Result for C13B9ABC45B6316B4544CF8C9932DE2D09A55AC3

Query result

Key Value
FileName./usr/share/doc/python3-emcee/changelog.Debian.gz
FileSize321
MD538515227BFDA9D1C269206ACB31F0831
SHA-1C13B9ABC45B6316B4544CF8C9932DE2D09A55AC3
SHA-2563486954D855A5E65D9CCAC40ED6AF7B995CBD056DFB02B04D7C316A41E66376B
SSDEEP6:XtrvwxIZ60V65J4XqCA5ub+IdcuDWrVXpvC32pj/S4TyTKmK4uUtdlpiwRM:XFox+JUbCzbLDWrVXpvt/xR45MKM
TLSHT11AE07DC346729237F474C5F0824CAA46D0ADA69E10BC92D05A5FB6A4D7A910076BCA29
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
FileSize20950
MD59154029D2D6E37E077740FEFD94A3E45
PackageDescriptionAffine-invariant ensemble MCMC sampling for Python 3 emcee is an extensible, pure-Python implementation of Goodman & Weare's Affine Invariant Markov chain Monte Carlo (MCMC) Ensemble sampler. It's designed for Bayesian parameter estimation. . This is the Python 3 package.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython3-emcee
PackageSectionpython
PackageVersion2.1.0-5
SHA-181B325B0B94D7FAB52443297373A512798696D19
SHA-256C5C120686BB4A2034D7F8A2D87FCFA5BC247F6CA7BA084FAD41E1C759A76B5F2
Key Value
FileSize20878
MD5DB5C74813F73B5D3FB76B4D17EA27E8E
PackageDescriptionAffine-invariant ensemble MCMC sampling for Python emcee is an extensible, pure-Python implementation of Goodman & Weare's Affine Invariant Markov chain Monte Carlo (MCMC) Ensemble sampler. It's designed for Bayesian parameter estimation. . This is the Python 2 package.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython-emcee
PackageSectionpython
PackageVersion2.1.0-5
SHA-107A6AD42D90C8AE4C36D89D7AFC8772F00F4D050
SHA-2566BE3C88F3F83E4B872ABE37ADEFA8D939C882C6619C0246AAA8F9DBF627C3AF1