Result for 14C2AE1384EC35873501DE448B9FBFCDDC6AB16B

Query result

Key Value
FileName./usr/share/doc/python-h5py-doc/html/_sources/build.rst.txt
FileSize8121
MD526377C4F34FCB184D2C31090800FCEE1
SHA-114C2AE1384EC35873501DE448B9FBFCDDC6AB16B
SHA-256F7A043E4D6E9D87B1FE383BACDF46D91F9489A2CDA45BB14B51CCE7D9E227410
SSDEEP96:PV3Ku20SlfDR9Fr4YK5vTvufKK5BhnmtDAdLziI+0vSdUQWKWMUTyFTizAV+NyZz:9UrKvuxBxPzBQ9yuiEV+/NWruRWOIBb
TLSHT1D5F1B53FAE687774F601C396A25B0192EF32DE3731809454A8BF40D80363B2692BF55B
hashlookup:parent-total3
hashlookup:trust65

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Parents (Total: 3)

The searched file hash is included in 3 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize217148
MD5ADDBDEFD9EFA40637AB17F932D2CD986
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
PackageVersion3.4.0-1exp1
SHA-1E919494F1C0AD25A7636A1DC754EAB1247A79B93
SHA-2566805615FDF3889E0943231DAA99FF99782DB23EE9A87B071E8FA6386F0ABB503
Key Value
FileSize216580
MD593C56CBD71CE10A56794BA4FAD2D1724
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
PackageVersion3.3.0-2
SHA-1C091938D35DDE45D65E95D38EE595498B4318AD7
SHA-256450BECE82FCF2D3DCA69FC807E65427CA579657E9F15D84DDBEBA2FAAD772D28
Key Value
FileSize218852
MD5B60D783670B3601E533F59C529FE28E8
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
PackageVersion3.3.0-3
SHA-178E7F257B4643E5A4B0183A00E520FF48CB721FA
SHA-2563A17B441E95740F3DFBDF03B28A08B4D28EA85CCFB22FC257869CA98C199FBAE