Metadata-Version: 1.0
Name: datalad
Version: 0.9.0
Summary: data distribution geared toward scientific datasets
Home-page: UNKNOWN
Author: The DataLad Team and Contributors
Author-email: team@datalad.org
License: UNKNOWN
Description: ::
        
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                                                          Read me
        
        |Travis tests status| |codecov.io| |Documentation|
        
        The full documentation is available at: http://docs.datalad.org
        
        10000ft overview
        ================
        
        DataLad makes data management and data distribution more accessible. To
        do that it stands on the shoulders of `Git <https://git-scm.com>`__ and
        `Git-annex <http://git-annex.branchable.com>`__ 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.
        
        Status
        ======
        
        DataLad is under rapid development. While the code base is still
        growing, the focus is increasingly shifting towards robust and safe
        operation with a sensible API. Organization and configuration are still
        subject of considerable reorganization and standardization. However,
        DataLad is, in fact, usable today and user feedback is always welcome.
        
        Support
        =======
        
        `Neurostars <https://neurostars.org>`__ is the preferred venue for
        DataLad support. Forum login is possible with your existing Google,
        Twitter, or GitHub account. Before posting a `new
        topic <https://neurostars.org/new-topic?tags=datalad>`__, please check
        the `previous posts <https://neurostars.org/search?q=tags%3Adatalad>`__
        tagged with ``#datalad``. To get help on a datalad-related issue, please
        consider to follow this `message
        template <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>`__.
        
        DataLad 101
        ===========
        
        A growing number of datasets is made available from
        http://datasets.datalad.org . Those datasets are just regular
        git/git-annex repositories organized into a hierarchy using git
        submodules mechanism. So you can use regular git/git-annex commands to
        work with them, but might need ``datalad`` to be installed to provide
        additional functionality (e.g., fetching from portals requiring
        authentication such as CRCNS, HCP; or accessing data originally
        distributed in tarballs). But datalad aims to provide higher level
        interface on top of git/git-annex to simplify consumption and sharing of
        new or derived datasets. To that end, you can install **all** of those
        datasets using
        
        ::
        
            datalad install -r ///
        
        which will ``git clone`` all of those datasets under
        ``datasets.datalad.org`` sub-directory. This command will not fetch any
        large data files, but will merely recreate full hierarchy of all of
        those datasets locally, which also takes a good chunk of your filesystem
        meta-data storage. Instead of fetching all datasets at once you could
        either specify specific dataset to be installed, e.g.
        
        ::
        
            datalad install ///openfmri/ds000113
        
        or install top level dataset by omitting ``-r`` option and then calling
        ``datalad install`` for specific sub-datasets you want to have
        installed, possibly with ``-r`` to install their sub-datasets as well,
        e.g.
        
        ::
        
            datalad install ///
            cd datasets.datalad.org
            datalad install -r openfmri/ds000001 indi/fcon1000
        
        You can navigate datasets you have installed in your terminal or
        browser, while fetching necessary files or installing new sub-datasets
        using the ``datalad get [FILE|DIR]`` command. DataLad will take care
        about downloading, extracting, and possibly authenticating (would ask
        you for credentials) in a uniform fashion regardless of the original
        data location or distribution serialization (e.g., a tarball). Since it
        is using git and git-annex underneath, you can be assured that you are
        getting **exact** correct version of the data.
        
        Use-cases DataLad covers are not limited to "consumption" of data.
        DataLad aims also to help publishing original or derived data, thus
        facilitating more efficient data management when collaborating or simply
        sharing your data. You can find more documentation at
        http://docs.datalad.org .
        
        Contributing
        ============
        
        See `CONTRIBUTING.md <CONTRIBUTING.md>`__ if you are interested in
        internals or contributing to the project.
        
        Installation
        ============
        
        Debian-based systems
        --------------------
        
        On Debian-based systems we recommend to enable
        `NeuroDebian <http://neuro.debian.net>`__ from which we provide recent
        releases of DataLad. datalad package recommends some relatively heavy
        packages (e.g. scrapy) which are useful only if you are interested in
        using ``crawl`` functionality. If you need just the base functionality
        of the datalad, install without recommended packages (e.g.,
        ``apt-get install --no-install-recommends datalad``)
        
        Other Linux'es, OSX (Windows yet TODO) via pip
        ----------------------------------------------
        
        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
        
        -  ``crawl`` to also install ``scrapy`` which is used in some crawling
           constructs
        -  ``tests`` to also install dependencies used by unit-tests battery of
           the datalad
        -  ``full`` to install all dependencies.
        
        For installation through ``pip`` you would need some external
        dependencies not shipped from it (e.g. ``git-annex``, etc.) for which
        please refer to the next section.
        
        Dependencies
        ------------
        
        Our
        `setup.py <https://github.com/datalad/datalad/blob/master/setup.py>`__
        and accompanying packaging describe all necessary dependencies. On
        Debian-based systems we recommend to enable
        `NeuroDebian <http://neuro.debian.net>`__ since we use it to provide
        backports of recent fixed external modules we depend upon, and
        up-to-date `Git-annex <http://git-annex.branchable.com>`__ is necessary
        for proper operation of DataLad packaged (install
        ``git-annex-standalone`` from NeuroDebian repository). Additionally, if
        you would like to develop and run our tests battery see
        `CONTRIBUTING.md <CONTRIBUTING.md>`__ regarding additional dependencies.
        
        Later we will provide bundled installations of DataLad across popular
        platforms.
        
        License
        =======
        
        MIT/Expat
        
        Disclaimer
        ==========
        
        It is in a alpha stage -- **nothing** is set in stone yet -- but already
        usable in a limited scope.
        
        .. |Travis tests status| image:: https://secure.travis-ci.org/datalad/datalad.png?branch=master
           :target: https://travis-ci.org/datalad/datalad
        .. |codecov.io| image:: https://codecov.io/github/datalad/datalad/coverage.svg?branch=master
           :target: https://codecov.io/github/datalad/datalad?branch=master
        .. |Documentation| image:: https://readthedocs.org/projects/datalad/badge/?version=latest
           :target: http://datalad.rtfd.org
        
Platform: UNKNOWN
