Result for 076A06EF5C616E94A6F3E40F94CA18ABD183E63C

Query result

Key Value
FileName./usr/lib/python2.7/dist-packages/h5py/h5g.so
FileSize91056
MD5893FC9383574772536B88A7003BAE18A
SHA-1076A06EF5C616E94A6F3E40F94CA18ABD183E63C
SHA-256A6752ED5B6E378D9FAEDAA5EA0BE19287F939C3A798341DC8FFABAE4389EA848
SSDEEP1536:MVcV2DtXKnynhFZRW44rXZztGE6/q1I86x0KCRMzaXFsTrOSeSDR8CxY8E1i1uO2:MGV2D1MELZRP8FnItGie1WevBQPz
TLSHT12593094B7383C5B2E6A64EB417964A7066204212D1E3D3E5F919FF897F36201BF293B0
hashlookup:parent-total1
hashlookup:trust55

Network graph view

Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize493810
MD573FEC70D6D5D5CC9198D515E539E7A74
PackageDescriptionh5py is a 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.
PackageMaintainerSoeren Sonnenburg <sonne@debian.org>
PackageNamepython-h5py
PackageSectionpython
PackageVersion2.2.1-1.1+b1
SHA-18ACF012722B63C06E8F8995AA162134F92A8C790
SHA-256C339A4623BA8FAEA6CF7F7C57ED8617A11711372B9E839D5917CA0D2BCB3EB43