   • SOAP: Use Basic or OAuth authentication.

   See the Help documentation for more information on configuring OAuth with Workday.

   
4. Click Save & Test
5. Navigate to the Permissions tab and update the user-based permissions.

Generate a Personal Access Token (PAT)

The Python SDK authenticates to Connect AI with your account email and a Personal Access Token (PAT). It is best practice to create a separate PAT for each application to maintain granularity of access.

1. Click the Gear icon () at the top right of the Connect AI app to open the Settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create.
4. The PAT is only visible at creation, so copy it and store it securely.

Install Required Modules

Install the SDK and the petl framework using the pip utility:

pip install cdata-connect-ai
pip install petl

Build an ETL App for Workday Data in Python

Once the required modules are installed, you are ready to build the ETL app. Code snippets follow, but the full source code is available at the end of the article.

First, import the modules and connect to Connect AI with your account email and PAT:

import petl as etl
import cdata_connect_ai

conn = cdata_connect_ai.connect(
    username="[email protected]",
    password="<your_pat>",
)

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. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, Workday1).

sql = (
    "SELECT Worker_Reference_WID, Legal_Name_Last_Name "
    "FROM [Workday1].[Workday].[Workers] "
    "WHERE Legal_Name_Last_Name = 'Morgan'"
)

Extract, Transform, and Load the Workday Data

With a connection and query in hand, 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.

table1 = etl.fromdb(conn, sql)

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

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

Load New Rows Back into Workday

When Workday supports writes, load rows back with a batch INSERT. The SDK's executemany takes @name placeholders and a list of parameter dictionaries, one per row.

cur = conn.cursor()
cur.executemany(
    "INSERT INTO [Workday1].[Workday].[Workers] (Worker_Reference_WID, Legal_Name_Last_Name) "
    "VALUES (@val1, @val2)",
    [
        {"@val1": "New value 1", "@val2": "New value 1"},
        {"@val1": "New value 2", "@val2": "New value 2"},
    ],
)
print(f"Rows inserted: {cur.rowcount}")

conn.close()

Note: Even for writable sources, a read-only PAT or connection permission will reject write operations.

With the CData Connect AI Python SDK, you can work with Workday data just like you would with any database, including direct access to data in ETL packages like petl.

More Information and Free Trial

Now you can pipe live Workday data through petl using the CData Connect AI Python SDK. For more information on connecting to Workday (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start building data pipelines for live Workday data in Python.

Full Source Code

import petl as etl
import cdata_connect_ai

conn = cdata_connect_ai.connect(
    username="[email protected]",
    password="<your_pat>",
)

sql = (
    "SELECT Worker_Reference_WID, Legal_Name_Last_Name "
    "FROM [Workday1].[Workday].[Workers] "
    "WHERE Legal_Name_Last_Name = 'Morgan'"
)

table1 = etl.fromdb(conn, sql)

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

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

cur = conn.cursor()
cur.executemany(
    "INSERT INTO [Workday1].[Workday].[Workers] (Worker_Reference_WID, Legal_Name_Last_Name) "
    "VALUES (@val1, @val2)",
    [
        {"@val1": "New value 1", "@val2": "New value 1"},
        {"@val1": "New value 2", "@val2": "New value 2"},
    ],
)
print(f"Rows inserted: {cur.rowcount}")
conn.close()