Python extension for computing string edit distances and similarities.
Project description
Levenshtein
Introduction
The Levenshtein Python C extension module contains functions for fast computation of:
- Levenshtein (edit) distance, and edit operations
- string similarity
- approximate median strings, and generally string averaging
- string sequence and set similarity
This is a fork of ztane/python-Levenshtein <https://github.com/ztane/python-Levenshtein>
_, since the original
project is no longer actively maintained.
Requirements
- Python 2.7 or later
Installation
.. code-block:: bash pip install levenshtein
Documentation
The documentation for the current version can be found at <https://maxbachmann.github.io/Levenshtein/>
_
License
Levenshtein is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.
See the file COPYING <https://github.com/maxbachmann/Levenshtein/blob/main/COPYING>
_ for the full text of GNU General Public License version 2.
Changelog
v0.13.0
- Maintainership passed to Max Bachmann
- use faster bitparallel implementations for distance and ratio
- avoid string copies in distance, ratio and hamming
- Fix usage of deprecated Unicode APIs in distance, ratio and hamming
- Fixed incorrect window size inside Jaro and Jaro-Winkler implementation
- Fixed incorrect exception messages
- Removed unused functions and compiler specific hacks
- Split the Python and C implementations to simplify building of the C library
- Fixed multiple bugs which prevented the use as C library, since some functions only got defined when compiling for Python
- Build and deliver python wheels for the library
- Fixed incorrect allocation size in lev_editops_matching_blocks and lev_opcodes_matching_blocks
v0.12.1
- Fixed handling of numerous possible wraparounds in calculating the size of memory allocations; incorrect handling of which could cause denial of service or even possible remote code execution in previous versions of the library.
v0.12.0
- Fixed a bug in StringMatcher.StringMatcher.get_matching_blocks /
extract_editops for Python 3; now allow only
str
editops on both Python 2 and Python 3, for simpler and working code. - Added documentation in the source distribution and in GIT
- Fixed the package layout: renamed the .so/.dll to _levenshtein, and made it reside inside a package, along with the StringMatcher class.
- Fixed spelling errors.
v0.11.2
-
Fixed a bug in setup.py: installation would fail on Python 3 if the locale did not specify UTF-8 charset (Felix Yan).
-
Added COPYING, StringMatcher.py, gendoc.sh and NEWS in MANIFEST.in, as they were missing from source distributions.
v0.11.1
- Added Levenshtein.h to MANIFEST.in
v0.11.0
- Python 3 support, maintainership passed to Antti Haapala
v0.10.2
- Made python-Lehvenstein Git compatible and use setuptools for PyPi upload
- Created HISTORY.txt and made README reST compatible
v0.10.1
- apply_edit() broken for Unicodes was fixed (thanks to Radovan Garabik)
- subtract_edit() function was added
v0.10.0
- Hamming distance, Jaro similarity metric and Jaro-Winkler similarity metric were added
- ValueErrors raised on wrong argument types were fixed to TypeErrors
v0.9.0
- a poor-but-fast generalized median method quickmedian() was added
- some auxiliary functions added to the C api (lev_set_median_index, lev_editops_normalize, ...)
v0.8.2
- fixed missing `static' in the method list
v0.8.1
- some compilation problems with non-gcc were fixed
v0.8.0
- median_improve(), a generalized median improving function, was added
- an arbitrary length limitation imposed on greedy median() result was removed
- out of memory should be handled more gracefully (on systems w/o memory overcomitting)
- the documentation now passes doctest
v0.7.0
- fixed greedy median() for Unicode characters > U+FFFF, it's now usable with whatever integer type wchar_t happens to be
- added missing MANIFEST
- renamed exported C functions, all public names now have lev_, LEV_ or Lev prefix; defined lev_byte, lev_wchar, and otherwise santinized the (still unstable) C interface
- added edit-ops group of functions, with two interfaces: native, useful for string averaging, and difflib-like for interoperability
- added an example SequenceMatcher-like class StringMatcher
v0.6.0
- a segfault in seqratio()/setratio() on invalid input has been fixed to an exception
- optimized ratio() and distance() (about 20%)
- Levenshtein.h header file was added to make it easier to actually use it as a C library
v0.5.0
- a segfault in setratio() was fixed
- median() handles all empty strings situation more gracefully
v0.4.0
- new functions seqratio() and setratio() computing similarity between string sequences and sets
