h5py 2.0.1-1build1 source package in Ubuntu

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h5py (2.0.1-1build1) precise; urgency=low

  * Rebuild against numpy 1.6
 -- Julian Taylor <email address hidden>   Thu, 16 Feb 2012 00:17:26 +0100

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Uploaded by:
Julian Taylor
Uploaded to:
Precise
Original maintainer:
Soeren Sonnenburg
Architectures:
any
Section:
python
Urgency:
Low Urgency

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Series Pocket Published Component Section
Precise release universe python

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h5py_2.0.1.orig.tar.gz 823.8 KiB cc5242c8ede616af9d8781c6d06603ff5a1f0de3044877176cc31a00cc581c40
h5py_2.0.1-1build1.debian.tar.gz 3.7 KiB a85271ff968487f69b5e48e2dd142a75bb7ece78f4a776ac0c2b6a321d20c369
h5py_2.0.1-1build1.dsc 1.8 KiB 3f9c55f1f26b319783c379c3af43266732be11fb070cfb06b560e49f8cc6f213

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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.