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compare-strings-0.0.3


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توضیحات

A library for measuring similarity between strings
ویژگی مقدار
سیستم عامل -
نام فایل compare-strings-0.0.3
نام compare-strings
نسخه کتابخانه 0.0.3
نگهدارنده []
ایمیل نگهدارنده []
نویسنده -
ایمیل نویسنده -
آدرس صفحه اصلی -
آدرس اینترنتی https://pypi.org/project/compare-strings/
مجوز -
# CompareStrings CompareStrings accepts either two strings or two Pandas Series' containing strings, as inputs, and provides a simple way to tell how similar or dissimilar two strings are. By default, the `compare_strings` function returns the Levenshtein Distance between the strings, divided by the length of the first string, where 0 represents absolute similiarity, higher values represent increasing dissimilarity. Optional argument `method` allows selection of alternative methods of calculation, such as the absolute Levenshtein distance - `method = lev_abs`, or the cosine distance (not yet released). CompareStrings by default stripes numeric and punctuation characters from the string before performing the calculation. The optional `email` argument takes 1 or 2 as values, and indicates to the function that either string (or series) 1 or 2 contain an email address. When this argument is used, the input that contains an email address is split on the '@' and the email domain is discarded before the calculation is performed. The `precision` argument is used to determine the number of decimals returns in the resulting float. ## Installation ```python pip install CompareStrings ``` ## Usage ### Strings: `compare_strings` supports indivdual strings as inputs. Examples: ```python from CompareStrings import compare_strings ``` ```method='lev_abs'``` ```python # Levenshtein Distance compare_strings('string one','string', method='lev_abs') ``` `Out[1]: 4` *There were 4 additions, deletions or substitutions required to change the first string into the second* ```method='lev_props'``` ```python # Levenshtein Distance as a proportion of the length of the first string compare_strings('string one','string', method='lev_props') ``` `Out[1]: 0.4` *There were 4 additions, deletions or substitutions required to change the first string into the second string, and 10 characters in the first string.* ### Pandas Series: `compare_strings` also accepts pandas series as inputs. It will return a new DataFrame containing the inputs and a new column with the output. The `email` argument can be used to tell the function if one of the inputs contains an email address, and performs some preprocessing to remove the domain - for example: Without `email` set: | | email | full_name | levenshtein_proportions | |-----:|:---------------------------------|:----------------------|--------------------------:| | 6203 | tom_johnson1@hotmail.com | Tom Jonhson | 0.46 | | 8990 | suzanne_stevenson54@hotmail.com | Suzanne stevenson | 0.43 | | 6769 | marie.eriksson99@hotmail.com | Ann Eriksson | 0.62 | | 2552 | elisabeth.henriksson8@hotmail.com| Elisabeth Henriksson | 0.38 | With `email = 1` set: | | email | full_name | levenshtein_proportions | |-----:|:---------------------------------|:----------------------|--------------------------:| | 6203 | tom_jonson1@hotmail.com | Tom Jonson | 0 | | 8990 | suzanne_stevenson54@hotmail.com | Suzanne Stevenson | 0 | | 6769 | marie.eriksson99@hotmail.com | Ann Eriksson | 0.29 | | 2552 | elisabeth.henriksson8@hotmail.com| Elisabeth Henriksson | 0 | Passing `1` to the `email` argument tells the function to ignore the characters after and including the '@' in the first column when performing the calculation. #### `check_names`: The `check_names` argument is intended to be used in conjunction with the `email` argument. It adds another column to the returned DataFrame with a `True` or `False` value, indicating whether any part of the string was found in the `big_names_list`. For example, it may be useful to ignore the similarity score if the email address passed into the function does not contain anything recognised as a name. *Disclaimer* the names list currently contains 7.6k first and surnames from a number of nationalities, but is in no way exhaustive. It also contains some names that are quite short, and may return false positives if those short strings are found in the inputs. ## Coming soon: - Support for additional alternative measures of similarity/dissimilarity - Support for lists as inputs - Probably other stuff - want to help? See below ## Contribution This is my very first python package so contributions are very much welcome. Suggestions include: - Documentation incl. tidying up docstrings and comments - Additions to the big_names_list - Support for names in other languages - New similarity measures - Support or suggestions for other use cases


نیازمندی

مقدار نام
>=1.2.4 pandas
>=1.19.5 numpy
>=0.12.2 python-Levenshtein
>=3.7 pytest


نحوه نصب


نصب پکیج whl compare-strings-0.0.3:

    pip install compare-strings-0.0.3.whl


نصب پکیج tar.gz compare-strings-0.0.3:

    pip install compare-strings-0.0.3.tar.gz