--- id: dbt-autofix version: "0.21.6" license: unclear license_treatment: unclear maintenance: active --- # dbt-autofix — CLI to autofix deprecations in dbt projects License: unclear · Maintenance: active · Downloads: 181.6K/mo ## What it is and what it does dbt-autofix is a CLI tool that automatically detects and fixes deprecated configurations in dbt projects. It handles a wide range of deprecation types across YAML, SQL, and Python files—including property migrations, custom key handling, duplicate key removal, and Jinja block cleanup—making it easier to resolve deprecation warnings introduced in dbt v1.10 and prepare projects for dbt Fusion. The tool runs in dry-run mode by default and outputs results in human-readable or JSON format, allowing you to review changes before applying them. The package depends on common utilities like click, typer, httpx, jinja2, pyyaml, and yamllint, plus dbt-specific tools (dbt-extractor, dbt-fusion-package-tools). It can also check and upgrade package dependencies for Fusion compatibility. For deprecations that cannot be automatically resolved, the documentation references an AGENTS.md guide for manual intervention strategies. Use it for: - Automatically fix deprecation warnings when upgrading a dbt project to dbt v1.10 or later. - Prepare a dbt project for migration to the dbt Fusion engine by scanning and updating incompatible configurations. - Batch-update YAML files across a large dbt project to move custom configs under the correct meta or config blocks. - Check installed dbt packages for Fusion compatibility and automatically upgrade them to compatible versions. - Run in dry-run mode to audit deprecations in a project before committing any changes. ## Worth the install? AI-flagged interpretation of the facts above — verify before relying. dbt-autofix scans dbt projects for deprecated configurations and automatically updates them to align with current best practices and dbt Fusion compatibility. Yes. The tool is actively maintained, has low install friction, carries no known security vulnerabilities, and directly solves a real problem for dbt users managing deprecation warnings and Fusion migration. The dry-run mode and JSON output make it safe to evaluate before applying changes. License status is unclear, so verify licensing terms before use in commercial projects. ## Install pip install dbt-autofix uv add dbt-autofix poetry add dbt-autofix ## Installing dbt-autofix Before you install: Low install friction with a pure Python wheel and straightforward dependencies. Active maintenance with a recent release within the last two weeks. Quickstart: # Install with uv (recommended) uvx dbt-autofix # Or with pip in a virtual environment pip install dbt-autofix dbt-autofix deprecations --path . --dry-run Requires Python 3.10 or later (and below 3.14). dbt project must be present at the specified path. Verify before relying: - Whether all deprecations listed in the coverage tables are actually implemented in version 0.21.6 or if coverage has evolved since the description was written. - Whether the package dependency upgrade feature (mentioned as new in 0.17.0) remains functional and well-maintained in current releases. - Performance characteristics when running against large dbt projects with many files. ## Package facts - License: not declared (unclear) - Python support: supports_current - Install friction: low - Maintenance: active - Downloads: 181.6K/month (top 15,000 on PyPI) - Known vulnerabilities: none known ## Tags dbt deprecation fixer, dbt project migration tool, dbt fusion compatibility, dbt yaml config updater, dbt deprecation scanner, dbt best practices automation, dbt version upgrade helper, dbt-ecosystem, deprecation-migration, cli-automation [View on SkillFed](https://skillfed.io/packages/dbt-autofix) · [View on PyPI](https://pypi.org/project/dbt-autofix/)