Extract embedded metadata from HTML markup
Project description
extruct is a library for extracting embedded metadata from HTML markup.
It also has a built-in HTTP server to test its output as JSON.
Currently, extruct only supports W3C’s HTML Microdata and embedded JSON-LD.
The microdata algorithm is a revisit of this Scrapinghub blog post showing how to use EXSLT extensions.
Roadmap
support for RDFa Lite (e.g. Facebook Open Graph protocol metadata)
Installation
pip install extruct
Usage
Microdata extraction
>>> from pprint import pprint
>>>
>>> from extruct.w3cmicrodata import MicrodataExtractor
>>>
>>> # example from http://www.w3.org/TR/microdata/#associating-names-with-items
>>> html = """<!DOCTYPE HTML>
... <html>
... <head>
... <title>Photo gallery</title>
... </head>
... <body>
... <h1>My photos</h1>
... <figure itemscope itemtype="http://n.whatwg.org/work" itemref="licenses">
... <img itemprop="work" src="images/house.jpeg" alt="A white house, boarded up, sits in a forest.">
... <figcaption itemprop="title">The house I found.</figcaption>
... </figure>
... <figure itemscope itemtype="http://n.whatwg.org/work" itemref="licenses">
... <img itemprop="work" src="images/mailbox.jpeg" alt="Outside the house is a mailbox. It has a leaflet inside.">
... <figcaption itemprop="title">The mailbox.</figcaption>
... </figure>
... <footer>
... <p id="licenses">All images licensed under the <a itemprop="license"
... href="http://www.opensource.org/licenses/mit-license.php">MIT
... license</a>.</p>
... </footer>
... </body>
... </html>"""
>>>
>>> mde = MicrodataExtractor()
>>> data = mde.extract(html)
>>> pprint(data)
[{'properties': {'license': 'http://www.opensource.org/licenses/mit-license.php',
'title': 'The house I found.',
'work': 'http://www.example.com/images/house.jpeg'},
'type': 'http://n.whatwg.org/work'},
{'properties': {'license': 'http://www.opensource.org/licenses/mit-license.php',
'title': 'The mailbox.',
'work': 'http://www.example.com/images/mailbox.jpeg'},
'type': 'http://n.whatwg.org/work'}]
JSON-LD extraction
>>> from pprint import pprint
>>>
>>> from extruct.jsonld import JsonLdExtractor
>>>
>>> html = """<!DOCTYPE HTML>
... <html>
... <head>
... <title>Some Person Page</title>
... </head>
... <body>
... <h1>This guys</h1>
... <script type="application/ld+json">
... {
... "@context": "http://schema.org",
... "@type": "Person",
... "name": "John Doe",
... "jobTitle": "Graduate research assistant",
... "affiliation": "University of Dreams",
... "additionalName": "Johnny",
... "url": "http://www.example.com",
... "address": {
... "@type": "PostalAddress",
... "streetAddress": "1234 Peach Drive",
... "addressLocality": "Wonderland",
... "addressRegion": "Georgia"
... }
... }
... </script>
... </body>
... </html>"""
>>>
>>> jslde = JsonLdExtractor()
>>>
>>> data = jslde.extract(html)
>>> pprint(data)
[{'@context': 'http://schema.org',
'@type': 'Person',
'additionalName': 'Johnny',
'address': {'@type': 'PostalAddress',
'addressLocality': 'Wonderland',
'addressRegion': 'Georgia',
'streetAddress': '1234 Peach Drive'},
'affiliation': 'University of Dreams',
'jobTitle': 'Graduate research assistant',
'name': 'John Doe',
'url': 'http://www.example.com'}]
RDFa extraction (experimental)
First, install the extra dependencies for RDFa support (extruct depends on rdflib and rdflib-jsonld for this):
pip install extruct[rdfa]
Then feed some HTML to a extruct.rdfa.RDFaExtractor instance using .extract():
>>> from pprint import pprint
>>> from extruct.rdfa import RDFaExtractor # you can ignore the warning about html5lib not being available
INFO:rdflib:RDFLib Version: 4.2.1
/home/paul/.virtualenvs/extruct.wheel.test/lib/python3.5/site-packages/rdflib/plugins/parsers/structureddata.py:30: UserWarning: html5lib not found! RDFa and Microdata parsers will not be available.
'parsers will not be available.')
>>>
>>> html = """<html>
... <head>
... ...
