fuzzywuzzy python library

Опубликовано: 16 Март 2024
на канале: CodeWrite

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fuzzywuzzy is a python library used for fuzzy string matching. it provides simple and powerful methods to compare strings and determine their similarity based on fuzzy logic. this tutorial will guide you through the basics of using fuzzywuzzy, including installation, key functionalities, and code examples.
first, you need to install the fuzzywuzzy library using pip. open your terminal or command prompt and run the following command:
once installed, you can import the library into your python scripts or interactive sessions.
fuzzywuzzy offers several methods for comparing strings. the most commonly used ones are ratio(), partial_ratio(), token_sort_ratio(), and token_set_ratio(). let's explore each of these methods with examples:
the ratio() method compares two strings and returns a similarity score as a percentage, where 100 indicates a perfect match.
output:
the partial_ratio() method compares parts of two strings and returns a similarity score based on the best partial match.
output:
the token_sort_ratio() method compares strings after sorting their tokens alphabetically. this is useful for cases where word order might vary.
output:
the token_set_ratio() method compares strings by tokenizing and comparing unique tokens, which is helpful for cases where strings may contain different words but convey the same meaning.
output:
in this tutorial, you've learned the basics of using the fuzzywuzzy python library for fuzzy string matching. by applying methods such as ratio(), partial_ratio(), token_sort_ratio(), and token_set_ratio(), you can efficiently compare strings and determine their similarity. fuzzywuzzy is particularly useful in scenarios where exact string matching might not be feasible due to variations or typos in the data. explore further and integrate fuzzywuzzy into your projects to improve string matching accuracy.

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