From 1d293337af7fa16e4f6bb59ba0d00f0e1cee5a40 Mon Sep 17 00:00:00 2001 From: Ruslan Kuprieiev Date: Thu, 22 Mar 2018 20:37:57 +0200 Subject: [PATCH] readme: convert from md to rst Signed-off-by: Ruslan Kuprieiev --- README.md | 79 -------------------------------- README.rst | 131 +++++++++++++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 131 insertions(+), 79 deletions(-) delete mode 100644 README.md create mode 100644 README.rst diff --git a/README.md b/README.md deleted file mode 100644 index 11413436c..000000000 --- a/README.md +++ /dev/null @@ -1,79 +0,0 @@ - -| Linux & Mac OS | Windows | Code quality | Unit-tests | -|-------------|---------------|--------------|------------| -|[![Build Status](https://travis-ci.org/dataversioncontrol/dvc.svg?branch=master)](https://travis-ci.org/dataversioncontrol/dvc)|[![Build status](https://ci.appveyor.com/api/projects/status/rnqygb4rp1tsjvhb/branch/master?svg=true)](https://ci.appveyor.com/project/dataversioncontrol/dvc/branch/master)|[![Code Climate](https://codeclimate.com/github/dataversioncontrol/dvc/badges/gpa.svg)](https://codeclimate.com/github/dataversioncontrol/dvc)|[![Test Coverage](https://codeclimate.com/github/dataversioncontrol/dvc/badges/coverage.svg)](https://codeclimate.com/github/dataversioncontrol/dvc)| - -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 config AWS.StoragePath mybucket/image_cnn`
`$ dvc push`| - -See more in [tutorial](https://blog.dataversioncontrol.com/data-version-control-tutorial-9146715eda46). - -# 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/dataversioncontrol/dvc/releases - -## Python Pip - -DVC could be installed via the Python Package Index (PyPI). - -```bash -pip install dvc -``` - -## Homebrew (Mac OS) - -### Formula: - -```bash -brew install dataversioncontrol/homebrew-dvc/dvc -``` - -### Cask: - -```bash -brew cask install dataversioncontrol/homebrew-dvc/dvc -``` - -# Links - -Website: https://dataversioncontrol.com - -Tutorial: https://blog.dataversioncontrol.com/data-version-control-tutorial-9146715eda46 - -Documentation: http://dataversioncontrol.com/docs/ - -Discussion: https://discuss.dataversioncontrol.com/ - -# Related technologies - -1. [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. -2. [Git-LFS](https://git-lfs.github.com/). -3. Makefile (and it's analogues). DVC tracks dependencies (DAG). -4. [Workflow Management Systems](https://en.wikipedia.org/wiki/Workflow_management_system). 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 and GCP storge are supported. - -# How DVC works - -![how_dvc_works](https://s3-us-west-2.amazonaws.com/dvc-share/images/0.9/how_dvc_works.png) - -# 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. - diff --git a/README.rst b/README.rst new file mode 100644 index 000000000..adc8a7b89 --- /dev/null +++ b/README.rst @@ -0,0 +1,131 @@ +.. role:: raw-html-m2r(raw) + :format: html + + +.. list-table:: + :header-rows: 1 + + * - Linux & Mac OS + - Windows + - Code quality + - Unit-tests + * - + .. image:: https://travis-ci.org/dataversioncontrol/dvc.svg?branch=master + :target: https://travis-ci.org/dataversioncontrol/dvc + :alt: Build Status + + - + .. image:: https://ci.appveyor.com/api/projects/status/rnqygb4rp1tsjvhb/branch/master?svg=true + :target: https://ci.appveyor.com/project/dataversioncontrol/dvc/branch/master + :alt: Build status + + - + .. image:: https://codeclimate.com/github/dataversioncontrol/dvc/badges/gpa.svg + :target: https://codeclimate.com/github/dataversioncontrol/dvc + :alt: Code Climate + + - + .. image:: https://codeclimate.com/github/dataversioncontrol/dvc/badges/coverage.svg + :target: https://codeclimate.com/github/dataversioncontrol/dvc + :alt: Test Coverage + + + +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 +=========== + +.. list-table:: + :header-rows: 1 + + * - Step + - Command + * - Track code and data together + - ``$ git add train.py`` :raw-html-m2r:`
` ``$ dvc add images.zip`` + * - Connect code and data by commands + - ``$ dvc run -d images.zip -o images/ unzip -q images.zip`` :raw-html-m2r:`
` ``$ dvc run -d images/ -d train.py -o model.p python train.py`` + * - Make changes and reproduce + - ``$ vi train.py`` :raw-html-m2r:`
` ``$ dvc repro model.p.dvc`` + * - Share code + - ``$ git add .`` :raw-html-m2r:`
` ``$ git commit -m 'The baseline model'`` :raw-html-m2r:`
` ``$ git push`` + * - Share data and ML models + - ``$ dvc config AWS.StoragePath mybucket/image_cnn`` :raw-html-m2r:`
` ``$ 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/dataversioncontrol/dvc/releases + +Python Pip +---------- + +DVC could be installed via the Python Package Index (PyPI). + +.. code-block:: bash + + pip install dvc + +Homebrew (Mac OS) +----------------- + +Formula: +^^^^^^^^ + +.. code-block:: bash + + brew install dataversioncontrol/homebrew-dvc/dvc + +Cask: +^^^^^ + +.. code-block:: bash + + brew cask install dataversioncontrol/homebrew-dvc/dvc + +Links +===== + +Website: https://dataversioncontrol.com + +Tutorial: https://blog.dataversioncontrol.com/data-version-control-tutorial-9146715eda46 + +Documentation: http://dataversioncontrol.com/docs/ + +Discussion: https://discuss.dataversioncontrol.com/ + +Related technologies +==================== + + +#. `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. +#. `Git-LFS `_. +#. Makefile (and it's analogues). DVC tracks dependencies (DAG). +#. `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 and GCP storge are supported. + +How DVC works +============= + + +.. image:: https://s3-us-west-2.amazonaws.com/dvc-share/images/0.9/how_dvc_works.png + :target: https://s3-us-west-2.amazonaws.com/dvc-share/images/0.9/how_dvc_works.png + :alt: how_dvc_works + + +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.