dbt-osmosis
A dbt utility for managing YAML to make developing with dbt more delightful.
Decision gist · record as of 2026-08-14
Yes. dbt-osmosis is actively maintained, has low install friction, carries a permissive Apache-2.0 license, and solves a real pain point in dbt workflows—YAML management and documentation inheritance. It is well-suited for teams using dbt-core 1.8+ who want to reduce manual YAML maintenance and improve documentation consistency. Start with the core yaml commands; optional extras can be added later if needed.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10–3.13, dbt-core 1.8+, and a compatible dbt adapter in your environment.
- Low install friction with a pure-Python wheel.
- Actively maintained (released 2026-07-05, 40 days ago).
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most development and production workflows.
last release 2026-07-05 (40 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 149,686 downloads/mo, #10,989 on PyPI
Alternatives
Verify before relying
pip install dbt-osmosis
# Configure in dbt_project.yml:
# models:
# your_project_name:
# +dbt-osmosis: "_{model}.yml"
dbt-osmosis yaml refactor --dry-run --check- Whether all optional extras (workbench, duckdb, openai, azure, proxy) are production-ready or experimental.
- Specific adapter compatibility matrix beyond the dbt-core 1.8+ requirement.
- Performance characteristics on large dbt projects with many models and YAML files.
What it is and what it does
dbt-osmosis extends dbt development by automating schema YAML file organization, managing column-level documentation inheritance across dbt lineage, and providing ad-hoc SQL compilation and execution helpers. It ships as a CLI with a Python package interface, centered on four primary surfaces: schema YAML management (organize, document, refactor), documentation inheritance, SQL compile/run helpers, and an optional Streamlit workbench for interactive development. The tool also includes command families for generation, natural-language helpers, schema diffing, migration planning, validation, documentation analysis, SQL linting, and test suggestions.
The package depends on 13 runtime dependencies including dbt-core, dbt-common, dbt-core-interface, click, rich, sqlglot, pyyaml, and others. It targets Python 3.10–3.13 and requires dbt-core 1.8 or later with a compatible adapter. Optional extras unlock Streamlit workbench features, DuckDB adapter support, LLM-assisted synthesis, Azure AD authentication, and an experimental SQL proxy runtime. No known security vulnerabilities are recorded.
Use it for
- Automatically organize and refactor schema YAML files across a dbt project to maintain consistent structure and naming conventions.
- Inherit column-level documentation from upstream dbt models down the lineage to reduce documentation duplication.
- Compile and run ad-hoc SQL queries within dbt context without materializing models, for testing and exploration.
- Use the Streamlit workbench for interactive SQL development and model testing during dbt development cycles.
- Analyze documentation coverage and gaps across a dbt project to identify undocumented models and columns.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
dbt-osmosis is actively maintained, has low install friction, carries a permissive Apache-2.0 license, and solves a real pain point in dbt workflows—YAML management and documentation inheritance. It is well-suited for teams using dbt-core 1.8+ who want to reduce manual YAML maintenance and improve documentation consistency. Start with the core yaml commands; optional extras can be added later if needed.
Install
dbt-osmosis on PyPI
Before you install
Low install friction with a pure-Python wheel. Actively maintained (released 2026-07-05, 40 days ago). Requires dbt-core 1.8+ and a compatible adapter; the package intentionally leaves dbt-core unpinned to allow newer releases, though audited support covers dbt Core 1.8.x through 1.11.x.
Requires Python 3.10–3.13, dbt-core 1.8+, and a compatible dbt adapter in your environment.
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most development and production workflows.
Quickstart
pip install dbt-osmosis
# Configure in dbt_project.yml:
# models:
# your_project_name:
# +dbt-osmosis: "_{model}.yml"
dbt-osmosis yaml refactor --dry-run --checkVerify before relying
- Whether all optional extras (workbench, duckdb, openai, azure, proxy) are production-ready or experimental.
- Specific adapter compatibility matrix beyond the dbt-core 1.8+ requirement.
- Performance characteristics on large dbt projects with many models and YAML files.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release <3.14,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 13 packagesagateclickdbt-commondbt-core-interfacedbt-corepackagingpluggypyyamlrapidfuzzrichruamel-yamlsqlglottyping-extensions |
| Maintenance | Actively maintained 40 days since the last release |
| First released | |
| Downloads | 149,686 / month, #10,989 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: Software Development :: Build Tools |
Evidence: dbt_osmosis-1.5.0-py3-none-any.whl
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See also dbt-bigquery · dbt-adapters · dbt-postgres · dbt-autofix · dbt-fusion-package-tools · dbt-sqlserver · sqlfluff-templater-dbt · dbt-oracle · dbt-redshift · datacontract-cli