datalad-revolution 0.4.0

Revolutionary DataLad extension package

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This software is a DataLad extension that equips DataLad with alternative and additional core commands that are leaner and written specifically with enhanced cross-platform compatibility and speed in mind.

Note: There is no support for git-annex direct mode repositories. Users that previously relied on this mode, and Windows users in particular, are recommended to use git-annex V6 or V7 mode. DataLad can be instructed to always use this mode by running:

git config --global --add datalad.repo.version 6

Commands provided by this extension

• rev-status – like git status, but simpler and working with dataset hierarchies

• rev-save – a 2-in-1 replacement for save and add

• rev-create – a ~30% faster create

Additional base class functionality

• GitRepo.status()

• GitRepo.annexstatus()

• GitRepo.diff()

• GitRepo.save()

Installation

Before you install this package, please make sure that you install a recent version of git-annex. Afterwards, install the latest version of datalad-revolution from PyPi. It is recommended to use a dedicated virtualenv:

# create and enter a new virtual environment (optional)
virtualenv --system-site-packages --python=python3 ~/env/datalad
. ~/env/datalad/bin/activate

# install from PyPi
pip install datalad_revolution

Support

For general information on how to use or contribute to DataLad (and this extension), please see the DataLad website or the main GitHub project page. The documentation is found here: http://docs.datalad.org/projects/revolution

All bugs, concerns and enhancement requests for this software can be submitted here: https://github.com/datalad/datalad-revolution/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 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/

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).