dbt-fusion-package-tools
Add your description here
Decision gist · record as of 2026-08-14
Yes, if you maintain dbt projects and need to migrate to Fusion. Install friction is low, maintenance is active, and there are no known vulnerabilities. License treatment is unclear (no SPDX or raw license declared), so verify licensing before use in proprietary codebases. The package is narrowly scoped to a specific dbt workflow; install only if you actually need Fusion compatibility upgrades.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later (supports up to <3.14).
- Expects a dbt project directory containing packages.yml or dependencies.yml with at least one package dependency.
- Low friction: pure Python wheel with seven common runtime dependencies (click, typer, requests, rich, pyyaml, mashumaro, dbt-protos).
License · maintenance · safety
(unclear)
last release 2026-07-31 (14 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 401,757 downloads/mo, #6,923 on PyPI
Alternatives
Verify before relying
pip install dbt-fusion-package-tools
from dbt_fusion_package_tools.main import upgrade_packages
upgrade_packages(path='/path/to/dbt/project', dry_run=True)- Whether the package hub cache (fusion_version_compatibility_output.py) is included in the distribution or must be fetched separately.
- Support status for private dbt packages, as the description notes this as an open TODO.
- Whether dry-run mode actually prevents file writes or only prints proposed changes.
What it is and what it does
dbt-fusion-package-tools is a CLI and library for automatically upgrading dbt package dependencies to versions compatible with dbt Fusion. It reads packages.yml or dependencies.yml from a dbt project, cross-references each package against a local cache of Fusion compatibility data (built from hub.getdbt.com), identifies which versions need updating, and rewrites the version strings in the original file while preserving formatting and comments.
The package centers on four classes: DbtPackageFile (represents a dependency manifest), DbtPackage (a single dependency), DbtPackageVersion (a specific release), and DbtPackageTextFile (preserves raw file layout during rewrites). It includes helper scripts to download package hub data and compute Fusion compatibility matrices, though these are primarily used offline to generate a cached compatibility index. The upgrade workflow is designed to be fast and resilient by avoiding repeated network calls to the package hub.
Use it for
- Bulk-upgrade all packages in an existing dbt project to Fusion-compatible versions without manual version lookup.
- Dry-run package upgrades to preview changes before committing them to packages.yml.
- Integrate package compatibility checking into CI/CD pipelines to catch incompatible versions early.
- Migrate legacy dbt projects to Fusion by automating the dependency version audit and rewrite step.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you maintain dbt projects and need to migrate to Fusion.
Install friction is low, maintenance is active, and there are no known vulnerabilities. License treatment is unclear (no SPDX or raw license declared), so verify licensing before use in proprietary codebases. The package is narrowly scoped to a specific dbt workflow; install only if you actually need Fusion compatibility upgrades.
Install
dbt-fusion-package-tools on PyPI
Before you install
Low friction: pure Python wheel with seven common runtime dependencies (click, typer, requests, rich, pyyaml, mashumaro, dbt-protos). Active maintenance with a release 14 days ago.
Requires Python 3.10 or later (supports up to <3.14). Expects a dbt project directory containing packages.yml or dependencies.yml with at least one package dependency.
Quickstart
pip install dbt-fusion-package-tools
from dbt_fusion_package_tools.main import upgrade_packages
upgrade_packages(path='/path/to/dbt/project', dry_run=True)Verify before relying
- Whether the package hub cache (fusion_version_compatibility_output.py) is included in the distribution or must be fetched separately.
- Support status for private dbt packages, as the description notes this as an open TODO.
- Whether dry-run mode actually prevents file writes or only prints proposed changes.
Package facts
| License | Not declared unclear |
| Python support | Supports the current Python release <3.14,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 7 packagesclickdbt-protosmashumaropyyamlrequestsrichtyper |
| Maintenance | Actively maintained 14 days since the last release |
| First released | |
| Downloads | 401,757 / month, #6,923 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: dbt_fusion_package_tools-0.21.6-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “dbt package version upgrade”
- dbt-fusion-package-toolsUpgrades dbt package dependencies to versions compatible with dbt…
- dbt-autofixdbt-autofix scans dbt projects for deprecated configurations and…
- oslo.upgradecheckProvides a framework for writing and running upgrade checks in…
Give your agent the search over MCP, or paste the wish link into any chat.
More Build Tools packages
Provides reusable utilities for Python packaging interoperability, including version handling, specifiers, markers, requirements, tags, and metadata parsing according to standards like PEP 440 and PEP 425.
Wraps any iterable to display a real-time progress bar in the terminal or Jupyter notebook, showing iteration count, elapsed time, and estimated time remaining.
pip is the standard installer for Python packages, enabling you to download and install packages from the Python Package Index and other indexes into your Python environment.
Hatchling is a standards-compliant Python build backend that handles packaging, metadata, and distribution of Python projects when configured in a project's pyproject.toml file.
Generates Python gRPC service stubs and message classes from Protocol Buffer definitions, enabling developers to build gRPC clients and servers.
pre-commit is a framework for installing and running git hooks written in any language before commits are made, automating code quality and validation checks across multi-language projects.
Install it if your team needs consistent, automated validation at commit time.
See also dbt-autofix · dbt-osmosis · dbt-metricflow · dbt-sqlserver · dbt-fabric · dbt-core-experimental-parser · cube_dbt · dbt-state · dbt-coverage · cognite-toolkit