h5py 2.10.0-2 source package in Ubuntu
Changelog
h5py (2.10.0-2) unstable; urgency=medium * Team upload. * Drop Python 2 package. Closes: #936684 -- Ole Streicher <email address hidden> Tue, 15 Oct 2019 14:41:14 +0200
Upload details
- Uploaded by:
- Debian Science Team
- Uploaded to:
- Sid
- Original maintainer:
- Debian Science Team
- Architectures:
- any all
- Section:
- python
- Urgency:
- Medium Urgency
See full publishing history Publishing
Series | Published | Component | Section |
---|
Downloads
File | Size | SHA-256 Checksum |
---|---|---|
h5py_2.10.0-2.dsc | 2.4 KiB | 500f0abfb489a74d552c6972ae1fb13e64fbb8db5fd5679163759aac9903798c |
h5py_2.10.0.orig.tar.gz | 294.0 KiB | 84412798925dc870ffd7107f045d7659e60f5d46d1c70c700375248bf6bf512d |
h5py_2.10.0-2.debian.tar.xz | 10.3 KiB | 6a6a93b8d33084fbf7be53a6af0dcbff75a8d5d85ec962da9ce62bf748246bdc |
Available diffs
- diff from 2.9.0-7 to 2.10.0-2 (127.9 KiB)
- diff from 2.10.0-1build1 (in Ubuntu) to 2.10.0-2 (1.8 KiB)
No changes file available.
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.