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HTML to JSON

PyPI codecov

Convert HTML and/or HTML tables to JSON.

Current Status

📢 I have a lot of demands on my time at the moment and won't be able to work on this library without sponsorship. If this library is useful to you or if you're using this library for a business - please consider sponsoring me. Even a small sponsorship allows me to prioritize work on this library and ongoing maintainance. Thanks!

Installation

pip install html-to-json

Usage

HTML to JSON

import html_to_json

html_string = """<head>
    <title>Test site</title>
    <meta charset="UTF-8"></head>"""
output_json = html_to_json.convert(html_string)
print(output_json)

When calling the html_to_json.convert function, you can choose to not capture the text values from the html by passing in the key-word argument capture_element_values=False. You can also choose to not capture the attributes of the elements by passing capture_element_attributes=False into the function.

Example

Example input:

<head>
    <title>Floyd Hightower's Projects</title>
    <meta charset="UTF-8">
    <meta name="description" content="Floyd Hightower&#39;s Projects">
    <meta name="keywords" content="projects,fhightower,Floyd,Hightower">
</head>

Example output:

{
    "head": [
    {
        "title": [
        {
            "_value": "Floyd Hightower's Projects"
        }],
        "meta": [
        {
            "_attributes":
            {
                "charset": "UTF-8"
            }
        },
        {
            "_attributes":
            {
                "name": "description",
                "content": "Floyd Hightower's Projects"
            }
        },
        {
            "_attributes":
            {
                "name": "keywords",
                "content": "projects,fhightower,Floyd,Hightower"
            }
        }]
    }]
}

HTML Tables to JSON

In addition to converting HTML to JSON, this library can also intelligently convert HTML tables to JSON.

Currently, this library can handle three types of tables:

A. Those with table headers in the first row B. Those with table headers in the first column C. Those without table headers

Tables of type A and B are diagrammed below:

This package can handle tables with the headers in the first row or headers in the first column

Example

This code:

import html_to_json

html_string = """<table>
    <tr>
        <th>#</th>
        <th>Malware</th>
        <th>MD5</th>
        <th>Date Added</th>
    </tr>

    <tr>
        <td>25548</td>
        <td><a href="/stats/DarkComet/">DarkComet</a></td>
        <td><a href="/config/034a37b2a2307f876adc9538986d7b86">034a37b2a2307f876adc9538986d7b86</a></td>
        <td>July 9, 2018, 6:25 a.m.</td>
    </tr>
    
    <tr>
        <td>25547</td>
        <td><a href="/stats/DarkComet/">DarkComet</a></td>
        <td><a href="/config/706eeefbac3de4d58b27d964173999c3">706eeefbac3de4d58b27d964173999c3</a></td>
        <td>July 7, 2018, 6:25 a.m.</td>
    </tr></table>"""
tables = html_to_json.convert_tables(html_string)
print(tables)

will produce this output:

[
    [
        {
            "#": "25548",
            "Malware": "DarkComet",
            "MD5": "034a37b2a2307f876adc9538986d7b86",
            "Date Added": "July 9, 2018, 6:25 a.m."
        }, {
            "#": "25547",
            "Malware": "DarkComet",
            "MD5": "706eeefbac3de4d58b27d964173999c3",
            "Date Added": "July 7, 2018, 6:25 a.m."
        }
    ]
]

Credits

This package was created with Cookiecutter and fhightower's Python project template.