Ubuntu
h5py package

h5py 2.2.1-1 source package in Ubuntu

Changelog

h5py (2.2.1-1) unstable; urgency=low


  * New upstream version
  * Fix python3 dependency (Closes: #732586)

 -- Soeren Sonnenburg <email address hidden>  Sat, 04 Jan 2014 23:18:29 +0100

Upload details

Uploaded by:
Soeren Sonnenburg
Uploaded to:
Sid
Original maintainer:
Soeren Sonnenburg
Architectures:
any
Section:
python
Urgency:
Low Urgency

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File Size SHA-256 Checksum
h5py_2.2.1-1.dsc 2.0 KiB ec6be204622a348f7d54907aee51ccba7e7ea92c44bc6142adce39d2e373b8b4
h5py_2.2.1.orig.tar.gz 955.9 KiB b4510cb74aef332847dc88e3df6910d7af68c709b3556fc960a687c56ba6a4cb
h5py_2.2.1-1.debian.tar.gz 3.9 KiB a8d7690aa91bb64d59ed07e5f8f064acaa44f5c56c2f15fb99e39937104eb85a

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Binary packages built by this source

python-h5py: h5py is a general-purpose Python interface to hdf5

 HDF5 for Python (h5py) is a general-purpose Python interface to the
 Hierarchical Data Format library, version 5. HDF5 is a versatile, mature
 scientific software library designed for the fast, flexible storage of
 enormous amounts of data.
 .
 From a Python programmer's perspective, HDF5 provides a robust way to
 store data, organized by name in a tree-like fashion. You can create
 datasets (arrays on disk) hundreds of gigabytes in size, and perform
 random-access I/O on desired sections. Datasets are organized in a
 filesystem-like hierarchy using containers called "groups", and accessed
 using the tradional POSIX /path/to/resource syntax.
 .
 H5py provides a simple, robust read/write interface to HDF5 data from
 Python. Existing Python and Numpy concepts are used for the interface;
 for example, datasets on disk are represented by a proxy class that
 supports slicing, and has dtype and shape attributes. HDF5 groups are
 presented using a dictionary metaphor, indexed by name.

python3-h5py: h5py is a general-purpose Python interface to hdf5

 HDF5 for Python (h5py) is a general-purpose Python interface to the
 Hierarchical Data Format library, version 5. HDF5 is a versatile, mature
 scientific software library designed for the fast, flexible storage of
 enormous amounts of data.
 .
 From a Python programmer's perspective, HDF5 provides a robust way to
 store data, organized by name in a tree-like fashion. You can create
 datasets (arrays on disk) hundreds of gigabytes in size, and perform
 random-access I/O on desired sections. Datasets are organized in a
 filesystem-like hierarchy using containers called "groups", and accessed
 using the tradional POSIX /path/to/resource syntax.
 .
 H5py provides a simple, robust read/write interface to HDF5 data from
 Python. Existing Python and Numpy concepts are used for the interface;
 for example, datasets on disk are represented by a proxy class that
 supports slicing, and has dtype and shape attributes. HDF5 groups are
 presented using a dictionary metaphor, indexed by name.