Parents (Total: 9)

The searched file hash is included in 9 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	32808
MD5	E84480C7537C72439E5949D9DEA099DA
PackageDescription	extension for computing string similarities and edit distances The Levenshtein module computes Levenshtein distances, similarity ratios, generalized medians and set medians of Unicode or non-Unicode strings. Because it's implemented in C, it's much faster than the corresponding Python library functions and methods. . The Levenshtein distance is the minimum number of single-character insertions, deletions, and substitutions to transform one string into another. . It is useful for spell checking, or fuzzy matching of gettext messages.
PackageMaintainer	Ubuntu MOTU Developers <ubuntu-motu@lists.ubuntu.com>
PackageName	python-levenshtein
PackageSection	python
PackageVersion	0.10.1-1ubuntu2
SHA-1	9433B65175FCD0B603CB45FB846A7E0FC3B2B035
SHA-256	96F2F8DBA2A263FB9D15EA7D72838D6E9D0264EAEB9D9D434093D4E91493644D

Key	Value
FileSize	38092
MD5	DEC96A4DDA7E0C5F02D8CCC27B09B184
PackageDescription	extension for computing string similarities and edit distances The Levenshtein module computes Levenshtein distances, similarity ratios, generalized medians and set medians of Unicode or non-Unicode strings. Because it's implemented in C, it's much faster than the corresponding Python library functions and methods. . The Levenshtein distance is the minimum number of single-character insertions, deletions, and substitutions to transform one string into another. . It is useful for spell checking, or fuzzy matching of gettext messages.
PackageMaintainer	Ubuntu MOTU Developers <ubuntu-motu@lists.ubuntu.com>
PackageName	python-levenshtein
PackageSection	python
PackageVersion	0.10.1-1ubuntu2
SHA-1	95324A0C14CA7C08D783DFCF2E8B14476EC94332
SHA-256	A781BE5D41E10A490153C0FABAF724957E5A5D879E31752F1C058C0A13856C1B

Key	Value
FileSize	38280
MD5	A90E9B63C1706CAA84344FEA5E747040
PackageDescription	extension for computing string similarities and edit distances The Levenshtein module computes Levenshtein distances, similarity ratios, generalized medians and set medians of Unicode or non-Unicode strings. Because it's implemented in C, it's much faster than the corresponding Python library functions and methods. . The Levenshtein distance is the minimum number of single-character insertions, deletions, and substitutions to transform one string into another. . It is useful for spell checking, or fuzzy matching of gettext messages.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	python-levenshtein
PackageSection	python
PackageVersion	0.10.1-1.1
SHA-1	370270C7DA0BBDD1E9E867A7E9FF7643E6FB192E
SHA-256	1CFE7482A8E1B139B3B7FFCBB6F8D4A060EA7DF5AB93FAC7B3CBD82A93DB1F37

Key	Value
FileSize	35436
MD5	42FEFA5726655522DCA82C8ABC16FE16
PackageDescription	extension for computing string similarities and edit distances The Levenshtein module computes Levenshtein distances, similarity ratios, generalized medians and set medians of Unicode or non-Unicode strings. Because it's implemented in C, it's much faster than the corresponding Python library functions and methods. . The Levenshtein distance is the minimum number of single-character insertions, deletions, and substitutions to transform one string into another. . It is useful for spell checking, or fuzzy matching of gettext messages.
PackageMaintainer	Ubuntu MOTU Developers <ubuntu-motu@lists.ubuntu.com>
PackageName	python-levenshtein
PackageSection	python
PackageVersion	0.10.1-1ubuntu2
SHA-1	73D32A4ED4DEAFB648B7A52B576909A77282189E
SHA-256	62B4838B1755B1C390BFD6824DFAC0D0A50A5A08F360C8823E1B7110115C2EB0

Key	Value
FileSize	38170
MD5	981532A67A314C0EC87CA38BD41F2F42
PackageDescription	extension for computing string similarities and edit distances The Levenshtein module computes Levenshtein distances, similarity ratios, generalized medians and set medians of Unicode or non-Unicode strings. Because it's implemented in C, it's much faster than the corresponding Python library functions and methods. . The Levenshtein distance is the minimum number of single-character insertions, deletions, and substitutions to transform one string into another. . It is useful for spell checking, or fuzzy matching of gettext messages.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	python-levenshtein
PackageSection	python
PackageVersion	0.10.1-1.1
SHA-1	5102525E247BB32477983CF1270382F77A34D9CC
SHA-256	ABB043E06D070BD5EF0F91B0676E1A5FB8FD6C9B0732E0C6260D4B742F8F0128

Key	Value
FileSize	51350
MD5	81CE09442EE86E2657EB9EE7F683413A
PackageDescription	extension for computing string similarities and edit distances The Levenshtein module computes Levenshtein distances, similarity ratios, generalized medians and set medians of Unicode or non-Unicode strings. Because it's implemented in C, it's much faster than the corresponding Python library functions and methods. . The Levenshtein distance is the minimum number of single-character insertions, deletions, and substitutions to transform one string into another. . It is useful for spell checking, or fuzzy matching of gettext messages.
PackageMaintainer	Ubuntu MOTU Developers <ubuntu-motu@lists.ubuntu.com>
PackageName	python-levenshtein
PackageSection	python
PackageVersion	0.10.1-1ubuntu2
SHA-1	89B3E23CD44BA0A1B27F82C500EF56FDCD60DC62
SHA-256	40E275E9A5CC9B47E7A0B71630B401678277913EDCC70A5A6E2AE38F674D2FA0

Key	Value
FileSize	38192
MD5	309D005A7CD51331AC207E70451CC488
PackageDescription	extension for computing string similarities and edit distances The Levenshtein module computes Levenshtein distances, similarity ratios, generalized medians and set medians of Unicode or non-Unicode strings. Because it's implemented in C, it's much faster than the corresponding Python library functions and methods. . The Levenshtein distance is the minimum number of single-character insertions, deletions, and substitutions to transform one string into another. . It is useful for spell checking, or fuzzy matching of gettext messages.
PackageMaintainer	Ubuntu MOTU Developers <ubuntu-motu@lists.ubuntu.com>
PackageName	python-levenshtein
PackageSection	python
PackageVersion	0.10.1-1ubuntu2
SHA-1	3693AC0EF422ECFECD8395EC0D8F535EC3DB3008
SHA-256	B3725B99D34D51A04BDA5C064F5E6C8C89E375304F0B0E1FCE4494582EE398FB

Key	Value
FileSize	35442
MD5	E826C59096CEE42C3AA4154EA880B474
PackageDescription	extension for computing string similarities and edit distances The Levenshtein module computes Levenshtein distances, similarity ratios, generalized medians and set medians of Unicode or non-Unicode strings. Because it's implemented in C, it's much faster than the corresponding Python library functions and methods. . The Levenshtein distance is the minimum number of single-character insertions, deletions, and substitutions to transform one string into another. . It is useful for spell checking, or fuzzy matching of gettext messages.
PackageMaintainer	Ubuntu MOTU Developers <ubuntu-motu@lists.ubuntu.com>
PackageName	python-levenshtein
PackageSection	python
PackageVersion	0.10.1-1ubuntu2
SHA-1	86F3139C2BCECC5B2CD1FA3B6F1B7D8C331C48D6
SHA-256	B82E7F0FF7DF489F35A02112B95E61A50B8A6CD50B3B5957ED710A1DD3737092

Key	Value
FileSize	35410
MD5	B728CB64DADD720A5583721684DAC4A7
PackageDescription	extension for computing string similarities and edit distances The Levenshtein module computes Levenshtein distances, similarity ratios, generalized medians and set medians of Unicode or non-Unicode strings. Because it's implemented in C, it's much faster than the corresponding Python library functions and methods. . The Levenshtein distance is the minimum number of single-character insertions, deletions, and substitutions to transform one string into another. . It is useful for spell checking, or fuzzy matching of gettext messages.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	python-levenshtein
PackageSection	python
PackageVersion	0.10.1-1.1
SHA-1	9CE66F6613C2B4E67423CF9F9FE16AEB145F299D
SHA-256	76D69270E3572A900B50D981ACB6A0889150E862B3A672AC1173AA6D032C1E9D