fuzzywuzzy | Fuzzy String Matching in Python | Search Engine library

 by   seatgeek Python Version: 0.18.0 License: GPL-2.0

kandi X-RAY | fuzzywuzzy Summary

kandi X-RAY | fuzzywuzzy Summary

fuzzywuzzy is a Python library typically used in Database, Search Engine applications. fuzzywuzzy has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has high support. You can install using 'pip install fuzzywuzzy' or download it from GitHub, PyPI.

Fuzzy String Matching in Python

            kandi-support Support

              fuzzywuzzy has a highly active ecosystem.
              It has 8884 star(s) with 898 fork(s). There are 265 watchers for this library.
              It had no major release in the last 12 months.
              There are 82 open issues and 103 have been closed. On average issues are closed in 124 days. There are 26 open pull requests and 0 closed requests.
              It has a positive sentiment in the developer community.
              The latest version of fuzzywuzzy is 0.18.0

            kandi-Quality Quality

              fuzzywuzzy has 0 bugs and 0 code smells.

            kandi-Security Security

              fuzzywuzzy has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              fuzzywuzzy code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              fuzzywuzzy is licensed under the GPL-2.0 License. This license is Strong Copyleft.
              Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

            kandi-Reuse Reuse

              fuzzywuzzy releases are available to install and integrate.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.

            Top functions reviewed by kandi - BETA

            kandi has reviewed fuzzywuzzy and discovered the below as its top functions. This is intended to give you an instant insight into fuzzywuzzy implemented functionality, and help decide if they suit your requirements.
            • UWRatio between two strings
            • Get opcodes
            • Get all matching blocks
            • Return the similarity between two strings
            • Uratio ratio
            • Return the similarity between two sequences
            • Return the ratio between two strings
            • Compare two strings
            • Removes duplicates from a list
            • Extract elements from a query
            • Extract a single item from a query
            • Print the result from a timeit
            • Extract the best matches from the query
            • Extracts the best match from choices
            • Generate a quick ratio
            Get all kandi verified functions for this library.

            fuzzywuzzy Key Features

            No Key Features are available at this moment for fuzzywuzzy.

            fuzzywuzzy Examples and Code Snippets

            check if the string equals the first letters of a list of words
            Pythondot img1Lines of Code : 3dot img1License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            def example_task(words, beginning):
                return [w for w in words if w.startswith(beginning)]
            Fuzzy matching and grouping
            Pythondot img2Lines of Code : 52dot img2License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            #Run this to install the required libraries
            #pip install python-levenshtein fuzzywuzzy
            from fuzzywuzzy import fuzz
            l_data =[
                 ['Robert','9185 Pumpkin Hill St.']
                ,['Rob','9185 Pumpkin Hill Street']
                ,['Mike','1296 Tunnel St.']
            Fuzzy matching for groups in pandas
            Pythondot img3Lines of Code : 66dot img3License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            def match_groups(addresses, threshold):
                subgroups = [i for i in range(1, len(addresses)+1)]
                for i, val_i in enumerate(addresses):
                    for j, val_j in enumerate(addresses):
                        if j>i:
                            ratio = fuzz.rat
            Fuzzy Matching with different fuzz ratios
            Pythondot img4Lines of Code : 60dot img4License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            import pandas as pd
            from fuzzywuzzy import fuzz
            # Setup
            df1.columns = [f"df1_{col}" for col in df1.columns]
            # Add new columns
            df1["fuzz_ratio_lname"] = (
                    lambda x: max(
                        [(value, fuzz.r
            How to set a column value by fuzzy string matching with another dataframe?
            Pythondot img5Lines of Code : 33dot img5License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            from functools import cache
            import pandas as pd
            from fuzzywuzzy import fuzz
            # First, define indices and values to check for matches
            indices_and_values = [(i, value) for i, value in enumerate(df2["lname"] + df2["fname"])]
            # Define helper
            Setting a Threshold for fuzzywuzzy process.extractOne
            Pythondot img6Lines of Code : 13dot img6License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            best_match = process.extractOne(text, choices_dict, score_cutoff=80)
            if best_match:
                value, score, key = best_match
                print(f"best match is {key}:{value} with the similarity {score}")
                print("no match found")
            how token sort ratio works?
            Pythondot img7Lines of Code : 35dot img7License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            >>> from rapidfuzz.distance import Levenshtein
            >>> Levenshtein.distance('controlled', 'comparative')
            >>> Levenshtein.similarity('controlled', 'comparative')
            >>> Levenshtein.normalized_distance('contr
            Compare Similarity of two strings
            Pythondot img8Lines of Code : 9dot img8License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            from fuzzywuzzy import fuzz
            df['score'] = df[['Name Left','Name Right']].apply(lambda x : fuzz.partial_ratio(*x),axis=1)
               Match ID     Name Left           Name Right  score
            0         1    LemonFarms      Lemon Farms Inc    
            fuzzywuzzy returning single characters, not strings
            Pythondot img9Lines of Code : 66dot img9License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            import os
            import csv
            import shutil
            import usaddress
            import pandas as pd
            from fuzzywuzzy import process
            with open(r"TEST_Cass_Howard.csv") as csv_file, \
                    open(".\Scratch\Final_Test_Clean.csv", "w") as f, \
            fuzzywuzzy returning single characters, not strings
            Pythondot img10Lines of Code : 56dot img10License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            import usaddress
            from fuzzywuzzy import process
            data1 = "3176 DETRIT ROAD"
            choices = ["DETROIT RD"]
                data1 = usaddress.tag(data1)
            except usaddress.RepeatedLabelError:
            parts = [

            Community Discussions


            check if the string equals the first letters of a list of words
            Asked 2022-Mar-28 at 14:59

            I am confused about a simple task

            the user will give me a string and my program will check if this string equals the first letters of a list of words ( like this example)



            Answered 2022-Mar-28 at 14:59

            No need for some weird libraries, Python has a nice builtin str function called startswith that does just that.

            Source https://stackoverflow.com/questions/71649455


            The airflow scheduler stops working after updating pypi packages on google cloud composer 2.0.1
            Asked 2022-Mar-27 at 07:04

            I am trying to migrate from google cloud composer composer-1.16.4-airflow-1.10.15 to composer-2.0.1-airflow-2.1.4, However we are getting some difficulties with the libraries as each time I upload the libs, the scheduler fails to work.

            here is my requirements.txt



            Answered 2022-Mar-27 at 07:04

            We have found out what was happening. The root cause was the performances of the workers. To be properly working, composer expects the scanning of the dags to take less than 15% of the CPU ressources. If it exceeds this limit, it fails to schedule or update the dags. We have just taken bigger workers and it has worked well

            Source https://stackoverflow.com/questions/70684862


            Pipreqs: SyntaxError: invalid non-printable character U+FEFF
            Asked 2022-Mar-22 at 01:33

            When I try to run pipreqs /path/to/project it comes back with



            Answered 2022-Mar-21 at 23:52

            Are you on Windows? Your file contains a Unicode byte-order mark. Some services don't like that. If you remove the BOM, it should work.

            Source https://stackoverflow.com/questions/71565071


            Fuzzy matching for groups in pandas
            Asked 2022-Mar-21 at 07:59

            I have the following dataset:



            Answered 2022-Mar-21 at 07:59

            One way might be to create a parallel DataFrame, then join. Here are a couple of variations on that approach. There may well be a better way.

            Here's a slightly modified match_groups function, so that it takes a Series rather than a DataFrame:

            Source https://stackoverflow.com/questions/71552594


            How to set a column value by fuzzy string matching with another dataframe?
            Asked 2022-Mar-02 at 14:16

            I have referred to this post but cannot get it to run for my particular case. I have two dataframes:



            Answered 2021-Dec-26 at 17:50


            Setting a Threshold for fuzzywuzzy process.extractOne
            Asked 2022-Feb-23 at 14:13

            I'm currently doing some string product similarity matches between two different retailers and I'm using the fuzzywuzzy process.extractOne function to find the best match.

            However, I want to be able to set a scoring threshold so that the product will only match if the score is above a certain threshold, because currently it is just matching every single product based on the closest string.

            The following code gives me the best match: (currently getting errors)

            title, index, score = process.extractOne(text, choices_dict)

            I then tried the following code to try set a threshold:

            title, index, score = process.extractOne(text, choices_dict, score_cutoff=80)

            Which results in the following TypeError:

            TypeError: cannot unpack non-iterable NoneType object

            Finally, I also tried the following code:

            title, index, scorer, score = process.extractOne(text, choices_dict, scorer=fuzz.token_sort_ratio, score_cutoff=80)

            Which results in the following error:

            ValueError: not enough values to unpack (expected 4, got 3)



            Answered 2022-Feb-23 at 14:12

            process.extractOne will return None, when the best score is below score_cutoff. So you either have to check for None, or catch the exception:

            Source https://stackoverflow.com/questions/71236203


            How to replace using for() with all() in a pandas dataframe?
            Asked 2022-Feb-21 at 13:36

            I have a university activity that makes the following dataframe available:



            Answered 2022-Feb-21 at 12:43

            You can't use fuzz.ratio this way directly, the function is not vectorial. You need to pass it to apply:

            Source https://stackoverflow.com/questions/71206431


            how token sort ratio works?
            Asked 2022-Feb-17 at 05:13

            Can someone explain me how this function of the library fuzzywuzzy in Python works? I know how the Levenshtein distance works but I don't understand how the ratio is computed.



            Answered 2022-Feb-17 at 05:13
            Levenshtein distance

            As you probably already know the Levenshtein distance is the minimum amount of insertions / deletions / substitutions to convert one sequence into another sequence. It can be normalized as dist / max_dist, where max_dist is the maximum distance possible given the two sequence lengths. In the case of the Levenshtein distance this results in the normalization dist / max(len(s1), len(s2)). In addition a normalized similarity can be calculated by inverting this: 1 - normalized distance.

            Source https://stackoverflow.com/questions/71146287


            Optimize the traversal of a column of a dataframe
            Asked 2022-Feb-15 at 08:30

            I want to check for fuzzy duplicates in a column of the dataframe using fuzzywuzzy. In this case, I have to iterate over the rows one by one using two nested for loops.



            Answered 2022-Feb-15 at 08:30

            For your use case I would recommend the usage of RapidFuzz (I am the author). In particular the function process.cdist should allow you to implement this very efficiently:

            Source https://stackoverflow.com/questions/71084826


            fuzzywuzzy returning single characters, not strings
            Asked 2022-Jan-28 at 02:42

            I'm not sure where I'm going wrong here and why my data is returning wrong. Writing this code to use fuzzywuzzy to clean bad input road names against a list of correct names, replacing the incorrect with the closest match.

            It's returning all lines of data2 back. I'm looking for it to return the same, or replaced lines of data1 back to me.

            My Minimal, Reproducible Example:



            Answered 2022-Jan-25 at 18:21

            Okay, I'm not certain I've fully understood your issue, but modifying your reprex, I have produced the following solution.

            Source https://stackoverflow.com/questions/70851051

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install fuzzywuzzy

            You can install using 'pip install fuzzywuzzy' or download it from GitHub, PyPI.
            You can use fuzzywuzzy like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.


            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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