gto
Version and deploy your models following GitOps principles
Decision gist · record as of 2026-08-14
Yes, if you need Git-native artifact versioning and lifecycle management for CI/CD workflows. The package is actively maintained, has low install friction, carries no vulnerabilities, and integrates well with DVC-based ML pipelines. Pre-Alpha status means the API may change, but the core functionality is stable enough for production use in teams already using Git as their source of truth.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later and a Git repository to operate on.
- Low friction: pure Python wheel with 10 runtime dependencies including click, pydantic, and ruamel.yaml.
- Active maintenance with a release 36 days ago and recent commits; requires Python 3.10 or later.
License · maintenance · safety
Apache License 2.0 (permissive) — Apache License 2.0 is permissive; you can use, modify, and distribute this package freely in commercial and private projects provided you include the license notice.
last release 2026-07-09 (36 days) · last repo commit 2026-08-09 · 161 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 2,058,805 downloads/mo, #3,333 on PyPI
Alternatives
Verify before relying
pip install gto
from gto import api
# Create a Git tag for artifact versioning
api.assign("path/to/repo", "artifact-name", "v1.0.0", "stage-name")- Whether the Python API is fully documented or primarily a CLI tool.
- Integration requirements or configuration needed to connect with DVC or other CI/CD systems.
- Performance characteristics when managing large numbers of tags or artifacts.
What it is and what it does
GTO is a command-line and Python tool that transforms a Git repository into an artifact registry by managing annotated Git tags in a standard format. It lets you track artifact versions, define lifecycle stages (like 'staging' or 'production'), and emit signals that trigger CI/CD automation when versions change or stages are updated. The tool works by creating and reading Git tags rather than maintaining a separate database, making it lightweight and Git-native.
The package is designed to work alongside DVC and serves as a backbone for Git-based model registries in systems like Iterative Studio. It has 10 runtime dependencies including click for CLI handling, pydantic for data validation, and ruamel.yaml for configuration. The codebase is actively maintained, supports Python 3.10 through 3.14, and carries no known security vulnerabilities.
Use it for
- Track model versions and their deployment status across environments using Git tags as the source of truth.
- Automate CI/CD pipelines to deploy new artifact versions when lifecycle stages are updated (e.g., promoting from staging to production).
- Manage release readiness by marking artifacts with stages that indicate their consumption status for specific environments.
- Integrate with DVC-based ML workflows to maintain a Git-native model registry without external infrastructure.
- Signal downstream systems about artifact changes without polling, using Git tags as events.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need Git-native artifact versioning and lifecycle management for CI/CD workflows.
The package is actively maintained, has low install friction, carries no vulnerabilities, and integrates well with DVC-based ML pipelines. Pre-Alpha status means the API may change, but the core functionality is stable enough for production use in teams already using Git as their source of truth.
Install
gto on PyPI
Before you install
Low friction: pure Python wheel with 10 runtime dependencies including click, pydantic, and ruamel.yaml. Active maintenance with a release 36 days ago and recent commits; requires Python 3.10 or later.
Requires Python 3.10 or later and a Git repository to operate on.
License in practice
Apache License 2.0 is permissive; you can use, modify, and distribute this package freely in commercial and private projects provided you include the license notice.
Quickstart
pip install gto
from gto import api
# Create a Git tag for artifact versioning
api.assign("path/to/repo", "artifact-name", "v1.0.0", "stage-name")Verify before relying
- Whether the Python API is fully documented or primarily a CLI tool.
- Integration requirements or configuration needed to connect with DVC or other CI/CD systems.
- Performance characteristics when managing large numbers of tags or artifacts.
Package facts
| License | Apache License 2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 10 packagesclickentrypointsfuncypydanticpydantic-settingsrichruamel.yamlscmreposemvertabulate |
| Maintenance | Actively maintained 36 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 2,058,805 / month, #3,333 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 2 - Pre-AlphaProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14 |
Evidence: gto-1.10.1-py3-none-any.whl
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See also google-cloud-artifact-registry · gitman · setuptools-scm-git-archive · azure-containerregistry · keyrings.google-artifactregistry-auth · release-tag · autosemver · dvc · mkdocs-auto-tag-plugin · abx-plugins