Группа :: Разработка/Python
Пакет: h5py
Главная Изменения Спек Патчи Sources Загрузить Gear Bugs and FR Repocop
Текущая версия: 1.2.1-alt1
Время сборки: 12 сентября 2009, 22:13 ( 758.8 недели назад )
Размер архива: 181.51 Kb
Домашняя страница: http://code.google.com/p/h5py/
Лицензия: MIT
О пакете: Python interface to the Hierarchical Data Format library, version 5
Описание:
Список всех майнтейнеров, принимавших участие
в данной и/или предыдущих сборках пакета: Список rpm-пакетов, предоставляемый данным srpm-пакетом:
ACL:
Время сборки: 12 сентября 2009, 22:13 ( 758.8 недели назад )
Размер архива: 181.51 Kb
Домашняя страница: http://code.google.com/p/h5py/
Лицензия: MIT
О пакете: Python interface to the Hierarchical Data Format library, version 5
Описание:
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.
Текущий майнтейнер: Eugeny A. Rostovtsev (REAL) 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.
Список всех майнтейнеров, принимавших участие
в данной и/или предыдущих сборках пакета: Список rpm-пакетов, предоставляемый данным srpm-пакетом:
- python-module-h5py
- python-module-h5py-doc