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.. image:: https://img.shields.io/travis/iterative/dvc/master.svg?label=Linux%20%26%20Mac%20OS
:target: https://travis-ci.org/iterative/dvc
.. image:: https://img.shields.io/appveyor/ci/iterative/dvc/master.svg?label=Windows
:target: https://ci.appveyor.com/project/iterative/dvc/branch/master
.. image:: https://codeclimate.com/github/iterative/dvc/badges/gpa.svg
:target: https://codeclimate.com/github/iterative/dvc
.. image:: https://codecov.io/gh/iterative/dvc/branch/master/graph/badge.svg
:target: https://codecov.io/gh/iterative/dvc
Data Science Version Control or DVC is an open source tool for data science projects.
It helps data scientists manage their code and data together in a simple form of Git-like commands.
Get started
===========
See details in `Get Started <https://dvc.org/doc/get-started>`_.
+-----------------------------------+-------------------------------------------------------------------+
| Step | Command |
+===================================+===================================================================+
| Track code and data together | | ``$ git add train.py`` |
| | | ``$ dvc add images.zip`` |
+-----------------------------------+-------------------------------------------------------------------+
| Connect code and data by commands | | ``$ dvc run -d images.zip -o images/ unzip -q images.zip`` |
| | | ``$ dvc run -d images/ -d train.py -o model.p python train.py`` |
+-----------------------------------+-------------------------------------------------------------------+
| Make changes and reproduce | | ``$ vi train.py`` |
| | | ``$ dvc repro model.p.dvc`` |
+-----------------------------------+-------------------------------------------------------------------+
| Share code | | ``$ git add .`` |
| | | ``$ git commit -m 'The baseline model'`` |
| | | ``$ git push`` |
+-----------------------------------+-------------------------------------------------------------------+
| Share data and ML models | | ``$ dvc remote add myremote s3://mybucket/image_cnn`` |
| | | ``$ dvc core.remote myremote`` |
| | | ``$ dvc push`` |
+-----------------------------------+-------------------------------------------------------------------+
Installation
============
It could be installed using ``pip``, Homebrew or an OS-specific package.
.. code-block:: bash
pip install dvc
Package
-------
Self-contained packages for Windows, Linux, Mac are available. The latest version of the packages can be found at
GitHub `releases page <https://github.com/iterative/dvc/releases>`_.
Homebrew
--------
.. code-block:: bash
brew install iterative/homebrew-dvc/dvc
or:
.. code-block:: bash
brew cask install iterative/homebrew-dvc/dvc
Related technologies
====================
#. `Git-annex <https://git-annex.branchable.com/>`_ - DVC uses the idea of storing the content of large files (that you
don't want to see in your Git repository) in a local key-value store and uses file hardlinks/symlinks instead of the
copying actual files.
#. `Git-LFS <https://git-lfs.github.com/>`_. - DVC is compatible with any remote storage (S3, Google Cloud, Azure, SSH,
etc). DVC utilizes reflinks or hardlinks to avoid copy operation on checkouts which makes much more efficient for
large data files.
#. Makefile (and it's analogues). DVC tracks dependencies (DAG).
#. `Workflow Management Systems <https://en.wikipedia.org/wiki/Workflow_management_system>`_. DVC is a workflow
management system designed specifically to manage machine learning experiments. DVC is built on top of Git.
DVC is compatible with Git for storing code and the dependency graph (DAG), but not data files cache.
To store and share data files cache DVC supports remotes - any cloud (S3, Azure, Google Cloud, etc) or any on-premise
network storage (via SSH, for example).
How DVC works
=============
.. image:: https://dvc.org/static/img/flow.png
:target: https://dvc.org/static/img/flow.png
:alt: how_dvc_works
Contributing
============
Contributions are welcome! Please see our `Contributing Guide <https://dvc.org/doc/user-guide/contributing/>`_ for more
details.
Copyright
=========
This project is distributed under the Apache license version 2.0 (see the LICENSE file in the project root).
By submitting a pull request for this project, you agree to license your contribution under the Apache license version
2.0 to this project.