h5py 3.6.0-2 source package in Ubuntu
Changelog
h5py (3.6.0-2) unstable; urgency=medium * Team upload. * upload 3.6.0 to unstable -- Drew Parsons <email address hidden> Mon, 13 Dec 2021 11:32:22 +0100
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_3.6.0-2.dsc | 2.7 KiB | 6bad161509ff960b9d75b07b1f41bd8b54250a8e2e41b96691aa0e8bf20e34d5 |
h5py_3.6.0.orig.tar.gz | 375.2 KiB | 8752d2814a92aba4e2b2a5922d2782d0029102d99caaf3c201a566bc0b40db29 |
h5py_3.6.0-2.debian.tar.xz | 18.3 KiB | cef21bb91f87232e452e010c150ea460f9fea6ee4805c1758a9597287491a108 |
Available diffs
No changes file available.
Binary packages built by this source
- hdf5-plugin-lzf: hdf5 plugin to lzf compression library
HDF5 (Hierarchical Data Format library, version 5) is a versatile,
mature scientific software library designed for the fast, flexible
storage of enormous amounts of data.
.
This package provides a plugin to the HDF5 LZF filter for the LZF
compression library. Plugins are built for both serial (single
processor) jobs (libhdf5-dev) and for multiprocessor (threaded) jobs
(libhdf5-mpi-dev).
- hdf5-plugin-lzf-dbgsym: debug symbols for hdf5-plugin-lzf
- 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
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 is a simple dependency package which depends on the serial or
MPI build of h5py and provides test data files.
- python3-h5py-mpi: general-purpose Python interface to hdf5 (Python 3 MPI)
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, built with support
for MPI (multiprocessor) jobs.
- python3-h5py-mpi-dbgsym: debug symbols for python3-h5py-mpi
- python3-h5py-serial: general-purpose Python interface to hdf5 (Python 3 serial)
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, built for serial
(single processor) jobs.
- python3-h5py-serial-dbgsym: debug symbols for python3-h5py-serial