def dedup(dataset):
ds = Dataset.by_name(dataset)
from time import time
from nomenklatura.matching import match
begin = time()
for value in Value.all(ds).limit(20):
matches = match(value.value, ds)
matches = filter(lambda (c, v, s): v != value.id, matches)
print[value.value, '=?', matches[0][1], matches[0][2]]
print "Time: %.2fms" % ((time() - begin) * 1000)
def dedup(dataset):
ds = Dataset.by_name(dataset)
from time import time
from nomenklatura.matching import match
begin = time()
for value in Value.all(ds).limit(20):
matches = match(value.value, ds)
matches = filter(lambda (c,v,s): v!=value.id, matches)
print [value.value, '=?', matches[0][1], matches[0][2]]
print "Time: %.2fms" % ((time() - begin)*1000)
def reconcile_op(dataset, query):
try:
limit = max(1, min(100, int(query.get('limit'))))
except ValueError:
limit = 5
except TypeError:
limit = 5
filters = [(p.get('p'), p.get('v')) for p in query.get('properties', [])]
if dataset is None:
dataset = type_to_dataset(query.get('type', ''))
results = match(query.get('query', ''), dataset)[:limit]
entities = Entity.id_map(dataset, map(lambda (c, e, s): e, results))
matches = []
skip = False
for (candidate, entity_id, score) in results:
entity = entities[entity_id]
for key, fv in filters:
if entity.data.get(key) != fv:
skip = True
if skip:
continue
id = url_for('entity.view', dataset=dataset.name, entity=entity.id)
uri = url_for('entity.view',
dataset=dataset.name,
entity=entity.id,
_external=True)
matches.append({
'name':
entity.name,
'score':
score,
'type': [{
'id': '/' + dataset.name,
'name': dataset.label
}],
'id':
id,
'uri':
uri,
'match':
score == 100
})
return {'result': matches, 'num': len(results)}
def reconcile_op(dataset, query):
try:
limit = max(1, min(100, int(query.get('limit'))))
except ValueError: limit = 5
except TypeError: limit = 5
filters = [(p.get('p'), p.get('v')) for p in query.get('properties', [])]
if dataset is None:
dataset = type_to_dataset(query.get('type', ''))
results = match(query.get('query', ''), dataset)[:limit]
entities = Entity.id_map(dataset, map(lambda (c,e,s): e, results))
matches = []
skip = False
for (candidate, entity_id, score) in results:
entity = entities[entity_id]
for key, fv in filters:
if entity.data.get(key) != fv:
skip = True
if skip:
continue
id = url_for('entity.view', dataset=dataset.name, entity=entity.id)
uri = url_for('entity.view', dataset=dataset.name, entity=entity.id, _external=True)
matches.append({
'name': entity.name,
'score': score,
'type': [{
'id': '/' + dataset.name,
'name': dataset.label
}],
'id': id,
'uri': uri,
'match': score==100
})
return {
'result': matches,
'num': len(results)
}