A few weeks ago, we introduced the support for Python in our semantic layer. Now you can use Python to configure Cube programmatically; moreover, you can also use Python and Jinja to define dynamic data models, reuse code, and simplify your day-to-day data modeling tasks.
It means that you can have Python-only experience with Cube, either providing programmatic configuration or authoring dynamic data models with YAML and Jinja. You can read more about that in the following blog posts:
In this webinar, we’ll do a deep dive into Python and Jinja. We’ll start by discussing the common cases for programmatic configuration and dynamic data models, review the code structure and syntax for Python and Jinja, and explore an elaborate live demo.
Register here and join us on Wednesday, December 6th at 9:00am PST.