Implementation of query analysis for the ICU tokenizer.
"""
from typing import Tuple, Dict, List, Optional, NamedTuple, Iterator, Any, cast
-from copy import copy
from collections import defaultdict
import dataclasses
import difflib
from nominatim.api.logging import log
from nominatim.api.search import query as qmod
from nominatim.api.search.query_analyzer_factory import AbstractQueryAnalyzer
+from nominatim.db.sqlalchemy_types import Json
DB_TO_TOKEN_TYPE = {
sa.Column('word_token', sa.Text, nullable=False),
sa.Column('type', sa.Text, nullable=False),
sa.Column('word', sa.Text),
- sa.Column('info', self.conn.t.types.Json))
+ sa.Column('info', Json))
async def analyze_query(self, phrases: List[qmod.Phrase]) -> qmod.QueryStruct:
if trange.start == 0:
query.add_token(trange, qmod.TokenType.NEAR_ITEM, token)
else:
- query.add_token(trange, qmod.TokenType.QUALIFIER, token)
- if trange.start == 0 or trange.end == query.num_token_slots():
- token = copy(token)
- token.penalty += 0.1 * (query.num_token_slots())
+ if trange.start == 0 and trange.end == query.num_token_slots():
query.add_token(trange, qmod.TokenType.NEAR_ITEM, token)
+ else:
+ query.add_token(trange, qmod.TokenType.QUALIFIER, token)
else:
query.add_token(trange, DB_TO_TOKEN_TYPE[row.type], token)
standardized form search will work with. All information removed
at this stage is inevitably lost.
"""
- return cast(str, self.normalizer.transliterate(text))
+ norm = cast(str, self.normalizer.transliterate(text))
+ numspaces = norm.count(' ')
+ if numspaces > 4 and len(norm) <= (numspaces + 1) * 3:
+ return ''
+
+ return norm
def split_query(self, query: qmod.QueryStruct) -> Tuple[QueryParts, WordDict]: