RDTextract 0.1.1

HTML→Markdown extractor optimized for LLM training corpora — zero noise artifacts, integrated quality scoring, low-value stub detection.

RDTextract

HTML→Markdown extractor built for AI / LLM training corpora — every byte should carry signal, not boilerplate.

Language scope (current): filters, paywall markers, and the is_low_value_stub() heuristic are tuned for French content (the corpus this lib was extracted from is FR-only). Core extraction is language-agnostic and works on any language; only the stub detector is FR-specific. Multi-language support is on the roadmap.

• Zero noise artifacts — no double-bullets, no orphan punctuation, no link dumps, no widget repetition.
• Integrated quality scoring — is_low_value_stub() filters paywalls, login walls, skip-link stubs, empty pages.
• Meta fallback — degrades gracefully on SPA / React pages where the body is empty (extracts <title> + meta description instead of returning nothing).
• One dependency: beautifulsoup4.

Install

pip install RDTextract

Quick start

import rdtextract

html = open("page.html").read()

# One-shot
markdown = rdtextract.extract(html)

# Or two-step (re-use cleaned HTML for caching, debugging, etc.)
cleaned = rdtextract.clean_html(html)
markdown = rdtextract.to_markdown(cleaned)

# Filter low-value pages before writing to your corpus
if not rdtextract.is_low_value_stub(markdown):
    save(markdown)

Note : PyPI distribution is RDTextract, Python module is rdtextract (PEP 8 lowercase).

Why another HTML→Markdown lib?

Existing tools target human readability (newsletters, archive). RDTextract targets LLM training data: every byte should carry signal.

Benchmark on Tranco top-1000 .fr homepages (672 pages successfully fetched and processed), measured against a corpus quality scorer (lower artifact counts = cleaner output):

Extractor	Quality (corrected)	double-bullet	orphan punct	http dump	para dup
RDTextract	98.3	0	0	0	0
html2text	96.2	1	148	70	2 373
trafilatura	96.1	18	780	10	309
markdownify	85.5	0	246	107	5 042

RDTextract wins on quality and on all 4 artifact metrics — zero artifacts on every counter. Reproducible: see benchmark/ — domain list is committed (Tranco, deterministic), HTML cache is .gitignored.

Trade-off: RDTextract is ~3× slower than html2text (filtering + walking + dedup) and filters more aggressively, so a handful of content-light landing pages return empty — by design.

API

clean_html(html: str) -> str

Strip nav/footer/scripts/ads/hidden elements. Drops responsive duplicates (mobile/desktop variants), icon font ligatures, role-based junk (role=navigation, role=banner, …).

to_markdown(cleaned_html: str) -> str

Walk the cleaned tree and emit Markdown. Includes:

• Heading levels, lists (with sublist flattening), tables (colspan, nested), code blocks, blockquotes, definition lists.
• Post-processing: collapse whitespace, restore breadcrumb separators, dedup consecutive blocks, dedup global blocks (UI widgets repeated ≥3×).
• Meta fallback for SPA pages.

extract(html: str) -> str

Convenience: to_markdown(clean_html(html)).

is_low_value_stub(markdown: str) -> bool

True if the markdown is a paywall (FR markers), login stub, MediaWiki skip-link alone, or empty. Combined length + marker check (avoids false positives on real articles that happen to mention these phrases).

License

MIT