TL;DR: Python has come to Cube; and this is huge. However, please bear with us for a complete story.
We’re building Cube as a feature-rich, universal semantic layer that works great for many use cases. Consequently, Cube needs and provides a great deal of flexibility in configuration. On the technical side, that includes plenty of environment variables—quite unsurprising for a modern cloud-native application. However, some of the most powerful configuration options, usually related to multitenancy and access control, are provided programmatically in a configuration file.
Usually, real-world Cube deployment will employ both environment variables and a configuration file with dozens, if not hundreds, lines of code. Cube would use programmatic configuration to fine-tune multitenancy, inspect and transform queries on-the-fly, or implement custom authentication to the rich set of APIs that Cube provides; this list can go on and on.
This is very much in sync with the code-first principle that we embrace here at Cube. We firmly believe that application of software engineering best practices—like the use of version control systems, code reviews, and sound code organization—to the data engineering field moves it further in the right direction and helps create high-quality data products. Programmatic configuration is crucial to this approach.
The Good, the Bad, and the Ugly
Since then, Cube has grown its audience to an exciting blend of software developers and data engineers, marked by more than 16,000 stars on GitHub. Cube has also expanded supported use cases with connected BI and, of course, AI. With all that, we felt the urge to take Cube further to better serve its expansive, diverse, and opinionated audience.
Today, we’re happy to announce that now Cube supports Python programming language in the
cube.py file to define configuration options!
Look how beautiful it is:
Support for Python comes with Cube Core v0.34 release. You can get started today in Cube Cloud; please make sure to switch to the latest version channel. You can also get started with Cube Core; however, please note that macOS on M1/M2 as well as Windows are not supported yet; we’re actively working on introducing the support for these platforms in the nearest future.
Please give Python a try out and join our Slack community to share your thoughts feedback. Also, stay tuned for further updates—we have so much more to share!