X-Git-Url: https://git.openstreetmap.org./nominatim.git/blobdiff_plain/6e89310a9285f1ad15d8002bf68f578eada367a0..23369ce9704d3815faae22697338916a60ddf682:/src/nominatim_api/search/icu_tokenizer.py

diff --git a/src/nominatim_api/search/icu_tokenizer.py b/src/nominatim_api/search/icu_tokenizer.py
index 42665679..fa14531a 100644
--- a/src/nominatim_api/search/icu_tokenizer.py
+++ b/src/nominatim_api/search/icu_tokenizer.py
@@ -16,8 +16,8 @@ from icu import Transliterator
 
 import sqlalchemy as sa
 
-from nominatim_core.typing import SaRow
-from nominatim_core.db.sqlalchemy_types import Json
+from ..typing import SaRow
+from ..sql.sqlalchemy_types import Json
 from ..connection import SearchConnection
 from ..logging import log
 from ..search import query as qmod
@@ -48,6 +48,7 @@ class QueryPart(NamedTuple):
 QueryParts = List[QueryPart]
 WordDict = Dict[str, List[qmod.TokenRange]]
 
+
 def yield_words(terms: List[QueryPart], start: int) -> Iterator[Tuple[str, qmod.TokenRange]]:
     """ Return all combinations of words in the terms list after the
         given position.
@@ -72,7 +73,6 @@ class ICUToken(qmod.Token):
         assert self.info
         return self.info.get('class', ''), self.info.get('type', '')
 
-
     def rematch(self, norm: str) -> None:
         """ Check how well the token matches the given normalized string
             and add a penalty, if necessary.
@@ -91,7 +91,6 @@ class ICUToken(qmod.Token):
                 distance += abs((ato-afrom) - (bto-bfrom))
         self.penalty += (distance/len(self.lookup_word))
 
-
     @staticmethod
     def from_db_row(row: SaRow) -> 'ICUToken':
         """ Create a ICUToken from the row of the word table.
@@ -123,21 +122,18 @@ class ICUToken(qmod.Token):
             lookup_word = row.word_token
 
         return ICUToken(penalty=penalty, token=row.word_id, count=max(1, count),
-                        lookup_word=lookup_word, is_indexed=True,
+                        lookup_word=lookup_word,
                         word_token=row.word_token, info=row.info,
                         addr_count=max(1, addr_count))
 
 
-
 class ICUQueryAnalyzer(AbstractQueryAnalyzer):
     """ Converter for query strings into a tokenized query
         using the tokens created by a ICU tokenizer.
     """
-
     def __init__(self, conn: SearchConnection) -> None:
         self.conn = conn
 
-
     async def setup(self) -> None:
         """ Set up static data structures needed for the analysis.
         """
@@ -163,7 +159,6 @@ class ICUQueryAnalyzer(AbstractQueryAnalyzer):
                      sa.Column('word', sa.Text),
                      sa.Column('info', Json))
 
-
     async def analyze_query(self, phrases: List[qmod.Phrase]) -> qmod.QueryStruct:
         """ Analyze the given list of phrases and return the
             tokenized query.
@@ -202,7 +197,6 @@ class ICUQueryAnalyzer(AbstractQueryAnalyzer):
 
         return query
 
-
     def normalize_text(self, text: str) -> str:
         """ Bring the given text into a normalized form. That is the
             standardized form search will work with. All information removed
@@ -210,7 +204,6 @@ class ICUQueryAnalyzer(AbstractQueryAnalyzer):
         """
         return cast(str, self.normalizer.transliterate(text))
 
-
     def split_query(self, query: qmod.QueryStruct) -> Tuple[QueryParts, WordDict]:
         """ Transliterate the phrases and split them into tokens.
 
@@ -243,7 +236,6 @@ class ICUQueryAnalyzer(AbstractQueryAnalyzer):
 
         return parts, words
 
-
     async def lookup_in_db(self, words: List[str]) -> 'sa.Result[Any]':
         """ Return the token information from the database for the
             given word tokens.
@@ -251,7 +243,6 @@ class ICUQueryAnalyzer(AbstractQueryAnalyzer):
         t = self.conn.t.meta.tables['word']
         return await self.conn.execute(t.select().where(t.c.word_token.in_(words)))
 
-
     def add_extra_tokens(self, query: qmod.QueryStruct, parts: QueryParts) -> None:
         """ Add tokens to query that are not saved in the database.
         """
@@ -259,8 +250,9 @@ class ICUQueryAnalyzer(AbstractQueryAnalyzer):
             if len(part.token) <= 4 and part[0].isdigit()\
                and not node.has_tokens(i+1, qmod.TokenType.HOUSENUMBER):
                 query.add_token(qmod.TokenRange(i, i+1), qmod.TokenType.HOUSENUMBER,
-                                ICUToken(0.5, 0, 1, 1, part.token, True, part.token, None))
-
+                                ICUToken(penalty=0.5, token=0,
+                                         count=1, addr_count=1, lookup_word=part.token,
+                                         word_token=part.token, info=None))
 
     def rerank_tokens(self, query: qmod.QueryStruct, parts: QueryParts) -> None:
         """ Add penalties to tokens that depend on presence of other token.
@@ -272,8 +264,8 @@ class ICUQueryAnalyzer(AbstractQueryAnalyzer):
                        and (repl.ttype != qmod.TokenType.HOUSENUMBER
                             or len(tlist.tokens[0].lookup_word) > 4):
                         repl.add_penalty(0.39)
-            elif tlist.ttype == qmod.TokenType.HOUSENUMBER \
-                 and len(tlist.tokens[0].lookup_word) <= 3:
+            elif (tlist.ttype == qmod.TokenType.HOUSENUMBER
+                  and len(tlist.tokens[0].lookup_word) <= 3):
                 if any(c.isdigit() for c in tlist.tokens[0].lookup_word):
                     for repl in node.starting:
                         if repl.end == tlist.end and repl.ttype != qmod.TokenType.HOUSENUMBER: