def dump_articles():
connection = MongoClient('localhost', 27017)
db = connection.PTEST_BACKUP
results = db.crawling.find({}, {'_id': False})
"""
{
"_id" : ObjectId("54dd29d2b396811764a01330"),
"url" : "http://www.nasa.gov/pdf/55395main_12%20Earth%20Science.pdf",
"home" : "NASA",
"abstract" : "The mission of NASA's Earth Science ... and help answer qu
estions concerning many related aspects of ... forecasters in assessing particul
ate pollutio ...",
"title" : "Earth Science - NASA",
"keyword" : "aerosols+(pollution+aspects)",
"stored" : true,
"complete" : false,
"key" : "aerosols (pollution aspects)",
"hashed" : "aHR0cDovL3d3dy5uYXNhLmdvdi9wZGYvNTUzOTVtYWluXzEyJTIwRWFydGglMjBTY2llbmNlLnBkZg=="
}
"""
# upload via POST endpoint
from scripts.remote.remote import post_curling
import json
for record in results:
post_curling(_CRAWLING_POST['local'], {'resource': json.dumps(record), 'pwd': _TEMP_SECRET}, display=True)
# close the connection to MongoDB
connection.close()
def test_post_to_component_endpoint(self):
"""
WARNING: it stores in the local datastore the json-ld in testdata.component
:return:
"""
#from models import Component
from scripts.testdata.component import component
from scripts.remote.remote import post_curling
post_curling(url='http://localhost:8080/database/cots/store',
params={'pwd': _TEMP_SECRET, 'data': component},
display=True)
def test_dumping_pipe_full(cls):
"""
Tests creating python instances > dumping JSON-LD > translate into N-TRIPLES
:return:
"""
print " --- full test for generating components and dumping them in JSON-LD"
jsons = [SubSystem.generate_py_instance(k, v) for k, v in tech_constrains.items()]
jsonlds = [SubSystem.generate_jsonld(c) for c in jsons]
print json.dumps(jsonlds, indent=4)
print " --- Translating the component into ntriples via RDFtranslator"
from scripts.remote.remote import post_curling
url = 'http://rdf-translator.appspot.com/convert/json-ld/nt/content'
post_curling(url, {'content': json.dumps(jsonlds)}, display=True)
def set_typeof_and_ingraph_properties(self, bookmark='start'):
print "Fetching page: " + bookmark
articles = get_curling(_ENV[self.test_env]['_SERVICE'] + '/datastore/index',
{'token': _CLIENT_TOKEN,
'bookmark': bookmark if bookmark != 'start' else ''})
articles = json.loads(articles)
# fetch single article
for a in articles['articles']:
res = get_curling(
_ENV[self.test_env]['_SERVICE'] + '/datastore/webresource',
{
'retrieve': a,
'token': _CLIENT_TOKEN
}
)
res = json.loads(res)
if not res['type_of'] in res.keys():
try:
int(res['title'])
update = {'type_of': 'tweet', 'in_graph': False }
except Exception:
if res['title'] == '':
if res['url'].endswith(('jpg', 'jpeg', 'png', 'mp3', 'mp4')):
update = {'type_of': 'media', 'in_graph': False }
else:
update = {'type_of': 'link', 'in_graph': False }
else:
update = {'type_of': 'feed', 'in_graph': False }
print update
post_curling(
_ENV[self.test_env]['_SERVICE'] + '/datastore/webresource',
{ 'token': _CLIENT_TOKEN,
'update': a,
'properties': json.dumps(update)
},
display=True
)
if not articles['next']:
return None
return self.fetch_and_dump_webresources(
bookmark=articles['next']
)
def dump_concepts_to_graph(self, list_of_ids, url):
"""
Take a list of unique ids, create a graph of concepts, serialize it to triples and dump them to
right graph in the shard.
:param list_of_ids: a list() of numerical ids from the datastore
:param url: the url of the sparql endpoint of the shard
:return: None
"""
g = Graph()
for uuid in list_of_ids:
[g.add(c) for c in self.create_concepts_triples(uuid)]
triples = g.serialize(format='nt')
post_curling(url,
{'token': _CLIENT_TOKEN,
'triple': triples,
'graph_id': _CONCEPTS_GRAPH_ID},
display=True
)
def dump_webresources_to_graph(self, list_of_ids, url):
"""
Take a list of unique ids, create a graph of webresources, serialize it to triples and dump them to the
right graph in the shard.
:param list_of_ids: a list() of numerical ids from the datastore
:param url: the url of the sparql endpoint of the shard
:return: None
"""
g = Graph()
for uuid in list_of_ids:
print uuid
g.add(self.create_webresource_triple(uuid))
triples = g.serialize(format='nt')
post_curling(url,
{'token': _CLIENT_TOKEN,
'triple': triples,
'graph_id': _WEBRES_GRAPH_ID},
display=True
)
def dump_articles():
connection = MongoClient('localhost', 27017)
db = connection.PTEST_BACKUP
results = db.crawling.find({}, {'_id': False})
"""
{
"_id" : ObjectId("54dd29d2b396811764a01330"),
"url" : "http://www.nasa.gov/pdf/55395main_12%20Earth%20Science.pdf",
"home" : "NASA",
"abstract" : "The mission of NASA's Earth Science ... and help answer qu
estions concerning many related aspects of ... forecasters in assessing particul
ate pollutio ...",
"title" : "Earth Science - NASA",
"keyword" : "aerosols+(pollution+aspects)",
"stored" : true,
"complete" : false,
"key" : "aerosols (pollution aspects)",
"hashed" : "aHR0cDovL3d3dy5uYXNhLmdvdi9wZGYvNTUzOTVtYWluXzEyJTIwRWFydGglMjBTY2llbmNlLnBkZg=="
}
"""
# upload via POST endpoint
from scripts.remote.remote import post_curling
import json
for record in results:
post_curling(_CRAWLING_POST['local'], {
'resource': json.dumps(record),
'pwd': _TEMP_SECRET
},
display=True)
# close the connection to MongoDB
connection.close()
def test_n3_endpoints(self):
"""
Test the N3
"""
print "Running test_n3_endpoints"
env = self.test_env
base_url_resource = _ENV[env]['_SERVICE'] + "/datastore/webresource"
base_url_concept = _ENV[env]['_SERVICE'] + "/datastore/concept"
test_concepts = []
response = post_curling(base_url_resource, {"token": _CLIENT_TOKEN})
print response
pass