... </head>
... <body prefix="dc: http://purl.org/dc/terms/ schema: http://schema.org/">
... <div resource="/alice/posts/trouble_with_bob" typeof="schema:BlogPosting">
... <h2 property="dc:title">The trouble with Bob</h2>
... ...
... <h3 property="dc:creator schema:creator" resource="#me">Alice</h3>
... <div property="schema:articleBody">
... <p>The trouble with Bob is that he takes much better photos than I do:</p>
... </div>
... ...
... </div>
... </body>
... </html>
... """
>>>
>>> rdfae = RDFaExtractor()
>>> pprint(
... rdfae.extract(html, url='http://www.example.com/index.html')
... )
[{'@id': 'http://www.example.com/alice/posts/trouble_with_bob',
'@type': ['http://schema.org/BlogPosting'],
'http://purl.org/dc/terms/creator': [{'@id': 'http://www.example.com/index.html#me'}],
'http://purl.org/dc/terms/title': [{'@value': 'The trouble with Bob'}],
'http://schema.org/articleBody': [{'@value': '\n'
' The trouble with Bob '
'is that he takes much better '
'photos than I do:\n'
' '}],
'http://schema.org/creator': [{'@id': 'http://www.example.com/index.html#me'}]}]
You’ll get a list of expanded JSON-LD nodes.
REST API service
extruct also ships with a REST API service to test its output from URLs.
Dependencies
Usage
python -m extruct.service
launches an HTTP server listening on port 10005.
Methods supported
/extruct/<URL>
method = GET
/extruct/batch
method = POST
params:
urls - a list of URLs separted by newlines
urlsfile - a file with one URL per line
E.g. http://localhost:10005/extruct/http://www.sarenza.com/i-love-shoes-susket-s767163-p0000119412
will output something like this:
{
"url":"http://www.sarenza.com/i-love-shoes-susket-s767163-p0000119412",
"status":"ok",
"microdata":[
{
"type":"http://schema.org/Product",
"properties":{
"name":"Susket",
"color":[
"http://www.sarenza.com/i-love-shoes-susket-s767163-p0000119412",
"http://www.sarenza.com/i-love-shoes-susket-s767163-p0000119412"
],
"brand":"http://www.sarenza.com/i-love-shoes",
"aggregateRating":{
"type":"http://schema.org/AggregateRating",
"properties":{
"description":"Soyez le premier \u00e0 donner votre avis"
}
},
"offers":{
"type":"http://schema.org/AggregateOffer",
"properties":{
"lowPrice":"59,00 \u20ac",
"price":"A partir de\r\n 59,00 \u20ac",
"priceCurrency":"EUR",
"highPrice":"59,00 \u20ac",
"availability":"http://schema.org/InStock"
}
},
"size":[
"36 - Epuis\u00e9 - \u00catre alert\u00e9",
"37 - Epuis\u00e9 - \u00catre alert\u00e9",
"38 - Epuis\u00e9 - \u00catre alert\u00e9",
"39 - Derni\u00e8re paire !",
"40",
"41",
"42 - Derni\u00e8re paire !"
],
"image":[
"http://cdn2.sarenza.net/static/_img/productsV4/0000119412/MD_0000119412_223992_09.jpg?201509221045",
"http://cdn1.sarenza.net/static/_img/productsV4/0000119412/MD_0000119412_223992_03.jpg?201509221045",
"http://cdn3.sarenza.net/static/_img/productsV4/0000119412/MD_0000119412_223992_04.jpg?201509221045",
"http://cdn2.sarenza.net/static/_img/productsV4/0000119412/MD_0000119412_223992_05.jpg?201509221045",
"http://cdn1.sarenza.net/static/_img/productsV4/0000119412/MD_0000119412_223992_06.jpg?201509221045",
"http://cdn1.sarenza.net/static/_img/productsV4/0000119412/MD_0000119412_223992_07.jpg?201509221045",
"http://cdn1.sarenza.net/static/_img/productsV4/0000119412/MD_0000119412_223992_08.jpg?201509221045",
"http://cdn2.sarenza.net/static/_img/productsV4/0000119412/MD_0000119412_223992_02.jpg?201509291747"
],
"description":""
}
}
]
}
Development version
mkvirtualenv extruct pip install -r requirements-dev.txt
Tests
Run tests in current environment:
py.test tests
Use tox to run tests with different Python versions:
tox
Versioning
Use bumpversion to conveniently change project version:
bumpversion patch # 0.0.0 -> 0.0.1 bumpversion minor # 0.0.1 -> 0.1.0 bumpversion major # 0.1.0 -> 1.0.0
Release history Release notifications | RSS feed
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