def get(self, term):
"""
Returns list of matching concepts or entities using lexical search
"""
args = simple_parser.parse_args()
q = GolrSearchQuery(term,
**args)
results = q.exec()
return results
def test_search_go_ontol():
q = GolrSearchQuery("transport*", category='ontology_class', is_go=True)
print("Q={}".format(q))
params = q.solr_params()
print("PARAMS={}".format(params))
results = q.exec()
print("RESULTS={}".format(results))
docs = results['docs']
for r in docs:
print(str(r))
assert len(docs) > 0
def test_search():
q = GolrSearchQuery("abnormal")
print("Q={}".format(q))
params = q.solr_params()
print("PARAMS={}".format(params))
results = q.exec()
print("RESULTS={}".format(results))
docs = results['docs']
for r in docs:
print(str(r))
assert len(docs) > 0
def test_search_go_all():
q = GolrSearchQuery("transport*", is_go=True)
print("Q={}".format(q))
params = q.solr_params()
print("PARAMS={}".format(params))
results = q.exec()
print("RESULTS={}".format(results))
docs = results['docs']
for r in docs:
print(str(r))
assert len(docs) > 0
print(str(results['facet_counts']))
def test_cursor():
"""
Tests rows and start parameters.
First fetch 100 docs, then same query but iterate with cursor in increments of ten.
The two sets of IDs returned should be identicial
"""
q = GolrSearchQuery("abnormal", rows=100)
results = q.exec()
docs = results['docs']
ids = set([d['id'] for d in docs])
print('Init ids={}'.format(ids))
assert len(ids) == 100
matches = set()
for i in range(0,10):
q = GolrSearchQuery("abnormal", start=i*10, rows=10)
docs = q.exec()['docs']
next_ids = [d['id'] for d in docs]
assert len(next_ids) == 10
print('Next ids (from {}) = {}'.format(i*10, next_ids))
matches.update(next_ids)
assert len(matches) == 100
assert len(matches.intersection(ids)) == 100
def get_concepts():
keywords = request.args.get('keywords', None)
semanticGroups = request.args.get('semanticGroups', None)
pageSize = int(request.args.get('pageSize', 1))
pageNumber = int(request.args.get('pageNumber', 1))
validatePagination(pageSize, pageNumber)
validateKeywords(keywords)
q = GolrSearchQuery(term=keywords,
category=build_categories(semanticGroups),
rows=pageSize,
start=getStartIndex(pageNumber, pageSize))
results = q.exec()
concepts = []
for d in results['docs']:
concept = parse_concept(d)
concepts.append(concept)
return jsonify(concepts)
def search(term, args):
q = GolrSearchQuery(term, args)
return q.exec()
