@iocium/domhash

Structure-aware and layout-aware perceptual hashing for HTML and DOM content.

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Features

• Structural and visual similarity detection for DOM trees
• Layout-aware hashing using tag display roles (block, inline, etc.)
• Supports perceptual hash algorithms: sha256, murmur3, blake3, simhash, minhash
• Resilience scoring to detect obfuscated or fragile DOMs
• Rich CLI and programmatic API
• Markdown and HTML output with structural diffs
• 100% test coverage

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Installation

npm install @iocium/domhash

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CLI Usage

npx domhash <input> [options]

Flags

Option	Description
--algo <type>	Choose hashing algorithm
--include <attrs>	Comma-separated list of attributes to include
--shape	Output tag shape vector
--layoutAware	Enable layout-based canonicalization
--resilience	Output a resilience score
--compare <input>	Compare against another HTML or URL
--diff	Show structural diff
--output <type>	Output format: json, markdown, html

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Programmatic API

import { domhash, computeResilienceScore, compareStructures } from '@iocium/domhash';

const result = await domhash('<form><input></form>', {
  layoutAware: true,
  resilience: true,
  shapeVector: true,
  includeAttributes: ['action']
});

console.log(result.hash);              // structure hash
console.log(result.layoutHash);        // layout-aware hash
console.log(result.resilienceScore);   // between 0 and 1
console.log(result.shape);             // tag structure vector

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Output Example (Markdown)

### DOM Hash Comparison Report

- SHA A: `abc123`
- SHA B: `def456`
- Structural Similarity: `91.25%`
- Shape Similarity: `88.00%`

**Structural Diff:**

```diff
- <p></p>
+ <span></span>

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🪪 License

MIT License — see LICENSE for full terms.

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Made with 💙 by iocium