Result for 040D16BD67A14D6C3EDE43E7550756E7B48E4450

Query result

Key Value
FileName./usr/lib/python3.8/site-packages/seaborn/__pycache__/linearmodels.cpython-38.pyc
FileSize288
MD569F3472782BD2691536C0661B15AAA6A
SHA-1040D16BD67A14D6C3EDE43E7550756E7B48E4450
SHA-256D4E73726C8526C892B1EC7E4F9097260FE806564065645816CCBAC5D7BA282C7
SSDEEP6:cIt/Y+JjXsiXYs/lIWBMFXnFB00S0oXD0HjbFQC9YvLorbz7DIRm:cS/Y2wm/qxVB00LiD0DRQCw+7UA
TLSHT1BFD02B4001145FA5C519F4F57120687107D914D1F26F410A5B8C72DBAD9C5E60DA6D54
hashlookup:parent-total1
hashlookup:trust55

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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
MD5CA1DD84D60A3070490F95F0C640E2B2B
PackageArchnoarch
PackageDescriptionSeaborn is a library for making attractive and informative statistical graphics in Python. It is built on top of matplotlib and tightly integrated with the PyData stack, including support for numpy and pandas data structures and statistical routines from scipy and statsmodels.
PackageMaintainerFedora Project
PackageNamepython3-seaborn
PackageRelease9.fc32
PackageVersion0.9.0
SHA-15254451A8880CF7EE1308F6B7578705B08E3A845
SHA-256E6AE8D1FD7761305897D4B3C56698582A767EFBA11337C7487AB268FA8E5A16A