Result for A7987710D63848958660F4C793AF0F32D29D6B40

Query result

Key Value
FileName./usr/share/doc/python-fuzzywuzzy/changelog.Debian.gz
FileSize661
MD5B8A404B11C21D703B07B55539140BD0F
SHA-1A7987710D63848958660F4C793AF0F32D29D6B40
SHA-256D6AB41F83EA63A753C808E52900AD3E4E2C6EFD42100A26681B672F98E781F46
SSDEEP12:X1FZ24L0BKExGVTZ+VmYttfuQ2Laayrc83DaXW/EVjHnKIxIINu28qz6CcPuNr2Q:X1m4L0BtYUMTajmZbXISbWwNr2Q
TLSHT17701C808802B723DD76000BDC10E71153527B1441C57B20712870CE501602B1DB4E8DC
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
FileSize10796
MD59B63717E5859651B144808240A7EFE53
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 sort: 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
PackageVersion0.11.1-2
SHA-1A7FE4F10628635E9AF609B5A50EBE59620F37840
SHA-256EC5A042CCA0DE032EC8DC6C12F53587F8C5D55ECCB48B7CBD5AAEF8968D9121B