def search():
search_term = request.args.get('q')
print 'User searched for', search_term
keys = []
# Lab 5: Use the English FTS index to search with the term provided
result = bucket.search('English', FT.MatchQuery(search_term, fuzziness=1))
for row in result:
keys.append(row['id'])
print 'Found matches', ', '.join(keys)
return jsonify({'keys': keys})
def test_match_query(self):
exp_json = {
'query': {
'match': 'salty beers',
'analyzer': 'analyzer',
'boost': 1.5,
'field': 'field',
'fuzziness': 1234,
'prefix_length': 4
},
'size': 10,
'indexName': 'ix'
}
q = cbft.MatchQuery('salty beers', boost=1.5, analyzer='analyzer',
field='field', fuzziness=1234, prefix_length=4)
p = cbft.Params(limit=10)
self.assertEqual(exp_json, cbft.make_search_body('ix', q, p))
#!/usr/bin/env python
from __future__ import print_function
from pprint import pprint
from couchbase.bucket import Bucket
import couchbase.fulltext as FT
cb = Bucket()
results = cb.search('travel-search',
FT.MatchQuery('part', fuzziness=0, field='content'),
limit=3,
facets={'countries': FT.TermFacet('country', limit=3)})
for row in results:
pprint(row)
print('Facet results:')