{"categories":[{"label":"Database","url":"https://skillfed.io/packages/category/database/4"}],"enrichment":{"capability":"Integrates dbt models with Cube's semantic layer by parsing dbt manifests and converting model definitions into Cube-compatible data model specifications.","skillfed_tags":["dbt-integration","semantic-layer","data-modeling"],"use_cases":["Automatically generate Cube data models from existing dbt projects without manual schema definition.","Filter dbt models by path, tag, or name to expose only specific models to Cube's semantic layer.","Extract column metadata (names, descriptions, data types) from dbt to populate Cube dimensions and measures.","Preprocess large dbt manifests for performance optimization when working with complex projects.","Integrate dbt and Cube in CI/CD pipelines to keep semantic definitions in sync with dbt transformations."],"what_it_does":"cube_dbt is a bridge between dbt and Cube's semantic layer. It reads dbt manifest files (the compiled output of a dbt project) and exposes dbt models and their metadata\u2014names, descriptions, columns, tags, data types\u2014in a form that Cube can consume to build its data model. The package provides a Python API to load a manifest from a URL, filter models by path or tag, and convert individual models or columns into Cube dimension and measure specifications.\n\nTypically used in workflows where dbt defines the transformation layer and Cube defines the semantic/metrics layer on top. You load the manifest, filter to the models you want Cube to know about, and then call methods like `as_cube()` or `as_dimensions()` to generate Cube-compatible definitions. The package is lightweight\u2014only PyYAML and orjson as dependencies\u2014and supports Python 3.8 and later.","worth_installing":"Yes, if you are actively using both dbt and Cube and want to automate the connection between them. The low install friction, permissive license, and clean API make it straightforward to adopt. However, the aging maintenance status (296 days since last release) means you should verify compatibility with your current dbt and Cube versions before relying on it in production, and be prepared for slower issue resolution if problems arise."},"id":"cube-dbt","links":{"html":"https://skillfed.io/packages/cube-dbt","md":"https://skillfed.io/packages/cube-dbt.md","pypi":"https://pypi.org/project/cube-dbt/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2025-10-22","license_spdx":null,"license_treatment":"permissive","name":"cube_dbt","python_support":"supports_current","summary":"dbt integration for Cube"},"popularity":{"monthly_downloads":106005,"position":12674,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.6.3"}