Result for FEF1DF3EDD9BE0F7C986A1B8C44E14F2919848F9

Query result

Key	Value
FileName	./usr/lib/python3.10/site-packages/pykdtree/__pycache__/__init__.cpython-310.pyc
FileSize	147
MD5	F12DC397636F0D0403AF7D6F3821DB50
SHA-1	FEF1DF3EDD9BE0F7C986A1B8C44E14F2919848F9
SHA-256	FCD626131EC95FA24C9DC6F1E8D084F0455EAF71B0D4E372B6F8F9F4831D2F6C
SSDEEP	3:y/EdL/luleh/wZWe/JG9YJgLdWrziRQHRkcTgp:y/EPqeh/wtG9YJgMrVD4
TLSH	T157C0220082288283F82EFE323020232020C0CAA2A38BA8C33E08028A0C08B880C23000
hashlookup:parent-total	2
hashlookup:trust	60

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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
MD5	823B9153725C050C3EC1CFCB6925087C
PackageArch	armv7hl
PackageDescription	Pykdtree is a kd-tree implementation for fast nearest neighbour search in Python. The aim is to be the fastest implementation around for common use cases (low dimensions and low number of neighbours) for both tree construction and queries. Queries are optionally multithreaded using OpenMP.
PackageMaintainer	umeabot <umeabot>
PackageName	python3-pykdtree
PackageRelease	4.mga9
PackageVersion	1.3.4
SHA-1	CD716BF017C6393D4C32140AD0BD46DFB0A7B10D
SHA-256	948EACC0B8FE87361F3ACFC5DE0CA5C1012CADB76089D04A2E2355B8541B388D

Key	Value
MD5	186A80D81B8F5B38DD34410E18460B24
PackageArch	i586
PackageDescription	Pykdtree is a kd-tree implementation for fast nearest neighbour search in Python. The aim is to be the fastest implementation around for common use cases (low dimensions and low number of neighbours) for both tree construction and queries. Queries are optionally multithreaded using OpenMP.
PackageMaintainer	umeabot <umeabot>
PackageName	python3-pykdtree
PackageRelease	4.mga9
PackageVersion	1.3.4
SHA-1	37930A94E2D585D801587DCB591869942F2E61BD
SHA-256	51939D6CEBA33A701AED1E23B352771F456B44CB4F19C157D7A7217F41D7DE92