- Levenshtein optimizations (affects all routines except median())
- all Sequence objects are accepted, not just Lists
v0.3.0
- setmedian() finding set median was added
- median() initial overhead for Unicodes was reduced
v0.2.0
- ratio() and distance() now accept both Strings and Unicodes
- removed uratio() and udistance()
- Levenshtein.c is now compilable as a C library (with -DNO_PYTHON)
- a median() function finding approximate weighted median of a string set was added
v0.1.0
- Inital release
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BLAKE2b-256 | aeeba68347ab77be185a9fc6bb5e2cce07305855f244c6ed1a1a8389e2c937e8 |
Hashes for Levenshtein-0.13.0-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
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SHA256 | d6429a677486936590d4728dc8b2abed7d82a5bb816ebff620a79a0771753298 |
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MD5 | ff5878c327d04e9b38c0f9332542d744 |
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BLAKE2b-256 | 293c371f139838267987cb1fe760659b634f4b33c70cbba01d6f4c5594915623 |
Hashes for Levenshtein-0.13.0-cp36-cp36m-win_amd64.whl
Algorithm | Hash digest | |
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SHA256 | e13bfb16eec734f24664403efdd96130b57e15e36156ff26c71117e176c760e2 |
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MD5 | 34ebfa87b65c80b8042a702d22a6f691 |
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BLAKE2b-256 | b36418e1f249d70739b87cde178aaadf25e0fa9c0c5a3df23e804a9b3263b69e |
Hashes for Levenshtein-0.13.0-cp36-cp36m-win32.whl
Algorithm | Hash digest | |
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SHA256 | 24c29fa766364a664ddbab8cf25e38d56eac0ce99b81f1a163219c674c731cae |
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MD5 | 1065fb99c4bfa3868c727baf59ed7c64 |
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BLAKE2b-256 | fd04151ed35867c0bf415a2180a00d5db3cefe0adad3a008f9c931e7c325f88a |
Hashes for Levenshtein-0.13.0-cp36-cp36m-manylinux2014_s390x.whl
Algorithm | Hash digest | |
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SHA256 | 22fb7848097245d552e1bf85f23a030fd984d3cf2bcb033e54d68b599723c9cd |
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MD5 | c1a8291bc34b55c318f78dae0175e122 |
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BLAKE2b-256 | 3c39ef6243e327eb32b986f37c8439da683f0a468484408490ebe589ec575927 |
Hashes for Levenshtein-0.13.0-cp36-cp36m-manylinux2014_ppc64le.whl
Algorithm | Hash digest | |
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SHA256 | a0966aab2bf1eebe56a23dcb8189054aad0dcd25f5e846f79698601f1adf9a9b |
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MD5 | c0619b35ff305ebd348d9bfd4d8e9479 |
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BLAKE2b-256 | 55d47e9adf31e57909a36d74d6f1dfbd55e24d0ceb5eeffb846eb8c09c904398 |
Hashes for Levenshtein-0.13.0-cp36-cp36m-manylinux2014_aarch64.whl
Algorithm | Hash digest | |
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SHA256 | 4bd322fc2e057102cade0cf86f72676d1c22be2e920e98eab4abac55118bfe34 |
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MD5 | 3d52879a5cba09b7e5308b8daf0b882d |
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BLAKE2b-256 | 959b53d47b933b0b4c14c7bd02f008a9bf8924de7f0ea6547d8ddd47d7ba97a9 |
Hashes for Levenshtein-0.13.0-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | dcd1849314c29b403b1928f0a72980149f64376305368ed4061cf8aff5f75dcb |
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MD5 | ed4fbb412263e330f6f2b895c7a4702e |
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BLAKE2b-256 | d1d654348ab0c2e6ab6b5ff28957861a2965c6d7f7116d2898482f3822005211 |
Hashes for Levenshtein-0.13.0-cp36-cp36m-manylinux2010_i686.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b755e796a1ab72b4520a75d20da175e69f443eb8648214a8f233de6c79ce70fa |
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MD5 | 8c6e47099af313ec5aab0e764edcc603 |
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BLAKE2b-256 | aa7c5d4e8fa022e8bff2762e372cd783dcf59186b31e1b0c0c429a363b90a5f4 |
Hashes for Levenshtein-0.13.0-cp36-cp36m-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | ec249d2f3f3c1cf1d53f04d61de1bb5378d22865651c7d21c395581d197e942e |
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MD5 | e0d8c3cfb129d4fe2d2ab8c4ea4b503a |
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BLAKE2b-256 | 0a89e8cc72e8efa98f118c9a55b803d548a1672280c666a3a66a015e3a6dacb5 |
Hashes for Levenshtein-0.13.0-cp36-cp36m-manylinux1_i686.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | adae32eb8c292f249f13532ae63ce9ca33ed9327a93ac20059ee47eba571fd51 |
