Revolutionary DataLad extension package
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. Please see the extension documentation for a description on additional commands and functionality.
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 V7 mode. DataLad can be instructed to always use this mode by running:
git config --global --add datalad.repo.version 6
Command(s) currently provided by this extension
- rev-extract-metadata – new and improved dedicated command to run any and all of DataLad’s metadata extractors. Much improved versions of the core extractor implementations also ship with this extension.
- rev-aggregate-metadata – complete reimplementation of metadata aggregation, with stellar performance benefits, in particular on large dataset hierarchies.
- query-metadata – new command to specifically access the aggregated metadata present in a dataset, much faster and more predictable behavior than the metadata command in datalad-core.
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
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/
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).
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