Metadata-Version: 1.1
Name: textdistance
Version: 1.0.0
Summary: Compute distance between the two texts.
Home-page: https://github.com/orsinium/textdistance
Author: orsinium
Author-email: master_fess@mail.ru
License: GNU Lesser General Public License v3.0
Download-URL: https://github.com/orsinium/textdistance/tarball/master
Description: # Algorithms
        
        * **h -- hamming: substitution**. Compute the Hamming distance between the two or more sequences. The Hamming distance is the number of differing items in ordered sequences.
        * **l -- levenstein: deletion, insertion, substitution**. Compute the absolute Levenshtein distance between the two sequences. The Levenshtein distance is the minimum number of edit operations necessary for transforming one sequence into the other.
        * **dl -- damerau-levenshtein: deletion, insertion, substitution, transposition**. Compute the absolute Damerau-Levenshtein distance between the two sequences. The Levenshtein distance is the minimum number of edit operations necessary for transforming one sequence into the other.
        * **s -- sorensen**. Compute the Sorensen distance between the two sequences. They should contain hashable items. The return value is a float between 0 and 1, where 0 means equal, and 1 totally different.
        * **j -- jaccard**. Compute the Jaccard distance between the two sequences. They should contain hashable items. The return value is a float between 0 and 1, where 0 means equal, and 1 totally different.
        
        # Installation
        
        ```bash
        sudo pip3 install textdistance
        ```
        
        # Usage
        
        ## Importing
        
        ```python
        >>> from textdistance import distance
        
        ```
        
        ## Hamming
        
        ```python
        >>> distance('h', 'lorem', 'lorum')
        1
        >>> distance('h', 'lorem', 'loremus')
        2
        >>> distance('h', 'lorem', 'lorimus')
        3
        >>> distance('h', 'lorimus', 'larem')
        4
        >>> distance.h(lorimus', 'larem')
        4
        ```
        
        ## Sorensen
        
        ```python
        >>> distance('s', 'lorem', 'lorem')
        0.0
        >>> distance('s', 'lorem', 'lorum')
        0.19999999999999996
        >>> distance('s', 'lorem', 'lorme')
        0.0
        >>> distance('s', 'lorem', 'melor')
        0.0
        >>> distance('s', 'lorem', 'loremus')
        0.16666666666666663
        >>> distance.s('lorem', 'loremus')
        0.16666666666666663
        ```
        
        ## Jaccard
        
        ```python
        >>> distance('j', 'lorem', 'lorem')
        0.0
        >>> distance('j', 'lorem', 'lorum')
        0.33333333333333337
        >>> distance('j', 'lorem', 'lorme')
        0.0
        >>> distance('j', 'lorem', 'melor')
        0.0
        >>> distance('j', 'lorem', 'loremus')
        0.2857142857142857
        >>> distance.j('lorem', 'loremus')
        0.2857142857142857
        ```
        
        ## Levenstein
        
        ```python
        >>> distance('l', 'lorem', 'lorim')
        1
        >>> #substitution
        ... distance('l', 'lorem', 'lorim')
        1
        >>> #insertion
        ... distance('l', 'lorem', 'loriem')
        1
        >>> #deletion
        ... distance('l', 'lorem', 'lrem')
        1
        >>> distance.l('lorem', 'lrem')
        1
        ```
        
        ## Damerau-Levenshtein
        
        ```python
        >>> distance('dl', 'lorem', 'lorim')
        1
        >>> #substitution
        ... distance('dl', 'lorem', 'lorim')
        1
        >>> #insertion
        ... distance('dl', 'lorem', 'loriem')
        1
        >>> #deletion
        ... distance('dl', 'lorem', 'lrem')
        1
        >>> #transposition
        ... distance('dl', 'lorem', 'lorme')
        1
        >>> distance.dl('lorem', 'lorme')
        1
        ```
        
        ## Test with words permutations
        
        ```python
        >>> distance('dlw', 'lorem ipsum', 'ipsum lorum')
        1
        >>> distance('dlw', 'lorem ipsum dolor', 'ipsum lorum')
        7
        >>> distance('dlwe', 'lorem ipsum dolor', 'ipsum lorum')
        1
        ```
        
        ## Find minimal text by distance
        
        ```python
        >>> distance.find_minimal('h', 'lorem', ['larum', 'lorum'])
        (1, 'lorum')
        ```
        
Keywords: distance between text strings sequences iterators
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Plugins
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 or later (LGPLv3+)
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering :: Human Machine Interfaces
Requires: python (>= 3.4)
