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trafilaturavsextruct

GPLv3+ 68 3 2,594
251.4 thousand (month) Jul 17 2019 1.7.0(2 months ago)
802 10 53 BSD
0.16.0(8 months ago) Oct 27 2015 187.8 thousand (month)

Trafilatura is a Python package and command-line tool designed to gather text on the Web. It includes discovery, extraction and text processing components. Its main applications are web crawling, downloads, scraping, and extraction of main texts, metadata and comments. It aims at staying handy and modular: no database is required, the output can be converted to various commonly used formats.

Going from raw HTML to essential parts can alleviate many problems related to text quality, first by avoiding the noise caused by recurring elements (headers, footers, links/blogroll etc.) and second by including information such as author and date in order to make sense of the data. The extractor tries to strike a balance between limiting noise (precision) and including all valid parts (recall). It also has to be robust and reasonably fast, it runs in production on millions of documents.

This tool can be useful for quantitative research in corpus linguistics, natural language processing, computational social science and beyond: it is relevant to anyone interested in data science, information extraction, text mining, and scraping-intensive use cases like search engine optimization, business analytics or information security.

extruct is a library for extracting embedded metadata from HTML markup.

Currently, extruct supports:

  • W3C's HTML Microdata
  • embedded JSON-LD
  • Microformat via mf2py
  • Facebook's Open Graph
  • (experimental) RDFa via rdflib
  • Dublin Core Metadata (DC-HTML-2003)

Extruct is a brilliant data parser for schema.org marked up websites (many modern websites) and is an easy way to extract popular details like product information, company contact details etc.

Example Use


# it can be used to clean HTML files
from trafilatura import clean_html

html = '<html><head><title>My Title</title></head><body><p>This is some <b>bold</b> text.</p></body></html>'
cleaned_html = clean_html(html)
print(cleaned_html)

# can strip away tags:
clean_html(html, tags_to_remove=["title"])
# or attributes
clean_html(html, attributes_to_remove=["title"])
# retrieve HTML content
import httpx

response = httpx.get('https://webscraping.fyi/lib/python/extruct')

import extruct

all_data = extruct.extract(response.text, response.url)

# or we can extract specific metadata format by importing individuals extractors:


extractor = extruct.MicrodataExtractor()
microdata = extractor.extract(response.text)

extractor = extruct.JsonLdExtractor()
jsonld = extractor.extract(response.text) 

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