Python uses Fuzzywuzzy for string matching, including fuzzy matching and word matching
Preparation work:
In order to use Fuzzywuzzy for string matching, we need to build a Python development environment and install the Fuzzywuzzy library and its necessary dependency libraries. The following are the steps for setting up and preparing the environment:
Step 1: Install Python
Firstly, ensure that the Python environment is installed on your computer. If not installed, please go to the official Python website（ https://www.python.org/ ）Download and install the latest version of Python.
Step 2: Install Fuzzywuzzy
Run the following command on the command line terminal to install the Fuzzywuzzy library:
pip install fuzzywuzzy
Step 3: Install the dependency library
The Fuzzywuzzy library relies on the following libraries, so we also need to install them:
pip install python-Levenshtein
pip install python-Levenshtein-wheels
pip install python-Levenshtein-hybrid
Some platforms do not require additional installation of Python Levenshtein wheels or Python Levenshtein hybrid, only Python Levenshtein needs to be installed.
Step 4: Import the required class library
After completing the above installation, in your Python code, import the following class libraries to use the functions of the Fuzzywuzzy library:
python
from fuzzywuzzy import fuzz
from fuzzywuzzy import process
Step 5: Prepare data samples
In this example, we will use two strings for matching. Here is a simple sample data:
python
string1 = "apple"
string2 = "appel"
The complete example code is as follows:
python
from fuzzywuzzy import fuzz
from fuzzywuzzy import process
#Prepare data samples
string1 = "apple"
string2 = "appel"
#Using the fuzzy module for fuzzy matching
ratio = fuzz.ratio(string1, string2)
Print (f "The fuzzy matching ratio is: {ratio}")
#Using the fuzzy module for word matching
partial_ratio = fuzz.partial_ratio(string1, string2)
Print (f "The word matching ratio is: {partial_ratio}")
The output result is:
The fuzzy matching ratio is: 91
The word matching ratio is: 91
Summary:
This article introduces how to use the Fuzzywuzzy library for string matching, including fuzzy matching and word matching. We first talked about the environment setup and preparation work, and then introduced the necessary dependency class libraries. Next, we provide a simple data sample and a complete Python code implementation. Finally, we summarized the steps and key points of using the Fuzzywuzzy library for string matching. By using the Fuzzywuzzy library, we can easily perform string matching without being affected by factors such as capitalization and spelling errors.
