Package: datalad Version: 0.7.0-2~nd100+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 98 Depends: neurodebian-popularity-contest, python-argcomplete, python-datalad (= 0.7.0-2~nd100+1), python:any Homepage: http://datalad.org Priority: optional Section: science Filename: pool/main/d/datalad/datalad_0.7.0-2~nd100+1_all.deb Size: 66286 SHA256: 4b5babb074a4688a19c483255b2bca4655041c7097037f865b1faa051a36fe85 SHA1: 6c9587036437c32d1d64d04025cfe0045b1d0830 MD5sum: 6b8979d628b568fdcbb1f17a8d9f49ea Description: data files crawler and data distribution DataLad is a data distribution providing access to a wide range of data resources already available online (initially aiming at neuroscience domain). Using git-annex as its backend for data logistics it provides following facilities . - crawling of web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc - command line interface for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get), as well as search within aggregated meta-data . This package provides the command line tool. Install without Recommends if you need only core functionality. Package: nuitka Version: 0.5.26.4+ds-1~nd100+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3461 Depends: neurodebian-popularity-contest, gcc (>= 5.0) | g++ (>= 4.4) | clang (>= 3.0), scons (>= 2.0.0), python-dev (>= 2.6.6-2), python:any (>= 2.7.5-5~) Recommends: python-lxml (>= 2.3), python-pyqt5, strace, chrpath Suggests: ccache Homepage: http://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.5.26.4+ds-1~nd100+1_all.deb Size: 683878 SHA256: 975a385b58daec07bee9c2782221b94a245474647ea72a763999ff36e54f5e2d SHA1: 7f68313131ebb516d9814a69c7046a77bca1cc76 MD5sum: 4c75d70c942c58d3092c74e2b515881b Description: Python compiler with full language support and CPython compatibility This Python compiler achieves full language compatibility and compiles Python code into compiled objects that are not second class at all. Instead they can be used in the same way as pure Python objects. Package: python-datalad Source: datalad Version: 0.7.0-2~nd100+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3650 Depends: neurodebian-popularity-contest, git-annex (>= 6.20160808~) | git-annex-standalone (>= 6.20160808~), patool, python-appdirs, python-git (>= 2.1~), python-github, python-humanize, python-iso8601, python-keyrings.alt | python-keyring (<= 8), python-secretstorage | python-keyring (<< 9.2), python-keyring, python-mock, python-msgpack, python-pyld, python-requests, python-tqdm, python-simplejson, python-six (>= 1.8.0), python-wrapt, python-boto, python-jsmin, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: python-html5lib, python-httpretty, python-nose, python-numpy, python-requests-ftp, python-scrapy, python-vcr, python-yaml Suggests: python-bs4 Provides: python2.7-datalad Homepage: http://datalad.org Priority: optional Section: python Filename: pool/main/d/datalad/python-datalad_0.7.0-2~nd100+1_all.deb Size: 707520 SHA256: afc01141c5d52675a8e324df201745562f90a7c0bc60d06b06ef90346638491b SHA1: 5e5d058b091b8324853ff26f630f8a31b31b4393 MD5sum: 9135212fc9154b6cf61180b027419ae6 Description: data files crawler and data distribution (Python 2) DataLad is a data distribution providing access to a wide range of data resources already available online (initially aiming at neuroscience domain). Using git-annex as its backend for data logistics it provides following facilities . - crawling of web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc - command line interface for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get), as well as search within aggregated meta-data . This package installs the module for Python 2, and Recommends install all dependencies necessary for crawling, publishing, and testing. If you need base functionality, install without Recommends.