pyxDamerauLevenshtein


NamepyxDamerauLevenshtein JSON
Version 1.8.0 PyPI version JSON
download
home_pagehttps://github.com/lanl/pyxDamerauLevenshtein
SummarypyxDamerauLevenshtein implements the Damerau-Levenshtein (DL) edit distance algorithm for Python in Cython for high performance.
upload_time2024-05-02 18:11:47
maintainerGeoffrey Fairchild
docs_urlNone
authorGeoffrey Fairchild
requires_pythonNone
licenseBSD 3-Clause License
keywords
VCS
bugtrack_url
requirements Cython
Travis-CI
coveralls test coverage No coveralls.
            pyxDamerauLevenshtein implements the Damerau-Levenshtein (DL) edit distance algorithm for Python in Cython for high performance. Courtesy `Wikipedia <http://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance>`_: In information theory and computer science, the Damerau-Levenshtein distance (named after Frederick J. Damerau and Vladimir I. Levenshtein) is a "distance" (string metric) between two strings, i.e., finite sequence of symbols, given by counting the minimum number of operations needed to transform one string into the other, where an operation is defined as an insertion, deletion, or substitution of a single character, or a transposition of two adjacent characters. This implementation is based on `Michael Homer's pure Python implementation <https://web.archive.org/web/20150909134357/http://mwh.geek.nz:80/2009/04/26/python-damerau-levenshtein-distance/>`_, which implements the `optimal string alignment distance algorithm <https://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance#Optimal_string_alignment_distance>`_. It runs in ``O(N*M)`` time using ``O(M)`` space. It supports unicode characters. For more information on pyxDamerauLevenshtein, visit the `GitHub project page <https://github.com/lanl/pyxDamerauLevenshtein>`_.

            

Raw data

            {
    "_id": null,
    "home_page": "https://github.com/lanl/pyxDamerauLevenshtein",
    "name": "pyxDamerauLevenshtein",
    "maintainer": "Geoffrey Fairchild",
    "docs_url": null,
    "requires_python": null,
    "maintainer_email": "mail@gfairchild.com",
    "keywords": null,
    "author": "Geoffrey Fairchild",
    "author_email": "mail@gfairchild.com",
    "download_url": "https://files.pythonhosted.org/packages/9b/05/bf5cd8fd5cf64d29f61e756a6fda23eb2b468e680d3ea2fbf130c816ebed/pyxdameraulevenshtein-1.8.0.tar.gz",
    "platform": null,
    "description": "pyxDamerauLevenshtein implements the Damerau-Levenshtein (DL) edit distance algorithm for Python in Cython for high performance. Courtesy `Wikipedia <http://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance>`_: In information theory and computer science, the Damerau-Levenshtein distance (named after Frederick J. Damerau and Vladimir I. Levenshtein) is a \"distance\" (string metric) between two strings, i.e., finite sequence of symbols, given by counting the minimum number of operations needed to transform one string into the other, where an operation is defined as an insertion, deletion, or substitution of a single character, or a transposition of two adjacent characters. This implementation is based on `Michael Homer's pure Python implementation <https://web.archive.org/web/20150909134357/http://mwh.geek.nz:80/2009/04/26/python-damerau-levenshtein-distance/>`_, which implements the `optimal string alignment distance algorithm <https://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance#Optimal_string_alignment_distance>`_. It runs in ``O(N*M)`` time using ``O(M)`` space. It supports unicode characters. For more information on pyxDamerauLevenshtein, visit the `GitHub project page <https://github.com/lanl/pyxDamerauLevenshtein>`_.\n",
    "bugtrack_url": null,
    "license": "BSD 3-Clause License",
    "summary": "pyxDamerauLevenshtein implements the Damerau-Levenshtein (DL) edit distance algorithm for Python in Cython for high performance.",
    "version": "1.8.0",
    "project_urls": {
        "Homepage": "https://github.com/lanl/pyxDamerauLevenshtein"
    },
    "split_keywords": [],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "f966269dcc109e4c440da866ca78aedb5f8e63aa50cb6542fb4d3744e2f5cf96",
                "md5": "4cdccc3941e8d793ea1a5153c8dae930",
                "sha256": "d817ded320d32aab30e7bf691f2a255cb92bf7d6da468175956a82b2274c5e1f"
            },
            "downloads": -1,
            "filename": "pyxDamerauLevenshtein-1.8.0-cp312-cp312-macosx_10_9_x86_64.whl",
            "has_sig": false,
            "md5_digest": "4cdccc3941e8d793ea1a5153c8dae930",
            "packagetype": "bdist_wheel",
            "python_version": "cp312",
            "requires_python": null,
            "size": 30586,
            "upload_time": "2024-05-02T18:11:45",
            "upload_time_iso_8601": "2024-05-02T18:11:45.852793Z",
            "url": "https://files.pythonhosted.org/packages/f9/66/269dcc109e4c440da866ca78aedb5f8e63aa50cb6542fb4d3744e2f5cf96/pyxDamerauLevenshtein-1.8.0-cp312-cp312-macosx_10_9_x86_64.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "9b05bf5cd8fd5cf64d29f61e756a6fda23eb2b468e680d3ea2fbf130c816ebed",
                "md5": "4539c59189371cc25a90ff2026e3a2ea",
                "sha256": "1beecc0f546dacddfcbc0300c4f04d7e84ab95c0b6492c316435f94c886ed01e"
            },
            "downloads": -1,
            "filename": "pyxdameraulevenshtein-1.8.0.tar.gz",
            "has_sig": false,
            "md5_digest": "4539c59189371cc25a90ff2026e3a2ea",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 62631,
            "upload_time": "2024-05-02T18:11:47",
            "upload_time_iso_8601": "2024-05-02T18:11:47.387870Z",
            "url": "https://files.pythonhosted.org/packages/9b/05/bf5cd8fd5cf64d29f61e756a6fda23eb2b468e680d3ea2fbf130c816ebed/pyxdameraulevenshtein-1.8.0.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2024-05-02 18:11:47",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "lanl",
    "github_project": "pyxDamerauLevenshtein",
    "travis_ci": true,
    "coveralls": false,
    "github_actions": false,
    "requirements": [
        {
            "name": "Cython",
            "specs": []
        }
    ],
    "lcname": "pyxdameraulevenshtein"
}
        
Elapsed time: 7.62355s