Result for 149177E70255485EE12E8AF0BF92C4D8C7E777A8

Query result

Key	Value
FileName	usr/lib/python3.12/site-packages/emcee-3.1.6.dist-info/LICENSE
FileSize	1109
MD5	7BFC9A1ED80CAA4546DDEC66FD540C47
SHA-1	149177E70255485EE12E8AF0BF92C4D8C7E777A8
SHA-256	5B4188C62D1CA46481057AB47CC15548552C06773E0704A6385CD98F330CB170
SHA-512	15BFF45EE0C9B9D64CB6C275F88406804BBB4B8365AA341E162ADEC88AC0947A755F88EE8388C7A2F2C9F5DC68A9BCACE859B9530F581F7BEC02348827ED1411
SSDEEP	24:b7oCrmJHHH0yN3gtsHw1hC09QHOsUv4eOk4/+/m3oqLFh:bECaJHlxE3dQHOs5exm3ogFh
TLSH	T11111891EB25507721C5A13605579ACD5B13F715F7A5F2A85146DF245133A06CD1FF840
insert-timestamp	1721650331.892127
mimetype	text/plain
source	snap:S3VpJTklG9hO6cKHP7KfqdPS5dhSsdYt_31
tar:gname	root
tar:uname	root
hashlookup:parent-total	28
hashlookup:trust	100

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Parents (Total: 28)

The searched file hash is included in 28 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	03E1F0C041D1CB4B738CE9656FDB92EB
PackageArch	noarch
PackageDescription	Emcee is a stable, well tested Python implementation of the affine-invariant ensemble sampler for Markov chain Monte Carlo (MCMC) proposed by Goodman & Weare (2010). The code is open source and has already been used in several published projects in the Astrophysics literature.
PackageMaintainer	ghibo <ghibo>
PackageName	python3-emcee
PackageRelease	1.mga9
PackageVersion	3.1.3
SHA-1	00D6403585F9B1EF62326C20CDFADAF86894DC67
SHA-256	9AA97DFBED62C986C7BF782C4B4DF4B600D5D4F31B2E03377FA29ECD90661255

Key	Value
MD5	06A7C768308BB5F4EA3A2BDA9960946D
PackageArch	noarch
PackageDescription	Emcee is a Python implementation of the affine-invariant ensemble sampler for Markov chain Monte Carlo (MCMC) proposed by Goodman & Weare (2010) http://cims.nyu.edu/~weare/papers/d13.pdf
PackageName	python38-emcee
PackageRelease	7.10
PackageVersion	3.1.1
SHA-1	0B83C84B987968ADFE53508D88E3B920807BCD9D
SHA-256	1BA7BFDF31C878A77335B985A224122CE37151EE16B3443B5203628B3ED7D07A

Key	Value
MD5	387069683E9154BE807FBC9446C67658
PackageArch	noarch
PackageDescription	Emcee is a Python implementation of the affine-invariant ensemble sampler for Markov chain Monte Carlo (MCMC) proposed by Goodman & Weare (2010) http://cims.nyu.edu/~weare/papers/d13.pdf
PackageName	python39-emcee
PackageRelease	1.1
PackageVersion	3.1.0
SHA-1	12298657739E619DF5C7E0337ACFD9FAF0093138
SHA-256	6DA021854063D785C086F782084E011877FDDAF69968E5C004626E3F4901E778

Key	Value
MD5	DFA9691B2D38D4CF783A0476876D5D8B
PackageArch	noarch
PackageDescription	Emcee is a Python implementation of the affine-invariant ensemble sampler for Markov chain Monte Carlo (MCMC) proposed by Goodman & Weare (2010) http://cims.nyu.edu/~weare/papers/d13.pdf
PackageMaintainer	https://bugs.opensuse.org
PackageName	python38-emcee
PackageRelease	1.2
PackageVersion	3.1.1
SHA-1	1ADB56B575FD15742109771FE6619FC0510B4F46
SHA-256	E12BAA04B4EF0A16620DF2BE87562912304FE4203EC67141C483C73C6C210476

