Skip to main content

Git for data scientists - manage your code and data together

Project description

https://img.shields.io/travis/iterative/dvc/master.svg?label=Linux%20%26%20Mac%20OS https://img.shields.io/appveyor/ci/iterative/dvc/master.svg?label=Windows https://codeclimate.com/github/iterative/dvc/badges/gpa.svg https://codecov.io/gh/iterative/dvc/branch/master/graph/badge.svg

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


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

dvc-0.10.1-py2.py3-none-any.whl (59.3 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file dvc-0.10.1-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for dvc-0.10.1-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 4cf315f2f488396c9d73dc76c6a30cad10c2aad5eafe500a861cf688af1649a7
MD5 4fc01245e8f5d747b78e0b22f6b83372
BLAKE2b-256 c9c12f05f0de17001e7cb2afbe37fcca0b2ebc6d12915766f1e4b1015965f9b8

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page