Result for 02A89597E01EC113042FB01092DDD9781EC5D0D7

Query result

Key Value
FileName./usr/lib64/python3.6/site-packages/numpy/matrixlib/tests/__pycache__/test_regression.cpython-36.pyc
FileSize1988
MD595F4CDB557EB56B30696EF4C3613B045
SHA-102A89597E01EC113042FB01092DDD9781EC5D0D7
SHA-256173EBC3A6AED4C6A8CE2B0E9B758CB427627296C95CE84B5C4AF98776D35215F
SSDEEP48:Q+M5VXn3b0Dlrk0eOOhc5J0H0la1i9/BkAdh58IqeR:ubgpJeOOW5JM04g5kAH
TLSHT16F41699E8A414C7AFDD1F5FDE42A07204B728162F7C6D271562D951E1E615C70EF0781
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
MD596F1E09D933D373B32E122AE47C30A69
PackageArchppc64
PackageDescriptionNumPy is a general-purpose array-processing package designed to efficiently manipulate large multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional arrays. NumPy is built on the Numeric code base and adds features introduced by numarray as well as an extended C-API and the ability to create arrays of arbitrary type. There are also basic facilities for discrete fourier transform, basic linear algebra and random number generation.
PackageMaintainerFedora Project
PackageNamepython36-numpy
PackageRelease7.el7
PackageVersion1.10.4
SHA-1B1CCAA7A355D9E011C723E3E00B47E8446A7886C
SHA-256FB2DEBC3E677C4BABA71F9C43D29A4E385AF2D7FB2533258136DE29C102403E0