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Template Fingerprinting

Use cases

Auditing large sites by template instead of individual pages Finding pages using wrong or outdated templates Understanding site structure and page types Prioritising template-level technical SEO fixes

Classifies pages into template groups using TF-IDF vectorisation and K-Means clustering on HTML structure.

Extracts four feature dimensions: tag counts, CSS classes, ID attributes, and meta tags.

Default 5 clusters with reproducible results (random state 42).

Streamlit App

Platform

Browser-based (no installation required)

Input

Crawl CSV with URLs

Output

CSV with template cluster assignments

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Features

  • TF-IDF vectorisation of HTML structural features
  • K-Means clustering (configurable cluster count, default 5)
  • Four feature dimensions: tag counts, CSS classes, IDs, meta tags
  • Reproducible results (random state 42)
  • Bulk URL fetching with progress indicator

How to use

  1. 1 Upload CSV with URL list (requires "Address" column)
  2. 2 Set number of template clusters to detect
  3. 3 Run analysis (fetches HTML, extracts features, clusters)
  4. 4 Review cluster assignments (Type 0, Type 1, etc.)
  5. 5 Download CSV with original data plus Cluster and Page Type columns

Want me to run this for you?

I offer this as a managed service. You get the insights without touching the tool.

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