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python-extraction

python-extraction

Use Trafilatura's Python APIs to extract text, metadata, comments, tables, and structured TXT/Markdown/JSON/HTML/XML/XML-TEI from in-memory HTML inputs.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: python-extraction description: "Use Trafilatura's Python APIs to extract text, metadata, comments, tables, and structured TXT/Markdown/JSON/HTML/XML/XML-TEI from in-memory HTML inputs." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Python Extraction

Use this sub-skill when a task needs Trafilatura's Python API to turn an already available HTML payload, response body, or parsed LXML tree into extracted article text, metadata, comments, tables, or structured output.

Route here

  • In-memory extraction from str, bytes, response-like objects with .data, or lxml.html.HtmlElement inputs.
  • Choosing between extract(), bare_extraction(), extract_with_metadata(), extract_metadata(), html2txt(), baseline(), and load_html().
  • Selecting output_format among txt, markdown, json, html, csv, xml, and xmltei.
  • Using metadata/comment/table/link/image/formatting flags, precision/recall/fast modes, Extractor settings objects, prune_xpath, date parameters, language filtering, and config-driven size limits.
  • Diagnosing None output, too-short results, malformed HTML, metadata/date surprises, and Markdown/XML conversion quirks.

Route elsewhere

  • CLI flags, shell pipelines, filesystem output, batch command construction, or stdin/stdout behavior: cli-batch-processing.
  • Live downloading, feed/sitemap discovery, URL queues, crawl loops, or response fetching: discovery-downloads.
  • Corpus-level deduplication strategy, TEI validation depth, benchmark evaluation, or quality scoring: corpus-quality.

Start points

  1. Read references/api-reference.md for function signatures, return shapes, option semantics, and output-format tradeoffs.
  2. Use references/workflows.md for copy-paste Python recipes and failure-aware extraction decisions.
  3. Use references/troubleshooting.md when extraction returns None, metadata is missing, language filtering behaves unexpectedly, or output formatting looks wrong.
  4. Run scripts/extraction_smoke.py in an environment with trafilatura installed to verify the basic no-network API surface.

Minimal pattern

from trafilatura import extract

html = """<html><body><article><h1>Title</h1><p>Main article text.</p></article></body></html>"""
text = extract(html, include_comments=False)
if text is None:
    # Retry with recall or a fallback API; see references/workflows.md.
    ...

Safety and scope notes

  • This sub-skill assumes HTML is already available. Do not initiate live network access from these recipes unless another sub-skill has explicitly selected and prepared that workflow.
  • Public runtime guidance here is self-contained for Trafilatura 2.2.0 and does not require reopening the source repository.
  • Some optional behavior, especially robust target_language body-language detection and speedups, depends on optional extras such as trafilatura[all]; handle absence as a runtime capability limit, not as an extraction bug.
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