def housenumbers_pairs_deindexer(db, key, doc, tokens, **kwargs):
for field, value in doc.items():
field = field.decode()
if not field.startswith('h|'):
continue
number, lat, lon, *extra = value.decode().split('|')
hn = field[2:]
for token in tokens:
k = '|'.join(['didx', hn, token])
commons = db.zinterstore(k, [token_key(hn), token_key(token)])
db.delete(k)
if not commons:
db.srem(pair_key(hn), token)
db.srem(pair_key(token), hn)
def pairs_deindexer(db, key, doc, tokens, **kwargs):
els = list(set(tokens)) # Unique values.
loop = 0
for el in els:
for el2 in els[loop:]:
if el != el2:
key = '|'.join(['didx', el, el2])
# Do we have other documents that share el and el2?
commons = db.zinterstore(key, [token_key(el), token_key(el2)])
db.delete(key)
if not commons:
db.srem(pair_key(el), el2)
db.srem(pair_key(el2), el)
loop += 1
def try_fuzzy(helper, tokens, include_common=True):
if not helper.bucket_dry or not tokens:
return
helper.debug('Fuzzy on. Trying with %s.', tokens)
tokens.sort(key=lambda t: len(t), reverse=True)
allkeys = helper.keys[:]
if include_common:
# As we are in fuzzy, try to narrow as much as possible by adding
# unused commons tokens.
common = [t for t in helper.common if t.db_key not in helper.keys]
allkeys.extend([t.db_key for t in common])
for try_one in tokens:
if helper.bucket_full:
break
keys = allkeys[:]
if try_one.db_key in keys:
keys.remove(try_one.db_key)
if try_one.isdigit():
continue
helper.debug('Going fuzzy with %s', try_one)
neighbors = make_fuzzy(try_one.original, max=helper.fuzzy)
if len(keys):
# Only retains tokens that have been seen in the index at least
# once with the other tokens.
DB.sadd(helper.query, *neighbors)
interkeys = [pair_key(k[2:]) for k in keys]
interkeys.append(helper.query)
fuzzy_words = DB.sinter(interkeys)
DB.delete(helper.query)
# Keep the priority we gave in building fuzzy terms (inversion
# first, then substitution, etc.).
fuzzy_words = [w.decode() for w in fuzzy_words]
fuzzy_words.sort(key=lambda x: neighbors.index(x))
else:
# The token we are considering is alone.
fuzzy_words = []
for neighbor in neighbors:
key = token_key(neighbor)
count = DB.zcard(key)
if count:
fuzzy_words.append(neighbor)
helper.debug('Found fuzzy candidates %s', fuzzy_words)
fuzzy_keys = [token_key(w) for w in fuzzy_words]
for key in fuzzy_keys:
if helper.bucket_dry:
helper.add_to_bucket(keys + [key])
def autocomplete(helper, tokens, skip_commons=False, use_geohash=False):
helper.debug('Autocompleting %s', helper.last_token)
# helper.last_token.autocomplete()
keys = [t.db_key for t in tokens if not t.is_last]
pair_keys = [pair_key(t.original) for t in tokens if not t.is_last]
key = edge_ngram_key(helper.last_token.original)
autocomplete_tokens = DB.sinter(pair_keys + [key])
helper.debug('Found tokens to autocomplete %s', autocomplete_tokens)
for token in autocomplete_tokens:
key = token_key(token.decode())
if skip_commons\
and token_key_frequency(key) > config.COMMON_THRESHOLD:
helper.debug('Skip common token to autocomplete %s', key)
continue
if not helper.bucket_overflow or helper.last_token in helper.not_found:
helper.debug('Trying to extend bucket. Autocomplete %s', key)
extra_keys = [key]
if use_geohash and helper.geohash_key:
extra_keys.append(helper.geohash_key)
helper.add_to_bucket(keys + extra_keys)
def edge_ngram_deindexer(db, key, doc, tokens, **kwargs):
if config.INDEX_EDGE_NGRAMS:
for token in tokens:
tkey = token_key(token)
if not DB.exists(tkey):
deindex_edge_ngrams(token)