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MD5 | fbd49ba8afbb540ef3969039a295cd71 |
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BLAKE2b-256 | c1ae13ccb19e4b6e9b9ee915a817b060d704aa4e9910cf2520eef5a08b8f9a36 |
Hashes for Levenshtein-0.13.0-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | f648d38e710ed4d0b37c3197b047087bcecf7ba466c0819a5d29479795add609 |
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MD5 | d1aad0ef086d75cdd39a8fe688abb7a2 |
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BLAKE2b-256 | fd0db6b583e7f3b303231fc32cb4ca25f39aebb231ccd3a450f12c7aee5856fc |
Hashes for Levenshtein-0.13.0-cp35-cp35m-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 557fd5e905dfa09a358f68c20c1906f9b134fa5e529f37f750e499527cffa46b |
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MD5 | d43e65b55ffaeed9e12d139027fee113 |
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BLAKE2b-256 | c36dac34fe6aa0f2f4058fb8abd6b4820d094981e3de3d1d4c57f58aa994bbc0 |
Hashes for Levenshtein-0.13.0-cp35-cp35m-win32.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | a09a509f13a46fadff6f31ebd5fcc49485f59556cee1ec5b080fd3c69a4161ac |
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MD5 | 8e0f6a7618436025cd452e08d7f26643 |
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BLAKE2b-256 | 8951068d871a26e137094e1130cfad9641ff6554efd00ee65aba22f97519be1d |
Hashes for Levenshtein-0.13.0-cp35-cp35m-manylinux2014_s390x.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5db88bf4d8a8bda677386d7ac68a643855c417e357d36ac760860cedb24be8e7 |
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MD5 | 066ba41832823a9f4772dc67b75f952b |
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BLAKE2b-256 | 611fefb3ace71d13eb184df0a84b022b1dd556d8f0689df19e35cc3851dade41 |
Hashes for Levenshtein-0.13.0-cp35-cp35m-manylinux2014_ppc64le.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 6854628006c38cd1b707f621cb211e5e618f25214d607c7002f5fbbc9c31eff4 |
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MD5 | 571c5b6b6a3e4822fae5a84bebcb6550 |
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BLAKE2b-256 | 9052e9a5e4c2f57ac9fb07e58ae69b09a4ab1f53654e2bdee114884c74d63093 |
Hashes for Levenshtein-0.13.0-cp35-cp35m-manylinux2014_aarch64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | cff5999f33c5fbf262e040ca53152749f804f54149a4bd4b4584c918ca0f275e |
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MD5 | b891f6188e08ca7eef3ea37e69b3c64b |
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BLAKE2b-256 | e863d66ca7507f2404b821caba827a83c1ecfb81e3ce80dab5e821259927a613 |
Hashes for Levenshtein-0.13.0-cp35-cp35m-manylinux2010_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0d619cc01d818abb7bf95618a04d23adb069f0e93d6c58abf9c6fbcdad9a96c6 |
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MD5 | 7ce6ba1b79101a0c7a1e78f0bdeab32b |
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BLAKE2b-256 | c160e6168adc394d75abbce5d00912209b79eae5b6eb13f2cc9d9344e1361071 |
Hashes for Levenshtein-0.13.0-cp35-cp35m-manylinux2010_i686.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0c54ecf6b8edfccfd873bb53c8759a4be528828fed22fd77f173df73cd2c0c75 |
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MD5 | 6e4af4f106c05c5f1b71eeade3c698ef |
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BLAKE2b-256 | 2bfc57d51f01b5fb40f2bcb127baa623346f1b0cf855c41e2e2904a58a790b64 |
Hashes for Levenshtein-0.13.0-cp35-cp35m-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2c2a61f0b323cabbfbf603f279619012231e2aa609cb86c63f37df1e7c04749b |
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MD5 | b63899fca157fd424e206d1913f8ed38 |
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BLAKE2b-256 | ab48ed3c298776aed54e7b7574bc544bb6c08e798c4dde1a73902bba98f8effa |
Hashes for Levenshtein-0.13.0-cp35-cp35m-manylinux1_i686.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | a49bb6e0b46a0fd85c497475dc5751e2e87aa30f436ee2f5011c97ee9c71f4a3 |
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MD5 | 9015eae1775274782240424c6983e0cc |
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BLAKE2b-256 | d8cce411936a7921afaafd58b5a55a127639bf20a59dcad6f08b66606b9815eb |
Hashes for Levenshtein-0.13.0-cp35-cp35m-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 62b0004a24271ce8c69016364e371ec448eded0a9a0df0d1672ff0027cfc2f0b |
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MD5 | a2343667cbd42318a230b963142acf6a |
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BLAKE2b-256 | 1fee9345a4bba5ab61fa89aee1ca0415546f9da4b2662fe93fa04710807549de |