Merge pull request #3260 from lonvia/improve-catgeory-search

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

diff --git a/nominatim/api/search/db_search_builder.py b/nominatim/api/search/db_search_builder.py
index 66e7efaf7f729dec8fdc8f0f889295b6ed8a6f67..7826925aed6ce77271e92bbef4612a3b1e5357bd 100644 (file)
--- a/nominatim/api/search/db_search_builder.py
+++ b/nominatim/api/search/db_search_builder.py
@@ -7,7 +7,7 @@
 """
 Convertion from token assignment to an abstract DB search.
 """
-from typing import Optional, List, Tuple, Iterator
+from typing import Optional, List, Tuple, Iterator, Dict
 import heapq
 
 from nominatim.api.types import SearchDetails, DataLayer
@@ -208,7 +208,7 @@ class SearchBuilder:
                            and all(t.is_indexed for t in addr_partials)
         exp_count = min(t.count for t in name_partials) / (2**(len(name_partials) - 1))
 
-        if (len(name_partials) > 3 or exp_count < 3000) and partials_indexed:
+        if (len(name_partials) > 3 or exp_count < 8000) and partials_indexed:
             yield penalty, exp_count, dbf.lookup_by_names(name_tokens, addr_tokens)
             return
 
@@ -339,12 +339,13 @@ class SearchBuilder:
             Returns None if no category search is requested.
         """
         if assignment.category:
-            tokens = [t for t in self.query.get_tokens(assignment.category,
-                                                       TokenType.CATEGORY)
-                      if not self.details.categories
-                         or t.get_category() in self.details.categories]
-            return dbf.WeightedCategories([t.get_category() for t in tokens],
-                                          [t.penalty for t in tokens])
+            tokens: Dict[Tuple[str, str], float] = {}
+            for t in self.query.get_tokens(assignment.category, TokenType.CATEGORY):
+                cat = t.get_category()
+                if (not self.details.categories or cat in self.details.categories)\
+                   and t.penalty < tokens.get(cat, 1000.0):
+                    tokens[cat] = t.penalty
+            return dbf.WeightedCategories(list(tokens.keys()), list(tokens.values()))
 
         if self.details.categories:
             return dbf.WeightedCategories(self.details.categories,