documentation: clarify osm2pgsql isnt in project directory by default

[nominatim.git] / nominatim / tokenizer / legacy_tokenizer.py

diff --git a/nominatim/tokenizer/legacy_tokenizer.py b/nominatim/tokenizer/legacy_tokenizer.py
index d901a68d2e53f77e5c96210c11ede863e7e5e36f..28f4b32756c0756ea172ca3aa16a458ac6ce929d 100644 (file)
--- a/nominatim/tokenizer/legacy_tokenizer.py
+++ b/nominatim/tokenizer/legacy_tokenizer.py
@@ -1,3 +1,9 @@
+# SPDX-License-Identifier: GPL-2.0-only
+#
+# This file is part of Nominatim. (https://nominatim.org)
+#
+# Copyright (C) 2022 by the Nominatim developer community.
+# For a full list of authors see the git log.
 """
 Tokenizer implementing normalisation as used before Nominatim 4.
 """
@@ -190,20 +196,28 @@ class LegacyTokenizer(AbstractTokenizer):
         """ Recompute the frequency of full words.
         """
         with connect(self.dsn) as conn:
-            with conn.cursor() as cur:
-                cur.drop_table("word_frequencies")
-                LOG.info("Computing word frequencies")
-                cur.execute("""CREATE TEMP TABLE word_frequencies AS
-                                 SELECT unnest(name_vector) as id, count(*)
-                                 FROM search_name GROUP BY id""")
-                cur.execute("CREATE INDEX ON word_frequencies(id)")
-                LOG.info("Update word table with recomputed frequencies")
-                cur.execute("""UPDATE word SET search_name_count = count
-                               FROM word_frequencies
-                               WHERE word_token like ' %' and word_id = id""")
-                cur.drop_table("word_frequencies")
+            if conn.table_exists('search_name'):
+                with conn.cursor() as cur:
+                    cur.drop_table("word_frequencies")
+                    LOG.info("Computing word frequencies")
+                    cur.execute("""CREATE TEMP TABLE word_frequencies AS
+                                     SELECT unnest(name_vector) as id, count(*)
+                                     FROM search_name GROUP BY id""")
+                    cur.execute("CREATE INDEX ON word_frequencies(id)")
+                    LOG.info("Update word table with recomputed frequencies")
+                    cur.execute("""UPDATE word SET search_name_count = count
+                                   FROM word_frequencies
+                                   WHERE word_token like ' %' and word_id = id""")
+                    cur.drop_table("word_frequencies")
             conn.commit()
 
+
+    def update_word_tokens(self):
+        """ No house-keeping implemented for the legacy tokenizer.
+        """
+        LOG.info("No tokenizer clean-up available.")
+
+
     def name_analyzer(self):
         """ Create a new analyzer for tokenizing names and queries
             using this tokinzer. Analyzers are context managers and should
@@ -501,7 +515,7 @@ class _TokenInfo:
             simple_list = list(set(simple_list))
 
         with conn.cursor() as cur:
-            cur.execute("SELECT (create_housenumbers(%s)).* ", (simple_list, ))
+            cur.execute("SELECT * FROM create_housenumbers(%s)", (simple_list, ))
             self.data['hnr_tokens'], self.data['hnr'] = cur.fetchone()
 
 
@@ -512,7 +526,9 @@ class _TokenInfo:
             with conn.cursor() as cur:
                 return cur.scalar("SELECT word_ids_from_name(%s)::text", (name, ))
 
-        self.data['street'] = self.cache.streets.get(street, _get_street)
+        tokens = self.cache.streets.get(street, _get_street)
+        if tokens:
+            self.data['street'] = tokens
 
 
     def add_place(self, conn, place):
@@ -541,9 +557,12 @@ class _TokenInfo:
 
         tokens = {}
         for key, value in terms:
-            tokens[key] = self.cache.address_terms.get(value, _get_address_term)
+            items = self.cache.address_terms.get(value, _get_address_term)
+            if items[0] or items[1]:
+                tokens[key] = items
 
-        self.data['addr'] = tokens
+        if tokens:
+            self.data['addr'] = tokens
 
 
 class _LRU: