Package: git-annex-standalone
Source: git-annex
Version: 7.20190730+git103-g070fbd693-1~ndall+1
Architecture: amd64
Maintainer: Richard Hartmann <richih@debian.org>
Installed-Size: 184272
Depends: git, netbase, openssh-client
Recommends: lsof, gnupg, bind9-host, youtube-dl, git-remote-gcrypt (>= 0.20130908-6), nocache, aria2
Suggests: xdot, bup, adb, tor, magic-wormhole, tahoe-lafs, libnss-mdns, uftp
Conflicts: git-annex
Breaks: datalad (<= 0.11.1~)
Provides: git-annex
Homepage: http://git-annex.branchable.com/
Priority: optional
Section: utils
Filename: pool/main/g/git-annex/git-annex-standalone_7.20190730+git103-g070fbd693-1~ndall+1_amd64.deb
Size: 64130812
SHA256: e7342b650247d504778e72bb3772bd516f1e5718c00177cb8cc13b7f19ecdf3b
SHA1: 55f30fce9d0ceea9935fa3eaf2ded1d1aabe7f35
MD5sum: d8f6a67606e8372d664bb7983b13e8ab
Description: manage files with git, without checking their contents into git -- standalone build
 git-annex allows managing files with git, without checking the file
 contents into git. While that may seem paradoxical, it is useful when
 dealing with files larger than git can currently easily handle, whether due
 to limitations in memory, time, or disk space.
 .
 It can store large files in many places, from local hard drives, to a
 large number of cloud storage services, including S3, WebDAV,
 and rsync, with a dozen cloud storage providers usable via plugins.
 Files can be stored encrypted with gpg, so that the cloud storage
 provider cannot see your data. git-annex keeps track of where each file
 is stored, so it knows how many copies are available, and has many
 facilities to ensure your data is preserved.
 .
 git-annex can also be used to keep a folder in sync between computers,
 noticing when files are changed, and automatically committing them
 to git and transferring them to other computers. The git-annex webapp
 makes it easy to set up and use git-annex this way.
 .
 This package provides a standalone bundle build of git-annex, which
 should be installable on any more or less recent Debian or Ubuntu
 release.

Package: python3-hdmf
Source: hdmf
Version: 1.1.2-1~nd110+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 392
Depends: neurodebian-popularity-contest, python3-dateutil, python3-h5py, python3-numpy, python3-pandas, python3-requests, python3-ruamel.yaml, python3-six, python3:any, python3-certifi, python3-chardet, python3-idna, python3-urllib3
Homepage: https://github.com/hdmf-dev/hdmf
Priority: optional
Section: python
Filename: pool/main/h/hdmf/python3-hdmf_1.1.2-1~nd110+1_all.deb
Size: 63672
SHA256: ae1c5f98e5e75b469c43f879721ab57561b69b14086575b455bebafff545caf4
SHA1: b0629cd131b4672d0f7c2d072f9e7215a462ca62
MD5sum: 64e5974e6b2358f9b349259f637437e5
Description: Hierarchical Data Modeling Framework
 The Hierarchical Data Modeling Framework (HDMF) is a Python package
 for working with hierarchical data.  It provides APIs for specifying
 data models, reading and writing data to different storage backends,
 and representing data with Python object.

Package: python3-pynwb
Source: pynwb
Version: 1.0.3-1~nd110+1
Architecture: all
Maintainer: NeuroDebian Maintainers <team@neuro.debian.net>
Installed-Size: 424
Depends: neurodebian-popularity-contest, python3-chardet, python3-dateutil, python3-h5py (>= 2.7.1), python3-hdmf, python3-numpy, python3-pandas, python3-ruamel.yaml, python3-six, python3:any
Homepage: https://github.com/NeurodataWithoutBorders/pynwb
Priority: optional
Section: python
Filename: pool/main/p/pynwb/python3-pynwb_1.0.3-1~nd110+1_all.deb
Size: 60480
SHA256: 0bfbc0e279e515a0ce05da671d3f5c2cbebddcc4f26d91f2b5d31c5d6eb55c75
SHA1: c2a15401e2a757cd6d9f802532f7ed53af6df4bf
MD5sum: f124f2fbebd81f8c8c69dca1a32a1d95
Description: Python library for working with Neurodata in the NWB format
 PyNWB is a Python package for working with NWB files. It provides a
 high-level API for efficiently working with Neurodata stored in the
 NWB format.
 .
 Neurodata Without Borders: Neurophysiology (NWB:N) is a project to
 develop a unified data format for cellular-based neurophysiology
 data, focused on the dynamics of groups of neurons measured under a
 large range of experimental conditions.