Result for 257712C5FA4C87FCCE4B6B226BAE493A04C7A635

Query result

Key Value
FileName./usr/lib/python3/dist-packages/emcee/__init__.py
FileSize933
MD5996BB3F0BCF6AD09B059C8449499E3F1
SHA-1257712C5FA4C87FCCE4B6B226BAE493A04C7A635
SHA-25651C7EF33F14617F1E0E65E884DEB88FE6D01F8F714EBFCFB09308BDB0B7DDB30
SSDEEP12:HtcKyuj661wa4JCfRo63XUHZiNwzQE9Q/YInA82CZZesQmq+SAAdqlXWo5YLDEI5:m6l1wl6Js7Q/YIUKsdqPYLXUi
TLSHT10E11B10B8D232690975BC1DC08D64030177F6A3B1F443829F4DC57514F522286AA5B7D
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