adding-dbt-unit-test

Run dbt unit tests by defining a unit_tests schema in YAML with the model name, given inputs as fixtures, and expected outputs to validate transformation logic and prevent regressions.

Dbt unit test fixtures can be defined using dict, csv, or sql input formats within the YAML schema, allowing flexible mocked inputs to validate model logic against expected outputs.

Yes, you can unit test incremental and versioned dbt models. The testing schema supports versioning specifications and handles dependency-heavy projects to validate logic across different model states.

Overrides in dbt unit tests allow you to mock macros and variables, enabling controlled testing of dependency-heavy models by replacing external dependencies with expected static values.

Dbt unit testing supports test-driven development by codifying input and output expectations in YAML, allowing you to define expected transformation behavior before running models to prevent regression bugs.

Dbt unit testing requires a model name, given inputs, and expected outputs defined under the unit_tests YAML schema. Complex dependency-heavy models may need macro and variable overrides for accurate mocking.