# dragnet-org/dragnet

Just the facts -- web page content extraction

Repository: https://github.com/dragnet-org/dragnet
Canonical: https://ross.abutalabs.com/products/dragnet
Language: Python
License: MIT
License Family: permissive
Last push: 2025-07-08T00:53:21+00:00

## Health v2 (maintenance only)
Score: 36/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 30, release rhythm 8, longevity 100
- inputs: {"age_days": 5187, "days_push": 422, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1274, forks 176 (observed 2026-08-28T04:04:12.825539+00:00)

## What it is
Dragnet is a Python library that uses machine learning models to extract the main article content, and optionally user comments, from HTML web pages. It provides simple extraction functions plus sklearn-style trainable extractors with pre-trained models.

## Use cases
- extract main article text from html pages
- strip boilerplate and chrome from web pages
- extract article content and comments from a webpage
- readability-style content extraction in python
- train a custom content extraction model
- clean html for text mining pipelines

## When to choose
- you need high-accuracy main-content extraction from article pages
- you want to also capture user comments alongside the article
- you want to train or fine-tune your own extraction model with sklearn-style APIs

## When to avoid
- you need to extract structured data like tables or product listings rather than article text
- you need a maintained general-purpose scraper with JavaScript rendering
- your project requires actively developed dependencies and recent community activity

## Facets
- artifact type: library
- maturity: maintenance
- function: nlp, parser, machine-learning, web-scraping
- domain: web-development, machine-learning, crawlers
- platform: python
- tags: content-extraction, boilerplate-removal, html-parsing, readability, article-extraction, natural-language-processing

## Member repositories
- dragnet-org/dragnet (main) score 36

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:12.825539+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T05:03:07.034187+00:00, confidence not recorded.
  - readme: https://github.com/dragnet-org/dragnet (fetched 2026-08-28T04:04:12.825539+00:00, sha 07d69d2f0d0e)
- Data as of 2026-08-30T08:39:29.467469+00:00.