PyPI 官网下载 | datalad-0.13.6.tar.gz

____ _ _ _ | _ \ __ _ | |_ __ _ | | __ _ __| | | | | | / _` | | __| / _` | | | / _` | / _` | | |_| | | (_| | | |_ | (_| | | |___ | (_| | | (_| | |____/ \__,_| \__| \__,_| |_____| \__,_| \__,_| Read me [](https://travis-ci.org/datalad/datalad) [](https://ci.appveyor.com/project/mih/datalad/branch/master) [](https://codecov.io/github/datalad/datalad?branch=master) [](http://datalad.rtfd.org) [](https://opensource.org/licenses/MIT) [](https://GitHub.com/datalad/datalad/releases/) [](https://pypi.python.org/pypi/datalad/) [](https://pypi.org/project/datalad/) [](https://github.com/datalad/datalad/wiki/Testimonials) [](https://singularity-hub.org/collections/667) [](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. An [annotated list of extensions](http://handbook.datalad.org/extension_pkgs.html) is available in the [DataLad handbook](http://handbook.datalad.org). # 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