Result for 01C2F2D4BC916C1D4AB6ECE52ED628D8C7837299

Query result

Key Value
FileName./usr/lib/python3.9/site-packages/sklearn/metrics/tests/__pycache__/test_ranking.cpython-39.pyc
FileSize38072
MD5ABACD49C8FA52A90ECD4A27B68793838
SHA-101C2F2D4BC916C1D4AB6ECE52ED628D8C7837299
SHA-256042E6AEF7287586D13BCE0168DF9FC24CA80DC9F63E1D1A6678EC92A54452294
SSDEEP768:I3YP/Clc7t9iyoEOEyygZt1SD0M4LMMI2IN6TyvKb7LcJmHYKbY6pep:EPhXhxLLI26/STUwK
TLSHT1CF03C6ABF8435D6EF911F0F980693310839E832CFB42D743AD15D55EAC527EB4E29688
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
MD520093B191066E2B3C413FD2644EDF50F
PackageArcharmv7hl
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.fc33
PackageVersion0.23.1
SHA-1D98B8D00AD3953C84B8054127546A3FCC82465AD
SHA-25625BE297BA6B732912E4C50F346269044AD14196A5D7D7BF937DFA419CE28C66D