hangar 0.5.2
Hangar is version control for tensor data. Commit, branch, merge, revert, and collaborate in the data-defined software era.
License: Apache 2.0
Requires Python: >= 3.6.0

========
Overview
========

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    * - docs
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    * - tests
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        | |supported-versions| |supported-implementations|
        | |license|
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    :alt: Build Status
    :target: https://github.com/tensorwerk/hangar-py/actions?query=workflow%3A%22Run+Test+Suite%22+branch%3Amaster+event%3Apush+is%3Acompleted

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   :target: https://codecov.io/gh/tensorwerk/hangar-py

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   :alt: Language grade: Python
   :target: https://lgtm.com/projects/g/tensorwerk/hangar-py/context:python

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    :target: https://pypi.org/project/hangar

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   :alt: GitHub license
   :target: https://github.com/tensorwerk/hangar-py/blob/master/LICENSE

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   :target: https://anaconda.org/conda-forge/hangar

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    :target: https://pypi.org/project/hangar

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    :target: https://pypi.org/project/hangar

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    :alt: Supported implementations
    :target: https://pypi.org/project/hangar


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Hangar is version control for tensor data. Commit, branch, merge, revert, and
collaborate in the data-defined software era.

* Free software: Apache 2.0 license

What is Hangar?
===============

Hangar is based off the belief that too much time is spent collecting, managing,
and creating home-brewed version control systems for data. At it's core Hangar
is designed to solve many of the same problems faced by traditional code version
control system (ie. ``Git``), just adapted for numerical data:

* Time travel through the historical evolution of a dataset.
* Zero-cost Branching to enable exploratory analysis and collaboration
* Cheap Merging to build datasets over time (with multiple collaborators)
* Completely abstracted organization and management of data files on disk
* Ability to only retrieve a small portion of the data (as needed) while still
  maintaining complete historical record
* Ability to push and pull changes directly to collaborators or a central server
  (ie a truly distributed version control system)

The ability of version control systems to perform these tasks for codebases is
largely taken for granted by almost every developer today; However, we are
in-fact standing on the shoulders of giants, with decades of engineering which
has resulted in these phenomenally useful tools. Now that a new era of
"Data-Defined software" is taking hold, we find there is a strong need for
analogous version control systems which are designed to handle numerical data at
large scale... Welcome to Hangar!


The Hangar Workflow:

::

       Checkout Branch
              |
              ▼
     Create/Access Data
              |
              ▼
    Add/Remove/Update Samples
              |
              ▼
           Commit

Log Style Output:

.. code-block:: text

   *   5254ec (master) : merge commit combining training updates and new validation samples
   |\
   | * 650361 (add-validation-data) : Add validation labels and image data in isolated branch
   * | 5f15b4 : Add some metadata for later reference and add new training samples received after initial import
   |/
   *   baddba : Initial commit adding training images and labels


Learn more about what Hangar is all about at https://hangar-py.readthedocs.io/


Installation
============

Hangar is in early alpha development release!

::

    pip install hangar

Documentation
=============

https://hangar-py.readthedocs.io/


Development
===========

To run the all tests run::

    tox

Note, to combine the coverage data from all the tox environments run:

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    :widths: 10 90
    :stub-columns: 1

    - - Windows
      - ::

            set PYTEST_ADDOPTS=--cov-append
            tox

    - - Other
      - ::

            PYTEST_ADDOPTS=--cov-append tox