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html to json

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Release: 2023-04-21 15:16:33
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HTML to JSON conversion: implemented through Python

With the rise of big data and artificial intelligence, data processing and statistical analysis skills are becoming more and more important. For web developers, HTML is one of the most commonly used data formats. In this article, we will learn how to convert HTML to JSON format for more data processing and statistical analysis in Python.

What is JSON?

JSON (JavaScript Object Notation) is a lightweight data exchange format. It is based on JavaScript object syntax, but has now become an independent data format and is widely used in web services and data exchange. Compared with XML, JSON is simpler, faster, easier to use and understand, so it is often used for front-end and back-end data exchange.

Why do you need to convert HTML to JSON?

Web development often needs to extract data from various websites and APIs and use it for analysis or display in one's own website. HTML may be one of the data formats, but in most cases we want to convert it to JSON format. This is because the JSON format is more compact, easier to process and transmit, and is more versatile and can be used for data exchange between multiple languages ​​and technologies.

Python program to convert HTML to JSON

Python is a popular programming language with rich libraries and tools that can easily convert HTML to JSON. In this article, we will use the Python library Beautiful Soup and lxml to parse HTML and convert it into JSON format. The following are the implementation steps:

  1. Install the required libraries and tools

To convert HTML to JSON in Python, we need to use the following libraries and tools:

  • Beautiful Soup: used to parse HTML documents
  • lxml: Beautiful Soup's parser, used to parse HTML documents into tree structures
  • json: Python's built-in JSON Libraries for processing JSON data

You can use PIP tools (such as pip install beautifulsoup4 lxml) to install these libraries and tools.

  1. Prepare HTML document

Before converting HTML to JSON, you need to prepare the HTML document to be converted. This can be HTML code copied from a web page, or an HTML document read from a local file. In this article, we will use the following HTML code as an example:



My Web Page


Welcome to my Web Page


This is my first attempt at creating a Web Page.



  1. Use Beautiful Soup and lxml to parse HTML documents

With HTML documents, we can use Beautiful Soup and lxml to parse it. The following is the Python code:

from bs4 import BeautifulSoup
import lxml

html_doc = """


< title>My Web Page


Welcome to my Web Page


This is my first attempt at creating a Web Page.




"""

soup = BeautifulSoup(html_doc, "lxml" )

This code parses the HTML document into a tree structure. We can use the functions and methods of Beautiful Soup to get the various parts of the HTML document.

  1. Convert HTML to JSON

We can convert it to JSON format by traversing the parsed HTML document. The following is a Python code example:

import json

Get the HTML title

title = soup.title.string

Get the HTML body

body = soup.body
content_list = []
for tag in body.descendants:
if tag.string is not None:

<code>content_list.append(tag.string.strip())</code>
Copy after login

content = " ".join(content_list)

Convert HTML to JSON

web_page = {"title": title, "content": content}
json_data = json.dumps(web_page)

print (json_data)

The output results are as follows:

{"title": "My Web Page", "content": "Welcome to my Web Page This is my first attempt at creating a Web Page ."}

By traversing the parsed HTML document, we obtain the HTML title and body and convert them into JSON format. We use Python's json library to convert the JSON data into a string and then print the JSON data.

Conclusion

In this article, we learned how to convert HTML to JSON format using Python’s Beautiful Soup and lxml library. Through this method, we can extract the data from the HTML web page and perform more processing and analysis in the Python environment. This approach can play an important role in web development, data processing, and data analysis.

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