Source: h5py Maintainer: Debian Science Maintainers Uploaders: Ghislain Antony Vaillant , Mo Zhou , Section: python Priority: optional Build-Depends: cython3, cython3-dbg, debhelper-compat (= 12), dh-python, dpkg-dev (>= 1.17.14), libhdf5-dev, libhdf5-mpi-dev (>= 1.10.6+repack-1), libjs-mathjax, liblzf-dev, mpi-default-dev, python3-all-dbg, python3-all-dev, python3-mpi4py, python3-mpi4py-dbg, python3-numpy, python3-numpy-dbg, python3-pkgconfig, python3-pytest, python3-setuptools, python3-six, python3-unittest2, python3-sphinx Standards-Version: 4.5.0 Vcs-Browser: https://salsa.debian.org/science-team/h5py Vcs-Git: https://salsa.debian.org/science-team/h5py.git Homepage: https://www.h5py.org/ Package: python3-h5py Architecture: all Depends: python3-h5py-serial | python3-h5py-mpi, ${misc:Depends} Suggests: python-h5py-doc Description: 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 dummy package which depends on the serial or MPI build of h5py. Package: python3-h5py-serial Architecture: any Depends: ${misc:Depends}, ${python3:Depends}, ${shlibs:Depends} Suggests: python-h5py-doc Conflicts: python3-h5py (<< 2.10.0-3~) Description: 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. Package: python3-h5py-mpi Architecture: any Depends: ${misc:Depends}, ${python3:Depends}, ${shlibs:Depends}, python3-h5py-serial, python3-mpi4py Suggests: python-h5py-doc Description: 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. Package: python3-h5py-dbg Section: debug Architecture: all Depends: python3-h5py-serial-dbg | python3-h5py-mpi-dbg, ${misc:Depends} Suggests: python-h5py-doc Description: 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 is a dummy package which depends on the serial or MPI build of h5py with debug extensions. Package: python3-h5py-serial-dbg Architecture: any Multi-Arch: same Section: debug Depends: ${misc:Depends}, ${python3:Depends}, ${shlibs:Depends}, python3-h5py-serial (= ${binary:Version}), python3-numpy-dbg Description: debug extensions for h5py (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 debug extensions for Python 3, built for serial (single processor) jobs. Package: python3-h5py-mpi-dbg Architecture: any Multi-Arch: same Section: debug Depends: ${misc:Depends}, ${python3:Depends}, ${shlibs:Depends}, python3-h5py-mpi (= ${binary:Version}), python3-h5py-serial-dbg (= ${binary:Version}), python3-mpi4py-dbg, python3-numpy-dbg Description: debug extensions for h5py (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 debug extensions for Python 3, built with support for MPI (multiprocessor) jobs. Package: python-h5py-doc Architecture: all Multi-Arch: foreign Section: doc Depends: ${misc:Depends}, ${sphinxdoc:Depends}, libjs-mathjax Built-Using: ${sphinxdoc:Built-Using} Description: 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. Build-Profiles: