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mirror of https://github.com/gsi-upm/sitc synced 2024-11-24 23:42:29 +00:00

Add Beatles introduction

This commit is contained in:
J. Fernando Sánchez 2019-02-20 18:52:05 +01:00
parent 9937490213
commit 1f5318a357
7 changed files with 1910 additions and 1992 deletions

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@ -1,49 +0,0 @@
import sys
from future.standard_library import install_aliases
install_aliases()
from urllib import request, parse
from rdflib import Graph, term
from lxml import etree
if len(sys.argv) < 2:
print('Usage: python {} <URL>'.format(sys.argv[0]))
print('')
print('Extract rdfa, microdata and json-ld annotations from a website')
exit(1)
url = sys.argv[1]
g = Graph()
g.parse(url, format='rdfa')
g.parse(url, format='microdata')
def sanitize_triple(t):
"""Function to remove bad URIs from the graph that would otherwise
make the serialization fail."""
def sanitize_triple_item(item):
if isinstance(item, term.URIRef) and '/' not in item:
return term.URIRef(parse.quote(str(item)))
return item
return (sanitize_triple_item(t[0]),
sanitize_triple_item(t[1]),
sanitize_triple_item(t[2]))
with request.urlopen(url) as response:
# Get all json-ld objects embedded in the html file
html = response.read().decode('utf-8', errors='ignore')
parser = etree.XMLParser(recover=True)
root = etree.fromstring(html, parser=parser)
if root:
for jsonld in root.findall(".//script[@type='application/ld+json']"):
g.parse(data=jsonld.text, publicID=url, format='json-ld')
fixedgraph = Graph()
fixedgraph += [sanitize_triple(s) for s in g]
print(g.serialize(format='turtle').decode('utf-8', errors='ignore'))

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@ -1,12 +1,22 @@
'''
Helper functions and ipython magic for the SPARQL exercises.
The tests in the notebooks rely on the `LAST_QUERY` variable, which is updated by the `%%sparql` magic after every query.
This variable contains the full query used (`LAST_QUERY["query"]`), the endpoint it was sent to (`LAST_QUERY["endpoint"]`), and a dictionary with the response of the endpoint (`LAST_QUERY["results"]`).
For convenience, the results are also given as tuples (`LAST_QUERY["tuples"]`), and as a dictionary of of `{column:[values]}` (`LAST_QUERY["columns"]`).
'''
from IPython.core.magic import (register_line_magic, register_cell_magic,
register_line_cell_magic)
from IPython.display import HTML, display, Image
from IPython.display import HTML, display, Image, display_javascript
from urllib.request import Request, urlopen
from urllib.parse import quote_plus, urlencode
from urllib.error import HTTPError
import json
import sys
js = "IPython.CodeCell.options_default.highlight_modes['magic_sparql'] = {'reg':[/^%%sparql/]};"
display_javascript(js, raw=True)
def send_query(query, endpoint):
@ -20,7 +30,11 @@ def send_query(query, endpoint):
headers={'content-type': 'application/x-www-form-urlencoded',
'accept': FORMATS},
method='POST')
return json.loads(urlopen(r).read().decode('utf-8'));
res = urlopen(r)
data = res.read().decode('utf-8')
if res.getcode() == 200:
return json.loads(data)
raise Exception('Error getting results: {}'.format(data))
def tabulate(tuples, header=None):
@ -39,11 +53,14 @@ def tabulate(tuples, header=None):
LAST_QUERY = {}
def solution():
return LAST_QUERY
def query(query, endpoint=None, print_table=False):
global LAST_QUERY
endpoint = endpoint or "http://dbpedia.org/sparql"
endpoint = endpoint or "http://fuseki.cluster.gsi.dit.upm.es/sitc/"
results = send_query(query, endpoint)
tuples = to_table(results)
@ -80,12 +97,30 @@ def to_table(results):
@register_cell_magic
def sparql(line, cell):
'''
Sparql magic command for ipython. It can be used in a cell like this:
```
%%sparql
... Your SPARQL query ...
```
by default, it will use the DBpedia endpoint, but you can use a different endpoint like this:
```
%%sparql http://my-sparql-endpoint...
... Your SPARQL query ...
```
'''
try:
return query(cell, endpoint=line, print_table=True)
except HTTPError as ex:
error_message = ex.read().decode('utf-8')
print('Error {}. Reason: {}'.format(ex.status, ex.reason))
print(error_message)
print(error_message, file=sys.stderr)
def show_photos(values):

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@ -1,29 +0,0 @@
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix schema: <http://schema.org/> .
_:Hotel1 a schema:Hotel ;
schema:description "A fictitious hotel" .
_:Review1 a schema:Review ;
schema:reviewBody "This is a great review" ;
schema:reviewRating [
a schema:Rating ;
schema:author <http://jfernando.es/me> ;
schema:ratingValue "0.7"
] ;
schema:itemReviewed _:Hotel1 .
_:Review2 a schema:Review ;
schema:reviewBody "This is a not so great review" ;
schema:reviewRating [
a schema:Rating ;
schema:author [ a schema:Person ;
schema:givenName "anonymous" ] ;
schema:ratingValue "0.3"
] ;
schema:itemReviewed _:Hotel1 .

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@ -1,23 +0,0 @@
# !/bin/env python #
# Ejemplo de consultas SPARQL sobre turtle #
# python consultas.py #
import rdflib
import sys
dataset = sys.argv[1] if len(sys.argv) > 1 else 'reviews.ttl'
g = rdflib.Graph()
schema = rdflib.Namespace("http://schema.org/")
# Read Turtle file #
g.parse(dataset, format='turtle')
results = g.query(
"""SELECT DISTINCT ?review ?p ?o
WHERE {
?review a schema:Review.
?review ?p ?o.
}""", initNs={'schema': schema})
for row in results:
print("%s %s %s" % row)

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@ -1,6 +0,0 @@
import rdflib
import sys
g = rdflib.Graph()
dataset = sys.argv[1] if len(sys.argv) > 1 else 'reviews.ttl'
g.parse(dataset, format="n3")
print(g.serialize(format="n3").decode('utf-8'))