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

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Okta and the petl framework, you can build Okta-connected applications and pipelines for extracting, transforming, and loading Okta data. This article shows how to connect to Okta with the CData Python Connector and use petl and pandas to extract, transform, and load Okta data.

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

Connecting to Okta Data

Connecting to Okta 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 Okta, set the Domain connection string property to your Okta domain.

You will use OAuth to authenticate with Okta, so you need to create a custom OAuth application.

Creating a Custom OAuth Application

From your Okta account:

1. Sign in to your Okta developer edition organization with your administrator account.
2. In the Admin Console, go to Applications > Applications.
3. Click Create App Integration.
4. For the Sign-in method, select OIDC - OpenID Connect.
5. For Application type, choose Web Application.
6. Enter a name for your custom application.
7. Set the Grant Type to Authorization Code. If you want the token to be automatically refreshed, also check Refresh Token.
8. Set the callback URL:
   • For desktop applications and headless machines, use http://localhost:33333 or another port number of your choice. The URI you set here becomes the property.
   • For web applications, set the callback URL to a trusted redirect URL. This URL is the web location the user returns to with the token that verifies that your application has been granted access.
9. In the Assignments section, either select Limit access to selected groups and add a group, or skip group assignment for now.
10. Save the OAuth application.
11. The application's Client Id and Client Secret are displayed on the application's General tab. Record these for future use. You will use the Client Id to set the OAuthClientId and the Client Secret to set the OAuthClientSecret.
12. Check the Assignments tab to confirm that all users who must access the application are assigned to the application.
13. On the Okta API Scopes tab, select the scopes you wish to grant to the OAuth application. These scopes determine the data that the app has permission to read, so a scope for a particular view must be granted for the driver to have permission to query that view. To confirm the scopes required for each view, see the view-specific pages in Data Model < Views in the Help documentation.

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

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

cnxn = mod.connect("Domain=dev-44876464.okta.com;InitiateOAuth=GETANDREFRESH;")

Create a SQL Statement to Query Okta

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

sql = "SELECT Id, ProfileFirstName FROM Users WHERE Status = 'Active'"

Extract, Transform, and Load the Okta Data

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

Loading Okta Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

With the CData Python Connector for Okta, you can work with Okta 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 Okta to start building Python apps and scripts with connectivity to Okta data. Reach out to our Support Team if you have any questions.

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Full Source Code

import petl as etl
import pandas as pd
import cdata.okta as mod

cnxn = mod.connect("Domain=dev-44876464.okta.com;InitiateOAuth=GETANDREFRESH;")

sql = "SELECT Id, ProfileFirstName FROM Users WHERE Status = 'Active'"

table1 = etl.fromdb(cnxn,sql)

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

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