Python Tutorial for Creating and Running Questions

The examples in this tutorial show how to use Python to configure programmatic question runs so that you can gain familiarity with formatting Clean Room API requests. This is not necessarily a "recommended" approach (you can follow your organization's Python best practices or constructs).

Most clean room customers leverage the API to programmatically execute runs and pull results of insights for already created questions in a clean room. Unless you plan to programmatically perform every Clean Room API operation, you can skip to Step 7: Run Questions.

Tip: This tutorial is also provided as a Jupyter Notebook IPYNB file for use in your Jupyter Notebook environment. The IPYNB file is available for download here.

This tutorial assumes that you have configured your system to be able to open the IPYNB file via Jupyter Notebook and execute Python code.

Overall Steps

This tutorial has the following overall steps:

1. Environmental Configuration
2. Defining API Operations
3. Creating a Clean Room
4. Provisioning Datasets
5. Creating Analytical Questions
6. Assign Datasets to Questions
7. Run Questions
8. Get Question Run Status and Results
9. Creating Flows