dbt-bouncer

What it is and what it does

dbt-bouncer is a CLI tool that enforces naming conventions and project structure rules on dbt projects by analyzing dbt artifacts (manifest.json, catalog.json, run_results.json). It reads a YAML configuration file defining checks—such as model naming patterns, documentation requirements, or test coverage—then runs those checks against your dbt project and reports violations with severity levels.

The tool integrates into dbt workflows and CI/CD pipelines to catch convention violations early. It depends on Jinja2 for templating, Pydantic for configuration validation, sqlglot for SQL parsing, and rich for formatted terminal output. Configuration is declarative and human-readable, making it accessible for teams to define and maintain their own dbt standards without writing code.

Use it for:

• Enforce naming conventions (e.g., staging models start with 'stg_') across a dbt project in CI/CD.
• Validate that all models have documentation and tests before deployment.
• Check for consistency in model structure, column naming, or tagging across a team's dbt codebase.
• Prevent common dbt anti-patterns by defining project-specific rules in a config file.
• Generate a summary report of dbt project structure and check results for governance audits.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

dbt-bouncer validates dbt projects against configurable conventions and naming rules, running checks on dbt artifacts to enforce project-wide standards.

Yes. dbt-bouncer is actively maintained, has low install friction, carries no known vulnerabilities, and solves a real problem for teams using dbt—enforcing conventions at scale. The MIT license is permissive. Install it if your team uses dbt and wants to standardize project structure and naming without manual code review.

Install

dbt-bouncer on PyPI

pip install dbt-bouncer

uv add dbt-bouncer

poetry add dbt-bouncer

Installing dbt-bouncer

Before you install

Low install friction with a pure Python wheel and 12 well-established runtime dependencies. Active maintenance with a release 28 days ago; supports current Python versions (3.11–3.14).

License in practice

MIT license permits unrestricted use, modification, and distribution with minimal legal obligations.

Quickstart

pip install dbt-bouncer
dbt parse
dbt-bouncer init
dbt-bouncer run

Requires a dbt project with a manifest.json file (generated by `dbt parse`) and a dbt-bouncer.yml config file.

Verify before relying

• Whether the package supports dbt versions other than the latest; compatibility matrix not provided in fact sheet.
• Performance characteristics when running against large dbt projects with many models and tests.
• Whether custom check rules can be written or if only built-in checks are available.

Package facts

Evidence: dbt_bouncer-3.8.0-py3-none-any.whl

Keywords: CI/CD, cli, dbt, python

Tags

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