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A library to match and compare strings.

Project description

stringmatch

PyPI PyPI - Python Version Code style: black

stringmatch is a small, lightweight string matching library written in Python, based on the Levenshtein distance and the Levenshtein Python C Extension.
Inspired by libraries like seatgeek/thefuzz, which did not quite fit my needs. And so I am building this library for myself, primarily.

Table of Contents

Key Features

This library matches compares and strings to each other based mainly on, among others, the Levenshtein distance.
What makes stringmatch special compared to other libraries with similar functions:

  • 💨 Lightweight, straightforward and easy to use
  • ⚡ Extremely fast, up to 10x faster than comparable libraries
  • 🧰 Allows for highly customisable searches
  • 📚 Lots of utility functions to make your life easier
  • 🌍 Handles special unicode characters, like emojis or characters from other languages, like ジャパニーズ

Requirements

  • Python 3.9 or later.

Installation

Install the latest stable version with pip:

pip install stringmatch

Or install the newest version via git (Might be unstable or unfinished):

pip install -U git+https://github.com/atomflunder/stringmatch

Basic Usage

Matching

The match functions allow you to compare 2 strings and check if they are "similar enough" to each other, or get the best match(es) from a list of strings:

from stringmatch import Match

match = Match()

# Checks if the strings are similar.
match.match("stringmatch", "strngmach")         # returns True
match.match("stringmatch", "something else")    # returns False

# Returns the best match(es) found in the list.
searches = ["stringmat", "strinma", "strings", "mtch", "whatever", "s"]
match.get_best_match("stringmatch", searches)   # returns "stringmat"
match.get_best_matches("stringmatch", searches) # returns ["stringmat", "strinma"]

Ratios

The "ratio of similarity" describes how similar the strings are to each other. It ranges from 100 being an exact match to 0 being something completely different.
You can get the ratio between strings like this:

from stringmatch import Ratio

ratio = Ratio()

# Getting the ratio between the two strings.
ratio.ratio("stringmatch", "stringmatch")   # returns 100
ratio.ratio("stringmatch", "strngmach") # returns 90
ratio.ratio("stringmatch", "eh")        # returns 15

# Getting the ratio between the first string and the list of strings at once.
searches = ["stringmatch", "strngmach", "eh"]
ratio.ratio_list("searchlib", searches) # returns [100, 90, 15]

Matching & Ratios

You can also get both the match and the ratio together in a tuple using these functions:

from stringmatch import Match

match = Match()

match.match_with_ratio("stringmatch", "strngmach")    # returns (True, 90)

searches = ["test", "nope", "tset"]
match.get_best_match_with_ratio("test", searches)     # returns ("test", 100)
match.get_best_matches_with_ratio("test", searches)   # returns [("test", 100), ("tset", 75)]

Distances

Instead of the ratio, you can also get the Levenshtein distance between strings directly:

from stringmatch import Distance

distance = Distance()

distance.distance("kitten", "sitting")      # returns 3

searches = ["sitting", "kitten"]
distance.distance_list("kitten", searches)  # returns [3, 0]

Strings

This is primarily meant for internal usage, but you can also use this library to modify strings:

from stringmatch import Strings

strings = Strings()

strings.latinise("Héllö, world!")               # returns "Hello, world!"
strings.remove_punctuation("wh'at;, ever")      # returns "what ever"
strings.only_letters("Héllö, world!")           # returns "Hll world"
strings.ignore_case("test test!", lower=False)  # returns "TEST TEST!"

Advanced Usage

Keyword Arguments

You can pass in these optional arguments for the Match() and Ratio() functions to customise your search further:

score

Name Description Type Default Required?
score The score cutoff for matching. Only available for Match() functions. Integer 70 No
# Example:

match("stringmatch", "strngmach", score=95)    # returns False
match("stringmatch", "strngmach", score=70)    # returns True

limit

Name Description Type Default Required?
limit The limit of how many matches to return. If you want to return every match set this to 0 or None. Only available for the get_best_matches() funcion. Integer 5 No
# Example:

searches = ["limit 5", "limit 4", "limit 3", "limit 2", "limit 1", "limit 0"]
get_best_matches("limit 5", searches, limit=2)    # returns ["limit 5", "limit 4"]
get_best_matches("limit 5", searches, limit=1)    # returns ["limit 5"]
get_best_matches("limit 5", searches, limit=None) # returns ["limit 5", "limit 4", "limit 3", "limit 2", "limit 1", "limit 0"]

latinise

Name Description Type Default Required?
latinise Replaces special unicode characters with their latin alphabet equivalents. Examples: Ǽ -> AE, ノース -> nosu Boolean False No
# Example:

match("séärçh", "search", latinise=True)    # returns True
match("séärçh", "search", latinise=False)   # returns False

ignore_case

Name Description Type Default Required?
ignore_case If you want to ignore case sensitivity while searching. Boolean False No
# Example:

match("test", "TEST", ignore_case=True)     # returns True
match("test", "TEST", ignore_case=False)    # returns False

remove_punctuation

Name Description Type Default Required?
remove_punctuation Removes commonly used punctuation symbols from the strings, like .,;:!? and so on. Boolean False No
# Example:

match("test,---....", "test", remove_punctuation=True)  # returns True
match("test,---....", "test", remove_punctuation=False) # returns False

only_letters

Name Description Type Default Required?
only_letters Removes every character that is not in the latin alphabet, a more extreme version of remove_punctuation. Boolean False No
# Example:

match("»»ᅳtestᅳ►", "test", only_letters=True)   # returns True
match("»»ᅳtestᅳ►", "test", only_letters=False)  # returns False

Scoring Algorithms

You can pass in different scoring algorithms when initialising the Match() and Ratio() classes.
The available options are: LevenshteinScorer, JaroScorer, JaroWinklerScorer.
Different algorithms will produce different results, obviously. By default set to LevenshteinScorer.

from stringmatch import Match, LevenshteinScorer, JaroWinklerScorer

levenshtein_matcher = Match(scorer=LevenshteinScorer)
jaro_winkler_matcher = Match(scorer=JaroWinklerScorer)

levenshtein_matcher.match("test", "th test")  # returns True (score = 73)
jaro_winkler_matcher.match("test", "th test") # returns False (score = 60)

Contributing

Contributions to this library are always appreciated! If you have any sort of feedback, or are interested in contributing, head on over to the Contributing Guidelines.
Additionally, if you like this library, leaving a star and spreading the word would be appreciated a lot!
Thanks in advance for taking the time to do so.

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