h5py 2.10.0-2build1 source package in Ubuntu
Changelog
h5py (2.10.0-2build1) focal; urgency=medium * No-change rebuild to generate dependencies on python2. -- Matthias Klose <email address hidden> Tue, 17 Dec 2019 12:34:03 +0000
Upload details
- Uploaded by:
- Matthias Klose
- Uploaded to:
- Focal
- Original maintainer:
- Debian Science Team
- Architectures:
- any all
- Section:
- python
- Urgency:
- Medium Urgency
See full publishing history Publishing
Series | Published | Component | Section |
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Downloads
File | Size | SHA-256 Checksum |
---|---|---|
h5py_2.10.0.orig.tar.gz | 294.0 KiB | 84412798925dc870ffd7107f045d7659e60f5d46d1c70c700375248bf6bf512d |
h5py_2.10.0-2build1.debian.tar.xz | 10.4 KiB | 15580e0d5c495e4d7f3484a2e1c6ac20af6a5efa743a855e47c1212d7d61f5f5 |
h5py_2.10.0-2build1.dsc | 2.5 KiB | 8b838c7d0fc649a02aa71b42d29d07ffdb13a7b19e445d8db2ec7bccbbfc68c7 |
Available diffs
- diff from 2.10.0-2 (in Debian) to 2.10.0-2build1 (307 bytes)
Binary packages built by this source
- python-h5py-doc: documentation for h5py
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.
.
This package provides the documentation.
- python3-h5py: general-purpose Python interface to hdf5 (Python 3)
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.
.
This package provides the modules for Python 3.
- python3-h5py-dbg: debug extensions for h5py (Python 3)
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.
.
This package provides the debug extensions for Python 3.