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Git for data scientists - manage your code and data together

Project description

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Data 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

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

See more in tutorial.

Installation

Packages

Operating system dependent packages are the recommended way to install DVC. The latest version of the packages can be found at GitHub releases page: https://github.com/iterative/dvc/releases

Python Pip

DVC could be installed via the Python Package Index (PyPI).

pip install dvc

Homebrew (Mac OS)

Formula:

brew install iterative/homebrew-dvc/dvc

Cask:

brew cask install iterative/homebrew-dvc/dvc

How DVC works

how_dvc_works

Project details


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