Result for 76F1D580FD712C84680D37CCCFBA48FC59523C09

Query result

Key Value
FileName./usr/share/doc/python-fuzzywuzzy/changelog.Debian.gz
FileSize696
MD5F15FA4FDFCB89953C1497502487BC12F
SHA-176F1D580FD712C84680D37CCCFBA48FC59523C09
SHA-2568EB3A92F194B18C86DE8855705AB5CAB4D4B237819354CEF46D0E5C9AF80D625
SSDEEP12:XZcFWvyHpw8LmU7Bwd/T/vmwfg358mJywHZ2HfqVYGBo7AuMlxPpI5oRZPwzjCPZ:XZqWvyjLXlwdr/v/gJ8mQq+fWYGBoMh/
TLSHT122014452281A74930BCA954DF97802A9673E3E2AD7F144479DCD363351178602577817
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize12036
MD56CF16F017F310E64F026A767E31F5A17
PackageDescriptionPython module for fuzzy string matching Various methods for fuzzy matching of strings in Python, including: . - String similarity: Gives a measure of string similarity between 0 and 100. - Partial string similarity: Inconsistent substrings are a common problem when string matching. To get around it, use a "best partial" heuristic when two strings are of noticeably different lengths. - Token sort: This approach involves tokenizing the string in question, sorting the tokens alphabetically, and then joining them back into a string. - Token set: A slightly more flexible approach. Tokenize both strings, but instead of immediately sorting and comparing, split the tokens into two groups: intersection and remainder.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython-fuzzywuzzy
PackageSectionpython
PackageVersion0.16.0-2
SHA-15CC40B87E3967560027A26982A7A82FC5E7EDE18
SHA-2564E98805C5DDEB56C5C2D000270F9222F02EF4DB16041A18E577DE92F27787C89