Package: datalad Version: 0.8.1-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 100 Depends: neurodebian-popularity-contest, python-argcomplete, python-datalad (= 0.8.1-1~nd16.10+1), python:any Homepage: http://datalad.org Priority: optional Section: science Filename: pool/main/d/datalad/datalad_0.8.1-1~nd16.10+1_all.deb Size: 68100 SHA256: f8f847ae6d336575af357c7beb3408eeff75390cf06131fa02e9bb0a130ffc9c SHA1: 3e6a0542b81491e474353fb4b71bfe72faf1f547 MD5sum: c39eb86285792e2c44a9f16d9ad406f2 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: fail2ban Version: 0.9.7-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1274 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), init-system-helpers (>= 1.18~), lsb-base (>= 2.0-7) Recommends: python, iptables, whois, python3-pyinotify, python3-systemd Suggests: mailx, system-log-daemon, monit Homepage: http://www.fail2ban.org Priority: optional Section: net Filename: pool/main/f/fail2ban/fail2ban_0.9.7-1~nd16.10+1_all.deb Size: 262474 SHA256: 3ea30f6147b8c438449464618578f6f78a21c6aaae0e19f07eb8f7989a038d7a SHA1: eeaf48d38df1199ce608de4d13ba5228d8d74566 MD5sum: ba602683afe5185db86aeb4d4c7c226b Description: ban hosts that cause multiple authentication errors Fail2ban monitors log files (e.g. /var/log/auth.log, /var/log/apache/access.log) and temporarily or persistently bans failure-prone addresses by updating existing firewall rules. Fail2ban allows easy specification of different actions to be taken such as to ban an IP using iptables or hostsdeny rules, or simply to send a notification email. . By default, it comes with filter expressions for various services (sshd, apache, qmail, proftpd, sasl etc.) but configuration can be easily extended for monitoring any other text file. All filters and actions are given in the config files, thus fail2ban can be adopted to be used with a variety of files and firewalls. Following recommends are listed: . - iptables -- default installation uses iptables for banning. You most probably need it - whois -- used by a number of *mail-whois* actions to send notification emails with whois information about attacker hosts. Unless you will use those you don't need whois - python3-pyinotify -- unless you monitor services logs via systemd, you need pyinotify for efficient monitoring for log files changes Package: git-annex-remote-rclone Version: 0.5-1~ndall+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23 Depends: neurodebian-popularity-contest, git-annex | git-annex-standalone, rclone Homepage: https://github.com/DanielDent/git-annex-remote-rclone Priority: optional Section: utils Filename: pool/main/g/git-annex-remote-rclone/git-annex-remote-rclone_0.5-1~ndall+1_all.deb Size: 7842 SHA256: 0b1d65c740ce1073ecdae6db121d304fe02c4bb95df552326894118a65b38319 SHA1: 34a2323c4387e61c4a69617150c463f9a7b772c5 MD5sum: 00c5a0407a998eba72d4f5eb0ad71189 Description: rclone-based git annex special remote This is a wrapper around rclone to make any destination supported by rclone usable with git-annex. . Cloud storage providers supported by rclone currently include: * Google Drive * Amazon S3 * Openstack Swift / Rackspace cloud files / Memset Memstore * Dropbox * Google Cloud Storage * Microsoft One Drive * Hubic * Backblaze B2 * Yandex Disk . Note: although Amazon Cloud Drive support is implemented, it is broken ATM see https://github.com/DanielDent/git-annex-remote-rclone/issues/22 . Package: golang-github-ncw-rclone-dev Source: rclone Version: 1.36-1~ndall0 Architecture: all Maintainer: Debian Go Packaging Team Installed-Size: 1198 Depends: golang-bazil-fuse-dev, golang-github-aws-aws-sdk-go-dev, golang-github-mreiferson-go-httpclient-dev, golang-github-ncw-go-acd-dev, golang-github-ncw-swift-dev, golang-github-pkg-errors-dev, golang-github-rfjakob-eme-dev, golang-github-skratchdot-open-golang-dev, golang-github-spf13-cobra-dev, golang-github-spf13-pflag-dev, golang-github-stacktic-dropbox-dev, golang-github-stretchr-testify-dev, golang-github-tsenart-tb-dev, golang-github-unknwon-goconfig-dev, golang-github-vividcortex-ewma-dev, golang-golang-x-crypto-dev, golang-golang-x-net-dev, golang-golang-x-oauth2-google-dev, golang-golang-x-sys-dev, golang-golang-x-text-dev, golang-google-api-dev Built-Using: go-md2man (= 1.0.6+ds-1), golang-1.7 (= 1.7.4-2), golang-bazil-fuse (= 0.0~git20160811.0.371fbbd-2), golang-blackfriday (= 1.4+git20161003.40.5f33e7b-1), golang-github-aws-aws-sdk-go (= 1.1.14+dfsg-2), golang-github-davecgh-go-spew (= 1.1.0-1), golang-github-go-ini-ini (= 1.8.6-2), golang-github-google-go-querystring (= 0.0~git20151028.0.2a60fc2-1), golang-github-jmespath-go-jmespath (= 0.2.2-2), golang-github-kr-fs (= 0.0~git20131111.0.2788f0d-2), golang-github-ncw-go-acd (= 0.0~git20161119.0.7954f1f-1), golang-github-ncw-swift (= 0.0~git20160617.0.b964f2c-2), golang-github-pkg-errors (= 0.8.0-1), golang-github-pkg-sftp (= 0.0~git20160930.0.4d0e916-1), golang-github-pmezard-go-difflib (= 1.0.0-1), golang-github-rfjakob-eme (= 1.0-2), golang-github-shurcool-sanitized-anchor-name (= 0.0~git20160918.0.1dba4b3-1), golang-github-skratchdot-open-golang (= 0.0~git20160302.0.75fb7ed-2), golang-github-spf13-cobra (= 0.0~git20161229.0.1dd5ff2-1), golang-github-spf13-pflag (= 0.0~git20161024.0.5ccb023-1), golang-github-stacktic-dropbox (= 0.0~git20160424.0.58f839b-2), golang-github-tsenart-tb (= 0.0~git20151208.0.19f4c3d-2), golang-github-unknwon-goconfig (= 0.0~git20160828.0.5aa4f8c-3), golang-github-vividcortex-ewma (= 0.0~git20160822.20.c595cd8-3), golang-go.crypto (= 1:0.0~git20170407.0.55a552f+REALLY.0.0~git20161012.0.5f31782-1), golang-golang-x-net-dev (= 1:0.0+git20161013.8b4af36+dfsg-3), golang-golang-x-oauth2 (= 0.0~git20161103.0.36bc617-4), golang-golang-x-sys (= 0.0~git20161122.0.30237cf-1), golang-google-api (= 0.0~git20161128.3cc2e59-2), golang-google-cloud (= 0.5.0-2), golang-testify (= 1.1.4+ds-1), golang-x-text (= 0.0~git20161013.0.c745997-2) Homepage: https://github.com/ncw/rclone Priority: extra Section: devel Filename: pool/main/r/rclone/golang-github-ncw-rclone-dev_1.36-1~ndall0_all.deb Size: 201776 SHA256: 88274c394a26a9f8f5f4766873acde54192537112e0f0e24ddfff1b9a5361f7c SHA1: fb44d37c3df4bdf641c85720b35bbfd835870a05 MD5sum: fdc9cfc7b0a9e18cdc83ed2fbce61433 Description: go source code of rclone Rclone is a program to sync files and directories between the local file system and a variety of commercial cloud storage providers. . This package contains rclone's source code. Package: nuitka Version: 0.5.27+ds-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3568 Depends: neurodebian-popularity-contest, gcc (>= 5.0) | g++ (>= 4.4) | clang (>= 3.0), scons (>= 2.0.0), python-appdirs | base-files (<< 7.2), python3-appdirs | base-files (<< 7.2), 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_0.5.27+ds-1~nd16.10+1_all.deb Size: 701180 SHA256: 663020060aff9a755f28ae904c2cc5c4531be086bd0c9c69227dada4f5cc364b SHA1: de1aa9672435fd873cfd0a3219ceb4ce7c28aaa9 MD5sum: f6998c0334b763ffe2eebd5c82595cee 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: prov-tools Source: python-prov Version: 1.5.0-1+nd1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24 Depends: neurodebian-popularity-contest, python3:any (>= 3.3~), python3-prov (= 1.5.0-1+nd1~nd16.10+1) Homepage: https://github.com/trungdong/prov Priority: optional Section: utils Filename: pool/main/p/python-prov/prov-tools_1.5.0-1+nd1~nd16.10+1_all.deb Size: 6940 SHA256: 24cc27ea014089213c4668f054cf05b518abe716d3c75e085f5acd4afa03711b SHA1: 55ceb639983a7137745ea53e7e91f7a0d664c6e6 MD5sum: 78a7ae5487e90461130569cbb4589fa6 Description: tools for prov A library for W3C Provenance Data Model supporting PROV-JSON and PROV- XML import/export. . Features: - An implementation of the W3C PROV Data Model in Python. - In-memory classes for PROV assertions, which can then be output as PROV-N. - Serialization and deserializtion support: PROV-JSON and PROV-XML. - Exporting PROV documents into various graphical formats (e.g. PDF, PNG, SVG). . This package provides the command-line tools for the prov library. Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.14.20170611.dfsg1-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 254124 Depends: neurodebian-popularity-contest Recommends: alsa-utils Suggests: gnuplot Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.14.20170611.dfsg1-1~nd16.10+1_all.deb Size: 24281738 SHA256: cc0643cdc16fbe3853ffd8f6c81f5cef211d831f98fce8592a561dcca5961b26 SHA1: 739e2aa2635d06f0d3357c872a1ccf447d420b4a MD5sum: 245d3854514cae5e6ca3c1056fef7075 Description: toolbox for vision research -- arch/interpreter independent part Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains architecture independent files (such as .m scripts) Package: python-click Version: 6.6-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 258 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-colorama Homepage: https://github.com/mitsuhiko/click Priority: optional Section: python Filename: pool/main/p/python-click/python-click_6.6-1~nd16.10+1_all.deb Size: 56174 SHA256: 32d0b5e186ff972dd41c006c235d02264ac9445d39dfa4791189f44f3096a91a SHA1: f5306481f1332b056cfb87d4551dc75f5f6ee942 MD5sum: 4ed195d0c7aba265e847fd7b48554490 Description: Simple wrapper around optparse for powerful command line utilities - Python 2.7 Click is a Python package for creating beautiful command line interfaces in a composable way with as little code as necessary. It's the "Command Line Interface Creation Kit". It's highly configurable but comes with sensible defaults out of the box. . It aims to make the process of writing command line tools quick and fun while also preventing any frustration caused by the inability to implement an intended CLI API. . This is the Python 2 compatible package. Package: python-datalad Source: datalad Version: 0.8.1-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3738 Depends: neurodebian-popularity-contest, git-annex (>= 6.20170525~) | git-annex-standalone (>= 6.20170525~), 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_0.8.1-1~nd16.10+1_all.deb Size: 725930 SHA256: 8b8e9febc29cbf37aa5e0c7091cdf46120d160df1cbcf1673362e65072423a55 SHA1: 43808960f367c633dbf47e6e0544e755a41601bc MD5sum: 8dd543f8bc5c37475a251815ef729587 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. Package: python-dipy Source: dipy Version: 0.12.0-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6926 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python:any (>= 2.6.6-7~), python-numpy (>= 1:1.7.1~), python-scipy, python-dipy-lib (>= 0.12.0-1~nd16.10+1) Recommends: python-matplotlib, python-vtk, python-nose, python-nibabel, python-tables Suggests: ipython Provides: python2.7-dipy Homepage: http://dipy.org Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy_0.12.0-1~nd16.10+1_all.deb Size: 3011930 SHA256: 14cc74cfe0ad317b5398c8e4683843583e8ba9e76dd1a702d46eed2e06ddc8dc SHA1: bd38cea9725d50e3e088f4cd1d171479d38f3d8f MD5sum: a39834bbb9c26669c2cf1ba744b9e26a Description: Python library for the analysis of diffusion MRI datasets DIPY is a software project for computational neuroanatomy. It focuses on diffusion magnetic resonance imaging (dMRI) analysis and tractography but also contains implementations of other computational imaging methods such as denoising and registration that are applicable to the greater medical imaging and image processing communities. Additionally, DIPY is an international project which brings together scientists across labs and countries to share their state-of-the-art code and expertise in the same codebase, accelerating scientific research in medical imaging. . Here are some of the highlights: - Reconstruction algorithms: CSD, DSI, GQI, DTI, DKI, QBI, SHORE and MAPMRI - Fiber tracking algorithms: deterministic and probabilistic - Native linear and nonlinear registration of images - Fast operations on streamlines (selection, resampling, registration) - Tractography segmentation and clustering - Many image operations, e.g., reslicing or denoising with NLMEANS - Estimation of distances/correspondences between streamlines and connectivity matrices - Interactive visualization of streamlines in the space of images Python-Version: 2.7 Package: python-dipy-doc Source: dipy Version: 0.12.0-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14201 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-dipy Homepage: http://dipy.org Priority: extra Section: doc Filename: pool/main/d/dipy/python-dipy-doc_0.12.0-1~nd16.10+1_all.deb Size: 10545858 SHA256: 8307e60d43365df920e381828a7ebf7f78c02b6c79e5d4607b4393c136dfffa2 SHA1: 58b4a2b436e2c42cbd43f75444cc2f3fe4cd8233 MD5sum: 5a44a14563f50de1f08b14b35061b1c0 Description: Python library for the analysis of diffusion MRI datasets -- documentation DIPY is a library for the analysis of diffusion magnetic resonance imaging data. . This package provides the documentation in HTML format. Package: python-git Version: 2.1.3-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1629 Depends: neurodebian-popularity-contest, git (>= 1:1.7) | git-core (>= 1:1.5.3.7), python-gitdb (>= 2), python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-smmap, python-git-doc Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: python Filename: pool/main/p/python-git/python-git_2.1.3-1~nd16.10+1_all.deb Size: 299250 SHA256: f82f4e650d199dbe49208d6a3bec73a554aae521421572c55b907d92f13e112e SHA1: 8ee1a22b371df51423ea50c63671cef0c682ef75 MD5sum: a6e532f4dbfee9a7dcdbb53e7082f7bd Description: Python library to interact with Git repositories - Python 2.7 python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. . This package provides the Python 2.7 module. Python-Version: 2.7 Package: python-git-doc Source: python-git Version: 2.1.3-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 981 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: doc Filename: pool/main/p/python-git/python-git-doc_2.1.3-1~nd16.10+1_all.deb Size: 127558 SHA256: a4e11fda2557101226b04b7745ba1aed0ee7864d35fac6a708a424227b2efba4 SHA1: 31dd7a37c44530af58d3d8befbe10d4dbfd5874e MD5sum: 82310d28e6b199fa0a46f3c1f817be51 Description: Python library to interact with Git repositories - docs python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. . This package provides the documentation. Package: python-mvpa2 Source: pymvpa2 Version: 2.6.1-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8560 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy, python:any (>= 2.6.6-7~), python-mvpa2-lib (>= 2.6.1-1~nd16.10+1) Recommends: python-h5py, python-lxml, python-matplotlib, python-mdp, python-nibabel, python-nipy, python-psutil, python-psyco, python-pywt, python-reportlab, python-scipy, python-sklearn, python-shogun, liblapack-dev, python-pprocess, python-statsmodels, python-joblib, python-duecredit, python-mock Suggests: fslview, fsl, python-mvpa2-doc, python-nose, python-openopt, python-rpy2 Provides: python2.7-mvpa2 Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2_2.6.1-1~nd16.10+1_all.deb Size: 5098848 SHA256: c7922f497eaf72bbc3b35986ca070dca768571209698f28050db810aa78d316c SHA1: 08137a74b9e7fa9b349ab672773f015b6ea38467 MD5sum: 9c1d198c2c689b7333461b62acecdc59 Description: multivariate pattern analysis with Python v. 2 PyMVPA eases pattern classification analyses of large datasets, with an accent on neuroimaging. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. . This is a package of PyMVPA v.2. Previously released stable version is provided by the python-mvpa package. Python-Version: 2.7 Package: python-mvpa2-doc Source: pymvpa2 Version: 2.6.1-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 36330 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-mvpa2, python-mvpa2-tutorialdata, ipython-notebook Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa2/python-mvpa2-doc_2.6.1-1~nd16.10+1_all.deb Size: 4651240 SHA256: ced18392e6f0776fa2191d5d37e05d4dacded1809e7b86b2150b8cad4984a3a4 SHA1: 1c01d23568ab4469c9302b1ce7993018818ea4ac MD5sum: e52234f058849dd72191b8dd7f85eb1c Description: documentation and examples for PyMVPA v. 2 This is an add-on package for the PyMVPA framework. It provides a HTML documentation (tutorial, FAQ etc.), and example scripts. In addition the PyMVPA tutorial is also provided as IPython notebooks. Package: python-nipy Source: nipy Version: 0.4.1-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3545 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.2), python (>= 2.7), python (<< 2.8), python:any (>= 2.6.6-7~), python-scipy, python-nibabel, python-nipy-lib (>= 0.4.1-1~nd16.10+1) Recommends: python-matplotlib, mayavi2, python-sympy Suggests: python-mvpa Provides: python2.7-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy_0.4.1-1~nd16.10+1_all.deb Size: 779772 SHA256: 2d3307992f663ec37a497c43169399f81ac236285735ffa70063d5cc6b5dd01a SHA1: 53056e55ee42ecec5f27acc36daa4747ab8e33e7 MD5sum: 9a0394be63096038f8b97ab6d2884d21 Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. It provides functionality for - General linear model (GLM) statistical analysis - Combined slice time correction and motion correction - General image registration routines with flexible cost functions, optimizers and re-sampling schemes - Image segmentation - Basic visualization of results in 2D and 3D - Basic time series diagnostics - Clustering and activation pattern analysis across subjects - Reproducibility analysis for group studies Python-Version: 2.7 Package: python-nipy-doc Source: nipy Version: 0.4.1-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10720 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Recommends: python-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: doc Filename: pool/main/n/nipy/python-nipy-doc_0.4.1-1~nd16.10+1_all.deb Size: 2859118 SHA256: 3f4e16b6e14cf0cf5280c6838734924d782a15de615f8b7e1e5d6725d9809ec4 SHA1: 2ebb6a2128c555f1891433af0cee023b5cfddbf4 MD5sum: 661587e14a331cb70170253bbac93ab2 Description: documentation and examples for NiPy This package contains NiPy documentation in various formats (HTML, TXT) including * User manual * Developer guidelines * API documentation Package: python-pprocess Source: pprocess Version: 0.5-2~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 762 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Provides: python2.7-pprocess Homepage: http://www.boddie.org.uk/python/pprocess.html Priority: optional Section: python Filename: pool/main/p/pprocess/python-pprocess_0.5-2~nd16.10+1_all.deb Size: 83172 SHA256: c875c3e07f2204b4a22a426d7c8c89df415d797f23d2b8e6069545456dd527fd SHA1: e2525465a40f3be802602cf0477c8f34a1cc7b32 MD5sum: 37e65fd749b7988bb8e0ebaa5aca3cd8 Description: elementary parallel programming for Python The pprocess module provides elementary support for parallel programming in Python using a fork-based process creation model in conjunction with a channel-based communications model implemented using socketpair and poll. On systems with multiple CPUs or multicore CPUs, processes should take advantage of as many CPUs or cores as the operating system permits. Package: python-prov Version: 1.5.0-1+nd1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1951 Depends: neurodebian-popularity-contest, python-dateutil, python-lxml, python-networkx, python-rdflib, python-six (>= 1.9.0), python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-prov-doc, python-pydotplus Homepage: https://github.com/trungdong/prov Priority: optional Section: python Filename: pool/main/p/python-prov/python-prov_1.5.0-1+nd1~nd16.10+1_all.deb Size: 100618 SHA256: b8d985f4238ad8deaa139f3bcc9f0d08d3606e378bf62ef2177878651f5a18da SHA1: 93238737516ecc64ecb95dc27680859712640de7 MD5sum: c99ea8d71581c47a6946e483160b8827 Description: W3C Provenance Data Model (Python 2) A library for W3C Provenance Data Model supporting PROV-JSON and PROV- XML import/export. . Features: - An implementation of the W3C PROV Data Model in Python. - In-memory classes for PROV assertions, which can then be output as PROV-N. - Serialization and deserializtion support: PROV-JSON and PROV-XML. - Exporting PROV documents into various graphical formats (e.g. PDF, PNG, SVG). . This package provides the prov library for Python 2. Package: python-prov-doc Source: python-prov Version: 1.5.0-1+nd1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 958 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://github.com/trungdong/prov Priority: optional Section: doc Filename: pool/main/p/python-prov/python-prov-doc_1.5.0-1+nd1~nd16.10+1_all.deb Size: 76636 SHA256: 2aeee990c70b45c5062f5033caa78bf32c908857a9d192822899e23d1bd1076c SHA1: 99b6cafe7c834ccb945d62dfe899f8630f7a3a51 MD5sum: a4d76b310e84cda436af0dff14749942 Description: documentation for prov A library for W3C Provenance Data Model supporting PROV-JSON and PROV- XML import/export. . Features: - An implementation of the W3C PROV Data Model in Python. - In-memory classes for PROV assertions, which can then be output as PROV-N. - Serialization and deserializtion support: PROV-JSON and PROV-XML. - Exporting PROV documents into various graphical formats (e.g. PDF, PNG, SVG). . This package provides the documentation for the prov library. Package: python-pydotplus Version: 2.0.2-2~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 104 Depends: neurodebian-popularity-contest, graphviz, python-pyparsing (>= 2.0.1), python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-pydotplus-doc Homepage: http://pydotplus.readthedocs.org/ Priority: optional Section: python Filename: pool/main/p/python-pydotplus/python-pydotplus_2.0.2-2~nd16.10+1_all.deb Size: 20322 SHA256: f0bcc06713e2224bc5df41330d7080f7cd30c2bfea27a900946a834529002562 SHA1: 0188b4080058fc2fac657702776fb15438857e8d MD5sum: 3244608551cac07910f20069b088a5e2 Description: interface to Graphviz's Dot language - Python 2.7 PyDotPlus is an improved version of the old pydot project that provides a Python Interface to Graphviz's Dot language. . Differences with pydot: * Compatible with PyParsing 2.0+. * Python 2.7 - Python 3 compatible. * Well documented. * CI Tested. . This package contains the Python 2.7 module. Package: python-pydotplus-doc Source: python-pydotplus Version: 2.0.2-2~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 533 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0), sphinx-rtd-theme-common Homepage: http://pydotplus.readthedocs.org/ Priority: optional Section: doc Filename: pool/main/p/python-pydotplus/python-pydotplus-doc_2.0.2-2~nd16.10+1_all.deb Size: 47682 SHA256: e652381942582d862b29b8c2c2599c11f6458ebf88efd8c750f4f5da2217b4ec SHA1: 8b8e82888144d8d52a7cc68056af2ebc6a2bdacc MD5sum: 23f2b5dd0d7141533ca3aca0f6ec9313 Description: interface to Graphviz's Dot language - doc PyDotPlus is an improved version of the old pydot project that provides a Python Interface to Graphviz's Dot language. . Differences with pydot: * Compatible with PyParsing 2.0+. * Python 2.7 - Python 3 compatible. * Well documented. * CI Tested. . This package contains the documentation. Package: python-pyglet Source: pyglet Version: 1.3.0~rc1-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5414 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-ctypes | python (>= 2.5), libgtk2.0-0, libgl1 | libgl1-mesa-swx11, libglu1 | libglu1-mesa Recommends: libasound2 | libopenal1 Provides: python2.7-pyglet Homepage: http://www.pyglet.org Priority: optional Section: python Filename: pool/main/p/pyglet/python-pyglet_1.3.0~rc1-1~nd16.10+1_all.deb Size: 1121434 SHA256: 6f0fba6f788471538cc673f6a92ab8796436270664c2b43bf80fbb949b8f813a SHA1: e163aff1d6ac1181c6ab418d05fea705308e5988 MD5sum: 1d8a25757f7d037a89713b62604a1c91 Description: cross-platform windowing and multimedia library This library provides an object-oriented programming interface for developing games and other visually-rich applications with Python. pyglet has virtually no external dependencies. For most applications and game requirements, pyglet needs nothing else besides Python, simplifying distribution and installation. It also handles multiple windows and fully aware of multi-monitor setups. . pyglet might be seen as an alternative to PyGame. Package: python-rdflib Source: rdflib Version: 4.2.1-2~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1240 Depends: neurodebian-popularity-contest, python-isodate, python-pyparsing, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: python-sparqlwrapper (>= 1.7.6~), python-html5lib Suggests: python-rdflib-doc, python-rdflib-tools Provides: python2.7-rdflib Homepage: https://github.com/RDFLib/rdflib Priority: optional Section: python Filename: pool/main/r/rdflib/python-rdflib_4.2.1-2~nd16.10+1_all.deb Size: 238040 SHA256: 7642c218dcfde52f7de9861becad685fcd9c6b61465d81ee700c34c8f36c96be SHA1: 6d57a60c0ee0d52d5da134cd101a932d5a0728f9 MD5sum: 360f8c41818a3fb7d95d67042ac02699 Description: Python library containing an RDF triple store and RDF parsers/serializers RDFLib is a Python library for working with the RDF W3C standard. The library contains RDF parsers/serializers and both in-memory and persistent Graph backend. . This package contains the Python 2 version of RDFLib. Package: python-rdflib-doc Source: rdflib Version: 4.2.1-2~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8157 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Built-Using: sphinx (= 1.4.8-1) Homepage: https://github.com/RDFLib/rdflib Priority: optional Section: doc Filename: pool/main/r/rdflib/python-rdflib-doc_4.2.1-2~nd16.10+1_all.deb Size: 589198 SHA256: 57baa851a1099a6d7f9471dd2b8c5d19d2192f44c1d0b09cd8fef12c2e867c04 SHA1: 8bf933a8b919240764f16c6a371a1417d41f7a60 MD5sum: 871960e931c3879ad04040e95b7c3c41 Description: Python library containing an RDF triple store [...] (documentation) RDFLib is a Python library for working with the RDF W3C standard. The library contains RDF parsers/serializers and both in-memory and persistent Graph backend. . This is the common documentation package. Package: python-rdflib-tools Source: rdflib Version: 4.2.1-2~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 38 Depends: neurodebian-popularity-contest, python, python-rdflib (>= 4.0.1-1) Breaks: python-rdflib (<< 4.0.1-1) Replaces: python-rdflib (<< 4.0.1-1) Homepage: https://github.com/RDFLib/rdflib Priority: optional Section: python Filename: pool/main/r/rdflib/python-rdflib-tools_4.2.1-2~nd16.10+1_all.deb Size: 11846 SHA256: a27dc1fbc95fd66006da2c6d34ed25c29b1ec1205876a6d81eb04b25285182d1 SHA1: 07b79a3099d4f1f6954fc5c71b7300973b956579 MD5sum: f7fd79d5deafd8a2120fc2535b3a9307 Description: Python tools for converting to and from RDF RDFLib is a Python library for working with the RDF W3C standard. The library contains RDF parsers/serializers and both in-memory and persistent Graph backend. . This package contains some executable tools. Package: python-scikits-learn Source: scikit-learn Version: 0.19.0-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 93 Depends: neurodebian-popularity-contest, python-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: oldlibs Filename: pool/main/s/scikit-learn/python-scikits-learn_0.19.0-1~nd16.10+1_all.deb Size: 83672 SHA256: 1d612ccad300ae0ab882123e74a3d693cb62a0c6c317b5686f32e957e78d1ed6 SHA1: 5ccbfe7580f0e8e1aa200f4b1b82f911d57f264a MD5sum: 371cf6287f43a6e870116d39b463f00e Description: transitional compatibility package for scikits.learn -> sklearn migration Provides old namespace (scikits.learn) and could be removed if dependent code migrated to use sklearn for clarity of the namespace. Package: python-sklearn Source: scikit-learn Version: 0.19.0-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6995 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-numpy, python-scipy, python-sklearn-lib (>= 0.19.0-1~nd16.10+1), python-joblib (>= 0.9.2) Recommends: python-nose, python-pytest, python-matplotlib Suggests: python-dap, python-scikits-optimization, python-sklearn-doc, ipython Enhances: python-mdp, python-mvpa2 Breaks: python-scikits-learn (<< 0.9~) Replaces: python-scikits-learn (<< 0.9~) Provides: python2.7-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn_0.19.0-1~nd16.10+1_all.deb Size: 1450722 SHA256: 7a9acd447c5d91f9a0566339a445963908ea2b15073de8af50a3fd6fec30a14c SHA1: 7f7cd9c9244fa10123f9f124f790b99c4734ba5f MD5sum: 60fffd7bf581ed14d4c07993deb95f15 Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) Package: python-sklearn-doc Source: scikit-learn Version: 0.19.0-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 33094 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-sklearn Conflicts: python-scikits-learn-doc Replaces: python-scikits-learn-doc Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: doc Filename: pool/main/s/scikit-learn/python-sklearn-doc_0.19.0-1~nd16.10+1_all.deb Size: 5040258 SHA256: 100452c60435c1651338ab5996b499296d8e12c8a1fb93fc73ea04d8b86dbb3a SHA1: e1f6211b443e2cb9517d978e40263bdfc183f1f6 MD5sum: 0e4c24cfc635308c91b42d7d8815a97f Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-sklearn. Package: python-sparqlwrapper Source: sparql-wrapper-python Version: 1.7.6-3~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 94 Depends: neurodebian-popularity-contest, python-rdflib, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: http://rdflib.github.io/sparqlwrapper/ Priority: optional Section: python Filename: pool/main/s/sparql-wrapper-python/python-sparqlwrapper_1.7.6-3~nd16.10+1_all.deb Size: 22154 SHA256: f67e9698585def43ce0cb843da98688250bf4980813d56d5466d9a7a76ef9f2f SHA1: eec079be52007a036e25b3b0a097610c776a29fa MD5sum: 3c377e1fd34d8a0dbf14827d89241dc7 Description: SPARQL endpoint interface to Python This is a wrapper around a SPARQL service. It helps in creating the query URI and, possibly, convert