Exposure Parsing

[z3z1ma]

Description

Parsing exposures from Metabase automatically in relation to a dbt project. This function is huge for understanding exposures within your data model. Close the loop between model composition and tangible BI exposures of those models creating an extremely valuable company asset in the dbt docs. In the nature of this project, the aim is we can use almost the same invocation parameters users set up in CI / CD for dbt-metabase export as they can with dbt-metabase exposures. This lets you run the invocation in production to essentially keep you docs in full sync with BI.

Note: Just opening this for visibility and preliminary code introspection. A bit more to do (but not too much).

Type of change

• [x] New feature (non-breaking change which adds functionality)
• [x] This change requires a documentation update

How Has This Been Tested?

Open to ideas but ultimately I think making a mock api from metabase running on top of a database that has been seeded and ran through with the dbt jaffle shop project would be most robust. Just a lot of work.

• [ ] CI test for exposure documentation

Test Configuration:

• Python version: 3.8

Checklist:

• [x] My code follows the style guidelines of this project
• [x] I have performed a self-review of my own code
• [x] I have commented my code, particularly in hard-to-understand areas
• [ ] I have made corresponding changes to the documentation
• [x] My changes generate no new warnings
• [x] I have added tests that prove my fix is effective or that my feature works
• [x] New and existing unit tests pass locally with my changes

References #22

[z3z1ma]

Working on documentation updates now Then will move onto some pretty cool unit tests

Code is in a reviewable state as is though

[z3z1ma]

Example native query parsed from Metabase into exposure with verbose documentation auto-generated into revisionable YAML.

Example DAG of exposures on a single focused node.