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Overview
🦉 Data Versioning and ML Experiments
Capability facts
- CLI
- CLI entrypoint
Source: pyproject.toml:[project.scripts] · Jul 11, 2026
- Languages
- python
Source: github.language+pyproject.toml · Jul 11, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Jul 11, 2026)
|CI| |Python Version| |Coverage| |VS Code| |DOI|Source link
Source: README excerpt (regex_v1, Jul 11, 2026)
• `VS Code Extension`_Source link
Tags
README
|Banner|
Website <https://dvc.org>_
• Docs <https://dvc.org/doc>_
• Blog <http://blog.dataversioncontrol.com>_
• Tutorial <https://dvc.org/doc/get-started>_
• Related Technologies <https://dvc.org/doc/user-guide/related-technologies>_
• How DVC works_
• VS Code Extension_
• Installation_
• Contributing_
• Community and Support_
|CI| |Python Version| |Coverage| |VS Code| |DOI|
|PyPI| |PyPI Downloads| |Packages| |Brew| |Conda| |Choco| |Snap|
|
Data Version Control or DVC is a command line tool and VS Code Extension_ to help you develop reproducible machine learning projects:
#. Version your data and models. Store them in your cloud storage but keep their version info in your Git repo.
#. Iterate fast with lightweight pipelines. When you make changes, only run the steps impacted by those changes.
#. Track experiments in your local Git repo (no servers needed).
#. Compare any data, code, parameters, model, or performance plots.
#. Share experiments and automatically reproduce anyone's experiment.
Quick start
Please read our `Command Reference <https://dvc.org/doc/command-reference>`_ for a complete list.
A common CLI workflow includes:
+-----------------------------------+----------------------------------------------------------------------------------------------------+
| Task | Terminal |
+===================================+====================================================================================================+
| Track data | | $ git add train.py params.yaml |
| | | $ dvc add images/ |
+-----------------------------------+----------------------------------------------------------------------------------------------------+
| Connect code and data | | $ dvc stage add -n featurize -d images/ -o features/ python featurize.py |
| | | $ dvc stage add -n train -d features/ -d train.py -o model.p -M metrics.json python train.py |
+-----------------------------------+----------------------------------------------------------------------------------------------------+
| Make changes and experiment | | $ dvc exp run -n exp-baseline |
| | | $ vi train.py |
| | | $ dvc exp run -n exp-code-change |
+-----------------------------------+----------------------------------------------------------------------------------------------------+
| Compare and select experiments | | $ dvc exp show |
| | | $ dvc exp apply exp-baseline |
+-----------------------------------+----------------------------------------------------------------------------------------------------+
| Share code | | $ git add . |
| | | $ git commit -m 'The baseline model' |
| | | $ git push |
+-----------------------------------+-------------------------------------------------------------------------------------