Merge remote-tracking branch 'upstream/master'

[nominatim.git] / nominatim / api / search / icu_tokenizer.py

diff --git a/nominatim/api/search/icu_tokenizer.py b/nominatim/api/search/icu_tokenizer.py
index fceec2df522feb5105936204b099e9a8a7a2ad96..76a1a2e5d362688d5388044b511a9d3f0ae4a13c 100644 (file)
--- a/nominatim/api/search/icu_tokenizer.py
+++ b/nominatim/api/search/icu_tokenizer.py
@@ -8,7 +8,6 @@
 Implementation of query analysis for the ICU tokenizer.
 """
 from typing import Tuple, Dict, List, Optional, NamedTuple, Iterator, Any, cast
 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 collections import defaultdict
 import dataclasses
 import difflib


@@ -22,6 +21,7 @@ from nominatim.api.connection import SearchConnection
 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.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 = {
 
 
 DB_TO_TOKEN_TYPE = {


@@ -159,7 +159,7 @@ class ICUQueryAnalyzer(AbstractQueryAnalyzer):
                      sa.Column('word_token', sa.Text, nullable=False),
                      sa.Column('type', sa.Text, nullable=False),
                      sa.Column('word', sa.Text),
                      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:
 
 
     async def analyze_query(self, phrases: List[qmod.Phrase]) -> qmod.QueryStruct:


@@ -186,11 +186,10 @@ class ICUQueryAnalyzer(AbstractQueryAnalyzer):
                         if trange.start == 0:
                             query.add_token(trange, qmod.TokenType.NEAR_ITEM, token)
                     else:
                         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)
                             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)
 
                 else:
                     query.add_token(trange, DB_TO_TOKEN_TYPE[row.type], token)
 


@@ -207,7 +206,12 @@ class ICUQueryAnalyzer(AbstractQueryAnalyzer):
             standardized form search will work with. All information removed
             at this stage is inevitably lost.
         """
             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]:
 
 
     def split_query(self, query: qmod.QueryStruct) -> Tuple[QueryParts, WordDict]: