Skip to main content

Project dedicated to content extraction from unstructured files that contain some useful information.

Project description

HTML Content Extraction Tool

A powerful command-line tool for extracting structured content from HTML documents. Converts HTML sections into hierarchical JSON data while preserving formatting, links, and semantic structure.

Features

  • Hierarchical Parsing: Automatically detects heading levels and creates nested section structures
  • HTML Preservation: Maintains original formatting, links, and semantic elements
  • Smart Element Filtering: Includes meaningful content while filtering out irrelevant elements
  • Flexible Input/Output: Read from files or stdin, output to files or stdout
  • Section Support: Works with existing <section>, <article>, and <main> elements
  • Custom Headings: Supports both standard headings (h1-h6) and custom headings with aria-level

Installation

# Install dependencies
pip install beautifulsoup4

# Clone or download this repository
git clone <repository-url>
cd content-extraction

Usage

Basic Usage

# Parse HTML file and output to stdout
python main.py example.html

# Parse with pretty-printed JSON
python main.py --pretty example.html

# Save output to file
python main.py example.html -o output.json

# Read from stdin
cat example.html | python main.py --pretty

# Verbose mode with debug information
python main.py --verbose example.html

Command Line Options

usage: main.py [-h] [-o FILE] [--pretty] [-v] [--version] [input_file]

Extract structured content from HTML documents

positional arguments:
  input_file         Input HTML file (if not provided, reads from stdin)

options:
  -h, --help         show this help message and exit
  -o, --output FILE  Output JSON file (if not provided, writes to stdout)
  --pretty           Pretty-print JSON output with indentation
  -v, --verbose      Show verbose output and debug information
  --version          show program's version number and exit

Output Format

The tool outputs JSON with the following structure:

{
  "title": "Section Title",
  "text": "<p>HTML content preserved</p>",
  "level": 1,
  "subsections": [
    {
      "title": "Subsection Title",
      "text": "<p>Subsection content</p>",
      "level": 2,
      "subsections": []
    }
  ]
}

Fields

  • title: Text content of the highest-level heading in the section
  • text: All content except headings, with HTML formatting preserved
  • level: Aria level of the main heading (1-6, or custom levels)
  • subsections: Array of nested subsections with the same structure

Examples

Simple Section

Input HTML:

<section>
    <h2>Getting Started</h2>
    <p>Welcome to our <a href="/api">API</a>!</p>
    <ul>
        <li>Step 1: Register</li>
        <li>Step 2: Get API key</li>
    </ul>
</section>

Output:

{
  "title": "Getting Started",
  "text": "<p>Welcome to our <a href=\"/api\">API</a>!</p>\n<ul>\n<li>Step 1: Register</li>\n<li>Step 2: Get API key</li>\n</ul>",
  "level": 2,
  "subsections": []
}

Nested Sections

Input HTML:

<main>
    <h1>Documentation</h1>
    <p>Introduction text.</p>
    <h2>Installation</h2>
    <p>Installation instructions.</p>
    <h3>Requirements</h3>
    <p>System requirements.</p>
    <h2>Usage</h2>
    <p>Usage examples.</p>
</main>

Output:

{
  "title": "Documentation",
  "text": "<p>Introduction text.</p>",
  "level": 1,
  "subsections": [
    {
      "title": "Installation",
      "text": "<p>Installation instructions.</p>",
      "level": 2,
      "subsections": [
        {
          "title": "Requirements",
          "text": "<p>System requirements.</p>",
          "level": 3,
          "subsections": []
        }
      ]
    },
    {
      "title": "Usage",
      "text": "<p>Usage examples.</p>",
      "level": 2,
      "subsections": []
    }
  ]
}

Supported HTML Elements

Included Elements

  • Paragraphs (<p>)
  • Lists (<ul>, <ol>, <li>)
  • Links (<a>)
  • Formatting (<strong>, <em>, <code>, etc.)
  • Semantic elements (<section>, <article>, <aside>, etc.)
  • Tables (<table>, <tr>, <td>, etc.)
  • Media (<img>, <figure>)
  • Code blocks (<pre>, <code>)
  • Quotes (<blockquote>, <q>)
  • All other content elements with meaningful text

Excluded Elements

  • Headings (processed separately as section titles)
  • Script and style tags
  • Meta elements
  • Empty elements
  • Elements containing headings (processed as subsections)

Smart Root Element Detection

The tool automatically detects the best root element in this priority order:

  1. <main> - Primary content area
  2. <article> - Standalone article content
  3. <section> - Document section
  4. <body> - Document body
  5. First substantial <div> - Fallback for div-based layouts
  6. Entire document - Last resort

Advanced Features

Custom Headings

Supports custom headings with ARIA attributes:

<div role="heading" aria-level="2">Custom Heading</div>

Aria Level Overrides

Standard headings can have their levels overridden:

<h3 aria-level="1">This is treated as level 1</h3>

Mixed Content

Handles complex layouts with mixed content types:

<div>
    <h1>Main Title</h1>
    <p>Introduction</p>
    <section>
        <h2>Section in Section</h2>
        <p>Section content</p>
    </section>
    <h2>Regular Heading</h2>
    <p>Regular content</p>
</div>

Testing

Run the test suite:

python -m pytest tests/ -v

The project includes comprehensive tests covering:

  • Basic parsing functionality
  • Heading level detection
  • Content extraction
  • Section handling
  • Edge cases and error conditions

License

This project is open source. See LICENSE file for details.

Contributing

Contributions are welcome! Please submit pull requests with tests for any new features.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

content_extraction-0.3.0.tar.gz (21.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

content_extraction-0.3.0-py3-none-any.whl (22.7 kB view details)

Uploaded Python 3

File details

Details for the file content_extraction-0.3.0.tar.gz.

File metadata

  • Download URL: content_extraction-0.3.0.tar.gz
  • Upload date:
  • Size: 21.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for content_extraction-0.3.0.tar.gz
Algorithm Hash digest
SHA256 a049c7f0c1d7c6f9e4770c5ff22693d3a976bc338fc306eb69e424e2b280bc6f
MD5 771d05102dcfc2350f028da13b5b6792
BLAKE2b-256 fb06cea34c3c23a037fbe2555766dbcfdbb00e441b97d323ca0a96198c0efc9c

See more details on using hashes here.

Provenance

The following attestation bundles were made for content_extraction-0.3.0.tar.gz:

Publisher: python-package.yml on ChrisW-priv/html-chunking

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file content_extraction-0.3.0-py3-none-any.whl.

File metadata

File hashes

Hashes for content_extraction-0.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 f1a01e87f4ad8ca7a9ea70b7f853554a89ec08071e164e415c510eac11978a90
MD5 6a4c56a52be2dabce0d2f4fa1d296d67
BLAKE2b-256 ef4cd2e744d32b18a27770052ae5f9ca16e5bf04513e87f77295846202dc4cd2

See more details on using hashes here.

Provenance

The following attestation bundles were made for content_extraction-0.3.0-py3-none-any.whl:

Publisher: python-package.yml on ChrisW-priv/html-chunking

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page