Conda - Fuzzy String Matching Made Easy with BlurWuzzy

Are you tired of manually matching strings and getting mediocre results? Look no further than BlurWuzzy, a powerful fuzzy string matching library for Python that can accurately match strings even with typos and variable spellings.

What is Fuzzy String Matching?

Fuzzy String Matching is a process of finding strings that match a pattern approximately. It involves comparing two strings and calculating how similar they are based on various factors like typos, spelling variations, word order, spacing, etc.

What is BlurWuzzy?

BlurWuzzy is an open-source Python package that provides functions for fuzzy string matching. It uses the Levenshtein distance algorithm to calculate the edit distance between two strings. It also provides various methods to improve matching accuracy, like tokenization, stopword removal, and string length normalization.

How to Install BlurWuzzy

You can easily install BlurWuzzy using Conda, the popular package manager for Python.

conda install -c conda-forge fuzzywuzzy

How to Use BlurWuzzy

BlurWuzzy provides several functions for string matching, each with its unique features and usage.

Here are a few examples:

1. Simple Ratio

fuzz.ratio() function uses the Levenshtein distance to calculate the edit distance between two strings and returns a similarity score in the range of 0 to 100, where 100 means the strings are identical.

from fuzzywuzzy import fuzz

str1 = "Hello World"
str2 = "Helo wrld"

ratio = fuzz.ratio(str1, str2)
print(ratio)  # Output: 67

2. Token Sort Ratio

fuzz.token_sort_ratio() function sorts the tokens in each string alphabetically before comparing them, providing a better matching score for strings with the same words but in different order.

from fuzzywuzzy import fuzz

str1 = "Apple Banana Cherry"
str2 = "Cherry Banana Apple"

ratio = fuzz.token_sort_ratio(str1, str2)
print(ratio)  # Output: 100

3. Token Set Ratio

fuzz.token_set_ratio() function compares two strings and matches the intersection of the token sets in each string, providing a better matching score for strings with different word order and spacing.

from fuzzywuzzy import fuzz

str1 = "Apple Banana Cherry"
str2 = "Banana Cherry Apple Pear"

ratio = fuzz.token_set_ratio(str1, str2)
print(ratio)  # Output: 75

Conclusion

BlurWuzzy is an essential tool for any programmer who deals with string matching. It provides a vast array of functions that can handle various use cases with high accuracy. So, if you want to save time and get better string matching results, give it a try with Conda!