Result for 43550C797786416D9CCF28D7E2D33A054CF8060A

Query result

Key Value
FileName./usr/lib/python3/dist-packages/emcee/ensemble.py
FileSize18687
MD51A6BD62BC3E24C702F765E7E5DDD047B
SHA-143550C797786416D9CCF28D7E2D33A054CF8060A
SHA-256D181A960E568B1AD0E9673388849EBC61B6CE2742FC3BEA46E5E4584FB82A9B0
SSDEEP384:pLjO55lZolRAyhxx0rREYGdh4NLcoarNmFWq:pLi/o7AyhjFYIO4cFWq
TLSHT1AE82E722FA405BB38347453915EFA113673A9827A2E8D46878BED2581F06D34D3F4EE8
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