Key	Value
MD5	AD964B64831F212D3B01875019EB9C81
PackageArch	noarch
PackageDescription	Emcee is a Python implementation of the affine-invariant ensemble sampler for Markov chain Monte Carlo (MCMC) proposed by Goodman & Weare (2010) http://cims.nyu.edu/~weare/papers/d13.pdf
PackageName	python39-emcee
PackageRelease	7.12
PackageVersion	3.1.1
SHA-1	254A60D826B0452AA9EE299DB3156CED3849758A
SHA-256	8F9A0B28EC754E28D63E893C940B4FB63EC39C2EBE6B1711281EDC71E87B1E98

Key	Value
FileName	http://dl-cdn.alpinelinux.org/alpine/latest-stable//community//x86_64//py3-emcee-3.1.6-r0.apk
MD5	8D3832B2C98FBB1EDF59126CD1F45031
SHA-1	299FE8EA8CF70F2F2C3595D6900E6A5CD689679A
SHA-256	B15328E9C470C2C51D15EEF442E586C909EC8F79BA64172ABA3436748BCC7940
SSDEEP	768:ixOK9OIb0MvKRdfowYkrSY9OGA4lZfnPd:0OK3JKnthAAfn1
TLSH	T190D2F17A45001666B0FF80A6E1710CBE50694AD675AAB3F3653D16B203393CD0CE3BAF

Key	Value
MD5	3E4B6178816B41DB46D3EA46EF2AB1D5
PackageArch	noarch
PackageDescription	Emcee is a Python implementation of the affine-invariant ensemble sampler for Markov chain Monte Carlo (MCMC) proposed by Goodman & Weare (2010) http://cims.nyu.edu/~weare/papers/d13.pdf
PackageName	python39-emcee
PackageRelease	7.11
PackageVersion	3.1.1
SHA-1	2A680AEC6E675EC28CB68BBAE4F855C3B6F808FC
SHA-256	B138C47B80E6F83A1E4B88D01FF296F7FB16AF563814919589B56418177746CB

Key	Value
MD5	73C4AF9D87621DE9B5DF374835C9388A
PackageArch	noarch
PackageDescription	Emcee is a Python implementation of the affine-invariant ensemble sampler for Markov chain Monte Carlo (MCMC) proposed by Goodman & Weare (2010) http://cims.nyu.edu/~weare/papers/d13.pdf
PackageName	python310-emcee
PackageRelease	7.11
PackageVersion	3.1.1
SHA-1	3495D3E0FC0B9B1B577BBCF4FE72F9BF9F3F917D
SHA-256	4A5B2A9709D3106DE0D352AC95684BE1D62CD3D981CFD141062CA8AC6F00B16A

Key	Value
MD5	8BB9C19AF1E7D1F7C6AC1A638A2F90A5
PackageArch	noarch
PackageDescription	Emcee is a Python implementation of the affine-invariant ensemble sampler for Markov chain Monte Carlo (MCMC) proposed by Goodman & Weare (2010) http://cims.nyu.edu/~weare/papers/d13.pdf
PackageName	python3-emcee
PackageRelease	2.4
PackageVersion	3.1.1
SHA-1	39298F9D84B6D35467F3052EAEF97DFD2FA1DFA7
SHA-256	72A7E780B39DD6C272F7AEF220307E831831E259A384C7DB6E16B07ACB7F1899

Key	Value
MD5	52D86774823AF30231A30C358FC7ACB3
PackageArch	noarch
PackageDescription	Emcee is a stable, well tested Python implementation of the affine-invariant ensemble sampler for Markov chain Monte Carlo (MCMC) proposed by Goodman & Weare (2010). The code is open source and has already been used in several published projects in the Astrophysics literature.
PackageMaintainer	umeabot <umeabot>
PackageName	python3-emcee
PackageRelease	3.mga9
PackageVersion	3.1.1
SHA-1	3E2BCA13E99F20D16BF5D81B414DD0950B0D02BA
SHA-256	D3EF1E9BC2A171DFF8F47848917991DFD1C999CDEA9F9EE8CA1B948159786487