Metadata-Version: 2.1
Name: datalad
Version: 0.12.6
Summary: data distribution geared toward scientific datasets
Home-page: UNKNOWN
Author: The DataLad Team and Contributors
Author-email: team@datalad.org
License: UNKNOWN
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                                                          Read me
        
        [![Travis tests status](https://secure.travis-ci.org/datalad/datalad.png?branch=master)](https://travis-ci.org/datalad/datalad) [![Build status](https://ci.appveyor.com/api/projects/status/github/datalad/datalad?branch=master&svg=true)](https://ci.appveyor.com/project/mih/datalad/branch/master) [![codecov.io](https://codecov.io/github/datalad/datalad/coverage.svg?branch=master)](https://codecov.io/github/datalad/datalad?branch=master) [![Documentation](https://readthedocs.org/projects/datalad/badge/?version=latest)](http://datalad.rtfd.org) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) [![GitHub release](https://img.shields.io/github/release/datalad/datalad.svg)](https://GitHub.com/datalad/datalad/releases/) [![PyPI version fury.io](https://badge.fury.io/py/datalad.svg)](https://pypi.python.org/pypi/datalad/) [![Testimonials 4](https://img.shields.io/badge/testimonials-4-brightgreen.svg)](https://github.com/datalad/datalad/wiki/Testimonials) [![https://www.singularity-hub.org/static/img/hosted-singularity--hub-%23e32929.svg](https://www.singularity-hub.org/static/img/hosted-singularity--hub-%23e32929.svg)](https://singularity-hub.org/collections/667) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3233911.svg)](https://doi.org/10.5281/zenodo.3233911)
        
        
        
        # 10000ft overview
        
        DataLad makes data management and data distribution more accessible.
        To do that, it stands on the shoulders of [Git] and [Git-annex] to deliver a
        decentralized system for data exchange. This includes automated ingestion of
        data from online portals and exposing it in readily usable form as Git(-annex)
        repositories, so-called datasets. The actual data storage and permission
        management, however, remains with the original data providers.
        
        The full documentation is available at http://docs.datalad.org and
        http://handbook.datalad.org provides a hands-on crash-course on DataLad.
        
        # Extensions
        
        A number of extensions are available that provide additional functionality for
        DataLad. Extensions are separate packages that are to be installed in addition
        to DataLad. In order to install DataLad customized for a particular domain, one
        can simply install an extension directly, and DataLad itself will be
        automatically installed with it. Here is a list of known extensions:
        
        - [crawler](https://github.com/datalad/datalad-crawler) -- tracking web resources and automated data distributions [![crawler release](https://img.shields.io/github/release/datalad/datalad-crawler.svg)](https://GitHub.com/datalad/datalad-crawler/releases/)
        - [neuroimaging](https://github.com/datalad/datalad-neuroimaging) -- neuroimaging research data and workflows [![neuroimaging release](https://img.shields.io/github/release/datalad/datalad-neuroimaging.svg)](https://GitHub.com/datalad/datalad-neuroimaging/releases/)
        - [container](https://github.com/datalad/datalad-container) -- support for containerized computational environments [![container release](https://img.shields.io/github/release/datalad/datalad-container.svg)](https://GitHub.com/datalad/datalad-container/releases/)
        
        - [webapp](https://github.com/datalad/datalad-webapp) -- support for exposing selected DataLad API as REST API webapp [tech demo]
        
        
        # Support
        
        The documentation of this project is found here:
        http://docs.datalad.org
        
        All bugs, concerns and enhancement requests for this software can be submitted here:
        https://github.com/datalad/datalad/issues
        
        If you have a problem or would like to ask a question about how to use DataLad,
        please [submit a question to
        NeuroStars.org](https://neurostars.org/new-topic?body=-%20Please%20describe%20the%20problem.%0A-%20What%20steps%20will%20reproduce%20the%20problem%3F%0A-%20What%20version%20of%20DataLad%20are%20you%20using%20%28run%20%60datalad%20--version%60%29%3F%20On%20what%20operating%20system%20%28consider%20running%20%60datalad%20plugin%20wtf%60%29%3F%0A-%20Please%20provide%20any%20additional%20information%20below.%0A-%20Have%20you%20had%20any%20luck%20using%20DataLad%20before%3F%20%28Sometimes%20we%20get%20tired%20of%20reading%20bug%20reports%20all%20day%20and%20a%20lil'%20positive%20end%20note%20does%20wonders%29&tags=datalad)
        with a ``datalad`` tag.  NeuroStars.org is a platform similar to StackOverflow
        but dedicated to neuroinformatics.
        
        All previous DataLad questions are available here:
        http://neurostars.org/tags/datalad/
        
        
        # Installation
        
        ## Debian-based systems
        
        On Debian-based systems, we recommend to enable [NeuroDebian] from which we
        provide recent releases of DataLad. Once enabled, just do:
        
            apt-get install datalad
        
        ## Other Linux'es via conda
        
            conda install -c conda-forge datalad
        
        will install released released version, and release candidates are available
        via
        
            conda install -c conda-forge/label/rc datalad
        
        ## Other Linux'es, OSX via pip
        
        Before you install this package, please make sure that you [install a recent
        version of git-annex](https://git-annex.branchable.com/install).  Afterwards,
        install the latest version of `datalad` from
        [PyPi](https://pypi.org/project/datalad). It is recommended to use
        a dedicated [virtualenv](https://virtualenv.pypa.io):
        
            # create and enter a new virtual environment (optional)
            virtualenv --python=python3 ~/env/datalad
            . ~/env/datalad/bin/activate
        
            # install from PyPi
            pip install datalad
        
        By default, installation via pip installs core functionality of datalad
        allowing for managing datasets etc.  Additional installation schemes
        are available, so you could provide enhanced installation via
        `pip install datalad[SCHEME]` where `SCHEME` could be
        
        - `tests`
             to also install dependencies used by unit-tests battery of the datalad
        - `full`
             to install all dependencies.
        
        There is also a [Singularity container](http://singularity.lbl.gov) available.
        The latest release version can be obtained by running:
        
            singularity pull shub://datalad/datalad
        
        More details on installation and initial configuration could be found in the
        [DataLad Handbook: Installation].
        
        # License
        
        MIT/Expat
        
        
        # Contributing
        
        See [CONTRIBUTING.md](CONTRIBUTING.md) if you are interested in internals or
        contributing to the project.
        
        
        ## Acknowledgements
        
        DataLad development is supported by a US-German collaboration in computational
        neuroscience (CRCNS) project "DataGit: converging catalogues, warehouses, and
        deployment logistics into a federated 'data distribution'" (Halchenko/Hanke),
        co-funded by the US National Science Foundation (NSF 1429999) and the German
        Federal Ministry of Education and Research (BMBF 01GQ1411). Additional support
        is provided by the German federal state of Saxony-Anhalt and the European
        Regional Development Fund (ERDF), Project: Center for Behavioral Brain
        Sciences, Imaging Platform.  This work is further facilitated by the ReproNim
        project (NIH 1P41EB019936-01A1).
        
        
        [Git]: https://git-scm.com
        [Git-annex]: http://git-annex.branchable.com
        [setup.py]: https://github.com/datalad/datalad/blob/master/setup.py
        [NeuroDebian]: http://neuro.debian.net
        
        [DataLad Handbook: Installation]: http://handbook.datalad.org/en/latest/intro/installation.html
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
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