Metadata-Version: 2.1
Name: editdistance
Version: 0.6.2
Summary: Fast implementation of the edit distance(Levenshtein distance)
Home-page: https://www.github.com/roy-ht/editdistance
Author: Hiroyuki Tanaka
Author-email: aflc0x@gmail.com
License: UNKNOWN
Description: ============
        editdistance
        ============
        
        Fast implementation of the edit distance (Levenshtein distance).
        
        This library simply implements `Levenshtein distance <http://en.wikipedia.org/wiki/Levenshtein_distance>`_ with C++ and Cython.
        
        The algorithm used in this library is proposed by
        `Heikki Hyyrö, "Explaining and extending the bit-parallel approximate string matching algorithm of Myers", (2001) <http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.19.7158&rep=rep1&type=pdf>`_.
        
        -------------
        Binary wheels
        -------------
        
        Thanks to `joerick/cibuildwheel <https://github.com/joerick/cibuildwheel>`_, 
        There are binary wheels on Linux, Mac OS, and Windows.
        
        -------
        Install
        -------
        
        You can install via pip:
        
        .. code-block:: bash
        
            pip install editdistance
        
        
        -----
        Usage
        -----
        
        It's quite simple:
        
        .. code-block:: python
        
            import editdistance
            editdistance.eval('banana', 'bahama')
            # 2L
        
        
        ----------------
        Simple Benchmark
        ----------------
        
        With IPython, I tried several libraries:
        
        * `pyxDamerauLevenshtein <https://pypi.python.org/pypi/pyxDamerauLevenshtein>`_
        * `pylev <https://pypi.python.org/pypi/pylev>`_
        * `python-Levenshtein <https://pypi.python.org/pypi/python-Levenshtein>`_
        
        On Python 2.7.5:
        
        .. code-block:: python
        
            a = 'fsffvfdsbbdfvvdavavavavavava'
            b = 'fvdaabavvvvvadvdvavavadfsfsdafvvav'
            import pylev
            timeit pylev.levenshtein(a, b)
            # 100 loops, best of 3: 7.48 ms per loop
            
            from pyxdameraulevenshtein import damerau_levenshtein_distance
            timeit damerau_levenshtein_distance(a, b)
            # 100000 loops, best of 3: 11.4 µs per loop
            
            timeit editdistance.eval(a, b)  # my library
            # 100000 loops, best of 3: 3.5 µs per loop
            
            import Levenshtein
            
            timeit Levenshtein.distance(a, b)
            # 100000 loops, best of 3: 3.21 µs per loop
        
        
        ------------------------
        Distance with Any Object
        ------------------------
        
        Above libraries only support strings.
        But Sometimes other type of objects such as list of strings(words).
        I support any iterable, only requires hashable object of it:
        
        .. code-block:: python
        
            Levenshtein.distance(['spam', 'egg'], ['spam', 'ham'])
            # ---------------------------------------------------------------------------
            # TypeError                                 Traceback (most recent call last)
            # <ipython-input-22-3e0b30d145ac> in <module>()
            # ----> 1 Levenshtein.distance(['spam', 'egg'], ['spam', 'ham'])
            #
            # TypeError: distance expected two Strings or two Unicodes
            
            editdistance.eval(['spam', 'egg'], ['spam', 'ham'])
            # 1L
        
        So if object's hash is same, it's same.
        You can provide ``__hash__`` method to your object instances.
        
        Enjoy!
        
        
        -------
        License
        -------
        
        It is released under the MIT license.
        
            Copyright (c) 2013 Hiroyuki Tanaka
        
            Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
        
            The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
        
            THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
