Result for 0D4E1D973D6EE5BA0EADD8F00E64EEFC1BEEBC7E

Query result

Key Value
FileName./usr/share/doc/python-h5py-doc/html/_sources/vds.rst.txt
FileSize5070
MD5E20CAB78A0C142E35033424C87746DEA
SHA-10D4E1D973D6EE5BA0EADD8F00E64EEFC1BEEBC7E
SHA-256112795FA1F9E4BC4C74314FE56601DCCB528A41628FB593C38B4603D55F65E68
SSDEEP96:JKr+oHxfREX0TYSXzD70oO8IOcKUCOQJSmAkTCZzXWBU:J2H5Re0D70jbnGTWX2U
TLSHT11FA1128F7F04D6351A17A8EA570C6280CB20EA6EBA94C55474BC94383B1DF3A31DF692
hashlookup:parent-total4
hashlookup:trust70

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Parents (Total: 4)

The searched file hash is included in 4 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize187392
MD573BDF23091DDA1A47167601DBD0BA4C0
PackageDescriptiondocumentation 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.
PackageMaintainerDebian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageNamepython-h5py-doc
PackageSectiondoc
PackageVersion2.10.0-9
SHA-15F8B8C7139C6525915B5E0DAE7F203AC53C0E021
SHA-256E536066186C6345EB86CC602ABC8085C5CC98B74F7E637648576A17DD7C657EE
Key Value
FileSize182716
MD52B493D17C279E0769C89ECD4E8CED32F
PackageDescriptiondocumentation 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.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython-h5py-doc
PackageSectiondoc
PackageVersion2.10.0-9build2
SHA-1CDCEB3D85D44AA6E1D1E50DD0E14D3C275988F16
SHA-2561931B6C494A83F4064AB6870603EAD3F85EE227641CB5A77A894C6E994D1B82D
Key Value
FileSize183232
MD5E6245B4DE080754614BCC5FA8F9A2292
PackageDescriptiondocumentation 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.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython-h5py-doc
PackageSectiondoc
PackageVersion2.10.0-9
SHA-16006AAA7732E3F283FC9B3A00E03137360FB123B
SHA-2565C56E896A9B454DB48062ACEFBC5F5162EBF388D607ED8323576FB2B753DB744
Key Value
FileSize187568
MD5BE656591DF15D3337F987D8793527B6B
PackageDescriptiondocumentation 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.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython-h5py-doc
PackageSectiondoc
PackageVersion2.10.0-2build2
SHA-1EC29324B4F5212040019DC6785C2A2AD6872C170
SHA-2566993D6AA2B0934CFD10CC070FD795D79C13D4C5F7E92D64A73FDBD09A58F31B8