the result into a more manageable format. . This is the Python 2 version of the package. Package: python-whoosh Version: 2.7.4+git6-g9134ad92-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1745 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-whoosh-doc Homepage: http://bitbucket.org/mchaput/whoosh/ Priority: optional Section: python Filename: pool/main/p/python-whoosh/python-whoosh_2.7.4+git6-g9134ad92-1~nd16.10+1_all.deb Size: 290748 SHA256: 18a1aea1cc556dfcdc026d7dd3402d8a9da92accc80702b1b265dfbf07b78608 SHA1: 62cbe449395f35bc6d96c70c539a4d7c38713e3b MD5sum: 8f1f1e8eb42f440e7c991560d6238178 Description: pure-Python full-text indexing, search, and spell checking library (Python 2) Whoosh is a fast, pure-Python indexing and search library. Programmers can use it to easily add search functionality to their applications and websites. As Whoosh is pure Python, you don't have to compile or install a binary support library and/or make Python work with a JVM, yet indexing and searching is still very fast. Whoosh is designed to be modular, so every part can be extended or replaced to meet your needs exactly. . This package contains the python2 library Package: python-whoosh-doc Source: python-whoosh Version: 2.7.4+git6-g9134ad92-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2218 Pre-Depends: dpkg (>= 1.17.14) Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Replaces: python-whoosh (<< 2.1.0) Homepage: http://bitbucket.org/mchaput/whoosh/ Priority: extra Section: doc Filename: pool/main/p/python-whoosh/python-whoosh-doc_2.7.4+git6-g9134ad92-1~nd16.10+1_all.deb Size: 242488 SHA256: 8a79e85853aef625e9c45e3585cf21569b4c9f6ba30d6b1993e1caa7a4074ef5 SHA1: d83c5d50324302ec657b6df5c0ff7197e8ed4eae MD5sum: f585674764ee3426557485866d9dbf96 Description: full-text indexing, search, and spell checking library (doc) Whoosh is a fast, pure-Python indexing and search library. Programmers can use it to easily add search functionality to their applications and websites. As Whoosh is pure Python, you don't have to compile or install a binary support library and/or make Python work with a JVM, yet indexing and searching is still very fast. Whoosh is designed to be modular, so every part can be extended or replaced to meet your needs exactly. . This package contains the library documentation for python-whoosh. Package: python3-click Source: python-click Version: 6.6-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 258 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-colorama Homepage: https://github.com/mitsuhiko/click Priority: optional Section: python Filename: pool/main/p/python-click/python3-click_6.6-1~nd16.10+1_all.deb Size: 56250 SHA256: 4447a544b603f966204d9e2fb175df83c81769c7f7fe3aa6de425fd9b66ed860 SHA1: 235894dc54c7fddd1c2696390855e99cecc3fcc2 MD5sum: 9003dbb977789a8ccef55badbe49b1de Description: Simple wrapper around optparse for powerful command line utilities - Python 3.x Click is a Python package for creating beautiful command line interfaces in a composable way with as little code as necessary. It's the "Command Line Interface Creation Kit". It's highly configurable but comes with sensible defaults out of the box. . It aims to make the process of writing command line tools quick and fun while also preventing any frustration caused by the inability to implement an intended CLI API. . This is the Python 3 compatible package. Package: python3-git Source: python-git Version: 2.1.3-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1626 Depends: neurodebian-popularity-contest, git (>= 1:1.7) | git-core (>= 1:1.5.3.7), python3-gitdb (>= 2), python3:any (>= 3.3.2-2~) Suggests: python-git-doc Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: python Filename: pool/main/p/python-git/python3-git_2.1.3-1~nd16.10+1_all.deb Size: 299006 SHA256: 375bbade32f2bc7c81aa94106d2533cf488dc2174e96f98e051054e74be85fc6 SHA1: b48a48e4b98ea6ebc86573628bd71290f7339dab MD5sum: c81eda597005844cadb8e79b3b232736 Description: Python library to interact with Git repositories - Python 3.x python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. . This package provides the Python 3.x module. Package: python3-prov Source: python-prov Version: 1.5.0-1+nd1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1951 Depends: neurodebian-popularity-contest, python3-dateutil, python3-lxml, python3-networkx, python3-rdflib (>= 4.2.1), python3-six (>= 1.9.0), python3:any (>= 3.3.2-2~) Suggests: python-prov-doc, python3-pydotplus Homepage: https://github.com/trungdong/prov Priority: optional Section: python Filename: pool/main/p/python-prov/python3-prov_1.5.0-1+nd1~nd16.10+1_all.deb Size: 100790 SHA256: eda116fc858ae257731653425cbc4fc70fb7315125715f84d5a2e9a15e5d35c9 SHA1: 655f5be48a6e1709b647bf7f49b6ffd768aef9c2 MD5sum: 8913f06d2daac4bde60b70f45c4079f7 Description: W3C Provenance Data Model (Python 3) A library for W3C Provenance Data Model supporting PROV-JSON and PROV- XML import/export. . Features: - An implementation of the W3C PROV Data Model in Python. - In-memory classes for PROV assertions, which can then be output as PROV-N. - Serialization and deserializtion support: PROV-JSON and PROV-XML. - Exporting PROV documents into various graphical formats (e.g. PDF, PNG, SVG). . This package provides the prov library for Python 3. Package: python3-pydotplus Source: python-pydotplus Version: 2.0.2-2~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 104 Depends: neurodebian-popularity-contest, graphviz, python3-pyparsing (>= 2.0.1), python3:any (>= 3.3.2-2~) Suggests: python-pydotplus-doc Homepage: http://pydotplus.readthedocs.org/ Priority: optional Section: python Filename: pool/main/p/python-pydotplus/python3-pydotplus_2.0.2-2~nd16.10+1_all.deb Size: 20402 SHA256: 109cf12269bab55a82c280b1d922ab95cf47ead0951e7483d2e87d6db6fbe4ae SHA1: 31fdf098923e50a5690db9d29506c819a86e463a MD5sum: f83f3759a21211f2c396b30e3a4168bf Description: interface to Graphviz's Dot language - Python 3.x PyDotPlus is an improved version of the old pydot project that provides a Python Interface to Graphviz's Dot language. . Differences with pydot: * Compatible with PyParsing 2.0+. * Python 2.7 - Python 3 compatible. * Well documented. * CI Tested. . This package contains the Python 3.x module. Package: python3-rdflib Source: rdflib Version: 4.2.1-2~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1237 Depends: neurodebian-popularity-contest, python3-isodate, python3-pyparsing, python3:any (>= 3.3.2-2~) Recommends: python3-sparqlwrapper (>= 1.7.6~), python3-html5lib Suggests: python-rdflib-doc Homepage: https://github.com/RDFLib/rdflib Priority: optional Section: python Filename: pool/main/r/rdflib/python3-rdflib_4.2.1-2~nd16.10+1_all.deb Size: 236730 SHA256: db9dec2d407ae2787996462c3fd775921bf5c1b21ea7746868075533a7fc0cc7 SHA1: 4f827c396ac390ce7218da712f2e693f236d59b5 MD5sum: 50d98931750dae9df2dc7de136c0c92e Description: Python 3 library containing an RDF triple store and RDF parsers/serializers RDFLib is a Python library for working with the RDF W3C standard. The library contains RDF parsers/serializers and both in-memory and persistent Graph backend. . This package contains the Python 3 version of RDFLib. Package: python3-sklearn Source: scikit-learn Version: 0.19.0-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6994 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-sklearn-lib (>= 0.19.0-1~nd16.10+1), python3-joblib (>= 0.9.2) Recommends: python3-nose, python-pytest, python3-matplotlib Suggests: python3-dap, python-sklearn-doc, ipython3 Enhances: python3-mdp, python3-mvpa2 Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python3-sklearn_0.19.0-1~nd16.10+1_all.deb Size: 1450590 SHA256: 1a53645b753abe14a825a40eadfd48ebb0ec156cf288567bb118b64dbd84d38e SHA1: a9e6cb5649f4f6c5fdcf2db5bfe11e4d8ec92384 MD5sum: 118a95053d23785a20b72780223ac07c Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) . This package contains the Python 3 version. Package: python3-sparqlwrapper Source: sparql-wrapper-python Version: 1.7.6-3~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 86 Depends: neurodebian-popularity-contest, python3-rdflib, python3:any (>= 3.3.2-2~) Homepage: http://rdflib.github.io/sparqlwrapper/ Priority: optional Section: python Filename: pool/main/s/sparql-wrapper-python/python3-sparqlwrapper_1.7.6-3~nd16.10+1_all.deb Size: 20738 SHA256: 36093261a89c7467e3f6df6c0920f811d6e51217fa075f50ae9f42587aadfcef SHA1: b3ebc2410d20b5f1471823943b8bdb992154fd62 MD5sum: aae68947aa38773bbbd5768019a15e77 Description: SPARQL endpoint interface to Python3 This is a wrapper around a SPARQL service. It helps in creating the query URI and, possibly, convert the result into a more manageable format. . This is the Python 3 version of the package. Package: python3-whoosh Source: python-whoosh Version: 2.7.4+git6-g9134ad92-1~nd16.10+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1745 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Suggests: python-whoosh-doc Homepage: http://bitbucket.org/mchaput/whoosh/ Priority: optional Section: python Filename: pool/main/p/python-whoosh/python3-whoosh_2.7.4+git6-g9134ad92-1~nd16.10+1_all.deb Size: 290750 SHA256: 60f0a9643a3807a1bea26c95d1a1ab571a7515ebe35ae83ad234094bea59580b SHA1: 3fa40ccf4905753d5c92011ac0a6355af2378a6d MD5sum: 11749974bf698038ea19d654b4540b4d Description: pure-Python full-text indexing, search, and spell checking library (Python 3) Whoosh is a fast, pure-Python indexing and search library. Programmers can use it to easily add search functionality to their applications and websites. As Whoosh is pure Python, you don't have to compile or install a binary support library and/or make Python work with a JVM, yet indexing and searching is still very fast. Whoosh is designed to be modular, so every part can be extended or replaced to meet your needs exactly. . This package contains the python3 library