Result for 007D9673AB515F50E6467E0DBB3EC88830254244

Query result

Key Value
FileName./usr/lib64/python3.8/site-packages/sklearn/linear_model/tests/__pycache__/test_ridge.cpython-38.pyc
FileSize31514
MD5CA2B1CCB658050E356B913C486631261
SHA-1007D9673AB515F50E6467E0DBB3EC88830254244
SHA-2561629A61E5A2E2499055D4064AB155DEB2248FBAB688C618C27D1F3976D31388A
SSDEEP768:LIOMAJqEly71/NwE/9Lyr31xqwHXwV1KWDciO3nZhraKT:IAJBy71/NwE/Jyr31xk8thr5
TLSHT166E2FBB4B0B76E56FD72F1FC217605109D19E38DA3C6B623F830E31E7DA50892D26668
hashlookup:parent-total2
hashlookup:trust60

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Parents (Total: 2)

The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD561A52FA64006DA080E9B8D3F952C4E81
PackageArchx86_64
PackageDescription Scikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world, building upon numpy, scipy, and matplotlib. As a machine-learning module, it provides versatile tools for data mining and analysis in any field of science and engineering. It strives to be simple and efficient, accessible to everybody, and reusable in various contexts.
PackageMaintainerFedora Project
PackageNamepython3-scikit-learn
PackageRelease2.fc32
PackageVersion0.22.1
SHA-1DB0E60B1636CCF1DA08F6DE62C04A2C4A85E16F9
SHA-256C10285BEAA8944C8F698E3BF9CAB30FCA5E17FD8898D0975C14B9014EF02B418
Key Value
MD5C2EB81F2F4FFA86579390FF7D437AA58
PackageArchaarch64
PackageDescription Scikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world, building upon numpy, scipy, and matplotlib. As a machine-learning module, it provides versatile tools for data mining and analysis in any field of science and engineering. It strives to be simple and efficient, accessible to everybody, and reusable in various contexts.
PackageMaintainerFedora Project
PackageNamepython3-scikit-learn
PackageRelease2.fc32
PackageVersion0.22.1
SHA-1BA9E1CFDF19A6783B0B93CE48A0BBED51B38BA93
SHA-2567A4C5A99C3F3A2C76FB29E124FD5EF82089431B2B87A35FDA68EA979EB04C90F