111

GitHub - iterative/dvc: Data Science Version Control - Git for data scientists

 5 years ago
source link: https://github.com/iterative/dvc
Go to the source link to view the article. You can view the picture content, updated content and better typesetting reading experience. If the link is broken, please click the button below to view the snapshot at that time.

README.rst

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 68747470733a2f2f636f6465636c696d6174652e636f6d2f6769746875622f6974657261746976652f6476632f6261646765732f6770612e737667 68747470733a2f2f636f6465636f762e696f2f67682f6974657261746976652f6476632f6272616e63682f6d61737465722f67726170682f62616467652e737667

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

Links

Website: https://dvc.org

Tutorial: https://dvc.org/doc/tutorial

Documentation: http://dvc.org/doc

Discussion: https://discuss.dvc.org/

Related technologies

  1. Git-annex - 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.
  2. Git-LFS.
  3. Makefile (and it's analogues). DVC tracks dependencies (DAG).
  4. Workflow Management Systems. DVC is workflow management system designed specificaly to manage machine learning experiments. DVC was built on top of Git.

DVC is compatible with Git for storing code and the dependency graph (DAG), but not data files cache. Data files caches can be transferred separately - now data cache transfer throught AWS S3, Azure Blob Storage and GCP storge are supported.

How DVC works

how_dvc_works

Contributing

Contributions are welcome! Please see our Contributing Guide 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.


About Joyk


Aggregate valuable and interesting links.
Joyk means Joy of geeK