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CLI to autofix deprecations in dbt projects

Project description

dbt-autofix

dbt-autofix automatically scans your dbt project for deprecated configurations and updates them to align with the latest best practices. This makes it easier to resolve deprecation warnings introduced in dbt v1.10 as well as prepare for migration to the dbt Fusion engine.

There will also be cases that dbt-autofix cannot resolve and require manual intervention. For those scenarios, using AI Agents can be helpfiul see the below section on Using AGENTS.md. Even if you don't intend to use LLMs, the AGENTS.md can be a very helpful guidance for work that may need to be done after autofix has done it's part.

Deprecation Coverage - Project Files

The following deprecations are covered by dbt-autofix deprecations:

Deprecation Code in dbt Core Files Handling Support Behavior Change
PropertyMovedToConfigDeprecation YAML files Move all deprecated property-level configs under config: in YAML files across all resource types (models, exposures, owners, etc) Full No
CustomKeyInObjectDeprecation YAML files Move all models extra config (not valid or custom) under meta: and meta under config: Full No
DuplicateYAMLKeysDeprecation YAML files Remove duplicate keys in YAML files, keeping the second one to keep the same behaviour Full No
CustomTopLevelKeyDeprecation YAML files Delete custom top-level key-value pairs in YAML files Full No
UnexpectedJinjaBlockDeprecation SQL files Remove extra {% endmacro %} and {% endif %} that don't have corresponding opening statements Full No
MissingPlusPrefixDeprecation dbt_project.yml Prefix all built-in configs for models/tests etc... with a + Partial (Does not yet prefix custom configs) No
ConfigDataPathDeprecation dbt_project.yml Remove deprecated config for data path (now seed) Full No
ConfigLogPathDeprecation dbt_project.yml Remove deprecated config for log path Full No
ConfigSourcePathDeprecation dbt_project.yml Remove deprecated config for source path Full No
ConfigTargetPathDeprecation dbt_project.yml Remove deprecated config for target path Full No
ExposureNameDeprecation YAML files Replaces spaces with underscores and removes non-alphanumeric characters in exposure names Full Yes
ResourceNamesWithSpacesDeprecation SQL files, YAML files Replaces spaces with underscores in resource names, updating .sql filenames as necessary Full Yes
SourceFreshnessProjectHooksNotRun dbt_project.yml Set source_freshness_run_project_hooks in dbt_project.yml "flags" to true Full Yes
MissingArgumentsPropertyInGenericTestDeprecation YAML files Move any keyword arguments defined as top-level property on generic test to arguments property Full No

Deprecation Coverage - CLI Commands

The following deprecations are covered by dbt-autofix jobs:

Deprecation Code in dbt Handling Support Behavior Change
ModelParamUsageDeprecation Replace -m/--model with -s/--select Full No
CustomOutputPathInSourceFreshnessDeprecation Remove -o/--output usage in dbt source freshness commands Full Yes

Installation

From PyPi

With uv (recommended)

We recommend using uv/uvx to run the package. If you don't have uv installed, you can install uv and uvx, following the instructions on the offical website.

  • to run the latest version of the tool: uvx dbt-autofix
  • to run a specific version of the tool: uvx dbt-autofix@0.1.2
  • to install the tool as a dedicated CLI: uv tool install dbt-autofix

With pip

You can also use pip if you prefer, but we then recommend installing the tool in its own Python virtual environment. Once in a venv, install the tool with pip install dbt-autofix and then run dbt-autofix ...

From the source repo

To run it from the git repo directly, install uv following those instructions and then:

run the tool directly

uvx --from git+https://github.com/dbt-labs/dbt-autofix.git dbt-autofix --help

or install it so that it can be run with dbt-cleanup in the future

uv tool install --from git+https://github.com/dbt-labs/dbt-autofix.git dbt-autofix

Usage

deprecations - the main one

  • dbt-autofix deprecations: refactor YAML and SQL files to fix some deprecations
    • add --path <mypath> to configure the path of the dbt project (defaults to .)
    • add --dry-run for running in dry run mode
    • add --json to get resulting data in a JSONL format
    • add --json-schema-version v2.0.0-beta.4 to get the JSON schema from a specific Fusion release (by default we pick the latest)
    • add --select <path> to only select files in a given path (by default the tool will look at all files of the dbt project)
    • add --include-packages to also autofix the packages installed. Just note that those fixes will be reverted at the next dbt deps and the long term fix will be to update the packages to versions compatible with Fusion.
    • add --behavior-change to run the subset of fixes that would resolve deprecations that require a behavior change. Refer to the coverage tables above to determine which deprecations require behavior changes.

Each JSON object will have the following keys:

  • "mode": "applied" or "dry_run"
  • "file_path": the full path of the file modified. Each file will appear only once
  • "refactors": the list of refactoring rules applied

Calling deprecations without --dry-run should be safe if your dbt code is part of a git repo.

Please review the suggested changes to your dbt project before merging to main and make those changes go through your typical CI/CD process.

jobs

dbt-autofix jobs: update dbt platform jobs steps to use -s/--select selectors instead of -m/--models/--model which are deprecated in the Fusion engine

Run dbt-autofix jobs --help to see the required parameters and supported arguments.

This tool requires connecting to the dbt Admin API to retrieve and update jobs which means that the user token or service token used need to have Read and Write access to jobs

Running with --dry-run/d will output what changes would have been triggered without triggering them

Running with --behavior-changes will run the subset of fixes that would resolve deprecations that require a behavior change. Refer to the coverage tables above to determine which deprecations require behavior changes.

Using AGENTS.md

AGENTS.md is provided as a reference and starting place for those interested in using AI agents to assist them with migration work that dbt-autofix is not capable of resolving.

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